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A search has been performed for the semileptonic decays D0→K0SK−e+νe, D+→K0SK0Se+νe and D+→K+K−e+νe, using 7.9 fb−1 of e+e− annihilation data collected at the center-of-mass energy s√=3.773 GeV by the BESIII detector operating at the BEPCII collider. No significant signals are observed, and upper limits are set at the 90\% confidence level of 2.13×10−5, 1.54×10−5 and 2.10×10−5 for the branching fractions of D0→K0SK−e+νe, D+→K0SK0Se+νe and D+→K+K−e+νe, respectively.
Dynamic imaging of landmark organelles, such as nuclei, cell membrane, nuclear envelope, and lipid droplets enables image-based phenotyping of functional states of cells. Multispectral fluorescent imaging of landmark organelles requires labor-intensive labeling, limits throughput, and compromises cell health. Virtual staining of label-free images with deep neural networks is an emerging solution for this problem. Multiplexed imaging of cellular landmarks from scattered light and subsequent demultiplexing with virtual staining saves the light spectrum for imaging additional molecular reporters, photomanipulation, or other tasks. Published approaches for virtual staining of landmark organelles are fragile in the presence of nuisance variations in imaging, culture conditions, and cell types. This paper reports model training protocols for virtual staining of nuclei and membranes robust to cell types, cell states, and imaging parameters. We developed a flexible and scalable convolutional architecture, named UNeXt2, for supervised training and self-supervised pre-training. The strategies we report here enable robust virtual staining of nuclei and cell membranes in multiple cell types, including neuromasts of zebrafish, across a range of imaging conditions. We assess the models by comparing the intensity, segmentations, and application-specific measurements obtained from virtually stained and experimentally stained nuclei and membranes. The models rescue the missing label, non-uniform expression of labels, and photobleaching. We share three pre-trained models, named VSCyto3D, VSCyto2D, and VSNeuromast, as well as VisCy, a PyTorch-based pipeline for training, inference, and deployment that leverages the modern OME-Zarr format.
The free energy of TAP-solutions for the SK-model of mean field spin glasses can be expressed as a nonlinear functional of local terms: we exploit this feature in order to contrive abstract REM-like models which we then solve by a classical large deviations treatment. This allows to identify the origin of the physically unsettling quadratic (in the inverse of temperature) correction to the Parisi free energy for the SK-model, and formalizes the true cavity dynamics which acts on TAP-space, i.e. on the space of TAP-solutions. From a non-spin glass point of view, this work is the first in a series of refinements which addresses the stability of hierarchical structures in models of evolving populations.
Oncogenic transformation of lung epithelial cells is a multi-step process, frequently starting with the inactivation of tumor suppressors and subsequent activating mutations in proto-oncogenes, such as members of the PI3K or MAPK family. Cells undergoing transformation have to adjust to changes, such as metabolic requirements. This is achieved, in part, by modulating the protein abundance of transcription factors, which manifest these adjustments. Here, we report that the deubiquitylase USP28 enables oncogenic reprogramming by regulating the protein abundance of proto-oncogenes, such as c-JUN, c-MYC, NOTCH and ΔNP63, at early stages of malignant transformation. USP28 is increased in cancer compared to normal cells due to a feed-forward loop, driven by increased amounts of oncogenic transcription factors, such as c-MYC and c-JUN. Irrespective of oncogenic driver, interference with USP28 abundance or activity suppresses growth and survival of transformed lung cells. Furthermore, inhibition of USP28 via a small molecule inhibitor reset the proteome of transformed cells towards a ‘pre-malignant’ state, and its inhibition cooperated with clinically established compounds used to target EGFRL858R, BRAFV600E or PI3KH1047R driven tumor cells. Targeting USP28 protein abundance already at an early stage via inhibition of its activity therefore is a feasible strategy for the treatment of early stage lung tumours and the observed synergism with current standard of care inhibitors holds the potential for improved targeting of established tumors.
Off-central heavy-ion collisions are known to feature magnetic fields with magnitudes and characteristic gradients corresponding to the scale of the strong interactions. In this work, we employ equilibrium lattice simulations of the underlying theory, QCD, involving similar inhomogeneous magnetic field profiles to achieve a better understanding of this system. We simulate three flavors of dynamical staggered quarks with physical masses at a range of magnetic fields and temperatures, and extrapolate the results to the continuum limit. Analyzing the impact of the field on the quark condensate and the Polyakov loop, we find non-trivial spatial features that render the QCD medium qualitatively different as in the homogeneous setup, especially at temperatures around the transition. In addition, we construct leading-order chiral perturbation theory for the inhomogeneous background and compare its prediction to our lattice results at low temperature. Our findings will be useful to benchmark effective theories and low-energy models of QCD for a better description of peripheral heavy-ion collisions.
Off-central heavy-ion collisions are known to feature magnetic fields with magnitudes and characteristic gradients corresponding to the scale of the strong interactions. In this work, we employ equilibrium lattice simulations of the underlying theory, QCD, involving similar inhomogeneous magnetic field profiles to achieve a better understanding of this system. We simulate three flavors of dynamical staggered quarks with physical masses at a range of magnetic fields and temperatures, and extrapolate the results to the continuum limit. Analyzing the impact of the field on the quark condensate and the Polyakov loop, we find non-trivial spatial features that render the QCD medium qualitatively different as in the homogeneous setup, especially at temperatures around the transition. In addition, we construct leading-order chiral perturbation theory for the inhomogeneous background and compare its prediction to our lattice results at low temperature. Our findings will be useful to benchmark effective theories and low-energy models of QCD for a better description of peripheral heavy-ion collisions.
Off-central heavy-ion collisions are known to feature magnetic fields with magnitudes and characteristic gradients corresponding to the scale of the strong interactions. In this work, we employ equilibrium lattice simulations of the underlying theory, QCD, involving similar inhomogeneous magnetic field profiles to achieve a better understanding of this system. We simulate three flavors of dynamical staggered quarks with physical masses at a range of magnetic fields and temperatures, and extrapolate the results to the continuum limit. Analyzing the impact of the field on the quark condensate and the Polyakov loop, we find non-trivial spatial features that render the QCD medium qualitatively different as in the homogeneous setup, especially at temperatures around the transition. In addition, we construct leading-order chiral perturbation theory for the inhomogeneous background and compare its prediction to our lattice results at low temperature. Our findings will be useful to benchmark effective theories and low-energy models of QCD for a better description of peripheral heavy-ion collisions.
Mitochondria are dynamic organelles exhibiting diverse shapes. While the variation of shapes, ranging from spheres to elongated tubules, and the transition between them, are clearly seen in many cell types, the molecular mechanisms governing this morphological variability remain poorly understood. Here, we propose a novel shaping mechanism based on the interplay between the inner and outer mitochondrial membranes. Our biophysical model suggests that the difference in surface area, arising from the pulling of the inner membrane into cristae, correlates with mitochondrial elongation. Analysis of live cell super-resolution microscopy data supports this correlation, linking elongated shapes to the extent of cristae in the inner membrane. Knocking down cristae shaping proteins further confirms the impact on mitochondrial shape, demonstrating that defects in cristae formation correlate with mitochondrial sphericity. Our results suggest that the dynamics of the inner mitochondrial membrane are important not only for simply creating surface area required for respiratory capacity, but go beyond that to affect the whole organelle morphology. This work explores the biophysical foundations of individual mitochondrial shape, suggesting potential links between mitochondrial structure and function. This should be of profound significance, particularly in the context of disrupted cristae shaping proteins and their implications in mitochondrial diseases.
Tree-related microhabitats (TReMs) have been proposed as important indicators of biodiversity to guide forest management. However, their application has been limited mostly to temperate ecosystems, and it is largely unknown how the diversity of TReMs varies along environmental gradients. In this study, we assessed the diversity of TReMs on 180 individual trees and 44 plots alongside a large environmental gradient on Kilimanjaro, Tanzania. We used a typology adjusted to tropical ecosystems and a tree-climbing protocol to obtain quantitative information on TreMs on large trees and dense canopies. We computed the diversity of TReMs for each individual tree and plot and tested how TReM diversity was associated with properties of individual trees and environmental conditions in terms of climate and human impact. We further used non-metric multidimensional scaling (NMDS) to investigate the composition of TReM assemblages alongside the environmental gradients. We found that diameter at breast height (DBH) and height of the first branch were the most important determinants of TReM diversity on individual trees, with higher DBH and lower first branch height promoting TReM diversity. At the plot level, we found that TReM diversity increased with mean annual temperature and decreased with human impact. The composition of TReMs showed high turnover across ecosystem types, with a stark difference between forest and non-forest ecosystems. Climate and the intensity of human impact were associated with TReM composition. Our study is a first test of how TReM diversity and composition vary along environmental gradients in tropical ecosystems. The importance of tree size and architecture in fostering microhabitat diversity underlines the importance of large veteran trees in tropical ecosystems. Because diversity and composition of TReMs are sensitive to climate and land-use effects, our study suggests that TReMs can be used to efficiently monitor consequences of global change for tropical biodiversity.
Tree-related microhabitats (TReMs) have been proposed as important indicators of biodiversity to guide forest management. However, their application has been limited mostly to temperate ecosystems, and it is largely unknown how the diversity of TReMs varies along environmental gradients. In this study, we assessed the diversity of TReMs on 180 individual trees and 46 plots alongside a large environmental gradient on Kilimanjaro, Tanzania. We used a typology adjusted to tropical ecosystems and a tree-climbing protocol to obtain quantitative information on TreMs on large trees and dense canopies. We computed the diversity of TReMs for each individual tree and plot and tested how TReM diversity was associated with properties of individual trees and environmental conditions in terms of climate and human impact. We further used non-metric multidimensional scaling (NMDS) to investigate the composition of TReM assemblages alongside the environmental gradients. We found that diameter at breast height (DBH) and height of the first branch were the most important determinants of TReM diversity on individual trees, with higher DBH and lower first branch height promoting TReM diversity. At the plot level, we found that TReM diversity increased with mean annual temperature and decreased with human impact. The composition of TReMs showed high turnover across ecosystem types, with a stark difference between forest and non-forest ecosystems. Climate and the intensity of human impact were associated with TReM composition. Our study is a first test of how TReM diversity and composition vary along environmental gradients in tropical ecosystems. The importance of tree size and architecture in fostering microhabitat diversity underlines the importance of large veteran trees in tropical ecosystems. Because diversity and composition of TReMs are sensitive to climate and land-use effects, our study suggests that TReMs can be used to efficiently monitor consequences of global change for tropical biodiversity.
In natural environments, background noise can degrade the integrity of acoustic signals, posing a problem for animals that rely on their vocalizations for communication and navigation. A simple behavioral strategy to combat acoustic interference would be to restrict call emissions to periods of low-amplitude or no noise. Using audio playback and computational tools for the automated detection of over 2.5 million vocalizations from groups of freely vocalizing bats, we show that bats (Carollia perspicillata) can dynamically adapt the timing of their calls to avoid acoustic jamming in both predictably and unpredictably patterned noise. This study demonstrates that bats spontaneously seek out temporal windows of opportunity for vocalizing in acoustically crowded environments, providing a mechanism for efficient echolocation and communication in cluttered acoustic landscapes.
One Sentence Summary Bats avoid acoustic interference by rapidly adjusting the timing of vocalizations to the temporal pattern of varying noise.
In natural environments, background noise can degrade the integrity of acoustic signals, posing a problem for animals that rely on their vocalizations for communication and navigation. A simple behavioral strategy to combat acoustic interference would be to restrict call emissions to periods of low-amplitude or no noise. Using audio playback and computational tools for the automated detection of over 2.5 million vocalizations from groups of freely vocalizing bats, we show that bats (Carollia perspicillata) can dynamically adapt the timing of their calls to avoid acoustic jamming in both predictably and unpredictably patterned noise. This study demonstrates that bats spontaneously seek out temporal windows of opportunity for vocalizing in acoustically crowded environments, providing a mechanism for efficient echolocation and communication in cluttered acoustic landscapes.
One Sentence Summary: Bats avoid acoustic interference by rapidly adjusting the timing of vocalizations to the temporal pattern of varying noise.
Human feline leukemia virus subgroup C receptor-related proteins 1 and 2 (FLVCR1 and 2) are members of the major facilitator superfamily1. Their dysfunction is linked to several clinical disorders, including PCARP, HSAN, and Fowler syndrome2–7. Earlier studies concluded that FLVCR1 may function as a putative heme exporter8–12, while FLVCR2 was suggested to act as a heme importer13, yet conclusive biochemical and detailed molecular evidence remained elusive for the function of both transporters14–17. Here, we show that FLVCR1 and FLVCR2 facilitate the transport of choline and ethanolamine across human plasma membranes, utilizing a concentration-driven substrate translocation process. Through structural and computational analyses, we have identified distinct conformational states of FLVCRs and unraveled the coordination chemistry underlying their substrate interactions. Within the binding pocket of both transporters, we identify fully conserved tryptophan and tyrosine residues holding a central role in the formation of cation-π interactions, essential for choline and ethanolamine selectivity. Our findings not only clarify the mechanisms of choline and ethanolamine transport by FLVCR1 and FLVCR2, enhancing our comprehension of disease-associated mutations that interfere with these vital processes, but also shed light on the conformational dynamics of these MFS-type proteins during the transport cycle.
Metabolic differences between symbiont subpopulations in the deep-sea tubeworm Riftia pachyptila
(2020)
The hydrothermal vent tube worm Riftia pachyptila lives in intimate symbiosis with intracellular sulfur-oxidizing gammaproteobacteria. Although the symbiont population consists of a single 16S rRNA phylotype, bacteria in the same host animal exhibit a remarkable degree of metabolic diversity: They simultaneously utilize two carbon fixation pathways and various energy sources and electron acceptors. Whether these multiple metabolic routes are employed in the same symbiont cells, or rather in distinct symbiont subpopulations, was unclear. As Riftia symbionts vary considerably in cell size and shape, we enriched individual symbiont cell sizes by density gradient centrifugation in order to test whether symbiont cells of different sizes show different metabolic profiles. Metaproteomic analysis and statistical evaluation using clustering and random forests, supported by microscopy and flow cytometry, strongly suggest that Riftia symbiont cells of different sizes represent metabolically dissimilar stages of a physiological differentiation process: Small symbionts actively divide and may establish cellular symbiont-host interaction, as indicated by highest abundance of the cell division key protein FtsZ and highly abundant chaperones and porins in this initial phase. Large symbionts, on the other hand, apparently do not divide, but still replicate DNA, leading to DNA endoreduplication. Highest abundance of enzymes for CO2 fixation, carbon storage and biosynthesis in large symbionts indicates that in this late differentiation stage the symbiont’s metabolism is efficiently geared towards the production of organic material. We propose that this division of labor between smaller and larger symbionts benefits the productivity of the symbiosis as a whole.
Generating predictions about environmental regularities, relying on these predictions, and updating these predictions when there is a violation from incoming sensory evidence are considered crucial functions of our cognitive system for being adaptive in the future. The violation of a prediction can result in a prediction error (PE) which affects subsequent memory processing. In our preregistered studies, we examined the effects of different levels of PE on episodic memory. Participants were asked to generate predictions about the associations between sequentially presented cue-target pairs, which were violated later with individual items in three PE levels, namely low, medium, and high PE. Hereafter, participants were asked to provide old/new judgments on the items with confidence ratings, and to retrieve the paired cues. Our results indicated a better recognition memory for low PE than medium and high PE levels, suggesting a memory congruency effect. On the other hand, there was no evidence of memory benefit for high PE level. Together, these novel and coherent findings strongly suggest that high PE does not guarantee better memory.
From early to middle childhood, brain regions that underlie memory consolidation undergo profound maturational changes. However, there is little empirical investigation that directly relates age-related differences in brain structural measures to the memory consolidation processes. The present study examined system-level memory consolidations of intentionally studied object-location associations after one night of sleep (short delay) and after two weeks (long delay) in normally developing 5-to-7-year-old children (n = 50) and young adults (n = 39). Behavioural differences in memory consolidation were related to structural brain measures. Our results showed that children, in comparison to young adults, consolidate correctly learnt object-location associations less robustly over short and long delay. Moreover, using partial least squares correlation method, a unique multivariate profile comprised of specific neocortical (prefrontal, parietal, and occipital), cerebellar, and hippocampal subfield structures was found to be associated with variation in short-delay memory consolidation. A different multivariate profile comprised of a reduced set of brain structures, mainly consisting of neocortical (prefrontal, parietal, and occipital), and selective hippocampal subfield structures (CA1-2 and subiculum) was associated with variation in long-delay memory consolidation. Taken together, the results suggest that multivariate structural pattern of unique sets of brain regions are related to variations in short- and long-delay memory consolidation across children and young adults.
RESEARCH HIGHLIGHTS
* Short- and long-delay memory consolidation is less robust in children than in young adults
* Short-delay brain profile comprised of hippocampal, cerebellar, and neocortical brain regions
* Long-delay brain profile comprised of neocortical and selected hippocampal brain regions.
* Brain profiles differ between children and young adults.
From early to middle childhood, brain regions that underlie memory consolidation undergo profound maturational changes. However, there is little empirical investigation that directly relates age-related differences in brain structural measures to the memory consolidation processes. The present study examined system-level memory consolidations of intentionally studied object-location associations after one night of sleep (short delay) and after two weeks (long delay) in normally developing 5-to-7-year-old children (n = 50) and young adults (n = 39). Behavioural differences in memory consolidation were related to structural brain measures. Our results showed that children, in comparison to young adults, consolidate correctly learnt object-location associations less robustly over short and long delay. Moreover, using partial least squares correlation method, a unique multivariate profile comprised of specific neocortical (prefrontal, parietal, and occipital), cerebellar, and hippocampal subfield structures was found to be associated with variation in short-delay memory consolidation. A different multivariate profile comprised of a reduced set of brain structures, mainly consisting of neocortical (prefrontal, parietal, and occipital), and selective hippocampal subfield structures (CA1-2 and subiculum) was associated with variation in long-delay memory consolidation. Taken together, the results suggest that multivariate structural pattern of unique sets of brain regions are related to variations in short- and long-delay memory consolidation across children and young adults.
RESEARCH HIGHLIGHTS
Short- and long-delay memory consolidation is less robust in children than in young adults
* Short-delay brain profile comprised of hippocampal, cerebellar, and neocortical brain regions
* Long-delay brain profile comprised of neocortical and selected hippocampal brain regions.
* Brain profiles differ between children and young adults.
Owing to their morphological complexity and dense network connections, neurons modify their proteomes locally, using mRNAs and ribosomes present in the neuropil (tissue enriched for dendrites and axons). Although ribosome biogenesis largely takes place in the nucleus and perinuclear region, neuronal ribosomal protein (RP) mRNAs have been frequently detected remotely, in dendrites and axons. Here, using imaging and ribosome profiling, we directly detected the RP mRNAs and their translation in the neuropil. Combining brief metabolic labeling with mass spectrometry, we found that a group of RPs quickly associated with translating ribosomes in the cytoplasm and that this incorporation is independent of canonical ribosome biogenesis. Moreover, the incorporation probability of some RPs was regulated by location (neurites vs. cell bodies) and changes in the cellular environment (in response to oxidative stress). Our results suggest new mechanisms for the local activation, repair and/or specialization of the translational machinery within neuronal processes, potentially allowing remote neuronal synapses a rapid solution to the relatively slow and energy-demanding requirement of nuclear ribosome biogenesis.
Memory consolidation tends to be less robust in childhood than adulthood. However, little is known about the corresponding functional differences in the developing brain that may underlie age-related differences in retention of memories over time. This study examined system-level memory consolidation of object-scene associations after learning (immediate delay), one night of sleep (short delay), as well as two weeks (long delay) in 5-to-7-year-old children (n = 49) and in young adults (n = 39), as a reference group with mature consolidation systems. Particularly, we characterized how functional neural activation and reinstatement of neural patterns change over time, assessed by functional magnetic resonance imaging combined with representational similarity analysis (RSA). Our results showed that memory consolidation in children was less robust and strong (i.e., more forgetting) compared to young adults. Contrasting correctly retained remote versus recent memories across time delay, children showed less upregulation in posterior parahippocampal gyrus, lateral occipital cortex, and cerebellum than adults. In addition, both children and adults showed decrease in scene-specific neural reinstatement over time, indicating time-related decay of detailed differentiated memories. At the same time, we observed more generic gist-like neural reinstatement in medial-temporal and prefrontal brain regions uniquely in children, indicating qualitative difference in memory trace in children. Taken together, 5-to-7-year-old children, compared to young adults, show less robust memory consolidation, possibly due to difficulties in engaging in differentiated neural reinstatement in neocortical mnemonic regions during retrieval of remote memories, coupled with relying more on gist-like generic neural reinstatement.
Memory consolidation tends to be less robust in childhood than adulthood. However, little is known about the corresponding functional differences in the developing brain that may underlie age-related differences in retention of memories over time. This study examined system-level memory consolidation of object-scene associations after learning (immediate delay), one night of sleep (short delay), as well as two weeks (long delay) in 5-to-7-year-old children (n = 49) and in young adults (n = 39), as a reference group with mature consolidation systems. Particularly, we characterized how functional neural activation and reinstatement of neural patterns change over time, assessed by functional magnetic resonance imaging combined with representational (dis)similarity analysis (RSA). Our results showed that memory consolidation in children was less robust (i.e., more forgetting) compared to young adults. For correctly retained remote memories, young adults showed increased neural activation from short to long delay in neocortical (parietal, prefrontal and occipital) and cerebellar brain regions, while children showed increased neural activation in prefrontal and decrease in neural activity in parietal brain regions over time. In addition, there was an overall attenuated scene-specific memory reinstatement of neural patterns in children compared to young adults. At the same time, we observed category-based reinstatement in medial-temporal, neocortical (prefrontal and parietal), and cerebellar brain regions only in children. Taken together, 5-to-7-year-old children, compared to young adults, show less robust memory consolidation, possibly due to difficulties in engaging in differentiated neural reinstatement in neocortical mnemonic regions during retrieval of remote memories, coupled with relying more on gist-like, category-based neural reinstatement.
Mitochondrial matrix peptidase CLPP is crucial during cell stress. Its loss causes Perrault syndrome type 3 (PRLTS3) with infertility, neurodegeneration and growth deficit. Its target proteins are disaggregated by CLPX, which also regulates heme biosynthesis via unfolding ALAS enzyme, providing access of pyridoxal-5’-phosphate (PLP). Despite efforts in diverse organisms with multiple techniques, CLPXP substrates remain controversial. Here, avoiding recombinant overexpression, we employed complexomics in mitochondria from three mouse tissues to identify endogenous targets. CLPP absence caused accumulation and dispersion of CLPX-VWA8 as AAA+ unfoldases, and of PLPBP. Similar changes and CLPX-VWA8 comigration were evident for mitoribosomal central protuberance clusters, translation factors like GFM1-HARS2, RNA granule components LRPPRC-SLIRP, and enzymes OAT-ALDH18A1. Mitochondrially translated proteins in testis showed reductions to <30% for MTCO1-3, misassembly of complex-IV supercomplex, and accumulated metal-binding assembly factors COX15-SFXN4. Indeed, heavy metal levels were increased for iron, molybdenum, cobalt and manganese. RT-qPCR showed compensatory downregulation only for Clpx mRNA, most accumulated proteins appeared transcriptionally upregulated. Immunoblots validated VWA8, MRPL38, MRPL18, GFM1 and OAT accumulation. Coimmunoprecipitation confirmed CLPX binding to MRPL38, GFM1 and OAT, so excess CLPX and PLP may affect their activity. Our data elucidate mechanistically the mitochondrial translation fidelity deficits, which underlie progressive hearing impairment in PRLTS3.
Viruses that carry a positive-sense, single-stranded (+ssRNA) RNA translate their genomes soon after entering the host cell to produce viral proteins, with the exception of retroviruses. A distinguishing feature of retroviruses is reverse transcription, where the +ssRNA genome serves as a template to synthesize a double-stranded DNA copy that subsequently integrates into the host genome. As retroviral RNAs are produced by the host cell transcriptional machinery and are largely indistinguishable from cellular mRNAs, we investigated the potential of incoming retroviral genomes to directly express proteins. Here we show through multiple, complementary methods that retroviral genomes are translated after entry. Our findings challenge the notion that retroviruses require reverse transcription to produce viral proteins. Synthesis of retroviral proteins in the absence of productive infection has significant implications for basic retrovirology, immune responses and gene therapy applications.
Viruses that carry a positive-sense, single-stranded RNA translate their genomes after entering the host cell to produce viral proteins, with the exception of retroviruses. A distinguishing feature of retroviruses is reverse transcription, where the ssRNA genome serves as a template to synthesize a double-stranded DNA copy that subsequently integrates into the host genome. As retroviral RNAs are produced by the host transcriptional machinery and are largely indistinguishable from cellular mRNAs, we investigated the potential of incoming retroviral genomes to express proteins. Here we show through various biochemical methods that HIV-1 genomes are translated after entry, in case of minimal or full-length genomes, envelopes using different cellular entry pathways and in diverse cell types. Our findings challenge the dogma that retroviruses require reverse transcription to produce viral proteins. Synthesis of retroviral proteins in the absence of productive infection has significant implications for basic retrovirology, immune responses and gene therapy applications.
The total charm-quark production cross section per unit of rapidity dσ(cc)/dy, and the fragmentation fractions of charm quarks to different charm-hadron species f(c → hc), are measured for the first time in p–Pb collisions at √sNN = 5.02 TeV at midrapidity (−0.96 < y < 0.04 in the centre-ofmass frame) using data collected by ALICE at the CERN LHC. The results are obtained based on all the available measurements of prompt production of ground-state charm-hadron species: D0, D+,D+s, and J/ψ mesons, and Λ+cand Ξ0cbaryons. The resulting cross section is dσ(cc)/dy = 219.6±6.3 (stat.)+10.5−11.8(syst.)+7.6−2.9(extr.)±5.4 (BR)±4.6 (lumi.)±19.5 (rapidity shape) +15.0 (Ω0c) mb, which is consistent with a binary scaling of pQCD calculations from pp ollisions. The measured fragmentation fractions are compatible with those measured in pp collisions at √s = 5.02 and 13 TeV, showing an increase in the relative production rates of charm baryons with respect to charm mesons in pp and p–Pb collisions compared with e+e − and e−p collisions. The pT-integrated nuclear modification factor of charm quarks, RpPb(cc) = 0.91±0.04 (stat.) +0.08 −0.09 (syst.) +0.04 −0.03 (extr.)±0.03 (lumi.), is found to be consistent with unity and with theoretical predictions including nuclear modifications of the parton distribution functions.
This work aims to differentiate strangeness produced from hard processes (jet-like) and softer processes (underlying event) by measuring the angular correlation between a high-momentum trigger hadron (h) acting as a jet-proxy and a produced strange hadron (φ(1020) meson). Measuring h–φ correlations at midrapidity in p–Pb collisions at √sNN = 5.02 TeV as a function of event multiplicity provides insight into the microscopic origin of strangeness enhancement in small collision systems. The jet-like and the underlying-event-like strangeness production are investigated as a function of event multiplicity. They are also compared between a lower and higher momentum region. The evolution of the per-trigger yields within the near-side (aligned with the trigger hadron) and away-side (in the opposite direction of the trigger hadron) jet is studied separately, allowing for the characterization of two distinct jet-like production regimes. Furthermore, the h–φ correlations within the underlying event give access to a production regime dominated by soft production processes, which can be compared directly to the in-jet production. Comparisons between h–φ and dihadron correlations show that the observed strangeness enhancement is largely driven by the underlying event, where the φ/h ratio is significantly larger than within the jet regions. As multiplicity increases, the fraction of the total φ(1020) yield coming from jets decreases compared to the underlying event production, leading to high-multiplicity events being dominated by the increased strangeness production from the underlying event
After myocardial infarction in the adult heart the remaining, non-infarcted tissue adapts to compensate the loss of functional tissue. This adaptation requires changes in gene expression networks, which are mostly controlled by transcription regulating proteins. Long non-coding transcripts (lncRNAs) are now recognized for taking part in fine-tuning such gene programs. We identified and characterized the cardiomyocyte specific lncRNA Sweetheart RNA (Swhtr), an approximately 10 kb long transcript divergently expressed from the cardiac core transcription factor coding gene Nkx2-5. We show that Swhtr is dispensable for normal heart development and function, but becomes essential for the tissue adaptation process after myocardial infarction. Re-expressing Swhtr from an exogenous locus rescues the Swhtr null phenotype. Genes depending on Swhtr after cardiac stress are significantly occupied, and therefore most likely regulated by NKX2-5. Our results indicate a synergistic role for Swhtr and the developmentally essential transcription factor NKX2-5 in tissue adaptation after myocardial injury.
Long non-coding RNAs are a very versatile class of molecules that can have important roles in regulating a cells function, including regulating other genes on the transcriptional level. One of these mechanisms is that RNA can directly interact with DNA thereby recruiting additional components such as proteins to these sites via a RNA:dsDNA triplex formation. We genetically deleted the triplex forming sequence (FendrrBox) from the lncRNA Fendrr in mice and find that this FendrrBox is partially required for Fendrr function in vivo. We find that the loss of the triplex forming site in developing lungs causes a dysregulation of gene programs, associated with lung fibrosis. A set of these genes contain a triplex site directly at their promoter and are expressed in fibroblasts. We confirm the formation of RNA:dsDNA formation with target promoters. We find that Fendrr with the Wnt signalling pathway regulates these genes, implicating that Fendrr synergizes with Wnt signalling in lung fibrosis.
Fendrr synergizes with Wnt signalling to regulate fibrosis related genes during lung development
(2021)
Long non-coding RNAs are a very versatile class of molecules that can have important roles in regulating a cells function, including regulating other genes on the transcriptional level. One of these mechanisms is that RNA can directly interact with DNA thereby recruiting additional components such as proteins to these sites via a RNA:dsDNA triplex formation. We genetically deleted the triplex forming sequence (FendrrBox) from the lncRNA Fendrr in mice and find that this FendrrBox is partially required for Fendrr function in vivo. We find that the loss of the triplex forming site in developing lungs causes a dysregulation of gene programs, associated with lung fibrosis. A set of these genes contain a triplex site directly at their promoter and are expressed in fibroblasts. We find that Fendrr with the Wnt signaling pathway regulates these genes, implicating that Fendrr synergizes with Wnt signaling in lung fibrosis.
Cannabis is the most commonly used illicit drug in the world. However due to a changing legal landscape, and rising interest in therapeutic utility, there is an increasing trend in (long-term) use and possibly, cannabis impairment. Importantly, a growing body of evidence suggests regular cannabis users develop tolerance to the impairing, as well as the rewarding, effects of the drug. However, the neuroadaptations that may underlie cannabis tolerance remain unclear. Therefore, this double-blind, randomized, placebo controlled, cross-over study assessed the acute influence of cannabis on brain and behavioral outcomes in two distinct cannabis user groups. Twelve occasional (OUs) and 12 chronic (CUs) cannabis users received acute doses of cannabis (300 μg/kg THC) and placebo, and underwent ultra-high field functional magnetic resonance imaging (fMRI) and magnetic resonance spectroscopy (MRS). In OUs, cannabis induced significant neurometabolic alterations in reward circuitry, namely decrements in functional connectivity and increments in striatal glutamate concentrations, which were associated with increases in subjective high and decreases in performance on a sustained attention task. Such changes were absent in CUs. The finding that cannabis altered circuitry and distorted behavior in OUs, but not CUs, suggests reduced responsiveness of the reward circuitry to cannabis intoxication in chronic users Taken together, the results suggest a pharmacodynamic mechanism for the development of tolerance to cannabis impairment.
The production of K∗(892)± meson resonance is measured at midrapidity (|y|<0.5) in Pb-Pb collisions at sNN−−−√=5.02 TeV using the ALICE detector at the LHC. The resonance is reconstructed via its hadronic decay channel K∗(892)±→K0Sπ±. The transverse momentum distributions are obtained for various centrality intervals in the pT range of 0.4-16 GeV/c. The reported measurements of integrated yields, mean transverse momenta, and particle yield ratios are consistent with previous ALICE measurements for K∗(892)0. The pT-integrated yield ratio 2K∗(892)±/(K++K−) in central Pb-Pb collisions shows a significant suppression (9.3σ) relative to pp collisions. Thermal model calculations overpredict the particle yield ratio. Although both simulations consider the hadronic phase, only HRG-PCE accurately represents the measurements, whereas MUSIC+SMASH tends to overpredict them. These observations, along with the kinetic freeze-out temperatures extracted from the yields of light-flavored hadrons using the HRG-PCE model, indicate a finite hadronic phase lifetime, which increases towards central collisions. The pT-differential yield ratios 2K∗(892)±/(K++K−) and 2K∗(892)±/(π++π−) are suppressed by up to a factor of five at pT<2 GeV/c in central Pb-Pb collisions compared to pp collisions at s√= 5.02 TeV. Both particle ratios and are qualitatively consistent with expectations for rescattering effects in the hadronic phase. The nuclear modification factor shows a smooth evolution with centrality and is below unity at pT>8 GeV/c, consistent with measurements for other light-flavored hadrons. The smallest values are observed in most central collisions, indicating larger energy loss of partons traversing the dense medium.
The production of K∗(892)± meson resonance is measured at midrapidity (|y|<0.5) in Pb-Pb collisions at sNN−−−√=5.02 TeV using the ALICE detector at the LHC. The resonance is reconstructed via its hadronic decay channel K∗(892)±→K0Sπ±. The transverse momentum distributions are obtained for various centrality intervals in the pT range of 0.4-16 GeV/c. The reported measurements of integrated yields, mean transverse momenta, and particle yield ratios are consistent with previous ALICE measurements for K∗(892)0. The pT-integrated yield ratio 2K∗(892)±/(K++K−) in central Pb-Pb collisions shows a significant suppression (9.3σ) relative to pp collisions. Thermal model calculations overpredict the particle yield ratio. Although both simulations consider the hadronic phase, only HRG-PCE accurately represents the measurements, whereas MUSIC+SMASH tends to overpredict them. These observations, along with the kinetic freeze-out temperatures extracted from the yields of light-flavored hadrons using the HRG-PCE model, indicate a finite hadronic phase lifetime, which increases towards central collisions. The pT-differential yield ratios 2K∗(892)±/(K++K−) and 2K∗(892)±/(π++π−) are suppressed by up to a factor of five at pT<2 GeV/c in central Pb-Pb collisions compared to pp collisions at s√= 5.02 TeV. Both particle ratios and are qualitatively consistent with expectations for rescattering effects in the hadronic phase. The nuclear modification factor shows a smooth evolution with centrality and is below unity at pT>8 GeV/c, consistent with measurements for other light-flavored hadrons. The smallest values are observed in most central collisions, indicating larger energy loss of partons traversing the dense medium.
Long- and short-range correlations for pairs of charged particles are studied via two-particle angular correlations in pp collisions at s√=13 TeV and p−Pb collisions at sNN−−−√=5.02 TeV. The correlation functions are measured as a function of relative azimuthal angle Δφ and pseudorapidity separation Δη for pairs of primary charged particles within the pseudorapidity interval |η|<0.9 and the transverse-momentum interval 1<pT<4 GeV/c. Flow coefficients are extracted for the long-range correlations (1.6<|Δη|<1.8) in various high-multiplicity event classes using the low-multiplicity template fit method. The method is used to subtract the enhanced yield of away-side jet fragments in high-multiplicity events. These results show decreasing flow signals toward lower multiplicity events. Furthermore, the flow coefficients for events with hard probes, such as jets or leading particles, do not exhibit any significant changes compared to those obtained from high-multiplicity events without any specific event selection criteria. The results are compared with hydrodynamic-model calculations, and it is found that a better understanding of the initial conditions is necessary to describe the results, particularly for low-multiplicity events.
The knowledge of the material budget with a high precision is fundamental for measurements of direct photon production using the photon conversion method due to its direct impact on the total systematic uncertainty. Moreover, it influences many aspects of the charged-particle reconstruction performance. In this article, two procedures to determine data-driven corrections to the material-budget description in ALICE simulation software are developed. One is based on the precise knowledge of the gas composition in the Time Projection Chamber. The other is based on the robustness of the ratio between the produced number of photons and charged particles, to a large extent due to the approximate isospin symmetry in the number of produced neutral and charged pions. Both methods are applied to ALICE data allowing for a reduction of the overall material budget systematic uncertainty from 4.5% down to 2.5%. Using these methods, a locally correct material budget is also achieved. The two proposed methods are generic and can be applied to any experiment in a similar fashion.
Dielectrons are unique observables in ultra-relativistic heavy-ion collisions. Thanks to their penetrating nature, they carry information from all stages of the collision and can provide knowledge about pre-equilibirium dynamics, QGP temperature and transport coefficients, and chiral symmetry restoration. On the other hand, experimental challenges are enormous because production cross sections are small and the signal of interest is eclipsed by a huge combinatorial and physics background from light- and heavy-flavour hadron decays. In this talk the status of dielectron measurements with ALICE is shown and the perspectives with the recently installed and planned ALICE detector upgrades are discussed.
The inclusive production of the charm-strange baryon Ω0c is measured for the first time via its semileptonic decay into Ω−e+νe at midrapidity (|y| < 0.8) in proton–proton (pp) collisions at the centre-of-mass energy √s = 13 TeV with the ALICE detector at the LHC. The transverse momentum (pT) differential cross section multiplied by the branching ratio is presented in the interval 2 < pT < 12 GeV/c. The branching-fraction ratio BR(Ω0c → Ω−e+νe)/BR(Ω0c → Ω−π+) is measured to be 1.12 ± 0.22 (stat.) ± 0.27 (syst.). Comparisons with other experimental measurements, as well as with theoretical calculations, are presented.
Aim: Replicate the analysis conducted by Prof. Dr. Alexander W. Schmidt-Catran (Goethe University Frankfurt), Prof. Dr. Malcolm Fairbrother (Umea University), and Prof. Dr. Hans-Jürgen Andreß (University of Cologne) that was published in a special issue on Cross-National Comparative Research in the German academic journal Kölner Zeitschrift für Soziologie und Sozialpsychologie in 2019. Result: Almost all calculations, tables and graphs from Schmidt-Catran et al. (2019) could be replicated sufficiently well in R.
In Arabidopsis thaliana, the stem cell niche (SCN) within the root apical meristem (RAM) is maintained by an intricate regulatory network that ensures optimal growth and high developmental plasticity. Yet, many aspects of this regulatory network of stem cell quiescence and replenishment are still not fully understood. Here, we investigate the interplay of the key transcription factors (TFs) BRASSINOSTEROID AT VASCULAR AND ORGANIZING CENTRE (BRAVO), PLETHORA 3 (PLT3) and WUSCHEL-RELATED HOMEOBOX 5 (WOX5) involved in SCN maintenance. Phenotypical analysis of mutants involving these TFs uncover their combinatorial regulation of cell fates and divisions in the SCN. Moreover, interaction studies employing fluorescence resonance energy transfer fluorescence lifetime imaging microscopy (FRET-FLIM) in combination with novel analysis methods, allowed us to quantify protein-protein interaction (PPI) affinities as well as higher-order complex formation of these TFs. We integrated our experimental results into a computational model, suggesting that cell type specific profiles of protein complexes and characteristic complex formation, that is also dependent on prion-like domains in PLT3, contribute to the intricate regulation of the SCN. We propose that these unique protein complex ‘signatures’ could serve as a read-out for cell specificity thereby adding another layer to the sophisticated regulatory network that balances stem cell maintenance and replenishment in the Arabidopsis root.
Bone vasculature provides protection and signals necessary to control stem cell quiescence and renewal1. Specifically, type H capillaries, which highly express Endomucin, constitute the endothelial niche supporting a microenvironment of osteoprogenitors and long-term hematopoietic stem cells2–4. The age-dependent decline in type H endothelial cells was shown to be associated with bone dysregulation and accumulation of hematopoietic stem cells, which display cell-intrinsic alterations and reduced functionality3. The regulation of bone vasculature by chronic diseases, such as heart failure is unknown. Here, we describe the effects of myocardial infarction and post-infarction heart failure on the vascular bone cell composition. We demonstrate an age-independent loss of type H bone endothelium in heart failure after myocardial infarction in both mice and in humans. Using single-cell RNA sequencing, we delineate the transcriptional heterogeneity of human bone marrow endothelium showing increased expression of inflammatory genes, including IL1B and MYC, in ischemic heart failure. Inhibition of NLRP3-dependent IL-1β production partially prevents the post-myocardial infarction loss of type H vasculature in mice. These results provide a rationale for using anti-inflammatory therapies to prevent or reverse the deterioration of vascular bone function in ischemic heart disease.
Efficient processing of visual environment necessitates the integration of incoming sensory evidence with concurrent contextual inputs and mnemonic content from our past experiences. To delineate how this integration takes place in the brain, we studied modulations of feedback neural patterns in non-stimulated areas of the early visual cortex in humans (i.e., V1 and V2). Using functional magnetic resonance imaging and multivariate pattern analysis, we show that both, concurrent contextual and time-distant mnemonic information, coexist in V1/V2 as feedback signals. The extent to which mnemonic information is reinstated in V1/V2 depends on whether the information is retrieved episodically or semantically. These results demonstrate that our stream of visual experience contains not just information from the visual surrounding, but also memory-based predictions internally generated in the brain.
Understanding the complexity of transcriptional regulation is a major goal of computational biology. Because experimental linkage of regulatory sites to genes is challenging, computational methods considering epigenomics data have been proposed to create tissue-specific regulatory maps. However, we showed that these approaches are not well suited to account for the variations of the regulatory landscape between cell-types. To overcome these drawbacks, we developed a new method called STITCHIT, that identifies and links putative regulatory sites to genes. Within STITCHIT, we consider the chromatin accessibility signal of all samples jointly to identify regions exhibiting a signal variation related to the expression of a distinct gene. STITCHIT outperforms previous approaches in various validation experiments and was used with a genome-wide CRISPR-Cas9 screen to prioritize novel doxorubicin-resistance genes and their associated non-coding regulatory regions. We believe that our work paves the way for a more refined understanding of transcriptional regulation at the gene-level.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3' untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
Coronavirus disease 2019 (COVID-19) is caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and can affect multiple organs, among which is the circulatory system. Inflammation and mortality risk markers were previously detected in COVID-19 plasma and red blood cells (RBCs) metabolic and proteomic profiles. Additionally, biophysical properties, such as deformability, were found to be changed during the infection. Based on such data, we aim to better characterize RBC functions in COVID-19. We evaluate the flow properties of RBCs in severe COVID-19 patients admitted to the intensive care unit by using in vitro microfluidic techniques and automated methods, including artificial neural networks, for an unbiased RBC analysis. We find strong flow and RBC shape impairment in COVID-19 samples and demonstrate that such changes are reversible upon suspension of COVID-19 RBCs in healthy plasma. Vice versa, healthy RBCs immediately resemble COVID-19 RBCs when suspended in COVID-19 plasma. Proteomics and metabolomics analyses allow us to detect the effect of plasma exchanges on both plasma and RBCs and demonstrate a new role of RBCs in maintaining plasma equilibria at the expense of their flow properties. Our findings provide a framework for further investigations of clinical relevance for therapies against COVID-19 and possibly other infectious diseases.
Coronavirus disease 2019 (COVID-19) is caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and can affect multiple organs, among which is the circulatory system. Inflammation and mortality risk markers were previously detected in COVID-19 plasma and red blood cells (RBCs) metabolic and proteomic profiles. Additionally, biophysical properties, such as deformability, were found to be changed during the infection. Based on such data, we aim to better characterize RBC functions in COVID-19. We evaluate the flow properties of RBCs in severe COVID-19 patients admitted to the intensive care unit by using in vitro microfluidic techniques and automated methods, including artificial neural networks, for an unbiased RBC analysis. We find strong flow and RBC shape impairment in COVID-19 samples and demonstrate that such changes are reversible upon suspension of COVID-19 RBCs in healthy plasma. Vice versa, healthy RBCs immediately resemble COVID-19 RBCs when suspended in COVID-19 plasma. Proteomics and metabolomics analyses allow us to detect the effect of plasma exchanges on both plasma and RBCs and demonstrate a new role of RBCs in maintaining plasma equilibria at the expense of their flow properties. Our findings provide a framework for further investigations of clinical relevance for therapies against COVID-19 and possibly other infectious diseases.
We carry out an in-depth analysis of the prompt-collapse behaviour of binary neutron star (BNS) mergers. To this end, we perform more than 80 general relativistic BNS merger simulations using a family of realistic Equations of State (EOS) with different stiffness, which feature a first order deconfinement phase transition between hadronic and quark matter. From these simulations we infer the critical binary mass Mcrit that separates the prompt from the non-prompt collapse regime. We show that the critical mass increases with the stiffness of the EOS and obeys a tight quasi-universal relation, Mcrit/MTOV ≈ 1.41 ± 0.06, which links it to the maximum mass MTOV of static neutron stars, and therefore provides a straightforward estimate for the total binary mass beyond which prompt collapse becomes inevitable. In addition, we introduce a novel gauge independent definition for a one-parameter family of threshold masses in terms of curvature invariants of the Riemann tensor which characterizes the development toward a more rapid collapse with increasing binary mass. Using these diagnostics, we find that the amount of matter remaining outside the black hole sharply drops in supercritical mass mergers compared to subcritical ones and is further reduced in mergers where the black hole collapse is induced by the formation of a quark matter core. This implies that Mcrit, particularly for merger remnants featuring quark matter cores, imposes a strict upper limit on the emission of any detectable electromagnetic counterpart in BNS mergers.
In this special issue of Matrix Biology centered on proteoglycan biology we have assembled a blend of articles focused on the state-of-the-art of proteoglycanology. The field has greatly expanded in the past three decades and now encompasses all the areas of biology. This special issue is divided into five chapters describing hyaluronan metabolism, biosynthetic and catabolic pathways of proteoglycans and their roles in inflammation, cancer, repair and development. We hope that the new original work and the reviews from recognized leaders will stimulate investigations in this exciting and fertile field of research.
Post-merger gravitational-wave signal from neutron-star binaries: a new look at an old problem
(2023)
The spectral properties of the post-merger gravitational-wave signal from a binary of neutron stars encodes a variety of information about the features of the system and of the equation of state describing matter around and above nuclear saturation density. Characterising the properties of such a signal is an “old” problem, which first emerged when a number of frequencies were shown to be related to the properties of the binary through “quasi-universal” relations. Here we take a new look at this old problem by computing the properties of the signal in terms of the Weyl scalar ψ4. In this way, and using a database of more than 100 simulations, we provide the first evidence for a new instantaneous frequency, f ψ4 0, associated with the instant of quasi timesymmetry in the postmerger dynamics, and which also follows a quasi-universal relation. We also derive a new quasi-universal relation for the merger frequency f h mer, which provides a description of the data that is four times more accurate than previous expressions while requiring fewer fitting coefficients. Finally, consistently with the findings of numerous studies before ours, and using an enlarged ensamble of binary systems we point out that the ℓ = 2, m = 1 gravitational-wave mode could become comparable with the traditional ℓ = 2, m = 2 mode on sufficiently long timescales, with strain amplitudes in a ratio |h 21|/|h 22| ∼ 0.1 − 1 under generic orientations of the binary, which could be measured by present detectors for signals with large signal-to-noise ratio or by third-generation detectors for generic signals should no collapse occur.
A considerable effort has been dedicated recently to the construction of generic equations of state (EOSs) for matter in neutron stars. The advantage of these approaches is that they can provide model-independent information on the interior structure and global properties of neutron stars. Making use of more than 106 generic EOSs, we asses the validity of quasi-universal relations of neutron star properties for a broad range of rotation rates, from slow-rotation up to the mass-shedding limit. In this way, we are able to determine with unprecedented accuracy the quasi-universal maximum-mass ratio between rotating and nonrotating stars and reveal the existence of a new relation for the surface oblateness, i.e., the ratio between the polar and equatorial proper radii. We discuss the impact that our findings have on the imminent detection of new binary neutron-star mergers and how they can be used to set new and more stringent limits on the maximum mass of nonrotating neutron stars, as well as to improve the modelling of the X-ray emission from the surface of rotating stars.
We have investigated the systematic differences introduced when performing a Bayesian-inference analysis of the equation of state of neutron stars employing either variable- or constant-likelihood functions. The former have the advantage that it retains the full information on the distributions of the measurements, making an exhaustive usage of the data. The latter, on the other hand, have the advantage of a much simpler implementation and reduced computational costs. In both approaches, the EOSs have identical priors and have been built using the sound-speed parameterization method so as to satisfy the constraints from X-ray and gravitationalwaves observations, as well as those from Chiral Effective Theory and perturbative QCD. In all cases, the two approaches lead to very similar results and the 90%-confidence levels are essentially overlapping. Some differences do appear, but in regions where the probability density is extremely small and are mostly due to the sharp cutoff set on the binary tidal deformability Λ˜ ≤ 720 employed in the constant-likelihood analysis. Our analysis has also produced two additional results. First, a clear inverse correlation between the normalized central number density of a maximally massive star, nc,TOV/ns, and the radius of a maximally massive star, RTOV. Second, and most importantly, it has confirmed the relation between the chirp mass Mchirp and the binary tidal deformability Λ˜. The importance of this result is that it relates a quantity that is measured very accurately, Mchirp, with a quantity that contains important information on the micro-physics, Λ˜. Hence, once Mchirp is measured in future detections, our relation has the potential of setting tight constraints on Λ˜.
Using full 3+1 dimensional general-relativistic hydrodynamic simulations of equal- and unequal-mass neutron-star binaries with properties that are consistent with those inferred from the inspiral of GW170817, we perform a detailed study of the quark-formation processes that could take place after merger. We use three equations of state consistent with current pulsar observations derived from a novel finite-temperature framework based on V-QCD, a non-perturbative gauge/gravity model for Quantum Chromodynamics. In this way, we identify three different post-merger stages at which mixed baryonic and quark matter, as well as pure quark matter, are generated. A phase transition triggered collapse already ≲10ms after the merger reveals that the softest version of our equations of state is actually inconsistent with the expected second-long post-merger lifetime of GW170817. Our results underline the impact that multi-messenger observations of binary neutron-star mergers can have in constraining the equation of state of nuclear matter, especially in its most extreme regimes.
Holography has provided valuable insights into the time evolution of strongly coupled gauge theories in a fixed spacetime. However, this framework is insufficient if this spacetime is dynamical. We present a novel scheme to evolve a four-dimensional, strongly interacting gauge theory coupled to four-dimensional dynamical gravity in the semiclassical regime. We use holography to evolve the quantum gauge theory stress tensor. The four-dimensional metric evolves according to the four-dimensional Einstein equations coupled to the expectation value of the stress tensor. We focus on Friedmann-Lemaître-Robertson-Walker geometries and evolve far-from-equilibrium initial states that lead to asymptotically expanding, flat or collapsing Universes.
We use the quantum null energy condition in strongly coupled two-dimensional field theories (QNEC2) as diagnostic tool to study a variety of phase structures, including crossover, second and first order phase transitions. We find a universal QNEC2 constraint for first order phase transitions with kinked entanglement entropy and discuss in general the relation between the QNEC2-inequality and monotonicity of the Casini-Huerta c-function. We then focus on a specific example, the holographic dual of which is modelled by three-dimensional Einstein gravity plus a massive scalar field with one free parameter in the self-interaction potential. We study translation invariant stationary states dual to domain walls and black branes. Depending on the value of the free parameter we find crossover, second and first order phase transitions between such states, and the c-function either flows to zero or to a finite value in the infrared. Strikingly, evaluating QNEC2 for ground state solutions allows to predict the existence of phase transitions at finite temperature.
We use the quantum null energy condition in strongly coupled two-dimensional field theories (QNEC2) as diagnostic tool to study a variety of phase structures, including crossover, second and first order phase transitions. We find a universal QNEC2 constraint for first order phase transitions with kinked entanglement entropy and discuss in general the relation between the QNEC2-inequality and monotonicity of the Casini-Huerta c-function. We then focus on a specific example, the holographic dual of which is modelled by three-dimensional Einstein gravity plus a massive scalar field with one free parameter in the self-interaction potential. We study translation invariant stationary states dual to domain walls and black branes. Depending on the value of the free parameter we find crossover, second and first order phase transitions between such states, and the c-function either flows to zero or to a finite value in the infrared. Strikingly, evaluating QNEC2 for ground state solutions allows to predict the existence of phase transitions at finite temperature.
We use the quantum null energy condition in strongly coupled two-dimensional field theories (QNEC2) as diagnostic tool to study a variety of phase structures, including crossover, second and first order phase transitions. We find a universal QNEC2 constraint for first order phase transitions with kinked entanglement entropy and discuss in general the relation between the QNEC2-inequality and monotonicity of the Casini-Huerta c-function. We then focus on a specific example, the holographic dual of which is modelled by three-dimensional Einstein gravity plus a massive scalar field with one free parameter in the self-interaction potential. We study translation invariant stationary states dual to domain walls and black branes. Depending on the value of the free parameter we find crossover, second and first order phase transitions between such states, and the c-function either flows to zero or to a finite value in the infrared. Strikingly, evaluating QNEC2 for ground state solutions allows to predict the existence of phase transitions at finite temperature.
Holography has provided valuable insights into the time evolution of strongly coupled gauge theories in a fixed spacetime. However, this framework is insufficient if this spacetime is dynamical. We present a scheme to evolve a four-dimensional, strongly interacting gauge theory coupled to four-dimensional dynamical gravity in the semiclassical regime. As in previous work, we use holography to evolve the quantum gauge theory stress tensor, whereas the four-dimensional metric evolves according to Einstein's equations coupled to the expectation value of the stress tensor. The novelty of our approach is that both the boundary and the bulk spacetimes are constructed dynamically, one time step at a time. We focus on Friedmann-Lemaître-Robertson-Walker geometries and evolve far-from-equilibrium initial states that lead to asymptotically expanding, flat or collapsing Universes.
We present a novel framework for the equation of state of dense and hot Quantum Chromodynamics (QCD), which focuses on the region of the phase diagram relevant for neutron star mergers and core-collapse supernovae. The model combines predictions from the gauge/gravity duality with input from lattice field theory, QCD perturbation theory, chiral effective theory and statistical modeling. It is therefore, by construction, in good agreement with theoretical constraints both at low and high densities and temperatures. The main ingredients of our setup are the non-perturbative V-QCD model based on the gauge/gravity duality, a van der Waals model for nucleon liquid, and the DD2 version of the Hempel-Schaffner-Bielich statistical model of nuclear matter. By consistently combining these models, we also obtain a description for the nuclear to quark matter phase transition and its critical endpoint. The parameter dependence of the model is represented by three (soft, intermediate and stiff) variants of the equation of state, all of which agree with observational constraints from neutron stars and their mergers. We discuss resulting constraints for the equation of state, predictions for neutron stars and the location of the critical point.
According to the inflationary theory of cosmology, most elementary particles in the current universe were created during a period of reheating after inflation. In this work we self-consistently couple the Einstein-inflaton equations to a strongly coupled quantum field theory (QFT) as described by holography. We show that this leads to an inflating universe, a reheating phase and finally a universe dominated by the QFT in thermal equilibrium.
We use holography to study the dynamics of a strongly-coupled gauge theory in four-dimensional de Sitter space with Hubble rate H. The gauge theory is non-conformal with a characteristic mass scale M. We solve Einstein’s equations numerically and determine the time evolution of homogeneous gauge theory states. If their initial energy density is high compared with H4 then the early-time evolution is well described by viscous hydrodynamics with a non-zero bulk viscosity. At late times the dynamics is always far from equilibrium. The asymptotic late-time state preserves the full de Sitter symmetry group and its dual geometry is a domain-wall in AdS5. The approach to this state is characterised by an emergent relation of the form P = w E that is different from the equilibrium equation of state in flat space. The constant w does not depend on the initial conditions but only on H/M and is negative if the ratio H/M is close to unity. The event and the apparent horizons of the late-time solution do not coincide with one another, reflecting its non-equilibrium nature. In between them lies an “entanglement horizon” that cannot be penetrated by extremal surfaces anchored at the boundary, which we use to compute the entanglement entropy of boundary regions. If the entangling region equals the observable universe then the extremal surface coincides with a bulk cosmological horizon that just touches the event horizon, while for larger regions the extremal surface probes behind the event horizon.
We present the first holographic simulations of non-equilibrium steady state formation in strongly coupled N=4 SYM theory in 3+1 dimensions. We initially join together two thermal baths at different temperatures and chemical potentials and compare the subsequent evolution of the combined system to analytic solutions of the corresponding Riemann problem and to numeric solutions of ideal and viscous hydrodynamics. The time evolution of the energy density that we obtain holographically is consistent with the combination of a shock and a rarefaction wave: A shock wave moves towards the cold bath, and a smooth broadening wave towards the hot bath. Between the two waves emerges a steady state with constant temperature and flow velocity, both of which are accurately described by a shock+rarefaction wave solution of the Riemann problem. In the steady state region, a smooth crossover develops between two regions of different charge density. This is reminiscent of a contact discontinuity in the Riemann problem. We also obtain results for the entanglement entropy of regions crossed by shock and rarefaction waves and find both of them to closely follow the evolution of the energy density.
We present the first holographic simulations of non-equilibrium steady state formation in strongly coupled N=4 SYM theory in 3+1 dimensions. We initially join together two thermal baths at different temperatures and chemical potentials and compare the subsequent evolution of the combined system to analytic solutions of the corresponding Riemann problem and to numeric solutions of ideal and viscous hydrodynamics. The time evolution of the energy density that we obtain holographically is consistent with the combination of a shock and a rarefaction wave: A shock wave moves towards the cold bath, and a smooth broader wave towards the hot bath. Between the two waves emerges a steady state with constant temperature and flow velocity, both of which are accurately described by a shock+rarefaction wave solution of the Riemann problem. In the steady state region develops a smooth crossover between two regions of different charge densities that diffuses on a timescale proportional to t√ and is reminiscent of a contact discontinuity in the Riemann problem. We also obtain results for the entanglement entropy of regions crossed by shock and rarefaction waves and find both of them to closely follow the evolution of the energy density.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions, using signals from nanopore direct RNA sequencing. CHEUI processes observed and expected signals with convolutional neural networks to achieve high single-molecule accuracy and outperform other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A significant roadblock hindering progress in epitranscriptomics is the identification of more than one modification in individual transcript molecules. We address this with CHEUI (CH3 (methylation) Estimation Using Ionic current). CHEUI predicts N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual molecules from the same sample, the stoichiometry at transcript reference sites, and differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals to achieve high single-molecule, transcript-site, and stoichiometry accuracies in multiple tests using synthetic RNA standards and cell line data. CHEUI’s capability to identify two modification types in the same sample reveals a co-occurrence of m6A and m5C in individual mRNAs in cell line and tissue transcriptomes. CHEUI provides new avenues to discover and study the function of the epitranscriptome.
The expanding field of epitranscriptomics might rival the epigenome in the diversity of the biological processes impacted. However, the identification of modifications in individual RNA molecules remains challenging. We present CHEUI, a new method that detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) at single-nucleotide and single-molecule resolution from Nanopore signals. CHEUI predicts methylation in Nanopore reads and transcriptomic sites in a single condition, and differential m6A and m5C methylation between any two conditions. Using extensive benchmarking with Nanopore data derived from synthetic and natural RNA, CHEUI showed higher accuracy than other existing methods in detecting m6A and m5C sites and quantifying the site stoichiometry levels, while maintaining a lower proportion of false positives. CHEUI provides a new capability to detect RNA modifications with high accuracy and resolution that can be cost-effectively expanded to other modifications to unveil the full span of the epitranscriptome in normal and disease conditions.
Nuclear pore complexes (NPCs) constitute giant channels within the nuclear envelope that mediate nucleocytoplasmic exchange. NPC diameter is thought to be regulated by nuclear envelope tension, but how such diameter changes are physiologically linked to cell differentiation, where mechanical properties of nuclei are remodeled and nuclear mechanosensing occurs, remains unstudied. Here we used cryo-electron tomography to show that NPCs dilate during differentiation of mouse embryonic stem cells into neural progenitors. In Nup133-deficient cells, which are known to display impaired neural differentiation, NPCs however fail to dilate. By analyzing the architectures of individual NPCs with template matching, we revealed that the Nup133-deficient NPCs are structurally heterogeneous and frequently disintegrate, resulting in the formation of large nuclear envelope openings. We propose that the elasticity of the NPC scaffold mechanically safeguards the nuclear envelope. Our studies provide a molecular explanation for how genetic perturbation of scaffolding components of macromolecular complexes causes tissue-specific phenotypes.
Upon infection, human immunodeficiency virus (HIV-1) releases its cone-shaped capsid into the cytoplasm of infected T-cells and macrophages. As its largest known cargo, the capsid enters the nuclear pore complex (NPC), driven by interactions with numerous FG-repeat nucleoporins (FG-Nups). Whether NPCs structurally adapt to capsid passage and whether capsids are modified during passage remains unknown, however. Here, we combined super-resolution and correlative microscopy with cryo electron tomography and molecular simulations to study nuclear entry of HIV-1 capsids in primary human macrophages. We found that cytosolically bound cyclophilin A is stripped off capsids entering the NPC, and the capsid hexagonal lattice remains largely intact inside and beyond the central channel. Strikingly, the NPC scaffold rings frequently crack during capsid passage, consistent with computer simulations indicating the need for NPC widening. The unique cone shape of the HIV-1 capsid facilitates its entry into NPCs and helps to crack their rings.
Tree-related microhabitats (TreMs) describe the microhabitats that a tree can provide for a multitude of other taxonomic groups and have been proposed as an important indicator for forest biodiversity (Asbeck et al., 2021). So far, the focus of TreM studies has been on temperate forests, although many trees in the tropics harbour exceptionally high numbers of TreMs. In this study, TreMs in the lowland tropical forests of the Choco (Ecuador) and in the mountain tropical forests of Mount Kilimanjaro (Tanzania) were surveyed. Our results extend the existing typology of TreMs of Larrieu et al. (2018) to include tropical forests and enabled a comparison of the relative recordings and diversity of TreMs between tropical and temperate forests. A new TreM form, Root formations, and three new TreM groups, concavities build by fruits or leaves, dendrotelms, and root formations, were established. In total, 15 new TreM types in five different TreM groups were specified. The relative recordings of most TreMs were similar between tropical and temperate forests. However, ivy and lianas, and ferns were more common in the lowland rainforest than in temperate forests, and bark microsoil, limb breakage, and foliose and fruticose lichens in tropical montane forest than in lowland rainforest. Mountain tropical forests hosted the highest diversity for common and dominant TreM types, and lowland tropical forest the highest diversity for rare TreMs. Our extended typology of tree-related microhabitats can support studies of forest-dwelling biodiversity in tropical forests. Specifically, given the ongoing threat to tropical forests, TreMs can serve as an additional tool allowing rapid assessments of biodiversity in these hyperdiverse ecosystems.
Upon infection of host cells, Legionella pneumophila releases a multitude of effector enzymes into the cells cytoplasm that hijack a plethora of cellular activities, including the hosts ubiquitination pathways. Effectors belonging to the SidE-family are involved in non-canonical serine phosphoribosyl ubiquitination of host substrate proteins contributing to the formation of a Legionella-containing vacuole that is crucial in the onset of Legionnaires’ disease. This dynamic process is reversed by effectors called Dups that hydrolyse the phosphodiester in the phosphoribosyl ubiquitinated protein. We installed reactive warheads on chemically prepared ribosylated ubiquitin to generate a set of probes targeting these Legionella enzymes. In vitro tests on recombinant DupA revealed that a vinyl sulfonate warhead was most efficient in covalent complex formation. Mutagenesis and x-ray crystallography approaches were used to identify the site of covalent crosslinking to be an allosteric cysteine residue. The subsequent application of this probe highlights the potential to selectively enrich the Dup enzymes from Legionella-infected cell lysates.
An important question concerning inter-areal communication in the cortex is whether these interactions are synergistic, i.e. brain signals can either share common information (redundancy) or they can encode complementary information that is only available when both signals are considered together (synergy). Here, we dissociated cortical interactions sharing common information from those encoding complementary information during prediction error processing. To this end, we computed co-information, an information-theoretical measure that distinguishes redundant from synergistic information among brain signals. We analyzed auditory and frontal electrocorticography (ECoG) signals in five common awake marmosets performing two distinct auditory oddball tasks and investigated to what extent event-related potentials (ERP) and broadband (BB) dynamics encoded redundant and synergistic information during auditory prediction error processing. In both tasks, we observed multiple patterns of synergy across the entire cortical hierarchy with distinct dynamics. The information conveyed by ERPs and BB signals was highly synergistic even at lower stages of the hierarchy in the auditory cortex, as well as between auditory and frontal regions. Using a brain-constrained neural network, we simulated the spatio-temporal patterns of synergy and redundancy observed in the experimental results and further demonstrated that the emergence of synergy between auditory and frontal regions requires the presence of strong, long-distance, feedback and feedforward connections. These results indicate that the distributed representations of prediction error signals across the cortical hierarchy can be highly synergistic.
EF-P and its paralog EfpL (YeiP) differentially control translation of proline containing sequences
(2024)
Polyproline sequences (XPPX) stall ribosomes, thus being deleterious for all living organisms. In bacteria, translation elongation factor P (EF-P) plays a crucial role in overcoming such arrests. 12% of eubacteria possess an EF-P paralog – YeiP (EfpL) of unknown function. Here, we functionally and structurally characterize EfpL from Escherichia coli and demonstrate its yet unrecognized role in the translational stress response. Through ribosome profiling, we analyzed the EfpL arrest motif spectrum and discovered additional stalls beyond the canonical XPPX motifs at single-proline sequences (XPX), that both EF-P and EfpL can resolve. Notably, the two factors can also induce pauses. We further report that, contrary to the housekeeping EF-P, EfpL can sense the metabolic state of the cell, via lysine acylation. Together, our work uncovers a new player in ribosome rescue at proline-containing sequences, and provides evidence that co-occurrence of EF-P and EfpL is an evolutionary driver for higher bacterial growth rates.
Coarse-grained modeling has become an important tool to supplement experimental measurements, allowing access to spatio-temporal scales beyond all-atom based approaches. The GōMartini model combines structure- and physics-based coarse-grained approaches, balancing computational efficiency and accurate representation of protein dynamics with the capabilities of studying proteins in different biological environments. This paper introduces an enhanced GōMartini model, which combines a virtual-site implementation of Gō models with Martini 3. The implementation has been extensively tested by the community since the release of the new version of Martini. This work demonstrates the capabilities of the model in diverse case studies, ranging from protein-membrane binding to protein-ligand interactions and AFM force profile calculations. The model is also versatile, as it can address recent inaccuracies reported in the Martini protein model. Lastly, the paper discusses the advantages, limitations, and future perspectives of the Martini 3 protein model and its combination with Gō models.
Human functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Rare states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture and to be highly subject-specific. However, it is unclear whether such network-defining states also contribute to individual variations in cognitive abilities – which strongly rely on the interactions among distributed brain regions. By introducing CMEP, a new eigenvector-based prediction framework, we show that as few as 16 temporally separated time frames (< 1.5% of 10min resting-state fMRI) can significantly predict individual differences in intelligence (N = 263, p < .001). Against previous expectations, individual’s network-defining time frames of particularly high cofluctuation do not predict intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N = 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest connectivity, temporally distributed information is necessary to extract information about cognitive abilities. This information is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.
In high light, the antenna system in oxygenic photosynthetic organisms switches to a photoprotective mode, dissipating excess energy in a process called non-photochemical quenching (NPQ). Diatoms exhibit very efficient NPQ, accompanied by a xanthophyll cycle in which diadinoxanthin is de-epoxidized into diatoxanthin. Diatoms accumulate pigments from this cycle in high light, and exhibit faster and more pronounced NPQ. The mechanisms underlying NPQ in diatoms remain unclear, but it can be mimicked by aggregation of their isolated light-harvesting complexes, FCP (fucoxanthin chlorophyll-a/c protein). We assess this model system by resonance Raman measurements of two peripheral FCPs, trimeric FCPa and nonameric FCPb, isolated from high- and low-light-adapted cells (LL, HL). Quenching is associated with a reorganisation of these proteins, affecting the conformation of their bound carotenoids, and in a manner which is highly dependent on the protein considered. FCPa from LL diatoms exhibits significant changes in diadinoxanthin structure, together with a smaller conformational change of at least one fucoxanthin. For these LL-FCPa, quenching is associated with consecutive events, displaying distinct spectral signatures, and its amplitude correlates with the planarity of the diadinoxanthin structure. HL-FCPa aggregation is associated with a change in planarity of a 515-nm-absorbing fucoxanthin, and, to a lesser extent, of diadinoxanthin. Finally, in FCPb, a blue-absorbing fucoxanthin is primarily affected. FCPs thus possess a plastic structure, undergoing several conformational changes upon aggregation, dependent upon their precise composition and structure. NPQ in diatoms may therefore arise from a combination of structural changes, dependent on the environment the cells are adapted to.
Microbial rhodopsins are omnipresent on Earth, however the vast majority of them remain uncharacterized. Here we describe a new rhodopsin clade from cold-adapted organisms and cold environments, such as glaciers, denoted as CryoRhodopsins (CryoRs). Our data suggest that CryoRs have photosensory activity. A distinguishing feature of the clade is the presence of a buried arginine residue close to the cytoplasmic face of its members. Combining single-particle cryo-electron microscopy and X-ray crystallography with the rhodopsin activation by light, we demonstrate that the arginine stabilizes a strongly blue-shifted intermediate of an extremely slow CryoRhodopsin photocycle. Together with extensive spectroscopic characterization, our investigations on CryoR1 and CryoR2 proteins reveal mechanisms of photoswitching in the newly identified clade and demonstrate principles of the adaptation of these rhodopsins to low temperatures.
Microbial rhodopsins are omnipresent on Earth, however the vast majority of them remain uncharacterized. Here we describe a new rhodopsin group from cold-adapted organisms and cold environments, such as glaciers, denoted as CryoRhodopsins (CryoRs). Our data suggest that CryoRs have dual functionality switching between inward transmembrane proton translocation and photosensory activity, both of which can be modulated with UV light. CryoR1 exhibits two subpopulations in the ground state, which upon light activation lead to transient photocurrents of opposing polarities. A distinguishing feature of the group is the presence of a buried arginine residue close to the cytoplasmic face of its members. Combining single-particle cryo-electron microscopy and X-ray crystallography with the rhodopsin activation by lit, we demonstrate that the arginine stabilizes a UV-absorbing intermediate of an extremely slow CryoRhodopsin photocycle. Together with extensive spectroscopic characterization, our investigations on CryoR1 and CryoR2 proteins reveal mechanisms of photoswitching in the newly identified group and demonstrate principles of the adaptation of these rhodopsins to low temperatures.Microbial rhodopsins are omnipresent on Earth, however the vast majority of them remain uncharacterized. Here we describe a new rhodopsin group from cold-adapted organisms and cold environments, such as glaciers, denoted as CryoRhodopsins (CryoRs). Our data suggest that CryoRs have dual functionality switching between inward transmembrane proton translocation and photosensory activity, both of which can be modulated with UV light. CryoR1 exhibits two subpopulations in the ground state, which upon light activation lead to transient photocurrents of opposing polarities. A distinguishing feature of the group is the presence of a buried arginine residue close to the cytoplasmic face of its members. Combining single-particle cryo-electron microscopy and X-ray crystallography with the rhodopsin activation by light, we demonstrate that the arginine stabilizes a UV-absorbing intermediate of an extremely slow CryoRhodopsin photocycle. Together with extensive spectroscopic characterization, our investigations on CryoR1 and CryoR2 proteins reveal mechanisms of photoswitching in the newly identified group and demonstrate principles of the adaptation of these rhodopsins to low temperatures.
The spike protein of SARS-CoV-2 is a highly flexible membrane receptor that triggers the translocation of the virus into cells by attaching to the human receptors. Like other type I membrane receptors, this protein has several extracellular domains connected by flexible hinges. The presence of these hinges results in high flexibility, which consequently results in challenges in defining the conformation of the protein. Here, We developed a new method to define the conformational space based on a few variables inspired by the robotic field’s methods to determine a robotic arm’s forward kinematics. Using newly performed atomistic molecular dynamics (MD) simulations and publicly available data, we found that the Denavit-Hartenberg (DH) parameters can reliably show the changes in the local conformation. Furthermore, the rotational and translational components of the homogenous transformation matrix constructed based on the DH parameters can identify the changes in the global conformation of the spike and also differentiate between the conformation with a similar position of the spike head, which other types of parameters, such as spherical coordinates, fail to distinguish between such conformations. Finally, the new method will be beneficial for looking at the conformational heterogeneity in all other type I membrane receptors.
Background: Trauma-related guilt and shame are crucial for the development and maintenance of PTSD (posttraumatic stress disorder). We developed an intervention combining cognitive techniques with loving-kindness meditations (C-METTA) that specifically target these emotions. C-METTA is an intervention of six weekly individual treatment sessions followed by a four-week practice phase.
Objective: This study examined C-METTA in a proof-of-concept study within a randomized wait-list controlled trial.
Method: We randomly assigned 32 trauma-exposed patients with a DSM-5 diagnosis to C-METTA or a wait-list condition (WL). Primary outcomes were clinician-rated PTSD symptoms (CAPS-5) and trauma-related guilt and shame. Secondary outcomes included psychopathology, self-criticism, well-being, and self-compassion. Outcomes were assessed before the intervention phase and after the practice phase.
Results: Mixed-design analyses showed greater reductions in C-METTA versus WL in clinician-rated PTSD symptoms (d = −1.09), guilt (d = −2.85), shame (d = −2.14), psychopathology and self-criticism.
Conclusion: Our findings support positive outcomes of C-METTA and might contribute to improved care for patients with stress-related disorders. The study was registered in the German Clinical Trials Register (DRKS00023470).
HIGHLIGHTS
C-METTA is an intervention that addresses trauma-related guilt and shame and combines cognitive interventions with loving-kindness meditations.
A proof-of-concept study was conducted examining C-METTA in a wait-list randomized controlled trial
C-METTA led to reductions in trauma-related guilt and shame and PTSD symptoms.
From hunting and foraging to clearing land for agriculture, humans modify forest biodiversity, landscapes, and climate. Forests constantly undergo disturbance–recovery dynamics and understanding them is a major objective of ecologists and conservationists. Chronosequences are a useful tool for understanding global restoration efforts. They represent a space-for-time substitution approach suited for the quantification of the resistance of ecosystem properties to withstand disturbance and the resilience of these properties until reaching pre-disturbance levels. Here we introduce a newly established chronosequence with 62 plots (50 ⍰ 50 m) in active cacao plantations and pastures, early and late regeneration, and mature old-growth forests, across a 200 km2 area in the extremely wet Chocó rainforest. Our chronosequence covers by far the largest total area of plots compared to others in the Neotropics. Plots ranged from 159–615 masl in a forested landscape with 74 ± 2.8 % forest cover within a 1-km radius including substantial old-growth forest cover. Land-use legacy and regeneration time were not confounded by elevation. We tested how six forest structure variables (maximum tree height and DBH, basal area, number of stems, vertical vegetation heterogeneity, and light availability), aboveground biomass (AGB), and rarefied tree species richness change along our chronosequence. Forest structure variables, AGB, and tree species richness increased with regeneration time and are predicted to reach similar levels to those in old-growth forests after ca. 30–116, 202, and 108 yrs, respectively. Compared to previous work in the Neotropics, old-growth forests in Canandé accumulate high AGB that takes one of the largest time spans reported until total recovery. Our chronosequence comprises one of the largest tree species pools, covers the largest total area of regenerating and old-growth forests, and has higher forest cover than other Neotropical chronosequences. Hence, our chronosequence can be used to determine the time for recovery and stability (resistance and resilience) of different taxa and ecosystem functions, including species interaction networks. This integrative effort will ultimately help to understand how one of the most diverse forests on the planet recovers from large-scale disturbances.
The small GTPases H, K, and NRAS are molecular switches that are indispensable for proper regulation of cellular proliferation and growth. Mutations in this family of proteins are associated with cancer and result in aberrant activation of signaling processes caused by a deregulated recruitment of downstream effector proteins. In this study, we engineered novel variants of the Ras-binding domain (RBD) of the kinase CRAF. These variants bound with high affinity to the effector binding site of active Ras. Structural characterization showed how the newly identified mutations cooperate to enhance affinity to the effector binding site compared to RBDwt. The engineered RBD variants closely mimic the interaction mode of naturally occurring Ras effectors and as dominant negative affinity reagent block their activation. Experiments with cancer cells showed that expression of these RBD variants inhibits Ras signaling leading to a reduced growth and inductions of apoptosis. Using the optimized RBD variants, we stratified patient-derived colorectal cancer organoids according to Ras dependency, which showed that the presence of Ras mutations was insufficient to predict sensitivity to Ras inhibition.
Light-driven sodium pumps (NaRs) are unique ion-transporting microbial rhodopsins. The major group of NaRs is characterized by an NDQ motif and has two aspartic acid residues in the central region essential for sodium transport. Here we identified a new subgroup of the NDQ rhodopsins bearing an additional glutamic acid residue in the close vicinity to the retinal Schiff base. We thoroughly characterized a member of this subgroup, namely the protein ErNaR from Erythrobacter sp. HL-111 and showed that the additional glutamic acid results in almost complete loss of pH sensitivity for sodium-pumping activity, which is in contrast to previously studied NaRs. ErNaR is capable of transporting sodium efficiently even at acidic pH levels. X-ray crystallography and single particle cryo-electron microscopy reveal that the additional glutamic acid residue mediates the connection between the other two Schiff base counterions and strongly interacts with the aspartic acid of the characteristic NDQ motif. Hence, it reduces its pKa. Our findings shed light on a new subgroup of NaRs and might serve as a basis for their rational optimization for optogenetics.
Attention-Deficit/Hyperactivity Disorder (ADHD) is frequently comorbid with other psychiatric disorders and also with somatic conditions, such as obesity. In addition to the clinical overlap, significant genetic correlations have been found between ADHD and obesity as well as body mass index (BMI). The biological mechanisms driving this association are largely unknown, but some candidate systems, like dopaminergic neurotransmission and circadian rhythm, have been suggested. Our aim was to identify the biological mechanisms underpinning the link between ADHD and obesity measures. Using the largest GWAS summary statistics currently available for ADHD (N=53,293), BMI (N=681,275), and obesity (N=98,697), we first tested the association of dopaminergic and circadian rhythm gene sets with each phenotype. This hypothesis-driven approach showed that the dopaminergic gene set was associated with both ADHD (P=5.81×10−3) and BMI (P=1.63×10−5), while the circadian rhythm gene set was associated with BMI only (P=1.28×10−3). We then took a data-driven approach by conducting genome-wide ADHD-BMI and ADHD-obesity gene-based meta-analyses, followed by pathway enrichment analyses. This approach further supported the implication of dopaminergic signaling in the link between ADHD and obesity measures, as the Dopamine-DARPP32 Feedback in cAMP Signaling pathway was significantly enriched in both the ADHD-BMI and ADHD-obesity gene-based meta-analysis results. Our findings suggest that dopaminergic neurotransmission, partially through DARPP-32-dependent signaling, is a key player underlying the genetic overlap between ADHD and obesity measures. Uncovering the shared etiological factors underlying the frequently observed ADHD-obesity comorbidity may have important implications in terms of preventive interventions and/or efficient treatment of these conditions.
Attention-Deficit/Hyperactivity Disorder (ADHD) and obesity are frequently comorbid, genetically correlated, and share brain substrates. The biological mechanisms driving this association are unclear, but candidate systems, like dopaminergic neurotransmission and circadian rhythm, have been suggested. Our aim was to identify the biological mechanisms underpinning the genetic link between ADHD and obesity measures and investigate associations of overlapping genes with brain volumes. We tested the association of dopaminergic and circadian rhythm gene sets with ADHD, body mass index (BMI), and obesity (using GWAS data of N=53,293, N=681,275, and N=98,697, respectively). We then conducted genome-wide ADHD-BMI and ADHD-obesity gene-based meta-analyses, followed by pathway enrichment analyses. Finally, we tested the association of ADHD-BMI overlapping genes with brain volumes (primary GWAS data N=10,720–10,928; replication data N=9,428). The dopaminergic gene set was associated with both ADHD (P=5.81×10−3) and BMI (P=1.63×10−5), the circadian rhythm was associated with BMI (P=1.28×10−3). The genome-wide approach also implicated the dopaminergic system, as the Dopamine-DARPP32 Feedback in cAMP Signaling pathway was enriched in both ADHD-BMI and ADHD-obesity results. The ADHD-BMI overlapping genes were associated with putamen volume (P=7.7×10−3; replication data P=3.9×10−2) – a brain region with volumetric reductions in ADHD and BMI and linked to inhibitory control. Our findings suggest that dopaminergic neurotransmission, partially through DARPP-32-dependent signaling and involving the putamen, is a key player underlying the genetic overlap between ADHD and obesity measures. Uncovering shared etiological factors underlying the frequently observed ADHD-obesity comorbidity may have important implications in terms of prevention and/or efficient treatment of these conditions.
Abstract
Natural plant populations often harbour substantial heritable variation in DNA methylation. However, a thorough understanding of the genetic and environmental drivers of this epigenetic variation requires large-scale and high-resolution data, which currently exist only for a few model species. Here, we studied 207 lines of the annual weed Thlaspi arvense (field pennycress), collected across a large latitudinal gradient in Europe and propagated in a common environment. By screening for variation in DNA sequence and DNA methylation using whole-genome (bisulfite) sequencing, we found significant epigenetic population structure across Europe. Average levels of DNA methylation were strongly context-dependent, with highest DNA methylation in CG context, particularly in transposable elements and in intergenic regions. Residual DNA methylation variation within all contexts was associated with genetic variants, which often co-localized with annotated methylation machinery genes but also with new candidates. Variation in DNA methylation was also significantly associated with climate of origin, with methylation levels being higher in warmer regions and lower in more variable climates. Finally, we used variance decomposition to assess genetic versus environmental associations with differentially methylation regions (DMRs). We found that while genetic variation was generally the strongest predictor of DMRs, the strength of environmental associations increased from CG to CHG and CHH, with climate-of-origin as the strongest predictor in about one third of the CHH DMRs. In summary, our data show that natural epigenetic variation in Thlaspi arvense is significantly associated with both DNA sequence and environment of origin, and that the relative importance of the two factors strongly depends on the sequence context of DNA methylation. T. arvense is an emerging biofuel and winter cover crop; our results may hence be relevant for breeding efforts and agricultural practices in the context of rapidly changing environmental conditions.
Author Summary: Variation within species is an important level of biodiversity, and it is key for future adaptation. Besides variation in DNA sequence, plants also harbour heritable variation in DNA methylation, and we want to understand the evolutionary significance of this epigenetic variation, in particular how much of it is under genetic control, and how much is associated with the environment. We addressed these questions in a high-resolution molecular analysis of 207 lines of the common plant field pennycress (Thlaspi arvense), which we collected across Europe, propagated under standardized conditions, and sequenced for their genetic and epigenetic variation. We found large geographic variation in DNA methylation, associated with both DNA sequence and climate of origin. Genetic variation was generally the stronger predictor of DNA methylation variation, but the strength of environmental association varied between different sequence contexts. Climate-of-origin was the strongest predictor in about one third of the differentially methylated regions in the CHH context, which suggests that epigenetic variation may play a role in the short-term climate adaptation of pennycress. As pennycress is currently being domesticated as a new biofuel and winter cover crop, our results may be relevant also for agriculture, particularly in changing environments.
Interferon-stimulated gene-15 (ISG15) is an interferon-induced protein with two ubiquitin-like (Ubl) domains linked by a short peptide chain, and the conjugated protein of the ISGylation system. Similar to ubiquitin and other Ubls, ISG15 is ligated to its target proteins with a series of E1, E2, and E3 enzymes known as Uba7, Ube2L6/UbcH8, and HERC5, respectively. Ube2L6/UbcH8 plays a literal central role in ISGylation, underscoring it as an important drug target for boosting innate antiviral immunity. Depending on the type of conjugated protein and the ultimate target protein, E2 enzymes have been shown to function as monomers, dimers, or both. UbcH8 has been crystalized in both monomeric and dimeric forms, but the functional state is unclear. Here, we used a combined approach of small-angle X-ray scattering (SAXS) and nuclear magnetic resonance (NMR) spectroscopy to characterize UbcH8′s oligomeric state in solution. SAXS revealed a dimeric UbcH8 structure that could be dissociated when fused with an N-terminal glutathione S-transferase molecule. NMR spectroscopy validated the presence of a concentration-dependent monomer-dimer equilibrium and suggested a backside dimerization interface. Chemical shift perturbation and peak intensity analysis further suggest dimer-induced conformational dynamics at ISG15 and E3 interfaces - providing hypotheses for the protein′s functional mechanisms. Our study highlights the power of combining NMR and SAXS techniques in providing structural information about proteins in solution.
Interferon-stimulated gene-15 (ISG15) is an interferon-induced protein with two ubiquitin-like (Ubl) domains linked by a short peptide chain, and the conjugated protein of the ISGylation system. Similar to ubiquitin and other Ubls, ISG15 is ligated to its target proteins with a series of E1, E2, and E3 enzymes known as Uba7, Ube2L6/UbcH8, and HERC5, respectively. Ube2L6/UbcH8 plays a literal central role in ISGylation, underscoring it as an important drug target for boosting innate antiviral immunity. Depending on the type of conjugated protein and the ultimate target protein, E2 enzymes have been shown to function as monomers, dimers, or both. UbcH8 has been crystalized in both monomeric and dimeric forms, but the functional state is unclear. Here, we used a combined approach of small-angle X-ray scattering (SAXS) and nuclear magnetic resonance (NMR) spectroscopy to characterize UbcH8′s oligomeric state in solution. SAXS revealed a dimeric UbcH8 structure that could be dissociated when fused with an N-terminal glutathione S-transferase molecule. NMR spectroscopy validated the presence of a concentration-dependent monomer-dimer equilibrium and suggested a backside dimerization interface. Chemical shift perturbation and peak intensity analysis further suggest dimer-induced conformational dynamics at ISG15 and E3 interfaces - providing hypotheses for the protein′s functional mechanisms. Our study highlights the power of combining NMR and SAXS techniques in providing structural information about proteins in solution.
Interferon-stimulated gene-15 (ISG15) is an interferon-induced protein with two ubiquitin-like (Ubl) domains linked by a short peptide chain, and the conjugated protein of the ISGylation system. Similar to ubiquitin and other Ubls, ISG15 is ligated to its target proteins with a series of E1, E2, and E3 enzymes known as Uba7, Ube2L6/UbcH8, and HERC5, respectively. Ube2L6/UbcH8 plays a literal central role in ISGylation, underscoring it as an important drug target for boosting innate antiviral immunity. Depending on the type of conjugated protein and the ultimate target protein, E2 enzymes have been shown to function as monomers, dimers, or both. UbcH8 has been crystalized in both monomeric and dimeric forms, but the functional state is unclear. Here, we used a combined approach of small-angle X-ray scattering (SAXS) and nuclear magnetic resonance (NMR) spectroscopy to characterize UbcH8’s oligomeric state in solution. SAXS revealed a dimeric UbcH8 structure that could be dissociated when fused with an N-terminal glutathione S-transferase molecule. NMR spectroscopy validated the presence of a concentration-dependent monomer-dimer equilibrium and suggested a backside dimerization interface. Chemical shift perturbation and peak intensity analysis further suggest dimer-induced conformational dynamics at ISG15 and E3 interfaces - providing hypotheses for the protein’s functional mechanisms. Our study highlights the power of combining NMR and SAXS techniques in providing structural information about proteins in solution.
Interferon-stimulated gene-15 (ISG15) is an interferon-induced protein with two ubiquitin-like (Ubl) domains linked by a short peptide chain, and the conjugated protein of the ISGylation system. Similar to ubiquitin and other Ubls, ISG15 is ligated to its target proteins with a series of E1, E2, and E3 enzymes known as Uba7, Ube2L6/UbcH8, and HERC5, respectively. Ube2L6/UbcH8 plays a literal central role in ISGylation, underscoring it as an important drug target for boosting innate antiviral immunity. Depending on the type of conjugated protein and the ultimate target protein, E2 enzymes have been shown to function as monomers, dimers, or both. UbcH8 has been crystalized in both monomeric and dimeric forms, but the functional state is unclear. Here, we used a combined approach of small-angle X-ray scattering (SAXS) and nuclear magnetic resonance (NMR) spectroscopy to characterize UbcH8’s oligomeric state in solution. SAXS revealed a dimeric UbcH8 structure that could be dissociated when fused with an N-terminal glutathione S-transferase molecule. NMR spectroscopy validated the presence of a concentration-dependent monomer-dimer equilibrium and suggested a backside dimerization interface. Chemical shift perturbation and peak intensity analysis further suggest dimer-induced conformational dynamics at ISG15 and E3 interfaces - providing hypotheses for the protein’s functional mechanisms. Our study highlights the power of combining NMR and SAXS techniques in providing structural information about proteins in solution.
Interferon-stimulated gene-15 (ISG15) is an interferon-induced protein with two ubiquitin-like (Ubl) domains linked by a short peptide chain, and the conjugated protein of the ISGylation system. Similar to ubiquitin and other Ubls, ISG15 is ligated to its target proteins with a series of E1, E2, and E3 enzymes known as Uba7, Ube2L6/UbcH8, and HERC5, respectively. Ube2L6/UbcH8 plays a literal central role in ISGylation, underscoring it as an important drug target for boosting innate antiviral immunity. Depending on the type of conjugated protein and the ultimate target protein, E2 enzymes have been shown to function as monomers, dimers, or both. UbcH8 has been crystalized in both monomeric and dimeric forms, but the functional state is unclear. Here, we used a combined approach of small-angle X-ray scattering (SAXS) and nuclear magnetic resonance (NMR) spectroscopy to characterize UbcH8’s oligomeric state in solution. SAXS revealed a dimeric UbcH8 structure that could be dissociated when fused with an N-terminal glutathione S-transferase molecule. NMR spectroscopy validated the presence of a concentration-dependent monomer-dimer equilibrium and suggested a backside dimerization interface. Chemical shift perturbation and peak intensity analysis further suggest dimer-induced conformational dynamics at ISG15 and E3 interfaces - providing hypotheses for the protein’s functional mechanisms. Our study highlights the power of combining NMR and SAXS techniques in providing structural information about proteins in solution.
Interferon-stimulated gene-15 (ISG15) is an interferon-induced protein with two ubiquitin-like (Ubl) domains linked by a short peptide chain, and the conjugated protein of the ISGylation system. Similar to ubiquitin and other Ubls, ISG15 is ligated to its target proteins with a series of E1, E2, and E3 enzymes known as Uba7, Ube2L6/UbcH8, and HERC5, respectively. Ube2L6/UbcH8 plays a literal central role in ISGylation, underscoring it as an important drug target for boosting innate antiviral immunity. Depending on the type of conjugated protein and the ultimate target protein, E2 enzymes have been shown to function as monomers, dimers, or both. UbcH8 has been crystalized in both monomeric and dimeric forms, but the functional state is unclear. Here, we used a combined approach of small-angle X-ray scattering (SAXS) and nuclear magnetic resonance (NMR) spectroscopy to characterize UbcH8’s oligomeric state in solution. SAXS revealed a dimeric UbcH8 structure that could be dissociated when fused with an N-terminal glutathione S-transferase molecule. NMR spectroscopy validated the presence of a concentration-dependent monomer-dimer equilibrium and suggested a backside dimerization interface. Chemical shift perturbation and peak intensity analysis further suggest dimer-induced conformational dynamics at ISG15 and E3 interfaces - providing hypotheses for the protein’s functional mechanisms. Our study highlights the power of combining NMR and SAXS techniques in providing structural information about proteins in solution.
Measurements of the pT-dependent flow vector fluctuations in Pb-Pb collisions at sNN−−−√=5.02 TeV using azimuthal correlations with the ALICE experiment at the LHC are presented. A four-particle correlation approach [1] is used to quantify the effects of flow angle and magnitude fluctuations separately. This paper extends previous studies to additional centrality intervals and provides measurements of the pT-dependent flow vector fluctuations at sNN−−−√=5.02 TeV with two-particle correlations. Significant pT-dependent fluctuations of the V⃗ 2 flow vector in Pb-Pb collisions are found across different centrality ranges, with the largest fluctuations of up to ∼15% being present in the 5% most central collisions. In parallel, no evidence of significant pT-dependent fluctuations of V⃗ 3 or V⃗ 4 is found. Additionally, evidence of flow angle and magnitude fluctuations is observed with more than 5σ significance in central collisions. These observations in Pb-Pb collisions indicate where the classical picture of hydrodynamic modeling with a common symmetry plane breaks down. This has implications for hard probes at high pT, which might be biased by pT-dependent flow angle fluctuations of at least 23% in central collisions. Given the presented results, existing theoretical models should be re-examined to improve our understanding of initial conditions, quark--gluon plasma (QGP) properties, and the dynamic evolution of the created system.
The intense photon fluxes from relativistic nuclei provide an opportunity to study photonuclear interactions in ultraperipheral collisions. The measurement of coherently photoproduced π+π−π+π− final states in ultraperipheral Pb-Pb collisions at sNN−−−√=5.02 TeV is presented for the first time. The cross section, dσ/dy, times the branching ratio (ρ→π+π+π−π−) is found to be 47.8±2.3 (stat.)±7.7 (syst.) mb in the rapidity interval |y|<0.5. The invariant mass distribution is not well described with a single Breit-Wigner resonance. The production of two interfering resonances, ρ(1450) and ρ(1700), provides a good description of the data. The values of the masses (m) and widths (Γ) of the resonances extracted from the fit are m1=1385±14 (stat.)±3 (syst.) MeV/c2, Γ1=431±36 (stat.)±82 (syst.) MeV/c2, m2=1663±13 (stat.)±22 (syst.) MeV/c2 and Γ2=357±31 (stat.)±49 (syst.) MeV/c2, respectively. The measured cross sections times the branching ratios are compared to recent theoretical predictions.
Measurement of beauty-quark production in pp collisions at √s = 13 TeV via non-prompt D mesons
(2024)
The pT-differential production cross sections of non-prompt D0, D+, and D+s mesons originating from beauty-hadron decays are measured in proton−proton collisions at a centre-of-mass energy s√ of 13 TeV. The measurements are performed at midrapidity, |y|<0.5, with the data sample collected by ALICE from 2016 to 2018. The results are in agreement with predictions from several perturbative QCD calculations. The fragmentation fraction of beauty quarks to strange mesons divided by the one to non-strange mesons, fs/(fu+fd), is found to be 0.114±0.016 (stat.)±0.006 (syst.)±0.003 (BR)±0.003 (extrap.). This value is compatible with previous measurements at lower centre-of-mass energies and in different collision systems in agreement with the assumption of universality of fragmentation functions. In addition, the dependence of the non-prompt D meson production on the centre-of-mass energy is investigated by comparing the results obtained at s√=5.02 and 13 TeV, showing a hardening of the non-prompt D-meson pT-differential production cross section at higher s√. Finally, the bb¯¯¯ production cross section per unit of rapidity at midrapidity is calculated from the non-prompt D0, D+, D+s, and Λ+c hadron measurements, obtaining dσ/dy=75.2±3.2 (stat.)±5.2 (syst.)+12.3−3.2 (extrap.) μb.
The two-particle momentum correlation functions between charm mesons (D∗± and D±) and charged light-flavor mesons (π± and K±) in all charge-combinations are measured for the first time by the ALICE Collaboration in high-multiplicity proton–proton collisions at a center-of-mass energy of √s = 13 TeV. For DK and D∗K pairs, the experimental results are in agreement with theoretical predictions of the residual strong interaction based on quantum chromodynamics calculations on the lattice and chiral effective field theory. In the case of Dπ and D∗π pairs, tension between the calculations including strong interactions and the measurement is observed. For all particle pairs, the data can be adequately described by Coulomb interaction only, indicating a shallow interaction between charm and light-flavor mesons. Finally, the scattering lengths governing the residual strong interaction of the Dπ and D∗π systems are determined by fitting the experimental correlation functions with a model that employs a Gaussian potential. The extracted values are small and compatible with zero.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3’ untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
Key Points:
* Deep profiling identifies novel targets of miR-181 associated with global gene regulation.
* miR-181 MREs in repeat elements in the coding sequence act through translational inhibition.
* High-resolution analysis reveals an alternative seed match in functional MREs.
Studying the neural basis of human dynamic visual perception requires extensive experimental data to evaluate the large swathes of functionally diverse brain neural networks driven by perceiving visual events. Here, we introduce the BOLD Moments Dataset (BMD), a repository of whole-brain fMRI responses to over 1,000 short (3s) naturalistic video clips of visual events across ten human subjects. We use the videos’ extensive metadata to show how the brain represents word- and sentence-level descriptions of visual events and identify correlates of video memorability scores extending into the parietal cortex. Furthermore, we reveal a match in hierarchical processing between cortical regions of interest and video-computable deep neural networks, and we showcase that BMD successfully captures temporal dynamics of visual events at second resolution. With its rich metadata, BMD offers new perspectives and accelerates research on the human brain basis of visual event perception.
Highlights
• Family structure transitions decrease academic school track attendance among children of less educated parents.
• Children of highly educated fathers in single-mother families also have lower outcomes.
• Reduced income and increased exposure to poverty are relevant mediators.
• There is no cumulative disadvantage linked to a further transition to a stepfamily.
• Previous parental separation does not affect educational outcomes for children residing with a highly educated stepfather.
Abstract
Recent research has documented that the effect of parental separation on children’s educational outcomes depends on socioeconomic background. Yet, parental separation could lead to a stable single-parent family or to a further transition to a stepfamily. Little is known about how the effect of family structure transitions on educational outcomes depends on the education of parents and stepparents, and there has been limited empirical research into the mechanisms that explain heterogeneity in the effects of family transitions. Using longitudinal data from the German Socio-Economic Panel and models with entropy balancing and sibling fixed effects, I explore the heterogeneous effects of family transitions during early and middle childhood on academic secondary school track attendance, grades and aspirations. I find that family transitions only reduce the academic school track attendance among children of less educated parents living in stepfamilies or with a single mother after parental separation, and among children of highly educated fathers living in single-mother families. The mechanisms that partly explain these effects relate to reduced income and exposure to poverty after parental separation. The findings underscore the importance of considering the stepparent's educational level, indicating that the adverse consequences of parental separation on educational outcomes are mitigated when a highly educated stepfather becomes part of the family. Overall, these findings align more closely with the resource perspective than the family stability perspective.