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he first measurement of 3ΛH and 3Λ¯¯¯¯H¯¯¯¯ differential production with respect to transverse momentum and centrality in Pb−Pb collisions at sNN−−−√=5.02~TeV is presented. The 3ΛH has been reconstructed via its two-charged-body decay channel, i.e., 3ΛH→3He+π−. A Blast-Wave model fit of the pT-differential spectra of all nuclear species measured by the ALICE collaboration suggests that the 3ΛH kinetic freeze-out surface is consistent with that of other nuclei. The ratio between the integrated yields of 3ΛH and 3He is compared to predictions from the statistical hadronisation model and the coalescence model, with the latter being favoured by the presented measurements.
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.
Previous studies towards reduced oxygen availability have mostly focused on changes in total mRNA expression, neglecting underlying transcriptional and post-transcriptional events. Therefore, we generated a comprehensive overview of hypoxia-induced changes in total mRNA expression, global de novo transcription, and mRNA stability in monocytic THP-1 cells. Since hypoxic episodes often persist for prolonged periods, we further compared the adaptation to acute and chronic hypoxia. While total mRNA changes correlated well with enhanced transcription during short-term hypoxia, mRNA destabilization gained importance under chronic conditions. Reduced mRNA stability not only added to a compensatory attenuation of immune responses, but also, most notably, to the reduction in nuclear-encoded mRNAs associated with various mitochondrial functions. These changes may prevent the futile production of new mitochondria under conditions where mitochondria cannot exert their full metabolic function and are indeed actively removed by mitophagy. The post-transcriptional mode of regulation might further allow for the rapid recovery of mitochondrial capacities upon reoxygenation. Our results provide a comprehensive resource of functional mRNA expression dynamics and underlying transcriptional and post-transcriptional regulatory principles during the adaptation to hypoxia. Furthermore, we uncover that RNA stability regulation controls mitochondrial functions in the context of hypoxia.
An experiment addressing electron capture (EC) decay of hydrogen-like 142Pm60+ions has been conducted at the experimental storage ring (ESR) at GSI. The decay appears to be purely exponential and no modulations were observed. Decay times for about 9000 individual EC decays have been measured by applying the single-ion decay spectroscopy method. Both visually and automatically analysed data can be described by a single exponential decay with decay constants of 0.0126(7)s−1 for automatic analysis and 0.0141(7)s−1 for manual analysis. If a modulation superimposed on the exponential decay curve is assumed, the best fit gives a modulation amplitude of merely 0.019(15), which is compatible with zero and by 4.9 standard deviations smaller than in the original observation which had an amplitude of 0.23(4).
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 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.