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In this talk we presented a novel technique, based on Deep Learning, to determine the impact parameter of nuclear collisions at the CBM experiment. PointNet based Deep Learning models are trained on UrQMD followed by CBMRoot simulations of Au+Au collisions at 10 AGeV to reconstruct the impact parameter of collisions from raw experimental data such as hits of the particles in the detector planes, tracks reconstructed from the hits or their combinations. The PointNet models can perform fast, accurate, event-by-event impact parameter determination in heavy ion collision experiments. They are shown to outperform a simple model which maps the track multiplicity to the impact parameter. While conventional methods for centrality classification merely provide an expected impact parameter distribution for a given centrality class, the PointNet models predict the impact parameter from 2–14 fm on an event-by-event basis with a mean error of −0.33 to 0.22 fm.
Cell fate clusters in ICM organoids arise from cell fate heredity and division: a modelling approach
(2020)
During the mammalian preimplantation phase, cells undergo two subsequent cell fate decisions. During the first decision, the trophectoderm and the inner cell mass are formed. Subsequently, the inner cell mass segregates into the epiblast and the primitive endoderm. Inner cell mass organoids represent an experimental model system, mimicking the second cell fate decision. It has been shown that cells of the same fate tend to cluster stronger than expected for random cell fate decisions. Three major processes are hypothesised to contribute to the cell fate arrangements: (1) chemical signalling; (2) cell sorting; and (3) cell proliferation. In order to quantify the influence of cell proliferation on the observed cell lineage type clustering, we developed an agent-based model accounting for mechanical cell–cell interaction, i.e. adhesion and repulsion, cell division, stochastic cell fate decision and cell fate heredity. The model supports the hypothesis that initial cell fate acquisition is a stochastically driven process, taking place in the early development of inner cell mass organoids. Further, we show that the observed neighbourhood structures can emerge solely due to cell fate heredity during cell division.
Reprogramming of tomato leaf metabolome by the activity of heat stress transcription factor HsfB1
(2020)
Plants respond to high temperatures with global changes of the transcriptome, proteome, and metabolome. Heat stress transcription factors (Hsfs) are the core regulators of transcriptome responses as they control the reprogramming of expression of hundreds of genes. The thermotolerance-related function of Hsfs is mainly based on the regulation of many heat shock proteins (HSPs). Instead, the Hsf-dependent reprogramming of metabolic pathways and their contribution to thermotolerance are not well described. In tomato (Solanum lycopersicum), manipulation of HsfB1, either by suppression or overexpression (OE) leads to enhanced thermotolerance and coincides with distinct profile of metabolic routes based on a metabolome profiling of wild-type (WT) and HsfB1 transgenic plants. Leaves of HsfB1 knock-down plants show an accumulation of metabolites with a positive effect on thermotolerance such as the sugars sucrose and glucose and the polyamine putrescine. OE of HsfB1 leads to the accumulation of products of the phenylpropanoid and flavonoid pathways, including several caffeoyl quinic acid isomers. The latter is due to the enhanced transcription of genes coding key enzymes in both pathways, in some cases in both non-stressed and stressed plants. Our results show that beyond the control of the expression of Hsfs and HSPs, HsfB1 has a wider activity range by regulating important metabolic pathways providing an important link between stress response and physiological tomato development.
Background: Cognitive dysfunctions represent a core feature of schizophrenia and a predictor for clinical outcomes. One possible mechanism for cognitive impairments could involve an impairment in the experience-dependent modifications of cortical networks.
Methods: To address this issue, we employed magnetoencephalography (MEG) during a visual priming paradigm in a sample of chronic patients with schizophrenia (n = 14), and in a group of healthy controls (n = 14). We obtained MEG-recordings during the presentation of visual stimuli that were presented three times either consecutively or with intervening stimuli. MEG-data were analyzed for event-related fields as well as spectral power in the 1–200 Hz range to examine repetition suppression and repetition enhancement. We defined regions of interest in occipital and thalamic regions and obtained virtual-channel data.
Results: Behavioral priming did not differ between groups. However, patients with schizophrenia showed prominently reduced oscillatory response to novel stimuli in the gamma-frequency band as well as significantly reduced repetition suppression of gamma-band activity and reduced repetition enhancement of beta-band power in occipital cortex to both consecutive repetitions as well as repetitions with intervening stimuli. Moreover, schizophrenia patients were characterized by a significant deficit in suppression of the C1m component in occipital cortex and thalamus as well as of the late positive component (LPC) in occipital cortex.
Conclusions: These data provide novel evidence for impaired repetition suppression in cortical and subcortical circuits in schizophrenia. Although behavioral priming was preserved, patients with schizophrenia showed deficits in repetition suppression as well as repetition enhancement in thalamic and occipital regions, suggesting that experience-dependent modification of neural circuits is impaired in the disorder.
Nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) is a subtype of Hodgkin lymphoma with a preserved B‐cell phenotype and follicular T helper (TFH) cells rosetting around the tumor cells, the lymphocyte‐predominant (LP) cells. As we recently described reactivity of the B‐cell receptors of LP cells of some NLPHL cases with Moraxella spp. proteins, we hypothesized that LP cells could present peptides to rosetting T cells in a major histocompatibility complex class II (MHCII)‐bound manner. Rosetting PD1+ T cells were present in the majority of NLPHL cases, both in typical (17/20) and variant patterns (16/19). In most cases, T‐cell rosettes were CD69+ (typical NLPHL, 17/20; NLPHL variant, 14/19). Furthermore, both MHCII alpha and beta chains were expressed in the LP cells in 23/39 NLPHL. Proximity ligation assay and confocal laser imaging demonstrated interaction of the MHCII beta chain expressed by the LP cells and the T‐cell receptor alpha chain expressed by rosetting T cells. We thus conclude that rosetting T cells in NLPHL express markers that are encountered after antigenic exposure, that MHCII is expressed by the LP cells, and that LP cells interact with rosetting T cells in an immunological synapse in a subset of cases. As they likely receive growth stimulatory signals in this way, blockade of this interaction, for example, by PD1‐directed checkpoint inhibitors, could be a treatment option in a subset of cases in the future.
Volatility clustering and fat tails are prominently observed in financial markets. Here, we analyze the underlying mechanisms of three agent-based models explaining these stylized facts in terms of market instabilities and compare them on empirical grounds. To this end, we first develop a general framework for detecting tail events in stock markets. In particular, we introduce Hawkes processes to automatically identify and date onsets of market turmoils which result in increased volatility. Second, we introduce three different indicators to predict those onsets. Each of the three indicators is derived from and tailored to one of the models, namely quantifying information content, critical slowing down or market risk perception. Finally, we apply our indicators to simulated and real market data. We find that all indicators reliably predict market events on simulated data and clearly distinguish the different models. In contrast, a systematic comparison on the stocks of the Forbes 500 companies shows a markedly lower performance. Overall, predicting the onset of market turmoils appears difficult, yet, over very short time horizons high or rising volatility exhibits some predictive power.
Neuraminidase inhibitors in influenza treatment and prevention – is it time to call it a day?
(2018)
Stockpiling neuraminidase inhibitors (NAIs) such as oseltamivir and zanamivir is part of a global effort to be prepared for an influenza pandemic. However, the contribution of NAIs for the treatment and prevention of influenza and its complications is largely debatable due to constraints in the ability to control for confounders and to explore unobserved areas of the drug effects. For this study, we used a mathematical model of influenza infection which allowed transparent analyses. The model recreated the oseltamivir effects and indicated that: (i) the efficacy was limited by design, (ii) a 99% efficacy could be achieved by using high drug doses (however, taking high doses of drug 48 h post-infection could only yield a maximum of 1.6-day reduction in the time to symptom alleviation), and (iii) contributions of oseltamivir to epidemic control could be high, but were observed only in fragile settings. In a typical influenza infection, NAIs’ efficacy is inherently not high, and even if their efficacy is improved, the effect can be negligible in practice.
We construct a new equation of state for the baryonic matter under an intense magnetic field within the framework of covariant density functional theory. The composition of matter includes hyperons as well as Δ-resonances. The extension of the nucleonic functional to the hypernuclear sector is constrained by the experimental data on Λ and Ξ-hypernuclei. We find that the equation of state stiffens with the inclusion of the magnetic field, which increases the maximum mass of neutron star compared to the non-magnetic case. In addition, the strangeness fraction in the matter is enhanced. Several observables, like the Dirac effective mass, particle abundances, etc. show typical oscillatory behavior as a function of the magnetic field and/or density which is traced back to the occupation pattern of Landau levels.
Glia, the helper cells of the brain, are essential in maintaining neural resilience across time and varying challenges: By reacting to changes in neuronal health glia carefully balance repair or disposal of injured neurons. Malfunction of these interactions is implicated in many neurodegenerative diseases. We present a reductionist model that mimics repair-or-dispose decisions to generate a hypothesis for the cause of disease onset. The model assumes four tissue states: healthy and challenged tissue, primed tissue at risk of acute damage propagation, and chronic neurodegeneration. We discuss analogies to progression stages observed in the most common neurodegenerative conditions and to experimental observations of cellular signaling pathways of glia-neuron crosstalk. The model suggests that the onset of neurodegeneration can result as a compromise between two conflicting goals: short-term resilience to stressors versus long-term prevention of tissue damage.
We derive the relation between cumulants of a conserved charge measured in a subvolume of a thermal system and the corresponding grand-canonical susceptibilities, taking into account exact global conservation of that charge. The derivation is presented for an arbitrary equation of state, with the assumption that the subvolume is sufficiently large to be close to the thermodynamic limit. Our framework – the subensemble acceptance method (SAM) – quantifies the effect of global conservation laws and is an important step toward a direct comparison between cumulants of conserved charges measured in central heavy ion collisions and theoretical calculations of grand-canonical susceptibilities, such as lattice QCD. As an example, we apply our formalism to net-baryon fluctuations at vanishing baryon chemical potentials as encountered in collisions at the LHC and RHIC.