Miracle-dz/UniFAR-FTUs huggingface dataset:
Transcriptome analysis of Edwardsiella piscicida during intracellular infection reveals excludons are involved with the activation of a mitochondrion-like energy generation program

ABSTRACT Phylogenetic evidence suggests a shared ancestry between mitochondria and modern Proteobacteria, a phylum including several genera of intracellular pathogens. Studying these diverse pathogens, particularly during intracellular infection of their hosts, can reveal characteristics potentially representative of the mitochondrial-Proteobacterial ancestor by identifying traits shared with mitochondria. While transcriptomic approaches can provide global insights into intracellular acclimatization by pathogens, they are often limited by excess host RNAs in extracts. Here, we developed a method employing magnetic nanoparticles to enrich RNA from an intracellular Gammaproteobacterium, Edwardsiella piscicida, within zebrafish, Danio rerio, fin fibroblasts, enabling comprehensive exploration of the bacterial transcriptome. Our findings revealed that the intracellular E. piscicida transcriptome reflects a mitochondrion-like energy generation program characterized by the suppression of glycolysis and sugar transport, coupled with upregulation of the tricarboxylic acid (TCA) cycle and alternative import of simple organic acids that directly flux into TCA cycle intermediates or electron transport chain donors. Additionally, genes predicted to be members of excludons, loci of gene pairs antagonistically co-regulated by overlapping antisense transcription, are significantly enriched in the set of all genes with perturbed sense and antisense transcription, suggesting a general but important involvement of excludons with intracellular acclimatization. Notably, genes involved with the activation of the mitochondrion-like energy generation program, specifically with metabolite import and glycolysis, are also members of predicted excludons. Other intracellular Proteobacterial pathogens appear to employ a similar mitochondrion-like energy generation program, suggesting a potentially conserved mechanism for optimized energy acquisition from hosts centered around the TCA cycle. IMPORTANCE Phylogenetic evidence suggests that mitochondria and Proteobacteria, a phylum encompassing various intracellular pathogens, share a common ancestral lineage. In this study, we developed a novel method employing magnetic nanoparticles to explore the transcriptome of an aquatic Gammaproteobacterium, Edwardsiella piscicida, during intracellular infection of host cells. We show that the strategy E. piscicida uses to generate energy strikingly mirrors the function of mitochondria—energy generators devoid of glycolytic processes. Notably, several implicated genes are members of excludons—gene pairs antagonistically co-regulated by overlapping antisense transcription. Other intracellular Proteobacterial pathogens appear to adopt a similar mitochondrion-like energy generation program, indicating a possibly conserved strategy for optimized energy acquisition from hosts centered around the tricarboxylic acid cycle.
Further delineation of Wiedemann‐Rautenstrauch syndrome linked with POLR3A

Abstract Wiedemann‐Rautenstrauch Syndrome (WRS; MIM 264090) is an extremely rare and highly heterogeneous syndrome that is inherited in a recessive fashion. The patients have hallmark features such as prenatal and postnatal growth retardation, short stature, a progeroid appearance, hypotonia, facial dysmorphology, hypomyelination leukodystrophy, and mental impairment. Biallelic disease‐causing variants in the RNA polymerase III subunit A (POLR3A) have been associated with WRS. Here, we report the first identified cases of WRS syndrome with novel phenotypes in three consanguineous families (two Omani and one Saudi) characterized by biallelic variants in POLR3A. Using whole‐exome sequencing, we identified one novel homozygous missense variant (NM_007055: c.2456C>T; p. Pro819Leu) in two Omani families and one novel homozygous variant (c.1895G>T; p Cys632Phe) in Saudi family that segregates with the disease in the POLR3A gene. In silico homology modeling of wild‐type and mutated proteins revealed a substantial change in the structure and stability of both proteins, demonstrating a possible effect on function. By identifying the homozygous variants in the exon 14 and 18 of the POLR3A gene, our findings will contribute to a better understanding of the phenotype‐genotype relationship and molecular etiology of WRS syndrome.
Hippocampome.org 2.0 is a knowledge base enabling data-driven spiking neural network simulations of rodent hippocampal circuits

Hippocampome.org is a mature open-access knowledge base of the rodent hippocampal formation focusing on neuron types and their properties. Previously, Hippocampome.org v1.0 established a foundational classification system identifying 122 hippocampal neuron types based on their axonal and dendritic morphologies, main neurotransmitter, membrane biophysics, and molecular expression (Wheeler et al., 2015). Releases v1.1 through v1.12 furthered the aggregation of literature-mined data, including among others neuron counts, spiking patterns, synaptic physiology, in vivo firing phases, and connection probabilities. Those additional properties increased the online information content of this public resource over 100-fold, enabling numerous independent discoveries by the scientific community. Hippocampome.org v2.0, introduced here, besides incorporating over 50 new neuron types, now recenters its focus on extending the functionality to build real-scale, biologically detailed, data-driven computational simulations. In all cases, the freely downloadable model parameters are directly linked to the specific peer-reviewed empirical evidence from which they were derived. Possible research applications include quantitative, multiscale analyses of circuit connectivity and spiking neural network simulations of activity dynamics. These advances can help generate precise, experimentally testable hypotheses and shed light on the neural mechanisms underlying associative memory and spatial navigation.
Utilizing Human-Induced Pluripotent Stem Cells to Study Cardiac Electroporation Pulsed-Field Ablation

BACKGROUND: Electroporation is a promising nonthermal ablation method for cardiac arrhythmia treatment. Although initial clinical studies found electroporation pulsed-field ablation (PFA) both safe and efficacious, there are significant knowledge gaps concerning the mechanistic nature and electrophysiological consequences of cardiomyocyte electroporation, contributed by the paucity of suitable human in vitro models. Here, we aimed to establish and characterize a functional in vitro model based on human-induced pluripotent stem cells (hiPSCs)-derived cardiac tissue, and to study the fundamentals of cardiac PFA. METHODS: hiPSC-derived cardiomyocytes were seeded as circular cell sheets and subjected to different PFA protocols. Detailed optical mapping, cellular, and molecular characterizations were performed to study PFA mechanisms and electrophysiological outcomes. RESULTS: PFA generated electrically silenced lesions within the hiPSC-derived cardiac circular cell sheets, resulting in areas of conduction block. Both reversible and irreversible electroporation components were identified. Significant electroporation reversibility was documented within 5 to 15-minutes post-PFA. Irreversibly electroporated regions persisted at 24-hours post-PFA. Per single pulse, high-frequency PFA was less efficacious than standard (monophasic) PFA, whereas increasing pulse-number augmented lesion size and diminished reversible electroporation. PFA augmentation could also be achieved by increasing extracellular Ca2+ levels. Flow-cytometry experiments revealed that regulated cell death played an important role following PFA. Assessing for PFA antiarrhythmic properties, sustainable lines of conduction block could be generated using PFA, which could either terminate or isolate arrhythmic activity in the hiPSC-derived cardiac circular cell sheets. CONCLUSIONS: Cardiac electroporation may be studied using hiPSC-derived cardiac tissue, providing novel insights into PFA temporal and electrophysiological characteristics, facilitating electroporation protocol optimization, screening for potential PFA-sensitizers, and investigating the mechanistic nature of PFA antiarrhythmic properties.
The potential role of sucrose transport gene expression in the photosynthetic and yield response of rice cultivars to future CO2 concentration

The metabolic basis for observed differences in the yield response of rice to projected carbon dioxide concentrations (CO2) is unclear. In this study, three rice cultivars, differing in their yield response to elevated CO2, were grown under ambient and elevated CO2 conditions, using the free‐air CO2 enrichment technology. Flag leaves of rice were used to determine (1) if manipulative increases in sink strength decreased the soluble sucrose concentration for the ‘weak’ responders and (2), whether the genetic expression of sucrose transporters OsSUT1 and OsSUT2 was associated with an accumulation of soluble sugars and the maintenance of photosynthetic capacity. For the cultivars that showed a weak response to additional CO2, photosynthetic capacity declined under elevated CO2 and was associated with an accumulation of soluble sugars. For these cultivars, increasing sink relative to source strength did not increase photosynthesis and no change in OsSUT1 or OsSUT2 expression was observed. In contrast, the ‘strong’ response cultivar did not show an increase in soluble sugars or a decline in photosynthesis but demonstrated significant increases in OsSUT1 and OsSUT2 expression at elevated CO2. Overall, these data suggest that the expression of the sucrose transport genes OsSUT1 and OsSUT2 may be associated with the maintenance of photosynthetic capacity of the flag leaf during grain fill; and, potentially, greater yield response of rice as atmospheric CO2 increases.
A Cross-Sectional and Longitudinal Integrated Study on Brain Functional Changes in a Neuropathic Pain Rat Model

Human and animal imaging studies demonstrated that chronic pain profoundly alters the structure and the functionality of several brain regions and even causes mental dysfunctions such as depression and anxiety disorders. In this article, we conducted a multimodal study cross-sectionally and longitudinally, to evaluate how neuropathic pain affects the brain. Using the spared nerve injury (SNI) model which promotes long-lasting mechanical allodynia, results showed that neuropathic pain deeply modified the intrinsic organization of the brain functional network 2 weeks after injury. There are significant changes in the activity of the left thalamus (Th_L) and left olfactory bulb (OB_L) brain regions after SNI, as evidenced by both the blood oxygen level-dependent (BOLD) signal and c-Fos expression. Importantly, these changes were closely related to mechanical pain behavior of rats. However, it is worth noting that after morphine administration for analgesia, only the increased activity in the TH region is reversed, while the decreased activity in the OB region becomes more prominent. Functional connectivity (FC) and c-Fos correlation analysis further showed these two regions of interest (ROIs) exhibit different FC patterns with other brain regions. Our study comprehensively revealed the adaptive changes of brain neural networks induced by nerve injury in both cross-sectional and longitudinal dimensions and emphasized the abnormal activity and FC of Th_L and OB_L in the pathological condition. It provides reliable assistance in exploring the intricate mechanisms of diseases.
Épreuves de validation dans l'analyse de structures génétiques multivariées : comment tester l'équilibre panmictique ?

This article deals with the methods used in population genetics forthe study of multilocus interindividual polymorphism. After a short description of the data structure and of the problems of significance linked with the interpretation of the outputs yielded by the most commonly used multivariate techniques, we explore several validation procedures. Affording a realistic nul hypothesis (the panmictic equilibrium), we proprose a sample reuse-method coupled with validation tests based on the study of statistical distribution of various inter-table indexes. Following a comparaison of the various approaches on a real cases, we evaluate their merits and conclude on their limits. 48 E. MATHIEU, M. AUTEM, M. ROUX. F. BONHOMME
Dynamic modeling of industrial wastewater treatment plant data

While much is understood about the basic mechanisms of activated sludge system re sponse to environmental changes, changing waste characteristics, and operating modifica tions, reducing the theory to practice to predict performance accurately or understand tradeoffs in full-scale units is usually difficult. A his torical data record containing information about system operation is maintained by most treatment facilities. If properly analyzed, these data could provide information about the practical operating efficiency of the plant and techniques to improve performance. However, the data collected by most treatment plants usually are not analyzed meaningfully. Ex tracting useful information from raw waste water treatment plant data is usually an un pleasant task because simply collecting and organizing the data are very difficult. The task becomes almost unmanageable when the data sets become large. The effort required to analyze daily data may be reduced by com puting weekly or monthly averages that can be used to monitor and report plant performance. The daily observations are usually plotted in time sequence to look for trends and examine variability, and only cursory attempts are made to look for correlations between variables in the data record.
Lipids in Health and Disease the Influence of Walking Performed Immediately before Meals with Moderate Fat Content on Postprandial Lipemia

Background: Postprandial lipemia is an independent risk factor for coronary heart disease. Single bouts of moderate exercise may lower this risk, but the minimum duration of moderate intensity exercise that still lowers postprandial lipemia is not known. We, therefore, performed a dose-response study with a normal, daily life setting, to identify the minimum duration of moderate intensity walking that lowers postprandial lipemia in sedentary, healthy young men.
Therapy for Specific Problems Therapy for Specific Problems : Youth Tobacco Cessation

There are declines with age in speed of processing, working memory, inhibitory function, and long-term memory, as well as decreases in brain structure size and white matter integrity. In the face of these decreases, functional imaging studies have demonstrated, somewhat surprisingly, reliable increases in prefrontal activation. To account for these joint phenomena, we propose the scaffolding theory of aging and cognition (STAC). STAC provides an integrative view of the aging mind, suggesting that pervasive increased frontal activation with age is a marker of an adaptive brain that engages in compensatory scaffolding in response to the challenges posed by declining neural structures and function. Scaffolding is a normal process present across the lifespan that involves use and development of complementary, alternative neural circuits to achieve a particular cognitive goal. Scaffolding is protective of cognitive function in the aging brain, and available evidence suggests that the ability to use this mechanism is strengthened by cognitive engagement, exercise, and low levels of default network engagement. 173 A nn u. R ev . P sy ch ol . 2 00 9. 60 :1 73 -1 96 . D ow nl oa de d fr om w w w . a nn ua lr ev ie w s. or g by U ni ve rs ity o f T ex as D al la s on 0 8/ 24 /1 1. F or p er so na l u se o nl y. ANRV364-PS60-07 ARI 24 November 2008 18:45 fMRI: functional magnetic resonance imaging PET: positron emission tomography
The Monte Carlo Computational Summit -- October 25&26, 2023 -- Notre Dame, Indiana, USA

The Monte Carlo Computational Summit was held on the campus of the University of Notre Dame in South Bend, Indiana, USA on 25--26 October 2023. The goals of the summit were to discuss algorithmic and software alterations required for successfully porting respective code bases to exascale-class computing hardware, compare software engineering techniques used by various code teams, and consider the adoption of industry-standard benchmark problems to better facilitate code-to-code performance comparisons. A large portion of the meeting included candid discussions of direct experiences with approaches that have and have not worked. Participants reported that identifying and implementing suitable Monte Carlo algorithms for GPUs continues to be a sticking point. They also report significant difficulty porting existing algorithms between GPU APIs (specifically Nvidia CUDA to AMD ROCm). To better compare code-to-code performance, participants decided to design a C5G7-like benchmark problem with a defined figure of merit, with the expectation of adding more benchmarks in the future. Problem specifications and results will eventually be hosted in a public repository and will be open to submissions by all Monte Carlo transport codes capable of running the benchmark problem. The participants also identified the need to explore the intermediate and long-term future of the Monte Carlo neutron transport community and how best to modernize and contextualize Monte Carlo as a useful tool in modern industry. Overall the summit was considered to be a success by the organizers and participants, and the group shared a strong desire for future, potentially larger, Monte Carlo summits.
Conservative and Risk-Aware Offline Multi-Agent Reinforcement Learning for Digital Twins

Digital twin (DT) platforms are increasingly regarded as a promising technology for controlling, optimizing, and monitoring complex engineering systems such as next-generation wireless networks. An important challenge in adopting DT solutions is their reliance on data collected offline, lacking direct access to the physical environment. This limitation is particularly severe in multi-agent systems, for which conventional multi-agent reinforcement (MARL) requires online interactions with the environment. A direct application of online MARL schemes to an offline setting would generally fail due to the epistemic uncertainty entailed by the limited availability of data. In this work, we propose an offline MARL scheme for DT-based wireless networks that integrates distributional RL and conservative Q-learning to address the environment's inherent aleatoric uncertainty and the epistemic uncertainty arising from limited data. To further exploit the offline data, we adapt the proposed scheme to the centralized training decentralized execution framework, allowing joint training of the agents' policies. The proposed MARL scheme, referred to as multi-agent conservative quantile regression (MA-CQR) addresses general risk-sensitive design criteria and is applied to the trajectory planning problem in drone networks, showcasing its advantages.
Tandem Transformers for Inference Efficient LLMs

The autoregressive nature of conventional large language models (LLMs) inherently limits inference speed, as tokens are generated sequentially. While speculative and parallel decoding techniques attempt to mitigate this, they face limitations: either relying on less accurate smaller models for generation or failing to fully leverage the base LLM's representations. We introduce a novel architecture, Tandem transformers, to address these issues. This architecture uniquely combines (1) a small autoregressive model and (2) a large model operating in block mode (processing multiple tokens simultaneously). The small model's predictive accuracy is substantially enhanced by granting it attention to the large model's richer representations. On the PaLM2 pretraining dataset, a tandem of PaLM2-Bison and PaLM2-Gecko demonstrates a 3.3% improvement in next-token prediction accuracy over a standalone PaLM2-Gecko, offering a 1.16x speedup compared to a PaLM2-Otter model with comparable downstream performance. We further incorporate the tandem model within the speculative decoding (SPEED) framework where the large model validates tokens from the small model. This ensures that the Tandem of PaLM2-Bison and PaLM2-Gecko achieves substantial speedup (around 1.14x faster than using vanilla PaLM2-Gecko in SPEED) while maintaining identical downstream task accuracy.
Self-similarity of the third type in ultra relativistic blastwaves

A new type of self-similarity is found in the problem of a plane-parallel, ultra-relativistic blast wave, propagating in a powerlaw density profile of the form $\rho \propto z^{-k}$. Self-similar solutions of the first kind can be found for $k<7/4$ using dimensional considerations. For steeper density gradients with $k>2$, second type solutions are obtained by eliminating a singularity from the equations. However, for intermediate powerlaw indices $7/4<k<2$ the flow does not obey any of the known types of self-similarity. Instead, the solutions belong to a new class in which the self-similar dynamics are dictated by the non self-similar part of the flow. We obtain an exact solution to the ultra-relativistic fluid equations and find that the non self-similar flow is described by relativistic expansion into vacuum, composed of (1) an accelerating piston that contains most of the energy and (2) a leading edge of fast material that coincides with the interiors of the blastwave and terminates at the shock. The dynamics of the piston itself are self-similar and universal, and do not depend on the external medium. The exact solution of the non self-similar flow is used to solve for the shock in the new class of solutions.
What the Fix? A Study of ASATs Rule Documentation

Automatic Static Analysis Tools (ASATs) are widely used by software developers to diffuse and enforce coding practices. Yet, we know little about the documentation of ASATs, despite it being critical to learn about the coding practices in the first place. We shed light on this through several contributions. First, we analyze the documentation of more than 100 rules of 16 ASATs for multiple programming languages, and distill a taxonomy of the purposes of the documentation-What triggers a rule; Why it is important; and how to Fix an issue-and its types of contents. Then, we conduct a survey to assess the effectiveness of the documentation in terms of its goals and types of content. We highlight opportunities for improvement in ASAT documentation. In particular, we find that the Why purpose is missing in half of the rules we survey; moreover, when the Why is present, it is more likely to have quality issues than the What and the Fix.
On Bayesian Filtering for Markov Regime Switching Models

This paper presents a framework for empirical analysis of dynamic macroeconomic models using Bayesian filtering, with a specific focus on the state-space formulation of Dynamic Stochastic General Equilibrium (DSGE) models with multiple regimes. We outline the theoretical foundations of model estimation, provide the details of two families of powerful multiple-regime filters, IMM and GPB, and construct corresponding multiple-regime smoothers. A simulation exercise, based on a prototypical New Keynesian DSGE model, is used to demonstrate the computational robustness of the proposed filters and smoothers and evaluate their accuracy and speed for a selection of filters from each family. We show that the canonical IMM filter is faster and is no less, and often more, accurate than its competitors within IMM and GPB families, the latter including the commonly used Kim and Nelson (1999) filter. Using it with the matching smoother improves the precision in recovering unobserved variables by about 25 percent. Furthermore, applying it to the U.S. 1947-2023 macroeconomic time series, we successfully identify significant past policy shifts including those related to the post-Covid-19 period. Our results demonstrate the practical applicability and potential of the proposed routines in macroeconomic analysis.