bluuebunny/crossref_metadata_2025_split huggingface dataset:
The glucocorticoid dexamethasone inhibits HIF-1alpha stabilisation and metabolic reprogramming in lipopolysaccharide-stimulated primary macrophages
Authors: Clayton Sally A , Lockwood Chloe , O’Neil John D , Daley Kalbinder K , Hain Sofia , Abdelmottaleb Dina , Bolimowska Oliwia O , Tennant Daniel A , Clark Andrew R 
Published: September 2023

ABSTRACTSynthetic glucocorticoids are used to treat many chronic and acute inflammatory conditions. Frequent adverse effects of prolonged exposure to glucocorticoids include disturbances of glucose homeostasis, caused by changes of glucose traffic and metabolism in muscle, liver and adipose tissues. Macrophages are important targets for the anti-inflammatory actions of glucocorticoids. These cells rely on aerobic glycolysis to support various pro-inflammatory and antimicrobial functions. Employing a potent pro-inflammatory stimulus in two commonly-used model systems (mouse bone marrow-derived and human monocyte-derived macrophages), we showed that the synthetic glucocorticoid dexamethasone inhibited lipopolysaccharide-mediated activation of the hypoxia- inducible transcription factor HIF-1α, a critical driver of glycolysis. In both cell types, dexamethasone-mediated inhibition of HIF-1α reduced the expression of the glucose transporter GLUT1, which imports glucose to fuel aerobic glycolysis. Aside from this conserved response, other metabolic effects of lipopolysaccharide and dexamethasone differed between human and mouse macrophages. These findings suggest that glucocorticoids exert anti-inflammatory effects by impairing HIF-1α-dependent glucose uptake in activated macrophages. Furthermore, harmful and beneficial (anti-inflammatory) effects of glucocorticoids may have a shared mechanistic basis, depending on alteration of glucose utilisation.GRAPHICAL ABSTRACT
Subnet Communicability: Diffusive Communication Across the Brain Through a Backbone Subnetwork
Authors: Parlett Jonathan , Jeyapratap Abhishek , Shokoufandeh Ali , Tunc Birkan , Osmanlioglu Yusuf 
Published: September 2023

AbstractOne of the fundamental challenges in modern neuroscience is understanding the interplay between the brain’s functional activity and its underlying structural pathways. To address this question, we propose a novel communication pattern calledsubnet communicability, which models diffusive communication between pairs of regions through a small, intermediary subnetwork of brain regions as opposed to spreading messages through the entire network. We demonstrate that subnet communicability strengthens coupling between the structural and functional connectomes better than previous models, including communicability. Over two large datasets, we show that the optimal subnetwork is consistent across the population. Subnet communicability provides new insights into structure-function coupling in the brain and offers a balance between redundancy in message passing and economy of brain wiring.
GPFN: Prior-Data Fitted Networks for Genomic Prediction
Authors: Ubbens Jordan , Stavness Ian , Sharpe Andrew G. 
Published: September 2023

AbstractGenomic Prediction (GP) methods predict the breeding value of unphenotyped individuals in order to select parental candidates in breeding populations. Among models for GP, classical linear models have remained consistently popular, while more complex nonlinear methods such as deep neural networks have shown comparable accuracy at best. In this work we propose the Genomic Prior-Data Fitted Network (GPFN), a new paradigm for GP. GPFNs perform amortized Bayesian inference by drawing hundreds of thousands or millions of synthetic breeding populations during the prior fitting phase. This allows GPFNs to be deployed without requiring any training or tuning, providing predictions in a single inference pass. On three populations of crop plants across two different crop species, GPFNs perform significantly better than the linear baseline on 13 out of 16 traits. On a challenging between-families NAM prediction task, the GPFN performs significantly better in 3 locations while only falling behind in one. GPFNs represent a completely new direction for the field of genomic prediction, and have the potential to unlock levels of selection accuracy not possible with existing methods.
Rapid evolution ofWolbachiagenomes in mosquito cell culture
Authors: Martinez Julien , Sinkins Steve P. 
Published: September 2023

AbstractWolbachiabacterial symbionts are widespread across arthropods where they cause reproductive manipulations and/or confer fitness benefits such as protection against viral pathogens. Their self-spreading ability coupled with their antiviral effect has been harnessed in health programmes to curb the transmission of dengue virus. Comparative genomics ofWolbachiastrains has been a useful tool to understand the general trends in the evolution of the symbiont genome; however, short-term evolutionary processes occurring within hosts remain poorly explored. Understanding these short-term dynamics is necessary to provide a more complete picture ofWolbachiaevolution and will inform ongoingWolbachia-based disease control interventions. Here we generated six new mosquito cell lines by introducing a range ofWolbachiastrains fromDrosophilainto the symbiont-freeAedes albopictusAa23 cell line. Following transinfection, we tracked temporal variation inWolbachiadensity and identifiedde novomutations through re-sequencing of the symbiont genome. Several mutations were associated with major shifts in bacterial density. Moreover, signs of parallel evolution across cell lines, combined with an excess of non-synonymous mutations, indicate thatWolbachiaevolution in cell culture is dominated by selective processes rather than genetic drift. Our results also provide new candidate genes likely to be involved in symbiont density regulation. Altogether, our study demonstrates that cell culture is a valuable tool to investigate symbiont short-term evolution, identify the genetic basis of bacterial density variation and for the generation of new higher-density variants for use in control programmes.
Biological warfare between two bacterial viruses in a genomic archipelago sheds light on the spread of CRISPR-Cas systems
Authors: Rubio Alejandro , Garzón Andrés , Moreno-Rodriguez Antonio , Pérez-Pulido Antonio J. 
Published: September 2023

AbstractCRISPR-Cas systems are acquired immunity systems of bacteria and archaea that prevent infection by phages and other mobile genetic elements. It is currently known that this defense system has also been co-opted by viruses. These viruses could use CRISPR-Cas systems to compete against other rival viruses. We have discovered a virus in the bacteriumAcinetobacter baumanniithat incorporates a CRISPR-Cas system into an integration hotspot of the host genome. Once integrated, this could prevent the infection of the most frequent viruses in this bacterial species, especially one that competes with the CRISPR-Cas system itself for the same integration site. This latter virus is prevalent in strains of the species belonging to the so-called Global Clone 2, which causes the most frequent outbreaks worldwide. Knowledge of this new viral warfare using CRISPR-Cas systems, known to limit the entry of antibiotic resistance genes into bacteria, could be useful in the fight against the infections they cause. But it would also shed light on the way in which these defense systems expand in bacteria.
Decoding Nucleosome-Depleted Regions: Insights from Epigenetic Marks, Nucleosome Size, and Thermodynamic Modelling
Authors: Tartour Kévin , Barbier Jérémy , Hungyo Kharerin , Sassolas Fabien , Vaillant Cédric , Padmanabhan Kiran , Audit Benjamin 
Published: September 2023

AbstractElucidating the global and local rules that govern genome-wide nucleosome organisation and chromatin architecture remains a critical challenge. Thermodynamic modelling based on DNA elastic properties predicts the presence of sequence-encoded nucleosome-inhibiting energy barriers (NIEBs) along vertebrate genomes. They delineatein vivonucleosome-depleted regions (NDRs) flanked by 2-3 well positioned nucleosomes. Here, we compared mouse NIEBs to NDRs observed at CTCF binding sites and active TSSs to reveal specific chromatin organizations. We uncover in MNase-seq chromatin profiles the presence of particles of subnucleosomal length specifically positioned at the border of NIEBs with an enrichment of H3.3 and its modification H3.3 S31Ph, whereas the positioning of nucleosomes bearing H3K27ac appears insensitive to NIEBs. Surprisingly, post-translational modifications affect the size distribution of nucleosomes as seen by MNase digestion and so likely their breathing capability. We implemented an extension of our thermodynamic model allowing for variable particle size and suggest that subnucleomes at NIEB borders would result from the recruitment of chromatin remodellers at NIEBs. Our findings provide new insights into the mechanisms by which the DNA sequence and epigenetic marks shape the nucleosome positioning and breathing.
Mechanical and elemental characterization of ant mandibles: consequences for bite mechanics
Authors: Klunk Cristian L. , Heethoff Michael , Hammel Jörg U. , Gorb Stanislav N. , Krings Wencke 
Published: September 2023

AbstractChewing with the mandibles is a food processing behavior observed in most current insect lineages. Mandible morphology has an essential role in biting behavior and food processing capacity. However, the mandible cuticle can have regional differences in its mechanical properties, associated or not with the accumulation of elements that increase cuticle stiffness. The effects of such a heterogeneous distribution of cuticle material properties in the mandible responses to biting loading are still poorly explored in chewing insects. Here we measured the elemental composition and material properties of workers of an ant species,Formica cunicularia, and tested the effects of the cuticular variation in Young’s modulus (E) under bite-loading with Finite Element Analysis (FEA). We divided worker mandibles into four regions that we expect would vary in elemental composition and material properties, namely the masticatory margin, mandible blade, ventral (VMA), and dorsal (DMA) mandibular articulations with the head. Specifically, we expect the masticatory margin will show higher cuticular hardness (H) and E values, followed by the mandibular joints and the mandible blade. We also predict that such cuticle material properties variation is functionally relevant under bite-loading, changing stress patterns when compared to the mechanical responses of a mandible with a homogeneous distribution of material properties. To measure elemental composition, we used energy disperse X-ray spectroscopy, while H and E were accessed through nanoindentation tests. Mandible mechanical responses to bite-loading were tested with FEA, comparing a mandible with a homogeneous versus a heterogeneous E distribution. As expected, the mandibular regions showed distinct proportions of relevant elements, like Cu and Zn, with the masticatory margin showing the higher levels of those elements, followed by the mandibular articulations with the head and the mandible blade. The same pattern was observed regarding the values of cuticle H and E. When incorporated into FEA, this variation in E effectively changed mandible stress patterns, leading to a higher concentration of stresses in the stiffer mandibular regions, letting the softer mandible blade with relatively lower stress levels. Our results demonstrated the relevance of cuticle heterogeneity in mechanical properties to deal with bite-loading demands and suggest that the accumulation of transition metals such as Cu and Zn has a relevant correlation with such mechanical characteristics of the mandible in this ant species.
Modeling the evolution of segment trees reveals deficiencies in current inferential methods for genomic reassortment
Authors: Lin Qianying , Goldberg Emma E. , Leitner Thomas , Molina-París Carmen , King Aaron A. , Romero-Severson Ethan O. 
Published: September 2023

AbstractReassortment is an evolutionary process common in viruses with segmented genomes. These viruses can swap whole genomic segments during cellular co-infection, giving rise to new viral variants. Large-scale genome rearrangements, such as reassortment, have the potential to quickly generate new phenotypes, making the understanding of viral reassortment important to both evolutionary biology and public health research. In this paper, we argue that reassortment cannot be reliably inferred from incongruities between segment phylogenies using the established remove-and-rejoin or coalescent approaches. We instead show that reassortment must be considered in the context of a broader population process that includes the dynamics of the infected hosts. Using illustrative examples and simulation we identify four types of evolutionary events that are difficult or impossible to reconstruct with incongruence-based methods. Further, we show that these specific situations are very common and will likely occur even in small samples. Finally, we argue that existing methods can be augmented or modified to account for all the problematic situations that we identify in this paper. Robust assessment of the role of reassortment in viral evolution is difficult, and we hope to provide conceptual clarity on some important methodological issues that can arise in the development of the next generation of tools for studying reassortment.
Perinatal Morphine Exposure Induces Long-Term Changes in the Intestinal Microbiota of Male and Female Rats
Authors: Harder Hannah J. , Dauriat Charlène J.G. , Chassaing Benoit , Murphy Anne Z. 
Published: September 2023

AbstractThe increased use of opioids by women of reproductive age has resulted in a dramatic rise in number of infants exposed to opioidsin utero. Although perinatal opioid exposure (POE) has been associated with an elevated risk of infection and hospitalization later in life, the mechanism(s) by which opioids influence immune development and maturation is not fully elucidated. Alterations in the intestinal microbiota composition, which leads to changes in immune training and maturation, could be at play. Chronic opioid use in adults is associated with a proinflammatory and pathogenic microbiota composition; therefore, we hypothesized here thatin uteromorphine exposure could negatively affect intestinal microbiota composition, leading to alterations in immune system function. We report that a clinically-relevant model of perinatal opioid exposure, in rats, induces profound intestinal microbiota dysbiosis that is maintained into adulthood. Furthermore, microbial maturity was reduced in morphine-exposed offspring. This suggests that increased risk of infection observed in children exposed to opioids during gestation may be a consequence of microbiota alterations with downstream impact on immune system development. Further investigation of how perinatal morphine induces dysbiosis will be critical to the development of early life interventions designed to ameliorate the increased risk of infection observed in these children.
Independent Influences of Movement Distance and Visual Distance on Fitts' Law
Authors: Al-Fawakhiri Naser , McDougle Samuel D. 
Published: September 2023

AbstractFitts’ Law is one among a small number of psychophysical laws. However, a fundamental variable in Fitts’ Law – the movement distance, D – confounds two quantities: the physical distance the effector has to move to reach a goal, and the visually perceived distance to that goal. While these two quantities are functionally equivalent in everyday motor behavior, decoupling them might improve our understanding of the factors that shape speed-accuracy tradeoffs. Here we leveraged the phenomenon of visuomotor gain adaptation to de-confound movement and visual distance during goal-directed reaching. We found that movement distance and visual distance can influence movement times, supporting a variant of Fitts’ Law that considers both. The weighting of movement versus visual distance was modified by restricting movement range and degrading visual feedback. These results may reflect the role of sensory context in early stages of motor planning.Public SignificanceYou will automatically slow your movement when picking up a needle five inches away versus a handkerchief three inches away. This fact is elegantly formalized by Fitts’ Law, which mathematically relates movement duration to movement difficulty. However, one of the fundamental variables in the law – the distance of a planned movement – is ambiguous: Is it the actual distance the hand must move that biases movement duration, or is it the visually perceived distance? We decoupled these variables, finding that Fitts’ Law is shaped by both quantities, and that the influence of one versus the other may be related to the relevance of visual information. We believe our “addendum” to Fitts’ Law is timely, as everyday motor behavior has become increasingly enmeshed with virtual environments that abstract our movements into digital realities.
A neural signature for the subjective experience of threat anticipation under uncertainty
Authors: Liu Xiqin , Jiao Guojuan , Zhou Feng , Kendrick Keith M , Yao Dezhong , Xiang Shitong , Jia Tianye , Zhang Xiaoyong , Zhang Jie , Feng Jianfeng , Becker Benjamin 
Published: September 2023

AbstractUncertainty about potential future threats and the associated anxious anticipation represents a key feature of anxiety. However, the neural systems that underlie the subjective experience of threat anticipation under uncertainty remain unclear. Combining a novel uncertain shock anticipation paradigm that allows precise modulation of the level of momentary anxious arousal during functional magnetic resonance imaging (fMRI) with multivariate predictive modeling, we trained a brain model that accurately predicted the intensity of subjective experience of anxious arousal on the population and individual level. In a series of analyses utilizing available fMRI datasets, we further demonstrate that the signature specifically predicted anxious anticipation and was not sensitive in predicting pain, general anticipation or unspecific arousal. The signature was functionally and spatially distinguishable from representations of subjective fear or negative affect. We developed a sensitive, generalizable, and specific neuromarker for subjective anxious arousal experienced during uncertain threat anticipation that can facilitate model development and clinical translation.
Effect of Menstrual Cycle and Menopause on Human Gastric Electrophysiology
Authors: Lim Alexandria H , Varghese Chris , Sebaratnam Gabrielle , Schamberg Gabriel , Calder Stefan , Gharibans Armen , Andrews Christopher N , Foong Daphne , Ho Vincent , Ishida Shunichi , Imai Yohsuke , Wise Michelle R , O’Grady Greg 
Published: September 2023

AbstractChronic gastroduodenal symptoms disproportionately affect females of childbearing age; however, the effect of menstrual cycling on gastric electrophysiology is poorly defined. To establish the effect of the menstrual cycle on gastric electrophysiology, healthy subjects underwent non-invasive Body Surface Gastric Mapping (BSGM; 8×8 array), with validated symptom logging App (Gastric AlimetryⓇ, New Zealand). Participants were premenopausal females in follicular (n=26) and luteal phases (n=18). Postmenopausal females (n=30) and males (n=51) were controls. Principal gastric frequency (PGF), BMI-adjusted amplitude, Gastric Alimetry Rhythm Index (GA-RI), fasted-fed amplitude ratio (ff-AR), meal response curves, and symptom burden were analysed. Menstrual cycle-related electrophysiological changes were then transferred to an established anatomically-accurate computational gastric fluid dynamics model (meal viscosity 0.1 Pas), to predict the impact on gastric mixing and emptying. PGF was significantly higher in the luteal vs. follicular phase (mean 3.21 cpm, SD (0.17) vs. 2.94 cpm, SD (0.17), p<0.001) and vs. males (3.01 cpm, SD (0.2), p<0.001). In the computational model, this translated to 8.1% higher gastric mixing strength and 5.3% faster gastric emptying for luteal versus follicular phases. Postmenopausal females also exhibited higher PGF than females in the follicular phase (3.10 cpm, SD (0.24) vs. 2.94 cpm, SD (0.17), p=0.01), and higher BMI-adjusted amplitude (40.7 µV (33.02-52.58) vs. 29.6 µV (26.15-39.65), p<0.001), GA-RI (0.60 (0.48-0.73) vs. 0.43 (0.30-0.60), p=0.005), and ff-AR (2.51 (1.79-3.47) vs. 1.48 (1.21-2.17), p=0.001) than males. There were no differences in symptoms. These results define variations in gastric electrophysiology with regard to human menstrual cycling and menopause.New and NoteworthyThis study evaluates gastric electrophysiology in relation to the menstrual cycle using a novel non-invasive high-resolution methodology, revealing substantial variations in gastric activity with menstrual cycling and menopause. Gastric slow wave frequency is significantly higher in the luteal versus follicular menstrual phase. Computational modelling predicts that this difference translates to higher rates of gastric mixing and emptying in the luteal phase, which is consistent with previous experimental data evaluating menstrual cycling effects on gastric emptying.
Simultaneous estimation of gene regulatory network structure and RNA kinetics from single cell gene expression
Authors: Jackson Christopher A , Beheler-Amass Maggie , Tjärnberg Andreas , Suresh Ina , Hickey Angela Shang-mei , Bonneau Richard , Gresham David 
Published: September 2023

Cells respond to environmental and developmental stimuli by remodeling their transcriptomes through regulation of both mRNA transcription and mRNA decay. A central goal of biology is identifying the global set of regulatory relationships between factors that control mRNA production and degradation and their target transcripts and construct a predictive model of gene expression. Regulatory relationships are typically identified using transcriptome measurements and causal inference algorithms. RNA kinetic parameters are determined experimentally by employing run-on or metabolic labeling (e.g. 4-thiouracil) methods that allow transcription and decay rates to be separately measured. Here, we develop a deep learning model, trained with single-cell RNA-seq data, that both infers causal regulatory relationships and estimates RNA kinetic parameters. The resultingin silicomodel predicts future gene expression states and can be perturbed to simulate the effect of transcription factor changes.We acquired model training data by sequencing the transcriptomes of 175,000 individualSaccharomyces cerevisiaecells that were subject to an external perturbation and continuously sampled over a one hour period. The rate of change for each transcript was calculated on a per-cell basis to estimate RNA velocity. We then trained a deep learning model with transcriptome and RNA velocity data to calculate time-dependent estimates of mRNA production and decay rates. By separating RNA velocity into transcription and decay rates, we show that rapamycin treatment causes existing ribosomal protein transcripts to be rapidly destabilized, while production of new transcripts gradually slows over the course of an hour.The neural network framework we present is designed to explicitly model causal regulatory relationships between transcription factors and their genes, and shows superior performance to existing models on the basis of recovery of known regulatory relationships. We validated the predictive power of the model by perturbing transcription factorsin silicoand comparing transcriptome-wide effects with experimental data. Our study represents the first step in constructing a complete, predictive, biophysical model of gene expression regulation.