bluuebunny/crossref_metadata_2025 huggingface dataset:
Transcriptomic alterations including p53 pathway dysregulation prime DNMT3A mutant cells for transformation
Authors: Lawrence Erin , Cooray Amali , Kueh Andrew , Pal Martin , Tai Lin , Garnham Alexandra , Li-Wai-Suen Connie S. N. , Vanyai Hannah , Gouil Quentin , Lancaster James , Callegari Sylvie , Whelan Lauren , Lieschke Elizabeth , Thomas Annabella , Strasser Andreas , Liao Yang , Shi Wei , Wei Andrew , Herold Marco J
Published: August 2024

DNMT3A mutations are prevalent in haematologic malignancies. Our mouse model introduced the murine homologue (R878H) of the human hotspot R882H mutation into the mouse Dnmt3a locus, resulting in globally reduced DNA methylation in all tissues. Mice with heterozygous R878H mutations developed gamma-radiation induced thymic lymphoma more rapidly than control mice, suggesting a vulnerability to stress stimuli in Dnmt3a cells. In competitive transplantations, Dnmt3a Lin-Sca-1+Kit+ (LSK) cells had a competitive advantage over wt cells, indicating a self-renewal phenotype at the expense of differentiation. RNA-sequencing of Dnmt3aR878H/+ LSKs exposed to low dose gamma-radiation showed downregulation of the p53 pathway. Accordingly, reduced PUMA expression was observed by flow cytometry in the bone marrow of gamma-irradiated Dnmt3a mice due to altered p53 signalling. These findings provide new insights as to how DNMT3A mutations cause subtle changes in the transcriptome of LSK cells which contribute to their increased self-renewal and propensity for malignant transformation.
SAFARI: Pangenome Alignment of Ancient DNA Using Purine/Pyrimidine Encodings
Authors: Rubin Joshua , van Waaij Jan , Kraft Louis , Sirén Jouni , Sackett Peter Wad , Renaud Gabriel
Published: August 2024

Aligning DNA sequences retrieved from fossils or other paleontological artifacts, referred to as ancient DNA, is particularly challenging due to the short sequence length and chemical damage which creates a specific pattern of substitution (C→T and G→A) in addition to the heightened divergence between the sample and the reference genome thus exacerbating reference bias. This bias can be mitigated by aligning to pangenome graphs to incorporate documented organismic variation, but this approach still suffers from substitution patterns due to chemical damage. We introduce a novel methodology introducing the RYmer index, a variant of the commonly-used minimizer index which represents purines (A,G) and pyrimidines (C,T) as R and Y respectively. This creates an indexing scheme robust to the aforementioned chemical damage. We implementedSAFARI, an ancient DNA damage-aware version of the pangenome alignervg giraffewhich uses RYmers to rescue alignments containing deaminated seeds. We show that our approach produces more correct alignments from ancient DNA sequences than current approaches while maintaining a tolerable rate of spurious alignments. In addition, we demonstrate that our algorithm improves the estimate of the rate of ancient DNA damage, especially for highly damaged samples. Crucially, we show that this improved alignment can directly translate into better insights gained from the data by showcasing its integration with a number of extant pangenome tools.
MRGM: An enhanced catalog of mouse gut microbial genomes substantially broadening taxonomic and functional landscapes
Authors: Kim Nayeon , Kim Chan Yeong , Ma Junyeong , Yang Sunmo , Park Dongjin , Ha Sang-Jun , Belenky Peter , Lee Insuk
Published: August 2024

Mouse gut microbiome research is pivotal for understanding the human gut microbiome, providing insights into disease modeling, host-microbe interactions, and the dietary influence on the gut microbiome. To enhance the translational value of mouse gut microbiome studies, we need detailed and high-quality catalogs of mouse gut microbial genomes. We introduce the Mouse Reference Gut Microbiome (MRGM), a comprehensive catalog with 42,245 non-redundant mouse gut bacterial genomes across 1,524 species. MRGM marks a 40% increase in the known taxonomic diversity of mouse gut microbes, capturing previously underrepresented lineages through refined genome quality assessment techniques. MRGM not only broadens the taxonomic landscape but also enriches the functional landscape of the mouse gut microbiome. Using deep learning, we have elevated the Gene Ontology annotation rate for mouse gut microbial proteins from 3.2% with orthology to 60%, marking an over 18-fold increase. MRGM supports both DNA- and marker-based taxonomic profiling by providing custom databases, surpassing previous catalogs in performance. Finally, taxonomic and functional comparisons between human and mouse gut microbiota reveal diet-driven divergences in their taxonomic composition and functional enrichment. Overall, our study highlights the value of high-quality microbial genome catalogs in advancing our understanding of the co-evolution between gut microbes and their host.
Unraveling lncRNA Diversity at a Single Cell Resolution and in a Spatial Context across Different Cancer Types
Authors: Prakrithi P. , Vo Tuan , Vu Hani , Xiong Zherui , Nguyen Loan , Newman Andrew , Whitehall Vicki , Gonzalez Cruz Jazmina L. , Gupta Ishaan , Nguyen Quan
Published: August 2024

Long non-coding RNAs (lncRNAs) play pivotal roles in gene regulation and disease, including cancer. Overcoming the limitations of lncRNA analysis with bulk data, we analyzed single-cell and spatial transcriptomics data to uncover 354937 novel lncRNAs and their functions across 13 cancer types. LncRNA functions were assessed by identifying their cell-type specificity and distinct spatial distributions across different tissue regions. First, lncRNAs were computationally validated by comparing to existing databases, and experimentally validated using spatial long read sequencing methods. Further, genome-wide computation of spatial-autocorrelation identified coexpression of lncRNAs with cancer-associated protein coding genes across the tissue. Additionally, genomic co-localization of lncRNAs with regulatory features and disease-associated genetic variants suggest possible functional association. The identified lncRNAs were analyzed for responses to immunotherapy and prognostic value, revealing cancer-outcome associated lncRNAs. We have made this novel resource available as an open website ‘SPanC-Lnc’ hosted on AWS cloud to serve as a pan-cancer atlas of single cell- and spatially-resolved lncRNAs. These can complement established biomarkers because they reflect the unique characteristics of specific cell populations within tumors, offering new insights into disease progression and treatment response.
Endoplasmic reticulum stress inhibition preserves mitochondrial function and cell survival during early onset of isoniazid-induced oxidative stress
Authors: Nhung Truong Thi My , Phat Nguyen Ky , Anh Trinh Tam , Nghi Tran Diem , Thu Nguyen Quang , Lee Ara , Tien Nguyen Tran Nam , Anh Nguyen Ky , Kim Kimoon , Nguyen Duc Ninh , Kim Dong-Hyun , Park Sang Ki , Long Nguyen Phuoc
Published: August 2024

A comprehensive understanding of isoniazid (INH)-mediated hepatotoxic effects is essential for developing strategies to predict and prevent severe liver toxicity in tuberculosis treatment. Our study utilized multi-omics profiling to investigate the toxic effects of INH, revealing significant involvement of endoplasmic reticulum (ER) stress, mitochondrial impairment, redox imbalance, and altered metabolism. Followed-up mechanistic studies revealed that INH triggered the generation of cytosolic reactive oxygen species (ROS) and the activation of the Nrf2 signaling pathway prior to mitochondrial ROS accumulation. Subsequently, INH disrupted mitochondrial function by impairing respiratory complexes I-IV and caused mitochondrial membrane proton leaks without affecting ATP synthase activity, together leading to mitochondrial depolarization and reduced ATP production. These disturbances enhanced mitochondrial fission and mitophagy. While much attention has been given to mitochondrial dysfunction and oxidative stress in INH-induced hepatotoxicity, our findings highlight the potential of inhibiting ER stress during early INH exposure to mitigate cytosolic and mitochondrial oxidative stress. We further revealed the critical role of Nrf2 signaling in protecting liver cells under INH-induced oxidative stress by maintaining redox homeostasis and enabling metabolic reprogramming via regulating the expression of antioxidant genes and cellular lipid abundance. We also identified other antioxidant pathways (e.g., selenocompound metabolism, HIF-1 signaling pathway, and pentose phosphate pathway) as potential alternative mechanisms besides Nrf2 signaling in response to INH-induced oxidative stress. In conclusion, our research emphasizes the importance of ER stress, redox imbalance, metabolic changes, and mitochondrial dysfunction underlying INH-induced hepatotoxicity.
Ferroptosis susceptibility of melanoma cells: dependence on cell-type, acquired drug resistance, and medium composition
Authors: Preis Jasmin Renate , Rolvering Catherine , Kirchmeyer Mélanie , Halilovic Dzeneta , Wroblewska Joanna Patrycja , Tolle Fabrice , Behrmann Iris , Haan Claude
Published: August 2024

Resistance of melanoma cells to targeted therapy (BRAF and MEK inhibitors) is a major clinical problem and alternative treatments are sought. We describe the establishment of modular physiologic medium (MPM) and Mel-MPM (which contains additional supplements and sustains the 3D growth of melanoma cells, fibroblasts (NHDFs) and HMEC-1 endothelial cells) as novel resources for melanoma and combine them with a multi-cell-type matrix-embedded 3D culture model to investigate melanoma cell vulnerabilities in a more physiological setting.

We made use of the modular nature of MPM to interrogate NEAA dependencies in melanoma cells and we found them to be particularly sensitive to the depletion of C/C. We additionally describe that melanoma cells are less sensitive to ferroptosis inducing compounds when cultured in MPM compared to RPMI and we could attribute this to different components of MPM and Mel-MPM (selenite, B27). Cell death induced by the glutathione peroxidase 4 inhibitor, ML162, had characteristics of ferroptosis or apoptosis depending on cell type, its drug resistance status and the culture medium. Cystine/cysteine starvation and ML162 treatment combinations increased melanoma cell death in 2D, 3D, and also in the complex matrix embedded multi-cell-type-3D system in OrganoplatesTM. This underlines the potential of combining metabolism-oriented drug treatments with amino acid starvation conditions, which is of interest in view of future therapeutic approaches to combat melanoma and other cancer types.
Scalable and universal prediction of cellular phenotypes
Authors: Ji Yuge , Tejada-Lapuerta Alejandro , Schmacke Niklas A. , Zheng Zihe , Zhang Xinyue , Khan Simrah , Rothenaigner Ina , Tschuck Juliane , Hadian Kamyar , Theis Fabian J.
Published: August 2024

Biological systems can be understood by perturbing individual components and studying the system’s response. Cell biology experiments are defined by the applied treatment, cellular state, and the assayed phenotype. Given the vast number of possible combinations, testing every scenario is impractical. We present Prophet, a transformer-based computational model for cellular phenotype prediction. Prophet learns a representation of the cell biology experiment space, enabling it to predict the outcomes of untested small molecule or genetic perturbations in new cellular contexts across diverse phenotypes including gene expression, cell viability, and cell morphology. Its scalable architecture facilitates training across independent assays, using transfer learning to enhance performance across phenotypes. In vitro validation shows Prophet’s potential to guide experimental design, making it a valuable tool for accelerating biological discovery.
Fast and Accurate LSTM Meta-modeling of TNF-induced Tumor Resistance In Vitro
Authors: Abrate Marco P. , Smeriglio Riccardo , Bardini Roberta , Savino Alessandro , Di Carlo Stefano
Published: August 2024

Multi-level, hybrid models and simulations, among other methods, are essential to enable predictions and hypothesis generation in systems biology research. However, the computational complexity of these models poses a bottleneck, limiting the applicability of methodologies relying on large number of simulations, such as the Optimization via Simulation (OvS) of complex biological processes. Meta-models based on approximate surrogate models simplify multi-level simulations, maintaining accuracy while reducing computational costs. Among Artificial Neural Networks (ANNs), Long Short-Term Memory (LSTM) networks are well suited to handle sequential data, which often characterizes biological simulations. This paper presents an LSTM-based surrogate modeling approach for multi-level simulations of complex biological processes. Validation relies on the simulation of Tumor Necrosis Factor (TNF) administration to a 3T3 mouse fibroblasts tumor spheroid based on PhysiBoSS 2.0, a hybrid agent-based multi-level modeling framework. Results show that the proposed LSTM meta-model is accurate and fast compared with the simulator. In fact, it infers simulated behavior with an average relative error of 7.5%. Moreover, it is at least five orders of magnitude faster. Even considering the cost of training, this approach provides a faster, more accurate, and reusable surrogate of multi-scale simulations in computationally complex tasks, such as model-based OvS of biological processes.
The primary sclerosing cholangitis and ulcerative colitis colonic mucosa defined through paired microbial and single-cell RNA sequencing
Authors: Tearle Jacqueline LE , Zhang Fan , Jackson Katherine JL , Malhotra Pratibha , Tavakoli Paris , Koentgen Sabrina , Warren Joanna , Williams Cameron , Haque Ashraful , Arzivian Arteen , Tedla Nicodemus , Kim Andrew , King Hamish W , Hold Georgina L , Ghaly Simon , James Kylie R
Published: August 2024

Primary sclerosing cholangitis (PSC) is a chronic progressing cholestatic disease that often co-occurs with inflammatory bowel disease (PSC-IBD). PSC-IBD affecting the colon (PSC-UC) is likened clinically to ulcerative colitis (UC), however differences include a right colon dominance, less severe inflammatory presentation and a greater lifetime risk of colorectal cancer. To understand the basis of clinical differences, we combine single-cell mRNA and antigen receptor sequencing, 16S ribosomal DNA analysis and spatial transcriptomics on biopsies from multiple colon regions of both PSC-UC and UC patients in remission or at the time of relapse. We discover disease-specific cell and microbial profiles between these cohorts, highlighting a distinct landscape in the right colon of PSC-UC patients and an epithelial-endothelial cell state that may contribute to intestinal permeability in UC. We show the expansion of an activated mast cell state in both diseases during flare, and demonstrate the requirement of TMEM176B in sustaining this activated state. Together this work demonstrates that PSC-UC and UC are distinct diseases with common cell mechanisms during inflammation, providing cellular and microbial insights to improve treatment of both patient cohorts.
Recurrent sex chromosome turn-over in termites
Authors: Fraser Roxanne , Moraa Ruth , Djolai Annika , Meisenheimer Nils , Laube Sophie , Vicoso Beatriz , Huylmans Ann Kathrin
Published: August 2024

Termites, together with cockroaches, belong to the Blattodea. They possess an XX/XY sex determination system which has evolved from an XX/X0 system present in other Blattodean species such as cockroaches and wood roaches. Little is currently known about the sex chromosomes of termites, their gene content, or their evolution. We here investigate the X chromosome of multiple termite species and compare them to the X chromosome of cockroaches using genomic and transcriptomic data. We find that the X chromosome of the termiteMacrotermes natalensisis large and differentiated showing hall marks of sex chromosome evolution such as dosage compensation, while this does not seem to be the case in the other two termite species investigated here where sex chromosomes are probably evolutionary young. Furthermore, that X chromosome inM. natalensisis different from the X chromosome found in the cockroachBlattella germanicaindicating at least one, potentially multiple, sex chromosome turn-over events during termite evolution.
Cytokine-Induced Cell Exhaustion to Mitigate Hyperinflammation
Authors: Marchetti Tommaso , Milanesi Samantha , Tintor Diana , Lorenzini Tiziana , Walser Severin , Vavassori Stefano , Boyman Onur , Schmid Jana Pachlopnik
Published: August 2024

Haemophagocytic lymphohistiocytosis (HLH), a life-threatening hyperinflammatory disorder often driven by dysfunctional cytotoxic CD8+T cells, is marked by cytokine storms, which may follow viral infections. In a study of a perforin-deficient mouse model of HLH with a viral trigger, we aimed to determine if CD8+T cell behaviour could be modulated by targeted interleukin (IL)-2 treatment. We observed a paradoxical benefit that contrasted with IL-2’s typical role in boosting T cell activity: targeted IL-2 delivery to CD8+T cells led to reduced hyperinflammation and disease severity. Our results demonstrated that IL-2 induced exhaustion in overactive CD8+T cells, thus mitigating hyperinflammation. These findings highlight the context-dependency of cytokine treatment and suggest new therapeutic strategies for HLH and other inflammatory diseases by leveraging cell exhaustion.
Investigating the impact of edge weight selection on the pig trade network topology
Authors: Puspitarani Gavrila Amadea , Liao Yan-Shin Jackson , Fuchs Reinhard , Desvars-Larrive Amélie
Published: August 2024

Traceability of animal movements and robust surveillance are crucial for identifying and controlling animal diseases. Risk-based surveillance, i.e. network-based approaches, can identify higher-risk holdings or trades. However, node ranking, useful to identify ”influential” nodes (holdings) in the network, varies with the considered metrics.

We use a dataset of pig movements in Upper Austria from 2021 to study the robustness of node ranking through three centrality metrics and compare them with epidemic model ranking. Incorporating edge weights may influence the network analysis, therefore, we simulate two representations using edge weights based on: i) the frequency of exchanges between holdings (”frequency-based”) and ii) the number of pigs exchanged (”volume-based”). We compare the impact of the edge weight on the network topology, community structure, and node ranking in a network with 5,766 nodes and 92,914 edges. Results revealed distinct edge weight distributions: frequency-based network exhibited a bimodal pattern, while volume-based was more uniform. Strength centrality exhibited the highest correlation with simulation-based rankings, particularly for the top 5% highest-ranked nodes (τb= 0.51 for frequency-based andτb= 0.5 for volume-based). These findings highlight that using strength centrality to identify critical nodes can significantly enhance surveillance strategies, making them more efficient and field-deployable, enhancing traditional methods without requiring extensive simulations.

Author summary

Early detection of infectious diseases through surveillance activities is important to prevent severe impacts on the livestock sector and avoid major economic losses that often result from delayed detection. Prioritizing surveillance efforts through a data-driven approach presents a strategic advantage compared to random sampling. Here, we propose two network representations of the Upper Austrian pig trade network 2021, which show livestock holdings as nodes and animal movements as links between these nodes, which can represent the volume of pigs exchanged or the frequency of these exchanges. Using network analysis methods, we identify ”influential” holdings in the network, i.e., those playing a key role in the network, either due to their numerous connections with other holdings, their position on many trade paths, or their crucial role in disease transmission dynamics. We show that using strength centrality can effectively identify key holdings for targeted surveillance. Adopting network-based surveillance can facilitate resource allocation for veterinary surveillance programs, offering a cost-effective strategy for disease management, enabling tailored, more effective, and timely interventions.
4D hybrid model interrogates agent-level rules and parameters driving hiPS cell colony dynamics
Authors: Yu Jessica S. , Lyons Blair , Rafelski Susanne , Theriot Julie A. , Bagheri Neda , Johnson Graham T.
Published: August 2024

Iterating between data-driven research and generative computational models is a powerful approach for emulating biological systems, testing hypotheses, and gaining a deeper understanding of these systems. We developed a hybrid agent-based model (ABM) that integrates a Cellular Potts Model (CPM) designed to investigate cell shape and colony dynamics in human induced pluripotent stem cell (hiPS cell) colonies. This model aimed to first mimic and then explore the dynamics observed in real-world hiPS cell cultures.

Initial outputs showed great potential, seeming to mimic small colony behaviors relatively well. However, longer simulations and quantitative comparisons revealed limitations, particularly with the CPM component, which lacked long-range interactions that might be necessary for accurate simulations. This challenge led us to thoroughly examine the hybrid model’s potential and limitations, providing insights and recommendations for systems where cell-wide mechanics play significant roles.

The CPM supports 2D and 3D cell shapes using a Monte Carlo algorithm to prevent cell fragmentation. Basic “out of the box” CPM Hamiltonian terms of volume and adhesion were insufficient to match live cell imaging of hiPS cell cultures. Adding substrate adhesion resulted in flatter colonies, highlighting the need to consider environmental context in modeling. High-throughput parameter sweeps identified regimes that produced consistent simulated shapes and demonstrated the impact of specific model decisions on emergent dynamics. Full-scale simulations showed that while certain agent rules could form a hiPS cell monolayer in 3D, they could not maintain it over time.

Our study underscores that “out of the box” 3D CPMs, which do not natively incorporate long-range cell mechanics like elasticity, may be insufficient for accurately simulating hiPS cell and colony dynamics. To address this limitation, future work could add mechanical constraints to the CPM Hamiltonian or integrate global agent rules. Alternatively, replacing the CPM with a methodology that directly represents cell mechanics might be necessary.

Documenting and sharing our model development process fosters open team science and supports the broader research community in developing computational models of complex biological systems.
Listeria monocytogenesRequires Phosphotransferase Systems to Facilitate Intracellular Growth and Virulence
Authors: Freeman Matthew J. , Sauer John-Demian
Published: August 2024

The metabolism of bacterial pathogens is exquisitely evolved to support growth and survival in the nutrient-limiting host. Many bacterial pathogens utilize bipartite metabolism to support intracellular growth by splitting carbon utilization between two carbon sources and dividing flux to distinct metabolic needs. For example, previous studies suggest that the professional cytosolic pathogenListeria monocytogenes(L. monocytogenes) utilizes glycerol and hexose phosphates (e.g. Glucose-6-Phosphate) as catabolic and anabolic carbon sources in the host cytosol, respectively. However, the role of this putative bipartite glycerol and hexose phosphate metabolism inL. monocytogenesvirulence has not been fully assessed. Here, we demonstrate that whenL. monocytogenesis unable to consume either glycerol (ΔglpD/ΔgolD), hexose phosphates (ΔuhpT), or both (ΔglpD/ΔgolD/ΔuhpT), it is still able to grow in the host cytosol and is minimally attenuatedin vivosuggesting thatL. monocytogenes consumes alternative carbon source(s) in the host. An in vitrometabolic screen using BioLog’s phenotypic microarrays demonstrated that both WT and PrfA*L. monocytogenes, a strain with constitutive virulence gene expression mimicking cytosolic replication, use phosphotransferase system (PTS) mediated carbon sources. These findings contrast with the existing metabolic model that cytosolic L. monocytogenesexpressing PrfA does not use PTS mediated carbon sources. We next demonstrate that two independent and universal phosphocarrier proteins (PtsI [EI] and PtsH [HPr]), essential for the function of all PTS, are critical for intracellular growth and virulence in vivo. Finally, virulence phenotypes of these mutants were additive to mutants unable to consume glycerol and hexose phosphates (ΔglpD/ΔgolD/ΔuhpT)in vivo, suggesting that hexose phosphates and glycerol are relevant metabolitesin vivoin addition to those derived from PTS. Taken together, these studies indicate that PTS are critical virulence factors for the cytosolic growth and virulence ofL. monocytogenes.
Gut microbiome diversity associates with estimated lifetime and annual reproductive success in male but not female collared flycatchers
Authors: Martta Liukkonen , Lars Gustafsson , Kirsten Grond , Suvi Ruuskanen
Published: August 2024

The gut microbiome (hereafter, GM) varies across individuals of the same species and this pattern has been observed in multiple wild species. Evidence shows that the GM connects to individual health and survival especially in captive species, but more research is needed to understand how the GM connects to host fitness in wild species. We used long-term monitoring data to investigate whether the GM of collared flycatchersFicedula albicollisassociates with annual and lifetime reproductive success (LRS), and survival to the following breeding season. This is the first study that 1) characterized the collared flycatcher GM, and 2) investigated how variation in the GM related to LRS in wild birds. Our results showed that higher GM diversity was associated with a higher annual and lifetime reproductive success in especially male collared flycatchers. We also found that the compositional variation in collared flycatcher GMs was explained by sex, age, and breeding habitat, but not by annual or lifetime reproductive success. Individuals that died before the next breeding season had higher abundances of ASVs belonging to the pathogenic familiesEnterobacteriaceaeandParachlamydiaceae, and the generaCorynebacteriaandSphingomonas. Our results show that the GM associates with different aspects of host fitness in a wild bird population. More research is needed to evaluate if there is a causal relationship between the GM and individual fitness. These findings also contribute to our understanding of the GMs role in evolution by elucidating the connection between the GM (trait) and reproductive success.
Machine Learning to Predict Gut Microbiomes of Agricultural Pests
Authors: Jobayer Md , Taylor Alexander , Hasan Md Rakibul , Ahmed Khandaker Asif , Hossain Md Zakir
Published: August 2024

Context

While current efforts to control agricultural insect pests largely focus on the widespread use of insecticides, predicting microbiome composition can provide important data for creating more efficient and long-lasting pest control methods by analysing the pest’s food-digesting capacity and resistance to bacteria or viruses.

Aims

Instead of using computationally expensive techniques, we aim to investigate the dynamics of these microbiome compositions using metagenomic samples taken from fruit flies.

Methods

In this paper, we propose the three machine learning-based biological models. Firstly, we propose theintrafamilial successor prediction, which predicts the relative abundance of each bacterial family using the past four generations. Next, we propose ourinterfamilial quantitative prediction, where the model predicts the amount of a given bacterial family in each sample using the amount of all other bacteria present in the sample. Lastly. we propose ourinterfamilial qualitative prediction, which predicts the relative abundance of each bacterial family within a sample using binary information of all bacterial families.

Key Results

All three models were tested against Least Angle Regression, Random Forest, Elastic-Net, and Lasso. The third approach exhibits promising results by applying a Random Forest with the lowest mean Coefficient of Variance of 1.25.

Conclusion

The overall results of this study highlight how complex these dynamic systems are and demonstrate that more computationally efficient methods can characterise them quickly.
Microglia are Required for Developmental Specification of AgRP Innervation in the Hypothalamus of Offspring Exposed to Maternal High-Fat Diet During Lactation
Authors: Mendoza-Romero Haley N. , Biddinger Jessica E. , Bedenbaugh Michelle N. , Simerly Richard B.
Published: August 2024

Agouti-related peptide (AgRP) neurons in the arcuate nucleus of the hypothalamus respond to multiple metabolic signals and distribute neuroendocrine information to other brain regions such as the paraventricular hypothalamic nucleus (PVH), which plays a central role in metabolic homeostasis. Neural projections from AgRP neurons to the PVH form during the postnatal lactational period in mice and these projections are reduced in offspring of dams that consumed a high-fat diet (HFD) during lactation (MHFD-L). Here we used immunohistochemistry to visualize microglial morphology in MHFD-L offspring and identified changes that were regionally localized to the PVH and appeared temporally restricted to the period when AgRP neurons innervate this region. In addition, axon labeling experiments revealed that microglia engulf AgRP terminals in the PVH, and that the density of AgRP innervation to the PVH in MHFD-L offspring may be dependent on microglia, because microglial depletion blocked the decrease in PVH AgRP innervation observed in MHFD-L offspring, as well as prevented the increased body weight exhibited at weaning. Together, these findings suggest that microglia are activated by exposure to MHFD-L and interact directly with AgRP axons during postnatal development to permanently alter innervation of the PVH, with implications for developmental programming of metabolic phenotype.

Impact Statement

Microglia appear to play an essential role in specifying patterns of hypothalamic innervation during development in response to maternal HFD exposure, which may contribute to developmental programming of metabolic phenotype.
Longitudinal deformation based morphometry pipeline to study neuroanatomical differences in structural MRI based on SyN unbiased templates
Authors: Germann Jürgen , Gouveia Flavia Venetucci , Chakravarty M. Mallar , Devenyi Gabriel A.
Published: August 2024

Morphometric measures in humans derived from magnetic resonance imaging (MRI) have provided important insights into brain differences and changes associated with development and disease in vivo. Deformation-based morphometry (DBM) is a registration-based technique that has been shown to be useful in detecting local volume differences and longitudinal brain changes while not requiring a priori segmentation or tissue classification. Typically, DBM measures are derived from registration to common template brain space (one-level DBM). Here, we present a two-level DBM technique: first, the Jacobian determinants are calculated for each individual input MRI at the subject level to capture longitudinal individual brain changes; then, in a second step, an unbiased common group space is created, and the Jacobians co-registered to enable the comparison of individual morphological changes across subjects or groups. This two-level DBM is particularly suitable for capturing longitudinal intra-individual changes in vivo, as calculating the Jacobians within-subject space leads to superior accuracy. Using artificially induced volume differences, we demonstrate that this two-level DBM pipeline is 4.5x more sensitive in detecting longitudinal within-subject volume changes compared to a typical one-level DBM approach. It also captures the magnitude of the induced volume change much more accurately. Using 150 subjects from the OASIS-2 dataset, we demonstrate that the two-level DBM is superior in capturing cortical volume changes associated with cognitive decline across patients with dementia and cognitively healthy individuals. This pipeline provides researchers with a powerful tool to study longitudinal brain changes with superior accuracy and sensitivity. It is publicly available and has already been used successfully, proving its utility.
Bayesian inference of sample-specific coexpression networks
Authors: Saha Enakshi , Fanfani Viola , Mandros Panagiotis , Ben Guebila Marouen , Fischer Jonas , Shutta Katherine H. , DeMeo Dawn L. , Lopes-Ramos Camila M. , Quackenbush John
Published: August 2024

Gene regulatory networks (GRNs) are effective tools for inferring complex interactions between molecules that regulate biological processes and hence can provide insights into drivers of biological systems. Inferring coexpression networks is a critical element of GRN inference, as the correlation between expression patterns may indicate that genes are coregulated by common factors. However, methods that estimate coexpression networks generally derive an aggregate network representing the mean regulatory properties of the population and so fail to fully capture population heterogeneity. Bayesian optimized networks obtained by assimilating omic data (BONOBO) is a scalable Bayesian model for deriving individual sample-specific coexpression matrices that recognizes variations in molecular interactions across individuals. For each sample, BONOBO assumes a Gaussian distribution on the log-transformed centered gene expression and a conjugate prior distribution on the sample-specific coexpression matrix constructed from all other samples in the data. Combining the sample-specific gene coexpression with the prior distribution, BONOBO yields a closed-form solution for the posterior distribution of the sample-specific coexpression matrices, thus allowing the analysis of large data sets. We demonstrate BONOBO's utility in several contexts, including analyzing gene regulation in yeast transcription factor knockout studies, the prognostic significance of miRNA–mRNA interaction in human breast cancer subtypes, and sex differences in gene regulation within human thyroid tissue. We find that BONOBO outperforms other methods that have been used for sample-specific coexpression network inference and provides insight into individual differences in the drivers of biological processes.
Universal reconstruction method for x-ray scattering tensor tomography based on wavefront modulation
Authors: Lautizi Ginevra , Studer Alain , Zdora Marie-Christine , De Marco Fabio , Kim Jisoo , Di Trapani Vittorio , Marone Federica , Thibault Pierre , Stampanoni Marco
Published: August 2024

We present a versatile method for full-field x-ray scattering tensor tomography that is based on energy conservation and is applicable to data obtained using different wavefront modulators. Using this algorithm, we pave the way for speckle-based tensor tomography. The proposed model relies on a mathematical approach that allows tuning spatial resolution and signal sensitivity. We present the application of the algorithm to three different imaging modalities and demonstrate its potential for applications of x-ray directional dark-field imaging.

Published by the American Physical Society
2024
Rearrangement collision theory of phonon-driven exciton dissociation
Authors: Coveney Christopher J. N. , Haber Jonah B. , Alvertis Antonios M. , Neaton Jeffrey B. , Filip Marina R.
Published: August 2024

Understanding the processes governing the dissociation of excitons to free charge carriers in semiconductors and insulators is of central importance for photovoltaic applications. Dyson's S-matrix formalism provides a framework for computing scattering rates between quasiparticle states derived from the same underlying Hamiltonian, often reducing to familiar Fermi's “golden rule” like expressions at first order. By presenting a rigorous formalism for multichannel scattering, we extend this approach to describe scattering between composite quasiparticles and, in particular, the process of exciton dissociation mediated by the electron-phonon interaction. Subsequently, we derive rigorous expressions for the exciton dissociation rate, a key quantity of interest in optoelectronic materials, which enforce correct energy conservation and may be readily used in calculations. We apply our formalism to a three-dimensional model system to compare temperature-dependent exciton rates obtained for different scattering channels.

Published by the American Physical Society
2024
Effect of Coriolis force on electrical conductivity tensor for the rotating hadron resonance gas
Authors: Padhan Nandita , Dwibedi Ashutosh , Chatterjee Arghya , Ghosh Sabyasachi
Published: August 2024

We have investigated the influence of the Coriolis force on the electrical conductivity of hadronic matter formed in relativistic nuclear collisions, employing the hadron resonance gas model. A rotating matter in the peripheral heavy-ion collisions can be expected from the initial stage of quark matter to late-stage hadronic matter. Present work is focused on rotating hadronic matter, whose medium constituents—hadron resonances—can face a nonzero Coriolis force, which can influence the hadronic flow or conductivity. We estimate this conductivity tensor by using the relativistic Boltzmann transport equation. In the absence of Coriolis force, an isotropic conductivity tensor for hadronic matter is expected. However, our study finds that the presence of Coriolis force can generate an anisotropic conductivity tensor with three main conductivity components—parallel, perpendicular, and Hall—similarly to the effect of Lorentz force at a finite magnetic field. Our study has indicated that a noticeable anisotropy of conductivity tensor can be found within the phenomenological range of angular velocity Ω=0.001–0.02 GeV and hadronic scattering radius a=0.2–2 fm.

Published by the American Physical Society
2024
Electromagnetic and two-photon transition form factors of the pseudoscalar mesons: An algebraic model computation
Authors: Higuera-Angulo I. M. , Hernández-Pinto R. J. , Raya K. , Bashir A.
Published: August 2024

We compute electromagnetic and two-photon transition form factors of ground-state pseudoscalar mesons: π,K,ηc,ηb. To this end, we employ an algebraic model based upon the coupled formalism of Schwinger-Dyson and Bethe-Salpeter equations. Within this approach, the dressed quark propagator and the relevant Bethe-Salpeter amplitude encode the internal structure of the corresponding meson. Electromagnetic properties of the meson are probed via the quark-photon interaction. The algebraic model employed by us unifies the treatment of all ground-state pseudoscalar mesons. Its parameters are carefully fitted performing a global analysis of existing experimental data including the knowledge of the charge radii of the mesons studied. We then compute and predict electromagnetic and two-photon transition form factors for a wide range of probing photon momentum-squared which is of direct relevance to the experimental observations carried out thus far or planned at different hadron physics facilities such as the Thomas Jefferson National Accelerator Facility (JLab) and the forthcoming Electron-Ion Collider. We also present comparisons with other theoretical models and approaches and lattice quantum chromodynamics.

Published by the American Physical Society
2024
Production of pentaquarks with hidden charm and double strangeness in
Ξb
and
Ωb
decays
Authors: Oset E. , Roca L. , Whitehead M.
Published: August 2024

Recently, several pentaquark states Pcss, with global flavor c¯cssn, have been predicted within a theoretical framework based on unitary coupled channels. We study theoretically the feasibility to observe the Pcss with I(JP)=12(12−) in the decays Ξb0→ηηcΞ0 and Ωb−→K−ηcΞ0. Indeed, within the model, the ηcΞ0 channel is the lowest mass pseudoscalar-baryon channel to which this pentaquark state couples, thus we can expect to observe its signal in the ηcΞ0 invariant mass distribution of the mentioned decays. We identify the dominant weak decay processes and then implement the hadronization into the different meson-baryon channels in the final state, linked by flavor symmetry. The dominant meson-baryon final state interaction is then implemented to generate the full amplitude, implicitly accounting for the dynamical emergence of the pentaquark states. We obtain a clear Breit-Wigner-like resonant signal in the spectrum of the Ωb− decay, exceeding that in the Ξb0 decay by two to three orders of magnitude. In the case of the latter decay, the resonant state would manifest as a significant dip in the spectrum. We study the feasibility of searching for these b-hadron decay modes and analyzing their resonant components using the current and future data samples from the LHCb experiment.

Published by the American Physical Society
2024
Lepton flavor violation in semileptonic observables
Authors: Plakias I. , Sumensari O.
Published: August 2024

In this paper, we perform a comprehensive study of lepton flavor violation (LFV) in semileptonic transitions in the framework of an effective field theory with general flavor structure. We account for the renormalization group equations, which induce nontrivial correlations between the different types of LFV processes. In particular, we show that these loop effects are needed to improve the bounds on several coefficients that are not efficiently constrained at tree level. For illustration, we consider a few concrete scenarios, with predominant couplings to third-generation quarks, and we explore the correlations between the various tree- and loop-level constraints on these models. As a by-product, we also provide expressions for several semileptonic LFV meson decays by using the latest determinations of the relevant hadronic form factors on the lattice.

Published by the American Physical Society
2024
Testing leptogenesis and seesaw in the
B−L
model using long-lived particle searches
Authors: Liu Wei , Deppisch Frank F. , Chen Zixiang
Published: August 2024

We discuss the potential of using long-lived particle (LLP) searches for right-handed neutrinos (RHNs) to test resonant leptogenesis and the seesaw mechanism. This is challenging if only RHNs are added to the Standard Model, as naturally the active-sterile mixing strengths |VℓN|2 are small, for 1  GeV≲MN≲1000  GeV. Instead, we consider the minimal B−L gauge model, where a Z′ gauge boson couples to fermions including the RHNs. During leptogenesis, this gauge coupling introduces scattering processes that washout the B−L asymmetry. At colliders, it can lead to abundant production of RHNs which allows probing the associated seesaw mechanism using LLP searches. We find that LLP searches at the FCC-hh can test leptogenesis and the seesaw mechanism simultaneously and probe the active-sterile mixing at or below the seesaw floor.

Published by the American Physical Society
2024
Can a femtoscopic correlation function shed light on the nature of the lightest charm axial mesons?
Authors: Khemchandani K. P. , Abreu Luciano M. , Torres A. Martínez , Navarra F. S.
Published: August 2024

We present a coupled channel treatment of meson-meson dynamics, for systems with spin-parity 1+, and determine the corresponding amplitudes by solving the Bethe-Salpeter equations, which lead to the generation of two axial resonances when mesons are considered as the degrees of freedom in the model. One of them is narrow and has properties in good agreement with those of D1(2420). The other pole is wider, but its real and imaginary parts do not match well with the mass and width of D1(2430). The situation improves when a bare quark-model state is included, indicating that the dynamics at the quark level as well as among hadrons can describe the two states simultaneously. Further, we discuss that there exists a divergence in the value of the D*π scattering length determined through data coming from lattice QCD calculations and from heavy ion collisions. Such different values can be accommodated in the model by making small changes in the parameters while producing two poles having properties compatible with the two lightest D1 states. With these results, we proceed to calculate the correlation function for the D*+(0)π0(+) system for different sizes of the source. We discuss which scenarios can be useful to shed some light on the issue.

Published by the American Physical Society
2024
Supernova limits on QCD axionlike particles
Authors: Lella Alessandro , Ravensburg Eike , Carenza Pierluca , Marsh M. C. David
Published: August 2024

In this paper, we explore the phenomenology of massive axionlike particles (ALPs) coupled to quarks and gluons, dubbed “QCD ALPs,” with an emphasis on the associated low-energy observables. ALPs coupled to gluons and quarks not only induce nuclear interactions at scales below the QCD scale, relevant for ALP production in supernovae (SNe), but naturally also couple to photons similarly to the QCD axion. We discuss the link between the high-energy formulation of ALP theories and their effective couplings with nucleons and photons. The induced photon coupling allows ALPs with masses ma≳1  MeV to efficiently decay into photons, and astrophysical observables severely constrain the ALP parameter space. We show that a combination of arguments related to SN events rule out ALP-nucleon couplings down to gaN≳10−11–10−10 for ma≳1  MeV—a region of the parameter space that was hitherto unconstrained.

Published by the American Physical Society
2024
Sub-MeV dark matter detection with bilayer graphene
Authors: Das Anirban , Jang Jiho , Min Hongki
Published: August 2024

The light dark matter mass regime has emerged as the next frontier in the direct detection experiment due to the lack of any detection signal in the higher mass range. In this paper, we propose a new detector material, a bilayer stack of graphene to detect sub-MeV dark matter. Its voltage-tunable low energy sub-eV electronic band gap makes it an excellent choice for the detector material of a light dark matter search experiment. We compute its dielectric function using the random phase approximation and estimate the projected sensitivity for sub-MeV dark matter-electron scattering and sub-eV dark matter absorption. We show that a bilayer graphene dark matter detector can have competitive sensitivity as other candidate target materials, like a superconductor, but with a tunable threshold energy in this mass regime. The dark matter scattering rate in bilayer graphene is also characterized by a daily modulation from the rotation of the Earth which may help us mitigate the backgrounds in a future experiment. We also outline a detector design concept and provide noise estimates that can be followed to set up an experiment in the future.

Published by the American Physical Society
2024