bluuebunny/crossref_metadata_2025_split huggingface dataset:
TIDAL – Tool to Implement Developmental Analysis of Longitudinal data
Authors: Kwong Alex S. F. , Edmondson-Stait Amelia , Xu Eileen , Thompson Ellen J. , Parker Richard M. A. , Elhakeem Ahmed , Romaniuk Liana , Pearson Rebecca M. , Tilling Kate , Eley Thalia C. , McIntosh Andrew M , Whalley Heather C. 
Published: August 2024

AbstractMotivationGrowth curve modelling is one method used to model trajectories of traits and behaviours over time. However, accessing, analysing and interpreting trajectories requires statistical expertise, thereby creating potential barriers for users to implement and understand longitudinal traits. TIDAL is a user-friendly research tool designed to facilitate trajectory modelling by improving access, analysis and interpretation of trajectory and longitudinal data.ImplementationTIDAL is available in two formats: an R package and an online Shiny application. The R package can be used offline, negating the need to upload potentially sensitive data.General featuresTIDAL includes all the main steps of trajectory analysis including: 1) data preparation, (converting data from wide to long format); 2) data exploration, via basic plots and descriptive information; 3) analysis of trajectories using mixed effects modelling, interpretation of results, visualisation of trajectories, and extraction of key features (scores at different ages; area under the curve); and 4) interactions to derive population specific trajectories, combined with all the above. TIDAL is built with a simple graphical interface to guide users through each step. R syntax accompanies each step.AvailabilityBoth versions of TIDAL can be found here: [https://tidal-modelling.github.io/].
Results of the Protein Engineering Tournament: An Open Science Benchmark for Protein Modeling and Design
Authors: Armer Chase , Kane Hassan , Cortade Dana L. , Redestig Henning , Estell David A. , Yusuf Adil , Rollins Nathan , Spinner Hansen , Marks Debora , Brunette TJ , Kelly Peter J. , DeBenedictis Erika 
Published: August 2024

AbstractThe grand challenge of protein engineering is the development of computational models to characterize and generate protein sequences for arbitrary functions. Progress is limited by lack of 1) benchmarking opportunities, 2) large protein function datasets, and 3) access to experimental protein characterization. We introduce the Protein Engineering Tournament—a fully-remote competition designed to foster the development and evaluation of computational approaches in protein engineering. The tournament consists of anin silicoround, predicting biophysical properties from protein sequences, followed by anin vitroround where novel protein sequences are designed, expressed and characterized using automated methods. Upon completion, all datasets, experimental protocols, and methods are made publicly available. We detail the structure and outcomes of a pilot Tournament involving seven protein design teams, powered by six multi-objective datasets, with experimental characterization by our partner, International Flavors and Fragrances. Forthcoming Protein Engineering Tournaments aim to mobilize the scientific community towards transparent evaluation of progress in the field.Graphical Abstract
A posture subspace in primary motor cortex
Authors: Marino Patrick J. , Bahureksa Lindsay , Fernández Fisac Carmen , Oby Emily R. , Smoulder Adam L. , Motiwala Asma , Degenhart Alan D. , Grigsby Erinn M. , Joiner Wilsaan M. , Chase Steven M. , Yu Byron M. , Batista Aaron P. 
Published: August 2024

SummaryTo generate movements, the brain must combine information about movement goal and body posture. Motor cortex (M1) is a key node for the convergence of these information streams. How are posture and goal information organized within M1’s activity to permit the flexible generation of movement commands? To answer this question, we recorded M1 activity while monkeys performed a variety of tasks with the forearm in a range of postures. We found that posture- and goal-related components of neural population activity were separable and resided in nearly orthogonal subspaces. The posture subspace was stable across tasks. Within each task, neural trajectories for each goal had similar shapes across postures. Our results reveal a simpler organization of posture information in M1 than previously recognized. The compartmentalization of posture and goal information might allow the two to be flexibly combined in the service of our broad repertoire of actions.
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

AbstractAligning 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.
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

AbstractA 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

AbstractResistance 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.
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

AbstractMulti-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

AbstractPrimary 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

AbstractTermites, 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

AbstractHaemophagocytic 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

AbstractTraceability 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 summaryEarly 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

AbstractIterating 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

ABSTRACTThe 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.