bluuebunny/crossref_metadata_2025_split huggingface dataset:
ApoDock: Ligand-Conditioned Sidechain Packing for Flexible Molecular Docking
Authors: Luo Ding , Qu Xiaoyang , Lu Dexin , Wang Yiqiu , Dong Lina , Wang Binju 
Published: November 2024

AbstractMolecular docking is a crucial technique for elucidating protein-ligand interactions. Machine learning-based docking methods offer promising advantages over traditional approaches, with significant potential for further development. However, many current machine learning-based methods face challenges in ensuring the physical plausibility of generated docking poses. Additionally, accommodating protein flexibility remains difficult for existing methods, limiting their effectiveness in real-world scenarios. Diffusion based models has already show a good solution of those problems, such as Alphafold3(AF3). Herein, we present ApoDock, a modular docking paradigm that combines machine learning-driven conditional sidechain packing based on protein backbone and ligand information with traditional sampling methods to ensure physically realistic poses. With accurate sidechain packing and physical based pose sampling, ApoDock demonstrates competitive performance across diverse applications, highlighting its potential as a valuable tool for protein-ligand binding studies and related applications.
DeepAssembly2: A Web Server for Protein Complex Structure Assembly Based on Domain-Domain Interactions
Authors: Xia Yuhao , Pu Yilin , Wang Suhui , Zhuang Jianan , Liu Dong , Hou Minghua , Zhang Guijun 
Published: November 2024

AbstractProteins often perform biological functions by forming complexes, thereby accurately predicting the structure of protein complexes is crucial to understanding and mastering their functions, as well as facilitating drug discovery. Protein monomeric structure prediction has made a breakthrough in recent years, but the accurate prediction of complex structure remains a challenge. In this work, we present DeepAssembly2, a web server for automatically assembling protein complex structure based on domain-domain interactions. First, the features are constructed according to the input complex sequence and monomeric structures, then these features are used to predict the inter-chain residue distance through a deep learning model, and finally, the complex structure is assembled under the guidance of inter-chain residue distances. Compared with the previously developed version, DeepAssembly2 is trained on a newly constructed inter-chain domain-domain interaction dataset. Meanwhile, several important features have been added, such as Interface Residue Propensity and Ultrafast Shape Recognition. In addition, we introduced the inter-chain residue distance from the AlphaFold-Multimer model to further improve the accuracy. Finally, we also integrate our recently developed model quality assessment method to select the output models. The performance of DeepAssembly2 is significantly improved compared with the previous version, providing a solution for large protein complex structure modeling through divide-and-conquer assembly strategy, and is expected to provide new insights and an effective tool for drug development, vaccine design, etc. The web server of DeepAssembly2 is freely available athttp://zhanglab-bioinf.com/DeepAssembly/.
Leveraging Persistent Homology of Eye Movements for Neural Disorder Screening
Authors: He Dongcheng , Wang Shaoying , Ogmen Haluk 
Published: November 2024

AbstractAbnormal ocular behaviors are associated with numerous neural disorders, detectable through specific eye movement patterns. Eye tracking—a non-invasive, accessible method—has thus been investigated as a tool for the automated diagnosis of these disorders. However, traditional eye movement feature extraction methods have limitations and are not universally applicable across diverse tasks. In this study, we present a novel feature extraction approach using Persistent Homology, a topological data analysis technique, to capture spatial and temporal topological features from eye movement data. Topological features retain multiple theoretical properties, making them robust for identifying abnormal eye movements and broadly applicable across tasks. By using only spatio-temporal topological features, our approach demonstrated promising performance in screening dyslexia and ADHD with a simple shallow perceptron classifier containing one or two hidden layers. These results support the informative validity of topological features as well as the efficacy of our proposed methods for extracting them.
The Lorenz’s side of Gene Set Enrichment Analysis: Similarity and divergences of the Gene Set Enrichment Analysis from the measure of wealth inequality
Authors: Pagnotta Stefano Maria 
Published: November 2024

AbstractIn the age of microarrays (about 20 years ago), the poor quality of expression levels prompted the development of methods for associating a set of significant genes with their biological meaning. A fundamental shift in methodology was the consideration of the entire gene profile, summarizing the differential level of genes measured in two conditions. A preliminary proposal was to mimic the two samples Kolmogorov-Smirnov test. Still, the winning idea was to introduce a system of weights in constructing the empirical distribution functions. Since 2005, the Gene Set Enrichment Analysis has emerged as the most well-known methodology from these premises.This method is always referred to as based on a weighted Kolmogorov-Smirnov test. Sometimes, what is introduced as an innovation that improves a standard methodology leads to a well-known tool in a different science subject. While the accumulation of counts generates the empirical distribution function, the accumulation of weights, as defined in GSEA, leads to a function known as the Lorenz curve, introduced in 1905. Such a tool is a cornerstone in welfare studies to measure the concentration or equidistribution of richness in populations.This paper reviews the essentials of the Lorenz curve and Gene Set Enrichment Analysis. It shows that the test statistic of the last is linked to the null hypothesis comparing two Lorenz curves. The new light of the enrichment procedure makes consistent analytical tools and conceptual formulation of the methodology.
Molecular patterns of evolutionary changes throughout the whole nervous system of multiple nematode species
Authors: Toker Itai Antoine , Ripoll-Sánchez Lidia , Geiger Luke T. , Saini Karan S. , Beets Isabel , Vértes Petra E. , Schafer William R. , Ben-David Eyal , Hobert Oliver 
Published: November 2024

AbstractOne avenue to better understand brain evolution is to map molecular patterns of evolutionary changes in neuronal cell types across entire nervous systems of distantly related species. Generating whole-animal single-cell transcriptomes of three nematode species from theCaenorhabditisgenus, we observed a remarkable stability of neuronal cell type identities over more than 45 million years of evolution. Conserved patterns of combinatorial expression of homeodomain transcription factors are among the best classifiers of homologous neuron classes. Unexpectedly, we discover an extensive divergence in neuronal signaling pathways. While identities of neurotransmitter-producing neurons (glutamate, acetylcholine, GABA and several monoamines) remain stable, ionotropic and metabotropic receptors for all these neurotransmitter systems show substantial divergence, resulting in more than half of all neuron classes changing their capacity to be receptive to specific neurotransmitters. Neuropeptidergic signaling is also remarkably divergent, both at the level of neuropeptide expression and receptor expression, yet the overall dense network topology of the wireless neuropeptidergic connectome remains stable. Novel neuronal signaling pathways are suggested by our discovery of small secreted proteins that show no obvious hallmarks of conventional neuropeptides, but show similar patterns of highly neuron-type-specific and highly evolvable expression profiles. In conclusion, by investigating the evolution of entire nervous systems at the resolution of single neuron classes, we uncover patterns that may reflect basic principles governing evolutionary novelty in neuronal circuits.
The Relationship between Latent Inhibition, Divergent Thinking, and Eyewitness Memory: A Study on Attention to Irrelevant Stimuli
Authors: Badiola-Lekue Ixone , Arriola Naiara , Rodríguez Gabriel 
Published: November 2024

AbstractLatent inhibition is a retardation in learning about a stimulus due to its prior exposure without explicit consequences. It has been suggested that individuals who tend to show less latent inhibition possess a "leaky" attentional style, finding it difficult to inhibit the processing of irrelevant information, which would manifest as an ability to generate uncommon and creative ideas. In the present study, we tested this hypothesis within a new framework—the field of eyewitness memory—by investigating whether the degree of attenuated latent inhibition is associated with the inclusion of more peripheral (seemingly irrelevant) information in testimonies about a witnessed event. In an experiment involving 116 university students, the LI Group was pre-exposed without masking to a target auditory stimulus without consequences, while the CTRL Group did not receive this pre-exposure. Subsequently, both groups engaged in a learning phase where they had to learn the association between the target stimulus and a novel outcome. A latent inhibition effect was observed, with participants in the LI Group showing retardation in learning this association compared to the CTRL Group.Additionally, all participants completed the Alternative Uses Task to assess divergent thinking and provided eyewitness testimonies based on the viewing of a video of a criminal event. We confirmed the known relationship between attenuated latent inhibition and creativity, finding that the lesser the latent inhibition exhibited, the higher the performance on the Alternative Uses Task. Moreover, we found that a lower degree of latent inhibition was associated with a higher number of peripheral details included in the testimonies. These results are discussed in terms of the leaky attention hypothesis, and an alternative explanation based on cognitive flexibility. According to this, individuals exhibiting attenuated latent inhibition may have an intact capacity to ignore irrelevant stimuli but would be highly efficient at rapidly redirecting their attention when changes occur.
Mitophagy Facilitates Cytosolic Proteostasis to Preserve Cardiac Function
Authors: Rawnsley David R. , Islam Moydul , Zhao Chen , Kargar Gaz Kooh Yasaman , Mendoza Adelita , Navid Honora , Kumari Minu , Guan Xumin , Murphy John T. , Nigro Jess , Kovacs Attila , Mani Kartik , Huebsch Nathaniel , Ma Xiucui , Diwan Abhinav 
Published: November 2024

AbstractBackgroundProtein quality control (PQC) is critical for maintaining sarcomere structure and function in cardiac myocytes, and mutations in PQC pathway proteins, such as CRYAB (arginine to glycine at position 120, R120G) and BAG3 (proline to lysine at position 209, P209L) induce protein aggregate pathology with cardiomyopathy in humans. Novel observations in yeast and mammalian cells demonstrate mitochondrial uptake of cytosolic protein aggregates. We hypothesized that mitochondrial uptake of cytosolic protein aggregates and their removal by mitophagy, a lysosomal degradative pathway essential for myocardial homeostasis, facilitates cytosolic protein quality control in cardiac myocytes.MethodsMice with inducible cardiac myocyte specific ablation of TRAF2 (TRAF2icKO), which impairs mitophagy, were assessed for protein aggregates with biochemical fractionation and super-resolution imaging in comparison to floxed controls. Induced pluripotent stem cell (iPSC)-derived cardiac myocytes with R120G knock-in to theCRYABlocus were assessed for localization of the CRYAB protein. Transgenic mice expressing R120G CRYAB protein (R120G-TG) were subjected to both TRAF2 gain-of-function (with AAV9-cardiac Troponin T promoter-driven TRAF2 transduction) and TRAF2 loss-of-function (with tamoxifen-inducible ablation of oneTraf2allele) in cardiac myocytes to determine the effect of mitophagy modulation on cardiac structure, function, and protein aggregate pathology.ResultsCardiomyocyte-specific ablation of TRAF2 results accumulation of mitochondrial and cytosolic protein aggregates and DESMIN mis-localization to protein aggregates. Isolated mitochondria take up cardiomyopathy-associated aggregate-prone cytosolic chaperone proteins, namely arginine to glycine (R120G) CRYAB mutant and proline to lysine (P209L) BAG3 mutant. R120G-CRYAB mutant protein increasingly localizes to mitochondria in human and mouse cardiomyocytes. R120G-TG mice demonstrate upregulation of TRAF2 in the mitochondrial fraction with increased mitophagy as compared with wild type. Adult-onset inducible haplo-insufficiency of TRAF2 resulted in accelerated mortality, impaired left ventricular systolic function and increased protein aggregates in R120G-TG mice as compared with controls. Conversely, AAV9-mediated TRAF2 transduction in R120G-TG mice reduced mortality and attenuated left ventricular systolic dysfunction, with reduced protein aggregates and restoration of normal localization of DESMIN, a cytosolic scaffolding protein chaperoned by CRYAB, as compared with control AAV9-GFP group.ConclusionsTRAF2-mediated mitophagy in cardiac myocytes facilitates removal of cytosolic protein aggregates and can be stimulated to ameliorate proteotoxic cardiomyopathy.
Impacts of urbanization on the health of American Robins (Turdus migratorus) in Chicagoland
Authors: Riccardi Anna , Douglass Kimberly R. , Jackson Vera Soloview , Dehnert Gavin K. , Herbst Hannah , Grewe Felix , Walker Morgan , Magle Seth , Murray Maureen H. , Adams Henry , Brook Cara E. , Ruhs Emily Cornelius 
Published: November 2024

AbstractWild animals in urbanized environments face several unique challenges, including increased anthropogenic stressors, decreased natural food availability and quality, and increased pollutant exposure. While some work has shown that individual urbanization stressors can have negative impacts on aspects of wild bird physiology, other studies have demonstrated ambiguous or sometimes positive interactions. As such, the impact of multiple, coincident urban stressors on avian health still needs to be fully understood. Here, we addressed this knowledge gap by holistically measuring multiple physiological markers of American robin (Turdus migratorius) health across a gradient of urbanization throughout Chicagoland. We predicted that birds using highly urbanized habitats would experience higher heavy metal contamination, higher oxidative stress, lower body condition, higher avian malaria burden, and decreased measures of immune response compared to exurban birds in the Chicagoland area. Multiple linear models revealed that robins in more urbanized areas exhibited higher levels of heavy metal contamination and slightly elevated levels of associated physiological impairments compared to their counterparts in exurban sites. Additionally, noise and light pollution were significantly associated with oxidative stress and infection status, respectively, albeit in different directions. Overall, our findings underscore how the complex environmental changes that accompany urbanization can impact the health of urban bird populations.
Evidence for non-optimal codon choice in highly transcribed sex-biased genes ofDrosophila melanogaster
Authors: Whittle Carrie A. , Extavour Cassandra G. 
Published: November 2024

AbstractBiases in synonymous codon use occur across multicellular organisms. Optimal codons, defined as those most commonly used in highly transcribed genes, are thought to arise from selection for cost-efficient translation, which would favor codons with abundant matching tRNAs. Such presumed selection is described as optimal codon choice. Non-optimal codons, defined as those least commonly used in highly transcribed genes, may in principle also play important roles, including regulating protein folding or mRNA translation. However, the dynamics of non-optimal codon use remain understudied. Here we rigorously examine non-optimal codon use, using sex-biased genes expressed in the gonads ofDrosophila melanogasteras a case study. Using this model, we show that as genes evolve sex-biased expression, they tend to evolve a preference for non-optimal codon use, and that this preference is stronger for testis-biased genes than for ovary-biased genes. Further, from thorough analyses of each of 18 degenerate amino acids, we found evidence that the use of non-optimal codons is not random. Instead, specific non-optimal codons are favored over their synonymous non-optimal codons, an effect again especially pronounced in testis-biased genes. Moreover, we found that non-optimal codon use is positively linked to elevated disorder of the encoded proteins, a pattern most consequential in testis-biased genes. Remarkably, all 18 degenerate amino acids were associated with higher disorder when they were encoded by the identified primary non-optimal codon, than when encoded by its sister optimal codon. We hypothesize that selection may have acted to promote non-optimal codon choice to regulate translation. We discuss the putative roles of tRNA gene copy numbers, pleiotropy, and sex-biased expression in the evolution of this level of gene regulation.Classification:Research Report, Genetics
Glutaminolysis promotes the function of follicular helper T cells in lupus-prone mice
Authors: Choi Seung-Chul , Ge Yong , Joshi Milind V. , Jimenez Damian , Padilla Lauren T. , LaPlante Cassandra , Rathmell Jeffery C. , Mohamadzadeh Mansour , Morel Laurence 
Published: November 2024

AbstractGlutamine metabolism is essential for T cell activation and functions. The inhibition of glutaminolysis impairs Th17 cell differentiation and alters Th1 cell functions. There is evidence for an active glutaminolysis in the immune cells of lupus patients. Treatment of lupus-prone mice with glutaminolysis inhibitors ameliorated disease in association with a reduced frequency of Th17 cells. This study was performed to determine the role of glutaminolysis in murine Tfh cells, a critical subset of helper CD4+T cells in lupus that provide help to autoreactive B cells to produce autoantibodies. We showed that lupus Tfh present a high level of glutamine metabolism. The pharmacological inhibition of glutaminolysis with DON had little effect on the Tfh cells of healthy mice, but it reduced the expression of the critical costimulatory molecule ICOS on lupus Tfh cells, in association with a reduction of autoantibody production, germinal center B cell dynamics, as well as a reduction of the frequency of atypical age-related B cells and plasma cells. Accordingly, profound transcriptomic and metabolic changes, including an inhibition of glycolysis, were induced in lupus Tfh cells by DON, while healthy Tfh cells showed little changes. The T cell-specific inhibition of glutaminolysis by deletion of the gene encoding for the glutaminase enzyme GLS1 largely phenocopied the effects of DON on Tfh cells and B cells in an autoimmune genetic background with little effect in a congenic control background. These results were confirmed in an induced model of lupus. Finally, we showed that T cell-specificGls1deletion impaired T- dependent humoral responses in autoimmune mice as well as their Tfh response to a viral infection. Overall, these results demonstrated a greater intrinsic requirement of lupus Tfh cells for their helper functions, and they suggest that targeting glutaminolysis may be beneficial to treat lupus.
A Versatile Anti-CRISPR Platform for Opto- and Chemogenetic Control of CRISPR-Cas9 and Cas12 across a Wide Range of Orthologs
Authors: Brenker Luca , Aschenbrenner Sabine , Bubeck Felix , Staykov Kaloyan , Gebhardt Carolin , Wolf Benedict , Jendrusch Michael , Kröll Ann-Sophie , Mathony Jan , Niopek Dominik 
Published: November 2024

ABSTRACTCRISPR-Cas technologies have revolutionized life sciences by enabling programmable genome editing across diverse organisms. Achieving dynamic and precise control over CRISPR-Cas activity with exogenous triggers, such as light or chemical ligands, remains an important need. Existing tools for CRISPR-Cas control are often limited to specific Cas orthologs or selected applications, restricting their versatility. Anti-CRISPR (Acr) proteins, natural inhibitors of CRISPR-Cas systems, provide a flexible regulatory layer but are constitutively active in their native forms.In this study, we built on our previously reported concept for optogenetic CRISPR-Cas control with engineered, light-switchable anti-CRISPR proteins and expanded it from ortholog-specific Acrs towards AcrIIA5 and AcrVA1, broad-spectrum inhibitors of CRISPR-Cas9 and -Cas12a, respectively. We then conceived and implemented a novel, chemogenetic anti-CRISPR platform based on engineered, circularly permuted ligand receptor domains of human origin, that together respond to six different, clinically-relevant drugs. The resulting toolbox achieves both optogenetic and chemogenetic control of genome editing in human cells with a wide range of CRISPR-Cas effectors, including type II-A and -C CRISPR-Cas9s, and -Cas12a. In sum, this work establishes a versatile platform for multidimensional control of CRISPR-Cas systems, with immediate applications in basic research and biotechnology and potential for therapeutic use in the future.
Absolute quantification of cerebral metabolites using 2D1H-MRSI with quantitative MRI-based water reference
Authors: Thomas Dennis C. , Alcicek Seyma , Manzhurtsev Andrei , Hattingen Elke , Wenger Katharina J. , Pilatus Ulrich 
Published: November 2024

AbstractPurposeMetabolite concentrations are valuable biomarkers in brain tumors (BT). However, correction of water relaxation effects often requires time-consuming quantitative MRI (qMRI) sequences on top of a lengthy spectroscopic water reference acquisition. The goal of this work was to develop and validate a fast metabolite quantification method where a 2D spectroscopic water reference acquisition is obtained using a fast qMRI protocol and single-voxel STEAM sequence.MethodsA 2D sLASER sequence was acquired for MRSI. An 8-minute qMRI protocol was also acquired. A single-voxel unsuppressed water signal was acquired using a STEAM sequence. The H2O map, obtained from qMRI, was calibrated based on the STEAM-signal to obtain the spectroscopic water reference (proposed method). Five healthy volunteers and one BT patient were scanned at 3T. Concentrations obtained using the proposed and two reference methods, one where water relaxation effects were corrected using literature values (Reference method) and one where they were corrected using qMRI-derived values (Reference method with qMRI) were compared.ResultsIn healthy subjects, WM metabolite concentrations obtained using water relaxation using literature values (Reference method) significantly differed from those using individual-specific corrections (Reference method with qMRI and proposed method). Bland-Altman analyses revealed a very low bias and SD of the differences between the ‘Reference method with qMRI’ and the ‘proposed-method’ (Bias<0.5% and SD<10%). The BT regions showed a ∼15% underestimation of metabolite concentrations using the ‘Reference method’.ConclusionFor metabolite quantification, accurate water referencing with individual-specific corrections for water relaxation times was obtained in 8 minutes using the proposed method.