bluuebunny/crossref_metadata_2025_split huggingface dataset:
Stochastic Epigenetic Mutations: Reliable Detection and Associations with Cardiovascular Aging
Authors: Markov Yaroslav , Levine Morgan , Higgins-Chen Albert T. 
Published: December 2023

ABSTRACTStochastic Epigenetic Mutations (SEMs) have been proposed as novel aging biomarkers that have the potential to capture heterogeneity in age-related DNA methylation (DNAme) changes. SEMs are defined as outlier methylation patterns at cytosine-guanine dinucleotide (CpG) sites, categorized as hypermethylated (hyperSEM) or hypomethylated (hypoSEM) relative to a reference. While individual SEMs are rarely consistent across subjects, the SEM load – the total number of SEMs – increases with age. However, given poor technical reliability of measurement for many DNA methylation sites, we posited that many outliers might represent technical noise. Our study of whole blood samples from 36 individuals, each measured twice, found that 23.3% of hypoSEM and 45.6% hyperSEM are not shared between replicates. This diminishes the reliability of SEM loads, where intraclass correlation coefficients are 0.96 for hypoSEM and 0.90 for hyperSEM. We linked SEM reliability to multiple factors, including blood cell type composition, probe beta-value statistics, and presence of SNPs. A machine learning approach, leveraging these factors, filtered unreliable SEMs, enhancing reliability in a separate dataset of technical replicates from 128 individuals. Analysis of the Framingham Heart Study confirmed previously reported SEM association with mortality and revealed novel connections to cardiovascular disease. We discover that associations with aging outcomes are primarily driven by hypoSEMs at baseline methylated probes and hyperSEMs at baseline unmethylated probes, which are the same subsets that demonstrate highest technical reliability. These aging associations are preserved after filtering out unreliable SEMs and are enhanced after adjusting for blood cell composition. Finally, we utilize these insights to formulate best practices for SEM detection and introduce a novel R package,SEMdetectR, which utilizes parallel programming for efficient SEM detection with comprehensive options for detection, filtering, and analysis.
Tertiary-interaction characters enable fast, model-based structural phylogenetics beyond the twilight zone
Authors: Puente-Lelievre Caroline , Malik Ashar J. , Douglas Jordan , Ascher David , Baker Matthew , Allison Jane , Poole Anthony , Lundin Daniel , Fullmer Matthew , Bouckert Remco , Kim Hyunbin , Steinegger Martin , Matzke Nicholas 
Published: December 2023

AbstractProtein structure is more conserved than protein sequence, and therefore may be useful for phylogenetic inference beyond the “twilight zone” where sequence similarity is highly decayed. Until recently, structural phylogenetics was constrained by the lack of solved structures for most proteins, and the reliance on phylogenetic distance methods which made it difficult to treat inference and uncertainty statistically. AlphaFold has mostly overcome the first problem by making structural predictions readily available. We address the second problem by redeploying a structural alphabet recently developed for Foldseek, a highly-efficient deep homology search program. For each residue in a structure, Foldseek identifies a tertiary interaction closest-neighbor residue in the structure, and classifies it into one of twenty “3Di” states. We test the hypothesis that 3Dis can be used as standard phylogenetic characters using a dataset of 53 structures from the ferritin-like superfamily. We performed 60 IQtree Maximum Likelihood runs to compare structure-free, PDB, and AlphaFold analyses, and default versus custom model sets that include a 3DI-specific rate matrix. Analyses that combine amino acids, 3Di characters, partitioning, and custom models produce the closest match to the structural distances tree of Malik et al. (2020), avoiding the long-branch attraction errors of structure-free analyses. Analyses include standard ultrafast bootstrapping confidence measures, and take minutes instead of weeks to run on desktop computers. These results suggest that structural phylogenetics could soon be routine practice in protein phylogenetics, allowing the re-exploration of many fundamental phylogenetic problems.
Inhibition of hypoxia-inducible factors suppresses subretinal fibrosis
Authors: Shoda Chiho , Lee Deokho , Miwa Yukihiro , Yamagami Satoru , Nakashizuka Hiroyuki , Nimura Kazumi , Okamoto Kazutoshi , Kawagishi Hirokazu , Negishi Kazuno , Kurihara Toshihide 
Published: December 2023

AbstractAge-related macular degeneration (AMD) is a common cause of vision loss. The aggressive form of AMD is associated with ocular neovascularization and subretinal fibrosis, representing a responsive outcome against neovascularization mediated by epithelial-mesenchymal transition of retinal pigment epithelium cells. A failure of the current treatment (anti-vascular endothelial growth factor therapy) has also been attributed to the progression of subretinal fibrosis. Hypoxia-inducible factors (HIFs) increase gene expressions to promote fibrosis and neovascularization. HIFs act as a central pathway in the pathogenesis of AMD. HIF inhibitors may suppress ocular neovascularization. Nonetheless, further investigation is required to unravel the aspects of subretinal fibrosis. In this study, we used RPE-specific HIFs or von Hippel-Lindau (VHL, a regulator of HIFs) conditional knockout (cKO) mice, along with pharmacological HIF inhibitors, to demonstrate the suppression of subretinal fibrosis. Fibrosis was suppressed by treatments of HIF inhibitors, and similar suppressive effects were detected in RPE-specificHif1a/Hif2a-andHif1a-cKO mice. Promotive effects were observed in RPE-specificVhl-cKO mice, where fibrosis-mediated pathologic processes were evident. Marine products’ extracts and their component taurine suppressed fibrosis as HIF inhibitors. Our study shows critical roles of HIFs in the progression of fibrosis, linking them to the potential development of therapeutics for AMD.
Functional divergence shaped the network architecture of plant immune receptors
Authors: Huang Ching-Yi , Huang Yu-Seng , Sugihara Yu , Wang Hung-Yu , Huang Lo-Ting , Lopez-Agudelo Juan Carlos , Chen Yi-Feng , Lin Kuan-Yu , Chiang Bing-Jen , Toghani AmirAli , Kourelis Jiorgos , Derevnina Lida , Wu Chih-Hang 
Published: December 2023

AbstractIn solanaceous plants, several sensor NLRs and their helper NLRs, known as NRC, form a complex network to confer immunity against pathogens. While the sensor NLRs and downstream NRC helpers display diverse genetic compatibility, the evolution and molecular basis of the complex network structure remained elusive. Here we demonstrated that functional divergence of NRC3 variants has shaped the genetic architecture of the NLR network. Natural NRC3 variants form three allelic groups displaying distinct compatibilities with sensor NLRs. Ancestral sequence reconstruction and analyses of natural and chimeric variants identified six key amino acids involved in sensor-helper compatibility, with two residues critical for subfunctionalization. Co-functioning Rpi-blb2 and NRC3 variants showed stronger transient interactions upon effector detection, with NRC3 membrane-associated complexes forming subsequently. Our findings reveal how mutations in helper NLRs, particularly NRC3, have driven the evolution of their transient interactions with sensor NLRs, leading to subfunctionalization and contributing significantly to the complexity of the NRC network in plant immunity.TeaserHelper NLR subfunctionalization alters transient interactions with sensor NLRs, enhancing plant immune system complexity.
Optimizing representations for integrative structural modeling using Bayesian model selection
Authors: Arvindekar Shreyas , Pathak Aditi S. , Majila Kartik , Viswanath Shruthi 
Published: December 2023

AbstractMotivationIntegrative structural modeling combines data from experiments, physical principles, statistics of previous structures, and prior models to obtain structures of macromolecular assemblies that are challenging to characterize experimentally. The choice of model representation is a key decision in integrative modeling, as it dictates the accuracy of scoring, efficiency of sampling, and resolution of analysis. But currently, the choice is usually madead hoc, manually.ResultsHere, we report NestOR (Nested Sampling forOptimizingRepresentation), a fully automated, statistically rigorous method based on Bayesian model selection to identify the optimal coarse-grained representation for a given integrative modeling setup. Given an integrative modeling setup, it determines the optimal representations from given candidate representations based on their model evidence and sampling efficiency. The performance of NestOR was evaluated on a benchmark of four macromolecular assemblies.AvailabilityNestOR is implemented in the Integrative Modeling Platform (https://integrativemodeling.org) and is available athttps://github.com/isblab/nestor.Data for the benchmark is athttps://www.doi.org/10.5281/zenodo.10360718.Supplementary Information is available online.
Benchmarking the translational potential of spatial gene expression prediction from histology
Authors: Chan Adam S. , Wang Chuhan , Fu Xiaohang , Ghazanfar Shila , Kim Jinman , Patrick Ellis , Yang Jean YH 
Published: December 2023

AbstractSpatial transcriptomics has enabled the quantification of gene expression at spatial coordinates, offering crucial insights into molecular underpinnings of diseases. In light of this, several methods predicting spatial gene expression from paired histology images have offered the opportunity of enhancing the utility of readily obtainable and cost-effective haematoxylin-and-eosin-stained histology images. To this end, we conducted a comprehensive benchmarking study encompassing six developed methods. These methods were reproduced and evaluated using HER2-positive breast tumour and human cutaneous squamous cell carcinoma datasets, followed by external validation using The Cancer Genome Atlas data. Our evaluation incorporates diverse metrics which capture the performance of predicted gene expression, model generalisability, translational potential, usability and computational efficiency of each method. Our findings demonstrate the capacity of methods to spatial gene expression from histology and highlight key areas that can be addressed to support the advancement of this emerging field.
An integrative data-centric approach to derivation and characterization of an adverse outcome pathway network for cadmium-induced toxicity
Authors: Sahoo Ajaya Kumar , Chivukula Nikhil , Ramesh Kundhanathan , Singha Jasmine , Marigoudar Shambanagouda Rudragouda , Sharma Krishna Venkatarama , Samal Areejit 
Published: December 2023

AbstractCadmium is a prominent toxic heavy metal that contaminates both terrestrial and aquatic environments. Owing to its high biological half-life and low excretion rates, cadmium causes a variety of adverse biological outcomes. Adverse outcome pathway (AOP) networks were envisioned to systematically capture toxicological information to enable risk assessment and chemical regulation. Here, we leveraged AOP-Wiki and integrated heterogeneous data from four other exposome-relevant resources to build the first AOP network relevant for inorganic cadmium-induced toxicity. From AOP-Wiki, we filtered 309 high confidence AOPs, identified 312 key events (KEs) associated with inorganic cadmium, and thereafter, curated 30 cadmium relevant AOPs (cadmium-AOPs), using a data-centric approach. By constructing the undirected AOP network, we identified a large connected component of 18 cadmium-AOPs. Further, we analyzed the directed network of 59 KEs and 82 key event relationships (KERs) in the largest component using graph-theoretic approaches. Subsequently, we mined published literature using artificial intelligence-based tools to provide auxiliary evidence of cadmium association for all KEs in the largest component. Finally, we performed case studies to verify the rationality of cadmium-induced toxicity in humans and aquatic species. Overall, cadmium-AOP network constructed in this study will aid ongoing research in systems toxicology and chemical exposome.
Amino acid characteristics in protein native state structures
Authors: Škrbić Tatjana , Giacometti Achille , Hoang Trinh X. , Maritan Amos , Banavar Jayanth R. 
Published: December 2023

AbstractWe present a geometrical analysis of the protrusion statistics of side chains in more than 4,000 high-resolution protein structures. We employ a coarse-grained representation of the protein backbone viewed as a linear chain of Cαatoms and consider just the heavy atoms of the side chains. We study the large variety of behaviors of the amino acids based on both rudimentary structural chemistry as well as geometry. Our geometrical analysis uses a backbone Frenet coordinate system for the common study of all amino acids. Our analysis underscores the richness of the repertoire of amino acids that is available to nature to design protein sequences that fit within the putative native state folds.
Role of Ribeye PXDLS/T-binding cleft in normal synaptic ribbon function
Authors: Zhu Jie , Lv Caixia , Henry Diane , Viviano Stephen , Santos-Sacchi Joseph , Matthews Gary , Zenisek David 
Published: December 2023

AbstractNon-spiking sensory hair cells of the auditory and vestibular systems encode a dynamic range of graded signals with high fidelity by vesicle exocytosis at ribbon synapses. Ribeye, the most abundant protein in the synaptic ribbon, is composed of a unique A domain specific for ribbons and a B-domain nearly identical to the transcriptional corepressor CtBP2. CTBP2 and the B-domain of Ribeye contain a surface cleft that binds to proteins harboring a PXDLS/T peptide motif. Little is known about the importance of this binding site in synaptic function. Piccolo has a well-conserved PVDLT motif and we find that overexpressed Ribeye exhibits striking co-localization with Piccolo in INS-cells, while two separate mutants containing mutations in PXDLS/T-binding region, fail to co-localize with Piccolo. Similarly, co-transfected Ribeye and a piccolo fragment containing the PVDLT region co-localize in HEK cells. Expression of wild-type Ribeye-YFP in zebrafish neuromast hair cells returns electron densities to ribbon structures and mostly rescued normal synaptic transmission and morphological phenotypes in a mutant zebrafish lacking most Ribeye. By contrast, Ribeye-YFP harboring a mutation in the PXDLS/T-binding cleft resulted in ectopic electron dense aggregates that did not collect vesicles and the persistence of ribbons lacking electron densities. Furthermore, overexpression failed to return capacitance responses to normal levels. These results point toward a role for the PXDLS/T-binding cleft in the recruitment of Ribeye to ribbons and in normal synaptic function.Significance statementHair cell synaptic ribbons are evolutionarily conserved structures that appear dense in electron micrographs, extend from the release site into the cytoplasm and tether synaptic vesicles for release. Here, we show that Ribeye, the major component of the synaptic ribbon electron density is directed to ribbons via its PXDLS/T-binding site and that mutant isoforms of Ribeye with point mutations disrupting these interactions fail to rescue normal function in mutant zebrafish lacking most Ribeye.
A generative model of the hippocampal formation trained with theta driven local learning rules
Authors: George Tom M , Barry Caswell , Stachenfeld Kimberly , Clopath Claudia , Fukai Tomoki 
Published: December 2023

AbstractAdvances in generative models have recently revolutionised machine learning. Meanwhile, in neuroscience, generative models have long been thought fundamental to animal intelligence. Understanding the biological mechanisms that support these processes promises to shed light on the relationship between biological and artificial intelligence. In animals, the hippocampal formation is thought to learn and use a generative model to support its role in spatial and non-spatial memory. Here we introduce a biologically plausible model of the hippocampal formation tantamount to a Helmholtz machine that we apply to a temporal stream of inputs. A novel component of our model is that fast theta-band oscillations (5-10 Hz) gate the direction of information flow throughout the network, training it akin to a high-frequency wake-sleep algorithm. Our model accurately infers the latent state of high-dimensional sensory environments and generates realistic sensory predictions. Furthermore, it can learn to path integrate by developing a ring attractor connectivity structure matching previous theoretical proposals and flexibly transfer this structure between environments. Whereas many models trade-off biological plausibility with generality, our model captures a variety of hippocampal cognitive functions under one biologically plausible local learning rule.
Senolytic Intervention Improves Cognition, Metabolism, and Adiposity in Female APPNL-F/NL-FMice
Authors: Fang Yimin , Peck Mackenzie R. , Quinn Kathleen , Chapman Jenelle E. , Medina David , McFadden Samuel A. , Bartke Andrzej , Hascup Kevin N. , Hascup Erin R. 
Published: December 2023

AbstractSenescent cells accumulate throughout the body and brain contributing to unhealthy aging and Alzheimer’s disease (AD). The APPNL-F/NL-Famyloidogenic AD mouse model exhibits increased markers of senescent cells and the senescence-associated secretory phenotype (SASP) in visceral white adipose tissue before plaque accumulation and cognitive decline. We hypothesized that senolytic intervention would alleviate cellular senescence thereby improving spatial memory in APPNL-F/NL-Fmice. Thus, four month old male and female APPNL-F/NL-Fmice were treated monthly with vehicle, 5 mg/kg Dasatinib + 50 mg/kg Quercetin, or 100 mg/kg Fisetin. Blood glucose levels, energy metabolism, spatial memory, amyloid burden, and senescent cell markers were assayed. Dasatinib + Quercetin treatment in female APPNL-F/NL-Fmice increased oxygen consumption and energy expenditure resulting in decreased body mass. White adipose tissue mass was decreased along with senescence markers, SASP, blood glucose, and plasma insulin and triglycerides. Hippocampal senescence markers and SASP were reduced along with soluble and insoluble amyloid-β (Aβ)42and senescence associated-β-gal activity leading to improved spatial memory. Fisetin had negligible effects on these measures in female APPNL-F/NL-Fmice while neither senolytic intervention altered these parameters in the male mice. Considering women have a greater risk of dementia, identifying senotherapeutics appropriate for sex and disease stage is necessary for personalized medicine.
Corporate social responsibility performance and social reputation via corporate social responsibility awarding: is there a threshold effect?
Authors: Kuzey Cemil , Uyar Ali , Ellili Nejla Ould Daoud , Karaman Abdullah S. 
Published: December 2023

Purpose
This study aims to examine the potential threshold effect in the association between corporate social responsibility (CSR) performance and social reputation.

Design/methodology/approach
This study includes an international and cross-sector sample covering 41 countries, nine sectors and 45,395 firm-year observations. It applies a parabolic relationship, rather than linear regressions, between CSR engagement and social reputation via CSR awarding. This implies that CSR performance should increase until a certain point to gain a social reputation but then should decrease after reaching that threshold point considering limited financial resources.

Findings
The findings of country-industry-year fixed-effects logistic regressions confirm the threshold effect with an inverted U-shaped relationship between CSR and CSR awarding. More specifically, firms increase their environmental and social engagement until a certain point, and then they reduce it after reaching a social reputation. This finding is confirmed by three dimensions of the environmental pillar (i.e. resource use, emissions and eco-innovation) as well as four dimensions of the social pillar (i.e. workforce, human rights, community and product responsibility). The findings are robust to alternative samples, alternative methodology and endogeneity concerns.

Practical implications
The findings of this study have implications for firms about the better allocation of available funds between CSR and operations. The findings could be particularly useful for CSR teams/committees of the firms who formulate CSR policies and how to mobilize firm resources for better social enhancement via environmental and social reputation.

Originality/value
This study examines deeper the nature of the association between CSR engagement and social reputation and considers the possibility of an inverted U-shaped relationship between them. The determination of a threshold effect suggests that CSR engagement increases social reputation, but once it reaches a certain point, social reputation will decrease owing to financial resource constraints.
Parameters calculation method of energetic model for symmetrical static hysteresis loop and asymmetrical minor loop
Authors: Ji Junan , Zhao Zhigang , Zhang Shi , Chen Tianyuan 
Published: December 2023

Purpose
This paper aims to propose an energetic model parameter calculation method for predicting the materials’ symmetrical static hysteresis loop and asymmetrical minor loop to improve the accuracy of electromagnetic analysis of equipment.

Design/methodology/approach
For predicting the symmetrical static hysteresis loop, this paper deduces the functional relationship between magnetic flux density and energetic model parameters based on the materials’ magnetization mechanism. It realizes the efficient and accurate symmetrical static hysteresis loop prediction under different magnetizations. For predicting the asymmetrical minor loop, a new algorithm is proposed that updates the energetic model parameters of the asymmetrical minor loop to consider the return-point memory effect.

Findings
The comparison of simulation and experimental results verifies that the proposed parameters calculation method has high accuracy and strong universality.

Originality/value
The proposed parameter calculation method improves the existing parameter calculation method’s problem of relying on too much experimental data and inaccuracy. Consequently, the presented work facilitates the application of the finite element electromagnetic field analysis method coupling the hysteresis model.