bluuebunny/crossref_metadata_2025_split huggingface dataset:
MIGRENE: The toolbox for microbial and individualized GEMs, reactobiome and community network modelling
Authors: Bidkhori Gholamreza , Shoaie Saeed 
Published: September 2023

AbstractMotivationUnderstanding microbial metabolism is crucial for evaluating shifts in human host-microbiome interactions during health and disease. However, the primary hurdle in the realm of constraint-based modeling and genome-scale metabolic models (GEMs) pertaining to host-microbiome interactions lies in the efficient utilization of metagenomic data for constructing GEMs that encompass unexplored and uncharacterized genomes. Challenges persist in effectively employing metagenomic data to address individualized microbial metabolism to investigate host-microbiome interactions.ResultTo tackle this issue, we have created a computational framework designed for personalized microbiome metabolism. This framework takes into account factors such as microbiome composition, metagenomic species profiles and microbial gene catalogues. Subsequently, it generates GEMs at microbial level and individualized microbiome metabolism, including reaction richness, reaction abundance, reactobiome, individualized reaction set enrichment (iRSE), and community models.Availability and implementationThe MIGRENE toolbox is freely available at our GitHub repositoryhttps://github.com/sysbiomelab/MIGRENE. Comprehensive tutorials on the GitHub were provided for each step of the workflow.
Human deleterious mutation rate implies high fitness variance, with declining mean fitness compensated by rarer beneficial mutations of larger effect
Authors: Matheson Joseph , Bertram Jason , Masel Joanna 
Published: September 2023

AbstractEach new human has an expectedUd=2 - 10 new deleterious mutations. This deluge of deleterious mutations cannot all be purged, and therefore accumulate in a declining fitness ratchet. Using a novel simulation framework designed to efficiently handle genome-wide linkage disequilibria across many segregating sites, we find that rarer, beneficial mutations of larger effect are sufficient to compensate fitness declines due to the fixation of many slightly deleterious mutations. Drift barrier theory posits a similar asymmetric pattern of fixations to explain ratcheting genome size and complexity, but in our theory, the cause isUd>1 rather than small population size. In our simulations,Ud∼2 - 10 generates high within-population variance in relative fitness; two individuals will typically differ in fitness by 15- 40%.Ud∼2 - 10 also slows net adaptation by ∼13%-39%. Surprisingly, fixation rates are more sensitive to changes in the beneficial than the deleterious mutation rate, e.g. a 10% increase in overall mutation rate leads to faster adaptation; this puts to rest dysgenic fears about increasing mutation rates due to rising paternal age.
The universe is asymmetric, the mouse brain too
Authors: Rivera-Olvera Alejandro , Houwing Danielle J. , Ellegood Jacob , Masifi Shang , Martina Stephany LL. , Silberfeld Andrew , Pourquie Olivier , Lerch Jason P. , Francks Clyde , Homberg Judith R. , van Heukelum Sabrina , Grandjean Joanes 
Published: September 2023

AbstractHemispheric brain asymmetry is a basic organizational principle of the human brain and has been implicated in various psychiatric conditions, including autism spectrum disorder. Brain asymmetry is not a uniquely human feature and is observed in other species such as the mouse. Yet, asymmetry patterns are generally nuanced, and substantial sample sizes are required to detect these patterns. In this pre-registered study, we use a mouse dataset from the Province of Ontario Neurodevelopmental Network, which comprises structural MRI data from over 2000 mice, including genetic models for autism spectrum disorder, to reveal the scope and magnitude of hemispheric asymmetry in the mouse. Our findings demonstrate the presence of robust hemispheric asymmetry in the mouse brain, such as larger right hemispheric volumes towards the anterior pole and larger left hemispheric volumes toward the posterior pole, opposite to what has been shown in humans. This suggests the existence of species-specific traits. Further clustering analysis identified distinct asymmetry patterns in autism spectrum disorder models, a phenomenon that is also seen in atypically developing participants. Our study shows potential for the use of mouse models in studying the biological bases of typical and atypical brain asymmetry but also warrants caution as asymmetry patterns seem to differ between humans and mice.
Toxicity testing of two pesticides against the Carthusian snailin vitro
Authors: Bashandy A.S. , Awwad M.H 
Published: September 2023

AbstractIn this work, the land snail,Monacha cartusiana, was studied to assess the deadly toxic activity of two pesticides (lambda and methomyl) on this snail invitro, utilizing contact and dipping techniques. The results revealed that methomyl was more effective against snails compared with lambda in both methods of treatment. However, the contact application strategy resulted in greater death rates than the poison dipping studies. Accordingly, the mortality rate was increased by increasing concentration, with contact technique which recorded 96.3% and 69.99±15.1% deaths by dipping way on concentration 3%. For this reason, the percent Lethal Concentration fifty (LC50) was 1.30% for one day and 1.67% for seven days for methomyl by contact and dipping techniques, respectively. On the other hand, the LC50for lambda pesticide was achieved at 1.45% by contact method but was 7.51% by using the dipping application within ten days. As a result, mortality was greater after contact application than after dipping, and methomyl was disclosed to be more poisonous than lambda as a molluscicide.
Penile cavernous sinusoids are Prox1-positive hybrid vessels
Authors: Schnabellehner Sarah , Kraft Marle , Schoofs Hans , Ortsäter Henrik , Mäkinen Taija 
Published: September 2023

AbstractEndothelial cells (ECs) of blood and lymphatic vessels have distinct identity markers that define their specialized functions. Recently, specialized hybrid vasculatures with both blood and lymphatic vessel-specific features have been discovered in multiple tissues. Here, we identify the penile cavernous sinusoidal (pc-S) blood vasculature as a new hybrid vascular bed expressing key lymphatic EC identity genesProx1, Vegfr3andLyve1. Using single cell transcriptome data of human corpus cavernosum tissue, we found heterogeneity within pc-S endothelia and observed distinct phenotypic alterations related to inflammation response in hybrid ECs in erectile dysfunction. Molecular, ultrastructural and functional studies further establish shared hybrid identity of pc-Ss in mouse, and reveal their morphological adaptations and ability to perform lymphatic-like function in draining high molecular weight tracers. Interestingly, we found that inhibition of the key lymphangiogenic growth factor VEGF-C did not block the development of pc-Ss in mice, distinguishing them from other lymphatic and hybrid vessels analyzed so far. Our findings provide a detailed molecular characterization of hybrid pc-Ss and pave the way for the identification of molecular targets for therapies in conditions of dysregulated penile vasculature, including erectile dysfunction.
Assessing Per- and Polyfluoroalkyl Substances (PFAS) in Fish Fillet Using Non-Targeted Analyses
Authors: Boatman Anna K. , Chappel Jessie R. , Polera Madison E. , Dodds James N. , Belcher Scott M. , Baker Erin S. 
Published: September 2023

ABSTRACTPer- and polyfluoroalkyl substances (PFAS) are a class of thousands of man-made chemicals that are persistent and highly stable in the environment. Fish consumption has been identified as a key route of PFAS exposure for humans. However, routine fish monitoring targets only a handful of PFAS, and non-targeted analyses have largely only evaluated fish from heavily PFAS-impacted waters. Here, we evaluated PFAS in fish fillets from recreational and drinking water sources in central North Carolina to assess whether PFAS are present in these fillets that would not be detected by conventional targeted methods. We used liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) to collect full scan feature data, performed suspect screening using an in-house library of 100 PFAS for high confidence feature identification, searched for additional PFAS features using non-targeted data analyses, and quantified perfluorooctane sulfonic acid (PFOS) in the fillet samples. A total of 36 PFAS were detected in the fish fillets, including 19 that would not be detected using common targeted methods, with a minimum of 6 and a maximum of 22 in individual fish. Median fillet PFOS levels were concerningly high at 11.6 to 42.3 ppb, and no significant correlation between PFOS levels and number of PFAS per fish was observed. Future PFAS monitoring in this region should target more of these 36 PFAS, and other regions not considered heavily PFAS contaminated should consider incorporating non-targeted analyses into ongoing fish monitoring studies.SYNOPSISConcerningly high PFOS levels were detected in fish fillets from recreational and drinking water sources in central North Carolina. Of the 36 total PFAS identified, 19 would not be detected using routine targeted monitoring methods.GRAPHICAL ABSTRACTFor use in table of contents only
Self-generating autocatalytic networks: structural results, algorithms, and their relevance to evolutionary processes
Authors: Huson Daniel , Xavier Joana C. , Steel Mike 
Published: September 2023

AbstractThe concept of an autocatalytic network of reactions that can form and persist, starting from just an available food source, has been formalised by the notion of a Reflexively-Autocatalytic and Food generated (RAF) set. The theory and algorithmic results concerning RAFs have been applied to a range of settings, from metabolic questions arising at the origin of life, to ecological networks, and cognitive models in cultural evolution. In this paper, we present new structural and algorithmic results concerning RAF sets, by studying more complex modes of catalysis that allow certain reactions to require multiple catalysts (or to not require catalysis at all), and discuss the differing ways catalysis has been viewed in the literature. We then focus on the structure and analysis of minimal RAFs, and derive structural results and polynomial-time algorithms, with applications to metabolic network data described briefly.
Meisoindigo: An Effective Inhibitor of SARS-CoV-2 Main Protease Revealed by Yeast System
Authors: Grabiński Wojciech , Kicińska Anna , Kosicka Ewa , Baranek-Grabińska Martyna , Hejenkowska Ewelina D , Budzik Joanna , Śliska Paulina , Śliwińska Weronika , Karachitos Andonis 
Published: September 2023

AbstractThe COVID-19 pandemic caused by SARS-CoV-2 has had a significant impact on global health and the global economy. Despite the availability of vaccines, limited accessibility and vaccine hesitancy pose challenges in controlling the spread of the disease. Effective therapeutic strategies, including antiviral drugs, are needed to combat the future spread of new SARS-CoV-2 virus variants. The main protease (Mpro) is a critical therapeutic target for COVID-19 medicines, as its inhibition impairs viral replication. However, the use of substances that inhibit Mpro may induce selection pressure. Thus, it is vital to monitor viral resistance to known drugs and to develop new drugs. Here, we have developed a yeast system for the identification of Mpro inhibitors as an alternative to costly and demanding high-biosecurity procedures. The system is based on stable expression of Mpro and does not require selection media. Yeast can be cultured on a rich carbon source, providing rapid growth and screening results. The designed tool was subsequently used to screen the FDA-Approved Drug Library. Several chemicals with Mpro inhibitory properties were identified. We found that meisoindigo, which was not previously known to have the potential to inhibit Mpro, was highly effective. Our results may promote the development of new derivatives with therapeutic properties against SARS-CoV-2 and other beta-coronaviruses.
Structure of Native Chromatin Fibres Revealed by Cryo-ETin situ
Authors: Hou Zhen , Nightingale Frank , Zhu Yanan , MacGregor-Chatwin Craig , Zhang Peijun 
Published: September 2023

AbstractThe structure of chromatin plays pivotal roles in regulating gene transcription, DNA replication and repair, and chromosome segregation. This structure, however, remains elusive. Using cryo-FIB and cryo-ET, we delineated the 3D architecture of native chromatin fibres in intact interphase human T-lymphoblasts and determined thein-situstructures of nucleosomes in different conformations. These chromatin fibres are not structured as uniform 30 nm one-start or two-start filaments but are composed of relaxed, variable zigzag organizations of nucleosomes connected by straight linker DNA. Nucleosomes with little H1 and linker DNA density were distributed randomly without any spatial preference. This work sets a precedent for future high-resolution investigations on native chromatin structuresin-situat both a single-nucleosome level and a population level under many different cellular conditions in health and disease.
Mechanosensing through talin 1 contributes to tissue mechanical homeostasis
Authors: Chanduri Manasa V.L. , Kumar Abhishek , Weiss Dar , Emuna Nir , Barsukov Igor , Shi Muisi , Tanaka Keiichiro , Wang Xinzhe , Datye Amit , Kanyo Jean , Collin Florine , Lam TuKiet , Schwarz Udo D. , Bai Suxia , Nottoli Timothy , Goult Benjamin T , Humphrey Jay D. , Schwartz Martin A 
Published: September 2023

AbstractIt is widely believed that tissue mechanical properties, determined mainly by the extracellular matrix (ECM), are actively maintained. However, despite its broad importance to biology and medicine, tissue mechanical homeostasis is poorly understood. To explore this hypothesis, we developed mutations in the mechanosensitive protein talin1 that alter cellular sensing of ECM stiffness. Mutation of a novel mechanosensitive site between talin1 rod domain helix bundles 1 and 2 (R1 and R2) shifted cellular stiffness sensing curves, enabling cells to spread and exert tension on compliant substrates. Opening of the R1-R2 interface promotes binding of the ARP2/3 complex subunit ARPC5L, which mediates the altered stiffness sensing. Ascending aortas from mice bearing these mutations show increased compliance, less fibrillar collagen, and rupture at lower pressure. Together, these results demonstrate that cellular stiffness sensing regulates ECM mechanical properties. These data thus directly support the mechanical homeostasis hypothesis and identify a novel mechanosensitive interaction within talin that contributes to this mechanism.
A Three-Stage Algorithm for Quantification of the MMSE Interlocking Pentagon Areas
Authors: Kim Namhee , Truty Timothy , Han S. Duke , Heo Moonseong , Buchman Aron S. , Bennett David A. , Tasaki Shinya 
Published: September 2023

ABSTRACTThe Mini-Mental State Examination (MMSE) is a widely employed assessment tool for measuring the severity of cognitive impairment. Among the MMSE items, the pentagon copying test (PCT) requires participants to accurately replicate a sample of two interlocking pentagons. While the PCT are traditionally scored on a binary scale, there has been limited developments of granular scoring scale to assess task performance. In this paper, we present a novel three-stage algorithm, called Quantification of Interlocking Pentagons (QIP), which quantifies PCT performance by computing the areas of individual pentagons and their intersection areas, and a balance ratio between the areas of the two individual pentagons. The three stages of the QIP algorithm include: (1) detection of line segments, (2) unraveling of the interlocking pentagons, and (3) quantification of areas. The QIP algorithm was applied to 497 cases from 84 participants. Analysis of the quantified data revealed a significant inverse relationship between age and balance ratio between two pentagon areas (beta = -0.49, p = 0.0033), indicating that older age was associated with a smaller balance ratio. The QIP algorithm enhanced the scoring of performance in the PCT. It can serve as a useful tool for granular level scoring of PCT.
Foundation Models for Quantitative Biomarker Discovery in Cancer Imaging
Authors: Pai Suraj , Bontempi Dennis , Hadzic Ibrahim , Prudente Vasco , Sokač Mateo , Chaunzwa Tafadzwa L. , Bernatz Simon , Hosny Ahmed , Mak Raymond H , Birkbak Nicolai J , Aerts Hugo JWL 
Published: September 2023

AbstractFoundation models represent a recent paradigm shift in deep learning, where a single large-scale model trained on vast amounts of data can serve as the foundation for various downstream tasks. Foundation models are generally trained using self-supervised learning and excel in reducing the demand for training samples in downstream applications. This is especially important in medicine, where large labeled datasets are often scarce. Here, we developed a foundation model for imaging biomarker discovery by training a convolutional encoder through self-supervised learning using a comprehensive dataset of 11,467 radiographic lesions. The foundation model was evaluated in distinct and clinically relevant applications of imaging-based biomarkers. We found that they facilitated better and more efficient learning of imaging biomarkers and yielded task-specific models that significantly outperformed their conventional supervised counterparts on downstream tasks. The performance gain was most prominent when training dataset sizes were very limited. Furthermore, foundation models were more stable to input and inter-reader variations and showed stronger associations with underlying biology. Our results demonstrate the tremendous potential of foundation models in discovering novel imaging biomarkers that may extend to other clinical use cases and can accelerate the widespread translation of imaging biomarkers into clinical settings.
Characterizing HIV status documentation among cancer patients at regional cancer centers in Malawi, Zimbabwe, and South Africa
Authors: Montaño Michalina A , Mtisi Takudzwa , Ndlovu Ntokozo , Borok Margaret , Bula Agatha , Joffe Maureen , Ignacio Rachel Bender , Chagomerana Maganizo B 
Published: September 2023

AbstractIntroductionIn East and Southern Africa, people with HIV (PWH) experience worse cancer-related outcomes and are at higher risk of developing certain cancers. Siloed care delivery pathways pose a substantial barrier to co-management of HIV and cancer care delivery.MethodsWe conducted cross-sectional studies of adult cancer patients at public radiotherapy and oncology units in Malawi (Kamuzu Central Hospital), Zimbabwe (Parirenyatwa Group of Hospitals), and South Africa (Charlotte Maxeke Hospital) between 2018-2019. We abstracted cancer- and HIV-related data from new cancer patient records and used Poisson regression with robust variance to identify patient characteristics associated with HIV documentation.ResultsWe included 1,648 records from Malawi (median age 46 years), 1,044 records from South Africa (median age 55 years), and 1,135 records from Zimbabwe (median age 52 years). Records from all three sites were predominately from female patients; the most common cancers were cervical (Malawi [29%] and Zimbabwe [43%]) and breast (South Africa [87%]). HIV status was documented in 22% of cancer records from Malawi, 92% from South Africa, and 86% from Zimbabwe. Patients with infection-related cancers were more likely to have HIV status documented in Malawi (adjusted prevalence ratio [aPR]: 1.92, 95% confidence interval [CI]: 1.56-2.38) and Zimbabwe (aPR: 1.16, 95%CI: 1.10-1.22). Patients aged ≥60 years were less likely to have HIV status documented (Malawi: aPR: 0.66, 95% CI: 0.50-0.87; Zimbabwe: aPR: 0.76, 95%CI: 0.72-0.81) than patients under age 40 years. Patient age and cancer type were not associated with HIV status documentation in South Africa.ConclusionDifferent cancer centers have different gaps in HIV status documentation and will require tailored strategies to improve processes for ascertaining and recording HIV-related information in cancer records. Further research by our consortium to identify opportunities for integrating HIV and cancer care delivery is underway.
EEG-based Machine Learning Models for the Prediction of Phenoconversion Time and Subtype in iRBD
Authors: Jeong El , Shin Yong Woo , Byun Jung-Ick , Sunwoo Jun-Sang , Roascio Monica , Mattioli Pietro , Giorgetti Laura , Famà Francesco , Arnulfo Gabriele , Arnaldi Dario , Kim Han-Joon , Jung Ki-Young 
Published: September 2023

AbstractBackgroundIdiopathic/Isolated rapid eye movement sleep behavior disorder (iRBD) is a prodromal stage of α-synucleinopathies and eventually phenoconverts to overt neurodegenerative diseases including Parkinson’s disease (PD), dementia with Lewy bodies (DLB) and multiple system atrophy (MSA). Associations of baseline resting-state electroencephalography (EEG) with phenoconversion have been reported.ObjectivesIn this study, we aimed to develop machine learning models to predict phenoconversion time and subtype using baseline EEG features in patients with iRBD.MethodsAt baseline, resting-state EEG and neurological assessments were performed on patients with iRBD. Calculated EEG features included spectral power, weighted phase lag index and Shannon entropy. Three models were used for survival prediction, and four models were used for α-synucleinopathy subtype prediction. The models were externally validated using data from a different institution.ResultsA total of 236 iRBD patients were followed-up for up to eight years (mean 3.5 years), and 31 patients converted to α-synucleinopathies (16 PD, 9 DLB, 6 MSA). The best model for survival prediction was the random survival forest model with an integrated Brier score of 0.114 and a concordance index of 0.775. The K-nearest neighbor model was the best model for subtype prediction with an area under the receiver operating characteristic curve of 0.901. EEG slowing was an important feature for both models.ConclusionsMachine learning models using baseline EEG features can be used to predict phenoconversion time and its subtype in patients with iRBD. Further research including large sample data from many countries is needed to make a more robust model.
A powerful replicability analysis of genome-wide association studies
Authors: Li Yan , Lei Haochen , Wen Xiaoquan , Cao Hongyuan 
Published: September 2023

AbstractReplicability is the cornerstone of modern scientific research. Reliable identifications of genotype-phenotype associations that are significant in multiple genome-wide association studies (GWASs) provide stronger evidence for the findings. Current replicability analysis relies on the independence assumption among single nucleotide polymorphisms (SNPs) and ignores the linkage disequilibrium (LD) structure. We show that such a strategy may produce either overly liberal or overly conservative results in practice. We develop an efficient method, ReAD, to detect replicable SNPs associated with the phenotype from two GWASs accounting for the LD structure. The local dependence structure of SNPs across two heterogeneous studies is captured by a four-state hidden Markov model (HMM) built on two sequences ofp-values. By incorporating information from adjacent locations via the HMM, our approach provides more accurate SNP significance rankings. ReAD is scalable, platform independent and more powerful than existing replicability analysis methods with effective false discovery rate (FDR) control. Through analysis of datasets from two asthma GWASs and two ulcerative colitis GWASs, we show that ReAD can identify replicable genetic loci that existing methods might otherwise miss.