bluuebunny/crossref_metadata_2025_split huggingface dataset:
Disrupted Ecology andH. parainfluenzaeDistinguish the Gut Microbiota of an Ethnic Minority Predisposed to Type 2 Diabetes Mellitus
Authors: Nayman Eric I. , Schwartz Brooke A. , Polmann Michaela , Gumabong Alayna C. , Nieuwdorp Max , Cickovski Trevor , Mathee Kalai 
Published: October 2023

AbstractPurposeDecreased gut microbiota production of short-chain fatty acids (SCFAs) has been implicated in type 2 diabetes mellitus (T2DM) disease progression. Most microbiome studies focus on ethnic majorities. This study aims to understand microbiome differences between an ethnic majority (the Dutch) and minority (the South-Asian Surinamese (SAS)) group with a lower and higher prevalence of T2DM, respectively.MethodsMicrobiome data from the Healthy Life in an Urban Setting (HELIUS) cohort were used. The 16S rRNA V4 region was sequenced. Two age– and gender-matched groups were compared: the Dutch (n = 41) and SAS (n = 43). Microbial compositions were generated via DADA2. Alpha and beta-diversity and Principal Coordinate Analysis (PCoA) were computed. DESeq2 differential bacterial abundance and LEfSe biomarker analyses were performed to determine discriminating features. Co-occurrence networks were constructed to examine gut ecology.ResultsA tight cluster of bacterial abundances was observed in the Dutch women, which overlapped with some of the SAS microbiomes. The Dutch gut contained a more interconnected microbial ecology, whereas the SAS network was dispersed.Bacteroides caccae, Butyricicoccus, Alistipes putredinis, Coprococcus comes,Odoribacter splanchnicus,andLachnospiracharacterized the Dutch gut.Haemophilus,Bifidobacterium,andAnaerostipes hadruscharacterized the SAS gut. All butLachnospiraand certain strains ofHaemophilusare known SCFA producers.ConclusionThe Dutch gut microbiome was distinguished from the SAS by diverse, differentially abundant SCFA-producing taxa with significant cooperation. The dynamic ecology observed in the Dutch was lost in the SAS. The higher prevalence of T2DM in the SAS may be associated with the dysbiosis observed.
PhyGCN: Pre-trained Hypergraph Convolutional Neural Networks with Self-supervised Learning
Authors: Deng Yihe , Zhang Ruochi , Xu Pan , Ma Jian , Gu Quanquan 
Published: October 2023

AbstractHypergraphs are powerful tools for modeling complex interactions across various domains, including biomedicine. However, learning meaningful node representations from hypergraphs remains a challenge. Existing supervised methods often lack generalizability, thereby limiting their real-world applications. We propose a new method, Pre-trained Hypergraph Convolutional Neural Networks with Self-supervised Learning (PhyGCN), which leverages hypergraph structure for self-supervision to enhance node representations. PhyGCN introduces a unique training strategy that integrates variable hyperedge sizes with self-supervised learning, enabling improved generalization to unseen data. Applications on multi-way chromatin interactions and polypharmacy side-effects demonstrate the effectiveness of PhyGCN. As a generic framework for high-order interaction datasets with abundant unlabeled data, PhyGCN holds strong potential for enhancing hypergraph node representations across various domains.
An exploratory review of resiliency assessments after brain injury
Authors: Griffioen Janna , Gingrich Nicole , Pollock Courtney , Schmidt Julia 
Published: October 2023

AbstractObjectiveTo identify resiliency measures which have been established for use with people after acquired brain injury, using the process-based Traumatic Brain Injury Resiliency Model as the guiding conceptual framework.MethodDatabases CINAHL, EMBASE, Medline, and PsychINFO were searched. Using COnsensus based Standards for the selection of Health guidelines of health status Measurement INstruments (COSMIN) guidelines for reporting, articles providing data on psychometric properties for measures of resilience for people with brain injury were retrieved. Psychometric properties and clinical utility (number of items, scoring details) were summarized.ResultsNine articles were retrieved, including 9 measures of resiliency.ConclusionThere are established measures of resiliency in brain injury rehabilitation. Future work may explore use of these measures in a clinical context and implementation of rehabilitation goals for improving resiliency after brain injury.
CarDS-Plus ECG Platform: Development and Feasibility Evaluation of a Multiplatform Artificial Intelligence Toolkit for Portable and Wearable Device Electrocardiograms
Authors: Shankar Sumukh Vasisht , Oikonomou Evangelos K , Khera Rohan 
Published: October 2023

AbstractIn the rapidly evolving landscape of modern healthcare, the integration of wearable and portable technology provides a unique opportunity for personalized health monitoring in the community. Devices like the Apple Watch, FitBit, and AliveCor KardiaMobile have revolutionized the acquisition and processing of intricate health data streams that were previously accessible only through devices only available to healthcare providers. Amidst the variety of data collected by these gadgets, single-lead electrocardiogram (ECG) recordings have emerged as a crucial source of information for monitoring cardiovascular health. Notably, there has been significant advances in artificial intelligence capable of interpreting these 1-lead ECGs, facilitating clinical diagnosis as well as the detection of rare cardiac disorders. This design study describes the development of an innovative multi-platform system aimed at the rapid deployment of AI-based ECG solutions for clinical investigation and care delivery. The study examines various design considerations, aligning them with specific applications, and develops data flows to maximize efficiency for research and clinical use. This process encompasses the reception of single-lead ECGs from diverse wearable devices, channeling this data into a centralized data lake, and facilitating real-time inference through AI models for ECG interpretation. An evaluation of the platform demonstrates a mean duration from acquisition to reporting of results of 33.0 to 35.7 seconds, after a standard 30 second acquisition, allowing the complete process to be completed in 63.0 to 65.7 seconds. There were no substantial differences in acquisition to reporting across two commercially available devices (Apple Watch and KardiaMobile). These results demonstrate the succcessful translation of design principles into a fully integrated and efficient strategy for leveraging 1-lead ECGs across platforms and interpretation by AI-ECG algorithms. Such a platform is critical to translating AI discoveries for wearable and portable ECG devices to clinical impact through rapid deployment.
Evaluating the life-extending potential and safety profile of rapamycin: a Mendelian Randomization study of the mTOR pathway
Authors: Sobczyk Maria K , Gaunt Tom R 
Published: October 2023

AbstractObjectiveThe mechanistic target of rapamycin (mTOR) pathway plays an integral role in cellular metabolism, growth, and aging. While rapamycin and its analogs inhibit the mTOR pathway, extending lifespan in various organisms, the long-term safety and efficacy of these compounds in humans remain understudied.MethodsUtilizing two mTOR expression QTL instruments derived from the eQTLgen and MetaBrain studies, we sought to explore the potential causal relationship between mTOR expression inhibition in blood and brain cortex (mimicking chronic rapamycin use), and its effects on longevity, cardiometabolic disease, prostate cancer and anthropometric risk factors. Subsequently, we extended the selection of instruments to 47 other members of the mTOR pathway. To complement this Mendelian randomization (MR) evidence, we conducted genetic colocalisation and sampling-based enrichment testing.ResultsOur findings suggest that genetically proxied mTOR inhibition may increase the odds of attaining top 1% longest lifespan in the population (OR=1.24, OR95%CI=1-1.53, p-value=0.048). Moreover, mTOR inhibition significantly reduced body mass index (BMI), basal metabolic rate (BMR), height, and age at menopause, while increasing bone mineral density. Interestingly, there was generally little evidence linking mTOR inhibition to cardiovascular disease incidence, with the exception of weak evidence for a protective effect against heart failure (OR=0.94, OR95%CI=0.89-0.99, p-value=0.039). Chronic mTOR inhibition did not causally affect prostate cancer incidence but increased the risk of developing type 2 diabetes. A higher-than-expected (p-value = 0.05) number of genes in the mTOR pathway were causally associated with BMR.ConclusionsThis study highlights the potential lifespan-extending effects of mTOR inhibition and its significant influence on metabolic risk factors and disease. Members of the mTOR complex, especially mTORC1, play a disproportionate role in influencing BMR and BMI, which provides valuable insight for potential therapeutic target development.
Layer 1 NDNF Interneurons are Specialized Top-Down Master Regulators of Cortical Circuits
Authors: Hartung J , Schroeder A , Péréz Vázquez RA , Poorthuis RB , Letzkus JJ 
Published: October 2023

AbstractDiverse types of inhibitory interneurons (INs) impart computational power and flexibility to neocortical circuits. Whereas markers for different IN types in cortical layers (L) 2-6 have been instrumental for generating a wealth of functional insights, only the recent identification of the first selective marker (NDNF) has opened comparable opportunities for INs in L1. However, at present we know very little about the connectivity of NDNF L1INs with other IN types, their input-output conversion, and the existence of potential NDNF L1IN subtypes. Here, we report pervasive inhibition of L2/3 INs (including PV- and VIPINs) by NDNF L1INs. Intersectional genetics revealed similar physiology and connectivity in the NDNF L1IN subpopulation co-expressing NPY. Finally, NDNF L1INs prominently and selectively engage in persistent firing, a physiological hallmark disconnecting their output from the current input. Collectively, our work therefore identifies NDNF L1INs as specialized master regulators of superficial neocortex according to their pervasive top-down afferents.
The EFFECT benchmark suite: measuring cancer sensitivity prediction performance - without the bias
Authors: Szalai Bence , Gáspár Imre , Kaszás Valér , Mérő László , Sztilkovics Milán , Szalay Kristóf Z. 
Published: October 2023

1.AbstractCreating computational biology models applicable to industry is much more difficult than it appears. There is a major gap between a model that looks good on paper and a model that performs well in the drug discovery process. We are trying to shrink this gap by introducing the Evaluation Framework For predicting Efficiency of Cancer Treatment (EFFECT) benchmark suite based on the DepMap and GDSC data sets to facilitate the creation of well-applicable machine learning models capable of predicting gene essentiality and/or drug sensitivity on in vitro cancer cell lines.We show that standard evaluation metrics like Pearson correlation are misleading due to inherent biases in the data. Thus, to assess the performance of models properly, we propose the use of cell line/perturbation exclusive data splits, perturbation-wise evaluation, and the application of our Bias Detector framework, which can identify model predictions not explicable by data bias alone.Testing the EFFECT suite on a few popular machine learning (ML) models showed that while library-standard non-linear models have measurable performance in splits representing precision medicine and target identification tasks, the actual corrected correlations are rather low, showing that even simple knock-out (KO)/drug sensitivity prediction is a yet unsolved task.For this reason, we aim our proposed framework to be a unified test and evaluation pipeline for ML models predicting cancer sensitivity data, facilitating unbiased benchmarking to support teams to improve on the state of the art.
A method of identifying false positives in the strain-specific variant calling of rice
Authors: Kim Sunhee , Chu Sang-Ho , Park Yong-Jin , Lee Chang-Yong 
Published: October 2023

AbstractIn this study, we investigated the strain-specific effect in genetic variant calling from next-generation sequencing data. For this purpose, we used two major strains of the rice genome, Indica and Japonica, to build different variant calling models that differ in the composition of samples from the two strains. We found that the more the samples differed in their strains from the reference sequence, the more variants were predicted. In particular, the increase in predicted variants was noticeable when the samples that differed in their strains from the reference were included. We used machine learning approaches to understand this finding and compared the performance of different variant calling models using confusion matrices constructed from the predicted variants. We found that a significant proportion of the incrementally predicted variants are potential false positives, which becomes more pronounced the more phylogenetically different accessions from the reference are included in the samples. For the accuracy of the predicted variants, we proposed a method to identify the false positives that can be excluded from the potential false positives if necessary. The proposed method involves calling true variants from the purebred samples. We demonstrated the validity of the proposed method on the different variant calling models and showed a reduction of false positives in the predicted variants. As an example of practical utility, we applied the method to the dbSNP, a database of known variants, and demonstrated a way to identify false positives in the dbSNP. In these respects, this study provides general recommendations for effective practices in strain-specific variant calling in rice.
Activation of the Keap1/Nrf2 pathway suppresses mitochondrial dysfunction inC9orf72ALS/FTDin vivomodels and patient iNeurons
Authors: Au Wing Hei , Miller-Fleming Leonor , Sanchez-Martinez Alvaro , Lee James A. K. , Twyning Madeleine J. , Prag Hiran A. , Granger Sarah , Roome Katie , Ferraiuolo Laura , Mortiboys Heather , Whitworth Alexander J. 
Published: October 2023

AbstractMitochondrial dysfunction such as excess production of reactive oxygen species (ROS) and defective mitochondrial dynamics are common features ofC9orf72Amyotrophic Lateral Sclerosis/Frontotemporal Dementia (ALS/FTD), but it remains unclear whether these are causative or a consequence of the pathogenic process. To address this, we have performed a comprehensive characterisation of mitochondrial dysfunctionin vivomodel, analysing multiple transgenicDrosophilamodels ofC9orf72-related pathology, which can be correlated to disease-relevant locomotor deficits. Genetic manipulations to reverse different aspects of mitochondrial disruption revealed that only genetic upregulation of antioxidants such as mitochondrial Sod2 and catalase were able to rescueC9orf72locomotor deficits, suggesting a causative link between mitochondrial dysfunction, ROS and behavioural phenotypes. By analysing the Keap1/Nuclear factor erythroid 2–related factor 2 (Nrf2) pathway, a central antioxidant response pathway, we observed a blunted response in theC9orf72models. However, both genetic reduction of Keap1 and its pharmacological targeting by dimethyl fumarate (DMF), was able to rescueC9orf72-related motor deficits. In addition, analysis ofC9orf72patient-derived iNeurons showed increased ROS that was suppressed by DMF treatment. These results indicate that mitochondrial oxidative stress is an upstream pathogenic mechanism leading to downstream mitochondrial dysfunction such as alterations in mitochondrial function and turnover. Consequently, our data support targeting the Keap1/Nrf2 signalling pathway as a viable therapeutic strategy forC9orf72-related ALS/FTD.
Computational prediction of structure, function and interaction of aphid salivary effector proteins
Authors: Waksman Thomas , Astin Edmund , Fisher S. Ronan , Hunter William N. , Bos Jorunn I.B. 
Published: October 2023

AbstractSimilar to plant pathogens, phloem-feeding insects such as aphids deliver effector proteins inside their hosts that act to promote host susceptibility and enable feeding and infestation. Despite exciting progress towards identifying and characterizing effector proteins from these insects, their functions remain largely unknown. The recent ground-breaking development in protein structure prediction algorithms combined with the availability of proteomics and transcriptomic datasets for agriculturally important pests, such as the aphidMyzus persicae(green peach aphid), provides new opportunities to explore the structural and functional diversity of effector repertoires. In this study, we sought to gain insight into the theM. persicaeeffector repertoire by predicting and analysing the structures of a set of 71 effector candidate proteins. We used two protein structure prediction methods, AlphaFold and OmegaFold, which produced mutually consistent results. We observed a wide continuous spectrum of sizes and structures among the effector candidates, from disordered proteins to globular enzymes. We made use of the structural information and state-of-the-art computational methods to predictM. persicaeeffector protein properties, including function and interaction with host plant proteins. Overall, our investigation provides novel insights into the structure, function, and interaction prediction of aphid effector repertoires and will guide the necessary experimental characterization to address new hypotheses.
A simple optical flow model explains why certain object viewpoints are special
Authors: Stewart Emma E.M. , Fleming Roland W. , Schütz Alexander C. 
Published: October 2023

AbstractA core challenge in perception is recognizing objects across the highly variable retinal input that occurs when objects are viewed from different directions (e.g., frontvsside views). It has long been known that certain views are of particular importance, but it remains unclear why. We reasoned that characterising the computations underlying visual comparisons between objects could explain the privileged status of certain qualitatively special views. We measured pose discrimination for a wide range of objects, finding large variations in performance depending on the object and the view angle, with front and back views yielding particularly good discrimination. Strikingly, a simple and biologically plausible computational model based on measuring the projected 3D optical flow between views of objects accurately predicted both successes and failures of discrimination performance. This provides a computational account of why certain views have a privileged status.Significance statementSome viewpoints of objects are qualitatively and perceptually special, making them easier to recognize and remember. We show that qualitatively special viewpoints of familiar and novel 3D objects can be predicted by an optical-flow model that measures how points on the surface shift in the image as viewpoint changes. This provides a quantitative account for why some viewpoints of objects are perceptually special.
The COMBO window: A chronic cranial implant for multiscale circuit interrogation in mice
Authors: Edelman Bradley Jay , Siegenthaler Dominique , Wanken Paulina , Jenkins Bethan , Schmid Bianca , Ressle Andrea , Gogolla Nadine , Frank Thomas , Macé Emilie 
Published: October 2023

ABSTRACTNeuroscientists studying the neural correlates of mouse behavior often lack access to the brain-wide activity patterns elicited during a specific task of interest. Fortunately, large-scale imaging is becoming increasingly accessible thanks to modalities such as Ca2+imaging and functional ultrasound (fUS). However, these and other techniques often involve challenging cranial window procedures, and are difficult to combine with other neuroscience tools. We address this need with an open-source 3D-printable cranial implant - the COMBO (ChrOnicMultimodal imaging andBehavioralObservation) window. The COMBO window enables chronic imaging of large portions of the brain in head-fixed mice while preserving orofacial movements. We validate the COMBO window stability using both brain-wide fUS and multi-site two-photon imaging. Moreover, we demonstrate how the COMBO window facilitates the combination of optogenetics, fUS and electrophysiology in the same animals to study the effects of circuit perturbations at both the brain-wide and single-neuron level. Overall, the COMBO window provides a versatile solution for performing multimodal brain recordings in head-fixed mice.
Predation-resistantPseudomonasbacteria engage in symbiont-like behavior with the social amoebaDictyostelium discoideum
Authors: Steele Margaret I. , Peiser Jessica , Strassmann Joan E. , Queller David C. 
Published: October 2023

AbstractThe soil amoebaDictyostelium discoideumacts as both a predator and potential host for diverse bacteria. We tested fifteenPseudomonasstrains that were isolated from transiently infected wildD. discoideumfor ability to escape predation and infectD. discoideumfruiting bodies. Three predation-resistant strains frequently caused extracellular infections of fruiting bodies but were not found within spores. Furthermore, infection by one of these species induces secondary infections and suppresses predation of otherwise edible bacteria. Another strain can persist inside of amoebae after being phagocytosed but is rarely ingested. We sequenced isolate genomes and discovered that predation-resistant isolates are not monophyletic. ManyPseudomonasisolates encode secretion systems and toxins known to improve resistance to phagocytosis in other species, as well as diverse secondary metabolite biosynthetic gene clusters that may contribute to predation resistance. However, the distribution of these genes alone cannot explain why some strains are edible and others are not. Each lineage may employ a unique mechanism for resistance.
The Biofilm Lifestyle Shapes the Evolution of β-Lactamases
Authors: Lorentzen Øyvind M. , Haukefer Anne Sofie B. , Johnsen Pål J. , Frøhlich Christopher 
Published: October 2023

AbstractThe evolutionary relationship between the biofilm lifestyle and antibiotic resistance enzymes remains a subject of limited understanding. Here, we investigate how β-lactamases affect biofilm formation inVibrio choleraeand how selection for a biofilm lifestyle impacts the evolution of these enzymes. Seven genetically diverse β-lactamases expressed inV. choleraedisplayed a strong inhibitory effect on biofilm production, ranging from 17% to 61%. To understand how natural evolution affects this antagonistic pleiotropy under biofilm selecting conditions, we randomly mutagenized one β-lactamase and selected for elevated biofilm formation. Our results revealed that biofilm evolution selects for mutations predominantly clustered around the β-lactamase’s active site, yielding functional variants still proficient in β-lactam hydrolysis without biofilm inhibition. Mutational analysis of evolved variants demonstrated that restoration of biofilm development could be achieved either independent of enzymatic function or by actively leveraging enzymatic activity to increase biofilm formation. Taken together, the biofilm lifestyle can impose a profound selective pressure on antimicrobial resistance enzymes. Shedding light on such evolutionary interplays is of great importance to understand the various factors driving antimicrobial resistance.Impact statementβ-lactamases inhibit biofilm formation and the selection for increased biofilm production can mitigate this antagonistic pleiotropic effect. The emergence of β-lactamase variants avoiding biofilm inhibition strongly suggests that the biofilm lifestyle affects the evolutionary fate of these enzymes.