bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamics of efficient ensemble coding
Authors: Ni Long , Stocker Alan A.
Published: January 2025

Ensemble coding creates compressed representations of a stimulus array. When discriminating the ensemble average against a reference, however, items in the ensemble with feature values closer to the reference are typically weighed stronger. We have recently shown that this “robust averaging” behavior can be explained as a form of efficient coding, where the sensory encoding precision is dynamically adapted to efficiently represent ensemble stimuli according to their overall distribution relative to a trial-by-trial varying reference. However, the specific mechanisms underlying such dynamic, efficient ensemble coding remain unknown. Here, we demonstrate that the relative timing between the presentation of the reference and the stimulus ensemble strongly affects efficient ensemble coding. We systematically probed participants’ decision behavior for varying time intervals between the presentation of the ensemble and the reference. We found that efficient ensemble coding was only clearly established when reference and ensemble were simultaneously presented. It was much weaker when the ensemble preceded the reference, and largely absent when the ensemble followed the reference. As captured by our model, reduced efficient ensemble coding thereby coincided with decreased decision accuracy in those asynchronous conditions. Our results indicate that any temporal offset between the ensemble and reference stimuli substantially disrupts the dynamic and efficient allocation of coding resource. This suggests that efficient ensemble coding is not the result of a preparatory attentional process nor due to evidence selection at the decision stage. Rather, it arises from a fast interaction between the simultaneously evoked, sensory representations of reference and ensemble stimuli.
Characterisation ofin vitroresistance selection against second-/last-line antibiotics in methicillin-resistantStaphylococcus aureus
Authors: Prasetyoputri Anggia , Pitt Miranda E. , Cao Minh Duc , Ramu Soumya , Kavanagh Angela , Elliott Alysha G. , Ganesamoorthy Devika , Monk Ian , Stinear Timothy P. , Cooper Matthew A. , Coin Lachlan J.M. , Blaskovich Mark A. T.
Published: January 2025

SYNOPSIS

Background

The increasing occurrence of MRSA clinical isolates harbouring reduced susceptibility to mainstay antibiotics has escalated the use of second and last line antibiotics. Hence, it is critical to evaluate the likelihood of MRSA developing clinical resistance to these antibiotics.

Objectives

Our study sought to identify the rate in which MRSA develop resistance to vancomycin, daptomycin and linezolidin vitroand further determine the mechanisms underpinning resistance.

Methods

MRSA was exposed to increasing concentrations of vancomycin, daptomycin, and linezolid for 20 days, with eight replicates for each antibiotic conducted in parallel. The resulting day 20 (D20) isolates were subjected to antimicrobial susceptibility testing, whole genome sequencing, autolysis assays, and growth curves to determine bacterial fitness.

Results

Exposure to vancomycin or linezolid for 20 days resulted in a subtle two-fold increase in the MIC, whereas daptomycin exposure yielded daptomycin-nonsusceptible isolates with up to 16-fold MIC increase. The MIC increase was accompanied by variable changes in relative fitness and reduced resistance to autolysis in some isolates. D20 isolates harboured mutations in genes commonly associated with resistance to the respective antibiotics (e.g.walKfor vancomycin,mprFandrpoBfor daptomycin,rplCfor linezolid), along with several previously unreported variants. Introduction of key mutations to these identified genes in the parental strain via allelic exchange confirmed their role in the development of resistance.

Conclusions

In vitroselection against vancomycin, daptomycin, or linezolid resulted in the acquisition of mutations similar to those correlated with clinical resistance, including the associated phenotypic alterations.
Chronic Complications of Type 2 Diabetes Patients in Southern Ethiopia
Authors: Demisse Andarge Biniyam , Hayelom Desta Haftu , Mehari Sayih , Esubalew Habtamu , Wondmagegn Habtamu , Habtegiorgis Yohannes , Bekele Muluken , Chisha Yilma
Published: January 2025

Background

Type 2 diabetes mellitus (T2DM) is a global health concern associated with complications that significantly impact patients’ quality of life and place significant burdens on healthcare systems. While the prevalence of T2DM is rising in Ethiopia, the scope and factors contributing to its complications remain understudied. Hence, this study aimed to assess the burden and identify associated factors of chronic complications among Type 2 diabetes mellitus patients attending Wolaita Sodo University Comprehensive Specialized Hospital in Southern Ethiopia.

Methods

A facility-based cross-sectional quantitative study was conducted from July to August 2024, involving 404 systematically sampled T2DM patients. Data on sociodemographic characteristics, clinical profiles, self-care practices, and chronic complications were collected through structured interviews and medical record reviews. Descriptive statistics summarized patient characteristics, while General Poisson regression identified factors associated with chronic complications. Results were reported as Adjusted Prevalence Ratios (APRs) with 95% Confidence Intervals (CIs), and a p-value < 0.05 was considered statistically significant.

Results

Of the 404 participants, 45.54% (95% CI: 40.61 - 50.54) had at least one chronic complication. Among these, 20.05% experienced one complication, 14.60% had two, 8.42% had three, and 2.48% had four. Peripheral neuropathy (14.85%) and nephropathy (9.65%) were the most common microvascular complications, while congestive heart failure (14.11%) and cerebrovascular disorders (11.39%) were the leading macrovascular complications. Multivariable Poisson regression identified older age (APR = 2.30; 95% CI: 1.23–4.28), longer diabetes duration (APR = 1.87; 95% CI: 1.28–2.76), elevated blood pressure (APR = 2.02; 95% CI: 1.21–3.37), and higher Body Mass Index (APR = 2.63; 95% CI: 1.43–4.81) as significant factors associated with increased prevalence of chronic complications.

Conclusion

The study reveals a substantial burden of chronic complications among T2DM patients, driven by modifiable and non-modifiable risk factors such as age, diabetes duration, blood pressure, and body mass index. These findings emphasize the urgent need for targeted interventions, including improved disease management, regular monitoring, and lifestyle modifications, to mitigate complications and enhance patient outcomes.
From Ice Cores to Dinosaurs: Physical Collections Managers’ Research Data Curation Perceptions and Behaviors
Authors: Bishop Bradley Wade , Fox Jaxx , Gavel Sidney Wanda Taylor , Chapin Emily Grace , Kansa Sarah
Published: January 2025

Physical collections provide the tangible objects that when analyzed become data informing all sciences. Physical collection managers aim to make physical objects discoverable, accessible, and reusable. The volume and variety of physical collections acquired, described, and stored across decades, and in some cases centuries, results from large public and private investments. The purpose of this study is to understand the curation perceptions and behaviors of physical collection managers across domains to inform cross-disciplinary research data management. Ten focus groups were conducted with thirty-two participants across several physical collection communities. Participants responded to open-ended questions about the data lifecycle of their physical objects. Results indicated that physical collections attempt to use universal metadata and data storage standards to increase discoverability, but interdisciplinary physical collections and derived data reuse require more investments to increase reusability of these invaluable items. This study concludes with a domain-agnostic discussion of the results to inform investment in cyberinfrastructure tools and services.

Author summary

Physical collections across the life and geosciences provide the tangible objects used to analyze and gain knowledge. There are collection managers in many museums and other information agencies working hard to curate these items in a way to keep them secure for long-term use. This study conducted focus groups with collection managers across several physical collection communities, including anthropology, archaeology, paleontology, ichthyology, herbaria, entomology, herpetology, and geology. Participants discussed their collection management approaches using the stages of the data lifecycle to frame how they make their items discoverable and reusable. Results indicated metadata and data storage standards help increase discoverability, but more work could be done to ensure better interdisciplinary reuse through increased investment and user-informed design of the cyberinfrastructure that preserves and makes available these invaluable items.
Identifying brain-penetrant small molecule modulators of human microglia using a cellular model of synaptic pruning
Authors: McCrea Liam T. , Batorsky Rebecca E. , Bowen Joshua J. , Yeh Hana , Thanos Jessica M. , Fu Ting , Perlis Roy H. , Sheridan Steven D.
Published: January 2025

Microglia dysregulation is implicated across a range of neurodevelopmental and neurodegenerative disorders, making their modulation a promising therapeutic target. Using PBMC-derived induced microglia-like cells (piMGLCs) in a scalable assay, we screened 489 CNS-penetrant compounds for modulation of microglial phagocytosis of human synaptosomes in a validated assay for microglia-mediated synaptic pruning. Compounds from the library that reduced phagocytosis by ≥2 standard deviations across the library without cytotoxicity were validated in secondary screens, with 28 of them further confirmed to reduce phagocytosis by 50% or more. Image-based morphological measurements were calculated to measure the degree of ramified vs. amoeboid morphotype as an indicator of activation state. Additionally, transcriptomic profiling indicated divergent effects on cell signaling, metabolism, activation, and actin dynamics across confirmed compounds. In particular, multiple CNS-penetrant small molecules with prior FDA approval or demonstration of safetyin vivodemonstrated modulatory effects on microglia. These potential disease-modifying agents represent high-priority candidates for repositioning studies in neurodevelopmental, neuroinflammatory, or neurodegenerative disorders.
A compendium of nonredundant short Polymerase III promoters for CRISPR applications
Authors: Deguchi Michihito , Sinclair Kayla M. , Patel Annie , Coile Mckenna , Ortega Maria A. , Bewg William P. , Tsai Chung-Jui
Published: January 2025

Multiplex genome editing via CRISPR is a powerful tool for the simultaneous knockout, activation, and/or repression of distinct genes or noncoding sequences. However, current toolkits for multiplex editing lack diversity. Repeated use of the same promoter in multiple expression cassettes complicates construct assembly and has long been a concern for genetic stability in the host organism. Additionally, using unnecessarily long promoters may increase the genetic load and introduce uncertainties that impact CRISPR efficiency. To address these challenges, we present a collection of short Polymerase III (Pol III) promoters of diverse origins to support increasingly sophisticated genome editing applications in dicots.
Citation Contamination of Systematic Review Literature in the Life Sciences by Paper Mills
Authors: Tang Gengyan , Cai Hao
Published: January 2025

Importance

Paper mills are systematic fraud organizations that mass-produce fabricated papers, submit them under researchers’ names, and profit by charging fees or selling authorship. Their products have infiltrated scientific literature databases, yet the academic community remains uncertain about their potential impact on scholarly research.

Objective

Our study investigates the citation contamination of systematic reviews in the life sciences by paper mill articles, aiming to determine whether these fabricated papers undermine the status of systematic reviews as the “gold standard” of evidence synthesis.

Evidence Review

We conducted a cross-sectional study of 100,000 systematic reviews published in the life sciences between 2013 and 2023, as indexed in the Web of Science. We extracted their references and matched them against retracted articles in the Retraction Watch Database, specifically those retracted due to paper mills. Descriptive statistical analyses were used to characterize the features of contaminated systematic reviews, including their subject areas, journals of publication, and citation patterns.

Findings

A total of 179 systematic reviews were contaminated by paper mill articles, representing a contamination rate of 0.179%. Although the overall extent of contamination was small, an increasing trend was observed. Notably, 61 citations occurred after the articles had been retracted. Oncology was the most severely affected field. Four systematic reviews each cited five or more paper mill articles; all were published by journals under the same academic publisher. Among those citing three or more paper mill articles, 23 (76.67%) were published in journals ranked in the top 50% of their respective fields by impact factor (i.e., those classified as Q1 or Q2).

Conclusions and Relevance

Systematic reviews, as comprehensive syntheses of high-quality evidence, must not incorporate systematically fabricated articles. The scientific community should remain vigilant about the growing trend of paper mill contamination in life sciences systematic reviews. Correcting and retracting previously contaminated reviews, and developing new tools to help researchers identify potential paper mill articles in literature databases, will be essential steps to ensure the integrity of evidence synthesis.

Key Points

Question

Do paper mill articles contaminate systematic reviews in the life sciences, and what is their potential impact on the integrity of evidence synthesis?

Findings

In a cross-sectional study of 100,000 systematic reviews published between 2013 and 2023, 0.179% were contaminated by paper mill articles, with an increasing trend observed over time. Oncology was the most affected field, and 61 post-retraction citations were identified.

Meaning

These findings underscore the need for heightened vigilance, systematic correction of contaminated reviews, and development of tools to identify paper mill articles to safeguard the integrity of evidence synthesis.
Genomic diversity andBCL9Lmutational status in CTC pools predict overall survival in metastatic colorectal cancer
Authors: Alves Joao M. , Estévez-Gómez Nuria , Piñeiro Roberto , Muinelo-Romay Laura , Mondelo-Macía Patricia , Salgado Mercedes , Iglesias-Gómez Agueda , Codesido-Prada Laura , Diez-Martín Astrid , Cubiella Joaquin , Posada David
Published: January 2025

The genomic diversity of circulating tumor cells (CTCs) and its clinical implications remain poorly understood. In this study, we characterized the mutational landscape of CTC pools stemming from 29 metastatic colorectal cancer (mCRC) patients and examined its relationship with disease progression. Our analysis revealed substantial variation in mutational burden among patients, with all CTC pools harboring non-silent mutations in key CRC driver genes. Importantly, higher genomic diversity in CTC pools was significantly associated with reduced overall survival. Furthermore, the presence of non-silent mutations inBCL9Lemerged as a strong predictor of patient survival. Taken together, these findings underscore the potential of CTC genomic profiling as a promising prognostic tool in mCRC and highlight the need for further research into its clinical applications.
Extended Plasmonic Nanostructures Templated by Tobacco Mosaic Virus Coat Protein
Authors: Abu-Baker Ismael , Al-Feghali Alexander , Zolfaghar Elliot , Velpula Gangamallaiah , Biela Artur P. , De Feyter Steven , Heddle Jonathan G. , Cosa Gonzalo , Blum Amy Szuchmacher
Published: January 2025

Optical and magnetic metamaterials possess interesting properties that cannot be achieved with conventional materials. However, there is currently no synthetic method offering both scalability and nanometer spatial precision. Biotemplating is a promising technique that has the potential to organize nanoscale components with high precision while being scalable and low-cost. Here we demonstrate a versatile template using hexahistidine-tagged tobacco mosaic virus coat protein. The protein self-assembles into disks which further assemble into extended nanostructures under mild conditions. Large sheets with either hexagonal or square packing and core-shell nanorods were formed, and gold nanoparticles were attached to the disks within each nanostructure to form assemblies of nanoparticle rings.
Implementation and utilization of real-time prescription benefit tools across three large academic health systems
Authors: Ali Muhammad , Schwartz Jeremy I. , Wang Jiangxia , Liu Jing , Potu Niteesh , Rottier William , Dziedzic Peter , Smith Erika , Mehta Tanvi , Kashyap Nitu , Fliotsos Michael J. , Luo Jing , Epstein Jeremy , Segal Jodi B. , Lehmann Harold , Crotty Bradley H. , Woreta Fasika A.
Published: January 2025

Background

Real-time prescription benefit (RTPB) tools provide clinicians an out-of-pocket cost (OOPC) estimate at the time of prescribing and may help them select medications with lower OOPC for their patients.

Objective

To evaluate how RTPB tools altered medication orders during clinical encounters and assess patient and clinician characteristics associated with the display of RTPB tool and alternative selection.

Design

Retrospective cohort study

Setting

Outpatient encounters at three academic medical centers

Participants

Patients and clinicians

Measurements

Patient characteristics, clinician characteristics and medication alternatives suggested by RTPB tool were compared across the three sites.

Results

From April 2019 to October 2021, 6,562,442 patient encounters occurred between 3,624 clinicians and 1,261,551 unique patients. Medications were prescribed in 2,152,772 (32.8%) encounters, of which RTPB tool retrieved and displayed alternatives in 968,811 (45.0%) encounters. The clinician selected an alternative in 68,731/968,811 (7.1%) of the encounters during which 89,050 medications were prescribed. The unit cost of alternative medications remained the same for most orders (n=41,212; 58.4%), while 18,629 (26.4%) had lower cost and 10,728 (15.2%) alternate orders had higher cost. Clinicians selected a different pharmacy among 39,634 (44.5%) and a different pharmacy type (mail vs retail) among 7,508 (12.7%) of the alternate medication orders, of which most were to mail order 4,680 (62.3%).

Limitations

We could not assess the role of pharmacy benefit manager coverage, cash-based alternative pricing, and impact of prior authorizations which may be assessed during future investigations.

Conclusion

Alternate prescribing after implementation of RTPB tools was low across the three institutions. Unit cost of the medication did not often change. Most changes reflected pharmacy choice. Further studies are needed to assess the barriers in adoption of RTPB tools.
Subregional Biomarkers in FDG PET for Alzheimer’s Diagnosis and Staging: An Interpretable and Explainable model
Authors: Rasi Ramin , Guvenis Albert ,   the Alzheimer’s Disease Neuroimaging Initiative
Published: January 2025

Objective

To investigate the radiomics features of the hippocampus and the amygdala subregions in FDG-PET images that can best differentiate Mild Cognitive Impairment (MCI), Alzheimer’s Disease (AD), and healthy patients.

Methods

Baseline FDG-PET data from 555 participants in the ADNI dataset were analyzed, comprising 189 cognitively normal (CN) individuals, 201 with MCI, and 165 with AD. The hippocampus and amygdala were segmented based on the DKT-Atlas, with additional subdivisions guided by probabilistic atlases from Freesurfer. Then radiomic features (n=120) were extracted from 38 hippocampal subregions and 18 amygdala nuclei using PyRadiomics. Various feature selection techniques, including ANOVA, PCA, Chi-square, and LASSO, were applied alongside nine machine learning classifiers.

Results

The Multi-Layer Perceptron (MLP) model combined with LASSO demonstrated excellent classification performance: ROC AUC of 0.957 for CN vs. AD, ROC AUC of 0.867 for MCI vs. AD, and ROC AUC of 0.782 for CN vs. MCI. Key regions, including the accessory basal nucleus, presubiculum head, and CA4 head, were identified as critical biomarkers. Features including GLRLM (Long Run Emphasis) and Small Dependence Emphasis (GLDM) showed strong diagnostic potential, reflecting subtle metabolic and microstructural changes often preceding anatomical alterations.

Conclusion

Specific hippocampal and amygdala subregions and their four radiomic features were found to have a significant role in the early diagnosis of AD, its staging, and its severity assessment by capturing subtle shifts in metabolic patterns. Furthermore, these features offer potential insights into the disease’s underlying mechanisms and model interpretability.
Novel blood-based proteomic signatures across multiple neurodegenerative diseases
Authors: Durcan Robert , Heslegrave Amanda , Swann Peter , Goddard Julia , Chouliaras Leonidas , Murley Alexander G , Savulich George , Bevan-Jones W Richard , Swann Owen , Ashton Nicholas J , Blennow Kaj , McEwan William , Zetterberg Henrik , Rowe James B , O’Brien John T , Malpetti Maura
Published: January 2025

INTRODUCTION

Blood-based biomarkers have the potential to support early and accurate diagnosis of neurodegenerative diseases, which is sensitive to molecular pathology and predictive of outcome. We evaluated a novel multiplex proteomic method in people with diverse neurodegenerative diseases.

METHODS

Serum from people with Alzheimer’s disease (N=36), Lewy body dementia (N=34), frontotemporal dementia (N=36) and progressive supranuclear palsy (N=36) and age-matched controls (N=30) was analysed with the NUcleic acid Linked Immuno-Sandwich Assay (NULISA) central nervous system panel (∼120 analytes) and inflammation panel (250 analytes). Biomarkers were compared across groups and included as predictors of survival.

RESULTS

The NULISA panels demonstrated high sensitivity and reliability for detecting multiple biomarkers across neurodegenerative disorders. There were condition-specific proteomic biomarkers, while NfL, CRH, CD276 and S100A12 were significant transdiagnostic outcome predictors.

DISCUSSION

The sensitive NULISA multiplex approach supports differential diagnosis and target identification, with prognostically informative dementia-related biomarkers.
Untangling structural molecular details of the endocytic adaptor protein CALM upon binding with phosphatidylinositol 4,5-bisphosphate-containing model membranes
Authors: Santamaria Andreas , Pereira Daniel , Pawar Nisha , Kelly Bernard T. , Carrascosa-Tejedor Javier , Sardo Mariana , Mafra Luís , Fragneto Giovanna , Owen David J. , Marín-Montesinos Ildefonso , Guzmán Eduardo , Zaccai Nathan R. , Maestro Armando
Published: January 2025

Clathrin assembly lymphoid myeloid leukemia protein (CALM) is involved in the formation of clathrin-mediated endocytic coats by virtue of binding many proteins involved in the process, including clathrin itself and AP2 cargo adaptor complex. CALM is able to specifically recognize the inner leaflet of the plasma membrane by binding the membrane’s phosphatidylinositol 4,5-bisphosphate (PtdIns(4,5)P2). Here, a biophysical approach, primarily using neutron and X-ray scattering and solid-state NMR experiments, was exploited to investigate CALM interaction with PtdIns(4,5)P2-presenting model membranes. The presented experimental data reveal how the CALM folded domain is partly accommodated within the lipid membrane, directly interacting with PtdIns(4,5)P2phosphates. Moreover, these data suggest that CALM’s amphiphilic N-terminal helix buries into the membrane, not only stabilising the protein docking to the membrane but also providing a mechanism to induce membrane curvature.
Cancer vs. Conversational Artificial Intelligence
Authors: Kawchak Kevin
Published: January 2025

Solving cancer mechanisms is challenging due to the complexity of the disease integrated with many approaches that researchers take. In this study, information retrieval was performed on 40 oncological papers to obtain authors' methods regarding the tumor immune microenvironment (TIME) or organ-specific research. 20 TIME summaries were combined and analyzed to yield valuable insights regarding how research based papers compliment information from review papers using Large Language Model (LLM) in-context comparisons, followed by code generation to illustrate each of the authors' methods in a knowledge graph. Next, the 20 combined organ-specific emerging papers impacting historical papers was obtained to serve as a source of data to update a mechanism by Zhang, Y., et al., which was further translated into code by the LLM. The new signaling pathway incorporated four additional authors' area of cancer research followed by the benefit they could have on the original Zhang, Y., et al. pathway. The 40 papers in the study represented over 600,000 words which were focused to specific areas totaling approximately 17,000 words represented by detailed and reproducible reports by Clau-3Opus. ChatGPT o1 provided advanced reasoning based on these authors' methods with extensive correlations and citations. Python or LaTeX code generated by ChatGPT o1 added methods to visualize Conversational AI findings to better understand the intricate nature of cancer research.
Development of a high-throughput 3D culture microfluidic platform for
multi-parameter phenotypic and omics profiling of patient-derived
organoids
Authors: Botrugno Oronza A. , Bianchi Elena , Bruno Jolanda M. , Felici Claudia , Gallo Giovanni F.M. , Sommella Eduardo , Stefano Paola De , Giansanti Valentina , Rossella Valeria , Lazarevic Dejan , Merciai Fabrizio , Caponigro Vicky , Golino Valentina , Gioia Danila La , Malinconico Antonio , Colombo Emanuele , Giovannoni Giulio , Gatti Guido , Ratti Francesca , Buonanno Silvia , Pedica Federica , Tacchetti Carlo , Falletta Paola , Zambrano Samuel , Mazza Davide , Cittaro Davide , Campiglia Pietro , Aldrighetti Luca , Tonon Giovanni , Dubini Gabriele
Published: January 2025

Patient-derived organoids (PDOs) are poised to become central tools in
clinical practice, to preemptively identify patient optimal treatments, and in
drug discovery, overcoming the limitations of cancer cell lines. However, the
implementation of PDOs in both these settings has been hampered by several
bottlenecks including sample requirements, assay time and handling in the
context of high-throughput-based drug assays. We report here the development of
a microfluidic-based device
(MicrofluidicPlatform
forOrganoids culture, MPO) that
miniaturises and greatly simplifies PDO cultures in a 384-plate format. Both
retrospective and prospective clinical studies demonstrate its predictive value
and the swift and straightforward implementation in the clinical setting.
Obtaining comprehensive functional and molecular information on the response to
drugs is becoming a requirement in drug discovery. MPO allows subcellular
phenotypic and imaging screenings, target engagement for the assessment of the
efficacy of therapies, alongside the ability to comprehensively and
concomitantly define PDOs genomic, transcriptomic, proteomic, lipidomic and
metabolomic landscape. In all, we demonstrate the potential of our platform to
impact clinical practice generating relevant information on drug sensitivity
within a time frame that could inform treatment decisions alongside exploration
of the mechanisms underlying compound response and resistance in drug discovery
efforts.
NeuroTorch: A Python library for neuroscience-oriented machine learning
Authors: Gince Jérémie , Drouin Anthony , Desrosiers Patrick , Hardy Simon V
Published: January 2025

Machine learning (ML) has become a powerful tool for data analysis, leading to significant advances in neuroscience research. While ML algorithms are proficient in general-purpose tasks, their highly technical nature often hinders their compatibility with the observed biological principles and constraints in the brain, thereby limiting their suitability for neuroscience applications. In this work, we introduce NeuroTorch, a comprehensive ML pipeline specifically designed to assist neuroscientists in leveraging ML techniques using biologically inspired neural network models. NeuroTorch enables the training of recurrent neural networks equipped with either spiking or firing-rate dynamics, incorporating additional biological constraints such as Dale's law and synaptic excitatory-inhibitory balance. The pipeline offers various learning methods, including backpropagation through time and eligibility trace forward propagation, aiming to allow neuroscientists to effectively employ ML approaches. To evaluate the performance of NeuroTorch, we conducted experiments on well-established public datasets for classification tasks, namely MNIST, Fashion-MNIST, and Heidelberg. Notably, NeuroTorch achieved accuracies that replicated the results obtained using the Norse and SpyTorch packages. Additionally, we tested NeuroTorch on real neuronal activity data obtained through volumetric calcium imaging in larval zebrafish. On training sets representing 9.3 minutes of activity under darkflash stimuli from 522 neurons, the mean proportion of variance explained for the spiking and firing-rate neural network models, subject to Dale's law, exceeded 0.97 and 0.96, respectively. Our analysis of networks trained on these datasets indicates that both Dale's law and spiking dynamics have a beneficial impact on the resilience of network models when subjected to connection ablations. NeuroTorch provides an accessible and well-performing tool for neuroscientists, granting them access to state-of-the-art ML models used in the field without requiring in-depth expertise in computer science.
Inverted topologies in sequential fitness landscapes enable evolutionary control
Authors: Chen Peng , Krishnan Nikhil , Stacy Anna , Weaver Davis T. , Barker-Clarke Rowan , Hinczewski Michael , Maltas Jeff , Scott Jacob G.
Published: January 2025

Adaptive populations rarely evolve in a static environment. Therefore, understanding and ultimately controlling the evolution of a population requires consideration of fluctuating selective pressures. The fitness landscape metaphor has long been used as a tool for representing the selective pressures a given environment imposes on a population. Much work has already been done to understand the dynamics of evolution on a single fitness landscape. More recently, evolution on fluctuating or sequentially applied landscapes has come to the fore of evolutionary biology. As more empirical landscapes are described, metrics for describing salient features of paired landscapes will have uses for understanding likely evolutionary dynamics. Currently, Pearson correlation coefficient and collateral sensitivity likelihoods are used to quantify topological relatedness or dissimilarity of a pair of landscapes. Here, we introduce the edge flip fraction, a new metric for comparing landscapes, which quantifies changes in the directionality of evolution between pairs of fitness landscapes. We demonstrate that the edge flip fraction captures topological differences that traditional metrics may overlook. By applying this metric to both empirical and synthetic fitness landscapes, we show that it partially predicts the collateral sensitivity likelihoods and can inform the optimality of drug sequences. We show that optimal drug sequences that keep populations within lower fitness regions require shifts in evolutionary directions, which are quantified by the edge flip fraction. Edge flip fraction complements existing measures and may help researchers understand how populations evolve under changing environmental conditions.
Socioecological benefits of academic greenspace for human health, plant, and pollinator diversity: a mixed-method study protocol
Authors: Kehinde T.O. , Akinsulore A. , Mapayi B.O. , Okorie V.O. , Oziegbe M. , Ndiribe C.C. , Adedoja O.A. , Balogun I.
Published: January 2025

Introduction

Significant risks to the health of humans and ecosystems are posed by environmental pollution, urban warming, and fragmentation, which are primary urban factors that contribute to the deterioration of urban ecosystems. The purpose of this multidisciplinary study is to compare greenspaces in university campuses and the host cities in order to assess how valuable they are for promoting human and ecosystem health in Nigeria.

Methods

Mixed-methods research that will be conducted in five tertiary institutions and their host cities in southwestern Nigeria. Based on the objectives, the study is divided into four work packages (WP). WP 1 will use suitable sampling traps and scheduled field observations to quantify the diversity of plants and pollinators. Quantitative evaluation of well-being and mental health will be done in WP 2. In WP 3, the relationship between ecosystem health and mental health will be examined and in-depth interviews will be used to explore the socioecological perceptions and interaction of people with specific indicators of ecosystem health in greenspace. In WP 4, a nature-based intervention will be developed and evaluated in a pilot study to determine its feasibility and acceptability.

Results

The 2023 TETFund National Research Fund Intervention provided funding for this work, which is currently ongoing.

Conclusion

This project will provide scientific knowledge to support evidence-based policy for relevant stakeholders and regulatory organisations, with the goal of promoting greenspace infrastructure in Nigerian tertiary institutions.
Utilization Analysis and Fraud Detection in Medicare via Machine Learning
Authors: Tajrobehkar Mahan , Guo Xin , Nguyen Diane , Chigullapally Nikita , Shravah Varun , Yee Shannon , Chozhan Abishek , Hoang Kathy , Chang Robert T. , Gutierrez Carolina , Lee Scott
Published: January 2025

Healthcare fraud and overutilization pose significant challenges in the United States, leading to substantial financial losses and compromised patient care. Medicare, a vital federal healthcare program, is particularly susceptible to such abuses. With over 63 million Americans enrolled in Medicare and growing expenses, the need for effective fraud detection is paramount. Traditional methods relying on manual audits have proven insufficient, allowing a significant portion of fraudulent activity to go undetected. Machine learning (ML), however, has gained significant attention in recent years due to its potential for improving the efficiency of fraud detection and prevention. Nonetheless, there are several issues with the existing studies utilizing ML that limit their effectiveness. The most common issue is the heavy reliance on the List of Excluded Individuals and Entities (LEIE) from the Office of the Inspector General for model training and evaluation. Apart from the severe class imbalance issue (with a fraud rate between 0.038% and 0.074%), another notable problem associated with using the LEIE dataset is that many of the providers listed there were prosecuted due to overt and deliberate fraudulent billing. Consequently, using this dataset to train ML models can help detect brazen, outlandish billing patterns, but would be unable to pinpoint instances of more subtle fraud from which a majority of the financial loss and waste occurs. In this paper, we leverage the experience of seasoned physicians and medical billers to create a labeled dataset that overcomes the issues of class imbalance and the exclusive focus on overtly fraudulent providers. We leverage our access to domain knowledge by focusing on the field of ophthalmology. Additionally, using the labeled dataset, we conduct a comparative study of various machine learning models for the task of predicting Medicare overutilization within ophthalmology. The results indicate that our proposed ensemble outperforms individual models such as extreme gradient boosting and multilayer perceptron in detecting overutilization, achieving Area Under the Receiver Operating Characteristic Curve (AUROC score) of 0.907. By deploying the stacking ensemble model, our paper estimates nationwide and jurisdiction-specific overutilization rates, revealing that approximately 8.6% of ophthalmologists engaged in overutilization practices in 2021. We also highlight potential monetary losses of $437.1 million attributed to overutilization activities within ophthalmology for that year alone. Furthermore, feature importance analysis using SHAP (SHapley Additive exPlanations) values provides insights into the key factors influencing the model’s overutilization predictions. Notably, the ratio of total Medicare payments to the total number of patients emerges as a crucial feature in identifying potential overutilizers.
Genome-Wide Associations within Diverse Wild Apple Germplasm for Postharvest Blue Mold Resistance toPenicillium expansum
Authors: Whitt Lauren , Bennett John S. , Collum Tamara D. , Evans Breyn , Raines Doug , Gutierrez Ben , Janisiewicz Wojciech J. , Jurick Wayne M. , Gottschalk Christopher
Published: January 2025

Post-harvest disease caused by the blue mold fungus,Penicillium expansum, accounts for a substantial proportion of economic losses in United States apple industry. Multiple modes of entry in the apple supply chain, plus emerging fungicide resistance, limit the current and long-term viability of using chemical controls alone. Previous phenotypic screens ofMalusaccessions in the USDA-ARS apple germplasm have identified varying levels of blue mold disease resistance in some wild apple accessions and hybrids. These wild apple species contain reservoirs of genetic resistance that can be integrated into apple breeding programs to complement the previously identifiedqM-Pe3.1marker fromM. sieversii. We sought to identify these novel loci by combining historical phenotypes of the USDA-ARS wild apple germplasm with low-pass genomic sequencing to perform association mapping. Multi-locus mixed models identified five single nucleotide polymorphisms (SNPs) significantly associated with reduction of post-harvest rot under high concentration ofP. expansum inoculum, and one SNP associated under low inoculum concentration. Within a 25,000 base pair window of these SNPs, we found candidate genes encoding proteins with known pathogen immune response and defense roles, such as a Cobra-like 7, flavin monooxygenase, LRR receptors, PR5-like receptor kinase, and a putative resistance protein RGA3. We present these loci as targets for identifying accessions with beneficial alleles that can be targeted for fine mapping and use inMalusbreeding programs to achieveM. domesticalines with natural post-harvest rot resistance.
How to deal with darkness: Modelling and visualization of zero-inflated personal light exposure data on a logarithmic scale
Authors: Zauner Johannes , Guidolin Carolina , Spitschan Manuel
Published: January 2025

Personal light exposure, the pattern of ocular light levels across time under free-living conditions measured with wearable devices, has become increasingly important in circadian and myopia research. Very small measurement values in light exposure patterns, especially zero, are regularly recorded in field studies. These zero-lux values are problematic for commonly applied logarithmic transformations, and should neither be dismissed nor be unduly influential in visualizations and statistical models. Common approaches used in zero-inflated data sets fail in at least one of these regards. We compare four ways to visualize such data on a linear, logarithmic, hybrid, or symlog scale and we model the light exposure patterns with a generalized additive model by removing zero-lux values, adding a very small or −1 log10lux value to the dataset, or using the Tweedie error distribution. We show that asymlog-transformed visualization displays relevant features of light exposure across scales, including zero-lux, while at the same time reducing the emphasis on the small values (<1 lux).Symlogis well-suited to visualize differences in light exposure covering heavy-tailed negative values. The open-source software packageLightLogRincludes the symlog transformation for easy access. We further show that small but not negligible value additions to the light exposure data of -1 log10lux for statistical modelling allow for acceptable models on a logarithmic scale, while very small values distort results. We also demonstrate the utility of the Tweedie distribution, which does not require prior transformations, models data on a logarithmic scale, and includes zero-lux values, capturing personal light exposure patterns satisfactorily. Data from field studies of personal light exposure requires appropriate handling of zero-lux values in a logarithmic context.Symlogscales for visualizations and an appropriate addition to input values for modelling, or the Tweedie distribution, provide a solid basis.
Graph Network-Based Analysis of Disease-Gene-Drug Associations: Zero-Shot Disease-Drug Prediction and Analysis Strategies
Authors: Liu Yinbo , Niu Guodong , Wu Siqi , Wang Jinming , Qiu Hesong , Meng Sijun , Zhang Wen
Published: January 2025

ZGNT, an innovative, novel workflow for zero-shot learning in drug repurposing that leverages meta-path graph neural network transform- ers. This method infers disease-drug relationships indirectly, utilizing disease-gene associations and gene-drug interactions via acting genes. It also generates a TOP drug-TOP gene linkage map, providing clini- cians with a visual tool to assess the plausibility of the suggested drugs before advancing to clinical trials. Experimental results demonstrate that, among the top 1% of disease-related drug candidates identified by ZGNT, the proportion of usable drugs is ***, surpassing four base- line methods. Furthermore, the accuracy of interaction link prediction achieves ***, also surpassing these benchmarks. Ultimatley, by inte- grating data acquisition, model design, and application workflows, our approach effectively identifies potential drug targets, offering new in- sights into therapeutic strategies for disease management. This paper thoroughly details the methodology and validates its effectiveness across various diseases, highlighting its robustness and practical value.
Molecular basis for the assembly of the dynein transport machinery on microtubules
Authors: Rao Qinhui , Chai Pengxin , Zhang Kai
Published: January 2025

Cytoplasmic dynein-1, a microtubule-based motor protein, requires dynactin and an adaptor to form the processive dynein-dynactin-adaptor (DDA) complex. The role of microtubules in DDA assembly has been elusive. Here, we reveal detailed structural insights into microtubule-mediated DDA assembly using cryo-electron microscopy. We find that an adaptor-independent dynein- dynactin complex (DD) predominantly forms on microtubules in an intrinsic 2:1 stoichiometry, induced by spontaneous parallelization of dynein upon microtubule binding. Adaptors can squeeze in and exchange within the assembled microtubule-bound DD complex, which is enabled by relative rotations between dynein and dynactin, and further facilitated by dynein light intermediate chains that assist in an adaptor ‘search’ mechanism. Our findings elucidate the dynamic adaptability of the dynein transport machinery, and reveal a new mode for assembly of the motile complex.
Imaging-based screen identifies novel natural compounds that perturb cell and chloroplast division inChlamydomonas reinhardtii
Authors: Clark-Cotton Manuella R. , Chen Sheng-An , Gomez Aracely , Mulabagal Aditya , Perry Adriana , Malhotra Varenyam , Onishi Masayuki
Published: January 2025

Successful cell division requires faithful division and segregation of organelles into daughter cells. The unicellular algaChlamydomonas reinhardtiihas a single, large chloroplast whose division is spatiotemporally coordinated with furrowing. Cytoskeletal structures form in the same plane at the midzone of the dividing chloroplast (FtsZ) and the cell (microtubules), but how these structures are coordinated is not understood. Previous work showed that loss of F-actin blocks chloroplast division but not furrow ingression, suggesting that pharmacological perturbations can disorganize these events. In this study, we developed an imaging platform to screen natural compounds that perturb cell division while monitoring FtsZ and microtubules and identified 70 unique compounds. One compound, curcumin, has been proposed to bind to both FtsZ and tubulin proteins in bacteria and eukaryotes, respectively. InC. reinhardtii,where both targets coexist and are involved in cell division, curcumin at a specific dose range caused a severe disruption of the FtsZ ring in chloroplast while leaving the furrow-associated microtubule structures largely intact. Time-lapse imaging showed that loss of FtsZ and chloroplast division failure delayed the completion of furrowing but not the initiation, suggesting that the chloroplast-division checkpoint proposed in other algae requires FtsZ or is absent altogether inC. reinhardtii.

SIGNIFICANCE STATEMENT

Successful cell division requires the coordination of both organelle inheritance and cytokinesis. The unicellular algaChlamydomonas reinhardtii, which spatiotemporally coordinates the division of its chloroplast with cytokinesis, is an excellent model to study the regulation.

We screened libraries of natural compounds for perturbations of cell and/or chloroplast division, identifying 70 unique chemicals. By time-lapse microscopy using one of the hits, curcumin, we demonstrate that although chloroplast division failures delay the completion of cytokinesis, it does not impair initiation.

These findings suggest that the chloroplast-division checkpoint proposed in other algae requires FtsZ or is absent altogether inC. reinhardtii.
Fusobacterium nucleatumis enriched in invasive biofilms in colorectal cancer
Authors: Queen Jessica , Cing Zam , Minsky Hana , Nandi Asmita , Southward Taylor , Ferri Jacqueline , McMann Madison , Iyadorai Thevambiga , Vadivelu Jamuna , Roslani April , Loke Mun Fai , Wanyiri Jane , White James R. , Drewes Julia L. , Sears Cynthia L.
Published: January 2025

Fusobacterium nucleatumis an oral bacterium known to colonize colorectal tumors, where it is thought to play an important role in cancer progression. Recent advances in sequencing and phenotyping ofF. nucleatumhave revealed important differences at the subspecies level, but whether these differences impact the overall tumor ecology, and tumorigenesis itself, remain poorly understood. In this study, we sought to characterizeFusobacteriain the tumor microbiome of a cohort of individuals with CRC through a combination of molecular, spatial, and microbiologic analyses. We assessed for relative abundance ofF. nucleatumin tumors compared to paired normal tissue, and correlated abundance with clinical and pathological features. We demonstrate striking enrichment ofF. nucleatumand the recently discovered subspeciesanimalisclade 2 (Fna C2) specifically in colon tumors that have biofilms, highlighting the importance of complex community partnerships in the pathogenesis of this important organism.