bluuebunny/crossref_metadata_2025 huggingface dataset:
StrPhaser constructs tandem repeat alleles from VCF data
Authors: Wang Xuewen , King Jonathan , Meng Huang , Coble Michael D. , Woerner August E.
Published: January 2025

Variant calling is a ubiquitous genomic technique that underpins many scientific disciplines. From a computational perspective, variant calling is a form of logical compression; neglecting large variation, a person’s genome can be losslessly described as a set of differences (SNP and small InDel alleles) relative to the reference sequence. Another common genomic technique is haplotype phasing, wherein alleles are partitioned into their paternal and maternal components (as haplotypes). Some classes of alleles are more difficult to describe than others, e.g., short tandem repeats (STRs). STRs serve as a critical marker for many genetic assays. However, STRs tend not to be explicitly reported in most genomic workflows. Here, we present StrPhaser, a novel algorithm that leverages phased variant calling datasets in the VCF file format to construct STR alleles. We evaluated StrPhaser on ∼10,000 STR alleles from 284 human genomes, achieving an average allele accuracy of 91%. In addition, StrPhaser better recovers longer STR alleles than competing approaches; in principle, STR alleles that are longer than the maximum read length can be characterized. This capability, combined with its user-friendly interface, speed, and generation of both STR genotypes and visualizations, makes StrPhaser a valuable tool for a wide range of genomic studies.

Availability

The StrPhaser is publicly available athttps://github.com/XuewenWangUGA/StrPhaser.
MitoEdit: a pipeline for optimizing mtDNA base editing and predicting bystander effects
Authors: Shah Devansh , McCastlain Kelly , Chang Ti-Cheng , Wu Gang , Kundu Mondira
Published: January 2025

Short Structured Abstract

Motivation

Human mitochondrial DNA (mtDNA) mutations are causally implicated in maternally inherited mitochondrial respiratory disorders; however, the role of somatic mtDNA mutations in both late-onset chronic diseases and cancer remains less clear. Although recent advances in mtDNA base editing technology have the potential to model and characterize many of these mutations, current editing approaches are complicated by the potential for multiple unintentional edits (bystanders) that are only identifiable through empirical ‘trial and error’, thereby sacrificing valuable time and effort towards suboptimal construct development.

Results

We developed MitoEdit, a novel tool that incorporates empirical base editor patterns to facilitate identification of optimal target windows and potential bystander edits. MitoEdit allows users to input DNA sequences in a text-based format, specifying the target base position and its desired modification. The program generates a list of candidate target windows with a predicted number of bystander edits and their functional impact, along with flanking nucleotide sequences designed to bind TALE (transcription activator-like effectors) array proteins.In silicoevaluations indicate that MitoEdit can predict the majority of bystander edits, thereby reducing the number of constructs that need to be tested empirically. To the best of our knowledge, MitoEdit is the first tool to automate prediction of base edits.

Availability and implementation

MitoEdit is freely available at Kundu Lab GitHub (https://github.com/Kundu-Lab/mitoedit).

Contact

Corresponding email:Gang.Wu@stjude.org;Mondira.Kundu@stjude.org

Supplementary information

Supplementary data are available atBioinformaticsonline.
Structured simulation-based training with frugal ophthalmic instruments rapidly equips non-ophthalmologists to identify malarial retinopathy
Authors: Wilson Kyle J , Kousha Obaid , Nkume Harold , Liomba Alice M , Beare Nicholas AV , Blaikie Andrew
Published: January 2025

Background

Malaria, particularly cerebral malaria, poses a significant health threat, especially for children in sub-Saharan Africa. Identification of malarial retinopathy (MR) has diagnostic value in cerebral malaria but can be impractical due to lack of availability of trained and equipped ophthalmic specialists. Recent developments in low-cost simulation tools and ophthalmoscopes offer the potential to train non-ophthalmologists to offer fundus assessments in low-resource settings.

Methods

Twenty non-ophthalmologist healthcare providers in Malawi attended a training program focused on identification of MR using direct and binocular indirect ophthalmoscopy. The curriculum included didactic sessions, hands-on practice with simulation eyes, and assessment of skill acquisition with immediate feedback. Pre- and post-training confidence surveys were conducted.

Results

Participants demonstrated significant improvement in identification of malarial retinopathy after completing the training, with a mean accuracy of 83%. Clinician confidence levels increased across all domains of retinal examination covered in the course.

Conclusion

Structured simulation-based training using frugal ophthalmoscopes can equip non-ophthalmologists with skills to identify MR in simulation eyes. Future work should focus on long-term skill retention and validation in a real-world clinical setting.
Automated Oxygen Delivery in Home Setting for Patients with COPD on Long-Term Oxygen Therapy – a randomized crossover feasibility trial
Authors: Kofod Linette Marie , Hansen Ejvind Frausing , Kristensen Morten Tange , Brocki Barbara Cristina , Westerdahl Elisabeth
Published: January 2025

Rationale

Patients with COPD on long-term oxygen therapy (LTOT) have an unmet need for oxygen adjustments during sleep, rest, and activity, documented by continuous monitoring of oxygen saturation. While emerging technology enables automated adjustments, its feasibility in home settings remains uncertain. This randomized crossover trial evaluated the feasibility and preliminary effects of continuous automated oxygen titration in the homes of patients on LTOT.

Methods

The intervention involved four days of automated oxygen titration targeting a SpO₂ of 90-94% using a Bluetooth-connected electronic device and wrist pulse oximeter, forming a closed-loop system. Oxygen flow (0.9-6.8 L/min) was continuously adjusted based on SpO₂. During the control period, patients received their usual fixed dose oxygen. Feasibility was defined as successful automated titration time and time spent with normoxia. Changes in health status were measured using the Clinical COPD Questionnaire (CCQ).

Results

Twelve patients on LTOT (2.0±0.8 L/min) were included, with more than 217,000 paired SpO2and oxygen flow data points collected per patient. Oxygen flow was automatically adjusted for a median (IQR) of 77 (68.0–84.3) hours, covering 83% of the time. Time within target saturation increased significantly from 52% (42–63) to 86% (75–90) during intervention, with all patients utilizing the full available flow range. The CCQ score improved by 0.74±0.47 points, p <0.001.

Conclusion

Automated home oxygen titration is feasible, achieving more time with normoxia, but it required a wide flow range and continuous monitoring. The patients reported notable reductions in COPD symptoms.
TICTAC: Target Illumination Clinical Trial Analytics with Cheminformatics
Authors: Abok Jeremiah I , Edwards Jeremy S , Yang Jeremy J
Published: January 2025

Abstract

Introduction

Identifying disease–target associations is a pivotal step in drug discovery, offering insights that guide the development and optimization of therapeutic interventions. Clinical trial data serves as a valuable source for inferring these associations. However, issues such as inconsistent data quality and limited interpretability pose significant challenges. To overcome these limitations, an integrated approach is required that consolidates evidence from diverse data sources to support the effective prioritization of biological targets for further research.

Methods

We developed a comprehensive data integration and visualization pipeline to infer and evaluate associations between diseases and known and potential drug targets. This pipeline integrates clinical trial data with standardized metadata, providing an analytical workflow that enables the exploration of diseases linked to specific drug targets as well as facilitating the discovery of drug targets associated with specific diseases. The pipeline employs robust aggregation techniques to consolidate multivariate evidence from multiple studies, leveraging harmonized datasets to ensure consistency and reliability. Disease–target associations are systematically ranked and filtered using a rational scoring framework that assigns confidence scores derived from aggregated statistical metrics.

Results

Our pipeline evaluates disease–target associations by linking protein-coding genes to diseases and incorporates a confidence assessment method based on aggregated evidence. Metrics such as meanRank scores are employed to prioritize associations, enabling researchers to focus on the most promising hypotheses. This systematic approach streamlines the identification and prioritization of biological targets, enhancing hypothesis generation and evidence-based decision-making.

Discussion

This innovative pipeline provides a scalable solution for hypothesis generation, scoring, and ranking in drug discovery. As an open-source tool, it is equipped with publicly available datasets and designed for ease of use by researchers. The platform empowers scientists to make data-driven decisions in the prioritization of biological targets, facilitating the discovery of novel therapeutic opportunities.
Comparing Esri ArcGIS and SAS Geocoding Approaches: Test case with 3,238 Wisconsin addresses
Authors: Johnson Hannah K. , Hampton John M. , Arroyo Natalia , Schultz Amy , Gangnon Ronald E. , Malecki Kristen M. , Trentham-Dietz Amy
Published: January 2025

This report describes a comparison of two geocoding methods used by the Cohorts for Environmental Exposures and Cancer Risks (CEECR) consortium: ArcGIS Geocoding by Esri and the SAS GEOCODE Procedure. The goal of this report is to determine the comparability of data sets that employ different approaches for linking survey data with spatial surrogates of exposure to environmental and socioeconomic factors. ArcGIS and SAS GEOCODE were selected as two platforms for this comparison because both programs are being used by one or more CEECR cohort study teams and they can be used locally offline. The latter minimizes confidentiality issues related to online data linkages. Residential addresses from 3,238 Wisconsin residents in theCancer & COVID Studyand theWisconsin in situ Cohort(WISC) were geocoded and linked to eight different publicly available datasets of environmental and socioeconomic factors at various geographic scales using both geocoding platforms. Since the two analytic platforms vary in geocoding approaches, the validity and accuracy of both platforms were compared to examine differences when assigning surrogate measurements of exposure based on spatial locations. ArcGIS offered a higher specificity for matched addresses with slightly more latitude/longitude point and street matches (97.7%) than SAS (95.9%), with the remainder matching at the zip code level. The two geocoding platforms showed high concordance in assignment at the county (99.6%), census tract (96.5%), and census block group (94.7%). As a result, the correlations based on census tracts and block groups were very strong for linked exposure measures of socioeconomic status, environmental justice, urban/rural residence, air pollution, proximity to industrial sites, and cancer risk (all intraclass correlation coefficients ≥98%). Slightly lower concordance was observed for point source linkages (intraclass correlation coefficients 96-97%). Approximately ~4% of addresses were mis-matched largely in rural areas where census areas are larger and accurate geocoding base-layers are less widely available than in urban areas. For researchers that are already utilizing SAS, the GEOCODE procedure can be a logical choice as it is included in base SAS software and does not require an additional cost. However, SAS and ArcGIS provide similar options for the vast majority of study address locations.
Genomic Analysis of Trichotillomania
Authors: Halvorsen Matthew W. , Garrett Melanie E. , Cuccaro Michael L. , Ashley-Koch Allison E. , Crowley James J.
Published: January 2025

Trichotillomania (TTM) is a psychiatric condition in which people feel an overwhelming urge to pull out their hair, resulting in noticeable hair loss and significant distress. Twin, family and candidate gene studies suggest that TTM is at least partly genetic, but no genome-wide analyses have been completed. To fill the gap in this field, we have conducted a case-control study of genotype array data from 101 European ancestry TTM cases and 488 ancestry-matched unaffected controls. TTM cases were ascertained in the USA through web-based recruitment, patient support groups, and conferences organized by the Trichotillomania Learning Center. Following clinical confirmation of a TTM diagnosis, patients completed self-report assessments of frequency and duration of hair pulling, other psychiatric symptoms, and family history. Unaffected controls were also ascertained in the USA and were matched to cases by ancestry. In the first formal genome-wide association study of TTM, we did not identify any common variants with a genome-wide significant (P < 5×10−8) association level with case status. We found that TTM cases carry a higher load of common polygenic risk for psychiatric disorders than unaffected controls (P= 0.008). We also detected copy number variants previously associated with neuropsychiatric disorders in TTM cases (specifically, deletions inNRXN1, CSMD1, and 15q11.2). These results further support genetics’ role in the etiology of TTM and suggest that larger studies are likely to identify risk variation and, ultimately, specific risk genes associated with the condition.
Whole Genome Sequencing in Adolescent Idiopathic Scoliosis Cohort Indicates Polygenic Disease Involving Multiple Biological Pathways
Authors: Tuncay Islam Oguz , Lee Eun Kyoung , Gustafson Anxhela , Lee Yoonsuh , Jung Dawoon , Koh June-Young , Lee Wonchul , Lee Sangmoon , Shazand Kamran
Published: January 2025

Adolescent idiopathic scoliosis (AIS) is the most common nondegenerative spinal abnormality. Research indicates a strong correlation between genetics and AIS, with heritability estimates of 87.5%. However, the rarity of shared causative genes among patients, and the difficulty of replication between studies suggest that AIS is a highly complex polygenic disease. In this study, we utilized whole-genome sequencing (WGS) to comprehensively explore the genetic landscape of 119 AIS patients from 103 families. We implemented an automated WGS analysis pipeline powered by RareVisionTMconsisting of automated algorithms and manual curation. We identified clinically relevant candidate variants in 20/119 (16.8%) patients and potentially relevant strong or moderate candidate variants in another 73/119 (61.3%) patients. Candidate variants included coding and noncoding point mutations, along with structural variants and large indels, showing the utility of WGS. Candidate genes included AIS-associated genes (e.g.CHD7,COL11A1/2,FBN1/2,HSPG2,KIF7), as well as genes associated with other musculoskeletal and developmental syndromes where scoliosis is a known symptom (e.g.RYR1,GJB2,MYH2,MYH7). Association analysis showed 4 known AIS single nucleotide polymorphisms (rs12946942, rs10756785, rs3904778, rs7633294) also correlated with AIS in our cohort. Finally, through gene set enrichment analysis, we were able to identify 3 gene clusters involved in skeletal muscle contraction, extracellular matrix composition, and gene expression regulation. In summary, through scalable WGS-based familial testing we were able to (1) find clinically relevant genetic variations in the majority of our patients and (2) create a large dataset that allowed us to identify biological pathways relevant to AIS etiopathogenesis.
Known Group Validity of Assessment of Work Performance for Thai Homeless People
Authors: Thanapet Uthaikan , Ammawat Watthanaree , Rueankam Maliwan , Chatthong Winai , Khemthong Supalak
Published: January 2025

Background

Substance use and mental disorders are highly prevalent in Thai homeless people living with no mental health recovery. The lack of psychosocial occupational therapists may be one huge problem for none of the measurement outcomes for clinical utility. We aimed to determine the known-group validity of the Assessment of Work Performance (AWP) with good content and internal consistency reliability.

Methods

Participants (N = 60) were recruited by screening with no cognitive impairment, no psychiatric symptoms, independent self-care, and on-the-job assignment at Nonthaburi’s destitute home. Mann–Whitney U tests firstly found a significant difference in process skills between males and females (p < .05). Data analysis of the ceiling effect was then conducted to design using cleaned samples (N = 22), and the Mann–Whitney U tests secondly found a significant difference in communication skills between males and females (p < .05).

Results

There were no associations between the frequency of genders and substance abusers were computed using cross-tabulation (N = 60 versus N = 22). Besides a corrected sample, natural contexts of too easy job selection, no preparatory of supported employment, and non-purposeful living activities may be confounding factors of avolition, poor habit, and inactive life roles without wellness at the end of life.

Conclusion

These preliminary results suggest a useful AWP with good known-group validity for measuring outcomes among vulnerable people and describing how to improve motor, process, and interactive communication skills based on the Model of Human Occupation (MOHO) in occupational therapists and Mental Health Recovery (MHR) workers.
Simulating The Effect of the Radiotherapy on Cancer Stem Cell Evolution
Authors: Heryanto Yusri Dwi , Imoto Seiya
Published: January 2025

Radiotherapy is one of the most effective treatments for cancer. However, the radiation on cancer often leads to further tumor evolution and resistance. Accumulating evidence suggests that the cancer stem cells (CSCs) play a significant role in the tumor’s radioresistance and invasiveness. Therefore, we set out to investigate the aggressiveness and radioresistance that emerge because of radiation-induced selective pressures on CSCs. We developed an agent-based model (ABM) that tracks the evolution and growth of the cancer after treated by different regimens of radiotherapy. In the ABM, each cell is an agent that follows some predefined rules for their behaviors and interactions with other agents. We showed that the radiotherapy treatment increased the resistance, proliferation rate, and the CSC proportion of the tumor. Our simulation also showed that the CSC-targeted treatment is important for eliminating tumor completely.
Epidermal tumour-resistant progenitors require SOX2-driven developmental reprogramming to drive tumorigenesis
Authors: Centeno Patricia P , Chester Christopher , Ford Catriona A , Ridgway Rachel A , Cammareri Patrizia , Jamieson Thomas , Marais Richard , Campbell Andrew D , Sansom Owen J
Published: January 2025

The epidermal basal layer consists of two distinct progenitor populations contributing differentially to skin homeostasis or wound healing. However, their resilience to oncogenic insults is unknown. Here, we developed mouse models allowing lineage tracing and oncogene expression in both populations. Our findings support the existence of two long-lived and functionally distinct epidermal progenitors and define them as tumour-primed and tumour-resistant. The tumour-primed progenitors drive cutaneous squamous cell carcinoma (cSCC), within days from oncogenic expression resembling the rapid onset of BRAF-inhibitor-driven cSCC. The tumour-resistant progenitors transform gradually, requiring SOX2 activation. Once transformed, they share a transcriptomic profile revealing molecular hallmarks of epidermal transformation independently of the cell-of-origin or the oncogenic driving mutations. Importantly, SOX2 is expressed in a subset of cSCC patients hinting at its cell-of-origin. These highlight the need for an in-depth understanding of the cell-specific vulnerabilities that apply in each tissue to open new avenues for rational treatment.
Unraveling Dengue Serotype 3 Transmission in Brazil: Evidence for Multiple Introductions of the 3III_B.3.2 Lineage
Authors: Pereira James Siqueira , Slavov Svetoslav Nanev , Brcko Isabela Carvalho , Ribeiro Gabriela , de Souza Vinicius Carius , Ribeiro Igor Santana , De Lima Iago Trezena T. , Lima Borges Gleissy Adriane , de Lima Furtado Katia Cristina , da Silva Chagas Shirley Moreira , Barros da Costa Patricia Miriam Sayuri Sato , Adelino Talita , de Melo Iani Felipe C. , Junior Alcantara Luiz Carlos , Hill Verity , Grubaugh Nathan D. , Sampaio Sandra Coccuzzo , Elias Maria Carolina , Giovanetti Marta , Lima Alex Ranieri J.
Published: January 2025

Dengue, caused by DENV 1-4, remains a global public health concern, with Brazil experiencing some of the largest epidemics. The reemergence of DENV-3 in Brazil between 2023 and 2024 has raised concerns about new outbreaks due to the absence of sustained circulation of this serotype in recent years. This study investigates the dynamics of DENV-3 in Brazil, focusing on the spread of the 3III_B.3.2 lineage within genotype 3III and its introduction routes. We analyzed 1,536 DENV-3 genomes, all classified as genotype 3III, the dominant DENV-3 genotype in Brazil since 2001. Phylogenetic analysis identified the 3III_B.3.2 lineage in all recent Brazilian cases, with detections also reported in Central America, the United States, and Europe. At least six independent introduction events of this lineage into Brazil were identified, with the Caribbean region and Costa Rica as the primary sources. The earliest introduction likely occurred in late 2022 in Roraima, followed by introductions in São Paulo, Minas Gerais, and Pará. While one instance of interstate transmission was detected — from São Paulo to Minas Gerais — our findings indicate that external introductions, rather than domestic spread, were the primary drivers of DENV-3 circulation during this period. These results underscore the importance of continued genomic surveillance and coordinated public health strategies to monitor and mitigate future outbreaks.
Carbonic anhydrase 4 disruption and pharmacological inhibition reduce synaptic and behavioral adaptations following oxycodone withdrawal
Authors: Gupta Subhash C , Taugher-Hebl Rebecca J. , Ghobbeh Ali , Jahnke Marshal T. , Fan Rong , LaLumiere Ryan T. , Wemmie John A.
Published: January 2025

The ongoing opioid crisis underscores the need for innovative treatments targeting neurobiological mechanisms underlying opioid-seeking behaviors and relapse. Here we explored the role of carbonic anhydrase 4 (CA4) in modulating synaptic adaptations to oxycodone withdrawal in mice. We disrupted CA4 genetically and inhibited it pharmacologically with acetazolamide (AZD), a carbonic anhydrase inhibitor used clinically. We found that oxycodone withdrawal increased AMPAR/NMDAR ratio and synaptic recruitment of calcium-permeable AMPARs in nucleus accumbens core (NAcC) medium spiny neurons (MSNs). Synaptic changes required an extended period of abstinence, generalized across opioids including morphine and heroin, were specific to D1 dopamine receptor-expressing MSNs, and were prevented by CA4 disruption. AZD administrationin vitroandin vivoreversed the synaptic alterations, and effects of AZD depended on CA4 and acid sensing ion channel 1A (ASIC1A). Interestingly, abstinence from oxycodone did not affect dendritic spine density in NAcC MSNs, in contrast to previously observed effects of abstinence from cocaine. Finally, in an oxycodone self-administration paradigm, CA4 disruption and AZD reduced drug-seeking behaviors following 30 days of forced abstinence. Together, these findings identify a critical role for CA4 in synaptic adaptations in opioid withdrawn mice and drug-seeking behavior. Moreover, they suggest pharmacological inhibitors of CA4 may hold therapeutic potential for reducing opioid-seeking and relapse in opioid use disorder.
The central limit theorem for the number of mutations in the genealogy of a sample from a large population
Authors: Fu Yun-Xin
Published: January 2025

The number K of mutations identifiable in a sample of n sequences from a large population is one of the most important summary statistics in population genetics and is ubiquitous in the analysis of DNA sequence data. K can be expressed as the sum of n-1 independent geometric random variables. Consequently, its probability generating function was established long ago, yielding its well-known expectation and variance. However, the statistical properties of K is much less understood than those of the number of distinct alleles in a sample. This paper demonstrates that the central limit theorem holds for K, implying that K follows approximately a normal distribution when a large sample is drawn from a population evolving according to the Wright-Fisher model with a constant effective size, or according to the constant-in-state model, which allows population sizes to vary independently but bounded uniformly across different states of the coalescent process. Additionally, the skewness and kurtosis of K are derived, confirming that K has asymptotically the same skewness and kurtosis as a normal distribution. Furthermore, skewness converges at speed $1/\sqrt{\ln(n)}$ and while kurtosis at speed $1/\ln(n)$. Despite the overall convergence speed to normality is relatively slow, the distribution of K for a modest sample size is already not too far from normality, therefore the asymptotic normality may be sufficient for certain applications when the sample size is large enough.
The cost of diarrhoea: a household perspective from seven countries in the Global Enteric Multicenter Study (GEMS)
Authors: Al Fidah Md Fuad , Islam Md Ridwan , Amin Rukaeya , Nuzhat Sharika , Ahmed Tahmeed , Faruque ASG
Published: January 2025

Background

The burden of diarrhoeal diseases is considerable in South Asia, as well as in sub-Saharan Africa (SSA). Its economic impact is more profound in resource-limited settings like low- and middle-income countries (LMICs). In this study, we aimed to estimate the direct and indirect cost reported by the caregivers of participants from seven LMICs.

Methods

The current study used data from the multicenter, Global Enteric Multicenter Study (GEMS) which enrolled under-5 children (U5C). This prospective case-control study was conducted in 7 sites, all of them located in LMICS. Cost data was collected from the caregivers and after adjustment for inflation, were converted into International Dollar (I$). Quantile regression models were developed after adjusting for age, sex and country.

Results

This study analyzed data from 4,592 participants. The median (IQR) total direct cost (TDC) and total indirect cost (TIC) were 8.4 (11.0) I$ and 10.2 (14.3) I$, respectively. Statistically significant differences were found across continents for multiple variables. The highest median TDC and TIC was in Bangladesh (13.6 I$ and 23.2 I$ respectively), while Mozambique reported the lowest (0.4 I$ and 4.9 I$ respectively) with medication accounting for 60.9% of TDC. Quantile regression analysis showed TDC was positively associated with factors like family size, urban residence, moderate-to-severe disease, caregiver education, and use of rehydration methods, while treated drinking water and overweight status were negatively associated. TIC was significantly associated with seeking prior care.

Conclusion

The indirect cost of diarrhoea was higher than the direct cost which indicates the impact of lost productivity due to the disease. Bolstering the healthcare financing systems, ensuring affordable medication, promoting WASH initiative and timely healthcare-seeking can reduce the economic burden.
A micro-ChromaDot array with AI integration for the detection of multiple biomarkers in a small portable device
Authors: Lin Zuan-Tao , Peng Yun , Kong Yifei , Zhang Yi , Shou Wan , Jana Biswabandhu , Korupolu Sandeep , Gao Shilin , Li Yongli , Liang Chen , Wang Zhilong , Matusik Wojciech , Wu Mei X.
Published: January 2025

With the rapid growth of digital healthcare, diagnosis, prognosis, and monitoring of chronic and acute diseases at home are increasingly in demand. In light of the intricate biological processes underlying many diseases, a single biomarker is often insufficient for disease diagnosis, whereas multiplexed measurements of biomarkers remain a significant challenge at point-of-care (POC). Herein, we introduce a micro-ChromaDot array (McDa) designed to qualify a panel of biomarkers at POC in a one-biomarker-one-dot fashion. The McDa colorimetric signals were engraved from a 3D microneedle array with chem-spatial signal amplification cascade, which allowed seamless and precise data acquisition and analysis by smartphone. This home-use and cost-effective platform achieved similar specificity and superior sensitivity to conventional enzyme-linked immunoassay (ELISA), a clinic assay that typically requires a fully equipped laboratory, and trained personnel, and is time-consuming. Five biomarkers of clinical sera, collected from a cohort of systemic lupus erythematosus (SLE) patients (n = 42) and healthy controls (n = 34), were measured by McDa and modeled with deep learning. By leveraging the support vector machines (SVM) model combined with 5-fold cross-validation, we demonstrated that a selected panel of three biomarkers effectively discriminated SLE patients from healthy controls with a remarkable 97% specificity, representing an impressive 70% improvement over the clinical standard of the single biomarker antinuclear antibodies (ANA) test, while sustaining the same 93% sensitivity. This platform can easily adapt to assess other biomarkers with a mere drop of blood or any other body liquids and holds great promise to transform POC.
Different functions for the lateral line in schooling behavior in three fish species
Authors: Tidswell Ben K. , Tytell Eric D.
Published: January 2025

Fish use vision and the lateral line in order to school together. Previous studies suggest that some species rely more than others on the lateral line for schooling, and no clear mechanistic reason for these differences has been identified. To address the question of how species-level differences in the lateral line might impact schooling behavior, we identified three schooling species (giant daniosDevario aequipinnatus, cherry barbsPuntius titteya, and neon tetrasParacheirodon innesi) that come from different environments and have differently structured lateral line systems. We expected to see larger changes in schooling behavior in species of fish with more neuromasts. To test this hypothesis we imaged the lateral lines of these fishes, then quantified schooling behavior before and after lateral line ablation. Giant danios had the lowest density of neuromasts and, as expected, showed little response to ablation. Cherry barbs and neon tetras both had higher densities of neuromasts and schooled differently after ablation, but in opposite ways. Cherry barbs became a less cohesive school while neon tetras formed a more cohesive school. Both of these species had a greater density of neuromasts than giant danios, but the cherry barbs had a greater number of canal neuromasts. This difference in canal neuromasts in cherry barbs may explain the differences in schooling behavior after ablation if they depended more on them for schooling. Overall, these results shed light on the importance of the lateral line, and the diversity of roles it plays in fish schooling.
Optimized antibody with W32I mutation enhances antiviral efficacy against influenza
Authors: Guan Shanshan , Wang Qingyu , Nie Jiaojiao , Yao Xin , Xie Kunpeng , Zhao Weihao , Chang Yaotian , Zhu Lvzhou , Hui Jiaru , Yin Tieyan , Liu Xiaopan , Shan Yaming
Published: January 2025

The influenza virus has caused a global pandemic with significant morbidity and mortality, highlighting the need to optimize antibodies for improved antiviral efficacy. The 3E1 antibody effectively neutralizes influenza subtypes H1 and H5 by inhibiting acid-induced conformational changes of hemagglutinin (HA). This study aimed to optimize the antibody’s bioactivity by modifying amino acid residues, resulting in single-point mutants (3E1-L [W32I], 3E1-H [F103I]) and a double mutant (3E1-H+L [F103I, W32I]). The binding affinity, neutralizing activity, and antiviral mechanisms of the mutants were evaluated. Notably, the 3E1-L mutant showed significantly enhanced antiviral activity against H1N1 and H3N2 compared to wild-type 3E1, inhibiting both viral entry and release. The prophylactic and therapeutic efficacy of the 3E1-L mutant was validated. Molecular dynamics simulations of the 3E1-L/HA complex showed that the W32I mutation reduces steric hindrance between tryptophan at position 32 and the complementarity-determining region (CDR) L1 loop of HA. In conclusion, the W32I substitution enhances the antiviral activity of wild-type 3E1, making the optimization of 3E1-L a promising strategy for developing more effective influenza therapies.
High short tandem repeat mutation recurrence in heat-stressedArabidopsis thalianalines
Authors: Reinar William B. , Greulich Anne , Lalun Vilde O. , Butenko Melinka A. , Jakobsen Kjetill S.
Published: January 2025

The rise of the annual average temperature presents a strong selection pressure for many species. Sessile organisms, such as the plantArabidopsis thaliana(A. thaliana), need to adapt to elevated temperatures. Here, we conducted a mutation accumulation experiment inA. thalianaunder high temperature to monitor genetic changes over nine generations in three parallel lines compared to three lines under normal growth conditions. Whole-genome sequencing of every sample allowed us to accurately capture mutations in troublesome regions by utilizing the genotypes of both parent and offspring. Our approach revealed that high temperature treatment disproportionally increased the rate of insertions and deletions in dimeric short tandem repeats (STRs) compared to the rate of single nucleotide variants. Recurrent mutations appeared more often than expected, indicating a mutation bias along the genome sequence. Our study sheds light on the mutational landscape of a plant genome when exposed to high temperature stress and points to STRs as key genomic elements that rapidly increase the standing genetic variation available for natural selection.
A serotonergic mechanism is involved in the pro-cognitive effect of AM6545 treatment in a mouse model of fragile X syndrome
Authors: de los Reyes-Ramírez Lucía , Bergadà-Martínez Araceli , Martínez-Torres Sara , Martínez-Gallego Irene , Losada-Ruiz Pilar , Arboleya Silvia , Gueimonde Miguel , Maldonado Rafael , Rodríguez-Moreno Antonio , Ozaita Andrés
Published: January 2025

Fragile X syndrome (FXS) is the principal monogenic syndrome leading to inherited intellectual disability and autism. It is caused by the silencing ofFMR1gene that leads to the loss in the expression of its encoded protein, the fragile X messenger ribonucleoprotein 1 (FMRP). In synapses, FMRP has a key role in local mRNA modulation to maintain synaptic plasticity. TheFmr1KO (FX) mouse model shows cognitive impairment and some of the synaptic traits present in individuals with FXS together with alterations in gut microbiota. Previous studies revealed that pharmacological and genetic cannabinoid type-1 receptor (CB1R) inhibition significantly prevented central key alterations in FX mice. Here, we aimed to evaluate the effect of a sub-chronic treatment with the largely peripherally-restricted CB1R antagonist AM6545. We found that AM6545 reduced memory deficits and restored enhanced hippocampal mGluR5-dependent long-term depression and aberrant dendritic spine density in FX mice. At the peripheral level, AM6545 modified altered FX mice fecal microbiota composition, while in the hippocampus AM6545 treatment upregulated hippocampalHtr4, the gene encoding for serotonin receptor 4 (5-HT4R) This upregulation positively correlated with memory performance. Notably, acute pharmacological blockade of 5-HT4R abolished the pro-cognitive effect produced by AM6545. Together, our results suggest that peripheral CB1R inhibition ameliorates key alterations in FX mouse model and modifies the expression of serotonergic receptors important for cognitive performance.
Lipidomic Analysis Reveals Drug-Induced Lipoxins in Glaucoma Treatment
Authors: Mathew DJ , Maurya S , Ho J , Livne-Bar I , Chan D , Buys Y , Sit M , Trope G , Flanagan JG , Gronert K , Sivak JM
Published: January 2025

Synthetic prostaglandin analogues, such as latanoprost, are first-line treatments to reduce intraocular pressure (IOP) in the management of glaucoma, treating millions of patients daily. Glaucoma is a leading cause of blindness, characterized by progressive optic neuropathy, with elevated IOP being the sole modifiable risk factor. Despite this importance, the underlying latanoprost mechanism is still not well defined, being associated with both acute and long term activities, and ocular side effects. Prostaglandins are eicosanoid lipid mediators. Yet, there has not been a comprehensive assessment of small lipid mediators in glaucomatous eyes. Here we performed a lipidomic screen of aqueous humour sampled from glaucoma patients or healthy control eyes. The resulting signature was surprisingly focused on significantly elevated levels of arachidonic acid (AA) and the potent proresolving mediator, lipoxin A4(LXA4) in glaucoma eyes. Subsequent experiments revealed that this response is due to latanoprost actions, rather than a consequence of elevated IOP. We demonstrated that increased LXA4inhibits pro-inflammatory cues and promotes TGF-β3mediated tissue remodeling in the anterior chamber. In concert, an autocrine prostaglandin circuit mediates rapid IOP-lowering. This work reveals parallel mechanisms underlying acute and long-term latanoprost activities during the treatment of glaucoma.
ECLARE: multi-teacher contrastive learning via ensemble distillation for diagonal integration of single-cell multi-omic data
Authors: Mann-Krzisnik Dylan , Li Yue
Published: January 2025

Integrating multimodal single-cell data, such as scRNA-seq and scATAC-seq, is key for decoding gene regulatory networks but remains challenging due to issues like feature harmonization and limited quantity of paired data. To address these challenges, we introduceECLARE, a novel framework combining multi-teacher ensemble knowledge distillation with contrastive learning for diagonal integration of single-cell multi-omic data.ECLAREtrains teacher models on paired datasets to guide a student model for unpaired data, leveraging a refined contrastive objective and transport-based loss for precise cross-modality alignment. Experiments demonstrateECLARE’s competitive performance in cell pairing accuracy, multimodal integration and biological structure preservation, indicating that multi-teacher knowledge distillation provides an effective mean to improve a diagonal integration model beyond its zero-shot capabilities. Additionally, we validateECLARE’s applicability through a case study on major depressive disorder (MDD) data, illustrating its capability to reveal gene regulatory insights from unpaired nuclei. While current results highlight the potential of ensemble distillation in multi-omic analyses, future work will focus on optimizing model complexity, dataset scalability, and exploring applications in diverse multi-omic contexts.ECLAREestablishes a robust foundation for biologically informed single-cell data integration, facilitating advanced downstream analyses and scaling multi-omic data for training advanced machine learning models.
Molecular Mechanisms of Drug Resistance and Compensation in SARS-CoV-2 Main Protease: The Interplay Between E166 and L50
Authors: Zvornicanin Sarah N. , Shaqra Ala M. , Flynn Julia , Carias Martinez Heidi , Jia Weiping , Moquin Stephanie , Dovala Dustin , Bolon Daniel N. , Kurt Yilmaz Nese , Schiffer Celia A.
Published: January 2025

The SARS-CoV-2 main protease (Mpro) is essential for viral replication, and a primary target for COVID-19 antivirals. Direct-acting antivirals such as nirmatrelvir, the active component of Paxlovid, target the Mproactive site to block viral polyprotein cleavage and thus replication. However, drug resistance mutations at the active site residue Glu166 (E166) have emerged inin vitroselection studies, raising concerns about the durability of current antiviral strategies. Here, we investigate the molecular basis of drug resistance conferred by E166A and E166V mutations against nirmatrelvir and the related PF-00835231, individually and in combination with the distal mutation L50F. We found that E166 mutations reduce nirmatrelvir potency by up to 3000-fold while preserving substrate cleavage, with catalytic efficiency reduced by only up to 2- fold. This loss of catalytic efficiency was compensated for by the addition of L50F in the double- mutant variants. We have determined three cocrystal structures of the E166 variants (E166A, E166V, and E166V/L50F) bound to PF-00835231. Comparison of these structures with wild- type demonstrated that E166 is crucial for dimerization and for shaping the substrate-binding S1 pocket. Our findings highlight the mutability of E166, a prime site for resistance for inhibitors that leverage direct interactions with this position, and the potential emergence of highly resistant and active variants in combination with the compensatory mutation L50F. These insights support the design of inhibitors that target conserved protease features and avoid E166 side- chain interactions to minimize susceptibility to resistance.
Toti: an integrated multi-omics database to decipher the epigenetic regulation of gene expression in totipotent stem cells
Authors: Chai Yi , Zhang Ruiying , Jia Shunze , Zhu Danfei , Chen Siyi , Fu Xudong , Sheng Xin
Published: January 2025

Totipotent cells (TSCs), the origin of mammalian life and foundation to early mammalian embryogenesis, are characterized by the highest differentiation capacity and extensive developmental potential. However, none of the existing embryonic databases have provided epigenetic and transcriptomic resources on totipotency, greatly limiting our understanding of the mechanisms governing the establishment and exit of totipotency. Here, we present Toti, a pioneering multi-omics database exclusively developed for totipotency, coveringin vivo,in vitroand genome-edited human and mouse embryonic TSCs, TSC-like cells, pluripotent cells (PSCs), and embryos spanning preimplantation stages, with a total of 8,265 samples. Toti facilitates an in-depth exploration of the molecular mechanisms underlying totipotency by offering Search, Browse and Analysis modules available athttp://toti.zju.edu.cn/.
Unveiling Cognitive Processes Underlying Depression-like Behaviors in the Force Swim and Tail Suspension Tests
Authors: Li Zhihan , Lu Tianyu , Yan Jiaozhao , Zhang Xiang , Li Yun-Feng
Published: January 2025

The forced swim test (FST) and tail suspension test (TST) are widely used to assess depression-like behaviors in rodents, with immobility time serving as a primary metric. However, this measure oversimplifies the complex cognitive processes involved, obscuring the relationship between immobility and cognitive biases. Here, we employ a custom-developed tool to capture complete behavioral trajectories in mice and apply reinforcement learning models for systematic analysis. Our findings indicate that behaviors in both tests can be interpreted as reinforcement learning processes that encompass learning, consequence perceiving, and decision-making. Notably, the underlying cognitive processes differ between the two tests, challenging the assumption that the FST and TST are interchangeable for cross-validation. Additionally, we exam two methods for inducing depression-like behavior: chronic restraint stress and medial prefrontal cortex inhibition. Both approaches increase immobility by altering learning dynamics and consequence sensitivity. Regression analyses further reveal two distinct behavior phases: an early phase dominated by learning-related factors and a later phase influenced by consequence sensitivity. These results suggests that conventional metrics focus solely on the final minutes of testing may underestimate learning processes while overemphasize sensitivity to consequences. Our study underscores the importance of computational modeling in revealing the complex cognitive mechanisms underlying animal behavior.
Dietary protein source mediates colitis pathogenesis through bacterial modulation of bile acids
Authors: Gray Simon M. , Wood Michael C. , Mulkeen Samantha C. , Ahmed Sunjida , Thaker Shrey D. , Chen Bo , Sander William R. , Bibeva Vladimira , Zhang Xiaoyue , Yang Jie , Herzog Jeremy W. , Zhang Shiying , Dogan Belgin , Simpson Kenneth W. , Sartor R. Balfour , Montrose David C.
Published: January 2025

Introductory paragraph

Evidence-based dietary recommendations for individuals with inflammatory bowel diseases (IBD) are limited. Red meat consumption is associated with increased IBD incidence and relapse in patients, suggesting that switching to a plant-based diet may limit gut inflammation. However, the mechanisms underlying the differential effects of these diets remain poorly understood. Feeding diets containing plant- or animal-derived proteins to murine colitis models revealed that mice given a beef protein (BP) diet exhibited the most severe colitis, while mice fed pea protein (PP) developed mild inflammation. The colitis-promoting effects of BP were microbially-mediated as determined by bacterial elimination or depletion and microbiota transplant studies. In the absence of colitis, BP-feeding reduced abundance ofLactobacillus johnsoniiandTuricibacter sanguinisand expandedAkkermansia muciniphila, which localized to the mucus in association with decreased mucus thickness and quality. BP-fed mice had elevated primary and conjugated fecal bile acids (BAs), and taurocholic acid administration to PP-fed mice worsened colitis. Dietary psyllium protected against BP-mediated inflammation, restored BA-modulating commensals and normalized BA ratios. Collectively, these data suggest that the protein component of red meat may be responsible, in part, for the colitis-promoting effects of this food source and provide insight into dietary factors that may influence IBD severity.
PathX-CNN: An Enhanced Explainable Convolutional Neural Network for Survival Prediction and Pathway Analysis in Glioblastoma
Authors: Sobhan Masrur , Islam Md Mezbahul , Mondal Ananda Mohan
Published: January 2025

Motivation

Convolutional neural networks (CNNs) offer potential for analyzing non-grid structured data, such as biological array data, by converting it into image-like formats using principal component analysis (PCA) of pathway genes. However, PCA-derived principal components (PCs) from the entire dataset capture global variance but fail to extract sub-cohort (class-specific) variances. Consequently, CNNs trained on global PCs perform poorly in survival prediction of glioblastoma multiforme (GBM), and the corresponding explanation of CNN outcomes may not align with disease-relevant pathways.

Results

We present PathX-CNN, an explainable CNN framework that addresses these limitations by integrating multi-omics data through pathway-based images derived from sub-cohort-specific PCs. PathX-CNN outperformed existing pathway-based methods in predicting long-term survival (LTS) versus non-LTS in GBM. By leveraging SHAP (SHapley Additive exPlanations), a cooperative game theory-based explainable AI method, PathX-CNN identified biologically plausible pathways associated with GBM survival. Additionally, experiments on other cancer types demonstrated superior performance compared to traditional approaches. PathX-CNN demonstrates the potential of CNNs for multiomics integration, offering both improved prediction accuracy and pathway-specific insights into disease mechanisms.

Code Availability

https://github.com/codebysobhan/PathX-CNN

Contact

amondal@fiu.edu

Supplementary information

Supplementary data are available atBioinformaticsonline.