Biology subjects

Patil, K.

Publications and source records attributed to Patil, K..

17 recordsLinked to original sources

bioRxiv2026

Widespread use of invalid statistical tests in biomedical machine learning

Cross-validation is routinely used to compare performance in biomedical artificial intelligence. Standard tests ignore correlation across cross-validation folds, inflating false-positive rates. In a PRISMA-guided meta-analysis of 184 studies (impact factor [≥] 15) across 30 biomedical fields, 97% use invalid tests. Among studies with abstract-level claims supported by invalid tests, 59% rely on a spurious comparison: one that loses significance after correcting for this correlation. On average, regaining significance requires a 43% larger effect. Extending these findings to the broader literature, we estimate that spurious comparisons occur in nearly two in three studies and support abstract-level claims in nearly one in three studies. Simulations confirm false-positive rates paradoxically approach 100% when cross-validation is repeated to improve stability. We introduce SHARP, a redesign of cross-validation, which best balances false-positive control and power among 13 benchmarked tests. These results reveal widespread fragility in biomedical artificial intelligence and offer a practical route to valid comparisons.

bioinformatics↗

bioRxiv2026

Normative Deviations Reveal Task-Evoked and Clinical Network Reorganization

Understanding how cognitive demands and pathology reshape large-scale functional connectivity (FC) requires methods that are both multivariate and region-specific. Here we introduce One-class SVM-based Connectome Anomaly Recognition (OSCAR), a normative modelling framework that detects condition-related deviations in the multivariate connectivity profile of a brain region. OSCAR learns the distribution of region-to-whole-brain connectivity patterns given a reference state sample (e.g. resting-state data; RS) using a one-class support vector machine (OCSVM). The trained models are then applied to FC profiles from a target condition (e.g., task or patient group). The outlier proportions are used to quantify the difference between the reference and target condition. We validated OSCAR on three diverse tasks and a patient cohort with early psychosis. OSCAR consistently identified condition-sensitive regions in networks known to support conflict processing, object-location memory, lexical learning, and early psychosis, respectively, including thalamic and basal ganglia regions. Moreover, it detected additional well-established task- or disease-relevant parcels not captured by the comparison method permutation-based multivariate analysis of variance (perMANOVA). Regions flagged by OSCAR were at least as close, and often closer, to independent task-activation findings than those identified by perMANOVA. These results demonstrate that OSCAR provides an interpretable, region-centred normative modelling approach that is sensitive to subtle multivariate FC deviations, and offers a practical tool for mapping condition-specific reconfigurations of functional brain networks with high external validity, in both experimental and clinical settings.

neuroscience↗

bioRxiv2025

Sub-cellular chemical mapping in bacteria using correlated cryogenic electron and mass spectrometry imaging

Electron cryomicroscopy (cryo-EM) allows high-resolution spatial visualization of biological specimens, however, it is challenging to chemically identify densities observed in cryo-EM. To overcome this, we combined cryo-EM with chemical imaging using focused ion beam secondary ion mass spectrometry (FIB-SIMS) for integrated spatio-chemical analysis of untagged specimens. We show that our correlative workflow permits sub-cellular localisation of molecules inside bacterial cells and is compatible with cryogenic light microscopy and FIB-milled lamellae of multicellular specimens. To highlight biological insights enabled by the workflow, we studied the uptake of Bisphenol-AF, a widespread chemical pollutant, by environmental bacteria, revealing the storage of these chemicals within cytosolic phase-separated aggregates in pollutant-exposed cells, where they cannot be removed by the bacterial efflux machinery despite its robust upregulation. These mechanistic insights were directly facilitated by the versatile cryo-EM-FIB-SIMS technique, showing that it is an effective avenue to map elemental and molecular signatures in near-native biological samples, which can be extended in the future for multiple applications in cell biology and imaging.

molecular biology↗

bioRxiv2024

Can we predict sleep health based on brain features? A large-scale machine learning study

BackgroundsSeveral correlational or group comparison evidence highlighted robust associations between sleep health and macro-scale brain organization. However, inter-individual variability is critical in such interplay. Therefore, in this study, we aimed to investigate the role of brain imaging features in predicting diverse sleep health-related characteristics at the individual subject level using the Machine Learning (ML) approach. MethodsA sample of 28,088 participants from the UK Biobank was employed to calculate 4677 structural and functional neuroimaging markers. Then, we employed them to predict self-reported insomnia symptoms, sleep duration, easiness of getting up in the morning, chronotype, daily nap, daytime sleepiness, and snoring. To assess the predictability of brain features, we built seven different linear and nonlinear ML models for each sleep health-related characteristic. ResultsWe performed extensive ML analyses that involved more than 19 years of compute time. We observed relatively low performance in predicting all sleep health-related characteristics from brain images (e.g., balanced accuracy ranging between 0.50-0.59). Across all models, the best performance achieved was 0.59, using a linear ML model to predict the ease of getting up in the morning. In fact, a similar performance was achieved with models trained solely on age and sex, indicating that these demographic factors might be the ones driving the predictions. ConclusionsThe low capability of multimodal neuroimaging markers in predicting sleep health-related characteristics, even under extensive ML optimization in a large population sample, suggests a complex relationship between sleep health and brain organization.

neuroscience↗

bioRxiv2024

Coupled Solvent Dynamics and Protein Dynamics Help Drive Functional Differences in Exon-19 Deletion Mutants in the Epidermal Growth Factor Receptor (EGFR/ErbB1/HER1) Kinase Domain

Deletions in Exon-19 of the epidermal growth factor receptor (EGFR) play a pivotal role in the pathogenesis of non-small cell lung cancer (NSCLC), influencing patient response to tyrosine kinase inhibitors (TKIs). Although these mutations are known to affect treatment efficacy, the precise molecular mechanisms have been unclear. Building upon recent insights from the study [DOI: 10.1038/s41467-022-34398-z], which identified two distinct mutation profiles associated with differential drug sensitivity and clinical outcomes, our research delves into the molecular dynamics that drive these variances. We employed molecular dynamics simulations, enhanced sampling methods, and machine learning to classify Exon-19 deletion mutations into two profiles based on their conformational dynamics. Profile 1 mutations display only localized motions in key subdomains in their fluctuations about the equilibrium state, and a high affinity for ATP and consequent resistance to TKIs, while profile 2 mutations show reduced ATP binding affinity due to delocalized motion characterized by an increased flexibility between the N- and C-lobes of the EGFR kinase domain. This structural flexibility perturbs the ATP binding site, leading to decreased affinity and, heightened sensitivity to TKIs. Our use of the INDirect Umbrella Sampling (INDUS) technique has shed light on the collective solvent dynamics, further elucidating the coupling between long timescale solvent fluctuations and protein conformational dynamics, that likely contributes to the observations in HDX-MS studies. Our free energy analysis, covering timescales relevant to both HDX-MS and ligand interaction, provides a deeper understanding of the relationship between protein and solvent dynamics and their collective impact on drug efficacy in NSCLC with EGFR Exon-19 deletions. Significance StatementEGFR Exon 19 deletion mutations are key drivers in non-small cell lung cancer (NSCLC), yet their drug sensitivity to tyrosine kinase inhibitors (TKIs) varies significantly. This study identifies two mutation profiles: mutations that exhibit high ATP binding affinity and localized conformational motion, driving TKI resistance, and mutations that show reduced ATP affinity due to delocalized structural flexibility, enhancing TKI sensitivity. Using molecular dynamics simulations and free energy sampling techniques, we reveal how solvent fluctuations and protein dynamics collectively affect drug binding and efficacy. These findings provide a mechanistic basis for differential drug sensitivity, informing precision medicine strategies for NSCLC patients with EGFR Exon-19 mutations.

biophysics↗

bioRxiv2024

Conformational flexibility is a critical factor in designing broad-spectrum human norovirus protease inhibitors

Human norovirus (HuNoV) infection is a global health and economic burden. Currently, there are no licensed HuNoV vaccines or antiviral drugs available. The protease encoded by the HuNoV genome plays a critical role in virus replication by cleaving the polyprotein and is, therefore, an excellent target for developing small molecule inhibitors. While rupintrivir, a potent small-molecule inhibitor of several picornavirus proteases, effectively inhibits GI.1 protease, it is an order of magnitude less effective against GII protease. Other GI.1 protease inhibitors also tend to be less effective against GII proteases. To understand the structural basis for the potency difference, we determined the crystal structures of proteases of GI.1, pandemic GII.4 (Houston and Sydney), and GII.3 in complex with rupintrivir. These structures show that the open substrate pocket in GI protease binds rupintrivir without requiring significant conformational changes, whereas, in GII proteases, the closed pocket flexibly extends, reorienting arginine-112 in the BII-CII loop to accommodate rupintrivir. Structures of R112A protease mutants with rupintrivir, coupled with enzymatic and inhibition studies, suggest R112 is involved in displacing both substrate and ligands from the active site, implying a role in the release of cleaved products during polyprotein processing. Thus, the primary determinant for differential inhibitor potency between the GI and GII proteases is the increased flexibility in the BII-CII loop of the GII proteases caused by H-G mutation in this loop. Therefore, the inherent flexibility of the BII-CII loop in GII proteases is a critical factor to consider when developing broad-spectrum inhibitors for HuNoV proteases. IMPORTANCEHuman noroviruses are a significant cause of sporadic and epidemic gastroenteritis worldwide. There are no vaccines or antiviral drugs currently available to treat infections. Our work elucidates the structural differences between GI.1 and GII proteases in response to inhibitor binding and will inform the future development of broad-spectrum norovirus protease inhibitors.

biochemistry↗

bioRxiv2024

2'-Fucosyllactose Inhibits Human Norovirus Replication in Human Intestinal Enteroids

Human noroviruses (HuNoVs) are the leading cause of acute gastroenteritis worldwide. Currently, there are no targeted antivirals for the treatment of HuNoV infection. Histo-blood group antigens (HBGAs) on the intestinal epithelium are cellular attachment factors for HuNoVs; molecules that block the binding of HuNoVs to HBGAs thus have the potential to be developed as antivirals. Human milk oligosaccharides (HMOs) are glycans in human milk with structures analogous to HBGAs. HMOs have been shown to act as decoy receptors to prevent the attachment of multiple enteric pathogens to host cells. Previous X-ray crystallography studies have demonstrated the binding of HMO 2-fucosyllactose (2FL) in the same pocket as HBGAs for some HuNoV strains. We evaluated the effect of 2FL on the replication of a globally dominant GII.4 Sydney [P16] HuNoV strain using human intestinal enteroids (HIEs) from adults and children. A significant reduction in GII.4 Sydney [P16] replication was seen in duodenal and jejunal HIEs from multiple adult donors, all segments of the small intestine from an adult organ donor and in two pediatric duodenal HIEs. However, 2FL did not inhibit HuNoV replication in two infant jejunal HIEs that had significantly lower expression of 1-2-fucosylated glycans. 2FL can be synthesized in large scale, and safety and tolerance have been assessed previously. Our data suggest that 2FL has the potential to be developed as a therapeutic for HuNoV gastroenteritis. IMPORTANCEHuman noroviruses infect the gastrointestinal tract and are a leading cause of acute gastroenteritis worldwide. Common symptoms of norovirus include diarrhea, vomiting and stomach cramps. Virus shedding and symptoms are prolonged and debilitating in immunocompromised patients. Currently, there are no approved vaccines or targeted antivirals for treating human norovirus infection. Human intestinal enteroids derived from intestinal stem cells allow the successful replication of norovirus in the laboratory and can be used as a physiologically relevant model system to evaluate antivirals. We discovered that 2fucosyllactose (2FL), an oligosaccharide naturally occurring in human milk, inhibits norovirus replication in HIEs from multiple donors and thus has the potential to be developed as a therapeutic for human norovirus. These findings have high translational potential since 2FL from several manufacturers have GRAS (generally recognized as safe) status and can be synthesized on a large scale for immediate application.

microbiology↗

bioRxiv2024

Advancements in Human Norovirus Cultivation in Human Intestinal Enteroids

Human noroviruses (HuNoVs) are a significant cause of epidemic and sporadic acute gastroenteritis worldwide. The lack of a reproducible culture system hindered the study of HuNoV replication and pathogenesis for almost a half-century. This barrier was overcome with our successful cultivation of multiple HuNoV strains in human intestinal enteroids (HIEs), which has significantly advanced HuNoV research. We optimized culture media conditions and generated genetically-modified HIE cultures to enhance HuNoV replication in HIEs. Building upon these achievements, we now present new insights to this culture system, which involve testing different media, unique HIE lines, and additional virus strains. HuNoV infectivity was evaluated and compared in new HIE models, including HIEs generated from different intestinal segments of individual adult organ donors, HIEs from human intestinal organoids produced from directed differentiation of human embryonic stem cells into intestinal organoids that were transplanted and matured in mice before making enteroids (H9tHIEs), genetically-engineered (J4FUT2 knock-in [KI], J2STAT1 knock-out [KO]) HIEs, as well as HIEs derived from a patient with common variable immunodeficiency (CVID) and from infants. Our findings reveal that small intestinal HIEs, but not colonoids, from adults, H9tHIEs, HIEs from a CVID patient, and HIEs from infants support HuNoV replication with segment and strain-specific differences in viral infection. J4FUT2-KI HIEs exhibit the highest susceptibility to HuNoV infection, allowing the cultivation of a broader range of GI and GII HuNoV strains than previously reported. Overall, these results contribute to a deeper understanding of HuNoVs and highlight the transformative potential of HIE cultures in HuNoV research. ImportanceHuNoVs cause global diarrheal illness and chronic infections in immunocompromised patients. This manuscript reports approaches for cultivating HuNoVs in secretor positive human intestinal enteroids (HIEs). HuNoV infectivity was compared in new HIE models, including ones from i) different intestinal segments of single donors, ii) human embryonic stem cell-derived organoids transplanted into mice, iii) genetically-modified lines, and iv) a patient with chronic variable immunodeficiency disease. HIEs from small intestine, but not colon, support HuNoV replication with donor, segment and strain-specific variations. Unexpectedly, HIEs from one donor are resistant to GII.3 infection. The genetically-modified J4FUT2-KI HIEs enable cultivation of a broad range of GI and GII genotypes. New insights into strain-specific differences in HuNoV replication in HIEs support this platform for advancing understanding of HuNoV biology and developing potential therapeutics.

microbiology↗

bioRxiv2023

A Standardized Antiviral Pipeline for Human Norovirus in Human Intestinal Enteroids Demonstrates No Antiviral Activity of Nitazoxanide

Human noroviruses (HuNoVs) are the leading cause of acute gastroenteritis. In immunocompetent hosts, symptoms usually resolve within three days; however, in immunocompromised persons, HuNoV infection can become persistent, debilitating, and sometimes life-threatening. There are no licensed therapeutics for HuNoV due to a near half-century delay in its cultivation. Treatment for chronic HuNoV infection in immunosuppressed patients anecdotally includes nitazoxanide, a broad-spectrum antimicrobial licensed for treatment of parasite-induced gastroenteritis. Despite its off-label use for chronic HuNoV infection, nitazoxanide has not been clearly demonstrated to be an effective treatment. In this study, we established a standardized pipeline for antiviral testing using multiple human small intestinal enteroid (HIE) lines representing different intestinal segments and evaluated whether nitazoxanide inhibits replication of 5 HuNoV strains in vitro. Nitazoxanide did not exhibit high selective antiviral activity against any HuNoV strains tested, indicating it is not an effective antiviral for norovirus infection. HIEs are further demonstrated as a model to serve as a pre-clinical platform to test antivirals against human noroviruses to treat gastrointestinal disease.

microbiology↗

bioRxiv2023

Infant and Adult Human Intestinal Enteroids are Morphologically and Functionally Distinct

Background & AimsHuman intestinal enteroids (HIEs) are gaining recognition as physiologically relevant models of the intestinal epithelium. While HIEs from adults are used extensively in biomedical research, few studies have used HIEs from infants. Considering the dramatic developmental changes that occur during infancy, it is important to establish models that represent infant intestinal characteristics and physiological responses. MethodsWe established jejunal HIEs from infant surgical samples and performed comparisons to jejunal HIEs from adults using RNA sequencing (RNA-Seq) and morphologic analyses. We validated differences in key pathways through functional studies and determined if these cultures recapitulate known features of the infant intestinal epithelium. ResultsRNA-Seq analysis showed significant differences in the transcriptome of infant and adult HIEs, including differences in genes and pathways associated with cell differentiation and proliferation, tissue development, lipid metabolism, innate immunity, and biological adhesion. Validating these results, we observed a higher abundance of cells expressing specific enterocyte, goblet cell and enteroendocrine cell markers in differentiated infant HIE monolayers, and greater numbers of proliferative cells in undifferentiated 3D cultures. Compared to adult HIEs, infant HIEs portray characteristics of an immature gastrointestinal epithelium including significantly shorter cell height, lower epithelial barrier integrity, and lower innate immune responses to infection with an oral poliovirus vaccine. ConclusionsHIEs established from infant intestinal tissues reflect characteristics of the infant gut and are distinct from adult cultures. Our data support the use of infant HIEs as an ex-vivo model to advance studies of infant-specific diseases and drug discovery for this population. ImportanceTissue or biopsy stem cell-derived human intestinal enteroids are increasingly recognized as physiologically relevant models of the human gastrointestinal epithelium. While enteroids from adults and fetal tissues have been extensively used for studying many infectious and non-infectious diseases, there are few reports on enteroids from infants. We show that infant enteroids exhibit both transcriptomic and morphological differences compared to adult cultures. They also differ in functional responses to barrier disruption and innate immune responses to infection, suggesting that infant and adult enteroids are distinct model systems. Considering the dramatic changes in body composition and physiology that begins during infancy, tools that appropriately model intestinal development and diseases are critical. Infant enteroids model key features of the infant gastrointestinal epithelium. This study is significant in establishing infant enteroids as age-appropriate models for infant intestinal physiology, infant-specific diseases and responses to pathogens.

microbiology↗

bioRxiv2023

A Latent Clinical-anatomical Dimension Relating Metabolic Syndrome to Brain Morphology - Evidence from a Multivariate Imaging Analysis of 40,087 Individuals

The link between metabolic syndrome (MetS) and neurodegenerative as well cerebrovascular conditions holds substantial implications for brain health in at-risk populations. This study elucidates the complex relationship between MetS and brain health by conducting a comprehensive examination of cardiometabolic risk factors, cortical morphology, and cognitive function in 40,087 individuals. Multivariate, data-driven statistics identified a latent dimension linking more severe MetS to widespread brain morphological abnormalities, accounting for up to 71% of shared variance in the data. This dimension was replicable across sub-samples. In a mediation analysis we could demonstrate that MetS-related brain morphological abnormalities mediated the link between MetS severity and cognitive performance in multiple domains. Employing imaging transcriptomics and connectomics, our results also suggest that MetS-related morphological abnormalities are linked to the regional cellular composition and macroscopic brain network organization. By leveraging extensive, multi-domain data combined with a dimensional stratification approach, our analysis provides profound insights into the association of MetS and brain health. These findings can inform effective therapeutic and risk mitigation strategies aimed at maintaining brain integrity.

neuroscience↗

bioRxiv2023

Is resting state fMRI better than individual characteristics at predicting cognition?

Changes in spontaneous brain activity at rest provide rich information about behavior and cognition. The mathematical properties of resting-state functional magnetic resonance imaging (rsfMRI) are a depiction of brain function and are frequently used to predict cognitive phenotypes. Individual characteristics such as age, gender, and total intracranial volume (TIV) play an important role in predictive modeling of rsfMRI (for example, as "confounders" in many cases). It is unclear, however, to what extent rsfMRI carries independent information from the individual characteristics that is able to predict cognitive phenotypes. Here, we used predictive modeling to thoroughly examine the predictability of four cognitive phenotypes in 20,000 healthy UK Biobank subjects. We extracted common rsfMRI features of functional brain connectivity (FC) and temporal complexity (TC). We assessed the ability of these features to predict outcomes in the presence and absence of age, gender, and TIV. Additionally, we assessed the predictiveness of age, gender, and TIV only. We find TC and FC features to perform comparably with regard to predicting cognitive phenotypes. As compared to rsfMRI features, individual characteristics provide systematically better predictions with smaller sample sizes and, to some extent, in larger cohorts. It is also consistent across different levels of inherent temporal noise in rsfMRI. Our results suggest that when the objective is to perform cognitive predictions as opposed to understanding the relationship between brain and behavior, individual characteristics are more applicable than rsfMRI features.

neuroscience↗

bioRxiv2023

Alpaca Single B Cell Interrogation and Heavy-Chain-Only Antibody Discovery on an Optofluidic Platform

In vivo discovery approaches for single domain antibodies such as VHH have been limited by the lack of methodologies available for camelid B cell interrogation. Here, we report a novel application of the Berkeley Lights Beacon(R) optofluidic platform to the discovery of heavy-chain-only antibodies by screening single B cells from alpacas immunized with two different targets. Custom methods for alpaca B cell enrichment, culture, on-Beacon IgG2/3 detection, and sequencing were developed and used to discover target-specific VHH candidates from an alpaca immunized with either human prostate specific membrane antigen (PSMA) or a second blinded target, in a proof-of-concept study. PSMA-specific VHH hits discovered on the Beacon were recombinantly expressed as VHH-Fc, purified, and characterized using label-free techniques. All but one VHH-Fc bound PSMA with a single-digit nanomolar affinity, and four candidates were successfully humanized in silico using a rapid bulk humanization approach. In addition, next-generation repertoire sequencing was performed at longitudinal timepoints after immunization, uncovering additional variants within the clonal lineages of the validated hits discovered on the Beacon platform. The establishment of this single B cell VHH discovery workflow extends the powerful Beacon technology to enable rapid discovery of VHH directly from natural camelid immune repertoires.

immunology↗

bioRxiv2022

A genome-scale metabolic model of Drosophila melanogaster for integrative analysis of brain diseases

High conservation of the disease-associated genes between fly and human facilitates the common use of Drosophila melanogaster to study metabolic disorders under controlled laboratory conditions. However, metabolic modeling studies are highly limited for this organism. We here report a comprehensively curated genome-scale metabolic network model of Drosophila using an orthology-based approach. The gene coverage and metabolic information of the orthology-based draft model were expanded via Drosophila-specific KEGG and MetaCyc databases, with several curation steps to avoid metabolic redundancy and stoichiometric inconsistency. Further, we performed literature-based curations to improve gene-reaction associations, subcellular metabolite locations, and updated various metabolic pathways including cholesterol metabolism. The performance of the resulting Drosophila model, termed iDrosophila1 (8,230 reactions, 6,990 metabolites, and 2,388 genes), was assessed using flux balance analysis in comparison with the other currently available fly models leading to superior or comparable results. We also evaluated transcriptome-based prediction capacity of the iDrosophila1, where differential metabolic pathways during Parkinsons disease could be successfully elucidated. Overall, iDrosophila1 is promising to investigate systems-level metabolic alterations in response to genetic and environmental perturbations.

systems biology↗

bioRxiv2021

Drivers of Transcriptional Variance in Human Intestinal Epithelial Organoids

Background & AimsHuman intestinal epithelial organoids (enteroids and colonoids) are tissue cultures used for understanding the physiology of the intestinal epithelium. Here, we explored the effect on the transcriptome of common variations in culture methods, including extracellular matrix substrate, format, tissue segment, differentiation status, and patient heterogeneity. MethodsRNA-sequencing datasets from 251 experiments performed on 35 human enteroid and colonoid lines from 28 patients were aggregated from several groups in the Texas Medical Center. DESeq2 and Gene Set Enrichment Analysis (GSEA) was used to identify differentially expressed genes and enriched of pathways. ResultsPERMANOVA, Pearson correlations, and dendrogram analysis of all data indicated three tiers of influence of culture methods on transcriptomic variation: substrate (collagen vs. Matrigel) and format (3D, transwell, and monolayer) had the largest effect (7,271-1,305 differentially expressed genes-DEGs); segment of origin (duodenum, jejunum, ileum, colon) and differentiation status had a moderate effect (5,977-420 DEGs), and patient heterogeneity and specific experimental manipulations (e.g., pathogen infection) had the smallest effect. GSEA identified hundreds of pathways that varied between culture methods, such as IL1 cytokine signaling enriched in transwell vs. monolayer cultures, and cholesterol biosynthesis genes enriched in Matrigel vs. collagen cultures. ConclusionsSurprisingly large differences in organoid transcriptome were driven by variations in culture methods such as format and substrate, whereas experimental manipulations such as infection had modest effects. These results show that common variations in culture conditions can have large effects on intestinal organoids and should be accounted for when designing experiments and comparing results between laboratories. Our data constitute the largest RNA-seq dataset interrogating human intestinal organoids.

molecular biology↗

bioRxiv2021

ILORA: A database of alien vascular flora of India

1) Biological invasions pose an unprecedented threat to biodiversity and ecosystems at different spatial scales, especially for a biodiversity-rich developing nation like India. While country-level checklists of alien taxa are important, databases having their biological and ecological attributes are of paramount importance for facilitating research activities and developing policy interventions. Such a comprehensive database for alien flora is lacking in India. 2) We have curated data for 14 variables related to ecology, biogeography, introduction pathway, socio-economy and distribution of 1747 alien vascular plant species from 22 national and global sources to produce the Indian Alien Flora Information (ILORA) version 1.0 database. This paper describes the detailed methodology of curating these data along with the rationale behind selecting these variables. 3) The database, the first of its kind for the Indian alien flora, will provide easy access to high quality data and offer a ready reference to comprehend the existing scenario of alien plant species in the country. The database is dynamic and will be updated regularly. It has a provision to incorporate user submitted data, which will allow increasing the resolution of the database as well as the expansion of its capacity. 4) The database is envisaged to become a nationwide collaborative platform for a wide spectrum of stakeholders. It is freely accessible via an online data repository as well as through a dedicated website (https://ilora2020.wixsite.com/ilora2020).

ecology↗

bioRxiv2019

Sex classification by resting state brain connectivity

1A large amount of brain imaging research has focused on group studies delineating differences between males and females with respect to both cognitive performance as well as structural and functional brain organization. To supplement existing findings, the present study employed a machine learning approach to assess how accurately participants sex can be classified based on spatially specific resting state (RS) brain-connectivity, using two samples from the Human Connectome Project (n1 = 434, n2 = 310) and one fully independent sample from the 1000BRAINS study (n=941). The classifier, which was trained on one sample and tested on the other two, was able to reliably classify sex, both within sample and across independent samples, differing both with respect to imaging parameters and sample characteristics. Brain regions displaying highest sex classification accuracies were mainly located along the cingulate cortex, medial and lateral frontal cortex, temporo-parietal regions, insula and precuneus. These areas were stable across samples and match well with previously described sex differences in functional brain organization. While our data show a clear link between sex and regionally specific brain connectivity, they do not support a clear-cut dimorphism in functional brain organization that is driven by sex alone.

neuroscience↗