Biology subjects

Dudley, J.

Publications and source records attributed to Dudley, J..

7 recordsLinked to original sources

bioRxiv2024

Gaze audits food items for bite points during human withdraw-to-eat movements

Food handling and eating are central to the skill of primate hand movements, and their analysis can provide insights into the evolutionary origins of hand use and its generalization to other behaviors, such as tool use. Vision contributes differently to the reach, grasp, and withdraw-to-eat components of hand use when eating, suggesting that these component movements are controlled by different visuomotor networks with distinct evolutionary histories. This study examines the role of gaze in mediating the withdraw-to-eat movement in human participants eating various food items, including candy, donuts, carrots, bananas, and apples, or pantomiming the eating movements for some of these items. Eye-tracking and frame-by-frame video analyses are used to describe gaze, gaze duration, gaze disengagement, eye blinking, and hand preference in eating each food item. The results show that gaze first identifies points on a food item that the dominant hand can grasp and then identifies points on the food item that the mouth can bite. The hand and finger shaping movements of both the initial grasp and subsequent food handling aid in exposing targets on the food for grasping and biting. The comparison of real and pantomime eating suggests that only real food items possess the affordances that elicit gaze patterns associated with identifying online targets for grasps and bites. The findings are discussed in relation to idea that gaze has a feature-detector-like role linking food cues to the skilled movements of hand shaping to grasp a food item and then to orient a food item to the mouth for biting.

animal behavior and cognition↗

bioRxiv2021

A wipe-based stool collection and preservation kit for microbiome community profiling

While a range of methods for stool collection exist, many require complicated, self-directed protocols and stool transfer. In this study, we introduce and validate a novel, wipe-based approach to fecal sample collection and stabilization for metagenomics analysis. A total of 72 samples were collected across four different preservation types: freezing at -20{degrees}C, room temperature storage, a commercial DNA preservation kit, and DESS (dimethyl sulfoxide, ethylenediaminetetraacetic acid, sodium chloride) solution. These samples were sequenced and analyzed for taxonomic abundance metrics, metabolic pathway classification, and diversity analysis. Overall, the DESS wipe results validated the use of a wipe-based capture method to collect stool samples for microbiome analysis, showing an R2 of 0.96 for species across all kingdoms, as well as exhibiting a maintenance of Shannon diversity (3.1-3.3) and species richness (151-159) compared to frozen samples. Moreover, DESS showed comparable performance to the commercially available preservation kit (R2 of 0.98), and samples consistently clustered by subject across each method. Future studies will be needed to further explore sample processing options and their applications in non-healthy subjects, particularly patients with irritable bowel syndrome, inflammatory bowel disease, and colorectal cancer, but these data suggest the DESS wipe method can be used for stable, room temperature collection and transport of human stool specimens.

microbiology↗

bioRxiv2021

Pleiotropic Variability Score: A Genome Interpretation Metric to Quantify Phenomic Associations of Genomic Variants

A more complete understanding of phenomic space is critical for elucidating genome-phenome relationships and for assessing disease risk from genome sequencing. To incorporate knowledge of how related a variants associations are, we developed a new genome interpretation metric called Pleiotropic Variability Score (PVS). PVS uses semantic reasoning to score the relatedness of a genetic variants associated phenotypes based on those phenotypes relationships in the human phenotype ontology (HPO) and disease ontology (DO). We tested 78 unique semantic similarity methods and integrated six robust metrics to define the pleiotropy score of SNPs. We computed PVS for 12,541 SNPs which were mapped to 382 HPO and 317 DO unique phenotype terms in a genotype-phenotype catalog (10,021 SNPs mapped to DO phenotypes and 8,569 SNPs mapped to HPO phenotypes). We validated the utility of PVS by computing pleiotropy using an electronic health record linked genomic database (BioME, n=11,210). Further we demonstrate the application of PVS in personalized medicine using "personalized pleiotropy score" reports for individuals with genomic data that could potentially aid in variant interpretation. We further developed a software framework to incorporate PVS into VCF files and to consolidate pleiotropy assessment as part of genome interpretation pipelines. As the genome-phenome catalogs are growing, PVS will be a useful metric to assess genetic variation to find SNPs with highly pleiotropic effects. Additionally, variants with varying degree of pleiotropy can be prioritized for explorative studies to understand specific roles of SNPs and pleiotropic hubs in mediating novel phenotypes and drug development.

bioinformatics↗

bioRxiv2019

Identification and genetic validation of drug-comorbidity interactions in type 2 diabetes using data-driven disease trajectory analysis

Given various risk profiles, manifestations, comorbidities, and outcomes for individuals with Type 2 diabetes mellitus (T2D), a one-size-fits-all approach towards treatment and management is inadequate, and there is a clear need for personalized medications to reduce rates of complications and comorbidities. Here, we leveraged comprehensive Electronic Medical Records (EMR) to identify associations between T2D comorbidities and medications and evaluated their biological determinants using EMR-linked genetic information. We discovered clinically novel associations supported by the previous laboratory studies; e.g. 5-hydroxytryptamine 3 receptor antagonists, ondansetron and granisetron, are protective against cognitive disorders, and clopidogrel is protective against retinopathy. Furthermore, potentially novel associations were validated by genetic analysis; e.g. association between gabapentin and cognitive disorders was supported via variants of its target genes, GRIN1 and CACNA2D2. These results of the current study open the door for optimizing treatment combinations to mitigate risks and for individualizing therapy based on T2D subtype risk profiles.

bioinformatics↗

bioRxiv2018

Predictive modeling of susceptibility to substance abuse, mortality and drug-drug interactions in opioid patients

Opioid addiction causes high degree of morbidity and mortality. Preemptive identification of patients at risk of opioid dependence and developing intelligent clinical decisions to deprescribe opioids to the vulnerable patient population may help in reducing the burden. Identifying patients susceptible to mortality due to opioid-induced side effects and understanding the landscape of drug-drug interaction pairs aggravating opioid usage are significant, yet, unexplored research questions. In this study, we present a collection of predictive models to identify patients at risk of opioid abuse, mortality and drug-drug interactions in the context of opioid usage. Using publicly available dataset from MIMIC-III, we developed predictive models (opioid abuse models a=Logistic Regression; b=Extreme Gradient Boosting and mortality model= Extreme Gradient Boosting) and identified potential drug-drug interaction patterns. To enable the translational value of our work, the predictive model and all associated software code is provided. This repository could be used to build clinical decision aids and thus improve the optimization of prescription rates for vulnerable population.

epidemiology↗

bioRxiv2018

Designing robust N-of-1 studies for precision medicine

Recent advances in molecular biology, sensors, and digital medicine have led to an explosion of products and services for high-resolution monitoring of individual health. The N-of-1 study has emerged as an important methodological tool for harnessing these new data sources, enabling researchers to compare the effectiveness of health interventions at the level of a single individual. We have developed a stochastic time series model that simulates an N-of-1 study, facilitating rapid optimization of N-of-1 study designs and increasing the likelihood of study success while minimizing participant burden. Using simulation, we demonstrate how the number of treatment blocks, ordering of treatments within blocks, duration of each treatment, and sampling frequency affect our ability to detect true differences in treatment efficacy. We provide a set of recommendations for study designs based on treatment, outcome, and instrument parameters, and provide our simulation software as a supplement to the paper.

bioinformatics↗

bioRxiv2018

Rapid Therapeutic Recommendations in the Context of a Global Public Health Crisis using Translational Bioinformatics Approaches: A proof-of-concept study using Nipah Virus Infection

We live in a world of emerging new diseases and old diseases resurging in more aggressive forms. Drug development by pharmaceutical companies is a market-driven and costly endeavor, and thus it is often a challenge when drugs are needed for diseases endemic only to certain regions or which affect only a few patients. However, biomedical open data is accessible and reusable for reanalysis and generation of a new hypotheses and discovery. In this study, we leverage biomedical data and tools to analyze available data on Nipah Virus (NiV) infection. NiV infection is an emerging zoonosis that is transmissible to humans and is associated with high mortality rates. In this study, explored the application of computational drug repositioning and chemogenomic enrichment analyses using host transcriptome data to match drugs that could reverse the virus-induced gene signature. We performed analyses using two gene signatures: i) A previously published gene signature (n=34), and ii) a gene signature generated using the characteristic direction method (n= 5,533). Our predictive framework suggests that several drugs including FDA approved therapies like beclometasone, trihexyphenidyl, S-propranolol etc. could modulate the NiV infection induced gene signatures in endothelial cells. A target specific analysis of CXCL10 also suggests the potential application of Eldelumab, an investigative therapy for Crohns disease and ulcerative colitis, as a putative candidate for drug repositioning. To conclude, we also discuss challenges and opportunities in clinical trials (n-of-1 and adaptive trials) for repositioned drugs. Further follow-up studies including biochemical assays and clinical trials are required to identify effective therapies for clinical use. Our proof-of-concept study highlights that translational bioinformatics methods including gene expression analyses and computational drug repositioning could augment epidemiological investigations in the context of an emerging disease with no effective treatment.

microbiology↗