Biology subjects

Moore, F.

Publications and source records attributed to Moore, F..

3 recordsLinked to original sources

bioRxiv2018

Cystinosin regulates kidney inflammation through its interaction with galectin-3

Inflammation is implicated in the pathogenesis of many disorders. Here, we show that cystinosin, protein defective in the lysosomal storage disorder cystinosis, is a critical regulator of galectin-3 during inflammation. Cystinosis is a lysosomal storage disorder and despite ubiquitous expression of cystinosin, kidney is the primary organ to be impacted by the disease. Here, we show that cystinosin interacts with galectin-3 and enhances its lysosomal localization and degradation. Galectin-3 is also found overexpressed in the kidney of the mouse model of cystinosis, Ctns-/-mice. Absence of galectin-3 in Ctns-/- mice led to a better renal function and structure, and decreased macrophage/monocyte infiltration in the kidney. Finally, galectin-3 interacts with a protein implicated in the recruitment of monocytes and macrophages during inflammation, Monocyte Chemoattractant Protein-1 (MCP1), that was found increased in the serum of Ctns-/- mice. These findings highlight a new role of cystinosin and galectin-3 interaction in inflammation, providing a mechanistic explanation for kidney disease pathogenesis in cystinosis, which may lead to the identification of new drug targets to delay its progression.

molecular biology↗

bioRxiv2017

Automated collection of pathogen-specific diagnostic data for real-time syndromic epidemiological studies

Health-care and public health professionals rely on accurate, real-time monitoring of infectious diseases for outbreak preparedness and response. Early detection of outbreaks is improved by systems that are pathogen-specific. We describe a system, FilmArray(R) Trend, for rapid disease reporting that is syndrome-based but pathogen-specific. Results from a multiplex molecular diagnostic test are sent directly to a cloud database. www.syndromictrends.com presents these data in near real-time. Trend preserves patient privacy by removing or obfuscating patient identifiers. We summarize the respiratory pathogen results, for 20 organisms from 344,000 patient samples acquired as standard of care testing over the last four years from 20 clinical laboratories in the United States. The majority of pathogens show influenza-like seasonality, rhinovirus has fall and spring peaks and adenovirus and bacterial pathogens show constant detection over the year. Interestingly, the rate of pathogen co-detections, on average 7.7%, matches predictions based on the relative abundance of organisms present.

epidemiology↗

bioRxiv2016

Identifying Migrant Origins Using Genetics, Isotopes, and Habitat Suitability

O_LIIdentifying migratory connections across the annual cycle is important for studies of migrant ecology, evolution, and conservation. While recent studies have demonstrated the utility of high-resolution SNP-based genetic markers for identifying population-specific migratory patterns, the accuracy of this approach relative to other intrinsic tagging techniques has not yet been assessed.\nC_LIO_LIHere, using a straightforward application of Bayes' Rule, we develop a method for combining inferences from high-resolution genetic markers, stable isotopes, and habitat suitability models, to spatially infer the breeding origin of migrants captured anywhere along their migratory pathway. Using leave-one-out cross validation, we compare the accuracy of this combined approach with the accuracy attained using each source of data independently.\nC_LIO_LIOur results indicate that when each method is considered in isolation, the accuracy of genetic assignments far exceeded that of assignments based on stable isotopes or habitat suitability models. However, our joint assignment method consistently resulted in small, but informative increases in accuracy and did help to correct misassignments based on genetic data alone. We demonstrate the utility of the combined method by identifying previously undetectable patterns in the timing of migration in a North American migratory songbird, the Wilson's warbler.\nC_LIO_LIOverall, our results support the idea that while genetic data provides the most accurate method for tracking animals using intrinsic markers when each method is considered independently, there is value in combining all three methods. The resulting methods are provided as part of a new computationally-efficient R-package, GIAIH, allowing broad application of our statistical framework to other migratory animal systems.\nC_LI

ecology↗