Biology subjects

Nicholson, J.

Publications and source records attributed to Nicholson, J..

3 recordsLinked to original sources

bioRxiv2018

G-Protein signaling increases germline stem cell activity in Drosophila males in response to multiple rounds of mating

Adult stem cells divide to renew the stem cell pool and replenish specialized cells that are lost due to death or usage. However, little is known about the mechanisms regulating how stem cells adjust to a demand for specialized cells. A failure of the stem cells to respond to this demand can have serious consequences, such as tissue loss, or prolonged recovery post injury. Here, we challenge the male germline stem cells (GSCs) of Drosophila melanogaster for the production of specialized cells using mating experiments. We show that repeated mating reduced the sperm pool and accelerated germline stem cell (GSC) divisions. The increase in GSC divisions depended on the activity of the highly conserved G-proteins. Germline expression of RNA-Interference (RNA-i) constructs against G-proteins or a dominant negative G-protein eliminated the increase in GSC divisions in mated males. Consistent with a role for the G-proteins in the regulation of GSC divisions, RNA-i against seven out of 35 G-protein coupled receptors (GPCRs) within the germline cells also eliminated the capability of males to accelerate their GSC divisions in response to mating. Our data show that GSCs are receptive to GPCR stimulus, potentially through a network of interactions among multiple signaling pathways.

developmental biology↗

bioRxiv2017

Differential Impacts of Dietary Modification on Individual Metabolic Phenotypes and their Relationship to Blood Pressure: Evidence of Latent Dietary Responder Sub-phenotypes

BackgroundHypertension is a worldwide public health issue with significant comorbidity and mortality. We aimed to identify urinary metabolic phenotypes associated with three healthy diets and to establish their relationship to blood pressure (BP).\n\nMethods and Results--24-h urine samples from 158 participants, with pre-hypertension and hypertension, consumed a carbohydrate-rich, a protein-rich and a monounsaturated fat-rich healthy diet (6-week per diet) in randomized order, were analyzed by nuclear magnetic resonance spectroscopy. Combinations of metabolites significantly associated with each diet were identified, and associations between these metabolites and cardiovascular disease risk were established. We found coherent responses to all three diets including increased excretion of metabolites originating from vegetables/fruits, protein, tryptophan metabolism and gut microbial-mammalian co-metabolism. Proline betaine (marker of citrus fruit) was significantly inversely associated with systolic BP; 4-cresyl sulfate (gut microbial metabolite) inversely correlated with both systolic and diastolic BP; and hippurate (gut microbial metabolite) - directly associated with reduced systolic BP.\n\nConclusionsVariation in metabolic phenotypes in response to specific diets may hold clues as to the mechanisms underlying inter-individual differences in dietary response. Stratification of individuals based on diet-specific urinary phenotypes highlights the feasibility for individualized approaches to dietary therapy for lowering BP.\n\nClinical Trial RegistrationThis intervention study is registered at http://www.clinicaltrials.gov as NCT00051350

molecular biology↗

bioRxiv2017

Science with no fiction: measuring the veracity of scientific reports by citation analysis

The current crisis of veracity in biomedical research is enabled by the lack of publicly accessible information on whether the reported scientific claims are valid. One approach to solve this problem is to replicate previous studies by specialized reproducibility centers. However, this approach is costly or unaffordable and raises a number of yet to be resolved concerns that question its effectiveness and validity. We propose to use an approach that yields a simple numerical measure of veracity, the R-factor, by summarizing the outcomes of already published studies that have attempted to test a claim. The R-factor of an investigator, a journal, or an institution would be the average of the R-factors of the claims they reported. We illustrate this approach using three studies recently tested by a replication initiative, compare the results, and discuss how using the R-factor can help improve the veracity of scientific research.

scientific communication and education↗