Estimating the Permanent Loss of Groundwater Storage in the Southern San Joaquin Valley, California

In the San Joaquin Valley, California, recent droughts starting in 2007 have increased the pumping of groundwater, leading to widespread subsidence. In the southern portion of the San Joaquin Valley, vertical subsidence as high as 85 cm has been observed between June 2007 and December 2010 using Interferometric Synthetic Aperture Radar (InSAR). This study seeks to map regions where inelastic (not recoverable) deformation occurred during the study period, resulting in permanent compaction and loss of groundwater storage. We estimated the amount of permanent compaction by incorporating multiple data sets: the total deformation derived from InSAR, estimated skeletal-specific storage and hydraulic parameters, geologic information, and measured water levels during our study period. We used two approaches, one that we consider to provide an estimate of the lowest possible amount of inelastic deformation, and one that provides a more reasonable estimate. These two approaches resulted in a spatial distribution of values for the percentage of the total deformation that was inelastic, with the former estimating a spatially averaged value of 54%, and the latter a spatially averaged value of 98%. The former corresponds to the permanent loss of 4.14*108 m3 of groundwater storage, or roughly 5% of the volume of groundwater used over the study time period; the latter corresponds to the loss of 7.48*108 m3 of groundwater storage, or roughly 9% of the volume of groundwater used. This study demonstrates that a data-driven approach can be used effectively to estimate the permanent loss of groundwater storage

MicroRNA Biomarkers for Infectious Diseases: From Basic Research to Biosensing

In the pursuit of improved diagnostic tests for infectious diseases, several classes of molecules have been scrutinized as prospective biomarkers. Small (18–22 nucleotide), non-coding RNA transcripts called microRNAs (miRNAs) have emerged as promising candidates with extensive diagnostic potential, due to their role in numerous diseases, previously established methods for quantitation and their stability within biofluids. Despite efforts to identify, characterize and apply miRNA signatures as diagnostic markers in a range of non-infectious diseases, their application in infectious disease has advanced relatively slowly. Here, we outline the benefits that miRNA biomarkers offer to the diagnosis, management, and treatment of infectious diseases. Investigation of these novel biomarkers could advance the use of personalized medicine in infectious disease treatment, which raises important considerations for validating their use as diagnostic or prognostic markers. Finally, we discuss new and emerging miRNA detection platforms, with a focus on rapid, point-of-care testing, to evaluate the benefits and obstacles of miRNA biomarkers for infectious disease

A comparative analysis of high-throughput platforms for validation of a circulating microRNA signature in diabetic retinopathy

MicroRNAs are now increasingly recognized as biomarkers of disease progression. Several quantitative real-time PCR (qPCR) platforms have been developed to determine the relative levels of microRNAs in biological fluids. We systematically compared the detection of cellular and circulating microRNA using a standard 96-well platform, a high-content microfluidics platform and two ultrahigh content platforms. We used extensive analytical tools to compute inter- and intra-run variability and concordance measured using fidelity scoring, coefficient of variation and cluster analysis. We carried out unprejudiced next generation sequencing to identify a microRNA signature for Diabetic Retinopathy (DR) and systematically assessed the validation of this signature on clinical samples using each of the above four qPCR platforms. The results indicate that sensitivity to measure low copy number microRNAs is inversely related to qPCR reaction volume and that the choice of platform for microRNA biomarker validation should be made based on the abundance of miRNAs of interest

A self-consistent method to estimate the rate of compact binary coalescences with a Poisson mixture model

The recently published GWTC-1 - a journal article summarizing the search for gravitational waves (GWs) from coalescing compact binaries in data produced by the LIGO-Virgo network of ground-based detectors during their first and second observing runs - quoted estimates for the rates of binary neutron star, neutron star black hole binary, and binary black hole mergers, as well as assigned probabilities of astrophysical origin for various significant and marginal GW candidate events. In this paper, we delineate the formalism used to compute these rates and probabilities, which assumes that triggers above a low ranking statistic threshold, whether of terrestrial or astrophysical origin, occur as independent Poisson processes. In particular, we include an arbitrary number of astrophysical categories by redistributing, via mass-based template weighting, the foreground probabilities of candidate events, across source classes. We evaluate this formalism on synthetic GW data, and demonstrate that this method works well for the kind of GW signals observed during the first and second observing runs.Comment: 19 pages, 5 figure

A self-consistent method to estimate the rate of compact binary coalescences with a Poisson mixture model

The recently published GWTC-1 (Abbott B P et al (LIGO Scientific Collaboration and Virgo Collaboration) 2019 Phys. Rev. X 9 031040)—a journal article summarizing the search for gravitational waves (GWs) from coalescing compact binaries in data produced by the LIGO-Virgo network of ground-based detectors during their first and second observing runs—quoted estimates for the rates of binary neutron star, neutron star black hole binary, and binary black hole mergers, as well as assigned probabilities of astrophysical origin for various significant and marginal GW candidate events. In this paper, we delineate the formalism used to compute these rates and probabilities, which assumes that triggers above a low ranking statistic threshold, whether of terrestrial or astrophysical origin, occur as independent Poisson processes. In particular, we include an arbitrary number of astrophysical categories by redistributing, via mass-based template weighting, the foreground probabilities of candidate events, across source classes. We evaluate this formalism on synthetic GW data, and demonstrate that this method works well for the kind of GW signals observed during the first and second observing runs

A self-consistent method to estimate the rate of compact binary coalescences with a Poisson mixture model

The recently published GWTC-1 - a journal article summarizing the search for gravitational waves (GWs) from coalescing compact binaries in data produced by the LIGO-Virgo network of ground-based detectors during their first and second observing runs - quoted estimates for the rates of binary neutron star, neutron star black hole binary, and binary black hole mergers, as well as assigned probabilities of astrophysical origin for various significant and marginal GW candidate events. In this paper, we delineate the formalism used to compute these rates and probabilities, which assumes that triggers above a low ranking statistic threshold, whether of terrestrial or astrophysical origin, occur as independent Poisson processes. In particular, we include an arbitrary number of astrophysical categories by redistributing, via mass-based template weighting, the foreground probabilities of candidate events, across source classes. We evaluate this formalism on synthetic GW data, and demonstrate that this method works well for the kind of GW signals observed during the first and second observing runs.Comment: 19 pages, 5 figure

Insulin micro-secretion in Type 1 diabetes and related microRNA profiles

The aim of this cross-sectional study was to compare plasma C-peptide presence and levels in people without diabetes (CON) and with Type 1 diabetes and relate C-peptide status to clinical factors. In a subset we evaluated 50 microRNAs (miRs) previously implicated in beta-cell death and associations with clinical status and C-peptide levels. Diabetes age of onset was stratified as adult (≥ 18 y.o) or childhood ( 20 years. Plasma C-peptide was measured by ultrasensitive ELISA. Plasma miRs were quantified using TaqMan probe-primer mix on an OpenArray platform. C-peptide was detectable in 55.3% of (n= 349) people with diabetes, including 64.1% of adults and 34.0% of youth with diabetes, p 20 years) had detectable C-peptide (60%) than in those with shorter diabetes duration (39%, p for trend< 0.05). Nine miRs significantly correlated with detectable C-peptide levels in people with diabetes and 16 miRs correlated with C-peptide levels in CON. Our cross-sectional study results are supportive of (a) greater beta-cell function loss in younger onset Type 1 diabetes; (b) persistent insulin secretion in adult-onset diabetes and possibly regenerative secretion in childhood-onset long diabetes duration; and (c) relationships of C-peptide levels with circulating miRs. Confirmatory clinical studies and related basic science studies are merited

A pilot of the feasibility and usefulness of an aged obese model for use in stroke research

Background: Animal models of stroke have been criticised as having poor predictive validity, lacking risk factors prevalent in an aging population. This pilot study examined the development of comorbidities in a combined aged and high-fat diet model, and then examined the feasibility of modelling stroke in such rats. Methods: Twelve-month old male Wistar-Han rats (n=15) were fed a 60% fat diet for 8 months during which monthly serial blood samples were taken to assess the development of metabolic syndrome and pro-inflammatory markers. Following this, to pilot the suitability of these rats for undergoing surgical models of stroke, they underwent 30min of middle cerebral artery occlusion (MCAO) alongside younger controls fed a standard diet (n=10). Survival, weight and functional outcome were monitored, and blood vessels and tissues collected for analysis. Results: A high fat diet in aged rats led to substantial obesity. These rats did not develop type 2 diabetes or hypertension. There was thickening of the thoracic arterial wall and vacuole formation in the liver; but of the cytokines examined changes were not seen. MCAO surgery and behavioural assessment was possible in this model (with some caveats discussed in manuscript). Conclusions: This study shows MCAO is possible in aged, obese rats. However, this model is not ideal for recapitulating the complex comorbidities commonly seen in stroke patients