Genetic and Haplotype Diversity of Manila Clam Ruditapes philippinarum in Different Regions of China Based on Three Molecular Markers.

China has the largest production yield of Manila clam Ruditapes philippinarum in the world. Most of the clam seeds for aquaculture are mainly derived from artificial breeding in southern China, likely resulting in the loss of genetic variation and inbreeding depression. To understand the genetic and haplotype diversity of R. philippinarum, 14 clam populations sampled from different regions of China were analyzed by three molecular markers, including COI, 16SrRNA and ITS. Based on the results of the COI and ITS genes, the 14 populations showed a moderate to high level of genetic diversity, with an average haplotype diversity of 0.9242 and nucleotide diversity of 0.05248. AMOVA showed that there was significant genetic differentiation among all populations (mean FST of the total population was 0.4534). Pairwise FST analysis showed that genetic differentiation reached significant levels between Laizhou and other populations. Two Laizhou populations showed great divergence from other populations, forming an independent branch in the phylogenetic tree. The shared haplotypes Hap_2 and Hap_4 of COI appeared most frequently in most clam populations. In contrast, 16SrRNA analysis of the clam populations revealed the dominated haplotype Hap_2, accounting for 70% of the total number of individuals. The haplotype diversity of the Laizhou population (Laizhou shell-wide (KK) and Laizhou dock (LZMT)) was relatively higher than other populations, showing multiple unique haplotypes (e.g., Hap_40, Hap_41 and Hap_42). These findings of genetic and haplotype diversity of clam populations provide guiding information for genetic resource conservation and genetic improvement of the commercially important R. philippinarum.

Dysregulation of miR-146a: a causative factor in epilepsy pathogenesis, diagnosis, and prognosis.

miR-146a is an NF-κB-dependent miRNA that acts as an anti-inflammatory miRNA via the Toll-like receptor (TLR) pathway. miR-146a targets multiple genes and has been identified to directly or indirectly regulate processes other than inflammation, including intracellular Ca changes, apoptosis, oxidative stress, and neurodegeneration. miR-146a is an important regulator of gene expression in epilepsy development and progression. Furthermore, miR-146a-related single nucleotide polymorphisms (SNPs) and single nucleotide variants (SNVs) contribute to the genetic susceptibility to drug resistance and seizure severity in epilepsy patients. This study summarizes the abnormal expression patterns of miR-146a in different types and stages of epilepsy and its potential molecular regulation mechanism, indicating that miR-146a can be used as a novel biomarker for epilepsy diagnosis, prognosis, and treatment.

Applying principal component pursuit to investigate the association between source-specific fine particulate matter and myocardial infarction hospitalizations in New York City.

The association between fine particulate matter (PM2.5) and cardiovascular outcomes is well established. To evaluate whether source-specific PM2.5 is differentially associated with cardiovascular disease in New York City (NYC), we identified PM2.5 sources and examined the association between source-specific PM2.5 exposure and risk of hospitalization for myocardial infarction (MI). Methods: We adapted principal component pursuit (PCP), a dimensionality-reduction technique previously used in computer vision, as a novel pattern recognition method for environmental mixtures to apportion speciated PM2.5 to its sources. We used data from the NY Department of Health Statewide Planning and Research Cooperative System of daily city-wide counts of MI admissions (2007-2015). We examined associations between same-day, lag 1, and lag 2 source-specific PM2.5 exposure and MI admissions in a time-series analysis, using a quasi-Poisson regression model adjusting for potential confounders. Results: We identified four sources of PM2.5 pollution: crustal, salt, traffic, and regional and detected three single-species factors: cadmium, chromium, and barium. In adjusted models, we observed a 0.40% (95% confidence interval [CI]: -0.21, 1.01%) increase in MI admission rates per 1 µg/m3 increase in traffic PM2.5, a 0.44% (95% CI: -0.04, 0.93%) increase per 1 µg/m3 increase in crustal PM2.5, and a 1.34% (95% CI: -0.46, 3.17%) increase per 1 µg/m3 increase in chromium-related PM2.5, on average. Conclusions: In our NYC study, we identified traffic, crustal dust, and chromium PM2.5 as potentially relevant sources for cardiovascular disease. We also demonstrated the potential utility of PCP as a pattern recognition method for environmental mixtures.

Principal Component Pursuit for Pattern Identification in Environmental Mixtures.

BACKGROUND: Environmental health researchers often aim to identify sources or behaviors that give rise to potentially harmful environmental exposures. OBJECTIVE: We adapted principal component pursuit (PCP)-a robust and well-established technique for dimensionality reduction in computer vision and signal processing-to identify patterns in environmental mixtures. PCP decomposes the exposure mixture into a low-rank matrix containing consistent patterns of exposure across pollutants and a sparse matrix isolating unique or extreme exposure events. METHODS: We adapted PCP to accommodate nonnegative data, missing data, and values below a given limit of detection (LOD). We simulated data to represent environmental mixtures of two sizes with increasing proportions

Compressed Sensing Image Reconstruction of Scanning Electrochemical Microscopy Measurements Carried Out at Ultrahigh Scan Speeds Using Continuous Line Probes.

Previous studies on scanning electrochemical microscopy (SECM) imaging with nonlocal continuous line probes (CLPs) have demonstrated the ability to increase areal imaging rates by an order of magnitude compared to SECM based on conventional ultramicroelectrode (UME) disk electrodes. Increasing the linear scan speed of the CLP during imaging presents an opportunity to increase imaging rates even further but results in a significant deterioration in image quality due to transport processes in the liquid electrolyte. Here, we show that compressed sensing (CS) postprocessing can be successfully applied to CLP-based SECM measurements to reconstruct images with minimal distortion at probe scan rates greatly exceeding the conventional SECM ″speed limit″. By systematically evaluating the image quality of images generated by adaptable postprocessing CS methods for CLP-SECM data collected at varying scan rates, this work establishes a new upper bound for CLP scan rates. While conventional SECM imaging typically uses probe scan speeds characterized by Péclet numbers (Pe) < 1, this study shows that CS postprocessing methods can allow for an accurate image reconstruction for Pe approaching 5, corresponding to an order of magnitude increase in the maximum probe scan speed. This upper limit corresponds to the onset of chaotic convective flows within the electrolyte for the probes investigated in this work, highlighting the importance of considering hydrodynamics in the design of fast-scanning probes.