Genomic Variation, Population History, and Long-Term Genetic Adaptation to High Altitudes in Tibetan Partridge (Perdix hodgsoniae).

Species residing across elevational gradients display adaptations in response to environmental changes such as oxygen availability, ultraviolet radiation, and temperature. Here, we study genomic variation, gene expression, and long-term adaptation in Tibetan Partridge (Perdix hodgsoniae) populations residing across the elevational gradient of the Tibetan Plateau. We generated a high-quality draft genome and used it to carry out downstream population genomic and transcriptomic analysis. The P. hodgsoniae populations residing across various elevations were genetically distinct, and their phylogenetic clustering was consistent with their geographic distribution. We identified possible evidence of gene flow between populations residing in <3,000 and >4,200 m elevation that is consistent with known habitat expansion of high-altitude populations of P. hodgsoniae to a lower elevation. We identified a 60 kb haplotype encompassing the Estrogen Receptor 1 (ESR1) gene, showing strong genetic divergence between populations of P. hodgsoniae. We identified six single nucleotide polymorphisms within the ESR1 gene fixed for derived alleles in high-altitude populations that are strongly conserved across vertebrates. We also compared blood transcriptome profiles and identified differentially expressed genes (such as GAPDH, LDHA, and ALDOC) that correlated with differences in altitude among populations of P. hodgsoniae. These candidate genes from population genomics and transcriptomics analysis were enriched for neutrophil degranulation and glycolysis pathways, which are known to respond to hypoxia and hence may contribute to long-term adaptation to high altitudes in P. hodgsoniae. Our results highlight Tibetan Partridges as a useful model to study molecular mechanisms underlying long-term adaptation to high altitudes.

Sensitive Electrochemical Detection of Ammonia Nitrogen via a Platinum-Zinc Alloy Nanoflower-Modified Carbon Cloth Electrode.

As a common water pollutant, ammonia nitrogen poses a serious risk to human health and the ecological environment. Therefore, it is important to develop a simple and efficient sensing scheme to achieve accurate detection of ammonia nitrogen. Here, we report a simple fabrication electrode for the electrochemical synthesis of platinum-zinc alloy nanoflowers (PtZn NFs) on the surface of carbon cloth. The obtained PtZn NFs/CC electrode was applied to the electrochemical detection of ammonia nitrogen by differential pulse voltammetry (DPV). The enhanced electrocatalytic activity of PtZn NFs and the larger electrochemical active area of the self-supported PtZn NFs/CC electrode are conducive to improving the ammonia nitrogen detection performance of the sensitive electrode. Under optimized conditions, the PtZn NFs/CC electrode exhibits excellent electrochemical performance with a wide linear range from 1 to 1000 µM, a sensitivity of 21.5 µA µM-1 (from 1 µM to 100 µM) and a lower detection limit of 27.81 nM, respectively. PtZn NFs/CC electrodes show excellent stability and anti-interference. In addition, the fabricated electrochemical sensor can be used to detect ammonia nitrogen in tap water and lake water samples.

Measurements of aerosol phase function and vertical backscattering coefficient using a charge-coupled device side-scatter lidar.

By using a charge-coupled device (CCD) as the detector, side-scatter lidar has great potential applications in the near range atmospheric detection. A new inversion method is proposed for CCD side-scatter lidar (Clidar) to retrieve aerosol phase function and vertical backscattering coefficient. Case studies show the retrieved results from Clidar are in good agreements with those obtained from other instruments. It indicates that the new proposed inversion method is reliable and feasible and that the Clidar is practicable.

Metabolomics reveals early pregnancy biomarkers in sows: a non-invasive diagnostic approach.

In an effort to enhance reproductive management and reduce non-productive periods in swine breeding, this study presents a novel, non-invasive metabolomics approach for the identification of early pregnancy biomarkers in sows. Utilizing an untargeted metabolomics approach with mass spectrometry analysis, we examined saliva samples from pregnant (n = 6) and non-pregnant control sows (n = 6, artificially inseminated with non-viable sperm). Our analysis revealed 286 differentially expressed metabolites, with 152 being up-regulated and 134 down-regulated in the pregnant group. Among these, three metabolites, namely Hyodeoxycholic acid, 2'-deoxyguanosine, and Thymidine, emerged as potential early pregnancy biomarkers. These biomarkers were further evaluated using targeted LC-MS/MS quantification and qualification, accompanied by ROC curve analysis. The study confirmed Hyodeoxycholic acid and 2'-deoxyguanosine as promising biomarkers for early pregnancy detection, offering potential for future implementation in swine production environments. This research establishes a robust theoretical foundation for the development of innovative molecular diagnostic techniques and explores new avenues for molecular genetic breeding and non-invasive diagnostics, ultimately enhancing fertility and productivity in sow herds.