Insights into growth stages and genotypes in airborne Pb accumulation in Oryza sativa L. grains: Utilizing isotope fingerprinting alongside a model study.

Atmospheric exposure is an important pathway of accumulation of lead (Pb) in Oryza sativa L. grains. In this study, source contributions of soil, early atmospheric exposure, and late atmospheric exposure, along with their bioaccumulation ratios were examined both in the pot and field experiments using stable Pb isotope fingerprinting technology combined with a three-compartment accumulation model. Furthermore, genotype differences in airborne Pb accumulation among four field-grown rice cultivars were investigated using the partial least squares path model (PLS-PM) linking rice Pb accumulation to agronomic traits. The findings revealed that during the late growth period, the air-foliar-grain transfer of Pb was crucial for rice Pb accumulation. Approximately 69-82% of the Pb found in polished rice was contributed by atmospheric source, with more than 80% accumulating during the late growth stage. The air accumulation ratios of rice grains were genotype-specific and estimated to be 0.364-1.062 m3/g during the late growth. Notably, grain size exhibited the highest standardized total effects on the airborne Pb concentrations in the polished rice, followed by leaf Pb and the upward translocation efficiency of Pb. The present study indicates that mitigating the health risks associated with Pb in rice can be achieved by controlling atmospheric Pb levels during the late growth stage and choosing Japonica inbred varieties characterized by large grain size.

A High-Voltage-Specialized Direct-Current Triboelectric Nanogenerator for Air Purification.

Human health and the environment face significant challenges of air pollution, which is predominantly caused by PM2.5 or PM10 particles. Existing control methods often require elevated energy consumption or bulky high-voltage electrical equipment. To overcome these limitations, a self-powered, convenient, and compact direct current high-voltage triboelectric nanogenerator based on triboelectrification and electrostatic breakdown effects is proposed. By optimizing the structure-design of the direct current triboelectric nanogenerator and corresponding output voltage, it can easily achieve an output voltage of over 3 kV with a high charge density of 320 µC m-2 . A power management circuit is designed to overcome the influence of third domain self-breakdown, optimize 92.5% amplitude of voltage shake, and raise 5% charge utilization ratio. With a device size as tiny as 2.25 cm3 , it can continuously drive carbon nanowires to generate negative ions that settle dust within 300 s. This compact, simple, efficient, and safe high-voltage direct current triboelectric nanogenerator represents a promising sustainable solution. It offers efficient dust mitigation, fostering cleaner environments, and enhancing overall health.

A COMPASS histone H3K4 trimethyltransferase pentamer transactivates drought tolerance and growth/biomass production in Populus trichocarpa.

Histone H3 lysine-4 trimethylation (H3K4me3) activating drought-responsive genes in plants for drought adaptation has long been established, but the underlying regulatory mechanisms are unknown. Here, using yeast two-hybrid, bimolecular fluorescence complementation, biochemical analyses, transient and CRISPR-mediated transgenesis in Populus trichocarpa, we unveiled in this adaptation a regulatory interplay between chromatin regulation and gene transactivation mediated by an epigenetic determinant, a PtrSDG2-1-PtrCOMPASS (complex proteins associated with Set1)-like H3K4me3 complex, PtrSDG2-1-PtrWDR5a-1-PtrRbBP5-1-PtrAsh2-2 (PtrSWRA). Under drought conditions, a transcription factor PtrAREB1-2 interacts with PtrSWRA, forming a PtrSWRA-PtrAREB1-2 pentamer, to recruit PtrSWRA to specific promoter elements of drought-tolerant genes, such as PtrHox2, PtrHox46, and PtrHox52, for depositing H3K4me3 to promote and maintain activated state of such genes for tolerance. CRISPR-edited defects in the pentamer impaired drought tolerance and elevated expression of PtrHox2, PtrHox46, or PtrHox52 improved the tolerance as well as growth in P. trichocarpa. Our findings revealed the identity of the underlying H3K4 trimethyltransferase and its interactive arrangement with the COMPASS for catalysis specificity and efficiency. Furthermore, our study uncovered how the H3K4 trimethyltransferase-COMPASS complex is recruited to the effector genes for elevating H3K4me3 marks for improved drought tolerance and growth/biomass production in plants.

Analysis on Changes and Influencing Factors of the Intestinal Microbiota of Alpine Musk Deer between the Place of Origin and Migration.

In China, the population of wild musk deer, belonging to the family Moschidae, has drastically decreased in recent years owing to human activities and environmental changes. During the 1990s, artificial breeding of Alpine musk deer was conducted in Xinglong Mountain, Gansu Province, China, and their ex situ conservation was explored for over a decade. Ex situ protection is beneficial for expanding the population of animals and maintaining their genetic diversity; however, it can also induce metabolic diseases and parasitic infections and reduce reproductive capacity. The gut microbiota of animals has a considerable impact on host energy metabolism and immune regulation, thereby playing a crucial role in the overall health and reproductive success of the host. In this study, by comparing the differences in the intestinal microbiome of the musk deer according to their place of origin and migration, the changes in their gut microbiota and the influencing factors were explored to provide a theoretical basis for monitoring the health status of the musk deer. We used 16S rRNA high-throughput sequencing technology to analyze the structure and diversity of the gut microbiota of Alpine musk deer in Gansu (G, place of origin) and Sichuan (S, place of migration). The results showed that the dominant bacteria and genera in the intestinal microbiome of captive musk deer were similar in the places of origin and migration, but significant differences were observed in their relative abundance (p < 0.05). Regarding Firmicutes and Actinobacteria, which are related to plant cellulose digestion, the relative abundance in group G was higher than that in group S; regarding Proteobacteria and Verrucomicrobia, which are related to fat and starch intake, the relative abundance in group S was higher than that in group G; the relative abundance of Bacillus and Clostridium sensu stricto, which are related to fiber digestibility, was higher in group G than in group S; the relative abundance of conditional pathogens Acinetobacter and Escherichia-Shigella was higher in group S than in group G. The results of α and ß diversity analysis also showed significant differences between the two groups (p < 0.05). The ACE and Shannon indices of musk deer in group G were considerably higher than those in group S, and the Simpson index of musk deer in group S was greater than that in group G, indicating that the abundance and diversity of intestinal microbiome were higher in musk deer of Gansu than those of Sichuan. Comparison of the changes in the intestinal microbiome of the musk deer according to the place of origin and migration showed that the plant cellulose content in the food of the musk deer, the fat content in the concentrated feed, and changes in the feeding environment have an impact on the intestinal microbiome. Effective monitoring of the health and immunity of the musk deer is crucial for ensuring their overall health, which in turn will aid in formulating a scientific and reasonable management plan for their conservation.

Factors influencing advanced colorectal neoplasm anatomic site distribution in China: An epidemiological study based on colorectal cancer screening data.

OBJECTIVE: Existing studies indicate that advanced colorectal neoplasms exhibit distinct clinical and biological traits based on anatomical sites. However, in China, especially for advanced colorectal neoplasms, there's limited information available on these traits. Our primary objective is to comprehensively study the characteristics of advanced colorectal neoplasm patients in different anatomical sites in China. METHODS: We selected information from the colorectal cancer screening database in Tianjin, China, since 2010 as the study subject. We chose valid information from 3113 patients with comprehensive data and diagnosed advanced colorectal neoplasms (ANs) from a pool of 19,308 individuals to be included in the study. We then conducted further analysis to examine the correlation between these epidemiological data and tumor location. RESULTS: Among the 3113 patients, neoplasms in the left side of the colon accounted for the largest proportion, while neoplasms in the right side of the colon had the smallest proportion, followed by rectal neoplasms. The highest proportion of advanced colorectal neoplasms was found among men. In the age group of 39-49 years old, the proportion of left late-stage advanced colon neoplasms was equal to that of right late-stage advanced colon neoplasms, while late-stage advanced rectal neoplasms increased with age. Smoking, drinking, and a history of colon cancer in first-degree relatives showed statistically significant associations with the location distribution of advanced colorectal neoplasms. A history of appendicitis, appendectomy, cholecystitis, or cholecystectomy did not significantly affect the location distribution of advanced colorectal neoplasms. However, among patients with such histories, there was a statistically significant relationship between advanced colon neoplasms on the right and those on the left and in the rectum. Similar results were observed for BMI. CONCLUSION: Our research findings demonstrate that advanced colorectal neoplasms display unique epidemiological characteristics depending on their anatomical locations, and these distinctions deviate from those observed in Western populations. These insights contribute to a more comprehensive understanding of the topic and offer valuable guidance for future research in China. We advocate for further investigations centered on the anatomical location of colorectal neoplasms to enhance the precision of colorectal cancer (CRC) screening and treatment.

Detecting Forest Musk Deer Abscess Disease Pathogens Using 16S rRNA High-Throughput Sequencing Technology.

Currently, researchers use bacterial culture and targeted PCR methods to classify, culture, and identify the pathogens causing abscess diseases. However, this method is limited by factors such as the type of culture medium and culture conditions, making it challenging to screen and proliferate many bacteria effectively. Fortunately, with the development of high-throughput sequencing technology, pathogen identification at the genetic level has become possible. Not only can this approach overcome the limitations of bacterial culture, but it can also accurately identify the types and relative abundance of pathogens. In this study, we used high-throughput sequencing of 16S rRNA to identify the pathogens in purulent fluid samples. Our results not only confirmed the presence of the main pathogen reported by previous researchers, Trueperella pyogenes, but also other obligate anaerobes, Fusobacterium necrophorum and Bacteroides fragilis as the dominant pathogens causing abscess diseases for the first time. Therefore, our findings suggest that high-throughput sequencing technology has the potential to replace traditional bacterial culture and targeted PCR methods.

Inter-bacterial mutualism promoted by public goods in a system characterized by deterministic temperature variation.

Mutualism is commonly observed in nature but not often reported for bacterial communities. Although abiotic stress is thought to promote microbial mutualism, there is a paucity of research in this area. Here, we monitor microbial communities in a quasi-natural composting system, where temperature variation (20 °C-70 °C) is the main abiotic stress. Genomic analyses and culturing experiments provide evidence that temperature selects for slow-growing and stress-tolerant strains (i.e., Thermobifida fusca and Saccharomonospora viridis), and mutualistic interactions emerge between them and the remaining strains through the sharing of cobalamin. Comparison of 3000 bacterial pairings reveals that mutualism is common (~39.1%) and competition is rare (~13.9%) in pairs involving T. fusca and S. viridis. Overall, our work provides insights into how high temperature can favour mutualism and reduce competition at both the community and species levels.

Vertical migration and dissipation of oxytetracycline induces the recoverable shift in microbial community and antibiotic resistance.

Antibiotic resistance gene (ARG) spread in anthropogenic polluted soils is believed to be accelerated by the incidental inputs of antibiotics via fertilizing and irrigation, and endangering food and human health. However, due to the complex nature of substrates and uncertain microbial responses, the primary drivers of ARG dissemination remain unclear. To address this concern, the effects of antibiotic inputs on soil microbes and antibiotic resistance under simulated natural conditions was investigated in this study. Specifically, four flow-through reactors with gravity flow were established, and the oxytetracycline (OTC) a typical antibiotic in agricultural soils was studied at environmental concentrations (i.e. 0.1, 1 and 10 mg/kg) for 31 days. The vertical distribution and dissipation of OTC were profiled by measuring the residuals in layers over time. Correspondingly, the effects of antibiotic exposure on microbial communities and ARG abundances were studied. The results showed that the average exposure intensity of OTC in different soil layers ranged in 0.03-6.45 mg/kg, and resulted in different dissipation kinetics. In addition, top layer was found to be the main site of OTC reduction, where OTC dissipated at magnitude of 74.0-96.6 %, depending on the initial OTC concentration. OTC migration and dissipation resulted in the shift of community composition to the extent of 0.25-0.33 in terms of Bray-Curtis distance, which partially recovered over time. And the achievement of alternative community compositions was supposed to be largely affected by the microbial interaction. Along with the community changes, a short-term accumulation of resistance genes was detected, while the relative abundance of indicator ARGs, i.e. tetG and mexB, rising up to 10-fold higher than the initial, although eventually decayed. Collective findings of this study indicated that antibiotics at environmental concentrations might trigger extra microbial interactions and thereby reducing the demand for ARGs accumulation. It provided valuable understandings in the risk of antibiotic spillage, especially for the incident exposure at the environmentally relevant concentrations.

A Rotating Triboelectric Nanogenerator Driven by Bidirectional Swing for Water Wave Energy Harvesting.

Due to the simple installation and convenient maintenance, the floating water wave energy harvesting devices have significant economic advantages. Mass power density is the most important index to evaluate the advancement of floating wave energy harvesting devices. Herein, a self-adaptive rotating triboelectric nanogenerator (SR-TENG) with a compound pendulum and a functional gear-set is provided for wave energy harvesting. First, a compound pendulum structure with a low center of gravity and high moment of inertia is obtained by the geometric design and mechanical study. Besides, compared with the previous triboelectric nanogenerator with one-way clutch, SR-TENG can harvest twice the kinetic energy utilization through the functional gear-set. Importantly, depending on the structure design, the SR-TENG obtains the average mass power density of 45.18 mW kg-1 under low frequency driving conditions, which is about 10 times the reference electromagnetic generator with a similar structure and size. This result shows that the SR-TENG has a significant advantage in small water wave energy harvesting. These findings provide an important example of the floating water wave energy harvesting devices.

Accurate luminance and chromaticity controls of digital colors using CIE-based RGBW algorithms.

Emerging high brightness of color displays and high signal-to-noise ratio of camera sensors require an addition of white (W) subpixels to ordinary red, green, and blue (RGB) subpixels. Conventional algorithms converting RGB signals to RGBW signals suffer from reduced chroma of highly saturated colors and complicated coordinate transformations between RGB color spaces and color spaces defined by the Commission internationale de l'éclairage (CIE). In this work, we developed a complete set of RGBW algorithms to digitally code a color in the CIE-based color spaces, making complicated processes including color space transformations and white balancing become largely unnecessary. The analytic three-dimensional gamut can be obtained so that the maximal hue and luminance of a digital frame could be simultaneously obtained. Exemplary applications in adaptive controls of the colors of an RGB display in accordance with the W component of background light validate our theory. The algorithm opens an avenue toward accurate manipulations of digital colors for RGBW sensors and displays.

Mechanical Alloying Behavior and Thermal Stability of CoCrCuFeMnNix High-Entropy Alloy Powders Prepared via MA.

CoCrCuFeMnNix (x = 0, 0.5, 1.0, 1.5, 2.0 mol, named as Ni0, Ni0.5, Ni1.0, Ni1.5, and Ni2.0, respectively) high-entropy alloy powders (HEAPs) were prepared via mechanical alloying (MA), and XRD, SEM, EDS, and vacuum annealing were used to study the alloying behavior, phase transition, and thermal stability. The results indicated that the Ni0, Ni0.5, and Ni1.0 HEAPs were alloyed at the initial stage (5-15 h), the metastable BCC + FCC two-phase solid solution structure was formed, and the BCC phase disappeared gradually with the prolonging of ball milling time. Finally, a single FCC structure was formed. Both Ni1.5 and Ni2.0 alloys with high nickel content formed a single FCC structure during the whole mechanical alloying process. The five kinds of HEAPs showed equiaxed particles in dry milling, and the particle size increased with an increase in milling time. After wet milling, they changed into lamellar morphology with thickness less than 1 µm and maximum size less than 20 µm. The composition of each component was close to its nominal composition, and the alloying sequence during ball milling was Cu→Mn→Co→Ni→Fe→Cr. After vacuum annealing at 700~900 °C, the FCC phase in the HEAPs with low Ni content transformed into FCC2 secondary phase, FCC1 primary phase, and a minor σ phase. The thermal stability of HEAPs can be improved by increasing Ni content.

Continuous diagnosis and prognosis by controlling the update process of deep neural networks.

Continuous diagnosis and prognosis are essential for critical patients. They can provide more opportunities for timely treatment and rational allocation. Although deep-learning techniques have demonstrated superiority in many medical tasks, they frequently forget, overfit, and produce results too late when performing continuous diagnosis and prognosis. In this work, we summarize the four requirements; propose a concept, continuous classification of time series (CCTS); and design a training method for deep learning, restricted update strategy (RU). The RU outperforms all baselines and achieves average accuracies of 90%, 97%, and 85% on continuous sepsis prognosis, COVID-19 mortality prediction, and eight disease classifications, respectively. The RU can also endow deep learning with interpretability, exploring disease mechanisms through staging and biomarker discovery. We find four sepsis stages, three COVID-19 stages, and their respective biomarkers. Further, our approach is data and model agnostic. It can be applied to other diseases and even in other fields.

Adaptive model training strategy for continuous classification of time series.

The classification of time series is essential in many real-world applications like healthcare. The class of a time series is usually labeled at the final time, but more and more time-sensitive applications require classifying time series continuously. For example, the outcome of a critical patient is only determined at the end, but he should be diagnosed at all times for timely treatment. For this demand, we propose a new concept, Continuous Classification of Time Series (CCTS). Different from the existing single-shot classification, the key of CCTS is to model multiple distributions simultaneously due to the dynamic evolution of time series. But the deep learning model will encounter intertwined problems of catastrophic forgetting and over-fitting when learning multi-distribution. In this work, we found that the well-designed distribution division and replay strategies in the model training process can help to solve the problems. We propose a novel Adaptive model training strategy for CCTS (ACCTS). Its adaptability represents two aspects: (1) Adaptive multi-distribution extraction policy. Instead of the fixed rules and the prior knowledge, ACCTS extracts data distributions adaptive to the time series evolution and the model change; (2) Adaptive importance-based replay policy. Instead of reviewing all old distributions, ACCTS only replays important samples adaptive to their contribution to the model. Experiments on four real-world datasets show that our method outperforms all baselines.

Cross-Domain Object Detection by Dual Adaptive Branch.

The object detection task usually assumes that the training and test samples obey the same distribution, and this assumption is not valid in reality, therefore the study of cross-domain object detection is proposed. Compared with image classification, the cross-domain object detection task presents the greater challenge, which requires both accurate classification and localization of samples in the target domain. The teacher-student framework (the student model is supervised by pseudo-labels from the teacher model) has produced a large accuracy improvement in cross-domain object detection. Feature-level adversarial training is used in the student model, which allows features in the source and target domains to share a similar distribution. However, the direction and gradient of the weights can be divided into domain-specific and domain-invariant features, and the purpose of domain adaptive is to focus on the domain-invariant features while eliminating interference from the domain-specific features. Inspired by this, we propose a teacher-student framework named dual adaptive branch (DAB), which uses domain adversarial learning to address the domain distribution. Specifically, we ensure that the student model aligns domain-invariant features and suppresses domain-specific features in this process. We further validate our method based on multiple domains. The experimental results demonstrate that our proposed method significantly improves the performance of cross-domain object detection and achieves the competitive experimental results on common benchmarks.

Deterministic Effect of pH on Shaping Soil Resistome Revealed by Metagenomic Analysis.

Soil is recognized as the major reservoir of antibiotic resistance genes (ARGs), harboring the most diverse naturally evolved ARGs on the planet. Multidrug resistance genes are a class of ARGs, and their high prevalence in natural soil ecosystems has recently raised concerns. Since most of these genes express proton motive force (PMF) driven efflux pumps, studying whether soil pH is a determinant for the selection of multidrug efflux pump genes and thus shaping the soil resistome are of great interest. In this study, we collected 108 soils with pH values ranging from 4.37 to 9.69 from multiple ecosystems and profiled the composition of ARGs for metagenomes and metagenome-assembled genomes. We observed the multidrug efflux pump genes enriched in the acidic soil resistome, and their abundances have significant soil pH dependence. This reflects the benefits of high soil proton activity on the multidrug efflux pump genes, especially for the PMF-driven inner membrane transferase. In addition, we preliminary indicate the putative microbial participants in pH shaping the soil resistome by applying ecological analyzing tools such as stepwise regression and random forest model fitting. The decisive influence of proton activity on shaping the resistome is more impactful than any other examined factors, and as the consequence, we revisited the influence of edaphic factors on the soil resistome; i.e., the deterministic selection of resistance mechanisms by edaphic factors could lead to the bottom-up shaping of the ARG composition. Such natural developing mechanisms of the resistome are herein suggested to be considered in assessing human-driven ARG transmissions.

Cell-type-specific PtrWOX4a and PtrVCS2 form a regulatory nexus with a histone modification system for stem cambium development in Populus trichocarpa.

Stem vascular cambium cells in forest trees produce wood for materials and energy. WOX4 affects the proliferation of such cells in Populus. Here we show that PtrWOX4a is the most highly expressed stem vascular-cambium-specific (VCS) gene in P. trichocarpa, and its expression is controlled by the product of the second most highly expressed VCS gene, PtrVCS2, encoding a zinc finger protein. PtrVCS2 binds to the PtrWOX4a promoter as part of a PtrWOX13a-PtrVCS2-PtrGCN5-1-PtrADA2b-3 protein tetramer. PtrVCS2 prevented the interaction between PtrGCN5-1 and PtrADA2b-3, resulting in H3K9, H3K14 and H3K27 hypoacetylation at the PtrWOX4a promoter, which led to fewer cambium cell layers. These effects on cambium cell proliferation were consistent across more than 20 sets of transgenic lines overexpressing individual genes, gene-edited mutants and RNA interference lines in P. trichocarpa. We propose that the tetramer-PtrWOX4a system may coordinate genetic and epigenetic regulation to maintain normal vascular cambium development for wood formation.

Kinesiophobia in patients with angina pectoris of coronary artery disease: A cross-sectional survey.

BACKGROUND: In the field of chronic pain research, kinesiophobia is defined as avoidance behavior due to fear of pain, but this perspective seems to be neglected in the field of coronary artery disease (CAD). OBJECTIVE: To investigate the status quo of angina pectoris (AP) and kinesiophobia and factors associated with kinesiophobia in patients with AP of CAD. METHODS: This was a cross-sectional study. Participants were recruited by convenience sampling, and patients with AP of CAD in four wards of the Cardiology Department of a hospital were enrolled in this study. Participants completed questionnaires and scales face-to-face with researchers. RESULTS: Most patients with AP of CAD suffered from at least moderate pain episodes (60.2%) of at least 5 minutes per episode (53.8%), but less than 1/3 of patients reached 5 instances of pain per week (29.1%). The total score of kinesiophobia in patients was 40.80±6.65, and the vast majority of patients had moderate to high levels of kinesiophobia (75.7%). The results of multiple linear stepwise regression analysis showed that personal monthly income, New York Heart Function Assessment (NYHA) classification, pain intensity, and pain resilience were independent factors associated with kinesiophobia, and these factors explained 30.2% of the variation in total scores of kinesiophobia. CONCLUSION: The symptoms of AP were prominent in terms of pain intensity and duration of pain. The level of kinesiophobia was moderate, and this was affected by multiple factors. Health care providers and researchers seldom pay attention to the kinesiophobia of patients with AP of CAD. This study refocused on the effect of "fear of pain" in kinesiophobia in patients with CAD. It opens up new horizons for the application of fear-avoidance models in CAD patients and helps to raise awareness of kinesiophobia in AP patients with CAD and provides guidance for reducing the level of kinesiophobia in the future.

Effects of different weaning times on the stress response and the intestinal microbiota composition of female forest musk deer (Moschus berezovskii) and their fawns.

The effects of mother-infant separation (i.e., weaning) on the physiology, psychology and nutrition of mammalian infants have attracted much attention. Forest musk deer (FMD) is a first-class protected species in China and listed endangered in the IUCN Red List. The captive breeding population is not only an important source for restocking of wild resources, but also a necessary way to supply the market with legal musk. So far, there is no scientific basis for the appropriate separation time of FMD females and their infants. Therefore, we used metagenome sequencing and enzyme-linked immunosorbent assays to study changes in the fecal cortisol concentration, as well as the intestinal microbiome composition and function of females and fawns at three different separation times, i.e., after 80 days, 90 days and 100 days. The results showed that the increment of the cortisol concentration in female FMD increased with increasing lactation time. The increment of cortisol concentration in infant FMD was highest in the 80 days weaning group, but there was no significant difference between the 90 days and the 100 days separation time. Based on the annotation results of COG, KEGG and CAZy databases, the abundance of different functions annotated by the intestinal microbiome of mothers and fawns of the 90 days weaning group changed slightly after separation. Based on the above results, the separation of mother and infant FMD is recommended after 90 days, i.e., the separation time that triggered the lowest rate of weaning stress and that supported a relatively stable gastro-intestinal physiology.

Interaction between arsenic metabolism genes and arsenic leads to a lose-lose situation.

Microorganisms are essential for modifying arsenic morphology, mobility, and toxicity. Still, knowledge of the microorganisms responsible for arsenic metabolism in specific arsenic-contaminated fields, such as metallurgical plants is limited. We sampled on-field soils from three depths at 70 day intervals to explore the distribution and transformation of arsenic in the soil. Arsenic-metabolizing microorganisms were identified from the mapped gene sequences. Arsenic metabolism pathways were constructed with metagenomics and AsChip analysis (a high-throughput qPCR chip for arsenic metabolism genes). It has been shown in the result that 350 genera of arsenic-metabolizing microorganisms carrying 17 arsenic metabolism genes in field soils were identified, as relevant to arsenic reduction, arsenic methylation, arsenic respiration, and arsenic oxidation, respectively. Arsenic reduction genes were the only genes shared by the 10 high-ranking arsenic-metabolizing microorganisms. Arsenic reduction genes (arsABCDRT and acr3) accounted for 73.47%-78.11% of all arsenic metabolism genes. Such genes dominated arsenic metabolism, mediating the reduction of 14.11%-19.86% of As(V) to As(III) in 0-100 cm soils. Arsenic reduction disrupts microbial energy metabolism, DNA replication and repair and membrane transport. Arsenic reduction led to a significant decrease in the abundance of 17 arsenic metabolism genes (p < 0.0001). The critical role of arsenic-reducing microorganisms in the migration and transformation of arsenic in metallurgical field soils, was emphasized with such results. These results were of pronounced significance for understanding the transformation behavior of arsenic and the precise regulation of arsenic in field soil.

Population genomics reveals moderate genetic differentiation between populations of endangered Forest Musk Deer located in Shaanxi and Sichuan.

BACKGROUND: Many endangered species exist in small, genetically depauperate, or inbred populations, hence promoting genetic differentiation and reducing long-term population viability. Forest Musk Deer (Moschus berezovskii) has been subject to illegal hunting for hundreds of years due to the medical and commercial values of musk, resulting in a significant decline in population size. However, it is still unclear to what extent the genetic exchange and inbreeding levels are between geographically isolated populations. By using whole-genome data, we reconstructed the demographic history, evaluated genetic diversity, and characterized the population genetic structure of Forest Musk Deer from one wild population in Sichuan Province and two captive populations from two ex-situ centers in Shaanxi Province. RESULTS: SNP calling by GATK resulted in a total of 44,008,662 SNPs. Principal component analysis (PCA), phylogenetic tree (NJ tree), ancestral component analysis (ADMIXTURE) and the ABBA-BABA test separated Sichuan and Shaanxi Forest Musk Deer as two genetic clusters, but no obvious genetic differentiation was observed between the two captive populations. The average pairwise FST value between the populations in Sichuan and Shaanxi ranged from 0.05-0.07, suggesting a low to moderate genetic differentiation. The mean heterozygous SNPs rate was 0.14% (0.11%-0.15%) for Forest Musk Deer at the genomic scale, and varied significantly among three populations (Chi-square = 1.22, p < 0.05, Kruskal-Wallis Test), with the Sichuan population having the lowest (0.11%). The nucleotide diversity of three populations varied significantly (p < 0.05, Kruskal-Wallis Test), with the Sichuan population having the lowest genetic θπ (1.69 × 10-3). CONCLUSIONS: Genetic diversity of Forest Musk Deer was moderate at the genomic scale compared with other endangered species. Genetic differentiation between populations in Sichuan and Shaanxi may not only result from historical biogeographical factors but also be associated with contemporary human disturbances. Our findings provide scientific aid for the conservation and management of Forest Musk Deer. They can extend the proposed measures at the genomic level to apply to other musk deer species worldwide.