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The prevalence of dyslipidemia is increasing, and it has become a significant global public health concern. Some studies have demonstrated contradictory relationships between urinary metals and dyslipidemia, and the combined effects of mixed urinary metal exposure on dyslipidemia remain ambiguous. In this study, we examined how individual and combined urinary metal exposure are associated with the occurrence of dyslipidemia. According to the data from the 2018–2019 baseline survey database of the China Multi-Ethnic Cohort (CMEC) Study, a population of 9348 individuals was studied. Inductively coupled plasmamass spectrometry (ICP-MS) was used to measure 21 urinary metal concentrations in the collected adult urinary samples. The associations between urinary metals and dyslipidemia were analyzed by logistic regression, weighted quantile sum regression (WQS), and quantile-based g-computation (qgcomp), controlled for potential confounders to examine single and combined effects. Dyslipidemia was detected in 3231 individuals, which represented approximately 34.6 % of the total population. According to the single-exposure model, Al and Na were inversely associated with the risk of dyslipidemia (OR = 0.95, 95 % CI: 0.93, 0.98; OR = 0.89, 95 % CI: 0.83, 0.95, respectively), whereas Zn, Ca, and P were positively associated (OR = 1.69, 95 % CI: 1.42, 2.01; OR = 1.12, 95 % CI: 1.06, 1.18; OR = 1.21, 95 % CI: 1.09, 1.34, respectively). Moreover, Zn and P were significantly positively associated even after adjusting for these metals, whereas Al and Cr were negatively associated with the risk of dyslipidemia. The results of the WQS and qgcomp analyses showed that urinary metal mixtures were positively associated with the risk of dyslipidemia (OR = 1.26, 95 % CI: 1.15, 1.38; OR = 1.09, 95 % CI: 1.01, 1.19). This positive association was primarily driven by Zn, P, and Ca. In the sensitivity analyses with collinearity diagnosis, interaction, and stratified analysis, the results remained, confirming the reliability of the study findings. In this study, the individual and combined effects of urinary Zn, P, and Ca on dyslipidemia were determined, which provided novel insights into the link between exposure to metals and dyslipidemia.

Constituents of cigarette smoke are known to be carcinogens. Additionally, there is mounting evidence that the liver is an organ susceptible to tobacco carcinogenicity. Nicotine, the primary constituent of tobacco, plays a role in cancer progression. In our previous study, it was found that nicotine enhances the proliferation of a human normal fetal hepatic (WRL68) cell due to the activation of p53 mutation at Ser249 (p53-RS)/STAT1/CCND1 signaling pathway. Here, we further elucidated the mechanism of regulating this pathway. Firstly, dose-dependent increase of SETDB1 protein level in WRL68 cells upon exposure to nicotine (1.25, 2.5, and 5 μM), significantly enhanced cellular proliferation. In addition, the upregulation of SETDB1 protein was necessary for the nuclear translocation of p53-RS to establish a ternary complex with STAT1 and SETDB1, which facilitated p53-RS di-methylation at K370 (p53-RS/K370me2). After that, the activation of CCND1/PI3K/AKT pathway was initiated when STAT1 stability was enhanced by p53-RS/K370me2, ultimately resulting in cell proliferation. Altogether, the study revealed that the increase in SETDB1 expression could potentially have a significant impact on the activation of CCND1/PI3K/AKT pathway through p53-RS/K370me2, leading to the proliferation of WRL68 cells induced by nicotine, which could contribute to hepatocellular carcinoma for smokers. Besides, the results of this study provided a foundation for the development of anticancer therapies for cancers associated with tobacco use.

Summary: Microorganisms are critical to the stability of aquatic environments, and understanding the ecological mechanisms of microbial community is essential. However, the distinctions and linkages across biogeographic patterns, ecological processes, and formation mechanisms of microbes in rivers and lakes remain unknown. Accordingly, microbiome-centric analysis was conducted in rivers and lakes in the Yangtze River watershed. Results revealed significant differences in the structure and diversity of microbial communities between rivers and lakes, with rivers showing higher diversity. Lakes exhibited lower community stability, despite higher species interactions. Although deterministic processes dominated microbial community assembly both in rivers and lakes, higher stochastic processes of rare and abundant taxa exhibited in rivers. Spatial factors influenced river microbial community, while environmental factors drove differences in the lake bacterial community. This study deepened the understanding of microbial biogeography and formation mechanisms in large watershed rivers and lakes, highlighting distinct community aggregation patterns between river and lake microorganisms.

Lyophyllum decastes is a common mushroom that is prone to browning during prolonged storage. In this study, the effects of ultrasonic treatment on metabolic gene expression, enzyme activity, and metabolic compounds related to L. decastes browning were investigated. Treatment of the fruiting body at 35 kHz and 300 W for 10 min reduced the browning index of L. decastes by 21.0 % and increased the L* value by 11.1 %. Ultrasonic treatment of the fruiting body resulted in higher levels of total phenols, flavonoids, and 9 kinds of amino acid with catalase (CAT) and peroxidase (POD) activities maintained at high levels. Higher cytochrome c oxidase (CCO), succinate dehydrogenase (SDH), phosphofructokinase (PFK), and pyruvate kinase (PK) activities may be ascribed to increased antioxidant capacity. Moreover, ultrasonication retained higher adenosine triphosphate (ATP) concentrations with an increased energy charge, while there were lower levels of adenosine diphosphate (ADP) and reduced and oxidized nicotinamide adenine dinucleotide (NADH and NAD+), respectively. Meanwhile, lower lignin contents were observed, along with retarded polyphenol oxidase (PPO) and lipoxygenase (LOX) activities. Lower PPO activity reduced the fruiting body enzymatic browning rate through decreased expression of LdPpo1, LdPpo2, and LdPpo3 during storage at 4 °C for 16 days. This activity may be used to determine the effectiveness of ultrasonication.

Chronic arsenic exposure is associated with the increased risk of several types of cancer, among which, lung cancer is the most deadly one. Nuclear factor erythroid 2 like 1 (NFE2L1), a transcription factor belonging to CNC-bZIP family, regulates multiple important cellular functions in response to acute arsenite exposure. However, the role of NFE2L1 in lung cancer induced by chronic arsenite exposure is unknown. In this study, we firstly showed that chronic arsenite exposure (36 weeks) led to epithelial-mesenchymal transition (EMT) and malignant transformation in human bronchial epithelial cells (BEAS-2B). During the process of malignant transformation, the expression of long isoforms of NFE2L1 (NFE2L1-L) was elevated. Thereafter, BEAS-2B cells with NFE2L1-L stable knockdown (NFE2L1-L-KD) was chronically exposed to arsenite. As expected, silencing of NFE2L1-L gene strikingly inhibited the arsenite-induced EMT and the subsequent malignant transformation. Additionally, NFE2L1-L silencing suppressed the transcription of EMT-inducer SNAIL1 and increased the expression of E-cadherin. Conversely, NFE2L1-L overexpression increased SNAIL1 transcription but decreased E-cadherin expression. Collectively, our data suggest that NFE2L1-L promotes EMT by positively regulating SNAIL1 transcription, and is involved in malignant transformation induced by arsenite.

Study region: Urban built-up area of Zhengzhou, China. Study focus: A coupled urban flood forecasting model based on WRF-SWMM is proposed. Different spatial resolution data as input for WRF (Weather Research and Forecasting Model) to study the characteristics of forecasting precipitation, combined with measured precipitation series, the SWMM (Storm Water Management Model) was driven to forecast the urban flood process. New hydrological insights for the study region: Using the WRF-SWMM coupling model to simulate flood disasters can effectively improve the timeliness of urban flood prediction. The results indicate that a spatial resolution of 0.25-degree improved the overall precipitation prediction results. With an increase in lead time, the prediction performance of the WRF decreased. The WRF model can simulate results effectively owing to its sensitivity to bimodal rainfall patterns. When the WRF model produces an overestimate (or underestimate), part of the urban canals in the SWMM model will also carry out a high forecast (or low forecast) output of flood peak discharge. The SWMM model also has a cumulative amplification effect on the results of flood simulation. In addition, the quantitative accuracy of precipitation forecasts plays a vital role in urban flood simulation, and the existing coupling models based on WRF-SWMM can generate reasonable forecasts 3–6 h in advance.

Chronic exposure to arsenic has been associated with a variety of cancers with the mechanisms undefined. Arsenic exposure causes alterations in metabolites in bio-samples. Recent research progress on cancer biology suggests that metabolic reprogramming contributes to tumorigenesis. Therefore, metabolic reprogramming provides a new clue for the mechanisms of arsenic carcinogenesis. In the present manuscript, we review the latest findings in reprogramming of glucose, lipids, and amino acids in response to arsenic exposure. Most studies focused on glucose reprogramming and found that arsenic exposure enhanced glycolysis. However, in vivo studies observed “reverse Warburg effect” in some cases due to the complexity of the disease evolution and microenvironment. Arsenic exposure has been reported to disturb lipid deposition by inhibiting lipolysis, and induce serine-glycine one-carbon pathway. As a dominant mechanism for arsenic toxicity, oxidative stress is considered to link with metabolism reprogramming. Few studies analyzed the causal relationship between metabolic reprogramming and arsenic-induced cancers. Metabolic alterations may vary with exposure doses and periods. Identifying metabolic alterations common among humans and experiment models with human-relevant exposure characteristics may guide future investigations.

Diffusion tensor magnetic resonance imaging (DTI) is unsurpassed in its ability to map tissue microstructure and structural connectivity in the living human brain. Nonetheless, the angular sampling requirement for DTI leads to long scan times and poses a critical barrier to performing high-quality DTI in routine clinical practice and large-scale research studies. In this work we present a new processing framework for DTI entitled DeepDTI that minimizes the data requirement of DTI to six diffusion-weighted images (DWIs) required by conventional voxel-wise fitting methods for deriving the six unique unknowns in a diffusion tensor using data-driven supervised deep learning. DeepDTI maps the input non-diffusion-weighted (b ​= ​0) image and six DWI volumes sampled along optimized diffusion-encoding directions, along with T1-weighted and T2-weighted image volumes, to the residuals between the input and high-quality output b = 0 image and DWI volumes using a 10-layer three-dimensional convolutional neural network (CNN). The inputs and outputs of DeepDTI are uniquely formulated, which not only enables residual learning to boost CNN performance but also enables tensor fitting of resultant high-quality DWIs to generate orientational DTI metrics for tractography. The very deep CNN used by DeepDTI leverages the redundancy in local and non-local spatial information and across diffusion-encoding directions and image contrasts in the data. The performance of DeepDTI was systematically quantified in terms of the quality of the output images, DTI metrics, DTI-based tractography and tract-specific analysis results. We demonstrate rotationally-invariant and robust estimation of DTI metrics from DeepDTI that are comparable to those obtained with two b ​= ​0 images and 21 DWIs for the primary eigenvector derived from DTI and two b ​= ​0 images and 26–30 DWIs for various scalar metrics derived from DTI, achieving 3.3–4.6 × ​acceleration, and twice as good as those of a state-of-the-art denoising algorithm at the group level. The twenty major white-matter tracts can be accurately identified from the tractography of DeepDTI results. The mean distance between the core of the major white-matter tracts identified from DeepDTI results and those from the ground-truth results using 18 ​b ​= ​0 images and 90 DWIs measures around 1–1.5 ​mm. DeepDTI leverages domain knowledge of diffusion MRI physics and power of deep learning to render DTI, DTI-based tractography, major white-matter tracts identification and tract-specific analysis more feasible for a wider range of neuroscientific and clinical studies.

Marine protected areas (MPAs) across various countries have contributed to safeguarding coastal and marine environments. Despite these efforts, marine non-native species (NNS) continue to threaten biodiversity and ecosystems, even within MPAs. Currently, there is a lack of comprehensive studies on the inventories, distribution patterns, and effect factors of NNS within MPAs. Here we show a database containing over 15,000 occurrence records of 2714 marine NNS across 16,401 national or regional MPAs worldwide. To identify the primary mechanisms driving the occurrence of NNS, we utilize model selection with proxies representing colonization pressure, environmental variables, and MPA characteristics. Among the environmental predictors analyzed, sea surface temperature emerged as the sole factor strongly associated with NNS richness. Higher sea surface temperatures are linked to increased NNS richness, aligning with global marine biodiversity trends. Furthermore, human activities help species overcome geographical barriers and migration constraints. Consequently, this influences the distribution patterns of marine introduced species and associated environmental factors. As global climate change continues to alter sea temperatures, it is crucial to protect marine regions that are increasingly vulnerable to intense human activities and biological invasions.

Rapid urbanization is one of the major causes of the degradation of ecosystem services (ESs), which poses serious threats to the ecological security of cities. Assessing ESs and their trade-offs and synergies is crucial for enhancing integrated ESs and promoting coordinated economic-social-ecological development in highly urbanized regions. This study used a combined GeoSOS-FLUS-InVEST model to simulate the trends and spatial distribution of five essential ESs (carbon sequestration, habitat quality, water conservation, soil retention and food supply) and explored their trade-offs and synergies under three future scenarios: natural development scenario, policy optimization scenario, and sustainable development scenario. Results showed that: (1) Carbon sequestration, habitat quality, water conservation, and soil retention services exhibit a declining trend from land to sea, while food supply service is closely linked to land use types; (2) The integrated ESs of all three future scenarios decreased compared to 2020. Among them, the integrated ESs under the sustainable development scenario surpassed those of the policy optimization scenario and the natural development scenario; (3) In Xiamen, the ESs were predominantly characterized by synergy, with trade-off relationship occurring sporadically in certain parts of the city. The sustainable development scenario exhibits the highest number of synergy units and the fewest trade-off units. The findings of this study provide valuable insights into managing the inherent contradictions between ecological conservation and human development in other rapidly urbanizing regions with similar challenges.

Summary: Fanconi anemia (FA) is characterized by congenital abnormalities, bone marrow failure, and cancer susceptibility. The central FA protein complex FANCI/FANCD2 (ID2) is activated by monoubiquitination and recruits DNA repair proteins for interstrand crosslink (ICL) repair and replication fork protection. Defects in the FA pathway lead to R-loop accumulation, which contributes to genomic instability. Here, we report that the splicing factor SRSF1 and FANCD2 interact physically and act together to suppress R-loop formation via mRNA export regulation. We show that SRSF1 stimulates FANCD2 monoubiquitination in an RNA-dependent fashion. In turn, FANCD2 monoubiquitination proves crucial for the assembly of the SRSF1-NXF1 nuclear export complex and mRNA export. Importantly, several SRSF1 cancer-associated mutants fail to interact with FANCD2, leading to inefficient FANCD2 monoubiquitination, decreased mRNA export, and R-loop accumulation. We propose a model wherein SRSF1 and FANCD2 interaction links DNA damage response to the avoidance of pathogenic R-loops via regulation of mRNA export.

Recent research has highlighted a correlation between exposure to ambient fine particulate matter (PM2.5) and the development of systemic insulin resistance (IR) along with an elevated risk of diabetes. Ceramide has emerged as one of the pathogenic mechanisms contributing to IR. The inhibition of acid sphingomyelinase (ASMase) activity by desipramine (DES) has been shown to effectively reduce ceramide levels. In the present study, 24 female C57BL/6 N mice were randomized into one of the four groups: the filtered air exposure (FA) group, the concentrated PM2.5 exposure (PM) group, the concentrated PM2.5 treated with low-dose DES (DL) group, and the concentrated PM2.5 treated with high-dose DES (DH) group. The PM, DL and DH groups were exposed to PM2.5 for an 8-week period within a whole-body exposure system. The study encompassed extensive examinations of glucose homeostasis, liver lipid profile, ceramide pathway, and insulin signaling pathway. Our results demonstrated that PM2.5 exposure caused impaired glucose tolerance, elevated ceramide levels, increased phosphorylation PP2A, reduced Akt phosphorylation, and hindered GLUT2 expression. Remarkably, DES administration mitigated PM2.5-induced IR by effectively lowering ceramide levels. In conclusion, the reduction of ceramide levels by DES may be a promising therapeutic strategy for coping PM2.5-induced IR.

Seasonal thermal stratification is a common environmental phenomenon in reservoir water bodies and an important research topic for deep water reservoirs. A thermally stratified reservoir is an ideal system for investigating the interaction between factors affecting the environment and microorganism communities under spatial–temporal variation. However, few studies have focused on the effects of water stratification and mixing periods in microbial communities and nitrogen conversion. Therefore, using metagenomic sequencing and quantitative polymerase chain reaction, we investigated the microbial diversity and function in the Xin'anjiang Reservoir during water stratification and mixing period. Principal component analysis indicated that the bacterial communities were mostly affected by water stratification, mainly at 10-m depths, whereas the archaea community was influenced by the entire water profile. The predominant archaeal phyla changed from Candidatus_Woesearchaeota and Euryarchaeota to Thaumarchaeota with the increasing water depth during water stratification. The stratified variations of the dominant archaeal phyla strongly reflected the seasonal changes and vertical gradient in water temperature, dissolved oxygen, and pH. Linear regression analysis indicated that variations in microbial composition altered the overall functional attributes of the communities, especially in the archaeal community. Regarding nitrogen metabolism across the whole reservoir, the number of nitrification and denitrification genes dropped in the same direction as the river flow in spring and summer, while the opposite trend was observed in autumn and winter. The functional genes of the water profiles in the transitional and lacustrine zones varied considerably except in winter. Additionally, the copies of nitrification-related genes were more during the stratification stage than during the mixing stage, whereas copies of denitrification-related genes showed the opposite trend. Overall, this study provides unique insights regarding the effects of seasonal stratification on the distribution and function of microorganisms in large-deep reservoirs, which should be considered when establishing guidelines for reservoirs management.

Alterations in aboveground plant litter inputs due to global climate change can strongly change soil nitrogen (N) cycling, which will influence soil processes and functions. However, a comprehensive evaluation for the effects of altered litter inputs on soil N cycling is not available. We evaluated these effects using a global meta-analysis based on 1829 observations from 119 studies across different ecosystems including forests, shrublands and grasslands. Results showed that litter addition significantly increased soil N pools including total N (TN), dissolved organic N (DON), ammonium (NH4+), nitrate (NO3–) and microbial biomass N (MBN) by 4–––24 %, while litter removal decreased them by 10–––42 %. High initial soil TN pool weakened the positive effect of litter addition on soil TN. Moreover, litter addition significantly increased soil net N mineralization (+19 %), DON leaching (+56 %) and nitrous oxide (N2O) emission (+27 %), whereas litter removal reduced net N mineralization (-10 %) and increased NO3– leaching (+51 %). The response of soil net N mineralization to litter addition was stronger in broadleaved forests than that in coniferous forests, and negatively correlated with mean annual temperature and precipitation. The responses of soil TN, NH4+, NO3–, MBN and N2O emission to litter manipulation increased with increasing litter input rates. Therefore, altered litter inputs had strong effects on soil N cycling and these effects were regulated by soil N status, ecosystems, climates and experimental conditions. Our results provide insights into understanding how altered plant litter input affects soil N cycling and help better assess the soil processes under global climate change.

Di-(2-Ethylhexyl) phthalate (DEHP) is widely used as an additive in many plastic products. Studies have revealed that DEHP persistent exposure can affect embryonic development and lead to adverse female reproductive disorders. The establishment of pregnancy involves extensive changes in the endometrial tissue, including massive extracellular matrix (ECM) remodeling. Decidualization of the endometrium provides a suitable environment for subsequent growth by causing changes in the morphology of the uterine stromal cells, is a key process in human pregnancy. Resveratrol (RSV) is a natural polyphenolic plant antitoxin with a wide range of pharmacological effects. Growing evidence indicates that RSV has therapeutic effects on certain female reproductive disorders. In this study, the effect of DEHP on cell viability was investigated by cell proliferation assay. Cell decidualization was induced in vitro, and the downregulation of molecules associated with decidualization was confirmed through quantitative real-time PCR and western blot analysis. Immunofluorescence analysis revealed alteration in cell morphology, and found that administration of DEHP sufficiently induced ERα entry into the nucleus. The effect of DEHP on cells was fully verified by RNA-seq analysis. Interestingly, an upregulation of decidual molecules was observed after rescue with RSV, which was confirmed by RNA-seq transcriptome analysis and quantitative real-time PCR assay. Additionally, the expression of ECM remodeling-related genes was significantly restored by RSV administration. The study revealed the potential mechanisms of DEHP-induced decidualization defects and the functional relieving roles of RSV while providing a perspective therapeutic candidate for alleviating the DEHP-induced deficiencies in decidualization.

Aims: To compared the amniotic fluid and vaginal microbiota of pregnant women, who developed gestational diabetes mellitus to those who did not, and explored if any differences exist in the composition and functional genes of their amniotic fluid and vaginal microbiota. Methods: We compared the amniotic fluid and vaginal microbiota of five GDM patients and five non-GDM pregnant women in the third trimester of pregnancy by using metagenomics, and analyzed the characteristics, functions, and differences between two groups. Results: The analysis of the amniotic fluid showed significant differences in genus and species. In contrast, there was no significant difference in vaginal microbial community structure between two groups. The alpha diversity in the GDM group was higher than the control, but the difference was not statistically significant. There was a statistically significant difference in the species-level beta-diversity measured by Bray–Curtis distance of the amniotic fluid communities between two groups, while no significant differences were observed in the vaginal microbiota. Regarding the functions, we observed that the microbial communities of the amniotic fluid and vaginal secretions were involved in the regulation of a variety of host metabolic pathways, including carbohydrate metabolism, membrane transport, energy, amino acid metabolism, nucleotide metabolism, etc. No significant differences were observed between two groups, but different sites exist. Conclusion: The amniotic fluid of this study was discovered to have a heterogeneous, albeit small in number, community of microorganisms.Our research suggests that gestational diabetes has a very limited impact on the amniotic fluid and vaginal microbiome. The composition and the functions of the microbiota at different sites are different.

Although aroma is one of the most essential factors determining the quality of Fu brick tea (FBT), the aroma profiles of FBTs from different manufacturing areas are rarely investigated. The aroma profiles of FBTs manufactured in five typical provinces of China were comprehensively analyzed on the basis of headspace gas chromatography–ion mobility spectrometry (HS–GC–IMS), headspace solid-phase microextraction gas chromatography–mass spectrometry (HS–SPME–GC–MS), sensory evaluation, odor activity value (OAV), and relative odor activity value (ROAV). HS–GC–IMS and HS–SPME–GC–MS identified 63 and 93 volatile organic compounds (VOCs), respectively. Multivariate statistical analysis indicated that the FBTs from different production regions had remarkably varied aromas. HS–SPME–GC–MS revealed that 27 VOCs (OAV >1) contributed to the overall aroma of the samples, of which 15 key differential compounds can effectively distinguish the aroma profiles of different FBTs. FBT from Shaanxi manifested a strong floral and fruity aroma; that from Hunan had a floral, grassy, and pine-woody aroma; that from Guizhou presented a grassy and herbal aroma; that from Guangxi exhibited a sweet, floral, and minty aroma; and that from Zhejiang possessed various fruit flavors and floral fragrance. OAV analysis identified the biomarkers responsible for the variation in the aroma characteristics of diverse FBTs. These biomarkers included linalool, 6-methyl-5-hepten-2-one, α-ionone, hexanal, and ethyl hexanoate. Sensory evaluation demonstrated that the infusion color and aroma of FBT samples from different provinces also greatly varied. Network correlation analysis revealed that Aspergillus and Eurotium were the crucial microorganisms for the metabolism and formation of VOCs. These findings provide new insight into the VOCs and fragrance features of FBTs produced in different regions of China.

Sphagnum plants are sensitive to nitrogen deposition changes. However, previous literature is inconclusive on the response of Sphagnum to nitrogen deposition, little is known about the nitrogen critical load for Sphagnum growth, and the factors that influence the response of Sphagnum plant growth to nitrogen deposition are still unclear. Therefore, we conducted a meta-analysis of 60 experiments with different gradients of nitrogen application to Sphagnum plants in 14 countries around the world, and the results showed that excess nitrogen reduces Sphagnum production. Mixed-effects models were established to analyze the nutrient, environmental and climatic factors that may affect the response of Sphagnum plants to nitrogen deposition, and the results indicated that the water table and cumulative nitrogen were the most important influencing factors. We compared AICc values to select an optimal model set. We used a meta-analysis combined with general additive models (GAMs) to estimate the nitrogen critical load for Sphagnum, and we concluded that this load in the mid- to high-latitude region is in the range of 5–40 kg ha−1yr−1.

Boreal peatlands, of which Sphagnum bogs are one of the main types, play essential roles in the terrestrial soil carbon pool. Vegetation phenology is a sensitive indicator that reveals the underlying processes as well as responses to climate change, while currently there remain knowledge gaps in exploring and monitoring the long-term bog vegetation phenology due to insufficient remote sensing application experiences. In this study, we investigated three remotely sensed vegetation phenological parameters, the start of growing season (SOS), the end of growing season (EOS), and the length of growing season (LOS) in two bogs located in norther China by using double-logistic reconstructed MOD13Q1-EVI from 2001 to 2018, which were evaluated by the flux phenology. Also combing with meteorological data to detect interactions between vegetation phenology and climate change. The results showed that remotely sensed EOS had 8-day time lags with flux phenological date, while that outperformed SOS. Bog vegetation generally with a life pattern of SOS at the 108th day of year (doy) and EOS at the 328th doy, though the life cycle of individual vegetation groups varies among different vegetation communities. There was no significant delayed (or extended) trend in each phenological features in bogs. Precipitation and minimum temperature (monthly and annual) were the driving forces for bog vegetation growth (R2 > 0.9, P

Objective: In this study, we aimed to examine the changes in the composition of vaginal and gut microbiota during the third trimester of pregnancy among women who delivered preterm. To further understand the relationship of these changes to preterm birth, we analyzed the microecology of vaginal and gut microbiota in mothers, as well as oral and gut microbiota in their newborns, and then compared the microecological characteristics of the microbiome at different body sites between the mothers and their newborns, as well as between the mothers and between the newborns from different groups. Methods: In total, 26 women who delivered at Zhujiang Hospital, Southern Medical University (China) from July 2020 to January 2021 were categorized into the preterm and term groups. A blank swab and laboratory air and water samples were collected as part of the control group. We collected maternal vaginal and rectal samples, as well as neonatal oral and rectal samples. Total DNA from different parts of the swabs was extracted and sequenced using the 16s rRNA technique. Then, the data was analyzed using bioinformatics and statistical analysis. Results: The abundance and alpha diversity of vaginal microbiota in the preterm group was found to be higher, but the difference was not statistically significant. There were significant differences in beta diversity of vaginal microbiota between the two groups (p ​