Association between plasma metal exposure and health span in very elderly adults: a prospective cohort study with mixture statistical approach.

BACKGROUND: Metals have been linked to a diverse spectrum of age-related diseases; however, the effects of metal exposure on health span remains largely unknown. This cohort study aims to determine the association between plasma metal and health span in elder adults aged ≥ 90 years. METHODS: The plasma concentrations of seven metals were measured at baseline in 300 elder adults. The end of the health span (EHS) was identified as the occurrence of one of eight major morbidities or mortality events. We used Cox regression to assess hazard ratios (HR). The combined effects of multiple metal mixtures were estimated using grouped-weighted quantile sum (GWQS), quantile g-computation (Q-gcomp), and Bayesian kernel machine regression (BKMR) methods. RESULTS: The estimated HR for EHS with an inter-quartile range (IQR) increment for selenium (Se) was 0.826 (95% confidence interval [CI]: 0.737-0.926); magnesium (Mg), 0.806 (95% CI: 0.691-0.941); iron (Fe), 0.756 (95% CI: 0.623-0.917), and copper (Cu), 0.856 (95% CI: 0.750-0.976). The P for trend of Se, Mg, and Fe were all < 0.05. In the mixture analyses, Q-gcomp showed a negative correlation with EHS (P = 0.904), with the sum of the negative coefficients being -0.211. CONCLUSION: Higher plasma Se, Mg, and Fe reduced the risk of premature end of health span, suggesting that essential metal elements played a role in health maintenance in elder adults.

SurfPro-NN: A 3D point cloud neural network for the scoring of protein-protein docking models based on surfaces features and protein language models.

Protein-protein interactions (PPI) play a crucial role in numerous key biological processes, and the structure of protein complexes provides valuable clues for in-depth exploration of molecular-level biological processes. Protein-protein docking technology is widely used to simulate the spatial structure of proteins. However, there are still challenges in selecting candidate decoys that closely resemble the native structure from protein-protein docking simulations. In this study, we introduce a docking evaluation method based on three-dimensional point cloud neural networks named SurfPro-NN, which represents protein structures as point clouds and learns interaction information from protein interfaces by applying a point cloud neural network. With the continuous advancement of deep learning in the field of biology, a series of knowledge-rich pre-trained models have emerged. We incorporate protein surface representation models and language models into our approach, greatly enhancing feature representation capabilities and achieving superior performance in protein docking model scoring tasks. Through comprehensive testing on public datasets, we find that our method outperforms state-of-the-art deep learning approaches in protein-protein docking model scoring. Not only does it significantly improve performance, but it also greatly accelerates training speed. This study demonstrates the potential of our approach in addressing protein interaction assessment problems, providing strong support for future research and applications in the field of biology.

Association and mediation between educational attainment and respiratory diseases: a Mendelian randomization study.

BACKGROUND: Respiratory diseases are a major health burden, and educational inequalities may influence disease prevalence. We aim to evaluate the causal link between educational attainment and respiratory disease, and to determine the mediating influence of several known modifiable risk factors. METHODS: We conducted a two-step, two-sample Mendelian randomization (MR) analysis using summary statistics from genome-wide association studies (GWAS) and single nucleotide polymorphisms (SNPs) as instrumental variables for educational attainment and respiratory diseases. Additionally, we performed a multivariable MR analysis to estimate the direct causal effect of each exposure variable included in the analysis on the outcome, conditional on the other exposure variables included in the model. The mediating roles of body mass index (BMI), physical activity, and smoking were also assessed. FINDINGS: MR analyses provide evidence of genetically predicted educational attainment on the risk of FEV1 (ß = 0.10, 95% CI 0.06, 0.14), FVC (ß = 0.12, 95% CI 0.07, 0.16), FEV1/FVC (ß = - 0.005, 95% CI - 0.05, 0.04), lung cancer (OR = 0.54, 95% CI 0.45, 0.65) and asthma (OR = 0.86, 95% CI 0.78, 0.94). Multivariable MR dicated the effect of educational attainment on FEV1 (ß = 0.10, 95% CI 0.04, 0.16), FVC (ß = 0.07, 95% CI 0.01, 0.12), FEV1/FVC (ß = 0.07, 95% CI 0.01, 0.01), lung cancer (OR = 0.55, 95% CI 0.42, 0.71) and asthma (OR = 0.88, 95% CI 0.78, 0.99) persisted after adjusting BMI and cigarettes per day. Of the 23 potential risk factors, BMI, smoking may partially mediate the relationship between education and lung disease. CONCLUSION: High levels of educational attainment have a potential causal protective effect on respiratory diseases. Reducing smoking and adiposity may be a target for the prevention of respiratory diseases attributable to low educational attainment.

Molecular mechanisms of Na+-driven bile acid transport in human NTCP.

Human Na+ taurocholate co-transporting protein (hNTCP) is a key bile salt transporter to maintain enterohepatic circulation and is responsible for the recognition of hepatitis B and D viruses. Despite landmark cryoelectron microscopy studies revealing open-pore and inward-facing states of hNTCP stabilized by antibodies, the transport mechanism remains largely unknown. To address this knowledge gap, we used molecular dynamics and enhanced sampling metadynamics simulations to elucidate the intrinsic mechanism of hNTCP-mediated taurocholate acid (TCA) transport driven by Na+ binding. We uncovered three TCA-binding modes, including one that closely matched the limited cryoelectron microscopy density observed in the open-pore hNTCP. We also captured several key hNTCP conformations in the substrate transport cycle, particularly including an outward-facing, substrate-bound state. Furthermore, we provided thermodynamic evidence supporting that changes in the Na+-binding state drive the TCA transport by exploiting the amphiphilic nature of the substrate and modulating the protein environment, thereby enabling the TCA molecule to flip through. Understanding these mechanistic details of Na+-driven bile acid transport may aid in the development of hNTCP-targeted therapies for liver diseases.

Self-Enhancement of Perfluorinated Sulfonic Acid Proton Exchange Membrane with Its Own Nanofibers.

High-performance proton exchange membrane (PEM) is crucial for the proton exchange membrane fuel cell (PEMFC). Herein, a novel "self-enhanced" PEM is fabricated for the first time, which is composed of perfluorinated sulfonic acid (PFSA) resin and its own nanofibers as reinforcement. With this strategy, the interfacial compatibility issue of conventional fiber-reinforced membranes is fully addressed and up to 80 wt% loading of PFSA nanofibers can be incorporated. Furthermore, on account of chain orientation within the PFSA nanofiber, single fiber exhibits super-high conductivity of 1.45 S cm-1, leading to state-of-the-art proton conductivity (1.1 S cm-1) of the as-prepared "self-enhanced" PEM so far, which is an order of magnitude increase compared with the bulk PFSA membrane (0.29 S cm-1). It surpasses any commercial PEM including the popular GORE-SELECT and Nafion HP membranes and is the only PEM with conductivity at 100 S cm-1 level. In addition, the mechanical strength and swelling ratio of membranes are both substantially improved simultaneously. Based on the high-performance "self-enhanced" PEM, high peak power densities of up to 3.6 W cm-2 and 1.7 W cm-2 are achieved in H2-O2 and H2-Air fuel cells, respectively. This strategy can be applied in any polymeric electrolyte membrane.

Tpgen: a language model for stable protein design with a specific topology structure.

BACKGROUND: Natural proteins occupy a small portion of the protein sequence space, whereas artificial proteins can explore a wider range of possibilities within the sequence space. However, specific requirements may not be met when generating sequences blindly. Research indicates that small proteins have notable advantages, including high stability, accurate resolution prediction, and facile specificity modification. RESULTS: This study involves the construction of a neural network model named TopoProGenerator(TPGen) using a transformer decoder. The model is trained with sequences consisting of a maximum of 65 amino acids. The training process of TopoProGenerator incorporates reinforcement learning and adversarial learning, for fine-tuning. Additionally, it encompasses a stability predictive model trained with a dataset comprising over 200,000 sequences. The results demonstrate that TopoProGenerator is capable of designing stable small protein sequences with specified topology structures. CONCLUSION: TPGen has the ability to generate protein sequences that fold into the specified topology, and the pretraining and fine-tuning methods proposed in this study can serve as a framework for designing various types of proteins.

Mechanical Metamaterials for Handwritten Digits Recognition.

The increasing needs for new types of computing lie in the requirements in harsh environments. In this study, the successful development of a non-electrical neural network is presented that functions based on mechanical computing. By overcoming the challenges of low mechanical signal transmission efficiency and intricate layout design methodologies, a mechanical neural network based on bistable kirigami-based mechanical metamaterials have designed. In preliminary tests, the system exhibits high reliability in recognizing handwritten digits and proves operable in low-temperature environments. This work paves the way for a new, alternative computing system with broad applications in areas where electricity is not accessible. By integrating with the traditional electronic computers, the present system lays the foundation for a more diversified form of computing.

Epidemiological characteristics of HIV transmission in southeastern China from 2015 to 2020 based on HIV molecular network.

Objective: HIV/AIDS remains a global public health problem, and understanding the structure of social networks of people living with HIV/AIDS is of great importance to unravel HIV transmission, propose precision control and reduce new infections. This study aimed to investigate the epidemiological characteristics of HIV transmission in Fujian province, southeastern China from 2015 to 2020 based on HIV molecular network. Methods: Newly diagnosed, treatment-naive HIV/AIDS patients were randomly sampled from Fujian province in 2015 and 2020. Plasma was sampled for in-house genotyping resistance test, and HIV molecular network was created using the HIV-TRACE tool. Factors affecting the inclusion of variables in the HIV molecular network were identified using univariate and multivariate logistic regression analyses. Results: A total of 1,714 eligible cases were finally recruited, including 806 cases in 2015 and 908 cases in 2020. The dominant HIV subtypes were CRF01_AE (41.7%) and CRF07_BC (38.3%) in 2015 and CRF07_BC (53. 3%) and CRF01_AE (29.1%) in 2020, and the prevalence of HIV drug resistance was 4.2% in 2015 and 5.3% in 2020. Sequences of CRF07_BC formed the largest HIV-1 transmission cluster at a genetic distance threshold of both 1.5 and 0.5%. Univariate and multivariate logistic regression analyses showed that ages of under 20 years and over 60 years, CRF07_BC subtype, Han ethnicity, sampling in 2015, absence of HIV drug resistance, married with spouse, sampling from three cities of Jinjiang, Nanping and Quanzhou resulted in higher proportions of sequences included in the HIV transmission molecular network at a genetic distance threshold of 1.5% (p < 0.05). Conclusion: Our findings unravel the HIV molecular transmission network of newly diagnosed HIV/AIDS patients in Fujian province, southeastern China, which facilitates the understanding of HIV transmission patterns in the province.

A 2-step prediction model for diagnosis of germinomas in the pineal region.

Background: Germinomas are sensitive to radiation and chemotherapy, and their management distinctly differs from other kinds of pineal region tumors. The aim of this study was to construct a prediction model based on clinical features and preoperative magnetic resonance (MR) manifestations to achieve noninvasive diagnosis of germinomas in pineal region. Methods: A total of 126 patients with pineal region tumors were enrolled, including 36 germinomas, 53 nongerminomatous germ cell tumors (NGGCTs), and 37 pineal parenchymal tumors (PPTs). They were divided into a training cohort (n = 90) and a validation cohort (n = 36). Features were extracted from clinical records and conventional MR images. Multivariate analysis was performed to screen for independent predictors to differentiate germ cell tumors (GCTs) and PPTs, germinomas, and NGGCTs, respectively. From this, a 2-step nomogram model was established, with model 1 for discriminating GCTs from PPTs and model 2 for identifying germinomas in GCTs. The model was tested in a validation cohort. Results: Both model 1 and model 2 yielded good predictive efficacy, with c-indexes of 0.967 and 0.896 for the diagnosis of GCT and germinoma, respectively. Calibration curve, decision curve, and clinical impact curve analysis further confirmed their predictive accuracy and clinical usefulness. The validation cohort achieved areas under the receiver operating curves of 0.885 and 0.926, respectively. Conclusions: The 2-step model in this study can noninvasively differentiate GCTs from PPTs and further identify germinomas, thus holding potential to facilitate treatment decision-making for pineal region tumors.

Physics-supervised deep learning-based optimization (PSDLO) with accuracy and efficiency.

Identifying efficient and accurate optimization algorithms is a long-desired goal for the scientific community. At present, a combination of evolutionary and deep-learning methods is widely used for optimization. In this paper, we demonstrate three cases involving different physics and conclude that no matter how accurate a deep-learning model is for a single, specific problem, a simple combination of evolutionary and deep-learning methods cannot achieve the desired optimization because of the intrinsic nature of the evolutionary method. We begin by using a physics-supervised deep-learning optimization algorithm (PSDLO) to supervise the results from the deep-learning model. We then intervene in the evolutionary process to eventually achieve simultaneous accuracy and efficiency. PSDLO is successfully demonstrated using both sufficient and insufficient datasets. PSDLO offers a perspective for solving optimization problems and can tackle complex science and engineering problems having many features. This approach to optimization algorithms holds tremendous potential for application in real-world engineering domains.

Differences in epidemiological and clinical features between adult and pediatric tracheobronchial tuberculosis patients in Southwest China.

Background: Tracheobronchial tuberculosis (TBTB) is a common form of extrapulmonary tuberculosis that affects the tracheobronchial tree. However, the mechanism has not been fully elucidated. Comparisons of clinical characteristics in various age groups can aid in the understanding of TBTB. Methods: This retrospective study was conducted at the Public Health Clinical Center of Chengdu between July 2017 and December 2021, including adults and children with TBTB. Clinical data were extracted from medical records. T/T' test, Mann-Whitney U test, Chi-square test, or Fisher's exact test were used in this study. Results: This study enrolled 347 patients with TBTB (175 adults and 172 children). Adult females were more susceptible to TBTB, whereas gender-based differences were not observed in children. Children had a higher occurrence of irritant dry cough and fever, and acute hematogenous disseminated PTB, and specific types of EPTB, but a shorter interval before diagnosis, and lower diagnostic yields compared to adults (P < 0.05). Adults presented more extensive lung lesions and cavitations as compared to children. Granulation hyperplasia and lymph fistula were more frequently observed in children, as well as airway stenosis, but less severe. Conclusions: The study revealed important variations exist in multiple respects between adults and children with TBTB.

Association of ambient PM10 and PM2.5 with coronary stenosis measured using selective coronary angiography.

BACKGROUND: Long-term ambient particulate matter (PM) exposure exerts detrimental effects on cardiovascular health. Evidence on the relation of chronically exposed ambient PM10 and PM2.5 with coronary stenosis remains lacking. Our aim was to investigate the association of PM10 and PM2.5 with coronary stenosis in patients undergoing coronary angiography. METHODS: We performed a retrospective cohort study consisting of 7513 individuals who underwent coronary angiography in Fujian Province, China, from January 2019 to December 2021. We calculated a modified Gensini score (GS) to represent the degree of stenosis in coronary arteries by selective coronary angiography. We fitted linear regressions and logistic models to assess the association of PM10 and PM2.5 with coronary stenosis. We employed restricted cubic splines to describe the exposure-response curves. We performed mediation analyses to assess the potential mediators. RESULTS: Long-term ambient PM10 and PM2.5 (prior three years average) exposure was significantly associated with the GS, with a breakpoint concentration of 47.5 µg/m3 and 25.8 µg/m3 for PM10 and PM2.5, respectively, above which we found a linear positive exposure-response relationship of ambient PM with GS. Each 10 µg /m3 increase in PM10 exposure (ß: 4.81, 95 % CI: 0.44-9.19) and PM2.5 exposure [ß: 10.50, 95 % CI: 3.14-17.86] were positively related to the GS. The adjusted odds ratio (OR) for each 10 µg/m3 increment in PM10 exposure on severe coronary stenosis was 1.33 (95 % CI: 1.04-1.76). Correspondingly, the adjusted OR for PM2.5 was 1.87 (95 % CI: 1.24-2.99). The mediation analysis indicated that the effect of PM10 on coronary stenosis may be partially mediated through total cholesterol, low-density lipoprotein cholesterol, apolipoprotein B, serum creatinine and blood urea nitrogen, and the effect of PM2.5 may be mediated in part by hemoglobin A1c. CONCLUSION: Our study provides the first evidence that chronic ambient PM10 and PM2.5 exposure was associated with coronary stenosis assessed by GS in patients with suspected coronary artery disease and reveals its potential mediators.

Xuebijing injection protects sepsis induced myocardial injury by mediating TLR4/NF-κB/IKKα and JAK2/STAT3 signaling pathways.

OBJECTIVE: Compelling evidence has demonstrated that Xuebijing (XBJ) exerted protective effects against SIMI. The aims of this study were to investigate whether TLR4/IKKα-mediated NF-κB and JAK2/STAT3 pathways were involved in XBJ's cardio-protection during sepsis and the mechanisms. METHODS: In this study, rats were randomly assigned to three groups: Sham group; CLP group; XBJ group. Rats were treated with XBJ or sanitary saline after CLP. Echocardiography, myocardial enzymes and HE were used to detect cardiac function. IL-1ß, IL-6 and TNF-α in serum were measured using ELISA kits. Cardiomyocyte apoptosis were tested by TUNEL staining. The protein levels of Bax, Bcl-2, Bcl-xl, Cleaved-Caspase 3, Cleaved-Caspase 9, Cleaved-PARP, TLR4, p-NF-κB, p-IKKα, p-JAK2 and p-STAT3 in the myocardium were assayed by western blotting. And finally, immunofluorescence was used to assess the level of p-JAK2 and p-STAT3 in heart tissue. RESULTS: The results of echocardiography, myocardial enzyme and HE test showed that XBJ could significantly improve SIMI. The IL-1ß, IL-6 and TNF-α levels in the serum were markedly lower in the XBJ group than in the CLP group (p<0.05). TUNEL staining's results showed that XBJ ameliorated CLP-induced cardiomyocyte apoptosis. Meanwhile, XBJ downregulated the protein levels of Bax, Cleaved-Caspase 3, Cleaved-Caspase 9, Cleaved-PARP, TLR4, p-NF-κB, p-IKKα, p-JAK2 and p-STAT3, as well as upregulated the protein levels of Bcl-2, Bcl-xl (p <0.05). CONCLUSIONS: In here, we observed that XBJ's cardioprotective advantages may be attributable to its ability to suppress inflammation and apoptosis via inhibiting the TLR4/ IKKα-mediated NF-κB and JAK2/STAT3 pathways during sepsis.

Self-Assembly and Photothermal Conversion of MetallaRussian Doll and Metalla[2]catenanes Induced via Multiple Stacking Interactions.

A variety of organometallic supramolecular architectures have been constructed over the past decades and their properties were also explored via different strategies. However, the synthesis of metalla-Russian doll is still a fascinating challenge. Herein, a series of new coordination supramolecular complexes, including a metalla-Russian doll, metalla[2]catenanes, and metallarectangles, were synthesized by using meticulously selected Cp*Rh (Cp* = η5-C5Me5) building units (E1, E2, and E3) and three rigid anthracylpyridine ligands (L1, L2, and L3) via a self-assembly strategy. While the combination of the short ligand L1 and E1 or E2 generated two metallarectangles, the longer ligand L2 containing an alkynyl group resulted in two new [2]catenanes, most likely due to which the strong electron-donating effect of alkynyl groups causes self-accumulation. Interestingly, an unusual Russian doll assembly was obtained through the reaction of L3 and E3 based on sextuple π···π stacking interactions. Furthermore, the dynamic structural conversion between [2]catenanes and the corresponding metallarectangles could be observed through concentration-, solvent-, and guest-induced effects. The [2]catenane complexes 4b displayed efficient photothermal conversion efficiency in solution (20.2%), in comparison with other organometallic macrocycles. We believe that π···π stacking interactions generate active nonradiative pathways and promote radiative photodeactivation pathways. This study proves the versatility of half-sandwich building units, not only to build complicated supramolecular topologies but also in effective functional materials for various appealing applications.

Effect of Direct Steam Injection and Instantaneous Ultra-High-Temperature (DSI-IUHT) Sterilization on the Physicochemical Quality and Volatile Flavor Components of Milk.

The effects of variations in the heat treatment process of milk on its quality and flavor are inevitable. This study investigated the effect of direct steam injection and instantaneous ultra-high-temperature (DSI-IUHT, 143 °C, 1-2 s) sterilization on the physicochemical properties, whey protein denaturation (WPD) rate, and volatile compounds (VCs) of milk. The experiment compared raw milk as a control with high-temperature short-time (HTST, 75 °C 15 s and 85 °C 15 s) pasteurization and indirect ultra-high-temperature (IND-UHT, 143 °C, 3-4 s) sterilization. The results showed no significant differences (p > 0.05) in physical stability between milk samples with different heat treatments. The DSI-IUHT and IND-UHT milks presented smaller particle sizes (p < 0.05) and more concentrated distributions than the HTST milk. The apparent viscosity of the DSI-IUHT milk was significantly higher than the other samples (p < 0.05) and is consistent with the microrheological results. The WPD of DSI-IUHT milk was 27.52% lower than that of IND-UHT milk. Solid-phase microextraction (SPME) and solvent-assisted flavor evaporation (SAFE) were combined with the WPD rates to analyze the VCs, which were positively correlated with ketones, acids, and esters and negatively associated with alcohols, heterocycles, sulfur, and aldehydes. The DSI-IUHT samples exhibited a higher similarity to raw and HTST milk than the IND-UHT samples. In summary, DSI-IUHT was more successful in preserving the milk's quality due to its milder sterilization conditions compared to IND-UHT. This study provides excellent reference data for the application of DSI-IUHT treatment in milk processing.

His bundle pacing versus left bundle branch pacing on ventricular function in atrial fibrillation patients referred for pacing: a prospective crossover comparison.

BACKGROUND: His bundle pacing (HBP) and left bundle branch pacing (LBBP) both provide physiologic pacing which maintain left ventricular synchrony. They both improve heart failure (HF) symptoms in atrial fibrillation (AF) patients. We aimed to assess the intra-patient comparison of ventricular function and remodeling as well as leads parameters corresponding to two pacing modalities in AF patients referred for pacing in intermediate term. METHODS: Uncontrolled tachycardia AF patients with both leads implantation successfully were randomized to either modality. Echocardiographic measurements, New York Heart Association (NYHA) classification, quality-of-life assessments and leads parameters were obtained at baseline and at each 6-month follow up. Left ventricular function including the left ventricular endo-systolic volume (LVESV), left ventricular ejection fraction (LVEF) and right ventricular (RV) function quantified by tricuspid annular plane systolic excursion (TAPSE) were all assessed. RESULTS: Consecutively twenty-eight patients implanted with both HBP and LBBP leads successfully were enrolled (69.1 ± 8.1 years, 53.6% male, LVEF 59.2% ± 13.7%). The LVESV was improved by both pacing modalities in all patients (n = 23) and the LVEF was improved in patients with baseline LVEF at less than 50% (n = 6). The TAPSE was improved by HBP but not LBBP (n = 23). CONCLUSION: In this crossover comparison between HBP and LBBP, LBBP was found to have an equivalent effect on LV function and remodeling but better and more stable parameters in AF patients with uncontrolled ventricular rates referred for atrioventricular node (AVN) ablation. HBP could be preferred in patients with reduced TAPSE at baseline rather than LBBP.

Predictive value of 3D ultrasound assessment of endometrial receptivity for PGD/PGS for transfer pregnancy outcome.

OBJECTIVE: To investigate the predictive value of three-dimensional ultrasound assessment of endometrial receptivity in PGD/PGS transplantation patients on pregnancy outcome. METHODS: 280 patients undergoing PGD/PGS transplantation were enrolled and divided into group A and group B according to the patients' pregnancy outcomes. The general conditions, endometrial receptivity indexes of the two groups were compared. Multifactorial logistic regression analysis was used to determine the factors influencing pregnancy outcome in PGD/PGS transplant patients. ROC curves were plotted to analyze the predictive value of 3D ultrasound parameters on pregnancy outcome. The results of the study were validated with patients who underwent FET transplantation, and the patients in the validation group were treated with the same 3D ultrasound examination method and treatment plan as the observation group. RESULTS: The differences in basic situations between two groups were not statistically significant (P > 0.05). The percentage of endometrial thickness, endometrial blood flow, and endometrial blood flow classification type II + II were higher in group A than in group B (P < 0.05). Multifactorial logistic regression analysis showed that endometrial thickness, endometrial blood flow and endometrial blood flow classification were influencing factors of pregnancy outcome in PGD/PGS patients. The sensitivity of predicting pregnancy outcome based on the results of transcatheter 3D ultrasound was 91.18%, the specificity was 82.35%, and the accuracy was 90.00%, which has a high predictive value. CONCLUSION: 3D ultrasound can predict pregnancy outcome by assessing the endometrial receptivity of PGD/PGS transplantation, in which endometrial thickness and endometrial blood flow have a good predictive value.

[Hydrochemical and Isotopic Evidence for Groundwater Conversion of Surface Water in Alpine Arid Areas: A Case Study of the Datong River Basin].

Global warming and regional extreme climates will lead to unbalanced rainfall, melting glaciers, and permafrost degradation in alpine and arid mountain plains, thereby changing the regional hydrological cycle. The relationship between surface water and groundwater conversion is one of the important scientific issues of hydrological cycle climate response in alpine arid areas. Taking the Datong River Basin at the southern foot of the Qilian Mountains as the study area, based on 119 sets of basic hydrochemical parameters and deuterium-oxygen isotope data, using multivariate statistical analysis and isotopic techniques, the hydrochemical characteristics of surface water and groundwater in the basin and their mutual transformation process were studied. The results showed that the surface water was HCO3-Mg·Ca type, which was mainly controlled by rock weathering, whereas the groundwater was HCO3-Mg·Ca type and Cl·SO4-Na type, which was controlled by rock weathering and evaporation concentration. There was a small amount of calcium and magnesium feldspar dissolved in the upstream groundwater, and the chemical components of the midstream groundwater were mainly the weathering and dissolution of carbonate rocks. The contribution rates of weathering filtration, anthropogenic activities, native sedimentary environment, alternating adsorption of cations, and other factors to the chemical components of surface water and groundwater in the study area were 39.1%, 15.0%, 12.6%, 13.8%, and 19.5%, respectively. The deuterium and oxygen isotope contents of Datong River water showed a trend of enrichment to depletion along the groundwater flow direction. The δD and δ18O isotope test results showed that the deuterium and oxygen isotope content in the Datong River along the groundwater flow showed a trend of enrichment to depletion. The upper and middle reaches of the Datong River were mainly recharged by atmospheric precipitation, whereas the lower reaches were affected by geological structure and influenced by hydrogeological conditions, which was mainly due to diving and spring water overflow to supply river water, as the discharge area of groundwater.