Multiview confocal super-resolution microscopy.

Confocal microscopy1 remains a major workhorse in biomedical optical microscopy owing to its reliability and flexibility in imaging various samples, but suffers from substantial point spread function anisotropy, diffraction-limited resolution, depth-dependent degradation in scattering samples and volumetric bleaching2. Here we address these problems, enhancing confocal microscopy performance from the sub-micrometre to millimetre spatial scale and the millisecond to hour temporal scale, improving both lateral and axial resolution more than twofold while simultaneously reducing phototoxicity. We achieve these gains using an integrated, four-pronged approach: (1) developing compact line scanners that enable sensitive, rapid, diffraction-limited imaging over large areas; (2) combining line-scanning with multiview imaging, developing reconstruction algorithms that improve resolution isotropy and recover signal otherwise lost to scattering; (3) adapting techniques from structured illumination microscopy, achieving super-resolution imaging in densely labelled, thick samples; (4) synergizing deep learning with these advances, further improving imaging speed, resolution and duration. We demonstrate these capabilities on more than 20 distinct fixed and live samples, including protein distributions in single cells; nuclei and developing neurons in Caenorhabditis elegans embryos, larvae and adults; myoblasts in imaginal disks of Drosophila wings; and mouse renal, oesophageal, cardiac and brain tissues.

Advances in Mechanism of HIV-1 Immune Reconstitution Failure: Understanding Lymphocyte Subpopulations and Interventions for Immunological Nonresponders.

In individuals diagnosed with AIDS, the primary method of sustained suppression of HIV-1 replication is antiretroviral therapy, which systematically increases CD4+ T cell levels and restores immune function. However, there is still a subset of 10-40% of people living with HIV who not only fail to reach normal CD4+ T cell counts but also experience severe immune dysfunction. These individuals are referred to as immunological nonresponders (INRs). INRs have a higher susceptibility to opportunistic infections and non-AIDS-related illnesses, resulting in increased morbidity and mortality rates. Therefore, it is crucial to gain new insights into the primary mechanisms of immune reconstitution failure to enable early and effective treatment for individuals at risk. This review provides an overview of the dynamics of key lymphocyte subpopulations, the main molecular mechanisms of INRs, clinical diagnosis, and intervention strategies during immune reconstitution failure, primarily from a multiomics perspective.

Postprocedural Anticoagulation After Primary Percutaneous Coronary Intervention for ST-Segment-Elevation Myocardial Infarction: A Multicenter, Randomized, Double-Blind Trial.

BACKGROUND: Postprocedural anticoagulation (PPA) is frequently administered after primary percutaneous coronary intervention in ST-segment-elevation myocardial infarction, although no conclusive data support this practice. METHODS: The RIGHT trial (Comparison of Anticoagulation Prolongation vs no Anticoagulation in STEMI Patients After Primary PCI) was an investigator-initiated, multicenter, randomized, double-blind, placebo-controlled, superiority trial conducted at 53 centers in China. Patients with ST-segment-elevation myocardial infarction undergoing primary percutaneous coronary intervention were randomly assigned by center to receive low-dose PPA or matching placebo for at least 48 hours. Before trial initiation, each center selected 1 of 3 PPA regimens (40 mg of enoxaparin once daily subcutaneously; 10 U·kg·h of unfractionated heparin intravenously, adjusted to maintain activated clotting time between 150 and 220 seconds; or 0.2 mg·kg·h of bivalirudin intravenously). The primary efficacy objective was to demonstrate superiority of PPA to reduce the primary efficacy end point of all-cause death, nonfatal myocardial infarction, nonfatal stroke, stent thrombosis (definite), or urgent revascularization (any vessel) within 30 days. The key secondary objective was to evaluate the effect of each specific anticoagulation regimen (enoxaparin, unfractionated heparin, or bivalirudin) on the primary efficacy end point. The primary safety end point was Bleeding Academic Research Consortium 3 to 5 bleeding at 30 days. RESULTS: Between January 10, 2019, and September 18, 2021, a total of 2989 patients were randomized. The primary efficacy end point occurred in 37 patients (2.5%) in both the PPA and placebo groups (hazard ratio, 1.00 [95% CI, 0.63 to 1.57]). The incidence of Bleeding Academic Research Consortium 3 to 5 bleeding did not differ between the PPA and placebo groups (8 [0.5%] vs 11 [0.7%] patients; hazard ratio, 0.74 [95% CI, 0.30 to 1.83]). CONCLUSIONS: Routine PPA after primary percutaneous coronary intervention was safe but did not reduce 30-day ischemic events. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03664180.

Incorporating the image formation process into deep learning improves network performance.

We present Richardson-Lucy network (RLN), a fast and lightweight deep learning method for three-dimensional fluorescence microscopy deconvolution. RLN combines the traditional Richardson-Lucy iteration with a fully convolutional network structure, establishing a connection to the image formation process and thereby improving network performance. Containing only roughly 16,000 parameters, RLN enables four- to 50-fold faster processing than purely data-driven networks with many more parameters. By visual and quantitative analysis, we show that RLN provides better deconvolution, better generalizability and fewer artifacts than other networks, especially along the axial dimension. RLN outperforms classic Richardson-Lucy deconvolution on volumes contaminated with severe out of focus fluorescence or noise and provides four- to sixfold faster reconstructions of large, cleared-tissue datasets than classic multi-view pipelines. We demonstrate RLN's performance on cells, tissues and embryos imaged with widefield-, light-sheet-, confocal- and super-resolution microscopy.

Pro-regenerative biomaterials recruit immunoregulatory dendritic cells after traumatic injury.

During wound healing and surgical implantation, the body establishes a delicate balance between immune activation to fight off infection and clear debris and immune tolerance to control reactivity against self-tissue. Nonetheless, how such a balance is achieved is not well understood. Here we describe that pro-regenerative biomaterials for muscle injury treatment promote the proliferation of a BATF3-dependent CD103+XCR1+CD206+CD301b+ dendritic cell population associated with cross-presentation and self-tolerance. Upregulation of E-cadherin, the ligand for CD103, and XCL-1 in injured tissue suggests a mechanism for cell recruitment to trauma. Muscle injury recruited natural killer cells that produced Xcl1 when stimulated with fragmented extracellular matrix. Without cross-presenting cells, T-cell activation increases, pro-regenerative macrophage polarization decreases and there are alterations in myogenesis, adipogenesis, fibrosis and increased muscle calcification. These results, previously observed in cancer progression, suggest a fundamental mechanism of immune regulation in trauma and material implantation with implications for both short- and long-term injury recovery.

Tumor Suppressor Adenomatous Polyposis Coli Sustains Dendritic Cell Tolerance through IL-10 in a ß-Catenin-Dependent Manner.

Dendritic cells (DC) play important roles in balancing immunity and tolerance, in which ß-catenin signaling plays an important role, yet the underlying mechanisms remain elusive. In this study, we investigated the functions of the tumor suppressor adenomatous polyposis coli (APC), also a key component of the ß-catenin upstream destruction complex in DC. APC depletion in DC does not alter DC and T cell homeostasis under resting conditions. However, APC deficiency in DC leads to attenuated antitumor immunity in mice, which exhibit fewer CD8+ T cells and more Foxp3+ regulatory T cells in tumor and draining lymph nodes. Loss of APC in DC does not affect the expression levels of costimulatory molecules. However, APC-deficient DC produce more IL-10 and exhibit a higher ability of inducing regulatory T cells but a lower ability of priming CD8+ T cells, both of which can be reversed by IL-10 inhibition. Lastly, ß-catenin depletion in APC-deficient DC rescues their antitumor immunity and reverses elevated IL-10 production. Taken together, our results identify that APC drives DC tolerance via the ß-catenin/IL-10 axis.

Designing a Magnesium/Sodium Hybrid Battery Using Hierarchical Iron Selenide Architecture as Cathode Material and Modified Dual-Ion Salts in Ether as Electrolyte.

We developed a magnesium/sodium (Mg/Na) hybrid battery using a hierarchical disk-whisker FeSe2 architecture (HD-FeSe2) as the cathode material and a modified dual-ion electrolyte. The polarizable Se2- anion reduced the Mg2+ migration barrier, and the 3D configuration possessed a large surface area, which facilitated both Mg2+/Na+ cation diffusion and electron transport. The dual-ion salts with NaTFSI in ether reduced the Mg plating/stripping overvoltage in a symmetric cell. The hybrid battery exhibited an energy density of 260.9 Wh kg-1 and a power density of 600.8 W kg-1 at 0.2 A g-1. It showed a capacity retention of 154 mAh g-1 and a Coulombic efficiency of over 99.5% under 1.0 A g-1 after 800 long cycles. The battery also displayed outstanding temperature tolerance. The findings of 3D architecture as cathode material and hybrid electrolyte provide a pathway to design a highly reliable Mg/Na hybrid battery.

Design and rationale of the Comprehensive intelligent Hypertension managEment SyStem (CHESS) evaluation study: A cluster randomized controlled trial for hypertension management in primary care.

BACKGROUND: Hypertension management in China is suboptimal with high prevalence and low control rate due to various barriers, including lack of self-management awareness of patients and inadequate capacity of physicians. Digital therapeutic interventions including mobile health and computational device algorithms such as clinical decision support systems (CDSS) are scalable with the potential to improve blood pressure (BP) management and strengthen the healthcare system in resource-constrained areas, yet their effectiveness remains to be tested. The aim of this report is to describe the protocol of the Comprehensive intelligent Hypertension managEment SyStem (CHESS) evaluation study assessing the effect of a multifaceted hypertension management system for supporting patients and physicians on BP lowering in primary care settings. MATERIALS AND METHODS: The CHESS evaluation study is a parallel-group, cluster-randomized controlled trial conducted in primary care settings in China. Forty-one primary care sites from 3 counties of China are randomly assigned to either the usual care or the intervention group with the implementation of the CHESS system, more than 1,600 patients aged 35 to 80 years with uncontrolled hypertension and access to a smartphone by themselves or relatives are recruited into the study and followed up for 12 months. In the intervention group, participants receive patient-tailored reminders and alerts via messages or intelligent voice calls triggered by uploaded home blood pressure monitoring data and participants' characteristics, while physicians receive guideline-based prescription instructions according to updated individual data from each visit, and administrators receive auto-renewed feedback of hypertension management performance from the data analysis platform. The multiple components of the CHESS system can work synergistically and have undergone rigorous development and pilot evaluation using a theory-informed approach. The primary outcome is the mean change in 24-hour ambulatory systolic BP from baseline to 12 months. DISCUSSION: The CHESS trial will provide evidence and novel insight into the effectiveness and feasibility of an implementation strategy using a comprehensive digital BP management system for reducing hypertension burden in primary care settings. TRIAL REGISTRATION: https://www. CLINICALTRIALS: gov, NCT05605418.

Three-dimensional residual channel attention networks denoise and sharpen fluorescence microscopy image volumes.

We demonstrate residual channel attention networks (RCAN) for the restoration and enhancement of volumetric time-lapse (four-dimensional) fluorescence microscopy data. First we modify RCAN to handle image volumes, showing that our network enables denoising competitive with three other state-of-the-art neural networks. We use RCAN to restore noisy four-dimensional super-resolution data, enabling image capture of over tens of thousands of images (thousands of volumes) without apparent photobleaching. Second, using simulations we show that RCAN enables resolution enhancement equivalent to, or better than, other networks. Third, we exploit RCAN for denoising and resolution improvement in confocal microscopy, enabling ~2.5-fold lateral resolution enhancement using stimulated emission depletion microscopy ground truth. Fourth, we develop methods to improve spatial resolution in structured illumination microscopy using expansion microscopy data as ground truth, achieving improvements of ~1.9-fold laterally and ~3.6-fold axially. Finally, we characterize the limits of denoising and resolution enhancement, suggesting practical benchmarks for evaluation and further enhancement of network performance.

Linearized EUV mask optimization based on the adjoint method.

Mask optimization, a compensation method for the thick mask effect and the optical proximity effect in projection lithography, is essential for advanced EUV-enabled production nodes. However, owing to high computation costs and the absence of gradient calculations, it is challenging to optimize EUV masks under rigorous consideration of the thick mask effect. In this work, a linearized EUV mask optimization method based on the adjoint method is proposed to provide fast and effective optimizations. The adjoint method is introduced to calculate the gradient of the EUV mask model. Additionally, a linearized gradient is proposed to quickly compensate for wafer pattern distortion caused by the prominent thick mask effect. Two examples of the EUV mask optimization implemented with a two-step strategy were provided, from which it was observed that the linearized gradient can improve the efficiency by about 40% in the coarse optimization step. The proposed method is promising for accurate full-chip EUV mask optimization.

Assessing the role of programmed cell death signatures and related gene TOP2A in progression and prognostic prediction of clear cell renal cell carcinoma.

Kidney Clear Cell Carcinoma (KIRC), the predominant form of kidney cancer, exhibits a diverse therapeutic response to Immune Checkpoint Inhibitors (ICIs), highlighting the need for predictive models of ICI efficacy. Our study has constructed a prognostic model based on 13 types of Programmed Cell Death (PCD), which are intertwined with tumor progression and the immune microenvironment. Validated by analyses of comprehensive datasets, this model identifies seven key PCD genes that delineate two subtypes with distinct immune profiles and sensitivities to anti-PD-1 therapy. The high-PCD group demonstrates a more immune-suppressive environment, while the low-PCD group shows better responses to PD-1 treatment. In particular, TOP2A emerged as crucial, with its inhibition markedly reducing KIRC cell growth and mobility. These findings underscore the relevance of PCDs in predicting KIRC outcomes and immunotherapy response, with implications for enhancing clinical decision-making.

Asymmetric synthesis of atropisomeric arylpyrazoles via direct arylation of 5-aminopyrazoles with naphthoquinones.

Construction of axially chiral arylpyrazoles represents an attractive challenge due to the relatively low rotational barrier of biaryl structures containing five-membered heterocycles. This work describes the catalytic asymmetric construction of axially chiral arylpyrazoles using 5-aminopyrazoles and naphthoquinone derivatives. The chiral axis could be formed through a central-to-axial chirality relay step of the chiral phosphoric acid-catalyzed arylation reaction, which features excellent yields and enantioselectivities with a broad substrate scope under mild reaction conditions.

Development of a machine learning-based model for predicting individual responses to antihypertensive treatments.

BACKGROUND AND AIMS: Personalized antihypertensive drug selection is essential for optimizing hypertension management. The study aimed to develop a machine learning (ML) model to predict individual blood pressure (BP) responses to different antihypertensive medications. METHODS AND RESULTS: We used data from a pragmatic, cluster-randomized trial on hypertension management in China. Each patient's multiple visit records were included, and two consecutive visits were paired as the index and subsequent visits. The least absolute shrinkage and selection operator method was used to select index visit variables for predicting subsequent BP. The dataset was randomly divided into training and test sets in a 7:3 ratio. Model performance was evaluated using mean absolute error (MAE) and R-square in the test set. A total of 19,013 hypertension management visit records (6282 patients) were included. The mean age of the study population was 63.9 years, and 2657 (42.3%) were females. A total of 12 phenotypical features (age, sex, smoking within seven days, body mass index, waist circumference, index visit systolic BP, diastolic BP, heart rate, comorbidities of diabetes, dyslipidemia, coronary heart disease, and stroke), together with currently taking any prescribed antihypertensive medication regimens and visits time interval were selected to build the model. The Extreme Gradient Boost model performed best among all candidate algorithms, with an MAE of 8.57 mmHg and an R2 = 0.28 in the test set. CONCLUSION: The ML techniques exhibit significant potential for predicting individual responses to antihypertensive treatments, thereby aiding clinicians in achieving optimal BP control safely and efficiently. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03636334. Registered July 3, 2018, https://clinicaltrials.gov/study/NCT03636334.

Left ventricular hypertrophy phenotype to predict incident atrial fibrillation: The Multi-Ethnic Study of Atherosclerosis.

BACKGROUND AND AIM: Left ventricular hypertrophy (LVH) has been shown to be associated with the occurrence of atrial fibrillation (AF). However, the predictive value of the LVH phenotype for incident AF remains uncertain. This study aimed to investigate the predictive value of LVH phenotype for incident AF. METHODS AND RESULTS: This study utilized the Multi-Ethnic Study of Atherosclerosis (MESA) data. LVH was defined by cardiac magnetic resonance measured LV mass index. Isolated LVH was determined as LVH without elevated cardiac biomarker and malignant LVH was determined as LVH with at least 1 elevated biomarker. Receiver-operating characteristic (ROC) analysis was performed to calculate areas under the curves (AUC) for predicting AF. A total of 4983 community-dwelling participants were included, with a mean age of 61.5 years. 279 (5.6 %) had isolated LVH, and 222 (4.5 %) had malignant LVH. During a median follow-up of 8.5 years, 272 incident AF was observed. Compared to participants without LVH and elevated cardiac biomarkers, those with isolated LVH (HR, 1.82; 95 % CI, 1.03-3.20) and malignant LVH (HR, 4.13; 95 % CI, 2.77-6.16) had a higher risk of incident AF. Malignant LVH carried a 1.5-fold increased risk of AF compared to isolated LVH (HR: 2.48, 95 % CI: 1.30-4.73). Including the LVH phenotype in the CHARGE-AF model improved model discrimination (AUC increase: 0.03, p < 0.001). CONCLUSIONS: The risks of AF incidence varied across LVH phenotypes. Malignant LVH carried the highest risk among LVH phenotypes. LVH phenotype provides incremental predictive value over the variables included in the CHARGE-AF model.

Environmental triggers of autoimmunity: The association between bisphenol analogues and systemic lupus erythematosus.

The aim of this research was to examine the correlation between the exposure to bisphenol analogues (BPs), such as bisphenol A (BPA), bisphenol F (BPF), and bisphenol S (BPS), and the risk of developing systemic lupus erythematosus (SLE). Ultra performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS) was utilized to measure the levels of BPA, BPF, and BPS in the urine of 168 female participants diagnosed with SLE and 175 female participants who were deemed healthy controls. Logistic regression models were utilized to assess the connections between levels of bisphenol and the risk of SLE. The findings indicated that levels of BPA and BPF in the urine of individuals with SLE were markedly elevated compared to those in the control group. Higher exposure to BPA and BPF exhibited positive dose-response relationships with increased SLE risk. No significant associations were identified between BPS and the risk of SLE. These findings suggest exposure to BPA and BPF may be implicated as novel environmental triggers in the development of autoimmunity such as SLE. The significantly increased levels of these bisphenol analogues detected in SLE patients versus healthy controls, along with the associations between higher exposures and elevated SLE risk, which offers crucial hints for comprehending how endocrine-disrupting substances contribute to the genesis of autoimmune illnesses. Further research using robust longitudinal assessments of bisphenol analogue exposures is warranted to corroborate these epidemiological findings. Overall, this study highlights potential environmental risk factors for SLE while calling for additional investigation into the impact of bisphenol exposures on autoimmunity development.

MicroRNA-2285f regulates milk fat metabolism by targeting MAP2K2 in bovine mammary epithelial cells.

In this study, Holstein dairy cows raised in Ningxia were selected as the research object. Mammary epithelial cells (BMECs) were extracted from the milk of eight Holstein cows with significantly different milk fat expression rates and transcribed for sequencing. Bioinformatics analysis was used to analyse the correlation of fat milk percentage, and the critical miR-2285f regulating milk fat was screened out. The target gene binding sites were predicted, and 293T cells and mammary epithelial cells were used as miRNA and target gene models for functional verification in vitro. The tissue difference of miR-2285f Holstein cows was quantitatively analysed by transfecting miR-2285f mimic and inhibitor. Assay (dual luciferase reporter gene assay) and quantitative real-time PCR (quantitative real-time PCR, qRT-PCR), triglyceride (TAG) detection, oil red O detection of lipid droplets, Western Blot assay, Edu and Flow cytometry, The molecular regulatory effects of miR-2285f and target gene MAP2K2 on milk fat metabolism of Holstein dairy cows were studied. The wild-type vector and mutant vector of map2k2-3'utr were constructed, and double luciferase reporting experiments were conducted to verify that MAP2K2 was one of the target genes of miR-2285f. According to qRT-PCR and Western Blot analysis, miR-2285f mainly regulates the expression of MAP2K2 protein in BMECs at the translation level. Bta-miR-2285f can promote cell proliferation and slow cell apoptosis by regulating MAP2K2. Bta-miR-2285f can promote triglyceride (TAG) and lipid droplet accumulation in mammary epithelial cells by targeting MAP2K2. Bta-miR-2285f can regulate protein levels of fat milk marker gene PPARG by targeting MAP2K2. In conclusion, miR-2285f can target the expression of the MAP2K2 gene, promote the proliferation of dairy mammary epithelial cells, inhibit cell apoptosis and regulate the milk fat metabolism in dairy mammary epithelial cells. The results of this study revealed the function of miR-2285f in regulating the differential expression of fat milk in Holstein dairy cows at the cellular level. They provided a theoretical and experimental basis for analysing the regulation network of milk fat synthesis of Holstein dairy cows and the molecular breeding of dairy cows.

Effect of Salicylic Acid Treatment on Disease Resistance to Coleosporium zanthoxyli in Chinese Pepper (Zanthoxylum armatum).

The fungus Coleosporium zanthoxyli causes leaf rust in Chinese pepper (Zanthoxylum armatum). To investigate the control effect of elicitor treatment on leaf rust in this species, the impact of salicylic acid (SA) on the spores and growth of C. zanthoxyli and the induced resistance to leaf rust by Z. armatum were analyzed, and the possible defense mechanisms involved in SA induction were evaluated. The results showed that SA had no effect on C. zanthoxyli spore germination and growth; however, rust resistance was induced in Z. armatum. The optimal SA treatment concentration was 0.4 mg/ml, and the relative cure effect reached 44.56%. SA-induced disease resistance was evident for up to 10 days, while the optimal induction interval was 48 h after stimulation. Consistent with the induced resistance, H2O2, total protein, total phenol, and lignin concentrations and polyphenol oxidase (PPO), peroxidase (POD), phenylalanine ammonia lyase (PAL), superoxide dismutase (SOD), and catalase (CAT) activities were significantly increased with the SA treatment, whereas the malondialdehyde content was significantly decreased. In addition, exogenous SA promoted defense-related enzyme activities, including those of POD, CAT, and PAL, and increased H2O2, lignin, and endogenous SA contents. Furthermore, SA induced the expression of SA signaling pathway genes such as ZaPR1 and ZaNPR1, and silencing ZaPR1 enhanced the sensitivity of Z. armatum to leaf rust. Our results demonstrated that 0.4 mg/ml SA priming increased the activities of CAT, POD, and PAL, elevated the contents of H2O2, lignin, and endogenous SA, and upregulated the expression of the SA-related gene ZaPR1, thereby enhancing the resistance of Z. armatum to leaf rust.

Assessing the influence of simulated environmental gradients on the spatial heterogeneity of landscape patterns in the Tibetan Plateau.

Landscape patterns are pivotal in the realms of land use planning and ecological development, yet there remains a dearth of comprehensive research pertaining to the prediction of changes in landscape pattern characteristics. Within this study, we adopt the PLUS-CA-Markov and Fragstats models to forecast landscape patterns on the Tibetan Plateau spanning the period from 2030 to 2050. Through qualitative and quantitative analyses, we explore the spatiotemporal characteristics of landscape pattern changes between 2000 and 2050, concurrently identifying correlations among landscape pattern indices. Moreover, acknowledging the distinctive environmental gradients encompassing the plateau, notably elevation, slope, temperature, and precipitation, we investigate their implications on landscape pattern changes. Our findings indicate that: (1) Grassland degradation exhibited the utmost severity between 2000 and 2020, primarily attributed to overgrazing and climate-induced glacial melt. In contrast, cropland, forest, and water showcased divergent trends from 2020 to 2050 when compared to the preceding two decades, indicative of the efficacy of climate change control measures. (2) The distribution of landscape patterns on the Tibetan Plateau exhibited a considerable level of instability, marked by a decline in aggregation, reduced diversity and complexity, and amplified ecological connectivity between 2000 and 2020, signifying a partial amelioration in ecological quality. Between 2020 and 2050, landscape aggregation decreased alongside landscape fragmentation and the number of connectivity paths, signifying a discernible degradation of the plateau's ecosystem. (3) The most significant trade-off relationship was observed between landscape division index and largest patch index, while the synergistic relationship between landscape shape index and mean shape index was more pronounced. (4) Landscape aggregation, division, and largest patch index demonstrated non-linear quadratic trends in relation to elevation and temperature. Landscape shape index and patch density exhibited irregular non-linear effects. Largest patch index was predominantly influenced by slope, whereas division index was most affected by precipitation.

Water-related ecosystem services interactions and their natural-human activity drivers: Implications for ecological protection and restoration.

Sustainable development faces the crucial challenge of safeguarding water-related ecosystem services, particularly in arid regions. However, scale-dependent interactions and their influencing factors remain unclear. This study addresses this local gap on the regional level by focusing on ecologically vulnerable mountain areas, employing a comprehensive quantitative and spatial analysis approach, utilizing Spearman coefficient, trade-off/synergy index, and trade-off/synergy criterion, to examine water-related ecosystem services interactions across scales in arid area. Additionally, a Geographical detector was used to identify dominant natural and human activity factors. Finally, we determined ecologically optimal and worst areas and proposed spatial planning and management recommendations for ecological protection and restoration. Key results indicate that: (1) From 1995 to 2015, water yield and nutrient delivery ratio exhibited a declining trend, while soil retention showed an increasing trend, with the weakest nutrient delivery ratio function in the reserve. (2) At the grid scale, there were 2 trade-offs among water-related ecosystem services in 1995, which decreased to 1 trade-off in 2005 and 2015. The synergistic was most prominent near Qinghai Lake, while the trade-off was most obvious in the western mountainous areas. Conversely, the county scale demonstrated synergy. (3) NDVI, slope, and precipitation dominantly influence the spatial heterogeneity patterns of soil retention_water yield, soil retention_nutrient delivery ratio, and water yield_nutrient delivery ratio, respectively, with natural factors outweighing human activities in impacting water-related ecosystem services. This study contributes to the improvement and optimization of ecological environment management decisions.

Scale effects and spatial heterogeneity of driving factors in ecosystem services value interactions within the Tibet autonomous region.

Widespread land development, deforestation, and wetland degradation have disrupted the physical integrity and functional capacity of ecosystems, leading to a reduction in ecosystem service values (ESV). However, comprehensive research addressing ESV interactions that represent various ecosystem services from multifaceted angles is limited. Moreover, the relative significance and spatiotemporal diversity of natural and socio-economic variables influencing ESV demand further investigation. This study conducts both quantitative and qualitative assessments of the spatiotemporal dynamics and interrelationships of ESV in the Tibet autonomous region from 2000 to 2020. Geographical detector and geographically weighted regression models are applied to ascertain the relative importance and spatial heterogeneity of diverse ESV determinants. The findings reveal the following key insights: (1) Barren lands experienced the most substantial expansion from 2000 to 2020, indicating an exacerbation of desertification in the Tibet autonomous region. (2) Over the two decades, ESV exhibited an overall upward trajectory, with regulation of water flows, water bodies, and forests making the most significant contributions to ESV and its growth. (3) The quantitative and qualitative assessment of ESV interrelations has identified the number of trade-offs and synergies, along with spatial occurrences, offering a detailed foundation for the scientific management of ecosystems. Specifically, quantitative results portray ESV correlations as positive or negative, qualitative spatial mapping elucidates intricate local interactions among ESV. (4) The primary driver of ESV in the Tibet autonomous region is NDVI (0.072), with elevation following closely behind, underscoring the predominant influence of natural factors relative to socio-economic variables. This research serves as a scientific underpinning for the development of ecological conservation policies and the execution of ecological restoration initiatives.