Decoding 2.3 million ECGs: interpretable deep learning for advancing cardiovascular diagnosis and mortality risk stratification.

Aims: Electrocardiogram (ECG) is widely considered the primary test for evaluating cardiovascular diseases. However, the use of artificial intelligence (AI) to advance these medical practices and learn new clinical insights from ECGs remains largely unexplored. We hypothesize that AI models with a specific design can provide fine-grained interpretation of ECGs to advance cardiovascular diagnosis, stratify mortality risks, and identify new clinically useful information. Methods and results: Utilizing a data set of 2 322 513 ECGs collected from 1 558 772 patients with 7 years follow-up, we developed a deep-learning model with state-of-the-art granularity for the interpretable diagnosis of cardiac abnormalities, gender identification, and hypertension screening solely from ECGs, which are then used to stratify the risk of mortality. The model achieved the area under the receiver operating characteristic curve (AUC) scores of 0.998 (95% confidence interval (CI), 0.995-0.999), 0.964 (95% CI, 0.963-0.965), and 0.839 (95% CI, 0.837-0.841) for the three diagnostic tasks separately. Using ECG-predicted results, we find high risks of mortality for subjects with sinus tachycardia (adjusted hazard ratio (HR) of 2.24, 1.96-2.57), and atrial fibrillation (adjusted HR of 2.22, 1.99-2.48). We further use salient morphologies produced by the deep-learning model to identify key ECG leads that achieved similar performance for the three diagnoses, and we find that the V1 ECG lead is important for hypertension screening and mortality risk stratification of hypertensive cohorts, with an AUC of 0.816 (0.814-0.818) and a univariate HR of 1.70 (1.61-1.79) for the two tasks separately. Conclusion: Using ECGs alone, our developed model showed cardiologist-level accuracy in interpretable cardiac diagnosis and the advancement in mortality risk stratification. In addition, it demonstrated the potential to facilitate clinical knowledge discovery for gender and hypertension detection which are not readily available.

Stable CO2 Reduction under Natural Air on Ni-Sn Hydroxide Photocatalyst with Dynamic Renewable Oxygen Vacancies.

Advanced photocatalysts are highly desired to activate the photocatalytic CO2 reduction reaction (CO2RR) with low concentration. Herein, the NiSn(OH)6 with rich surface lattice hydroxyls was synthesized to boost the activity directly under the natural air. Results showed that terminal Ni-OH could serve as donors to feed protons and generate oxygen vacancies (VO), thus beneficial to convert the activated CO2 (HCO3-) mainly into CO (5.60 µmol/g) in the atmosphere. It was flexible and widely applicable for a stable CO2RR from high pure to air level free of additionally adding H2O reactant, and higher than the traditional gas-liquid-solid (1.58 µmol/g) and gas-solid (4.07 µmol/g) reaction system both using high pure CO2 and plenty of H2O. The strong hydrophilia by the rich surface hydroxyls allowed robust H2O molecule adsorption and dissociation at VO sites to achieve the Ni-OH regeneration, leading to a stable CO yield (11.61 µmol/g) with the enriched renewable VO regardless of the poor CO2 and H2O in air. This work opens up new possibilities for the practical application of natural photosynthesis.

The interaction of endorepellin and neurexin triggers neuroepithelial autophagy and maintains neural tube development.

Heparan sulfate proteoglycan 2 (HSPG2) gene encodes the matrix protein Perlecan, and genetic inactivation of this gene creates mice that are embryonic lethal with severe neural tube defects (NTDs). We discovered rare genetic variants of HSPG2 in 10% cases compared to only 4% in controls among a cohort of 369 NTDs. Endorepellin, a peptide cleaved from the domain V of Perlecan, is known to promote angiogenesis and autophagy in endothelial cells. The roles of enderepellin in neurodevelopment remain unclear so far. Our study revealed that endorepellin can migrate to the neuroepithelial cells and then be recognized and bind with the neuroepithelia receptor neurexin in vivo. Through the endocytic pathway, the interaction of endorepellin and neurexin physiologically triggers autophagy and appropriately modulates the differentiation of neural stem cells into neurons as a blocker, which is necessary for normal neural tube closure. We created knock-in (KI) mouse models with human-derived HSPG2 variants, using sperm-like stem cells that had been genetically edited by CRISPR/Cas9. We realized that any HSPG2 variants that affected the function of endorepellin were considered pathogenic causal variants for human NTDs given that the severe NTD phenotypes exhibited by these KI embryos occurred in a significantly higher response frequency compared to wildtype embryos. Our study provides a paradigm for effectively confirming pathogenic mutations in other genetic diseases. Furthermore, we demonstrated that using autophagy inhibitors at a cellular level can repress neuronal differentiation. Therefore, autophagy agonists may prevent NTDs resulting from failed autophagy maintenance and neuronal over-differentiation caused by deleterious endorepellin variants.

Deep reinforcement learning for multi-class imbalanced training: applications in healthcare.

With the rapid growth of memory and computing power, datasets are becoming increasingly complex and imbalanced. This is especially severe in the context of clinical data, where there may be one rare event for many cases in the majority class. We introduce an imbalanced classification framework, based on reinforcement learning, for training extremely imbalanced data sets, and extend it for use in multi-class settings. We combine dueling and double deep Q-learning architectures, and formulate a custom reward function and episode-training procedure, specifically with the capability of handling multi-class imbalanced training. Using real-world clinical case studies, we demonstrate that our proposed framework outperforms current state-of-the-art imbalanced learning methods, achieving more fair and balanced classification, while also significantly improving the prediction of minority classes. Supplementary Information: The online version contains supplementary material available at 10.1007/s10994-023-06481-z.

Ketamine administration causes cognitive impairment by destroying the circulation function of the glymphatic system.

BACKGROUND: Ketamine, as a non-competitive antagonist of N-methyl-D-aspartate (NMDA) receptors, was originally used in general anesthesia. Epidemiological data show that ketamine has become one of the most commonly abused drugs in China. Ketamine administration might cause cognitive impairment; however, its molecular mechanism remains unclear. The glymphatic system is a lymphoid system that plays a key role in metabolic waste removal and cognitive regulation in the central nervous system. METHODS: Focusing on the glymphatic system, this study evaluated the behavioral performance and circulatory function of the glymphatic system by building a short-term ketamine administration model in mice, and detected the expression levels of the 5-HT2c receptor, ΔFosb, Pten, Akt, and Aqp4 in the hippocampus. Primary astrocytes were cultured to verify the regulatory relationships among related indexes using a 5-HT2c receptor antagonist, a 5-HT2c receptor short interfering RNA (siRNA), and a ΔFosb siRNA. RESULTS: Ketamine administration induced ΔFosb accumulation by increasing 5-HT2c receptor expression in mouse hippocampal astrocytes and primary astrocytes. ΔFosb acted as a transcription factor to recognize the AATGATTAAT bases in the 5' regulatory region of the Aqp4 gene (-1096 bp to -1087 bp), which inhibited Aqp4 expression, thus causing the circulatory dysfunction of the glymphatic system, leading to cognitive impairment. CONCLUSIONS: Although this regulatory mechanism does not involve the Pten/Akt pathway, this study revealed a new mechanism of ketamine-induced cognitive impairment in non-neuronal systems, and provided a theoretical basis for the safety of clinical treatment and the effectiveness of withdrawal.

Hyperthermia improves gemcitabine sensitivity of pancreatic cancer cells by suppressing the EFNA4/ß-catenin axis and activating dCK.

Background: Previously, our investigations have underscored the potential of hyperthermia to improve the therapeutic efficacy of gemcitabine (GEM) in pancreatic cancer (PC). Nonetheless, the precise underlying mechanisms remain elusive. Methods: We engineered two GEM-resistant PC cell lines (BxPC-3/GEM and PANC-1/GEM) and treated them with GEM alongside hyperthermia. The impact of hyperthermia on the therapeutic potency of GEM was ascertained through MTT assay, assessment of the concentration of its active metabolite dFdCTP, and evaluation of deoxycytidine kinase (dCK) activity. Lentivirus-mediated dCK silencing was further employed to validate its involvement in mediating the GEM-sensitizing effect of hyperthermia. The mechanism underlying hyperthermia-mediated dCK activation was explored using bioinformatics analyses. The interplay between hyperthermia and the ephrin A4 (EFNA4)/ß-catenin/dCK axis was investigated, and their roles in GEM resistance was further explored via the establishment of xenograft tumor models in nude mice. Results: Hyperthermia restored dCK expression in GEM-resistant cell lines, concurrently enhancing GEM sensitivity and fostering DNA damage and cell death. These observed effects were negated by dCK silencing. Regarding the mechanism, hyperthermia activated dCK by downregulating EFNA4 expression and mitigating ß-catenin activation. Overexpression of EFNA4 activated the ß-catenin while suppressing dCK, thus diminishing cellular GEM sensitivity-a phenomenon remediated by the ß-catenin antagonist MSAB. Consistently, in vivo, hyperthermia augmented the therapeutic efficacy of GEM on xenograft tumors through modulation of the ephrin A4/ß-catenin/dCK axis. Conclusion: This study delineates the role of hyperthermia in enhancing GEM sensitivity of PC cells, primarily mediated through the suppression of the EFNA4/ß-catenin axis and activation of dCK.

De novo design of drug-binding proteins with predictable binding energy and specificity.

The de novo design of small molecule-binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase-1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from <5 nM to low micromolar. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free energy calculations performed directly on the designed models were in excellent agreement with the experimentally measured affinities. We conclude that de novo design of high-affinity small molecule-binding proteins with tuned interaction energies is feasible entirely from computation.

Bisphenol A Exposure Interferes with Reproductive Hormones and Decreases Sperm Counts: A Systematic Review and Meta-Analysis of Epidemiological Studies.

Bisphenol A (BPA), an acknowledged endocrine disrupter, is easily exposed to humans via food packaging and container. However, a consensus has not been reached on the extent to which BPA exposure affects the reproductive system. We therefore conducted this systematic review and meta-analysis to elucidate the relationship between BPA exposure and male reproduction-related indicators. Up to October 2023, a comprehensive search was carried out in the PubMed, Embase, Cochrane and Web of Science, and 18 studies were ultimately included. ß coefficients from multivariate linear regression analyses were pooled using a random effects model. The results showed that the urinary BPA concentration was negatively correlated with the sperm concentration (ß coefficient = -0.03; 95% CI: -0.06 to -0.01; I2 = 0.0%, p = 0.003) and total sperm count (ß coefficient = -0.05; 95% CI: -0.08 to -0.02; I2 = 0.0%, p < 0.001). In addition, BPA concentrations were associated with increased sex hormone-binding globulin (SHBG) levels, increased estradiol (E2) levels, and reduced biologically active androgen levels. However, the relationship between an increased risk of below-reference sperm quality and BPA exposure was not robust. This systematic review revealed that BPA exposure disrupts reproductive hormones, reduces sperm counts and may ultimately adversely affect male reproduction.

Aberrant activated Notch1 promotes prostate enlargement driven by androgen signaling via disrupting mitochondrial function in mouse.

The prostate is a vital accessory gonad in the mammalian male reproductive system. With the ever-increasing proportion of the population over 60 years of age worldwide, the incidence of prostate diseases, such as benign prostatic hyperplasia (BPH) and prostate cancer (PCa), is on the rise and is gradually becoming a significant medical problem globally. The notch signaling pathway is essential in regulating prostate early development. However, the potential regulatory mechanism of Notch signaling in prostatic enlargement and hyperplasia remains unclear. In this study, we proved that overactivation of Notch1 signaling in mouse prostatic epithelial cells (OEx) led to prostatic enlargement via enhancing proliferation and inhibiting apoptosis of prostatic epithelial cells. Further study showed that N1ICD/RBPJ directly up-regulated the androgen receptor (AR) and enhanced prostatic sensitivity to androgens. Hyper-proliferation was not found in orchidectomized OEx mice without androgen supply but was observed after Dihydrotestosterone (DHT) supplementation. Our data showed that the number of mitochondrion in prostatic epithelial cells of OEx mice was increased, but the mitochondrial function was impaired, and the essential activity of the mitochondrial respiratory electron transport chain was significantly weakened. Disordered mitochondrial number and metabolic function further resulted in excessive accumulation of reactive oxygen species (ROS). Importantly, anti-oxidant N-Acetyl-L-Cysteine (NAC) therapy could alleviate prostatic hyperplasia caused by the over-activation of Notch1 signaling. Furthermore, we observed the incremental Notch signaling activity in progenitor-like club cells in the scRNA-seq data set of human BPH patients. Moreover, the increased number of TROP2+ progenitors and Club cells was also confirmed in our OEx mice. In conclusion, our study revealed that over-activated Notch1 signaling induces prostatic enlargement by increasing androgen receptor sensitivity, disrupting cellular mitochondrial metabolism, increasing ROS, and a higher number of progenitor cells, all of which can be effectively rescued by NAC treatment.

Facile synthesis of nanoparticles-stacked Co3O4 nanoflakes with catalase-like activity for accelerating wound healing.

Delayed wound healing caused by excessive reactive oxygen species (ROS) remains a considerable challenge. In recent years, metal oxide nanozymes have gained significant attention in biomedical research. However, a comprehensive investigation of Co3O4-based nanozymes for enhancing wound healing and tissue regeneration is lacking. This study focuses on developing a facile synthesis method to produce high-stability and cost-effective Co3O4 nanoflakes (NFs) with promising catalase (CAT)-like activity to regulate the oxidative microenvironment and accelerate wound healing. The closely arranged Co3O4 nanoparticles (NPs) within the NFs structure result in a significantly larger surface area, thereby amplifying the enzymatic activity compared to commercially available Co3O4 NPs. Under physiological conditions, it was observed that Co3O4 NFs efficiently break down hydrogen peroxide (H2O2) without generating harmful radicals (·OH). Moreover, they exhibit excellent compatibility with various cells involved in wound healing, promoting fibroblast growth and protecting cells from oxidative stress. In a rat model, Co3O4 NFs facilitate both the hemostatic and proliferative phases of wound healing, consequently accelerating the process. Overall, the promising results of Co3O4 NFs highlight their potential in promoting wound healing and tissue regeneration.

Fluoroquinolones: Neurological Complications and Side Effects in Clinical Practice.

Fluoroquinolones, a popular antibiotic class that inhibits nucleic acid synthesis of bacteria by disrupting the activity of the enzyme's topoisomerase IV and DNA gyrase, are used to treat bacterial infections. However, the widespread use of these drugs has allowed for the development of microbial resistance in recent years. Quinolones also have many clinically relevant side effects, including psychosis, confusion, seizures, headaches, dizziness, and nausea. Common side effects include tendinitis, myopathy, depression, and fatigue. Cardiovascular side effects include increased risk of aortic aneurysm, aortic dissection, and QT interval prolongation. Overall, quinolones can be an effective choice for treating bacterial infections. Still, the side effect profile and decreased efficacy secondary to microbial resistance no longer make the quinolone class an ideal choice for many types of infection. A better understanding of the role of quinolone-mediated or neurological damage, cardiovascular impairment, and musculoskeletal involvement is imperative to determine the risks/benefits for the clinician.

AutoNet-Generated Deep Layer-Wise Convex Networks for ECG Classification.

The design of neural networks typically involves trial-and-error, a time-consuming process for obtaining an optimal architecture, even for experienced researchers. Additionally, it is widely accepted that loss functions of deep neural networks are generally non-convex with respect to the parameters to be optimised. We propose the Layer-wise Convex Theorem to ensure that the loss is convex with respect to the parameters of a given layer, achieved by constraining each layer to be an overdetermined system of non-linear equations. Based on this theorem, we developed an end-to-end algorithm (the AutoNet) to automatically generate layer-wise convex networks (LCNs) for any given training set. We then demonstrate the performance of the AutoNet-generated LCNs (AutoNet-LCNs) compared to state-of-the-art models on three electrocardiogram (ECG) classification benchmark datasets, with further validation on two non-ECG benchmark datasets for more general tasks. The AutoNet-LCN was able to find networks customised for each dataset without manual fine-tuning under 2 GPU-hours, and the resulting networks outperformed the state-of-the-art models with fewer than 5% parameters on all the above five benchmark datasets. The efficiency and robustness of the AutoNet-LCN markedly reduce model discovery costs and enable efficient training of deep learning models in resource-constrained settings.

Study on Fatigue Life of Aluminum Alloy 6061-T6 Based on Random Defect Characteristics.

A certain number of hole-like defects will occur in aluminum alloys under cyclic loading. The internal holes will reduce the strength of the material and cause stress concentration, which will aggravate the development of fatigue damage. A classification method of defect features based on X-ray CT damage data is proposed. The random hole distribution model is established through the linear congruence method and the region division method. The hole parameter is introduced as the intermediate variable of the 3D reconstruction model of internal defects. In the mesoscopic stage, the function relationship between the distribution of random holes and the fatigue life is established based on the coupling relationship between the number and proportion of pores and the fatigue life. In the macroscopic stage, the relationship between the random holes and the macroscopic crack growth life is established by taking the crack length as the damage variable. The crack propagation rate decreased with the increase in the number of holes. The prediction model of the whole life stage is established using the life function from microcrack initiation to macroscopic crack propagation. Finally, the validity of the whole stage fatigue life prediction model is demonstrated through the comparison and verification of experiments, which provides a certain engineering value for the life estimation of 6061-T6 aluminum alloy materials.

Mitigation of Salt Stress in Rice by the Halotolerant Plant Growth-Promoting Bacterium Enterobacter asburiae D2.

Salinity is a major abiotic stress that seriously affects crop growth worldwide. In this work, we aimed to isolate potential halotolerant plant growth-promoting rhizobacteria (PGPR) to mitigate the adverse impacts of salt stress in rice. An isolate, D2, with multiple plant growth-promoting (PGP) characteristics was identified as Enterobacter asburiae D2. Strain D2 could produce indole-3-acetic acid and siderophore. It also exhibited phosphate solubilization and 1-aminocyclopropane-1-carboxylic deaminase activity. Genome analysis further provided insights into the molecular mechanism of its PGP abilities. Strain D2 inoculation efficiently stimulated rice growth under both normal and saline conditions. Compared with the non-inoculated plants, a significant increase in plant height (18.1-34.7%), root length (25.9-57.1%), root dry weight (57.1-150%), and shoot dry weight (17.3-50.4%) was recorded in inoculated rice seedlings. Meanwhile, rice seedlings inoculated with strain D2 showed improvement in chlorophyll and proline content, while the oxidant damage was reduced in these plants in comparison with the control group. Moreover, the K+/Na+ ratio of the inoculated rice seedlings exposed to NaCl and Na2CO3 was higher than that of the uninoculated groups. These results imply that Enterobacter asburiae D2 is a potential PGPR that can be used for alleviation of salt stress in rice.

The value of Lp(a) and TG/HDLC in peripheral blood to assess the stability of carotid plaque in patients with ischemic stroke.

OBJECTIVE: The objective of this study was to investigate the relationship between lipoprotein (a) (Lp(a)), triglyceride/high-density lipoprotein cholesterol (TG/HDL-C), and the stability of carotid atherosclerotic plaque in patients with acute ischemic stroke. METHODS: A total of 142 patients with acute ischemic stroke were selected and divided into group A (59 cases of stable plaque formation) and group B (83 cases of unstable plaque formation) according to the characteristics of carotid artery plaque formation detected by carotid color Doppler ultrasound. The serum Lp(a), lipid metabolism indexes, peripheral blood routine indexes, and related serum inflammatory factors indexes were compared between the two groups. Receiver operating characteristic curve and multivariate logistic regression model were used to analyze the relationship between each index and the formation of carotid unstable plaque. RESULTS: There were no significant differences in serum total cholesterol (TC), HDL-C, and low-density lipoprotein cholesterol (LDL-C) between groups A and B (p > .05). The values of Lp(a), TG, and TG/HDL-C in group B were higher than those in group A, and the differences were statistically significant (p < .05). There were no significant differences in serum TC, HDL-C, and LDL-C between groups A and B (p > .05). The values of Lp(a), TG, and TG/HDL-C in group B were higher than those in group A, and the differences were statistically significant (p < .05). The values of HBA1C, Lp-PLA2, CRP, CysC, Hcy, TNF-α, neutrophils, and NLR in group B were higher than those in group A, and the differences were statistically significant (p < .05). There was no significant difference in FPG, systolic blood pressure, diastolic blood pressure, Hb, white blood cells, platelets, and lymphocytes between groups A and B (p > .05). The results of logistic regression model showed that the increase of Lp(a), TG/HDL-C, HBA1C, Lp-PLA2, CRP, CysC, Hcy, and NLR could increase the risk of carotid artery unstable plaque in patients with ischemic stroke (p < .05). CONCLUSION: Lp(a) and TG/HDL-C have certain value in evaluating the stability of carotid atherosclerotic plaque in patients with acute ischemic stroke, and the increased levels of LP (a) and TG/HDL-C will significantly increase the risk of carotid unstable plaque in patients.

G-protein-coupled estrogen receptor 1 promotes peritoneal metastasis of gastric cancer through nicotinamide adenine dinucleotide kinase 1-mediated redox modulation.

Adipose tissue is the second most important site of estrogen production, where androgens are converted into estrogen by aromatase. While gastric cancer patients often develop adipocyte-rich peritoneal metastasis, the underlying mechanism remains unclear. In this study, we identified the G-protein-coupled estrogen receptor (GPER1) as a promoter of gastric cancer peritoneal metastasis. Functional in vitro studies revealed that ß-Estradiol (E2) or the GPER1 agonist G1 inhibited anoikis in gastric cancer cells. Additionally, genetic overexpression or knockout of GPER1 significantly inhibited or enhanced gastric cancer cell anoikis in vitro and peritoneal metastasis in vivo, respectively. Mechanically, GPER1 knockout disrupted the NADPH pool and increased reactive oxygen species (ROS) generation. Conversely, overexpression of GPER1 had the opposite effects. GPER1 suppressed nicotinamide adenine dinucleotide kinase 1(NADK1) ubiquitination and promoted its phosphorylation, which were responsible for the elevated expression of NADK1 at protein levels and activity, respectively. Moreover, genetic inhibition of NADK1 disrupted NADPH and redox homeostasis, leading to high levels of ROS and significant anoikis, which inhibited lung and peritoneal metastasis in cell-based xenograft models. In summary, our study suggests that inhibiting GPER1-mediated NADK1 activity and its ubiquitination may be a promising therapeutic strategy for peritoneal metastasis of gastric cancer.

Is managerial ability a catalyst for driving digital transformation in enterprises? An empirical analysis from internal and external pressure perspectives.

In a dynamic and competitive business environment, managerial ability emerges as a pivotal strategic factor for capitalizing on new opportunities within the technological revolution and digital transformation of enterprises. Based on data from Chinese A-share listed firms spanning from 2009 to 2019, this study integrates insights from the upper echelons theory and the behavioral theory of the firm to investigate the moderating roles of historical aspiration shortfalls and industrial competitiveness on the relationship between managerial ability and enterprise digital transformation from internal and external pressure perspectives. Our findings indicate a positive impact of managerial ability on digital transformation. The relationship between managerial ability and digital transformation is reinforced by historical aspiration shortfalls; nevertheless, industrial competitiveness has attenuated the aforementioned relationship. This study contributes to a better understanding of the strategic implications of managerial ability within the context of organizational innovation strategies. It offers valuable insights into the decision-making processes of firms as they navigate the challenges of digital transformation within an ever-evolving business environment.

Assessment of Self-report, Palpation, and Surface Electromyography Dataset During Isometric Muscle Contraction.

Measuring muscle fatigue involves assessing various components within the motor system. While subjective and sensor-based measures have been proposed, a comprehensive comparison of these assessment measures is currently lacking. This study aims to bridge this gap by utilizing three commonly used measures: participant self-reported perceived muscle fatigue scores, a sports physiotherapist's manual palpation-based muscle tightness scores, and surface electromyography sensors. Compensatory muscle fatigue occurs when one muscle group becomes fatigued, leading to the involvement and subsequent fatigue of other muscles as they compensate for the workload. The evaluation of compensatory muscle fatigue focuses on nine different upper body muscles selected by the sports physiotherapist. With a cohort of 30 male subjects, this study provides a valuable dataset for researchers and healthcare practitioners in sports science, rehabilitation, and human performance. It enables the exploration and comparison of diverse methods for evaluating different muscles in isometric contraction.

Satellite observed dryland greening in Asian endorheic basins: Drivers and implications to sustainable development.

A large portion of Central-Western Asia is made up of contiguous closed basins, collectively termed as the Asian Endorheic Basins (AEBs). As these retention basins are only being replenished by the intermittent and scarce rainfall, global warming coupled with ever-rising human demand for water is exerting unprecedented pressures on local water and ecological security. Recent studies revealed a persistent and widespread water storage decline across the AEBs, yet the response of dryland vegetation to this recent hydroclimatic trend and a spatially explicit partitioning of the impact into the hydroclimatic factors and human activities remain largely unknown. To fill in this knowledge gap, we conducted trend and partial correlation analysis of vegetation and hydroclimatic change from 2001 to 2021 using multi-satellite observations, including vegetation greenness, total water storage anomalies (TWSA) and meteorological data. Here we show that much of the AEB (65.53 %), encompassing Mongolia Plateau, Northwest China, Qinghai Tibet Plateau, and Western Asia (except the Arabian Peninsula), exhibited a significant greening trend over the past two decades. In arid AEB, precipitation dominated the vegetation productivity trend. Such a rainfall dominance gave way to TWSA dominance in the hyper-arid AEB. We further showed that the decoupling of rainfall and hyper-arid vegetation greening was largely due to a significant expansion (17.3 %) in irrigated cropland across the hyper-arid AEB. Given the extremely harsh environment in the AEB, our results therefore raised a significant concern on the ecological and societal sustainability in this region, where a mild increase in precipitation cannot catch up the rising evaporative demand and water consumption resulted from global warming and agriculture intensification.

The influence of bootleg innovation on individual innovation performance: The mediating effect of cognitive flexibility and the moderating effect of leadership's emotional intelligence.

Based Correctly handling the creativity of employees who have not been adopted is not only conducive to continuously stimulating employees' creativity and improving individual innovation performance, but also conducive to making the best use of organizational resources. This study integrates conservation of resource theory (COR) and social information processing theory to explore the influence of bootleg innovation behavior in organizations on individual innovation performance, as well as the mediating role of cognitive flexibility and the moderating role of leadership emotional intelligence. A three-stage time-lagged research design is used to obtain a valid sample of 327 employees from China. The PROCESS macro for SPSS was applied to test the hypothesized relationships. Findings demonstrated that bootleg innovation is positively related to individual innovation performance; cognitive flexibility mediates the relationship between bootleg innovation and individual innovation performance. Moreover, leadership emotional intelligence moderates the relationship between bootleg innovation and individual innovation performance and between bootleg innovation and cognitive flexibility and between cognitive flexibility and individual innovation performance respectively. The conclusion of the study not only provides a theoretical basis for individuals and leaders to deal with employees' creative abortion, but also provides a new thinking mode for how to maximize the effectiveness of unaccepted ideas and promote individual innovation performance.