Hydrological dynamics in the China-Mongolia arid region: An integrated analysis of precipitation recycling and water vapor conversion.

This study examines the atmospheric water cycle dynamics in the China-Mongolia Arid Region (CMAR), a region significantly affected by aridity. By employing a combination of Empirical Orthogonal Function (EOF) analysis, ERA5 reanalysis data, and the Dynamic Recycling Model (DRM), we investigate the spatial and temporal variations in the Precipitation Recycling Ratio (PRR) and Precipitable Water Conversion Rate (PWCR) over a forty-year period (1979-2021). Our findings reveal that both PRR and PWCR are generally higher but decreasing in most subregions of CMAR, suggesting a notable contribution of local moisture to precipitation. We also identify an increasing trend in PRR across the northwestern subregions and a decreasing trend in other areas. Similarly, PWCR exhibits an increasing trend in the northwestern and southern subregions, while decreasing elsewhere, implying a decline in water vapor conversion and recycling efficiency. Furthermore, our EOF analysis uncovers distinct spatial patterns, with dominant modes accounting for significant variances in PRR and PWCR, correlating with local variations in atmospheric moisture and advective changes. These results underscore the complex interplay between regional topography, atmospheric dynamics, and the hydrological cycle in CMAR. The insights from this study are vital for formulating effective water management strategies and adapting to climate change impacts in arid regions, holding broad implications for environmental science, climate studies, and sustainable resource management. Our findings reveal distinct spatial patterns and contrasting trends in precipitation recycling and water vapor conversion across the subregions of CMAR. This heterogeneity underscores the importance of conducting analyses at finer spatial scales to avoid contradictory conclusions that can arise from topographic influences when treating CMAR as a single unit. Future studies should focus on smaller subregions to accurately capture the intricacies of the water cycle in this topographically complex arid region.

Correction: Improved runoff forecasting based on time-varying model averaging method and deep learning.

[This corrects the article DOI: 10.1371/journal.pone.0274004.].

Effects of aerobic and resistance exercises on psychological and cognitive functions in patients with post-stroke migraine.

OBJECTIVE: To investigate the impact of a combination of aerobic and resistance exercises on the psychological and cognitive functions of post-stroke migraine patients. METHODS: This study recruited 100 patients suffering from post-stroke migraine pain who were admitted to the hospital, categorizing them into a control group (n = 50) and an intervention group (n = 50). The control group received conventional drug treatment, while the intervention group received the exercise-based intervention that combined aerobic exercise with resistance exercise. RESULTS: Before treatment, both groups displayed similar Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Mini-mental State Examination (MMSE) and MoCA scores. However, after the intervention, the intervention group exhibited lower scores on these measures compared to the control group (all p < 0.05). Additionally, there were no discernible disparity in Migraine Disability Assessment (MIDAS) and Headache Impact Test (HIT-6) scores between the two cohorts of patients before treatment (p > 0.05), whereas the intervention group demonstrated significantly lower MIDAS and HIT-6 scores following the intervention (p < 0.05). Although there were no discernible distinctions in National Institute of Health stroke scale (NIHSS) and Stroke Specialized Quality of Life Scale (SS-QOL) measurements between the two patient groups before treatment (p > 0.05), the intervention group exhibited a significant decrease in NIHSS scores and a notable increase in SS-QOL scores after the intervention (p > 0.05). Moreover, the satisfaction rate and overall satisfaction rate were significantly higher in the intervention group (p < 0.05). CONCLUSION: The combination of aerobic and resistance exercises demonstrated positive effects on the psychological well-being and overall quality of life for post-stroke migraine patients.

Identification and Functional Characterization of Carboxylesterase Genes Involved in Spirodiclofen Resistance in Panonychus citri (McGregor).

Overexpression of carboxyl/cholinesterase (CCE) genes has been reported to be associated with many cases of pesticide resistance in arthropods. However, it has been rarely documented that CCE genes participate in spirodiclofen resistance in Panonychus citri. In previous research, we found that spirodiclofen resistance is related to increased P450 and CCE enzyme activities in P. citri. In this study, we identified two CCE genes, PcCCE3 and PcCCE5, which were significantly upregulated in spirodiclofen-resistant strain and after exposure to spirodiclofen. RNA interference of PcCCE3 and PcCCE5 increased the spirodiclofen susceptibility in P. citri. In vitro metabolism indicated that PcCCE3 and PcCCE5 could interact with spirodiclofen, but metabolites were detected only in the PcCCE3 treatment. Our results indicated that PcCCE3 participates in spirodiclofen resistance through direct metabolism, and PcCCE5 may be involved in the spirodiclofen resistance by passive binding and sequestration, which provides new insights into spirodiclofen resistance in P. citri.

Multi-Scale Marine Object Detection in Side-Scan Sonar Images Based on BES-YOLO.

Aiming at the problem of low accuracy of multi-scale seafloor target detection in side-scan sonar images with high noise and complex background texture, a model for multi-scale target detection using the BES-YOLO network is proposed. First, an efficient multi-scale attention (EMA) mechanism is used in the backbone of the YOLOv8 network, and a bi-directional feature pyramid network (Bifpn) is introduced to merge the information of different scales, finally, a Shape_IoU loss function is introduced to continuously optimize the model and improve its accuracy. Before training, the dataset is preprocessed using 2D discrete wavelet decomposition and reconstruction to enhance the robustness of the network. The experimental results show that 92.4% of the mean average accuracy at IoU of 0.5 (mAP@0.5) and 67.7% of the mean average accuracy at IoU of 0.5 to 0.95 (mAP@0.5:0.95) are achieved using the BES-YOLO network, which is an increase of 5.3% and 4.4% compared to the YOLOv8n model. The research results can effectively improve the detection accuracy and efficiency of multi-scale targets in side-scan sonar images, which can be applied to AUVs and other underwater platforms to implement intelligent detection of undersea targets.

[Retracted] Effects of Grb2­associated binding protein 2­specific siRNA on the migration and invasion of MG­63 osteosarcoma cells.

[This retracts the article DOI: 10.3892/ol.2017.7375.].

Development and validation of a machine learning-based readmission risk prediction model for non-ST elevation myocardial infarction patients after percutaneous coronary intervention.

To investigate the factors that influence readmissions in patients with acute non-ST elevation myocardial infarction (NSTEMI) after percutaneous coronary intervention (PCI) by using multiple machine learning (ML) methods to establish a predictive model. In this study, 1576 NSTEMI patients who were hospitalized at the Affiliated Hospital of North Sichuan Medical College were selected as the research subjects. They were divided into two groups: the readmitted group and the non-readmitted group. The division was based on whether the patients experienced complications or another incident of myocardial infarction within one year after undergoing PCI. Common variables selected by univariate and multivariate logistic regression, LASSO regression, and random forest were used as independent influencing factors for NSTEMI patients' readmissions after PCI. Six different ML models were constructed using these common variables. The area under the ROC curve, accuracy, sensitivity, and specificity were used to evaluate the performance of the six ML models. Finally, the optimal model was selected, and a nomogram was created to visually represent its clinical effectiveness. Three different methods were used to select seven representative common variables. These variables were then utilized to construct six different ML models, which were subsequently compared. The findings indicated that the LR model exhibited the most optimal performance in terms of AUC, accuracy, sensitivity, and specificity. The outcome, admission mode (walking and non-walking), communication ability, CRP, TC, HDL, and LDL were identified as independent predicators of readmissions in NSTEMI patients after PCI. The prediction model constructed by the LR algorithm was the best. The established column graph model established proved to be effective in identifying high-risk groups with high accuracy and differentiation. It holds a specific predictive value for the occurrence of readmissions after direct PCI in NSTEMI patients.

Attosecond chronoscopy of the photoemission near a bandgap of a single-element layered dielectric.

We report on the energy dependence of the photoemission time delay from the single-element layered dielectric HOPG (highly oriented pyrolytic graphite). This system offers the unique opportunity to directly observe the Eisenbud-Wigner-Smith (EWS) time delays related to the bulk electronic band structure without being strongly perturbed by ubiquitous effects of transport, screening, and multiple scattering. We find the experimental streaking time shifts to be sensitive to the modulation of the density of states in the high-energy region (E ≈ 100 eV) of the band structure. The present attosecond chronoscopy experiments reveal an energy-dependent increase of the photoemission time delay when the final state energy of the excited electrons lies in the vicinity of the bandgap providing information difficult to access by conventional spectroscopy. Accompanying simulations further corroborate our interpretation.

Research progress on the mechanism of acupuncture on type â ¡ diabetes mellitus. / é’ˆåˆºæ²»ç–—â ¡åž‹ç³–å°¿ç— æ•ˆåº”æœºåˆ¶ç ”ç©¶è¿›å±•.

Acupuncture is an effective measure for treating type 2 diabetes mellitus (T2DM). Many studies have shown that acupuncture can reduce blood glucose in patients with T2DM, but its mechanism is still unclear. This review summarized the mechanism of acupuncture on T2DM, the mechanisms of acupuncture in treating T2DM is related to improving insulin resistance, regulating inflammation, promoting insulin secretion, improving lipid metabolism disorders, resisting oxidative stress, improving obesity, controlling intestinal flora, and regulating the nervous system. At the same time, this review also points out the lack of current relevant research and the future research directions to provide a reference for further exploring the mechanism of acupuncture hypoglycemic action.

Association between remote resistance exercises programs delivered by a smartphone application and skeletal muscle mass among elderly patients with type 2 diabetes- a retrospective real-world study.

Objective: We aimed to explore the relationship between remote resistance exercise programs delivered via a smartphone application and skeletal muscle mass among elderly patients with type 2 diabetes, utilizing real-world data. Methods: The resistance exercises were provided through Joymotion®, a web-based telerehabilitation smartphone application (Shanghai Medmotion Medical Management Co., Ltd). The primary outcome was the changes in skeletal muscle index (SMI) before and after the remote resistance exercises programs. The secondary outcomes were changes in skeletal muscle cross-sectional area (SMA), skeletal muscle radiodensity (SMD) and intermuscular adipose tissue (IMAT). Results: A total of 101 elderly patients with type 2 diabetes were analyzed. The participants had an average age of 72.9 ± 6.11 years for males and 74.4 ± 4.39 years for females. The pre- and post-intervention SMI mean (± SE) was 31.64 ± 4.14 vs. 33.25 ± 4.22 cm2/m2 in male, and 22.72 ± 3.24 vs. 24.28 ± 3.60 cm2/m2 in female respectively (all P < 0.001). Similarly, a statistically significant improvement in SMA, IMAT, and SMD for both male and female groups were also observed respectively (P < 0.001). Multiple linear regression models showed potential confounding factors of baseline hemoglobin A1c and duration of diabetes with changes in SMI in male, while hemoglobin A1c and high density lipoprotein cholesterol with changes in SMI in female. Conclusion: Remote resistance exercises programs delivered by a smartphone application were feasible and effective in helping elderly patients with type 2 diabetes to improve their skeletal muscle mass.

Co-Doped Porous Carbon/Carbon Nanotube Heterostructures Derived from ZIF-L@ZIF-67 for Efficient Microwave Absorption.

Carbon-based magnetic metal composites derived from metal-organic frameworks (MOFs) are promising materials for the preparation of broadband microwave absorbers. In this work, the leaf-like co-doped porous carbon/carbon nanotube heterostructure was obtained using ZIF-L@ZIF-67 as precursor. The number of carbon nanotubes can be controlled by varying the amount of ZIF-67, thus regulating the dielectric constant of the sample. An optimum reflection loss of -42.2 dB is attained when ZIF-67 is added at 2 mmol. An effective absorption bandwidth (EAB) of 4.8 GHz is achieved with a thickness of 2.2 mm and a filler weight of 12%. The excellent microwave absorption (MA) ability is generated from the mesopore structure, uniform heterogeneous interfaces, and high conduction loss. The work offers useful guidelines to devise and prepare such nanostructured materials for MA materials.

Chinese college students' PGD symptoms and their relationship to cognitive variables: a latent profile analysis.

Bereavement is a commonly experienced grief event; however, bereavement can also trigger a number of psychological consequences, such as prolonged grief disorder (PGD). At present, the differences in prolonged grief disorder symptoms (PGD symptoms) among various individuals and how those symptoms relate to cognitive variables are unclear. In the present study, 817 Chinese college students with bereavement experience were selected as participants. Based on the evaluation results of their irrational beliefs, bereavement-related irrational beliefs, basic world assumptions, and PGD symptoms, an individual-centered latent profile analysis was used to divide a group with PGD symptoms into several subgroups and comprehensively examine the relationships between these subgroups and cognitive variables. (1) The severity of PGD symptoms among Chinese college students can be categorized into three subgroups: mild, moderate, and severe. (2) Cognitive variables such as irrational beliefs and basic world assumptions were all found to correlate with the severity of PGD symptoms; bereavement-related irrational beliefs was the variable with the largest correlation. However, for the first time, this study found that different dimensions of basic world assumptions had different directions of correlation, based on the severity of the PGD symptoms. Justice, control, randomness, and self-control had significantly positive correlations. Conversely, benevolence of the world, benevolence of people, and worthiness of the self had significantly negative correlations. These results have important reference value for cognitive behavioral therapy (CBT) treatment and interventions for PGD issues in Chinese college students.

Layer-specific mechanisms of perfluoroalkyl acid (PFAA) transport and partition in estuarine environments: Unveiling the depth-dependent differences.

Understanding of characteristics and transport of perfluoroalkyl acids (PFAAs) in heterogeneous estuarine environments is limited. Furthermore, the role of suspended particles (SPS) in different layers remains unclear. This study explores the multiphase distribution process and mechanism of PFAAs controlled by SPS across surface and bottom layers in five small estuaries. Peaks in PFAA concentrations are consistently observed at strongly stratified sites. Concentrations of the PFAAs in both surface and bottom SPS decreased as the degree of mixing increased from strongly stratified levels to well-mixed levels. The water-SPS partitioning of some short-chain PFAAs (PFBS, PFHxA, and PFHpA) is influenced by environmental factors (pH, depth, temperature, and salinity) due to electrostatic interactions, while the sorption of some long-chain PFAAs (PFOA, PFOS, and PFNA) is controlled by SPS and dissolved organic carbon (OC), driven by hydrophobic interactions. Additionally, SPS dominates OC transport in estuarine systems, except in sandy sediment environments. SPS plays a dominant role in PFAA partitioning in both surface and bottom water-SPS systems (p < 0.05), and salinity only significantly affects PFBS in bottom layer (p < 0.01). These findings are critical for understanding the drivers of PFAA partitioning and the roles of SPS in different layers, underscoring the necessity of considering particle-associated PFAA fractions in future coastal environmental management.

Zinc ions regulate mitochondrial quality control in neurons under oxidative stress and reduce PANoptosis in spinal cord injury models via the Lgals3-Bax pathway.

Spinal cord injury is a serious traumatic nervous system disorder characterized by extensive neuronal apoptosis. Oxidative stress, a key factor in neuronal apoptosis, leads to the accumulation of reactive oxygen species, making mitochondrial quality control within cells crucial. Previous studies have demonstrated zinc's anti-inflammatory and anti-apoptotic properties in protecting mitochondria during spinal cord injury treatment, yet the precise mechanisms remain elusive. Single-cell sequencing analysis has identified Lgals3 and Bax as core genes in apoptosis. This study aimed to investigate whether zinc ions protect intracellular mitochondria by inhibiting the apoptotic proteins Lgals3 and Bax. We elucidated zinc ions' key role in mitigating mitochondrial quality control dysfunction triggered by oxidative stress and confirmed this was achieved by targeting the Lgals3-Bax pathway. Zinc's inhibitory effect on this pathway not only preserved mitochondrial integrity but also significantly reduced PANoptosis after spinal cord injury. Under oxidative stress, zinc ion regulation of mitochondrial quality control reveals an organelle-targeted therapeutic strategy, offering a novel approach for more precise treatment of spinal cord injury.

Developing excellent plantar pressure sensors for monitoring human motions by using highly compressible and resilient PMMA conductive iongels.

Based on real-time detection of plantar pressure, gait recognition could provide important health information for rehabilitation administration, fatigue prevention, and sports training assessment. So far, such researches are extremely limited due to lacking of reliable, stable and comfortable plantar pressure sensors. Herein, a strategy for preparing high compression strength and resilience conductive iongels has been proposed by implanting physically entangled polymer chains with covalently cross-linked networks. The resulting iongels have excellent mechanical properties including nice compliance (young's modulus < 300 kPa), high compression strength (>10 MPa at a strain of 90 %), and good resilience (self-recovery within seconds). And capacitive pressure sensor composed by them possesses excellent sensitivity, good linear response even under very small stress (∼kPa), and long-term durability (cycles > 100,000) under high-stress conditions (133 kPa). Then, capacitive pressure sensor arrays have been prepared for high-precision detection of plantar pressure spatial distribution, which also exhibit excellent sensing performances and long-term stability. Further, an extremely sensitive and fast response plantar pressure monitoring system has been designed for monitoring plantar pressure of foot at different postures including upright, forward and backward. The system achieves real-time tracking and monitoring of changes of plantar pressure during different static and dynamic posture processes. And the characteristics of plantar pressure information can be digitally and photography displayed. Finally, we propose an intelligent framework for real-time detection of plantar pressure by combining electronic insoles with data analysis system, which presents excellent applications in sport trainings and safety precautions.

Neutrophil Extracellular Traps Regulate Surgical Brain Injury by Activating the cGAS-STING Pathway.

Surgical brain injury (SBI), induced by neurosurgical procedures or instruments, has not attracted adequate attention. The pathophysiological process of SBI remains sparse compared to that of other central nervous system diseases thus far. Therefore, novel and effective therapies for SBI are urgently needed. In this study, we found that neutrophil extracellular traps (NETs) were present in the circulation and brain tissues of rats after SBI, which promoted neuroinflammation, cerebral edema, neuronal cell death, and aggravated neurological dysfunction. Inhibition of NETs formation by peptidylarginine deiminase (PAD) inhibitor or disruption of NETs with deoxyribonuclease I (DNase I) attenuated SBI-induced damages and improved the recovery of neurological function. We show that SBI triggered the activation of cyclic guanosine monophosphate-adenosine monophosphate synthase stimulator of interferon genes (cGAS-STING), and that inhibition of the cGAS-STING pathway could be beneficial. It is worth noting that DNase I markedly suppressed the activation of cGAS-STING, which was reversed by the cGAS product cyclic guanosine monophosphate-adenosine monophosphate (cGMP-AMP, cGAMP). Furthermore, the neuroprotective effect of DNase I in SBI was also abolished by cGAMP. NETs may participate in the pathophysiological regulation of SBI by acting through the cGAS-STING pathway. We also found that high-dose vitamin C administration could effectively inhibit the formation of NETs post-SBI. Thus, targeting NETs may provide a novel therapeutic strategy for SBI treatment, and high-dose vitamin C intervention may be a promising translational therapy with an excellent safety profile and low cost.

HyGAnno: hybrid graph neural network-based cell type annotation for single-cell ATAC sequencing data.

Reliable cell type annotations are crucial for investigating cellular heterogeneity in single-cell omics data. Although various computational approaches have been proposed for single-cell RNA sequencing (scRNA-seq) annotation, high-quality cell labels are still lacking in single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) data, because of extreme sparsity and inconsistent chromatin accessibility between datasets. Here, we present a novel automated cell annotation method that transfers cell type information from a well-labeled scRNA-seq reference to an unlabeled scATAC-seq target, via a parallel graph neural network, in a semi-supervised manner. Unlike existing methods that utilize only gene expression or gene activity features, HyGAnno leverages genome-wide accessibility peak features to facilitate the training process. In addition, HyGAnno reconstructs a reference-target cell graph to detect cells with low prediction reliability, according to their specific graph connectivity patterns. HyGAnno was assessed across various datasets, showcasing its strengths in precise cell annotation, generating interpretable cell embeddings, robustness to noisy reference data and adaptability to tumor tissues.

Construction and validation of somatic mutation-derived long non-coding RNAs signatures of genomic instability to predict prognosis of hepatocellular carcinoma.

BACKGROUND: Long non-coding RNAs (LncRNAs) have been found to be a potential prognostic factor for cancers, including hepatocellular carcinoma (HCC). Some LncRNAs have been confirmed as potential indicators to quantify genomic instability (GI). Nevertheless, GI-LncRNAs remain largely unexplored. This study established a GI-derived LncRNA signature (GILncSig) that can predict the prognosis of HCC patients. AIM: To establish a GILncSig that can predict the prognosis of HCC patients. METHODS: Identification of GI-LncRNAs was conducted by combining LncRNA expression and somatic mutation profiles. The GI-LncRNAs were then analyzed for functional enrichment. The GILncSig was established in the training set by Cox regression analysis, and its predictive ability was verified in the testing set and TCGA set. In addition, we explored the effects of the GILncSig and TP53 on prognosis. RESULTS: A total of 88 GI-LncRNAs were found, and functional enrichment analysis showed that their functions were mainly involved in small molecule metabolism and GI. The GILncSig was constructed by 5 LncRNAs (miR210HG, AC016735.1, AC116351.1, AC010643.1, LUCAT1). In the training set, the prognosis of high-risk patients was significantly worse than that of low-risk patients, and similar results were verified in the testing set and TCGA set. Multivariate Cox regression analysis and stratified analysis confirmed that the GILncSig could be used as an independent prognostic factor. Receiver operating characteristic curve analysis of the GILncSig showed that the area under the curve (0.773) was higher than the two LncRNA signatures published recently. Furthermore, the GILncSig may have a better predictive performance than TP53 mutation status alone. CONCLUSION: We established a GILncSig that can predict the prognosis of HCC patients, which will help to guide prognostic evaluation and treatment decisions.

Ingenious Modulation of Third-Order Nonlinear Optical Response of Zr-MOFs through Defect Engineering Based on a Mixed-Linker Strategy.

Defect engineering plays a pivotal role in regulating electronic structure and facilitating charge transfer, yielding captivating effects on third-order nonlinear optical (NLO) properties. In this work, we utilized a mixed-linker strategy to intentionally disrupt the initial periodic arrangement of UiO-66 and construct defects. Specifically, we incorporated tetrakis(4-carboxyphenyl)porphyrin (TCPP) with an exceptionally electron-rich delocalization system into the framework of UiO-66 using a one-pot solvothermal method, ingeniously occupying the partial distribution sites of the Zr6 clusters. Compared to UiO-66, the NLO absorption and refraction performance of TCPP/UiO-66 were significantly improved. Additionally, due to the presence of nitrogen-rich sites that can accommodate metal ions in the porphyrin ring of TCPP, Co(II), Ni(II), Cu(II), and Zn(II) are introduced into TCPP/UiO-66, extending the d-π conjugation effect to further regulate the defects. The NLO absorption behavior transforms saturation absorption (SA) to reverse saturation absorption (RSA), while the refraction behavior shifts from self-defocusing to self-focusing. This work shows that defects can effectively regulate the electronic structure, while TCPP plays a crucial role in significantly enhancing electron delocalization.

Carbon wet deposition flux and river carbon output in a forest watershed in permafrost region of the Da Xing'an Mountains.

Carbon wet deposition and river carbon output in river basins are important components of global carbon cycle. The assessment of both properties is of great significance for regional carbon budget. However, research on these topics in high-latitude permafrost regions in China is still lacking. We conducted dynamic monitoring of carbon wet deposition and carbon output in the river from May 28th to October 30th, 2022, in Laoyeling watershed, a typical forested watershed in the Da Xing'an Mountains permafrost region. We analyzed the variations of carbon component concentrations and fluxes in precipitation and river water, and estimated the contribution of carbon wet deposition to carbon output in the watershed. The results showed that wet deposition fluxes of dissolved organic carbon (DOC), dissolved inorganic carbon (DIC), and total dissolved carbon (TDC) in the Laoyeling watershed were 1354.86, 684.59, and 2039.45 kg·km-2, respectively. The fluxes of DOC, DIC, TDC, particulate organic carbon (POC), particulate inorganic carbon (PIC), and total carbon (TC) in the river were 601.75, 1977.30, 2579.05, 125.13, 21.99, and 2726.17 kg·km-2, respectively. The contribution of TDC wet deposition to the river TDC output was 9941.89 kg, accounting for 17.6% of total output. The DIC concentration in the river showed significant seasonal differences, with increased runoff resulting from precipitation leading to a decrease in DIC concentration in the river and showing a clear dilution effect, while the concentrations of DOC, POC, and PIC increased, mainly due to erosion effect. In conclusion, carbon wet deposition flux in the Laoyeling watershed was mainly determined by precipitation, and its contribution to river carbon output was relatively small compared to other factor. Runoff was the dominant factor affecting river carbon output. The results would provide important insights into carbon cycling and carbon budget balance in permafrost regions under climate change.