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Abstract Liver kinase B1 (LKB1) is a serine/threonine kinase controlling cell homeostasis. Among post-translational modification, Sumoylation is vital for LKB1 activating adenosine 5’-monophosphate (AMP)-activated protein kinase (AMPK), the key regulator in energy metabolism. Of note, AMPK-regulated fatty acid metabolism is highly involved in maintaining normal renal function. However, the regulative mechanisms of LKB1 Sumoylation remain elusive. In this study, we demonstrated that β-catenin, a notorious signal in renal fibrosis, inhibited the Sumoylation of LKB1, thereby disrupting fatty acid oxidation in renal tubular cells and triggering renal fibrosis. Mechanically, we found that Sumo3 was the key mediator for LKB1 Sumoylation in renal tubular cells, which was transcriptionally inhibited by β-catenin/Transcription factor 4 (TCF4) signaling. Overexpression of Sumo3, not Sumo1 or Sumo2, restored β-catenin-disrupted fatty acid metabolism, and retarded lipid accumulation and fibrogenesis in the kidney. In vivo, conditional knockout of β-catenin in tubular cells effectively preserved fatty acid oxidation and blocked lipid accumulation by maintaining LKB1 Sumoylation and AMPK activation. Furthermore, ectopic expression of Sumo3 strongly inhibited Wnt1-aggravated lipid accumulation and fibrogenesis in unilateral ischemia-reperfusion mice. In patients with chronic kidney disease, we found a loss of Sumo3 expression, and it was highly related to LKB1 repression. This contributes to fatty acid metabolism disruption and lipid accumulation, resulting in renal fibrosis. Overall, our study revealed a new mechanism in fatty acid metabolism dysfunction and provided a new therapeutic target pathway for regulating Sumo modification in renal fibrosis.

Abstract Background Coronary artery bypass grafting is associated with a high occurrence of postoperative cardiopulmonary complications. Preliminary evidence suggested that enhanced recovery after surgery can effectively reduce the occurrence of postoperative cardiopulmonary complications. However, enhanced recovery after surgery with systematic integration of cardiopulmonary rehabilitation (ERAS-CaRe) into for Coronary artery bypass grafting has not been evaluated so far. We thus design the ERAS-CaRe randomized-controlled trial to evaluate possible superiority of embedding cardiopulmonary rehabilitation in ERAS over ERAS alone as well as to investigate effects of differential timing of cardiopulmonary rehabilitation within enhanced recovery after surgery (pre-, post-, perio-operative) on post-operative cardiopulmonary complications following Coronary artery bypass grafting surgery. Methods ERAS-CaRe is a pragmatic, randomized-controlled, parallel four-arm, clinical trial. Three hundred sixty patients scheduled for Coronary artery bypass grafting in two Chinese hospitals will be grouped randomly into (i) Standard enhanced recovery after surgery or (ii) pre-operative ERAS-CaRe or (iii) post-operative ERAS-CaRe or (iv) perio-operative ERAS-CaRe. Primary outcome is the occurrence of cardiopulmonary complications at 10 days after Coronary artery bypass grafting. Secondary outcomes include the occurrence of other individual complications including cardiac, pulmonary, stroke, acute kidney injury, gastrointestinal event, ICU delirium rate, reintubation rate, early drainage tube removal rate, unplanned revascularization rate, all-cause mortality, ICU readmission rate, plasma concentration of myocardial infarction-related key biomarkers etc. Discussion The trial is designed to evaluate the hypothesis that a cardiopulmonary rehabilitation based enhanced recovery after surgery program reduces the occurrence of cardiopulmonary complications following Coronary artery bypass grafting and to determine optimal timing of cardiopulmonary rehabilitation within enhanced recovery after surgery. The project will contribute to increasing the currently limited knowledge base in the field as well as devising clinical recommendations. Trial registration The trial was registered at the Chinese Clinical Trials Registry on 25 August 2023 (ChiCTR2300075125; date recorded: 25/8/2023, https://www.chictr.org.cn/ ).

Abstract Two-dimensional (2D) materials, as adsorbents, have garnered great attention in removing heavy metal ions (HMIs) from drinking water due to their extensive exposed adsorption sites. Nevertheless, there remains a paucity of experimental research to remarkably unlock their adsorption capabilities and fully elucidate their adsorption mechanisms. In this work, exceptional lead ion (Pb2+) (a common HMI) removal capacity (up to 758 mg g−1) is achieved using our synthesized metallic 1T/1T′ phase 2D transition metal dichalcogenide (TMD, including MoS2, WS2, TaS2, and TiS2) nanosheets, which hold tremendous activated S chemisorption sites. The residual Pb2+ concentration can be reduced from 2 mg L−1 to 2 μg L−1 within 0.5 min, meeting the drinking water standards following World Health Organization guideline (Pb2+ concentrations

Abstract Background Decellularized extracellular matrix (dECM) is an intriguing natural biomaterial that has garnered significant attention due to its remarkable biological properties. In our study, we employed a cell-matrixed nerve graft for the repair of sciatic nerve defects in rats. The efficacy of this approach was assessed, and concurrently, the underlying molecular regulatory mechanisms were explored to elucidate how such grafts facilitate nerve regeneration. Long noncoding RNAs (lncRNAs) regulate mRNA expression via multiple mechanisms, including post-transcriptional regulation, transcription factor effects, and competitive binding with miRNAs. These interactions between lncRNAs and mRNAs facilitate precise control of gene expression, allowing organisms to adapt to varying biological environments and physiological states. By investigating the expression profiles and interaction dynamics of mRNAs and lncRNAs, we can enhance our understanding of the molecular mechanisms through which cell-matrixed nerve grafts influence neural repair. Such studies are pivotal in uncovering the intricate networks of gene regulation that underpin this process. Results Weighted gene co-expression network analysis (WGCNA) utilizes clustering algorithms, such as hierarchical clustering, to aggregate genes with similar expression profiles into modules. These modules, which potentially correspond to distinct biological functions or processes, can subsequently be analyzed for their association with external sample traits. By correlating gene modules with specific conditions, such as disease states or responses to treatments, WGCNA enables a deeper understanding of the genetic architecture underlying various phenotypic traits and their functional implications. We identified seven mRNA modules and five lncRNA modules that exhibited associations with treatment or time-related events by WGCNA. We found the blue (mRNAs) module which displayed a remarkable enrichment in “axonal guidance” and “metabolic pathways”, exhibited strong co-expression with multiple lncRNA modules, including blue (related to “GnRH secretion” and “pyrimidine metabolism”), green (related to “arginine and proline metabolism”), black (related to “nitrogen metabolism”), grey60 (related to “PPAR signaling pathway”), and greenyellow (related to “steroid hormone biosynthesis”). All of the top 50 mRNAs and lncRNAs exhibiting the strongest correlation were derived from the blue module. Validation of key molecules were performed using immunohistochemistry and qRT-PCR. Conclusion Revealing the principles and molecular regulatory mechanisms of the interaction between materials and biological entities, such as cells and tissues, is a direction for the development of biomimetic tissue engineering technologies and clinically effective products.

Abstract Background Periodontal ligament stem cells (PDLSCs) are important seed cells in tissue engineering and clinical applications. They are the priority receptor cells for sensing various mechanical stresses. Yes-associated protein (YAP) is a recognized mechanically sensitive transcription factor. However, the role of YAP in regulating the fate of PDLSCs under tension stress (TS) and its underlying mechanism is still unclear. Methods The effects of TS on the morphology and fate of PDLSCs were investigated using fluorescence staining, transmission electron microscopy, flow cytometry and quantitative real-time polymerase chain reaction (qRT-PCR). Then qRT-PCR, western blotting, immunofluorescence staining and gene knockdown experiments were performed to investigate the expression and distribution of YAP and its correlation with PDLSCs proliferation. The effects of cytoskeleton dynamics on YAP nuclear translocation were subsequently explored by adding cytoskeleton inhibitors. The effect of cytoskeleton dynamics on the expression of the LINC complex was proved through qRT-PCR and western blotting. After destroying the LINC complex by adenovirus, the effects of the LINC complex on YAP nuclear translocation and PDLSCs proliferation were investigated. Mitochondria-related detections were then performed to explore the role of mitochondria in YAP nuclear translocation. Finally, the in vitro results were verified by constructing orthodontic tooth movement models in Sprague-Dawley rats. Results TS enhanced the polymerization and stretching of F-actin, which upregulated the expression of the LINC complex. This further strengthened the pull on the nuclear envelope, enlarged the nuclear pore, and facilitated YAP’s nuclear entry, thus enhancing the expression of proliferation-related genes. In this process, mitochondria were transported to the periphery of the nucleus along the reconstructed microtubules. They generated ATP to aid YAP’s nuclear translocation and drove F-actin polymerization to a certain degree. When the LINC complex was destroyed, the nuclear translocation of YAP was inhibited, which limited PDLSCs proliferation, impeded periodontal tissue remodeling, and hindered tooth movement. Conclusions Our study confirmed that appropriate TS could promote PDLSCs proliferation and periodontal tissue remodeling through the mechanically driven F-actin/LINC complex/YAP axis, which could provide theoretical guidance for seed cell expansion and for promoting healthy and effective tooth movement in clinical practice.

Cancer is a formidable threat to human life, a cure for which in advanced stages remains challenging. Early detection and treatment of cancer are paramount, yet a substantial number of cancer patients receive diagnoses at an advanced stage, resulting in a lower 5-year survival rate. Early-stage cancers, however, frequently elude detection. Conventional tumor screening techniques, such as tumor biopsy, serve as essential means for an early cancer diagnosis. However, these procedures are invasive and may inadvertently facilitate cancer metastasis. A current research focal point involves liquid biopsy technologies, offering a potential solution to mitigate the above-mentioned issues, but often exhibiting low sensitivity. A research team from the Massachusetts Institute of Technology has recently pioneered an innovative approach to enhance the sensitivity of liquid biopsy for cancer diagnosis. By administering a pre-treatment agent 1–2 h prior to sampling, a greater than 10-fold increase in collected ctDNA was obtained. Subsequent tumor analysis using ctDNA not only demonstrated heightened sensitivity in detecting small tumors (>75%) but also presented a promising avenue for early clinical cancer detection and diagnosis. This discovery holds significant potential for advancing the prospects of early cancer detection, diagnosis, and treatment.

Zinc (Zn) alloys have demonstrated significant potential in healing critical-sized bone defects. However, the clinical application of Zn alloys implants is still hindered by challenges including excessive release of zinc ions (Zn2+), particularly in the early stage of implantation, and absence of bio-functions related to complex bone repair processes. Herein, a biodegradable aliphatic polycarbonate drug-eluting coating was fabricated on zinc-lithium (Zn–Li) alloys to inhibit Zn2+ release and enhance the osteogenesis, angiogenesis, and bacteriostasis of Zn alloys. Specifically, the photo-curable aliphatic polycarbonates were co-assembled with simvastatin and deposited onto Zn alloys to produce a drug-loaded coating, which was crosslinked by subsequent UV light irradiation. During the 60 days long-term immersion test, the coating showed distinguished stable drug release and Zn2+ release inhibition properties. Benefiting from the regulated release of Zn2+ and simvastatin, the coating facilitated the adhesion, proliferation, and differentiation of MC3T3-E1 cells, as well as the migration and tube formation of EA.hy926 cells. Astonishingly, the coating also showed remarkable antibacterial properties against both S. aureus and E. coli. The in vivo rabbit critical-size femur bone defects model demonstrated that the drug-eluting coating could efficiently promote new bone formation and the expression of platelet endothelial cell adhesion molecule-1 (CD31) and osteocalcin (OCN). The enhancement of osteogenesis, angiogenesis, and bacteriostasis is achieved by precisely controlling of the released Zn2+ at an appropriate level, as well as the stable release profile of simvastatin. This tailored aliphatic polycarbonate drug-eluting coating provides significant potential for clinical applications of Zn alloys implants.

Abstract This present research aims to clarify the intricate conjunction of enterprise social media (ESM) utilization and employee agility with a main focus on uncovering the underlying mechanisms that work through the mediating influence of work engagement and the moderating influence of regulatory focus. Drawing upon regularity focus theory, 353 Chinese samples of ESM users in organizational contexts are analyzed using SPSS 23.0. The empirical findings substantiate a robust and significant positive linkage between ESM usage and worker agility. Further reinforcing the model, the mediating role of work engagement is established as it channels the impact of ESM usage on worker agility. Turning to the moderating effects, the study unveils the differential impact of prevention focus and promotion focus, wherein individuals with a lower prevention focus exhibit a more pronounced positive linkage between ESM usage and worker agility. Similarly, individuals with a higher promotion focus demonstrate a heightened positive association between ESM usage and worker agility. By comprehensively inspecting the intricate dynamics of ESM usage, work engagement, and regulatory focus, this study enhances our theoretical understanding of how these factors synergistically shape employee agility, ultimately furnishing organizations with invaluable insights to foster and cultivate an agile workforce.

Context: Polygonum hydropiper L. (P. hydropiper) has outstanding clinical efficacy in treating both acute and chronic gastroenteritis. However, the definite mechanism remains unclear. Objective: This study aimed to explore the potential mechanisms of the total flavonoid of P. hydropiper (FPH) in stress-induced gastric mucosal damage (SGMD) rats through a combination of network pharmacology, molecular docking, and animal experiments. Methods: Network pharmacology and molecular docking were utilized to predict the potential mechanisms of FPH against SGMD. In experimental studies, SGMD rat models were established using water-immersion restraint stress (WIRS). FPH was administered at doses of 140, 70, and 35 mg/kg, with ranitidine serving as a positive control, through gavage once daily for 6 consecutive days after model establishment. Stomach and serum specimens were analyzed using HE staining, Western blotting, qPCR, and ELISA to investigate the protective mechanism of FPH in SGMD. Results: The network pharmacology analysis identified 16 active ingredients and 183 common targets, with potential pathways including PI3K/Akt, MAPK and Keap1/Nrf2. In vivo experiments demonstrated that FPH intervention alleviated SGMD pathological changes, reduced elevated serum IL-6 and TNF-α levels, and enhanced SOD and GSH activity in rats. Additionally, FPH increased the protein expression of p62, Nrf2, HO-1, PI3K, and p-Akt, along with mRNA levels of Nrf2, p62, and HO-1. Conclusions: FPH exerts a gastric mucosal protective effect by upregulating antioxidant gene expression through the PI3K/Akt and Keap1/Nrf2 pathways. This study provides an experimental basis for the potential clinical treatment of SGMD with the traditional Chinese medicine P. hydropiper.

Abstract The degradation of earthen sites due to natural and human factors has become a pressing issue, necessitating urgent protection measures. In this context, accurate assessment of the vulnerability of earthen sites is essential for the development of effective conservation strategies. In this study, a comprehensive evaluation framework that incorporates multiple indicators is proposed. In particular, the entropy weight- (Technique for Order Preference by Similarity to an Ideal Solution) TOPSIS method is employed for quantitative vulnerability assessment and combined with K-means clustering to define vulnerability levels for earthen sites. To validate the proposed approach, the vulnerability of 29 sections of the Ming Great Wall is evaluated. Eventually, the 29 earthen sites are categorized into three levels: high, medium, and low, according to their degree of vulnerability. The results of gray correlation analysis and entropy weight-TOPSIS method are compared using the ontology missing amount in the original data as the validation standard. The results show that the Pearson correlation coefficient value of the entropy weight-TOPSIS method with the ontology missing amount was 0.859, while the Pearson correlation coefficient value of the gray correlation analysis method with the ontology missing amount was 0.691, so that the results of the entropy weight-TOPSIS method can more accurately reflect the actual vulnerability of earthen sites.

Abstract Background This study investigates the therapeutic mechanisms of dendrobine, a primary bioactive compound in Dendrobium nobile, for Metabolic Associated Fatty Liver Disease (MASLD) management. Utilizing network pharmacology combined with experimental validation, the clinical effectiveness of dendrobine in MASLD treatment was assessed and analyzed. Results The study demonstrates significant improvement in liver function among MASLD patients treated with Dendrobium nobile. Network pharmacology identified key targets such as Peroxisome Proliferator-Activated Receptor Gamma (PPARG), Interleukin 6 (IL6), Tumor Necrosis Factor (TNF), Interleukin 1 Beta (IL1B), and AKT Serine/Threonine Kinase 1 (AKT1), with molecular docking confirming their interactions. Additionally, dendrobine significantly reduced ALT and AST levels in palmitic acid-treated HepG2 cells, indicating hepatoprotective properties and amelioration of oxidative stress through decreased Malondialdehyde (MDA) levels and increased Superoxide Dismutase (SOD) levels. Conclusion Dendrobine mitigates liver damage in MASLD through modulating inflammatory and immune responses and affecting lipid metabolism, potentially by downregulating inflammatory mediators like TNF, IL6, IL1B, and inhibiting AKT1 and Signal Transducer and Activator of Transcription 3 (STAT3). This study provides a theoretical basis for the application of dendrobine in MASLD treatment, highlighting its potential as a therapeutic agent.

In this study, donepezil hydrochloride (DZ HCl), a crucial medication for the treatment of Alzheimer's disease, is detected using a new sensor built on CuO-TiO2 hybrid nanostructures. The sensor showed improved performance characteristics with a computed limit of quantitation of 0.211 and a limit of detection of 0.063. These qualities included improved stability, selectivity, and sensitivity. The fabrication process demonstrated repeatability, with a 4.27% relative standard deviation. After 10 successive readings, the sensor maintained 95% of its initial response, demonstrating its long-term stability. By quantifying DZ HCl in urine samples, the practical applicability of the sensor was confirmed. Remarkably, the sensor achieved a remarkable recovery rate of 97.00–99.41% and a suitable relative standard deviation range of 3.29–4.71%. The results of this work contribute to the development of trustworthy electrochemical sensors for medicinal chemicals and have prospective uses in pharmacological, biological, and therapeutic fields.

Abstract The emergence of microhemispherical resonant gyroscopes, which integrate the advantages of exceptional stability and long lifetime with miniaturization, has afforded new possibilities for the development of whole-angle gyroscopes. However, existing methods used for manufacturing microhemispherical resonant gyroscopes based on MEMS technology face the primary drawback of intricate and costly processing. Here, we report the design, fabrication, and characterization of the first 3D-printable microhemispherical shell resonator for a Coriolis vibrating gyroscope. We remarkably achieve fabrication in just two steps bypassing the dozen or so steps required in traditional micromachining. By utilizing the intricate shaping capability and ultrahigh precision offered by projection microstereolithography, we fabricate 3D high-aspect-ratio resonant structures and controllable capacitive air gaps, both of which are extremely difficult to obtain via MEMS technology. In addition, the resonance frequency of the fabricated resonators can be tuned by electrostatic forces, and the fabricated resonators exhibit a higher quality factor in air than do typical MEMS microhemispherical resonators. This work demonstrates the feasibility of rapidly batch-manufacturing microhemispherical shell resonators, paving the way for the development of microhemispherical resonator gyroscopes for portable inertial navigation. Moreover, this particular design concept could be further applied to increase uptake of resonator tools in the MEMS community.

Background Multiple target‐organ damages (TODs) in the same patient are common and further increase the risk of cardiovascular disease. However, the relationship between ambulatory central systolic blood pressure (SBP) and multiple TODs has yet to be explored. Methods and Results MobilO‐Graph PWA was used to monitor the participants' ambulatory blood pressure, and the presence of left ventricular hypertrophy, carotid hypertrophy, and kidney injury were used to define TOD. Logistic regression analyses and receiver operating characteristic analyses were used to explore the correlation between SBP and TOD. Overall, 2018 nondialysis patients with chronic kidney disease were included and 580 (28.74%) had multiple TODs. Twenty‐four‐hour central SBP with c2 calibration exhibited a stronger correlation with the increasing number of TOD compared with 24‐hour brachial SBP in ordinal logistic regression analyses. In the multivariable analyses with the presence of multiple TODs, the odds ratios were 1.786 (95% CI, 1.474–2.165; P

Key Clinical Message Maxillary canines are often impacted, which can result in tooth disorders and adversely affect occlusal and facial development. The case report describes complete bilateral impaction of maxillary canines and significant root resorption of a central incisor. The multidisciplinary approach is the optimal strategy for addressing impacted maxillary canines.

Summary: Chronic kidney disease (CKD) raises major concerns for global public health as it is characterized by high prevalence, low awareness, high healthcare costs, and poor prognosis. Therefore, our study prospectively established and validated native T1 mapping-based radiomics models for the prediction of renal fibrosis and renal function in patients with CKD. Moreover, the area under the receiver operating characteristic curve (AUC) and diagnostic sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were used to evaluate its performance. Thus, our results show that radiomics based on native T1 mapping images can better identify renal function and renal fibrosis in patients with CKD and outperform conventional T1 mapping parameters of ΔT1 and T1%, thus providing more information for CKD management and clinical decision-making.

A fundamental question in the study of happiness is whether there is neural evidence to support a well-known hypothesis that happy people are always similar while unfortunate people have their own misfortunes. To investigate this, we employed several happiness-related questionnaires to identify potential components of happiness, and further investigated and confirmed their associations with personality, mood, aggressive behaviors, and amygdala reactivity to fearful faces within a substantial sample size of college students (n = 570). Additionally, we examined the functional and morphological similarities and differences among happy individuals using the inter-subject representational similarity analysis (IS-RSA). IS-RSA emphasizes the geometric properties in a high-dimensional space constructed by brain or behavioral patterns and focuses on individual subjects. Our behavioral findings unveiled two factors of happiness: individual and social, both of which mediated the effect of personality traits on individual aggression. Subsequently, mood mediated the impact of happiness on aggressive behaviors across two subgroup splits. Functional imaging data revealed that individuals with higher levels of happiness exhibited reduced amygdala reactivity to fearful faces, as evidenced by a conventional face-matching task (n = 104). Moreover, IS-RSA demonstrated that these participants manifested similar neural activation patterns when processing fearful faces within the visual pathway, but not within the emotional network (e.g., amygdala). Morphological observations (n = 425) indicated that individuals with similar high happiness levels exhibited comparable gray matter volume patterns within several networks, including the default mode network, fronto-parietal network, visual network, and attention network. Collectively, these findings offer early neural evidence supporting the proposition that happy individuals may share common neural characteristics.

Nano-TiO2 is widely used in various fields such as industry, daily necessities, food and medicine. Previous studies have shown that it can enter mammalian tissues through the digestive tract or respiratory tract and have effects on various organs and systems. However, the effect of nano-TiO2 on the mammalian thyroid gland has not been reported. In this study, we fed SD rats with rutile nano-TiO2 at a dose of 5 mg/kg body weight for 3 weeks, and then examined the thyroid histology and thyroid function of the rats. In vitro experiments were conducted to determine the effects of nano-TiO2 on the viability, apoptosis, inflammatory factors, antioxidant enzymes, and oxidative stress of human thyroid follicular epithelial cells. Histological evidence showed abnormal morphology of rat thyroid follicles and organelle damage in follicular epithelial cells. Nano-TiO2 caused a decrease in the level of sodium/iodide symporter (NIS), an increase in the level of apoptotic protein cleaved-caspase 3, and an increase in the levels of pro-inflammatory factors IL-1β and TNF-α in rat thyroid tissue. Nano-TiO2 also resulted in increased serum FT4 and TPO-Ab levels. In in vitro experiments, nano-TiO2 reduced the viability of human thyroid follicular cells, downregulated the levels and activities of antioxidant enzymes CAT, GPX1 and SOD, and increased the levels of ROS and MDA caused by oxidative stress. These results indicate that nano-TiO2 damages the structure and function of thyroid follicular epithelial cells through oxidative stress. Long-term exposure to nano-TiO2 could be a potential risk factor for thyroid dysfunction.

Abstract The design of high‐entropy single‐atom catalysts (HESAC) with 5.2 times higher entropy compared to single‐atom catalysts (SAC) is proposed, by using four different metals (FeCoNiRu‐HESAC) for oxygen reduction reaction (ORR). Fe active sites with intermetallic distances of 6.1 Å exhibit a low ORR overpotential of 0.44 V, which originates from weakening the adsorption of OH intermediates. Based on density functional theory (DFT) findings, the FeCoNiRu‐HESAC with a nitrogen‐doped sample were synthesized. The atomic structures are confirmed with X‐ray photoelectron spectroscopy (XPS), X‐ray absorption (XAS), and scanning transmission electron microscopy (STEM). The predicted high catalytic activity is experimentally verified, finding that FeCoNiRu‐HESAC has overpotentials of 0.41 and 0.37 V with Tafel slopes of 101 and 210 mVdec−1 at the current density of 1 mA cm−2 and the kinetic current densities of 8.2 and 5.3 mA cm−2, respectively, in acidic and alkaline electrolytes. These results are comparable with Pt/C. The FeCoNiRu‐HESAC is used for Zinc–air battery applications with an open circuit potential of 1.39 V and power density of 0.16 W cm−2. Therefore, a strategy guided by DFT is provided for the rational design of HESAC which can be replaced with high‐cost Pt catalysts toward ORR and beyond.

Abstract Flexible pressure sensors play a significant role in wearable devices and electronic skin. Iontronic pressure sensors with high sensitivity, wide measurement range, and high resolution can meet requirements. Based on the significant deformation characteristics of alveoli to improve compressibility, and the ability of the arch to disperse vertical pressure into horizontal thrust to increase contact area, a graded hollow ball arch (GHBA) microstructure is proposed, greatly improving sensitivity. The fabrication of GHBA ingeniously employs a double‐sided structure. One side uses mold casting to create convex structures, while the other utilizes the evaporation of moisture during the curing process to form concave structures. At the same time, a novel side‐by‐side package structure is proposed, ensuring pressure on flexible substrate is maximally transferred to the GHBA microstructure. Within the range of 0.2 Pa–300 kPa, the iontronic pressure sensor achieves a maximum sensitivity of 10 420.8 kPa−1, pressure resolution of 0.1% under the pressure of 100 kPa, and rapid response/recovery time of 40/35 ms. In wearable devices, it is capable of monitoring dumbbell curl exercises and wirelessly correcting sitting positions. In electronic skin, it can non‐contactly detect the location of the wind source and achieve object classification prediction when combined with the CNN model.

Background Left ventricular opacification (LVO) improves the accuracy of left ventricular ejection fraction (LVEF) by enhancing the visualization of the endocardium. Manual delineation of the endocardium by sonographers has observer variability. Artificial intelligence (AI) has the potential to improve the reproducibility of LVO to assess LVEF. Objectives The aim was to develop an AI model and evaluate the feasibility and reproducibility of LVO in the assessment of LVEF. Methods This retrospective study included 1305 echocardiography of 797 patients who had LVO at the Department of Ultrasound Medicine, Union Hospital, Huazhong University of Science and Technology from 2013 to 2021. The AI model was developed by 5-fold cross validation. The validation datasets included 50 patients prospectively collected in our center and 42 patients retrospectively collected in the external institution. To evaluate the differences between LV function determined by AI and sonographers, the median absolute error (MAE), spearman correlation coefficient, and intraclass correlation coefficient (ICC) were calculated. Results In LVO, the MAE of LVEF between AI and manual measurements was 2.6% in the development cohort, 2.5% in the internal validation cohort, and 2.7% in the external validation cohort. Compared with two-dimensional echocardiography (2DE), the left ventricular (LV) volumes and LVEF of LVO measured by AI correlated significantly with manual measurements. AI model provided excellent reliability for the LV parameters of LVO (ICC > 0.95). Conclusions AI-assisted LVO enables more accurate identification of the LV endocardium and reduces observer variability, providing a more reliable way for assessing LV function.

Reliable communication and intensive computing power cannot be provided effectively by temporary hot spots in disaster areas and complex terrain ground infrastructure. Mitigating this has greatly developed the application and integration of UAV and Mobile Edge Computing (MEC) to the Internet of Things (IoT). However, problems such as multi-user and huge data flow in large areas, which contradict the reality that a single UAV is constrained by limited computing power, still exist. Due to allowing UAV collaboration to accomplish complex tasks, cooperative task offloading between multiple UAVs must meet the interdependence of tasks and realize parallel processing, which reduces the computing power consumption and endurance pressure of terminals. Considering the computing requirements of the user terminal, delay constraint of a computing task, energy constraint, and safe distance of UAV, we constructed a UAV-Assisted cooperative offloading energy efficiency system for mobile edge computing to minimize user terminal energy consumption. However, the resulting optimization problem is originally nonconvex and thus, difficult to solve optimally. To tackle this problem, we developed an energy efficiency optimization algorithm using Block Coordinate Descent (BCD) that decomposes the problem into three convex subproblems. Furthermore, we jointly optimized the number of local computing tasks, number of computing offloaded tasks, trajectories of UAV, and offloading matching relationship between multi-UAVs and multiuser terminals. Simulation results show that the proposed approach is suitable for different channel conditions and significantly saves the user terminal energy consumption compared with other benchmark schemes.

Abstract Based on the nonlinear algorithmic theory, the R-SVM water source discrimination model and prediction method were established by using the piper qualitatively to compare the differences between the ionic components and R-type factor approximation indicator input dimensions. Taking the mine water samples of Zhaogezhuang Coal Mine as an example, according to the chemical composition analysis of the water samples from different monitoring points, six indexes of Na+, Ca2+, Mg2+, Cl–, SO4 2– and HCO3 – were selected as the discrimination factors. According to the water characteristics of each aquifer and the actual needs of discrimination, the water inrush sources in the mining area were divided into four categories: The goaf water is class I, Ordovician carbonate is class II, Sandstone fracture water from the 13 coal system is class III, and Sandstone fracture water from the 12 coal system is class IV. Taking 56 typical water inrush samples as training samples, 11 groups for prediction samples, establish the input index as typical ion content, output as water source type, using SPSS statistics and MATLAB to realize the R-SVM water source discriminant analysis model, automatically establishing the mapping relationship between the water quality indexes and the evaluation standards, which can achieve the purpose of rapid and accurate discrimination of the water sample data. The results showed that the accuracy of the R-SVM model classification was 90.90% in the verification of the water source discrimination example of Zhaogezhuang mine and the coupled model has high accuracy, good applicability and discriminant ability, and has certain guiding significance for the prevention and control of water damage and the related field work.

Abstract Background MicroRNA (miRNA)-based therapies have shown great potential in myocardial repair following myocardial infarction (MI). MicroRNA-302 (miR302) has been reported to exert a protective effect on MI. However, miRNAs are easily degraded and ineffective in penetrating cells, which limit their clinical applications. Exosomes, which are small bioactive molecules, have been considered as an ideal vehicle for miRNAs delivery due to their cell penetration, low immunogenicity and excellent stability potential. Herein, we explored cardiomyocyte-targeting exosomes as vehicles for delivery of miR302 into cardiomyocyte to potentially treat MI. Methods To generate an efficient exosomal delivery system that can target cardiomyocytes, we engineered exosomes with cardiomyocyte specific peptide (CMP, WLSEAGPVVTVRALRGTGSW). Afterwards, the engineered exosomes were characterized and identified using transmission electron microscope (TEM) and Nanoparticle Tracking Analysis (NTA). Later on, the miR302 mimics were loaded into the engineered exosomes via electroporation technique. Subsequently, the effect of the engineered exosomes on myocardial ischemia and reperfusion (I/R) injury was evaluated in vitro and in vivo, including MTT, ELISA, real-time quantitative polymerase chain reaction (PCR), western blot, TUNNEL staining, echocardiogram and hematoxylin and eosin (HE) staining. Results Results of in vitro experimentation showed that DSPE-PEG-CMP-EXO could be more efficiently internalized by H9C2 cells than unmodified exosomes (blank‐exosomes). Importantly, compared with the DSPE-PEG-CMP-EXO group, DSPE-PEG-CMP-miR302-EXO significantly upregulated the expression of miR302, while exosomes loaded with miR302 could enhance proliferation of H9C2 cells. Western blot results showed that the DSPE-PEG-CMP-miR302-EXO significantly increased the protein level of Ki67 and Yap, which suggests that DSPE-PEG-CMP-miR302-EXO enhanced the activity of Yap, the principal downstream effector of Hippo pathway. In vivo, DSPE-PEG-CMP-miR302-EXO improved cardiac function, attenuated myocardial apoptosis and inflammatory response, as well as reduced infarct size significantly. Conclusion In conclusion, our findings suggest that CMP-engineered exosomes loaded with miR302 was internalized by H9C2 cells, an in vitro model for cardiomyocytes coupled with potential enhancement of the therapeutic effects on myocardial I/R injury.

Abstract Designing high-performance thermal catalysts with stable catalytic sites is an important challenge. Conventional wisdom holds that strong metal-support interactions can benefit the catalyst performance, but there is a knowledge gap in generalizing this effect across different metals. Here, we have successfully developed a generalizable strong metal-support interaction strategy guided by Tammann temperatures of materials, enabling functional oxide encapsulation of transition metal nanocatalysts. As an illustrative example, Co@BaAl2O4 core@shell is synthesized and tracked in real-time through in-situ microscopy and spectroscopy, revealing an unconventional strong metal-support interaction encapsulation mechanism. Notably, Co@BaAl2O4 exhibits exceptional activity relative to previously reported core@shell catalysts, displaying excellent long-term stability during high-temperature chemical reactions and overcoming the durability and reusability limitations of conventional supported catalysts. This pioneering design and widely applicable approach has been validated to guide the encapsulation of various transition metal nanoparticles for environmental tolerance functionalities, offering great potential to advance energy, catalysis, and environmental fields.

Highlights A simple two-step multi-element co-doping strategy is proposed to fabricate core-shell structured LiCoO2 based on the different diffusivities of dopant ions. The high diffusivity Al3+/Mg2+ ions occupy the core of single-crystal grain while the low diffusivity Ti4+ ions enrich the shell layer. In-situ XRD demonstrates the mitigated structural distortion under a high cut-off voltage of 4.6 V, resulting in a significantly improved cycling stability.

Abstract The deterministic creation and modification of domain walls in ferroelectric films have attracted broad interest due to their unprecedented potential as the active element in non-volatile memory, logic computation and energy-harvesting technologies. However, the correlation between charged and antiphase states, and their hybridization into a single domain wall still remain elusive. Here we demonstrate the facile fabrication of antiphase boundaries in BiFeO3 thin films using a He-ion implantation process. Cross-sectional electron microscopy, spectroscopy and piezoresponse force measurement reveal the creation of a continuous in-plane charged antiphase boundaries around the implanted depth and a variety of atomic bonding configurations at the antiphase interface, showing the atomically sharp 180° polarization reversal across the boundary. Therefore, this work not only inspires a domain-wall fabrication strategy using He-ion implantation, which is compatible with the wafer-scale patterning, but also provides atomic-scale structural insights for its future utilization in domain-wall nanoelectronics.

The rotational mechanism, which plays a critical role in energy supply, payload antenna pointing, and attitude stabilization in satellites is essential for the overall functionality and performance stability of the satellite. This paper takes the space turntable of a specific satellite model as an example, utilizing high-frequency and high-dimensional telemetry data. An improved informer model is used to predict and diagnose features related to the turntable’s operational health, including temperature, rotational speed, and current. In this paper, we present a forecasting method for turntable temperature data using a hybrid model that combines singular spectrum analysis with an enhanced informer model (SSA-Informer), comparing the results with threshold limits to determine if faults occur in the satellite’s rotational mechanism. First, during telemetry data processing, singular spectrum analysis (SSA) is proposed to retain the long-term and oscillatory trends in the original data while filtering out noise from interference. Next, the improved informer model predicts the turntable temperature based on the mapping relationship between the turntable subsystem’s motor current and temperature, with multiple experiments conducted to obtain optimal parameters. Finally, temperature thresholds generated from the prediction results are used to forecast faults in the rotational mechanism over different time periods. The proposed method is compared with current popular time-series prediction models. The experimental results show that the model achieves high prediction accuracy, with reductions of at least 10% in both the MAE and MSE than CNN-LSTM, DA-RNN, TCN-SE and informer, demonstrating the outstanding advantages of the SSA and improved informer-based method in predicting temperature faults in satellite rotational mechanisms.

The You Only Look Once (YOLO) series algorithms have been widely adopted in concrete crack detection, with attention mechanisms frequently being incorporated to enhance recognition accuracy and efficiency. However, existing research is confronted by two primary challenges: the suboptimal performance of attention mechanism modules and the lack of explanation regarding how these mechanisms influence the model’s decision-making process to improve accuracy. To address these issues, a novel Dynamic Efficient Channel Attention (DECA) module is proposed in this study, which is designed to enhance the performance of the YOLOv10 model in concrete crack detection, and the effectiveness of this module is visually demonstrated through the application of interpretable analysis algorithms. In this paper, a concrete dataset with a complex background is used. Experimental results indicate that the DECA module significantly improves the model’s accuracy in crack localization and the detection of discontinuous cracks, outperforming the existing Efficient Channel Attention (ECA). When compared to the similarly sized YOLOv10n model, the proposed YOLOv10-DECA model demonstrates improvements of 4.40%, 3.06%, 4.48%, and 5.56% in precision, recall, mAP50, and mAP50-95 metrics, respectively. Moreover, even when compared with the larger YOLOv10s model, these performance indicators are increased by 2.00%, 0.04%, 2.27%, and 1.12%, respectively. In terms of speed evaluation, owing to the lightweight design of the DECA module, the YOLOv10-DECA model achieves an inference speed of 78 frames per second, which is 2.5 times faster than YOLOv10s, thereby fully meeting the requirements for real-time detection. These results demonstrate that an optimized balance between accuracy and speed in concrete crack detection tasks has been achieved by the YOLOv10-DECA model. Consequently, this study provides valuable insights for future research and applications in this field.

(1) Background: The aim of this study was to assess lower limb muscle strength in older adults during the transfer from sitting to standing (STS) using an inertial measurement unit (IMU). Muscle weakness in this population can severely impact function and independence in daily living and increase the risk of falls. By using an IMU, we quantified lower limb joint moments in the STS test to support health management and individualized rehabilitation program development for older adults. (2) Methods: This study involved 28 healthy older adults (13 males and 15 females) aged 60–70 years. The lower limb joint angles and moments estimated using the IMU were compared with a motion capture system (Mocap) (pair t-test, ICC, Spearman correlations, Bland–Altman plots) to verify the accuracy of the IMU in estimating lower limb muscle strength in the elderly. (3) Results: There was no significant difference in the lower limb joint angles and moments calculated by the two systems. Joint angles and moments were not significantly different (p > 0.05), and the accuracy and consistency of the IMU system was comparable to that of the Mocap system. For the hip, knee, and ankle joints, the ICCs for joint angles were 0.990, 0.989, and 0.885, and the ICCs for joint moments were 0.94, 0.92, and 0.89, respectively. In addition, the results of the two systems were highly correlated with each other: the r-values for hip, knee, and ankle joint angles were 0.99, 0.99, and 0.96, and the r-values for joint moments were 0.92, 0.96, and 0.85. In the present study, there was no significant difference (p > 0.05) between the IMU system and the Mocap system in calculating lower limb joint angles and moments. (4) Conclusions: This study confirms the accuracy of the IMU in assessing lower limb muscle strength in the elderly. It provides a portable and accurate alternative for the assessment of lower limb muscle strength in the elderly.

Abstract 2D conjugated metal‐organic frameworks (c‐MOFs) have emerged as promising materials for (opto)electronic applications due to their excellent charge transport properties originating from the unique layered‐stacked structures with extended in‐plane conjugation. The further advancement of MOF‐based (opto)electronics necessitates the development of novel 2D c‐MOF thin films with high quality. Cu‐HHHATN (HHHATN: hexahydroxyl‐hexaazatrinaphthylene) is a recently reported 2D c‐MOF featuring high in‐plane conjugation, strong interlayer π–π stacking, and multiple coordination sites, while the production of its thin‐film form has not yet been reported. Herein, large‐area Cu‐HHHATN thin films with preferential orientation, high uniformity, and smooth surfaces are realized by using a convenient layer‐by‐layer growth method. Flexible photodetectors are fabricated, showing broadband photoresponse ranging from UV to short‐wave infrared (370 to 1450 nm). The relatively long relaxation time of photocurrent, which arises from the trapping of photocarriers, renders the device's synaptic plasticity similar to that of biological synapses, promising its use in neuromorphic visual systems. This work demonstrates the great potential of Cu‐HHHATN thin films in flexible optoelectronic devices for various applications.

Summary: It is imperative to explore biomarkers that are both precise and readily accessible in the comprehensive management of breast cancer. A multicenter cohort, including 512 breast cancer patients and 198 nonneoplastic individuals, was recruited to detect the level of tumor-derived extracellular vesicles using our method based on dual DNA tetrahedral nanostructures. The level of tumor-derived extracellular vesicles was significantly higher in newly diagnosed breast cancer patients than in nonneoplastic individuals at a cutoff value of 3.58 U/μL. For postoperative metastasis monitoring, the level of tumor-derived extracellular vesicles was significantly higher in breast cancer patients with metastasis than in those without metastasis at a cutoff value of 3.91 U/μL. Its efficacy of diagnosis and metastasis monitoring was superior to traditional tumor markers. Elevated level of tumor-derived extracellular vesicles served as a predictive biomarker for diagnosis and metastasis monitoring in breast cancer patients.

Non-alcoholic fatty liver disease (NAFLD) is one of the most common liver diseases and is emerging as one of the fastest-growing causes of liver-related deaths worldwide. It is necessary to find strategies to effectively prevent and treat NAFLD, as no definitive drug has been approved. Nobiletin (NOB) is the critical active ingredient of Chinese herbal medicines such as Citrus aurantium and Citri Reticulatae Pericarpium, which have anti-inflammatory, antioxidant, lipid regulating, and insulin resistance regulating effects. Numerous studies have demonstrated that NOB can prevent and treat the onset and progression of NAFLD. In this review, the mechanisms of NOB for treating NAFLD have been summarized, hoping to provide a basis for subsequent studies of NOB and to provide a research ground for the development of therapeutic drugs for NAFLD.

Multiple primary malignant neoplasms are a rare gynecologic malignancy; particularly, cases originating from the heterologous organs, such as the ovary and cervix. Here, we report a case of two primary malignant neoplasms in a patient who had undergone laparoscopic radical hysterectomy + bilateral salpingo-oophorectomy + pelvic lymph node dissection + para-aortic lymphadenectomy + appendectomy + omentectomy + metastasectomy under general anesthesia. The patient experienced complete remission after six courses of postoperative chemotherapy with a standard Taxol and Carboplatin regimen. Genetic testing was performed to detect BRCA2 mutations, and poly (ADP-ribose) polymerase (PARP) inhibitors were used for maintenance therapy.

Abstract Changing thermal regime is one of the key mechanisms driving seismogenic behaviors at cold megathrusts, but it is difficult to interpret warm subduction zones such as Vanuatu for the temperatures are higher than that accommodates shallow brittle failures. We construct a 3-D thermomechanical model to clarify the thermal structure that controls tectonic seismicity in Vanuatu and predict a warm circumstance associated with abundant seismicity. Results reveal a heterogeneous slab ranging from 300 °C to over 900 °C from the Moho to subvolcanic depth. The subduction seismicity corresponds well to the plate interface where dynamic thermal dehydration is focused. The transformation from hydrated basalts to eclogites along the slab facilitates the occurrence of intense earthquakes and slips. Multistage mineralogical metamorphism affects the dynamic stability of megathrusts and favors the generation of active interplate large events. Therefore, slab thermal dehydration plays a greater role than slab temperature condition in influencing the subduction earthquake distribution in warm subduction systems.

Intrauterine adhesion (IUA) is the fibrosis within the uterine cavity. It is the second most common cause of female infertility, significantly affecting women's physical and mental health. Current treatment strategies fail to provide a satisfactory therapeutic outcome for IUA patients, leaving an enormous challenge for reproductive science. A self-healing adhesive hydrogel with antioxidant properties will be highly helpful in IUA prevention. In this work, we prepare a series of self-healing hydrogels (P10G15, P10G20, and P10G25) with antioxidant and adhesive properties. Those hydrogels exhibit good self-healing properties and can adapt themselves to different structures. They possess good injectability and fit the shape of the human uterus. Moreover, the hydrogels exhibit good tissue adhesiveness, which is desirable for stable retention and therapeutic efficacy. The in vitro experiments using P10G20 show that the adhesive effectively scavenges ABTS+, DPPH, and hydroxyl radicals, rescuing cells from oxidative stress. In addition, P10G20 offers good hemocompatibility and in vitro and in vivo biocompatibility. Furthermore, P10G20 lowers down the in vivo oxidative stress and prevents IUA with less fibrotic tissue and better endometrial regeneration in the animal model. It can effectively downregulate fibrosis-related transforming growth factor beta 1 (TGF-β1) and vascular endothelial growth factor (VEGF). Altogether, these adhesives may be a good alternative for the clinical treatment of intrauterine adhesion.

The impressive adhesive capacity of marine mussels has inspired various fascinating designs in biomedical fields. Mussel-inspired injectable adhesive hydrogels, as a type of promising mussel-inspired material, have attracted much attention due to their minimally invasive property and desirable functions provided by mussel-inspired components. In recent decades, various mussel-inspired injectable adhesive hydrogels have been designed and widely applied in numerous biomedical fields. The rational incorporation of mussel-inspired catechol groups endows the injectable hydrogels with the potential to exhibit many properties, including tissue adhesiveness and self-healing, antimicrobial, and antioxidant capabilities, broadening the applications of injectable hydrogels in biomedical fields. In this review, we first give a brief introduction to the adhesion mechanism of mussels and the characteristics of injectable hydrogels. Further, the typical design strategies of mussel-inspired injectable adhesive hydrogels are summarized. The methodologies for integrating catechol groups into polymers and the crosslinking methods of mussel-inspired hydrogels are discussed in this section. In addition, we systematically overview recent mussel-inspired injectable adhesive hydrogels for biomedical applications, with a focus on how the unique properties of these hydrogels benefit their applications in these fields. The challenges and perspectives of mussel-inspired injectable hydrogels are discussed in the last section. This review may provide new inspiration for the design of novel bioinspired injectable hydrogels and facilitate their application in various biomedical fields.

Since their invention by Akachi in 1990s, pulsating heat pipes (PHPs) have attracted widespread interest and application in practice, e.g., grinding, chip cooling, the thermal management of batteries, etc., owing to their notable efficiency in heat transfer and their simplicity and flexibility in structure. Key factors influencing the heat transfer efficacy of pulsating heat pipes are mainly attributed to the thermophysical properties of the working fluid, the structural parameters, and the operating conditions. Research on pulsating heat pipes is conducted through theoretical investigations, numerical simulations, and visual experiments. In this paper, the research on PHPs in recent decades is reviewed with the consideration of the heat transfer performance mechanism and application of pulsating heat pipes, especially research under operation conditions such as with “status with motion” and with “inconsistent heat flux”.

Compelling evidence has shown that geomagnetic disturbances in vertical intensity polarization before great earthquakes are promising precursors across diverse rupture conditions. However, the geomagnetic vertical intensity polarization method uses the spectrum of smooth signals, and the anomalous waveforms of seismic electromagnetic radiation, which are basically nonstationary, have not been adequately considered. By combining pulse amplitude analysis and an experimental study of the cumulative frequency of anomalies, we found that the pulse amplitudes before the 2022 Luding M6.8 earthquake show characteristics of multiple synchronous anomalies, with the highest (or higher) values occurring during the analyzed period. Similar synchronous anomalies were observed before the 2021 Yangbi M6.4 earthquake, the 2022 Lushan M6.1 earthquake and the 2022 Malcolm M6.0 earthquake, and these anomalies indicate migration from the periphery toward the epicenters over time. The synchronous changes are in line with the recognition of previous geomagnetic anomalies with characteristics of high values before an earthquake and gradual recovery after the earthquake. Our study suggests that the pulse amplitude is effective for extracting anomalies in geomagnetic vertical intensity polarization, especially in the presence of nonstationary signals when utilizing observations from multiple station arrays. Our findings highlight the importance of incorporating pulse amplitude analysis into earthquake prediction research on geomagnetic disturbances.

Electromagnetic indices play a potential role in the forecast of short-term to imminent M ≥ 5.5 earthquakes and have good application prospects. However, despite possible progress in earthquake forecasting, concerns remain because it is difficult to obtain accurate epicenter forecasts based on different forecast indices, and the forecast time span is as large as months in areas with multiple earthquakes. In this study, based on the actual demand for short-term earthquake forecasts in the Gansu–Qinghai–Sichuan region of western China, we refined the construction of earthquake forecast indicators in view of the abundant electromagnetic anomalies before moderate and strong earthquakes. We revealed the advantageous forecast indicators of each method for the three primary earthquake elements (time, epicenter, magnitude) and the spatiotemporal evolution characteristics of the anomalies. The correlations between the magnitude, time, intensity, and electromagnetic anomalies of different M ≥ 5.5 earthquakes indicate that the combination of short-term electromagnetic indices is pivotal in earthquake forecasting.

As 5G becomes commercial, researchers have turned attention toward the Sixth-Generation (6G) network with the vision of connecting intelligence in a green energy-efficient manner. Federated learning triggers an upsurge of green intelligent services such as resources orchestration of communication infrastructures while preserving privacy and increasing communication efficiency. However, designing effective incentives in federated learning is challenging due to the dynamic available clients and the correlation between clients' contributions during the learning process. In this paper, we propose a dynamic incentive and reputation mechanism to improve energy efficiency and training performance of federated learning. The proposed incentive based on the Stackelberg game can timely adjust optimal energy consumption with changes in available clients during federated learning. Meanwhile, clients’ contributions in reputation management are formulated based on the cooperative game to capture the correlation between tasks, which satisfies availability, fairness, and additivity. The simulation results show that the proposed scheme can significantly motivate high-performance clients to participate in federated learning and improve the accuracy and energy efficiency of the federated learning model.

The increasing concurrences of heatwaves and droughts in the context of global warming have attracted much attention from the scientific community given their devastating social and environmental impacts. In this study, the effects of heatwaves in each adjacent week of flash drought onset on the intensification rate of soil moisture were quantified through a meta-Gaussian-based conditional probability model. Results showed that both heatwaves and flash droughts have become more frequent since the middle of the 1990s. For the seasonal distributions, except for the southwestern region where flash droughts lagged behind heatwaves, there was a good synchronization between the two climate extremes. Strong correlations between heatwaves and flash droughts were found in the northeastern, northern, and southwestern regions. Heatwaves with varied timing of emergence behave differently on the formation of flash droughts, along with significant regional differences. Short-term impending hot conditions were crucial for the breakout of flash droughts, especially for the week when flash droughts were initiated, the emergence of heatwaves was likely to increase the intensification rate of soil moisture by 20% compared to those with no heatwaves in their development stage. HIGHLIGHTS The composite patterns of concurrent heatwaves and flash droughts are investigated.; Conditional probability is adopted to quantify the effect of heatwaves on drought.; Heatwaves increase the intensification rate of drought events by about 20%.;

Abstract Lithium (Li) is an essential element in modern energy production and storage devices. Technology to extract Li from seawater, which contains ~ 230 billion tons of Li, offers a solution to the widespread concern regarding quantitative and geographical limitations of future Li supplies. To obtain green Li from seawater, we propose an unassisted photoelectrochemical (PEC) Li extraction system based on an III-V-based triple-junction (3J) photoelectrode and a Li-ion selective membrane with only sunlight as an input. A light-harvesting/catalysis decoupling scheme yielded a 3J photoelectrode with excellent light-harvesting and catalysis reaction capabilities and superb stability over the 840 h of the extraction process. It allows the system to successfully enrich seawater Li by 4,350 times (i.e., from 0.18 ppm to 783.56 ppm) after three extraction stages. The overall reaction of the unassisted PEC green Li extraction system achieved 2.08 mg kJ−1 of solar-to-Li efficiency and 3.65% of solar-to-hydrogen efficiency. Graphical Abstract Photoelectrochemical (PEC) lithium extraction device is designed to explore lithium from seawater for the first time. The PEC cell with a triple-junction (InGaP/GaAs/Ge) photoelectrode and light-harvesting/catalysis decoupling scheme is constructed, offering a suitable operating potential and superb stability to the membrane-based extraction process in the seawater. The device can successfully enrich lithium by 4,350 times (from 0.18 to 783.56 ppm).

Abstract Given the deformation and instability of the layered floor of weakly cemented soft rock roadway, taking the mining roadway of Meihuajing Mine as the engineering background, the deformation and instability mechanism of the floor and the control measures of the surrounding rock under different stratum combination conditions are studied by using the methods of field investigation, numerical calculation and field test. The results show that: (1) the layered characteristics of surrounding rock in weakly cemented soft rock roadways are significant, and the combination structure of floor rock strata is complex and changeable. Under the influence of engineering disturbance, the roadway has a tendency of large deformation, especially floor heave. (2) The buckling instability of the layered floor is caused by the layered weakening effect, and the unstable zone, the substable zone and the stable zone are formed successively from the shallow to the deep. With the increase of the layer thickness, the integrity of the layered floor is improved, the layered weakening effect is reduced, and the overall stability of the layered floor is improved. (3) The existence of weak interlayer further degrades the integrity of layered floor, and the progressive failure of floor rock mass layer by layer is more significant under the influence of layered weakening effect. (4) The relatively hard rock stratum in the composite structure plays an important role in controlling the deformation and failure of the floor, playing the role of “local key stratum.” (5) Based on the cooperative control countermeasure of roof–rib–floor surrounding rock, the support technology of roof and ribs supported by blots mesh beam cable + floor supported by bolts grouting hardening + full section shotcrete is proposed. The results of numerical calculation and field test show that the support scheme greatly improves the stability of layered floor.

This paper investigates $ \mathcal{L}_{2}-\mathcal{L}_{\infty} $ control for memristive neural networks (MNNs) with a non-necessarily differentiable time-varying delay. The objective is to design an output-feedback controller to ensure the $ \mathcal{L}_{2}-\mathcal{L}_{\infty} $ stability of the considered MNN. A criterion on the $ \mathcal{L}_{2}-\mathcal{L}_{\infty} $ stability is proposed using a Lyapunov functional, the Bessel-Legendre inequality, and the convex combination inequality. Then, a linear matrix inequalities-based design scheme for the required output-feedback controller is developed by decoupling nonlinear terms. Finally, two examples are presented to verify the proposed $ \mathcal{L}_{2}-\mathcal{L}_{\infty} $ stability criterion and design method.

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder and early diagnosis is crucial for effective treatment. Stable and effective biomarkers are essential for understanding the underlying causes of the disorder and improving diagnostic accuracy. Electroencephalography (EEG) signals have proven to be reliable biomarkers for diagnosing ASD. Extracting stable connectivity patterns from EEG signals helps ensure robustness in ASD diagnostic systems. In this study, we propose a hybrid graph convolutional network framework called Rest-HGCN, which utilizes resting-state EEG signals to capture differential patterns of brain connectivity between normal children and ASD patients using graph learning strategies. The Rest-HGCN combines brain network analysis techniques and data-driven strategies to extract discriminative graph features from resting-state EEG signals. By automatically extracting differential graph patterns from these signals, the Rest-HGCN achieves reliable ASD diagnosis. To evaluate the performance of Rest-HGCN, we conducted ASD diagnosis experiments using k-fold cross-validation on the public ABC-CT resting EEG dataset. The proposed Rest-HGCN model achieved accuracies of 87.12 % and 85.32 % in single-subject and cross-experiment analyses, respectively. The results suggest that Rest-HGCN can effectively capture discriminant graph patterns from resting EEG signals and achieve robust ASD diagnosis. This may provide an effective and convenient tool for clinical ASD diagnosis.

ObjectChronic pain and negative emotions are often linked, and both can impact the reward circuit. The use of electroacupuncture (EA) has been found to regulate and improve these conditions. This study explores the potential mechanism of chronic pain relief by adding acupoints with emotional regulation effect to the basis of routine EA analgesia, to optimize the acupoint compatibility scheme of EA in the treatment of analgesia.MethodFor this study, 42 male Wistar rats were used. Recombinant adeno-associated viruses were used to label and regulate the activity of dopamine (DA) neurons. The rat model was established by complete Freund’s adjuvant (CFA). Lower limb electroacupuncture (LEA) was applied to the ST36 and BL60 acupoints. In addition, LEA + scalp EA (SEA) was given using the GV20 and GV24+ acupoints besides ST36 and BL60. To evaluate the pain threshold, we measured 50% paw withdrawal thresholds and thermal paw withdrawal latencies. Negative emotions were evaluated through the open field test, marble-burying test, sucrose preference test, and forced swimming test. Moreover, the conditional place preference test was conducted to measure the reward behavior in response to pain relief. Immunofluorescence staining, Western blotting, and qPCR were used to detect the activity of the VTADA-NAc reward circuit.ResultThe injection of CFA significantly lowered the pain threshold. As the pain persisted, the anxiety and depression-like behaviors escalated while the response to reward reduced. Meanwhile, the VTADA-NAc pathway was suppressed with pain chronification. However, activating DA neurons in VTA attenuated the effects induced by CFA. LEA could relieve chronic pain, negative emotions, and reward disorders, while also activating the VTADA-NAc pathway. In addition, LEA + SEA exhibited a more pronounced effect compared with LEA alone. Nevertheless, chemogenetic inhibition of DA neurons decreased the efficacy of LEA + SEA in the treatment of chronic pain and associated comorbidities.ConclusionAdding SEA to conventional LEA effectively alleviates negative emotions and chronic pain, potentially due to the activation of the VTADA-NAc reward neural circuit. Thus, LEA + SEA is a more effective treatment for hyperalgesia and associated negative emotions compared with LEA alone.

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.