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Background:Stephania tetrandra has been used for treating rheumatic diseases for thousands of years in rural areas of China. Several studies have found that tetrandrine and fangchinoline can inactivate the PI3K/Akt signaling pathway by reducing the expression and phosphorylation of AKT. However, the mechanism underlying the therapeutic actions of S. tetrandra on RA is not well known.Methods: In this study, we determined the molecular mechanism of the therapeutic effects of the multiple ingredients of S. tetrandra extract (STE) on collagen-induced arthritic (CIA) rats by integrating pharmacometabolomics, proteomics, and PTMomics.Results: In the multi-omics joint analysis, first, the expression signatures of proteins, PTMs, metabolites, and STE ingredients were profiled in CIA rats PBMCs that underwent STE treatment. Bioinformatics analysis were subsequently probed that STE mainly regulated tryptophan metabolism, inflammatory response, and cell adhesion pathways in CIA rats. The interrelated pathways were further constructed, and the findings revealed that STE attenuated the inflammatory response and proliferation of PBMCs in CIA rats by mediating the key targets of the PI3K/Akt pathway, including Hint1, ACP1, FGR, HSP90@157W + dioxidation, and Prkca@220N + 845.4540 Da. The rheumatic functions of Hint1 and ACP1 were further confirmed by applying a transcriptomic data of RA patients who clinically received abatacept therapy. Furthermore, a cross-ome correlation analysis was performed and major in vivo ingredients of STE, including coclaurine-N-glucuronide, Me,coclaurine-O-glc, N-gluA-schefferine, corydamine, corypamine, tetrandrine, and fangchiniline, were found to act on these targerts to inactivate the PI3K/Akt pathway.Conclusion: These results elucidated the molecular mechanism by which the ingredients of STE mediate the expression of the key targets in the PI3K/Akt pathway, leading to anti-rheumatic functions. The findings of this study provided new insights into the synergistic effect of STE against arthritis in rats.

The penetration fuze, as the initiation control component of the penetration weapon, usually experiences an overload of tens of thousands or even hundreds of thousands of g during the penetration process. In order to prevent the fuze from being overloaded and causing the weapon to explode or misfire early, this article introduces the use of internal sealing reinforcement and external energy absorbing buffer materials to protect the internal circuit modules of the fuze. Several kinds of energy absorbing and buffering materials, including foam metal materials and composite sandwich structure materials, as well as metamaterials that have recently attracted the attention of industry and academia, are reviewed. The high overload impact energy absorption characteristics of materials and the mechanical properties of different material structures are emphatically introduced. In addition, this article also evaluates the applicability and limitations of existing buffer materials and methods, and proposes some potential improvement plans, such as the impact of parameters such as viscoelasticity, porosity, surface coating, printing process, heat treatment process on the energy absorption effect of materials, further improving the engineering practicality of buffer protection materials. A summary of the key technologies in the research of penetration fuze protective materials was made, and some mechanical testing methods were proposed, which can better characterize the impact resistance and resilience of materials. Finally, the future development direction of buffer materials for penetration fuzes was explored, which will help promote the research on the concept of buffer materials used on penetration missiles.

To enhance the impact resistance of penetration fuze, this paper investigates the response of fuze buffer materials to stress waves and develops a model for stress wave transmission inside the fuze. The stress concentration impacts of different cell structures of Imitation Bamboo Type Penetration Fuze Buffer Protection Structure (IBS) under stress wave action are compared and analyzed. The paper elucidates the impact of different cell parameters on stress concentration impacts, establishes nonlinear fitting functions of Stress Concentration Factor (SCF) and cell parameters, and solves the prediction error. Based on the wave function expansion method, an expression for Dynamic Stress Concentration Factor (DSCF) when stress waves interact with the potting material is derived, and numerical results of DSCF around bubbles under different physical parameters are provided. Finally, dynamic impact tests are conducted on the combined buffer scheme of penetration fuze. Impact test results show that, under an initial velocity impact of 50 m/s, the overload peak attenuation rate is 39.42%, and under an initial velocity impact of 70 m/s, the overload peak attenuation rate is 32.87%. IBS can effectively protect the electronic components inside the fuze.

Abstract Background and objectives Sepsis is accompanied by a considerably high risk of mortality in the short term, despite the availability of recommended mortality risk assessment tools. However, these risk assessment tools seem to have limited predictive value. With the gradual integration of machine learning into clinical practice, some researchers have attempted to employ machine learning for early mortality risk prediction in sepsis patients. Nevertheless, there is a lack of comprehensive understanding regarding the construction of predictive variables using machine learning and the value of various machine learning methods. Thus, we carried out this systematic review and meta-analysis to explore the predictive value of machine learning for sepsis-related death at different time points. Methods PubMed, Embase, Cochrane, and Web of Science databases were searched until August 9th, 2022. The risk of bias in predictive models was assessed using the Prediction model Risk of Bias Assessment Tool (PROBAST). We also performed subgroup analysis according to time of death and type of model and summarized current predictive variables used to construct models for sepsis death prediction. Results Fifty original studies were included, covering 104 models. The combined Concordance index (C-index), sensitivity, and specificity of machine learning models were 0.799, 0.81, and 0.80 in the training set, and 0.774, 0.71, and 0.68 in the validation set, respectively. Machine learning outperformed conventional clinical scoring tools and showed excellent C-index, sensitivity, and specificity in different subgroups. Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) are the preferred machine learning models because they showed more favorable accuracy with similar modeling variables. This study found that lactate was the most frequent predictor but was seriously ignored by current clinical scoring tools. Conclusion Machine learning methods demonstrate relatively favorable accuracy in predicting the mortality risk in sepsis patients. Given the limitations in accuracy and applicability of existing prediction scoring systems, there is an opportunity to explore updates based on existing machine learning approaches. Specifically, it is essential to develop or update more suitable mortality risk assessment tools based on the specific contexts of use, such as emergency departments, general wards, and intensive care units.

Identifying ecosystem service functions, clarifying the spatiotemporal trade-offs and synergies of terrestrial ecosystem services and their driving mechanisms, and exploring differentiated ecological functional zoning are crucial steps in achieving healthy regional ecosystem management, and are conducive to developing diversified ecological restoration strategies, establishing a robust cross-regional collaborative management mechanism, implementing differentiated ecological management strategies, and contributing to the construction of a Beautiful China. This paper, based on the InVEST model, Pearson correlation, GeoDetector, and Spatiotemporal Geographically Weighted Regression models, constructs a spatial quantification model of the trade-offs and synergies among five key ecosystem service functions—habitat quality, soil retention, water conservation, food supply, and carbon sequestration—of China’s terrestrial ecosystems from 2000 to 2020. It explores the influencing factors of terrestrial ecosystem services in China and their spatiotemporal heterogeneity, thereby investigating the future strategies for ecological functional zoning and management of China’s national land space. The results indicate that: (1) during 2000–2020, China’s food supply and soil conservation have increased. However, the habitat quality, water conservation, and carbon sequestration have decreased. (2) Significant spatial and temporal heterogeneities exist in the key ecosystem services of China’s terrestrial ecosystems. (3) Natural, economic, and social factors all impact China’s terrestrial key ecosystem services. Among them, slope, annual average precipitation, land development intensity, and vegetation coverage are the main influencing factors, and different factors exhibit significant spatial heterogeneity. (4) Significant trade-offs/synergy effects among critical terrestrial ecosystem services exist in China. (5) China’s national territory is divided into four ecological protection functional zones: ecological restoration areas, ecological control areas, resilient development areas, and ecological conservation areas, and explores differentiated zoning optimization control paths.

A large amount of high salinity wastewater rich in dyes is produced in the printing and dyeing industry. Benefiting from the selective separating property，hollow fiber nanofiltration（NF） membranes are expected to achieve the efficient separation of dyes and inorganic salts，which can complete the pollution control of printing and dyeing wastewater as well as the synchronous recovery of valuable resources. Compared to the conventional spiral-wound NF membrane，hollow fiber NF membrane also presents advantages including high packing density and self-supporting ability. Therefore，it has received increasing attention in the field of printing and dyeing wastewater treatment. The recent research progress of hollow fiber NF technology in the dye separation process were reviewed. Specifically，the preparation of loose hollow fiber NF membrane and positively charged hollow fiber NF membrane suitable for dye separation were discussed. The membrane fouling characteristics of hollow fiber nanofiltration membrane in dye separation process and the corresponding membrane fouling control measures were analyzed. Finally，the future research directions were prospected to further promote the application of hollow fiber nanofiltration membrane technology in dye wastewater treatment.

Abstract Background Autonomic remodeling of the atria plays a pivotal role in the development of atrial fibrillation (AF) and exerts a substantial influence on the progression of this condition. Hyperlipidemia is a predisposing factor for AF, but its effect on atrial nerve remodeling is unclear. The primary goal of this study was to explore the possible mechanisms through which the consumption of a high-fat diet (HFD) induces remodeling of atrial nerves, and to identify novel targets for clinical intervention. Methods Cell models were created in vitro by subjecting cells to palmitic acid (PA), while rat models were established by feeding them a high-fat diet. To investigate the interplay between cardiomyocytes and nerve cells in a co-culture system, we utilized Transwell cell culture plates featuring a pore size of 0.4 μm. The CCK-8 assay was employed to determine cell viability, fluorescent probe DCFH-DA and flow cytometry were utilized for measuring ROS levels, JC-1 was used to assess the mitochondrial membrane potential, the Griess method was employed to measure the nitric oxide (NO) level in the supernatant, a fluorescence-based method was used to measure ATP levels, and MitoTracker was utilized for assessing mitochondrial morphology. The expression of pertinent proteins was evaluated using western blotting (WB) and immunohistochemistry techniques. SNAP was used to treat nerve cells in order to replicate a high-NO atmosphere, and the level of nitroso was assessed using the iodoTMT reagent labeling method. Results The study found that cardiomyocytes’ mitochondrial morphology and function were impaired under high-fat stimulation, affecting nitric oxide (NO) production through the CRIF1/SIRT1/eNOS axis. In a coculture model, overexpression of eNOS in cardiomyocytes increased NO expression. Moreover, the increased Keap1 nitrosylation within neuronal cells facilitated the entry of Nrf2 into the nucleus, resulting in an augmentation of P21 transcription and a suppression of proliferation. Atrial neural remodeling occurred in the HFD rat model and was ameliorated by increasing myocardial tissue eNOS protein expression with trimetazidine (TMZ). Conclusions Neural remodeling is triggered by high-fat stimulation, which decreases the production of NO through the CRIF1/eNOS/P21 axis. Additionally, TMZ prevents neural remodeling and reduces the occurrence of AF by enhancing eNOS expression.

In order to guide the geophysical exploration technology of coal field fire area, judge the development stage of coal fire, accurately identify the boundary of hidden fire area, carry out targeted high-temperature electrical property research of coal and coal surrounding rock by analyzing the conductive mechanism of rock and the electrical property characteristics of coal rock mass in a narrow sense, by testing the resistance values of coal and rock mass at different temperatures, the change law of coal and rock resistivity with temperature and its influence mechanism are summarized; by means of numerical simulation method, the geoelectric model of the coal field fire area is established and the forward and reverse calculation of transient electromagnetic (TEM) is carried out. The results show that the resistivity of coal decreases with the increase of temperature, and the carbon content of coal is the dominant factor affecting its resistivity at high temperature stage; the resistivity of the surrounding rock of dry coal decreases with the increase of temperature, and the number of free moving carriers under the thermal dynamic condition is the dominant factor affecting its resistivity. Through numerical simulation, it is found that the transient electromagnetic abnormal response amplitude caused by high-temperature coal is much larger than that caused by high-temperature surrounding rock, the coupling effect of the transient electromagnetic central loop device on the high-temperature fire area is the best, and the shallower the burial depth of the fire area, the more obvious the electrical abnormal effects.

Abstract Background Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver condition that affects a quarter of the global adult population. To date, only a few NAFLD risk prediction models have been developed for Chinese older adults aged ≥ 60 years. This study presented the development of a risk prediction model for NAFLD in Chinese individuals aged ≥ 60 years and proposed personalised health interventions based on key risk factors to reduce NAFLD incidence among the population. Methods A cross-sectional survey was carried out among 9,041 community residents in Shanghai. Three NAFLD risk prediction models (I, II, and III) were constructed using multivariate logistic regression analysis based on the least absolute shrinkage and selection operator regression analysis, and random forest model to select individual characteristics, respectively. To determine the optimal model, the three models’ discrimination, calibration, clinical application, and prediction capability were evaluated using the receiver operating characteristic (ROC) curve, calibration plot, decision curve analysis, and net reclassification index (NRI), respectively. To evaluate the optimal model’s effectiveness, the previously published NAFLD risk prediction models (Hepatic steatosis index [HSI] and ZJU index) were evaluated using the following five indicators: accuracy, precision, recall, F1-score, and balanced accuracy. A dynamic nomogram was constructed for the optimal model, and a Bayesian network model for predicting NAFLD risk in older adults was visually displayed using Netica software. Results The area under the ROC curve of Models I, II, and III in the training dataset was 0.810, 0.826, and 0.825, respectively, and that of the testing data was 0.777, 0.797, and 0.790, respectively. No significant difference was found in the accuracy or NRI between the models; therefore, Model III with the fewest variables was determined as the optimal model. Compared with the HSI and ZJU index, Model III had the highest accuracy (0.716), precision (0.808), recall (0.605), F1 score (0.692), and balanced accuracy (0.723). The risk threshold for Model III was 20%–80%. Model III included body mass index, alanine aminotransferase level, triglyceride level, and lymphocyte count. Conclusions A dynamic nomogram and Bayesian network model were developed to identify NAFLD risk in older Chinese adults, providing personalized health management strategies and reducing NAFLD incidence.

Abstract Background Pheochromocytoma (PCC) crisis is a rare life-threatening endocrine emergency. The diagnosis and treatment of PCC crisis, with acute respiratory distress syndrome (ARDS) as the first manifestation, is highly challenging, and traditional PCC management strategies are no longer suitable for these patients. Case presentation A 46-year-old female patient was admitted to the Intensive Care Unit (ICU) following sudden-onset acute respiratory distress and subsequent initiation of mechanical ventilation via endotracheal intubation. She was initially suspected of having a PCC crisis through the bedside critical care ultrasonic examination protocol. The computed tomography examination revealed a left adrenal neoplasm of 6.5cm × 5.9cm. The plasma-free metanephrine level was 100 times higher than the reference value. These findings were compatible with her PCC diagnosis. Alpha-blockers and fluid intake were started immediately. The endotracheal intubation was removed on the 11th day after admission to the ICU. The patient progressed to severe ARDS again, and invasive ventilation and continuous renal replacement therapy were needed. Despite aggressive therapy, her condition deteriorated. Therefore, she underwent veno-arterial extracorporeal membrane oxygenation (VA-ECMO)-assisted emergency adrenalectomy after multidisciplinary discussion. Postoperatively, the patient was supported by VA-ECMO for 7days. She was discharged from the hospital on day 30 after tumor resection. Conclusions This case highlighted the challenges in diagnosing and managing ARDS associated with PCC crisis. The traditional preoperative preparation protocol and optimal operation timing for patients with PCC are not suitable for patients with PCC crisis. Patients with life-threatening PCC crisis may benefit from early tumor removal, and VA-ECMO could maintain hemodynamic stability during and after surgery.

Abstract Chronic prostatic inflammation promotes cell survival and fibrosis, leading to benign prostatic hyperplasia (BPH) with aggravated urinary symptoms. It is investigated whether yes‐associated protein 1 (YAP1), an organ size controller and mechanical transductor, is implicated in inflammation‐induced BPH. The correlation between YAP1 expression and fibrosis in human and rat BPH specimens is analyzed. Furthermore, the effects of YAP1 activation on prostatic cell survival and fibrosis, as well as the underlying mechanism, are also studied. As a result, total and nuclear YAP1 expression, along with downstream genes are significantly upregulated in inflammation‐associated human and rat specimens. There is a significant positive correlation between YAP1 expression and the severity of fibrosis or clinical performance. YAP1 silencing suppresses cell survival by decreasing cell proliferation and increasing apoptosis, and alleviates fibrosis by reversing epithelial‐mesenchymal transition (EMT) and extracellular matrix (ECM) deposition in prostatic BPH‐1 and WPMY‐1 cells. Mechanistically, inflammatory stimulus and rigid matrix stiffness synergistically activate the RhoA/ROCK1 pathway to provoke cytoskeleton remodeling, thereby promoting YAP1 activation to exacerbate BPH development. Overall, inflammation‐triggered mechanical stiffness reinforcement activates the RhoA/ROCK1/F‐actin/YAP1 axis, thereby promoting prostatic cell survival and fibrosis to accelerate BPH progression.

In dynamic complex environments, it is inevitable for UAVs to be damaged due to their confrontational nature. The challenge to minimize the adverse effects of the damage and reallocate the mission is vital for achieving the operational goal. This paper proposes a distributed Multi-UAV mission reallocation method in the case of UAV damage based on the improved consensus-based bundle algorithm (CBBA). Firstly, a dynamic optimization model for Multi-UAV mission reallocation is established based on an improved resource update model. Secondly, a distributed damage inspection method based on the heartbeat hold mechanism is proposed for real-time monitoring of UAV conditions, which could enable the rapid response to UAV damage events. Furthermore, the CBBA is improved by introducing a timeliness parameter to adjust the bidding strategy and optimizing the mission selection strategy based on the time-order priority insertion principle to generate mission reallocation plans quickly. Through numerical examples, the results show that the proposed method can effectively reallocate Multi-UAV missions under damage events and has superior performance compared with original the CBBA, the particle swarm optimization (PSO) algorithm, and the performance impact (PI) algorithm. The proposed method has a faster solving speed, while the obtained solution has higher mission reallocation effectiveness.

With businesses increasingly prioritizing data-driven decision making, the demand for business analysts is high and expected to grow. In response, many universities and institutions have developed courses and programs related to business analytics to prepare more graduates for careers in this field. Business analytics programs and educators consistently strive to achieve a high level of student learning success, ensuring competence in working in the business analytics field after graduation. In this study, we aim to examine key factors influencing student learning in business analytics, focusing on performance expectancy and satisfaction. We examined specific factors, including personal interest, career relevance expectancy, learning effort, and perceived course structure effectiveness, from perspectives related to both students and instructors. A research model was developed and empirically tested. The results showed that all factors significantly influenced both perceived academic performance and learning satisfaction. Additionally, personal interest and career relevance expectancy could significantly impact learning effort.

Abstract Background Postoperative delayed hyponatremia (PDH) is a major cause of readmission after endoscopic transsphenoidal surgery (eTSS) for pituitary adenomas (PAs). However, the risk factors associated with PDH have not been well established, and the development of a dynamic online nomogram for predicting PDH is yet to be realized. We aimed to investigate the predictive factors for PDH and construct a dynamic online nomogram to aid in its prediction. Methods We analyzed the data of 226 consecutive patients who underwent eTSS for PAs at the Department of Neurosurgery in Jinling Hospital between January 2018 and October 2020. An additional 97 external patients were included for external validation. PDH was defined as a serum sodium level below 137 mmol/L, occurring on the third postoperative day (POD) or later. Results Hyponatremia on POD 1–2 (OR = 2.64, P = 0.033), prothrombin time (PT) (OR = 1.78, P = 0.008), and percentage of monocytes (OR = 1.22, P = 0.047) were identified as predictive factors for PDH via multivariable logistic regression analysis. Based on these predictors, a nomogram was constructed with great discrimination in internal validation (adjusted AUC: 0.613–0.688) and external validation (AUC: 0.594–0.617). Furthermore, the nomogram demonstrated good performance in calibration plot, Brier Score, and decision curve analysis. Subgroup analysis revealed robust predictive performance in patients with various clinical subtypes and mild to moderate PDH. Conclusions Preoperative PT and the percentage of monocytes were, for the first time, identified as predictive factors for PDH. The dynamic nomogram proved to be a valuable tool for predicting PDH after eTSS for PAs and demonstrated good generalizability. Patients could benefit from early identification of PDH and optimized treatment decisions.

Typically, Cu catalysts agglomerate under electrochemical conditions. Here, the authors report a coordination polymer catalyst with neighboring Cu sites which remain isolated and reduce CO2 to C2H4 with high selectivity and stability

Whether the stems and leaves of leaf-vegetable sweet potatoes can be listed ahead of schedule is related to the improvement in economic benefits for farmers, and the key to all of this is to implement the safe overwintering of potato seedlings under the premise of saving production costs. Only in this way can we truly seize the “market opportunity” and achieve the goals of cost saving and increasing economic benefit. In this study, the main leaf-vegetable sweet potato variety Fucai 18 was used as the material, and the L9(34) orthogonal experiment was carried out in a simple solar greenhouse environment for two consecutive years from 2021 to 2022 and from 2022 to 2023, respectively. The effects of nine different combinations of factors on the above-ground and underground agronomic traits of overwintering sweet potato seedlings were studied under the conditions of four factors and three levels: planting density (a); different cutting seedlings (b); rooting agent concentration (c); and transplanting time (d). The methods of principal component analysis, membership function method, cluster analysis, grey correlation degree and stepwise regression analysis were used to evaluate the growth of overwintering seedlings, and try to screen out the key indicators that can be used to identify and evaluate the growth of overwintering sweet potato seedlings. Through range analysis, identify the optimal combination of four factors and three levels, and explore the main factors that have a significant impact on the key indicators for evaluating the growth of overwintering potato seedlings. The results indicate the following: (1) The use of simple sunlight greenhouse in Changsha area can achieve the safe overwintering of vegetable sweet potato seedlings. (2) Stem thickness, root length, and root diameter can be used as three key indicators for identifying and evaluating the growth potential of vegetable sweet potato overwintering seedlings. (3) Under four factors and three levels, the best combination was A3B3C1D1 (planting density of 250,000 plants/ha, stem tip core-plucking seedlings, rooting agent concentration of 50 mg/L, the first batch of transplanting time). (4) The transplanting time (D) is the main factor for the two key evaluation indicators of stem diameter and root diameter, while there is no significant difference in the three other factors. (5) Different cutting seedlings (B) are the main influencing factors for the key evaluation index of root length, while the other three factors have the following impact on root length: transplanting time (D) > rooting agent concentration (C) > planting density (A). The results of this study not only contribute to the construction of a safe overwintering cultivation technology system for vegetable sweet potato seedlings, but also provide a certain theoretical basis for the breeding of new cold-leaf-vegetable sweet potato varieties in the future.

The excellent insulation performance of roof insulators is crucial to the reliability of operating trains. The complex environment encountered by trains may cause roof insulator insulation failure, thus affecting the normal operation of the train. The field operation experience shows that during the operation of Hainan CRHAF-A trains, partial arcs are generated frequently on the roof insulators and even flashover accidents occur. In addition, the insulation failure probability of the insulators in the coastal environment is higher than that in other areas, and pollution is an important factor leading to lower insulation performance. Therefore, the pollution accumulation characteristics of roof insulators are investigated and analyzed in this paper. The accumulated pollution simulation model is built based on the operating environment of the train, and the electric field, flow field, and pressure field around the roof insulators are simulated. This has important engineering application and economic value for the study of insulator anti-pollution.

To ensure the reliable functioning of hard target-penetration fuze on the battlefield, this study focuses on research related to fuze protective pads. The main factors causing fuze functional failure are summarized, and a simplified model of projectile penetration into target plates is established. The design conditions for the yield stress parameter of the fuze casing material are derived based on stress wave propagation theory. Modal analysis of the projectile is conducted using dynamic simulation software ANSYS to determine its vibration modes and low-pass filtering frequency. Static compression experiments are performed on different rubber materials (nitrile rubber, fluorine rubber, silicone rubber, and natural rubber) to obtain stress–strain curves and constitutive model parameters. Marshall hammer tests were carried out on rubber pads of different materials and thicknesses, confirming the validity of the simulation results and the feasibility of rubber filtering. The study indicates that when using a 2 mm thick rubber pad for protection, natural rubber provides the best protection. When using a 6 mm thick rubber pad, nitrile rubber shows the best protective performance. Under a 13-tooth tooling impact load, the best protection is achieved using a 2 mm thick natural rubber pad. When using a 6 mm thick pad, silicone rubber provides the best protection. Under a 15-tooth tooling impact load, fluorine rubber provides the best protection when using a 2 mm thick pad, while silicone rubber offers the best protection when using a 6 mm thick pad. Under a 17-tooth tooling impact load, natural rubber offers the best protection when using a 2 mm thick pad, and fluorine rubber demonstrates the best protection when using a 6 mm thick pad. The obtained research results provide a reference for protective methods of hard target-penetration fuze.

Obesity has become a serious public health problem globally. China has the world's largest number of people with obesity or overweight. More than 50% of adults and about 20% of children and adolescents in China are overweight or obese. Over the past 20 years, China has made many efforts in obesity intervention, while obesity rates continued rising. In recent years, China has taken more actions for obesity prevention. The World Obesity Day (WOD) was established in 2015 by the World Obesity Federation, and is a unified day of action calling for a cohesive, cross-sector response to fight obesity. WOD has drawn increasing attention in recent years. China formally joined the WOD activities this year, promoted by The Obesity Prevention and Control Section of Chinese Nutrition Society, which cooperated closely with other organizations in carrying out a series of activities during the 2022 WOD. These efforts aimed to encourage the whole society to pay attention to the obesity problem and take more practical actions. The activities include: (1) The 2022 “World Obesity Day” China Summit; (2) a specifically developed WOD obesity prevention education video; and (3) the launch of The Expert Consensus on Obesity Prevention and Treatment in China. These can serve as examples for other organizations and countries to consider in future intervention efforts. To fight the global obesity epidemic, all counties and people need to act. Countries can learn from each other's successful practices.

During attempts to prevent and control the COVID-19 pandemic in China, higher education programs shifted their traditional educational models to online models. This paper aimed to explore how Chinese universities organized online teaching and learning during the pandemic. It investigated the factors affecting the implementation of online teaching and provided policy recommendations for improving the quality of education in the post-pandemic period. The primary data for this study came from in-depth interviews with nine students and five teaching and administrative staff at eight major universities in mainland China. Literature was obtained in both English and Chinese from January 2020 to September 2021. Peer-reviewed journals, policy reports, and university documents regarding online education in Chinese universities were reviewed, and their challenges and countermeasures were investigated. The paper found that the implementation of online education was affected by various sources, including technologies, teachers' teaching skills, network information literacy, and students' learning motivations and self-directed learning skills. Based on the insiders' views, the paper suggested that to promote the quality of online education in the post-COVID-19 pandemic, higher education institutes and programs could develop their infrastructure construction, improve teachers' quality of teaching, and focus on students' learning motivations.

Although research has always related e-portfolios to self-regulated learning, recently agency, which includes individual, relational, and contextual domains, has also been highlighted. Likewise, agency has been explored in technological environments that support collaborative and co-design learning processes. This study, investigating the enactment of student agency within e-portfolio learning co-design with 68 secondary students in Hong Kong, focuses on how students perceive their agency within a co-design e-portfolio learning framework, which was coined as the Co-PIRS model in previous stages of research. With descriptive aims, a mixed research methodology was designed using quantitative and qualitative data collection instruments. Among the findings, it is argued that students report a greater awareness of agency, characterized by competence beliefs (individual domain) in the showcase phase of e-portfolios, peer learning (relational domain), and the opportunities to make choices (contextual domain) in the implementation phase. The study also reveals students' positive attitudes towards reflection, which suggests the suitability of structuring collaboration in the co-design approach. These insights serve as a foundation for implementing e-portfolio co-design frameworks to empower students' agency and provide educators with guidance in Secondary Education and beyond. [Note: The page range (190-203) shown on the PDF is incorrect. The correct page range is 190-202.]

Abstract Objective Acute respiratory distress syndrome (ARDS) leads to life-threatening acute hypoxemic respiratory failure and requires mechanical ventilation. However, there is a lack of certainty regarding recruitment maneuvers (RMs) and positive end-expiratory pressure (PEEP) levels. Therefore, we performed a network meta-analysis to identify the optimal RM and PEEP levels of patients with ARDS. Methods We searched the PubMed, OVID and Cochrane Central Register of Controlled Trials (Central) databases for randomized controlled trials (RCTs). The primary outcome was death on the 28th day, and the secondary outcomes included in-hospital death, ventilator-free days, and barotrauma. The relative effect sizes were estimated by risk ratios (RRs) for binary variables and standard mean difference (SMD) for continuous variables. The efficacy of the interventions was ranked using surface under the cumulative ranking. Multiple intervention comparisons based on the Bayesian framework were performed to integrate the efficacy of all included strategies. Results Thirteen RCTs comprising 4410 patients were included in the network meta-analysis. In terms of death at 28 days, inconsistencies were found globally and locally in the tests. None of the ventilation strategies was significantly superior to the others on any outcomes. According to the relative rank probabilities, RM + lower PEEP levels showed the highest probability of reducing the risk of in-hospital death and reducing ventilator-free days. Lower PEEP levels showed the highest probability of benefitting barotrauma. The overall quality of the evidence per grade was moderate to low. Conclusions The no ventilation strategy is significantly superior to the other strategies. RM + lower PEEP levels has the highest probability of benefitting survival. The evidence has low overall quality and should be further studied.

Abstract Elderly patients with nonalcoholic fatty liver disease are at a higher risk of developing. This study established an effective, individualised, early Hypertension risk-prediction model and proposed health management advice for patients over 60 years of age with NAFLD. Questionnaire surveys, physical examinations, and biochemical tests were conducted in 11,136 participants. The prevalence of NAFLD among 11,136 participants was 52.1%. Risk factors were screened using the least absolute shrinkage and selection operator model and random forest model. A risk-prediction model was established using logistic regression analysis and a dynamic nomogram was drawn. The model was evaluated for discrimination, calibration, and clinical applicability using receiver operating characteristic curves, calibration curves, decision curve analysis, net reclassification index (NRI), and external validation. The results suggested that the model showed moderate predictive ability. The area under curve (AUC) of internal validation was 0.707 (95% CI: 0.688–0.727) and the AUC of external validation was 0.688 (95% CI: 0.672–0.705). The calibration plots showed good calibration, the risk threshold of the decision curve was 30–56%, and the NRI value was 0.109. This Hypertension risk factor model may be used in clinical practice to predict the Hypertension risk in NAFLD patients.

Abstract Background To observe the changes of hepatic function and efficacy of conventional dosage of caspofungin in the treatment of patients with different Child–Pugh scores. Methods In total, 200 patients (Child–Pugh A group: 66 patients, Child–Pugh B group: 83 patients, Child–Pugh C group: 51 patients) treated with caspofungin from May 2018 to March 2021 in the Second Affiliated Hospital of Chongqing Medical University were enrolled. Main investigation items were as follows: sex, age, weight, duration of treatment, dosage, department, underlying diseases, risk factors for fungal infection, albumin, liver enzyme, total bilirubin, serum creatinine, estimated glomerular filtration rate. To investigate the changes of liver, kidney function tests and efficacy during the treatments of caspofungin. Patients were divided into three groups according to the duration of treatment of caspofungin:1-week group, 2-week group and 3-week group, respectively. Results In the three groups, albumin, liver enzyme levels, total bilirubin and serum creatinine, estimated glomerular filtration rate had no significant difference (P > 0.05). The efficacy of different Child–Pugh scores and different duration of treatment was also significantly different (P > 0.05). Conclusions Caspofungin is well tolerated and highly effective. And it will not exacerbate the hepatic and renal function when administered with the not-reducing dose, which indicate the clinical application value of caspofungin. Besides, extending the treatment duration has little effect on improving the efficacy of caspofungin. The drug should be withdrawn timely according to the patients’ clinical condition in order to reduce the adverse reactions and economic burden.