Objective To explore the incidence and risk factors of sarcopenia in non-dialysis patients with stage 5 chronic kidney disease (CKD). Methods Non-dialysis stage 5 CKD patients in Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences from October 2023 to October 2024 were enrolled and divided into the non-sarcopenia group and the sarcopenia group according to lean tissue index (LTI) and handgrip strength (HGS). Demographic data of patients were collected and biochemical indicators were detected. Serum advanced glycation end products (AGEs) were detected by competitive ELISA. Multivariate logistic regression analysis was conducted to analyze the risk factors of sarcopenia in these patients. The diagnostic efficacy of the risk factors was evaluated by the receiver operating characteristic (ROC) curve. Results A total of 102 non-dialysis stage 5 CKD patients with (68.52±7.39) years, were enrolled, including 61 male (59.8%). Among them, 24 were diagnosed with sarcopenia (23.5%). Compared with patients in non-sarcopenia group, patients in sarcopenia group were older and had higher interleukin-6 (IL-6) and AGEs, lower body mass index (BMI) and lower serum albumin (sAlb; P＜0.05). Multivariate logistic regression showed that advanced age (OR＝1.153, 95%CI 1.045–1.273, P＝0.005), higher IL-6 (OR＝1.165, 95%CI 1.042–1.302, P＝0.007)、lower sAlb (OR＝0.675, 95%CI 0.542–0.840, P＝0.001), and higher serum AGEs (OR＝1.105, 95%CI 1.013–1.206, P＝0.024) were independent risk factors of sarcopenia in non-dialysis CKD 5 patients. The areas under the curve (AUC) for the age, IL-6, sAlb, and serum AGEs were 0.896, 0.643, 0.658, and 0.724, respectively. Conclusions Sarcopenia is common in non-dialysis stage 5 CKD patients, and the risk of sarcopenia is higher in non-dialysis stage 5 CKD patients with advanced age, higher IL-6, lower sAlb, and higher serum AGEs.

Intelligent prescription recommendation has become an important research direction in traditional Chinese medicine (TCM), offering new opportunities to support clinical decision-making and promote the modernization of TCM practice. With the rapid development of artificial intelligence (AI), a variety of computational approaches have been proposed to learn prescription patterns from clinical data and generate personalized treatment recommendations. However, despite increasing research activity, systematic and comprehensive reviews of AI-driven methods for TCM prescription recommendation remain limited. In this study, we present a comprehensive review of computational approaches for herbal prescription recommendation (HPR) in TCM. Existing methods are systematically categorized into several major paradigms, including traditional machine learning methods, topic model methods, sequential generative methods, deep learning and graph-based methods, and large language model–based frameworks. In addition to summarizing methodological developments, we also review commonly used public datasets and evaluation metrics in this field. Furthermore, representative models with publicly available implementations are experimentally evaluated on multiple benchmark datasets to provide a comparative analysis of their performance on the HPR task. Finally, we discuss the key challenges that hinder the practical deployment of intelligent prescription recommendation systems, including data heterogeneity, limited interpretability, and insufficient integration of TCM domain knowledge. Future research directions are outlined to facilitate the development of more reliable, interpretable, and clinically applicable AI-assisted HPR systems for TCM.

ObjectiveTo investigate the current awareness and optimization recommendations on pneumonia with unknown etiology (PUE) surveillance among Shanghai healthcare professionals, and to provide evidence for the improvement of the surveillance system. MethodsIn December 2024, healthcare professional participants from diverse medical and health institutions were randomly selected within each stratum using a stratified cluster sampling method in all 16 districts of Shanghai for questionnaire surveys on their knowledge and suggestions for optimization of the PUE surveillance system. Descriptive statistics analyses, multivariate logistic regressions, and content analyses were used for data analyses. ResultsA total of 385 survey subjects were involved in the study, including 119 professional staffs from disease prevention and control centers and 266 from medical institutions. Those who understood the case definition for PUE correctly accounted for 67.01% (258/385). Multivariate regression model analyses showed that female gender (aOR=2.22, 95%CI: 1.36‒3.66), professionals from disease control institutions (aOR=2.02, 95%CI: 1.12‒3.72), and those who self-assessed as being familiar with the monitoring system (aOR=2.18, 95%CI:1.23‒3.89) had better understanding of the definition. Overall, 89.61% (345/385) of the survey subjects acknowledged the necessity of the surveillance system. Small number of cases meeting the case definition (54.46%, 214/379), insufficient diagnostic awareness (39.84%, 151/379), and lack of incentives for case reporting (29.29%, 111/379) were major problems for the current surveillance system, with variations observed across different types of institutions. Suggested segments for optimizing the surveillance system included monitoring purpose, case definition, form of monitoring and reporting procedure, organization mechanism, and epidemiological investigation and response. ConclusionThe necessity of PUE surveillance is commonly recognized among healthcare workers. However, the existing system falls short in terms of mastery of case definition and overall surveillance adaptability. There is an urgent need for optimization and improvement to enhance the capacity for preventing and controlling emerging and sudden respiratory infectious diseases.

Objective: To investigate the associations of sleep quality and weight stigma with depressive mood among college students, so as to provide evidence for mental health promotion in higher education institutions. Methods: From September to November 2024, a stratified cluster random sampling method was used to survey 4 524 undergraduate students from the first to third year in comprehensive universities across various cities in Inner Mongolia. The χ 2 test was used to compare the detection rates of poor sleep quality, experiences of weight stigma, and depressive mood among students with different characteristics, and multivariate Logistic regression analysis was conducted to examine the independent and combined associations between sleep quality, the number of types of weight stigma experienced, and depressive mood. Results: Among students, the detection rate of poor sleep quality was 21.60%; those with experiences of weight stigma had a detection rate of 11.52%; those with depressive mood had a detection rate of 9.46%. Multivariate Logistic regression analysis showed that, compared with those who had good sleep quality, individuals with poor sleep quality were more likely to experience depressive mood [ OR (95% CI )=2.99(2.41- 3.71 )]; compared with those who had no experience of weight stigma, individuals who experienced ≥2 types of weight stigma were more likely to experience depressive mood [ OR (95% CI )=4.51(2.82-7.22)] (both P <0.01). Multivariate Logistic regression analysis, with "good sleep quality and no weight stigma experience" as the reference group, showed that all other joint groups had a higher likelihood of developing depressive mood, with the highest likelihood observed among students who had poor sleep quality and had experienced ≥2 types of weight stigma [ OR (95% CI )=14.21(6.95-29.06), P <0.01]. Conclusions Poor sleep quality and a greater number of weight stigma types are both associated with depressive mood among college students. Mental health programs in higher education institutions should simultaneously address students sleep problems and weight related adverse experiences, and implement comprehensive interventions.

The success of implementation research is closely tied to the institution's pre-implementation readiness. This study aims to explore the organizational readiness for change (ORC) and its influencing factors on primary healthcare settings in the implementation of the "Shared Medical Appointment for Diabetes (SMART) in China: design of an optimization trial" and to enhance ORC and provide insights to support the effective implementation of the program.

This study aimed to localize the workplace readiness questionnaire (WRQ) and validate its applicability for assessing readiness for implementation of evidence-based practices (EBP) in primary care settings in China. The localization of the instrument will provide a practical instrument for assessing organizational readiness for change (ORC).

Neuroscience is a significant frontier discipline within the natural sciences and has become an important interdisciplinary frontier scientific field. Brain is one of the most complex organs in the human body, and its structural and functional analysis is considered the “ultimate frontier” of human self-awareness and exploration of nature. Driven by the strategic layout of “China Brain Project”, Chinese scientists have conducted systematic research focusing on “understanding the brain, simulating the brain, and protecting the brain”. They have made breakthrough progress in areas such as the principles of brain cognition, mechanisms and interventions for brain diseases, brain-like computation, and applications of brain-machine intelligence technology, aiming to enhance brain health through biomedical technology and improve the quality of human life. Due to limited understanding and comprehension of neuroscience, there are still many important unresolved issues in the field of neuroscience, resulting in a lack of effective measures to prevent and protect brain health. Therefore, in addition to actively developing new generation drugs, exploring non pharmacological treatment strategies with better health benefits and higher safety is particularly important. Epidemiological data shows that, exercise is not only an indispensable part of daily life but also an important non-pharmacological approach for protecting brain health and preventing neurodegenerative diseases, forming an emerging research field known as motor neuroscience. Basic research in motor neuroscience primarily focuses on analyzing the dynamic coding mechanisms of neural circuits involved in motor control, breakthroughs in motor neuroscience research depend on the construction of dynamic monitoring systems across temporal and spatial scales. Therefore, high spatiotemporal resolution detection of movement processes and movement-induced changes in brain structure and neural activity signals is an important technical foundation for conducting motor neuroscience research and has developed a set of tools based on traditional neuroscience methods combined with novel motor behavior decoding technologies, providing an innovative technical platform for motor neuroscience research. The protective effect of exercise in neurodegenerative diseases provides broad application prospects for its clinical translation. Applied research in motor neuroscience centers on deciphering the regulatory networks of neuroprotective molecules mediated by exercise. From the perspectives of exercise promoting neurogenesis and regeneration, enhancing synaptic plasticity, modulating neuronal functional activity, and remodeling the molecular homeostasis of the neuronal microenvironment, it aims to improve cognitive function and reduce the incidence of Parkinson’s disease and Alzheimer’s disease. This has also advanced research into the molecular regulatory networks mediating exercise-induced neuroprotection and facilitated the clinical application and promotion of exercise rehabilitation strategies. Multidimensional analysis of exercise-regulated neural plasticity is the theoretical basis for elucidating the brain-protective mechanisms mediated by exercise and developing intervention strategies for neurological diseases. Thus,real-time analysis of different neural signals during active exercise is needed to study the health effects of exercise throughout the entire life cycle and enhance lifelong sports awareness. Therefore, this article will systematically summarize the innovative technological developments in motor neuroscience research, review the mechanisms of neural plasticity that exercise utilizes to protect the brain, and explore the role of exercise in the prevention and treatment of major neurodegenerative diseases. This aims to provide new ideas for future theoretical innovations and clinical applications in the field of exercise-induced brain protection.

OBJECTIVE To evaluate the efficacy and safety of high-dose ilaprazole combined with amoxicillin for newly diagnosed elderly patients with Helicobacter pylori （Hp） infection， and analyze independent risk factors for failure of Hp infection eradication treatment. METHODS Totally 200 cases of newly diagnosed elderly patients with Hp infection in Xinxiang Central Hospital from August 1， 2021 to December 1， 2024 were selected and randomly divided into control group and study group， with 100 cases in each group. The control group was treated with classic quadruple therapy regimen （Amoxicillin capsules+ Clarithromycin tablets+Bismuth potassium citrate tablets+Ilaprazole enteric-coated tablets）. The study group was treated with high- dose Ilaprazole enteric-coated tablets+Amoxicillin capsules. All patients were administered medication for 2 weeks. Hp eradication rates in the two groups were compared using intention-to-treat （ITT） and per-protocol （PP） analyses. The incidence of adverse reactions in both groups was also recorded. The multiple-factor Logistic regression analysis was used to identify independent risk factors for failure of Hp infection eradication treatment. RESULTS In ITT and PP analyses， there was no significant difference of Hp eradication rates between the two groups （P＞0.05）. There was no significant difference in incidence of mild to moderate adverse reactions between the two groups （P＞0.05）. BMI ≤18.5 kg/m2， BMI ＞23.9 kg/m2， rural residence， concomitant diabetes and concomitant heart disease were identified as independent risk factors influencing the failure of Hp infection eradication treatment （P＜0.05）. CONCLUSIONS The efficacy and safety of high-dose ilaprazole combined with amoxicillin are comparable to classic quadruple therapy regimen in treating newly diagnosed elderly patients with Hp infection. Independent risk factors influencing the failure of Hp infection eradication treatment include BMI ≤18.5 kg/m2， BMI ＞23.9 kg/m2， rural residence， concomitant diabetes and concomitant heart disease.

As China accelerates its efforts in deep space exploration and long-duration space missions, including the operationalization of the Tiangong Space Station and the development of manned lunar missions, safeguarding astronauts’ physiological and cognitive functions under extreme space conditions becomes a pressing scientific imperative. Among the multifactorial stressors of spaceflight, microgravity emerges as a particularly potent disruptor of neurobehavioral homeostasis. Dopamine (DA) plays a central role in regulating behavior under space microgravity by influencing reward processing, motivation, executive function and sensorimotor integration. Changes in gravity disrupt dopaminergic signaling at multiple levels, leading to impairments in motor coordination, cognitive flexibility, and emotional stability. Microgravity exposure induces a cascade of neurobiological changes that challenge dopaminergic stability at multiple levels: from the transcriptional regulation of DA synthesis enzymes and the excitability of DA neurons, to receptor distribution dynamics and the efficiency of downstream signaling pathways. These changes involve downregulation of tyrosine hydroxylase in the substantia nigra, reduced phosphorylation of DA receptors, and alterations in vesicular monoamine transporter expression, all of which compromise synaptic DA availability. Experimental findings from space analog studies and simulated microgravity models suggest that gravitational unloading alters striatal and mesocorticolimbic DA circuitry, resulting in diminished motor coordination, impaired vestibular compensation, and decreased cognitive flexibility. These alterations not only compromise astronauts’ operational performance but also elevate the risk of mood disturbances and motivational deficits during prolonged missions. The review systematically synthesizes current findings across multiple domains: molecular neurobiology, behavioral neuroscience, and gravitational physiology. It highlights that maintaining DA homeostasis is pivotal in preserving neuroplasticity, particularly within brain regions critical to adaptation, such as the basal ganglia, prefrontal cortex, and cerebellum. The paper also discusses the dual-edged nature of DA plasticity: while adaptive remodeling of synapses and receptor sensitivity can serve as compensatory mechanisms under stress, chronic dopaminergic imbalance may lead to maladaptive outcomes, such as cognitive rigidity and motor dysregulation. Furthermore, we propose a conceptual framework that integrates homeostatic neuroregulation with the demands of space environmental adaptation. By drawing from interdisciplinary research, the review underscores the potential of multiple intervention strategies including pharmacological treatment, nutritional support, neural stimulation techniques, and most importantly, structured physical exercise. Recent rodent studies demonstrate that treadmill exercise upregulates DA transporter expression in the dorsal striatum, enhances tyrosine hydroxylase activity, and increases DA release during cognitive tasks, indicating both protective and restorative effects on dopaminergic networks. Thus, exercise is highlighted as a key approach because of its sustained effects on DA production, receptor function, and brain plasticity, making it a strong candidate for developing effective measures to support astronauts in maintaining cognitive and emotional stability during space missions. In conclusion, the paper not only underscores the centrality of DA homeostasis in space neuroscience but also reflects the authors’ broader academic viewpoint: understanding the neurochemical substrates of behavior under microgravity is fundamental to both space health and terrestrial neuroscience. By bridging basic neurobiology with applied space medicine, this work contributes to the emerging field of gravitational neurobiology and provides a foundation for future research into individualized performance optimization in extreme environments.

With the ongoing evolution of minimally invasive thoracic surgery techniques, innovative anatomical approaches facilitating rapid perioperative recovery while achieving optimal aesthetic results and pain-free outcomes have become a pivotal direction in pulmonary resection. While periareolar incisions have demonstrated well-established advantages in cosmetic preservation and pain management in breast and thyroid procedures, the standardization of this approach for video-assisted thoracoscopic pulmonary resection requires further refinement. This consensus synthesizes the collective expertise of China's leading thoracic surgery centers in periareolar approach pulmonary resections. It aims to establish comprehensive clinical consensus that encompasses prerequisite surgical criteria, standardized perioperative management protocols, technically optimized operative procedures, and evidence-based complication prevention and management strategies, ultimately providing guidance for the standardized application of this innovative surgical technique.