ObjectiveTo evaluate the impact of yang-reinforcing and blood-activating therapy on the long-term prognosis for patients with dilated cardiomyopathy （DCM） of yang deficiency and blood stasis syndrome. MethodsA retrospective cohort study was conducted involving 371 DCM patients with yang deficiency and blood stasis syndrome. The yang-reinforcing and blood-activating therapy was defined as the exposure factor. Patients were categorized into exposure group （186 cases） and non-exposure group （185 cases） according to whether they received yang-reinforcing and blood-activating therapy combined with conventional western medicine for 6 months or longer. The follow-up period was set at 48 months， and the Kaplan-Meier survival analysis was used to assess the cumulative incidence of major adverse cardiovascular events （MACE） in both groups. Cox regression analysis was used to explore the impact of yang-reinforcing and blood-activating therapy on the risk of MACE， and subgroup analysis was performed. Changes in traditional Chinese medicine （TCM） syndrome score， left ventricular ejection fraction （LVEF）， left ventricular fractional shortening （LVFS）， left ventricular end-diastolic diameter （LVEDD）， and Minnesota Living with Heart Failure Questionnaire （MLHFQ） score were compared between groups at the time of first combined use of yang-reinforcing and blood-activating therapy （before treatment） and 1 year after receiving the therapy （after treatment）. ResultsMACE occurred in 31 cases （16.67%） in the exposure group and 47 cases （25.41%） in the non-exposure group. The cumulative incidence of MACE in the exposure group was significantly lower than that in the non-exposure group ［HR=0.559， 95%CI（0.361，0.895）， P=0.014］. Cox regression analysis showed that yang-reinforcing and blood-activating therapy was an independent factor for reducing the risk of MACE in DCM patients ［HR=0.623， 95%CI（0.396，0.980）， P=0.041］， and consistent results were observed in different subgroups. Compared with pre-treatment， the exposure group showed decreased TCM syndrome score and MLHFQ score， reduced LVEDD， and increased LVEF and LVFS after treatment （P＜0.05）； in the non-exposure group， TCM syndrome score decreased， LVEF and LVFS increased， and LVEDD reduced after treatment （P＜0.05）. After treatment， the exposure group had higher LVEF and LVFS， smaller LVEDD， and lower TCM syndrome score and MLHFQ score compared with the non-exposure group （P＜0.05）. ConclusionCombining yang-reinforcing and blood-activating therapy with conventional western medicine can reduce the risk of MACE in DCM patients with yang deficiency and blood stasis syndrome， meanwhile improving their clinical symptoms， cardiac function， and quality of life.

ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

The standard of Pharmaceutical packaging materials is an important part of the Chinese Pharmacopoeia. This article focuses on working background, general idea, working process, main framework, and its role and significance of the pharmaceutical packaging materials standards system in the Chinese Pharmacopoeia 2025 Edition, which can contribute to accurately understand and utilize the standards in the Chinese Pharmacopoeia 2025 Edition.

Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

Objective To explore the influence of blood uric acid (serum uric acid, SUA) and fasting plasma glucose (FPG） on the occurrence of coronary heart disease in patients with type 2 diabetes mellitus (T2DM). Methods T2DM patients admitted to 3201 Hospital from January 2021 to January 2024 were selected and divided into a combined coronary heart disease(CHD) and a simple diabetes mellitus (DM). The clinical data were collected, and the blood SUA and FPG levels were analyzed. The basic characteristics and biochemical indicators of the two groups were analyzed. Risk factors affecting the severity of coronary lesions were identified by multivariate logistic regression analysis. The interaction between SUA and FPG was also evaluated. Results A total of 98 T2DM patients were included in this study, including 53 and 45 patients in the DM and combined CHD groups, respectively. Compared with the DM group, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), triglycerides (TG), SUA and FPG levels were significantly higher in the combined CHD group. The differences were all statistically significant (P<0.05). The multivariate logistic regression model analysis showed that LDL-C (OR=1.490, 95%CI: 1.044-1.824), HDL-C (OR=1.182, 95%CI: 0.846-1.314), TC (OR=1.075, 95%CI: 0.891-1.190), TG (OR=1.695, 95%CI: 1.230-2.164), SUA (OR=1.820, 95%CI: 1.294-2.424) and the FPG level (OR=2.154, 95%CI: 1.532-3.079) could be an independent risk factor for the development of CHD (OR value>1, P<0.05). The results of the interaction analysis showed a positive and additive interaction between SUA and FPG, and the difference was statistically significant (P<0.05). Conclusion Both SUA and FPG levels are independent risk factors for the occurrence of CHD. A positive additive interaction between the two may together contribute to the risk of CHD in T2DM patients.

Objective To analyze the current situation of the knowledge-attitude-practice among noise-exposed workers at an airport apron. Methods A total of 494 noise-exposed workers from an airport apron were selected as the study subjects using the judgmental sampling method. A self-designed "Occupational Protection Knowledge, Attitudes, and Practices Questionnaire" was used to assess the current situation of knowledge-attitude-practice on occupational protection. Results Regarding the awareness of noise hazards among the study subjects, the awareness rates of noise-induced impairment on digestive function and reproductive system were the lowest (44.9% and 37.7%, respectively). The awareness rate of noise-induced negative emotions increased with length of service (P<0.01). Regarding the occupational protection knowledge for noise, the awareness rate of occupational noise-induced deafness was “incurable” was the lowest (39.1%). The support rate for five kinds of occupational protection attitudes for noise was generally >85.0%, while only 58.3% of the study subjects consistently or frequently wearing earplugs during work. The most common source of noise hazard and protection knowledge was pre-employment training (76.9%), followed by occupational disease prevention and control campaigns (76.1%). Conclusion Noise-exposed workers in this airport apron have incomplete awareness of non-auditory system hazards caused by noise, and the awareness of knowledge of some occupational protection is relatively low. Although their attitudes toward occupational protection are positive, many workers still fail to consistently wear personal protective equipment at work.

Parkinson’s disease (PD) is a common neurodegenerative disorder that significantly impacts patients’ independence and quality of life, imposing a substantial burden on both individuals and society. Although dopaminergic replacement therapies provide temporary relief from various symptoms, their long-term use often leads to motor complications, limiting overall effectiveness. In recent years, non-invasive deep brain stimulation (DBS) techniques have emerged as promising therapeutic alternatives for PD, offering a means to modulate deep brain regions with high precision without invasive procedures. These techniques include temporal interference stimulation (TIs), low-intensity transcranial focused ultrasound stimulation (LITFUS), transcranial magneto-acoustic stimulation (TMAS), non-invasive optogenetic modulation, and non-invasive magnetoelectric stimulation. They have demonstrated significant potential in alleviating various PD symptoms by modulating neural activity within specific deep brain structures affected by the disease. Among these approaches, TIs and LITFUS have received considerable attention. TIs generate low-frequency interference by applying two slightly different high-frequency electric fields, targeting specific brain areas to alleviate symptoms such as tremors and bradykinesia. LITFUS, on the other hand, uses low-intensity focused ultrasound to non-invasively stimulate deep brain structures, showing promise in improving both motor function and cognition in PD patients. The other three techniques, while still in early research stages, also hold significant promise for deep brain modulation and broader clinical applications, potentially complementing existing treatment strategies. Despite these promising findings, significant challenges remain in translating these techniques into clinical practice. The heterogeneous nature of PD, characterized by variable disease progression and individualized treatment responses, necessitates flexible protocols tailored to each patient’s unique needs. Additionally, a comprehensive understanding of the mechanisms underlying these treatments is crucial for refining protocols and maximizing their therapeutic potential. Personalized medicine approaches, such as the integration of neuroimaging and biomarkers, will be pivotal in customizing stimulation parameters to optimize efficacy. Furthermore, while early-stage clinical trials have reported improvements in certain symptoms, long-term efficacy and safety data are limited. To validate these techniques, large-scale, multi-center, randomized controlled trials are essential. Parallel advancements in device design, including the development of portable and cost-effective systems, will improve patient access and adherence to treatment protocols. Combining non-invasive DBS with other interventions, such as pharmacological treatments and physical therapy, could also provide a more comprehensive and synergistic approach to managing PD. In conclusion, non-invasive deep brain stimulation techniques represent a promising frontier in the treatment of Parkinson’s disease. While they have demonstrated considerable potential in improving symptoms and restoring neural function, further research is needed to refine protocols, validate long-term outcomes, and optimize clinical applications. With ongoing technological and scientific advancements, these methods could offer PD patients safer, more effective, and personalized treatment options, ultimately improving their quality of life and reducing the societal burden of the disease.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Objective: To examine the relationship between self-management behaviors and time perspective among patients with comorbid diabetes, so as to provide the evidence for improving self-management behaviors among patients with comorbid diabetes. Methods: The patients with comorbid diabetes who were registered in the chronic disease health management system of Minhang District, Shanghai Municipality in 2021, followed up regularly, and lived in Meilong Town were recruited. Demographic information and family history of diabetes were collected through questionnaire surveys. Time perspective and self-management behaviors were assessed using the Zimbardo Time Perspective Inventory and Diabetes Self-Management Behavior Scale, respectively. The relationship between self-management behaviors and time perspective was analyzed using a multivariable ordinal logistic regression model. Results: A total of 907 patients with comorbid diabetes were enrolled, including 472 males (52.04%) and 435 females (47.96%). There were 652 cases aged 65 years and above, accounting for 71.89%. In terms of the types of time perspective, 280 patients were future-oriented (30.87%), 236 were balanced (26.02%), 162 were sensation-seeking (17.86%), 123 were fatalistic (13.56%), and 106 were negative (11.69%). In terms of the self-management behaviors, 46 patients were good (5.07%), 643 were moderate (70.89%), and 218 were poor (24.04%). Multivariable ordinal logistic regression analysis showed that after adjusting for age, gender, educational level, marital status, occupation status, monthly income, and family history of diabetes, the patients with comorbid diabetes who had a future-oriented time perspective had better self-management behaviors (OR=1.874, 95%CI: 1.204-2.915). Conclusion The self-management behaviors among patients with comorbid diabetes are moderate to poor, and patients with a future-oriented time perspective can better engage in self-management behaviors.