Objective To evaluate the short-term effects of comprehensive health management interventions for stroke high-risk population screening on the prevention and treatment of ischemic stroke, and to provide reference and basis for improving and exploring health management and prevention strategies for stroke high-risk population. Methods From 2018 to 2022, 13 community health service centers in Jiading District, Shanghai were selected in the present study. Based on information push platform, stroke risk assessment and health intervention follow-up were conducted for community residents through convenience sampling. The residents were divided into a full course intervention group (intervention group) and a routine intervention group (control group) according to different health intervention measures and forms. The incidence of ischemic stroke in the two groups of survey subjects was tracked within 36 months. Results A total of 52144 subjects were included in the study. The total number of patients in the full course intervention group was 14227, with an incidence density of 577.32/100 000 (556.49/100 000-598.12/100 000), which was lower than that of the conventional intervention group (37 917), with an incidence density of 1 485.47/100 000 (1 464.99/100 000-1 505.94/100 000) (χ²=2490.212, P<0.001). The relative risk of the full course intervention group was 0.39, and the relative risk of stroke risk factors in the full course intervention group from low to high was 0.33, 0.43, 0.45, and 0.49, respectively. The incidence density of males in the full course intervention group was 660.76 (627.46/100 000 - 694.05/100 000), with a relative risk of 0.43, and the incidence density of female patients was 509.71/100 000 (483.37/100 000 - 536.05/100 000), with a relative risk of 0.35. The overall incidence density of the population under 62 years old gourp, 62-75 years old group and over 75 years old group was 197.45/100 000 (173.09/100 000 -221.80/100 000), 608.36/100 000 (580.19/100 000-636.54/100 000), and 1 025.06/100 000 (958.51/100 000-1 091.61/100 000), with relative risks of 0.51, 0.44, and 0.38, respectively. Conclusion Comprehensive health management measures can effectively reduce the short-term risk of ischemic stroke, and should be further promoted and improved to enhance the effectiveness of stroke prevention and control.

Hydrogenases, as a class of highly efficient and reversible biological catalysts, can catalyze the reduction of protons to molecular hydrogen, thus demonstrating great potential in a wide range of fields such as renewable energy production and green chemistry. Despite their significant potential, the large-scale industrial application of hydrogenases has long been constrained by several inherent limitations, including high sensitivity to molecular oxygen, the challenges in the in vitro reconstitution and maturation of their catalytic centers, and the inefficiency and instability of the natural electron transfer pathways. To overcome these limitations and enhance the catalytic performance of hydrogenases, researchers have developed various strategies, among which enzyme molecular engineering, photo-driven modification, and enzyme immobilization techniques are the most common exploration directions. Particularly, enzyme immobilization technology is widely used to improve the reusability of hydrogenases, but traditional immobilization methods often come with disadvantages in practical applications, such as complex multi-step procedures and insufficient biocompatibility of the immobilization materials. In recent years, bioencapsulation technology has emerged as a promising alternative strategy to enhance the catalytic performance of hydrogenases. This method utilizes biologically derived encapsulation materials to construct physically confined and precisely defined chemical microenvironments around the enzyme molecules, offering simpler self-assembly processes and superior biocompatibility. With these biomimetic constructs, bioencapsulation technology not only provides better oxygen tolerance but also helps to create a local microenvironment conducive to sustained catalytic function. This article systematically reviews the latest research progress of two main bioencapsulation strategies for hydrogenases: one is the encapsulation technology based on protein-based nanocages; the other is the engineering strategy for whole-cell hydrogenase expression. In the nanocage-based systems, this article focuses on the structural and functional characteristics of virus-like capsids and carboxysome protein shells, which serve as efficient enzyme encapsulation scaffolds, not only providing a stable physical barrier to prevent oxygen diffusion but also enabling high-density enzyme loading, thereby promoting substrate channeling effects and electron transfer kinetics. This article also discusses whole-cell encapsulation systems, which achieve hydrogenase compartmentalization within engineered cellular structures or by using external natural polysaccharide-based encapsulation matrices to wrap whole-cell catalysts. Bioencapsulation strategies can bring multiple synergistic benefits: they can effectively protect hydrogenases from oxygen-mediated inactivation, significantly delay the decline of catalytic activity over time, and enhance the hydrogen production rate by increasing the local concentration of active enzyme molecules and optimizing the electron transfer efficiency from redox partners to the catalytic center.Despite the significant progress made, several technical challenges remain to be addressed. The main obstacles include limited enzyme loading and encapsulation efficiency, insufficient long-term stability of encapsulation materials under operating conditions, and the need to improve the matching of the photo-biological interface in systems integrating light-harvesting components with enzymatic catalysis. Future efforts can focus on the integration of multiple technological approaches, such as using computer-aided protein design to optimize encapsulation structures, developing engineered electron transfer pathways to enhance catalytic conversion efficiency, and designing composite multifunctional materials with both structural stability and functional adaptability. These directions collectively aim to achieve efficient, stable, and scalable hydrogen production applications of bioencapsulated hydrogenase systems.

Hydrogenases, as a class of highly efficient and reversible biological catalysts, can catalyze the reduction of protons to molecular hydrogen, thus demonstrating great potential in a wide range of fields such as renewable energy production and green chemistry. Despite their significant potential, the large-scale industrial application of hydrogenases has long been constrained by several inherent limitations, including high sensitivity to molecular oxygen, the challenges in the in vitro reconstitution and maturation of their catalytic centers, and the inefficiency and instability of the natural electron transfer pathways. To overcome these limitations and enhance the catalytic performance of hydrogenases, researchers have developed various strategies, among which enzyme molecular engineering, photo-driven modification, and enzyme immobilization techniques are the most common exploration directions. Particularly, enzyme immobilization technology is widely used to improve the reusability of hydrogenases, but traditional immobilization methods often come with disadvantages in practical applications, such as complex multi-step procedures and insufficient biocompatibility of the immobilization materials. In recent years, bioencapsulation technology has emerged as a promising alternative strategy to enhance the catalytic performance of hydrogenases. This method utilizes biologically derived encapsulation materials to construct physically confined and precisely defined chemical microenvironments around the enzyme molecules, offering simpler self-assembly processes and superior biocompatibility. With these biomimetic constructs, bioencapsulation technology not only provides better oxygen tolerance but also helps to create a local microenvironment conducive to sustained catalytic function. This article systematically reviews the latest research progress of two main bioencapsulation strategies for hydrogenases: one is the encapsulation technology based on protein-based nanocages; the other is the engineering strategy for whole-cell hydrogenase expression. In the nanocage-based systems, this article focuses on the structural and functional characteristics of virus-like capsids and carboxysome protein shells, which serve as efficient enzyme encapsulation scaffolds, not only providing a stable physical barrier to prevent oxygen diffusion but also enabling high-density enzyme loading, thereby promoting substrate channeling effects and electron transfer kinetics. This article also discusses whole-cell encapsulation systems, which achieve hydrogenase compartmentalization within engineered cellular structures or by using external natural polysaccharide-based encapsulation matrices to wrap whole-cell catalysts. Bioencapsulation strategies can bring multiple synergistic benefits: they can effectively protect hydrogenases from oxygen-mediated inactivation, significantly delay the decline of catalytic activity over time, and enhance the hydrogen production rate by increasing the local concentration of active enzyme molecules and optimizing the electron transfer efficiency from redox partners to the catalytic center.Despite the significant progress made, several technical challenges remain to be addressed. The main obstacles include limited enzyme loading and encapsulation efficiency, insufficient long-term stability of encapsulation materials under operating conditions, and the need to improve the matching of the photo-biological interface in systems integrating light-harvesting components with enzymatic catalysis. Future efforts can focus on the integration of multiple technological approaches, such as using computer-aided protein design to optimize encapsulation structures, developing engineered electron transfer pathways to enhance catalytic conversion efficiency, and designing composite multifunctional materials with both structural stability and functional adaptability. These directions collectively aim to achieve efficient, stable, and scalable hydrogen production applications of bioencapsulated hydrogenase systems.

ObjectiveTo investigate the association of the traditional Chinese medicine （TCM） syndrome types of primary liver cancer （PLC） with clinical features and multimodal quantitative radiological features on computed tomography （CT） and magnetic resonance imaging （MRI）， and to provide a reference for the objectification of TCM syndrome differentiation and precise diagnosis and treatment. MethodsA retrospective analysis was performed for the clinical data of 312 patients who were diagnosed with PLC in The First Affiliated Hospital of Hunan University of Chinese Medicine from March 2020 to June 2025， and according to the TCM syndrome type， they were divided into stagnation of liver Qi group with 40 patients， stagnation of liver Qi and spleen deficiency group with 109 patients， Qi stagnation and blood stasis group with 62 patients， dampness-heat toxin amassment group with 81 patients， and liver-kidney Yin deficiency group with 20 patients. Clinical features and multimodal quantitative radiological features were compared between the patients with different TCM syndrome types. A one-way analysis of variance was used for comparison of normally distributed continuous data between multiple groups， and the least significant difference t-test was used for further comparison between two groups； the Kruskal-Wallis H test was used for comparison of non-normally distributed continuous data between multiple groups， and the Dunn’s multiple test was used for further comparison between two groups； the chi-square test was used for comparison of categorical data between groups， and the Bonferroni method was used for further comparison between two groups. ResultsThere were significant differences between the patients with different TCM syndrome types in China liver cancer staging （CNLC）， Child-Pugh class， alanine aminotransferase， aspartate aminotransferase， albumin， direct bilirubin， total bilirubin， prothrombin time， neutrophil， and albumin-bilirubin score （all P<0.05）. In the stagnation of liver Qi group， the patients with Child-Pugh class A accounted for 75.00%； among the patients with CNLC stage I PLC， the patients with stagnation of liver Qi accounted for 60.00%， and those with Qi stagnation and blood stasis syndrome accounted for 59.68%， while among the patients with CNLC stage IV PLC， the distribution proportion of dampness-heat toxin amassment （27.16%） and liver-kidney Yin deficiency （30.00%） was significantly higher than that of stagnation of liver Qi （2.50%） （all P<0.05）. Radiological examination showed that there were significant differences between the patients with different TCM syndrome types in the number of tumors， ascites， venous tumor thrombus， maximum tumor diameter， intrahepatic metastasis， and lymph node metastasis in the hepatic hilar and retroperitoneal regions （all P<0.05）. Compared with the patients with stagnation of liver Qi， the patients with liver depression and spleen deficiency or liver-kidney Yin deficiency were more likely to develop intrahepatic metastasis； the patients with liver depression and spleen deficiency， dampness-heat toxin amassment， or liver-kidney Yin deficiency were more likely to develop lymph node metastasis in the hepatic hilar and retroperitoneal regions； the patients with liver-kidney Yin deficiency were more likely to experience multiple tumors； the patients with liver depression and spleen deficiency or dampness-heat toxin amassment were more likely to develop ascites （all P<0.05）. Compared with the patients with Qi stagnation and blood stasis syndrome， the patients with liver depression and spleen deficiency had a significantly longer maximum tumor diameter and a significantly higher proportion of patients with venous tumor thrombus （both P<0.05）. Furthermore， among the 184 patients with MRI diffusion-weighted imaging sequences， the patients with dampness-heat toxin amassment or Qi stagnation and blood stasis syndrome had significantly higher ADC values and relative ADC values than those with stagnation of liver Qi （all P<0.05）. ConclusionThere are significant differences in CT/MRI radiological features and clinical features between PLC patients with different TCM syndrome types， among whom the patients with liver depression and spleen deficiency， dampness-heat toxin amassment， and liver-kidney Yin deficiency tend to exhibit progressive radiological features， and those with dampness-heat toxin amassment or Qi stagnation and blood stasis syndrome tend to have higher ADC values. These findings provide an objective basis for TCM syndrome differentiation in PLC.

ObjectiveStroke poses a heavy burden due to its high mortality and morbidity rates. Accurate and real-time detection of lesions is pivotal for prompt clinical intervention and favorable prognosis. Electrical impedance tomography (EIT) and microwave tomography (MWT) have emerged as compelling alternatives for stroke screening, owing to their non-ionizing, non-invasive and portable nature. EIT provides information on tissue conductivity, and MWT offers high sensitivity to changes in dielectric properties. However, single-modality imaging is inherently limited, EIT suffers from low sensitivity to deep-seated tissues and severe ill-posedness of inverse problems, whereas MWT is challenged by strong nonlinearity in inverse scattering and susceptibility to modeling errors. Consequently, the clinical utility of standalone EIT or MWT for stroke diagnosis remains constrained by poor spatial resolution and imaging artifacts. To improve the accuracy and robustness of stroke imaging, a dual-modality fusion conditional denoising diffusion probabilistic model (DM-DDPM) was proposed for high-precision dual-modality image reconstruction. MethodsA dual-encoder network with a symmetric architecture and independently trained parameters was constructed to extract heterogeneous features separately from EIT boundary voltage measurements and MWT scattered field signals. Attentional feature fusion (AFF) is employed to integrate complementary information from the two modalities adaptively, generating robust fused priors that suppress redundant noise while preserving key physical characteristics. Subsequently, the fused priors are embedded into a Transformer-based diffusion model via a cross attention mechanism to guide the reverse denoising process. This approach effectively reduces artifacts and enhances the stability of conductivity distribution reconstruction. Time step embedding is introduced to enable the network to perceive the diffusion stage and further improve the accuracy of noise prediction. ResultsSimulated experiments demonstrated that DM-DDPM significantly outperforms single-modality and multi-modality networks under various noise levels. A head model simulation dataset was constructed based on COMSOL Multiphysics, and tests were carried out under 50 dB, 40 dB and 30 dB signal-to-noise ratio levels. At 30 dB, the average relative error (RE) was below 0.20, while the structural similarity index measure (SSIM) and correlation coefficient (CC) remained above 0.90 and 0.89, respectively. Compared with single-modality and multi-modality networks, artifacts were significantly reduced, lesion edges were clearer, and localization was more accurate. The model maintains high reconstruction quality and strong robustness for single, double, and triple lesions simultaneously. Furthermore, physical experiments were conducted using a 16-electrode EIT system and a 16-antenna MWT system with asynchronous data acquisition. These experiments confirmed the feasibility of the method in real-world scenarios and demonstrated that it can robustly reconstruct simulated lesions despite environmental interference and measurement noise, validating its reliability for practical clinical applications. ConclusionThe proposed method effectively combines complementary dual-modality information with a conditional diffusion model. Low accuracy and poor noise resistance in single-modality imaging were effectively addressed, while the noise amplification issue caused by direct multimodal data fusion was avoided. The proposed algorithm exhibits strong anti-noise interference ability and high imaging stability in both simulation and physical experiments. Precise localization of stroke lesions with different quantities was achieved, providing a high-precision, and practical technical support for clinical stroke detection.

Objective To explore the recognition capabilities of electronic nose combined with machine learning in identifying the breath odor map of benign and malignant pulmonary nodules and Traditional Chinese Medicine (TCM) syndrome elements. Methods The study design was a single-center observational study. General data and four diagnostic information were collected from 108 patients with pulmonary nodules admitted to the Department of Cardiothoracic Surgery of Hospital of Chengdu University of TCM from April 2023 to March 2024. The patients' TCM disease location and nature distribution characteristics were analyzed using the syndrome differentiation method. The Cyranose 320 electronic nose was used to collect the odor profiles of oral exhalation, and five machine learning algorithms including random forest (RF), K-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM), and eXtreme gradient boosting (XGBoost) were employed to identify the exhaled breath profiles of benign and malignant pulmonary nodules and different TCM syndromes. Results (1) The common disease locations in pulmonary nodules were ranked in descending order as liver, lung, and kidney; the common disease natures were ranked in descending order as Yin deficiency, phlegm, dampness, Qi stagnation, and blood deficiency. (2) The electronic nose combined with the RF algorithm had the best efficacy in identifying the exhaled breath profiles of benign and malignant pulmonary nodules, with an AUC of 0.91, accuracy of 86.36%, specificity of 75.00%, and sensitivity of 92.85%. (3) The electronic nose combined with RF, LR, or XGBoost algorithms could effectively identify the different TCM disease locations and natures of pulmonary nodules, with classification accuracy, specificity, and sensitivity generally exceeding 80.00%.Conclusion Electronic nose combined with machine learning not only has the potential capabilities to differentiate the benign and malignant pulmonary nodules, but also provides new technologies and methods for the objective diagnosis of TCM syndromes in pulmonary nodules.

Laparoscopic subtotal cholecystectomy (LSC) has been a safe and viable alternative to conversion to laparotomy in cases of severe cholecystitis. The objective of this study is to determine the utility of intraoperative choledochoscopy in LSC for the exploration of the gallbladder, cyst duct, and subsequent stone clearance of the cystic duct in cases of severe cholecystitis. A total of 72 patients diagnosed with severe cholecystitis received choledochoscopy-assisted laparoscopic subtotal cholecystectomy (CALSC). A choledochoscopy was performed to explore the gallbladder cavity and/or cystic duct, and to extract stones using a range of techniques. The clinical records, including the operative records and outcomes, were subjected to analysis. No LSC was converted to open surgery, and no bile duct or vascular injuries were sustained. All stones within the cystic duct were removed by a combination of techniques, including high-frequency needle knife electrotomy, basket, and electrohydraulic lithotripsy. A follow-up examination revealed the absence of residual bile duct stones, with the exception of one common bile duct stone, which was extracted via endoscopic retrograde cholangiopancreatography. In certain special cases, CALSC may prove to be an efficacious treatment for the management of severe cholecystitis. This technique allows for optimal comprehension of the situation within the gallbladder cavity and cystic duct, facilitating the removal of stones from the cystic duct and reducing the residue of the non-functional gallbladder remnant.

This study explored whether Astragalus polysaccharide(APS)can regulate the VEGF/VEGFR signaling pathway to affect the proliferative activity of rat intestinal mucosal microvascu-lar endothelial cells(RIMMVECs).RIMMVECs were isolated from newborn rats,then purified and treated with APS at concentrations of 0.1,1.0,10.0,100.0,1 000.0,and 10 000.0 mg/L.MTT was used to determine the effect of APS on RIMMVECs proliferation and screen for the optimal concentration of APS.Subsequently,flow cytometry was used to detect the changes in cell cycle to evaluate the stage of action of APS on the cell cycle in RIMMVECs.Then,the ELISA was used to detect the changes of VEGFA in cell supernatant to evaluate the potential of cell proliferation and angiogenesis.The changes in fluorescence intensity of Fluo-8AM was observed using fluorescence microscopy to evaluate intracellular Ca2+levels.Finally,Western blot was used to detect the ex-pression of PERK in RIMMVECs to analyze the possible mechanism of APS.The results showed that 100 mg/L APS significantly enhanced the proliferative activity of RIMMVECs,increased the content of VEGFA in the cell supernatant,the intracellular Ca2+levels,and the expression of PERK protein,indicating that APS promotes the proliferation of RIMMVECs,which may be a-chieved by promoting the expression of VEGFA and activating the ERK pathway.

Objective:To construct a nursing quality evaluation indicator system for pulse indicator continuous cardiac output (PiCCO) monitoring and provide a basis for evaluating the nursing quality of PiCCO monitoring.Methods:Using Donabedian′s "structure-process-result" three-dimensional quality evaluation model as the theoretical framework, the nursing quality evaluation indicator system for PiCCO was established through literature search, Delphi expert correspondence, and hierarchical analysis during the period May to August 2023.Results:Of the 22 experts, 6 were male and 16 were female, aged (46.59 ± 4.34) years. The return rates of the questionnaires of the 2 rounds of expert correspondence were both 100%, the coefficients of expert authority were both 0.945, and the Kendall coordination coefficients were 0.045-0.186 ( χ2 values were 2.00-221.46, all P<0.05) and 0.045-0.132 ( χ2 values were 2.00-82.16, all P<0.05), respectively. The finalized nursing quality evaluation indicator system for PiCCO included 3 primary indicators, 7 secondary indicators, and 36 tertiary indicators. Conclusions:The nursing quality evaluation indicator system for PiCCO is practical and scientific, which can provide reference for PiCCO monitoring nursing quality evaluation.

Objective:To develop and validate the Pain nursing Competency Evaluation Questionnaire for Nursing Students to provide an effective tool for measuring the pain management competency of nursing students in China.Methods:The questionnaire was constructed through literature review, semi-structured interviews, focus group discussions, Delphi expert consultation, and a pre-survey. From September 2023 to January 2024, a convenience sampling method was used to select 250 nursing students from Hangzhou Normal University and Lishui University in Zhejiang Province for the survey. Reliability and validity of the developed questionnaire were tested. A random sample of 30 nursing students was selected for retesting after two weeks.Results:A total of 10 female experts were consulted through correspondence. The Pain Care Competency Evaluation Questionnaire for nursing students consists of 36 items. Through exploratory factor analysis, five common factors were extracted: pain health education, comprehensive pain assessment, pain screening and assessment, analgesic interventions, and analgesic side effects nursing, which together explained 61.695% of the variance. The content validity of the questionnaire was 0.96, and the item-level content validity index ranged from 0.900 to 1.000. The overall Cronbach′s α coefficient was 0.924, and the Cronbach′s α coefficients for the five dimensions ranged from 0.856 to 0.915. The test-retest reliability was 0.831. Conclusions:The Pain Care Competency Evaluation Questionnaire for nursing students developed in this study has good reliability and validity. It can be used as a tool to assess nursing students′ competency in pain care and provides a reference for the design and optimization of pain care courses and clinical practice programs for nursing students in undergraduate institutions.