The gut microbiota is regarded as the "eighth organ" of the human body and plays a critical regulatory role in the occurrence and progression of various diseases. Ulcerative colitis （UC） is a chronic inflammatory bowel disease with a complex etiology and a tendency toward recurrent episodes. In recent years， studies have shown that gut microbiota dysbiosis plays a key role in its pathological processes. Meanwhile， an increasing number of studies have demonstrated that imbalances in the gut microbiota and abnormalities in its metabolites are closely associated with the development of atrial fibrillation （AF）. Although UC and AF belong to diseases of the digestive system and cardiovascular system， respectively， both exhibit systemic inflammatory characteristics and are often accompanied by gut microbiota dysregulation and abnormal metabolic products. However， systematic investigations into the mechanisms by which gut microbiota-derived metabolites act in these two diseases remain limited. Based on this， the present study adopts literature review and theoretical analysis methods， taking the "gut microbiota-gut-heart" axis as the entry point， to systematically summarize the signaling networks of three key classes of metabolites， i.e.， short-chain fatty acids （SCFAs）， bile acids （BAs）， and trimethylamine N-oxide （TMAO）， in the comorbidity mechanism of UC and AF. The findings indicate that these metabolites may activate key inflammatory pathways， such as NF-κB and NLRP3， thereby synergistically mediating intestinal barrier dysfunction and systemic inflammation and constructing a potential comorbidity network. On this basis， potential intervention strategies for the treatment of UC-AF comorbidity， including probiotic intervention and fecal microbiota transplantation， are further discussed. This study aims to provide new theoretical evidence and research perspectives for prevention and treatment strategies of cross-system diseases.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveGastric hemorrhage is one of the most common and life-threatening emergencies of the upper digestive tract. Early identification and continuous monitoring are essential for reducing rebleeding rates and mortality, particularly within the critical early hours after onset. Although endoscopy and radiological imaging can accurately localize bleeding sites, these approaches are invasive, resource-intensive, and unsuitable for continuous bedside monitoring. Electrical impedance tomography (EIT), as a noninvasive and radiation-free functional imaging technique, offers real-time visualization of conductivity distribution and has the potential for detecting intragastric bleeding based on the electrical contrast between blood and surrounding gastric tissues. In this study, a three-dimensional gastric EIT (3D-gEIT) framework is proposed to achieve noninvasive, real-time, and dynamic monitoring of gastric hemorrhage, with emphasis on spatial localization and quantitative volume assessment. MethodsA three-dimensional upper-abdominal simulation model incorporating the stomach, gastric wall, gastric contents, and surrounding tissues was established. Three electrode configurations, namely the dual layer ring, the four layer staggered ring, and the opposed dual plane array, were designed and systematically compared to evaluate their influence on depth sensitivity and spatial resolution. Based on the Tikhonov-Noser hybrid regularization scheme, a region-clustering constraint was introduced to develop the TK-Noser-RCC algorithm. This approach aggregates spatially adjacent elements with similar conductivity variations, thereby enhancing structural continuity and suppressing isolated noise artifacts. To validate the proposed framework, an upper-abdominal physical phantom was constructed using agar to simulate background tissue conductivity. Hemispherical high-conductivity inclusions with volumes ranging from 10 ml to 50 ml were attached to the inner gastric wall to mimic localized bleeding under different gastric filling states. Boundary voltages were acquired under a 120 kHz excitation current and reconstructed using the TK-Noser-RCC algorithm. Furthermore, an in vivo animal experiment was performed using a porcine model with adult-scale abdominal dimensions. A total of 100 ml of autologous blood was injected incrementally into the stomach to simulate progressive gastric hemorrhage, and time-difference EIT reconstruction was conducted at each injection stage to assess the dynamic system response under physiological conditions. ResultsSimulation results demonstrated that the opposed dual-plane electrode array achieved superior depth sensitivity distribution and spatial resolution. For a 40 ml hemorrhage model, the average ICC and SSIM improved by 55.9% and 38.8% compared with the dual-layer ring configuration, and by 64.0% and 39.5% compared with the four-layer staggered configuration. The proposed region-clustering constraint significantly enhanced reconstruction stability. Under added Gaussian noise of 40 dB and 30 dB, ICC values remained approximately 0.85, indicating effective artifact suppression and preservation of boundary integrity. In physical phantom experiments, reconstructed hemorrhage volumes increased approximately linearly with the preset hemispherical volumes, and the reconstructed high-conductivity regions closely matched the actual bleeding locations. Both empty-stomach and full-stomach conditions were evaluated, demonstrating that the opposed dual-plane configuration maintained stable imaging performance across varying gastric contents. In the animal experiment, reconstructed low-impedance regions expanded progressively with increasing injected blood volume. The spatial localization of the hemorrhage remained stable throughout the procedure, and no significant artifacts were observed. Quantitative analysis showed that reconstructed volume and average conductivity variation exhibited an approximately linear growth trend with injected blood volume, confirming the sensitivity of the system to dynamic intragastric conductivity changes. ConclusionThe proposed 3D-gEIT framework enables quantitative reconstruction of gastric hemorrhage volume and spatial distribution with improved depth sensitivity, structural continuity, and noise robustness compared with conventional EIT approaches. By integrating optimized electrode configuration and a region-clustering-constrained reconstruction algorithm, the system provides stable dynamic monitoring under both controlled phantom conditions and in vivo physiological environments. This method offers a noninvasive, real-time, and low-cost imaging strategy for early diagnosis, postoperative monitoring, and bedside surveillance of gastric bleeding.

OBJECTIVE To formulate Guidelines for the standardized implementation of pharmacist-managed clinics （ 2026 edition ） in response to the challenges faced by such clinics in China， including uneven development， large discrepancies in service specifications， insufficient patient awareness， and limited medical insurance coverage. METHODS Led by the Pharmaceutical Affairs Professional Committee of the Chinese Hospital Association， the Evidence-based Pharmacy Professional Committee of the Chinese Pharmaceutical Association， and the Hospital Pharmacy Professional Committee of the Cross-strait Medical and Health Exchange Association， a total of 19 domestic hospital pharmacy experts were organized. Through a systematic review of national policies and literature research， current practical experience was summarized. Consensus on the contents of the guidelines was reached after in-depth discussions. RESULTS &CONCLUSIONS The guidelines covered five sections： definition and connotation of pharmacist-managed clinics， establishment requirements， implementation and management， post competency， and practical research. Firstly， the definition and connotation included three operational forms of pharmacist-managed clinics （independent mode， physician-pharmacist joint mode， and online pharmacist-managed clinic mode） and classified service modes （specialty-specific， drug-specific， and disease-specific pharmacist-managed clinics）. The establishment requirements were further refined， covering system construction （pharmaceutical service management system， quality control and assessment mechanism）， personnel qualifications （professional credentials， continuing education and professional training， etc）， service recipients， as well as service venues and facilities. Subsequently， the implementation and management of pharmacist-managed clinics were proposed， involving service procedures， intervention measures， documentation and records， patient education and follow-up， humanistic care， as well as risk management and quality control. Finally， post competency encompassed the competency requirements for pharmacists providing services in pharmacist-managed clinics， as well as the suggestions on teaching methods； practical research encouraged the conduct of high-quality pharmaceutical practice in the setting of pharmacist-managed clinics. The guidelines provide valuable guidance for the standardized implementation of pharmacist-managed clinics in China in terms of establishment， management， teaching， and research， fill the guideline gap in this field， and can promote the high-quality development of pharmacist-managed clinics.

By consulting herbal texts， medical records， formula collections， and other relevant literature from various historical periods， as well as modern and contemporary research materials， different aspects of the historical evolution of Zijingpi， including its name， origin， scientific name verification， medicinal part， genuine producing areas， harvesting， processing， and preparation， properties and flavors， and primary indications， were systematically reviewed and verified， providing a basis for the development of famous classical formula preparations containing this medicinal material. According to the textual research， Cercis chinensis was first recorded under the name "Zijingmu" in the Rihuazi Bencao from the Five Dynasties period. From the Song Dynasty to the Qing Dynasty， it was known by various names such as "Zijing"， "Zijingpi"， and "Zijingmupi". In modern and contemporary times， it has been officially named "Zijingpi"， with aliases such as "Mantiaohong"， "Zihuashu"， and "Qingminghua". Historically， the mainstream source of Zijingpi was the dried bark of Cercis chinensis Bunge， a species of the legume family. However， there were also instances of confusion with the Lythraceae plant Lagerstroemia indica L. The producing areas of Zijingpi have no special geographical limitation， and the plant is currently distributed throughout most parts of China. There were no special requirements for harvesting time in ancient times， while modern records indicate harvesting time in spring， summer， and autumn. Ancient processing methods were rarely recorded， with only mentions of stir-frying Zijingpi. Modern practice mostly uses the raw material medicinally. Modern standards prefer it to be "dry， long strips， and thick". The functions of Zijingpi， mainly to promote blood circulation， relieve strangury， and detoxify， have remained consistent from ancient to modern times. Based on the textual research findings， it is recommended that when developing and exploiting the famous classical formulas containing Zijingpi， the bark of C. chinensis should be selected as the source. The processing method should be chosen according to the formula requirements， and if no specific requirements are indicated， it is suggested to use the raw material medicinally.

Objective To analyze the spatiotemporal distribution characteristics of and trends in the disease burden of dengue fever in China from 2005 to 2024, so as to provide insights into formulation of dengue fever control strategies. Methods Data pertaining to dengue fever cases in China from 2005 to 2024 were retrieved from the Infectious Disease Reporting Information System of Chinese Center for Disease Control and Prevention, and city population, gross domestic product (GDP), GDP per capita, and consumer price index in China were captured from the China Statistical Yearbook, National Bureau of Statistics of China, the China City Statistical Yearbook, and bureaus of statistics in each city. The disability-adjusted life years (DALYs), years of life lost (YLLs), and years lived with disability (YLDs) due to dengue fever were calculated in China from 2005 to 2024. The direct and indirect economic burdens of dengue fever were estimated to calculate the total economic burden. The trends in the disease burden of dengue fever were estimated in China from 2005 to 2024 using a Joinpoint regression model with the software Joinpoint 4.9.0.0, and the average annual percent change (AAPC) and its 95% confidence interval (CI) were calculated. In addition, the DALYs rate and economic burden of dengue fever in China were subjected to global and local spatial autocorrelation analyses using the software ArcGIS 10.8. Results The gross DALYs due to dengue fever were 5 558 person-years in China from 2005 to 2024, and the DALYs of dengue fever increased from 36 person-years in 2005 to 899 person-years in 2024, with an increase of 23.97 folds. The average annual DALYs rate of dengue fever was 0.02 person-years/10⁵ in China during the 20-year study period from 2005 to 2024, and the DALYs rate peaked in 2014 (0.13 person-years/10⁵) and reduced during the COVID-19 pandemic from 2020 to 2022. YLDs were the main contributor of DALYs due to dengue fever in China from 2005 to 2024, with a total of 5 354 person-years, accounting for 96.33% (5 354 person-years/5 558 person-years) of the gross DALYs. The gross DALYs of dengue fever were 2 982 person-years among men (53.66%) and 2 575 person-years among women (46.34%) in China from 2005 to 2024, and high DALYs of dengue fever were measured among residents at ages of 15 to 30 years (1 639 person-years), 30 to 45 years (1 857 person-years), and 45 to 60 years (1 204 person-years), respectively, accounting for 84.56% (4 700 person-years/5 558 person-years) of total DALYs due to dengue fever in China. The total economic burden of dengue fever was estimated to be 612 million Yuan in China from 2005 to 2024, with an average annual economic burden of 30.584 million Yuan. The economic burden of dengue fever increased from 196 000 Yuan in 2005 to 121 million Yuan in 2024 in China, with an increase of 616.35 folds, and the per capita economic burden increased from 3 322.21 Yuan in 2005 to 4 940.01 Yuan in 2024, with an increase of 48.70%. Dengue fever cases were reported in 274 cities (counties) across 31 provinces (autonomous regions, municipalities) in China from 2005 to 2024, with relatively higher DALYs in Guangdong Province and Yunnan Province. Spatial autocorrelation analysis revealed that the disease burden of dengue fever appeared positive aggregation in Chinese cities (counties) from 2005 to 2024 (global Moran’s I = 0.045, Z = 2.24, P < 0.05), with high-high clusters mainly concentrated in the Pearl River Delta region in Guangdong Province and Xishuangbanna Dai Autonomous Prefecture and Pu’er City in Yunnan Province, and the total economic burden (global Moran’s I = 0.032, Z = 9.55, P < 0.001), per capita economic burden (global Moran’s I = 0.208, Z = 27.34, P < 0.001), and the proportion of total economic burdens in GDP in 2024 (global Moran’s I = 0.017, Z = 5.91, P < 0.001) all presented positive aggregation, with relatively higher total economic burdens mainly concentrated in Guangdong Province and Yunnan Province. Joinpoint regression analysis showed that the gross DALYs rates of dengue fever appeared an overall tendency towards a rise in China from 2005 to 2024 (AAPC = 16.24%, P = 0.029), and the DALYs rate presented an overall tendency towards a rise among both men (AAPC = 14.75%, P = 0.028) and women (AAPC = 14.93%, P = 0.037) during the study period. The per capita direct economic burden appeared an overall tendency towards a rise among dengue fever patients in China from 2005 to 2024 (AAPC = 2.16%, P = 0.012); however, there was no significant difference in the trends in the per capita indirect economic burden (AAPC = 0.46%, P = 0.470). In addition, the DALYs rate of dengue fever appeared a tendency towards a rise in 84.67% (232/274) of cities (counties) in China from 2005 to 2024, and the per capita economic burden appeared a tendency towards a rise in 85.40% (234/274) of cities (counties), while the DALYs rate and per capita economic burden of dengue fever appeared a tendency towards a rise in 77.01% (211/274) of cities (counties). Conclusions The disease burden of dengue fever significantly increased in China from 2005 to 2024. It is recommended to reinforce integrated dengue fever control in high-risk areas and among high-risk populations, and to improve the surveillance of imported dengue fever cases and vector control.

Traditional Chinese medicine （TCM） therapy has unique clinical advantages in the treatment of atrial fibrillation， mainly reflected in five aspects， improving quality of life， enabling early diagnosis and treatment， promoting cardiac rehabilitation， making up for the limitations of Western medicine， and improving the success rate of catheter ablation. However， there is insufficient evidence in current clinical research. Based on the current status of TCM research in the treatment of atrial fibrillation， it is suggested that future studies should focus on standardized research on syndrome differentiation and classification. This can be achieved through clinical epidemiological surveys， expert consensus， and other methods to establish a unified syndrome differentiation and classification standard for atrial fibrillation. Clinical efficacy evaluation indicators should be standardized， and core outcome measures for clinical research on TCM treatment of atrial fibrillation should be developed through systematic reviews， patient interviews， and other methods. Additionally， clinical research design， implementation， and data management should be improved. By leveraging modern information technologies such as artificial intelligence， the scientific and standardized nature of TCM intervention research on atrial fibrillation can be enhanced， ultimately improving the quality of research.

Objective To evaluate the ambient dose equivalent rates of photons and neutrons inside and outside the door of a 10 MV accelerator room, and to report the shielding effect of boron-containing polyethylene as maze wall lining. Methods The ambient dose equivalent rates of photons and neutrons inside and outside the door of an accelerator room were taken as the research subject. The Kersey, Falcão, and modified Kersey methods were used to calculate the ambient dose equivalent rates of neutrons and neutron capture gamma rays inside and outside the door of the room before and after renovation. Measurements were made using an X-ray/γ-ray dose rate instrument and a neutron ambient dose equivalent rate meter. Calculated and measured results were compared. Results Before renovation, the measured neutron dose rate inside the door was 409 μSv/h, while the calculated values were 323 μSv/h (Kersey method), 428 μSv/h (Falcão method), and 219 μSv/h (modified Kersey method). The Falcão method yielded a value closest to the measured value, while the Kersey and the modified Kersey methods underestimated the value by 21% and 46%, respectively. After the installation of boron-containing polyethylene plates, the measured neutron dose rate inside the door was 190 μSv/h, with a 54% reduction. The neutron and photon ambient dose equivalent rates outside the door were 5.8 μSv/h and 6.0 μSv/h, respectively, before renovation, and 0.14 μSv/h and 1.6 μSv/h, respectively, after renovation. Conclusion For a 10 MV accelerator room, neutron shielding and protection measurements are necessary, especially for rooms with short mazes. The Falcão method provides the best estimate of neutron dose rates inside and outside the door. Using boron-containing polyethylene plates as maze wall lining is an economical and effective shielding method.

Objective To explore the accuracy of artificial intelligence-based diagnosis of ovarian malignant tumors and the identification of benign and malignant tumors under transabdominal scanning and transvaginal scanning methods. Methods A dataset of transabdominal and transvaginal two-dimensional ultrasound images was used and the images were preprocessed to enhance quality. The region of interest was segmented and divided into a training set and a test set. A convolutional neural network (CNN) was trained on the images in the training set, and the accuracy of the model on the test set was calculated. Results Transvaginal scanning was 14% more accurate in diagnosing malignant ovarian tumors than transabdo-minal scanning on the test set. For identifying the benign and malignant ovarian tumors containing cystic components, a mixture of transvaginal and transabdominal scanning increased the accuracy by 9.7% over transabdominal scanning alone. Conclusion CNN can identify ovarian malignant tumors under both scanning methods, but the accuracy of transvaginal scanning is higher than that of transabdominal scanning, and the CNN model has a higher accuracy in identifying benign and malignant ovarian tumors under transvaginal scanning.