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.

This paper analyzed the characteristics of peer psychological counseling conducted by class committee member for psychology in universities and the dilemmas they faced in four aspects， including dual relationships， confidentiality issues， competence issues， and informed consent. It also examined the causes of these ethical dilemmas and corresponding countermeasures one by one. Specific work requirements were proposed for class committee member for psychology in conducting peer psychological counseling. These encompassed clarifying the nature and boundaries of the helping relationship， establishing appropriate settings， discussing the impacts of dual relationships， maintaining confidentiality awareness， adopting appropriate confidentiality measures， actively participating in training to improve competence， making timely referrals when exceeding their professional scope， ensuring proper informed consent， and maintaining value neutrality. Recommendations were also put forward for universities to strengthen the training and management of class committee member for psychology， enhance their ethical awareness， and ensure the effectiveness of peer counseling.

The active components in traditional Chinese medicine （TCM） generally have problems such as poor solubility and low bioavailability， which seriously restrict their clinical efficacy. In recent years， TCM nano-self-assembly based on the non-covalent interactions between molecules has become the research frontier in this field because it can spontaneously form an orderly structure and improve the insoluble components in the body. Moreover， TCM nano-self-assembly has shown unique advantages in the treatment of fibrosis， inflammatory and immune diseases， infectious diseases， and cancer. This article summarizes the research context， structural system， and potential as a pharmacological substance basis of TCM nano-self-assembly by reviewing recent published studies， with focuses on the application of TCM nano-self-assembly in the treatment of diseases from single components to complex systems. In addition， this article summarizes its advantages， mechanism characteristics， and main challenges faced. At present， this field still faces issues such as insufficient mechanism research， a lack of in-depth understanding of the competitive assembly rules of multiple components， difficulty in quality control， unclear in vivo processes and safety， and obstacles to clinical translation. To address these issues， this article proposes a series of solutions， including introducing molecular dynamics simulation and artificial intelligence to predict assembly behavior， using experimental techniques to analyze non-covalent interactions， establishing a comprehensive evaluation system with multiple indicators， using isotope labeling and in vivo imaging techniques to dynamically track in vivo processes， conducting standardized safety evaluation， promoting the filing of hospital preparations and new drug applications， and strengthening early communication between research and regulation. Finally， this article points out the future development directions， aiming to provide reference for subsequent research and clinical translation.

The active components in traditional Chinese medicine （TCM） generally have problems such as poor solubility and low bioavailability， which seriously restrict their clinical efficacy. In recent years， TCM nano-self-assembly based on the non-covalent interactions between molecules has become the research frontier in this field because it can spontaneously form an orderly structure and improve the insoluble components in the body. Moreover， TCM nano-self-assembly has shown unique advantages in the treatment of fibrosis， inflammatory and immune diseases， infectious diseases， and cancer. This article summarizes the research context， structural system， and potential as a pharmacological substance basis of TCM nano-self-assembly by reviewing recent published studies， with focuses on the application of TCM nano-self-assembly in the treatment of diseases from single components to complex systems. In addition， this article summarizes its advantages， mechanism characteristics， and main challenges faced. At present， this field still faces issues such as insufficient mechanism research， a lack of in-depth understanding of the competitive assembly rules of multiple components， difficulty in quality control， unclear in vivo processes and safety， and obstacles to clinical translation. To address these issues， this article proposes a series of solutions， including introducing molecular dynamics simulation and artificial intelligence to predict assembly behavior， using experimental techniques to analyze non-covalent interactions， establishing a comprehensive evaluation system with multiple indicators， using isotope labeling and in vivo imaging techniques to dynamically track in vivo processes， conducting standardized safety evaluation， promoting the filing of hospital preparations and new drug applications， and strengthening early communication between research and regulation. Finally， this article points out the future development directions， aiming to provide reference for subsequent research and clinical translation.

ObjectiveTo construct a group-based trajectory model (GBTM) for early medication adherence check-in, and to analyze the relationship between different trajectories and treatment outcomes in tuberculosis patients using data that were generated from smart tools for monitoring their medication adherence and check-in. MethodsFrom October 1, 2022 to September 30, 2023, a total of 163 pulmonary tuberculosis patients diagnosed in Fengxian District were selected as the study subjects. The GBTM was utilized to analyze the weekly active check-in trajectories of the subjects during the first 4 weeks and establish different trajectory groups. The χ² tests were employed to compare the differences between groups and logistic regression analysis was conducted to explore the relationship between different trajectory groups and treatment outcomes. ResultsA total of four groups were generated by GBTM analyses, of which a low level of punch card was maintained in group A, 6% of the drug users increased rapidly from a low level in group B, 17% of drug users increased gradually from a low level in group C, and 18% of drug users maintained a high level of punch card in group D. The trajectory group was divided into two groups according to homogeneity, namely the low level medication punch card group (group A) and the high level medication punch card group (group B, group C, and group D). The results of multivariate logistic regression analyses revealed that low-level medication check-in (OR=3.250, 95%CI: 1.089‒9.696), increasing age (OR=1.030, 95%CI: 1.004‒1.056), and not undergoing sputum examination at the end of the fifth month (OR=2.746, 95%CI: 1.090‒7.009) were significantly associated with poor treatment outcomes. ConclusionThe medication check-in trajectory of pulmonary tuberculosis patients within the first 4 weeks is correlated with adverse outcomes, or namely consistent low-level medication adherence check-ins are associated with poor treatment outcomes, while high-level medication adherence check-ins are associated with a lower incidence of adverse outcomes.

The pharmaceutical industry faces challenges in quality digitization for complex multi-stage processes, especially in small-sample systems. Here, an intelligent quality prediction and diagnostic (IQPD) framework was developed and applied to Tong Ren Tang's Niuhuang Qingxin Pills, utilizing four years of data collected from four production units, covering the entire process from raw materials to finished products. In this framework, a novel path-enhanced double ensemble quality prediction model (PeDGAT) is proposed, which combines a graph attention network and path information to encode inter-unit long-range and sequential dependencies. Additionally, the double ensemble strategy enhances model stability in small samples. Compared to global traditional models, PeDGAT achieves state-of-the-art results, with an average improvement of 13.18% and 87.67% in prediction accuracy and stability on three indicators. Additionally, a more in-depth diagnostic model leveraging grey correlation analysis and expert knowledge reduces reliance on large samples, offering a panoramic view of attribute relationships across units and improving process transparency. Finally, the IQPD framework integrates into a Human-Cyber-Physical system, enabling faster decision-making and real-time quality adjustments for Tong Ren Tang's Niuhuang Qingxin Pills, a product with annual sales exceeding 100 million CNY. This facilitates the transition from experience-driven to data-driven manufacturing.

BACKGROUND: Metabolic-associated fatty liver disease (MAFLD) is the predominant form of chronic liver disease worldwide. This study was designed to investigate the proportion and characteristics of MAFLD within the general Chinese population and to identify the contributory risk factors for liver fibrosis among MAFLD individuals. METHODS: The participants were recruited from a cohort undergoing routine health evaluations at the Third Hospital of Hebei Medical University between May 2019 and March 2023. The diagnosis of MAFLD was based on the established clinical practice guidelines. The fibrosis-4 index score (FIB-4) was employed to evaluate hepatic fibrosis, with a FIB-4 score of ≥1.3 indicating significant fibrosis. Binary logistic regression analyses were used to determine risk factors associated with significant hepatic fibrosis in MAFLD. RESULTS: A total of 22,970 participants who underwent comprehensive medical examinations were included in the analysis. The overall proportion of MAFLD was 28.77% (6608/22,970), with 16.87% (1115/6608) of these patients showing significant fibrosis as assessed using FIB-4. Independent risk factors for significant liver fibrosis in MAFLD patients were male (odds ratio [OR] = 0.676, 95% confidence interval [CI]: 0.558-0.821), hepatitis B surface antigen (HBsAg) positivity (OR = 2.611, 95% CI: 1.557-4.379), body mass index ≥23.00 kg/m 2 (OR = 0.632, 95% CI: 0.470-0.851), blood pressure ≥130/85 mmHg (OR = 1.885, 95% CI: 1.564-2.272), and plasma glucose ≥5.6 mmol/L (OR = 1.815, 95% CI: 1.507-2.186) (all P <0.001). CONCLUSIONS The proportion of MAFLD in an urban Chinese population is 28.77%. About 16.87% of MAFLD patients presented with significant liver fibrosis. Independent risk factors for significant liver fibrosis in MAFLD patients should be noticed.
Humans ; Male ; Female ; Liver Cirrhosis/pathology* ; Middle Aged ; Risk Factors ; Adult ; Fatty Liver/pathology* ; Aged ; China/epidemiology* ; Logistic Models ; Urban Population ; East Asian People

This study aims to comprehensively analyze the material basis of toad visceral oil(hereafter referred to as toad oil), and explore the pharmacological effect of toad oil on atopic dermatitis(AD). Ultra-high performance liquid chromatography-linear ion trap/orbitrap high-resolution mass spectrometry(UHPLC-LTQ-Orbitrap-MS) and gas chromatography-mass spectrometry(GC-MS) were employed to comprehensively identify the chemical components in toad oil. The animal model of AD was prepared by the hapten stimulation method. The modeled animals were respectively administrated with positive drug(0.1% hydrocortisone butyrate cream) and low-and high-doses(1%, 10%) of toad oil by gavage. The effect of toad oil on AD was evaluated with the AD score, ear swelling rate, spleen index, and pathological section results as indicators. A total of 99 components were identified by UHPLC-LTQ-Orbitrap-MS, including 14 bufadienolides, 7 fatty acids, 6 alkaloids, 10 ketones, 18 amides, and other compounds. After methylation of toad oil samples, a total of 20 compounds were identified by GC-MS. Compared with the model group, the low-and high-dose toad oil groups showed declined AD score, ear swelling rate, and spleen index, alleviated skin lesions, and reduced infiltrating mast cells. This study comprehensively analyzes the chemical composition and clarifies the material basis of toad oil. Meanwhile, this study proves that toad oil has a good therapeutic effect on AD and is a reserve resource of traditional Chinese medicine for external use in the treatment of AD.
Animals ; Dermatitis, Atopic/immunology* ; Disease Models, Animal ; Mice ; Male ; Gas Chromatography-Mass Spectrometry ; Humans ; Bufonidae ; Oils/administration & dosage* ; Chromatography, High Pressure Liquid ; Female ; Mice, Inbred BALB C

The chemical composition of Paeoniae Radix Alba(PRA) is complex, with primary secondary metabolites including monoterpenoids, tannins, triterpenoids, and flavonoids. In previous studies on the material basis of PRA, it was found that, in addition to the widely studied characteristic monoterpene glycosides, tannic acid components also play an important role in the efficacy of PRA. However, their pharmacological effects have not been thoroughly investigated. This paper reviews the tannic acid components in PRA, including pentagaloyl glucose(PGG), tetragaloyl glucose(TGG), trigaloyl glucose(TriGG), and gallic acid, along with their structures, properties, and characteristics to provide a detailed discussion of their pharmacological activities and related mechanisms, aiming to offer a theoretical basis for the material basis research and clinical application of PRA.
Paeonia/chemistry* ; Tannins/chemistry* ; Humans ; Drugs, Chinese Herbal/chemistry* ; Animals ; Plant Extracts