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.

The diagnosis of hematological disorders is currently established from the combined results of different tests, including those assessing morphology (M), immunophenotype (I), cytogenetics (C), and molecular biology (M) (collectively known as the MICM classification). In this workflow, most of the results are interpreted manually (i.e., by a human, without automation), which is expertise-dependent, labor-intensive, time-consuming, and with inherent interobserver variability. Also, with advances in instruments and technologies, the data is gaining higher dimensionality and throughput, making additional challenges for manual analysis. Recently, artificial intelligence (AI) has emerged as a promising tool in clinical hematology to ensure timely diagnosis, precise risk stratification, and treatment success. In this review, we summarize the current advances, limitations, and challenges of AI models and raise potential strategies for improving their performance in each sector of the MICM pipeline. Finally, we share perspectives, highlight future directions, and call for extensive interdisciplinary cooperation to perfect AI with wise human-level strategies and promote its integration into the clinical workflow.

Ferroptosis has been shown to mediate the development of fibrosis. Polyphyllin VII (PP7), a bioactive component of Paris polyphylla, exhibits potent anti-inflammatory activity and can significantly alleviate liver fibrosis. In this study, treatment with PP7 significantly inhibited the proliferation and activation of hepatic stellate cells (HSCs), which could be suppressed by a ferroptosis inhibitor. In addition, it promoted HSC ferroptosis by suppressing glutathione (GSH) peroxidase 4 (GPX4) and enhanced the expression of CX3C chemokine ligand 1 (CX3CL1). Depletion of CX3CL1 attenuated the effects of PP7 on the activation and ferroptosis of HSCs and the expression of GPX4. Notably, CX3CL1 directly interacted with GPX4, triggering HSC ferroptosis. The transcription factor hypermethylated in cancer 1 (Hic1), which binds to the Cx3cl1 promoter, increased the expression of CX3CL1. Its absence resulted in downregulation of CX3CL1, suppressing the GPX4-dependent ferroptosis of PP7-treated HSCs and promoting their activation. HIC1 was found to directly interact with PP7 at the GLY164 site. Co-culture experiments showed that PP7-induced HSC ferroptosis attenuated macrophage recruitment by regulating inflammation-related genes. HSC-specific inhibition of HIC1 counteracted PP7-induced collagen depletion and HSC ferroptosis in vivo. These findings suggest that PP7 induces HSC ferroptosis through the HIC1/CX3CL1/GPX4 axis.

Clinical practice guidelines represent the best recommendations for patient care. They are developed through systematically reviewing currently available clinical evidence and weighing the relative benefits and risks of various interventions. However, clinical practice guidelines have to go through a long translation cycle from development and revision to clinical promotion and application, facing problems such as scattered distribution, high duplication rate, and low actual utilization. At present, the clinical practice guideline information platform can directly or indirectly solve the problems related to the lengthy revision cycles, decentralized dissemination and limited application of clinical practice guidelines. Therefore, this paper systematically examines different types of clinical practice guideline information platforms and investigates their corresponding challenges and emerging trends in platform design, data integration, and practical implementation, with the aim of clarifying the current status of this field and providing valuable reference for future research on clinical practice guideline information platforms.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Ferroptosis has been shown to mediate the development of fibrosis.Polyphyllin Ⅶ(PP7),a bioactive component of Paris polyphylla,exhibits potent anti-inflammatory activity and can significantly alleviate liver fibrosis.In this study,treatment with PP7 significantly inhibited the proliferation and activation of hepatic stellate cells(HSCs),which could be suppressed by a ferroptosis inhibitor.In addition,it promoted HSC ferroptosis by suppressing glutathione(GSH)peroxidase 4(GPX4)and enhanced the expression of CX3C chemokine ligand 1(CX3CL1).Depletion of CX3CL1 attenuated the effects of PP7 on the activation and ferroptosis of HSCs and the expression of GPX4.Notably,CX3CL1 directly interacted with GPX4,triggering HSC ferroptosis.The transcription factor hypermethylated in cancer 1(Hic1),which binds to the Cx3cl1 promoter,increased the expression of CX3CL1.Its absence resulted in downregulation of CX3CL1,sup-pressing the GPX4-dependent ferroptosis of PP7-treated HSCs and promoting their activation.HIC1 was found to directly interact with PP7 at the GLY164 site.Co-culture experiments showed that PP7-induced HSC ferroptosis attenuated macrophage recruitment by regulating inflammation-related genes.HSC-specific inhibition of HIC1 counteracted PP7-induced collagen depletion and HSC ferroptosis in vivo.These findings suggest that PP7 induces HSC ferroptosis through the HIC1/CX3CL1/GPX4 axis.

ObjectiveThe research focuses on developing modeling and evaluation methodologies for an animal model exhibiting spleen deficiency and dampness excess syndrome， with the aim of standardizing such animal models for future reference. MethodsBy conducting a literature search on animal models of spleen deficiency and dampness excess syndrome， relevant publications meeting inclusion and exclusion criteria will be identified based on publication date， data source， types of diseases involved， animal characteristics， modeling methods， modeling duration， macroscopic syndrome assessment indicators， macroscopic quantification indicators， laboratory testing parameters， intervention approaches， positive controls and application context. A database will be established to facilitate the extraction of this information for quantitative analysis， statistical evaluation， and visual representation. ResultsA total of 137 literature articles meeting the standards have been included in the research. The primary animal species used in animal models of spleen deficiency and dampness excess are SD rats. Modeling methods include single-factor， dual-factor composite， and triple-factor composite methods， with various models widely applied in validation of pharmacological effects and mechanistic explorations. Evaluation indices of animal models for spleen deficiency and dampness excess primarily consist of macroscopic syndrome evaluation indicators and macroscopic quantitative indicators. Laboratory testing indicators are mostly related to research areas such as fluid metabolism and gastrointestinal function. The most commonly studied herbal formulas currently include Shenling Baizhu San and Pingwei San， with natural recovery and the use of the western medicine metronidazole as the most frequently used positive controls. ConclusionThe application of animal models for spleen deficiency and dampness excess is gradually increasing， with various modeling methods already simulating the typical characteristics of this syndrome pattern. However， there are still many areas that are worth contemplating and improving. This study aims to provide reference and ideas for the standardization of symptom names in animal models of spleen deficiency and dampness excess， as well as for the improvement of model construction and evaluation systems.

Objective:To investigate the prevalence, comorbidity patterns, and associated factors of cardiometabolic multimorbidity (CMM) in China.Methods:From 2012 to 2015, a total of 34 994 residents aged ≥35 years were enrolled using a stratified multistage random sampling method across 31 provinces, autonomous regions, and municipalities in China. Data were collected through questionnaires, covering demographic characteristics, behavioral and lifestyle factors, and self-reported history of cardiometabolic diseases. CMM was defined as the coexistence of two or more cardiometabolic diseases in the same individual. Association rule analysis using the Apriori algorithm from the arules package was employed to identify strong CMM patterns. Multivariable logistic regression was employed to explore factors associated with CMM.Results:The mean age of the participants was 55.6 years. Among them, 15 926 were male (45.51%). The prevalence of cardiometabolic multimorbidity (CMM) was 11.25% (3 937/34 994). A total of 35 distinct CMM combinations (each with a frequency ≥10) were identified. The most prevalent dyad, triad, and tetrad comorbidity patterns were hypertension+hyperlipidemia (1 036 cases), hypertension+hyperlipidemia+diabetes (352 cases), and hypertension+stroke+hyperlipidemia+diabetes (54 cases), respectively. Nine strong CMM patterns were identified using the Apriori association rule algorithm. Multivariable logistic regression analysis showed that older age (≥70 years: OR=17.39,95% CI 13.92-21.71, P<0.01), junior high school education ( OR=1.31, 95% CI 1.17-1.48, P<0.01), senior high school or above education ( OR=1.45, 95% CI 1.27-1.65, P<0.01), retirement ( OR=3.09, 95% CI 2.76-3.46, P<0.01), unemployment or being laid-off ( OR=1.16, 95% CI 1.06-1.28, P<0.01), a family history of cardiometabolic disease ( OR=4.37, 95% CI 4.04-4.72, P<0.01), regular smoking ( OR=1.38, 95% CI 1.24-1.53, P<0.05), and occasional smoking ( OR=1.21, 95% CI 1.00-1.49, P<0.01) were significantly associated with an increased risk of CMM. Conclusion:The prevalence of cardiometabolic multimorbidity in China is relatively high, with the most common comorbidity patterns involving combinations of hypertension and hyperlipidemia, often accompanied by diabetes and stroke. Older age, retirement status, smoking, and a family history of cardiovascular disease are associated with an increased risk of both single and multiple cardiometabolic conditions. Greater attention should be paid to individuals with a single cardiometabolic disorder due to their elevated risk of developing multimorbidity.

Objective:To analyze the incidence and influencing factors of lymphopenia in prostate cancer patients undergoing pelvic radiotherapy.Methods:A retrospective analysis was conducted on 123 prostate cancer patients treated at the Department of Radiation Oncology, Peking University First Hospital, from November 2011 to May 2015. Radiotherapy was administered using conventional fractionated intensity-modulated radiotherapy. Blood routine, including absolute lymphocyte count (ALC), was performed on patients before radiotherapy, weekly during radiotherapy, and at the end of radiotherapy. Severe lymphopenia was defined as an ALC <500 cells/μl. Based on whether the minimum ALC during radiotherapy was lower than 500 cells/μl, the entire cohort and 55 patients (excluding those with undelineated pelvic bone marrow due to radiotherapy planning system issues) with delineated pelvic bone marrow (divided into pelvic bone marrow, iliac bone marrow, and lower pelvic bone marrow) were stratified into a severe lymphopenia group (33 cases and 16 cases, respectively) and a mild lymphopenia group (90 cases and 39 cases, respectively). Differences in clinical factors and dosimetric parameters were compared between the groups using the chi-square test (or Fisher's exact test), t-test, and Wilcoxon rank-sum test. Univariate and multivariate logistic regression analyses were performed to identify the clinical and dosimetric factors influencing severe lymphopenia. Results:All 123 prostate cancer patients experienced lymphopenia during radiotherapy, with a median minimum ALC of 0.6×10 9/L [range: (0.2-2.3)×10 9/L]. Severe lymphopenia occurred in 26.8% (33 cases) of patients. Univariate analysis of the entire cohort showed that pre-radiotherapy baseline ALC, initial neutrophil-to-lymphocyte ratio, prostate-specific antigen value, Gleason score, and pelvic radiotherapy were promoting factors for severe lymphopenia ( P<0.05). Multivariate analysis identified pre-radiotherapy baseline ALC ( OR=0.217, 95% CI: 0.072-0.650, P=0.006) and pelvic radiotherapy ( OR=23.852, 95% CI: 2.834-200.787, P=0.004) as promoting factors for severe lymphopenia. In patients with delineated pelvic bone marrow, univariate analysis showed that pelvic bone marrow V 30 Gy and V 40 Gy, iliac bone marrow V 30 Gy and V 40 Gy, lower pelvic bone marrow V 30 Gy and V 40 Gy were promoting factors for severe lymphopenia during treatment ( P<0.05). Conclusions:Lymphopenia is common in prostate cancer patients undergoing radiotherapy, with a high incidence of severe lymphopenia. Pre-radiotherapy baseline ALC, as well as pelvic, iliac, and lower pelvic bone marrow V 30 Gy and V 40 Gy, are promoting factors for severe lymphopenia during radiotherapy.

Objective:To establish a cutoff level of anti-Müllerian hormone(AMH)which could help with the di-agnosis of polycystic ovary syndrome(PCOS)in adults,and to analyze the risk factors of metabolic syndrome(MS).Methods:A retrospectively analyzed 426 PCOS patients(PCOS group)and 205 healthy controls aged 20-39 years from the Health Checkup Center of the Gynecological Endocrine Center,Hunan Maternal and Child Health Hospital from January 2021 to December 2023.AMH diagnostic validity was estimated by receiver operating characteristic(ROC)curves.Patients were subgrouped into PCOS combined metabolic syndrome group(MS-PCOS)and the uncomplicated MS group(UMS-PCOS)according to metabolic status.Multivariate Logistic regression analysis was performed to determine the risk factors for MS in PCOS patients.Results:The serum AMH level was higher in PCOS group than that in the control group(8.42±3.71 ng/ml vs.2.99±0.94 ng/ml,P＜0.001).AMH cutoff for the diagnosis of PCOS was determined as≥4.87 ng/ml on ROC analysis,and the area under the curve is 0.981 with 92.7％sensitivity and 94.6％specificity.The prevalence of MS was 18.3％(78 ca-ses)in PCOS group.Subgroup analysis showed that MS-PCOS patients had higher waist circumference,BMI,fasting glucose,dyslipidemia,hypertension(BP＞130/85 mmHg),and hormone related index androgen level,but lower AMH vs.UMS-PCOS.Multivariate Logistic regression analysis identified insulin resistance(OR 39.17,95％CI 9.33-164.48),BMI ≥24 kg/m2(OR 3.72,95％CI 1.86-7.45),and hyperandrogenism(OR 2.56,95％CI 1.34-4.89)as independent risk factors of MS.AMH was negatively associated with MS,a single-unit increase in AMH was associated with an 17％decrease in odds of MS(OR 0.83,95％CI 0.73-0.95,P=0.006).Conclusions:Serum AMH levels were significantly higher in adult PCOS patients,with an optimal diagnostic threshold of 4.87 ng/ml.Hyperandrogenism and low AMH levels may predict a higher risk of MS,in addition to metabolism-related factors.