ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

Malignant tumors are one of the major causes of death in the population. Owing to limited clinical treatments， susceptibility to drug resistance， and generally low cure rates of conventional therapies， new treatment strategies need to be explored. Compared with existing therapies， traditional Chinese medicine （TCM） has unique advantages， such as low side effects， in the treatment of malignant tumors. Ferroptosis is a recently characterized form of regulated cell death associated with iron metabolism imbalance， lipid peroxidation， antioxidant system malfunction and other aspects. Studies have shown that TCM regulates Fe³⁺， Fe²⁺， glutathione， glutathione peroxidase 4 and other substances related to ferroptosis， thereby affecting lipid peroxidation and antioxidant processes， and then inducing ferroptosis. Through these mechanisms， TCM plays a key role in inhibiting the growth and spread of tumor cells and is involved in multiple stages of malignant tumor progression. In this study， we systematically retrieved the literature indexed in PbuMed and China National Knowledge Infrastructure （CNKI） with the keywords TCM， ferroptosis， and malignant tumors. We outlined the mechanisms of ferroptosis and its association with malignant tumors， and summarized the research progress on the prevention and treatment of malignant tumors through the modulation of ferroptosis by TCM monomers， single herbs， and compounds. The study aims to provide new perspectives for the prevention and treatment of malignant tumors by TCM.

AIM:To investigate the expression levels of serum sirtuin 6(Sirt6)and nicotinamide adenine dinucleotide phosphate oxidase 2(NOX2)in patients with primary glaucoma and their correlation with the severity of the disease. METHODS:This study is a cross-sectional study. Patients diagnosed with primary glaucoma at the hospital from August 2022 to June 2025 were enrolled and divided into mild-to-moderate and severe groups based on the mean deviation of visual field defects, along with healthy individuals as a control group. Clinical data were collected, and serum levels of Sirt6 and NOX2 were measured using enzyme-linked immunosorbent assay(ELISA). Correlations between serum Sirt6 and NOX2 levels and clinical parameters were analyzed. Multivariate Logistic regression was used to identify factors influencing disease severity, and the diagnostic efficacy of serum Sirt6 and NOX2 levels was evaluated using receiver operating characteristic(ROC)curves. RESULTS:A total of 120 patients with primary glaucoma(58 males, 62 females, mean age 60.08±8.19 y)and 100 controls(46 males, 56 females, mean age 60.23±8.67 y)were enrolled in this study. There were no statistically significant differences in sex or age between the two groups(both P>0.05). The intraocular pressure and serum NOX2 expression level in the primary glaucoma group were significantly higher than those in the control group, while the Sirt6 level was significantly lower than in the control group(all P<0.001). The AUC values of serum Sirt6 and NOX2 in the diagnosis of primary glaucoma were 0.733 and 0.770, respectively, with optimal cutoff values of 2.35 and 4.25 ng/mL, respectively. The AUC of the combined diagnosis of the two was 0.901, and its efficacy was obviously better than that of a single indicator(Zcombination-Sirt6=5.317, Zcombination-NOX2=4.720, P<0.001).The severe group had lower serum Sirt6 expression levels(P<0.05), and higher NOX2 expression levels(P<0.05)than the mild-to-moderate group. Serum Sirt6 expression levels were prominently negatively correlated with mean intraocular pressure(r=-0.354, P<0.05); NOX2 expression levels were prominently positively correlated with mean intraocular pressure(r=0.240, P<0.05). Multivariate Logistic regression analysis showed that a decrease in serum Sirt6 expression levels(OR=0.229, 95%CI: 0.090-0.581), an increase in serum NOX2 expression levels(OR=2.649, 95%CI: 1.658-4.232), an increase in mean intraocular pressure(OR=1.278, 95%CI: 1.118-1.462)which were risk factors for the progression to severe glaucoma. The AUC values of serums Sirt6 and NOX2 expression levels in diagnosing severe primary glaucoma were 0.794 and 0.800, respectively, the AUC, sensitivity, and specificity of the combined diagnosis of the two were 0.916, 80.00%, and 89.33%, respectively, and the combined diagnostic efficacy was better than that of a single indicator(Zcombination-Sirt6=2.627, P=0.009, Zcombination-NOX2=2.762, P=0.006). CONCLUSION:The decreased serum Sirt6 and increased NOX2 expression levels in patients with primary glaucoma are significantly correlated with disease severity, and the combined detection demonstrates good diagnostic value for primary glaucoma and its severity.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

Malignant tumors are one of the major causes of death in the population. Owing to limited clinical treatments， susceptibility to drug resistance， and generally low cure rates of conventional therapies， new treatment strategies need to be explored. Compared with existing therapies， traditional Chinese medicine （TCM） has unique advantages， such as low side effects， in the treatment of malignant tumors. Ferroptosis is a recently characterized form of regulated cell death associated with iron metabolism imbalance， lipid peroxidation， antioxidant system malfunction and other aspects. Studies have shown that TCM regulates Fe³⁺， Fe²⁺， glutathione， glutathione peroxidase 4 and other substances related to ferroptosis， thereby affecting lipid peroxidation and antioxidant processes， and then inducing ferroptosis. Through these mechanisms， TCM plays a key role in inhibiting the growth and spread of tumor cells and is involved in multiple stages of malignant tumor progression. In this study， we systematically retrieved the literature indexed in PbuMed and China National Knowledge Infrastructure （CNKI） with the keywords TCM， ferroptosis， and malignant tumors. We outlined the mechanisms of ferroptosis and its association with malignant tumors， and summarized the research progress on the prevention and treatment of malignant tumors through the modulation of ferroptosis by TCM monomers， single herbs， and compounds. The study aims to provide new perspectives for the prevention and treatment of malignant tumors by TCM.

OBJECTIVE: To explore the application value of artificial intelligence (AI)-assisted chromosomal karyotype analysis in the diagnosis of prenatal chromosomal mosaicism. METHODS: A retrospective analysis was conducted on 172 pregnant women who underwent amniocentesis at the Department of Medical Genetics and Prenatal Diagnosis, the Third Affiliated Hospital of Zhengzhou University between January 2019 and December 2024. All cases whose fetuses were diagnosed with chromosomal mosaicism via karyotype analysis and stratified into two groups based on the analytical software employed: the conventional analysis group (n = 70), which utilized Leica analysis software for karyotype image recognition and cell counting; and the AI-assisted analysis group (n = 102), which utilized AI-assisted software for the same procedures. The clinical performance of AI-assisted karyotype analysis in diagnosing chromosomal mosaicism was comprehensively evaluated by comparing the types of mosaic karyotypes, distribution of mosaic ratios, and verification outcomes of different detection modalities between the two groups. This study was approved by the Medical Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethics No.: 2024-406-01). RESULTS: No statistically significant difference was observed in baseline characteristics (maternal age, gestational week, and indications for prenatal diagnosis) between the two groups. Regarding the detection efficacy for numerical and structural mosaicisms, no significant difference was found in the detection of numerical mosaicism. However, the conventional analysis group exhibited a significantly higher detection rate of autosomal structural mosaicism compared to the AI-assisted group (11.43% vs. 0.98%, P < 0.05). Numerical mosaicism cases were further verified using copy number variation sequencing (CNV-seq) and/or fluorescence in situ hybridization (FISH). The AI-assisted group demonstrated a significantly lower inconsistency rate (5.56% vs. 20.41%, P < 0.05) compared to the conventional group. For low-proportion (< 10%) chromosomal mosaicism, the AI-assisted group had a significantly lower detection rate (13.25% vs. 29.69%, P < 0.05). Subsequent validation of low-proportion mosaicism by CNV-seq and/or FISH showed a higher consistency rate in the AI-assisted group (81.82% vs. 54.55%), though the difference did not reach statistical significance (P = 0.360). CONCLUSION For the karyotyping analysis of prenatal chromosomal mosaicism, AI-assisted karyotype analysis shows high accuracy and consistency in identifying numerical chromosomal mosaicism, particularly in reducing the detection of low-proportion (< 10%) mosaicism while improving verification accuracy. AI-assisted analysis can significantly improve the detection accuracy of numerical mosaicism and mitigate the risk of misclassification for low-proportion (< 10%) mosaicism, thereby providing more precise clinical evidence for the prenatal diagnosis of chromosomal mosaicisms.
Humans ; Female ; Mosaicism ; Pregnancy ; Karyotyping/methods* ; Artificial Intelligence ; Prenatal Diagnosis/methods* ; Adult ; Retrospective Studies ; Chromosome Disorders/genetics* ; Amniocentesis

As a distinctive resource of Chinese civilization， traditional Chinese medicine （TCM） technology transfer faces significant opportunities under the background of digital and intelligent transformation， while also being constrained by unique challenges such as the complexity of its theoretical system， lengthy industrial chains， and multidimensional policy restrictions， resulting in a "high-value-high-threshold" paradox. At present， TCM technology transfer is deeply trapped in a "threefold reluctance" dilemma， i.e.， unwillingness to transfer， inability to transfer， and lack of capacity to transfer. Specifically， the disconnection between scientific research evaluation systems and market demand leads to low conversion rates of research achievements， unclear ownership and compliance risks suppress innovation incentives， and the absence of professional services intensifies supply-demand mismatches. This article systematically analyzes the specific characteristics of TCM technology transfer and proposes a breakthrough pathway centered on full-chain digital and intelligent transformation. By integrating technologies such as intelligent sorting systems， blockchain-based traceability， and AI diagnostic models， the TCM ecosystem spanning "cultivation-production-service" can be reconstructed. In terms of standardization， promoting the progression from "experience-based data conversion" to "data standardization" and further to "intelligent standardization" is advocated to resolve quality control challenges. For example， a "three-no-one-full" certification system can strengthen quality trust. Policy coordination should focus on optimizing mechanisms for the transformation of scientific and technological achievements， while exploring intellectual property securitization and risk-sharing models to stimulate research momentum. In terms of internationalization， reliance on the Belt and Road Initiative platform to promote the export of geo-authentic medicinal material brands and standards is recommended to build a dual-driven model of "technology plus culture". Looking ahead， through the construction of national-level databases， the cultivation of interdisciplinary talent， and the mutual recognition of international standards， a new paradigm of "scientific intelligent manufacturing" can be formed， providing systematic solutions for the modernization of TCM and global health governance.

Parkinson's disease （PD） is a neurodegenerative disorder primarily characterized by motor dysfunction. Traditionally， its main clinical features include resting tremor， muscular rigidity， bradykinesia， and postural balance disorders. However， an increasing number of studies have shown that its non-motor symptoms （NMS） exert an even greater impact on patients' quality of life than motor symptoms， severely affecting daily functioning and increasing the burden on families and society. Among these， depression is one of the most common and most debilitating NMS， with statistics indicating that the incidence of depression among PD patients reaches as high as 40%-50%. The pathological mechanisms are complex， involving the interplay between degenerative changes in dopaminergic neurons and disruptions in emotional regulatory circuits， which poses a substantial challenge to clinical treatment. Traditional Chinese medicine （TCM）， characterized by holistic regulation and multi-target intervention， has demonstrated significant advantages in the treatment of PD and depression， offering new insights for managing PD-depression comorbidity. This study integrates research extracted from multiple databases， including PubMed， Web of Science， Google Scholar， and China National Knowledge Infrastructure （CNKI）， that investigates the potential mechanisms of PD and depression as well as TCM-based treatments for these conditions. The aim is to elucidate the shared pathological mechanisms underlying PD and depression and to explore the therapeutic potential of TCM in effectively combating PD-depression comorbidity through these shared mechanisms， thereby providing valuable insights for the development of targeted therapies.

ObjectiveTo evaluate the effects and safety of the optimized new Shengmai Powder （优化新生脉散方） on exercise tolerance in patients with chronic heart failure （CHF） of qi deficiency， blood stasis， and fluid retention syndrome. MethodsA randomized， double-blind， placebo-controlled trial was conducted. A total of 78 CHF patients with qi deficiency， blood stasis， and fluid retention syndrome were recruited and randomly assigned to a treatment group （39 cases） and a control group （39 cases）. On the basis of conventional western medical therapy， patients in the treatment group additionally received the optimized new Shengmai Powder granules， while the control group was given an oral placebo of optimized new Shengmai Powder granules. Patients in both groups took 30.6 g each time， twice a day， mixed with water for administration， with a total treatment course of 4 weeks. The primary outcomes were 6-minute walk distance （6MWD） and peak oxygen uptake （Peak VO₂） measured by cardiopulmonary exercise testing. Secondary outcomes included New York Heart Association （NYHA） functional classification， B-type natriuretic peptide （BNP） levels， cardiac function indexes including left ventricular ejection fraction （LVEF）， left ventri-cular end-systolic diameter （LVESD） and left ventricular end-diastolic diameter （LVEDD）， Minnesota Living with Heart Failure Questionnaire （MLHFQ） scores， and scores of four diagnostic information of traditional Chinese medicine （TCM）. All indicators were assessed once before and after treatment respectively. Safety indicators were evaluated， and adverse events during the trial were recorded. ResultsAll patients in both groups were included in the full ana-lysis set （FAS） and safety set （SS）. Compared with baseline， the 6MWD and Peak VO₂ of cardiopulmonary exercise test in the treatment group significantly increased after treatment， while the MLHFQ scores， serum BNP levels and scores of TCM four diagnostic information significantly decreased， and the NYHA cardiac function grade significantly improved （P＜0.01）. After treatment， the 6MWD and Peak VO₂ of cardiopulmonary exercise test， as well as their changes from baseline in the treatment group were higher than those in the control group； the MLHFQ scores， serum BNP levels and scores of TCM four diagnostic information in the treatment group were lower than those in the control group； and the improvement of NYHA cardiac function grade in the treatment group was superior to that in the control group （P＜0.01）. There was no statistically significant differences in all indicators after treatment in the control group （P＞0.05）. The incidence of adverse events was 5.1% （2/39） in the treatment group and 2.6% （1/39） in the control group， with no statistically significant difference between groups （P＞0.05）. ConclusionOn the basis of conventional western medicine treatment， the addition of the optimized new Shengmai Powder can further improve exercise tolerance， cardiac function and quality of life in patients with CHF of qi deficiency， blood stasis and fluid retention syndrome， and show good safety.

Animal experimentation constitutes a critical link between basic research and clinical application, making its research quality and translational efficiency paramount. Although considerable progress has been made in standardizing operational procedures and ethical guidelines, the standardization of outcome evaluation systems has significantly lagged, creating a key bottleneck that constrains the quality of biomedical research and evidence synthesis. This deficiency is manifested by pronounced heterogeneity in outcome selection across similar studies, incomplete methodological reporting, and disparate criteria for result interpretation, which severely impairs the comparability of findings and the evidence integration. To cope with this challenge, this paper systematically introduces a mature methodological tool from clinical research–the core outcome set (COS)–and explores its construction strategies and application potential in the field of animal experimentation. Given the extensive diversity of animal experiments, a pragmatic strategy of "focusing on key areas, implementing phased pilots, and promoting gradual expansion" should be adopted. This approach prioritizes the development of domain-specific COS for disease areas characterized by high research volume, urgent translational needs, and well-established animal models. A multi-source integration pathway for COS development is detailed, comprising systematic literature searches, methodological appraisals, and expert consensus, with the feasibility of leveraging artificial intelligence (AI) to enhance efficiency also being examined. The development and promotion of such COS are not intended to restrict scientific exploration; rather, they aim to establish a new, tiered evaluation paradigm consisting of "core outcomes" (mandatory), "recommended outcomes" (encouraged), and "exploratory outcomes" (optional). This framework is expected not only to enhance research quality through standardization and to adhere to the "3R" principles but also to accelerate the accumulation of high-quality evidence. This, in turn, provides a solid foundation for higher-level evidence synthesis, ultimately facilitating the effective translation of basic research findings into clinical practice and providing an essential methodological framework for scientific advancement in relevant disciplines.