This study explored the potential therapeutic targets and mechanisms of Danggui Shaoyao San(DSS) in the prevention and treatment of Alzheimer's disease(AD) through transcriptomics and metabolomics, combined with animal experiments. Fifty male C57BL/6J mice, aged seven weeks, were randomly divided into the following five groups: control, model, positive drug, low-dose DSS, and high-dose DSS groups. After the intervention, the Morris water maze was used to assess learning and memory abilities of mice, and Nissl staining and hematoxylin-eosin(HE) staining were performed to observe pathological changes in the hippocampal tissue. Transcriptomics and metabolomics were employed to sequence brain tissue and identify differential metabolites, analyzing key genes and metabolites related to disease progression. Reverse transcription-quantitative polymerase chain reaction(RT-qPCR) was employed to validate the expression of key genes. The Morris water maze results indicated that DSS significantly improved learning and cognitive function in scopolamine(SCOP)-induced model mice, with the high-dose DSS group showing the best results. Pathological staining showed that DSS effectively reduced hippocampal neuronal damage, increased Nissl body numbers, and reduced nuclear pyknosis and neuronal loss. Transcriptomics identified seven key genes, including neurexin 1(Nrxn1) and sodium voltage-gated channel α subunit 1(Scn1a), and metabolomics revealed 113 differential metabolites, all of which were closely associated with synaptic function, oxidative stress, and metabolic regulation. RT-qPCR experiments confirmed that the expression of these seven key genes was consistent with the transcriptomics results. This study suggests that DSS significantly improves learning and memory in SCOP model mice and alleviates hippocampal neuronal pathological damage. The mechanisms likely involve the modulation of synaptic function, reduction of oxidative stress, and metabolic balance, with these seven key genes serving as important targets for DSS in the treatment of AD.
Animals ; Alzheimer Disease/genetics* ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Mice, Inbred C57BL ; Metabolomics ; Transcriptome/drug effects* ; Maze Learning/drug effects* ; Hippocampus/metabolism* ; Humans ; Disease Models, Animal ; Memory/drug effects*

OBJECTIVE: To explore the correlation between chromosome 8 open reading frame 76 (C8orf76) and cyclin-dependent kinase 4 (CDK4) and the potential predictive effect of C8orf76 and CDK4 on the prognosis of colorectal cancer (CRC). METHODS: We constructed a protein-protein interaction network of C8orf76-related genes and analyzed the prognostic signatures of C8orf76 and CDK4. Clinicopathological features of C8orf76 and CDK4 were visualized using a nomogram. RESULTS: C8orf76 and CDK4 levels were positively correlated in two independent human CRC cohorts ( n = 83 and n = 597). A consistent positive correlation was observed between C8orf76 and CDK4 expression in the CRC cell lines. The nomogram included prognostic genes (C8orf76 and CDK4) and pathological N and M stages. The concordance index (C-index) in our cohort was 0.776, which suggests that the ability of the indicators to predict the overall survival of patients with CRC in our cohort was strong. CONCLUSION We found that C8orf76 was positively correlated with CDK4 in both the cohorts as well as in CRC cell lines. Therefore, C8orf76 and CDK4 can be used as potential biomarkers to predict the prognosis of CRC.
Humans ; Colorectal Neoplasms/diagnosis* ; Cyclin-Dependent Kinase 4/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/genetics* ; Aged ; Cell Line, Tumor ; Gene Expression Regulation, Neoplastic

Fibrosis, the pathological scarring of vital organs, is a severe and often irreversible condition that leads to progressive organ dysfunction. It is particularly pronounced in organs like the liver, kidneys, lungs, and heart. Despite its clinical significance, the full understanding of its etiology and complex pathogenesis remains incomplete, posing substantial challenges to diagnosing, treating, and preventing the progression of fibrosis. Among the various molecular players involved, platelet-derived growth factor-C (PDGF-C) has emerged as a crucial factor in fibrotic diseases, contributing to the pathological transformation of tissues in several key organs. PDGF-C is a member of the PDGFs family of growth factors and is synthesized and secreted by various cell types, including fibroblasts, smooth muscle cells, and endothelial cells. It acts through both autocrine and paracrine mechanisms, exerting its biological effects by binding to and activating the PDGF receptors (PDGFRs), specifically PDGFRα and PDGFRβ. This binding triggers multiple intracellular signaling pathways, such as JAK/STAT, PI3K/AKT and Ras-MAPK pathways. which are integral to the regulation of cell proliferation, survival, migration, and fibrosis. Notably, PDGF-C has been shown to promote the proliferation and migration of fibroblasts, key effector cells in the fibrotic process, thus accelerating the accumulation of extracellular matrix components and the formation of fibrotic tissue. Numerous studies have documented an upregulation of PDGF-C expression in various fibrotic diseases, suggesting its significant role in the initiation and progression of fibrosis. For instance, in liver fibrosis, PDGF-C stimulates hepatic stellate cell activation, contributing to the excessive deposition of collagen and other extracellular matrix proteins. Similarly, in pulmonary fibrosis, PDGF-C enhances the migration of fibroblasts into the damaged areas of lungs, thereby worsening the pathological process. Such findings highlight the pivotal role of PDGF-C in fibrotic diseases and underscore its potential as a therapeutic target for these conditions. Given its central role in the pathogenesis of fibrosis, PDGF-C has become an attractive target for therapeutic intervention. Several studies have focused on developing inhibitors that block the PDGF-C/PDGFR signaling pathway. These inhibitors aim to reduce fibroblast activation, prevent the excessive accumulation of extracellular matrix components, and halt the progression of fibrosis. Preclinical studies have demonstrated the efficacy of such inhibitors in animal models of liver, kidney, and lung fibrosis, with promising results in reducing fibrotic lesions and improving organ function. Furthermore, several clinical inhibitors, such as Olaratumab and Seralutinib, are ongoing to assess the safety and efficacy of these inhibitors in human patients, offering hope for novel therapeutic options in the treatment of fibrotic diseases. In conclusion, PDGF-C plays a critical role in the development and progression of fibrosis in vital organs. Its ability to regulate fibroblast activity and influence key signaling pathways makes it a promising target for therapeutic strategies aiming at combating fibrosis. Ongoing research into the regulation of PDGF-C expression and the development of PDGF-C/PDGFR inhibitors holds the potential to offer new insights and approaches for the diagnosis, treatment, and prevention of fibrotic diseases. Ultimately, these efforts may lead to the development of more effective and targeted therapies that can mitigate the impact of fibrosis and improve patient outcomes.

The development status of the key technologies of first-aid robotics was introduced in autonomous system,embo-died intelligence,digital twins,large artificial intelligence model and autonomous unmanned medical treatment.The present situation in first-aid robotics equipment was reviewed for first-aid diagnosis,treatment,assistance and transportation.The development trends of the key technology and equipment of first-aid robotics were analyzed.It was pointed out the involve-ment of big model-based embodied intelligence technology and digital twins technology in first aid might provide new pers-pectives for the application and advancement of specialized first-aid robotics.[Chinese Medical Equipment Journal,2025,46(3):96-114]

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Objective:This study aimed was to analyze the disease progression of postoperative recurrence/me-tastasis of pancreatic ductal adenocarcinoma(PDAC)and provide clinical evidence for evaluating the difference in prog-nosis between site and pattern of recurrence/metastasis.Methods:The clinical data of 167 patients with PDAC who underwent pancreatectomy in Panjin Liao-Oil Gem Flower Hospital from January 2011 to June 2019 were retrospec-tively analyzed.Kaplan-Meier curves and Cox-regression analyses were applied to assess survival outcomes.Results:In this study,96 patients(57.5%)recurred within 12 months after surgery,and the median recurrence time was 10.9 months.Compared to patients without recurrence,patients with recurrence/metastasis had higher baseline CA19-9>100 IU/mL and were treated more often with neoadjuvant chemotherapy(P<0.05).In the no recurrence group,patients had histopathological analyses yielded lower less poorly differentiated tumors,less positive margin,less pT3+4 stages and pN1+2 stages(P<0.05).In a multivariate Cox regression analysis,receipt of neoadjuvant chemotherapy,poor tumor differ-entiation and positive margin were independent predictors for recurrence/metastasis within 12 months after surgery(P<0.05).Neoadjuvant treated patients had less pT1+2 stages(P=0.015),a lower lymph node ratio,less perineural invasion,less positive margin,and were less likely to be treated with adjuvant chemotherapy compared to upfront surgery treated patients(P<0.05).Recurrence/metastasis rates were higher in the neoadjuvant treated cohort versus the upfront surgery cohort(P=0.014).There was no statistical difference in the recurrence/metastasis rate distribution between neoadjuvant therapy and upfront surgery,and neoadjuvant therapy exhibited no significant impact on recurrence/metastasis patterns in PDAC(P>0.05).The overall survival period of patients without recurrence/metastasis within 12 months was signifi-cantly longer than that of patients with recurrence/metastasis after PDAC resection(P<0.001).Conclusion:The varying site recurrence/metastasis rates and time to recurrence/metastasis,underline the inherent heterogeneity of PDAC and the specific interactions in the tumor microenvironments at the recurrence/metastasis sites.Further research is essential to establish optimal personalized treatment strategies for patients with recurrent PDAC.

The development status of the key technologies of first-aid robotics was introduced in autonomous system,embo-died intelligence,digital twins,large artificial intelligence model and autonomous unmanned medical treatment.The present situation in first-aid robotics equipment was reviewed for first-aid diagnosis,treatment,assistance and transportation.The development trends of the key technology and equipment of first-aid robotics were analyzed.It was pointed out the involve-ment of big model-based embodied intelligence technology and digital twins technology in first aid might provide new pers-pectives for the application and advancement of specialized first-aid robotics.[Chinese Medical Equipment Journal,2025,46(3):96-114]

Objective:This study aimed was to analyze the disease progression of postoperative recurrence/me-tastasis of pancreatic ductal adenocarcinoma(PDAC)and provide clinical evidence for evaluating the difference in prog-nosis between site and pattern of recurrence/metastasis.Methods:The clinical data of 167 patients with PDAC who underwent pancreatectomy in Panjin Liao-Oil Gem Flower Hospital from January 2011 to June 2019 were retrospec-tively analyzed.Kaplan-Meier curves and Cox-regression analyses were applied to assess survival outcomes.Results:In this study,96 patients(57.5%)recurred within 12 months after surgery,and the median recurrence time was 10.9 months.Compared to patients without recurrence,patients with recurrence/metastasis had higher baseline CA19-9>100 IU/mL and were treated more often with neoadjuvant chemotherapy(P<0.05).In the no recurrence group,patients had histopathological analyses yielded lower less poorly differentiated tumors,less positive margin,less pT3+4 stages and pN1+2 stages(P<0.05).In a multivariate Cox regression analysis,receipt of neoadjuvant chemotherapy,poor tumor differ-entiation and positive margin were independent predictors for recurrence/metastasis within 12 months after surgery(P<0.05).Neoadjuvant treated patients had less pT1+2 stages(P=0.015),a lower lymph node ratio,less perineural invasion,less positive margin,and were less likely to be treated with adjuvant chemotherapy compared to upfront surgery treated patients(P<0.05).Recurrence/metastasis rates were higher in the neoadjuvant treated cohort versus the upfront surgery cohort(P=0.014).There was no statistical difference in the recurrence/metastasis rate distribution between neoadjuvant therapy and upfront surgery,and neoadjuvant therapy exhibited no significant impact on recurrence/metastasis patterns in PDAC(P>0.05).The overall survival period of patients without recurrence/metastasis within 12 months was signifi-cantly longer than that of patients with recurrence/metastasis after PDAC resection(P<0.001).Conclusion:The varying site recurrence/metastasis rates and time to recurrence/metastasis,underline the inherent heterogeneity of PDAC and the specific interactions in the tumor microenvironments at the recurrence/metastasis sites.Further research is essential to establish optimal personalized treatment strategies for patients with recurrent PDAC.

In recent years, with the increasing societal focus on drug quality and safety, quality issues have become a major challenge faced by the pharmaceutical industry, directly impacting consumer health and market trust. By combining multispectral imaging technology with machine learning, it is possible to achieve rapid, non-destructive, and precise detection of traditional Chinese medicine(TCM) preparations, thereby revolutionizing traditional detection methods and developing more convenient and automated solutions. This paper provides a comprehensive review of the current applications of rapid, non-destructive detection techniques based on machine learning algorithms in the field of TCM preparations. It analyzed the principles and advantages of commonly used rapid, non-destructive detection techniques, offering a reference for the application and promotion of these technologies in TCM preparation detection. Additionally, this paper explored various data preprocessing techniques, operational processes, and machine learning algorithms to enhance data utilization efficiency. Finally, it focused on the challenges of applying machine learning in TCM preparation detection and offered corresponding recommendations, providing guidance for the future integration of machine learning with rapid, non-destructive detection techniques in practical production.
Machine Learning ; Drugs, Chinese Herbal/analysis* ; Medicine, Chinese Traditional/methods* ; Humans ; Quality Control

OBJECTIVE: To investigate whether the combination of chemotherapy with staged Chinese herbal medicine (CHM) therapy could enhance health-related quality of life (QoL) in non-small-cell lung cancer (NSCLC) patients and prolong the time before deterioration of lung cancer symptoms, in comparison to chemotherapy alone. METHODS: A prospective, double-blind, randomized, controlled trial was conducted from December 14, 2017 to August 28, 2020. A total of 180 patients with stage I B-IIIA NSCLC from 5 hospitals in Shanghai were randomly divided into chemotherapy combined with CHM (chemo+CHM) group (120 cases) or chemotherapy combined with placebo (chemo+placebo) group (60 cases) using stratified blocking randomization. The European Organization for Research and Treatment of Cancer (EORTC) Quality-of-Life-Core 30 Scale (QLQ-C30) was used to evaluate the patient-reported outcomes (PROs) during postoperative adjuvant chemotherapy in patients with early-stage NSCLC. Adverse events (AEs) were assessed in the safety analysis. RESULTS: Out of the total 180 patients, 173 patients (116 in the chemo+CHM group and 57 in the chemo+placebo group) were included in the PRO analyses. The initial mean QLQ-C30 Global Health Status (GHS)/QoL scores at baseline were 57.16 ± 1.64 and 57.67 ± 2.25 for the two respective groups (P>0.05). Compared with baseline, the chemo+CHM group had an improvement in EORTC QLQ-C30 GHS/QoL score at week 18 [least squares mean (LSM) change 17.83, 95% confidence interval (CI) 14.29 to 21.38]. Conversely, the chemo+placebo group had a decrease in the score (LSM change -13.67, 95% CI -22.70 to -4.63). A significant between-group difference in the LSM GHS/QoL score was observed, amounting to 31.63 points (95% CI 25.61 to 37.64, P<0.001). The similar trends were observed in physical functioning, fatigue and appetite loss. At week 18, patients in the chemo+CHM group had a higher proportion of improvement or stabilization in GHS/QoL functional and symptom scores compared to chemo+placebo group (P<0.001). The median time to deterioration was longer in the chemo+CHM group for GHS/QoL score [hazard ratio (HR)=0.33, 95% CI 0.23 to 0.48, P<0.0010], physical functioning (HR=0.43, 95% CI 0.25 to 0.75, P=0.0005), fatigue (HR=0.47, 95% CI 0.30 to 0.72, P<0.0001) and appetite loss (HR=0.65, 95% CI 0.42 to 1.00, P=0.0215). The incidence of AEs was lower in the chemo+CHM group than in the chemo+placebo group (9.83% vs. 15.79%, P=0.52). CONCLUSION The staged CHM therapy could help improve the PROs of postoperative patients with early-stage NSCLC during adjuvant chemotherapy, which is worthy of further clinical research. (Registry No. NCT03372694).
Humans ; Carcinoma, Non-Small-Cell Lung/surgery* ; Male ; Middle Aged ; Female ; Lung Neoplasms/pathology* ; Double-Blind Method ; Drugs, Chinese Herbal/therapeutic use* ; Chemotherapy, Adjuvant ; Patient Reported Outcome Measures ; Quality of Life ; Aged ; Postoperative Period ; Prospective Studies