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.

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

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:To investigate the value of antioxidant-associated long non-coding RNAs(lncRNAs)risk score model in prognosis and the association with immune microenvironment of the gastric cancer patients.Methods:Gastric cancer transcriptome data and clinical information were downloaded from TCGA database.Antioxidant-associated lncRNAs were obtained by co-ex-pression analysis of lncRNAs and antioxidant genes.Risk score was constructed using univariate cox regression analysis and lasso regression analysis.Log-Rank test was used to compare the survival differences between two groups.Receiver operating characteristic curve(ROC)was used to assess the specificity and sensitivity of the prognostic risk score model.Nomogram was constructed com-bining risk score and clinical parameters.Immune cell infiltration was assessed by TIMER 2.0.Im-munotherapy sensitivity of each sample was analyzed at TIDE website.Results:A risk score in-cluding 12 IncRNAs was constructed by univariate cox regression analysis and lasso regression anal-ysis.The risk score was an independent factor influencing patient prognosis[HR=5.406(3.131～9.335),P＜0.001].Risk score was positively correlated with multiple suppressive immune cells infil-tration(M2 macrophage,tumor-associated fibroblast).Meanwhile,multiple aberrant expression of immune checkpoint genes and higher TIDE score were found in high-risk group,suggesting that high-risk groups may be more sensitive to immunotherapy.Conclusion:The antioxidant-associ-ated IncRNAs risk score is a good prognostic predictor and can act as a reference in individualized immunotherapy for gastric cancer patients.

Objective To compare the efficacy and safety of empagliflozin and linagliptin in the treatment of patients with type 2 diabetes mellitus(T2DM)with heart failure(HF).Methods Patients with T2DM and HF were randomly into control group and treatment group.Both groups were treated with individualized anti-HF and metformin-based hypoglycemic therapy.On this basis,the control group was given linagliptin orally(5 mg each time,once a day),while the treatment group was given oral administration of empagliflozin 10 mg every day.Patients in both groups were treated continuously for 6 months.The clinical efficacy and blood glucose indicators[fasting blood glucose(FBG),2 h postprandial blood glucose(2 h PBG),hemoglobin A1c(HbA1c)],cardiac molecular markers[N-terminal pro-brain natriuretic peptide(NT-proBNP),fibroblast growth factor 23(FGF23),copeptin(CPP)]and caridac function indicators[left ventricular end-diastolic diameter(LVEDD),left ventricular ejection fraction(LVEF),left ventricular remodeling index(LVRI)]before and after treatment were compared,and the adverse drug reactions were recorded.Results There were 40 cases in treatment group and 40 cases in control group.After treatment,the total effective rates in treatment group and control group were 97.50％(39 cases/40 cases)and 80.00％(32 cases/40 cases),with no significant difference(P＜0.05).The FBG levels in treatment group and control group were(7.64±1.18)and(7.83±1.24)mmol·L-1;2 h PBG levels were(8.97±1.46)and(9.04±1.35)mmol·L-1;HbA1c levels were(7.58±1.27)％and(7.65±1.42)％,all with no significant difference(all P＞0.05).The NT-proBNP levels in treatment group and control group were(612.53±204.62)and(1 045.24±316.75)pg·mL-1;FGF23 levels were(362.74±62.61)and(493.27±74.64)μg·L-1;CPP levels were(12.58±3.43)and(16.87±4.36)pmol·L-1;LVEDD values were(51.19±2.36)and(53.35±2.24)mm;LVEF values were(52.69±3.38)％and(50.28±3.75)％;LVRI values were(2.62±0.29)and(2.96±0.33)kg·L-1,all with significant difference(all P＜0.05).The incidence rates of adverse reactions in treatment group and control group were 5.00％(2 cases/40 cases)and 10.00％(4 cases/40 cases),with no significant difference(P＞0.05).Conclusion Both empagliflozin and linagliptin can effectively reduce the blood glucose in patients with T2DM complicated with HF.Empagliflozin can better promote the improvement of cardiac function in patients without significantly increase the incidence of adverse drug reactions.

Objective:To investigate the effect of pre-treatment plasma Epstein-Barr virus(EBV)DNA copy number on the clinical features and prognosis of patients with adult secondary hemophagocytic lymphohistiocytosis(sHLH).Methods:The clinical characteristics,survival rate,and prognostic factors of 171 patients with adult sHLH treated at Jiangsu Province Hospital from June 2017 to January 2022 were retrospectively analyzed in this study.Patients were divided into three groups,including the EBV DNA-negative group(＜5.0 × 102 copies/ml),lower EBV-DNA loads group(5.0 × 102-8.51 × 104 copies/ml),and higher EBV-DNA loads group(＞8.51 × 104 copies/ml),according to pre-treatment plasma EBV-DNA copy number.Cox regression model was established for screening prognostic factors.Adult sHLH survival prediction model was constructed and realized through the nomogram based on EBV-DNA load after adjusted the factors affecting survival of etiology and treatment strategy.Concordance index(C-index)and calibration curves were calculated to verify model predictive and discriminatory capacity.Results:Among 171 adult sHLH patients,84 patients were not infected with EBV(EBV DNA-negative group),and 87 with EBV(EBV DNA-positive group,48 lower EBV-DNA loads group and 39 higher EBV-DNA loads group).Consistent elevations in the levels of liver enzymes(ALT and AST),LDH,TG,β2-microglobulin and ferritin across the increasing of EBV-DNA load(all P＜0.05),while the levels of fibrinogen decrease(P＜0.001).The median follow-up time was 52 days(range 20-230 days),and 123 patients died.The overall survival(OS)rate of patients in EBV DNA-positive group was lower than that in EBV DNA-negative group(median OS:40 days vs 118 days,P＜0.001).Higher EBV-DNA loads had worse OS(median OS:24 days vs 45 days vs 118 days,P＜0.0001 for trend)compared to lower EBV-DNA loads and EBV DNA-negative group.Multivariate Cox analysis revealed that higher EBV-DNA loads(P=0.005),fibrinogen≤ 1.5 g/L(P=0.012),ferritin(P=0.041),associated lymphoma(P=0.002),and anti-tumor based strategy(P=0.001)were independent prognostic factors for OS.The C-indexes of 30 day,90 days,365 days survival rate were all greater than 0.8 of the nomogram model and calibration curves provided credibility to their predictive capability.Subgroup analysis showed that patients with higher EBV-DNA loads had a significantly worse prognosis in adult sHLH who were women,ferritin＞5 000 μg/L,β2-microglobulin＞7.4 mmol/L and regardless of age,etiologies,HScore points.Conclusion:The EBV-DNA load is a strong and independent predictor for survival in patients with sHLH.The prognostic nomogram based on EBV-DNA loads was dependable and provides a visual tool for evaluating the survival of adult sHLH.

Objective To investigate the feasibility of translocation of pedicled buccal fat pad in the treatment of the temporomandibular joint ankylosis(TMJA)by measuring the diameter of buccal fat pad and related anatomical structures of the transverse blood vessels,nerves and temporomandibular joint.Methods A total of 40 adult head and neck specimens were randomly divided into group A and group B,with 20 cases in each group.The morphology of the buccal fat pad in group A was observed,and its size and compression diameter through blood vessels and nerves were measured.The anatomical structures of the temporomandibular joint in group B were observed and measured.Results The volume of buccal fat pad in group A was(10.10±1.10)mL on the left side and(9.70±1.50)mL on the right side.The longitudinal axis length of buccal fat pad was(28.18±1.35)mm on the left side and(29.47±1.12)mm on the right side;Transverse axis length of buccal fat pad was(18.56±1.67)mm on the left side and(18.97±1.73)mm on the right side;There are facial artery,facial vein,maxillary artery branch,facial nerve buccal branch and so on through the buccal fat pad.In group B,the sagittal section of the temporomandibular joint disc presented S-type in 15 cases(75.0%),L-type in 3 cases(15.0%),and transitional type in 2 cases(10.0%).Anterior and posterior diameter of the articular disc was(14.42±1.94)mm on the left side and(15.34±1.37)mm on the right side;inside and outside diameter of the articular disc was(20.18±1.77)mm on the left side and(19.57±1.32)mm on the right side.Branches of maxillary artery and superficial temporal artery were respectively distributed within and outside the joint.Conclusion The pedicled buccal fat pad has a constant anatomical position,abundant blood supply,strong tissue repair,anti-infection ability and"buffer pad"function,which can reduce the formation of scar after surgery for TMJA,reduce the postoperative recurrence rate,and contribute to the recovery of joint function after surgery.

Objective To propose a object detection method based on an improved YOLOv8 model to solve the problems of the inspection robot in low accuracy for recognizing pointer-type or obscured meters.Methods Firstly,a YOLOv8 model was chosen as the foundation object detection model,based on which the coordinate attention(CA)mechanism was introduced to enhance the model's understanding of the spatial structure of the input data over long distances;secondly,the original complete IoU(CIoU)loss function was replaced by an efficient IoU(EIoU)loss function to accelerate the convergence of the model's detection frame;finally,the soft non-maximum suppression(Soft-NMS)function took the place of the traditional NMS method to suppress the redundant bounding box smoothly and further improve the detection accuracy.The improved YOLOv8 model(YOLOv8nxt model)was compared with the YOLOv8n model to verify its efficacy for object detection.Results The YOLOv8nxt model with a size of 6.2 M had the position loss decreased by 1.3％,mAP_0.5∶0.95 increased by 1.7％,detection accuracy raised by 0.87％and detection time prolonged by only 0.2 ms when comparted with the YOLOv8n model.Conclusion The improved YOLOv8 model-based object detection method enhances the accuracy and speed of the inspection robot's recognition of meters during movement,and can effectively solve the problems of the inspection robot in the object detection stage.[Chinese Medical Equipment Journal,2024,45(3):1-8]

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