Quality control (QC) of biospecimens from oral and maxillofacial tumors patients constitutes a critical foundation for the prevention, diagnosis, treatment, and precision medicine research of these diseases. Biospecimen quality directly governs the discovery and validation of disease biomarkers, the elucidation of pathogenesis, and the efficacy of clinical translation. QC spans the entire biospecimen lifecycle—encompassing collection, processing, storage, transportation, and utilization. Its primary objectives are to ensure sample integrity, reliability, traceability, and consistency, thereby guaranteeing the robustness of research data; the accuracy of molecular subtyping, biomarker identification, and treatment response prediction; and the precision of clinical decision-making. However, current QC frameworks for these biospecimens remain underdeveloped. Drawing on domestic and international technical standards, regulatory guidelines, and recent research advances, this paper elaborates on the importance of implementing a QC management system throughout the biospecimen lifecycle. It focuses on QC methodologies tailored to diverse biospecimen types, examining how standardized sampling procedures, regulated preprocessing workflows, and optimized long-term storage conditions influence sample quality. We aim to provide concrete guidance and a transferable paradigm for establishing standardized QC protocols and an informatics-enabled traceability system specific to oral and maxillofacial tumors. Such efforts are intended to enhance the research value and clinical utility of these biospecimens, furnishing reliable sample resources and technical support for the development of precision diagnostics and therapeutics. Furthermore, we advocate for a dual-track “QC plus Ethics” management framework within biobanks. This approach would reinforce ethical and legal safeguards, establishing a robust barrier to support safe scientific innovation and clinical translation.

OBJECTIVE To construct ensemble learning models for predicting high-use days of budesonide based on meteorological factors， thereby providing reference for hospital pharmacy management. METHODS Meteorological data for 2024 and outpatient budesonide usage data from the jurisdiction of Sanming Hospital of Integrated Traditional Chinese and Western Medicine were collected. High-use days were defined as the 75th percentile of outpatient budesonide usage， and a corresponding dataset was established. The prediction task was formulated as a classification problem， and three ensemble learning models were developed： Random Forest， Extreme Gradient Boosting （XGBoost）， and Histogram-based Gradient Boosting Classifier. Model performance was evaluated using accuracy， precision， recall， F1-score， and log-loss. Model interpretability was analyzed using Shapley Additive Explanations （SHAP）. RESULTS The Histogram-based Gradient Boosting Classifier achieved the best performance （accuracy＝0.75， F1-score＝0.48）， followed by XGBoost （accuracy＝0.74， F1-score＝0.43） and Random Forest （accuracy＝0.72， F1-score＝0.22）. SHAP results suggested that the prediction results of the last two models have the highest correction. CONCLUSIONS Ensemble learning models can effectively predict high-use days of budesonide， with the Histogram- based Gradient Boosting Classifier demonstrating the best predictive performance. Low temperature， high humidity， and low atmospheric pressure show significant positive impacts on the prediction of daily budesonide usage.

Objective To understand the willingness to engage in the combine medical care with old-age care institutions of medical students in vocational colleges and analyze their influencing factors.Methods By convenient sampling method,1 266 medical students from 3 vocational colleges in Hunan Province were select-ed as the research objects,and their occupational cognition and occupational willingness were investigated and analyzed.Through objective sampling,20 medical students who were not willing to work in medical institu-tions were selected for semi-structured interviews.Results 62.1%of medical students intend to work in med-ical institutions after graduation;The results of multi-factor analysis showed that the experience of caring for the elderly,understanding of the nursing institution,participating in the volunteer service of the nursing insti-tution,and cognition score of the combination of medical care and nursing were the influencing factors of med-ical students'career intention(P＜0.05).The qualitative interview found that professional identity,job abili-ty,salary,social security and promotion were the main influencing factors.Conclusion Medical students in medical nursing institutions do not have strong willingness,so they should improve their professional cogni-tion of old-age service,enhance their professional identity and post competency,fully implement salary,social security and professional title promotion,attract more medical students to engage in the combined service in-dustry,and promote the combined development of medical care.

Objective This study aims to explore effective approaches for the transfer of medical scientific and techno-logical achievements to promote the development of research-oriented hospitals.Methods The technology transfer achievements of an affiliated hospital of a university in Guangdong Province over the past six years(2018-2023)were statistically analyzed.The challenges faced during the transfer process,the measures taken,and the current achievements were discussed.Results The number of patent authorizations and authorized departments in the hospital has increased year by year.The transfer rate has risen from 0％in 2019 to 6.69％in 2023.Currently,46 projects have been successfully transferred,with a total transfer amount exceeding 30 million yuan,indicating significant effectiveness in the transfer of medical scientific and technological achievements.Conclusion The hospital attaches great importance to and overall manages the transfer process,establishing a sound manage-ment structure,improving incentive and support systems,and regularly conducting special lectures,training,and guidance.These efforts guide researchers to start from clinical problems and ultimately serve clinical diagnosis and treatment,creating a fa-vorable environment for technology transfer,improving the transfer rate,and promoting the development of research-oriented hos-pitals.

Objective:To explore the application value of CT-guided percutaneous coaxial needle biopsy (CT-PTCB) in the diagnosis of malignant tumors.Methods:A retrospective case series study was conducted. The clinical data of 802 suspected malignant tumor patients who underwent CT-PTCB upon admission to Beijing Chaoyang District Huanxing Cancer Hospital from January 2019 to December 2023 were analyzed. All patients underwent imaging follow-up combined with CT-PTCB or surgical pathology to determine the final diagnosis. The CT-PTCB puncture effect, diagnosis effect and incidence of complications were recorded.Results:Among the 802 patients, 488 (60.8%) were male and 314 (39.2%) were female, with the age of (51±11) years. The puncture sites included 610 cases (76.1%) in the chest, 169 cases (21.1%) in the abdomen, 17 cases (2.1%) in the bones, and 6 cases (0.7%) in the pelvic cavity. The success rate of CT-PTCB puncture upon admission was 99.5% (798/802), the diagnostic accuracy was 96.5% (774/802), and the false negative rate was 3.5% (28/802). The incidence of pneumothorax and bleeding in patients undergoing pulmonary CT-PTCB was 13.0% (75/575) and 17.9% (103/575), respectively; the incidence of puncture bleeding in patients undergoing liver CT-PTCB was 0.8% (1/125), and the incidence of pain was 1.6% (2/125); the incidence of pneumothorax in patients undergoing mediastinal CT-PTCB was 8.7% (2/23); no obvious complications were observed in other puncture sites. All complications were cured through active treatment.Conclusions:The application of CT-PTCB for the diagnosis of malignant tumors has high success rate and diagnosis rate, and is safe and minimally invasive.

OBJECTIVE To explore the mechanism by which Gongfa Static Training regulates mitophagy through the PTEN-in-duced kinase 1(PINK1)/Parkin pathway in skeletal muscle insulin resistance in type 2 diabetes mellitus(T2DM).METHODS T2DM mouse model was established using a high-fat diet combined with streptozotocin(STZ)intraperitoneal injection.Mice were ran-domly divided into a model group,a metformin group,an aerobic exercise group,and a Gongfa Static Training group.The intervention effects of Gongfa Static Training were evaluated by measuring fasting blood glucose,Homeostatic Model Assessment of Insulin Resist-ance(HOMA-IR),glycated hemoglobin(HbA1c),lipid metabolism indicators,mitochondrial function in the gastrocnemius muscle,and the expression of PINK1 and Parkin-related genes and proteins.RESULTS Gongfa Static Training significantly reduced fasting blood glucose,HbA1c,and insulin resistance index in T2DM mice,improved lipid metabolism,and enhanced insulin sensitivity.It improved the structure and function of mitochondria in the gastrocnemius muscle by upregulating the mRNA and protein expression of PINK1 and Parkin.CONCLUSION Gongfa Static Training improves mitochondrial function and insulin resistance in the skeletal muscle of T2DM mice by regulating the PINK1/Parkin pathway.

Objective To analyze the multi-target mechanism of Paeoniflorin in the intervention of oral submucosal fibrosis(OSF)systematically,based on molecular dynamics simulation and network pharmacology.Methods Identify potential targets of Paeoniflorin were predicted by using database.OSF-related disease targets and identified drug-disease intersecting targets were screened.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis were conducted to validate the molecular binding capabilities between Paeoniflorin and core targets.Finally,molecular dynamics simulations were performed to verify binding stability.Results A total of 20 overlapping targets were identified,including key genes such as transforming growth factor(TGF)-β1,interleukin(IL)-6,and tumor necrosis factor(TNF)-α.TGF-β1,IL-6,and TNF formed the core hub.The enrichment analysis revealed that the target molecules were significantly enriched in the TGF-β1,phosphatidylinositol 3-kinease-actin(PI3K-Akt),and nuclear factor κB(NF-κB)signaling pathways.Molecular docking confirmed high affinity binding of Paeoniflorin to targets including TGF-β1,while molecular dynamics simulations verified stable interactions between Paeoniflorin and both TGF-β1 and B-cell lymphoma-2 targets.Conclusion This study revealed that Paeoniflorin inhibits the inflammatory-fibrotic cascade of OSF through synergistic regulation of TGF-β1/Smad,PI3K-Akt and NF-κB pathways.

OBJECTIVE To explore the mechanism by which Gongfa Static Training regulates mitophagy through the PTEN-in-duced kinase 1(PINK1)/Parkin pathway in skeletal muscle insulin resistance in type 2 diabetes mellitus(T2DM).METHODS T2DM mouse model was established using a high-fat diet combined with streptozotocin(STZ)intraperitoneal injection.Mice were ran-domly divided into a model group,a metformin group,an aerobic exercise group,and a Gongfa Static Training group.The intervention effects of Gongfa Static Training were evaluated by measuring fasting blood glucose,Homeostatic Model Assessment of Insulin Resist-ance(HOMA-IR),glycated hemoglobin(HbA1c),lipid metabolism indicators,mitochondrial function in the gastrocnemius muscle,and the expression of PINK1 and Parkin-related genes and proteins.RESULTS Gongfa Static Training significantly reduced fasting blood glucose,HbA1c,and insulin resistance index in T2DM mice,improved lipid metabolism,and enhanced insulin sensitivity.It improved the structure and function of mitochondria in the gastrocnemius muscle by upregulating the mRNA and protein expression of PINK1 and Parkin.CONCLUSION Gongfa Static Training improves mitochondrial function and insulin resistance in the skeletal muscle of T2DM mice by regulating the PINK1/Parkin pathway.

Objective:To investigate the relationship between the serum levels of vascular endothelial growth factor (VEGF), matrix metalloproteinase-9 (MMP-9), S100 calcium binding protein B (S100B) with glycolipid metabolism, pregnancy outcome in pregnant women with gestational diabetes.Methods:The clinical data of 153 pregnant women with gestational diabetes (research group) and 153 healthy pregnant women (control group) in the Second Affiliated Hospital of Xi ′an Medical University from January 2020 to October 2023 were retrospectively analyzed. The serum levels of VEGF, MMP-9 and S100B were measured by enzyme linked immunosorbent assay, and the fasting blood glucose, triglyceride, total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), fasting insulin and glycated hemoglobin were measured, and the homeostasis model assessment insulin resistance index (HOMA-IR) was calculated. The adverse outcomes of pregnant women with gestational diabetes were recorded. Pearson method was used to analyze the correlation between glycolipid metabolism indexes and VEGF, MMP-9, S100B in pregnant women with gestational diabetes. Multivariate Logistic regression was used to analyze the independent risk factors of adverse pregnancy outcome in pregnant women with gestational diabetes. Receiver operating characteristic (ROC) curve was drawn to analyze the predictive value of VEGF, MMP-9 and S100B on adverse pregnancy outcome in pregnant women with gestational diabetes. Results:The fasting blood glucose, fasting insulin, glycated hemoglobin, HOMA-IR, triglyceride, total cholesterol, LDL-C, VEGF, MMP-9 and S100B in research group were significantly higher than those in control group: (9.42 ± 0.65) mmol/L vs. (4.13 ± 0.46) mmol/L, (16.58 ± 2.37) mU/L vs. (13.41 ± 2.05) mU/L, (7.28 ± 0.46)% vs. (4.35 ± 0.39)%, 4.83 ± 0.42 vs. 2.71 ± 0.37, (3.41 ± 0.67) mmol/L vs. (2.85 ± 0.63) mmol/L, (5.54 ± 1.56) mmol/L vs. (5.12 ± 1.50) mmol/L, (3.14 ± 0.97) mmol/L vs. (2.86 ± 0.93) mmol/L, (184.02 ± 30.25) ng/L vs. (156.33 ± 26.41) ng/L, (45.78 ± 7.56) μg/L vs. (29.36 ± 5.03) μg/L and (117.51 ± 25.12) ng/L vs. (89.74 ± 22.46) ng/L, the HDL-C was significantly lower than that in control group: (1.34 ± 0.27) mmol/L vs. (1.42 ± 0.30) mmol/L, and there were statistical differences ( P<0.01 or <0.05). Pearson correlation analysis result showed that VEGF, MMP-9, S100B in pregnant women with gestational diabetes were positively correlated with fasting blood glucose, fasting insulin, glycated hemoglobin, HOMA-IR, triglyceride, total cholesterol and LDL-C ( P<0.01), negatively correlated with HDL-C ( P<0.01). Among 153 pregnant women with gestational diabetes, 49 had adverse pregnancy outcome, and 104 had good pregnancy outcome. The VEGF, MMP-9 and S100B in pregnant women with adverse pregnancy outcome were significantly higher than those in pregnant women with good pregnancy outcome: (212.75 ± 28.63) ng/L vs. (170.49 ± 26.58) ng/L, (52.37 ± 7.14) μg/L vs. (42.68 ± 6.35) μg/L and (136.83 ± 23.62) ng/L vs. (108.41 ± 21.35) ng/L, and there were statistical differences ( P<0.01). Multivariate Logistic regression analysis result showed that VEGF, MMP-9 and S100B were independent risk factors for adverse pregnancy outcome in pregnant women with gestational diabetes ( OR = 7.013, 5.382 and 6.129; 95% CI 5.206 to 9.447, 3.449 to 8.398 and 3.520 to 10.673; P<0.01). ROC curve analysis result showed that the area under the curve of VEGF, MMP-9 combined S100B in predicting adverse pregnancy outcome in pregnant women with gestational diabetes was significantly larger than that of VEGF, MMP-9 and S100B alone (0.945 vs. 0.863, 0.847 and 0.801; P<0.05 or <0.01), with sensitivity of 89.80% and specificity of 91.30%. Conclusions:The high serum levels of VEGF, MMP-9 and S100B are associated with abnormal glycolipid metabolism and adverse pregnancy outcome in pregnant women with gestational diabetes, and the combination of the three indexes has a high predictive value for adverse pregnancy outcome.