Objective: To explore the impact of donor reentry experience, specifically among those with a single reactive serological result who completed the reentry process, on their willingness to return for future blood donation, and to examine the mediating roles of blood donation knowledge and trait anxiety. Methods: A cross-sectional survey was conducted between November and December 2025. A total of 386 blood donors from the Changsha Blood Center were categorized into a reentry group (n=123) and a control group (n=263). Data on demographic characteristics, blood donation knowledge (BDKQ), trait anxiety (STAI-T), and blood donation return intention (BDRIS) were collected via questionnaires. SPSS 27.0 and AMOS 28.0 were used for statistical analyses, including independent-samples t-test, one-way ANOVA, multiple linear regression, and path analysis for mediating effect testing. Results: There were statistically significant differences in age, occupation, education level, monthly income and donation frequency between the reentry group and the control group (all P<0.05). The reentry group scored significantly higher in blood donation knowledge and blood donation return intention than the control group (both P<0.05). The mean BDRIS score was 11.51±3.62, indicating a relatively high intention to return. Blood donation knowledge was significantly negatively correlated with trait anxiety (r=-0.15, P<0.05) and positively correlated with blood donation return intention (r=0.19, P<0.05); trait anxiety was significantly negatively correlated with blood donation return intention (r=-0.33, P<0.05). Significant differences in BDRIS scores were found based on group (reentry vs control), age, and number of previous donations (all P<0.05). Multiple linear regression showed that BDKQ positively predicted BDRIS (β=0.11, P<0.05), while STAI-T negatively predicted BDRIS (β=-0.27, P<0.05). Path analysis further revealed that the reentry experience had no direct effect on the intention to return. However, it exerted a positive influence through two indirect pathways: 1) a simple mediating effect via increased blood donation knowledge (β=0.17, accounting for 25.0% of the total effect), and 2) a chain mediating effect through "increased blood donation knowledge → decreased trait anxiety" (β=0.05, accounting for 8.1% of the total effect). The model fit indices reached the ideal fitting criteria. Conclusion: The donor reentry experience does not directly enhance the intention to return for blood donation. Rather, it may exert an indirect positive influence by increasing blood donation knowledge and through the sequential pathway of "increased knowledge → decreased trait anxiety". Blood collection institutions should leverage the reentry process as an opportunity for education and psychological support to improve donor retention rate.

Radiochemotherapy-induced oral mucositis (OM) is a common oral complication in patients with tumors following head and neck radiotherapy or chemotherapy. Erosion and ulcers are the main features of OM that seriously affect the quality of life of patients and even the progress of tumor treatment. To date, differences in clinical prevention and treatment plans for OM have been noted among doctors of various specialties, which has increased the uncertainty of treatment effects. On the basis of current research evidence, this expert consensus outlines risk factors, clinical manifestations, clinical grading, ancillary examinations, diagnostic basis, prevention and treatment strategies and efficacy indicators for OM. In addition to strategies such as basic oral care, anti-inflammatory and analgesic agents, anti-infective agents, pro-healing agents, and photobiotherapy recommended in previous guidelines, we also emphasize the role of traditional Chinese medicine in OM prevention and treatment. This expert consensus aims to provide references and guidance for dental physicians and oncologists in formulating strategies for OM prevention, diagnosis, and treatment, standardizing clinical practice, reducing OM occurrence, promoting healing, and improving the quality of life of patients.
Humans ; Chemoradiotherapy/adverse effects* ; Consensus ; Risk Factors ; Stomatitis/etiology*

OBJECTIVE: To evaluate the safety and clinical therapeutic effect of in-line mechanical in-exsufflation to assist sputum clearance in patients with invasive mechanical ventilation. METHODS: A prospective observational study was conducted at the department of critical care medicine, the First Affiliated Hospital of Sun Yat-sen University from April 2022 to May 2023. Patients who were invasively ventilated and treated with in-line mechanical in-exsufflation to assist sputum clearance were enrolled. Baseline data were collected. Sputum viscosity, oxygenation index, parameters of ventilatory function and respiratory mechanics, clinical pulmonary infection score (CPIS) and vital signs before and after day 1, 2, 3, 5, 7 of use of the in-line mechanical in-exsufflation were assessed and recorded. Statistical analyses were performed by using generalized estimating equation (GEE). RESULTS: A total of 13 invasively ventilated patients using in-line mechanical in-exsufflation were included, all of whom were male and had respiratory failure, with the main cause being cervical spinal cord injury/high-level paraplegia (38.46%). Before the use of the in-line mechanical in-exsufflation, the proportion of patients with sputum viscosity of grade III was 38.46% (5/13) and decreased to 22.22% (2/9) 7 days after treatment with in-line mechanical in-exsufflation. With the prolonged use of the in-line mechanical in-exsufflation, the patients' CPIS scores tended to decrease significantly, with a mean decrease of 0.5 points per day (P < 0.01). Oxygenation improved significantly, with the oxygenation index (PaO₂/FiO₂) increasing by a mean of 23.3 mmHg (1 mmHg ≈ 0.133 kPa) per day and the arterial partial pressure of oxygen increasing by a mean of 12.6 mmHg per day (both P < 0.01). Compared to baseline, the respiratory mechanics of the patients improved significantly 7 days after in-line mechanical in-exsufflation use, with a significant increase in the compliance of respiratory system (Cst) [mL/cmH₂O (1 cmH₂O ≈ 0.098 kPa): 55.6 (50.0, 58.0) vs. 40.9 (37.5, 50.0), P < 0.01], and both the airway resistance and driving pressure (DP) were significantly decreased [airway resistance (cmH₂O×L^-1×s^-1): 9.6 (6.9, 10.5) vs. 12.0 (10.0, 13.0), DP (cmH₂O): 9.0 (9.0, 12.0) vs. 11.0 (10.0, 15.0), both P < 0.01]. At the same time, no new lung collapse was observed during the treatment period. No significant discomfort was reported by patients, and there were no substantial changes in heart rate, systolic blood pressure, diastolic blood pressure, and mean arterial pressure before and after the in-line mechanical in-exsufflation treatment. CONCLUSIONS The combined use of the in-line mechanical in-exsufflation to assist sputum clearance in patients on invasive mechanical ventilation can effectively improve sputum characteristics, oxygenation and respiratory mechanics. The in-line mechanical in-exsufflation was well tolerated by the patients, with no treatment-related adverse events, which demonstrated its effectiveness and safety.
Humans ; Prospective Studies ; Respiration, Artificial/methods* ; Respiratory Insufficiency/therapy* ; Sputum

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

Objective To analyze and evaluate the early warning efficacy of D-dimer/albumin ratio(DAR)combined with interleukin-6(IL-6)and fibrin degradation products(FDP)in the postoperative treatment of acute Stanford type A aortic dissection(ATAAD).Methods A retrospective cohort study was conducted on 284 ATAAD patients who underwent the Sun's procedure at our hospital from July 2024 to March 2025.Patients were divided into a non-adverse outcome group(n=196)and an adverse outcome group(n=88)based on the occurrence of postop-erative complications within 30 days,including acute renal failure requiring dialysis,secondary thoracotomy for hemostasis,severe neurological complications,multiple organ failure,or all-cause mortality.Preoperative baseline data,perioperative parameters,and laboratory indicators were collected via the electronic medical record system.The Mann-Whitney U test was used to compare the differences between groups for continuous variables that did not conform to the normal distribution,and Chi-square test or Fisher's exact test was selected for statistical difference analysis according to the frequency distribution characteristics of categorical variables.On the basis of univariate analysis,multivariate logistic regression analysis was used to screen independent risk factors.Results Statistically significant differences were observed between the non-adverse and adverse outcome group in age,cardiopulmonary bypass time,lactate dehydrogenase(LDH),IL-6,D-dimer(D-D),FDP,and DAR levels(P<0.05).Multivariate analysis revealed that DAR,IL-6,D-D,FDP,and prolonged cardiopulmonary bypass time were independent risk factors for adverse postoperative outcomes(P<0.05).Combined detection analysis demonstrated that the combination of DAR,IL-6,FDP,and cardiopulmonary bypass time yielded the highest predictive efficacy,with an area under the ROC curve of 0.886(95％CI:0.846～0.927).Conclusion The combination of DAR,IL-6,FDP,and cardio-pulmonary bypass time effectively predicts adverse postoperative outcomes in ATAAD patients.This biomarker panel may serve as a robust predictive tool for postoperative risk stratification.

Objective To explore the predictive value of intratumor and peritumoral edema radiomics combined with the autoencoder algorithm for human epidermal growth factor receptor(HER-2)status in breast cancer to provide a new idea for preoperative noninvasive prediction of HER-2 status.Methods Totally 145 breast cancer patients from Yancheng Hospital Affiliated to Nanjing University Medical College(Center 1)and 52 ones from Jianhu Hospital Affiliated to Nantong University(Center 2)had their clinical and imaging data collected retrospectively,who were divided into a HER-2 positive group including 87 ones from Center 1 and 30 ones from Center 2 and a HER-2 negative group including 58 ones from Center 1 and 22 ones from Center 2.From December 2018 to October 2024 there were 78 patients with peritumoral edema from Center 1 randomly enrolled into a training set(55 patients)and a validation set(23 patients)in a ratio of 7∶3,and from November 2024 to March 2025 another 26 ones placed into a time validation set.The 52 patients with peritumoral edema from Center 2 were included into an external test set.Firstly,the Mazda software was used to delineate the regions of interest for the largest tumor layer and the peritumoral edema area.Secondly,multivariate analysis of variance(ANOVA),Kruskal-Wallis test,recursive feature elimination(RFE)and Relief algorithm were respectively employed to screen the radiomics features;finally,combined with ten-fold cross validation,the receiver operating characteristic curve was drawn,and the diagnostic efficacy of the models respectively constructed with radiomics parameters and ten types of machine learning algorithms,including auto encoder,support vector machine,linear discriminant analysis,random forest,Logistic regression,Logistic regression via Lasso,adaptive boosting,Gaussian process,native Bayes and decision tree,was evaluated for the HER-2 status in breast cancer.Results The model established by the auto encoder algorithm combined with three feature parameters including intratumor MaxNorm and Variance and peritumoral edema SumAverg behaved the best.The average AUC values of the training and validation sets were 0.808 and 0.735 resepctively,and the AUC values of the time validation and external test sets were 0.746 and 0.732 respectively.Conclusion The model developed with intratumor and peritumoral edema radiomics combined with the auto encoder algorithm can be used for preoperative noninvasive prediction of HER-2 status of breast cancer,which provides references for the preparation of individualized treatment scheme of breast cancer patients.[Chinese Medical Equipment Journal,2025,46(9):9-15]

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.

Objective To investigate the predictive value of the diagnostic model constructed by CT radiomics combined with clin-ical and CT features for the P53 mutation status in lung adenocarcinoma.Methods The data of 177 patients with lung adenocarcinoma were retrospectively collected,including 75 cases of P53 mutant type and 102 cases of wild type.They were randomly divided into training cohort(n=123)and validation cohort(n=54)in a 7∶3 ratio.The region of interest(ROI)was delineated using MaZda software,and the features were screened using the least absolute shrinkage and selection operator(LASSO).The predictive model was devel-oped based on logistic regression analysis,and its diagnostic efficacy was evaluated.Results There were statistically significant differences in lesion diameter,maximum solid component diameter,lobulation sign,and lymph node metastasis between the two groups in the training cohort(P＜0.05).The area under the curve(AUC)in the training cohort of the radiomics score model,clinical imaging feature model,and combined model were 0.778,0.759,and 0.817,and the AUC in the validation cohort were 0.668,0.722,and 0.783,respectively.The clinical decision curve suggested that the combined model demonstrated superior clinical net benefits.Conclusion The combined model constructed by CT radiomics,lesion diameter,and lymph node metastasis has better predictive value for the P53 mutation status in lung adenocarcinoma.

Purpose To investigate the immunohistochemical HER2 expression in a large group of patients with urothelial carcinoma and to compare the results with the pathologic features and survival rate.Methods A total of 519 urothelial carcinoma specimens were collected from two centers.HER2 expression was measured by EnVision immuno-histochemistry.HER2 expression was compared with clinicopathological parameters,and further analyzed in relation to patient prognosis.Results The median age of the 519 patients was 66 years with a male to female ratio of 1.93∶1.Among them,160 cases were radical specimens,and 359 were transurethral resection specimens.The overall HER2 positivity rate was 61.7％(320/519),of which 148 cases(28.5％)were HER2 1+,238(45.9％)were HER2 2+,and 82(15.8％)were HER2 3+.In addition,51 cases(9.8％)were HER2-negative.HER2-positive ex-pression was associated with age,tumor location,histological grade,histological type,surgical approach,lymphovas-cular invasion,and neural invasion(all P＜0.05),but there was no significant correlation with gender,pT stage,muscular invasion,or lymph node metastasis.Univariate and multivariate logistic regression analysis showed that age≥ 66 years,higher tumor grade,and lymphovascular invasion were risk factors for positive HER2 expression,and high histological grade and lymphovascular invasion were independent risk factors affecting HER2 expression after controlling for confounders.Survival analysis showed no significant difference in recurrence-free survival between patients with HER2-positive and HER2-negative non-muscle-invasive urothelial carcinoma(P=0.274).Conclusion High histologic grade,tumor lymphovascular invasion,and neural invasion were associated with positive HER2 expression in patients with urothelial carcinoma,and higher histologic grade and lymphovascular invasion are important factors affect-ing HER2 expression.However,HER2-positive expression may not affect the prognosis of patients with non-muscle-invasive bladder urothelial carcinoma.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]