Objective To introduce the causes of accidents and the diagnosis and treatment of two patients with radiation-induced skin injury admitted to our hospital in 2023, and to provide a reference for the clinical treatment of subsequent radiation-induced skin injury. Methods The clinical treatment process of two patients with acute skin injury caused by external radiation exposure were summarized and analyzed. Results The exposure history of the two patients was reconstructed, the flaw detection scenario was simulated, the biological dose and hand skin exposure dose were estimated, and the infrared thermal imaging device was used for dynamic monitoring. A comprehensive analysis was conducted based on clinical manifestations and other data. The diagnosis of “Xie” was excessive exposure combined with acute radiation-induced skin injury on both hands (Grade IV for the right hand palm, index finger, and middle finger and Grade II for the left hand little finger). The diagnosis of “Hao” was acute radiation-induced skin injury on both hands (Grade I). The two patients received different clinical treatment measures: “Xie” was treated with both local and systemic therapies, while “Hao” was mainly treated with systemic therapy. Conclusion After systematic and effective treatment, the radiation-induced skin injuries healed in both patients.

Objective:To explore the mediating effect of sleep quality on the relationship between serum vitamin D3 level and depressive symptoms in community-dwelling elderly people with mild cognitive impairment(MCI).Methods:A total of 480 elderly people with MCI meeting inclusion criteria in a community health service center from Jan 2023 to Dec 2023 were selected as the research objects.The general information questionnaire,mini-mental state examination(MMSE),activity of daily living scale(ADL),Center for Epidemiological Studies Depression Scale(CES-D)and Pittsburgh sleep quality index(PSQI)were used to investigate the subjects.Serum vitamin D3 level was detected within 1 week.Spearson correlation analysis was used to explore the correlation between sleep quality,serum vitamin D3 level and depressive symptoms.The mediating effect model was tested by Model 4 in the Process plug-in.Results:Among the 480 MCI elderly,the average score of depression was(12.28±4.75),the average serum vitamin D3 level was(25.81±7.09)ng/ml,and the average score of sleep quality was(7.17±2.71).Depression severity was positively correlated with sleep quality score(r=0.294,P＜0.01),and negatively correlated with serum vitamin D3 level(r=-0.237,P＜0.01).Serum vitamin D3 level was negatively correlated with sleep quality score(r=-0.225,P＜0.01).Bootstrap analysis showed that the mediating effect of sleep quality between serum vitamin D3 level and depression level was-0.064(95%CI:-0.115--0.023),accounting for 26.57%of the total effect.Conclusion:Sleep quality partially mediates the relationship between serum vitamin D3 level and depressive symptoms in the elderly with MCI in the community.

Objective:In carbon ion treatment planning of water phantom, establish a conversion factor calculation system and conversion factor curves for organs at risk (OAR) for microdosimetric kinetic models (MKM) and local effect models (LEM), and validate them in clinical patient planning.Methods:Using a uniform spherical water phantom as the research object, relative biological effectiveness-weighted doses (RWD) for the LEM were re-calculated based on the physical dose of RayStation-MKM. The median dose within the planning target volume (PTV) of LEM and MKM was regarded as the conversion factor. The impacts of single-fraction target prescription dose, spread-out Bragg peak (SOBP) width and depth, shape, and irradiation mode on the conversion factor were assessed, and a conversion factor calculation system was established. Additionally, the accuracy of the conversion factor calculation system was validated using both water phantoms and clinical patient cases. The conversion factor curves for OAR were computed based on clinical patient treatment plans.Results:The primary influencing factors for the conversion factors were the single-fraction prescription dose, target SOBP width and depth. The conversion factors were increased with the increase of SOBP width and target depth, whereas decreased with the increase of the single-fraction prescription dose. Under single-field irradiation, a conversion factor calculation system was established based on above 3 parameters. For the plans of 9 patients, the average difference between the calculated results and the conversion factor calculation system was 0.340% ± 0.203%, and the average difference in the conversion curves for OAR was 2.650% ± 2.399%.Conclusion:A dose conversion factor calculation system and conversion factor curves for OAR for carbon ion radiotherapy are established for MKM and LEM, and their accuracy meets the requirements for use in clinical patient treatment plans.

The pathway by which cells obtain energy is inconsistent in aerobic and anaerobic conditions, glucose enters the cell and is converted into pyruvate by glycolysis under the action of hexokinase. When oxygen is sufficient, pyruvate enters the mitochondrial matrix and is converted into acetyl-CoA under the action of pyruvate dehydrogenase to participate in the tricarboxylic acid cycle and ultimately produce the necessary energy support for cell activities. When the cells are in an hypoxic state, pyruvate can produce lactic acid under the action of lactate dehydrogenase, and then carry out the corresponding cell activities after being energized. In recent years, advances in scientific research have elucidated that lactate serves not only as a crucial energy source, directly participating in metabolic processes such as mitochondrial respiration, but also plays critical roles in various physiological and pathological processes, including the regulation of inflammation, tissue repair, memory formation, and neuroprotection. These multifaceted functions further influence the onset, progression, and prognosis of diseases, thereby underscoring the broad regulatory significance of lactate in organismal physiology. Lactic acid modification is also associated with the occurrence and development of vascular related diseases, including changes in vascular endothelial microenvironment, lactic acid accumulation after thrombosis and inflammation, promotion of vascular endothelial microenvironment hypoxia, and lactic acid stimulation of vascular endothelial cells to produce inflammatory response. Clarifying the relationship between lactate modification and vaso-related diseases may help to reveal the underlying mechanism of disease occurrence and development. This article reviews the relationship between Lactylation and vascular related diseases, aiming to provide new targets and references for the treatment of vascular related diseases.

Objective:To explore the mediating effect of sleep quality on the relationship between serum vitamin D3 level and depressive symptoms in community-dwelling elderly people with mild cognitive impairment(MCI).Methods:A total of 480 elderly people with MCI meeting inclusion criteria in a community health service center from Jan 2023 to Dec 2023 were selected as the research objects.The general information questionnaire,mini-mental state examination(MMSE),activity of daily living scale(ADL),Center for Epidemiological Studies Depression Scale(CES-D)and Pittsburgh sleep quality index(PSQI)were used to investigate the subjects.Serum vitamin D3 level was detected within 1 week.Spearson correlation analysis was used to explore the correlation between sleep quality,serum vitamin D3 level and depressive symptoms.The mediating effect model was tested by Model 4 in the Process plug-in.Results:Among the 480 MCI elderly,the average score of depression was(12.28±4.75),the average serum vitamin D3 level was(25.81±7.09)ng/ml,and the average score of sleep quality was(7.17±2.71).Depression severity was positively correlated with sleep quality score(r=0.294,P＜0.01),and negatively correlated with serum vitamin D3 level(r=-0.237,P＜0.01).Serum vitamin D3 level was negatively correlated with sleep quality score(r=-0.225,P＜0.01).Bootstrap analysis showed that the mediating effect of sleep quality between serum vitamin D3 level and depression level was-0.064(95%CI:-0.115--0.023),accounting for 26.57%of the total effect.Conclusion:Sleep quality partially mediates the relationship between serum vitamin D3 level and depressive symptoms in the elderly with MCI in the community.

Objective:In carbon ion treatment planning of water phantom, establish a conversion factor calculation system and conversion factor curves for organs at risk (OAR) for microdosimetric kinetic models (MKM) and local effect models (LEM), and validate them in clinical patient planning.Methods:Using a uniform spherical water phantom as the research object, relative biological effectiveness-weighted doses (RWD) for the LEM were re-calculated based on the physical dose of RayStation-MKM. The median dose within the planning target volume (PTV) of LEM and MKM was regarded as the conversion factor. The impacts of single-fraction target prescription dose, spread-out Bragg peak (SOBP) width and depth, shape, and irradiation mode on the conversion factor were assessed, and a conversion factor calculation system was established. Additionally, the accuracy of the conversion factor calculation system was validated using both water phantoms and clinical patient cases. The conversion factor curves for OAR were computed based on clinical patient treatment plans.Results:The primary influencing factors for the conversion factors were the single-fraction prescription dose, target SOBP width and depth. The conversion factors were increased with the increase of SOBP width and target depth, whereas decreased with the increase of the single-fraction prescription dose. Under single-field irradiation, a conversion factor calculation system was established based on above 3 parameters. For the plans of 9 patients, the average difference between the calculated results and the conversion factor calculation system was 0.340% ± 0.203%, and the average difference in the conversion curves for OAR was 2.650% ± 2.399%.Conclusion:A dose conversion factor calculation system and conversion factor curves for OAR for carbon ion radiotherapy are established for MKM and LEM, and their accuracy meets the requirements for use in clinical patient treatment plans.

Objective:To investigate the relationship between health promoting behavior and frailty in elderly patients with proliferative diabetic retinopathy(PDR),and the mediating effects of self-efficacy and loneliness.Methods:In an eye hospital of Anhui Province,214 elderly patients with PDR were selected from May 2021 to Nov 2022 by convenient sampling method.The Frailty Scale,Chinese Version of Health-Promoting Lifestyle Profile-Ⅱ,Self-Efficacy Scale and Simplified Loneliness Scale were used in this survey.Bootstrap method of Process software was used to analyze the mediating effect of self-efficacy on the relationship between health promoting behaviors and frailty in elderly PDR patients and the moderating effect of loneliness on the relationship between self-efficacy and frailty.Results:A total of 220 questionnaires were distributed and 214 valid questionnaires were returned,with valid response rate of 97.27% .Moderated mediation effect analysis suggested that health-promoting behaviors negatively predicted frailty(β=-0.508,P＜0.01).Health promoting behaviors and self-efficacy had significant predictive effects on frailty(β=-0.191 and-0.433,P＜0.01),and health promoting behaviors also had a significant predictive effect on self-efficacy(β=0.063,P＜0.01).Self-efficacy played a partially mediating role between health promoting behaviors and frailty,and the mediating effect accounted for 14.76% of the total effect.The product term of loneliness and self-efficacy significantly predicted frailty(β=0.255,P＜0.01),the mediating effect of self-efficacy on frailty was moderated by loneliness.Conclusions:The health-promoting behaviors of elderly patients with PDR affect frailty through self-efficacy,and loneliness moderates the relationship between self-efficacy and frailty.The moderated mediation model is established.

Objective To construct a machine learning model for predicting benign and malignant pulmonary nodules based on CT features.Methods A total of 129 patients with single solid nodules on CT from January 2021 to January 2023 in Hai'an People's Hospital were selected.All of them underwent chest CT scan,and the quantitative parameters,morphological features and radiomics features were recorded.The differentiation of benign and malignant pulmonary nodules was carried out according to relevant diagnostic criteria.The cases were divided into the training set and the internal test set.The constructed models included radiomics labels,morphological model,CT model and combined model.Results There were 98 cases in the training set(27 malignance and 71 benign)and 31 cases in the internal test set(7 malignance and 24 benign).Univariate analysis showed that there were significant differences in age,lesion diameter,mean density,burr sign,pleural depression sign,vacuole sign and air bronchial sign between malignant group and benign group(P<0.05).Compared with benign group,malignant group had higher proportions of burr sign,pleural depression sign,vacuole sign,air bronchial sign,and larger lesion diameter and mean density(P<0.05).LinkDocAI intelligent diagnosis system for pulmonary nodules was used to outline regions of interest and from which 1 000 radiomics features were extracted.The feature selection was performed in 98 cases,and 20 features were screened out after standardized treatment and correlation testing,excluding missing features,low importance feature values and highly correlated features.Through LASSO regression and 10-fold cross validation,λ1se was selected as the optimal λ to construct radiomics labels,and the two most meaningful features(LBP_Glszm_ZoneEntropy and Gradient_Shape_MinorAxis)were enrolled.CT model was considered as the optimal model in this study,and it had an area under receiver operating characteristic curve of 0.912 and 0.889 in the training set and the internal testing set,respectively.Conclusion The machine learning model to predict benign and malignant lung nodules based on CT features has good predictive efficiency,and it can realize the differential diagnosis of benign and malignant pulmonary nodules.

Purpose To investigate the clinical value of artificial intelligence(AI)quantitative parameters in predicting the invasion degree of lung adenocarcinoma with diameter≤2 cm of ground-glass density.Materials and Methods A total of 80 patients with lung adenocarcinoma with diameter≤2 cm ground-glass density confirmed by pathology from March 2019 to April 2022 were retrospectively analyzed.A total of 90 nodules were rerolled,including 8 adenocarcinomas in situ(AIS),34 minimally invasive adenocarcinomas(MIA)and 48 invasive adenocarcinomas(IAC).They were divided into the experimental group(IAC)and the control group(AIS and MIA).The differences of the AI quantitative parameters such as volume,three-dimensional length diameter,maximum area,maximum CT value,minimum CT value and average CT value were compared between two groups,and the predictive values of AI quantitative parameters for the invasion degree of lung adenocarcinoma was evaluated.Results There were statistically significant differences with age,volume,three-dimensional length diameter,maximum area,maximum CT value and average CT value between the two groups(all P<0.05),but no statistically significant differences in gender and minimum CT value(both P>0.05).Binary Logistic regression analysis showed that the three-dimensional length diameter(odd ratio=2.020,P=0.034)and the maximum CT value(odd ratio=1.008,P=0.013)were independent predictors for lung adenocarcinoma with diameter≤2 cm of ground-glass density.The regression model based on the three-dimensional length diameter and the maximum CT value had the best predictive performance,and its AUC was 0.901.When the critical value was 2.432,its sensitivity and specificity were 93.75%and 71.43%,respectively.Conclusion AI quantitative parameters have a high value in predicting the degree of invasion of lung adenocarcinoma with diameter≤2 cm of ground-glass density,and the combined model with three dimensional long diameter and maximum CT value has the highest diagnostic efficiency.

Objective To explore the prognostic value of MCF in elderly patients with cardiac amy-loidosis using CMR.Methods A retrospective analysis was conducted on 54 elderly patients with cardiac amyloidosis diagnosed in our hospital.All patients underwent CMR imaging.They were di-vided into a survival group of 25 cases and a mortality group of 29 cases based on clinical out-comes.Correlations of MCF with CMR parameters and biochemical indicators were evaluated.Cox regression analysis was performed to identify independent predictors of patient survival.Survival analysis was used to assess the value of MCF in predicting patient prognosis.Results The surviv-al group had significantly higher MCF than the mortality group[(70.63±24.72)％vs(43.59± 13.36)％,P=0.001].As MCF increasing,LVEF level was in an increasing trend,while LVMI,LVGPWT,ECV,and troponin T and NT-proBNP levels showed a decreasing trend.Multivariate Cox regression analysis revealed that MCF was an independent predictor of patient survival(HR=0.922,95％CI:0.866-0.981,P=0.011).Kaplan-Meier survival curve showed that the patients with MCF＞57％had significantly higher survival rates than those with MCF ≤57％(P＜0.01).Conclusion MCF is an effective imaging indicator for evaluating the prognosis of elderly patients with cardiac amyloidosis,which can help identify high-risk patients and guide clinical treatment.