Objective To investigate the correlation between glycemic variability metrics and the risk of diabetic foot(DF)in patients with type 2 diabetes mellitus(T2DM)utilizing flash glucose monitoring(FGM)tech-nology.Methods A retrospective analysis was conducted on 233 hospitalized patients with T2DM,with or without DF,who were treated in the Department of Endocrinology at Lianyungang First People's Hospital from January 2021 to May 2022 and monitored using FGM.Patients were categorized into a non-DF group(n=147)and a DF group(n=86)based on the presence of DF.The study compared general clinical characteristics,biochemical parameters,and glycemic variability metrics between the two groups and performed subgroup analyses.Binary logistic regression was employed to identify factors associated with the risk of DF,while receiver operating characteristic(ROC)curves were utilized to assess the predictive value of glycemic variability metrics for DF.Results Compared with the non-DF group,patients in the DF group exhibited significantly longer disease duration,higher body mass index(BMI),glycated hemoglobin(HbA1c),urinary albumin-to-creatinine ratio(UACR),alanine aminotransferase(ALT),serum uric acid(SUA),mean amplitude of glycemic excursions(MAGE),coefficient of variation(CV),mean of daily differences(MODD),and mean blood glucose(MBG),but lower fasting C-peptide(FCP),fasting insulin(FINS),high-density lipoprotein cholesterol(HDL-C),and time in range(TIR),with statistically signifi-cant differences(P<0.05).Subgroup analysis revealed that TIR was associated with the incidence of DF and diabetic retinopathy(DR).Binary logistic regression analysis identified HbA1c,MAGE,MODD,and MBG as risk factors for DF,while TIR was a protective factor(P<0.05).ROC curve analysis demonstrated that the area under the curve(AUC)for predicting DF using HbA1c,TIR,MAGE,MODD,MBG,and their combination were 0.646,0.850,0.868,0.764,0.619,and 0.967,respectively,indicating superior performance of the combined prediction model.Conclusions HbA1c,TIR,MAGE,MODD,and MBG are critical factors associated with the development of DF in patients with T2DM.Targeted early interventions aimed at optimizing these glycemic variability indicators may effectively reduce the incidence of DF.

This study innovatively incorporates on-site teaching with the International Museum of Stomatology into the curriculum to establish an immersive and intuitive teaching mode,promoting education from both theoretical and practical dimensions.The teaching effect is comprehensively evaluated to explore the pathway to optimization.Multi-dimensional questionnaires are designed to collect feedback data from students on teaching satisfaction,knowledge mastery,professional identity,and humanistic literacy perception,fol-lowed by in-depth quantitative and qualitative analyses.The results demonstrate that this teaching mode significantly enhances literacy,playing a critical role in helping stomatological students fully understand professional knowledge and humanistic connotations while sub-stantially improving their professional identity.This teaching mode gives a direction for innovative stomatological education,holds sig-nificant importance for cultivating stomatological professionals with both clinical skills and humanistic literacy,possessing substantial potential for promotion,application,and further refinement.

Aim To evaluate the bioequivalence of two oral preparations of rivaroxaban tablets(test preparation T and refe-rence preparation R)in fasting/postprandibular state in healthy Chinese subjects.Methods A randomized,open,single-dose,four-cycle,completely repeated crossover experiment was used in this study.A total of 70 healthy male and female subjects were enrolled,including 38 subjects in the fasting group and 32 sub-jects in the postprandial group.Rivaroxaban tablets(2.5 mg/tablet)were taken orally once per cycle and their reference preparations were tested.The plasma rivaroxaban concentration was determined by LC-MS/MS method.The pharmacokinetic parameters of rivaroxaban tablets were calculated by WinNonlin software,and the parameters were analyzed and processed.Re-sults The PK parameters of rivaroxaban tablets and reference preparations in fasting group were as follows:Cmax was(72.48±17.08)and(66.36±15.64)μg·L-1,respectively.AUC0-t were(383.49±101.06)and(370.43±102.16)h·ng·mL-1,and AUC0-inr were(389.58±102.28)and(375.84±103.01)h·μg·L-,respectively.Main PK parameters of subjects taking rivaroxaban tablets orally after meals:Cmax were(66.48±15.64 and 60.87±13.44)μg·L-1,AUC0-t were(404.44±72.58)and(381.80±79.93)h·μg·L-1,re-spectively.AUC0_inf was(410.88±73.55)and(393.64±69.71)h·μg·L-1,respectively.Under fasting and postmeal conditions,subjects took rivaroxaban test and reference prepara-tion orally,one tablet(2.5 mg/tablet)each time.The geometric mean of the main pharmacokinetic parameters of rivaroxaban in plasma(Cmax,AUC0-t,AUC0-inf)and their corresponding values had a 90％confidence interval ranging from 80.00％to 125.00％.No serious adverse events or unexpected adverse e-vents occurred in both groups.Conclusion Rivaroxaban tablets are bioequivalent and safe in vivo under fasting and postprandial conditions.

Extremely unbalanced data refers to datasets with independent or dependent variables showing severe imbalances in proportions, which might lead to deviation of classical test statistics from theoretical distribution and difficulties in controlling type Ⅰ error. The increased availability of genome-wide resources from large population cohorts has highlighted the growing demand for efficient and accurate statistical methods for the process of extremely unbalanced data to improve the development of genetic statistical methods. This paper introduces two widely used correction methods in current genome-wide association study for extremely unbalanced data, i.e. Firth correction and saddle point approximation, describes their effectiveness in controlling type Ⅰ errors confirmed by simulation experiments, finally, and summarizes the commonly used software for extremely unbalanced genomic data to provide theoretical reference and suggestion for its application for the statistical analysis on extremely unbalanced data in future.

Different insect drugs have their own characteristics in terms of efficacy,including removing blood stasis and promoting blood circulation,dispelling phlegm and dispersing lumps,and nourishing the body.This article discussed the use of insect medicines in the treatment of chronic heart failure(CHF)based on the theory of"collateral deficiency and tonifying".Taking the TCM theory of"collateral deficiency and tonifying"as the entry point,this article categorized the pathogenesis of CHF into deficiency of qi and yang,deficiency of collaterals,phlegm retention and dampness stagnation,and accumulation of collaterals,and believes that the treatment should be based on resolving blood stasis and promoting collaterals,eliminating phlegm and promoting collaterals,dispersing lumps and promoting collaterals,and tonifying heart collaterals,thus achieving the effect of"collateral deficiency and tonifying".It also summarized the efficacy and modern pharmacological mechanisms of insect drugs,providing medication ideas for the treatment of CHF.

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 explore the effects of deep hyperthermia on chemotherapy-related adverse effects and immune-inflammatory indicators in the patients undergoing postoperative adjuvant chemotherapy for colorectal cancer.Methods:This retrospective study included 52 patients who underwent surgery for colorectal cancer at the Affiliated Zhongshan Hospital of Dalian University from September 2021 to December 2023. The patients were divided into two groups based on treatment method: the combination group ( n=29) received postoperative adjuvant chemotherapy combined with deep hyperthermia, while the chemotherapy group ( n=23) received postoperative adjuvant chemotherapy alone. Both groups were treated with the XELOX regimen (oxaliplatin + capecitabine). The degree of bone marrow suppression during treatment was assessed by analyzing peripheral blood parameters, including hemoglobin, leukocyte count, neutrophil count, and platelet count. Immune-inflammatory indicators, including complement, procalcitonin (PCT), interleukin-6 (IL-6), systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), were compared before and after treatment in both groups to evaluate the effects of deep hyperthermia on the immune-inflammatory response. Chi-square test or Fisher's exact test (two-tailed) was used to compare bone marrow suppression rates, and the immune-inflammatory indicators between the two groups were compared using t-tests or non-parametric tests, depending on whether the data conformed to a normal distribution. Results:In terms of myelosuppression, the incidence rates of moderate to severe decreases in leukocytes, neutrophils, platelets, and hemoglobin in the combination group were 31%, 31%, 21%, and 14%, respectively, compared to 52%, 61%, 48%, and 9% in the chemotherapy group. The change in PCT levels before and after treatment was significantly greater in the combination group than in the chemotherapy group ( P = 0.010). Both the combination group and the chemotherapy group showed significant reductions in SII, NLR and PLR after treatment, and the differences were statistically significant (all P < 0.05). The change in NLR before and after treatment was significantly greater in the combination group than in the chemotherapy group ( P = 0.031). Conclusions:Deep hyperthermia can alleviate chemotherapy-induced adverse effects such as thrombocytopenia and neutropenia in patients undergoing postoperative adjuvant chemotherapy for colorectal cancer. It also appears to improve the inflammatory response in these patients.

Extremely unbalanced data refers to datasets with independent or dependent variables showing severe imbalances in proportions, which might lead to deviation of classical test statistics from theoretical distribution and difficulties in controlling type Ⅰ error. The increased availability of genome-wide resources from large population cohorts has highlighted the growing demand for efficient and accurate statistical methods for the process of extremely unbalanced data to improve the development of genetic statistical methods. This paper introduces two widely used correction methods in current genome-wide association study for extremely unbalanced data, i.e. Firth correction and saddle point approximation, describes their effectiveness in controlling type Ⅰ errors confirmed by simulation experiments, finally, and summarizes the commonly used software for extremely unbalanced genomic data to provide theoretical reference and suggestion for its application for the statistical analysis on extremely unbalanced data in future.

This study innovatively incorporates on-site teaching with the International Museum of Stomatology into the curriculum to establish an immersive and intuitive teaching mode,promoting education from both theoretical and practical dimensions.The teaching effect is comprehensively evaluated to explore the pathway to optimization.Multi-dimensional questionnaires are designed to collect feedback data from students on teaching satisfaction,knowledge mastery,professional identity,and humanistic literacy perception,fol-lowed by in-depth quantitative and qualitative analyses.The results demonstrate that this teaching mode significantly enhances literacy,playing a critical role in helping stomatological students fully understand professional knowledge and humanistic connotations while sub-stantially improving their professional identity.This teaching mode gives a direction for innovative stomatological education,holds sig-nificant importance for cultivating stomatological professionals with both clinical skills and humanistic literacy,possessing substantial potential for promotion,application,and further refinement.

Objective:Middle ear cholesteatoma is a common otolaryngological disease, and traditional diagnostic methods have certain limitations. This study aims to construct a computer-aided diagnosis model for middle ear cholesteatoma based on integrated convolutional neural networks (CNNs) to improve diagnostic accuracy and efficiency.Methods:Firstly, Data were collected from patients who visited the Department of Otorhinolaryngology Head and Neck Surgery at the First People′s Hospital of Yinchuan between January 2020 and December 2021. 8 000 temporal bone CT images were collected, including 5 000 images diagnosed pathologically as middle ear cholesteatoma and 3 000 normal images. A five-fold cross-validation method was used to divide the dataset into training and testing sets. Next, a transfer learning approach was used to initialize model parameters, and the AlexNet, GoogleNet, and ResNet networks were pre-trained to extract deep features from the images. Then, the Softmax classification algorithm was applied to classify the features, resulting in three independent classifiers. These classifiers were combined using an ensemble learning method with a weighted voting approach to obtain the final diagnostic results. Finally, the model was evaluated by comparing the ensemble classifier with individual classifiers to assess its accuracy, precision, sensitivity, specificity, and diagnostic time, and a comparison with low-mid-and high-experience physician groups was conducted to comprehensively evaluate the model′s diagnostic performance.Results:The experimental results showed that the model achieved an accuracy of 88.8%(178/200), precision of 92.9%,(112/120) sensitivity of 89.8%(108/120), and specificity of 88.1%(70/80). The average diagnostic time for individual patient temporal bone CT images was reduced to 2-3 seconds. Compared to the diagnostic results from low-mid-and high-experience physician groups, the model demonstrated significant advantages and effectively assisted clinicians in making rapid and accurate middle ear cholesteatoma diagnoses.Conclusion:The proposed middle ear cholesteatoma diagnostic model based on integrated convolutional neural networks exhibits high recognition accuracy and rapid diagnostic speed, significantly improving clinical diagnostic efficiency, especially in early screening and auxiliary diagnosis, making it of considerable value in clinical practice.