Objective:To explore the changes of sex hormones in children with cryptorchidism of different ages after laparoscopic treatment and the risk factors that affect the timing of surgery, so as to improve the surgical effect of the treatment of children with cryptorchidism.Methods:A total of 80 children with cryptorchidism admitted to our hospital from Jun. 2018 to Aug. 2021 were selected as the study subjects, and all children underwent laparoscopic surgery. Twenty-six children aged 6 to 12 months were included in the younger group, 42 children aged 1 to 2 years were included in the middle age group, and 12 children >2 years old were included in the over-age group. Surgical data of the children were recorded, and the levels of follicle-stimulating hormone (FSH) , Luteinizing hormone (LH) and Testosterone (T) were detected. Logistic analysis was used to analyze the independent risk factors affecting the timing of operation in children with cryptorchidism, and ROC curve analysis was used to analyze the diagnostic value of factors affecting the timing of operation in children with cryptorchidism.Results:The level of T (the younger group (7.36±1.63) vs (7.48±1.67) ng/ml; the middle-age group (7.03±1.26) vs (7.11±1.07) ng/ml; the over-age group (4.81±1.37) vs (4.92±1.63) ng/ml) , occult testicular volume (the younger group (0.30±0.01) vs (0.32±0.03) cm3; the middle-age group (0.45±0.14) vs (0.47±0.11) cm 3; the over-age group (0.45±0.09) vs (0.61±0.08) cm 3) and occult testicular minimum blood flow velocity (the younger group (3.42±0.87) vs (4.26±0.94) cm/s; the middle-age group (3.51±0.26) vs (5.69±0.35) cm/s; the over-age group (8.41±0.34) vs (23.64±0.19) cm/s) increased in all three groups,In terms of intraoperative blood loss, postoperative time to get out of bed, and incision pain time, the over-age group > the middle age group > the younger group; FSH and LH decreased in the young age group and increased in the middle age group and over-age group ( P < 0.05) . Age, family income, primiparas, smoking or passive smoking during pregnancy, gestational diabetes mellitus, and protein supplementation during pregnancy were independent risk factors affecting the timing of surgery in children with untorchidism. The areas under ROC curve were 0.884, 0.704, 0.785, 0.842, 0.904, and 0.845, respectively. The area under ROC curve to evaluate the differentiation was 0.866. Conclusion:The range of sex hormone changes in children with cryptorchidism of different ages after laparoscopic treatment is related to age, family income, primipara, smoking or passive smoking during pregnancy, diabetes mellitus during pregnancy, and no protein supplement during pregnancy are the factors affecting the timing of surgery.

Objective:To explore the values of ultrasound, pathology combined with inflammatory indicators in predicting high nodal burden (HNB) in patients with early breast cancer and to construct a nomogram to provide reference for individualized diagnosis and treatment.Methods:The ultrasonographic, pathological features and preoperative inflammatory indicators of 378 female patients diagnosed with early breast cancer confirmed by pathology in the South Hospital of the Sixth People′s Hospital Affiliated to Shanghai Jiaotong University from January 2014 to July 2022 were retrospectively analyzed. They were randomly divided into training set ( n=302) and test set ( n=76) in a ratio of 8∶2, and the baseline data of the two groups were compared. The optimal cutoff values of neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) and lymphocyte to monocyte ratio (LMR) were obtained by ROC curve. In the training set, with axillary high lymph node load (≥3 metastatic lymph nodes) as the dependent variable, independent influencing factors of HNB were identified by univariate and multivariate Logistic regression analyses, and the nomogram was established. The test set data were used to verify the model. The discrimination, calibration and clinical applicability of the model were assessed by the area under the ROC curve (AUC), C-index, the calibration curve, Brier score and the decision curve analysis, respectively. Results:There were no significant differences in all variables between the training set and the test set (all P>0.05). ROC curve analysis results showed that AUCs of NLR, PLR and LMR were 0.578, 0.547 and 0.516, respectively, and the optimal cut-off values were 2.184, 150 and 3.042, respectively. Univariate Logistic regression analysis showed that age, pathological type, histological grade, Ki-67, lymphovascular invasion, NLR, PLR, ultrasonic characteristics (maximum diameter of primary tumor, shape, long/short diameter of lymph node, cortical thickness, cortical and medullary boundary, lymph node hilum, lymph node blood flow pattern) were correlated with HNB of early breast cancer (all P<0.05). Multivariate Logistic regression analysis showed that ultrasonic characteristics (maximum diameter of primary tumor >2 cm, effacement of lymph node hilum, non-lymphatic portal blood flow), lymphovascular invasion, Ki-67>14% and NLR>2.184 were independent risk factors for HNB in early breast cancer ( OR=7.258, 8.784, 6.120, 8.031, 3.394 and 3.767, respectively; all P<0.05) and were used to construct the nomogram model. The AUC of the training set was 0.914 (95% CI=0.878-0.949), C-index was 0.914; The AUC of the test set was 0.871 (95% CI=0.769-0.973), C-index was 0.871, indicating good discrimination. Calibration curve and Brier score were 0.090, indicating high calibration degree of the model. The clinical decision curve indicated good clinical benefit. Conclusions:The nomogram based on ultrasonic characteristics (maximum diameter of primary tumor, lymph node hilum, lymph node blood flow pattern), lymphovascular invasion, Ki-67 and NLR can effectively predict the risk of HNB in patients with early breast cancer, and provide a reference for precision diagnosis and treatment to avoid excessive or insufficient treatment.

Objective:To evaluate the immunogenicity of a novel influenza virus mRNA vaccine based on conserved antigens delivered by lipopolyplex (LPP) platform in a mouse model.Methods:Four copies of genes coding for extracellular domain of matrix 2 protein (M2e) and nucleoprotein (NP) of influenza A virus were synthetized after codon optimization. The fusion antigens were transcribed in vitro and delivered by LPP platform, named as LPP-4M2eNP. Expression of M2e and NP in eukaryotic cells was detected by immunofluorescence assay (IFA). BALB/c mice were inoculated intramuscularly twice with 10 μg or 30 μg LPP-4M2eNP vaccine at an interval of four weeks. Antibody response was detected by ELISA and cellular-mediated immunity (CMI) was detected by enzyme-linked immunospot assay (ELISPOT). Results:IFA showed that NP and M2e were expressed correctly in eukaryotic cells. Single dose immunization could induce significant antigen (NP, M2e)-specific CMI and antigen (NP, M2e)-specific antibody response was induced in mice with Th1 type bias after boost immunization. Moreover, NP-specific CMI was increased significantly after the second immunization, while no significant change in M2e-specific CMI was observed.Conclusions:Stronger CMI was triggered in mice by single dose of LPP-4M2eNP vaccine. Furthermore, robust humoral and cellular immune responses were induced after boost immunization. This study suggested that LPP-4M2eNP vaccine, which based on conserved antigen of influenza A and delivered by LPP platform, had great potential for development and application.

Objective:To establish an ultrasound radiomics model by integrating clinical, pathological, and conventional ultrasound features with radiomics characteristics, and to explore its clinical value in predicting endocrine resistance in hormone receptor(HR)-positive breast cancer.Methods:A retrospective analysis was performed on 478 patients with HR-positive breast cancer from January 2017 to December 2021 in the Second Affiliated Hospital of Harbin Medical University, of which 430 were resistant and 48 were sensitive. The clinical, pathological and immunohistochemical data and ultrasound images were collected.Firstly, the propensity score was used to process and match the data. Secondly, Logistic regression was used to screen clinical, pathological, and conventional ultrasound features associated with endocrine resistance. Then, PyRadiomics was used to extract the radiomic features of grayscale ultrasound images, and a series of methods such as Lasso regression were used to screen the radiomic features related to endocrine resistance. Seven machine learning methods such as random forest were used to build a radiomics model. Finally, clinical, pathological and ultrasound features were added to establish a clinical pathological model, a clinical pathological ultrasound model, a clinical pathological radiomics model and a combined model of the four features, and the model effectiveness was evaluated.Results:①Propensity score matching: 96 patients were matched, including 48 patients in the drug-resistant group and 48 patients in the sensitive group. ②Screening clinical pathological conventional ultrasound features related to endocrine resistance: lymph node metastasis, tumor diameter, posterior echo attenuation, and growth orientation were independent predictors of endocrine resistance (all P<0.05). ③Screening radiomics features related to endocrine resistance: 18 features such as Dependence Entropy. ④Establishing radiomics model: the machine learning model of random forest method (AUC=0.80) performed best. ⑤Radiomics model integrating clinical, pathological and conventional ultrasound features: the AUC of the clinical pathological model was 0.70, the AUC of the clinical pathological ultrasound model was 0.78, the AUC of the clinical pathological radiomics model was 0.82, and the AUC of the combined model was 0.86. Conclusions:The radiomics model established by the random forest method performs best in predicting endocrine resistance in HR-positive breast cancer. The model that integrates multiple features performs best in assessing endocrine resistance.which is expected to provide an objective basis for clinicians to predict endocrine resistance in HR-positive breast cancer.

Objective This study aimed to identify PAX9 variants in non-syndromic tooth agenesis families of Chi-na,as well as to analyze the genotype-phenotype of non-syndromic tooth agenesis caused by PAX9 variants,which can provide a basis for the genetic diagnosis of tooth agenesis.Methods We collected the data of 44 patients with non-syn-dromic oligodontia who underwent treatment at Stomatological Hospital of Hebei Medical University between 2018 and 2023.Whole-exome sequencing was performed on the peripheral blood of the proband and its core family members,and the variants were verified by Sanger sequencing.Pathogenicity analysis and function prediction of the variants were per-formed using bioinformatics tools.The correlation between the genotype of PAX9 variant and its corresponding pheno-type was examined by reviewing 55 publications retrieved from PubMed.The studies involved 232 tooth agenesis pa-tients with PAX9 variants.Results A novel PAX9 c.447delG(p.Pro150Argfs*62)and a reported PAX9 c.406C>T(p.Gln136*)were identified in two Chinese families.Through bioinformatics analysis and three-dimensional structural mod-eling,we postulated that the frameshift variant was pathogenic.The outcome was the premature cessation of PAX9 pro-tein,which caused severe structural and functional deficiencies.Summarizing the PAX9 genotype-phenotype relationship revealed that patients carrying the PAX9 variant commonly led to loss of the second molars.Conclusion We identified the novel PAX9 c.447delG(p.Pro150Argfs*62)in a Chinese family of non-syndromic oligodontia,expanding the known variant spectrum of PAX9.The most susceptible tooth position for PAX9 variants of tooth agenesis was the second mo-lars and the deciduous molars during the deciduous dentition.

OBJECTIVE: To evaluate the effect of health self-management on self-efficiency of diabetes patients.
 METHODS: A total of 184 eligible and voluntary diabetes patients were recruited for 6 consecutive weeks of knowledge and skills intervention, and interviewed with questionnaire by diabetes self-efficacy scale (DSES) before and after the intervention. The changes in self-efficiency were compared with two paired sample McNemar test.
 RESULTS: After the intervention, the total scores of self-efficiency on diet, medication, blood sugar monitoring, foot care and complications management were all increased significantly compared with those before the intervention (P<0.05).
 CONCLUSION The intervention model of health self-management for self-efficiency in diabetes patients is effective, and the quality of patients' life can be improved.
Diabetes Mellitus ; psychology ; therapy ; Disease Management ; Humans ; Self Care ; Self Efficacy ; Surveys and Questionnaires