Objective To investigate the pathological and molecular characteristics of subcutaneous implanted thyroid lesions after endoscopic thyroid surgery.Methods A retrospective analysis was conducted on three postoperative implantation cases diagnosed in the Department of Pathology of our hospital from 2017 to 2024.Morphological evaluation,immunohistochemical staining,and next generation sequencing(NGS)targeting 66 cancer-related genes and 177 fusion loci were performed to compare features between primary and implanted lesions.Results All three implanted lesions exhibited morphological similarity to their primary counterparts,but displayed enriched mutational profiles.Case 1:a 13-year-old female.The primary lesion was an atypical follicular adenoma progressing to follicular carcinoma,while the implanted lesion was follicular carcinoma.Both lesions harbored MEN1 mutations,with an additional PTPRT mutation detected in the implanted lesion.Case 2:a 45-year-old male.The primary lesion was bilateral nodular goiter,and the implanted lesion showed follicular epithelial hyperplasia with a 0.3 cm papillary carcinoma focus.No mutations were identified in the primary lesion,whereas the implanted lesion exhibited MEN1,GLIS3,EZH1,and KMT2C mutations.Case 3:a 42-year-old female.The primary lesion included a left thyroid adenoma with cystic degeneration and right nodular goiter.A nodular goiter-like implanted lesion was detected in the right breast 5 years postoperatively.The primary lesion harbored TERT,GLIS3,and SPOP mutations,while the implanted lesion showed TERT,GLIS3,EIF1AX,and KMT2C mutations.Conclusions Endoscopic thyroid surgery is widely applied in clinical practice,however,implantation dissemination of thyroid lesions along surgical pathways may occur,encompassing both benign and malignant entities.Implanted lesions exhibit pathological similarities to their primary counterparts,but demonstrate mutational enrichment.

OBJECTIVE To explore the association of peripheral blood glucose 6 phosphate dehydrogenase(G6PD),progranulin(PGRN)and neutrophil CD64 index with the disease outcomes of the neonates with septicemia.METHODS A total of 147 neonates with septicemia who were treated in the Second Affiliated Hospital of Wenzhou Medical University from Jun.2021 to Nov.2023 were assigned as the septicemia group,meanwhile,140 healthy neonates were chosen as the healthy group.The neonates of the septicemia group were divided into the early-onset group and the late-onset group according to the type of disease,the non-critically severe group,the critically se-vere group and the extremely critically severe group according to the severity of diseases,the survival group and the death group according to 30-day prognosis.The levels of peripheral blood G6PD,PGRN and neutrophil CD64 indexes were observed and compared among the various types of groups,and the values of the peripheral blood in-dexes in prediction of the prognosis were analyzed.RESULTS The peripheral blood G6PD level of the septicemia group was significantly lower than that of the healthy group,the levels of PGRN and neutrophil CD64 index of the septicemia group were significantly higher than those of the healthy group(P＜0.05).As compared with the pe-ripheral blood G6PD level among the neonates with different illness condition,the result was as follows:the non-critically severe group＞the critically severe group＞the extremely critically severe group(P＜0.05);as com-pared with the levels of PGRN and neutrophil CD64 index,the result was as follows:the non-critically severe group＜the critically severe group＜the extremely critically severe group(P＜0.05).The peripheral blood G6PD level of the death group was significantly lower than that of the survival group(P＜0.05),and the levels of PGRN and neutrophil CD64 index of the death group were significantly higher than those of the survival group(P＜0.05).The area under the curve(AUC)of the joint detection of peripheral blood G6PD,PGRN and CD64 index was 0.831 in prediction of the prognosis of the neonates,significantly higher than that of the single detection of the three indexes(P＜0.05).CONCLUSIONS The neonates with septicemia show the decline of peripheral blood G6PD and the rise of levels of PGRN and CD64 index.The expression levels of the indexes are associated with the severi-ty of disease and,to some extent,can predict the prognosis.

Objective:To evaluate the clinical utility of machine learning model based radiomics in predicting high-risk molecular subtypes of lower-grade gliomas(LrGGs).Methods:This was a cross-sectional study. A total of 287 patients diagnosed with LrGGs in the First Hospital of Shanxi Medical University, Shanxi Provincial People′s Hospital, and the Third Hospital of Shanxi Medical University from January 2011 to September 2023 were retrospectively collected, including 166 males and 121 females; 114 cases of high-risk molecular subtypes and 173 cases of non-high-risk molecular subtypes. All patients were divided into 201 cases in the training set and 86 cases in the test set according to 7∶3 in simple randomized grouping method. All patients underwent contrast-enhanced T 1WI (CE-T 1WI) and T 2-weighted fluid-attenuated inversion recovery sequence imaging (T 2-FLAIR), and the imaging features of high-risk and non-high-risk molecular subtypes were analyzed. Analysis of variance, recursive feature elimination, and Kruskal-Wallis were used for radiomics feature screening, and a support vector machine (SVM) classifier was used to construct a radiomics-based classifier model. Univariate and multivariate logistic regression were used to analyze clinical variables independently influencing high-risk molecular subtypes of LrGGs to construct a clinical model; a combined model was developed by integrating radiomics labels and clinical variables. Receiver operating characteristic curve and area under the curve (AUC), calibration curve, and decision curve were used to compare the predictive performance of different models. Results:The patient′s age ( OR=1.042, 95% CI 1.018-1.068, P=0.001), pathological grade ( OR=2.270, 95% CI 1.212-4.311, P=0.011), MGMT methylation status ( OR=0.456, 95% CI 0.238-0.866, P=0.017), and ependymal involvement ( OR=7.335, 95% CI 2.929-18.370, P<0.001) were independent influencing factors for the high-risk molecular subtype of LrGGs, and a clinical model was developed based on these factors. An SVM model was constructed based on 12 radiomics features (3 radiomics features based on CE-T 1WI and 9 radiomics features based on T 2-FLAIR). The radiomics score of the probability output by the SVM model was combined with age, pathological grade, MGMT methylation status, and ependymal involvement to develop a combined model. The AUC values of the SVM model for predicting the high-risk molecular subtype of LrGGs were 0.824 and 0.859 in the training set and test set, respectively; the AUC values of the clinical model in the training set and test set were 0.759 and 0.721, respectively; and the AUC values of the combined model in the training set and test set were 0.823 and 0.815, respectively. The combined model had a high clinical net benefit. Conclusion:The machine learning MRI radiomics model can preoperatively predict high risk molecular subtypes of LGGrs, assist in individualized treatment decisions.

[Objective] To analyze the influencing factors of repeat blood donor lapsing using a zero-inflated poisson regression model (ZIP). [Methods] The blood donation behavior of 12 498 whole blood donors from 2020 was tracked until December 31, 2023. The factors influencing the frequency of blood donations in a given year was analyzed using ZIP, and donors with 0 blood donation in that year were considered to have lapsed. The changes in relevant influencing factors associated with each blood donation were measured and modeled for analysis. [Results] The zero-inflated part of ZIP showed that the risk of lapsing of male blood donors was 2.24 times that of female blood donors (OR 95% CI:1.864-2.696, P<0.001); the risk of lapsing of the 35-44 age group and over 45 age group was respectively 40% (OR 95% CI:0.455-0.790, P<0.001) and 61%(OR 95% CI:0.268-0.578, P<0.001) lower than that of the under 25 age group; the risk of lapsing for those who have donated blood twice and ≥3 times was respectively 50% (OR 95% CI:0.405-0.609, P<0.001) and 81% (OR 95% CI:0.154-0.225, P<0.001) lower than that of first-time donors; the risk of lapsing of those with junior high or high school education was 1.2 times that of those with a college degree or higher (OR 95% CI:1.033-1.384, P<0.05); the risk of lapsing for the divorced group was 2.02 times that of the married group (OR 95% CI:1.445-2.820, P<0.001); the risk of lapsing for those with an income (Yuan) of 10 000 to 50 000, 50 000 to 100 000 and more than 100 000 was respectively 0.67 (OR 95% CI:0.552-0.818, P<0.001), 0.72 (OR 95% CI:0.591-0.884, P=0.002) and 0.67 (OR 95% CI:0.535-0.834, P<0.001) times that of those with an income (Yuan) of less than 10 000. The results of the Poisson part are consistent with the results of the zero-inflated part in terms of age and education level. [Conclusion] Blood donor lapsing is overall related to factors such as gender, age, donation frequency, education, marital status and family income. It's essential to care for those blood donors prone to lapse to retain more regular blood donors.

Objective: To preliminarily develop a multidimensional blood donor role scale based on role theory and systematically compare the psychosocial characteristic differences between award-winning donors and first-time donors in Guangzhou, and to provide an empirical reference for formulating differentiated donor retention strategies. Methods: A cross-sectional survey design was adopted. A random sample of award-winning donors and concurrently sampled first-time donors yielding 1 361 valid responses collected (721 from the award group, 640 from the first-time group). Exploratory factor analysis was used to assess the scale structure. Data were post-stratified and weighted according to the gender and age distributions of the general donor population. Independent samples t-tests, multivariate analysis of covariance (MANCOVA), and generalized linear models were employed to compare dimensional scores between the two groups. A paired t-test was conducted to analyze the annual donation frequency of award-winning donors before and after receiving the award. Results: Exploratory factor analysis yielded a 5-factor structure, including Role Identity and Expectations, Role Adaptation and Maintenance, Role Environment and Experience, Role Relationships and Conflict, and Role Incentives and Rewards, with a cumulative variance contribution rate of 56.43%. The scale demonstrated good internal consistency reliability (Cronbach's α=0.906). Known-group validity test showed that award-winning donors scored significantly higher than first-time donors on Role Identity and Expectations (t=4.366, P<0.001, d=0.240), Role Adaptation and Maintenance (t=5.436, P<0.001, d=0.500), and Role Relationships and Conflict (t=4.844, P<0.001, d=0.220). These differences remained significant after controlling for selected demographic variables (MANCOVA, Wilks' λ=0.943, P<0.001). Generalized linear models suggested that donation frequency was an independent predictor for these dimensions. Additionally, the annual donation frequency of award-winning donors was slightly higher after receiving the award than before (t=2.007, P=0.045). Conclusion: The preliminary blood donor role scale demonstrates acceptable reliability and validity and can effectively distinguish groups with different donation behavior characteristics. The study reveals that award-winning donors exhibit more positive psychological characteristics across multiple role identity dimensions and maintain their donation behavior after receiving an award. External incentives and internal role identity may jointly contribute to behavioral persistence. The findings provide a preliminary reference for further exploring the formation pathways of donor role identity and developing differentiated donor retention strategies.

Objective To investigate the pathological and molecular characteristics of subcutaneous implanted thyroid lesions after endoscopic thyroid surgery. Methods A retrospective analysis was conducted on three postoperative implantation cases diagnosed in the Department of Pathology of our hospital from 2017 to 2024. Morphological evaluation, immunohistochemical staining, and next generation sequencing (NGS) targeting 66 cancer-related genes and 177 fusion loci were performed to compare features between primary and implanted lesions. Results All three implanted lesions exhibited morphological similarity to their primary counterparts, but displayed enriched mutational profiles. Case 1: a 13-year-old female. The primary lesion was an atypical follicular adenoma progressing to follicular carcinoma, while the implanted lesion was follicular carcinoma. Both lesions harbored MEN1 mutations, with an additional PTPRT mutation detected in the implanted lesion. Case 2: a 45-year-old male. The primary lesion was bilateral nodular goiter, and the implanted lesion showed follicular epithelial hyperplasia with a 0.3 cm papillary carcinoma focus. No mutations were identified in the primary lesion, whereas the implanted lesion exhibited MEN1, GLIS3, EZH1, and KMT2C mutations. Case 3: a 42-year-old female. The primary lesion included a left thyroid adenoma with cystic degeneration and right nodular goiter. A nodular goiter-like implanted lesion was detected in the right breast 5 years postoperatively. The primary lesion harbored TERT, GLIS3, and SPOP mutations, while the implanted lesion showed TERT, GLIS3, EIF1AX, and KMT2C mutations. Conclusions Endoscopic thyroid surgery is widely applied in clinical practice, however, implantation dissemination of thyroid lesions along surgical pathways may occur, encompassing both benign and malignant entities. Implanted lesions exhibit pathological similarities to their primary counterparts, but demonstrate mutational enrichment.

Objective:To evaluate the clinical utility of machine learning model based radiomics in predicting high-risk molecular subtypes of lower-grade gliomas(LrGGs).Methods:This was a cross-sectional study. A total of 287 patients diagnosed with LrGGs in the First Hospital of Shanxi Medical University, Shanxi Provincial People′s Hospital, and the Third Hospital of Shanxi Medical University from January 2011 to September 2023 were retrospectively collected, including 166 males and 121 females; 114 cases of high-risk molecular subtypes and 173 cases of non-high-risk molecular subtypes. All patients were divided into 201 cases in the training set and 86 cases in the test set according to 7∶3 in simple randomized grouping method. All patients underwent contrast-enhanced T 1WI (CE-T 1WI) and T 2-weighted fluid-attenuated inversion recovery sequence imaging (T 2-FLAIR), and the imaging features of high-risk and non-high-risk molecular subtypes were analyzed. Analysis of variance, recursive feature elimination, and Kruskal-Wallis were used for radiomics feature screening, and a support vector machine (SVM) classifier was used to construct a radiomics-based classifier model. Univariate and multivariate logistic regression were used to analyze clinical variables independently influencing high-risk molecular subtypes of LrGGs to construct a clinical model; a combined model was developed by integrating radiomics labels and clinical variables. Receiver operating characteristic curve and area under the curve (AUC), calibration curve, and decision curve were used to compare the predictive performance of different models. Results:The patient′s age ( OR=1.042, 95% CI 1.018-1.068, P=0.001), pathological grade ( OR=2.270, 95% CI 1.212-4.311, P=0.011), MGMT methylation status ( OR=0.456, 95% CI 0.238-0.866, P=0.017), and ependymal involvement ( OR=7.335, 95% CI 2.929-18.370, P<0.001) were independent influencing factors for the high-risk molecular subtype of LrGGs, and a clinical model was developed based on these factors. An SVM model was constructed based on 12 radiomics features (3 radiomics features based on CE-T 1WI and 9 radiomics features based on T 2-FLAIR). The radiomics score of the probability output by the SVM model was combined with age, pathological grade, MGMT methylation status, and ependymal involvement to develop a combined model. The AUC values of the SVM model for predicting the high-risk molecular subtype of LrGGs were 0.824 and 0.859 in the training set and test set, respectively; the AUC values of the clinical model in the training set and test set were 0.759 and 0.721, respectively; and the AUC values of the combined model in the training set and test set were 0.823 and 0.815, respectively. The combined model had a high clinical net benefit. Conclusion:The machine learning MRI radiomics model can preoperatively predict high risk molecular subtypes of LGGrs, assist in individualized treatment decisions.

OBJECTIVE To explore the association of peripheral blood glucose 6 phosphate dehydrogenase(G6PD),progranulin(PGRN)and neutrophil CD64 index with the disease outcomes of the neonates with septicemia.METHODS A total of 147 neonates with septicemia who were treated in the Second Affiliated Hospital of Wenzhou Medical University from Jun.2021 to Nov.2023 were assigned as the septicemia group,meanwhile,140 healthy neonates were chosen as the healthy group.The neonates of the septicemia group were divided into the early-onset group and the late-onset group according to the type of disease,the non-critically severe group,the critically se-vere group and the extremely critically severe group according to the severity of diseases,the survival group and the death group according to 30-day prognosis.The levels of peripheral blood G6PD,PGRN and neutrophil CD64 indexes were observed and compared among the various types of groups,and the values of the peripheral blood in-dexes in prediction of the prognosis were analyzed.RESULTS The peripheral blood G6PD level of the septicemia group was significantly lower than that of the healthy group,the levels of PGRN and neutrophil CD64 index of the septicemia group were significantly higher than those of the healthy group(P＜0.05).As compared with the pe-ripheral blood G6PD level among the neonates with different illness condition,the result was as follows:the non-critically severe group＞the critically severe group＞the extremely critically severe group(P＜0.05);as com-pared with the levels of PGRN and neutrophil CD64 index,the result was as follows:the non-critically severe group＜the critically severe group＜the extremely critically severe group(P＜0.05).The peripheral blood G6PD level of the death group was significantly lower than that of the survival group(P＜0.05),and the levels of PGRN and neutrophil CD64 index of the death group were significantly higher than those of the survival group(P＜0.05).The area under the curve(AUC)of the joint detection of peripheral blood G6PD,PGRN and CD64 index was 0.831 in prediction of the prognosis of the neonates,significantly higher than that of the single detection of the three indexes(P＜0.05).CONCLUSIONS The neonates with septicemia show the decline of peripheral blood G6PD and the rise of levels of PGRN and CD64 index.The expression levels of the indexes are associated with the severi-ty of disease and,to some extent,can predict the prognosis.

Objective To quantitatively evaluate the structure and content of the long-term care insurance(LTCI)policy in China's deeply aging areas.Methods Using the Policy Modeling Consistency(PMC)index model indicator design method,a LTCI policy evalua-tion index system was constructed,consisting of nine primary indicators and 34 secondary indicators.A total of 123 provincial-level LTCI policies issued in deeply aging regions of China between June 1,2014,and October 1,2024 were analyzed.High-frequency word extraction was performed using ROSTCM 6.0,and a social network diagram of LTCI policies was created.The policy structure and content were quantitatively evaluated and ana-lyzed based on the established policy evaluation index system.Results The main content of LTCI policies in deeply aging areas of China covered services,institutions and assessment.The highest policy score was 7.28,and the lowest was 2.20,with an average score of 5.00.There were 25 perfect policies,63 excellent policies,28 good policies and seven qualified policies.In the dimension of policy content,the indexes of five primary indicators of policy evaluation,policy target groups,policy nature,policy perspective and policy tools were 0.60 or more;while the indexes of four primary indicators of policy content,incentives and constraints,policy timeliness,and policy level were 0.50 or less.Conclusion LTCI policies issued in China's deeply aging areas provide comprehensive coverage in aspects such as poli-cy evaluation,policy target groups and policy nature,and need to be improved in policy tool selection and the construction of incentive and constraint mechanisms.

Objective To quantitatively evaluate the structure and content of the long-term care insurance(LTCI)policy in China's deeply aging areas.Methods Using the Policy Modeling Consistency(PMC)index model indicator design method,a LTCI policy evalua-tion index system was constructed,consisting of nine primary indicators and 34 secondary indicators.A total of 123 provincial-level LTCI policies issued in deeply aging regions of China between June 1,2014,and October 1,2024 were analyzed.High-frequency word extraction was performed using ROSTCM 6.0,and a social network diagram of LTCI policies was created.The policy structure and content were quantitatively evaluated and ana-lyzed based on the established policy evaluation index system.Results The main content of LTCI policies in deeply aging areas of China covered services,institutions and assessment.The highest policy score was 7.28,and the lowest was 2.20,with an average score of 5.00.There were 25 perfect policies,63 excellent policies,28 good policies and seven qualified policies.In the dimension of policy content,the indexes of five primary indicators of policy evaluation,policy target groups,policy nature,policy perspective and policy tools were 0.60 or more;while the indexes of four primary indicators of policy content,incentives and constraints,policy timeliness,and policy level were 0.50 or less.Conclusion LTCI policies issued in China's deeply aging areas provide comprehensive coverage in aspects such as poli-cy evaluation,policy target groups and policy nature,and need to be improved in policy tool selection and the construction of incentive and constraint mechanisms.