Objective: To analyze the serological phenotypes and molecular genetic characteristics of a proband with ABO forward and reverse typing discrepancy and their family members, and to investigate the molecular genetic mechanism underlying the Ael/AelB phenotype caused by the c. 575T>C variant on an ABO A1.02 background. Methods: Serological testing and adsorption-elution assays were performed for blood group identification of the proband and family members. PCR-SBT, cloning sequencing, and Nanopore third-generation sequencing were used to analyze ABO gene variants and haplotypes. Phyre2 and PyMOL were used to predict the effect of the p. Ile192Thr variant on the structure of glycosyltransferase A (GTA), and plasma GTA activity was evaluated using an in vitro transferase assay. Results: Among thirteen family members, four members showed a serological phenotype consistent with the Ael subtype and one with the AelB subtype. Cloning sequencing and third-generation sequencing confirmed that five family members carried the ABO A1.02 (c. 575T>C) variant, which co-segregated with the weak A phenotype in the family. Structural modeling suggested that p. Ile192Thr may alter the local spatial conformation and hydrogen-bond interactions of GTA. Plasma GTA activity testing showed markedly reduced GTA activity in the tested individuals. Conclusion: The ABO A1.02 (c. 575T>C) variant is associated with the Ael/AelB phenotype. The p. Ile192Thr substitution may weaken A antigen expression by altering GTA conformation and reducing enzymatic activity. This study provides additional evidence for the role of this variant in the Ael/AelB phenotype from the perspectives of familial inheritance, full-length haplotype analysis, and functional assessment, which is important for accurate ABO subtype identification and individualized transfusion strategies.

ObjectiveTo investigate the mechanism underlying the weight loss effect of electrothermal acupuncture （ETA） in diet-induced obese （DIO） model mice based on the hypoxia-inducible factor-1α （HIF-1α）/sphingosine-1-phosphate （S1P）sphingosine-1-phosphate receptor 3 （S1PR3） signaling pathway-mediated macrophage polarization. MethodsAn obesity mouse model was established by continuously feeding at a high-fat diet （HFD） for 8 weeks. Twenty successfully modeled obese mice were randomly divided into a model group and an electrothermal acupuncture （ETA） group with 10 mice per group， both of which continued to receive the HFD till week 12. Another 10 mice were assigned to the normal group and fed a standard chow diet continuously for 12 weeks. Starting from week 9 of the experiment， mice in the ETA group received electrothermal acupuncture stimulation at Zhongwan （CV12）， bilateral Tianshu （ST25）， and bilateral Zusanli （ST36） for 30 minutes per session， with the instrument current set at （40±0.5）mA and a constant temperature of （40±0.5）℃. Mice in the normal group and the model group were restrained in the same manner for 30 minutes without acupuncture. All interventions were performed once every other day for a total of 4 weeks. Ten hours after the final intervention， the body weight， waist circumference， and body length of mice in each group were measured， and Lee's index was calculated. Serum biochemical analysis was performed to assess fasting blood glucose （FBG）， total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein cholesterol （HDL-C）， low-density lipoprotein cholesterol （LDL-C）， alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， blood urea nitrogen （BUN）， and creatinine （Cr）. Serum leptin （LEP） and adiponectin （ADPN） levels， as well as sphingosine-1-phosphate （S1P） levels in epididymal white adipose tissue （eWAT）， were detected by ELISA. Histomorphological changes in eWAT were monitored via HE staining. Flow cytometry was used to analyze macrophage subtype-related indexes in eWAT， including the total proportion of macrophages， the proportion of M1 macrophages， the proportion of M2 macrophages， and the M1/M2 ratio. Antibody array technology was used to determine the levels of differentially expressed inflammatory factors in eWAT between the model and blank groups， as well as between the ETA and model groups. Western blot and qPCR were used to detect the protein and mRNA expression levels of HIF-1α and S1PR3 in the eWAT， respectively. ResultsCompared to the normal group， the model group showed significantly increased body weight， Lee's index， waist circumference， and FBG， TC， TG， HDL-C， LDL-C， AST， and ALT levels， upgraded LEP and S1P levels， decreased ADPN level and ADPN/LEP ratio， elevated proportion of M1 macrophages and the M1/M2 ratio， reduced proportion of M2 macrophages， and upregulated protein and mRNA expression levels of HIF-1α and S1PR3 （P＜0.05 or P＜0.01）. With the exception of HDL-C， all the abovementioned indicators in the ETA group were significantly improved compared to the model group （P＜0.05 or P＜0.01）. Analysis of differentially expressed inflammatory cytokines revealed that， compared to the normal group， the levels of interleukin-1β （IL-1β）， interferon-γ （IFN-γ）， interleukin-6 （IL-6）， and interleukin-12p70 （IL-12p70） in the eWAT of the model group were elevated； conversely， the levels of interleukin-17 （IL-17）， interleukin-5 （IL-5）， IL-6， and interleukin-23 （IL-23） in the eWAT of the ETA group decreased compared to the model group （P＜0.05 or P＜0.01）. ConclusionETA exerts a weight-reducing effect in obese model mice， and the mechanism may involve inhibition of the HIF-1α/S1P/S1PR3 signaling pathway activation， which shifts macrophage polarization from the M1 to M2 phenotype， thereby alleviating chronic inflammation.

Objective:To explore the correlation between serum hepcidin antimicrobial peptide (HAMP), secreted phosphoprotein 1 (SPP1), and regulator of G protein signaling 2 (RGS2) levels and the clinical pathological characteristics of gastric cancer patients, and their predictive value for postoperative recurrence or metastasis.Methods:A total of 92 gastric cancer patients treated at Handan First Hospital from March 2021 to March 2023 were selected as the gastric cancer group, and 92 healthy individuals who underwent physical examinations during the same period were selected as the control group. The serum levels of HAMP, SPP1 and RGS2 were compared between the two groups. According to the mean levels of HAMP, SPP1, and RGS2 in the serum of gastric cancer patients, they were divided into HAMP high level group and HAMP low level group, SPP1 high level group and SPP1 low level group, RGS2 high level group and RGS2 low level group. The clinicopathological characteristics of gastric cancer patients with different levels of HAMP, SPP1 and RGS2 were compared respectively. After a median follow-up of 18 months, gastric cancer patients were divided into a non-recurrence or metastasis group ( n=59) and a recurrence and metastasis group ( n=33) based on whether the tumor recurred or metastasized. The serum levels of HAMP, SPP1, and RGS2 were compared between the two groups of patients. The predictive value of HAMP, SPP1 and RGS2 for postoperative recurrence or metastasis in patients with gastric cancer was analyzed by using the receiver operator characteristic (ROC) curve. Results:Compared with the control group, the gastric cancer group had higher levels of serum HAMP [ (52.28±5.44) ng/ml vs. (31.22±4.18) ng/ml] and SPP1 [ (55.96±6.43) ng/ml vs. (36.99±5.25) ng/ml] ( t=29.44, P<0.001; t=21.92, P<0.001), and lower level of RGS2 [ (3.72±0.66) mg/L vs. (5.11±0.87) mg/L) ] ( t=12.21, P<0.001). There were statistically significant differences in maximum tumor diameter ( χ2=13.07, P<0.001; χ2=6.71, P=0.010; χ2=10.56, P=0.001), TNM staging ( χ2=7.42, P=0.006; χ2=6.36, P=0.012; χ2=5.39, P=0.020), lymph node metastasis ( χ2=23.41, P<0.001; χ2=6.52, P=0.011; χ2=13.11, P<0.001), and differentiation degree ( χ2=9.01, P=0.003; χ2=7.97, P=0.005; χ2=15.29, P<0.001) between the gastric cancer patients in the HAMP high level group ( n=44) and the HAMP low level group ( n=48), the SPP1 high level group ( n=43) and the SPP1 low level group ( n=49), and the RGS2 high level group ( n=50) and the RGS2 low level group ( n=42). Compared with the non-recurrence or metastatic group, the recurrence and metastatic group had higher levels of serum HAMP [ (59.26±5.66) ng/ml vs. (48.37±4.28) ng/ml] and SPP1 [ (62.85±6.36) ng/ml vs. (52.11±5.38) ng/ml] level ( t=10.40, P<0.001; t=8.60, P<0.001), and lower level of RGS2 [ (3.01±0.48) mg/L vs. (4.12±0.69) mg/L] ( t=8.19, P<0.001). ROC curve analysis showed that the area under the curve (AUC) values of serum HAMP, SPP1, and RGS2 levels alone for predicting postoperative recurrence or metastasis in gastric cancer patients were 0.777, 0.813, and 0.778, respectively. The AUC value of the combination of the three indicators for predicting postoperative recurrence or metastasis in gastric cancer patients was 0.871. The predictive efficacy of the combination of the three indicators for predicting postoperative recurrence or metastasis in gastric cancer patients was better than that alone ( Z=2.51, P=0.035; Z=2.61, P=0.032; Z=2.71, P=0.029) . Conclusions:The levels of HAMP and SPP1 in the serum of gastric cancer patients increase, while the level of RGS2 decreases, and the levels of the three are related to the maximum tumor diameter, TNM staging, lymph node metastasis and differentiation degree, and their combined detection has higher predictive value for postoperative recurrence or metastasis in gastric cancer patients.

Senile sarcopenia is an age-related geriatric syndrome characterized by a progressive decline in muscle mass, strength, and physical function, posing a significant threat to the health and quality of life of the elderly.In recent years, ultrasound technology has emerged as an important research tool in the evaluation of sarcopenia, owing to its advantages such as safety, convenience, and radiation-free nature.However, challenges remain in achieving parameter standardization, operational consistency, and clinical implementation.This review comprehensively summarizes recent domestic and international research advances in the application of multiparametric ultrasound technology for the diagnosis and evaluation of sarcopenia in the elderly.It also analyzes the practicality, advancements, and limitations of this technology while providing insights into future development trends, aiming to provide clinical research reference basis for the precise diagnosis and intervention strategies of sarcopenia.

Objective:To investigate the predictive efficacy of Delta radiomics for the patholo-gical complete remission (pCR) of pancreatic cancer after total neoadjuvant therapy (TNT).Methods:The retrospective cohort study was conducted. The clinicopathological data of 263 patients with pancreatic cancer who were admitted to Henan Provincial People′s Hospital (Zhengzhou University People's Hspital) from January 2019 to September 2024 were collected. There were 166 males and 97 females, aged (56±12)years. All patients underwent TNT. The 263 patients were randomly divided into a training set of 184 cases and a test set of 79 cases using a 7∶3 random seed count. The training set was used to construct the prediction model, and the test set was used to validate the performance of the prediction model. Observation indicators: (1) postoperative and follow-up condi-tions; (2) imaging feature selection and model construction; (3) evaluation of predictive efficacy of different radiomic models. Comparison of measurement data with normal distribution between groups was conducted using the t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. The Kaplan-Meier method was used to calculate the survival rate and draw survival curve. The Log-rank test was used for survival analysis. The perfor-mance of the prediction model for pCR after TNT was evaluated using the receiver operator charac-teristic (ROC) curve, precision-recall (P-R) curve and Bootstrap method, along with the calculation of area under the curve (AUC), precision rate, recall rate, F1-score. Results:(1) Postoperative and follow-up conditions. All 263 patients underwent surgery after TNT, with pathological examination revealing 124 cases of pCR (86 cases in the training set, 38 cases in the test set) and 139 cases of non-pCR (98 cases in the training set, 41 cases in the test set), respectively. All 263 patients were followed up for 6(range, 3-12) months after surgery, of which 15 cases (4 cases of pCR and 11 cases of non-pCR) were lost to follow-up or died due to non-tumor reasons within 6 months after surgery. The postoperative 6-month recurrence-free survival rate of 124 pCR patients and 139 non-pCR patients were 80% and 50%, respectively, showing a significant difference between the two groups of patients ( χ2=22.84, P<0.05). (2) Imaging feature selection and model construction. Construction of the traditional radiology model: based on the response evaluation criteria in solid tumors 1.1, the Logistic regression model was constructed using the relative shrinkage (D%) as a predictive variable. The AUC of traditional radiology model was 0.72 [95% confidence interval ( CI) as 0.63?0.81] in the training set and 0.75 (95% CI as 0.66?0.84) in the test set, respectively. Construction of the Delta radiomics model: 10 non-zero coefficient features were selected. The Delta radiomics models were constructed by using the regularized Logistic regression, random forest, gradient boosting machine, and support vector machine algorithms through using selected features as input variables. (3) Evaluation of predictive efficacy of different radiomic models. The AUC of Delta radiomics model constructed by regularized Logistic regression algorithm in the test set for predicting pCR in pancreatic cancer after TNT was 0.90, higher than that of the random forest algorithm, gradient boosting machine algorithm, support vector machine algorithm (AUC as 0.81, 0.81, 0.83), and higher than that of the traditional radiology model (AUC as 0.72). Results of Bootstrap method revealed significant differences in the predictive efficacy of Delta radiomics model constructed by regularized Logistic regression algorithm compared to the Delta radiomics model constructed by random forest algorithm, gradient boosting machine algorithm, support vector machine algorithm and the tradi-tional radiology model (95% CI as 0.03?0.16, 0.03?0.16, 0.03?0.13, 0.08?0.29, P<0.05). The regularized Logistic regression algorithm within the Delta radiomics model demonstrated the best overall performance among the above models evaluated. Conclusion:Compared to the traditional radiology model, the Delta radiomics model offers superior efficacy in predicting pCR of pancreatic cancer after TNT, in which the regularized Logistic regression algorithm demonstrates the best overall performance metrics.

Objective:To analyze the factors associated with long-term survival after radical resection of hepatitis B virus(HBV)-associated hepatocellular carcinoma(HCC),and to construct random forest and Cox regression models,to evaluate the two models.Methods:A total of 368 patients with HBV-infected HCC who underwent radical resection were selected retrospectively.These patients were categorized as having a good prognosis(n=266)or a poor prognosis(n=102)based on their survival and mortality status.Univariate and Cox regression analysis were used to identify fac-tors that predict poor prognosis in HCC patients after surgery,and Cox regression and random forest prediction models were constructed and evaluated.Results:There were significant differences in smoking history,Child-Pugh classifica-tion,cirrhosis,microvascular invasion,TNM staging,tumor capsule integrity,platelet-to-lymphocyte ratio(PLR),regular antiviral therapy,HBV-DNA load,alpha-fetoprotein(AFP),neutrophil-to-lymphocyte ratio(NLR),systemic immune in-flammatory index(SII),and albumin-to-globulin ratio(AGR)between the two groups(P<0.05);Cox regression showed that cirrhosis,microvascular invasion,regular antiviral treatment,HBV-DNA load,NLR,PLR,SII,and AGR were related factors that negatively affected the prognosis of patients with HBV-infected HCC after surgery(P<0.05),with an AUC of 0.870 for predicting prognosis;the importance ranking obtained by the random forest model was HBV-DNA load,cirrho-sis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII,with an AUC of 0.926 for predicting prog-nosis;the AUC predicted by the random forest model was greater than that predicted by the Cox regression model(Z=2.411,P=0.016).Conclusion:HBV-DNA load,cirrhosis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII are factors that affect the poor prognosis of patients with HBV-related HCC after surgery.The random for-est prediction model constructed based on these factors has high predictive value and is superior to the Cox regression prediction model.

PURPOSE: This study aims to identify the prevalence and risk factors of military training-related abdominal injuries and help plan and conduct training properly. METHODS: This questionnaire survey study was conducted from October 2021 to May 2022 among military personnel from 6 military units and 8 military medical centers and participants' medical records were consulted to identify the training-related abdominal injuries. All the military personnel who ever participated in military training were included. Those who refused to participate in this study or provided an incomplete questionnaire were excluded. The questionnaire collected demographic information, type of abdominal injury, frequency, training subjects, triggers, treatment, and training disturbance. Chi-square test and t-test were used to compare baseline information. Univariate and multivariate regression analyses were used to explore the risk factors associated with military training-related abdominal injuries. RESULTS: A total of 3058 participants were involved in this study, among which 1797 (58.8%) had suffered training-related abdominal injuries (the mean age was 24.3 years and the service time was 5.6 years), while 1261 (41.2%) had no training-related abdominal injuries (the mean age was 23.1 years and the service time was 4.3 years). There were 546 injured patients (30.4%) suspended the training and 84 (4.6%) needed to be referred to higher-level hospitals. The most common triggers included inadequate warm-up, fatigue, and intense training. The training subjects with the most abdominal injuries were long-distance running (589, 32.8%). Civil servants had the highest rate of abdominal trauma (17.1%). Age ≥ 25 years, military service ≥ 3 years, poor sleep status, and previous abdominal history were independent risk factors for training-related abdominal injury. CONCLUSION More than half of the military personnel have suffered military training-related abdominal injuries. Inadequate warm-up, fatigue, and high training intensity are the most common inducing factors. Scientific and proper training should be conducted according to the factors causing abdominal injuries.
Humans ; Military Personnel ; Risk Factors ; Prevalence ; Male ; Abdominal Injuries/etiology* ; Female ; Adult ; Surveys and Questionnaires ; Young Adult

OBJECTIVES: To evaluate the causal association between circulating levels of zinc, magnesium, and other minerals and autism spectrum disorder (ASD). METHODS: A two-sample Mendelian randomization (MR) analysis was performed using summary statistics from large-scale genome-wide association studies of European populations, including 18 382 ASD cases and 27 969 controls. Genetic data for iron, calcium, and magnesium were obtained from the UK Biobank, and data for zinc and selenium were sourced from an Australian-British cohort. A total of 351 genetic instrumental variables were selected. Causal inference was performed using inverse-variance weighting as the primary analysis method. Sensitivity analyses were performed by Cochran's Q test and MR-PRESSO global test to assess the robustness of the findings. RESULTS: No statistically significant causal effect was observed for circulating zinc, magnesium, calcium, selenium, or iron levels on ASD risk (all P>0.05). The odds ratios and 95% confidence intervals from the inverse-variance weighting analysis were 0.934 (0.869-1.003) for zinc, 1.315 (0.971-1.850) for magnesium, 1.055 (0.960-1.159) for calcium, 1.015 (0.953-1.080) for selenium, and 0.946 (0.687-1.303) for iron. Sensitivity analysis revealed significant heterogeneity in the causal association between circulating calcium and ASD (P=0.006), while the effect estimate remained stable after MR-PRESSO correction (P=0.487). The causal effect estimates for the remaining minerals demonstrated good robustness. CONCLUSIONS This study did not find significant evidence supporting a causal association between circulating zinc, magnesium, calcium, selenium, or iron levels and ASD risk, providing important clues for the etiology of ASD and precision nutritional interventions.
Humans ; Mendelian Randomization Analysis ; Autism Spectrum Disorder/genetics* ; Magnesium/blood* ; Zinc/blood* ; Minerals/blood* ; Genome-Wide Association Study ; Selenium/blood*

Objective:To investigate the predictive efficacy of Delta radiomics for the patholo-gical complete remission (pCR) of pancreatic cancer after total neoadjuvant therapy (TNT).Methods:The retrospective cohort study was conducted. The clinicopathological data of 263 patients with pancreatic cancer who were admitted to Henan Provincial People′s Hospital (Zhengzhou University People's Hspital) from January 2019 to September 2024 were collected. There were 166 males and 97 females, aged (56±12)years. All patients underwent TNT. The 263 patients were randomly divided into a training set of 184 cases and a test set of 79 cases using a 7∶3 random seed count. The training set was used to construct the prediction model, and the test set was used to validate the performance of the prediction model. Observation indicators: (1) postoperative and follow-up condi-tions; (2) imaging feature selection and model construction; (3) evaluation of predictive efficacy of different radiomic models. Comparison of measurement data with normal distribution between groups was conducted using the t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. The Kaplan-Meier method was used to calculate the survival rate and draw survival curve. The Log-rank test was used for survival analysis. The perfor-mance of the prediction model for pCR after TNT was evaluated using the receiver operator charac-teristic (ROC) curve, precision-recall (P-R) curve and Bootstrap method, along with the calculation of area under the curve (AUC), precision rate, recall rate, F1-score. Results:(1) Postoperative and follow-up conditions. All 263 patients underwent surgery after TNT, with pathological examination revealing 124 cases of pCR (86 cases in the training set, 38 cases in the test set) and 139 cases of non-pCR (98 cases in the training set, 41 cases in the test set), respectively. All 263 patients were followed up for 6(range, 3-12) months after surgery, of which 15 cases (4 cases of pCR and 11 cases of non-pCR) were lost to follow-up or died due to non-tumor reasons within 6 months after surgery. The postoperative 6-month recurrence-free survival rate of 124 pCR patients and 139 non-pCR patients were 80% and 50%, respectively, showing a significant difference between the two groups of patients ( χ2=22.84, P<0.05). (2) Imaging feature selection and model construction. Construction of the traditional radiology model: based on the response evaluation criteria in solid tumors 1.1, the Logistic regression model was constructed using the relative shrinkage (D%) as a predictive variable. The AUC of traditional radiology model was 0.72 [95% confidence interval ( CI) as 0.63?0.81] in the training set and 0.75 (95% CI as 0.66?0.84) in the test set, respectively. Construction of the Delta radiomics model: 10 non-zero coefficient features were selected. The Delta radiomics models were constructed by using the regularized Logistic regression, random forest, gradient boosting machine, and support vector machine algorithms through using selected features as input variables. (3) Evaluation of predictive efficacy of different radiomic models. The AUC of Delta radiomics model constructed by regularized Logistic regression algorithm in the test set for predicting pCR in pancreatic cancer after TNT was 0.90, higher than that of the random forest algorithm, gradient boosting machine algorithm, support vector machine algorithm (AUC as 0.81, 0.81, 0.83), and higher than that of the traditional radiology model (AUC as 0.72). Results of Bootstrap method revealed significant differences in the predictive efficacy of Delta radiomics model constructed by regularized Logistic regression algorithm compared to the Delta radiomics model constructed by random forest algorithm, gradient boosting machine algorithm, support vector machine algorithm and the tradi-tional radiology model (95% CI as 0.03?0.16, 0.03?0.16, 0.03?0.13, 0.08?0.29, P<0.05). The regularized Logistic regression algorithm within the Delta radiomics model demonstrated the best overall performance among the above models evaluated. Conclusion:Compared to the traditional radiology model, the Delta radiomics model offers superior efficacy in predicting pCR of pancreatic cancer after TNT, in which the regularized Logistic regression algorithm demonstrates the best overall performance metrics.

Objective:To analyze the factors associated with long-term survival after radical resection of hepatitis B virus(HBV)-associated hepatocellular carcinoma(HCC),and to construct random forest and Cox regression models,to evaluate the two models.Methods:A total of 368 patients with HBV-infected HCC who underwent radical resection were selected retrospectively.These patients were categorized as having a good prognosis(n=266)or a poor prognosis(n=102)based on their survival and mortality status.Univariate and Cox regression analysis were used to identify fac-tors that predict poor prognosis in HCC patients after surgery,and Cox regression and random forest prediction models were constructed and evaluated.Results:There were significant differences in smoking history,Child-Pugh classifica-tion,cirrhosis,microvascular invasion,TNM staging,tumor capsule integrity,platelet-to-lymphocyte ratio(PLR),regular antiviral therapy,HBV-DNA load,alpha-fetoprotein(AFP),neutrophil-to-lymphocyte ratio(NLR),systemic immune in-flammatory index(SII),and albumin-to-globulin ratio(AGR)between the two groups(P<0.05);Cox regression showed that cirrhosis,microvascular invasion,regular antiviral treatment,HBV-DNA load,NLR,PLR,SII,and AGR were related factors that negatively affected the prognosis of patients with HBV-infected HCC after surgery(P<0.05),with an AUC of 0.870 for predicting prognosis;the importance ranking obtained by the random forest model was HBV-DNA load,cirrho-sis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII,with an AUC of 0.926 for predicting prog-nosis;the AUC predicted by the random forest model was greater than that predicted by the Cox regression model(Z=2.411,P=0.016).Conclusion:HBV-DNA load,cirrhosis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII are factors that affect the poor prognosis of patients with HBV-related HCC after surgery.The random for-est prediction model constructed based on these factors has high predictive value and is superior to the Cox regression prediction model.