Objective: To investigate the characteristics of allele frequencies for 9 red blood cell (RBC) blood group systems in the Hui ethnic voluntary blood donor population of Suzhou using real-time fluorescence PCR technology, so as to provide technical support for establishing a RBC blood group genetic database. Methods: PCR-TaqMan technology was employed to perform genotyping detection for 9 RBC blood group systems using 144 samples from Hui voluntary blood donors in Suzhou, collected between October 2023 and August 2024. Results: Blood group allele frequencies among Suzhou Hui voluntary blood donors were distributed as follows: MNS system (M=0.566 0, N=0.434 0; S=0.079 9, s=0.920 1); Lutheran system (Lu =0.003 5, Lu =0.996 5; Au =0.895 8, Au =0.104 2); Kell system (K=0.000 0, k=1.000 0; Kp =0.003 5, Kp =0.996 5; JS =0.000 0, JS =1.000 0); Duffy system (Fy =0.899 3, Fy =0.100 7); Kidd system (JK =0.451 4, JK =0.548 6); Diego system (Di =0.041 7, Di =0.958 3); Yt system (Yt =0.996 5, Yt =0.003 5); Dombrock system (Do =0.128 5, Do =0.871 5); Colton system (Co =1.000 0, Co =0.000 0). The PCR-TaqMan-based RBC blood group genotyping technology successfully completed testing for all samples. Conclusion: The MNS, Lutheran, Duffy, Kidd, Diego, and Dombrock blood group systems in the Suzhou Hui population exhibited polymorphic distribution patterns, whereas the Colton system was monomorphic. Standardized application of PCR-TaqMan technology facilitates the establishment of an RBC blood group genetic database.

Objective:To explore the external treatment methods of hemorrhoids based on ancient books and documents; To guide clinical medication.Methods:The relevant articles on external treatment of hemorrhoids using Chinese materia medica included in Zhong Hua Yi Dian (5th edition) were retrieved. Excel 2021 was used to analyze the properties, tastes, meridian tropism, external treatment methods and drug efficacy of Chinese materia medica included in the prescriptions, and the relevant discussion contents were sorted out according to the classification of external treatment methods of hemorrhoids. Results:A total of 255 articles in ancient books were included, involving 165 prescriptions. 146 kinds of Chinese materia medica for external treatment of hemorrhoids were selected. The medicinal properties were mainly cold and warm, the main tastes were pungent, bitter and sweet, and the meridian tropism mainly involved the liver, spleen, stomach, heart, lung and large intestine meridians. Fumigation, application and application are the most widely used external treatment methods. Chinese materia medica efficacy mainly includes heat clearing drugs, surface relieving drugs, resuscitation drugs, astringent drugs, anti venom, anti insect and anti itching drugs, and tonic drugs.Conclusions:Ancient physicians treated hemorrhoids with both cold and heat, and paid equal attention to clearing heat and reducing fire, warming and activating blood circulation. They paid attention to the combination of local medication of lesions and the overall treatment of multiple meridians and multiple viscera, so as to achieve the simultaneous treatment of specimens. The treatment methods were rich, including fumigation and washing method to improve local microcirculation, application method using natural adhesive, coating method focusing on precise administration and ligation method of minimally invasive, forming a unique external treatment system, which can be used for modern clinical reference.

As a novel form of cell death, ferroptosis is mainly regulated by the accumulation of soluble iron ions in the cytoplasm and the production of lipid peroxides and is closely associated with several diseases, including acute kidney injury, ischemic reperfusion injury, neurodegenerative diseases, and cancer. The term "immunosuppression" refers to various factors that can directly harm immune cells' structure and function and affect the synthesis, release, and biological activity of immune molecules, leading to the insufficient response of the immune system to antigen production, failure to successfully resist the invasion of foreign pathogens, and even organ damage and metabolic disorders. An immunosuppressive phase commonly occurs in the progression of many ferroptosis-related diseases, and ferroptosis can directly inhibit immune cell function. However, the relationship between ferroptosis and immunosuppression has not yet been published due to their complicated interactions in various diseases. Therefore, this review deeply discusses the contribution of ferroptosis to immunosuppression in specific cases. In addition to offering new therapeutic targets for ferroptosis-related diseases, the findings will help clarify the issues on how ferroptosis contributes to immunosuppression.
Ferroptosis/immunology* ; Humans ; Immune Tolerance/immunology* ; Animals ; Immunosuppression Therapy ; Iron/metabolism* ; Neoplasms/immunology*

Objective To construct a model for predicting ki-67 expression in hepatocellular carcinoma using the intratumoral and peritumoral radiomic features of contrast enhanced magnetic resonance imaging(CEMRI)in the arterial phase as well as clinical imaging features.Methods A total of 120 patients pathologically diagnosed with hepatocellular carcinoma(HCC)from January 2016 to December 2024 in No.910 Hospital of the Joint Logis-tics Support Force of the Chinese People's Liberation Army were retrospectively enrolled and randomly divided into a training set(84 cases)and a test set(36 cases)in a ratio of 7∶3.ITK-SNAP software was used to delineate the global region of interest(ROI)of HCC on the arterial phase MR images.The ROIs of all patients were automatically expanded outward by 2 mm,and then the intratumoral ROI areas were eliminated to obtain the peritumoral ROI.With the help of PyRadiomics software,1 198 intratumoral and peritumoral radiomic features were extracted.Spearman correlation analysis,maximum relevance-minimum redundancy(mRMR),and least absolute shrinkage and selection operator(LASSO)regression were used to reduce the data dimension and select the best features.Then,a radiomics model of the logistic regression(LR)machine learning algorithm was constructed.A combined model including clinical imaging features and radiomics features was established.The area under the curve(AUC),accuracy,sensitivity,specificity,positive predictive value(PPV),negative predictive value(NPV),calibration curve and decision curve analysis(DCA)were used to evaluate the efficacy of the intratumoral and peritumoral radiomics features combined with clinical imaging features model in predicting ki-67 expression in hepatocellular car-cinoma.Results The intratumor model exhibited an efficacy in predicting the expression of ki-67 in hepatocellular carcinoma with AUC values of 0.817 and 0.787 in the training set and test set,respectively.The peritumoral model showed an efficacy with AUC values of 0.805 and 0.633 in the training set and test set,respectively.The intratumoral and peritumoral model demonstrated AUC values of 0.874 and 0.836 in the training set and test set,respectively.The combined model constructed by integrating the intratumoral and peritumoral model with clinical imaging features yielded AUC values of 0.877 and 0.849 in the training set and test set,respectively,indicating clinical imaging features improved the performance of the model.DCA showed that the combined models all had good clinical benefits,with the intratumoral and peritumoral model performing the best.Conclusion The intratumoral and peritumoral radiomics model based on CEMRI arterial phase combined with clinical imaging data can accurately predict the expression of ki-67 in hepatocellular carcinoma.This combined model yields the best clinical benefit.

Objective:To analyze differences in the expression of routine laboratory parameters and cerebrospinal fluid (CSF) examination indicators between patients with non-neurosyphilis (syphilis without nervous system involvement) and those with neurosyphilis, to screen for key predictive factors, and to construct a predictive model for neurosyphilis.Methods:A retrospective analysis was conducted on the clinical data from patients with syphilis at the Fifth People's Hospital of Suzhou from 2019 to 2024. Patients with neurosyphilis and non-neurosyphilis who were hospitalized from November 2019 to June 2022 were included in the model cohort, and those hospitalized from January 2024 to October 2024 were included in the validation cohort. The patients' basic information and laboratory test indicators (including routine blood tests, CSF biochemical analysis, and syphilitic antibody tests) were collected. Statistical analysis was performed using the GraphPad software. The receiver operating characteristic (ROC) curve and the binary logistic regression method were used to analyze the predictive performance of key indicators in patients from the model cohort with SPSS software, and a predictive model for neurosyphilis was constructed. The performance of the neurosyphilis predictive model for neurosyphilis was validated based on relevant indicators from the validation cohort.Results:The model cohort included 99 patients with non-neurosyphilis (including 49 males and 50 females), and they were aged between 19 and 85 years, with an average age of 47 years; 69 patients with neurosyphilis were also included in the model cohort, including 58 males and 11 females, and they were aged between 26 and 73 years, with an average age of 51 years. The neurosyphilis group showed a significant increase in the median levels of CSF adenosine deaminase (1 U/L) and microprotein (711 mg/L), white blood cell counts (0.009 × 10?/L), as well as in the proportion of positive Pandy tests (35/69, 50.7%) compared with the non-neurosyphilis group (0 U/L, 309 mg/L, 0.002 × 10?/L, 2 /99 [2.0%], respectively, all P < 0.001). Based on the ROC curve analysis, the CSF microprotein and white blood cell count had relatively high discriminative ability (area under the ROC curve [AUC] > 0.85), while adenosine deaminase and the Pandy test showed moderate discriminative ability (0.7 < AUC < 0.85). According to the above four indicators, the logistic regression analysis showed that CSF microprotein combined with CSF white blood cell counts could construct the best predictive model for neurosyphilis, with a prediction accuracy rate of 0.980, a sensitivity of 98.5%, and a specificity of 89.9%. The prediction formula was logit (p) = -9.926 + 0.015 × microprotein + 362.33 × CSF white blood cell count, with a cutoff value of ≥ -0.867. The validation cohort enrolled 72 patients with non-neurosyphilis and 51 with neurosyphilis, and there were significant differences in CSF microprotein levels and white blood cell counts between the two groups (both P < 0.001). In the validation cohort, the predictive model demonstrated an accuracy of 86.2%, with a sensitivity of 83.6% and a specificity of 91.1% for predicting neurosyphilis. Conclusion:The predictive model for neurosyphilis constructed by combining CSF microprotein and CSF white blood cell count may contribute to the early differential diagnosis of neurosyphilis.

Objective:To analyze differences in the expression of routine laboratory parameters and cerebrospinal fluid (CSF) examination indicators between patients with non-neurosyphilis (syphilis without nervous system involvement) and those with neurosyphilis, to screen for key predictive factors, and to construct a predictive model for neurosyphilis.Methods:A retrospective analysis was conducted on the clinical data from patients with syphilis at the Fifth People's Hospital of Suzhou from 2019 to 2024. Patients with neurosyphilis and non-neurosyphilis who were hospitalized from November 2019 to June 2022 were included in the model cohort, and those hospitalized from January 2024 to October 2024 were included in the validation cohort. The patients' basic information and laboratory test indicators (including routine blood tests, CSF biochemical analysis, and syphilitic antibody tests) were collected. Statistical analysis was performed using the GraphPad software. The receiver operating characteristic (ROC) curve and the binary logistic regression method were used to analyze the predictive performance of key indicators in patients from the model cohort with SPSS software, and a predictive model for neurosyphilis was constructed. The performance of the neurosyphilis predictive model for neurosyphilis was validated based on relevant indicators from the validation cohort.Results:The model cohort included 99 patients with non-neurosyphilis (including 49 males and 50 females), and they were aged between 19 and 85 years, with an average age of 47 years; 69 patients with neurosyphilis were also included in the model cohort, including 58 males and 11 females, and they were aged between 26 and 73 years, with an average age of 51 years. The neurosyphilis group showed a significant increase in the median levels of CSF adenosine deaminase (1 U/L) and microprotein (711 mg/L), white blood cell counts (0.009 × 10?/L), as well as in the proportion of positive Pandy tests (35/69, 50.7%) compared with the non-neurosyphilis group (0 U/L, 309 mg/L, 0.002 × 10?/L, 2 /99 [2.0%], respectively, all P < 0.001). Based on the ROC curve analysis, the CSF microprotein and white blood cell count had relatively high discriminative ability (area under the ROC curve [AUC] > 0.85), while adenosine deaminase and the Pandy test showed moderate discriminative ability (0.7 < AUC < 0.85). According to the above four indicators, the logistic regression analysis showed that CSF microprotein combined with CSF white blood cell counts could construct the best predictive model for neurosyphilis, with a prediction accuracy rate of 0.980, a sensitivity of 98.5%, and a specificity of 89.9%. The prediction formula was logit (p) = -9.926 + 0.015 × microprotein + 362.33 × CSF white blood cell count, with a cutoff value of ≥ -0.867. The validation cohort enrolled 72 patients with non-neurosyphilis and 51 with neurosyphilis, and there were significant differences in CSF microprotein levels and white blood cell counts between the two groups (both P < 0.001). In the validation cohort, the predictive model demonstrated an accuracy of 86.2%, with a sensitivity of 83.6% and a specificity of 91.1% for predicting neurosyphilis. Conclusion:The predictive model for neurosyphilis constructed by combining CSF microprotein and CSF white blood cell count may contribute to the early differential diagnosis of neurosyphilis.

Objective To construct a model for predicting ki-67 expression in hepatocellular carcinoma using the intratumoral and peritumoral radiomic features of contrast enhanced magnetic resonance imaging(CEMRI)in the arterial phase as well as clinical imaging features.Methods A total of 120 patients pathologically diagnosed with hepatocellular carcinoma(HCC)from January 2016 to December 2024 in No.910 Hospital of the Joint Logis-tics Support Force of the Chinese People's Liberation Army were retrospectively enrolled and randomly divided into a training set(84 cases)and a test set(36 cases)in a ratio of 7∶3.ITK-SNAP software was used to delineate the global region of interest(ROI)of HCC on the arterial phase MR images.The ROIs of all patients were automatically expanded outward by 2 mm,and then the intratumoral ROI areas were eliminated to obtain the peritumoral ROI.With the help of PyRadiomics software,1 198 intratumoral and peritumoral radiomic features were extracted.Spearman correlation analysis,maximum relevance-minimum redundancy(mRMR),and least absolute shrinkage and selection operator(LASSO)regression were used to reduce the data dimension and select the best features.Then,a radiomics model of the logistic regression(LR)machine learning algorithm was constructed.A combined model including clinical imaging features and radiomics features was established.The area under the curve(AUC),accuracy,sensitivity,specificity,positive predictive value(PPV),negative predictive value(NPV),calibration curve and decision curve analysis(DCA)were used to evaluate the efficacy of the intratumoral and peritumoral radiomics features combined with clinical imaging features model in predicting ki-67 expression in hepatocellular car-cinoma.Results The intratumor model exhibited an efficacy in predicting the expression of ki-67 in hepatocellular carcinoma with AUC values of 0.817 and 0.787 in the training set and test set,respectively.The peritumoral model showed an efficacy with AUC values of 0.805 and 0.633 in the training set and test set,respectively.The intratumoral and peritumoral model demonstrated AUC values of 0.874 and 0.836 in the training set and test set,respectively.The combined model constructed by integrating the intratumoral and peritumoral model with clinical imaging features yielded AUC values of 0.877 and 0.849 in the training set and test set,respectively,indicating clinical imaging features improved the performance of the model.DCA showed that the combined models all had good clinical benefits,with the intratumoral and peritumoral model performing the best.Conclusion The intratumoral and peritumoral radiomics model based on CEMRI arterial phase combined with clinical imaging data can accurately predict the expression of ki-67 in hepatocellular carcinoma.This combined model yields the best clinical benefit.

Here, we report a previously unrecognized syndromic neurodevelopmental disorder associated with biallelic loss-of-function variants in the RBM42 gene. The patient is a 2-year-old female with severe central nervous system (CNS) abnormalities, hypotonia, hearing loss, congenital heart defects, and dysmorphic facial features. Familial whole-exome sequencing (WES) reveals that the patient has two compound heterozygous variants, c.304C>T (p.R102*) and c.1312G>A (p.A438T), in the RBM42 gene which encodes an integral component of splicing complex in the RNA-binding motif protein family. The p.A438T variant is in the RRM domain which impairs RBM42 protein stability in vivo. Additionally, p.A438T disrupts the interaction of RBM42 with hnRNP K, which is the causative gene for Au-Kline syndrome with overlapping disease characteristics seen in the index patient. The human R102* or A438T mutant protein failed to fully rescue the growth defects of RBM42 ortholog knockout ΔFgRbp1 in Fusarium while it was rescued by the wild-type (WT) human RBM42. A mouse model carrying Rbm42 compound heterozygous variants, c.280C>T (p.Q94*) and c.1306_1308delinsACA (p.A436T), demonstrated gross fetal developmental defects and most of the double mutant animals died by E13.5. RNA-seq data confirmed that Rbm42 was involved in neurological and myocardial functions with an essential role in alternative splicing (AS). Overall, we present clinical, genetic, and functional data to demonstrate that defects in RBM42 constitute the underlying etiology of a new neurodevelopmental disease which links the dysregulation of global AS to abnormal embryonic development.
Female ; Animals ; Mice ; Humans ; Child, Preschool ; Intellectual Disability/genetics* ; Heart Defects, Congenital/genetics* ; Facies ; Cleft Palate ; Muscle Hypotonia

Objective:To translate and culturally adjust Decisional Fatigue Scale (DFS) , and test its reliability and validity.Methods:The Chinese version of DFS was formed through the method of double translation, back translation and expert consultation. Using the convenient sampling method, 247 medical staffs from 16 departments in 76 wards of Xiangyang No.1 People's Hospital Affiliated to Hubei University of Medicine were selected as the research objects. Content validity, criterion validity and structure validity were used for validity evaluation, and internal consistency reliability, split half reliability and retest reliability were used for reliability evaluation. A total of 247 questionnaires were sent out in this study and 247 were effectively received, with effective recovery of 100.00%.Results:The total Cronbach's α coefficient of Chinese DFS was 0.933, the half-reliability coefficient was 0.849 and the retest reliability coefficient was 0.838 ( P<0.01) . Both the item content validity index and scale content validity index were 1.00, and the correlation coefficient with the total score of SRF-S was 0.729 ( P<0.01) . One common factor was extracted by exploratory factor analysis and 65.64% of the variation was explained cumulatively, which was consistent with the dimensions of the original scale. Confirmatory factor analysis showed that all fitting indexes were up to standard and the fitting degree was good. Conclusions:The reliability and validity of the Chinese version of DFS in medical staffs is good, which can be used to evaluate the degree of decision-making fatigue of Chinese medical staffs.

Objective:To investigate the value of pulse oxygen saturation (SpO 2) monitoring in predicting children with moderate-to-severe obstructive sleep apnea (OSA). Methods:It was a retrospective study involving 341 children with snoring during nighttime sleep who had visited the Children′s Hospital of Soochow University from June 2017 to November 2020 and monitored for polysomnography (PSG) and SpO 2.The SpO 2 parameters mainly included oxygen desaturation index (ODI), oxygen desaturation index ≥3% (ODI3), oxygen desaturation index ≥4% (ODI4), mean pulse blood oxygen saturation (MSpO 2), lowest pulse blood oxygen saturation (LSpO 2), cumulative time spent with blood oxygen saturation below 95%, 92% and 90%(T95, T92 and T90). According to obstructive sleep apnea hypopnea index (OAHI), patients were divided into the snoring and mild OSA group (OAHI≤5 times/h) and moderate-to-severe OSA group (OAHI>5 times/h). Differences in SpO 2 parameters were compared between groups using the Chi- square test and Mann- Whitney U test. Spearman correlation analysis was used to analyze the correlation between SpO 2 parameters and OAHI in all children.The SpO 2 parameters were included in the Logistic regression model.Receiver operating characteristic (ROC) curve was used to analyze the diagnostic efficiency of SpO 2 parameters on moderate-to-severe OSA. Results:A total of 341 patients were recruited, including 206 male and 135 female patients with the mean age, body mass index (BMI) and OAHI of 6.0 (4.0, 7.5) years, 16.2 (15.1, 18.0) kg/m 2 and 0.6 (0.1, 3.0) times /h, respectively.There were 283(83.0%) and 58 (17.0%) patients in the snoring and mild OSA group and moderate-to-severe OSA group.The ODI3[0.7 (0.3, 1.4) times/h vs.7.7 (4.4, 12.8) times/h], ODI4[0.4 (0.1, 0.8) times/h vs.5.3 (2.7, 9.1) times/h], T95[1.4 (0.3, 5.3) min vs.13.7 (7.0, 33.5) min], T92[0.1 (0, 0.5) min vs.1.8 (0.9, 6.0) min] and T90[0 (0, 0.1) min vs.0.6 (0.2, 2.2) min] were significantly lower in the snoring and mild OSA group than those of moderate-to-severe group, while LSpO 2[91.0 (89.0, 93.0)% vs.86.5 (82.0, 88.0)%] and MSpO 2[ 97.0 (97.0, 98.0)% vs.96.0 (96.0, 97.0)%] were significantly higher(all P<0.001). All SpO 2 parameters were significantly correlated with OAHI (all P<0.001), and the correlation coefficient between ODI3 and OAHI was 0.660.ODI3 was an independent predictor of moderate-to-severe OSA ( OR=3.117, 95% CI: 1.635-5.945, P=0.001). The area under the ROC curve of ODI3 in predicting the moderate-to-severe OSA was 0.957, and the cut-off value of 3.45 times/h and specificity of 95.4%.MSpO 2 was an independent predictor of moderate-to-severe OSA ( OR=2.917, 95% CI: 1.589-5.354, P=0.001). Conclusions:ODI3 can be used to predict the moderate-to-severe OSA in children.