Objective: To investigate the identification process of a case with anti-Fy combined with Rh blood group system antibodies and to review the transfusion strategy and epidemiological characteristics of Duffy blood group system antibodies. Methods: The antibody specificity of a patient diagnosed with liver cirrhosis, who exhibited unexpected antibodies, was determined using the microcolumn gel method, enzyme method, and elution test. A retrospective analysis was performed to assess the incidence and clinical characteristics of antibodies associated with the Duffy blood group system among a cohort of 652 003 patients treated at our hospital from 2014 to 2024. Results: The patient's serum contained anti-Fy , anti-c, and anti-E antibodies. Through the targeted recruitment of African international students, the patient successfully received four units of Fy -negative blood that matched the ABO and Rh phenotypes. Between 2014 and 2024, the incidence of Duffy blood group system antibodies was 0.005 7% (37 out of 652 003), with 9 cases (24.3%) combined with Rh antibodies. Conclusion: Patients with anti-Fy combined with Rh antibodies require Fy -negative blood with matched Rh phenotypes. Targeted recruitment based on racial antigen differences can effectively resolve rare blood type transfusion challenges.

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.

Synovium is the target organ of rheumatoid arthritis.The excessive proliferation of synovial cells and insufficient apoptosis lead to synovial hyperplasia,which in turn causes damage to the surrounding tissues of the joint and bone destruction."Yang transforming qi and yin forming elements"is derived from Su Wen and is a highly summarized description of the functions of yin and yang,which runs through the entire course of the disease.This article elucidated the theoretical connotation of"yang transforming qi and yin forming elements"and its connection with synovial hyperplasia,proposing that the insufficiency of"yang transforming qi"is the root of synovial hyperplasia,while the excess of"yin forming elements"is the manifestation of synovial hyperplasia.Based on this,it put forward that"assisting yang qi as the priority,and according to the bias of pathogenic factors of yin,supplementing the method of reducing yin forming elements"is an important principle for treating this disease,which could provide new ideas for the treatment of the disease.

Synovium is the target organ of rheumatoid arthritis.The excessive proliferation of synovial cells and insufficient apoptosis lead to synovial hyperplasia,which in turn causes damage to the surrounding tissues of the joint and bone destruction."Yang transforming qi and yin forming elements"is derived from Su Wen and is a highly summarized description of the functions of yin and yang,which runs through the entire course of the disease.This article elucidated the theoretical connotation of"yang transforming qi and yin forming elements"and its connection with synovial hyperplasia,proposing that the insufficiency of"yang transforming qi"is the root of synovial hyperplasia,while the excess of"yin forming elements"is the manifestation of synovial hyperplasia.Based on this,it put forward that"assisting yang qi as the priority,and according to the bias of pathogenic factors of yin,supplementing the method of reducing yin forming elements"is an important principle for treating this disease,which could provide new ideas for the treatment of the disease.

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 Based on the multi-software visual analysis of the literature on the effect of Janus kinase(JAK)/signal transducer and activator of transcription(STAT)signaling pathway on rheumatoid arthritis in the past decade,the development trend and research hotspot in this field are summarized.To provide researchers with new directions and ideas to promote the innovative development of the field.Methods The literatures related to JAK/STAT signaling pathway in rheumatoid arthritis were collected from the Web of Science Core Collection database from 2013 to 2023.CiteSpace and VOSviewer software were used to analyze the number of publications,countries,authors and keywords of 354 articles retrieved.Results The number of published papers in this field continues to increase.According to the author's research direction,the presentation of high-frequency words,and the attention to the preface and hot topics,it is suggested that this field focuses on gene expression,immune mechanism,inflammatory mechanism,pathway inhibitors,drug therapy,etc.Future research will focus on the safety,mechanism and controlled trials of pathway inhibitors and antirheumatic drugs.Conclusion The effect of JAK/STAT signaling pathway on rheumatoid arthritis has attracted much attention in the past,present and future.There are differences in the research of different teams in this field,and the regional development is unbalanced,suggesting that we should strengthen cooperation and exchanges,focus on the international frontier,and carry out more high-quality research to promote the development and progress of this field,and provide clinical basis.

Objective: To explore the epidemic characteristics of injury related deaths in children and adolescents aged 1-24 years old in China from 2010 to 2020, so as to provide a basis for the formulation of policies and measures related to the control of injuries and deaths among children and adolescents. Methods: The data were sourced from the China Death Cause Monitoring Dataset from 2010 to 2020. Annual percentage change (APC) and average annual percentage change (AAPC) of injury deaths in China in this age group during the period 2010 to 2020 were analyzed by Join point regression. Results: From 2010 to 2020, the standardized death rate of injury showed a decreasing trend (AAPC=-6.90%, t =4.58, P <0.01). The standardized death rates of male and rural injuries showed an overall downward trend, with AAPC rates of -8.37% and -7.79%( t =11.87, 10.34, P <0.01). An increasing trend was observed in the 20-24 year-old age group during 2010-2018 (APC=18.11%, t =6.50, P <0.01). The death rate from injuries was higher in males than females, and higher in rural areas compared with urban areas ( χ 2=16 483.64, 3 268.65 , P <0.01). A downward trend was observed in accidental falls and suicide, the overall standardized mortality rate of traffic accidents, accidental poisoning, fire, drowning, homicide and other injuries (AAPC=-10.22%, -6.21%, -7.50%, -7.94%, -9.01% , -10.97%, t =16.23, 7.29, 2.53, 9.32, 7.88, 4.58, P <0.05). Conclusion From 2010 to 2020, the overall injury standardized mortality rate in the 1-24 year-old age group shows a decreasing trend, but it remains at a relatively high level. Prevention efforts should be continuously strengthened, especially for urban areas, and should focus on women and those aged 20-24 years old, as well as accidental falls and suicide prevention.

Background::The dermoscopic features of rosacea have already been reported. However, the current findings are incomplete, and little is known about phymatous rosacea. Hence, this study aimed to summarize and compare the dermoscopic features and patterns of three rosacea subtypes (erythematotelangiectatic [ETR], papulopustular [PPR], and phymatous [PHR]) in the Chinese Han population and to evaluate whether these features differ with patients’ genders, ages, and durations.Methods::Dermoscopic images of 87 rosacea patients were collected in non-polarized and polarized dermoscopy contact modes at 20-fold magnification. Dermoscopic features, including vessels, scales, follicular findings, and other structures, were summarized and evaluated.Results::The reticular linear vessels and red diffuse structureless areas of ETR were distinctive. For PPR, red diffuse structureless areas, reticular linear vessels, yellow scales, follicular plugs, and follicular pustules were typical dermoscopic criteria. The common dermoscopic features of PHR were: orange diffuse structureless areas, linear vessels with branches, perifollicular white color, orange focal structureless areas, and white lines. The following features statistically differed among the three rosacea subtypes: reticular linear vessels ( P < 0.001), unspecific linear vessels ( P= 0.005), linear vessels with branches ( P < 0.001), yellow scales ( P = 0.001), follicular plugs ( P < 0.001), perifollicular white color ( P < 0.001), red diffuse structureless areas ( P = 0.022), orange diffuse structureless areas ( P < 0.001), red focal structureless areas ( P = 0.002), orange focal structureless areas ( P = 0.003), white lines ( P < 0.001), follicular pustules ( P < 0.001), and black vellus hairs ( P < 0.001). Conclusions::The dermoscopic patterns of ETR are red diffuse structureless areas and reticular linear vessels. For PPR, the pattern comprehends combinations of red diffuse structureless areas, reticular linear vessels, yellow scales, follicular plugs, and follicular pustules. Meanwhile, PHR is characterized by remarkable orange diffuse structureless areas, linear vessels with branches, perifollicular white color, orange focal structureless areas, and white lines.

Objective    To introduce a new type thoracic vest designed according to the incision characteristics of female patients undergoing totally thoracoscopic cardiac surgery. Methods    Sixty-one female patients undergoing totally thoracoscopic cardiac surgery from February 2019 to May 2020 in our department were enrolled. All female patients had hypermastia and (or) mastoptosis which covered the incision. They were randomly divided into a research group (group A, n=32) and a control group (group B, n=29). The group A used the new type thoracic vest, while the group B used the traditional single shoulder belt. The degree of satisfaction, visual analogue scale (VAS) score 24 hours after the thoracic drainage tube removed, the average time-consuming of dressing change, dressing frequency and the incision infection rate were compared between two groups. Results    The degree of satisfaction in the group A was higher than that of the group B (P<0.001). The VAS scores of pain, average time-consuming of dressing change and dressing frequency in the group A were less or lower than those of the group B (P<0.001). There was no statistical difference in the incision infection rate between the two groups (P=0.214), but incision infection rate of the group A was lower than that of the group B. Conclusion    The new type thoracic vest seems to be more beneficial for patients than traditional single shoulder belt. It is easy to use, increases the psychological satisfaction of patients, reduces the pain and the incision infection and improves work efficiency, which is worthy of clinical application.

Objective:To explore the relationship between microRNA-4429 (miR-4429) derived from serum exosomes and prognosis of radical radiation and chemotherapy for non-small cell lung cancer (NSCLC).Methods:309 blood samples of NSCLC patients were collected [before chemotherapy (T0), after 1 cycle of chemotherapy (T1) and after 2 cycles of chemotherapy (T2), 103 cases at each time point], and the expression level of miR-4429 was detected by real-time fluorescent quantitative PCR method, and the relationship between it and the prognosis of radical radiation and chemotherapy in NSCLC was analyzed.Results:The 1-year, 2-year and 3-year survival rates of 103 NSCLC patients were 69.90%, 45.63% and 34.95%, respectively. The expression levels of T1-miR-4429 and T2-miR-4429 in the survival group were 0.66±0.14 and 0.77±0.11, respectively, which were higher than T1-miR-4429 (0.60±0.06) and T2-miR-4429 (0.62±0.11) in the death group, and the differences were statistically significant ( t=2.269, 6.997, P<0.05). Restricted cubic spline fitting COX regression analysis showed that T2-miR-4429 had a linear relationship with survival in NSCLC. COX regression analysis showed that TNM staging was an independent risk factor for the survival and prognosis in NSCLC ( P<0.05), and the degree of differentiation, targeted therapy and T2-miR-4429 were all independent protective factors for the survival and prognosis in NSCLC ( P<0.05). The calibration curve of the nomogram regression model constructed by TNM stage, degree of differentiation, targeted therapy and T2-miR-4429 coincided well with the ideal curve, and the C-index was 0.713. Conclusions:The high expression level of T2-miR-4429 indicates that NSCLC patients have a low risk of poor survival prognosis. The nomogram regression model constructed by TNM staging, degree of differentiation, targeted therapy and T2-miR-4429 has a certain degree of discrimination and accuracy, which can assist in evaluating the prognosis of NSCLC.