Congenital blood group chimerism refers to the coexistence of two or more distinct blood types within an individual, resulting from the presence of hematopoietic cell populations with different genotypes. Consequently, red blood cells in such individuals may express different blood group antigens. Based on the timing and mechanism of formation, blood group chimerism can be classified as either congenital or acquired. Although congenital blood group chimerism is rare and involves complex mechanisms, it holds significant implications in transfusion medicine, transplantation, and obstetrics. This article reviews the formation mechanisms, detection methods, and clinical significance of congenital blood group chimerism in transfusion medicine. Particular emphasis is placed on the principles, advantages, and limitations of various detection techniques. Furthermore, the potential applications of these technologies in clinical diagnosis are discussed, providing a technical foundation for the development of precise transfusion strategies.

OBJECTIVE To evaluate the cost-effectiveness of cefiderocol versus best available therapy （BAT） or standard-of- care （SOC） for the treatment of confirmed or suspected carbapenem-resistant Gram-negative bacterial （CRGNB） serious infections from the perspective of the Chinese healthcare system， and to explore its reasonable pricing. METHODS A decision tree model was constructed based on data from two phase Ⅲ clinical trials （CREDIBLE-CR and GAME CHANGER） to simulate the cost- effectiveness of cefiderocol in two scenarios： salvage therapy for confirmed CRGNB infection （scenario 1） and empirical therapy for suspected CRGNB infection （scenario 2）. The primary outcome measure was the incremental cost-effectiveness ratio （ICER）. The willingness-to-pay （WTP） was set at 1 to 3 times China’s per capita GDP in 2024. To verify the robustness of the results， one- way and probabilistic sensitivity analyses were conducted， and based on these， a reasonable price range for cefiderocol in the Chinese market was explored. RESULTS The results for scenario 1 showed that the clinical cure rate in the cefiderocol group was higher than that in the BAT group （47.50% vs. 34.21%）， but its ICER was 415 065.03 yuan per cured case， exceeding three times China’s GDP per capita. Scenario 2 revealed that the ICER for cefiderocol relative to SOC was as high as 1 362 446.16 yuan per cured case， far exceeding the WTP. Sensitivity analysis indicated that the treatment duration and price of cefiderocol were key factors affecting its cost-effectiveness. In the two scenarios described above， the unit price of cefiderocol must fall below 683.47 and 242.00 yuan/g， respectively， to be considered cost-effective. CONCLUSIONS Based on the current market price， cefiderocol lacks sufficient cost-effectiveness for treating confirmed or suspected CRGNB serious infections within China’s healthcare system. To improve its accessibility， price negotiations or a tiered medical insurance payment strategy are required.

OBJECTIVES: Pelvic floor dysfunction is common among pregnant and postpartum women and significantly impacts quality of life. This study aims to translate the German Pelvic Floor Questionnaire for Pregnant and Postpartum Women into Chinese and to evaluate its reliability and validity in the Chinese population. METHODS: The questionnaire was translated using the Brislin model. A cross-sectional study was conducted among pregnant and postpartum women to assess the content validity, construct validity, Cronbach's α coefficient, test-retest reliability, and split-half reliability of the Chinese version. RESULTS: A total of 72 women were included, with 6.9% being pregnant and 93.1% postpartum; the age was (32.3±3.6) years. The Chinese version of the questionnaire contains 4 dimensions and 45 items. The content validity index of individual items ranged from 0.833 to 1.000, with a scale-level content validity index of 0.977 and intraclass correlation coefficients (ICCs) exceeding 0.90. The overall Cronbach's α coefficient was 0.891, with subscale coefficients ranging from 0.732 to 0.884 (all ICCs>0.70). The test-retest reliability of the total scale was 0.833, and for the 4 dimensions, bladder, bowel, prolapse, and sexual function, the values were 0.776, 0.579, 0.732, and 0.645, respectively. The split-half reliability was 0.74. CONCLUSIONS The Chinese version of the questionnaire demonstrated good reliability and validity, indicating its applicability in assessing pelvic floor dysfunction and associated risk factors during pregnancy and postpartum.
Humans ; Female ; Surveys and Questionnaires ; Pregnancy ; Adult ; Postpartum Period ; Psychometrics ; Pelvic Floor Disorders/diagnosis* ; Cross-Sectional Studies ; Quality of Life ; Pelvic Floor/physiopathology* ; Reproducibility of Results ; China ; Translations ; Young Adult

OBJECTIVE: To construct machine learning prediction model for sepsis-associated encephalopathy (SAE), and analyze the application value of the model on early identification of SAE risk in elderly septic patients. METHODS: Patients aged over 60 years with a primary diagnosis of sepsis admitted to intensive care unit (ICU) from 2008 to 2023 were selected from Medical Information Mart for Intensive Care-IV 2.2 (MIMIC-IV 2.2). Demographic variables, disease severity scores, comorbidities, interventions, laboratory indicators, and hospitalization details were collected. Key factors associated with SAE were identified using univariate Logistic regression analysis. The data were randomly divided into training and validation sets in a 7 : 3 ratio. Multivariable Logistic regression analysis was conducted in the training set and visualized using a nomogram model for prediction of SAE. The discrimination of the model was evaluated in the validation set using the receiver operator characteristic curve (ROC curve), and its calibration was assessed using calibration curve. Furthermore, multiple machine learning algorithms, including multi-layer perceptron (MLP), support vector machine (SVM), naive bayes (NB), gradient boosting machine (GBM), random forest (RF), and extreme gradient boosting (XGB), were constructed in the training set. Their predictive performance was subsequently evaluated on the validation set. Taking the XGB model as an example, the interpretability of the model through the SHapley Additive exPlanations (SHAP) algorithm was enhanced to identify the key predictive factors and their contributions. RESULTS: A total of 2 204 septic patients were finally enrolled, of whom 840 developed SAE (38.1%). A total of 21 variables associated with SAE were screened through univariate Logistic regression analysis. Multivariable Logistic regression analysis showed that endotracheal intubation [odds ratio (OR) = 0.40, 95% confidence interval (95%CI) was 0.19-0.88, P < 0.001], oxygen therapy (OR = 0.76, 95%CI was 0.53-0.95, P = 0.023), tracheotomy (OR = 0.20, 95%CI was 0.07-0.53, P < 0.001), continuous renal replacement therapy (CRRT; OR = 0.32, 95%CI was 0.15-0.70, P < 0.001), cerebrovascular disease (OR = 0.31, 95%CI was 0.16-0.60, P < 0.001), rheumatic disease (OR = 0.44, 95%CI was 0.19-0.99, P < 0.001), male (OR = 0.68, 95%CI was 0.54-0.86, P = 0.001), and maximum anion gap (AG; OR = 0.95, 95%CI was 0.93-0.97, P < 0.001) were associated with an decreased probability of SAE, and age (OR = 1.05, 95%CI was 1.03-1.06, P < 0.001), acute physiology score III (APSIII; OR = 1.02, 95%CI was 1.01-1.02, P < 0.001), Oxford acute severity of illness score (OASIS; OR = 1.04, 95%CI was 1.03-1.06, P < 0.001), and length of hospital stay (OR = 1.01, 95%CI was 1.01-1.02, P < 0.001) were associated with an increased probability of SAE. A nomogram model was constructed based on these variables. In the validation set, ROC curve analysis showed that the model achieved an area under the ROC curve (AUC) of 0.723, and the calibration curve showed good consistency between the predicted probability of the model and the observed probability. Among the machine learning algorithms, including MLP, SVM, NB, GBM, RF, and XGB, the SVM model and RF model demonstrated relatively good predictive performance, with AUC of 0.748 and 0.739, respectively, and the sensitivity was both exceeding 85%. The predictive performance of the XGB model was explained through SHAP analysis, and the results indicated that APSIII score (SHAP value was 0.871), age (SHAP value was 0.521), and OASIS score (SHAP value was 0.443) were important factors affecting the predictive performance of the model. CONCLUSIONS The machine learning-based SAE prediction model exhibits good predictive capability and holds significant application value for the early identification of SAE risk in elderly septic patients.
Humans ; Machine Learning ; Aged ; Sepsis-Associated Encephalopathy ; Sepsis/complications* ; Intensive Care Units ; Logistic Models ; Middle Aged ; Male ; ROC Curve ; Female ; Bayes Theorem ; Nomograms ; Support Vector Machine ; Algorithms

OBJECTIVE To investigate the prognostic factors of chondrosarcoma of the larynx,deeply analyze its clinical data,and provide a theoretical basis for better treatment of chondrosarcoma of the larynx.METHODS A retrospective analysis was conducted on the complete clinical data of patients with primary chondrosarcoma of the larynx admitted to the Department of Otolaryngology Head and Neck Surgery,Beijing Tongren Hospital,Capital Medical University from January 2010 to December 2024.RESULTS A total of 15 patients were included,including 11 males and 4 females,with a gender ratio of 11∶4.The average age of onset was 57.3 years,and the average clinical symptom duration was 12.2 months.The tumors were mainly located in the cricoid cartilage in 11 patients,in the arytenoid cartilage in 2 patients,and in the thyroid cartilage in 2 patients.Tumor grading showed that 7 patients were grade I and 8 were grade II.Four patients underwent transoral laser minimally invasive surgery,2 patients underwent partial laryngectomy+tracheotomy,and 9 patients underwent total laryngectomy/cervical lymph node dissection+tracheostomy.The 5-year overall survival rate was 85.7%,the 5-year disease-specific survival rate was 100%,and the 5-year local-regional control rate was 90.9%.Gender,tumor location,tumor grade,Ki-67,tumor size,and whether larynx preservation surgery was performed did not affect the local-regional control rate or disease-specific survival rate.CONCLUSION Laryngeal chondrosarcoma generally has a longer disease history and is difficult to detect.The pathological type is mostly well-differentiated.Regional or distant metastasis is rare,and the long-term survival rate is good.Surgical resection is the preferred treatment option.On the basis of not reducing the tumor control rate,surgery that prioritizes preserving laryngeal function should be given priority,while comprehensive treatment is generally not recommended.

To elucidate the mechanism by which steaming affects the quality of Curcuma kwangsiensis root tubers, methods such as LSCM, RVA, dual-wavelength spectrophotometry, LF-NMR, and LC-MS were employed to qualitatively and quantitatively detect changes in starch gelatinization characteristics, water distribution, and material composition of C. kwangsiensis root tubers under different steaming durations. Based on multivariate statistical analysis, the correlation between differences in gelatinization parameters, water distribution, and terpenoid material composition was investigated. The results indicate that steaming affects both starch gelatinization and water distribution in C. kwangsiensis. During the steaming process, transformations occur between amylose and amylopectin, as well as between semi-bound water and free water. After 60 min of steaming, starch gelatinization and water distribution reached an equilibrium state. The content of amylopectin, the amylose-to-amylopectin ratio, and parameters such as gelatinization temperature, viscosity, breakdown value, and setback value were significantly correlated(P≤0.05). Additionally, the amylose-to-amylopectin ratio was significantly correlated with total free water and total water content(P≤0.05). Steaming induced differences in the material composition of C. kwangsiensis root tubers. Clustering of primary metabolites in the OPLS-DA model was distinct, while secondary metabolites were classified into 9 clusters using the K-means clustering algorithm. Differential terpenoid metabolites such as(-)-α-curcumene were significantly correlated with zerumbone, retinal, and all-trans-retinoic acid(P<0.05). Curcumenol was significantly correlated with isoalantolactone and ursolic acid(P<0.05), while all-trans-retinoic acid was significantly correlated with both zerumbone and retinal(P<0.05). Alpha-tocotrienol exhibited a significant correlation with retinal and all-trans-retinoic acid(P<0.05). Amylose was extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and α-tocotrienol(P<0.05). Amylopectin was significantly correlated with zerumbone(P<0.05) and extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and 9-cis-retinoic acid(P<0.01). The results provide scientific evidence for elucidating the mechanism of quality formation of steamed C. kwangsiensis root tubers as a medicinal material.
Curcuma/chemistry* ; Starch/chemistry* ; Multivariate Analysis ; Water/chemistry* ; Terpenes/analysis* ; Plant Roots/chemistry* ; Plant Tubers/chemistry* ; Drugs, Chinese Herbal/chemistry*

The accurate segmentation of breast ultrasound images is an important precondition for the lesion determination. The existing segmentation approaches embrace massive parameters, sluggish inference speed, and huge memory consumption. To tackle this problem, we propose T ²KD Attention U-Net (dual-Teacher Knowledge Distillation Attention U-Net), a lightweight semantic segmentation method combined double-path joint distillation in breast ultrasound images. Primarily, we designed two teacher models to learn the fine-grained features from each class of images according to different feature representation and semantic information of benign and malignant breast lesions. Then we leveraged the joint distillation to train a lightweight student model. Finally, we constructed a novel weight balance loss to focus on the semantic feature of small objection, solving the unbalance problem of tumor and background. Specifically, the extensive experiments conducted on Dataset BUSI and Dataset B demonstrated that the T ²KD Attention U-Net outperformed various knowledge distillation counterparts. Concretely, the accuracy, recall, precision, Dice, and mIoU of proposed method were 95.26%, 86.23%, 85.09%, 83.59%and 77.78% on Dataset BUSI, respectively. And these performance indexes were 97.95%, 92.80%, 88.33%, 88.40% and 82.42% on Dataset B, respectively. Compared with other models, the performance of this model was significantly improved. Meanwhile, compared with the teacher model, the number, size, and complexity of student model were significantly reduced (2.2×10 ⁶ vs. 106.1×10 ⁶, 8.4 MB vs. 414 MB, 16.59 GFLOPs vs. 205.98 GFLOPs, respectively). Indeedy, the proposed model guarantees the performances while greatly decreasing the amount of computation, which provides a new method for the deployment of clinical medical scenarios.
Humans ; Breast Neoplasms/diagnostic imaging* ; Female ; Ultrasonography, Mammary/methods* ; Image Processing, Computer-Assisted/methods* ; Algorithms ; Neural Networks, Computer ; Breast/diagnostic imaging*

OBJECTIVE To evaluate the cost-utiliby of capivasertib combined with fulvestrant for the second-line treatment of hormone receptor-positive/human epidermal growth factor receptor-2-negative （HR+/HER2－） advanced breast cancer from the perspective of the Chinese healthcare system. METHODS A partitioned survival model was constructed using clinical data from the CAPItello-291 trial. Costs and quality-adjusted life years （QALYs） were used as the output indicators of the model， and the incremental cost-effectiveness ratio （ICER） was used as the evaluation indicator of the model. Using three times the per capita gross domestic product （GDP） of China in 2024 as the willingness-to-pay threshold （WTP）， this study analyzed the cost-utility of capivasertib combined with fulvestrant versus fulvestrant monotherapy in the treatment of HR+/HER2－ advanced breast cancer， and conducted sensitivity analysis and scenario analysis under conditions where the price of capivasertib was reduced by 50%， 60%， 70% and 95%， respectively. RESULTS The results of the basic analysis showed that compared with the fulvestrant monotherapy regimen， the ICER of capivasertib combined with fulvestrant was 843 038.46 yuan/QALY， which was higher than the WTP（287 247 yuan/QALY）. The one-way sensitivity analysis revealed that the top three factors with the most substantial influence on ICER were the utility value in the progression disease state， the price of capivasertib， and the utility value inthe progression free survival state. Probabilistic sensitivity analysis demonstrated the robustness of the basic analysis results. Scenario analysis revealed that even if the price of capivasertib were reduced by 95%， capivasertib combined with fulvestrant did not exhibit cost-effectiveness at the current WTP. CONCLUSION At a WTP of three times China’s GDP per capita in 2024， compared to fulvestrant monotherapy， capivasertib combined with fulvestrant as the second-line treatment for HR+/ HER2－ advanced breast cancer is not cost-effective.

Objective:To characterize the epidemiology, antimicrobial susceptibility, and molecular mechanisms of carbapenem-resistant Enterobacterales (CRE) carrying multiple carbapenemase genes in China, and to provide evidence for infection control and antibiotic stewardship.Methods:From 2016 to 2023, 115 CRE isolates harboring at least two carbapenemase genes were collected from 41 hospitals in 18 provinces across China. Species identification, antimicrobial susceptibility testing, and whole-genome sequencing were performed. Multilocus sequence typing (MLST) and capsular typing were conducted using Kleborate, plasmid replicon types were identified with PlasmidFinder, and a core genome phylogenetic tree was constructed.Results:The majority of isolates belonged to Klebsiella spp. (80.0%, 92/115), followed by E. cloacae (8.7%, 10/115) and E. coli (6.1%, 7/115). The isolates were mainly from Hebei, Beijing, Shandong, and Hunan (60.9%, 70/115), and sputum was the predominant specimen (43.5%, 50/115). The most common genotype was bla KPC+bla NDM (73.0%, 84/115), primarily in Klebsiella spp. (79.8%, 67/84), followed by bla NDM+bla IMP (15.7%, 18/115). The prevalent plasmid replicon types were IncFII (77.5%, 86/111), IncFIB (68.5%, 76/111), IncR (51.4%, 57/111), and IncX3 (20.7%, 23/111). Notably, 88.6% (31/35) of ST11-KL64 K. pneumoniae strains co-harbored IncFII, IncFIB, and IncR plasmids simultaneously. Between 2016 and 2022, the dominant subtype among Klebsiella spp. isolates was bla KPC-2+bla NDM-1 (56.2%, 36/64). In 2023, the bla KPC-2+bla NDM-13 subtype (29.5%, 19/64) emerged and exhibited clonal transmission (single nucleotide polymorphism 2?74 bp) in Hebei, Beijing, and Jilin. Susceptibility testing showed widespread resistance to β-lactams (90.2%-100%). Aztreonam-avibactam, tigecycline, and colistin retained high activity, with susceptibility rates of 90.16%-98.36%. Conclusions:In China, the majority of clinical Enterobacteriaceae strains that harbor multiple carbapenemases are Klebsiella spp. co-producing KPC and NDM enzymes. Dissemination is driven by both clonal expansion of ST11-KL64 and horizontal transfer of IncFII, IncFIB, and IncR plasmids. The recent emergence and regional clonal spread of the bla KPC-2+bla NDM-13 genotype underscore the urgent need for strengthened surveillance and containment measures.