Objective: To investigate the factors influencing intraoperative blood transfusion in patients with hip fractures and to develop a machine learning (ML) model for predicting this risk. Methods: A total of 424 patients with hip fractures who underwent surgical treatment between November 2022 and March 2025 in our hospital were selected. Key feature variables of intraoperative blood transfusion risk were identified using the Boruta algorithm. Four different ML algorithms—support vector machine (SVM), linear discriminant analysis (LDA), mixed discriminant analysis (MDA), and extreme gradient boosting (XGBoost)—were used to develop predictive models for intraoperative blood transfusion risk. The predictive performance of the four ML models were evaluated using accuracy, precision, receiver operating characteristic (ROC) curves, precision-recall curves (PRC), precision-recall gain curves (PRGC), and F1 scores. Shapley additive interpretation (SHAP) was used to interpret the final model. Results: Among the 424 patients, 77(18.2%) received intraoperative blood transfusion. The Boruta algorithm identified albumin (ALB), activated partial thromboplastin time (APTT), types of anesthesia, types of fracture, and hemoglobin (Hb) as key feature variables for predicting intraoperative blood transfusion risk. In model evaluation, the SVM model outperforms the other three models across multiple metrics, including the area under the receiver operating characteristic curve (AUC), recall, recall gain, accuracy, precision, F1 score, and the area under the precision-recall curve (PRC-AUC). The SVM model, interpreted and visualized based on SHAP values, effectively predicted intraoperative blood transfusion risk in patients with hip fracture. A visual online application was developed based on the SVM model (https://pbo-nomogram.shinyapps.io/blood/). Conclusion: Preoperative low ALB and Hb levels, prolonged APTT, general anesthesia, and intertrochanteric fractures are risk factors for intraoperative blood transfusion in hip fracture patients. The risk prediction model for intraoperative blood transfusion constructed based on the SVM algorithm has optimal performance, which provides new ideas and methods for the clinical early identification of hip fracture patients with high transfusion risk and the implementation of targeted interventions.

Background: Cytomegalovirus (CMV) infection remains a major cause of morbidity, mortality, and increased healthcare burden in recipients of allogeneic hematopoietic stem cell transplantation (allo-HSCT). Its clinical manifestations range from asymptomatic CMV replication to end-organ diseases such as pneumonia, gastroenteritis, and retinitis, all of which are associated with a higher rate of nonrelapse mortality. Methods: We reviewed case records of children who underwent allo-HSCT at our center between April 2013 and October 2024. CMV monitoring was performed weekly until at least day +100 post-HSCT using a quantitative polymerase chain reaction assay. All patients received acyclovir prophylaxis. Pre-emptive intravenous ganciclovir therapy was initiated when CMV-DNA levels exceeded 500 IU/mL Results: A total of 150 consecutive patients (58% male) were included. The median age at HSCT was 6.3 years (interquartile range [IQR], 3.4–11.3 years). Indications for HSCT were hematologic malignancy (n=81, 54.0%), inborn errors of immunity and bone marrow failure (n=46, 30.7%), and hemoglobinopathy (n=23, 15.3%). Donor and recipient CMV seropositivity rates were 86.7% and 94.0%, respectively. CMV infection occurred in 43.4% of patients, with a median onset of 30 days post-HSCT (IQR, 21–47 days). There were five (3.3%) cases of CMV disease, resulting in one (0.7%) CMV-related death. Human leukocyte antigen (HLA)-haploidentical donor status (odds ratio [OR], 5.00; 95% confidence interval [CI], 2.43–10.29; P<0.001) and the use of serotherapy in the conditioning regimen (OR, 2.87; 95% CI, 1.47–5.60; P=0.002) were significantly associated with an increased risk of CMV infection. Conclusions CMV infection was a common occurrence, particularly among patients with HLA-haploidentical donors. Preventive strategies such as weekly surveillance and pre-emptive ganciclovir therapy proved effective in preventing overt CMV disease.

Objective:To explore the application value of the artificial intelligence (AI) morphological assisted analysis system in the pre-classification of blood cells in patients with acute myeloid leukemia, myelodysplasia-related (AML-MR).Methods:A retrospective analysis was conducted on the bone marrow and peripheral blood cell morphology of patients initially diagnosed with AML-MR at Taizhou Hospital in Zhejiang Province from September 1, 2022, to December 31, 2023. A total of 44 patients, including 25 males and 19 females, with a median age of 71 (63.5, 75.3) years. Bone marrow and peripheral blood morphology were examined using the Morphogo cell morphology assisted analysis system, with the artificial classification results serving as the gold standard. A confusion matrix was constructed to evaluate the precision, sensitivity, and specificity of the AI system in identifying various cell types in bone marrow and peripheral blood for AML-MR diagnosis. The impact of dysplastic hematopoiesis on AI pre-classification was analyzed by comparing AI and manual classification results.Results:The AI system completed the pre-classification of 44 bone marrow smears and 42 corresponding peripheral blood smears from AML-MR patients. For bone marrow smears, the precision, sensitivity, and specificity of AI in pre-classifying blast cells were 85.78%, 91.01%, and 94.58%, respectively. For peripheral blood smears, these values were 87.11%, 87.05%, and 98.29%, respectively. The precision and sensitivity of AI in pre-classifying promyelocytes were 54.26% and 46.93%, respectively, while for monocytes, they were 58.16% and 68.34%, both lower than those for blast cells. The precision and sensitivity of AI in identifying myelocytes and metamyelocytes also decreased (77.47%, 66.25% and 81.91%, 63.29%, respectively). The precision and sensitivity of AI in pre-classifying erythroblasts/proerythroblasts (67.71%, 69.89%) were lower than those for polychromatic and orthochromatic normoblasts (83.43%, 85.53% and 92.97%, 86.96%, respectively). The confusion matrix and comparative analysis of AI and manual classification indicated that the decline in AI pre-classification precision and sensitivity was due to frequent misclassification between promonocytes and monocytes, as well as between monocytes and promyelocytes. Additionally, this decline is associated with dysplasia. However, the impact of dysplasia on the AI pre-classification of mature-stage granulocytes was minimal.Conclusion:The AI system demonstrated high precision, sensitivity, and specificity in pre-classifying blast cells in bone marrow and peripheral blood smears from AML-MR patients. The AI-assisted morphological analysis system can be effectively utilized for the pre-classification of blood cells in AML-MR patients.

Objective:To explore the immunophenotypic differences between acute promyelocytic leukemia (APL) and APL-like NPM1 mutant acute myeloid leukemia (NPM1mutAML) using flow cytometry, and to investigate early diagnostic markers for differentiating APL from NPM1mutAML.Methods:A retrospective study was conducted on 72 cases of APL diagnosed at Taizhou Hospital, affiliated with Wenzhou Medical University, from February 2nd, 2018 to December 16th, 2023, including 42 male and 30 female patients with a median age of 42 (32, 57) years old. Based on morphology, 51 cases were classified as the coarse-granular type and 21 cases as the fine-granular type. Additionally, 45 cases of NPM1mutAML, comprising 20 male and 25 female patients with a median age of 58 (47, 65) years old, were included. Of these, 12 cases were classified as the coarse-granular type and 33 as the fine-granular type. Immunophenotypic analysis was performed using multiparameter flow cytometry, and all patients underwent cytogenetic analysis for chromosome karyotyping. FISH analysis was used for detecting the PML-RARα fusion gene in APL cases, and sequencing was used for identifying NPM1 mutations in NPM1mutAML patients. The antigen expression parameters (expression rate, median fluorescence intensity [MdFI], and coefficient of variation [ CV]) were analyzed using principal component analysis (PCA). The antigen expression rates were compared using the Wilcoxon rank-sum test, and the positive rates of antigens were compared using the Chi-square test. Sensitivity and specificity for diagnosis by the some antigens were evaluated using ROC curve analysis. Results:The immunophenotypic analysis revealed that the expression rates of CD123, CD64, CD13, and CD9 were significantly higher in APL compared to NPM1mutAML ( Z values of-6.72, -6.29, -5.63, -7.67, P<0.01). In the coarse-granular type, the expression rates of CD123 and CD9 in APL were also significantly higher than those in NPM1mutAML ( P<0.01). In the fine-granular type, the expression levels of CD123, CD13, CD64, and CD9 were significantly higher in APL than in NPM1mutAML ( P<0.01). ROC curve analysis showed that in the fine-granular type, the areas under the curve (AUC) for CD64, CD13, CD123, and CD9 in diagnosing APL and NPM1mutAML were 0.96, 0.89, 0.86, and 0.89, respectively ( P<0.01). In the coarse-granular type, the AUC for CD64 and CD13 were 0.49 and 0.51 ( P>0.05), while the AUC for CD123 and CD9 were 0.96 and 0.96 ( P<0.01). Principal component analysis (PCA) of antigen expression (expression rate, MdFI, CV) showed complete separation of the APL and NPM1mutAML groups. Conclusion:APL and APL-like NPM1mutAML patients exhibit distinct antigen expression profiles. Specifically, a combined detection of CD64, CD13, CD123, and CD9 can help to rapidly differentiate APL from APL-like NPM1mutAML at initial diagnosis.

Aim To explore the roles and mechanisms of long non-coding RNA(lncRNA)AC087388.1 and poly(A)binding protein cytoplasmic 1(PABPC1)in esophageal squamous cell carcinoma(ESCC).Meth-ods The expression level of AC087388.1 in ESCC tissues and cells was detected by real-time fluorescence quantitative polymerase chain reaction(RT-qPCR)and fluorescence in situ hybridization experiments and its clinical relevance was analyzed.Cell counting kit-8(CCK-8),clone formation,scratch and Transwell inva-sion assays were used to detect the effects of knock-down of AC087388.1 on the cell viability,prolifera-tion,migratory,and invasion of ESCC cells respectively ability,and sub-localization in cells.RNA pull down and Western blot experiments were employed to verify the interaction between AC087388.1 and PABPC1 in ESCC cells.Salvage experiments were performed to detect the effect of AC087388.1 targeting PABPC1 on ESCC cells.Results AC087388.1 was highly ex-pressed in ESCC tissues and cells and positively corre-lated with clinical stage of ESCC patients,mainly local-ized in cytoplasm.Knockdown AC087388.1 inhibited ESCC cell viability,proliferation,migration and inva-sionability.PABPC1 was selected from the results of RNA Pull Down-MS experiments for subsequent experi-ments,and AC087388.1 was verified to bind to PAB-PC1 by RNA Pull Down and Western blot experiments.Overexpression of AC087388.1 was verified by rescue experiment to reverse the effects of knockdown of PAB-PC1 on ESCC cell viability,proliferation,migration and invasion.Conclusions High expression of AC087388.1 correlates with clinical stage and may be a risk factor for ESCC progression.AC087388.1 pro-motes the cell viability,proliferation,migration and in-vasive ability of ESCC cells by targeting PABPC1,which may be a novel biomarker for the diagnosis and treatment of ESCC.

Aim To investigate the effects of circ_0071653 targeting miR-197-3p on the proliferation and metastasis of esophageal squamous cell carcinoma(ES-CC)cells.Methods The circular structure of circ_0071653 was confirmed by Sanger sequencing and ribo-nuclease R tolerance experiments.Real-time quantita-tive polymerase chain reaction(RT-qPCR)and tissue fluorescence in situ hybridization assay were performed to detect the circ_0071653 expression levels and ana-lyze its clinical relevance.Cell fluorescence in situ hy-bridization and nuclear cytoplasmic separation assays were used to verify the subcellular localization of circ_0071653 and miR-197-3p.Bioinformatics analysis,dual luciferase reporter gene and RT-qPCR assays were conducted to validate the interactions between circ_0071653 and miR-197-3p.Moreover,the cell counting Kit-8(CCK-8),colony formation,scratch,Transwell invasion and subcutaneous tumor formation in nude mice assays were used to evaluate the effects of circ_0071653 and miR-197-3p on cell viability,prolifera-tion,migration,and invasion and in vivo tumorigenesi-sability.Results Circ_0071653 was a circular RNA,which showed high expression in ESCC cell lines and tissues.The expression of circ_0071653 was signifi-cantly correlated with lymph node metastasis and clini-cal stage of ESCC patients.Circ_0071653 and miR-197-3p were mainly localized in the cytoplasm.The databases predict that circ_0071653 had complementa-ry binding sites with miR-197-3p,and their binding were confirmed by dual luciferase reporter geneand RT-qPCR assays.Moreover,the activity,proliferation,migration,invasion and in vivo tumorigenesis abilities of ESCC cells were significantly reduced after knocking down circ_0071653,and this effect could be reversed by downregulating the expression of miR-197-3p.Con-clusions Circ_0071653 promotes the malignant pro-gression of ESCC through targeted regulation of miR-197-3p.

Objective To explore the application effect of 3D printed individualized model in the treatment of complex ankle fractures(AF).Methods Patients with complex AF admitted to our hospital from July 2021 to October 2022 were selected and divided into the control group and the observation group using a random number table method,with 50 cases in each group.Patients in the control group were received minimally invasive reduction and internal fixation,while these in the observation group were given minimally invasive reduction and internal fixation under the guidance of 3D printed individualized model.The surgical conditions,ankle joint reduction,stress indicators[norepinephrine(NE)and angiotensin Ⅱ(AngⅡ)],ankle function and postoperative complications were compared between the two groups.Results There were 2 patients in the observation group and 3 patients in the control group were lost to follow-up 12 months after surgery.Compared with the control group,the observation group showed a decrease in the intraoperative blood loss,shortened surgical time,hospitalization time,and weight-bearing activity time,and an increase in the anatomical reduction rate(P<0.05).The observation group had lower serum levels of NE and AngⅡ 1 and 3 days after surgery(P<0.05)and higher Kofoed score and American Orthopedic Foot and Ankle Society(AOFAS)scores 1,6,and 12 months after surgery(P<0.05),as well as lower incidence of postoperative complications(P<0.05)than those in the control group.Conclusion For the treatment of complex AF,3D printed individualized model assisted the formulation of minimally invasive reduction and fixation surgical plans before surgery can shorten surgical time,reduce stress injury,decrease the risk of complications,and simultaneously increase the anatomical reduction rate and improve ankle joint function,thereby accelerating postoperative recovery of patients.

Aim To explore the roles and mechanisms of long non-coding RNA(lncRNA)AC087388.1 and poly(A)binding protein cytoplasmic 1(PABPC1)in esophageal squamous cell carcinoma(ESCC).Meth-ods The expression level of AC087388.1 in ESCC tissues and cells was detected by real-time fluorescence quantitative polymerase chain reaction(RT-qPCR)and fluorescence in situ hybridization experiments and its clinical relevance was analyzed.Cell counting kit-8(CCK-8),clone formation,scratch and Transwell inva-sion assays were used to detect the effects of knock-down of AC087388.1 on the cell viability,prolifera-tion,migratory,and invasion of ESCC cells respectively ability,and sub-localization in cells.RNA pull down and Western blot experiments were employed to verify the interaction between AC087388.1 and PABPC1 in ESCC cells.Salvage experiments were performed to detect the effect of AC087388.1 targeting PABPC1 on ESCC cells.Results AC087388.1 was highly ex-pressed in ESCC tissues and cells and positively corre-lated with clinical stage of ESCC patients,mainly local-ized in cytoplasm.Knockdown AC087388.1 inhibited ESCC cell viability,proliferation,migration and inva-sionability.PABPC1 was selected from the results of RNA Pull Down-MS experiments for subsequent experi-ments,and AC087388.1 was verified to bind to PAB-PC1 by RNA Pull Down and Western blot experiments.Overexpression of AC087388.1 was verified by rescue experiment to reverse the effects of knockdown of PAB-PC1 on ESCC cell viability,proliferation,migration and invasion.Conclusions High expression of AC087388.1 correlates with clinical stage and may be a risk factor for ESCC progression.AC087388.1 pro-motes the cell viability,proliferation,migration and in-vasive ability of ESCC cells by targeting PABPC1,which may be a novel biomarker for the diagnosis and treatment of ESCC.

Aim To investigate the effects of circ_0071653 targeting miR-197-3p on the proliferation and metastasis of esophageal squamous cell carcinoma(ES-CC)cells.Methods The circular structure of circ_0071653 was confirmed by Sanger sequencing and ribo-nuclease R tolerance experiments.Real-time quantita-tive polymerase chain reaction(RT-qPCR)and tissue fluorescence in situ hybridization assay were performed to detect the circ_0071653 expression levels and ana-lyze its clinical relevance.Cell fluorescence in situ hy-bridization and nuclear cytoplasmic separation assays were used to verify the subcellular localization of circ_0071653 and miR-197-3p.Bioinformatics analysis,dual luciferase reporter gene and RT-qPCR assays were conducted to validate the interactions between circ_0071653 and miR-197-3p.Moreover,the cell counting Kit-8(CCK-8),colony formation,scratch,Transwell invasion and subcutaneous tumor formation in nude mice assays were used to evaluate the effects of circ_0071653 and miR-197-3p on cell viability,prolifera-tion,migration,and invasion and in vivo tumorigenesi-sability.Results Circ_0071653 was a circular RNA,which showed high expression in ESCC cell lines and tissues.The expression of circ_0071653 was signifi-cantly correlated with lymph node metastasis and clini-cal stage of ESCC patients.Circ_0071653 and miR-197-3p were mainly localized in the cytoplasm.The databases predict that circ_0071653 had complementa-ry binding sites with miR-197-3p,and their binding were confirmed by dual luciferase reporter geneand RT-qPCR assays.Moreover,the activity,proliferation,migration,invasion and in vivo tumorigenesis abilities of ESCC cells were significantly reduced after knocking down circ_0071653,and this effect could be reversed by downregulating the expression of miR-197-3p.Con-clusions Circ_0071653 promotes the malignant pro-gression of ESCC through targeted regulation of miR-197-3p.

Objective:To explore the application value of the artificial intelligence (AI) morphological assisted analysis system in the pre-classification of blood cells in patients with acute myeloid leukemia, myelodysplasia-related (AML-MR).Methods:A retrospective analysis was conducted on the bone marrow and peripheral blood cell morphology of patients initially diagnosed with AML-MR at Taizhou Hospital in Zhejiang Province from September 1, 2022, to December 31, 2023. A total of 44 patients, including 25 males and 19 females, with a median age of 71 (63.5, 75.3) years. Bone marrow and peripheral blood morphology were examined using the Morphogo cell morphology assisted analysis system, with the artificial classification results serving as the gold standard. A confusion matrix was constructed to evaluate the precision, sensitivity, and specificity of the AI system in identifying various cell types in bone marrow and peripheral blood for AML-MR diagnosis. The impact of dysplastic hematopoiesis on AI pre-classification was analyzed by comparing AI and manual classification results.Results:The AI system completed the pre-classification of 44 bone marrow smears and 42 corresponding peripheral blood smears from AML-MR patients. For bone marrow smears, the precision, sensitivity, and specificity of AI in pre-classifying blast cells were 85.78%, 91.01%, and 94.58%, respectively. For peripheral blood smears, these values were 87.11%, 87.05%, and 98.29%, respectively. The precision and sensitivity of AI in pre-classifying promyelocytes were 54.26% and 46.93%, respectively, while for monocytes, they were 58.16% and 68.34%, both lower than those for blast cells. The precision and sensitivity of AI in identifying myelocytes and metamyelocytes also decreased (77.47%, 66.25% and 81.91%, 63.29%, respectively). The precision and sensitivity of AI in pre-classifying erythroblasts/proerythroblasts (67.71%, 69.89%) were lower than those for polychromatic and orthochromatic normoblasts (83.43%, 85.53% and 92.97%, 86.96%, respectively). The confusion matrix and comparative analysis of AI and manual classification indicated that the decline in AI pre-classification precision and sensitivity was due to frequent misclassification between promonocytes and monocytes, as well as between monocytes and promyelocytes. Additionally, this decline is associated with dysplasia. However, the impact of dysplasia on the AI pre-classification of mature-stage granulocytes was minimal.Conclusion:The AI system demonstrated high precision, sensitivity, and specificity in pre-classifying blast cells in bone marrow and peripheral blood smears from AML-MR patients. The AI-assisted morphological analysis system can be effectively utilized for the pre-classification of blood cells in AML-MR patients.