Objective To evaluate the value of serum Mac-2 binding protein (M2BP) for assessment of the severity of schisto somiasis-induced liver fibrosis, so as to provide insights into non-invasive diagnosis and disease surveillance of liver fibrosis caused by schistosomiasis. Methods A total of 234 individuals with a history of Schistosoma japonicum infection were sampled from Xinhua Village, Lushan City, Jiangxi Province from 2019 to 2020, and 234 serum samples were collected from all participants. All participants received B-ultrasound examinations of the liver. Serum samples were categorized into four groups (grades 0, Ⅰ, Ⅱ and Ⅲ schistosomiasis-induced liver fibrosis groups) according to B-ultrasound examination results, and then, each group was randomly divided into a receiver operating characteristic (ROC) curve group and an efficacy assessment group at a ratio of 7∶3. Serum M2BP concentration was measured in four groups using the enzyme-linked immunosorbent assay (ELISA), and differences in serum M2BP concentrations were compared with analysis of variance and Spearman correlation analysis. Serum M2BP concentration was subjected to ROC curve analysis among individuals with different grades of schistosomiasis-induced liver fibrosis in the ROC curve group to determine the optimal diagnostic threshold of M2BP concentration at different fibrosis grades, and the area under the ROC curve (AUC) was calculated to evaluate the diagnostic performance. The diagnostic accuracy was verified by comparing the accordance rate and Kappa consistency test in the efficacy assessment group. Results Among 234 serum samples, there were 79 samples with grade 0 schistosomiasis-induced liver fibrosis, 87 samples with Grade Ⅰ, 46 samples with Grade Ⅱ and 22 samples with Grade Ⅲ according to the B-ultrasound examinations. The mean serum M2BP concentrations were (0.40 ± 0.31) [95% confidence interval (CI): (0.33, 0.47)], (0.64 ± 0.48) [95% CI: (0.53, 0.74)], (1.76 ± 0.58) [95% CI: (1.59, 1.93)] μg/mL and (2.56 ± 0.93) [95% CI: (2.14, 2.97)] μg/mL in the four groups, respectively (F = 150.796, P < 0.001), and the severity of schistosomiasis-induced liver fibrosis significantly positively correlated with serum M2BP concentration (rs = 0.715, P < 0. 001). The sample sizes of grades 0, Ⅰ, Ⅱ and Ⅲ schistosomiasis-induced liver fibrosis sera were randomly allocated as follows: 55 versus 24, 61 versus 26, 32 versus 14, and 15 versus 7 in the ROC curve and efficacy assessment groups, respectively, and the serum M2BP concentrations were (0.39 ± 0.29) μg/mL and (0.42 ± 0.36) μg/mL (F = 0.196, P > 0.05), (0.59 ± 0.47) μg/mL and (0.75 ± 0.51) μg/mL (F = 1.967, P > 0.05), (1.73 ± 0.59) μg/mL and (1.85 ± 0.57) μg/mL (F = 0.417, P > 0.05), and (2.46 ± 0.64) μg/mL and (2.76 ± 1.41) μg/mL (F = 0.491, P > 0.05), respectively. ROC curve analysis showed that the optimal diagnostic thresholds of serum M2BP concentration were 0.347 86 μg/mL (AUC = 0.635, P < 0.05), 1.188 83 μg/mL (AUC = 0.938, P < 0.000 1) and 2.021 21 μg/mL (AUC = 0.821, P < 0.000 1) for grade Ⅰ, Ⅱ and Ⅲ schistosomiasis-induced liver fibrosis. In addition, the accordance rates between the optimal diagnostic threshold of serum M2BP and B-ultrasound examinations for predicting grade Ⅰ, Ⅱ and Ⅲ schistosomiasis-induceed liver fibrosis were 69.23%, 85.71% and 71.43% (χ2 = 1.340, P > 0.05), and the overall Kappa consistency test showed moderate consistency [Kappa = 0.608, 95% CI: (0.428, 0.788); Z = 6.609, P < 0.000 1]. Conclusions Serum M2BP may serve as a potential biomarker for assessing moderate to advanced schistosomiasis-induced liver fibrosis; however, its diagnostic value for early-stage schistosomiasis-induced liver fibrosis remains limited.

B cell receptor(BCR)is the main molecular basis for B cell specific recognition and binding of antigen,and its complementarity determining region(CDR3)presents high diversity and specificity.Using single-cell immune repertoire sequencing technology can accurately analyze the composition and characteristics of each B cell BCR CDR3 sequence,and can better understand the process and mechanism of B cell differentiation,development,and response.Single-cell immune repertoire sequencing technology provides new ideas and theoretical basis for the pathogenesis,monitoring,diagnosis and treatment of B-cell immune-related diseases.This paper mainly compares and analyzes the commonly used detection methods and detection platforms of B-cell BCR CDR3 receptor library,and focuses on the application,research status and progress of single-cell sequencing technology in B-cell BCR CDR3 recep-tor library.

Objective:To explore the application of machine learning (ML) models based on radiomics and dosiomics to the assessment of hematologic toxicity (HT) in patients with locally advanced cervical cancer, and to preliminarily explore the comprehensive application of multi-omics features.Methods:A retrospective study was conducted on the clinical data, planning computed tomography (CT) images, and dose files of 205 patients with locally advanced cervical cancer who received concurrent chemoradiotherapy at the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, from January 2022 to June 2023. Patients were categorized according to the severity of HT. Radiomics and dosiomics features were extracted from the same regions of interest (ROIs), followed by feature selection utilizing a random forest algorithm. Then, radiomics, dosiomics, and hybrid models were established based on extreme gradient boosting (XGBoost). The classification performance of these models was assessed by calculating their sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).Results:The radiomics model yielded sensitivity, specificity, and AUC of 0.42, 0.86, and 0.78, respectively. The dosiomics model exhibited sensitivity, specificity, and AUC of 0.50, 0.90, and 0.74, respectively. In contrast, the hybrid model achieved sensitivity, specificity, and AUC of 0.50, 0.83, and 0.83, respectively. These findings suggest that the hybrid model possessed an enhanced classification capability compared to the individual radiomics and dosiomics models.Conclusions:It is feasible to use ML models based on radiomics and dosiomics to conduct the classification and prediction of HT in patients with locally advanced cervical cancer treated with concurrent chemoradiotherapy. Furthermore, integrating both radiomics features and dosiomics features can improve the classification performance of relevant prediction models, thus holding application potentials to optimize treatment strategies for patients with locally advanced cervical cancer.

Objective:To investigate the effects of prognostic nutritional index (PNI) on the readmission rate, complication rate, mortality rate and survival of patients with liver cirrhosis.Methods:From January 1, 2020 to December 31, 2022, 395 hospitalized patients with liver cirrhosis at Tianmen Hospital Affiliated to Wuhan University of Science and Technology were retrospectively enrolled. The clinical data were collected from the patients at their first hospitalization (baseline period) and re-hospitalization during follow-up period. The 18-month follow-up was divided into 4 periods, including the first period (from the 0th to the 3rd month), the second one was from the 4th to the 6th month, the third one was from the 7th to the 12th month, and the fourth one was from the 13th to the 18th month of follow-up. The prognostic value of PNI for patients with liver cirrhosis was evaluated through the receiver operating characteristic curve (ROC) of the baseline PNI. The 395 patients were divided into the low PNI group and the high PNI group based on the optimal cut-off value of PNI on the ROC. Patients readmitted during each follow-up period were divided into the PNI improvement group (PNI at follow-up -PNI at baseline>0) and the PNI non-improvement group (PNI at follow-up-PNI at baseline ≤0). Independent sample t-test, one-way analysis of variance (ANOVA), Mann-Whitney U test, chi-square test or Fisher′s exact test were used for statistical analysis. Survival curves depicting the relationship between PNI and overall survival rate of patients with liver cirrhosis were constructed using the Kaplan-Meier method. Results:The ROC analysis indicated that the optimal cut-off value of PNI at baseline was 32.65, with an area under the curve of 0.639 (95% confidence interval: 0.541 to 0.738, P=0.011), with a sensitivity of 0.567 and a specificity of 0.701. There were 269 cases in the high PNI group and 126 cases in the low PNI group. The readmission rate, complication rate and mortality rate in the low PNI group were all higher than those in the high PNI group at the first and fourth follow-up periods (32.5% (41/126) vs. 22.3% (60/269), 31.7% (40/126) vs. 20.4% (55/269), 6.3% (8/126) vs. 1.1% (3/269), 25.0% (29/116) vs. 16.2% (42/260), 25.0% (29/116) vs. 15.4% (40/260), 6.0% (7/116) vs. 1.5% (4/260)), and the differences were statistically significant ( χ2=4.72, 6.00, 6.86, 4.10, 4.95, and 4.24; P=0.030, 0.014, 0.009, 0.043, 0.026, and 0.040). The mortality rates of the PNI improvement group at the first and fourth follow-up periods were both lower than those of the PNI non-improvement group (4.3% (2/47) vs. 16.7% (9/54), 0 (0/24) vs. 23.4% (11/47)), and the differences were statistically significant ( χ2=3.99, Fisher′s exact test; P=0.046 and 0.012). There were no statistically significant difference in the incidence of complications between the PNI improvement group and the PNI non-improvement group at each follow-up period (all P>0.05). The Kaplan-Meier survival curve demonstrated that the average survival time of the high PNI group was longer than that of the low PNI group (17.54 months (95% confidence interval: 17.26 to 17.83 months) vs. 16.74 months (95% confidence interval: 16.96 to 17.52 months), and the difference was statistically significant ( χ2=9.18, P<0.001). The survival rate of the high PNI group at the 18th month of follow-up period was higher than that of the low PNI group (95.2% (256/269) vs. 86.5% (109/126), and the difference was statistically significant ( χ2=9.17, P=0.002). Conclusions:PNI has certain predictive efficacy for the survival period of patients with liver cirrhosis. Low-level PNI may increase the readmission rate, complication rate, and mortality of patients with liver cirrhosis, and shorten the survival period, indicating poor prognosis.

PURPOSE: The rate of complications among patients undergoing surgery has increased due to infection with SARS-CoV-2 and other variants of concern. However, Omicron has shown decreased pathogenicity, raising questions about the risk of postoperative complications among patients who are infected with this variant. This study aimed to investigate complications and related factors among patients with recent Omicron infection prior to undergoing orthopedic surgery. METHODS: A historical control study was conducted. Data were collected from all patients who underwent surgery during 2 distinct periods: (1) between Dec 12, 2022 and Jan 31, 2023 (COVID-19 positive group), (2) between Dec 12, 2021 and Jan 31, 2022 (COVID-19 negative control group). The patients were at least 18 years old. Patients who received conservative treatment after admission or had high-risk diseases or special circumstances (use of anticoagulants before surgery) were excluded from the study. The study outcomes were the total complication rate and related factors. Binary logistic regression analysis was used to identify related factors, and odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the impact of COVID-19 infection on complications. RESULTS: In the analysis, a total of 847 patients who underwent surgery were included, with 275 of these patients testing positive for COVID-19 and 572 testing negative. The COVID-19-positive group had a significantly higher rate of total complications (11.27%) than the control group (4.90%, p < 0.001). After adjusting for relevant factors, the OR was 3.08 (95% CI: 1.45-6.53). Patients who were diagnosed with COVID-19 at 3-4 weeks (OR = 0.20 (95% CI: 0.06-0.59), p = 0.005), 5-6 weeks (OR = 0.16 (95% CI: 0.04-0.59), p = 0.010), or ≥7 weeks (OR = 0.26 (95% CI: 0.06-1.02), p = 0.069) prior to surgery had a lower risk of complications than those who were diagnosed at 0-2 weeks prior to surgery. Seven factors (age, indications for surgery, time of operation, time of COVID-19 diagnosis prior to surgery, C-reactive protein levels, alanine transaminase levels, and aspartate aminotransferase levels) were found to be associated with complications; thus, these factors were used to create a nomogram. CONCLUSION Omicron continues to be a significant factor in the incidence of postoperative complications among patients undergoing orthopedic surgery. By identifying the factors associated with these complications, we can determine the optimal surgical timing, provide more accurate prognostic information, and offer appropriate consultation for orthopedic surgery patients who have been infected with Omicron.
Humans ; COVID-19/complications* ; Male ; Female ; Middle Aged ; Postoperative Complications/epidemiology* ; SARS-CoV-2 ; Orthopedic Procedures/adverse effects* ; Aged ; Nomograms ; Adult ; Retrospective Studies ; Risk Factors

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To explore the application of machine learning (ML) models based on radiomics and dosiomics to the assessment of hematologic toxicity (HT) in patients with locally advanced cervical cancer, and to preliminarily explore the comprehensive application of multi-omics features.Methods:A retrospective study was conducted on the clinical data, planning computed tomography (CT) images, and dose files of 205 patients with locally advanced cervical cancer who received concurrent chemoradiotherapy at the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, from January 2022 to June 2023. Patients were categorized according to the severity of HT. Radiomics and dosiomics features were extracted from the same regions of interest (ROIs), followed by feature selection utilizing a random forest algorithm. Then, radiomics, dosiomics, and hybrid models were established based on extreme gradient boosting (XGBoost). The classification performance of these models was assessed by calculating their sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).Results:The radiomics model yielded sensitivity, specificity, and AUC of 0.42, 0.86, and 0.78, respectively. The dosiomics model exhibited sensitivity, specificity, and AUC of 0.50, 0.90, and 0.74, respectively. In contrast, the hybrid model achieved sensitivity, specificity, and AUC of 0.50, 0.83, and 0.83, respectively. These findings suggest that the hybrid model possessed an enhanced classification capability compared to the individual radiomics and dosiomics models.Conclusions:It is feasible to use ML models based on radiomics and dosiomics to conduct the classification and prediction of HT in patients with locally advanced cervical cancer treated with concurrent chemoradiotherapy. Furthermore, integrating both radiomics features and dosiomics features can improve the classification performance of relevant prediction models, thus holding application potentials to optimize treatment strategies for patients with locally advanced cervical cancer.

Objective:To investigate the effects of prognostic nutritional index (PNI) on the readmission rate, complication rate, mortality rate and survival of patients with liver cirrhosis.Methods:From January 1, 2020 to December 31, 2022, 395 hospitalized patients with liver cirrhosis at Tianmen Hospital Affiliated to Wuhan University of Science and Technology were retrospectively enrolled. The clinical data were collected from the patients at their first hospitalization (baseline period) and re-hospitalization during follow-up period. The 18-month follow-up was divided into 4 periods, including the first period (from the 0th to the 3rd month), the second one was from the 4th to the 6th month, the third one was from the 7th to the 12th month, and the fourth one was from the 13th to the 18th month of follow-up. The prognostic value of PNI for patients with liver cirrhosis was evaluated through the receiver operating characteristic curve (ROC) of the baseline PNI. The 395 patients were divided into the low PNI group and the high PNI group based on the optimal cut-off value of PNI on the ROC. Patients readmitted during each follow-up period were divided into the PNI improvement group (PNI at follow-up -PNI at baseline>0) and the PNI non-improvement group (PNI at follow-up-PNI at baseline ≤0). Independent sample t-test, one-way analysis of variance (ANOVA), Mann-Whitney U test, chi-square test or Fisher′s exact test were used for statistical analysis. Survival curves depicting the relationship between PNI and overall survival rate of patients with liver cirrhosis were constructed using the Kaplan-Meier method. Results:The ROC analysis indicated that the optimal cut-off value of PNI at baseline was 32.65, with an area under the curve of 0.639 (95% confidence interval: 0.541 to 0.738, P=0.011), with a sensitivity of 0.567 and a specificity of 0.701. There were 269 cases in the high PNI group and 126 cases in the low PNI group. The readmission rate, complication rate and mortality rate in the low PNI group were all higher than those in the high PNI group at the first and fourth follow-up periods (32.5% (41/126) vs. 22.3% (60/269), 31.7% (40/126) vs. 20.4% (55/269), 6.3% (8/126) vs. 1.1% (3/269), 25.0% (29/116) vs. 16.2% (42/260), 25.0% (29/116) vs. 15.4% (40/260), 6.0% (7/116) vs. 1.5% (4/260)), and the differences were statistically significant ( χ2=4.72, 6.00, 6.86, 4.10, 4.95, and 4.24; P=0.030, 0.014, 0.009, 0.043, 0.026, and 0.040). The mortality rates of the PNI improvement group at the first and fourth follow-up periods were both lower than those of the PNI non-improvement group (4.3% (2/47) vs. 16.7% (9/54), 0 (0/24) vs. 23.4% (11/47)), and the differences were statistically significant ( χ2=3.99, Fisher′s exact test; P=0.046 and 0.012). There were no statistically significant difference in the incidence of complications between the PNI improvement group and the PNI non-improvement group at each follow-up period (all P>0.05). The Kaplan-Meier survival curve demonstrated that the average survival time of the high PNI group was longer than that of the low PNI group (17.54 months (95% confidence interval: 17.26 to 17.83 months) vs. 16.74 months (95% confidence interval: 16.96 to 17.52 months), and the difference was statistically significant ( χ2=9.18, P<0.001). The survival rate of the high PNI group at the 18th month of follow-up period was higher than that of the low PNI group (95.2% (256/269) vs. 86.5% (109/126), and the difference was statistically significant ( χ2=9.17, P=0.002). Conclusions:PNI has certain predictive efficacy for the survival period of patients with liver cirrhosis. Low-level PNI may increase the readmission rate, complication rate, and mortality of patients with liver cirrhosis, and shorten the survival period, indicating poor prognosis.

B cell receptor(BCR)is the main molecular basis for B cell specific recognition and binding of antigen,and its complementarity determining region(CDR3)presents high diversity and specificity.Using single-cell immune repertoire sequencing technology can accurately analyze the composition and characteristics of each B cell BCR CDR3 sequence,and can better understand the process and mechanism of B cell differentiation,development,and response.Single-cell immune repertoire sequencing technology provides new ideas and theoretical basis for the pathogenesis,monitoring,diagnosis and treatment of B-cell immune-related diseases.This paper mainly compares and analyzes the commonly used detection methods and detection platforms of B-cell BCR CDR3 receptor library,and focuses on the application,research status and progress of single-cell sequencing technology in B-cell BCR CDR3 recep-tor library.