Objective: To investigate factors influencing perioperative blood transfusion in patients with scarred uterus during pregnancy undergoing cesarean section, construct and validate a transfusion risk prediction model, and provide evidence for preoperative assessment and blood management. Methods: Clinical data of 405 patients undergoing cesarean section for scarred uterus during pregnancy at the First Affiliated Hospital of Xi'an Jiaotong University from January 2020 to December 2024 were retrospectively collected. The dataset was randomly divided into a training set (n=284) and a validation set (n=121) at a 7∶3 ratio. Within the training set, Firth-penalized logistic regression was employed for multivariate analysis to identify independent factors influencing perioperative blood transfusion and construct a predictive model. Model performance was evaluated in the validation set. Results: Multivariate Firth regression analysis showed that severe placenta previa (OR=75.566, 95%CI: 8.603-9979.174) and placenta accreta (OR=4.591, 95%CI: 1.120-19.416) were independent risk factors for perioperative blood transfusion, while preoperative red blood cell count (OR=0.189, 95%CI: 0.083-0.405) and fibrinogen levels (OR=0.588, 95%CI: 0.395-0.855) were protective factors. The predictive model constructed based on these four variables demonstrated good discriminatory performance, with areas under the receiver operating characteristic curves of 0.803 (95%CI: 0.740-0.867) and 0.753 (95%CI: 0.644-0.862) in the training and validation sets, respectively. Conclusion: For patients with scarred uterus during pregnancy undergoing cesarean section, severe placenta previa and placenta accreta significantly increase the risk of transfusion, while higher preoperative red blood cell count and fibrinogen levels exert a protective effect. The predictive model established in this study facilitates the identification of patients requiring transfusion, thereby enabling preoperative blood preparation and optimized blood management.

Neurodegenerative diseases such as Alzheimer's disease （AD）， Parkinson's disease （PD）， and Huntington's disease （HD） are increasingly becoming major challenges to global public health. The pathogenesis of these diseases is highly complex， with oxidative damage and ferroptosis emerging as potential core factors. Oxidative damage primarily results from the accumulation of reactive oxygen species （ROS） within cells， a process that impairs cellular function and viability. Ferroptosis， an iron-dependent form of programmed cell death， plays a crucial role in neuronal injury and apoptosis. Multiple studies indicate a significant interaction between oxidative damage and ferroptosis. This interplay not only accelerates the progression of neurodegenerative diseases but also offers new directions for potential therapeutic targets. This review systematically analyzes the mechanisms of oxidative damage and ferroptosis in various neurodegenerative diseases， evaluates current research frontiers， and explores feasible therapeutic strategies， aiming to provide new insights and perspectives for in-depth research in this field.

Background/Aims: Natural killer (NK) cell function is generally considered dampened in chronic hepatitis B virus (HBV) infection; however, the NK cell pool exhibits phenotypic and functional heterogeneity, and the antibody--mediated effect of NK cells remains less characterized. This study evaluated the dynamic changes in antibody-mediated NK cell responses and the involvement of distinct NK subsets across disease stages and during antiviral treatment. Methods: A T-cell receptor-like antibody specific for the HBV core 18–27 peptide (cTCRL-Ab) was used to determine the antibody-mediated effect of NK cells, and an array of NK cell surface markers were analyzed in cross-sectional and longitudinal cohorts of patients with chronic HBV infection. Single-cell RNA sequencing (scRNA-seq) was performed to identify the heterogeneity of NK subsets. Results: The cTCRL-Ab enabled the detection of NK cell cytolytic activity and IFNγ production. Notably, cTCRL-Ab-mediated NK cell responses were compromised in chronically HBV-infected patients, particularly in those receiving pegylated interferon-α (Peg-IFNα), which was associated with the downregulation of CD16 expression. Correspondingly, Peg-IFNα inhibited cTCRL-Ab-mediated NK cell function by reducing CD16 expression in vitro. scRNA-seq revealed that CD16 downregulation occurred mainly within a dysfunctional CD16hi NK subset exhibiting exhaustion properties. In contrast, an activated CD16hiNK subpopulation (CX3CR1⁺KLRC2–CD16hi) with high cytotoxicity was enriched in patients who experienced favorable treatment responses. Furthermore, the intrahepatic CX3CR1+KLRC2–CD16hi subset tended to exhibit functional restoration in HBsAg-loss individuals. Conclusions Our data contribute to the understanding of antibody-mediated responses of NK cells in chronic HBV infection, and highlight a previously unappreciated functional CX3CR1+KLRC2–CD16hiNK subset as a potential therapeutic target.

Objective To identify novel biomarkers for predicting the risk of latent tuberculosis infection(LTBI)activation using bio-informatics and machine-learning algorithms and to establish a risk model.Methods The GSE112104 and GSE193777 datasets were obtained from the Gene Expression Omnibus.Differential gene expression and weighted gene co-expression network analyses were per-formed to identify ferroptosis-related differentially expressed genes(FRG-DEGs)associated with LTBI activation.Three machine-learning algorithms,least absolute shrinkage and selection operator,support vector machine-recursive feature elimination,and random forest,were used to identify ferroptosis-related hub genes(FRG-hubs).The reliability of these genes was validated using independent validation datasets and reverse transcription polymerase chain reaction(PCR).A risk model was established using R software.Results In the GSE 112104 dataset,296 genes were upregulated and 1 569 genes were downregulated in active tuberculosis compared to those in LTBI.Among the LTBI progressors,506 genes were upregulated and 1 132 genes were downregulated.Weighted correlation network analysis identified five gene modules,with the blue module showing the strongest correlation with LTBI activation(cor=0.62,P=0.000 04),con-taining 1 340 genes.Intersections with 728 ferroptosis-related genes resulted in eight FRG-DEGs.The machine-learning algorithms iden-tified four FRG-hubs:PLA2G6,GLS2,JUN,and AMN,whose expression decreased with LTBI activation.Reverse transcription PCR con-firmed this trend.A risk model based on these genes yielded an area under the curve of 0.98 to 1.00.Conclusion This study successfully identified novel biomarkers for predicting the risk of LTBI activation and developed an accurate predictive risk model.

[Purpose]To analyze the changes in the incidence trend of thyroid cancer from 1990 to 2021,and to predict the future incidence from 2022 to 2030.[Methods]We collected data related to the incidence of thyroid cancer among Chinese residents from 1990 to 2021 in the Global Bur-den of Disease 2021(GBD 2021)study,analyzed the trend of thyroid cancer incidence using the Joinpoint regression model,and constructed a Bayesian age-period-cohort(BAPC)model to pre-dict the future incidence of thyroid cancer during the years of 2022-2030,based on the inci-dence data during the years of 1990-2021.[Results]From 1990 to 2021,the age-standardized incidence rate(ASIR)of thyroid cancer in China showed a fluctuating upward trend,and the ASIR of thyroid cancer in China in 2021 was 2.47/105,slightly lower than the global average(2.91/105)in the same year.In 2021,there were significant differences in new cases and incidence rate of thyroid cancer between men and women,with the incidence rate of women being higher than that of men.Among them,the number of new cases in women was 27 915,the crude incidence rate was 4.02/105,and the ASIR was 2.87/105;in men,the number of new cases was 20 189,the crude incidence rate was 2.77/105,and the ASIR was 2.11/105.Between 1990 and 2021,the increase in the number of new cases,the crude incidence rate,and the ASIR of men in China was much larger than that of women.The ASIR of thyroid cancer in both male and female showed an in-creasing trend,while the average annual percentage change(AAPC)in female was lower than that in male.There were significant gender differences in the age-specific incidence rates of thyroid cancer.In 2021,the incidence rate of women was higher than that of men in the Chinese population＜75 years old,whereas the incidence rate of men was higher than that of women in the population≥75 years old.From 1990 to 2021,the incidence rates of the Chinese male population aged 45～59 years old and ≥75 years old increased significantly;and the incidence rate of the Chinese fe-male popu-lation aged 50～74 years old increased significantly.Projections showed that the ASIR of overall,male and female standardized incidence rates in 2030 increased to 2.90/105,2.44/105 and 3.26/105 respectively.[Conclusion]The incidence rate of thyroid cancer in China is on the rise,with the incidence rate of women being higher than that of men,but the incidence rate of men has increased more than that of women,and the gap between the incidence rates is narrow-ing,and the peak age of incidence of men is mostly in the senior age group.

Esophageal cancer is one of the most prevalent malignant tumors globally.Its clinical management is challenged by difficulties in early diagnosis,significant inter-individual variability in therapeutic efficacy,and high rates of tumor residuals and recurrence.Circulating tumor DNA(ctDNA),a novel liquid biopsy biomarker,reflects tumor burden and genetic characteristics.It offers advantages such as non-invasiveness,repeatability,and real-time dynamic monitoring,pro-viding a promising approach for precision diagnosis and treatment of esophageal cancer.In recent years,ctDNA has shown remarkable progress in the early detection,efficacy prediction,prognos-tic assessment,and monitoring of tumor residuals and recurrence in esophageal cancer,emerging as an essential tool in the clinical management of the disease.This review summarizes the latest advancements in ctDNA research in esophageal cancer,providing valuable insights and inspiration for future studies and clinical applications.

Objective:To explore the molecular mechanism by which the methionine adenosyltransferase 2A (MAT2A)/β-catenin/zinc finger E-box binding homeobox 1 (ZEB1)/epithelial-mesenchymal transition (EMT) pathway regulates neural tube defect (NTD) through intracellular S-adenosylmethionine (SAM).Methods:A mouse NTD model was induced using the SAM metabolic disorder inhibitor ethionine. Eighty specific pathogen-free C57BL/6 mice were divided into three groups: a normal group (36 mice), an ethionine group (46 mice), and an ethionine+SAM group (44 mice). Phosphate-buffered saline (PBS), ethionine, and ethionine+SAM were respectively injected intraperitoneally on embryonic day 7.5 (E7.5), and the mice were sacrificed on E10.5. Embryonic tissues were collected, and the morphology of embryos in each group was observed under a stereomicroscope. The interaction between ethionine and MAT2A was analyzed using Autodock software. The expression levels of MAT2A, β-catenin, ZEB1, and EMT-related proteins in the brain tissues of embryos from the three groups were measured using immunofluorescence, immunohistochemistry, Western blotting, enzyme-linked immunosorbent assay (ELISA), and real-time quantitative polymerase chain reaction (RT-qPCR). Variance analysis was used for intergroup comparisons.Results:(1) Autodock analysis results showed that MAT2A binds to ethionine through covalent bonds, exhibiting a complementary effect, thereby accelerating the expression of MAT2A. (2) After successful construction of the NTD model, normal embryos were plump with well-developed brains. NTD embryos showed delayed development, obvious anencephaly, unclosed neural tubes, and asymmetry. (3) The levels of SAM and SAH in the embryonic tissues of the ethionine group were significantly lower than those in the normal group (1 737.56±95.64 vs. 872.33±205.11, and 89.17±9.50 vs. 51.25±9.48, respectively). The SAM and SAH levels in the ethionine+SAM group was 1 197.00±222.27 and 66.61±12.25, significantly higher than those in the ethionine group ( P<0.017). Compared with the normal group and the ethionine+SAM group, the expression of MAT2A mRNA in the embryonic brain tissue of the ethionine group was significantly upregulated (1.00±0.00, 1.59±0.52, and 2.42±0.53, respectively, F=49.64, P<0.001; pairwise comparisons between groups P<0.017). (4) Compared with the normal group, the expression of Ctnnb1 in the ethionine group was reduced, and the expression of Ctnnb1 in the ethionine+SAM group was higher than that in the ethionine group (1.00±0.00, 0.38±0.16, and 0.76±0.10, respectively, F=149.03, P<0.001; pairwise comparisons between groups P<0.017). (5) The expression of ZEB1 in the ethionine group was higher than that in the normal group and the ethionine+SAM group (2.91±0.55, 1.00±0.00, and 1.61±0.20, respectively, F=150.01, P<0.001; pairwise comparisons between groups P<0.017). (6) The expression levels of E-cadherin and Vimentin in the ethionine group were lower than those in the normal group. In contrast, the expression of N-cadherin was higher than that in the normal group. After SAM supplementation, the expression levels of E-cadherin and Vimentin were upregulated, and the expression level of N-cadherin was downregulated (0.54±0.12, 1.00±0.00, and 0.72±0.14, respectively, F=87.44; 0.53±0.17, 1.00±0.00, and 0.76±0.09, F=87.44; 3.11±0.53, 1.00±0.00, and 2.13±0.56, F=95.54; all P<0.001; pairwise comparisons within the same index group P<0.017]). Conclusions:Ethionine promotes the expression of MAT2A, leading to reduced SAM production. Ethionine regulates the level of ZEB1 by increasing MAT2A and inhibits the EMT process to interfere with methionine cycle metabolism, ultimately resulting in NTD.

Objective To investigate the clinical diagnostic value of serum sTREM2 level in patients with cerebral small vessel disease(CSVD)and its correlation with depression and its severity.Methods A total of 208 CSVD inpatients admitted in Department of Neurology of the First Affiliated Hospital of Shihezi University from December 2023 to November 2024 were en-rolled,and according to their score of HAMD,they were divided into a depression group(CSVD+D group,112 cases)and a non-depression group(CSVD—D group,96 cases).According to the 17-item HAMD,the depression group(CSVD+D group)was further divided into mild(8-17,n=80),moderate(18-24,n=27)and severe depression(≥25,n=5)subgroups.Another 208 healthy individuals who taking health checkups in the same period were selected and served as the control group.The general clinical data were compared among the groups and subgroups,and mul-tivariate logistic regression analysis was applied to identify the risk factors for the occurrence of depression and the relationship between sTREM2 and depression severity in the CSVD patients.ROC curve was plotted to evaluate the predicative performance of serum sTREM2 level for the occurrence of depression in the CSVD patients.Results The serum sTREM2 level was remark-ably higher in the CSVD patients than the control group(5.95±3.82 μg/L vs 1.40±1.21 μg/L,P＜0.01).ROC curve analysis indicated that the AUC value of serum sTREM2 level in predicting CSVD was 0.917,with a sensitivity of 87.52％and a specificity of 85.64％,and an optimal cut-ff value of 2.272 μg/L.The CSVD+D group also had significantly higher serum sTREM2 level than the CSVD—D group(6.40±3.93 μg/L vs 5.01±2.87 μg/L,P＜0.01).Multivariate logistic regression analysis showed that serum sTREM2 level was an independent influencing factor for occurrence of depression in the CSVD patients(OR=1.115,95％CI:1.019-1.220,P=0.018).Statistical difference was also observed in the patients without and with mild,moderate and severe depression(P＜0.05).Multivariate ordinal logistic regression analysis revealed that serum sTREM2 level was an independent influencing factor for mild,moderate and severe depression(OR=1.113,95％CI:1.013-1.223,P=0.026;OR=1.135,95％CI:1.004-1.284,P=0.043).The AUC value of serum sTREM2 level in predicting depressive symptoms in CSVD patients was 0.603.Conclusion Serum sTREM2 is closely associated with CSVD patients.Its level may provide certain reference value for clinical diagnosis of CSVD,and has potentially predictive value for the occurrence of depression in the CSVD patients.

Alzheimer's disease(AD), a neurodegenerative disorder associated with aging, is the most prevalent form of dementia.As the aging population continues to expand, AD presents significant health and caregiving challenges for families and society, making it a pressing international public health concern.In recent years, numerous countries have implemented dementia prevention and treatment strategies that emphasize community-based comprehensive approaches.Currently, the community-based AD prevention and treatment model in China is still in the exploratory phase, with community efforts lacking organization.In alignment with China's action plan for advancing dementia prevention and treatment, and to achieve the strategic objective of "healthy aging, " this consensus is based on the principle of three-level prevention and is tailored to the characteristics of AD disease progression.It aims to develop a comprehensive prevention and treatment strategy for AD that is suitable for communities in China, providing technical guidance and support to establish a scientific basis for formulating community AD prevention and treatment models.

Objective To establish the reference interval of urine Alzheimer-associated neuronal thread protein(AD7c-NTP)for healthy adults in Mianyang area using the indirect method.Methods The detection results of urine AD7c-NTP from 5 093 healthy in-dividuals were collected from the information management database of Medical Laboratory Department of Sichuan Science City Hospital from March 2017 to March 2022.Skewness-kurtosis and Kolmogorov-Smirnov tests were used to determine whether the data followed a normal distribution.After removing outliers using the Box Plots method,the enrolled subjects were grouped by gender and age.The Mann-Whitney U or Kruska-Wallis H tests were used to analyze the between-group differences of urine AD7c-NTP in healthy individu-als with different genders and ages.The adjacent age groups without statistically significant difference(P＞0.05)were combined,and the indirect method(non-parametric test method)was used to calculate the reference intervals for different gender and age groups.Results Skewness-kurtosis and Kolmogorov-Smirnov tests showed that the data followed a non-normal distribution.After removing 293 outliers using the Box Plots method,a total of 4 800 subjects,including 3 199 males and 1 601 females,were enrolled.The enrolled subjects were grouped by gender and age,and the non-parametric test method were used to establish the reference intervals of urine AD7c-NTP in healthy populations with different genders.The Mann-Whitney U test confirmed that urine AD7c-NTP levels existed gen-der differences(Z=14.09,P＜0.01),and the reference intervals for males and females were≤1.10 ng/mL and≤1.40 ng/mL,re-spectively.There were also statistical differences in urine AD7c-NTP levels among different age groups of the same gender.After combi-ning adjacent age groups without statistically significant difference(P＞0.05),the reference intervals of urine AD7c-NTP in healthy populations with different genders and ages were established by the non-parametric test method,which were≤1.00 ng/mL for male 20-39 years old group,≤1.10 ng/mL for male 40-79 years old group,≤1.60 ng/mL for male≥80 years old group,≤1.30 ng/mL for female 20-69 years old group,and≤1.60 ng/mL for female≥70 years old group,respectively.The established reference intervals of urine AD7c-NTP were further verified by healthy individuals,and the results met the standards.Conclusion The reference intervals of urine AD7c-NTP in healthy populations with different genders and ages in Mianyang area are established successfully using the indi-rect method,which may help to predict the risk of Alzheimer's disease in clinical practice and provide support for the diagnosis and treatment of the disease.