OBJECTIVE: To investigate the genetic etiology of a fetus diagnosed with Mandibulofacial dysostosis with microcephaly (MFDM). METHODS: A fetus that underwent prenatal diagnosis at Beijing Obstetrics and Gynecology Hospital, Capital Medical University, on May 19, 2025 was selected for analysis. Results of fetal ultrasound findings, chromosomal karyotyping, copy number variation sequencing (CNV-seq), and whole-exome sequencing (WES) were collected. Sanger sequencing was performed for familial validation of the pathogenic variant. The Human Protein Atlas (HPA), STRING, and Simple ClinVar databases were queried to characterize the biological features of the candidate gene. Three-dimensional structures of the wild-type and variant proteins were modeled and analyzed, and the evolutionary conservation of the affected amino acid was assessed using UGENE. Prenatal phenotypes associated with EFTUD2 variants were summarized through a review of the literature. This study was approved by the Ethics Committee of Beijing Obstetrics and Gynecology Hospital, Capital Medical University (Ethics No.: 2025-KY-029-01). RESULTS: At 23⁺² weeks of gestation, ultrasound examination revealed bilateral microtia with low-set ears, mild micrognathia with a reduced mandibular-facial angle, a single umbilical artery, a slightly narrow aortic diameter, and trivial mitral regurgitation. Amniotic fluid karyotyping and CNV-seq showed no abnormalities. WES identified a de novo, previously unreported EFTUD2 variant, c.698dupA (p.V235Gfs*27), in the fetus. This frameshift variant is predicted to alter the structural integrity of the EFTUD2 protein. Literature review indicated that micrognathia and microtia or low-set ears are the most common sonographic features in fetuses with EFTUD2 variants, while secondary findings may include abnormal stomach bubble, cleft palate, single umbilical artery, gastrointestinal atresia, polyhydramnios, and reduced aortic diameter. CONCLUSION The EFTUD2: c.698dupA (p.V235Gfs*27) variant is likely the genetic cause underlying MFDM in this fetus.
Humans ; Mandibulofacial Dysostosis/diagnostic imaging* ; Microcephaly/diagnostic imaging* ; Female ; Pregnancy ; Ribonucleoprotein, U5 Small Nuclear/chemistry* ; Peptide Elongation Factors/chemistry* ; Fetus ; DNA Copy Number Variations/genetics* ; Adult ; Ultrasonography, Prenatal

[摘 要] 目的：探讨m6A调控因子在宫颈癌预后评估、免疫微环境特征及治疗反应中的作用，构建基于m6A调控因子的预后风险模型，并分析其与免疫浸润、药物敏感性及细胞间通信的关系。方法：基于TCGA和GEO数据库中宫颈鳞癌及腺癌（CESC）转录组数据，分析22个m6A调控因子的表达与突变情况；采用LASSO‑Cox回归构建m6A相关预后风险模型，并依据风险评分将患者分为高、低风险组。利用CIBERSORT和ESTIMATE算法评估两组免疫细胞浸润及微环境特征；通过oncoPredict预测抗肿瘤药物敏感性。整合单细胞转录组数据（E-MTAB-12305），采用CellChat分析细胞间通信网络。结果：共鉴定出12个在宫颈癌中差异表达的m6A调控因子。高风险组患者总生存期缩短（P < 0.05），免疫评分降低，且对紫杉醇、氟尿嘧啶、多柔比星等抗肿瘤药物敏感性较差（IC50较高）。单细胞分析显示宫颈癌组织中细胞间通信网络发生改变，其中T细胞与内皮/上皮细胞间的相互作用可能主要由CCL5‑ACKR1和MIF‑（CD74 + CXCR4）配体‑受体介导。在临床样本中，对关键的m6A调控因子进行mRNA和蛋白水平的验证，结果显示部分调控因子在宫颈癌组织中的表达水平高于正常宫颈组织（P < 0.05）。结论：m6A调控因子特征可有效预测宫颈癌患者预后，其风险评分与肿瘤免疫浸润、药物敏感性及细胞通信密切相关，为宫颈癌的预后分层及个体化治疗提供了新的分子依据。

ObjectiveTo elucidate the effects of autonomic neuromodulators [calcium chloride (CaCl₂)-acetylcholine (ACh)] on atrial electrical remodeling and histopathological changes in rats, thereby providing evidence for further investigation into the pathological mechanisms by which autonomic imbalance induces atrial fibrillation (AF). MethodsTen 8-week-old male Sprague-Dawley (SD) rats were randomly divided into experimental and control groups, with 5 rats in each group. The experimental group received daily tail vein injections of a CaCl₂-ACh mixed solution for 28 days, while the control group received an equal volume of saline. Surface electrocardiograms were recorded before and after daily administration. On day 28 of administration, under isoflurane inhalation anesthesia, echocardiography was performed, and then the rats were euthanized by exsanguination under isoflurane anesthesia for tissue collection. Body weight and heart weight of rats were measured, and electrophysiological parameters including AF inducibility, conduction velocity, and conduction dispersion in isolated rat hearts were monitored using the MappingLab multichannel electrophysiological mapping system. HE staining was performed to evaluate atrial tissue architecture and inflammatory cell infiltration. The expression levels of matrix metalloproteinase 9 (MMP-9) and interleukin-1 beta (IL-1β) were analyzed by Western blotting. Masson staining was used to quantitatively analyze the proportional distribution of collagen fibers and myocardial fibers, and to calculate the area of collagen deposition, thereby evaluating the degree of myocardial fibrosis. Wheat germ agglutinin (WGA) staining was used to evaluate morphological changes of cardiomyocytes. Dihydroethidium (DHE) staining was used to detect the level of oxidative stress in atrial myocytes. Terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) staining was used to detect atrial cell apoptosis. ResultsCompared with the control group, the experimental group showed obvious arrhythmias on electrocardiograms. Echocardiography after 28 days of administration revealed significant structural remodeling in the experimental group, with a marked increase in left atrial anteroposterior diameter (P < 0.05), and also showed cardiac dysfunction, with significant decreases in left ventricular ejection fraction and left ventricular fractional shortening (P < 0.01). Compared with the control group, the experimental group showed a significantly increased heart weight-to-body weight ratio (P < 0.05), a markedly higher AF inducibility (P < 0.001), a significantly slowed atrial conduction velocity (P < 0.05), an uneven isochronal map with irregular directions, and a significantly increased conduction dispersion (P < 0.01). HE staining showed that atrial myocytes in the experimental group were disorganized, with slight inflammatory cell infiltration. Western blotting showed that the expression levels of MMP-9 and IL-1β in the atrial tissue of the experimental group were significantly upregulated (P < 0.05). Masson staining showed a significant increase in collagen deposition and a significant increase in fibrosis area in the atrial tissue of the experimental group (P < 0.001). WGA staining showed that cardiomyocytes in the experimental group were significantly hypertrophied compared with the control group (P < 0.05). DHE staining and TUNEL staining revealed that the level of oxidative stress in atrial myocytes (P < 0.001) and the apoptotic rate (P < 0.01) were both significantly increased. Conclusion Daily tail vein injections of the autonomic neuromodulator CaCl₂-ACh mixed solution for 28 days can successfully induce AF in rats, accompanied by significant atrial structural remodeling, electrical remodeling, and oxidative stress.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

OBJECTIVE To construct a predictive tool for surgical site infections(SSIs)in spinal surgery for Chi-nese population to provide evidence support for reducing SSIs.METHODS A systematic review of Chinese and English database literature was conducted for Meta-analysis to obtain pooled risk values for influencing factors,and a risk prediction scoring tool was constructed based on the logistic regression model.Patients who underwent spinal surgery and completed postoperative follow-up in a tertiary hospital in Beijing from Jan.to Dec.2021 were selected to validate the predictive effect of the tool.RESULTS The predictive model for SSIs in Chinese spinal sur-gery patients was Logit(P)=—3.47+0.63(age 60 years)+0.31 ×(patient with cardiovascular disease)+0.69 ×(rheumatoid arthritis)+1.07 ×(diabetes)+1.06 ×(operation duration＞3 h)+1.17 ×(preopera-tive albumin＜35 g/L)+0.71 ×(history of spinal surgery)+0.67 ×(carrying internal implants)+0.73 ×(blood transfusion).The total score of the predictive tool was 92,with a cutoff score of≥24.50 indicating high-risk individuals.The area under the curve was 0.733,with the sensitivity 58.30％and the specificity 79.60％.CONCLUSION The established predictive model for SSIs in Chinese spine surgery demonstrates good predictive performance and can be used as a reference assessment tool in clinical practice.

Objective:To investigate the risk factors and their predictive efficacy for early postoperative complications in elderly patients with hip fracture.Methods:A retrospective cohort study was conducted on the clinical data of 203 elderly patients with hip fracture admitted to the 908th Hospital of the Joint Logistics Support Force of the PLA and the First Affiliated Hospital of Nanchang University from January 2022 to December 2023, including 54 males and 149 females, aged 65-100 years [(80.5±7.7)years]. There were 96 patients with femoral neck fracture and 107 patients with intertrochanteric fracture. According to the AO/OTA classification, the fracture was classified as type 31A in 107 patients and type 31B in 96. Among them, 81 patients were treated with proximal femoral nail antirotation (PFNA), 65 with semi-hip arthroplasty, 52 with total hip arthroplasty (THA), and 5 with closed reduction and cannulated nail internal fixation. The patients were divided into complication group ( n=65) and non-complication group ( n=138) according to whether complications (mainly including delirium, lung infection, stress ulcer, and deep vein thrombosis of the lower limbs) occurred within 15 days after surgery. The gender, age, age stage, educational level, cause of injury, associated underlying diseases before surgery, AO/OTA classification, American Society of Anesthesiologists (ASA) classification, 5-factor modified frailty index (mFI-5) score, prognostic nutritional index (PNI), anesthesia method, operation method, operation time, intraoperative blood loss, length of hospital stay, etc., were recorded in the two groups. Univariate analysis and multivariate binary logistic regression analysis were used to evaluate the correlation between the above indexes and the occurrence of early postoperative complications in elderly patients with hip fracture and to determine their independent risk factors. The receiver operating characteristic (ROC) curve was plotted and the area under the curve (AUC) was calculated to evaluate the predictive efficacy of each risk factor for the occurrence of early postoperative complications in elderly patients with hip fracture. Results:Univariate analysis showed a certain correlation between age, age stage, associated underlying diseases before surgery, AO/OTA classification, ASA classification, mFI-5 score, PNI, operation method, and length of hospital stay and the occurrence of early postoperative complications in elderly patients with hip fracture ( P<0.05), while gender, educational level, cause of injury, anesthesia method, operation time, and intraoperative blood loss were not correlated with the occurrence of early postoperative complications in elderly patients with hip fracture ( P>0.05). The results of multivariate binary logistic regression analysis showed that the associated underlying diseases before surgery ( OR=5.46, 95% CI 1.33, 22.39, P<0.05), mFI-5 score ( OR=15.90, 95% CI 5.36, 47.15, P<0.01), and PNI ( OR=0.70, 95% CI 0.60, 0.81, P<0.01) were significantly correlated with the occurrence of early postoperative complications in elderly patients with hip fracture. The results of ROC curve analysis showed that mFI-5 score (AUC=0.85, 95% CI 0.80, 0.91) and PNI (AUC=0.87, 95% CI 0.82, 0.93) had moderate predictive efficacy, while the early warning efficacy of associated underlying diseases was low (AUC=0.54, 95% CI 0.45, 0.62). The combination of the above risk factors was more effective in predicting early postoperative complications in elderly patients with hip fracture (AUC=0.95, 95% CI 0.92, 0.98). Conclusions:The mFI-5 score, PNI, and associated underlying diseases before surgery are independent risk factors for early postoperative complications in elderly patients with hip fracture. The mFI-5 score and PNI have a higher predictive efficacy than associated diseases before surgery on the occurrence of early postoperative complications in elderly patients with hip fracture, while the combination of the above risk factors provides a significantly better predictive performance.

Objective:To investigate the feasibility of the bortezomib, lenalidomide, and dexamethasone (VRD) regimen combined with autologous hematopoietic stem cell transplantation (auto-HSCT) in patients with multiple myeloma (MM) and renal impairment, analyze treatment efficacy and renal responses stratified based on renal dysfunction severity, and explore the prognostic significance of early renal response and its affecting factors.Methods:This retrospective study, conducted at the First Affiliated Hospital of Soochow University, categorized 316 patients with newly diagnosed MM (NDMM) from August 2018 to October 2022 based on renal function for analysis of clinical characteristics, treatment response, and prognosis. Continuous variables were compared using t-tests or Mann-Whitney U tests, categorical variables utilizing Chi-square tests, survival outcomes employing Kaplan-Meier and Log-rank tests, and renal response predictors with logistic regression.Results:Patients were stratified based on baseline estimated glomerular filtration rate (eGFR) : normal [≥90 ml·min -1· (1.73 m 2) -1, n=160], mild [≥60 ml·min -1· (1.73 m 2) -1 to <90 ml·min -1· (1.73 m 2) -1, n=55], moderate [≥30 ml·min -1· (1.73 m 2) -1 to <60 ml·min -1· (1.73 m 2) -1, n=39], and severe impairment [<30 ml·min -1· (1.73 m 2) -1, n=62]. Moderate and severe renal impairment correlated with advanced International Staging System/Revised International Staging System classification, lower hemoglobin levels, frailty, and higher light-chain/IgD subtype prevalence ( P<0.05). Despite younger age ( P=0.001) and higher transplant rates ( P=0.041) in severe cases, overall response rates ( ORR: 93.7% ; ≥VGPR: 82.9% ) were comparable across groups ( P>0.05). Among 24 dialysis-dependent patients at diagnosis, 11 (45.8% ) achieved dialysis independence after induction [median: 3.0 (0.5–4.0) months], including 10 undergoing auto-HSCT. In 89 evaluable patients [baseline eGFR <50 ml·min -1· (1.73 m 2) -1], renal ORR (RORR) was 70.8% [rapid complete response: 31.5% ; rapid partial response: 11.2% ; rapid minimal response (RMR) : 28.1% ]. Renal response predicted better survival (overall survival: HR=0.36, 95% CI: 0.13–0.99, P=0.049). Moderate-to-severe renal impairment was associated with increased transplant-related adverse events and delayed engraftment ( P<0.05) ; however, auto-HSCT significantly improved outcomes after 33.5-month median follow-up (range: 2–65 months). Multivariate analysis identified 1q21+ ( OR=3.58, 95% CI: 1.17–11.02, P=0.026) and light-chain subtype ( OR=2.86, 95% CI: 1.08–7.69, P=0.036) as independent predictors of poor renal response. Conclusion:VRD regimen plus auto-HSCT demonstrates robust efficacy in NDMM, including patients with renal impairment, with a 70.8% RORR and manageable toxicity. Achieving ≥RMR correlates with superior prognosis, whereas 1q21+ and light-chain subtype independently predict inferior renal response.