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

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 explore the health issues and influencing factors of workers in new forms of employment, represented by couriers and food delivery workers, based on the social-ecological model (SEM). Methods A total of 44 couriers and food delivery workers from Beijing City, Shanghai City, Guangzhou City, and Chongqing City were recruited as the study subjects using purposive sampling combined with snowball sampling method. An interview guide was developed based on the SEM to conduct semi-structured interviews. Thematic analysis was employed to code and analyze the interview data. Results The health influencing factors among the couriers and food delivery workers based on the SEM included three first-level themes at the micro-, meso-, and macro-levels, namely "individual factors," "occupational environmental factors," and "social environmental factors," each comprising three second-level themes. At the micro-level, individual factors such as insufficient health literacy, unhealthy lifestyles and behaviors, and sustained psychological burden jointly contributed to the health vulnerability among these couriers and food delivery workers. At the meso-level, occupational environmental factors including algorithmic management, high-load work environments, and inadequate interpersonal support, jointly construct a high-pressure and high-intensity work pattern. At the macro-level, social environmental factors such as insufficient social security caused by the de facto nature of labor relations, economic pressure resulting from unstable income in the market environment, and psychological depletion caused by occupational discrimination further exacerbate the health vulnerability among these workers. Conclusion The health issues of the couriers and food delivery workers result from the interplay of factors across micro-, meso-, and macro- levels. Therefore, a multi-level collaborative health protection system involving individuals, organizations, and society should be established to improve their health status.

To summarize the clinical experience of Professor LIU Shangyi in treating pruritus vulvae. It is believed that women have the physiological characteristics of liver and kidney as the root， and their pubic area is easily attacked by wind-dampness pathogenic qi， so the core mechanism of pruritus vulvae is proposed as wind-dampness accumulation and deficiency of liver and kidney. The core treatment method is to dispel wind-dampness and nourish the liver and kidneys， and modify the Danggui Decoction （当归饮子） to form a self-prescribed Yinyang Formula （阴痒方） as the basic prescription to treat pruritus vulvaen.

Objective To analyze the influencing factors of chronic atrophic gastritis diagnosed by gastroscopy based on living habits and cytochrome P4501A1(CYP1A1)gene polymorphism.Methods A total of 118 patients with chronic atrophic gastritis diagnosed by gastroscopy in our hospital from May 2023 to May 2024 were included in the chronic atrophic gastritis group,and another 120 patients with chronic non-atrophic gastritis diagnosed by gastroscopy during the same period were included in the chronic non-atrophic gastritis group.Clinical data,lifestyle,gastroscopy and CYP1A1 gene polymorphism were compared between the two groups.The risk factors of chronic atrophic gastritis diagnosed by gastroscopy were analyzed by multivariate Logistic regression,and the regression equation was established.Receiver operating characteristic curve(ROC curve)was drawn to analyze the predictive value of the regression equation for the diagnosis of chronic atrophic gastritis by gastroscopy.Results Multivariate Logistic analysis showed that Helicobacter pylori infection,family history of gastritis,fast eating,hot eating,insomnia,CYP1A1 genotype G/G were the risk factors for the diagnosis of chronic atrophic gastritis by gastroscopy(P<0.05).The above factors were included in the regression equation:Logit(P)=-8.252+Helicobacter pylori infection×0.741+family history of gastritis×0.636+fast food×0.595+hot food×0.754+insomnia×0.791+CYP1A1 genotype G/G×0.752.According to the regression equation,ROC curve was drawn to predict the occurrence of chronic atrophic gastritis diagnosed by gastroscopy.The results showed that when Logit(P)>0.727,the sensitivity was 87.29%,the specificity was 86.67%,and the area under the curve(AUC)was 0.922.Conclusion The influencing factors of chronic atrophic gastritis diagnosed by gastroscopy include Helicobacter pylori infection,family history of gastritis,fast food,hot food,insomnia,CYP1A1 genotype G/G,the establishment of the regression equation is effective,which can lay a foundation for screening high-risk patients and formulating preventive interventions.

OBJECTIVE: To study the genetic polymorphism of red blood cell blood group among in Shenzhen Han, Indian and Xinjiang Uyghur populations, to provide scientific basis for the demand prediction and collection strategy of rare blood group, and to explore the genetic differences of blood group between Han and Caucasians. METHODS: The haplotypes of antigen coding genes of 10 target blood group systems from 87 Han Chinese and 50 Indian blood donors in Shenzhen, and 49 healthy Uyghur people in Xinjiang were obtained by three-generation sequencing technology, and the polymorphism and frequency characteristics were analyzed. RESULTS: Only a single genotype was detected the Langereis and Vel blood group systems in samples from three different populations. Only one genotype of Dombrock blood group was detected in Shenzhen Han, and Junior blood group in Xinjiang Uygur populations. In the MNS, Duffy, Kidd, Dombrock and Junior blood group systems, the haplotype frequency of Indian and Uyghur people was significantly different from that of Han people. Compared with the Han ethnic group, the rare blood group s-, Fy(a-), Jk(a-b-), and Do(a+b-) have a higher frequency among the Uyghur and Indian populations. CONCLUSION Haplotype frequencies of antigen genes for MNS, Duffy, Kidd, Dombrock and Junior blood group system in Shenzhen Han, Indian and Uyghur populations displayed a polymorphic difference with unique distribution characteristics different from the ethnic groups in other regions.
Humans ; Blood Group Antigens/genetics* ; China/ethnology* ; Erythrocytes ; Ethnicity/genetics* ; Gene Frequency ; Genotype ; Haplotypes ; India/ethnology* ; Polymorphism, Genetic ; White People/genetics* ; Central Asian People/genetics* ; East Asian People/genetics*

OBJECTIVE: To standardize the operative procedure for tissue-engineered cartilage repair, by demonstrating surgical technique of arthroscopic implantation of decalcified cortex-cancellous bone scaffolds, and summarizing the surgical experience of the sports medicine department team at Peking University Third Hospital. METHODS: This article elaborates on surgical techniques and skills, focusing on the unabridged implantation technology and surgical procedure of decalcified cortex-cancellous bone scaffolds under arthroscopy: First, the patient was placed in the supine position. After anesthesia had been established, the surgeon established an arthroscope and explored the damaged area under the scope. After confirming the size and location of the injury site, the surgeon cleaned the damaged cartilage, and also trimmed the edges of the cartilage to ensure that the cut surface was smooth and stable. the surgeon performed the micro-fracture surgery in the area of cartilage injury, and then measured the size of the injured area under the scope. Next, the surgeon manually trimmed the tissue-engineered scaffold based on the measurements taken under the arthroscope, and then directly implanted the scaffold using a sleeve. A honeycomb-shaped fixator was used to implant absorbable nails to fix the scaffold. After the scaffold was installed, the knee was repeatedly flexed and extended for 10-20 times to ensure stability and range of motion. Finally, the arthroscope was withdrawn and the wound was closed. RESULTS: Decalcified cortex-cancellous bone scaffolds possessed unparalleled advantages over synthetic materials in terms of morphology and biomechanics. The cancellous bone part of the scaffold provided a three-dimensional, porous space for cell growth, while the cortical bone part offered the necessary mechanical strength. The surgery was performed entirely under arthroscopy to minimize invasiveness to the patient. Absorbable pins were used for fixation to ensure the stability of the scaffold. This technique could effectively improve the prognosis of the patients with cartilage injuries and standardized the surgical procedures for arthroscopic tissue-engineered scaffold operations in the patients with cartilage damage. CONCLUSION With the standard arthroscopic tissue-engineered scaffold repair technique, it is possible to successfully repair damaged cartilage, alleviate symptoms in the short term, and provide a more ideal long-term prognosis. The author and their team explain the surgical procedures for tissue-engineered scaffolds under arthroscopy, with the aim of guiding future clinical practice.
Tissue Engineering/methods* ; Humans ; Tissue Scaffolds ; Arthroscopy/methods* ; Cartilage, Articular/surgery*

Objective:To clarify the genetic associations between obesity, diabetes, smoking, non-alcoholic fatty liver disease, acute and chronic pancreatitis, and pancreatic cancer risk.Methods:Summary data from genome-wide association studies (GWAS) of individuals of European descent were used. Obesity, alcohol consumption, diabetes, and acute and chronic pancreatitis data for the UK population were obtained from the GWAS catalog, while alcohol consumption, non-alcoholic fatty liver disease, occasional smoking, and regular smoking data were obtained from the UK biobank. Pancreatic cancer-related data for the Finnish population were sourced from the latest R11 version of the Finnish database. Two-sample Mendelian randomization (MR) analysis was conducted on the associations between the aforementioned risk factors and pancreatic cancer using five MR methods, primarily inverse variance weighting. The robustness of the results was assessed through Q heterogeneity tests, pleiotropy tests, MR-PRESSO analysis, and reverse MR analysis.Results:Obesity showed a significant positive association with pancreatic cancer risk ( OR=1.407, 95% CI: 1.100-1.714, P=0.030), and the results were robust based on Q heterogeneity tests, pleiotropy tests, MR-PRESSO, and reverse MR analysis (all P>0.05). However, no significant associations were found between pancreatic cancer risk and alcohol consumption ( P=0.330), heavy drinking ( P=0.382), type 1 diabetes ( P=0.674), type 2 diabetes ( P=0.825), occasional smoking ( P=0.607), regular smoking ( P=0.758), non-alcoholic fatty liver disease ( P=0.287), acute pancreatitis ( P=0.336), or chronic pancreatitis ( P=0.545). Conclusion:This study further confirms the strong genetic association between obesity and increased pancreatic cancer risk.