OBJECTIVE: To explore the genotype-phenotype correlation in a Chinese family with structural brain abnormalities due to variant of the TUBB gene. METHODS: A family undergoing prenatal diagnosis at Beijing Obstetrics and Gynecology Hospital in October 2024 was selected as the study subject. Clinical data were collected. Amniotic fluid sample was subjected to chromosomal copy number variation sequencing (CNV-seq). Trio whole-exome sequencing (Trio-WES) was carried out on the amniotic fluid and parental blood samples, and candidate variant was verified by Sanger sequencing. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: 2023-KY-076-01). RESULTS: Both prenatal ultrasound and fetal MRI showed deviation of brain midline, unilateral lateral ventriculomegaly, and bilateral gyral asymmetry. Trio-WES revealed that the fetus has harbored a maternally derived heterozygous missense variant of the TUBB gene [NM_178014.4: c.155A>G (p.N52S)]. Sanger sequencing confirmed that the woman and a previously terminated fetus both harbored the same variant. Both the proband and two fetuses exhibited similar neuroimaging abnormalities including midline deviation and asymmetrical gyri. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the variant was classified as likely pathogenic (PM2_Supporting+PS2_Moderate+PS3). CONCLUSION The heterozygous c.155A>G (p.N52S) variant was the TUBB gene probably underlay the pathogenesis of the structural brain abnormalities in this family. Above findings have expanded the phenotypic spectrum associated with the variant and facilitated the prenatal diagnosis for this family.
Humans ; Female ; Pregnancy ; Prenatal Diagnosis ; Tubulin/genetics* ; Adult ; Brain/diagnostic imaging* ; Male ; Pedigree ; DNA Copy Number Variations/genetics* ; Exome Sequencing ; Genetic Association Studies ; Magnetic Resonance Imaging

Objective To investigate the current symptom status of maintenance hemodialysis(MHD)patients,analyze the influencing factors from the perspective of multidimensional symptom burden,extract symptom groups,and construct a symptom network.Methods A total of 490 patients who received MHD at the blood purification center of a tertiary hospital in Shanghai from March to April 2025 were selected using a convenience sampling method.30 symptoms of MHD patients were investigated using a modified dialysis symptom index table.SPSS and R software were utilized to analyze the influencing factors,extract symptom groups,and construct a multidimensional symptom network.Results A total of 488 valid questionnaires were collected,with a valid questionnaire recovery rate of 99.59％.The median number of symptoms experienced by patients was 6(interquartile range:4,8),with the top 5 symptoms being dry skin(69.88％),fatigue or tiredness(56.97％),itching(56.97％),worry(50.20％),and dry mouth(46.31％).Multidimensional analysis indicated that age,duration of dialysis,education level,and complications were influencing factors of symptom burden scores across different dimensions.6 stable symptom groups were extracted,namely skin discomfort,fatigue and pain,gastrointestinal tract,sleep disorders,water-electrolyte imbalance,and uremia.The results of the symptom network analysis revealed that difficulty of falling asleep had the highest intensity centrality(rs=2.18,2.25,2.12).Conclusion The symptom association is relatively stable,and difficulty of falling asleep is the core symptom.This finding can assist clinical medical staff in achieving efficiency and precision in symptom group management.

Iron is an essential trace element for the human body and is critical for vital cellular processes,such as DNA synthesis,respiration,and oxygen transport.The body maintains iron homeostasis through a coordinated balance of absorption,utilization,storage,and distribution.Both iron deficiency and excess can lead to pathologies,with the latter triggering lipid peroxidation and DNA mutations via the Fenton reaction,potentially causing iron-induced cell death in severe cases.Although iron overload can inflict severe damage on multiple organs,including the brain,liver,spleen,heart,ovaries,and kidneys,the mechanisms that regulate iron homeostasis in response to overload are not fully understood.Various animal models have been developed to help elucidate these mechanisms,each reflecting different aspects of iron overload relevant to human diseases,and selection of the most appropriate animal model is needed for the accurate simulation of the pathological and physiological states associated with human iron overload-related diseases.This review synthesizes recent literature on animal models pertinent to iron overload,to offer insights to support the development and analysis of models for diseases related to iron overload.

Objectives:To evaluate the effectiveness of functionalized decellularized extracellular matrix(F-dECM)prepared from porcine auricular cartilage or porcine rib cartilage in repairing xenogeneic articular osteochondral defects.Methods:The por-cine auricular cartilage and rib cartilage were crushed and decellularized.Heparin modification and multi-factor loading were a-chieved through amide bond reaction.The physical characteristics of the particles were characterized by SEM observation and mer-cury intrusion.The chemical characteristics of the particles were characterized by tissue section staining and kit detection.The rabbit knee joint full-thickness defect models were established and implanted by different particles respectively.After 6 weeks and 12 weeks of operation,the samples were taken for gross observation,CT scanning and tissue sectioning to comprehensively evaluate the repair effect.Results:After heparin modification,the glycosaminoglycan lost during the decellularization process was replen-ished.Both heparinized auricular cartilage and costal cartilage presented a highly developed porous structure.Among them,the porosity and pore diameter of costal cartilage were both lower than those of auricular cartilage(P＜0.05).During the observation periods of 6 weeks and 12 weeks,the porcine costal cartilage F-dECM implantation group was superior to other experimental groups in knee joint repair effects(P＜0.05).Conclusion:Costal-derived F-dECM is a joint osteochondral defect repair material with application potential.

Iron is an essential trace element for the human body and is critical for vital cellular processes,such as DNA synthesis,respiration,and oxygen transport.The body maintains iron homeostasis through a coordinated balance of absorption,utilization,storage,and distribution.Both iron deficiency and excess can lead to pathologies,with the latter triggering lipid peroxidation and DNA mutations via the Fenton reaction,potentially causing iron-induced cell death in severe cases.Although iron overload can inflict severe damage on multiple organs,including the brain,liver,spleen,heart,ovaries,and kidneys,the mechanisms that regulate iron homeostasis in response to overload are not fully understood.Various animal models have been developed to help elucidate these mechanisms,each reflecting different aspects of iron overload relevant to human diseases,and selection of the most appropriate animal model is needed for the accurate simulation of the pathological and physiological states associated with human iron overload-related diseases.This review synthesizes recent literature on animal models pertinent to iron overload,to offer insights to support the development and analysis of models for diseases related to iron overload.

Objectives:To evaluate the effectiveness of functionalized decellularized extracellular matrix(F-dECM)prepared from porcine auricular cartilage or porcine rib cartilage in repairing xenogeneic articular osteochondral defects.Methods:The por-cine auricular cartilage and rib cartilage were crushed and decellularized.Heparin modification and multi-factor loading were a-chieved through amide bond reaction.The physical characteristics of the particles were characterized by SEM observation and mer-cury intrusion.The chemical characteristics of the particles were characterized by tissue section staining and kit detection.The rabbit knee joint full-thickness defect models were established and implanted by different particles respectively.After 6 weeks and 12 weeks of operation,the samples were taken for gross observation,CT scanning and tissue sectioning to comprehensively evaluate the repair effect.Results:After heparin modification,the glycosaminoglycan lost during the decellularization process was replen-ished.Both heparinized auricular cartilage and costal cartilage presented a highly developed porous structure.Among them,the porosity and pore diameter of costal cartilage were both lower than those of auricular cartilage(P＜0.05).During the observation periods of 6 weeks and 12 weeks,the porcine costal cartilage F-dECM implantation group was superior to other experimental groups in knee joint repair effects(P＜0.05).Conclusion:Costal-derived F-dECM is a joint osteochondral defect repair material with application potential.

Objective To develop a core outcome set(COS)for clinical effectiveness trials of heart failure with preserved ejection fraction(HFpEF).Methods Outcome measures were collected through database literatures search,clinical experts questionnaire survey and semi-structured patients interview.Then,the outcome measures pool was constructed and domains were divided.Candidate outcome measures of COS were screened through two rounds of Delphi survey.Finally,a consensus meeting was held to determine COS and reach a consensus.Results A total of 317 outcome measures which could be divided into 6 domains were collected through literature research,questionnaire survey and semi-structured interview.15 candidate outcome measures of COS were screened through two rounds of Delphi survey.Finally,the consensus meeting reached consensus on a COS with 6 entries.Conclusion In this study,a COS for clinical effectiveness trials of HFpEF was developed,which is conducive to the standardization of efficacy evaluation.

Objectives:To investigate the factors affecting the formation of coronary collateral circulation(CCC)in patients with chronic total occlusion(CTO)lesion of coronary artery.Methods:A total of 305 consecutive patients who were hospitalized in the department of cardiology of the First Hospital of Lanzhou University from December 2022 to December 2023 and CTO lesions were confirmed by coronary angiography in at least one major coronary artery were included.The clinical data were collected,and the patients were divided into poor CCC group(Rentrop grade 0-1,n=109)and good CCC group(Rentrop grade 2-3,n=196)according to Rentrop criteria.Univariate logistic regression and multivariate logistic regression analysis were used to investigate the risk factors of poor CCC formation in CTO lesion patients.Results:There were 109 patients with poor CCC formation and 196 patients with good CCC formation in this cohort.The levels of white blood cell count,neutrophil count,platelet count,platelet to lymphocyte ratio,neutrophil to lymphocyte ratio,systemic immunoinflammatory index(SII),lipoprotein a and fibringen(Fib)were significantly higher,lymphocyte count and mean platelet volume were significantly lower in patients with poor CCC formation than in patients with good CCC formation(all P<0.05).Multivariate logistic regression analysis showed that higher SII(OR=1.004,95%CI:1.003-1.006,P<0.001),Fib(OR=1.546,95%CI:1.038-2.301,P=0.032)levels were independent predictors of poor CCC formation in CTO lesion patients.Conclusions:Higher levels of SII and Fib are independently correlated with poor CCC formation,which may be used as clinical predictor of poor CCC formation in CTO lesion patients.

Objective:To investigate the current status of subjective well-being among stroke patients, and to explore the pathways and effects of influencing factors using structural equation model, so as to provide reference for improving subjective well-being among stroke patients.Methods:From July to November 2024, the stroke patients admitted to the First Affiliated Hospital of Bengbu Medical University, the Second Affiliated Hospital of Bengbu Medical University, Hefei First People′s Hospital were selected by convenience sampling method. A cross-sectional survey was conducted using a general demographic questionnaire, General Well-Being Scale, Cognitive Reserve Index questionnaire, Social Support Rating Scale, Stroke Symptom Cluster Scale, and FRAIL Scale, and AMOS 26.0 was used to analyse the pathways and effects of influencing factors of subjective well-being.Results:A total of 435 questionnaires were collected, 410 were valid.Among 410 cases, 266 case were males, 144 were females, with an age of (65.96 ± 12.15) years. The subjective well-being scores of stroke patients were (72.58 ± 11.66) points. Cognitive reserve and social support were positively correlated with subjective well-being ( r = 0.517, 0.554, both P<0.01), while symptom burden and frailty were negatively correlated with subjective well-being ( r = -0.687, -0.670, both P<0.01). Path analysis showed that symptom burden, frailty, cognitive reserve, and social support had a direct impact on subjective well-being (path coefficients were -0.500, -0.266, 0.148, and 0.144, respectively, all P<0.05), while cognitive reserve, social support, and symptom burden had an indirect impact on subjective well-being (path coefficients were 0.287, 0.249, and 0.108, respectively, all P<0.05). Conclusions:The subjective well-being of stroke patients is influenced by multiple factors, with symptom burden being an important factor affecting subjective well-being. Intervention strategies such as improving cognitive reserve, strengthening social support systems, and preventing frailty can improve the subjective well-being of patients.

Objective:To assess the fall risk of hospitalized patients with cardiovascular diseases, analyze the related influencing factors, and construct a prediction model based on machine learning technology, so as to provide a basis for the fall management of hospitalized patients with cardiovascular diseases.Methods:This study was a retrospective cohort study. A total of 450 patients admitted to the Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University from June 2017 to June 2024 were selected as the research objects by convenience sampling method. By reviewing electronic medical records, trained nurses extracted the patients' general information and Activities of Daily Living Scale (ADL) scores during hospitalization. Lasso regression was used to screen risk factors, and machine learning libraries were used to construct support vector machine (SVM), decision tree, XGBoost, and neural network models. Bootstrap resampling method and area under the curve (AUC) were used to verify the model performance.Results:Among the 450 patients, there were 261 males and 189 females, with a mean age of (66.0 ± 8.4) years. Among them, 90 patients fell during hospitalization and 360 patients did not fall. The results of Lasso regression showed that ADL score ≤60 points, use of hypnotics, hypokalemia, nighttime toilet visits≥2 times, use of antihypertensive drugs, no caregiver, and history of atrial fibrillation were all risk factors for falls in hospitalized patients with cardiovascular diseases (regression coefficients ranging from 0.61 to 1.20, all P<0.01). Among the machine learning models, XGBoost had the best comprehensive performance (AUC=0.98), which was better than decision tree (AUC=0.66), SVM (AUC=0.95), and neural network (AUC=0.87). Conclusions:The fall risk of hospitalized patients with cardiovascular diseases is jointly affected by physiological, medication and behavioral factors, and the XGBoost model can effectively identify high-risk groups. In actual clinical work, nursing strategies can be optimized in combination with risk factors, and the application of intelligent fall prediction and assessment tools can be promoted.