OBJECTIVE: To investigate the clinical features and genetic variants associated with Multiple mitochondrial dysfunction syndrome (MMDS) type 3 in two children. METHODS: Two children diagnosed with MMDS type 3 at Zhuhai Maternal and Child Health Care Hospital in January 2021 were selected for this study. A retrospective analysis of their clinical data was carried out. Whole exome sequencing was conducted on the two children and their parents, followed by Sanger sequencing for candidate variants and bioinformatic analysis. Both children received comprehensive rehabilitative therapy and were followed up for 3 years. This study was approved by the Ethics Committee of Zhuhai Maternal and Child Health Hospital (Ethics No. 202380). RESULTS: The two MMDS type 3 children were monozygotic twin girls, aged 9 months, presenting with developmental regression, pyramidal signs, and other clinical manifestations. Cranial MRI revealed widespread abnormal signals and vacuolar changes in the white matter. Whole exome sequencing revealed that both children had harbored compound heterozygous variants of the IBA57 gene, namely c.286T>C (p.Tyr96His) and c.307C>T (p.Gln103Ter). Sanger sequencing confirmed that these variants were inherited from their father and mother, respectively. According to the American College of Medical Genetics and Genomics (ACMG) guidelines, both variants were classified as pathogenic (PM2_Supporting+PM3_Very Strong+PP3_Moderate; PVS1+PM2_Supporting+PM3). After treatment with vitamins, levocarnitine, ATP, coenzyme Q10, and other drugs, both children showed partial recovery of neurodevelopmental regression, with improvement in feeding and sleep. Over the 3-year follow-up, there was slow but progressive improvement in motor, language, and cognitive development. CONCLUSION The compound heterozygous variants c.286T>C (p.Tyr96His) and c.307C>T (p.Gln103Ter) of the IBA57 gene probably underlay the MMDS type 3 in the twin pair. Clinicians should be vigilant about the possibility of MMDS type 3 in children with neurodevelopmental regression and early cranial MRI findings indicating widespread white matter abnormalities with vacuolar changes, as these may be indicative of IBA57 gene variants.
Female ; Humans ; Infant ; Calcium-Binding Proteins/genetics* ; Exome Sequencing ; Genetic Testing/methods* ; Microfilament Proteins/genetics* ; Mitochondrial Diseases/genetics* ; Mutation ; Retrospective Studies ; Carrier Proteins

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

Objective:To investigate the clinical features and genetic variants associated with Multiple mitochondrial dysfunction syndrome (MMDS) type 3 in two children.Methods:Two children diagnosed with MMDS type 3 at Zhuhai Maternal and Child Health Care Hospital in January 2021 were selected for this study. A retrospective analysis of their clinical data was carried out. Whole exome sequencing was conducted on the two children and their parents, followed by Sanger sequencing for candidate variants and bioinformatic analysis. Both children received comprehensive rehabilitative therapy and were followed up for 3 years. This study was approved by the Ethics Committee of Zhuhai Maternal and Child Health Hospital (Ethics No. 202380).Results:① The two MMDS type 3 children were monozygotic twin girls, aged 9 months, presenting with developmental regression, pyramidal signs, and other clinical manifestations. Cranial MRI revealed widespread abnormal signals and vacuolar changes in the white matter. ② Whole exome sequencing revealed that both children had harbored compound heterozygous variants of the IBA57 gene, namely c. 286T>C (p.Tyr96His) and c. 307C>T (p.Gln103Ter). Sanger sequencing confirmed that these variants were inherited from their father and mother, respectively. ③ According to the American College of Medical Genetics and Genomics (ACMG) guidelines, both variants were classified as pathogenic (PM2_Supporting + PM3_Very Strong + PP3_Moderate; PVS1 + PM2_Supporting + PM3). ④ After treatment with vitamins, levocarnitine, ATP, coenzyme Q10, and other drugs, both children showed partial recovery of neurodevelopmental regression, with improvement in feeding and sleep. Over the 3-year follow-up, there was slow but progressive improvement in motor, language, and cognitive development. Conclusion:The compound heterozygous variants c. 286T>C (p.Tyr96His) and c. 307C>T (p.Gln103Ter) of the IBA57 gene probably underlay the MMDS type 3 in the twin pair. Clinicians should be vigilant about the possibility of MMDS type 3 in children with neurodevelopmental regression and early cranial MRI findings indicating widespread white matter abnormalities with vacuolar changes, as these may be indicative of IBA57 gene variants.

Objective:To investigate the clinical features and genetic variants associated with Multiple mitochondrial dysfunction syndrome (MMDS) type 3 in two children.Methods:Two children diagnosed with MMDS type 3 at Zhuhai Maternal and Child Health Care Hospital in January 2021 were selected for this study. A retrospective analysis of their clinical data was carried out. Whole exome sequencing was conducted on the two children and their parents, followed by Sanger sequencing for candidate variants and bioinformatic analysis. Both children received comprehensive rehabilitative therapy and were followed up for 3 years. This study was approved by the Ethics Committee of Zhuhai Maternal and Child Health Hospital (Ethics No. 202380).Results:① The two MMDS type 3 children were monozygotic twin girls, aged 9 months, presenting with developmental regression, pyramidal signs, and other clinical manifestations. Cranial MRI revealed widespread abnormal signals and vacuolar changes in the white matter. ② Whole exome sequencing revealed that both children had harbored compound heterozygous variants of the IBA57 gene, namely c. 286T>C (p.Tyr96His) and c. 307C>T (p.Gln103Ter). Sanger sequencing confirmed that these variants were inherited from their father and mother, respectively. ③ According to the American College of Medical Genetics and Genomics (ACMG) guidelines, both variants were classified as pathogenic (PM2_Supporting + PM3_Very Strong + PP3_Moderate; PVS1 + PM2_Supporting + PM3). ④ After treatment with vitamins, levocarnitine, ATP, coenzyme Q10, and other drugs, both children showed partial recovery of neurodevelopmental regression, with improvement in feeding and sleep. Over the 3-year follow-up, there was slow but progressive improvement in motor, language, and cognitive development. Conclusion:The compound heterozygous variants c. 286T>C (p.Tyr96His) and c. 307C>T (p.Gln103Ter) of the IBA57 gene probably underlay the MMDS type 3 in the twin pair. Clinicians should be vigilant about the possibility of MMDS type 3 in children with neurodevelopmental regression and early cranial MRI findings indicating widespread white matter abnormalities with vacuolar changes, as these may be indicative of IBA57 gene variants.

Engineered probiotics can serve as therapeutics based on their ability of produce recombinant immune-stimulating properties. In this study, we built the recombinant Bacillus subtilis WB800 expressing antimicrobial peptide KR32 (WB800-KR32) using genetic engineering methods and investigated its protective effects of nuclear factor-E2-related factor 2 (Nrf2)‍-Kelch-like ECH-associated protein 1 (Keap1) pathway activation in intestinal oxidative disturbance induced by enterotoxigenic Escherichia coli (ETEC) K88 in weaned piglets. Twenty-eight weaned piglets were randomly distributed into four treatment groups with seven replicates fed with a basal diet. The feed of the control group (CON) was infused with normal sterilized saline; meanwhile, the ETEC, ETEC+WB800, and ETEC+WB800-KR32 groups were orally administered normal sterilized saline, 5×10¹⁰ CFU (CFU: colony forming units) WB800, and 5×10¹⁰ CFU WB800-KR32, respectively, on Days 1‍‒‍14 and all infused with ETEC K88 1×10¹⁰ CFU on Days 15‍‒‍17. The results showed that pretreatment with WB800-KR32 attenuated ETEC-induced intestinal disturbance, improved the mucosal activity of antioxidant enzyme (catalase (CAT), superoxide dismutase (SOD), and glutathione peroxidase (GPx)) and decreased the content of malondialdehyde (MDA). More importantly, WB800-KR32 downregulated genes involved in antioxidant defense (GPx and SOD1). Interestingly, WB800-KR32 upregulated the protein expression of Nrf2 and downregulated the protein expression of Keap1 in the ileum. WB800-KR32 markedly changed the richness estimators (Ace and Chao) of gut microbiota and increased the abundance of Eubacterium_rectale_ATCC_33656 in the feces. The results suggested that WB800-KR32 may alleviate ETEC-induced intestinal oxidative injury through the Nrf2-Keap1 pathway, providing a new perspective for WB800-KR32 as potential therapeutics to regulate intestinal oxidative disturbance in ETEC K88 infection.
Animals ; Swine ; Enterotoxigenic Escherichia coli ; Kelch-Like ECH-Associated Protein 1 ; Bacillus subtilis ; NF-E2-Related Factor 2 ; Antioxidants ; Oxidative Stress

Objective:To analyze the influence of work engagement and self-efficacy of nurses on clinical practice ability in burn intensive care unit (BICU), and to explore its potential pathways of action.Methods:A cross-sectional survey was conducted. From May to October 2020, a total of 30 hospitals with BICU in China were selected by stratified sampling method. Among BICU nurses who met the inclusion criteria, their clinical practice ability, work engagement, and self-efficacy were evaluated by self-evaluation scale of oriented problem-solving behavior in nursing practice (OPSN), Utrecht work engagement scale (UWES), and general self-efficacy scale (GSES), respectively. The total scale scores of each index and the average item scores were recorded. The self-designed general data questionnaire was used to investigate the nurses' gender, age, marital status, education background, working years, professional title, and the economic region of the hospital that they belonged to. The total scale scores of the above-mentioned three evaluation indexes were compared after the classification of nurses according to general data, and the data were statistically analyzed with independent sample t test or one-way analysis of variance. Pearson correlation analysis was used to analyze the correlation between the total scale scores of the three evaluation indexes. Based on the total scale scores of the above-mentioned three evaluation indexes, a structural equation model was established, the mediation analysis of the relationship among the three evaluation indexes and the pathway analysis of the structural model were conducted, and the Bootstrap method was used to verify the pathways of action. Results:A total of 401 questionnaires were distributed, and 337 valid questionnaires were returned, with a valid return rate of 84.04%. The total scale scores of clinical practice ability, work engagement, and self-efficacy of 337 nurses were 98.2±11.7, 67.7±18.6, and 26.6±5.6, respectively, and the average item scores were 3.9±0.5, 4.5±1.2, and 2.7±0.6, respectively. Among the 337 nurses, the majority were female, aged 40 or below, married, and had a bachelor's degree with work experience of ≤10 years; both nurses with professional nurse title and nurses from the Southeast region accounted for about 50%. There were statistically significant differences in the total scale score of clinical practice ability among nurses with different ages, education backgrounds, working years, and professional titles (with F values of 3.26, 4.36, 3.12, and 2.80, respectively, P<0.05). There was statistically significant difference in the total scale score of work engagement among nurses with different working years ( F=4.50, P<0.05). There were statistically significant differences in the total scale score of self-efficacy among nurses with different ages, working years, and professional titles (with F values of 4.91, 4.50, and 2.91, respectively, P<0.05). The total scale score of nurses' work engagement was significantly positively correlated with the total scale score of clinical practice ability and the total scale score of self-efficacy (with r values of 0.30 and 0.51, respectively, P<0.05). The total scale score of nurses' self-efficacy was significantly positively correlated with the total scale score of clinical practice ability ( r=0.37, P<0.05). The model had good adaptability, and the intermediary model was established. Nurses' work engagement had a significantly positive effect on both self-efficacy and clinical practice ability (with β values of 0.54 and 0.16, respectively, P<0.05), and nurses' self-efficacy had a significantly positive effect on clinical practice ability ( β=0.29, P<0.05). Work engagement had a direct effect on self-efficacy and clinical practice ability, and self-efficacy had a direct effect on clinical practice ability and played a mediating role between work engagement and clinical practice ability. Bootstrap validation showed that self-efficacy played a significantly mediating role in the influence of work engagement on clinical practice ability (with effect size of 0.16, with 95% confidence interval of 0.08-0.24, P<0.05), accounting for half of the total effect of work engagement on clinical practice ability (with effect size of 0.32). Conclusions:BICU nurses have an above-average level of clinical practice ability, a medium level of self-efficacy, and a high level of work engagement. Work engagement and self-efficacy are positively correlated with clinical practice ability. Work engagement can directly affect clinical practice ability or indirectly affect clinical practice ability through the mediating role of self-efficacy.

Objective:To investigate the cause of missed diagnosis by transthoracic echocardiography (TTE) based on the characteristics of partial anomalous pulmonary venous connection (PAPVC), and to improve the ultrasonic diagnostic accuracy of PAPVC in children.Methods:The TTE results of 252 children under 12 years old who were confirmed with PAPVC at Guangdong Provincial People′s Hospital from January 2011 to June 2019 were reviewed retrospectively.The types of PAPVC and the associated atrial septal defects (ASD) as well as the confirmed and missed cases by TTE were analyzed.Results:PAPVC was right-sided in 238 patients (94.4%), left-sided in 8 patients (3.2%), and bilateral in 6 patients (2.4%). There were 177 cases (70.2%) whose pulmonary veins were abnorma-lly connected to the right atrium(RA), 37 cases (14.7%) to the junction of the RA and the superior vena cava (SVC), 27 cases (10.7%) to the distal SVC, and 6 cases (2.4%) to the inferior vena cava.Besides, pulmonary veins of 5 cases (2.0%) flew back to the RA through the coronary sinus.One hundred and ninety PAPVC cases were combined with sinus venous defects (SVD) and 53 cases combined with secondum ASD.Two hundred and twenty-one cases were accurately diagnosed while 31 cases were underestimated by TTE.The omission diagnostic rates of right superior pulmonary veins connecting to the distal SVC, 1 or 2 right pulmonary veins connecting to the RA or the junction of the RA and SVC, and left-sided PAPVC were 8 out of 18 (44.4%), 22 out of 215 (10.2%) and 1 out of 8 (12.5%), respectively.Among 54 cases with right superior pulmonary veins anomalously connected to the RA or the junction of the RA and SVC, 88.9% of them (48/54 cases) were combined with superior SVD.Among 161 cases with the right inferior pulmonary veins or 2 right pulmonary veins connected to the RA, 78.2% of them (126/161 cases) were combined with inferior SVD.There were statistically significant differences in ASD types between the 2 right-sided PAPVC groups.Conclusions:SVD is often associated with 1 or 2 right pulmonary veins connected to the RA or the junction of the RA and SVC.The cases with right superior pulmonary veins connected to the distal SVC are prone to be underestimated by TTE.Whether there is abnormal blood flowing into SVC should be noticed during superior sternal fossa examinations.Each pulmonary vein should be examined in detail in the TTE test and accurate diagnosis of PAPVC can be made in most cases.

Objective:This study analyzes the expression level of miR-1180-3p and constructs the regulatory network of relevant ceRNA by integrating the DNA methylation and gene expression profile of hepatocellular carcinoma from the Cancer Genome Atlas (TCGA).Methods:Firstly, the expression level of miR-1180-3p in hepatocellular carcinoma and adjacent tissues was analyzed by TCGA database, and the differential expression of lncrna and mRNA was screened. Secondly, the LncBase database and the TargetScan database were used to predict the relationship between miR-1180-3p and lncRNA and mRNA, and the DNA methylation-mediated lncRNA was screened by the DNA methylation profile of lncRNA. Finally, Cytoscape software was used to construct miR-1180-3p relevant ceRNA network, and WebGestalt website was used to perform GO and KEGG analysis of related mRNA in ceRNA.Results:Compared with patients with low expression of miR-1180-3p (mean overall survival duration, 5.69 ± 0.35 years), patients with high expression of miR-1180-3p had shorter overall survival time (mean overall survival duration, 3.99 ± 0.47 years), indicating that the high expression of miR-1180-3p was hepatocellular carcinoma risk factor affecting the prognosis ( HR = 1.28, 95% CI = 1.1 ~ 1.5, P < 0.01). A miR-1180-3p related ceRNA regulatory network was constructed in this study, which contained 2 lncRNAs (F11-AS1 and LINC01511) and 37 mRNAs. Conclusion:This study has successfully constructed miR-1180-3p relevant ceRNA regulatory network, and DNA methylation-mediated F11-AS1 and F11-AS1/miR-1180-3p/C11of54 ceRNA regulatory axis has played an important role in the occurrence and development of hepatocellular carcinoma.

Objective:To screen and analyze the differentially-expressed genes (DEGs) in primary hepatocellular carcinoma tissues and adjacent tissues using bioinformatics methods to explore the molecular mechanism of the occurrence and prognosis of primary hepatocellular carcinoma.Methods:GSE76427 data set was collected through GEO database, and DEGs were identified using GEO2R online analysis. Go and KEGG databases were used for enrichment and functional annotation of DEGs. Protein interaction network was built based on the STRING database and Cytoscape software to analyze the key genes of hepatocellular carcinoma, and the survival curve of these key genes were analyzed using the GEPIA database.Results:A total of 74 hepatocellular carcinoma DEGs were screened, of which 3 and 71 were up-and-down-regulated genes. The results of GO enrichment analysis showed that the down-regulated DEGs were mainly involved in cell response to cadmium and zinc ions, negative growth regulation, heterologous metabolic processes and hormone-mediated signaling pathways. KEGG pathway enrichment analysis results showed that the down-regulated DEGs pathway were mainly involved in retinol metabolism, chemical carcinogenesis, drug metabolism-cytochrome P450, cytochrome P450 metabolizing xenobiotics, tryptophan metabolism and caffeine metabolism. Protein interaction network had screened out 10 down-regulated core genes: MT1G, MT1F, MT1X, MT1E, MT1H, insulin-like growth factor 1, FOS, CXCL12, EGR1, and BGN. Among them, the insulin-like growth factor 1 was related to the prognosis of primary hepatocellular carcinoma.Conclusion:Bioinformatics analysis results of HCC chip data showed that 10 key genes may play a key role in the occurrence and development of HCC and the insulin like growth factor 1 is associated with the prognosis of primary hepatocellular carcinoma.