Background Acute carbon monoxide poisoning is now one of the major causes of morbidity and mortality in occupational and non-occupational poisoning in China, and become a serious public health problem. Understanding the current and predicting the future disease burden of carbon monoxide poisoning are essential for adopting effective disease prevention and control strategies in the future. Objective To understand the burden of disease of carbon monoxide poisoning in China from 1990 to 2019 and predict the trend of morbidity and mortality in the following decade to provide a scientific basis for the prevention of carbon monoxide poisoning in China. Methods The incidence, mortality and disability-adjusted-life-years (DALYs) rates of carbon monoxide poisoning in China from 1990 to 2019 were extracted from the Global Burden of Disease Database (GBD2019). Time trend analysis of the burden of disease for carbon monoxide poisoning was performed using Joinpoint 5.0.2 software, and annual percentage change (APC) and average annual percentage change (AAPC) and their 95%CIs were calculated. Bayesian age-period-cohort model (BAPC) and Nordpred age-period-cohort model were used in R 4.3.3 to predict the disease burden of carbon monoxide poisoning among Chinese residents in 2020—2029. Results An overall increasing trend of the age-standardized incidence rate of carbon monoxide poisoning in China from 1990 to 2019 was observed and AAPC=1.05%, of which the AAPC for women was 0.90% and that for men was 1.16%. An overall decreasing trend of the age-standardized mortality rate and age-standardized DALYs from 1990 to 2019 was observed and the AAPC for males or females was <0. the results of the BAPC model expected that an increasing trend from 2020 to 2029 in age-standardized morbidity rate (females: 18.85/100 000 in 2020 to 19.12/100,000 in 2029; males: 22.51/100 000 in 2020 to 22.60/100 000 in 2029); and a decreasing trend in age-standardized mortality rate (females: 0.70/100,000 in 2020 to 0.52/100 000 in 2029; males: 1.13/100 000 in 2020 to 0.97/100 000 in 2029). The results of the Nordpred age-period-cohort model showed similar trends, suggesting that the results were stable. Conclusion Carbon monoxide poisoning caused a serious burden of disease in the Chinese population during the period 1990—2019, with adolescents and middle-aged and elderly people being the most affected groups. Subsequent projections have shown an upward trend in age-standardized incidence rates and numbers of cases, so we still need to deepen the implementation of prevention and treatment of the occurrence and development of carbon monoxide poisoning, and to reduce the harm it causes to the population.

OBJECTIVE: To explore the genetic basis for a Chinese patient featuring cleidocranial dysplasia(CCD). METHODS: Genomic DNA was extracted from peripheral blood samples of the patient and his parents. Whole exome sequencing (WES) was carried out for the patient, and suspected variant was verified by Sanger sequencing. RESULTS: WES has identified a missense c.460G>T (p.Val154Phe) (GRCh37/hg19) variant of the RUNX2 gene. The variant was located in the Runt domain, a highly conserved region (PM1); it was not present in either the Genome Aggregation Database or the 1000 Genomes Project (PM2), and was predicted to have a deleterious effect on the gene product by multiple in silico prediction tools (PP3); the clinical phenotype of the patient was highly consistent with that of cleidocranial dysplasia (PP4). Furthermore, the variant was unreported in medical literature and was absent in both parents (PS2). Based on the American College of Medical Genetics and Genomics guidelines, the c.460 G>T variant of RUNX2 gene was predicted to be pathogenic (PS2+PM1+PM2+PP3+PP4). CONCLUSION The c.460G>T (p.Val154Phe) variant of the RUNX2 gene probably underlay the clinical phenotype in the patient. Above finding has enabled accurate diagnosis and expanded the spectrum of RUNX2 variants.
China ; Cleidocranial Dysplasia/genetics* ; Core Binding Factor Alpha 1 Subunit/genetics* ; Humans ; Mutation ; Whole Exome Sequencing

Objective To investigate the differences in plasma metabolites between patients with altitude-related hypertension(ARH)and healthy individuals,and analyze the potential pathogenesis of ARH.Methods Convenient sampling was conducted on a unit of male healthy officers and soldiers who resident at altitude of＜500 m and migrated to an altitude of 4 200 m in July 2020.Twenty of them diagnosed with ARH were assigned into the ARH group,and another 30 non-ARH individuals served as the control group.Their blood pressure,body mass index(BMI),blood oxygen saturation,and heart rate were measured and recorded,and fasting venous blood samples were harvested to screen and identify plasma metabolites with ultra-high performance liquid chromatography-tandem mass spectrometry(UHPLC-MS/MS).Metabolite fingerprinting was performed using unsupervised Principal Component Analysis(PCA)and supervised Orthogonal Partial Least Squares Discrimination Analysis(OPLS-DA)models in order to assist in biomarker screening.The quality of the OPLS-DA model was assessed and validated to guarantee the stability and reliability of the model.Differential plasma metabolites were screened using independent sample t test and fold change(FC)analysis,and volcano plots were drawn.Finally,Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment pathway analysis was used to perform functional pathway enrichment and topological analysis on the screened differential metabolites.Results Compared to the control group,the ARH group showed significantly higher systolic and diastolic blood pressure and heart rate,and lower arterial oxygen saturation(P＜0.05).PCA analysis showed that 81.96％of the variance was explained in the positive ion mode and 79.25％in the negative ion mode,indicating significant metabolic differences between the 2 groups.OPLS-DA model analysis indicated that in the positive ion mode,PC1 explained 77.36％of the variance and PC2 explained 12.25％of the variance,with R2Y=0.96 and Q2Y=0.91;in the negative ion mode,PC1 explained 84.15％of the variance and PC2 explained 17.24％of the variance,with R2Y=0.99 and Q2Y=0.86.Inter-group difference exceeded 75％,and intra-group difference was less than 20％.The 7-fold cross-validation and 200 permutation test confirmed that the model was stable and reliable.In the positive ion mode,the Y-axis intercepts of the R2 and Q2 fitted lines were 0.58 and-0.48,respectively;in the negative ion mode,the Y-axis intercepts were 0.93 and-0.41,respectively.A total of 32 significantly different metabolites were screened out,including amino acids,nucleosides,fatty acids,and organic alkaloids.KEGG analysis revealed that among the 10 metabolic pathways,4 were amino acid metabolic pathways,with the aminoacyl-tRNA biosynthesis pathway having the most enriched metabolites.Conclusion Based on UHPLC-MS/MS technology,untargeted metabolomics analysis identifies 32 significantly different metabolites,which may serve as characteristic biomarkers for ARH,and the aminoacyl-tRNA biosynthesis pathway may be associated with the pathogenesis of ARH.

Animals ; Callithrix ; Sex Factors ; Vocalization, Animal ; Sex Characteristics