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Abstract Background: Hyperhomocysteinemia is associated with autoimmune diseases such as ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), and rheumatoid arthritis (RA). Current findings regarding plasma/serum homocysteine (HCY) levels in AS patients are inconsistent. This study aims to systematically evaluate the association between circulating HCY levels and AS. Methods: Online electronic databases (PubMed, Web of Science, Embase, ScienceDirect, China National Knowledge Infrastructure (CNKI), and Wanfang data) were used to retrieve all relevant articles published up to May 7, 2020. The pooled standardized mean difference (SMD) with 95% confidence interval (CI) was calculated using the random-effect model, Stata16 software. Results: Nine articles containing 778 AS patients and 522 controls were included in this meta-analysis. No significant differences in HCY levels were found between AS and control groups (pooled SMD = 0.46, 95% CI = − 0.30 to 1.23, P = 0.23). However, subgroup analysis suggested that HCY levels were significantly higher (P < 0.05) in the AS group treated with methotrexate (MTX) compared with the control group. In contrast, HCY levels were significantly (P < 0.05) lower in the AS group receiving anti-TNF-α treatment compared with the control group. No significant differences were detected between HCY levels and disease activity scores (Bath AS disease activity index, BASDAI), and methylenetetrahydrofolate reductase (MTHFR) C677T genotype. Conclusion: This meta-analysis indicates that HCY levels are similar between AS and controls, and do not correlate with disease activity. However, different medical treatments cause fluctuations of circulating HCY levels in AS patients. Further and larger-scale studies are needed to confirm these findings. Trial registration: This study was registered at international prospective register of systematic reviews (PROSPERO), registration number: CRD42020184426.(AU)
Assuntos
Humanos , Espondilite Anquilosante/etiologia , Homocisteína/análise , Estudos de Casos e Controles , Metotrexato/uso terapêutico , Fator de Necrose Tumoral alfa/uso terapêuticoRESUMO
In this work we present unique signatures manifested by the local electronic properties of the topological surface state in Bi2Te3 nanostructures as the spatial limit is approached. We concentrate on the pure nanoscale limit (nanoplatelets) with spatial electronic resolution down to 1 nm. The highlights include strong dependencies on nanoplatelet size: (1) observation of a phase separation of Dirac electrons whose length scale decreases as the spatial limit is approached, and (2) the evolution from heavily n-type to lightly n-type surface doping as nanoplatelet thickness increases. Our results show a new approach to tune the Dirac point together with reduction of electronic disorder in topological insulator (TI) nanostructured systems. We expect our work will provide a new route for application of these nanostructured Dirac systems in electronic devices.
RESUMO
The objective of the present study was to evaluate the predictive values of percent body fat (PBF) and body mass index (BMI) for cardiovascular risk factors, especially when PBF and BMI are conflicting. BMI was calculated by the standard formula and PBF was determined by bioelectrical impedance analysis. A total of 3859 ambulatory adult Han Chinese subjects (2173 males and 1686 females, age range: 18-85 years) without a history of cardiovascular diseases were recruited from February to September 2009. Based on BMI and PBF, they were classified into group 1 (normal BMI and PBF, N = 1961), group 2 (normal BMI, but abnormal PBF, N = 381), group 3 (abnormal BMI, but normal PBF, N = 681), and group 4 (abnormal BMI and PBF, N = 836). When age, gender, lifestyle, and family history of obesity were adjusted, PBF, but not BMI, was correlated with blood glucose and lipid levels. The odds ratio (OR) and 95% confidence interval (CI) for cardiovascular risk factors in groups 2 and 4 were 1.88 (1.45-2.45) and 2.06 (1.26-3.35) times those in group 1, respectively, but remained unchanged in group 3 (OR = 1.32, 95%CI = 0.92-1.89). Logistic regression models also demonstrated that PBF, rather than BMI, was independently associated with cardiovascular risk factors. In conclusion, PBF, and not BMI, is independently associated with cardiovascular risk factors, indicating that PBF is a better predictor.
Assuntos
Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Adulto Jovem , Tecido Adiposo , Índice de Massa Corporal , Doenças Cardiovasculares/etiologia , Glicemia , Pressão Sanguínea , Doenças Cardiovasculares/sangue , Impedância Elétrica , Lipídeos/sangue , Valor Preditivo dos Testes , Fatores de RiscoRESUMO
The objective of the present study was to evaluate the predictive values of percent body fat (PBF) and body mass index (BMI) for cardiovascular risk factors, especially when PBF and BMI are conflicting. BMI was calculated by the standard formula and PBF was determined by bioelectrical impedance analysis. A total of 3859 ambulatory adult Han Chinese subjects (2173 males and 1686 females, age range: 18-85 years) without a history of cardiovascular diseases were recruited from February to September 2009. Based on BMI and PBF, they were classified into group 1 (normal BMI and PBF, N = 1961), group 2 (normal BMI, but abnormal PBF, N = 381), group 3 (abnormal BMI, but normal PBF, N = 681), and group 4 (abnormal BMI and PBF, N = 836). When age, gender, lifestyle, and family history of obesity were adjusted, PBF, but not BMI, was correlated with blood glucose and lipid levels. The odds ratio (OR) and 95% confidence interval (CI) for cardiovascular risk factors in groups 2 and 4 were 1.88 (1.45-2.45) and 2.06 (1.26-3.35) times those in group 1, respectively, but remained unchanged in group 3 (OR = 1.32, 95%CI = 0.92-1.89). Logistic regression models also demonstrated that PBF, rather than BMI, was independently associated with cardiovascular risk factors. In conclusion, PBF, and not BMI, is independently associated with cardiovascular risk factors, indicating that PBF is a better predictor.