BackgroundHomocysteine (Hcy) has been considered as an independent risk factor for coronary artery disease (CAD). Folic acid and vitamin B12 are two vital regulators in Hcy metabolic process. We evaluated the correlations between serum Hcy, folic acid and vitamin B12 with the categories of CAD.MethodsSerum Hcy, folic acid and vitamin B12 from 292 CAD patients, including 73 acute myocardial infarction (AMI), 116 unstable angina pectoris (UAP), 103 stable angina pectoris (SAP), and 100 controls with chest pain patients were measured, and the data were analyzed by SPSS software.ResultsCompared to SAP patients, patients with AMI and UAP had higher Hcy levels with approximately average elevated (4-5) μmol/L, while SAP patients were approximately higher 8 μmol/L than controls. However, the levels of folic acid and vitamin B12 had opposite results, which in AMI group was the lowest, while in controls was the highest. CAD categories were positively correlated with Hcy (r = 0.286, p < 0.001), and negatively correlated with folic acid (r = -0.297, p < 0.001) and vitamin B12 (r = -0.208, p < 0.001). There were significant trend toward increase in the prevalence of high Hcy, low folic acid and vitamin B12 from controls, to SAP, to UAP, and to AMI.ConclusionsThe present study provide the valuable evidence that high concentrations of Hcy and low levels of folic acid and vitamin B12 are significantly correlated with CAD categories.

This study aims to develop an artificial intelligence (AI)-based model to assist radiologists in pneumoconiosis screening and staging using chest radiographs. The model, based on chest radiographs, was developed using a training cohort and validated using an independent test cohort. Every image in the training and test datasets were labeled by experienced radiologists in a double-blinded fashion. The computational model started by segmenting the lung field into six subregions. Then, convolutional neural network classification model was used to predict the opacity level for each subregion respectively. Finally, the diagnosis for each subject (normal, stage I, II, or III pneumoconiosis) was determined by summarizing the subregion-based prediction results. For the independent test cohort, pneumoconiosis screening accuracy was 0.973, with both sensitivity and specificity greater than 0.97. The accuracy for pneumoconiosis staging was 0.927, better than that achieved by two groups of radiologists (0.87 and 0.84, respectively). This study develops a deep learning-based model for screening and staging of pneumoconiosis using man-annotated chest radiographs. The model outperformed two groups of radiologists in the accuracy of pneumoconiosis staging. This pioneer work demonstrates the feasibility and efficiency of AI-assisted radiography screening and diagnosis in occupational lung diseases.

Carbon dots (CDs) have received extensive attention and applications in recent years due to their remarkable characteristics of tunable emission wavelength, high stability, and a variety of synthetic raw materials. Since the formation process and photoluminescence properties of CDs are affected by multiple factors, the luminescence regulation of CDs has always been a troublesome problem. Furthermore, it is still a lack of appropriate approaches to reveal the hidden rules between the synthesis conditions and the luminescence properties of CDs. Inspired by machine learning (ML) applications in molecular and materials science, herein, a data-driven ML strategy is proposed to multi-dimensionally investigate the correlation between reaction parameters and the photoluminescence properties of CDs. Meanwhile, it is demonstrated that reaction parameters and solvent properties have different influences on the fluorescence properties of CDs, and the intelligently optimizing synthesis route of CDs is achieved using ML algorithms. CDs with excellent luminescent properties screened by ML are further applied to high-capacity colorful information encryption. This study provides an efficient ML-assisted strategy to guide the synthesis of multicolor CDs, helping researchers to quickly and easily obtain CDs according to experimental requirements.

ObjectiveAs a classical immunosuppressant, tacrolimus (TAC) has been widely used in organ transplantation therapy, but the general benefits of TAC for the treatment of IgA nephropathy (IgAN) remain uncertain. We conducted a meta-analysis to examine the effects of TAC combined with glucocorticoid on IgAN.MethodsWe searched the information databases PubMed/Medline, Embase, Science Citation Index, Chinese Biomedical Literature and the Chinese databases VIP, CNKI and Wan Fang for randomized controlled trials of TAC combined with glucocorticoid as a therapy for IgAN.ResultsTen relevant studies involving 472 patients were included in a meta-analysis. Overall, the TAC group showed a significant decrease in proteinuria compared with the control group (MD: −0.18 g/d, 95% CI: −0.32 to −0.04). No increased risk of adverse events was observed (OR: 0.93, 95% CI: 0.65 to 1.33). In general, the TAC group showed good tolerance.ConclusionEvidence to date clearly indicates that TAC combined with glucocorticoid is quite effective in reducing proteinuria and albuminuria in patients with IgAN. Moreover, we found that patients receiving TAC therapy did not show an increased risk of side effects compared with control group patients. TAC combined with glucocorticoid is a promising medication and merits further research.

Objectives:To study the associations between hyperhomocysteinemia (HHcy) and the severity of coronary heart disease (CHD).Methods:We retrospectively analyzed metabolic parameters, anthropometric variables, and life style habits in 292 CHD patients of different categories, and 100 controlled non-CHD patients with chest pain symptoms who were hospitalized in the Department of Cardiovascular Medicine, Sichuan Academy of Medical Sciences and Sichuan Provincial People’s Hospital, Chengdu, China between October 2013 and September 2014.Results:The prevalence of HHcy in CHD patients was 79.1%, while only 5% of non-CHD patients had elevated serum homocysteine (Hcy) concentrations. The prevalence of HHcy significantly increased from 5% in non-CHD controls to 66% in the stable angina pectoris (SAP) group, to 81.9% in the unstable angina pectoris group, and to 93.15% in the acute myocardial infarction (AMI) group (p<0.001). After adjusting for confounding factors, multivariate logistic regression analysis showed that HHcy was independently associated with CHD category (AMI versus SAP, odds ratio [6.38], 95% confidence interval; 1.18-34.46). The Hcy was negatively correlated with folic acid (r=-0.67, p<0.001) and vitamin B12 (r=-0.56, p<0.001). Of the CHD patients with HHcy, 51.1% had low folic acid and 42% had low vitamin B12, 7 or 5 times higher than that of CHD patients with normal-low Hcy concentrations (p<0.001).Conclusion:Hyperhomocysteinemia is independently associated with the severity of CHD, and significantly correlated with low status of folic acid and vitamin B12 in CHD patients.