This study was to assess the chronic morbidity and metabolic disordelters in 262 patients with type 2 diabetes.Of all participants,64(24.4%)coexisted with peripheral neuropathy,34(13.0%)combined with peripheral vascular disease.41(15.6%)were diagnosed as diabetic retinopathy,and 46 (17.6%)had concurrent diabetic nephropathy.In comparison with diabetic patients without these complications,those with the chronic conditions generally had higher plasma glucose,blood pressure or body mass index.

Objective: To explore drug resistance of different viral loads, and investigate the relationship between drug resistance and CD4⁺T cell counts in patients with HIV antiretroviral therapy (ART) in China from 2003 to 2015. Methods: Data were extracted from the Chinese National HIVDR Surveillance database from 2003 to 2015. For this study, the data collected were as follows: having received ART for ≥12 months; 18 years or older; demographic characteristics, information of ART, CD4⁺T cell counts, viral load (VL) and HIV drug resistance of a total of 8 362 patients were collected. Multi-variables non-conditional logistic regression model was used to study the relationship between viral load, HIV drug resistance and CD4⁺T cell counts. Results: Participants with age of (41.8±10.5) years were enrolled in this study. Among them, 59.9% (5 009 cases) were men. The percentage of CD4⁺T cell counts <200 cells/μl in the total population was 17.9% (1 496 cases), the highest was in VL ≥1 000 copies/ml with drug resistance, which was 43.0% (397/923) , followed by VL 50-999 copies/ml with drug resistance, which was 31.1% (69/222), and the lowest was in VL 50-999 copies/ml without drug resistance 13.2% (273/2 068). Compared to VL 50-999 copies/ml without drug resistance, VL<50 copies/ml, VL 50-999 with drug resistance, VL≥1 000 copies/ml without drug resistance, and VL ≥1 000 copies/ml with drug resistance, the OR (95%CI) of CD4 <200 cells/μl were 0.9 (0.7-1.0), 3.2 (2.3-4.4), 2.6 (2.1-3.2), and 4.9 (4.0-5.9), respectively. Among 222 patients with VL 50-999 and HIVDR, the most frequent antiretroviral drugs were EFV and NVP, both of which were NNRTI, and whose percentage both were 94.1% (209 cases). The most frequent mutations were M184V/I (NNRTI), and the percentage was 26.1% (58 cases). The second one was K103N (NNRTI), and the percentage was 22.5% (50 cases). The percentage of V32L/E (PI) and V82A (PI) were lower, they were 0.9% (2 cases) and 0.5% (1 case) respectively. Conclusion Decreased CD4⁺T cell counts were associated with HIV drug resistance at low viraemia. In the case of low viral load, the most vulnerable were the NNRTI antiviral drugs such as EFV and NVP.

Pharmacokinetics (PK) is the study of the absorption, distribution, metabolism, and excretion (ADME) processes of a drug. Understanding PK properties is essential for drug development and precision medication. In this review we provided an overview of recent research on PK with focus on the following aspects: (1) an update on drug-metabolizing enzymes and transporters in the determination of PK, as well as advances in xenobiotic receptors and noncoding RNAs (ncRNAs) in the modulation of PK, providing new understanding of the transcriptional and posttranscriptional regulatory mechanisms that result in inter-individual variations in pharmacotherapy; (2) current status and trends in assessing drug-drug interactions, especially interactions between drugs and herbs, between drugs and therapeutic biologics, and microbiota-mediated interactions; (3) advances in understanding the effects of diseases on PK, particularly changes in metabolizing enzymes and transporters with disease progression; (4) trends in mathematical modeling including physiologically-based PK modeling and novel animal models such as CRISPR/Cas9-based animal models for DMPK studies; (5) emerging non-classical xenobiotic metabolic pathways and the involvement of novel metabolic enzymes, especially non-P450s. Existing challenges and perspectives on future directions are discussed, and may stimulate the development of new research models, technologies, and strategies towards the development of better drugs and improved clinical practice.