Obesity is related to many diseases,such as diabetes,hypertension,angina pectoris and arthritis,and has become an increasingly serious global public health problem.Chronic low-grade inflammation and activation of immune system are involved in pathogenesis of obesity-related insulin resistance.Insulin is only hormone that can lower blood sugar,and works through insulin signaling pathway.Under normal circumstances,interaction of pro-inflammatory and anti-inflammatory system maintains immune homeostasis.Dynamic balance of pro-inflammatory and anti-inflammatory reactions determines occurrence,development and outcome of inflamma-tion.Activation of inflammatory signaling pathways can induce insulin resistance in central and peripheral tissues,and Toll-like recep-tor 4(TLR4)signaling pathway is one of important pathways that produce pro-inflammatory responses.It has known high-fat diet is associated with chronic low-grade inflammation,which may due to saturated fatty acids activate TLR4 receptors,stimulate expression of inflammatory cytokines,and inhibit insulin signal transduction.In anti-inflammatory system,cholinergic anti-inflammatory pathway(CAP)is a neuroimmunological regulation pathway,which is fast,reversible,accurate and can adapt to changes in inflammatory input signals,which is mainly composed of vagus nerve,spleen and splenic sympathetic nerve,acetylcholine and α7 nicotinic acetyl-choline receptor(α7nAChR).Activation of CAP can improve obesity-induced inflammation and insulin resistance.This review focus on obesity-mediated inflammation,CAP anti-inflammatory pathways,and their relationship with insulin resistance,in order to enrich molecular immune mechanism of insulin resistance,and provide a basis for research of anti-inflammatory diagnosis and treatment of insulin resistance-related diseases.

Model informed precision dosing (MIPD) is a new concept to guide precision dosing for individual patient by modeling and simulation based on the available information about the individual patient, medications and the disease. Compared to the empirical dosing, MIPD could improve the efficacy, safety, economics and adherence of the pharmacotherapy according to the individual's pathophysiology, genotyping and disease progression. This consensus report provides a brief account of the concept, methodology and implementation of MIPD as well as clinical decision supporting systems for MIPD. The status and future advancing of MIPD was also discussed to facilitate the appropriate application and development of MIPD in China.

With the increasing cost of drug development and clinical trials, it is of great value to make full use of all kinds of data to improve the efficiency of drug development and to provide valid information for medication guidelines. Model-based meta-analysis (MBMA) combines mathematical models with meta-analysis to integrate information from multiple sources (preclinical and clinical data, etc.) and multiple dimensions (targets/mechanisms, pharmacokinetics/pharmacodynamics, diseases/indications, populations, regimens, biomarkers/efficacy/safety, etc.), which not only provides decision-making for all key points of drug development, but also provides effective information for rational drug use and cost-effectiveness analysis. The classical meta-analysis requires high homogeneity of the data, while MBMA can combine and analyze the heterogeneous data of different doses, different time courses, and different populations through modeling, so as to quantify the dose-effect relationship, time-effect relationship, and the relevant impact factors, and thus the efficacy or safety features at the level of dose, time and covariable that have not been involved in previous studies. Although the modeling and simulation methods of MBMA are similar to population pharmacokinetics/pharmacodynamics (Pop PK/PD), compared with Pop PK/PD, the advantage of MBMA is that it can make full use of literature data, which not only improves the strength of evidence, but also can answer the questions that have not been proved or can not be answered by a single study. At present, MBMA has become one of the important methods in the strategy of model-informed drug development (MIDD). This paper will focus on the application value, data analysis plan, data acquisition and processing, data analysis and reporting of MBMA, in order to provide reference for the application of MBMA in drug development and clinical practice.

We conducted a randomized, open-label, parallel-controlled, multicenter trial on the use of Shuanghuanglian (SHL), a traditional Chinese patent medicine, in treating cases of COVID-19. A total of 176 patients received SHL by three doses (56 in low dose, 61 in middle dose, and 59 in high dose) in addition to standard care. The control group was composed of 59 patients who received standard therapy alone. Treatment with SHL was not associated with a difference from standard care in the time to disease recovery. Patients with 14-day SHL treatment had significantly higher rate in negative conversion of SARS-CoV-2 in nucleic acid swab tests than the patients from the control group (93.4% vs. 73.9%, P = 0.006). Analysis of chest computed tomography images showed that treatment with high-dose SHL significantly promoted absorption of inflammatory focus of pneumonia, which was evaluated by density reduction of inflammatory focus from baseline, at day 7 (mean difference (95% CI), -46.39 (-86.83 to -5.94) HU; P = 0.025) and day 14 (mean difference (95% CI), -74.21 (-133.35 to -15.08) HU; P = 0.014). No serious adverse events occurred in the SHL groups. This study illustrated that SHL in combination with standard care was safe and partially effective for the treatment of COVID-19.
COVID-19 ; Humans ; Medicine, Chinese Traditional ; Research ; SARS-CoV-2 ; Treatment Outcome