Highlights d Discovery of prognosis-associated proteins and pathways at early stage of LUAD d Proteomics revealed three subtypes related to clinical and molecular features d Identification of subtype-specific kinases and cancerassociated phosphoproteins d Identification of potential prognostic biomarkers and drug targets in LUAD

This study provides evidence that low shear stress enhances PCSK9 expression in concert with ROS generation in vascular ECs and SMCs. ROS seem to regulate PCSK9 expression. We propose that PCSK9-ROS interaction may be important in the development of atherosclerosis in arterial channels with low shear stress.

BackgroundWith the rise of the aging population, it is particularly important for health services to be used fairly and reasonably in the elderly. This study aimed to assess the present inequality and horizontal inequity for health service use among the elderly in China and to identify the main determinants associated with the disparity.MethodsThis cross-sectional study was based on the sample of the survey of the China Health and Retirement Longitudinal Study (CHARLS) for 2015. The elderly was defined as individuals aged 60 and above, with a total of 7836 participants. We used the concentration index (CI) and the horizontal inequity (HI) to measure the inequity of the utilization of health services. The method of concentration index decomposition was utilized to measure the contribution of various influential factors to the overall unfairness.ResultsThe CI for the probability and the frequency of outpatient use were 0.1102 and 0.1015, respectively, and the corresponding values of inpatient use were 0.2777 and 0.2980, respectively. The household consumption expenditure disparity was the greatest inequality factor favoring the better-off. The Urban Employee Basic Medical Insurance made a pro-wealth contribution to inequality in frequency of health services utilization (17.58% for outpatient and 13.40% for inpatient). The contributions of New Rural Cooperative Medical Scheme on reducing unfairness in inpatient use were limited (− 2.23% for probability of inpatient use and − 5.89% for frequency of inpatient use).ConclusionsThere was a strong pro-rich inequality in both the probability and the frequency of use for health services among the elderly in China. The medical insurance was not enough to address this inequity, and different medical insurance schemes had different effects on the unfairness of health service utilization.Electronic supplementary materialThe online version of this article (10.1186/s12939-018-0861-6) contains supplementary material, which is available to authorized users.

Development of noninvasive, reliable biomarkers for lung cancer diagnosis has many clinical benefits knowing that most of lung cancer patients are diagnosed at the late stage. For this purpose, we conducted proteomic analyses of 231 human urine samples in healthy individuals (n = 33), benign pulmonary diseases (n = 40), lung cancer (n = 33), bladder cancer (n = 17), cervical cancer (n = 25), colorectal cancer (n = 22), esophageal cancer (n = 14), and gastric cancer (n = 47) patients collected from multiple medical centers. By random forest modeling, we nominated a list of urine proteins that could separate lung cancers from other cases. With a feature selection algorithm, we selected a panel of five urinary biomarkers (FTL: Ferritin light chain; MAPK1IP1L: Mitogen-Activated Protein Kinase 1 Interacting Protein 1 Like; FGB: Fibrinogen Beta Chain; RAB33B: RAB33B, Member RAS Oncogene Family; RAB15: RAB15, Member RAS Oncogene Family) and established a combinatorial model that can correctly classify the majority of lung cancer cases both in the training set (n = 46) and the test sets (n = 14–47 per set) with an AUC ranging from 0.8747 to 0.9853. A combination of five urinary biomarkers not only discriminates lung cancer patients from control groups but also differentiates lung cancer from other common tumors. The biomarker panel and the predictive model, when validated by more samples in a multi-center setting, may be used as an auxiliary diagnostic tool along with imaging technology for lung cancer detection.

Some debates exist regarding the association of coffee consumption with hypertension risk. We performed a meta-analysis including dose-response analysis aimed to derive a more quantitatively precise estimation of this association. PubMed and Embase were searched for cohort studies published up to 18 July 2017. Fixed-effects generalized least-squares regression models were used to assess the quantitative association between coffee consumption and hypertension risk across studies. Restricted cubic spline was used to model the dose-response association. We identified eight articles (10 studies) investigating the risk of hypertension with the level of coffee consumption, including 243,869 individuals and 58,094 incident cases of hypertension. We found no evidence of a nonlinear dose-response association of coffee consumption and hypertension (P = 0.243). The risk of hypertension was reduced by 2% (relative risk (RR) = 0.98, 95% confidence interval (CI) 0.98-0.99) with each one cup/day increment of coffee consumption. With the linear cubic spline model, the RRs of hypertension risk were 0.97 (95% CI 0.95-0.99), 0.95 (95% CI 0.91-0.99), 0.92 (95% CI 0.87-0.98), and 0.90 (95% CI 0.83-0.97) for 2, 4, 6, and 8 cups/day, respectively, compared with individuals with no coffee intakes. This meta-analysis provides quantitative evidence that consumption of coffee was inversely associated with the risk of hypertension in a dose-response manner.