BackgroundThe beneficial outcome associated with the use of proton pump inhibitors (PPIs) in idiopathic pulmonary fibrosis (IPF) has been reported in retrospective studies. To date, no prospective study has been conducted to confirm these outcomes. In addition, the potential mechanism by which PPIs improve measures of lung function and/or transplant-free survival in IPF has not been elucidated.MethodsHere, we used biochemical, cell biological and preclinical studies to evaluate regulation of markers associated with inflammation and fibrosis. In our in vitro studies, we exposed primary lung fibroblasts, epithelial and endothelial cells to ionizing radiation or bleomycin; stimuli typically used to induce inflammation and fibrosis. In addition, we cultured lung fibroblasts from IPF patients and studied the effect of esomeprazole on collagen release. Our preclinical study tested efficacy of esomeprazole in a rat model of bleomycin-induced lung injury. Furthermore, we performed retrospective analysis of interstitial lung disease (ILD) databases to examine the effect of PPIs on transplant-free survival.ResultsThe cell culture studies revealed that esomeprazole controls inflammation by suppressing the expression of pro-inflammatory molecules including vascular cell adhesion molecule-1, inducible nitric oxide synthase, tumor necrosis factor-alpha (TNF-α) and interleukins (IL-1β and IL-6). The antioxidant effect is associated with strong induction of the stress-inducible cytoprotective protein heme oxygenase-1 (HO1) and the antifibrotic effect is associated with potent inhibition of fibroblast proliferation as well as downregulation of profibrotic proteins including receptors for transforming growth factor β (TGFβ), fibronectin and matrix metalloproteinases (MMPs). Furthermore, esomeprazole showed robust effect in mitigating the inflammatory and fibrotic responses in a murine model of acute lung injury. Finally, retrospective analysis of two ILD databases was performed to assess the effect of PPIs on transplant-free survival in IPF patients. Intriguingly, this data demonstrated that IPF patients on PPIs had prolonged survival over controls (median survival of 3.4 vs 2 years).ConclusionsOverall, these data indicate the possibility that PPIs may have protective function in IPF by directly modulating the disease process and suggest that they may have other clinical utility in the treatment of extra-intestinal diseases characterized by inflammatory and/or fibrotic phases.Electronic supplementary materialThe online version of this article (doi:10.1186/s12967-015-0614-x) contains supplementary material, which is available to authorized users.

ObjectiveTo evaluate the impact of body mass index (BMI) on survival of a Chinese cohort of medical patients with sepsis.DesignA single-centre prospective cohort study conducted from May 2015 to April 2017.SettingA tertiary care university hospital in China.ParticipantsA total of 178 patients with sepsis admitted to the medical intensive care unit (ICU) were included.Main outcome measuresThe primary outcome was 90-day mortality while the secondary outcomes were in-hospital mortality, length of ICU stay and length of hospital stay.ResultsThe median age (IQR) was 78 (66–84) years old, and 77.0% patients were older than 65 years. The 90-day mortality was 47.2%. The in-hospital mortality was 41.6%, and the length of ICU stay and hospital stay were 12 (5–22) and 15 (9–28) days, respectively. Cox proportional hazard regression analysis identified that Sequential Organ Failure Assessment score (HR=1.229, p<0.001), Acute Physiology and Chronic Health Evaluation II score (HR=1.050, p<0.001) and BMI (HR=0.940, p=0.029) were all independently associated with the 90-day mortality. Patients were divided into four groups based on BMI (underweight 33 (18.5%), normal 98 (55.1%), overweight 36 (20.2%) and obese 11 (6.2%)). The 90-day mortality (66.7%, 48.0%, 36.1% and 18.2%, p=0.015) and in-hospital mortality (60.6%, 41.8%, 30.6% and 18.2%, p=0.027) were statistically different among the four groups. Differences in survival among the four groups were demonstrated by Kaplan-Meier survival analysis (p=0.008), with the underweight patients showing a lower survival rate.ConclusionsBMI was an independent factor associated with 90-day survival in a Chinese cohort of medical patients with sepsis, with patients having a lower BMI at a higher risk of death.

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Background With the spread of COVID-19 from Wuhan, Hubei Province to other areas of the country, medical staff in Fever Clinics faced the challenge of identifying suspected cases among febrile patients with acute respiratory infections. We aimed to describe the prevalence and clinical features of COVID-19 as compared to pneumonias of other etiologies in a Fever Clinic in Beijing.

Shortwave solar radiation is an important component of the surface energy balance and provides the principal source of energy for terrestrial ecosystems. This paper presents a machine learning approach in the form of a random forest (RF) model for estimating daily downward solar radiation flux at the land surface over complex terrain using MODIS (MODerate Resolution Imaging Spectroradiometer) remote sensing data. The model-building technique makes use of a unique network of 16 solar flux measurements in the semi-arid Reynolds Creek Experimental Watershed and Critical Zone Observatory, in southwest Idaho, USA. Based on a composite RF model built on daily observations from all 16 sites in the watershed, the model simulation of downward solar radiation matches well with the observation data (r2 = 0.96). To evaluate model performance, RF models were built from 12 of 16 sites selected at random and validated against the observations at the remaining four sites. Overall root mean square errors (RMSE), bias, and mean absolute error (MAE) are small (range: 37.17 W/m2-81.27 W/m2, -48.31 W/m2-15.67 W/m2, and 26.56 W/m2-63.77 W/m2, respectively). When extrapolated to the entire watershed, spatiotemporal patterns of solar flux are largely consistent with expected trends in this watershed. We also explored significant predictors of downward solar flux in order to reveal important properties and processes controlling downward solar radiation. Based on the composite RF model built on all 16 sites, the three most important predictors to estimate downward solar radiation include the black sky albedo (BSA) near infrared band (0.858 μm), BSA visible band (0.3–0.7 μm), and clear day coverage. This study has important implications for improving the ability to derive downward solar radiation through a fusion of multiple remote sensing datasets and can potentially capture spatiotemporally varying trends in solar radiation that is useful for land surface hydrologic and terrestrial ecosystem modeling.