Adcockcochrane7208

Acute lung injury (ALI) is a potentially life-threatening, devastating disease with an extremely high rate of mortality. The underlying mechanism of ALI is currently unclear. In this study, we aimed to confirm the hub genes associated with ALI and explore their functions and molecular mechanisms using bioinformatics methods. Five microarray datasets available in GEO were used to perform Robust Rank Aggregation (RRA) to identify differentially expressed genes (DEGs) and the key genes were identified via the protein-protein interaction (PPI) network. Lipopolysaccharide intraperitoneal injection was administered to establish an ALI model. Overall, 40 robust DEGs, which are mainly involved in the inflammatory response, protein catabolic process, and NF-κB signaling pathway were identified. Among these DEGs, we identified two genes associated with ALI, of which the CAV-1/NF-κB axis was significantly upregulated in ALI, and was identified as one of the most effective targets for ALI prevention. Subsequently, the expression of CAV-1 was knocked down using AAV-shCAV-1 or CAV-1-siRNA to study its effect on the pathogenesis of ALI in vivo and in vitro. The results of this study indicated that CAV-1/NF-κB axis levels were elevated in vivo and in vitro, accompanied by an increase in lung inflammation and autophagy. The knockdown of CAV-1 may improve ALI. Mechanistically, inflammation was reduced mainly by decreasing the expression levels of CD3 and F4/80, and activating autophagy by inhibiting AKT/mTOR and promoting the AMPK signaling pathway. Taken together, this study provides crucial evidence that CAV-1 knockdown inhibits the occurrence of ALI, suggesting that the CAV-1/NF-κB axis may be a promising therapeutic target for ALI treatment.Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease with a rapid progression and no effective treatment. Metabolic and mitochondrial alterations in peripheral tissues of ALS patients may present diagnostic and therapeutic interest. We aimed to identify mitochondrial fingerprints in lymphoblast from ALS patients harboring SOD1 mutations (mutSOD1) or with unidentified mutations (undSOD1), compared with age-/sex-matched controls. Three groups of lymphoblasts, from mutSOD1 or undSOD1 ALS patients and age-/sex-matched controls, were obtained from Coriell Biobank and divided into 3 age-/sex-matched cohorts. Mitochondria-associated metabolic pathways were analyzed using Seahorse MitoStress and ATP Rate assays, complemented with metabolic phenotype microarrays, metabolite levels, gene expression, and protein expression and activity. Pooled (all cohorts) and paired (intra-cohort) analyses were performed by using bioinformatic tools, and the features with higher information gain values were selected and used for principal component analysis and Naïve Bayes classification. Considering the group as a target, the features that contributed to better segregation of control, undSOD1, and mutSOD1 were found to be the protein levels of Tfam and glycolytic ATP production rate. Metabolic phenotypic profiles in lymphoblasts from ALS patients with mutSOD1 and undSOD1 revealed unique age-dependent different substrate oxidation profiles. For most parameters, different patterns of variation in experimental endpoints in lymphoblasts were found between cohorts, which may be due to the age or sex of the donor. In the present work, we investigated several metabolic and mitochondrial hallmarks in lymphoblasts from each donor, and although a high heterogeneity of results was found, we identified specific metabolic and mitochondrial fingerprints, especially protein levels of Tfam and glycolytic ATP production rate, that may have a diagnostic and therapeutic interest.The tumour stroma, and in particular the extracellular matrix (ECM), is a salient feature of solid tumours that plays a crucial role in shaping their progression. Many desmoplastic tumours including breast cancer involve the significant accumulation of type I collagen. However, recently it has become clear that the precise distribution and organisation of matrix molecules such as collagen I is equally as important in the tumour as their abundance. Cancer-associated fibroblasts (CAFs) coexist within breast cancer tissues and play both pro- and anti-tumourigenic roles through remodelling the ECM. Here, using temporal proteomic profiling of decellularized tumours, we interrogate the evolving matrisome during breast cancer progression. We identify 4 key matrisomal clusters, and pinpoint collagen type XII as a critical component that regulates collagen type I organisation. Through combining our proteomics with single-cell transcriptomics, and genetic manipulation models, we show how CAF-secreted collagen XII alters collagen I organisation to create a pro-invasive microenvironment supporting metastatic dissemination. Finally, we show in patient cohorts that collagen XII may represent an indicator of breast cancer patients at high risk of metastatic relapse.This paper describes the development and implementation of an anesthesia data warehouse in the Lille University Hospital. We share the lessons learned from a ten-year project and provide guidance for the implementation of such a project. Our clinical data warehouse is mainly fed with data collected by the anesthesia information management system and hospital discharge reports. The data warehouse stores historical and accurate data with an accuracy level of the day for administrative data, and of the second for monitoring data. Datamarts complete the architecture and provide secondary computed data and indicators, in order to execute queries faster and easily. Between 2010 and 2021, 636 784 anesthesia records were integrated for 353 152 patients. We reported the main concerns and barriers during the development of this project and we provided 8 tips to handle them. We have implemented our data warehouse into the OMOP common data model as a complementary downstream data model. The next step of the project will be to disseminate the use of the OMOP data model for anesthesia and critical care, and drive the trend towards federated learning to enhance collaborations and multicenter studies.The marginal ice zone is the dynamic interface between the open ocean and consolidated inner pack ice. Surface gravity waves regulate marginal ice zone extent and properties, and, hence, atmosphere-ocean fluxes and ice advance/retreat. this website Over the past decade, seminal experimental campaigns have generated much needed measurements of wave evolution in the marginal ice zone, which, notwithstanding the prominent knowledge gaps that remain, are underpinning major advances in understanding the region's role in the climate system. Here, we report three-dimensional imaging of waves from a moving vessel and simultaneous imaging of floe sizes, with the potential to enhance the marginal ice zone database substantially. The images give the direction-frequency wave spectrum, which we combine with concurrent measurements of wind speeds and reanalysis products to reveal the complex multi-component wind-plus-swell nature of a cyclone-driven wave field, and quantify evolution of large-amplitude waves in sea ice.Genitourinary surgeons and oncologists are particularly interested in whether a robotic surgery improves times to Prostate Specific Antigen (PSA) recurrence compared to a non-robotic surgery for removing the cancerous prostate. Time to PSA recurrence is an example of a survival time that is typically interval-censored between two consecutive clinical inspections with opposite test results. In addition, success of medical devices and technologies often depends on factors such as experience and skill level of the medical service providers, thus leading to clustering of these survival times. For analyzing the effects of surgery types and other covariates on median of clustered interval-censored time to post-surgery PSA recurrence, we present three competing novel models and associated frequentist and Bayesian analyses. The first model is based on a transform-both-sides of survival time with Gaussian random effects to account for the within-cluster association. Our second model assumes an approximate marginal Laplace distribution for the transformed log-survival times with a Gaussian copula to accommodate clustering. Our third model is a special case of the second model with Laplace distribution for the marginal log-survival times and Gaussian copula for the within-cluster association. Simulation studies establish the second model to be highly robust against extreme observations while estimating median regression coefficients. We provide a comprehensive comparison among these three competing models based on the model properties and the computational ease of their Frequentist and Bayesian analysis. We also illustrate the practical implementations and uses of these methods via analysis of a simulated clustered interval-censored data-set similar in design to a post-surgery PSA recurrence study.Focusing on non-ergodic macroscopic systems, we reconsider the variances [Formula see text] of time averages [Formula see text] of time-series [Formula see text]. The total variance [Formula see text] (direct average over all time series) is known to be the sum of an internal variance [Formula see text] (fluctuations within the meta-basins) and an external variance [Formula see text] (fluctuations between meta-basins). It is shown that whenever [Formula see text] can be expressed as a volume average of a local field [Formula see text] the three variances can be written as volume averages of correlation functions [Formula see text], [Formula see text] and [Formula see text] with [Formula see text]. The dependences of the [Formula see text] on the sampling time [Formula see text] and the system volume V can thus be traced back to [Formula see text] and [Formula see text]. Various relations are illustrated using lattice spring models with spatially correlated spring constants. .Developing underwater adhesives that can rapidly and reversibly switch the adhesion in wet conditions is important in various industrial and biomedical applications. Despite extensive progresses, the manifestation of underwater adhesion with rapid reversibility remains a big challenge. Here, we report a simple strategy that achieves strong underwater adhesion between two surfaces as well as rapid and reversible detachment in on-demand manner. Our approach leverages on the design of patterned hybrid wettability on surfaces that selectively creates a spatially confined integral air shell to preserve the water bridge in underwater environment. The overall adhesion strength can be multiplied by introducing multiple air shells and rapidly broken by disturbing the integrity of the protective air shell in response to the applied voltage on two surfaces. Our design can be constructed on the flexible substrate with hybrid wettability, which can be applied to non-conductive substrates and adapted to more complicated morphologies, extending the choice of underlying materials.Sport-related concussions can result from a single high magnitude impact that generates concussive symptoms, repeated subconcussive head impacts aggregating to generate concussive symptoms, or a combined effect from the two mechanisms. The array of symptoms produced by these mechanisms may be clinically interpreted as a sport-related concussion. It was hypothesized that head impact exposure resulting in concussion is influenced by severity, total number, and frequency of subconcussive head impacts. The influence of total number and magnitude of impacts was previously explored, but frequency was investigated to a lesser degree. In this analysis, head impact frequency was investigated over a new metric called 'time delta', the time difference from the first recorded head impact of the day until the concussive impact. Four exposure metrics were analyzed over the time delta to determine whether frequency of head impact exposure was greater for athletes on their concussion date relative to other dates of contact participation.