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Non-alcoholic fatty liver disease (NAFLD) is gaining in importance and is linked to obesity. Especially,thedevelopmentoffibrosisandportalhypertensioninNAFLDpatientsrequirestreatment. Transgenic TGR(mREN2)27 rats overexpressing mouse renin spontaneously develop NAFLD with portal hypertension but without obesity. This study investigated the additional role of obesity in this model on the development of portal hypertension and fibrosis. Obesity was induced in twelve-week old TGR(mREN2)27 rats after receiving Western diet (WD) for two or four weeks. Liver fibrosis was assessed using standard techniques. Hepatic expression of transforming growth factor-β1 (TGF-β1), collagen type Iα1, α-smooth muscle actin, and the macrophage markers Emr1, as well as the chemoattractant Ccl2, interleukin-1β (IL1β) and tumor necrosis factor-α (TNFα) were analyzed. Assessment of portal and systemic hemodynamics was performed using the colored microsphere technique. Asexpected,WDinducedobesityandliverfibrosisasconfirmedbySiriusRedandOilRed O staining. The expression of the monocyte-macrophage markers, Emr1, Ccl2, IL1β and TNFα were increasedduringfeedingofWD,indicatinginfiltrationofmacrophagesintotheliver,eventhoughthis increase was statistically not significant for the EGF module-containing mucin-like receptor (Emr1) mRNA expression levels. Of note, portal pressure increased with the duration of WD compared to animals that received a normal chow. Besides obesity, WD feeding increased systemic vascular resistance reflecting systemic endothelial and splanchnic vascular dysfunction. We conclude that transgenic TGR(mREN2)27 rats are a suitable model to investigate NAFLD development with liver fibrosis and portal hypertension. Tendency towards elevated expression of Emr1 is associated with macrophage activity point to a significant role of macrophages in NAFLD pathogenesis, probably due to a shift of the renin–angiotensin system towards a higher activation of the classical pathway. The hepatic injury induced by WD in TGR(mREN2)27 rats is suitable to evaluate different stages of fibrosis and portal hypertension in NAFLD with obesity.
Pre-publication peer review of scientific literature in its present state suffers from a lack of evaluation validity and transparency to the community. Inspired by social networks, we propose a framework for the open exchange of post-publication evaluation to complement the current system. We first formulate a number of necessary conditions that should be met by any design dedicated to perform open scientific evaluation. To introduce our framework, we provide a basic data standard and communication protocol. We argue for the superiority of a provider-independent framework, over a few isolated implementations, which allows the collection and analysis of open evaluation content across a wide range of diverse providers like scientific journals, research institutions, social networks, publishers websites, and more. Furthermore, we describe how its technical implementation can be achieved by using existing web standards and technology. Finally, we illustrate this with a set of examples and discuss further potential.
As new generations of targeted therapies emerge and tumor genome sequencing discovers increasingly comprehensive mutation repertoires, the functional relationships of mutations to tumor phenotypes remain largely unknown. Here, we measured ex vivo sensitivity of 246 blood cancers to 63 drugs alongside genome, transcriptome, and DNA methylome analysis to understand determinants of drug response. We assembled a primary blood cancer cell encyclopedia data set that revealed disease-specific sensitivities for each cancer. Within chronic lymphocytic leukemia (CLL), responses to 62% of drugs were associated with 2 or more mutations, and linked the B cell receptor (BCR) pathway to trisomy 12, an important driver of CLL. Based on drug responses, the disease could be organized into phenotypic subgroups characterized by exploitable dependencies on BCR, mTOR, or MEK signaling and associated with mutations, gene expression, and DNA methylation. Fourteen percent of CLLs were driven by mTOR signaling in a non–BCR-dependent manner. Multivariate modeling revealed immunoglobulin heavy chain variable gene (IGHV) mutation status and trisomy 12 as the most important modulators of response to kinase inhibitors in CLL. Ex vivo drug responses were associated with outcome. This study overcomes the perception that most mutations do not influence drug response of cancer, and points to an updated approach to understanding tumor biology, with implications for biomarker discovery and cancer care.
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
Background: The aim of this study was to identify pre-operative parameters able to predict length of stay (LoS) based on clinical data and patient-reported outcome measures (PROMs) from a scorecard database in patients with significant aortic stenosis who underwent TAVI (transfemoral aortic valve implantation). Methods: 302 participants (51.7% males, age range 78.2–84.2 years.) were prospectively recruited. After computing the median LoS value (=6 days, range = 5–8 days), we implemented a decision tree algorithm by setting dichotomized values at median LoS as the dependent variable and assessed baseline clinical variables and PROMs (Clinical Frailty Scale (CFS), EuroQol-5 Dimension-5 Levels (EQ-5D) and Kansas City Cardiomyopathy Questionnaire (KCCQ)) as potential predictors. Results: Among clinical parameters, only peripheral arterial disease (p = 0.029, HR = 1.826) and glomerular filtration rate (GFR, cut-off < 33 mL/min/1.73 m2, p = 0.003, HR = 2.252) were predictive of LoS. Additionally, two PROMs (CFS; cut-off = 3, p < 0.001, HR = 1.324 and KCCQ; cut-off = 30, p = 0.003, HR = 2.274) were strong predictors. Further, a risk score for LoS (RS_LoS) was calculated based on these predictors. Patients with RS_LoS = 0 had a median LoS of 5 days; patients RS_LoS ≥ 3 had a median LoS of 8 days. Conclusions: based on the pre-operative values of the above four predictors, a personalized prediction of LoS after TAVI can be achieved.
Simulation results for future measurements of electromagnetic proton form factors at PANDA (FAIR) within the PandaRoot software framework are reported. The statistical precision with which the proton form factors can be determined is estimated. The signal channel p¯p→e+e− is studied on the basis of two different but consistent procedures. The suppression of the main background channel, i.e. p¯p→π+π−, is studied. Furthermore, the background versus signal efficiency, statistical and systematical uncertainties on the extracted proton form factors are evaluated using two different procedures. The results are consistent with those of a previous simulation study using an older, simplified framework. However, a slightly better precision is achieved in the PandaRoot study in a large range of momentum transfer, assuming the nominal beam conditions and detector performance.
