Introducing PIONEER: a project to harness big data in prostate cancer research

Prostate Cancer Diagnosis and Treatment Enhancement Through the Power of Big Data in Europe (PIONEER) is a European network of excellence for big data in prostate cancer, consisting of 32 private and public stakeholders from 9 countries across Europe. Launched by the Innovative Medicines Initiative 2 and part of the Big Data for Better Outcomes Programme (BD4BO), the overarching goal of PIONEER is to provide high-quality evidence on prostate cancer management by unlocking the potential of big data. The project has identified critical evidence gaps in prostate cancer care, via a detailed prioritization exercise including all key stakeholders. By standardizing and integrating existing high-quality and multidisciplinary data sources from patients with prostate cancer across different stages of the disease, the resulting big data will be assembled into a single innovative data platform for research. Based on a unique set of methodologies, PIONEER aims to advance the field of prostate cancer care with a particular focus on improving prostate-cancer-related outcomes, health system efficiency by streamlining patient management, and the quality of health and social care delivered to all men with prostate cancer and their families worldwide.Prostate Cancer Diagnosis and Treatment Enhancement Through the Power of Big Data in Europe (PIONEER) is a European network of excellence for big data in prostate cancer, consisting of 32 private and public stakeholders from 9 countries across Europe. In this Perspectives article, the authors introduce the PIONEER project and describe its aims and plans for ultimately improving prostate cancer care through the use of big data

The Cholecystectomy As A Day Case (CAAD) Score: A Validated Score of Preoperative Predictors of Successful Day-Case Cholecystectomy Using the CholeS Data Set

Background Day-case surgery is associated with significant patient and cost benefits. However, only 43% of cholecystectomy patients are discharged home the same day. One hypothesis is day-case cholecystectomy rates, defined as patients discharged the same day as their operation, may be improved by better assessment of patients using standard preoperative variables. Methods Data were extracted from a prospectively collected data set of cholecystectomy patients from 166 UK and Irish hospitals (CholeS). Cholecystectomies performed as elective procedures were divided into main (75%) and validation (25%) data sets. Preoperative predictors were identified, and a risk score of failed day case was devised using multivariate logistic regression. Receiver operating curve analysis was used to validate the score in the validation data set. Results Of the 7426 elective cholecystectomies performed, 49% of these were discharged home the same day. Same-day discharge following cholecystectomy was less likely with older patients (OR 0.18, 95% CI 0.15–0.23), higher ASA scores (OR 0.19, 95% CI 0.15–0.23), complicated cholelithiasis (OR 0.38, 95% CI 0.31 to 0.48), male gender (OR 0.66, 95% CI 0.58–0.74), previous acute gallstone-related admissions (OR 0.54, 95% CI 0.48–0.60) and preoperative endoscopic intervention (OR 0.40, 95% CI 0.34–0.47). The CAAD score was developed using these variables. When applied to the validation subgroup, a CAAD score of ≤5 was associated with 80.8% successful day-case cholecystectomy compared with 19.2% associated with a CAAD score >5 (p < 0.001). Conclusions The CAAD score which utilises data readily available from clinic letters and electronic sources can predict same-day discharges following cholecystectomy

Assessing the immediate outcomes and etiology of comatose adult subjects

Introduction: Adult subjects who are a comatose present challenge to the treating healthcare professionals in Indian subjects. Prompt and proper handling of these subjects is vital to attain favorable outcomes. Attaining the diagnosis based on the etiology is vital to handle these subjects properly. Aims: The present study was conducted to assess the immediate outcomes and etiology of comatose adult subjects in Indian settings. Methods: The present prospective and observational clinical study included 150 adult comatose subjects admitted for etiologies other than non-traumatic cases and GCS of less than/equal to 10 in the Indian healthcare center.&nbsp; In malignancy cases, 1.49% (n=1) subject died, whereas, 3.61% (n=3) subjects survived, in snake bite 5.97% (n=4) subjects died and 4.81% (n=4) subjects survived, in infection, 7.46% (n=5) subjects died and 19.27% (n=16) subjects survived, in metabolic cause, 13.43% (n=9) subjects died and 40.96% (n=34) subjects survived, and in stroke as etiology, 71.64% (n=48) subjects died and 31.32% (n=26) subjects survived. Based on GCS scores, 30% (n=45) subjects had GCS score of 3-6 where 56.71% (n=38) subjects died and 8.43% (n=7) subjects survived, whereas, there were 70% (n=105) subjects with GCS score of 7-10 where 43.28% (n=29) subjects died and 91.56% (n=76) subjects survived

Tribological properties of CNT-filled epoxy-carbon fabric composites: Optimization and modelling by machine learning

Polymer matrix composites reinforced with fibers/fillers are extensively used in several tribological components of automotive and boating applications. The mechanical performance of polymer composites improves by incorporating nanofillers as secondary reinforcement. The present research work fabricated carbon fabric-reinforced epoxy composites using the hand layup. The carbon fabric-reinforced polymer composites were fabricated with 0.1 wt%, 0.2 wt%, and 0.5 wt% of carbon nanotubes (CNT) fillers as secondary reinforcement. Tribological properties of carbon fabric-reinforced epoxy composites filled with CNT have been carried out using a pin‐on‐disc method. Adding fillers significantly improves the tribological behaviour of the carbon fabric-reinforced epoxy composites by reducing wear rate and coefficient of friction. The large surface area of interaction due to the higher aspect ratio of CNT shows improved adhesion between epoxy matrix and carbon fabrics. It improves the various mechanical and tribological characteristics of composites—also, an analysis of worn surfaces is carried out to analyze the wear mechanisms using scanning electronic microscopy. The research employs a combination of experimental analyses and machine learning (ML) techniques to explore the wear resistance, hardness, and predictive modeling of volume loss in the composites. The hyperparameter fine-tuning of ML algorithms, including Random Forest (RF), k-Nearest Neighbors (KNN), and XGBoost, demonstrates superior predictive capabilities, particularly with RF. The study bridges material science, ML, and practical applications, contributing valuable insights for developing advanced composite materials

Predictors of Occupational Burnout: A Systematic Review.

We aimed to review occupational burnout predictors, considering their type, effect size and role (protective versus harmful), and the overall evidence of their importance. MEDLINE, PsycINFO, and Embase were searched from January 1990 to August 2018 for longitudinal studies examining any predictor of occupational burnout among workers. We arranged predictors in four families and 13 subfamilies of homogenous constructs. The plots of z-scores per predictor type enabled graphical discrimination of the effects. The vote-counting and binomial test enabled discrimination of the effect direction. The size of the effect was estimated using Cohen's formula. The risk of bias and the overall evidence were assessed using the MEVORECH and GRADE methods, respectively. Eighty-five studies examining 261 predictors were included. We found a moderate quality of evidence for the harmful effects of the job demands subfamily (six predictors), and negative job attitudes, with effect sizes from small to medium. We also found a moderate quality of evidence for the protective effect of adaptive coping (small effect sizes) and leisure (small to medium effect sizes). Preventive interventions for occupational burnout might benefit from intervening on the established predictors regarding reducing job demands and negative job attitudes and promoting adaptive coping and leisure

Induction of transplantation tolerance in non-human primate preclinical models

Short-term outcomes following organ transplantation have improved considerably since the availability of cyclosporine ushered in the modern era of immunosuppression. In spite of this, many of the current limitations to progress in the field are directly related to the existing practice of relatively non-specific immunosuppression. These include increased risks of opportunistic infection and cancer, and toxicity associated with long-term immunosuppressive drug exposure. In addition, long-term graft loss continues to result in part from a failure to adequately control the anti-donor immune response. The development of a safe and reliable means of inducing tolerance would ameliorate these issues and improve the lives of transplant recipients, yet given the improving clinical standard of care, the translation of new therapies has become appropriately more cautious and dependent on increasingly predictive preclinical models. While convenient and easy to use, rodent tolerance models have not to date been reliably capable of predicting a therapy's potential efficacy in humans. Non-human primates possess an immune system that more closely approximates that found in humans, and have served as a more rigorous preclinical testing ground for novel therapies. Prior to clinical adaptation therefore, tolerance regimens should be vetted in non-human primates to ensure that there is sufficient potential for efficacy to justify the risk of its application

The potential for agro-industrial waste utilization using oleaginous yeast for the production of biodiesel

Abstract Environmental problems are making it necessary to find renewable and sustainable alternatives to fossil fuels in the field of transport. Biodiesel may replace diesel fuel under an environmentally friendly and economically sound process, as long as the raw material employed is of low cost and can be derived from sustainable sources. Such an alternative feedstock from non-vegetable sources could be provided by microbial oil produced by oleaginous microorganisms that may possess similar chemical composition to that of the most commonly used vegetable oils in the biodiesel industry. Moreover, oleaginous yeasts could accumulate intracellular lipids through cultivation on various agro-industrial wastes. Oleaginous yeasts may accumulate different amounts of microbial oil with varying fatty acid profiles, depending on the substrate or growing conditions. This review presents the most relevant aspects regarding yeast oil production using agro-industrial waste as culture media and evaluates the potential of this microbial oil as feedstock for biodiesel production