Dietary fibre to reduce colon cancer risk in Alaska Native people: the Alaska FIRST randomised clinical trial protocol

Introduction Diet, shown to impact colorectal cancer (CRC) risk, is a modifiable environmental factor. Fibre foods fermented by gut microbiota produce metabolites that not only provide food for the colonic epithelium but also exert regulatory effects on colonic mucosal inflammation and proliferation. We describe methods used in a double-blinded, randomised, controlled trial with Alaska Native (AN) people to determine if dietary fibre supplementation can substantially reduce CRC risk among people with the highest reported CRC incidence worldwide. Methods and analyses Eligible patients undergoing routine screening colonoscopy consent to baseline assessments and specimen/data collection (blood, urine, stool, saliva, breath and colon mucosal biopsies) at the time of colonoscopy. Following an 8-week stabilisation period to re-establish normal gut microbiota post colonoscopy, study personnel randomise participants to either a high fibre supplement (resistant starch, n=30) or placebo (digestible starch, n=30) condition, repeating stool sample collection. During the 28-day supplement trial, each participant consumes their usual diet plus their supplement under direct observation. On day 29, participants undergo a flexible sigmoidoscopy to obtain mucosal biopsy samples to measure the effect of the supplement on inflammatory and proliferative biomarkers of cancer risk, with follow-up assessments and data/specimen collection similar to baseline. Secondary outcome measures include the impact of a high fibre supplement on the oral and colonic microbiome and biofluid metabolome. Ethics and dissemination Approvals were obtained from the Alaska Area and University of Pittsburgh Institutional Review Boards and Alaska Native Tribal Health Consortium and Southcentral Foundation research review bodies. A data safety monitoring board, material transfer agreements and weekly study team meetings provide regular oversight throughout the study. Study findings will first be shared with AN tribal leaders, health administrators, providers and community members. Peer-reviewed journal articles and conference presentations will be forthcoming once approved by tribal review bodies

Prevalence and costs of hospitalizations for poisoning and accidental intoxication in Brazilian elderly

A cross-sectional study of secondary data/information obtained from the Hospital Information System (HIS) spanning the years 2008 - 2009 was performed. The distribution of the main hospital admissions by gender, age, color/race, region and federal unit of residence, average expenditure and average length of hospital stay, year of hospitalization and mortality rates (MR) were studied. The data collected were tabulated by TabNet and keyed into Microsoft Excel 2007. It was verified that elderly males (54.3%), from 60 to 69 years old (50.6%), nonwhites (36.3%) and residents of Southeast and North regions of the country had the highest rates of hospitalization. Seniors were hospitalized for an average of 4.8 days, and the major causes were exposure to alcohol (43.7%) and to drugs (33.9%). Expenses related to hospital admissions were, on average, R$ 529,817.70. The highest mortality rates were recorded among females (MR = 4.34), in elderly, 80 years or older (MR = 10.16) and Caucasians (MR = 3.95), where pharmacological substances with action on the Autonomic Nervous System were the leading cause of death. There are demographic differences in morbi-mortality of these elderly since, although men and younger elderly were the main victims, women and elderly of advanced age have greater mortality. The leading causes of hospitalization were alcohol and drugs

Search for jet extinction in the inclusive jet-pT spectrum from proton-proton collisions at s=8 TeV

Published by the American Physical Society under the terms of the Creative Commons Attribution 3.0 License. Further distribution of this work must maintain attribution to the author(s) and the published articles title, journal citation, and DOI.The first search at the LHC for the extinction of QCD jet production is presented, using data collected with the CMS detector corresponding to an integrated luminosity of 10.7  fb−1 of proton-proton collisions at a center-of-mass energy of 8 TeV. The extinction model studied in this analysis is motivated by the search for signatures of strong gravity at the TeV scale (terascale gravity) and assumes the existence of string couplings in the strong-coupling limit. In this limit, the string model predicts the suppression of all high-transverse-momentum standard model processes, including jet production, beyond a certain energy scale. To test this prediction, the measured transverse-momentum spectrum is compared to the theoretical prediction of the standard model. No significant deficit of events is found at high transverse momentum. A 95% confidence level lower limit of 3.3 TeV is set on the extinction mass scale

Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector

International audienceMeasurements of electrons from νe interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as searches for physics beyond the standard model, supernova neutrino detection, and solar neutrino measurements. This article describes the selection and reconstruction of low-energy (Michel) electrons in the ProtoDUNE-SP detector. ProtoDUNE-SP is one of the prototypes for the DUNE far detector, built and operated at CERN as a charged particle test beam experiment. A sample of low-energy electrons produced by the decay of cosmic muons is selected with a purity of 95%. This sample is used to calibrate the low-energy electron energy scale with two techniques. An electron energy calibration based on a cosmic ray muon sample uses calibration constants derived from measured and simulated cosmic ray muon events. Another calibration technique makes use of the theoretically well-understood Michel electron energy spectrum to convert reconstructed charge to electron energy. In addition, the effects of detector response to low-energy electron energy scale and its resolution including readout electronics threshold effects are quantified. Finally, the relation between the theoretical and reconstructed low-energy electron energy spectrum is derived and the energy resolution is characterized. The low-energy electron selection presented here accounts for about 75% of the total electron deposited energy. After the addition of missing energy using a Monte Carlo simulation, the energy resolution improves from about 40% to 25% at 50 MeV. These results are used to validate the expected capabilities of the DUNE far detector to reconstruct low-energy electrons

Rare disease gene association discovery in the 100,000 Genomes Project

Up to 80% of rare disease patients remain undiagnosed after genomic sequencing1, with many probably involving pathogenic variants in yet to be discovered disease–gene associations. To search for such associations, we developed a rare variant gene burden analytical framework for Mendelian diseases, and applied it to protein-coding variants from whole-genome sequencing of 34,851 cases and their family members recruited to the 100,000 Genomes Project2. A total of 141 new associations were identified, including five for which independent disease–gene evidence was recently published. Following in silico triaging and clinical expert review, 69 associations were prioritized, of which 30 could be linked to existing experimental evidence. The five associations with strongest overall genetic and experimental evidence were monogenic diabetes with the known β cell regulator3,4 UNC13A, schizophrenia with GPR17, epilepsy with RBFOX3, Charcot–Marie–Tooth disease with ARPC3 and anterior segment ocular abnormalities with POMK. Further confirmation of these and other associations could lead to numerous diagnoses, highlighting the clinical impact of large-scale statistical approaches to rare disease–gene association discovery

Mouse Chromosome 11

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46996/1/335_2004_Article_BF00648429.pd

Supernova neutrino detection in NOvA

The NOvA long-baseline neutrino experiment uses a pair of large, segmented, liquid-scintillator calorimeters to study neutrino oscillations, using GeV-scale neutrinos from the Fermilab NuMI beam. These detectors are also sensitive to the flux of neutrinos which are emitted during a core-collapse supernova through inverse beta decay interactions on carbon at energies of O(10 MeV). This signature provides a means to study the dominant mode of energy release for a core-collapse supernova occurring in our galaxy. We describe the data-driven software trigger system developed and employed by the NOvA experiment to identify and record neutrino data from nearby galactic supernovae. This technique has been used by NOvA to self-trigger on potential core-collapse supernovae in our galaxy, with an estimated sensitivity reaching out to 10 kpc distance while achieving a detection efficiency of 23% to 49% for supernovae from progenitor stars with masses of 9.6 M☉ to 27 M☉, respectively

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for nonmucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.http://www.nature.com/ejhgam2023Genetic

Novel textbook outcomes following emergency laparotomy: Delphi exercise

Background Textbook outcomes are composite outcome measures that reflect the ideal overall experience for patients. There are many of these in the elective surgery literature but no textbook outcomes have been proposed for patients following emergency laparotomy. The aim was to achieve international consensus amongst experts and patients for the best Textbook Outcomes for non-trauma and trauma emergency laparotomy. Methods A modified Delphi exercise was undertaken with three planned rounds to achieve consensus regarding the best Textbook Outcomes based on the category, number and importance (Likert scale of 1–5) of individual outcome measures. There were separate questions for non-trauma and trauma. A patient engagement exercise was undertaken after round 2 to inform the final round. Results A total of 337 participants from 53 countries participated in all three rounds of the exercise. The final Textbook Outcomes were divided into ‘early’ and ‘longer-term’. For non-trauma patients the proposed early Textbook Outcome was ‘Discharged from hospital without serious postoperative complications (Clavien–Dindo ≥ grade III; including intra-abdominal sepsis, organ failure, unplanned re-operation or death). For trauma patients it was ‘Discharged from hospital without unexpected transfusion after haemostasis, and no serious postoperative complications (adapted Clavien–Dindo for trauma ≥ grade III; including intra-abdominal sepsis, organ failure, unplanned re-operation on or death)’. The longer-term Textbook Outcome for both non-trauma and trauma was ‘Achieved the early Textbook Outcome, and restoration of baseline quality of life at 1 year’. Conclusion Early and longer-term Textbook Outcomes have been agreed by an international consensus of experts for non-trauma and trauma emergency laparotomy. These now require clinical validation with patient data

Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes.

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes