Altered organization of the intermediate filament cytoskeleton and relocalization of proteostasis modulators in cells lacking the ataxia protein sacsin

This work was supported by BBSRC [BB/L02294X/1]; the CIHR Rare Disease Emerging Team grant, the Ataxia of Charlevoix-Saguenay Foundation; Muscular Dystrophy Canada and Barts and the London Charity [417/1699]. The LSM880 confocal used in these studies was purchased through a Barts and the London Charity grant MGU0293

Identification of Critical Amino Acids in an Immunodominant IgE Epitope of Pen c 13, a Major Allergen from Penicillium citrinum

Background: Pen c 13, identified as a 33-kDa alkaline serine protease, is a major allergen secreted by Penicillium citrinum. Detailed knowledge about the epitopes responsible for IgE binding would help inform the diagnosis/prognosis of fungal allergy and facilitate the rational design of hypoallergenic candidate vaccines. The goal of the present study was to characterize the IgE epitopes of Pen c 13. Methodology/Principal Findings: Serum samples were collected from 10 patients with mold allergy and positive Pen c 13 skin test results. IgE-binding epitopes on rPen c 13 were mapped using an enzymatic digestion and chemical cleavage method, followed by dot-blotting and mass spectrometry. A B-cell epitope-predicting server and molecular modeling were used to predict the residues most likely involved in IgE binding. Theoretically predicted IgE-binding regions were further confirmed by site-directed mutagenesis assays. At least twelve different IgE-binding epitopes located throughout Pen c 13 were identified. Of these, peptides S16 (A 148 –E 166) and S22 (A 243 –K 274) were recognized by sera from 90 % and 100 % of the patients tested, and were further confirmed by inhibition assays. Peptide S22 was selected for further analysis of IgE-binding ability. The results of serum screening showed that the majority of IgE-binding ability resided in the C-terminus. One Pen c 13 mutant, G270A (T 261 –K 274), exhibited clearly enhanced IgE reactivity, whereas another, K274A, exhibited dramatically reduced IgE reactivity

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

Design of the ECCE Detector for the Electron Ion Collider

Preprint submitted to Nuclear Instruments and Methods A. The file archived on this institutional repository has not been certified by peer review.32 pages, 29 figures, 9 tablesThe EIC Comprehensive Chromodynamics Experiment (ECCE) detector has been designed to address the full scope of the proposed Electron Ion Collider (EIC) physics program as presented by the National Academy of Science and provide a deeper understanding of the quark-gluon structure of matter. To accomplish this, the ECCE detector offers nearly acceptance and energy coverage along with excellent tracking and particle identification. The ECCE detector was designed to be built within the budget envelope set out by the EIC project while simultaneously managing cost and schedule risks. This detector concept has been selected to be the basis for the EIC project detector.Office of Science in the Department of Energy, the National Science Foundation, and the Los Alamos National Laboratory Laboratory Directed Research and Development (LDRD) 20200022DR; This research used resources of the Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05- 00OR22725. The work of AANL group are supported by the Science Committee of RA, in the frames of the research project # 21AG-1C028. And we gratefully acknowledge that support of Brookhaven National Lab and the Thomas Jefferson National Accelerator Facility which are operated under contracts DESC0012704 and DE-AC05-06OR23177 respectivel

Degradation of haloaromatic compounds

An ever increasing number of halogenated organic compounds has been produced by industry in the last few decades. These compounds are employed as biocides, for synthetic polymers, as solvents, and as synthetic intermediates. Production figures are often incomplete, and total production has frequently to be extrapolated from estimates for individual countries. Compounds of this type as a rule are highly persistent against biodegradation and belong, as "recalcitrant" chemicals, to the class of so-called xenobiotics. This term is used to characterise chemical substances which have no or limited structural analogy to natural compounds for which degradation pathways have evolved over billions of years. Xenobiotics frequently have some common features. e.g. high octanol/water partitioning coefficients and low water solubility which makes for a high accumulation ratio in the biosphere (bioaccumulation potential). Recalcitrant compounds therefore are found accumulated in mammals, especially in fat tissue, animal milk supplies and also in human milk. Highly sophisticated analytical techniques have been developed for the detection of organochlorines at the trace and ultratrace level

AI-assisted optimization of the ECCE tracking system at the Electron Ion Collider

arXiv preprint [v2] Fri, 20 May 2022 03:23:44 UTC (2,296 KB) made available under a Creative Commons (CC BY) Attribution Licence, now in press, published by Elsevier: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, available online 17 November 2022 at: https://doi.org/10.1016/j.nima.2022.167748The Electron-Ion Collider (EIC) is a cutting-edge accelerator facility that will study the nature of the "glue" that binds the building blocks of the visible matter in the universe. The proposed experiment will be realized at Brookhaven National Laboratory in approximately 10 years from now, with detector design and R&D currently ongoing. Notably, EIC is one of the first large-scale facilities to leverage Artificial Intelligence (AI) already starting from the design and R&D phases. The EIC Comprehensive Chromodynamics Experiment (ECCE) is a consortium that proposed a detector design based on a 1.5T solenoid. The EIC detector proposal review concluded that the ECCE design will serve as the reference design for an EIC detector. Herein we describe a comprehensive optimization of the ECCE tracker using AI. The work required a complex parametrization of the simulated detector system. Our approach dealt with an optimization problem in a multidimensional design space driven by multiple objectives that encode the detector performance, while satisfying several mechanical constraints. We describe our strategy and show results obtained for the ECCE tracking system. The AI-assisted design is agnostic to the simulation framework and can be extended to other sub-detectors or to a system of sub-detectors to further optimize the performance of the EIC detector.Office of Nuclear Physics in the Office of Science in the Department of Energy; National Science Foundation, and the Los Alamos National Laboratory Laboratory Directed Research and Development (LDRD) 20200022DR