Electrophysiological Mechanisms of Gastrointestinal Arrhythmogenesis: Lessons from the Heart.

This is the final published version. It first appeared at http://journal.frontiersin.org/article/10.3389/fphys.2016.00230/full.Disruptions in the orderly activation and recovery of electrical excitation traveling through the heart and the gastrointestinal (GI) tract can lead to arrhythmogenesis. For example, cardiac arrhythmias predispose to thromboembolic events resulting in cerebrovascular accidents and myocardial infarction, and to sudden cardiac death. By contrast, arrhythmias in the GI tract are usually not life-threatening and much less well characterized. However, they have been implicated in the pathogenesis of a number of GI motility disorders, including gastroparesis, dyspepsia, irritable bowel syndrome, mesenteric ischaemia, Hirschsprung disease, slow transit constipation, all of which are associated with significant morbidity. Both cardiac and gastrointestinal arrhythmias can broadly be divided into non-reentrant and reentrant activity. The aim of this paper is to compare and contrast the mechanisms underlying arrhythmogenesis in both systems to provide insight into the pathogenesis of GI motility disorders and potential molecular targets for future therapy

673. Study of Prescribing patterns and Effectiveness of Ceftolozane/Tazobactam Real-world Analysis (SPECTRA): Results from a multi-national, multicenter observational study

Abstract Background Ceftolozane/tazobactam (C/T) has demonstrated efficacy to treat complicated intra-abdominal infections (cIAI), complicated urinary tract infections (cUTI) and hospital acquired bacterial and ventilator-associated bacterial pneumonia. However, physicians, providers, and other stakeholders including payers want broader real-world evidence to inform clinical decisions and optimize healthcare resource use. Methods SPECTRA is a multi-national, multicenter, retrospective, inpatient, observational study of patients treated with C/T in Australia, Austria, Germany, Italy, Mexico, Spain and The United Kingdom. Adult inpatients treated with ≥48 hours of C/T were included. Demographics, clinical characteristics, treatment management patterns, and outcomes were analyzed. Results There were 687 patients from 38 participating hospitals in 7 countries. The average age was 57.6 years (±17.3 [SD]) and most were male 456 (66.4%). The majority had at least one comorbidity 563 (82.0%), with the most common being heart disease 208 (30.3%), immunocompromised state 207 (30.1%) and chronic pulmonary disease 195 (28.4%). The most common indications were pneumonia 204 (29.7%), sepsis 147 (21.4%), and cIAI 106 (15.4%); 162 (23.6%) had multiple sites of infection and 245 (35.7%) were polymicrobial infections. Median C/T treatment was 12.0 days (11.0 [IQR]). Half of the patients were admitted to the ICU 343 (49.9%), 43.4% of which was related to the infection. Clinical success was 66.1%. All-cause in-hospital mortality was 22.0% with 8.7% being infection related. 30-day all-cause readmission was 9.8% and 4.7% were infection related. Conclusion C/T was used to treat infections among critically ill patients and for multi-source, polymicrobial infections. Despite the complexity of the patients in this real-world analysis, most C/T patients had beneficial outcomes that are similar to results of controlled clinical trials. Disclosures Alex Soriano, MD, MSD, Pfizer, Shionogi, Angelini, Menarini, Gilead: Honoraria Laura A. Puzniak, MPH, PhD, Merck & Co., Inc.: former employee and stockholder David Paterson, MBBS, Accelerate: Honoraria|bioMerieux: Honoraria|Entasis: Advisor/Consultant|Janssen-Cilag: Grant/Research Support|MSD: Advisor/Consultant|MSD: Grant/Research Support|MSD: Honoraria|Pfizer: Grant/Research Support|Pfizer: Honoraria|PPD: Grant/Research Support|Shionogi: Grant/Research Support|VenatoRx: Advisor/Consultant Stefan Kluge, MD, Astrazeneca: Lecture fees|Biotest: Lecture fees|Cytosorbents: Grant/Research Support|Cytosorbents: Lecture fees|Daiichi Sankyo: Grant/Research Support|Daiichi Sankyo: Lecture fees|Fresenius Medical Care: Advisor/Consultant|Fresenius Medical Care: Lecture fees|Gilead: Advisor/Consultant|Gilead: Lecture fees|Mitsubishi Tanabe Pharma: Lecture fees|MSD: Advisor/Consultant|MSD: Lecture fees|Pfizer: Advisor/Consultant|Pfizer: Lecture fees|Phillips: Lecture fees|Zoll: Lecture fees Alexandre H. Watanabe, PharmD, Merck & Co., Inc.: Employee Engels N. Obi, PhD, Merck & Co., Inc.: Employee|Merck & Co., Inc.: Stocks/Bonds Sunny Kaul, BSc, MBChB, PHD, FRCP, FFICM, Chiesi: Speaker fees|Gilead: Speaker fees|GlaxoSmithKline: Speaker fees|MSD: Grant/Research Support|MSD: Speaker fees|Shionogi: Speaker fees|Vifor Pharma: Grant/Research Support

Serum neurofilament light chain levels predict long-term disability progression in patients with progressive multiple sclerosis

© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.Objective : There is a lack of sensitive and specific biomarkers for use in progressive multiple sclerosis (MS). The study aimed to assess the potential of serum neurofilament light chain (sNfL) levels as biomarker of disability progression in patients with progressive MS. Methods: We performed a prospective observational cohort study in 51 patients with progressive MS who participated in a 2-year phase II single-centre, randomised, double-blind, placebo-controlled trial of interferon-beta. Mean (SD) follow-up duration was 13.9 (6.2) years. Levels of sNfL were measured using a single molecule array immunoassay at baseline, 1, 2 and 6 years. Univariable and multivariable analyses were carried out to evaluate associations between sNfL levels and disability progression at short term (2 years), medium term (6 years) and long term (at the time of the last follow-up). Results: A sNfL cut-off value of 10.2¿pg/mL at baseline discriminated between long-term progressors and non-progressors with a 75% sensitivity and 67% specificity (adjusted OR 7.8; 95%¿CI 1.8 to 46.4; p=0.01). Similar performance to discriminate between long-term progressors and non-progressors was observed using age/body mass index-adjusted sNfL Z-scores derived from a normative database of healthy controls. A cut-off increase of 5.1¿pg/mL in sNfL levels between baseline and 6 years also discriminated between long-term progressors and non-progressors with a 71% sensitivity and 86% specificity (adjusted OR 49.4; 95%¿CI 4.4 to 2×103; p=0.008). Conclusions: sNfL can be considered a prognostic biomarker of future long-term disability progression in patients with progressive MS. These data expand the little knowledge existing on the role of sNfL as long-term prognostic biomarker in patients with progressive MS.Postprint (author's final draft

Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning

Understanding the spatial organization of tissues is of critical importance for both basic and translational research. While recent advances in tissue imaging are opening an exciting new window into the biology of human tissues, interpreting the data that they create is a significant computational challenge. Cell segmentation, the task of uniquely identifying each cell in an image, remains a substantial barrier for tissue imaging, as existing approaches are inaccurate or require a substantial amount of manual curation to yield useful results. Here, we addressed the problem of cell segmentation in tissue imaging data through large-scale data annotation and deep learning. We constructed TissueNet, an image dataset containing >1 million paired whole-cell and nuclear annotations for tissue images from nine organs and six imaging platforms. We created Mesmer, a deep learning-enabled segmentation algorithm trained on TissueNet that performs nuclear and whole-cell segmentation in tissue imaging data. We demonstrated that Mesmer has better speed and accuracy than previous methods, generalizes to the full diversity of tissue types and imaging platforms in TissueNet, and achieves human-level performance for whole-cell segmentation. Mesmer enabled the automated extraction of key cellular features, such as subcellular localization of protein signal, which was challenging with previous approaches. We further showed that Mesmer could be adapted to harness cell lineage information present in highly multiplexed datasets. We used this enhanced version to quantify cell morphology changes during human gestation. All underlying code and models are released with permissive licenses as a community resource

Energy gain of wetted-foam implosions with auxiliary heating for inertial fusion studies

Low convergence ratio implosions (where wetted-foam layers are used to limit capsule convergence, achieving improved robustness to instability growth) and auxiliary heating (where electron beams are used to provide collisionless heating of a hotspot) are two promising techniques that are being explored for inertial fusion energy applications. In this paper, a new analytic study is presented to understand and predict the performance of these implosions. Firstly, conventional gain models are adapted to produce gain curves for fixed convergence ratios, which are shown to well-describe previously simulated results. Secondly, auxiliary heating is demonstrated to be well understood and interpreted through the burn-up fraction of the deuterium-tritium fuel, with the gradient of burn-up with respect to burn-averaged temperature shown to provide good qualitative predictions of the effectiveness of this technique for a given implosion. Simulations of auxiliary heating for a range of implosions are presented in support of this and demonstrate that this heating can have significant benefit for high gain implosions, being most effective when the burn-averaged temperature is between 5 and 20 keV

LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models

The advent of large language models (LLMs) and their adoption by the legal community has given rise to the question: what types of legal reasoning can LLMs perform? To enable greater study of this question, we present LegalBench: a collaboratively constructed legal reasoning benchmark consisting of 162 tasks covering six different types of legal reasoning. LegalBench was built through an interdisciplinary process, in which we collected tasks designed and hand-crafted by legal professionals. Because these subject matter experts took a leading role in construction, tasks either measure legal reasoning capabilities that are practically useful, or measure reasoning skills that lawyers find interesting. To enable cross-disciplinary conversations about LLMs in the law, we additionally show how popular legal frameworks for describing legal reasoning -- which distinguish between its many forms -- correspond to LegalBench tasks, thus giving lawyers and LLM developers a common vocabulary. This paper describes LegalBench, presents an empirical evaluation of 20 open-source and commercial LLMs, and illustrates the types of research explorations LegalBench enables.Comment: 143 pages, 79 tables, 4 figure

LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models

The advent of large language models (LLMs) and their adoption by the legal community has given rise to the question: what types of legal reasoning can LLMs perform? To enable greater study of this question, we present LegalBench: a collaboratively constructed legal reasoning benchmark consisting of 162 tasks covering six different types of legal reasoning. LegalBench was built through an interdisciplinary process, in which we collected tasks designed and hand-crafted by legal professionals. Because these subject matter experts took a leading role in construction, tasks either measure legal reasoning capabilities that are practically useful, or measure reasoning skills that lawyers find interesting. To enable cross-disciplinary conversations about LLMs in the law, we additionally show how popular legal frameworks for describing legal reasoning—which distinguish between its many forms—correspond to LegalBench tasks, thus giving lawyers and LLM developers a common vocabulary. This paper describes LegalBench, presents an empirical evaluation of 20 open-source and commercial LLMs, and illustrates the types of research explorations LegalBench enables

Citizen science in schools: engaging students in research on urban habitat for pollinators

Citizen science can play an important role in school science education. Citizen science is particularly relevant to addressing current societal environmental sustainability challenges, as it engages the students directly with environmental science and gives students an understanding of the scientific process. In addition, it allows students to observe local representations of global challenges. Here, we report a citizen science programme designed to engage school‐age children in real‐world scientific research. The programme used standardized methods deployed across multiple schools through scientist–school partnerships to engage students with an important conservation problem: habitat for pollinator insects in urban environments. Citizen science programmes such as the programme presented here can be used to enhance scientific literacy and skills. Provided key challenges to maintain data quality are met, this approach is a powerful way to contribute valuable citizen science data for understudied, but ecologically important study systems, particularly in urban environments across broad geographical areas

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely