72 research outputs found

    Identifying the Opportunities for the Design of Digital Platforms: A Topic Modelling Approach

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    Aquaculture is one of the fast-growing food-producing agriculture subsectors. However, the digital infrastructures developed in aquaculture are self-organising platforms i.e. they do not rely on a centralized intermediary for monitoring, coordinating activities or for overseeing transactions. Hence, the main objective of this research paper is to identify the challenges farmers face in an entire supply chain for designing a digital platform for the aquaculture domain. The main problems faced by the farmers include water quality issues, disease outbreak, lack of proper information regarding suitable insurance policies etc. We have identified eight such issues that the farmers face in an entire harvest period and also prioritized them. The results from our study could be used for the further advancement of an integrative perspective in the design and implementation of the digital platform for aquaculture

    Protein quality control meets transcriptome remodeling under stress

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    To tolerate and recover from genotoxic stress cells must coordinate a range of stress response activities including cell cycle arrest, DNA repair, and remodeling of the transcriptome and proteome. The suppression of ribosome production is a key feature of many stress responses in yeast, and much is known about the dynamics of this process at the transcriptional level. In our recent study, (J Cell Biol doi: 10.1083/ jcb.201612018) we focus on the stress related dynamic behaviour of a splicing factor called Hsh155, which is a core component of the SF3B subcomplex of the U2 small nuclear ribonucleoprotein complex, homologous to human SF3B1. The disassembly from its complex and sequestration of Hsh155 into nuclear protein aggregates contributes to suppressing ribosome production post-transcriptionally by promoting intron retention in ribosomal protein gene transcripts. The relocalization of Hsh155 is facilitated by TORC1-driven transcriptional changes and molecular chaperones that recognize disassembled Hsh155, eventually aiding in efficient recovery from stress

    The Histone-Fold Protein CHRAC14 Influences Chromatin Composition in Response to DNA Damage

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    Chromatin reorganization and the incorporation of specific histone modifications during DNA damage response are essential steps for the successful repair of any DNA lesion. Here, we show that the histone-fold protein CHRAC14 plays an essential role in response to DNA damage in Drosophila. Chrac14 mutants are hypersensitive to genotoxic stress and do not activate the G2/M cell-cycle checkpoint after damage induction. Even though the DNA damage repair process is activated in the absence of CHRAC14, lesions are not repaired efficiently. In the absence of CHRAC14, the centromere-specific histone H3 variant CENP-A localizes to sites of DNA damage, causing ectopic kinetochore formation and genome instability. CENP-A and CHRAC14 are able to interact upon damage. Our data suggest that CHRAC14 modulates chromatin composition in response to DNA damage, which is required for efficient DNA damage repair in Drosophila

    Disease phenotyping using deep learning: A diabetes case study

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    Characterization of a patient clinical phenotype is central to biomedical informatics. ICD codes, assigned to inpatient encounters by coders, is important for population health and cohort discovery when clinical information is limited. While ICD codes are assigned to patients by professionals trained and certified in coding there is substantial variability in coding. We present a methodology that uses deep learning methods to model coder decision making and that predicts ICD codes. Our approach predicts codes based on demographics, lab results, and medications, as well as codes from previous encounters. We are able to predict existing codes with high accuracy for all three of the test cases we investigated: diabetes, acute renal failure, and chronic kidney disease. We employed a panel of clinicians, in a blinded manner, to assess ground truth and compared the predictions of coders, model and clinicians. When disparities between the model prediction and coder assigned codes were reviewed, our model outperformed coder assigned ICD codes.Comment: Machine Learning for Health (ML4H) Workshop at NeurIPS 2018 arXiv:cs/010120

    Real-world, Multicenter Experience With Meropenem-Vaborbactam for Gram-Negative Bacterial Infections Including Carbapenem-Resistant Enterobacterales and Pseudomonas Aeruginosa

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    Background: We aimed to describe the clinical characteristics and outcomes of patients treated with meropenem-vaborbactam (MEV) for a variety of gram-negative infections (GNIs), primarily including carbapenem-resistant Enterobacterales (CRE). Methods: This is a real-world, multicenter, retrospective cohort within the United States between 2017 and 2020. Adult patients who received MEV for ≥72 hours were eligible for inclusion. The primary outcome was 30-day mortality. Classification and regression tree analysis (CART) was used to identify the time breakpoint (BP) that delineated the risk of negative clinical outcomes (NCOs) and was examined by multivariable logistic regression analysis (MLR). Results: Overall, 126 patients were evaluated from 13 medical centers in 10 states. The most common infection sources were respiratory tract (38.1%) and intra-abdominal (19.0%) origin, while the most common isolated pathogens were CRE (78.6%). Thirty-day mortality and recurrence occurred in 18.3% and 11.9%, respectively. Adverse events occurred in 4 patients: nephrotoxicity (n = 2), hepatoxicity (n = 1), and rash (n = 1). CART-BP between early and delayed treatment was 48 hours (P = .04). MEV initiation within 48 hours was independently associated with reduced NCO following analysis by MLR (adusted odds ratio, 0.277; 95% CI, 0.081-0.941). Conclusions: Our results support current evidence establishing positive clinical and safety outcomes of MEV in GNIs, including CRE. We suggest that delaying appropriate therapy for CRE significantly increases the risk of NCOs

    Post-intervention Status in Patients With Refractory Myasthenia Gravis Treated With Eculizumab During REGAIN and Its Open-Label Extension

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    OBJECTIVE: To evaluate whether eculizumab helps patients with anti-acetylcholine receptor-positive (AChR+) refractory generalized myasthenia gravis (gMG) achieve the Myasthenia Gravis Foundation of America (MGFA) post-intervention status of minimal manifestations (MM), we assessed patients' status throughout REGAIN (Safety and Efficacy of Eculizumab in AChR+ Refractory Generalized Myasthenia Gravis) and its open-label extension. METHODS: Patients who completed the REGAIN randomized controlled trial and continued into the open-label extension were included in this tertiary endpoint analysis. Patients were assessed for the MGFA post-intervention status of improved, unchanged, worse, MM, and pharmacologic remission at defined time points during REGAIN and through week 130 of the open-label study. RESULTS: A total of 117 patients completed REGAIN and continued into the open-label study (eculizumab/eculizumab: 56; placebo/eculizumab: 61). At week 26 of REGAIN, more eculizumab-treated patients than placebo-treated patients achieved a status of improved (60.7% vs 41.7%) or MM (25.0% vs 13.3%; common OR: 2.3; 95% CI: 1.1-4.5). After 130 weeks of eculizumab treatment, 88.0% of patients achieved improved status and 57.3% of patients achieved MM status. The safety profile of eculizumab was consistent with its known profile and no new safety signals were detected. CONCLUSION: Eculizumab led to rapid and sustained achievement of MM in patients with AChR+ refractory gMG. These findings support the use of eculizumab in this previously difficult-to-treat patient population. CLINICALTRIALSGOV IDENTIFIER: REGAIN, NCT01997229; REGAIN open-label extension, NCT02301624. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that, after 26 weeks of eculizumab treatment, 25.0% of adults with AChR+ refractory gMG achieved MM, compared with 13.3% who received placebo
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