12,292 results match your criteria query anti-apoptotic

Critical challenges and creative solutions for quantifying nicotine vaping: qualitative reports from young adults.

Nicotine Tob Res 2021 Apr 13. Epub 2021 Apr 13.

Department of Preventive Medicine, University of Southern California, Los Angeles, CA.

Background: Previous studies suggest that young adults who vape nicotine experience difficulty when answering survey items assessing quantity of vaping. The current study asked young adults who vape to provide suggestions for improving the scientific measurement of vaping.

Methods: We conducted semi-structured qualitative interviews with 62 young adults who vape in Los Angeles, California between June 2018 and June 2019. Read More

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Multisystem inflammatory syndrome in children. An emerging clinical challenge for pediatric surgeons in the COVID 19 era.

J Pediatr Surg Case Rep 2021 Apr 8:101838. Epub 2021 Apr 8.

Department of Pediatrics, Santobono Pausilipon Children's Hospital, Naples, Italy.

Background/purpose: Multisystem inflammatory syndrome in children (MIS-C) is a potentially life-threatening condition occurring 2-6 weeks after Coronavirus disease 2019 (COVID-19) in previously healthy children and adolescents, characterized by clinical and laboratory evidence of multiorgan inflammation. We reported the case of a 6-year-old child presented with acute abdomen and then diagnosed with MIS-C. In addition, to better portray this new entity, we performed a systematic review of MIS-C gastrointestinal features and particularly on those mimicking surgical emergencies. Read More

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COVID-19 information retrieval with deep-learning based semantic search, question answering, and abstractive summarization.

NPJ Digit Med 2021 Apr 12;4(1):68. Epub 2021 Apr 12.

Salesforce Research, Palo Alto, CA, USA.

The COVID-19 global pandemic has resulted in international efforts to understand, track, and mitigate the disease, yielding a significant corpus of COVID-19 and SARS-CoV-2-related publications across scientific disciplines. Throughout 2020, over 400,000 coronavirus-related publications have been collected through the COVID-19 Open Research Dataset. Here, we present CO-Search, a semantic, multi-stage, search engine designed to handle complex queries over the COVID-19 literature, potentially aiding overburdened health workers in finding scientific answers and avoiding misinformation during a time of crisis. Read More

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The lipidome in nonalcoholic fatty liver disease: Actionable targets.

J Lipid Res 2021 Apr 9:100073. Epub 2021 Apr 9.

Universidad de Buenos Aires, Facultad de Medicina, Instituto de Investigaciones Médicas A Lanari, Ciudad Autónoma de Buenos Aires, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)-Universidad de Buenos Aires, Instituto of Investigaciones Médicas (IDIM), Departamento de Hepatología Clínica y Molecular, Ciudad Autónoma de Buenos Aires, Argentina. Electronic address:

Nonalcoholic fatty liver disease (NAFLD) has become the most prevalent chronic liver disease. Recent technological advances, combined with OMICs experiments and explorations involving different biological samples, have uncovered vital aspects of NAFLD biology. In this review, we summarize recent work by our group and others that expands what is known about the role of lipidome in NAFLD pathogenesis. Read More

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Centrality Analysis of Protein-Protein Interaction Networks and Molecular Docking Prioritize Potential Drug-Targets in Type 1 Diabetes.

Iran J Pharm Res 2020 ;19(4):121-134

Endocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences, Tehran, Iran.

Type 1 diabetes (T1D) occurs as a consequence of an autoimmune attack against pancreatic β- cells. Due to a lack of a clear understanding of the T1D pathogenesis, the identification of effective therapies for T1D is the active area in the research. The study purpose was to prioritize potential drugs and targets in T1D via systems biology approach. Read More

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January 2020

iQCAR: inter-Query Contention Analyzer for Data Analytics Frameworks.

Proc ACM SIGMOD Int Conf Manag Data 2019 Jun;2019:918-935

Duke University, Durham, North Carolina.

Resource interferences caused by concurrent queries is one of the key reasons for unpredictable performance and missed workload SLAs in cluster computing systems. Analyzing these inter-query resource interactions is critical in order to answer time-sensitive questions like 'who is creating resource conflicts to my query'. More importantly, diagnosing whether the resource blocked times of a 'victim' query are caused by other queries or some other external factor can help the database administrator narrow down the many possibilities of query performance degradation. Read More

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miR-194 ameliorates hepatic ischemia/reperfusion injury via targeting PHLDA1 in a TRAF6-dependent manner.

Int Immunopharmacol 2021 Apr 8;96:107604. Epub 2021 Apr 8.

The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China. Electronic address:

Hepatic ischemia/reperfusion injury (IRI) is an inevitable pathological process in liver resection, shock and transplantation. However, the internal mechanism of hepatic IRI, including inflammatory transduction of multiple signaling pathways, is not fully understood. In the present study, we identified pleckstrin homology-like domain family member 1 (PHLDA1), suppressed by microRNA (miR)-194, as a critical intersection of dual inflammatory signals in hepatic IRI. Read More

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Distinct clinical phenotypes for Crohn's disease derived from patient surveys.

BMC Gastroenterol 2021 Apr 9;21(1):160. Epub 2021 Apr 9.

Department of Bioengineering, Stanford University, Shriram Room 209, MC: 4245, 443 Via Ortega Drive, Stanford, CA, 94305-4145, USA.

Background: Defining clinical phenotypes provides opportunities for new diagnostics and may provide insights into early intervention and disease prevention. There is increasing evidence that patient-derived health data may contain information that complements traditional methods of clinical phenotyping. The utility of these data for defining meaningful phenotypic groups is of great interest because social media and online resources make it possible to query large cohorts of patients with health conditions. Read More

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The Administrative Risk Analysis Index (RAI-A) Does Not Predict Reintervention or Mortality Within 30 Days in Patients Who Undergo Elective Open or Endovascular Abdominal Aortic Aneurysm Repair.

Jeanette Man Jun Xu

J Surg Res 2021 Apr 6;264:179-185. Epub 2021 Apr 6.

Department of Surgery, Division of Vascular Surgery, University of Iowa, Iowa City, Iowa. Electronic address:

Objective: Frailty scores are increasingly utilized to predict postoperative complications. The purpose of this study is to determine whether the administrative risk analysis index (RAI-A) can be used to predict reintervention or mortality within 30 days in patients who undergo elective open or endovascular abdominal aortic aneurysm (AAA) repair.

Methods: The American College of Surgeons National Surgical Quality Improvement Program database was used to query data from elective open or endovascular aortic aneurysm repairs from 2011 to 2018. Read More

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Neuroimaging markers of adolescent depression in the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study.

J Affect Disord 2021 Mar 31;287:380-386. Epub 2021 Mar 31.

University of California, San Diego, United States. Electronic address:

Background: Adolescents are at increased risk of developing major depressive disorder (MDD) than many other age groups. Although the neural correlates of MDD in adults have been studied prospectively, such adolescent depression studies are mainly cross-sectional. We extracted data regarding the relationship between cortical thickness and later development of adolescent MDD from a national community study that uses an accelerated longitudinal design to examine the psychological, environmental, and neural differences related to drinking and brain development. Read More

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REDASA: A Secure Continually Updating Web-Source Processing Pipeline supporting a REaltime DAta Synthesis and Analysis of Scientific Literature.

J Med Internet Res 2021 04 3. Epub 2021 Apr 3.

PanSurg Collaborative, Department of Surgery and Cancer, Imperial College London, London, GB.

Background: The scale and quality of the global scientific response to the COVID-19 pandemic has unquestionably saved lives. However, COVID-19 has also triggered an unprecedented "infodemic"; the velocity and volume of data production has overwhelmed many key stakeholders such as clinicians and policymakers who have been unable to process structured and unstructured data for evidence-based decision making. Current solutions which aim to alleviate this data synthesis challenge are unable to capture heterogeneous web data in "real-time" for the production of concomitant answers and are not based on the high-quality information in response to a free-text query. Read More

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WHISTLE: A Functionally Annotated High-Accuracy Map of Human mA Epitranscriptome.

Methods Mol Biol 2021 ;2284:519-529

Department of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, China.

N-Methyladenosine (mA) is the most prevalent posttranscriptional modification in eukaryotes and plays a pivotal role in various biological processes, such as splicing, RNA degradation, and RNA-protein interaction. Accurately identification of the location of mA is essential for related downstream studies. In this chapter, we introduce a prediction framework WHISTLE, which enables us to acquire so far the most accurate map of the transcriptome-wide human mA RNA-methylation sites (with an average AUC: 0. Read More

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January 2021

MeT-DB V2.0: Elucidating Context-Specific Functions of N6-Methyl-Adenosine Methyltranscriptome.

Methods Mol Biol 2021 ;2284:507-518

School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, Jiangsu, China.

N6-methyladenosine (mA) is the most prevalent posttranscriptional modification in eukaryotes and plays a pivotal role in various biological processes. A knowledge base with the systematic collection and curation of context specific transcriptome-wide methylations is critical for elucidating their biological functions as well as for developing bioinformatics tools. In this chapter, we present a comprehensive platform MeT-DB V2. Read More

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January 2021

An Automatic Ontology-Based Approach to Support Logical Representation of Observable and Measurable Data for Healthy Lifestyle Management: Proof-of-Concept Study.

J Med Internet Res 2021 Apr 9;23(4):e24656. Epub 2021 Apr 9.

Department of Health and Nursing Science, Centre for e-Health, University of Agder, Grimstad, Norway.

Background: Lifestyle diseases, because of adverse health behavior, are the foremost cause of death worldwide. An eCoach system may encourage individuals to lead a healthy lifestyle with early health risk prediction, personalized recommendation generation, and goal evaluation. Such an eCoach system needs to collect and transform distributed heterogenous health and wellness data into meaningful information to train an artificially intelligent health risk prediction model. Read More

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Trends in Peripheral Nerve Epidemiology and Reconstruction: A State Database Study of Direct Repairs, Grafts, and Conduits.

Ann Plast Surg 2021 Mar 24. Epub 2021 Mar 24.

From the Division of Plastic and Reconstructive Surgery, Icahn School of Medicine at Mount Sinai, New York, NY.

Background: Peripheral nerve injuries (PNIs) are most commonly treated with direct nerve repair procedures or nerve autografts. However, recent advancements in synthetic and vein conduits have led to their increased utilization. The present study quantifies the incidence of these procedures over time and geography and identifies differences in complication rates, illustrating the current epidemiologic climate regarding conduit use for PNI repair. Read More

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Machine learning of free energies in chemical compound space using ensemble representations: Reaching experimental uncertainty for solvation.

J Chem Phys 2021 Apr;154(13):134113

University of Vienna, Faculty of Physics, Kolingasse 14-16, AT-1090 Wien, Austria.

Free energies govern the behavior of soft and liquid matter, and improving their predictions could have a large impact on the development of drugs, electrolytes, or homogeneous catalysts. Unfortunately, it is challenging to devise an accurate description of effects governing solvation such as hydrogen-bonding, van der Waals interactions, or conformational sampling. We present a Free energy Machine Learning (FML) model applicable throughout chemical compound space and based on a representation that employs Boltzmann averages to account for an approximated sampling of configurational space. Read More

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Improved Recognition of Maternal Deaths Using Modern Data Analytics.

Obstet Gynecol 2021 Apr 8. Epub 2021 Apr 8.

Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, University of Rochester Medical Center, Rochester, New York.

Objective: To use a data-fusion approach to improve ascertainment of maternal deaths not detected with standard surveillance strategies.

Methods: We conducted a retrospective cohort study from the electronic health records of a tertiary medical center from 2011 to 2018. Cases of maternal death were identified in two ways: 1) using a standard medical informatics service query of hospital data and 2) using the TriNetX discovery tool as patients with a vital status of "deceased" and evidence of antecedent pregnancy exposure based on such factors as obstetric diagnostic codes or obstetric-related procedures. Read More

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Few-Shot Common-Object Reasoning using Common-Centric Localization Network.

IEEE Trans Image Process 2021 Apr 8;PP. Epub 2021 Apr 8.

In the few-shot common-localization task, given few support images without bounding box annotations at each episode, the goal is to localize the common object in the query image of unseen categories. The few-shot common-localization task involves common object reasoning from the given images, predicting the spatial locations of the object with different shapes, sizes, and orientations. In this work, we propose a common-centric localization (CCL) network for few-shot common-localization. Read More

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Active Fine-Tuning from gMAD Examples Improves Blind Image Quality Assessment.

Zhihua Wang Kede Ma

IEEE Trans Pattern Anal Mach Intell 2021 Apr 8;PP. Epub 2021 Apr 8.

The research in image quality assessment (IQA) has a long history, and significant progress has been made by leveraging recent advances in deep neural networks (DNNs). Despite high correlation numbers on existing IQA datasets, DNN-based models may be easily falsified in the group maximum differentiation (gMAD) competition with strong counterexamples being identified. Here we show that gMAD examples can be used to improve blind IQA (BIQA) methods. Read More

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LINflow: a computational pipeline that combines an alignment-free with an alignment-based method to accelerate generation of similarity matrices for prokaryotic genomes.

PeerJ 2021 24;9:e10906. Epub 2021 Mar 24.

School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, VA, USA.

Background: Computing genomic similarity between strains is a prerequisite for genome-based prokaryotic classification and identification. Genomic similarity was first computed as Average Nucleotide Identity (ANI) values based on the alignment of genomic fragments. Since this is computationally expensive, faster and computationally cheaper alignment-free methods have been developed to estimate ANI. Read More

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Whole-Mount RNA In Situ Hybridization and Immunofluorescence of Embryos and Tadpoles.

Cold Spring Harb Protoc 2021 Apr 7. Epub 2021 Apr 7.

Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California 94143, USA

A major advantage of experimentation in is the ability to query the localization of endogenous proteins and RNAs in situ in the entire animal during all of development. Here I describe three variations of staining to visualize mRNAs and proteins in developing embryos and tadpoles. The first section outlines a traditional colorimetric staining for mRNAs that is suitable for all stages of development, and the second extends this protocol for fluorescence-based detection for higher spatial and quantitative resolution. Read More

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Basic of machine learning and deep learning in imaging for medical physicists.

Phys Med 2021 Apr 4;83:194-205. Epub 2021 Apr 4.

IRCCS Azienda Ospedaliera Universitaria di Bologna, Medical Physics Department, Bologna, Italy. Electronic address:

The manuscript aims at providing an overview of the published algorithms/automation tool for artificial intelligence applied to imaging for Healthcare. A PubMed search was performed using the query string to identify the proposed approaches (algorithms/automation tools) for artificial intelligence (machine and deep learning) in a 5-year period. The distribution of manuscript in the various disciplines and the investigated image types according to the AI approaches are presented. Read More

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Variance Reduced Methods for Non-convex Composition Optimization.

IEEE Trans Pattern Anal Mach Intell 2021 Apr 7;PP. Epub 2021 Apr 7.

This paper explores the non-convex composition optimization consisting of inner and outer finite-sum functions with a large number of component functions. This problem arises in important applications such as nonlinear embedding and reinforcement learning. Although existing approaches such as stochastic gradient descent (SGD) and stochastic variance reduced gradient (SVRG) descent can be applied to solve this problem, their query complexities tend to be high, especially when the number of inner component functions is large. Read More

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A systematic review and meta-analysis of Histoscanning™ in prostate cancer diagnostics.

World J Urol 2021 Apr 7. Epub 2021 Apr 7.

Institute for Urology and Reproductive Health, Sechenov University, Bolshaya Pirogovskaya str. 2 bld. 1, Moscow, 119991, Russia.

Context: The value of Histoscanning™ (HS) in prostate cancer (PCa) imaging is much debated, although it has been used in clinical practice for more than 10 years now.

Objective: To summarize the data on HS from various PCa diagnostic perspectives to determine its potential.

Materials And Methods: We performed a systematic search using 2 databases (Medline and Scopus) on the query "Histoscan*". Read More

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Spatially and temporally distributed data foraging decisions in disciplinary field science.

Cogn Res Princ Implic 2021 Apr 7;6(1):29. Epub 2021 Apr 7.

Department of Psychology, Temple University, Philadelphia, PA, USA.

How do scientists generate and weight candidate queries for hypothesis testing, and how does learning from observations or experimental data impact query selection? Field sciences offer a compelling context to ask these questions because query selection and adaptation involves consideration of the spatiotemporal arrangement of data, and therefore closely parallels classic search and foraging behavior. Here we conduct a novel simulated data foraging study-and a complementary real-world case study-to determine how spatiotemporal data collection decisions are made in field sciences, and how search is adapted in response to in-situ data. Expert geoscientists evaluated a hypothesis by collecting environmental data using a mobile robot. Read More

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Simplitigs as an efficient and scalable representation of de Bruijn graphs.

Genome Biol 2021 Apr 6;22(1):96. Epub 2021 Apr 6.

CNRS/LIGM Univ Gustave Eiffel, Marne-la-Vallée, France.

de Bruijn graphs play an essential role in bioinformatics, yet they lack a universal scalable representation. Here, we introduce simplitigs as a compact, efficient, and scalable representation, and ProphAsm, a fast algorithm for their computation. For the example of assemblies of model organisms and two bacterial pan-genomes, we compare simplitigs to unitigs, the best existing representation, and demonstrate that simplitigs provide a substantial improvement in the cumulative sequence length and their number. Read More

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Diagnostic performance of Milan system for reporting salivary gland cytopathology: A prospective study.

Diagn Cytopathol 2021 Apr 6. Epub 2021 Apr 6.

Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Background: Fine-needle aspiration (FNA) is a well-established modality for diagnosing salivary gland pathologies. The Milan System for Reporting Salivary Gland Cytopathology (MSRSGC) provides a standardized uniform framework leading to an evidence-based risk of malignancy (ROM). Based on the current literature, ROM in the 6-tier MSRSGC ranges from <5% for neoplasm-benign to >90% for the malignant category. Read More

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Short-term chemosensory distortions and phantoms in COVID-19.

Laryngoscope Investig Otolaryngol 2021 Feb 1. Epub 2021 Feb 1.

Department of Otolaryngology-Head and Neck Surgery University of California, San Francisco San Francisco California USA.

Objective: To identify differentiation features of chemosensory dysfunction in COVID-19 infection and their primary drivers.

Study Design: Cross-sectional cohort comparison.

Methods: A national anonymous survey was used to query participants regarding nasal symptoms and chemosensory dysfunction including sensitivity levels, and presence or absence of distortions and phantoms within the 6-week time window surrounding their COVID-19 testing and survey completion. Read More

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February 2021

Combatting Anti-Vaccination Misinformation: Improving Immunization Rates of Black/African American Children at UW Health.

WMJ 2021 Mar;120(S1):S31-S38

University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.

Introduction: Vaccine hesitancy is a rising public health threat, thwarting progress to reduce vaccine-preventable diseases. While drivers of racial disparities in childhood immunization rates (CIR) have been described, none have explored these disparities at UW Health, and few have highlighted the role of anti-vaccination (anti-vaxx) campaigns in the Black/African American (BAA) community.

Objectives: This quality improvement study evaluates childhood immunization data for racial and ethnic disparities, identifies possible drivers, and proposes equitable solutions. Read More

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