6,189 results match your criteria Acm Transactions On Database Systems[Journal]


Predicting miRNA-disease associations from miRNA-gene-disease heterogeneous network with multi-relational graph convolutional network model.

IEEE/ACM Trans Comput Biol Bioinform 2022 Jul 1;PP. Epub 2022 Jul 1.

MiRNAs are reported to be linked to the pathogenesis of human complex diseases. Disease-related miRNAs may serve as novel bio-marks and drug targets. This work focuses on designing a multi-relational Graph Convolutional Network model to predict miRNA-disease associations (HGCNMDA) from a Heterogeneous network. Read More

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Melatonin Rhythm and Its Relation to Sleep and Circadian Parameters in Children and Adolescents With Autism Spectrum Disorder.

Front Neurol 2022 14;13:813692. Epub 2022 Jun 14.

Department of Pediatrics, Instituto de Investigaciones Sanitarias- Fundación Jiménez Díaz, Universidad Autónoma de Madrid, Madrid, Spain.

Introduction: Sleep problems are prevalent among individuals with autism spectrum disorder (ASD), and a role has been attributed to melatonin in this multifactorial comorbidity.

Methods: A cross-sectional study was conducted on 41 autistic children and adolescents (9.9 ± 3. Read More

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Seq: A High-Performance Language for Bioinformatics.

Proc ACM Program Lang 2019 Oct 10;3. Epub 2019 Oct 10.

MIT CSAIL, 77 Massachusetts Ave, Cambridge, MA, 02139, USA.

The scope and scale of biological data are increasing at an exponential rate, as technologies like next-generation sequencing are becoming radically cheaper and more prevalent. Over the last two decades, the cost of sequencing a genome has dropped from $100 million to nearly $100-a factor of over 10-and the amount of data to be analyzed has increased proportionally. Yet, as Moore's Law continues to slow, computational biologists can no longer rely on computing hardware to compensate for the ever-increasing size of biological datasets. Read More

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October 2019

RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms.

ACM J Emerg Technol Comput Syst 2022 Apr 16;18(2). Epub 2022 Mar 16.

Rice University, USA.

There exists a gap in terms of the signals provided by pacemakers (i.e., intracardiac electrogram (EGM)) and the signals doctors use (i. Read More

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Literature Review of Automated Grading Systems utilising MRI for Neuroforaminal Stenosis.

Curr Med Imaging 2022 Jun 28. Epub 2022 Jun 28.

Department of Neurosurgery, Leeds General Infirmary, Leeds, UK.

Background Cervical neural foraminal stenosis is a common and debilitating condition affecting people 40-60 years old. Although it is established that MRI is the best method of scanning the neural foramen, the question remains whether there is a role for three-dimensional MRIs and subsequently if it is possible to develop a computer aided automated grading system to establish the degree of clinically relevant cervical foraminal stenosis. Objective The aim of the study is to review the literature for current or emerging automated grading systems of the cervical neural foramen, also including volumetric assessments of the neural foramen using MRI. Read More

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Obesity Prediction with EHR Data: A deep learning approach with interpretable elements.

ACM Trans Comput Healthc 2022 Jul 7;3(3). Epub 2022 Apr 7.

University of Delaware, USA.

Childhood obesity is a major public health challenge. Early prediction and identification of the children at an elevated risk of developing childhood obesity may help in engaging earlier and more effective interventions to prevent and manage obesity. Most existing predictive tools for childhood obesity primarily rely on traditional regression-type methods using only a few hand-picked features and without exploiting longitudinal patterns of children's data. Read More

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Rethinking Model-Based Gaze Estimation.

Proc ACM Comput Graph Interact Tech 2022 May 17;5(2). Epub 2022 May 17.

University of California, Santa Cruz.

Over the past several years, a number of data-driven gaze tracking algorithms have been proposed, which have been shown to outperform classic model-based methods in terms of gaze direction accuracy. These algorithms leverage the recent development of sophisticated CNN architectures, as well as the availability of large gaze datasets captured under various conditions. One shortcoming of black-box, end-to-end methods, though, is that any unexpected behaviors are difficult to explain. Read More

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Neuroimaging for Pediatric Non-First-Time Seizures in the Emergency Department.

Neurol Clin Pract 2022 Jun;12(3):e7-e13

Section of Neurology (EM, SR, ES, JJ, JM, RM, MS), Department of Pediatrics, University of Colorado Anschutz Medical Campus, Children's Hospital Colorado, Aurora; Section of Emergency Medicine Department of Pediatrics (RDM, JL), University of Colorado Anschutz Medical Campus, Children's Hospital Colorado, Aurora; and Division of Neurology (CAP), Department of Pediatrics, Children's Hospital of Philadelphia, PA.

Background And Objectives: Neuroimaging is often part of the workup for a pediatric patient presenting with a seizure to an emergency department (ED). We aim to evaluate when neuroimaging in the ED for children with a non-first-time seizure, or nonindex seizure (NIS), is associated with an acute change in management (ACM).

Methods: This is a retrospective cohort study of all pediatric patients presenting to an ED from 2008 to 2018 with a NIS, excluding repeat febrile seizures, who underwent neuroimaging. Read More

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Planar Rooted Phylogenetic Networks.

IEEE/ACM Trans Comput Biol Bioinform 2022 Jun 23;PP. Epub 2022 Jun 23.

A rooted phylogenetic network is a directed acyclic graph with a single root, whose sinks correspond to a set of species. As such networks are useful for representing the evolution of species that have undergone reticulate evolution, there has been great interest in developing the theory behind and algorithms for constructing them. However, unlike evolutionary trees, these networks can be highly non-planar, which can make them difficult to visualise and interpret. Read More

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Diffusion Alignment Coefficient (DAC): A Novel Similarity Metric for Protein-Protein Interaction Network.

Authors:
Volkan Altuntas

IEEE/ACM Trans Comput Biol Bioinform 2022 Jun 23;PP. Epub 2022 Jun 23.

Interaction networks can be used to predict the functions of unknown proteins using known interactions and proteins with known functions. Many graph theory or diffusion-based methods have been proposed, using the assumption that the topological properties of a protein in a network are related to its biological function. Here we seek to improve function prediction by finding more similar neighbors with a new diffusion-based alignment technique to overcome the topological information loss of the node. Read More

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Federated Learning Empowered Real-Time Medical Data Processing Method for Smart Healthcare.

IEEE/ACM Trans Comput Biol Bioinform 2022 Jun 23;PP. Epub 2022 Jun 23.

Computer-aided diagnosis (CAD) has always been an important research topic for applying artificial intelligence in smart healthcare. Sufficient medical data are one of the most critical factors in CAD research. However, medical data are usually obtained in chronological order and cannot be collected all at once, which poses difficulties for the application of deep learning technology in the medical field. Read More

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Asymmetric pore windows in MOF membranes for natural gas valorization.

Nature 2022 06 22;606(7915):706-712. Epub 2022 Jun 22.

Division of Physical Science and Engineering (PSE), King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia.

To use natural gas as a feedstock alternative to coal and oil, its main constituent, methane, needs to be isolated with high purity. In particular, nitrogen dilutes the heating value of natural gas and is, therefore, of prime importance for removal. However, the inertness of nitrogen and its similarities to methane in terms of kinetic size, polarizability and boiling point pose particular challenges for the development of energy-efficient nitrogen-removing processes. Read More

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The use of social robots with children and young people on the autism spectrum: A systematic review and meta-analysis.

PLoS One 2022 22;17(6):e0269800. Epub 2022 Jun 22.

School of Life and Medical Sciences, University of Hertfordshire, Hatfield, United Kingdom.

Background: Robot-mediated interventions show promise in supporting the development of children on the autism spectrum.

Objectives: In this systematic review and meta-analysis, we summarize key features of available evidence on robot-interventions for children and young people on the autism spectrum aged up to 18 years old, as well as consider their efficacy for specific domains of learning.

Data Sources: PubMed, Scopus, EBSCOhost, Google Scholar, Cochrane Library, ACM Digital Library, and IEEE Xplore. Read More

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Trimming gene deletion strategies for growth-coupled production in constraint-based metabolic networks: TrimGdel.

Authors:
Takeyuki Tamura

IEEE/ACM Trans Comput Biol Bioinform 2022 Jun 22;PP. Epub 2022 Jun 22.

When simulating genome-scale metabolite production using constraint-based metabolic networks, it is often necessary to find gene deletion strategies which lead to growth-coupled production, which means that target metabolites are produced when cell growth is maximized. Existing methods are effective when the number of gene deletions is relatively small, but when the number of required gene deletions exceeds approximately 1% of whole genes, the time required for the calculation is often unfeasible. Therefore, a complementing algorithm that is effective even when the required number of gene deletions is approximately 1% to 5% of whole genes would be helpful because the number of deletable genes in a strain is increasing with advances in genetic engineering technology. Read More

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MV-H-RKM: A Multiple View-based Hypergraph Regularized Restricted Kernel Machine for Predicting DNA-binding Proteins.

IEEE/ACM Trans Comput Biol Bioinform 2022 Jun 22;PP. Epub 2022 Jun 22.

DNA-binding proteins (DBPs) have a significant impact on many life activities, so identification of DBPs is a crucial issue. And it is greatly helpful to understand the mechanism of protein-DNA interactions. In traditional experimental methods, it is significant time-consuming and labor-consuming to identify DBPs. Read More

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Polydatin attenuates chronic alcohol consumption-induced cardiomyopathy through a SIRT6-dependent mechanism.

Food Funct 2022 Jun 21. Epub 2022 Jun 21.

Department of Cardiovascular Surgery, General Hospital of Northern Theater Command, 83 Wenhua Road, Shenyang, Liaoning 110016, P. R. China.

Polydatin has attracted much attention as a potential cardioprotective agent against ischemic heart disease and diabetic cardiomyopathy. However, the effect and mechanism of polydatin supplementation on alcoholic cardiomyopathy (ACM) are still unknown. This study aimed to determine the therapeutic effect of polydatin against ACM and to explore the molecular mechanisms with a focus on SIRT6-AMP-activated protein kinase (AMPK) signaling and mitochondrial function. Read More

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Seizures detection using multimodal signals: a scoping review.

Physiol Meas 2022 Jun 20. Epub 2022 Jun 20.

Duke University, 4223 Interprofessional Education Building 307 Trent Drive, Durham, North Carolina, 27710, UNITED STATES.

Introduction: Epileptic seizures are common neurological disorders in the world, impacting 50 million people globally. Around 30% of patients with seizures suffer from refractory epilepsy, where seizures are not controlled by medications. The unpredictability of seizures makes it essential to have a continuous seizure monitoring system outside clinical settings for the purpose of minimizing patients' injuries and providing additional pathways for evaluation and treatment follow-up. Read More

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Integrated CNN and Federated Learning for COVID-19 Detection on Chest X-Ray Images.

IEEE/ACM Trans Comput Biol Bioinform 2022 Jun 20;PP. Epub 2022 Jun 20.

Currently, Coronavirus Disease 2019 (COVID-19) is still endangering world health and safety and deep learning (DL) is expected to be the most powerful method for efficient detection of COVID-19. However, patients' privacy concerns prohibit data sharing between medical institutions, leading to unexpected performance of deep neural network (DNN) models. Fortunately, federated learning (FL), as a novel paradigm, allows participating clients to collaboratively train models without exposing source data outside original location. Read More

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KGNMDA: a knowledge graph neural network method for predicting microbe-disease associations.

IEEE/ACM Trans Comput Biol Bioinform 2022 Jun 20;PP. Epub 2022 Jun 20.

Accumulated studies discovered that various microbes in human bodies were closely related to complex human diseases and could provide new insight into drug development. Multiple computational methods were constructed to predict microbes that were potentially associated with diseases. However, most previous methods were based on single characteristics of microbes or diseases, that lacked important biological information related to microorganisms or diseases. Read More

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Efficacy and safety of tedizolid for the treatment of ventilated gram-positive hospital-acquired or ventilator-associated bacterial pneumonia in Japanese patients: Results from a subgroup analysis of a phase 3, randomized, double-blind study comparing tedizolid and linezolid.

J Infect Chemother 2022 Jun 16. Epub 2022 Jun 16.

Japan Development, MSD K.K., 1-13-12 Kudan-kita, Chiyoda-ku, Tokyo, 102-8667, Japan. Electronic address:

Introduction: The results from the phase 3 study that evaluated the efficacy and safety of tedizolid phosphate, an oxazolidinone drug, for the treatment of gram-positive ventilated hospital-acquired bacterial pneumonia (vHABP)/ventilator-associated bacterial pneumonia (VABP) compared with linezolid (VITAL study), have been previously reported. We conducted a subgroup analysis to report the data obtained from Japanese patients enrolled in this study.

Methods: Patients aged ≥18 years with vHABP/VABP likely to be caused by gram-positive cocci were randomized 1:1 to tedizolid phosphate 200 mg once daily for 7 days or linezolid 600 mg twice daily for 10 days. Read More

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SGLT2 inhibitor dapagliflozin attenuates cardiac fibrosis and inflammation by reverting the HIF-2α signaling pathway in arrhythmogenic cardiomyopathy.

FASEB J 2022 Jul;36(7):e22410

The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan, China.

Excessive cardiac fibrosis and inflammation aberrantly contribute to the progressive pathogenesis of arrhythmogenic cardiomyopathy (ACM). Whether sodium-glucose cotransporter-2 inhibitor (SGLT2i), as a new hypoglycemic drug, benefits ACM remains unclear. Cardiomyocyte-specific Dsg2 exon-11 knockout and wild-type (WT) littermate mice were used as the animal model of ACM and controls, respectively. Read More

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GCN5 contributes to intracellular lipid accumulation in human primary cardiac stromal cells from patients affected by Arrhythmogenic cardiomyopathy.

J Cell Mol Med 2022 Jun 16. Epub 2022 Jun 16.

Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy.

Arrhythmogenic cardiomyopathy (ACM) is a genetic disease associated with sudden cardiac death and cardiac fibro-fatty replacement. Over the last years, several works have demonstrated that different epigenetic enzymes can affect not only gene expression changes in cardiac diseases but also cellular metabolism. Specifically, the histone acetyltransferase GCN5 is known to facilitate adipogenesis and modulate cardiac metabolism in heart failure. Read More

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Strength-Cognitive Training: A Systemic Review in Adults and Older Adults, and Guidelines to Promote "Strength Exergaming" Innovations.

Front Psychol 2022 27;13:855703. Epub 2022 May 27.

Active Life Lab, South-Eastern Finland University of Applied Sciences, Mikkeli, Finland.

Background: Despite functional and cognitive benefits, few adults and older adults do strength training twice per week with sufficient intensity. Exercise-based active video games (exergaming) may amplify the cognitive benefits of exercise and increase adherence and motivation toward training. However, the benefits of a well-defined and monitored dose of strength training, executed simultaneously or sequentially with a cognitive element, has received little attention. Read More

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Combating COVID-19 Using Generative Adversarial Networks and Artificial Intelligence for Medical Images: Scoping Review.

JMIR Med Inform 2022 Jun 29;10(6):e37365. Epub 2022 Jun 29.

College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.

Background: Research on the diagnosis of COVID-19 using lung images is limited by the scarcity of imaging data. Generative adversarial networks (GANs) are popular for synthesis and data augmentation. GANs have been explored for data augmentation to enhance the performance of artificial intelligence (AI) methods for the diagnosis of COVID-19 within lung computed tomography (CT) and X-ray images. Read More

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PreTP-Stack: prediction of therapeutic peptide based on the stacked ensemble learning.

IEEE/ACM Trans Comput Biol Bioinform 2022 Jun 14;PP. Epub 2022 Jun 14.

Therapeutic peptide prediction is critical for drug development and therapeutic therapy. Researchers have developed several computational methods to identify different therapeutic peptide types. However, most computational methods focus on identifying the specific type of therapeutic peptides and fail to accurately predict all types of therapeutic peptides. Read More

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MASS: Modality-collaborative semi-supervised segmentation by exploiting cross-modal consistency from unpaired CT and MRI images.

Med Image Anal 2022 Jun 5;80:102506. Epub 2022 Jun 5.

Department of Computer Science, The University of Hong Kong, Pokfulam, Hong Kong. Electronic address:

Training deep segmentation models for medical images often requires a large amount of labeled data. To tackle this issue, semi-supervised segmentation has been employed to produce satisfactory delineation results with affordable labeling cost. However, traditional semi-supervised segmentation methods fail to exploit unpaired multi-modal data, which are widely adopted in today's clinical routine. Read More

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Quiescent cancer cells: Therapeutic targets to overcome immunotherapy resistance?

Med (N Y) 2022 06;3(6):358-360

Departments of Pathology and Oncology, The Johns Hopkins University School of Medicine, 401 N Broadway, Weinberg 2242, Baltimore, MD 21287, USA.

Triple-negative breast cancer (TNBC) is a heterogeneous disease with poor clinical outcomes. Chemoimmunotherapy improves outcomes in high-risk, early-stage disease, but not all patients benefit. Baldominos and colleagues drill down into early TNBC sub-microenvironments using single-cell technologies, characterizing quiescent cancer cell niches that may drive immunotherapy resistance and disease relapse. Read More

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Phase I study of alvocidib plus cytarabine/mitoxantrone or cytarabine/daunorubicin for acute myeloid leukemia in Japan.

Cancer Sci 2022 Jun 11. Epub 2022 Jun 11.

Department of Medicine and Biosystemic Science Faculty of Medicine, Kyushu University, Fukuoka, Japan.

Therapeutic improvements are needed for patients with AML, particularly those who have relapsed or who have treatment-refractory (R/R) AML or newly diagnosed patients with poor prognostic factors. Alvocidib (DSP-2033), a potent cyclin-dependent kinase 9 inhibitor, has previously demonstrated promising clinical activity for the treatment of AML. In this multicenter, open-label, uncontrolled, 3+3 phase I study, we investigated the safety and tolerability of alvocidib administered in combination with either cytarabine and mitoxantrone (ACM) for R/R AML, or cytarabine/daunorubicin (A+7+3) for newly diagnosed AML. Read More

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Using TikTok for public and youth mental health - A systematic review and content analysis.

Clin Child Psychol Psychiatry 2022 Jun 10:13591045221106608. Epub 2022 Jun 10.

8818Dublin City University, Dublin, Ireland.

Globally, TikTok is now the fastest growing social media platform among children and young people; but it remains surprisingly under-researched in psychology and psychiatry. This is despite the fact that social media platforms have been subject to intense academic and societal scrutiny regarding their potentially adverse effects on youth mental health and wellbeing, notwithstanding the inconsistent findings across the literature. In this two part study, we conducted a systematic review concerning studies that have examined TikTok for any public health or mental health purpose; and a follow-up content analysis of TikTok within an Irish context. Read More

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