6,131 results match your criteria ACM Transactions on Architecture and Code Optimization[Journal]


Effects of App-Based Mobile Interventions for Dementia Family Caregivers: A Systematic Review and Meta-Analysis.

Dement Geriatr Cogn Disord 2022 May 24:1-11. Epub 2022 May 24.

Department of Nursing, Chung Cheong University, Cheongju-si, Republic of Korea.

Background: Dementia was caregivers experience tremendous difficulties both physically and psychologically, leading to high levels of depression and caregiver burden. The advantage of mobile interventions has been recognized due to its freedom from time and space restrictions.

Objectives: A systematic review and meta-analysis was conducted to evaluate effectiveness of app-based mobile interventions for dementia caregivers. Read More

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Layer-Specific Modules Detection in Cancer Multi-layer Networks.

IEEE/ACM Trans Comput Biol Bioinform 2022 May 24;PP. Epub 2022 May 24.

Multi-layer networks provide an effective and efficient tool to model and characterize the complex systems with multiple types of interactions, which differ greatly from the traditional single-layer networks. Graph clustering in multi-layer networks is highly non-trivial since it is difficult to balance the connectivity of clusters and connection of various layers. The current algorithms for the layer-specific clusters are criticized for the low accuracy and sensitivity to the perturbation of networks. Read More

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Hygeia: A multilabel deep learning-based classification method for imbalanced electrocardiogram data.

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

Electrocardiogram (ECG) is a common diagnostic indicator of heart disease. Because of the low price and noninvasiveness of ECG diagnosis, it is widely used for prescreening and physical examination of heart diseases. In several studies on ECG analysis, only rough diagnoses are made to determine whether ECGs are abnormal or on a few kinds of ECG. Read More

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Real-Time Electrocardiogram Monitoring during Treadmill Training in Mice.

J Vis Exp 2022 May 5(183). Epub 2022 May 5.

Department of Medicine I, University Hospital Munich, Ludwig-Maximilians University Munich (LMU); DZHK (German Centre for Cardiovascular Research), Partner Site Munich, Munich Heart Alliance (MHA); Institute of Surgical Research at the Walter-Brendel-Centre of Experimental Medicine, University Hospital Munich, Ludwig-Maximilians University Munich (LMU);

Regular physical exercise is a major contributor to cardiovascular health, influencing various metabolic as well as electrophysiological processes. However, in certain cardiac diseases such as inherited arrhythmia syndromes, e.g. Read More

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Reactive Astrocytes Derived From Human Induced Pluripotent Stem Cells Suppress Oligodendrocyte Precursor Cell Differentiation.

Front Mol Neurosci 2022 6;15:874299. Epub 2022 May 6.

Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.

Astrocytes are instrumental in maintaining central nervous system (CNS) homeostasis and responding to injury. A major limitation of studying neurodegenerative diseases like multiple sclerosis (MS) is lack of human pathological specimens obtained during the acute stages, thereby relegating research to post-mortem specimens obtained years after the initiation of pathology. Rodent reactive astrocytes have been shown to be cytotoxic to neurons and oligodendrocytes but may differ from human cells, especially in diseases with genetic susceptibility. Read More

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A scoping review of distributed ledger technology in genomics: thematic analysis and directions for future research.

J Am Med Inform Assoc 2022 May 20. Epub 2022 May 20.

Department of Economics and Management, Karlsruhe Institute of Technology, Karlsruhe, Germany.

Objective: Rising interests in distributed ledger technology (DLT) and genomics have sparked various interdisciplinary research streams with a proliferating number of scattered publications investigating the application of DLT in genomics. This review aims to uncover the current state of research on DLT in genomics, in terms of focal research themes and directions for future research.

Materials And Methods: We conducted a scoping review and thematic analysis. Read More

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Complex Disease genes Identification using a heterogeneous network embedding approach.

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

Finding the causal relation between a gene and a disease using experimental approaches is a time-consuming and expensive task. However, computational approaches are cost-efficient methods for identifying candidate genes. This article proposes a new heterogeneous biological network embedding approach, named NetEM, to identify disease-associated genes. Read More

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Dynamic Network Construction for Identifying Early Warning Signals based on a Data-Driven Approach: Early Diagnosis Biomarker Discovery for Gastric Cancer.

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

During the development of complex diseases, there is a critical transition from one status to another at a tipping point, which can be an early indicator of disease deterioration. To effectively enhance the performance of early risk identification, a novel dynamic network construction algorithm for identifying early warning signals based on a data-driven approach (EWS-DDA) was proposed. In EWS-DDA, the shrunken centroid was introduced to measure dynamic expression changes in assumed pathway reactions during the progression of complex disease for network construction and to define early warning signals by means of a data-driven approach. Read More

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Problem of Domain/Building Block Preservation in the Evolution of Biological Macromolecules and Evolutionary Computation.

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

Structurally and functionally isolated domains in biological macromolecular evolution, both natural and artificial, are largely similar to "schemata", building blocks (BBs), in evolutionary computation (EC). The problem of preserving in subsequent evolutionary searches the already found domains / BBs is well known and quite relevant in biology as well as in EC. Both biology and EC are seeing parallel and independent development of several approaches to identifying and preserving previously identified domains / BBs. Read More

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DomBpred: protein domain boundary prediction based on domain-residue clustering using inter-residue distance.

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

Domain boundary prediction is one of the most important problems in the study of protein structure and function, especially for large proteins. At present, most domain boundary prediction methods have low accuracy and limitations in dealing with multi-domain proteins. In this study, we develop a sequence-based protein domain boundary prediction, named DomBpred. Read More

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MuCoMiD: A Multitask graph Convolutional Learning Framework for miRNA-Disease Association Prediction.

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

Recent studies suggest that miRNA could serve as biomarkers in various human diseases. Since wet-lab experiments are expensive and time-consuming, computational techniques for miRNA-disease association prediction have attracted much attention in recent years. Data scarcity is one of the major challenges in building reliable machine learning models. Read More

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Factors Influencing the Adoption of Contact Tracing Applications: Systematic Review and Recommendations.

Front Digit Health 2022 3;4:862466. Epub 2022 May 3.

School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada.

Background: The emergence of new variants of COVID-19 causing breakthrough infections and the endemic potential of the coronavirus are an indication that digital contact tracing apps (CTAs) may continue to be useful for the long haul. However, the uptake of these apps in many countries around the world has been low due to several factors militating against their adoption and usage.

Objective: In this systematic review, we set out to uncover the key factors that facilitate or militate against the adoption of CTAs, which researchers, designers and other stakeholders should focus on in future iterations to increase their adoption and effectiveness in curbing the spread of COVID-19. Read More

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Can the Eight Hop Test Be Measured with Sensors? A Systematic Review.

Sensors (Basel) 2022 May 8;22(9). Epub 2022 May 8.

Escola de Ciências e Tecnologia, University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal.

Rehabilitation aims to increase the independence and physical function after injury, surgery, or other trauma, so that patients can recover to their previous ability as much as possible. To be able to measure the degree of recovery and impact of the treatment, various functional performance tests are used. The Eight Hop Test is a hop exercise that is directly linked to the rehabilitation of people suffering from tendon and ligament injuries on the lower limb. Read More

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Impact of Metastasectomy on Cancer Specific and Overall Survival in Metastatic Renal Cell Carcinoma: Analysis of the REMARCC Registry.

Clin Genitourin Cancer 2022 Apr 9. Epub 2022 Apr 9.

Department of Urology, UC San Diego School of Medicine, La Jolla, CA. Electronic address:

Background: Treatment paradigms for management of metastatic renal cell carcinoma (mRCC) are evolving. We examined impact of surgical metastasectomy on survival across in mRCC stratified by risk-group.

Methods: Multicenter retrospective analysis from the Registry of Metastatic RCC database. Read More

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Exploring the Equity Impact of Current Digital Health Design Practices: Protocol for a Scoping Review.

JMIR Res Protoc 2022 May 17;11(5):e34013. Epub 2022 May 17.

UNICEF, New York, NY, United States.

Background: The field of digital health has grown rapidly in part due to digital health tools' potential to reduce health inequities. However, such potential has not always been realized. The design approaches used in digital health are one of the known aspects that have an impact on health equity. Read More

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Use of Robots in Critical Care: Systematic Review.

J Med Internet Res 2022 05 16;24(5):e33380. Epub 2022 May 16.

Division of Respiratory & Critical Care Medicine, Department of Medicine, National University Hospital, Singapore, Singapore.

Background: The recent focus on the critical setting, especially with the COVID-19 pandemic, has highlighted the need for minimizing contact-based care and increasing robotic use. Robotics is a rising field in the context of health care, and we sought to evaluate the use of robots in critical care settings.

Objective: Although robotic presence is prevalent in the surgical setting, its role in critical care has not been well established. Read More

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Spatial transcriptomics unveils ZBTB11 as a regulator of cardiomyocyte degeneration in arrhythmogenic cardiomyopathy.

Cardiovasc Res 2022 May 16. Epub 2022 May 16.

Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences (KNAW) and University Medical Center Utrecht, Utrecht, Netherlands.

Aims: Arrhythmogenic cardiomyopathy (ACM) is an inherited cardiac disorder that is characterized by progressive loss of myocardium that is replaced by fibro-fatty cells, arrhythmias, and sudden cardiac death. While myocardial degeneration and fibro-fatty replacement occur in specific locations, the underlying molecular changes remain poorly characterized. Here we aim to delineate local changes in gene expression to identify new genes and pathways that are relevant for specific remodelling processes occurring during ACM. Read More

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Biomedical Argument Mining Based on Sequential Multi-Task Learning.

IEEE/ACM Trans Comput Biol Bioinform 2022 May 16;PP. Epub 2022 May 16.

Biomedical argument mining aims to automatically identify and extract the argumentative structure in biomedical text. It helps to determine not only what positions people adopt, but also why they hold such opinions, which provides valuable insights into medical decision making. Generally, biomedical argument mining consists of three subtasks: argument component identification, argument component classification and relation identification. Read More

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Modular multi--source prediction of drug side--effects with DruGNN.

IEEE/ACM Trans Comput Biol Bioinform 2022 May 16;PP. Epub 2022 May 16.

Drug Side--Effects (DSEs) have a high impact on public health, care system costs, and drug discovery processes. Predicting the probability of side--effects, before their occurrence, is fundamental to reduce this impact, in particular on drug discovery. Candidate molecules could be screened before undergoing clinical trials, reducing the costs in time, money, and health of the participants. Read More

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Heterogeneous Multi-task Learning with Expert Diversity.

IEEE/ACM Trans Comput Biol Bioinform 2022 May 16;PP. Epub 2022 May 16.

Predicting multiple heterogeneous biological and medical targets is a challenge for traditional deep learning models. In contrast to single-task learning, in which a separate model is trained for each target, multi-task learning (MTL) optimizes a single model to predict multiple related targets simultaneously. To address this challenge, we propose the Multi-gate Mixture-of-Experts with Exclusivity (MMoEEx). Read More

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Virtual Reality (VR) Technology for Treatment of Mental Health Problems during COVID-19: A Systematic Review.

Int J Environ Res Public Health 2022 Apr 28;19(9). Epub 2022 Apr 28.

Department of Psychiatry, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur 56000, Malaysia.

There was a surge in psychological distress and emotional burnout during the COVID-19 pandemic. Virtual reality (VR) is helpful as a psychological intervention whilst maintaining physical or social distancing. The present systematic review assessed the role of VR as a psychological intervention tool for mental health problems during the COVID-19 pandemic. Read More

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Prenatal glucocorticoid exposure selectively impairs neuroligin 1-dependent neurogenesis by suppressing astrocytic FGF2-neuronal FGFR1 axis.

Cell Mol Life Sci 2022 May 13;79(6):294. Epub 2022 May 13.

Department of Veterinary Physiology, College of Veterinary Medicine, Research Institute for Veterinary Science, and BK21 Four Future Veterinary Medicine Leading Education and Research Center, Seoul National University, Seoul, 08826, Korea.

Exposure to maternal stress irreversibly impairs neurogenesis of offspring by inducing life-long effects on interaction between neurons and glia under raging differentiation process, culminating in cognitive and neuropsychiatric abnormalities in adulthood. We identified that prenatal exposure to stress-responsive hormone glucocorticoid impaired neurogenesis and induced abnormal behaviors in ICR mice. Then, we used human induced pluripotent stem cell (iPSC)-derived neural stem cell (NSC) to investigate how neurogenesis deficits occur. Read More

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A Biomathematical Model of Tumor Response to Radioimmunotherapy with PDL1 and CTLA4.

IEEE/ACM Trans Comput Biol Bioinform 2022 May 11;PP. Epub 2022 May 11.

There is evidence of synergy between radiotherapy and immunotherapy. Radiotherapy can increase liberation of tumor antigens, causing activation of antitumor T-cells. This effect can be boosted with immunotherapy. Read More

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MCWS-Transformers: Towards an Efficient Modeling of Protein Sequences via Multi Context-Window Based Scaled Self-Attention.

IEEE/ACM Trans Comput Biol Bioinform 2022 May 10;PP. Epub 2022 May 10.

This paper advances the self-attention mechanism in the standard transformer network specific to the modeling of the protein sequences. We introduce a novel context-window based scaled self-attention mechanism for processing protein sequences that is based on the notion of (i) local context and (ii) large contextual pattern. Both notions are essential to building a good representation for protein sequences. Read More

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ELMo4m6A: a contextual language embedding-based predictor for detecting RNA N6-methyladenosine sites.

IEEE/ACM Trans Comput Biol Bioinform 2022 May 10;PP. Epub 2022 May 10.

N6-methyladenosine (m6A) is a universal post-transcriptional modification of RNAs, and it is widely involved in various biological processes. Identifying m6A modification sites accurately is indispensable to further investigate m6A-mediated biological functions. How to better represent RNA sequences is crucial for building effective computational methods for detecting m6A modification sites. Read More

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Robust Kalman Filter State Estimation for Gene Regulatory Networks.

IEEE/ACM Trans Comput Biol Bioinform 2022 May 10;PP. Epub 2022 May 10.

This paper proposes a revised version of the robust generalized maximum likelihood (GM)-type unscented Kalman filter (GM-UKF) for the state estimation of gene regulatory networks (GRNs) in the presence of different types of deviations from assumptions. As known, the parameters and the power of the assumed noises within the GRN model may change abruptly as a result of jump behavior and bursting process in transcription and translation phases. Moreover, there may be outlying samples among genomic measurement data. Read More

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SCAMPER: accurate type-specific prediction of calcium-binding residues using sequence-derived features.

IEEE/ACM Trans Comput Biol Bioinform 2022 May 10;PP. Epub 2022 May 10.

Understanding molecular mechanisms involved in calcium-protein interactions and modeling corresponding docking rely on the accurate identification of calcium-binding residues (CaBRs). The defects of experimentally annotating protein functions enhances the development of computational approaches that correctly identify calcium-binding interactions. Studies have reported that current methods severely cross-predict residues that interact with other types of molecules (e. Read More

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Semi-supervised Deep Learning for Cell Type Identification from Single-Cell Transcriptomic Data.

IEEE/ACM Trans Comput Biol Bioinform 2022 May 10;PP. Epub 2022 May 10.

Cell type identification from single-cell transcriptomic data is a common goal of single-cell RNA sequencing (scRNAseq) data analysis. Deep neural networks have been employed to identify cell types from scRNAseq data with high performance. However, it requires a large mount of individual cells with accurate and unbiased annotated types to train the identification models. Read More

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Transfer Learning Based Lightweight Ensemble Model for Imbalanced Breast Cancer Classification.

IEEE/ACM Trans Comput Biol Bioinform 2022 May 10;PP. Epub 2022 May 10.

Automated classification of breast cancer can often save lives, as manual detection is usually time-consuming & expensive. Since the last decade, deep learning techniques have been most widely used for the automatic classification of breast cancer using histopathology images. This paper has performed the binary and multi-class classification of breast cancer using a transfer learning-based ensemble model. Read More

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LitMC-BERT: transformer-based multi-label classification of biomedical literature with an application on COVID-19 literature curation.

IEEE/ACM Trans Comput Biol Bioinform 2022 May 10;PP. Epub 2022 May 10.

The rapid growth of biomedical literature poses a significant challenge for curation and interpretation. This has become more evident during the COVID-19 pandemic. LitCovid, a literature database of COVID-19 related papers in PubMed, has accumulated over 180,000 articles with millions of accesses. Read More

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