11,270 results match your criteria best performing


Removal and recovery of heavy metals from sewage sludge via three-stage integrated process.

Chemosphere 2021 Apr 27;280:130650. Epub 2021 Apr 27.

Department of Environmental Engineering, Marmara University, 34722, Goztepe, Istanbul, Turkey. Electronic address:

Heavy metal contamination of sewage sludge is one of the concerns preventing its land application. Traditional processes applied for stabilization of sewage sludge are still inadequate to serve sustainable solutions to heavy metal problem. In this study, fermentation and bioleaching potentials of sewage sludge were investigated in anaerobic reactors for either non-pretreated or ultrasonicated sludge at three different pH regimes (free of pH regulation, acidic, and alkaline). Read More

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Dynamic foot morphology explained through 4D scanning and shape modeling.

J Biomech 2021 Apr 25;122:110465. Epub 2021 Apr 25.

Ann and H.J. Smead Department of Aerospace Engineering Sciences, University of Colorado Boulder, USA.

A detailed understanding of foot morphology can enable the design of more comfortable and better fitting footwear. However, foot morphology varies widely within the population, and changes dynamically as the foot is loaded during stance. This study presents a parametric statistical shape model from 4D foot scans to capture both the inter- and intra-individual variability in foot morphology. Read More

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Automated mapping and N-Staging of thoracic lymph nodes in contrast-enhanced CT scans of the chest using a fully convolutional neural network.

Eur J Radiol 2021 Apr 20;139:109718. Epub 2021 Apr 20.

Institute for Diagnostic and Interventional Radiology, University Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Straße 62, 50937, Cologne, Germany.

Purpose: To develop a deep-learning (DL)-based approach for thoracic lymph node (LN) mapping based on their anatomical location.

Method: The training-and validation-dataset included 89 contrast-enhanced computed tomography (CT) scans of the chest. 4201 LNs were semi-automatically segmented and then assigned to LN levels according to their anatomical location. Read More

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Neural network strategies for plasma membrane selection in quantitative fluorescence microscopy images.

Biophys J 2021 May 4. Epub 2021 May 4.

Department of Materials Science and Engineering and Institute for NanoBioTechnology, Johns Hopkins University, Baltimore MD 21218. Electronic address:

In recent years there has been an explosion of fluorescence microscopy studies of live cells in the literature. The analysis of the images obtained in these studies often requires labor-intensive manual annotation to extract meaningful information. In this study, we explore the utility of a neural network approach to recognize, classify, and select plasma membranes in high resolution images, thus greatly speeding up data analysis and reducing the need for personnel training for highly repetitive tasks. Read More

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Improving deep learning-based protein distance prediction in CASP14.

Bioinformatics 2021 May 7. Epub 2021 May 7.

Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA.

Motivation: Accurate prediction of residue-residue distances is important for protein structure prediction. We developed several protein distance predictors based on a deep learning distance prediction method and blindly tested them in the 14th Critical Assessment of Protein Structure Prediction (CASP14). The prediction method uses deep residual neural networks with the channel-wise attention mechanism to classify the distance between every two residues into multiple distance intervals. Read More

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Neural systems underlying the learning of cognitive effort costs.

Cogn Affect Behav Neurosci 2021 May 7. Epub 2021 May 7.

Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI, USA.

People balance the benefits of cognitive work against the costs of cognitive effort. Models that incorporate prospective estimates of the costs of cognitive effort into decision making require a mechanism by which these costs are learned. However, it remains an open question what brain systems are important for this learning, particularly when learning is not tied explicitly to a decision about what task to perform. Read More

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Efficient syncope prediction from resting state clinical data using wavelet bispectrum and multilayer perceptron neural network.

Med Biol Eng Comput 2021 May 6. Epub 2021 May 6.

Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, GR 54645, Thessaloniki, Greece.

Neurally mediated syncope (NMS) is the most common type of syncope, and head up tilt test (HUTT) is, so far, the most appropriate tool to identify NMS. In this work, an effort to predict the NMS before performing the HUTT is attempted. To achieve this, the heart rate variability (HRV) at rest and during the first minutes of tilting position during HUTT was analyzed using both time and frequency domains. Read More

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Radiomics and gene expression profile to characterise the disease and predict outcome in patients with lung cancer.

Eur J Nucl Med Mol Imaging 2021 May 7. Epub 2021 May 7.

Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20090, Pieve Emanuele, Milan, Italy.

Objective: The objectives of our study were to assess the association of radiomic and genomic data with histology and patient outcome in non-small cell lung cancer (NSCLC).

Methods: In this retrospective single-centre observational study, we selected 151 surgically treated patients with adenocarcinoma or squamous cell carcinoma who performed baseline [18F] FDG PET/CT. A subgroup of patients with cancer tissue samples at the Institutional Biobank (n = 74/151) was included in the genomic analysis. Read More

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Exploring effectiveness of ab-initio protein-protein docking methods on a novel antibacterial protein complex dataset.

Brief Bioinform 2021 May 6. Epub 2021 May 6.

School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin, China.

Diseases caused by bacterial infections become a critical problem in public heath. Antibiotic, the traditional treatment, gradually loses their effectiveness due to the resistance. Meanwhile, antibacterial proteins attract more attention because of broad spectrum and little harm to host cells. Read More

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Cell-free DNA as a marker for the outcome of end-stage renal disease patients on haemodialysis.

Clin Kidney J 2021 May 24;14(5):1371-1378. Epub 2020 Aug 24.

UCIBIO/REQUIMTE, Laboratory of Biochemistry, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, Porto, Portugal.

Background: DNA damage and inflammation are common in end-stage renal disease (ESRD). Our aim was to evaluate the levels of circulating cell-free DNA (cfDNA) and the relationship with inflammation, anaemia, oxidative stress and haemostatic disturbances in ESRD patients on dialysis. By performing a 1-year follow-up study, we also aimed to evaluate the predictive value of cfDNA for the outcome of ESRD patients. Read More

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Metagenomic Geolocation Prediction Using an Adaptive Ensemble Classifier.

Front Genet 2021 20;12:642282. Epub 2021 Apr 20.

Department of Biostatistics, University of Florida, Gainesville, FL, United States.

Microbiome samples harvested from urban environments can be informative in predicting the geographic location of unknown samples. The idea that different cities may have geographically disparate microbial signatures can be utilized to predict the geographical location based on city-specific microbiome samples. We implemented this idea first; by utilizing standard bioinformatics procedures to pre-process the raw metagenomics samples provided by the CAMDA organizers. Read More

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Machine learning of EEG spectra classifies unconsciousness during GABAergic anesthesia.

PLoS One 2021 6;16(5):e0246165. Epub 2021 May 6.

Department of Anesthesiology, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, United States of America.

In current anesthesiology practice, anesthesiologists infer the state of unconsciousness without directly monitoring the brain. Drug- and patient-specific electroencephalographic (EEG) signatures of anesthesia-induced unconsciousness have been identified previously. We applied machine learning approaches to construct classification models for real-time tracking of unconscious state during anesthesia-induced unconsciousness. Read More

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Reference Energies for Intramolecular Charge-Transfer Excitations.

J Chem Theory Comput 2021 May 6. Epub 2021 May 6.

Université de Nantes, CNRS, CEISAM UMR 6230, F-44000 Nantes, France.

With the aim of completing our previous efforts devoted to local and Rydberg transitions in organic compounds, we provide a series of highly accurate vertical transition energies for intramolecular charge-transfer transitions occurring in (π-conjugated) molecular compounds. To this end, we apply a composite protocol consisting of linear-response CCSDT excitation energies determined with Dunning's double-ζ basis set corrected by CC3/CCSDT-3 energies obtained with the corresponding triple-ζ basis. Further basis set corrections (up to aug-cc-pVQZ) are obtained at the CCSD and CC2 levels. Read More

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A Novel 5-Cytokine Panel Outperforms Conventional Predictive Markers of Persistent Organ Failure in Acute Pancreatitis.

Clin Transl Gastroenterol 2021 May 6;12(5):e00351. Epub 2021 May 6.

Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.

Introduction: Existing laboratory markers and clinical scoring systems have shown suboptimal accuracies for early prediction of persistent organ failure (POF) in acute pancreatitis (AP). We used information theory and machine learning to select the best-performing panel of circulating cytokines for predicting POF early in the disease course and performed verification of the cytokine panel's prognostic accuracy in an independent AP cohort.

Methods: The derivation cohort included 60 subjects with AP with early serum samples collected between 2007 and 2010. Read More

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Combined Use of Taylor Spatial Frame and Wake-up Test for Acute Correction of Idiopathic External Torsion of the Tibia: A Case Report.

J Orthop Case Rep 2020 May-Jun;10(3):10-14

Department of Orthopedic Surgery, Akita University Graduate School of Medicine.

Introduction: We herein report a case of idiopathic unilateral external torsion of the tibia treated with Taylor spatial frame (TSF) fixation combined with performance of the wake-up test under anesthesia. The wake-up test is performed toward the end of a surgical procedure after all corrections have been made and hardware has been placed. The patient is slowly awakened and asked to move their feet. Read More

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Determining chemical air equivalency using silicone personal monitors.

J Expo Sci Environ Epidemiol 2021 May 5. Epub 2021 May 5.

MyExposome, Inc., Corvallis, OR, USA.

Background: Silicone personal samplers are increasingly being used to measure chemical exposures, but many of these studies do not attempt to calculate environmental concentrations.

Objective: Using measurements of silicone wristband uptake of organic chemicals from atmospheric exposure, create log K and k predictive models based on empirical data to help develop air equivalency calculations for both volatile and semi-volatile organic compounds.

Methods: An atmospheric vapor generator and a custom exposure chamber were used to measure the uptake of organic chemicals into silicone wristbands under simulated indoor conditions. Read More

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Assessment of Performance of Density Functionals for Predicting Potential Energy Curves in Hydrogen Storage Applications.

J Phys Chem A 2021 May 5. Epub 2021 May 5.

Department of Chemistry, University of California, Berkeley, California 94720, United States.

The availability of accurate computational tools for modeling and simulation is vital to accelerate the discovery of materials capable of storing hydrogen (H) under given parameters of pressure swing and temperature. Previously, we compiled the H2Bind275 data set consisting of equilibrium geometries and assessed the performance of 55 density functionals over this data set (Veccham, S. P. Read More

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Is Human Walking a Network Medicine Problem? An Analysis Using Symbolic Regression Models with Genetic Programming.

Comput Methods Programs Biomed 2021 Apr 10;206:106104. Epub 2021 Apr 10.

Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15261, USA; Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15261, USA; Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15261, USA.

Background And Objective: Human walking is typically assessed using a sensor placed on the lower back or the hip. Such analyses often ignore that the arms, legs, and body trunk movements all have significant roles during walking; in other words, these body nodes with accelerometers form a body sensor network (BSN). BSN refers to a network of wearable sensors or devices on the human body that collects physiological signals. Read More

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Nutritional markers of undiagnosed type 2 diabetes in adults: Findings of a machine learning analysis with external validation and benchmarking.

PLoS One 2021 5;16(5):e0250832. Epub 2021 May 5.

Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Clayton, Australia.

Objectives: Using a nationally-representative, cross-sectional cohort, we examined nutritional markers of undiagnosed type 2 diabetes in adults via machine learning.

Methods: A total of 16429 men and non-pregnant women ≥ 20 years of age were analysed from five consecutive cycles of the National Health and Nutrition Examination Survey. Cohorts from years 2013-2016 (n = 6673) was used for external validation. Read More

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Serum markers for predicting advanced fibrosis in patients with chronic hepatitis B and nonalcoholic fatty liver disease.

Medicine (Baltimore) 2021 May;100(18):e25327

Center of Liver Diseases.

Abstract: To compare the diagnostic utility of serum markers in nonalcoholic fatty liver disease (NAFLD) patients with chronic hepatitis B (CHB).This study enrolled 118 consecutive biopsy-proven NAFLD patients with or without CHB. Fibrosis scores of each marker were compared against histological fibrosis staging. Read More

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Pain Assessment Tool With Electrodermal Activity for Postoperative Patients: Method Validation Study.

JMIR Mhealth Uhealth 2021 May 5;9(5):e25258. Epub 2021 May 5.

Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, United States.

Background: Accurate, objective pain assessment is required in the health care domain and clinical settings for appropriate pain management. Automated, objective pain detection from physiological data in patients provides valuable information to hospital staff and caregivers to better manage pain, particularly for patients who are unable to self-report. Galvanic skin response (GSR) is one of the physiologic signals that refers to the changes in sweat gland activity, which can identify features of emotional states and anxiety induced by varying pain levels. Read More

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Aiding clinical assessment of neonatal sepsis using hematological analyzer data with machine learning techniques.

Int J Lab Hematol 2021 May 4. Epub 2021 May 4.

Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA.

Introduction: Early diagnosis and antibiotic administration are essential for reducing sepsis morbidity and mortality; however, diagnosis remains difficult due to complex pathogenesis and presentation. We created a machine learning model for bacterial sepsis identification in the neonatal intensive care unit (NICU) using hematological analyzer data.

Methods: Hematological analyzer data were gathered from NICU patients up to 48 hours prior to clinical evaluation for bacterial sepsis. Read More

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Clinically Applicable Machine Learning Approaches to Identify Attributes of Chronic Kidney Disease (CKD) for Use in Low-Cost Diagnostic Screening.

IEEE J Transl Eng Health Med 2021 15;9:4900511. Epub 2021 Apr 15.

WHO Collaborating Centre of eHealth, School of Public Health and Community MedicineUniversity of New South WalesSydneyNSW2052Australia.

Objective: Chronic kidney disease (CKD) is a major public health concern worldwide. High costs of late-stage diagnosis and insufficient testing facilities can contribute to high morbidity and mortality rates in CKD patients, particularly in less developed countries. Thus, early diagnosis aided by vital parameter analytics using affordable computer-aided diagnosis could not only reduce diagnosis costs but improve patient management and outcomes. Read More

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Constructing Turing complete Euler flows in dimension 3.

Proc Natl Acad Sci U S A 2021 May;118(19)

Instituto de Ciencias Matemáticas (ICMAT)-Consejo Superior de Investigaciones Científicas (CSIC), Campus Cantoblanco Universidad Autónoma de Madrid (UAM), 28049 Madrid,Spain.

Can every physical system simulate any Turing machine? This is a classical problem that is intimately connected with the undecidability of certain physical phenomena. Concerning fluid flows, Moore [C. Moore, 4, 199 (1991)] asked if hydrodynamics is capable of performing computations. Read More

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Crystal Structure of Agmatinase: Catalytic Mechanism and Residues Relevant for Substrate Specificity.

Int J Mol Sci 2021 Apr 30;22(9). Epub 2021 Apr 30.

Departamento de Bioquímica y Biología Molecular, Facultad de Ciencias Biológicas, Universidad de Concepción, Casilla 160-C, Concepción 4070386, Concepción, Chile.

Agmatine is the product of the decarboxylation of L-arginine by the enzyme arginine decarboxylase. This amine has been attributed to neurotransmitter functions, anticonvulsant, anti-neurotoxic, and antidepressant in mammals and is a potential therapeutic agent for diseases such as Alzheimer's, Parkinson's, and cancer. Agmatinase enzyme hydrolyze agmatine into urea and putrescine, which belong to one of the pathways producing polyamines, essential for cell proliferation. Read More

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Validation of Dairy Cow Bodyweight Prediction Using Traits Easily Recorded by Dairy Herd Improvement Organizations and Its Potential Improvement Using Feature Selection Algorithms.

Animals (Basel) 2021 Apr 30;11(5). Epub 2021 Apr 30.

AGROBIOCHEM Department, Research and Teaching Centre (TERRA), Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium.

Knowing the body weight (BW) of a cow at a specific moment or measuring its changes through time is of interest for management purposes. The current work aimed to validate the feasibility of predicting BW using the day in milk, parity, milk yield, and milk mid-infrared (MIR) spectrum from a multiple-country dataset and reduce the number of predictors to limit the risk of over-fitting and potentially improve its accuracy. The BW modeling procedure involved feature selections and herd-independent validation in identifying the most interesting subsets of predictors and then external validation of the models. Read More

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MRI-US fusion guided prostate biopsy: how I do it.

Med Ultrason 2021 Apr 22. Epub 2021 Apr 22.

Department of Urology, Clinical Municipal Hospital and Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.

Multiparametric magnetic resonance imaging (MRI) and MRI-guided prostate biopsy have become the standard for pros-tate cancer diagnosis. As their implementation is relatively recent, experience is still limited in various centres. MRI-guided biopsy requires basic knowledge in prostate MRI and ultrasound (US), but also in the image processing protocol specific for each device. Read More

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Evaluation of polygenic prediction methodology within a reference-standardized framework.

PLoS Genet 2021 May 4;17(5):e1009021. Epub 2021 May 4.

Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.

The predictive utility of polygenic scores is increasing, and many polygenic scoring methods are available, but it is unclear which method performs best. This study evaluates the predictive utility of polygenic scoring methods within a reference-standardized framework, which uses a common set of variants and reference-based estimates of linkage disequilibrium and allele frequencies to construct scores. Eight polygenic score methods were tested: p-value thresholding and clumping (pT+clump), SBLUP, lassosum, LDpred1, LDpred2, PRScs, DBSLMM and SBayesR, evaluating their performance to predict outcomes in UK Biobank and the Twins Early Development Study (TEDS). Read More

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Computational flow cytometry as a diagnostic tool in suspected-myelodysplastic syndromes.

Cytometry A 2021 May 3. Epub 2021 May 3.

Department of Hematology, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, Netherlands.

The diagnostic work-up of patients suspected for myelodysplastic syndromes is challenging and mainly relies on bone marrow morphology and cytogenetics. In this study, we developed and prospectively validated a fully computational tool for flow cytometry diagnostics in suspected-MDS. The computational diagnostic workflow consists of methods for pre-processing flow cytometry data, followed by a cell population detection method (FlowSOM) and a machine learning classifier (Random Forest). Read More

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Benchmarking deep learning splice prediction tools using functional splice assays.

Hum Mutat 2021 May 3. Epub 2021 May 3.

Centre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.

Hereditary disorders are frequently caused by genetic variants that affect pre-mRNA splicing. Whilst genetic variants in the canonical splice motifs are almost always disrupting splicing, the pathogenicity of variants in the non-canonical splice sites (NCSS) and deep intronic (DI) regions are difficult to predict. Multiple splice prediction tools have been developed for this purpose, with the latest tools employing deep learning algorithms. Read More

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