Do Neuro-Muscular Adaptations Occur in Endurance-Trained Boys and Men?

Most research on the effects of endurance training has focused on endurance training's health-related benefits and metabolic effects in both children and adults. The purpose of this study was to examine the neuromuscular effects of endurance training and to investigate whether they differ in children (9.0-12.9 years) and adults (18.4-35.6 years). Maximal isometric torque, rate of torque development (RTD), rate of muscle activation (Q30), electromechanical delay (EMD), and time to peak torque and peak RTD were determined by isokinetic dynamometry and surface electromyography (EMG) in elbow and knee flexion and extension. The subjects were 12 endurance-trained and 16 untrained boys, and 15 endurance-trained and 20 untrained men. The adults displayed consistently higher peak torque, RTD, and Q30, in both absolute and normalized values, whereas the boys had longer EMD (64.7+/-17.1 vs. 56.6+/-15.4 ms) and time to peak RTD (98.5+/-32.1 vs. 80.4+/-15.0 ms for boys and men, respectively). Q30, normalized for peak EMG amplitude, was the only observed training effect (1.95+/-1.16 vs. 1.10+/-0.67 ms for trained and untrained men, respectively). This effect could not be shown in the boys. The findings show normalized muscle strength and rate of activation to be lower in children compared with adults, regardless of training status. Because the observed higher Q30 values were not matched by corresponding higher performance measures in the trained men, the functional and discriminatory significance of Q30 remains unclear. Endurance training does not appear to affect muscle strength or rate of force development in either men or boys

Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis : From the PARADIGM Registry

Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed tomography angiography-determined qualitative and quantitative plaque features within a machine learning (ML) framework to determine its performance for predicting RPP. Methods and Results Qualitative and quantitative coronary computed tomography angiography plaque characterization was performed in 1083 patients who underwent serial coronary computed tomography angiography from the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) registry. RPP was defined as an annual progression of percentage atheroma volume 651.0%. We employed the following ML models: model 1, clinical variables; model 2, model 1 plus qualitative plaque features; model 3, model 2 plus quantitative plaque features. ML models were compared with the atherosclerotic cardiovascular disease risk score, Duke coronary artery disease score, and a logistic regression statistical model. 224 patients (21%) were identified as RPP. Feature selection in ML identifies that quantitative computed tomography variables were higher-ranking features, followed by qualitative computed tomography variables and clinical/laboratory variables. ML model 3 exhibited the highest discriminatory performance to identify individuals who would experience RPP when compared with atherosclerotic cardiovascular disease risk score, the other ML models, and the statistical model (area under the receiver operating characteristic curve in ML model 3, 0.83 [95% CI 0.78-0.89], versus atherosclerotic cardiovascular disease risk score, 0.60 [0.52-0.67]; Duke coronary artery disease score, 0.74 [0.68-0.79]; ML model 1, 0.62 [0.55-0.69]; ML model 2, 0.73 [0.67-0.80]; all P<0.001; statistical model, 0.81 [0.75-0.87], P=0.128). Conclusions Based on a ML framework, quantitative atherosclerosis characterization has been shown to be the most important feature when compared with clinical, laboratory, and qualitative measures in identifying patients at risk of RPP

Topological data analysis of coronary plaques demonstrates the natural history of coronary atherosclerosis

OBJECTIVES This study sought to identify distinct patient groups and their association with outcome based on the patient similarity network using quantitative coronary plaque characteristics from coronary computed tomography angiography (CTA).BACKGROUND Coronary CTA can noninvasively assess coronary plaques quantitatively.METHODS Patients who underwent 2 coronary CTAs at a minimum of 24 months' interval were analyzed (n = 1,264). A similarity Mapper network of patients was built by topological data analysis (TDA) based on the whole-heart quantitative coronary plaque analysis on coronary CTA to identify distinct patient groups and their association with outcome.RESULTS Three distinct patient groups were identified by TDA, and the patient similarity network by TDA showed a dosed loop, demonstrating a continuous trend of coronary plaque progression. Group A had the least coronary plaque amount (median 12.4 mm(3) [interquartile range (IQR): 0.0 to 39.6 mm(3)]) in the entire coronary tree. Group B had a moderate coronary plaque amount (31.7 mm(3) [IQR: 0.0 to 127.4 mm(3)]) with relative enrichment of fibrofatty and necrotic core (32.6% [IQR: 16.7% to 46.2%] and 2.7% [IQR: 0.1% to 6.9%] of the total plaque, respectively) components. Group C had the largest coronary plaque amount (187.0 mm(3) [IQR: 96.7 to 306.4 mm(3)]) and was enriched for dense calcium component (46.8% [IQR: 32.0% to 63.7%] of the total plaque). At follow-up, total plaque volume, fibrous, and dense calcium volumes increased in all groups, but the proportion of fibrofatty component decreased in groups B and C, whereas the necrotic core portion decreased in only group B (all p< 0.05). Group B showed a higher acute coronary syndrome incidence than other groups (0.3% vs. 2.6% vs. 0.6%; p= 0.009) but both group B and C had a higher revascularization incidence than group A (3.1% vs. 15.5% vs. 17.8%; p < 0.001). Incorporating group information from TDA demonstrated increase of model fitness for predicting acute coronary syndrome or revascularization compared with that incorporating clinical risk factors, percentage diameter stenosis, and high-risk plaque features.CONCLUSIONS The TDA of quantitative whole-heart coronary plaque characteristics on coronary CTA identified distinct patient groups with different plaque dynamics and clinical outcomes. (Progression of AtheRosclerotic PlAque Determined by Computed TomoGraphic Angiography Imaging [PARADIGM]; NCT02803411) (C) 2021 by the American College of Cardiology Foundation.Cardiolog

Reassessing the effect of colour on attitude and behavioural intentions in promotional activities: The moderating role of mood and involvement

The present research examines the effect of background colour on attitude and behavioural intentions in various promotional activities taking into consideration the moderating role of mood and involvement. Three experiments reflecting different promotional activities (window display, consumer trade show, guerrilla marketing) were conducted for this purpose. Overall, findings indicate that cool background colours, in contrast to warm colours, induce more positive attitudes and behavioural intentions mainly in positive mood, and low involvement conditions. Implications are also discussed

Evaluation of the Haemophilus influenzae EUCAST and CLSI disc diffusion methods to recognize aminopenicillin and amoxicillin/clavulanate resistance

Objectives Implementation of EUCAST susceptibility testing in an Australian hospital laboratory demonstrated higher rates of aminopenicillin and amoxicillin/clavulanate resistance in Haemophilus influenzae than previously recognized. This study aimed to better define the variability in the detection of β-lactam resistance based on EUCAST and CLSI disc diffusion (DD) methodology, by comparison with the recommended reference method, broth microdilution (BMD), and by concordance with genomic analysis. Methods A total of 100 random H. influenzae isolates were assessed for ampicillin and amoxicillin/clavulanate susceptibility by EUCAST and CLSI DD and BMD. WGS was used to analyse the ftsI gene of a subset of isolates with β-lactam resistance, other than that due to isolated β-lactamase production. Results Of the 100 isolates, 32 were categorized as either β-lactamase negative, ampicillin resistant (BLNAR) (n = 18) or β-lactamase positive, amoxicillin/clavulanate resistant (BLPACR) (n = 14) by EUCAST DD. All 18 EUCAST BLNAR isolates were genotypically confirmed by WGS. Five of 18 BLNAR isolates were concordant by CLSI DD, 12 by EUCAST BMD and 4 by CLSI BMD. Nine of 14 EUCAST BLPACR isolates were confirmed by WGS; the remaining 5 were 1 mm below the EUCAST DD breakpoint. Only one isolate was detected as BLPACR by CLSI DD. Group III mutations associated with high-level ampicillin resistance were identified in 10/32 isolates. Conclusions The EUCAST DD susceptibility method is more reliable than either CLSI or BMD for the detection of genotypically defined BLNAR resistance. However, accurate categorization of amoxicillin/clavulanate resistance remains problematic. Continuous and reproducible surveillance of resistance is needed; for this to be possible, robust susceptibility methods are required