RESUMO
The growth of sport science technology is enabling more sporting teams to implement athlete monitoring practices related to performance testing and load monitoring. Despite the increased emphasis on youth athlete development, the lack of longitudinal athlete monitoring literature in youth athletes is concerning, especially for indoor sports such as basketball. The aim of this study was to evaluate the effectiveness of six different athlete monitoring methods over 10 weeks of youth basketball training. Fourteen state-level youth basketball players (5 males and 9 females; 15.1 ± 1.0 years) completed this study during their pre-competition phase prior to their national basketball tournament. Daily wellness and activity surveys were completed using the OwnUrGoal mobile application, along with heart rate (HR) and inertial measurement unit (IMU) recordings at each state training session, and weekly performance testing (3x countermovement jumps [CMJs], and 3x isometric mid-thigh pulls [IMTPs]). All of the athlete monitoring methods demonstrated the coaching staff's training intent to maintain performance and avoid spikes in workload. Monitoring IMU data combined with PlayerLoad™ data analysis demonstrated more effectiveness for monitoring accumulated load (AL) compared to HR analysis. All six methods of athlete monitoring detected similar trends for all sessions despite small-trivial correlations between each method (Pearson's correlation: -0.24 < r < 0.28). The use of subjective monitoring questionnaire applications, such as OwnUrGoal, is recommended for youth sporting clubs, given its practicability and low-cost. Regular athlete education from coaches and support staff regarding the use of these questionnaires is required to gain the best data.
Assuntos
Inibidores Enzimáticos/uso terapêutico , Óxido Nítrico Sintase/antagonistas & inibidores , Sepse/tratamento farmacológico , Animais , Linhagem Celular , Modelos Animais de Doenças , Humanos , Lipopolissacarídeos/toxicidade , Camundongos , Óxido Nítrico Sintase Tipo II , Nitritos/urina , Fator de Necrose Tumoral alfa/análiseRESUMO
A series of substituted 2-iminopyrrolidines has been prepared and shown to be potent and selective inhibitors of the human inducible nitric oxide synthase (hiNOS) isoform versus the human endothelial nitric oxide synthase (heNOS) and the human neuronal nitric oxide synthase (hnNOS). Simple substitutions at the 3-, 4-, or 5-position afforded more potent analogues than the parent 2-iminopyrrolidine 1. The effect of ring substitutions on both potency and selectivity for the different NOS isoforms is described. Substitution at the 4- and 5-positions of the 2-iminopyrrolidine yielded both potent and selective inhibitors of hiNOS. In particular, (+)-cis-4-methyl-5-pentylpyrrolidin-2-imine, monohydrochloride (20), displayed potent inhibition of hiNOS (IC50 = 0.25 microM) and selectivities of 897 (heNOS IC50/hiNOS IC50) and 13 (hnNOS IC50/hiNOS IC50). Example 20 was shown to be an efficacious inhibitor of NO production in the mouse endotoxin assay. Furthermore, 20 displayed in vivo selectivity, versus heNOS isoform, by not elevating blood pressure at multiples of the effective dose in the mouse.
Assuntos
Inibidores Enzimáticos/síntese química , Iminas/síntese química , Isoenzimas/antagonistas & inibidores , Óxido Nítrico Sintase/antagonistas & inibidores , Pirrolidinas/síntese química , Animais , Pressão Sanguínea/efeitos dos fármacos , Indução Enzimática , Inibidores Enzimáticos/química , Inibidores Enzimáticos/farmacologia , Humanos , Iminas/química , Iminas/farmacologia , Lipopolissacarídeos/farmacologia , Espectroscopia de Ressonância Magnética , Masculino , Camundongos , Camundongos Endogâmicos BALB C , Neurônios/efeitos dos fármacos , Neurônios/enzimologia , Óxido Nítrico/antagonistas & inibidores , Óxido Nítrico Sintase Tipo II , Óxido Nítrico Sintase Tipo III , Pirrolidinas/química , Pirrolidinas/farmacologia , Estereoisomerismo , Relação Estrutura-AtividadeRESUMO
New clinical information systems use client-server software applications that require knowledge of personal computers, Microsoft Windows, and mouse control. Here, the authors describe a low-cost training method to supplement classroom teaching.
Assuntos
Capacitação de Usuário de Computador/métodos , Instrução por Computador/métodos , Educação Continuada em Enfermagem/organização & administração , Capacitação em Serviço/organização & administração , Recursos Humanos de Enfermagem Hospitalar/educação , Controle de Custos , Humanos , Sistemas Computadorizados de Registros Médicos , Microcomputadores , SoftwareAssuntos
Endotelinas/antagonistas & inibidores , Glicopeptídeos/síntese química , Neprilisina/antagonistas & inibidores , Compostos Organofosforados/síntese química , Animais , Cromatografia Líquida de Alta Pressão , Glicopeptídeos/química , Glicopeptídeos/farmacologia , Compostos Organofosforados/farmacologia , Coelhos , Relação Estrutura-AtividadeRESUMO
We compared low-density lipoprotein cholesterol (LDL) values obtained by the Friedewald formula--i.e., total cholesterol minus high-density lipoprotein (HDL) cholesterol minus very-low-density lipoprotein (VLDL) cholesterol (estimated as triglyceride divided by 5)--with those obtained by lipoprotein fractionation, using 4736 specimens. When triglycerides were less than 2.0 g/L, greater than 90% of estimated LDL cholesterol values were acceptable, within +/- 10% of measured values. At triglyceride concentrations of 2.0-4.0 g/L and 4.0-6.0 g/L, only 72% and 39%, respectively, of the estimates were acceptable. LDL values derived from an alternative formula, estimating VLDL as triglycerides divided by 6, were even less accurate. Nevertheless, the use of estimated LDL for risk classification based on the National Cholesterol Education Program Adult Treatment Panel cutpoints of 1.30 and 1.60 g/L was considered acceptable. At triglyceride concentrations less than or equal to 5.0 g/L, 88% of classifications based on estimated LDL (using triglycerides divided by 5) were concordant with those by measured LDL. Eleven percent of classifications were shifted across one cutpoint, evenly distributed between high and low. Fewer than 1% of classifications, all with Type III hyperlipoproteinemia, were misclassified two cutpoints high. Refinements in the estimation model did not substantially improve LDL estimation or concordance of risk classification.