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1.
Hum Brain Mapp ; 45(7): e26699, 2024 May.
Artículo en Inglés | MEDLINE | ID: mdl-38726907

RESUMEN

With the steadily increasing abundance of longitudinal neuroimaging studies with large sample sizes and multiple repeated measures, questions arise regarding the appropriate modeling of variance and covariance. The current study examined the influence of standard classes of variance-covariance structures in linear mixed effects (LME) modeling of fMRI data from patients with pediatric mild traumatic brain injury (pmTBI; N = 181) and healthy controls (N = 162). During two visits, participants performed a cognitive control fMRI paradigm that compared congruent and incongruent stimuli. The hemodynamic response function was parsed into peak and late peak phases. Data were analyzed with a 4-way (GROUP×VISIT×CONGRUENCY×PHASE) LME using AFNI's 3dLME and compound symmetry (CS), autoregressive process of order 1 (AR1), and unstructured (UN) variance-covariance matrices. Voxel-wise results dramatically varied both within the cognitive control network (UN>CS for CONGRUENCY effect) and broader brain regions (CS>UN for GROUP:VISIT) depending on the variance-covariance matrix that was selected. Additional testing indicated that both model fit and estimated standard error were superior for the UN matrix, likely as a result of the modeling of individual terms. In summary, current findings suggest that the interpretation of results from complex designs is highly dependent on the selection of the variance-covariance structure using LME modeling.


Asunto(s)
Imagen por Resonancia Magnética , Humanos , Masculino , Femenino , Adolescente , Niño , Conmoción Encefálica/diagnóstico por imagen , Conmoción Encefálica/fisiopatología , Modelos Lineales , Encéfalo/diagnóstico por imagen , Encéfalo/fisiología , Mapeo Encefálico/métodos , Función Ejecutiva/fisiología
2.
BMC Med Res Methodol ; 24(1): 111, 2024 May 10.
Artículo en Inglés | MEDLINE | ID: mdl-38730436

RESUMEN

BACKGROUND: A Generalized Linear Mixed Model (GLMM) is recommended to meta-analyze diagnostic test accuracy studies (DTAs) based on aggregate or individual participant data. Since a GLMM does not have a closed-form likelihood function or parameter solutions, computational methods are conventionally used to approximate the likelihoods and obtain parameter estimates. The most commonly used computational methods are the Iteratively Reweighted Least Squares (IRLS), the Laplace approximation (LA), and the Adaptive Gauss-Hermite quadrature (AGHQ). Despite being widely used, it has not been clear how these computational methods compare and perform in the context of an aggregate data meta-analysis (ADMA) of DTAs. METHODS: We compared and evaluated the performance of three commonly used computational methods for GLMM - the IRLS, the LA, and the AGHQ, via a comprehensive simulation study and real-life data examples, in the context of an ADMA of DTAs. By varying several parameters in our simulations, we assessed the performance of the three methods in terms of bias, root mean squared error, confidence interval (CI) width, coverage of the 95% CI, convergence rate, and computational speed. RESULTS: For most of the scenarios, especially when the meta-analytic data were not sparse (i.e., there were no or negligible studies with perfect diagnosis), the three computational methods were comparable for the estimation of sensitivity and specificity. However, the LA had the largest bias and root mean squared error for pooled sensitivity and specificity when the meta-analytic data were sparse. Moreover, the AGHQ took a longer computational time to converge relative to the other two methods, although it had the best convergence rate. CONCLUSIONS: We recommend practitioners and researchers carefully choose an appropriate computational algorithm when fitting a GLMM to an ADMA of DTAs. We do not recommend the LA for sparse meta-analytic data sets. However, either the AGHQ or the IRLS can be used regardless of the characteristics of the meta-analytic data.


Asunto(s)
Simulación por Computador , Pruebas Diagnósticas de Rutina , Metaanálisis como Asunto , Humanos , Pruebas Diagnósticas de Rutina/métodos , Pruebas Diagnósticas de Rutina/normas , Pruebas Diagnósticas de Rutina/estadística & datos numéricos , Modelos Lineales , Algoritmos , Funciones de Verosimilitud , Sensibilidad y Especificidad
3.
Accid Anal Prev ; 202: 107584, 2024 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-38692126

RESUMEN

INTRODUCTION: Modifying risk perceptions related to driving after cannabis use (DACU) could deter individuals from enacting this behavior, as low-risk perception is associated with DACU engagement. This study identified sociodemographic characteristics, substance use, other driving behaviors, peer norms, and psychological characteristics that are associated with lower risk perception regarding DACU. METHODS: Canadian drivers aged 17-35 who have used cannabis in the past year (n = 1,467) completed an online questionnaire. A multivariate linear regression model allowed for identifying variables associated with the low-risk perception of DACU (i.e. believing it to be safe as one's driving ability is not impaired by cannabis or by being high). RESULTS: Lower risk perception of DACU was associated with identifying as male, weekly to daily cannabis use, engagement in DACU, general risky driving behaviors, being a passenger of a driver who engages in DACU, number of friends who engage in DACU, and peer approval of DACU. Having driven under the influence of alcohol, living in urban areas, having received traffic tickets in the past three years, and declaring past-week irritability and cognitive problems were associated with holding a higher risk perception related to DACU. DISCUSSION: Road education and prevention programs should target attitudes and perceptions regarding risks shaped by sociocultural norms and past risky driving experiences. They need to reach out more specifically to drivers with the identified characteristics associated with the low-risk perception of DACU. These interventions can potentially help reduce the rate of individuals who engage in this behavior.


Asunto(s)
Conducir bajo la Influencia , Asunción de Riesgos , Humanos , Masculino , Adulto , Adulto Joven , Adolescente , Femenino , Conducir bajo la Influencia/psicología , Conducir bajo la Influencia/estadística & datos numéricos , Encuestas y Cuestionarios , Canadá , Percepción , Conducción de Automóvil/psicología , Modelos Lineales , Factores Sexuales , Análisis Multivariante
4.
Clin Interv Aging ; 19: 763-768, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-38741720

RESUMEN

Purpose: Vitamin D deficiency is a common finding in geriatric patients. The ESPEN micronutrient guideline states that vitamin D serum levels significantly decrease in the presence of inflammation and should be interpreted with caution. This is of great interest for hospital care and would imply a significant change to the current approach to hospitalized patients with suspected vitamin D deficiency. Patients and methods: To evaluate the association of vitamin D and inflammation, we reanalyzed the data set of serum 25(OH)D-Levels of 687 consecutive geriatric hospitalized patients of a previously published study. Results: We found that vitamin D deficiency (<20 ng/dl) was prevalent in 78.0% and vitamin D insufficiency (20-30 ng/dl) in 9.9% of patients. Sperman's correlation showed a significant but very weak correlation (R = -0.100, P < 0.01) of serum vitamin D and C-reactive protein. However, linear regression with the inclusion of age and gender revealed no significant association (beta-coefficient -0.070; p=0.067). Conclusion: In this study, we could not confirm a significant and clinically relevant association between serum vitamin D levels and inflammation, contrasting with a previous study. However, longitudinal studies need to be performed to draw a final conclusion.


Asunto(s)
Proteína C-Reactiva , Hospitalización , Inflamación , Deficiencia de Vitamina D , Vitamina D , Humanos , Deficiencia de Vitamina D/sangre , Masculino , Femenino , Vitamina D/sangre , Anciano , Estudios Retrospectivos , Inflamación/sangre , Proteína C-Reactiva/análisis , Anciano de 80 o más Años , Hospitalización/estadística & datos numéricos , Modelos Lineales , Prevalencia
5.
J Mass Spectrom ; 59(6): e5031, 2024 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-38726684

RESUMEN

Managing ocular microbial infections typically requires pharmacotherapy using antibiotic eye drops, such as moxifloxacin hydrochloride (MFX), combined with an antifungal agent like amphotericin B (AB). We carried out and validated an LC-MS/MS assay to quantify these compounds in rabbit tear fluid in order to look into the pharmacokinetics of these two drugs. We employed a protein precipitation technique for the extraction of drugs under examination. A Waters Symmetry C18 column was used to separate the analytes and internal standard. The composition of the mobile phase was like (A) 0.1% v/v formic acid in water and (B) methanol. The detection of MFX and AB was accomplished through the utilization of positive ion electrospray ionization under multiple reaction monitoring mode. The linearity curves for both analytes exhibited an acceptable trendline across a concentration range of 2.34-300 ng/mL for MFX and 7.81-1000 ng/mL for AB in surrogate rabbit tear fluid. The lower limit of quantitation for MFX was 2.34 ng/mL, while for AB, it was 7.81 ng/mL. The approach was strictly validated, encompassing tests of selectivity, linearity (with r2 > 0.99), precision, accuracy, matrix effects, and stability. Consequently, we employed this method to evaluate the pharmacokinetics profiles of MFX and AB in rabbit tear fluid following single topical doses.


Asunto(s)
Moxifloxacino , Espectrometría de Masas en Tándem , Lágrimas , Conejos , Animales , Espectrometría de Masas en Tándem/métodos , Lágrimas/química , Moxifloxacino/farmacocinética , Moxifloxacino/análisis , Reproducibilidad de los Resultados , Anfotericina B/farmacocinética , Anfotericina B/análisis , Límite de Detección , Antiinfecciosos/farmacocinética , Antiinfecciosos/análisis , Cromatografía Liquida/métodos , Soluciones Oftálmicas/farmacocinética , Modelos Lineales , Cromatografía Líquida con Espectrometría de Masas
6.
Arch Iran Med ; 27(5): 239-247, 2024 May 01.
Artículo en Inglés | MEDLINE | ID: mdl-38690790

RESUMEN

BACKGROUND: Today, cardiovascular disease (CVD) is the most important cause of death around the world. In this study, our main aim was to predict CVD using some of the most important indicators of this disease and present a tree-based statistical framework for detecting CVD patients according to these indicators. METHODS: We used data from the baseline phase of the Fasa Cohort Study (FACS). The outcome variable was the presence of CVD. The ordinary Tree and generalized linear mixed models (GLMM) were fitted to the data and their predictive power for detecting CVD was compared with the obtained results from the GLMM tree. Statistical analysis was performed using the RStudio software. RESULTS: Data of 9499 participants aged 35‒70 years were analyzed. The results of the multivariable mixed-effects logistic regression model revealed that participants' age, total cholesterol, marital status, smoking status, glucose, history of cardiac disease or myocardial infarction (MI) in first- and second-degree relatives, and presence of other diseases (like hypertension, depression, chronic headaches, and thyroid disease) were significantly related to the presence of CVD (P<0.05). Fitting the ordinary tree, GLMM, and GLMM tree resulted in area under the curve (AUC) values of 0.58 (0.56, 0.61), 0.81 (0.77, 0.84), and 0.80 (0.76, 0.83), respectively, among the study population. In addition, the tree model had the best specificity at 81% but the lowest sensitivity at 65% compared to the other models. CONCLUSION: Given the superior performance of the GLMM tree compared with the standard tree and the lack of significant difference with the GLMM, using this model is suggested due to its simpler interpretation and fewer assumptions. Using updated statistical models for more accurate CVD prediction can result in more precise frameworks to aid in proactive patient detection planning.


Asunto(s)
Enfermedades Cardiovasculares , Humanos , Persona de Mediana Edad , Enfermedades Cardiovasculares/epidemiología , Masculino , Femenino , Adulto , Anciano , Irán/epidemiología , Modelos Lineales , Modelos Logísticos , Estudios de Cohortes , Medición de Riesgo/métodos , Factores de Riesgo , Factores de Riesgo de Enfermedad Cardiaca , Área Bajo la Curva
7.
Skin Res Technol ; 30(5): e13719, 2024 May.
Artículo en Inglés | MEDLINE | ID: mdl-38696230

RESUMEN

BACKGROUND: The assessment of skin aging through skin measurements faces limitations, making perceived age evaluation a more valuable and direct tool for assessing skin aging. Given that the aging process markedly affects the appearance of the eye contour, characterizing the eye region could be beneficial for perceived age assessment. This study aimed to analyze age-correlated changes in the eye contour within the Chinese Han female population and to develop, validate, and apply a multiple linear regression model for predicting perceived age. MATERIALS AND METHODS: A naïve panel of 107 Chinese women assessed the perceived ages of 212 Chinese Han women. Instrumental analysis evaluated periorbital parameters, including palpebral fissure width (PFW), palpebral fissure height (PFH), acclivity of palpebral fissure (AX), angle of inner canthal (AEN), and angle of outer canthal (AEX). These parameters were used to construct a multiple linear regression model for predicting the perceived ages of Chinese Han women. A combined treatment using Fotona 4D and an anti-aging eye cream, formulated with plant extracts, peptides, and antioxidants, was conducted to verify the cream's anti-aging efficacy and safety. This eye cream was then tested in a large-scale clinical trial involving 101 participants. The prediction model was employed in this trial to assess the perceived ages of the women after an 8-week application of the eye cream. RESULTS: All parameters were observed to decrease with age. An intergroup comparison indicated that eyelid aging in Chinese Han women accelerates beyond the age of 50. Consequently, a linear regression model was constructed and validated, with the perceived age being calculated as 183.159 - 1.078 * AEN - 4.487 * PFW + 6.061 * PFH - 1.003 * AX - 0.328 * AEX. The anti-aging efficacy and safety of the eye cream were confirmed through combined treatment with Fotona 4D, showing improvements in wrinkles, elasticity, and dark circles under the eyes. In a large-scale clinical evaluation using this eye cream, a perceived age prediction model was applied, suggesting that 8 weeks of use made participants appear 2.25 years younger. CONCLUSION: Our study developed and validated a multiple linear regression model to predict the perceived age of Chinese Han women. This model was successfully utilized in a large-scale clinical evaluation of anti-aging eye cream, revealing that 8 weeks of usage made participants appear 2.25 years younger. This method effectively bridges the gap between clinical research and consumer perceptions, explores the complex factors influencing perceived age, and aims to improve anti-aging formulations.


Asunto(s)
Pueblo Asiatico , Envejecimiento de la Piel , Humanos , Femenino , Envejecimiento de la Piel/efectos de los fármacos , Envejecimiento de la Piel/fisiología , Envejecimiento de la Piel/etnología , Persona de Mediana Edad , Adulto , Anciano , China/etnología , Adulto Joven , Extractos Vegetales/farmacología , Extractos Vegetales/uso terapéutico , Crema para la Piel/administración & dosificación , Modelos Lineales , Ojo , Pueblos del Este de Asia
8.
J Orthop Surg Res ; 19(1): 277, 2024 May 03.
Artículo en Inglés | MEDLINE | ID: mdl-38698472

RESUMEN

PURPOSE: To determine whether posterior cruciate ligament (PCL) buckling (angular change) is associated with anterior cruciate ligament (ACL) status (intact or ruptured), meniscal bone angle (MBA), anterior tibial translation (ATT), body weight, femoral-tibial rotation (FTR), posterior tibial slope (PTS), PCL length and femoral-tibial distance (FTD) and to identify the factors that have the greatest influence. METHODS: All enrolled participants were scanned with a 3.0 T, 8-channel coil MRI system (Magnetom Verio; Siemens). Bone and soft tissue parameters were measured by MIMICS software for each subject and each measured parameter was correlated with PCL buckling phenomena. The correlated and statistically significant parameters were then analyzed by multiple linear regression to determine the magnitude of the effect of the different parameters on the PCL buckling phenomenon. RESULTS: A total of 116 subjects (50 ACL ruptured and 66 age, weight and height matched volunteers with uninjured knees) were enrolled. Among all measured parameters, there were 8 parameters that correlated with PCL angle (PCLA), of which ACL status had the strongest correlation with PCLA (r = - 0.67, p = < 0.001); and 7 parameters that correlated with PCL-posterior femoral cortex angle (PCL-PCA), of which ATT had the strongest correlation with PCL-PCA (r = 0.69, p = < 0.001). PCLIA was not significantly correlated with any of the measured parameters. Multiple linear regression analyses revealed four parameters can explain PCLA, of which ACL status had the strongest effect on PCLA (absolute value of standardized coefficient Beta was 0.508). Three parameters can explain PCL-PCA, of which ATT had the strongest effect on PCLIA (r = 0.69, p = < 0.001), ATT has the greatest effect on PCL-PCA (absolute value of normalized coefficient Beta is 0.523). CONCLUSIONS: PCLA may be a simple and easily reproducible and important supplement for the diagnosis of ACL injury; PCL-PCA is a simple and easily reproducible and important complementary tool for the detection of ATT. The use of PCLA is more recommended to aid in the diagnosis of ACL injury.


Asunto(s)
Articulación de la Rodilla , Imagen por Resonancia Magnética , Ligamento Cruzado Posterior , Tibia , Humanos , Ligamento Cruzado Posterior/diagnóstico por imagen , Masculino , Femenino , Adulto , Articulación de la Rodilla/diagnóstico por imagen , Modelos Lineales , Adulto Joven , Tibia/diagnóstico por imagen , Tibia/anatomía & histología , Imagen por Resonancia Magnética/métodos , Persona de Mediana Edad , Fémur/diagnóstico por imagen , Fémur/anatomía & histología , Lesiones del Ligamento Cruzado Anterior/diagnóstico por imagen , Adolescente
9.
Braz Oral Res ; 38: e032, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-38747819

RESUMEN

This study assessed the reliability of a color measurement method using images obtained from a charge-coupled device (CCD) camera and a stereoscopic loupe. Disc-shaped specimens were created using the composite Filtek Z350 XT (shades DA1, DA2, DA3, and DA4) (n = 3). CIELAB color coordinates of the specimens were measured using the spectrophotometer SP60 over white and black backgrounds. Images of the same specimens were taken using a CCD camera attached to a stereoscopic loupe. The color of the image was measured (red-green-blue [RGB]) using an image processing software and converted to CIELAB coordinates. For each color coordinate, data from images were adjusted using linear regressions predicting those values from SP60. The whiteness index for dentistry (WID) and translucency parameter (TP00) of the specimens as well as the color differences (ΔE00) among pairwise shades were calculated. Data were analyzed via repeated-measures analysis of variance and Tukey's post hoc test (α = 0.05). Images obtained using the loupe tended to be darker and redder than the actual color. Data adjustment resulted in similar WID, ΔE00, and TP00 values to those observed for the spectrophotometer. Differences were observed only for the WID of shade DA3 and ΔE00 for comparing DA1 and DA3 over the black background. However, these differences were not clinically relevant. The use of adjusted data from images taken using a stereoscopic loupe is considered a feasible method for color measurement.


Asunto(s)
Color , Colorimetría , Resinas Compuestas , Ensayo de Materiales , Espectrofotometría , Reproducibilidad de los Resultados , Resinas Compuestas/química , Espectrofotometría/métodos , Colorimetría/métodos , Colorimetría/instrumentación , Análisis de Varianza , Valores de Referencia , Modelos Lineales , Procesamiento de Imagen Asistido por Computador/métodos
10.
Braz Oral Res ; 38: e043, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-38747830

RESUMEN

This cross-sectional study evaluated the association between salivary immunoglobulins, plaque index, and gingival index in Brazilian children with and without type 1 diabetes mellitus (DM1). The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist for the reporting of observational studies was followed. The DM1 group had 38 children, and an equal number of volunteers matched by sex and age were recruited as controls. Clinical examination was performed for plaque index and gingival index determination. Non-stimulated whole saliva was collected. Concentrations of IgA, IgG, and IgM were determined by ELISA test. Data were tested by the Kolmogorov-Smirnov, Mann-Whitney, and Spearman tests and a multiple linear regression model (p<0.05) was performed. Gingival index was higher in the Control (DM1: 0.16±0.17; Control: 0.24±0.23, p=0.040). In DM1, there was a correlation between IgA and age (rho=0.371, p=0.024), IgM and IgG (rho=0.459, p=0.007), and IgM and gingival index (rho=0.394, p=0.014). In DM1, multiple linear regression showed that age (p=0.041; ß=0.363), gingival index (p=0.041; ß=0.398), and plaque index (p=0.008; ß=-0.506) were good predictors of IgA levels in saliva. Thus, IgA was the only researched immunoglobulin that was directly associated with plaque and gingival indices in Brazilian children with DM1, but not in control subjects.


Asunto(s)
Índice de Placa Dental , Diabetes Mellitus Tipo 1 , Inmunoglobulina A , Índice Periodontal , Saliva , Humanos , Diabetes Mellitus Tipo 1/inmunología , Masculino , Femenino , Saliva/química , Saliva/inmunología , Estudios Transversales , Niño , Brasil/epidemiología , Estudios de Casos y Controles , Inmunoglobulina A/análisis , Inmunoglobulina G/análisis , Estadísticas no Paramétricas , Inmunoglobulina M/análisis , Valores de Referencia , Ensayo de Inmunoadsorción Enzimática , Adolescente , Modelos Lineales , Factores de Edad , Inmunoglobulinas/análisis
11.
J Forensic Odontostomatol ; 42(1): 22-29, 2024 Apr 30.
Artículo en Inglés | MEDLINE | ID: mdl-38742569

RESUMEN

BACKGROUND: The utilization of segmentation method using volumetric data in adults dental age estimation (DAE) from cone-beam computed tomography (CBCT) was further expanded by using current 5-Part Tooth Segmentation (SG) method. Additionally, supervised machine learning modelling -namely support vector regression (SVR) with linear and polynomial kernel, and regression tree - was tested and compared with the multiple linear regression model. MATERIAL AND METHODS: CBCT scans from 99 patients aged between 20 to 59.99 was collected. Eighty eligible teeth including maxillary canine, lateral incisor, and central incisor were used in this study. Enamel to dentine volume ratio, pulp to dentine volume ratio, lower tooth volume ratio, and sex was utilized as independent variable to predict chronological age. RESULTS: No multicollinearity was detected in the models. The best performing model comes from maxillary lateral incisor using SVR with polynomial kernel ( = 0.73). The lowest error rate achieved by the model was given also by maxillary lateral incisor, with 4.86 years of mean average error and 6.05 years of root means squared error. However, demands a complex approach to segment the enamel volume in the crown section and a lengthier labour time of 45 minutes per tooth.


Asunto(s)
Determinación de la Edad por los Dientes , Tomografía Computarizada de Haz Cónico , Aprendizaje Automático , Humanos , Adulto , Determinación de la Edad por los Dientes/métodos , Masculino , Femenino , Adulto Joven , Persona de Mediana Edad , Esmalte Dental/diagnóstico por imagen , Dentina/diagnóstico por imagen , Modelos Lineales , Pulpa Dental/diagnóstico por imagen , Máquina de Vectores de Soporte
12.
Sci Rep ; 14(1): 10967, 2024 05 14.
Artículo en Inglés | MEDLINE | ID: mdl-38744956

RESUMEN

Spatial transcriptomics (ST) assays represent a revolution in how the architecture of tissues is studied by allowing for the exploration of cells in their spatial context. A common element in the analysis is delineating tissue domains or "niches" followed by detecting differentially expressed genes to infer the biological identity of the tissue domains or cell types. However, many studies approach differential expression analysis by using statistical approaches often applied in the analysis of non-spatial scRNA data (e.g., two-sample t-tests, Wilcoxon's rank sum test), hence neglecting the spatial dependency observed in ST data. In this study, we show that applying linear mixed models with spatial correlation structures using spatial random effects effectively accounts for the spatial autocorrelation and reduces inflation of type-I error rate observed in non-spatial based differential expression testing. We also show that spatial linear models with an exponential correlation structure provide a better fit to the ST data as compared to non-spatial models, particularly for spatially resolved technologies that quantify expression at finer scales (i.e., single-cell resolution).


Asunto(s)
Perfilación de la Expresión Génica , Transcriptoma , Perfilación de la Expresión Génica/métodos , Análisis de la Célula Individual/métodos , Modelos Lineales , Análisis Espacial , Animales , Humanos
13.
J Sports Sci ; 42(6): 519-526, 2024 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-38704669

RESUMEN

This study aimed to optimise performance prediction in short-course swimming through Principal Component Analyses (PCA) and multiple regression. All women's freestyle races at the European Short-Course Swimming Championships were analysed. Established performance metrics were obtained including start, free-swimming, and turn performance metrics. PCA were conducted to reduce redundant variables, and a multiple linear regression was performed where the criterion was swimming time. A practical tool, the Potential Predictor, was developed from regression equations to facilitate performance prediction. Bland and Altman analyses with 95% limits of agreement (95% LOA) were used to assess agreement between predicted and actual swimming performance. There was a very strong agreement between predicted and actual swimming performance. The mean bias for all race distances was less than 0.1s with wider LOAs for the 800 m (95% LOA -7.6 to + 7.7s) but tighter LOAs for the other races (95% LOAs -0.6 to + 0.6s). Free-Swimming Speed (FSS) and turn performance were identified as Key Performance Indicators (KPIs) in the longer distance races (200 m, 400 m, 800 m). Start performance emerged as a KPI in sprint races (50 m and 100 m). The successful implementation of PCA and multiple regression provides coaches with a valuable tool to uncover individual potential and empowers data-driven decision-making in athlete training.


Asunto(s)
Rendimiento Atlético , Análisis de Componente Principal , Natación , Humanos , Natación/fisiología , Rendimiento Atlético/fisiología , Femenino , Modelos Lineales , Conducta Competitiva/fisiología
14.
Sci Rep ; 14(1): 10866, 2024 05 13.
Artículo en Inglés | MEDLINE | ID: mdl-38740920

RESUMEN

The presence of Arbuscular Mycorrhizal Fungi (AMF) in vascular land plant roots is one of the most ancient of symbioses supporting nitrogen and phosphorus exchange for photosynthetically derived carbon. Here we provide a multi-scale modeling approach to predict AMF colonization of a worldwide crop from a Recombinant Inbred Line (RIL) population derived from Sorghum bicolor and S. propinquum. The high-throughput phenotyping methods of fungal structures here rely on a Mask Region-based Convolutional Neural Network (Mask R-CNN) in computer vision for pixel-wise fungal structure segmentations and mixed linear models to explore the relations of AMF colonization, root niche, and fungal structure allocation. Models proposed capture over 95% of the variation in AMF colonization as a function of root niche and relative abundance of fungal structures in each plant. Arbuscule allocation is a significant predictor of AMF colonization among sibling plants. Arbuscules and extraradical hyphae implicated in nutrient exchange predict highest AMF colonization in the top root section. Our work demonstrates that deep learning can be used by the community for the high-throughput phenotyping of AMF in plant roots. Mixed linear modeling provides a framework for testing hypotheses about AMF colonization phenotypes as a function of root niche and fungal structure allocations.


Asunto(s)
Micorrizas , Raíces de Plantas , Sorghum , Micorrizas/fisiología , Raíces de Plantas/microbiología , Sorghum/microbiología , Modelos Lineales , Simbiosis , Redes Neurales de la Computación
15.
BMC Womens Health ; 24(1): 277, 2024 May 07.
Artículo en Inglés | MEDLINE | ID: mdl-38714996

RESUMEN

BACKGROUND: Quality of life research can guide clinical workers to adopt more targeted treatment and intervention measures, so as to achieve the purpose of improving patients' quality of life. The objective of this study was to evaluate health-related quality of life in Chinese patients with cervical cancer and to explore its influencing factors. METHODS: A total of 186 patients with cervical cancer were investigated by using the QLICP-CE (V2.0) scale (Quality of Life Instruments for Cancer Patients-Cervical Cancer) developed by our group in China. The data were analyzed by t-test, one-way ANOVA, univariate analysis, and multivariate linear regression. RESULTS: The total score of quality of life scale for cervical cancer patients was (62.58 ± 12.69), Univariate analysis of objective clinical indexes showed that creatinine concentration was a negative influence factor in the psychological domain, potassium ion concentration was a negative influence factor in the common symptoms and side effect domain, erythrocyte content was a positive influence factor physical domain and common general domain. Multiple linear regression results suggested that clinical staging was the influencing factor of common symptom and side effect domain, common general module and total score of scale. Marital status has different degrees of influence on the psychological, social, and common general domains. The level of education also influenced scores in the social domain. CONCLUSION: The total score of quality of life in patients with cervical cancer who received active treatment was acceptable. Marital status, clinical staging, and educational level are the factors that affect the quality of life of patients with cervical cancer. At the same time, potassium ion concentration, red blood cell count and creatinine concentration also have important effects on quality of life in patients with cervical cancer. Therefore, it is very important to give personalized treatment and nursing to patients based on various factors.


Asunto(s)
Calidad de Vida , Neoplasias del Cuello Uterino , Humanos , Femenino , Neoplasias del Cuello Uterino/psicología , Calidad de Vida/psicología , Persona de Mediana Edad , Adulto , China/epidemiología , Encuestas y Cuestionarios , Anciano , Estadificación de Neoplasias , Creatinina/sangre , Estado Civil , Modelos Lineales
16.
Age Ageing ; 53(5)2024 May 01.
Artículo en Inglés | MEDLINE | ID: mdl-38706394

RESUMEN

BACKGROUND: The updated European Working Group on Sarcopenia in Older People (EWGSOP2) recommends handgrip strength (HGS) and the chair stand test (CST) to assess muscle strength, with the CST being a convenient proxy for lower limb strength. However, adiposity may differentially influence these strength criteria and produce discrepant sarcopenia prevalence. OBJECTIVE: To determine the prevalence of sarcopenia using HGS or the CST, and to investigate the associations between these strength criteria and adiposity in adults with type 2 diabetes mellitus. METHODS: The EWGSOP2 definition was used to assess the prevalence of probable (low muscle strength), confirmed (plus low muscle mass) and severe (plus poor physical performance) sarcopenia. Linear regression models were used to study the association between different measures of muscle strength and adiposity. RESULTS: We used data from 732 adults with type 2 diabetes mellitus (35.7% female, aged 64 ± 8 years, body mass index 30.7 ± 5.0 kg/m2). Using the CST compared with HGS produced a higher prevalence of probable (31.7% vs. 7.1%), confirmed (5.6% vs. 1.6%) and severe (1.0% vs. 0.3%) sarcopenia, with poor agreement between strength criteria to identify probable sarcopenia. CST performance, but not HGS, was significantly associated with all measures of adiposity in unadjusted and adjusted models. CONCLUSIONS: Higher levels of adiposity may impact CST performance, but not HGS, resulting in a higher prevalence of sarcopenia in adults with type 2 diabetes mellitus. Consideration should be paid to the most appropriate measure of muscle function in this population.


Asunto(s)
Adiposidad , Diabetes Mellitus Tipo 2 , Fuerza de la Mano , Sarcopenia , Humanos , Sarcopenia/epidemiología , Sarcopenia/fisiopatología , Sarcopenia/diagnóstico , Femenino , Diabetes Mellitus Tipo 2/epidemiología , Diabetes Mellitus Tipo 2/fisiopatología , Diabetes Mellitus Tipo 2/diagnóstico , Diabetes Mellitus Tipo 2/complicaciones , Masculino , Anciano , Prevalencia , Persona de Mediana Edad , Estudios Transversales , Evaluación Geriátrica/métodos , Valor Predictivo de las Pruebas , Factores de Edad , Modelos Lineales
17.
Bull Math Biol ; 86(6): 68, 2024 May 04.
Artículo en Inglés | MEDLINE | ID: mdl-38703247

RESUMEN

We demonstrate that the Michaelis-Menten reaction mechanism can be accurately approximated by a linear system when the initial substrate concentration is low. This leads to pseudo-first-order kinetics, simplifying mathematical calculations and experimental analysis. Our proof utilizes a monotonicity property of the system and Kamke's comparison theorem. This linear approximation yields a closed-form solution, enabling accurate modeling and estimation of reaction rate constants even without timescale separation. Building on prior work, we establish that the sufficient condition for the validity of this approximation is s 0 ≪ K , where K = k 2 / k 1 is the Van Slyke-Cullen constant. This condition is independent of the initial enzyme concentration. Further, we investigate timescale separation within the linear system, identifying necessary and sufficient conditions and deriving the corresponding reduced one-dimensional equations.


Asunto(s)
Conceptos Matemáticos , Cinética , Modelos Lineales , Enzimas/metabolismo , Modelos Químicos , Modelos Biológicos , Simulación por Computador , Factores de Tiempo
18.
J Comput Aided Mol Des ; 38(1): 21, 2024 May 01.
Artículo en Inglés | MEDLINE | ID: mdl-38693331

RESUMEN

Covalent inhibition offers many advantages over non-covalent inhibition, but covalent warhead reactivity must be carefully balanced to maintain potency while avoiding unwanted side effects. While warhead reactivities are commonly measured with assays, a computational model to predict warhead reactivities could be useful for several aspects of the covalent inhibitor design process. Studies have shown correlations between covalent warhead reactivities and quantum mechanic (QM) properties that describe important aspects of the covalent reaction mechanism. However, the models from these studies are often linear regression equations and can have limitations associated with their usage. Applications of machine learning (ML) models to predict covalent warhead reactivities with QM descriptors are not extensively seen in the literature. This study uses QM descriptors, calculated at different levels of theory, to train ML models to predict reactivities of covalent acrylamide warheads. The QM/ML models are compared with linear regression models built upon the same QM descriptors and with ML models trained on structure-based features like Morgan fingerprints and RDKit descriptors. Experiments show that the QM/ML models outperform the linear regression models and the structure-based ML models, and literature test sets demonstrate the power of the QM/ML models to predict reactivities of unseen acrylamide warhead scaffolds. Ultimately, these QM/ML models are effective, computationally feasible tools that can expedite the design of new covalent inhibitors.


Asunto(s)
Cisteína , Diseño de Fármacos , Aprendizaje Automático , Teoría Cuántica , Cisteína/química , Acrilamida/química , Humanos , Modelos Moleculares , Relación Estructura-Actividad Cuantitativa , Modelos Lineales , Estructura Molecular
19.
Front Public Health ; 12: 1348088, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-38577285

RESUMEN

Introduction: Inequitable access to COVID-19 vaccines among countries is a pressing global health issue. Factors such as economic power, political power, political stability, and health system strength contribute to disparities in vaccine distribution. This study aims to assess the inequality in vaccine distribution among countries based on these factors and identify their relationship with COVID-19 vaccine distribution. Methods: A Concentration Index (CI) analysis was conducted to evaluate inequalities in the distribution of COVID-19 vaccines among countries based on four separate variables: GDP per capita, political stability (PS), World Power Index (WPI), and Universal Health Coverage (UHC). Additionally, Multiple Linear Regression (MLR) analysis was employed to explore the relationship between vaccine distribution and these independent variables. Two vaccine distribution variables were utilized for result reliability. Results: The analysis revealed significant inequalities in COVID-19 vaccine distribution according to the countries' GDP/capita, PS, WPI, and UHC. However, the multiple linear regression analysis showed that there is no significant relationship between COVID-19 vaccine distribution and the countries' GDP/capita and that UHC is the most influential factor impacting COVID-19 vaccine distribution and accessibility. Discussion: The findings underscore the complex interplay between economic, political, and health system factors in shaping vaccine distribution patterns. To improve the accessibility to vaccines in future pandemics, Global Health Governance (GHG) and countries should consider working on three areas; enhance political stabilities in countries, separate the political power from decision-making at the global level and most importantly support countries to achieve UHC.


Asunto(s)
Vacunas contra la COVID-19 , COVID-19 , Humanos , Modelos Lineales , Reproducibilidad de los Resultados , COVID-19/epidemiología , COVID-19/prevención & control , Análisis de Regresión
20.
Pan Afr Med J ; 47: 47, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-38681102

RESUMEN

Introduction: the obesity epidemic is growing faster in developing countries with no exception of Ethiopia. Currently, abdominal obesity is identified as a major risk factor for chronic diseases due to the accumulation of liable fat. However, despite the evidence of certain documented data, abdominal obesity has been on the rise in Ethiopia, especially in urban areas. Therefore, this study aimed to assess the prevalence and factors associated with abdominal obesity among adults in Jimma town, Southwest Ethiopia. Methods: a community-based cross-sectional study was employed on 845 adults selected using a multi-stage sampling technique. Data were collected using a pretested interviewer-administered questionnaire. Data were entered using Epi-data version 3.1 and exported to STATA version 14 for analysis. Simple linear regression was conducted to identify candidate variables. A multivariable linear regression model was fitted to identify factors associated with abdominal obesity. P-value<0.05 was used to declare statistical significance. Results: a total of 806 respondents participated in this study, making a response rate of 95.4%. The magnitude of abdominal obesity was found to be 24.6% (95% CI: 21.5, 27.5). Physical activity (ß= -2.053; 95%CI: -3.353, -0.454), alcohol consumption (ß=1.631; 95%CI: 0.176, 3.087), and age (ß=0.319; 95%CI: 0.250, 0.389) were significantly associated with abdominal obesity. Conclusion: the magnitude of abdominal obesity among adults in the study area was high compared to previous studies. Alcohol drinking, being physically inactive, and age were predictors of abdominal obesity. There is a need for intervention for adults with physical inactivity and alcohol consumption to reduce abdominal obesity.


Asunto(s)
Consumo de Bebidas Alcohólicas , Ejercicio Físico , Obesidad Abdominal , Población Urbana , Humanos , Etiopía/epidemiología , Estudios Transversales , Obesidad Abdominal/epidemiología , Adulto , Femenino , Masculino , Persona de Mediana Edad , Factores de Riesgo , Adulto Joven , Prevalencia , Población Urbana/estadística & datos numéricos , Consumo de Bebidas Alcohólicas/epidemiología , Encuestas y Cuestionarios , Modelos Lineales , Adolescente
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