Autopercepción e insatisfacción de la imagen corporal con relación al IMC y porcentaje de grasa entre hombres y mujeres estudiantes universitarios chilenos / Self-Perception and Body Image Dissatisfaction about BMI and Fat Percentage Among Male and Female Chilean University Students / Autopercepção e insatisfação com a imagem corporal em relação ao IMC e à porcentagem de gordura entre os estudantes universitários chilenos do sexo masculino e feminino

Resumen: Introducción: Uno de los factores que condiciona el peso corporal es la percepción de la imagen corporal. En estudiantes universitarios la ingesta de comida rápida puede generar dificultades en la autopercepción de la imagen corporal como lo son la subestimación o sobreestimación del estado nutricional, llegando a producir trastornos como anorexia, bulimia e intentos de suicidio. Objetivo: Comparar la autopercepción de la imagen corporal, insatisfacción corporal, índice de masa corporal (IMC) y porcentaje de grasa corporal entre mujeres y hombres de la Universidad Adventista de Chile. Materiales y métodos: Estudio de tipo descriptivo comparativo de diseño transversal, aplicado a 150 estudiantes regulares de la Universidad Adventista de Chile, Chillán (UnACh). Se realizaron evaluaciones antropométricas (IMC y pliegues cutáneos), aplicación de Body Shape Questionnaire (BSQ) y Test de Modelo anatómico de Montero (MAM). Resultados: Entre los principales hallazgos se presentaron diferencias entre hombres y mujeres tanto en el BSQ como en el porcentaje de grasa, no así en el MAM y en el IMC donde no se encontraron diferencias significativas. Conclusiones: Las mujeres evaluadas poseen mayor insatisfacción corporal y porcentaje de grasa que los hombres universitarios; sin embargo, tanto hombres como mujeres poseen autopercepción corporal que se ajusta a su IMC, no habiendo diferencias significativas entre ambos sexos.

Abstract: Introduction: One of the factors that conditions body weight is the perception of body image. In university students, eating fast food can generate disorders in the self-perception of body image, such as underestimation or overestimation of nutritional status, leading to disorders such as anorexia, bulimia, and suicide attempts. Objective: To compare the self-perception of body image, body dissatisfaction, body mass index (BMI) and percentage of body fat between women and men from the Chilean Adventist University. Material and methods: A comparative descriptive study of cross-sectional design applied to 150 regular students of the Adventist University of Chile, Chillán (UnACh). Anthropometric evaluations (BMI and skinfolds), application of the Body Shape Questionnaire (BSQ), and the Montero Anatomical Model Test (MAM) were performed. Results: Among the main findings, there were differences between men and women both in the BSQ and in the fat percentage, but not in the MAM and in the BMI, where no significant differences were found. Conclusions: The women evaluated have higher body dissatisfaction and fat percentage than university men; however, both men and women have body self-perception that adjusts to their BMI, with no significant differences between the sexes.

Resumo: Introdução: Um dos fatores que condicionam o peso corporal é a percepção da imagem corporal. Em estudantes universitários, a ingestão de fast food pode gerar desordens na autopercepção da imagem corporal, como subestimação ou superestimação do estado nutricional, levando a desordens como anorexia, bulimia e tentativas de suicídio. Objetivo: Comparar a autopercepção da imagem corporal, insatisfação corporal, índice de massa corporal (IMC) e porcentagem de gordura corporal entre mulheres e homens na Universidade Adventista do Chile. Material e métodos: Estudo descritivo comparativo do projeto transversal, aplicado a 150 estudantes regulares da Universidade Adventista do Chile, Chillán (UnACh). Avaliações antropométricas (IMC e pregas cutâneas), aplicação do Questionário de imagem orporal (BSQ) e Teste de Modelo Anatômico de Montero (MAM) foram realizados. Resultados: Entre as principais constatações estavam diferenças entre homens e mulheres tanto no BSQ quanto na porcentagem de gordura, mas não no MAM e IMC, onde não foram encontradas diferenças significativas. Conclusões: As mulheres avaliadas têm maior insatisfação corporal e maior percentual de gordura do que os homens universitários; no entanto, tanto homens como mulheres têm uma autopercepção corporal que se ajusta ao seu IMC, sem diferenças significativas entre os dois sexos.

Automated prioritization of sick newborns for whole genome sequencing using clinical natural language processing and machine learning.

BACKGROUND: Rapidly and efficiently identifying critically ill infants for whole genome sequencing (WGS) is a costly and challenging task currently performed by scarce, highly trained experts and is a major bottleneck for application of WGS in the NICU. There is a dire need for automated means to prioritize patients for WGS. METHODS: Institutional databases of electronic health records (EHRs) are logical starting points for identifying patients with undiagnosed Mendelian diseases. We have developed automated means to prioritize patients for rapid and whole genome sequencing (rWGS and WGS) directly from clinical notes. Our approach combines a clinical natural language processing (CNLP) workflow with a machine learning-based prioritization tool named Mendelian Phenotype Search Engine (MPSE). RESULTS: MPSE accurately and robustly identified NICU patients selected for WGS by clinical experts from Rady Children's Hospital in San Diego (AUC 0.86) and the University of Utah (AUC 0.85). In addition to effectively identifying patients for WGS, MPSE scores also strongly prioritize diagnostic cases over non-diagnostic cases, with projected diagnostic yields exceeding 50% throughout the first and second quartiles of score-ranked patients. CONCLUSIONS: Our results indicate that an automated pipeline for selecting acutely ill infants in neonatal intensive care units (NICU) for WGS can meet or exceed diagnostic yields obtained through current selection procedures, which require time-consuming manual review of clinical notes and histories by specialized personnel.

A genome sequencing system for universal newborn screening, diagnosis, and precision medicine for severe genetic diseases.

Newborn screening (NBS) dramatically improves outcomes in severe childhood disorders by treatment before symptom onset. In many genetic diseases, however, outcomes remain poor because NBS has lagged behind drug development. Rapid whole-genome sequencing (rWGS) is attractive for comprehensive NBS because it concomitantly examines almost all genetic diseases and is gaining acceptance for genetic disease diagnosis in ill newborns. We describe prototypic methods for scalable, parentally consented, feedback-informed NBS and diagnosis of genetic diseases by rWGS and virtual, acute management guidance (NBS-rWGS). Using established criteria and the Delphi method, we reviewed 457 genetic diseases for NBS-rWGS, retaining 388 (85%) with effective treatments. Simulated NBS-rWGS in 454,707 UK Biobank subjects with 29,865 pathogenic or likely pathogenic variants associated with 388 disorders had a true negative rate (specificity) of 99.7% following root cause analysis. In 2,208 critically ill children with suspected genetic disorders and 2,168 of their parents, simulated NBS-rWGS for 388 disorders identified 104 (87%) of 119 diagnoses previously made by rWGS and 15 findings not previously reported (NBS-rWGS negative predictive value 99.6%, true positive rate [sensitivity] 88.8%). Retrospective NBS-rWGS diagnosed 15 children with disorders that had been undetected by conventional NBS. In 43 of the 104 children, had NBS-rWGS-based interventions been started on day of life 5, the Delphi consensus was that symptoms could have been avoided completely in seven critically ill children, mostly in 21, and partially in 13. We invite groups worldwide to refine these NBS-rWGS conditions and join us to prospectively examine clinical utility and cost effectiveness.

Imaging-Based Machine Learning Analysis of Patient-Derived Tumor Organoid Drug Response.

Three-quarters of compounds that enter clinical trials fail to make it to market due to safety or efficacy concerns. This statistic strongly suggests a need for better screening methods that result in improved translatability of compounds during the preclinical testing period. Patient-derived organoids have been touted as a promising 3D preclinical model system to impact the drug discovery pipeline, particularly in oncology. However, assessing drug efficacy in such models poses its own set of challenges, and traditional cell viability readouts fail to leverage some of the advantages that the organoid systems provide. Consequently, phenotypically evaluating complex 3D cell culture models remains difficult due to intra- and inter-patient organoid size differences, cellular heterogeneities, and temporal response dynamics. Here, we present an image-based high-content assay that provides object level information on 3D patient-derived tumor organoids without the need for vital dyes. Leveraging computer vision, we segment and define organoids as independent regions of interest and obtain morphometric and textural information per organoid. By acquiring brightfield images at different timepoints in a robust, non-destructive manner, we can track the dynamic response of individual organoids to various drugs. Furthermore, to simplify the analysis of the resulting large, complex data files, we developed a web-based data visualization tool, the Organoizer, that is available for public use. Our work demonstrates the feasibility and utility of using imaging, computer vision and machine learning to determine the vital status of individual patient-derived organoids without relying upon vital dyes, thus taking advantage of the characteristics offered by this preclinical model system.