Using individual growth model to analyze the change in quality of life from adolescence to adulthood

BACKGROUND: The individual growth model is a relatively new statistical technique now widely used to examine the unique trajectories of individuals and groups in repeated measures data. This technique is increasingly used to analyze the changes over time in quality of life (QOL) data. This study examines the change from adolescence to adulthood in physical health as an aspect of QOL as an illustration of the use of this analytic method. METHODS: Employing data from the Children in the Community (CIC) study, a prospective longitudinal investigation, physical health was assessed at mean ages 16, 22, and 33 in 752 persons born between 1965 and 1975. RESULTS: The analyses using individual growth models show a linear decline in average physical health from age 10 to age 40. Males reported better physical health and declined less per year on average. Time-varying psychiatric disorders accounted for 8.6% of the explained variation in mean physical health, and 6.7% of the explained variation in linear change in physical health. Those with such a disorder reported lower mean physical health and a more rapid decline with age than those without a current psychiatric disorder. The use of SAS PROC MIXED, including syntax and interpretation of output are provided. Applications of these models including statistical assumptions, centering issues and cohort effects are discussed. CONCLUSION: This paper highlights the usefulness of the individual growth model in modeling longitudinal change in QOL variables

KD_ConvNeXt: knowledge distillation-based image classification of lung tumor surgical specimen sections

Introduction: Lung cancer is currently among the most prevalent and lethal cancers in the world in terms of incidence and fatality rates. In clinical practice, identifying the specific subtypes of lung cancer is essential in diagnosing and treating lung lesions.Methods: This paper aims to collect histopathological section images of lung tumor surgical specimens to construct a clinical dataset for researching and addressing the classification problem of specific subtypes of lung tumors. Our method proposes a teacher-student network architecture based on a knowledge distillation mechanism for the specific subtype classification of lung tumor histopathological section images to assist clinical applications, namely KD_ConvNeXt. The proposed approach enables the student network (ConvNeXt) to extract knowledge from the intermediate feature layers of the teacher network (Swin Transformer), improving the feature extraction and fitting capabilities of ConvNeXt. Meanwhile, Swin Transformer provides soft labels containing information about the distribution of images in various categories, making the model focused more on the information carried by types with smaller sample sizes while training.Results: This work has designed many experiments on a clinical lung tumor image dataset, and the KD_ConvNeXt achieved a superior classification accuracy of 85.64% and an F1-score of 0.7717 compared with other advanced image classification method

Associations of prenatal maternal depressive symptoms with cord blood glucocorticoids and child hair cortisol levels in the project viva and the generation R cohorts:a prospective cohort study

Background: Prior studies have reported conflicting results regarding the association of prenatal maternal depression with offspring cortisol levels. We examined associations of high levels of prenatal depressive symptoms with child cortisol biomarkers. Methods:In Project Viva (n = 925, Massachusetts USA), mothers reported their depressive symptoms using the Edinburgh Postnatal Depression Scale (EPDS) during pregnancy, cord blood glucocorticoids were measured at delivery, and child hair cortisol levels were measured in mid-childhood (mean (SD) age: 7.8 (0.8) years) and early adolescence (mean (SD) age: 13.2 (0.9) years). In the Generation R Study (n = 1644, Rotterdam, The Netherlands), mothers reported depressive symptoms using the Brief Symptom Inventory (BSI) during pregnancy, and child hair cortisol was measured at a mean (SD) age of 6.0 (0.5) years. We used cutoffs of ≥ 13 for the EPDS and &gt; 0.75 for the BSI to indicate high levels of prenatal depressive symptoms. We used multivariable linear regression models adjusted for child sex and age (at outcome), and maternal pre-pregnancy BMI, education, social support from friends/family, pregnancy smoking status, marital status, and household income to assess associations separately in each cohort. We also meta-analyzed childhood hair cortisol results from both cohorts. Results: 8.0% and 5.1% of women respectively experienced high levels of prenatal depressive symptoms in Project Viva and the Generation R Study. We found no associations between high levels of maternal depressive symptoms during pregnancy and child cortisol biomarkers in either cohort. Conclusions: The present study does not find support for the direct link between high levels of maternal depressive symptoms and offspring cortisol levels.</p

The 25(OH)D/PTH Threshold in Black Women

Context: Black women have lower 25-hydroxyvitamin D [25(OH)D] and higher PTH than white women. Recent evidence implicates PTH in adverse cardiovascular outcomes

Study on Material Properties of Magnesium Oxide Carbonized Prestressed Pipe Piles

Traditional PHC pipe pile in foundation engineering consumes high energy and has insufficient durability. A magnesium oxide carbonization test block is a new type of environmental protection block which bases on activated magnesium oxide cementation technology. The use of CO2 carbonation technology allows reactive magnesia to react to form basic magnesium carbonate to increase the compressive strength and durability of the block. Three kinds of different magnesium oxide powders were subjected to pressure test and determined the key technical parameters, such as optimal raw materials, sample preparation methods, carbonization environment and technology, and optimized design of pipe pile concrete material system