A Motivational Climate Intervention and Exercise-Related Outcomes: A Longitudinal Perspective

While researchers have suggested that the social context in exercise settings is linked to individuals’ physical activity motivation and potential exercise-related outcomes, few research designs have examined the nuance of those relationships. Moreover, interventions targeting the social context of exercise settings are sparse, so the potential impact of staff training on members’ motivation to exercise are not well known. Drawing from two major motivation theories, achievement goal perspective theory and self-determination theory, this study considered an intervention with fitness center staff from the members’ perspectives. Members completed a survey before and after an intervention designed to help staff create a high caring, task-involving, and low ego-involving motivational climate. Using a half-longitudinal structural equation model, participants’ perceptions of the motivational climate, basic psychological needs, exercise motivation, and exercise experiences (including commitment to exercise, life satisfaction, body image) were modeled pre-post intervention. The model revealed significant latent mean differences for post-intervention constructs, with participants experiencing a more positive motivational climate, higher competence and relatedness, intrinsic motivation, commitment, life satisfaction, and body image. The final mediation model demonstrated tenable fit, with perceptions of climate having significant, direct and indirect effects on commitment, life satisfaction, and body image. Our study supports that the motivational climate contributes to an optimal social context for exercise where basic psychological needs are nurtured, intrinsic motivation is fostered, and individuals experience well-being benefits, including increased life satisfaction. Further, short and targeted training meetings with fitness center staff can result in members’ perceiving a significant change in the motivational climate

Psychometric Properties of the Abbreviated Perceived Motivational Climate in Exercise Questionnaire

The purpose of this study was to develop an abbreviated version of the Perceived Motivational Climate in Exercise Questionnaire (PMCEQ-A) to provide a more practical instrument for use in applied exercise settings. In the calibration step, 2 shortened versions’ measurement and latent model values were compared to each other and the original PMCEQ using a 3-group CFA invariance testing approach with previously collected exercise setting data (N = 5,427). Based on the model fit and reliability values, the 12-item version performed better than the 17-item version. The resultant 12-item PMCEQ-A’s CFA model estimates were then compared to the PMCEQ’s model values for 2 different, previously conducted studies of exercise settings (N = 414 and 770). The more parsimonious 12-item PMCEQ-A can be used by exercise psychology researchers to gain insight into members’ perspectives on the motivational climate and may lead to developing effective strategies to enhance members’ experiences and commitment

Developing a Novel Image Marker to Predict the Responses of Neoadjuvant Chemotherapy (NACT) for Ovarian Cancer Patients

Objective: Neoadjuvant chemotherapy (NACT) is one kind of treatment for advanced stage ovarian cancer patients. However, due to the nature of tumor heterogeneity, the patients' responses to NACT varies significantly among different subgroups. To address this clinical challenge, the purpose of this study is to develop a novel image marker to achieve high accuracy response prediction of the NACT at an early stage. Methods: For this purpose, we first computed a total of 1373 radiomics features to quantify the tumor characteristics, which can be grouped into three categories: geometric, intensity, and texture features. Second, all these features were optimized by principal component analysis algorithm to generate a compact and informative feature cluster. Using this cluster as the input, an SVM based classifier was developed and optimized to create a final marker, indicating the likelihood of the patient being responsive to the NACT treatment. To validate this scheme, a total of 42 ovarian cancer patients were retrospectively collected. A nested leave-one-out cross-validation was adopted for model performance assessment. Results: The results demonstrate that the new method yielded an AUC (area under the ROC [receiver characteristic operation] curve) of 0.745. Meanwhile, the model achieved overall accuracy of 76.2%, positive predictive value of 70%, and negative predictive value of 78.1%. Conclusion: This study provides meaningful information for the development of radiomics based image markers in NACT response prediction

Evaluating the Effectiveness of 2D and 3D Features for Predicting Tumor Response to Chemotherapy

2D and 3D tumor features are widely used in a variety of medical image analysis tasks. However, for chemotherapy response prediction, the effectiveness between different kinds of 2D and 3D features are not comprehensively assessed, especially in ovarian cancer-related applications. This investigation aims to accomplish such a comprehensive evaluation. For this purpose, CT images were collected retrospectively from 188 advanced-stage ovarian cancer patients. All the metastatic tumors that occurred in each patient were segmented and then processed by a set of six filters. Next, three categories of features, namely geometric, density, and texture features, were calculated from both the filtered results and the original segmented tumors, generating a total of 1595 and 1403 features for the 3D and 2D tumors, respectively. In addition to the conventional single-slice 2D and full-volume 3D tumor features, we also computed the incomplete-3D tumor features, which were achieved by sequentially adding one individual CT slice and calculating the corresponding features. Support vector machine (SVM) based prediction models were developed and optimized for each feature set. 5-fold cross-validation was used to assess the performance of each individual model. The results show that the 2D feature-based model achieved an AUC (area under the ROC curve [receiver operating characteristic]) of 0.84+-0.02. When adding more slices, the AUC first increased to reach the maximum and then gradually decreased to 0.86+-0.02. The maximum AUC was yielded when adding two adjacent slices, with a value of 0.91+-0.01. This initial result provides meaningful information for optimizing machine learning-based decision-making support tools in the future

Standardization of Epidemiological Surveillance of Group A Streptococcal Impetigo

Impetigo is a highly contagious bacterial infection of the superficial layer of skin. Impetigo is caused by group A Streptococcus (Strep A) and Staphylococcus aureus, alone or in combination, with the former predominating in many tropical climates. Strep A impetigo occurs mainly in early childhood, and the burden varies worldwide. It is an acute, self-limited disease, but many children experience frequent recurrences that make it a chronic illness in some endemic settings. We present a standardized surveillance protocol including case definitions for impetigo including both active (purulent, crusted) and resolving (flat, dry) phases and discuss the current tests used to detect Strep A among persons with impetigo. Case classifications that can be applied are detailed, including differentiating between incident (new) and prevalent (existing) cases of Strep A impetigo. The type of surveillance methodology depends on the burden of impetigo in the community. Active surveillance and laboratory confirmation is the preferred method for case detection, particularly in endemic settings. Participant eligibility, surveillance population and additional considerations for surveillance of impetigo, including examination of lesions, use of photographs to document lesions, and staff training requirements (including cultural awareness), are addressed. Finally, the core elements of case report forms for impetigo are presented and guidance for recording the course and severity of impetigo provided

Standardization of epidemiological surveillance of group A streptococcal cellulitis

Cellulitis is an acute bacterial infection of the dermis and subcutaneous tissue usually found complicating a wound, ulcer, or dermatosis. This article provides guidelines for the surveillance of cellulitis. The primary objectives of cellulitis surveillance are to (1) monitor trends in rates of infection, (2) describe the demographic and clinical characteristics of patients with cellulitis, (3) estimate the frequency of complications, and (4) describe the risk factors associated with primary and recurrent cellulitis. This article includes case definitions for clinical cellulitis and group A streptococcal cellulitis, based on clinical and laboratory evidence, and case classifications for an initial and recurrent case. It is expected that surveillance for cellulitis will be for all-cause cellulitis, rather than specifically for Strep A cellulitis. Considerations of the type of surveillance are also presented, including identification of data sources and surveillance type. Minimal surveillance necessary for cellulitis is facility-based, passive surveillance. Prospective, active, facility-based surveillance is recommended for estimates of pathogen-specific cellulitis burden. Participant eligibility, surveillance population, and additional surveillance considerations such as active follow-up of cases, the use of International Classification of Disease diagnosis codes, and microbiological sampling of cases are discussed. Finally, the core data elements to be collected on case report forms are presented

Standardization of epidemiological surveillance of acute poststreptococcal glomerulonephritis

Acute poststreptococcal glomerulonephritis (APSGN) is an immune complex-induced glomerulonephritis that develops as a sequela of streptococcal infections. This article provides guidelines for the surveillance of APSGN due to group A Streptococcus (Strep A). The primary objectives of APSGN surveillance are to monitor trends in age- and sex-specific incidence, describe the demographic and clinical characteristics of patients with APSGN, document accompanying risk factors, then monitor trends in frequency of complications, illness duration, hospitalization rates, and mortality. This document provides surveillance case definitions for APSGN, including clinical and subclinical APSGN based on clinical and laboratory evidence. It also details case classifications that can be used to differentiate between confirmed and probable cases, and it discusses the current investigations used to provide evidence of antecedent Strep A infection. The type of surveillance recommended depends on the burden of APSGN in the community and the objectives of surveillance. Strategies for minimal surveillance and enhanced surveillance of APSGN are provided. Furthermore, a discussion covers the surveillance population and additional APSGN-specific surveillance considerations such as contact testing, active follow up of cases and contacts, frequency of reporting, surveillance visits, period of surveillance, and community engagement. Finally, the document presents core data elements to be collected on case report forms, along with guidance for documenting the course and severity of APSGN

Fetus-derived DLK1 is required for maternal metabolic adaptations to pregnancy and is associated with fetal growth restriction.

Pregnancy is a state of high metabolic demand. Fasting diverts metabolism to fatty acid oxidation, and the fasted response occurs much more rapidly in pregnant women than in non-pregnant women. The product of the imprinted DLK1 gene (delta-like homolog 1) is an endocrine signaling molecule that reaches a high concentration in the maternal circulation during late pregnancy. By using mouse models with deleted Dlk1, we show that the fetus is the source of maternal circulating DLK1. In the absence of fetally derived DLK1, the maternal fasting response is impaired. Furthermore, we found that maternal circulating DLK1 levels predict embryonic mass in mice and can differentiate healthy small-for-gestational-age (SGA) infants from pathologically small infants in a human cohort. Therefore, measurement of DLK1 concentration in maternal blood may be a valuable method for diagnosing human disorders associated with impaired DLK1 expression and to predict poor intrauterine growth and complications of pregnancy.M.A.M.C. was supported by a PhD studentship from the Cambridge Centre for Trophoblast Research. Research was supported by grants from the MRC (MR/J001597/1 and MR/L002345/1), the Medical College of Saint Bartholomew's Hospital Trust, a Wellcome Trust Investigator Award, EpigeneSys (FP7 Health-257082), EpiHealth (FP7 Health-278414), a Herchel Smith Fellowship (N.T.) and NIH grant RO1 DK89989. The contents are the authors' sole responsibility and do not necessarily represent official NIH views. We thank G. Burton for invaluable support, and M. Constância and I. Sandovici (University of Cambridge) for the Meox2-cre mice. We are extremely grateful to all of the participants in the Pregnancy Outcome Prediction study. This work was supported by the NIHR Cambridge Comprehensive Biomedical Research Centre (Women's Health theme) and project grants from the MRC (G1100221) and Sands (Stillbirth and Neonatal Death Charity). The study was also supported by GE Healthcare (donation of two Voluson i ultrasound systems for this study) and by the NIHR Cambridge Clinical Research Facility, where all research visits took place.This is the author accepted manuscript. The final version is available from Nature Publishing Group via https://doi.org/10.1038/ng.369