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The collection of data from a personal digital device to characterize current health conditions and behaviors that determine how an individual’s health will evolve has been called digital phenotyping. In this paper, we describe the development of and early experiences with a comprehensive digital phenotyping platform: Health Outcomes through Positive Engagement and Self-Empowerment (HOPES). HOPES is based on the open-source Beiwe platform but adds a wider range of data collection, including the integration of wearable devices and further sensor collection from smartphones. Requirements were partly derived from a concurrent clinical trial for schizophrenia that required the development of significant capabilities in HOPES for security, privacy, ease of use, and scalability, based on a careful combination of public cloud and on-premises operation. We describe new data pipelines to clean, process, present, and analyze data. This includes a set of dashboards customized to the needs of research study operations and clinical care. A test use case for HOPES was described by analyzing the digital behavior of 22 participants during the SARS-CoV-2 pandemic.

BackgroundThe radial artery pulse wave is a widely used physiological signal for disease diagnosis and personal health monitoring because it provides insight into the overall health of the heart and blood vessels. Periodic radial artery pulse signals are subsequently decomposed into single pulse wave periods (segments) for physiological parameter evaluations. However, abnormal periods frequently arise due to external interference, the inherent imperfections of current segmentation methods, and the quality of the pulse wave signals. ObjectiveThe objective of this paper was to develop a machine learning model to detect abnormal pulse periods in real clinical data. MethodsVarious machine learning models, such as k-nearest neighbor, logistic regression, and support vector machines, were applied to classify the normal and abnormal periods in 8561 segments extracted from the radial pulse waves of 390 outpatients. The recursive feature elimination method was used to simplify the classifier. ResultsIt was found that a logistic regression model with only four input features can achieve a satisfactory result. The area under the receiver operating characteristic curve from the test set was 0.9920. In addition, these classifiers can be easily interpreted. ConclusionsWe expect that this model can be applied in smart sport watches and watchbands to accurately evaluate human health status.

Vulvar squamous cell cancer (VSC) accounts for 90% of vulvar cancers. Next-generation sequencing studies of VSC imply human papillomavirus (HPV) and p53 status play separate roles in carcinogenesis and prognosis. We sought to describe the genomic landscape and analyze the immunologic profiles of VSC with respect to HPV and p53 status. A total of 443 VSC tumors underwent tumor profiling. Next-generation sequencing was performed on genomic DNA isolated from formalin-fixed paraffin-embedded tumor samples. PD-L1, microsatellite instability were tested by fragment analysis, IHC, and next-generation sequencing. Tumor mutational burden-high was defined as >10 mutations per MB. HPV 16/18 positive (HPV+) status was determined using whole exome sequencing on 105 samples. Three cohorts were identified from 105 samples with known HPV: HPV+, HPV-/p53wt, and HPV-/p53mt. Where HPV and p53 status were examined, TP53 mutations were exclusive of HPV+ tumors. In all, 37% of samples were HPV+. Among the 66 HPV- tumors, 52 (78.8%) were HPV-/p53mt and 14 (21.2%) were HPV-/p53wt. The HPV-/p53wt cohort had a higher rate of mutations in the PI3KCA gene (42.9% HPV-/p53wt vs 26.3% HPV+ vs. 5.8% HPV-/p53mt, q =0.028) and alterations in the PI3K/AkT/mTOR pathway (57.1% HPV-/p53wt vs. 34.2% HPV+ vs. 7.7% HPV-/p53mt, q =0.0386) than the other 2 cohorts. Ninety-eight VSC tumors with HPV16/18 information underwent transcriptomic analysis and immune deconvolution method. No differences were observed in immune profiles. The HPV-/p53wt VSC tumors had significantly higher rates of mutations in the PI3KCA gene and alterations in the PI3K/AkT/mTOR pathway, a potential target that merits further investigation in this subgroup.

This article gives an historical perspective of block scheduling as well as looking squarely at the advantages and disadvantages of it. It focuses on how block scheduling affects such things as school climate, staff morale, and most importantly student achievement. Results from surveys given to administrators and students utilizing block scheduling form the basis for discussing a number of the issues and problems generated by utilizing block scheduling. These issues include such things as the scheduling of students in classes to adjusting individual teaching styles to better meet the needs of learners in extended class periods.

The purpose of this study is to examine principals' perceptions of their roles as curriculum leaders in high, middle and elementary school levels. This study employs a qualitative design with direct personal interview technique to collect data. Principals from twenty-two high schools, twenty-four middle schools, and thirty-six elementary schools from five school districts in the Atlanta area participated in the study. The research instrument was researcher-constructed with reference to current literature of school curriculum leadership. Principals' responses were coded by categories of curriculum development, organization, implementation, evaluation, and improvement. Emerging themes and recurring patterns of principals' responses were observed. The findings show that principals' perceptions of their curriculum leadership roles had more in common than difference among school levels in all the categories of curriculum development, organization, implementation, evaluation, and improvement.