Notes

Controls working brings about sex-specific effects upon Western diet-associated sugar homeostasis as well as brain blood insulin signaling with out altering food-related impulsive option.
Digital technologies such as smartphones are transforming the way scientists conduct biomedical research. Several remotely conducted studies have recruited thousands of participants over a span of a few months allowing researchers to collect real-world data at scale and at a fraction of the cost of traditional research. Unfortunately, remote studies have been hampered by substantial participant attrition, calling into question the representativeness of the collected data including generalizability of outcomes. We report the findings regarding recruitment and retention from eight remote digital health studies conducted between 2014-2019 that provided individual-level study-app usage data from more than 100,000 participants completing nearly 3.5 million remote health evaluations over cumulative participation of 850,000 days. Median participant retention across eight studies varied widely from 2-26 days (median across all studies = 5.5 days). Survival analysis revealed several factors significantly associated with increase in participant retention time, including (i) referral by a clinician to the study (increase of 40 days in median retention time); (ii) compensation for participation (increase of 22 days, 1 study); (iii) having the clinical condition of interest in the study (increase of 7 days compared with controls); and (iv) older age (increase of 4 days). Additionally, four distinct patterns of daily app usage behavior were identified by unsupervised clustering, which were also associated with participant demographics. Most studies were not able to recruit a sample that was representative of the race/ethnicity or geographical diversity of the US. Together these findings can help inform recruitment and retention strategies to enable equitable participation of populations in future digital health research. © The Author(s) 2020.Accessibility of evidence-based behavioral health interventions is one of the main challenges in health care and effective treatment approaches are not always available for patients that would benefit from them. Digitization has dramatically changed the health care landscape. TI17 in vitro Although mHealth has shown promise in addressing issues of accessibility and reach, there is vast room for improvements. The integration of technical innovations and theory driven development is a key concern. Digital solutions developed by industry alone often lack a clear theoretical framework and the solutions are not properly evaluated to meet the standards of scientifically proven efficacy. On the other hand, mHealth interventions developed in academia may be theory driven but lack user friendliness and are commonly technically outdated by the time they are implemented in regular care, if they ever are. In an ongoing project aimed at scientific innovation, the mHealth Agile Development and Evaluation Lifecycle was used to combine strengths from both industry and academia in the development of ACTsmart - a smartphone-based Acceptance and Commitment Therapy treatment for adult chronic pain patients. The present study describes the early development of ACTsmart, in the process of moving the product from alpha testing to a clinical trial ready solution. © The Author(s) 2020.Mechano-acoustic signals emanating from the heart and lungs contain valuable information about the cardiopulmonary system. Unobtrusive wearable sensors capable of monitoring these signals longitudinally can detect early pathological signatures and titrate care accordingly. Here, we present a wearable, hermetically-sealed high-precision vibration sensor that combines the characteristics of an accelerometer and a contact microphone to acquire wideband mechano-acoustic physiological signals, and enable simultaneous monitoring of multiple health factors associated with the cardiopulmonary system including heart and respiratory rate, heart sounds, lung sounds, and body motion and position of an individual. The encapsulated accelerometer contact microphone (ACM) utilizes nano-gap transducers to achieve extraordinary sensitivity in a wide bandwidth (DC-12 kHz) with high dynamic range. The sensors were used to obtain health factors of six control subjects with varying body mass index, and their feasibility in detection of weak mechano-acoustic signals such as pathological heart sounds and shallow breathing patterns is evaluated on patients with preexisting conditions. © The Author(s) 2020.Recently, super-enhancers (SEs) have been identified as a unique type of transcriptional regulation involved in cancer development. SEs exhibit a size, high transcription factor density, and strong binding to the transcriptional machinery compared with typical enhancers. SEs play an essential role in cell growth, differentiation, and disease initiation and progression including tumorigenesis. In particular, cancer-specific SEs have been proven to be key oncogenic drivers types of tumor cells. Furthermore, it has been confirmed that cancer-specific SEs can mediate the dysregulation of signaling pathways and promote cancer cell growth. Additionally, therapeutic strategies directly targeting SE components, for example, by disrupting SE structure or inhibiting SE cofactors, have shown a good curative effect on various cancers. © The Author(s) 2020.Background The shift in the medical education system from a time-based to a competency-based model has encouraged its adoption and application in competency-based education in anatomy classrooms, such as team-based learning models and flipped classroom models. This pilot study aimed to build on previous work of the linkages between anatomy-based learning (a flipped classroom model inspired by a modified team-based learning) and student learning and engagement, and further to assess the linkage between anatomy-based learning and academic performance. Methods A sequential mixed-methods design was employed to first gather and analyse quantitative data, including confidential student first semester scores in anatomy gender, stream, anatomy-based learning, and final anatomy overall mark. The quantitative phase was followed by a qualitative phase in which a series of 8 anatomy laboratories were observed (4 anatomy-based learning and 4 traditional). Thematic analysis was performed on the observation data. Results Aggregate anatomy-based learning and traditional stream tests, and final unit scores were compared.
Homepage: https://www.selleckchem.com/products/ti17.html