View source for Interleukin27 stimulates autophagy throughout individual seruminduced principal macrophages with an mTOR and LC3independent path

RESULTS The results demonstrated that suicide attempters showed a significantly higher level of suicidal ideation (t563.64=5.04; P less then .001; two-tailed) and more suicide-related social media use behaviors, which included attending to suicide information (t567=1.94; P=.05; two-tailed), commenting on or reposting suicide information (t567=2.12; P=.03; two-tailed), or talking about suicide (t542.22=5.12; P less then .001; two-tailed). Suicidal ideation also affected suicide attempts through the mediational chains. CONCLUSIONS Our findings thus support the social cognitive theory, and there are implications for population-based suicide prevention that can be achieved by identifying behavioral signals. ©Xingyun Liu, Jiasheng Huang, Nancy Xiaonan Yu, Qing Li, Tingshao Zhu. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 28.04.2020.BACKGROUND Poor discharge preparation during hospitalization may lead to adverse events after discharge. Checklists and videos that systematically engage patients in preparing for discharge have the potential to improve safety, especially when integrated into clinician workflow via the electronic health record (EHR). OBJECTIVE This study aims to evaluate the implementation of a suite of digital health tools integrated with the EHR to engage hospitalized patients, caregivers, and their care team in preparing for discharge. METHODS We used the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework to identify pertinent research questions related to implementation. We iteratively refined patient and clinician-facing intervention components using a participatory process involving end users and institutional stakeholders. The intervention was implemented at a large academic medical center from December 2017 to July 2018. Patients who agreed to participate were coached to watch a discharntation. We offer strategies to address implementation barriers and promote adoption of these tools. TRIAL REGISTRATION ClinicalTrials.gov NCT03116074; https//clinicaltrials.gov/ct2/show/NCT03116074. ©Theresa E Fuller, Denise D Pong, Nicholas Piniella, Michael Pardo, Nathaniel Bessa, Catherine Yoon, Robert B Boxer, Jeffrey Lawrence Schnipper, Anuj K Dalal. [https://www.selleckchem.com/products/vazegepant-hydrochloride.html Selleck Vazegepant] Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 28.04.2020.BACKGROUND Combination therapy plays an important role in the effective treatment of malignant neoplasms and precision medicine. Numerous clinical studies have been carried out to investigate combination drug therapies. Automated knowledge discovery of these combinations and their graphic representation in knowledge graphs will enable pattern recognition and identification of drug combinations used to treat a specific type of cancer, improve drug efficacy and treatment of human disorders. OBJECTIVE This paper aims to develop an automated, visual approach to discover knowledge about combination therapies from biomedical literature, especially from those studies with high-level evidence such as clinical trial reports and clinical practice guidelines. METHODS Based on semantic predications, which consist of a triple structure of subject-predicate-object (SPO), we proposed an automated algorithm to discover knowledge of combination drug therapies using the following rules 1) two or more semantic predications (S1-take full advantage of the identified markers and other contextual features. ©Jian Du, Xiaoying Li. Originally published in JMIR Medical Informatics (http//medinform.jmir.org), 28.04.2020.BACKGROUND In primary care, patients play a crucial role in managing care processes and handling drug treatment. A decisive factor for success is their health literacy, and several interventions have been introduced to support patients in fulfilling their responsibility. OBJECTIVE The aim of this study is to assess the influence of such an intervention (ie, a medication module) within a patient-led electronic health record on patients' health literacy. METHODS We conducted a randomized controlled study among community-dwelling patients with type 2 diabetes mellitus. Patients were recruited from primary care practices. After randomization, patients either had access to an internet-based medication module allowing them to store their medication information, look up drug information, and print a medication schedule (intervention group), or they received an information brochure on the importance of medication schedules (control group). After 4-8 weeks, all patients were invited to attend a structured medication rto the protocol and dropout of 29 patients) and the actual interaction with the medication module was modest (ie, dropout of 9 patients). CONCLUSIONS The conduct of this randomized controlled study was challenging, leaving it open whether inadequate implementation, too short of a duration, or insufficient efficacy of the intervention, as such, contributed to the null effect of this study. This clearly outlines the value of piloting complex interventions and the accompanying process evaluations. ©Hanna Marita Seidling, Cornelia Mahler, Beate Strauß, Aline Weis, Marion Stützle, Johannes Krisam, INFOPAT P4/P5 Study Team, Joachim Szecsenyi, Walter Emil Haefeli. Originally published in JMIR Formative Research (http//formative.jmir.org), 28.04.2020.BACKGROUND Blended Web-based and face-to-face treatment is a promising electronic health service because it is expected that in a blended treatment the strengths of one mode of delivery will compensate for the weaknesses of the other. OBJECTIVE The aim of this study was to explore this expectation by examining the patients' user experience (UX) in a blended smoking cessation treatment (BSCT) in routine care. METHODS Patients' UX was collected by in-depth interviews (n=10) at an outpatient smoking cessation clinic in the Netherlands. Content analysis of the semantic domains was used to analyze the patients' UX. For the description of the UX, Hassenzahl's UX model was applied, examining the 4 of the 5 key elements of UX that form the UX from a user's perspective (1) standards and expectations, (2) apparent character (pragmatic and hedonic attributes), (3) usage situation, and (4) consequences (appeal, emotions, and behavior). RESULTS BSCT appeared to be a mostly positively experienced service. Patients had a positive-pragmatic standard and neutral-open expectation toward BSCT at the treatment start.