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Abstract Background There is considerable evidence that microRNAs (miRNAs) regulate several key tumor-associated genes/pathways and may themselves have a dual regulatory function either as tumor suppressors or oncogenic miRNA, depending on the tumor type. MicroRNA-590-3p (miR-590-3p) is a small non-coding RNA involved in the initiation and progression of numerous tumors. However, its expression pattern and biological role in hepatocellular carcinoma (HCC) are controversial. Results In the current work, computational and RT-qPCR analysis revealed that HCC tissues and cell lines exhibited miR-590-3p downregulation. Forced expression of miR-590-3p attenuated HepG2 cells proliferation, migration, and repressed EMT-related gene expression. Bioinformatic, RT-qPCR, and luciferase assays revealed that MDM2 is a direct functional target of miR-590-3p. Moreover, the knockdown of MDM2 mimicked the inhibitory effect of miR-590-3p in HepG2 cells. Conclusion We have identified not only novel targets for miR-590-3p in HCC, but also novel target genes for miR590-3p/MDM2 pathway in HCC like SNAIL, SLUG, ZEB1, ZEB2, and N-cadherin. Furthermore, these findings demonstrate a crucial role for MDM2 in the regulatory mechanism of EMT in HCC.

Importance: Safe integration of artificial intelligence (AI) into clinical settings often requires randomized clinical trials (RCT) to compare AI efficacy with conventional care. Diabetic retinopathy (DR) screening is at the forefront of clinical AI applications, marked by the first US Food and Drug Administration (FDA) De Novo authorization for an autonomous AI for such use., Objective: To determine the generalizability of the 7 ethical research principles for clinical trials endorsed by the National Institute of Health (NIH), and identify ethical concerns unique to clinical trials of AI., Design, Setting, and Participants: This qualitative study included semistructured interviews conducted with 11 investigators engaged in the design and implementation of clinical trials of AI for DR screening from November 11, 2022, to February 20, 2023. The study was a collaboration with the ACCESS (AI for Children's Diabetic Eye Exams) trial, the first clinical trial of autonomous AI in pediatrics. Participant recruitment initially utilized purposeful sampling, and later expanded with snowball sampling. Study methodology for analysis combined a deductive approach to explore investigators' perspectives of the 7 ethical principles for clinical research endorsed by the NIH and an inductive approach to uncover the broader ethical considerations implementing clinical trials of AI within care delivery., Results: A total of 11 participants (mean [SD] age, 47.5 [12.0] years; 7 male [64%], 4 female [36%]; 3 Asian [27%], 8 White [73%]) were included, with diverse expertise in ethics, ophthalmology, translational medicine, biostatistics, and AI development. Key themes revealed several ethical challenges unique to clinical trials of AI. These themes included difficulties in measuring social value, establishing scientific validity, ensuring fair participant selection, evaluating risk-benefit ratios across various patient subgroups, and addressing the complexities inherent in the data use terms of informed consent., Conclusions and Relevance: This qualitative study identified practical ethical challenges that investigators need to consider and negotiate when conducting AI clinical trials, exemplified by the DR screening use-case. These considerations call for further guidance on where to focus empirical and normative ethical efforts to best support conduct clinical trials of AI and minimize unintended harm to trial participants.

Given the potential benefits of artificial intelligence and machine learning (AI/ML) within healthcare, it is critical to consider how these technologies can be deployed in pediatric research and practice. Currently, healthcare AI/ML has not yet adapted to the specific technical considerations related to pediatric data nor adequately addressed the specific vulnerabilities of children and young people (CYP) in relation to AI. While the greatest burden of disease in CYP is firmly concentrated in lower and middle-income countries (LMICs), existing applied pediatric AI/ML efforts are concentrated in a small number of high-income countries (HICs). In LMICs, use-cases remain primarily in the proof-of-concept stage. This narrative review identifies a number of intersecting challenges that pose barriers to effective AI/ML for CYP globally and explores the shifts needed to make progress across multiple domains. Child-specific technical considerations throughout the AI/ML lifecycle have been largely overlooked thus far, yet these can be critical to model effectiveness. Governance concerns are paramount, with suitable national and international frameworks and guidance required to enable the safe and responsible deployment of advanced technologies impacting the care of CYP and using their data. An ambitious vision for child health demands that the potential benefits of AI/Ml are realized universally through greater international collaboration, capacity building, strong oversight, and ultimately diffusing the AI/ML locus of power to empower researchers and clinicians globally. In order that AI/ML systems that do not exacerbate inequalities in pediatric care, teams researching and developing these technologies in LMICs must ensure that AI/ML research is inclusive of the needs and concerns of CYP and their caregivers. A broad, interdisciplinary, and human-centered approach to AI/ML is essential for developing tools for healthcare workers delivering care, such that the creation and deployment of ML is grounded in local systems, cultures, and clinical practice. Decisions to invest in developing and testing pediatric AI/ML in resource-constrained settings must always be part of a broader evaluation of the overall needs of a healthcare system, considering the critical building blocks underpinning effective, sustainable, and cost-efficient healthcare delivery for CYP., Competing Interests: In addition to his academic role, JS is an employee of GSK (a private company) and holds shares in the GSK group of companies. LAC is the Editor-in-Chief of PLOS Digital Health., (Copyright: © 2024 Muralidharan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Importance: Limited sharing of data sets that accurately represent disease and patient diversity limits the generalizability of artificial intelligence (AI) algorithms in health care., Objective: To explore the factors associated with organizational motivation to share health data for AI development., Design, Setting, and Participants: This qualitative study investigated organizational readiness for sharing health data across the academic, governmental, nonprofit, and private sectors. Using a multiple case studies approach, 27 semistructured interviews were conducted with leaders in data-sharing roles from August 29, 2022, to January 9, 2023. The interviews were conducted in the English language using a video conferencing platform. Using a purposive and nonprobabilistic sampling strategy, 78 individuals across 52 unique organizations were identified. Of these, 35 participants were enrolled. Participant recruitment concluded after 27 interviews, as theoretical saturation was reached and no additional themes emerged., Main Outcome and Measure: Concepts defining organizational readiness for data sharing and the association between data-sharing factors and organizational behavior were mapped through iterative qualitative analysis to establish a framework defining organizational readiness for sharing clinical data for AI development., Results: Interviews included 27 leaders from 18 organizations (academia: 10, government: 7, nonprofit: 8, and private: 2). Organizational readiness for data sharing centered around 2 main constructs: motivation and capabilities. Motivation related to the alignment of an organization's values with data-sharing priorities and was associated with its engagement in data-sharing efforts. However, organizational motivation could be modulated by extrinsic incentives for financial or reputational gains. Organizational capabilities comprised infrastructure, people, expertise, and access to data. Cross-sector collaboration was a key strategy to mitigate barriers to access health data., Conclusions and Relevance: This qualitative study identified sector-specific factors that may affect the data-sharing behaviors of health organizations. External incentives may bolster cross-sector collaborations by helping overcome barriers to accessing health data for AI development. The findings suggest that tailored incentives may boost organizational motivation and facilitate sustainable flow of health data for AI development.

Importance: The lack of data quality frameworks to guide the development of artificial intelligence (AI)-ready data sets limits their usefulness for machine learning (ML) research in health care and hinders the diagnostic excellence of developed clinical AI applications for patient care., Objective: To discern what constitutes high-quality and useful data sets for health and biomedical ML research purposes according to subject matter experts., Design, Setting, and Participants: This qualitative study interviewed data set experts, particularly those who are creators and ML researchers. Semistructured interviews were conducted in English and remotely through a secure video conferencing platform between August 23, 2022, and January 5, 2023. A total of 93 experts were invited to participate. Twenty experts were enrolled and interviewed. Using purposive sampling, experts were affiliated with a diverse representation of 16 health data sets/databases across organizational sectors. Content analysis was used to evaluate survey information and thematic analysis was used to analyze interview data., Main Outcomes and Measures: Data set experts' perceptions on what makes data sets AI ready., Results: Participants included 20 data set experts (11 [55%] men; mean [SD] age, 42 [11] years), of whom all were health data set creators, and 18 of the 20 were also ML researchers. Themes (3 main and 11 subthemes) were identified and integrated into an AI-readiness framework to show their association within the health data ecosystem. Participants partially determined the AI readiness of data sets using priority appraisal elements of accuracy, completeness, consistency, and fitness. Ethical acquisition and societal impact emerged as appraisal considerations in that participant samples have not been described to date in prior data quality frameworks. Factors that drive creation of high-quality health data sets and mitigate risks associated with data reuse in ML research were also relevant to AI readiness. The state of data availability, data quality standards, documentation, team science, and incentivization were associated with elements of AI readiness and the overall perception of data set usefulness., Conclusions and Relevance: In this qualitative study of data set experts, participants contributed to the development of a grounded framework for AI data set quality. Data set AI readiness required the concerted appraisal of many elements and the balancing of transparency and ethical reflection against pragmatic constraints. The movement toward more reliable, relevant, and ethical AI and ML applications for patient care will inevitably require strategic updates to data set creation practices.

Background: Administrative data are generated when educating, licensing, and regulating future physicians but these data are rarely used beyond their pre-specified purposes. The capacity necessary for sensitive and responsive oversight that supports the sharing of administrative medical education data across institutions for research purposes needs to be developed., Method: A pan-Canadian consensus-building project was undertaken to develop agreement on the goals, benefits, risks, values, and principles that should underpin inter-institutional data-driven medical education research in Canada. A survey of key literature, consultations with various stakeholders and five successive knowledge synthesis workshops informed this project. Propositions were developed, driving subsequent discussions until collective agreement was distilled., Results: Consensus coalesced around six key principles: establishing clear purposes, rationale, and methodology for inter-institutional data-driven research a priori ; informed consent from data generators in education systems is non-negotiable; multi-institutional data sharing requires special governance; data governance should be guided by data sovereignty; data use should be guided by an identified set of shared values; and best practices in research data-management should be applied., Conclusion: We recommend establishing a representative governance body, engaging trusted data facility, and adherence to extant data management policies when sharing administrative medical education data for research purposes in Canada., Competing Interests: None., (© 2023 Grierson, Cavanagh, Youssef, Lee-Krueger, McNeill, Button, Kulasegaram; licensee Synergies Partners.)

Alopecia or hair loss is a widespread issue that has significant effects on personal well-being for both genders nationally and internationally. In addition, alopecia causes extreme emotional stress and negatively impacts the psychological health and self-esteem of cancer patients suffering from chemotherapy-induced alopecia. Unfortunately, available synthetic medications are costly, invasive, or have extreme adverse effects. On the contrary, natural and herbal hair loss products are widely available in the local and international markets in variable pharmaceutical forms with different mechanisms of action, namely, androgen antagonists, nutritional supplements, vasodilators, and 5 α -reductase inhibitors or dihydrotestosterone blockers. Thus, it is of great importance to encourage researchers to investigate these natural alternatives that can act as potent therapeutic agents having diverse mechanisms of action as well as limited side effects. Currently, natural remedies are considered a fast-rising pharmaceutical segment with demand from a wide range of consumers. In this study, we present a review of reported herbal remedies and herb combinations recommended for hair loss and their mode of action, along with an overview of available market products and formulations, their composition, and declared effects. In addition, a general outline of the different forms of alopecia, its causes, and recommended treatments are mentioned as well. This was all done with the aim of assisting further studies with developing standardized natural formulations for alopecia as many were found to lack standardization of their bioactive ingredients and efficiency confirmation.

Although most bariatric patients achieve significant weight loss and improvements in both physical and mental health-related quality of life (HRQoL) in the short-term, there is wide variability in weight and long-term HRQoL outcomes. The role of bariatric patients' self-management style in explaining variability in long-term outcomes is unclear. This qualitative study examined bariatric patients' self-management experiences after bariatric surgery in relation to long-term outcomes. A qualitative study was conducted using semi-structured individual interviews with post-surgery patients (n = 23) at a Canadian bariatric surgery program. A constant comparative approach was used to systematically analyse the data and identify overarching themes. Variation in patients' experiences and follow-up time were the two primary units of analysis. Patients were predominantly female (n = 19; 82.6%) and had a mean age of 50 ± 8.49 years. The median time post-surgery was 2 years (range: 6 months-7 years). Three distinct phases described the process of self-management post-bariatric surgery: (1) rediscovering self-esteem and confidence in one's ability to self-manage (1-month to 1.5-years post-surgery), (2) achieving weight maintenance and addressing emotion dysregulation (1.5-3-years post-surgery) and (3) embracing a flexible balanced lifestyle (beyond 3-years). Bariatric surgery patients experience distinct challenges relative to their post-surgery time course. Facilitating access to interprofessional bariatric care after surgery allowed patients to acquire the self-management knowledge and skills necessary to address challenges to following the bariatric guidelines in the long-term., (© 2021 World Obesity Federation.)

Background: The coronavirus disease 2019 (COVID-19) pandemic has had far reaching consequences on the health and well-being of the general public. Evidence from previous pandemics suggest that bariatric patients may experience increased emotional distress and difficulty adhering to healthy lifestyle changes post-surgery., Objective: We aimed to examine the impact of the novel COVID-19 public health crisis on bariatric patients' self-management post-surgery., Method: In a nested-qualitative study, semi-structured telephone interviews were conducted with 23 post-operative bariatric patients who had undergone Roux-en-Y gastric bypass (RYGB) at a Canadian Bariatric Surgery Program between 2014 and 2020. A constant comparative approach was used to systematically analyze the data and identify the overarching themes., Results: Participants (n = 23) had a mean age of (48.82 ± 10.03) years and most were female (n = 19). The median time post-surgery was 2 years (range: 6 months-7 years). Themes describing the impact of COVID-19 pandemic on patients' post-bariatric surgery self-management included: coping with COVID-19; vulnerability factors and physical isolation; resiliency factors during pandemic; and valuing access to support by virtual care. The need for patients to access post-operative bariatric care during COVID-19 differed based on gender and socioeconomic status., Conclusion: This study showed that the COVID-19 pandemic has impacted patients' ability to self-manage obesity and their mental health in a variety of ways. These findings suggest that patients may experience unique psychological distress and challenges requiring personalized care strategies to improve obesity self-care and overall well-being., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background: The COVID-19 pandemic has resulted in a number of negative health related consequences, including impacts on mental health. More than 22% of Canadians reported that they had felt depressed in the last week, in response to a December 2020 national survey. Given the need to physically distance during the pandemic, and the increase in demand for mental health services, digital interventions that support mental health and wellness may be beneficial., Objective: The purpose of this research was to identify digital interventions that could be used to support the mental health of the Canadian general population during the COVID-19 pandemic. The objectives were to identify (1) the populations these interventions were developed for, inclusive of exploring areas of equity such as socioeconomic status, sex/gender, race/ethnicity and culture, and relevance to Indigenous peoples and communities; (2) the effect of the interventions; and (3) any barriers or facilitators to the use of the intervention., Methods: This study was completed using a Cochrane Rapid Review methodology. A search of Embase, PsycInfo, Medline, and Web of Science, along with Google, Million Short, and popular mobile app libraries, was conducted. Two screeners were involved in applying inclusion criteria using Covidence software. Academic articles and mobile apps identified were screened using the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields resource, the American Psychiatric Association App Evaluation Framework, and the Mental Health Commission of Canada's guidance on app assessment and selection., Results: A total of 31 mobile apps and 114 web-based resources (eg, telemedicine, virtual peer support groups, discussion forums, etc) that could be used to support the mental health of the Canadian population during the pandemic were identified. These resources have been listed on a publicly available website along with search tags that may help an individual make a suitable selection. Variability exists in the populations that the interventions were developed for, and little assessment has been done with regard to areas of equity. The effect of the interventions was not reported for all those identified in this synthesis; however, for those that did report the effect, it was shown that they were effective in the context that they were used. A number of barriers and facilitators to using these interventions were identified, such as access, cost, and connectivity., Conclusions: A number of digital interventions that could support population mental health in Canada during the global COVID-19 pandemic were identified, indicating that individuals have several options to choose from. These interventions vary in their purpose, approach, design, cost, and targeted user group. While some research and digital interventions addressed equity-related considerations, more research and focused attention should be given to this area., (©Gillian Strudwick, Sanjeev Sockalingam, Iman Kassam, Lydia Sequeira, Sarah Bonato, Alaa Youssef, Rohan Mehta, Nadia Green, Branka Agic, Sophie Soklaridis, Danielle Impey, David Wiljer, Allison Crawford. Originally published in JMIR Mental Health (http://mental.jmir.org), 02.03.2021.)

Background: While bariatric surgery has proven to be effective to achieve significant weight loss and short-term improvements in both physical and mental (HRQoL), little is known about the factors associated with long-term decline in mental HRQoL after bariatric surgery., Objective: To examine differences in physical and mental HRQoL trajectories in a bariatric patient population 3 years after bariatric surgery and examine associated sociodemographic, weight, and mental health factors., Setting: A Canadian academic bariatric care center., Methods: A group-based trajectory model was used to examine physical and mental HRQoL trajectories 3 years after bariatric surgery. In a prospective cohort bariatric sample (n = 2270), demographic factors, body mass index, binge eating symptoms, anxiety symptoms (Generalized Anxiety Disorder-7), depressive symptoms (Patient Health Questionnaire-9), and physical and mental HRQoL (Short-form health survey-36 (SF-36)), were measured at baseline, 6 months, 1, 2, and 3 years respectively. The effect of time-varying covariates (body mass index, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7) were investigated to examine effects on physical and mental HRQoL trajectories., Results: Five distinct trajectories described changes in (n = 1939 of 2270) individuals' physical HRQoL outcomes (SF-36-physical health component summary score) and five other trajectories described changes in mental HRQoL (SF-36-mental health component summary score) outcomes from baseline to 3 years postsurgery. The group-based distribution for the 5 physical HRQoL trajectories were as follows: (1) low baseline-stable low (5.8%); (2) low baseline-moderate rise (12%); (3) low baseline-stable high (41.1%); (4) high baseline-stable high (33.2%); and (5) moderate baseline-decline (7.9%). The 5 mental HRQoL trajectories were as follows: (1) low baseline-slow decline (10%); (2) low baseline-stable high (25%); (3) high baseline-unstable rise (12%); (4) high baseline-stable high (48.9%); and (5) high baseline-transient decline (4.1%). Compared with physical HRQoL, mental HRQoL trajectories were not associated with changes in body mass index, yet strongly correlated with changes in binge eating symptoms, Generalized Anxiety Disorder-7, and Patient Health Questionnaire measures at all time points., Conclusion: This study demonstrates distinct patterns in physical and mental HRQoL trajectories after bariatric surgery. The decline in mental HRQoL trajectories was more heterogeneous and associated with several psychosocial predictors that may be useful to guide risk prediction of long-term physical and mental HRQoL outcomes postbariatric surgery., (Copyright © 2020 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.)

Objective: The aim of this study is to examine patients' experiences in integrated care (IC) settings., Design: Qualitative study using semistructured interviews., Settings: Two IC sites in Toronto, Canada: (1) a community-based primary healthcare centre, supporting patients with hepatitis C and comorbid mental health and substance use issues; and (2) an integrated bariatric surgery programme, an academic tertiary care centre., Participants: The study included patients (n=12) with co-occurring mental and physical health conditions. Seven participants (58%) were female and five (42%) were male., Methods: Twelve indepth semistructured interviews were conducted with a purposeful sample of patients (n=12) with comorbid mental and physical conditions at two IC sites in Toronto between 2017 and 2018. Data were collected and analysed using grounded theory approach., Results: Four themes emerged in our analysis reflecting patients' perspectives on patient-centred care experience in IC: (1) caring about me; (2) collaborating with me; (3) helping me understand and self-manage my care; and (4) personalising care to address my needs. Patients' experiences of care were primarily shaped by quality of relational interactions with IC team members. Positive interactions with IC team members led to enhanced patient access to care and fostered personalising care plans to address unique needs., Conclusion: This study adds to the literature on creating patient-centredness in IC settings by highlighting the importance of recognising patients' unique needs and the context of care for the specific patient population., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: Despite the established clinical and cost-effectiveness of integrated care (IC) models for patients with comorbid mental and physical illness, little is known about whether these models facilitate a better care experience from the patient's perspective. The authors conducted a scoping review of the literature to explore how IC influences patients' care experiences., Methods: MEDLINE, EMBASE, PSYC INFO CINAHL, AMED, the Cochrane Library, and grey literature were searched to identify relevant articles. Eligible studies were systematically reviewed and analyzed, using thematic analysis approach, to identify patterns, trends, and variation in patient experience within IC settings., Results: Search results yielded 5250 unique resources of which 21 primary studies met our eligibility criteria for analysis. Findings from this scoping review revealed variation in patients' experiences in IC settings. IC models enhanced patients' experience by creating theraputic spaces: improving patient access to care, developing collaborative relationships, and personalizing patient care to address individual needs., Conclusion: Productive interactions with care team were key to improve patient engagement and experience of centeredness in IC settings. Successful implementation of IC demanded purposeful alignment of IC structural components and care processes to create therapeutic spaces that address patient care needs and preferences., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Introduction: Practice data can inform the selection of educational strategies; however, it is not widely used, even when available. This study's purpose was to determine factors that influence physician engagement with practice data to advance competence and drive practice change., Methods: A practice-based, pan-Canadian survey was administered to three physician subspecialties: psychiatrists (Psy), radiation oncologists (RO), and general surgeons (GS). The survey was distributed through national specialty society membership lists. The survey assessed factors that influence the use of data for practice improvement and orientation to lifelong learning, using the Jefferson Scale of Physician Lifelong Learning (JeffSPLL). Linear regression was used to model the relationship between the outcome variable frequency of data use and independent predictors of continuous learning to improving practice., Results: A total of 305 practicing physicians (Psy = 203, RO = 53, GS = 49) participated in this study. Most respondents used data for practice improvement (n = 177, 61.7%; Psy = 115, 40.1%; RO = 35; 12.2%; GS = 27, 9.4%) and had high orientation to lifelong learning (JeffSPLL mean scores: Psy = 47.4; RO = 43.5; GS = 45.1; Max = 56). Linear regression analysis identified significant predictors of data use in practice being: frequency of assessing learning needs, helpfulness of data to improve practice, and frequency to develop learning plans. Together, these predictors explained 42.9% of the variance in physicians' orientation toward integrating accessible data into practice (R = 0.426, P < .001)., Discussion: This study demonstrates an association between practice data use and perceived data utility, reflection on learning needs and learning plan development. Implications for this work include process development for data-informed action planning for practice improvement for physicians.

Hypericin (HY) is a naturally-occurring, potent photosensitizer. However, its lipophilicity limits its therapeutic applications. Our attempt is, thus, to develop a biodegradable nanocarrier for hypericin capable of preserving its antibacterial photoactivity. Amphiphilic block copolymers were synthesized to prepare hypericin-laden nanoparticles (HY-NPs). The antimicrobial photoactivity of HY-NPs was assessed; in vitro against biofilm and planktonic cells of methicillin resistant Staphylococcus aureus (MRSA) clinical isolates and in vivo on infected wounds in rats. Nanoparticles of 45 nm in diameter ensured higher amounts of reactive oxygen species upon irradiation. HY-NPs demonstrated superior inhibition of biofilm over planktonic cells. In vivo wound healing studies in rats revealed faster healing, better epithelialization, keratinization and development of collagen fibers when HY-NPs were applied. Determination of growth factors and inflammatory mediators in the wound area confirmed superior healing potential of nanoencapsulated hypericin suggesting that hypericin can join the era of antibiotic-free antimicrobial therapy., (Copyright © 2013 Elsevier B.V. All rights reserved.)