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A cyclin-dependent kinase 4/6 (CDK4/6) inhibitor combined with endocrine therapy is the standard-of-care for patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative advanced breast cancer. However, not all patients respond to the treatment, resistance often occurs and efficacy outcomes from early breast cancer trials have been mixed. To identify biomarkers associated with CDK4/6 inhibitor response or resistance, we combined bioinformatic-database analyses, artificial intelligence-assisted literature review, and manual literature review (Embase and OVID Medline; search window: January 2012–October 2022) to compile data to comprehensively describe the CDK4/6 inhibitor biomarker landscape. Based on these results, and validation by external experts, we identified 15 biomarkers of clinical importance (AR,AURKA, ERBB2, ESR1, CCNE1, CDKN1A/B, CDK2, CDK6, CDK7, CDK9, FGFR1/2, MYC, PIK3CA/AKT, RB1 and STAT3) that could guide future breast cancer research. Plain Language Summary Finding treatment targets in breast cancer using bioinformatics and artificial intelligence: Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) advanced breast cancer is the most common type of breast cancer. This type of breast cancer responds to hormones like estrogen or progesterone. Inhibitors of cyclin-dependent kinase 4/6 (CDK4/6) reduce the action of hormones. These CDK4/6 inhibitors in combination with other therapies are used to treat HR+/HER2- advanced breast cancer. CDK4/6 inhibitors slow or stop cancer growth in many patients with HR+/HER2- breast cancer. However, in some cases, the drug is not effective or stops working early on in treatment. Finding ways to predict how well and how long these patients will respond to CDK4/6 inhibitors is important for doctors when planning treatment. We used artificial intelligence to search databases and research articles to identify molecules in cancer cells that may predict how well CDK4/6 inhibitors will slow cancer growth. Many molecules were identified that might predict how well CDK4/6 inhibitors will work in people with advanced breast cancer. These types of molecules are called biomarkers. Experts reviewed the findings of the search and based on the evidence, selected 15 biomarkers that may be useful for predicting how well CDK4/6 inhibitors will slow cancer growth. The findings of this study can be used to guide future breast cancer research and help discover new treatments for people with HR+/HER2- advanced breast cancer. Article highlights Introduction CDK4/6 inhibitors in combination with endocrine therapy are the standard-of-care for patients with HR+/HER2 – ABC, but not all patients respond to these drugs, and many become resistant to CDK4/6 inhibitor treatment over time. Identifying biomarkers of response or resistance to CDK4/6 inhibitors may inform the selection of the most appropriate treatment for patients and drive the development of new therapies. Aim This review aimed to identify clinically relevant biomarkers for assessing CDK4/6 inhibitor response or resistance using bioinformatic database analyses, AI-assisted literature review and manual compilation of data to map the current CDK4/6 inhibitor biomarker landscape in HR+/HER2- ABC. Findings Our analyses identified 876 biomarkers with known functions that were potentially related to CDK4/6 inhibitor response in breast cancer; 15 biomarkers were prioritized as potential targets for informing patient treatment decisions and future drug development Most of the identified biomarkers are either currently being investigated in preclinical studies, in clinical trials or are already targeted by US FDA approved drugs Conclusion & future perspective By using a range of computational approaches, we were able to explore multiple bioinformatic databases and review a vast amount of literature, providing robust support for the key biomarkers identified. This information may help inform the development of future clinical trials and provide direction for the development of new therapies to treat advanced breast cancer. [ABSTRACT FROM AUTHOR]

With the rapid adoption of telemedicine since the COVID-19 pandemic, it has become imperative to teach and evaluate health professional trainees on skills important to conducting effective virtual visits. We developed a simulation-based workshop with (1) readings, (2) a lecture covering online communication and the virtual head and neck exam, (3) a telemedicine simulation with a standardized patient observed by faculty, (4) personalized feedback from faculty, and (5) a group debrief session. We created an evaluation rubric based on three of 20 Association of American Medical Colleges (AAMC) telemedicine competencies to assess learner performance during the simulations. Students (medical and physician assistant students; n = 50), and internal medicine residents (n = 20) completed this workshop in 2023. At least 90% of trainees across the two groups were rated as approaching entrustment or entrustable in each competency. This workshop is an example of a scalable telemedicine curriculum that can be used to teach and evaluate learners in the virtual physical exam across the training continuum. [ABSTRACT FROM AUTHOR]

Given the importance of telemedicine in improving healthcare access for underserved patients, professional students need experience using virtual clinical workflows. We developed an educational workshop with (1) readings, (2) a knowledge assessment test, (3) dermatology and teledermatology lectures, (5) a telemedicine simulation with a standardized patient, and (6) a debriefing session. The simulation included a "hybrid" workflow with live videoconferencing and store-and-forward image review. We measured student performance using three American Association of Medical Colleges (AAMC) Telemedicine Competencies for medical education. Ninety-eight medical and physician assistant students completed this workshop between 2021 and 2022, and 80% were entrustable or approaching entrustment in each competency. Some students struggled with data collection and technology use. Our results suggest that this workshop offers a practical and generalizable way to teach about multiple virtual workflows and strengthen students' telemedicine competencies. [ABSTRACT FROM AUTHOR]

While medication reconciliation is necessary to reduce errors, it is often challenging to gather an accurate history in the clinic. Telemedicine offers a relative advantage over clinic and hospital-based interviews by enabling the clinician to inspect the home environment, review pill bottles, and identify social determinants affecting adherence, such as financial instability. To be effective, however, clinicians must be trained in best-practice interview methods and the proper use of telemedicine. There is very little information in the literature describing the best strategies for teaching students or measuring competencies in telemedicine. Therefore, we created an educational module with a telemedicine simulation and an evaluation rubric. We piloted this module with 48 medical and physician assistant students. Most students could complete a virtual interview and gather a medication history. However, only half identified an over-the-counter medication missing from the list. Most students were either entrustable or approaching entrustment in the six telemedicine competencies measured in this simulation. This simulation is valuable for teaching students about medication reconciliation, using telemedicine to close gaps in access to care, and identifying health-related social needs affecting medication adherence. [ABSTRACT FROM AUTHOR]

Technology failures in telehealth are common, and clinicians need the skills to diagnose and manage them at the point of care. However, there are issues beyond technology failures mediating the effective use of telehealth. We must teach best-practice procedures for conducting telemedicine visits and include in instructional simulations commonly encountered failure modes so students can build their skills. To this end, we recruited medical students to conduct a Healthcare Failure Modes and Effects Analysis (HFMEA) to predict failures in telemedicine, their potential causes, and the consequences to develop and teach prevention strategies. Sixteen students observed telehealth appointments independently. Based on their observations, we identified four categories of failures in telemedicine: technical issues, patient safety, communication, and social and structural determinants. We proposed a normalized workflow that included management and prevention strategies. Our findings can inform the creation of new curricula. [ABSTRACT FROM AUTHOR]

While there is a global desire to increase digital health capacity, digital health should transform health services delivery rather than simply automate – or worse – replicate existing practices. Failing to capitalize on this transformative potential misses an opportunity to engage patients and other users to provide a more person-centered experience. However, digital transformation done recklessly can disrupt workflow, alienate users, and jeopardize patient safety, as we have observed with implementation of many digital health tools. This paper uses a telemedicine example to provide insight into how digital health innovation can be a meaningful enabler of health system transformation. Examining different ways to leverage digital health technologies is crucial to best capitalize on their potential. [ABSTRACT FROM AUTHOR]

Failure of tall slender masonry structures during earthquakes often involves partial collapse of the structure well-above ground level. Consequently, the elastic response of the structure needs to be considered, which often requires modal analysis using finite element models — the generation of which can be labour-intensive and time-consuming. This paper presents a new integrated modelling approach which combines finite element analysis with rocking dynamics to model the seismic response of complex structural geometries in a computationally-efficient manner. The modelling strategy is implemented within the open-source computational framework COMPAS and is incorporated within the broader framework of a tool being developed for the seismic collapse assessment of masonry structures. The framework of this tool is first outlined, and the utility of the new modelling approach then demonstrated through application to the seismic assessment of a three historic masonry towers in North-Eastern Italy. The importance of accounting for elastic amplification effects, as well as the influence of varying boundary conditions on the dynamic response, is also illustrated. [ABSTRACT FROM AUTHOR]

Sarcopenia affects many elderly people via generally accepted losses in lean muscle and muscle strength attributed to aging. The dangers of sarcopenia lie in the lack of widespread understanding among [...]