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Nearly fifty years ago, Timothy Gallwey published "The Inner Game of Tennis," which left an indelible mark on sports psychology; subsequently, Barry Green used similar principles to author "The Inner Game of Music." As far as can be determined, there lacks a concise guide that translates key insights from sports and music psychology into practical strategies for large ensembles. To address this gap in the professional literature, we draw on the sports and music psychology literature, as well as our own professional applied experience, to discuss the benefits of psychological skills for musicians, and we present ten practical strategies to aid the development of psychological skills for large-ensemble musicians. We conclude with some final thoughts on developing the inner musician.

Author summary: Artificial Intelligence (AI) and Machine Learning (ML) models are increasingly deployed on biomedical and health data to shed insights on biological mechanism, predict disease outcomes, and support clinical decision-making. However, ensuring model validity is challenging. The 10 quick tips described here discuss useful practices on how to check AI/ML models from 2 perspectives—the user and the developer. [ABSTRACT FROM AUTHOR]

The 'rule-of-6' prediction tool was shown to be able to identify COVID-19 patients at risk of adverse outcomes. During the pandemic, we frequently observed hyponatremia at presentation. We sought to evaluate if adding hyponatremia at presentation could improve the 'rule-of-6' prediction tool. We retrospectively analysed 1781 consecutive patients admitted to a single tertiary academic institution in Singapore with COVID-19 infection from February 2020 to October 2021. A total of 161 (9.0%) patients had hyponatremia. These patients were significantly older, with more co-morbidities and more likely to be admitted during the Delta wave (2021). They were more likely to have radiographic evidence of pneumonia (46.0% versus 13.0%, p < 0.001) and more adverse outcomes (25.5% vs. 4.1%, p < 0.001). Hyponatremia remained independently associated with adverse outcomes after adjusting for age, lack of medical co-morbidities, vaccination status, year of admission, CRP, LDH, and ferritin. The optimised cut-off for serum sodium in predicting adverse outcomes was approximately <135 mmol/L as determined by the Youden index. Although derived in early 2020, the 'rule-of-6' prediction tool continued to perform well in our later cohort (AUC: 0.72, 95%CI: 0.66–0.78). Adding hyponatremia to the 'rule-of-6' improved its performance (AUC: 0.76, 95%CI: 0.71–0.82). Patients with hyponatremia at presentation for COVID-19 had poorer outcomes even as new variants emerged. [ABSTRACT FROM AUTHOR]

Motivation Deep graph learning (DGL) has been widely employed in the realm of ligand-based virtual screening. Within this field, a key hurdle is the existence of activity cliffs (ACs), where minor chemical alterations can lead to significant changes in bioactivity. In response, several DGL models have been developed to enhance ligand bioactivity prediction in the presence of ACs. Yet, there remains a largely unexplored opportunity within ACs for optimizing ligand bioactivity, making it an area ripe for further investigation. Results We present a novel approach to simultaneously predict and optimize ligand bioactivities through DGL and ACs (OLB-AC). OLB-AC possesses the capability to optimize ligand molecules located near ACs, providing a direct reference for optimizing ligand bioactivities with the matching of original ligands. To accomplish this, a novel attentive graph reconstruction neural network and ligand optimization scheme are proposed. Attentive graph reconstruction neural network reconstructs original ligands and optimizes them through adversarial representations derived from their bioactivity prediction process. Experimental results on nine drug targets reveal that out of the 667 molecules generated through OLB-AC optimization on datasets comprising 974 low-activity, noninhibitor, or highly toxic ligands, 49 are recognized as known highly active, inhibitor, or nontoxic ligands beyond the datasets' scope. The 27 out of 49 matched molecular pairs generated by OLB-AC reveal novel transformations not present in their training sets. The adversarial representations employed for ligand optimization originate from the gradients of bioactivity predictions. Therefore, we also assess OLB-AC's prediction accuracy across 33 different bioactivity datasets. Results show that OLB-AC achieves the best Pearson correlation coefficient (r 2) on 27/33 datasets, with an average improvement of 7.2%–22.9% against the state-of-the-art bioactivity prediction methods. Availability and implementation The code and dataset developed in this work are available at github.com/Yueming-Yin/OLB-AC. [ABSTRACT FROM AUTHOR]

Providing family updates is a common clinical task for medical trainees and practitioners working in hospital settings. Good clinical communication skills are essential in clinical care as it is associated with improved patient satisfaction, understanding of condition, treatment adherence, and better overall clinical outcomes. Moreover, poor communications are often the source of medical complaints. However, while patient-centred communication skills training has generally been incorporated into clinical education, there hitherto remains inadequate training on clinical communications with patients' families, which carry different nuances. In recent years, it is increasingly recognized that familial involvement in the care of hospitalized patients leads to better clinical and psychological outcomes. In fact, in Asian populations with more collectivistic cultures, families are generally highly involved in patient care and decision-making. Therefore, effective clinical communications and regular provision of family updates are essential to build therapeutic rapport, facilitate familial involvement in patient care, and also provide a more holistic understanding of the patient's background and psychosocial set-up. In this article, we herein describe a seven-step understand the clinical context, gather perspectives , deliver medical information, address questions, concerns and expectations, provide tentative plans, demonstrate empathy , postcommunication reflections model as a practical guide for medical trainees and practitioners in provision of structured and effective family updates in their clinical practice. [ABSTRACT FROM AUTHOR]

The term 'insight' is generically defined in English language as the ability to perceive deeper truths about people and situations. In clinical practice, patient insight is known to have important implications in treatment compliance and clinical outcomes, and can be assessed clinically by looking for the presence of illness awareness, correct attribution of symptoms to underlying condition, and acceptance of treatment. In this article, we suggest that cultivating insight is actually a highly important, yet often overlooked, component of medical training, which may explain why some consistently learn well, communicate effectively, and quickly attain clinical competency, while others struggle throughout their clinical training and may even be difficult to remediate. We herein define 'insight' in the context of medical training as having an astute perception of personal cognitive processes, motivations, emotions, and ability (strengths, weaknesses, and limitations) that should drive self-improvement and effective behavioural regulation. We then describe the utility of cultivating 'insight' in medical training through three lenses of (i) promoting self-regulated, lifelong clinical learning, (ii) improving clinical competencies and person-centred care, and (iii) enhancing physician mental health and well-being. In addition, we review educational pedagogies that are helpful to create a medical eco-system that promotes the cultivation of insight among its trainees and practitioners. Finally, we highlight several tell-tale signs of poor insight and discuss psychological and non-psychological interventions that may help those severely lacking in insight to become more amenable to change and remediation. [ABSTRACT FROM AUTHOR]