Colors with the highest sadness ratings were related to dark and dull bluish ones. On the other hand, lighter bluish colors mixed with green appearance were similarly congruent with both sadness and happiness. The lightness properties of these sadness-related bluish colors continuously represent sadness dominancy (sadness rating minus happiness rating). Additionally, sadness dominancy of each sadness-related color group was differently associated with sadness-related situations. EN4 research buy These findings indicate that color features contribute to memory representation of sadness in association with situations and that color features continuously instantiate negative and positive aspects of sadness.This study was conducted to adapt the COV19-QoL scale to Turkish culture and to examine its psychometric properties in individuals diagnosed with and without COVID-19. A total of 1069 people aged between 18 and 65 years participated in the study. The COV19-QoLTR scale has six items, and it was confirmed to be one-dimensional in the Turkish sample (participants diagnosed with and without COVID-19 and the general population). Participants’ perceived quality of life and levels of anxiety and depression were the most affected areas and their physical and mental health levels were the least affected by the pandemic.Background and purpose – Artificial intelligence (AI), deep learning (DL), and machine learning (ML) have become common research fields in orthopedics and medicine in general. Engineers perform much of the work. While they gear the results towards healthcare professionals, the difference in competencies and goals creates challenges for collaboration and knowledge exchange. We aim to provide clinicians with a context and understanding of AI research by facilitating communication between creators, researchers, clinicians, and readers of medical AI and ML research.Methods and results – We present the common tasks, considerations, and pitfalls (both methodological and ethical) that clinicians will encounter in AI research. We discuss the following topics labeling, missing data, training, testing, and overfitting. Common performance and outcome measures for various AI and ML tasks are presented, including accuracy, precision, recall, F1 score, Dice score, the area under the curve, and ROC curves. We also discuss ethical considerations in terms of privacy, fairness, autonomy, safety, responsibility, and liability regarding data collecting or sharing.Interpretation – We have developed guidelines for reporting medical AI research to clinicians in the run-up to a broader consensus process. The proposed guidelines consist of a Clinical Artificial Intelligence Research (CAIR) checklist and specific performance metrics guidelines to present and evaluate research using AI components. Researchers, engineers, clinicians, and other stakeholders can use these proposal guidelines and the CAIR checklist to read, present, and evaluate AI research geared towards a healthcare setting.

During the coronavirus disease 2019 (COVID-19) pandemic, professional caregivers caring for the elderly may experience more vocal tract problems in addition to regular high vocal demands while wearing face masks/coverings.

Vocal tract discomfort (VTD) was assessed in 64 caregivers in one home for the elderly (64% participation rate) in June 2020 using the German version of the VTD scale.

More than one-half of the participating caregivers experienced VTD, described mostly as dryness, irritability, and tightness. Approximately, 80% reported that sensations were not perceived before enhanced infection prevention standards were implemented.

Among caregivers caring for the elderly during the COVID-19 pandemic, special care should be focused on the voice and vocal tract well-being.

Among caregivers caring for the elderly during the COVID-19 pandemic, special care should be focused on the voice and vocal tract well-being.Herbal formulations mentioned in traditional medicinal texts were investigated for in silico effect against SARS-COV-2 proteins involved in various functions of a virus such as attachment, entry, replication, transcription, etc. To repurpose and validate polyherbal formulations, molecular docking was performed to study the interactions of more than 150 compounds from various formulations against the SARS-CoV-2 proteins. Molecular dynamics (MD) simulation was performed to evaluate the interaction of top scored ligands with the various receptor proteins. The docking results showed that Liquiritic acid, Liquorice acid, Terchebulin, Glabrolide, Casuarinin, Corilagin, Chebulagic acid, Neochebulinic acid, Daturataturin A, and Taraxerol were effective against SARS-COV-2 proteins with higher binding affinities with different proteins. Results of MD simulations validated the stability of ligands from potent formulations with various receptors of SARS-CoV-2. Binding free energy analysis suggested the favourable interactions of phytocompounds with the recpetors. Besides, in silico comparison of the various formulations determined that Pathyadi kwath, Sanjeevani vati, Yashtimadhu, Tribhuvan Keeratiras, and Septillin were more effective than Samshamni vati, AYUSH-64, and Trikatu. Polyherbal formulations having anti-COVID-19 potential can be used for the treatment with adequate monitoring. New formulations may also be developed for systematic trials based on ranking from these studies.Communicated by Ramaswamy H. Sarma.Background and purpose – From previous studies, we know that clinical outcomes of revision total knee arthroplasty (rTKA) differ among reasons for revision. Whether the prevalence of repeat rTKAs is different depending on the reason for index rTKA is unclear. Therefore, we (1) compared the repeat revision rates between the different reasons for index rTKA, and (2) evaluated whether the reason for repeat rTKA was the same as the reason for the index revision.Patients and methods – Patients (n = 8,978) who underwent an index rTKA between 2010 and 2018 as registered in the Dutch Arthroplasty Register were included. Reasons for revision, as reported by the surgeon, were categorized as infection, loosening, malposition, instability, stiffness, patellar problems, and other. Competing risk analyses were performed to determine the cumulative repeat revision rates after an index rTKA for each reason for revision.Results – Overall, the cumulative repeat revision rate was 19% within 8 years after index rTKA. Patients revised for infection had the highest cumulative repeat revision rate (28%, 95% CI 25-32) within 8 years after index rTKA.