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Photobiomodulation (PBM) using low-level laser therapy (LLLT) is a treatment that is increasingly used in oncology. Studies reported enhancement of wound healing with reduction in pain, tissue swelling and inflammatory conditions such as radiation dermatitis, oral mucositis, and lymphedema. However, factors such as wavelength, energy density and irradiation frequency influence the cellular mechanisms of LLLT. Moreover, the effects of LLLT vary according to cell types. Thus, controversy arose as a result of poor clinical response reported in some studies that may have used inadequately planned treatment protocols. Since LLLT may enhance tumor cell proliferation, these will also need to be considered before clinical use. This review aims to summarize the current knowledge of the cellular mechanisms of LLLT by considering its effects on cell proliferation, metabolism, angiogenesis, apoptosis and inflammation. With a better understanding of the cellular mechanisms, bridging findings from laboratory studies to clinical application can be improved.

The use of impedance cardiography to monitor physiological changes in sports is rarely reported. Using head-up tilt test, we evaluated a portable noninvasive impedance cardiography device (PhysioFlow) by comparing it with a reference Doppler monitor (USCOM). Accuracy in tracking hemodynamic changes deteriorated with higher tilt, implying a gravitational influence on its performance. Stroke volume measurements were overestimated, but the changes were underestimated. Despite its convenient physical features, the suitability of PhysioFlow for sports use is questionable.

Introduction: Community face mask use during the coronavirus disease 2019 (COVID-19) pandemic has considerably differed worldwide. Generally, Asians are more inclined to wear face masks during disease outbreaks. Hong Kong has emerged relatively unscathed during the initial outbreak of COVID-19, despite its dense population. Previous infectious disease outbreaks influenced the local masking behaviour and response to public health measures. Thus, local behavioural insights are important for the successful implementation of infection control measures. This study explored the behaviour and attitudes of wearing face masks in the community during the initial spread of COVID-19 in Hong Kong. Methods:We observed the masking behaviour of 10 211 pedestrians in several regions across Hong Kong from 1 to 29 February 2020. We supplemented the data with an online survey of 3199 respondents' views on face mask use.Results: Among pedestrians, the masking rate was 94.8%; 83.7% wore disposable surgical masks. However, 13.0% wore surgical masks incorrectly with 42.5% worn too low, exposing the nostrils or mouth; 35.5% worn 'inside-out' or 'upside-down' . Most online respondents believed in the efficacy of wearing face mask for protection (94.6%) and prevention

Modern medicine is reliant on various medical imaging technologies for non-invasively observing patients’ anatomy. However, the interpretation of medical images can be highly subjective and dependent on the expertise of clinicians. Moreover, some potentially useful quantitative information in medical images, especially that which is not visible to the naked eye, is often ignored during clinical practice. In contrast, radiomics performs high-throughput feature extraction from medical images, which enables quantitative analysis of medical images and prediction of various clinical endpoints. Studies have reported that radiomics exhibits promising performance in diagnosis and predicting treatment responses and prognosis, demonstrating its potential to be a non-invasive auxiliary tool for personalized medicine. However, radiomics remains in a developmental phase as numerous technical challenges have yet to be solved, especially in feature engineering and statistical modeling. In this review, we introduce the current utility of radiomics by summarizing research on its application in the diagnosis, prognosis, and prediction of treatment responses in patients with cancer. We focus on machine learning approaches, for feature extraction and selection during feature engineering and for imbalanced datasets and multi-modality fusion during statistical modeling. Furthermore, we introduce the stability, reproducibility, and interpretability of features, and the generalizability and interpretability of models. Finally, we offer possible solutions to current challenges in radiomics research.

The rapid spread of the coronavirus disease 2019 (COVID-19) into a global pandemic caught the world unprepared. Previously effective measures for containing disease outbreaks were overwhelmed, necessitating strict controls such as lockdowns or curfews. Among the disease control interventions, community mass masking was one of the highly controversial issues with differing opinions on its indications or effectiveness from different health authorities around the world. Regions where community mass masking was timely introduced were associated with lower transmission rates, and more effective disease control. In this article, we discuss the evidence on the effectiveness, and rationale for community mass masking to prevent the COVID-19 transmission. Areas for further research to define the role of mass masking in light of the COVID-19 pandemic will be suggested. This would help policy makers in formulating mass masking policies.

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TO THE EDITOR: We thank Myers and Leprêtre (1) for their comments. It appears that they have misunderstood our study (2) and also expressed misconceptions of Ultrasonic Cardiac Output Monitor (USCOM) measurements, which we will address.We used head-up tilt (HUT) solely as a test for accuracy and not as a surrogate for exercise test, as incorrectly claimed by Myers and Leprêtre. Although HUT and exercise are physiologically different, a cardiac output (CO) monitor should be able to accurately measure hemodynamic changes in both. It was evident in our study using