UMOYA: a prospective longitudinal cohort study to evaluate novel diagnostic tools and to assess long-term impact on lung health in South African children with presumptive pulmonary TB-a study protocol.

BACKGROUND: Despite a high paediatric tuberculosis (TB) burden globally, sensitive and specific diagnostic tools are lacking. In addition, no data exist on the impact of pulmonary TB on long-term child lung health in low- and middle-income countries. The prospective observational UMOYA study aims (1) to build a state-of-the-art clinical, radiological, and biological repository of well-characterised children with presumptive pulmonary TB as a platform for future studies to explore new emerging diagnostic tools and biomarkers for early diagnosis and treatment response; and (2) to investigate the short and long-term impact of pulmonary TB on lung health and quality of life in children. METHODS: We will recruit up to 600 children (0-13 years) with presumptive pulmonary TB and 100 healthy controls. Recruitment started in November 2017 and is expected to continue until May 2023. Sputum and non-sputum-based samples are collected at enrolment and during follow-up in TB cases and symptomatic controls. TB treatment is started by routine care services. Intensive follow-up for 6 months will allow for TB cases to retrospectively be classified according to international consensus clinical case definitions for TB. Long-term follow-up, including imaging, comprehensive assessment of lung function and quality of life questionnaires, are done yearly up to 4 years after recruitment. DISCUSSION: The UMOYA study will provide a unique platform to evaluate new emerging diagnostic tools and biomarkers for early diagnosis and treatment response and to investigate long-term outcomes of pulmonary TB and other respiratory events on lung health in children.

Characteristics of and User Engagement With Antivaping Posts on Instagram: Observational Study.

BACKGROUND: Although government agencies acknowledge that messages about the adverse health effects of e-cigarette use should be promoted on social media, effectively delivering those health messages is challenging. Instagram is one of the most popular social media platforms among US youth and young adults, and it has been used to educate the public about the potential harm of vaping through antivaping posts. OBJECTIVE: We aim to analyze the characteristics of and user engagement with antivaping posts on Instagram to inform future message development and information delivery. METHODS: A total of 11,322 Instagram posts were collected from November 18, 2019, to January 2, 2020, by using antivaping hashtags including #novape, #novaping, #stopvaping, #dontvape, #antivaping, #quitvaping, #antivape, #stopjuuling, #dontvapeonthepizza, and #escapethevape. Among those posts, 1025 posts were randomly selected and 500 antivaping posts were further identified by hand coding. The image type, image content, and account type of antivaping posts were hand coded, the text information in the caption was explored by topic modeling, and the user engagement of each category was compared. RESULTS: Analyses found that antivaping images of the educational/warning type were the most common (253/500; 50.6%). The average likes of the educational/warning type (15 likes/post) were significantly lower than the catchphrase image type (these emphasized a slogan such as "athletesdontvape" in the image; 32.5 likes/post; P<.001). The majority of the antivaping posts contained the image content element text (n=332, 66.4%), followed by the image content element people/person (n=110, 22%). The images containing people/person elements (32.8 likes/post) had more likes than the images containing other elements (13.8-21.1 likes/post). The captions of the antivaping Instagram posts covered topics including "lung health," "teen vaping," "stop vaping," and "vaping death cases." Among the 500 antivaping Instagram posts, while most posts were from the antivaping community (n=177, 35.4%) and personal account types (n=182, 36.4%), the antivaping community account type had the highest average number of posts (1.69 posts/account). However, there was no difference in the number of likes among different account types. CONCLUSIONS: Multiple features of antivaping Instagram posts may be related to user engagement and perception. This study identified the critical elements associated with high user engagement, which could be used to design antivaping posts to deliver health-related information more efficiently.

Impact of N-Acetyl Cysteine (NAC) on Tuberculosis (TB) Patients-A Systematic Review.

Sustained TB infection overproduces reactive oxygen species (ROS) as a host defense mechanism. Research shows ROS is destructive to lung tissue. Glutathione (GSH) neutralizes ROS, although it is consumed. NAC is a precursor of GSH synthesis, and administering an appropriate dose of NAC to patients with respiratory conditions may enhance lung recovery and replenish GSH. The present review searched for articles reporting on the effects of NAC in TB treatment from 1960 to 31 May 2022. The PICO search strategy was used in Google Scholar, PubMed, SciFinder, and Wiley online library databases. The COVIDENCE tool was used to delete inappropriate content. We eventually discovered five clinical trials, one case report, seven reviews, in vitro research, and four experimental animal studies from the twenty-four accepted articles. The use of NAC resulted in increased GSH levels, decreased treatment time, and was safe with minimal adverse events. However, the evidence is currently insufficient to estimate the overall effects of NAC, thus the study warrants more NAC clinical trials to demonstrate its effects in TB treatment.

LHSPred: A web based application for predicting lung health severity.

Background and objectives: The computed tomography (CT) scan facilities are crucial for diagnosis of pulmonary diseases and are overburdened during the current pandemic of novel coronavirus disease 2019 (COVID-19). LHSPred (Lung Health Severity Prediction) is a web based tool that enables users to determine a score that evaluates CT scans, without radiologist intervention, and predict risk of pneumonia with features of blood examination and age of patient. It can help in early assessment of lung health severity of patients without CT-scan results and also enable monitoring of post-COVID lung health for recovered patients. Methods: This tool uses Support Vector Regression (SVR) and Multi-Layer Perceptron Regression (MLPR), trained on COVID-19 patient data reported in the literature. It allows to compute a score (CT severity score) that evaluates the involvement of lesions in lung lobes and to predict risk of pneumonia. A web application was implemented that uses the trained regression models. Results: The application has proven to be effective and user friendly in a clinical setting for pulmonary disease treatment. The SVR model achieved Pearson correlation coefficient (PCC) of 0.77 and mean absolute error (MAE) of 2.239 while determining the computed tomography (CT) severity score. The MLPR model achieved PCC of 0.77 and MAE of 2.309. Thus, it can be applied as a useful tool in predicting pneumonia in the post COVID-19 era. Conclusion: LHSPred can be used as a decision support system by the clinicians and as a tool for self-assessment by the patients with only six blood test input features.

SingStrong - singing for better lung health in pulmonary fibrosis: A feasibility study

BACKGROUND PURPOSE: Pulmonary fibrosis (PF) is a debilitating, incurable disease. Strategies to optimise health-related quality of life and minimise symptom impact are advocated. Available treatment options such as pulmonary rehabilitation have been severely disrupted due to COVID-19. This feasibility study explored the clinical efficacy and acceptability of an online singing and breathing retraining programme (SingStrong) for people with PF. METHODS: The weekly online programme conducted over 12 weeks was comprised of 45-minute classes of mindfulness, breathing retraining, vocal exercises and singing conducted by a trained vocal coach. People with PF were invited to participate and sessions were recorded for non-attenders. Demographic data were collected, and the St Georges Respiratory Questionnaire (SGRQ) and Idiopathic PF Patient Reported Outcome measure (IPF-PROM) were administered. The questionnaire also invited participants to provide feedback on the utility, enjoyability and main pros/cons of the intervention. Participation in the research element of the programme was not required to attend the weekly classes. RESULTS: Of 24 participants recruited, data from 15 (mean (Standard Deviation) age of 66 (8.7);male: n = 8) who completed both pre and post-intervention questionnaires were analysed. Statistically significant improvements were recorded in the IPF-PROM (p = 0.019) and self-reported quality of life (p = 0.028). Class attendance by study participants and the broader PF group cumulatively, increased from 14 to 25 participants between weeks 1 and 12. Qualitatively, strong satisfaction with classes and improved efficacy in self-management of lung health, in particular breathlessness, were reported. CONCLUSIONS: Singing and breathing retraining interventions may endow biopsychosocial benefits for people with PF, in the presence of modest objective clinical gains. Singing programmes are popular and may provide helpful adjuncts to existing clinical strategies such as pulmonary rehabilitation. © 2022 - IOS Press. All rights reserved.

Accessible, Affordable and Low-Risk Lungs Health Monitoring in Covid-19: Deep Cascade Reconstruction from Degraded LR-ULDCT

We present deep cascade reconstruction of degraded low-resolution ultra-low-dose computed tomography (LR-ULDCT) chest images to restored and super-resolved (SR) ULDCT as accessible, affordable, and relatively less hazardous recourse for lungs health monitoring in COVID-19;when compared to relatively less available, costly, and high radiation dose high-resolution CT (HRCT). The degraded LR-ULDCT is first restored with unsupervised dictionary-based deep residual learning network that handles degradations along with Poisson noise found in CT data. The restored version is given to SR network that increases its spatial resolution by minimizing adversarial loss between LR-ULDCT and reconstructed SR-ULDCT within minimax game. It is then fed for segmentation which is achieved by additional block of convolution, Leaky-ReLU, and batch-normalization in U-Net. Thus restored segmented SR-ULDCT estimates presence of ground glass opacity and facilitates monitoring of lungs health at par HRCT. Comparative experiments and ablation study are presented using synthetic and real COVID-19 data. © 2022 IEEE.

Poor Respiratory Health Following Relapsing SARS-CoV-2 Infection in Children with Cystic Fibrosis.

Children with cystic fibrosis (CF) constitute a high-risk group for COVID-19 with underlying chronic lung disease. COVID-19 severity varying from mild infection to need of intensive care has been described in children with CF. Two children with significant underlying pulmonary morbidity are described here, who developed severe disease following SARS-CoV-2 infection. Case 1 (a 9-y-old boy) had pneumonia with respiratory failure requiring noninvasive ventilation support. He had delayed clearance of SARS-CoV-2, with recurrence of symptomatic disease with short asymptomatic period in between. He was also diagnosed with CF-related diabetes and allergic bronchopulmonary aspergillosis during the second episode. Case 2 (an 18-mo-old boy) had two episodes of SARS-CoV-2-related severe lower respiratory infection within a period of 2 mo, requiring high-flow nasal oxygen support. Both children had 3rd pulmonary exacerbation but SARS-CoV-2 was not detected in respiratory secretions. To conclude, children with CF with underlying pulmonary morbidity, can develop severe COVID-19 and prolonged SARS-CoV-2 shedding.

Kloman Metre: An EMD-Based Tool for Triaging Diseases Leading to Lung Infections Including COVID-19

The digital revolution can help developing countries to overcome the problem of limited healthcare infrastructure in developing nations such as India. The COVID-19 pandemic has shown the urgency of integration of digital technologies into healthcare infrastructure. In order to solve the issue of lack of trained healthcare professionals at public health centres (PHCs), researchers are trying to build tools which can help to tag pulmonary ailment within a fraction of second. Such tagging will help the medical community to utilize their time more efficiently. In this work, we have tried to assess the “lung health” of patients suffering from a variety of pulmonary diseases including COVID-19, tuberculosis and pneumonia by applying Earth Mover’s Distance algorithm to the X-ray images of the patients. The lung X-ray images of patients suffering from pneumonia, TB and COVID-19 and healthy persons are pooled together from various datasets. Our preliminary data based upon 100 random images depicting each type of lung disease such as COVID-19, tuberculosis and pneumonia revealed that patients suffering from tuberculosis have the highest severity as per the values obtained from the EMD scale. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Lung Health Analysis: Adventitious Respiratory Sound Classification Using Filterbank Energies

Audio-based healthcare technologies are among the most significant applications of pattern recognition and Artificial Intelligence. Lately, a major chunk of the World population has been infected with serious respiratory diseases such as COVID-19. Early recognition of lung health abnormalities can facilitate early intervention, and decrease the mortality rate of the infected population. Research has shown that it is possible to automatically monitor lung health abnormalities through respiratory sounds. In this paper, we propose an approach that employs filter bank energy-based features and Random Forests to classify lung problem types from respiratory sounds. The adventitious sounds, crackles and wheezes appear distinct to the human ear. Moreover, different sounds are characterized by different frequency ranges that are dominant. The proposed approach attempts to distinguish the adventitious sounds (crackles and wheezes) by modeling the human auditory perception of these sounds. Specifically, we propose a respiratory sounds representation technique capable of modeling the dominant frequency range present in such sounds. On a publicly available dataset (ICBHI) of size 6898 cycles spanning over 5h, our results can be compared with the state-of-the-art results, in distinguishing two different types of adventitious sounds: crackles and wheezes.

Immunomodulatory Role of Nutrients: How Can Pulmonary Dysfunctions Improve?

Nutrition is an important tool that can be used to modulate the immune response during infectious diseases. In addition, through diet, important substrates are acquired for the biosynthesis of regulatory molecules in the immune response, influencing the progression and treatment of chronic lung diseases, such as asthma and chronic obstructive pulmonary disease (COPD). In this way, nutrition can promote lung health status. A range of nutrients, such as vitamins (A, C, D, and E), minerals (zinc, selenium, iron, and magnesium), flavonoids and fatty acids, play important roles in reducing the risk of pulmonary chronic diseases and viral infections. Through their antioxidant and anti-inflammatory effects, nutrients are associated with better lung function and a lower risk of complications since they can decrease the harmful effects from the immune system during the inflammatory response. In addition, bioactive compounds can even contribute to epigenetic changes, including histone deacetylase (HDAC) modifications that inhibit the transcription of proinflammatory cytokines, which can contribute to the maintenance of homeostasis in the context of infections and chronic inflammatory diseases. These nutrients also play an important role in activating immune responses against pathogens, which can help the immune system during infections. Here, we provide an updated overview of the roles played by dietary factors and how they can affect respiratory health. Therefore, we will show the anti-inflammatory role of flavonoids, fatty acids, vitamins and microbiota, important for the control of chronic inflammatory diseases and allergies, in addition to the antiviral role of vitamins, flavonoids, and minerals during pulmonary viral infections, addressing the mechanisms involved in each function. These mechanisms are interesting in the discussion of perspectives associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and its pulmonary complications since patients with severe disease have vitamins deficiency, especially vitamin D. In addition, researches with the use of flavonoids have been shown to decrease viral replication in vitro. This way, a full understanding of dietary influences can improve the lung health of patients.

Bronchiectasis-Could Immunonutrition Have a Role to Play in Future Management?

Bronchiectasis is a chronic condition in which areas of the bronchial tubes become permanently widened predisposing the lungs to infection. Bronchiectasis is an age-associated disease with the highest prevalence in people older than 75 years. While the prevalence of bronchiectasis is higher in males, disease is more severe in females who have a poorer prognosis. The overall prevalence of the disease is thought to be rising. Its aetiology is multi-faceted, but a compromised immune system is now thought to play a central role in the pathology of this disease. Research has begun to study the role of malnutrition and certain nutrients-vitamin D and zinc-along with the role of the lung microbiome in relation to the management of bronchiectasis. Given this, the present mini review sets out to provide an overview of the state-of-the-art within the field, identify research gaps and pave the way for future developments and research investment within this field.