Displaying publications 21 - 28 of 28 in total

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  1. Phoon WO, Ong CN, Foo SC, Plueksawan W
    Ann Acad Med Singap, 1984 Apr;13(2 Suppl):408-16.
    PMID: 6497345
    This study was conducted on 506 firemen in Singapore. Interviews, pulmonary function tests and audiometry were conducted. With regard to pulmonary function, the results showed that forced vital capacity (FVC) increased up to the age of 25-30 years for both Chinese and Malays. Both FVC and forced expiratory volume in one second (FEV1.0) increased with standing height over the whole age range studied. The mean values of FVC and FEV1.0 were higher in Chinese. It was also found that the FEV1 of the subjects in the study showed a greater decline in rate with age than other workers studied by the authors previously. The hearing threshold of 83 fire fighters showed a prominent upward shift of 6-8 KHz at ages 20-30. This upward shift was more pronounced in the right ear. The implications of the findings are discussed and a comparison with results of other similar studies in other countries is made.
    Matched MeSH terms: Lung/physiopathology
  2. Thakur AK, Chellappan DK, Dua K, Mehta M, Satija S, Singh I
    Expert Opin Ther Pat, 2020 May;30(5):375-387.
    PMID: 32178542 DOI: 10.1080/13543776.2020.1741547
    Introduction: Pulmonary route is one of the preferred routes for the administration of therapeutically active agents for systemic as well as localized delivery. Chronic obstructive pulmonary disease (COPD), bronchial asthma, pneumonia, pulmonary hypertension, bronchiolitis, lung cancer, and tuberculosis are the major chronic diseases associated with the pulmonary system. Knowledge about the affecting factors, namely, the etiology, pathophysiology, and the various barriers (mechanical, chemical, immunological, and behavioral) in pulmonary drug delivery is essential to develop an effective drug delivery system. Formulation strategies and mechanisms of particle deposition in the lungs also play an important role in designing a suitable delivery system.Areas covered: In the present paper, various drug delivery strategies, viz. nanoparticles, microparticles, liposomes, powders, and microemulsions have been discussed systematically, from a patent perspective.Expert opinion: Patent publications on formulation strategies have been instrumental in the evolution of new techniques and technologies for safe and effective treatment of pulmonary diseases. New delivery systems are required to be simple/reproducible/scalable/cost-effective scale for manufacturing ability and should be safe/effective/stable/controllable for meeting quality and regulatory compliance.
    Matched MeSH terms: Lung/physiopathology
  3. Nabi FG, Sundaraj K, Lam CK, Palaniappan R
    J Asthma, 2020 04;57(4):353-365.
    PMID: 30810448 DOI: 10.1080/02770903.2019.1576193
    Objective: This study aimed to statistically analyze the behavior of time-frequency features in digital recordings of wheeze sounds obtained from patients with various levels of asthma severity (mild, moderate, and severe), and this analysis was based on the auscultation location and/or breath phase. Method: Segmented and validated wheeze sounds were collected from the trachea and lower lung base (LLB) of 55 asthmatic patients during tidal breathing maneuvers and grouped into nine different datasets. The quartile frequencies F25, F50, F75, F90 and F99, mean frequency (MF) and average power (AP) were computed as features, and a univariate statistical analysis was then performed to analyze the behavior of the time-frequency features. Results: All features generally showed statistical significance in most of the datasets for all severity levels [χ2 = 6.021-71.65, p 
    Matched MeSH terms: Lung/physiopathology
  4. Jong WL, Ung NM, Vannyat A, Rosenfeld AB, Wong JHD
    Phys Med, 2017 Oct;42:39-46.
    PMID: 29173919 DOI: 10.1016/j.ejmp.2017.08.011
    Challenges in treating lung tumours are related to the respiratory-induced tumour motion and the accuracy of dose calculation in charged particle disequilibrium condition. The dosimetric characteristics near the interface of lung and Perspex media in a moving phantom during respiratory-gated and non-gated radiotherapy were investigated using Gafchromic EBT2 and the MOSkin detector. The MOSkin detectors showed good agreement with the EBT2 films during static and gated radiotherapy. In static radiotherapy, the penumbral widths were found to be 3.66mm and 7.22mm in Perspex and lung media, respectively. In non-gated (moving) radiotherapy with 40mm respiratory amplitude, dose smearing effect was observed and the penumbral widths were increased to 28.81mm and 26.40mm, respectively. This has been reduced to 6.85mm and 9.81mm, respectively, in gated radiotherapy with 25% gating window. There were still some dose discrepancies as compared to static radiotherapy due to the residual motion. This should be taken into account in the margin generation for the target tumour.
    Matched MeSH terms: Lung/physiopathology
  5. Harun SN, Wainwright C, Klein K, Hennig S
    Paediatr Respir Rev, 2016 Sep;20:55-66.
    PMID: 27259460 DOI: 10.1016/j.prrv.2016.03.002
    A systematic review was performed (i) to describe the reported overall rate of progression of CF lung disease quantified as FEV1%predicted decline with age, (ii) to summarise identified influencing risk factors and (iii) to review methods used to analyse CF lung disease progression data. A search of publications providing FEV1%predicted values over age was conducted in PUBMED and EMBASE. Baseline and rate of FEV1%predicted decline were summarised overall and by identified risk factors. Thirty-nine studies were included and reported variable linear rates of lung function decline in patients with CF. The overall weighted mean FEV1%predicted over age was graphically summarised and showed a nonlinear, time-variant decline of lung function. Compared to their peers, Pseudomonas aeruginosa infection and pancreatic insufficiency were most commonly associated with lower baseline and more rapid FEV1%predicted declines respectively. Considering nonlinear models and drop-out in lung disease progression, analysis is lacking and more studies are warranted.
    Matched MeSH terms: Lung/physiopathology*
  6. Fauzi MA, Fadilah SA, Bahariah K
    Med J Malaysia, 2007 Mar;62(1):66-7.
    PMID: 17682575 MyJurnal
    Multiple lung cavitations and endobronchial nodules are rare presentations of newly diagnosed and recurrent Hodgkin's disease. The clinical and radiological features can be confused with pulmonary tuberculosis, which can be difficult to exclude in endemic areas. However, the presence of endobronchial nodules point, towards Hodgkin's disease. Differential diagnosis is aided by the fact that these lesions usually respond promptly to specific therapy. We present a case of an adolescent male who had constitutional and pulmonary symptoms associated with pulmonary cavities and endobronchial nodules subsequently confirmed to be Hodgkin's disease.
    Matched MeSH terms: Lung/physiopathology*
  7. Albadr MAA, Tiun S, Ayob M, Al-Dhief FT, Omar K, Hamzah FA
    PLoS One, 2020;15(12):e0242899.
    PMID: 33320858 DOI: 10.1371/journal.pone.0242899
    The coronavirus disease (COVID-19), is an ongoing global pandemic caused by severe acute respiratory syndrome. Chest Computed Tomography (CT) is an effective method for detecting lung illnesses, including COVID-19. However, the CT scan is expensive and time-consuming. Therefore, this work focus on detecting COVID-19 using chest X-ray images because it is widely available, faster, and cheaper than CT scan. Many machine learning approaches such as Deep Learning, Neural Network, and Support Vector Machine; have used X-ray for detecting the COVID-19. Although the performance of those approaches is acceptable in terms of accuracy, however, they require high computational time and more memory space. Therefore, this work employs an Optimised Genetic Algorithm-Extreme Learning Machine (OGA-ELM) with three selection criteria (i.e., random, K-tournament, and roulette wheel) to detect COVID-19 using X-ray images. The most crucial strength factors of the Extreme Learning Machine (ELM) are: (i) high capability of the ELM in avoiding overfitting; (ii) its usability on binary and multi-type classifiers; and (iii) ELM could work as a kernel-based support vector machine with a structure of a neural network. These advantages make the ELM efficient in achieving an excellent learning performance. ELMs have successfully been applied in many domains, including medical domains such as breast cancer detection, pathological brain detection, and ductal carcinoma in situ detection, but not yet tested on detecting COVID-19. Hence, this work aims to identify the effectiveness of employing OGA-ELM in detecting COVID-19 using chest X-ray images. In order to reduce the dimensionality of a histogram oriented gradient features, we use principal component analysis. The performance of OGA-ELM is evaluated on a benchmark dataset containing 188 chest X-ray images with two classes: a healthy and a COVID-19 infected. The experimental result shows that the OGA-ELM achieves 100.00% accuracy with fast computation time. This demonstrates that OGA-ELM is an efficient method for COVID-19 detecting using chest X-ray images.
    Matched MeSH terms: Lung/physiopathology
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