Global Strategy for the Diagnosis, Management, and Prevention of COPD 2018 is a consensus report published periodically since 2001 by an international panel of health professionals from respiratory medicine, socioeconomics, public health, and education comprising the Global Initiative for Chronic Obstructive Lung Disease (GOLD). The GOLD documents endeavor to incorporate latest evidence and expert consensus and are intended for use as "strategy documents" for implementation of effective care for chronic obstructive lung disease (COPD) on a global level. The GOLD 2018 report defines COPD as a "common, preventable and treatable disease that is characterized by persistent respiratory symptoms and airflow limitation that is due to airway and/or alveolar abnormalities, usually caused by significant exposure to noxious particles or gases," with the criteria of "persistent respiratory symptoms" being a new and controversial inclusion since 2017. With the availability of newer pharmacotherapy options, treatment recommendations are made on the basis of a review of the latest literature and directed by symptom burden and health care utilization. Apart from the change in definition, a major shift in the recommendations is the exclusion of severity of airflow limitation as one of the major factors in guiding therapy. We review the salient features of the GOLD 2018 document and provide commentary on features that merit further discussion based on our clinical experience and practice as well as literature review current as
We report here on a novel methodology in detecting Mycobacterium bovis (M. bovis) infection in cattle, based on identifying unique volatile organic compounds (VOCs) or a VOC profile in the breath of cattle. The study was conducted on an M. bovis-infected dairy located in southern Colorado, USA, and on two tuberculosis-free dairies from northern Colorado examined as negative controls. Gaschromatography/mass-spectrometry analysis revealed the presence of 2 VOCs associated with M. bovis infection and 2 other VOCs associated with the healthy state in the exhaled breath of M. bovis-infected and not infected animals, yielding distinctly different VOC patterns for the two study groups. Based on these results, a nanotechnology-based array of sensors was then tailored for detection of M. bovis-infected cattle via breath. Our system successfully identified all M. bovis-infected animals, while 21% of the not infected animals were classified as M. bovis-infected. This technique could form the basis for a real-time cattle monitoring system that allows efficient and non-invasive screening for new M. bovis infections on dairy farms.
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