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      A comprehensive survey on investigation techniques of exhaled breath (EB) for diagnosis of diseases in human body

      , ,
      Informatics in Medicine Unlocked
      Elsevier BV

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          The Global Burden of Latent Tuberculosis Infection: A Re-estimation Using Mathematical Modelling

          Background The existing estimate of the global burden of latent TB infection (LTBI) as “one-third” of the world population is nearly 20 y old. Given the importance of controlling LTBI as part of the End TB Strategy for eliminating TB by 2050, changes in demography and scientific understanding, and progress in TB control, it is important to re-assess the global burden of LTBI. Methods and Findings We constructed trends in annual risk in infection (ARI) for countries between 1934 and 2014 using a combination of direct estimates of ARI from LTBI surveys (131 surveys from 1950 to 2011) and indirect estimates of ARI calculated from World Health Organisation (WHO) estimates of smear positive TB prevalence from 1990 to 2014. Gaussian process regression was used to generate ARIs for country-years without data and to represent uncertainty. Estimated ARI time-series were applied to the demography in each country to calculate the number and proportions of individuals infected, recently infected (infected within 2 y), and recently infected with isoniazid (INH)-resistant strains. Resulting estimates were aggregated by WHO region. We estimated the contribution of existing infections to TB incidence in 2035 and 2050. In 2014, the global burden of LTBI was 23.0% (95% uncertainty interval [UI]: 20.4%–26.4%), amounting to approximately 1.7 billion people. WHO South-East Asia, Western-Pacific, and Africa regions had the highest prevalence and accounted for around 80% of those with LTBI. Prevalence of recent infection was 0.8% (95% UI: 0.7%–0.9%) of the global population, amounting to 55.5 (95% UI: 48.2–63.8) million individuals currently at high risk of TB disease, of which 10.9% (95% UI:10.2%–11.8%) was isoniazid-resistant. Current LTBI alone, assuming no additional infections from 2015 onwards, would be expected to generate TB incidences in the region of 16.5 per 100,000 per year in 2035 and 8.3 per 100,000 per year in 2050. Limitations included the quantity and methodological heterogeneity of direct ARI data, and limited evidence to inform on potential clearance of LTBI. Conclusions We estimate that approximately 1.7 billion individuals were latently infected with Mycobacterium tuberculosis (M.tb) globally in 2014, just under a quarter of the global population. Investment in new tools to improve diagnosis and treatment of those with LTBI at risk of progressing to disease is urgently needed to address this latent reservoir if the 2050 target of eliminating TB is to be reached.
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            Diagnosing lung cancer in exhaled breath using gold nanoparticles.

            Conventional diagnostic methods for lung cancer are unsuitable for widespread screening because they are expensive and occasionally miss tumours. Gas chromatography/mass spectrometry studies have shown that several volatile organic compounds, which normally appear at levels of 1-20 ppb in healthy human breath, are elevated to levels between 10 and 100 ppb in lung cancer patients. Here we show that an array of sensors based on gold nanoparticles can rapidly distinguish the breath of lung cancer patients from the breath of healthy individuals in an atmosphere of high humidity. In combination with solid-phase microextraction, gas chromatography/mass spectrometry was used to identify 42 volatile organic compounds that represent lung cancer biomarkers. Four of these were used to train and optimize the sensors, demonstrating good agreement between patient and simulated breath samples. Our results show that sensors based on gold nanoparticles could form the basis of an inexpensive and non-invasive diagnostic tool for lung cancer.
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              Volatile organic compounds in breath as markers of lung cancer: a cross-sectional study.

              Many volatile organic compounds (VOCs), principally alkanes and benzene derivatives, have been identified in breath from patients with lung cancer. We investigated whether a combination of VOCs could identify such patients. We collected breath samples from 108 patients with an abnormal chest radiograph who were scheduled for bronchoscopy. The samples were collected with a portable apparatus, then assayed by gas chromatography and mass spectroscopy. The alveolar gradient of each breath VOC, the difference between the amount in breath and in air, was calculated. Forward stepwise discriminant analysis was used to identify VOCs that discriminated between patients with and without lung cancer. Lung cancer was confirmed histologically in 60 patients. A combination of 22 breath VOCs, predominantly alkanes, alkane derivatives, and benzene derivatives, discriminated between patients with and without lung cancer, regardless of stage (all p<0.0003). For stage 1 lung cancer, the 22 VOCs had 100% sensitivity and 81.3% specificity. Cross-validation of the combination correctly predicted the diagnosis in 71.7% patients with lung cancer and 66.7% of those without lung cancer. In patients with an abnormal chest radiograph, a combination of 22 VOCs in breath samples distinguished between patients with and without lung cancer. Prospective studies are needed to confirm the usefulness of breath VOCs for detecting lung cancer in the general population.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Informatics in Medicine Unlocked
                Informatics in Medicine Unlocked
                Elsevier BV
                23529148
                2021
                2021
                : 26
                : 100715
                Article
                10.1016/j.imu.2021.100715
                a34de61c-faff-4676-aaf5-facd74df0fac
                © 2021

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://creativecommons.org/licenses/by-nc-nd/4.0/

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