Publications by authors named "Anselmo Elcana de Oliveira"

Article Synopsis
  • Human cerumen analysis is emerging as a non-invasive method for diagnosing diseases by detecting volatile organic metabolites (VOMs) in earwax, potentially identifying biomarkers for various health conditions.
  • A study examined how demographic factors like BMI, sex, age, and ethnicity influence the presence and abundance of these VOMs, using data from 70 volunteers and advanced analysis techniques.
  • Results indicated that sex and BMI had a significant effect on VOM abundance, while no clear patterns of discrimination based on demographic factors emerged, highlighting the need for further research in personalized medicine approaches using cerumen analysis.
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Cancer is the deadliest human disease and the development of new diagnosis methods is important to increase the chances of a cure. In this work it was developed a new method, named here for the first time as cerumenogram, using cerumen (earwax) as a new biomatrix for diagnosis. Earwax samples collected from cancer patients (cancer group) and cancer-free patients (control group) were analyzed by Headspace/Gas Chromatography-Mass Spectrometry (HS/GC-MS), following with multivariate analysis steps to process the raw data generated.

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Important metabolic changes occur during transition period of late pregnancy and early lactation to meet increasing energy demands of the growing fetus and for milk production. The aim of this investigation is to present an innovative and non-invasive tool using ewe earwax sample analysis to assess the metabolic profile in ewes during late pregnancy and early lactation. In this work, earwax samples were collected from 28 healthy Brazilian Santa Inês ewes divided into 3 sub-groups: 9 non-pregnant ewes, 6 pregnant ewes in the last 30 days of gestation, and 13 lactating ewes ≤ 30 days postpartum.

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Unlabelled: This work combines the advantages of volatile metabolites profiling as a young growing research field with a non-invasive sampling technique using earwax "a neglected body secretion" for detection and monitoring of biomarkers for diabetes mellitus (types 1 and 2). Earwax samples were collected from 26 diabetic patients of both types, analyzed by headspace gas chromatography mass spectrometry and confronted to the volatile earwax composition of 33 healthy individuals. Data mining analysis was conducted using different models to discriminate the healthy individuals from the diabetic patients and to discriminate between both types of diabetes as well.

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