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Keywords = earlobe color

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13 pages, 11823 KiB  
Article
Study on the Differences in Fecal Metabolites and Microbial Diversity of Jiangshan Black-Bone Chickens with Different Earlobe Colors
by Zhijun Wang, Shiru Li, Xiangying Ding, Xue Du and Ayong Zhao
Animals 2024, 14(21), 3060; https://doi.org/10.3390/ani14213060 - 23 Oct 2024
Viewed by 1070
Abstract
The differences in earlobe color of Jiangshan black-bone chickens have been reported to be caused by the combined effects of melanin and collagen. In this study, we conducted LC-MS untargeted metabolomics and 16S rDNA diversity sequencing on the cecal contents of two types [...] Read more.
The differences in earlobe color of Jiangshan black-bone chickens have been reported to be caused by the combined effects of melanin and collagen. In this study, we conducted LC-MS untargeted metabolomics and 16S rDNA diversity sequencing on the cecal contents of two types of earlobes: peacock green (Blue and Green group) and dark reddish-purple (Black group). The metabolomic sequencing identified a total of 747 differential metabolites (DMs), in which the metabolites were primarily enriched in tyrosine and tryptophan metabolism pathways between peacock green and dark reddish-purple earlobes. There were 15 different bacterial taxa among the three groups of earlobes at the genus level, and correlation analysis between metabolites and microbes revealed that the DMs between peacock green and dark reddish-purple earlobes were positively correlated with the different bacterial taxa. In short, there are differences in gut microbiota and metabolites between Jiangshan black-bone chickens with peacock green earlobes and those with dark reddish-purple earlobes. Our results suggest that the bacterial phyla Firmicutes and Bacteroidota may influence melanin synthesis by affecting tryptophan metabolism, induced by 5-Methoxyindoleacetate, and tyrosine metabolism, induced by maleylacetoacetic acid and maleic acid, leading to differences in earlobe color. Full article
(This article belongs to the Section Animal Physiology)
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10 pages, 2178 KiB  
Communication
Non-Contact Oxygen Saturation Measurement Using YCgCr Color Space with an RGB Camera
by Na Hye Kim, Su-Gyeong Yu, So-Eui Kim and Eui Chul Lee
Sensors 2021, 21(18), 6120; https://doi.org/10.3390/s21186120 - 12 Sep 2021
Cited by 35 | Viewed by 6863
Abstract
Oxygen saturation (SPO2) is an important indicator of health, and is usually measured by placing a pulse oximeter in contact with a finger or earlobe. However, this method has a problem in that the skin and the sensor must be in [...] Read more.
Oxygen saturation (SPO2) is an important indicator of health, and is usually measured by placing a pulse oximeter in contact with a finger or earlobe. However, this method has a problem in that the skin and the sensor must be in contact, and an additional light source is required. To solve these problems, we propose a non-contact oxygen saturation measurement technique that uses a single RGB camera in an ambient light environment. Utilizing the fact that oxygenated and deoxygenated hemoglobin have opposite absorption coefficients at green and red wavelengths, the color space of photoplethysmographic (PPG) signals recorded from the faces of study participants were converted to the YCgCr color space. Substituting the peaks and valleys extracted from the converted Cg and Cr PPG signals into the Beer–Lambert law yields the SPO2 via a linear equation. When the non-contact SPO2 measurement value was evaluated based on the reference SPO2 measured with a pulse oximeter, the mean absolute error was 0.537, the root mean square error was 0.692, the Pearson correlation coefficient was 0.86, the cosine similarity was 0.99, and the intraclass correlation coefficient was 0.922. These results confirm the feasibility of non-contact SPO2 measurements. Full article
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