| 11. |
- Sattari, Zahra, et al.
(författare)
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Fraction of Clumpy Star-forming Galaxies at 0.5 ≤ z ≤ 3 in UVCANDELS : Dependence on Stellar Mass and Environment
- 2023
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Ingår i: Astrophysical Journal. - 0004-637X .- 1538-4357. ; 951:2
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Tidskriftsartikel (refereegranskat)abstract
- High-resolution imaging of galaxies in rest-frame UV has revealed the existence of giant star-forming clumps prevalent in high-redshift galaxies. Studying these substructures provides important information about their formation and evolution and informs theoretical galaxy evolution models. We present a new method to identify clumps in galaxies' high-resolution rest-frame UV images. Using imaging data from CANDELS and UVCANDELS, we identify star-forming clumps in an HST/F160W ≤ 25 AB mag sample of 6767 galaxies at 0.5 ≤ z ≤ 3 in four fields, GOODS-N, GOODS-S, EGS, and COSMOS. We use a low-passband filter in Fourier space to reconstruct the background image of a galaxy and detect small-scale features (clumps) on the background-subtracted image. Clumpy galaxies are defined as those having at least one off-center clump that contributes a minimum of 10% of the galaxy's total rest-frame UV flux. We measure the fraction of clumpy galaxies (fclumpy) as a function of stellar mass, redshift, and galaxy environment. Our results indicate that fclumpy increases with redshift, reaching ∼65% at z ∼ 1.5. We also find that fclumpy in low-mass galaxies () is 10% higher compared to that of their high-mass counterparts (). Moreover, we find no evidence of significant environmental dependence of fclumpy for galaxies at the redshift range of this study. Our results suggest that the fragmentation of gas clouds under violent disk instability remains the primary driving mechanism for clump formation, and incidents common in dense environments, such as mergers, are not the dominant processes.
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| 12. |
- Zhang, Cuili, et al.
(författare)
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Association of lifestyle with deep learning predicted electrocardiographic age
- 2023
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Ingår i: Frontiers in Cardiovascular Medicine. - : Frontiers Media S.A.. - 2297-055X. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Background: People age at different rates. Biological age is a risk factor for many chronic diseases independent of chronological age. A good lifestyle is known to improve overall health, but its association with biological age is unclear.Methods: This study included participants from the UK Biobank who had undergone 12-lead resting electrocardiography (ECG). Biological age was estimated by a deep learning model (defined as ECG-age), and the difference between ECG-age and chronological age was defined as Delta age. Participants were further categorized into an ideal (score 4), intermediate (scores 2 and 3) or unfavorable lifestyle (score 0 or 1). Four lifestyle factors were investigated, including diet, alcohol consumption, physical activity, and smoking. Linear regression models were used to examine the association between lifestyle factors and Delta age, and the models were adjusted for sex and chronological age.Results: This study included 44,094 individuals (mean age 64 +/- 8, 51.4% females). A significant correlation was observed between predicted biological age and chronological age (correlation coefficient = 0.54, P < 0.001) and the mean Delta age (absolute error of biological age and chronological age) was 9.8 +/- 7.4 years. Delta age was significantly associated with all of the four lifestyle factors, with the effect size ranging from 0.41 +/- 0.11 for the healthy diet to 2.37 +/- 0.30 for non-smoking. Compared with an ideal lifestyle, an unfavorable lifestyle was associated with an average of 2.50 +/- 0.29 years of older predicted ECG-age.Conclusion: In this large contemporary population, a strong association was observed between all four studied healthy lifestyle factors and deaccelerated aging. Our study underscores the importance of a healthy lifestyle to reduce the burden of aging-related diseases.
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