The role of oxygen as a driver for early animal evolution is widely debated. During the Cambrian explosion, episodic radiations of major animal phyla occurred coincident with repeated carbon isotope fluctuations. However, the driver of these isotope fluctuations and potential links to environmental oxygenation are unclear. Here, we report high-resolution carbon and sulphur isotope data for marine carbonates from the southeastern Siberian Platform that document the canonical explosive phase of the Cambrian radiation from ~524 to ~514 Myr ago. These analyses demonstrate a strong positive covariation between carbonate δC and carbonate-associated sulphate δS through five isotope cycles. Biogeochemical modelling suggests that this isotopic coupling reflects periodic oscillations in atmospheric O and the extent of shallow ocean oxygenation. Episodic maxima in the biodiversity of animal phyla directly coincided with these extreme oxygen perturbations. Conversely, the subsequent Botoman-Toyonian animal extinction events (~514 to ~512 Myr ago) coincided with decoupled isotope records that suggest a shrinking marine sulphate reservoir and expanded shallow marine anoxia. We suggest that fluctuations in oxygen availability in the shallow marine realm exerted a primary control on the timing and tempo of biodiversity radiations at a crucial phase in the early history of animal life.
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http://dx.doi.org/10.1038/s41561-019-0357-z | DOI Listing |
Sci Rep
January 2025
Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
Observing quantum mechanical characteristics in biological processes is a surprising and important discovery. One example, which is gaining more experimental evidence and practical applications, is the effect of weak magnetic fields with extremely low frequencies on cells, especially cancerous ones. In this study, we use a mathematical model of ROS dynamics in cancer cells to show how ROS oscillatory patterns can act as a resonator to amplify the small effects of the magnetic fields on the radical pair dynamics in mitochondrial Complex III.
View Article and Find Full Text PDFJ Control Release
January 2025
Department of Cardiology, Zhongda Hospital, School of Medicine, Southeast University, 87 Dingjiaqiao, Nanjing 210009, China. Electronic address:
Treatment of myocardial ischemia-reperfusion (MI/R) injury still faces the lack of clinically approved drugs. Apelin-13 is a highly promising drug candidate of MI/R injury, but hampered by its extremely short half-life in plasma. This calls for efficient and smart delivering system for Apelin-13 delivery, but has not been reported.
View Article and Find Full Text PDFFront Genet
January 2025
Center of Cellular and Genetic Science, Henan Academy of Sciences, Zhengzhou, China.
High-altitude adaptation is a remarkable example of natural selection, yet the genomic and physiological adaptation mechanisms of Ethiopian highlanders remain poorly understood compared to their Andean and Tibetan counterparts. Ethiopian populations, such as the Amhara and Oromo, exhibit unique adaptive strategies characterized by moderate hemoglobin levels and enhanced arterial oxygen saturation, indicating distinct mechanisms of coping with chronic hypoxia. This review synthesizes current genomic insights into Ethiopian high-altitude adaptation, identifying key candidate genes involved in hypoxia tolerance and examining the influence of genetic diversity and historical admixture on adaptive responses.
View Article and Find Full Text PDFSmall
January 2025
Department of Nano-scale Semiconductor Engineering, Hanyang University, Seoul, 04763, Republic of Korea.
Spiking neurons are essential for building energy-efficient biomimetic spatiotemporal systems because they communicate with other neurons using sparse and binary signals. However, the achievable high density of artificial neurons having a capacitor for emulating the integrate function of biological neurons has a limit. Furthermore, a low-voltage operation (<1.
View Article and Find Full Text PDFJMIR Form Res
January 2025
1, Department of Health Administration, College of Software and Digital Healthcare Convergence, Yonsei University, Changjogwan, Yonseidae-gil 1, Wonju, 26493, Republic of Korea, +82 (0) 33-760-2257.
Background: Diabetes is prevalent in older adults, and machine learning algorithms could help predict diabetes in this population.
Objective: This study determined diabetes risk factors among older adults aged ≥60 years using machine learning algorithms and selected an optimized prediction model.
Methods: This cross-sectional study was conducted on 3084 older adults aged ≥60 years in Seoul from January to November 2023.
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