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  1. Yu D, Zhang J, Li P, Zheng R, Shao C
    PLoS One, 2015;10(4):e0124825.
    PMID: 25875761 DOI: 10.1371/journal.pone.0124825
    he Chinese tiger frog Hoplobatrachus rugulosus is widely distributed in southern China, Malaysia, Myanmar, Thailand, and Vietnam. It is listed in Appendix II of CITES as the only Class II nationally-protected frog in China. The bred tiger frog known as the Thailand tiger frog, is also identified as H. rugulosus. Our analysis of the Cyt b gene showed high genetic divergence (13.8%) between wild and bred samples of tiger frog. Unexpected genetic divergence of the complete mt genome (14.0%) was also observed between wild and bred samples of tiger frog. Yet, the nuclear genes (NCX1, Rag1, Rhod, Tyr) showed little divergence between them. Despite this and their very similar morphology, the features of the mitochondrial genome including genetic divergence of other genes, different three-dimensional structures of ND5 proteins, and gene rearrangements indicate that H. rugulosus may be a cryptic species complex. Using Bayesian inference, maximum likelihood, and maximum parsimony analyses, Hoplobatrachus was resolved as a sister clade to Euphlyctis, and H. rugulosus (BT) as a sister clade to H. rugulosus (WT). We suggest that we should prevent Thailand tiger frogs (bred type) from escaping into wild environments lest they produce hybrids with Chinese tiger frogs (wild type).
  2. Pastorello G, Trotta C, Canfora E, Chu H, Christianson D, Cheah YW, et al.
    Sci Data, 2020 07 09;7(1):225.
    PMID: 32647314 DOI: 10.1038/s41597-020-0534-3
    The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.
  3. Pastorello G, Trotta C, Canfora E, Chu H, Christianson D, Cheah YW, et al.
    Sci Data, 2021 Feb 25;8(1):72.
    PMID: 33633116 DOI: 10.1038/s41597-021-00851-9
  4. Klionsky DJ, Abdel-Aziz AK, Abdelfatah S, Abdellatif M, Abdoli A, Abel S, et al.
    Autophagy, 2021 Jan;17(1):1-382.
    PMID: 33634751 DOI: 10.1080/15548627.2020.1797280
    In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.
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