Molecular phylogeny of Parapenaeopsis Alcock, 1901 (Decapoda: Penaeidae) based on Chinese materials and 16S rDNA and COI sequence

Li, Xinzheng; Xu, Ying; Kou, Qi

doi:10.1007/s11802-014-2272-7

Cited by 9 publications

(3 citation statements)

References 21 publications

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“…There are several mechanisms of MeHg toxicity suggested, involving several biological processes. These processes include increased lipid peroxidation, reactive oxygen species (ROS) generation and glutathione (GSH) depletion in vivo and in vitro ( Crespo-López et al, 2009 ), reduced cell membrane integrity ( Polunas et al, 2011 ), altered cell signalling ( Worth et al, 2001 ), mitochondrial impacts ( Dreiem et al, 2005 ), altered DNA repair ( Pieper et al, 2014 ), immunomodulatory impacts ( Li et al, 2014 ), affected regulation of Ca 2+ ( Aschner et al, 2007 ), and changed DNA methylation (DNAm), as well as other epigenetics marks ( Farina et al, 2011 ; Cardenas et al, 2017a ; Khan et al, 2019 ). As a consequence of the epigenetics changes, several genes involved in response to oxidative stress, stress response, metabolism, transport, gene regulation, inflammatory response, apoptosis, and hormone regulation, have been associated with differential expression in human cells exposed to MeHg ( Yang et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

DNA methylation changes associated with prenatal mercury exposure: A meta-analysis of prospective cohort studies from PACE consortium

Lozano

Yousefi

Broberg

et al. 2022

Environmental Research

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Section: Introductionmentioning

confidence: 99%

DNA methylation changes associated with prenatal mercury exposure: A meta-analysis of prospective cohort studies from PACE consortium

Lozano

Yousefi

Broberg

et al. 2022

Environmental Research

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“…The conserved regions are not significantly different among microbial species, while the hypervariable regions showed species specificity which altered with the difference of affiliation. At present, 16S rDNA sequencing technology has been widely used in microbial diversity research on animal flora, such as nematodes (Razia, Karthikraja, Padmanaban, Chellapandi, & Sivaramakrishnan, ), pigs (Qin et al., ), planthoppers (Yeh, Yang, & Hui, ), shrimps (Li, Xu, & Kou, ), fish (Pandey & Rajagopal, ), cattle and sheep (Gamal, Ahmed, Ahmed, & Teleb, ), bacterial and fungal pathogens, such as Cucumber wilt (Du et al., ), bacteremia (Alfonso et al., ), otitis media (Priit & Jelena, ), as well as soil microbial (Rana, Nidhal, & Abed, ), acid mine (Xie et al., ), and biological desulfurization (Lv et al., ). Besides, 16S rDNA is also considered as an important indicator for the classification of microorganisms in fermented foods such as industrial vinegar (Trček, Lipoglavšek, & Avguštin, ; Trček, Mahnič, & Rupnik, ), Chinese cereal vinegar (Li et al., ), grain vinegar (Wang, Zhang, & Gui, ), coconut vinegar (Mohamad, Yeap, & Ky, ), wine‐soaked vinegar (Trček et al., , ), apple vinegar (Štornik, Skok, & Trček, ), and other food microbial fermentation products.…”

Section: Introductionmentioning

confidence: 99%

Analysis of microbial diversity in apple vinegar fermentation process through 16s rDNA sequencing

Song

Zhang

Kang

et al. 2019

Food Science & Nutrition

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Based on SPME‐GC‐MS analysis, it could be found that the production of acetic acid, phenethyl acetate, and isoamyl acetate gradually increased in the apple vinegar fermentation broth with the fermentation time. Consequently, in order to systematically explore the dynamic changes of microbial diversity and metabolites in the process of apple vinegar fermentation, 16S rDNA were sequenced and analyzed in this work. The present results showed that bacterial diversity was rich and exhibited a certain variation during the dynamic fermentation process of apple vinegar. Furthermore, Lactococcus and Oenococcus were the predominant bacteria in the pre‐fermentation (alcoholic fermentation) of apple vinegar, while the dominant bacteria in the middle and late fermentation stages (acetic acid fermentation) were Lactococcus and Acetobacter . In addition, during the whole fermentation process of apple vinegar, Lactococcus was the most dominant bacteria, Oenococcus was the unique species in the stage of alcohol fermentation, and Acetobacter increased rapidly in the stage of acetic acid fermentation. In conclusion, our finding provided a theoretical basis for the processing technology of apple vinegar fermentation, and a theory evidence for the safety and health assessment of apple vinegar.

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“…Currently, the dual-number theory is mainly applied in the spatial mechanisms, robot design, matrix mechanics, and spacecraft pilot. Li [4] pointed out the importance of the theory in the spatial mechanisms and robot design. Zhang [5] described the displacement relationship in the spatial mechanisms using the dual-number conception.…”

Section: Introductionmentioning

confidence: 99%

New data assimilation system DNDAS for high-dimensional models

et al. 2016

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The tangent linear (TL) models and adjoint (AD) models have brought great difficulties for the development of variational data assimilation system. It might be impossible to develop them perfectly without great efforts, either by hand, or by automatic differentiation tools. In order to break these limitations, a new data assimilation system, dual-number data assimilation system (DNDAS), is designed based on the dual-number automatic differentiation principles. We investigate the performance of DNDAS with two different optimization schemes and subsequently give a discussion on whether DNDAS is appropriate for high-dimensional forecast models. The new data assimilation system can avoid the complicated reverse integration of the adjoint model, and it only needs the forward integration in the dual-number space to obtain the cost function and its gradient vector concurrently. To verify the correctness and effectiveness of DNDAS, we implemented DNDAS on a simple ordinary differential model and the Lorenz-63 model with different optimization methods. We then concentrate on the adaptability of DNDAS to the Lorenz-96 model with high-dimensional state variables. The results indicate that whether the system is simple or nonlinear, DNDAS can accurately reconstruct the initial condition for the forecast model and has a strong anti-noise characteristic. Given adequate computing resource, the quasi-Newton optimization method performs better than the conjugate gradient method in DNDAS.

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Molecular phylogeny of Parapenaeopsis Alcock, 1901 (Decapoda: Penaeidae) based on Chinese materials and 16S rDNA and COI sequence

Cited by 9 publications

References 21 publications

DNA methylation changes associated with prenatal mercury exposure: A meta-analysis of prospective cohort studies from PACE consortium

DNA methylation changes associated with prenatal mercury exposure: A meta-analysis of prospective cohort studies from PACE consortium

Analysis of microbial diversity in apple vinegar fermentation process through 16s rDNA sequencing

New data assimilation system DNDAS for high-dimensional models

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