Eight previously unreported glycosides, designated gomphandranosides I-VIII, along with nine known compounds, were isolated from the roots of Gomphandra mollis Merr. Their structures were elucidated through comprehens...
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Eight previously unreported glycosides, designated gomphandranosides I-VIII, along with nine known compounds, were isolated from the roots of Gomphandra mollis Merr. Their structures were elucidated through comprehensive spectroscopic analyses, including NMR, HR-ESI-MS, Cd, dP4+ probability, and ECd calculations. The anti-inflammatory activities of the isolated compounds were assessed using nitric oxide inhibition assays in LPS-stimulated RAW264.7 macrophages. Compounds 5, 10, and 16 exhibited significant anti-inflammatory activity with IC values of 7.56 ± 0.9, 15.0 ± 1.2, and 14.2 ± 0.9 μM, respectively. Network pharmacology, gene ontology, Kyoto Encyclopedia of Genes and Genomes analysis, and molecular docking studies identified IL-6, TNF-α, MMP9, PTGS2, and HIF1A as key targets, with potentially involved in the NF-κB and IL-17 signaling pathways. These findings highlight G. mollis as a promising candidate for the treatment of inflammation-relateddiseases.
Saccharomyces cerevisiae is the most commonly used yeast in the fermentation process on high starch/carbohydrate substrates, for example, cassava pulp, a by-product from the tapioca industry. In addition to the pure c...
Saccharomyces cerevisiae is the most commonly used yeast in the fermentation process on high starch/carbohydrate substrates, for example, cassava pulp, a by-product from the tapioca industry. In addition to the pure culture of S. cerevisiae, the fermentation process of cassava pulp can be done using tape yeast (a consortium of yeast, fungal and bacteria). The objective of this research was to study the growth kinetics of S. cerevisiae and tape yeast on cassava pulp fermentation. The growth kinetics of Saccharomyces cerevisiae and tape yeast was observed through cells number, rate of starch degradation, rate of dietary fiber degradation, rate of cyanide degradation, and rate of protein formation. The research showed that the S. cerevisiae pure culture could grow better during cassava pulp fermentation compared to tape yeast, which is reflected by the logarithmic growth rate (up to 72 h versus 48 h). The difference in the growth rate between S. cerevisiae pure culture and tape yeast will cause a difference in starch degradation rate (73.02 mg/h versus 65.09 mg/h), dietary fiber degradation rate (87.33 mg/h versus 21.09 mg/h), cyanide degradation rate (92.57.10−2 ppm/h versus 97.49.10−2 ppm/h), protein formation rate (48.92 mg/h versus 50.08 mg/h).
The association between metal mixtures and kidney function has been reported. However, reports on the mechanism of metal toxicity were limited. Oxidative stress was reported as a possible cause. This study aimed to de...
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The association between metal mixtures and kidney function has been reported. However, reports on the mechanism of metal toxicity were limited. Oxidative stress was reported as a possible cause. This study aimed to determine the association between of kidney function and metals, such as arsenic (As), cadmium (Cd), cobalt (Co), copper (Cu), lead (Pb), selenium (Se), and zinc (Zn), and to explore the possible mediating role of tumor necrosis factor alpha (TNF-α) between metal toxicity and kidney function. In this study, we recruited 421 adults from a health examination. The concentration of blood metals was analyzed using inductively coupled plasma mass spectrometry. We used linear regression models to assess the association between metals and TNF-α. Then, mediation analysis was applied to investigate the relationship between metal exposure, TNF-α, and kidney function. In univariate linear regression, blood As, Cd, Co, Cu, Pb, and Zn levels significantly increased TNF-α anddecreased kidney function. Higher blood As and Pb levels significantly increased TNF-α in multivariable linear regressions after adjusting for covariates. We found that blood levels of As (coefficients = -0.021, p = 0.011), Pb (coefficients = -0.060, p < 0.001), and Zn (coefficients = -0.230, p < 0.001) showed a significant negative association with eGFR in the multiple-metal model. Furthermore, mediation analysis showed that TNF-α mediated 41.7 %, 38.8 %, and 20.8 % of blood Cd, As and Pb, respectively. Among the essential elements, TNF-α mediated 24.5 %, 21.5 % and 19.9 % in the effects of blood Co, Cu, and Zn on kidney function, respectively. TNF-α, acting as a mediator, accounted for 20.1 % of the contribution between the WQS score of metal mixtures and the eGFR (p < 0.001). This study suggested that TNF-α may be a persuasive pathway mediating the association between metals and kidney function. Inflammation and kidney injury could be the underlying mechanisms of metal exposure. However, there i
This paper implements an automatic birddata capture system which uploads data captured from social network websites to the server and stores them in the database. When using the Facebook API to capture data of intere...
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This paper implements an automatic birddata capture system which uploads data captured from social network websites to the server and stores them in the database. When using the Facebook API to capture data of interest, the system needs to filter the captureddata to avoid false data storage. This paper takes building an automatic system that includes reinforcing the training database of the bird community as a top priority.
In the original publication of the article, the first author name was incorrectly published as “Benyamin Ghoreishii”. However, the correct name is “Benyamin Ghoreishi”. The original article has been corrected.
In the original publication of the article, the first author name was incorrectly published as “Benyamin Ghoreishii”. However, the correct name is “Benyamin Ghoreishi”. The original article has been corrected.
Thanks to advances in wireless communication technologies, the wireless sensor network (WSNs) have been attracting a lot of attention from academic communities and successfully applied to various domains. Along with d...
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Thanks to advances in wireless communication technologies, the wireless sensor network (WSNs) have been attracting a lot of attention from academic communities and successfully applied to various domains. Along with developments of the Industry 4.0, the WSNs start to play a vital role in the construction of smart factories and realization of intelligent manufacturing. Although, the industrial WSNs (IWSNs) presents great quantity of advantages, there still have some drawbacks to overcome such as challenges of the quality of data for IWSNs. In order to resolve the data missing problems in the context of IWSNs, the Last Observation Carried Forward method is adopted to estimate the missing value and reconstruct the sensing dataset which takes into account the temporal characteristics of sensing data in IWSNs. Through experiments, this method is proved to be an easy and effective measurement for missing value imputation of the large multi-dimensional sensing data achieved by the IWSNs.
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