These findings suggest a glucose-lowering effect of curcuminoids in type 2 diabetes, which is partially due to decrease in serum FFAs, which may result from promoting fatty acid oxidation and utilization.
Polyphenol oxidase (PPO) activity is highly related to the undesirable browning of wheat-based end products, especially Asian noodles. Characterization of PPO genes and the development of their functional markers are of great importance for marker-assisted selection in wheat breeding. In the present study, complete genomic DNA sequences of two PPO genes, one each located on chromosomes 2A and 2D and their allelic variants were characterized by means of in silico cloning and experimental validation. Sequences were aligned at both DNA and protein levels. Two haplotypes on chromosome 2D showed 95.2% sequence identity at the DNA level, indicating much more sequence diversity than those on chromosome 2A with 99.6% sequence identity. Both of the PPO genes on chromosomes 2A and 2D contain an open reading frame (ORF) of 1,731 bp, encoding a PPO precursor peptide of 577 amino acids with a predicted molecular mass of approximately 64 kD. Two complementary dominant STS markers, PPO16 and PPO29, were developed based on the PPO gene haplotypes located on chromosome 2D; they amplify a 713-bp fragment in cultivars with low PPO activity and a 490-bp fragment in those with high PPO activity, respectively. The two markers were mapped on chromosome 2DL using a doubled haploid population derived from the cross Zhongyou 9507/CA9632, and a set of nullisomic-tetrasomic lines and ditelosomic line 2DS of Chinese Spring. QTL analysis indicated that the PPO gene co-segregated with the two STS markers and was closely linked to SSR marker Xwmc41 on chromosome 2DL, explaining from 9.6 to 24.4% of the phenotypic variance for PPO activity across three environments. In order to simultaneously detect PPO loci on chromosomes 2A and 2D, a multiplexed marker combination PPO33/PPO16 was developed and yielded distinguishable DNA patterns in a number of cultivars. The STS marker PPO33 for the PPO gene on chromosome 2A was developed from the same gene sequences as PPO18 that we reported previously, and can amplify a 481-bp and a 290-bp fragment from cultivars with low and high PPO activity, respectively. A total of 217 Chinese wheat cultivars and advanced lines were used to validate the association between the polymorphic fragments and grain PPO activity. The results showed that the marker combination PPO33/PPO16 is efficient and reliable for evaluating PPO activity and can be used in wheat breeding programs aimed for noodle and other end product quality improvement.
The global COVID-19 outbreak is worrisome both for its high rate of spread, and the high case fatality rate reported by early studies and now in Italy. We report a new methodology, the Patient Information Based Algorithm (PIBA), for estimating the death rate of a disease in real-time using publicly available data collected during an outbreak. PIBA estimated the death rate based on data of the patients in Wuhan and then in other cities throughout China. The estimated days from hospital admission to death was 13 (standard deviation (SD), 6 days). The death Science of the Total Environment 727 (2020) 138394 rates based on PIBA were used to predict the daily numbers of deaths since the week of February 25, 2020, in China overall, Hubei province, Wuhan city, and the rest of the country except Hubei province. The death rate of COVID-19 ranges from 0.75% to 3% and may decrease in the future. The results showed that the real death numbers had fallen into the predicted ranges. In addition, using the preliminary data from China, the PIBA method was successfully used to estimate the death rate and predict the death numbers of the Korean population. In conclusion, PIBA can be used to efficiently estimate the death rate of a new infectious disease in real-time and to predict future deaths. The spread of 2019-nCoV and its case fatality rate may vary in regions with different climates and temperatures from Hubei and Wuhan. PIBA model can be built based on known information of early patients in different countries.
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