Publications

Abstract Thermal processing is the most important and popular domestic cooking method. More than 30 heterocyclic aromatic amines have been identified in cooked meat using various methods. This review highlights preventive potential and mechanism of dietary polyphenols on the formation of heterocyclic amines. Tea, coffee, fruits, vegetable, and spice extracts rich in polyphenols exerted significant inhibition against the formation of heterocyclic aromatic amines. Some polyphenols, such as naringenin and epigallocatechin 3‐O‐gallate, can actively participate into food chemistry reaction to trap Strecker aldehyde and lower the formation of heterocyclic aromatic amines. In addition, some polyphenols can lower the mutagenicity of heterocyclic aromatic amines. More specifically, polyphenols possessing two hydroxyl groups at the meta position of aromatic ring are the most efficient one, but the presence of carboxylic or alkyl groups as substituents in the aromatic ring slightly reduced the inhibitory effect.

<i>Moringa oleifera</i> Lam. is a perennial tropical deciduous tree with high economic and pharmaceutical value. As an edible plant, <i>M. oleifera</i> Lam. is rich in nutrients, such as proteins, amino acids, mineral elements and vitamins. Besides, it also contains an important number of bioactive phytochemicals, such as polysaccharides, flavonoids, alkaloids, glucosinolates and isothiocyanates. <i>M. oleifera</i> for long has been used as a natural anti-diabetic herb in India and other Asian countries. Thus, the anti-diabetic properties of Moringa plant have evolved highly attention to the researchers. In the last twenty years, a huge number of new chemical structures and their pharmacological activities have been reported in particularly the anti-diabetic properties. The current review highlighted the bioactive phytochemicals from <i>M. Oleifera</i>. Moreover, evidence regarding the therapeutic potential of <i>M. oleifera</i> for diabetes including experimental and clinical data was presented and the underlying mechanisms were revealed in order to provide insights for the development of novel drugs.

Abstract A detailed understanding of how and when SARS-CoV-2 transmission occurs is crucial for designing effective prevention measures. Other than contact tracing, genome sequencing provides information to help infer who infected whom. However, the effectiveness of the genomic approach in this context depends on both (high enough) mutation and (low enough) transmission rates. Today, the level of resolution that we can obtain when describing SARS-CoV-2 outbreaks using just genomic information alone remains unclear. In order to answer this question, we sequenced 49 SARS-CoV-2 patient samples from ten local clusters for which partial epidemiological information was available, and inferred transmission history using genomic variants. Importantly, we obtained high-quality genomic data, sequencing each sample twice and using unique barcodes to exclude cross-sample contamination. Phylogenetic and cluster analyses showed that consensus genomes were generally sufficient to discriminate among independent transmission clusters. However, levels of intrahost variation were low, which prevented in most cases the unambiguous identification of direct transmission events. After filtering out recurrent variants across clusters, the genomic data were generally compatible with the epidemiological information but did not support specific transmission events over possible alternatives. We estimated the effective transmission bottleneck size to be 1-2 viral particles for sample pairs whose donor-recipient relationship was likely. Our analyses suggest that intrahost genomic variation in SARS-CoV-2 might be generally limited and that homoplasy and recurrent errors complicate identifying shared intrahost variants. Reliable reconstruction of direct SARS-CoV-2 transmission based solely on genomic data seems hindered by a slow mutation rate, potential convergent events, and technical artifacts. Detailed contact tracing seems essential in most cases to study SARS-CoV-2 transmission at high resolution.