Bin Du

Bio: Bin Du is an academic researcher from Hebei Normal University of Science and Technology. The author has contributed to research in topics: Medicine & Chemistry. The author has an hindex of 19, co-authored 40 publications receiving 1463 citations. Previous affiliations of Bin Du include Hong Kong Baptist University.

Anti-inflammatory effects of phytochemicals from fruits, vegetables, and food legumes: A review

Abstract: Inflammation is the first biological response of the immune system to infection, injury or irritation. Evidence suggests that the anti-inflammatory effect is mediated through the regulation of various inflammatory cytokines, such as nitric oxide, interleukins, tumor necrosis factor alpha-α, interferon gamma-γ as well as noncytokine mediator, prostaglandin E2. Fruits, vegetables, and food legumes contain high levels of phytochemicals that show anti-inflammatory effect, but their mechanisms of actions have not been completely identified. The aim of this paper was to summarize the recent investigations and findings regarding in vitro and animal model studies on the anti-inflammatory effects of fruits, vegetables, and food legumes. Specific cytokines released for specific type of physiological event might shed some light on the specific use of each source of phytochemicals that can benefit to counter the inflammatory response. As natural modulators of proinflammatory gene expressions, phytochemical from fruits, vegetables, and food legumes could be incorporated into novel bioactive anti-inflammatory formulations of various nutraceuticals and pharmaceuticals. Finally, these phytochemicals are discussed as the natural promotion strategy for the improvement of human health status. The phenolics and triterpenoids in fruits and vegetables showed higher anti-inflammatory activity than other compounds. In food legumes, lectins and peptides had anti-inflammatory activity in most cases. However, there are lack of human study data on the anti-inflammatory activity of phytochemicals from fruits, vegetables, and food legumes.

Skin Health Promotion Effects of Natural Beta‐Glucan Derived from Cereals and Microorganisms: A Review

Abstract: β-Glucans are natural cell wall polysaccharides found in yeast, fungi (including mushrooms), some bacteria, seaweeds and cereals. Natural β-glucans possess many health promotion effects on human health, such as anti-tumor, anti-diabetes, anti-infection, lowering blood cholesterol and immune-modulating properties. These effects have been reviewed previously. However, skin health promotion of β-glucan derived from cereals and microorganisms has received little attention. This review focuses on antioxidant activity, anti-wrinkle activity, anti-ultraviolet light, wound healing, and moisturizing effect and skin permeation absorption of β-glucan. Furthermore, applications of β-glucan in cosmetics are also discussed.

eMedicine

Abstract: eMedicine创建于1996年，由近万名临床医师作为作者或编辑参与此临床医学知识库的建设，其中编辑均是来自美国哈佛、耶鲁、斯坦福、芝加哥、德克萨斯、加州大学等各分校医学院的教授或副教授。

Dietary Choices and Habits during COVID-19 Lockdown: Experience from Poland.

Abstract: The outbreak of coronavirus disease (COVID-19) in late December 2019 in China, which later developed into a pandemic, has forced different countries to implement strict sanitary regimes and social distancing measures. Globally, at least four billion people were under lockdown, working remotely, homeschooling children, and facing challenges coping with quarantine and the stressful events. The present cross-sectional online survey of adult Poles (n = 1097), conducted during a nationwide quarantine, aimed to assess whether nutritional and consumer habits have been affected under these conditions. Over 43.0% and nearly 52% reported eating and snacking more, respectively, and these tendencies were more frequent in overweight and obese individuals. Almost 30% and over 18% experienced weight gain (mean ± SD 3.0 ± 1.6 kg) and loss (−2.9 ± 1.5 kg), respectively. Overweight, obese, and older subjects (aged 36–45 and >45) tended to gain weight more frequently, whereas those with underweight tended to lose it further. Increased BMI was associated with less frequent consumption of vegetables, fruit, and legumes during quarantine, and higher adherence to meat, dairy, and fast-foods. An increase in alcohol consumption was seen in 14.6%, with a higher tendency to drink more found among alcohol addicts. Over 45% of smokers experienced a rise in smoking frequency during the quarantine. The study highlights that lockdown imposed to contain an infectious agent may affect eating behaviors and dietary habits, and advocates for organized nutritional support during future epidemic-related quarantines, particularly for the most vulnerable groups, including overweight and obese subjects.

Addressing accuracy and precision issues in iTRAQ quantitation

Abstract: iTRAQ (isobaric tags for relative or absolute quantitation) is a mass spectrometry technology that allows quantitative comparison of protein abundance by measuring peak intensities of reporter ions released from iTRAQ-tagged peptides by fragmentation during MS/MS. However, current data analysis techniques for iTRAQ struggle to report reliable relative protein abundance estimates and suffer with problems of precision and accuracy. The precision of the data is affected by variance heterogeneity: low signal data have higher relative variability; however, low abundance peptides dominate data sets. Accuracy is compromised as ratios are compressed toward 1, leading to underestimation of the ratio. This study investigated both issues and proposed a methodology that combines the peptide measurements to give a robust protein estimate even when the data for the protein are sparse or at low intensity. Our data indicated that ratio compression arises from contamination during precursor ion selection, which occurs at a consistent proportion within an experiment and thus results in a linear relationship between expected and observed ratios. We proposed that a correction factor can be calculated from spiked proteins at known ratios. Then we demonstrated that variance heterogeneity is present in iTRAQ data sets irrespective of the analytical packages, LC-MS/MS instrumentation, and iTRAQ labeling kit (4-plex or 8-plex) used. We proposed using an additive-multiplicative error model for peak intensities in MS/MS quantitation and demonstrated that a variance-stabilizing normalization is able to address the error structure and stabilize the variance across the entire intensity range. The resulting uniform variance structure simplifies the downstream analysis. Heterogeneity of variance consistent with an additive-multiplicative model has been reported in other MS-based quantitation including fields outside of proteomics; consequently the variance-stabilizing normalization methodology has the potential to increase the capabilities of MS in quantitation across diverse areas of biology and chemistry.