Quantitative proteomic analysis for characterization of protein components related to dough quality and celiac disease in wheat flour, dough, and heat-treated dough.

High-sensitivity 4D label-free proteomic technology was used to identify protein components related to gluten quality and celiac disease (CD) in strong-gluten wheat cultivar KX 3302 and medium-gluten wheat cultivar BN 207. The highly expressed storage protein components in KX3302 were high-molecular-weight-glutenin-subunits (HMW-GSs), α-gliadin, and globulin, whereas those in BN207 were γ-gliadin, low-molecular-weight-glutenin-subunits (LMW-GSs) and avenin-like proteins. In addition, BN207 had more upregulated metabolic proteins than KX3302. The abundance of storage proteins increased during dough formation. After heat treatment, the upregulated proteins accounted for 57.53 % of the total proteins, but the downregulated storage proteins accounted for 79.34 % of the total storage proteins. In cultivar KX3302, CD proteins mainly included α-gliadin and HMW-GSs, whereas in BN207, they were mainly γ-gliadin and LMW-GSs. Thermal treatment significantly reduces the expression levels of CD-related proteins. These findings provide a new perspective on reducing the content of CD-related proteins in wheat products.

Metabolite identification in fresh wheat grains of different colors and the influence of heat processing on metabolites via targeted and non-targeted metabolomics.

Phenolic antioxidants are phytochemical components in wheat grains that provide a variety of potential health benefits. The metabolites and antioxidant activity of fresh, mature, and heat-treated, wheat grains with black, blue, purple, and white grain coats were identified by targeted and non-targeted metabolomics. The total phenolic (TPC) and flavonoid contents (TFC) and antioxidant activity (AOA) increased with the darkening of grain color, the general trend being black > purple > blue > white. Purple and black wheat are rich in rutin (3916 µg/kg and 3066 µg/kg, respectively) and peonidin-3-O-glucoside chloride (2595 µg/kg and 1740 µg/kg, respectively), while blue wheat is rich in luteolin (2076 µg/kg). In most cases, TPC, TFC, and AOA had the greatest values in fresh grains and the lowest values in mature grains. Using non-targeted metabolomics, a total of 866 metabolites were identified in the tested fresh wheat grains, 106 flavonoids and 39 phenolic acids. In total, the relative abundance of flavonoids in purple and black wheat was higher than in blue wheat, indicating a higher nutritional value of fresh black and purple grains. After heat processing, the content of most metabolites decreased in heat-treated purple grain, whereas heat treatment significantly increased the content of peonidin-3-O-glucoside chloride (2.27-fold) and cynaroside (12.01-fold). This study clarifies that seed coat color and processing treatments impact the metabolite contents and antioxidant activity of wheat grains, providing valuable information for improving the nutritional quality of food during processing.

Dynamic Metabolomics and Transcriptomics Analyses for Characterization of Phenolic Compounds and Their Biosynthetic Characteristics in Wheat Grain.

Phenolic compounds are important bioactive phytochemicals with potential health benefits. In this study, integrated metabolomics and transcriptomics analysis was used to analyze the metabolites and differentially expressed genes in grains of two wheat cultivars (HPm512 with high antioxidant activity, and ZM22 with low antioxidant activity) during grain development. A total of 188 differentially expressed phenolic components, including 82 phenolic acids, 81 flavonoids, 10 lignans, and 15 other phenolics, were identified in the developing wheat grains, of which apigenin glycosides were identified as the primary flavonoid component. The relative abundance of identified phenolics showed a decreasing trend with grain development. Additionally, 51 differentially expressed phenolic components were identified between HPm512 and ZM22, of which 41 components, including 23 flavonoids, were up-regulated in HPm512. In developing grain, most of the identified differentially expressed genes involved in phenolic accumulation followed a similar trend. Integrated metabolomics and transcriptomics analysis revealed that certain genes encoding structural proteins, glycosyltransferase, and transcription factors were closely related to metabolite accumulation. The relatively higher accumulation of phenolics in HPm512 could be due to up-regulated structural and regulatory genes. A sketch map was drawn to depict the synthetic pathway of identified phenolics and their corresponding genes. This study enhanced the current understanding of the accumulation of phenolics in wheat grains. Besides, active components and their related genes were also identified, providing crucial information for the improvement of wheat's nutritional quality.

Wheat grain phenolics: a review on composition, bioactivity, and influencing factors.

Wheat (Triticum aestivum L.) is a widely cultivated crop and one of the most commonly consumed food grains in the world. It possesses several nutritional elements. Increasing attention to wheat grain phenolics bioactivity is due to the increasing demand for foods with natural antioxidants. To provide a comprehensive understanding of phenolics in wheat grain, this review first summarizes the phenolics' form and distribution and the phenolic components identified in wheat grain. In particular, the biosynthesis path for phenolics is discussed, identifying some candidate genes involved in the biosynthesis of phenolic acids and flavonoids. After discussing the methods for determining antioxidant activity, the effect of genotypes, environmental conditions, and cultivation systems on grain phenolic component content are explored. Finally, the bioavailability of phenolics under different food processing method are reported and discussed. Future research is recommended to increase wheat grain phenolic content by genetic engineering, and to improve its bioavailability through proper food processing. © 2021 Society of Chemical Industry.

Patient expectations and awareness of information regarding adverse reactions in drug labelling in China.

Background The misunderstanding of adverse drug reaction labelling information is not conducive to the rational use of drugs. There has been no research on how doctors can effectively transmit information on adverse drug reactions to patients in China. Objective To assess how well patients understand the adverse reactions presented in the labelling of drugs and how much information they want from their doctor regarding the adverse reactions. Setting The study was conducted in secondary medical institutions, tertiary medical institutions and community healthcare centres in Shanghai. Method A cross-sectional self-administered survey was conducted from November 2018 to March 2019. Mixed methods involving paper questionnaires and online surveys (scan a QR code by the WeChat app) were used. Main outcome measure Participants' demand for adverse reaction information. Results A total of 295 people completed the questionnaires, of which 31.8% of people thought that the greater the number of adverse reactions listed on the label of a drug, the more insecure they felt about that drug. At the same time, 30.13% of people thought that if the adverse reactions listed on a label were undefined, then the drug was safe for use (for example, some Chinese patent medicines). Most of the respondents (45.4%) thought that it was better to give a brief description of possible adverse reactions and to answer patients' questions in detail only if necessary. Conclusions Most patients wanted doctors to give them a brief introduction to serious and common adverse reactions when they prescribed drugs, and only a small percentage of people wanted to obtain all the information about adverse reactions. It was found that many people misunderstood the contents of the adverse reactions provided on the labels and equated the number of adverse reactions with drug safety.

Limited Sampling Strategy for the Estimation of Tacrolimus Area Under the Concentration-Time Curve in Chinese Adult Liver Transplant Patients.

OBJECTIVES: Limited sampling strategies (LSS) have been proposed as an alternative method for estimating area under concentration-time curve (AUC) of immunosuppressive agent tacrolimus (TAC). In this study, we aimed to develop the LSS models for predicting AUC of TAC in Chinese liver transplant patients. METHODS: Twenty-eight adult liver transplant patients receiving immunosuppressive regimen including TAC were enrolled. A total of 47 pharmacokinetic profiles were obtained after 1 or 3 weeks therapy. TAC concentrations were determined before dose (0 h) and at 1, 1.5, 2, 2.5, 3, 4, 6, 8 and 12 h after dosing by LC-MS/MS assay. Optimal subset regression analysis was used to establish the models for estimating TAC AUC0-12. Prediction error (PE) and absolute PE were calculated. The agreement between predicted and measured AUC0-12 was investigated by Bland-Altman analysis. The obtained models were validated by bootstrap analysis. The prediction performance among various CYP3A5 and ABCB1 genotypes was compared. The models selected from previous published studies were also validated using our data. RESULTS: Twenty-eight models including 1, 2, 3 and 4 blood time points sampling were established (r2 = 0.653-0.979). The best model for prediction of TAC AUC0-12 was 0.81 + 1.73C1 + 1.32C2 + 3.87C4 + 3.75C8 (r2 = 0.979). Forty profiles (85.1%) had estimated TAC AUC0-12 within ±15% of observed TAC AUC0-12. Model with C0-C2 (r2 = 0.880) can be used for outpatients who need monitoring to be carried out in a short period. We also found that ABCB1 genotype may be a reason of variation in the prediction performance. There was good correlation between predicted and measured AUC0-12 (r2 = 0.880-0.928) by using models from previous studies with sample collected within 4 h post dose. CONCLUSION: The LSS is an effective approach for estimation of full TAC AUC0-12 in Chinese liver transplant patients.

Clinical pharmacy service practice in a Chinese tertiary hospital.

Clinical pharmacy service is focused on the rationality and safety of medication therapy. Clinical pharmacists play an important role in designing therapeutic regimen, preventing medication errors, reducing the incidence of adverse drug reaction, and saving medical costs. Although clinical pharmacy service in China is in its early stage, its development is rapid. In this manuscript, the working model of clinical pharmacists in a Chinese tertiary hospital is introduced, including ward rounds, consultation, stewardship of antimicrobial therapy, drug adverse reaction monitoring, therapeutic drug monitoring, clinical pharmacokinetics and pharmacogenetics, and training system. With the efforts of clinical pharmacists, there will be a significant increase in the optimization of medication therapy and a notable reduction in preventable adverse drug events as well as health-care cost in China.