Effects of different precursors on the structure of lignin-based biochar and its ability to adsorb benzopyrene from sesame oil.

Agricultural by-products of sesame are promising bioresources in food processing. This study extracted lignin from the by-products of sesame oil production, namely, the capsules and straw of black and white sesame. Using acid, alkali, and ethanol methods, 12 distinct lignins were obtained to prepare biochar, aiming to investigate both the structural characteristics of lignin-based biochar (LBB) and its ability to remove benzo[a]pyrene (BaP) from sesame oil. The results showed that white sesame straw was the most suitable raw material for preparing biochar. In terms of the preparation method, acid-extracted lignin biochar was more effective in removing BaP than alkaline or ethanol methods. Notably, WS-1LB (white sesame straw acid-extracted lignin biochar) exhibited the highest BaP adsorption efficiency (91.44 %) and the maximum specific surface area (1065.8187 m2/g), characterized by porous structures. The pseudo 2nd and Freundlich models were found to be the best fit for the adsorption kinetics and isotherms of BaP on LBB, respectively, suggesting that a multilayer adsorption process was dominant. The high adsorption of LBB mainly resulted from pore filling. This study provides an economical and highly efficient biochar adsorbent for the removal of BaP in oil.

Effect of Chinese quince proanthocyanidins on the inhibition of heterocyclic amines and quality of fried chicken meatballs and tofu.

Heterocyclic amines (HCAs) have potential carcinogenic and mutagenic activity and are generated in cooked protein-rich foods. Adding proanthocyanidins (PAs) to these foods before frying is an effective way to reduce HCAs. In this study, polymeric PAs (PPA) and ultrasound-assisted acid-catalyzed/catechin nucleophilic depolymerized PAs (UAPA, a type of oligomeric PA) were prepared from Chinese quince fruits (CQF). Different levels of PPA and UAPA (0.05%, 0.1%, and 0.15%) were added to chicken meatballs and tofu; then these foods were fried, and the content of HCAs in them after frying was investigated. The results showed that PPA and, particularly, UAPA significantly inhibited the formation of HCAs in fried meatballs and tofu, and this inhibition was dose-dependent. The inhibition of HCAs by both PPA and UAPA was stronger in the chicken meatballs than in fried tofu. The level of total HCAs was significantly reduced by 57.84% (from 11.93 to 5.03 ng/g) after treatment of meatballs with 0.15% UAPA, with inhibition rates of 78.94%, 50.37%, and 17.81% for norharman, harman, and 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP), respectively. Of note, there was a negative correlation between water, lipid, protein, creatine, and glucose content and HCA content in the crust, interior, and whole (crust-plus-interior) measurements of all fried samples. Interestingly, PPA and UAPA were found more effective in inhibiting HCAs in the exterior crust than in the interior of the fried chicken meatballs. These results provide evidence that further studies on the reduction of the formation of harmful HCAs in fried foods by adding CQF PAs could be valuable to the fried food industry. PRACTICAL APPLICATION: Chinese quince proanthocyanidins treatments significantly inhibited the generation of heterocyclic amines (HCAs) in chicken meatballs and tofu when deep-fried. These results suggest that Chinese quince proanthocyanidins can be used as natural food additive for reducing HCAs in fried foods, laying the foundation for using Chinese quince fruit proanthocyanidins for HCA inhibition in the food industry.

A Comprehensive Survey on Deep Graph Representation Learning.

Graph representation learning aims to effectively encode high-dimensional sparse graph-structured data into low-dimensional dense vectors, which is a fundamental task that has been widely studied in a range of fields, including machine learning and data mining. Classic graph embedding methods follow the basic idea that the embedding vectors of interconnected nodes in the graph can still maintain a relatively close distance, thereby preserving the structural information between the nodes in the graph. However, this is sub-optimal due to: (i) traditional methods have limited model capacity which limits the learning performance; (ii) existing techniques typically rely on unsupervised learning strategies and fail to couple with the latest learning paradigms; (iii) representation learning and downstream tasks are dependent on each other which should be jointly enhanced. With the remarkable success of deep learning, deep graph representation learning has shown great potential and advantages over shallow (traditional) methods, there exist a large number of deep graph representation learning techniques have been proposed in the past decade, especially graph neural networks. In this survey, we conduct a comprehensive survey on current deep graph representation learning algorithms by proposing a new taxonomy of existing state-of-the-art literature. Specifically, we systematically summarize the essential components of graph representation learning and categorize existing approaches by the ways of graph neural network architectures and the most recent advanced learning paradigms. Moreover, this survey also provides the practical and promising applications of deep graph representation learning. Last but not least, we state new perspectives and suggest challenging directions which deserve further investigations in the future.

Comparison of methods for activating sesame stalk lignin biochar for removing benzo[a]pyrene from sesame oil.

In this study, three activators and two activation methods were employed to activate sesame lignin-based biochar. The biochar samples were comprehensively characterized, their abilities to adsorb benzo[a]pyrene (BaP) from sesame oil were assessed, and the mechanism was analyzed. The results showed that the biochar obtained by one-step activation was more effective in removing BaP from sesame oil than the biochar produced by two-step activation. Among them, the biochar generated by one-step activation with ZnCl2 as the activator had the largest specific surface area (1068.8776 m3/g), and the richest mesoporous structure (0.7891 m3/g); it removed 90.53 % of BaP from sesame oil. BaP was mainly adsorbed by the mesopores of biochar. Mechanistically, pore-filling, π-π conjugations, hydrogen bonding, and n-π interactions were involved. The adsorption was spontaneous and heat-absorbing. In conclusion, the preparation of sesame lignin biochar using one-step activation with ZnCl2 as the activator was found to be the best for removing BaP from sesame oil. This biochar may be an economical adsorbent for the industrial removal of BaP from sesame oil.

Interaction between Chinese quince fruit proanthocyanidins and bovine serum albumin: Antioxidant activity, thermal stability and heterocyclic amine inhibition.

Heterocyclic amines (HCAs) are carcinogenic and mutagenic substances produced in fried meat. Adding natural antioxidants (e.g., proanthocyanidins (PAs)) is a common method to reduce HCAs; however, the interaction between the PAs and protein can affect the inhibitory efficacy of PAs on the formation of HCAs. In this study, two PAs (F1 and F2) with different degrees of polymerization (DP) were extracted from Chinese quince fruits. These were combined with bovine serum albumin (BSA). The thermal stability, antioxidant capacity and HCAs inhibition of all four (F1, F2, F1-BSA, F2-BSA) were compared. The results showed that F1 and F2 interact with BSA to form complexes. Circular dichroism spectra indicate that complexes had fewer α-helices and more ß-sheets, ß-turns and random coils than BSA. Molecular docking studies indicated that hydrogen bonds and hydrophobic interactions are the forces holding the complexes together. The thermal stabilities of F1 and, particularly, F2 were stronger than those of F1-BSA and F2-BSA. Interestingly, F1-BSA and F2-BSA showed increased antioxidant activity with increasing temperature. F1-BSA's and F2-BSA's HCAs inhibition was stronger than F1 and F2, reaching 72.06 % and 76.3 %, respectively, for norharman. This suggests that PAs can be used as natural antioxidants for reducing the HCAs in fried foods.

The chicken gut metagenome and the modulatory effects of plant-derived benzylisoquinoline alkaloids.

BACKGROUND: Sub-therapeutic antibiotics are widely used as growth promoters in the poultry industry; however, the resulting antibiotic resistance threatens public health. A plant-derived growth promoter, Macleaya cordata extract (MCE), with effective ingredients of benzylisoquinoline alkaloids, is a potential alternative to antibiotic growth promoters. Altered intestinal microbiota play important roles in growth promotion, but the underlying mechanism remains unknown. RESULTS: We generated 1.64 terabases of metagenomic data from 495 chicken intestinal digesta samples and constructed a comprehensive chicken gut microbial gene catalog (9.04 million genes), which is also the first gene catalog of an animal's gut microbiome that covers all intestinal compartments. Then, we identified the distinctive characteristics and temporal changes in the foregut and hindgut microbiota. Next, we assessed the impact of MCE on chickens and gut microbiota. Chickens fed with MCE had improved growth performance, and major microbial changes were confined to the foregut, with the predominant role of Lactobacillus being enhanced, and the amino acids, vitamins, and secondary bile acids biosynthesis pathways being upregulated, but lacked the accumulation of antibiotic-resistance genes. In comparison, treatment with chlortetracycline similarly enriched some biosynthesis pathways of nutrients in the foregut microbiota, but elicited an increase in antibiotic-producing bacteria and antibiotic-resistance genes. CONCLUSION: The reference gene catalog of the chicken gut microbiome is an important supplement to animal gut metagenomes. Metagenomic analysis provides insights into the growth-promoting mechanism of MCE, and underscored the importance of utilizing safe and effective growth promoters.

[Effects of platelet and fibrinogen on progressive ovarian cancer].

OBJECTIVE: To assess the effects of platelet and fibrinogen on progressive ovarian cancer. METHODS: The platelet counts and fibrinogen levels were measured in 180 initially treated ovarian cancer patients within 2 weeks before and 1 week after operation and 6 months after chemotherapy. The results were compared with those of 40 patients with epithelial ovarian neoplasms. RESULTS: The platelet counts and fibrinogen levels were significantly higher in ovarian cancer patients than in patients with epithelial ovarian neoplasms (P < 0.05), significantly higher in late stage than in early stage (P < 0.05), and significantly lower after operation than before operation (P < 0.05). The platelet counts and fibrinogen levels were also significantly lower 6 months after operation in patients who responded well to the therapies than the levels before operation (P < 0.05); however, such difference did not exist between patients who were refractory to the therapies 6 months after treatment and the post-operation levels (P > 0.05). CONCLUSIONS: Platelet and fibrinogen may be closely correlated with progressive ovarian cancer. Monitoring platelet counts and fibrinogen levels are instrumental for the early diagnosis of cancer and metastasis.