It is unclear whether different processing methods change the biological functions of foods and how these functions are evaluated in the human body. Here, steamed bread and baked bread, the traditional staple foods in China and many Western countries, were made by steaming and baking, respectively, using one piece of fermented wheat dough and then consumed by 16 healthy young volunteers. By detecting 38 cytokines, 12 metabolic enzymes, glucose, lactate, and nicotinamide adenine dinucleotide (NADH) in the serum, the cytokine network and central metabolic pathway network were investigated to compare the effects of the two staple foods on immunity and metabolism. Compared with steamed bread, baked bread increased (p < 0.05) concentrations of fractalkine and macrophage-derived chemokine, decreased (p < 0.05) the concentration of interleukin-1RA, increased (p < 0.05) the expression level of phosphofructokinase, and decreased (p < 0.05) the expression level of glucose-6-phosphate dehydrogenase in the serum. Two network analyses indicated that baked bread, as compared to the steamed bread, enhanced communication between immune cells, increased catabolism, and decreased anabolism. Further, a correlation analysis of cytokines and metabolic enzymes suggested that the two staple foods may affect metabolism by regulating the secretion of cytokines. These findings highlight how the same raw food material processed by different methods may have different impacts on immunity and metabolism in humans.

Background: High-protein diets can increase the colonic health risks. A moderate reduction of dietary crude-protein (CP) level can improve the colonic bacterial community and mucosal immunity of pigs. However, greatly reducing the dietary CP level, even supplemented with all amino acids (AAs), detrimentally affects the colonic health, which may be due to the lack of protein-derived peptides. Therefore, this study evaluated the effects of supplementation of casein hydrolysate (peptide source) in low-protein (LP) diets, in comparison with AAs supplementation, on the colonic microbiota, microbial metabolites and mucosal immunity in pigs, aiming to determine whether a supplementation of casein hydrolysate can improve colonic health under very LP level. Twenty-one pigs (initial BW 19.90 ± 1.00 kg, 63 ± 1 days of age) were assigned to three groups and fed with control diet (16% CP), LP diets (13% CP) supplemented with free AAs (LPA) or casein hydrolysate (LPC) for 4 weeks. Results: Compared with control diet, LPA and LPC diet decreased the relative abundance of Streptococcus and Escherichia coli, and LPC diet further decreased the relative abundance of Proteobacteria. LPC diet also increased the relative abundance of Lactobacillus reuteri. Both LP diets decreased concentrations of ammonia and cadaverine, and LPC diet also reduced concentrations of putrescine, phenol and indole. Moreover, LPC diet increased total short-chain fatty acid concentration. In comparison with control diet, both LP diets decreased protein expressions of Toll-like receptor-4, nuclear factor-κB, interleukin-1β and tumor necrosis factor-α, and LPC diet further decreased protein expressions of nucleotide-binding oligomerization domain protein-1 and interferon-γ. LPC diet also increased protein expressions of G-protein coupled receptor-43, interleukin-4, transforming growth factor-β, immunoglobulin A and mucin-4, which are indicators for mucosal defense activity. Conclusions: The results showed that supplementing casein hydrolysate showed beneficial effects on the colonic microbiota and mucosal immunity and barrier function in comparison with supplementing free AAs in LP diets. These findings may provide new framework for future nutritional interventions for colon health in pigs.

Introduction: Lyophyllum decastes is an edible mushroom with nutritional and medicinal value, but approaches for accelerating mycelial biomass accumulation during submerged cultivation remain limited. Methods: This study evaluated the effects of Acanthopanax senticosus aqueous extract (ASAE) on submerged mycelial growth and examined associated transcriptional responses using time-course RNA sequencing, weighted gene co-expression network analysis, gene set enrichment analysis, and independent RT-qPCR experiments. Results: Among the concentrations tested, 50 mg/L ASAE produced the greatest biomass accumulation at day 7, increasing mycelial dry weight by 22.7% relative to the untreated control, whereas 1,000 mg/L ASAE inhibited biomass accumulation. However, the treatment effect was no longer statistically significant at day 9, indicating a transient acceleration of biomass accumulation rather than an increase in final biomass yield under the conditions tested. Two-way ANOVA identified significant effects of cultivation time, treatment, and their interaction on mycelial dry weight. WGCNA module eigengenes were further analyzed using models incorporating cultivation time, treatment, and their interaction. MEblue remained significantly associated with all three factors, including their interaction, but was interpreted as a time- and treatment-associated co-expression module rather than a treatment-specific regulatory module. Direction-separated GSEA showed time-resolved enrichment of gene sets related to energy metabolism, RNA processing, protein homeostasis, carbon metabolism, translation, intracellular trafficking, and carbohydrate-associated metabolism. Upregulated GSEA leading-edge genes were intersected with MEblue genes for candidate-gene visualization without performing a second enrichment analysis. Independent RT-qPCR experiments confirmed the expression trends of selected candidates, including CHSG , UAP1 , ALG5 , and RPN12 . A homology-based transcript-collapse sensitivity analysis produced qualitatively similar module- and pathway-level patterns. Discussion: These findings indicate that ASAE-associated acceleration of L. decastes biomass accumulation is accompanied by time-resolved transcriptional remodeling. The proposed biological interpretation remains hypothesis-generating, and direct physiological, biochemical, protein-level, and genetic validation will be required to establish causality.