Deep learning is evolving in nutritional epidemiology to address challenges including precise nutrition and data-driven disease modeling. Fermented dairy products consumption as the implementation of specific dietary priority contributes to a lower risk of all-cause mortality, cardiovascular disease, and obesity. Various lipid types play different roles in cardiometabolic health and fermentation process changes the lipid profile in dairy products. Leveraging the power of multiple biological datasets can provide mechanistic insights into how proteins impact lipid pathways, and establish connections among fermentation-lipid biomarkers-protein. The recent leap of deep learning has been performed in food category recognition, agro-food freshness detection, and food flavor prediction and regulation. The proposed multimodal deep learning method includes four steps: (i) Forming data matrices based on data generated from different omics layers. (ii) Decomposing high-dimensional omics data according to self-attention mechanism. (iii) Constructing View Correlation Discovery Network to learn the cross-omics correlations and integrate different omics datasets. (iv) Depicting a biological network for lipid metabolism-centered quantitative multi-omics data analysis. Relying on the cytidine diphosphate-diacylglycerol synthase-mediated lipid metabolism regulates the glycerophospholipid composition of fermented dairy effectively. Innovative processing strategies including ohmic heating and pulsed electric field improve the sensory qualities and nutritional characteristics of the products.

The potential of probiotics to benefit digestion has been widely reported, while its utilization in high-risk patients and potential adverse reactions have focused interest on postbiotics. A variable data-independent acquisition (vDIA)-based spatial-omics strategy integrated with unsupervised variational autoencoders was applied to profile the functional mechanism underlying the action of Lactobacillus casei-derived postbiotic supplementation in goat milk digestion in an infant digestive system, from a metabolomics-peptidomics-proteomics perspective. Amide and olefin derivatives were proved to elevate the activities of pepsin and trypsin through hydrogen bonding and hydrophobic forces based on allosteric effects, and recognition of nine endopeptidases and their cleavage to serine, proline, and aspartate were introduced by postbiotics, thereby promoting the generation of hydrophilic peptides and elevating the bioaccessibility of goat milk protein. The peptides originating from αs1-casein, β-casein, β-lactoglobulin, Ig-like domain-containing protein, κ-casein, and serum amyloid A protein, with multiple bioactivities including angiotensin I-converting enzyme (ACE)-inhibitory, osteoanabolic, dipeptidyl peptidase IV (DPP-IV) inhibitory, antimicrobial, bradykinin-potentiating, antioxidant, and anti-inflammatory activities, were significantly increased in the postbiotic supplementation group, which was also considered to potentially prevent necrotizing enterocolitis through inhibiting the multiplication of pathogenic bacteria and blocking signal transducer and activator of transcription 1 and nuclear factor kappa-light-chain-enhancer of activated B cells inflammatory pathways. This research deepened the understanding of the mechanism underlying the postbiotics affecting goat milk digestion, which established a critical groundwork for the clinical application of postbiotics in infant complementary foods.

In July 2022, the food safety accident that excessive propylene glycol was detected in milk processing factory raised widespread concerns about quality and nutrition of milk with illegal additive. To the best of our knowledge, the influences of propylene glycol to lipids in milk had not been systematically explored. Therefore, spatiotemporal distributions of lipids related to propylene glycol reaction and changes of sensory quality were investigated by food exogenous. Briefly, 10 subclasses (Cer, DG, HexCer, LPC, LPE, PC, PE, PI, SPH and TG) included 147 lipids and 38 pivotal enzymes were annotated. Propylene glycol altered lysophospholipidase and phospholipase A₂ through altering structural order in lipids domains surrounding proteins to inhibit glycerophospholipid metabolism and initiated obvious changes in PC (10.45-27.91 mg kg^-1) and PE (12.92-49.02 mg kg^-1). This study offered insights into influences of propylene glycol doses and storage time on milk metabolism at molecular level to assess the quality of milk.

The effect of peptides on the flavor profile of Baijiu is unclear as a result of their trace concentrations in the complex matrix, and therefore, the study involving the interaction mechanism between peptides and flavor compounds is limited. In this study, short-chain peptides (amino acid number between 2 and 4, SCPs) associated with the Feng-flavor Baijiu (FFB) were comprehensively analyzed by a dedicated workflow using ultra-high-performance liquid chromatography Q Orbitrap high-resolution mass spectrometry, flavor reconstitution experiments, sensory analysis, and density functional theory (DFT) analysis. The concentrations of 96 SCPs intimately related with six different grades of honey aroma intensity in FFB were quantified (0.12-155.01 μg L^-1) after multivariable analysis, Spearman's correlation analysis (ρ ≥ 0.7), and confirmation with synthetic standards, and 32 dominant odorants with an odor activity value of ≥1 in FFB with the highest intensity of honey aroma were quantified by gas chromatography-mass spectrometry and gas chromatography-flame ionization detection analyses. The results of flavor reconstitution experiments and sensory analysis indicated that the SCPs can obviously influence the honey aroma with amplifying the fruity, sweet, and flora flavor odor characters (p < 0.05) while significantly reducing the acidic character (p < 0.001), which could be attributed to the most stable complex structure between SCPs and odor-active compounds calculated by DFT being butanoic acid, followed by β-damascenone, 3-methylbutanal, and ethyl hexanoate, and the multiple sites as a hydrogen bond donor or acceptor in SCPs can form a stable ternary structure with water and ethanol inside the peptide chain or carboxyl terminal of SCPs, consequently improving the stability of the Baijiu system. The results highlighted the important role of SCPs on the volatiles in Baijiu and laid the foundation for further facilitating the sensory quality of Baijiu products.