Traditional fermented foods harbor microbes that transform raw food components, improving their nutritional, shelf life, organoleptic, and health-promoting characteristics. Fermented foods are an important conduit of contact between bioactive components that act like antigens and the human body system. Versatile microbes in traditional fermented foods are associated with many health-promoting end-products, including dietary fatty acids and inherent fermenting microbial cells. Evidence shows that dietary fatty acid components regulate genes in a hormonally dependent manner, either directly via specific binding to nuclear receptors or indirectly by changing regulatory transcription factors. Fatty acids are implicated in anti-inflammatory, anti-obesogenic, immunoregulatory, cardioprotective, etc., activities. Challenges with scaling the production of traditional fermented foods stem from losing effective consortiums of microbial groups and the production of differential end-products. Industrialists scaling the production of traditional fermented foods must overcome safety and consistency challenges. They need to combine processes that lessen the advent of public health issues and introduce omics technologies that identify and maintain effective consortium groups, prune genes that code for toxic products, and inculcate microbes with additional beneficial characteristics. Incorporating omics in production will avail the benefits of traditional fermented foods to a larger population that craves them outside their native areas.

Ethanol and other congeners in alcoholic beverages and foods are known triggers of alcohol-induced headaches (AIHs). Recent studies implicate AIHs as an important underlying factor for neuroinflammation. Studies show the relationship between alcoholic beverages, AIH agents, neuroinflammation, and the pathway they elicit. However, studies elucidating specific AIH agents’ pathways are scarce. Works reviewing their pathways can give invaluable insights into specific substances’ patterns and how they can be controlled. Hence, we reviewed the current understanding of how AIH agents in alcoholic beverages affect neuroinflammation and their specific roles. Ethanol upregulates transient receptor potential cation channel subfamily V member 1 (TRPV1) and Toll-like receptor 4 (TLR4) expression levels; both receptors trigger a neuroinflammation response that promotes AIH manifestation—the most common cause of AIHs. Other congeners such as histamine, 5-HT, and condensed tannins also upregulate TRPV1 and TLR4, neuroinflammatory conditions, and AIHs. Data elucidating AIH agents, associating pathways, and fermentation parameters can help reduce or eliminate AIH inducers and create healthier beverages.

Background/Objectives: The present study aimed to investigate the effects of frozen (−18 °C) and refrigerated (4 °C) storage conditions on several beef bottom round quality parameters. Methods: Fresh beef bottom round samples were stored under both frozen (−18 °C) and refrigerated (4 °C) conditions. For frozen samples, the pH, color, cooking loss, thawing loss, centrifugal loss, drip loss, moisture content, shear force, TBARS and TPA were measured at 0, 30 and 60 days. For refrigerated samples, the pH and color were analyzed at 0, 1, 3, 5 and 7 days, and the differential metabolites were also identified based on the VOCs analysis combined with multivariate statistical analysis. Results: The surface color (L*, a*, and b*) of the beef bottom round became darker during both the frozen and refrigerated periods of prolonged storage. The samples’ pH significantly declined (p < 0.05) during the frozen storage but alternated (initially reduced and then increased) under refrigerated conditions. Additionally, the frozen treatment led to a significant change (p < 0.05) in the texture profile. The thiobarbituric acid reactive substance (TBAR) values, shear force, cooking loss, thawing loss, centrifugal loss, and drip loss increased significantly with an extended frozen storage time, while the moisture content was significantly lower (p < 0.05). Moreover, nine volatile organic compounds (VOCs) were identified as potential determinants of beef bottom quality during refrigerated storage. Conclusions: The findings can contribute to a deeper understanding of quality variations during frozen storage and refrigerated storage, and provide new thoughts to improve preservation and storage strategies for the beef bottom round.

Background: Fingerprinting Chinese red prickly ash ( Zanthoxylum bungeanum or Dahongpao) samples helped establish baseline qualities and components. These data will provide valuable insights into determining the extent to which cultivation practices and locations may affect a plant’s output, providing insight into maximizing its agricultural potential and ensuring consistent quality. Methods: In this paper, we evaluated prickly ash samples from eight regions, all in the Shandong, Sichuan, Shaanxi, and Gansu provinces, using Fourier‐transform infrared spectroscopy (FTIR) technologies. Gas chromatography–mass spectrometry (GC‐MS) was used to analyze the volatile components from prickly ash extract and powder samples, and they were compared with the NIST database. Results: Data from sample analysis yielded 91 volatile flavour components. Lastly, 14 compounds were identified as fingerprints with harvest site bias based on the GC‐MS data, principal component analysis (PCA), hierarchical cluster analysis (HCA), and orthogonal partial least squares discriminant analysis (OPLS‐DA) models. Conclusion: Data from this comprehensive analysis contributes to the growing body of knowledge regarding the quality of prickly ash samples. Our findings underscore the critical role that cultivation practices play in the quality of plants—which could influence both traditional medical and modern culinary art usages.

Mercury, as one type of toxic heavy metal, represents a great threat to environmental and biological metabolic systems. Thus, reliable and sensitive quantitative detection of mercury levels is particularly meaningful for environmental protection and human health. We proposed a high-throughput single-particle color imaging strategy under dark-field microscopy (DFM) for mercury ions (Hg²⁺) detection by using individual concave cube Au nanoparticles as optical probes. In the presence of ascorbic acid (AA), Hg²⁺ was reduced to Hg which forms Au–Hg amalgamate with Au nanoparticles, altering their localized surface plasmon resonance (LSPR). Transmission electron microscopy (TEM) images demonstrated that the concave cube Au nanoparticles were approaching to sphere upon increasing the concentration of Hg²⁺. The nanoparticles underwent an obvious color change from red to yellow, green, and finally blue under DFM due to the shape-evolution and LSPR changes. In addition, we demonstrated for the first time that the LSPR of Au–Hg amalgamated below 400 nm. Inspired by the above-mentioned results, single-particle color variations were digitalized by converting the color image into RGB channels to obtain (green+blue)/red intensity ratios [(G+B)/R]. The concentration-dependence change was quantified by statistically analyzing the (G+B)/R ratios of a large number of particles. A linear range from 10 to 2000 nM (R² = 0.972) and a limit of detection (LOD) of 1.857 nM were acquired. Furthermore, many other metal ions, like Cu²⁺, Cr³⁺, etc., did not interfere with Hg²⁺ detection. More importantly, Hg²⁺ content in industrial wastewater samples and in the inner regions of human HepG2 cells was determined, showing great potential for developing a single-particle color imaging sensor in complex biological samples using concave cube Au nanoparticles as optical probes.

The grading of beef appearance quality is crucial for standardizing market circulation and promoting the upgrading of the beef cattle industry. China’s current beef quality grading system, which relies primarily on human sensory-based visual assessment with marbling and meat color as core parameters, suffers from strong subjectivity, low efficiency, and large errors. This study proposes a rapid grading method for beef rib eye muscle using smartphone imaging combined with ImageJ software. Standardized images were acquired, and ImageJ was employed for grayscale conversion, threshold segmentation, and morphological processing to extract length, width, area, and marbling proportion. The R, G, B color channels were separated to calculate the R/(R + G + B) color ratio. Pearson correlation analysis showed that the ImageJ results were highly consistent with manual measurements (correlation coefficients > 0.97), indicating good reliability. A five-level grading standard (A1–A5) was established, characterized by low cost, simple operation, and objective results. It provides an economical technical solution for beef quality grading and facilitates the intelligent development of the industry. It should be noted that this experimental grading model has only been validated under the specific experimental conditions of this study, and further verification is required for broader application.