Chemical Characteristics and Bioactivities of Chestnut Flower Polysaccharides: Insights Into the Impact of Extraction Methods June 16, 2025

This study systematically evaluated and compared the effects of six extraction methods, namely hot water extraction (HWE), ultrasound-assisted extraction (UAE), microwave-assisted extraction (MAE), acid-assisted extraction (CAE), alkali-assisted extraction (AAE), and enzyme-assisted extraction (EAE), on the structural characteristics, in vitro biological activities, and cytotoxicity of polysaccharides from chestnut flowers (CFPs). The results show that CFPs extracted by different extraction methods have significant differences in terms of chemical composition, monosaccharide spectrum, molecular weight distribution, and surface morphology. However, their similar infrared spectra, crystal structures and thermal stabilities indicate that despite the different degrees of degradation, the main structure of CFPs remains basically intact in different extraction methods. It is worth noting that the CFPs produced by HWE have the strongest antioxidant activity (98.5 ± 0.48%, evaluated by the DPPH free radical scavenging assay), while the CFPs produced by EAE have the highest hypoglycemic activity (94.3 ± 0.4%, evaluated by the α-glucosylase inhibition assay). Furthermore, the CFPs of all extraction methods showed biocompatibility. Under the condition of conforming to physiological relevance, the selected cell concentrations all promoted the proliferation of RAW264.7 mouse macrophages, indicating their lack of cytotoxicity. These findings provide a theoretical basis for the selection of CFPs extraction methods with targeted biological activity. Specifically, HWE is recommended for the production of CFPs rich in antioxidants, while EAE is the best choice for preparing CFPs with hypoglycemic properties. This study also lays a foundation for further research on the in vivo biological activity of CFPs.

Synthesis and Characterization of Cationic and Non‐Ionic Surfactant Added Organomodified Montmorillonite and the Effect on Migration Characteristics for Starch‐Based Film Materials June 16, 2025

The separation of montmorillonite (Mt) clay platelets was achieved and optimized through organic modification using cationic (cetyltrimethylammonium bromide [CTAB]) and non-ionic (Tween80) surfactants. Organomodified Mt (oMt) was characterized via particle size analysis, zeta potential, conductivity measurements, Fourier transform infrared (FT-IR) spectroscopy, and x-ray diffraction (XRD). Particle size analysis revealed synergy interaction between surfactants and clay. In CTAB-modified oMt, zeta potential shifted from negative to positive values, indicating increased surface potential. Conductivity decreased upon reaching critical micelle concentration (CMC) level, suggesting micelle formation. FT-IR confirmed the attachment of surfactant functional groups to Mt, whereas XRD verified clay platelet intercalation in both surfactant-modified organoclays. Optimized organoclays were incorporated into starch-based biomaterials, and overall migration as well as specific migration of aluminum (Al) from the resulting bionanocomposite films were assessed for food packaging in accordance with the European Union (EU) and Turkish regulations. The addition of organoclay in matrix effectively lowered overall migration results below the regulatory limit (10 mg/dm²) with hydrophilic and acidic food simulants, meeting strict food safety requirements. In specific migration analysis, it was found that although the incorporation of organoclay into biomaterial led to an increase in aluminum migration with acidic simulant, the results remained below the regulation limit (1 mg/kg); meanwhile, the migration levels with aqueous simulant were below the limit of quantification. Moreover, organoclay incorporation significantly decreased both the water absorption capacity and the water solubility of the resulting nanocomposite films. These findings highlight the potential applicability of the developed bionanocomposites for food packaging applications.

Predicting Stress, Anxiety, and Depression in Adult Men Based on Nutritional and Lifestyle Variables: A Comparative Analysis of Machine Learning Methods June 16, 2025

Mental health disorders like depression, anxiety, and stress (DAS) are rising globally. Understanding how diet and lifestyle influence these conditions is vital for targeted interventions. This study explores the potential of machine learning (ML) to identify key risk factors and improve mental health predictions in adult males. This cross-sectional study gathered dietary data from 400 adult males using the Food Frequency Questionnaire (FFQ). The dataset contained 59 predictor variables, and DAS was classified as either normal or indicative of some degree of disorder. The predictive performance of five ML models [bagging, boosting, Naive Bayes (NB), support vector machine (SVM), and random forest (RF)] was assessed using cross-validation. Metrics such as sensitivity, specificity, precision (positive predictive value, PPV), negative predictive value (NPV), accuracy, and the area under the curve (AUC) were used to evaluate performance. DAS were present in 103 (25.47%) of participants. Bagging, boosting, and RF models outperformed others, achieving over 70% in all metrics. Key prognostic factors for predicting DAS include fried fast food, physical activity (PA), body mass index (BMI), magnesium, sodium, and other dietary elements like butter/margarine, fructose, and vitamin K. Chromium and caffeine were significant predictors of depression and anxiety, while cholesterol and olive oil were strongly associated with stress. The study shows that the RF, boosting, and bagging algorithms outperformed other models in predicting DAS across all evaluation criteria. Key dietary and lifestyle factors, such as magnesium, sodium, BMI, caffeine, and cholesterol, were identified as significant predictors, highlighting the potential of ML for advancing targeted mental health interventions.

Regulation of Arginine Metabolism by Transcription Factor Btn2p in a Mixed Culture of Saccharomyces cerevisiae and Pediococcus pentosaceus and Subsequent Ethanol Tolerance June 16, 2025

Ethyl carbamate (EC) is a natural carcinogen widely found in fermented alcoholic beverages. The compound is mainly generated through the reaction of urea and citrulline with ethanol. The transcription factor Btn2p may affect arginine metabolism, and thus regulate EC in different fermentation systems. Therefore, in this study, we investigated the effects of Btn2p on arginine metabolism in Saccharomyces cerevisiae in different culture systems and analyzed the potential regulatory mechanisms of EC formation. In addition, we studied the ethanol tolerance of BTN2-modified yeast to determine its applicability in huangjiu fermentation and to provide a theoretical basis for subsequent studies. We found that BTN2 knockout inhibited two major EC precursors, and the inhibitory effect was better in mixed cultures with Pediococcus pentosaceus. In addition, BTN2 knockout promoted the activities of urease and ornithine transcarbamoylase, but reduced the activity of arginine deiminase, which led to the reduction of urea and citrulline concentrations. The growth conditions of BTN2-modified strains under different ethanol concentrations were also studied for future applications in huangjiu fermentation. The results showed that BTN2 overexpression promoted cell growth and increased ethanol tolerance, whereas BTN2 knockout reduced the ethanol tolerance of cell. The findings indicated that Btn2p was involved in arginine metabolism, possibly through the regulation of urea and citrulline metabolism, and BTN2-knockout strains can be used as a potential target for EC reduction.

Extrusion Process to Improve the Availability of Fermentable Sugars in Sorghum Wort June 16, 2025

A common challenge in producing gluten-free beer from sorghum is the inefficient conversion of sorghum starch into fermentable sugars. This issue can be attributed to the high proportion of resistant starch and natural inhibitors that hinder starch digestibility in sorghum grains. To address this, an extrusion process was proposed to improve gelatinization and hydrolysis of sorghum starch. Two experimental designs were conducted, one with extrusion and one without, to assess the impact of utilizing two exogenous enzymes during mashing: papain and α-amylase. The results showed that the extrusion process significantly improved sorghum starch gelatinization and increased the concentration of fermentable sugars by an average of four times compared to trials without extrusion. By incorporating the extrusion process and utilizing 3% α-amylase and 0.1% papain, a high-quality wort with the desired concentration of fermentable sugars for yeast fermentation was obtained. This improvement was supported through the analysis of scanning electron microscopy (SEM) images and energy dispersive x-ray spectroscopy (EDS) by revealing changes in the structure and composition of gelatinized and hydrolyzed sorghum grains with and without extrusion.

JUNE 2025: Food Safety 2025: Insights on Recalls, Risks, and Resilience June 16, 2025

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EP 61: Riding the AI Wave, The Iron Man Speaks June 9, 2025

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EP 60: African Food Trend Heats Up, Cornell Scientists Serve Up Food Solutions, Hitting the Sweet Spot with Sugar Reduction May 19, 2025

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MAY 2025: Insider Tips on Launching Your Food Science Career May 12, 2025

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EP 59: Building a Better Food Ecosystem, Inside Aseptic Processing, GRAS Reform May 5, 2025

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