Dietary flavonoids modulate the gut microbiota: A new perspective on improving autism spectrum disorder through the gut-brain axis.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with an unknown etiology. It is associated with various factors and causes great inconvenience to the patient's life. The gut-brain axis (GBA), which serves as a bidirectional information channel for exchanging information between the gut microbiota and the brain, is vital in studying many neurodegenerative diseases. Dietary flavonoids provide anti-inflammatory and antioxidant benefits, as well as regulating the structure and function of the gut microbiota. The occurrence and development of ASD are associated with dysbiosis of the gut microbiota. Modulation of gut microbiota can effectively improve the severity of ASD. This paper reviews the links between gut microbiota, flavonoids, and ASD, focusing on the mechanism of dietary flavonoids in regulating ASD through the GBA.

NSUN5/TET2-directed chromatin-associated RNA modification of 5-methylcytosine to 5-hydroxymethylcytosine governs glioma immune evasion.

Malignant glioma exhibits immune evasion characterized by highly expressing the immune checkpoint CD47. RNA 5-methylcytosine(m5C) modification plays a pivotal role in tumor pathogenesis. However, the mechanism underlying m5C-modified RNA metabolism remains unclear, as does the contribution of m5C-modified RNA to the glioma immune microenvironment. In this study, we demonstrate that the canonical 28SrRNA methyltransferase NSUN5 down-regulates ß-catenin by promoting the degradation of its mRNA, leading to enhanced phagocytosis of tumor-associated macrophages (TAMs). Specifically, the NSUN5-induced suppression of ß-catenin relies on its methyltransferase activity mediated by cysteine 359 (C359) and is not influenced by its localization in the nucleolus. Intriguingly, NSUN5 directly interacts with and deposits m5C on CTNNB1 caRNA (chromatin-associated RNA). NSUN5-induced recruitment of TET2 to chromatin is independent of its methyltransferase activity. The m5C modification on caRNA is subsequently oxidized into 5-hydroxymethylcytosine (5hmC) by TET2, which is dependent on its binding affinity for Fe2+ and α-KG. Furthermore, NSUN5 enhances the chromatin recruitment of RBFOX2 which acts as a 5hmC-specific reader to recognize and facilitate the degradation of 5hmC caRNA. Notably, hmeRIP-seq analysis reveals numerous mRNA substrates of NSUN5 that potentially undergo this mode of metabolism. In addition, NSUN5 is epigenetically suppressed by DNA methylation and is negatively correlated with IDH1-R132H mutation in glioma patients. Importantly, pharmacological blockage of DNA methylation or IDH1-R132H mutant and CD47/SIRPα signaling synergistically enhances TAM-based phagocytosis and glioma elimination in vivo. Our findings unveil a general mechanism by which NSUN5/TET2/RBFOX2 signaling regulates RNA metabolism and highlight NSUN5 targeting as a potential strategy for glioma immune therapy.

Improving the Accuracy of Saffron Adulteration Classification and Quantification through Data Fusion of Thin-Layer Chromatography Imaging and Raman Spectral Analysis.

Agricultural crops of high value are frequently targeted by economic adulteration across the world. Saffron powder, being one of the most expensive spices and colorants on the market, is particularly vulnerable to adulteration with extraneous plant materials or synthetic colorants. However, the current international standard method has several drawbacks, such as being vulnerable to yellow artificial colorant adulteration and requiring tedious laboratory measuring procedures. To address these challenges, we previously developed a portable and versatile method for determining saffron quality using a thin-layer chromatography technique coupled with Raman spectroscopy (TLC-Raman). In this study, our aim was to improve the accuracy of the classification and quantification of adulterants in saffron by utilizing mid-level data fusion of TLC imaging and Raman spectral data. In summary, the featured imaging data and featured Raman data were concatenated into one data matrix. The classification and quantification results of saffron adulterants were compared between the fused data and the analysis based on each individual dataset. The best classification result was obtained from the partial least squares-discriminant analysis (PLS-DA) model developed using the mid-level fusion dataset, which accurately determined saffron with artificial adulterants (red 40 or yellow 5 at 2-10%, w/w) and natural plant adulterants (safflower and turmeric at 20-100%, w/w) with an overall accuracy of 99.52% and 99.20% in the training and validation group, respectively. Regarding quantification analysis, the PLS models built with the fused data block demonstrated improved quantification performance in terms of R2 and root-mean-square errors for most of the PLS models. In conclusion, the present study highlighted the significant potential of fusing TLC imaging data and Raman spectral data to improve saffron classification and quantification accuracy via the mid-level data fusion, which will facilitate rapid and accurate decision-making on site.

Prediction of Anthocyanin Color Stability against Iron Co-Pigmentation by Surface-Enhanced Raman Spectroscopy.

The color change resulting from anthocyanin and iron co-pigmentation has been a significant challenge for the food industry in the development of many iron-fortified foods. This present study aims to establish a quantitative model to predict the degree of color stability in the presence of dissolved iron using surface-enhanced Raman spectroscopic (SERS) spectra. The SERS spectra of anthocyanin extracts from seven different plant sources were measured and analyzed by principal component analysis (PCA). Discrimination among different sources of anthocyanin was observed in the PCA plot. Different stability indexes, obtained by measuring both the color intensity stability and color hue stability of each sample, were established based on UV-vis analysis of anthocyanin at pH 3 and 6 with and without ferric sulfate. Partial least square (PLS) regression models were applied to establish the correlation between SERS spectra and stability indexes. The best PLS model was built based on the stability index calculated from the bathochromic shift (UV-vis spectral range: 380-750 nm) in pH3 buffer and the SERS spectra, achieving a root mean square error of prediction (RMSEP) of 2.16 nm and a correlation coefficient value (R2) of 0.98. In conclusion, the present study developed a feasible approach to predict the stability of anthocyanin colorants against iron co-pigmentation. The developed method and models can be used for fast screenings of raw ingredients in iron-fortified food products.

Toward a greener approach to detect inorganic arsenic using the Gutzeit method and X-ray fluorescence spectroscopy.

Inorganic arsenic is a carcinogen repeatedly found in water and foods threatening global human health. Prior work applied the Gutzeit method and X-ray fluorescence spectroscopy to quantify inorganic arsenic based on a harmful chemical, i.e., mercury bromide, to capture the arsine gas. In this project, we explored silver nitrate as an alternative to mercury bromide for the capture and detection of inorganic arsenic. To compare the performance of mercury bromide and silver nitrate, two standard curves were established in the range from 0 to 33.3 µg/L after optimization of reaction conditions such as the quantity of reagents and reaction time. Our result shows silver nitrate-based standard curve had a lower limit of detection and limit of quantification at 1.02 µg/L and 3.40 µg/L, respectively, as compared to the one built upon mercury bromide that has limit of detection of 4.86 µg/L and limit of quantification of 16.2 µg/L. The relative higher sensitivity when using silver nitrate was contributed by the less interfering elements for X-ray fluorescence analysis and thus lower background signals. A commercial apple juice was studied for matrix inference, and the results show 85%-99% recoveries and 7.4%-24.5% relative standard deviation. In conclusion, we demonstrated silver nitrate is a better choice in terms of safety restrictions and detection capability at lower inorganic arsenic concentrations.

An innovative filtration based Raman mapping technique for the size characterization of anatase titanium dioxide nanoparticles.

Characterization of titanium dioxide nanoparticles (TiO2-NPs) is of significant importance in the production quality control, applications and study of their toxicological effects. In this study, we developed a filtration-based Raman mapping technique as a rapid approach for the analysis of different sizes and concentrations of anatase TiO2-NPs. Four different sizes of TiO2 standards: 173, 93, 41, and 8 nm measured by electron microscopy techniques were dispersed using a probe sonicator with sodium pyrophosphate as a dispersing agent. The resulting hydrodynamic diameter measured by dynamic light scattering (DLS) was stabilized at 192, 289, 325, and 360 nm respectively as a negative correlation with the ones by TEM. These NPs were then collected on a 0.1 µm (pore size) filter membrane with a vacuum pump and scanned using a Raman imaging microscope. The result shows that the 100 × objective lens was more capable of detecting the smallest size particles (8 nm) and lowest concentration (0.0004 g L-1) evaluated than the 20 × objective lens. Moreover, at low concentrations (i.e. 0.0004 and 0.004 g L-1), we established a linear correlation between the map area covered by the particles and the particle size measured by TEM. While at higher concentration (i.e. 0.04 g L-1), a positive correlation was established between the particle size and its corresponding Raman intensity. These results demonstrated a successful application of Raman mapping technique in rapid characterization of the size of anatase TiO2-NPs as small as 8 nm, which will facilaite the TiO2-NPs research, production, and applications.

Increasing the nutritional value of strawberry puree by adding xylo-oligosaccharides.

The present study identified the threshold concentration of xylo-oligosaccharides (XOS) that resulted in minimal quality changes (rheology, color, water activity, pH, and total soluble solids) in strawberry puree. Optimization of XOS concentration to 5% (w/w) did not significantly alter the quality attributes of the strawberry puree. In addition, this study also monitored the rheological properties, composition (total soluble solids, total phenolic content, flavonoids, and tannin content), physicochemical attributes (color, water activity, pH) and sensorial properties of XOS-enhanced (5%, w/w) strawberry puree after thermal processing (HTST: 75 °C, 15s and UHT: 121 °C, 2s) and storage after 1, 15, and 36 days at 4 °C and 55 °C. At 5% (w/w) concentration, the addition of XOS increased consumer preference without significantly compromising quality attributes. Thermally treated strawberry puree (HTST and UHT) were less preferred by consumers than fresh puree. However, all strawberry samples incorporated with XOS (5%, w/w) received statistically higher scores than the samples without the XOS addition. Thus, the proposed supplementation of strawberry puree with XOS could be a viable solution to increase consumers' dietary fiber intake with little need for behavioral changes.

Multi-phase detection of antioxidants using surface-enhanced Raman spectroscopy with a gold nanoparticle-coated fiber.

The development of a method for multi-phase detection of antioxidants using surface-enhanced Raman spectroscopy (SERS) with a gold nanoparticle (AuNP)-coated fiber as a substrate is described. The AuNP-coated fiber was directly inserted into a multi-phase system containing model analytes of ascorbic acid, ascorbyl palmitate, and α-tocopherol, representing hydrophilic, amphiphilic, and lipophilic antioxidants, respectively. The AuNP-coated fiber enabled simultaneous detection of antioxidants present within the aqueous, interfacial, and organic phases of the multi-phase system. An oil-in-water emulsion was used as a model multi-phase system, where the antioxidant profiles of the three model analytes were successfully characterized. This method enables rapid, simultaneous, and non-destructive analysis of multiple antioxidants in complex multi-phase systems.