Rapid non-destructive monitoring and quality assessment of the fumigation process of Shanxi aged vinegar based on Vis-NIR hyperspectral imaging combined with multiple chemometric algorithms.

The quality of the grains during the fumigation process can significantly affect the flavour and nutritional value of Shanxi aged vinegar (SAV). Hyperspectral imaging (HSI) was used to monitor the extent of fumigated grains, and it was combined with chemometrics to quantitatively predict three key physicochemical constituents: moisture content (MC), total acid (TA) and amino acid nitrogen (AAN). The noise reduction effects of five spectral preprocessing methods were compared, followed by the screening of optimal wavelengths using competitive adaptive reweighted sampling. Support vector machine classification was employed to establish a model for discriminating fumigated grains, and the best recognition accuracy reached 100%. Furthermore, the results of partial least squares regression slightly outperformed support vector machine regression, with correlation coefficient for prediction (Rp) of 0.9697, 0.9716, and 0.9098 for MC, TA, and AAN, respectively. The study demonstrates that HSI can be employed for rapid non-destructive monitoring and quality assessment of the fumigation process in SAV.

Simultaneous detection of multiple mycotoxins using MXene-based electrochemical aptasensor array and a self-developed multi-channel portable device.

In response to the pressing need for highly efficient simultaneous detection of multiple mycotoxins, which are often found co-occurring in food raw materials and feed, an MXene-based electrochemical aptasensor array (MBEAA) was developed. This aptasensor array utilizes high-specificity aptamers as recognition elements, enabling the capture of electrical signal changes in the presence of target mycotoxins. Based on this platform, a multi-channel portable electrochemical device, enabling rapid, cost-effective, and simultaneous detection of aflatoxin B1 (AFB1), ochratoxin A (OTA), and zealenone (ZEN) was further developed. The developed system boasts a wide detection range of 1.0 × 10-1 to 10.0 ng mL-1, with remarkable performance characterized by ultra-low detection limits of 41.2 pg mL-1, 27.6 pg mL-1, and 33.0 pg mL-1 for AFB1, OTA, and ZEN, respectively. Successfully applied in corn samples, this method offers a portable, easy-to-operate, and cost-effective solution for simultaneous multi-mycotoxin detection. Moreover, the application of the self-developed detection system could be expanded for simultaneous detection of many different targets when their specific aptamers or antibodies were available.

Production monitoring and quality characterization of black garlic using Vis-NIR hyperspectral imaging integrated with chemometrics strategies.

As a new deep-processing garlic product with notable health benefits, the accurate discrimination of processing stages and prediction of key physicochemical constituents in black garlic are vital for maintaining product quality. This study proposed a novel method utilizing hyperspectral imaging technology to both rapidly monitor the processing stages and quantitatively predict changes in the key physicochemical constituents during black garlic processing. Multiple methods of noise reduction and feature screening were used to process the acquired hyperspectral information. To differentiate processing stages, pattern recognition methods including linear discriminant analysis (LDA), K-nearest neighbor (KNN), support vector machine classification (SVC) analysis were utilized, achieving a discriminant accuracy of up to 98.46 %. Furthermore, partial least squares regression (PLSR) and support vector machine regression (SVR) analysis were performed to achieve quantitative prediction of the key physicochemical constituents including moisture and 5-HMF. PLSR models outperformed SVR models, with correlation coefficient of prediction of 0.9762 and 0.9744 for moisture and 5-HMF content, respectively. The current study can not only offer an effective approach for quality detection and assessment during black garlic processing, but also have a positive significance for the advancement of black garlic related industries.

Self-designed portable dual-mode fluorescence device with custom python-based analysis software for rapid detection via dual-color FRET aptasensor with IoT capabilities.

An innovative aptasensor incorporating MoS2-modified bicolor quantum dots and a portable spectrometer, designed for the simultaneous detection of ochratoxin A (OTA) and aflatoxin B1 (AFB1) in corn was developed. Carbon dots and CdZnTe quantum dots were as nano-donors to label OTA and AFB1 aptamers, respectively. These labeled aptamers were subsequently attached to MoS2 receptors, enabling fluorescence resonance energy transfer (FRET). With targets, the labeled aptamers detached from the nano-donors, thereby disrupting the FRET process and resulting in fluorescence recovery. Furthermore, a portable dual-mode fluorescence detection system, complemented with customized python-based analysis software, was developed to facilitate rapid and convenient detection using this dual-color FRET aptasensor. The developed host program is connected to the spectrometer and transmits data to the cloud, enabling the device to have Internet of Things (IoT) characteristics. Connected to the cloud, this IoT-enabled device offers convenient and reliable fungal toxin detection for food safety.

The relationship between VEGF-460(T>C) polymorphism and cancer risk: A systematic review and meta-analysis based on 46 reports.

BACKGROUND: Extensive studies on the link between single nucleotide polymorphisms (SNPs) in vascular endothelial growth factor (VEGF) and various malignancy risks produced conflicting results, notably for VEGF-460(T/C). To evaluate this correlation more comprehensively and accurately, we perform a meta-analysis. METHODS: Through retrieving 5 databases (Web of Science (WoS), Embase, Pubmed, Wanfang database (Wangfang), and China National Knowledge Infrastructure (CNKI)) and applying hand search, citation search, and gray literature search, 44 papers included 46 reports were enrolled. To evaluate the relationship between VEGF-460 and cancer risk, we pooled odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: Our results indicated that the VEGF-460 polymorphism is not related to malignancy susceptibility (dominant model, OR = 0.98, 95% CI = 0.87-1.09; recessive model, OR = 0.95, 95% CI = 0.82-1.10; heterozygous model, OR = 0.99, 95% CI = 0.90-1.10; homozygous model, OR = 0.92, 95% CI = 0.76-1.10; additive model, OR = 0.98, 95% CI = 0.90-1.07). While, in subgroup analysis, this SNP may reduce the risk of hepatocellular carcinoma. CONCLUSION: this meta-analysis indicated that VEGF-460 was irrelevant to overall malignancy risk, but it might be a protective factor for hepatocellular carcinoma.