The present study was aimed at developing a low-cost but rapid technique for qualitative and quantitative detection of beef adulterated with pork. An electronic nose based on colorimetric sensors was proposed. The fresh beef rib steaks and streaky pork were purchased and used from the local agricultural market in Suzhou, China. The minced beef was mixed with pork ranging at levels from 0%~100% by weight at increments of 20%. Protein, fat, and ash content were measured for validation of the differences between the pure beef and pork used in basic chemical compositions. Fisher linear discriminant analysis (Fisher LDA) and extreme learning machine (ELM) were utilized comparatively for identification of the ground pure beef, beef–pork mixtures, and pure pork. Back propagation-artificial neural network (BP-ANN) models were built for prediction of the adulteration levels. Results revealed that the ELM model built was superior to the Fisher LDA model with higher identification rates of 91.27% and 87.5% in the training and prediction sets respectively. Regarding the adulteration level prediction, the correlation coefficient and the root mean square error were 0.85 and 0.147 respectively in the prediction set of the BP-ANN model built. This suggests, from all the results, that the low-cost electronic nose based on colorimetric sensors coupled with chemometrics has a great potential in rapid detection of beef adulterated with pork.

The purpose of this present study was to develop a rapid and effective approach for identification of red wines that differ in geographical origins, brands, and grape varieties, a multi‐sensor fusion technology based on a novel cost‐effective electronic nose (E‐nose) and a voltammetric electronic tongue (E‐tongue) was proposed. The E‐nose sensors was created using porphyrins or metalloporphyrins, pH indicators and Nile red printed on a C2 reverse phase silica gel plate. The voltammetric E‐Tongue with six metallic working electrodes, namely platinum, gold, palladium, tungsten, titanium, and silver was employed to sense the taste of red wines. Principal component analysis (PCA) was utilized for dimensionality reduction and decorrelation of the raw sensors datasets. The fusion models derived from extreme learning machine (ELM) were built with PCA scores of E‐nose and tongue as the inputs. Results showed superior performance (100% recognition rate) using combination of odor and taste sensors than individual artificial systems. The results suggested that fusion of the novel cost‐effective E‐nose created and voltammetric E‐tongue coupled with ELM has a powerful potential in rapid quality evaluation of red wine.

Sarcodon aspratus is a popular edible fungus for its tasty flavour and can be used as a dietary supplement for its functional substances. This study was conducted to evaluate the potential health benefits of Sarcodon aspratus polysaccharides (SAFP) on water immersion and restraint stress (WIRS)-induced gastric ulcer in rats. The results indicated that SAFP could decrease myeloperoxidase (MPO) activity and plasma corticosterone levels, as well as enhance Prostaglandin E2 (PGE2) and Nitrate/nitrite (NOx) concentration in rats. Furthermore, SAFP significantly attenuated the stress damage, inflammation, pathological changes and gastric mucosal lesion in rats. Moreover, high-throughput pyrosequencing of 16S rRNA suggested that SAFP modulated the dysbiosis of gut microbiota by enhancing the relative abundance of probiotics, decreasing WIRS-triggered bacteria proliferation. In summary, these results provided the evidence that SAFP exerted a beneficial effect on a WIRS-induced gastric ulcer via blocking the TLR4 signaling pathway and activating the Nrf2 signaling pathway. Notably, SAFP could modulate the WIRS-induced dysbiosis of gut microbiota. Thus, SAFP might be explored as a natural gastric mucosal protective agent in the prevention of gastric ulcers and other related diseases in the food and pharmaceutical industries.

Sarcodon aspratus fruiting polysaccharides (SAFP) exhibit multiple therapeutic properties. In this study, a type 2 diabetes mellitus (T2DM) mouse model was established using a high-fat diet (HFD) and streptozotocin to evaluate the antidiabetic potential of SAFP. Then the benefits of SAFP on glucolipid metabolism, gut barrier integrity and intestinal microbiota were evaluated. The results indicated that SAFP alleviated disturbances in glycolipid metabolism and insulin resistance through activating Adenosine 5′-monophosphate (AMP)-activated protein kinase (AMPK) signaling pathway. Furthermore, SAFP ameliorated hepatic inflammation and hepatic steatosis, as well as restored dysbiosis in hepatic function. Notably, SAFP enhanced intestinal mucosal architecture and strengthened epithelial barrier functionality through upregulated expression of tight junction components such as Zonula occludens-1(ZO-1), Claudin-1, and Occludin proteins. The 16S rRNA analysis indicated that SAFP has the potential to restore the intestinal microbial barrier in T2DM mice through elevation of short-chain fatty acids (SCFAs) concentrations and regulation of microbial community imbalances. This research offers foundational evidence supporting the utilization of SAFP as an innovative dietary supplement or prospective prebiotic component in functional food formulations targeting diabetes management.