Research on Rapid and Low-Cost Spectral Device for the Estimation of the Quality Attributes of Tea Tree Leaves.

Tea polyphenols, amino acids, soluble sugars, and other ingredients in fresh tea leaves are the key parameters of tea quality. In this research, a tea leaf ingredient estimation sensor was developed based on a multi-channel spectral sensor. The experiment showed that the device could effectively acquire 700-1000 nm spectral data of tea tree leaves and could display the ingredients of leaf samples in real time through the visual interactive interface. The spectral data of Fuding white tea tree leaves acquired by the detection device were used to build an ingredient content prediction model based on the ridge regression model and random forest algorithm. As a result, the prediction model based on the random forest algorithm with better prediction performance was loaded into the ingredient detection device. Verification experiment showed that the root mean square error (RMSE) and determination coefficient (R2) in the prediction were, respectively, as follows: moisture content (1.61 and 0.35), free amino acid content (0.16 and 0.79), tea polyphenol content (1.35 and 0.28), sugar content (0.14 and 0.33), nitrogen content (1.15 and 0.91), and chlorophyll content (0.02 and 0.97). As a result, the device can predict some parameters with high accuracy (nitrogen, chlorophyll, free amino acid) but some of them with lower accuracy (moisture, polyphenol, sugar) based on the R2 values. The tea leaf ingredient estimation sensor could realize rapid non-destructive detection of key ingredients affecting tea quality, which is conducive to real-time monitoring of the current quality of tea leaves, evaluating the status during tea tree growth, and improving the quality of tea production. The application of this research will be helpful for the automatic management of tea plantations.

Transcriptome research identifies four hub genes related to primary myelofibrosis: a holistic research by weighted gene co-expression network analysis.

OBJECTIVES: This study aimed to identify specific diagnostic as well as predictive targets of primary myelofibrosis (PMF). METHODS: The gene expression profiles of GSE26049 were obtained from Gene Expression Omnibus (GEO) dataset, WGCNA was constructed to identify the most related module of PMF. Subsequently, Gene Ontology (GO), Kyoto Encyclopedia Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA) and Protein-Protein interaction (PPI) network were conducted to fully understand the detailed information of the interested green module. Machine learning, Principal component analysis (PCA), and expression pattern analysis including immunohistochemistry and immunofluorescence of genes and proteins were performed to validate the reliability of these hub genes. RESULTS: Green module was strongly correlated with PMF disease after WGCNA analysis. 20 genes in green module were identified as hub genes responsible for the progression of PMF. GO, KEGG revealed that these hub genes were primarily enriched in erythrocyte differentiation, transcription factor binding, hemoglobin complex, transcription factor complex and cell cycle, etc. Among them, EPB42, CALR, SLC4A1 and MPL had the most correlations with PMF. Machine learning, Principal component analysis (PCA), and expression pattern analysis proved the results in this study. CONCLUSIONS: EPB42, CALR, SLC4A1 and MPL were significantly highly expressed in PMF samples. These four genes may be considered as candidate prognostic biomarkers and potential therapeutic targets for early stage of PMF. The effects are worth expected whether in the diagnosis at early stage or as therapeutic target.

Deoxynivalenol Induces Inflammation in the Small Intestine of Weaned Rabbits by Activating Mitogen-Activated Protein Kinase Signaling.

Deoxynivalenol (DON) can activate related signaling pathways and induce gastrointestinal disorders. Based on the results of previous studies, this study tried to explore the relationship between DON-induced intestinal inflammation of weaned rabbits and the ERK-p38 signaling pathway. Forty-five weaned rabbits were divided into three treatments: control, LD and HD group. All rabbits were treated with diet containing a same nutrient content, but animals in the LD and HD groups were additionally administered DON via drinking water at 0.5 and 1.5 mg/kg b.w./d, respectively. The protocol consisted of a total feeding period of 31 days, including a pre-feeding period of 7 days. Western blotting, qRT-PCR, and immunohistochemistry were applied for analysis the expression of protein and mRNA of extracellular signal-regulated kinase (ERK), p38, double-stranded RNA-activated protein kinase (PKR), and hematopoietic cell kinase (Hck) in the duodenum, jejunum, and ileum of rabbits, as well as the distribution of positive reactants. The results proved that DON intake could enhance the levels of inflammatory factors in serum and damage the intestinal structure barrier of rabbits. Meanwhile, DON addition can stimulate the protein and mRNA expression for ERK, p38, PKR, and Hck in the intestine of rabbits, especially in the duodenum, as well as expand the distribution of positive reactants, in a dose-dependent manner.