In obesity, macrophages and other immune cells accumulate in insulin target tissues, promoting a chronic inflammatory state and insulin resistance. Galectin-3 (Gal3), a lectin mainly secreted by macrophages, is elevated in both obese subjects and mice. Administration of Gal3 to mice causes insulin resistance and glucose intolerance, whereas inhibition of Gal3, through either genetic or pharmacologic loss of function, improved insulin sensitivity in obese mice. In vitro treatment with Gal3 directly enhanced macrophage chemotaxis, reduced insulin-stimulated glucose uptake in myocytes and 3T3-L1 adipocytes and impaired insulin-mediated suppression of glucose output in primary mouse hepatocytes. Importantly, we found that Gal3 can bind directly to the insulin receptor (IR) and inhibit downstream IR signaling. These observations elucidate a novel role for Gal3 in hepatocyte, adipocyte, and myocyte insulin resistance, suggesting that Gal3 can link inflammation to decreased insulin sensitivity. Inhibition of Gal3 could be a new approach to treat insulin resistance.

Zanthoxylum bungeanum, a spice and medicinal plant, is cultivated in many parts of China and some countries in Southeast Asia; however, data on its genome are lacking. In the present study, we performed a whole-genome survey and developed novel genomic-SSR markers of Z. bungeanum. Clean data (∼197.16 Gb) were obtained and assembled into 11185221 scaffolds with an N50 of 183 bp. K-mer analysis revealed that Z. bungeanum has an estimated genome size of 3971.92 Mb, and the GC content, heterozygous rate, and repeat sequence rate are 37.21%, 1.73%, and 86.04%, respectively. These results indicate that the genome of Z. bungeanum is complex. Furthermore, 27153 simple sequence repeat (SSR) loci were identified from 57288 scaffolds with a minimum length > 1 kb. Mononucleotide repeats (19706) were the most abundant type, followed by dinucleotide repeats (5154). The most common motifs were A/T, followed by AT/AT; these SSRs accounted for 71.42% and 11.84% of all repeats, respectively. A total of 21243 non-repeating primer pairs were designed, and 100 were randomly selected and validated by PCR analysis using DNA from 10 Z. bungeanum individuals and 5 Zanthoxylum armatum individuals. Finally, 36 polymorphic SSR markers were developed with polymorphism information content (PIC) values ranging from 0.16 to 0.75. Cluster analysis revealed that Z. bungeanum and Z. armatum could be divided into two major clusters, suggesting that these newly developed SSR markers are useful for genetic diversity and germplasm resource identification in Z. bungeanum and Z. armatum.

In this study, the feasibility of classifying soybean frogeye leaf spot (FLS) is investigated. Leaf images and hyperspectral reflectance data of healthy and FLS diseased soybean leaves were acquired. First, image processing was used to classify FLS to create a reference for subsequent analysis of hyperspectral data. Then, dimensionality reduction methods of hyperspectral data were used to obtain the relevant information pertaining to FLS. Three single methods, namely spectral index (SI), principal component analysis (PCA), and competitive adaptive reweighted sampling (CARS), along with a PCA and SI combined method, were included. PCA was used to select the effective principal components (PCs), and evaluate SIs. Characteristic wavelengths (CWs) were selected using CARS. Finally, the full wavelengths, CWs, effective PCs, SIs, and significant SIs were divided into 14 datasets (DS1-DS14) and used as inputs to build the classification models. Models' performances were evaluated based on the classification accuracy for both the overall and individual classes. Our results suggest that the FLS comprised of five classes based on the proportion of total leaf surface covered with FLS. In the PCA and SI combination model, 5 PCs and 20 SIs with higher weight coefficient of each PC were extracted. For hyperspectral data, 20 CWs and 26 effective PCs were also selected. Out of the 14 datasets, the model input variables provided by five datasets (DS2, DS3, DS4, DS10, and DS11) were more superior than those of full wavelengths (DS1) both in support vector machine (SVM) and least squares support vector machine (LS-SVM) classifiers. The models developed using these five datasets achieved overall accuracies ranging from 91.8% to 94.5% in SVM, and 94.5% to 97.3% in LS-SVM. In addition, they improved the classification accuracies by 0.9% to 3.6% (SVM) and 0.9% to 3.7% (LS-SVM).

Most of our knowledge about translation regulatory mechanisms comes from studies on lower organisms. However, the translation control system of higher organisms is less understood. Here we find that in 5' untranslated region (5'UTR) of human Annexin II receptor (AXIIR) mRNA, there are two upstream open reading frames (uORFs) acting in a fail-safe manner to inhibit the translation from the main AUG. These uORFs are unfavorable for re-initiation after termination of uORF translation. Heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1), hnRNPA0 and ELAV like RNA binding protein 1 (ELAVL1) bind to the 5'UTR of AXIIR mRNA. They focus the translation of uORFs on uORF1 and attenuate leaky scanning that bypasses uORFs. The cooperation between the two uORFs and the three proteins formed a multiple fail-safe system that tightly inhibits the translation of downstream AXIIR. Such cooperation between multiple molecules and elements reflects that higher organism develops a complex translation regulatory system to achieve accurate and flexible gene expression control.

The aim of this work was to enrich the knowledge on the potential applications of Elaeagnus mollis leaf extracts. For this purpose, the bioactive compounds (phenolic, flavonoid, alkaloid, proanthocyanidin, chlorophyll and carotene content), antioxidant activity, anti-HepG2 cell proliferation, and cholinesterase inhibitory potential (AChE and BChE) of E. mollis leaves which obtained from different habitats were quantitatively analyzed using various solvents (water, methanol, ethanol, and n-hexane). The results showed that the methanol extracts exhibited the strongest 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical scavenging activity and the water extracts showed the best antioxidant activity in the 2,2'-azinobis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) free radical scavenging activity, ferric reducing antioxidant power (FRAP), and reducing power (RP) assays. Moreover, the methanol extracts showed the best inhibitory activity against cholinesterase and HepG2 cancer cells. Correlation analysis revealed that the high antioxidant and anti-HepG2 cell proliferation activities were mainly attributed to the total phenolics, flavonoids, and proanthocyanidins while AChE inhibition was attributed to the total alkaloid and carotene content. The statistical results showed that the effect of habitats was lower than that of different solvents used. Additionally, the metabolic profiles of E. mollis leaves were evaluated using HPLC-ESI-Q TRAP-MS/MS, and a total of 1,017 chemical components were detected and classified into 23 classes. The organic acids and derivatives ranked the first, followed by flavone, amino acid and derivatives, and so on. In conclusion, the effects of different solvents were more significant than the effects of different habitats and the methanol extracts of E. mollis leaves could be used as an effective source of functional active components, provide benefits to physical health care and be applied to the food and pharmaceutical industries.