Construction of a Winter Wheat Comprehensive Growth Monitoring Index Based on a Fuzzy Degree Comprehensive Evaluation Model of Multispectral UAV Data.

Realizing real-time and rapid monitoring of crop growth is crucial for providing an objective basis for agricultural production. To enhance the accuracy and comprehensiveness of monitoring winter wheat growth, comprehensive growth indicators are constructed using measurements of above-ground biomass, leaf chlorophyll content and water content of winter wheat taken on the ground. This construction is achieved through the utilization of the entropy weight method (EWM) and fuzzy comprehensive evaluation (FCE) model. Additionally, a correlation analysis is performed with the selected vegetation indexes (VIs). Then, using unmanned aerial vehicle (UAV) multispectral orthophotos to construct VIs and extract texture features (TFs), the aim is to explore the potential of combining the two as input variables to improve the accuracy of estimating the comprehensive growth indicators of winter wheat. Finally, we develop comprehensive growth indicator inversion models based on four machine learning algorithms: random forest (RF); partial least squares (PLS); extreme learning machine (ELM); and particle swarm optimization extreme learning machine (PSO-ELM), and the optimal model is selected by comparing the accuracy evaluation indexes of the model. The results show that: (1) The correlation among the comprehensive growth indicators (CGIs) constructed by EWM (CGIewm) and FCE (CGIfce) and VIs are all improved to different degrees compared with the single indicators, among which the correlation between CGIfce and most of the VIs is larger. (2) The inclusion of TFs has a positive impact on the performance of the comprehensive growth indicator inversion model. Specifically, the inversion model based on ELM exhibits the most significant improvement in accuracy. The coefficient of determination (R2) values of ELM-CGIewm and ELM- CGIfce increased by 20.83% and 20.37%, respectively. (3) The CGIfce inversion model constructed by VIs and TFs as input variables and based on the ELM algorithm is the best inversion model (ELM-CGIfce), with R2 reaching 0.65. Particle swarm optimization (PSO) is used to optimize the ELM-CGIfce (PSO-ELM-CGIfce), and the precision is significantly improved compared with that before optimization, with R2 reaching 0.84. The results of the study can provide a favorable reference for regional winter wheat growth monitoring.

Prediction models and major controlling factors of antibiotics bioavailability in hyporheic zone.

Recently, antibiotics have been frequently detected in the hyporheic zone (HZ) as a novel contaminant. Bioavailability assessment has gradually attracted more attention in order to provide a more realistic assessment of human health risks. In this study, two typical antibiotics, oxytetracycline (OTC) and sulfamethoxazole (SMZ), were used as target pollutants in the HZ of the Zaohe-Weihe River, and the polar organics integrated sampler was used to analyze the variation of antibiotics bioavailability. According to the characteristics of the HZ, the total concentration of pollutants, pH, and dissolved oxygen (DO) were selected as major predictive factors to analyze their correlation with the antibiotics bioavailability. Then the predictive antibiotic bioavailability models were constructed by stepwise multiple linear regression method. The results showed that there was a highly significant negative correlation between OTC bioavailability and DO (P < 0.001), while SMZ bioavailability showed a highly significant negative correlation with total concentration of pollutants (P < 0.001) and a significant negative correlation with DO (P < 0.01). The results of correlation analysis were further verified by Principal Component Analysis. Based on the experimental data, we constructed eight prediction models for the bioavailability of two antibiotics and verified them. The data points of the six prediction models were distributed in the 95% prediction band, indicating that the models were more reliable and accurate. The prediction models in this study provide reference for the accurate ecological risk assessment of the bioavailability of pollutants in the HZ, and also provide a new idea for predicting the bioavailability of pollutants in practical applications.

Piperine ameliorates insulin resistance via inhibiting metabolic inflammation in monosodium glutamate-treated obese mice.

BACKGROUND: Metabolic inflammation is an essential event in obesity-induced diabetes and insulin resistance. In obesity, an increasing number of macrophages recruited into visceral adipose tissues undergo significant M1-like polarization, secreting variable amounts of pro-inflammatory cytokines and causing insulin resistance. Piperine has excellent anti-inflammatory activities and may be used in the treatment of a variety of inflammatory diseases. In this study, we investigated the effect of piperine on adipose tissue inflammation and insulin resistance in obese mice. METHODS: Newborn mice were subcutaneously (s.c.) injected with monosodium glutamate (MSG) to establish a diabetes model. After 24 weeks, the MSG obese mice were divided into three groups and treated with piperine (40 mg/kg/day), metformin (150 mg/kg/day) and vehicle for 10 successive weeks, respectively. RESULTS: The obesity model was successfully established, as the body weight, insulin resistance, fasting blood glucose (FBG) and dyslipidemia were significantly increased. The 10-week administration of piperine to the obese mice not only significantly decreased the elevated FBG (Model: 6.45 ± 0.41 mM; Piperine: 4.72 ± 0.44 mM, p < 0.01), serum TC (Model: 5.66 ± 0.66 mM; Piperine: 3.55 ± 0.30 mM, p < 0.01) and TG (Model: 1.41 ± 0.08 mM; Piperine: 0.94 ± 0.05 mM, p < 0.001), but also enhanced the glucose infusion rate in the hyperglycemic clamp experiment. Meanwhile, piperine improved glucose intolerance and insulin resistance in MSG obese mice. Piperine markedly decreased the total and differential white blood cell (WBC) count, the serum levels of lipopolysaccharide (LPS) and pro-inflammatory cytokines such as galectin-3 (Gal-3) and interleukin-1ß (IL-1ß). Furthermore, piperine clearly down-regulated the mRNA levels of pro-inflammatory cytokines and the protein levels of M1-like polarization marker CD11c and Gal-3 in adipose tissues. The in vitro study showed that piperine inhibited LPS-stimulated polarization of RAW 264.7 cells toward the M1 phenotype. CONCLUSIONS: Piperine served as an immunomodulator for the treatment of obesity-related diabetes through its anti-inflammatory effects, which might be achieved by inhibiting macrophages M1 polarization in adipose tissues.

Genome-Wide Analysis of Polygalacturonase Gene Family Reveals Its Role in Strawberry Softening.

Fruit softening is a prominent attribute governing both longevity on shelves and commercial worth. Polygalacturonase (PG) plays a major role in strawberry fruit softening. However, the PG gene family in strawberry has not been comprehensively analyzed. In this study, 75 FaPG genes were identified in the octoploid strawberry genome, which were classified into three groups according to phylogenetic analysis. Subcellular localization prediction indicated that FaPGs are mostly localized to the plasma membrane, cytoplasm, and chloroplasts. Moreover, the expression of FaPGs during strawberry development and ripening of 'Benihoppe' and its softer mutant was estimated. The results showed that among all 75 FaPGs, most genes exhibited low expression across developmental stages, while two group c members (FxaC_21g15770 and FxaC_20g05360) and one group b member, FxaC_19g05040, displayed relatively higher and gradual increases in their expression trends during strawberry ripening and softening. FxaC_21g15770 was selected for subsequent silencing to validate its role in strawberry softening due to the fact that it exhibited the highest and most changed expression level across different developmental stages in 'Benihoppe' and its mutant. Silencing FxaC_21g15770 could significantly improve strawberry fruit firmness without affecting fruit color, soluble solids, cellulose, and hemicellulose. Conversely, silencing FxaC_21g15770 could significantly suppress the expression of other genes related to pectin degradation such as FaPG-like, FaPL, FaPME, FaCX, FaCel, FaGlu, FaXET, and FaEG. These findings provide basic information on the FaPG gene family for further functional research and indicate that FxaC_21g15770 plays a vital role in strawberry fruit softening.

Combining transcriptomics and HPLC to uncover variations in quality formation between 'Benihoppe' and 'Fenyu No.1' strawberries.

'Benihoppe' and 'Fenyu No.1' are representative varieties of red and pink strawberries in China, possess distinct hue and flavor profiles. This study analyzed the underlying biochemical and molecular differences of two varieties utilizing transcriptomics and high-performance liquid chromatography (HPLC). Ripening 'Benihoppe' fruits accumulated more sucrose and pelargonin-3-glucoside (P3G) with a little cyanidin and higher firmness. Whereas ripening 'Fenyu No.1' fruits contained more fructose, glucose, malic acid and ascorbic acid (AsA), but less P3G and citric acid. Moreover, genotype significantly influenced phenolic compounds contents in strawberries. Transcriptome analysis revealed that pectin degradation (PL, PG, PE), sucrose synthesis (CWINV, SUS, TPS) and citric acid metabolism (α-OGDH, ICDH, GAD, GS, GDH, PEPCK, AST) were weakened in 'Benihoppe' fruit. In contrast, the synthesis of sucrose (CWINH, SPS), citric acid (CS, PEPC), anthocyanin (F3H, F3'H, F3'5'H, DFR, UFGT and ANS), and citric acid transport (V-ATPase) was enhanced. In 'Fenyu No.1' fruit, the degradation of sucrose, citric acid, and pectin was enhanced, along with the synthesis of malic acid (ME) and ascorbic acid (PMM, MDHAR and GaLUR). However, anthocyanins synthesis, glucose metabolism (HK, G6PI, PFK, G6PDH, PGK, PGM, ENO, PK), fructose metabolism (FK), citric acid synthesis and transport, and AsA degradation (AO, APX) were relatively weak. RT-qPCR results corroborated the transcriptome data. In conclusion, this study revealed the distinctions and characteristics of strawberries with different fruit colors regarding texture, flavor and color formation processes. These findings offer valuable insights for regulating metabolic pathways and identifying key candidate genes to improve strawberry quality.

[Heavy Metal Concentration, Source, and Pollution Assessment in Topsoil of Chuzhou City].

In order to understand the pollution level and ecological risk of heavy metals in topsoil of Chuzhou City, a total of 4360 soil samples in Chuzhou City were collected, and the concentrations of eight heavy metals including Cr, Zn, Pb, Cu, Ni, Cd, As, and Hg were measured. Correlation analysis, cluster analysis, and principal component analysis were used to analyze the sources of the heavy metals, and the enrichment factor index, single-factor pollution index, pollution load index, geo-accumulation index method, and potential ecological risk index were selected to assess the environmental risk of the eight heavy metals in the topsoil. The results showed that the average values of Cr, Zn, Pb, Cu, Ni, Cd, As, and Hg contents in the surface soil of Chuzhou City were higher than the background value of that in the soil of Yangtze-Huaihe River Basin of Anhui, and Cd, Ni, As, and Hg were significantly different in space and influenced by external disturbance. The eight types of heavy metals could be divided into four categories based on correlation analysis, cluster analysis, and principal component analysis. Cr, Zn, Cu, and Ni were from natural background sources; As and Hg mainly came from sources of industrial and agricultural pollution; Pb mainly came from the sources of transportation pollution and industrial and agricultural pollution; and Cd came from the sources of transportation pollution, natural background, and industrial and agricultural pollution. The overall pollution degree of Chuzhou City was low, and the ecological risk level was at a slight level based on the pollution load index and the potential ecological risk index; however, the ecological risk of Cd and Hg was generally serious, and these two heavy metals should be taken as the objects of priority control. The results provided a scientific basis for soil safety utilization and classification control in Chuzhou City.

New insights into the interaction between dissolved organic matter and different types of antibiotics, oxytetracycline and sulfadiazine: Multi-spectroscopic methods and density functional theory calculations.

Dissolved organic matter (DOM) is composed of numerous fluorescent components. It is an indispensable parameter to affect the environmental fate of antibiotics in various ways. To assess the migration of antibiotics in environment compartments, it is crucial to understand the binding mechanism between DOM and antibiotics. How a particular component in DOM interacts with coexistence antibiotics is not still fully understood. Therefore, in the present study, interactions of two antibiotics oxytetracycline (OTC) and sulfadiazine (SD) with humic acid (HA) and L-tryptophan (L-Trp) which were representative DOM components, were investigated by multispectral techniques and density functional theory (DFT) calculations. The fluorescence quenching mechanism was static quenching. In the binding process, the quenching ability of OTC was stronger than that of SD in HA, which was the same as in L-Trp. DFT calculations were applied to confirm a stronger interaction between OTC and HA or L-Trp than SD. Meanwhile, analyzing the binding sequence by two-dimensional correlation spectroscopy (2D-COS), a humic-like substance bound antibiotics was earlier than a protein-like substance. In HA system, the combination of two antibiotics had a synergistic effect on HA quenching. In L-Trp system, the quenching relationship between the two antibiotics and L-Trp was antagonistic. The FTIR spectra showed that hydroxyl and amide were involved in the binding process of individual DOM components with OTC and SD. The work will help to further understand the behavior of coexistence antibiotics in the environment.

Piperine protects against pancreatic ß-cell dysfunction by alleviating macrophage inflammation in obese mice.

AIMS: Piperine, the major pharmacological ingredient of pepper, can delay the procession of "obesity to diabetes". However, the underlying mechanism remains unclear. This study aims to investigate whether piperine protects against ß-cell dysfunction by inhibiting macrophage accumulation and M1-like polarization. MATERIALS AND METHODS: Pre-diabetic model was induced by feeding 60% high-fat diet (HFD) in C57BL/6C mice, piperine (15 or 30 mg/kg/day) and rosiglitazone (4 mg/kg/day) were given orally for 8 weeks. Oral glucose tolerance test (OGTT), insulin tolerance test (ITT), fasting blood glucose (FBG), total cholesterol (TC) and triglyceride (TG) were used to assay the disorder of glycolipid metabolism. Serum levels of cytokines and insulin were measured by Elisa. Hyperglycemic clamp assay was carried out to evaluate ß-cell function. RT-PCR, immunofluorescence and western blot were used to detect the expression of biomarkers associated with macrophage polarization and ß-cell dedifferentiation. KEY FINDINGS: Piperine protected against ß-cell dysfunction, indicated by the improvement of hyperinsulinemia, OGTT and increased glucose infusion rate (GIR). Piperine dramatically reduced the serum levels of lipopolysaccharide (LPS), interleukin-1ß (IL-1ß) and Galectin-3 (Gal-3), suppressed the expression of M1-like cytokines (CD11c, IL-1ß and Gal-3) in epididymal adipose tissues and islets. Furthermore, piperine partially reversed the down-regulation of Pdx1, inhibited the up-regulation of ALDH1A3 in ß-cell, and these effects were closely related to the mTOR/S6/4E-BP1 signal pathway. SIGNIFICANCE: Piperine markedly ameliorates the dedifferentiation and dysfunction of ß-cell by inhibiting the accumulation and M1-like polarization of macrophages in visceral adipose tissues and islets.

New insights into the links between anti-diabetes drugs and gut microbiota.

In patients with type 2 diabetes mellitus (T2DM), the intestinal flora is out of balance and accompanied by leaky gut. The flora is characterized by an increase in mucus-degrading bacteria and a decrease in fiber-degrading bacteria. Short-chain fatty acids (SCFAs), as the major fiber-degrading bacteria fermentation, not only ameliorate the leaky gut, but also activate GPR43 to increase the mass of functional pancreatic ß-cells and exert anti-inflammation effect. At present, the gut microbiota is considered as the potential target for anti-diabetes drugs, and how to reverse the imbalance of gut microbiota has become a therapeutic strategy for T2DM. This review briefly summarizes the drugs or compounds that have direct or potential therapeutic effects on T2DM by modulating the gut microbiota, including biguanides, isoquinoline alkaloids, stilbene and C7N-aminocyclic alcohols.