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The two vegetation transfer parameters of $\tau $ τ (Vegetation Optical Depth,VOD) and $\omega $ ω (Omega) could vary significantly across microwave channels in terms of frequencies, polarizations, and incidence angles, and their channel-dependent characteristics have not yet been fully investigated. In this study, we investigate the channel dependence of vegetation effects on microwave emissions from soils using a higher-order vegetation radiative transfer model of Tor Vergata. Corn was selected as the subject of investigation, and a corn growth model was developed utilizing field data collected from the multifrequency and multi-angular ground-based microwave radiation experiment from the Soil Moisture Experiment in the Luan River (SMELR). Upon compilation of the simulation dataset of microwave emissions of the corn field, the effective scattering albedo across different channels were calculated using the Tor Vergata model. Results show that vertical polarization of the vegetation optical depth is more affected by incidence angle changes, while horizontal polarization exhibits lower variations in vegetation optical depth due to incidence angle adjustments. The channel dependence of vegetation optical depth can be described as the polarization dependence parameter (${C_P}$ C P ) and the frequency dependence parameter (${C_f}$ C f ). These two parameters enable the calculation of vegetation optical depth at any channel under three adjacent frequencies (L-band, C-band and X-band). The effective scattering albedo of vegetation does not vary significantly with vegetation height or angle. It primarily depends on frequency and polarization, showing an overall increasing trend with increasing frequency. The effective scattering albedo with vertical polarization is slightly higher than that with horizontal polarization at higher frequencies, while both are lower in the L-band. This investigation is helpful for understanding the vegetation effects on microwave emissions from soils, ultimately advancing the accuracy of large-scale soil moisture retrieval in vegetated areas. [ABSTRACT FROM AUTHOR]

Patients with end-stage renal disease (ESRD) especially those undergoing dialysis have a high prevalence of hyperkalemia, which must be detected and treated immediately. But the initial symptoms of hyperkalemia are insidious, and traditional laboratory serum potassium concentration testing takes time. Therefore, rapid and real-time measurement of serum potassium is urgently needed. In this study, different machine learning methods were used to make rapid predictions of different degrees of hyperkalemia by analyzing the ECG. A total of 1024 datasets of ECG and serum potassium concentrations were analyzed from December 2020 to December 2021. The data were scaled into training and test sets. Different machine learning models (LR, SVM, CNN, XGB, Adaboost) were built for dichotomous prediction of hyperkalemia by analyzing 48 features of chest leads V2-V5. The performance of the models was also evaluated and compared using sensitivity, specificity, accuracy, accuracy, F1 score and AUC. We constructed different machine models to predict hyperkalemia using LR and four other common machine-learning methods. The AUCs of the different models ranged from 0.740 (0.661, 0.810) to 0.931 (0.912,0.953) when different serum potassium concentrations were used as the diagnostic threshold for hyperkalemia, respectively. As the diagnostic threshold of hyperkalemia was raised, the sensitivity, specificity, accuracy and precision of the model decreased to various degrees. And AUC also performed less well than when predicting mild hyperkalemia. Noninvasive and rapid prediction of hyperkalemia can be achieved by analyzing specific waveforms on the ECG by machine learning methods. But overall, XGB had a higher AUC in mild hyperkalemia, but SVM performed better in predicting more severe hyperkalemia. [ABSTRACT FROM AUTHOR]

Dietary zinc oxide nanoparticle (ZnO NP) possessing multiple biological activities might be a potential substitute for the combination of ZnSO4 and antibiotic growth promoter in broiler diets. Therefore, this study was conducted to investigate the efficacy of dietary ZnO NP as a substitute to the combination of ZnSO4 and xanthomycin for growth, antioxidant capacity, immunity, intestinal barrier and liver function in broilers. Arbor Acres chicks (n = 320) were assigned to 5 treatments with 8 replicates. Birds received a basal diet supplemented with 80 mg/kg ZnSO4 plus 5 mg/kg xanthomycin (ZnSO4 + Xanthomycin) or 0 (negative control, NC), 40, 80, and 160 mg/kg ZnO NP for 42 days. The average daily gain, average daily feed intake and feed-to-gain ratio showed dose-dependent increases with the increasing level of dietary ZnO NP during the 21–42 day and 1–42 day stages. The final body weight (42 d) and serum concentrations of insulin-like growth factor 1 and growth hormone increased linearly with the increasing level of dietary ZnO NP. In addition, 80 mg/kg ZnO NP increased the serum concentrations of IgA, IgG, IgM, andinterleukin-10 and peroxidase activity, the jejunal mucosal villus height, villus width and goblet cell numbers. Dietary 80 or 160 mg/kg ZnO NP significantly altered mRNA abundances of genes related to antioxidant status, intestinal barrier and immunity in the jejunal mucosa. These results indicated that dietary supplementation with 40–160 mg/kg ZnO NP caused no obvious negative effects on liver function, but effectively improved growth performance, intestinal barrier function, immunity and antioxidant capacity. Dietary 40–160 mg/kg zinc oxide nanoparticle (ZnO NP) improved growth performance and enhanced immunity of broilers without obvious negative effects on liver function. Dietary 40–160 mg/kg ZnO NP improved intestinal barrier and intestinal morphology, and enhanced antioxidant capacity via Nrf2/HO-1 pathway. Doses of 40–80 mg/kg ZnO NP were suggested to alternate the combination of 80 mg/kg ZnSO4 and 5 mg/kg xanthomycin in diets of broilers. [ABSTRACT FROM AUTHOR]

This study investigated the effects of different doses of rutin on the growth performance, immunity, intestinal barrier, and antioxidant capacity of broilers. A total of two hundred and fifty-six 1-day-old male broilers were divided into 4 groups and fed basal diets supplemented with 0 (control group), 250, 500 and 1,000 mg rutin/kg, respectively, for 42 days. In the starter period (days 1–21) and whole trial period (days 1–42), broilers fed diets containing 500 mg rutin/kg had significantly (p < 0.05) higher average daily feed intake, body weight and average daily gain and better feed conversion ratio. Dietary 500 mg rutin/kg increased the villus height, villus height to crypt depth ratio and villus area, while reducing the B cell lymphoma 2 associated X mRNA expression (p < 0.05). Dietary 500 mg rutin/kg increased the level of IgA in serum and decreased serum tumour necrosis factor-α (TNF-α) content, and the nuclear factor kappa-B, interleukin-2 and TNF-α mRNA expression in jejunal mucosa (p < 0.05). Simultaneously, 500 and 1,000 mg rutin/kg significantly decreased serum diamine oxidase activity, D-lactic acid and lipopolysaccharide concentration, increased activities of total superoxide dismutase and total antioxidant capacity in jejunal mucosa (p < 0.05), and upregulated mRNA expressions of genes related to intestinal barrier and antioxidant capacity in jejunal mucosa (p < 0.05). These findings indicate that dietary rutin, especially at 500 mg/kg, improves broilers' growth performance, intestinal barrier function, immunity, and antioxidant capability, which may be related to the nuclear factor erythroid-2-related factor 2 (Nrf2) pathway. Dietary rutin improved growth performance, jejunal morphology, and intestinal barrier function. Dietary rutin enhanced the immunity via inhibiting NF-κB, and improved antioxidant capacity via activating Nrf2/HO-1 pathway in broilers. The optimal dose of rutin was 500 mg/kg in broiler diet. [ABSTRACT FROM AUTHOR]

In this paper, the nonlinear U model with time-varying coefficients is investigated and the transformation of the nonlinear model is accomplished by the Newton iterative algorithm. Based on the nonlinear U model, a control algorithm with cerebellar model articulation controller and proportional derivative (PD) in parallel is proposed. The algorithm learns online through a neural network while optimizing the output of the PD, which ultimately enables the actual output of the system to track up to the desired output. Considering that the nonlinear object has the characteristic of rapid change with time, the article improves the PD algorithm to nonlinear PD control algorithm to complete the design of the system. The algorithm automatically adjusts the weights according to the error magnitude to complete the controller parameter adjustment, thus reducing the error of the system. The simulation results show that the nonlinear PD algorithm is better than the PD algorithm, meanwhile, the tracking speed and control precision of the system are improved. [ABSTRACT FROM AUTHOR]

Ligustrazine and valsartan are commonly used drugs in the treatment of cardiac and cardiovascular disease. The interaction between ligustrazine and valsartan was studied to investigate the effect of ligustrazine on the pharmacokinetics of valsartan. The pharmacokinetics of valsartan (10 mg/kg) was investigated in Sprague–Dawley rats divided into three groups (with the pretreatment of 4 or 10 mg/kg/day ligustrazine for 10 days and without the pretreatment of ligustrazine as control) of six rats each. The in vitro experiments in rat liver microsomes were performed to explore the effect of ligustrazine on the metabolic stability of valsartan. Ligustrazine changed the pharmacokinetic profile of valsartan. In the presence of 4 mg/kg ligustrazine, the AUC(0–t) (385.37 ± 93.05 versus 851.64 ± 104.26 μg/L*h), t1/2 (5.46 ± 0.93 versus 6.34 ± 1.25 h), and Cmax (62.64 ± 9.09 versus 83.87 ± 6.15 μg/L) of valsartan was significantly decreased, and the clearance rate was increased from 10.92 ± 1.521 to 25.76 ± 6.24 L/h/kg and similar changes were observed in the group with 10 mg/kg ligustrazine (p < 0.05). The metabolic stability of valsartan was also decreased by ligustrazine as the half-life of valsartan in rat liver microsomes decreased from 37.12 ± 4.06 to 33.48 ± 3.56 min and the intrinsic clearance rate increased from 37.34 ± 3.84 to 41.40 ± 4.32 μL/min/mg protein (p < 0.05). Ligustrazine promoted the metabolism of valsartan via activating CYP3A4. The co-administration of ligustrazine and valsartan should be taken into account. [ABSTRACT FROM AUTHOR]

Cotyledon tomentosa Harv. is a well-known succulent plant that have important ornamental and economic value. In this study, we release and detail the complete chloroplast genome sequences of C. tomentosa. The whole chloroplast genome was 149,729 bp in length and comprised 131 genes, including 84 protein-coding genes, 37 tRNA genes, eight rRNA genes. The C. tomentosa. chloroplast genome had a GC content of 38.23%. Phylogenetic analysis based on the complete chloroplast genomes showed that C. tomentosa had a close relationship with Kalanchoe tomentosa, Bryophyllum daigremontianum and Kalanchoe fedtschenkoi. [ABSTRACT FROM AUTHOR]

Maternal diabetes has been demonstrated to adversely affect oocyte quality in mouse oocytes. However, the potential molecular mechanisms are poorly understood. Here, we established a type I diabetic mouse model and detected the increased reactive oxygen species (ROS) levels and decreased Sirt3 expression in oocytes from diabetic mice. Furthermore, we found that forced expression of Sirt3 in diabetic oocytes significantly attenuates such an excessive production of ROS. The acetylation status of lysine 68 of superoxide dismutase (SOD2K68) is dependent on Sirt3 in oocytes. In line with this, SOD2K68 acetylation levels were markedly increased in diabetic oocytes, and Sirt3 overexpression could effectively suppress this tendency. Importantly, the deacetylation-mimetic mutant SOD2K68R is capable of partly preventing the oxidative stress in oocytes from diabetic mice. In conclusion, our findings support a model where Sirt3 plays a protective role against oxidative stress in oocytes exposed to maternal diabetes through deacetylating SOD2K68. [ABSTRACT FROM PUBLISHER]

Adsorption plays an important role in the removal of pollutants such as fluoride from aqueous solutions. With the rapid development of environmental technology, TiO2particle has become promising material to adsorb fluoride ion because of its low cost, non-toxic, good chemical stability, and good sorption ability. This work used sol-gel and hydrothermal synthesis methods to prepare TiO2particles and load them onto SiO2particles. The physicochemical properties such as heat stability, particle size, and surface area of the resulting TiO2adsorbents were characterized with various analytical methods. In addition, their adsorption abilities to fluoride were determined under various conditions including different initial fluoride concentration, pH and coexisting ions. The maximum adsorption capacity of the TiO2adsorbents can reach up to 94.3 mg/g. The adsorption isotherms of fluoride onto the TiO2adsorbents can be closely described by the Langmuir model, suggesting the monolayer adsorption process. [ABSTRACT FROM PUBLISHER]

Pangenomes are replacing single reference genomes to capture all variants within a species or clade, but their analysis predominantly leverages graph-based methods that require multiple high-quality genomes and computationally intensive multiple-genome alignments. K-mer decomposition is an alternative to graph-based pangenomes. However, how to directly use k-mers for the population genetic analyses is unknown. Here, we developed a novel strategy that uses the variants of k-mer count in the genome for population analyses. To test the effectivity of this method, we compared it directly to the SNP-based method on the analysis of population structure and genetic diversity of 267 Saccharomyces cerevisiae strains within two simulated datasets and a real sequence dataset. The population structure identified with k-mers recapitulates that obtained using SNPs, indicating the effectiveness of k-mer-based approach, and higher genetic diversity within real dataset supported k-mers contained more genetic variants. Based on k-mer frequency, we found not only SNP but also some insertion/deletion and horizontal gene transfer (HGT) fragments related to the adaptive evolution of S. cerevisiae. Our study creates a framework for the alignment- and reference-free (ARF) method in population genetic analyses, which will be more pronounced in the species with no complete genome or highly diverged species. [ABSTRACT FROM AUTHOR]