The pharmacokinetic and residue depletion study of eugenol in carp (Cyprinus carpio)

IntroductionThe pharmacokinetic profile and residue depletion of eugenol in carp (Cyprinus carpio) tissues and plasma were performed by a convenient and reliable high-performance liquid chromatography (HPLC) method.MethodsThe eugenol in carp tissues and plasma was extracted with a mixed solution of acetonitrile and methanol. N-hexane was used to remove lipid impurities. The method was successfully applied to the pharmacokinetic and residue elimination of eugenol in carp after the carp was administered a medicated bath.ResultsThe average recoveries of eugenol in tissues and plasma fortified with four concentration levels were 69.0–106.6% and 80.0–86.7%, respectively. The relative standard deviations were < 8.9%. The limit of detection (LOD) was 0.01 μg/g in tissue and 0.008 μg/ml in plasma, respectively. The pharmacokinetic parameter of Cmax for eugenol in plasma at the concentrations of 20, 35, and 75 mg/L were 10.86, 17.21, and 37.32 mg/L, respectively. The t1/2 values were 3.68, 4.22, and 9.31 h. After the investigation of the anesthetic effect, 35 mg/L of eugenol was the optimal concentration for anesthesia. The highest accumulation concentration of eugenol in carp is in the liver and the lowest is in the muscle. In addition, the eugenol in tissue was eliminated rapidly and at a lower level than the LOD at 48 h. According to the residue elimination, the withdrawal time of eugenol was suggested at 5.2 days.DiscussionThese results indicate that the developed method had good linearity and accuracy, and is sensitive enough for the monitoring of eugenol residue in carp. The half-life of eugenol decreased with the increase in drug concentration and the eugenol was eliminated rapidly in carp tissues. 35 mg/L eugenol was recommended as an anesthetic in carp due to its favorable anesthetic effect and no mortality. This study will contribute to the establishment of MRL regulation and setting a withdrawal period

Growth differentiation factor-15/adiponectin ratio as a potential biomarker for metabolic syndrome in Han Chinese

AimsGrowth differentiation factor-15 (GDF-15) and adiponectin are adipokines that regulate metabolism. This study aimed to evaluate the roles of GDF-15, adiponectin, and GDF-15/adiponectin ratio (G/A ratio) as biomarkers for detecting metabolic syndrome (MS).Materials and methodsThis cross-sectional study included 676 participants aged 20–70 years in Jurong, China. The participants were divided into four groups based on sex and age (<40 and ≥40 years). MS was defined according to the modified National Cholesterol Education Program Adult Treatment Panel III criteria. Receiver operating characteristic curves were used to evaluate the performance of GDF-15, adiponectin, and the G/A ratio in predicting MS.ResultsThe prevalence of MS was 22.0% (149/676). Logistic regression analysis indicated that the G/A ratio and adiponectin levels, but not GDF-15 levels, were correlated with MS [odds ratio; 95% CI 1.010 (1.006–1.013) and 0.798 (0.735–0.865), respectively] after adjusting for confounding factors. The G/A ratio displayed a significant relationship with MS in each subgroup and with each MS component in both men and women; however, adiponectin concentrations were significantly associated with MS and all its components only in men (all P <0.05). The area under the curve (AUC) of the G/A ratio and the adiponectin level for MS was 0.758 and 0.748, respectively. The highest AUC was 0.757 for the adiponectin level in men and 0.724 for the G/A ratio in women.ConclusionsThis study suggests that the G/A ratio and adiponectin are potential biomarkers for detecting MS in women and men, respectively

Recovery of Magnesium from Ferronickel Slag to Prepare Magnesium Oxide by Sulfuric Acid Leaching

This paper provides a technical approach for efficiently recovering Mg from ferronickel slag to produce high-quality magnesium oxide (MgO) by using the sulfuric acid leaching method under atmospheric pressure. The leaching rate of magnesium is 84.97% after a typical one-step acid leaching process, which is because Mg in FNS mainly exists in the forsterite (Mg2SiO4) phase, which is chemically stable. In order to increase the leaching rate, a two-step acid leaching process was proposed in this work, and the overall leaching rate reached up to 95.82% under optimized conditions. The response surface methodology analysis for parameter optimization and Mg leaching rules revealed that temperature was the most critical factor affecting the Mg leaching rate when the sulfuric acid concentration was higher than 2 mol/L, followed by acid leaching time. Furthermore, interactive behavior also existed between the leaching temperature and leaching time. The leaching kinetics of magnesium from FNS followed a shrinkage-nuclear-reaction model with composite control, which were chemically controlled at lower temperatures and diffusion controlled at higher temperatures; the corresponding apparent activation energy was 19.57 kJ/mol. The leachate can be used to obtain spherical-like alkali magnesium carbonate particles with diameters of 5–10 μm at 97.62% purity. By using a further calcination process, the basic magnesium carbonate can be converted into a light magnesium oxide powder with a particle size of 2–5 μm (MgO content 94.85%), which can fulfill first-level quality standards for industrial magnesium oxide in China

Preparation of Silicon Carbide Powder from Amorphous Silica and Investigation of Synthesis Mechanism

An innovative process for preparing silicon carbide (SiC) from acid leaching residue of ferronickel slag through a carbon–thermal reduction process was proposed in this study. The results indicate that the acid leaching residue is an ideal silicon source for SiC preparation according to its high amorphous silica content of 84.20% and fine particle size of d50 = 29.16 μm. Compared with carbon black, activated carbon, and graphite, coke is the more appropriate carbon source for SiC preparation. A micron-size SiC powder with grade of 88.90% and an average particle size (d50) of 44.68 μm can be obtained under the following conditions: the mass ratio of coke to leaching residue as 1.2:1, in an air atmosphere, reducing at 1600 °C for 3 h, following by decarbonizing at 700 °C for 4 h. The XRD, SEM and FTIR analyses show that the prepared powder is 3C-SiC and belongs to the β-SiC crystal type. Based on thermodynamic analysis and micromorphology observation, it can be concluded that with amorphous silica as the silicon source, the carbon–thermal synthesis of SiC powder follows both the solid–solid reaction mechanism and the gas–solid mechanism. The SiC created through solid–solid reaction is primarily nucleated in situ on amorphous SiO2, with a size close to that of the original acid-leaching slag, while the SiC generated according to the gas–solid mechanism mainly nucleates heterogeneously on the surface of carbon particles, resulting in a smaller particle size and mostly adhering to the surface of solid–solid nucleated SiC particles. This study provides a feasible method for the effective utilization of amorphous silica, which is also significant for the efficient consumption of the vast acid leaching residue

Determination of polypeptide antibiotics in animal tissues using liquid chromatography tandem mass spectrometry based on in-line molecularly imprinted solid-phase extraction

Effective purification and enrichment of polypeptide antibiotics in animal tissues is always a challenge, due to the co-extraction of other endogenous peptides which usually interfere their final determination. In this study, a molecularly imprinted column was prepared by packing polymyxin E-imprinted particles into a 100 mm × 4.6 mm i.d. HPLC column. The as-prepared imprinted columns were able to tolerate 100% aqueous phase and exhibited good stability and high column efficiency. Polypeptides antibiotics with similar molecular size or spatial structure to polymyxin E were well retained by the imprinted column, suggesting class selectivity. After optimization of mobile phase conditions of imprinted column, polypeptide antibiotics in animal tissue extracts were enriched and cleaned up by in-line molecularly imprinted solid-phase extraction, allowing the screening of target analytes in complex samples at low concentration levels by UV detection. Eluate fraction from the imprinted column was collected, and further dried and re-dissolved with methanol-0.5% formic acid aqueous solution (80:20, v/v) for final LC-MS/MS analysis. Analysis was accomplished using multiple reaction monitoring (MRM) in positive electrospray ionization mode and analytes quantified using the matrix-matched external calibration curves. The results showed high correlation coefficients for target analytes in the linear range of 2 ∼ 200 μg kg-1. At four different concentration levels (limit of quantification, 50, 100 and 200 μg kg-1), recoveries of four polypeptide antibiotics in swine, cattle and chicken muscles ranged from 66.7 to 94.5% with relative standard deviations lower than 16.0%. The limits of detection (LOD) were 2.0 ∼ 4.0 μg/kg, depending upon the analyte and sample. Compared with a conventional pretreatment method, the imprinted column was able to remove more impurities and to significantly reduce matrix effects, allowing the accurate analysis of polypeptide antibiotics.This research was funded by the National Science Foundation of China (grant number 31572562), the Key Pro gram of Guangzhou Science and Technology Plan (grant number 201804020019) and the Special Funds of the National Natural Sci ence Foundation of Guizhou University ([2020]25)Peer reviewe

Correlation between skeletal muscle mass and islet function in patients with type 2 diabetes mellitus

"Objective To investigate the correlation between skeletal muscle mass and islet function, skeletal muscle mass and insulin resistance in patients with type 2 diabetes mellitus (T2DM), and to elaborate on the clinical significance of skeletal muscle mass in the maintenance of blood glucose homeostasis. Methods A total of 274 adult T2DM patients hospitalized in the Department of Endocrinology, the First Affiliated Hospital with Nanjing Medical University from August 2023 to February 2024 were retrospectively analyzed. The basic information of patients was collected, the grip strength of patients was measured, and the blood and urine samples were taken for biochemical detection. Bioelectrical impedance analysis (BIA) was used to measure the skeletal muscle content of the upper and lower limbs, visceral fat area (VFA) and waist circumference fat weight. The skeletal muscle mass index (SMI) and appendicular skeletal muscle mass index (ASMI) were calculated, respectively. Pearson correlation method was used to analyze the correlation of grip strength, SMI and ASMI levels with blood glucose, insulin and C-peptide levels, islet β cell function indicators ［islet β cell function (HOMA-β), corrected insulin reactivity (CIR), insulinogenic index (IGI)］, and homeostasis model assessment of insulin resistance (HOMA-IR) and insulin sensitivity index(ISI). Multirariable linear regression was further used to analyze the correlation between skeletal muscle mass and islet function in T2DM patients with different VFA and BMI. Results In T2DM patients, fasting blood glucose and insulin, 120-minute postprandial blood glucose, and HOMA-IR were negatively correlated with grip strength levels (P＜0.05), while 120-minte postprandial insulin was positively correlated with grip strength levels (P＜0.05). SMI and ASMI were negatively correlated with blood glucose levels at different time points of glucose tolerance in T2DM patients (P＜0.01), and positively correlated with serum C-peptide levels, HOMA-β, CIR, and IGI, respectively (P＜0.05). The level of SMI in lower limbs was negatively correlated with blood glucose, at different time points of glucose tolerance (P＜0.01), and positively correlated with insulin, C-peptide at different time points, as well as HOMA-β, IGI and CIR in T2DM patients (P＜0.05); However, except for the negative correlation between SMI level of upper limbs and 120 min blood glucose (P=0.019), there was no correlation between SMI level and other indicators mentioned above (P ＞0.05). After adjusting for gender and age, BMI stratified analysis showed that the correlations of SMI level with HOMA-β, IGI and CIR were significant in the normal BMI subgroup (P**＜0.05), while the correlations of SMI level with HOMA-IR , ISI were not significant in the normal BMI subgroup (P*>0.05), but significant in the overweight and obese subgroups (P*>0.05). Conclusion Skeletal muscle mass is closely associated with blood glucose, islet function and insulin resistance in patients with T2DM. Increasing skeletal muscle mass of the whole body, especially that of the lower limbs and reducing the fat content accordingly play critical roles in the maintenance of glycemic homeostasis and improving islet function in patients with T2DM.

Neural networks for solving linear and quadratic programming problems with modified Newton’s and Levenberg-Marquardt methods

Constrained optimization problems entail the minimization or maximization of a linear or quadratic objective function that is subject to linear equality and inequality restrictions. They are very important, appearing in real world scenarios including signal processing, identification, the design of filters and function approximation. In recent years, Artificial Neural Networks (ANNs) have been applied to several classes of constrained optimization problems, with promising results. Most of the ANN methods involve an iterative process, in which a feasible direction that decreases the objective function is determined at each step and a one-dimensional optimization is performed along this direction until a predetermined stopping criterion is satisfied. Normally, programming problems are solved through penalty function methods, often entailing a sequence of unconstrained optimization problems for different values of penalty parameters to ensure convergence. Currently, there are two main neural-network models for solving linear programming (LP) and quadratic programming (QP) problems. The first employs the steepest descent method and the penalty function method with an objective function that can be viewed as an "inexact" penalty function that can only obtain truly optimal solutions when the penalty parameter is infinite. In the second approach, the solution is formed by two mutually exclusive subsystems. Both of these specialized networks can solve LP and QP problems in execution times that are several orders of magnitude faster than the most popular numerical algorithms for general purpose digital computers. Nevertheless, the use of penalty function methods has been found to be somewhat disadvantageous due to inherent numerical instabilities. It is generally impossible to choose a very large penalty parameter in the networks making it very difficult to obtain approximate solutions and impossible to find accurate solutions. Moreover, the existing models concentrate on the steepest descent method. Here, drawbacks in this method are discussed, followed by a choice of two popular numerical algorithms, Newton's method and the Levenberg-Marquardt (L-M) method, as the focus of the investigation. After demonstrating the operation of these algorithms in a neural network setting, modifications to them are introduced. Benchmark LP and QP problems are utilized to illustrate the progress of the steepest descent algorithm and subsequently the superior performance of the modified Newton's and L-M methods