Batches Of Samples Research Articles

A study for quality evaluation of Lysimachiae herba from different origins based on fingerprint-activity relationship modeling and multi-component content determination

Ethnopharmacological relevanceLysimachiae Herba (LH), called Jinqiancao in Chinese, is a commonly used traditional Chinese medicine in clinical practice. Doctors in the Qing Dynasty recorded that it tastes bitter, sour, and slightly cold, and it belongs to the liver, gallbladder, kidney, and bladder meridians. It has the effects of removing dampness and jaundice, eliminating gallstones, and reducing blood stasis. Because of its potent pharmacological effects, it is extensively utilized in the treatment of hepatobiliary and urinary system stones, jaundice, hepatitis, and cholecystitis. Although LH is included in “Sichuan authentic Chinese herbal medicine records”, the quality of it from different origins still lacks reliable evaluation methods, which is difficult to reflect the high quality of LH from Sichuan. Aims of the studyThis study aimed to establish a fingerprint-activity relationship model between the fingerprint of LH and its protective effect on cholestatic liver injury, and to evaluate the quality of LH from Sichuan and Guizhou by multivariate statistical analysis. Materials and methods20 batches of LH samples were collected from Sichuan and Guizhou. Characteristic fingerprints of samples were established by UHPLC−Triple TOF−MS/MS and the chemical pattern recognition analysis was carried out by HCA. Then, a rat model of cholestatic liver injury was established by intragastric administration of ANIT. Combined with the common peak information of fingerprint and pharmacodynamic index results, GCA and BCA were used to screen the efficacy markers. Finally, based on UHPLC−QTRAP−MS/MS, the content of efficacy markers was simultaneously determined, and the overall quality of LH from two origins was evaluated by PCA and TOPSIS. ResultsIn the fingerprint of 20 batches of LH, 15 common peaks were identified in the negative ion mode, and the similarity was between 0.887 and 0.981. Pharmacological results showed that, compared with the control group, the content of AST, ALT, ALP, TBA, TBIL, and MDA in serum increased, and the content of GSH and SOD activity decreased after 48 h of ANIT administration. In addition, compared to the model group, different doses of LH from the two origins could decrease the serum levels of AST, ALT, ALP, TBA, TBIL, and MDA, raise the levels of GSH and SOD activity, reduce the infiltration range of inflammatory cells, and improve the cholestatic liver injury in rats. Among them, the pharmacodynamic indices of the SCHD group were significantly better. GCA and BCA showed that a total of 7 constituents related to the efficacy were screened, which were proanthocyanidin B1, ferulic acid, hyperoside, astragalin, nicotiflorin, afzelin, and kaempferol. Besides, the content of 7 active constituents in samples from Sichuan was higher than that from Guizhou, indicating that the quality of samples from Sichuan may be better, consistent with the result of the pharmacological experiment. ConclusionThe quality and efficacy of LH from different origins were stable, and all of them had protective effects on cholestatic liver injury in rats. The method established in this study is accurate and reliable, and it can be used to comprehensively evaluate the internal quality of LH.

ScDisInFact: disentangled learning for integration and prediction of multi-batch multi-condition single-cell RNA-sequencing data

Single-cell RNA-sequencing (scRNA-seq) has been widely used for disease studies, where sample batches are collected from donors under different conditions including demographic groups, disease stages, and drug treatments. It is worth noting that the differences among sample batches in such a study are a mixture of technical confounders caused by batch effect and biological variations caused by condition effect. However, current batch effect removal methods often eliminate both technical batch effect and meaningful condition effect, while perturbation prediction methods solely focus on condition effect, resulting in inaccurate gene expression predictions due to unaccounted batch effect. Here we introduce scDisInFact, a deep learning framework that models both batch effect and condition effect in scRNA-seq data. scDisInFact learns latent factors that disentangle condition effect from batch effect, enabling it to simultaneously perform three tasks: batch effect removal, condition-associated key gene detection, and perturbation prediction. We evaluate scDisInFact on both simulated and real datasets, and compare its performance with baseline methods for each task. Our results demonstrate that scDisInFact outperforms existing methods that focus on individual tasks, providing a more comprehensive and accurate approach for integrating and predicting multi-batch multi-condition single-cell RNA-sequencing data.

Multi-level chemical characterization and anti-inflammatory activity evaluation of the polysaccharides from Prunella vulgaris

Prunella vulgaris (PV) is a medicine and food homologous plant, but its quality evaluation seldom relies on the polysaccharides (PVPs). In this work, we established the multi-level fingerprinting and in vitro anti-inflammatory evaluation approaches to characterize and compare the polysaccharides of P. vulgaris collected from the major production regions in China. PVPs prepared from 22 batches of samples gave the content variation of 5.76–24.524 mg/g, but displayed high similarity in the molecular weight distribution. Hydrolyzed oligosaccharides with degrees of polymerization 2–14 were characterized with different numbers of pentose and hexose by HILIC-MS. The tested 22 batches of oligosaccharides exhibited visible differences in peak abundance, which failed to corelate to their production regions. All the PVPs contained Gal, Xyl, and Ara, as the main monosaccharides. Eleven batches among the tested PVPs showed the significant inhibitory effects on NO production on LPS-induced RAW264.7 cells at 10 μg/mL, but the exerted efficacy did not exhibit correlation with the production regions. Conclusively, we, for the first time, investigated the chemical features of PVPs at three levels, and assessed the chemical and anti-inflammatory variations among the different regions of P. vulgaris samples.

Authentication of the botanical origin of monofloral honey by dielectric barrier discharge ionization high resolution mass spectrometry (DBDI-HRMS). Breaching the 6 s barrier of analysis time

Rapid volatile profiling of monofloral honey with dielectric barrier discharge ionization high resolution mass spectrometry (DBDI-HRMS) enabled the authentication of the studied honeys’ floral sources in as little as 6 s in a solventless manner. The overarching goal of this study was the set-up of a rapid and cost effective tool for the determination of the botanical origin of monofloral honey that can be easily accessed i) by beekeepers to authenticate and, thus, enhance the value of their own honey and ii) by the food industry for quality checks. To this aim, the volatile compounds of two independent batches of honeys with seven different botanical origins (acacia, dandelion, chestnut, rhododendron, citrus, sunflower, and linden) were captured by DBD-HRMS. A total of 112 monofloral honeys were analyzed by three different operators. Using the spectral data of the first batch of honeys, we built up and compared the performances of three different classification algorithms: least absolute shrinkage and selection operator (LASSO), partial least squares discriminant analysis (PLS-DA), and random forest (RF). The performances of the three classifiers were verified by repeated cross-validation, permutation test, resubstitution into the training set, and then finally validated with a second, independent set of honeys by a different, inexperienced operator. The outcomes of the tests were expressed by the area under the curve (AUC), Kappa statistic, overall accuracy, and sensitivity and specificity rates. The misclassification rates of the built classifiers were evaluated by computing different key indicators, and the repeatability of the analytical method was also verified by cosine similarity. These insights are relevant for future adoption of the method in routine work. We determined that the RF classifier was the most powerful in predicting the floral source of the honeys. The RF classifier produced high performance values when predicting an independent batch of samples analyzed by a different, inexperienced operator (AUC 82.91 %, overall accuracy 81.25 %, Kappa 77.78 %, sensitivity 81.05 %, and specificity 96.76 %). The misclassified honeys were those characterized by the presence of other nectars and or pollens, as previously pointed to by the sensory panelists This proof-of-principle work warrants a future large-scale study to validate and challenge the method with honeys from different harvests and of different geographical origins.

Comprehensive metabolome characterization and comparison between two sources of Dragon's blood by integrating liquid chromatography/mass spectrometry and chemometrics.

Dragon's Blood (DB) serves as a precious Chinese medicine facilitating blood circulation and stasis dispersion. Daemonorops draco (D. draco; Qi-Lin-Jie) and Dracaena cochinchinensis (D. cochinchinenesis; Long-Xue-Jie) are two reputable plant sources for preparing DB. This work was designed to comprehensively characterize and compare the metabolome differences between D. draco and D. cochinchinenesis, by integrating liquid chromatography/mass spectrometry and untargeted metabolomics analysis. Offline two-dimensional liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (2D-LC/IM-QTOF-MS), by utilizing a powerful hybrid scan approach, was elaborated for multicomponent characterization. Configuration of an XBridge Amide column and an HSS T3 column in offline mode exhibited high orthogonality (A0 0.80) in separating the complex components in DB. Particularly, the hybrid high-definition MSE-high definition data-dependent acquisition (HDMSE-HDDDA) in both positive and negative ion modes was applied for data acquisition. Streamlined intelligent data processing facilitated by the UNIFI™ (Waters) bioinformatics platform and searching against an in-house chemical library (recording 223 known compounds) enabled efficient structural elucidation. We could characterize 285 components, including 143 from D. draco and 174 from D. cochinchinensis. Holistic comparison of the metabolomes among 21 batches of DB samples by the untargeted metabolomics workflows unveiled 43 significantly differential components. Separately, four and three components were considered as the marker compounds for identifying D. draco and D. cochinchinenesis, respectively. Conclusively, the chemical composition and metabolomic differences of two DB resources were investigated by a dimension-enhanced analytical approach, with the results beingbeneficial to quality control and thedifferentiated clinical application of DB.

Novel sfericase protease improves amino acid digestibility of soybean meal and rapeseed meal in broiler chickens

ABSTRACT 1. Two experiments were conducted to explore the effects of an exogenous sfericase protease on the apparent ileal nutrient digestibility of soybean meal (SBM) and rapeseed meal (RSM) in broiler chickens. 2. In each experiment, a total of 256 sixteen-day-old male Cobb 500 broilers were fed one of four semi-purified experimental diets, comprising two different batches (A and B) of samples for either SBM (Exp. 1) or RSM (Exp. 2) without or with an exogenous sfericase (0 or 30,000 NFP/kg). Each experimental diet was fed to eight replicate pens of broiler chickens from 16 to 21 d of age (eight birds per cage), and ileal digesta were collected for measuring the digestibility coefficients. 3. In Exp. 1, the amino acid digestibility was greater (P < 0.05) in SBM B compared with SBM A for Arg and Val, and a similar trend (P < 0.1) was observed for Tyr, Leu and Thr. Exogenous sfericase increased (P < 0.10) digestibility of most of amino acids except Gly, His and Trp. There was an interaction between SBM source and sfericase, whereby digestibility of P, N and Asp was increased by sfericase for SBM B but not for SBM A. In Exp. 2, there was no interaction (P > 0.05) between RSM source and sfericase for ileal nutrient digestibility. Digestibility was greater in RSM A compared to RSM B for all non-essential AA and most essential AA (except for Trp), while the reverse was noted for Ca and P (P < 0.05). Exogenous sfericase increased (P < 0.1) digestibility for all amino acids except Cys and Met. 4. In conclusion, the current studies showed that both SBM and RSM batches influenced amino acid digestibility. Sfericase protease supplementation increased amino acid digestibility for both SBM and RSM. The digestibility effects were greater in the SBM batch with low digestibility for N and Asp which was in line with an increase in P digestibility.

Metagenomics reveals differences in the composition of bacterial antimicrobial resistance and antibiotic resistance genes in pasteurized yogurt and probiotic bacteria yogurt from China

Antimicrobial resistance has become a global public health concern, and antibiotic resistance genes (ARG) in food are a research focus. In China, probiotics and pasteurized yogurts are the 2 main types of commercially available yogurt, but the distribution and differences of antibiotic-resistant bacteria and gene types in these products are not well known. This study used a shotgun metagenomic approach to analyze 22 different types of yogurt collected from 9 main yogurt-producing areas in China; each type of yogurt included 8 different batches of samples. The abundance and diversity of bacteria identified in probiotic yogurt were significantly higher than those in pasteurized yogurt, with Acetobacter, Raoultella, and Burkholderia identified as unique and highly abundant genera in probiotic yogurt. Similarly, the abundance of Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp. was higher than that in pasteurized yogurt. A total of 1,149 ARG subtypes belonging to 16 ARG types were identified, with the highest abundance of rifampicin, multidrug efflux pumps, and quinolone resistance genes detected. Network analysis revealed significant nonrandom co-occurrence relationships between different types and subtypes of ARG in yogurt samples. A total of 44 ARG subtypes in pasteurized yogurt were potentially hosted by 36 bacterial genera, and in probiotic yogurt, 63 ARG were expected to be hosted by 86 bacterial species from 37 genera. These findings indicate potential safety issues in fermented dairy products and emphasize the need for a more hygienic environment when processing probiotic yogurt.

Systematic evaluation of Rutongshu oral liquid based on chromatographic fingerprinting and nontargeted metabolomic analysis

AbstractBased on chromatographic fingerprinting combined with quantitative analysis on characteristic chemical constituents as well as hierarchical cluster analysis, an easy and sensitive approach utilizing high performance liquid chromatography (HPLC) was developed for the identification and quality evaluation of Rutongshu oral liquid (ROL). What is more, nontargeted metabolomic analysis was conducted to gain a global view in terms of its chemical profile. In this study, 16 peaks from different batches (S1–S10) of ROL samples produced by Taihe Hospital of Chinese Medicine were selected as common peaks for the evaluation of their similarity whose values of all tested 10 batches exceeded 0.90 when compared with the control fingerprints. Meanwhile, simultaneous quantification of five markers in the oral solution, including albiflorin, paeoniflorin, chlorogenic acid, quercetin and ferulic acid was performed, and standard curves established for respective reference substances showed good regression in the linear range (r2 &gt; 0.999) with recoveries in the range of 98.96–102.35%. The ultra-high performance liquid chromatography (UHPLC) combined with Orbitrap Exploris 120 mass spectrometer resulted in 88 identified compounds. The results of validation showed that the established method was reproducible, precise and stable. This study offers an effective, dependable and useful approach for the systematic evaluation of the hospital formulation ROL.

Lignan contents of Schisandra chinensis (Turcz.) Baill. from different origins—A new model for evaluating the content of prominent components of Chinese herbs

BackgroundAs a traditional Chinese herbal medicine, Schisandra chinensis exhibits various effects such as liver protection, blood sugar regulation, blood lipid regulation, immune function regulation, antidepressant activity, etc. However, because of its intricate composition, diverse origins, and medicinal effects depending on complex compound groups, there are differences in the lignan composition of S. chinensis from different origins. Therefore, it is currently difficult to evaluate the quality of medicinal materials from plants of different origins using a single qualitative quality control index. PurposeThis paper aims to investigate the potential relationship between the lignan components of S. chinensis from different origins and to establish stable assessment indices for determining the lignan content of S. chinensis from multiple perspectives. MethodsIn this study, we collected S. chinensis samples of seven major origins in China, and randomly sampled 6–9 batches of each origin for a total of 60 batches. The lignan content was determined by HPLC, and its distribution law of the ratio of each lignan component of S. chinensis to Schisandrol A content was analyzed. Combining network pharmacology and differential analysis between samples, the stable and effective substances used as quality markers were determined. ResultsThere were some correlations among the lignan contents of S. chinensis, some correlations between schisandrin A and other lignans of S. chinensis could be determined. The ratio of each component to the indicator component schisandrol A was evenly distributed and reflected the lignan content of S. chinensis to some extent. Four substances (schisandrol A, schisandrol B, schisantherin A, and schisandrin C) were determined by network pharmacology combined with the analysis results of HCA, PCA and PLS-DA to further optimize the model. They displayed a strong connection with the core target, a large contribution rate to the principal components, and a stable content in each batch of samples, suggesting that these components may be the main active substances of S. chinensis lignans. Therefore, they could be used as main indicators evaluating the advantages and disadvantages of S. chinensis by examining the consistency of component proportions. ConclusionThis method can intuitively evaluate the content of main lignans in S. chinensis. This quality assessment model is an exploration of the multi-component comprehensive evaluation system of S. chinensis, providing a new concept for the quality evaluation system of Chinese herbal medicines.

Characterization of ruminal degradation, intestinal digestion and total true nutrient supply to dairy cows from feedstocks and coproducts from Canola bio-oil processing: Impact by source origin.

The objective of this study was to characterize ruminal degradation, intestinal digestion and total true nutrient supply to dairy cows from canola feedstock (canola seeds) and coproducts (meal and pellets) from bio-oil processing which were impacted by source origin. The feedstocks and coproducts (mash, pellet) were randomly collected from five different bio-oil processing plants with five different batches of samples in each bio-processing plant in Canada (CA) and China (CH). In situ rumen degradation kinetics were determined using four fistulated Holstein cows with incubation times at 0, 2, 4, 8, 12, 24 and 48 h. Intestinal digestions were determined using the three-step in vitro method with preincubation at 12 h. The DVE/OEB and National Research Council systems were applied to evaluate the truly absorbable nutrient supply to dairy cows and feed milk values (FMVs). The results showed that in situ undegradable fractions (U) (p = 0.025) were higher in CA meals, and potentially degradable fraction of D was higher (p = 0.016) in CH meals. CH meals had higher total digestible dry matter (TDDM, p = 0.018) and intestinal digestibility of protein (dIDP, p = 0.016). Canola meals from CA had lower MREE (microbial protein synthesized in the rumen based on available rumen degradable protein; p = 0.011) and DVME (rumen synthesized microbial protein digested in the small intestine; p = 0.011) and had higher ECP (endogenous protein in the small intestine, p = 0.001) and absorbed endogenous crude protein (truly absorbed ECP in the small intestine) than CH (p = 0.001). The FMV evaluated based on the metabolic protein and net energy showed no differences between CA and CH in both coproducts and feedstocks.

GREEN TECHNOLOGY FOR SUSTAINABLE AGRICULTURE: BIO-FERTILIZER PRODUCTION FROM MUNICIPAL WASTE TO PRESERVE THE ENVIRONMENT

This study addresses the pressing issue of municipal waste (MW) management by proposing an innovative approach to transform residential solid waste into a valuable resource using green technology. MW, sourced from diverse sectors, undergoes various disposal methods, including incineration, recycling, and landfilling. In Malaysia, the composition of MW aligns with global trends, with food waste and plastic being the predominant categories. This research focuses on producing fertilizer from residential solid waste through a green technology process, utilizing a sequential procedure involving high pressure, high temperature, and energized water to de-polymerize hemicellulose and lignin, followed by microbial enzymatic fermentation. The developed green technology introduces a novel apparatus designed for treating MW in a high-temperature, low-pressure rotating vessel using indirect heating with thermal fluid. The experimental protocol involves four batches of MW samples, evaluating the mass differential before and after the treatment process. Furthermore, a 7-week observation period assesses chili plant growth as an indicator of fertilizer effectiveness. Results indicate a significant 71% mass reduction of MW, amounting to 201.26 kg, emphasizing the efficacy of the developed process. The investigation extends to plant height, comparing MW-derived fertilizer with commercial fertilizer over a 5-week period. Remarkably, chili plants fertilized with MW-derived fertilizer exhibit a greater height of 8.6 cm, surpassing the 7.3 cm observed with commercial fertilizer. This study concludes that MW-derived fertilizer is highly recommended for enhancing plant growth and health in Malaysia, suggesting a sustainable production system. The research not only contributes to waste management but also aligns with broader goals of promoting environmentally conscious and sustainable agricultural practices, emphasizing the potential of green technology in addressing the challenges of municipal waste.

Adsorption of rare earth elements on a magnetic geopolymer derived from rice husk: studies in batch, column, and application in real phosphogypsum leachate sample.

There is a growing need to develop new strategies for rare earth element (REE) recovery from secondary resources. Herein, a novel approach to utilize biogenic silica (from rice husk) and metakaolin was employed to fabricate magnetic geopolymer (MGP) by incorporating metallic iron. The fabricated MGP adsorbent material was used to uptake Ce3+, La3+, and Nd3+ from synthetic solutions and real phosphogypsum leachate in batch and column modes. The MGP offers a negatively charged surface at pH above 2.7, and the uptake of REEs rises from pH 3 to 6. The kinetic study validated that the kinetics was much faster for Nd3+, followed by La3+ and Ce3+. A thermodynamic investigation validated the exothermic nature of the adsorption process for all selected REEs. The desorption experiment using 2mol L-1 H2SO4 as the eluent demonstrated approximately 100% desorption of REEs from the adsorbent. After six adsorption-desorption cycles, the MGP maintained a high adsorption performance up to cycle five before suffering a significant decrease in performance in cycle six. The effectiveness of MGP was also assessed for its applicability in recovering numerous REEs (La3+, Ce3+, Pr3+, Sm3+, and Nd3+) from real leachate from phosphogypsum wastes, and the highest recovery was achieved for Nd3+ (95.03%) followed by Ce3+ (86.33%). The operation was also feasible in the column presenting suitable values of the length of the mass transfer zone. The findings of this investigation indicate that MGP adsorbent prepared via a simple route has the potential for the recovery of REEs from synthetic and real samples in both batch and continuous operations modes.

Self-organizing model reference adaptive control for aircraft with enhanced persistent excitation

Model Reference Adaptive Control (MRAC) methods are commonly applied in aerospace control systems, yet they face challenges in terms of persistent excitation, adaptation speed, and network structure design. To tackle these issues, this study introduces a novel MRAC method that employs practical techniques, including fast adaptation, experience replay, and network self-organization. Specifically, this study emphasizes three key contributions. First, it introduces a modified MRAC architecture that incorporates a fast adaptation term and a network approximation term to compensate for control errors more effectively. The fast adaptation term, which exhibits higher adaptive speed, enables quick response to dynamic variations and is stored in an experience replay buffer. Additionally, the network term is trained using batches of past samples extracted from the experience replay buffer, rather than relying solely on the current sample. This approach successfully overcomes challenges related to achieving persistent excitation and setting adaptation speed. Secondly, this paper introduces an online method for network self-organization to approximate a global model. This approach autonomously selects basis functions to enhance the organization of the network, leading to improved matching and overall performance. Finally, theoretical proofs and numerical simulations are presented to validate the effectiveness of the proposed techniques and demonstrate the advantages of the method in terms of parameter convergence, learning speed, and control stability.

Determination of teicoplanin and ramoplanin residues in aquaculture products by a modified QuEChERS method combined with UPLC-MS/MS

A QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) method was developed to provide good analytical results for teicoplanin (TEC) and ramoplanin (RAM) residues in aquaticproducts. The analytes was extraction from aquatic product samples using chitosan in the QuEChERS procedure. Compared to conventional adsorbents, chitosan has a relatively good purification ability for the targets.The matrix effects of aquatic products, such as crucian carp, carp, silver carp, tilapia, mandarin fish, turbot, shrimp, sea cucumber and so on, were evaluated by high performance liquid chromatography coupled to triple-quadrupole tandem mass spectrometry. Throughout the validation experiments, the limits of detections and quantifications ranged from 0.4 ∼ 0.8 μg kg−1 and 1.0 ∼ 3.0 μg kg−1, respectively. Calibration curves showed correlation coefficient values higher than 0.998 in range between 1 and 100 μg kg−1. The recoveries ranged from 89.8 % to 110.0 % with relative standard deviation less than 7.2 % in nine typical aquaticproducts. The method shows low matrix effect (-18.5 %∼-2.6 %) for all targets in different aquaticproducts. The proposed methods proved to be reliable, effective and enables rapid determination of large batch samples, indicating its good applicability for detection and monitoring of TEC and RAM residues in aquaticproducts.

Rapid and robust bacterial species identification using hyperspectral microscopy and gram staining techniques.

Gram staining can classify bacterial species into two large groups based on cell wall differences. Our study revealed that within the same gram group (gram-positive or gram-negative), subtle cell wall variations can alter staining outcomes, with the peptidoglycan layer and lipid content significantly influencing this effect. Thus, bacteria within the same group can also be differentiated by their spectra. Using hyperspectral microscopy, we identified six species of intestinal bacteria with 98.1% accuracy. Our study also demonstrated that selecting the right spectral band and background calibration can enhance the model's robustness and facilitate precise identification of varying sample batches. This method is suitable for analyzing bacterial community pathologies.

Towards generalizable food source identification: An explainable deep learning approach to rice authentication employing stable isotope and elemental marker analysis

In addressing the generalization issue faced by data-driven methods in food origin traceability, especially when encountering diverse input variable sets, such as elemental contents (C, N, S), stable isotopes (C, N, S, H and O) and 43 elements measured under varying laboratory conditions. We introduce an innovative, versatile deep learning-based framework incorporating explainable analysis, adept at determining feature importance through learned neuron weights. Our proposed framework, validated using three rice sample batches from four Asian countries, totaling 354 instances, exhibited exceptional identification accuracy of up to 97%, surpassing traditional reference methods like decision tree and support vector machine. The adaptable methodological system accommodates various combinations of traceability indicators, facilitating seamless replication and extensive applicability. This groundbreaking solution effectively tackles generalization challenges arising from disparate variable sets across distinct data batches, paving the way for enhanced food origin traceability in real-world applications.

MODELING AND INVESTIGATION OF THE INFLUENCE OF LOADINGMODE ON THE DEFORMATION PROCESS OF ASPHALT CONCRETEMATERIALS

The article considers a problem of calculating the deformations of forward and reversed creep tension of rheonomic materials. The hereditary theory of creep by Yu.N. Rabotnov is used to describe the nonlinear deformation process. Proposed a method for determining the necessary material characteristics from forward and reversed creep data. During the experiments, there were tested two batches of asphalt concrete samples. Also, was shown behavior of asphalt concrete at cyclic increasing and constant loading modes. At a temperature T = 24 °C were tested 10 samples at cyclic increasing loading mode. Cyclic stresses were equal to 0.041; 0.074; 0.111; 0.148; 0.183 MPa and duration period between loading and relax period were chosen to be 570 seconds. At cyclic constant loading were investigated individual samples for the parameters of forward and reversed creep at stresses of 0.041; 0.117. Then, investigated the affect of reloading two reversed creep process of asphalt concrete samples. From first batch of samples were tested 9 samples before destruction with a period 65 seconds: forward creep of samples at for the following 5 seconds; reversed creep at for the following 60 seconds. From the second batch of samples were tested 11 samples of asphalt concrete before destruction with period 70 seconds: forward creep for the following 10 seconds and reversed creep at for the following 60 seconds. Test results showed that the level of return of second batch increased than the first batch of samples. In the work were tested 5 samples of asphalt concrete according to the direct tensile scheme until a complete failure. Test temperature was T=22-24 °C. For each level of loading with constant rate: 0,6519; 0,4678; 0,0580; 0,0489; 0,0055 MPas-1.Using experimental data, were found parameters of the deformation at different constant rate of loading. As a result, all samples fractured brittle at small deformations.

Determination of 15 preservative allergens in cosmetics by gas chromatography-tandem mass spectrometry

Most preservatives are irritating and can easily induce skin sensitivities. Therefore, both domestic and international regulations impose clear restrictions on the use of preservatives in cosmetics. Herein, gas chromatography-tandem mass spectrometry (GC-MS/MS) was employed to simultaneously analyze the levels of 15 preservative allergens in cosmetics. Further, a precise identification approach based on a two-column retention index and mass spectrometry matching degree was developed. Cosmetic samples were extracted via acetonitrile vortex ultrasound extraction and then dehydrated with anhydrous MgSO4. The preservative allergens were separated on two columns, namely, DB-5MS and DB-WAX. Targets were identified using electron impact ionization (EI) source and the multiple reaction monitoring (MRM) mode and characterized using a retention index calibrated by a series of n-alkane standards. Following two tests, the LODs for the 15 preservative allergens on the DB-5MS column were in the range of 0.02-0.2 mg/kg, while those for 12 preservative allergens on the DB-WAX column were in the range of 0.01-20 mg/kg. The preservative allergens on the DB-5MS and DB-WAX columns demonstrated strong correlations, with all correlation coefficients exceeding 0.99. The recoveries for the 15 preservative allergens were in the range of 70.1%-129.8% at low, medium, and high levels, and the relative standard deviations (RSDs) were all below 15% (n=6) when using water, lotion, facial mask, and cream as the representative matrix. Next, 80 batches of genuine samples were tested using the established method. Isopropyl 4-hydroxybenzoate, a prohibited preservative, was detected in two sample batches using the DB-5MS and DB-WAX columns. Additionally, 11 and 10 restricted preservative allergens were identified on the DB-5MS and DB-WAX columns, respectively. The test results indicate that the double-column system approach offers excellent accuracy, effectively preventing false-positive and false-negative results, and can detect the 15 preservative allergens in cosmetics. The use of the retention index for the qualitative detection of these preservative allergens offers valuable options for non-targeted screening and meeting regulatory criteria.

Spin crossover FeIII complexes with a substituted Hqnal ligand: effects of anions and solvents.

A new substituted Hqnal ligand, Hqnal-5-Brq, and four resulting FeIII complexes [Fe(qnal-5-Brq)2]A·sol (A = NO3-, sol = CH3OH 1; A = ClO4-, sol = CH3OH 2; A = OTf-, sol = 2CH3OH·H2O 3; and A = NTf2-, sol = CH2Cl24; Hqnal-5-Brq = N-(5-bromo-8-quinolinyl)-2-hydroxynaphthaldimine), have been synthesized and characterized. All four complexes, despite having different anions, adopt similar 1D [Fe(qnal-5-Brq)2]+ cation chains linked by orthogonal π⋯π interactions. These chains are further connected to form 2D and 3D structures by other supramolecular interactions. Complexes 1-3 all exhibit abrupt spin crossover behaviors, with the transition temperatures being 230, 189, and 185 K, respectively, while complex 4 is in a high-spin state. The influence of solvents on spin crossover properties was assessed via magnetic measurements on the desolvated samples. Following desolvation, while complexes 1 and 2 show slight variations in their transition temperatures, complexes 3 and 4 undergo significant changes in their magnetic profiles. Desolvation in complex 3 leads to either a HS state or a very incomplete hysteretic transition with a low transition temperature for different sample batches. In contrast, the gradual desolvation in complex 4 leads to diminished solvent residues and progressive transition from a stable HS state to an SCO-active state.

Simultaneous determination of 78 pesticide residues and 16 mycotoxins in tsampa by an improved QuEChERS method coupled with ultra performance liquid chromatography-tandem mass spectrometry.

Tsampa may contain pesticide residues and mycotoxins, which may pose a risk to human health. Currently, pesticide detection and mycotoxin detection are two independent experiments. To improve the efficiency of the analysis, a method based on QuEChERS combined with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) for the simultaneous determination of 78 pesticides and 16 mycotoxins in tsampa was developed. All the target compounds showed good linear correlation with correlation coefficients (R2) greater than 0.9990. The limits of detection (LODs) and limits of quantification (LOQs) were in the ranges of 0.10-3.00 μg kg-1 and 0.40-10.00 μg kg-1, respectively. The average recoveries of the pesticides and mycotoxins spiked at the 1, 2, and 10-fold LOQ were in the range of 73.0-115.2%, and the relative standard deviations (RSDs) were lower than 11.7%. This method was applied to 19 batches of real samples in which 32% of samples exceeded the maximum residue limits of the European Union involving aflatoxin G2, ochratoxin A, and hexaconazole. It proved to be excellent, efficient, greatly simplified, and highly applicable, which could reduce the workload and time significantly for the daily monitoring of the pesticides and mycotoxins in tsampa.