Fractionation and purification of antioxidant peptides from Chinese sturgeon (Acipenser sinensis) protein hydrolysates prepared using papain and alcalase 2.4L

Protein hydrolysates have the potential to be natural and safer sources of bioactive peptides. In this study, two proteases were used to hydrolyze Chinese sturgeon (Acipenser sinensis) protein, and the hydrolysates were then purified to yield antioxidant peptides. The degree of hydrolysis of 23.56 % and 18.14 % was obtained using papain and alcalase 2.4L, respectivly, and hydrolysates had 96.80 % and 87.24 % total amino acid content, respectivly. The papain hydrolysate (PH) and alcalase 2.4L hydrolysate (AH) showed good antioxidant activity against DPPH^? (IC₅₀ of 3.64 and 3.15 mg/mL) and ABTS^?+ (IC₅₀ of 1.92 and 1.58 mg/mL), respectively. The low-molecular-weight (<1000 Da) fraction of both hydrolysates demonstrated the highest antiradical activity (IC₅₀ of 2.59 and 2.31 mg/mL, DPPH) and (IC₅₀ of 1.54 and 1.36 mg/mL, ABTS), respectively. Nine peptides were separated from both hydrolysates using reverse phase high performance liquid chromatography (RP-HPLC). The IC₅₀ for ABTS^?+ scavenging activity of peptide P5 with valine, glycine and asparagine (MW of 282.13 Da) from PH, and peptide P3 with histidine, glycine and alanine (MW of 302.74 Da) from AH was 0.89 and 0.72 mg/mL, respectively. The fractions and purified peptides obtained from Chinese sturgeon hydrolysates could be utilized as natural antioxidant substitutes in pharmaceuticals and food products.     

X-ray and IR spectroscopic studies of specific intermolecular interactions inN′-substituted isonicotinohydrazides

_N-Thenylidene- andN-(o-nitrobenzylidene)hydrazides of isonicotinic acid have been studied by X-ray structural analysis and IR spectroscopy. In the crystalline state, these molecules are linked through intermolecular N—H ... Np_y hydrogen bonds. Carbonyl groups are not involved in intermolecular hydrogen bonds. However, it was found that the C=O group participates in an attractive interaction with the sulfur atom of the thiophene group. The energy of this interaction is comparable with the energies of intermolecular C=O ... H—N hydrogen bonds in amides.Translated fromIzvestiya Akademii Nauk. Seriya Khimicheskaya, No. 4, pp. 896–900, April, 1996.     

Molecular structures of β-amino-α-bromovinyl trifluoromethyl ketones

The molecular structures of β-amino-α-bromovinyl trifluoromethyl ketones was studied by UV, IR, ¹H, ¹³C, and ¹⁵N NMR spectroscopy and using the density functional (B3LYP/6-31G(d,p) and PBE/QZ3P) and ab initio riMP2/cc-pVTZm quantum-chemical calculations. Factors affecting stabilization of the EZE-conformation of the molecules, which is atypical of analogous unsubstituted amino enones, are considered.__________Published in Russian in Izvestiya Akademii Nauk. Seriya Khimicheskaya, No. 1, pp. 102–106, January, 2005.     

Alcohols,ethers, carbohydrates,and related compounds. II. The anomeric effect

The anomeric effect has been studied for a variety of compounds using the MM4 force field, and also using MP2/6-311++G(2d,2p) ab initio calculations and experimental data for reference purposes. Geometries and energies, including conformational, rotational barriers, and heats of formation were examined. Overall, the agreement of MM4 with the experimental and ab initio data is good, and significantly better than the agreement obtained with the MM3 force field. The anomeric effect is represented in MM4 by various explicit terms in the force constant matrix. The bond length changes are accounted for with torsion-stretch elements. The angle changes are accounted for with torsion-bend elements. The energies are taken into account with a number of torsional terms in the usual way. A torsion-torsion interaction is also of some importance. With all of these elements included in the calculation, the MM4 results now appear to be adequately accurate. The heats of formation were examined for a total of 12 anomeric compounds, and the experimental values were fit by MM4 with an RMS error of 0.42 kcal/mol.     

Quantum-Inspired Complex-Valued Language Models for Aspect-Based Sentiment Classification

Aiming at classifying the polarities over aspects, aspect-based sentiment analysis (ABSA) is a fine-grained task of sentiment analysis. The vector representations of current models are generally constrained to real values. Based on mathematical formulations of quantum theory, quantum language models have drawn increasing attention. Words in such models can be projected as physical particles in quantum systems, and naturally represented by representation-rich complex-valued vectors in a Hilbert Space, rather than real-valued ones. In this paper, the Hilbert Space representation for ABSA models is investigated and the complexification of three strong real-valued baselines are constructed. Experimental results demonstrate the effectiveness of complexification and the outperformance of our complex-valued models, illustrating that the complex-valued embedding can carry additional information beyond the real embedding. Especially, a complex-valued RoBERTa model outperforms or approaches the previous state-of-the-art on three standard benchmarking datasets.     

An Algorithm Framework for Drug-Induced Liver Injury Prediction Based on Genetic Algorithm and Ensemble Learning

In the process of drug discovery, drug-induced liver injury (DILI) is still an active research field and is one of the most common and important issues in toxicity evaluation research. It directly leads to the high wear attrition of the drug. At present, there are a variety of computer algorithms based on molecular representations to predict DILI. It is found that a single molecular representation method is insufficient to complete the task of toxicity prediction, and multiple molecular fingerprint fusion methods have been used as model input. In order to solve the problem of high dimensional and unbalanced DILI prediction data, this paper integrates existing datasets and designs a new algorithm framework, Rotation-Ensemble-GA (R-E-GA). The main idea is to find a feature subset with better predictive performance after rotating the fusion vector of high-dimensional molecular representation in the feature space. Then, an Adaboost-type ensemble learning method is integrated into R-E-GA to improve the prediction accuracy. The experimental results show that the performance of R-E-GA is better than other state-of-art algorithms including ensemble learning-based and graph neural network-based methods. Through five-fold cross-validation, the R-E-GA obtains an ACC of 0.77, an F1 score of 0.769, and an AUC of 0.842.     

Virtual Screening and Hit Selection of Natural Compounds as Acetylcholinesterase Inhibitors

Acetylcholinesterase (AChE) is one of the classical targets in the treatment of Alzheimer’s disease (AD). Inhibition of AChE slows down the hydrolysis of acetycholine and increases choline levels, improving the cognitive function. The achieved success of plant-based natural drugs acting as AChE inhibitors, such as galantamine (GAL) from Galanthus genus and huperzine A from Huperzia serrate (approved drug in China), in the treatment of AD, and the fact that natural compounds (NCs) are considered as safer and less toxic compared to synthetic drugs, led us to screen the available NCs (almost 150,000) in the ZINC12 database for AChE inhibitory activity. The compounds were screened virtually by molecular docking, filtered for suitable ADME properties, and 32 ligands from 23 structural groups were selected. The stability of the complexes was estimated via 1 μs molecular dynamics simulation. Ten compounds formed stable complexes with the enzyme and had a vendor and a reasonable price per mg. They were tested for AChE inhibitory and antioxidant activity. Five compounds showed weak AChE inhibition and three of them exhibited high antioxidant activity.     

Assessment of Chemical Composition and Anti-Penicillium Activity of Vapours of Essential Oils from Abies Alba and Two Melaleuca Species in Food Model Systems

The possibilities of the practical utilization of essential oils (EOs) from various plant species in the food industry have attracted the attention of the scientific community. Following our previous studies, the antifungal activities of three further commercial EOs, Melaleuca armillaris subsp. armillaris (rosalina; REO), Melaleuca quinquenervia (niaouli; NEO), and Abies alba (fir; FEO), were evaluated in the present research in respect to their chemical profiles, over four different concentrations, 62.5 μL/L, 125 μL/L, 250 μL/L, and 500 μL/L. The findings revealed that the major compounds of REO, NEO, and FEO were linalool (47.5%), 1,8-cineole (40.8%), and α-pinene (25.2%), respectively. In vitro antifungal determinations showed that the inhibition zones of a Penicillium spp. mycelial growth ranged from no inhibitory effectiveness (00.00 ± 00.00 mm) to 16.00 ± 1.00 mm, indicating a very strong antifungal activity which was detected against P. citrinum after the highest REO concentration exposure. Furthermore, the in situ antifungal efficacy of all EOs investigated was shown to be dose-dependent. In this sense, we have found that the highest concentration (500 µL/L) of REO, NEO, and FEO significantly reduced (p < 0.05) the growth of all Penicillium strains inoculated on the bread, carrot, and potato models. These results indicate that the investigated EOs may be promising innovative agents in order to extend the shelf life of different types of food products, such as bread, carrot and potato.     

圆柱类构件超声相控阵聚焦模型

在利用平面相控阵超声换能器对圆柱类构件检测时,受曲界面结构引起的入射波和回波时延的影响,扫描声束的波阵面产生弯曲,在利用传统迭代遍历算法计算延迟时间时效率低,无法发挥相控阵换能器检测优势。针对上述问题,建立了一种基于圆柱类构件特征和耦合介质特性的超声相控阵扫描成像的聚焦模型。该模型基于换能器、耦合介质、圆柱类构件材料特性和几何关系以及声线模型和折射定律,建立了耦合介质及被检构件的声速、曲面曲率半径、阵列与曲面间的距离等关联的延迟时间聚焦控制模型。利用该模型计算出的延时时间,对各阵元发射时间进行控制,从而实现扫描声束的聚焦。该文以液体和有机玻璃制介质楔块为例,对圆柱钢曲面的相控阵声束聚焦进行了仿真实验,结果表明该文方法计算效率显著提升,同时声束可以在预设位置实现聚焦,验证了该模型在计算效率上的优势与有效性。     

Interplay Between Quark-Antiquark and Diquark Condensates in Vacuum in a Two-Flavor Nambu-Jona-Lasinio Model

By means of a relativistic effective potential, we analytically research competition between the quark- antiquark condensates （qq） and the diquark condensates （qq） in vacuum in ground state of a two-flavor Nambu Jona Lasinio （NJL） model and obtain the Gs-Hs phase diagram, where Gs and Hs are the respective four-fermion coupling constants in scalar quark-antiquark channel and scalar color anti-triplet diquark channel. The results show that, in the chiral limit, there is only the pure （qq） phase when Gs/Hs 〉 2/3, and as Gs/Hs decreases to 2/3 〉 Gs/Hs ≥ 0 one will first have a coexistence phase of the condensates （qq） and （qq） and then a pure （qq） phase. In non-zero bare quark mass case, the critical value of Gs/Hs at which the pure （qq） phase will transfer to the coexistence phase of the condensates （qq） and （qq） will be less than 2/3. Our theoretical results, combined with present phenomenological fact that there is no diquark condensates in the vacuum of QCD, will also impose a real restriction to any given two-flavor NJL model which is intended to simulate QCD, i.e. in such model the resulting sma/lest ratio Gs/Hs after the Fierz transformations in the Hartree approximation must be larger than 2/3. A few phenomenological QCD-like NJL models are checked and analyzed.