Acetylharpagide Protects Mice from Staphylococcus Aureus-Induced Acute Lung Injury by Inhibiting NF-κB Signaling Pathway

Staphylococcus aureus (S. aureus)-induced acute lung injury (ALI) is a serious disease that has a high risk of death among infants and teenagers. Acetylharpagide, a natural compound of Ajuga decumbens Thunb. (family Labiatae), has been found to have anti-tumor, anti-inflammatory and anti-viral effects. This study investigates the therapeutic effects of acetylharpagide on S. aureus-induced ALI in mice. Here, we found that acetylharpagide alleviated S. aureus-induced lung pathological morphology damage, protected the pulmonary blood-gas barrier and improved the survival of S. aureus-infected mice. Furthermore, S. aureus-induced myeloperoxidase (MPO) activity of lung homogenate and pro-inflammatory factors in bronchoalveolar lavage (BAL) fluid were suppressed by acetylharpagide. Mechanically, acetylharpagide inhibited the interaction between polyubiquitinated receptor interacting protein 1 (RIP1) and NF-κB essential modulator (NEMO), thereby suppressing NF-κB activity. In summary, these results show that acetylharpagide protects mice from S. aureus-induced ALI by suppressing the NF-κB signaling pathway. Acetylharpagide is expected to become a potential treatment for S. aureus-induced ALI.     

Methiocarb Degradation by Electro-Fenton: Ecotoxicological Evaluation

This paper studies the degradation of methiocarb, a highly hazardous pesticide found in waters and wastewaters, through an electro-Fenton process, using a boron-doped diamond anode and a carbon felt cathode; and evaluates its potential to reduce toxicity towards the model organism Daphnia magna. The influence of applied current density and type and concentration of added iron source, Fe₂(SO₄)₃·5H₂O or FeCl₃·6H₂O, is assessed in the degradation experiments of methiocarb aqueous solutions. The experimental results show that electro-Fenton can be successfully used to degrade methiocarb and to reduce its high toxicity towards D. magna. Total methiocarb removal is achieved at the applied electric charge of 90 C, and a 450× reduction in the acute toxicity towards D. magna, on average, from approximately 900 toxic units to 2 toxic units, is observed at the end of the experiments. No significant differences are found between the two iron sources studied. At the lowest applied anodic current density, 12.5 A m⁻², an increase in iron concentration led to lower methiocarb removal rates, but the opposite is found at the highest applied current densities. The highest organic carbon removal is obtained at the lowest applied current density and added iron concentration.     

Toxicological Screening of Four Bioactive Citroflavonoids: In Vitro,In Vivo,and In Silico Approaches

Many studies describe different pharmacological effects of flavonoids on experimental animals and humans. Nevertheless, few ones are confirming the safety of these compounds for therapeutic purposes. This study aimed to investigate the preclinical safety of naringenin, naringin, hesperidin, and quercetin by in vivo, in vitro, and in silico approaches. For this, an MTT-based cytotoxicity assay in VERO and MDCK cell lines was performed. In addition, acute toxicity was evaluated on Wistar rats by OECD Guidelines for the Testing of Chemicals (Test No. 423: Acute Oral Toxicity-Class Method). Furthermore, we used the ACD/Tox Suite to predict toxicological parameters such as hERG channel blockade, CYP450 inhibition, and acute toxicity in animals. The results showed that quercetin was slightly more cytotoxic on cell lines (IC₅₀ of 219.44 ± 7.22 mM and 465.41 ± 7.44 mM, respectively) than the other citroflavonoids. All flavonoids exhibited an LD₅₀ value > 2000 mg/kg, which classifies them as low-risk substances as OECD guidelines established. Similarly, predicted LD⁵⁰ was LD₅₀ > 300 to 2000 mg/kg for all flavonoids as acute toxicity assay estimated. Data suggests that all these flavonoids did not show significant toxicological effects, and they were classified as low-risk, useful substances for drug development.     

The Effect of Polymer Dots During Mammalian Early Embryo Development and Their Biocompatibility on Maternal Health

Conjugated polymer dots have excellent fluorescence properties in terms of their structural diversity and functional design, showing broad application prospects in the fields of biological imaging and biosensing. Polymer dots contain no heavy metals and are thought to be of low toxicity and good biocompatibility. Therefore, systematic studies on their potential toxicity are needed. Herein, the biocompatibility of poly[(9,9‐dioctylfluorenyl‐2,7diyl)‐co‐(1,4‐benzo‐{2,1′,3}‐thiadiazole)],10% benzothiadiazole(y) (PFBT) and poly[2‐methoxy‐5‐(2‐ethylhexyloxy)‐1,4‐phenylenevinylene] (MEH‐PPV) polymer dots on early embryo development as well as maternal health is studied in detail. The results show that prepared polymer dots are dose‐dependently toxic to preimplantation embryos, and low‐dose polymer dots can be used for cell labeling of early embryos without affecting the normal development of embryos into blastocysts. In addition, the in vivo distribution data show that the polymer dots accumulate mainly in the maternal liver, spleen, kidney, placenta, ovary, and lymph nodes of the pregnant mice. Histopathological examination and blood biochemical tests demonstrate that exposure of the maternal body to polymer dots at a dosage of 14 µg g^?1 does not affect the normal function of the maternal organs and early fetal development. The research provides a safe basis for the wide application of polymer dots.     

基于人工智能和互联网时代的化合物毒性预测综述

随着商品中所含各种化合物的不断使用,人们日益关注其对人类及生态环境的安全危害。在过去的几年里,通过计算方法预测化合物毒性已经显示出极大的潜力。在此,总结了常用的机器学习和深度学习算法在建立毒性预测模型上的优缺点,并系统回顾了近三年发表的可免费访问的毒性预测网络服务器。此外,还讨论了基于人工智能和互联网时代下毒性预测所面临的机遇和挑战。希望指导人们合理的选择算法和网络服务器进行建模及化合物毒性评估。     

Particle Size Determination of Trace Elements in Urban Air

Abstract

Airborne urban particulate matter was collected and fractionated according to size by cascade impactors. The elements zinc, cadmium, copper and lead on each size fraction were analyzed by anodic stripping voltammetry. The elements aluminum, iron, manganese, calcium and magnesium were analyzed by atomic absorption spectrophotometry. The data showed three different classes of particle size distribution for these nine elements. Lead and cadmium belonged to the first class with more than 70 % of the total collected element associated with particles having aerodynamic diameters below 0.5 micron. The calculated average mass median equivalent diameter (MMD) of cadmium and lead was approx. 0.1 micron. In the second class about 60% of the elements Zn, Cu, Mg and Fe was associated with particles smaller than 0.5 micron. The average MMD's for these elements were between 0.3 and 0.4 micron. For the elements Al, Ca and Mn about 50% of the metal was associated with particles smaller than 0.5 micron and the MMD's were between 0.5 and 0.6 micron. Examination of elemental ratios (using Al as a reference element) showed that Pb and Cd were about 1000 times more concentrated in atmospheric particulate matter than in average crustal material and that in general the Pb/Al and Cd/Al ratios are inversely proportional to particle size. The Zn/Al and Cu/Al ratios of atmospheric partides were age or less independent of particle size and approx. 20 times higher than these same ratios in average crustal material. The ratios Fe/Al, Mn/AI, Ca/M and Mg/AI in all sizes of particulate matter were essentially identical to the same ratios in average crustal material.     

Structural Characterization and Acute Toxicity Prediction of Substituted Aromatic Compounds by Using Molecular Vertexes Correlative Index

A molecular structural characterization (MSC) method called molecular vertexes correlative index (MVCI) was used to describe the structures of 30 substituted aromatic compounds. Through multiple linear regression (MLR) and stepwise multiple regression (SMR), a quantitative structure-toxicity relationship (QSTR) model with 4 variables was obtained. The correlation coefficient (R) of the model was 0.9467. Through partial least-squares regression (PLS), another QSTR model with 5 principal components was obtained. The correlation coefficient (R) of the model was 0.9518. Both models were evaluated by performing the cross-validation with the leave-one-out (LOO) procedure and the Cross-Validation (CV) correlation coefficients (RCV) were 0.9208 and 0.9214, respectively. The results suggested good stability and predictability of the models, and the molecular vertexes correlative index could successfully describe the structures of the substituted aromatic compounds.     

Synthesis and Comparison of Extraction Properties of p‐tert‐Butylcalix[n]arene Nitrile Derivatives for Selected Metals and Dichromate Anions

The article describes the syntheses and extraction properties of two p‐tert‐butylcalix[6]arene nitrile derivatives (3 and 4). The trinitrile derivative 3 has been synthesized from 5,11,17,23,29,35‐hexa‐tert‐butyl‐37,38,39,40,41,42‐hexahydroxy‐calix[6]arene 1. The compound 1 was directly converted to its hexanitrile derivative (4). In these syntheses, it was considered to explore the role of nitrile sites in the extraction of various metal cations and HCr₂O₇ ^?/Cr₂O₇ ^2? anions. The liquid‐liquid extraction properties of 3 and 4 towards selected alkali/transition metal cations and HCr₂O₇ ^?/Cr₂O₇ ^2? anions are reported. It has been observed that receptor 3 does not extract alkali/transition metal cations effectively, but shows affinity towards HCr₂O₇ ^?/Cr₂O₇ ^2? anions at low pH. The compound 4 is an effective form for transferring Ni²⁺ selectively, while it shows poor transferring ability for HCr₂O₇ ^?/Cr₂O₇ ^2? anions from an aqueous into a dichloromethane layer. It was observed that the cavity size of the calix[n]arenes and the cooperativity of the functionalities play important roles in two phase extraction systems.     

Comparative study to predict toxic modes of action of phenols from molecular structures

Quantitative structure–activity relationship models for the prediction of mode of toxic action (MOA) of 221 phenols to the ciliated protozoan Tetrahymena pyriformis using atom-based quadratic indices are reported. The phenols represent a variety of MOAs including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles and soft electrophiles. Linear discriminant analysis (LDA), and four machine learning techniques (ML), namely k-nearest neighbours (k-NN), support vector machine (SVM), classification trees (CTs) and artificial neural networks (ANNs), have been used to develop several models with higher accuracies and predictive capabilities for distinguishing between four MOAs. Most of them showed global accuracy of over 90%, and false alarm rate values were below 2.9% for the training set. Cross-validation, complementary subsets and external test set were performed, with good behaviour in all cases. Our models compare favourably with other previously published models, and in general the models obtained with ML techniques show better results than those developed with linear techniques. We developed unsupervised and supervised consensus, and these results were better than our ML models, the results of rule-based approach and other ensemble models previously published. This investigation highlights the merits of ML-based techniques as an alternative to other more traditional methods for modelling MOA.