GC-MS技术在舰船胶粘材料毒性评价中的应用

胶粘材料简称胶粘剂、粘合剂、粘结剂、接着剂。因其能把各种材料紧密地粘合在一起,并具有各种良好的性能,因而广泛地应用于海军舰船的制造及维修中。应用GC-MS技术对在使用环境及条件下其释放物及高温热解物的定性分析是对其进行使用过程中毒性评价的重要步骤。1实验部分1.1仪器与材料仪器:JMS-D300(日本JEOL);PIATFORMⅡGC-MS。     

Synthesis and Structure Investigations of Potential Sedative and Anticonvulsant Hydroxy- and Acetoxy-N-(3-oxobutyl)-pyrido[2,3-d]pyridazinonesa

Summary.  Novel N-(3-oxobutyl)-hydroxy- and acetoxypyrido[2,3-d]pyridazinones were synthesized and tested in vivo for their sedative and anticonvulsant activity. The Michael-type reaction of quinolinic acid hydrazide and methyl vinyl ketone afforded a mixture of two isomers, 5-hydroxy-N ⁷-(3-oxobutyl)-pyrido[2,3-d]pyridazin-8(7H)-one and 8-hydroxy-N ⁶-(3-oxobutyl)-pyrido[2,3,-d]pyridazin-5-(6H)-one, in a ratio of 2:1 which were separated by crystallization. Subsequent acetylation of both isomers yielded the corresponding 5- and 8-acetoxy compounds. The structures of the compounds were proven and completely assigned on the basis of ¹H, ¹³C, ¹⁵N NMR, and 1D NOE difference spectra as well as 2D C,H-correlation experiments. Preliminary pharmacological tests showed low acute toxicity with a LD ₅₀ > 1000 mg/kg in the mouse and sedative activity for the title compounds. 5-Acetoxy-N ⁷- (3-oxobutyl)-pyrido[2,3-d]pyridazin-8(7H)-one displayed a borderline anticonvulsant activity in the metrazole test model. Corresponding author. E-mail: edith.goessnitzer@uni-graz.at Received March 20, 2002; accepted April 3, 2002     

钒毒性的研究进展

综述了钒的一般毒性，生殖毒性，胚胎毒性，致畸，致突变，致癌毒性的研究进展。     

新型稀土杂多蓝的合成及其抗艾滋病病毒(HIV-1)活性和毒性研究

合成Keggin结构钨硅、钨锗、钨磷、钨坤两电子及四电子稀土钐盐杂多蓝，铈量滴定及元素分析方法确定了化合物的还原电子数及化学组成，采用IR，UV－Vis,^183W NMR和ESR等对其结果进行了表征，在人T淋巴MT－4内，对合成的化合物进行了系统的抗艾滋病毒（HIV－1）活性及毒性测定，发现Keggin结构钨硅、钨锗四电子稀土钐盐杂多蓝具有较强的抗HIV－1活性，其中钨锗酸钐四电子杂多蓝（代号HPBR－2）具有较高的治疗指数。     

Synthesis, structural and larvicidal studies of some triorganotin 2-(p-chlorophenyl)-3-methylbutyrates

A series of triorganotin 2-(p-chlorophenyl)-3-methylbutyrates, (R₃SnO₂CCH(CH(CH₃)₂)C₆H₄Cl-4), where R = methyl, ethyl, n-propyl, n-butyl, phenyl and cyclo-hexyl, have been synthesized. Elemental analyses, Mössbauer, Infrared and NMR spectroscopies have been used to characterize their structures. Based on the spectroscopic results, all the complexes with the exception of the tricyclohexyl compound were found to be five-coordinated in the solid state while the tricyclohexyltin derivative was determined to be four-coordinated. Structural assignments based on spectroscopic data are supported by the crystallographic results of four of the triorganotin butyrates (trimethyl-, tri-n-propyl-, tri-n-butyl- and tricyclohexyltin 2-(p-chlorophenyl)-3-methylbutyrate). Multinuclear NMR spectroscopy studies indicated that all the complexes were tetrahedral in solution. Larvicidal activities of the complexes were evaluated against the 2nd instar stage of the Anopheles stephensi, Aedes aegypti and Culex pipiens quinquefasciatus mosquitoes. The toxicity data indicate that there does not appear to be any significant differences of the compounds towards the different mosquito species based on their averaged toxicity values. In addition, the toxicity of the triorganotin compounds towards the mosquito larvae was concluded to be dependent on both the compound and the species of mosquito larvae.     

Induction of decision trees using genetic programming for modelling ecotoxicity data: adaptive discretization of real-valued endpoints

Recent literature has demonstrated the applicability of genetic programming to induction of decision trees for modelling toxicity endpoints. Compared with other decision tree induction techniques that are based upon recursive partitioning employing greedy searches to choose the best splitting attribute and value at each node that will necessarily miss regions of the search space, the genetic programming based approach can overcome the problem. However, the method still requires the discretization of the often continuous-valued toxicity endpoints prior to the tree induction. A novel extension of this method, YAdapt, is introduced in this work which models the original continuous endpoint by adaptively finding suitable ranges to describe the endpoints during the tree induction process, removing the need for discretization prior to tree induction and allowing the ordinal nature of the endpoint to be taken into account in the models built.     

Quantitative prediction of biodegradability,metabolite distribution and toxicity of stable metabolites

An evaluation of the capability of organic chemicals to mineralize is an important factor to consider when assessing their fate in the environment. Microbial degradation can convert a toxic chemical into an innocuous one, and vice versa , or alter the toxicity of a chemical. Moreover, primary biodegradation can convert chemicals into stable products that can be difficult to mineralize. In this paper, we present some new results obtained on the basis of a recently developed probabilistic approach to modeling biodegradation based on microbial transformation pathways. The metabolic transformations and their hierarchy were calibrated by making use of the ready biodegradability data from the MITI-I test and expert knowledge for the most probable transformation pathways. A model was developed and integrated into an expert software system named CATABOL that is able to predict the probability of biodegradation of organic chemicals directly from their structure. CATABOL simulates the effects of microbial enzyme systems, generates the most plausible transformation pathways, and quantitatively predicts the persistence and toxicity of the biodegradation products. A subset of 300 organic chemicals were selected from Canada's Domestic Substances List and subjected to CATABOL to compare predicted properties of the parent chemicals with their respective first stable metabolite. The results show that most of the stable metabolites have a lower acute toxicity to fish and a lower bioaccumulation potential compared to the parent chemicals. In contrast, the metabolites appear to be generally more estrogenic than the parent chemicals.     

Knowledge-Based Expert Systems for Toxicity and Metabolism Prediction: DEREK,StAR and METEOR

Abstract

It has long been recognised that the ability to predict the metabolic fate of a chemical substance and the potential toxicity of either the parent compound or its metabolites are important in novel drug design. The popularity of using computer models as an aid in this area has grown considerably in recent years.

LHASA Limited has been developing knowledge-based expert systems for toxicity and metabolism prediction in collaboration with industry and regulatory authorities. These systems, DEREK, StAR and METEOR, use rules to describe the relationship between chemical structure and either toxicity in the case of DEREK and StAR, or metabolic fate in the case of METEOR.

The rule refinement process for DEREK often involves assessing the predictions for a novel set of compounds and comparing them to their biological assay results as a measure of the system's performance. For example, 266 non-congeneric chemicals from the National Toxicology Program database have been processed through the DEREK mutagenicity knowledge base and the predictions compared to their Salmonella typhimurium mutagenicity data. Initially, 81 of 114 mutagens (71%) and 117 of 152 non-mutagens (77%) were correctly identified. Following further knowledge base development, the number of correctly identified mutagens has increased to 96 (84%). Further work on improving the predictive capabilities of DEREK, StAR and METEOR is in progress.     

Handling uncertainties in toxicity modelling using a fuzzy filter

A fundamental concern in the Quantitative Structure-Activity Relationship approach to toxicity evaluation is the generalization of the model over a wide range of compounds. The data driven modelling of toxicity, due to the complex and ill-defined nature of eco-toxicological systems, is an uncertain process. The development of a toxicity predicting model without considering uncertainties may produce a model with a low generalization performance. This study presents a novel approach to toxicity modelling that handles the involved uncertainties using a fuzzy filter, and thus improves the generalization capability of the model. The method is illustrated by considering a data set dealing with the fathead minnow (Pimephales promelas) toxicity of 568 organic compounds.     

Functionalization of short multi-walled carbon nanotubes with creatinine and aromatic aldehydes via microwave and thermal methods and their influence on the MKN45 and MCF7 cancer cells

The chemical functionalization of carboxylated short multi-walled carbon nanotubes (Sh–MWCNT–COOH) by creatinine (Sh–MWCNT–amide) and later modification with aromatic aldehydes for producing 2-amino-5-arylidene-1-methyl-1H–imidazol-4(5H)-one (Sh–MWCNT–imidazols) via thermal and microwave methods have been investigated. All the products were characterized by Fourier transform infrared spectroscopy, Raman spectroscopy, scanning electron microscope, elemental analysis, thermogravimetric analysis, derivative thermogravimetric and cellular investigations. These functionalizations have been chosen due to the active sites of CC and carbonyl groups in Sh–MWCNT–imidazols, which might be used as functional materials in the future. MTT assay was used to examine the behavior of cell proliferation after 72 h of cell culture experiments. Cellular investigations were performed for two kinds of cells, human breast and gastric cancer cells. Cellular results showed high toxicity of modified Sh–MWCNTs on the gastric cancer cells compared to breast cells.