Chemical binding

About: Chemical binding is a research topic. Over the lifetime, 1822 publications have been published within this topic receiving 52516 citations.

In vitro assessment of corrosive properties of titanium as a biomaterial.

Abstract: Titanium (Ti) is thought to be a highly biocompatible material, and its clinical applications are becoming increasingly frequent. However, there have recently been some clinical papers reporting hypersensitivity and allergic reactions to Ti. The purpose of this study was to assess the corrosive properties of Ti in the intra-oral environment in vitro. Cast pure Ti specimens were immersed in artificial saliva, physiological saline solution, and 128 mmol x L(-1) of lactic, formic and acetic acids for 3 weeks at 37 degrees C with shaking. The colour, weight, surface morphologies and chemical binding state of specimens were observed before and after immersion. Marked discoloration was recognized on the surface of specimens immersed in formic acid, and a significant difference was found between the immersion solutions. Weight changes also varied with solutions; a tendency to increase in formic acid and to decrease in lactic acid. A slight loss was observed in specimens immersed in lactic acid and artificial saliva. The oxide layer composed mainly of Ti-oxide on the surface of the immersed specimens was thinnest in lactic acid, and thickest in formic acid. The present study indicates that both hydrogen evolution type and oxygen diffusion type corrosion on Ti surfaces are possible in the living body. (Our results also confirm some clinical studies reporting Ti accumulation in surrounding tissues and Ti causing allergic reactions.)

Electrochemistry-mass spectrometry for mechanistic studies and simulation of oxidation processes in the environment

Abstract: Electrochemistry (EC) coupled to mass spectrometry (MS) has already been successfully applied to metabolism research for pharmaceutical applications, especially for the oxidation behaviour of drug substances. Xenobiotics (chemicals in the environment) also undergo various conversions; some of which are oxidative reactions. Therefore, EC-MS might be a suitable tool for the investigation of oxidative behaviour of xenobiotics. A further evaluation of this approach to environmental research is presented in the present paper using sulfonamide antibiotics. The results with sulfadiazine showed that EC-MS is a powerful tool for the elucidation of the oxidative degradation mechanism within a short time period. In addition, it was demonstrated that EC-MS can be used as a fast and easy method to model the chemical binding of xenobiotics to soil. The reaction of sulfadiazine with catechol, as a model substance for organic matter in soil, led to the expected chemical structure. Finally, by using EC-MS a first indication was obtained of the persistence of a component under chemical oxidation conditions for the comparison of the oxidative stability of different classes of xenobiotics. Overall, using just a few examples, the study demonstrates that EC-MS can be applied as a versatile tool for mechanistic studies of oxidative degradation pathways of xenobiotics and their possible interaction with soil organic matter as well as their oxidative stability in the environment. Further studies are needed to evaluate the full range of possibilities of the application of EC-MS in environmental research.

QSAR Models Using a Large Diverse Set of Estrogens.

Abstract: Endocrine disruptors (EDs) have a variety of adverse effects in humans and animals. About 58,000 chemicals, most having little safety data, must be tested in a group of tiered assays. As assays will take years, it is important to develop rapid methods to help in priority setting. For application to large data sets, we have developed an integrated system that contains sequential four phases to predict the ability of chemicals to bind to the estrogen receptor (ER), a prevalent mechanism for estrogenic EDs. Here we report the results of evaluating two types of QSAR models for inclusion in phase III to quantitatively predict chemical binding to the ER. Our data set for the relative binding affinities (RBAs) to the ER consists of 130 chemicals covering a wide range of structural diversity and a 6 orders of magnitude spread of RBAs. CoMFA and HQSAR models were constructed and compared for performance. The CoMFA model had a r2 = 0.91 and a q2LOO = 0.66. HQSAR showed reduced performance compared to CoMFA with r2 = 0.76 and q2LOO = 0.59. A number of parameters were examined to improve the CoMFA model. Of these, a phenol indicator increased the q2LOO to 0.71. When up to 50% of the chemicals were left out in the leave-N-out cross-validation, the q2 remained significant. Finally, the models were tested by using two test sets; the q2pred for these were 0.71 and 0.62, a significant result which demonstrates the utility of the CoMFA model for predicting the RBAs of chemicals not included in the training set. If used in conjunction with phases I and II, which reduced the size of the data set dramatically by eliminating most inactive chemicals, the current CoMFA model (phase III) can be used to predict the RBA of chemicals with sufficient accuracy and to provide quantitative information for priority setting.