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H H Borgstedt

Publications and source records attributed to H H Borgstedt.

17 recordsLinked to original sources
PubMed1991

Estimation of maximum tolerated dose for long-term bioassays from acute lethal dose and structure by QSAR.

A quantitative structure-activity relationship (QSAR) model has been developed to estimate maximum tolerated doses (MTD) from structural features of chemicals and the corresponding oral acute lethal doses (LD50) as determined in male rats. The model is based on a set of 269 diverse chemicals which have been tested under the National Cancer Institute/National Toxicology Program (NCI/NTP) protocols. The rat oral LD50 value was the strongest predictor. Additionally, 22 structural descriptors comprising nine substructural MOLSTAC(c) keys, three molecular connectivity indices, and sigma charges on 10 molecular fragments were identified as endpoint predictors. The model explains 76% of the variance and is significant (F = 35.7) at p less than 0.0001 with a standard error of the estimate of 0.40 in the log (1/mol) units used in Hansch-type equations. Cross-validation showed that the difference between the average deleted residual square (0.179) and the model residual square (0.160) was not significant (t = 0.98).

Animals↗
PubMed1990

Salmonella mutagenicity and rodent carcinogenicity: quantitative structure-activity relationships.

Based on a compilation of 222 reports of rodent nominal lifetime carcinogenicity bioassays by the NCI/NTP on the one hand, and corresponding Salmonella mutagenicity bioassays (Ames tests) on the other, Ashby and Tennant (1988) have divided the carcinogens and non-carcinogens into genotoxic (Ames test positive) and non-genotoxic (Ames test negative) groups and discussed structural characteristics common to each of these groups. The Ames test alone was deemed to be adequate for the identification of genotoxicity because other short-term bioassays, and even combinations, or batteries, appeared to offer no significant advantages. From the results of this study it is possible to achieve (1) a division of the carcinogens into the same genotoxic and non-genotoxic groups, and (2) a division of the non-genotoxic compounds into the same carcinogenic and non-carcinogenic groups, solely on the basis of structure-activity relationships, with a classification accuracy of approx. 95%. (1) An equation comprising 8 sigma molecular charge descriptors, 2 molecular connectivity indices (MCIs), 2 kappa molecular shape descriptors and one MOLSTAC substructure descriptor achieved discrimination between genotoxic and non-genotoxic carcinogens with an accuracy of 94.5%. (2) Another equation comprising 8 sigma molecular charge descriptors, 3 MCIs, one kappa shape descriptor and 12 substructural descriptors achieved discrimination between non-genotoxic carcinogens and non-genotoxic non-carcinogens with an accuracy of 95.2%. These SAR models are suitable for the distinction between (1) genotoxic and non-genotoxic carcinogens and (2) carcinogenic and non-carcinogenic non-genotoxins, both in the absence of animal bioassay data.

Carcinogenicity Tests↗
PubMed1990

Prediction of probability of carcinogenicity for a set of ongoing NTP bioassays.

Forty-four compounds currently undergoing carcinogenesis bioassay by the National Toxicology Program were submitted to the TOPKAT program for prediction of their potential carcinogenicity. Sixteen compounds could not be handled by TOPKAT. Of the 28 for which predictions were made, 26 (93%) had a confidence level in the estimate of at least moderate. Seventeen were predicted to be carcinogens and 11 non-carcinogens. These results will be compared with the assay results as the assays are completed.

Carcinogenicity Tests↗
PubMed1989

A QSAR model for the estimation of carcinogenicity: example application to an azo-dye.

Since carcinogenicity bioassays are time-consuming, costly, and use animal resources, structure-activity relationship equations which model toxicological end-points have been developed to make available alternative methods which approximate the results that could be obtained from bioassays but which are less expensive and time-consuming and use fewer, if any, animals. These equations are based on sets of bioassay results and explain the end-point under consideration in terms of substructural and other parameters which describe the chemical entities. The resulting equations--or models--can then be used to estimate--or predict--the end-point for new structures. The estimation is followed by validation procedures.

Animals↗
PubMedDate not supplied

The influence of chronic administration of hypnotics and analgesics on rate of recovery from inhalation anesthesia in rats.

A series of groups of Sprague-Dawley rats were given either secobarbital, phenobarbital, morphine, pentazocine, diazepam, methotrimeprazine, or saline (control) intraperitoneally on 4 consecutive days and then, on day 5, anesthetized with chloroform, trichlorethylene, fluroxene, halothane, methoxyflurane, enflurane, isoflurane, bromotrifluorocyclobutane, or chlorotrifluorocyclobutane. One control group received neither pretreatment nor anesthetics and another was given pretreatment but no anesthetics. The factor of "enzyme induction" is also evaluated, as are SGPT elevation and liver and kidney lesions. If enzyme induction occurred with the drugs used for pretreatment, the anesthetics suppressed the expected response. SGPT levels were generally within normal range. The combinations of all pretreatments with enflurane, halothane, or methoxyflurane had the fastest recovery; recovery was slower with the other anesthetic agents, but none of the prior chemotherapeutic drugs accelerated recovery from the inhalation anesthetics.

Alanine Transaminase↗