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A 'proof-of-concept' version of a software tool for making transparent predictions of acute aquatic toxicity has been developed. It is primarily limited to semi-quantitative predictions in one species, the ciliated protozoan, Tetrahymena pyriformis. A freely available system, 'Eco-Derek', was derived by adapting a well-established, knowledge-based structure-activity and reasoning platform (Derek for Windows, Lhasa Limited). The Derek reasoning code was modified to express potency rather than confidence. Structure-activity relationship (SAR) development utilised a curated version of a published dataset, supplemented with the CADASTER Challenge datasets. Forty-five structural alerts were produced. The dependence on log P was examined for each alert and entered into the system as qualitative reasoning rules specifying the predicted potency as Very Low, Low, Moderate, High or Very High. Evaluation studies showed: (a) moderate accuracy for the training set but low accuracy for an external test set; (b) non-linearity in the toxicity-log P relationship for chemicals without identified structural alerts; (c) insufficient differentiation of substituent effects in some of the reactivity-based structural alerts resulting in too few chemicals predicted with Very High toxicity; and (d) the need for additional structural alerts covering polar narcosis and less common reactive or metabolically activated chemical functionality.

This is the final article in a four part series reviewing the influence of humor and laughter on physiological and psychological well-being. This final article reviews the evidence for the effect of sense of humor, exposure to a humor stimulus and laughter on various immune system components, with a focus on the effects of laughter on natural killer cell cytotoxicity.

This is part three of a four-part series reviewing the evidence on how humor influences physiological and psychological well-being. The first article included basic background information, definitions and a review of the theoretical underpinnings for this area of research. The second article discussed use of humor as a complementary therapy within various clinical samples, as well as evidence concerning how a sense of humor influences physiological and psychological wellbeing. This third article examines how laughter influences health outcomes; including muscle tension, cardio-respiratory functioning and various stress physiology measures.

Our results support a connection between sense of humor and self-reported physical health, however, it is difficult to determine the relationship to any specific disease process. Whereas relationships between sense of humor and self-reported measures of physical well-being appear to be supported, more research is required to determine interrelationships between sense of humor and well-being.

Articles in both the lay and professional literature have extolled the virtues of humor, many giving the impression that the health benefits of humor are well documented by the scientific and medical community. The concept that humor or laughter can be therapeutic goes back to biblical times and this belief has received varying levels of support from the scientific community at different points in its history. Current research indicates that using humor is well accepted by the public and is frequently used as a coping mechanism. However, the scientific evidence of the benefits of using humor on various health related outcomes still leaves many questions unanswered.

Several mechanisms have been implicated in underlying the perception of cold, most notably the activation of TRPM8 and TRPA1. We have used ratiometric calcium imaging to reveal a population of neurons in the superior cervical ganglion (SCG) of the mouse that respond to cooling but are insensitive to menthol. Furthermore we show that the expression of the mRNA transcripts encoding the recently identified noxious cold-sensitive channel TRPA1 but not TRPM8 are expressed in the SCG. These data provide evidence for a population of cold-responsive neurons in the SCG whose cold-responsiveness could be mediated by the activation of TRPA1 and suggest that the sympathetic nervous system may play a direct role in mediating sympathetic responses to cold temperatures.

The current pediatric test battery is limited in the severe-to-profound hearing loss range by the inability to obtain frequency-specific thresholds. Auditory steady-state response (ASSR) is an evoked potential test that can accurately measure auditory sensitivity beyond the limits of other test methods. The limited amount of clinical research, however, has delayed the acceptance of ASSR into the standard pediatric test battery. This study compared thresholds from 76 children using ASSR, ABR, and behavioral test methods. Resulting correlations were strong and supported the inclusion of ASSR into the standard pediatric test battery. ASSR testing provides audiometric information that is essential in the management of children with severe-to-profound hearing loss.

Quantitative structure-activity relationships (QSARs) for predicting skin and respiratory sensitization are reviewed. Overall, progress has been hampered by the sparseness of good quality experimental data, a fact that makes it difficult, at this time, to recommend one or two QSARs for predicting skin and respiratory sensitization. Creation of appropriate data sets for uninvestigated classes of chemicals by experimentation should facilitate the development of more robust QSARs for predicting skin and respiratory sensitization. Such QSARs will be valuable in the evaluation of identifiable toxic hazards where dose responses are relevant, as is the case for skin and respiratory sensitization.

Several models have been published for calculating blood-air, tissue-air, or tissue-blood partition coefficients of volatile organic chemicals in human or rat tissues, from functions of their octanol-water partition coefficients or solubilities in vegetable oil and water. In this work, the relative accuracy, strengths, and limitations of the various models are examined. Comparison of predicted human tissue-air and tissue-blood partition coefficients with experimental values has been made for 12 chemicals, covering a wide range of lipophilicity (acetone, isopropanol, diethylether, methylene dichloride, benzene, toluene, trichloroethylene, trichloroethane, n-pentane, cyclohexane, n-hexane, and n-heptane). Seven published models for human tissue-air and 10 models for tissue-blood partition coefficients have been compared. Fewer models are available for predicting rat tissue-air and rat tissue-blood partition coefficients, but a similar comparison has been made. The ratio of predicted to experimental partition coefficients and their mean, R(mean), and the mean magnitude of the difference between predicted and experimental values of log(10) P, E, were used to assess the accuracy of each model. For the test set the most accurate for human blood-air partition coefficients were the empirical equations of Meulenberg and Vijverberg (R(mean) = 1.1 +/- 0.46, E = 0.156) and the empirical solvation equation of Abraham and Weathersby (1994) (R(mean) = 0.93 +/- 0.38, E = 0.166). For rat blood, predictions are much less accurate due to difficulties in modeling the effects of protein binding, which are much larger. Overall, for rat blood-air partition coefficients the equation of Meulenberg and Vijverberg (1999) (R(mean) = 0.74 +/- 0.50, E = 0.236) was the most accurate. The tissue-composition-based equations of Poulin and Krishnan, using solubilities in vegetable oil, performed well for human liver-air partition coefficients (R(mean) = 1.21 +/- 0.28, E = 0.079) for log(octanol-water partition coefficients) > 0.7 and for fat-air partition coefficients, but overestimated solubilities in human kidney and brain tissues (e.g., for kidney tissue, R = 1.88 +/- 0.58, E = 0.255). The equations of Meulenberg and Vijverberg (2000a), Abraham and Weathersby (1994), and Paterson and Mackay (1989) also performed moderately well for human tissue-air partition coefficients. For rat muscle-air, liver-air, and fat-air partition coefficients the model of Poulin and Krishnan (1996a) gave the most accurate predictions. For tissue-blood partition coefficients, generally good agreement with experimental values is obtained by the empirical model of Balaz and Lukacova (1999) (e.g., for human kidney, R(mean) = 1.15 +/- 0.38, E = 0.085) and, if solubility in fat is known, by the equations of Fiserova-Bergerova and Diaz (1986) (e.g., for human muscle, R(mean) = 1.10 +/- 0.39, E = 0.107). The equations of DeJongh et al. (1997) gave the most accurate predictions for rat muscle-blood, liver-blood and fat-blood partition coefficients (e.g., for rat muscle R(mean) = 1.03 +/- 0.39, E = 0.149), but predictions were less accurate than for human tissue-blood partition coefficients, attributable to difficulties in modeling the effect of protein binding. The choice of equation for use in physiologically based pharmacokinetic (PBPK) models depends on the species, tissue, and chemical lipophilicity.

Computer-based assessment of potential toxicity has become increasingly popular in recent years. The knowledge-base system DEREK is developed under the guidance of a multinational Collaborative Group of expert toxicologists and provides a qualitative approach to toxicity prediction. Major developments of the DEREK program and knowledge-base have taken place in the last 3 years. Program developments include improvements in both the user interface and data processing. Work on the knowledge-base has concentrated on the areas of genotoxicity and skin sensitisation. DEREK's predictive capabilities for these toxicological end-points has been demonstrated. In addition to the continued expansion of the knowledge-base, a number of enhancements are planned in the DEREK program. In particular, work is in progress to develop further DEREK's ability to report the reasoning behind its predictions.

There are currently no in vitro methods for the identification of skin sensitizers (contact allergens). Knowledge relating chemical structure to toxicity can be programmed into expert systems. An historical database containing results of 294 defined single substances tested in the guinea pig maximization test to a single protocol has been used to derive a set of structural alerts for skin sensitization. Where possible, the approach used was to group the substances according to their most likely mechanism of reaction with skin proteins. Where no mechanism could be identified, structural alerts were derived empirically for groups of molecules with similar chemical functionality. This process has currently resulted in the production of 40 structure-activity rules, which have been incorporated into the expert system DEREK. Rulebases of this type have potential for use as a preliminary screen in toxicological hazard identification and may ultimately lead to a reduction in the use of laboratory animals.

The development of qualitative structure-activity relationships for the prediction of skin sensitization potential, based on structural alerts (substructures associated with a toxicological mechanism), and suitable for incorporation as rules into a knowledge-based system is described. The structure dependence of the skin sensitization mechanism may be largely defined in terms of the presence or metabolic/nonmetabolic formation of protein reactive functional groups on the test compound and by the physicochemical requirements of significant skin penetration. The proposed structural alerts were tested on a data set of diverse chemicals. The results showed that the alerts have potential as preliminary indicators of skin sensitization potential for a wide range of low molecular weight chemicals.

A neural network was applied to a large, structurally heterogeneous data set of mutagens and non-mutagens to investigate structure-property relationships. Substructural data comprising a total of 1280 fragments were used as inputs. The training of the back-propagation networks was directed by an algorithm which selected an optimal subset of fragments in order to maximize their discriminating power, and a good predictive network. The system comprised three programs: the first used a keyfile of 100 fragments to generate training and test files, the second was the network itself and a procedure for ranking the effectiveness of these fragments and the third randomly replaced the lowest fragments. This cycle was then repeated. After running on a 386/33 PC several networks produced approximately 11% failures in the test set and 6% in the training set. By simplifying the output of the hidden layer it was possible to describe the hidden layer states in terms of clusters of mutagens and non-mutagens. Some of these clusters were structurally homogeneous and contained known mutagenic and non-mutagenic structural classes. This analysis provided a useful means of demonstrating how the network was classifying the data.

The rate and amount of growth of 4 field isolates and reference strain ATCC 6223 of Francisella tularensis were evaluated on isolation media with 2 different agar bases and with different supplements and incubated at 25 C, 35 C, and 42 C. Biochemical reactions on conventional differential media with and without cysteine were evaluated. Two of the field isolates and the reference strain were F. tularensis subspecies tularensis (formerly biovar tularensis or Type A), and 2 isolates were subspecies holarctica (formerly subspecies palaearctica or Type B). Bacto cystine heart blood agar supplemented with 1% hemoglobin, glucose cystine heart blood agar, and brain-heart infusion blood agar supported good growth of all 4 field strains, with the most luxuriant growth occurring on Bacto cystine heart blood agar with hemoglobin. Heart infusion blood agar and trypticase soy blood agar supported growth of the field isolates, although growth was diminished and delayed. Strain 6223 was distinctly fastidious and failed to grow on heart infusion or trypticase soy blood agars. Growth of strain 6223 was best on Bacto cystine heart blood agar with hemoglobin. The agar base did not affect growth unless the supplements became limiting, in which case Bacto agar base generally supported growth better than BiTek agar base. Incubation at 35 C was optimum for all 5 strains. Growth at 42 C was slow, with the greatest decrease in the rate and amount of growth occurring with field isolates of F. tularensis subspecies tularensis. Strain 6223 did not grow at 25 C, and the 4 field isolates grew slowly at the lower temperature.(ABSTRACT TRUNCATED AT 250 WORDS)

The innervation density of serotonin (5-HT)-immunoreactive fibers, identified using an antibody to 5-HT, was found to differ in the 4 subdivisions of the cat lateral geniculate nucleus complex (LGN). The mean density (fiber length per unit area) of anti-5-HT-stained fibers was highest in the ventral LGN (0.062 micron per micron 2), moderate in the medial interlaminar nucleus (MIN) and the parvicellular C laminae of the dorsal LGN (0.039-0.040 per micron 2), and lowest in the A and magnocellular C laminae of the dorsal LGN (0.020 per micron 2). The fiber density in MIN was particularly dense along the medial edge of the nucleus, a region called the geniculate wing. The heaviest serotonin innervation is thus found in geniculate structures receiving input from W-type retinal ganglion cells and lightest in structures receiving X and Y input.