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The safety evaluation of oral exposure to substances, such as food ingredients, additives, and their constituents, relies primarily on a careful evaluation and analysis of data from oral toxicity studies. When relevant oral toxicity studies are unavailable or may have significant data gaps that make them inadequate for use in safety evaluations, data from non-oral toxicity studies in animals, such as studies on inhalation, dermal exposure, etc., might be used in support of or in place of oral toxicity studies through route-to-route (R-t-R) extrapolation. R-t-R extrapolation is applied on a case-by-case basis as it requires attention to and comparison of substance-specific toxicokinetic (TK) and toxicodynamic (TD) data for oral and non-oral exposure routes. This article provides a commentary on the utility of R-t-R extrapolation to assess the safety of oral exposure to substances, with an emphasis on the relevance of TK and systemic toxicity data. [ABSTRACT FROM AUTHOR]

Reproductive toxicity is one of the prominent endpoints in the risk assessment of environmental and industrial chemicals. Due to the complexity of the reproductive system, traditional reproductive toxicity testing in animals, especially guideline multigeneration reproductive toxicity studies, take a long time and are expensive. Therefore, machine learning, as a promising alternative approach, should be considered when evaluating the reproductive toxicity of chemicals. We curated rat multigeneration reproductive toxicity testing data of 275 chemicals from ToxRefDB (Toxicity Reference Database) and developed predictive models using seven machine learning algorithms (decision tree, decision forest, random forest, k-nearest neighbors, support vector machine, linear discriminant analysis, and logistic regression). A consensus model was built based on the seven individual models. An external validation set was curated from the COSMOS database and the literature. The performances of individual and consensus models were evaluated using 500 iterations of 5-fold cross-validations and the external validation data set. The balanced accuracy of the models ranged from 58% to 65% in the 5-fold cross-validations and 45%-61% in the external validations. Prediction confidence analysis was conducted to provide additional information for more appropriate applications of the developed models. The impact of our findings is in increasing confidence in machine learning models. We demonstrate the importance of using consensus models for harnessing the benefits of multiple machine learning models (i.e., using redundant systems to check validity of outcomes). While we continue to build upon the models to better characterize weak toxicants, there is current utility in saving resources by being able to screen out strong reproductive toxicants before investing in vivo testing. The modeling approach (machine learning models) is offered for assessing the rat multigeneration reproductive toxicity of chemicals. Our results suggest that machine learning may be a promising alternative approach to evaluate the potential reproductive toxicity of chemicals. [ABSTRACT FROM AUTHOR]

Both the National Institute of Environmental Health Sciences (NIEHS) and the U.S. Food and Drug Administration (FDA) work to promote and protect public health. The NIEHS achieves this mission by [...]

Central serotonin (5-HT) neurons modulate many vital brain functions, including respiratory control. Whether breathing depends critically on 5-HT neurons, or whether their influence is excitatory or inhibitory, remains controversial. Here we show that neonatal Lmx1bflox/flox;ePet-Cre/+ mice (also called Lmx1bf/f/p mice), which selectively lack serotonin neurons, display frequent and severe apnea lasting as long as 55 s. This was associated with a marked decrease in ventilation to less than one-half of normal. These respiratory abnormalities were most severe during the postnatal period, markedly improving by the time the pups were 2- 4 weeks old. Despite the severe breathing dysfunction, many of these mice survived, but there was a high perinatal mortality, and those that survived had a decrease in growth rate until the age at which the respiratory defects resolved. Consistent with these in vivo observations, respiratory output was markedly reduced in isolated brainstem-spinal cord preparations from neonatal Lmx1bf/f/p mice and completely blocked in perfused brain preparations from neonatal rats treated with selective antagonists of 5-HT2A and neurokinin 1 (NK-1) receptors. The ventilatory deficits in neonatal Lmx1bf/f/p mice were reversed in vitro and in vivo with agonists of 5-HT2A and/or NK-1 receptors. These results demonstrate that ventilatory output in the neonatal period is critically dependent on serotonin neurons, which provide excitatory drive to the respiratory network via 5-HT2A and NK-1 receptor activation. These findings provide insight into the mechanisms of sudden infant death syndrome, which has been associated with abnormalities of 5-HT neurons and of cardiorespiratory control. [ABSTRACT FROM AUTHOR]

Brainstem serotonin (5-HT) neurons modulate activity of many neural circuits in the mammalian brain, but in many cases endogenous mechanisms have not been resolved. Here, we analyzed actions of raphé 5-HT neurons on respiratory network activity including at the level of the pre-Bötzinger complex (pre-BötC) in neonatal rat medullary slices in vitro, and in the more intact nervous system of juvenile rats in arterially perfused brainstem-spinal cord preparations in situ. At basal levels of activity, excitation of the respiratory network via simultaneous release of 5-HT and substance P (SP), acting at 5-HT2A/2C , 5-HT4 , and/or neurokinin-1 receptors, was required to maintain inspiratory motor output in both the neonatal and juvenile systems. The midline raphé obscurus contained spontaneously active 5-HT neurons, some of which projected to the pre-BötC and hypoglossal motoneurons, colocalized 5-HT and SP, and received reciprocal excitatory connections from the pre-BötC. Experimentally augmenting raphé obscurus activity increased motor output by simultaneously exciting pre-BötC and motor neurons. Biophysical analyses in vitro demonstrated that 5-HT and SP modulated background cation conductances in pre-BötC and motor neurons, including a nonselective cation leak current that contributed to the resting potential, which explains the neuronal depolarization that augmented motor output. Furthermore, we found that 5-HT, but not SP, can transform the electrophysiological phenotype of some pre-BötC neurons to intrinsic bursters, providing 5-HT with an additional role in promoting rhythm generation. We conclude that raphé 5-HT neurons excite key circuit components required for generation of respiratory motor output. [ABSTRACT FROM AUTHOR]

The article analyzes a study on the tuning properties of antennal lobe projection neurons. The olfactory systems of vertebrates and insects share a number of remarkable similarities both on the anatomical and functional level. In both phyla, a highly organized pattern of axonal convergence of isofunctional peripheral sensory neurons to one or a few discrete glomeruli in the antennal lobe (insects) or olfactory bulb (vertebrates) generates a chemotopic map of odor quality in the brain.