Human exposure to nitro musks and the evaluation of their potential toxicity: an overview

Synthetic nitro musks are fragrant chemicals found in household and personal care products. The use of these products leads to direct exposures via dermal absorption, as well as inhalation of contaminated dust and volatilized fragrances. Evidence also suggests that humans are exposed to low doses of these chemicals through oral absorption of contaminated liquids and foods. As these compounds are lipophilic, they and their metabolites, have been found not only in blood, but also breast milk and adipose tissue. After personal use, these environmentally persistent pollutants then pass through sewage treatment plants through their effluent into the environment. Little is known about the biological effects in humans after such a prolonged low dose exposure to these chemicals. While epidemiologic studies evaluating the effects of nitro musk exposures are lacking, there is limited evidence that suggest blood levels of nitro musks are inversely related to luteal hormone levels. This is supported by animal models and laboratory studies that have shown that nitro musks are weakly estrogenic. Nitro musks exposure has been associated with an increased risk of tumor formation in mice. The evidence suggests that while nitro musks by themselves are not genotoxic, they may increase the genotoxicity of other chemicals. However, animal models for nitro musk exposure have proven to be problematic since certain outcomes are species specific. This may explain why evidence for developmental effects in animals is conflicting and inconclusive. Given that animal models and cell-line experiments are suggestive of adverse outcomes, further epidemiologic studies are warranted

The feasibility of artificial consciousness through the lens of neuroscience

Interactions with large language models have led to the suggestion that these models may be conscious. From the perspective of neuroscience, this position is difficult to defend. For one, the architecture of large language models is missing key features of the thalamocortical system that have been linked to conscious awareness in mammals. Secondly, the inputs to large language models lack the embodied, embedded information content characteristic of our sensory contact with the world around us. Finally, while the previous two arguments can be overcome in future AI systems, the third one might be harder to bridge in the near future. Namely, we argue that consciousness might depend on having 'skin in the game', in that the existence of the system depends on its actions, which is not true for present-day artificial intelligence

Complete traumatic laryngo-tracheal separation.

Laryngotracheal separation injuries are rare and potentially fatal. Immediate respiratory signs may include dysphonia, aphonia, hemoptysis, subcutaneous emphysema and a sucking wound. Patients with this injury usually die at the site of the trauma. The absolute life saving intervention for patients with laryngotracheal injury is airway control via routine intubation or emergency tracheostomy. We present an extremely rare case of complete laryngotracheal separation in a teenager driving a quad bike in a \u27clothes line\u27 type injury with chicken wire. This case highlights the need for prompt airway evaluation, radiological imaging required, surgical management and long term injury sequelae

A Nonstationary Negative Binomial Time Series with Time-Dependent Covariates: Enterococcus Counts in Boston Harbor

Boston Harbor has had a history of poor water quality, including contamination by enteric pathogens. We conduct a statistical analysis of data collected by the Massachusetts Water Resources Authority (MWRA) between 1996 and 2002 to evaluate the effects of court-mandated improvements in sewage treatment. Motivated by the ineffectiveness of standard Poisson mixture models and their zero-inflated counterparts, we propose a new negative binomial model for time series of Enterococcus counts in Boston Harbor, where nonstationarity and autocorrelation are modeled using a nonparametric smooth function of time in the predictor. Without further restrictions, this function is not identifiable in the presence of time-dependent covariates; consequently we use a basis orthogonal to the space spanned by the covariates and use penalized quasi-likelihood (PQL) for estimation. We conclude that Enterococcus counts were greatly reduced near the Nut Island Treatment Plant (NITP) outfalls following the transfer of wastewaters from NITP to the Deer Island Treatment Plant (DITP) and that the transfer of wastewaters from Boston Harbor to the offshore diffusers in Massachusetts Bay reduced the Enterococcus counts near the DITP outfalls

Abnormal connectivity between the default mode and the visual system underlies the manifestation of visual hallucinations in Parkinson’s disease:A task-based fMRI study

Background: The neural substrates of visual hallucinations remain an enigma, due primarily to the difficulties associated with directly interrogating the brain during hallucinatory episodes. Aims: To delineate the functional patterns of brain network activity and connectivity underlying visual hallucinations in Parkinson’s disease. Methods: In this study, we combined functional magnetic resonance imaging (MRI) with a behavioral task capable of eliciting visual misperceptions, a confirmed surrogate for visual hallucinations, in 35 patients with idiopathic Parkinson’s disease. We then applied an independent component analysis to extract time series information for large-scale neuronal networks that have been previously implicated in the pathophysiology of visual hallucinations. These data were subjected to a task-based functional connectivity analysis, thus providing the first objective description of the neural activity and connectivity during visual hallucinations in patients with Parkinson’s disease. Results: Correct performance of the task was associated with increased activity in primary visual regions; however, during visual misperceptions, this same visual network became actively coupled with the default mode network (DMN). Further, the frequency of misperception errors on the task was positively correlated with the strength of connectivity between these two systems, as well as with decreased activity in the dorsal attention network (DAN), and with impaired connectivity between the DAN and the DMNs, and ventral attention networks. Finally, each of the network abnormalities identified in our analysis were significantly correlated with two independent clinical measures of hallucination severity. Conclusions: Together, these results provide evidence that visual hallucinations are due to increased engagement of the DMN with the primary visual system, and emphasize the role of dysfunctional engagement of attentional networks in the pathophysiology of hallucinations

Interactions between metals and microbial communities in New Bedford Harbor, Massachusetts.

The fate of toxic metals in marine sediments depends on a combination of the physical, chemical, and biologic conditions encountered in any given environment. These conditions may vary dramatically, both spatially and temporally, in response to factors ranging from seasonal changes and storm events to human activities such as dredging or remediation efforts. This paper describes a program designed to evaluate the interrelationships between the microbial community and pollutants in the New Bedford Harbor, Massachusetts, area, a U.S. Environmental Protection Agency designated Superfund site. Research has focused on establishing distributional relationships between contaminant metals, fluxes of metals between sediments and the overlying water, changes in microbial diversity in response to metals, and potential use of the microbial community as a biomarker of contaminant availability. This research has shown that a significant flux of metals to the water column is mediated by benthic biologic activity, and that microbial communities may be a responsive marker of contaminant stress. A combination of biogeochemical studies and the use of molecular tools can be used to improve our understanding of the fate and effect of heavy metals released to aquatic systems