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Current guidelines for developmental neurotoxicity (DNT) evaluation are based on animal models. These have limitations so more relevant, efficient and robust approaches for DNT assessment are needed. We have used the human SH-SY5Y neuroblastoma cell model to evaluate a panel of 93 mRNA markers that are frequent in Neuronal diseases and functional annotations and also differentially expressed during retinoic acid-induced differentiation in the cell model. Rotenone, valproic acid (VPA), acrylamide (ACR) and methylmercury chlo-ride (MeHg) were used as DNT positive compounds. Tolbutamide, D-mannitol and clofibrate were used as DNT negative compounds. To determine concentrations for exposure for gene expression analysis, we developed a pipeline for neurite outgrowth assessment by live-cell imaging. In addition, cell viability was measured by the resazurin assay. Gene expression was analyzed by RT-qPCR after 6 days of exposure during differentiation to concentrations of the DNT positive compounds that affected neurite outgrowth, but with no or minimal effect on cell viability. Methylmercury affected cell viability at lower concentrations than neurite outgrowth, hence the cells were exposed with the highest non-cytotoxic concentration. Rotenone (7.3 nM) induced 32 differentially expressed genes (DEGs), ACR (70 mu M) 8 DEGs, and VPA (75 mu M) 16 DEGs. No individual genes were significantly dysregulated by all 3 DNT positive compounds (p < 0.05), but 9 genes were differentially expressed by 2 of them. Methylmercury (0.8 nM) was used to validate the 9 DEGs. The expression of SEMA5A (encoding semaphorin 5A) and CHRNA7 (encoding nicotinic acetylcholine receptor subunit alpha 7) was downregulated by all 4 DNT positive compounds. None of the DNT negative compounds dysregulated any of the 9 DEGs in common for the DNT positive compounds. We suggest that SEMA5A or CHRNA7 should be further evaluated as biomarkers for DNT studies in vitro since they also are involved in neurodevelopmental adverse outcomes in humans.

Acute alcohol intoxication impairs cognitive and psychomotor abilities leading to various public health hazards such as road traffic accidents and alcohol-related violence. Intoxicated individuals are usually identified by measuring their blood alcohol concentration (BAC) using breathalysers that are expensive and labour-intensive. In this paper, we developed the Audio-based Deep Learning Algorithm to Identify Alcohol Inebriation (ADLAIA) that can instantly predict an individual's intoxication status based on a 12-second recording of their speech.ADLAIA was trained on a publicly available German Alcohol Language Corpus that comprises a total of 12,360 audio clips of inebriated and sober speakers (total of 162, aged 21-64, 47.7% female). ADLAIA's performance was determined by computing the unweighted average recall (UAR) and accuracy of inebriation prediction.ADLAIA was able to identify inebriated speakers-with BAC of 0.05% or higher-with an UAR of 68.09% and accuracy of 67.67%. ADLAIA had a higher performance (UAR of 75.7%) in identifying intoxicated speakers (BAC0.12%).Being able to identify intoxicated individuals solely based on their speech, ADLAIA could be integrated in mobile applications and used in environments (such as bars, sports stadiums) to get instantaneous results about inebriation status of individuals.

This study investigated the influence of social incentives, alcohol incentives, and responsibility disincentives on decisions to attend and drink at party events in young adult college students (n = 82; 55 women, 27 men) where 36 (20 women; 16 men) had an Alcohol Use Disorder (AUD) and 46 (35 women; 11 men) were Control participants without an AUD.In this within-subjects design participants were presented with a series of hypothetical drinking event scenarios that varied in terms of social incentives (knowing many versus few people), alcohol incentives (more versus less alcohol available), and next day responsibility disincentives (high vs moderate vs low). Participants were asked whether they would attend the event and how many drinks they would consume.Social incentives significantly predicted both decisions to attend party events and decisions about how much to drink for all participants. Participants were more likely to decide to attend and drink more at high social incentive party events (where they knew more people). However, while low social incentives generally discouraged attendance decisions, AUD participants were more likely than controls to decide to attend party events in low social incentive contexts. Alcohol incentives did not affect attendance decisions. However, alcohol incentives did increase drinking amount decisions for AUD participants. Finally, while disincentives decreased attendance and drinking amount decisions in general, AUD participants were less deterred by responsibility disincentives than Controls.The results highlight the important influence of social rewards on drinking related decisions and suggest individual differences in how incentives and disincentives affect drinking decisions in persons with an AUD.

Thiamethoxam, a neonicotinoid insecticide, is a widely used insecticide with neurotoxic potential. This study explored the neuroprotective effects of silymarin on thiamethoxam-triggered cortical injury in male rats. Animals were divided into four groups and treated daily either with SM (150 mg/kg), TMX (78.15 mg/kg), or both at the aforementioned doses for 28 days. Our results revealed marked declines in cortical SOD and CAT activities with elevations in MDA, IL-1b and TNF-α levels in thiamethoxam-treated rats. Further, thiamethoxam induced down-regulation in gene expressions of Sod, Cat, Gpx, and Nrf-2 genes, with up-regulation in the expression of IL-1b, IL-6, iNOS, TNF-α and NF-kB genes. Interestingly, pre-treatment with SM provided a notable neuroprotective action against TMX-mediated cortical damage that indicates its promising antioxidant and anti-inflammatory activities. This effect may be mediated by Nrf2/NF-kB/iNOS signalling and suppression of excess free radicals and production of inflammatory cytokines.

Insomnia is common among patients with AUD and can impair quality of life and cognitive functioning, as well as cause psycho-social problems and increased risk of relapse. Nonetheless, determinants of insomnia in patients with AUD have scarcely been studied. We aimed to examine prevalence and development of self-perceived insomnia among inpatients in treatment for AUD, and to examine factors in this group known to be associated with sleep disturbance in the general population. We examined self-reported information about sleep from ninety-four AUD inpatients in long-term treatment (up to nine months) using a questionnaire identifying probable insomnia. Potential predictors identified in bivariate tests were used in binomial logistic regressions to examine the effect on sleep at baseline and at six-week follow-up. Longitudinal multilevel analyses were used to examine factors affecting development of sleep quality during the treatment stay. At baseline, 54% of the patients reported sleep problems indicating insomnia. This was reduced to 35% at six-week follow-up. In a cross-sectional analysis of sleep at baseline, we found that being male (OR 0.18, p=0.042) and engaging in physical activity (OR 0.09, p