Accessible and reliable neurometric testing in humans using a smartphone platform

Estrogens' effects on hearing are documented across species, but the responsible molecular mechanisms remain unknown. The presence of estrogen receptors (ER) throughout the auditory system offers a potential pathway of direct estrogenic effects on auditory function, but little is known about how each ER's expression is regulated by the overall hormonal status of the body. In the present study, we determined the effects of ovariectomy and chronic 17β-estradiol treatment on mRNA and protein expression of ERα and ERβ in peripheral (cochlea) and central (inferior colliculus) auditory structures of mice, as well as on auditory-related behavior using the acoustic startle response (ASR), prepulse inhibition (PPI), and habituation of the startle response. 17β-Estradiol treatment down-regulated ERα but not ERβ and increased PPI and latency of the ASR. Neither the magnitude nor the habituation of ASR was affected. Furthermore, ER's mRNA and protein expression in the inner ear were analyzed throughout the estrous cycle (proestrus, estrus, metestrus, and diestrus), revealing a negative correlation of circulating estrogens with ERα expression, whereas ERβ was stable. Our findings show that ER not only are present in both the peripheral and central auditory system but also that circulating estrogen levels down-regulate ERα expression in the auditory system and affect PPI and the latency of ASR, suggesting a key role of ERα as a hormone-induced modulator of the auditory system and behavior.

Long-term impacts of adolescent risperidone treatment on behavioral responsiveness to olanzapine and clozapine in adulthood

Disruption of sensorimotor gating causes "flooding" of irrelevant sensory input and is considered a congenital trait in several neurodevelopmental disorders. Prepulse inhibition of acoustic startle response (PPI) is the operational measurement and has a high translational validity. Pharmacological studies in rodents have linked alterations in serotonin, dopamine and glutamate signalling to PPI disruption. How PPI response is associated with gene expression levels of these receptors is unknown. PPI response was assessed in 39 genetically heterogeneous National Institutes of Health-Heterogeneous Stock (NIH-HS) rats. Animals were classified as high, medium or low PPI. Expression levels of glutamate metabotropic receptor 2 (Grm2), dopamine receptor D2 (Drd2), dopamine receptor D1 (Drd1), serotonin receptor 1A (Htr1a), serotonin receptor 2A (Htr2a) and homer scaffolding protein 1 (Homer1) were investigated in prefrontal cortex (PFC) and striatum (STR). When comparing the two extreme phenotypes, only Drd2 in STR showed increased expression in the low PPI group. A multinomial model fitting all genes and all groups indicated that Grm2 in PFC, and Grm2 and Drd2 in the STR predicted PPI group. This was corroborated by a linear relationship of Grm2 with PPI in PFC, and Drd2 with PPI in STR. An interaction between levels of H3K27 trimethylation, associated with transcriptional repression, and PPI phenotype was observed for Drd2 in STR. Gene set enrichment analysis on a microarray dataset on Lewis rats confirmed enrichment of Drd2 in PFC in relation to PPI. These findings contribute to the understanding of the genetic substrate behind alterations in sensorimotor gating, relevant for its linkage to neurodevelopmental disorders.

Previously, we found a patient with intractable motor tic disorder, a spectrum of Tourette syndrome (TS), responsive to the ground leaf juice of Clerodendrum inerme (CI). Here, we examined the effect of the ethanol extract of CI leaves (CI extract) on animal behaviors mimicking TS, hyperlocomotion, and sensorimotor gating deficit. The latter is also observed in schizophrenic patients and can be reflected by a disruption of prepulse inhibition of acoustic startle response (PPI) in animal models induced by methamphetamine and NMDA channel blockers (ketamine or MK-801), based on hyperdopaminergic and hypoglutamatergic hypotheses, respectively. CI extract (10–300 mg/kg, i.p.) dose-dependently inhibited hyperlocomotion induced by methamphetamine (2 mg/kg, i.p.) and PPI disruptions induced by methamphetamine, ketamine (30 mg/kg, i.p.), and MK-801 (0.3 mg/kg, i.p.) but did not affect spontaneous locomotor activity, rotarod performance, and grip force. These results suggest that CI extract can relieve hyperlocomotion and improve sensorimotor gating deficit, supporting the therapeutic potential of CI for TS and schizophrenia.

Effects of anticholinergic drugs selective for muscarinic receptor subtypes on prepulse inhibition in mice

The effects of postnatal phthalate exposure on the development of auditory temporal processing in rats

Impact of postnatal blockade of N-methyl-d-aspartate receptors on rat behavior: A search for a new developmental model of schizophrenia

Hexahydrocannabinol (HHC) is a new psychoactive substance known for its mind-altering effects and temporary legal status. It is widely used in parts of the Europe and United Kingdom as a legal alternative to ∆9-tetrahydrocannabinol, yet little research has explored its effects and safety. This study examined how HHC is processed in the body, its toxicity, and its impact on behavior in male Wistar rats. A 1:1 mixture of (9R)-HHC and (9S)-HHC was administered via intragastric gavage at doses of 1, 5, and 10mg/kg. Behavioral effects were assessed using the open field test and the prepulse inhibition of acoustic startle response. Two hours after the highest dose (10mg/kg), peak concentrations of HHC were detected in blood and brain tissue. The Organization for Economic Co-operation and Development 423 toxicity test classified HHC as a Category 4 substance, estimating a lethal dose of 1000mg/kg. Compared to controls (administered by sunflower oil), 10mg/kg HHC reduced movement, increased anxiety, and impaired sensory processing. Overall, HHC crosses the blood-brain barrier, exhibits mild toxicity, and induces behavioral effects similar to tetrahydrocannabinol. Its dose-dependent anxiogenic properties and impact on information processing highlight the importance of the appropriate dosing in any potential therapeutic use.

PW01-236 - Impulsivity and startle habituation as vulnerability markers for alcoholism

Developmental stress disrupts habituation but spares prepulse inhibition in young rats

Labour productivity is a crucial factor in the success of construction projects. However, Sri Lankan construction industry has been struggling to enhance labour productivity due to inadequate labour management, poor monitoring systems and safety-related problems. These various challenges have led to problems such as project delays and cost overruns, and poor site performance. Computer vision (CV) has been found to overcome these issues and enhance labour management in the construction industry. Additionally, CV can monitor the activities of labours, track activities, control behaviour, detect the location and identify objects continuously, which ultimately enhances the labour productivity. By automating data collection through cameras and AI models, site managers gain accurate insights into performance without disrupting workflows. It ensures transparency, accountability, and quick response to inefficiencies. This research study focuses on deploying CV to improve labour productivity in the Sri Lankan construction industry. This study was based on information gathered from 16 expert interviews involving construction professionals and IT specialists. The findings highlight CV applications in labour management and further present substantial possibilities to transform the construction industry through CV. Moreover, the study highlights real-time monitoring together with task optimization, safety improvement and workforce efficiency enhancement. Finally, this research provides CV applications and key stages as follows with a view to indicating appropriate decisions to make. Application of CV can assist in avoiding problems and identifying the best practices in the application of CV technologies in the Sri Lankan construction industry.

Stress resilience is recognized as an important occupational prerequisite for air traffic controllers (ATCs). A system for input/output multimodal stress resilience assessment based on physiological features has been developed and applied in the ATC selection process on 40 ATC candidates, as well as on 40 age/sex-matched control subjects. The input stimulation paradigm includes acoustic startle stimuli and their prepulse and fear-potentiated modulations, airblasts, and semantically relevant aversive images and sounds. The output physiological features include resting heart rate variability and respiratory sinus arrhythmia, cardiac allostasis, electromyogram- and electrodermal activity-based acoustic startle response features, like startle reactivity and startle habituation, and acoustic startle modulation-related features, like fear-potentiated startle, prepulse inhibition of the startle response, and discrimination of startle responses in danger versus safety experimental conditions. Variability of each feature is assessed and illustrated in 8-D physiological resilience space. Statistically significant differences (p <; 0.05) between the two groups have been obtained for the three most relevant of eight applied features; specifically, ATC candidates exhibited significantly higher resting respiratory sinus arrhythmia, lower startle reactivity, and more pronounced cardiac allostasis than the control group. The observed feature variability justifies future research efforts toward augmenting the traditional ATC selection process with the presented stress resilience assessment approach. The proposed research paradigm can be also applied in selection processes of similarly stressful occupations such as first responders, airline/military pilots, military personnel, among others.

The Role of AI in Modern Hernia Surgery: A Review and Practical Insights.

SUMMARYBackground: This study was conducted to assess whether general practitioners (GPs) can be trained to use a simple battery of functional scales and neuropsychological tests to detect people likely to develop dementia as reliably as neuropsychologists in clinical practice.Methods: Fifty GPs with medium-sized practices in the Bordeaux area of France were recruited by monitors and trained to use a battery of tests (Mini-Mental State Examination (MMSE), Isaacs Set Test (IST), Benton Visual Retention Test (BVRT) and Zazzo's Cancellation Test (ZCT)). Each GP was required to recruit one patient. The tests were administered first by the GP, and then by a trained psychologist.Results: Overall, the GPs showed interest in participating in the study. They had no difficultyin recruiting patients according to the inclusion and exclusion criteria and none reported any difficulty in using the scales and tests battery. In total, 35 subjects were interviewed by both a trained GP and a psychologist. The scores obtained by the GPs and psychologists did not differ statistically for two of the four tests (IST, p = 0.6; BVRT, p = 0.7), but were statistically different for the other two tests (MMSE, p = 0.04; ZCT; p < 0.002).Conclusions: The results confirm the feasibility of conducting a study for detecting cognitive deficit in general practice. The GPs were interested and participated well, patient adherence was good, and the concordance correlation coefficients between the GPs' and psychologists' scores were satisfactory.

IntroductionArtificial intelligence and computer vision are revolutionizing the way we perceive video analysis in minimally invasive surgery. This emerging technology has increasingly been leveraged successfully for video segmentation, documentation, education, and formative assessment. New, sophisticated platforms allow pre-determined segments chosen by surgeons to be automatically presented without the need to review entire videos. This study aimed to validate and demonstrate the accuracy of the first reported AI-based computer vision algorithm that automatically recognizes surgical steps in videos of totally extraperitoneal (TEP) inguinal hernia repair.MethodsVideos of TEP procedures were manually labeled by a team of annotators trained to identify and label surgical workflow according to six major steps. For bilateral hernias, an additional change of focus step was also included. The videos were then used to train a computer vision AI algorithm. Performance accuracy was assessed in comparison to the manual annotations.ResultsA total of 619 full-length TEP videos were analyzed: 371 were used to train the model, 93 for internal validation, and the remaining 155 as a test set to evaluate algorithm accuracy. The overall accuracy for the complete procedure was 88.8%. Per-step accuracy reached the highest value for the hernia sac reduction step (94.3%) and the lowest for the preperitoneal dissection step (72.2%).ConclusionsThese results indicate that the novel AI model was able to provide fully automated video analysis with a high accuracy level. High-accuracy models leveraging AI to enable automation of surgical video analysis allow us to identify and monitor surgical performance, providing mathematical metrics that can be stored, evaluated, and compared. As such, the proposed model is capable of enabling data-driven insights to improve surgical quality and demonstrate best practices in TEP procedures.Graphical abstract