The Effect of Age on Decision Making During Unprotected Turns Across Oncoming Traffic

The present study examined whether age-related differences in quantitative measures of left-tum performance could explain older drivers\u27 increased susceptibility to crashing while making unprotected left turns across traffic. Older and younger adults made left turns across traffic in a driving simulator. Time to decide to turn, time to negotiate the turn, the size of the accepted gap, gap clearance, and time to collision with an oncoming vehicle were measured. Significant effects of age were found in decision time, turn time and gap size. A significant interaction between age group and the speed of oncoming traffic was obtained for decision time. Implications for older adult\u27s safety and future directions are discussed

Assessment of the SEEV Model to Predict Attention Allocation at Intersections During Simulated Driving

We attempted to model attention allocation of experienced drivers using the SEEV model. Unlike previous attempts, the present work looked at attention to entities (vehicles, signs, traffic control devices) in the outside world rather than considering the outside world as a unitary construct. Model parameters were generated from rankings of entities by experienced drivers. Experienced drivers drove a scenario that included a number of intersections interspersed with stretches of straight road. The intersections included non-hazard events. Eye movements were monitored during the driving session. The results of fitting the observed eye movement data to our SEEV model were poor, and were no better than fitting the data to a randomized SEEV model. A number of explanations for this are discussed

Insights into the function of HDAC3 and NCoR1/NCoR2 co-repressor complex in metabolic diseases

Histone deacetylase 3 (HDAC3) and nuclear receptor co-repressor (NCoR1/2) are epigenetic regulators that play a key role in gene expression and metabolism. HDAC3 is a class I histone deacetylase that functions as a transcriptional co-repressor, modulating gene expression by removing acetyl groups from histones and non-histone proteins. NCoR1, on the other hand, is a transcriptional co-repressor that interacts with nuclear hormone receptors, including peroxisome proliferator-activated receptor gamma (PPARγ) and liver X receptor (LXR), to regulate metabolic gene expression. Recent research has revealed a functional link between HDAC3 and NCoR1 in the regulation of metabolic gene expression. Genetic deletion of HDAC3 in mouse models has been shown to improve glucose intolerance and insulin sensitivity in the liver, skeletal muscle, and adipose tissue. Similarly, genetic deletion of NCoR1 has improved insulin resistance and reduced adiposity in mouse models. Dysregulation of this interaction has been associated with the development of cardio-metabolic diseases such as cardiovascular diseases, obesity and type 2 diabetes, suggesting that targeting this pathway may hold promise for the development of novel therapeutic interventions. In this review, we summarize the current understanding of individual functions of HDAC3 and NCoR1/2 and the co-repressor complex formation (HDAC3/NCoR1/2) in different metabolic tissues. Further studies are needed to thoroughly understand the mechanisms through which HDAC3, and NCoR1/2 govern metabolic processes and the implications for treating metabolic diseases

Comparison of Novice and Experienced Drivers Using the SEEV Model to Predict Attention Allocation at Intersections During Simulated Driving

We compared the eye movements of novice drivers and experienced drivers while they drove a simulated driving scenario that included a number of intersections interspersed with stretches of straight road. The intersections included non-hazard events. Cassavaugh, Bos, McDonald, Gunaratne, & Backs (2013) attempted to model attention allocation of experienced drivers using the SEEV model. Here we compared two SEEV model fits between those experienced drivers and a sample of novice drivers. The first was a simplified model and the second was a more complex intersection model. The observed eye movement data was found to be a good fit to the simplified model for both experienced (R2 = 0.88) and novice drivers (R2 = 0.30). Like the previous results of the intersection model for the experienced drivers, the fit of the observed eye movement data to the intersection model for novice drivers was poor, and was no better than fitting the data to a randomized SEEV model. We concluded based on the simplified SEEV model, fixation count and fixation variance that experienced drivers were found to be more efficient at distributing their visual search compared to novice drivers

Comparison of Novice and Experienced Drivers Using the SEEV Model to Predict Attention Allocation at Intersections During Simulated Driving

We compared the eye movements of novice drivers and experienced drivers while they drove a simulated driving scenario that included a number of intersections interspersed with stretches of straight road. The intersections included non-hazard events. Cassavaugh, Bos, McDonald, Gunaratne, & Backs (2013) attempted to model attention allocation of experienced drivers using the SEEV model. Here we compared two SEEV model fits between those experienced drivers and a sample of novice drivers. The first was a simplified model and the second was a more complex intersection model. The observed eye movement data was found to be a good fit to the simplified model for both experienced (R2 = 0.88) and novice drivers (R2 = 0.30). Like the previous results of the intersection model for the experienced drivers, the fit of the observed eye movement data to the intersection model for novice drivers was poor, and was no better than fitting the data to a randomized SEEV model. We concluded based on the simplified SEEV model, fixation count and fixation variance that experienced drivers were found to be more efficient at distributing their visual search compared to novice drivers

Modulation of chromatin position and gene expression by HDAC4 interaction with nucleoporins

The histone deacetylase HDAC4 associates with the nuclear pore complex component Nup155 to modulate gene expression during cardiomyocyte hypertrophy

Heart rate variability (HRV) and muscular system activity (EMG) in cases of crash threat during simulated driving of a passenger car

Objectives: The aim of the study was to verify whether simultaneous responses from the muscular and circulatory system occur in the driver's body under simulated conditions of a crash threat. Materials and Methods: The study was carried out in a passenger car driving simulator. The crash was included in the driving test scenario developed in an urban setting. In the group of 22 young male subjects, two physiological signals - ECG and EMG were continuously recorded. The length of the RR interval in the ECG signal was assessed. A HRV analysis was performed in the time and frequency domains for 1-minute record segments at rest (seated position), during undisturbed driving as well as during and several minutes after the crash. For the left and right side muscles: m. trapezius (TR) and m. flexor digitorum superficialis (FDS), the EMG signal amplitude was determined. The percentage of maximal voluntary contraction (MVC) was compared during driving and during the crash. Results: As for the ECG signal, it was found that in most of the drivers changes occurred in the parameter values reflecting HRV in the time domain. Significant changes were noted in the mean length of RR intervals (mRR). As for the EMG signal, the changes in the amplitude concerned the signal recorded from the FDS muscle. The changes in ECG and EMG were simultaneous in half of the cases. Conclusion: Such parameters as mRR (ECG signal) and FDS-L amplitude (EMG signal) were the responses to accident risk. Under simulated conditions, responses from the circulatory and musculoskeletal systems are not always simultaneous. The results indicate that a more complete driver's response to a crash in road traffic is obtained based on parallel recording of two physiological signals (ECG and EMG)

Growth factor stimulation of cardiomyocytes induces changes in the transcriptional contents of secreted exosomes

Exosomes are nano-sized extracellular vesicles, released from various cells, which can stimulate or repress responses in targets cells. We recently reported that cultured cardiomyocytes are able to release exosomes and that they, in turn, are involved in facilitating events in target cells by alteration of gene expression. We investigated whether external stimuli of the cardiomyocyte might influence the transcriptional content of the released exosomes.Exosomes were isolated from media collected from cultured cardiomyocytes (HL-1) with or without growth factor treatment (TGF-β2 and PDGF-BB), with a series of differential centrifugations, including preparative ultracentrifugation and separation with a sucrose gradient. The exosomes were characterized with dynamic light scattering (DLS), electron microscopy (EM) and Western blot and analyzed with Illumina whole genome microarray gene expression.The exosomes were rounded in shape and had an average size of 50–90 nm in diameter with no difference between treatment groups. Analysis of the mRNA content in repeated experiments conclusively revealed 505 transcripts in the control group, 562 in the TGF-β2-treated group and 300 in the PDGF-BB-treated group. Common transcripts (217) were found in all 3 groups.We show that the mode of stimulation of parental cells affects the characteristics of exosomes released. Hence, there is a difference in mRNA content between exosomes derived from cultured cardiomyocytes stimulated, or not stimulated, with growth factors. We also conclude that all exosomes contain a basic package consisting of ribosomal transcripts and mRNAs coding for proteins with functions within the energy supply system. To access the supplementary material to this article, please see Supplementary files under Article Tools online