Salivary levels of alpha-amylase are associated with neurobehavioral alertness during extended wakefulness, but not simulated night-shift work.

Sleep loss is one of the most common causes of accidents and errors in operational environments. Currently, no single method satisfies all of the requisite criteria of an effective system for assessing the risk of injury prior to safety being compromised. Research has concentrated towards the development of a biomarker for individualized assessment of sleepiness-related deficits in neurobehavioral alertness, with salivary alpha-amylase (sAA) recently reported as a potential biomarker during acute total sleep deprivation. The present study extends on previous research by investigating the association between sAA and neurobehavioral alertness during simulated night-shift work, during individuals are required to work at night when biological processes are strongly promoting sleep and sleep during the day when endogenous processes are promoting wakefulness. In a laboratory-controlled environment, 10 healthy non-shift working males aged 24.7 ±â€¯5.3 years (mean ±â€¯SD) underwent four consecutive nights of simulated night-shift work. Between 17:30-04:30 h participants provided saliva samples and completed a 3 min psychomotor vigilance test (PVT-B), 40 min simulated driving task, and 3 min digit symbol substitution test (DSST). Higher sAA levels were associated with faster response speed on the PVT-B, reduced lane variability on the simulated driving task, and improved information processing speed on the DSST during the first night-shift. There were no associations between sAA levels and performance outcomes during subsequent night-shifts. Findings indicate that the usability of sAA to assess the risk of neurobehavioral deficits during shift-work operations is limited. However, the robust circadian rhythm exhibited by sAA during the protocol of circadian misalignment suggests that sAA could serve as a potential circadian marker.

Synchronized drowsiness monitoring and simulated driving performance data under 50-hr sleep deprivation: A double-blind placebo-controlled caffeine intervention.

This paper presents the 60-s time-resolution segment from our 50-h total sleep deprivation (TSD) dataset (Aidman et al., 2018) [1] that captures minute-by-minute dynamics of driving performance (lane keeping and speed variability) along with objective, oculography-derived drowsiness estimates synchronised to the same 1-min driving epochs. Eleven participants (5 females, aged 18-28) were randomised into caffeine (administered in four 200 mg doses via chewing gum in the early morning hours) or placebo groups. Every three hours they performed a 40 min simulated drive in a medium fidelity driving simulator, while their drowsiness was continuously measured with a spectacle frame-mounted infra-red alertness monitoring system. The dataset covers 15 driving periods of 40 min each, and thus contains over 600 data points of paired data per participant. The 1-min time resolution enables detailed time-series analyses of both time-since-wake and time-on-task performance dynamics and associated drowsiness levels. It also enables direct examination of the relationships between drowsiness and task performance measures. The question of how these relationships might change under various intervention conditions (caffeine in our case) seems worth further investigation.

Direct detection of illicit drugs from biological fluids by desorption/ionization mass spectrometry with nanoporous silicon microparticles.

Surface-assisted laser desorption/ionization mass spectrometry (SALDI-MS) is a high throughput analytical technique capable of detecting low molecular weight analytes, including illicit drugs, and with potential applications in forensic toxicology as well as athlete and workplace testing, particularly for biological fluids (oral fluids, urine and blood). However, successful detection of illicit drugs using SALDI-MS often requires extraction steps to reduce the inherent complexity of biological fluids. Here, we demonstrate an all-in-one extraction and analytical system consisting of hydrophobically functionalized porous silicon microparticles (pSi-MPs) for affinity SALDI-MS of prescription and illicit drugs. This novel approach allows for the analysis of drugs from multiple biological fluids without sample preparation protocols. The effect of pSi-MP size, pore diameter, pore depth and functionalization on analytical performance is investigated. pSi-MPs were optimized for the rapid and high sensitivity detection of methadone, cocaine and 3,4-methylenedioxymethamphetamine (MDMA). This optimized system allowed extraction and detection of methadone from spiked saliva and clinical urine samples. Furthermore, by detecting oxycodone in additional clinical saliva and plasma samples, we were able to demonstrate the versatility of the pSi-MP SALDI-MS technique.