Determination of Δ9-tetrahydrocannabinolic acid A (Δ9-THCA-A) in whole blood and plasma by LC–MS/MS and application in authentic samples from drivers suspected of driving under the influence of cannabis

Delta-9-tetrahydrocannabinolic acid A (THCA-A) is the biosynthetic precursor of delta-9-tetrahydrocannabinol (THC) in cannabis plants, and has no psychotropic effects. THCA-A can be detected in blood and urine, and several metabolites have been identified. THCA-A was also shown to be incorporated in hair by side stream smoke to a minor extent, but incorporation via blood stream or sweat seems unlikely. The detection of THCA-A in biological fluids may serve as a marker for differentiating between the intake of prescribed THC medication – containing only pure THC – and cannabis products containing THC besides THC-acid A and other cannabinoids. However, the knowledge about its usefulness in forensic cases is very limited. The aim of the present work was the development of a reliable method for THCA-A determination in human blood or plasma using LC–MS/MS and application to cases of driving under the influence of drugs. Fifty eight (58) authentic whole blood and the respective plasma samples were collected from drivers suspected of driving under the influence of cannabis from the region of Bern (Switzerland). Samples were first tested for THC, 11-OH-THC and THC-COOH, and then additionally for THCA-A. For this purpose, the existing LC–MS/MS method was modified and validated, and found to be selective and linear over a range of 1.0 to 200 ng/mL (the correlation coefficients were above 0.9980 in all validation runs). Limit of detection (LOD) and limit of quantification (LOQ) were 0.3 ng/mL and 1.0 ng/mL respectively. Intra- and inter-assay accuracy were equal or better than 90% and intra- and inter-assay precision were equal or better than 11.1%. The mean extraction efficiencies were satisfactory being equal or higher than 85.4%. THCA-A was stable in whole blood samples after 3 freeze/thaw cycles and storage at 4 °C for 7 days. Re-injection (autosampler) stability was also satisfactory. THC was present in all blood samples with levels ranging from 0.7 to 51 ng/mL. THCA-A concentrations ranged from 1.0 to 496 ng/mL in blood samples and from 1.4 to 824 ng/mL in plasma samples. The plasma:blood partition coefficient had a mean value of 1.7 (±0.21, SD). No correlation was found between the degree of intoxication or impairment stated in the police protocols or reports of medical examinations and the detected THCA-A-concentration in blood.

Consensus statement of the European Heart Rhythm Association: updated recommendations for driving by patients with implantable cardioverter defibrillators

Patients with an implantable cardioverter defibrillator (ICD) have an ongoing risk of sudden incapacitation that might cause harm to others while driving a car. Driving restrictions vary across different countries in Europe. The most recent recommendations for driving of ICD patients in Europe were published in 1997 and focused mainly on patients implanted for secondary prevention. In recent years there has been a vast increase in the number of patients with an ICD and in the percentage of patients implanted for primary prevention. The EHRA task force on ICD and driving was formed to reassess the risk of driving for ICD patients based on the literature available. The recommendations are summarized in the following table and are further explained in the document, (Table see text). Driving restrictions are perceived as difficult for patients and their families, and have an immediate consequence for their lifestyle. To increase the adherence to the driving restrictions, adequate discharge of education and follow-up of patients and family are pivotal. The task force members hope this document may serve as an instrument for European and national regulatory authorities to formulate uniform driving regulations.

Cognition and driving in older persons

In Switzerland, approximately 350,000 people aged 70 years or older own a valid driving license. By law, these drivers are medically assessed every other year, most commonly by their general practitioner, to exclude that a medical condition is interfering with their driving skills. A prerequisite for driving is the integration of high-level cognitive functions with perception and motor function. Ageing, per se, does not necessarily impair driving or increase the crash risk. However, medical conditions, such as cognitive impairment and dementia, become more prevalent with advancing age and may contribute to poor driving and an increased crash risk. The extent to which driving skills are impaired depends on the cause of dementia, disease severity, other co-morbidities and individual compensation strategies. Dementia often remains undiagnosed and therefore general practitioners (GPs) can find themselves in the difficult situation to disclose a suspicion about cognitive impairment and queries about medical fitness to drive, at the same time. In addition, the literature suggests that cognitive screening tests, most commonly used by GPs, have a limited role in judging whether an older person remains fit to drive. Further specialist assessment, for example in a memory clinic or on the road testing (ORT), may be helpful when the diagnosis or its implication for driving remain unclear. Here, we review the literature about cognition and driving, for GPs who advise older drivers who wish to continue driving.

[Driving ability and daytime sleepiness]

Daytime sleepiness is a complaint of about 5-10% in a normal population. The consequences, such as impaired performance and accidents at the workplace and while driving, have major impact on the affected and on society. According to Swiss federal statistics only 1-3% of all motor vehicle accidents are due to excessive daytime sleepiness, which is in great contrast to a figure of 10 to 20% of all accidents derived from scientific studies. Due to the inadequate statistical representation of the problem, insufficient countermeasures have been realized, and the state of drivers breaching traffic regulations is not adequately investigated in this respect. The most prevalent cause of microsleep induced accidents is certainly lack of sleep due to social or professional reasons. A treating physician must also consider sedating drugs and various diseases. The typical characteristics of accidents due to falling asleep at the wheel and the risk factors involved are well established, so that informing the general public, taking prophylactic countermeasures and a targeted investigation in this respect of drivers who have breached the law are all feasible. Since symptoms of sleepiness can be recognized well before any impairment of performance occurs, the most important countermeasure is information of the drivers on the risk factors and on efficient countermeasures against sleepiness at the wheel. Besides correct diagnosis and treatment, the primary goal of physicians treating patients with pathological daytime sleepiness is to inform them at an early stage about the risks of sleepiness and the large responsibility they bear while driving. This information should be written down in the patients' records. Professional drivers suffering from daytime sleepiness, drivers who have already had an accident due to microsleep and unreasonable drivers should be referred to a centre of sleep disorders for objective measurements of sleepiness.

Spike-triggered reaction-time EEG as a possible assessment tool for driving ability

The impact of interictal epileptic activity (IEA) on driving is a rarely investigated issue. We analyzed the impact of IEA on reaction time in a pilot study. Reactions to simple visual stimuli (light flash) in the Flash test or complex visual stimuli (obstacle on a road) in a modified car driving computer game, the Steer Clear, were measured during IEA bursts and unremarkable electroencephalography (EEG) periods. Individual epilepsy patients showed slower reaction times (RTs) during generalized IEA compared to RTs during unremarkable EEG periods. RT differences were approximately 300 ms (p < 0.001) in the Flash test and approximately 200 ms (p < 0.001) in the Steer Clear. Prior work suggested that RT differences >100 ms may become clinically relevant. This occurred in 40% of patients in the Flash test and in up to 50% in the Steer Clear. When RT were pooled, mean RT differences were 157 ms in the Flash test (p < 0.0001) and 116 ms in the Steer Clear (p < 0.0001). Generalized IEA of short duration seems to impair brain function, that is, the ability to react. The reaction-time EEG could be used routinely to assess driving ability.

Is gamma band EEG synchronization reduced during auditory driving in schizophrenia patients with auditory verbal hallucinations?

Auditory verbal hallucinations (AVH) in schizophrenia patients assumingly result from a state inadequate activation of the primary auditory system. We tested brain responsiveness to auditory stimulation in healthy controls (n=26), and in schizophrenia patients that frequently (n=18) or never (n=11) experienced AVH. Responsiveness was assessed by driving the EEG with click-tones at 20, 30 and 40Hz. We compared stimulus induced EEG changes between groups using spectral amplitude maps and a global measure of phase-locking (GFS). As expected, the 40Hz stimulation elicited the strongest changes. However, while controls and non-hallucinators increased 40Hz EEG activity during stimulation, a left-lateralized decrease was observed in the hallucinators. These differences were significant (p=.02). As expected, GFS increased during stimulation in controls (p=.08) and non-hallucinating patients (p=.06), which was significant when combining the two groups (p=.01). In contrast, GFS decreased with stimulation in hallucinating patients (p=0.13), resulting in a significantly different GFS response when comparing subjects with and without AVH (p<.01). Our data suggests that normally, 40Hz stimulation leads to the activation of a synchronized network representing the sensory input, but in hallucinating patients, the same stimulation partly disrupts ongoing activity in this network.

Will International Pursuit of the Millenium Development Goals Alleviate Poverty in Mountains?

Since September 2000, when world leaders agreed on time-bound, measurable goals to reduce extreme poverty, hunger, illiteracy, and disease while fostering gender equality and ensuring environmental sustainability, the Millennium Development Goals (MDGs) have increasingly come to dominate the policy objectives of many states and development agencies. The concern has been raised that the tight timeframe and financial restrictions might force governments to invest in the more productive sectors, thus compromising the quality and sustainability of development efforts. In the long term, this may lead to even greater inequality, especially between geographical regions and social strata. Hence people living in marginal areas, for example in remote mountain regions, and minority peoples risk being disadvantaged by this internationally agreed agenda. Strategies to overcome hunger and poverty in their different dimensions in mountain areas need to focus on strengthening the economy of small-scale farmers, while also fostering the sustainable use of natural resources, taking into consideration their multifunctionality.

From EEG dependency multichannel matching pursuit to sparse topographic EEG decomposition

In this work, we present a multichannel EEG decomposition model based on an adaptive topographic time-frequency approximation technique. It is an extension of the Matching Pursuit algorithm and called dependency multichannel matching pursuit (DMMP). It takes the physiologically explainable and statistically observable topographic dependencies between the channels into account, namely the spatial smoothness of neighboring electrodes that is implied by the electric leadfield. DMMP decomposes a multichannel signal as a weighted sum of atoms from a given dictionary where the single channels are represented from exactly the same subset of a complete dictionary. The decomposition is illustrated on topographical EEG data during different physiological conditions using a complete Gabor dictionary. Further the extension of the single-channel time-frequency distribution to a multichannel time-frequency distribution is given. This can be used for the visualization of the decomposition structure of multichannel EEG. A clustering procedure applied to the topographies, the vectors of the corresponding contribution of an atom to the signal in each channel produced by DMMP, leads to an extremely sparse topographic decomposition of the EEG.