Neurologic Symptoms in Licensed Private Pesticide Applicators in the Agricultural Health Study

Exposure to high levels of many pesticides has both acute and long-term neurologic consequences, but little is known about the neurotoxicity of chronic exposure to moderate levels of pesticides. We analyzed cross-sectional data from 18,782 white male licensed private pesticide applicators enrolled in the Agricultural Health Study in 1993–1997. Applicators provided information on lifetime pesticide use and 23 neurologic symptoms typically associated with pesticide intoxication. An indicator of more symptoms (≥10 vs. < 10) during the year before enrollment was associated with cumulative lifetime days of insecticide use: odds ratios (95% confidence intervals) were 1.64 (1.36–1.97) for 1–50 days, 1.89 (1.58–2.25) for 51–500 days, and 2.50 (2.00–3.13) for > 500 days, compared with never users. A modest association for fumigants [> 50 days, 1.50 (1.24–1.81)] and weaker relationships for herbicides [> 500 days, 1.32 (0.99–1.75)] and fungicides [> 50 days, 1.23 (1.00–1.50)] were observed. Pesticide use within the year before enrollment was not associated with symptom count. Only associations with insecticides and fumigants persisted when all four pesticide groups were examined simultaneously. Among chemical classes of insecticides, associations were strongest for organophosphates and organochlorines. Associations with cumulative exposure persisted after excluding individuals who had a history of pesticide poisoning or had experienced an event involving high personal pesticide exposure. These results suggest that self-reported neurologic symptoms are associated with cumulative exposure to moderate levels of fumigants and organophosphate and organochlorine insecticides, regardless of recent exposure or history of poisoning

Studying Health Outcomes in Farmworker Populations Exposed to Pesticides

A major goal of studying farmworkers is to better understand how their work environment, including exposure to pesticides, affects their health. Although a number of health conditions have been associated with pesticide exposure, clear linkages have yet to be made between exposure and health effects except in cases of acute pesticide exposure. In this article, we review the most common health end points that have been studied and describe the epidemiologic challenges encountered in studying these health effects of pesticides among farmworkers, including the difficulties in accessing the population and challenges associated with obtaining health end point data. The assessment of neurobehavioral health effects serves as one of the most common and best examples of an approach used to study health outcomes in farmworkers and other populations exposed to pesticides. We review the current limitations in neurobehavioral assessment and strategies to improve these analytical methods. Emerging techniques to improve our assessment of health effects associated with pesticide exposure are reviewed. These techniques, which in most cases have not been applied to farmworker populations, hold promise in our ability to study and understand the relationship between pesticide exposure and a variety of health effects in this population

Urinary biomarker concentrations of captan, chlormequat, chlorpyrifos and cypermethrin in UK adults and children living near agricultural land

There is limited information on the exposure to pesticides experienced by UK residents living near agricultural land. This study aimed to investigate their pesticide exposure in relation to spray events. Farmers treating crops with captan, chlormequat, chlorpyrifos or cypermethrin provided spray event information. Adults and children residing ≤100 m from sprayed fields provided first-morning void urine samples during and outwith the spray season. Selected samples (1–2 days after a spray event and at other times (background samples)) were analysed and creatinine adjusted. Generalised Linear Mixed Models were used to investigate if urinary biomarkers of these pesticides were elevated after spray events. The final data set for statistical analysis contained 1518 urine samples from 140 participants, consisting of 523 spray event and 995 background samples which were analysed for pesticide urinary biomarkers. For captan and cypermethrin, the proportion of values below the limit of detection was greater than 80%, with no difference between spray event and background samples. For chlormequat and chlorpyrifos, the geometric mean urinary biomarker concentrations following spray events were 15.4 μg/g creatinine and 2.5 μg/g creatinine, respectively, compared with 16.5 μg/g creatinine and 3.0 μg/g creatinine for background samples within the spraying season. Outwith the spraying season, concentrations for chlorpyrifos were the same as those within spraying season backgrounds, but for chlormequat, lower concentrations were observed outwith the spraying season (12.3 μg/g creatinine). Overall, we observed no evidence indicative of additional urinary pesticide biomarker excretion as a result of spray events, suggesting that sources other than local spraying are responsible for the relatively low urinary pesticide biomarkers detected in the study population

Stochastic Theory of Relativistic Particles Moving in a Quantum Field: II. Scalar Abraham-Lorentz-Dirac-Langevin Equation, Radiation Reaction and Vacuum Fluctuations

We apply the open systems concept and the influence functional formalism introduced in Paper I to establish a stochastic theory of relativistic moving spinless particles in a quantum scalar field. The stochastic regime resting between the quantum and semi-classical captures the statistical mechanical attributes of the full theory. Applying the particle-centric world-line quantization formulation to the quantum field theory of scalar QED we derive a time-dependent (scalar) Abraham-Lorentz-Dirac (ALD) equation and show that it is the correct semiclassical limit for nonlinear particle-field systems without the need of making the dipole or non-relativistic approximations. Progressing to the stochastic regime, we derive multiparticle ALD-Langevin equations for nonlinearly coupled particle-field systems. With these equations we show how to address time-dependent dissipation/noise/renormalization in the semiclassical and stochastic limits of QED. We clarify the the relation of radiation reaction, quantum dissipation and vacuum fluctuations and the role that initial conditions may play in producing non-Lorentz invariant noise. We emphasize the fundamental role of decoherence in reaching the semiclassical limit, which also suggests the correct way to think about the issues of runaway solutions and preacceleration from the presence of third derivative terms in the ALD equation. We show that the semiclassical self-consistent solutions obtained in this way are ``paradox'' and pathology free both technically and conceptually. This self-consistent treatment serves as a new platform for investigations into problems related to relativistic moving charges.Comment: RevTex; 20 pages, 3 figures, Replaced version has corrected typos, slightly modified derivation, improved discussion including new section with comparisons to related work, and expanded reference

Intense Synaptic Activity Enhances Temporal Resolution in Spinal Motoneurons

In neurons, spike timing is determined by integration of synaptic potentials in delicate concert with intrinsic properties. Although the integration time is functionally crucial, it remains elusive during network activity. While mechanisms of rapid processing are well documented in sensory systems, agility in motor systems has received little attention. Here we analyze how intense synaptic activity affects integration time in spinal motoneurons during functional motor activity and report a 10-fold decrease. As a result, action potentials can only be predicted from the membrane potential within 10 ms of their occurrence and detected for less than 10 ms after their occurrence. Being shorter than the average inter-spike interval, the AHP has little effect on integration time and spike timing, which instead is entirely determined by fluctuations in membrane potential caused by the barrage of inhibitory and excitatory synaptic activity. By shortening the effective integration time, this intense synaptic input may serve to facilitate the generation of rapid changes in movements

Mouse models of neurodegenerative disease: preclinical imaging and neurovascular component.

Neurodegenerative diseases represent great challenges for basic science and clinical medicine because of their prevalence, pathologies, lack of mechanism-based treatments, and impacts on individuals. Translational research might contribute to the study of neurodegenerative diseases. The mouse has become a key model for studying disease mechanisms that might recapitulate in part some aspects of the corresponding human diseases. Neurode- generative disorders are very complicated and multifacto- rial. This has to be taken in account when testing drugs. Most of the drugs screening in mice are very di cult to be interpretated and often useless. Mouse models could be condiderated a ‘pathway models’, rather than as models for the whole complicated construct that makes a human disease. Non-invasive in vivo imaging in mice has gained increasing interest in preclinical research in the last years thanks to the availability of high-resolution single-photon emission computed tomography (SPECT), positron emission tomography (PET), high eld Magnetic resonance, Optical Imaging scanners and of highly speci c contrast agents. Behavioral test are useful tool to characterize di erent ani- mal models of neurodegenerative pathology. Furthermore, many authors have observed vascular pathological features associated to the di erent neurodegenerative disorders. Aim of this review is to focus on the di erent existing animal models of neurodegenerative disorders, describe behavioral tests and preclinical imaging techniques used for diagnose and describe the vascular pathological features associated to these diseases

Studying neuroanatomy using MRI

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging, and disease. Developments in MRI acquisition, image processing, and data modelling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and inferring microstructural properties; we also describe key artefacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, though methods need to improve and caution is required in its interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works