SUMMARYPurpose: To examine the risk of undergoing an epileptic seizure as a function of differing levels of occupational stress (physical and mental) in new military recruits with no previous history of epilepsy or with epilepsy in remission for over 2 years. Methods: The medical records of over 300,000 18-year-old men recruited to the Israeli army between mid-eighties and mid-nineties were used to assemble a cohort, which was followed for a period of 30 months. The severity of epilepsy at recruitment was determined according to four categories, 0 (no history of seizures) and 1-3 (history of seizures with different relapse-free periods, with or without treatment). The soldiers were subdivided according to their occupational categories to: combat units (CU), maintenance units (MU), and administrative units (AU). The prevalence of epilepsy is 0.5-1% worldwide, with the highest incidence occurring in early childhood and late adulthood (Hauser et al., 1991). Studies on the risk for recurrent seizures show that between 27% and 81% of patients will suffer a second seizure within 3-5 years (Shinnar et al Results

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The restriction rate achieved by medical examinations either done by an OP (Group A) or by a GP (Group B) was the same as in OHQ (Group C). The use of a self-administered questionnaire evaluated by an OP is the preferred method of pre-employment evaluation for non-hazardous occupations.

Every menstrual cycle, many follicles begin to develop but only a specific number ovulate. This ovulation number determines how many offspring are produced per litter, and differs between species. The physiological mechanism that controls ovulation number is unknown; a class of mathematical models can explain it, but these models have no physiological basis. Here, we suggest a physiological mechanism for ovulation number control, which enables selection of a specific number of follicles out of many, and analyze it in a mathematical model of follicular growth. The mechanism is based on a signal, intra-follicular androgen concentration, that measures follicle size relative to the other follicles. This signal has a biphasic effect, suppressing follicles that are too large or too small compared to others. The ovulation number is determined by the androgen inhibitory thresholds. The model has a scaling symmetry that explains why the dominant follicles grow linearly with time, as observed in human ultrasound data. This approach also explains how chronic hyperandrogenism disrupts ovulation in polycystic ovary syndrome (PCOS), a leading cause of infertility. We propose specific experiments for testing the proposed mechanism.