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Endometrial hyperplasia is a common clinical problem that all gynecologists will encounter in their practice. By de nition, endometrial hyperplasia is an abnormal proliferation of both the glandular and stromal elements of the endometrium, with the glandular component being the most prominent.1, 2 In addition to causing abnormal uterine bleeding, endometrial hyperplasia can predispose a woman to developing endometrioid adenocarcinoma. It is for this reason that hyperplasia warrants proper evaluation and management. Endometrial hyperplasia classi cation is based on two main histologic descriptions: architectural and cytologic. Architectural appearance refers to the amount of glandular crowding, and is classi ed as simple or complex.2 The presence or absence of cellular atypia is the most important prognostic factor in a woman with endometrial hyperplasia and will most often determine the treatment. It should be understood that only those patients with cytologic atypia are at signi cant risk of developing endometrial cancer.1, 3

Thus this criterion takes into account both the statistical goodness of fit and the number of parameters that have to be estimated to achieve this particular degree of fit, by imposing a penalty for increasing the number of parameters [Everitt 2006] For learning graphical models it can be defined as IC (G, | D) = 2 ln P(D | G, ) + | |, where D is the database of sample cases, G is the (directed or undirected) graph underlying the model, is the set of probability parameters associated with this graph, and | | is the number of parameters P(D | G, ) is the likelihood of the database given the (probabilistic) graphical model that is described by G and (How this probability can be computed was discussed for a Bayesian network in Section 712.

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The identi cation of leptin arose from examination of two obese mutant mice, ob/ob (Coleman, 1973) and db/db (Chua et al., 1996). Although originally described over 30 years ago, the nature of their defect was unclear until 1995 when the ob gene product was identi ed as leptin (Zhang et al., 1994). Leptin is a 16 kDa, 146 amino acid protein that is expressed and secreted from adipose tissue in most mammals, including humans. Circulating leptin concentrations are directly proportional to fat mass in both animals and man (Considine et al., 1996). The leptin receptor gene encodes a single transmembrane receptor belonging to the class I cytokine receptor family (Tartaglia et al., 1995). Subsequent work revealed multiple variants of OB-R with variable C-terminal portions. The functioning form appears to have both a large extracellular domain and a long intracellular region, in contrast to the shorter intracellular domains of the non-functioning receptors. In the hypothalamus, the long, functioning leptin receptor predominates and is found in areas important in the regulation of

) It is clear that for = 0 we get a measure that is equivalent to a maximum likelihood approach to model selection However, pure maximum likelihood is usually a bad choice, because it does not take care of the number of parameters..

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The EEG is not a test for epilepsy. In the appropriate clinical setting (i.e. a patient with a history suggestive of epilepsy) it may provide additional support for the diagnosis and help in distinguishing between the generalized and focal types of epilepsy. But remember: 10% of the normal population show mild, non-speci c EEG abnormalities, such as slow waves in one or both temporal regions; 30% of patients with epilepsy will have a normal EEG between their attacks (falling to 20% if the EEG includes a period of sleep). In other words, the EEG can mislead through both false positives and false negatives, and must be requested and interpreted with care. Prolonged ambulatory EEG recording (an immensely laborious activity) can be useful in very dif cult cases with frequent attacks, allowing the EEG to be sampled during the attack itself. But even here there is a false-negative problem, with 10% of focal seizures arising deep in a fold of the cerebral cortex and failing to give rise to abnormal discharges on the EEG. Imaging of the brain, preferably with MR rather than CT scanning, is an important part of the assessment of focal epilepsy, and in cases where the type of epilepsy is uncertain. It is probably unnecessary in patients with primary generalized epilepsy con rmed by EEG. The other routine tests (glucose, calcium, ECG) are very rarely informative.

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