There are functional inter-relationships between the beta cells of the endocrine pancreas and the pineal gland, where the synchronizing circadian molecule melatonin originates. The aim of this study was to elucidate a putative interaction between insulin and melatonin in diabetic patients and a diabetic rat model. We analyzed glucose, insulin, and melatonin levels of type 2 patients, as well as type 2 diabetic Goto Kakizaki (GK) rats by radioimmunoassay. Expression of pancreatic melatonin and pineal insulin receptors, as well as arylalkylamine-N-acetyltransferase (AANAT), was determined by real-time reverse transcriptase polymerase chain reaction (RT-PCR). The AANAT enzyme activity was measured in pineal homogenates. Diabetic patients showed a decrease in melatonin levels, while in the pancreas of GK rats an upregulation of the melatonin-receptor mRNA was determined. The pancreatic islets of GK rats showed expression of the mRNA for the pancreatic melatonin (MT1) receptor, which had previously been identified in rats and insulinoma (INS1) cells. Besides their presence in animal cells, the MT1-receptor transcript was also detected in human pancreas by RT-PCR. Whereas the rat pancreatic mRNA expression of the MT1-receptor was significantly increased, the activity of the pineal AANAT enzyme was reduced. The latter observation was in accordance with plasma melatonin levels. The insulin-receptor mRNA of the pineal gland was found to be reduced in GK rats. Our observations suggest a functional inter-relationship between melatonin and insulin, and may indicate a reduction of melatonin in the genesis of diabetes.

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Objective. Because of the increasing shortage of general practitioners (GPs) in many countries, this study aimed to explore factors related to GP career choice in recent medical graduates. Particular focus was placed on the impact of specific practice-orientated GP courses at different stages of the medical undergraduate curriculum. Design. Observational study. Multivariable binary logistic regression was used to reveal independent associations with career choice. Setting. Leipzig Medical School, Germany. Subjects. 659 graduates (response rate = 64.2%). Main outcome measure. Choice of general practice as a career. Results. Six student-associated variables were found to be independently related to choice of general practice as a career: age, having family or friends in general practice, consideration of a GP career at matriculation, preference for subsequent work in a rural or small-town area, valuing the ability to see a broad spectrum of patients, and valuing long-term doctor–patient relationships. Regarding the curriculum, after adjustment independent associations were found with a specific pre-clinical GP elective (OR = 2.6, 95% CI 1.3–5.3), a four-week GP clerkship during the clinical study section (OR = 2.6, 95% CI 1.3–5.0), and a four-month GP clinical rotation during the final year (OR = 10.7, 95% CI 4.3–26.7). It was also found that the work-related values of the female participants were more compatible with those of physicians who opt for a GP career than was the case for their male colleagues. Conclusion. These results support the suggestion that a practice-orientated GP curriculum in both the earlier and later stages of undergraduate medical education raises medical schools’ output of future GPs. The findings are of interest for medical schools (curriculum design, admission criteria), policy-makers, and GPs involved in undergraduate medical education. More research is needed on the effectiveness of specific educational interventions in promoting interest in general practice as a career.

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We quantitatively compare filtered backprojection (FBP), expectation-maximization (EM), and Bayesian reconstruction algorithms as applied to the IndyPET scanner--a dedicated research scanner which has been developed for small and intermediate field of view imaging applications. In contrast to previous approaches that rely on Monte Carlo simulations, a key feature of our investigation is the use of an empirical system kernel determined from scans of line source phantoms. This kernel is incorporated into the forward model of the EM and Bayesian algorithms to achieve resolution recovery. Three data sets are used, data collected on the IndyPET scanner using a bar phantom and a Hoffman three-dimensional brain phantom, and simulated data containing a hot lesion added to a uniform background. Reconstruction quality is analyzed quantitatively in terms of bias-variance measures (bar phantom) and mean square error (lesion phantom). We observe that without use of the empirical system kernel, the FBP, EM, and Bayesian algorithms give similar performance. However, with the inclusion of the empirical kernel, the iterative algorithms provide superior reconstructions compared with FBP, both in terms of visual quality and quantitative measures. Furthermore, Bayesian methods outperform EM. We conclude that significant improvements in reconstruction quality can be realized by combining accurate models of the system response with Bayesian reconstruction algorithms.

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The ICD-10 is reliable for coding managed problems on the chapter level. Further refinement of ICD-10 with three- and four-digit codes leads to significant coding uncertainties. There is no reliable coding scheme that meets the demands of general practice. The use of coded data for healthcare reimbursement requires a simplification of ICD-10 to provide a realistic picture of morbidity.