Retinal neurons: cell types and coupled networks

Retinal neurons with distinct dendritic morphologies are likely to comprise different cell types, subject to three important caveats. First, it is necessary to avoid creating “artificial” cell types based on arbitrary criteria—for example, the presence of two or three primary dendrites. Second, it is essential to take into account changes in morphology with retinal eccentricity and cell density. Third, the retina contains imperfections like any natural system and a significant number of retinal neurons display aberrant morphologies or make aberrant connections that are not typical of the population as a whole. Many types of retinal ganglion cells show diverse patterns of tracer coupling, with the simplest pattern represented by the homologous coupling shown by On-Off direction-selective (DS) ganglion cells in the rabbit retina. Neighboring DS ganglion cells with a common preferred direction have regularly spaced somata and territorial dendritic fields, whereas DS ganglion cells with different preferred directions may have closely spaced somata and overlapping dendritic fields.

Simplified criteria for the diagnosis of autoimmune hepatitis

Diagnosis of autoimmune hepatitis (AIH) may be challenging. However, early diagnosis is important because immunosuppression is life-saving. Diagnostic criteria of the International Autoimmune Hepatitis Group (IAIHG) were complex and purely meant for scientific purposes. This study of the IAIHG aims to define simplified diagnostic criteria for routine clinical practice. Candidate criteria included sex, age, autoantibodies, immunoglobutins, absence of viral hepatitis, and histology. The training set included 250 AIH patients and 193 controls from 11 centers worldwide. Scores were built from variables showing predictive ability in univariate analysis. Diagnostic value of each score was assessed by the area under the receiver operating characteristic (ROC) curve. The best score was validated using data of an additional 109 AIH patients and 284 controls. This score included autoantibodies, immunoglobulin G, histology, and exclusion of viral hepatitis. The area under the curve for prediction of AIH was 0.946 in the training set and 0.91 in the validation set. Based on the ROC curves, two cutoff points were chosen. The score was found to have 88% sensitivity and 97% specificity (cutoff >= 6) and 81% sensitivity and 99% specificity (cutoff 2:7) in the validation set. Conclusion: A reliable diagnosis of AIH can be made using a very simple diagnostic score. We propose the diagnosis of probable AIH at a cutoff point greater than 6 points and definite AIH 7 points or higher.