Classification Criteria for Intermediate Uveitis, Non–Pars Planitis Type

Purpose: To determine classification criteria for intermediate uveitis, non-pars planitis type (IU- NPP, also known as undifferentiated intermediate uveitis) / Design: Machine learning of cases with IU-NPP and 4 other intermediate uveitides. / Methods: Cases of intermediate uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the intermediate uveitides. The resulting criteria were evaluated on the validation set. / Results: Five hundred eighty-nine of cases of intermediate uveitides, including 114 cases of IU-NPP, were evaluated by machine learning. The overall accuracy for intermediate uveitides was 99.8% in the training set and 99.3% in the validation set (95% confidence interval 96.1, 99.9). Key criteria for IU-NPP included unilateral or bilateral intermediate uveitis with neither 1) snowballs in the vitreous nor 2) snowbanks on the pars plana. Other key exclusions included: 1) multiple sclerosis, 2) sarcoidosis, and 3) syphilis. The misclassification rates for pars planitis were 0 % in the training set and 0% in the validation set, respectively. / Conclusions: The criteria for IU-NPP had a low misclassification rate and appeared to perform well enough for use in clinical and translational research

Classification Criteria for Multiple Sclerosis-Associated Intermediate Uveitis

PURPOSE: The purpose of this study was to determine classification criteria for multiple sclerosis-associated intermediate uveitis. DESIGN: Machine learning of cases with multiple sclerosis-associated intermediate uveitis and 4 other intermediate uveitides. METHODS: Cases of intermediate uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used in the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the intermediate uveitides. The resulting criteria were evaluated in the validation set. RESULTS: A total of 589 cases of intermediate uveitides, including 112 cases of multiple sclerosis-associated intermediate uveitis, were evaluated by machine learning. The overall accuracy for intermediate uveitides was 99.8% in the training set and 99.3% in the validation set (95% confidence interval: 96.1-99.9). Key criteria for multiple sclerosis-associated intermediate uveitis included unilateral or bilateral intermediate uveitis and multiple sclerosis diagnosed by the McDonald criteria. Key exclusions included syphilis and sarcoidosis. The misclassification rates for multiple sclerosis-associated intermediate uveitis were 0 % in the training set and 0% in the validation set. CONCLUSIONS: The criteria for multiple sclerosis-associated intermediate uveitis had a low misclassification rate and appeared to perform sufficiently well enough for use in clinical and translational research

Transcranial sonography for diagnosis of Parkinson's disease

<p>Abstract</p> <p>Background</p> <p>In idiopathic Parkinson's disease (IPD) transcranial sonography (TCS) represents an alternative diagnostic method to verify clinical diagnosis. Although the phenomenon of an increased echogenicity of the Substantia nigra (SN) is well known this method is still not widly used in the diagnostic workup. Until now reliability of this method is still a matter of debate, partly because data only existed from a few laboratories using the same ultrasound machine. Therefore our study was conducted to test the reliability of this method by using a different ultrasound device and examining a large population of control and IPD subjects by two examiners to calculate interobserver reliability.</p> <p>Method</p> <p>In this study echogenicity of SN was examined in 199 IPD patients and 201 control subjects. All individuals underwent a neurological assessment including Perdue pegboard test and Webster gait test. Using a Sonos 5500 ultrasound device area of SN was measured, echogenicity of raphe, red nuclei, thalamus, caudate and lenticular nuclei, width of third and lateral ventricle were documented.</p> <p>Results</p> <p>We found a highly characteristic enlargement of the SN echogenic signal in IPD. The cut-off value for the SN area was established using a ROC curve with a sensitivity of 95% corresponding to an area of SN of 0.2 cm²and was found to be equivalent to the cut-off values of other studies using different ultrasound devices.</p> <p>Conclusions</p> <p>Our study shows that TCS is a reliable and highly sensitive tool for differentiation of IPD patients from individuals without CNS disorders.</p

Ameloblastin Inhibits Cranial Suture Closure by Modulating Msx2 Expression and Proliferation

Deformities of cranial sutures such as craniosynostosis and enlarged parietal foramina greatly impact human development and quality of life. Here we have examined the role of the extracellular matrix protein ameloblastin (Ambn), a recent addition to the family of non-collagenous extracellular bone matrix proteins, in craniofacial bone development and suture formation. Using RT-PCR, western blot and immunohistochemistry, Ambn was localized in mouse calvarial bone and adjacent condensed mesenchyme. Five-fold Ambn overexpression in a K14-driven transgenic mouse model resulted in delayed posterior frontal suture fusion and incomplete suture closure. Moreover, Ambn overexpressor skulls weighed 13.2% less, their interfrontal bones were 35.3% thinner, and the width between frontal bones plus interfrontal suture was 14.3% wider. Ambn overexpressing mice also featured reduced cell proliferation in suture blastemas and in mesenchymal cells from posterior frontal sutures. There was a more than 2-fold reduction of Msx2 in Ambn overexpressing calvariae and suture mesenchymal cells, and this effect was inversely proportionate to the level of Ambn overexpression in different cell lines. The reduction of Msx2 expression as a result of Ambn overexpression was further enhanced in the presence of the MEK/ERK pathway inhibitor O126. Finally, Ambn overexpression significantly reduced Msx2 down-stream target gene expression levels, including osteogenic transcription factors Runx2 and Osx, the bone matrix proteins Ibsp, ColI, Ocn and Opn, and the cell cycle-related gene CcnD1. Together, these data suggest that Ambn plays a crucial role in the regulation of cranial bone growth and suture closure via Msx 2 suppression and proliferation inhibition