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Background: Extracellular matrix molecular components, previously linked to multisystem syndromes include collagens, fibrillins and laminins. Recently, we described a novel multisystem syndrome caused by the c.9418G>A p.(V3140M) mutation in the laminin alpha-5 (LAMA5) gene, which affects connective tissues of all organs and apparatus in a three generation family. In the same family, we have also reported a myopic trait, which, however, was linked to the Prolyl 4-hydroxylase subunit alpha-2 (P4HA2) gene. Results of investigation on vitreous changes and their pathogenesis are reported in the present study.Materials and Methods: Nineteen family individuals underwent complete ophthalmic examination including best-corrected visual acuity (BCVA), fundus examination, fundus photography, intraocular pressure measurement, axial length measurement using ocular biometry, Goldmann visual field examination, standard electroretinogram, SD-OCT. Segregation analysis of LAMA5 and P4HA2 mutations was performed in enrolled members.Results: The vitreous alterations fully segregated with LAMA5 mutation in both young and adult family members. Slight reduction of retinal thickness and peripheral retinal degeneration in only two patients were reported.Conclusions: In this work we showed that PVD is a common trait of LAMA5 multisystem syndrome, therefore occurring as an age-unrelated trait. We hypothesize that the p.(V3140M) mutation results in a reduction of retinal inner limiting membrane (ILM) stability, leading to a derangement in the macromolecular structure of the vitreous gel, and PVD. Further investigations will be necessary to elucidate the role of wild type and mutated LAMA5 in the pathogenesis of PVD.  相似文献   
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PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.  相似文献   
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ObjectiveThe objective of this study was to investigate the association between morphological variation and postsurgical pulmonary vein (PV) stenosis (PPVS) in patients with cardiac total anomalous pulmonary venous connection (TAPVC).MethodsThis single-center, retrospective study included 168 pediatric patients who underwent surgical repair of cardiac TAPVC from 2013 to 2019 (connection to the coronary sinus [CS], n = 136; connection directly to the right atrium [RA], n = 32). Three-dimensional computed tomography modeling and geometric analysis were performed to investigate the morphological features; their relevance to the PPVS was examined.ResultsThe connection type had no association with PPVS (CS type: 18% vs right atrial type: 19%; P = .89) but there was a higher incidence of PPVS in patients with a single PV orifice than > 1 orifice (P < .001). Confluence-to-total PV area ratio (hazard ratio, 4.78, 95% CI, 1.86-12.32; P = .001) and length of drainage route (hazard ratio, 1.22; 95% CI, 1.14-1.31; P < .001) had a 4- and 1-fold increase in the risk for PPVS in the CS type after adjustment for age and preoperative pulmonary venous obstruction. In the right atrial type, those with anomalous PV return to the RA roof were more likely to develop PPVS than to the posterior wall of the RA (P < .001).ConclusionsThe number of inter-junction PV orifice correlated with PPVS development in cardiac TAPVC. The confluence-to-total PV ratio, length of drainage route, and anomalous PV return to the RA roof are important predictors for PPVS. Morphological subcategorization in this clinical setting can potentially assist in surgical decision-making.  相似文献   
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A typical time series in functional magnetic resonance imaging (fMRI) exhibits autocorrelation, that is, the samples of the time series are dependent. In addition, temporal filtering, one of the crucial steps in preprocessing of functional magnetic resonance images, induces its own autocorrelation. While performing connectivity analysis in fMRI, the impact of the autocorrelation is largely ignored. Recently, autocorrelation has been addressed by variance correction approaches, which are sensitive to the sampling rate. In this article, we aim to investigate the impact of the sampling rate on the variance correction approaches. Toward this end, we first derived a generalized expression for the variance of the sample Pearson correlation coefficient (SPCC) in terms of the sampling rate and the filter cutoff frequency, in addition to the autocorrelation and cross‐covariance functions of the time series. Through simulations, we illustrated the importance of the variance correction for a fixed sampling rate. Using the real resting state fMRI data sets, we demonstrated that the data sets with higher sampling rates were more prone to false positives, in agreement with the existing empirical reports. We further demonstrated with single subject results that for the data sets with higher sampling rates, the variance correction strategy restored the integrity of true connectivity.  相似文献   
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Gray platelet syndrome (GPS) is a rare (<1/1 000 000) and inherited platelet function disorder characterized by macrothrombocytopenia, α-granule deficiency, and hemorrhages. Bleeding intensity does not correlate with platelet count nor with functional test results. We hereby describe the perioperative bleeding prevention and management of a patient with GPS requiring multiple redo cardiac surgeries.  相似文献   
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