Towards a Long-Read Sequencing Approach for the Molecular Diagnosis of RPGRORF15 Genetic Variants

Sequencing of the low-complexity ORF15 exon of RPGR, a gene correlated with retinitis pigmentosa and cone dystrophy, is difficult to achieve with NGS and Sanger sequencing. False results could lead to the inaccurate annotation of genetic variants in dbSNP and ClinVar databases, tools on which HGMD and Ensembl rely, finally resulting in incorrect genetic variants interpretation. This paper aims to propose PacBio sequencing as a feasible method to correctly detect genetic variants in low-complexity regions, such as the ORF15 exon of RPGR, and interpret their pathogenicity by structural studies. Biological samples from 75 patients affected by retinitis pigmentosa or cone dystrophy were analyzed with NGS and repeated with PacBio. The results showed that NGS has a low coverage of the ORF15 region, while PacBio was able to sequence the region of interest and detect eight genetic variants, of which four are likely pathogenic. Furthermore, molecular modeling and dynamics of the RPGR Glu-Gly repeats binding to TTLL5 allowed for the structural evaluation of the variants, providing a way to predict their pathogenicity. Therefore, we propose PacBio sequencing as a standard procedure in diagnostic research for sequencing low-complexity regions such as RPGRORF15, aiding in the correct annotation of genetic variants in online databases

Effects of somatostatin analogues on muscle sympathetic nerve activity in acromegaly

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Acromegaly is associated with increased cancer risk: A survey in Italy

It is debated if acromegalic patients have an increased risk to develop malignancies. The aim of the present study was to assess the standardized incidence ratios (SIRs) of different types of cancer in acromegaly on a large series of acromegalic patients managed in the somatostatin analogs era. It was evaluated the incidence of cancer in an Italian nationwide multicenter cohort study of 1512 acromegalic patients, 624 men and 888 women, mean age at diagnosis 45 \uc2\ub1 13 years, followed up for a mean of 10 years (12573 person-years) in respect to the general Italian population. Cancer was diagnosed in 124 patients, 72 women and 52 men. The SIRs for all cancers was significantly increased compared to the general Italian population (expected: 88, SIR 1.41; 95% CI, 1.18-1.68, P < 0.001). In the whole series, we found a significantly increased incidence of colorectal cancer (SIR 1.67; 95% CI, 1.07-2.58, P = 0.022), kidney cancer (SIR 2.87; 95% CI, 1.55-5.34, P < 0.001) and thyroid cancer (SIR 3.99; 95% CI, 2.32-6.87, P < 0.001). The exclusion of 11 cancers occurring before diagnosis of acromegaly (all in women) did not change remarkably the study outcome. In multivariate analysis, the factors significantly associated with an increased risk of malignancy were age and family history of cancer, with a non-significant trend for the estimated duration of acromegaly before diagnosis. In conclusion, we found evidence that acromegaly in Italy is associated with a moderate increase in cancer risk

Automatic prediction of cardiovascular and cerebrovascular events using heart rate variability analysis

Background There is consensus that Heart Rate Variability is associated with the risk of vascular events. However, Heart Rate Variability predictive value for vascular events is not completely clear. The aim of this study is to develop novel predictive models based on data-mining algorithms to provide an automatic risk stratification tool for hypertensive patients. Methods A database of 139 Holter recordings with clinical data of hypertensive patients followed up for at least 12 months were collected ad hoc. Subjects who experienced a vascular event (i.e., myocardial infarction, stroke, syncopal event) were considered as high-risk subjects. Several data-mining algorithms (such as support vector machine, tree-based classifier, artificial neural network) were used to develop automatic classifiers and their accuracy was tested by assessing the receiver-operator characteristics curve. Moreover, we tested the echographic parameters, which have been showed as powerful predictors of future vascular events. Results The best predictive model was based on random forest and enabled to identify high-risk hypertensive patients with sensitivity and specificity rates of 71.4% and 87.8%, respectively. The Heart Rate Variability based classifier showed higher predictive values than the conventional echographic parameters, which are considered as significant cardiovascular risk factors. Conclusions Combination of Heart Rate Variability measures, analyzed with data-mining algorithm, could be a reliable tool for identifying hypertensive patients at high risk to develop future vascular events

Developing professional skills and social capital through computer supported collaborative learning in university contexts

This study aimed to compare the efficacy of collaborative learning in face-to-face and online university courses in developing professional skills and social capital. One hundred and sixty-six psychology majors learnt professional skills in seminars taught by the same teacher online and face-to-face. The different groups of participants achieved similar growth in level of professional knowledge, social self-efficacy, self-efficacy for problem solving and empowerment. Instead, online students were top performers on competence-based tasks. Follow-up evaluation after 9 months showed that social ties, formed initially more in the face-to-face groups, lasted more among online students. Our results indicate that Computer Assisted Collaborative Learning could provide educational opportunities to new groups of learners as well as to more traditional campus-based students. (c) 2006 Elsevier Ltd. All rights reserved

Intravitreal Injections for Macular Edema Secondary to Retinal Vein Occlusion: Long-Term Functional and Anatomic Outcomes

Purpose. To report the long-term visual and anatomic outcomes of intravitreal injections for macular edema (ME) secondary to retinal vein occlusion (RVO) in a real-life clinical setting. Design. Retrospective interventional case series. Methods. A total of 223 consecutive eyes with ME secondary to RVO, treated with the first three intravitreal Ranibizumab or dexamethasone injections between August 2008 and September 2018, were enrolled in the study. Subsequent retreatment was guided by best-corrected visual acuity (BCVA) and central macular thickness (CMT) measurements, aimed at achieving macular fluid regression and BCVA stability. BCVA and CMT were recorded at baseline and at subsequent annual time points. The mean number of injections administered each year and the incidence of adverse events were recorded. Results. The mean BCVA and CMT at baseline were 0.79 logMar (SD 0.71) and 615.7 μm (SD 257.5), respectively. The mean follow-up (FU) period was 47.8 months (min 12–max 120). At 12 months, the mean BCVA and CMT had significantly improved to 0.62 logMar (SD 0.68; p<0.0001) and 401.04 μm (SD 183.8; p<0.0001). Improvements remained significant at the final FU visit. Eyes with BRVO and nonischemic RVO showed significantly better visual outcomes when compared to eyes with CRVO and ischemic RVO, over the entire FU period. An average of 4.08 (SD 2.1) Ranibizumab and 1.5 (SD 0.6) Ozurdex injections were administered over the first 12 months. The number of injections decreased thereafter progressively. One eye with CRVO developed endophthalmitis and one with BRVO developed an intraocular pressure increase that was refractory to topical medications and ultimately treated with trabeculectomy. Conclusion. Intravitreal Ranibizumab and/or dexamethasone injections were found to be effective at inducing a long-lasting improvement of BCVA and CMT in a real-life clinical setting. A safety profile similar to that already well-established in Ranibizumab and dexamethasone treatment was observed, as well as a steady decrease in the number of intraocular injections required. The results support intravitreal treatments for BRVO and CRVO in patient populations with similar characteristics in similar settings

Subretinal Fibrosis in Stargardt’s Disease with Fundus Flavimaculatus and ABCA4 Gene Mutation

Purpose: To report on 4 patients affected by Stargardt’s disease (STGD) with fundus flavimaculatus (FFM) and ABCA4 gene mutation associated with subretinal fibrosis. Methods: Four patients with a diagnosis of STGD were clinically examined. All 4 cases underwent a full ophthalmologic evaluation, including best-corrected visual acuity measured by the Snellen visual chart, biomicroscopic examination, fundus examination, fundus photography, electroretinogram, microperimetry, optical coherence tomography and fundus autofluorescence. All patients were subsequently screened for ABCA4 gene mutations, identified by microarray genotyping and confirmed by conventional DNA sequencing of the relevant exons. Results: In all 4 patients, ophthalmologic exam showed areas of subretinal fibrosis in different retinal sectors. In only 1 case, these lesions were correlated to an ocular trauma as confirmed by biomicroscopic examination of the anterior segment that showed a nuclear cataract dislocated to the superior site and vitreous opacities along the lens capsule. The other patients reported a lifestyle characterized by competitive sport activities. The performed instrumental diagnostic investigations confirmed the diagnosis of STGD with FFM in all patients. Moreover, in all 4 affected individuals, mutations in the ABCA4 gene were found. Conclusions: Patients with the diagnosis of STGD associated with FFM can show atypical fundus findings. We report on 4 patients affected by STGD with ABCA4 gene mutation associated with subretinal fibrosis. Our findings suggest that this phenomenon can be accelerated by ocular trauma and also by ocular microtrauma caused by sport activities, highlighting that lifestyle can play a role in the onset of these lesions

A pilot study for development of a novel tool for clinical decision making to identify fallers among ophthalmic patients

Background Falls in the elderly is a major problem. Although falls have a multifactorial etiology, a commonly cited cause of falls in older people is poor vision. This study proposes a method to discriminate fallers and non-fallers among ophthalmic patients, based on data-mining algorithms applied to health and socio-demographic information. Methods A group of 150 subjects aged 55 years and older, recruited at the Eye Clinic of the Second University of Naples, underwent a baseline ophthalmic examination and a standardized questionnaire, including lifestyles, general health, social engagement and eyesight problems. A subject who reported at least one fall within one year was considered as faller, otherwise as non-faller. Different tree-based data-mining algorithms (i.e., C4.5, Adaboost and Random Forest) were used to develop automatic classifiers and their performances were evaluated by assessing the receiver-operator characteristics curve estimated with the 10-fold-crossvalidation approach. Results The best predictive model, based on Random Forest, enabled to identify fallers with a sensitivity and specificity rate of 72.6% and 77.9%, respectively. The most informative variables were: intraocular pressure, best corrected visual acuity and the answers to the total difficulty score of the Activities of Daily Vision Scale (a questionnaire for the measurement of visual disability). Conclusions The current study confirmed that some ophthalmic features (i.e. cataract surgery, lower intraocular pressure values) could be associated with a lower fall risk among visually impaired subjects. Finally, automatic analysis of a combination of visual function parameters (either self-evaluated either by ophthalmological test) and other health information, by data-mining algorithms, could be a feasible tool for identifying fallers among ophthalmic patients

Anti-inflammatory role of curcumin in retinal disorders (review)

Curcumin [1,7-bis-(4-hydroxy-3-methoxyphenyl)-hepta-1,6-diene-3,5-dione], the main component of turmeric (Curcuma longa, a flowering plant of the ginger family, Zingiberaceae), is known to possess different pharmacological activities, particularly anti-inflammatory and antioxidant properties. Since an underlying inflammatory process exists in several ocular conditions, such as anterior uveitis, glaucoma, age-related macular degeneration (AMD) and diabetic retinopathy (DR), the aim of the present review was to summarize the pleiotropic effects exerted by this molecule, focusing in particular on its beneficial role in retinal diseases. The anti-inflammatory activity of curcumin has also been described in numerous systemic inflammatory pathologies and tumors. Specifically, the biological, pharmaceutical and nutraceutical properties of curcumin are associated with its ability to downregulate the expression of the following genes: I kappa B alpha, cyclooxygenase 2, prostaglandin E2, interleukin (IL)-1, IL-6, IL-8 and tumor necrosis factor-alpha. According to this finding, curcumin may be useful in the treatment of some retinal disorders. In DR, proliferative vitreoretinopathy and AMD, beneficial effects have been observed following treatment with curcumin, including slowing down of the inflammatory process. Despite the aforementioned evidence, the main disadvantage of this substance is that it possesses a low solubility, as well as poor oral bioavailability due to its reduced absorption, rapid metabolism and rapid elimination. Therefore, several curcumin analogues have been synthesized and tested over the years, in order to improve the possible obtainable therapeutic effects. The purpose of the present review was to identify new aspects that could guide future research on this important traditional medicine, which is a well-tolerated natural product, and is widely considered safe and economical

Performance measurements estimated on the test set (hold-out estimation) of the best classifiers based on HRV features.

<p>Class.: Classifier</p><p>AB: Adaboost</p><p>MLP: Multilayer Perceptron</p><p>NB: Naïve Bayes classifier</p><p>RF: Random Forest</p><p>SVM: Support Vector Machine</p><p>NI: number of iteration</p><p>ML: minimum number of instances per leaf.</p><p>CF: confidence factor for pruning</p><p>LR: learning rate</p><p>M: momentum</p><p>NE: number of epoch</p><p>NT: number of trees</p><p>NF: number of randomly chosen features</p><p>G: gamma</p><p>Χ²-FS: chi squared feature selection algorithm (a subset of 10 HRV features)</p><p>CFS: correlation-based feature selection algorithm (a subset of 8 HRV features)</p><p>AUC: area under the curve</p><p>ACC: accuracy</p><p>CI: confidence interval</p><p>SEN: sensitivity</p><p>SPE: specificity.</p><p>Performance measurements estimated on the test set (hold-out estimation) of the best classifiers based on HRV features.</p