Non-Arteritic Anterior Ischemic Optic Neuropathy (NAION) associated with Paracentral Acute Middle Maculopathy (PAMM) and Cilioretinal Artery Occlusion (CILRAO): multimodal imaging of a newly described clinical association.

PURPOSE: To report multimodal imaging features of a novel association of non-arteritic anterior ischemic optic neuropathy (NAION), paracentral acute middle maculopathy (PAMM), and cilioretinal artery occlusion (CILRAO). METHODS: A 74-year-old male patient presented complaining of an acute subjective decline in visual acuity in the right eye over the previous days. This patient underwent a comprehensive ophthalmological assessment, including multimodal retinal imaging and visual field test. RESULTS: The eye examination revealed yellowish optic disc edema in the right eye with peripapillary hemorrhages and a whitish lesion extending from the temporal margin of the optic nerve head towards the macula. Multimodal imaging confirmed the diagnosis of NAION in the right eye. Notably, the structural B-scan and en face OCT images revealed hyperreflective areas in the inner and mid retinal layers, indicating an association with CILRAO and PAMM. CONCLUSION: We herein describe the clinical findings of a previously unreported association among NAION, CILRAO and PAMM.

Comparison of diabetic retinopathy screening between hospital-based multidisciplinary and general practice-based settings: insights from a regional study in Italy.

PURPOSE: To compare diabetic retinopathy screening among patients with type 1 or type 2 diabetes under care in two distinct setups: hospital-based multidisciplinary and general practice-based. MATERIALS AND METHODS: In this retrospective observational case series, we collected data from a total of 133 diabetic patients: subjects from the hospital-based multidisciplinary setting were referred by the diabetologist and screened by an ophthalmologist using the Optomed Aurora IQ fundus camera. These patients were compared with those who underwent DR screening arranged through a general practice-based setting. RESULTS: The proportion of patients treated with insulin was higher in the hospital-based multidisciplinary group, both considering the totality patients and those affected by type 2 diabetes (71.6% vs. 32.2%; p < 0.001, and 58.8% vs. 31.0%; p = 0.004 respectively). Patients from the hospital-based multidisciplinary group had a longer mean diabetes duration (19.6 vs 14.9 years, p < 0.001), underwent DR screening more frequently in the previous three years (2.9 vs 1.4, p < 0.001), the mean time between two DR screenings was shorter (14.6 vs 77.9 weeks, p < 0.001), and DR was detected more frequently (32,4% vs 13.5%; p = 0.011). CONCLUSION: We were able to demonstrate that patients screened in the multidisciplinary center, which had characteristics predisposing to a higher risk of DR, were more likely to be diagnosed with DR on time, with a higher mean number of DR screenings and a shorted interval between diabetic and ophthalmological assessments.

Inter-Reader and Inter-Modality Variability in Macular Atrophy Quantification in Neovascular AMD: Comparison of Six Imaging Modalities.

PURPOSE: Macular atrophy is a common complication in neovascular age-related macular degeneration (AMD) and is associated with poorer visual outcomes. This study evaluated inter-reader and inter-modality variability in measuring macular atrophy in previously-treated neovascular AMD eyes without exudation, using six imaging modalities. DESIGN: Prospective, cohort study. PARTICIPANTS: Thirty participants with previously-treated neovascular AMD, showing no signs of exudation at the time of enrollment, and exhibiting macular atrophy. METHODS: During the same clinic visit, patients were imaged using six different imaging modalities: color fundus photography (CFP; Clarus, Carl Zeiss Meditec), near-infrared imaging (NIR; Spectralis; Heidelberg Engineering, Heidelberg, Germany), structural optical coherence tomography (OCT; Spectralis; Heidelberg Engineering, Heidelberg, Germany), green fundus autofluorescence (GAF; Clarus, Carl Zeiss Meditec), blue fundus autofluorescence (BAF; Spectralis; Heidelberg Engineering, Heidelberg, Germany), and pseudocolor imaging (MultiColor; Spectralis; Heidelberg Engineering, Heidelberg, Germany). Two readers independently measured the macular atrophy area. MAIN OUTCOME MEASURES: Inter-reader and inter-modality agreement. RESULTS: The 95% coefficient of repeatability (CR) was 5.98 mm2 for CFP, 4.46 mm2 for MultiColor, 3.90 mm2 for BAF, 3.92 mm2 for GAF, 4.86 mm2 for NIR, and 3.55 mm2 for OCT. Similarly, the coefficient of variation (CV) was lowest for the OCT-based grading at 0.08 and highest for the NIR-based grading at 0.28. Accordingly, the intraclass correlation coefficient (ICC) was 0.742 for CFP, 0.805 for MultiColor, 0.857 for BAF, 0.850 for GAF, 0.755 for NIR, and 0.917 for OCT. The 6 different imaging modalities presented measurements with different mean values, with only a limited number of comparisons not significantly different between the instruments, although measurements were correlated. The largest size of macular atrophy was with the structural OCT-based grading (median=4.65 mm2; interquartile range [IQR]=4.78 mm2) and the smallest was with the CFP-based grading (median=3.86 mm2; IQR=5.06 mm2). Inconsistencies arose from various factors. CONCLUSIONS: In patients with neovascular AMD, macular atrophy measurements vary significantly depending on the imaging technique used. CFP-based assessments yielded the smallest macular atrophy sizes, while structural OCT-based assessments produced the largest. These discrepancies stem from both the inherent limitations of each modality in assessing RPE atrophy and factors related to neovascularization, such as the coexistence of fibrosis.

Choriocapillaris in Age-Related Macular Degeneration.

Age-related macular degeneration (AMD) is a multifactorial disease characterized by progressive alterations of different retinal structures ultimately leading to vision loss. Among these, the choriocapillaris (CC) has been found to be affected in different stages of AMD. In this review we provide a discussion on the different stages of AMD, focusing particularly on the alterations involving the CC. This has been possible thanks to the introduction of optical coherence tomography-angiography, a recently developed imaging technique which allows the detection of blood flow in choroidal vessels. Therefore, the aim of this review is to provide a description of the various alterations involving the CC in the different stages of AMD.

Deep Learning in Neovascular Age-Related Macular Degeneration.

Background and objectives: Age-related macular degeneration (AMD) is a complex and multifactorial condition that can lead to permanent vision loss once it progresses to the neovascular exudative stage. This review aims to summarize the use of deep learning in neovascular AMD. Materials and Methods: Pubmed search. Results: Deep learning has demonstrated effectiveness in analyzing structural OCT images in patients with neovascular AMD. This review outlines the role of deep learning in identifying and measuring biomarkers linked to an elevated risk of transitioning to the neovascular form of AMD. Additionally, deep learning techniques can quantify critical OCT features associated with neovascular AMD, which have prognostic implications for these patients. Incorporating deep learning into the assessment of neovascular AMD eyes holds promise for enhancing clinical management strategies for affected individuals. Conclusion: Several studies have demonstrated effectiveness of deep learning in assessing neovascular AMD patients and this has a promising role in the assessment of these patients.

Mucopolysaccharidosis type II B complicated by optic disc swelling, pigmentary retinopathy and macular edema.

PURPOSE: To report clinical and imaging features of optic nerve and retinal involvement in a patient with mucopolysaccharidosis (MPS) type II B. METHODS: A 27-year-old man, diagnosed with MPS type II B and undergoing enzymatic substitution therapy for the past 19 years, was referred to the retina service. An ophthalmological evaluation, which included multimodal imaging, was conducted to investigate potential retinal and optic disc involvement. RESULTS: The eye examination revealed a pigmentary retinopathy with a predominant loss of the outer retinal loss, primarily in the parafoveal and perifoveal regions. Notably, multimodal imaging identified macular edema without any signs of leakage, implying an association between macular edema and retinal neurodegeneration. Additionally, both eyes exhibited an optic disc with blurred margins. CONCLUSION: We herein describe the multimodal imaging findings of retinal and optic disc involvement in a patient with MPS type II B. This report describes for the first-time the presence of macular edema without leakage alongside photoreceptor damage and optic disc swelling.

Insulin-like Growth Factor 1, Growth Hormone, and Anti-Müllerian Hormone Receptors Are Differentially Expressed during GnRH Neuron Development.

Gonadotropin-releasing hormone (GnRH) neurons are key neuroendocrine cells in the brain as they control reproduction by regulating hypothalamic-pituitary-gonadal axis function. In this context, anti-Müllerian hormone (AMH), growth hormone (GH), and insulin-like growth factor 1 (IGF1) were shown to improve GnRH neuron migration and function in vitro. Whether AMH, GH, and IGF1 signaling pathways participate in the development and function of GnRH neurons in vivo is, however, currently still unknown. To assess the role of AMH, GH, and IGF1 systems in the development of GnRH neuron, we evaluated the expression of AMH receptors (AMHR2), GH (GHR), and IGF1 (IGF1R) on sections of ex vivo mice at different development stages. The expression of AMHR2, GHR, and IGF1R was assessed by immunofluorescence using established protocols and commercial antibodies. The head sections of mice were analyzed at E12.5, E14.5, and E18.5. In particular, at E12.5, we focused on the neurogenic epithelium of the vomeronasal organ (VNO), where GnRH neurons, migratory mass cells, and the pioneering vomeronasal axon give rise. At E14.5, we focused on the VNO and nasal forebrain junction (NFJ), the two regions where GnRH neurons originate and migrate to the hypothalamus, respectively. At E18.5, the median eminence, which is the hypothalamic area where GnRH is released, was analyzed. At E12.5, double staining for the neuronal marker ß-tubulin III and AMHR2, GHR, or IGF1R revealed a signal in the neurogenic niches of the olfactory and VNO during early embryo development. Furthermore, IGF1R and GHR were expressed by VNO-emerging GnRH neurons. At E14.5, a similar expression pattern was found for the neuronal marker ß-tubulin III, while the expression of IGF1R and GHR began to decline, as also observed at E18.5. Of note, hypothalamic GnRH neurons labeled for PLXND1 tested positive for AMHR2 expression. Ex vivo experiments on mouse sections revealed differential protein expression patterns for AMHR2, GHR, and IGF1R at any time point in development between neurogenic areas and hypothalamic compartments. These findings suggest a differential functional role of related systems in the development of GnRH neurons.

Cameroonian Spice Extracts Modulate Molecular Mechanisms Relevant to Cardiometabolic Diseases in SW 872 Human Liposarcoma Cells.

The molecular pathophysiology of cardiometabolic diseases is known to be influenced by dysfunctional ectopic adipose tissue. In addition to lifestyle improvements, these conditions may be managed by novel nutraceutical products. This study evaluatedthe effects of 11 Cameroonian medicinal spice extracts on triglyceride accumulation, glucose uptake, reactive oxygen species (ROS) production and interleukin secretion in SW 872 human adipocytes after differentiation with 100 µM oleic acid. Triglyceride content was significantly reduced by all spice extracts. Glucose uptake was significantly increased by Tetrapleura tetraptera, Aframomum melegueta and Zanthoxylum leprieurii. Moreover, Xylopia parviflora, Echinops giganteus and Dichrostachys glomerata significantly reduced the production of ROS. Concerning pro-inflammatory cytokine secretion, we observed that Tetrapleura tetraptera, Echinops giganteus, Dichrostachys glomerata and Aframomum melegueta reduced IL-6 secretion. In addition, Xylopia parviflora, Monodora myristica, Zanthoxylum leprieurii, and Xylopia aethiopica reduced IL-8 secretion, while Dichrostachys glomerata and Aframomum citratum increased it. These findings highlight some interesting properties of these Cameroonian spice extracts in the modulation of cellular parameters relevant to cardiometabolic diseases, which may be further exploited, aiming to develop novel treatment options for these conditions based on nutraceutical products.

Cortical response to levodopa in Parkinson's disease patients with dyskinesias.

Levodopa-induced dyskinesias are a common and disabling side effect of dopaminergic therapy in Parkinson's disease, but their neural mechanisms in vivo are still poorly understood. Besides striatal pathology, the importance of cortical dysfunction has been increasingly recognized. The supplementary motor area in particular, may have a relevant role in dyskinesias onset given its involvement in endogenously generated actions. The aim of the present study was to investigate the levodopa-related cortical excitability changes along with the emergence of levodopa-induced peak-of-dose dyskinesias in subjects with Parkinson's disease. Thirteen patients without dyskinesias and ten with dyskinesias received 200/50 mg fast-acting oral levodopa/benserazide following overnight withdrawal (12 hr) from their dopaminergic medication. We targeted transcranial magnetic stimulation to the supplementary motor area, ipsilateral to the most dopamine-depleted striatum defined with single-photon emission computed tomography with [123 I]N-ω-fluoropropyl-2ß-carbomethoxy-3ß-(4-iodophenyl)nortropane, and recorded transcranial magnetic stimulation-evoked potentials with high-density electroencephalography before and at 30, 60, and 180 min after levodopa/benserazide intake. Clinical improvement from levodopa/benserazide paralleled the increase in cortical excitability in both groups. Subjects with dyskinesias showed higher fluctuation of cortical excitability in comparison to non-dyskinetic patients, possibly reflecting dyskinetic movements. Together with endogenous brain oscillation, levodopa-related dynamics of brain state could influence the therapeutic response of neuromodulatory interventions.

Diagnosis of autism through EEG processed by advanced computational algorithms: A pilot study.

BACKGROUND: Multi-Scale Ranked Organizing Map coupled with Implicit Function as Squashing Time algorithm(MS-ROM/I-FAST) is a new, complex system based on Artificial Neural networks (ANNs) able to extract features of interest in computerized EEG through the analysis of few minutes of their EEG without any preliminary pre-processing. A proof of concept study previously published showed accuracy values ranging from 94%-98% in discerning subjects with Mild Cognitive Impairment and/or Alzheimer's Disease from healthy elderly people. The presence of deviant patterns in simple resting state EEG recordings in autism, consistent with the atypical organization of the cerebral cortex present, prompted us in applying this potent analytical systems in search of a EEG signature of the disease. AIM OF THE STUDY: The aim of the study is to assess how effectively this methodology distinguishes subjects with autism from typically developing ones. METHODS: Fifteen definite ASD subjects (13 males; 2 females; age range 7-14; mean value = 10.4) and ten typically developing subjects (4 males; 6 females; age range 7-12; mean value 9.2) were included in the study. Patients received Autism diagnoses according to DSM-V criteria, subsequently confirmed by the ADOS scale. A segment of artefact-free EEG lasting 60 seconds was used to compute input values for subsequent analyses. MS-ROM/I-FAST coupled with a well-documented evolutionary system able to select predictive features (TWIST) created an invariant features vector input of EEG on which supervised machine learning systems acted as blind classifiers. RESULTS: The overall predictive capability of machine learning system in sorting out autistic cases from normal control amounted consistently to 100% with all kind of systems employed using training-testing protocol and to 84% - 92.8% using Leave One Out protocol. The similarities among the ANN weight matrixes measured with apposite algorithms were not affected by the age of the subjects. This suggests that the ANNs do not read age-related EEG patterns, but rather invariant features related to the brain's underlying disconnection signature. CONCLUSION: This pilot study seems to open up new avenues for the development of non-invasive diagnostic testing for the early detection of ASD.

Local MRI analysis approach in the diagnosis of early and prodromal Alzheimer's disease.

BACKGROUND: Medial temporal lobe (MTL) atrophy is one of the key biomarkers to detect early neurodegenerative changes in the course of Alzheimer's disease (AD). There is active research aimed at identifying automated methodologies able to extract accurate classification indexes from T1-weighted magnetic resonance images (MRI). Such indexes should be fit for identifying AD patients as early as possible. SUBJECTS: A reference group composed of 144AD patients and 189 age-matched controls was used to train and test the procedure. It was then applied on a study group composed of 302 MCI subjects, 136 having progressed to clinically probable AD (MCI-converters) and 166 having remained stable or recovered to normal condition after a 24month follow-up (MCI-non converters). All subjects came from the ADNI database. METHODS: We sampled the brain with 7 relatively small volumes, mainly centered on the MTL, and 2 control regions. These volumes were filtered to give intensity and textural MRI-based features. Each filtered region was analyzed with a Random Forest (RF) classifier to extract relevant features, which were subsequently processed with a Support Vector Machine (SVM) classifier. Once a prediction model was trained and tested on the reference group, it was used to compute a classification index (CI) on the MCI cohort and to assess its accuracy in predicting AD conversion in MCI patients. The performance of the classification based on the features extracted by the whole 9 volumes is compared with that derived from each single volume. All experiments were performed using a bootstrap sampling estimation, and classifier performance was cross-validated with a 20-fold paradigm. RESULTS: We identified a restricted set of image features correlated with the conversion to AD. It is shown that most information originate from a small subset of the total available features, and that it is enough to give a reliable assessment. We found multiple, highly localized image-based features which alone are responsible for the overall clinical diagnosis and prognosis. The classification index is able to discriminate Controls from AD with an Area Under Curve (AUC)=0.97 (sensitivity ≃89% at specificity ≃94%) and Controls from MCI-converters with an AUC=0.92 (sensitivity ≃89% at specificity ≃80%). MCI-converters are separated from MCI-non converters with AUC=0.74(sensitivity ≃72% at specificity ≃65%). FINDINGS: The present automated MRI-based technique revealed a strong relationship between highly localized baseline-MRI features and the baseline clinical assessment. In addition, the classification index was also used to predict the probability of AD conversion within a time frame of two years. The definition of a single index combining local analysis of several regions can be useful to detect AD neurodegeneration in a typical MCI population.