Clear lens phacoemulsification in the anterior lenticonus due to Alport Syndrome: two case reports

<p>Abstract</p> <p>Introduction</p> <p>Alport Syndrome has a prevalence of 1 case per 5,000 people and 85% of patients have the X-linked form, where affected males develop renal failure and usually have high-tone sensorineural deafness by age 20. The main abnormality is deficient synthesis of type IV collagen, the main component of basement membranes. Common ocular abnormalities of this syndrome consist of dot-and-fleck retinopathy, posterior polymorphous corneal dystrophy, and anterior lenticonus, but other ocular defects such as cataracts, posterior lenticonus, and retinal detachments have also been reported.</p> <p>Case presentation</p> <p>We report two cases of anterior lenticonus due to Alport Syndrome and describe clear lens phacoemulsification and foldable intraocular lens implantation as an effective and safe refractive procedure in the four eyes of these two patients.</p> <p>Conclusion</p> <p>All four eyes of the two patients were in good condition after surgery and achieved satisfactory optical and visual results and had no remarkable complications at six-months follow-up. Clear lens phacoemulsification with foldable intraocular lens implantation can be used as an efficient and safe procedure for vision disorders in these patients.</p

Gyrate atrophy of the choroid and retina with hyper-ornithinemia responsive to vitamin B6: a case report

<p>Abstract</p> <p>Background</p> <p>Gyrate atrophy of the retina and choroid is a rare autosomal recessive inherited disease, characterized by progressive chorioretinal atrophy that results in progressive deterioration of peripheral and night vision and leading to blindness.</p> <p>Case presentation</p> <p>This report presents a case of a 28-year-old man consulting for a progressive fall of visual acuity with hemeralopia. Eye fundoscopy showed regions of confluent rounded chorioretinal atrophy. The visual field and retinal angiography were altered. A high level of plasma ornithine (629 nmol/mL) was detected and a diagnosis of gyrate atrophy of the retina and choroid was made. The patient was treated with high dose Pyridoxine supplement (300 mg/d for 6 months) and the ornithine level of his serum was successfully reduced.</p> <p>Conclusion</p> <p>The exact mechanism of chorioretinal atrophy in hyper-ornithinemia is not known and a small percentage of the affected people respond to Vitamin B6 supplementation.</p

The Unreasonable Effectiveness of Encoder-Decoder Networks for Retinal Vessel Segmentation

We propose an encoder-decoder framework for the segmentation of blood vessels in retinal images that relies on the extraction of large-scale patches at multiple image-scales during training. Experiments on three fundus image datasets demonstrate that this approach achieves state-of-the-art results and can be implemented using a simple and efficient fully-convolutional network with a parameter count of less than 0.8M. Furthermore, we show that this framework - called VLight - avoids overfitting to specific training images and generalizes well across different datasets, which makes it highly suitable for real-world applications where robustness, accuracy as well as low inference time on high-resolution fundus images is required

International Consensus Based Review and Recommendations for Minimum Reporting Standards in Research on Transcutaneous Vagus Nerve Stimulation (Version 2020).

Given its non-invasive nature, there is increasing interest in the use of transcutaneous vagus nerve stimulation (tVNS) across basic, translational and clinical research. Contemporaneously, tVNS can be achieved by stimulating either the auricular branch or the cervical bundle of the vagus nerve, referred to as transcutaneous auricular vagus nerve stimulation(VNS) and transcutaneous cervical VNS, respectively. In order to advance the field in a systematic manner, studies using these technologies need to adequately report sufficient methodological detail to enable comparison of results between studies, replication of studies, as well as enhancing study participant safety. We systematically reviewed the existing tVNS literature to evaluate current reporting practices. Based on this review, and consensus among participating authors, we propose a set of minimal reporting items to guide future tVNS studies. The suggested items address specific technical aspects of the device and stimulation parameters. We also cover general recommendations including inclusion and exclusion criteria for participants, outcome parameters and the detailed reporting of side effects. Furthermore, we review strategies used to identify the optimal stimulation parameters for a given research setting and summarize ongoing developments in animal research with potential implications for the application of tVNS in humans. Finally, we discuss the potential of tVNS in future research as well as the associated challenges across several disciplines in research and clinical practice

Deep brain stimulation of the anterior nucleus of the thalamus in drug-resistant epilepsy in the MORE multicenter patient registry

Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (CC BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background and objectives: The efficacy of deep brain stimulation of the anterior nucleus of the thalamus (ANT DBS) in patients with drug-resistant epilepsy (DRE) was demonstrated in the double-blind Stimulation of the Anterior Nucleus of the Thalamus for Epilepsy randomized controlled trial. The Medtronic Registry for Epilepsy (MORE) aims to understand the safety and longer-term effectiveness of ANT DBS therapy in routine clinical practice. Methods: MORE is an observational registry collecting prospective and retrospective clinical data. Participants were at least 18 years old, with focal DRE recruited across 25 centers from 13 countries. They were followed for at least 2 years in terms of seizure frequency (SF), responder rate (RR), health-related quality of life (Quality of Life in Epilepsy Inventory 31), depression, and safety outcomes. Results: Of the 191 patients recruited, 170 (mean [SD] age of 35.6 [10.7] years, 43% female) were implanted with DBS therapy and met all eligibility criteria. At baseline, 38% of patients reported cognitive impairment. The median monthly SF decreased by 33.1% from 15.8 at baseline to 8.8 at 2 years (p 10 implantations) had 42.8% reduction in median monthly SF by 2 years in comparison with 25.8% in low-volume center. In patients with cognitive impairment, the reduction in median monthly SF was 26.0% by 2 years compared with 36.1% in patients without cognitive impairment. The most frequently reported adverse events were changes (e.g., increased frequency/severity) in seizure (16%), memory impairment (patient-reported complaint, 15%), depressive mood (patient-reported complaint, 13%), and epilepsy (12%). One definite sudden unexpected death in epilepsy case was reported. Discussion: The MORE registry supports the effectiveness and safety of ANT DBS therapy in a real-world setting in the 2 years following implantation. Classification of evidence: This study provides Class IV evidence that ANT DBS reduces the frequency of seizures in patients with drug-resistant focal epilepsy.The MORE registry was sponsored and funded by Medtronic, plc.info:eu-repo/semantics/publishedVersio

Machine Learning to Predict Area Fugitive Emission Fluxes of GHGs from Open-Pit Mines

Greenhouse gas (GHG) emissions from open-pit mines pose a global climate challenge, which necessitates appropriate quantification to support effective mitigation measures. This study considers the area-fugitive methane advective flux (as a proxy for emission flux) released from a tailings pond and two open-pit mines, denominated “old” and “new”, within a facility in northern Canada. To estimate the emission fluxes of methane from these sources, this research employed near-surface observations and modeling using the weather research and forecasting (WRF) passive tracer dispersion method. Various machine learning (ML) methods were trained and tested on these data for the operational forecasting of emissions. Predicted emission fluxes and meteorological variables from the WRF model were used as training and input datasets for ML algorithms. A series of 10 ML algorithms were evaluated. The four models that generated the most accurate forecasts were selected. These ML models are the multi-layer perception (MLP) artificial neural network, the gradient boosting (GBR), XGBOOST (XGB), and support vector machines (SVM). Overall, the simulations predicted the emission fluxes with R2 (-) values higher than 0.8 (-). Considering the bias (Tonnes h−1), the ML predicted the emission fluxes within 6.3%, 3.3%, and 0.3% of WRF predictions for the old mine, new mine, and the pond, respectively