Background: The electroretinogram is a clinical test used to assess the function of the photoreceptors and retinal circuits of various cells in the eye, with the recorded waveform being the result of the summated response of neural generators across the retina. Methods: The present investigation involved an analysis of the electroretinogram waveform in both the time and time-frequency domain through the utilization of the discrete wavelet transform and continuous wavelet transform techniques. The primary aim of this study was to monitor and evaluate the effects of treatment in a New Zealand rabbit model of endophthalmitis via electroretinogram waveform analysis and to compare these with normal human electroretinograms Results: The wavelet scalograms were analyzed using various mother wavelets, including the Daubechies, Ricker, Wavelet Biorthogonal 3.1 (bior3.1), Morlet, Haar, and Gaussian wavelets. Distinctive variances were identified in the wavelet scalograms between rabbit and human electroretinograms. The wavelet scalograms in the rabbit model of endophthalmitis showed recovery with treatment in parallel with the time -domain features. Conclusions: The study compared Adult, Child, and Rabbit electroretinogram responses using DWT and CWT, finding that Adult signals had higher power than Child signals, and Rabbit signals showed differences in a-wave and b-wave depending on the type of response tested, while Haar Wavelet was found to be superior in visualizing frequency components in electrophysiological signals in following the treatment of endophthalmitis and may give additional outcome measures for the management of retinal disease.

The electroretinography (ERG) is a diagnostic test that measures the electrical activity of the retina in response to a light stimulus. This test has a long history and has been extensively studied among years. Dr. James Dewar recorded the first electroretinogram signal in 1873. Later he described signal analysis using 4 components, namely amplitude, and latency of a-wave and b-wave. Nowadays, the international electrophysiology community has established the standard for electroretinography in 2008. However, from the point of view of signal analysis, the major change did not happen. ERG analysis is still based on the 4 components evaluation. The article describes ERG database including the classification of signals by using advanced analysis of electroretinograms based on wavelet scalogram processing. To implement an extended analysis of the ERG, the parameters extracted from the wavelet scalogram of the signal were obtained using digital image processing and machine learning methods. The results of the study show that the proposed algorithm implements the classification of adult electroretinogram signals by 19% more accurately and pediatric signals by 20% more accurately than the classical algorithm. The promising use of ERG is differential diagnostics, which may also be used in preclinical toxicology and experimental modeling. The problem of developing methods for electrophysiological signals analysis in ophthalmology is associated with the complex morphological structure of electrophysiological signals components, due to the generation of retina cell electrical responses to light stimulus.

A Challenging task in routine practice is finding distinction between benign and malignant paragangliomas and pheochromocytomas. The aim of this study is a comparative analysis of angiogenesis by assessing intratumoral microvascular density (MVD) with immunohistochemical (IHC) markers (CD31, CD34, CD105, ERG), and S100 immunoreactivity, Ki67 proliferative index, SDHB expressiveness, tumor size with one the most utilized score Pheochromocytoma of Adrenal Gland Scales Score (PASS), using tissue microarray (TMA) with 115 tumor samples, 61 benign (PASS<4) and 54 potentially malignant (PASS ≥4). We found no notable difference between intratumoral MVD and potentially malignant behavior. Group of potentially malignant tumors are significantly larger in size, have lower intratumoral MVD, and decreased number of S100 labeled sustentacular cells. Both groups have low proliferative activity (mean Ki67 is 1,02 and 1,22 respectively). Most tumors maintains SDHB expression, only 6 cases (5,2%) showed a loss of expression (4 of them in PASS<4 group and 2 in PASS≥4). PASS score is easy available for assessment, and complemented with markers of biological behavior completes risk stratification algorithm. Size is directly related with PASS score and malignancy. Intratumoral MVD is extensively developed but it is not crucial in evaluating the malignant potential.

The continuous advancements in healthcare technology have empowered the discovery, diagnosis, and prediction of diseases, revolutionizing the field. Artificial intelligence (AI) is expected to play a pivotal role in achieving the goals of precision medicine, particularly in disease prevention, detection, and personalized treatment. This study aims to determine the optimal combination of the mother wavelet and AI model for the analysis of pediatric electroretinogram (ERG) signals. The dataset, consisting of signals and corresponding diagnoses, undergoes Continuous Wavelet Transform (CWT) using commonly used wavelets to obtain a time-frequency representation. Wavelet images were used for the training of five widely used deep learning models: VGG-11, ResNet-50, DensNet-121, ResNext-50, and Vision Transformer, to evaluate their accuracy in classifying healthy and unhealthy patients. The findings demonstrate that the combination of Ricker Wavelet and Vision Transformer consistently yields the highest median accuracy values for ERG analysis, as evidenced by the upper and lower quartile values. The median balanced accuracy of the obtained combination of the three considered types of ERG signals in the article are 0.83, 0.85, and 0.88. However, other wavelet types also achieved high accuracy levels, indicating the importance of carefully selecting the mother wavelet for accurate classification. The study provides valuable insights into the effectiveness of different combinations of wavelets and models in classifying ERG wavelet scalograms.

Erythropoietin (EPO) protects cells by inhibiting apoptosis, oxidative stress and inflammation in several models of retinal degeneration. In this study, we demonstrate the effects of recombinant Adeno Associated Virus (AAV) vector-mediated delivery of a modified form of erythropoietin (EPO-R76E) in an established mouse model of dry-AMD in which retinal degeneration is induced by RPE oxidative stress. Experimental vector AAV-EPO-R76E and control vector AAV-GFP were packaged into serotype-1 (AAV1) to enable RPE selective expression. RPE oxidative stress-mediated retinal degeneration was induced by exon specific deletion of the protective enzyme MnSOD (encoded by Sod2) by cre/lox mechanism. Experimental mice received subretinal injection of AAV-EPO-R76E in the right eye and AAV-GFP in the left eye. Western blotting of RPE/Choroid protein samples from AAV-EPO-R76E injected eyes showed RPE specific exogenous protein expression. Retinal degeneration was monitored by electroretinography (ERG). EPO-R76E over-expression in RPE delayed the progressive retinal degeneration as measured by light microscopy in RPE specific Sod2 knockout mice. Delivery of EPO-R76E vector can be used as a tool to prevent retinal degeneration induced by RPE oxidative stress as seen in this mouse model.

Candidiasis is one of the global public health problems. In fluconazole resistant Candida spp. (FRCS), mutations in ergosterol biosynthesis gene 11 (ERG 11) have been commonly found. This study aimed to determine the profile of FRCS isolates and to detect mutations in part of ERG 11 gene in fluconazole resistant Candida albicans (FRCA) isolates. Study was conducted on 150 isolates of FRCS obtained from patients admitted in a tertiary care hospital, South India from September 2019 to December 2021. Candida spp. was identified by MALDI-TOF MS and fluconazole resistance was detected by VITEK 2 system. Following which a part of the ERG 11 gene of the FRCA isolates were amplified, purified, sequenced and a phylogenetic tree was constructed. Out of the 150 FRCS, the most common FRCS was C. auris followed by C. glabrata, C. krusei, C. parapsilosis, C. albicans, C. tropicalis and C. guilliermondii. Sequencing of amplicons detected a single missense mutation and 44 silent mutations. We opined that fluconazole resistance in FRCA isolates may be due to mecha-nisms other than the studied one in our region. Phylogenetic analysis of amplified sequences of 12 FRCA isolates observed three clusters and all 12 sequences showed relatedness to Malaysian 2019 isolates.

Abstract: The pathobiology of ascending aorta aneurysms (AAA) onset and progression is not well understood and only partially characterized. AAA are also complicated in case of bicuspid aorta valve (BAV) anatomy. There is emerging evidence about the crucial role of endothelium-related pathways, which show in AAA an altered expression and function. Here, we examined the involvement of ERG-related pathways in the differential progression of disease in aortic tissues from patients having a BAV or tricuspid aorta valve (TAV) with or without AAA. Our findings identified ERG as a novel endothelial-specific regulator of TGF-β-SMAD, Notch, and NO pathways, by modulating a differential fibrotic or calcified AAA progression in BAV and TAV aortas. We provided evidence that calcification is correlated to different ERG expression (as gene and protein), which appears to be under control of Notch signaling. The latter, when increased, associated with an early calcification in aortas with BAV valve and aneurysmatic, was demonstrated to favor the progression versus severe complications, i.e., dissection or rupture. In TAV aneurysmatic aortas, ERG appeared to modulate fibrosis. Therefore, we proposed that ERG may represent a sensitive tissue biomarker to monitor AAA progression and a target to develop therapeutic strategies and influence surgical procedures.