Biometry in Silicone Oil Filled Eyes. A Review

The “gold standard” of modern vitreoretinal surgery is silicone oil tamponade of the vitreous cavity. The lens opacity development is in the list of complications of prolonged silicone oil eye filling (from 2 weeks to 2 years). Polydimethylsiloxanes hydrophobicity, direct contact with the front of the silicone bladder, macrophage and toxic reaction, trophic disturbances are the causes leading to the cataract initiation. This makes the problem of cataract surgery and preliminary intraocular lens calculation in silicone oil filled eyes before its removing very relevant as well as cloudy retina visualization and the necessity of minimization of number of operations through their combination. Certainly, the main error in IOL power calculation is associated with axial length measurement inaccuracy, as the most significant term of an equation. Silicone oil filled eyes biometry errors, and, consequently, postoperative refraction biases remain unresolved problem until now. To date authors report only 58 % of cases in which target refraction was achieved after combined surgery. Some researchers figure out that average calculation error after phacoemulsification with IOL implantation in avitreal eyes was 0.8 D despite of the optical biometry usage. Today it is represented by several methods: partial coherent interferometry, optical low-coherence reflectometry and optical coherence tomography, which are implemented in devices such as IOLMaster 500, Lenstar LS 900 and IOLMaster 700, which have their own characteristics and measurement accuracy. Their advantages as well as creation an accurate IOL calculation method for silicone oil filled eyes could reduce postoperative refraction error that outline significant medical and social problem.

Theta oscillations in the prefrontal-hippocampal circuit do not couple to respiration-related oscillations

Oscillatory activity is thought to coordinate neural computations across brain regions, and theta oscillations are critical for learning and memory. Because the frequency of respiratory-related oscillations (RROs) in rodents can overlap with the frequency of theta in the prefrontal cortex (PFC) and the hippocampus, we asked whether odor-cued working memory may be supported by coupling between these two oscillations. We first confirmed that RROs are propagated to the hippocampus and PFC and that RRO frequency overlaps with canonical theta frequency. However, we found low coherence between RROs and local theta oscillations in the hippocampus-PFC network when the two types of oscillations overlapped in frequency. This effect was observed during all behavioral phases including during movement and while odors were actively sampled when stationary. Despite the similarity in frequency, RROs and theta oscillations therefore appear to be limited to supporting computation in distinct networks, which suggests that sustained long-range coordination between oscillation patterns that depend on separate pacemakers is not necessary to support at least one type of working memory.

New Approaches and Technologies to Improve Accuracy of Acute Otitis Media Diagnosis

Several studies have shown that in recent years incidence of acute otitis media (AOM) has declined worldwide. However, related medical, social, and economic problems for patients, their families, and society remain very high. Better knowledge of potential risk factors for AOM development and more effective preventive interventions, particularly in AOM-prone children, can further reduce disease incidence. However, a more accurate AOM diagnosis seems essential to achieve this goal. Diagnostic uncertainty is common, and to avoid risks related to a disease caused mainly by bacteria, several children without AOM are treated with antibiotics and followed as true AOM cases. The main objective of this manuscript is to discuss the most common difficulties that presently limit accurate AOM diagnosis and the new approaches and technologies that have been proposed to improve disease detection. We showed that misdiagnosis can be dangerous or lead to relevant therapeutic mistakes. The need to improve AOM diagnosis has allowed the identification of a long list of technologies to visualize and evaluate the tympanic membrane and to assess middle-ear effusion. Most of the new instruments, including light field otoscopy, optical coherence tomography, low-coherence interferometry, and Raman spectroscopy, are far from being introduced in clinical practice. Video-otoscopy can be effective, especially when it is used in association with telemedicine, parents’ cooperation, and artificial intelligence. Introduction of otologic telemedicine and use of artificial intelligence among pediatricians and ENT specialists must be strongly promoted in order to reduce mistakes in AOM diagnosis.

Enhancing Coherence Images for Coherent Change Detection: An Example on Vehicle Tracks in Airborne SAR Images

In Synthetic Aperture Radar (SAR) interferometry, one of the most widely used measures for the quality of the interferometric phase is coherence. However, in favorable conditions coherence can also be used to detect subtle changes on the ground, which are not visible in the amplitude images. For such applications, i.e., coherent change detection, it is important to have a good contrast between the unchanged (high-coherence) parts of the scene and the changed (low-coherence) parts. In this paper, an algorithm is introduced that aims at enhancing this contrast. The enhancement is achieved by a combination of careful filtering of the amplitude images and the interferometric phase image. The algorithm is applied to an airborne interferometric SAR image pair recorded by the SmartRadar experimental sensor of Hensoldt Sensors GmbH. The data were recorded during a measurement campaign over the Bann B installations of POLYGONE Range in southern Rhineland-Palatinate (Germany), with a time gap of approximately four hours between the overflights. In-between the overflights, several vehicles were moved on the site and the goal of this work is to enhance the coherence image such that the tracks of these vehicles can be detected as completely as possible in an automated way. Several coherence estimation schemes found in the literature are explored for the enhancement, as well as several commonly used speckle filters. The results of these filtering steps are evaluated visually and quantitatively, showing that the mean gray-level difference between the low-coherence tracks and their high-coherence surroundings could be enhanced by at least 28%. Line extraction is then applied to the best enhancement. The results show that the tracks can be detected much more completely using the coherence contrast enhancement scheme proposed in this paper.

Nanolasers with Feedback as Low-Coherence Illumination Sources for Speckle-Free Imaging: A Numerical Analysis of the Superthermal Emission Regime

Lasers distinguish themselves for the high coherence and high brightness of their radiation, features which have been exploited both in fundamental research and a broad range of technologies. However, emerging applications in the field of imaging, which can benefit from brightness, directionality and efficiency, are impaired by the speckle noise superimposed onto the picture by the interference of coherent scattered fields. We contribute a novel approach to the longstanding efforts in speckle noise reduction by exploiting a new emission regime typical of nanolasers, where low-coherence laser pulses are spontaneously emitted below the laser threshold. Exploring the dynamic properties of this kind of emission in the presence of optical reinjection we show, through the numerical analysis of a fully stochastic approach, that it is possible to tailor some of the properties of the emitted radiation, in addition to exploiting this naturally existing regime. This investigation, therefore, proposes semiconductor nanolasers as potential attractive, miniaturized and versatile future sources of low-coherence radiation for imaging.

Epidemiological associations with genomic variation in SARS-CoV-2

SARS-CoV-2 (CoV) is the etiological agent of the COVID-19 pandemic and evolves to evade both host immune systems and intervention strategies. We divided the CoV genome into 29 constituent regions and applied novel analytical approaches to identify associations between CoV genomic features and epidemiological metadata. Our results show that nonstructural protein 3 (nsp3) and Spike protein (S) have the highest variation and greatest correlation with the viral whole-genome variation. S protein variation is correlated with nsp3, nsp6, and 3′-to-5′ exonuclease variation. Country of origin and time since the start of the pandemic were the most influential metadata associated with genomic variation, while host sex and age were the least influential. We define a novel statistic—coherence—and show its utility in identifying geographic regions (populations) with unusually high (many new variants) or low (isolated) viral phylogenetic diversity. Interestingly, at both global and regional scales, we identify geographic locations with high coherence neighboring regions of low coherence; this emphasizes the utility of this metric to inform public health measures for disease spread. Our results provide a direction to prioritize genes associated with outcome predictors (e.g., health, therapeutic, and vaccine outcomes) and to improve DNA tests for predicting disease status.