Features of intermediate and late dry age-related macular degeneration on adaptive optics ophthalmoscopy: Pinnacle Study Report 8.

Background/objectives: Adaptive optics ophthalmoscopy (AOO) has the potential to provide insights into AMD pathology and to assess the risk of progression. We aim to utilise AOO to describe detailed features of intermediate AMD and to characterise microscopic changes during atrophy development.

Subjects/methods: Patients with intermediate AMD were recruited into PINNACLE, a prospective observational cohort study.

SD-LayerNet: Robust and label-efficient retinal layer segmentation via anatomical priors.

Background And Objectives: Automated, anatomically coherent retinal layer segmentation in optical coherence tomography (OCT) is one of the most important components of retinal disease management. However, current methods rely on large amounts of labeled data, which can be difficult and expensive to obtain. In addition, these systems tend often propose anatomically impossible results, which undermines their clinical reliability.

Artificial intelligence in assessing progression of age-related macular degeneration.

The human population is steadily growing with increased life expectancy, impacting the prevalence of age-dependent diseases, including age-related macular degeneration (AMD). Health care systems are confronted with an increasing burden with rising patient numbers accompanied by ongoing developments of therapeutic approaches. Concurrent advances in imaging modalities provide eye care professionals with a large amount of data for each patient.

Mental health of non-binary youth: a systematic review and meta-analysis.

Background: Non-binary identities are increasingly recognized within the spectrum of gender diversity, yet there is a dearth of research exploring the mental health challenges specific to this population. Therefore, this systematic review and meta-analysis aimed to comprehensively assess the mental health outcomes of non-binary youth in comparison to their transgender and cisgender peers.

Methods: A systematic search was conducted to identify relevant studies across three electronic databases (PubMed, Scopus, Web of Science) covering the period from inception to October 2023.

Evolution of the conformational dynamics of the molecular chaperone Hsp90.

Hsp90 is a molecular chaperone of central importance for protein homeostasis in the cytosol of eukaryotic cells, with key functional and structural traits conserved from yeast to man. During evolution, Hsp90 has gained additional functional importance, leading to an increased number of interacting co-chaperones and client proteins. Here, we show that the overall conformational transitions coupled to the ATPase cycle of Hsp90 are conserved from yeast to humans, but cycle timing as well as the dynamics are significantly altered.

AI in the clinical management of GA: A novel therapeutic universe requires novel tools.

Regulatory approval of the first two therapeutic substances for the management of geographic atrophy (GA) secondary to age-related macular degeneration (AMD) is a major breakthrough following failure of numerous previous trials. However, in the absence of therapeutic standards, diagnostic tools are a key challenge as functional parameters in GA are hard to provide. The majority of anatomical biomarkers are subclinical, necessitating advanced and sensitive image analyses.

Quantitative comparison of automated OCT and conventional FAF-based geographic atrophy measurements in the phase 3 OAKS/DERBY trials.

With the approval of the first two substances for the treatment of geographic atrophy (GA) secondary to age-related macular degeneration (AMD), a standardized monitoring of patients treated with complement inhibitors in clinical practice is needed. Optical coherence tomography (OCT) provides high-resolution access to the retinal pigment epithelium (RPE) and neurosensory layers, such as the ellipsoid zone (EZ), which further enhances the understanding of disease progression and therapeutic effects in GA compared to conventional fundus autofluorescence (FAF). In addition, artificial intelligence-based methodology allows the identification and quantification of GA-related pathology on OCT in an objective and standardized manner.

Metadata-enhanced contrastive learning from retinal optical coherence tomography images.

Deep learning has potential to automate screening, monitoring and grading of disease in medical images. Pretraining with contrastive learning enables models to extract robust and generalisable features from natural image datasets, facilitating label-efficient downstream image analysis. However, the direct application of conventional contrastive methods to medical datasets introduces two domain-specific issues.

Disease Activity and Therapeutic Response to Pegcetacoplan for Geographic Atrophy Identified by Deep Learning-Based Analysis of OCT.

Purpose: To quantify morphological changes of the photoreceptors (PRs) and retinal pigment epithelium (RPE) layers under pegcetacoplan therapy in geographic atrophy (GA) using deep learning-based analysis of OCT images.

Design: Post hoc longitudinal image analysis.

Participants: Patients with GA due to age-related macular degeneration from 2 prospective randomized phase III clinical trials (OAKS and DERBY).

Sequence of Morphological Changes Preceding Atrophy in Intermediate AMD Using Deep Learning.

Purpose: Investigating the sequence of morphological changes preceding outer plexiform layer (OPL) subsidence, a marker preceding geographic atrophy, in intermediate AMD (iAMD) using high-precision artificial intelligence (AI) quantifications on optical coherence tomography imaging.

Methods: In this longitudinal observational study, individuals with bilateral iAMD participating in a multicenter clinical trial were screened for OPL subsidence and RPE and outer retinal atrophy. OPL subsidence was segmented on an A-scan basis in optical coherence tomography volumes, obtained 6-monthly with 36 months follow-up.

Deep Neural Networks for Automated Outer Plexiform Layer Subsidence Detection on Retinal OCT of Patients With Intermediate AMD.

Purpose: The subsidence of the outer plexiform layer (OPL) is an important imaging biomarker on optical coherence tomography (OCT) associated with early outer retinal atrophy and a risk factor for progression to geographic atrophy in patients with intermediate age-related macular degeneration (AMD). Deep neural networks (DNNs) for OCT can support automated detection and localization of this biomarker.

Methods: The method predicts potential OPL subsidence locations on retinal OCTs.

An interactive task-based method for the avoidance of metal artifacts in CBCT.

Purpose: Intraoperative cone-beam CT imaging enables 3D validation of implant positioning and fracture reduction for orthopedic and trauma surgeries. However, the emergence of metal artifacts, especially in the vicinity of metallic objects, severely degrades the clinical value of the imaging modality. In previous works, metal artifact avoidance (MAA) methods have been shown to reduce metal artifacts by adapting the scanning trajectory.

Treatment trajectories of gender incongruent Austrian youth seeking gender-affirming hormone therapy.

Objective: The aim of this study was to describe the treatment trajectories of Austrian children and adolescents with gender incongruence seeking gender-affirming medical care.

Methods: Patients who presented with gender incongruence at the pediatric outpatient clinic for differences in sex development at a large university hospital in Austria from January 2008 to December 2022 were included in a retrospective chart review, and analyzed regarding referral numbers, patient characteristics, treatment trajectories, fertility preservation, and legal gender marker changes.

Results: Of 310 eligible patients, 230 (74.

Body Mass Index Distributions and Obesity Prevalence in a Transgender Youth Cohort - A Retrospective Analysis.

Purpose: To evaluate differences in auxological parameters between transgender and cisgender adolescents.

Methods: Retrospective analysis of auxological data of 269 transgender and gender diverse patients (75% assigned female at birth or AFAB, 25% assigned male at birth or AMAB) at the outpatient clinic for Pediatric Endocrinology at the Vienna General Hospital. All were treatment naïve at initial measurement.

[Complement inhibition treatment for geographic atrophy (GA): functional and morphological efficacy and relevant biomarkers in clinical practice].

The approval of complement inhibitory therapeutic agents for the treatment of geographic atrophy (GA) has highlighted the need for reliable and reproducible measurement of disease progression and therapeutic efficacy. Due to its availability and imaging characteristics optical coherence tomography (OCT) is the method of choice. Using OCT analysis based on artificial intelligence (AI), the therapeutic efficacy of pegcetacoplan was demonstrated at the levels of both the retinal pigment epithelium (RPE) and photoreceptors (PR).

3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression From Longitudinal OCTs.

Self-supervised learning (SSL) has emerged as a powerful technique for improving the efficiency and effectiveness of deep learning models. Contrastive methods are a prominent family of SSL that extract similar representations of two augmented views of an image while pushing away others in the representation space as negatives. However, the state-of-the-art contrastive methods require large batch sizes and augmentations designed for natural images that are impractical for 3D medical images.

Morph-SSL: Self-Supervision With Longitudinal Morphing for Forecasting AMD Progression From OCT Volumes.

The lack of reliable biomarkers makes predicting the conversion from intermediate to neovascular age-related macular degeneration (iAMD, nAMD) a challenging task. We develop a Deep Learning (DL) model to predict the future risk of conversion of an eye from iAMD to nAMD from its current OCT scan. Although eye clinics generate vast amounts of longitudinal OCT scans to monitor AMD progression, only a small subset can be manually labeled for supervised DL.

Deep Learning-Based Prediction of Individual Geographic Atrophy Progression from a Single Baseline OCT.

Objective: To identify the individual progression of geographic atrophy (GA) lesions from baseline OCT images of patients in routine clinical care.

Design: Clinical evaluation of a deep learning-based algorithm.

Subjects: One hundred eighty-four eyes of 100 consecutively enrolled patients.

Three-year follow-up analysis of the short-stitch versus long-stitch technique for elective midline abdominal closure randomized-controlled (ESTOIH) trial.

Background: Clinical trials have shown reduced incisional hernia rates 1 year after elective median laparotomy closure using a short-stitch technique. With hernia development continuing beyond the first postoperative year, we aimed to compare incisional hernias 3 years after midline closure using short or long stitches in patients from the ESTOIH trial.

Methods: The ESTOIH trial was a prospective, multicenter, parallel-group, double-blind, randomized-controlled study of primary elective midline closure.

Lipidation and PEGylation Strategies to Prolong the Half-Life of a Nanomolar EphA4 Receptor Antagonist.

The EphA4 receptor tyrosine kinase plays a role in neurodegenerative diseases, inhibition of nerve regeneration, cancer progression and other diseases. Therefore, EphA4 inhibition has potential therapeutic value. Selective EphA4 kinase inhibitors are not available, but we identified peptide antagonists that inhibit ephrin ligand binding to EphA4 with high specificity.

Automated deep learning-based AMD detection and staging in real-world OCT datasets (PINNACLE study report 5).

Real-world retinal optical coherence tomography (OCT) scans are available in abundance in primary and secondary eye care centres. They contain a wealth of information to be analyzed in retrospective studies. The associated electronic health records alone are often not enough to generate a high-quality dataset for clinical, statistical, and machine learning analysis.

Lectin-anticancer peptide fusion demonstrates a significant cancer-cell-selective cytotoxic effect and inspires the production of "clickable" anticancer peptide in Escherichia coli.

Targeted killing of tumor cells while protecting healthy cells is the pressing priority in cancer treatment. Lectins that target a specific glycan marker abundant in cancer cells can be valuable new tools for selective cancer cell killing. The lectin Shiga-like toxin 1 B subunit (Stx1B) is an example that specifically binds globotriaosylceramide (CD77 or Gb3), which is overexpressed in certain cancers.

Comparison of Novel Volumetric Microperimetry Metrics in Intermediate Age-Related Macular Degeneration: PINNACLE Study Report 3.

Purpose: To investigate and compare novel volumetric microperimetry (MP)-derived metrics in intermediate age-related macular degeneration (iAMD), as current MP metrics show high variability and low sensitivity.

Methods: This is a cross-sectional analysis of microperimetry baseline data from the multicenter, prospective PINNACLE study (ClinicalTrials.gov NCT04269304).