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Abstract 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. The purpose of this study was to comprehensively evaluate automated OCT monitoring for GA compared to reading center-based manual FAF measurements in the largest successful phase 3 clinical trial data of complement inhibitor therapy to date. Automated OCT analysis of RPE loss showed a high and consistent correlation to manual GA measurements on conventional FAF. EZ loss on OCT was generally larger than areas of RPE loss, supporting the hypothesis that EZ loss exceeds underlying RPE loss as a fundamental pathophysiology in GA progression. Automated OCT analysis is well suited to monitor disease progression in GA patients treated in clinical practice and clinical trials.

This case report describes the death of a 73-year-old man who suffered a fatal myocardial infarction following pulmonary vein isolation (PVI) for the treatment of atrial fibrillation. Post-mortem examination and imaging revealed the presence of an atrioesophageal fistula (AEF) leading to gas embolism at various sites of the heart including the right coronary artery. Atrioesophageal fistulas are rare complications of pulmonary vein isolation with high mortality rates.

Global trade is plagued by slow and inefficient manual processes associated with physical documents. Firms are constantly looking for new ways to improve transparency and increase the resilience of their supply chains. This can be solved by the digitalisation of supply chains and the automation of document- and information-sharing processes. Blockchain is touted as a solution to these issues due to its unique combination of features, such as immutability, decentralisation and transparency. A lack of business cases that quantify the costs and benefits causes uncertainty regarding the truth of these claims. This paper explores how the costs and benefits of a blockchain-based solution for digitalising and automating documentation flows in cross-border supply chains compare to a conventional centralised relational database solution. The research described in this paper uses primary data collected through semi-structured interviews with industry experts, as well as secondary data from literature. Two models based on existing services were developed and the costs and benefits compared and then analysed using the Architecture Trade-off Analysis Method (ATAM) and the Analytic Network Process (ANP). Findings from the analysis show that a consortium blockchain solution like TradeLens is the favourable solution for digitalising and automating information flows in cross-border supply chains. [ABSTRACT FROM AUTHOR]

Based upon the vector representation of complex numbers and the vector exponential function, we introduce the vector representation of characteristic functions and consider some of its elementary properties such as its polar representation and a vector power expansion.

Abstract Background Effective dental plaque removal is essential for oral health. Different toothbrush parameters including head-size, filament-diameter and interdent-height and different brushing movements like horizontal, rotating and vertical may affect plaque removal efficacy. The purpose of the study was to examine plaque removal efficacy of different design parameters of manual toothbrushes. Methods Eight manual toothbrushes were tested using a validated robot test to examine efficacy of toothbrush on replicated human teeth. Characteristics tested were: (i) head-size, (ii) filament-diameter, (iii) cutting-height, (iv) hardness, (v) interdental-height. Each test ran five times in horizontal, rotating, vertical movements. Simulated Plaque removal was evaluated using automated plaque planimetry: 30 fields/tooth, 13 areas representing buccal, lingual, proximal tooth sites. The Kolmogorov-Smirnov-test was applied to test tooth surface variables for normal distribution of plaque removal values. Parameters were analysed by independent two-sample t-test to assess mean differences. Where null hypothesis of normality was rejected, the Wilcoxon-Mann-Whitney-U-test was used. Results Plaque removal was significantly better with toothbrush having smaller head-size (compact vs. full-size); smaller filament-diameter (0.12 mm vs. 0.15 mm); larger cutting-height (12 mm vs. 9 mm); softer filaments (0.15 or 0.18 mm vs. 0.23 mm) and greater interdent-height difference (8.5/11 mm vs. 10/11 mm). Conclusions Manual brushes allowing filaments free to flex with longer, softer and/or having a difference in filament length overall removed significantly more simulated plaque as compared to more standard flat trim, stiff brushes with shorter, harder bristles and a larger head size. While limited by the in vitro nature of the study design, this indicates that the advances in toothbrush design can further enhance plaque removal.

Background: This longitudinal prospective study aimed to assess orthodontic patients’ immune system response to metal ion release in saliva. Methods: Thirty adult patients (18–35 years) were equally divided into three groups: groups at the end (G1) and beginning (G2) of multibracket appliances (MBA) treatment and a non-treated control group (G3). Participants were evaluated at four timepoints within 21 days, with saliva samples being analyzed for metal ion concentrations and blood for the lymphocyte transformation test (LTT). Results: There were no significant differences between groups or timepoints for saliva. LTT analyses revealed hypersensitivity in one-third of all patients and 50% of G2 for nickel, with three developing sensitizations after MBA insertion. All nickel-sensitized patients exhibited varying elevated saliva nickel concentrations. The most nickel-sensitized patients had low ion saliva loads. In borderline nickel-sensitization cases, saliva ion concentrations were up to 20 times higher than the reference. Hypersensitivity to palladium, gold, and mercury was also observed. Conclusions: These findings indicate that increased MBA ion release was not inherently linked to the immune response (Type-IV sensitization), as reactions occurred even with ion levels below thresholds. This underlines the need for a comprehensive evaluation of the immune response to metal ion release in orthodontic patients.

Abstract Geographic atrophy (GA) represents a late stage of age-related macular degeneration, which leads to irreversible vision loss. With the first successful therapeutic approach, namely complement inhibition, huge numbers of patients will have to be monitored regularly. Given these perspectives, a strong need for automated GA segmentation has evolved. The main purpose of this study was the clinical validation of an artificial intelligence (AI)-based algorithm to segment a topographic 2D GA area on a 3D optical coherence tomography (OCT) volume, and to evaluate its potential for AI-based monitoring of GA progression under complement-targeted treatment. 100 GA patients from routine clinical care at the Medical University of Vienna for internal validation and 113 patients from the FILLY phase 2 clinical trial for external validation were included. Mean Dice Similarity Coefficient (DSC) was 0.86 ± 0.12 and 0.91 ± 0.05 for total GA area on the internal and external validation, respectively. Mean DSC for the GA growth area at month 12 on the external test set was 0.46 ± 0.16. Importantly, the automated segmentation by the algorithm corresponded to the outcome of the original FILLY trial measured manually on fundus autofluorescence. The proposed AI approach can reliably segment GA area on OCT with high accuracy. The availability of such tools represents an important step towards AI-based monitoring of GA progression under treatment on OCT for clinical management as well as regulatory trials.