Comparison of Intravitreal Bevacizumab versus Triamcinolone for the Treatment of Diffuse Diabetic Macular Edema

Background: Our purpose was to compare the effect of triamcinolone and bevacizumab (Avastin) on the retinal thickness and functional outcome in patients with diabetic macular edema. Methods and Materials: A collective of 32 patients, who had been treated by a single 4.0-mg intravitreal triamcinolone injection (group 1), was matched to 32 patients ('matched pairs'), who had received 3 injections of 1.25 mg of bevacizumab within 3 months in 4-week intervals (group 2). The outcome variables were changes in best corrected visual acuity (VA) and central retinal thickness 3 months after therapy. Results: Both groups did not differ regarding preoperative VA and central retinal thickness measured by optical coherence tomography. The baseline mean VA was 0.72 +/- 0.39 logMAR in group 1 and 0.73 +/- 0.39 logMAR in group 2 (p = 0.709). The mean central retinal thickness measured by optical coherence tomography was 548 +/- 185 mu m in group 1 and 507 +/- 192 mu m in group 2. While the patients in group 1 experienced a slight increase in VA of on average 0.7 lines following a single triamcinolone injection to a mean of 0.64 +/- 0.40 logMAR (p = 0.066) after 3 months, the patients in group 2 showed almost no effect on VA with an average increase of 0.2 lines to a mean VA of 0.72 +/- 0.30 logMAR (p = 0.948) following 3 intravitreal injections of bevacizumab. Comparing the effect on VA between both groups no statistically significant difference (p = 0.115) was noted. Concerning decrease in central retinal thickness both therapies were highly effective (p < 0.001 each), again, without statistically significant difference between the groups (p < 0.128). Conclusion: Our data suggest that a single triamcinolone injection may be as effective as a 3 times repeated intravitreal administration of bevacizumab for the treatment of diabetic macular edema. Further prospective trials should be performed. Copyright (C) 2010 S. Karger AG, Base

Sandbox:Creating and analysing synthetic sediment sections with R

Past environmental information is typically inferred from proxy data contained in accretionary sediments. The validity of proxy data and analysis workflows are usually assumed implicitly, with systematic tests and uncertainty estimates restricted to modern analogue studies or reduced-complexity case studies. However, a more generic and consistent approach to exploring the validity and variability of proxy functions would be to translate a sediment section into a model scenario: a “virtual twin”. Here, we introduce a conceptual framework and numerical tool set that allows the definition and analysis of synthetic sediment sections. The R package sandbox describes arbitrary stratigraphically consistent deposits by depth-dependent rules and grain-specific parameters, allowing full scalability and flexibility. Virtual samples can be taken, resulting in discrete grain mixtures with defined parameters. These samples can be virtually prepared and analysed, for example, to test hypotheses. We illustrate the concept of sandbox, explain how a sediment section can be mapped into the model and explore geochronological research questions related to the effects of sample geometry and grain-size-specific age inheritance. We summarise further application scenarios of the model framework, relevant for but not restricted to the broader geochronological community.CREDit - Chronological REference Datasets and Sites (CREDit) towards improved accuracy and precision in luminescence-based chronologie

Correlation between weather and incidence of selected ophthalmological diagnoses: a database analysis

Purpose: Our aim was to correlate the overall patient volume and the incidence of several ophthalmological diseases in our emergency department with weather data. Patients and methods: For data analysis, we used our clinical data warehouse and weather data. We investigated the weekly overall patient volume and the average weekly incidence of all encoded diagnoses of "conjunctivitis", "foreign body", "acute iridocyclitis", and "corneal abrasion". A Spearman's correlation was performed to link these data with the weekly average sunshine duration, temperature, and wind speed. Results: We noticed increased patient volume in correlation with increasing sunshine duration and higher temperature. Moreover, we found a positive correlation between the weekly incidences of conjunctivitis and of foreign body and weather data. Conclusion: The results of this data analysis reveal the possible influence of external conditions on the health of a population and can be used for weather-dependent resource allocation

MixUp-MIL: Novel Data Augmentation for Multiple Instance Learning and a Study on Thyroid Cancer Diagnosis

Multiple instance learning exhibits a powerful approach for whole slide image-based diagnosis in the absence of pixel- or patch-level annotations. In spite of the huge size of hole slide images, the number of individual slides is often rather small, leading to a small number of labeled samples. To improve training, we propose and investigate different data augmentation strategies for multiple instance learning based on the idea of linear interpolations of feature vectors (known as MixUp). Based on state-of-the-art multiple instance learning architectures and two thyroid cancer data sets, an exhaustive study is conducted considering a range of common data augmentation strategies. Whereas a strategy based on to the original MixUp approach showed decreases in accuracy, the use of a novel intra-slide interpolation method led to consistent increases in accuracy.Comment: MICCAI'23, https://gitlab.com/mgadermayr/mixupmi

MixUp-MIL: A Study on Linear & Multilinear Interpolation-Based Data Augmentation for Whole Slide Image Classification

For classifying digital whole slide images in the absence of pixel level annotation, typically multiple instance learning methods are applied. Due to the generic applicability, such methods are currently of very high interest in the research community, however, the issue of data augmentation in this context is rarely explored. Here we investigate linear and multilinear interpolation between feature vectors, a data augmentation technique, which proved to be capable of improving the generalization performance classification networks and also for multiple instance learning. Experiments, however, have been performed on only two rather small data sets and one specific feature extraction approach so far and a strong dependence on the data set has been identified. Here we conduct a large study incorporating 10 different data set configurations, two different feature extraction approaches (supervised and self-supervised), stain normalization and two multiple instance learning architectures. The results showed an extraordinarily high variability in the effect of the method. We identified several interesting aspects to bring light into the darkness and identified novel promising fields of research.Comment: for code and data, see gitlab repo: https://gitlab.com/mgadermayr/mixupmil. arXiv admin note: substantial text overlap with arXiv:2211.0586

Towards Secure Urban Infrastructures: Cyber Security Challenges to Information and Communication Technology in Smart Cities

The growth of cities continues to be a global megatrend. As more and more people live in urban areas and urban services and infrastructures are under growing strain, technologies are increasingly being researched and used to make city life more efficient and comfortable. As a result, so-called “Smart Cities” have complex IT infrastructures and cyber-physical systems such as sensor/actuator networks for the general population and are developing worldwide. Urban infrastructure must be secured against attacks, ensuring reliable and resilient services for citizens as well as privacy and data security. This paper introduces selected challenges faced by infrastructure providers, citizens and decision-makers in handling attacks aimed at information and communication technologies (ICT) of urban infrastructures and presents current research avenues for tackling cyberattacks and for developing tools for creating, portraying and disseminating actionable information as one important response to security challenges. It then presents findings from a representative survey conducted in Germany (N=1091) on the experiences and perceptions of citizens concerning the relevance of cyberattacks will be presented

Exercise-Induced Th17 Lymphocyte Response and Their Relationship to Cardiovascular Disease Risk Factors in Obese, Post-Menopausal Women

Obesity-induced inflammation promotes type 2 diabetes and cardiovascular disease (CVD). A causative link between adaptive immunity and pathogenesis of obesity-associated diseases has been established. PURPOSE: To examine the effects of exercise on circulating T-helper (Th) 17 lymphocytes in overweight/obese post-menopausal women. METHODS: Twenty-seven overweight/obese women (BMI 32.7 ± 5.1 kg×m-2, 55-75 yr) were randomly assigned to the exercise (EX, n=14) or education (ED, n=13) groups. EX performed a 25-min walk (75-80% HRR) and 2 sets of 8 resistance exercises (70-80% 1RM) with blood samples obtained at: pre-exercise, post-exercise, one-hour and two-hour post-exercise. Blood samples were obtained at the same time points in resting ED. Whole blood was stained using the extracellular markers CD4, CD196, CD194, CD26, and CD161 to identify Th17 lymphocytes via flow cytometry. RESULTS: Acute exercise increased lymphocyte number (p = 0.0001), but decreased percent of CD4+ cells (p = 0.019) at PO. We observed a diurnal response (main effect) where CD26 expression was significantly lower by 2H compared to PRE (PR: 10631 ± 208; 2H: 9961 ± 271 MFI). There was a main effect (p=0.024) of group for CD26 expression (EX: 10745 ± 251; ED 9880 ± 260 MFI). The difference may have been driven by the apparent exercise-induced plateau of CD26 expression at 2H, which minimized the diurnal reduction observed in ED (p \u3e 0.05). There was a tendency (p = 0.09) for a group x time interaction in Th17 cell number at 1HR (EX = 25.3 ± 4.8; ED =37.2 ± 5.2 x 103 cells×ml-1). BMI was significantly correlated with Th17% (r = 0.5, p = 0.008). HbA1c was positively correlated with Th17 number and percentage (r = 0.598, p = 0.003; r = 0.614, p = 0.001, respectively), as well as CCR4+ Th17 cells (r = 0.421, p = 0.036). Multiple regression analysis revealed that BMI, fat percentage, and HbA1c were significant predictors (69%, r2 = 0.685) of Th17 cell %. CONCLUSION: Exercise reduced CD26 expression, the receptor responsible for Th17 cell migration, but did not significantly alter Th17 concentration (p = 0.09). CD26 upregulation may indicate that Th17 cells, via chemokine release, promote the stress-dependent migratory response of T-helper cells (CD4+). Obese individuals may experience a preferential differentiation of Th17 cells, based on their association with adiposity (BMI and %fat) and HbA1c