Effect of treatment with epoetin-β on survival, tumour progression and thromboembolic events in patients with cancer: an updated meta-analysis of 12 randomised controlled studies including 2301 patients

Epoetin-β is used to treat patients with metastatic cancer undergoing chemotherapy to alleviate the symptoms of anaemia, reduce the risk of blood transfusions and improve quality of life. This meta-analysis of 12 randomised, controlled studies evaluated the impact of epoetin-β on overall survival, tumour progression and thromboembolic events (TEEs). A total of 2297 patients were included in the analysis (epoetin-β, n=1244; control, n=1053; 65% solid and 35% nonmyeloid haematological malignancies). A prespecified subgroup analysis assessed the effects in patients with a baseline Hb⩽11 g dl−1, corresponding to current European Organisation for Research and Treatment of Cancer (EORTC) guidelines. No statistically significant effect on mortality was observed with epoetin-β vs control, both overall (hazard ratio (HR)=1.13; 95% CI: 0.87, 1.46; P=0.355) and in patients with baseline Hb⩽11 g dl−1 (HR=1.09; 95% CI: 0.80, 1.47; P=0.579). A trend for a beneficial effect on tumour progression was seen overall (HR=0.85; 95% CI: 0.72, 1.01; P=0.072) and in patients with an Hb⩽11 g dl−1 (HR=0.80; 95% CI: 0.65, 0.99; P=0.041). An increased frequency of TEEs was seen with epoetin-β vs control (7 vs 4% of patients); however, TEEs-related mortality was similar in both groups (1% each). The results of this meta-analysis indicate that when used within current EORTC treatment guidelines, epoetin-β has no negative impact on survival, tumour progression or TEEs-related mortality

Chemical composition of manganese nodules from the Northeast Pacific belt

The nodules examined were sampled during the R/V Valdivia cruises VA 04, 05, 09, 13/1, and 18. The majority of these samples was taken from a region extending from 135°w to 155°W and from 5° N to 15°N. In the pelagic area investigated a very fine-grained siliceous ooze to siliceous clay is dominant. Three genetic types have been determined: type A (diagenetic) mainly on slopes or in the vicinity of seamounts; type B (Hydrogenetic) in the center of the basin regions and type C (dia-hydrogenetic) characterized by a vertical dual structure with a smooth top and and a rough gritty bottom separated by a distintive knotted botryoidal equatorial band. Chemical analyses have been performed on dried samples

Detecting Face Morphing Attacks by Analyzing the Directed Distances of Facial Landmarks Shifts

Face morphing attacks create face images that are verifiable to multiple identities. Associating such images to identity documents lead to building faulty identity links, causing attacks on operations like border crossing. Most of previously proposed morphing attack detection approaches directly classified features extracted from the investigated image. We discuss the operational opportunity of having a live face probe to support the morphing detection decision and propose a detection approach that take advantage of that. Our proposed solution considers the facial landmarks shifting patterns between reference and probe images. This is represented by the directed distances to avoid confusion with shifts caused by other variations. We validated our approach using a publicly available database, built on 549 identities. Our proposed detection concept is tested with three landmark detectors and proved to outperform the baseline concept based on handcrafted and transferable CNN features

On the Detection of GAN-Based Face Morphs Using Established Morph Detectors

Face recognition systems (FRS) have been found to be highly vulnerable to face morphing attacks. Due to this severe security risk, morph detection systems do not only need to be robust against classical landmark-based face morphing approach (LMA), but also future attacks such as neural network based morph generation techniques. The focus of this paper lies on an experimental evaluation of the morph detection capabilities of various state-of-the-art morph detectors with respect to a recently presented novel face morphing approach, MorGAN, which is based on Generative Adversarial Networks (GANs). In this work, existing detection algorithms are confronted with different attack scenarios: known and unknown attacks comprising different morph types (LMA and MorGAN). The detectors’ performance results are highly dependent on the features used by the detection algorithms. In addition, the image quality of the morphed face images produced with the MorGAN approach is assessed using well-established no-reference image quality metrics and compared to LMA morphs. The results indicate that the image quality of MorGAN morphs is more similar to bona fide images compared to classical LMA morphs