Ancestral genome estimation reveals the history of ecological diversification in Agrobacterium

Horizontal gene transfer (HGT) is considered as a major source of innovation in bacteria, and as such is expected to drive adaptation to new ecological niches. However, among the many genes acquired through HGT along the diversification history of genomes, only a fraction may have actively contributed to sustained ecological adaptation. We used a phylogenetic approach accounting for the transfer of genes (or groups of genes) to estimate the history of genomes in Agrobacterium biovar 1, a diverse group of soil and plant-dwelling bacterial species. We identified clade-specific blocks of cotransferred genes encoding coherent biochemical pathways that may have contributed to the evolutionary success of key Agrobacterium clades. This pattern of gene coevolution rejects a neutral model of transfer, in which neighboring genes would be transferred independently of their function and rather suggests purifying selection on collectively coded acquired pathways. The acquisition of these synapomorphic blocks of cofunctioning genes probably drove the ecological diversification of Agrobacterium and defined features of ancestral ecological niches, which consistently hint at a strong selective role of host plant rhizospheres

Exploring adversarial attacks in federated learning for medical imaging

Federated learning offers a privacy-preserving framework for medical image analysis but exposes the system to adversarial attacks. This paper aims to evaluate the vulnerabilities of federated learning networks in medical image analysis against such attacks. Employing domain-specific MRI tumor and pathology imaging datasets, we assess the effectiveness of known threat scenarios in a federated learning environment. Our tests reveal that domain-specific configurations can increase the attacker's success rate significantly. The findings emphasize the urgent need for effective defense mechanisms and suggest a critical re-evaluation of current security protocols in federated medical image analysis systems

The Leiodolide B Puzzle

Out of options? Even though a systematic approach was chosen, which led to a set of four diastereomeric macrolides modeled around the proposed structure of leiodolide B (see picture), the puzzle concerning the stereostructure of this cytotoxic metabolite derived from a deep-sea sponge still remains unsolved

The Hidden Adversarial Vulnerabilities of Medical Federated Learning

In this paper, we delve into the susceptibility of federated medical image analysis systems to adversarial attacks. Our analysis uncovers a novel exploitation avenue: using gradient information from prior global model updates, adversaries can enhance the efficiency and transferability of their attacks. Specifically, we demonstrate that single-step attacks (e.g. FGSM), when aptly initialized, can outperform the efficiency of their iterative counterparts but with reduced computational demand. Our findings underscore the need to revisit our understanding of AI security in federated healthcare settings

Spectral Data Augmentation Techniques to quantify Lung Pathology from CT-images

Data augmentation is of paramount importance in biomedical image processing tasks, characterized by inadequate amounts of labelled data, to best use all of the data that is present. In-use techniques range from intensity transformations and elastic deformations, to linearly combining existing data points to make new ones. In this work, we propose the use of spectral techniques for data augmentation, using the discrete cosine and wavelet transforms. We empirically evaluate our approaches on a CT texture analysis task to detect abnormal lung-tissue in patients with cystic fibrosis. Empirical experiments show that the proposed spectral methods perform favourably as compared to the existing methods. When used in combination with existing methods, our proposed approach can increase the relative minor class segmentation performance by 44.1% over a simple replication baseline.Comment: 5 pages including references, accepted as Oral presentation at IEEE ISBI 202

Certified quantum non-demolition measurement of material systems

An extensive debate on quantum non-demolition (QND) measurement, reviewed in Grangier et al. [Nature, {\bf 396}, 537 (1998)], finds that true QND measurements must have both non-classical state-preparation capability and non-classical information-damage tradeoff. Existing figures of merit for these non-classicality criteria require direct measurement of the signal variable and are thus difficult to apply to optically-probed material systems. Here we describe a method to demonstrate both criteria without need for to direct signal measurements. Using a covariance matrix formalism and a general noise model, we compute meter observables for QND measurement triples, which suffice to compute all QND figures of merit. The result will allow certified QND measurement of atomic spin ensembles using existing techniques.Comment: 11 pages, zero figure

Quantification of Lung Abnormalities in Cystic Fibrosis using Deep Networks

Cystic fibrosis is a genetic disease which may appear in early life with structural abnormalities in lung tissues. We propose to detect these abnormalities using a texture classification approach. Our method is a cascade of two convolutional neural networks. The first network detects the presence of abnormal tissues. The second network identifies the type of the structural abnormalities: bronchiectasis, atelectasis or mucus plugging.We also propose a network computing pixel-wise heatmaps of abnormality presence learning only from the patch-wise annotations. Our database consists of CT scans of 194 subjects. We use 154 subjects to train our algorithms and the 40 remaining ones as a test set. We compare our method with random forest and a single neural network approach. The first network reaches an accuracy of 0,94 for disease detection, 0,18 higher than the random forest classifier and 0,37 higher than the single neural network. Our cascade approach yields a final class-averaged F1-score of 0,33, outperforming the baseline method and the single network by 0,10 and 0,12.Comment: SPIE - Medical Imaging 2018: Image Processin

IL-6 gene amplification and expression in human glioblastomas

The aggressiveness of human gliomas appears to be correlated with the upregulation of interleukin 6 (IL-6) gene. Using quantitative PCR methods, we detected amplification and expression of the IL-6 gene in 5 of 5 primary glioblastoma samples and in 4 of 5 glioblastoma cell lines. This finding suggests that the amplification of IL-6 gene may be a common feature in glioblastomas and may contribute to the IL-6 over-expression. © 2001 Cancer Research Campaign http://www.bjcancer.co

Acute mesenteric ischaemia in refractory shock on veno-arterial extracorporeal membrane oxygenation

Background: Acute mesenteric ischaemia is a severe complication in critically ill patients, but has never been evaluated in patients on veno-arterial extracorporeal membrane oxygenation (V-A ECMO). This study was designed to determine the prevalence of mesenteric ischaemia in patients supported by V-A ECMO and to evaluate its risk factors, as well as to appreciate therapeutic modalities and outcome. Methods: In a retrospective single centre study (January 2013 to January 2017), all consecutive adult patients who underwent V-A ECMO were included, with exclusion of those dying in the first 24 hours. Diagnosis of mesenteric ischaemia was performed using digestive endoscopy, computed tomography scan or first-line laparotomy. Results: One hundred and fifty V-A ECMOs were implanted (65 for post-cardiotomy shock, 85 for acute cardiogenic shock, including 39 patients after refractory cardiac arrest). Overall, median age was 58 (48-69) years and mortality 56%. Acute mesenteric ischaemia was suspected in 38 patients, with a delay of four (2-7) days after ECMO implantation, and confirmed in 14 patients, that is, a prevalence of 9%. Exploratory laparotomy was performed in six out of 14 patients, the others being too unstable to undergo surgery. All patients with mesenteric ischaemia died. Independent risk factors for developing mesenteric ischaemia were renal replacement therapy (odds ratio (OR) 4.5, 95% confidence interval (CI) 1.3-15.7, p=0.02) and onset of a second shock within the first five days (OR 7.8, 95% CI 1.5-41.3, p=0.02). Conversely, early initiation of enteral nutrition was negatively associated with mesenteric ischaemia (OR 0.15, 95% CI 0.03-0.69, p=0.02). Conclusions: Acute mesenteric ischaemia is a relatively frequent but dramatic complication among patients on V-A ECMO