Large 2D Coulomb crystals in a radio frequency surface ion trap

We designed and operated a surface ion trap, with an ion-substrate distance of 500\mum, realized with standard printed-circuit-board techniques. The trap has been loaded with up to a few thousand Sr+ ions in the Coulomb-crystal regime. An analytical model of the pseudo-potential allowed us to determine the parameters that drive the trap into anisotropic regimes in which we obtain large (N>150) purely 2D ion Coulomb crystals. These crystals may open a simple and reliable way to experiments on quantum simulations of large 2D systems.Comment: 4 pages, 4 figure

Scanning Tunneling Spectroscopy on the novel superconductor CaC6

We present scanning tunneling microscopy and spectroscopy of the newly discovered superconductor CaC$_6$. The tunneling conductance spectra, measured between 3 K and 15 K, show a clear superconducting gap in the quasiparticle density of states. The gap function extracted from the spectra is in good agreement with the conventional BCS theory with $\Delta(0)$ = 1.6 $\pm$ 0.2 meV. The possibility of gap anisotropy and two-gap superconductivity is also discussed. In a magnetic field, direct imaging of the vortices allows to deduce a coherence length in the ab plane $\xi_{ab}\simeq$ 33 nm

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 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

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

Influence éventuelle de la Chlortetracycline, mélangée à la nourriture du poulet comme adjuvant d’alimentation, sur la teneur en cholestérol des principaux organes et sur l’apparition d’athérosclérose

Dubost P., Ganter P., Julou L., Pascal S., Bressou C. Influence de la chlorté-tracycline, mélangée à la nourriture du poulet comme adjuvant d’alimentation sur la teneur en cholestérol des principaux organes et sur l’apparition d’athérosclérose. In: Bulletin de l'Académie Vétérinaire de France tome 113 n°7, 1960. pp. 399-410

A doubly responsive probe for the detection of Cys4-tagged proteins

International audienceRecombinant proteins bearing a tag are crucial tools for assessing protein location or function. Small tags such as Cys4 tag (tetracysteine; Cys–Cys–X–X–Cys–Cys) are less likely disrupt protein function in the living cell than green fluorescent protein. Herein we report the first example of the design and synthesis of a dual fluorescence and hyperpolarized 129Xe NMR-based sensor of Cys4-tagged proteins. This sensor becomes fluorescent when bound to such Cys4-tagged peptides, and the 129Xe NMR spectrum exhibits a specific signal, characteristic of the biosensor-peptide association

Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors

Adversarial attacks are considered a potentially serious security threat for machine learning systems. Medical image analysis (MedIA) systems have recently been argued to be vulnerable to adversarial attacks due to strong financial incentives and the associated technological infrastructure. In this paper, we study previously unexplored factors affecting adversarial attack vulnerability of deep learning MedIA systems in three medical domains: ophthalmology, radiology, and pathology. We focus on adversarial black-box settings, in which the attacker does not have full access to the target model and usually uses another model, commonly referred to as surrogate model, to craft adversarial examples. We consider this to be the most realistic scenario for MedIA systems. Firstly, we study the effect of weight initialization (ImageNet vs. random) on the transferability of adversarial attacks from the surrogate model to the target model. Secondly, we study the influence of differences in development data between target and surrogate models. We further study the interaction of weight initialization and data differences with differences in model architecture. All experiments were done with a perturbation degree tuned to ensure maximal transferability at minimal visual perceptibility of the attacks. Our experiments show that pre-training may dramatically increase the transferability of adversarial examples, even when the target and surrogate's architectures are different: the larger the performance gain using pre-training, the larger the transferability. Differences in the development data between target and surrogate models considerably decrease the performance of the attack; this decrease is further amplified by difference in the model architecture. We believe these factors should be considered when developing security-critical MedIA systems planned to be deployed in clinical practice.Comment: First three authors contributed equall

Idiosyncratic features in tRNAs participating in bacterial cell wall synthesis

The FemXWv aminoacyl transferase of Weissella viridescens initiates the synthesis of the side chain of peptidoglycan precursors by transferring l-Ala from Ala-tRNAAla to UDP-MurNAc-pentadepsipeptide. FemXWv is an attractive target for the development of novel antibiotics, since the side chain is essential for the last cross-linking step of peptidoglycan synthesis. Here, we show that FemXWv is highly specific for incorporation of l-Ala in vivo based on extensive analysis of the structure of peptidoglycan. Comparison of various natural and in vitro-transcribed tRNAs indicated that the specificity of FemXWv depends mainly upon the sequence of the tRNA although additional specificity determinants may include post-transcriptional modifications and recognition of the esterified amino acid. Site-directed mutagenesis identified cytosines in the G1–C72 and G2–C71 base pairs of the acceptor stem as critical for FemXWv activity in agreement with modeling of tRNAAla in the catalytic cavity of the enzyme. In contrast, semi-synthesis of Ala-tRNAAla harboring nucleotide substitutions in the G3–U70 wobble base pair showed that this main identity determinant of alanyl-tRNA synthetase is non-essential for FemXWv. The different modes of recognition of the acceptor stem indicate that specific inhibition of FemXWv could be achieved by targeting the distal portion of tRNAAla for the design of substrate analogues

Cognitive loading affects motor awareness and movement kinematics but not locomotor trajectories during goal-directed walking in a virtual reality environment.

The primary purpose of this study was to investigate the effects of cognitive loading on movement kinematics and trajectory formation during goal-directed walking in a virtual reality (VR) environment. The secondary objective was to measure how participants corrected their trajectories for perturbed feedback and how participants' awareness of such perturbations changed under cognitive loading. We asked 14 healthy young adults to walk towards four different target locations in a VR environment while their movements were tracked and played back in real-time on a large projection screen. In 75% of all trials we introduced angular deviations of ±5° to ±30° between the veridical walking trajectory and the visual feedback. Participants performed a second experimental block under cognitive load (serial-7 subtraction, counter-balanced across participants). We measured walking kinematics (joint-angles, velocity profiles) and motor performance (end-point-compensation, trajectory-deviations). Motor awareness was determined by asking participants to rate the veracity of the feedback after every trial. In-line with previous findings in natural settings, participants displayed stereotypical walking trajectories in a VR environment. Our results extend these findings as they demonstrate that taxing cognitive resources did not affect trajectory formation and deviations although it interfered with the participants' movement kinematics, in particular walking velocity. Additionally, we report that motor awareness was selectively impaired by the secondary task in trials with high perceptual uncertainty. Compared with data on eye and arm movements our findings lend support to the hypothesis that the central nervous system (CNS) uses common mechanisms to govern goal-directed movements, including locomotion. We discuss our results with respect to the use of VR methods in gait control and rehabilitation