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Nitric oxide, a ubiquitous molecule found throughout the natural world, is a key molecule implicated in many central and benefic molecular pathways and has a well-established role in the function of the central nervous system, as numerous studies have previously shown. Dysregulation of its metabolism, mainly the upregulation of nitric oxide production, has been proposed as a trigger and/or aggravator for many neurological affections. Increasing evidence supports the implication of this molecule in prevalent neurodegenerative diseases, such as Parkinson’s disease, Alzheimer’s disease, or amyotrophic lateral sclerosis. The mechanisms proposed for its neurotoxicity mainly center around the increased quantities of nitric oxide that are produced in the brain, their cause, and, most importantly, the pathological metabolic cascades created. These cascades lead to the formation of neuronal toxic substances that impair the neurons’ function and structure on multiple levels. The purpose of this review is to present the main causes of increased pathological production, as well as the most important pathophysiological mechanisms triggered by nitric oxide, mechanisms that could help explain a part of the complex picture of neurodegenerative diseases and help develop targeted therapies.

Implantable medical devices, sensors and wearables are widely deployed today. However, establishing a secure wireless communication channel to these devices is a major challenge, amongst others due to the constraints on energy consumption and the need to obtain immediate access in emergencies. To address this issue, researchers have proposed various key agreement protocols based on the measurement of physiological signals such as a person's heart signal. At the core of such protocols are fuzzy cryptographic primitives that allow to agree on a shared secret based on several simultaneous, noisy measurements of the same signal. So far, although many fuzzy primitives have been proposed, there is no comprehensive evaluation and comparison yet of the overhead that such methods incur on resource-constrained embedded devices. In this paper, we study the feasibility of six types of fuzzy cryptographic primitives on embedded devices for 128-bit key agreement. We configure several variants for each fuzzy primitive under different parameter selections and mismatch rates of the physiological signal measurements on an MSP430 microcontroller, and then measure and compare their energy consumption and communication overhead. The most efficient constructions consume between 0.021 mJ and 0.198 mJ for the transmitter and between 0.029 mJ and 0.380 mJ for the receiver under different mismatch rates. Subsequently, we modify the best performing methods so that they run in constant time to protect against timing side-channel attacks, and observe that these changes only minimally affect resource consumption. Finally, we provide open-source implementations and energy consumption data of each fuzzy primitive as a reference for real-world designs.

There are multiple concerns associated with methotrexate (MTX), widely recognized for anti-neoplastic and anti-inflammatory effects in life-threatening disease conditions, i.e., acute lymphoblastic leukemia, non-Hodgkin’s lymphoma, psoriasis, and rheumatoid arthritis, due to long-term side effects and associated toxicity, which limits its valuable potential. MTX acts as an inhibitor of dihydrofolate reductase, leading to suppression of purine and pyrimidine synthesis in high metabolic and turnover cells, targeting cancer and dysregulated immune cells. Due to low discrimination between neoplastic cells and naturally high turnover cells, MTX is prone to inhibiting the division of all fast-dividing cells, causing toxicity in multiple organs. Nutraceutical compounds are plant-based or food-derived compounds, used for their preventive and therapeutic role, ascertained in multiple organ dysfunctions, including cardiovascular disease, ischemic stroke, cancer, and neurodegenerative diseases. Gut microbiota and microbiota-derived metabolites take part in multiple physiological processes, their dysregulation being involved in disease pathogenesis. Modulation of gut microbiota by using nutraceutical compounds represents a promising therapeutic direction to restore intestinal dysfunction associated with MTX treatment. In this review, we address the main organ dysfunctions induced by MTX treatment, and modulations of them by using nutraceutical compounds. Moreover, we revealed the protective mechanisms of nutraceuticals in MTX-induced intestinal dysfunctions by modulation of gut microbiota.

We propose and implement a Privacy-preserving Federated Learning ($PPFL$) framework for mobile systems to limit privacy leakages in federated learning. Leveraging the widespread presence of Trusted Execution Environments (TEEs) in high-end and mobile devices, we utilize TEEs on clients for local training, and on servers for secure aggregation, so that model/gradient updates are hidden from adversaries. Challenged by the limited memory size of current TEEs, we leverage greedy layer-wise training to train each model's layer inside the trusted area until its convergence. The performance evaluation of our implementation shows that $PPFL$ can significantly improve privacy while incurring small system overheads at the client-side. In particular, $PPFL$ can successfully defend the trained model against data reconstruction, property inference, and membership inference attacks. Furthermore, it can achieve comparable model utility with fewer communication rounds (0.54$\times$) and a similar amount of network traffic (1.002$\times$) compared to the standard federated learning of a complete model. This is achieved while only introducing up to ~15% CPU time, ~18% memory usage, and ~21% energy consumption overhead in $PPFL$'s client-side., Comment: 15 pages, 8 figures, accepted to MobiSys 2021

The European Union (EU) General Data Protection Regulation (GDPR) imposes legal responsibilities concerning the collection and processing of personal information from individuals who live in the EU. It has particular implications for the remote monitoring of cardiac implantable electronic devices (CIEDs). This report from a joint Task Force of the European Heart Rhythm Association and the Regulatory Affairs Committee of the European Society of Cardiology (ESC) recommends a common legal interpretation of the GDPR. Manufacturers and hospitals should be designated as joint controllers of the data collected by remote monitoring (depending upon the system architecture) and they should have a mutual contract in place that defines their respective roles; a generic template is proposed. Alternatively, they may be two independent controllers. Self-employed cardiologists also are data controllers. Third-party providers of monitoring platforms may act as data processors. Manufacturers should always collect and process the minimum amount of identifiable data necessary, and wherever feasible have access only to pseudonymized data. Cybersecurity vulnerabilities have been reported concerning the security of transmission of data between a patient's device and the transceiver, so manufacturers should use secure communication protocols. Patients need to be informed how their remotely monitored data will be handled and used, and their informed consent should be sought before their device is implanted. Review of consent forms in current use revealed great variability in length and content, and sometimes very technical language; therefore, a standard information sheet and generic consent form are proposed. Cardiologists who care for patients with CIEDs that are remotely monitored should be aware of these issues. ispartof: EP-Europace vol:22 issue:11 pages:1742-+ ispartof: location:England status: Published online

Fine-grained metering data threatens users’ privacy, as it typically reveals the users’ consumption patterns and thereby their behaviour. To address this problem, the use of pseudonyms when sending such fine-grained data has been proposed in the literature. In this paper, we demonstrate experimentally that an adversary who has access to pseudonymized fine-grained data and identifiable billing data can fully de-pseudonymize all users using a simple matching algorithm. Our experiments use realworld metering data collected from ca. 6500 smart meters. As pseudonymization alone is not sufficient to provide privacy, we propose three simple yet effective countermeasures against depseudonymization: deliberately not reporting some of the finegrained metering values, rounding these values before reporting them and regularly changing the pseudonyms. We experimentally demonstrate that our countermeasures considerably improve users’ privacy protection without significantly lowering the usefulness of the data. They also do not affect the billing process.

© Springer Nature Switzerland AG 2018. This paper presents the design and implementation of a low-power privacy-preserving device tracking system based on Internet of Things (IOT) technology. The system consists of low-power nodes and a set of dedicated beacons. Each tracking node broadcasts pseudonyms and encrypted versions of observed beacon identifiers over a Low-Power Wide-Area Network (LPWAN). Unlike most commercial systems, our solution ensures that the device owners are the only ones who can locate their devices. We present a detailed design and validate the result with a prototype implementation that considers power and energy consumption as well as side-channel attacks. Our implementation uses Physically Unclonable Function (PUF) technology for secure key-storage in an innovative way. We build and evaluate a complete demonstrator with off-the-shelf IoT nodes, Bluetooth Low Energy (BLE) beacons, and LoRa long distance communication (LPWAN). We validate the setup for a bicycle tracking application and also estimate the requirements for a low-cost ASIC node. ispartof: pages:347-369 ispartof: Lecture Notes in Computer Science vol:11261 pages:347-369 ispartof: CANS 2017 location:HONG KONG, Chinese Univ Hong Kong, Dept Informat Engn, Hong Kong date:30 Nov - 2 Dec 2017 status: accepted

Implantable Medical Devices (IMDs) typically use proprietary protocols with no or limited security to wirelessly communicate with a device programmer. These protocols enable doctors to carry out critical functions, such as changing the IMD's therapy or collecting telemetry data, without having to perform surgery on the patient. In this paper, we fully reverse-engineer the proprietary communication protocol between a device programmer and the latest generation of a widely used Implantable Cardioverter Defibrillator (ICD) which communicate over a long-range RF channel (from two to five meters). For this we follow a black-box reverse-engineering approach and use inexpensive Commercial Off-The-Shelf (COTS) equipment. We demonstrate that reverse-engineering is feasible by a weak adversary who has limited resources and capabilities without physical access to the devices. Our analysis of the proprietary protocol results in the identification of several protocol and implementation weaknesses. Unlike previous studies, which found no security measures, this article discovers the first known attempt to obfuscate the data that is transmitted over the air. Furthermore, we conduct privacy and Denial-of-Service (DoS) attacks and give evidence of other attacks that can compromise the patient's safety. All these attacks can be performed without needing to be in close proximity to the patient. We validate that our findings apply to (at least) 10 types of ICDs that are currently on the market. Finally, we propose several practical short- and long-term countermeasures to mitigate or prevent existing vulnerabilities.