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Neutrophils are the most abundant white blood cell and the first line of defence against pathogens. Their development is characterised by the compaction and lobulation of their nuclei. They have a wide variety of mechanisms to clear out pathogens and defects in their development or activity result in severe immunodeficiency. To better understand neutrophil function, we analysed ataxia-telangiectasia (A-T), a genetic recessive disease caused by mutations in ataxia telangiectasia mutated (ATM) gene. A-T patients suffer from increased susceptibility to bacterial infections and malignancies. ATM is involved in chromatin double strand break repair and has been shown to be necessary for the development of B- and T-cells. However, little is known about the role of ATM in neutrophil biology. Based on the immunodeficiency observed in A-T patients, we hypothesised ATM might regulate neutrophil development and/or function. We established a CRISPR/Cas9 ATM knockout (ATM-/-) and inducible ATM shRNA knockdown cell line, which we differentiated into a neutrophil-like cell. We tested the antimicrobial capacity of the cell line as well as primary neutrophils treated with an ATM inhibitor and found a decreased ability to kill Staphyloccocus aureus in both systems. To understand the mechanism behind this phenotype, we compared differentiation from precursors as well as different antimicrobial responses in both WT and ATM-/- cells. We found increased expression of CD11b and decreased expression of C-type lectin receptors, indicating developmental disturbances as well as reduced production of reactive oxygen species (ROS) and NETs. Increased CD11b surface marker expression was confirmed in neutrophils from A-T patients. These differences were related to dysregulated transcription and nuclear organisation in ATM deficient cells, implicating ATM in neutrophil chromatin regulation. In conclusion, we identified ATM as a regulator of neutrophil development and antimicrobial activity, and a potential therapeutic target in immunodeficiency or inflammatory disease.

Achieving precise control over quantum systems has groundbreaking ap-plications, such as simulating complex quantum systems, or implementing quantum algorithms with an improved efficiency over classical algorithms. Quantum computing has been under development for the last decades, re-sulting in the so-called Noisy Intermediate-Scale Quantum (NISQ) devices with about 50 qubits. While these devices are built with the purpose of achieving practical advantages over classical processors, they are vulnerable to noise sources. In order to account for error sources, one needs to im-plement Quantum Error Correction (QEC) techniques. These techniques protect quantum information by encoding a logical qubit into several phys-ical ones. For the implementation of NISQ devices and QEC techniques, it is vital to keep improving the quantum operations and states involved. Here we develop calibration protocols based on the application of Bayesian inference. We show their advantages compared to the more traditional frequentist approaches, such as their ability to maximise the information gained with each measurement, or their straightforward automation. In our first line of research, we develop a Bayesian protocol for the correction of unwanted phases appearing in the experimental preparation of Steane code states. This protocol requires 13 times less measurements than the frequentist approach. In our second line of research, we develop a proto-col for locking a laser to the qubit transition frequency in a trapped-ion architecture. This calibration is vital, since the correct implementation of single-qubit gates depends on it. In our final line of research, we study the Mølmer-Sørensen entangling gate, used in trapped-ion systems. First we introduce the calibration parameters, and derive a semianalytical model of the effects of one of them, for which there was no previous analytical understanding. Finally, we develop a Bayesian protocol for the calibration of these parameters, which was successfully implemented and tested in an experimental trapped-ion quantum processor.

Cloud computing has completely changed our lives. This technology is one of the building blocks of our modern society and it dramatically impacted on how we play, work and live. It has been widely adopted in many sectors mainly because it reduces the cost of performing tasks in a flexible, scalable and reliable way. However, all of these benefits also come with threats. Since this technology is core for our society, it is also a very rewarding target for attackers and therefore it is imperative to have secure cloud systems. To offer secure cloud services, vendors and providers must safeguard their infrastructure with up-to-date defenses and countermeasures to ensure the provision of high levels of protection, enabling users and consumers to enjoy their services as securely as possible. Unfortunately, the application of certain security mechanisms at infrastructure level can lead to the reduction of the efficient use of hardware resources, such as inefficient memory utilization. Therefore, in some cases security mechanisms cannot be easily combined with other optimization mechanisms and techniques used to obtain more profit of the existing resources. When this occurs, providers are forced to undertake actions that impact performance and to use their resources inefficiently in order to keep security [1–3]. In other cases, priority is given to resource optimization, thereby compromising security [4–6]. This thesis makes contributions to overcome existing barriers that prevent the secure and efficient utilization of memory resources in cloud environments. Memory deduplication is an important memory saving technique particularly desired in cloud environments because it is capable of reducing memory footprint across virtual machines. Unfortunately, it is known that it can introduce security problems through side channels. To overcome this problem and to enable the use of the memory saving technique, we propose Slicedup, a memory deduplication design that prevents side-channel attacks in multi-tenant cloud systems. As described in Chapter 4, Slicedup allows cloud providers to secure the use of memory deduplication, increasing the profit of existing memory resources and decreasing the total cost of managing and ownership. Kernel randomization is an essential and widely used security technique that consists in placing kernel memory regions at random locations to hinder the successful exploitation of vulnerabilities that rely on knowing valid addresses. Unfortunately, its use in cloud environments produces alterations in memory contents, leading to a breakage of memory sharing and, consequently, to a higher memory consumption. In Chapter 5, after analyzing the problem and its causes in detail, we propose KASLR-MT, a new kernel randomization design for multi-tenant cloud systems compatible with memory deduplication that maximizes memory savings rate while providing a strong security. Afterwards, Chapter 6 presents the evolution and the next steps of this security technique, and we extend the effectiveness of KASLR-MT to include support for a finer granularity to include protection against info-leaks. Concerning the security of important components of the kernel, the availability of high quality entropy is critical and necessary to ensure that such security mechanisms operate correctly and without any weakness that could compromise their effectiveness. Unfortunately, it is unfeasible to generate true randomness by running deterministic algorithms in computers. As a consequence, obtaining high quality entropy is still a challenge, specially at boot time. In Chapter 7, after analyzing the boot-time entropy starvation problem, we propose E-Boot, a novel technique that provides high-quality random numbers to guest virtual machines, being the first technique that completely satisfies the entropy demand of virtualized boot-loaders and operating systems at boot time. As a result of this research, we provide important advantages to the efficiency of environments based on virtualization technologies such as multi-tenant cloud computing systems, which are the foundation of most of the services we currently use on a daily basis and for which we strongly depend.