Self-adaptation in next-generation Internet networks: how to react to traffic changes while respecting QoS?

Next-generation network infrastructure should support different services and several levels of quality of service (QoS) and resilience. The main requirements for such multiservice networks are flexibility, effective utilization of network resources, and ability to react to traffic demand changes with time. These requisites lead to the fact that next-generation networks should, to some extend, be "self-adapting," to cope with the need of promptly reacting to traffic demand changes, in an effective way, while taking into account the different requirements in terms of QoS. This paper sketches the reference network scenario and discusses the subject of self-adapting networks, attempting to focus on the key issues that need to be solved to realize future infrastructures. As a relevant example, this paper briefly reports a system developed by the authors' laboratory that implements a traffic engineering solution able to fulfill the mentioned requirements. This system could be regarded as a first concrete step toward the realization of self-adapting networks. In addition, some relevant results that were obtained either by simulation or by experiments on a real test bed are reported to discuss the main characteristics of such a system and assess the feasibility of the concept. Finally, the paper reviews the main hot issues that need to be addressed, in the authors' opinion, by the international research community.     

Monitoring and improving Greek banking services using Bayesian Networks: An analysis of mystery shopping data

Mystery shopping is a well known marketing technique used by companies and marketing analysts to measure quality of service, and gather information about products and services. In this article, we analyse data from mystery shopping surveys via Bayesian Networks in order to examine and evaluate the quality of service offered by the loan departments of Greek Banks. We use mystery shopping visits to collect information about loan products and services and, by this way, evaluate the customer satisfaction and plan improvement strategies that will assist banks to reach their internal standards. Bayesian Networks not only provide a pictorial representation of the dependence structure between the characteristics of interest but also allow to evaluate, interpret and understand the effects of possible improvement strategies.     

Cooperation and Competition in ALIAS: A Logic Framework for Agents that Negotiate

This paper presents ALIAS, an agent architecture based on intelligent logic agents, where the main form of agent reasoning is abduction. The system is particularly suited for solving problems where knowledge is incomplete, where agents may need to make reasonable hypotheses about the problem domain and other agents, and where the raised hypotheses have to be consistent for the overall set of agents. ALIAS agents are pro-active, exhibiting a goal-directed behavior, and autonomous, since each one can solve problems using its own private knowledge base. ALIAS agents are also social, because they are able to interact with other agents, in order to cooperatively solve problems. The coordination mechanisms are modeled by means of LAILA, a logic-based language which allows to express intra-agent reasoning and inter-agent coordination. As an application, we show how LAILA can be used to implement inter-agent dialogues, e.g., for negotiation. In particular, LAILA is well-suited to coordinate the process of negotiation aimed at exchanging resources between agents, thus allowing them to execute the plans to achieve their goals.     

Specification and Verification of Agent Interaction using Social Integrity Constraints

In this paper we propose a logic-based social approach to the specification and verification of agent interaction. We firstly introduce integrity constraints about social acts (called Social Integrity Constraints) as a formalism to express interaction protocols and to give a social semantics to the behavior of agents, focusing on communicative acts. Then, we discuss several possible kinds of verification of agent interaction, and we show how social integrity constraints can be used to verify some properties in this respect. We focus our attention on static verification of compliance of agent specifications to interaction protocols, and on run-time verification, based on agents' observable behavior. We adopt as a running example the NetBill security transaction protocol for the selling and delivery of information goods.     

Identification of a Maturation Plasma Cell Index through a Highly Sensitive Droplet Digital PCR Assay Gene Expression Signature Validation in Newly Diagnosed Multiple Myeloma Patients

DNA microarrays and RNA-based sequencing approaches are considered important discovery tools in clinical medicine. However, cross-platform reproducibility studies undertaken so far have highlighted that microarrays are not able to accurately measure gene expression, particularly when they are expressed at low levels. Here, we consider the employment of a digital PCR assay (ddPCR) to validate a gene signature previously identified by gene expression profile. This signature included ten Hedgehog (HH) pathways’ genes able to stratify multiple myeloma (MM) patients according to their self-renewal status. Results show that the designed assay is able to validate gene expression data, both in a retrospective as well as in a prospective cohort. In addition, the plasma cells’ differentiation status determined by ddPCR was further confirmed by other techniques, such as flow cytometry, allowing the identification of patients with immature plasma cells’ phenotype (i.e., expressing CD19+/CD81+ markers) upregulating HH genes, as compared to others, whose plasma cells lose the expression of these markers and were more differentiated. To our knowledge, this is the first technical report of gene expression data validation by ddPCR instead of classical qPCR. This approach permitted the identification of a Maturation Index through the integration of molecular and phenotypic data, able to possibly define upfront the differentiation status of MM patients that would be clinically relevant in the future.     

Autoimmune Neutropenia and Immune-Dysregulation in a Patient Carrying a TINF2 Variant

In recent years, the knowledge about the immune-mediated impairment of bone marrow precursors in immune-dysregulation and autoimmune disorders has increased. In addition, immune-dysregulation, secondary to marrow failure, has been reported as being, in some cases, the most evident and early sign of the disease and making the diagnosis of both groups of disorders challenging. Dyskeratosis congenita is a disorder characterized by premature telomere erosion, typically showing marrow failure, nail dystrophy and leukoplakia, although incomplete genetic penetrance and phenotypes with immune-dysregulation features have been described. We report on a previously healthy 17-year-old girl, with a cousin successfully treated for acute lymphoblastic leukemia, who presented with leukopenia and neutropenia. The diagnostic work-up showed positive anti-neutrophil antibodies, leading to the diagnosis of autoimmune neutropenia, a slightly low NK count and high TCR-αβ+-double-negative T-cells. A next-generation sequencing (NGS) analysis showed the 734C>A variant on exon 6 of the TINF2 gene, leading to the p.Ser245Tyr. The telomere length was short on the lymphocytes and granulocytes, suggesting the diagnosis of an atypical telomeropathy showing with immune-dysregulation. This case underlines the importance of an accurate diagnostic work-up of patients with immune-dysregulation, who should undergo NGS or whole exome sequencing to identify specific disorders that deserve targeted follow-up and treatment.     

Cardiac Toxicity Associated with Immune Checkpoint Inhibitors: A Systematic Review

Immune checkpoint inhibitors (ICIs) are an important advancement in the field of cancer treatment, significantly improving the survival of patients with a series of advanced malignancies, like melanoma, non-small cell lung cancer (NSCLC), hepatocellular carcinoma (HCC), renal cell carcinoma (RCC), and Hodgkin lymphoma. ICIs act upon T lymphocytes and antigen-presenting cells, targeting programmed cell death protein 1 (PD1), programmed cell death protein ligand 1 (PD-L1), and cytotoxic T-lymphocyte antigen 4 (CTLA-4), breaking the immune tolerance of the T cells against malignant cells and enhancing the body’s own immune response. A variety of cardiac-adverse effects are associated with ICI-based treatment, including pericarditis, arrhythmias, cardiomyopathy, and acute coronary syndrome, with myocarditis being the most studied due to its often-unexpected onset and severity. Overall, Myocarditis is rare but presents an immune-related adverse event (irAE) that has a high fatality rate. Considering the rising number of oncological patients treated with ICIs and the severity of their potential adverse effects, a good understanding and continuous investigation of cardiac irAEs is of the utmost importance. This systematic review aimed to revise recent publications (between 2016–2022) on ICI-induced cardiac toxicities and highlight the therapeutical approach and evolution in the selected cases.     

The Flavonol Quercitrin Hinders GSK3 Activity and Potentiates the Wnt/β-Catenin Signaling Pathway

The Wnt/β-catenin signaling pathway dictates cell proliferation and differentiation during embryonic development and tissue homeostasis. Its deregulation is associated with many pathological conditions, including neurodegenerative disease, frequently downregulated. The lack of efficient treatment for these diseases, including Alzheimer’s disease (AD), makes Wnt signaling an attractive target for therapies. Interestingly, novel Wnt signaling activating compounds are less frequently described than inhibitors, turning the quest for novel positive modulators even more appealing. In that sense, natural compounds are an outstanding source of potential drug leads. Here, we combine different experimental models, cell-based approaches, neuronal culture assays, and rodent behavior tests with Xenopus laevis phenotypic analysis to characterize quercitrin, a natural compound, as a novel Wnt signaling potentiator. We find that quercitrin potentiates the signaling in a concentration-dependent manner and increases the occurrence of the Xenopus secondary axis phenotype mediated by Xwnt8 injection. Using a GSK3 biosensor, we describe that quercitrin impairs GSK3 activity and increases phosphorylated GSK3β S9 levels. Treatment with XAV939, an inhibitor downstream of GSK3, impairs the quercitrin-mediated effect. Next, we show that quercitrin potentiates the Wnt3a-synaptogenic effect in hippocampal neurons in culture, which is blocked by XAV939. Quercitrin treatment also rescues the hippocampal synapse loss induced by intracerebroventricular injection of amyloid-β oligomers (AβO) in mice. Finally, quercitrin rescues AβO-mediated memory impairment, which is prevented by XAV939. Thus, our study uncovers a novel function for quercitrin as a Wnt/β-catenin signaling potentiator, describes its mechanism of action, and opens new avenues for AD treatments.