Investigating the role of Copy Number Variants in Specific Language Impairment and identification of new candidate genes

Specific language impairment (SLI) is a complex neurodevelopmental disorder defined as an unexpected failure to develop normal language abilities for no obvious reason. Copy number variants (CNVs) are an important source of variation in the susceptibility to neuropsychiatric disorders. Therefore, a CNV study within SLI families was performed to investigate the role of structural variants in SLI. Among the identified CNVs, we focused on CNVs on chromosome 15q11-q13, recurrently observed in neuropsychiatric conditions, and a homozygous exonic microdeletion in ZNF277. Since this microdeletion falls within the AUTS1 locus, a region linked to autism spectrum disorders (ASD), we investigated a potential role of ZNF277 in SLI and ASD. Frequency data and expression analysis of the ZNF277 microdeletion suggested that this variant may contribute to the risk of language impairments in a complex manner, that is independent of the autism risk previously described in this region. Moreover, we identified an affected individual with a dihydropyrimidine dehydrogenase (DPD) deficiency, caused by compound heterozygosity of two deleterious variants in the gene DPYD. Since DPYD represents a good candidate gene for both SLI and ASD, we investigated its involvement in the susceptibility to these two disorders, focusing on the splicing variant rs3918290, the most common mutation in the DPD deficiency. We observed a higher frequency of rs3918290 in SLI cases (1.2%), compared to controls (~0.6%), while no difference was observed in a large ASD cohort. DPYD mutation screening in 4 SLI and 7 ASD families carrying the splicing variant identified six known missense changes and a novel variant in the promoter region. These data suggest that the combined effect of the mutations identified in affected individuals may lead to an altered DPD activity and that rare variants in DPYD might contribute to a minority of cases, in conjunction with other genetic or non-genetic factors.

Specification, execution and verification of interaction protocols: an approach based on computational logic

Interaction protocols establish how different computational entities can interact with each other. The interaction can be finalized to the exchange of data, as in 'communication protocols', or can be oriented to achieve some result, as in 'application protocols'. Moreover, with the increasing complexity of modern distributed systems, protocols are used also to control such a complexity, and to ensure that the system as a whole evolves with certain features. However, the extensive use of protocols has raised some issues, from the language for specifying them to the several verification aspects. Computational Logic provides models, languages and tools that can be effectively adopted to address such issues: its declarative nature can be exploited for a protocol specification language, while its operational counterpart can be used to reason upon such specifications. In this thesis we propose a proof-theoretic framework, called SCIFF, together with its extensions. SCIFF is based on Abductive Logic Programming, and provides a formal specification language with a clear declarative semantics (based on abduction). The operational counterpart is given by a proof procedure, that allows to reason upon the specifications and to test the conformance of given interactions w.r.t. a defined protocol. Moreover, by suitably adapting the SCIFF Framework, we propose solutions for addressing (1) the protocol properties verification (g-SCIFF Framework), and (2) the a-priori conformance verification of peers w.r.t. the given protocol (AlLoWS Framework). We introduce also an agent based architecture, the SCIFF Agent Platform, where the same protocol specification can be used to program and to ease the implementation task of the interacting peers.

Specification and Verification of Declarative Open Interaction Models - A Logic-based framework

The advent of distributed and heterogeneous systems has laid the foundation for the birth of new architectural paradigms, in which many separated and autonomous entities collaborate and interact to the aim of achieving complex strategic goals, impossible to be accomplished on their own. A non exhaustive list of systems targeted by such paradigms includes Business Process Management, Clinical Guidelines and Careflow Protocols, Service-Oriented and Multi-Agent Systems. It is largely recognized that engineering these systems requires novel modeling techniques. In particular, many authors are claiming that an open, declarative perspective is needed to complement the closed, procedural nature of the state of the art specification languages. For example, the ConDec language has been recently proposed to target the declarative and open specification of Business Processes, overcoming the over-specification and over-constraining issues of classical procedural approaches. On the one hand, the success of such novel modeling languages strongly depends on their usability by non-IT savvy: they must provide an appealing, intuitive graphical front-end. On the other hand, they must be prone to verification, in order to guarantee the trustworthiness and reliability of the developed model, as well as to ensure that the actual executions of the system effectively comply with it. In this dissertation, we claim that Computational Logic is a suitable framework for dealing with the specification, verification, execution, monitoring and analysis of these systems. We propose to adopt an extended version of the ConDec language for specifying interaction models with a declarative, open flavor. We show how all the (extended) ConDec constructs can be automatically translated to the CLIMB Computational Logic-based language, and illustrate how its corresponding reasoning techniques can be successfully exploited to provide support and verification capabilities along the whole life cycle of the targeted systems.

The language of others mirrored in thy face: The role of political affiliation in automatic facial effects of language

People tend to automatically mimic facial expressions of others. If clear evidence exists on the effect of non-verbal behavior (emotion faces) on automatic facial mimicry, little is known about the role of verbal behavior (emotion language) in triggering such effects. Whereas it is well-established that political affiliation modulates facial mimicry, no evidence exists on whether this modulation passes also through verbal means. This research addressed the role of verbal behavior in triggering automatic facial effects depending on whether verbal stimuli are attributed to leaders of different political parties. Study 1 investigated the role of interpersonal verbs, referring to positive and negative emotion expressions and encoding them at different levels of abstraction, in triggering corresponding facial muscle activation in a reader. Study 2 examined the role of verbs expressing positive and negative emotional behaviors of political leaders in modulating automatic facial effects depending on the matched or mismatched political affiliation of participants and politicians of left-and right-wing. Study 3 examined whether verbs expressing happiness displays of ingroup politicians induce a more sincere smile (Duchenne) pattern among readers of same political affiliation relative to happiness expressions of outgroup politicians. Results showed that verbs encoding facial actions at different levels of abstraction elicited differential facial muscle activity (Study 1). Furthermore, political affiliation significantly modulated facial activation triggered by emotion verbs as participants showed more congruent and enhanced facial activity towards ingroup politicians’ smiles and frowns compared to those of outgroup politicians (Study 2). Participants facially responded with a more sincere smile pattern towards verbs expressing smiles of ingroup compared to outgroup politicians (Study 3). Altogether, results showed that the role of political affiliation in modulating automatic facial effects passes also through verbal channels and is revealed at a fine-grained level by inducing quantitative and qualitative differences in automatic facial reactions of readers.