Modular Logic Programming: Full Compositionality and Conflict Handling for Practical Reasoning

With the recent development of a new ubiquitous nature of data and the profusity of available knowledge, there is nowadays the need to reason from multiple sources of often incomplete and uncertain knowledge. Our goal was to provide a way to combine declarative knowledge bases – represented as logic programming modules under the answer set semantics – as well as the individual results one already inferred from them, without having to recalculate the results for their composition and without having to explicitly know the original logic programming encodings that produced such results. This posed us many challenges such as how to deal with fundamental problems of modular frameworks for logic programming, namely how to define a general compositional semantics that allows us to compose unrestricted modules. Building upon existing logic programming approaches, we devised a framework capable of composing generic logic programming modules while preserving the crucial property of compositionality, which informally means that the combination of models of individual modules are the models of the union of modules. We are also still able to reason in the presence of knowledge containing incoherencies, which is informally characterised by a logic program that does not have an answer set due to cyclic dependencies of an atom from its default negation. In this thesis we also discuss how the same approach can be extended to deal with probabilistic knowledge in a modular and compositional way. We depart from the Modular Logic Programming approach in Oikarinen & Janhunen (2008); Janhunen et al. (2009) which achieved a restricted form of compositionality of answer set programming modules. We aim at generalising this framework of modular logic programming and start by lifting restrictive conditions that were originally imposed, and use alternative ways of combining these (so called by us) Generalised Modular Logic Programs. We then deal with conflicts arising in generalised modular logic programming and provide modular justifications and debugging for the generalised modular logic programming setting, where justification models answer the question: Why is a given interpretation indeed an Answer Set? and Debugging models answer the question: Why is a given interpretation not an Answer Set? In summary, our research deals with the problematic of formally devising a generic modular logic programming framework, providing: operators for combining arbitrary modular logic programs together with a compositional semantics; We characterise conflicts that occur when composing access control policies, which are generalisable to our context of generalised modular logic programming, and ways of dealing with them syntactically: provided a unification for justification and debugging of logic programs; and semantically: provide a new semantics capable of dealing with incoherences. We also provide an extension of modular logic programming to a probabilistic setting. These goals are already covered with published work. A prototypical tool implementing the unification of justifications and debugging is available for download from http://cptkirk.sourceforge.net

Low level genome mistranslations deregulate the transcriptome and translatome and generate proteotoxic stress in yeast

Organisms use highly accurate molecular processes to transcribe their genes and a variety of mRNA quality control and ribosome proofreading mechanisms to maintain intact the fidelity of genetic information flow. Despite this, low level gene translational errors induced by mutations and environmental factors cause neurodegeneration and premature death in mice and mitochondrial disorders in humans. Paradoxically, such errors can generate advantageous phenotypic diversity in fungi and bacteria through poorly understood molecular processes.publishe

Calibration of bi-planar radiography with minimal phantoms

In this paper we propose a method for the geometrical calibration of bi-planar radiography that aims at minimising the impact of calibration phantoms on the content of radiographs. These phantoms are required for determining scale or to estimate the geometrical parameters of the system. Unfortunately, they often overlap anatomical structures. For accomplishing this goal, we propose a small extension to conventional imaging systems: a distance measuring device that enables to estimate some of the geometrical parameters. This leads to a reduction of the search space of solutions, which makes possible reducing requirements of calibration phantoms.The proposed method was tested on 17 pairs of radiographs of a phantom object of known dimensions. For calculating scale, only a reference distance of 40mm was used. Results show a RMS error of 0.36mm with 99% of the errors inferior to 0.85mm. Additionally, the requirements of the calibration phantom are very low when compared with other methods, but experiments with anatomical structures should be conducted to confirm these results

The Yeast PNC1 Longevity Gene Is Up-Regulated by mRNA Mistranslation

Translation fidelity is critical for protein synthesis and to ensure correct cell functioning. Mutations in the protein synthesis machinery or environmental factors that increase synthesis of mistranslated proteins result in cell death and degeneration and are associated with neurodegenerative diseases, cancer and with an increasing number of mitochondrial disorders. Remarkably, mRNA mistranslation plays critical roles in the evolution of the genetic code, can be beneficial under stress conditions in yeast and in Escherichia coli and is an important source of peptides for MHC class I complex in dendritic cells. Despite this, its biology has been overlooked over the years due to technical difficulties in its detection and quantification. In order to shed new light on the biological relevance of mistranslation we have generated codon misreading in Saccharomyces cerevisiae using drugs and tRNA engineering methodologies. Surprisingly, such mistranslation up-regulated the longevity gene PNC1. Similar results were also obtained in cells grown in the presence of amino acid analogues that promote protein misfolding. The overall data showed that PNC1 is a biomarker of mRNA mistranslation and protein misfolding and that PNC1-GFP fusions can be used to monitor these two important biological phenomena in vivo in an easy manner, thus opening new avenues to understand their biological relevance

Development of the genetic code: insights from a fungal codon reassignment

The high conservation of the genetic code and its fundamental role in genome decoding suggest that its evolution is highly restricted or even frozen. However, various prokaryotic and eukaryotic genetic code alterations, several alternative tRNA-dependent amino acid biosynthesis pathways, regulation of tRNA decoding by diverse nucleoside modifications and recent in vivo incorporation of non-natural amino acids into prokaryotic and eukaryotic proteins, show that the code evolves and is surprisingly flexible. The cellular mechanisms and the proteome buffering capacity that support such evolutionary processes remain unclear. Here we explore the hypothesis that codon misreading and reassignment played fundamental roles in the development of the genetic code and we show how a fungal codon reassignment is enlightening its evolution.publishe

Towards a characterization of semi-stable models in the logic of here-and-there

The main motivation for any paraconsistent logic is the idea that reasoning with inconsistent information should be allowed and possible in a controlled and discriminating way. The principle of explosion makes this inviable, and as such must be abandoned. In non-paraconsistent logics, only one inconsistent theory exists: the trivial theory that contains every sentence as a theorem. Paraconsistent logic allows distinguishing between inconsistent theories and to reason with them. Sometimes it is possible to revise a theory to make it consistent, however in other cases (e.g., large software systems) it is currently impossible to attain consistency. Some philosophers and logicians take a radical approach, holding that some contradictions are true, and thus a theory being inconsistent is not something undesirable.We characterize and present a new way of calculating semi-stable models models of a program which are paraconsistent in the presence of incoherence, without having to explicitly perform a syntactical transformation as the epistemic transformation presented in the original definition. We do this by dealing with strong negation and then calculating the program's Routley models. Afterwards we need only perform a selection according to criteria we characterize in this document.6

Cirrhosis is associated with lower serological responses to COVID-19 vaccines in patients with chronic liver disease

Background & Aims: The response of patients with chronic liver disease (CLD) to COVID-19 vaccines remains unclear. Our aim was to assess the humoral immune response and efficacy of two-dose COVID-19 vaccines among patients with CLD of different aetiologies and disease stages. Methods: A total of 357 patients were recruited in clinical centres from six European countries, and 132 healthy volunteers served as controls. Serum IgG (nM), IgM (nM), and neutralising antibodies (%) against the Wuhan-Hu-1, B.1.617, and B.1.1.529 SARS-CoV-2 spike proteins were determined before vaccination (T0) and 14 days (T2) and 6 months (T3) after the second-dose vaccination. Patients fulfilling inclusion criteria at T2 (n = 212) were stratified into ‘low’ or ‘high’ responders according to IgG levels. Infection rates and severity were collected throughout the study. Results: Wuhan-Hu-1 IgG, IgM, and neutralisation levels significantly increased from T0 to T2 in patients vaccinated with BNT162b2 (70.3%), mRNA-1273 (18.9%), or ChAdOx1 (10.8%). In multivariate analysis, age, cirrhosis, and type of vaccine (ChAdOx1 > BNT162b2 > mRNA-1273) predicted ‘low’ humoral response, whereas viral hepatitis and antiviral therapy predicted ‘high’ humoral response. Compared with Wuhan-Hu-1, B.1.617 and, further, B.1.1.529 IgG levels were significantly lower at both T2 and T3. Compared with healthy individuals, patients with CLD presented with lower B.1.1.529 IgGs at T2 with no additional key differences. No major clinical or immune IgG parameters associated with SARS-CoV-2 infection rates or vaccine efficacy. Conclusions: Patients with CLD and cirrhosis exhibit lower immune responses to COVID-19 vaccination, irrespective of disease aetiology. The type of vaccine leads to different antibody responses that appear not to associate with distinct efficacy, although this needs validation in larger cohorts with a more balanced representation of all vaccines. Impact and Implications: In patients with CLD vaccinated with two-dose vaccines, age, cirrhosis, and type of vaccine (Vaxzevria > Pfizer BioNTech > Moderna) predict a ‘lower’ humoral response, whereas viral hepatitis aetiology and prior antiviral therapy predict a ‘higher’ humoral response. This differential response appears not to associate with SARS-CoV-2 infection incidence or vaccine efficacy. However, compared with Wuhan-Hu-1, humoral immunity was lower for the Delta and Omicron variants, and all decreased after 6 months. As such, patients with CLD, particularly those older and with cirrhosis, should be prioritised for receiving booster doses and/or recently approved adapted vaccines