Computational investigations of ion conduction mechanisms using enhanced sampling methods

Proper ion channels’ functioning is a prerequisite for a normal cell and disorders involving ion channels, or channelopathies, underlie many human diseases. Long QT syndromes (LQTS) for example may arise from the malfunctioning of hERG channel, caused either by the binding of drugs or mutations in HERG gene. In the first part of this thesis I present a framework to investigate the mechanism of ion conduction through hERG channel. The free energy profile governing the elementary steps of ion translocation in the pore was computed by means of umbrella sampling simulations. Compared to previous studies, we detected a different dynamic behavior: according to our data hERG is more likely to mediate a conduction mechanism which has been referred to as “single-vacancy-like” by Roux and coworkers (2001), rather then a “knock-on” mechanism. The same protocol was applied to a model of hERG presenting the Gly628Ser mutation, found to be cause of congenital LQTS. The results provided interesting insights about the reason of the malfunctioning of the mutant channel. Since they have critical functions in viruses’ life cycle, viral ion channels, such as M2 proton channel, are considered attractive targets for antiviral therapy. A deep knowledge of the mechanisms that the virus employs to survive in the host cell is of primary importance in the identification of new antiviral strategies. In the second part of this thesis I shed light on the role that M2 plays in the control of electrical potential inside the virus, being the charge equilibration a condition required to allow proton influx. The ion conduction through M2 was simulated using metadynamics technique. Based on our results we suggest that a potential anion-mediated cation-proton exchange, as well as a direct anion-proton exchange could both contribute to explain the activity of the M2 channel.

Predictive Ability of NGAL as a Marker of Renal Damage: evaluation of Multiple Clinical Settings

Introduction. Neutrophil Gelatinase-Associated Lipocalin (NGAL) belongs to the family of lipocalins and it is produced by several cell types, including renal tubular epithelium. In the kidney its production increases during acute damage and this is reflected by the increase in serum and urine levels. In animal studies and clinical trials, NGAL was found to be a sensitive and specific indicator of acute kidney injury (AKI). Purpose. The aim of this work was to investigate, in a prospective manner, whether urine NGAL can be used as a marker in preeclampsia, kidney transplantation, VLBI and diabetic nephropathy. Materials and methods. The study involved 44 consecutive patients who received renal transplantation; 18 women affected by preeclampsia (PE); a total of 55 infants weighing ≤1500 g and 80 patients with Type 1 diabetes. Results. A positive correlation was found between urinary NGAL and 24 hours proteinuria within the PE group. The detection of higher uNGAL values in case of severe PE, even in absence of statistical significance, confirms that these women suffer from an initial renal damage. In our population of VLBW infants, we found a positive correlation of uNGAL values at birth with differences in sCreat and eGFR values from birth to day 21, but no correlation was found between uNGAL values at birth and sCreat and eGFR at day 7. systolic an diastolic blood pressure decreased with increasing levels of uNGAL. The patients with uNGAL <25 ng/ml had significantly higher levels of systolic blood pressure compared with the patients with uNGAL >50 ng/ml ( p<0.005). Our results indicate the ability of NGAL to predict the delay in functional recovery of the graft. Conclusions. In acute renal pathology, urinary NGAL confirms to be a valuable predictive marker of the progress and status of acute injury.

Longitudinal evolution of cognitive functions in patients with multiple system atrophy: a prospective study

Introduction and Background: Multiple system atrophy (MSA) is a sporadic, adult-onset, progressive neurodegenerative disease characterized clinically by parkinsonism, cerebellar ataxia, and autonomic failure. We investigated cognitive functions longitudinally in a group of probable MSA patients, matching data with sleep parameters. Patients and Methods: 10 patients (7m/3f) underwent a detailed interview, a general and neurological examination, laboratory exams, MRI scans, a cardiovascular reflexes study, a battery of neuropsychological tests, and video-polysomnographic recording (VPSG). Patients were revaluated (T1) a mean of 16±5 (range: 12-28) months after the initial evaluation (T0). At T1, the neuropsychological assessment and VPSG were repeated. Results: The mean patient age was 57.8±6.4 years (range: 47-64) with a mean age at disease onset of 53.2±7.1 years (range: 43-61) and symptoms duration at T0 of 60±48 months (range: 12-144). At T0, 7 patients showed no cognitive deficits while 3 patients showed isolated cognitive deficits. At T1, 1 patient worsened developing multiple cognitive deficits from a normal condition. At T0 and T1, sleep efficiency was reduced, REM latency increased, NREM sleep stages 1-2 slightly increased. Comparisons between T1 and T0 showed a significant worsening in two tests of attention and no significant differences of VPSG parameters. No correlation was found between neuropsychological results and VPSG findings or RBD duration. Discussion and Conclusions: The majority of our patients do not show any cognitive deficits at T0 and T1, while isolated cognitive deficits are present in the remaining patients. Attention is the cognitive function which significantly worsened. Our data confirm the previous findings concerning the prevalence, type and the evolution of cognitive deficits in MSA. Regarding the developing of a condition of dementia, our data did not show a clear-cut diagnosis of dementia. We confirm a mild alteration of sleep structure. RBD duration does not correlate with neuropsychological findings.

Machine-learning methods for structure prediction of β-barrel membrane proteins

Different types of proteins exist with diverse functions that are essential for living organisms. An important class of proteins is represented by transmembrane proteins which are specifically designed to be inserted into biological membranes and devised to perform very important functions in the cell such as cell communication and active transport across the membrane. Transmembrane β-barrels (TMBBs) are a sub-class of membrane proteins largely under-represented in structure databases because of the extreme difficulty in experimental structure determination. For this reason, computational tools that are able to predict the structure of TMBBs are needed. In this thesis, two computational problems related to TMBBs were addressed: the detection of TMBBs in large datasets of proteins and the prediction of the topology of TMBB proteins. Firstly, a method for TMBB detection was presented based on a novel neural network framework for variable-length sequence classification. The proposed approach was validated on a non-redundant dataset of proteins. Furthermore, we carried-out genome-wide detection using the entire Escherichia coli proteome. In both experiments, the method significantly outperformed other existing state-of-the-art approaches, reaching very high PPV (92%) and MCC (0.82). Secondly, a method was also introduced for TMBB topology prediction. The proposed approach is based on grammatical modelling and probabilistic discriminative models for sequence data labeling. The method was evaluated using a newly generated dataset of 38 TMBB proteins obtained from high-resolution data in the PDB. Results have shown that the model is able to correctly predict topologies of 25 out of 38 protein chains in the dataset. When tested on previously released datasets, the performances of the proposed approach were measured as comparable or superior to the current state-of-the-art of TMBB topology prediction.

Spectroscopic studies on Cyclodextrin and Metal Organic Framework based potential nanovectors for delivery of Anticancer and Antiviral drugs

The aim of this work is to contribute to the development of new multifunctional nanocarriers for improved encapsulation and delivery of anticancer and antiviral drugs. The work focused on water soluble and biocompatible oligosaccharides, the cyclodextrins (CyDs), and a new family of nanostructured, biodegradable carrier materials made of porous metal-organic frameworks (nanoMOFs). The drugs of choice were the anticancer doxorubicin (DOX), azidothymidine (AZT) and its phosphate derivatives and artemisinin (ART). DOX possesses a pharmacological drawback due to its self-aggregation tendency in water. The non covalent binding of DOX to a series of CyD derivatives, such as g-CyD, an epichlorohydrin crosslinked b-CyD polymer (pb-CyD) and a citric acid crosslinked g-CyD polymer (pg-CyD) was studied by UV visible absorption, circular dichroism and fluorescence. Multivariate global analysis of multiwavelength data from spectroscopic titrations allowed identification and characterization of the stable complexes. pg-CyD proved to be the best carrier showing both high association constants and ability to monomerize DOX. AZT is an important antiretroviral drug. The active form is AZT-triphosphate (AZT-TP), formed in metabolic paths of low efficiency. Direct administration of AZT-TP is limited by its poor stability in biological media. So the development of suitable carriers is highly important. In this context we studied the binding of some phosphorilated derivatives to nanoMOFs by spectroscopic methods. The results obtained with iron(III)-trimesate nanoMOFs allowed to prove that the binding of these drugs mainly occurs by strong iono-covalent bonds to iron(III) centers. On the basis of these and other results obtained in partner laboratories, it was possible to propose this highly versatile and “green” carrier system for delivery of phosphorylated nucleoside analogues. The interaction of DOX with nanoMOFs was also studied. Finally the binding of the antimalarial drug, artemisinin (ART) with two cyclodextrin-based carriers,the pb-CyD and a light responsive bis(b-CyD) host, was also studied.

Monitoring Complex Processes to Verify System Conformance: A Declarative Rule-Based Framework

Over the last 60 years, computers and software have favoured incredible advancements in every field. Nowadays, however, these systems are so complicated that it is difficult – if not challenging – to understand whether they meet some requirement or are able to show some desired behaviour or property. This dissertation introduces a Just-In-Time (JIT) a posteriori approach to perform the conformance check to identify any deviation from the desired behaviour as soon as possible, and possibly apply some corrections. The declarative framework that implements our approach – entirely developed on the promising open source forward-chaining Production Rule System (PRS) named Drools – consists of three components: 1. a monitoring module based on a novel, efficient implementation of Event Calculus (EC), 2. a general purpose hybrid reasoning module (the first of its genre) merging temporal, semantic, fuzzy and rule-based reasoning, 3. a logic formalism based on the concept of expectations introducing Event-Condition-Expectation rules (ECE-rules) to assess the global conformance of a system. The framework is also accompanied by an optional module that provides Probabilistic Inductive Logic Programming (PILP). By shifting the conformance check from after execution to just in time, this approach combines the advantages of many a posteriori and a priori methods proposed in literature. Quite remarkably, if the corrective actions are explicitly given, the reactive nature of this methodology allows to reconcile any deviations from the desired behaviour as soon as it is detected. In conclusion, the proposed methodology brings some advancements to solve the problem of the conformance checking, helping to fill the gap between humans and the increasingly complex technology.

Numerical methods for the dispersion analysis of Guided Waves

The use of guided ultrasonic waves (GUW) has increased considerably in the fields of non-destructive (NDE) testing and structural health monitoring (SHM) due to their ability to perform long range inspections, to probe hidden areas as well as to provide a complete monitoring of the entire waveguide. Guided waves can be fully exploited only once their dispersive properties are known for the given waveguide. In this context, well stated analytical and numerical methods are represented by the Matrix family methods and the Semi Analytical Finite Element (SAFE) methods. However, while the former are limited to simple geometries of finite or infinite extent, the latter can model arbitrary cross-section waveguides of finite domain only. This thesis is aimed at developing three different numerical methods for modelling wave propagation in complex translational invariant systems. First, a classical SAFE formulation for viscoelastic waveguides is extended to account for a three dimensional translational invariant static prestress state. The effect of prestress, residual stress and applied loads on the dispersion properties of the guided waves is shown. Next, a two-and-a-half Boundary Element Method (2.5D BEM) for the dispersion analysis of damped guided waves in waveguides and cavities of arbitrary cross-section is proposed. The attenuation dispersive spectrum due to material damping and geometrical spreading of cavities with arbitrary shape is shown for the first time. Finally, a coupled SAFE-2.5D BEM framework is developed to study the dispersion characteristics of waves in viscoelastic waveguides of arbitrary geometry embedded in infinite solid or liquid media. Dispersion of leaky and non-leaky guided waves in terms of speed and attenuation, as well as the radiated wavefields, can be computed. The results obtained in this thesis can be helpful for the design of both actuation and sensing systems in practical application, as well as to tune experimental setup.

Interpreting Judgements using Knowledge Representation Methods and Computational Models of Argument

The goal of the present research is to define a Semantic Web framework for precedent modelling, by using knowledge extracted from text, metadata, and rules, while maintaining a strong text-to-knowledge morphism between legal text and legal concepts, in order to fill the gap between legal document and its semantics. The framework is composed of four different models that make use of standard languages from the Semantic Web stack of technologies: a document metadata structure, modelling the main parts of a judgement, and creating a bridge between a text and its semantic annotations of legal concepts; a legal core ontology, modelling abstract legal concepts and institutions contained in a rule of law; a legal domain ontology, modelling the main legal concepts in a specific domain concerned by case-law; an argumentation system, modelling the structure of argumentation. The input to the framework includes metadata associated with judicial concepts, and an ontology library representing the structure of case-law. The research relies on the previous efforts of the community in the field of legal knowledge representation and rule interchange for applications in the legal domain, in order to apply the theory to a set of real legal documents, stressing the OWL axioms definitions as much as possible in order to enable them to provide a semantically powerful representation of the legal document and a solid ground for an argumentation system using a defeasible subset of predicate logics. It appears that some new features of OWL2 unlock useful reasoning features for legal knowledge, especially if combined with defeasible rules and argumentation schemes. The main task is thus to formalize legal concepts and argumentation patterns contained in a judgement, with the following requirement: to check, validate and reuse the discourse of a judge - and the argumentation he produces - as expressed by the judicial text.

A Semantic-based Framework for Digital Survey of Architectural Heritage

The research aims at developing a framework for semantic-based digital survey of architectural heritage. Rooted in knowledge-based modeling which extracts mathematical constraints of geometry from architectural treatises, as-built information of architecture obtained from image-based modeling is integrated with the ideal model in BIM platform. The knowledge-based modeling transforms the geometry and parametric relation of architectural components from 2D printings to 3D digital models, and create large amount variations based on shape grammar in real time thanks to parametric modeling. It also provides prior knowledge for semantically segmenting unorganized survey data. The emergence of SfM (Structure from Motion) provides access to reconstruct large complex architectural scenes with high flexibility, low cost and full automation, but low reliability of metric accuracy. We solve this problem by combing photogrammetric approaches which consists of camera configuration, image enhancement, and bundle adjustment, etc. Experiments show the accuracy of image-based modeling following our workflow is comparable to that from range-based modeling. We also demonstrate positive results of our optimized approach in digital reconstruction of portico where low-texture-vault and dramatical transition of illumination bring huge difficulties in the workflow without optimization. Once the as-built model is obtained, it is integrated with the ideal model in BIM platform which allows multiple data enrichment. In spite of its promising prospect in AEC industry, BIM is developed with limited consideration of reverse-engineering from survey data. Besides representing the architectural heritage in parallel ways (ideal model and as-built model) and comparing their difference, we concern how to create as-built model in BIM software which is still an open area to be addressed. The research is supposed to be fundamental for research of architectural history, documentation and conservation of architectural heritage, and renovation of existing buildings.

Novel investigation methods in Computational Social Dynamics and Complex Systems

In this thesis the evolution of the techno-social systems analysis methods will be reported, through the explanation of the various research experience directly faced. The first case presented is a research based on data mining of a dataset of words association named Human Brain Cloud: validation will be faced and, also through a non-trivial modeling, a better understanding of language properties will be presented. Then, a real complex system experiment will be introduced: the WideNoise experiment in the context of the EveryAware european project. The project and the experiment course will be illustrated and data analysis will be displayed. Then the Experimental Tribe platform for social computation will be introduced . It has been conceived to help researchers in the implementation of web experiments, and aims also to catalyze the cumulative growth of experimental methodologies and the standardization of tools cited above. In the last part, three other research experience which already took place on the Experimental Tribe platform will be discussed in detail, from the design of the experiment to the analysis of the results and, eventually, to the modeling of the systems involved. The experiments are: CityRace, about the measurement of human traffic-facing strategies; laPENSOcosì, aiming to unveil the political opinion structure; AirProbe, implemented again in the EveryAware project framework, which consisted in monitoring air quality opinion shift of a community informed about local air pollution. At the end, the evolution of the technosocial systems investigation methods shall emerge together with the opportunities and the threats offered by this new scientific path.

Development of new molecular methods for the diagnosis and the study of viral diseases of fish

The increase in aquaculture operations worldwide has provided new opportunities for the transmission of aquatic viruses. The occurrence of viral diseases remains a significant limiting factor in aquaculture production and for the sustainability. The ability to identify quickly the presence/absence of a pathogenic organism in fish would have significant advantages for the aquaculture systems. Several molecular methods have found successful application in fish pathology both for confirmatory diagnosis of overt diseases and for detection of asymptomatic infections. However, a lot of different variants occur among fish host species and virus strains and consequently specific methods need to be developed and optimized for each pathogen and often also for each host species. The first chapter of this PhD thesis presents a complete description of the major viruses that infect fish and provides a relevant information regarding the most common methods and emerging technologies for the molecular diagnosis of viral diseases of fish. The development and application of a real time PCR assay for the detection and quantification of lymphocystivirus was described in the second chapter. It showed to be highly sensitive, specific, reproducible and versatile for the detection and quantitation of lymphocystivirus. The use of this technique can find multiple application such as asymptomatic carrier detection or pathogenesis studies of different LCDV strains. The third chapter, a multiplex RT-PCR (mRT-PCR) assay was developed for the simultaneous detection of viral haemorrhagic septicaemia (VHS), infectious haematopoietic necrosis (IHN), infectious pancreatic necrosis (IPN) and sleeping disease (SD) in a single assay. This method was able to efficiently detect the viral RNA in tissue samples, showing the presence of single infections and co-infections in rainbow trout samples. The mRT-PCR method was revealed to be an accurate and fast method to support traditional diagnostic techniques in the diagnosis of major viral diseases of rainbow trout.

Matrix Designs and Methods for Secure and Efficient Compressed Sensing

The idea of balancing the resources spent in the acquisition and encoding of natural signals strictly to their intrinsic information content has interested nearly a decade of research under the name of compressed sensing. In this doctoral dissertation we develop some extensions and improvements upon this technique's foundations, by modifying the random sensing matrices on which the signals of interest are projected to achieve different objectives. Firstly, we propose two methods for the adaptation of sensing matrix ensembles to the second-order moments of natural signals. These techniques leverage the maximisation of different proxies for the quantity of information acquired by compressed sensing, and are efficiently applied in the encoding of electrocardiographic tracks with minimum-complexity digital hardware. Secondly, we focus on the possibility of using compressed sensing as a method to provide a partial, yet cryptanalysis-resistant form of encryption; in this context, we show how a random matrix generation strategy with a controlled amount of perturbations can be used to distinguish between multiple user classes with different quality of access to the encrypted information content. Finally, we explore the application of compressed sensing in the design of a multispectral imager, by implementing an optical scheme that entails a coded aperture array and Fabry-Pérot spectral filters. The signal recoveries obtained by processing real-world measurements show promising results, that leave room for an improvement of the sensing matrix calibration problem in the devised imager.

Assessment of the population structure and temporal changes in spatial dynamics and genetic characteristics of the Atlantic bluefin tuna under a fishery independent framework.

As a large and long-lived species with high economic value, restricted spawning areas and short spawning periods, the Atlantic bluefin tuna (BFT; Thunnus thynnus) is particularly susceptible to over-exploitation. Although BFT have been targeted by fisheries in the Mediterranean Sea for thousands of years, it has only been in these last decades that the exploitation rate has reached far beyond sustainable levels. An understanding of the population structure, spatial dynamics, exploitation rates and the environmental variables that affect BFT is crucial for the conservation of the species. The aims of this PhD project were 1) to assess the accuracy of larval identification methods, 2) determine the genetic structure of modern BFT populations, 3) assess the self-recruitment rate in the Gulf of Mexico and Mediterranean spawning areas, 4) estimate the immigration rate of BFT to feeding aggregations from the various spawning areas, and 5) develop tools capable of investigating the temporal stability of population structuring in the Mediterranean Sea. Several weaknesses in modern morphology-based taxonomy including demographic decline of expert taxonomists, flawed identification keys, reluctance of the taxonomic community to embrace advances in digital communications and a general scarcity of modern user-friendly materials are reviewed. Barcoding of scombrid larvae revealed important differences in the accuracy of the taxonomic identifications carried out by different ichthyoplanktologists following morphology-based methods. Using a Genotyping-by-Sequencing a panel of 95 SNPs was developed and used to characterize the population structuring of BFT and composition of adult feeding aggregations. Using novel molecular techniques, DNA was extracted from bluefin tuna vertebrae excavated from late iron age, ancient roman settlements Byzantine-era Constantinople and a 20th century collection. A second panel of 96 SNPs was developed to genotype historical and modern samples in order to elucidate changes in population structuring and allele frequencies of loci associated with selective traits.

Analysis of cumulative effects of multiple stressors on saltmarshes and consideration of management options

Natural systems face pressures exerted by natural physical-chemical forcings and a myriad of co-occurring human stressors that may interact to cause larger than expected effects, thereby presenting a challenge to ecosystem management. This thesis aimed to develop new information that can contribute to reduce the existing knowledge gaps hampering the holistic management of multiple stressors. I undertook a review of the state-of-the-art methods to detect, quantify and predict stressor interactions, identifying techniques that could be applied in this thesis research. Then, I conducted a systematic review of saltmarsh multiple stressor studies in conjunction with a multiple stressor mapping exercise for the study system in order to infer potential important synergistic stressor interactions. This analysis identified key stressors that are affecting the study system, but also pointed to data gaps in terms of driver and pressure data and raised issues for potentially overlooked stressors. Using field mesocosms, I explored how a local stressor (nutrient availability) affects the responses of saltmarsh vegetation to a global stressor (increased inundation) in different soil types. Results indicate that saltmarsh vegetation would be more drastically affected by increased inundation in low than in medium organic matter soils, and especially in estuaries already under high nutrient availability. In another field experiment, I examined the challenges of managing co-occurring and potentially interacting local stressors on saltmarsh vegetation: recreational trampling and smothering by deposition of excess macroalgal wrack due to high nutrient loads. Trampling and wrack prevention had interacting effects, causing non-linear responses of the vegetation to simulated management of these stressors, such that vegetation recovered only in those treatments simulating the combined prevention of both stressors. During this research I detected, using molecular genetic methods, a widespread presence of S. anglica (and to a lesser extent S. townsendii), two previously unrecorded non-native Spartinas in the study areas.

Ancient Greek harbours used as geo-archives for palaeotsunami research : case studies from Krane (Cefalonia), Lechaion (Gulf of Corinth) and Kyllini (Peloponnese)

Since historical times, coastal areas throughout the eastern Mediterranean are exposed to tsunami hazard. For many decades the knowledge about palaeotsunamis was solely based on historical accounts. However, results from timeline analyses reveal different characteristics affecting the quality of the dataset (i.e. distribution of data, temporal thinning backward of events, local periodization phenomena) that emphasize the fragmentary character of the historical data. As an increasing number of geo-scientific studies give convincing examples of well dated tsunami signatures not reported in catalogues, the non-existing record is a major problem to palaeotsunami research. While the compilation of historical data allows a first approach in the identification of areas vulnerable to tsunamis, it must not be regarded as reliable for hazard assessment. Considering the increasing economic significance of coastal regions (e.g. for mass tourism) and the constantly growing coastal population, our knowledge on the local, regional and supraregional tsunami hazard along Mediterranean coasts has to be improved. For setting up a reliable tsunami risk assessment and developing risk mitigation strategies, it is of major importance (i) to identify areas under risk and (ii) to estimate the intensity and frequency of potential events. This approach is most promising when based on the analysis of palaeotsunami research seeking to detect areas of high palaeotsunami hazard, to calculate recurrence intervals and to document palaeotsunami destructiveness in terms of wave run-up, inundation and long-term coastal change. Within the past few years, geo-scientific studies on palaeotsunami events provided convincing evidence that throughout the Mediterranean ancient harbours were subject to strong tsunami-related disturbance or destruction. Constructed to protect ships from storm and wave activity, harbours provide especially sheltered and quiescent environments and thus turned out to be valuable geo-archives for tsunamigenic high-energy impacts on coastal areas. Directly exposed to the Hellenic Trench and extensive local fault systems, coastal areas in the Ionian Sea and the Gulf of Corinth hold a considerably high risk for tsunami events, respectively.Geo-scientific and geoarcheaological studies carried out in the environs of the ancient harbours of Krane (Cefalonia Island), Lechaion (Corinth, Gulf of Corinth) and Kyllini (western Peloponnese) comprised on-shore and near-shore vibracoring and subsequent sedimentological, geochemical and microfossil analyses of the recovered sediments. Geophysical methods like electrical resistivity tomography and ground penetrating radar were applied in order to detect subsurface structures and to verify stratigraphical patterns derived from vibracores over long distances. The overall geochronological framework of each study area is based on radiocarbon dating of biogenic material and age determination of diagnostic ceramic fragments. Results presented within this study provide distinct evidence of multiple palaeotsunami landfalls for the investigated areas. Tsunami signatures encountered in the environs of Krane, Lechaion and Kyllini include (i) coarse-grained allochthonous marine sediments intersecting silt-dominated quiescent harbour deposits and/or shallow marine environments, (ii) disturbed microfaunal assemblages and/or (iii) distinct geochemical fingerprints as well as (iv) geo-archaeological destruction layers and (v) extensive units of beachrock-type calcarenitic tsunamites. For Krane, geochronological data yielded termini ad or post quem (maximum ages) for tsunami event generations dated to 4150 ± 60 cal BC, ~ 3200 ± 110 cal BC, ~ 650 ± 110 cal BC, and ~ 930 ± 40 cal AD, respectively. Results for Lechaion suggest that the harbour was hit by strong tsunami impacts in the 8th-6th century BC, the 1st-2nd century AD and in the 6th century AD. At Kyllini, the harbour site was affected by tsunami impact in between the late 7th and early 4th cent. BC and between the 4th and 6th cent. AD. In case of Lechaion and Kyllini, the final destruction of the harbour facilities also seems to be related to the tsunami impact. Comparing the tsunami signals obtained for each study areas with geo-scientific data from palaeotsunami events from other sites indicates that the investigated harbour sites represent excellent geo-archives for supra-regional mega-tsunamis.