Recombinant Collagen Engineered to Bind to Discoidin Domain Receptors Functions as a Receptor Inhibitor

A bacterial collagen-like protein Scl2 has been developed as a recombinant collagen model system to host human collagen ligand-binding sequences, with the goal of generating biomaterials with selective collagen bioactivities. Defined binding sites in human collagen for integrins, fibronectin, heparin, and MMP-1 have been introduced into the triple-helical domain of the bacterial collagen and led to the expected biological activities. The modular insertion of activities is extended here to the discoidin domain receptors (DDRs), which are collagen-activated receptor tyrosine kinases. Insertion of the DDR-binding sequence from human collagen III into bacterial collagen led to specific receptor binding. However, even at the highest testable concentrations, the construct was unable to stimulate DDR autophosphorylation. The recombinant collagen expressed in Escherichia coli does not contain hydroxyproline (Hyp), and complementary synthetic peptide studies showed that replacement of Hyp by Pro at the critical Gly-Val-Met-Gly-Phe-Hyp position decreased the DDR-binding affinity and consequently required a higher concentration for the induction of receptor activation. The ability of the recombinant bacterial collagen to bind the DDRs without inducing kinase activation suggested it could interfere with the interactions between animal collagen and the DDRs, and such an inhibitory role was confirmed in vitro and with a cell migration assay. This study illustrates that recombinant collagen can complement synthetic peptides in investigating structure-activity relationships, and this system has the potential for the introduction or inhibition of specific biological activities

Clonal Chromosome Anomalies Affecting Fli1 Mimic Inherited Thrombocytopenia Of The Paris-Trousseau Type

Introduction: The thrombocytopenia of the Paris-Trousseau (TCPT) type is a contiguous gene syndrome characterized by mild bleeding tendency, variable thrombocytopenia (THC), abnormal giant alpha-granules in platelets and dysmegakaryopoiesis: it derives from a constitutional deletion of chromosome 11 leading to the loss of FLI1, a transcription factor involved in megakaryocyte differentiation and maturation. Case report: A women with an acquired, isolated THC developing over 10 yr showed morphological features typical of TCPT in platelets and bone marrow (BM). Twenty years after the onset of THC, the other hematological parameters are still normal and the patient is well. Results: Clonal hemopoiesis was shown and chromosome analyses performed on BM revealed a clone with 45 chromosomes and a complex unbalanced translocation involving chromosomes 2, 3, and 11. The anomaly was present in the majority of bone marrow cells but only in a few peripheral blood elements. A microarray-based comparative genomic hybridization defined the deleted region of chromosome 11 including the FLI1 locus that was missing. Conclusion: Although our patient presented with nearly all the characteristics of TCPT, her illness was acquired instead of being inherited and the most appropriate diagnosis is that of the unilineage dysplasia 'refractory THC.' This observation suggests that appropriate cytogenetic investigations should be always considered in patients with acquired THC of unknown origin

Sportsman's hernia? An ambiguous term.

Groin pain is common in athletes. Yet, there is disagreement on aetiology, pathomechanics and terminology. A plethora of terms have been employed to explain inguinal-related groin pain in athletes. Recently, at the British Hernia Society in Manchester 2012, a consensus was reached to use the term inguinal disruption based on the pathophysiology while lately the Doha agreement in 2014 defined it as inguinal-related groin pain, a clinically based taxonomy. This review article emphasizes the anatomy, pathogenesis, standard clinical assessment and imaging, and highlights the treatment options for inguinal disruption

Age- and sex-related variations in platelet count in Italy: a proposal of reference ranges based on 40987 subjects' data

BACKGROUND AND OBJECTIVES: Although several studies demonstrated that platelet count is higher in women, decreases with age, and is influenced by genetic background, most clinical laboratories still use the reference interval 150-400×10(9) platelets/L for all subjects. The present study was to identify age- and sex-specific reference intervals for platelet count. METHODS: We analysed electronic records of subjects enrolled in three population-based studies that investigated inhabitants of seven Italian areas including six geographic isolates. After exclusion of patients with malignancies, liver diseases, or inherited thrombocytopenias, which could affect platelet count, reference intervals were estimated from 40,987 subjects with the non parametric method computing the 2.5° and 97.5° percentiles. RESULTS: Platelet count was similar in men and women until the age of 14, but subsequently women had steadily more platelets than men. The number of platelets decreases quickly in childhood, stabilizes in adulthood, and further decreases in oldness. The final result of this phenomenon is that platelet count in old age was reduced by 35% in men and by 25% in women compared with early infancy. Based on these findings, we estimated reference intervals for platelet count ×10(9)/L in children (176-452), adult men (141-362), adult women (156-405), old men (122-350) and, old women (140-379). Moreover, we calculated an extended reference interval that takes into account the differences in platelet count observed in different geographic areas. CONCLUSIONS: The age-, sex-, and origin-related variability of platelet count is very wide, and the patient-adapted reference intervals we propose change the thresholds for diagnosing both thrombocytopenia and thrombocytosis in Italy

On the continuous and reactive analysis of a variety of spatio-temporal data

Negli ultimi anni, in un numero sempre crescente di situazioni, é nata la necessitá di prendere decisioni in modo reattivo basandosi su flussi di dati continui ed eterogenei. In questo contesto, l’ambiente urbano risulta particolarmente rilevante grazie alla presenza di una fitta rete di interazioni tra le persone e lo spazio cittadino. Questa rete produce un’enorme quantitá di dati spazio-temporali che si evolvono velocemente nel tempo. Inoltre, in ambito cittadino convivono una moltitudine di stakeholder interessati allo sviluppo di un processo decisionale reattivo per la pianificazione urbana, la gestione della mobilitá, il turismo, ecc. L’uso sempre piú ampio della geo-localizzazione nei social network e, piú in generale, la diffusione di dispositivi di comunicazione mobili, ha migliorato la capacitá di creare un’accurata rappresentazione della realtá in tempo reale, in inglese spesso denominata Digital footprint o Digital reflection o Digital twin. Cinque anni fa, lo stato dell’arte sfruttava solo una singola fonte di dati, ad esempio, i social media o i dati telefonici. Tuttavia, un uso simultaneo di piú fonti dati eterogenee, aiuta a creare una piú accurata rappresentazione digitale della realtá. n questo contesto, abbiamo affrontato il problema della creazione di un modello concettuale olistico per rappresentare dati spazio-temporali eterogenei e il problema dello sviluppo di un modello computazionale per flussi di dati continui. I principali risultati di questa ricerca sono un modello concettuale chiamato FraPPE e un modello computazionale denominato RIVER con le sue implementazioni. FraPPE é un modello concettutale, piú precisamente un’ontologia, che sfrutta termini dell’elaborazione delle immagini (in inglese, Image Processing) per modellare dati spazio-temporali e abilitare analisi nell’ambito spaziale, temporale e di contenuto. FraPPE sfrutta termini comuni nell’ambito dell’image processing per colmare il divario tra la prospettiva del data engineer e quella dell’analista. L’annullamento di questo divario permette di abilitare analisi visuale su dati spazio-temporali. Durante questo percorso di dottorato, abbiamo per prima cosa formalizzato in FraPPE 1.0 i concetti spaziali e temporali, abbiamo poi aggiunto i frammenti relativi alla provenienza del dato (Data Provenance in inglese) del dato e al suo contenuto in FraPPE 2.0. Abbiamo controllato che entrambe le versioni di FraPPE rispettassero i cinque principi di Tom Gruber, e abbiamo dimostrato la validitá del modello concettuale attraverso casi d’uso reali. RIVER é un modello computazionale per flussi di dati continui ed é basato su due principi: (P1) tutti i dati possono essere modellati come flussi continui – un motore per l’analisi di flussi di dati deve essere in grado di accettare in ingresso flussi di dati con differenti velocitá, di qualsiasi dimensione e provenienti da qualsiasi fonte –, e (P2) Ingestion Continua – il sistema deve catturare continuamente i dati che, una volta arrivati, vengono marcati con un timestamp crescente. Al contrario della maggior parte dei motori per l’analisi di flussi, che trasforma e adatta il dato non appena questo entra nel sistema, RIVER é costruito intorno all’idea della LazyTransformation. Un sistema che implementa RIVER, ritarda la trasformazione del dato in ingresso fino a quandoil sistema puó beneficiare di tale trasformazione. Abbiamo formulato l’ipotesi secondo cui la Lazy Transformation permette di risparmiare tempo e risorse durante la computazione. RIVER si basa principalmente su due concetti: il Generic Data Stream(S⟨T⟩) e la Generic Time-Varying Collection (C⟨T⟩) e propone cinque operatori per l’ingestion, l’eleaborazione e l’emissione di flussi di dati. L’operatore IN⟨T⟩ rappresenta la porta d’ingresso del sistema, prende un flusso di dati esterno e crea un nuovo S⟨T⟩. Gli operatori S2C⟨T⟩, C2C⟨T, T′⟩ e C2S⟨T⟩ sono ispirati al Continuous Query Language(CQL, il lavoro seminale dell’Università di Standford sull’elaborazione di flussi continui di dati) e permettono la trasformazione da S⟨T⟩ a C⟨T⟩ e vice-versa. L’operatore OUT⟨T⟩ trasforma un S⟨T⟩ in un nuovo flusso di dati esterno. Sfruttando il Pipeline Definition Language (PDL) – il nostro linguaggio visuale che astrae la complessitá implementativa degli operatori –, RIVER abilita l’utente a definire piani computazionali sotto forma di pipeline di operatori. In questa tesi, proponiamo tre implementazioni di RIVER: Natron – un’implementazione single-threaded scalabile verticalmente –, rvr@Spark e rvr@Hive – due implementazioni a scalabilitá orizzontale basate su framework distribuiti (Spark e Hive). Con l’intento di provare la validitá dell’approccio basato sulla Lazy Transformation, abbiamo valutato Natron rispetto al nostro motore Streaming Linked Data che trasforma il dato non appena questo entra nel sistema. Il risultato di questa valutazione dimostra che Natron consuma meno risorse, in termini di processore e memoria, e approssima meglio la risposta corretta in condizioni di stress. Per determinare l’efficacia di Natron sotto l’aspetto dei costi, l’abbiamo valutato rispetto a rvr@Spark, in modo da provare che una soluzione distribuita non é la migliore in tutte le condizioni. Analizzando dati telefonici a diversa scala (cittadina, regionale, nazionale ed estrema), abbiamo osservato che Natron risulta piú efficace, sotto l’aspetto dei costi, rispetto a rvr@Spark per dati fino alla scala nazionale. I risultati di questa valutazioni dimostrano la validitá dell’approccio basato sulla Lazy Transformation e confermano che, nell’ambito dei motori di analisi di flussi di dati, la soluzione distribuita non é sempre la migliore. Per dimostrare la capacita ́di FraPPE e RIVER di abilitare un processo decisionale reattivo basato su flussi di dati spazio-temporali eterogenei, abbiamo presentato cinque casi d’uso reali portati avanti nelle cittá di Milano e Como. Durante questi casi di studio, abbiamo presentato le visualizzazioni a platee diverse (partecipanti ad eventi e stackeholder cittadini) per dimostrare la validitá delle nostre interfacce visuali. Infine, abbiamo riflettuto sulle limitazioni delle soluzioni proposte e preso decisioni riguardo la direzione futura di questo lavoro di ricerca. In particolare, le nostre riflessioni hanno riguardato le capacitá di ragionamento automatico abilitate da FraPPE, le future valutazioni di RIVER basate su casi d’uso piú lunghi e complessi, e l’evoluzione del Pipeline Definition Language (PDL).In recent years, an increasing number of situations call for reactive decisions making process based on a heterogeneous streaming data. In this context, the urban environment results particularly relevant, because there is a dense network of interactions between people and urban spaces that produces a great amount of spatio-temporal fast evolving data. Moreover, in a modern city there is a multitude of stakeholders who are interested in reactive decisions for urban planning, mobility management, tourism, etc. The growing usage of location-based social networks, and, in general, the diffusion of mobile devices improved the ability to create an accurate and up-to-date representation of reality (a.k.a. Digital footprint or Digital reflection or Digital twin). Five years ago, the state of the art was exploiting only a single data source either social media or mobile phones. However, better decisions can result from the analyses of multiple data sources simultaneously. Multiple heterogeneous data sources, and their simultaneous usage, of- fer a more accurate digital reflection of the reality. In this context, we investigate the problem of how to create an holistic conceptual model to represent multiple heterogeneous spatio-temporal data and how to develop a streaming computational model to enable reactive decisions. The main outcomes of this research are FraPPE conceptual model and RIVER streaming computational model with its implementations. FraPPE is a conceptual model, more precisely an ontology, that exploits digital image processing terms to model spatio-temporal data and to enable space, time, and content analysis. It uses image processing common terms to bridge the gap between the data engineer perspective and visual data analysis perspective. It does so to enable visual analytics on spatio-temporal data. During my PhD, we first formalize the spatial and temporal concepts in FraPPE 1.0, and, then, we add concepts related to the provenance and the content in FraPPE 2.0. We check the adherence of both versions of FraPPE to the five Tom Gruber’s principles, and demonstrate the validity of the conceptual model in real world use cases. RIVER is a streaming computational inspired by two principles:(P1) everything is a data stream – a variety-proof stream processing engine must indifferently ingest data with different velocities from any sources and of any size –, and (P2) Continuous Ingestion – the data in input is continuously captured by the system and, once arrived, it is marked with an increasing timestamp. Most of the stream processing engines in the state of the art transform and adapt data at ingestion time. Contrariwise, RIVER is built around the idea of Lazy Transformation. So,a system that implements RIVER postpones data transformations until it can really benefits from them. Our hypothesis is that Lazy Transformation saves time and resources. RIVER relies on two main concepts: the Generic Data Stream (S⟨T⟩) and the Generic Time-Varying Collection (C⟨T⟩) and it proposes five different operators in order to ingest, process and emit data. The IN⟨T⟩ operator is the entry point of the system, it takes an external data flow and injects the items into the system creating a new S⟨T⟩. The S2C⟨T⟩, C2C⟨T, T′⟩ and C2S⟨T⟩ operators in RIVER, inspired to the Continuous Query Language(CQL, the work on streaming data proposed by the Stanford DB Group) processing model, allows to move from S⟨T⟩ to C⟨T⟩ and vice-versa. The OUT⟨T⟩ operator transform an S⟨T⟩ into a new external data flow. Exploiting the Pipeline Definition Language (PDL) – our graphical language to abstract the operators’ implementation complexity –, RIVER allows users to define computational plans, in the form of pipelines. In this thesis, we propose three different implementations of RIVER: Natron – a single-threaded vertically scalable implementation –, rvr@Spark and rvr@Hive – two horizontally scalable implementations based on distributed technologies (Spark and Hive). In order to prove the validity of the Lazy Transformation approach, we first evaluate Natron against our Streaming Linked Data engine that performs the data transformation at ingestion time. The result of this evaluation shows that Natron is cheaper – it consumes less resources in terms of memory and CPU load – and better approximates the correct answer under stress conditions. Moreover, we evaluate the cost effectiveness of Natron against rvr@Spark to prove that a distributed solution does not pay in all the situations. Indeed, in a mobile telco analysis, we observe that Natron is more cost-effective than rvr@Spark up to the scale of a nation. The results of those evaluations demonstrate the validity of the Lazy Transformation approach and confirm, in the stream processing engine field, that the a distributed solution does not pay at all scale. In order to prove the feasibility and the effectiveness of FraPPE and RIVER in enabling reactive decision-making processes on heterogeneous streaming spatio-temporal data, we present five real world use cases in Milan and Como. Moreover, during those case studies, we propose the data visualizations to different audiences (public users and stakeholders) in order to prove the guessability of our visual analytics interfaces. Finally, we reflect on limitations and state the future directions of this research work. In particular, those reflections involve the reasoning capabilities enabled by FraPPE, the future evaluations of RIVER against longer and more complex use cases and the evolution out the Pipeline Definition Language (PDL).DIPARTIMENTO DI ELETTRONICA, INFORMAZIONE E BIOINGEGNERIAComputer Science and Engineering30CERI, STEFANOPERNICI, BARBAR

MYH9-related disease: Five novel mutations expanding the spectrum of causative mutations and confirming genotype/phenotype correlations

MYH9-related disease (MYH9-RD) is a rare autosomal dominant syndromic disorder caused by mutations in MYH9, the gene encoding for the heavy chain of non-muscle myosin IIA (myosin-9). MYH9-RD is characterized by congenital macrothrombocytopenia and typical inclusion bodies in neutrophils associated with a variable risk of developing sensorineural deafness, presenile cataract, and/or progressive nephropathy. The spectrum of mutations responsible for MYH9-RD is limited. We report five families, each with a novel MYH9 mutation. Two mutations, p.Val34Gly and p.Arg702Ser, affect the motor domain of myosin-9, whereas the other three, p.Met847_Glu853dup, p.Lys1048_Glu1054del, and p.Asp1447Tyr, hit the coiled-coil tail domain of the protein. The motor domain mutations were associated with more severe clinical phenotypes than those in the tail domain.Fil: de Rocco, Daniela. Istituto di Ricovero e Cura a Carattere Scientifico "Burlo Garofolo"; ItaliaFil: Zieger, Barbara. University of Freiburg; AlemaniaFil: Platokouki, Helen. “Aghia Sophia” Children; GreciaFil: Heller, Paula Graciela. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Investigaciones Medicas; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Pastore, Annalisa. National Institute for Medical Research; Reino UnidoFil: Bottega, Roberta. Istituto di Ricovero e Cura a Carattere Scientifico "Burlo Garofolo"; ItaliaFil: Noris, Patrizia. Istituto di Ricovero e Cura a Carattere Scientifico "Burlo Garofolo"; Italia. University of Pavia; ItaliaFil: Barozzi, Serena. Istituto di Ricovero e Cura a Carattere Scientifico "Burlo Garofolo"; Italia. University of Pavia; ItaliaFil: Glembotsky, Ana Claudia. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; Argentina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Investigaciones Medicas; ArgentinaFil: Pergantou, Helen. “Aghia Sophia” Children; GreciaFil: Balduini, Carlo L.. Istituto di Ricovero e Cura a Carattere Scientifico "Burlo Garofolo"; Italia. University of Pavia; ItaliaFil: Savoia, Anna. Istituto di Ricovero e Cura a Carattere Scientifico "Burlo Garofolo"; Italia. Universita Degli Studi Di Trieste; ItaliaFil: Pecci, Alessandro. Istituto di Ricovero e Cura a Carattere Scientifico "Burlo Garofolo"; Italia. University of Pavia; Itali

Shippers’ choice behaviour on choosing transport mode: a case of ASEAN region

Using South East Asia as a case study, shippers’ choice of transport modes taking into consideration their economic and environmental impacts was examined in this research. A triangulation of both quantitative and qualitative methods was deployed. First, a quantitative analysis using secondary data was conducted to establish the index score, which includes four quantitative factors (transport distance, cost, time, and CO2 emission), for each transport mode. In addition, in order to examine at what level of the importance weight shippers would change their decision on transport mode, a sensitivity analysis involving the four aforesaid factors was also conducted. Next, an in-depth interview with a major shipper in Singapore was also carried out to qualitatively validate the aforesaid four quantitative factors as well as two additional qualitative factors, namely, customer service and shipper-forwarder relationship in relation to shipper’s choice. The results from this study indicate that shippers might change to the short-sea shipping (SSS) mode when the importance weights of cost and CO2 emission increase, and to trucking mode when the weight of time decreases. It was also found that cost is the most important factor when shippers choose carriers/forwarders, whereas CO2 emission is not an important factor at the current stage. However, if the government imposes financial measures such as fine and/or tax for CO2 emission, shippers would choose eco-friendlier transport modes. This research is the first study considering the environmental issue as one of important factors that influence shippers’ choice behaviour. This research also facilitates managers’ understanding on how shippers may select LSPs taking into account important factors including the environmental consideration