The abuse of intellectual property rights and regulations in China: a law and economic analysis

From the institutional point of view, the legal system of IPR (intellectual property right, hereafter, IPR) is one of incentive institutions of innovation and it plays very important role in the development of economy. According to the law, the owner of the IPR enjoy a kind of exclusive right to use his IP(intellectual property, hereafter, IP), in other words, he enjoys a kind of legal monopoly position in the market. How to well protect the IPR and at the same time to regulate the abuse of IPR is very interested topic in this knowledge-orientated market and it is the basic research question in this dissertation. In this paper, by way of comparing study and by way of law and economic analyses, and based on the Austrian Economics School’s theories, the writer claims that there is no any contradiction between the IPR and competition law. However, in this new economy (high-technology industries), there is really probability of the owner of IPR to abuse his dominant position. And with the characteristics of the new economy, such as, the high rates of innovation, “instant scalability”, network externality and lock-in effects, the IPR “will vest the dominant undertakings with the power not just to monopolize the market but to shift such power from one market to another, to create strong barriers to enter and, in so doing, granting the perpetuation of such dominance for quite a long time.”1 Therefore, in order to keep the order of market, to vitalize the competition and innovation, and to benefit the customer, in EU and US, it is common ways to apply the competition law to regulate the IPR abuse. In Austrian Economic School perspective, especially the Schumpeterian theories, the innovation/competition/monopoly and entrepreneurship are inter-correlated, therefore, we should apply the dynamic antitrust model based on the AES theories to analysis the relationship between the IPR and competition law. China is still a developing country with relative not so high ability of innovation. Therefore, at present, to protect the IPR and to make good use of the incentive mechanism of IPR legal system is the first important task for Chinese government to do. However, according to the investigation reports,2 based on their IPR advantage and capital advantage, some multinational companies really obtained the dominant or monopoly market position in some aspects of some industries, and there are some IPR abuses conducted by such multinational companies. And then, the Chinese government should be paying close attention to regulate any IPR abuse. However, how to effectively regulate the IPR abuse by way of competition law in Chinese situation, from the law and economic theories’ perspective, from the legislation perspective, and from the judicial practice perspective, there is a long way for China to go!

The role of the NadR regulator during infection and its implication for the coverage of a new Meningococcus B vaccine

Background: Neisseria meningitides represents a major cause of meningitis and sepsis. The meningococcal regulator NadR was previously shown to repress the expression of the Neisserial Adhesin A (NadA) and play a major role in its phase-variation. NadA is a surface exposed protein involved in epithelial cell adhesion and colonization and a major component of 4CMenB, a novel vaccine to prevent meningococcus serogroup B infection. The NadR mediated repression of NadA is attenuated by 4-HPA, a natural molecule released in human saliva. Results: In this thesis we investigated the global role of NadR during meningogoccal infection, identifying through microarray analysis the NadR regulon. Two distinct types of NadR targets were identified, differing in their promoter architectures and 4HPA responsive activities: type I are induced, while type II are co-repressed in response to the same 4HPA signal. We then investigate the mechanism of regulation of NadR by 4-HPA, generating NadR mutants and identifying classes or residues involved in either NadR DNA binding or 4HPA responsive activities. Finally, we studied the impact of NadR mediated repression of NadA on the vaccine coverage of 4CMenB. A selected MenB strains is not killed by sera from immunized infants when the strain is grown in vitro, however, in an in vivo passive protection model, the same sera protected infant rats from bacteremia. Finally, using bioluminescent reporters, nadA expression in the infant rat model was induced in vivo at 3 h post-infection. Conclusions: Our results suggest that NadR coordinates a broad transcriptional response to signals present in the human host, enabling the meningococcus to adapt to the relevant host niche. During infectious disease the effect of the same signal on NadR changes between different targets. In particular NadA expression is induced in vivo, leading to efficient killing of meningococcus by anti-NadA antibodies elicited by the 4CMenB vaccine.

Topological aspects of the human protein interaction network

It is currently widely accepted that the understanding of complex cell functions depends on an integrated network theoretical approach and not on an isolated view of the different molecular agents. Aim of this thesis was the examination of topological properties that mirror known biological aspects by depicting the human protein network with methods from graph- and network theory. The presented network is a partial human interactome of 9222 proteins and 36324 interactions, consisting of single interactions reliably extracted from peer-reviewed scientific publications. In general, one can focus on intra- or intermodular characteristics, where a functional module is defined as "a discrete entity whose function is separable from those of other modules". It is found that the presented human network is also scale-free and hierarchically organised, as shown for yeast networks before. The interactome also exhibits proteins with high betweenness and low connectivity which are biologically analyzed and interpreted here as shuttling proteins between organelles (e.g. ER to Golgi, internal ER protein translocation, peroxisomal import, nuclear pores import/export) for the first time. As an optimisation for finding proteins that connect modules, a new method is developed here based on proteins located between highly clustered regions, rather than regarding highly connected regions. As a proof of principle, the Mediator complex is found in first place, the prime example for a connector complex. Focusing on intramodular aspects, the measurement of k-clique communities discriminates overlapping modules very well. Twenty of the largest identified modules are analysed in detail and annotated to known biological structures (e.g. proteasome, the NFκB-, TGF-β complex). Additionally, two large and highly interconnected modules for signal transducer and transcription factor proteins are revealed, separated by known shuttling proteins. These proteins yield also the highest number of redundant shortcuts (by calculating the skeleton), exhibit the highest numbers of interactions and might constitute highly interconnected but spatially separated rich-clubs either for signal transduction or for transcription factors. This design principle allows manifold regulatory events for signal transduction and enables a high diversity of transcription events in the nucleus by a limited set of proteins. Altogether, biological aspects are mirrored by pure topological features, leading to a new view and to new methods that assist the annotation of proteins to biological functions, structures and subcellular localisations. As the human protein network is one of the most complex networks at all, these results will be fruitful for other fields of network theory and will help understanding complex network functions in general.

Implementation of network entropy algorithms on hpc machines, with application to high-dimensional experimental data

Network Theory is a prolific and lively field, especially when it approaches Biology. New concepts from this theory find application in areas where extensive datasets are already available for analysis, without the need to invest money to collect them. The only tools that are necessary to accomplish an analysis are easily accessible: a computing machine and a good algorithm. As these two tools progress, thanks to technology advancement and human efforts, wider and wider datasets can be analysed. The aim of this paper is twofold. Firstly, to provide an overview of one of these concepts, which originates at the meeting point between Network Theory and Statistical Mechanics: the entropy of a network ensemble. This quantity has been described from different angles in the literature. Our approach tries to be a synthesis of the different points of view. The second part of the work is devoted to presenting a parallel algorithm that can evaluate this quantity over an extensive dataset. Eventually, the algorithm will also be used to analyse high-throughput data coming from biology.

Phosphonic acid-containing molecules as proton conductors and linkers for hybrid materials

In dieser Arbeit werden zwei Arten von nicht-kovalent verknüpften Netzwerkstrukturen vorgestellt, die aus phosphonsäurehaltigen Molekülen aufgebaut sind. Einerseits sollen diese phosphonsäurehaltigen Moleküle als Protonenleiter in Brennstoffzellen eingesetzt werden. Dies ist durch die Möglichkeit des kooperativen Protonentransports in wasserstoffbrückenhaltigen Netzwerken begründet. Auf der anderen Seite sollen die phosphonsäurehaltigen Moleküle unter Einsatz von Metallkationen zur Darstellung ionischer Netzwerke verwendet werden. In diesem Fall fungieren die phosphonierten Moleküle als Linker in porösen organisch-anorganischen Hybridmaterialien, die sich beispielsweise zur Gasspeicherung eignen.rnEine Brennstoffzelle stellt Energie mit hoher Effizienz und geringer Umweltbelastung bereit. Das Herzstück der Brennstoffzelle ist die Elektrolytmembran, die auch als Separator oder Protonenaustauschmembran (PEM) bezeichnet wird. Es wird davon ausgegangen, daß der Schlüssel zur Weiterentwicklung der PEM-Brennstoffzellen in der Entwicklung von Elektrolyten liegt, die ausschließlich und effizient Protonen transportieren und darüber hinaus chemisch (oxidationsbeständig) und mechanisch stabil sind. Die mechanische Stabilität betrifft insbesondere den Betrieb der Brennstoffzelle bei hohen Temperaturen und niedriger relativer Feuchtigkeit. In dieser Arbeit wird ein neuartiger Ansatz zum Erreichen eines hohen Protonentransports im Festkörper vorgestellt, der auf dem Einsatz kleiner Moleküle beruht, die durch Selbstorganisation eine kontinuierliche protonenleitende Phase erzeugen. Bis jetzt stellt Hexakis(p-phosphonatophenyl)benzol das erste Beispiel eines kristallinen Protonenleiters dar, der im festen Zustand eine hohe und konstante Leistung zeigt. Die Modifizierung von Hexakis(p-phosphonatophenyl)benzol, entweder durch Änderung von para- zu meta-Substitution oder die Einführung von Alkylketten, führt zu Verbindungen geringerer Kristallinität und niedriger Protonenleitfähigkeit.rnIm zweiten Teil der Arbeit wurde 1,3,5-Tris(p-phosphonatophenyl)benzol als Linker in der Synthese von offenen Phosphonat-Netzwerken eingesetzt. Es bilden sich aufgrund der ionischen Wechselwirkung zwischen den positiv geladenen Metallkationen und den negativ geladenen Phosphonsäuregruppen hochstabile Feststoffe. Eines der wichtigsten Ergebnisse dieser Arbeit besteht darin, daß 1,3,5-Tris(p-phosphonatophenyl)benzol als Linker zum Aufbau poröser Hybridmaterialien eingesetzt werden kann. Zum ersten Mal wurde ein dreifach phosphoniertes organisches Molekül zum Aufbau mikroporöser offener Phosphonat-Netzwerke verwendet. Zudem konnte gezeigt werden, daß die Porosität mit dem Wachstumsmechanismus dieser Materialien zusammenhängt. Es ist nur dann möglich ein gleichfalls mikroporöses und kristallines ionisches Netzwerk auf der Grundlage phosphonierter Moleküle zu erhalten, wenn Linker und Konnektor die gleiche Geometrie und Funktionalität besitzen.rn

LPS-induced modifications in spontaneous network activity causes neuronal apoptosis in neonatal cerebral cortex

During the perinatal period the developing brain is most vulnerable to inflammation. Prenatal infection or exposure to inflammatory factors can have a profound impact on fetal neurodevelopment with long-term neurological deficits, such as cognitive impairment, learning deficits, perinatal brain damage and cerebral palsy. Inflammation in the brain is characterized by activation of resident immune cells, especially microglia and astrocytes whose activation is associated with a variety of neurodegenerative disorders like Alzheimer´s disease and Multiple sclerosis. These cell types express, release and respond to pro-inflammatory mediators such as cytokines, which are critically involved in the immune response to infection. It has been demonstrated recently that cytokines also directly influence neuronal function. Glial cells are capable of releaseing the pro-inflammatory cytokines MIP-2, which is involved in cell death, and tumor necrosis factor alpha (TNFalpha), which enhances excitatory synaptic function by increasing the surface expression of AMPA receptors. Thus constitutively released TNFalpha homeostatically regulates the balance between neuronal excitation and inhibition in an activity-dependent manner. Since TNFalpha is also involved in neuronal cell death, the interplay between neuronal activity MIP-2 and TNFalpha may control the process of cell death and cell survival in developing neuronal networks. An increasing body of evidence suggests that neuronal activity is important in the regulation of neuronal survival during early development, e.g. programmed cell death (apoptosis) is augmented when neuronal activity is blocked. In our study we were interested on the impact of inflammation on neuronal activity and cell survival during early cortical development. To address this question, we investigated the impact of inflammation on neuronal activity and cell survival during early cortical development in vivo and in vitro. Inflammation was experimentally induced by application of the endotoxin lipopolysaccharide (LPS), which initiates a rapid and well-characterized immune response. I studied the consequences of inflammation on spontaneous neuronal network activity and cell death by combining electrophysiological recordings with multi-electrode arrays and quantitative analyses of apoptosis. In addition, I used a cytokine array and antibodies directed against specific cytokines allowing the identification of the pro-inflammatory factors, which are critically involved in these processes. In this study I demonstrated a direct link between inflammation-induced modifications in neuronal network activity and the control of cell survival in a developing neuronal network for the first time. Our in vivo and in vitro recordings showed a fast LPS-induced reduction in occurrence of spontaneous oscillatory activity. It is indicated that LPS-induced inflammation causes fast release of proinflammatory factors which modify neuronal network activity. My experiments with specific antibodies demonstrate that TNFalpha and to a lesser extent MIP-2 seem to be the key mediators causing activity-dependent neuronal cell death in developing brain. These data may be of important clinical relevance, since spontaneous synchronized activity is also a hallmark of the developing human brain and inflammation-induced alterations in this early network activity may have a critical impact on the survival of immature neurons.

La cooperazione giudiziaria in rete nello spazio di liberta', sicurezza e giustizia

L’oggetto del lavoro si concentra sull’analisi in chiave giuridica del modello di cooperazione in rete tra le autorità nazionali degli Stati membri nel quadro dello Spazio LSG, allo scopo di valutarne il contributo, le prospettive e il potenziale. La trattazione si suddivide in due parti, precedute da una breve premessa teorica incentrata sull’analisi della nozione di rete e la sua valenza giuridica. La prima parte ricostruisce il percorso di maturazione della cooperazione in rete, dando risalto tanto ai fattori di ordine congiunturale quanto ai fattori giuridici e d’ordine strutturale che sono alla base del processo di retificazione dei settori giustizia e sicurezza. In particolare, vengono elaborati taluni rilievi critici, concernenti l’operatività degli strumenti giuridici che attuano il principio di mutuo riconoscimento e di quelli che danno applicazione al principio di disponibilità delle informazioni. Ciò allo scopo di evidenziare gli ostacoli che, di frequente, impediscono il buon esito delle procedure di cooperazione e di comprendere le potenzialità e le criticità derivanti dall’utilizzo della rete rispetto alla concreta applicazione di tali procedure. La seconda parte si focalizza sull’analisi delle principali reti attive in materia di giustizia e sicurezza, con particolare attenzione ai rispettivi meccanismi di funzionamento. La trattazione si suddivide in due distinte sezioni che si concentrano sulle a) reti che operano a supporto dell’applicazione delle procedure di assistenza giudiziaria e degli strumenti di mutuo riconoscimento e sulle b) reti che operano nel settore della cooperazione informativa e agevolano lo scambio di informazioni operative e tecniche nelle azioni di prevenzione e lotta alla criminalità - specialmente nel settore della protezione dell’economia lecita. La trattazione si conclude con la ricostruzione delle caratteristiche di un modello di rete europea e del ruolo che questo esercita rispetto all’esercizio delle competenze dell’Unione Europea in materia di giustizia e sicurezza.

Statistical mechanics formalism and methods for the analysis of real networks

This thesis provides a thoroughly theoretical background in network theory and shows novel applications to real problems and data. In the first chapter a general introduction to network ensembles is given, and the relations with “standard” equilibrium statistical mechanics are described. Moreover, an entropy measure is considered to analyze statistical properties of the integrated PPI-signalling-mRNA expression networks in different cases. In the second chapter multilayer networks are introduced to evaluate and quantify the correlations between real interdependent networks. Multiplex networks describing citation-collaboration interactions and patterns in colorectal cancer are presented. The last chapter is completely dedicated to control theory and its relation with network theory. We characterise how the structural controllability of a network is affected by the fraction of low in-degree and low out-degree nodes. Finally, we present a novel approach to the controllability of multiplex networks

Mathematical Optimization Applied to Thermal and Electrical Energy Systems

This Thesis aims at building and discussing mathematical models applications focused on Energy problems, both on the thermal and electrical side. The objective is to show how mathematical programming techniques developed within Operational Research can give useful answers in the Energy Sector, how they can provide tools to support decision making processes of Companies operating in the Energy production and distribution and how they can be successfully used to make simulations and sensitivity analyses to better understand the state of the art and convenience of a particular technology by comparing it with the available alternatives. The first part discusses the fundamental mathematical background followed by a comprehensive literature review about mathematical modelling in the Energy Sector. The second part presents mathematical models for the District Heating strategic network design and incremental network design. The objective is the selection of an optimal set of new users to be connected to an existing thermal network, maximizing revenues, minimizing infrastructure and operational costs and taking into account the main technical requirements of the real world application. Results on real and randomly generated benchmark networks are discussed with particular attention to instances characterized by big networks dimensions. The third part is devoted to the development of linear programming models for optimal battery operation in off-grid solar power schemes, with consideration of battery degradation. The key contribution of this work is the inclusion of battery degradation costs in the optimisation models. As available data on relating degradation costs to the nature of charge/discharge cycles are limited, we concentrate on investigating the sensitivity of operational patterns to the degradation cost structure. The objective is to investigate the combination of battery costs and performance at which such systems become economic. We also investigate how the system design should change when battery degradation is taken into account.

Membrane properties and synaptic integration of identified neuronal populations in the developing rodent neocortex

In my PhD work I concentrated on three elementary questions that are essential to understand the interactions between the different neuronal cell populations in the developing neocortex. The questions regarded the identity of Cajal-Retzius (CR) cells, the ubiquitous expression of glycine receptors in all major cell populations of the immature neocortex, and the role of taurine in the modulation of immature neocortical network activity.rnTo unravel whether CR cells of different ontogenetic origin have divergent functions I investigated the electrophysiological properties of YFP+ (derived from the septum and borders of the pallium) and YFP− CR cells (derived from other neocortical origins). This study demonstrated that the passive and active electrophysiological properties as well as features of GABAergic PSCs and glutamatergic currents are similar between both CR cell populations. These findings suggest that CR cells of different origins most probably support similar functions within the neuronal networks of the early postnatal cerebral cortex.rnTo elucidate whether glycine receptors are expressed in all major cell populations of the developing neocortex I analyzed the functional expression of glycine receptors on subplate (SP) cells. Activation of glycine receptors by glycine, -alanine and taurine elicited membrane responses that could be blocked by the selective glycinergic antagonist strychnine. Pharmacological experiments suggest that SP cells express functional heteromeric glycine receptors that do not contain 1 subunits. The activation of glycine receptors by glycine and taurine induced a membrane depolarization, which mediated excitatory effects. Considering the key role of SP cells in immature cortical networks and the development of thalamocortical connections, this glycinergic excitation may influence the properties of early cortical networks and the formation of cortical circuits.rnIn the third part of my project I demonstrated that tonic taurine application induced a massive increase in the frequency of PSCs. Based on their reversal potential and their pharmacological properties these taurine-induced PSCs are exclusively transmitted via GABAA receptors to the pyramidal neurons, while both GABAA and glycine receptors were implicated in the generation of the presynaptic activity. Accordingly, whole-cell and cell-attached recordings from genetically labeled interneurons revealed the expression of glycine and GABAA receptors, which mediated an excitatory action on these cells. These findings suggest that low taurine concentrations can tonically activate exclusively GABAergic networks. The activity level maintained by this GABAergic activity in the immature nervous system may contribute to network properties and can facilitate the activity dependent formation of adequate synaptic projections.rnIn summary, the results of my studies complemented the knowledge about neuronal interactions in the immature neocortex and improve our understanding of cellular processes that guide neuronal development and thus shape the brain.rn

Cognitive Assessment and Rehabilitation of subjects with Traumatic Brain Injury

This thesis regards the study and the development of new cognitive assessment and rehabilitation techniques of subjects with traumatic brain injury (TBI). In particular, this thesis i) provides an overview about the state of art of this new assessment and rehabilitation technologies, ii) suggests new methods for the assessment and rehabilitation and iii) contributes to the explanation of the neurophysiological mechanism that is involved in a rehabilitation treatment. Some chapters provide useful information to contextualize TBI and its outcome; they describe the methods used for its assessment/rehabilitation. The other chapters illustrate a series of experimental studies conducted in healthy subjects and TBI patients that suggest new approaches to assessment and rehabilitation. The new proposed approaches have in common the use of electroencefalografy (EEG). EEG was used in all the experimental studies with a different purpose, such as diagnostic tool, signal to command a BCI-system, outcome measure to evaluate the effects of a treatment, etc. The main achieved results are about: i) the study and the development of a system for the communication with patients with disorders of consciousness. It was possible to identify a paradigm of reliable activation during two imagery task using EEG signal or EEG and NIRS signal; ii) the study of the effects of a neuromodulation technique (tDCS) on EEG pattern. This topic is of great importance and interest. The emerged founding showed that the tDCS can manipulate the cortical network activity and through the research of optimal stimulation parameters, it is possible move the working point of a neural network and bring it in a condition of maximum learning. In this way could be possible improved the performance of a BCI system or to improve the efficacy of a rehabilitation treatment, like neurofeedback.

Enhancing quality of service in software-defined networks

Resource management is of paramount importance in network scenarios and it is a long-standing and still open issue. Unfortunately, while technology and innovation continue to evolve, our network infrastructure system has been maintained almost in the same shape for decades and this phenomenon is known as “Internet ossification”. Software-Defined Networking (SDN) is an emerging paradigm in computer networking that allows a logically centralized software program to control the behavior of an entire network. This is done by decoupling the network control logic from the underlying physical routers and switches that forward traffic to the selected destination. One mechanism that allows the control plane to communicate with the data plane is OpenFlow. The network operators could write high-level control programs that specify the behavior of an entire network. Moreover, the centralized control makes it possible to define more specific and complex tasks that could involve many network functionalities, e.g., security, resource management and control, into a single framework. Nowadays, the explosive growth of real time applications that require stringent Quality of Service (QoS) guarantees, brings the network programmers to design network protocols that deliver certain performance guarantees. This thesis exploits the use of SDN in conjunction with OpenFlow to manage differentiating network services with an high QoS. Initially, we define a QoS Management and Orchestration architecture that allows us to manage the network in a modular way. Then, we provide a seamless integration between the architecture and the standard SDN paradigm following the separation between the control and data planes. This work is a first step towards the deployment of our proposal in the University of California, Los Angeles (UCLA) campus network with differentiating services and stringent QoS requirements. We also plan to exploit our solution to manage the handoff between different network technologies, e.g., Wi-Fi and WiMAX. Indeed, the model can be run with different parameters, depending on the communication protocol and can provide optimal results to be implemented on the campus network.

Deep learning for computer vision: a comparison between convolutional neural networks and hierarchical temporal memories on object recognition tasks

In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

Landscape and well-being: a scoping study on the health-promoting impact of outdoor environments

OBJECTIVES: The present literature review conceptualises landscape as a health resource that promotes physical, mental, and social well-being. Different health-promoting landscape characteristics are discussed. METHODS: This article is based on a scoping study which represents a special kind of qualitative literature review. Over 120 studies have been reviewed in a five-step-procedure, resulting in a heuristic device. RESULTS: A set of meaningful pathways that link landscape and health have been identified. Landscapes have the potential to promote mental well-being through attention restoration, stress reduction, and the evocation of positive emotions; physical well-being through the promotion of physical activity in daily life as well as leisure time and through walkable environments; and social well-being through social integration, social engagement and participation, and through social support and security. CONCLUSION: This scoping study allows us to systematically describe the potential of landscape as a resource for physical, mental and social well-being. A heuristic framework is presented that can be applied in future studies, facilitating systematic and focused research approaches and informing practical public health interventions.

Pulsatile shear and Gja5 modulate arterial identity and remodeling events during flow-driven arteriogenesis

In the developing chicken embryo yolk sac vasculature, the expression of arterial identity genes requires arterial hemodynamic conditions. We hypothesize that arterial flow must provide a unique signal that is relevant for supporting arterial identity gene expression and is absent in veins. We analyzed factors related to flow, pressure and oxygenation in the chicken embryo vitelline vasculature in vivo. The best discrimination between arteries and veins was obtained by calculating the maximal pulsatile increase in shear rate relative to the time-averaged shear rate in the same vessel: the relative pulse slope index (RPSI). RPSI was significantly higher in arteries than veins. Arterial endothelial cells exposed to pulsatile shear in vitro augmented arterial marker expression as compared with exposure to constant shear. The expression of Gja5 correlated with arterial flow patterns: the redistribution of arterial flow provoked by vitelline artery ligation resulted in flow-driven collateral arterial network formation and was associated with increased expression of Gja5. In situ hybridization in normal and ligation embryos confirmed that Gja5 expression is confined to arteries and regulated by flow. In mice, Gja5 (connexin 40) was also expressed in arteries. In the adult, increased flow drives arteriogenesis and the formation of collateral arterial networks in peripheral occlusive diseases. Genetic ablation of Gja5 function in mice resulted in reduced arteriogenesis in two occlusion models. We conclude that pulsatile shear patterns may be central for supporting arterial identity, and that arterial Gja5 expression plays a functional role in flow-driven arteriogenesis.