The role of MMP-9 and its fibronectin-like domain in tumor growth & invasion : certainties, controversies & discrepancies

Tumors are often compared to wounds that do not heal, where the crosstalk between tumor cells and their surrounding stroma is crucial at all stages of development, from the initial primary growth to metastasis. Similar to wound healing, fibroblasts in the tumor stroma differentiate into myofibroblasts, also referred to as "cancer-associated fibroblasts" (CAFs), primarily, but not exclusively, in response to transforming growth factor-ß (TGF-ß). Myofibroblasts in turn enhance tumor progression by remodeling the stroma. Among molecules implicated in stroma remodeling, matrix metalloproteinases (MMPs), and MMP-g in particular, play a prominent role. However, the mechanisms that regulate MMP-g activation and function remain poorly understood. Recent evidence indicates that tumor cell surface association of MMP-g is an important event in its activation, and more generally in tumor growth and invasion. In the present work we address the potential association of MMP-g activity with cell-surface recruitment to human fibroblasts. We show for the first time that recruitment of MMP-g to the MRC-5 fibroblast cell surface occurs through the fibronectin-like (FN) domain, shared only by MMP-g and MMP-2 among all the MMPs. Functional assays suggest that both the pro- and active form of MMP-g trigger a-smooth muscle actin (aSMA) expression in resting fibroblasts that reflects myofibroblast differentiation, possibly through TGF-ß activation. Moreover, the FN domain of MMP-g inhibits both MMP-g-induced TGF-ß activation and aSMA expression by sequestering MMP-g. Xenograft experiments in NOD/SCID mice using HT1080 fibrosarcoma or MDA-MD231 breast adenocarcinoma cells stably expressing the FN domain of MMP-g revealed no changes in primary tumor growth. However, in the context of metastasis, expression of the FN domain by these same tumor cells dramatically increased their metastatic proclivity whereas expression of wt MMP-g either promoted no change or actually reduced the number of metastases. We observed a decrease of an active form of MMP-g in MDA-MB231 cells overexpressing the FN domain suggesting that the FN domain may inhibit MMP-g activity in Tumors are often compared to wounds that do not heal, where the crosstalk between tumor cells and their surrounding stroma is crucial at all stages of development, from the initial primary growth to metastasis. Similar to wound healing, fibroblasts in the tumor stroma differentiate into myofibroblasts, also referred to as "cancer-associated fibroblasts" (CAFs), primarily, but not exclusively, in response to transforming growth factor-ß (TGF-ß). Myofibroblasts in turn enhance tumor progression by remodeling the stroma. Among molecules implicated in stroma remodeling, matrix metalloproteinases (MMPs), and MMP-g in particular, play a prominent role. However, the mechanisms that regulate MMP-g activation and function remain poorly understood. Recent evidence indicates that tumor cell surface association of MMP-g is an important event in its activation, and more generally in tumor growth and invasion. In the present work we address the potential association of MMP-g activity with cell-surface recruitment to human fibroblasts. We show for the first time that recruitment of MMP-g to the MRC-5 fibroblast cell surface occurs through the fibronectin-like (FN) domain, shared only by MMP-g and MMP-2 among all the MMPs. Functional assays suggest that both the pro- and active form of MMP-g trigger a-smooth muscle actin (aSMA) expression in resting fibroblasts that reflects myofibroblast differentiation, possibly through TGF-ß activation. Moreover, the FN domain of MMP-g inhibits both MMP-g-induced TGF-ß activation and aSMA expression by sequestering MMP-g. Xenograft experiments in NOD/SCID mice using HT1080 fibrosarcoma or MDA-MD231 breast adenocarcinoma cells stably expressing the FN domain of MMP-9 revealed no changes in primary tumor growth. However, in the context of metastasis, expression of the FN domain by these same tumor cells dramatically increased their metastatic proclivity whereas expression of wt MMP-g either promoted no change or actually reduced the number of metastases. We observed a decrease of an active form of MMP-9 in MDA-MB231 cells overexpressing the FN domain suggesting that the FN domain may inhibit MMP-9 activity in those cells and therefore prevent MMP-9-induced activation of TGF-b, which results in increased invasion. Curiously, xenografts of SW480 colorectal adenocarcinoma cells stably expressing the FN domain of MMP-9 displayed reduced growth at both the primary (subcutaneous) injection site and the lungs of NOD/SCID mice, in experimental metastasis assays, whilst the same cells overexpressing wt MMP-9 showed enhanced growth and dissemination. Gelatin zymography of conditioned medium revealed that these effects may be due to the FN domain, which displaces MMP-9 from SW480 cell surface. These observations suggest a dual role of MMP-9 and its FN domain in primary tumor growth and metastasis, underscoring the notion that the effect of MMP-9 on tumor cells may depend on the cell type and highlighting possible protective effects of MMPs in tumor progression.

Effects of variety, soil type and nitrogen fertilizer supply on the nutritive value of barley for growing pigs

Selostus: Lajikkeen, typpilannoitustason ja maalajin vaikutus ohran ruokinnalliseen arvoon lihasioilla

A dynamic model for stem cell homeostasis and patterning in Arabidopsis meristems.

Plants maintain stem cells in their meristems as a source for new undifferentiated cells throughout their life. Meristems are small groups of cells that provide the microenvironment that allows stem cells to prosper. Homeostasis of a stem cell domain within a growing meristem is achieved by signalling between stem cells and surrounding cells. We have here simulated the origin and maintenance of a defined stem cell domain at the tip of Arabidopsis shoot meristems, based on the assumption that meristems are self-organizing systems. The model comprises two coupled feedback regulated genetic systems that control stem cell behaviour. Using a minimal set of spatial parameters, the mathematical model allows to predict the generation, shape and size of the stem cell domain, and the underlying organizing centre. We use the model to explore the parameter space that allows stem cell maintenance, and to simulate the consequences of mutations, gene misexpression and cell ablations.

Semantic domains and supersens tagging for domain-specific ontology learning

In this paper we propose a novel unsupervised approach to learning domain-specific ontologies from large open-domain text collections. The method is based on the joint exploitation of Semantic Domains and Super Sense Tagging for Information Retrieval tasks. Our approach is able to retrieve domain specific terms and concepts while associating them with a set of high level ontological types, named supersenses, providing flat ontologies characterized by very high accuracy and pertinence to the domain.

Fine speckle contrast in InGaAs/InP systems: Influence of layer thickness, missmatch, and growing temperature

This work is focused on the study of the fine speckle contrast present in planar view observations of matched and mismatched InGaAs layers grown by molecular beam epitaxy on InP substrates. Our results provide experimental evidence of the evolution of this fine structure with the mismatch, layer thickness, and growth temperature. The correlation of the influence of all these parameters on the appearance of the contrast modulation points to the development of the fine structure during the growth. Moreover, as growth proceeds, this structure shows a dynamic behavior which depends on the intrinsic layer substrate stress.

Feeding value of grass ensiled with absorbents assessed in growing lambs

Selostus: Eri absorbenteilla valmistettu säilörehu karitsoiden ruokinnassa

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

A time-domain method for the analysis of thermal impedance response preserving the convolution form

The study of the thermal behavior of complex packages as multichip modules (MCM¿s) is usually carried out by measuring the so-called thermal impedance response, that is: the transient temperature after a power step. From the analysis of this signal, the thermal frequency response can be estimated, and consequently, compact thermal models may be extracted. We present a method to obtain an estimate of the time constant distribution underlying the observed transient. The method is based on an iterative deconvolution that produces an approximation to the time constant spectrum while preserving a convenient convolution form. This method is applied to the obtained thermal response of a microstructure as analyzed by finite element method as well as to the measured thermal response of a transistor array integrated circuit (IC) in a SMD package.

Effect of dietary crude protein and energy content on nitrogen utilisation, water intake and urinary output in growing pigs

Selostus: Rehun valkuais- ja energiapitoisuuden vaikutus sikojen typen hyväksikäyttöön, veden kulutukseen ja virtsan eritykseen

An agency-oriented model to explain vine-growing specialization in the province of Barcelona (Catalonia, Spain) in the mid-nineteenth century

[cat] En aquest treball presentem un model per explicar el procés d’especialització vitícola assolit als municipis de la província de Barcelona, a mitjans del s. XIX,que cerca entendre com va sorgir històricament un avantatge comparatiu fruit d’un procés que esdevindria un dels punts de partida del procés d’industrialització a Catalunya. Els resultats confirmen els papers jugats pel impuls “Boserupià” de la població en un context d’intensificació de l’ús de la terra, i d’un impuls del mercat “Smithià” en un context d’expansió de la demanda per part de les economies atlàntiques. També es posa de manifest la importància de les dotacions agro-ecològiques i les condicions socioinstitucionals relacionades amb la desigualtat d’ingrés. La difusió de la vinya donà com a resultat unes comunitats rurals menys desiguals fins al 1820, tot i que aquesta desigualtat augmentà de nou a partir d'aleshores.

Utilisation of reactive lysine from meat and bone meals of different ash content by growing-finishing pigs

Selostus: Tuhkapitoisuuden vaikutus lihaluujauhon reaktiivisen lysiinin hyväksikäyttöön lihasioilla

c-Jun N-terminal kinase binding domain-dependent phosphorylation of mitogen-activated protein kinase kinase 4 and mitogen-activated protein kinase kinase 7 and balancing cross-talk between c-Jun N-terminal kinase and extracellular signal-regulated kinase pathways in cortical neurons

The c-Jun N-terminal kinase (JNK) is a mitogen-activated protein kinase (MAPK) activated by stress-signals and involved in many different diseases. Previous results proved the powerful effect of the cell permeable peptide inhibitor d-JNKI1 (d-retro-inverso form of c-Jun N-terminal kinase-inhibitor) against neuronal death in CNS diseases, but the precise features of this neuroprotection remain unclear. We here performed cell-free and in vitro experiments for a deeper characterization of d-JNKI1 features in physiological conditions. This peptide works by preventing JNK interaction with its c-Jun N-terminal kinase-binding domain (JBD) dependent targets. We here focused on the two JNK upstream MAPKKs, mitogen-activated protein kinase kinase 4 (MKK4) and mitogen-activated protein kinase kinase 7 (MKK7), because they contain a JBD homology domain. We proved that d-JNKI1 prevents MKK4 and MKK7 activity in cell-free and in vitro experiments: these MAPKK could be considered not only activators but also substrates of JNK. This means that d-JNKI1 can interrupt downstream but also upstream events along the JNK cascade, highlighting a new remarkable feature of this peptide. We also showed the lack of any direct effect of the peptide on p38, MEK1, and extracellular signal-regulated kinase (ERK) in cell free, while in rat primary cortical neurons JNK inhibition activates the MEK1-ERK-Ets1/c-Fos cascade. JNK inhibition induces a compensatory effect and leads to ERK activation via MEK1, resulting in an activation of the survival pathway-(MEK1/ERK) as a consequence of the death pathway-(JNK) inhibition. This study should hold as an important step to clarify the strong neuroprotective effect of d-JNKI1.

Option valuation as an expectation in the complex domain: The Black-Scholes case

It is very well known that the first succesful valuation of a stock option was done by solving a deterministic partial differential equation (PDE) of the parabolic type with some complementary conditions specific for the option. In this approach, the randomness in the option value process is eliminated through a no-arbitrage argument. An alternative approach is to construct a replicating portfolio for the option. From this viewpoint the payoff function for the option is a random process which, under a new probabilistic measure, turns out to be of a special type, a martingale. Accordingly, the value of the replicating portfolio (equivalently, of the option) is calculated as an expectation, with respect to this new measure, of the discounted value of the payoff function. Since the expectation is, by definition, an integral, its calculation can be made simpler by resorting to powerful methods already available in the theory of analytic functions. In this paper we use precisely two of those techniques to find the well-known value of a European call