Input diffusion and the evolution of production networks

What determines which inputs are initially considered and eventually adopted in the productionof new or improved goods? Why are some inputs much more prominent than others? We modelthe evolution of input linkages as a process where new producers first search for potentially usefulinputs and then decide which ones to adopt. A new product initially draws a set of 'essentialsuppliers'. The search stage is then confined to the network neighborhood of the latter, i.e., to theinputs used by the essential suppliers. The adoption decision is driven by a tradeoff between thebenefits accruing from input variety and the costs of input adoption. This has important implicationsfor the number of forward linkages that a product (input variety) develops over time. Inputdiffusion is fostered by network centrality ? an input that is initially represented in many networkneighborhoods is subsequently more likely to be adopted. This mechanism also delivers a powerlaw distribution of forward linkages. Our predictions continue to hold when varieties are aggregatedinto sectors. We can thus test them, using detailed sectoral US input-output tables. We showthat initial network proximity of a sector in 1967 significantly increases the likelihood of adoptionthroughout the subsequent four decades. The same is true for rapid productivity growth in aninput-producing sector. Our empirical results highlight two conditions for new products to becomecentral nodes: initial network proximity to prospective adopters, and technological progress thatreduces their relative price. Semiconductors met both conditions.

Premenopausal serum androgens and breast cancer risk: a nested case-control study.

ABSTRACT: INTRODUCTION: Prospective epidemiologic studies have consistently shown that levels of circulating androgens in postmenopausal women are positively associated with breast cancer risk. However, data in premenopausal women are limited. METHODS: A case-control study nested within the New York University Women's Health Study was conducted. A total of 356 cases (276 invasive and 80 in situ) and 683 individually-matched controls were included. Matching variables included age and date, phase, and day of menstrual cycle at blood donation. Testosterone, androstenedione, dehydroandrosterone sulfate (DHEAS) and sex hormone-binding globulin (SHBG) were measured using direct immunoassays. Free testosterone was calculated. RESULTS: Premenopausal serum testosterone and free testosterone concentrations were positively associated with breast cancer risk. In models adjusted for known risk factors of breast cancer, the odds ratios for increasing quintiles of testosterone were 1.0 (reference), 1.5 (95% confidence interval (CI), 0.9 to 2.3), 1.2 (95% CI, 0.7 to 1.9), 1.4 (95% CI, 0.9 to 2.3) and 1.8 (95% CI, 1.1 to 2.9; Ptrend = 0.04), and for free testosterone were 1.0 (reference), 1.2 (95% CI, 0.7 to 1.8), 1.5 (95% CI, 0.9 to 2.3), 1.5 (95% CI, 0.9 to 2.3), and 1.8 (95% CI, 1.1 to 2.8, Ptrend = 0.01). A marginally significant positive association was observed with androstenedione (P = 0.07), but no association with DHEAS or SHBG. Results were consistent in analyses stratified by tumor type (invasive, in situ), estrogen receptor status, age at blood donation, and menopausal status at diagnosis. Intra-class correlation coefficients for samples collected from 0.8 to 5.3 years apart (median 2 years) in 138 cases and 268 controls were greater than 0.7 for all biomarkers except for androstenedione (0.57 in controls). CONCLUSIONS: Premenopausal concentrations of testosterone and free testosterone are associated with breast cancer risk. Testosterone and free testosterone measurements are also highly reliable (that is, a single measurement is reflective of a woman's average level over time). Results from other prospective studies are consistent with our results. The impact of including testosterone or free testosterone in breast cancer risk prediction models for women between the ages of 40 and 50 years should be assessed. Improving risk prediction models for this age group could help decision making regarding both screening and chemoprevention of breast cancer.

The Ret receptor tyrosine kinase pathway functionally interacts with the ERalpha pathway in breast cancer.

A limited number of receptor tyrosine kinases (e.g., ErbB and fibroblast growth factor receptor families) have been genetically linked to breast cancer development. Here, we investigated the contribution of the Ret receptor tyrosine kinase to breast tumor biology. Ret was expressed in primary breast tumors and cell lines. In estrogen receptor (ER)alpha-positive MCF7 and T47D lines, the ligand (glial-derived neurotrophic factor) activated signaling pathways and increased anchorage-independent proliferation in a Ret-dependent manner, showing that Ret signaling is functional in breast tumor cells. Ret expression was induced by estrogens and Ret signaling enhanced estrogen-driven proliferation, highlighting the functional interaction of Ret and ER pathways. Furthermore, Ret was detected in primary cancers, and there were higher Ret levels in ERalpha-positive tumors. In summary, we showed that Ret is a novel proliferative pathway interacting with ER signaling in vitro. Expression of Ret in primary breast tumors suggests that Ret might be a novel therapeutic target in breast cancer.

Can resistance to trastuzumab be reversed by endocrine therapy? Combination of trastuzumab and letrozole after resistance to sequential trastuzumab and aromatase inhibitor monotherapies in patients with ER-positive, HER-2 positive, advanced breast cancer: a proof-of-concept trial (SAKK 23/03)

Introduction: Trastuzumab (T) is a cornerstone in the treatment of patients with HER2-overexpressing advanced breast cancer and development of resistance to T is a major therapeutic problem. HER-2 is part of a highly interactive signaling network that may impair efficacy of endocrine therapy. A sequential treatment design was chosen in this trial to ensure complete resistance to single agent therapy before receiving both a non-steroidal aromatase inhibitor (AI) and T. Any kind of clinical activity with combined treatment of AI and T after progression of single agent treatments could indicate restoration of sensitivity as a consequence of cross-talking and networking between both pathways. Methods: Key eligibility criteria included postmenopausal patients (pts.) with advanced, measurable, HER-2 positive (assessed by FISH, ratio (≥2)), HR positive disease and progression on prior treatment with a non-steroidal AI, e.g. letrozole or anastrozole, either in an adjuvant or advanced setting. Pts. received standard dose T monotherapy either weekly or three-weekly in step 1 and upon disease progression, continued T in combination with letrozole in step 2. The primary endpoint was clinical benefit response (CBR: CR, PR or SD for at least 24 weeks (+/- 1 week) according to RECIST) in step 2. Results: Thirteen pts. were enrolled in five centers in Switzerland. In step 1, six pts. (46%) achieved CBR. Median time to progression (TTP) was 161 days (Range: 50 - 627). Based on data collected until the end of May 2010, CBR was observed in seven out of the eleven evaluable pts. (64%) in step 2, including one pt. with partial response. Four of the seven pts. within step 2 that achieved CBR also had CBR in step 1. Seven out of eleven pts. have documented tumor progression during step 2 treatment. Median TTP for all eleven pts. was 184 days (range 61 - 471). Mean time on study treatment (TTP in step 1 plus TTP in step 2) for pts. reaching step 2 was 380 days (range 174 - 864). Adverse events were generally mild. Conclusion: Results of this proof-of-principle trial suggest that complete resistance to both AI and T can be overcome in a proportion of pts. by combined treatment of AI and T, as all pts. served as their own control. Our results appear promising for a new treatment strategy which offers a chemotherapy-free and well-tolerated option for at least a subset of the pts. with HR positive, HER-2 positive breast cancer. Further trials will need to corroborate this finding.

Cooperation of breast cancer proteins PALB2 and piccolo BRCA2 in stimulating homologous recombination.

Inherited mutations in human PALB2 are associated with a predisposition to breast and pancreatic cancers. PALB2's tumor-suppressing effect is thought to be based on its ability to facilitate BRCA2's function in homologous recombination. However, the biochemical properties of PALB2 are unknown. Here we show that human PALB2 binds DNA, preferentially D-loop structures, and directly interacts with the RAD51 recombinase to stimulate strand invasion, a vital step of homologous recombination. This stimulation occurs through reinforcing biochemical mechanisms, as PALB2 alleviates inhibition by RPA and stabilizes the RAD51 filament. Moreover, PALB2 can function synergistically with a BRCA2 chimera (termed piccolo, or piBRCA2) to further promote strand invasion. Finally, we show that PALB2-deficient cells are sensitive to PARP inhibitors. Our studies provide the first biochemical insights into PALB2's function with piBRCA2 as a mediator of homologous recombination in DNA double-strand break repair.

Simulation of stromatolite growth using diffusion-limited aggregation and a discrete model of biogeochemical exchanges in microbial mat

Resume : Mieux comprendre les stromatolithes et les tapis microbiens est un sujet important en biogéosciences puisque cela aide à l'étude des premières formes de vie sur Terre, a mieux cerner l'écologie des communautés microbiennes et la contribution des microorganismes a la biominéralisation, et même à poser certains fondements dans les recherches en exobiologie. D'autre part, la modélisation est un outil puissant utilisé dans les sciences naturelles pour appréhender différents phénomènes de façon théorique. Les modèles sont généralement construits sur un système d'équations différentielles et les résultats sont obtenus en résolvant ce système. Les logiciels disponibles pour implémenter les modèles incluent les logiciels mathématiques et les logiciels généraux de simulation. L'objectif principal de cette thèse est de développer des modèles et des logiciels pour aider a comprendre, via la simulation, le fonctionnement des stromatolithes et des tapis microbiens. Ces logiciels ont été développés en C++ en ne partant d'aucun pré-requis de façon a privilégier performance et flexibilité maximales. Cette démarche permet de construire des modèles bien plus spécifiques et plus appropriés aux phénomènes a modéliser. Premièrement, nous avons étudié la croissance et la morphologie des stromatolithes. Nous avons construit un modèle tridimensionnel fondé sur l'agrégation par diffusion limitée. Le modèle a été implémenté en deux applications C++: un moteur de simulation capable d'exécuter un batch de simulations et de produire des fichiers de résultats, et un outil de visualisation qui permet d'analyser les résultats en trois dimensions. Après avoir vérifié que ce modèle peut en effet reproduire la croissance et la morphologie de plusieurs types de stromatolithes, nous avons introduit un processus de sédimentation comme facteur externe. Ceci nous a mené a des résultats intéressants, et permis de soutenir l'hypothèse que la morphologie des stromatolithes pourrait être le résultat de facteurs externes autant que de facteurs internes. Ceci est important car la classification des stromatolithes est généralement fondée sur leur morphologie, imposant que la forme d'un stromatolithe est dépendante de facteurs internes uniquement (c'est-à-dire les tapis microbiens). Les résultats avancés dans ce mémoire contredisent donc ces assertions communément admises. Ensuite, nous avons décidé de mener des recherches plus en profondeur sur les aspects fonctionnels des tapis microbiens. Nous avons construit un modèle bidimensionnel de réaction-diffusion fondé sur la simulation discrète. Ce modèle a été implémenté dans une application C++ qui permet de paramétrer et exécuter des simulations. Nous avons ensuite pu comparer les résultats de simulation avec des données du monde réel et vérifier que le modèle peut en effet imiter le comportement de certains tapis microbiens. Ainsi, nous avons pu émettre et vérifier des hypothèses sur le fonctionnement de certains tapis microbiens pour nous aider à mieux en comprendre certains aspects, comme la dynamique des éléments, en particulier le soufre et l'oxygène. En conclusion, ce travail a abouti à l'écriture de logiciels dédiés à la simulation de tapis microbiens d'un point de vue tant morphologique que fonctionnel, suivant deux approches différentes, l'une holistique, l'autre plus analytique. Ces logiciels sont gratuits et diffusés sous licence GPL (General Public License). Abstract : Better understanding of stromatolites and microbial mats is an important topic in biogeosciences as it helps studying the early forms of life on Earth, provides clues re- garding the ecology of microbial ecosystems and their contribution to biomineralization, and gives basis to a new science, exobiology. On the other hand, modelling is a powerful tool used in natural sciences for the theoretical approach of various phenomena. Models are usually built on a system of differential equations and results are obtained by solving that system. Available software to implement models includes mathematical solvers and general simulation software. The main objective of this thesis is to develop models and software able to help to understand the functioning of stromatolites and microbial mats. Software was developed in C++ from scratch for maximum performance and flexibility. This allows to build models much more specific to a phenomenon rather than general software. First, we studied stromatolite growth and morphology. We built a three-dimensional model based on diffusion-limited aggregation. The model was implemented in two C++ applications: a simulator engine, which can run a batch of simulations and produce result files, and a Visualization tool, which allows results to be analysed in three dimensions. After verifying that our model can indeed reproduce the growth and morphology of several types of stromatolites, we introduced a sedimentation process as an external factor. This lead to interesting results, and allowed to emit the hypothesis that stromatolite morphology may be the result of external factors as much as internal factors. This is important as stromatolite classification is usually based on their morphology, imposing that a stromatolite shape is dependant on internal factors only (i.e. the microbial mat). This statement is contradicted by our findings, Second, we decided to investigate deeper the functioning of microbial mats, We built a two-dimensional reaction-diffusion model based on discrete simulation, The model was implemented in a C++ application that allows setting and running simulations. We could then compare simulation results with real world data and verify that our model can indeed mimic the behaviour of some microbial mats. Thus, we have proposed and verified hypotheses regarding microbial mats functioning in order to help to better understand them, e.g. the cycle of some elements such as oxygen or sulfur. ln conclusion, this PhD provides a simulation software, dealing with two different approaches. This software is free and available under a GPL licence.

Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen.

Background: Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30-40% of ER+ BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings.Results: We developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95% CI: 1.29-3.13; p = 0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response.Conclusion: We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen.

Analysis of a finite volume method for a cross-diffusion model in population dynamics

The main goal of this paper is to propose a convergent finite volume method for a reactionâeuro"diffusion system with cross-diffusion. First, we sketch an existence proof for a class of cross-diffusion systems. Then the standard two-point finite volume fluxes are used in combination with a nonlinear positivity-preserving approximation of the cross-diffusion coefficients. Existence and uniqueness of the approximate solution are addressed, and it is also shown that the scheme converges to the corresponding weak solution for the studied model. Furthermore, we provide a stability analysis to study pattern-formation phenomena, and we perform two-dimensional numerical examples which exhibit formation of nonuniform spatial patterns. From the simulations it is also found that experimental rates of convergence are slightly below second order. The convergence proof uses two ingredients of interest for various applications, namely the discrete Sobolev embedding inequalities with general boundary conditions and a space-time $L^1$ compactness argument that mimics the compactness lemma due to Kruzhkov. The proofs of these results are given in the Appendix.

Usability of Virtual Museums and the Diffusion of Cultural Heritage

Les prioritats per als museus canvien. La missió de la nova museologia és convertir els museus en llocs per a gaudir i aprendre, cosa que fa que hagin de dur a terme una gestió financera molt semblant a la d'una empresa social que competeixi en el sector del lleure. Amb el pas del temps, els museus han d'establir i aplicar els criteris necessaris per a la supervivència, aplanant el terreny perquè altres institucions públiques siguin més obertes en els seus esforços per comunicar i difondre el seu patrimoni. Ja podem començar a parlar d'algunes conclusions comunament acceptades sobre el comportament dels visitants, que són necessàries per a planificar exposicions futures que vegin l'aprenentatge com un procés constructiu, les col·leccions com a objectes amb significat i les mateixes exposicions com a mitjans de comunicació que haurien de transformar la manera de pensar de l'espectador i que estan al servei del mateix missatge. Sembla que internet representa un mitjà efectiu per a assolir aquests objectius, ja que és capaç (a) d'adaptar-se als interessos i les característiques intel·lectuals d'un públic divers; (b) de redescobrir els significats dels objectes i adquirir un reconeixement sociocultural del seu valor per mitjà del seu potencial interactiu, i (c) de fer ús d'elements atractius i estimulants perquè tothom en gaudeixi. Per a aquest propòsit, és bàsic fer-nos les preguntes següents: quins criteris ha de seguir un museu virtual per a optimar la difusió del seu patrimoni?; quins elements estimulen els usuaris a quedar-se en una pàgina web i fer visites virtuals que els siguin satisfactòries?; quin paper té la usabilitat de l'aplicació en tot això?

How Reliable Is Ki-67 Immunohistochemistry in Grade 2 Breast Carcinomas? A QA Study of the Swiss Working Group of Breast- and Gynecopathologists.

Adjuvant chemotherapy decisions in breast cancer are increasingly based on the pathologist's assessment of tumor proliferation. The Swiss Working Group of Gyneco- and Breast Pathologists has surveyed inter- and intraobserver consistency of Ki-67-based proliferative fraction in breast carcinomas. METHODS: Five pathologists evaluated MIB-1-labeling index (LI) in ten breast carcinomas (G1, G2, G3) by counting and eyeballing. In the same way, 15 pathologists all over Switzerland then assessed MIB-1-LI on three G2 carcinomas, in self-selected or pre-defined areas of the tumors, comparing centrally immunostained slides with slides immunostained in the different laboratoires. To study intra-observer variability, the same tumors were re-examined 4 months later. RESULTS: The Kappa values for the first series of ten carcinomas of various degrees of differentiation showed good to very good agreement for MIB-1-LI (Kappa 0.56-0.72). However, we found very high inter-observer variabilities (Kappa 0.04-0.14) in the read-outs of the G2 carcinomas. It was not possible to explain the inconsistencies exclusively by any of the following factors: (i) pathologists' divergent definitions of what counts as a positive nucleus (ii) the mode of assessment (counting vs. eyeballing), (iii) immunostaining technique, and (iv) the selection of the tumor area in which to count. Despite intensive confrontation of all participating pathologists with the problem, inter-observer agreement did not improve when the same slides were re-examined 4 months later (Kappa 0.01-0.04) and intra-observer agreement was likewise poor (Kappa 0.00-0.35). CONCLUSION: Assessment of mid-range Ki-67-LI suffers from high inter- and intra-observer variability. Oncologists should be aware of this caveat when using Ki-67-LI as a basis for treatment decisions in moderately differentiated breast carcinomas.