20 resultados para EXPERIMENTAL MODELS OF DISEASE


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Trabecular bone is a porous mineralized tissue playing a major load bearing role in the human body. Prediction of age-related and disease-related fractures and the behavior of bone implant systems needs a thorough understanding of its structure-mechanical property relationships, which can be obtained using microcomputed tomography-based finite element modeling. In this study, a nonlinear model for trabecular bone as a cohesive-frictional material was implemented in a large-scale computational framework and validated by comparison of μFE simulations with experimental tests in uniaxial tension and compression. A good correspondence of stiffness and yield points between simulations and experiments was found for a wide range of bone volume fraction and degree of anisotropy in both tension and compression using a non-calibrated, average set of material parameters. These results demonstrate the ability of the model to capture the effects leading to failure of bone for three anatomical sites and several donors, which may be used to determine the apparent behavior of trabecular bone and its evolution with age, disease, and treatment in the future.

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The prognosis from thyroid cancer subtypes in humans covers a spectrum from "cured at almost 90%" to "100% lethal." Invasive and poorly differentiated forms of thyroid cancer are among the most aggressive human cancers, and there are few effective therapeutic options. Genetically engineered mice, based on mutations observed in patients, can accurately recapitulate the human disease and its progression, providing invaluable tools for the preclinical evaluation of novel therapeutic approaches. This overview details models developed to date as well as their uses for identifying novel anticancer agents. © 2015 by John Wiley & Sons, Inc.

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The goal of the present thesis was to investigate the production of code-switched utterances in bilinguals’ speech production. This study investigates the availability of grammatical-category information during bilingual language processing. The specific aim is to examine the processes involved in the production of Persian-English bilingual compound verbs (BCVs). A bilingual compound verb is formed when the nominal constituent of a compound verb is replaced by an item from the other language. In the present cases of BCVs the nominal constituents are replaced by a verb from the other language. The main question addressed is how a lexical element corresponding to a verb node can be placed in a slot that corresponds to a noun lemma. This study also investigates how the production of BCVs might be captured within a model of BCVs and how such a model may be integrated within incremental network models of speech production. In the present study, both naturalistic and experimental data were used to investigate the processes involved in the production of BCVs. In the first part of the present study, I collected 2298 minutes of a popular Iranian TV program and found 962 code-switched utterances. In 83 (8%) of the switched cases, insertions occurred within the Persian compound verb structure, hence, resulting in BCVs. As to the second part of my work, a picture-word interference experiment was conducted. This study addressed whether in the case of the production of Persian-English BCVs, English verbs compete with the corresponding Persian compound verbs as a whole, or whether English verbs compete with the nominal constituents of Persian compound verbs only. Persian-English bilinguals named pictures depicting actions in 4 conditions in Persian (L1). In condition 1, participants named pictures of action using the whole Persian compound verb in the context of its English equivalent distractor verb. In condition 2, only the nominal constituent was produced in the presence of the light verb of the target Persian compound verb and in the context of a semantically closely related English distractor verb. In condition 3, the whole Persian compound verb was produced in the context of a semantically unrelated English distractor verb. In condition 4, only the nominal constituent was produced in the presence of the light verb of the target Persian compound verb and in the context of a semantically unrelated English distractor verb. The main effect of linguistic unit was significant by participants and items. Naming latencies were longer in the nominal linguistic unit compared to the compound verb (CV) linguistic unit. That is, participants were slower to produce the nominal constituent of compound verbs in the context of a semantically closely related English distractor verb compared to producing the whole compound verbs in the context of a semantically closely related English distractor verb. The three-way interaction between version of the experiment (CV and nominal versions), linguistic unit (nominal and CV linguistic units), and relation (semantically related and unrelated distractor words) was significant by participants. In both versions, naming latencies were longer in the semantically related nominal linguistic unit compared to the response latencies in the semantically related CV linguistic unit. In both versions, naming latencies were longer in the semantically related nominal linguistic unit compared to response latencies in the semantically unrelated nominal linguistic unit. Both the analysis of the naturalistic data and the results of the experiment revealed that in the case of the production of the nominal constituent of BCVs, a verb from the other language may compete with a noun from the base language, suggesting that grammatical category does not necessarily provide a constraint on lexical access during the production of the nominal constituent of BCVs. There was a minimal context in condition 2 (the nominal linguistic unit) in which the nominal constituent was produced in the presence of its corresponding light verb. The results suggest that generating words within a context may not guarantee that the effect of grammatical class becomes available. A model is proposed in order to characterize the processes involved in the production of BCVs. Implications for models of bilingual language production are discussed.

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One to two percent of all children are born with a developmental disorder requiring pediatric hospital admissions. For many such syndromes, the molecular pathogenesis remains poorly characterized. Parallel developmental disorders in other species could provide complementary models for human rare diseases by uncovering new candidate genes, improving the understanding of the molecular mechanisms and opening possibilities for therapeutic trials. We performed various experiments, e.g. combined genome-wide association and next generation sequencing, to investigate the clinico-pathological features and genetic causes of three developmental syndromes in dogs, including craniomandibular osteopathy (CMO), a previously undescribed skeletal syndrome, and dental hypomineralization, for which we identified pathogenic variants in the canine SLC37A2 (truncating splicing enhancer variant), SCARF2 (truncating 2-bp deletion) and FAM20C (missense variant) genes, respectively. CMO is a clinical equivalent to an infantile cortical hyperostosis (Caffey disease), for which SLC37A2 is a new candidate gene. SLC37A2 is a poorly characterized member of a glucose-phosphate transporter family without previous disease associations. It is expressed in many tissues, including cells of the macrophage lineage, e.g. osteoclasts, and suggests a disease mechanism, in which an impaired glucose homeostasis in osteoclasts compromises their function in the developing bone, leading to hyperostosis. Mutations in SCARF2 and FAM20C have been associated with the human van den Ende-Gupta and Raine syndromes that include numerous features similar to the affected dogs. Given the growing interest in the molecular characterization and treatment of human rare diseases, our study presents three novel physiologically relevant models for further research and therapy approaches, while providing the molecular identity for the canine conditions.

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We performed a quantitative comparison of brittle thrust wedge experiments to evaluate the variability among analogue models and to appraise the reproducibility and limits of model interpretation. Fifteen analogue modeling laboratories participated in this benchmark initiative. Each laboratory received a shipment of the same type of quartz and corundum sand and all laboratories adhered to a stringent model building protocol and used the same type of foil to cover base and sidewalls of the sandbox. Sieve structure, sifting height, filling rate, and details on off-scraping of excess sand followed prescribed procedures. Our analogue benchmark shows that even for simple plane-strain experiments with prescribed stringent model construction techniques, quantitative model results show variability, most notably for surface slope, thrust spacing and number of forward and backthrusts. One of the sources of the variability in model results is related to slight variations in how sand is deposited in the sandbox. Small changes in sifting height, sifting rate, and scraping will result in slightly heterogeneous material bulk densities, which will affect the mechanical properties of the sand, and will result in lateral and vertical differences in peak and boundary friction angles, as well as cohesion values once the model is constructed. Initial variations in basal friction are inferred to play the most important role in causing model variability. Our comparison shows that the human factor plays a decisive role, and even when one modeler repeats the same experiment, quantitative model results still show variability. Our observations highlight the limits of up-scaling quantitative analogue model results to nature or for making comparisons with numerical models. The frictional behavior of sand is highly sensitive to small variations in material state or experimental set-up, and hence, it will remain difficult to scale quantitative results such as number of thrusts, thrust spacing, and pop-up width from model to nature.