Image-based vs. mesh-based statistical appearance models of the human femur: Implications for finite element simulations.

Statistical appearance models have recently been introduced in bone mechanics to investigate bone geometry and mechanical properties in population studies. The establishment of accurate anatomical correspondences is a critical aspect for the construction of reliable models. Depending on the representation of a bone as an image or a mesh, correspondences are detected using image registration or mesh morphing. The objective of this study was to compare image-based and mesh-based statistical appearance models of the femur for finite element (FE) simulations. To this aim, (i) we compared correspondence detection methods on bone surface and in bone volume; (ii) we created an image-based and a mesh-based statistical appearance models from 130 images, which we validated using compactness, representation and generalization, and we analyzed the FE results on 50 recreated bones vs. original bones; (iii) we created 1000 new instances, and we compared the quality of the FE meshes. Results showed that the image-based approach was more accurate in volume correspondence detection and quality of FE meshes, whereas the mesh-based approach was more accurate for surface correspondence detection and model compactness. Based on our results, we recommend the use of image-based statistical appearance models for FE simulations of the femur.

Functional correction in mouse models of muscular dystrophy using exon-skipping tricyclo-DNA oligomers

Antisense oligonucleotides (AONs) hold promise for therapeutic correction of many genetic diseases via exon skipping, and the first AON-based drugs have entered clinical trials for neuromuscular disorders1, 2. However, despite advances in AON chemistry and design, systemic use of AONs is limited because of poor tissue uptake, and recent clinical reports confirm that sufficient therapeutic efficacy has not yet been achieved. Here we present a new class of AONs made of tricyclo-DNA (tcDNA), which displays unique pharmacological properties and unprecedented uptake by many tissues after systemic administration. We demonstrate these properties in two mouse models of Duchenne muscular dystrophy (DMD), a neurogenetic disease typically caused by frame-shifting deletions or nonsense mutations in the gene encoding dystrophin3, 4 and characterized by progressive muscle weakness, cardiomyopathy, respiratory failure5 and neurocognitive impairment6. Although current naked AONs do not enter the heart or cross the blood-brain barrier to any substantial extent, we show that systemic delivery of tcDNA-AONs promotes a high degree of rescue of dystrophin expression in skeletal muscles, the heart and, to a lesser extent, the brain. Our results demonstrate for the first time a physiological improvement of cardio-respiratory functions and a correction of behavioral features in DMD model mice. This makes tcDNA-AON chemistry particularly attractive as a potential future therapy for patients with DMD and other neuromuscular disorders or with other diseases that are eligible for exon-skipping approaches requiring whole-body treatment.

Standardised animal models of host microbial mutualism.

An appreciation of the importance of interactions between microbes and multicellular organisms is currently driving research in biology and biomedicine. Many human diseases involve interactions between the host and the microbiota, so investigating the mechanisms involved is important for human health. Although microbial ecology measurements capture considerable diversity of the communities between individuals, this diversity is highly problematic for reproducible experimental animal models that seek to establish the mechanistic basis for interactions within the overall host-microbial superorganism. Conflicting experimental results may be explained away through unknown differences in the microbiota composition between vivaria or between the microenvironment of different isolated cages. In this position paper, we propose standardised criteria for stabilised and defined experimental animal microbiotas to generate reproducible models of human disease that are suitable for systematic experimentation and are reproducible across different institutions.

Protective effect of a germline, IL-17-neutralizing antibody in murine models of autoimmune inflammatory disease.

Monoclonal antibodies (mAbs) inhibiting cytokines have recently emerged as new drug modalities for the treatment of chronic inflammatory diseases. Interleukin-17 (IL-17) is a T-cell-derived central mediator of autoimmunity. Immunization with Qβ-IL-17, a virus-like particle based vaccine, has been shown to produce autoantibodies in mice and was effective in ameliorating disease symptoms in animal models of autoimmunity. To characterize autoantibodies induced by vaccination at the molecular level, we generated mouse mAbs specific for IL-17 and compared them to germline Ig sequences. The variable regions of a selected hypermutated high-affinity anti-IL-17 antibody differed in only three amino acid residues compared to the likely germline progenitor. An antibody, which was backmutated to germline, maintained a surprisingly high affinity (0.5 nM). The ability of the parental hypermutated antibody and the derived germline antibody to block inflammation was subsequently tested in murine models of multiple sclerosis (experimental autoimmune encephalomyelitis), arthritis (collagen-induced arthritis), and psoriasis (imiquimod-induced skin inflammation). Both antibodies were able to delay disease onset and significantly reduced disease severity. Thus, the mouse genome unexpectedly encodes for antibodies with the ability to functionally neutralize IL-17 in vivo.

Theoretical models of planetary system formation II. Post-formation evolution

Aims. We extend the results of planetary formation synthesis by computing the long-term evolution of synthetic systems from the clearing of the gas disk into the dynamical evolution phase. Methods. We use the symplectic integrator SyMBA to numerically integrate the orbits of planets for 100 Myr, using populations from previous studies as initial conditions. Results. We show that within the populations studied, mass and semimajor axis distributions experience only minor changes from post-formation evolution. We also show that, depending upon their initial distribution, planetary eccentricities can statistically increase or decrease as a result of gravitational interactions. We find that planetary masses and orbital spacings provided by planet formation models do not result in eccentricity distributions comparable to observed exoplanet eccentricities, requiring other phenomena, such as stellar fly-bys, to account for observed eccentricities.

Code-switching: a touchstone of models of bilingual language production

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.

Calibrating a CGE model with NTBs that Incorporates Standard Models of Modern Trade Theory

We propose a way to incorporate NTBs for the four workhorse models of the modern trade literature in computable general equilibrium models (CGEs). CGE models feature intermediate linkages and thus allow us to study global value chains (GVCs). We show that the Ethier-Krugman monopolistic competition model, the Melitz firm heterogeneity model and the Eaton and Kortum model can be defined as an Armington model with generalized marginal costs, generalized trade costs and a demand externality. As already known in the literature in both the Ethier-Krugman model and the Melitz model generalized marginal costs are a function of the amount of factor input bundles. In the Melitz model generalized marginal costs are also a function of the price of the factor input bundles. Lower factor prices raise the number of firms that can enter the market profitably (extensive margin), reducing generalized marginal costs of a representative firm. For the same reason the Melitz model features a demand externality: in a larger market more firms can enter. We implement the different models in a CGE setting with multiple sectors, intermediate linkages, non-homothetic preferences and detailed data on trade costs. We find the largest welfare effects from trade cost reductions in the Melitz model. We also employ the Melitz model to mimic changes in Non tariff Barriers (NTBs) with a fixed cost-character by analysing the effect of changes in fixed trade costs. While we work here with a model calibrated to the GTAP database, the methods developed can also be applied to CGE models based on the WIOD database.

Input Aggregation in Models of Data Envelopment Analysis: A Statistical Test with an Application to Indian Manufacturing

A problem frequently encountered in Data Envelopment Analysis (DEA) is that the total number of inputs and outputs included tend to be too many relative to the sample size. One way to counter this problem is to combine several inputs (or outputs) into (meaningful) aggregate variables reducing thereby the dimension of the input (or output) vector. A direct effect of input aggregation is to reduce the number of constraints. This, in its turn, alters the optimal value of the objective function. In this paper, we show how a statistical test proposed by Banker (1993) may be applied to test the validity of a specific way of aggregating several inputs. An empirical application using data from Indian manufacturing for the year 2002-03 is included as an example of the proposed test.

The Devil’s Calculus: Mathematical Models of Civil War

In spite of the movement to turn political science into a real science, various mathematical methods that are now the staples of physics, biology, and even economics are thoroughly uncommon in political science, especially the study of civil war. This study seeks to apply such methods - specifically, ordinary differential equations (ODEs) - to model civil war based on what one might dub the capabilities school of thought, which roughly states that civil wars end only when one side’s ability to make war falls far enough to make peace truly attractive. I construct several different ODE-based models and then test them all to see which best predicts the instantaneous capabilities of both sides of the Sri Lankan civil war in the period from 1990 to 1994 given parameters and initial conditions. The model that the tests declare most accurate gives very accurate predictions of state military capabilities and reasonable short term predictions of cumulative deaths. Analysis of the model reveals the scale of the importance of rebel finances to the sustainability of insurgency, most notably that the number of troops required to put down the Tamil Tigers is reduced by nearly a full order of magnitude when Tiger foreign funding is stopped. The study thus demonstrates that accurate foresight may come of relatively simple dynamical models, and implies the great potential of advanced and currently unconventional non-statistical mathematical methods in political science.

Age models of sediment cores from the Southern Ocean

Recent geochemical models invoke ocean alkalinity changes, particularly in the surface Southern Ocean, to explain glacial age pCO2 reduction. In such models, alkalinity increases in glacial periods are driven by reductions in North Atlantic Deep Water (NADW) supply, which lead to increases in deep-water nutrients and dissolution of carbonate sediments, and to increased alkalinity of Circumpolar Deep Water upwelling in the surface Southern Ocean. We use cores from the Southeast Indian Ridge and from the deep Cape Basin in the South Atlantic to show that carbonate dissolution was enhanced during glacial stages in areas now bathed by Circumpolar Deep Water. This suggests that deep Southern Ocean carbonate ion concentrations were lower in glacial stages than in interglacials, rather than higher as suggested by the polar alkalinity model [Broecker and Peng, 1989, doi:10.1029/GB001i001p00015]. Our observations show that changes in Southern Ocean CaCO3 preservation are coherent with changes in the relative flux of NADW, suggesting that Southern Ocean carbonate chemistry is closely linked to changes in deepwater circulation. The pattern of enhanced dissolution in glacials is consistent with a reduction in the supply of nutrient-depleted water (NADW) to the Southern Ocean and with an increase of nutrients in deep water masses. Carbonate mass accumulation rates on the Southeast Indian Ridge (3200-3800 m), and in relatively shallow cores (<3000 m) from the Kerguelen Plateau and the South Pacific were significantly reduced during glacial stages, by about 50%. The reduced carbonate mass accumulation rates and enhanced dissolution during glacials may be partly due to decreases in CaCO3:Corg flux ratios, acting as another mechanism which would raise the alkalinity of Southern Ocean surface waters. The polar alkalinity model assumes that the ratio of organic carbon to carbonate production on surface alkalinity is constant. Even if overall productivity in the Southern Ocean were held constant, a decrease in the CaCO3:Corg ratio would result in increased alkalinity and reduced pCO2 in Southern Ocean surface waters during glacials. This ecologically driven surface alkalinity change may enhance deepwater-mediated changes in alkalinity, and amplify rapid changes in pCO2.

Comparing the quality of three models of postabortion care in public hospitals in Mexico City

artículo publicado en la revista Int Fam Plan Perspect. 2003 Sep;29(3):112-20

Age models of ODP sites from the Barents Sea-Svalbard region

Based on a revised chronostratigraphy, and compilation of borehole data from the Barents Sea continental margin, a coherent glaciation model is proposed for the Barents Sea ice sheet over the past 3.5 million years (Ma). Three phases of ice growth are suggested: (1) The initial build-up phase, covering mountainous regions and reaching the coastline/shelf edge in the northern Barents Sea during short-term glacial intensification, is concomitant with the onset of the Northern Hemisphere Glaciation (3.6-2.4 Ma). (2) A transitional growth phase (2.4-1.0 Ma), during which the ice sheet expanded towards the southern Barents Sea and reached the northwestern Kara Sea. This is inferred from step-wise decrease of Siberian river-supplied smectite-rich sediments, likely caused by ice sheet blockade and possibly reduced sea ice formation in the Kara Sea as well as glacigenic wedge growth along the northwestern Barents Sea margin hampering entrainment and transport of sea ice sediments to the Arctic-Atlantic gateway. (3) Finally, large-scale glaciation in the Barents Sea occurred after 1 Ma with repeated advances to the shelf edge. The timing is inferred from ice grounding on the Yermak Plateau at about 0.95 Ma, and higher frequencies of gravity-driven mass movements along the western Barents Sea margin associated with expansive glacial growth.