Estimating parameters for generalized mass action models using constraint propagation.

As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.

The kinetic parameters and energy cost of the Hsp70 chaperone as a polypeptide unfoldase.

Hsp70-Hsp40-NEF and possibly Hsp100 are the only known molecular chaperones that can use the energy of ATP to convert stably pre-aggregated polypeptides into natively refolded proteins. However, the kinetic parameters and ATP costs have remained elusive because refolding reactions have only been successful with a molar excess of chaperones over their polypeptide substrates. Here we describe a stable, misfolded luciferase species that can be efficiently renatured by substoichiometric amounts of bacterial Hsp70-Hsp40-NEF. The reactivation rates increased with substrate concentration and followed saturation kinetics, thus allowing the determination of apparent V(max)' and K(m)' values for a chaperone-mediated renaturation reaction for the first time. Under the in vitro conditions used, one Hsp70 molecule consumed five ATPs to effectively unfold a single misfolded protein into an intermediate that, upon chaperone dissociation, spontaneously refolded to the native state, a process with an ATP cost a thousand times lower than expected for protein degradation and resynthesis.

Modeling and mitigation of supply-demand mismatches

In this thesis, I develop analytical models to price the value of supply chain investments under demand uncer¬tainty. This thesis includes three self-contained papers. In the first paper, we investigate the value of lead-time reduction under the risk of sudden and abnormal changes in demand forecasts. We first consider the risk of a complete and permanent loss of demand. We then provide a more general jump-diffusion model, where we add a compound Poisson process to a constant-volatility demand process to explore the impact of sudden changes in demand forecasts on the value of lead-time reduction. We use an Edgeworth series expansion to divide the lead-time cost into that arising from constant instantaneous volatility, and that arising from the risk of jumps. We show that the value of lead-time reduction increases substantially in the intensity and/or the magnitude of jumps. In the second paper, we analyze the value of quantity flexibility in the presence of supply-chain dis- intermediation problems. We use the multiplicative martingale model and the "contracts as reference points" theory to capture both positive and negative effects of quantity flexibility for the downstream level in a supply chain. We show that lead-time reduction reduces both supply-chain disintermediation problems and supply- demand mismatches. We furthermore analyze the impact of the supplier's cost structure on the profitability of quantity-flexibility contracts. When the supplier's initial investment cost is relatively low, supply-chain disin¬termediation risk becomes less important, and hence the contract becomes more profitable for the retailer. We also find that the supply-chain efficiency increases substantially with the supplier's ability to disintermediate the chain when the initial investment cost is relatively high. In the third paper, we investigate the value of dual sourcing for the products with heavy-tailed demand distributions. We apply extreme-value theory and analyze the effects of tail heaviness of demand distribution on the optimal dual-sourcing strategy. We find that the effects of tail heaviness depend on the characteristics of demand and profit parameters. When both the profit margin of the product and the cost differential between the suppliers are relatively high, it is optimal to buffer the mismatch risk by increasing both the inventory level and the responsive capacity as demand uncertainty increases. In that case, however, both the optimal inventory level and the optimal responsive capacity decrease as the tail of demand becomes heavier. When the profit margin of the product is relatively high, and the cost differential between the suppliers is relatively low, it is optimal to buffer the mismatch risk by increasing the responsive capacity and reducing the inventory level as the demand uncertainty increases. In that case, how¬ever, it is optimal to buffer with more inventory and less capacity as the tail of demand becomes heavier. We also show that the optimal responsive capacity is higher for the products with heavier tails when the fill rate is extremely high.

Genetic parameters and estimated genetic gains in young rubber tree progenies

The objective of this work was to assess the genetic parameters and to estimate genetic gains in young rubber tree progenies. The experiments were carried out during three years, in a randomized block design, with six replicates and ten plants per plot, in three representative Hevea crop regions of the state of São Paulo, Brazil. Twenty-two progenies were evaluated, from three to five years old, for rubber yield and annual girth growth. Genetic gain was estimated with the multi-effect index (MEI). Selection by progenies means provided greater estimated genetic gain than selection based on individuals, since heritability values of progeny means were greater than the ones of individual heritability, for both evaluated variables, in all the assessment years. The selection of the three best progenies for rubber yield provided a selection gain of 1.28 g per plant. The genetic gains estimated with MEI using data from early assessments (from 3 to 5-year-old) were generally high for annual girth growth and rubber yield. The high genetic gains for annual girth growth in the first year of assessment indicate that progenies can be selected at the beginning of the breeding program. Population effective size was consistent with the three progenies selected, showing that they were not related and that the population genetic variability is ensured. Early selection with the genetic gains estimated by MEI can be made on rubber tree progenies.

Mating system parameters in a high density population of andirobas in the Amazon forest

The objective of this work was to estimate the mating system parameters of a andiroba (Carapa guianensis) population using microsatellite markers and the mixed and correlated mating models. Twelve open‑pollinated progeny arrays of 15 individuals were sampled in an area with C. guianensis estimated density of 25.7 trees per hectare. Overall, the species has a mixed reproductive system, with a predominance of outcrossing. The multilocus outcrossing rate (t m = 0.862) was significantly lower than the unity, indicating that self‑pollination occurred. The rate of biparental inbreeding was substantial (t m ‑ t s = 0.134) and significantly different from zero. The correlation of selfing within progenies was high (r s = 0.635), indicating variation in the individual outcrossing rate. Consistent with this result, the estimate of the individual outcrossing rate ranged from 0.598 to 0.978. The multilocus correlation of paternity was low (r p(m) = 0.081), but significantly different from zero, suggesting that the progenies contain full‑sibs. The coancestry within progenies (Θ = 0.185) was higher and the variance effective size (Ne(v) = 2.7) was lower than expected for true half‑sib progenies (Θ = 0.125; Ne(v) = 4). These results suggest that, in order to maintain a minimum effective size of 150 individuals for breeding, genetic conservation, and environmental reforestation programs, seeds from at least 56 trees must be collected.

Combining hypoxic methods for peak performance.

New methods and devices for pursuing performance enhancement through altitude training were developed in Scandinavia and the USA in the early 1990s. At present, several forms of hypoxic training and/or altitude exposure exist: traditional 'live high-train high' (LHTH), contemporary 'live high-train low' (LHTL), intermittent hypoxic exposure during rest (IHE) and intermittent hypoxic exposure during continuous session (IHT). Although substantial differences exist between these methods of hypoxic training and/or exposure, all have the same goal: to induce an improvement in athletic performance at sea level. They are also used for preparation for competition at altitude and/or for the acclimatization of mountaineers. The underlying mechanisms behind the effects of hypoxic training are widely debated. Although the popular view is that altitude training may lead to an increase in haematological capacity, this may not be the main, or the only, factor involved in the improvement of performance. Other central (such as ventilatory, haemodynamic or neural adaptation) or peripheral (such as muscle buffering capacity or economy) factors play an important role. LHTL was shown to be an efficient method. The optimal altitude for living high has been defined as being 2200-2500 m to provide an optimal erythropoietic effect and up to 3100 m for non-haematological parameters. The optimal duration at altitude appears to be 4 weeks for inducing accelerated erythropoiesis whereas <3 weeks (i.e. 18 days) are long enough for beneficial changes in economy, muscle buffering capacity, the hypoxic ventilatory response or Na(+)/K(+)-ATPase activity. One critical point is the daily dose of altitude. A natural altitude of 2500 m for 20-22 h/day (in fact, travelling down to the valley only for training) appears sufficient to increase erythropoiesis and improve sea-level performance. 'Longer is better' as regards haematological changes since additional benefits have been shown as hypoxic exposure increases beyond 16 h/day. The minimum daily dose for stimulating erythropoiesis seems to be 12 h/day. For non-haematological changes, the implementation of a much shorter duration of exposure seems possible. Athletes could take advantage of IHT, which seems more beneficial than IHE in performance enhancement. The intensity of hypoxic exercise might play a role on adaptations at the molecular level in skeletal muscle tissue. There is clear evidence that intense exercise at high altitude stimulates to a greater extent muscle adaptations for both aerobic and anaerobic exercises and limits the decrease in power. So although IHT induces no increase in VO(2max) due to the low 'altitude dose', improvement in athletic performance is likely to happen with high-intensity exercise (i.e. above the ventilatory threshold) due to an increase in mitochondrial efficiency and pH/lactate regulation. We propose a new combination of hypoxic method (which we suggest naming Living High-Training Low and High, interspersed; LHTLHi) combining LHTL (five nights at 3000 m and two nights at sea level) with training at sea level except for a few (2.3 per week) IHT sessions of supra-threshold training. This review also provides a rationale on how to combine the different hypoxic methods and suggests advances in both their implementation and their periodization during the yearly training programme of athletes competing in endurance, glycolytic or intermittent sports.

Repeatability of adaptability and stability parameters of common bean in unpredictable environments

The objective of this work was to estimate the repeatability of adaptability and stability parameters of common bean between years, within each biennium from 2003 to 2012, in Minas Gerais state, Brazil. Grain yield data from trials of value for cultivation and use common bean were analyzed. Grain yield, ecovalence, regression coefficient, and coefficient of determination were estimated considering location and sowing season per year, within each biennium. Subsequently, a analysis of variance these estimates was carried out, and repeatability was estimated in the biennia. Repeatability estimate for grain yield in most of the biennia was relatively high, but for ecovalence and regression coefficient it was null or of small magnitude, which indicates that confidence on identification of common bean lines for recommendation is greater when using means of yield, instead of stability parameters.

Use of individual race results in the estimation of genetic parameters of trotting performance for Finnhorse and Standardbred trotters

Selostus: Ravikilpailumenestysmittojen periytymisasteet ja toistumiskertoimet kilpailukohtaisten tulosten perusteella

Genetic parameters and simultaneous selection for root yield, adaptability and stability of cassava genotypes

The objective of this work was to estimate genetic parameters and to evaluate simultaneous selection for root yield and for adaptability and stability of cassava genotypes. The effects of genotypes were assumed as fixed and random, and the mixed model methodology (REML/Blup) was used to estimate genetic parameters and the harmonic mean of the relative performance of genotypic values (HMRPGV), for simultaneous selection purposes. Ten genotypes were analyzed in a complete randomized block design, with four replicates. The experiment was carried out in the municipalities of Altamira, Santarém, and Santa Luzia do Pará in the state of Pará, Brazil, in the growing seasons of 2009/2010, 2010/2011, and 2011/2012. Roots were harvested 12 months after planting, in all tested locations. Root yield had low coefficients of genotypic variation (4.25%) and broad-sense heritability of individual plots (0.0424), which resulted in low genetic gain. Due to the low genotypic correlation (0.15), genotype classification as to root yield varied according to the environment. Genotypes CPATU 060, CPATU 229, and CPATU 404 stood out as to their yield, adaptability, and stability.

Second-order parameter estimation

This work provides a general framework for the design of second-order blind estimators without adopting anyapproximation about the observation statistics or the a prioridistribution of the parameters. The proposed solution is obtainedminimizing the estimator variance subject to some constraints onthe estimator bias. The resulting optimal estimator is found todepend on the observation fourth-order moments that can be calculatedanalytically from the known signal model. Unfortunately,in most cases, the performance of this estimator is severely limitedby the residual bias inherent to nonlinear estimation problems.To overcome this limitation, the second-order minimum varianceunbiased estimator is deduced from the general solution by assumingaccurate prior information on the vector of parameters.This small-error approximation is adopted to design iterativeestimators or trackers. It is shown that the associated varianceconstitutes the lower bound for the variance of any unbiasedestimator based on the sample covariance matrix.The paper formulation is then applied to track the angle-of-arrival(AoA) of multiple digitally-modulated sources by means ofa uniform linear array. The optimal second-order tracker is comparedwith the classical maximum likelihood (ML) blind methodsthat are shown to be quadratic in the observed data as well. Simulationshave confirmed that the discrete nature of the transmittedsymbols can be exploited to improve considerably the discriminationof near sources in medium-to-high SNR scenarios.

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test-day milk yield (TDMY) from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

Seed biometric parameters in oil palm accessions from a Brazilian germplasm bank

The objective of this work was to evaluate the morphological diversity of oil palm seeds and to cluster the accessions according to their morphological characteristics. Forty-one accessions from the oil palm germplasm bank of Embrapa Amazônia Ocidental were evaluated - 18 of Elaeis oleifera and 23 of E. guineensis. The groups were formed based on morphological characteristics, by principal component analysis. In E. oleifera, four groups were formed, tied to their region of origin, but with significant morphological differences between accessions from the same population. For tenera-type E. guineensis seeds, three widely divergent groups were formed, especially as to external parameters, which differentiated them from the other ones. The parameter endocarp thickness stood out in intra- and inter-population differentiation. For dura-type E. guineensis, three groups were formed, with larger seeds and thicker endocarps, which differed from all the other ones. The variability observed for seed characteristics in the analyzed accessions allows the establishment of different groups, to define strategies for genetic improvement.

Recurrent TET2 mutations in peripheral T-cell lymphomas correlate with TFH-like features and adverse clinical parameters.

Inactivating mutations of the Ten-Eleven Translocation 2 (TET2) gene were first identified in myeloid malignancies and more recently in peripheral T-cell lymphomas (PTCLs). In the present study, we investigated the presence of TET2 coding sequence mutations and their clinical relevance in a large cohort of 190 PTCL patients. TET2 mutations were identified in 40 of 86 (47%) cases of angioimmunoblastic T-cell lymphoma (AITL) and in 22 of 58 (38%) cases of peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS), but were absent in all other PTCL entities, with the exception of 2 of 10 cases of enteropathy-associated T-cell lymphoma. Among PTCL-NOS, a heterogeneous group of lymphoma-comprising cases likely to derive from Th follicular (T(FH)) cells similarly to AITL, TET2 mutations were more frequent when PTCL-NOS expressed T(FH) markers and/or had features reminiscent of AITL (58% vs 24%, P = .01). In the AITL and PTCL-NOS subgroups, TET2 mutations were associated with advanced-stage disease, thrombocytopenia, high International Prognostic Index scores, and a shorter progression-free survival.

Effect of Tocopherol Extract, Staphylococcus carnosus Culture, and Celery Concentrate Addition on Quality Parameters of Organic and Conventional Dry-Cured Sausages

The effects of the addition to sausage mix of tocopherols (200 mg/kg), a conventional starter culture with or without Staphylococcus carnosus, celery concentrate (CP) (0.23% and 0.46%), and two doses of nitrate (70 and 140 mg/kg expressed as NaNO(3)) on residual nitrate and nitrite amounts, instrumental CIE Lab color, tocol content, oxidative stability, and overall acceptability were studied in fermented dry-cured sausages after ripening and after storage. Nitrate doses were provided by nitrate-rich CP or a chemical grade source. The lower dose complies with the EU requirements governing the maximum for ingoing amounts in organic meat products. Tocopherol addition protected against oxidation, whereas the nitrate dose, nitrate source, or starter culture had little influence on secondary oxidation values. The residual nitrate and nitrite amounts found in the sausages with the lower nitrate dose were within EU-permitted limits for organic meat products and residual nitrate can be further reduced by the presence of the S. carnosus culture. Color measurements were not affected by the CP dose. Product consumer acceptability was not affected negatively by any of the factors studied. As the two nitrate sources behaved similarly for the parameters studied, CP is a useful alternative to chemical ingredients for organic dry-cured sausage production.