The mechanisms of the residual force enhancement after stretch of skeletal muscle: non-uniformity in half-sarcomeres and stiffness of titin

When activated skeletal muscles are stretched, the force increases significantly. After the stretch, the force decreases and reaches a steady-state level that is higher than the force produced at the corresponding length during purely isometric contractions. This phenomenon, referred to as residual force enhancement, has been observed for more than 50 years, but the mechanism remains elusive, generating considerable debate in the literature. This paper reviews studies performed with single muscle fibres, myofibrils and sarcomeres to investigate the mechanisms of the stretch-induced force enhancement. First, the paper summarizes the characteristics of force enhancement and early hypotheses associated with non-uniformity of sarcomere length. Then, it reviews new evidence suggesting that force enhancement can also be associated with sarcomeric structures. Finally, this paper proposes that force enhancement is caused by: (i) half-sarcomere non-uniformities that will affect the levels of passive forces and overlap between myosin and actin filaments, and (ii) a Ca(2+)-induced stiffness of titin molecules. These mechanisms are compatible with most observations in the literature, and can be tested directly with emerging technologies in the near future.     

Instabilities in multiserotype disease models with antibody-dependent enhancement

This paper investigates the complex dynamics induced by antibody-dependent enhancement (ADE) in multiserotype disease models. ADE is the increase in viral growth rate in the presence of immunity due to a previous infection of a different serotype. The increased viral growth rate is thought to increase the infectivity of the secondary infectious class. In our models, ADE induces the onset of oscillations without external forcing. The oscillations in the infectious classes represent outbreaks of the disease. In this paper, we derive approximations of the ADE parameter needed to induce oscillations and analyze the associated bifurcations that separate the types of oscillations. We then investigate the stability of these dynamics by adding stochastic perturbations to the model. We also present a preliminary analysis of the effect of a single serotype vaccination in the model.     

Modelling the relationship between antibody-dependent enhancement and immunological distance with application to dengue

When antibodies raised in response to a particular pathogen bind with immunologically similar pathogens it may facilitate infection through a phenomenon known as antibody-dependent enhancement (ADE). This process occurs between the four serotypes of dengue virus and, furthermore, secondary infection is a major risk factor in dengue hemorrhagic fever (DHF). Theory has suggested that ADE may be responsible for the large immunological distance between dengue serotypes. We investigate this hypothesis using an epidemic model for dengue in which immunological distance and the strength of immune cross-reaction are expressed separately. Cross-enhancement is considered in three alternative forms acting on susceptibility, transmission and mortality. Previous models have shown that transmission and mortality enhancement can lead to periodicity or chaos. We confirm this result for reasonable levels of susceptibility and transmission enhancement but not for mortality enhancement. We also show that when the two strains have identical basic reproductive numbers no form of enhancement leads to competitive exclusion. When the two strains have different basic reproductive numbers susceptibility or transmission enhancement allow strains with greater immunological similarity to stably coexist but mortality enhancement forces strains to be more distinct. All three forms of enhancement can be associated with DHF and we conclude that mortality enhancement must be dominant if ADE really is responsible for the immunological distance between dengue serotypes.     

Growth enhancement due to global atmospheric change as predicted by terrestrial ecosystem models: consistent with US forest inventory data

Small reported growth enhancement factors based on analyses of forest inventory data from the eastern USA ( Caspersen et al. 2000 , Science, 290, 1148–1151) have been interpreted as evidence against CO₂ fertilization in natural forests. We show to the contrary that growth enhancement in response to rising CO₂, as found in ecosystems with experimental CO₂ enrichment and implemented in terrestrial ecosystem models, is consistent with the data that have been presented within their uncertainties. Comparing forest inventory data with results of an empirical model of age‐dependent biomass accumulation, we find that growth enhancement of plausible magnitude could not be detected in these data, even if it were present. Although forest regrowth due to land‐use change is recognized as an important cause of carbon uptake by eastern US forests, forest inventory data do not provide a basis for eliminating environmentally induced growth enhancement as a substantial contribution to the global terrestrial carbon sink.     

Maximum likelihood estimation in random effects cure rate models with nonignorable missing covariates

We introduce a method of parameter estimation for a random effects cure rate model. We also propose a methodology that allows us to account for nonignorable missing covariates in this class of models. The proposed method corrects for possible bias introduced by complete case analysis when missing data are not missing completely at random and is motivated by data from a pair of melanoma studies conducted by the Eastern Cooperative Oncology Group in which clustering by cohort or time of study entry was suspected. In addition, these models allow estimation of cure rates, which is desirable when we do not wish to assume that all subjects remain at risk of death or relapse from disease after sufficient follow-up. We develop an EM algorithm for the model and provide an efficient Gibbs sampling scheme for carrying out the E-step of the algorithm.     

Effects of temperature on the development and survival of an endangered butterfly,Lycaeides argyrognomon (Lepidoptera: Lycaenidae) with estimation of optimal and threshold temperatures using linear and nonlinear models

The effects of temperature on the development and survival of Lycaeides argyrognomon were examined in the laboratory. The eggs, larvae and pupae were reared at temperatures of 15, 17.5, 20, 25, 30 and 33°C under a long‐day photoperiod of 16‐h light and 8‐h darkness. The survival rates of the first–third instars ranged from 40.0 to 82.4%. The mortalities of the fourth instar were lower than those of the first–third instars. The development time of the overall immature stage decreased from 78.33 days at 15°C to 21.07 days at 30°C, and then increased to 24.33 days at 33°C. The common linear model and the Ikemoto–Takai model were used to estimate the thermal constant (K) and the developmental zero (T₀). The values of T₀ and K for the overall immature stages were 10.50°C and 418.83 degree‐days, and 9.71°C and 451.68 degree‐days by the common model and the Ikemoto–Takai model, respectively. The upper temperature thresholds (T_max) and the optimal temperatures (T_opt) of the egg, the first–third instars and the overall immature stages were estimated by the three nonlinear models. The ranges of T_opt estimated were from 30.33°C to 32.46°C in the overall immature stages and the estimates of T_max of the overall immature stages by the Briere‐1 and the Briere‐2 models were 37.18°C and 33.00°C, respectively. The method to predict the developmental period of L. argyrognomon using the nonlinear models was discussed based on the data of the average temperature per hour.