Evolutionary dynamics in an SI epidemic model with phenotype-structured susceptible compartment

When modeling infectious diseases, it is common to assume that infection-derived immunity is either (1) non-existent or (2) perfect and lifelong. However there are many diseases in which infection-derived immunity is known to be present but imperfect. There are various ways in which infection-derived immunity can fail, which can ultimately impact the probability that an individual be reinfected by the same pathogen, as well as the long-run population-level prevalence of the pathogen. Here we discuss seven different models of imperfect infection-derived immunity, including waning, leaky and all-or-nothing immunity. For each model we derive the probability that an infected individual becomes reinfected during their lifetime, given that the system is at endemic equilibrium. This can be thought of as the impact that each of these infection-derived immunity failures have on reinfection. This measure is useful because it provides us with a way to compare different modes of failure of infection-derived immunity.

     

Clinical Evaluation of Rega 8: An Updated Genotypic Interpretation System That Significantly Predicts HIV-Therapy Response

Introduction

Clinically evaluating genotypic interpretation systems is essential to provide optimal guidance in designing potent individualized HIV-regimens. This study aimed at investigating the ability of the latest Rega algorithm to predict virological response on a short and longer period.

Materials & Methods

9231 treatment changes episodes were extracted from an integrated patient database. The virological response after 8, 24 and 48 weeks was dichotomized to success and failure. Success was defined as a viral load below 50 copies/ml or alternatively, a 2 log decrease from the baseline viral load at 8 weeks. The predictive ability of Rega version 8 was analysed in comparison with that of previous evaluated version Rega 5 and two other algorithms (ANRS v2011.05 and Stanford HIVdb v6.0.11). A logistic model based on the genotypic susceptibility score was used to predict virological response, and additionally, confounding factors were added to the model. Performance of the models was compared using the area under the ROC curve (AUC) and a Wilcoxon signed-rank test.

Results

Per unit increase of the GSS reported by Rega 8, the odds on having a successful therapy response on week 8 increased significantly by 81% (OR = 1.81, CI = [1.76–1.86]), on week 24 by 73% (OR = 1.73, CI = [1.69–1.78]) and on week 48 by 85% (OR = 1.85, CI = [1.80–1.91]). No significant differences in AUC were found between the performance of Rega 8 and Rega 5, ANRS v2011.05 and Stanford HIVdb v6.0.11, however Rega 8 had the highest sensitivity: 76.9%, 76.5% and 77.2% on 8, 24 and 48 weeks respectively. Inclusion of additional factors increased the performance significantly.

Conclusion

Rega 8 is a significant predictor for virological response with a better sensitivity than previously, and with rules for recently approved drugs. Additional variables should be taken into account to ensure an effective regimen.     

Continued optimization of the MLPCN probe ML071 into highly potent agonists of the hM1 muscarinic acetylcholine receptor

This Letter describes the continued optimization of the MLPCN probe molecule ML071. After introducing numerous cyclic constraints and novel substitutions throughout the parent structure, we produced a number of more highly potent agonists of the M(1) mACh receptor. While many novel agonists demonstrated a promising ability to increase soluble APPα release, further characterization indicated they may be functioning as bitopic agonists. These results and the implications of a bitopic mode of action are presented.     

Tree seedling response to LED spectra: implications for forest restoration

We found that different spectra, provided by light-emitting diodes or a fluorescent lamp, caused different photomorphological responses depending on tree seedling type (coniferous or broad-leaved), species, seedling development stage, and seedling fraction (shoot or root). For two conifers (Picea abies and Pinus sylvestris) soon after germination (≤40 days), more seedling growth was related to a lower ratio of red-to-far-red (R:FR) light. As growth continued to 120 days, spectra with a greater complement of blue light yielded more growth. Roots showed more plasticity to light spectra than shoots. In general for the evergreen broad-leaved Quercus ilex, spectra with additional R:FR than for conifers yielded more growth in the first 57 days. Subsequently as seedlings grew, shoot growth appeared to be influenced less by light source than roots, with root length showing the greatest responses. Our results suggest that manipulating light spectra to foster desired seedling traits may be another tool for use in the production of high-quality seedlings as defined through the Target Plant Concept. Such seedlings are needed for restoration of the two billion hectares of degraded forestland, especially on harsh sites such as those found in the Mediterranean region, and to sequester carbon to mitigate climate change.     

Species distribution models as a tool to estimate reproductive parameters: a case study with a passerine bird species

1.?Correlative species distribution models (SDMs) assess relationships between species distribution data and environmental features, to evaluate the environmental suitability (ES) of a given area for a species, by providing a measure of the probability of presence. If the output of SDMs represents the relationships between habitat features and species performance well, SDM results can be related also to other key parameters of populations, including reproductive parameters. To test this hypothesis, we evaluated whether SDM results can be used as a proxy of reproductive parameters (breeding output, territory size) in red-backed shrikes (Lanius collurio). 2.?The distribution of 726 shrike territories in Northern Italy was obtained through multiple focused surveys; for a subset of pairs, we also measured territory area and number of fledged juveniles. We used Maximum Entropy modelling to build a SDM on the basis of territory distribution. We used generalized least squares and spatial generalized mixed models to relate territory size and number of fledged juveniles to SDM suitability, while controlling for spatial autocorrelation. 3.?Species distribution models predicted shrike distribution very well. Territory size was negatively related to suitability estimated through SDM, while the number of fledglings significantly increased with the suitability of the territory. This was true also when SDM was built using only spatially and temporally independent data. 4.?Results show a clear relationship between ES estimated through presence-only SDMs and two key parameters related to species' reproduction, suggesting that suitability estimated by SDM, and habitat quality determining reproduction parameters in our model system, are correlated. Our study shows the potential use of SDMs to infer important fitness parameters; this information can have great importance in management and conservation.