Optimality Clue for Graph Coloring Problem

In this paper, we present a new approach which qualifies or not a solution found by a heuristic as a potential optimal solution. Our approach is based on the following observation: for a minimization problem, the number of admissible solutions decreases with the value of the objective function. For the Graph Coloring Problem (GCP), we confirm this observation and present a new way to prove optimality. This proof is based on the counting of the number of different k-colorings and the number of independent sets of a given graph G. Exact solutions counting problems are difficult problems (\#P-complete). However, we show that, using only randomized heuristics, it is possible to define an estimation of the upper bound of the number of k-colorings. This estimate has been calibrated on a large benchmark of graph instances for which the exact number of optimal k-colorings is known. Our approach, called optimality clue, build a sample of k-colorings of a given graph by running many times one randomized heuristic on the same graph instance. We use the evolutionary algorithm HEAD [Moalic et Gondran, 2018], which is one of the most efficient heuristic for GCP. Optimality clue matches with the standard definition of optimality on a wide number of instances of DIMACS and RBCII benchmarks where the optimality is known. Then, we show the clue of optimality for another set of graph instances. Optimality Metaheuristics Near-optimal

How predation and landscape fragmentation affect vole population dynamics

Background: Microtine species in Fennoscandia display a distinct north-south gradient from regular cycles to stable populations. The gradient has often been attributed to changes in the interactions between microtines and their predators. Although the spatial structure of the environment is known to influence predator-prey dynamics of a wide range of species, it has scarcely been considered in relation to the Fennoscandian gradient. Furthermore, the length of microtine breeding season also displays a north-south gradient. However, little consideration has been given to its role in shaping or generating population cycles. Because these factors covary along the gradient it is difficult to distinguish their effects experimentally in the field. The distinction is here attempted using realistic agent-based modelling. Methodology/Principal Findings: By using a spatially explicit computer simulation model based on behavioural and ecological data from the field vole (Microtus agrestis), we generated a number of repeated time series of vole densities whose mean population size and amplitude were measured. Subsequently, these time series were subjected to statistical autoregressive modelling, to investigate the effects on vole population dynamics of making predators more specialised, of altering the breeding season, and increasing the level of habitat fragmentation. We found that fragmentation as well as the presence of specialist predators are necessary for the occurrence of population cycles. Habitat fragmentation and predator assembly jointly determined cycle length and amplitude. Length of vole breeding season had little impact on the oscillations. Significance: There is good agreement between our results and the experimental work from Fennoscandia, but our results allow distinction of causation that is hard to unravel in field experiments. We hope our results will help understand the reasons for cycle gradients observed in other areas. Our results clearly demonstrate the importance of landscape fragmentation for population cycling and we recommend that the degree of fragmentation be more fully considered in future analyses of vole dynamics

Toward molecular trait-based ecology through integration of biogeochemical, geographical and metagenomic data

Using metagenomic ‘parts lists' to study microbial ecology remains a significant challenge. This work proposes a molecular trait-based approach to biogeography by integrating metagenomic data with external metadata and using functional community composition as readout

Experimental evidence that livestock grazing intensity affects cyclic vole population regulation processes

Peer reviewedPublisher PD

PGRMC1: a new biomarker for the estrogen receptor in breast cancer

Estrogen receptor (ER) status is a critical biomarker in breast cancer, in large part because the ER is the target of tamoxifen and similar drugs. In the previous issue of Breast Cancer Research, Neubauer and colleagues used a proteomic approach to identify proteins that are differentially regulated by ER in breast tumors. The authors showed that ER-negative tumors have elevated levels of PGRMC1 (progesterone receptor membrane component-1), a hormone receptor component and binding partner for P450 proteins. In contrast, PGRMC1 was phosphorylated in ER-positive tumors. The staining patterns of ER and PGRMC1 were mutually exclusive in breast tumor sections, and PGRMC1 staining was sharply increased in hypoxic areas of the tumor. The results suggest that PGRMC1 is a candidate biomarker for ER status and hypoxia in breast cancer

Bayesian paternity analysis and mating patterns in a parasitic nematode, Trichostrongylus tenuis

Mating behaviour is a fundamental aspect of the evolutionary ecology of sexually reproducing species, but one that has been under-researched in parasitic nematodes. We analysed mating behaviour in the parasitic nematode Trichostrongylus tenuis by performing a paternity analysis in a population from a single red grouse host. Paternity of the 150 larval offspring of 25 mothers (sampled from one of the two host caeca) was assigned among 294 candidate fathers (sampled from both caeca). Each candidate father's probability of paternity of each offspring was estimated from 10-locus microsatellite genotypes. Seventy-six (51%) offspring were assigned a father with a probability of >0.8, and the estimated number of unsampled males was 136 (95% credible interval (CI) 77-219). The probability of a male from one caecum fathering an offspring in the other caecum was estimated as 0.024 (95% CI 0.003-0.077), indicating that the junction of the caeca is a strong barrier to dispersal. Levels of promiscuity (defined as the probability of two of an adult's offspring sharing only one parent) were high for both sexes. Variance in male reproductive success was moderately high, possibly because of a combination of random mating and high variance in post-copulatory reproductive success. These results provide the first data on individual mating behaviour among parasitic nematodes

VEGF and Delta-Notch: interacting signalling pathways in tumour angiogenesis

Tumour angiogenesis has become an important target for antitumour therapy, with most current therapies aimed at blocking the VEGF pathway. However, not all tumours are responsive to VEGF blockers, and some tumours that are responsive initially may become resistant during the course of treatment, thus there is a need to explore other angiogenesis signalling pathways. Recently, the Delta-Notch pathway, and particularly the ligand Delta-like 4 (Dll4), was identified as a new target in tumour angiogenesis. An important feature in angiogenesis is the manifold ways in which the VEGF and Delta-Notch pathways interact. The emerging picture is that the VEGF pathway acts as a potent upstream activating stimulus for angiogenesis, whereas Delta-Notch helps to guide cell fate decisions that appropriately shape the activation. Here we review the two signalling pathways and what is currently known about the ways in which they interact during tumour angiogenesis

Positive Interspecific Relationship between Temporal Occurrence and Abundance in Insects

One of the most studied macroecological patterns is the interspecific abundance–occupancy relationship, which relates species distribution and abundance across space. Interspecific relationships between temporal distribution and abundance, however, remain largely unexplored. Using data for a natural assemblage of tabanid flies measured daily during spring and summer in Nova Scotia, we found that temporal occurrence (proportion of sampling dates in which a species occurred in an experimental trap) was positively related to temporal mean abundance (number of individuals collected for a species during the study period divided by the total number of sampling dates). Moreover, two models that often describe spatial abundance–occupancy relationships well, the He–Gaston and negative binomial models, explained a high amount of the variation in our temporal data. As for the spatial abundance–occupancy relationship, the (temporal) aggregation parameter, k, emerged as an important component of the hereby named interspecific temporal abundance–occurrence relationship. This may be another case in which a macroecological pattern shows similarities across space and time, and it deserves further research because it may improve our ability to forecast colonization dynamics and biological impacts