A comparison of diversity estimators applied to a database of host–parasite associations

Understanding the drivers of biodiversity is important for forecasting changes in the distribution of life on earth. However, most studies of biodiversity are limited by uneven sampling effort, with some regions or taxa better sampled than others. Numerous methods have been developed to account for differences in sampling effort, but most methods were developed for systematic surveys in which all study units are sampled using the same design and assemblages are sampled randomly. Databases compiled from multiple sources, such as from the literature, often violate these assumptions because they are composed of studies that vary widely in their goals and methods. Here, we compared the performance of several popular methods for estimating parasite diversity based on a large and widely used parasite database, the Global Mammal Parasite Database (GMPD). We created artificial datasets of host–parasite interactions based on the structure of the GMPD, then used these datasets to evaluate which methods best control for differential sampling effort. We evaluated the precision and bias of seven methods, including species accumulation and nonparametric diversity estimators, compared to analyzing the raw data without controlling for sampling variation. We find that nonparametric estimators, and particularly the Chao2 and second-order jackknife estimators, perform better than other methods. However, these estimators still perform poorly relative to systematic sampling, and effect sizes should be interpreted with caution because they tend to be lower than actual effect sizes. Overall, these estimators are more effective in comparative studies than for producing true estimates of diversity. We make recommendations for future sampling strategies and statistical methods that would improve estimates of global parasite diversity.     

Predicting direct protein interactions from affinity purification mass spectrometry data

Background  

Affinity purification followed by mass spectrometry identification (AP-MS) is an increasingly popular approach to observe protein-protein interactions (PPI) in vivo. One drawback of AP-MS, however, is that it is prone to detecting indirect interactions mixed with direct physical interactions. Therefore, the ability to distinguish direct interactions from indirect ones is of much interest.     

Intracellular acidification induces decrease of cytosolic calcium in isolated osteoclasts

In this study the effects of changes in intracellular pH on cytosolic Ca2+ were examined in single isolated osteoclasts. Alkalinization, performed by incubation in HCO3 containing buffer, induced increases in [Ca2+]. Conversely acidification, obtained by incubation in Na-butyrate-containing buffer induced a rapid and sustained decrease of [Ca2+]. The decrease of [Ca2+], during acidification with Na-butyrate was inhibited by VO4, an inhibitor of the Ca2+-ATPase. All these pieces of information indicate that changes in pH1 can modulate osteoclast activity together with modifications of [Ca2+], probably acting as intracellular signals.     

Monoclonal antibody with high affinity for 1,25-dihydroxycholecalciferol

We have developed a monoclonal antibody capable of detecting 1 pg/ml of 1,25-dihydroxycholecalciferol. At a dilution of 1:80,000 of ascitic fluid this antibody has an apparent K_D of 3.3 × 10^?11ML^?1. The immunogen used was a vitamin D analogue, calcitroic acid [1α, 3 β-dihydroxy-9, 10 seco-24-nor 5,7,10 (19) cholatriene-23-oic acid], conjugated to bovine serum albumin. Although this antibody is extremely sensitive, it also recognizes other important vitamin D₃ metabolites.     

Osteoclasts; culprits in inflammatory osteolysis

Periarticular osteolysis, a crippling complication of rheumatoid arthritis, is the product of enhanced osteoclast recruitment and activation. The osteoclast, which is a member of the monocyte/macrophage family, is the exclusive bone resorptive cell, and its differentiation and activation are under the aegis of a variety of cytokines. Receptor activator of NF-kappaB ligand (RANKL) and macrophage colony-stimulating factor are the essential osteoclastogenic cytokines and are increased in inflammatory joint disease. Tumor necrosis factor-alpha, which perpetrates arthritic bone loss, exerts its osteoclastogenic effect in the context of RANKL with which it synergizes. Achieving an understanding of the mechanisms by which the three cytokines affect the osteoclast has resulted in a number of active and candidate therapeutic targets.