Does a Carbonatite Deposit Influence Its Surrounding Ecosystem?

Carbonatites are unusual alkaline rocks with diverse compositions. Although previous work has characterized the effects these rocks have on soils and plants, little is known about their impacts on local ecosystems. Using a deposit within the Great Lakes–St. Lawrence forest in northern Ontario, Canada, we investigated the effect of a carbonatite on soil chemistry and on the structure of plant and soil microbial communities. This was done using a vegetation survey conducted above and around the deposit, with corresponding soil samples collected for determining soil nutrient composition and for assessing microbial community structure using 16S/ITS Illumina Mi-Seq sequencing. In some soils above the deposit a soil chemical signature of the carbonatite was found, with the most important effect being an increase in soil pH compared with the non-deposit soils. Both plants and microorganisms responded to the altered soil chemistry: the plant communities present in carbonatite-impacted soils were dominated by ruderal species, and although differences in microbial communities across the surveyed areas were not obvious, the abundances of specific bacteria and fungi were reduced in response to the carbonatite. Overall, the deposit seems to have created microenvironments of relatively basic soil in an otherwise acidic forest soil. This study demonstrates for the first time how carbonatites can alter ecosystems in situ

Developmental expression of claudins in the mammary gland

Claudins are a large family of membrane proteins whose classic function is to regulate the permeability of tight junctions in epithelia. They are tetraspanins, with four alpha-helices crossing the membrane, two extracellular loops, a short cytoplasmic N-terminus and a longer and more variable C-terminus. The extracellular ends of the helices are known to undergo side-to-side (cis) interactions that allow the formation of claudin polymers in the plane of the membrane. The extracellular loops also engage in head-to-head (trans) interactions thought to mediate the formation of tight junctions. However, claudins are also present in intracellular structures, thought to be vesicles, with less well-characterized functions. Here, we briefly review our current understanding of claudin structure and function followed by an examination of changes in claudin mRNA and protein expression and localization through mammary gland development. Claudins-1, 3, 4, 7, and 8 are the five most prominent members of the claudin family in the mouse mammary gland, with varied abundance and intracellular localization during the different stages of post-pubertal development. Claudin-1 is clearly localized to tight junctions in mammary ducts in non-pregnant non-lactating animals. Cytoplasmic puncta that stain for claudin-7 are present throughout development. During pregnancy claudin-3 is localized both to the tight junction and basolaterally while claudin-4 is found only in sparse puncta. In the lactating mouse both claudin-3 and claudin-8 are localized at the tight junction where they may be important in forming the paracellular barrier. At involution and under challenge by lipopolysaccharide claudins -1, -3, and -4 are significantly upregulated. Claudin-3 is still colocalized with tight junction molecules but is also distributed through the cytoplasm as is claudin-4. These largely descriptive data provide the essential framework for future mechanistic studies of the function and regulation of mammary epithelial cell claudins

Modeling the Value of Strategic Actions in the Superior Colliculus

In learning models of strategic game play, an agent constructs a valuation (action value) over possible future choices as a function of past actions and rewards. Choices are then stochastic functions of these action values. Our goal is to uncover a neural signal that correlates with the action value posited by behavioral learning models. We measured activity from neurons in the superior colliculus (SC), a midbrain region involved in planning saccadic eye movements, while monkeys performed two saccade tasks. In the strategic task, monkeys competed against a computer in a saccade version of the mixed-strategy game ”matching-pennies”. In the instructed task, saccades were elicited through explicit instruction rather than free choices. In both tasks neuronal activity and behavior were shaped by past actions and rewards with more recent events exerting a larger influence. Further, SC activity predicted upcoming choices during the strategic task and upcoming reaction times during the instructed task. Finally, we found that neuronal activity in both tasks correlated with an established learning model, the Experience Weighted Attraction model of action valuation (Camerer and Ho, 1999). Collectively, our results provide evidence that action values hypothesized by learning models are represented in the motor planning regions of the brain in a manner that could be used to select strategic actions

Target localization and tracking by fusing doppler differentials from cellular emanations with a multi-spectral video tracker

We present an algorithm for fusing data from a constellation of RF sensors detecting cellular emanations with the output of a multi-spectral video tracker to localize and track a target with a specific cell phone. The RF sensors measure the Doppler shift caused by the moving cellular emanation and then Doppler differentials between all sensor pairs are calculated. The multi-spectral video tracker uses a Gaussian mixture model to detect foreground targets and SIFT features to track targets through the video sequence. The data is fused by associating the Doppler differential from the RF sensors with the theoretical Doppler differential computed from the multi-spectral tracker output. The absolute difference and the root-mean-square difference are computed to associate the Doppler differentials from the two sensor systems. Performance of the algorithm was evaluated using synthetically generated datasets of an urban scene with multiple moving vehicles. The presented fusion algorithm correctly associates the cellular emanation with the corresponding video target for low measurement uncertainty and in the presence of favorable motion patterns. For nearly all objects the fusion algorithm has high confidence in associating the emanation with the correct multi-spectral target from the most probable background target

The Phase Space and Stellar Populations of Cluster Galaxies at z ~ 1: Simultaneous Constraints on the Location and Timescale of Satellite Quenching

We investigate the velocity vs. position phase space of z ~ 1 cluster galaxies using a set of 424 spectroscopic redshifts in 9 clusters drawn from the GCLASS survey. Dividing the galaxy population into three categories: quiescent, star-forming, and poststarburst, we find that these populations have distinct distributions in phase space. Most striking are the poststarburst galaxies, which are commonly found at small clustercentric radii with high clustercentric velocities, and appear to trace a coherent ``ring" in phase space. Using several zoom simulations of clusters we show that the coherent distribution of the poststarbursts can be reasonably well-reproduced using a simple quenching scenario. Specifically, the phase space is best reproduced if satellite quenching occurs on a rapid timescale (0.1 < tau_{Q} < 0.5 Gyr) after galaxies make their first passage of R ~ 0.5R_{200}, a process that takes a total time of ~ 1 Gyr after first infall. We compare this quenching timescale to the timescale implied by the stellar populations of the poststarburst galaxies and find that the poststarburst spectra are well-fit by a rapid quenching (tau_{Q} = 0.4^{+0.3}_{-0.4} Gyr) of a typical star-forming galaxy. The similarity between the quenching timescales derived from these independent indicators is a strong consistency check of the quenching model. Given that the model implies satellite quenching is rapid, and occurs well within R_{200}, this would suggest that ram-pressure stripping of either the hot or cold gas component of galaxies are the most plausible candidates for the physical mechanism. The high cold gas consumption rates at z ~ 1 make it difficult to determine if hot or cold gas stripping is dominant; however, measurements of the redshift evolution of the satellite quenching timescale and location may be capable of distinguishing between the two.Comment: 10 pages, 4 figures, submitted to the Ap

Magnitude effects for experienced rewards at short delays in the escalating interest task

A first-person shooter video game was adapted for the study of choice between smaller sooner and larger later rewards. Participants chose when to fire a weapon that increased in damage potential over a short interval. When the delay to maximum damage was shorter (5 – 8 s), people showed greater sensitivity to the consequences of their choices than when the delay was longer (17 – 20 s). Participants also evidenced a magnitude effect by waiting proportionally longer when the damage magnitudes were doubled for all rewards. The experiment replicated the standard magnitude effect with this new video game preparation over time scales similar to those typically used in nonhuman animal studies and without complications due to satiation or cost

Genomic and physiological variability within Group II (non-proteolytic) Clostridium botulinum

BACKGROUND: Clostridium botulinum is a group of four physiologically and phylogenetically distinct bacteria that produce botulinum neurotoxin. While studies have characterised variability between strains of Group I (proteolytic) C. botulinum, the genetic and physiological variability and relationships between strains within Group II (non-proteolytic) C. botulinum are not well understood. In this study the genome of Group II strain C. botulinum Eklund 17B (NRP) was sequenced and used to construct a whole genome DNA microarray. This was used in a comparative genomic indexing study to compare the relatedness of 43 strains of Group II C. botulinum (14 type B, 24 type E and 5 type F). These results were compared with characteristics determined from physiological tests. RESULTS: Whole genome indexing showed that strains of Group II C. botulinum isolated from a wide variety of environments over more than 75 years clustered together indicating the genetic background of Group II C. botulinum is stable. Further analysis showed that strains forming type B or type F toxin are closely related with only toxin cluster genes targets being unique to either type. Strains producing type E toxin formed a separate subset. Carbohydrate fermentation tests supported the observation that type B and F strains form a separate subset to type E strains. All the type F strains and most of type B strains produced acid from amylopectin, amylose and glycogen whereas type E strains did not. However, these two subsets did not differ strongly in minimum growth temperature or maximum NaCl concentration for growth. No relationship was found between tellurite resistance and toxin type despite all the tested type B and type F strains carrying tehB, while the sequence was absent or diverged in all type E strains. CONCLUSIONS: Although Group II C. botulinum form a tight genetic group, genomic and physiological analysis indicates there are two distinct subsets within this group. All type B strains and type F strains are in one subset and all type E strains in the other