Apparent cooperative effects in acetylcholine receptor-mediated ion flux electroplax membrane preparations.

The kinetics of acetylcholine receptor-mediated flux of ²²sodium ions from microsacs has been measured in the presence of activators (carbamylcholine and decamethonium) and an inhibitor (d-tubocurarine) of neural transmission. The dependence of the first-order rate constant, k_obs, for ²²sodium ion efflux on either decamethonium or carbamylcholine concentration does not exhibit cooperativity. The apparent cooperativity observed by Kasai and Changeux in dose-response curves for ²²sodium flux from the same preparation is adequately accounted for by the contribution which efflux from non-excitable microsacs, the main component of the preparation, makes to the measurements. d-Tubocurarine was found to be a non-competitive inhibitor of decamethonium-activated ²²sodium efflux. The results of the kinetic measurements are in agreement with equilibrium measurements of the interaction of decamethonium with the same microsac preparation, i.e. adherence to a classic Langmuir binding isotherm and separate binding sites for activators and inhibitors of neural activity. The results indicate a direct relationship between ligand binding and receptor-mediated ion flux. How these two processes contribute to electrophysiological measurements is not apparent.     

Diet of a rare herbivore based on DNA metabarcoding of feces: Selection,seasonality, and survival

In herbivores, survival and reproduction are influenced by quality and quantity of forage, and hence, diet and foraging behavior are the foundation of an herbivore's life history strategy. Given the importance of diet to most herbivores, it is imperative that we know the species of plants they prefer, especially for herbivorous species that are at risk for extinction. However, it is often difficult to identify the diet of small herbivores because: (a) They are difficult to observe, (b) collecting stomach contents requires sacrificing animals, and (c) microhistology requires accurately identifying taxa from partially digested plant fragments and likely overemphasizes less‐digestible taxa. The northern Idaho ground squirrel (Urocitellus brunneus) is federally threatened in the United States under the Endangered Species Act. We used DNA metabarcoding techniques to identify the diet of 188 squirrels at 11 study sites from fecal samples. We identified 42 families, 126 genera, and 120 species of plants in the squirrel's diet. Our use of three gene regions was beneficial because reliance on only one gene region (e.g., only trnL) would have caused us to miss >30% of the taxa in their diet. Northern Idaho ground squirrel diet differed between spring and summer, frequency of many plants in the diet differed from their frequency within their foraging areas (evidence of selective foraging), and several plant genera in their diet were associated with survival. Our results suggest that while these squirrels are generalists (they consume a wide variety of plant species), they are also selective and do not eat plants relative to availability. Consumption of particular genera such as Perideridia may be associated with higher overwinter survival.     

Unusual nonmarine burrows from the Middle Jurassic of Scotland

The Kilmaluag Formation of the Great Estuarine Group (Middle Jurassic) of Scotland represents deposition of mixed carbonate and clastic sediments in a low‐salinity coastal lagoon to floodplain lake setting. Large, unusual trace fossils occur at two horizons within the formation. One type consists of platelike structures about 50 cm in diameter, which are found on wave‐rippled sandstone. These structures, strikingly similar to burrows produced by modern mudskippers, are assigned to fish that shallowly burrowed into the lagoon‐shore sediment.

The second type of burrows, found in brecciated, dolomitic limestones, are pipelike, about 4 to 7 cm in diameter and as much as 50 cm deep. One example has a chamber at the base of the pipe. Although most features of these structures appear similar to modern lungfish burrows, the chamber is most similar to structures produced by modern crayfish. The animal probably burrowed into the moist, mudflat sediment to escape desiccation during seasonal aridity.     

Evaluating atmospheric CO2 inversions at multiple scales over a highly inventoried agricultural landscape

An intensive regional research campaign was conducted by the North American Carbon Program (NACP) in 2007 to study the carbon cycle of the highly productive agricultural regions of the Midwestern United States. Forty‐five different associated projects were conducted across five US agencies over the course of nearly a decade involving hundreds of researchers. One of the primary objectives of the intensive campaign was to investigate the ability of atmospheric inversion techniques to use highly calibrated CO₂ mixing ratio data to estimate CO₂ flux over the major croplands of the United States by comparing the results to an inventory of CO₂ fluxes. Statistics from densely monitored crop production, consisting primarily of corn and soybeans, provided the backbone of a well studied bottom‐up inventory flux estimate that was used to evaluate the atmospheric inversion results. Estimates were compared to the inventory from three different inversion systems, representing spatial scales varying from high resolution mesoscale (PSU), to continental (CSU) and global (CarbonTracker), coupled to different transport models and optimization techniques. The inversion‐based mean CO₂‐C sink estimates were generally slightly larger, 8–20% for PSU, 10–20% for CSU, and 21% for CarbonTracker, but statistically indistinguishable, from the inventory estimate of 135 TgC. While the comparisons show that the MCI region‐wide C sink is robust across inversion system and spatial scale, only the continental and mesoscale inversions were able to reproduce the spatial patterns within the region. In general, the results demonstrate that inversions can recover CO₂ fluxes at sub‐regional scales with a relatively high density of CO₂ observations and adequate information on atmospheric transport in the region.     

A Naturalistic Study of the Acceptability and Effectiveness of Internet-Delivered Cognitive Behavioural Therapy for Psychiatric Disorders in Older Australians

Objectives

The current study investigates the acceptability, effectiveness and uptake of internet-delivered cognitive behavioural therapy (iCBT) amongst older individuals (>60 years) seeking psychiatric treatment in general practice.

Methods

The sample consisted of 2413 (mean age 39.5; range 18–83 years) patients prescribed iCBT through This Way Up clinic by their primary care clinician. The intervention consisted of six fully automated, unassisted online lessons specific to four disorders major depression, generalised anxiety disorder, panic disorder or social phobia. Patients were categorised into five age groups (18–29 years, 30–39 years, 40–49 years, 50–59 years, 60 years and above). 225 (9.3%) patients were aged over 60 years. Analyses were conducted across the four disorders to ensure sufficient sample sizes in the 60 years and older age group. Age differences in adherence to the six lesson courses were assessed to demonstrate acceptability. Age-based reductions in psychological distress (Kessler Psychological Distress Scale; K10) and disability (the World Health Organisation Disability Assessment Schedule; WHODAS-II) were compared to demonstrate effectiveness. To evaluate the uptake of iCBT, the age distribution of those commencing iCBT was compared with the prevalence of these disorders in the 2007 Australian National Survey of Mental Health and Well-Being.

Results

Older adults were more likely to complete all six lessons when compared with their younger counterparts. Marginal model analyses indicated that there were significant reductions in the K10 and WHODAS-II from baseline to post-intervention, regardless of age (p<0.001). The measurement occasion by age interactions were not significant, indicating that individuals showed similar reductions in the K10 and WHODAS-II regardless of age. In general, the age distribution of individuals commencing the iCBT courses matched the age distribution of the four diagnoses in the Australian general population, indicating that iCBT successfully captures older individuals who need treatment.

Conclusion

iCBT is effective and acceptable for use in older populations.     

Unsupervised Clustering of Subcellular Protein Expression Patterns in High-Throughput Microscopy Images Reveals Protein Complexes and Functional Relationships between Proteins

Protein subcellular localization has been systematically characterized in budding yeast using fluorescently tagged proteins. Based on the fluorescence microscopy images, subcellular localization of many proteins can be classified automatically using supervised machine learning approaches that have been trained to recognize predefined image classes based on statistical features. Here, we present an unsupervised analysis of protein expression patterns in a set of high-resolution, high-throughput microscope images. Our analysis is based on 7 biologically interpretable features which are evaluated on automatically identified cells, and whose cell-stage dependency is captured by a continuous model for cell growth. We show that it is possible to identify most previously identified localization patterns in a cluster analysis based on these features and that similarities between the inferred expression patterns contain more information about protein function than can be explained by a previous manual categorization of subcellular localization. Furthermore, the inferred cell-stage associated to each fluorescence measurement allows us to visualize large groups of proteins entering the bud at specific stages of bud growth. These correspond to proteins localized to organelles, revealing that the organelles must be entering the bud in a stereotypical order. We also identify and organize a smaller group of proteins that show subtle differences in the way they move around the bud during growth. Our results suggest that biologically interpretable features based on explicit models of cell morphology will yield unprecedented power for pattern discovery in high-resolution, high-throughput microscopy images.