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Imaging with Ca(2+)-sensitive fluorescent dye has provided a wealth of insight into the dynamics of cellular Ca(2+) signaling. The spatiotemporal evolution of intracellular free Ca(2+) observed in imaging experiments is shaped by binding and unbinding to cytoplasmic Ca(2+) buffers, as well as the fluorescent indicator used for imaging. These factors must be taken into account in the interpretation of Ca(2+) imaging data, and can be exploited to investigate endogenous Ca(2+) buffer properties. Here we extended the use of Ca(2+) fluorometry in the characterization of Ca(2+) binding molecules within cells, building on a method of titration of intracellular Ca(2+) binding sites in situ with measured amounts of Ca(2+) entering through voltage-gated Ca(2+) channels. We developed a systematic procedure for fitting fluorescence data acquired during a series of voltage steps to models with multiple Ca(2+) binding sites. The method was tested on simulated data, and then applied to 2-photon fluorescence imaging data from rat posterior pituitary nerve terminals patch clamp-loaded with the Ca(2+) indicator fluo-8. Focusing on data sets well described by a single endogenous Ca(2+) buffer and dye, this method yielded estimates of the endogenous buffer concentration and Kd, the dye Kd, and the fraction of Ca(2+) inaccessible cellular volume. The in situ Kd of fluo-8 thus obtained was indistinguishable from that measured in vitro. This method of calibrating Ca(2+)-sensitive fluorescent dyes in situ has significant advantages over previous methods. Our analysis of Ca(2+) titration fluorometric data makes more effective use of the experimental data, and provides a rigorous treatment of multivariate errors and multiple Ca(2+) binding species. This method offers a versatile approach to the study of endogenous Ca(2+) binding molecules in their physiological milieu., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

The expansion of Medicaid eligibility to Americans with incomes up to 138 percent of the federal poverty level should greatly increase access to coverage and services for people recently released from jail and, thus, improve health outcomes and reduce recidivism in this population. The population is disproportionately male, minority, and poor; suffers from high rates of mental and substance abuse disorders; and is expected to make up a substantial portion of the Medicaid expansion population. To ensure connections to needed services after release from jail, states could help inmates determine their eligibility and enroll in Medicaid; take advantage of federal grants to automate systems that determine eligibility; and include a robust array of behavioral health services in Medicaid benefit packages. In most states, new partnerships between Medicaid and corrections agencies at both the state and local levels will be needed to support these activities.

Objective: The purpose of this study is to further investigate the factor structure and strength of the Bystander Attitude Scale-Revised and Bystander Behavior Scale-Revised (BAS-R and BBS-R)., Participants: First-year students (N = 4,054) at a large public university in the Northeast completed a survey in 2010 as part of a larger longitudinal study of a sexual violence bystander education intervention program on campus., Methods: Exploratory structural equation modeling was used to analyze survey responses to the BAS-R and BBS-R., Results: For BAS-R, the best fit was a 4-factor model: (1) high-risk situations, (2) postassault support for victims, (3) postassault reporting of perpetrators, and (4) proactive opportunities. BBS-R was a 2-factor model: (1) intervention opportunities before, during, or after an assault, and (2) proactive opportunities., Conclusion: The BAS-R and BBS-R provide reliable tools that can be utilized to evaluate sexual violence bystander programs.

Tropical forest structural variation across heterogeneous landscapes may control above-ground carbon dynamics. We tested the hypothesis that canopy structure (leaf area and light availability) - remotely estimated from LiDAR - control variation in above-ground coarse wood production (biomass growth). Using a statistical model, these factors predicted biomass growth across tree size classes in forest near Manaus, Brazil. The same statistical model, with no parameterisation change but driven by different observed canopy structure, predicted the higher productivity of a site 500 km east. Gap fraction and a metric of vegetation vertical extent and evenness also predicted biomass gains and losses for one-hectare plots. Despite significant site differences in canopy structure and carbon dynamics, the relation between biomass growth and light fell on a unifying curve. This supported our hypothesis, suggesting that knowledge of canopy structure can explain variation in biomass growth over tropical landscapes and improve understanding of ecosystem function., (© 2012 Blackwell Publishing Ltd/CNRS.)

Most theories of forest biodiversity focus on the role of seed dispersal and seedling establishment in forest regeneration. In many ecosystems, however, sprouting by damaged stems determines which species occupies a site. Damaged trees can quickly recover from disturbance and out-compete seedlings. Links among species' traits, environmental conditions and sprouting could offer insight into species' resilience to changes in climate, land use, and disturbance. Using data for 25 Neotropical tree species at two sites with contrasting rainfall and soil, we tested hypotheses on how four functional traits (seed mass, leaf mass per area, wood density and nitrogen fixation) influence species' sprouting responses to disturbance and how these relationships are mediated by a tree's environmental context. Most species sprouted in response to cutting, and many species' sprouting rates differed significantly between sites. Individual traits showed no direct correlation with sprouting. However, interactions among traits and site variables did affect sprouting rates. Many species showed increased sprouting in the higher-quality site. Most nitrogen-fixing species showed the opposite trend, sprouting more frequently where resources are scarce. This study highlights the use of functional traits as a proxy for life histories, and demonstrates the importance of environmental effects on demography.

Understanding how species and ecosystems respond to climate change has become a major focus of ecology and conservation biology. Modelling approaches provide important tools for making future projections, but current models of the climate-biosphere interface remain overly simplistic, undermining the credibility of projections. We identify five ways in which substantial advances could be made in the next few years: (i) improving the accessibility and efficiency of biodiversity monitoring data, (ii) quantifying the main determinants of the sensitivity of species to climate change, (iii) incorporating community dynamics into projections of biodiversity responses, (iv) accounting for the influence of evolutionary processes on the response of species to climate change, and (v) improving the biophysical rule sets that define functional groupings of species in global models., (Published by Elsevier Ltd.)

Theoretical models indicate that trade-offs between growth and survival strategies of tree species can lead to coexistence across life history stages (ontogeny) and physical conditions experienced by individuals. There exist predicted physiological mechanisms regulating these trade-offs, such as an investment in leaf characters that may increase survival in stressful environments at the expense of investment in bole or root growth. Confirming these mechanisms, however, requires that potential environmental, ontogenetic, and trait influences are analyzed together. Here, we infer growth and mortality of tree species given size, site, and light characteristics from forest inventory data from Wisconsin to test hypotheses about growth-survival trade-offs given species functional trait values under different ontogenetic and environmental states. A series of regression analyses including traits and rates their interactions with environmental and ontogenetic stages supported the relationships between traits and vital rates expected from the expectations from tree physiology. A combined model including interactions between all variables indicated that relationships between demographic rates and functional traits supports growth-survival trade-offs and their differences across species in high-dimensional niche space. The combined model explained 65% of the variation in tree growth and supports a concept of community coexistence similar to Hutchinson's n-dimensional hypervolume and not a low-dimensional niche model or neutral model.

Forests and their soils contain the majority of the earth's terrestrial carbon stocks. Changes in patterns of tree growth can have a huge impact on atmospheric cycles, biogeochemical cycles, climate change, and biodiversity. Recent studies have shown increases in biomass across many forest types. This increase has been attributed to climate change. However, without knowing the disturbance history of a forest, growth could also be caused by normal recovery from unknown disturbances. Using a unique dataset of tree biomass collected over the past 22 years from 55 temperate forest plots with known land-use histories and stand ages ranging from 5 to 250 years, we found that recent biomass accumulation greatly exceeded the expected growth caused by natural recovery. We have also collected over 100 years of local weather measurements and 17 years of on-site atmospheric CO(2) measurements that show consistent increases in line with globally observed climate-change patterns. Combined, these observations show that changes in temperature and CO(2) that have been observed worldwide can fundamentally alter the rate of critical natural processes, which is predicted by biogeochemical models. Identifying this rate change is important to research on the current state of carbon stocks and the fluxes that influence how carbon moves between storage and the atmosphere. These results signal a pressing need to better understand the changes in growth rates in forest systems, which influence current and future states of the atmosphere and biosphere.

Forests are one of Earth's critical biomes. They have been shown to respond strongly to many of the drivers that are predicted to change natural systems over this century, including climate, introduced species, and other anthropogenic influences. Predicting how different tree species might respond to this complex of forces remains a daunting challenge for forest ecologists. Yet shifts in species composition and abundance can radically influence hydrological and atmospheric systems, plant and animal ranges, and human populations, making this challenge an important one to address. Forest ecologists have gathered a great deal of data over the past decades and are now using novel quantitative and computational tools to translate those data into predictions about the fate of forests. Here, after a brief review of the threats to forests over the next century, one of the more promising approaches to making ecological predictions is described: using hierarchical Bayesian methods to model forest demography and simulating future forests from those models. This approach captures complex processes, such as seed dispersal and mortality, and incorporates uncertainty due to unknown mechanisms, data problems, and parameter uncertainty. After describing the approach, an example by simulating drought for a southeastern forest is offered. Finally, there is a discussion of how this approach and others need to be cast within a framework of prediction that strives to answer the important questions posed to environmental scientists, but does so with a respect for the challenges inherent in predicting the future of a complex biological system.

A fundamental challenge to understanding patterns in ecological systems lies in employing methods that can analyse, test and draw inference from measured associations between variables across scales. Hierarchical linear models (HLM) use advanced estimation algorithms to measure regression relationships and variance-covariance parameters in hierarchically structured data. Although hierarchical models have occasionally been used in the analysis of ecological data, their full potential to describe scales of association, diagnose variance explained, and to partition uncertainty has not been employed. In this paper we argue that the use of the HLM framework can enable significantly improved inference about ecological processes across levels of organization. After briefly describing the principals behind HLM, we give two examples that demonstrate a protocol for building hierarchical models and answering questions about the relationships between variables at multiple scales. The first example employs maximum likelihood methods to construct a two-level linear model predicting herbivore damage to a perennial plant at the individual- and patch-scale; the second example uses Bayesian estimation techniques to develop a three-level logistic model of plant flowering probability across individual plants, microsites and populations. HLM model development and diagnostics illustrate the importance of incorporating scale when modelling associations in ecological systems and offer a sophisticated yet accessible method for studies of populations, communities and ecosystems. We suggest that a greater coupling of hierarchical study designs and hierarchical analysis will yield significant insights on how ecological processes operate across scales.

Background: There are minimal data on radiation doses to infants and children undergoing a modified barium swallow (MBS) study., Objective: To document screening times, dose area product (DAP) and effective doses to children undergoing MBS and to determine factors associated with increased screening times and effective dose., Materials and Methods: Fluoroscopic data (screening time, DAP, kVp) for 90 consecutive MBS studies using pulse fluoroscopy were prospectively recorded; effective dose was calculated and data were analyzed for effects of behavior, number of swallow presentations, swallowing dysfunction and medical problems., Results: Mean effective dose for the entire group was 0.0826 +/- 0.0544 mSv, screening time 2.48 +/- 0.81 min, and DAP 28.79 +/- 41.72 cGy cm2. Significant differences were found across three age groups (1.0-3.0 and >3.0 years) for effective dose (mean 0.1188, 0.0651 and 0.0529 mSv, respectively; P < 0.001), but not for screening time or DAP. Effective dose was correlated with screening time (P = 0.007), DAP (P < 0.001), number of swallow presentations (P = 0.007), lower age (P = 0.017), female gender (P = 0.004), and height (P < 0.001). Screening time was correlated with total number of swallow presentations (P < 0.001) and DAP (P < 0.001)., Conclusion: Screening times, DAP, effective dose, and child and procedural factors associated with higher effective doses are presented for children undergoing MBS studies.

The focus of political and public attention on health care costs has created pressures on hospitals to devise effective methods to decrease costs and still maintain excellent medical care. After identifying four medical specialty services in a unit of a tertiary-care hospital where lengths of stay were excessive, even when the average severity of the discharged patients' illnesses in these services was considered, the authors developed two educational interventions to decrease lengths of stay. First, individual meetings were held with each of the attending physicians from three of the four specialty services, and the data on lengths of stay on that particular service were discussed. The fourth service was used as a control. Second, a continuing education meeting was held with attending physicians on all of the specialty services admitting patients to the unit. The data on lengths of stay for all services were discussed. The lengths of stay subsequently decreased significantly in the three targeted specialty services without any measurable change in the quality of care. This improved efficiency persisted for the 16 months after the intervention. Significant changes in length of stay were not observed in the control service or in any of the other specialty services in which the attending physicians experienced only the continuing education meeting.

A method was developed and tested to analyze the efficiency of medical care using each patient's length of hospital stay (LOS) and comparing these LOS with patients with similar diagnoses, ages, and operative conditions. The method assigns a percentile score to each discharged patient's LOS in comparison with the group of patients in the referent population with the same medical condition. A percentile score calculated in this way removes the effect of case mix and intensity of service from each patient's LOS, and allows the efficiency of medical care to be analyzed. This method was applied to patients who were discharged from a secure unit of a general hospital that serves the tertiary medical needs of patients from the state's correctional system. The LOS for our patients on average corresponded to the 60th percentile for the LOS in other patients with comparable ages and medical conditions. This difference was significantly greater than an expected value of 50.0 (P less than 0.01). The LOS of patients discharged from each specialty service were examined. Two services were identified, in which an increased LOS represented a difference in the practice patterns of physicians in these specialties, in comparison with those of other physicians in this area. An application of the method described in this report should enable hospitals to identify units or services where patients are managed inefficiently and to guide the need for managerial intervention.

In 20 patients with acute pulmonary infections, sputum purulence, sputum volume, and concentration and excretion of cephalexin in the sputum significantly decreased concurrently during therapy. The concentration of cephalexin in the serum remained unchanged. Significant correlations were observed between drug concentrations in sputum and serum and between drug excretion in sputum and concentration in serum. These observations may be explained by decreased integrity of the "blood-bronchus barrier" during inflammation, with diffusion of serum into bronchial mucus, without the necessity of postulating active transport.