Biological mediators and periodontal regeneration: a review of enamel matrix proteins at the cellular and molecular levels

BACKGROUND: Despite a large body of clinical and histological data demonstrating beneficial effects of enamel matrix proteins (EMPs) for regenerative periodontal therapy, it is less clear how the available biological data can explain the mechanisms underlying the supportive effects of EMPs. OBJECTIVE: To analyse all available biological data of EMPs at the cellular and molecular levels that are relevant in the context of periodontal wound healing and tissue formation. METHODS: A stringent systematic approach was applied using the key words "enamel matrix proteins" OR "enamel matrix derivative" OR "emdogain" OR "amelogenin". The literature search was performed separately for epithelial cells, gingival fibroblasts, periodontal ligament cells, cementoblasts, osteogenic/chondrogenic/bone marrow cells, wound healing, and bacteria. RESULTS: A total of 103 papers met the inclusion criteria. EMPs affect many different cell types. Overall, the available data show that EMPs have effects on: (1) cell attachment, spreading, and chemotaxis; (2) cell proliferation and survival; (3) expression of transcription factors; (4) expression of growth factors, cytokines, extracellular matrix constituents, and other macromolecules; and (5) expression of molecules involved in the regulation of bone remodelling. CONCLUSION: All together, the data analysis provides strong evidence for EMPs to support wound healing and new periodontal tissue formation.

Biovolatilisation: a poorly studied pathway of the arsenic biogeochemical cycle

It has been known for over a hundred years that microorganisms can produce volatile arsenic (As) species, termed “arsines”. However, this topic has received relatively little attention compared to As behaviour in soils and biotransformation through the trophic level in the marine and terrestrial environment. We believe this is due to long-standing misconceptions regarding volatile As stability and transport as well as an absence, until recently, of appropriate sampling methods. First and foremost, an attempt is made to unify arsines' designations, notations and formulas, taking into account all the different terms used in the literature. Then, the stability of As volatile species is discussed and new analytical developments are explored. Further, the special cases of diffuse low-level emissions (e.g. soil and sediment biovolatilisation), and point sources with high-level emissions (geothermal environments, landfills, and natural gas) are comprehensively reviewed. In each case, future possible areas of research and unknown mechanisms are identified and their importance towards the global As biogeochemical cycle is explored. This review gathers new information regarding mechanisms, stability, transport and sampling of the very elusive arsines and shows that more research should be conducted on this important process.

General practitioner involvement in follow-up of childhood cancer survivors: a systematic review

BACKGROUND An increasing number of childhood cancer survivors need long-term follow-up care. Different models address this problem, including that of follow-up by general practitioners (GP). We describe models that involve GPs in follow-up for childhood cancer survivors, their advantages and disadvantages, clinics that employ these models, and the elements essential to high-quality, GP-led follow-up care. PROCEDURE We searched four databases (PubMed [including Medline], Embase, Cochrane, and CINAHL) without language restrictions. RESULTS We found 26 publications, which explicitly mentioned GP-led follow-up. Two models were commonly described: GP-only, and shared care between GP and pediatric oncology or late effects clinic. The shared care model appears to have advantages over GP-only follow-up. We found four clinics using models of GP-led follow-up, described in five papers. We identified well-organized transition, treatment summary, survivorship care plan, education of GPs and guidelines as necessary components of successful follow-up. CONCLUSION Scarcity of literature necessitated a review rather than a meta-analysis. More research on the outcomes of GP-led care is necessary to confirm the model for follow-up of childhood cancer survivors in the long term. However, with the necessary elements in place, the model of GP-led follow-up, and shared care in particular, holds promise.

Family Stability and Childhood Behavioral Outcomes: A Critical Review of the Literature

As the definition of what is considered a family changes in our society, the family unit itself continues to undergo changes. These changes can sometimes lead to decreased stability within the family unit. One of the greatest challenges facing those researching this phenomenon is the lack of consistency within the existing body of research surrounding what familial instability actually is (the definition). This critical review of the literature examines the current body of literature in order to identify what is known about family stability and its impact on adolescent behavior, as well as what gaps currently exist. This review focuses on definitions of family stability, current factors surrounding the stability of the family unit, and addresses the implications that the current body of literature presents.

The influence of sampling design on tree-ring-based quantification of forest growth

Tree-rings offer one of the few possibilities to empirically quantify and reconstruct forest growth dynamics over years to millennia. Contemporaneously with the growing scientific community employing tree-ring parameters, recent research has suggested that commonly applied sampling designs (i.e. how and which trees are selected for dendrochronological sampling) may introduce considerable biases in quantifications of forest responses to environmental change. To date, a systematic assessment of the consequences of sampling design on dendroecological and-climatological conclusions has not yet been performed. Here, we investigate potential biases by sampling a large population of trees and replicating diverse sampling designs. This is achieved by retroactively subsetting the population and specifically testing for biases emerging for climate reconstruction, growth response to climate variability, long-term growth trends, and quantification of forest productivity. We find that commonly applied sampling designs can impart systematic biases of varying magnitude to any type of tree-ring-based investigations, independent of the total number of samples considered. Quantifications of forest growth and productivity are particularly susceptible to biases, whereas growth responses to short-term climate variability are less affected by the choice of sampling design. The world's most frequently applied sampling design, focusing on dominant trees only, can bias absolute growth rates by up to 459% and trends in excess of 200%. Our findings challenge paradigms, where a subset of samples is typically considered to be representative for the entire population. The only two sampling strategies meeting the requirements for all types of investigations are the (i) sampling of all individuals within a fixed area; and (ii) fully randomized selection of trees. This result advertises the consistent implementation of a widely applicable sampling design to simultaneously reduce uncertainties in tree-ring-based quantifications of forest growth and increase the comparability of datasets beyond individual studies, investigators, laboratories, and geographical boundaries.

The structural substrate of brain function: analysis of brain structural networks based on diffusion-weighted imaging

The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.

Technical Efficiency of State Owned Enterprises in China (1980-1989): An Assessment of the Economic Reforms

This paper uses Data Envelopment Analysis to examine changes in levels of technical efficiency over time in China's state-owned enterprises (SOEs) during 1980-1989. Our paper adds to the growing body of literature in this area by obtaining measures of technical efficiency of individual SOEs over years and by identifying how different aspects of the reforms have affected efficiency. We estimate a Tobit regression model, using the technical efficiency score as the dependent variable and a set of reform variables and firm attributes as regressors. We find that specific aspects of the reforms were very effective in improving technical efficiency.

Understanding Impediments and Enablers to Physical Activity among African American Adults: A Systematic Review of Qualitative Studies

Objective: To systematically assess and summarize impediments and facilitating factors impacting physical activity participation among African American Adults. ^ Method: A systematic search of the literature was conducted, which included electronic databases, as well as reference list of relevant papers. Only qualitative studies which measured race and ethnicity and had African American as adult participants were included. The main themes and categories from the qualitative studies pertaining to impediments and facilitators to physical activity were identified and summarized, through descriptive meta-synthesis. ^ Result: Twenty nine qualitative studies were included. Twenty-one of the studies only focused on adult African American women, and the barriers and facilitators to physical activity as perceived by them. The biggest individual enabler towards physical activity was the positive health benefits associated with regular physical activity. Social support and easy access to parks and facilities were also identified as enablers. Barriers toward physical activity were lack of time, lack of motivation, long work hours, and physical disabilities. ^ Conclusions: The findings of this review study should be useful to those planning an intervention in African American communities. There is also a need for qualitative studies conducted only among African American men, to better understand their perspective on the facilitators and barriers to physical activity.^

Detection histories for eight species of Amazona parrots in Venezuela during the NeoMaps bird surveys in 2010

Documenting changes in distribution is necessary for understanding species' response to environmental changes, but data on species distributions are heterogeneous in accuracy and resolution. Combining different data sources and methodological approaches can fill gaps in knowledge about the dynamic processes driving changes in species-rich, but data-poor regions. We combined recent bird survey data from the Neotropical Biodiversity Mapping Initiative (NeoMaps) with historical distribution records to estimate potential changes in the distribution of eight species of Amazon parrots in Venezuela. Using environmental covariates and presence-only data from museum collections and the literature, we first used maximum likelihood to fit a species distribution model (SDM) estimating a historical maximum probability of occurrence for each species. We then used recent, NeoMaps survey data to build single-season occupancy models (OM) with the same environmental covariates, as well as with time- and effort-dependent detectability, resulting in estimates of the current probability of occurrence. We finally calculated the disagreement between predictions as a matrix of probability of change in the state of occurrence. Our results suggested negative changes for the only restricted, threatened species, Amazona barbadensis, which has been independently confirmed with field studies. Two of the three remaining widespread species that were detected, Amazona amazonica, Amazona ochrocephala, also had a high probability of negative changes in northern Venezuela, but results were not conclusive for Amazona farinosa. The four remaining species were undetected in recent field surveys; three of these were most probably absent from the survey locations (Amazona autumnalis, Amazona mercenaria and Amazona festiva), while a fourth (Amazona dufresniana) requires more intensive targeted sampling to estimate its current status. Our approach is unique in taking full advantage of available, but limited data, and in detecting a high probability of change even for rare and patchily-distributed species. However, it is presently limited to species meeting the strong assumptions required for maximum-likelihood estimation with presence-only data, including very high detectability and representative sampling of its historical distribution.

Sampling sites, sampled birds and plants of young larch plantations in Tokachi district, eastern Hokkaido, northern Japan, 2011

Models and data used to describe species-area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species-area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species-area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density-area relationships and occurrence probability-area relationships can alter the form of species-area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.

Video analysis based vehicle detection and tracking using an MCMC sampling framework

This article presents a probabilistic method for vehicle detection and tracking through the analysis of monocular images obtained from a vehicle-mounted camera. The method is designed to address the main shortcomings of traditional particle filtering approaches, namely Bayesian methods based on importance sampling, for use in traffic environments. These methods do not scale well when the dimensionality of the feature space grows, which creates significant limitations when tracking multiple objects. Alternatively, the proposed method is based on a Markov chain Monte Carlo (MCMC) approach, which allows efficient sampling of the feature space. The method involves important contributions in both the motion and the observation models of the tracker. Indeed, as opposed to particle filter-based tracking methods in the literature, which typically resort to observation models based on appearance or template matching, in this study a likelihood model that combines appearance analysis with information from motion parallax is introduced. Regarding the motion model, a new interaction treatment is defined based on Markov random fields (MRF) that allows for the handling of possible inter-dependencies in vehicle trajectories. As for vehicle detection, the method relies on a supervised classification stage using support vector machines (SVM). The contribution in this field is twofold. First, a new descriptor based on the analysis of gradient orientations in concentric rectangles is dened. This descriptor involves a much smaller feature space compared to traditional descriptors, which are too costly for real-time applications. Second, a new vehicle image database is generated to train the SVM and made public. The proposed vehicle detection and tracking method is proven to outperform existing methods and to successfully handle challenging situations in the test sequences.

Diffusion of Eco-innovations: exploring the literature

In recent years, the importance of the management of eco-innovations has been growing, more in practice than in academia. However, although in the literature there are already some evidences focussed on management of eco-innovations, there is no comprehensive review on the knowledge base of diffusion of eco-innovations. This paper provides a current overview of the existing body of literature, identifying the most active scholars and relevant publications in this field, and deepening in the major disciplines and research streams. Results show that the theory of diffusion of innovations which provided the philosophical underpinnings of how innovations are diffused is not the main knowledge base to explain the diffusion of eco-innovations. Lead market hypothesis, sustainable transitions and the ecological modernization appear as the initial base of the cognitive platform that can contribute to the understanding of diffusion of eco-innovations.