The role of bone anabolic drugs in the management of periodontitis: a scoping review

The aim of this scoping review was to summarise current knowledge about the effects of bone anabolic drugs on periodontitis, in order to identify new therapeutic strategies for preventing disease progression and reducing tooth loss. A technical expert panel (TEP) was established of 11 medical specialists, including periodontists and bone specialists that followed the PRISMA-ScR model to perform the scoping review and considered for eligibility both pre-clinical and clinical studies published in the English language up to September 2020. 716 items were initially found. After duplicate removal and screening of articles for eligibility criteria, 25 articles published between 2001 and 2019 were selected. Only studies concerning teriparatide, strontium ranelate, sclerostin antibodies and DKK1 antibodies met the eligibility criteria. In particular, only for teriparatide were there both clinical studies and experimental studies available, while for other bone anabolic drugs only animal studies were found. Available evidence about the use of bone anabolic drugs in periodontology demonstrates beneficial effects of these agents on biological pathways and histological parameters involved in periodontal tissue regeneration that suggest relevant clinical implications for the management of periodontitis.

A hierarchical point process model for spatial capture-recapture data

Spatial capture-recapture (SCR) is a popular method for estimating the abundance and density of wildlife populations. A standard SCR model consists of two sub-models: one for the activity centers of individuals and the other for the detections of each individual conditional on its activity center. So far, the detection sub-model of most SCR models is designed for sampling situations where fixed trap arrays are used to detect individuals.Non-invasive genetic sampling (NGS) is widely applied in SCR studies. Using NGS methods, one often searches the study area for potential sources of DNA such as hairs and faeces, and records the locations of these samples. To analyse such data with SCR models, investigators usually impose an artificial detector grid and project detections to the nearest detector. However, there is a trade-off between the computational efficiency (fewer detectors) and the spatial accuracy (more detectors) when using this method.Here, we propose a point process model for the detection process of SCR studies using NGS. The model better reflects the spatially continuous detection process and allows all spatial information in the data to be used without approximation error. As in many SCR models, we also use a point process model for the activity centers of individuals. The resulting hierarchical point process model enables estimation of total population size without imputing unobserved individuals via data augmentation, which can be computationally cumbersome. We write custom distributions for those spatial point processes and fit the SCR model in a Bayesian framework using Markov chain Monte Carlo in the R package nimble.Simulations indicate good performance of the proposed model for parameter estimation. We demonstrate the application of the model in a real-life scenario by fitting it to NGS data of female wolverines (Gulo gulo) collected in three counties of Norway during the winter of 2018/19. Our model estimates that the density of female wolverines is 9.53 (95% CI: 8–11) per 10,000km2 in the study area.

Development of Effective Momentum Model for Steam Injection Through Multi-Hole Spargers Using a Condensation Region Approach

The Pressure Suppression Pool (PSP) in a Boiling Water Reactor (BWR) is served as a heat sink to prevent containment over-pressure. The steam can be injected through the multi-hole spargers. The development of thermal stratification where a thermocline with a large temperature gradient appears in the pool can lead to the higher pressure in the dry well compared with completely mixing pool conditions. Prediction of the thermal phenomenon in the pool is necessary for the support of system design and operation. Thus, the Effective Heat Source (EHS) and Effective Momentum Source (EMS) models have been proposed. The models can be applied to CFD code by using (i) source terms in the transport equations or (ii) using respective boundary conditions at the Steam Condensation Region (SCR). Previous validation against PPOOLEX and PANDA tests using the source terms approach faced challenges in momentum distribution. Therefore, a preliminary investigation of using the second method was performed. The encouraging results implied that it is possible to further develop this approach. The goal of this work is to further develop the EHS/EMS models for the steam injection through a multi-hole sparger through the SCR model (i.e approach (ii)) and to validate it against the experimental data obtained from PANDA HP5 tests. Modeling guidelines are proposed. The temperature evolutions and vertical velocity profiles of these tests are compared to the simulation results. The agreement suggests that this model can provide an adequate estimation of the pool behavior.

Sex-specific population dynamics and demography of capercaillie (Tetrao urogallus L.) in a patchy environment

Modeling the population dynamics of patchily distributed species is a challenge, particularly when inference must be based on incomplete and small data sets such as those from most species of conservation concern. Open population spatial capture-recapture (SCR) models are ideally suited to quantify population trends, but have seen only limited use since their introduction.To investigate population trend and sex-specific population dynamics, we applied an open SCR model to a capercaillie (Tetrao urogallus) population in Switzerland living in eight distinct forest patches totalling 22 km2 within a region of 908 km2. The population was surveyed using genetic sampling of scat in 2009, 2012 and 2015. We fit an open SCR model with sex-specific detection and population dynamics parameters while accounting for the patchy distribution of habitat and the uncertainty introduced by observing the population in three years only.Between 2009 and 2015, a total of 143 males, 112 females and 4 individuals of uncertain sex were detected. The annual per capita recruitment rate was estimated at 0.115 (SE 0.0144) for males and 0.127 (0.0168) for females. The estimated annual survival probability for males was 0.758 (0.0241) and 0.707 (0.0356) for females. The population trajectory implied by these survival and recruitment estimates was a decline of 2% per year; however, the sex specificity of the model revealed a decline in the male population only, with no evidence of decline in the female population. Further, the population decline observed in males was explained by the demography of just two of the eight patches.Using a customized open population SCR model, we determined that the endangered capercaillie in our Swiss study area had a stable female population and a declining male population, with the male decline due to population dynamics in a subset of the study area. Our study highlights the flexibility of open population SCR models for assessing population trajectories through time and across space and emphasizes the desirability of estimating sex-stratified population trends especially in species of conservation concern.

Estimation of Ammonia Storage Nonuniformity for Urea-Based Selective Catalytic Reduction Systems

Ammonia storage nonuniformity has a significant impact on the emission reduction performance of urea-based selective catalytic reduction (SCR) systems. In this paper, a unique SCR platform with two catalysts in a parallel configuration was created for investigating the impact of ammonia storage nonuniformity on the emission reduction performance in a simulation environment. The established two-cell SCR platform allows users to independently control the ammonia-to-NOx ratio (ANR) for each catalyst using two independent urea solution injectors. Simulation results over US06 cycle demonstrate that, compared to the case without ammonia storage nonuniformity, the tailpipe NOx and ammonia emissions can be increased by 6.73% and 22.0%, respectively, due to the nonuniform ammonia storage in the case of an ANR nonuniformity index (NUI) at 0.2. Furthermore, an innovative model-based method was proposed for estimating the ammonia coverage ratio nonuniformity (i.e., ammonia storage nonuniformity if storage capacity is known) by utilizing a control-oriented SCR model and the tailpipe NOx and ammonia measurements at the confluence point. Simulation results proved the effectiveness of the proposed method in estimating the ammonia coverage ratio nonuniformity.

Adaptive Sampling for Spatial Capture-Recapture: An efficient sampling scheme for rare or patchily distributed species

Rare species present challenges to data collection, particularly when the species is spatially clustered over large areas, such that the encounter frequency of the organism is low. Sampling where the organism is absent consumes resources, and offers relatively low-quality information which are often difficult to model using standard statistical methods. In adaptive sampling, a probabilistic sampling method is employed first, and additional effort is allocated in the vicinity of sites where some measured index variable - assumed to be proportional to local population size - exceeds an a priori threshold. We applied this principle to the spatial capture-recapture (SCR) analytical framework in a Bayesian hierarchical model incorporating capture-recapture (CR) and index information from unsampled sites to estimate density. We assessed the adaptively sampled SCR model (AS-SCR) by simulating CR data and compared performance with a standard SCR baseline (F-SCR), adaptive SCR discarding index information (AS-SCR–), and standard SCR applied at a simple random sample of sites. Under AS-SCR, we observed minimal bias and comparable variance with respect to parameter estimates provided by the standard F-SCR model and sampling implementation, but with substantially reduced effort and significant cost saving potential. This represents the first application of adaptive sampling to SCR.

Spatial Mark-Resight for Categorically Marked Populations with an Application to Genetic Capture-Recapture

The estimation of animal population density is a fundamental goal in wildlife ecology and management, commonly met using mark recapture or spatial mark recapture (SCR) study designs and statistical methods. Mark-recapture methods require the identification of individuals; however, for many species and sampling methods, particularly noninvasive methods, no individuals or only a subset of individuals are individually identifiable. The unmarked SCR model, theoretically, can estimate the density of unmarked populations; however, it produces biased and imprecise density estimates in many sampling scenarios typically encountered. Spatial mark-resight (SMR) models extend the unmarked SCR model in three ways: 1) by introducing a subset of individuals that are marked and individually identifiable, 2) introducing the possibility of individual-linked telemetry data, and 3) introducing the possibility that the capture-recapture data from the survey used to deploy the marks can be used in a joint model, all improving the reliability of density estimates. The categorical spatial partial identity model (SPIM) improves the reliability of density estimates over unmarked SCR along another dimension, by adding categorical identity covariates that improve the probabilistic association of the latent identity samples. Here, we combine these two models into a “categorical SMR” model to exploit the benefits of both models simultaneously. We demonstrate using simulations that SMR alone can produce biased and imprecise density estimates with sparse data and/or when few individuals are marked. Then, using a fisher (Pekania pennanti) genetic capture-recapture data set, we show how categorical identity covariates, marked individuals, telemetry data, and jointly modeling the capture survey used to deploy marks with the resighting survey all combine to improve inference over the unmarked SCR model. As previously seen in an application of the categorical SPIM to a real-world data set, the fisher data set demonstrates that individual heterogeneity in detection function parameters, especially the spatial scale parameter σ, introduces positive bias into latent identity SCR models (e.g., unmarked SCR, SMR), but the categorical SMR model provides more tools to reduce this positive bias than SMR or the categorical SPIM alone. We introduce the possibility of detection functions that vary by identity category level, which will remove individual heterogeneity in detection function parameters than is explained by categorical covariates, such as individual sex. Finally, we provide efficient SMR algorithms that accommodate all SMR sample types, interspersed marking and sighting periods, and any number of identity covariates using the 2-dimensional individual by trap data in conjunction with precomputed constraint matrices, rather than the 3-dimensional individual by trap by occasion data used in SMR algorithms to date.

Common octopus settled in human-altered Mediterranean coastal waters: from individual home range to population dynamics

A spatially explicit capture-recapture (SCR) model was applied to estimate simultaneously population parameters and individual activity (i.e. home range size) of O. vulgaris, based on experimental mark-recapture data in a human-altered Mediterranean coastal area. Seventy-two octopuses were captured, tagged with subcutaneous PIT-tags and released. Nineteen tagged individuals were recaptured (recapture rate: 26.4%) in the same area over the study period, which spanned over 6 months. Population sizes and densities decreased over the study period, from 337 octopuses (8 ind. ha−1) in September-October to 105 octopuses (2.5 ind. ha−1) in February-March. The highest recruitment probability was estimated to occur at the beginning of the study but it clearly decreased over time, while mortality probability during a fishing period slightly increased. Mean specific growth rate was 0.82 ± 0.11 day−1. Individual home range or activity area ranged from 2.8 ha to 7.3 ha (median home range radius: 121.8 m). Overall, these results suggest that human-altered coastal habitats, which are characterized by abundant shelters, abundant food and absence of predators, can act as settlement and growth areas for juveniles and adults of O. vulgaris. Furthermore, the methodologies applied in this study are recommended as innovative tools to improve management actions of coastal resources.