Simple individual-based models effectively represent Afrotropical forest bird movement in complex landscapes

Reliable estimates of dispersal rates between habitat patches (i.e. functional connectivity) are critical for predicting long-term effects of habitat fragmentation on population persistence. Connectivity measures are frequently derived from least cost path or graph-based approaches, despite the fact that these methods make biologically unrealistic assumptions. Individual-based models (IBMs) have been proposed as an alternative as they allow modelling movement behaviour in response to landscape resistance. However, IBMs typically require excessive data to be useful for management. Here, we test the extent to which an IBM requiring only an uncomplicated set of movement rules [the 'stochastic movement simulator' (SMS)] can predict animal movement behaviour in real-world landscapes. Movement behaviour of two forest birds, the Cabanis's greenbul Phyllastrephus cabanisi (a forest specialist) and the white-starred robin Pogonocichla stellata (a habitat generalist), across an Afrotropical matrix was simulated using SMS. Predictions from SMS were evaluated against a set of detailed movement paths collected by radiotracking homing individuals. SMS was capable of generating credible predictions of bird movement, although simulations were sensitive to the cost values and the movement rules specified. Model performance was generally highest when movement was simulated across low-contrasting cost surfaces and when virtual individuals were assigned low directional persistence and limited perceptual range. SMS better predicted movements of the habitat specialist than the habitat generalist, which highlights its potential to model functional connectivity when species movements are affected by the matrix. Synthesis and applications. Modelling the dispersal process with greater biological realism is likely to be critical for improving our predictive capability regarding functional connectivity and population persistence. For more realistic models to be widely applied, it is vital that their application is not overly complicated or data demanding. Here, we show that given relatively basic understanding of a species' dispersal ecology, the stochastic movement simulator represents a promising tool for estimating connectivity, which can help improve the design of functional ecological networks aimed at successful species conservation

Evaluating Knowledge Anchors in Data Graphs against Basic Level Objects

The growing number of available data graphs in the form of RDF Linked Da-ta enables the development of semantic exploration applications in many domains. Often, the users are not domain experts and are therefore unaware of the complex knowledge structures represented in the data graphs they in-teract with. This hinders users’ experience and effectiveness. Our research concerns intelligent support to facilitate the exploration of data graphs by us-ers who are not domain experts. We propose a new navigation support ap-proach underpinned by the subsumption theory of meaningful learning, which postulates that new concepts are grasped by starting from familiar concepts which serve as knowledge anchors from where links to new knowledge are made. Our earlier work has developed several metrics and the corresponding algorithms for identifying knowledge anchors in data graphs. In this paper, we assess the performance of these algorithms by considering the user perspective and application context. The paper address the challenge of aligning basic level objects that represent familiar concepts in human cog-nitive structures with automatically derived knowledge anchors in data graphs. We present a systematic approach that adapts experimental methods from Cognitive Science to derive basic level objects underpinned by a data graph. This is used to evaluate knowledge anchors in data graphs in two ap-plication domains - semantic browsing (Music) and semantic search (Ca-reers). The evaluation validates the algorithms, which enables their adoption over different domains and application contexts

Promoter analysis by saturation mutagenesis

Gene expression and regulation are mediated by DNA sequences, in most instances, directly upstream to the coding sequences by recruiting transcription factors, regulators, and a RNA polymerase in a spatially defined fashion. Few nucleotides within a promoter make contact with the bound proteins. The minimal set of nucleotides that can recruit a protein factor is called a cis-acting element. This article addresses a powerful mutagenesis strategy that can be employed to define cis-acting elements at a molecular level. Technical details including primer design, saturation mutagenesis, construction of promoter libraries, phenotypic analysis, data analysis, and interpretation are discussed

Performance-based sub-selection of CMIP6 models for impact assessments in Europe

This is the final version. Available on open access from Copernicus Publications via the DOI in this recordCode and data availability: The code used to apply the ClimWIP method is publicly available via the ESMValTool (https://docs.esmvaltool.org/en/latest/recipes/recipe_climwip.html, ESMValTool, 2022). The data used in this study are available through the ESGF data portal at https://esgf-node.llnl.gov/projects/cmip6/ (CMIP, 2022). Further assessment plots for the models used in this paper are available on GitHub at https://github.com/tepmo42/cmip6_european_assessment (https://doi.org/10.5281/zenodo.782884, Palmer et al., 2023), as is a spreadsheet of all available assessments (for Europe) carried out for CMIP6 models to date. The RAPID-MOC monitoring project is funded by the Natural Environment Research Council and data (Frajka-Williams et al., 2021). E-OBS data (v.14.0, Cornes et al., 2018) can be found at https://www.ecad.eu/download/ensembles/download.php, in Cornes et al. (2018). The HadISST dataset (Rayner et al., 2003) is publicly available for download at https://www.metoffice.gov.uk/hadobs/hadisst/data/download.html. The ERA5 data (Hersbach et al., 2020) are available for download through the Copernicus Climate Change Service (2017) at https://cds.climate.copernicus.eu/cdsapp#!/home.We have created a performance-based assessment of CMIP6 models for Europe that can be used to inform the sub-selection of models for this region. Our assessment covers criteria indicative of the ability of individual models to capture a range of large-scale processes that are important for the representation of present-day European climate. We use this study to provide examples of how this performance-based assessment may be applied to a multi-model ensemble of CMIP6 models to (a) filter the ensemble for performance against these climatological and processed-based criteria and (b) create a smaller subset of models based on performance that also maintains model diversity and the filtered projection range as far as possible. Filtering by excluding the least-realistic models leads to higher-sensitivity models remaining in the ensemble as an emergent consequence of the assessment. This results in both the 25th percentile and the median of the projected temperature range being shifted towards greater warming for the filtered set of models. We also weight the unfiltered ensemble against global trends. In contrast, this shifts the distribution towards less warming. This highlights a tension for regional model selection in terms of selection based on regional climate processes versus the global mean warming trend.European Union Horizon 2020Deutsche Forschungsgemeinschaft (DFG)European Research Council (ERC

Symptom and Quality of Life Improvement in LUX-Lung 8, an Open-Label Phase III Study of Second-Line Afatinib Versus Erlotinib in Patients With Advanced Squamous Cell Carcinoma of the Lung After First-Line Platinum-Based Chemotherapy

INTRODUCTION: In the phase III LUX-Lung 8 trial, afatinib significantly improved progression-free survival (PFS) and overall survival (OS) versus erlotinib in patients with squamous cell carcinoma (SCC) of the lung progressing during or after platinum-based chemotherapy. Patient-reported outcomes (PROs) and health-related quality of life (QoL) in these patients are presented. PATIENTS AND METHODS: Patients (n = 795) were randomized 1:1 to oral afatinib (40 mg/d) or erlotinib (150 mg/d). PROs were collected (baseline, every 28 days until progression, 28 days after discontinuation) using the European Organization for Research and Treatment of Cancer QoL questionnaire and lung cancer-specific module. The percentage of patients improved during therapy, time to deterioration (TTD), and changes over time were analyzed for prespecified lung cancer-related symptoms and global health status (GHS)/QoL. RESULTS: Questionnaire compliance was 77.3% to 99.0% and 68.7% to 99.0% with afatinib and erlotinib, respectively. Significantly more patients who received afatinib versus erlotinib experienced improved scores for GHS/QoL (36% vs. 28%; P = .041) and cough (43% vs. 35%; P = .029). Afatinib significantly delayed TTD in dyspnea (P = .008) versus erlotinib, but not cough (P = .256) or pain (P = .869). Changes in mean scores favored afatinib for cough (P = .0022), dyspnea (P = .0007), pain (P = .0224), GHS/QoL (P = .0320), and all functional scales. Differences in adverse events between afatinib and erlotinib, specifically diarrhea, did not affect GHS/QoL. CONCLUSION: In patients with SCC of the lung, second-line afatinib was associated with improved prespecified disease-related symptoms and GHS/QoL versus erlotinib, complementing PFS and OS benefits with afatinib

Clinical course, costs and predictive factors for response to treatment in carpal tunnel syndrome: The PALMS study protocol

Background Carpal tunnel syndrome (CTS) is the most common neuropathy of the upper limb and a significant contributor to hand functional impairment and disability. Effective treatment options include conservative and surgical interventions, however it is not possible at present to predict the outcome of treatment. The primary aim of this study is to identify which baseline clinical factors predict a good outcome from conservative treatment (by injection) or surgery in patients diagnosed with carpal tunnel syndrome. Secondary aims are to describe the clinical course and progression of CTS, and to describe and predict the UK cost of CTS to the individual, National Health Service (NHS) and society over a two year period. Methods/Design In this prospective observational cohort study patients presenting with clinical signs and symptoms typical of CTS and in whom the diagnosis is confirmed by nerve conduction studies are invited to participate. Data on putative predictive factors are collected at baseline and follow-up through patient questionnaires and include standardised measures of symptom severity, hand function, psychological and physical health, comorbidity and quality of life. Resource use and cost over the 2 year period such as prescribed medications, NHS and private healthcare contacts are also collected through patient self-report at 6, 12, 18 and 24 months. The primary outcome used to classify treatment success or failures will be a 5-point global assessment of change. Secondary outcomes include changes in clinical symptoms, functioning, psychological health, quality of life and resource use. A multivariable model of factors which predict outcome and cost will be developed. Discussion This prospective cohort study will provide important data on the clinical course and UK costs of CTS over a two-year period and begin to identify predictive factors for treatment success from conservative and surgical interventions

Inspiratory muscle warm-up does not improve cycling time-trial performance

Purpose: This study examined the effects of an active cycling warm-up, with and without the addition of an inspiratory muscle warm-up (IMW), on 10-km cycling time-trial performance

A critical review of PASBio's argument structures for biomedical verbs

BACKGROUND: Propositional representations of biomedical knowledge are a critical component of most aspects of semantic mining in biomedicine. However, the proper set of propositions has yet to be determined. Recently, the PASBio project proposed a set of propositions and argument structures for biomedical verbs. This initial set of representations presents an opportunity for evaluating the suitability of predicate-argument structures as a scheme for representing verbal semantics in the biomedical domain. Here, we quantitatively evaluate several dimensions of the initial PASBio propositional structure repository. RESULTS: We propose a number of metrics and heuristics related to arity, role labelling, argument realization, and corpus coverage for evaluating large-scale predicate-argument structure proposals. We evaluate the metrics and heuristics by applying them to PASBio 1.0. CONCLUSION: PASBio demonstrates the suitability of predicate-argument structures for representing aspects of the semantics of biomedical verbs. Metrics related to theta-criterion violations and to the distribution of arguments are able to detect flaws in semantic representations, given a set of predicate-argument structures and a relatively small corpus annotated with them

Risk factors for methamphetamine use in youth: a systematic review

<p>Abstract</p> <p>Background</p> <p>Methamphetamine (MA) is a potent stimulant that is readily available. Its effects are similar to cocaine, but the drug has a profile associated with increased acute and chronic toxicities. The objective of this systematic review was to identify and synthesize literature on risk factors that are associated with MA use among youth.</p> <p>More than 40 electronic databases, websites, and key journals/meeting abstracts were searched. We included studies that compared children and adolescents (≤ 18 years) who used MA to those who did not. One reviewer extracted the data and a second checked for completeness and accuracy. For discrete risk factors, odds ratios (OR) were calculated and when appropriate, a pooled OR with 95% confidence intervals (95% CI) was calculated. For continuous risk factors, mean difference and 95% CI were calculated and when appropriate, a weighted mean difference (WMD) and 95% CI was calculated. Results were presented separately by comparison group: low-risk (no previous drug abuse) and high-risk children (reported previous drug abuse or were recruited from a juvenile detention center).</p> <p>Results</p> <p>Twelve studies were included. Among low-risk youth, factors associated with MA use were: history of heroin/opiate use (OR = 29.3; 95% CI: 9.8–87.8), family history of drug use (OR = 4.7; 95% CI: 2.8–7.9), risky sexual behavior (OR = 2.79; 95% CI: 2.25, 3.46) and some psychiatric disorders. History of alcohol use and smoking were also significantly associated with MA use. Among high-risk youth, factors associated with MA use were: family history of crime (OR = 2.0; 95% CI: 1.2–3.3), family history of drug use (OR = 4.7; 95% CI: 2.8–7.9), family history of alcohol abuse (OR = 3.2; 95% CI: 1.8–5.6), and psychiatric treatment (OR = 6.8; 95% CI: 3.6–12.9). Female sex was also significantly associated with MA use.</p> <p>Conclusion</p> <p>Among low-risk youth, a history of engaging in a variety of risky behaviors was significantly associated with MA use. A history of a psychiatric disorder was a risk factor for MA for both low- and high-risk youth. Family environment was also associated with MA use. Many of the included studies were cross-sectional making it difficult to assess causation. Future research should utilize prospective study designs so that temporal relationships between risk factors and MA use can be established.</p