bluuebunny/crossref_metadata_2025_split huggingface dataset:
A dynamic multi‐scale occupancy model to estimate temporal dynamics and hierarchical habitat use for nomadic species
Authors: Green Adam W. , Pavlacky David C. , George T. Luke 
Published: February 2019

AbstractDistribution models are increasingly being used to understand how landscape and climatic changes are affecting the processes driving spatial and temporal distributions of plants and animals. However, many modeling efforts ignore the dynamic processes that drive distributional patterns at different scales, which may result in misleading inference about the factors influencing species distributions. Current occupancy models allow estimation of occupancy at different scales and, separately, estimation of immigration and emigration. However, joint estimation of local extinction, colonization, and occupancy within a multi‐scale model is currently unpublished. We extended multi‐scale models to account for the dynamic processes governing species distributions, while concurrently modeling local‐scale availability. We fit the model to data for lark buntings and chestnut‐collared longspurs in the Great Plains, USA, collected under the Integrated Monitoring in Bird Conservation Regions program. We investigate how the amount of grassland and shrubland and annual vegetation conditions affect bird occupancy dynamics and local vegetation structure affects fine‐scale occupancy. Buntings were prevalent and longspurs rare in our study area, but both species were locally prevalent when present. Buntings colonized sites with preferred habitat configurations, longspurs colonized a wider range of landscape conditions, and site persistence of both was higher at sites with greener vegetation. Turnover rates were high for both species, quantifying the nomadic behavior of the species. Our model allows researchers to jointly investigate temporal dynamics of species distributions and hierarchical habitat use. Our results indicate that grassland birds respond to different covariates at landscape and local scales suggesting different conservation goals at each scale. High turnover rates of these species highlight the need to account for the dynamics of nomadic species, and our model can help inform how to coordinate management efforts to provide appropriate habitat configurations at the landscape scale and provide habitat targets for local managers.
Animal movement tools (amt): R package for managing tracking data and conducting habitat selection analyses
Authors: Signer Johannes , Fieberg John , Avgar Tal 
Published: February 2019

AbstractAdvances in tracking technology have led to an exponential increase in animal location data, greatly enhancing our ability to address interesting questions in movement ecology, but also presenting new challenges related to data management and analysis. Step‐selection functions (SSFs) are commonly used to link environmental covariates to animal location data collected at fine temporal resolution. SSFs are estimated by comparing observed steps connecting successive animal locations to random steps, using a likelihood equivalent of a Cox proportional hazards model. By using common statistical distributions to model step length and turn angle distributions, and including habitat‐ and movement‐related covariates (functions of distances between points, angular deviations), it is possible to make inference regarding habitat selection and movement processes or to control one process while investigating the other. The fitted model can also be used to estimate utilization distributions and mechanistic home ranges. Here, we present the R package amt (animal movement tools) that allows users to fit SSFs to data and to simulate space use of animals from fitted models. The amt package also provides tools for managing telemetry data. Using fisher (Pekania pennanti) data as a case study, we illustrate a four‐step approach to the analysis of animal movement data, consisting of data management, exploratory data analysis, fitting of models, and simulating from fitted models.
Estimability of migration survival rates from integrated breeding and winter capture–recapture data
Authors: Rushing Clark S. 
Published: February 2019

AbstractLong‐distance migration is a common phenomenon across the animal kingdom but the scale of annual migratory movements has made it difficult for researchers to estimate survival rates during these periods of the annual cycle. Estimating migration survival is particularly challenging for small‐bodied species that cannot carry satellite tags, a group that includes the vast majority of migratory species. When capture–recapture data are available for linked breeding and non‐breeding populations, estimation of overall migration survival is possible but current methods do not allow separate estimation of spring and autumn survival rates. Recent development of a Bayesian integrated survival model has provided a method to separately estimate the latent spring and autumn survival rates using capture–recapture data, though the accuracy and precision of these estimates has not been formally tested. Here, I used simulated data to explore the estimability of migration survival rates using this model. Under a variety of biologically realistic scenarios, I demonstrate that spring and autumn migration survival can be estimated from the integrated survival model, though estimates are biased toward the overall migration survival probability. The direction and magnitude of this bias are influenced by the relative difference in spring and autumn survival rates as well as the degree of annual variation in these rates. The inclusion of covariates can improve the model's performance, especially when annual variation in migration survival rates is low. Migration survival rates can be estimated from relatively short time series (4–5 years), but bias and precision of estimates are improved when longer time series (10–12 years) are available. The ability to estimate seasonal survival rates of small, migratory organisms opens the door to advancing our understanding of the ecology and conservation of these species. Application of this method will enable researchers to better understand when mortality occurs across the annual cycle and how the migratory periods contribute to population dynamics. Integrating summer and winter capture data requires knowledge of the migratory connectivity of sampled populations and therefore efforts to simultaneously collect both survival and tracking data should be a high priority, especially for species of conservation concern.
Nafion‐modified Carbon Based Sensor for Soil Potassium Detection
Authors: Bhandari Shruti , Singh Urvasini , Kumbhat Sunita 
Published: February 2019

AbstractIn the present investigation, we report a voltammetric sensor based on Nafion modified screen printed carbon ink functionalized with 4‐aminobenzo‐18‐crown‐6 ether for the detection of soil potassium. The potassium is one of the major nutrient elements required by the plants and is critical for the crop productivity. The selective and sensitive assay is based on recording change in current signal of a positively charged redox probe, hexammineruthenium(III)chloride in the absence and presence of K+ ion in solution. The sensing interface is highly stable and reproducible for detection of K+ ion a under a wide range of concentration 1 to 500 ppm. The detection sensitivity over a wide concentration range was achieved by altering the concentration of redox species. Mechanistically, the recognition properties of 4‐aminobenzo‐18‐Crown‐6 covalently bound to the Nafion on carbon surface was found to be selective for potassium ion over sodium, ammonium and calcium ion. Potassium recognition through host‐guest binding of crown ether derivative and proposed simplicity of fabrication protocol makes the systems highly promising for real‐time applications in soil analysis.
Characterizing beach intertidal bar systems using multi‐annual LiDAR data
Authors: Miles Andrew , Ilic Suzana , Whyatt Duncan , James Mike R. 
Published: February 2019

AbstractIntertidal bars are common in mesotidal/macrotidal low‐to‐moderate energy coastal environments and an understanding of their morphodynamics is important from the perspective of both coastal scientists and managers. However, previous studies have typically been limited by considering bar systems two‐dimensionally, or with very limited alongshore resolution. This article presents the first multi‐annual study of intertidal alongshore bars and troughs in a macrotidal environment using airborne LiDAR (light detection and ranging) data to extract three‐dimensional (3D) bar morphology at high resolution.Bar and trough positions are mapped along a 17.5 km stretch of coastline in the northwest of England on the eastern Irish Sea, using eight complete, and one partial, LiDAR surveys spanning 17 years. Typically, 3–4 bars are present, with significant obliquity identified in their orientation. This orientation mirrors the alignment of waves from the dominant south‐westerly direction of wave approach, undergoing refraction as they approach the shoreline. Bars also become narrower and steeper as they migrate onshore, in a pattern reminiscent of wave shoaling. This suggests that the configuration of the bars is being influenced by overlying wave activity. Net onshore migration is present for the entire coastline, though rates vary alongshore, and periods of offshore migration may occur locally, with greatest variability between northern and southern regions of the coastline.This work highlights the need to consider intertidal bar systems as 3D, particularly on coastlines with complex configurations and bathymetry, as localized studies of bar migration can overlook 3D behaviour. Furthermore, the wider potential of LiDAR data in enabling high‐resolution morphodynamic studies is clear, both within the coastal domain and beyond. © 2019 John Wiley & Sons, Ltd.
Intermittent demand forecasting in the Enterprise: Empirical verification
Authors: Doszyń Mariusz 
Published: February 2019

AbstractForecasting methods are often valued by means of simulation studies. For intermittent demand items there are often very few non–zero observations, so it is hard to check any assumptions, because statistical information is often too weak to determine, for example, distribution of a variable. Therefore, it seems important to verify the forecasting methods on the basis of real data. The main aim of the article is an empirical verification of several forecasting methods applicable in case of intermittent demand. Some items are sold only in specific subperiods (in given month in each year, for example), but most forecasting methods (such as Croston's method) give non–zero forecasts for all periods. For example, summer work clothes should have non–zero forecasts only for summer months and many methods will usually provide non–zero forecasts for all months under consideration. This was the motivation for proposing and testing a new forecasting technique which can be applicable to seasonal items. In the article six methods were applied to construct separate forecasting systems: Croston's, SBA (Syntetos–Boylan Approximation), TSB (Teunter, Syntetos, Babai), MA (Moving Average), SES (Simple Exponential Smoothing) and SESAP (Simple Exponential Smoothing for Analogous subPeriods). The latter method (SESAP) is an author's proposal dedicated for companies facing the problem of seasonal items. By analogous subperiods the same subperiods in each year are understood, for example, the same months in each year. A data set from the real company was used to apply all the above forecasting procedures. That data set contained monthly time series for about nine thousand products. The forecasts accuracy was tested by means of both parametric and non–parametric measures. The scaled mean and the scaled root mean squared error were used to check biasedness and efficiency. Also, the mean absolute scaled error and the shares of best forecasts were estimated. The general conclusion is that in the analyzed company a forecasting system should be based on two forecasting methods: TSB and SESAP, but the latter method should be applied only to seasonal items (products sold only in specific subperiods). It also turned out that Croston's and SBA methods work worse than much simpler methods, such as SES or MA. The presented analysis might be helpful for enterprises facing the problem of forecasting intermittent items (and seasonal intermittent items as well).
Resting state connectivity differences in eyes open versus eyes closed conditions
Authors: Agcaoglu Oktay , Wilson Tony W. , Wang Yu‐Ping , Stephen Julia , Calhoun Vince D. 
Published: February 2019

AbstractFunctional magnetic resonance imaging data are commonly collected during the resting state. Resting state functional magnetic resonance imaging (rs‐fMRI) is very practical and applicable for a wide range of study populations. Rs‐fMRI is usually collected in at least one of three different conditions/tasks, eyes closed (EC), eyes open (EO), or eyes fixated on an object (EO‐F). Several studies have shown that there are significant condition‐related differences in the acquired data. In this study, we compared the functional network connectivity (FNC) differences assessed via group independent component analysis on a large rs‐fMRI dataset collected in both EC and EO‐F conditions, and also investigated the effect of covariates (e.g., age, gender, and social status score). Our results indicated that task condition significantly affected a wide range of networks; connectivity of visual networks to themselves and other networks was increased during EO‐F, while EC was associated with increased connectivity of auditory and sensorimotor networks to other networks. In addition, the association of FNC with age, gender, and social status was observed to be significant only in the EO‐F condition (though limited as well). However, statistical analysis did not reveal any significant effect of interaction between eyes status and covariates. These results indicate that resting‐state condition is an important variable that may limit the generalizability of clinical findings using rs‐fMRI.
Influence of poly‐l‐lysine molecular weight on antibacterial efficacy in polymer multilayer films
Authors: Alkekhia Dahlia , Shukla Anita 
Published: February 2019

AbstractAntibacterial coatings can prevent and treat medical device‐associated infections. We examined the antibacterial properties of coatings assembled from poly‐l‐lysine (PLL) and hyaluronic acid (HA). PLL/HA films were fabricated using layer‐by‐layer assembly with three different PLL MWs, differentiated by number of repeat units, that is, 33, 91, and 407 (denoted by PLL30, PLL90, and PLL400). Films assembled with all three PLL MWs completely inhibited the growth of planktonic, gram‐positive Staphylococcus aureus and methicillin‐resistant S. aureus and gram‐negative Pseudomonas aeruginosa and Escherichia coli over a 24‐h exposure. All three film architectures also inhibited S. aureus attachment by ~60–70% compared to non‐film‐coated surfaces, likely attributed to significant film hydration and electrostatic repulsion due to HA. The true differences in antibacterial efficacy between different PLL MWs were observed upon repeated exposure of PLL/HA to S. aureus every 24 h. We found that PLL400 films lost the ability to inhibit planktonic S. aureus growth after one use while PLL30 and PLL90 films were effective over 4–5 and 9–13 repeated exposures, respectively. Our experiments indicated that differences in efficacy were related to low in‐film mobility of PLL400 and also agreed with dissolution timescales for PLL30 and PLL90 films. © 2019 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 107A: 1324–1339, 2019.
Discogenic Back Pain: Literature Review of Definition, Diagnosis, and Treatment
Authors: Fujii Kengo , Yamazaki Masashi , Kang James D , Risbud Makarand V , Cho Samuel K , Qureshi Sheeraz A , Hecht Andrew C , Iatridis James C 
Published: February 2019

AbstractDiscogenic back pain is multifactorial; hence, physicians often struggle to identify the underlying source of the pain. As a result, discogenic back pain is often hard to treat—even more so when clinical treatment strategies are of questionable efficacy. Based on a broad literature review, our aim was to define discogenic back pain into a series of more specific and interacting pathologies, and to highlight the need to develop novel approaches and treatment strategies for this challenging and unmet clinical need. Discogenic pain involves degenerative changes of the intervertebral disc, including structural defects that result in biomechanical instability and inflammation. These degenerative changes in intervertebral discs closely intersect with the peripheral and central nervous systems to cause nerve sensitization and ingrowth; eventually central sensitization results in a chronic pain condition. Existing imaging modalities are nonspecific to pain symptoms, whereas discography methods that are more specific have known comorbidities based on intervertebral disc puncture and injection. As a result, alternative noninvasive and specific diagnostic methods are needed to better diagnose and identify specific conditions and sources of pain that can be more directly treated. Currently, there are many treatments/interventions for discogenic back pain. Nevertheless, many surgical approaches for discogenic pain have limited efficacy, thus accentuating the need for the development of novel treatments. Regenerative therapies, such as biologics, cell‐based therapy, intervertebral disc repair, and gene‐based therapy, offer the most promise and have many advantages over current therapies. © 2019 The Authors. JBMR Plus Published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research
SiMPLOD, a Structure-Integrated Database of Collagen Lysyl Hydroxylase (LH/PLOD) Enzyme Variants
Authors: Scietti Luigi , Campioni Matteo , Forneris Federico 
Published: February 2019

ABSTRACT

PLOD genes encode for procollagen lysyl hydroxylase enzymes (LH/PLOD), a family of proteins essential for collagen biosynthesis. Several mutations affect these genes, causing severe disorders, such as Ehlers-Danlos and Bruck syndrome, as well a connective tissue disease with phenotype resembling osteogenesis imperfecta caused by lack of LH3 functions. The recently determined three-dimensional (3D) structures of the full-length human LH3/PLOD3 isoform, together with the structure of a fragment of a viral LH/PLOD homolog, are now allowing molecular mapping of the numerous disease-causing mutations, providing insights often suitable for the interpretation of the resulting disease phenotypes. However, the added value of molecular structure interpretation is affected by the limited accessibility of complex molecular data to scientific communities lacking direct expertise in structural biology. In this work, we present a Structurally-integrated database for Mutations of PLOD genes (SiMPLOD), a publicly-available manually-curated online database with an embedded molecular viewer interface for the visualization and interpretation of LH/PLOD mutations on available molecular models. Each SiMPLOD entry is accompanied by manual annotations extrapolated from literature references and comments about the localization of the amino acid variants on the molecular structure. Additional links to the appropriate online resources for clinically-relevant as well as biochemical data are also provided in a standardized format. The web application is available at http://fornerislab.unipv.it/SiMPLOD. © 2019 American Society for Bone and Mineral Research.
The IMPACT study: early loss of skeletal muscle mass in advanced pancreatic cancer patients
Authors: Basile Debora , Parnofiello Annamaria , Vitale Maria Grazia , Cortiula Francesco , Gerratana Lorenzo , Fanotto Valentina , Lisanti Camilla , Pelizzari Giacomo , Ongaro Elena , Bartoletti Michele , Garattini Silvio Ken , Andreotti Victoria Josephine , Bacco Anna , Iacono Donatella , Bonotto Marta , Casagrande Mariaelena , Ermacora Paola , Puglisi Fabio , Pella Nicoletta , Fasola Gianpiero , Aprile Giuseppe , Cardellino Giovanni G. 
Published: February 2019

AbstractBackgroundPancreatic cancer (PC) patients have multiple risk factors for sarcopenia and loss of skeletal muscle mass (LSMM), which may cause greater treatment toxicities, reduced response to cancer therapy, prolonged hospitalization, impaired quality of life, and worse prognosis.MethodsThis is a retrospective study on advanced PC patients treated at the Department of Oncology of Udine, Italy, from January 2012 to November 2017. Among 162 patients who received chemotherapy, 94 consecutive patients with an available computed tomography (CT) scan were retrospectively analyzed. The primary objective of our study was to explore if an early LSMM ≥ 10% (measured at first radiological evaluation and compared with baseline) and/or baseline sarcopenia may impact prognosis. Baseline sarcopenia was defined according to Prado's criteria. Skeletal muscle area was measured as cross‐sectional areas (cm2) using CT scan data through the Picture archiving and communication system (PACS) image system.ResultsIn the whole cohort, 48% of patients were ≤70 years old, and 50% had metastatic disease.At baseline, 73% of patients had sarcopenia, and 16% presented a visceral fat area ≥ 44 cm2/m2. Overall, 21% experienced an early LSMM ≥ 10%. Approximately 33% of sarcopenic patients at baseline and ~35% of patients with early LSMM ≥ 10% had a body mass index > 25 kg/m2. Of note, 71% of patients were evaluated by a nutritionist, and 56% received a dietary supplementation (oral and/or parenteral). After a median follow‐up of 30.44 months, median overall survival (OS) was 11.28 months, whereas median progression‐free survival (PFS) was 5.72 months. By multivariate analysis, early LSMM ≥ 10% was significantly associated with worse OS [hazard ratio (HR): 2.16; 95% confidence interval (CI) 1.23–3.78; P = 0.007] and PFS (HR: 2.31; 95% CI 1.30–4.09; P = 0.004). Moreover, an exploratory analysis showed that inflammatory indexes, such as neutrophil–lymphocyte ratio variation, impact early LSMM ≥ 10% (odds ratio 1.31, 95% CI 1.06–1.61, P = 0.010).ConclusionsEarly LSMM ≥ 10% has a negative prognostic role in advanced PC patients. Further prospective investigations are needed to confirm these preliminary data.
Frontline Science: TNF-α and GM-CSF1 priming augments the role of SOS1/2 in driving activation of Ras, PI3K-γ, and neutrophil proinflammatory responses
Authors: Suire Sabine , Baltanas Fernando C , Segonds-Pichon Anne , Davidson Keith , Santos Eugenio , Hawkins Phillip T , Stephens Len R 
Published: February 2019

Abstract
Circulating neutrophils are, by necessity, quiescent and relatively unresponsive to acute stimuli. In regions of inflammation, mediators can prime neutrophils to react to acute stimuli with stronger proinflammatory, pathogen-killing responses. In neutrophils G protein-coupled receptor (GPCR)-driven proinflammatory responses, such as reactive oxygen species (ROS) formation and accumulation of the key intracellular messenger phosphatidylinositol (3,4,5)-trisphosphate (PIP3), are highly dependent on PI3K-γ, a Ras-GTP, and Gβγ coincidence detector. In unprimed cells, the major GPCR-triggered activator of Ras is the Ras guanine nucleotide exchange factor (GEF), Ras guanine nucleotide releasing protein 4 (RasGRP4). Although priming is known to increase GPCR–PIP3 signaling, the mechanisms underlying this augmentation remain unclear. We used genetically modified mice to address the role of the 2 RasGEFs, RasGRP4 and son of sevenless (SOS)1/2, in neutrophil priming. We found that following GM-CSF/TNFα priming, RasGRP4 had only a minor role in the enhanced responses. In contrast, SOS1/2 acquired a substantial role in ROS formation, PIP3 accumulation, and ERK activation in primed cells. These results suggest that SOS1/2 signaling plays a key role in determining the responsiveness of neutrophils in regions of inflammation.