generalized linear modelling
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2021 ◽  
Vol 28 (4) ◽  
pp. 312-324
Author(s):  
Alexander Kurniawan Sariyanto Putera ◽  
Dyah Perwitasari-Farajallah ◽  
Yeni Aryati Mulyani ◽  
Stanislav Lhota ◽  
Riki Herliansyah ◽  
...  

Balikpapan Bay is one of the wetlands providing potential foraging habitat for waterbirds in Indonesia. Potential habitat loss due to oil industry expansion, recent waterbird occurrence, and co-occurrence of two closely related species with similar foraging characteristics led to habitat selection. Habitat selection could be affected by food as an intrinsic factor and extrinsic factor, for example, accessibility to the physical and biological components of the habitat. This study aimed to measure the foraging habitat selection, identify significant habitat quality parameters for the habitat selection and predict the foraging habitat selection model. We used one-zero sampling for collecting foraging habitat selection data, corer sampling for prey data, and collecting the abiotic environment, and Generalized Linear Modelling (GLM) to build the model. We identified four species as the migrant Little Egret (Egretta garzetta), Great Egret (Ardea alba), Purple Heron (Ardea purpurea), and Lesser Adjutant (Leptoptilos javanicus). All species, except Purple Heron, selected foraging habitats. A simple mathematic model of foraging habitat selection was significantly affected by two factors: water depth and patch area. A large patch area may provide primary prey abundance for waterbirds, while a low water depth level may give easy access to the prey.


2021 ◽  
pp. 205301962110446
Author(s):  
Matthew Adesanya Adeleye ◽  
Simon Edward Connor ◽  
Simon Graeme Haberle ◽  
Annika Herbert ◽  
Josephine Brown

The rapid increase in severe wildfires in many parts of the world, especially in temperate systems, requires urgent attention to reduce fires’ catastrophic impacts on human lives, livelihoods, health and economy. Of particular concern is southeast Australia, which harbours one of the most flammable vegetation types on Earth. While previous studies suggest climate and European activities drove changes in southeast Australian fire regimes in the last 200 years, no study has quantitatively tested the relative roles of these drivers. Here, we use a Generalized Linear Modelling to identify the major driver(s) of fire regime change in the southeast Australian mainland during and prior to European colonization. We use multiple charcoal and pollen records across the region and quantitatively compare fire history to records of climate and vegetation change. Results show low levels of biomass burned before colonization, when landscapes where under Indigenous management, even under variable climates. Biomass burned increased markedly due to vegetation/land-use change after colonization and a major decline in regional precipitation about 100 years later. We conclude that Indigenous-maintained open vegetation minimized the amount of biomass burned prior to colonization, while European-suppression of Indigenous land management has amplified biomass accumulation and fuel connectivity in southeast Australian forests since colonization. While climate change remains a major challenge for fire mitigation, implementation of a management approach similar to the pre-colonial period is suggested to ameliorate the risk of future catastrophic fires in the region.


PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256773
Author(s):  
Sharan Murali ◽  
Yuvaraj Krishnamoorthy ◽  
Selby Knudsen ◽  
Gautam Roy ◽  
Jerrold Ellner ◽  
...  

The rising geriatric population and the increased susceptibility of this age group to tuberculosis (TB), the deadliest single infectious agent, is bothersome for India. This study tried to explore the demographic and treatment outcome differences between the elderly (aged 60 years and above) and non-elderly TB (<60 years) patients from South India. This study was part of a large ongoing cohort study under the RePORT India consortium. Newly diagnosed TB patients recruited into the cohort between 2014 and 2018 were included in this study. Pretested and standardized questionnaire and tools were used to collect data and were stored securely for the entire cohort. Required demographic, anthropometric and treatment related variables were extracted from this database and analyzed using Stata version 14.0. Prevalence of elderly TB was summarized as percentage with 95% confidence interval (CI). Generalized linear modelling was attempted to find the factors associated with elderly TB. A total of 1,259 eligible TB patients were included into this present study. Mean (SD) of the participants in the elderly and non-elderly group was 65.8 (6.2) and 40.2 (12.0) respectively. Prevalence of elderly TB was 15.6% (95%CI: 13.6%-17.6%) with nearly 71% belonging to 60–69 age category. Male sex, OBC caste, poor education, unemployment, marriage, alcohol consumption and unable to work as per Karnofsky score were found to be significantly associated with an increased prevalence of elderly TB. Unfavorable outcomes (12% vs 6.5%, p value: 0.018), including death (9.3% vs 3.4%, p value: 0.001) were significantly higher among the elderly group when compared to their non-elderly counterparts. The current TB programme should have strategies to maintain follow up with due attention to adverse effects, social support and outcomes. Additional research should focus on predictors for unfavorable outcomes among the elderly TB group and explore ways to handle the same. Rendering adequate social support from the health system side and family side would be a good start.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Arturo Hernandez-Colina ◽  
Merit Gonzalez-Olvera ◽  
Emily Lomax ◽  
Freya Townsend ◽  
Amber Maddox ◽  
...  

Abstract Background Zoological gardens contain unique configurations of exotic and endemic animals and plants that create a diverse range of developing sites and potential sources of blood meals for local mosquitoes. This may imply unusual interspecific pathogen transmission risks involving zoo vertebrates, like avian malaria to captive penguins. Understanding mosquito ecology and host feeding patterns is necessary to improve mosquito control and disease prevention measures in these environments. Methods Mosquito sampling took place in Chester Zoo for 3 years (2017, 2018, and 2019) and for 1 year in Flamingo Land (2017) using different trapping methods. Blood-fed mosquitoes were identified and their blood meal was amplified by PCR, sequenced, and blasted for host species identification. Results In total, 640 blood-fed mosquitoes were collected [Culex pipiens (n = 497), Culiseta annulata (n = 81), Anopheles maculipennis s.l. (n = 7), An. claviger (n = 1), and unidentifiable (n = 55)]. Successful identification of the host species was achieved from 159 blood-fed mosquitoes. Mosquitoes fed on birds (n = 74), non-human mammals (n = 20), and humans (n = 71). There were mixed blood meals from two hosts (n = 6). The proportions of blood-fed mosquitoes varied across sampling seasons and sites within the zoos. The use of resting traps and aspiration of vegetation were more efficient techniques for capturing blood-fed mosquitoes than traps for host-seeking or gravid mosquitoes. By relating the locations of zoo vertebrates to where fed mosquitoes were trapped, the minimum travelling distances were calculated (13.7 to 366.7 m). Temperature, precipitation, relative humidity, proximity to zoo vertebrate exhibits, and vegetation level were found to be significantly associated with the proportion of captured blood-fed mosquitoes by generalized linear modelling. Conclusions Mosquito feeding behaviour in zoos is mainly influenced by time, location (sampling area), temperature, and host availability, which highlights the value of mosquito monitoring in complex settings to plan control strategies and potentially reduce inherent disease transmission risks for humans and threatened zoo vertebrates. Graphic abstract


F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 374
Author(s):  
Jeroen Gilis ◽  
Kristoffer Vitting-Seerup ◽  
Koen Van den Berge ◽  
Lieven Clement

Alternative splicing produces multiple functional transcripts from a single gene. Dysregulation of splicing is known to be associated with disease and as a hallmark of cancer. Existing tools for differential transcript usage (DTU) analysis either lack in performance, cannot account for complex experimental designs or do not scale to massive scRNA-seq data. We introduce satuRn, a fast and flexible quasi-binomial generalized linear modelling framework that is on par with the best performing DTU methods from the bulk RNA-seq realm, while providing good false discovery rate control, addressing complex experimental designs and scaling to scRNA-seq applications.


2021 ◽  
Vol 15 (Supplement_1) ◽  
pp. S014-S015
Author(s):  
B Verstockt ◽  
S Verstockt ◽  
J Sabino ◽  
M Ferrante ◽  
S Vermeire

Abstract Background Extracellular RNAs (exRNAs) are RNA species present outside of the cells in which they were transcribed. They are found in human serum, though the exact role of circulating exRNAs remains to be established, especially in inflammatory bowel diseases (IBD). Besides their potential help in our pathophysiological understanding of disease, they might serve as liquid biopsies or non-invasive biomarkers. We characterised exRNAs in serum from IBD patients, and questioned their potential in separating ulcerative colitis (UC) from Crohn’s disease (CD). Methods We carried out SILVER-seq (Small Input Liquid Volume Extracellular RNA-sequencing) on serum droplets (5-7ml) from a cross-sectional cohort of 26 IBD patients (15 UC, 11 CD) with active endoscopic disease (Mayo endoscopic sub score or Simple Endoscopic Score for Crohn’s disease) (Table 1). Normalization and differential expression were done using DESeq2 R package, co-expression network analyses performed using WGCNA (FDR adjusted p ≤0.05). Using randomized generalized linear modelling (RGLM), a diagnostic exRNA marker was designed to separate UC from CD samples (15 UC, 11 CD). Results We detected 60,675 exRNAs in serum from IBD patients, capturing 76.1% of all genes expressed in intestinal tissue, and including highly abundant intestinal genes (e.g MUC2) and intestinal barrier genes (e.g claudin 8, occludin and RETNLB). Co-expression network analysis identified 69 clusters of which 1 significantly correlated with the distinction between CD and UC (FDR p=0.003, r=-0.70). One of the hub genes within this module (consisting of 148 genes, upregulated in UC) was GNA12 (p=2.3E-4, r=0.66 for correlation with the module eigengene), encoding for a membrane bound GTPase that plays a key role in tight junction assembly and has previously been identified as UC-specific SNP in GWAS (Figure 1). Serum GNA12 expression was not associated with faecal calprotectin (p=0.55, r=0.12), disease duration (p=0.24, r=0.25), age (p=0.43, r=0.16) or gender (p=1.0), but did correlate with other UC-specific genes including TNFRSF14 (p=0.04, r=0.4), HNF4A (p=0.04, r=-0.4) and CAMK2A (p=0.004, r=0.54). Through machine learning within the UC-specific module (containing 148 genes), we identified an 8-gene exRNA panel, including GNA12, that could accurately discriminate between UC and CD patients (accuracy 96.2%). Figure 1: Visualisation of the identified exRNA network including GNA12 Conclusion Liquid biopsies are a novel non-invasive tool in IBD biomarker development. Although larger in-depth studies are required to further validate, explore and characterise the potential of serum exRNAs in the field of IBD, the current pilot project identified a new non-invasive tool to accurately distinguish CD from UC patients.


Author(s):  
Thomas Yamashita ◽  
Trinity Livinigston ◽  
Kevin Ryer ◽  
John Young ◽  
Richard Kline

Collisions with vehicles are a major threat to wildlife populations and often occur in identifiable patterns. To reduce wildlife road mortalities, mitigation structures including exclusionary fencing and wildlife crossings are constructed. Openings in fencing at road intersections may lead to concentration of road mortality hot spots at openings leading to a belief that these gaps concentrate road mortalities. However, it is also possible that hot spots existed at these locations before construction indicating that road mortality patterns have not changed with mitigation structure construction. Therefore, to assess mitigation structure effectiveness, it is important to examine both road mortality numbers and road mortality spatial distribution. Wildlife road mortality data was collected on a 15-km section of rural highway in Texas, USA before, during, and after the construction of wildlife mitigation structures. We expected that the number of road mortalities would decrease after construction compared to before construction and that road mortalities would become more concentrated around openings in the fence. We used ANOVA to compare numbers of road mortalities and emerging hot spot analysis and generalized linear modelling to assess changes in road mortality spatial distribution. Road mortalities were not significantly different in the before and after construction periods (p = 0.092). While there were no significant changes in road mortality patterns with construction, cluster intensity was greater when nearer to fence openings in all three time periods. Emerging hot spot analysis provides an effective and easy way to visualize road mortality patterns through time, however, due to low numbers of mortalities in many road mortality studies, including this one, the power of this analysis to detect significant changes in road mortality may be limited. This technique can provide both ecologists and transportation planners an effective tool for identifying patterns that may warrant further investigation using traditional statistical techniques.


2021 ◽  
Author(s):  
Jeroen Gilis ◽  
Kristoffer Vitting-Seerup ◽  
Koen Van den Berge ◽  
Lieven Clement

AbstractAlternative splicing produces multiple functional transcripts from a single gene. Dysregulation of splicing is known to be associated with disease and as a hallmark of cancer. Existing tools for differential transcript usage (DTU) analysis either lack in performance, cannot account for complex experimental designs or do not scale to massive scRNA-seq data. We introduce satuRn, a fast and flexible quasi-binomial generalized linear modelling framework that is on par with the best performing DTU methods from the bulk RNA-seq realm, while providing good false discovery rate control, addressing complex experimental designs and scaling to scRNA-seq applications.


Author(s):  
Kevin Filo ◽  
Millicent Kennelly ◽  
Richard J. Buning ◽  
Rana Sobh

Research into participatory sport event experiences and wellbeing outcomes has increased, however, much of this work explores Western contexts. The purpose of the current research is to examine the wellbeing outcomes related to sport event participation in Qatar, as well as how these outcomes differ across nationalities and by gender. An online questionnaire was administered to participants of the 2017 Ooredoo Doha Marathon (ODM) (N = 239). Inductive coding of responses to the open-ended items uncovered activation of relationships, meaning and accomplishment. The qualitative data revealed that event participation allowed participants to strengthen personal connections with others, fostered a sense of direction and allowed for goal setting among participants, and enabled participants to experience achievement. Meanwhile, generalized linear modelling revealed Qatari nationals and expats as well as males and females differentially reported wellbeing based on PERMA domains.


Author(s):  
Donald Quicke ◽  
Buntika A. Butcher ◽  
Rachel Kruft Welton

Abstract This chapter employs generalized linear modelling using the function glm when we know that variances are not constant with one or more explanatory variables and/or we know that the errors cannot be normally distributed, for example, they may be binary data, or count data where negative values are impossible, or proportions which are constrained between 0 and 1. A glm seeks to determine how much of the variation in the response variable can be explained by each explanatory variable, and whether such relationships are statistically significant. The data for generalized linear models take the form of a continuous response variable and a combination of continuous and discrete explanatory variables.


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