scholarly journals Using Food Webs and Metabolic Theory to Monitor, Model, and Manage Atlantic Salmon—A Keystone Species Under Threat

2021 ◽  
Vol 9 ◽  
Author(s):  
Guy Woodward ◽  
Olivia Morris ◽  
José Barquín ◽  
Andrea Belgrano ◽  
Colin Bull ◽  
...  
Keyword(s):  
Atlantic Salmon ◽  
Large Scale ◽  
Keystone Species ◽  
Population Data ◽  
Metabolic Theory ◽  
Huge Data ◽  
Scale Population ◽  
Natural Range ◽  
Underlying Causes

Populations of Atlantic salmon are crashing across most of its natural range: understanding the underlying causes and predicting these collapses in time to intervene effectively are urgent ecological and socioeconomic priorities. Current management techniques rely on phenomenological analyses of demographic population time-series and thus lack a mechanistic understanding of how and why populations may be declining. New multidisciplinary approaches are thus needed to capitalize on the long-term, large-scale population data that are currently scattered across various repositories in multiple countries, as well as marshaling additional data to understand the constraints on the life cycle and how salmon operate within the wider food web. Here, we explore how we might combine data and theory to develop the mechanistic models that we need to predict and manage responses to future change. Although we focus on Atlantic salmon—given the huge data resources that already exist for this species—the general principles developed here could be applied and extended to many other species and ecosystems.

Hybrid Information Systems for Agriculture: The Case of Cattle Trypanosomiasis in Africa

1994 ◽  
Vol 23 (4) ◽  
pp. 261-267 ◽  
Author(s):  
Iain J. Mckendrick ◽  
George Gettinby ◽  
Yiqun Gu ◽  
Andrew Peregrine ◽  
Crawford Revie
Keyword(s):  
Information Technology ◽  
Hybrid System ◽  
Food Production ◽  
Large Scale ◽  
Sub Saharan Africa ◽  
Software Systems ◽  
High Quality ◽  
Scale Population ◽  
Sub Saharan

Large scale population growth in sub-Saharan Africa makes it imperative to achieve an equivalent increase in food production in this area. It is also important that any increase be sustainable in the long-term, not causing lasting damage to local ecosystems. Recent advances in information technology make the successful diffusion of relevant expertise to farmers a more practical option than ever before. How this might be achieved is described in this paper, which considers the transfer of expertise in the diagnosis, treatment and management of trypanosomiasis in cattle. Using current technology, the combination of different software systems in one integrated hybrid system could allow the delivery of high quality, well focused information to the potential user.

Long-term incidence of secondary bladder and rectal cancer in patients treated with brachytherapy for localized prostate cancer: a large-scale population-based analysis

2019 ◽  
Vol 124 (6) ◽  
pp. 1006-1013 ◽  
Author(s):  
Elio Mazzone ◽  
Francesco A. Mistretta ◽  
Sophie Knipper ◽  
Carlotta Palumbo ◽  
Zhe Tian ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Rectal Cancer ◽  
Large Scale ◽  
Population Based ◽  
Localized Prostate Cancer ◽  
Scale Population

scholarly journals Reliability of the NIH toolbox cognitive battery in children and adolescents: a 3-year longitudinal examination

2020 ◽  
pp. 1-10
Author(s):  
Brittany K. Taylor ◽  
Michaela R. Frenzel ◽  
Jacob A. Eastman ◽  
Alex I. Wiesman ◽  
Yu-Ping Wang ◽  
...  
Keyword(s):  
Large Scale ◽  
Intraclass Correlation ◽  
Temporal Stability ◽  
Correlation Coefficients ◽  
Population Level ◽  
Clinical Applications ◽  
Intraclass Correlation Coefficients ◽  
Scale Population ◽  
Longitudinal Examination

Abstract Background The Cognitive Battery of the National Institutes of Health Toolbox (NIH-TB) is a collection of assessments that have been adapted and normed for administration across the lifespan and is increasingly used in large-scale population-level research. However, despite increasing adoption in longitudinal investigations of neurocognitive development, and growing recommendations that the Toolbox be used in clinical applications, little is known about the long-term temporal stability of the NIH-TB, particularly in youth. Methods The present study examined the long-term temporal reliability of the NIH-TB in a large cohort of youth (9–15 years-old) recruited across two data collection sites. Participants were invited to complete testing annually for 3 years. Results Reliability was generally low-to-moderate, with intraclass correlation coefficients ranging between 0.31 and 0.76 for the full sample. There were multiple significant differences between sites, with one site generally exhibiting stronger temporal stability than the other. Conclusions Reliability of the NIH-TB Cognitive Battery was lower than expected given early work examining shorter test-retest intervals. Moreover, there were very few instances of tests meeting stability requirements for use in research; none of the tests exhibited adequate reliability for use in clinical applications. Reliability is paramount to establishing the validity of the tool, thus the constructs assessed by the NIH-TB may vary over time in youth. We recommend further refinement of the NIH-TB Cognitive Battery and its norming procedures for children before further adoption as a neuropsychological assessment. We also urge researchers who have already employed the NIH-TB in their studies to interpret their results with caution.

Abstract P547: Cardiac Arrest in Patients Who Present With Subarachnoid Hemorrhage is Associated With Worse Outcomes

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Gurkamal Kaur ◽  
Jose Dominguez ◽  
Rosa Semaan ◽  
Leanne Fuentes ◽  
Jonathan Ogulnick ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Subarachnoid Hemorrhage ◽  
Large Scale ◽  
Clinical Decision Making ◽  
Population Data ◽  
Clinical Decision ◽  
Small Sample ◽  
P Value ◽  
Dismal Prognosis ◽  
Scale Population

Introduction: Subarachnoid hemorrhage (SAH) can be a devastating neurologic condition that leads to cardiac arrest (CA), and ultimately poor clinical outcomes. Existing literature on this subject reveal a dismal prognosis when analyzing relatively small sample sizes. We aimed to further elucidate the incidence, mortality rates, and outcomes of CA patients with SAH using large-scale population data. Methods: A retrospective cohort study was conducted using the National Inpatient Sample (NIS) database. Patients included in the study met criteria using International Classification of Diseases (ICD) codes 9th and 10th edition of: non-traumatic SAH, CA cause unspecified, and CA due to other underlying conditions between 2008 and 2014. For all regression analyses, a p-value of <0.05 was considered statistically significant. Results: We identified 170,869 patients hospitalized for non-traumatic SAH. Within these, there was a 3.17% incidence of CA. The mortality rate in CA with SAH was 82% (vs non-CA 18.4%, p< 0.001). Of the survivors of CA with SAH, 15.7% were discharged to special facilities and services (vs non-CA 37.6%, p<0.0001). The remaining 2.3% were discharged home (vs non-CA 44.0%, p<.0001). Higher NIS SAH severity score (NIS-SSS) was a predictor of CA in SAH patients (p <.0001). Patients treated with aneurysm clipping and coiling had lower odds ratio of CA (p <.0001). Conclusion: The study confirms the poor prognosis of patients with CA and SAH using large-scale population data. Patients that underwent aneurysm treatment show lower association with CA. Findings presented here provide useful data for clinical decision making and guiding goals of care discussion with family members. Further studies may identify interventions and protocols for treatment of these severely ill patients.

The disturbance regime of Norway spruce forests in Bulgaria

2015 ◽  
Vol 45 (9) ◽  
pp. 1143-1153 ◽  
Author(s):  
Momchil Panayotov ◽  
Peter Bebi ◽  
Nickolay Tsvetanov ◽  
Neno Alexandrov ◽  
Lucinda Laranjeiro ◽  
...  
Keyword(s):  
Norway Spruce ◽  
Large Scale ◽  
Natural Disturbance ◽  
Disturbance Regime ◽  
Forest Reserves ◽  
Spruce Forests ◽  
The Past ◽  
Natural Range ◽  
Old Trees

Natural disturbances are among the most important factors that shape forest dynamics and forest landscapes. However, the natural disturbance regime of Norway spruce (Picea abies (L.) Karst.) forests in Europe is not well understood. We studied the disturbance regimes in three forest reserves in Bulgaria (Parangalitsa, Bistrishko branishte, and Beglika), which are representative of the range of conditions typical for P. abies ecosystems in central and southern Europe. Our data indicated that large-scale disturbances were most numerous in forests that were between 120 and 160 years old, those with unimodal diameter at breast height (DBH) distributions, and especially those located in vulnerable topographic settings. Wind disturbances ranged up to 60 ha, followed in one case by a 200 ha Ips typographus (Linnaeus, 1758) outbreak. Older forests and those with more complex structures (i.e., reverse-J DBH) were characterized by numerous small gaps but were also affected by a few larger disturbances. In some old-growth forests at highly productive sites, gaps could be so numerous that the long-term existence of old trees may become an exception. Over the past centuries, the natural range of variability of these Norway spruce forests in Bulgaria appears to have been shaped mostly by wind and bark beetle disturbances of various sizes.

scholarly journals Cox-nnet v2.0: improved neural-network-based survival prediction extended to large-scale EMR data

2021 ◽  
Author(s):  
Di Wang ◽  
Zheng Jing ◽  
Kevin He ◽  
Lana X Garmire
Keyword(s):  
Neural Network ◽  
Large Scale ◽  
High Efficiency ◽  
Prediction Method ◽  
Population Data ◽  
Superior Performance ◽  
Supplementary Information ◽  
Survival Prediction ◽  
Training Time ◽  
Scale Population

Abstract Summary Cox-nnet is a neural-network-based prognosis prediction method, originally applied to genomics data. Here, we propose the version 2 of Cox-nnet, with significant improvement on efficiency and interpretability, making it suitable to predict prognosis based on large-scale population data, including those electronic medical records (EMR) datasets. We also add permutation-based feature importance scores and the direction of feature coefficients. When applied on a kidney transplantation dataset, Cox-nnet v2.0 reduces the training time of Cox-nnet up to 32-folds (n =10 000) and achieves better prediction accuracy than Cox-PH (P&lt;0.05). It also achieves similarly superior performance on a publicly available SUPPORT data (n=8000). The high efficiency and accuracy make Cox-nnet v2.0 a desirable method for survival prediction in large-scale EMR data. Availability and implementation Cox-nnet v2.0 is freely available to the public at https://github.com/lanagarmire/Cox-nnet-v2.0. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Improving variant calling using population data and deep learning

2021 ◽  
Author(s):  
Nae-Chyun Chen ◽  
Alexey Kolesnikov ◽  
Sidharth Goel ◽  
Taedong Yun ◽  
Pi-Chuan Chang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Variant Calling ◽  
Population Data ◽  
Training Data ◽  
1000 Genomes Project ◽  
1000 Genomes ◽  
Population Information ◽  
Scale Population ◽  
The Impact

Large-scale population variant data is often used to filter and aid interpretation of variant calls in a single sample. These approaches do not incorporate population information directly into the process of variant calling, and are often limited to filtering which trades recall for precision. In this study, we modify DeepVariant to add a new channel encoding population allele frequencies from the 1000 Genomes Project. We show that this model reduces variant calling errors, improving both precision and recall. We assess the impact of using population-specific or diverse reference panels. We achieve the greatest accuracy with diverse panels, suggesting that large, diverse panels are preferable to individual populations, even when the population matches sample ancestry. Finally, we show that this benefit generalizes to samples with different ancestry from the training data even when the ancestry is also excluded from the reference panel.

scholarly journals Possible influence of salmon farming on long-term resident behaviour of wild saithe (Pollachius virens L.)

2014 ◽  
Vol 71 (9) ◽  
pp. 2484-2493 ◽  
Author(s):  
Håkon Otterå ◽  
Ove T. Skilbrei
Keyword(s):  
Large Scale ◽  
Migration Routes ◽  
Salmon Farming ◽  
Dynamic Relationship ◽  
Natural Behaviour ◽  
Scale Population ◽  
Acoustic Tags ◽  
Release Area ◽  
And Migration

Abstract The culture of Atlantic salmon is one of the most developed aquaculture industries in the world. The production from smolt to market size usually takes place in sea cages in open waters, and these structures tend to attract wild fish, as they do for other farmed species. For salmon farming, saithe (Pollachius virens) is one of the most-frequently observed species around sea cages. An important question is whether the large concentration of salmon farms in some areas might alter the natural behaviour and migration pattern of wild saithe. We tagged 62 wild saithe with acoustic tags and followed their movements for up to 2 years in an area in Southwestern Norway with many salmon farms. Furthermore, nearly 2000 saithe were tagged with external T-bar tags to study migration beyond the study area. The recaptures of the T-bar tagged saithe from offshore areas suggest that the offshore migration routes of saithe are similar to published results from before salmon farming became significant in the area. However, a large proportion of the saithe population appears to remain in the release area and was observed at the salmon farms for much of the time. We conclude that the aquaculture industry is influencing the local saithe distribution. Large-scale population effects are more difficult to prove, but it is possible that the dynamic relationship between the coastal and oceanic phases has been altered.

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