Riverine salmonid egg burial depths: review of published data and implications for scour studies

1997 ◽  
Vol 54 (8) ◽  
pp. 1685-1698 ◽  
Author(s):  
P DeVries
Keyword(s):  
Primary Sources ◽  
Distribution Data ◽  
Published Data ◽  
Accurate Identification ◽  
Bed Elevation ◽  
Spawning Areas ◽  
Sources Of Variation ◽  
Reported Data ◽  
Threshold Criteria ◽  
Redd Superimposition

Published data on salmon, trout, and charr egg burial depths are highly variable and inconsistent. Primary sources of variation include elevation datum and portion of the egg pocket referenced to; differences in spawning behavior and the number, thickness, and location of egg pockets; relationships between egg depth, fish species, and corresponding size of female and spawning substrate and velocity characteristics; sampling method; presence of excavation barriers; redd superimposition; and scour and fill by hydraulic and other mechanical processes. Such sources of variability in the reported data have important implications for studies of scouring processes in salmonid spawning areas that require accurate identification of egg burial depths for predicting and preventing potential scour impacts. Cumulative measurement error and unexplained variation may amount to 5-20 cm or more in published values. The most relevant data for scour impact assessments are depths from the original stream bed elevation down to the top of the main egg pocket. Frequency distribution data are needed for determining probabilities and cumulative levels of scour impacts and for managing genetic diversity as well as population size. Preliminary depth threshold criteria are proposed for use now, pending further research.

scholarly journals Thermal Expansion of MgTiO3 Made by Sol-Gel Technique at Temperature Range 25–890 °C

Crystals ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 887 ◽  
Author(s):  
Tamir Tuval ◽  
Brian A. Rosen ◽  
Jacob Zabicky ◽  
Giora Kimmel ◽  
Helena Dilman ◽  
...  
Keyword(s):  
Thermal Expansion ◽  
Solid State ◽  
Sol Gel ◽  
Lattice Parameters ◽  
Published Data ◽  
Temperature Structure ◽  
Solid State Method ◽  
Synthesis Technique ◽  
Thermal Expansion Coefficients ◽  
Reported Data

MgTiO3 is a material commonly used in the industry as capacitors and resistors. The high-temperature structure of MgTiO3 has been reported only for materials synthesized by the solid-state method. This study deals with MgTiO3 formed at low temperatures by the sol-gel synthesis technique. Co-precipitated xerogel precursors of nanocrystalline magnesium titanates, with Mg:Ti ratio near 1:1, were subjected to thermal treatment at 1200 °C for 5 h in air. A sample with fine powders of MgTiO3 (geikielite) as a major phase with Mg2TiO4 (qandilite) as a minor phase was obtained. The powder was scanned on a hot-stage X-ray powder diffractometer at temperatures between 25 and 890 °C. The lattice parameters and the atomic positions of the two phases were determined as a function of temperature. The thermal expansion coefficients of the geikielite were derived and compared with previously published data using the solid-state synthesis technique, providing insights on trends in materials properties at elevated temperature as a function of synthesis. It was found that the deviation of the present results in comparison to previously reported data do not originate from the method of synthesis but rather from the fact that there is an asymmetric solubility gap in geikielite. The lattice parameters of this study present the property of stoichiometric MgTiO3 and are compared to previously reported non-stoichiometric MgTiO3 with excess of Ti. The values of lattice parameters of the non-stoichiometric versus temperature of geikielite found the same for both solid-state reaction and sol-gel products.

scholarly journals Distribution and Diversity of the Cryptic Ant GenusOxyepoecus(Hymenoptera: Formicidae: Myrmicinae) in Paraguay with Descriptions of Two New Species

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
T. Delsinne ◽  
W. Mackay ◽  
A. Wild ◽  
Y. Roisin ◽  
M. Leponce
Keyword(s):  
New Species ◽  
National Park ◽  
Red List ◽  
Biological Conservation ◽  
Distribution Data ◽  
Published Data ◽  
Two New Species ◽  
First Time ◽  
New Distribution

We discuss the diversity and distribution of the ant genusOxyepoecusin Paraguay.Oxyepoecus inquilinusis recorded for the first time, and new distribution data are given forO. rastratusandO. vezenyii. Published data forO. bruchi,O. rastratus,O. reticulatus,andO. vezenyiiare summarized. Two new species are described (O. bidentatusn. sp. andO. striatusn. sp.), and a key to the workers of the seven ParaguayanOxyepoecusspecies is provided. At Teniente Enciso National Park, four species cooccur. This locality appears as a promising site for studies documenting the biology of this poorly known ant genus, and because of the IUCN “vulnerable“ Red List classification ofO. inquilinus, the importance of the Teniente Enciso National Park for biological conservation is clearly established.

scholarly journals Accurate identification and quantification of commensal microbiota bound by host immunoglobulins

2020 ◽  
Author(s):  
Matthew A. Jackson ◽  
Claire Pearson ◽  
Nicholas E. Ilott ◽  
Kelsey E. Huus ◽  
Ahmed N. Hegazy ◽  
...  
Keyword(s):  
Immunoglobulin A ◽  
Amplicon Sequencing ◽  
Positive Control ◽  
Published Data ◽  
Case Control Studies ◽  
Scoring Method ◽  
Accurate Identification ◽  
Relative Abundances ◽  
Identification And Quantification

AbstractBackgroundIdentifying which taxa are targeted by immunoglobulins can uncover important host-microbe interactions. Immunoglobulin binding of commensal taxa can be assayed by sorting bound bacteria from samples and using amplicon sequencing to determine their taxonomy, a technique most widely applied to study Immunoglobulin A (IgA-Seq). Previous experiments have scored taxon binding in IgA-Seq datasets by comparing abundances in the IgA bound and unbound sorted fractions. However, as these are relative abundances, such scores are influenced by the levels of the other taxa present and represent an abstract combination of these effects. Diversity in the practical approaches of prior studies also warrants benchmarking of the individual stages involved. Here, we provide a detailed description of the design strategy for an optimised IgA-Seq protocol. Combined with a novel scoring method for IgA-Seq datasets that accounts for the aforementioned effects, this platform enables accurate identification and quantification of commensal gut microbiota targeted by host immunoglobulins.ResultsUsing germ-free and Rag1−/− mice as negative controls, and a strain-specific IgA antibody as a positive control, we determine optimal reagents and fluorescence activated cell sorting (FACS) parameters for IgA-Seq. Using simulated IgA-Seq data, we show that existing IgA-Seq scoring methods are influenced by pre-sort relative abundances. This has consequences for the interpretation of case-control studies where there are inherent differences in microbiota composition between groups. We show that these effects can be addressed using a novel scoring approach based on posterior probabilities. Finally, we demonstrate the utility of both the IgA-Seq protocol and probability-based scores by examining both novel and published data from in vivo disease models.ConclusionsWe provide a detailed IgA-Seq protocol to accurately isolate IgA-bound taxa from intestinal samples. Using simulated and experimental data, we demonstrate novel probability-based scores that adjust for the compositional nature of relative abundance data to accurately quantify taxon-level IgA binding. All scoring approaches are made available in the IgAScores R package. These methods should improve the generation and interpretation of IgA-Seq datasets and could be applied to study other immunoglobulins and sample types.

scholarly journals Dissecting genetic and sex-specific sources of host heterogeneity in pathogen shedding and spread

2021 ◽  
Vol 17 (1) ◽  
pp. e1009196
Author(s):  
Jonathon A. Siva-Jothy ◽  
Pedro F. Vale
Keyword(s):  
Viral Load ◽  
Individual Variation ◽  
Disease Transmission ◽  
Genetic Background ◽  
Pathogen Transmission ◽  
Published Data ◽  
Virus Shedding ◽  
Transmission Potential ◽  
Sources Of Variation ◽  
Host Heterogeneity

Host heterogeneity in disease transmission is widespread but precisely how different host traits drive this heterogeneity remains poorly understood. Part of the difficulty in linking individual variation to population-scale outcomes is that individual hosts can differ on multiple behavioral, physiological and immunological axes, which will together impact their transmission potential. Moreover, we lack well-characterized, empirical systems that enable the quantification of individual variation in key host traits, while also characterizing genetic or sex-based sources of such variation. Here we used Drosophila melanogaster and Drosophila C Virus as a host-pathogen model system to dissect the genetic and sex-specific sources of variation in multiple host traits that are central to pathogen transmission. Our findings show complex interactions between genetic background, sex, and female mating status accounting for a substantial proportion of variance in lifespan following infection, viral load, virus shedding, and viral load at death. Two notable findings include the interaction between genetic background and sex accounting for nearly 20% of the variance in viral load, and genetic background alone accounting for ~10% of the variance in viral shedding and in lifespan following infection. To understand how variation in these traits could generate heterogeneity in individual pathogen transmission potential, we combined measures of lifespan following infection, virus shedding, and previously published data on fly social aggregation. We found that the interaction between genetic background and sex explained ~12% of the variance in individual transmission potential. Our results highlight the importance of characterising the sources of variation in multiple host traits to understand the drivers of heterogeneity in disease transmission.

Dose prescription in SBRT for early-stage non-small cell lung cancer: are we all speaking the same language?

2020 ◽  
pp. 030089162092942
Author(s):  
Anna Merlotti ◽  
Pierluigi Bonomo ◽  
Riccardo Ragona ◽  
Marco Trovò ◽  
Filippo Alongi ◽  
...  
Keyword(s):  
Dose Distribution ◽  
Early Stage ◽  
Organs At Risk ◽  
Optimal Dose ◽  
Target Volume ◽  
Local Tumor Control ◽  
Oncologic Outcomes ◽  
Tumor Control ◽  
Distribution Data ◽  
Published Data

Introduction: Stereotactic body radiation therapy is increasingly used in the treatment of early-stage lung cancers. Guidelines provide indications regarding the constraints to the organs at risk (OARs) and the minimum coverage of the planning target volume but do not suggest optimal dose distribution. Data on dose distribution from the different published series are not comparable due to different prescription modalities and reported dose parameters. Methods: We conducted a review of the published data on dose prescription, focusing on the role of homogeneity on local tumor control, and present suggestions on how to specify and report the prescriptions to permit comparisons between studies or between cases from different centers. Conclusions: To identify the dose-prescription modality that better correlates with oncologic outcomes, future studies should guarantee a close uniformity of dose distribution between cases and complete dose parameters reporting for treatment volumes and OARs.

scholarly journals Accurate identification and quantification of commensal microbiota bound by host immunoglobulins

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Matthew A. Jackson ◽  
Claire Pearson ◽  
Nicholas E. Ilott ◽  
Kelsey E. Huus ◽  
Ahmed N. Hegazy ◽  
...  
Keyword(s):  
Immunoglobulin A ◽  
Amplicon Sequencing ◽  
Positive Control ◽  
Published Data ◽  
Case Control Studies ◽  
Scoring Method ◽  
Accurate Identification ◽  
Relative Abundances ◽  
Identification And Quantification

Abstract Background Identifying which taxa are targeted by immunoglobulins can uncover important host-microbe interactions. Immunoglobulin binding of commensal taxa can be assayed by sorting bound bacteria from samples and using amplicon sequencing to determine their taxonomy, a technique most widely applied to study Immunoglobulin A (IgA-Seq). Previous experiments have scored taxon binding in IgA-Seq datasets by comparing abundances in the IgA bound and unbound sorted fractions. However, as these are relative abundances, such scores are influenced by the levels of the other taxa present and represent an abstract combination of these effects. Diversity in the practical approaches of prior studies also warrants benchmarking of the individual stages involved. Here, we provide a detailed description of the design strategy for an optimised IgA-Seq protocol. Combined with a novel scoring method for IgA-Seq datasets that accounts for the aforementioned effects, this platform enables accurate identification and quantification of commensal gut microbiota targeted by host immunoglobulins. Results Using germ-free and Rag1−/− mice as negative controls, and a strain-specific IgA antibody as a positive control, we determine optimal reagents and fluorescence-activated cell sorting (FACS) parameters for IgA-Seq. Using simulated IgA-Seq data, we show that existing IgA-Seq scoring methods are influenced by pre-sort relative abundances. This has consequences for the interpretation of case-control studies where there are inherent differences in microbiota composition between groups. We show that these effects can be addressed using a novel scoring approach based on posterior probabilities. Finally, we demonstrate the utility of both the IgA-Seq protocol and probability-based scores by examining both novel and published data from in vivo disease models. Conclusions We provide a detailed IgA-Seq protocol to accurately isolate IgA-bound taxa from intestinal samples. Using simulated and experimental data, we demonstrate novel probability-based scores that adjust for the compositional nature of relative abundance data to accurately quantify taxon-level IgA binding. All scoring approaches are made available in the IgAScores R package. These methods should improve the generation and interpretation of IgA-Seq datasets and could be applied to study other immunoglobulins and sample types.

Effect of FGFR2 alterations on survival in patients receiving systemic chemotherapy for intrahepatic cholangiocarcinoma.

2021 ◽  
Vol 39 (3_suppl) ◽  
pp. 303-303
Author(s):  
Ghassan K. Abou-Alfa ◽  
Kristen Bibeau ◽  
Nikolaus Schultz ◽  
Amin Yaqubie ◽  
Brittanie M Millang ◽  
...  
Keyword(s):  
Systemic Chemotherapy ◽  
Progression Free Survival ◽  
Data Interpretation ◽  
Published Data ◽  
Second Line ◽  
Sequencing Data ◽  
First Line ◽  
Second Line Chemotherapy ◽  
Reported Data ◽  
Line Chemotherapy

303 Background: Most patients (pts) with cholangiocarcinoma (CCA) are diagnosed with advanced disease and are ineligible for surgery. FGFR2 fusions/rearrangements are oncogenic drivers and are present almost exclusively in pts with intrahepatic CCA (iCCA; 10–16% of pts); however, little is known about the effects of FGFR2 status on response to systemic chemotherapy. Memorial Sloan Kettering (MSK) obtains genomic sequencing data from almost all iCCA pts treated at the institution. This provides a unique, rich database from which genomic profiling data can be overlaid with clinical data to facilitate a meaningful understanding of pt outcomes, and to suggest potential therapeutic options. This retrospective analysis evaluated progression free survival (PFS) and overall survival (OS) in pts receiving standard systemic chemotherapy (CXT) for iCCA harboring FGFR2 fusions/rearrangements ( FGFR2 +), or harboring wild-type FGFR2 ( FGFR2wt). Methods: Clinical and genomic data were obtained from the MSK database for all iCCA pts to determine disease history and exposure to prior lines (PL) of CXT in the advanced setting. Only pts with complete data for PL of CXT were analyzed. Median PFS and OS were calculated using the Kaplan-Meier method. OS was calculated from diagnosis until death; PFS was calculated from first dose of first line of CXT until progression, death, last visit, relevant dates of later CXT lines; pts with unconfirmed outcomes were censored at last known follow-up date. Results: One-hundred-thirty-two pts were included in this analysis (median age at diagnosis: 62.0 y; 54.5% female; FGFR2+, n = 15; FGFR2wt, n = 115; other FGFR2 alterations, n = 2). Among pts receiving first-line CXT, median PFS was 7.1 months (95% CI: 5.0–8.3) for all pts (n = 124), 6.2 months (2.0–16.8) for FGFR2+ pts (n = 15), and 7.2 months (5.0–8.3) for FGFR2wt pts (n = 107). Among pts with ≥2 PL of CXT (n = 90), median PFS on second-line chemotherapy was 5.6 months (95% CI: 2.8–10.3) for FGFR2+ pts, and 3.7 months (2.6–5.6) for FGFR2wt pts. Median OS was numerically longer in FGFR2+ pts compared with FGFR2wt pts (31.3 months [95% CI: 5.8–not estimable] vs 21.8 months [16.7–26.6]). Conclusions: Among pts receiving standard systemic chemotherapy for iCCA, median PFS was similar in pts harboring FGFR2+ vs FGFR2wt receiving first-line chemotherapy, and relatively longer in pts harboring FGFR2+ receiving second-line chemotherapy. Median OS was longer in FGFR2+ vs FGFR2wt pts. Compared with recently published data in molecularly unselected CCA pts (Lowery. Cancer. 2019; 125: 4426), PFS was similar in pts receiving first-line chemotherapy, and slightly longer for second-line chemotherapy. Data interpretation is limited by the retrospective nature of this analysis of investigator-reported data, the study size, and by the possibility that the analysis population may not reflect the general population of pts with CCA.

Abstract WP331: Identifying Stroke Subtypes with High Accuracy Using Machine Learning and Icd-9 Claims Data

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Charles Esenwa ◽  
Jorge Luna ◽  
Benjamin Kummer ◽  
Hojjat Salmasian ◽  
Hooman Kamel ◽  
...  
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Claims Data ◽  
Detection Algorithm ◽  
Classification And Regression Tree ◽  
Published Data ◽  
Learning Models ◽  
Accurate Identification ◽  
Stroke Subtypes ◽  
Machine Learning Models

Introduction: Stroke research using widely available institutional, state-wide and national retrospective data is dependent on accurate identification of stroke subtypes using claims data. Despite the abundance of such data and the advances in clinical informatics, there is limited published data on the application of machine learning models to improve previously reported administrative stroke identification algorithms. Hypothesis: We hypothesized that machine learning models can be applied to claims data coded using the International Classification of Disease, version 9 (ICD-9), to accuracy identify patients with ischemic stroke (IS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH), and these models would outperform previously published algorithms in our patient cohort. Methods: We developed a gold standard list of 427 stroke patients continuously admitted to our institution from 1/1/2015 to 9/30/2015 using an internal stroke database and applied 75% of it to train and 25% to test two machine learning models: one using classification and regression tree (CART) and another using regularized logistic regression. There were 2,241 negative controls. We further applied a previously reported stroke detection algorithm, by Tirschwell and Longstreth, to our cohort for comparison. Results: The CART model had a κ of 0.72, 0.82, 0.59; sensitivity of 95%, 99%, 99%; and a specificity of 88%, 78%, 75%; for IS, ICH and SAH respectively. The regularized logistic regression model had a κ of 0.73, 0.80, 0.59; sensitivity of 95%, 99%, 99%, and a specificity of 89%, 78%, 75%; for IS, ICH and SAH respectively. The previously reported algorithm by Tirschwell et al, had a κ of 0.71,0.56, 0.64; sensitivity of 98%, 99%, 99%; and a specificity of 64%, 52%, 50%; for IS, ICH and SAH. Conclusion: Compared with the previously reported ICD 9 based detection algorithm, the machine learning models had a higher κ for diagnosis of IS and ICH, similar sensitivity for all subtypes, and higher specificity for all stroke subtypes in our cohort. Applying machine learning models to identify stroke subtypes from administrative data sets, can lead to highly accurate models of stroke subtype identification for health services researchers.

The Interfacial Pressure Distribution and Thermal Conductance of Bolted Joints

1994 ◽  
Vol 116 (4) ◽  
pp. 823-828 ◽  
Author(s):  
M. Mittelbach ◽  
C. Vogd ◽  
L. S. Fletcher ◽  
G. P. Peterson
Keyword(s):  
Pressure Distribution ◽  
Thermal Conductance ◽  
Heat Fluxes ◽  
Bolted Joints ◽  
Interface Temperature ◽  
Distribution Data ◽  
Published Data ◽  
Riveted Joints ◽  
Conductance Data ◽  
Theoretical Predictions

Experimental interface pressure distributions and thermal conductance data are presented for a bolted joint. The variables considered included the bolt torque and associated axial load, the upper and lower plate thicknesses, and the mean interface temperature within the bolt radius. For 7.62-cm-dia Aluminum 6061-T6 plates, axial loads of 6.69 to 13.425 kN (1500 to 3000 lb), three heat fluxes, and mean junction temperatures of up to 310 K were considered. Pressure distribution data obtained with a pressure-sensitive film compared favorably with both theoretical predictions and published experimental data. Thermal conductance data obtained at three radial locations for the bare interface compared favorably with published data. These data also were compared with a previously published correlation for heat transfer in bolted joints. Thermal conductance data for high-conductivity elastomeric gasket materials were obtained to ascertain their suitability for thermal enhancement. The results of this investigation will be useful in the thermal analysis of bolted and riveted joints.

Preparation, Vulcanization, and Characterization of Syndiotactic Trans-1,2-Polypentadiene

1970 ◽  
Vol 43 (4) ◽  
pp. 771-777
Author(s):  
G. S. Fielding-Russell ◽  
G. H. Smith
Keyword(s):  
Physical Properties ◽  
Spectroscopic Analysis ◽  
Crosslinking Agent ◽  
Catalyst System ◽  
Published Data ◽  
Monomer Mixture ◽  
Physical Measurements ◽  
Structural Differences ◽  
Reported Data

Abstract The polymerization, vulcanization, and some physical properties of two syndiotactic trans-1,2 polypentadienes (polypiperylenes) are described. Spectroscopic analysis indicated a significant (≈22%) cis-1,4 structure in the polymer prepared with the Et2AlCl/Co (AcAc)3 catalyst system which, although not in agreement with previously published data, is complementary to recently reported data. It is thought that the presence of water in the catalyst solvent or monomer mixture is responsible for the cis-1,4 content. Water appeared not to influence the Et2AlCl/Co(Octoate)2 polymerization in the same way: a greater than 95% trans-1,2 structure was obtained. Physical measurements on the vulcanizates reflected the structural differences. The copolymer vulcanizate, ≈22% cis-1,4 and ≈78% trans-1,2 structure, was more highly crosslinked than the polymer vulcanizate containing no detectable 1,4 structure. The relative levels and temperature location of the rubbery modulus and the Tg's and loss processes, respectively, are related to the 1,4 content: the vulcanizate containing 1,4 structure shows a higher Tg and rubbery modulus than the vulcanizate containing no detectable 1,4 structure. The inference is that the open copolymer presents a less sterically hindered path to the unsaturation for the bulky crosslinking agent and is therefore more susceptible to vulcanization, giving a tougher rubber that may also be reinforced by crystallization of the cis-1,4 units.

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