Temporal analysis of ion arrival for particle quantification

2021 ◽  
Author(s):  
Andrew M. Duffin ◽  
Edward D. Hoegg ◽  
Ryan I. Sumner ◽  
Trevor Cell ◽  
Gregory C. Eiden ◽  
...  
Keyword(s):  
Temporal Analysis ◽  
Transient Method ◽  
Accurate Identification ◽  
Individual Ion ◽  
Time Stamps ◽  
Particle Quantification ◽  
Identification And Quantification

The rapid transient method records time stamps of individual ion arrival for accurate identification and quantification of nanoparticles.

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 Evaluating Temporal Approximation Methods Using Burglary Data

2020 ◽  
Vol 9 (6) ◽  
pp. 386
Author(s):  
Lukas Oswald ◽  
Michael Leitner
Keyword(s):  
Temporal Analysis ◽  
Approximation Methods ◽  
The Novel ◽  
Occurrence Time ◽  
Criminal Intelligence ◽  
Time Stamps ◽  
Spatio Temporal ◽  
Crime Types ◽  
The City ◽  
Intelligence Service

Law enforcement is very interested in knowing when a crime has happened. Unfortunately, the occurrence time of a crime is often not exactly known. In such circumstances, estimating the most likely time that a crime has happened is crucial for spatio-temporal analysis. The main purpose of this research is to introduce two novel temporal approximation methods, termed retrospective temporal analysis (RTA) and extended retrospective temporal analysis (RTAext). Both methods are compared to six existing temporal approximation methods and subsequently evaluated in order to identify the method that can most accurately estimate the occurrence time of crimes. This research is conducted with 100,000+ burglary crimes from the city of Vienna, Austria provided by the Criminal Intelligence Service Austria, from 2009–2015. The RTA method assumes that crimes in the immediate past occur at very similar times as in the present and in the future. Historical crimes with accurately known time stamps can therefore be applied to estimate when crimes occur in the present/future. The RTAext method enhances one existing temporal approximation method, aoristicext, with probability values derived from historical crime data with accurately known time stamps. The results show that the RTA method performs superiorly to all other temporal approximation methods, including the novel RTAext method, in two out of the three crime types analyzed. Additionally, the RTAext method shows very good results that are similar to the best performing existing approximation methods.

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.

scholarly journals Developing a Real-Time PCR Assay for Direct Identification and Quantification of Pratylenchus penetrans in Soil

Plant Disease ◽  
2017 ◽  
Vol 101 (8) ◽  
pp. 1432-1441 ◽  
Author(s):  
Richard Baidoo ◽  
Guiping Yan ◽  
Seenivasan Nagachandrabose ◽  
Andrea M. Skantar
Keyword(s):  
Nematode Species ◽  
Qpcr Assay ◽  
Control Measures ◽  
Field Soil ◽  
Pratylenchus Penetrans ◽  
Accurate Identification ◽  
Soil P ◽  
Standard Curve ◽  
Efficient Detection ◽  
Identification And Quantification

The root-lesion nematode Pratylenchus penetrans is a major pathogen of potato worldwide. Yield losses may be exacerbated by interaction with the fungus Verticillium dahliae in the potato early dying disease complex. Accurate identification and quantification of P. penetrans prior to planting are essential for developing effective integrated pest control measures. However, distinction between P. penetrans and other Pratylenchus spp. based on morphology is a tedious task. A SYBR Green I-based qPCR assay was developed to discriminate, identify, and quantify P. penetrans in field soil. P. penetrans-specific qPCR primers were designed from the D2-D3 region of the 28S rDNA. The specificity of the assay was evaluated using eight isolates of P. penetrans populations and 31 isolates of other nematode species. A standard curve relating threshold cycle and log values of nematode number was generated from artificially infested soils. There was a high correlation between the P. penetrans numbers artificially added to soil or estimated from naturally infested field soils by conventional methods, and the numbers quantified using the qPCR assay. Grinding the field soil prior to DNA extraction improved P. penetrans detection from soil. The qPCR assay will not only be useful for differentiating P. penetrans from mixed populations of Pratylenchus spp., but also for efficient detection and quantification of P. penetrans from field soil. The assay requires no expertise in nematode taxonomy and morphology, and may serve as a useful diagnostic tool in research, diagnostic labs, and extension services for pest management.

scholarly journals Estimating and predicting the temporal information of apartment burglaries that possess imprecise time stamps: A comparative study using eight different temporal approximation methods in Vienna, Austria

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0253591
Author(s):  
Philip Glasner ◽  
Michael Leitner ◽  
Lukas Oswald
Keyword(s):  
Comparative Study ◽  
Spatiotemporal Analysis ◽  
Temporal Analysis ◽  
Temporal Information ◽  
New Method ◽  
Approximation Methods ◽  
Seasonal Differences ◽  
Crime Data ◽  
Time Stamps ◽  
The One

This research compares and evaluates different approaches to approximate offense times of crimes. It contributes to and extends all previously proposed naïve and aoristic temporal approximation methods and one recent study [1] that showed that the addition of historical crimes with accurately known time stamps to temporal approximation methods can outperform all traditional approximation methods. It is paramount to work with crime data that possess precise temporal information to conduct reliable (spatiotemporal) analysis and modeling. This study contributes to and extends existing studies on temporal analysis. One novel and one relatively new temporal approximation methods are introduced that rely on weighting aoristic scores with historic offenses with exactly known offense times. It is hypothesized that these methods enhance the accuracy of the temporal approximation. In total, eight different methods are evaluated for apartment burglaries in Vienna, Austria, for yearly and seasonal differences. Results show that the one novel and one relatively new method applied in this research outperform all other existing approximation methods to estimate and predict offense times. These two methods are particularly useful for both researchers and practitioners, who often work with temporally imprecise crime data.

scholarly journals NAD tagSeq reveals that NAD+-capped RNAs are mostly produced from a large number of protein-coding genes in Arabidopsis

2019 ◽  
pp. 201903683 ◽  
Author(s):  
Hailei Zhang ◽  
Huan Zhong ◽  
Shoudong Zhang ◽  
Xiaojian Shao ◽  
Min Ni ◽  
...  
Keyword(s):  
Single Molecule ◽  
Enzymatic Reaction ◽  
Accurate Identification ◽  
Protein Coding ◽  
Rna Molecules ◽  
Rna Transcripts ◽  
Protein Coding Genes ◽  
Oxford Nanopore ◽  
Almost All ◽  
Identification And Quantification

The 5′ end of a eukaryotic mRNA transcript generally has a 7-methylguanosine (m7G) cap that protects mRNA from degradation and mediates almost all other aspects of gene expression. Some RNAs in Escherichia coli, yeast, and mammals were recently found to contain an NAD+ cap. Here, we report the development of the method NAD tagSeq for transcriptome-wide identification and quantification of NAD+-capped RNAs (NAD-RNAs). The method uses an enzymatic reaction and then a click chemistry reaction to label NAD-RNAs with a synthetic RNA tag. The tagged RNA molecules can be enriched and directly sequenced using the Oxford Nanopore sequencing technology. NAD tagSeq can allow more accurate identification and quantification of NAD-RNAs, as well as reveal the sequences of whole NAD-RNA transcripts using single-molecule RNA sequencing. Using NAD tagSeq, we found that NAD-RNAs in Arabidopsis were produced by at least several thousand genes, most of which are protein-coding genes, with the majority of these transcripts coming from <200 genes. For some Arabidopsis genes, over 5% of their transcripts were NAD capped. Gene ontology terms overrepresented in the 2,000 genes that produced the highest numbers of NAD-RNAs are related to photosynthesis, protein synthesis, and responses to cytokinin and stresses. The NAD-RNAs in Arabidopsis generally have the same overall sequence structures as the canonical m7G-capped mRNAs, although most of them appear to have a shorter 5′ untranslated region (5′ UTR). The identification and quantification of NAD-RNAs and revelation of their sequence features can provide essential steps toward understanding the functions of NAD-RNAs.

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