ddPCR titration of AAV vectors v2

2021 ◽  
Author(s):  
Addgene The Nonprofit Plasmid Repository
Keyword(s):  
Clear Distinction ◽  
Dilution Series ◽  
Sample Data ◽  
Serial Dilutions

This protocol describes ddPCR titration of AAV vectors. To see the full abstract and additional resources, visit https://www.addgene.org/protocols/aav-ddpcr-titration/. Sample Data: When analyzing data there should be a clear distinction between negative droplets (black) and positive droplets (blue). The no template control (NTC) should be close to zero (B08). At Addgene, runs with an NTC >5 are invalid. To reduce NTC values, we recommend wiping down all pipettes and equipment with 10% bleach prior to use and keeping all reagents and samples on ice or pre-chilled 96-well freezer blocks during use. In this protocol, a dilution series is prepared for each AAV sample and the 3 final dilutions are assayed. The samples that are assayed are diluted 2-fold serially therefore, the concentration obtained by ddPCR should decrease by a factor of 2 across the dilutions. In the example below, 2-fold serial dilutions of a sample were loaded in wells A04, A05 and A06. As shown in the image and table below, the concentration of positive droplets decreases by a factor of ~2. To increase the accuracy of the titer, calculate an average of several dilutions. For additional tips on AAV titering using ddPCR, read our blog post.

The Most Suitable Number of Colonies on Plates for Counting1

1980 ◽  
Vol 43 (4) ◽  
pp. 282-286 ◽  
Author(s):  
DIANE M. TOMASIEWICZ ◽  
DONALD K. HOTCHKISS ◽  
GEORGE W. REINBOLD ◽  
RALSTON B. READ ◽  
PAUL A. HARTMAN
Keyword(s):  
Statistical Methods ◽  
Dairy Products ◽  
Mean Squared Error ◽  
Raw Milk ◽  
Dilution Series ◽  
Squared Error ◽  
Counting Range ◽  
The Mean ◽  
Serial Dilutions

Major events that led to acceptance of 30 to 300 as the most suitable number of colonies on plates for counting were reviewed. Three new sets of data were collected, involving triplicate plates of fifteen 1: 1.4 serial dilutions of 65 samples of raw milk. Statistical methods were developed to analyze bias (variability introduced primarily by crowding and analyst counting errors) and variance (sampling and dilution errors). Bias and variance were combined as mean-squared error, which was expresed as a function of the number of colonies per plate, The counting range that minimized the mean squared error could then be determined for selected dilution series. For two-fold, five-fold and ten-fold dilution series, respectively, the most suitable limits on plates for counting were 70 to 140, 40 to 200 and 25 to 250 colonies/plate. A range of 25 to 250 colonies/plate was suggested for the analysis of dairy products. Limitations in application of the data to other systems are discussed.

scholarly journals Quantification of Enterococci and Human Adenoviruses in Environmental Samples by Real-Time PCR

2005 ◽  
Vol 71 (5) ◽  
pp. 2250-2255 ◽  
Author(s):  
Jian-Wen He ◽  
Sunny Jiang
Keyword(s):  
Real Time ◽  
Real Time Pcr ◽  
Environmental Samples ◽  
Bacterial Culture ◽  
Culture Method ◽  
23S Rrna ◽  
Dilution Series ◽  
Human Adenoviruses ◽  
Standard Curve ◽  
Serial Dilutions

ABSTRACT Pathogenic bacteria and enteric viruses can be introduced into the environment via human waste discharge. Methods for rapid detection and quantification of human viruses and fecal indicator bacteria in water are urgently needed to prevent human exposure to pathogens through drinking and recreational waters. Here we describe the development of two real-time PCR methods to detect and quantify human adenoviruses and enterococci in environmental waters. For real-time quantification of enterococci, a set of primers and a probe targeting the 23S rRNA gene were used. The standard curve generated using Enterococcus faecalis genomic DNA was linear over a 7-log-dilution series. Serial dilutions of E. faecalis suspensions resulted in a lower limit of detection (LLD) of 5 CFU/reaction. To develop real-time PCR for adenoviruses, degenerate primers and a Taqman probe targeting a 163-bp region of the adenovirus hexon gene were designed to specifically amplify 14 different serotypes of human adenoviruses, including enteric adenovirus serotype 40 and 41. The standard curve generated was linear over a 5-log-dilution series, and the LLD was 100 PFU/reaction using serial dilutions of purified adenoviral particles of serotype 40. Both methods were optimized to be applicable to environmental samples. The real-time PCR methods showed a greater sensitivity in detection of adenoviruses in sewage samples than the viral plaque assay and in detection of enterococci in coastal waters than the bacterial culture method. However, enterococcus real-time PCR overestimated the number of bacteria in chlorinated sewage in comparison with the bacterial culture method. Overall, the ability via real-time PCR to detect enterococci and adenoviruses rapidly and quantitatively in the various environmental samples represents a considerable advancement and a great potential for environmental applications.

The Impact of Visual Stereotypes on Judgments about Rape

2016 ◽  
Vol 75 (3) ◽  
pp. 133-140
Author(s):  
Robert Busching ◽  
Johannes Lutz
Keyword(s):  
Mental Representations ◽  
Irrelevant Information ◽  
Clear Distinction ◽  
Rape Myth ◽  
Facial Features ◽  
Reverse Correlation ◽  
Correlation Technique ◽  
Specific Effects ◽  
Legal Judgments ◽  
The Impact

Abstract. Legally irrelevant information like facial features is used to form judgments about rape cases. Using a reverse-correlation technique, it is possible to visualize criminal stereotypes and test whether these representations influence judgments. In the first step, images of the stereotypical faces of a rapist, a thief, and a lifesaver were generated. These images showed a clear distinction between the lifesaver and the two criminal representations, but the criminal representations were rather similar. In the next step, the images were presented together with rape scenarios, and participants (N = 153) indicated the defendant’s level of liability. Participants with high rape myth acceptance scores attributed a lower level of liability to a defendant who resembled a stereotypical lifesaver. However, no specific effects of the image of the stereotypical rapist compared to the stereotypical thief were found. We discuss the findings with respect to the influence of visual stereotypes on legal judgments and the nature of these mental representations.

Reversion Toward the Mean Independently of Regression Toward the Mean

Methodology ◽  
2009 ◽  
Vol 5 (1) ◽  
pp. 3-6 ◽  
Author(s):  
Merton S. Krause
Keyword(s):  
Random Error ◽  
Evaluation Studies ◽  
Internal Validity ◽  
Intervention Evaluation ◽  
Population Mean ◽  
Experimental Intervention ◽  
Sample Data ◽  
The Mean ◽  
Regression Toward The Mean

There is another important artifactual contributor to the apparent improvement of persons subjected to an experimental intervention which may be mistaken for regression toward the mean. This is the phenomenon of random error and extreme selection, which does not at all involve the population regression of posttest on pretest scores but involves a quite different and independent reversion of subjects’ scores toward the population mean. These two independent threats to the internal validity of intervention evaluation studies, however, can be detected and differentiated on the sample data of such studies.

Delivering Sustainable Water Systems Using Kalman Filter and Statistical Approach

2017 ◽  
Vol 4 (1) ◽  
pp. 41-52
Author(s):  
Dedy Loebis
Keyword(s):  
Kalman Filtering ◽  
Statistical Approach ◽  
Water Systems ◽  
Data Sets ◽  
Pressure Data ◽  
Burst Event ◽  
Sample Data ◽  
Other Information ◽  
Supply Systems ◽  
Frequency Features

This paper presents the results of work undertaken to develop and test contrasting data analysis approaches for the detection of bursts/leaks and other anomalies within wate r supply systems at district meter area (DMA)level. This was conducted for Yorkshire Water (YW) sample data sets from the Harrogate and Dales (H&D), Yorkshire, United Kingdom water supply network as part of Project NEPTUNE EP/E003192/1 ). A data analysissystem based on Kalman filtering and statistical approach has been developed. The system has been applied to the analysis of flow and pressure data. The system was proved for one dataset case and have shown the ability to detect anomalies in flow and pres sure patterns, by correlating with other information. It will be shown that the Kalman/statistical approach is a promising approach at detecting subtle changes and higher frequency features, it has the potential to identify precursor features and smaller l eaks and hence could be useful for monitoring the development of leaks, prior to a large volume burst event.

Perancangan Aplikasi Prediksi Kelulusan Tepat Waktu Bagi Mahasiswa Baru Dengan Teknik Data Mining (Studi Kasus: Data Akademik Mahasiswa STMIK Dipanegara Makassar)

2015 ◽  
Vol 1 (4) ◽  
pp. 270
Author(s):  
Muhammad Syukri Mustafa ◽  
I. Wayan Simpen
Keyword(s):  
Data Mining ◽  
Nearest Neighbor ◽  
Test Results ◽  
K Nearest Neighbor ◽  
Accuracy Rate ◽  
Sample Data ◽  
New Students ◽  
K Nearest Neighbor Algorithm ◽  
Using Data ◽  
Existing Data

Penelitian ini dimaksudkan untuk melakukan prediksi terhadap kemungkian mahasiswa baru dapat menyelesaikan studi tepat waktu dengan menggunakan analisis data mining untuk menggali tumpukan histori data dengan menggunakan algoritma K-Nearest Neighbor (KNN). Aplikasi yang dihasilkan pada penelitian ini akan menggunakan berbagai atribut yang klasifikasikan dalam suatu data mining antara lain nilai ujian nasional (UN), asal sekolah/ daerah, jenis kelamin, pekerjaan dan penghasilan orang tua, jumlah bersaudara, dan lain-lain sehingga dengan menerapkan analysis KNN dapat dilakukan suatu prediksi berdasarkan kedekatan histori data yang ada dengan data yang baru, apakah mahasiswa tersebut berpeluang untuk menyelesaikan studi tepat waktu atau tidak. Dari hasil pengujian dengan menerapkan algoritma KNN dan menggunakan data sampel alumni tahun wisuda 2004 s.d. 2010 untuk kasus lama dan data alumni tahun wisuda 2011 untuk kasus baru diperoleh tingkat akurasi sebesar 83,36%.This research is intended to predict the possibility of new students time to complete studies using data mining analysis to explore the history stack data using K-Nearest Neighbor algorithm (KNN). Applications generated in this study will use a variety of attributes in a data mining classified among other Ujian Nasional scores (UN), the origin of the school / area, gender, occupation and income of parents, number of siblings, and others that by applying the analysis KNN can do a prediction based on historical proximity of existing data with new data, whether the student is likely to complete the study on time or not. From the test results by applying the KNN algorithm and uses sample data alumnus graduation year 2004 s.d 2010 for the case of a long and alumni data graduation year 2011 for new cases obtained accuracy rate of 83.36%.

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