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96
Bruker Corporation x ray diffraction xrd tests
X Ray Diffraction Xrd Tests, supplied by Bruker Corporation, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/x ray diffraction xrd tests/product/Bruker Corporation
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x ray diffraction xrd tests - by Bioz Stars, 2026-04
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Cellular Technology Ltd igg immunospot test
Igg Immunospot Test, supplied by Cellular Technology Ltd, used in various techniques. Bioz Stars score: 97/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/igg immunospot test/product/Cellular Technology Ltd
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igg immunospot test - by Bioz Stars, 2026-04
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Cellular Technology Ltd antigen specific b cell immunospot test principles
Rules for the basic evaluation of ImmunoSpot data. ( A – D ) Results are shown for a B cell hybridoma (M-F10-D8) line: ( A , B ) Graphing of spot-forming units (SFUs) described in  with the pan IgG results denoted with blue symbols and the S-antigen-specific assay results with red symbols. Mean ± SD of four replicate wells tested for each condition are shown. Note in panel ( B ) the linearity of SFU counts and the number of hybridoma cells plated per well up to 60 SFU/well, and the flattening of the curve at higher SFU counts seen in panel A resulting from the ELISA effect and SFU crowding observable in  . The extrapolated frequency (panel ( B )) of pan or S-antigen-specific ASC per 10 3 cells plated, along with the coefficient of determination ( R 2 ) of the respective frequency calculations, are denoted in the inset (refer to  ). ( C ) Increasing coefficient of variation (% CV) among replicate wells at SFU counts < 10/well. M-F10-D8 hybridoma cells were plated at decreasing numbers in 48 replicate wells from which the specified % CV was calculated. Note the profound increase in % CV at low SFU counts that is consistent with a Poisson distribution for low frequency events. ( D ) Q–Q plot establishing that a Poisson distribution applies to the observed inter-well variation in M-F10-D8-derived secretory footprints with a mean = 3 SFU/well and SD = 1.7 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.55 and further supports that the observed data fit a Poisson distribution model (refer to  ). ( E – H ) Results obtained testing for S-antigen-specific B mem -derived IgG + ASC following polyclonal stimulation of PBMC isolated from a convalescent donor (LP561) with PCR-verified SARS-CoV-2 infection (refer to  ). The PBMC were serially diluted and input into the S-antigen-specific assay. The SFU counts vs. number of PBMC plated are shown (panel ( E )) with the deviation from linearity clearly visible starting at >75 SFU/well; panel F focuses in on the linear range. Frequency of S-antigen-specific IgG + ASC per 10 5 PBMC plated, along with the R 2 value, is denoted in the inset of panel ( F ). ( G ) Increasing % CV between SFU counts detected in 48 replicate S-antigen-coated wells at decreasing inputs of PBMC from LP561 is shown. ( H ) Q-Q plot establishing that a Poisson distribution applies to the observed inter-well variation in S-antigen-specific IgG + secretory footprints with a mean = 1.6 SFU/well and SD = 1.3 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.24 and further supports that the observed data fit a Poisson distribution model. ( I – L ) Results obtained testing for pan IgG + ASC following polyclonal stimulation of PBMC isolated from a donor (LP667) collected in the post-COVID era (refer to  ). The PBMC were serially diluted and plated in a pan IgG-detecting assay with four replicates per cell input tested. The SFU counts vs. number of PBMC plated are shown in panel ( I ) and the linear section is shown in panel ( J ). Frequency of pan IgG + ASC per 10 5 PBMC plated, together with the R 2 value, is denoted in the inset of panel ( J) . ( K ) Increasing % CV between SFU counts detected in 48 replicate wells at decreasing inputs of PBMC from LP667 is shown. ( L ) Q-Q plot of pan IgG + SFU fitting a Poisson distribution in wells with a mean = 3.8 SFU/well and SD = 2.2 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.76. Collectively, these data establish that all of these Ig-detecting ImmunoSpot results have a Goldilocks range between 10 and up to ~100 SFU/well in which SFU counts are linearly related to the number of ASC present in the test sample, and from which frequencies of ASC can be calculated within all cells plated. At <10 SFU/well, however, stochastic variability inherent with Poisson distributions increasingly introduces uncertainty into the detection of rare events.
Antigen Specific B Cell Immunospot Test Principles, supplied by Cellular Technology Ltd, used in various techniques. Bioz Stars score: 97/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/antigen specific b cell immunospot test principles/product/Cellular Technology Ltd
Average 97 stars, based on 1 article reviews
antigen specific b cell immunospot test principles - by Bioz Stars, 2026-04
97/100 stars
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99
Bio-Rad bio rad image lab software version 6 1 hiv 1 tests
Rules for the basic evaluation of ImmunoSpot data. ( A – D ) Results are shown for a B cell hybridoma (M-F10-D8) line: ( A , B ) Graphing of spot-forming units (SFUs) described in  with the pan IgG results denoted with blue symbols and the S-antigen-specific assay results with red symbols. Mean ± SD of four replicate wells tested for each condition are shown. Note in panel ( B ) the linearity of SFU counts and the number of hybridoma cells plated per well up to 60 SFU/well, and the flattening of the curve at higher SFU counts seen in panel A resulting from the ELISA effect and SFU crowding observable in  . The extrapolated frequency (panel ( B )) of pan or S-antigen-specific ASC per 10 3 cells plated, along with the coefficient of determination ( R 2 ) of the respective frequency calculations, are denoted in the inset (refer to  ). ( C ) Increasing coefficient of variation (% CV) among replicate wells at SFU counts < 10/well. M-F10-D8 hybridoma cells were plated at decreasing numbers in 48 replicate wells from which the specified % CV was calculated. Note the profound increase in % CV at low SFU counts that is consistent with a Poisson distribution for low frequency events. ( D ) Q–Q plot establishing that a Poisson distribution applies to the observed inter-well variation in M-F10-D8-derived secretory footprints with a mean = 3 SFU/well and SD = 1.7 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.55 and further supports that the observed data fit a Poisson distribution model (refer to  ). ( E – H ) Results obtained testing for S-antigen-specific B mem -derived IgG + ASC following polyclonal stimulation of PBMC isolated from a convalescent donor (LP561) with PCR-verified SARS-CoV-2 infection (refer to  ). The PBMC were serially diluted and input into the S-antigen-specific assay. The SFU counts vs. number of PBMC plated are shown (panel ( E )) with the deviation from linearity clearly visible starting at >75 SFU/well; panel F focuses in on the linear range. Frequency of S-antigen-specific IgG + ASC per 10 5 PBMC plated, along with the R 2 value, is denoted in the inset of panel ( F ). ( G ) Increasing % CV between SFU counts detected in 48 replicate S-antigen-coated wells at decreasing inputs of PBMC from LP561 is shown. ( H ) Q-Q plot establishing that a Poisson distribution applies to the observed inter-well variation in S-antigen-specific IgG + secretory footprints with a mean = 1.6 SFU/well and SD = 1.3 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.24 and further supports that the observed data fit a Poisson distribution model. ( I – L ) Results obtained testing for pan IgG + ASC following polyclonal stimulation of PBMC isolated from a donor (LP667) collected in the post-COVID era (refer to  ). The PBMC were serially diluted and plated in a pan IgG-detecting assay with four replicates per cell input tested. The SFU counts vs. number of PBMC plated are shown in panel ( I ) and the linear section is shown in panel ( J ). Frequency of pan IgG + ASC per 10 5 PBMC plated, together with the R 2 value, is denoted in the inset of panel ( J) . ( K ) Increasing % CV between SFU counts detected in 48 replicate wells at decreasing inputs of PBMC from LP667 is shown. ( L ) Q-Q plot of pan IgG + SFU fitting a Poisson distribution in wells with a mean = 3.8 SFU/well and SD = 2.2 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.76. Collectively, these data establish that all of these Ig-detecting ImmunoSpot results have a Goldilocks range between 10 and up to ~100 SFU/well in which SFU counts are linearly related to the number of ASC present in the test sample, and from which frequencies of ASC can be calculated within all cells plated. At <10 SFU/well, however, stochastic variability inherent with Poisson distributions increasingly introduces uncertainty into the detection of rare events.
Bio Rad Image Lab Software Version 6 1 Hiv 1 Tests, supplied by Bio-Rad, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/bio rad image lab software version 6 1 hiv 1 tests/product/Bio-Rad
Average 99 stars, based on 1 article reviews
bio rad image lab software version 6 1 hiv 1 tests - by Bioz Stars, 2026-04
99/100 stars
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90
Instron Corp merlintm material testing software
Rules for the basic evaluation of ImmunoSpot data. ( A – D ) Results are shown for a B cell hybridoma (M-F10-D8) line: ( A , B ) Graphing of spot-forming units (SFUs) described in  with the pan IgG results denoted with blue symbols and the S-antigen-specific assay results with red symbols. Mean ± SD of four replicate wells tested for each condition are shown. Note in panel ( B ) the linearity of SFU counts and the number of hybridoma cells plated per well up to 60 SFU/well, and the flattening of the curve at higher SFU counts seen in panel A resulting from the ELISA effect and SFU crowding observable in  . The extrapolated frequency (panel ( B )) of pan or S-antigen-specific ASC per 10 3 cells plated, along with the coefficient of determination ( R 2 ) of the respective frequency calculations, are denoted in the inset (refer to  ). ( C ) Increasing coefficient of variation (% CV) among replicate wells at SFU counts < 10/well. M-F10-D8 hybridoma cells were plated at decreasing numbers in 48 replicate wells from which the specified % CV was calculated. Note the profound increase in % CV at low SFU counts that is consistent with a Poisson distribution for low frequency events. ( D ) Q–Q plot establishing that a Poisson distribution applies to the observed inter-well variation in M-F10-D8-derived secretory footprints with a mean = 3 SFU/well and SD = 1.7 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.55 and further supports that the observed data fit a Poisson distribution model (refer to  ). ( E – H ) Results obtained testing for S-antigen-specific B mem -derived IgG + ASC following polyclonal stimulation of PBMC isolated from a convalescent donor (LP561) with PCR-verified SARS-CoV-2 infection (refer to  ). The PBMC were serially diluted and input into the S-antigen-specific assay. The SFU counts vs. number of PBMC plated are shown (panel ( E )) with the deviation from linearity clearly visible starting at >75 SFU/well; panel F focuses in on the linear range. Frequency of S-antigen-specific IgG + ASC per 10 5 PBMC plated, along with the R 2 value, is denoted in the inset of panel ( F ). ( G ) Increasing % CV between SFU counts detected in 48 replicate S-antigen-coated wells at decreasing inputs of PBMC from LP561 is shown. ( H ) Q-Q plot establishing that a Poisson distribution applies to the observed inter-well variation in S-antigen-specific IgG + secretory footprints with a mean = 1.6 SFU/well and SD = 1.3 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.24 and further supports that the observed data fit a Poisson distribution model. ( I – L ) Results obtained testing for pan IgG + ASC following polyclonal stimulation of PBMC isolated from a donor (LP667) collected in the post-COVID era (refer to  ). The PBMC were serially diluted and plated in a pan IgG-detecting assay with four replicates per cell input tested. The SFU counts vs. number of PBMC plated are shown in panel ( I ) and the linear section is shown in panel ( J ). Frequency of pan IgG + ASC per 10 5 PBMC plated, together with the R 2 value, is denoted in the inset of panel ( J) . ( K ) Increasing % CV between SFU counts detected in 48 replicate wells at decreasing inputs of PBMC from LP667 is shown. ( L ) Q-Q plot of pan IgG + SFU fitting a Poisson distribution in wells with a mean = 3.8 SFU/well and SD = 2.2 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.76. Collectively, these data establish that all of these Ig-detecting ImmunoSpot results have a Goldilocks range between 10 and up to ~100 SFU/well in which SFU counts are linearly related to the number of ASC present in the test sample, and from which frequencies of ASC can be calculated within all cells plated. At <10 SFU/well, however, stochastic variability inherent with Poisson distributions increasingly introduces uncertainty into the detection of rare events.
Merlintm Material Testing Software, supplied by Instron Corp, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/merlintm material testing software/product/Instron Corp
Average 90 stars, based on 1 article reviews
merlintm material testing software - by Bioz Stars, 2026-04
90/100 stars
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90
OChem Inc toxicity estimation software tool (test)
Rules for the basic evaluation of ImmunoSpot data. ( A – D ) Results are shown for a B cell hybridoma (M-F10-D8) line: ( A , B ) Graphing of spot-forming units (SFUs) described in  with the pan IgG results denoted with blue symbols and the S-antigen-specific assay results with red symbols. Mean ± SD of four replicate wells tested for each condition are shown. Note in panel ( B ) the linearity of SFU counts and the number of hybridoma cells plated per well up to 60 SFU/well, and the flattening of the curve at higher SFU counts seen in panel A resulting from the ELISA effect and SFU crowding observable in  . The extrapolated frequency (panel ( B )) of pan or S-antigen-specific ASC per 10 3 cells plated, along with the coefficient of determination ( R 2 ) of the respective frequency calculations, are denoted in the inset (refer to  ). ( C ) Increasing coefficient of variation (% CV) among replicate wells at SFU counts < 10/well. M-F10-D8 hybridoma cells were plated at decreasing numbers in 48 replicate wells from which the specified % CV was calculated. Note the profound increase in % CV at low SFU counts that is consistent with a Poisson distribution for low frequency events. ( D ) Q–Q plot establishing that a Poisson distribution applies to the observed inter-well variation in M-F10-D8-derived secretory footprints with a mean = 3 SFU/well and SD = 1.7 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.55 and further supports that the observed data fit a Poisson distribution model (refer to  ). ( E – H ) Results obtained testing for S-antigen-specific B mem -derived IgG + ASC following polyclonal stimulation of PBMC isolated from a convalescent donor (LP561) with PCR-verified SARS-CoV-2 infection (refer to  ). The PBMC were serially diluted and input into the S-antigen-specific assay. The SFU counts vs. number of PBMC plated are shown (panel ( E )) with the deviation from linearity clearly visible starting at >75 SFU/well; panel F focuses in on the linear range. Frequency of S-antigen-specific IgG + ASC per 10 5 PBMC plated, along with the R 2 value, is denoted in the inset of panel ( F ). ( G ) Increasing % CV between SFU counts detected in 48 replicate S-antigen-coated wells at decreasing inputs of PBMC from LP561 is shown. ( H ) Q-Q plot establishing that a Poisson distribution applies to the observed inter-well variation in S-antigen-specific IgG + secretory footprints with a mean = 1.6 SFU/well and SD = 1.3 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.24 and further supports that the observed data fit a Poisson distribution model. ( I – L ) Results obtained testing for pan IgG + ASC following polyclonal stimulation of PBMC isolated from a donor (LP667) collected in the post-COVID era (refer to  ). The PBMC were serially diluted and plated in a pan IgG-detecting assay with four replicates per cell input tested. The SFU counts vs. number of PBMC plated are shown in panel ( I ) and the linear section is shown in panel ( J ). Frequency of pan IgG + ASC per 10 5 PBMC plated, together with the R 2 value, is denoted in the inset of panel ( J) . ( K ) Increasing % CV between SFU counts detected in 48 replicate wells at decreasing inputs of PBMC from LP667 is shown. ( L ) Q-Q plot of pan IgG + SFU fitting a Poisson distribution in wells with a mean = 3.8 SFU/well and SD = 2.2 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.76. Collectively, these data establish that all of these Ig-detecting ImmunoSpot results have a Goldilocks range between 10 and up to ~100 SFU/well in which SFU counts are linearly related to the number of ASC present in the test sample, and from which frequencies of ASC can be calculated within all cells plated. At <10 SFU/well, however, stochastic variability inherent with Poisson distributions increasingly introduces uncertainty into the detection of rare events.
Toxicity Estimation Software Tool (Test), supplied by OChem Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/toxicity estimation software tool (test)/product/OChem Inc
Average 90 stars, based on 1 article reviews
toxicity estimation software tool (test) - by Bioz Stars, 2026-04
90/100 stars
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GraphPad Software Inc mannwhitney u test by graphpad prism software
Rules for the basic evaluation of ImmunoSpot data. ( A – D ) Results are shown for a B cell hybridoma (M-F10-D8) line: ( A , B ) Graphing of spot-forming units (SFUs) described in  with the pan IgG results denoted with blue symbols and the S-antigen-specific assay results with red symbols. Mean ± SD of four replicate wells tested for each condition are shown. Note in panel ( B ) the linearity of SFU counts and the number of hybridoma cells plated per well up to 60 SFU/well, and the flattening of the curve at higher SFU counts seen in panel A resulting from the ELISA effect and SFU crowding observable in  . The extrapolated frequency (panel ( B )) of pan or S-antigen-specific ASC per 10 3 cells plated, along with the coefficient of determination ( R 2 ) of the respective frequency calculations, are denoted in the inset (refer to  ). ( C ) Increasing coefficient of variation (% CV) among replicate wells at SFU counts < 10/well. M-F10-D8 hybridoma cells were plated at decreasing numbers in 48 replicate wells from which the specified % CV was calculated. Note the profound increase in % CV at low SFU counts that is consistent with a Poisson distribution for low frequency events. ( D ) Q–Q plot establishing that a Poisson distribution applies to the observed inter-well variation in M-F10-D8-derived secretory footprints with a mean = 3 SFU/well and SD = 1.7 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.55 and further supports that the observed data fit a Poisson distribution model (refer to  ). ( E – H ) Results obtained testing for S-antigen-specific B mem -derived IgG + ASC following polyclonal stimulation of PBMC isolated from a convalescent donor (LP561) with PCR-verified SARS-CoV-2 infection (refer to  ). The PBMC were serially diluted and input into the S-antigen-specific assay. The SFU counts vs. number of PBMC plated are shown (panel ( E )) with the deviation from linearity clearly visible starting at >75 SFU/well; panel F focuses in on the linear range. Frequency of S-antigen-specific IgG + ASC per 10 5 PBMC plated, along with the R 2 value, is denoted in the inset of panel ( F ). ( G ) Increasing % CV between SFU counts detected in 48 replicate S-antigen-coated wells at decreasing inputs of PBMC from LP561 is shown. ( H ) Q-Q plot establishing that a Poisson distribution applies to the observed inter-well variation in S-antigen-specific IgG + secretory footprints with a mean = 1.6 SFU/well and SD = 1.3 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.24 and further supports that the observed data fit a Poisson distribution model. ( I – L ) Results obtained testing for pan IgG + ASC following polyclonal stimulation of PBMC isolated from a donor (LP667) collected in the post-COVID era (refer to  ). The PBMC were serially diluted and plated in a pan IgG-detecting assay with four replicates per cell input tested. The SFU counts vs. number of PBMC plated are shown in panel ( I ) and the linear section is shown in panel ( J ). Frequency of pan IgG + ASC per 10 5 PBMC plated, together with the R 2 value, is denoted in the inset of panel ( J) . ( K ) Increasing % CV between SFU counts detected in 48 replicate wells at decreasing inputs of PBMC from LP667 is shown. ( L ) Q-Q plot of pan IgG + SFU fitting a Poisson distribution in wells with a mean = 3.8 SFU/well and SD = 2.2 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.76. Collectively, these data establish that all of these Ig-detecting ImmunoSpot results have a Goldilocks range between 10 and up to ~100 SFU/well in which SFU counts are linearly related to the number of ASC present in the test sample, and from which frequencies of ASC can be calculated within all cells plated. At <10 SFU/well, however, stochastic variability inherent with Poisson distributions increasingly introduces uncertainty into the detection of rare events.
Mannwhitney U Test By Graphpad Prism Software, supplied by GraphPad Software Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/mannwhitney u test by graphpad prism software/product/GraphPad Software Inc
Average 90 stars, based on 1 article reviews
mannwhitney u test by graphpad prism software - by Bioz Stars, 2026-04
90/100 stars
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ToxRat Solutions GmbH commercial software for the statistical evaluation of standardized ecotoxicological tests
Rules for the basic evaluation of ImmunoSpot data. ( A – D ) Results are shown for a B cell hybridoma (M-F10-D8) line: ( A , B ) Graphing of spot-forming units (SFUs) described in  with the pan IgG results denoted with blue symbols and the S-antigen-specific assay results with red symbols. Mean ± SD of four replicate wells tested for each condition are shown. Note in panel ( B ) the linearity of SFU counts and the number of hybridoma cells plated per well up to 60 SFU/well, and the flattening of the curve at higher SFU counts seen in panel A resulting from the ELISA effect and SFU crowding observable in  . The extrapolated frequency (panel ( B )) of pan or S-antigen-specific ASC per 10 3 cells plated, along with the coefficient of determination ( R 2 ) of the respective frequency calculations, are denoted in the inset (refer to  ). ( C ) Increasing coefficient of variation (% CV) among replicate wells at SFU counts < 10/well. M-F10-D8 hybridoma cells were plated at decreasing numbers in 48 replicate wells from which the specified % CV was calculated. Note the profound increase in % CV at low SFU counts that is consistent with a Poisson distribution for low frequency events. ( D ) Q–Q plot establishing that a Poisson distribution applies to the observed inter-well variation in M-F10-D8-derived secretory footprints with a mean = 3 SFU/well and SD = 1.7 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.55 and further supports that the observed data fit a Poisson distribution model (refer to  ). ( E – H ) Results obtained testing for S-antigen-specific B mem -derived IgG + ASC following polyclonal stimulation of PBMC isolated from a convalescent donor (LP561) with PCR-verified SARS-CoV-2 infection (refer to  ). The PBMC were serially diluted and input into the S-antigen-specific assay. The SFU counts vs. number of PBMC plated are shown (panel ( E )) with the deviation from linearity clearly visible starting at >75 SFU/well; panel F focuses in on the linear range. Frequency of S-antigen-specific IgG + ASC per 10 5 PBMC plated, along with the R 2 value, is denoted in the inset of panel ( F ). ( G ) Increasing % CV between SFU counts detected in 48 replicate S-antigen-coated wells at decreasing inputs of PBMC from LP561 is shown. ( H ) Q-Q plot establishing that a Poisson distribution applies to the observed inter-well variation in S-antigen-specific IgG + secretory footprints with a mean = 1.6 SFU/well and SD = 1.3 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.24 and further supports that the observed data fit a Poisson distribution model. ( I – L ) Results obtained testing for pan IgG + ASC following polyclonal stimulation of PBMC isolated from a donor (LP667) collected in the post-COVID era (refer to  ). The PBMC were serially diluted and plated in a pan IgG-detecting assay with four replicates per cell input tested. The SFU counts vs. number of PBMC plated are shown in panel ( I ) and the linear section is shown in panel ( J ). Frequency of pan IgG + ASC per 10 5 PBMC plated, together with the R 2 value, is denoted in the inset of panel ( J) . ( K ) Increasing % CV between SFU counts detected in 48 replicate wells at decreasing inputs of PBMC from LP667 is shown. ( L ) Q-Q plot of pan IgG + SFU fitting a Poisson distribution in wells with a mean = 3.8 SFU/well and SD = 2.2 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.76. Collectively, these data establish that all of these Ig-detecting ImmunoSpot results have a Goldilocks range between 10 and up to ~100 SFU/well in which SFU counts are linearly related to the number of ASC present in the test sample, and from which frequencies of ASC can be calculated within all cells plated. At <10 SFU/well, however, stochastic variability inherent with Poisson distributions increasingly introduces uncertainty into the detection of rare events.
Commercial Software For The Statistical Evaluation Of Standardized Ecotoxicological Tests, supplied by ToxRat Solutions GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/commercial software for the statistical evaluation of standardized ecotoxicological tests/product/ToxRat Solutions GmbH
Average 90 stars, based on 1 article reviews
commercial software for the statistical evaluation of standardized ecotoxicological tests - by Bioz Stars, 2026-04
90/100 stars
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90
STATA Corporation egger test stata 17.0 software
Rules for the basic evaluation of ImmunoSpot data. ( A – D ) Results are shown for a B cell hybridoma (M-F10-D8) line: ( A , B ) Graphing of spot-forming units (SFUs) described in  with the pan IgG results denoted with blue symbols and the S-antigen-specific assay results with red symbols. Mean ± SD of four replicate wells tested for each condition are shown. Note in panel ( B ) the linearity of SFU counts and the number of hybridoma cells plated per well up to 60 SFU/well, and the flattening of the curve at higher SFU counts seen in panel A resulting from the ELISA effect and SFU crowding observable in  . The extrapolated frequency (panel ( B )) of pan or S-antigen-specific ASC per 10 3 cells plated, along with the coefficient of determination ( R 2 ) of the respective frequency calculations, are denoted in the inset (refer to  ). ( C ) Increasing coefficient of variation (% CV) among replicate wells at SFU counts < 10/well. M-F10-D8 hybridoma cells were plated at decreasing numbers in 48 replicate wells from which the specified % CV was calculated. Note the profound increase in % CV at low SFU counts that is consistent with a Poisson distribution for low frequency events. ( D ) Q–Q plot establishing that a Poisson distribution applies to the observed inter-well variation in M-F10-D8-derived secretory footprints with a mean = 3 SFU/well and SD = 1.7 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.55 and further supports that the observed data fit a Poisson distribution model (refer to  ). ( E – H ) Results obtained testing for S-antigen-specific B mem -derived IgG + ASC following polyclonal stimulation of PBMC isolated from a convalescent donor (LP561) with PCR-verified SARS-CoV-2 infection (refer to  ). The PBMC were serially diluted and input into the S-antigen-specific assay. The SFU counts vs. number of PBMC plated are shown (panel ( E )) with the deviation from linearity clearly visible starting at >75 SFU/well; panel F focuses in on the linear range. Frequency of S-antigen-specific IgG + ASC per 10 5 PBMC plated, along with the R 2 value, is denoted in the inset of panel ( F ). ( G ) Increasing % CV between SFU counts detected in 48 replicate S-antigen-coated wells at decreasing inputs of PBMC from LP561 is shown. ( H ) Q-Q plot establishing that a Poisson distribution applies to the observed inter-well variation in S-antigen-specific IgG + secretory footprints with a mean = 1.6 SFU/well and SD = 1.3 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.24 and further supports that the observed data fit a Poisson distribution model. ( I – L ) Results obtained testing for pan IgG + ASC following polyclonal stimulation of PBMC isolated from a donor (LP667) collected in the post-COVID era (refer to  ). The PBMC were serially diluted and plated in a pan IgG-detecting assay with four replicates per cell input tested. The SFU counts vs. number of PBMC plated are shown in panel ( I ) and the linear section is shown in panel ( J ). Frequency of pan IgG + ASC per 10 5 PBMC plated, together with the R 2 value, is denoted in the inset of panel ( J) . ( K ) Increasing % CV between SFU counts detected in 48 replicate wells at decreasing inputs of PBMC from LP667 is shown. ( L ) Q-Q plot of pan IgG + SFU fitting a Poisson distribution in wells with a mean = 3.8 SFU/well and SD = 2.2 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.76. Collectively, these data establish that all of these Ig-detecting ImmunoSpot results have a Goldilocks range between 10 and up to ~100 SFU/well in which SFU counts are linearly related to the number of ASC present in the test sample, and from which frequencies of ASC can be calculated within all cells plated. At <10 SFU/well, however, stochastic variability inherent with Poisson distributions increasingly introduces uncertainty into the detection of rare events.
Egger Test Stata 17.0 Software, supplied by STATA Corporation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/egger test stata 17.0 software/product/STATA Corporation
Average 90 stars, based on 1 article reviews
egger test stata 17.0 software - by Bioz Stars, 2026-04
90/100 stars
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Rules for the basic evaluation of ImmunoSpot data. ( A – D ) Results are shown for a B cell hybridoma (M-F10-D8) line: ( A , B ) Graphing of spot-forming units (SFUs) described in  with the pan IgG results denoted with blue symbols and the S-antigen-specific assay results with red symbols. Mean ± SD of four replicate wells tested for each condition are shown. Note in panel ( B ) the linearity of SFU counts and the number of hybridoma cells plated per well up to 60 SFU/well, and the flattening of the curve at higher SFU counts seen in panel A resulting from the ELISA effect and SFU crowding observable in  . The extrapolated frequency (panel ( B )) of pan or S-antigen-specific ASC per 10 3 cells plated, along with the coefficient of determination ( R 2 ) of the respective frequency calculations, are denoted in the inset (refer to  ). ( C ) Increasing coefficient of variation (% CV) among replicate wells at SFU counts < 10/well. M-F10-D8 hybridoma cells were plated at decreasing numbers in 48 replicate wells from which the specified % CV was calculated. Note the profound increase in % CV at low SFU counts that is consistent with a Poisson distribution for low frequency events. ( D ) Q–Q plot establishing that a Poisson distribution applies to the observed inter-well variation in M-F10-D8-derived secretory footprints with a mean = 3 SFU/well and SD = 1.7 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.55 and further supports that the observed data fit a Poisson distribution model (refer to  ). ( E – H ) Results obtained testing for S-antigen-specific B mem -derived IgG + ASC following polyclonal stimulation of PBMC isolated from a convalescent donor (LP561) with PCR-verified SARS-CoV-2 infection (refer to  ). The PBMC were serially diluted and input into the S-antigen-specific assay. The SFU counts vs. number of PBMC plated are shown (panel ( E )) with the deviation from linearity clearly visible starting at >75 SFU/well; panel F focuses in on the linear range. Frequency of S-antigen-specific IgG + ASC per 10 5 PBMC plated, along with the R 2 value, is denoted in the inset of panel ( F ). ( G ) Increasing % CV between SFU counts detected in 48 replicate S-antigen-coated wells at decreasing inputs of PBMC from LP561 is shown. ( H ) Q-Q plot establishing that a Poisson distribution applies to the observed inter-well variation in S-antigen-specific IgG + secretory footprints with a mean = 1.6 SFU/well and SD = 1.3 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.24 and further supports that the observed data fit a Poisson distribution model. ( I – L ) Results obtained testing for pan IgG + ASC following polyclonal stimulation of PBMC isolated from a donor (LP667) collected in the post-COVID era (refer to  ). The PBMC were serially diluted and plated in a pan IgG-detecting assay with four replicates per cell input tested. The SFU counts vs. number of PBMC plated are shown in panel ( I ) and the linear section is shown in panel ( J ). Frequency of pan IgG + ASC per 10 5 PBMC plated, together with the R 2 value, is denoted in the inset of panel ( J) . ( K ) Increasing % CV between SFU counts detected in 48 replicate wells at decreasing inputs of PBMC from LP667 is shown. ( L ) Q-Q plot of pan IgG + SFU fitting a Poisson distribution in wells with a mean = 3.8 SFU/well and SD = 2.2 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.76. Collectively, these data establish that all of these Ig-detecting ImmunoSpot results have a Goldilocks range between 10 and up to ~100 SFU/well in which SFU counts are linearly related to the number of ASC present in the test sample, and from which frequencies of ASC can be calculated within all cells plated. At <10 SFU/well, however, stochastic variability inherent with Poisson distributions increasingly introduces uncertainty into the detection of rare events.

Journal: Vaccines

Article Title: Extending ImmunoSpot ® Assays’ Sensitivity for Detecting Rare Antigen-Specific B Cells to One in a Million—And Possibly Lower

doi: 10.3390/vaccines14010088

Figure Lengend Snippet: Rules for the basic evaluation of ImmunoSpot data. ( A – D ) Results are shown for a B cell hybridoma (M-F10-D8) line: ( A , B ) Graphing of spot-forming units (SFUs) described in with the pan IgG results denoted with blue symbols and the S-antigen-specific assay results with red symbols. Mean ± SD of four replicate wells tested for each condition are shown. Note in panel ( B ) the linearity of SFU counts and the number of hybridoma cells plated per well up to 60 SFU/well, and the flattening of the curve at higher SFU counts seen in panel A resulting from the ELISA effect and SFU crowding observable in . The extrapolated frequency (panel ( B )) of pan or S-antigen-specific ASC per 10 3 cells plated, along with the coefficient of determination ( R 2 ) of the respective frequency calculations, are denoted in the inset (refer to ). ( C ) Increasing coefficient of variation (% CV) among replicate wells at SFU counts < 10/well. M-F10-D8 hybridoma cells were plated at decreasing numbers in 48 replicate wells from which the specified % CV was calculated. Note the profound increase in % CV at low SFU counts that is consistent with a Poisson distribution for low frequency events. ( D ) Q–Q plot establishing that a Poisson distribution applies to the observed inter-well variation in M-F10-D8-derived secretory footprints with a mean = 3 SFU/well and SD = 1.7 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.55 and further supports that the observed data fit a Poisson distribution model (refer to ). ( E – H ) Results obtained testing for S-antigen-specific B mem -derived IgG + ASC following polyclonal stimulation of PBMC isolated from a convalescent donor (LP561) with PCR-verified SARS-CoV-2 infection (refer to ). The PBMC were serially diluted and input into the S-antigen-specific assay. The SFU counts vs. number of PBMC plated are shown (panel ( E )) with the deviation from linearity clearly visible starting at >75 SFU/well; panel F focuses in on the linear range. Frequency of S-antigen-specific IgG + ASC per 10 5 PBMC plated, along with the R 2 value, is denoted in the inset of panel ( F ). ( G ) Increasing % CV between SFU counts detected in 48 replicate S-antigen-coated wells at decreasing inputs of PBMC from LP561 is shown. ( H ) Q-Q plot establishing that a Poisson distribution applies to the observed inter-well variation in S-antigen-specific IgG + secretory footprints with a mean = 1.6 SFU/well and SD = 1.3 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.24 and further supports that the observed data fit a Poisson distribution model. ( I – L ) Results obtained testing for pan IgG + ASC following polyclonal stimulation of PBMC isolated from a donor (LP667) collected in the post-COVID era (refer to ). The PBMC were serially diluted and plated in a pan IgG-detecting assay with four replicates per cell input tested. The SFU counts vs. number of PBMC plated are shown in panel ( I ) and the linear section is shown in panel ( J ). Frequency of pan IgG + ASC per 10 5 PBMC plated, together with the R 2 value, is denoted in the inset of panel ( J) . ( K ) Increasing % CV between SFU counts detected in 48 replicate wells at decreasing inputs of PBMC from LP667 is shown. ( L ) Q-Q plot of pan IgG + SFU fitting a Poisson distribution in wells with a mean = 3.8 SFU/well and SD = 2.2 SFU/well. Chi-square goodness of fit test for a continuous probability distribution yielded a p -value = 0.76. Collectively, these data establish that all of these Ig-detecting ImmunoSpot results have a Goldilocks range between 10 and up to ~100 SFU/well in which SFU counts are linearly related to the number of ASC present in the test sample, and from which frequencies of ASC can be calculated within all cells plated. At <10 SFU/well, however, stochastic variability inherent with Poisson distributions increasingly introduces uncertainty into the detection of rare events.

Article Snippet: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/vaccines14010088/s1 , Figure S1: Illustration of pan (total) and antigen-specific B cell ImmunoSpot ® test principles; Figure S2: Frequency calculations of S-antigen-specific B mem -derived IgG + ASCs in post-COVID era donors; Figure S3: Serial dilution of donor PBMC permits measurements of pan (total) IgG + ASCs; Figure S4: Frequency calculations of pan IgG + ASCs in post-COVID era donors; Figure S5: Power analysis enables prediction of replicate wells required to measure low frequencies of antigen-specific ASCs with defined level of precision; Figure S6: Crowding of third-party PBMC interferes with detection of secretory footprints in ImmunoSpot assays; Figure S7: Images depicting low-affinity vs. high-affinity NCAP-reactive IgG + secretory footprints at higher magnification; Figure S8: High resolution ImmunoSpot testing for influenza H1-specific B mem -derived IgG + ASCs; Figure S9: High resolution ImmunoSpot testing for influenza B HA-specific B mem -derived IgG + ASCs; Table S1: Donor demographics; Table S2: Viral antigen-specific B mem -derived IgG + ASC frequencies vary considerably between individual donors; Table S3: Increasing the number of PBMC plated per well does not result in a proportional increase in NCAP-specific IgG + SFU.

Techniques: Enzyme-linked Immunosorbent Assay, Derivative Assay, Isolation, Infection

S-antigen-specific B mem -derived IgG + ASC occur at relatively high frequencies among PBMC isolated from post-COVID era donors. A representative ELISPOT plate overview depicting testing of 12 donors collected in the post-COVID era (refer to  ) for S-antigen-specific B mem -derived IgG + ASC using a singlet serial dilution approach. The assay principle is illustrated in  . For each donor, the two-fold (1 + 1) serial dilution was initiated at 2 × 10 5 PBMC/well, as specified. The raw images and machine-assisted automated SFU counts are shown in the top left corner for each well. The ImmunoSpot ® Studio.SC software (refer to  ) automatically denotes wells yielding SFU counts within a defined upper and lower bound with green shading; for this assay plate 15 to 100 SFU/well. Using contiguous datapoints within the so-called “Goldilocks range” the software automatically calculates the frequency of ASC within all PBMC tested; the autogenerated frequency calculations for donors yielding three or more datapoints within the defined upper and lower SFU range are shown in  . The data highlight that frequencies of S-antigen-specific B mem -derived IgG + ASC span a wide range in healthy individuals, requiring the serial dilution strategy for accurate calculations for most donors; however, in 3 of the 12 donors the number of SFUs detected was too low for frequency calculations using this strategy.

Journal: Vaccines

Article Title: Extending ImmunoSpot ® Assays’ Sensitivity for Detecting Rare Antigen-Specific B Cells to One in a Million—And Possibly Lower

doi: 10.3390/vaccines14010088

Figure Lengend Snippet: S-antigen-specific B mem -derived IgG + ASC occur at relatively high frequencies among PBMC isolated from post-COVID era donors. A representative ELISPOT plate overview depicting testing of 12 donors collected in the post-COVID era (refer to ) for S-antigen-specific B mem -derived IgG + ASC using a singlet serial dilution approach. The assay principle is illustrated in . For each donor, the two-fold (1 + 1) serial dilution was initiated at 2 × 10 5 PBMC/well, as specified. The raw images and machine-assisted automated SFU counts are shown in the top left corner for each well. The ImmunoSpot ® Studio.SC software (refer to ) automatically denotes wells yielding SFU counts within a defined upper and lower bound with green shading; for this assay plate 15 to 100 SFU/well. Using contiguous datapoints within the so-called “Goldilocks range” the software automatically calculates the frequency of ASC within all PBMC tested; the autogenerated frequency calculations for donors yielding three or more datapoints within the defined upper and lower SFU range are shown in . The data highlight that frequencies of S-antigen-specific B mem -derived IgG + ASC span a wide range in healthy individuals, requiring the serial dilution strategy for accurate calculations for most donors; however, in 3 of the 12 donors the number of SFUs detected was too low for frequency calculations using this strategy.

Article Snippet: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/vaccines14010088/s1 , Figure S1: Illustration of pan (total) and antigen-specific B cell ImmunoSpot ® test principles; Figure S2: Frequency calculations of S-antigen-specific B mem -derived IgG + ASCs in post-COVID era donors; Figure S3: Serial dilution of donor PBMC permits measurements of pan (total) IgG + ASCs; Figure S4: Frequency calculations of pan IgG + ASCs in post-COVID era donors; Figure S5: Power analysis enables prediction of replicate wells required to measure low frequencies of antigen-specific ASCs with defined level of precision; Figure S6: Crowding of third-party PBMC interferes with detection of secretory footprints in ImmunoSpot assays; Figure S7: Images depicting low-affinity vs. high-affinity NCAP-reactive IgG + secretory footprints at higher magnification; Figure S8: High resolution ImmunoSpot testing for influenza H1-specific B mem -derived IgG + ASCs; Figure S9: High resolution ImmunoSpot testing for influenza B HA-specific B mem -derived IgG + ASCs; Table S1: Donor demographics; Table S2: Viral antigen-specific B mem -derived IgG + ASC frequencies vary considerably between individual donors; Table S3: Increasing the number of PBMC plated per well does not result in a proportional increase in NCAP-specific IgG + SFU.

Techniques: Derivative Assay, Isolation, Enzyme-linked Immunospot, Serial Dilution, Software

Near complete absence of S-antigen-reactive IgG + SFU in pre-COVID era subjects compared to a verified SARS-CoV-2 infected donor. Raw data are shown from an S-antigen-specific ImmunoSpot assay in which pre-COVID era PBMC samples were plated into 10 replicate wells at 2 × 10 5 cells/well. LP565 served as an assay-specific positive control and owing to their elevated frequency of S-antigen-specific B mem -derived IgG + ASC PBMC were instead plated at 5 × 10 4 cells/well (denoted by an asterisk).

Journal: Vaccines

Article Title: Extending ImmunoSpot ® Assays’ Sensitivity for Detecting Rare Antigen-Specific B Cells to One in a Million—And Possibly Lower

doi: 10.3390/vaccines14010088

Figure Lengend Snippet: Near complete absence of S-antigen-reactive IgG + SFU in pre-COVID era subjects compared to a verified SARS-CoV-2 infected donor. Raw data are shown from an S-antigen-specific ImmunoSpot assay in which pre-COVID era PBMC samples were plated into 10 replicate wells at 2 × 10 5 cells/well. LP565 served as an assay-specific positive control and owing to their elevated frequency of S-antigen-specific B mem -derived IgG + ASC PBMC were instead plated at 5 × 10 4 cells/well (denoted by an asterisk).

Article Snippet: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/vaccines14010088/s1 , Figure S1: Illustration of pan (total) and antigen-specific B cell ImmunoSpot ® test principles; Figure S2: Frequency calculations of S-antigen-specific B mem -derived IgG + ASCs in post-COVID era donors; Figure S3: Serial dilution of donor PBMC permits measurements of pan (total) IgG + ASCs; Figure S4: Frequency calculations of pan IgG + ASCs in post-COVID era donors; Figure S5: Power analysis enables prediction of replicate wells required to measure low frequencies of antigen-specific ASCs with defined level of precision; Figure S6: Crowding of third-party PBMC interferes with detection of secretory footprints in ImmunoSpot assays; Figure S7: Images depicting low-affinity vs. high-affinity NCAP-reactive IgG + secretory footprints at higher magnification; Figure S8: High resolution ImmunoSpot testing for influenza H1-specific B mem -derived IgG + ASCs; Figure S9: High resolution ImmunoSpot testing for influenza B HA-specific B mem -derived IgG + ASCs; Table S1: Donor demographics; Table S2: Viral antigen-specific B mem -derived IgG + ASC frequencies vary considerably between individual donors; Table S3: Increasing the number of PBMC plated per well does not result in a proportional increase in NCAP-specific IgG + SFU.

Techniques: Infection, Positive Control, Derivative Assay

Detection of pristine influenza (H3)-specific B mem -derived IgG + SFU in pre-COVID era donors. Raw data are shown from an ImmunoSpot assay in which pre-COVID era donors were seeded at 2 × 10 5 PBMC/well into wells coated with recombinant hemagglutinin (rHA) protein representing a seasonal H3N2 vaccine strain (A/Texas/2012). Assay specifics were otherwise identical to those in  . Notably, while frequencies of influenza H3-specific IgG + SFU were variable among the pre-COVID era donors shown, they were detectable in all subjects and were crisp and dense, i.e., reflective of high-affinity antibody binding. Moreover, these data highlight that increasing the number of replicate wells, and cumulatively the number of PBMC interrogated, in a B cell ImmunoSpot test is a universal strategy for improving the limit of detection for rare antigen-specific B mem —even in the absence of available negative controls.

Journal: Vaccines

Article Title: Extending ImmunoSpot ® Assays’ Sensitivity for Detecting Rare Antigen-Specific B Cells to One in a Million—And Possibly Lower

doi: 10.3390/vaccines14010088

Figure Lengend Snippet: Detection of pristine influenza (H3)-specific B mem -derived IgG + SFU in pre-COVID era donors. Raw data are shown from an ImmunoSpot assay in which pre-COVID era donors were seeded at 2 × 10 5 PBMC/well into wells coated with recombinant hemagglutinin (rHA) protein representing a seasonal H3N2 vaccine strain (A/Texas/2012). Assay specifics were otherwise identical to those in . Notably, while frequencies of influenza H3-specific IgG + SFU were variable among the pre-COVID era donors shown, they were detectable in all subjects and were crisp and dense, i.e., reflective of high-affinity antibody binding. Moreover, these data highlight that increasing the number of replicate wells, and cumulatively the number of PBMC interrogated, in a B cell ImmunoSpot test is a universal strategy for improving the limit of detection for rare antigen-specific B mem —even in the absence of available negative controls.

Article Snippet: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/vaccines14010088/s1 , Figure S1: Illustration of pan (total) and antigen-specific B cell ImmunoSpot ® test principles; Figure S2: Frequency calculations of S-antigen-specific B mem -derived IgG + ASCs in post-COVID era donors; Figure S3: Serial dilution of donor PBMC permits measurements of pan (total) IgG + ASCs; Figure S4: Frequency calculations of pan IgG + ASCs in post-COVID era donors; Figure S5: Power analysis enables prediction of replicate wells required to measure low frequencies of antigen-specific ASCs with defined level of precision; Figure S6: Crowding of third-party PBMC interferes with detection of secretory footprints in ImmunoSpot assays; Figure S7: Images depicting low-affinity vs. high-affinity NCAP-reactive IgG + secretory footprints at higher magnification; Figure S8: High resolution ImmunoSpot testing for influenza H1-specific B mem -derived IgG + ASCs; Figure S9: High resolution ImmunoSpot testing for influenza B HA-specific B mem -derived IgG + ASCs; Table S1: Donor demographics; Table S2: Viral antigen-specific B mem -derived IgG + ASC frequencies vary considerably between individual donors; Table S3: Increasing the number of PBMC plated per well does not result in a proportional increase in NCAP-specific IgG + SFU.

Techniques: Derivative Assay, Recombinant, Binding Assay