https://wiki.oroboros.at/api.php?action=feedcontributions&user=Iglesias-Gonzalez+Javier&feedformat=atom
Bioblast - User contributions [en]
2024-03-28T20:09:31Z
User contributions
MediaWiki 1.36.1
https://wiki.oroboros.at/index.php?title=Bartlett_2008_Ultrasound_Obstet_Gynecol&diff=214656
Bartlett 2008 Ultrasound Obstet Gynecol
2021-01-27T14:52:35Z
<p>Iglesias-Gonzalez Javier: /* Selected text quotes */</p>
<hr />
<div>{{Publication<br />
|title=Bartlett JW, Frost C (2008) Reliability, repeatability and reproducibility: analysis of measurement errors in continuous variables. Ultrasound Obstet Gynecol 31:466-475.<br />
|info=[[PMID: 18306169]]<br />
|authors=Bartlett JW, Frost C<br />
|year=2008<br />
|journal=Ultrasound Obstet Gynecol<br />
|keywords=agreement; measurement error; method comparison; reliability; repeatability; reproducibility<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Selected text quotes ==<br />
::::* Reliability relates the magnitude of the measurement error in observed measurements to the inherent variability in the ‘error-free’, ‘true’, or underlying level of the quantity between subjects. <br />
<br />
::::*It is also known as the intraclass correlation, as it equals the correlation between any two measurements made on the same subject.Reliability takes values between zero and one, with a value of one corresponding to zero measurement error and a value of zero meaning that all the variability in measurements is due to measurement error.<br />
<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Bartlett_2008_Ultrasound_Obstet_Gynecol&diff=214655
Bartlett 2008 Ultrasound Obstet Gynecol
2021-01-27T14:52:25Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Bartlett JW, Frost C (2008) Reliability, repeatability and reproducibility: analysis of measurement errors in continuous variables. Ultrasound Obstet Gynecol 31:466-475.<br />
|info=[[PMID: 18306169]]<br />
|authors=Bartlett JW, Frost C<br />
|year=2008<br />
|journal=Ultrasound Obstet Gynecol<br />
|keywords=agreement; measurement error; method comparison; reliability; repeatability; reproducibility<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Selected text quotes ==<br />
::::* Reliability relates the magnitude of the measurement error in observed measurements to the inherent variability in the ‘error-free’, ‘true’, or underlying level of the quantity between subjects. <br />
<br />
::::*It is also known as the intraclass correlation, as it equals the correlation between any two measurements made on the same subject.Reliability takes values between zero and one, with a value of one corresponding to zero measurement error and a value of<br />
zero meaning that all the variability in measurements is due to measurement error.<br />
<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Reliability&diff=214651
Reliability
2021-01-27T14:50:09Z
<p>Iglesias-Gonzalez Javier: Created page with "{{MitoPedia |description='''Reliability''' relates the magnitude of the measurement error in observed measurements (i.e., precision or intermediate precision) to the inherent..."</p>
<hr />
<div>{{MitoPedia<br />
|description='''Reliability''' relates the magnitude of the measurement error in observed measurements (i.e., precision or intermediate precision) to the inherent variability in the ‘error-free’, ‘true’, or underlying level of the quantity between subjects. The value of the reliability takes a value between 0 and 1. When the variability value is zero, indicates that all the variability in the measurements is due to measurement error. And, on the contrary, when the value is 1 indicates that there is a zero error in the measurement error. It is also known as the intraclass correlation, as it equals the correlation between any two measurements made on the same subject.<br />
|info=[[Bartlett 2008 Ultrasound Obstet Gynecol]]<br />
}}<br />
{{MitoPedia concepts<br />
|mitopedia concept=MitoFit Quality Control System<br />
}}<br />
{{MitoPedia methods}}<br />
{{MitoPedia O2k and high-resolution respirometry}}<br />
{{MitoPedia topics}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Hekimo%C4%9Flu_2005&diff=214578
Hekimoğlu 2005
2021-01-26T12:59:52Z
<p>Iglesias-Gonzalez Javier: Iglesias-Gonzalez Javier moved page Hekimoğlu 2005 to Hekimoğlu 2005 zfv</p>
<hr />
<div>#REDIRECT [[Hekimoğlu 2005 zfv]]</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Hekimo%C4%9Flu_2005_zfv&diff=214577
Hekimoğlu 2005 zfv
2021-01-26T12:59:52Z
<p>Iglesias-Gonzalez Javier: Iglesias-Gonzalez Javier moved page Hekimoğlu 2005 to Hekimoğlu 2005 zfv</p>
<hr />
<div>{{Publication<br />
|title=Hekimoğlu S (2005) Do robust methods identify outliers more reliably than conventional tests for outliers?. zfv 130(3):174-180.<br />
|info=[https://www.semanticscholar.org/paper/Do-Robust-Methods-Identify-Outliniers-More-Reliably-Hekimo%C4%9Flu/6082da238036c8509a0e991089ec4fa929ed862c Open Access]<br />
|authors=Hekimoğlu S<br />
|year=2005<br />
|journal=zfv<br />
|abstract=In order to identify outliers, there are two approaches: the conventional tests for outliers and robust methods. Statisticians working with robust methods argue that their results are more reliable than the conventional tests for outliers. Which one of these approaches is more reliable? This question is investigated here in view of the problems caused by masking effects, swamping effects and leverage points and discussed by simulated linear regression models. The mean success rate is used to compare the two approaches. Summarizing, the robust methods can identify outliers at a rate of 22% more reliably than the conventional test for outliers in a simple regression.<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Analytical_2016&diff=214576
Analytical 2016
2021-01-26T12:47:48Z
<p>Iglesias-Gonzalez Javier: Iglesias-Gonzalez Javier moved page Analytical 2016 to AMCTB 2016 Anal Methods</p>
<hr />
<div>#REDIRECT [[AMCTB 2016 Anal Methods]]</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=AMCTB_2016_Anal_Methods&diff=214575
AMCTB 2016 Anal Methods
2021-01-26T12:47:48Z
<p>Iglesias-Gonzalez Javier: Iglesias-Gonzalez Javier moved page Analytical 2016 to AMCTB 2016 Anal Methods</p>
<hr />
<div>{{Publication<br />
|title=Analytical methods committee, AMCTB No. 74 (2016) z-Scores and other scores in chemical proficiency testing—their meanings, and some common misconceptions. Anal Methods 8:5553-5555.<br />
|info=[https://pubs.rsc.org/en/content/articlehtml/2016/ay/c6ay90078j Open Access]<br />
|authors=Analytical methods committee<br />
|year=2016<br />
|journal=Anal Methods<br />
|abstract=z-Scores were devised to provide a transparent but widely-applicable scoring system for participants in proficiency tests for analytical laboratories. The essential idea is to provide an appropriate scaling of the difference between a participant’s result and the ‘assigned value’ for the concentration of the analyte. Interpretation of a z-score is straightforward but some aspects need careful attention to avoid misconception. Over time several related scores have been devised to cope with a diversified range of applications. The main types of score have recently been codified in ISO 13528 (2015).<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=AMCTB_2016_Anal_Methods&diff=214574
AMCTB 2016 Anal Methods
2021-01-26T12:47:22Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Analytical methods committee, AMCTB No. 74 (2016) z-Scores and other scores in chemical proficiency testing—their meanings, and some common misconceptions. Anal Methods 8:5553-5555.<br />
|info=[https://pubs.rsc.org/en/content/articlehtml/2016/ay/c6ay90078j Open Access]<br />
|authors=Analytical methods committee<br />
|year=2016<br />
|journal=Anal Methods<br />
|abstract=z-Scores were devised to provide a transparent but widely-applicable scoring system for participants in proficiency tests for analytical laboratories. The essential idea is to provide an appropriate scaling of the difference between a participant’s result and the ‘assigned value’ for the concentration of the analyte. Interpretation of a z-score is straightforward but some aspects need careful attention to avoid misconception. Over time several related scores have been devised to cope with a diversified range of applications. The main types of score have recently been codified in ISO 13528 (2015).<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Visser_2006_Accred_Qual_Assur&diff=214572
Visser 2006 Accred Qual Assur
2021-01-26T11:21:32Z
<p>Iglesias-Gonzalez Javier: Iglesias-Gonzalez Javier moved page Visser 2006 Accred Qual Assur to Visser 2006 Accred Qual Asur</p>
<hr />
<div>#REDIRECT [[Visser 2006 Accred Qual Asur]]</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Visser_2006_Accred_Qual_Asur&diff=214571
Visser 2006 Accred Qual Asur
2021-01-26T11:21:32Z
<p>Iglesias-Gonzalez Javier: Iglesias-Gonzalez Javier moved page Visser 2006 Accred Qual Assur to Visser 2006 Accred Qual Asur</p>
<hr />
<div>{{Publication<br />
|title=Visser RG (2006) Interpretation of interlaboratory comparison results to evaluate laboratory proficiency. Accred Qual Asur 10:521-526.<br />
|info=[https://link.springer.com/article/10.1007/s00769-005-0051-2 Springer Link]<br />
|authors=Visser RG<br />
|year=2006<br />
|journal=Accred Qual Asur<br />
|abstract=Guidelines are given for the evaluation of proficiency test (PT) results in order to increase the<br />
effectivity of PT participation. For better understanding, some statistical background is given along with some examples to show the effects of the choices made by the PT provider. The calculation method of the assigned value and the selection of the standard deviation both affect the z-score that is used by the participating laboratory to judge the quality of its performance in the PT. Therefore, the participating laboratory is advised to use the PT results with care and, if necessary, to recalculate the z-scores. Finally, advice is given on how not to follow up bad PT results along with some valuable steps that could be part of an effective follow-up procedure<br />
|keywords=Proficiency test, Assigned value, Standard deviation, z-score, Root cause analysis, Corrective action, Effectivity<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Visser_2006_Accred_Qual_Asur&diff=214570
Visser 2006 Accred Qual Asur
2021-01-26T11:21:24Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Visser RG (2006) Interpretation of interlaboratory comparison results to evaluate laboratory proficiency. Accred Qual Asur 10:521-526.<br />
|info=[https://link.springer.com/article/10.1007/s00769-005-0051-2 Springer Link]<br />
|authors=Visser RG<br />
|year=2006<br />
|journal=Accred Qual Asur<br />
|abstract=Guidelines are given for the evaluation of proficiency test (PT) results in order to increase the<br />
effectivity of PT participation. For better understanding, some statistical background is given along with some examples to show the effects of the choices made by the PT provider. The calculation method of the assigned value and the selection of the standard deviation both affect the z-score that is used by the participating laboratory to judge the quality of its performance in the PT. Therefore, the participating laboratory is advised to use the PT results with care and, if necessary, to recalculate the z-scores. Finally, advice is given on how not to follow up bad PT results along with some valuable steps that could be part of an effective follow-up procedure<br />
|keywords=Proficiency test, Assigned value, Standard deviation, z-score, Root cause analysis, Corrective action, Effectivity<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Visser_2006_Accred_Qual_Asur&diff=214569
Visser 2006 Accred Qual Asur
2021-01-26T11:19:33Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Visser RG (2006) Interpretation of interlaboratory comparison results to evaluate laboratory proficiency. Accred Qual Assur 10:521-526.<br />
|authors=Visser RG<br />
|year=2006<br />
|journal=Accred Qual Assur<br />
|abstract=Guidelines are given for the evaluation of proficiency test (PT) results in order to increase the<br />
effectivity of PT participation. For better understanding, some statistical background is given along with some examples to show the effects of the choices made by the PT provider. The calculation method of the assigned value and the selection of the standard deviation both affect the z-score that is used by the participating laboratory to judge the quality of its performance in the PT. Therefore, the participating laboratory is advised to use the PT results with care and, if necessary, to recalculate the z-scores. Finally, advice is given on how not to follow up bad PT results along with some valuable steps that could be part of an effective follow-up procedure<br />
|keywords=Proficiency test, Assigned value, Standard deviation, z-score, Root cause analysis, Corrective action, Effectivity<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Visser_2006_Accred_Qual_Asur&diff=214568
Visser 2006 Accred Qual Asur
2021-01-26T11:19:17Z
<p>Iglesias-Gonzalez Javier: Created page with "{{Publication |title=Visser RG (2006) Interpretation of interlaboratory comparison results to evaluate laboratory proficiency. Accred Qual Assur 10:521-526. |authors=Visser..."</p>
<hr />
<div>{{Publication<br />
|title=Visser RG (2006) Interpretation of interlaboratory comparison results to evaluate laboratory proficiency. Accred Qual Assur 10:521-526.<br />
|authors=Visser RG<br />
|year=2006<br />
|journal=Accred Qual Assur<br />
|abstract=Guidelines are given for the evaluation of proficiency test (PT) results in order to increase the<br />
effectivity of PT participation. For better understanding, some statistical background is given along with some examples to show the effects of the choices made by the PT provider. The calculation method of the assigned value and the selection of the standard deviation both affect the z-score that is used by the participating laboratory to judge the quality of its performance in the PT. Therefore, the participating laboratory is advised to use the PT results with care and, if necessary, to recalculate the z-scores. Finally, advice is given on how not to follow up bad PT results along with some valuable steps that could be part of an effective follow-up procedure<br />
|keywords=Proficiency test, Assigned value, Standard deviation, z-score, Root cause analysis, Corrective action, Effectivity<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Thompson_2006_Pure_Appl_Chem&diff=214563
Thompson 2006 Pure Appl Chem
2021-01-26T11:11:38Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Thompson M, Ellison SLR, Wood R (2006) The international harmonized protocol for the proficiency testing of analytical chemistry laboratories. Pure Appl Chem 78(1):145-196.<br />
|info=[https://www.degruyter.com/view/journals/pac/78/1/article-p145.xml Open Access]<br />
|authors=Thompson M, Ellison SLR, Wood R<br />
|year=2006<br />
|journal=Pure Appl Chem<br />
|abstract=The international standardizing organizations—AOAC International,<br />
ISO, and IUPAC—cooperated to produce the International Harmonized Protocol<br />
for the Proficiency Testing of (Chemical) Analytical Laboratories. The Working<br />
Group that produced the protocol agreed to revise that Protocol in the light of recent<br />
developments and the experience gained since it was first published. This revision<br />
has been prepared and agreed upon in the light of comments received following<br />
open consultation.<br />
|keywords=harmonized; IUPAC Analytical Chemistry Division; uncertainty; analysis; proficiency testing; protocol<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Thompson_2006_Pure_Appl_Chem&diff=214562
Thompson 2006 Pure Appl Chem
2021-01-26T11:11:18Z
<p>Iglesias-Gonzalez Javier: Created page with "{{Publication |title=Thompson M, Ellison SLR, Wood R (2006) The international harmonized protocol for the proficiency testing of analytical chemistry laboratories. Pure Appl..."</p>
<hr />
<div>{{Publication<br />
|title=Thompson M, Ellison SLR, Wood R (2006) The international harmonized protocol for the proficiency testing of analytical chemistry laboratories. Pure Appl Chem 78(1):145-196.<br />
|info=[https://www.degruyter.com/view/journals/pac/78/1/article-p145.xml Open Access]<br />
|authors=Thompson M, Ellison SLR, Wood R<br />
|year=2006<br />
|journal=Pure Appl Chem<br />
|abstract=The international standardizing organizations—AOAC International,<br />
ISO, and IUPAC—cooperated to produce the International Harmonized Protocol<br />
for the Proficiency Testing of (Chemical) Analytical Laboratories. The Working<br />
Group that produced the protocol agreed to revise that Protocol in the light of recent<br />
developments and the experience gained since it was first published. This revision<br />
has been prepared and agreed upon in the light of comments received following<br />
open consultation.<br />
|keywords=harmonized; IUPAC Analytical Chemistry Division; uncertainty; analysis; proficiency testing; protocol<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Doerrier_2018_Methods_Mol_Biol&diff=214561
Doerrier 2018 Methods Mol Biol
2021-01-26T10:55:06Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Doerrier C, Garcia-Souza LF, Krumschnabel G, Wohlfarter Y, Mészáros AT, Gnaiger E (2018) High-Resolution FluoRespirometry and OXPHOS protocols for human cells, permeabilized fibers from small biopsies of muscle, and isolated mitochondria. Methods Mol Biol 1782:31-70.<br />
|info=[https://www.ncbi.nlm.nih.gov/pubmed/29850993 PMID: 29850993] »[[File:O2k-brief.png|36px|link=http://wiki.oroboros.at/images/4/46/Doerrier_2018_Methods_Mol_Biol_O2k-brief.pdf|O2k-brief]][[Image:O2k-Protocols.jpg|right|80px|link=O2k-Protocols|O2k-Protocols]]<br />
|authors=Doerrier C, Garcia-Souza LF, Krumschnabel G, Wohlfarter Y, Meszaros AT, Gnaiger E<br />
|year=2018<br />
|journal=Methods Mol Biol<br />
|abstract=Protocols for high-resolution respirometry of intact cells, permeabilized cells, permeabilized muscle fibers, isolated mitochondria and tissue homogenates offer sensitive diagnostic tests of integrated mitochondrial function using standard cell culture techniques, small needle biopsies of muscle, and mitochondrial preparation methods. Multiple substrate-uncoupler-inhibitor titration (SUIT) protocols for analysis of oxidative phosphorylation (OXPHOS) improve our understanding of mitochondrial respiratory control and the pathophysiology of mitochondrial diseases. Respiratory states are defined in functional terms to account for the network of metabolic interactions in complex SUIT protocols with stepwise modulation of coupling control and electron transfer pathway states. A regulated degree of intrinsic uncoupling is a hallmark of oxidative phosphorylation, whereas pathological and toxicological dyscoupling is evaluated as a mitochondrial defect. The noncoupled state of maximum respiration is experimentally induced by titration of established uncouplers (CCCP, FCCP, DNP), to collapse the protonmotive force across the mitochondrial inner membrane and measure the electron transfer capacity (ET; open-circuit operation of respiration). Intrinsic uncoupling and dyscoupling are evaluated as the flux control ratio between non-phosphorylating LEAK respiration (electron flow coupled to proton pumping to compensate for proton leaks) and ET capacity. If OXPHOS capacity (maximally ADP stimulated O2 flux) is less than ET capacity, the phosphorylation pathway contributes to flux control. Physiological substrate combinations supporting the NADH&succinate-pathway are required to reconstitute tricarboxylic acid cycle function. This supports maximum ET and OXPHOS capacities, due to the additive effect of multiple electron supply pathways converging at the Q-junction. ET-pathways with electron entry separately through NADH (pyruvate&malate or glutamate&malate) or succinate (succinate&rotenone) restricts ET capacity and artificially enhances flux control upstream of the Q-cycle, providing diagnostic information on specific ET-pathway branches. O2 concentration is maintained above air saturation in protocols with permeabilized muscle fibers to avoid experimental O2 limitation of respiration. Standardized two-point calibration of the polarographic oxygen sensor (static sensor calibration), calibration of the sensor response time (dynamic sensor calibration), and evaluation of instrumental background O2 flux (systemic flux compensation) provide the unique experimental basis for high accuracy of quantitative results and quality control in high-resolution respirometry.<br />
|editor=[[Gnaiger E]]<br />
|mipnetlab=AT Innsbruck Gnaiger E, AT Innsbruck Oroboros<br />
}}<br />
{{Labeling<br />
|area=Respiration, Instruments;methods<br />
|organism=Human, Mouse, Rat, Saccharomyces cerevisiae<br />
|tissues=Heart, Skeletal muscle, Endothelial;epithelial;mesothelial cell, Blood cells, HEK, Platelet<br />
|preparations=Permeabilized cells, Permeabilized tissue, Homogenate, Isolated mitochondria, Intact cells<br />
|topics=Oxygen kinetics<br />
|couplingstates=LEAK, ROUTINE, OXPHOS, ET<br />
|pathways=F, N, S, Gp, CIV, NS, Other combinations, ROX<br />
|instruments=Oxygraph-2k, TIP2k, O2k-Protocol<br />
|additional=MitoPathways, MitoFitPublication, MitoEAGLEPublication, O2k-chemicals and media, SUIT-001, SUIT-001 O2 mt D001, SUIT-001 O2 pfi D002, SUIT-001 O2 ce-pce D003, SUIT-001 O2 ce-pce D004, SUIT-002, SUIT-002 O2 mt D005, SUIT-002 O2 pfi D006, SUIT-002 O2 ce-pce D007, SUIT-002 O2 ce-pce D007a, SUIT-010, SUIT-010 O2 pce D008, SUIT-010, SUIT-010 O2 ce-pce D050, SUIT-010 O2 ce-pce D008, MitoEAGLE blood cells reviews, O2k-brief, Flux control ratio, BEC 2020.1, BEC 2020.2, MitoFit 2021 MgG, MitoFit 2021 CoQ, MitoFit 2021 PT<br />
}}<br />
[[File:O2k-brief.png|36px|left]]<br />
== O2k-brief ==<br />
::::» [[O2k-brief |List of O2k-Publications presented as O2k-brief]]<br />
<br />
=== RP1 and RP2 in mt-preparations ===<br />
:::: '''SUIT RP1''':1PM;2D:2c;3U;4G;5S;6Oct;7Rot;'''8Gp''';9Ama;'''10AsTm''';11Azd<br />
:::: [[SUIT-002 |SUIT RP2]]:1D;2M.1;3Oct;3c;4M2;5P;6G;7S;8Gp;9U;'''10Rot''';11Ama;'''12AsTm''';13Azd<br />
<br />
[[File:RP1&RP2.png|400px]] '''Harmonization between RP1 and RP2'''<br />
<br />
== Correction ==<br />
In Table 1, final concentration of oligomycin in a 2 mL O2k-chamber should be 2.5 µM instead of 2.5 µg/mL. Of note, it is mentioned in the text: “the use of 2.5 µM oligomycin may show an inhibitory effect on [[ET capacity]] in some biological samples (e.g. platelets)". Therefore, we recommend to 1) test the inhibitory effect of oligomycin on ET capacity (by uncoupler titrations in the absence of inhibitor) and, 2) evaluate lower oligomycin concentration (5-10 nM) to replace the standard 2.5 µM oligomycin concentration. See more details in [[Oligomycin|oligomycin]].<br />
<br />
== Cited by ==<br />
{{Template:Cited by Gnaiger 2020 BEC MitoPathways}}<br />
{{Template:Cited by Gnaiger 2020 BEC MitoPhysiology}}<br />
{{Template:Cited by Komlodi 2021 MitoFit CoQ}}<br />
{{Template:Cited by Cardoso 2021 MitoFit MgG}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Am_J_Clin_Pathol&diff=214560
Am J Clin Pathol
2021-01-26T10:51:54Z
<p>Iglesias-Gonzalez Javier: Created page with "{{Journal |Title=[https://academic.oup.com/ajcp American Journal of Clinical Pathology] }}"</p>
<hr />
<div>{{Journal<br />
|Title=[https://academic.oup.com/ajcp American Journal of Clinical Pathology] <br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Belk_1947_Am_J_Clin_Pathol&diff=214559
Belk 1947 Am J Clin Pathol
2021-01-26T10:50:51Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Belk WP, Sunderman FW (1947) A survey of the accuracy of chemical analyses in clinical laboratories. Am J Clin Pathol 17(11):853-61.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/20269991/ PMID:20269991]<br />
|authors=Belk WP, Sunderman FW<br />
|year=1947<br />
|journal=Am J Clin Pathol<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Belk_1947_Am_J_Clin_Pathol&diff=214558
Belk 1947 Am J Clin Pathol
2021-01-26T10:50:26Z
<p>Iglesias-Gonzalez Javier: Created page with "{{Publication |title=Belk WP, Sunderman FW (1947) A survey of the accuracy of chemical analyses in clinical laboratories. Am J Clin Pathol 17(11):853-61. |info=[https://pubme..."</p>
<hr />
<div>{{Publication<br />
|title=Belk WP, Sunderman FW (1947) A survey of the accuracy of chemical analyses in clinical laboratories. Am J Clin Pathol 17(11):853-61.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/20269991/ PMID:20269991]<br />
|authors=Belk WP, Sunderman FW<br />
|year=1947<br />
|journal=Am J Clin Pathol<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Tsilidis_2013_PLOS_Biol&diff=214556
Tsilidis 2013 PLOS Biol
2021-01-26T10:25:52Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Tsilidis KK, Panagiotou OA, Sena ES, Aretouli E, Evangelou E, Howells D, Salman RAS, Macleod MR, Ioannidis JPA (2013) Evaluation of excess significance bias in animal studies of neurological diseases. PLOS Biol 11(7): e10401609.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/23874156/ PMID:23874156 Open Access]<br />
|authors=Tsilidis KK, Panagiotou OA, Sena ES, Aretouli E, Evangelou E, Howells D, Salman RAS, Macleod MR, Ioannidis JPA<br />
|year=2013<br />
|journal=PLOS Biol<br />
|abstract=Animal studies generate valuable hypotheses that lead to the conduct of preventive or therapeutic clinical trials. We assessed whether there is evidence for excess statistical significance in results of animal studies on neurological disorders, suggesting biases. We used data from meta-analyses of interventions deposited in Collaborative Approach to Meta-Analysis and Review of Animal Data in Experimental Studies (CAMARADES). The number of observed studies with statistically significant results (O) was compared with the expected number (E), based on the statistical power of each study under different assumptions for the plausible effect size. We assessed 4,445 datasets synthesized in 160 meta-analyses on Alzheimer disease (n = 2), experimental autoimmune encephalomyelitis (n = 34), focal ischemia (n = 16), intracerebral hemorrhage (n = 61), Parkinson disease (n = 45), and spinal cord injury (n = 2). 112 meta-analyses (70%) found nominally (p≤0.05) statistically significant summary fixed effects. Assuming the effect size in the most precise study to be a plausible effect, 919 out of 4,445 nominally significant results were expected versus 1,719 observed (p<10−9). Excess significance was present across all neurological disorders, in all subgroups defined by methodological characteristics, and also according to alternative plausible effects. Asymmetry tests also showed evidence of small-study effects in 74 (46%) meta-analyses. Significantly effective interventions with more than 500 animals, and no hints of bias were seen in eight (5%) meta-analyses. Overall, there are too many animal studies with statistically significant results in the literature of neurological disorders. This observation suggests strong biases, with selective analysis and outcome reporting biases being plausible explanations, and provides novel evidence on how these biases might influence the whole research domain of neurological animal literature.<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Levitsky_2019_RSC_Adv&diff=214555
Levitsky 2019 RSC Adv
2021-01-26T10:24:15Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Levitsky Y, Pegouske DJ, Hammer SS, Frantz NL, Fisher KP, Muchnik AB, Saripalli AR, Kirschner P, Bazil JN, Busik JV, Proshlyakov DA (2019) Micro-respirometry of whole cells and isolated mitochondria. RSC Adv 9:33257-33267.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/32123561/ PMID:32123561 Open Access]<br />
|authors=Levitsky Y, Pegouske DJ, Hammer SS, Frantz NL, Fisher KP, Muchnik AB, Saripalli AR, Kirschner P, Bazil JN, Busik JV, Proshlyakov DA<br />
|year=2019<br />
|journal=RSC Adv<br />
|abstract=Oxygen consumption is a key metric of metabolism in aerobic organisms. Current respirometric methods led to seminal discoveries despite limitations such as high sample demand, exchange with atmospheric O2, and cumulative titration protocols leading to limited choice of useable tissue, complex data interpretation, and restricted experimental design. We developed a sensitive and customizable method of measuring O2 consumption rates by a variety of biological samples in microliter volumes without interference from the aerobic environment. We demonstrate that O2 permeability of the photopolymer, VeroClear, is comparable to that of polyetheretherketone (0.125 vs. 0.143 barrer, respectively) providing an efficient barrier to oxygen ingress. Optical transparency of VeroClear, combined with high resolution 3D printing, allows for optode-based oxygen detection in enclosed samples. These properties yield a microrespirometer with over 100× dynamic range for O2 consumption rates. Importantly, the enclosed respirometer configuration and very low oxygen permeability of materials makes it suitable, with resin pre-conditioning, for quantitative assessment of O2 consumption rates at any desired [O2], including hyperbaric, physiological or hypoxic conditions as necessary for each cell type. We characterized two configurations to study soluble enzymes, isolated mitochondria, cells in suspension, and adherent cells cultured on-chip. Improved sensitivity allows for routine quantitative detection of respiration by as few as several hundred cells. Specific activity of cell suspensions in the microrespirometer was in close agreement with that obtained by high-resolution polarographic respirometry. Adherent cell protocols allowed for physiologically relevant assessment of respiration in retinal pigment epithelial cells, ARPE-19, which displayed lower metabolic rates compared with those in suspension. By exchanging medium composition, we demonstrate that cells can be transiently inhibited by cyanide and that 99.6% of basal O2 uptake is recovered upon its removal. This approach is amenable to new experimental designs and precision measurements on limited sample quantities across basic research and applied fields.<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Ioannidis_2014_PLOS_Med&diff=214554
Ioannidis 2014 PLOS Med
2021-01-26T10:23:07Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Ioannidis JPA (2014) How to make more published research true. PLOS Med 11(10): e1001747.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/25334033/ PMID:25334033 Open Access]<br />
|authors=Ioannidis JPA<br />
|year=2014<br />
|journal=PLOS Med<br />
|abstract=The achievements of scientific research are amazing. Science has grown from the occupation of a few dilettanti into a vibrant global industry with more than 15,000,000 people authoring more than 25,000,000 scientific papers in 1996–2011 alone [1]. However, true and readily applicable major discoveries are far fewer. Many new proposed associations and/or effects are false or grossly exaggerated [2],[3], and translation of knowledge into useful applications is often slow and potentially inefficient [4]. Given the abundance of data, research on research (i.e., meta-research) can derive empirical estimates of the prevalence of risk factors for high false-positive rates (underpowered studies; small effect sizes; low pre-study odds; flexibility in designs, definitions, outcomes, analyses; biases and conflicts of interest; bandwagon patterns; and lack of collaboration) [3]. Currently, an estimated 85% of research resources are wasted [5].<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Goodman_2007_PLOS_Med&diff=214553
Goodman 2007 PLOS Med
2021-01-26T10:21:27Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Goodman S, Greenland S (2007) Why most published research findings are false: Problems in the analysis. PLoS Med 4:e168.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/17456002/ PMID:17456002 Open Access]<br />
|authors=Goodman S, Greenland S<br />
|year=2007<br />
|journal=PLOS Med<br />
|abstract=There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Forscher_1963_Science&diff=214552
Forscher 1963 Science
2021-01-26T10:17:55Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Forscher BK (1963) Chaos in the Brickyard. Science 142(3590):339.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/17799464/ PMID:17799464 Open Access]<br />
|authors=Forscher BK<br />
|year=1963<br />
|journal=Science<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Chiu_2017_PLOS_Biol&diff=214551
Chiu 2017 PLOS Biol
2021-01-26T10:16:59Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Chiu K, Grundy Q, Bero L (2017) `Spin' in published biomedical literature: A methodological systematic review. PLoS Biology 15(9): e2002173.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/28892482/ PMID:28892482 Open Access]<br />
|authors=Chiu K, Grundy Q, Bero L<br />
|year=2017<br />
|journal=PLOS Biol<br />
|abstract=In the scientific literature, spin refers to reporting practices that distort the interpretation of results and mislead readers so that results are viewed in a more favourable light. The presence of spin in biomedical research can negatively impact the development of further studies, clinical practice, and health policies. This systematic review aims to explore the nature and prevalence of spin in the biomedical literature. We searched MEDLINE, PreMEDLINE, Embase, Scopus, and hand searched reference lists for all reports that included the measurement of spin in the biomedical literature for at least 1 outcome. Two independent coders extracted data on the characteristics of reports and their included studies and all spin-related outcomes. Results were grouped inductively into themes by spin-related outcome and are presented as a narrative synthesis. We used meta-analyses to analyse the association of spin with industry sponsorship of research. We included 35 reports, which investigated spin in clinical trials, observational studies, diagnostic accuracy studies, systematic reviews, and meta-analyses. The nature of spin varied according to study design. The highest (but also greatest) variability in the prevalence of spin was present in trials. Some of the common practices used to spin results included detracting from statistically nonsignificant results and inappropriately using causal language. Source of funding was hypothesised by a few authors to be a factor associated with spin; however, results were inconclusive, possibly due to the heterogeneity of the included papers. Further research is needed to assess the impact of spin on readers’ decision-making. Editors and peer reviewers should be familiar with the prevalence and manifestations of spin in their area of research in order to ensure accurate interpretation and dissemination of research<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=Publication efficiency, MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Bespalov_2019_Eur_Neuropsychopharmacol&diff=214550
Bespalov 2019 Eur Neuropsychopharmacol
2021-01-26T10:15:50Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Bespalov A, Steckler T, Skolnick P (2019) Be positive about negatives-recommendations for the publication of negative (or null) results. Eur Neuropsychopharmacol 29(12): 1312-1320.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/31753777/ PMID:31753777 Open Access]<br />
|authors=Bespalov A, Steckler T, Skolnick P<br />
|year=2019<br />
|journal=Eur Neuropsychopharmacol<br />
|abstract=Both positive and negative (null or neutral) results are essential for the progress of science and its self-correcting nature. However, there is general reluctance to publish negative results, and this may be due a range of factors (e.g., the widely held perception that negative results are more difficult to publish, the preference to publish positive findings that are more likely to generate citations and funding for additional research). It is particularly challenging to disclose negative results that are not consistent with previously published positive data, especially if the initial publication appeared in a high impact journal. Ideally, there should be both incentives and support to reduce the costs associated with investing efforts into preparing publications with negative results. We describe here a set of criteria that can help scientists, reviewers and editors to publish technically sound, scientifically high-impact negative (or null) results originating from rigorously designed and executed studies. Proposed criteria emphasize the importance of collaborative efforts and communication among scientists (also including the authors of original publications with positive results).<br />
|keywords=Good research practiceNegative resultsReproducibilityPublication bias<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Baker_2016b_Nature&diff=214545
Baker 2016b Nature
2021-01-26T10:14:39Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Baker M (2016) How quality control could save your science. Nature 529:456–458.<br />
|info=[https://www.nature.com/news/polopoly_fs/1.19223!/menu/main/topColumns/topLeftColumn/pdf/529456a.pdf PMID:26819028 Open Access]<br />
|authors=Baker M<br />
|year=2016<br />
|journal=Nature<br />
|abstract=It may not be sexy, but quality assurance is becoming a crucial part of lab life<br />
<br />
<small> © 2016 Macmillan Publishers Limited. All rights reserved </small><br />
|editor=[[Antunes D]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=MiPNet21.14_Reference_sample_HRR&diff=214544
MiPNet21.14 Reference sample HRR
2021-01-26T09:57:58Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{OROBOROS header page name}}<br />
<br />
{{Publication<br />
<br />
|title=[[Image:O2k-Protocols.jpg|right|80px|link=O2k-Protocols|O2k-Protocols]] Development of a reference sample for HRR.<br />
|info=[[File:PDF.jpg|100px|link=http://bioblast.at/images/1/19/MiPNet21.14_ReferenceSampleHRR.pdf|Bioblast pdf]] »[http://wiki.oroboros.at/index.php/File:MiPNet21.14_ReferenceSampleHRR.pdf Versions]<br />
|authors=Oroboros <br />
|year=2016-10-19<br />
|journal=Mitochondr Physiol Network<br />
|abstract=Krumschnabel G, Lamberti G, Hiller E, Hansl M, Gnaiger E (2016) Development of a reference sample for HRR. Mitochondr Physiol Network 21.14(02):1-10.<br />
{{MiPNet pdf page linking to MitoPedia}}<br />
|mipnetlab=AT_Innsbruck_Oroboros<br />
}}<br />
{{Labeling<br />
|area=Respiration, Instruments;methods<br />
|injuries=Cryopreservation<br />
|organism=Human<br />
|tissues=HEK<br />
|preparations=Intact cells, Permeabilized cells<br />
|couplingstates=LEAK, ROUTINE, OXPHOS, ET<br />
|pathways=F, N, S, Gp, CIV, NS, Other combinations, ROX<br />
|instruments=Oxygraph-2k<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=MiPNet21.14_Reference_sample_HRR&diff=214543
MiPNet21.14 Reference sample HRR
2021-01-26T09:57:34Z
<p>Iglesias-Gonzalez Javier: Reverted edits by Iglesias-Gonzalez Javier (talk) to last revision by Antunes Diana</p>
<hr />
<div>{{OROBOROS header page name}}<br />
<br />
{{Publication<br />
<br />
|title=[[Image:O2k-Protocols.jpg|right|80px|link=O2k-Protocols|O2k-Protocols]] Development of a reference sample for HRR.<br />
|info=[[File:PDF.jpg|100px|link=http://bioblast.at/images/1/19/MiPNet21.14_ReferenceSampleHRR.pdf|Bioblast pdf]] »[http://wiki.oroboros.at/index.php/File:MiPNet21.14_ReferenceSampleHRR.pdf Versions]<br />
|authors=Oroboros <br />
|year=2016-10-19<br />
|journal=Mitochondr Physiol Network<br />
|abstract=Krumschnabel G, Lamberti G, Hiller E, Hansl M, Gnaiger E (2016) Development of a reference sample for HRR. Mitochondr Physiol Network 21.14(02):1-10.<br />
{{MiPNet pdf page linking to MitoPedia}}<br />
|mipnetlab=AT_Innsbruck_Oroboros<br />
}}<br />
{{Labeling<br />
|area=Respiration, Instruments;methods<br />
|injuries=Cryopreservation<br />
|organism=Human<br />
|tissues=HEK<br />
|preparations=Intact cells, Permeabilized cells<br />
|couplingstates=LEAK, ROUTINE, OXPHOS, ET<br />
|pathways=F, N, S, Gp, CIV, NS, Other combinations, ROX<br />
|instruments=Oxygraph-2k<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=MiPNet06.03_POS-calibration-SOP&diff=214542
MiPNet06.03 POS-calibration-SOP
2021-01-26T09:57:17Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Template:OROBOROS support page name}}<br />
{{Publication<br />
|title=[[Image:O2k-Manual.jpg|right|70px|link=O2k-Manual|O2k-Manual]] O2k Quality Control 1: Polarographic oxygen sensors and accuracy of calibration.<br />
|info=[[File:PDF.jpg|100px|link=http://wiki.oroboros.at/images/7/77/MiPNet06.03_POS-Calibration-SOP.pdf |Bioblast pdf]] » [http://www.bioblast.at/index.php/File:MiPNet06.03_POS-Calibration-SOP.pdf Versions]<br />
|authors=Oroboros<br />
|year=2020-02-16<br />
|journal=Mitochondr Physiol Network<br />
|abstract=Gnaiger E (2020) O2k Quality Control 1: Polarographic oxygen sensors and accuracy of calibration. Mitochondr Physiol Network 06.03(18):1-21.<br />
{{MiPNet pdf page linking to MitoPedia}}<br />
|mipnetlab=AT_Innsbruck_Oroboros<br />
}}<br />
<br />
{{Template:Keywords: Oxygen signal}}<br />
<br />
::::» [[Oxygen calibration - DatLab]]<br />
<br />
{{Labeling<br />
|area=Respiration, Instruments;methods<br />
|instruments=Oxygraph-2k, O2k-Manual<br />
|additional=DatLab, O2k-SOP, DL7, Oxygen solubility, MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=MiPNet06.03_POS-calibration-SOP&diff=214541
MiPNet06.03 POS-calibration-SOP
2021-01-26T09:57:05Z
<p>Iglesias-Gonzalez Javier: Reverted edits by Iglesias-Gonzalez Javier (talk) to last revision by Gnaiger Erich</p>
<hr />
<div>{{Template:OROBOROS support page name}}<br />
{{Publication<br />
|title=[[Image:O2k-Manual.jpg|right|70px|link=O2k-Manual|O2k-Manual]] O2k Quality Control 1: Polarographic oxygen sensors and accuracy of calibration.<br />
|info=[[File:PDF.jpg|100px|link=http://wiki.oroboros.at/images/7/77/MiPNet06.03_POS-Calibration-SOP.pdf |Bioblast pdf]] » [http://www.bioblast.at/index.php/File:MiPNet06.03_POS-Calibration-SOP.pdf Versions]<br />
|authors=Oroboros<br />
|year=2020-02-16<br />
|journal=Mitochondr Physiol Network<br />
|abstract=Gnaiger E (2020) O2k Quality Control 1: Polarographic oxygen sensors and accuracy of calibration. Mitochondr Physiol Network 06.03(18):1-21.<br />
{{MiPNet pdf page linking to MitoPedia}}<br />
|mipnetlab=AT_Innsbruck_Oroboros<br />
}}<br />
<br />
{{Template:Keywords: Oxygen signal}}<br />
<br />
::::» [[Oxygen calibration - DatLab]]<br />
<br />
{{Labeling<br />
|area=Respiration, Instruments;methods<br />
|instruments=Oxygraph-2k, O2k-Manual<br />
|additional=DatLab, O2k-SOP, DL7, Oxygen solubility<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=MiPNet14.06_Instrumental_O2_background&diff=214540
MiPNet14.06 Instrumental O2 background
2021-01-26T09:56:52Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Template:OROBOROS support page name}}<br />
{{Publication<br />
|title=[[Image:O2k-Manual.jpg|right|70px|link=O2k-Manual|O2k-Manual]] O2k Quality Control 2: Instrumental oxygen background correction and accuracy of oxygen flux.<br />
|info=[[File:PDF.jpg|100px|link=http://wiki.oroboros.at/images/6/65/MiPNet14.06_InstrumentalO2Background.pdf |Bioblast pdf]] » [http://www.bioblast.at/index.php/File:MiPNet14.06_InstrumentalO2Background.pdf Versions]<br />
|authors=Oroboros<br />
|year=2020-04-16<br />
|journal=Mitochondr Physiol Network<br />
|abstract=Fasching M, Gnaiger E (2020) O2k Quality Control 2: Instrumental oxygen background correction and accuracy of oxygen flux. Mitochondr Physiol Network 14.6(08):1-16.<br />
{{MiPNet pdf page linking to MitoPedia}}<br />
:» Product: [[O2k-FluoRespirometer]], [[Oroboros O2k-Catalogue |O2k-Catalogue]]<br />
|mipnetlab=AT_Innsbruck_Oroboros<br />
}}<br />
== Keywords ==<br />
{{Template:Keywords: Chamber volume}}<br />
<br />
<br />
'''Acknowledgements'''<br />
[[File:Template NextGen-O2k.jpg|left|400px|link=NextGen-O2k]]<br />
<br/><br />
<br/><br />
<br/><br />
<br/><br />
<br />
{{Labeling<br />
|area=Respiration, Instruments;methods<br />
|instruments=Oxygraph-2k, O2k-Manual<br />
|additional=DatLab, O2k-SOP, DL7, System, MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=MiPNet14.06_Instrumental_O2_background&diff=214539
MiPNet14.06 Instrumental O2 background
2021-01-26T09:56:38Z
<p>Iglesias-Gonzalez Javier: Reverted edits by Iglesias-Gonzalez Javier (talk) to last revision by Gnaiger Erich</p>
<hr />
<div>{{Template:OROBOROS support page name}}<br />
{{Publication<br />
|title=[[Image:O2k-Manual.jpg|right|70px|link=O2k-Manual|O2k-Manual]] O2k Quality Control 2: Instrumental oxygen background correction and accuracy of oxygen flux.<br />
|info=[[File:PDF.jpg|100px|link=http://wiki.oroboros.at/images/6/65/MiPNet14.06_InstrumentalO2Background.pdf |Bioblast pdf]] » [http://www.bioblast.at/index.php/File:MiPNet14.06_InstrumentalO2Background.pdf Versions]<br />
|authors=Oroboros<br />
|year=2020-04-16<br />
|journal=Mitochondr Physiol Network<br />
|abstract=Fasching M, Gnaiger E (2020) O2k Quality Control 2: Instrumental oxygen background correction and accuracy of oxygen flux. Mitochondr Physiol Network 14.6(08):1-16.<br />
{{MiPNet pdf page linking to MitoPedia}}<br />
:» Product: [[O2k-FluoRespirometer]], [[Oroboros O2k-Catalogue |O2k-Catalogue]]<br />
|mipnetlab=AT_Innsbruck_Oroboros<br />
}}<br />
== Keywords ==<br />
{{Template:Keywords: Chamber volume}}<br />
<br />
<br />
'''Acknowledgements'''<br />
[[File:Template NextGen-O2k.jpg|left|400px|link=NextGen-O2k]]<br />
<br/><br />
<br/><br />
<br/><br />
<br/><br />
<br />
{{Labeling<br />
|area=Respiration, Instruments;methods<br />
|instruments=Oxygraph-2k, O2k-Manual<br />
|additional=DatLab, O2k-SOP, DL7, System<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Yepez_2018_PLOS_One&diff=214538
Yepez 2018 PLOS One
2021-01-26T09:56:25Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Yepez VA, Kremer LS, Iuso A, Gusic M, Kopajtich R, Konarikova E, Nadel A, Wachutka L, Prokisch H, Gagneur J (2018) OCR-Stats: Robust estimation and statistical testing of mitochondrial respiration activities using Seahorse XF Analyzer. PLOS One 13(7): e0199938.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/29995917/ PMID: 29995917 Open Access]<br />
|authors=Yepez VA, Kremer LS, Iuso A, Gusic M, Kopajtich R, Konarikova E, Nadel A, Wachutka L, Prokisch H, Gagneur J<br />
|year=2018<br />
|journal=PLOS One<br />
|abstract=The accurate quantification of cellular and mitochondrial bioenergetic activity is of great interest in medicine and biology. Mitochondrial stress tests performed with Seahorse Bioscience XF Analyzers allow the estimation of different bioenergetic measures by monitoring the oxygen consumption rates (OCR) of living cells in multi-well plates. However, studies of the statistical best practices for determining aggregated OCR measurements and comparisons have been lacking. Therefore, to understand how OCR behaves across different biological samples, wells, and plates, we performed mitochondrial stress tests in 126 96-well plates involving 203 fibroblast cell lines. We show that the noise of OCR is multiplicative, that outlier data points can concern individual measurements or all measurements of a well, and that the inter-plate variation is greater than the intra-plate variation. Based on these insights, we developed a novel statistical method, OCR-Stats, that: i) robustly estimates OCR levels modeling multiplicative noise and automatically identifying outlier data points and outlier wells; and ii) performs statistical testing between samples, taking into account the different magnitudes of the between- and within-plate variations. This led to a significant reduction of the coefficient of variation across plates of basal respiration by 45% and of maximal respiration by 29%. Moreover, using positive and negative controls, we show that our statistical test outperforms the existing methods, which suffer from an excess of either false positives (within-plate methods), or false negatives (between-plate methods). Altogether, this study provides statistical good practices to support experimentalists in designing, analyzing, testing, and reporting the results of mitochondrial stress tests using this high throughput platform.<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|area=Instruments;methods<br />
|preparations=Intact cells<br />
|couplingstates=LEAK, ROUTINE, ET<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Wasserstein_2016_The_American_Statistician&diff=214537
Wasserstein 2016 The American Statistician
2021-01-26T09:56:04Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Wasserstein RL, Lazar NA (2016) The ASA's statement on p-values: context, process, and purpose. The American Statistician 70:129-33.<br />
|info=[http://dx.doi.org/10.1080/00031305.2016.1154108 Open Access]<br />
|authors=Wasserstein RL, Lazar NA<br />
|year=2016<br />
|journal=The American Statistician<br />
|abstract=In February, 2014, George Cobb, Professor Emeritus of Mathematics and Statistics at Mount Holyoke College, posed these questions to an ASA discussion forum:<br />
Q: Why do so many colleges and grad schools teach p = .05?<br />
A: Because that's still what the scientific community and journal editors use.<br />
Q: Why do so many people still use p = 0.05?<br />
A: Because that's what they were taught in college or grad school.<br />
Cobb’s concern was a long-worrisome circularity in the sociology of science based on the use of bright lines such as P < 0.05 : “We teach it because it’s what we do; we do it because it’s what we teach.” This concern was brought to the attention of the ASA Board.<br />
<br />
The ASA Board was also stimulated by highly visible discussions over the last few years. For example, ScienceNews (Siegfried, 2010) wrote: “It’s science’s dirtiest secret: The ‘scientific method’ of testing hypotheses by statistical analysis stands on a flimsy foundation.” A November, 2013, article in Phys.org Science News Wire (2013) cited “numerous deep flaws” in null hypothesis significance testing. A ScienceNews article (Siegfried, 2014) on February 7,<br />
2014, said “statistical techniques for testing hypotheses…have more flaws than Facebook’s privacy policies.” A week later, statistician and “Simply Statistics” blogger Jeff Leek responded. “The problem is not that people use P-values poorly,” Leek wrote, “it is that the vast majority of data analysis is not performed by people properly trained to perform data analysis” (Leek, 2014).<br />
...<br />
|editor=Krumschnabel G<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=Gentle Science, MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Tsilidis_2013_PLOS_Biol&diff=214536
Tsilidis 2013 PLOS Biol
2021-01-26T09:55:45Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Tsilidis KK, Panagiotou OA, Sena ES, Aretouli E, Evangelou E, Howells D, Salman RAS, Macleod MR, Ioannidis JPA (2013) Evaluation of excess significance bias in animal studies of neurological diseases. PLOS Biol 11(7): e10401609.<br />
|info=[https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001609 Open Access]<br />
|authors=Tsilidis KK, Panagiotou OA, Sena ES, Aretouli E, Evangelou E, Howells D, Salman RAS, Macleod MR, Ioannidis JPA<br />
|year=2013<br />
|journal=PLOS Biol<br />
|abstract=Animal studies generate valuable hypotheses that lead to the conduct of preventive or therapeutic clinical trials. We assessed whether there is evidence for excess statistical significance in results of animal studies on neurological disorders, suggesting biases. We used data from meta-analyses of interventions deposited in Collaborative Approach to Meta-Analysis and Review of Animal Data in Experimental Studies (CAMARADES). The number of observed studies with statistically significant results (O) was compared with the expected number (E), based on the statistical power of each study under different assumptions for the plausible effect size. We assessed 4,445 datasets synthesized in 160 meta-analyses on Alzheimer disease (n = 2), experimental autoimmune encephalomyelitis (n = 34), focal ischemia (n = 16), intracerebral hemorrhage (n = 61), Parkinson disease (n = 45), and spinal cord injury (n = 2). 112 meta-analyses (70%) found nominally (p≤0.05) statistically significant summary fixed effects. Assuming the effect size in the most precise study to be a plausible effect, 919 out of 4,445 nominally significant results were expected versus 1,719 observed (p<10−9). Excess significance was present across all neurological disorders, in all subgroups defined by methodological characteristics, and also according to alternative plausible effects. Asymmetry tests also showed evidence of small-study effects in 74 (46%) meta-analyses. Significantly effective interventions with more than 500 animals, and no hints of bias were seen in eight (5%) meta-analyses. Overall, there are too many animal studies with statistically significant results in the literature of neurological disorders. This observation suggests strong biases, with selective analysis and outcome reporting biases being plausible explanations, and provides novel evidence on how these biases might influence the whole research domain of neurological animal literature.<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Thiese_2015_Biochem_Med&diff=214535
Thiese 2015 Biochem Med
2021-01-26T09:55:31Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Thiese MS, Arnold ZC, Walker S (2015) The misuse and abuse of statistics in biomedical research. Biochem Med 25(1):5-11.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/25672462/ PMID:25672462 Open Access]<br />
|authors=Thiese MS, Arnold ZC, Walker S<br />
|year=2015<br />
|journal=Biochem Med<br />
|abstract=Statistics are the primary tools for assessing relationships and evaluating study questions. Unfortunately, these tools are often misused, either inadvertently because of ignorance or lack of planning, or conspicuously to achieve a specified result. Data abuses include the incorrect application of statistical tests, lack of transparency and disclosure about decisions that are made, incomplete or incorrect multivariate model building, or exclusion of outliers. Individually, each of these actions may completely invalidate a study, and often studies are victim to more than one offense. Increasingly there are tools and guidance for researchers to look to, including the development of an analysis plan and a series of study specific checklists, in order to prevent or mitigate these offenses.<br />
|keywords=a priori; analytical plan; biostatistics; disclosure; statistical methods; transparency.<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Stark_2018_Nature&diff=214534
Stark 2018 Nature
2021-01-26T09:55:16Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Stark PB (2018) No reproducibility without preproducibility. Nature 557: 613.<br />
|info=[https://media.nature.com/original/magazine-assets/d41586-018-05256-0/d41586-018-05256-0.pdf Open Access]<br />
|authors=Stark PB<br />
|year=2018<br />
|journal=Nature<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Shahangian_1998_Arch_Pathol_Lab_Med&diff=214533
Shahangian 1998 Arch Pathol Lab Med
2021-01-26T09:55:03Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Shahangian S (1998) Proficiency testing in laboratory medicine: uses and limitations. Arch Pathol Lab Med 122(1): 15-30.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/9448012/ PMID:9448012]<br />
|authors=Shahangian S<br />
|year=1998<br />
|journal=Arch Pathol Lab Med<br />
|abstract=Objective: To provide a critical review of recently published literature on the effectiveness, uses, and limitations of proficiency testing (PT) as a mechanism for laboratory improvement, and to explore ways to improve the PT process.<br />
<br />
Data source: All publications identified by a MEDLINE search of the literature dating back to 1987 on the subject of "proficiency testing" in laboratory medicine, as well as selected references cited in recent review articles.<br />
<br />
Study selection: No specific selection criteria were used for inclusion of publications identified by the MEDLINE database as long as they dealt with PT as a mechanism of medical laboratory improvement or a measure of laboratory performance.<br />
<br />
Data extraction: Abstractions of data were made depending on relevance of the data.<br />
<br />
Data synthesis: Proficiency testing data are an indicator, but not a measure, of laboratory performance. Limitations of current PT practices are incomplete assessment of the total testing process, PT materials being treated differently than those from patients, PT performance criteria, and "matrix effect." Proficiency testing performance has been related to length of PT experience, test environment and volume, institutional size, laboratory and analyst workload, difficulty of PT materials, performing quality control, testing methodology, and degree of automation.<br />
<br />
Conclusions: Proficiency testing has a well-established role as both a laboratory improvement and an educational tool. There are, however, several practical and design limitations even for the best-administered PT programs. Suggestions to improve the PT process include increased reliance on PT results in combination with other quality indicators (such as performance in regional surveys), occasional use of "blind" PT, introduction of biological materials to PT participants, electronic grading and reporting of PT results, and introduction of challenging PT materials to fulfill the educational role of PT.<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Scherz_2017_PLOS_One&diff=214532
Scherz 2017 PLOS One
2021-01-26T09:54:14Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Scherz V, Durussel C & Greub G (2017) Internal quality assurance in diagnostic microbiology: A simple approach for insightful data. PLOS One 12(11):e0187263.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/29135992/ PMID:29135992 Open Access]<br />
|authors=Scherz V, Durussel C & Greub G<br />
|year=2017<br />
|journal=PLOS One<br />
|abstract=Given the importance of microbiology results on patient care, high quality standards are expected. Internal quality assurance (IQA) could mitigate the limitations of internal quality control, competency assessment and external quality assurance, adding a longitudinal insight, including pre- and post-analytical steps. Here, we implemented an IQA program in our clinical microbiology facilities with blind resubmission of routine samples during 22 months. One-hundred-and-twenty-one out of 123 (98.4%) serological analyses and 112 out of 122 (91.8%) molecular analyses were concordant. Among the discordances in molecular biology analyses, 6 results were low positive samples that turned out negative, likely due to stochastic repartition of nucleic acids. Moreover, one identified retranscription error led us to implement automated results transmission from the Applied Biosystems instruments to the laboratory information system (LIS). Regarding Gram stain microscopy, 560 out of 745 (75.2%) of compared parameters were concordant. As many as 67 out of 84 (79.8%) pairs of culture results were similar, including 16 sterile pairs, 27 having identical identification or description and semi-quantification and 24 only showing variations in semi-quantification with identical description or identification of colonies. Seventeen pairs had diverging identification or description of colonies. Culture was twice only done for one member of the pairs. Regarding antibiotic susceptibility testing, a major discrepancy was observed in 5 out of 48 results (10.4%). In conclusion, serological tests were highly reproducible. Molecular diagnosis also revealed to be robust except when the amounts of nucleic acids present in the sample were close to the limits of detection. Conventional microbiology was less robust with major discrepancies reaching 39.5% of the samples for microscopy. Similarly, culture and antibiotic susceptibility testing were prone to discrepancies. This work was ground for reconsidering multiples aspects of our practices and demonstrates the importance of IQA to complete the other quality management procedures.<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Sakata_2006&diff=214531
Sakata 2006
2021-01-26T09:54:03Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Sakata S, White H (2006) Breakdown point. Encyclopedia of Statistical Sciences. Ed. John Wiley & Sons, Inc. 1-6.<br />
|info=[https://onlinelibrary.wiley.com/doi/abs/10.1002/0471667196.ess0607.pub2 Open Access]<br />
|authors=Sakata S, White H<br />
|year=2006<br />
|journal=Ed. John Wiley & Sons, Inc.<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Rej_1993_Arch_Pathol_Lab_Med&diff=214530
Rej 1993 Arch Pathol Lab Med
2021-01-26T09:53:51Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Rej R (1993) Accurate enzyme activity measurements: Two decades of development in the commutability of enzyme quality control materials. Arch Pathol Lab Med 117(4):352-64.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/8466397/ PMID:8466397]<br />
|authors=Rej R<br />
|year=1993<br />
|journal=Arch Pathol Lab Med<br />
|abstract=Commercial serum preparations are integral components of both internal and external quality control programs for enzyme activity measurements. However, properties of these materials may differ significantly from those of clinical specimens. Differences from clinical specimens may include the following: species origin of the enzyme; isoenzyme form(s); integrity of the molecular species; matrix of the solution; processes such as lyophilization; and addition of preservatives. There are also significant differences among methods measuring the activity of a single enzyme including a diversity of compounds that may serve as substrate(s); variable cofactor or metal supplementation; and differences in the substrate concentration(s), buffer substances, pH, and temperature. The measured response to each of these variations in assay technique may differ among these types of specimens. To be acceptable, quality control materials must have properties similar to those of clinical specimens. Thus, the concept of commutability that we originated and first applied to enzyme activity measurements remains useful, and its further application to the problem of "matrix effects" is reviewed here. Multivariate display techniques are applied to the specific examples of aspartate aminotransferase, alpha-amylase, and alkaline phosphatase to judge the commutability of quality control materials for these enzymes.<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Prager_2018_J_Neurosci_Res&diff=214529
Prager 2018 J Neurosci Res
2021-01-26T09:53:40Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Prager EM, Chambers KE, Plotkin JL, McArthur DL, Bandrowski AE, Bansal N, Martone ME, Bergstrom HC, Bespalov A, Graf C (2018) Improving transparency and scientific rigor in academic publishing. J Neurosci Res 97(16):1-14.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/30506706/ PMID:30506706 Open Access]<br />
|authors=Prager EM, Chambers KE, Plotkin JL, McArthur DL, Bandrowski AE, Bansal N, Martone ME, Bergstrom HC, Bespalov A, Graf C<br />
|year=2018<br />
|journal=J Neurosci Res<br />
|abstract=Progress in basic and clinical research is slowed when researchers fail to provide a complete and accurate report of how a study was designed, executed, and the results analyzed. Publishing rigorous scientific research involves a full description of the methods, materials, procedures, and outcomes. Investigators may fail to provide a complete description of how their study was designed and executed because they may not know how to accurately report the information or the mechanisms are not in place to facilitate transparent reporting. Here, we provide an overview of how authors can write manuscripts in a transparent and thorough manner. We introduce a set of reporting criteria that can be used for publishing, including recommendations on reporting the experimental design and statistical approaches. We also discuss how to accurately visualize the results and provide recommendations for peer reviewers to enhance rigor and transparency. Incorporating transparency practices into research manuscripts will significantly improve the reproducibility of the results by independent laboratories.<br />
|keywords=Open Science; peer review; policy; publishing; scientific rigor; transparency<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Menditto_2006_Accred_Qual_Asur&diff=214528
Menditto 2006 Accred Qual Asur
2021-01-26T09:53:28Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Menditto A, Patriarca M, Magnusson B (2006) Understanding the meaning of accuracy, trueness and precision. Accred Qual Asur 12:45-47.<br />
|info=[https://link.springer.com/article/10.1007/s00769-006-0191-z Springer Link]<br />
|authors=Menditto A, Patriarca M, Magnusson B<br />
|year=2006<br />
|journal=Accred Qual Asur<br />
|abstract=Clear definitions of basic terms, used to describe the quality of measurements, is essential for communication among scientists as well as when reporting measurement results to clients. Even if appropriate definitions are given in international standards and guidelines, the understanding of some basic terms sometimes proves difficult. The reasons for this are various, e.g., the same words being defined rather differently in encyclopaedias and in international standards as well as concepts, well established in some languages, that may be relatively new in other national communities and at large in the international one. Here we present a matrix intended to clarify the relationships between the type of error affecting an analytical measurement, the respective qualitative concepts (performance characteristics) and their quantitative expression.<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Mann_2011&diff=214527
Mann 2011
2021-01-26T09:53:17Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Mann BB, Brookman B (2011) Eurachem Guide: Selection, Use and Interpretation of Proficiency Testing Schemes (2nd Ed.)<br />
|info=[https://www.eurachem.org/images/stories/Guides/pdf/Eurachem_PT_Guide_2011.pdf Open Access]<br />
|authors=Mann BB, Brookman B<br />
|year=2011<br />
|journal=Eurachem<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Magnusson_2018&diff=214526
Magnusson 2018
2021-01-26T09:52:23Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Magnusson B, Hovind H, Krysell M, Lund U, Mäkinen I (2018) Handbook-Inter quality control. Nordtest report TR 596 (Ed. 5)<br />
|info=[http://www.nordtest.info/wp/wp-content/uploads/2018/04/NT_TR_569_ed5_1_Internal_Quality_Control_English.pdf Open Access]<br />
|authors=Magnusson B, Hovind H, Krysell M, Lund U, Mäkinen I<br />
|year=2018<br />
|journal=<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Macleod_2014_Lancet&diff=214525
Macleod 2014 Lancet
2021-01-26T09:52:03Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Macleod MR, Michie S, Roberts I, Dirnagl U, Chalmers I, Ioanidis JPA, Salman RAS, Chan AW, Glasziou P (2014) Biomedicel research: increasing value, reducing waste.. Lancet 383(9912):101-4.<br />
|info=[https://pubmed.ncbi.nlm.nih.gov/24411643/ PMID: 24411643]<br />
|authors=Macleod MR, Michie S, Roberts I, Dirnagl U, Chalmers I, Ioanidis JPA, Salman RAS, Chan AW, Glasziou P<br />
|year=2014<br />
|journal=Lancet<br />
|abstract=Of 1575 reports about cancer prognostic markers published in 2005, 1509 (96%) detailed at least<br />
one significant prognostic variable. However, few identifi ed biomarkers have been confirmed by<br />
subsequent research and few have entered routine clinical practice. This pattern—initially promising findings not leading to improvements in health care—has been recorded across biomedical research.<br />
So why is research that might transform health care and reduce health problems not being successfully produced?<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Levitsky_2019_RSC_Adv&diff=214524
Levitsky 2019 RSC Adv
2021-01-26T09:51:51Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Levitsky Y, Pegouske DJ, Hammer SS, Frantz NL, Fisher KP, Muchnik AB, Saripalli AR, Kirschner P, Bazil JN, Busik JV, Proshlyakov DA (2019) Micro-respirometry of whole cells and isolated mitochondria. RSC Adv 9:33257-33267.<br />
|info=[https://pubs.rsc.org/en/content/articlelanding/2019/RA/C9RA05289E#!divAbstract Royal Society of Chemistry]<br />
|authors=Levitsky Y, Pegouske DJ, Hammer SS, Frantz NL, Fisher KP, Muchnik AB, Saripalli AR, Kirschner P, Bazil JN, Busik JV, Proshlyakov DA<br />
|year=2019<br />
|journal=RSC Adv<br />
|abstract=Oxygen consumption is a key metric of metabolism in aerobic organisms. Current respirometric methods led to seminal discoveries despite limitations such as high sample demand, exchange with atmospheric O2, and cumulative titration protocols leading to limited choice of useable tissue, complex data interpretation, and restricted experimental design. We developed a sensitive and customizable method of measuring O2 consumption rates by a variety of biological samples in microliter volumes without interference from the aerobic environment. We demonstrate that O2 permeability of the photopolymer, VeroClear, is comparable to that of polyetheretherketone (0.125 vs. 0.143 barrer, respectively) providing an efficient barrier to oxygen ingress. Optical transparency of VeroClear, combined with high resolution 3D printing, allows for optode-based oxygen detection in enclosed samples. These properties yield a microrespirometer with over 100× dynamic range for O2 consumption rates. Importantly, the enclosed respirometer configuration and very low oxygen permeability of materials makes it suitable, with resin pre-conditioning, for quantitative assessment of O2 consumption rates at any desired [O2], including hyperbaric, physiological or hypoxic conditions as necessary for each cell type. We characterized two configurations to study soluble enzymes, isolated mitochondria, cells in suspension, and adherent cells cultured on-chip. Improved sensitivity allows for routine quantitative detection of respiration by as few as several hundred cells. Specific activity of cell suspensions in the microrespirometer was in close agreement with that obtained by high-resolution polarographic respirometry. Adherent cell protocols allowed for physiologically relevant assessment of respiration in retinal pigment epithelial cells, ARPE-19, which displayed lower metabolic rates compared with those in suspension. By exchanging medium composition, we demonstrate that cells can be transiently inhibited by cyanide and that 99.6% of basal O2 uptake is recovered upon its removal. This approach is amenable to new experimental designs and precision measurements on limited sample quantities across basic research and applied fields.<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Lazic_2016&diff=214523
Lazic 2016
2021-01-26T09:51:38Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Lazic SE (2016) Experimental design for laboratory biologists. Maximizing information and improving reproducibility. Cambridge University Press 1.<br />
|info=[https://www.cambridge.org/highereducation/books/experimental-design-for-laboratory-biologists/31C1A347D0ADB25226D7220A99C0EF56 Cambridge University Press]<br />
|authors=Lazic SE<br />
|year=2016<br />
|journal=Cambridge University Press<br />
|abstract=Specifically intended for lab-based biomedical researchers, this practical guide shows how to design experiments that are reproducible, with low bias, high precision, and widely applicable results. With specific examples from research using both cell cultures and model organisms, it explores key ideas in experimental design, assesses common designs, and shows how to plan a successful experiment. It demonstrates how to control biological and technical factors that can introduce bias or add noise, and covers rarely discussed topics such as graphical data exploration, choosing outcome variables, data quality control checks, and data pre-processing. It also shows how to use R for analysis, and is designed for those with no prior experience. An accompanying website (https://stanlazic.github.io/EDLB.html) includes all R code, data sets, and the labstats R package. This is an ideal guide for anyone conducting lab-based biological research, from students to principle investigators working in either academia or industry.<br />
|editor=[[Iglesias-Gonzalez J]]<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|additional=MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier
https://wiki.oroboros.at/index.php?title=Krajcova_2020_PLOS_ONE&diff=214522
Krajcova 2020 PLOS ONE
2021-01-26T09:51:21Z
<p>Iglesias-Gonzalez Javier: </p>
<hr />
<div>{{Publication<br />
|title=Krajčová A, Urban T, Megvinet D, Waldauf P, Balík M, Hlavička J, Budera P, Janoušek L, Pokorná E, Duška F (2020) High resolution respirometry to assess function of mitochondria in native homogenates of human heart muscle. PLOS ONE 15:e0226142.<br />
|info=[https://www.ncbi.nlm.nih.gov/pubmed/31940313 PMID: 31940313 Open Access]<br />
|authors=Krajcova A, Urban T, Megvinet D, Waldauf P, Balik M, Hlavicka J, Budera P, Janousek L, Pokorna E, Duska F<br />
|year=2020<br />
|journal=PLOS ONE<br />
|abstract=Impaired myocardial bioenergetics is a hallmark of many cardiac diseases. There is a need of a simple and reproducible method of assessment of mitochondrial function from small human myocardial tissue samples. In this study we adopted high-resolution respirometry to homogenates of fresh human cardiac muscle and compared it with isolated mitochondria. We used atria resected during cardiac surgery (''N'' = 18) and atria and left ventricles from brain-dead organ donors (''N'' = 12). The protocol we developed consisting of two-step homogenization and exposure of 2.5 % homogenate in a respirometer to sequential addition of 2.5 mM malate, 15 mM glutamate, 2.5 mM ADP, 10 μM cytochrome ''c'', 10 mM succinate, 2.5 μM oligomycin, 1.5 μM FCCP, 3.5 μM rotenone, 4 μM antimycin and 1 mM KCN or 100 mM sodium azide. We found a linear dependence of oxygen consumption on oxygen concentration. This technique requires < 20 mg of myocardium and the preparation of the sample takes <20 min. Mitochondria in the homogenate, as compared to subsarcolemmal and interfibrillar isolated mitochondria, have comparable or better preserved integrity of outer mitochondrial membrane (increase of respiration after addition of cytochrome ''c'' is up to 11.7±1.8 % vs. 15.7±3.1 %, ''p''˂0.05 and 11.7±3.5 %, ''p'' = 0.99, resp.) and better efficiency of oxidative phosphorylation (respiratory control ratio = 3.65±0.5 vs. 3.04±0.27, ''p''˂0.01 and 2.65±0.17, ''p''˂0.0001, resp.). Results are reproducible with coefficient of variation between two duplicate measurements ≤8% for all indices. We found that whereas atrial myocardium contains less mitochondria than the ventricle, atrial bioenergetic profiles are comparable to left ventricle. In conclusion, high-resolution respirometry has been adapted to homogenates of human cardiac muscle and shown to be reliable and reproducible.<br />
|editor=[[Gnaiger E]],<br />
|mipnetlab=CZ Prague Krajcova A<br />
}}<br />
== Cited by ==<br />
{{Template:Cited by Iglesias-Gonzalez 2021 MitoFit PT}}<br />
{{Labeling<br />
|area=Respiration<br />
|injuries=Cryopreservation<br />
|organism=Human<br />
|tissues=Heart<br />
|preparations=Homogenate, Isolated mitochondria<br />
|topics=Oxygen kinetics<br />
|couplingstates=LEAK, OXPHOS, ET<br />
|pathways=N, S, NS, ROX<br />
|instruments=Oxygraph-2k<br />
|additional=Alert2020, MitoFit 2021 PT<br />
}}</div>
Iglesias-Gonzalez Javier