A Case for Using Plethodontid Salamanders for Monitoring Biodiversity and Ecosystem Integrity of North American Forests

Many patients treated with vitamin K antagonists (VKA) determine their INR using point-of-care (POC) whole blood coagulation monitors. The primary aim of the present study was to assess the INR within-subject variation in self-testing patients receiving a constant dose of VKA. The second aim of the study was to derive INR imprecision goals for whole blood coagulation monitors. Analytical performance goals for INR measurement can be derived from the average biological within-subject variation. Fifty-six Thrombosis Centres in the Netherlands were invited to select self-testing patients who were receiving a constant dose of either acenocoumarol or phenprocoumon for at least six consecutive INR measurements. In each patient, the coefficient of variation (CV) of INRs was calculated. One Thrombosis Centre selected regular patients being monitored with a POC device by professional staff. Sixteen Dutch Thrombosis Centres provided results for 322 selected patients, all using the CoaguChek XS. The median within-subject CV in patients receiving acenocoumarol (10.2 %) was significantly higher than the median CV in patients receiving phenprocoumon (8.6 %) (p = 0.001). The median CV in low-target intensity acenocoumarol self-testing patients (10.4 %) was similar to the median CV in regular patients monitored by professional staff (10.2 %). Desirable INR analytical imprecision goals for POC monitoring with CoaguChek XS in patients receiving either low-target intensity acenocoumarol or phenprocoumon were 5.1 % and 4.3 %, respectively. The approximate average value for the imprecision of the CoaguChek XS, i. e. 4 %, is in agreement with these goals.

BackgroundPET with O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET) has reached increasing clinical significance for patients with brain neoplasms. For quantification of standard PET-derived parameters such as the tumor-to-background ratio, the background activity is assessed using a region of interest (ROI) or volume of interest (VOI) in unaffected brain tissue. However, there is no standardized approach regarding the assessment of the background reference. Therefore, we evaluated the intra- and inter-reader variability of commonly applied approaches for clinical 18F-FET PET reading.The background activity of 20 18F-FET PET scans was independently evaluated by 6 readers using a (i) simple 2D-ROI, (ii) spherical VOI with 3.0 cm diameter, and (iii) VOI consisting of crescent-shaped ROIs; each in the contralateral, non-affected hemisphere including white and gray matter in line with the European Association of Nuclear Medicine (EANM) and German guidelines. To assess intra-reader variability, each scan was evaluated 10 times by each reader. The coefficient of variation (CoV) was assessed for determination of intra- and inter-reader variability. In a second step, the best method was refined by instructions for a guided background activity assessment and validated by 10 further scans.ResultsCompared to the other approaches, the crescent-shaped VOIs revealed most stable results with the lowest intra-reader variabilities (median CoV 1.52%, spherical VOI 4.20%, 2D-ROI 3.69%; p < 0.001) and inter-reader variabilities (median CoV 2.14%, spherical VOI 4.02%, 2D-ROI 3.83%; p = 0.001). Using the guided background assessment, both intra-reader variabilities (median CoV 1.10%) and inter-reader variabilities (median CoV 1.19%) could be reduced even more.ConclusionsThe commonly applied methods for background activity assessment show different variability which might hamper 18F-FET PET quantification and comparability in multicenter settings. The proposed background activity assessment using a (guided) crescent-shaped VOI allows minimization of both intra- and inter-reader variability and might facilitate comprehensive methodological standardization of amino acid PET which is of interest in the light of the anticipated EANM technical guidelines.

The aim of this study was to prepare control blood for an external quality assessment scheme (EQAS) for international normalized ratio (INR) point-of-care testing (POCT) in the Netherlands and to assess the performance of the participants. Control blood was prepared from dialyzed pooled patient plasma and washed human erythrocytes. Samples of control blood were mailed to participants of the Netherlands EQAS from October 2006 through December 2012. Most participants used CoaguChek XS (Roche Diagnostics, Mannheim, Germany) devices for POCT. The median between-center coefficient of variation (CV) of the reported INR decreased from 4.5% in 2006 to 2.6% in 2012. A few participants used the ProTime Microcoagulation System (ITC, Edison, NJ) for POCT. The median CV (per year) of the INR with the latter system was 7.0% to 10.6%. The control blood samples were useful for external quality assessment in the Netherlands. The participants' performance with the CoaguChek XS system improved with time, demonstrating the value of external quality assessment.

BackgroundCurrent quantification methods for mass spectrometry (MS)-based proteomics either do not provide sufficient control of variability or are difficult to implement for routine clinical testing.ResultsWe present here an integrated quantification (InteQuan) method that better controls pre-analytical and analytical variability than the popular quantification method using stable isotope-labeled standard peptides (SISQuan). We quantified 16 lung cancer biomarker candidates in human plasma samples in three assessment studies, using immunoaffinity depletion coupled with multiple reaction monitoring (MRM) MS. InteQuan outperformed SISQuan in precision in all three studies and tolerated a two-fold difference in sample loading. The three studies lasted over six months and encountered major changes in experimental settings. Nevertheless, plasma proteins in low ng/ml to low μg/ml concentrations were measured with a median technical coefficient of variation (CV) of 11.9% using InteQuan. The corresponding median CV using SISQuan was 15.3% after linear fitting. Furthermore, InteQuan surpassed SISQuan in measuring biological difference among clinical samples and in distinguishing benign versus cancer plasma samples.ConclusionsWe demonstrated that InteQuan is a simple yet robust quantification method for MS-based quantitative proteomics, especially for applications in biomarker research and in routine clinical testing.Electronic supplementary materialThe online version of this article (doi:10.1186/1559-0275-12-3) contains supplementary material, which is available to authorized users.

Microalbuminuria is a risk factor for renal failure, stroke, and cardiovascular disease. However, estimating laboratory precision for albumin excretion is problematic because of its highly skewed distribution and the presence of values below assay detection limits. The authors used 781 quality control pairs from 24-hour urine samples collected between 1996 and 1999 in the International Study on Macronutrients and Blood Pressure (INTERMAP) to compare percentage of technical error (%TE), the usual estimate of laboratory precision, with the mean and median values of within-pair coefficients of variation (CVs) for urinary albumin concentration and other urinary variables. In INTERMAP, %TE was larger than mean CV for all variables. Exclusion of potentially mislabeled samples reduced this difference; for example, for sodium, estimates of %TE and mean and median CV were 2.37%, 0.75%, and 0.28%, respectively, for all 781 pairs and 0.84%, 0.48%, and 0.27%, respectively, with possibly mislabeled pairs excluded. For urinary albumin concentration, exclusion of one mislabeled pair changed estimates for %TE and mean CV from 29.6% and 20.8% to 20.6% and 20.6%, while median CV was unchanged at 9.4%. After exclusion of urinary albumin concentration pairs with values below the detection limit, estimates were 15.4%, 11.4%, and 6.4%, respectively. Results indicate that mean and median CV are not equivalent to %TE and that values below the detection limit can markedly affect estimates and should be excluded.

PP09 Presentation Time: 10:50 AM: Interobserver Variability of Prostate MRI-Assisted Radiosurgery Postimplant Dosimetry: Comparison with Automatic Postimplant Dosimetry

Background: Impaired endogenous insulin secretion was related to instability of glucose variability (GV) in patients with type 2 diabetes (T2DM) in our previous studies. However, some patients, including those with fasting serum C-peptide (CPR) ≤2 ng/mL, did not show this relationship. Given these findings, the present study aimed to identify other factors that affect GV in T2DM patients with impaired endogenous insulin secretion. Methods: Data were obtained from our prospective observational study, comprising 2Japanese outpatients with T2DM who underwent continuous glucose monitoring (CGM) , fasting blood sample collection, and a computed tomography scan of their abdominal visceral and subcutaneous fat. Fasting CPR was used as a marker of endogenous insulin secretion and the coefficient of variation (CV) for the CGM data was used as a measure of GV. Background characteristics related to unstable GV were identified by multivariate logistic regression analysis after we extracted the data for patients with T2DM and CPR ≤2 ng/mL. All tests were two-sided. P&amp;lt;0.was considered to indicate statistical significance. Results: In the total cohort, mean age was 67.0 (IQR 58.0, 74.8) years, mean HbA1c 7.1% (IQR 6.6%, 7.7%) , and mean body mass index (BMI) 25.0 (IQR 23.0, 28.4) kg/m2. In patients with low CPR (≤2 ng/mL; n=119) , small visceral fat area (VFA) was an independent risk factor for CV above the median CV (OR 0.98, 95% CI 0.97-0.99, P=0.0443) , while subcutaneous fat area (SFA) and BMI were equally distributed. In patients with high CPR (&amp;gt;2 ng/mL; n=85) , VFA, SFA, and BMI were equally distributed between patients with CV above or below the median CV. Conclusions: GV is unstable in T2DM patients with impaired endogenous insulin secretion, particularly in patients with small VFA. The present findings suggest that visceral fat is related to the stability of GV. Disclosure A.Miya: None. A.Nakamura: Research Support; Kissei Pharmaceutical Co., Ltd., MSD, Nippon Boehringer Ingelheim, Taisho Pharmaceutical Holdings Co., Ltd. H.Nomoto: None. H.Kameda: None. K.Cho: None. S.Nagai: Other Relationship; Eli Lilly and Company. Y.M.Ito: None. H.Miyoshi: Research Support; Abbott Japan Co., Ltd., Boehringer Ingelheim International GmbH, Daiichi Sankyo, Kowa Company, Ltd., LifeScan, Mitsubishi Tanabe Pharma Corporation, Novo Nordisk, Ono Pharmaceutical Co., Ltd., Sumitomo Dainippon Pharma Co., Ltd., Taisho Pharmaceutical Holdings Co., Ltd., Speaker’s Bureau; Astellas Pharma Inc., Boehringer Ingelheim International GmbH, Eli Lilly and Company, Kowa Company, Ltd., Merck &amp; Co., Inc., Mitsubishi Tanabe Pharma Corporation, Novo Nordisk, Ono Pharmaceutical Co., Ltd., Sanofi K.K., Sumitomo Dainippon Pharma Co., Ltd., Taisho Pharmaceutical Holdings Co., Ltd. T.Atsumi: Consultant; AbbVie Inc., AstraZeneca, MEDICAL &amp; BIOLOGICAL LABORATORIES CO., Nippon Boehringer Ingelheim Co. Ltd., Novartis Pharma K.K., Ono Pharmaceutical Co., Ltd., Pfizer Inc., Research Support; AbbVie Inc., Alexion Pharmaceuticals, Inc., Astellas Pharma Inc., Chugai Pharmaceutical Co., Ltd., Daiichi Sankyo, Mitsubishi Tanabe Pharma Corporation, Nippon Boehringer Ingelheim Co. Ltd., Otsuka Pharmaceutical Co., Ltd., Pfizer Inc., Taiho Pharmaceutical Co. Ltd., Takeda Pharmaceutical Company Limited, Teijin Pharma Limited, Speaker’s Bureau; AbbVie Inc., Astellas Pharma Inc., Bristol-Myers Squibb Company, Chugai Pharmaceutical Co., Ltd., Daiichi Sankyo, Eisai Co., Ltd., Eli Lilly and Company, Kyowa Kirin Co., Ltd., Mitsubishi Tanabe Pharma Corporation, Novartis Pharma K.K., Pfizer Inc., Taiho Pharmaceutical Co. Ltd., Takeda Pharmaceutical Company Limited, UCB, Inc.

Interlaboratory Validation of a 3-Tube 10-Color Antibody Flow Cytometry Panel for Diagnosis of Myelodysplastic Syndromes

Quantitative proteomics plays an important role in validation of breast-cancer-related biomarkers. In this study, we systematically compared the performance of label-free quantification (LFQ) and SILAC with shotgun and directed methods for quantifying breast-cancer-related markers in microdissected tissues. We show that LFQ leads to slightly higher coefficient of variation (CV) for protein quantification (median CV = 16.3%) than SILAC quantification (median CV = 13.7%) (P < 0.0001), but LFQ method enables ∼60% more protein quantification and is also more reproducible (∼20% more proteins were quantified in all replicate samples). Furthermore, we describe a method to accurately quantify multiple proteins within one pathway, that is, "focal adhesion pathway", in trace amounts of breast cancer tissues using a SILAC-based SRM assay. Using this SILAC-based SRM assay, we precisely quantified five "focal adhesion" proteins with good quantitative precision (CV range: 2.4-5.9%) in replicate whole tissue lysate samples and replicate microdissected samples (CV range: 5.8-16.1%). Our results show that in microdissected breast cancer tissues LFQ in combination with shotgun proteomics performed the best overall and is therefore suitable for both biomarker discovery and validation in these types of specimens. The SILAC-based SRM method can be used for the development of clinically relevant protein assays in tumor biopsies.

Introduction: In patients with Cushing’s Disease (CD), intrapatient variability of hormone measurements creates significant clinical challenges, therefore multiple measurements are recommended.1 Urinary and salivary cortisol variation has been well described. However, intrapatient variation of adrenocorticotropic hormone (ACTH) in CD remains unknown. In CD patients, ACTH levels are inherently elevated from baseline but the coefficient of diurnal variation is reduced.2Additionally, at each diurnal time point, these exists a significant variation around the mean for the ACTH levels. In this study, we first analyzed the intrapatient variablility of ACTH at each diurnal timepoint in patients with CD. CD is primarily a disorder of ACTH excess, and treatment directed at pituitary adenomas would presumably perturb ACTH levels prior to affecting serum or urine cortisol. We hypothesized that the coefficient of variation at each diurnal time-point can help predict remission from CD following surgery.Methods: We conducted a retrospective review of patients (n = 645) who had histopathologically confirmed diagnosis of CD from 2005-2019 (NCT NCT00060541). We selected patients that had ≥ 3 plasma ACTH values over a 7 day span prior to surgical or medical intervention. We grouped the ACTH measurements into morning (AM) and midnight (PM) values to account for diurnal variation in ACTH secretion. We then analyzed post-operative hormone measurements performed every 6 hours prior to administration of replacement corticosteroids. Remission was assigned to patients with nadir serum cortisol level ≤5 mcg/dL within ten days post-operatively3,4.Results: We found 54 patients with multiple PM (n = 27) and AM (n = 41) ACTH measurements within a 7 day span. We found that the median coefficient of variation (CV) of intra-patient variability was 19.7% (N=41) (95% CI:12.5-27.5) for the AM and was 24% (N=27) (95% CI: 9.6-31.8) for the PM. Age, the number of tests, or the length of test period were not correlated with CV or absolute levels of ACTH. The intraclass correlation coefficient (ICC) of the AM data set was 0.59 and the PM data set was 0.79 which demonstrates a good and excellent reliability respectively. We found that that, in general, 30-60% decrease from pre-operative ACTH levels predicted remission from CD. ACTH decrease >50% on POD2 and 3 had 100% specificity and sensitivity in predicting remission. The decrease in ACTH preceded cortisol nadir in 3/10 patients by 24 hours.Conclusion: We found significant intra-patient variability in plasma levels of ACTH at individual diurnal timepoints in CD patients. We also found that the change in ACTH >50% on POD2 or 3 is an excellent predictor of remission from CD.

Knowledge about the extent of total variation experienced between samples from different individuals is of great importance for the design of not only proteomics but every clinical study. This variation defines the smallest statistically significant detectable signal difference when comparing two groups of individuals. We isolated platelets from 20 healthy human volunteers aged 56-100 years because this age group is most commonly encountered in the clinics. We determined the technical and total variation experienced in a proteome analysis using two-dimensional DIGE with IPGs in the pI ranges 4-7 and 6-9. Only spots that were reproducibly detectable in at least 90% of all gels (n = 908) were included in the study. All spots had a similar technical variation with a median coefficient of variation (cv) of about 7%. In contrast, spots showed a more diverse total variation between individuals with a surprisingly low median cv of only 18%. Because most known biomarkers show an effect size in a 1-2-fold range of their cv, any future clinical proteomics study with platelets will require an analytical method that is able to detect such small quantitative differences. In addition, we calculated the minimal number of samples (sample size) needed to detect given protein expression differences with statistical significance.

To evaluate the significance of CT perfusion parameters predicting response to neoadjuvant therapy in patients with pancreatic ductal adenocarcinoma (PDAC). Seventy patients with PDAC prospectively had CT perfusion acquisition incorporated into baseline multiphase staging CT. Twenty-eight who were naïve to therapy were retained for further investigation. Perfusion was performed 5-42.5s after contrast, followed by parenchymal and portal venous phases. Blood flow (BF), blood volume (BV), and permeability surface area product (PS) were calculated using deconvolution algorithms. Patients were categorized as responders or non-responders per RECIST 1.1. Perfusion variables with AUC ≥ 0.70 in differentiating responders from non-responders were retained. Logistic regression was used to assess associations between baseline perfusion variables and response. 18 of 28 patients showed favorable response to therapy. Baseline heterogeneity variables in tumor max ROI were higher in non-responders than responders [median BF coefficient of variation (CV) 0.91 vs. 0.51 respectively, odds ratio (OR) 6.8 per one standard deviation (1-SD) increase, P = 0.047; median PS CV 1.6 vs. 0.68, OR 3.9 per 1-SD increase, P = 0.047; and median BV CV 0.75 vs. 0.54, OR = 4.0 per 1-SD increase, P = 0.047]. Baseline BV mean in tumor center was lower in non-responders than responders (median BV mean: 0.74 vs. 2.9ml/100g respectively, OR 0.28 per 1-SD increase, P = 0.047). For patients with PDAC receiving neoadjuvant therapy, lower and more heterogeneous perfusion parameters correlated with an unfavorable response to therapy. Such quantitative information can be acquired utilizing a comprehensive protocol interleaving perfusion CT acquisition with standard of care multiphase CT scans using a single contrast injection, which could be used to identify surgical candidates and predict outcome.

Introduction: High tacrolimus intrapatient variability is associated with poor outcomes following transplantation. A commonly hypothesized cause of this variability is medication non-adherence, but this has not been conclusively demonstrated. Research Question: The purpose of this study was to evaluate the relationship between medication adherence and tacrolimus intrapatient variability. Design: This was a retrospective cohort study of kidney transplant recipients. Adherence was assessed at the 12-month clinic visit as a composite of patient self-report, pharmacist assessment, and lab monitoring frequency. Tacrolimus intrapatient variability was calculated as the coefficient of variation (CV). Linear regression and receiver operating curve (ROC) analysis were used to assess the relationship between adherence and CV. Results: Nonadherence was identified in 37.5% of patients. The median CV was 27.1% for adherent patients and 29.8% for non-adherent patients (P = 0.051). In the multivariable analysis, the only significant predictor of CV was the incidence of dose changes (P = 0.002). ROC analysis demonstrated poor discriminant power with an AUC of 0.597. Discussion: The results fail to support a clinically meaningful relationship between medication adherence and tacrolimus CV. There is very little evidence at this time that adherence is the primary contributing factor to tacrolimus intrapatient variability and, by extension, that CV can be used as a surrogate for adherence.

Editor's evaluation: The Cl--channel TMEM16A is involved in the generation of cochlear Ca2+ waves and promotes the refinement of auditory brainstem networks in mice

Decision letter: The Cl--channel TMEM16A is involved in the generation of cochlear Ca2+ waves and promotes the refinement of auditory brainstem networks in mice