scholarly journals Comparative Pathologists: Ultimate Control Freaks Seeking Validation!

2018 ◽  
Vol 56 (1) ◽  
pp. 19-23 ◽  
Author(s):  
Krista M. D. La Perle
Keyword(s):  
Experimental Design ◽  
Model Development ◽  
Clinical Pathology ◽  
Scoring Systems ◽  
Data Interpretation ◽  
Tissue Sampling ◽  
Sample Collection ◽  
Slide Preparation ◽  
Histopathologic Evaluation ◽  
Pathology Data

Definable, reproducible, and meaningful are elemental features of grading/scoring systems, while thoroughness, accuracy, and consistency are quality indicators of pathology reports. The expertise of pathologists is significantly underutilized when it is limited to rendering diagnoses. The opportunity to provide guidance on animal model development, experimental design, optimal sample collection, and data interpretation not only contributes to job satisfaction but also, more importantly, promotes validation of the pathology data. Keys to validation include standard operating procedures, experimental controls, and standardized nomenclature applied throughout the experimental design and execution, tissue sampling, and slide preparation, as well as the creation or adaptation and application of semiquantitative grading/scoring systems. Diagnostic drift, thresholds, mental noise, and various diurnal fluctuations strongly influence the repeatability of grading/scoring systems used by the same or different pathologists. Quantitative image analyses are not plagued by the visual and cognitive traps that affect manual semiquantitative grading schemes but may still be affected by technical variables associated with necropsy, tissue sampling, and slide preparation. The validity of a grading scheme is ultimately assessed by its repeatability and biologic relevance, so it is important to correlate scores with comprehensive pathobiology data such as results of antemortem imaging, clinical pathology data, body and organ weights, and histopathologic evaluation of full tissue sets.

scholarly journals Deciphering Sources of Variability in Clinical Pathology

2016 ◽  
Vol 45 (1) ◽  
pp. 90-93 ◽  
Author(s):  
Niraj K. Tripathi ◽  
Nancy E. Everds ◽  
A. Eric Schultze ◽  
Armando R. Irizarry ◽  
Robert L. Hall ◽  
...  
Keyword(s):  
Study Design ◽  
Toxicity Testing ◽  
Clinical Pathology ◽  
Data Interpretation ◽  
Potential Effect ◽  
Reference Intervals ◽  
Sample Collection ◽  
Related Factors ◽  
Specimen Handling ◽  
Pathology Data

The objectives of this session were to explore causes of variability in clinical pathology data due to preanalytical and analytical variables as well as study design and other procedures that occur in toxicity testing studies. The presenters highlighted challenges associated with such variability in differentiating test article–related effects from the effects of experimental procedures and its impact on overall data interpretation. These presentations focused on preanalytical and analytical variables and study design–related factors and their influence on clinical pathology data, and the importance of various factors that influence data interpretation including statistical analysis and reference intervals. Overall, these presentations touched upon potential effect of many variables on clinical pathology parameters, including animal physiology, sample collection process, specimen handling and analysis, study design, and some discussion points on how to manage those variables to ensure accurate interpretation of clinical pathology data in toxicity studies. This article is a brief synopsis of presentations given in a session entitled “Deciphering Sources of Variability in Clinical Pathology—It’s Not Just about the Numbers” that occurred at the 35th Annual Symposium of the Society of Toxicologic Pathology in San Diego, California.

Brief Synopsis: “Instruction Manual for Juvenile Clinical Pathology”

2021 ◽  
pp. 019262332110413
Author(s):  
Anne Provencher ◽  
Paula Katavolos
Keyword(s):  
Data Analysis ◽  
Clinical Pathology ◽  
Data Interpretation ◽  
Physiological Functions ◽  
Instruction Manual ◽  
Test Article ◽  
Accurate Interpretation ◽  
Key Points ◽  
Pathology Data

This symposium synopsis summarizes key points discussed related to clinical pathology data interpretation for reproduction and juvenile toxicology studies. In pregnant and growing animals, several changes in clinical pathology parameters linked to growth/maturation of organ and physiological functions can occur, and understanding these changes is important to enable accurate interpretation of clinical pathology data. A brief overview of the general approach to clinical pathology data analysis according to contemporary practices is provided, followed by a discussion focused specifically on reproductive and juvenile clinical pathology. In this context, the approach to recognize and differentiate changes that may be related to pregnancy and growth as opposed to those that may be related to test article effects is highlighted.

Factors Affecting the Interpretation of Canine and Nonhuman Primate Clinical Pathology

2003 ◽  
Vol 31 (1_suppl) ◽  
pp. 6-10 ◽  
Author(s):  
Robert L. Hall ◽  
Nancy E. Everds
Keyword(s):  
Study Design ◽  
Nonhuman Primate ◽  
Clinical Chemistry ◽  
Clinical Pathology ◽  
Data Interpretation ◽  
Pharmacokinetic Analysis ◽  
Test Results ◽  
Sample Collection ◽  
Test Species ◽  
Design Variables

Interpreting canine and nonhuman primate clinical pathology data from preclinical studies can be challenging. Relatively few animals are tested (typically beagles and macaques), and they often undergo study-related procedures (eg, sample collection for pharmacokinetic analysis) that can affect clinical pathology test results. Data interpretation requires an understanding of the significance of each test, species differences for each test, normal interanimal and intraanimal variability, the effects of study design variables, and supporting data from other disciplines. Interpretation of hematology, coagulation, clinical chemistry, and urinalysis parameters are discussed, with emphasis on species peculiarities and study design variables that may affect clinical pathology test results.

scholarly journals STP Best Practices for Evaluating Clinical Pathology in Pharmaceutical Recovery Studies

2016 ◽  
Vol 44 (2) ◽  
pp. 163-172 ◽  
Author(s):  
Lindsay Tomlinson ◽  
Lila Ramaiah ◽  
Niraj K. Tripathi ◽  
Valerie G. Barlow ◽  
Allison Vitsky ◽  
...  
Keyword(s):  
Best Practices ◽  
Vaccine Development ◽  
Clinical Pathology ◽  
Data Interpretation ◽  
Recovery Phase ◽  
Development Programs ◽  
Toxicity Studies ◽  
Delayed Toxicity ◽  
American Society ◽  
Pathology Data

The Society of Toxicologic Pathology formed a working group in collaboration with the American Society for Veterinary Clinical Pathology to provide recommendations for the appropriate inclusion of clinical pathology evaluation in recovery arms of nonclinical toxicity studies but not on when to perform recovery studies. Evaluation of the recovery of clinical pathology findings is not required routinely but provides useful information on risk assessment in nonclinical toxicity studies and is recommended when the ability of the organ to recover is uncertain. The study design generally requires inclusion of concurrent controls to separate procedure-related changes from test article–related changes, but return of clinical pathology values toward baseline may be sufficient in some cases. Evaluation of either a select or full panel of standard hematology, coagulation, and serum and urine chemistry biomarkers can be scientifically justified. It is also acceptable to redesignate dosing phase animals to the recovery phase or vice versa to optimize data interpretation. Assessment of delayed toxicity during the recovery phase is not required but may be appropriate in development programs with unique concerns. Evaluation of the recovery of clinical pathology data for vaccine development is required and, for efficacy markers, is recommended if it furthers pharmacologic understanding.

scholarly journals Practical Considerations in Clinical Pathology Data Interpretation and Description

2016 ◽  
Vol 45 (2) ◽  
pp. 362-365 ◽  
Author(s):  
Robert L. Hall
Keyword(s):  
Safety Assessment ◽  
Clinical Pathology ◽  
Data Interpretation ◽  
Potential Effect ◽  
Reference Intervals ◽  
Standard Approach ◽  
Test Results ◽  
Assessment Study ◽  
Preclinical Safety ◽  
Pathology Data

Although interpretation and description of clinical pathology test results for any preclinical safety assessment study should employ a consistent standard approach, companies differ regarding that approach and the appearance of the end product. Some rely heavily on statistical analysis, others do not. Some believe reference intervals are important, most do not. Some prefer severity of effects be described by percentage differences from, or multiples of, baseline or control, others prefer only word modifiers. Some expect a definitive decision for every potential effect, others accept uncertainty. This commentary addresses these differences and underscores the need for flexibility in a “consistent standard approach” because the conditions of every study are unique. This article constitutes an overview of material originally presented at Session 2 of the 2016 Society of Toxicologic Pathology Annual Symposium.

scholarly journals Oxidative Power: Tools for Assessing LPMO Activity on Cellulose

Biomolecules ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1098
Author(s):  
Federica Calderaro ◽  
Loes E. Bevers ◽  
Marco A. van den Berg
Keyword(s):  
Experimental Design ◽  
Mode Of Action ◽  
Data Interpretation ◽  
Electron Donors ◽  
Cellulolytic Enzymes ◽  
Inhibiting Factors ◽  
Lytic Polysaccharide Monooxygenases ◽  
Polysaccharide Monooxygenases ◽  
Power Tools ◽  
Reliable Methods

Lytic polysaccharide monooxygenases (LPMOs) have sparked a lot of research regarding their fascinating mode-of-action. Particularly, their boosting effect on top of the well-known cellulolytic enzymes in lignocellulosic hydrolysis makes them industrially relevant targets. As more characteristics of LPMO and its key role have been elucidated, the need for fast and reliable methods to assess its activity have become clear. Several aspects such as its co-substrates, electron donors, inhibiting factors, and the inhomogeneity of lignocellulose had to be considered during experimental design and data interpretation, as they can impact and often hamper outcomes. This review provides an overview of the currently available methods to measure LPMO activity, including their potential and limitations, and it is illustrated with practical examples.

scholarly journals Pliocene Model Intercomparison Project (PlioMIP): experimental design and boundary conditions (Experiment 2)

2011 ◽  
Vol 4 (3) ◽  
pp. 571-577 ◽  
Author(s):  
A. M. Haywood ◽  
H. J. Dowsett ◽  
M. M. Robinson ◽  
D. K. Stoll ◽  
A. M. Dolan ◽  
...  
Keyword(s):  
Experimental Design ◽  
Boundary Conditions ◽  
Initial Phase ◽  
Climate Models ◽  
Model Development ◽  
Warm Period ◽  
Model Intercomparison ◽  
Ocean Atmosphere ◽  
Intercomparison Project ◽  
Fully Coupled

Abstract. The Palaeoclimate Modelling Intercomparison Project has expanded to include a model intercomparison for the mid-Pliocene warm period (3.29 to 2.97 million yr ago). This project is referred to as PlioMIP (the Pliocene Model Intercomparison Project). Two experiments have been agreed upon and together compose the initial phase of PlioMIP. The first (Experiment 1) is being performed with atmosphere-only climate models. The second (Experiment 2) utilises fully coupled ocean-atmosphere climate models. Following on from the publication of the experimental design and boundary conditions for Experiment 1 in Geoscientific Model Development, this paper provides the necessary description of differences and/or additions to the experimental design for Experiment 2.

scholarly journals Measurement Error and Resolution in Quantitative Stable Isotope Probing: Implications for Experimental Design

mSystems ◽  
2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Ella T. Sieradzki ◽  
Benjamin J. Koch ◽  
Alex Greenlon ◽  
Rohan Sachdeva ◽  
Rex R. Malmstrom ◽  
...  
Keyword(s):  
Measurement Error ◽  
Experimental Design ◽  
Stable Isotope ◽  
Statistical Power ◽  
Quantitative Estimation ◽  
Cost Benefit ◽  
Data Interpretation ◽  
Stable Isotope Probing ◽  
Isotope Enrichment ◽  
Community Interactions

ABSTRACT Quantitative stable isotope probing (qSIP) estimates isotope tracer incorporation into DNA of individual microbes and can link microbial biodiversity and biogeochemistry in complex communities. As with any quantitative estimation technique, qSIP involves measurement error, and a fuller understanding of error, precision, and statistical power benefits qSIP experimental design and data interpretation. We used several qSIP data sets—from soil and seawater microbiomes—to evaluate how variance in isotope incorporation estimates depends on organism abundance and resolution of the density fractionation scheme. We assessed statistical power for replicated qSIP studies, plus sensitivity and specificity for unreplicated designs. As a taxon’s abundance increases, the variance of its weighted mean density declines. Nine fractions appear to be a reasonable trade-off between cost and precision for most qSIP applications. Increasing the number of density fractions beyond that reduces variance, although the magnitude of this benefit declines with additional fractions. Our analysis suggests that, if a taxon has an isotope enrichment of 10 atom% excess, there is a 60% chance that this will be detected as significantly different from zero (with alpha 0.1). With five replicates, isotope enrichment of 5 atom% could be detected with power (0.6) and alpha (0.1). Finally, we illustrate the importance of internal standards, which can help to calibrate per sample conversions of %GC to mean weighted density. These results should benefit researchers designing future SIP experiments and provide a useful reference for metagenomic SIP applications where both financial and computational limitations constrain experimental scope. IMPORTANCE One of the biggest challenges in microbial ecology is correlating the identity of microorganisms with the roles they fulfill in natural environmental systems. Studies of microbes in pure culture reveal much about their genomic content and potential functions but may not reflect an organism’s activity within its natural community. Culture-independent studies supply a community-wide view of composition and function in the context of community interactions but often fail to link the two. Quantitative stable isotope probing (qSIP) is a method that can link the identity and functional activity of specific microbes within a naturally occurring community. Here, we explore how the resolution of density gradient fractionation affects the error and precision of qSIP results, how they may be improved via additional experimental replication, and discuss cost-benefit balanced scenarios for SIP experimental design.

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