Do we truly see what we think we see? The role of cognitive bias in pathological interpretation.

In the histomorphological grading of prostate carcinoma, pathologists have regularly assigned comparable scores for the architectural Gleason and the now-obsolete nuclear World Health Organization (WHO) grading systems. Although both systems demonstrate good correspondence between grade and survival, they are based on fundamentally different biological criteria. We tested the hypothesis that this apparent concurrence between the two grading systems originates from an interpretation bias in the minds of diagnostic pathologists, rather than reflecting a biological reality. Three pathologists graded 178 prostatectomy specimens, assigning Gleason and WHO scores on glass slides and on digital images of nuclei isolated out of their architectural context. The results were analysed with respect to interdependencies among the grading systems, to tumour recurrence (PSA relapse > 0.1 ng/ml at 48 months) and robust nuclear morphometry, as assessed by computer-assisted image analysis. WHO and Gleason grades were strongly correlated (r = 0.82) and demonstrated identical prognostic power. However, WHO grades correlated poorly with nuclear morphology (r = 0.19). Grading of nuclei isolated out of their architectural context significantly improved accuracy for nuclear morphology (r = 0.55), but the prognostic power was virtually lost. In conclusion, the architectural organization of a tumour, which the pathologist cannot avoid noticing during initial slide viewing at low magnification, unwittingly influences the subsequent nuclear grade assignment. In our study, the prognostic power of the WHO grading system was dependent on visual assessment of tumour growth pattern. We demonstrate for the first time the influence a cognitive bias can have in the generation of an error in diagnostic pathology and highlight a considerable problem in histopathological tumour grading.

Evaluation of two HbA1c point-of-care analyzers.

BACKGROUND Measurement of HbA1c is the most important parameter to assess glycemic control in diabetic patients. Different point-of-care devices for HbA1c are available. The aim of this study was to evaluate two point-of-care testing (POCT) analyzers (DCA Vantage from Siemens and Afinion from Axis-Shield). We studied the bias and precision as well as interference from carbamylated hemoglobin. METHODS Bias of the POCT analyzers was obtained by measuring 53 blood samples from diabetic patients with a wide range of HbA1c, 4%-14% (20-130 mmol/mol), and comparing the results with those obtained by the laboratory method: HPLC HA 8160 Menarini. Precision was performed by 20 successive determinations of two samples with low 4.2% (22 mmol/mol) and high 9.5% (80 mmol/mol) HbA1c values. The possible interference from carbamylated hemoglobin was studied using 25 samples from patients with chronic renal failure. RESULTS The means of the differences between measurements performed by each POCT analyzer and the laboratory method (95% confidence interval) were: 0.28% (p<0.005) (0.10-0.44) for DCA and 0.27% (p<0.001) (0.19-0.35) for Afinion. Correlation coefficients were: r=0.973 for DCA, and r=0.991 for Afinion. The mean bias observed by using samples from chronic renal failure patients were 0.2 (range -0.4, 0.4) for DCA and 0.2 (-0.2, 0.5) for Afinion. Imprecision results were: CV=3.1% (high HbA1c) and 2.97% (low HbA1c) for DCA, CV=1.95% (high HbA1c) and 2.66% (low HbA1c) for Afinion. CONCLUSIONS Both POCT analyzers for HbA1c show good correlation with the laboratory method and acceptable precision.

Overcoming the heterologous bias: an in vivo functional analysis of multidrug efflux transporter, CgCdr1p in matched pair clinical isolates of Candida glabrata.

We have taken advantage of the natural milieu of matched pair of azole sensitive (AS) and azole resistant (AR) clinical isolates of Candida glabrata for expressing its major ABC multidrug transporter, CgCdr1p for structure and functional analysis. This was accomplished by tagging a green fluorescent protein (GFP) downstream of ORF of CgCDR1 and integrating the resultant fusion protein at its native chromosomal locus in AS and AR backgrounds. The characterization confirmed that in comparison to AS isolate, CgCdr1p-GFP was over-expressed in AR isolates due to its hyperactive native promoter and the GFP tag did not affect its functionality in either construct. We observed that in addition to Rhodamine 6 G (R6G) and Fluconazole (FLC), a recently identified fluorescent substrate of multidrug transporters Nile Red (NR) could also be expelled by CgCdr1p. Competition assays with these substrates revealed the presence of overlapping multiple drug binding sites in CgCdr1p. Point mutations employing site directed mutagenesis confirmed that the role played by unique amino acid residues critical to ATP catalysis and localization of ABC drug transporter proteins are well conserved in C. glabrata as in other yeasts. This study demonstrates a first in vivo novel system where over-expression of GFP tagged MDR transporter protein can be driven by its own hyperactive promoter of AR isolates. Taken together, this in vivo system can be exploited for the structure and functional analysis of CgCdr1p and similar proteins wherein the artefactual concerns encountered in using heterologous systems are totally excluded.

What Was I Thinking? Eye-Tracking Experiments Underscore the Bias that Architecture Exerts on Nuclear Grading in Prostate Cancer.

We previously reported that nuclear grade assignment of prostate carcinomas is subject to a cognitive bias induced by the tumor architecture. Here, we asked whether this bias is mediated by the non-conscious selection of nuclei that "match the expectation" induced by the inadvertent glance at the tumor architecture. 20 pathologists were asked to grade nuclei in high power fields of 20 prostate carcinomas displayed on a computer screen. Unknown to the pathologists, each carcinoma was shown twice, once before a background of a low grade, tubule-rich carcinoma and once before the background of a high grade, solid carcinoma. Eye tracking allowed to identify which nuclei the pathologists fixated during the 8 second projection period. For all 20 pathologists, nuclear grade assignment was significantly biased by tumor architecture. Pathologists tended to fixate on bigger, darker, and more irregular nuclei when those were projected before kigh grade, solid carcinomas than before low grade, tubule-rich carcinomas (and vice versa). However, the morphometric differences of the selected nuclei accounted for only 11% of the architecture-induced bias, suggesting that it can only to a small part be explained by the unconscious fixation on nuclei that "match the expectation". In conclusion, selection of « matching nuclei » represents an unconscious effort to vindicate the gravitation of nuclear grades towards the tumor architecture.

Sex-biased dispersal in a migratory bat: a characterization using sex-specific demographic parameters.

We studied the noctule bat (Nyctalus noctula), in which the mitochondrial F(ST) is about 10 times that revealed by nuclear markers, to address two questions. We first verified whether random dispersal of one sex is compatible with highly contrasted mitochondrial and nuclear population structures. Using computer simulations, we then assessed the power of multilocus population differentiation tests when the expected population structure departs only slightly from panmixia. Using an island model with sex-specific demographic parameters, we found that random male dispersal is consistent with the population structure observed in the noctule. However, other parameter combinations are also compatible with the data. We computed the minimum sex bias in dispersal (at least 69% of the dispersing individuals are males), a result that would not be available if we had used more classical population genetic models. The power of multilocus population differentiation tests was unexpectedly high, the tests being significant in almost 100% of the replicates, although the observed population structure infered from nuclear markers was extremely low (F(ST) = 0.6%).

Fault diagnosis by refining the parameter uncertainty space of nonlinear dynamic systems

This paper deals with fault detection and isolation problems for nonlinear dynamic systems. Both problems are stated as constraint satisfaction problems (CSP) and solved using consistency techniques. The main contribution is the isolation method based on consistency techniques and uncertainty space refining of interval parameters. The major advantage of this method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements, and model errors. Interval calculations bring independence from the assumption of monotony considered by several approaches for fault isolation which are based on observers. An application to a well known alcoholic fermentation process model is presented

A hierarchical approach to model parameter optimization for developmental systems.

In the context of Systems Biology, computer simulations of gene regulatory networks provide a powerful tool to validate hypotheses and to explore possible system behaviors. Nevertheless, modeling a system poses some challenges of its own: especially the step of model calibration is often difficult due to insufficient data. For example when considering developmental systems, mostly qualitative data describing the developmental trajectory is available while common calibration techniques rely on high-resolution quantitative data. Focusing on the calibration of differential equation models for developmental systems, this study investigates different approaches to utilize the available data to overcome these difficulties. More specifically, the fact that developmental processes are hierarchically organized is exploited to increase convergence rates of the calibration process as well as to save computation time. Using a gene regulatory network model for stem cell homeostasis in Arabidopsis thaliana the performance of the different investigated approaches is evaluated, documenting considerable gains provided by the proposed hierarchical approach.

Gestió incidental de l'enllumenat públic

Projecte per portar un control d'incidències enregistrades en l'enllumenat públic.

Testing for potential contextual bias effects during the verification stage of the ACE-V methodology when conducting fingerprint comparisons

This study was conducted to assess if fingerprint specialists could be influenced by extraneous contextual information during a verification process. Participants were separated into three groups: a control group (no contextual information was given), a low bias group (minimal contextual information was given in the form of a report prompting conclusions), and a high bias group (an internationally recognized fingerprint expert provided conclusions and case information to deceive this group into believing that it was his case and conclusions). A similar experiment was later conducted with laypersons. The results showed that fingerprint experts were influenced by contextual information during fingerprint comparisons, but not towards making errors. Instead, fingerprint experts under the biasing conditions provided significantly fewer definitive and erroneous conclusions than the control group. In contrast, the novice participants were more influenced by the bias conditions and did tend to make incorrect judgments, especially when prompted towards an incorrect response by the bias prompt.

Probabilistic evidential assessment of gunshot residue particle evidence (Part II) : Bayesian parameter estimation for experimental count data.

Part I of this series of articles focused on the construction of graphical probabilistic inference procedures, at various levels of detail, for assessing the evidential value of gunshot residue (GSR) particle evidence. The proposed models - in the form of Bayesian networks - address the issues of background presence of GSR particles, analytical performance (i.e., the efficiency of evidence searching and analysis procedures) and contamination. The use and practical implementation of Bayesian networks for case pre-assessment is also discussed. This paper, Part II, concentrates on Bayesian parameter estimation. This topic complements Part I in that it offers means for producing estimates useable for the numerical specification of the proposed probabilistic graphical models. Bayesian estimation procedures are given a primary focus of attention because they allow the scientist to combine (his/her) prior knowledge about the problem of interest with newly acquired experimental data. The present paper also considers further topics such as the sensitivity of the likelihood ratio due to uncertainty in parameters and the study of likelihood ratio values obtained for members of particular populations (e.g., individuals with or without exposure to GSR).

S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

Multiuser detection in a dynamic environment — Part II: Joint user identification and parameter estimation

The problem of jointly estimating the number, the identities, and the data of active users in a time-varying multiuser environment was examined in a companion paper (IEEE Trans. Information Theory, vol. 53, no. 9, September 2007), at whose core was the use of the theory of finite random sets on countable spaces. Here we extend that theory to encompass the more general problem of estimating unknown continuous parameters of the active-user signals. This problem is solved here by applying the theory of random finite sets constructed on hybrid spaces. We doso deriving Bayesian recursions that describe the evolution withtime of a posteriori densities of the unknown parameters and data.Unlike in the above cited paper, wherein one could evaluate theexact multiuser set posterior density, here the continuous-parameter Bayesian recursions do not admit closed-form expressions. To circumvent this difficulty, we develop numerical approximationsfor the receivers that are based on Sequential Monte Carlo (SMC)methods (“particle filtering”). Simulation results, referring to acode-divisin multiple-access (CDMA) system, are presented toillustrate the theory.

Prise en charge d'une lésion hépatique découverte fortuitement [The management of an incidental liver lesion]

The widespread use of abdominal imaging technologies has led to an increase in the incidental finding of liver tumors. Most of these lesions are asymptomatic and will not require any treatment. With the use of contrast-enhanced radiological studies, most of the tumors can be reliably diagnosed by non-invasive means. In case of diagnostic uncertainty, patients should not undergo percutaneous biopsy but rather complete resection of the lesion for an unequivocal diagnosis. Such pathologies must be taken charge of in centers with expertise by interdisciplinary teams.