Misleading Data Research Articles

The use of immersive technologies to improve consumer testing: The role of ecological validity, context and engagement in evaluating coffee

Traditionally, sensory consumer testing is completed in isolated sensory booths where the influence of non-product (e.g., environmental) attributes is controlled. However, these highly controlled environments strip away meaningful contextual (visual, auditory and olfactory) information important in forming consumer perceptions, liking and behaviors. Moreover, boredom and lack of panelist engagement associated with typical testing paradigms can result in uninformative or misleading consumer data. We utilized an immersive environment depicting a virtual coffeehouse, replete with visual, auditory and olfactory cues found regularly in this setting, and compared liking scores for five coffees to those obtained from the same individuals in a traditional testing environment in which contextual information was absent. We found significant differences in preference order and liking for coffees evaluated by the same people in the two settings and showed hedonic data collected in the virtual coffeehouse to be more discriminating and a more reliable predictor of future coffee liking unlike data collected in traditional sensory booths. Additionally, we found consumers to be more engaged in the testing when evaluating coffees in the virtual coffeehouse, an outcome that likely also contributed to improved data quality. These results suggest that during product evaluations, extrinsic contextual information is processed simultaneously with the intrinsic product attributes to influence hedonic assessments and shape reward outcomes. Further, these results suggest that methodological changes to current testing strategies have the potential to improve the reliability of consumer data providing food and consumer product companies significant savings on product development costs and failed launches.

A Novel Method for Detection of Internet Worm Malcodes using Principal Component Analysis and Multiclass Support Vector Machine

Internet worms are malware programs that imitate themselves and spread around the network. Internet worm, a wide spreading malcode exploits vulnerability in the operating system, hard disk, software and web browsers. This paper analyzes and classifies the Internet worm, depending on the training signatures. This work presents the Internet worm detection mechanism, using Principal Component Analysis (PCA) and Support Vector Machine (SVM). A Selective sampling technique is applied to maximize the performance of the classifier and to reduce misleading data instances. The results obtained show improved memory utilization, detection time and detection accuracy for Internet worms. Keyword - Malcode, Selective sampling, Multiclass SVM and PCA

Pulmonary venous hypertension vs. pulmonary arterial hypertension: Usefulness of echocardiography in the case of misleading heart catheterization data

Pulmonary venous hypertension vs. pulmonary arterial hypertension: Usefulness of echocardiography in the case of misleading heart catheterization data

Scope and limitations of the TEMPO/EPR method for singlet oxygen detection: the misleading role of electron transfer

For many biological and biomedical studies, it is essential to detect the production of 1O2 and quantify its production yield. Among the available methods, detection of the characteristic 1270-nm phosphorescence of singlet oxygen by time-resolved near-infrared (TRNIR) emission constitutes the most direct and unambiguous approach. An alternative indirect method is electron paramagnetic resonance (EPR) in combination with a singlet oxygen probe. This is based on the detection of the TEMPO free radical formed after oxidation of TEMP (2,2,6,6-tetramethylpiperidine) by singlet oxygen. Although the TEMPO/EPR method has been widely employed, it can produce misleading data. This is demonstrated by the present study, in which the quantum yields of singlet oxygen formation obtained by TRNIR emission and by the TEMPO/EPR method are compared for a set of well-known photosensitizers. The results reveal that the TEMPO/EPR method leads to significant overestimation of singlet oxygen yield when the singlet or triplet excited state of the photosensitizer is efficiently quenched by TEMP, acting as electron donor. In such case, generation of the TEMP+ radical cation, followed by deprotonation and reaction with molecular oxygen, gives rise to an EPR-detectable TEMPO signal that is not associated with singlet oxygen production. This knowledge is essential for an appropriate and error-free application of the TEMPO/EPR method in chemical, biological, and medical studies.

Cell-Based Sensing: From 2D to 3D Cell Culture

Cell-based biosensors use living cells or tissues as sensing element to monitor physiological and functional changes induced by external stimuli. They have become an important pillar of drug discovery process, to provide a simple, fast and cost-effective tool to avoid large-scale and cost-intensive animal testing. The sensing element---cultured cells, is the most critical part of a cell-based biosensor. To date, almost all cell-based biosensors use traditional 2 dimensional (2D) monolayer cells cultured on flat and rigid substrate as the sensing element. Although the time-honored 2D cell culture has proven to be a valuable method for cell-based studies, its limitations have been increasingly recognized. In in vivo environment, almost all cells are surrounded by other cells and extracellular matrix (ECM) in a 3D fashion. As a result, 2D cell culture tests sometimes give unsatisfactorily misleading and non-predictive data for in vivo responses. On the other hand, 3D cell culture provides a more physiologically relevant environment for cells and allows the study of cellular responses in a setting that resembles in vivo environments. The 3D structure not only influences the spatial organization of the cell surface receptors engaged in interactions with surrounding cells, but also induce the physical constraint to cells. These spatial and physical aspects in 3D affect the signal transduction from the outside to the inside of cells, and ultimately influence on gene expression and cellular behaviors. Compared to 2D cell culture, 3D culture replicates more accurately the actual microenvironment where cells reside in tissue and therefore the behavior of cells in 3D culture reflects closely the in vivo responses.This study focused on the adoption of 3D cell cultures to cell-based biosensors, aiming to provide more in vivo-like experimental results for drug discovery. In this study, we established the conditions for growing cancer cells into 3D spheroids on Matrigel for two different cancer cell lines: oral cancer cell line CAL 27 and prostate cancer cell line DU 145. We systematically investigated the cellular responses to different anticancer drugs in 3D culture in comparison to those of 2D culture, within the same cell line and between different cell lines. We also examined the difference in expressions of drug-action related factors in 3D and 2D cultures. The results showed that the cell proliferation rate in 3D culture on Matrigel in comparison to 2D culture was cell line dependent, as we observed the proliferation of CAL27 cells was enhanced in 3D whereas the proliferation DU 145 cells we reduced in 3D. Sensitivity of cellular responses to drugs in 3D relative to 2D was drug-action and cell line dependent. For DU 145 cells, 3D cell culture model was more resistant to Docetaxel, but less resistant to Rapamycin as compared to 2D cell culture model. And surprisingly, for CAL 27 cells, 3D cell culture model was less resistant to both bleomycin and erlotinib as compared to 2D cell culture. Further examination of drug-action related factors indicated that the cellular responses of 3D culture were correlated with the expression of drug action related biomarkers as compared to 2D cell culture. Acknowledgement: The research is supported by NSF (CBET #1159871)

Inconsistencies and misleading information in officially approved prescribing information from three major drug markets.

The summary of product characteristics (SPC) should provide information for the safe prescription and use of a drug. We evaluated the consistency of critical interaction warnings, the quality of presentation of undesirable effects as well as concordance of critical information of representative drugs marketed in the United States, the UK, and Germany. Reciprocal warnings regarding drug-drug interactions that constitute contraindications were frequently missing in the SPCs of the drugs concerned (all countries >40%). Most SPCs did not explicitly exclude adverse reactions considered not reasonably attributable to the use of the drug. Comparing SPCs of different generic brands of the same drug, only 60, 10, and 20% of the US, UK, and German SPCs, respectively, provided identical contraindications. Current SPCs contain inconsistencies and misleading data that are not compatible with the purpose of SPCs, which is to provide a basis for the safe prescription and use of drugs.

Flour concentration prediction using GAPLS and GAWLS focused on data sampling issues and applicability domain

In statistical analysis, several issues arise from inadequate data splitting, such as data misunderstanding and predictive quality misconceptions. This work aims to discuss the implications of poor training and test data splitting, focusing on applicability domain (AD) key aspects. This matter is highly overlooked, despite its basic and, to a certain extent, straightforward nature. While it is true that training and test data when poorly chosen result in a poor model, the main idea of this work is to discuss how such splitting should be done and how counter intuitive and misleading data splitting is being approached by several researchers. Relying on Fluorescence and Near infrared (NIR) spectroscopy data sets, prediction of protein concentration for a particular group of flour samples is presented via six different data splitting scenarios. Multiple scenarios allow AD and model predictive power to be evaluated in different ways from a singular data set. The regression models constructed were obtained using three somewhat related regression methods: partial least squares (PLS), generic algorithm-based partial least squares (GAPLS) and generic algorithm-based wavelength selection (GAWLS). The merits and demerits of GAWLS and GAPLS contribute for the assessment of AD in the same way that using two distinct data sets prevent the work to be biased by a single case study. NIR has overall better results than Fluorescence, since it has more information available for modeling and GA methods present better model performance than PLS. In order to evaluate the different data splitting used, T2 and Q indexes are used along prediction errors to assess model performance and determine data reliability. T2 and Q values can determine the similarity between training and test data, indicating how predictive a model will be. Standard deviation helps to identify how reliable a sample is for modeling within a given data set. When it comes to the model assessment and anomaly detection, standard deviation of prediction errors had the most consistent results, diagnosing which model had better prediction capabilities. In the end, for a given data set, arbitrary data splitting can be dangerous, since it can trigger generation of models that do not represent the entire nature of the data set represented.

The undeserving rich: American beliefs about inequality, opportunity, and redistribution

It is widely assumed that Americans care little about income inequality, believe opportunities abound, admire the rich, and dislike redistributive policies. In her talk, Leslie McCall shows how such assumptions are based on misleading survey data and economic conditions rooted in the past. Using data from the General Social Survey, a systematic analysis of media coverage from 1980 to 2010, and other sources, she provides evidence that Americans have long desired less inequality, becoming most concerned about it in times of inequitable growth, when they view the rich as prospering while opportunities for good jobs, fair pay, and high quality education are restricted for everyone else. This suggests that Americans do not pit equality of opportunity against equality of outcomes, favoring only the equality of opportunity, as is widely assumed, but see the two as interconnected. As a result, they favor policies to expand opportunity and redistribute earnings in the workplace, reducing inequality in the market rather than redistributing income after the fact with tax and spending policies. McCall helps to resolve the paradox of how Americans can express little enthusiasm for welfare state policies and yet still yearn for a more equitable society. She also forwards a new model of preferences about income inequality rooted in labor market opportunities rather than welfare state policies. Leslie McCall is Professor of Sociology and Political Science, as well as Faculty Fellow at the Institute for Policy Research, at Northwestern University. She is the author of Complex Inequality: Gender, Class, and Race in the New Economy (2001). The lecture is organized by David Brady, Head of the newly established Inequality and Social Policy research unit at the WZB.

The “Squeezing Maneuver” in Microsurgical Clipping of Intracranial Aneurysms Assisted by Indocyanine Green Videoangiography

Indocyanine green videoangiography (ICGV) is becoming routine in intracranial aneurysm surgery to assess intraoperatively both sac obliteration and vessel patency after clipping. However, ICGV-derived data have been reported to be misleading at times. We recently noted that a simple intraoperative maneuver, the "squeezing maneuver," allows the detection of deceptive ICGV data on aneurysm exclusion and allows potential clip repositioning. The squeezing maneuver is based on a gentle pinch of the dome of a clipped aneurysm when ICGV documents its apparent exclusion. To present the surgical findings and the clinical outcome of this squeezing maneuver. Data from 23 consecutive patients affected by intracranial aneurysms who underwent the squeezing maneuver were analyzed retrospectively. The clip was repositioned in all cases when the dyeing of the sac was visualized after the maneuver. In 22% of patients, after an initial ICGV showing the aneurysm exclusion after clipping, the squeezing maneuver caused the prompt dyeing of the sac; in all cases, the clip was consequently repositioned. A calcification/atheroma of the wall/neck was predictive of a positive maneuver (P = .001). The aneurysm exclusion rate at postoperative radiological findings was 100%. With the limits of our small series, the squeezing maneuver appears helpful in the intraoperative detection of misleading ICGV data, mostly when dealing with aneurysms with atheromatic and calcified walls.

Blinded interpretation of study results can feasibly and effectively diminish interpretation bias

ObjectiveControversial and misleading interpretation of data from randomized trials is common. How to avoid misleading interpretation has received little attention. Herein, we describe two applications of an approach that involves blinded interpretation of the results by study investigators. Study Design and SettingsThe approach involves developing two interpretations of the results on the basis of a blinded review of the primary outcome data (experimental treatment A compared with control treatment B). One interpretation assumes that A is the experimental intervention and another assumes that A is the control. After agreeing that there will be no further changes, the investigators record their decisions and sign the resulting document. The randomization code is then broken, the correct interpretation chosen, and the manuscript finalized. Review of the document by an external authority before finalization can provide another safeguard against interpretation bias. ResultsWe found the blinded preparation of a summary of data interpretation described in this article practical, efficient, and useful. ConclusionsBlinded data interpretation may decrease the frequency of misleading data interpretation. Widespread adoption of blinded data interpretation would be greatly facilitated were it added to the minimum set of recommendations outlining proper conduct of randomized controlled trials (eg, the Consolidated Standards of Reporting Trials statement).

Chapter Seven - Identifying and Reducing Potentially Wrong Immunoassay Results Even When Plausible and “Not-Unreasonable”

The primary role of the clinical laboratory is to report accurate results for diagnosis of disease and management of illnesses. This goal has, to a large extent been achieved for routine biochemical tests, but not for immunoassays which remained susceptible to interference from endogenous immunoglobulin antibodies, causing false, and clinically misleading results. Clinicians regard all abnormal results including false ones as "pathological" necessitating further investigations, or concluding iniquitous diagnosis. Even more seriously, "false-negative" results may wrongly exclude pathology, thus denying patients' necessary treatment. Analytical error rate in immunoassays is relatively high, ranging from 0.4% to 4.0%. Because analytical interference from endogenous antibodies is confined to individuals' sera, it can be inconspicuous, pernicious, sporadic, and insidious because it cannot be detected by internal or external quality assessment procedures. An approach based on Bayesian reasoning can enhance the robustness of clinical validation in highlighting potentially erroneous immunoassay results. When this rational clinical/statistical approach is followed by analytical affirmative follow-up tests, it can help identifying inaccurate and clinically misleading immunoassay data even when they appear plausible and "not-unreasonable." This chapter is largely based on peer reviewed articles associated with and related to this approach. The first section underlines (without mathematical equations) the dominance and misuse of conventional statistics and the underuse of Bayesian paradigm and shows that laboratorians are intuitively (albeit unwittingly) practicing Bayesians. Secondly, because interference from endogenous antibodies is method's dependent (with numerous formats and different reagents), it is almost impossible to accurately assess its incidence in all differently formulated immunoassays and for each analytes/biomarkers. However, reiterating the basic concepts underpinning interference from endogenous antibodies can highlight why interference will remain analytically pernicious, sporadic, and an inveterate problem. The following section discuses various stratagems to reduce this source of inaccuracy in current immunoassay results including the role of Bayesian reasoning. Finally, the role of three commonly used follow-up affirmative tests and their interpretation in confirming analytical interference is discussed.

Exploiting Image Processing and Analysis Versus Other Techniques for Composite Fines Particle Size and Shape Distribution Analysis

Reliable particles property distribution data is important in design of materials processing operation. With composite fines samples, such as the comminution fines in printed circuit board physical processing, having particles diverse in material type and morphology, size distribution data from some conventional techniques will not fully describe the sample. A review of basic analytical principles shows sieving, cyclosizing, and laser diffraction techniques will, in principle, return erroneous results. Rather, it was shown from test analysis carried out that detailed quantitative description of the particle size and shape distribution for such composite fines sample can be obtained by employing image processing and analysis of a good micrograph of the sample. Image processing with image analysis can be used to decompose the composite micrograph and separately characterize the constituent particle types. This is a good reference for composite fines size and shape distribution analysis, to narrow down applicable analytical techniques and avoid use of misleading data.

Misleading Generalized Itemset discovery

Frequent generalized itemset mining is a data mining technique utilized to discover a high-level view of interesting knowledge hidden in the analyzed data. By exploiting a taxonomy, patterns are usually extracted at any level of abstraction. However, some misleading high-level patterns could be included in the mined set.This paper proposes a novel generalized itemset type, namely the Misleading Generalized Itemset (MGI). Each MGI, denoted as X▷E, represents a frequent generalized itemset X and its set E of low-level frequent descendants for which the correlation type is in contrast to the one of X. To allow experts to analyze the misleading high-level data correlations separately and exploit such knowledge by making different decisions, MGIs are extracted only if the low-level descendant itemsets that represent contrasting correlations cover almost the same portion of data as the high-level (misleading) ancestor. An algorithm to mine MGIs at the top of traditional generalized itemsets is also proposed.The experiments performed on both real and synthetic datasets demonstrate the effectiveness and efficiency of the proposed approach.

Predictions of settlement in peat soils

Predictions from laboratory tests of the compression behaviour of peat from 14 sites are compared with full-scale field loading at five sites. Data presented confirm the heterogeneous nature of the deposits. However, for typical engineering works, calculations based on laboratory test data are likely to give reasonable predictions of the magnitude of immediate and primary compression. Standard (20 mm thickness) samples may give misleading data on time for primary consolidation. Thicker samples (e.g. 50 mm) should be used. Sampling by conventional samplers, as used for mineral soils, can cause densification of the peat, resulting in underestimation of actual settlement. Block samples or sample tubes with serrated cutting edges are recommended for peat soils. It was found that the data presented follow the C α / C c law of compressibility. There is also is some evidence to suggest that the H 2 scaling law may be applicable. Good correlations were found between vertical yield stress ( p vy ′) and compression index ( C c ) and index parameters such as water content ( w i ). Conventional staged construction with surcharge loading may be successfully applied to peat soils as long as adequate drainage exists to permit consolidation over reasonable time intervals.

ISUOG Practice Guidelines: use of Doppler ultrasonography in obstetrics

<scp>ISUOG</scp> Practice Guidelines: use of Doppler ultrasonography in obstetrics

Prognostic scoring indicator in evaluation of clinical outcome in intestinal perforations.

Acute generalised peritonitis coming forth due to underlying intestinal perforation is a critical & life-threatening medical condition. It is a common surgical emergency most of the times across the world. Misleading data on crude morbidity and mortality due to the condition usually contaminates substantially the very purpose of medical audit. Thus, early prognostic evaluation is not only desirable but mandate to much extent. High-risk patients require timely & aggressive treatment especially in severe peritonitis & to select them reasonably well, evaluation through prognostic scoring is an approach of choice. Well sought after & reasonably reliable APACHE II scoring system is used for the purpose & scores are correlated well to accentuate & measure the various factors needed for better management of condition. The study was conducted over the period of 18 months (Jan 2010 to June 2011) on 50 patients with confirmed diagnosis of intestinal perforation. APACHE II score was calculated and correlated with their symptoms & clinical outcomes regarding morbidity and mortality. APACHE II score correlated well with the outcome of the study, showing score affects of two major aspects in the treatment outcome & management.1.) APACHE II score of less than 10 included 30 low risk group patients discharged in a satisfactory gratifying manner. Three out of four in high risk group with APACHE II score >20, shown adverse outcomes. 2.)Mean ICU stay of 9.75 days was found in patients with APACHE II score 20 or more compared to those with mean ICU stay of 0.13 days in patients with APACHE II score 10 or less. Acute generalized peritonitis being life-threatening medical emergency requires careful consideration in its management that needs to be economically viable, acceptably feasible and outcome oriented with better allocation & utilization of ICU resources that needs meticulous case analysis & prioritization. This present study helps the clinicians in three major ways: a) To take better decisions on case to case basis; b) To design strategies in order to prevent adverse outcomes; c) Last but not least, to make better use of ICU resources.

Keratinocyte-based cell assays: their potential pitfalls

As an in vitro model system, patient-derived epidermolysis bullosa simplex keratinocytes have had an immense impact on what we know today about keratin filament function and their role in disease development. In the absence of gene therapy, screening compound libraries for new or better drugs is another approach to improve existing treatments for genodermatoses. However in this study, we report of the potential pitfalls when using this type of cell lines as a "reporter" system. When cell lines with different genetic backgrounds are being used in cell-based assays, the greatest obstacle is to determine the most appropriate culture conditions (i.e., the composition of medium, number of cells plated and number of days in culture). We demonstrate how culture conditions can greatly interfere with the cellular response in cell-based assays (cell proliferation, metabolic activity and migration), potentially also giving rise to misleading data.

Reliability of Pedometers to Measure Step Counts in Patients With Chronic Respiratory Disease

There are a variety of devices currently available to measure physical activity. Activity monitors are technologically advanced and provide complex data, leading to higher costs. Pedometers are simple, inexpensive devices that provide easy-to-view data. The aim of this study was to determine the reliability of pedometer step counting during slow walking speeds, typical of patients with chronic respiratory disease. The reproducibility of 8 pedometers was initially determined at slow walking speeds in a healthy individual. Thereafter, pedometer step counting was compared with an activity monitor and visual step counts in 9 healthy subjects and 48 patients with chronic respiratory disease. Pedometers were reproducible on the same wearer, on consecutive occasions, although they were not interchangeable. During healthy subject walking, there were no significant differences between the pedometer and activity monitor at all speeds. However, both significantly undercounted steps at slower walking speeds (P < .01). At slow and medium walking speeds with patients with chronic respiratory disease, both the pedometer and activity monitor significantly undercounted steps (P < .001 for both pedometer and activity monitor at slow and P < .003 for pedometer and P < .004 for activity monitor at medium speeds) compared with visual counts. Pedometers are an inexpensive and simple alternative to activity monitors and appear to be reliable during faster walking in both healthy subjects and patients with chronic respiratory disease. However, caution should be applied during slow walking speeds because of undercounting steps, causing misleading data that could become demotivating when used as a training adjunct.

Black Holes, Keyholes And Brown Worms: Challenges In Sense Making

We address the problems faced by analysts who have to sift through large amounts of data quickly and accurately in order to make sense of the information contained within the data or the circumstance represented in the data. We discuss the approach we have taken to visual analytics from the perspective of the Data-Frame Theory of Sense-making and its extension to Causal Reasoning, and how the cognitive strategies that are invoked in these processes need to be supported. We identify 20 problems that designers of visual analytics-type systems need to address in order to support sense-making. In particular, we discuss design issues associated with three exemplar problems: (i) Black holes - the problem of representing missing data; (ii) Keyholes - the problem of being able to access and view only a small part of a large dataset or only part of a problem; and (iii) Brown worms - the problem of dealing with and representing misleading or deceptive data.

São João del Rei is the type locality of Scytalopus speluncae (Aves: Passeriformes: Rhinocryptidae)—a response to Maurício et al. (2010)

The type locality and the identity of the holotype of the southeast Brazilian endemic Scytalopus speluncae (Ménétriés,1835) have attracted considerable recent scrutiny and controversy, based in large part on doubts expressed in theornithological literature concerning some of the same author’s other Brazilian type localities. Most recently, Maurício etal. (2010) recommended substituting a new type locality, the Serra dos Órgãos, for S. speluncae, based almost entirely onan analysis of photographs of the holotype. Separately, some of the same authors (Whitney et al. 2010) described a newspecies, Scytalopus petrophilus, including, as a paratype, a specimen from Ménétriés’ original type locality. Our ownknowledge of S. speluncae is based on a thorough examination of the holotype and a comprehensive review of all availablehistorical data concerning its collection. Because the holotype itself is partially damaged and the identification of somesoutheast Brazilian Scytalopus is unquestionably difficult using plumage alone (due to intraspecific variation), and furtherbecause all authors agree that only one species of Scytalopus occurs in the environs of São João del Rei, correctlyidentifying the type locality is of overriding importance to ensure the correct nomenclature of the entire species-group ofwhich S. speluncae is the senior synonym. All contemporaneous data (three expedition diaries, the original specimen label,and the original description) clearly demonstrate that Ménétriés collected S. speluncae close to a well-known limestonecave in the region of São João del Rei, in the state of Minas Gerais, on 7 June 1824. Even the bird’s name, speluncae(pertaining to “the cave”) witnesses the validity of these facts. The available historical evidence was dismissed byMaurício et al. (2010) in clear contravention of the recommendations of Article 76A.1 of the ICZN (1999), which governssuch cases. It is also relevant that all available first-hand information concerning the holotype’s morphology, as well asthe evidence from its topotypes, supports the proposition that S. speluncae was collected where Ménétriés claimed. Wefurther demonstrate that: (1) S. speluncae is the name applicable to the paler gray species with buff-fringed blackishfeathers on the flanks, thighs, vent and upper tail coverts; (2) S. petrophilus must be a junior synonym of S. speluncae; (3)the only historical argument presented by Maurício et al. (2010) contra the type locality is based on an unrepresentativetranslation; and (4) their morphological analysis uses incomplete, contradictory or misleading data, and focuses onsearching for specimens similar to the paler gray S. speluncae within the variation of the dark gray S. notorius, in order tojustify emending the type locality. Crucially, none of these specimens of S. notorius is apparently similar to the holotype and topotypes of S. speluncae in respect to all of the latter’s distinguishing characters.