Pathological Science

I discuss examples of what Dr. Irving Langmuir, a Nobel prize winner in Chemistry, called "the science of things that aren't so." Some of his examples are reviewed and others from High Energy Physics are added. It is hoped that discussing these incidents will help us develop an understanding of some potential pitfalls.Comment: Presented at Theoretical Advanced Study Institute In Elementary Particle Physics (Tasi), University of Colorado, Boulder, Colorado June, 2000. To appear in the proceedings. (10/31/2000 - Fixed a reference.

VEGF(164)-mediated inflammation is required for pathological, but not physiological, ischemia-induced retinal neovascularization

Hypoxia-induced VEGF governs both physiological retinal vascular development and pathological retinal neovascularization. In the current paper, the mechanisms of physiological and pathological neovascularization are compared and contrasted. During pathological neovascularization, both the absolute and relative expression levels for VEGF(164) increased to a greater degree than during physiological neovascularization. Furthermore, extensive leukocyte adhesion was observed at the leading edge of pathological, but not physiological, neovascularization. When a VEGF(164)-specific neutralizing aptamer was administered, it potently suppressed the leukocyte adhesion and pathological neovascularization, whereas it had little or no effect on physiological neovascularization. In parallel experiments, genetically altered VEGF(164)-deficient (VEGF(120/188)) mice exhibited no difference in physiological neovascularization when compared with wild-type (VEGF(+/+)) controls. In contrast, administration of a VEGFk-1/Fc fusion protein, which blocks all VEGF isoforms, led to significant suppression of both pathological and physiological neovascularization. In addition, the targeted inactivation of monocyte lineage cells with clodronate-liposomes led to the suppression of pathological neovascularization. Conversely, the blockade of T lymphocyte-mediated immune responses with an anti-CD2 antibody exacerbated pathological neovascularization. These data highlight important molecular and cellular differences between physiological and pathological retinal neovascularization. During pathological neovascularization, VEGF(164) selectively induces inflammation and cellular immunity. These processes provide positive and negative angiogenic regulation, respectively. Together, new therapeutic approaches for selectively targeting pathological, but not physiological, retinal neovascularization are outlined

What Makes Delusions Pathological?

Bortolotti argues that we cannot distinguish delusions from other irrational beliefs in virtue of their epistemic features alone. Although her arguments are convincing, her analysis leaves an important question unanswered: What makes delusions pathological? In this paper I set out to answer this question by arguing that the pathological character of delusions arises from an executive dysfunction in a subject’s ability to detect relevance in the environment. I further suggest that this dysfunction derives from an underlying emotional imbalance—one that leads delusional subjects to regard some contextual elements as deeply puzzling or highly significant

Pathological element-based active device models and their application to symbolic analysis

This paper proposes new pathological element-based active device models which can be used in analysis tasks of linear(ized) analog circuits. Nullators and norators along with the voltage mirror-current mirror (VM-CM) pair (collectively known as pathological elements) are used to model the behavior of active devices in voltage-, current-, and mixed-mode, also considering parasitic elements. Since analog circuits are transformed to nullor-based equivalent circuits or VM-CM pairs or as a combination of both, standard nodal analysis can be used to formulate the admittance matrix. We present a formulation method in order to build the nodal admittance (NA) matrix of nullor-equivalent circuits, where the order of the matrix is given by the number of nodes minus the number of nullors. Since pathological elements are used to model the behavior of active devices, we introduce a more efficient formulation method in order to compute small-signal characteristics of pathological element-based equivalent circuits, where the order of the NA matrix is given by the number of nodes minus the number of pathological elements. Examples are discussed in order to illustrate the potential of the proposed pathological element-based active device models and the new formulation method in performing symbolic analysis of analog circuits. The improved formulation method is compared with traditional formulation methods, showing that the NA matrix is more compact and the generation of nonzero coefficients is reduced. As a consequence, the proposed formulation method is the most efficient one reported so far, since the CPU time and memory consumption is reduced when recursive determinant-expansion techniques are used to solve the NA matrix.Promep-Mexico UATLX-PTC-088Junta de Andalucía TIC-2532Ministerio de Educación y Ciencia TEC2007-67247, TEC2010-14825UC-MEXUS-CONACyT CN-09-31

Pathological phenomena in Denjoy-Carleman classes

Let $\mathcal C^M$ denote a Denjoy-Carleman class of $\mathcal C^\infty$ functions (for a given logarithmically-convex sequence $M = (M_n)$). We construct: (1) a function in $\mathcal C^M((-1,1))$ which is nowhere in any smaller class; (2) a function on $\mathbb R$ which is formally $\mathcal C^M$ at every point, but not in $\mathcal C^M(\mathbb R)$; (3) (under the assumption of quasianalyticity) a smooth function on $\mathbb R^p$ ($p \geq 2$) which is $\mathcal C^M$ on every $\mathcal C^M$ curve, but not in $\mathcal C^M(\mathbb R^p)$.Comment: 21 page

Developing the Quantitative Histopathology Image Ontology : A case study using the hot spot detection problem

Interoperability across data sets is a key challenge for quantitative histopathological imaging. There is a need for an ontology that can support effective merging of pathological image data with associated clinical and demographic data. To foster organized, cross-disciplinary, information-driven collaborations in the pathological imaging field, we propose to develop an ontology to represent imaging data and methods used in pathological imaging and analysis, and call it Quantitative Histopathological Imaging Ontology – QHIO. We apply QHIO to breast cancer hot-spot detection with the goal of enhancing reliability of detection by promoting the sharing of data between image analysts

Structural validation of oral mucosal tissue using optical coherence tomography

Background: Optical coherence tomography (OCT) is a non-invasive optical technology using near-infrared light to produce cross-sectional tissue images with lateral resolution. Objectives: The overall aims of this study was to generate a bank of normative and pathological OCT data of the oral tissues to allow identification of cellular structures of normal and pathological processes with the aim to create a diagnostic algorithm which can be used in the early detection of oral disorders. Material and methods: Seventy-three patients with 78 suspicious oral lesions were referred for further management to the UCLH Head and Neck Centre, London. The entire cohort had their lesions surgically biopsied (incisional or excisional). The immediate ex vivo phase involved scanning the specimens using optical coherence tomography. The specimens were then processed by a histopathologist. Five tissue structures were evaluated as part of this study, including: keratin cell layer, epithelial layer, basement membrane, lamina propria and other microanatomical structures. Two independent assessors (clinician and pathologist trained to use OCT) assessed the OCT images and were asked to comment on the cellular structures and changes involving the five tissue structures in non-blind fashion. Results: Correct identification of the keratin cell layer and its structural changes was achieved in 87% of the cohort; for the epithelial layer it reached 93.5%, and 94% for the basement membrane. Microanatomical structures identification was 64% for blood vessels, 58% for salivary gland ducts and 89% for rete pegs. The agreement was “good” between the clinician and the pathologist. OCT was able to differential normal from pathological tissue and pathological tissue of different entities in this immediate ex vivo study. Unfortunately, OCT provided inadequate cellular and subcellular information to enable the grading of oral premalignant disorders. Conclusion: This study enabled the creation of OCT bank of normal and pathological oral tissues. The pathological changes identified using OCT enabled differentiation between normal and pathological tissues, and identification of different tissue pathologies. Further studies are required to assess the accuracy of OCT in identification of various pathological processes involving the oral tissues

Pathological abelian groups: a friendly example

We show that the group of bounded sequences of elements of $\mathbb{Z}[\sqrt 2]$ is an example of an abelian group with several well known, and not so well known, pathological properties. It appears to be simpler than all previously known examples for some of these properties, and at least simpler to describe for others.Comment: 6 page