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Harrow on the Hill, United Kingdom

Hodkinson H.M.,Northwick Park Hospital
Age and Ageing | Year: 2012

A mental test tcore consisting of 26 questions testing memory and orientation was used in a large inpatient study of mental impairment of the elderly. Analysis shows that the questions varied considerably in their discriminatory value. Deletion of the less effective questions results in an abbreviated test of ten questions with similar discriminatory powers to the full test. Shorter tests of this kind are recommended for further practical evaluation in geriatric departments. Source

Taylor-Robinson D.,Imperial College London | Keat A.,Northwick Park Hospital
International Journal of STD and AIDS | Year: 2015

There are problems in attributing causality in inflammatory arthritis. So far as C. trachomatis and sexually acquired reactive arthritis are concerned, there is much in favour of a causal relationship, although there are important caveats which need to be explored before it is possible to say unreservedly that C. trachomatis plays a causative role in reactive arthritis. For example, micro-organisms have never been cultured from synovial effusions in early disease, and only once has substantial benefit of antimicrobial treatment been reported. The claim that ocular strains of C. trachomatis are of over-riding importance in pathogenesis needs confirmation before it can be accepted. No conclusion can be made about the possibility of other small intracellular bacteria in joints having a role in causing disease. However, if it can be shown that eradication of the micro-organism, which may be difficult to prove, coincides with clinical recovery, it would go some way to recognising causality. In spite of the recognised difficulties, antibiotic studies have an important role in identifying aetiology. They need to focus on very early disease and on eradication of intra-articular bacteria. Treatment of established disease is likely to be less informative. Although a combination of antibiotics might have a future in treating established disease, diagnosing and treating non-gonococcal urethritis as soon as possible should be the aim in order to prevent the development of reactive arthritis. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav Source

Tadrous P.J.,Northwick Park Hospital
Pathology | Year: 2010

Aims: The term 'objective' connotes a method that is based on facts and not influenced by personal opinions, perception or emotion. One often reads in the biomedical literature claims of objectivity for methods that use digital image analysis applied to histology. Since objective assessment of histology would represent a huge leap forward in scientific measurement and clinical diagnosis, such claims should be substantiated by strong evidence. This paper takes a selective look at the literature on image analysis to assess the definition of objectivity in image analysis and asks whether such a claim is ever justified. Methods: First, a brief background on the basic science of image analysis in histology details some of the controversies and opinions in the field. Then, a literature review of a subset of papers pertaining to image analysis in histology (with claims of objectivity) is conducted to determine what evidence exists for objectivity in these methods. Results: It was found that image analysis may have many benefits (speed, indefatigability, standardisation, etc.). However, algorithms are devised and implemented by human beings who make subjective decisions at each stage of the algorithm design and implementation process. Thus, image analysis methods can be seen as deterministic processes which 'objectively' implement the subjective decisions of the programmer. This indicates that 'inter-observer' variation in image analysis is equivalent to 'inter-algorithm' variation (which is rarely studied) and that a single computer algorithm's repeatability is of lesser importance than the repeatability of the image analysis method as a whole (including the block, slide and field selection and the method of tissue processing). Conclusion: Repeatability and automaticity must not be confused with objectivity, but a lack of objectivity does not imply a lack of utility. Unless specific evidence of objectivity is provided, editors should insist that claims of objectivity in image analysis papers be either removed or justified prior to publication. © 2010 Royal College of Pathologists of Australasia. Source

Tadrous P.J.,Northwick Park Hospital
Journal of Microscopy | Year: 2010

This paper addresses the problem of 3D deconvolution of through focus widefield microscope datasets (Z-stacks). One of the most difficult stages in brightfield deconvolution is finding the point spread function. A theoretically calculated point spread function (called a 'synthetic PSF' in this paper) requires foreknowledge of many system parameters and still gives only approximate results. A point spread function measured from a sub-resolution bead suffers from low signal-to-noise ratio, compounded in the brightfield setting (by contrast to fluorescence) by absorptive, refractive and dispersal effects. This paper describes a method of point spread function estimation based on measurements of a Z-stack through a thin sample. This Z-stack is deconvolved by an idealized point spread function derived from the same Z-stack to yield a point spread function of high signal-to-noise ratio that is also inherently tailored to the imaging system. The theory is validated by a practical experiment comparing the non-blind 3D deconvolution of the yeast Saccharomyces cerevisiae with the point spread function generated using the method presented in this paper (called the 'extracted PSF') to a synthetic point spread function. Restoration of both high-and low-contrast brightfield structures is achieved with fewer artefacts using the extracted point spread function obtained with this method. Furthermore the deconvolution progresses further (more iterations are allowed before the error function reaches its nadir) with the extracted point spread function compared to the synthetic point spread function indicating that the extracted point spread function is a better fit to the brightfield deconvolution model than the synthetic point spread function. © 2009 The Royal Microscopical Society. Source

Tadrous P.J.,Northwick Park Hospital
Journal of Microscopy | Year: 2010

It is often desirable to perform digital image analyses on sections prepared for human interpretation, e.g. nuclear chromatin texture analysis or three-dimensional reconstructions using sections requiring human delineation of structures of interest. Unfortunately such analyses are often more effective using stains with less complex contrast. Here an automated selective 'de-staining' method for digital images is presented. The method separates an image into its red, green and blue and hue, saturation and intensity components. A mask of stained tissue is prepared by automatic percentile thresholding. A single weighted inverted colour channel is then added to each of the three primary colour channels separately by an iterative algorithm that adjusts the weights to give minimum variance within the mask. The modified red, green and blue channels are then recombined. This method is automatic requiring no pre-definition of stain colours or special hardware. The method is demonstrated to 'de-stain' nuclei in haematoxylin and eosin (H&E) sections (and a separate haematoxylin image can be derived from this). An image of isolated brown reaction product is produced with immunoperoxidase preparations counterstained with haematoxylin. Furthermore trichrome (haematoxylin van Gieson, picrosirius red) and other common stains may be separated into their components with modifications of the same algorithm. Although other methods for colour separation do exist (e.g. spectral pathology and colour deconvolution) these require special apparatus or precise calibration and foreknowledge of pure dye colour spectra. The present method of digital stain separation is fully automatic with no such prerequisites. © 2010 The Author Journal compilation © 2010 The Royal Microscopical Society. Source

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