Alzheimer's disease and vision: a proposed new diagnostic test

A potential non-invasive neurobiological test for Alzheimer's disease has been recently proposed and published. This test is likely to be of considerable interest to optometrists as it involves measurements of pupil dilation. This article decsribes some of the controversial issues surrounding the clinical diagnosis of Alzheimer's disease and discusses the advantages, limitations, and implications of the new test.

Shaping acoustic fields as a toolset for microfluidic manipulations in diagnostic technologies

Ultrasonics offers the possibility of developing sophisticated fluid manipulation tools in lab-on-a-chip technologies. Here we demonstrate the ability to shape ultrasonic fields by using phononic lattices, patterned on a disposable chip, to carry out the complex sequence of fluidic manipulations required to detect the rodent malaria parasite Plasmodium berghei in blood. To illustrate the different tools that are available to us, we used acoustic fields to produce the required rotational vortices that mechanically lyse both the red blood cells and the parasitic cells present in a drop of blood. This procedure was followed by the amplification of parasitic genomic sequences using different acoustic fields and frequencies to heat the sample and perform a real-time PCR amplification. The system does not require the use of lytic reagents nor enrichment steps, making it suitable for further integration into lab-on-a-chip point-of-care devices. This acoustic sample preparation and PCR enables us to detect ca. 30 parasites in a microliter-sized blood sample, which is the same order of magnitude in sensitivity as lab-based PCR tests. Unlike other lab-on-a-chip methods, where the sample moves through channels, here we use our ability to shape the acoustic fields in a frequency-dependent manner to provide different analytical functions. The methods also provide a clear route toward the integration of PCR to detect pathogens in a single handheld system.

The psychological impact of diagnostic food challenges to confirm the resolution of peanut or tree nut allergy

Background - Twenty percent of children outgrow peanut allergy and 10% outgrow tree nut allergy. Resolution can be confirmed by a food challenge. Little is known about the psychosocial impact of the challenge. We aimed to investigate effects of a food challenge on anxiety, stress and quality of life (QoL) in children and their mothers on the day of a food challenge to peanuts or nuts, and in the months following the challenge. Methods - One hundred and three families participated. Forty children undergoing food challenges to access resolution of allergy, and their mothers, completed validated questionnaires to measure generic and food specific quality of life, stress and anxiety prior to challenge, on the day of investigation and 3–6 months later. Sixty-three children with no clinical indication to challenge (i.e. in the opinion of the allergist had persistent allergy) acted as comparison group completing questionnaires 3–6 months apart. Results - Mothers reported raised anxiety on the day of challenge (P = 0.007), but children were less anxious. The children (P = 0.01) and mothers (P = 0.01) had improved food-related, but not general, QoL 3–6 months following challenge. Children reported lower anxiety levels following the challenge (P = 0.02), but anxiety remained unchanged in mothers. The improvements in maternal and children's QoL and anxiety levels were irrespective of the challenge outcome and despite co-existing food allergies in 50% of children. Conclusions - Mothers experienced increased anxiety on the day of food challenge, unlike the children, perhaps reflecting the differences in their perceived risks. Food challenges are associated with improved food-related QoL in the following months even in those with a positive challenge.

Automatic applications of diagnostic conditionaing monitoring

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Evidence of lipid degradation during overnight contact lens wear:gas chromatography mass spectrometry as the diagnostic tool

Purpose. We investigated structural differences in the fatty acid profiles of lipids extracted from ex vivo contact lenses by using gas chromatography mass spectrometry (GCMS). Two lens materials (balafilcon A or lotrafilcon A) were worn on a daily or continuous wear schedule for 30 and 7 days. Methods. Lipids from subject-worn lenses were extracted using 1:1 chloroform: methanol and transmethylated using 5% sulfuric acid in methanol. Fatty acid methyl esters (FAMEs) were collected using hexane and water, and analyzed by GCMS (Varian 3800 GC, Saturn 2000 MS). Results. The gas chromatograms of lens extracts that were worn on a continuous wear schedule showed two predominant peaks, C16:0 and C18:0, both of which are saturated fatty acids. This was the case for balafilcon A and lotrafilcon A lenses. However, the gas chromatograms of lens extracts that were worn on a daily wear schedule showed saturated (C16:0, C18:0) and unsaturated (C16:1 and C18:1) fatty acids. Conclusions. Unsaturated fatty acids are degraded during sleep in contact lenses. Degradation occurred independently of lens material or subject-to-subject variability in lipid deposition. The consequences of lipid degradation are the production of oxidative products, which may be linked to contact lens discomfort. © 2014 The Association for Research in Vision and Ophthalmology, Inc.

Basic principles of design and functioning of multifunctional laser diagnostic system for non-invasive medical spectrophotometry

The devising of a general engineering theory of multifunctional diagnostic systems for non-invasive medical spectrophotometry is an important and promising direction of modern biomedical engineering. We aim in this study to formalize in scientific engineering terms objectives for multifunctional laser non-invasive diagnostic system (MLNDS). The structure-functional model as well as a task-function of generalized MLNDS was formulated and developed. The key role of the system software for MLNDS general architecture at steps of ideological-technical designing has been proved. The basic principles of block-modules composition of MLNDS hardware are suggested as well. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Diagnostic Systems in Medicine as Personal Intellectual Tooling

The standards of diagnostic systems formation in medicine based on modeling expert’s “means of action” in form of illegible trees of solution-making taking into consideration the criteria of credibility and usefulness have been suggested. The fragments of “applied” trees at diagnosing infectious and urological diseases have been considered as well. The possibilities of modern tooling theory usage for decision-making during creation of artificial intelligence systems have been discussed.

Neural Networks: A Diagnostic Tool for Gastric Electrical Uncoupling?

Neural Networks have been successfully employed in different biomedical settings. They have been useful for feature extractions from images and biomedical data in a variety of diagnostic applications. In this paper, they are applied as a diagnostic tool for classifying different levels of gastric electrical uncoupling in controlled acute experiments on dogs. Data was collected from 16 dogs using six bipolar electrodes inserted into the serosa of the antral wall. Each dog underwent three recordings under different conditions: (1) basal state, (2) mild surgically-induced uncoupling, and (3) severe surgically-induced uncoupling. For each condition half-hour recordings were made. The neural network was implemented according to the Learning Vector Quantization model. This is a supervised learning model of the Kohonen Self-Organizing Maps. Majority of the recordings collected from the dogs were used for network training. Remaining recordings served as a testing tool to examine the validity of the training procedure. Approximately 90% of the dogs from the neural network training set were classified properly. However, only 31% of the dogs not included in the training process were accurately diagnosed. The poor neural-network based diagnosis of recordings that did not participate in the training process might have been caused by inappropriate representation of input data. Previous research has suggested characterizing signals according to certain features of the recorded data. This method, if employed, would reduce the noise and possibly improve the diagnostic abilities of the neural network.

Signposting for diagnosis of Autism Spectrum Disorder using the Diagnostic Interview for Social and Communication Disorders (DISCO)

Recent research has investigated the capability of the Diagnostic and Statistical Manual for Mental Disorders (DSM-5) descriptions to identify individuals who should receive a diagnosis of Autism Spectrum Disorder (ASD) using standardised diagnostic instruments. Building on previous research investigating behaviours essential for the diagnosis of DSM-5 ASD, the current study investigated the sensitivity and specificity of a set of 14 items derived from the Diagnostic Interview for Social and Communication Disorders (DISCO Signposting set) that have potential for signposting the diagnosis of autism according to both the new DSM-5 criteria for ASD and ICD-10 criteria for Childhood Autism. An algorithm threshold for the Signposting set was calculated in Sample 1 (n = 67), tested in an independent validation sample (Sample 2; n = 78), and applied across age and ability sub-groups in Sample 3 (n = 190). The algorithm had excellent predictive validity according to best estimate clinical diagnosis (Samples 1 and 2) and excellent agreement with established algorithms for both DSM-5 and ICD-10 (all samples). The signposting set has potential to inform our understanding of the profile of ASD in relation to other neurodevelopmental disorders and to form the basis of a Signposting Interview for use in clinical practice.

Implementation of a machine tool performance measurement and diagnostic system and its impact on parts verification

Five axis machine tools are increasing and becoming more popular as customers demand more complex machined parts. In high value manufacturing, the importance of machine tools in producing high accuracy products is essential. High accuracy manufacturing requires producing parts in a repeatable manner and precision in compliance to the defined design specifications. The performance of the machine tools is often affected by geometrical errors due to a variety of causes including incorrect tool offsets, errors in the centres of rotation and thermal growth. As a consequence, it can be difficult to produce highly accurate parts consistently. It is, therefore, essential to ensure that machine tools are verified in terms of their geometric and positioning accuracy. When machine tools are verified in terms of their accuracy, the resulting numerical values of positional accuracy and process capability can be used to define design for verification rules and algorithms so that machined parts can be easily produced without scrap and little or no after process measurement. In this paper the benefits of machine tool verification are listed and a case study is used to demonstrate the implementation of robust machine tool performance measurement and diagnostics using a ballbar system.

A Model of a Diagnostic Test for Controlling the Results of a Computer Based Education in Applied Mathematics at the University of Ruse

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015

The adoption and use of diagnostic and prognostic technology within UK-based manufacturers

Manufacturers are seeking increasingly innovative ways to achieve competitive advantage. An emerging trend is to exploit diagnostic and prognostic technology to support service-led competitive strategies where the emphasis is put on the 'sale of use' rather than the 'sale of product'. However, little is known about the extent to which this technology is being exploited, the drivers and inhibitors, and the sectors where adoption is most prolific. This paper introduces the results of a survey conducted across the UK manufacturing sector to explore the extent, motivations, benefits, and challenges of deploying diagnostic and prognostic technology as an element of competitive strategy.