Comparing the utility of DSM-5 Section II and III antisocial personality disorder diagnostic approaches for capturing psychopathic traits.

PubMed

Few, Lauren R; Lynam, Donald R; Maples, Jessica L; MacKillop, James; Miller, Joshua D

2015-01-01

The current study compares the 2 diagnostic approaches (Section II vs. Section III) included in the Diagnostic and Statistical Manual for Mental Disorders-5 (DSM-5; American Psychiatric Association, 2013) for diagnosis of antisocial personality disorder (ASPD) in terms of their relations with psychopathic traits and externalizing behaviors (EBs). The Section III approach to ASPD, which is more explicitly trait-based than the Section II approach, also includes a psychopathy specifier (PS) that was created with the goal of making the diagnosis of ASPD more congruent with psychopathy. In a community sample of individuals currently receiving mental health treatment (N = 106), ratings of the 2 DSM-5 diagnostic approaches were compared in relation to measures of psychopathy, as well as indices of EBs. Both DSM-5 ASPD approaches were significantly related to the psychopathy scores, although the Section III approach accounted for almost twice the amount of variance when compared with the Section II approach. Relatively little of this predictive advantage, however, was due to the PS, as these traits manifested little evidence of incremental validity in relation to existing psychopathy measures and EBs, with the exception of a measure of fearless dominance. Overall, the DSM-5 Section III diagnostic approach for ASPD is more convergent with the construct of psychopathy, from which ASPD was originally derived. These improvements, however, are due primarily to the new trait-based focus in the Section III ASPD diagnosis rather than the assessment of personality dysfunction or the inclusion of additional "psychopathy-specific" traits. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

A Review of Diagnostic Techniques for ISHM Applications

NASA Technical Reports Server (NTRS)

Patterson-Hine, Ann; Biswas, Gautam; Aaseng, Gordon; Narasimhan, Sriam; Pattipati, Krishna

2005-01-01

System diagnosis is an integral part of any Integrated System Health Management application. Diagnostic applications make use of system information from the design phase, such as safety and mission assurance analysis, failure modes and effects analysis, hazards analysis, functional models, fault propagation models, and testability analysis. In modern process control and equipment monitoring systems, topological and analytic , models of the nominal system, derived from design documents, are also employed for fault isolation and identification. Depending on the complexity of the monitored signals from the physical system, diagnostic applications may involve straightforward trending and feature extraction techniques to retrieve the parameters of importance from the sensor streams. They also may involve very complex analysis routines, such as signal processing, learning or classification methods to derive the parameters of importance to diagnosis. The process that is used to diagnose anomalous conditions from monitored system signals varies widely across the different approaches to system diagnosis. Rule-based expert systems, case-based reasoning systems, model-based reasoning systems, learning systems, and probabilistic reasoning systems are examples of the many diverse approaches ta diagnostic reasoning. Many engineering disciplines have specific approaches to modeling, monitoring and diagnosing anomalous conditions. Therefore, there is no "one-size-fits-all" approach to building diagnostic and health monitoring capabilities for a system. For instance, the conventional approaches to diagnosing failures in rotorcraft applications are very different from those used in communications systems. Further, online and offline automated diagnostic applications are integrated into an operations framework with flight crews, flight controllers and maintenance teams. While the emphasis of this paper is automation of health management functions, striking the correct balance between automated and human-performed tasks is a vital concern.

New diagnostic methods for pneumonia in the ICU.

PubMed

Douglas, Ivor S

2016-04-01

Pneumonia leading to severe sepsis and critical illness including respiratory failure remains a common and therapeutically challenging diagnosis. Current clinical approaches to surveillance, early detection, and conventional culture-based microbiology are inadequate for optimal targeted antibiotic treatment and stewardship. Efforts to enhance diagnosis of community-acquired and health care-acquired pneumonia, including ventilator-associated pneumonia (VAP), are the focus of recent studies reviewed here. Newer surveillance definitions are sensitive for pneumonia in the ICU including VAP but consistently underdetect patients that are clinically shown to have bacterial VAP based on clinical diagnostic criteria and response to antibiotic treatment. Routinely measured plasma biomarkers, including procalcitonin and C-reactive protein, lack sufficient precision and predictive accuracy to inform diagnosis. Novel rapid microbiological diagnostics, including nucleic-acid amplification, mass spectrometry, and fluorescence microscopy-based technologies are promising approaches for the future. Exhaled breath biomarkers, including measurement of volatile organic compounds, represent a future approach. The integration of novel diagnostics for rapid microbial identification, resistance phenotyping, and antibiotic sensitivity testing into usual care practice could significantly transform the care of patients and potentially inform significantly improved targeted antimicrobial selection, de-escalation, and stewardship.

Identification of species based on DNA barcode using k-mer feature vector and Random forest classifier.

PubMed

Meher, Prabina Kumar; Sahu, Tanmaya Kumar; Rao, A R

2016-11-05

DNA barcoding is a molecular diagnostic method that allows automated and accurate identification of species based on a short and standardized fragment of DNA. To this end, an attempt has been made in this study to develop a computational approach for identifying the species by comparing its barcode with the barcode sequence of known species present in the reference library. Each barcode sequence was first mapped onto a numeric feature vector based on k-mer frequencies and then Random forest methodology was employed on the transformed dataset for species identification. The proposed approach outperformed similarity-based, tree-based, diagnostic-based approaches and found comparable with existing supervised learning based approaches in terms of species identification success rate, while compared using real and simulated datasets. Based on the proposed approach, an online web interface SPIDBAR has also been developed and made freely available at http://cabgrid.res.in:8080/spidbar/ for species identification by the taxonomists. Copyright © 2016 Elsevier B.V. All rights reserved.

Breast tumor malignancy modelling using evolutionary neural logic networks.

PubMed

Tsakonas, Athanasios; Dounias, Georgios; Panagi, Georgia; Panourgias, Evangelia

2006-01-01

The present work proposes a computer assisted methodology for the effective modelling of the diagnostic decision for breast tumor malignancy. The suggested approach is based on innovative hybrid computational intelligence algorithms properly applied in related cytological data contained in past medical records. The experimental data used in this study were gathered in the early 1990s in the University of Wisconsin, based in post diagnostic cytological observations performed by expert medical staff. Data were properly encoded in a computer database and accordingly, various alternative modelling techniques were applied on them, in an attempt to form diagnostic models. Previous methods included standard optimisation techniques, as well as artificial intelligence approaches, in a way that a variety of related publications exists in modern literature on the subject. In this report, a hybrid computational intelligence approach is suggested, which effectively combines modern mathematical logic principles, neural computation and genetic programming in an effective manner. The approach proves promising either in terms of diagnostic accuracy and generalization capabilities, or in terms of comprehensibility and practical importance for the related medical staff.

Overcoming limitations of model-based diagnostic reasoning systems

NASA Technical Reports Server (NTRS)

Holtzblatt, Lester J.; Marcotte, Richard A.; Piazza, Richard L.

1989-01-01

The development of a model-based diagnostic system to overcome the limitations of model-based reasoning systems is discussed. It is noted that model-based reasoning techniques can be used to analyze the failure behavior and diagnosability of system and circuit designs as part of the system process itself. One goal of current research is the development of a diagnostic algorithm which can reason efficiently about large numbers of diagnostic suspects and can handle both combinational and sequential circuits. A second goal is to address the model-creation problem by developing an approach for using design models to construct the GMODS model in an automated fashion.

Organizing the Diagnostics of Multicultural Personality in College Students

ERIC Educational Resources Information Center

Begaliyeva, Saule; Issabekova, Gulnur; Saudabaeva, Gulmira; Zhanna, Axakalova; Abdildaev, Abdikhalyk Kosherbayuly

2016-01-01

The aim of present study is to reveal the actual state of multicultural personality development in college students, based on a specially selected diagnostic inventory. The problem of multicultural personality development on the level of present pedagogics development allows taking the leading methodologic theories and approaches as the bases.…

Novel diagnostic techniques for celiac disease.

PubMed

Kurppa, Kalle; Taavela, Juha; Saavalainen, Päivi; Kaukinen, Katri; Lindfors, Katri

2016-07-01

The diagnosis of celiac disease has long been based on the demonstration of gluten-induced small-bowel mucosal damage. However, due to the constantly increasing disease prevalence and limitations in the histology-based criteria there is a pressure towards more serology-based diagnostics. The serological tools are being improved and new non-invasive methods are being developed, but the constantly refined endoscopic and histologic techniques may still prove helpful. Moreover, growing understanding of the disease pathogenesis has led researchers to suggest completely novel approaches to celiac disease diagnostics regardless of disease activity. In this review, we will elucidate the most recent development and possible future innovations in the diagnostic techniques for celiac disease.

Application of the Systematic Sensor Selection Strategy for Turbofan Engine Diagnostics

NASA Technical Reports Server (NTRS)

Sowers, T. Shane; Kopasakis, George; Simon, Donald L.

2008-01-01

The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance, there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight, and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.

Application of the Systematic Sensor Selection Strategy for Turbofan Engine Diagnostics

NASA Technical Reports Server (NTRS)

Sowers, T. Shane; Kopasakis, George; Simon, Donald L.

2008-01-01

The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.

Optical biosensor technologies for molecular diagnostics at the point-of-care

NASA Astrophysics Data System (ADS)

Schotter, Joerg; Schrittwieser, Stefan; Muellner, Paul; Melnik, Eva; Hainberger, Rainer; Koppitsch, Guenther; Schrank, Franz; Soulantika, Katerina; Lentijo-Mozo, Sergio; Pelaz, Beatriz; Parak, Wolfgang; Ludwig, Frank; Dieckhoff, Jan

2015-05-01

Label-free optical schemes for molecular biosensing hold a strong promise for point-of-care applications in medical research and diagnostics. Apart from diagnostic requirements in terms of sensitivity, specificity, and multiplexing capability, also other aspects such as ease of use and manufacturability have to be considered in order to pave the way to a practical implementation. We present integrated optical waveguide as well as magnetic nanoparticle based molecular biosensor concepts that address these aspects. The integrated optical waveguide devices are based on low-loss photonic wires made of silicon nitride deposited by a CMOS compatible plasma-enhanced chemical vapor deposition (PECVD) process that allows for backend integration of waveguides on optoelectronic CMOS chips. The molecular detection principle relies on evanescent wave sensing in the 0.85 μm wavelength regime by means of Mach-Zehnder interferometers, which enables on-chip integration of silicon photodiodes and, thus, the realization of system-on-chip solutions. Our nanoparticle-based approach is based on optical observation of the dynamic response of functionalized magneticcore/ noble-metal-shell nanorods (`nanoprobes') to an externally applied time-varying magnetic field. As target molecules specifically bind to the surface of the nanoprobes, the observed dynamics of the nanoprobes changes, and the concentration of target molecules in the sample solution can be quantified. This approach is suitable for dynamic real-time measurements and only requires minimal sample preparation, thus presenting a highly promising point-of-care diagnostic system. In this paper, we present a prototype of a diagnostic device suitable for highly automated sample analysis by our nanoparticle-based approach.

Engineering Paper-Based Sensors for Zika Virus

DOE PAGES

Meagher, Robert J.; Negrete, Oscar A.; Van Rompay, Koen K.

2016-05-30

The emergence of Zika virus in Latin America has created an urgent need for new, simple yet sensitive diagnostic tests. We highlight recent work using paper-based sensors coupled with CRISPR/Cas9 to detect Zika RNA, as a new approach to rapid development and deployment of field-ready diagnostics for emerging infectious diseases.

Engineering Paper-Based Sensors for Zika Virus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meagher, Robert J.; Negrete, Oscar A.; Van Rompay, Koen K.

The emergence of Zika virus in Latin America has created an urgent need for new, simple yet sensitive diagnostic tests. We highlight recent work using paper-based sensors coupled with CRISPR/Cas9 to detect Zika RNA, as a new approach to rapid development and deployment of field-ready diagnostics for emerging infectious diseases.

A clinical approach to diagnosis of autoimmune encephalitis

PubMed Central

Graus, Francesc; Titulaer, Maarten J; Balu, Ramani; Benseler, Susanne; Bien, Christian G; Cellucci, Tania; Cortese, Irene; Dale, Russell C; Gelfand, Jeffrey M; Geschwind, Michael; Glaser, Carol A; Honnorat, Jerome; Höftberger, Romana; Iizuka, Takahiro; Irani, Sarosh R; Lancaster, Eric; Leypoldt, Frank; Prüss, Harald; Rae-Grant, Alexander; Reindl, Markus; Rosenfeld, Myrna R; Rostásy, Kevin; Saiz, Albert; Venkatesan, Arun; Vincent, Angela; Wandinger, Klaus-Peter; Waters, Patrick; Dalmau, Josep

2016-01-01

Encephalitis is a severe inflammatory disorder of the brain with many possible causes and a complex differential diagnosis. Advances in autoimmune encephalitis research in the past 10 years have led to the identification of new syndromes and biomarkers that have transformed the diagnostic approach to these disorders. However, existing criteria for autoimmune encephalitis are too reliant on antibody testing and response to immunotherapy, which might delay the diagnosis. We reviewed the literature and gathered the experience of a team of experts with the aims of developing a practical, syndrome-based diagnostic approach to autoimmune encephalitis and providing guidelines to navigate through the differential diagnosis. Because autoantibody test results and response to therapy are not available at disease onset, we based the initial diagnostic approach on neurological assessment and conventional tests that are accessible to most clinicians. Through logical differential diagnosis, levels of evidence for autoimmune encephalitis (possible, probable, or definite) are achieved, which can lead to prompt immunotherapy. PMID:26906964

Diagnostic devices for isothermal nucleic acid amplification.

PubMed

Chang, Chia-Chen; Chen, Chien-Cheng; Wei, Shih-Chung; Lu, Hui-Hsin; Liang, Yang-Hung; Lin, Chii-Wann

2012-01-01

Since the development of the polymerase chain reaction (PCR) technique, genomic information has been retrievable from lesser amounts of DNA than previously possible. PCR-based amplifications require high-precision instruments to perform temperature cycling reactions; further, they are cumbersome for routine clinical use. However, the use of isothermal approaches can eliminate many complications associated with thermocycling. The application of diagnostic devices for isothermal DNA amplification has recently been studied extensively. In this paper, we describe the basic concepts of several isothermal amplification approaches and review recent progress in diagnostic device development.

Diagnostic Devices for Isothermal Nucleic Acid Amplification

PubMed Central

Chang, Chia-Chen; Chen, Chien-Cheng; Wei, Shih-Chung; Lu, Hui-Hsin; Liang, Yang-Hung; Lin, Chii-Wann

2012-01-01

Since the development of the polymerase chain reaction (PCR) technique, genomic information has been retrievable from lesser amounts of DNA than previously possible. PCR-based amplifications require high-precision instruments to perform temperature cycling reactions; further, they are cumbersome for routine clinical use. However, the use of isothermal approaches can eliminate many complications associated with thermocycling. The application of diagnostic devices for isothermal DNA amplification has recently been studied extensively. In this paper, we describe the basic concepts of several isothermal amplification approaches and review recent progress in diagnostic device development. PMID:22969402

A Framework for Final Drive Simultaneous Failure Diagnosis Based on Fuzzy Entropy and Sparse Bayesian Extreme Learning Machine

PubMed Central

Ye, Qing; Pan, Hao; Liu, Changhua

2015-01-01

This research proposes a novel framework of final drive simultaneous failure diagnosis containing feature extraction, training paired diagnostic models, generating decision threshold, and recognizing simultaneous failure modes. In feature extraction module, adopt wavelet package transform and fuzzy entropy to reduce noise interference and extract representative features of failure mode. Use single failure sample to construct probability classifiers based on paired sparse Bayesian extreme learning machine which is trained only by single failure modes and have high generalization and sparsity of sparse Bayesian learning approach. To generate optimal decision threshold which can convert probability output obtained from classifiers into final simultaneous failure modes, this research proposes using samples containing both single and simultaneous failure modes and Grid search method which is superior to traditional techniques in global optimization. Compared with other frequently used diagnostic approaches based on support vector machine and probability neural networks, experiment results based on F 1-measure value verify that the diagnostic accuracy and efficiency of the proposed framework which are crucial for simultaneous failure diagnosis are superior to the existing approach. PMID:25722717

On the cutting edge of obstructive sleep apnoea: where next?

PubMed Central

Malhotra, Atul; Orr, Jeremy E; Owens, Robert L

2015-01-01

Obstructive sleep apnoea is a common disease that is now more widely recognised because of the rise in prevalence and the increasingly compelling data that shows major neurocognitive and cardiovascular sequelae. At the same time, the clinical practice of sleep medicine is changing rapidly, with novel diagnostics and treatments that have established a home-based (rather than laboratory-based) management approach. We review the most recent insights and discoveries in obstructive sleep apnoea, with a focus on diagnostics and therapeutics. As will be discussed, management of obstructive sleep apnoea could soon transition from a so-called one size fits all approach to an individualised approach. PMID:25887980

Universal antifungal therapy is not needed in persistent febrile neutropenia: a tailored diagnostic and therapeutic approach

PubMed Central

Aguilar-Guisado, Manuela; Martín-Peña, Almudena; Espigado, Ildefonso; Ruiz Pérez de Pipaon, Maite; Falantes, José; de la Cruz, Fátima; Cisneros, José M.

2012-01-01

Background Giving antifungal therapy exclusively to selected patients with persistent febrile neutropenia may avoid over-treatment without increasing mortality. The aim of this study was to validate an innovative diagnostic and therapeutic approach based on assessing patients’ risk profile and clinical criteria in order to select those patients requiring antifungal therapy. The efficacy of this approach was compared to that of universal empirical antifungal therapy. Design and Methods This was a prospective study which included all consecutive adult hematology patients with neutropenia and fever refractory to 5 days of empirical antibacterial therapy admitted to a teaching hospital in Spain over a 2-year period. A diagnostic and therapeutic approach based on clinical criteria and risk profile was applied in order to select patients for antifungal therapy. The sensitivity, specificity and negative predictive value of this approach and also the overall success rate, according to the same criteria of efficacy described in classical clinical trials, were analyzed. Results Eighty-five episodes were included, 35 of them (41.2%) in patients at high risk of invasive fungal infections. Antifungal therapy was not indicated in 33 episodes (38.8%). The overall incidence of proven and probable invasive fungal infections was 14.1%, all of which occurred in patients who had received empirical antifungal therapy. The 30-day crude mortality rate was 15.3% and the invasive fungal infection-related mortality rate was 2.8% (2/72). The overall success rate following the diagnostic and therapeutic approach was 36.5% compared with 33.9% and 33.7% obtained in the trial by Walsh et al. The sensitivity, specificity and negative predictive value of the study approach were 100%, 52.4% and 100%, respectively. Conclusions Based on the high negative predictive value of this diagnostic and therapeutic approach in persistent febrile neutropenia patients with hematologic malignancies or patients who have received a hematopoietic stem cell transplant, the approach is useful for identifying patients who are not likely to develop invasive fungal infection and do not, therefore, require antifungal therapy. The effectiveness of the strategy is similar to that of universal empirical antifungal therapy reported in controlled trials. PMID:22058202

Immune-Response Patterns and Next Generation Sequencing Diagnostics for the Detection of Mycoses in Patients with Septic Shock-Results of a Combined Clinical and Experimental Investigation.

PubMed

Decker, Sebastian O; Sigl, Annette; Grumaz, Christian; Stevens, Philip; Vainshtein, Yevhen; Zimmermann, Stefan; Weigand, Markus A; Hofer, Stefan; Sohn, Kai; Brenner, Thorsten

2017-08-18

Fungi are of increasing importance in sepsis. However, culture-based diagnostic procedures are associated with relevant weaknesses. Therefore, culture- and next-generation sequencing (NGS)-based fungal findings as well as corresponding plasma levels of β-d-glucan, interferon gamma (INF-γ), tumor necrosis factor alpha (TNF-α), interleukin (IL)-2, -4, -6, -10, -17A, and mid-regional proadrenomedullin (MR-proADM) were evaluated in 50 septic patients at six consecutive time points within 28 days after sepsis onset. Furthermore, immune-response patterns during infections with Candida spp. were studied in a reconstituted human epithelium model. In total, 22% ( n = 11) of patients suffered from a fungal infection. An NGS-based diagnostic approach appeared to be suitable for the identification of fungal pathogens in patients suffering from fungemia as well as in patients with negative blood cultures. Moreover, MR-proADM and IL-17A in plasma proved suitable for the identification of patients with a fungal infection. Using RNA-seq., adrenomedullin (ADM) was shown to be a target gene which is upregulated early after an epithelial infection with Candida spp. In summary, an NGS-based diagnostic approach was able to close the diagnostic gap of routinely used culture-based diagnostic procedures, which can be further facilitated by plasmatic measurements of MR-proADM and IL-17A. In addition, ADM was identified as an early target gene in response to epithelial infections with Candida spp.

Next-generation sequencing diagnostics of bacteremia in sepsis (Next GeneSiS-Trial): Study protocol of a prospective, observational, noninterventional, multicenter, clinical trial.

PubMed

Brenner, Thorsten; Decker, Sebastian O; Grumaz, Silke; Stevens, Philip; Bruckner, Thomas; Schmoch, Thomas; Pletz, Mathias W; Bracht, Hendrik; Hofer, Stefan; Marx, Gernot; Weigand, Markus A; Sohn, Kai

2018-02-01

Sepsis remains a major challenge, even in modern intensive care medicine. The identification of the causative pathogen is crucial for an early optimization of the antimicrobial treatment regime. In this context, culture-based diagnostic procedures (e.g., blood cultures) represent the standard of care, although they are associated with relevant limitations. Accordingly, culture-independent molecular diagnostic procedures might be of help for the identification of the causative pathogen in infected patients. The concept of an unbiased sequence analysis of circulating cell-free DNA (cfDNA) from plasma samples of septic patients by next-generation sequencing (NGS) has recently been identified to be a promising diagnostic platform for critically ill patients suffering from bloodstream infections. Although this new approach might be more sensitive and specific than culture-based state-of-the-art technologies, additional clinical trials are needed to exactly define the performance as well as clinical value of a NGS-based approach. Next GeneSiS is a prospective, observational, noninterventional, multicenter study to assess the diagnostic performance of a NGS-based approach for the detection of relevant infecting organisms in patients with suspected or proven sepsis [according to recent sepsis definitions (sepsis-3)] by the use of the quantitative sepsis indicating quantifier (SIQ) score in comparison to standard (culture-based) microbiological diagnostics. The clinical value of this NGS-based approach will be estimated by a panel of independent clinical specialists, retrospectively identifying potential changes in patients' management based on NGS results. Further subgroup analyses will focus on the clinical value especially for patients suffering from a failure of empiric treatment within the first 3 days after onset [as assessed by death of the patient or lack of improvement of the patient's clinical condition (in terms of an inadequate decrease of SOFA-score) or persistent high procalcitonin levels]. This prospective, observational, noninterventional, multicenter study for the first time investigates the performance as well as the clinical value of a NGS-based approach for the detection of bacteremia in patients with sepsis and may therefore be a pivotal step toward the clinical use of NGS in this indication. DRKS-ID: DRKS00011911 (registered October 9, 2017) https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00011911; ClinicalTrials.gov Identifier: NCT03356249 (registered November 29, 2017) https://clinicaltrials.gov/ct2/show/NCT03356249.

The computation in diagnostics for tokamaks: systems, designs, approaches

NASA Astrophysics Data System (ADS)

Krawczyk, Rafał; Linczuk, Paweł; Czarski, Tomasz; Wojeński, Andrzej; Chernyshova, Maryna; Poźniak, Krzysztof; Kolasiński, Piotr; Kasprowicz, Grzegorz; Zabołotny, Wojciech; Kowalska-Strzeciwilk, Ewa; Malinowski, Karol; Gaska, Michał

2017-08-01

The requirements given for GEM (Gaseous Electron Multiplier) detector based acquisition system for plasma impurities diagnostics triggered a need for the development of a specialized software and hardware architecture. The amount of computations with latency and throughput restrictions cause that an advanced solution is sought for. In order to provide a mechanism fitting the designated tokamaks, an insight into existing solutions was necessary. In the article there is discussed architecture of systems used for plasma diagnostics and in related scientific fields. The developed solution is compared and contrasted with other diagnostic and control systems. Particular attention is payed to specific requirements for plasma impurities diagnostics in tokamak thermal fusion reactor. Subsequently, the details are presented that justified the choice of the system architecture and the discussion on various approaches is given.

A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2001-01-01

In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.

[Conceptual foundation of the operational diagnostic approach in psychiatry].

PubMed

Jäger, M; Strauss, A; Frasch, K; Becker, T

2007-08-01

Based on the pioneering work of Emil Kraepelin, Karl Jaspers, Kurt Schneider and representatives of logical empiricism, the basic principles of the operational diagnostic approach in psychiatry are described. Operational diagnostic systems like ICD-10 and DSM-IV aimed at a standardisation of psychiatric language which can be accepted by different schools in psychiatry. However, ICD-10 and DSM-IV should not be misinterpreted as "nosology" because they do not reflect a specific model of psychiatric diseases. The advantages of operational diagnostic systems as instruments for communication in a clinical and scientific context are limited by the fact that they disregard the subjective psychopathology. This dimension, however, deserves attention in clinic and research.

Microfluidic technology for molecular diagnostics.

PubMed

Robinson, Tom; Dittrich, Petra S

2013-01-01

Molecular diagnostics have helped to improve the lives of millions of patients worldwide by allowing clinicians to diagnose patients earlier as well as providing better ongoing therapies. Point-of-care (POC) testing can bring these laboratory-based techniques to the patient in a home setting or to remote settings in the developing world. However, despite substantial progress in the field, there still remain many challenges. Progress in molecular diagnostics has benefitted greatly from microfluidic technology. This chapter aims to summarise the more recent advances in microfluidic-based molecular diagnostics. Sections include an introduction to microfluidic technology, the challenges of molecular diagnostics, how microfluidic advances are working to solve these issues, some alternative design approaches, and detection within these systems.

Recurrent Pneumonia in Children: A Reasoned Diagnostic Approach and a Single Centre Experience.

PubMed

Montella, Silvia; Corcione, Adele; Santamaria, Francesca

2017-01-29

Recurrent pneumonia (RP), i.e., at least two episodes of pneumonia in one year or three episodes ever with intercritical radiographic clearing of densities, occurs in 7.7%-9% of children with community-acquired pneumonia. In RP, the challenge is to discriminate between children with self-limiting or minor problems, that do not require a diagnostic work-up, and those with an underlying disease. The aim of the current review is to discuss a reasoned diagnostic approach to RP in childhood. Particular emphasis has been placed on which children should undergo a diagnostic work-up and which tests should be performed. A pediatric case series is also presented, in order to document a single centre experience of RP. A management algorithm for the approach to children with RP, based on the evidence from a literature review, is proposed. Like all algorithms, it is not meant to replace clinical judgment, but it should drive physicians to adopt a systematic approach to pediatric RP and provide a useful guide to the clinician.

Molecular diagnostics: the changing culture of medical microbiology.

PubMed

Bullman, Susan; Lucey, Brigid; Sleator, Roy D

2012-01-01

Diagnostic molecular biology is arguably the fastest growing area in current laboratory-based medicine. Growth of the so called 'omics' technologies has, over the last decade, led to a gradual migration away from the 'one test, one pathogen' paradigm, toward multiplex approaches to infectious disease diagnosis, which have led to significant improvements in clinical diagnostics and ultimately improved patient care.

A hybrid model for combining case-control and cohort studies in systematic reviews of diagnostic tests

PubMed Central

Chen, Yong; Liu, Yulun; Ning, Jing; Cormier, Janice; Chu, Haitao

2014-01-01

Systematic reviews of diagnostic tests often involve a mixture of case-control and cohort studies. The standard methods for evaluating diagnostic accuracy only focus on sensitivity and specificity and ignore the information on disease prevalence contained in cohort studies. Consequently, such methods cannot provide estimates of measures related to disease prevalence, such as population averaged or overall positive and negative predictive values, which reflect the clinical utility of a diagnostic test. In this paper, we propose a hybrid approach that jointly models the disease prevalence along with the diagnostic test sensitivity and specificity in cohort studies, and the sensitivity and specificity in case-control studies. In order to overcome the potential computational difficulties in the standard full likelihood inference of the proposed hybrid model, we propose an alternative inference procedure based on the composite likelihood. Such composite likelihood based inference does not suffer computational problems and maintains high relative efficiency. In addition, it is more robust to model mis-specifications compared to the standard full likelihood inference. We apply our approach to a review of the performance of contemporary diagnostic imaging modalities for detecting metastases in patients with melanoma. PMID:25897179

TROUBLE 3: A fault diagnostic expert system for Space Station Freedom's power system

NASA Technical Reports Server (NTRS)

Manner, David B.

1990-01-01

Designing Space Station Freedom has given NASA many opportunities to develop expert systems that automate onboard operations of space based systems. One such development, TROUBLE 3, an expert system that was designed to automate the fault diagnostics of Space Station Freedom's electric power system is described. TROUBLE 3's design is complicated by the fact that Space Station Freedom's power system is evolving and changing. TROUBLE 3 has to be made flexible enough to handle changes with minimal changes to the program. Three types of expert systems were studied: rule-based, set-covering, and model-based. A set-covering approach was selected for TROUBLE 3 because if offered the needed flexibility that was missing from the other approaches. With this flexibility, TROUBLE 3 is not limited to Space Station Freedom applications, it can easily be adapted to handle any diagnostic system.

The Buffer Diagnostic Prototype: A fault isolation application using CLIPS

NASA Technical Reports Server (NTRS)

Porter, Ken

1994-01-01

This paper describes problem domain characteristics and development experiences from using CLIPS 6.0 in a proof-of-concept troubleshooting application called the Buffer Diagnostic Prototype. The problem domain is a large digital communications subsystems called the real-time network (RTN), which was designed to upgrade the launch processing system used for shuttle support at KSC. The RTN enables up to 255 computers to share 50,000 data points with millisecond response times. The RTN's extensive built-in test capability but lack of any automatic fault isolation capability presents a unique opportunity for a diagnostic expert system application. The Buffer Diagnostic Prototype addresses RTN diagnosis with a multiple strategy approach. A novel technique called 'faulty causality' employs inexact qualitative models to process test results. Experimental knowledge provides a capability to recognize symptom-fault associations. The implementation utilizes rule-based and procedural programming techniques, including a goal-directed control structure and simple text-based generic user interface that may be reusable for other rapid prototyping applications. Although limited in scope, this project demonstrates a diagnostic approach that may be adapted to troubleshoot a broad range of equipment.

Immune-Response Patterns and Next Generation Sequencing Diagnostics for the Detection of Mycoses in Patients with Septic Shock—Results of a Combined Clinical and Experimental Investigation

PubMed Central

Decker, Sebastian O.; Sigl, Annette; Grumaz, Christian; Stevens, Philip; Vainshtein, Yevhen; Zimmermann, Stefan; Weigand, Markus A.; Hofer, Stefan; Sohn, Kai; Brenner, Thorsten

2017-01-01

Fungi are of increasing importance in sepsis. However, culture-based diagnostic procedures are associated with relevant weaknesses. Therefore, culture- and next-generation sequencing (NGS)-based fungal findings as well as corresponding plasma levels of β-d-glucan, interferon gamma (INF-γ), tumor necrosis factor alpha (TNF-α), interleukin (IL)-2, -4, -6, -10, -17A, and mid-regional proadrenomedullin (MR-proADM) were evaluated in 50 septic patients at six consecutive time points within 28 days after sepsis onset. Furthermore, immune-response patterns during infections with Candida spp. were studied in a reconstituted human epithelium model. In total, 22% (n = 11) of patients suffered from a fungal infection. An NGS-based diagnostic approach appeared to be suitable for the identification of fungal pathogens in patients suffering from fungemia as well as in patients with negative blood cultures. Moreover, MR-proADM and IL-17A in plasma proved suitable for the identification of patients with a fungal infection. Using RNA-seq., adrenomedullin (ADM) was shown to be a target gene which is upregulated early after an epithelial infection with Candida spp. In summary, an NGS-based diagnostic approach was able to close the diagnostic gap of routinely used culture-based diagnostic procedures, which can be further facilitated by plasmatic measurements of MR-proADM and IL-17A. In addition, ADM was identified as an early target gene in response to epithelial infections with Candida spp. PMID:28820494

Faultfinder: A diagnostic expert system with graceful degradation for onboard aircraft applications

NASA Technical Reports Server (NTRS)

Abbott, Kathy H.; Schutte, Paul C.; Palmer, Michael T.; Ricks, Wendell R.

1988-01-01

A research effort was conducted to explore the application of artificial intelligence technology to automation of fault monitoring and diagnosis as an aid to the flight crew. Human diagnostic reasoning was analyzed and actual accident and incident cases were reconstructed. Based on this analysis and reconstruction, diagnostic concepts were conceived and implemented for an aircraft's engine and hydraulic subsystems. These concepts are embedded within a multistage approach to diagnosis that reasons about time-based, causal, and qualitative information, and enables a certain amount of graceful degradation. The diagnostic concepts are implemented in a computer program called Faultfinder that serves as a research prototype.

Leading Antibacterial Laboratory Research by Integrating Conventional and Innovative Approaches: The Laboratory Center of the Antibacterial Resistance Leadership Group.

PubMed

Manca, Claudia; Hill, Carol; Hujer, Andrea M; Patel, Robin; Evans, Scott R; Bonomo, Robert A; Kreiswirth, Barry N

2017-03-15

The Antibacterial Resistance Leadership Group (ARLG) Laboratory Center (LC) leads the evaluation, development, and implementation of laboratory-based research by providing scientific leadership and supporting standard/specialized laboratory services. The LC has developed a physical biorepository and a virtual biorepository. The physical biorepository contains bacterial isolates from ARLG-funded studies located in a centralized laboratory and they are available to ARLG investigators. The Web-based virtual biorepository strain catalogue includes well-characterized gram-positive and gram-negative bacterial strains published by ARLG investigators. The LC, in collaboration with the ARLG Leadership and Operations Center, developed procedures for review and approval of strain requests, guidance during the selection process, and for shipping strains from the distributing laboratories to the requesting investigators. ARLG strains and scientific and/or technical guidance have been provided to basic research laboratories and diagnostic companies for research and development, facilitating collaboration between diagnostic companies and the ARLG Master Protocol for Evaluating Multiple Infection Diagnostics (MASTERMIND) initiative for evaluation of multiple diagnostic devices from a single patient sampling event. In addition, the LC has completed several laboratory-based studies designed to help evaluate new rapid molecular diagnostics by developing, testing, and applying a MASTERMIND approach using purified bacterial strains. In collaboration with the ARLG's Statistical and Data Management Center (SDMC), the LC has developed novel analytical strategies that integrate microbiologic and genetic data for improved and accurate identification of antimicrobial resistance. These novel approaches will aid in the design of future ARLG studies and help correlate pathogenic markers with clinical outcomes. The LC's accomplishments are the result of a successful collaboration with the ARLG's Leadership and Operations Center, Diagnostics and Devices Committee, and SDMC. This interactive approach has been pivotal for the success of LC projects. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

An Integrated Architecture for Aircraft Engine Performance Monitoring and Fault Diagnostics: Engine Test Results

NASA Technical Reports Server (NTRS)

Rinehart, Aidan W.; Simon, Donald L.

2015-01-01

This paper presents a model-based architecture for performance trend monitoring and gas path fault diagnostics designed for analyzing streaming transient aircraft engine measurement data. The technique analyzes residuals between sensed engine outputs and model predicted outputs for fault detection and isolation purposes. Diagnostic results from the application of the approach to test data acquired from an aircraft turbofan engine are presented. The approach is found to avoid false alarms when presented nominal fault-free data. Additionally, the approach is found to successfully detect and isolate gas path seeded-faults under steady-state operating scenarios although some fault misclassifications are noted during engine transients. Recommendations for follow-on maturation and evaluation of the technique are also presented.

An Integrated Architecture for Aircraft Engine Performance Monitoring and Fault Diagnostics: Engine Test Results

NASA Technical Reports Server (NTRS)

Rinehart, Aidan W.; Simon, Donald L.

2014-01-01

This paper presents a model-based architecture for performance trend monitoring and gas path fault diagnostics designed for analyzing streaming transient aircraft engine measurement data. The technique analyzes residuals between sensed engine outputs and model predicted outputs for fault detection and isolation purposes. Diagnostic results from the application of the approach to test data acquired from an aircraft turbofan engine are presented. The approach is found to avoid false alarms when presented nominal fault-free data. Additionally, the approach is found to successfully detect and isolate gas path seeded-faults under steady-state operating scenarios although some fault misclassifications are noted during engine transients. Recommendations for follow-on maturation and evaluation of the technique are also presented.

Venous malformations of the head and neck: a diagnostic approach and a proposed management approach based on clinical, radiological, and histopathology findings.

PubMed

Aboelatta, Yasser Abdallah; Nagy, Eman; Shaker, Mohamed; Massoud, Karim Samir

2014-07-01

There is no easy road map for venous malformations (VMs) of the head and neck according to which treatment modality can be chosen. The purpose of this study was to identify different types of VMs of the head and neck based on clinical, histopathology, MRI, and venography findings that help in specification of different treatment modalities. Sixty-nine patients with VMs of the head and neck were included in this study. Our results proposed a diagnostic approach for VMs of the head and neck. MRI, venography, and clinical examination had important impact in decision-making, whereas histopathology had no impact. A management approach has been suggested for each type and its subtypes. Copyright © 2013 Wiley Periodicals, Inc.

[Quantitative measures for assessing the functional state of the human body during diagnostic procedure].

PubMed

Artemenko, M V

2008-01-01

Two approaches to calculation of the qualitative measures for assessing the functional state level of human body are considered. These approaches are based on image and fuzzy set recognition theories and are used to construct diagnostic decision rules. The first approach uses the data on deviation of detected parameters from those for healthy persons; the second approach analyzes the degree of deviation of detected parameters from the approximants characterizing the correlation differences between the parameters. A method for synthesis of decision rules and the results of blood count-based research for a number of diseases (hemophilia, thrombocytopathy, hypertension, arrhythmia, hepatic cirrhosis, trichophytia) are considered. An effect of a change in the functional link between the cholesterol content in blood and the relative rate of variation of AST and ALT enzymes in blood from direct proportional (healthy state) to inverse proportional (hepatic cirrhosis) is discussed. It is shown that analysis of correlation changes in detected parameters of the human body state during diagnostic process is more effective for application in decision support systems than the state space analysis.

Model-based diagnostics for Space Station Freedom

NASA Technical Reports Server (NTRS)

Fesq, Lorraine M.; Stephan, Amy; Martin, Eric R.; Lerutte, Marcel G.

1991-01-01

An innovative approach to fault management was recently demonstrated for the NASA LeRC Space Station Freedom (SSF) power system testbed. This project capitalized on research in model-based reasoning, which uses knowledge of a system's behavior to monitor its health. The fault management system (FMS) can isolate failures online, or in a post analysis mode, and requires no knowledge of failure symptoms to perform its diagnostics. An in-house tool called MARPLE was used to develop and run the FMS. MARPLE's capabilities are similar to those available from commercial expert system shells, although MARPLE is designed to build model-based as opposed to rule-based systems. These capabilities include functions for capturing behavioral knowledge, a reasoning engine that implements a model-based technique known as constraint suspension, and a tool for quickly generating new user interfaces. The prototype produced by applying MARPLE to SSF not only demonstrated that model-based reasoning is a valuable diagnostic approach, but it also suggested several new applications of MARPLE, including an integration and testing aid, and a complement to state estimation.

International Expert Consensus Document on Takotsubo Syndrome (Part II): Diagnostic Workup, Outcome, and Management.

PubMed

Ghadri, Jelena-Rima; Wittstein, Ilan Shor; Prasad, Abhiram; Sharkey, Scott; Dote, Keigo; Akashi, Yoshihiro John; Cammann, Victoria Lucia; Crea, Filippo; Galiuto, Leonarda; Desmet, Walter; Yoshida, Tetsuro; Manfredini, Roberto; Eitel, Ingo; Kosuge, Masami; Nef, Holger M; Deshmukh, Abhishek; Lerman, Amir; Bossone, Eduardo; Citro, Rodolfo; Ueyama, Takashi; Corrado, Domenico; Kurisu, Satoshi; Ruschitzka, Frank; Winchester, David; Lyon, Alexander R; Omerovic, Elmir; Bax, Jeroen J; Meimoun, Patrick; Tarantini, Guiseppe; Rihal, Charanjit; Y-Hassan, Shams; Migliore, Federico; Horowitz, John D; Shimokawa, Hiroaki; Lüscher, Thomas Felix; Templin, Christian

2018-06-07

The clinical expert consensus statement on takotsubo syndrome (TTS) part II focuses on the diagnostic workup, outcome, and management. The recommendations are based on interpretation of the limited clinical trial data currently available and experience of international TTS experts. It summarizes the diagnostic approach, which may facilitate correct and timely diagnosis. Furthermore, the document covers areas where controversies still exist in risk stratification and management of TTS. Based on available data the document provides recommendations on optimal care of such patients for practising physicians.

International Expert Consensus Document on Takotsubo Syndrome (Part II): Diagnostic Workup, Outcome, and Management

PubMed Central

Ghadri, Jelena-Rima; Wittstein, Ilan Shor; Prasad, Abhiram; Sharkey, Scott; Dote, Keigo; Akashi, Yoshihiro John; Cammann, Victoria Lucia; Crea, Filippo; Galiuto, Leonarda; Desmet, Walter; Yoshida, Tetsuro; Manfredini, Roberto; Eitel, Ingo; Kosuge, Masami; Nef, Holger M; Deshmukh, Abhishek; Lerman, Amir; Bossone, Eduardo; Citro, Rodolfo; Ueyama, Takashi; Corrado, Domenico; Kurisu, Satoshi; Ruschitzka, Frank; Winchester, David; Lyon, Alexander R; Omerovic, Elmir; Bax, Jeroen J; Meimoun, Patrick; Tarantini, Guiseppe; Rihal, Charanjit; Y.-Hassan, Shams; Migliore, Federico; Horowitz, John D; Shimokawa, Hiroaki; Lüscher, Thomas Felix; Templin, Christian

2018-01-01

Abstract The clinical expert consensus statement on takotsubo syndrome (TTS) part II focuses on the diagnostic workup, outcome, and management. The recommendations are based on interpretation of the limited clinical trial data currently available and experience of international TTS experts. It summarizes the diagnostic approach, which may facilitate correct and timely diagnosis. Furthermore, the document covers areas where controversies still exist in risk stratification and management of TTS. Based on available data the document provides recommendations on optimal care of such patients for practising physicians. PMID:29850820

A genetic programming approach for Burkholderia Pseudomallei diagnostic pattern discovery

PubMed Central

Yang, Zheng Rong; Lertmemongkolchai, Ganjana; Tan, Gladys; Felgner, Philip L.; Titball, Richard

2009-01-01

Motivation: Finding diagnostic patterns for fighting diseases like Burkholderia pseudomallei using biomarkers involves two key issues. First, exhausting all subsets of testable biomarkers (antigens in this context) to find a best one is computationally infeasible. Therefore, a proper optimization approach like evolutionary computation should be investigated. Second, a properly selected function of the antigens as the diagnostic pattern which is commonly unknown is a key to the diagnostic accuracy and the diagnostic effectiveness in clinical use. Results: A conversion function is proposed to convert serum tests of antigens on patients to binary values based on which Boolean functions as the diagnostic patterns are developed. A genetic programming approach is designed for optimizing the diagnostic patterns in terms of their accuracy and effectiveness. During optimization, it is aimed to maximize the coverage (the rate of positive response to antigens) in the infected patients and minimize the coverage in the non-infected patients while maintaining the fewest number of testable antigens used in the Boolean functions as possible. The final coverage in the infected patients is 96.55% using 17 of 215 (7.4%) antigens with zero coverage in the non-infected patients. Among these 17 antigens, BPSL2697 is the most frequently selected one for the diagnosis of Burkholderia Pseudomallei. The approach has been evaluated using both the cross-validation and the Jack–knife simulation methods with the prediction accuracy as 93% and 92%, respectively. A novel approach is also proposed in this study to evaluate a model with binary data using ROC analysis. Contact: z.r.yang@ex.ac.uk PMID:19561021

Knowledge-based diagnosis for aerospace systems

NASA Technical Reports Server (NTRS)

Atkinson, David J.

1988-01-01

The need for automated diagnosis in aerospace systems and the approach of using knowledge-based systems are examined. Research issues in knowledge-based diagnosis which are important for aerospace applications are treated along with a review of recent relevant research developments in Artificial Intelligence. The design and operation of some existing knowledge-based diagnosis systems are described. The systems described and compared include the LES expert system for liquid oxygen loading at NASA Kennedy Space Center, the FAITH diagnosis system developed at the Jet Propulsion Laboratory, the PES procedural expert system developed at SRI International, the CSRL approach developed at Ohio State University, the StarPlan system developed by Ford Aerospace, the IDM integrated diagnostic model, and the DRAPhys diagnostic system developed at NASA Langley Research Center.

Comparison of prognostic and diagnostic surface flux modeling approaches over the Nile River Basin

USDA-ARS?s Scientific Manuscript database

Regional evapotranspiration (ET) can be estimated using diagnostic remote sensing models, generally based on principles of energy balance, or with spatially distributed prognostic models that simultaneously balance both the energy and water budgets over landscapes using predictive equations for land...

Validity Arguments for Diagnostic Assessment Using Automated Writing Evaluation

ERIC Educational Resources Information Center

Chapelle, Carol A.; Cotos, Elena; Lee, Jooyoung

2015-01-01

Two examples demonstrate an argument-based approach to validation of diagnostic assessment using automated writing evaluation (AWE). "Criterion"®, was developed by Educational Testing Service to analyze students' papers grammatically, providing sentence-level error feedback. An interpretive argument was developed for its use as part of…

Precision medicine for cancer with next-generation functional diagnostics.

PubMed

Friedman, Adam A; Letai, Anthony; Fisher, David E; Flaherty, Keith T

2015-12-01

Precision medicine is about matching the right drugs to the right patients. Although this approach is technology agnostic, in cancer there is a tendency to make precision medicine synonymous with genomics. However, genome-based cancer therapeutic matching is limited by incomplete biological understanding of the relationship between phenotype and cancer genotype. This limitation can be addressed by functional testing of live patient tumour cells exposed to potential therapies. Recently, several 'next-generation' functional diagnostic technologies have been reported, including novel methods for tumour manipulation, molecularly precise assays of tumour responses and device-based in situ approaches; these address the limitations of the older generation of chemosensitivity tests. The promise of these new technologies suggests a future diagnostic strategy that integrates functional testing with next-generation sequencing and immunoprofiling to precisely match combination therapies to individual cancer patients.

Clinically relevant advances in on-chip affinity-based electrophoresis and electrochromatography.

PubMed

Hou, Chenlu; Herr, Amy E

2008-08-01

Clinical and point-of-care disease diagnostics promise to play an important role in personalized medicine, new approaches to global health, and health monitoring. Emerging instrument platforms based on lab-on-a-chip technology can confer performance advantages successfully exploited in electrophoresis and electrochromatography to affinity-based electrokinetic separations. This review surveys lab-on-a-chip diagnostic developments in affinity-based electrokinetic separations for quantitation of proteins, integration of preparatory functions needed for subsequent analysis of diverse biological samples, and initial forays into multiplexed analyses. The technologies detailed here underpin new clinical and point-of-care diagnostic strategies. The techniques and devices promise to advance translation of until now laboratory-based sample preparation and analytical assays to near-patient settings.

Hybrid Kalman Filter: A New Approach for Aircraft Engine In-Flight Diagnostics

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2006-01-01

In this paper, a uniquely structured Kalman filter is developed for its application to in-flight diagnostics of aircraft gas turbine engines. The Kalman filter is a hybrid of a nonlinear on-board engine model (OBEM) and piecewise linear models. The utilization of the nonlinear OBEM allows the reference health baseline of the in-flight diagnostic system to be updated to the degraded health condition of the engines through a relatively simple process. Through this health baseline update, the effectiveness of the in-flight diagnostic algorithm can be maintained as the health of the engine degrades over time. Another significant aspect of the hybrid Kalman filter methodology is its capability to take advantage of conventional linear and nonlinear Kalman filter approaches. Based on the hybrid Kalman filter, an in-flight fault detection system is developed, and its diagnostic capability is evaluated in a simulation environment. Through the evaluation, the suitability of the hybrid Kalman filter technique for aircraft engine in-flight diagnostics is demonstrated.

Precision diagnostics: moving towards protein biomarker signatures of clinical utility in cancer.

PubMed

Borrebaeck, Carl A K

2017-03-01

Interest in precision diagnostics has been fuelled by the concept that early detection of cancer would benefit patients; that is, if detected early, more tumours should be resectable and treatment more efficacious. Serum contains massive amounts of potentially diagnostic information, and affinity proteomics has risen as an accurate approach to decipher this, to generate actionable information that should result in more precise and evidence-based options to manage cancer. To achieve this, we need to move from single to multiplex biomarkers, a so-called signature, that can provide significantly increased diagnostic accuracy. This Opinion article focuses on the progress being made in identifying protein biomarker signatures of clinical utility, using blood-based proteomics.

A Pilot Study on Modeling of Diagnostic Criteria Using OWL and SWRL.

PubMed

Hong, Na; Jiang, Guoqian; Pathak, Jyotishiman; Chute, Christopher G

2015-01-01

The objective of this study is to describe our efforts in a pilot study on modeling diagnostic criteria using a Semantic Web-based approach. We reused the basic framework of the ICD-11 content model and refined it into an operational model in the Web Ontology Language (OWL). The refinement is based on a bottom-up analysis method, in which we analyzed data elements (including value sets) in a collection (n=20) of randomly selected diagnostic criteria. We also performed a case study to formalize rule logic in the diagnostic criteria of metabolic syndrome using the Semantic Web Rule Language (SWRL). The results demonstrated that it is feasible to use OWL and SWRL to formalize the diagnostic criteria knowledge, and to execute the rules through reasoning.

Array-based disease diagnostics using lipid/polydiacetylene vesicles encapsulated in a sol-gel matrix.

PubMed

Kolusheva, S; Yossef, R; Kugel, A; Katz, M; Volinsky, R; Welt, M; Hadad, U; Drory, V; Kliger, M; Rubin, E; Porgador, A; Jelinek, R

2012-07-17

We demonstrate a novel array-based diagnostic platform comprising lipid/polydiacetylene (PDA) vesicles embedded within a transparent silica-gel matrix. The diagnostic scheme is based upon the unique chromatic properties of PDA, which undergoes blue-red transformations induced by interactions with amphiphilic or membrane-active analytes. We show that constructing a gel matrix array hosting PDA vesicles with different lipid compositions and applying to blood plasma obtained from healthy individuals and from patients suffering from disease, respectively, allow distinguishing among the disease conditions through application of a simple machine-learning algorithm, using the colorimetric response of the lipid/PDA/gel matrix as the input. Importantly, the new colorimetric diagnostic approach does not require a priori knowledge on the exact metabolite compositions of the blood plasma, since the concept relies only on identifying statistically significant changes in overall disease-induced chromatic response. The chromatic lipid/PDA/gel array-based "fingerprinting" concept is generic, easy to apply, and could be implemented for varied diagnostic and screening applications.

The INTELSAT VI SSTDMA network diagnostic system

NASA Astrophysics Data System (ADS)

Tamboli, Satish P.; Zhu, Xiaobo; Wilkins, Kim N.; Gupta, Ramesh K.

The system-level design of an expert-system-based, near-real-time diagnostic system for INTELSAT VI satellite-switched time-division multiple access (SSTDMA) network is described. The challenges of INTELSAT VI diagnostics are discussed, along with alternative approaches for network diagnostics and the rationale for choosing a method based on burst unique-word detection. The focal point of the diagnostic system is the diagnostic processor, which resides in the central control and monitoring facility known as the INTELSAT Operations Center TDMA Facility (IOCTF). As real-time information such as burst unique-word detection data, reference terminal status data, and satellite telemetry alarm data are received at the IOCTF, the diagnostic processor continuously monitors the data streams. When a burst status change is detected, a 'snapshot' of the real-time data is forwarded to the expert system. Receipt of the change causes a set of rules to be invoked which associate the traffic pattern with a set of probable causes. A user-friendly interface allows a graphical view of the burst time plan and provides the ability to browse through the knowledge bases.

Tissue classification and diagnostics using a fiber probe for combined Raman and fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Cicchi, Riccardo; Anand, Suresh; Rossari, Susanna; Sturiale, Alessandro; Giordano, Flavio; De Giorgi, Vincenzo; Maio, Vincenza; Massi, Daniela; Nesi, Gabriella; Buccoliero, Anna Maria; Tonelli, Francesco; Guerrini, Renzo; Pimpinelli, Nicola; Pavone, Francesco S.

2015-03-01

Two different optical fiber probes for combined Raman and fluorescence spectroscopic measurements were designed, developed and used for tissue diagnostics. Two visible laser diodes were used for fluorescence spectroscopy, whereas a laser diode emitting in the NIR was used for Raman spectroscopy. The two probes were based on fiber bundles with a central multimode optical fiber, used for delivering light to the tissue, and 24 surrounding optical fibers for signal collection. Both fluorescence and Raman spectra were acquired using the same detection unit, based on a cooled CCD camera, connected to a spectrograph. The two probes were successfully employed for diagnostic purposes on various tissues in a good agreement with common routine histology. This study included skin, brain and bladder tissues and in particular the classification of: malignant melanoma against melanocytic lesions and healthy skin; urothelial carcinoma against healthy bladder mucosa; brain tumor against dysplastic brain tissue. The diagnostic capabilities were determined using a cross-validation method with a leave-one-out approach, finding very high sensitivity and specificity for all the examined tissues. The obtained results demonstrated that the multimodal approach is crucial for improving diagnostic capabilities. The system presented here can improve diagnostic capabilities on a broad range of tissues and has the potential of being used for endoscopic inspections in the near future.

Tissue classification and diagnostics using a fiber probe for combined Raman and fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Cicchi, Riccardo; Anand, Suresh; Crisci, Alfonso; Giordano, Flavio; Rossari, Susanna; De Giorgi, Vincenzo; Maio, Vincenza; Massi, Daniela; Nesi, Gabriella; Buccoliero, Anna Maria; Guerrini, Renzo; Pimpinelli, Nicola; Pavone, Francesco S.

2015-07-01

Two different optical fiber probes for combined Raman and fluorescence spectroscopic measurements were designed, developed and used for tissue diagnostics. Two visible laser diodes were used for fluorescence spectroscopy, whereas a laser diode emitting in the NIR was used for Raman spectroscopy. The two probes were based on fiber bundles with a central multimode optical fiber, used for delivering light to the tissue, and 24 surrounding optical fibers for signal collection. Both fluorescence and Raman spectra were acquired using the same detection unit, based on a cooled CCD camera, connected to a spectrograph. The two probes were successfully employed for diagnostic purposes on various tissues in a good agreement with common routine histology. This study included skin, brain and bladder tissues and in particular the classification of: malignant melanoma against melanocytic lesions and healthy skin; urothelial carcinoma against healthy bladder mucosa; brain tumor against dysplastic brain tissue. The diagnostic capabilities were determined using a cross-validation method with a leave-one-out approach, finding very high sensitivity and specificity for all the examined tissues. The obtained results demonstrated that the multimodal approach is crucial for improving diagnostic capabilities. The system presented here can improve diagnostic capabilities on a broad range of tissues and has the potential of being used for endoscopic inspections in the near future.

Comparison of Prognostic and Diagnostic Approaches to Modeling Evapotranspiration in the Nile River Basin

NASA Astrophysics Data System (ADS)

Yilmaz, M.; Anderson, M. C.; Zaitchik, B. F.; Crow, W. T.; Hain, C.; Ozdogan, M.; Chun, J. A.

2012-12-01

Actual evapotranspiration (ET) can be estimated using both prognostic and diagnostic modeling approaches, providing independent yet complementary information for hydrologic applications. Both approaches have advantages and disadvantages. When provided with temporally continuous atmospheric forcing data, prognostic models offer continuous sub-daily ET information together with the full set of water and energy balance fluxes and states (i.e. soil moisture, runoff, sensible and latent heat). On the other hand, the diagnostic modeling approach provides ET estimates over regions where reliable information about available soil water is not known (e.g., due to irrigation practices or shallow ground water levels not included in the prognostic model structure, unknown soil texture or plant rooting depth, etc). Prognostic model-based ET estimates are of great interest whenever consistent and complete water budget information is required or when there is a need to project ET for climate or land use change scenarios. Diagnostic models establish a stronger link to remote sensing observations, can be applied in regions with limited or questionable atmospheric forcing data, and provide valuable observation-derived information about the current land-surface state. Analysis of independently obtained ET estimates is particularly important in data poor regions. Such comparisons can help to reduce the uncertainty in the modeled ET estimates and to exclude outliers based on physical considerations. The Nile river basin is home to tens of millions of people whose daily life depends on water extracted from the river Nile. Yet the complete basin scale water balance of the Nile has been studied only a few times, and the temporal and the spatial distribution of hydrological fluxes (particularly ET) are still a subject of active research. This is due in part to a scarcity of ground-based station data for validation. In such regions, comparison between prognostic and diagnostic model output may be a valuable model evaluation tool. Motivated by the complementary information that exists in prognostic and diagnostic energy balance modeling, as well as the need for evaluation of water consumption estimates over the Nile basin, the purpose of this study is to 1) better describe the conceptual differences between prognostic and diagnostic modeling, 2) present the potential for diagnostic models to capture important hydrologic features that are not explicitly represented in prognostic model, 3) explore the differences in these two approaches over the Nile Basin, where ground data are sparse and transnational data sharing is unreliable. More specifically, we will compare output from the Noah prognostic model and the Atmosphere-Land Exchange Inverse (ALEXI) diagnostic model generated over ground truth data-poor Nile basin. Preliminary results indicate spatially, temporally, and magnitude wise consistent flux estimates for ALEXI and NOAH over irrigated Delta region, while there are differences over river-fed wetlands.

Power calculation for comparing diagnostic accuracies in a multi-reader, multi-test design.

PubMed

Kim, Eunhee; Zhang, Zheng; Wang, Youdan; Zeng, Donglin

2014-12-01

Receiver operating characteristic (ROC) analysis is widely used to evaluate the performance of diagnostic tests with continuous or ordinal responses. A popular study design for assessing the accuracy of diagnostic tests involves multiple readers interpreting multiple diagnostic test results, called the multi-reader, multi-test design. Although several different approaches to analyzing data from this design exist, few methods have discussed the sample size and power issues. In this article, we develop a power formula to compare the correlated areas under the ROC curves (AUC) in a multi-reader, multi-test design. We present a nonparametric approach to estimate and compare the correlated AUCs by extending DeLong et al.'s (1988, Biometrics 44, 837-845) approach. A power formula is derived based on the asymptotic distribution of the nonparametric AUCs. Simulation studies are conducted to demonstrate the performance of the proposed power formula and an example is provided to illustrate the proposed procedure. © 2014, The International Biometric Society.

ISHM-oriented adaptive fault diagnostics for avionics based on a distributed intelligent agent system

NASA Astrophysics Data System (ADS)

Xu, Jiuping; Zhong, Zhengqiang; Xu, Lei

2015-10-01

In this paper, an integrated system health management-oriented adaptive fault diagnostics and model for avionics is proposed. With avionics becoming increasingly complicated, precise and comprehensive avionics fault diagnostics has become an extremely complicated task. For the proposed fault diagnostic system, specific approaches, such as the artificial immune system, the intelligent agents system and the Dempster-Shafer evidence theory, are used to conduct deep fault avionics diagnostics. Through this proposed fault diagnostic system, efficient and accurate diagnostics can be achieved. A numerical example is conducted to apply the proposed hybrid diagnostics to a set of radar transmitters on an avionics system and to illustrate that the proposed system and model have the ability to achieve efficient and accurate fault diagnostics. By analyzing the diagnostic system's feasibility and pragmatics, the advantages of this system are demonstrated.

DNA-mounted self-assembly: new approaches for genomic analysis and SNP detection.

PubMed

Bichenkova, Elena V; Lang, Zhaolei; Yu, Xuan; Rogert, Candelaria; Douglas, Kenneth T

2011-01-01

This article presents an overview of new emerging approaches for nucleic acid detection via hybridization techniques that can potentially be applied to genomic analysis and SNP identification in clinical diagnostics. Despite the availability of a diverse variety of SNP genotyping technologies on the diagnostic market, none has truly succeeded in dominating its competitors thus far. Having been designed for specific diagnostic purposes or clinical applications, each of the existing bio-assay systems (briefly outlined here) is usually limited to a relatively narrow aspect or format of nucleic acid detection, and thus cannot entirely satisfy all the varieties of commercial requirements and clinical demands. This drives the diagnostic sector to pursue novel, cost-effective approaches to ensure rapid and reliable identification of pathogenic or hereditary human diseases. Hence, the purpose of this review is to highlight some new strategic directions in DNA detection technologies in order to inspire development of novel molecular diagnostic tools and bio-assay systems with superior reliability, reproducibility, robustness, accuracy and sensitivity at lower assay cost. One approach to improving the sensitivity of an assay to confidently discriminate between single point mutations is based on the use of target assembled, split-probe systems, which constitutes the main focus of this review. Copyright © 2010 Elsevier B.V. All rights reserved.

A Model-Based Expert System for Space Power Distribution Diagnostics

NASA Technical Reports Server (NTRS)

Quinn, Todd M.; Schlegelmilch, Richard F.

1994-01-01

When engineers diagnose system failures, they often use models to confirm system operation. This concept has produced a class of advanced expert systems that perform model-based diagnosis. A model-based diagnostic expert system for the Space Station Freedom electrical power distribution test bed is currently being developed at the NASA Lewis Research Center. The objective of this expert system is to autonomously detect and isolate electrical fault conditions. Marple, a software package developed at TRW, provides a model-based environment utilizing constraint suspension. Originally, constraint suspension techniques were developed for digital systems. However, Marple provides the mechanisms for applying this approach to analog systems such as the test bed, as well. The expert system was developed using Marple and Lucid Common Lisp running on a Sun Sparc-2 workstation. The Marple modeling environment has proved to be a useful tool for investigating the various aspects of model-based diagnostics. This report describes work completed to date and lessons learned while employing model-based diagnostics using constraint suspension within an analog system.

Clinical applications of MS-based protein quantification.

PubMed

Sabbagh, Bassel; Mindt, Sonani; Neumaier, Michael; Findeisen, Peter

2016-04-01

Mass spectrometry-based assays are increasingly important in clinical laboratory medicine and nowadays are already commonly used in several areas of routine diagnostics. These include therapeutic drug monitoring, toxicology, endocrinology, pediatrics, and microbiology. Accordingly, some of the most common analyses are therapeutic drug monitoring of immunosuppressants, vitamin D, steroids, newborn screening, and bacterial identification. However, MS-based quantification of peptides and proteins for routine diagnostic use is rather rare up to now despite excellent analytical specificity and good sensitivity. Here, we want to give an overview over current fit-for-purpose assays for MS-based protein quantification. Advantages as well as challenges of this approach will be discussed with focus on feasibility for routine diagnostic use. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Haemolytic uremic syndrome and thrombotic thrombocytopenic purpura: classification based on molecular etiology and review of recent developments in diagnostics].

PubMed

Prohászka, Zoltán

2008-07-06

Haemolytic uremic syndrome and thrombotic thrombocytopenic purpura are overlapping clinical entities based on historical classification. Recent developments in the unfolding of the pathomechanisms of these diseases resulted in the creation of a molecular etiology-based classification. Understanding of some causative relationships yielded detailed diagnostic approaches, novel therapeutic options and thorough prognostic assortment of the patients. Although haemolytic uremic syndrome and thrombotic thrombocytopenic purpura are rare diseases with poor prognosis, the precise molecular etiology-based diagnosis might properly direct the therapy of the affected patients. The current review focuses on the theoretical background and detailed description of the available diagnostic possibilities, and some practical information necessary for the interpretation of their results.

Development of immune-diagnostic reagents to diagnose bovine tuberculosis in cattle.

PubMed

Vordermeier, H Martin; Jones, Gareth J; Buddle, Bryce M; Hewinson, R Glyn

2016-11-15

Bovine tuberculosis remains a major economic and animal welfare concern worldwide. As part of control strategies, cattle vaccination is being considered. This approach, used alongside conventional control policies, also requires the development of vaccine compatible diagnostic assays to distinguish infected from vaccinated animals (DIVA). In this review we discuss recent advances in DIVA development based on the detection of host cellular immune responses by blood testing or skin testing approaches. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

An SSME High Pressure Oxidizer Turbopump diagnostic system using G2 real-time expert system

NASA Technical Reports Server (NTRS)

Guo, Ten-Huei

1991-01-01

An expert system which diagnoses various seal leakage faults in the High Pressure Oxidizer Turbopump of the SSME was developed using G2 real-time expert system. Three major functions of the software were implemented: model-based data generation, real-time expert system reasoning, and real-time input/output communication. This system is proposed as one module of a complete diagnostic system for the SSME. Diagnosis of a fault is defined as the determination of its type, severity, and likelihood. Since fault diagnosis is often accomplished through the use of heuristic human knowledge, an expert system based approach has been adopted as a paradigm to develop this diagnostic system. To implement this approach, a software shell which can be easily programmed to emulate the human decision process, the G2 Real-Time Expert System, was selected. Lessons learned from this implementation are discussed.

An SSME high pressure oxidizer turbopump diagnostic system using G2(TM) real-time expert system

NASA Technical Reports Server (NTRS)

Guo, Ten-Huei

1991-01-01

An expert system which diagnoses various seal leakage faults in the High Pressure Oxidizer Turbopump of the SSME was developed using G2(TM) real-time expert system. Three major functions of the software were implemented: model-based data generation, real-time expert system reasoning, and real-time input/output communication. This system is proposed as one module of a complete diagnostic system for Space Shuttle Main Engine. Diagnosis of a fault is defined as the determination of its type, severity, and likelihood. Since fault diagnosis is often accomplished through the use of heuristic human knowledge, an expert system based approach was adopted as a paradigm to develop this diagnostic system. To implement this approach, a software shell which can be easily programmed to emulate the human decision process, the G2 Real-Time Expert System, was selected. Lessons learned from this implementation are discussed.

LAMP detection assays for boxwood blight pathogens: A comparative genomics approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Malapi-Wight, Martha; Demers, Jill E.; Veltri, Daniel

Rapid and accurate molecular diagnostic tools are critical to efforts to minimize the impact and spread of emergent pathogens. The identification of diagnostic markers for novel pathogens presents several challenges, especially in the absence of information about population diversity and where genetic resources are limited. The objective of this study was to use comparative genomics datasets to find unique target regions suitable for the diagnosis of two fungal species causing a newly emergent blight disease of boxwood. Candidate marker regions for loop-mediated isothermal amplification (LAMP) assays were identified from draft genomes of Calonectria henricotiae and C. pseudonaviculata, as well asmore » three related species not associated with this disease. To increase the probability of identifying unique targets, we used three approaches to mine genome datasets, based on (i) unique regions, (ii) polymorphisms, and (iii) presence/absence of regions across datasets. From a pool of candidate markers, we demonstrate LAMP assay specificity by testing related fungal species, common boxwood pathogens, and environmental samples containing 445 diverse fungal taxa. In conclusion, this comparative-genomics-based approach to the development of LAMP diagnostic assays is the first of its kind for fungi and could be easily applied to diagnostic marker development for other newly emergent plant pathogens.« less

New Approaches to Sepsis: Molecular Diagnostics and Biomarkers

PubMed Central

Bauer, Michael; Riedemann, Niels C.; Hartog, Christiane S.

2012-01-01

Summary: Sepsis is among the most common causes of death in hospitals. It arises from the host response to infection. Currently, diagnosis relies on nonspecific physiological criteria and culture-based pathogen detection. This results in diagnostic uncertainty, therapeutic delays, the mis- and overuse of antibiotics, and the failure to identify patients who might benefit from immunomodulatory therapies. There is a need for new sepsis biomarkers that can aid in therapeutic decision making and add information about screening, diagnosis, risk stratification, and monitoring of the response to therapy. The host response involves hundreds of mediators and single molecules, many of which have been proposed as biomarkers. It is, however, unlikely that one single biomarker is able to satisfy all the needs and expectations for sepsis research and management. Among biomarkers that are measurable by assays approved for clinical use, procalcitonin (PCT) has shown some usefulness as an infection marker and for antibiotic stewardship. Other possible new approaches consist of molecular strategies to improve pathogen detection and molecular diagnostics and prognostics based on transcriptomic, proteomic, or metabolic profiling. Novel approaches to sepsis promise to transform sepsis from a physiologic syndrome into a group of distinct biochemical disorders and help in the development of better diagnostic tools and effective adjunctive sepsis therapies. PMID:23034322

LAMP detection assays for boxwood blight pathogens: A comparative genomics approach

DOE PAGES

Malapi-Wight, Martha; Demers, Jill E.; Veltri, Daniel; ...

2016-05-20

Rapid and accurate molecular diagnostic tools are critical to efforts to minimize the impact and spread of emergent pathogens. The identification of diagnostic markers for novel pathogens presents several challenges, especially in the absence of information about population diversity and where genetic resources are limited. The objective of this study was to use comparative genomics datasets to find unique target regions suitable for the diagnosis of two fungal species causing a newly emergent blight disease of boxwood. Candidate marker regions for loop-mediated isothermal amplification (LAMP) assays were identified from draft genomes of Calonectria henricotiae and C. pseudonaviculata, as well asmore » three related species not associated with this disease. To increase the probability of identifying unique targets, we used three approaches to mine genome datasets, based on (i) unique regions, (ii) polymorphisms, and (iii) presence/absence of regions across datasets. From a pool of candidate markers, we demonstrate LAMP assay specificity by testing related fungal species, common boxwood pathogens, and environmental samples containing 445 diverse fungal taxa. In conclusion, this comparative-genomics-based approach to the development of LAMP diagnostic assays is the first of its kind for fungi and could be easily applied to diagnostic marker development for other newly emergent plant pathogens.« less

Transrenal DNA-based diagnosis of Strongyloides stercoralis (Grassi, 1879) infection: Bayesian latent class modeling of test accuracy.

PubMed

Krolewiecki, Alejandro J; Koukounari, Artemis; Romano, Miryam; Caro, Reynaldo N; Scott, Alan L; Fleitas, Pedro; Cimino, Ruben; Shiff, Clive J

2018-06-01

For epidemiological work with soil transmitted helminths the recommended diagnostic approaches are to examine fecal samples for microscopic evidence of the parasite. In addition to several logistical and processing issues, traditional diagnostic approaches have been shown to lack the sensitivity required to reliably identify patients harboring low-level infections such as those associated with effective mass drug intervention programs. In this context, there is a need to rethink the approaches used for helminth diagnostics. Serological methods are now in use, however these tests are indirect and depend on individual immune responses, exposure patterns and the nature of the antigen. However, it has been demonstrated that cell-free DNA from pathogens and cancers can be readily detected in patient's urine which can be collected in the field, filtered in situ and processed later for analysis. In the work presented here, we employ three diagnostic procedures-stool examination, serology (NIE-ELISA) and PCR-based amplification of parasite transrenal DNA from urine-to determine their relative utility in the diagnosis of S. stercoralis infections from 359 field samples from an endemic area of Argentina. Bayesian Latent Class analysis was used to assess the relative performance of the three diagnostic procedures. The results underscore the low sensitivity of stool examination and support the idea that the use of serology combined with parasite transrenal DNA detection may be a useful strategy for sensitive and specific detection of low-level strongyloidiasis.

An Overview of Prognosis Health Management Research at Glenn Research Center for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Goldberg, Robert K.; Lerch, Bradley A.; Saleeb, Atef F.

2009-01-01

Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include (1) diagnostic/detection methodology, (2) prognosis/lifing methodology, (3) diagnostic/prognosis linkage, (4) experimental validation, and (5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multimechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.

An Overview of Prognosis Health Management Research at GRC for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Goldberg, Robert K.; Lerch, Bradley A.; Saleeb, Atef F.

2009-01-01

Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include 1) diagnostic/detection methodology, 2) prognosis/lifing methodology, 3) diagnostic/prognosis linkage, 4) experimental validation and 5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multi-mechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.

The ACTTION-American Pain Society Pain Taxonomy (AAPT): an evidence-based and multidimensional approach to classifying chronic pain conditions.

PubMed

Fillingim, Roger B; Bruehl, Stephen; Dworkin, Robert H; Dworkin, Samuel F; Loeser, John D; Turk, Dennis C; Widerstrom-Noga, Eva; Arnold, Lesley; Bennett, Robert; Edwards, Robert R; Freeman, Roy; Gewandter, Jennifer; Hertz, Sharon; Hochberg, Marc; Krane, Elliot; Mantyh, Patrick W; Markman, John; Neogi, Tuhina; Ohrbach, Richard; Paice, Judith A; Porreca, Frank; Rappaport, Bob A; Smith, Shannon M; Smith, Thomas J; Sullivan, Mark D; Verne, G Nicholas; Wasan, Ajay D; Wesselmann, Ursula

2014-03-01

Current approaches to classification of chronic pain conditions suffer from the absence of a systematically implemented and evidence-based taxonomy. Moreover, existing diagnostic approaches typically fail to incorporate available knowledge regarding the biopsychosocial mechanisms contributing to pain conditions. To address these gaps, the Analgesic, Anesthetic, and Addiction Clinical Trial Translations Innovations Opportunities and Networks (ACTTION) public-private partnership with the U.S. Food and Drug Administration and the American Pain Society (APS) have joined together to develop an evidence-based chronic pain classification system called the ACTTION-APS Pain Taxonomy. This paper describes the outcome of an ACTTION-APS consensus meeting, at which experts agreed on a structure for this new taxonomy of chronic pain conditions. Several major issues around which discussion revolved are presented and summarized, and the structure of the taxonomy is presented. ACTTION-APS Pain Taxonomy will include the following dimensions: 1) core diagnostic criteria; 2) common features; 3) common medical comorbidities; 4) neurobiological, psychosocial, and functional consequences; and 5) putative neurobiological and psychosocial mechanisms, risk factors, and protective factors. In coming months, expert working groups will apply this taxonomy to clusters of chronic pain conditions, thereby developing a set of diagnostic criteria that have been consistently and systematically implemented across nearly all common chronic pain conditions. It is anticipated that the availability of this evidence-based and mechanistic approach to pain classification will be of substantial benefit to chronic pain research and treatment. The ACTTION-APS Pain Taxonomy is an evidence-based chronic pain classification system designed to classify chronic pain along the following dimensions: 1) core diagnostic criteria; 2) common features; 3) common medical comorbidities; 4) neurobiological, psychosocial, and functional consequences; and 5) putative neurobiological and psychosocial mechanisms, risk factors, and protective factors. Copyright © 2014 American Pain Society. Published by Elsevier Inc. All rights reserved.

Current and future molecular diagnostics for ocular infectious diseases.

PubMed

Doan, Thuy; Pinsky, Benjamin A

2016-11-01

Confirmation of ocular infections can pose great challenges to the clinician. A fundamental limitation is the small amounts of specimen that can be obtained from the eye. Molecular diagnostics can circumvent this limitation and have been shown to be more sensitive than conventional culture. The purpose of this review is to describe new molecular methods and to discuss the applications of next-generation sequencing-based approaches in the diagnosis of ocular infections. Efforts have focused on improving the sensitivity of pathogen detection using molecular methods. This review describes a new molecular target for Toxoplasma gondii-directed polymerase chain reaction assays. Molecular diagnostics for Chlamydia trachomatis and Acanthamoeba species are also discussed. Finally, we describe a hypothesis-free approach, metagenomic deep sequencing, which can detect DNA and RNA pathogens from a single specimen in one test. In some cases, this method can provide the geographic location and timing of the infection. Pathogen-directed PCRs have been powerful tools in the diagnosis of ocular infections for over 20 years. The use of next-generation sequencing-based approaches, when available, will further improve sensitivity of detection with the potential to improve patient care.

American Pancreatic Association Practice Guidelines in Chronic Pancreatitis: evidence-based report on diagnostic guidelines.

PubMed

Conwell, Darwin L; Lee, Linda S; Yadav, Dhiraj; Longnecker, Daniel S; Miller, Frank H; Mortele, Koenraad J; Levy, Michael J; Kwon, Richard; Lieb, John G; Stevens, Tyler; Toskes, Phillip P; Gardner, Timothy B; Gelrud, Andres; Wu, Bechien U; Forsmark, Christopher E; Vege, Santhi S

2014-11-01

The diagnosis of chronic pancreatitis remains challenging in early stages of the disease. This report defines the diagnostic criteria useful in the assessment of patients with suspected and established chronic pancreatitis. All current diagnostic procedures are reviewed, and evidence-based statements are provided about their utility and limitations. Diagnostic criteria for chronic pancreatitis are classified as definitive, probable, or insufficient evidence. A diagnostic (STEP-wise; survey, tomography, endoscopy, and pancreas function testing) algorithm is proposed that proceeds from a noninvasive to a more invasive approach. This algorithm maximizes specificity (low false-positive rate) in subjects with chronic abdominal pain and equivocal imaging changes. Furthermore, a nomenclature is suggested to further characterize patients with established chronic pancreatitis based on TIGAR-O (toxic, idiopathic, genetic, autoimmune, recurrent, and obstructive) etiology, gland morphology (Cambridge criteria), and physiologic state (exocrine, endocrine function) for uniformity across future multicenter research collaborations. This guideline will serve as a baseline manuscript that will be modified as new evidence becomes available and our knowledge of chronic pancreatitis improves.

Size-based molecular diagnostics using plasma DNA for noninvasive prenatal testing.

PubMed

Yu, Stephanie C Y; Chan, K C Allen; Zheng, Yama W L; Jiang, Peiyong; Liao, Gary J W; Sun, Hao; Akolekar, Ranjit; Leung, Tak Y; Go, Attie T J I; van Vugt, John M G; Minekawa, Ryoko; Oudejans, Cees B M; Nicolaides, Kypros H; Chiu, Rossa W K; Lo, Y M Dennis

2014-06-10

Noninvasive prenatal testing using fetal DNA in maternal plasma is an actively researched area. The current generation of tests using massively parallel sequencing is based on counting plasma DNA sequences originating from different genomic regions. In this study, we explored a different approach that is based on the use of DNA fragment size as a diagnostic parameter. This approach is dependent on the fact that circulating fetal DNA molecules are generally shorter than the corresponding maternal DNA molecules. First, we performed plasma DNA size analysis using paired-end massively parallel sequencing and microchip-based capillary electrophoresis. We demonstrated that the fetal DNA fraction in maternal plasma could be deduced from the overall size distribution of maternal plasma DNA. The fetal DNA fraction is a critical parameter affecting the accuracy of noninvasive prenatal testing using maternal plasma DNA. Second, we showed that fetal chromosomal aneuploidy could be detected by observing an aberrant proportion of short fragments from an aneuploid chromosome in the paired-end sequencing data. Using this approach, we detected fetal trisomy 21 and trisomy 18 with 100% sensitivity (T21: 36/36; T18: 27/27) and 100% specificity (non-T21: 88/88; non-T18: 97/97). For trisomy 13, the sensitivity and specificity were 95.2% (20/21) and 99% (102/103), respectively. For monosomy X, the sensitivity and specificity were both 100% (10/10 and 8/8). Thus, this study establishes the principle of size-based molecular diagnostics using plasma DNA. This approach has potential applications beyond noninvasive prenatal testing to areas such as oncology and transplantation monitoring.

Size-based molecular diagnostics using plasma DNA for noninvasive prenatal testing

PubMed Central

Yu, Stephanie C. Y.; Chan, K. C. Allen; Zheng, Yama W. L.; Jiang, Peiyong; Liao, Gary J. W.; Sun, Hao; Akolekar, Ranjit; Leung, Tak Y.; Go, Attie T. J. I.; van Vugt, John M. G.; Minekawa, Ryoko; Oudejans, Cees B. M.; Nicolaides, Kypros H.; Chiu, Rossa W. K.; Lo, Y. M. Dennis

2014-01-01

Noninvasive prenatal testing using fetal DNA in maternal plasma is an actively researched area. The current generation of tests using massively parallel sequencing is based on counting plasma DNA sequences originating from different genomic regions. In this study, we explored a different approach that is based on the use of DNA fragment size as a diagnostic parameter. This approach is dependent on the fact that circulating fetal DNA molecules are generally shorter than the corresponding maternal DNA molecules. First, we performed plasma DNA size analysis using paired-end massively parallel sequencing and microchip-based capillary electrophoresis. We demonstrated that the fetal DNA fraction in maternal plasma could be deduced from the overall size distribution of maternal plasma DNA. The fetal DNA fraction is a critical parameter affecting the accuracy of noninvasive prenatal testing using maternal plasma DNA. Second, we showed that fetal chromosomal aneuploidy could be detected by observing an aberrant proportion of short fragments from an aneuploid chromosome in the paired-end sequencing data. Using this approach, we detected fetal trisomy 21 and trisomy 18 with 100% sensitivity (T21: 36/36; T18: 27/27) and 100% specificity (non-T21: 88/88; non-T18: 97/97). For trisomy 13, the sensitivity and specificity were 95.2% (20/21) and 99% (102/103), respectively. For monosomy X, the sensitivity and specificity were both 100% (10/10 and 8/8). Thus, this study establishes the principle of size-based molecular diagnostics using plasma DNA. This approach has potential applications beyond noninvasive prenatal testing to areas such as oncology and transplantation monitoring. PMID:24843150

Economic analysis of empiric versus diagnostic-driven strategies for immunocompromised patients with suspected fungal infections in the People's Republic of China.

PubMed

Mao, Ningying; Lesher, Beth; Liu, Qifa; Qin, Lei; Chen, Yixi; Gao, Xin; Earnshaw, Stephanie R; McDade, Cheryl L; Charbonneau, Claudie

2016-01-01

Invasive fungal infections (IFIs) require rapid diagnosis and treatment. A decision-analytic model was used to estimate total costs and survival associated with a diagnostic-driven (DD) or an empiric treatment approach in neutropenic patients with hematological malignancies receiving chemotherapy or autologous/allogeneic stem cell transplants in Shanghai, Beijing, Chengdu, and Guangzhou, the People's Republic of China. Treatment initiation for the empiric approach occurred after clinical suspicion of an IFI; treatment initiation for the DD approach occurred after clinical suspicion and a positive IFI diagnostic test result. Model inputs were obtained from the literature; treatment patterns and resource use were based on clinical opinion. Total costs were lower for the DD versus the empiric approach in Shanghai (¥3,232 vs ¥4,331), Beijing (¥3,894 vs ¥4,864), Chengdu, (¥4,632 vs ¥5,795), and Guangzhou (¥8,489 vs ¥9,795). Antifungal administration was lower using the DD (5.7%) than empiric (9.8%) approach, with similar survival rates. Results from one-way and probabilistic sensitivity analyses were most sensitive to changes in diagnostic test sensitivity and IFI incidence; the DD approach dominated the empiric approach in 88% of scenarios. These results suggest that a DD compared to an empiric treatment approach in the People's Republic of China may be cost saving, with similar overall survival in immunocompromised patients with suspected IFIs.

Electron Scale Turbulence and Transport in an NSTX H-mode Plasma Using a Synthetic Diagnostic for High-k Scattering Measurements

NASA Astrophysics Data System (ADS)

Ruiz Ruiz, Juan; Guttenfelder, Walter; Loureiro, Nuno; Ren, Yang; White, Anne; MIT/PPPL Collaboration

2017-10-01

Turbulent fluctuations on the electron gyro-radius length scale are thought to cause anomalous transport of electron energy in spherical tokamaks such as NSTX and MAST in some parametric regimes. In NSTX, electron-scale turbulence is studied through a combination of experimental measurements from a high-k scattering system and gyrokinetic simulations. Until now most comparisons between experiment and simulation of electron scale turbulence have been qualitative, with recent work expanding to more quantitative comparisons via synthetic diagnostic development. In this new work, we propose two alternate, complementary ways to perform a synthetic diagnostic using the gyrokinetic code GYRO. The first approach builds on previous work and is based on the traditional selection of wavenumbers using a wavenumber filter, for which a new wavenumber mapping was implemented for general axisymmetric geometry. A second alternate approach selects wavenumbers in real-space to compute the power spectra. These approaches are complementary, and recent results from both synthetic diagnostic approaches applied to NSTX plasmas will be presented. Work supported by U.S. DOE contracts DE-AC02-09CH11466 and DE-AC02-05CH11231.

Combining computer adaptive testing technology with cognitively diagnostic assessment.

PubMed

McGlohen, Meghan; Chang, Hua-Hua

2008-08-01

A major advantage of computerized adaptive testing (CAT) is that it allows the test to home in on an examinee's ability level in an interactive manner. The aim of the new area of cognitive diagnosis is to provide information about specific content areas in which an examinee needs help. The goal of this study was to combine the benefit of specific feedback from cognitively diagnostic assessment with the advantages of CAT. In this study, three approaches to combining these were investigated: (1) item selection based on the traditional ability level estimate (theta), (2) item selection based on the attribute mastery feedback provided by cognitively diagnostic assessment (alpha), and (3) item selection based on both the traditional ability level estimate (theta) and the attribute mastery feedback provided by cognitively diagnostic assessment (alpha). The results from these three approaches were compared for theta estimation accuracy, attribute mastery estimation accuracy, and item exposure control. The theta- and alpha-based condition outperformed the alpha-based condition regarding theta estimation, attribute mastery pattern estimation, and item exposure control. Both the theta-based condition and the theta- and alpha-based condition performed similarly with regard to theta estimation, attribute mastery estimation, and item exposure control, but the theta- and alpha-based condition has an additional advantage in that it uses the shadow test method, which allows the administrator to incorporate additional constraints in the item selection process, such as content balancing, item type constraints, and so forth, and also to select items on the basis of both the current theta and alpha estimates, which can be built on top of existing 3PL testing programs.

[SCAN system--semi-structured interview based on diagnostic criteria].

PubMed

Adamowski, Tomasz; Kiejna, Andrzej; Hadryś, Tomasz

2006-01-01

This paper presents the main features of contemporary diagnostic systems which are implemented into the SCAN--modern and semi-structured diagnostic interview. The concepts of further development of the classifications, rationale for operationalized diagnostic criteria and for the divisional approach to mental diagnoses will be in focus. The structure and components of SCAN ver. 2.1 (WHO), i.e. Present State Examination--10th edition, Item Group Checklist, Clinical History Schedule, Glossary of Definitions and computer software with the diagnostic algorithm: I-Shell, as well as rules for a reliable use of diagnostic rating scales, will be discussed within the scope of this paper. The materials and training sets necessary for the learning of proper use of the SCAN, especially training sets for SCAN Training Centers and the Reference Manual--a form of guidebook for SCAN shall be introduced. Finally the paper will present evidence that SCAN is an instrument feasible in different cultural settings. Reliability and validity data of SCAN will also be dealt with indicating that SCAN could be widely used in research studies as well as in everyday clinical practice facilitating more detailed diagnostic approach to a patient.

Noninvasive express diagnostics of pulmonary diseases based on control of patient's gas emission using methods of IR and terahertz laser spectroscopy

NASA Astrophysics Data System (ADS)

Starikova, M. K.; Bulanova, A. A.; Bukreeva, E. B.; Karapuzikov, A. A.; Karapuzikov, A. I.; Kistenev, Y. V.; Klementyev, V. M.; Kolker, D. B.; Kuzmin, D. A.; Nikiforova, O. Y.; Ponomarev, Yu. N.; Sherstov, I. V.; Boyko, A. A.

2013-11-01

Pulmonary diseases diagnostics always occupies one of the key positions in medicine practices. A large variety of high technology methods are used today, but none of them cannot be used for early screening of pulmonary diseases. We discuss abilities of methods of IR and terahertz laser spectroscopy for noninvasive express diagnostics of pulmonary diseases on a base of analysis of absorption spectra of patient's gas emission, in particular, exhaled air. Experience in the field of approaches to experimental data analysis and hard-ware realization of gas analyzers for medical applications is also discussed.

Automated Dermoscopy Image Analysis of Pigmented Skin Lesions

PubMed Central

Baldi, Alfonso; Quartulli, Marco; Murace, Raffaele; Dragonetti, Emanuele; Manganaro, Mario; Guerra, Oscar; Bizzi, Stefano

2010-01-01

Dermoscopy (dermatoscopy, epiluminescence microscopy) is a non-invasive diagnostic technique for the in vivo observation of pigmented skin lesions (PSLs), allowing a better visualization of surface and subsurface structures (from the epidermis to the papillary dermis). This diagnostic tool permits the recognition of morphologic structures not visible by the naked eye, thus opening a new dimension in the analysis of the clinical morphologic features of PSLs. In order to reduce the learning-curve of non-expert clinicians and to mitigate problems inherent in the reliability and reproducibility of the diagnostic criteria used in pattern analysis, several indicative methods based on diagnostic algorithms have been introduced in the last few years. Recently, numerous systems designed to provide computer-aided analysis of digital images obtained by dermoscopy have been reported in the literature. The goal of this article is to review these systems, focusing on the most recent approaches based on content-based image retrieval systems (CBIR). PMID:24281070

Diagnostic value of tendon thickness and structure in the sonographic diagnosis of supraspinatus tendinopathy: room for a two-step approach.

PubMed

Arend, Carlos Frederico; Arend, Ana Amalia; da Silva, Tiago Rodrigues

2014-06-01

The aim of our study was to systematically compare different methodologies to establish an evidence-based approach based on tendon thickness and structure for sonographic diagnosis of supraspinatus tendinopathy when compared to MRI. US was obtained from 164 symptomatic patients with supraspinatus tendinopathy detected at MRI and 42 asymptomatic controls with normal MRI. Diagnostic yield was calculated for either maximal supraspinatus tendon thickness (MSTT) and tendon structure as isolated criteria and using different combinations of parallel and sequential testing at US. Chi-squared tests were performed to assess sensitivity, specificity, and accuracy of different diagnostic approaches. Mean MSTT was 6.68 mm in symptomatic patients and 5.61 mm in asymptomatic controls (P<.05). When used as an isolated criterion, MSTT>6.0mm provided best results for accuracy (93.7%) when compared to other measurements of tendon thickness. Also as an isolated criterion, abnormal tendon structure (ATS) yielded 93.2% accuracy for diagnosis. The best overall yield was obtained by both parallel and sequential testing using either MSTT>6.0mm or ATS as diagnostic criteria at no particular order, which provided 99.0% accuracy, 100% sensitivity, and 95.2% specificity. Among these parallel and sequential tests that provided best overall yield, additional analysis revealed that sequential testing first evaluating tendon structure required assessment of 258 criteria (vs. 261 for sequential testing first evaluating tendon thickness and 412 for parallel testing) and demanded a mean of 16.1s to assess diagnostic criteria and reach the diagnosis (vs. 43.3s for sequential testing first evaluating tendon thickness and 47.4s for parallel testing). We found that using either MSTT>6.0mm or ATS as diagnostic criteria for both parallel and sequential testing provides the best overall yield for sonographic diagnosis of supraspinatus tendinopathy when compared to MRI. Among these strategies, a two-step sequential approach first assessing tendon structure was advantageous because it required a lower number of criteria to be assessed and demanded less time to assess diagnostic criteria and reach the diagnosis. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A Needs-Based Approach to the Development of a Diagnostic College English Speaking Test

ERIC Educational Resources Information Center

Zhao, Zhongbao

2014-01-01

This paper investigated the current situation of oral English teaching, learning, and assessment at the tertiary level in China through needs analysis and explored the implications for the development of a diagnostic speaking test. Through random sampling, the researcher administered both a student questionnaire and a teacher questionnaire to over…

Interrelation of Evaluation and Self-Evaluation in the Diagnostic Procedures to Assess Teachers' Readiness for Innovation

ERIC Educational Resources Information Center

Tyunnikov, Yurii S.

2016-01-01

The paper solves the problem of the relationship of external diagnosis and self-diagnosis of readiness of teachers to innovative activity. It highlights major disadvantages of measurement tools that are used to this process. The author demonstrates an alternative approach to harmonizing the diagnosis, based on a modular diagnostic model, general…

Diagnostic Accuracy of Multivariate Universal Screening Procedures for Reading in Upper Elementary Grades

ERIC Educational Resources Information Center

Klingbeil, David A.; Nelson, Peter M.; Van Norman, Ethan R.; Birr, Chris

2017-01-01

We examined the diagnostic accuracy and efficiency of three approaches to universal screening for reading difficulties using retrospective data from 1,307 students in Grades 3 through 5. School staff collected screening data using the Measures of Academic Progress (MAP), a curriculum-based measure (CBM), and running records (RR). The criterion…

Developing Prospective Teachers' Diagnostic Skills through Collaborative Video Analysis: Focus on L2 Reading

ERIC Educational Resources Information Center

Finkbeiner, Claudia; Schluer, Jennifer

2017-01-01

This paper contains a collaborative video-based approach to foster prospective teachers' diagnostic skills with respect to pupils' L2 reading processes. Together with a peer, the prospective teachers watched, systematically selected, analysed and commented on clips from a comprehensive video corpus on L2 reading strategies. In order to assist the…

Profiles of Receptive and Expressive Language Abilities in Boys with Comorbid Fragile X Syndrome and Autism

ERIC Educational Resources Information Center

McDuffie, Andrea; Kover, Sara; Abbeduto, Leonard; Lewis, Pamela; Brown, Ted

2012-01-01

The authors examined receptive and expressive language profiles for a group of verbal male children and adolescents who had fragile X syndrome along with varying degrees of autism symptoms. A categorical approach for assigning autism diagnostic classification, based on the combined use of the Autism Diagnostic Interview--Revised and the Autism…

Digital diffraction analysis enables low-cost molecular diagnostics on a smartphone

PubMed Central

Im, Hyungsoon; Castro, Cesar M.; Shao, Huilin; Liong, Monty; Song, Jun; Pathania, Divya; Fexon, Lioubov; Min, Changwook; Avila-Wallace, Maria; Zurkiya, Omar; Rho, Junsung; Magaoay, Brady; Tambouret, Rosemary H.; Pivovarov, Misha; Weissleder, Ralph; Lee, Hakho

2015-01-01

The widespread distribution of smartphones, with their integrated sensors and communication capabilities, makes them an ideal platform for point-of-care (POC) diagnosis, especially in resource-limited settings. Molecular diagnostics, however, have been difficult to implement in smartphones. We herein report a diffraction-based approach that enables molecular and cellular diagnostics. The D3 (digital diffraction diagnosis) system uses microbeads to generate unique diffraction patterns which can be acquired by smartphones and processed by a remote server. We applied the D3 platform to screen for precancerous or cancerous cells in cervical specimens and to detect human papillomavirus (HPV) DNA. The D3 assay generated readouts within 45 min and showed excellent agreement with gold-standard pathology or HPV testing, respectively. This approach could have favorable global health applications where medical access is limited or when pathology bottlenecks challenge prompt diagnostic readouts. PMID:25870273

Digital diffraction analysis enables low-cost molecular diagnostics on a smartphone.

PubMed

Im, Hyungsoon; Castro, Cesar M; Shao, Huilin; Liong, Monty; Song, Jun; Pathania, Divya; Fexon, Lioubov; Min, Changwook; Avila-Wallace, Maria; Zurkiya, Omar; Rho, Junsung; Magaoay, Brady; Tambouret, Rosemary H; Pivovarov, Misha; Weissleder, Ralph; Lee, Hakho

2015-05-05

The widespread distribution of smartphones, with their integrated sensors and communication capabilities, makes them an ideal platform for point-of-care (POC) diagnosis, especially in resource-limited settings. Molecular diagnostics, however, have been difficult to implement in smartphones. We herein report a diffraction-based approach that enables molecular and cellular diagnostics. The D3 (digital diffraction diagnosis) system uses microbeads to generate unique diffraction patterns which can be acquired by smartphones and processed by a remote server. We applied the D3 platform to screen for precancerous or cancerous cells in cervical specimens and to detect human papillomavirus (HPV) DNA. The D3 assay generated readouts within 45 min and showed excellent agreement with gold-standard pathology or HPV testing, respectively. This approach could have favorable global health applications where medical access is limited or when pathology bottlenecks challenge prompt diagnostic readouts.

Exosomal microRNA Biomarkers: Emerging Frontiers in Colorectal and Other Human Cancers

PubMed Central

Goel, Ajay; Tovar-Camargo, Oscar A; Toden, Shusuke

2016-01-01

Diagnostic strategies, particularly non-invasive blood-based screening approaches, are gaining increased attention for the early detection and attenuation of mortality associated with colorectal cancer (CRC). However, the majority of current screening approaches are inadequate at replacing the conventional CRC diagnostic procedures. Yet, due to technological advances and a better understanding of molecular events underlying human cancer, a new category of biomarkers are on the horizon. Recent evidence indicates that cells release a distinct class of small vesicles called ‘exosomes’, which contain nucleic acids and proteins that reflect and typify host-cell molecular architecture. Intriguingly, exosomes released from cancer cells have a distinct genetic and epigenetic makeup, which allows them to undertake their tumorigenic function. From a clinical standpoint, these unique cancer-specific fingerprints present in exosomes appear to be detectable in a small amount of blood, making them very attractive substrates for developing cancer biomarkers, particularly noninvasive diagnostic approaches. PMID:26892862

Non-invasive optical detection of esophagus cancer based on urine surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Huang, Shaohua; Wang, Lan; Chen, Weiwei; Lin, Duo; Huang, Lingling; Wu, Shanshan; Feng, Shangyuan; Chen, Rong

2014-09-01

A surface-enhanced Raman spectroscopy (SERS) approach was utilized for urine biochemical analysis with the aim to develop a label-free and non-invasive optical diagnostic method for esophagus cancer detection. SERS spectrums were acquired from 31 normal urine samples and 47 malignant esophagus cancer (EC) urine samples. Tentative assignments of urine SERS bands demonstrated esophagus cancer specific changes, including an increase in the relative amounts of urea and a decrease in the percentage of uric acid in the urine of normal compared with EC. The empirical algorithm integrated with linear discriminant analysis (LDA) were employed to identify some important urine SERS bands for differentiation between healthy subjects and EC urine. The empirical diagnostic approach based on the ratio of the SERS peak intensity at 527 to 1002 cm-1 and 725 to 1002 cm-1 coupled with LDA yielded a diagnostic sensitivity of 72.3% and specificity of 96.8%, respectively. The area under the receive operating characteristic (ROC) curve was 0.954, which further evaluate the performance of the diagnostic algorithm based on the ratio of the SERS peak intensity combined with LDA analysis. This work demonstrated that the urine SERS spectra associated with empirical algorithm has potential for noninvasive diagnosis of esophagus cancer.

A Multimodal Approach in Dealing with Chronic Epstein-Barr Viral Syndrome.

ERIC Educational Resources Information Center

Weikel, William J.

1989-01-01

Discusses Epstein-Barr Viral Syndrome, a puzzling and controversial disease with a variety of symptoms that frequently include depression and emotional debilitation. Offers diagnostic signs and suggests a possible treatment strategy based on the multimodal approach. (Author/ABL)

A methodological approach based on gold-nanoparticles followed by matrix assisted laser desorption ionization time of flight mass spectrometry for the analysis of urine profiling of knee osteoarthritis.

PubMed

López-Cortés, Rubén; Formigo, Jacobo; Reboiro-Jato, Miguel; Fdez-Riverola, Florentino; Blanco, Francisco J; Lodeiro, Carlos; Oliveira, Elisabete; Capelo, J L; Santos, H M

2016-04-01

The aim of this work is to develop a nanoparticle-based methodology to find out biomarkers of diagnostic for knee osteoarthritis, KOA, through the use of matrix assisted laser desorption ionization time-of-flight-based mass spectrometry profiling. Urine samples used for this study were obtained from KOA patients (42 patients), patients with prosthesis (58 patients), and controls (36 individuals) with no history of joint disease. Gold-nano particle MALDI-based urine profiling was optimized and then applied over the 136 individuals. Jaccard index and 10 different classifiers over MALDI MS datasets were used to find out potential biomarkers. Then, the specificity and sensitivity of the method were evaluated. The presence of ten m/z signals as potential biomarkers in the healthy versus non-healthy approach suggests that patients (KOA and prosthesis) are differentiable from the healthy volunteers through profiling. The automatic diagnostic study confirmed these preliminary conclusions. The sensitivity and the specificity for the urine profiling criteria here reported, achieved by the C4.5 classifier, is 97% and 69% respectively. Thus, it is confirmed the utility of the method proposed in this work as an additional fast, non-expensive and robust test for KOA diagnostic. When the proposed method is compared with those used in common practice it is found that sensitivity is the highest, thus with a low false negative rate for diagnostic KOA patients in the population studied. Specificity is lower but in the range accepted for diagnostic objectives. Copyright © 2016. Published by Elsevier B.V.

A hierarchical fuzzy rule-based approach to aphasia diagnosis.

PubMed

Akbarzadeh-T, Mohammad-R; Moshtagh-Khorasani, Majid

2007-10-01

Aphasia diagnosis is a particularly challenging medical diagnostic task due to the linguistic uncertainty and vagueness, inconsistencies in the definition of aphasic syndromes, large number of measurements with imprecision, natural diversity and subjectivity in test objects as well as in opinions of experts who diagnose the disease. To efficiently address this diagnostic process, a hierarchical fuzzy rule-based structure is proposed here that considers the effect of different features of aphasia by statistical analysis in its construction. This approach can be efficient for diagnosis of aphasia and possibly other medical diagnostic applications due to its fuzzy and hierarchical reasoning construction. Initially, the symptoms of the disease which each consists of different features are analyzed statistically. The measured statistical parameters from the training set are then used to define membership functions and the fuzzy rules. The resulting two-layered fuzzy rule-based system is then compared with a back propagating feed-forward neural network for diagnosis of four Aphasia types: Anomic, Broca, Global and Wernicke. In order to reduce the number of required inputs, the technique is applied and compared on both comprehensive and spontaneous speech tests. Statistical t-test analysis confirms that the proposed approach uses fewer Aphasia features while also presenting a significant improvement in terms of accuracy.

Livingstone Model-Based Diagnosis of Earth Observing One Infusion Experiment

NASA Technical Reports Server (NTRS)

Hayden, Sandra C.; Sweet, Adam J.; Christa, Scott E.

2004-01-01

The Earth Observing One satellite, launched in November 2000, is an active earth science observation platform. This paper reports on the progress of an infusion experiment in which the Livingstone 2 Model-Based Diagnostic engine is deployed on Earth Observing One, demonstrating the capability to monitor the nominal operation of the spacecraft under command of an on-board planner, and demonstrating on-board diagnosis of spacecraft failures. Design and development of the experiment, specification and validation of diagnostic scenarios, characterization of performance results and benefits of the model- based approach are presented.

A defect-driven diagnostic method for machine tool spindles

PubMed Central

Vogl, Gregory W.; Donmez, M. Alkan

2016-01-01

Simple vibration-based metrics are, in many cases, insufficient to diagnose machine tool spindle condition. These metrics couple defect-based motion with spindle dynamics; diagnostics should be defect-driven. A new method and spindle condition estimation device (SCED) were developed to acquire data and to separate system dynamics from defect geometry. Based on this method, a spindle condition metric relying only on defect geometry is proposed. Application of the SCED on various milling and turning spindles shows that the new approach is robust for diagnosing the machine tool spindle condition. PMID:28065985

Modeling companion diagnostics in economic evaluations of targeted oncology therapies: systematic review and methodological checklist.

PubMed

Doble, Brett; Tan, Marcus; Harris, Anthony; Lorgelly, Paula

2015-02-01

The successful use of a targeted therapy is intrinsically linked to the ability of a companion diagnostic to correctly identify patients most likely to benefit from treatment. The aim of this study was to review the characteristics of companion diagnostics that are of importance for inclusion in an economic evaluation. Approaches for including these characteristics in model-based economic evaluations are compared with the intent to describe best practice methods. Five databases and government agency websites were searched to identify model-based economic evaluations comparing a companion diagnostic and subsequent treatment strategy to another alternative treatment strategy with model parameters for the sensitivity and specificity of the companion diagnostic (primary synthesis). Economic evaluations that limited model parameters for the companion diagnostic to only its cost were also identified (secondary synthesis). Quality was assessed using the Quality of Health Economic Studies instrument. 30 studies were included in the review (primary synthesis n = 12; secondary synthesis n = 18). Incremental cost-effectiveness ratios may be lower when the only parameter for the companion diagnostic included in a model is the cost of testing. Incorporating the test's accuracy in addition to its cost may be a more appropriate methodological approach. Altering the prevalence of the genetic biomarker, specific population tested, type of test, test accuracy and timing/sequence of multiple tests can all impact overall model results. The impact of altering a test's threshold for positivity is unknown as it was not addressed in any of the included studies. Additional quality criteria as outlined in our methodological checklist should be considered due to the shortcomings of standard quality assessment tools in differentiating studies that incorporate important test-related characteristics and those that do not. There is a need to refine methods for incorporating the characteristics of companion diagnostics into model-based economic evaluations to ensure consistent and transparent reimbursement decisions are made.

Propulsion Diagnostic Method Evaluation Strategy (ProDiMES) User's Guide

NASA Technical Reports Server (NTRS)

Simon, Donald L.

2010-01-01

This report is a User's Guide for the Propulsion Diagnostic Method Evaluation Strategy (ProDiMES). ProDiMES is a standard benchmarking problem and a set of evaluation metrics to enable the comparison of candidate aircraft engine gas path diagnostic methods. This Matlab (The Mathworks, Inc.) based software tool enables users to independently develop and evaluate diagnostic methods. Additionally, a set of blind test case data is also distributed as part of the software. This will enable the side-by-side comparison of diagnostic approaches developed by multiple users. The Users Guide describes the various components of ProDiMES, and provides instructions for the installation and operation of the tool.

Pulmonary infections in critical/intensive care - rapid diagnosis and optimizing antimicrobial usage.

PubMed

Douglas, Ivor S

2017-05-01

Diagnosis of pulmonary infection, including hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP) in the critically ill patient remains a common and therapeutically challenging diagnosis with significant attributable morbidity, mortality, and cost. Current clinical approaches to surveillance, early detection and, conventional culture-based microbiology are inadequate for optimal targeted antibiotic treatment and stewardship. Efforts to enhance diagnosis of HAP and VAP and the impact of these novel approaches on rational antimicrobial selection and stewardship are the focus of recent studies reviewed here. Recent consensus guidelines for diagnosis and management of HAP and VAP are relatively silent on the potential role of novel rapid microbiological techniques and reply heavily on conventional culture strategies of noninvasively obtained (including endotracheal aspirate samples). Novel rapid microbiological diagnostics, including nucleic acid amplification, mass spectrometry, and fluorescence microscopy-based technologies are promising approaches for the future. Exhaled breath biomarkers, including measurement of VOC represent a future approach. Further validation of novel diagnostic technology platforms will be required to evaluate their utility for enhancing diagnosis and guiding treatment of pulmonary infections in the critically ill. However, the integration of novel diagnostics for rapid microbial identification, resistance phenotyping, and antibiotic sensitivity testing into usual care practice could significantly transform the care of patients and potentially inform improved targeted antimicrobial selection, de-escalation, and stewardship.

Neuroscience and Values: A Case Study Illustrating Developments in Policy, Training and Research in the UK and Internationally**

PubMed Central

Fulford, K. W. M

2011-01-01

In the current climate of dramatic advances in the neurosciences, it has been widely assumed that the diagnosis of mental disorder is a matter exclusively for value-free science. Starting from a detailed case history, this paper describes how, to the contrary, values come into the diagnosis of mental disorders, directly through the criteria at the heart of psychiatry’s most scientifically grounded classification, the American Psychiatric Association’s DSM (Diagnostic and Statistical Manual). Various possible interpretations of the prominence of values in psychiatric diagnosis are outlined. Drawing on work in the Oxford analytic tradition of philosophy, it is shown that, properly understood, the prominence of psychiatric diagnostic values reflects the necessary engagement of psychiatry with the diversity of individual human values. This interpretation opens up psychiatric diagnostic assessment to the resources of a new skills-based approach to working with complex and conflicting values (also derived from analytic philosophy) called ‘values-based practice.’ Developments in values-based practice in training, policy and research in mental health are briefly outlined. The paper concludes with an indication of how the integration of values-based with evidence-based approaches provides the basis for psychiatric practice in the twenty-first century that is both science-based and person-centred. PMID:21694963

Systems Biology and Mode of Action Based Risk Assessment.

EPA Science Inventory

The application of systems biology approaches has greatly increased in the past decade largely as a consequence of the human genome project and technological advances in genomics and proteomics. Systems approaches have been used in the medical & pharmaceutical realm for diagnost...

Effect of Watermarking on Diagnostic Preservation of Atherosclerotic Ultrasound Video in Stroke Telemedicine.

PubMed

Dey, Nilanjan; Bose, Soumyo; Das, Achintya; Chaudhuri, Sheli Sinha; Saba, Luca; Shafique, Shoaib; Nicolaides, Andrew; Suri, Jasjit S

2016-04-01

Embedding of diagnostic and health care information requires secure encryption and watermarking. This research paper presents a comprehensive study for the behavior of some well established watermarking algorithms in frequency domain for the preservation of stroke-based diagnostic parameters. Two different sets of watermarking algorithms namely: two correlation-based (binary logo hiding) and two singular value decomposition (SVD)-based (gray logo hiding) watermarking algorithms are used for embedding ownership logo. The diagnostic parameters in atherosclerotic plaque ultrasound video are namely: (a) bulb identification and recognition which consists of identifying the bulb edge points in far and near carotid walls; (b) carotid bulb diameter; and (c) carotid lumen thickness all along the carotid artery. The tested data set consists of carotid atherosclerotic movies taken under IRB protocol from University of Indiana Hospital, USA-AtheroPoint™ (Roseville, CA, USA) joint pilot study. ROC (receiver operating characteristic) analysis was performed on the bulb detection process that showed an accuracy and sensitivity of 100 % each, respectively. The diagnostic preservation (DPsystem) for SVD-based approach was above 99 % with PSNR (Peak signal-to-noise ratio) above 41, ensuring the retention of diagnostic parameter devalorization as an effect of watermarking. Thus, the fully automated proposed system proved to be an efficient method for watermarking the atherosclerotic ultrasound video for stroke application.

A Design Research Study of a Curriculum and Diagnostic Assessment System for a Learning Trajectory on Equipartitioning

ERIC Educational Resources Information Center

Confrey, Jere; Maloney, Alan

2015-01-01

Design research studies provide significant opportunities to study new innovations and approaches and how they affect the forms of learning in complex classroom ecologies. This paper reports on a two-week long design research study with twelve 2nd through 4th graders using curricular materials and a tablet-based diagnostic assessment system, both…

A rational regulatory approach for positron emission tomography imaging probes: from "first in man" to NDA approval and reimbursement.

PubMed

Barrio, Jorge R; Marcus, Carol S; Hung, Joseph C; Keppler, Jennifer S

2004-01-01

We propose a new regulatory approach for positron emission tomography (PET) molecular imaging probes, essential tools in today's medicine. Even though the focus of this paper is on positron-emitting labeled probes, it is also justified to extend this proposed regulatory approach to other diagnostic nuclear medicine radiopharmaceuticals. Key aspects of this proposal include: (1) PET molecular imaging probes would be placed in a "no significant risk" category, similar to that category for devices in current Food and Drug Administration (FDA) regulations, based on overwhelming scientific evidence that demonstrates their faultless safety profile; (2) the FDA-sanctioned Radioactive Drug Research Committee (RDRC) will oversee all diagnostic research with these probes. The newly defined RDRC should approve "first in man" use; supervise a broader spectrum of diagnostic research protocols, including those looking to demonstrate initial efficacy, as well as multicenter clinical trials and the use of molecular imaging probes as a screening tool in drug discovery. The current investigational new drug (IND) mechanism is thus eliminated for these diagnostic probes; (3) when a molecular imaging probe has demonstrated diagnostic efficacy, FDA approval (i.e., NDA) will be sought. The review will be done by a newly constituted Radioactive Drug Advisory Committee (RDAC) composed of experts chosen by the professional societies, who would provide a binding assessment of the adequacy of the safety and efficacy data. When the RDAC recommends its diagnostic use on scientific and medical grounds, the molecular imaging probe becomes FDA approved. After a molecular imaging probe is approved for a diagnostic indication, the existing mechanism to seek reimbursement will be utilized; and (4) the FDA would retain its direct oversight function for traditional manufacturers engaged in commercial distribution of the approved diagnostic molecular imaging probes (i.e., under NDA) to monitor compliance with existing US Pharmacopeia (USP) requirements. With abbreviated and more appropriate regulations, new PET molecular imaging probes for diagnostic use would be then rapidly incorporated into the mainstream diagnostic medicine. Equally importantly, this approach would facilitate the use of molecular imaging in drug discovery and development, which would substantially reduce the costs and time required to bring new therapeutic drugs to market.

The clinical inadequacy of the DSM-5 classification of somatic symptom and related disorders: an alternative trans-diagnostic model.

PubMed

Cosci, Fiammetta; Fava, Giovanni A

2016-08-01

The Diagnostic and Statistical of Mental Disorders, Fifth Edition (DSM-5) somatic symptom and related disorders chapter has a limited clinical utility. In addition to the problems that the single diagnostic rubrics and the deletion of the diagnosis of hypochondriasis entail, there are 2 major ambiguities: (1) the use of the term "somatic symptoms" reflects an ill-defined concept of somatization and (2) abnormal illness behavior is included in all diagnostic rubrics, but it is never conceptually defined. In the present review of the literature, we will attempt to approach the clinical issue from a different angle, by introducing the trans-diagnostic viewpoint of illness behavior and propose an alternative clinimetric classification system, based on the Diagnostic Criteria for Psychosomatic Research.

Array-based sensing using nanoparticles: an alternative approach for cancer diagnostics.

PubMed

Le, Ngoc D B; Yazdani, Mahdieh; Rotello, Vincent M

2014-07-01

Array-based sensing using nanoparticles (NPs) provides an attractive alternative to specific biomarker-focused strategies for cancer diagnosis. The physical and chemical properties of NPs provide both the recognition and transduction capabilities required for biosensing. Array-based sensors utilize a combined response from the interactions between sensors and analytes to generate a distinct pattern (fingerprint) for each analyte. These interactions can be the result of either the combination of multiple specific biomarker recognition (specific binding) or multiple selective binding responses, known as chemical nose sensing. The versatility of the latter array-based sensing using NPs can facilitate the development of new personalized diagnostic methodologies in cancer diagnostics, a necessary evolution in the current healthcare system to better provide personalized treatments. This review will describe the basic principle of array-based sensors, along with providing examples of both invasive and noninvasive samples used in cancer diagnosis.

Untangling nociceptive, neuropathic and neuroplastic mechanisms underlying the biological domain of back pain.

PubMed

Hush, Julia M; Stanton, Tasha R; Siddall, Philip; Marcuzzi, Anna; Attal, Nadine

2013-05-01

SUMMARY Current clinical practice guidelines advocate a model of diagnostic triage for back pain, underpinned by the biopsychosocial paradigm. However, limitations of this clinical model have become apparent: it can be difficult to classify patients into the diagnostic triage categories; patients with 'nonspecific back pain' are clearly not a homogenous group; and mean effects of treatments based on this approach are small. In this article, it is proposed that the biological domain of the biopsychosocial model needs to be reconceptualized using a neurobiological mechanism-based approach. Recent evidence about nociceptive and neuropathic contributors to back pain is outlined in the context of maladaptive neuroplastic changes of the somatosensory system. Implications for clinical practice and research are discussed.

Electromagnetic Nanoparticles for Sensing and Medical Diagnostic Applications

PubMed Central

Vegni, Lucio

2018-01-01

A modeling and design approach is proposed for nanoparticle-based electromagnetic devices. First, the structure properties were analytically studied using Maxwell’s equations. The method provides us a robust link between nanoparticles electromagnetic response (amplitude and phase) and their geometrical characteristics (shape, geometry, and dimensions). Secondly, new designs based on “metamaterial” concept are proposed, demonstrating great performances in terms of wide-angle range functionality and multi/wide behavior, compared to conventional devices working at the same frequencies. The approach offers potential applications to build-up new advanced platforms for sensing and medical diagnostics. Therefore, in the final part of the article, some practical examples are reported such as cancer detection, water content measurements, chemical analysis, glucose concentration measurements and blood diseases monitoring. PMID:29652853

Continuous stacking computational approach based automated microscope slide scanner

NASA Astrophysics Data System (ADS)

Murali, Swetha; Adhikari, Jayesh Vasudeva; Jagannadh, Veerendra Kalyan; Gorthi, Sai Siva

2018-02-01

Cost-effective and automated acquisition of whole slide images is a bottleneck for wide-scale deployment of digital pathology. In this article, a computation augmented approach for the development of an automated microscope slide scanner is presented. The realization of a prototype device built using inexpensive off-the-shelf optical components and motors is detailed. The applicability of the developed prototype to clinical diagnostic testing is demonstrated by generating good quality digital images of malaria-infected blood smears. Further, the acquired slide images have been processed to identify and count the number of malaria-infected red blood cells and thereby perform quantitative parasitemia level estimation. The presented prototype would enable cost-effective deployment of slide-based cyto-diagnostic testing in endemic areas.

Fetal alcohol spectrum disorder: Canadian guidelines for diagnosis

PubMed Central

Chudley, Albert E.; Conry, Julianne; Cook, Jocelynn L.; Loock, Christine; Rosales, Ted; LeBlanc, Nicole

2005-01-01

THE DIAGNOSIS OF FETAL ALCOHOL SPECTRUM DISORDER (FASD) is complex and guidelines are warranted. A subcommittee of the Public Health Agency of Canada's National Advisory Committee on Fetal Alcohol Spectrum Disorder reviewed, analysed and integrated current approaches to diagnosis to reach agreement on a standard in Canada. The purpose of this paper is to review and clarify the use of current diagnostic systems and make recommendations on their application for diagnosis of FASD-related disabilities in people of all ages. The guidelines are based on widespread consultation of expert practitioners and partners in the field. The guidelines have been organized into 7 categories: screening and referral; the physical examination and differential diagnosis; the neurobehavioural assessment; and treatment and follow-up; maternal alcohol history in pregnancy; diagnostic criteria for fetal alcohol syndrome (FAS), partial FAS and alcohol-related neurodevelopmental disorder; and harmonization of Institute of Medicine and 4-Digit Diagnostic Code approaches. The diagnosis requires a comprehensive history and physical and neurobehavioural assessments; a multidisciplinary approach is necessary. These are the first Canadian guidelines for the diagnosis of FAS and its related disabilities, developed by broad-based consultation among experts in diagnosis. PMID:15738468

Nano-carriers for targeted delivery and biomedical imaging enhancement.

PubMed

Parekh, Gaurav; Shi, Yuanyuan; Zheng, Juanjuan; Zhang, Xingcai; Leporatti, Stefano

2018-05-01

Theranostic approaches using nanotechnology have been a hot research area for the past decade. All nano drug delivery techniques and architectures have some limitations, as do diagnostic nano-approaches. Thus, combining nano drug delivery strategies with diagnostic techniques using nanoparticles for improving imaging modalities has been the key to fill up those gaps. In the past decade, lots of approaches have been made with different combinations of biomaterials fabricated/synthesized to nanostructures with modified surface functionalization to improve their overall theranostic properties. This article summarizes recent research works based on the biomaterials used for fabricating these nanostructures. Their combinations with other biomaterials have been demonstrated with their overall advantages and limitations.

American Pancreatic Association Practice Guidelines in Chronic Pancreatitis: Evidence-Based Report on Diagnostic Guidelines

PubMed Central

Conwell, Darwin L.; Lee, Linda S.; Yadav, Dhiraj; Longnecker, Daniel S.; Miller, Frank H.; Mortele, Koenraad J.; Levy, Michael J.; Kwon, Richard; Lieb, John G.; Stevens, Tyler; Toskes, Philip P.; Gardner, Timothy B.; Gelrud, Andres; Wu, Bechien U.; Forsmark, Christopher E.; Vege, Santhi S.

2016-01-01

The diagnosis of chronic pancreatitis remains challenging in early stages of the disease. This report defines the diagnostic criteria useful in the assessment of patients with suspected and established chronic pancreatitis. All current diagnostic procedures are reviewed and evidence based statements are provided about their utility and limitations. Diagnostic criteria for chronic pancreatitis are classified as definitive, probable or insufficient evidence. A diagnostic (STEP-wise; S-survey, T-tomography, E-endoscopy and P-pancreas function testing) algorithm is proposed that proceeds from a non-invasive to a more invasive approach. This algorithm maximizes specificity (low false positive rate) in subjects with chronic abdominal pain and equivocal imaging changes. Futhermore, a nomenclature is suggested to further characterize patients with established chronic pancreatitis based on TIGAR-O (T-toxic, I-idiopathic, G-genetic, A- autoimmune, R-recurrent and O-obstructive) etiology, gland morphology (Cambridge criteria) and physiologic state (exocrine, endocrine function) for uniformity across future multi-center research collaborations. This guideline will serve as a baseline manuscript that will be modified as new evidence becomes available and our knowledge of chronic pancreatitis improves. PMID:25333398

AFM feature definition for neural cells on nanofibrillar tissue scaffolds.

PubMed

Tiryaki, Volkan M; Khan, Adeel A; Ayres, Virginia M

2012-01-01

A diagnostic approach is developed and implemented that provides clear feature definition in atomic force microscopy (AFM) images of neural cells on nanofibrillar tissue scaffolds. Because the cellular edges and processes are on the same order as the background nanofibers, this imaging situation presents a feature definition problem. The diagnostic approach is based on analysis of discrete Fourier transforms of standard AFM section measurements. The diagnostic conclusion that the combination of dynamic range enhancement with low-frequency component suppression enhances feature definition is shown to be correct and to lead to clear-featured images that could change previously held assumptions about the cell-cell interactions present. Clear feature definition of cells on scaffolds extends the usefulness of AFM imaging for use in regenerative medicine. © Wiley Periodicals, Inc.

Primary progressive aphasia: a clinical approach.

PubMed

Marshall, Charles R; Hardy, Chris J D; Volkmer, Anna; Russell, Lucy L; Bond, Rebecca L; Fletcher, Phillip D; Clark, Camilla N; Mummery, Catherine J; Schott, Jonathan M; Rossor, Martin N; Fox, Nick C; Crutch, Sebastian J; Rohrer, Jonathan D; Warren, Jason D

2018-06-01

The primary progressive aphasias are a heterogeneous group of focal 'language-led' dementias that pose substantial challenges for diagnosis and management. Here we present a clinical approach to the progressive aphasias, based on our experience of these disorders and directed at non-specialists. We first outline a framework for assessing language, tailored to the common presentations of progressive aphasia. We then consider the defining features of the canonical progressive nonfluent, semantic and logopenic aphasic syndromes, including 'clinical pearls' that we have found diagnostically useful and neuroanatomical and other key associations of each syndrome. We review potential diagnostic pitfalls and problematic presentations not well captured by conventional classifications and propose a diagnostic 'roadmap'. After outlining principles of management, we conclude with a prospect for future progress in these diseases, emphasising generic information processing deficits and novel pathophysiological biomarkers.

A One-Versus-All Class Binarization Strategy for Bearing Diagnostics of Concurrent Defects

PubMed Central

Ng, Selina S. Y.; Tse, Peter W.; Tsui, Kwok L.

2014-01-01

In bearing diagnostics using a data-driven modeling approach, a concern is the need for data from all possible scenarios to build a practical model for all operating conditions. This paper is a study on bearing diagnostics with the concurrent occurrence of multiple defect types. The authors are not aware of any work in the literature that studies this practical problem. A strategy based on one-versus-all (OVA) class binarization is proposed to improve fault diagnostics accuracy while reducing the number of scenarios for data collection, by predicting concurrent defects from training data of normal and single defects. The proposed OVA diagnostic approach is evaluated with empirical analysis using support vector machine (SVM) and C4.5 decision tree, two popular classification algorithms frequently applied to system health diagnostics and prognostics. Statistical features are extracted from the time domain and the frequency domain. Prediction performance of the proposed strategy is compared with that of a simple multi-class classification, as well as that of random guess and worst-case classification. We have verified the potential of the proposed OVA diagnostic strategy in performance improvements for single-defect diagnosis and predictions of BPFO plus BPFI concurrent defects using two laboratory-collected vibration data sets. PMID:24419162

A one-versus-all class binarization strategy for bearing diagnostics of concurrent defects.

PubMed

Ng, Selina S Y; Tse, Peter W; Tsui, Kwok L

2014-01-13

In bearing diagnostics using a data-driven modeling approach, a concern is the need for data from all possible scenarios to build a practical model for all operating conditions. This paper is a study on bearing diagnostics with the concurrent occurrence of multiple defect types. The authors are not aware of any work in the literature that studies this practical problem. A strategy based on one-versus-all (OVA) class binarization is proposed to improve fault diagnostics accuracy while reducing the number of scenarios for data collection, by predicting concurrent defects from training data of normal and single defects. The proposed OVA diagnostic approach is evaluated with empirical analysis using support vector machine (SVM) and C4.5 decision tree, two popular classification algorithms frequently applied to system health diagnostics and prognostics. Statistical features are extracted from the time domain and the frequency domain. Prediction performance of the proposed strategy is compared with that of a simple multi-class classification, as well as that of random guess and worst-case classification. We have verified the potential of the proposed OVA diagnostic strategy in performance improvements for single-defect diagnosis and predictions of BPFO plus BPFI concurrent defects using two laboratory-collected vibration data sets.

Real-time diagnostics for a reusable rocket engine

NASA Technical Reports Server (NTRS)

Guo, T. H.; Merrill, W.; Duyar, A.

1992-01-01

A hierarchical, decentralized diagnostic system is proposed for the Real-Time Diagnostic System component of the Intelligent Control System (ICS) for reusable rocket engines. The proposed diagnostic system has three layers of information processing: condition monitoring, fault mode detection, and expert system diagnostics. The condition monitoring layer is the first level of signal processing. Here, important features of the sensor data are extracted. These processed data are then used by the higher level fault mode detection layer to do preliminary diagnosis on potential faults at the component level. Because of the closely coupled nature of the rocket engine propulsion system components, it is expected that a given engine condition may trigger more than one fault mode detector. Expert knowledge is needed to resolve the conflicting reports from the various failure mode detectors. This is the function of the diagnostic expert layer. Here, the heuristic nature of this decision process makes it desirable to use an expert system approach. Implementation of the real-time diagnostic system described above requires a wide spectrum of information processing capability. Generally, in the condition monitoring layer, fast data processing is often needed for feature extraction and signal conditioning. This is usually followed by some detection logic to determine the selected faults on the component level. Three different techniques are used to attack different fault detection problems in the NASA LeRC ICS testbed simulation. The first technique employed is the neural network application for real-time sensor validation which includes failure detection, isolation, and accommodation. The second approach demonstrated is the model-based fault diagnosis system using on-line parameter identification. Besides these model based diagnostic schemes, there are still many failure modes which need to be diagnosed by the heuristic expert knowledge. The heuristic expert knowledge is implemented using a real-time expert system tool called G2 by Gensym Corp. Finally, the distributed diagnostic system requires another level of intelligence to oversee the fault mode reports generated by component fault detectors. The decision making at this level can best be done using a rule-based expert system. This level of expert knowledge is also implemented using G2.

Diagnosing pulmonary embolisms: the clinician's point of view.

PubMed

Carrillo Alcaraz, A; Martínez, A López; Solano, F J Sotos

Pulmonary thromboembolism is common and potentially severe. To ensure the correct approach to the diagnostic workup of pulmonary thromboembolism, it is essential to know the basic concepts governing the use of the different tests available. The diagnostic approach to pulmonary thromboembolism is an example of the application of the conditional probabilities of Bayes' theorem in daily practice. To interpret the available diagnostic tests correctly, it is necessary to analyze different concepts that are fundamental for decision making. Thus, it is necessary to know what the likelihood ratios, 95% confidence intervals, and decision thresholds mean. Whether to determine the D-dimer concentration or to do CT angiography or other imaging tests depends on their capacity to modify the pretest probability of having the disease to a posttest probability that is higher or lower than the thresholds for action. This review aims to clarify the diagnostic sequence of thromboembolic pulmonary disease, analyzing the main diagnostic tools (clinical examination, laboratory tests, and imaging tests), placing special emphasis on the principles that govern evidence-based medicine. Copyright © 2016 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

Decentralized diagnostics based on a distributed micro-genetic algorithm for transducer networks monitoring large experimental systems.

PubMed

Arpaia, P; Cimmino, P; Girone, M; La Commara, G; Maisto, D; Manna, C; Pezzetti, M

2014-09-01

Evolutionary approach to centralized multiple-faults diagnostics is extended to distributed transducer networks monitoring large experimental systems. Given a set of anomalies detected by the transducers, each instance of the multiple-fault problem is formulated as several parallel communicating sub-tasks running on different transducers, and thus solved one-by-one on spatially separated parallel processes. A micro-genetic algorithm merges evaluation time efficiency, arising from a small-size population distributed on parallel-synchronized processors, with the effectiveness of centralized evolutionary techniques due to optimal mix of exploitation and exploration. In this way, holistic view and effectiveness advantages of evolutionary global diagnostics are combined with reliability and efficiency benefits of distributed parallel architectures. The proposed approach was validated both (i) by simulation at CERN, on a case study of a cold box for enhancing the cryogeny diagnostics of the Large Hadron Collider, and (ii) by experiments, under the framework of the industrial research project MONDIEVOB (Building Remote Monitoring and Evolutionary Diagnostics), co-funded by EU and the company Del Bo srl, Napoli, Italy.

Emerging Rapid Resistance Testing Methods for Clinical Microbiology Laboratories and Their Potential Impact on Patient Management

PubMed Central

Frickmann, Hagen; Zautner, Andreas E.

2014-01-01

Atypical and multidrug resistance, especially ESBL and carbapenemase expressing Enterobacteriaceae, is globally spreading. Therefore, it becomes increasingly difficult to achieve therapeutic success by calculated antibiotic therapy. Consequently, rapid antibiotic resistance testing is essential. Various molecular and mass spectrometry-based approaches have been introduced in diagnostic microbiology to speed up the providing of reliable resistance data. PCR- and sequencing-based approaches are the most expensive but the most frequently applied modes of testing, suitable for the detection of resistance genes even from primary material. Next generation sequencing, based either on assessment of allelic single nucleotide polymorphisms or on the detection of nonubiquitous resistance mechanisms might allow for sequence-based bacterial resistance testing comparable to viral resistance testing on the long term. Fluorescence in situ hybridization (FISH), based on specific binding of fluorescence-labeled oligonucleotide probes, provides a less expensive molecular bridging technique. It is particularly useful for detection of resistance mechanisms based on mutations in ribosomal RNA. Approaches based on MALDI-TOF-MS, alone or in combination with molecular techniques, like PCR/electrospray ionization MS or minisequencing provide the fastest resistance results from pure colonies or even primary samples with a growing number of protocols. This review details the various approaches of rapid resistance testing, their pros and cons, and their potential use for the diagnostic laboratory. PMID:25343142

Diffuse optical microscopy for quantification of depth-dependent epithelial backscattering in the cervix

NASA Astrophysics Data System (ADS)

Bodenschatz, Nico; Lam, Sylvia; Carraro, Anita; Korbelik, Jagoda; Miller, Dianne M.; McAlpine, Jessica N.; Lee, Marette; Kienle, Alwin; MacAulay, Calum

2016-06-01

A fiber optic imaging approach is presented using structured illumination for quantification of almost pure epithelial backscattering. We employ multiple spatially modulated projection patterns and camera-based reflectance capture to image depth-dependent epithelial scattering. The potential diagnostic value of our approach is investigated on cervical ex vivo tissue specimens. Our study indicates a strong backscattering increase in the upper part of the cervical epithelium caused by dysplastic microstructural changes. Quantization of relative depth-dependent backscattering is confirmed as a potentially useful diagnostic feature for detection of precancerous lesions in cervical squamous epithelium.

Teacher Incentive through Performance Contracting: A Programmatic Approach

ERIC Educational Resources Information Center

Quarles, Royce W.

1974-01-01

Describes an instructional program which applied the incentive theories of performance contracting--but with individualized, diagnostic-based instruction both designed and conducted by the teachers. (RB)

LASERS IN MEDICINE: Laser diagnostics of biofractals

NASA Astrophysics Data System (ADS)

Ushenko, A. G.

1999-12-01

An optical approach to the problem of modelling and diagnostics of the structures of biofractal formations was considered in relation to human bone tissue. A model was proposed for the optical properties of this tissue, including three levels of fractal organisation: microcrystalline, macrocrystalline, and architectural. The studies were based on laser coherent polarimetry ensuring the retrieval of the fullest information about the optical and polarisation properties of bone tissue. A method was developed for contactless noninvasive diagnostics of the orientational and mineralogical structure of bone tissue considered as a biofractal.

Diagnostic performance of an automated analysis software for the diagnosis of Alzheimer’s dementia with 18F FDG PET

PubMed Central

Partovi, Sasan; Yuh, Roger; Pirozzi, Sara; Lu, Ziang; Couturier, Spencer; Grosse, Ulrich; Schluchter, Mark D; Nelson, Aaron; Jones, Robert; O’Donnell, James K; Faulhaber, Peter

2017-01-01

The objective of this study was to assess the ability of a quantitative software-aided approach to improve the diagnostic accuracy of 18F FDG PET for Alzheimer’s dementia over visual analysis alone. Twenty normal subjects (M:F-12:8; mean age 80.6 years) and twenty mild AD subjects (M:F-12:8; mean age 70.6 years) with 18F FDG PET scans were obtained from the ADNI database. Three blinded readers interpreted these PET images first using a visual qualitative approach and then using a quantitative software-aided approach. Images were classified on two five-point scales based on normal/abnormal (1-definitely normal; 5-definitely abnormal) and presence of AD (1-definitely not AD; 5-definitely AD). Diagnostic sensitivity, specificity, and accuracy for both approaches were compared based on the aforementioned scales. The sensitivity, specificity, and accuracy for the normal vs. abnormal readings of all readers combined were higher when comparing the software-aided vs. visual approach (sensitivity 0.93 vs. 0.83 P = 0.0466; specificity 0.85 vs. 0.60 P = 0.0005; accuracy 0.89 vs. 0.72 P<0.0001). The specificity and accuracy for absence vs. presence of AD of all readers combined were higher when comparing the software-aided vs. visual approach (specificity 0.90 vs. 0.70 P = 0.0008; accuracy 0.81 vs. 0.72 P = 0.0356). Sensitivities of the software-aided and visual approaches did not differ significantly (0.72 vs. 0.73 P = 0.74). The quantitative software-aided approach appears to improve the performance of 18F FDG PET for the diagnosis of mild AD. It may be helpful for experienced 18F FDG PET readers analyzing challenging cases. PMID:28123864

The Quantitative Science of Evaluating Imaging Evidence.

PubMed

Genders, Tessa S S; Ferket, Bart S; Hunink, M G Myriam

2017-03-01

Cardiovascular diagnostic imaging tests are increasingly used in everyday clinical practice, but are often imperfect, just like any other diagnostic test. The performance of a cardiovascular diagnostic imaging test is usually expressed in terms of sensitivity and specificity compared with the reference standard (gold standard) for diagnosing the disease. However, evidence-based application of a diagnostic test also requires knowledge about the pre-test probability of disease, the benefit of making a correct diagnosis, the harm caused by false-positive imaging test results, and potential adverse effects of performing the test itself. To assist in clinical decision making regarding appropriate use of cardiovascular diagnostic imaging tests, we reviewed quantitative concepts related to diagnostic performance (e.g., sensitivity, specificity, predictive values, likelihood ratios), as well as possible biases and solutions in diagnostic performance studies, Bayesian principles, and the threshold approach to decision making. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Programmable bio-nano-chip system for saliva diagnostics

NASA Astrophysics Data System (ADS)

Christodoulides, Nicolaos; De La Garza, Richard; Simmons, Glennon W.; McRae, Michael P.; Wong, Jorge; Kosten, Thomas R.; Miller, Craig S.; Ebersole, Jeffrey L.; McDevitt, John

2014-06-01

This manuscript describes programmable Bio-Nano-Chip (p-BNC) approach that serves as miniaturized assay platform designed for the rapid detection and quantitation of multiple analytes in biological fluids along with the specific applications in salivary diagnostics intended for the point of need (PON). Included here are oral fluid-based tests for local periodontal disease, systemic cardiac disease and multiplexed tests for drugs of abuse.

Management of Epistaxis in Children and Adolescents: Avoiding a Chaotic Approach.

PubMed

Svider, Peter; Arianpour, Khashayar; Mutchnick, Sean

2018-06-01

This article provides an organized foundation that facilitates the management of acute epistaxis and an understanding of features that merit further diagnostic workup. Prompt management, including measures such as holding pressure and using nasal packing, takes precedence over comprehensive diagnostic workup. Severe, recurrent, and posteriorly based bleeds should prompt consideration of alternate interventions and expert consultation. Copyright © 2018 Elsevier Inc. All rights reserved.

Application of content-based image compression to telepathology

NASA Astrophysics Data System (ADS)

Varga, Margaret J.; Ducksbury, Paul G.; Callagy, Grace

2002-05-01

Telepathology is a means of practicing pathology at a distance, viewing images on a computer display rather than directly through a microscope. Without compression, images take too long to transmit to a remote location and are very expensive to store for future examination. However, to date the use of compressed images in pathology remains controversial. This is because commercial image compression algorithms such as JPEG achieve data compression without knowledge of the diagnostic content. Often images are lossily compressed at the expense of corrupting informative content. None of the currently available lossy compression techniques are concerned with what information has been preserved and what data has been discarded. Their sole objective is to compress and transmit the images as fast as possible. By contrast, this paper presents a novel image compression technique, which exploits knowledge of the slide diagnostic content. This 'content based' approach combines visually lossless and lossy compression techniques, judiciously applying each in the appropriate context across an image so as to maintain 'diagnostic' information while still maximising the possible compression. Standard compression algorithms, e.g. wavelets, can still be used, but their use in a context sensitive manner can offer high compression ratios and preservation of diagnostically important information. When compared with lossless compression the novel content-based approach can potentially provide the same degree of information with a smaller amount of data. When compared with lossy compression it can provide more information for a given amount of compression. The precise gain in the compression performance depends on the application (e.g. database archive or second opinion consultation) and the diagnostic content of the images.

Diagnostic challenges of childhood asthma.

PubMed

Bakirtas, Arzu

2017-01-01

Diagnosis of asthma in childhood is challenging. Both underdiagnosis and overdiagnosis of asthma are important issues. The present review gives information about challenging factors for an accurate diagnosis of childhood asthma. Although underdiagnosis of asthma in childhood has always been the most important diagnostic problem, overdiagnosis of asthma has also been increasingly recognized. This is probably due to diagnosis of asthma based on symptoms and signs alone. Demonstration of variable airflow obstruction by lung function tests is the most common asthma diagnostic tests used in practice and is therefore strongly recommended in children who can cooperate. Recently, an asthma guideline combining the clinical and economic evidences with sensitivity and specificity of diagnostic procedures was developed to improve accuracy of diagnosis and to avoid overdiagnosis. This guideline provided an algorithmic clinical and cost-effective approach and included fractional exhaled nitric oxide measurement as one of the diagnostic tests in addition to lung function. Diagnosis of asthma in children should be made by combining relevant history with at least two confirmatory diagnostic tests whenever possible. Diagnosis based on short-period treatment trials should be limited to young children who are unable to cooperate with these tests.

Development of Electrochemiluminescent Serology Assays to Measure the Humoral Response to Antigens of Respiratory Syncytial Virus.

PubMed

Maifeld, Sarah V; Ro, Bodrey; Mok, Hoyin; Chu, Marla; Yu, Li; Yamagata, Ryan; Leonardson, Tansy; Chio, Vera; Parhy, Bandita; Park, Samuel; Carlson, Marcia; Machhi, Shushil; Ulbrandt, Nancy; Falsey, Ann R; Walsh, Edward E; Wang, C Kathy; Esser, Mark T; Zuo, Fengrong

2016-01-01

Sensitive and precise serology assays are needed to measure the humoral response to antigens of respiratory syncytial virus (RSV) following natural infection or vaccination. We developed and evaluated a collection of electrochemiluminescent (ECL) serology assays using four RSV antigens (F, N, Ga and Gb). To assess the merits of ECL technology, the four ECL serology assays were evaluated using a well-characterized "gold standard" panel of acute and convalescent serum samples from fifty-nine RSV-positive and thirty RSV-negative elderly subjects (≥65 years old). The combined results from the four ECL assays demonstrated good concordance to the "gold standard" diagnosis, reaching 95% diagnostic sensitivity and 100% diagnostic specificity. Additionally, a combination of ECL assays provided higher diagnostic sensitivity than a commercially available diagnostic ELISA or cell-based microneutralization assay. In summary, these data demonstrate the advantages of using ECL-based serology assays and highlight their use as a sensitive diagnostic approach to detect recent RSV infection in an elderly population.

Genetic Evaluation of Short Stature

PubMed Central

Rosenfeld, Ron G.

2014-01-01

Context: Genetics plays a major role in determining an individual's height. Although there are many monogenic disorders that lead to perturbations in growth and result in short stature, there is still no consensus as to the role that genetic diagnostics should play in the evaluation of a child with short stature. Evidence Acquisition: A search of PubMed was performed, focusing on the genetic diagnosis of short stature as well as on specific diagnostic subgroups included in this article. Consensus guidelines were reviewed. Evidence Synthesis: There are a multitude of rare genetic causes of severe short stature. There is no high-quality evidence to define the optimal approach to the genetic evaluation of short stature. We review genetic etiologies of a number of diagnostic subgroups and propose an algorithm for genetic testing based on these subgroups. Conclusion: Advances in genomic technologies are revolutionizing the diagnostic approach to short stature. Endocrinologists must become facile with the use of genetic testing in order to identify the various monogenic disorders that present with short stature. PMID:24915122

Functional reasoning in diagnostic problem solving

NASA Technical Reports Server (NTRS)

Sticklen, Jon; Bond, W. E.; Stclair, D. C.

1988-01-01

This work is one facet of an integrated approach to diagnostic problem solving for aircraft and space systems currently under development. The authors are applying a method of modeling and reasoning about deep knowledge based on a functional viewpoint. The approach recognizes a level of device understanding which is intermediate between a compiled level of typical Expert Systems, and a deep level at which large-scale device behavior is derived from known properties of device structure and component behavior. At this intermediate functional level, a device is modeled in three steps. First, a component decomposition of the device is defined. Second, the functionality of each device/subdevice is abstractly identified. Third, the state sequences which implement each function are specified. Given a functional representation and a set of initial conditions, the functional reasoner acts as a consequence finder. The output of the consequence finder can be utilized in diagnostic problem solving. The paper also discussed ways in which this functional approach may find application in the aerospace field.

Thousand-fold fluorescent signal amplification for mHealth diagnostics

USDA-ARS?s Scientific Manuscript database

The low sensitivity of Mobile Health (mHealth) optical detectors, such as those found on mobile phones, is a limiting factor for many mHealth clinical applications. To improve sensitivity, we have combined two approaches for optical signal amplification: (1) a computational approach based on an imag...

An Integrative, Cognitive-Behavioral, Systemic Approach to Working with Students Diagnosed with Attention Deficit Hyperactive Disorder

ERIC Educational Resources Information Center

Shillingford, Margaret Ann; Lambie, Glenn W.; Walter, Sara Meghan

2007-01-01

Attention deficit hyperactive disorder (ADHD) is a prevalent diagnostic disorder for many students, which correlates with negative academic, social, and personal consequences. This article presents an integrative, cognitive-behavioral, systemic approach that offers behaviorally based interventions for professional school counselors to support…

The Stewart approach--one clinician's perspective.

PubMed

Morgan, T John

2009-05-01

Peter Stewart added controversy to an already troubled subject when he entered the clinical acid-base arena. His approach puts water dissociation at the centre of the acid-base status of body fluids. It is based on six simultaneous equations, incorporating the Laws of Mass Action, Mass Conservation, and Electrical Neutrality. Together with Gibbs-Donnan equilibria, these equations explain the diagnostically important PaCO(2)/pH relationship, and improve understanding of the physiologic basis of traditional acid-base approaches. Spin-offs have included new scanning tools for unmeasured ions, in particular the 'strong ion gap' and 'net unmeasured ions'. The most controversial feature is the designation of pH and bicarbonate concentrations as dependent variables, answerable exclusively to three independent variables. These are the strong ion difference (SID), the total concentration of non-volatile weak acid (A(TOT)), and PCO(2). Aspects of this assertion conflict with traditional renal physiology, and with current models of membrane H(+)/base transporters, oxidative phosphorylation, and proton and bicarbonate ionophores. The debate in this area is ongoing. Meanwhile, Stewart-style diagnostic and decision support systems such as the 'Strong Ion Calculator' and the web-site www.acidbase.org are now appearing.

The Stewart Approach – One Clinician’s Perspective

PubMed Central

Morgan, T John

2009-01-01

Peter Stewart added controversy to an already troubled subject when he entered the clinical acid-base arena. His approach puts water dissociation at the centre of the acid-base status of body fluids. It is based on six simultaneous equations, incorporating the Laws of Mass Action, Mass Conservation, and Electrical Neutrality. Together with Gibbs-Donnan equilibria, these equations explain the diagnostically important PaCO2/pH relationship, and improve understanding of the physiologic basis of traditional acid-base approaches. Spin-offs have included new scanning tools for unmeasured ions, in particular the ‘strong ion gap’ and ‘net unmeasured ions’. The most controversial feature is the designation of pH and bicarbonate concentrations as dependent variables, answerable exclusively to three independent variables. These are the strong ion difference (SID), the total concentration of non-volatile weak acid (ATOT), and PCO2. Aspects of this assertion conflict with traditional renal physiology, and with current models of membrane H+/base transporters, oxidative phosphorylation, and proton and bicarbonate ionophores. The debate in this area is ongoing. Meanwhile, Stewart-style diagnostic and decision support systems such as the ‘Strong Ion Calculator’ and the web-site www.acidbase.org are now appearing. PMID:19565024

A Clinical Approach to the Diagnosis of Acid-Base Disorders

PubMed Central

Bear, Robert A.

1986-01-01

The ability to diagnose and manage acid-base disorders rapidly and effectively is essential to the care of critically ill patients. This article presents an approach to the diagnosis of pure and mixed acid-base disorders, metabolic or respiratory. The approach taken is based on using the law of mass-action equation as it applies to the bicarbonate buffer system (Henderson equation), using sub-classifications for diagnostic purposes of causes of metabolic acidosis and metabolic alkalosis, and using a knowledge of the well-defined and predictable compensatory responses that attempt to limit the change in pH in each of the primary acid-base disorders. PMID:21267134

Dynamic CT myocardial perfusion imaging: performance of 3D semi-automated evaluation software.

PubMed

Ebersberger, Ullrich; Marcus, Roy P; Schoepf, U Joseph; Lo, Gladys G; Wang, Yining; Blanke, Philipp; Geyer, Lucas L; Gray, J Cranston; McQuiston, Andrew D; Cho, Young Jun; Scheuering, Michael; Canstein, Christian; Nikolaou, Konstantin; Hoffmann, Ellen; Bamberg, Fabian

2014-01-01

To evaluate the performance of three-dimensional semi-automated evaluation software for the assessment of myocardial blood flow (MBF) and blood volume (MBV) at dynamic myocardial perfusion computed tomography (CT). Volume-based software relying on marginal space learning and probabilistic boosting tree-based contour fitting was applied to CT myocardial perfusion imaging data of 37 subjects. In addition, all image data were analysed manually and both approaches were compared with SPECT findings. Study endpoints included time of analysis and conventional measures of diagnostic accuracy. Of 592 analysable segments, 42 showed perfusion defects on SPECT. Average analysis times for the manual and software-based approaches were 49.1 ± 11.2 and 16.5 ± 3.7 min respectively (P < 0.01). There was strong agreement between the two measures of interest (MBF, ICC = 0.91, and MBV, ICC = 0.88, both P < 0.01) and no significant difference in MBF/MBV with respect to diagnostic accuracy between the two approaches for both MBF and MBV for manual versus software-based approach; respectively; all comparisons P > 0.05. Three-dimensional semi-automated evaluation of dynamic myocardial perfusion CT data provides similar measures and diagnostic accuracy to manual evaluation, albeit with substantially reduced analysis times. This capability may aid the integration of this test into clinical workflows. • Myocardial perfusion CT is attractive for comprehensive coronary heart disease assessment. • Traditional image analysis methods are cumbersome and time-consuming. • Automated 3D perfusion software shortens analysis times. • Automated 3D perfusion software increases standardisation of myocardial perfusion CT. • Automated, standardised analysis fosters myocardial perfusion CT integration into clinical practice.

Efficient Probabilistic Diagnostics for Electrical Power Systems

NASA Technical Reports Server (NTRS)

Mengshoel, Ole J.; Chavira, Mark; Cascio, Keith; Poll, Scott; Darwiche, Adnan; Uckun, Serdar

2008-01-01

We consider in this work the probabilistic approach to model-based diagnosis when applied to electrical power systems (EPSs). Our probabilistic approach is formally well-founded, as it based on Bayesian networks and arithmetic circuits. We investigate the diagnostic task known as fault isolation, and pay special attention to meeting two of the main challenges . model development and real-time reasoning . often associated with real-world application of model-based diagnosis technologies. To address the challenge of model development, we develop a systematic approach to representing electrical power systems as Bayesian networks, supported by an easy-to-use speci.cation language. To address the real-time reasoning challenge, we compile Bayesian networks into arithmetic circuits. Arithmetic circuit evaluation supports real-time diagnosis by being predictable and fast. In essence, we introduce a high-level EPS speci.cation language from which Bayesian networks that can diagnose multiple simultaneous failures are auto-generated, and we illustrate the feasibility of using arithmetic circuits, compiled from Bayesian networks, for real-time diagnosis on real-world EPSs of interest to NASA. The experimental system is a real-world EPS, namely the Advanced Diagnostic and Prognostic Testbed (ADAPT) located at the NASA Ames Research Center. In experiments with the ADAPT Bayesian network, which currently contains 503 discrete nodes and 579 edges, we .nd high diagnostic accuracy in scenarios where one to three faults, both in components and sensors, were inserted. The time taken to compute the most probable explanation using arithmetic circuits has a small mean of 0.2625 milliseconds and standard deviation of 0.2028 milliseconds. In experiments with data from ADAPT we also show that arithmetic circuit evaluation substantially outperforms joint tree propagation and variable elimination, two alternative algorithms for diagnosis using Bayesian network inference.

A systematic review of diagnostic criteria for psoriasis in adults and children: evidence from studies with a primary aim to develop or validate diagnostic criteria.

PubMed

Burden-Teh, E; Phillips, R C; Thomas, K S; Ratib, S; Grindlay, D; Murphy, R

2017-11-06

The diagnosis of psoriasis in adults and children is made clinically, for both patient management and the selection of participants in research. Diagnostic criteria provide a structure for clinical assessment, which in turn helps standardize patient recruitment into clinical trials and case definitions in observational studies. The aim of this systematic review was to identify and critically appraise the published studies to date that had a primary research aim to develop or validate diagnostic criteria for psoriasis. A search of Ovid MEDLINE and Ovid Embase was conducted in October 2016. The primary objective was to record the sensitivity and specificity of diagnostic criteria for psoriasis. Secondary objectives included diagnostic recommendations, applicability to children and study characteristics. Diagnostic accuracy studies were critically appraised for risk of bias using the QUADAS-2 tool. Twenty-three studies met the inclusion criteria. None detailed clinical examination-based diagnostic criteria. The included criteria varied from genetic and molecular diagnostic models to skin imaging, histopathology, and questionnaire-based, computer-aided and traditional Chinese medicine criteria. High sensitivity and specificity (> 90%) were reported in many studies. However, the study authors often did not specify how the criteria would be used clinically or in research. This review identified studies with varying risk of bias, and due to each study developing separate criteria meta-analysis was not possible. Clinical examination-based diagnostic criteria are currently lacking for psoriasis. Future research could follow an international collaborative approach and employ study designs allowing high-quality diagnostic accuracy testing. Existing and newly developed criteria require validation. © 2017 British Association of Dermatologists.

Circulating tumor DNA as a liquid biopsy target for detection of pancreatic cancer

PubMed Central

Takai, Erina; Yachida, Shinichi

2016-01-01

Most pancreatic cancer patients present with advanced metastatic disease, resulting in extremely poor 5-year survival, mainly because of the lack of a reliable modality for early detection and limited therapeutic options for advanced disease. Therefore, there is a need for minimally-invasive diagnostic tools for detecting pancreatic cancer at an early stage, when curative surgery and also novel therapeutic approaches including precision medicine may be feasible. The “liquid biopsy” addresses these unmet clinical needs based on the concept that simple peripheral blood sampling and detection of circulating tumor DNA (ctDNA) could provide diagnostic information. In this review, we provide an overview of the current status of blood-based tests for diagnosis of pancreatic cancer and the potential utility of ctDNA for precision medicine. We also discuss challenges that remain to be addressed in developing practical ctDNA-based liquid biopsy approaches for early diagnosis of pancreatic cancer. PMID:27784960

Circulating tumor DNA as a liquid biopsy target for detection of pancreatic cancer.

PubMed

Takai, Erina; Yachida, Shinichi

2016-10-14

Most pancreatic cancer patients present with advanced metastatic disease, resulting in extremely poor 5-year survival, mainly because of the lack of a reliable modality for early detection and limited therapeutic options for advanced disease. Therefore, there is a need for minimally-invasive diagnostic tools for detecting pancreatic cancer at an early stage, when curative surgery and also novel therapeutic approaches including precision medicine may be feasible. The "liquid biopsy" addresses these unmet clinical needs based on the concept that simple peripheral blood sampling and detection of circulating tumor DNA (ctDNA) could provide diagnostic information. In this review, we provide an overview of the current status of blood-based tests for diagnosis of pancreatic cancer and the potential utility of ctDNA for precision medicine. We also discuss challenges that remain to be addressed in developing practical ctDNA-based liquid biopsy approaches for early diagnosis of pancreatic cancer.

Diagnosis support system based on clinical guidelines: comparison between case-based fuzzy cognitive maps and Bayesian networks.

PubMed

Douali, Nassim; Csaba, Huszka; De Roo, Jos; Papageorgiou, Elpiniki I; Jaulent, Marie-Christine

2014-01-01

Several studies have described the prevalence and severity of diagnostic errors. Diagnostic errors can arise from cognitive, training, educational and other issues. Examples of cognitive issues include flawed reasoning, incomplete knowledge, faulty information gathering or interpretation, and inappropriate use of decision-making heuristics. We describe a new approach, case-based fuzzy cognitive maps, for medical diagnosis and evaluate it by comparison with Bayesian belief networks. We created a semantic web framework that supports the two reasoning methods. We used database of 174 anonymous patients from several European hospitals: 80 of the patients were female and 94 male with an average age 45±16 (average±stdev). Thirty of the 80 female patients were pregnant. For each patient, signs/symptoms/observables/age/sex were taken into account by the system. We used a statistical approach to compare the two methods. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

SELDI-TOF-based serum proteomic pattern diagnostics for early detection of cancer.

PubMed

Petricoin, Emanuel F; Liotta, Lance A

2004-02-01

Proteomics is more than just generating lists of proteins that increase or decrease in expression as a cause or consequence of pathology. The goal should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. The nature of this information can be a cause, or a consequence, of disease and toxicity-based processes. Serum proteomic pattern diagnostics is a new type of proteomic platform in which patterns of proteomic signatures from high dimensional mass spectrometry data are used as a diagnostic classifier. This approach has recently shown tremendous promise in the detection of early-stage cancers. The biomarkers found by SELDI-TOF-based pattern recognition analysis are mostly low molecular weight fragments produced at the specific tumor microenvironment.

Laser diagnostics for combustion temperature and species

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eckbreth, A.C.

1987-01-01

Laser approaches to combustion diagnostics are of considerable interest due to their remote, nonintrusive and in-situ character, unlimited temperature capability and potential for simultaneous temporal and spatial resolution, This book aims to make these powerful and important new tools in combustion research understandable. The focus of this text is on spectroscopically-based, spatially-precise laser techniques for temperature and chemical composition measurements in reacting and nonreacting flows. After introductory chapters providing a fundamental theoretical and experimental background, attention is directed to diagnostics based upon spontaneous Raman and Rayleigh scattering, coherent anti-Stokes Raman spectroscopy (CARS) and laser-induced fluorescence (LIFS). The book concludes withmore » a treatment of techniques which permit spatially-resolved measurements over an entire two-dimensional field simultaneously.« less

Clinical approaches to infertility in the bitch.

PubMed

Wilborn, Robyn R; Maxwell, Herris S

2012-05-01

When presented with the apparently infertile bitch, the practitioner must sort through a myriad of facts, historical events, and diagnostic tests to uncover the etiology of the problem. Many bitches that present for infertility are reproductively normal and are able to conceive with appropriate intervention and breeding management. An algorithmic approach is helpful in cases of infertility, where simple questions lead to the next appropriate step. Most bitches can be categorized as either cyclic or acyclic, and then further classified based on historical data and diagnostic testing. Each female has a unique set of circumstances that can affect her reproductive potential. By utilizing all available information and a logical approach, the clinician can narrow the list of differentials and reach a diagnosis more quickly.

Machine Learning Approach to Extract Diagnostic and Prognostic Thresholds: Application in Prognosis of Cardiovascular Mortality

PubMed Central

Mena, Luis J.; Orozco, Eber E.; Felix, Vanessa G.; Ostos, Rodolfo; Melgarejo, Jesus; Maestre, Gladys E.

2012-01-01

Machine learning has become a powerful tool for analysing medical domains, assessing the importance of clinical parameters, and extracting medical knowledge for outcomes research. In this paper, we present a machine learning method for extracting diagnostic and prognostic thresholds, based on a symbolic classification algorithm called REMED. We evaluated the performance of our method by determining new prognostic thresholds for well-known and potential cardiovascular risk factors that are used to support medical decisions in the prognosis of fatal cardiovascular diseases. Our approach predicted 36% of cardiovascular deaths with 80% specificity and 75% general accuracy. The new method provides an innovative approach that might be useful to support decisions about medical diagnoses and prognoses. PMID:22924062

Swyer Syndrome With Gonadoblastoma: A Clinicoradiological Approach.

PubMed

Agarwal, Arjit; Agarwal, Shubhra

2017-01-01

Primary amenorrhea is a common diagnostic challenge in the gynecology department, wherein there are numerous causes that need to be approached in a systematic manner. However, when a case with a pelvic lump or a solid pelvic mass presents to a gynecologist or a radiologist, the approach becomes difficult to justify amenorrhea and pelvic mass as a single entity. We present the case of a 36-year-old female with the complaints of primary amenorrhea with a pelvic mass. The case was approached keeping in view the diagnostic possibilities and applying the role of clinical, radiological, and laboratory analyses. The final diagnosis of Swyer syndrome with gonadoblastoma was made, and she was further subjected to operative resection and hormonal therapy. This study stresses on the approach to a case, wherein the diagnosis was based only on the clinician's acumen and the radiologist's expertise, providing a way to simplify the protocol in the evaluation of such types of cases.

Future Issues and Approaches to Health Monitoring and Failure Prevention for Oil-Free Gas Turbines

NASA Technical Reports Server (NTRS)

DellaCorte, Christopher

2004-01-01

Recent technology advances in foil air bearings, high temperature solid lubricants and computer based modeling has enabled the development of small Oil-Free gas turbines. These turbomachines are currently commercialized as small (<100 kW) microturbine generators and larger machines are being developed. Based upon these successes and the high potential payoffs offered by Oil-Free systems, NASA, industry, and other government entities are anticipating Oil-Free gas turbine propulsion systems to proliferate future markets. Since an Oil-Free engine has no oil system, traditional approaches to health monitoring and diagnostics, such as chip detection, oil analysis, and possibly vibration signature analyses (e.g., ball pass frequency) will be unavailable. As such, new approaches will need to be considered. These could include shaft orbit analyses, foil bearing temperature measurements, embedded wear sensors and start-up/coast down speed analysis. In addition, novel, as yet undeveloped techniques may emerge based upon concurrent developments in MEMS technology. This paper introduces Oil-Free technology, reviews the current state of the art and potential for future turbomachinery applications and discusses possible approaches to health monitoring, diagnostics and failure prevention.

Using complex networks towards information retrieval and diagnostics in multidimensional imaging

NASA Astrophysics Data System (ADS)

Banerjee, Soumya Jyoti; Azharuddin, Mohammad; Sen, Debanjan; Savale, Smruti; Datta, Himadri; Dasgupta, Anjan Kr; Roy, Soumen

2015-12-01

We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers.

Using complex networks towards information retrieval and diagnostics in multidimensional imaging.

PubMed

Banerjee, Soumya Jyoti; Azharuddin, Mohammad; Sen, Debanjan; Savale, Smruti; Datta, Himadri; Dasgupta, Anjan Kr; Roy, Soumen

2015-12-02

We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers.

Using complex networks towards information retrieval and diagnostics in multidimensional imaging

PubMed Central

Banerjee, Soumya Jyoti; Azharuddin, Mohammad; Sen, Debanjan; Savale, Smruti; Datta, Himadri; Dasgupta, Anjan Kr; Roy, Soumen

2015-01-01

We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers. PMID:26626047

Pre-examination factors affecting molecular diagnostic test results and interpretation: A case-based approach.

PubMed

Payne, Deborah A; Baluchova, Katarina; Peoc'h, Katell H; van Schaik, Ron H N; Chan, K C Allen; Maekawa, Masato; Mamotte, Cyril; Russomando, Graciela; Rousseau, François; Ahmad-Nejad, Parviz

2017-04-01

Multiple organizations produce guidance documents that provide opportunities to harmonize quality practices for diagnostic testing. The International Organization for Standardization ISO 15189 standard addresses requirements for quality in management and technical aspects of the clinical laboratory. One technical aspect addresses the complexities of the pre-examination phase prior to diagnostic testing. The Committee for Molecular Diagnostics of the International Federation for Clinical Chemistry and Laboratory Medicine (also known as, IFCC C-MD) conducted a survey of international molecular laboratories and determined ISO 15189 to be the most referenced guidance document. In this review, the IFCC C-MD provides case-based examples illustrating the value of select pre-examination processes as these processes relate to molecular diagnostic testing. Case-based examples in infectious disease, oncology, inherited disease and pharmacogenomics address the utility of: 1) providing information to patients and users, 2) designing requisition forms, 3) obtaining informed consent and 4) maintaining sample integrity prior to testing. The pre-examination phase requires extensive and consistent communication between the laboratory, the healthcare provider and the end user. The clinical vignettes presented in this paper illustrate the value of applying select ISO 15189 recommendations for general laboratory to the more specialized area of Molecular Diagnostics. Copyright © 2016 Elsevier B.V. All rights reserved.

Development and Application of a Novel Rasch-Based Methodology for Evaluating Multi-Tiered Assessment Instruments: Validation and Utilization of an Undergraduate Diagnostic Test of the Water Cycle

ERIC Educational Resources Information Center

Romine, William L.; Schaffer, Dane L.; Barrow, Lloyd

2015-01-01

We describe the development and validation of a three-tiered diagnostic test of the water cycle (DTWC) and use it to evaluate the impact of prior learning experiences on undergraduates' misconceptions. While most approaches to instrument validation take a positivist perspective using singular criteria such as reliability and fit with a measurement…

Diagnostic Approach to a Patient With Paraneoplastic Neurological Syndrome.

PubMed

Mahta, Ali; Vijayvergia, Namrata; Bhavsar, Tapan M; Ward, Lawrence D

2012-10-01

Herein, we discussed a case of an otherwise healthy man who presented with progressive gait imbalance and ataxia, found to have small cell lung cancer. Based upon our clinical findings and laboratory data, a diagnosis of paraneoplastic cerebellar degeneration was made. Paraneoplastic neurological syndromes (PNS) are relatively rare but diverse and always should be considered in differentials. A diagnostic algorithm along with appropriate work up is discussed here.

Diagnostic Approach to a Patient With Paraneoplastic Neurological Syndrome

PubMed Central

Mahta, Ali; Vijayvergia, Namrata; Bhavsar, Tapan M.; Ward, Lawrence D.

2012-01-01

Herein, we discussed a case of an otherwise healthy man who presented with progressive gait imbalance and ataxia, found to have small cell lung cancer. Based upon our clinical findings and laboratory data, a diagnosis of paraneoplastic cerebellar degeneration was made. Paraneoplastic neurological syndromes (PNS) are relatively rare but diverse and always should be considered in differentials. A diagnostic algorithm along with appropriate work up is discussed here. PMID:29147315

Methods and means of diagnostics of oncological diseases on the basis of pattern recognition: intelligent morphological systems - problems and solutions

NASA Astrophysics Data System (ADS)

Nikitaev, V. G.

2017-01-01

The development of methods of pattern recognition in modern intelligent systems of clinical cancer diagnosis are discussed. The histological (morphological) diagnosis - primary diagnosis for medical setting with cancer are investigated. There are proposed: interactive methods of recognition and structure of intellectual morphological complexes based on expert training-diagnostic and telemedicine systems. The proposed approach successfully implemented in clinical practice.

Clinical decision making-a functional medicine perspective.

PubMed

Pizzorno, Joseph E

2012-09-01

As 21st century health care moves from a disease-based approach to a more patient-centric system that can address biochemical individuality to improve health and function, clinical decision making becomes more complex. Accentuating the problem is the lack of a clear standard for this more complex functional medicine approach. While there is relatively broad agreement in Western medicine for what constitutes competent assessment of disease and identification of related treatment approaches, the complex functional medicine model posits multiple and individualized diagnostic and therapeutic approaches, most or many of which have reasonable underlying science and principles, but which have not been rigorously tested in a research or clinical setting. This has led to non-rigorous thinking and sometimes to uncritical acceptance of both poorly documented diagnostic procedures and ineffective therapies, resulting in less than optimal clinical care.

Clinical Decision Making—A Functional Medicine Perspective

PubMed Central

2012-01-01

As 21st century health care moves from a disease-based approach to a more patient-centric system that can address biochemical individuality to improve health and function, clinical decision making becomes more complex. Accentuating the problem is the lack of a clear standard for this more complex functional medicine approach. While there is relatively broad agreement in Western medicine for what constitutes competent assessment of disease and identification of related treatment approaches, the complex functional medicine model posits multiple and individualized diagnostic and therapeutic approaches, most or many of which have reasonable underlying science and principles, but which have not been rigorously tested in a research or clinical setting. This has led to non-rigorous thinking and sometimes to uncritical acceptance of both poorly documented diagnostic procedures and ineffective therapies, resulting in less than optimal clinical care. PMID:24278827

Bootstrap-based procedures for inference in nonparametric receiver-operating characteristic curve regression analysis.

PubMed

Rodríguez-Álvarez, María Xosé; Roca-Pardiñas, Javier; Cadarso-Suárez, Carmen; Tahoces, Pablo G

2018-03-01

Prior to using a diagnostic test in a routine clinical setting, the rigorous evaluation of its diagnostic accuracy is essential. The receiver-operating characteristic curve is the measure of accuracy most widely used for continuous diagnostic tests. However, the possible impact of extra information about the patient (or even the environment) on diagnostic accuracy also needs to be assessed. In this paper, we focus on an estimator for the covariate-specific receiver-operating characteristic curve based on direct regression modelling and nonparametric smoothing techniques. This approach defines the class of generalised additive models for the receiver-operating characteristic curve. The main aim of the paper is to offer new inferential procedures for testing the effect of covariates on the conditional receiver-operating characteristic curve within the above-mentioned class. Specifically, two different bootstrap-based tests are suggested to check (a) the possible effect of continuous covariates on the receiver-operating characteristic curve and (b) the presence of factor-by-curve interaction terms. The validity of the proposed bootstrap-based procedures is supported by simulations. To facilitate the application of these new procedures in practice, an R-package, known as npROCRegression, is provided and briefly described. Finally, data derived from a computer-aided diagnostic system for the automatic detection of tumour masses in breast cancer is analysed.

Engineering as a new frontier for translational medicine

PubMed Central

Chien, Shu; Bashir, Rashid; Nerem, Robert M.; Pettigrew, Roderic

2015-01-01

The inclusion of engineering ideas and approaches makes medicine a quantitative and systems-based discipline that facilitates precision diagnostics and therapeutics to improve health care delivery for all. PMID:25834106

Toyota Prius HEV neurocontrol and diagnostics.

PubMed

Prokhorov, Danil V

2008-01-01

A neural network controller for improved fuel efficiency of the Toyota Prius hybrid electric vehicle is proposed. A new method to detect and mitigate a battery fault is also presented. The approach is based on recurrent neural networks and includes the extended Kalman filter. The proposed approach is quite general and applicable to other control systems.

Oncology Teaching: A Multidisciplinary Approach for Second-Year Medical Students

ERIC Educational Resources Information Center

Elkort, Richard; Mozden, Peter J.

1975-01-01

A Boston University School of Medicine course in oncology is described which covers basic science correlates, diagnostic approaches, treatment modalities, and psycho-social aspects. Based on five years experience, the course is considered a successful means of correlating basic and clinical information for second- and third-year medical students.…

Diagnosing Conceptions about the Epistemology of Science: Contributions of a Quantitative Assessment Methodology

ERIC Educational Resources Information Center

Vázquez-Alonso, Ángel; Manassero-Mas, María-Antonia; García-Carmona, Antonio; Montesano de Talavera, Marisa

2016-01-01

This study applies a new quantitative methodological approach to diagnose epistemology conceptions in a large sample. The analyses use seven multiple-rating items on the epistemology of science drawn from the item pool Views on Science-Technology-Society (VOSTS). The bases of the new methodological diagnostic approach are the empirical…

Biomedical visual data analysis to build an intelligent diagnostic decision support system in medical genetics.

PubMed

Kuru, Kaya; Niranjan, Mahesan; Tunca, Yusuf; Osvank, Erhan; Azim, Tayyaba

2014-10-01

In general, medical geneticists aim to pre-diagnose underlying syndromes based on facial features before performing cytological or molecular analyses where a genotype-phenotype interrelation is possible. However, determining correct genotype-phenotype interrelationships among many syndromes is tedious and labor-intensive, especially for extremely rare syndromes. Thus, a computer-aided system for pre-diagnosis can facilitate effective and efficient decision support, particularly when few similar cases are available, or in remote rural districts where diagnostic knowledge of syndromes is not readily available. The proposed methodology, visual diagnostic decision support system (visual diagnostic DSS), employs machine learning (ML) algorithms and digital image processing techniques in a hybrid approach for automated diagnosis in medical genetics. This approach uses facial features in reference images of disorders to identify visual genotype-phenotype interrelationships. Our statistical method describes facial image data as principal component features and diagnoses syndromes using these features. The proposed system was trained using a real dataset of previously published face images of subjects with syndromes, which provided accurate diagnostic information. The method was tested using a leave-one-out cross-validation scheme with 15 different syndromes, each of comprised 5-9 cases, i.e., 92 cases in total. An accuracy rate of 83% was achieved using this automated diagnosis technique, which was statistically significant (p<0.01). Furthermore, the sensitivity and specificity values were 0.857 and 0.870, respectively. Our results show that the accurate classification of syndromes is feasible using ML techniques. Thus, a large number of syndromes with characteristic facial anomaly patterns could be diagnosed with similar diagnostic DSSs to that described in the present study, i.e., visual diagnostic DSS, thereby demonstrating the benefits of using hybrid image processing and ML-based computer-aided diagnostics for identifying facial phenotypes. Copyright © 2014. Published by Elsevier B.V.

Diagnostic methods for atmospheric inversions of long-lived greenhouse gases

NASA Astrophysics Data System (ADS)

Michalak, Anna M.; Randazzo, Nina A.; Chevallier, Frédéric

2017-06-01

The ability to predict the trajectory of climate change requires a clear understanding of the emissions and uptake (i.e., surface fluxes) of long-lived greenhouse gases (GHGs). Furthermore, the development of climate policies is driving a need to constrain the budgets of anthropogenic GHG emissions. Inverse problems that couple atmospheric observations of GHG concentrations with an atmospheric chemistry and transport model have increasingly been used to gain insights into surface fluxes. Given the inherent technical challenges associated with their solution, it is imperative that objective approaches exist for the evaluation of such inverse problems. Because direct observation of fluxes at compatible spatiotemporal scales is rarely possible, diagnostics tools must rely on indirect measures. Here we review diagnostics that have been implemented in recent studies and discuss their use in informing adjustments to model setup. We group the diagnostics along a continuum starting with those that are most closely related to the scientific question being targeted, and ending with those most closely tied to the statistical and computational setup of the inversion. We thus begin with diagnostics based on assessments against independent information (e.g., unused atmospheric observations, large-scale scientific constraints), followed by statistical diagnostics of inversion results, diagnostics based on sensitivity tests, and analyses of robustness (e.g., tests focusing on the chemistry and transport model, the atmospheric observations, or the statistical and computational framework), and close with the use of synthetic data experiments (i.e., observing system simulation experiments, OSSEs). We find that existing diagnostics provide a crucial toolbox for evaluating and improving flux estimates but, not surprisingly, cannot overcome the fundamental challenges associated with limited atmospheric observations or the lack of direct flux measurements at compatible scales. As atmospheric inversions are increasingly expected to contribute to national reporting of GHG emissions, the need for developing and implementing robust and transparent evaluation approaches will only grow.

A structured proteomic approach identifies 14-3-3Sigma as a novel and reliable protein biomarker in panel based differential diagnostics of liver tumors.

PubMed

Reis, Henning; Pütter, Carolin; Megger, Dominik A; Bracht, Thilo; Weber, Frank; Hoffmann, Andreas-C; Bertram, Stefanie; Wohlschläger, Jeremias; Hagemann, Sascha; Eisenacher, Martin; Scherag, André; Schlaak, Jörg F; Canbay, Ali; Meyer, Helmut E; Sitek, Barbara; Baba, Hideo A

2015-06-01

Hepatocellular carcinoma (HCC) is a major lethal cancer worldwide. Despite sophisticated diagnostic algorithms, the differential diagnosis of small liver nodules still is difficult. While imaging techniques have advanced, adjuvant protein-biomarkers as glypican3 (GPC3), glutamine-synthetase (GS) and heat-shock protein 70 (HSP70) have enhanced diagnostic accuracy. The aim was to further detect useful protein-biomarkers of HCC with a structured systematic approach using differential proteome techniques, bring the results to practical application and compare the diagnostic accuracy of the candidates with the established biomarkers. After label-free and gel-based proteomics (n=18 HCC/corresponding non-tumorous liver tissue (NTLT)) biomarker candidates were tested for diagnostic accuracy in immunohistochemical analyses (n=14 HCC/NTLT). Suitable candidates were further tested for consistency in comparison to known protein-biomarkers in HCC (n=78), hepatocellular adenoma (n=25; HCA), focal nodular hyperplasia (n=28; FNH) and cirrhosis (n=28). Of all protein-biomarkers, 14-3-3Sigma (14-3-3S) exhibited the most pronounced up-regulation (58.8×) in proteomics and superior diagnostic accuracy (73.0%) in the differentiation of HCC from non-tumorous hepatocytes also compared to established biomarkers as GPC3 (64.7%) and GS (45.4%). 14-3-3S was part of the best diagnostic three-biomarker panel (GPC3, HSP70, 14-3-3S) for the differentiation of HCC and HCA which is of most important significance. Exclusion of GS and inclusion of 14-3-3S in the panel (>1 marker positive) resulted in a profound increase in specificity (+44.0%) and accuracy (+11.0%) while sensitivity remained stable (96.0%). 14-3-3S is an interesting protein biomarker with the potential to further improve the accuracy of differential diagnostic process of hepatocellular tumors. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

Variance Estimation for NAEP Data Using a Resampling-Based Approach: An Application of Cognitive Diagnostic Models. Research Report. ETS RR-10-26

ERIC Educational Resources Information Center

Hsieh, Chueh-an; Xu, Xueli; von Davier, Matthias

2010-01-01

This paper presents an application of a jackknifing approach to variance estimation of ability inferences for groups of students, using a multidimensional discrete model for item response data. The data utilized to demonstrate the approach come from the National Assessment of Educational Progress (NAEP). In contrast to the operational approach…

Avoidant/restrictive food intake disorder: a new eating disorder diagnosis in the diagnostic and statistical manual 5.

PubMed

Mammel, Kathleen A; Ornstein, Rollyn M

2017-08-01

Avoidant/restrictive food intake disorder (ARFID) is a new eating disorder diagnosis in the 5th edition of the diagnostic and statistical manual (DSM-5), published in 2013. The purpose of this review is to describe the creation of ARFID as a diagnostic category, and to explain the DSM-5 diagnostic criteria; to demonstrate what is known thus far about the prevalence of ARFID and characteristics of patients with this disorder; to provide guidance to the pediatrician and other providers on making a diagnosis of ARFID; and to discuss evolving treatment approaches. Several studies have been published recently on the prevalence and characteristics of patients with ARFID. Research has just begun to focus on new assessment measures, approaches to treatment based on established therapies for other eating/psychiatric disorders, and short-term outcomes. Robust treatment studies are in development. The addition of ARFID to the DSM-5 has captured a category of patients with clinically significant restrictive eating, but without weight and shape concerns, who were poorly classified in the past. Future research is needed to further elucidate the presentation, characteristics, diagnostic instruments, and effective management.

Evidence-Based Assessment in Case Management to Improve Abnormal Cancer Screen Follow-Up

ERIC Educational Resources Information Center

Vourlekis, Betsy; Ell, Kathleen; Padgett, Deborah

2005-01-01

The authors describe an evidence-based assessment protocol for intensive case management to improve screening diagnostic follow-up developed through a research project in breast and cervical cancer early detection funded by the Centers for Disease Control and Prevention. Three components of an evidence-based approach to assessment are presented…

PROcess Based Diagnostics PROBE

NASA Technical Reports Server (NTRS)

Clune, T.; Schmidt, G.; Kuo, K.; Bauer, M.; Oloso, H.

2013-01-01

Many of the aspects of the climate system that are of the greatest interest (e.g., the sensitivity of the system to external forcings) are emergent properties that arise via the complex interplay between disparate processes. This is also true for climate models most diagnostics are not a function of an isolated portion of source code, but rather are affected by multiple components and procedures. Thus any model-observation mismatch is hard to attribute to any specific piece of code or imperfection in a specific model assumption. An alternative approach is to identify diagnostics that are more closely tied to specific processes -- implying that if a mismatch is found, it should be much easier to identify and address specific algorithmic choices that will improve the simulation. However, this approach requires looking at model output and observational data in a more sophisticated way than the more traditional production of monthly or annual mean quantities. The data must instead be filtered in time and space for examples of the specific process being targeted.We are developing a data analysis environment called PROcess-Based Explorer (PROBE) that seeks to enable efficient and systematic computation of process-based diagnostics on very large sets of data. In this environment, investigators can define arbitrarily complex filters and then seamlessly perform computations in parallel on the filtered output from their model. The same analysis can be performed on additional related data sets (e.g., reanalyses) thereby enabling routine comparisons between model and observational data. PROBE also incorporates workflow technology to automatically update computed diagnostics for subsequent executions of a model. In this presentation, we will discuss the design and current status of PROBE as well as share results from some preliminary use cases.

Validation of α-Synuclein as a CSF Biomarker for Sporadic Creutzfeldt-Jakob Disease.

PubMed

Llorens, Franc; Kruse, Niels; Karch, André; Schmitz, Matthias; Zafar, Saima; Gotzmann, Nadine; Sun, Ting; Köchy, Silja; Knipper, Tobias; Cramm, Maria; Golanska, Ewa; Sikorska, Beata; Liberski, Pawel P; Sánchez-Valle, Raquel; Fischer, Andre; Mollenhauer, Brit; Zerr, Inga

2018-03-01

The analysis of cerebrospinal fluid (CSF) biomarkers gains importance in the differential diagnosis of prion diseases. However, no single diagnostic tool or combination of them can unequivocally confirm prion disease diagnosis. Electrochemiluminescence (ECL)-based immunoassays have demonstrated to achieve high diagnostic accuracy in a variety of sample types due to their high sensitivity and dynamic range. Quantification of CSF α-synuclein (a-syn) by an in-house ECL-based ELISA assay has been recently reported as an excellent approach for the diagnosis of sporadic Creutzfeldt-Jakob disease (sCJD), the most prevalent form of human prion disease. In the present study, we validated a commercially available ECL-based a-syn ELISA platform as a diagnostic test for correct classification of sCJD cases. CSF a-syn was analysed in 203 sCJD cases with definite diagnosis and in 445 non-CJD cases. We investigated reproducibility and stability of CSF a-syn and made recommendations for its analysis in the sCJD diagnostic workup. A sensitivity of 98% and a specificity of 97% were achieved when using an optimal cut-off of 820 pg/mL a-syn. Moreover, we were able to show a negative correlation between a-syn levels and disease duration suggesting that CSF a-syn may be a good prognostic marker for sCJD patients. The present study validates the use of a-syn as a CSF biomarker of sCJD and establishes the clinical and pre-analytical parameters for its use in differential diagnosis in clinical routine. Additionally, the current test presents some advantages compared to other diagnostic approaches: it is fast, economic, requires minimal amount of CSF and a-syn levels are stable along disease progression.

Use of 3×2 tables with an intention to diagnose approach to assess clinical performance of diagnostic tests: meta-analytical evaluation of coronary CT angiography studies

PubMed Central

Schuetz, Georg M; Schlattmann, Peter

2012-01-01

Objective To determine whether a 3×2 table, using an intention to diagnose approach, is better than the “classic” 2×2 table at handling transparent reporting and non-evaluable results, when assessing the accuracy of a diagnostic test. Design Based on a systematic search for diagnostic accuracy studies of coronary computed tomography (CT) angiography, full texts of relevant studies were evaluated to determine whether they could calculate an alternative 3×2 table. To quantify an overall effect, we pooled diagnostic accuracy values according to a meta-analytical approach. Data sources Medline (via PubMed), Embase (via Ovid), and ISI Web of Science electronic databases. Eligibility criteria Prospective English or German language studies comparing coronary CT with conventional coronary angiography in all patients and providing sufficient data for a patient level analysis. Results 120 studies (10 287 patients) were eligible. Studies varied greatly in their approaches to handling non-evaluable findings. We found 26 studies (including 2298 patients) that allowed us to calculate both 2×2 tables and 3×2 tables. Using a bivariate random effects model, we compared the 2×2 table with the 3×2 table, and found significant differences for pooled sensitivity (98.2 (95% confidence interval 96.7 to 99.1) v 92.7 (88.5 to 95.3)), area under the curve (0.99 (0.98 to 1.00) v 0.93 (0.91 to 0.95)), positive likelihood ratio (9.1 (6.2 to 13.3) v 4.4 (3.3 to 6.0)), and negative likelihood ratio (0.02 (0.01 to 0.04) v 0.09 (0.06 to 0.15); (P<0.05)). Conclusion Parameters for diagnostic performance significantly decrease if non-evaluable results are included by a 3×2 table for analysis (intention to diagnose approach). This approach provides a more realistic picture of the clinical potential of diagnostic tests. PMID:23097549

Cost of fetal alcohol spectrum disorder diagnosis in Canada.

PubMed

Popova, Svetlana; Lange, Shannon; Burd, Larry; Chudley, Albert E; Clarren, Sterling K; Rehm, Jürgen

2013-01-01

Fetal Alcohol Spectrum Disorder (FASD) is underdiagnosed in Canada. The diagnosis of FASD is not simple and currently, the recommendation is that a comprehensive, multidisciplinary assessment of the individual be done. The purpose of this study was to estimate the annual cost of FASD diagnosis on Canadian society. The diagnostic process breakdown was based on recommendations from the Fetal Alcohol Spectrum Disorder Canadian Guidelines for Diagnosis. The per person cost of diagnosis was calculated based on the number of hours (estimated based on expert opinion) required by each specialist involved in the diagnostic process. The average rate per hour for each respective specialist was estimated based on hourly costs across Canada. Based on the existing clinical capacity of all FASD multidisciplinary clinics in Canada, obtained from the 2005 and 2011 surveys conducted by the Canada Northwest FASD Research Network, the number of FASD cases diagnosed per year in Canada was estimated. The per person cost of FASD diagnosis was then applied to the number of cases diagnosed per year in Canada in order to calculated the overall annual cost. Using the most conservative approach, it was estimated that an FASD evaluation requires 32 to 47 hours for one individual to be screened, referred, admitted, and diagnosed with an FASD diagnosis, which results in a total cost of $3,110 to $4,570 per person. The total cost of FASD diagnostic services in Canada ranges from $3.6 to $5.2 million (lower estimate), up to $5.0 to $7.3 million (upper estimate) per year. As a result of using the most conservative approach, the cost of FASD diagnostic services presented in the current study is most likely underestimated. The reasons for this likelihood and the limitations of the study are discussed.

Evidence-based development of a diagnosis-dependent therapy planning system and its implementation in modern diagnostic software.

PubMed

Ahlers, M O; Jakstat, H A

2005-07-01

The prerequisite for structured individual therapy of craniomandibular dysfunctions is differential diagnostics. Suggestions for the structured recording of findings and their structured evaluation beyond the global diagnosis of "craniomandibular disorders" have been published. Only this structured approach enables computerization of the diagnostic process. The respective software is available for use in practice (CMDcheck for CMD screening, CMDfact for the differential diagnostics). Based on this structured diagnostics, knowledge-based therapy planning is also conceivable. The prerequisite for this would be a model of achieving consensus on the indicated forms of therapy related to the diagnosis. Therefore, a procedure for evidence-based achievement of consensus on suitable forms of therapy in CMD was developed first in multicentric cooperation, and then implemented in corresponding software. The clinical knowledge of experienced specialists was included consciously for the consensus achievement process. At the same time, anonymized mathematical statistical evaluations were used for control and objectification. Different examiners form different departments of several universities working independently of one another assigned the theoretically conceiveable therapeutic alternatives to the already published diagnostic scheme. After anonymization, the correlation of these assignments was then calculated mathematically. For achieving consensus in those cases for which no agreement initally existed, agreement was subsequently arrived at in the course of a consensus conference on the basis of literature evaluations and the discussion of clinical case examples. This consensus in turn finally served as the basis of a therapy planner implemented in the above-mentioned diagnostic software CMDfact. Contributing to quality assurance, the principles of programming this assistant as well as the interface for linking into the diagnostic software are documented and also published here.

Comparison of the Effectiveness of Interactive Didactic Lecture Versus Online Simulation-Based CME Programs Directed at Improving the Diagnostic Capabilities of Primary Care Practitioners.

PubMed

McFadden, Pam; Crim, Andrew

2016-01-01

Diagnostic errors in primary care contribute to increased morbidity and mortality, and billions in costs each year. Improvements in the way practicing physicians are taught so as to optimally perform differential diagnosis can increase patient safety and lower the costs of care. This study represents a comparison of the effectiveness of two approaches to CME training directed at improving the primary care practitioner's diagnostic capabilities against seven common and important causes of joint pain. Using a convenience sampling methodology, one group of primary care practitioners was trained by a traditional live, expert-led, multimedia-based training activity supplemented with interactive practice opportunities and feedback (control group). The second group was trained online with a multimedia-based training activity supplemented with interactive practice opportunities and feedback delivered by an artificial intelligence-driven simulation/tutor (treatment group). Before their respective instructional intervention, there were no significant differences in the diagnostic performance of the two groups against a battery of case vignettes presenting with joint pain. Using the same battery of case vignettes to assess postintervention diagnostic performance, there was a slight but not statistically significant improvement in the control group's diagnostic accuracy (P = .13). The treatment group, however, demonstrated a significant improvement in accuracy (P < .02; Cohen d, effect size = 0.79). These data indicate that within the context of a CME activity, a significant improvement in diagnostic accuracy can be achieved by the use of a web-delivered, multimedia-based instructional activity supplemented by practice opportunities and feedback delivered by an artificial intelligence-driven simulation/tutor.

Multidimensional Diagnostic Criteria for Chronic Pain: Introduction to the ACTTION-American Pain Society Pain Taxonomy (AAPT).

PubMed

Dworkin, Robert H; Bruehl, Stephen; Fillingim, Roger B; Loeser, John D; Terman, Gregory W; Turk, Dennis C

2016-09-01

A variety of approaches have been used to develop diagnostic criteria for chronic pain. The published evidence of the reliability and validity of existing diagnostic criteria is limited, and these criteria have typically not been used in clinical practice. The availability of a widely accepted, consistently applied, and evidence-based taxonomy of diagnostic criteria would improve the quality of clinical research on chronic pain and would be of great value in clinical practice. To address the need for evidence-based diagnostic criteria for the major chronic pain conditions, the Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION) public-private partnership with the US Food and Drug Administration and the American Pain Society (APS) have collaborated on the development of the ACTTION-APS Pain Taxonomy (AAPT). AAPT provides a multidimensional framework that is applied systematically in the development of diagnostic criteria. This article (1) describes the background and rationale for AAPT; (2) presents the AAPT taxonomy and the specific conditions for which diagnostic criteria have been developed (to be published separately); (3) briefly reviews the 5 dimensions that constitute the AAPT multidimensional framework and describes the 7 accompanying articles that discuss these dimensions and other important issues involving AAPT; and (4) provides an overview of next steps, specifically, the general processes by which the initial set of diagnostic criteria (for which the evidence base has been drawn from the literature, systematic reviews, and secondary analyses of existing databases) will undergo additional assessments of reliability and validity. To address the need for evidence-based diagnostic criteria for the major chronic pain conditions, the AAPT provides a multidimensional framework that is applied systematically in the development of diagnostic criteria. The long-term objective of AAPT is to advance the scientific understanding of chronic pain and its treatment. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

Diagnosing Appendicitis: Evidence-Based Review of the Diagnostic Approach in 2014

PubMed Central

Shogilev, Daniel J.; Duus, Nicolaj; Odom, Stephen R.; Shapiro, Nathan I.

2014-01-01

Introduction Acute appendicitis is the most common abdominal emergency requiring emergency surgery. However, the diagnosis is often challenging and the decision to operate, observe or further work-up a patient is often unclear. The utility of clinical scoring systems (namely the Alvarado score), laboratory markers, and the development of novel markers in the diagnosis of appendicitis remains controversial. This article presents an update on the diagnostic approach to appendicitis through an evidence-based review. Methods We performed a broad Medline search of radiological imaging, the Alvarado score, common laboratory markers, and novel markers in patients with suspected appendicitis. Results Computed tomography (CT) is the most accurate mode of imaging for suspected cases of appendicitis, but the associated increase in radiation exposure is problematic. The Alvarado score is a clinical scoring system that is used to predict the likelihood of appendicitis based on signs, symptoms and laboratory data. It can help risk stratify patients with suspected appendicitis and potentially decrease the use of CT imaging in patients with certain Alvarado scores. White blood cell (WBC), C-reactive protein (CRP), granulocyte count and proportion of polymorphonuclear (PMN) cells are frequently elevated in patients with appendicitis, but are insufficient on their own as a diagnostic modality. When multiple markers are used in combination their diagnostic utility is greatly increased. Several novel markers have been proposed to aid in the diagnosis of appendicitis; however, while promising, most are only in the preliminary stages of being studied. Conclusion While CT is the most accurate mode of imaging in suspected appendicitis, the accompanying radiation is a concern. Ultrasound may help in the diagnosis while decreasing the need for CT in certain circumstances. The Alvarado Score has good diagnostic utility at specific cutoff points. Laboratory markers have very limited diagnostic utility on their own but show promise when used in combination. Further studies are warranted for laboratory markers in combination and to validate potential novel markers. PMID:25493136

New ways to develop biosensors towards addressing practical problems

NASA Astrophysics Data System (ADS)

Starodub, N. F.

2013-11-01

The main modern approaches which were realized at the development of new generation of biosensors intended for application in field of diagnostics, food quality control and environmental monitoring are presented. The main attention was paid to creation of the multi-parametrical and multi-functional enzymatic and immune biosensors which were realized for the complex diagnostics of diabetes, autoimmune state and for the control of process of sugar production. The label-free bioaffine devices based on the nano-porouse silicon (NPS) with the registration of specific formed signal by chemiluminescence (ChL) and photoresistivity and intended for the determination mycotoxins and diagnostics of retroviral bovine leukemia (RBL) are analyzed too. Improving of ion sensitive field effect transistors (ISFETs) through changing silicon nitride on the cerium oxide is discussed as perspective approach in case of micotoxins and Salmonella control. In the conclusion the possibility to replace biological sensitive elements by artificial ones is considered.

Synthetic biology platform technologies for antimicrobial applications.

PubMed

Braff, Dana; Shis, David; Collins, James J

2016-10-01

The growing prevalence of antibiotic resistance calls for new approaches in the development of antimicrobial therapeutics. Likewise, improved diagnostic measures are essential in guiding the application of targeted therapies and preventing the evolution of therapeutic resistance. Discovery platforms are also needed to form new treatment strategies and identify novel antimicrobial agents. By applying engineering principles to molecular biology, synthetic biologists have developed platforms that improve upon, supplement, and will perhaps supplant traditional broad-spectrum antibiotics. Efforts in engineering bacteriophages and synthetic probiotics demonstrate targeted antimicrobial approaches that can be fine-tuned using synthetic biology-derived principles. Further, the development of paper-based, cell-free expression systems holds promise in promoting the clinical translation of molecular biology tools for diagnostic purposes. In this review, we highlight emerging synthetic biology platform technologies that are geared toward the generation of new antimicrobial therapies, diagnostics, and discovery channels. Copyright © 2016 Elsevier B.V. All rights reserved.

Recombinase polymerase amplification: Emergence as a critical molecular technology for rapid, low-resource diagnostics.

PubMed

James, Ameh; Macdonald, Joanne

2015-01-01

Isothermal molecular diagnostics are bridging the technology gap between traditional diagnostics and polymerase chain reaction-based methods. These new techniques enable timely and accurate testing, especially in settings where there is a lack of infrastructure to support polymerase chain reaction facilities. Despite this, there is a significant lack of uptake of these technologies in developing countries where they are highly needed. Among these novel isothermal technologies, recombinase polymerase amplification (RPA) holds particular potential for use in developing countries. This rapid nucleic acid amplification approach is fast, highly sensitive and specific, and amenable to countries with a high burden of infectious diseases. Implementation of RPA technology in developing countries is critically required to assess limitations and potentials of the diagnosis of infectious disease, and may help identify impediments that prevent adoption of new molecular technologies in low resource- and low skill settings. This review focuses on approaching diagnosis of infectious disease with RPA.

Synthetic biology devices for in vitro and in vivo diagnostics.

PubMed

Slomovic, Shimyn; Pardee, Keith; Collins, James J

2015-11-24

There is a growing need to enhance our capabilities in medical and environmental diagnostics. Synthetic biologists have begun to focus their biomolecular engineering approaches toward this goal, offering promising results that could lead to the development of new classes of inexpensive, rapidly deployable diagnostics. Many conventional diagnostics rely on antibody-based platforms that, although exquisitely sensitive, are slow and costly to generate and cannot readily confront rapidly emerging pathogens or be applied to orphan diseases. Synthetic biology, with its rational and short design-to-production cycles, has the potential to overcome many of these limitations. Synthetic biology devices, such as engineered gene circuits, bring new capabilities to molecular diagnostics, expanding the molecular detection palette, creating dynamic sensors, and untethering reactions from laboratory equipment. The field is also beginning to move toward in vivo diagnostics, which could provide near real-time surveillance of multiple pathological conditions. Here, we describe current efforts in synthetic biology, focusing on the translation of promising technologies into pragmatic diagnostic tools and platforms.

Synthetic biology devices for in vitro and in vivo diagnostics

PubMed Central

Slomovic, Shimyn; Pardee, Keith; Collins, James J.

2015-01-01

There is a growing need to enhance our capabilities in medical and environmental diagnostics. Synthetic biologists have begun to focus their biomolecular engineering approaches toward this goal, offering promising results that could lead to the development of new classes of inexpensive, rapidly deployable diagnostics. Many conventional diagnostics rely on antibody-based platforms that, although exquisitely sensitive, are slow and costly to generate and cannot readily confront rapidly emerging pathogens or be applied to orphan diseases. Synthetic biology, with its rational and short design-to-production cycles, has the potential to overcome many of these limitations. Synthetic biology devices, such as engineered gene circuits, bring new capabilities to molecular diagnostics, expanding the molecular detection palette, creating dynamic sensors, and untethering reactions from laboratory equipment. The field is also beginning to move toward in vivo diagnostics, which could provide near real-time surveillance of multiple pathological conditions. Here, we describe current efforts in synthetic biology, focusing on the translation of promising technologies into pragmatic diagnostic tools and platforms. PMID:26598662

Enhancing malaria diagnosis through microfluidic cell enrichment and magnetic resonance relaxometry detection

NASA Astrophysics Data System (ADS)

Fook Kong, Tian; Ye, Weijian; Peng, Weng Kung; Wei Hou, Han; Marcos; Preiser, Peter Rainer; Nguyen, Nam-Trung; Han, Jongyoon

2015-06-01

Despite significant advancements over the years, there remains an urgent need for low cost diagnostic approaches that allow for rapid, reliable and sensitive detection of malaria parasites in clinical samples. Our previous work has shown that magnetic resonance relaxometry (MRR) is a potentially highly sensitive tool for malaria diagnosis. A key challenge for making MRR based malaria diagnostics suitable for clinical testing is the fact that MRR baseline fluctuation exists between individuals, making it difficult to detect low level parasitemia. To overcome this problem, it is important to establish the MRR baseline of each individual while having the ability to reliably determine any changes that are caused by the infection of malaria parasite. Here we show that an approach that combines the use of microfluidic cell enrichment with a saponin lysis before MRR detection can overcome these challenges and provide the basis for a highly sensitive and reliable diagnostic approach of malaria parasites. Importantly, as little as 0.0005% of ring stage parasites can be detected reliably, making this ideally suited for the detection of malaria parasites in peripheral blood obtained from patients. The approaches used here are envisaged to provide a new malaria diagnosis solution in the near future.

Polar bear encephalitis: establishment of a comprehensive next-generation pathogen analysis pipeline for captive and free-living wildlife.

PubMed

Szentiks, C A; Tsangaras, K; Abendroth, B; Scheuch, M; Stenglein, M D; Wohlsein, P; Heeger, F; Höveler, R; Chen, W; Sun, W; Damiani, A; Nikolin, V; Gruber, A D; Grobbel, M; Kalthoff, D; Höper, D; Czirják, G Á; Derisi, J; Mazzoni, C J; Schüle, A; Aue, A; East, M L; Hofer, H; Beer, M; Osterrieder, N; Greenwood, A D

2014-05-01

This report describes three possibly related incidences of encephalitis, two of them lethal, in captive polar bears (Ursus maritimus). Standard diagnostic methods failed to identify pathogens in any of these cases. A comprehensive, three-stage diagnostic 'pipeline' employing both standard serological methods and new DNA microarray and next generation sequencing-based diagnostics was developed, in part as a consequence of this initial failure. This pipeline approach illustrates the strengths, weaknesses and limitations of these tools in determining pathogen caused deaths in non-model organisms such as wildlife species and why the use of a limited number of diagnostic tools may fail to uncover important wildlife pathogens. Copyright © 2013 Elsevier Ltd. All rights reserved.

Development and Testing of an LED-Based Near-Infrared Sensor for Human Kidney Tumor Diagnostics

PubMed Central

Zabarylo, Urszula; Kirsanov, Dmitry; Belikova, Valeria; Ageev, Vladimir; Usenov, Iskander; Galyanin, Vladislav; Minet, Olaf; Sakharova, Tatiana; Danielyan, Georgy; Feliksberger, Elena; Artyushenko, Viacheslav

2017-01-01

Optical spectroscopy is increasingly used for cancer diagnostics. Tumor detection feasibility in human kidney samples using mid- and near-infrared (NIR) spectroscopy, fluorescence spectroscopy, and Raman spectroscopy has been reported (Artyushenko et al., Spectral fiber sensors for cancer diagnostics in vitro. In Proceedings of the European Conference on Biomedical Optics, Munich, Germany, 21–25 June 2015). In the present work, a simplification of the NIR spectroscopic analysis for cancer diagnostics was studied. The conventional high-resolution NIR spectroscopic method of kidney tumor diagnostics was replaced by a compact optical sensing device constructively represented by a set of four light-emitting diodes (LEDs) at selected wavelengths and one detecting photodiode. Two sensor prototypes were tested using 14 in vitro clinical samples of 7 different patients. Statistical data evaluation using principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) confirmed the general applicability of the LED-based sensing approach to kidney tumor detection. An additional validation of the results was performed by means of sample permutation. PMID:28825612

A modern diagnostic approach for automobile systems condition monitoring

NASA Astrophysics Data System (ADS)

Selig, M.; Shi, Z.; Ball, A.; Schmidt, K.

2012-05-01

An important topic in automotive research and development is the area of active and passive safety systems. In general, it is grouped in active safety systems to prevent accidents and passive systems to reduce the impact of a crash. An example for an active system is ABS while a seat belt tensioner represents the group of passive systems. Current developments in the automotive industry try to link active with passive system components to enable a complete event sequence, beginning with the warning of the driver about a critical situation till the automatic emergency call after an accident. The cross-linking has an impact on the current diagnostic approach, which is described in this paper. Therefore, this contribution introduces a new diagnostic approach for automotive mechatronic systems. The concept is based on monitoring the messages which are exchanged via the automotive communication systems, e.g. the CAN bus. According to the authors' assumption, the messages on the bus are changing between faultless and faulty vehicle condition. The transmitted messages of the sensors and control units are different depending on the condition of the car. First experiments are carried and in addition, the hardware design of a suitable diagnostic interface is presented. Finally, first results will be presented and discussed.

[The history of schizophrenias: philosophical roots].

PubMed

Musalek, M

2005-11-01

Although the term "schizophrenia" has been introduced in medical usage by E. Bleuler, all variations of schizophrenia developed afterwards trace back to E. Kraepelin. In his work on dementia praecox he intended to discover a yet unknown entity from nature definitely following the principles and maxima of positivism. In the following a great number of different concepts of schizophrenia were developed and the psychiatrist of the seventies and eighties of the last century was left confronted with an abundance of varying schizophrenic criteria. The upcoming globalization in diagnostic stopped this process of diversity and the ideas of Kraepelin reappeared in the ICD-10 criteria for schizophrenia with only a few modifications. The main problem of positivistic research approaches is that nature obviously is completely unimpressed by human made principles of rules and systems. Nature itself does not know these forms and categories invented by human beings. That is one of the reasons why positivistic schizophrenic research considering human made categories as natural has not been quite successful. A possible way out of this diagnostic dilemma -- insufficient categorical classification systems on the one hand and the necessity of apprehending psychopathological phenomena for an effective therapy on the other -- can be a change of paradigms from the usual categorical diagnostics based on the maxima of positivism to dimensional diagnostics developed in the frame of post-modern strategies of thinking. Such process-oriented diagnostic approaches considering the singular phenomenon as well as its significance for the individual and its pathogenesis as main foci of diagnostics provide the possibility for post-modern psychiatrists to start a new dialogue overcoming a positivism based monologue made by experts on the sufferers.

The diagnostic plot analysis of artesian aquifers with case studies in Table Mountain Group of South Africa

NASA Astrophysics Data System (ADS)

Sun, Xiaobin; Xu, Yongxin; Lin, Lixiang

2015-05-01

Parameter estimates of artesian aquifers where piezometric head is above ground level are largely made through free-flowing and recovery tests. The straight-line method proposed by Jacob-Lohman is often used for interpretation of flow rate measured at flowing artesian boreholes. However, the approach fails to interpret the free-flowing test data from two artesian boreholes in the fractured-rock aquifer in Table Mountain Group (TMG) of South Africa. The diagnostic plot method using the reciprocal rate derivative is adapted to evaluate the artesian aquifer properties. The variation of the derivative helps not only identify flow regimes and discern the boundary conditions, but also facilitates conceptualization of the aquifer system and selection of an appropriate model for data interpretation later on. Test data from two free-flowing tests conducted in different sites in TMG are analysed using the diagnostic plot method. Based on the results, conceptual models and appropriate approaches are developed to evaluate the aquifer properties. The advantages and limitations of using the diagnostic plot method on free-flowing test data are discussed.

Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty: STRUCTURAL UNCERTAINTY DIAGNOSTICS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moges, Edom; Demissie, Yonas; Li, Hong-Yi

2016-04-01

In most water resources applications, a single model structure might be inadequate to capture the dynamic multi-scale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integratemore » expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses are used to assess the presence of multiple dominant processes and the adequacy of a single model, as well as to identify the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. The results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas, the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.« less

Feasibility of Self-Reflection as a Tool to Balance Clinical Reasoning Strategies

ERIC Educational Resources Information Center

Sibbald, Matthew; de Bruin, Anique B. H.

2012-01-01

Clinicians are believed to use two predominant reasoning strategies: system 1 based pattern recognition, and system 2 based analytical reasoning. Balancing these cognitive reasoning strategies is widely believed to reduce diagnostic error. However, clinicians approach different problems with different reasoning strategies. This study explores…

Internet gaming disorder: Inadequate diagnostic criteria wrapped in a constraining conceptual model.

PubMed

Starcevic, Vladan

2017-06-01

Background and aims The paper "Chaos and confusion in DSM-5 diagnosis of Internet Gaming Disorder: Issues, concerns, and recommendations for clarity in the field" by Kuss, Griffiths, and Pontes (in press) critically examines the DSM-5 diagnostic criteria for Internet gaming disorder (IGD) and addresses the issue of whether IGD should be reconceptualized as gaming disorder, regardless of whether video games are played online or offline. This commentary provides additional critical perspectives on the concept of IGD. Methods The focus of this commentary is on the addiction model on which the concept of IGD is based, the nature of the DSM-5 criteria for IGD, and the inclusion of withdrawal symptoms and tolerance as the diagnostic criteria for IGD. Results The addiction framework on which the DSM-5 concept of IGD is based is not without problems and represents only one of multiple theoretical approaches to problematic gaming. The polythetic, non-hierarchical DSM-5 diagnostic criteria for IGD make the concept of IGD unacceptably heterogeneous. There is no support for maintaining withdrawal symptoms and tolerance as the diagnostic criteria for IGD without their substantial revision. Conclusions The addiction model of IGD is constraining and does not contribute to a better understanding of the various patterns of problematic gaming. The corresponding diagnostic criteria need a thorough overhaul, which should be based on a model of problematic gaming that can accommodate its disparate aspects.

A new nanostructured Silicon biosensor for diagnostics of bovine leucosis

NASA Astrophysics Data System (ADS)

Luchenko, A. I.; Melnichenko, M. M.; Starodub, N. F.; Shmyryeva, O. M.

2010-08-01

In this report we propose a new instrumental method for the biochemical diagnostics of the bovine leucosis through the registration of the formation of the specific immune complex (antigen-antibody) with the help of biosensor based on the nano-structured silicon. The principle of the measurements is based on the determination of the photosensitivity of the surface. In spite of the existed traditional methods of the biochemical diagnostics of the bovine leucosis the proposed approach may provide the express control of the milk quality as direct on the farm and during the process raw materials. The proposed variant of the biosensor based on the nano-structured silicon may be applied for the determination of the concentration of different substances which may form the specific complex in the result of the bioaffine reactions. A new immune technique based on the nanostructured silicon and intended for the quantitative determination of some toxic substances is offered. The sensitivity of such biosensor allows determining T-2 mycotoxin at the concentration of 10 ng/ml during several minutes.

High-throughput microarray technology in diagnostics of enterobacteria based on genome-wide probe selection and regression analysis.

PubMed

Friedrich, Torben; Rahmann, Sven; Weigel, Wilfried; Rabsch, Wolfgang; Fruth, Angelika; Ron, Eliora; Gunzer, Florian; Dandekar, Thomas; Hacker, Jörg; Müller, Tobias; Dobrindt, Ulrich

2010-10-21

The Enterobacteriaceae comprise a large number of clinically relevant species with several individual subspecies. Overlapping virulence-associated gene pools and the high overall genome plasticity often interferes with correct enterobacterial strain typing and risk assessment. Array technology offers a fast, reproducible and standardisable means for bacterial typing and thus provides many advantages for bacterial diagnostics, risk assessment and surveillance. The development of highly discriminative broad-range microbial diagnostic microarrays remains a challenge, because of marked genome plasticity of many bacterial pathogens. We developed a DNA microarray for strain typing and detection of major antimicrobial resistance genes of clinically relevant enterobacteria. For this purpose, we applied a global genome-wide probe selection strategy on 32 available complete enterobacterial genomes combined with a regression model for pathogen classification. The discriminative power of the probe set was further tested in silico on 15 additional complete enterobacterial genome sequences. DNA microarrays based on the selected probes were used to type 92 clinical enterobacterial isolates. Phenotypic tests confirmed the array-based typing results and corroborate that the selected probes allowed correct typing and prediction of major antibiotic resistances of clinically relevant Enterobacteriaceae, including the subspecies level, e.g. the reliable distinction of different E. coli pathotypes. Our results demonstrate that the global probe selection approach based on longest common factor statistics as well as the design of a DNA microarray with a restricted set of discriminative probes enables robust discrimination of different enterobacterial variants and represents a proof of concept that can be adopted for diagnostics of a wide range of microbial pathogens. Our approach circumvents misclassifications arising from the application of virulence markers, which are highly affected by horizontal gene transfer. Moreover, a broad range of pathogens have been covered by an efficient probe set size enabling the design of high-throughput diagnostics.

Predicting the Reasons of Customer Complaints: A First Step Toward Anticipating Quality Issues of In Vitro Diagnostics Assays with Machine Learning.

PubMed

Aris-Brosou, Stephane; Kim, James; Li, Li; Liu, Hui

2018-05-15

Vendors in the health care industry produce diagnostic systems that, through a secured connection, allow them to monitor performance almost in real time. However, challenges exist in analyzing and interpreting large volumes of noisy quality control (QC) data. As a result, some QC shifts may not be detected early enough by the vendor, but lead a customer to complain. The aim of this study was to hypothesize that a more proactive response could be designed by utilizing the collected QC data more efficiently. Our aim is therefore to help prevent customer complaints by predicting them based on the QC data collected by in vitro diagnostic systems. QC data from five select in vitro diagnostic assays were combined with the corresponding database of customer complaints over a period of 90 days. A subset of these data over the last 45 days was also analyzed to assess how the length of the training period affects predictions. We defined a set of features used to train two classifiers, one based on decision trees and the other based on adaptive boosting, and assessed model performance by cross-validation. The cross-validations showed classification error rates close to zero for some assays with adaptive boosting when predicting the potential cause of customer complaints. Performance was improved by shortening the training period when the volume of complaints increased. Denoising filters that reduced the number of categories to predict further improved performance, as their application simplified the prediction problem. This novel approach to predicting customer complaints based on QC data may allow the diagnostic industry, the expected end user of our approach, to proactively identify potential product quality issues and fix these before receiving customer complaints. This represents a new step in the direction of using big data toward product quality improvement. ©Stephane Aris-Brosou, James Kim, Li Li, Hui Liu. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 15.05.2018.

Predicting the Reasons of Customer Complaints: A First Step Toward Anticipating Quality Issues of In Vitro Diagnostics Assays with Machine Learning

PubMed Central

Kim, James; Li, Li; Liu, Hui

2018-01-01

Background Vendors in the health care industry produce diagnostic systems that, through a secured connection, allow them to monitor performance almost in real time. However, challenges exist in analyzing and interpreting large volumes of noisy quality control (QC) data. As a result, some QC shifts may not be detected early enough by the vendor, but lead a customer to complain. Objective The aim of this study was to hypothesize that a more proactive response could be designed by utilizing the collected QC data more efficiently. Our aim is therefore to help prevent customer complaints by predicting them based on the QC data collected by in vitro diagnostic systems. Methods QC data from five select in vitro diagnostic assays were combined with the corresponding database of customer complaints over a period of 90 days. A subset of these data over the last 45 days was also analyzed to assess how the length of the training period affects predictions. We defined a set of features used to train two classifiers, one based on decision trees and the other based on adaptive boosting, and assessed model performance by cross-validation. Results The cross-validations showed classification error rates close to zero for some assays with adaptive boosting when predicting the potential cause of customer complaints. Performance was improved by shortening the training period when the volume of complaints increased. Denoising filters that reduced the number of categories to predict further improved performance, as their application simplified the prediction problem. Conclusions This novel approach to predicting customer complaints based on QC data may allow the diagnostic industry, the expected end user of our approach, to proactively identify potential product quality issues and fix these before receiving customer complaints. This represents a new step in the direction of using big data toward product quality improvement. PMID:29764796

Exhaled Breath Markers for Nonimaging and Noninvasive Measures for Detection of Multiple Sclerosis.

PubMed

Broza, Yoav Y; Har-Shai, Lior; Jeries, Raneen; Cancilla, John C; Glass-Marmor, Lea; Lejbkowicz, Izabella; Torrecilla, José S; Yao, Xuelin; Feng, Xinliang; Narita, Akimitsu; Müllen, Klaus; Miller, Ariel; Haick, Hossam

2017-11-15

Multiple sclerosis (MS) is the most common chronic neurological disease affecting young adults. MS diagnosis is based on clinical characteristics and confirmed by examination of the cerebrospinal fluids (CSF) or by magnetic resonance imaging (MRI) of the brain or spinal cord or both. However, neither of the current diagnostic procedures are adequate as a routine tool to determine disease state. Thus, diagnostic biomarkers are needed. In the current study, a novel approach that could meet these expectations is presented. The approach is based on noninvasive analysis of volatile organic compounds (VOCs) in breath. Exhaled breath was collected from 204 participants, 146 MS and 58 healthy control individuals. Analysis was performed by gas-chromatography mass-spectrometry (GC-MS) and nanomaterial-based sensor array. Predictive models were derived from the sensors, using artificial neural networks (ANNs). GC-MS analysis revealed significant differences in VOC abundance between MS patients and controls. Sensor data analysis on training sets was able to discriminate in binary comparisons between MS patients and controls with accuracies up to 90%. Blinded sets showed 95% positive predictive value (PPV) between MS-remission and control, 100% sensitivity with 100% negative predictive value (NPV) between MS not-treated (NT) and control, and 86% NPV between relapse and control. Possible links between VOC biomarkers and the MS pathogenesis were established. Preliminary results suggest the applicability of a new nanotechnology-based method for MS diagnostics.

Converging Human and Malaria Vector Diagnostics with Data Management towards an Integrated Holistic One Health Approach.

PubMed

Mitsakakis, Konstantinos; Hin, Sebastian; Müller, Pie; Wipf, Nadja; Thomsen, Edward; Coleman, Michael; Zengerle, Roland; Vontas, John; Mavridis, Konstantinos

2018-02-03

Monitoring malaria prevalence in humans, as well as vector populations, for the presence of Plasmodium , is an integral component of effective malaria control, and eventually, elimination. In the field of human diagnostics, a major challenge is the ability to define, precisely, the causative agent of fever, thereby differentiating among several candidate (also non-malaria) febrile diseases. This requires genetic-based pathogen identification and multiplexed analysis, which, in combination, are hardly provided by the current gold standard diagnostic tools. In the field of vectors, an essential component of control programs is the detection of Plasmodium species within its mosquito vectors, particularly in the salivary glands, where the infective sporozoites reside. In addition, the identification of species composition and insecticide resistance alleles within vector populations is a primary task in routine monitoring activities, aiming to support control efforts. In this context, the use of converging diagnostics is highly desirable for providing comprehensive information, including differential fever diagnosis in humans, and mosquito species composition, infection status, and resistance to insecticides of vectors. Nevertheless, the two fields of human diagnostics and vector control are rarely combined, both at the diagnostic and at the data management end, resulting in fragmented data and mis- or non-communication between various stakeholders. To this direction, molecular technologies, their integration in automated platforms, and the co-assessment of data from multiple diagnostic sources through information and communication technologies are possible pathways towards a unified human vector approach.

Converging Human and Malaria Vector Diagnostics with Data Management towards an Integrated Holistic One Health Approach

PubMed Central

Mitsakakis, Konstantinos; Hin, Sebastian; Wipf, Nadja; Coleman, Michael; Zengerle, Roland; Vontas, John; Mavridis, Konstantinos

2018-01-01

Monitoring malaria prevalence in humans, as well as vector populations, for the presence of Plasmodium, is an integral component of effective malaria control, and eventually, elimination. In the field of human diagnostics, a major challenge is the ability to define, precisely, the causative agent of fever, thereby differentiating among several candidate (also non-malaria) febrile diseases. This requires genetic-based pathogen identification and multiplexed analysis, which, in combination, are hardly provided by the current gold standard diagnostic tools. In the field of vectors, an essential component of control programs is the detection of Plasmodium species within its mosquito vectors, particularly in the salivary glands, where the infective sporozoites reside. In addition, the identification of species composition and insecticide resistance alleles within vector populations is a primary task in routine monitoring activities, aiming to support control efforts. In this context, the use of converging diagnostics is highly desirable for providing comprehensive information, including differential fever diagnosis in humans, and mosquito species composition, infection status, and resistance to insecticides of vectors. Nevertheless, the two fields of human diagnostics and vector control are rarely combined, both at the diagnostic and at the data management end, resulting in fragmented data and mis- or non-communication between various stakeholders. To this direction, molecular technologies, their integration in automated platforms, and the co-assessment of data from multiple diagnostic sources through information and communication technologies are possible pathways towards a unified human vector approach. PMID:29401670

ADIPOSITY-BASED CHRONIC DISEASE AS A NEW DIAGNOSTIC TERM: THE AMERICAN ASSOCIATION OF CLINICAL ENDOCRINOLOGISTS AND AMERICAN COLLEGE OF ENDOCRINOLOGY POSITION STATEMENT.

PubMed

Mechanick, Jeffrey I; Hurley, Daniel L; Garvey, W Timothy

2017-03-01

The American Association of Clinical Endocrinologists (AACE) and American College of Endocrinology (ACE) have created a chronic care model, advanced diagnostic framework, clinical practice guidelines, and clinical practice algorithm for the comprehensive management of obesity. This coordinated effort is not solely based on body mass index as in previous models, but emphasizes a complications-centric approach that primarily determines therapeutic decisions and desired outcomes. Adiposity-Based Chronic Disease (ABCD) is a new diagnostic term for obesity that explicitly identifies a chronic disease, alludes to a precise pathophysiologic basis, and avoids the stigmata and confusion related to the differential use and multiple meanings of the term "obesity." Key elements to further the care of patients using this new ABCD term are: (1) positioning lifestyle medicine in the promotion of overall health, not only as the first algorithmic step, but as the central, pervasive action; (2) standardizing protocols that comprehensively and durably address weight loss and management of adiposity-based complications; (3) approaching patient care through contextualization (e.g., primordial prevention to decrease obesogenic environmental risk factors and transculturalization to adapt evidence-based recommendations for different ethnicities, cultures, and socio-economics); and lastly, (4) developing evidence-based strategies for successful implementation, monitoring, and optimization of patient care over time. This AACE/ACE blueprint extends current work and aspires to meaningfully improve both individual and population health by presenting a new ABCD term for medical diagnostic purposes, use in a complications-centric management and staging strategy, and precise reference to the obesity chronic disease state, divested from counterproductive stigmata and ambiguities found in the general public sphere. AACE = American Association of Clinical Endocrinologists ABCD = Adiposity-Based Chronic Disease ACE = American College of Endocrinology BMI = body mass index CPG = clinical practice guidelines HCP = health care professionals.

Can the Diagnostics of Triangular Fibrocartilage Complex Lesions Be Improved by MRI-Based Soft-Tissue Reconstruction? An Imaging-Based Workup and Case Presentation.

PubMed

Hammer, Niels; Hirschfeld, Ulrich; Strunz, Hendrik; Werner, Michael; Wolfskämpf, Thomas; Löffler, Sabine

2017-01-01

Introduction . The triangular fibrocartilage complex (TFCC) provides both mobility and stability of the radiocarpal joint. TFCC lesions are difficult to diagnose due to the complex anatomy. The standard treatment for TFCC lesions is arthroscopy, posing surgery-related risks onto the patients. This feasibility study aimed at developing a workup for soft-tissue reconstruction using clinical imaging, to verify these results in retrospective patient data. Methods . Microcomputed tomography ( μ -CT), 3 T magnetic resonance imaging (MRI), and plastination were used to visualize the TFCC in cadaveric specimens applying segmentation-based 3D reconstruction. This approach further trialed the MRI dataset of a patient with minor radiological TFCC alterations but persistent pain. Results . TFCC reconstruction was impossible using μ -CT only but feasible using MRI, resulting in an appreciation of its substructures, as seen in the plastinates. Applying this approach allowed for visualizing a Palmer 2C lesion in a patient, confirming ex postum the arthroscopy findings, being markedly different from MRI (Palmer 1B). Discussion . This preliminary study showed that image-based TFCC reconstruction may help to identify pathologies invisible in standard MRI. The combined approach of μ -CT, MRI, and plastination allowed for a three-dimensional appreciation of the TFCC. Image quality and time expenditure limit the approach's usefulness as a diagnostic tool.

Can the Diagnostics of Triangular Fibrocartilage Complex Lesions Be Improved by MRI-Based Soft-Tissue Reconstruction? An Imaging-Based Workup and Case Presentation

PubMed Central

Hirschfeld, Ulrich; Strunz, Hendrik; Werner, Michael; Wolfskämpf, Thomas; Löffler, Sabine

2017-01-01

Introduction. The triangular fibrocartilage complex (TFCC) provides both mobility and stability of the radiocarpal joint. TFCC lesions are difficult to diagnose due to the complex anatomy. The standard treatment for TFCC lesions is arthroscopy, posing surgery-related risks onto the patients. This feasibility study aimed at developing a workup for soft-tissue reconstruction using clinical imaging, to verify these results in retrospective patient data. Methods. Microcomputed tomography (μ-CT), 3 T magnetic resonance imaging (MRI), and plastination were used to visualize the TFCC in cadaveric specimens applying segmentation-based 3D reconstruction. This approach further trialed the MRI dataset of a patient with minor radiological TFCC alterations but persistent pain. Results. TFCC reconstruction was impossible using μ-CT only but feasible using MRI, resulting in an appreciation of its substructures, as seen in the plastinates. Applying this approach allowed for visualizing a Palmer 2C lesion in a patient, confirming ex postum the arthroscopy findings, being markedly different from MRI (Palmer 1B). Discussion. This preliminary study showed that image-based TFCC reconstruction may help to identify pathologies invisible in standard MRI. The combined approach of μ-CT, MRI, and plastination allowed for a three-dimensional appreciation of the TFCC. Image quality and time expenditure limit the approach's usefulness as a diagnostic tool. PMID:28246600

Diagnostic decision-making and strategies to improve diagnosis.

PubMed

Thammasitboon, Satid; Cutrer, William B

2013-10-01

A significant portion of diagnostic errors arises through cognitive errors resulting from inadequate knowledge, faulty data gathering, and/or faulty verification. Experts estimate that 75% of diagnostic failures can be attributed to clinician diagnostic thinking failure. The cognitive processes that underlie diagnostic thinking of clinicians are complex and intriguing, and it is imperative that clinicians acquire explicit appreciation and application of different cognitive approaches to make decisions better. A dual-process model that unifies many theories of decision-making has emerged as a promising template for understanding how clinicians think and judge efficiently in a diagnostic reasoning process. The identification and implementation of strategies for decreasing or preventing such diagnostic errors has become a growing area of interest and research. Suggested strategies to decrease diagnostic error incidence include increasing clinician's clinical expertise and avoiding inherent cognitive errors to make decisions better. Implementing Interventions focused solely on avoiding errors may work effectively for patient safety issues such as medication errors. Addressing cognitive errors, however, requires equal effort on expanding the individual clinician's expertise. Providing cognitive support to clinicians for robust diagnostic decision-making serves as the final strategic target for decreasing diagnostic errors. Clinical guidelines and algorithms offer another method for streamlining decision-making and decreasing likelihood of cognitive diagnostic errors. Addressing cognitive processing errors is undeniably the most challenging task in reducing diagnostic errors. While many suggested approaches exist, they are mostly based on theories and sciences in cognitive psychology, decision-making, and education. The proposed interventions are primarily suggestions and very few of them have been tested in the actual practice settings. Collaborative research effort is required to effectively address cognitive processing errors. Researchers in various areas, including patient safety/quality improvement, decision-making, and problem solving, must work together to make medical diagnosis more reliable. © 2013 Mosby, Inc. All rights reserved.

Prognostic relevance of motor talent predictors in early adolescence: A group- and individual-based evaluation considering different levels of achievement in youth football.

PubMed

Höner, Oliver; Votteler, Andreas

2016-12-01

In the debate about the usefulness of motor diagnostics in the talent identification process, the prognostic validity for tests conducted in early adolescence is of critical interest. Using a group- and individual-based statistical approach, this prospective cohort study evaluated a nationwide assessment of speed abilities and technical skills regarding its relevance for future achievement levels. The sample consisted of 22,843 U12-players belonging to the top 4% in German football. The U12-results in five tests served as predictors for players' selection levels in U16-U19 (youth national team, regional association, youth academy, not selected). Group-mean differences proved the prognostic relevance for all predictors. Low individual selection probabilities demonstrated limited predictive values, while excellent test results proved their particular prognostic relevance. Players scoring percentile ranks (PRs) ≥ 99 had a 12 times higher chance to become youth national team players than players scoring PR < 99. Simulating increasing score cut-off values not only enhanced specificity (correctly identified non-talents) but also led to lower sensitivity (loss of talents). Extending the current research, these different approaches revealed the ambiguity of the diagnostics' prognostic relevance, representing both the usefulness and several pitfalls of nationwide diagnostics. Therefore, the present diagnostics can support but not substitute for coaches' subjective decisions for talent identification, and multidisciplinary designs are required.

[The advantage of a modern operational approach to the diagnosis of mental disorders. The case of the Bavarian King Ludwig II--an example from biographical research].

PubMed

von Zerssen, D

2013-05-01

Worldwide discrepancies in the classification, terminology and diagnosis of mental disorders have induced efforts for unification after World War II. This led to the introduction of an operational diagnostic approach according to strict criteria, at the same time taking into account the comorbidity of disorders. However, this approach is still not routinely used. The consequences of this deficiency are demonstrated here by an example from biographical research referring to the Bavarian King Ludwig II. The study is based on an extensive search of the relevant literature. Although the pathography of this Bavarian king is well documented, the diagnoses published between 1910 and 2010 by altogether 21 specialists, are distributed rather chaotically over 24 diagnostic categories of the ICD-10. Merely in the (probably wrong) diagnosis of a schizophrenic psychosis is there agreement among half of the authors. This is concordant with the expert diagnosis of paranoia by von Gudden and his colleagues (1886) when considering the then contemporary concept of the disorder. According to modern diagnostic principles almost half of the 24 diagnoses can be confirmed. The others have to be regarded as false diagnoses. The conclusion is that modern principles of the diagnosis of mental disorders should be applied according to internationally accepted diagnostic manuals. This approach should be used in, but is not exclusive to, biographical research. Precondition is, of course, the exact knowledge and careful application of these principles.

Spontaneous Raman Scattering Diagnostics: Applications in Practical Combustion Systems. Chapter 5

NASA Technical Reports Server (NTRS)

Kojima, Jun; Viet-Nguyen, Quang; Lackner, Maximilian (Editor); Winter, Franz (Editor); Agarwal, Avinash (Editor)

2010-01-01

In this chapter, the recent advancements and practical aspects of laser SRS diagnostics have been reviewed wi til regards to applications in practical combustion systems. Clearly, SRS represents a theoretically and experimentally mature diagnostic technology that has become an essential tool for multiscalar measurements in turbulent combustion at elevated pressures. Today, time-, space-, spectrally, and even polarization-resolved S RS diagnostics is at hand, with aid from recent innovations in theoretical and technological developments on electro-optical or electromechanical devices. Whilst a linear increase in SRS signals can be expected in high-pressure systems (this is perhaps one of the most important advantages for using SRS in high-pressure systems), there are practical (often severe) restrictions associated with pressurized vessels, due mainly to the limited degree of optical access. This narrows ti,e available choice of diagnostics that can be employed at any given time. Point-wise SRS diagnostics provides the highest accuracy on the chemical species and temperature measurements, and will continue to remain a vital approach for the study in such harsh environments. The practical design considerations and hands-on set-up guide for SRS diagnostics provided in this chapter are rarely presented elsewhere. Although the second-harmonic Nd:YAG pulsed laser (532 nm), combined with pulse-stretching optics or the recently introduced White Cell-based laser, seems to be the most favored excitation source of choice by the research community, UV excitation will undoubtedly continue to be used on many occasions, and especially in sooting flames. Detection methods may be divided into ICCD-based nanosecond-gate detection or a rotary-chopper electromechanical shutter-based CCD array detection, and the levels of background flame emission in individual cases would determine this critical design choice. Here, a process of Raman signal calibration based on ti,e crosstalk matrix formalism was explained step-by-step. As tI,is process may be very time-consuming and expensive, a well-planned experimental approach (01' building a transferable calibration database or library (at least with in a user's own facility over a series of different testing and runs) is vitally important. Hands on advice on the design and construction of flow control systems for high pressure burner facilities were also presented.

Intraoral fiber-optic-based diagnostic for periodontal disease

NASA Astrophysics Data System (ADS)

Colston, Bill W., Jr.; Gutierrez, Dora M.; Everett, Matthew J.; Brown, Steve B.; Langry, Kevin C.; Cox, Weldon R.; Johnson, Paul W.; Roe, Jeffrey N.

2000-05-01

The purpose of this initial study was to begin development of a new, objective diagnostic instrument that will allow simultaneous quantitation of multiple proteases within a single periodontal pocket using a chemical fiber optic senor. This approach could potentially be adapted to use specific antibodies and chemiluminescence to detect and quantitate virtually any compound and compare concentrations of different compounds within the same periodontal pocket. The device could also be used to assay secretions in salivary ducts or from a variety of wounds. The applicability is, therefore, not solely limited to dentistry and the device would be important both for clinical diagnostics and as a research too.

Computer-assisted education and interdisciplinary breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Whatmough, Pamela; Gale, Alastair G.; Wilson, A. R. M.

1996-04-01

The diagnosis of breast disease for screening or symptomatic women is largely arrived at by a multi-disciplinary team. We report work on the development and assessment of an inter- disciplinary computer based learning system to support the diagnosis of this disease. The diagnostic process is first modelled from different viewpoints and then appropriate knowledge structures pertinent to the domains of radiologist, pathologist and surgeon are depicted. Initially the underlying inter-relationships of the mammographic diagnostic approach were detailed which is largely considered here. Ultimately a system is envisaged which will link these specialties and act as a diagnostic aid as well as a multi-media educational system.

Tissue microarrays and quantitative tissue-based image analysis as a tool for oncology biomarker and diagnostic development.

PubMed

Dolled-Filhart, Marisa P; Gustavson, Mark D

2012-11-01

Translational oncology has been improved by using tissue microarrays (TMAs), which facilitate biomarker analysis of large cohorts on a single slide. This has allowed for rapid analysis and validation of potential biomarkers for prognostic and predictive value, as well as for evaluation of biomarker prevalence. Coupled with quantitative analysis of immunohistochemical (IHC) staining, objective and standardized biomarker data from tumor samples can further advance companion diagnostic approaches for the identification of drug-responsive or resistant patient subpopulations. This review covers the advantages, disadvantages and applications of TMAs for biomarker research. Research literature and reviews of TMAs and quantitative image analysis methodology have been surveyed for this review (with an AQUA® analysis focus). Applications such as multi-marker diagnostic development and pathway-based biomarker subpopulation analyses are described. Tissue microarrays are a useful tool for biomarker analyses including prevalence surveys, disease progression assessment and addressing potential prognostic or predictive value. By combining quantitative image analysis with TMAs, analyses will be more objective and reproducible, allowing for more robust IHC-based diagnostic test development. Quantitative multi-biomarker IHC diagnostic tests that can predict drug response will allow for greater success of clinical trials for targeted therapies and provide more personalized clinical decision making.

Panel-based Genetic Diagnostic Testing for Inherited Eye Diseases is Highly Accurate and Reproducible and More Sensitive for Variant Detection Than Exome Sequencing

PubMed Central

Bujakowska, Kinga M.; Sousa, Maria E.; Fonseca-Kelly, Zoë D.; Taub, Daniel G.; Janessian, Maria; Wang, Dan Yi; Au, Elizabeth D.; Sims, Katherine B.; Sweetser, David A.; Fulton, Anne B.; Liu, Qin; Wiggs, Janey L.; Gai, Xiaowu; Pierce, Eric A.

2015-01-01

Purpose Next-generation sequencing (NGS) based methods are being adopted broadly for genetic diagnostic testing, but the performance characteristics of these techniques have not been fully defined with regard to test accuracy and reproducibility. Methods We developed a targeted enrichment and NGS approach for genetic diagnostic testing of patients with inherited eye disorders, including inherited retinal degenerations, optic atrophy and glaucoma. In preparation for providing this Genetic Eye Disease (GEDi) test on a CLIA-certified basis, we performed experiments to measure the sensitivity, specificity, reproducibility as well as the clinical sensitivity of the test. Results The GEDi test is highly reproducible and accurate, with sensitivity and specificity for single nucleotide variant detection of 97.9% and 100%, respectively. The sensitivity for variant detection was notably better than the 88.3% achieved by whole exome sequencing (WES) using the same metrics, due to better coverage of targeted genes in the GEDi test compared to commercially available exome capture sets. Prospective testing of 192 patients with IRDs indicated that the clinical sensitivity of the GEDi test is high, with a diagnostic rate of 51%. Conclusion The data suggest that based on quantified performance metrics, selective targeted enrichment is preferable to WES for genetic diagnostic testing. PMID:25412400

Evidence-Based Toxicology.

PubMed

Hoffmann, Sebastian; Hartung, Thomas; Stephens, Martin

Evidence-based toxicology (EBT) was introduced independently by two groups in 2005, in the context of toxicological risk assessment and causation as well as based on parallels between the evaluation of test methods in toxicology and evidence-based assessment of diagnostics tests in medicine. The role model of evidence-based medicine (EBM) motivated both proposals and guided the evolution of EBT, whereas especially systematic reviews and evidence quality assessment attract considerable attention in toxicology.Regarding test assessment, in the search of solutions for various problems related to validation, such as the imperfectness of the reference standard or the challenge to comprehensively evaluate tests, the field of Diagnostic Test Assessment (DTA) was identified as a potential resource. DTA being an EBM discipline, test method assessment/validation therefore became one of the main drivers spurring the development of EBT.In the context of pathway-based toxicology, EBT approaches, given their objectivity, transparency and consistency, have been proposed to be used for carrying out a (retrospective) mechanistic validation.In summary, implementation of more evidence-based approaches may provide the tools necessary to adapt the assessment/validation of toxicological test methods and testing strategies to face the challenges of toxicology in the twenty first century.

A WAO - ARIA - GA²LEN consensus document on molecular-based allergy diagnostics

PubMed Central

2013-01-01

Molecular-based allergy (MA) diagnostics is an approach used to map the allergen sensitization of a patient at a molecular level, using purified natural or recombinant allergenic molecules (allergen components) instead of allergen extracts. Since its introduction, MA diagnostics has increasingly entered routine care, with currently more than 130 allergenic molecules commercially available for in vitro specific IgE (sIgE) testing. MA diagnostics allows for an increased accuracy in allergy diagnosis and prognosis and plays an important role in three key aspects of allergy diagnosis: (1) resolving genuine versus cross-reactive sensitization in poly-sensitized patients, thereby improving the understanding of triggering allergens; (2) assessing, in selected cases, the risk of severe, systemic versus mild, local reactions in food allergy, thereby reducing unnecessary anxiety for the patient and the need for food challenge testing; and (3) identifying patients and triggering allergens for specific immunotherapy (SIT). Singleplex and multiplex measurement platforms are available for MA diagnostics. The Immuno-Solid phase Allergen Chip (ISAC) is the most comprehensive platform currently available, which involves a biochip technology to measure sIgE antibodies against more than one hundred allergenic molecules in a single assay. As the field of MA diagnostics advances, future work needs to focus on large-scale, population-based studies involving practical applications, elucidation and expansion of additional allergenic molecules, and support for appropriate test interpretation. With the rapidly expanding evidence-base for MA diagnosis, there is a need for allergists to keep abreast of the latest information. The aim of this consensus document is to provide a practical guide for the indications, determination, and interpretation of MA diagnostics for clinicians trained in allergology. PMID:24090398

A WAO - ARIA - GA²LEN consensus document on molecular-based allergy diagnostics.

PubMed

Canonica, Giorgio Walter; Ansotegui, Ignacio J; Pawankar, Ruby; Schmid-Grendelmeier, Peter; van Hage, Marianne; Baena-Cagnani, Carlos E; Melioli, Giovanni; Nunes, Carlos; Passalacqua, Giovanni; Rosenwasser, Lanny; Sampson, Hugh; Sastre, Joaquin; Bousquet, Jean; Zuberbier, Torsten

2013-10-03

Molecular-based allergy (MA) diagnostics is an approach used to map the allergen sensitization of a patient at a molecular level, using purified natural or recombinant allergenic molecules (allergen components) instead of allergen extracts. Since its introduction, MA diagnostics has increasingly entered routine care, with currently more than 130 allergenic molecules commercially available for in vitro specific IgE (sIgE) testing.MA diagnostics allows for an increased accuracy in allergy diagnosis and prognosis and plays an important role in three key aspects of allergy diagnosis: (1) resolving genuine versus cross-reactive sensitization in poly-sensitized patients, thereby improving the understanding of triggering allergens; (2) assessing, in selected cases, the risk of severe, systemic versus mild, local reactions in food allergy, thereby reducing unnecessary anxiety for the patient and the need for food challenge testing; and (3) identifying patients and triggering allergens for specific immunotherapy (SIT).Singleplex and multiplex measurement platforms are available for MA diagnostics. The Immuno-Solid phase Allergen Chip (ISAC) is the most comprehensive platform currently available, which involves a biochip technology to measure sIgE antibodies against more than one hundred allergenic molecules in a single assay. As the field of MA diagnostics advances, future work needs to focus on large-scale, population-based studies involving practical applications, elucidation and expansion of additional allergenic molecules, and support for appropriate test interpretation. With the rapidly expanding evidence-base for MA diagnosis, there is a need for allergists to keep abreast of the latest information. The aim of this consensus document is to provide a practical guide for the indications, determination, and interpretation of MA diagnostics for clinicians trained in allergology.

A General Architecture for Intelligent Tutoring of Diagnostic Classification Problem Solving

PubMed Central

Crowley, Rebecca S.; Medvedeva, Olga

2003-01-01

We report on a general architecture for creating knowledge-based medical training systems to teach diagnostic classification problem solving. The approach is informed by our previous work describing the development of expertise in classification problem solving in Pathology. The architecture envelops the traditional Intelligent Tutoring System design within the Unified Problem-solving Method description Language (UPML) architecture, supporting component modularity and reuse. Based on the domain ontology, domain task ontology and case data, the abstract problem-solving methods of the expert model create a dynamic solution graph. Student interaction with the solution graph is filtered through an instructional layer, which is created by a second set of abstract problem-solving methods and pedagogic ontologies, in response to the current state of the student model. We outline the advantages and limitations of this general approach, and describe it’s implementation in SlideTutor–a developing Intelligent Tutoring System in Dermatopathology. PMID:14728159

Current challenges in diagnostic imaging of venous thromboembolism.

PubMed

Huisman, Menno V; Klok, Frederikus A

2015-01-01

Because the clinical diagnosis of deep-vein thrombosis and pulmonary embolism is nonspecific, integrated diagnostic approaches for patients with suspected venous thromboembolism have been developed over the years, involving both non-invasive bedside tools (clinical decision rules and D-dimer blood tests) for patients with low pretest probability and diagnostic techniques (compression ultrasound for deep-vein thrombosis and computed tomography pulmonary angiography for pulmonary embolism) for those with a high pretest probability. This combination has led to standardized diagnostic algorithms with proven safety for excluding venous thrombotic disease. At the same time, it has become apparent that, as a result of the natural history of venous thrombosis, there are special patient populations in which the current standard diagnostic algorithms are not sufficient. In this review, we present 3 evidence-based patient cases to underline recent developments in the imaging diagnosis of venous thromboembolism. © 2015 by The American Society of Hematology. All rights reserved.

[Chronic diarrhoea: Definition, classification and diagnosis].

PubMed

Fernández-Bañares, Fernando; Accarino, Anna; Balboa, Agustín; Domènech, Eugeni; Esteve, Maria; Garcia-Planella, Esther; Guardiola, Jordi; Molero, Xavier; Rodríguez-Luna, Alba; Ruiz-Cerulla, Alexandra; Santos, Javier; Vaquero, Eva

2016-10-01

Chronic diarrhoea is a common presenting symptom in both primary care medicine and in specialized gastroenterology clinics. It is estimated that >5% of the population has chronic diarrhoea and nearly 40% of these patients are older than 60 years. Clinicians often need to select the best diagnostic approach to these patients and choose between the multiple diagnostic tests available. In 2014 the Catalan Society of Gastroenterology formed a working group with the main objective of creating diagnostic algorithms based on clinical practice and to evaluate diagnostic tests and the scientific evidence available for their use. The GRADE system was used to classify scientific evidence and strength of recommendations. The consensus document contains 28 recommendations and 6 diagnostic algorithms. The document also describes criteria for referral from primary to specialized care. Copyright © 2015 Elsevier España, S.L.U. y AEEH y AEG. All rights reserved.

Design of character-based DNA barcode motif for species identification: A computational approach and its validation in fishes.

PubMed

Chakraborty, Mohua; Dhar, Bishal; Ghosh, Sankar Kumar

2017-11-01

The DNA barcodes are generally interpreted using distance-based and character-based methods. The former uses clustering of comparable groups, based on the relative genetic distance, while the latter is based on the presence or absence of discrete nucleotide substitutions. The distance-based approach has a limitation in defining a universal species boundary across the taxa as the rate of mtDNA evolution is not constant throughout the taxa. However, character-based approach more accurately defines this using a unique set of nucleotide characters. The character-based analysis of full-length barcode has some inherent limitations, like sequencing of the full-length barcode, use of a sparse-data matrix and lack of a uniform diagnostic position for each group. A short continuous stretch of a fragment can be used to resolve the limitations. Here, we observe that a 154-bp fragment, from the transversion-rich domain of 1367 COI barcode sequences can successfully delimit species in the three most diverse orders of freshwater fishes. This fragment is used to design species-specific barcode motifs for 109 species by the character-based method, which successfully identifies the correct species using a pattern-matching program. The motifs also correctly identify geographically isolated population of the Cypriniformes species. Further, this region is validated as a species-specific mini-barcode for freshwater fishes by successful PCR amplification and sequencing of the motif (154 bp) using the designed primers. We anticipate that use of such motifs will enhance the diagnostic power of DNA barcode, and the mini-barcode approach will greatly benefit the field-based system of rapid species identification. © 2017 John Wiley & Sons Ltd.

Target prioritization and strategy selection for active case-finding of pulmonary tuberculosis: a tool to support country-level project planning.

PubMed

Nishikiori, Nobuyuki; Van Weezenbeek, Catharina

2013-02-02

Despite the progress made in the past decade, tuberculosis (TB) control still faces significant challenges. In many countries with declining TB incidence, the disease tends to concentrate in vulnerable populations that often have limited access to health care. In light of the limitations of the current case-finding approach and the global urgency to improve case detection, active case-finding (ACF) has been suggested as an important complementary strategy to accelerate tuberculosis control especially among high-risk populations. The present exercise aims to develop a model that can be used for county-level project planning. A simple deterministic model was developed to calculate the number of estimated TB cases diagnosed and the associated costs of diagnosis. The model was designed to compare cost-effectiveness parameters, such as the cost per case detected, for different diagnostic algorithms when they are applied to different risk populations. The model was transformed into a web-based tool that can support national TB programmes and civil society partners in designing ACF activities. According to the model output, tuberculosis active case-finding can be a costly endeavor, depending on the target population and the diagnostic strategy. The analysis suggests the following: (1) Active case-finding activities are cost-effective only if the tuberculosis prevalence among the target population is high. (2) Extensive diagnostic methods (e.g. X-ray screening for the entire group, use of sputum culture or molecular diagnostics) can be applied only to very high-risk groups such as TB contacts, prisoners or people living with human immunodeficiency virus (HIV) infection. (3) Basic diagnostic approaches such as TB symptom screening are always applicable although the diagnostic yield is very limited. The cost-effectiveness parameter was sensitive to local diagnostic costs and the tuberculosis prevalence of target populations. The prioritization of appropriate target populations and careful selection of cost-effective diagnostic strategies are critical prerequisites for rational active case-finding activities. A decision to conduct such activities should be based on the setting-specific cost-effectiveness analysis and programmatic assessment. A web-based tool was developed and is available to support national tuberculosis programmes and partners in the formulation of cost-effective active case-finding activities at the national and subnational levels.

Comparison of Machine Learning Methods for the Arterial Hypertension Diagnostics

PubMed Central

Belo, David; Gamboa, Hugo

2017-01-01

The paper presents results of machine learning approach accuracy applied analysis of cardiac activity. The study evaluates the diagnostics possibilities of the arterial hypertension by means of the short-term heart rate variability signals. Two groups were studied: 30 relatively healthy volunteers and 40 patients suffering from the arterial hypertension of II-III degree. The following machine learning approaches were studied: linear and quadratic discriminant analysis, k-nearest neighbors, support vector machine with radial basis, decision trees, and naive Bayes classifier. Moreover, in the study, different methods of feature extraction are analyzed: statistical, spectral, wavelet, and multifractal. All in all, 53 features were investigated. Investigation results show that discriminant analysis achieves the highest classification accuracy. The suggested approach of noncorrelated feature set search achieved higher results than data set based on the principal components. PMID:28831239

Hypersensitivity reactions to non-steroidal anti-inflammatory drugs.

PubMed

Cornejo-Garcia, José Antonio; Blanca-López, Natalia; Doña, Inmaculada; Andreu, Inmaculada; Agúndez, José A G; Carballo, Miguel; Blanca, Miguel; Canto, María Gabriela

2009-11-01

NSAIDs are the most important group of drugs involved in hypersensitivity drug reactions, and include heterogeneous compounds with very different chemical structures. These reactions can be IgE dependent (immediate reactions), T cell-mediated (non-immediate), or induced by a non-specific immunological mechanism related with the blocking of the COX-1 enzyme and the shunting to the lipooxygenase pathway (cross-intolerant reactions). Cutaneous symptoms are the most frequent, with ibuprofen, naproxen and diclofenac being common culprit drugs worldwide, although others can be involved because patterns of consumption and exposure rates vary between countries. A very important proportion of immunological reactions are immediate, with urticaria and anaphylaxis being the typical clinical manifestations. Non-immediate reactions comprise a number of heterogeneous entities ranging from mild exanthema to severe TEN or DRESS syndrome, as well as organ-specific reactions such as hepatitis or pneumonitis. Cross-intolerant reactions appear to non-chemically related drugs, and involve respiratory airways, skin or both. In vivo diagnostic tests are based on the capacity of the skin to respond to the culprit drug, but their sensitivity is in many instances rather low. The approach for in vitro testing consists of either detecting specific IgE antibodies or studying the proliferation of T lymphocytes toward the eliciting drug. No appropriate tests are yet available for the in vitro validation of cross-intolerance reactions, although techniques based on the stimulation of basophils have been proposed. Based on these findings, the diagnostic approach is often based on the controlled administration of the drug to assess tolerance. In this work we review current knowledge on hypersensitivity reactions to NSAIDs, including diagnostic approach and genetic studies.

Current approach to the diagnosis of IgG4-related disease - Combination of comprehensive diagnostic and organ-specific criteria.

PubMed

Umehara, Hisanori; Okazaki, Kazuichi; Nakamura, Takuji; Satoh-Nakamura, Tomomi; Nakajima, Akio; Kawano, Mitsuhiro; Mimori, Tsuneyo; Chiba, Tsutomu

2017-05-01

IgG4-related disease (IgG4-RD) is a fascinating clinical entity proposed by Japanese investigators, and includes a wide variety of diseases, formerly diagnosed as Mikulicz's disease (MD), autoimmune pancreatitis (AIP), interstitial nephritis, prostatitis, retroperitoneal fibrosis, etc. Although all clinicians in every field of medicine may encounter this new disease, a unifying diagnostic criterion has not been established. In 2011, the Japanese IgG4 team, organized by the Ministry of Health, Labor and Welfare (MHLW) of Japan, published comprehensive diagnostic criteria for IgG4-RD. Several problems with these criteria have arisen in clinical practice, however, including the difficulty obtaining biopsy samples from some patients, and the sensitivity and the specificity of techniques used to measure serum IgG4 concentrations. Although serum IgG4 concentration is an important clinical marker for IgG4-RD, its diagnostic utility in differentiating IgG4-RD from other diseases, called IgG4-RD mimickers, remains unclear. This review describes the current optimal approach for the diagnosis of IgG4-RD, based on both comprehensive and organ-specific diagnostic criteria, in patients with diseases such as IgG4-related pancreatitis (AIP), sclerosing cholangitis, and renal, lung and orbital diseases.

Multimodal fiber-probe spectroscopy as a clinical tool for diagnosing and classifying biological tissues

NASA Astrophysics Data System (ADS)

Cicchi, Riccardo; Anand, Suresh; Fantechi, Riccardo; Giordano, Flavio; Gacci, Mauro; Conti, Valerio; Nesi, Gabriella; Buccoliero, Anna Maria; Carini, Marco; Guerrini, Renzo; Pavone, Francesco Saverio

2017-07-01

An optical fiber probe for multimodal spectroscopy was designed, developed and used for tissue diagnostics. The probe, based on a fiber bundle with optical fibers of various size and properties, allows performing spectroscopic measurements with different techniques, including fluorescence, Raman, and diffuse reflectance, using the same probe. Two visible laser diodes were used for fluorescence spectroscopy, a laser diode emitting in the NIR was used for Raman spectroscopy, and a fiber-coupled halogen lamp for diffuse reflectance. The developed probe was successfully employed for diagnostic purposes on various tissues, including brain and bladder. In particular, the device allowed discriminating healthy tissue from both tumor and dysplastic tissue as well as to perform tumor grading. The diagnostic capabilities of the method, determined using a cross-validation method with a leave-one-out approach, demonstrated high sensitivity and specificity for all the examined samples, as well as a good agreement with histopathological examination performed on the same samples. The obtained results demonstrated that the multimodal approach is crucial for improving diagnostic capabilities with respect to what can be obtained from individual techniques. The experimental setup presented here can improve diagnostic capabilities on a broad range of tissues and has the potential of being used clinically for guiding surgical resection in the near future.

Non-negative Matrix Factorization and Co-clustering: A Promising Tool for Multi-tasks Bearing Fault Diagnosis

NASA Astrophysics Data System (ADS)

Shen, Fei; Chen, Chao; Yan, Ruqiang

2017-05-01

Classical bearing fault diagnosis methods, being designed according to one specific task, always pay attention to the effectiveness of extracted features and the final diagnostic performance. However, most of these approaches suffer from inefficiency when multiple tasks exist, especially in a real-time diagnostic scenario. A fault diagnosis method based on Non-negative Matrix Factorization (NMF) and Co-clustering strategy is proposed to overcome this limitation. Firstly, some high-dimensional matrixes are constructed using the Short-Time Fourier Transform (STFT) features, where the dimension of each matrix equals to the number of target tasks. Then, the NMF algorithm is carried out to obtain different components in each dimension direction through optimized matching, such as Euclidean distance and divergence distance. Finally, a Co-clustering technique based on information entropy is utilized to realize classification of each component. To verity the effectiveness of the proposed approach, a series of bearing data sets were analysed in this research. The tests indicated that although the diagnostic performance of single task is comparable to traditional clustering methods such as K-mean algorithm and Guassian Mixture Model, the accuracy and computational efficiency in multi-tasks fault diagnosis are improved.

The Diagnostic Challenge Competition: Probabilistic Techniques for Fault Diagnosis in Electrical Power Systems

NASA Technical Reports Server (NTRS)

Ricks, Brian W.; Mengshoel, Ole J.

2009-01-01

Reliable systems health management is an important research area of NASA. A health management system that can accurately and quickly diagnose faults in various on-board systems of a vehicle will play a key role in the success of current and future NASA missions. We introduce in this paper the ProDiagnose algorithm, a diagnostic algorithm that uses a probabilistic approach, accomplished with Bayesian Network models compiled to Arithmetic Circuits, to diagnose these systems. We describe the ProDiagnose algorithm, how it works, and the probabilistic models involved. We show by experimentation on two Electrical Power Systems based on the ADAPT testbed, used in the Diagnostic Challenge Competition (DX 09), that ProDiagnose can produce results with over 96% accuracy and less than 1 second mean diagnostic time.

Computer-aided diagnostic strategy selection.

PubMed

Greenes, R A

1986-03-01

Determination of the optimal diagnostic work-up strategy for the patient is becoming a major concern for the practicing physician. Overlap of the indications for various diagnostic procedures, differences in their invasiveness or risk, and high costs have made physicians aware of the need to consider the choice of procedure carefully, as well as its relation to management actions available. In this article, the author discusses research approaches that aim toward development of formal decision analytic methods to allow the physician to determine optimal strategy; clinical algorithms or rules as guides to physician decisions; improved measures for characterizing the performance of diagnostic tests; educational tools for increasing the familiarity of physicians with the concepts underlying these measures and analytic procedures; and computer-based aids for facilitating the employment of these resources in actual clinical practice.

Optimal Combinations of Diagnostic Tests Based on AUC.

PubMed

Huang, Xin; Qin, Gengsheng; Fang, Yixin

2011-06-01

When several diagnostic tests are available, one can combine them to achieve better diagnostic accuracy. This article considers the optimal linear combination that maximizes the area under the receiver operating characteristic curve (AUC); the estimates of the combination's coefficients can be obtained via a nonparametric procedure. However, for estimating the AUC associated with the estimated coefficients, the apparent estimation by re-substitution is too optimistic. To adjust for the upward bias, several methods are proposed. Among them the cross-validation approach is especially advocated, and an approximated cross-validation is developed to reduce the computational cost. Furthermore, these proposed methods can be applied for variable selection to select important diagnostic tests. The proposed methods are examined through simulation studies and applications to three real examples. © 2010, The International Biometric Society.

Enzymatic testing sensitivity, variability and practical diagnostic algorithm for pyruvate dehydrogenase complex (PDC) deficiency.

PubMed

Shin, Ha Kyung; Grahame, George; McCandless, Shawn E; Kerr, Douglas S; Bedoyan, Jirair K

2017-11-01

Pyruvate dehydrogenase complex (PDC) deficiency is a major cause of primary lactic acidemia in children. Prompt and correct diagnosis of PDC deficiency and differentiating between specific vs generalized, or secondary deficiencies has important implications for clinical management and therapeutic interventions. Both genetic and enzymatic testing approaches are being used in the diagnosis of PDC deficiency. However, the diagnostic efficacy of such testing approaches for individuals affected with PDC deficiency has not been systematically investigated in this disorder. We sought to evaluate the diagnostic sensitivity and variability of the various PDC enzyme assays in females and males at the Center for Inherited Disorders of Energy Metabolism (CIDEM). CIDEM data were filtered by lactic acidosis and functional PDC deficiency in at least one cell/tissue type (blood lymphocytes, cultured fibroblasts or skeletal muscle) identifying 186 subjects (51% male and 49% female), about half were genetically resolved with 78% of those determined to have a pathogenic PDHA1 mutation. Assaying PDC in cultured fibroblasts in cases where the underlying genetic etiology is PDHA1, was highly sensitive irrespective of gender; 97% (95% confidence interval [CI]: 90%-100%) and 91% (95% CI: 82%-100%) in females and males, respectively. In contrast to the fibroblast-based testing, the lymphocyte- and muscle-based testing were not sensitive (36% [95% CI: 11%-61%, p=0.0003] and 58% [95% CI: 30%-86%, p=0.014], respectively) for identifying known PDC deficient females with pathogenic PDHA1 mutations. In males with a known PDHA1 mutation, the sensitivity of the various cell/tissue assays (75% lymphocyte, 91% fibroblast and 88% muscle) were not statistically different, and the discordance frequency due to the specific cell/tissue used for assaying PDC was 0.15±0.11. Based on this data, a practical diagnostic algorithm is proposed accounting for current molecular approaches, enzyme testing sensitivity, and variability due to gender, cell/tissue type used for testing, and successive repeat testing. Copyright © 2017 Elsevier Inc. All rights reserved.

The Application of Cognitive Diagnostic Approaches via Neural Network Analysis of Serious Educational Games

NASA Astrophysics Data System (ADS)

Lamb, Richard L.

Serious Educational Games (SEGs) have been a topic of increased popularity within the educational realm since the early millennia. SEGs are generalized form of Serious Games to mean games for purposes other than entertainment but, that also specifically include training, educational purpose and pedagogy within their design. This rise in popularity (for SEGs) has occurred at a time when school systems have increased the type, number, and presentations of student achievement tests for decision-making purposes. These tests often task the form of end of course (year) tests and periodic benchmark testing. As the use of these tests, has increased policymakers have suggested their use as a measure for teacher accountability. The change in testing resulted from a push by school districts and policy makers at various component levels for a data-driven decision-making (D3M) approach. With the data-driven decision making approaches by school districts, there has been an increased focus on the measurement and assessment of student content knowledge with little focus on the contributing factors and cognitive attributes within learning that cross multiple-content areas. One-way to increase the focus on these aspects of learning (factors and attributes) that are additional to content learning is through assessments based in cognitive diagnostics. Cognitive diagnostics are a family of methodological approaches in which tasks tie to specific cognitive attributes for analytical purposes. This study explores data derived from computer data logging (n=158,000) in an observational design, using traditional statistical techniques such as clustering (exploratory and confirmatory), item response theory and through data mining techniques such as artificial neural network analysis. From these analyses, a model of student learning emerges illustrating student thinking and learning while engaged in SEG Design. This study seeks to use cognitive diagnostic type approaches to measure student learning while designing science task based SEGs. In addition, the study suggests that it may be possible to use SEGs to provide a means to administer cognitive diagnostic based assessments in real time. Results of this study suggest the confirmation of four families (factors) of traits illustrating a simple factor loading structure. Item response theory (IRT) results illustrate a 2-parameter logistic model (2PLM) fit allowing for parameterization using the IRT-True Score Method (chi2=1.70, df=1, p=0.19). Finally, fit statistics for the artificial neural network suggest the developed model adequately fits the current data set and provides a means to explore cognitive attributes and their effect on task outcomes. This study has developed a justification for combining and developing two distinct areas of research related to student learning. The first is the use of cognitive diagnostic approaches to assess student learning as it relates to the cognitive attributes used during science processing. The second area is an examination and modeling of the relationship between attributes as propagated in an artificial neural network. Results of the study provide for an ANN model of student cognition while designing science based SEGs (r 2=0.73, RMSE= 0.21) at a convergence of 1000 training iterations. The literature presented in this dissertation work integrates work from multiple field areas. Fields represented in this work range from science education, educational psychology, measurement, and computational psychology.

Towards case-based medical learning in radiological decision making using content-based image retrieval

PubMed Central

2011-01-01

Background Radiologists' training is based on intensive practice and can be improved with the use of diagnostic training systems. However, existing systems typically require laboriously prepared training cases and lack integration into the clinical environment with a proper learning scenario. Consequently, diagnostic training systems advancing decision-making skills are not well established in radiological education. Methods We investigated didactic concepts and appraised methods appropriate to the radiology domain, as follows: (i) Adult learning theories stress the importance of work-related practice gained in a team of problem-solvers; (ii) Case-based reasoning (CBR) parallels the human problem-solving process; (iii) Content-based image retrieval (CBIR) can be useful for computer-aided diagnosis (CAD). To overcome the known drawbacks of existing learning systems, we developed the concept of image-based case retrieval for radiological education (IBCR-RE). The IBCR-RE diagnostic training is embedded into a didactic framework based on the Seven Jump approach, which is well established in problem-based learning (PBL). In order to provide a learning environment that is as similar as possible to radiological practice, we have analysed the radiological workflow and environment. Results We mapped the IBCR-RE diagnostic training approach into the Image Retrieval in Medical Applications (IRMA) framework, resulting in the proposed concept of the IRMAdiag training application. IRMAdiag makes use of the modular structure of IRMA and comprises (i) the IRMA core, i.e., the IRMA CBIR engine; and (ii) the IRMAcon viewer. We propose embedding IRMAdiag into hospital information technology (IT) infrastructure using the standard protocols Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7). Furthermore, we present a case description and a scheme of planned evaluations to comprehensively assess the system. Conclusions The IBCR-RE paradigm incorporates a novel combination of essential aspects of diagnostic learning in radiology: (i) Provision of work-relevant experiences in a training environment integrated into the radiologist's working context; (ii) Up-to-date training cases that do not require cumbersome preparation because they are provided by routinely generated electronic medical records; (iii) Support of the way adults learn while remaining suitable for the patient- and problem-oriented nature of medicine. Future work will address unanswered questions to complete the implementation of the IRMAdiag trainer. PMID:22032775

Towards case-based medical learning in radiological decision making using content-based image retrieval.

PubMed

Welter, Petra; Deserno, Thomas M; Fischer, Benedikt; Günther, Rolf W; Spreckelsen, Cord

2011-10-27

Radiologists' training is based on intensive practice and can be improved with the use of diagnostic training systems. However, existing systems typically require laboriously prepared training cases and lack integration into the clinical environment with a proper learning scenario. Consequently, diagnostic training systems advancing decision-making skills are not well established in radiological education. We investigated didactic concepts and appraised methods appropriate to the radiology domain, as follows: (i) Adult learning theories stress the importance of work-related practice gained in a team of problem-solvers; (ii) Case-based reasoning (CBR) parallels the human problem-solving process; (iii) Content-based image retrieval (CBIR) can be useful for computer-aided diagnosis (CAD). To overcome the known drawbacks of existing learning systems, we developed the concept of image-based case retrieval for radiological education (IBCR-RE). The IBCR-RE diagnostic training is embedded into a didactic framework based on the Seven Jump approach, which is well established in problem-based learning (PBL). In order to provide a learning environment that is as similar as possible to radiological practice, we have analysed the radiological workflow and environment. We mapped the IBCR-RE diagnostic training approach into the Image Retrieval in Medical Applications (IRMA) framework, resulting in the proposed concept of the IRMAdiag training application. IRMAdiag makes use of the modular structure of IRMA and comprises (i) the IRMA core, i.e., the IRMA CBIR engine; and (ii) the IRMAcon viewer. We propose embedding IRMAdiag into hospital information technology (IT) infrastructure using the standard protocols Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7). Furthermore, we present a case description and a scheme of planned evaluations to comprehensively assess the system. The IBCR-RE paradigm incorporates a novel combination of essential aspects of diagnostic learning in radiology: (i) Provision of work-relevant experiences in a training environment integrated into the radiologist's working context; (ii) Up-to-date training cases that do not require cumbersome preparation because they are provided by routinely generated electronic medical records; (iii) Support of the way adults learn while remaining suitable for the patient- and problem-oriented nature of medicine. Future work will address unanswered questions to complete the implementation of the IRMAdiag trainer.

Spatial enhancement of ECG using diagnostic similarity score based lead selective multi-scale linear model.

PubMed

Nallikuzhy, Jiss J; Dandapat, S

2017-06-01

In this work, a new patient-specific approach to enhance the spatial resolution of ECG is proposed and evaluated. The proposed model transforms a three-lead ECG into a standard twelve-lead ECG thereby enhancing its spatial resolution. The three leads used for prediction are obtained from the standard twelve-lead ECG. The proposed model takes advantage of the improved inter-lead correlation in wavelet domain. Since the model is patient-specific, it also selects the optimal predictor leads for a given patient using a lead selection algorithm. The lead selection algorithm is based on a new diagnostic similarity score which computes the diagnostic closeness between the original and the spatially enhanced leads. Standard closeness measures are used to assess the performance of the model. The similarity in diagnostic information between the original and the spatially enhanced leads are evaluated using various diagnostic measures. Repeatability and diagnosability are performed to quantify the applicability of the model. A comparison of the proposed model is performed with existing models that transform a subset of standard twelve-lead ECG into the standard twelve-lead ECG. From the analysis of the results, it is evident that the proposed model preserves diagnostic information better compared to other models. Copyright © 2017 Elsevier Ltd. All rights reserved.

Diagnostics based on nucleic acid sequence variant profiling: PCR, hybridization, and NGS approaches.

PubMed

Khodakov, Dmitriy; Wang, Chunyan; Zhang, David Yu

2016-10-01

Nucleic acid sequence variations have been implicated in many diseases, and reliable detection and quantitation of DNA/RNA biomarkers can inform effective therapeutic action, enabling precision medicine. Nucleic acid analysis technologies being translated into the clinic can broadly be classified into hybridization, PCR, and sequencing, as well as their combinations. Here we review the molecular mechanisms of popular commercial assays, and their progress in translation into in vitro diagnostics. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

LEADER - An integrated engine behavior and design analyses based real-time fault diagnostic expert system for Space Shuttle Main Engine (SSME)

NASA Technical Reports Server (NTRS)

Gupta, U. K.; Ali, M.

1989-01-01

The LEADER expert system has been developed for automatic learning tasks encompassing real-time detection, identification, verification, and correction of anomalous propulsion system operations, using a set of sensors to monitor engine component performance to ascertain anomalies in engine dynamics and behavior. Two diagnostic approaches are embodied in LEADER's architecture: (1) learning and identifying engine behavior patterns to generate novel hypotheses about possible abnormalities, and (2) the direction of engine sensor data processing to perform resoning based on engine design and functional knowledge, as well as the principles of the relevant mechanics and physics.

Improved PCR-Based Detection of Soil Transmitted Helminth Infections Using a Next-Generation Sequencing Approach to Assay Design.

PubMed

Pilotte, Nils; Papaiakovou, Marina; Grant, Jessica R; Bierwert, Lou Ann; Llewellyn, Stacey; McCarthy, James S; Williams, Steven A

2016-03-01

The soil transmitted helminths are a group of parasitic worms responsible for extensive morbidity in many of the world's most economically depressed locations. With growing emphasis on disease mapping and eradication, the availability of accurate and cost-effective diagnostic measures is of paramount importance to global control and elimination efforts. While real-time PCR-based molecular detection assays have shown great promise, to date, these assays have utilized sub-optimal targets. By performing next-generation sequencing-based repeat analyses, we have identified high copy-number, non-coding DNA sequences from a series of soil transmitted pathogens. We have used these repetitive DNA elements as targets in the development of novel, multi-parallel, PCR-based diagnostic assays. Utilizing next-generation sequencing and the Galaxy-based RepeatExplorer web server, we performed repeat DNA analysis on five species of soil transmitted helminths (Necator americanus, Ancylostoma duodenale, Trichuris trichiura, Ascaris lumbricoides, and Strongyloides stercoralis). Employing high copy-number, non-coding repeat DNA sequences as targets, novel real-time PCR assays were designed, and assays were tested against established molecular detection methods. Each assay provided consistent detection of genomic DNA at quantities of 2 fg or less, demonstrated species-specificity, and showed an improved limit of detection over the existing, proven PCR-based assay. The utilization of next-generation sequencing-based repeat DNA analysis methodologies for the identification of molecular diagnostic targets has the ability to improve assay species-specificity and limits of detection. By exploiting such high copy-number repeat sequences, the assays described here will facilitate soil transmitted helminth diagnostic efforts. We recommend similar analyses when designing PCR-based diagnostic tests for the detection of other eukaryotic pathogens.

Towards a mechanism-based approach to pain diagnosis

PubMed Central

Vardeh, Daniel

2016-01-01

The last few decades have witnessed a huge leap forward in our understanding of the mechanistic underpinnings of pain, both in normal states where it helps protect from injury, and in pathological states where pain evolves from a symptom reflecting tissue injury to become the disease itself. However, despite these scientific advances, chronic pain remains extremely challenging to manage clinically. While the number of potential treatment targets has grown substantially and a strong case has been made for a mechanism-based and individualized approach to pain therapy, arguably clinicians are not much more advanced now than 20 years ago, in their capacity to either diagnose or effectively treat their patients. The gulf between pain research and pain management is as wide as ever. We are still currently unable to apply an evidence-based approach to chronic pain management that reflects mechanistic understanding, and instead, clinical practice remains an empirical and often unsatisfactory journey for patients, whose individual response to treatment cannot be predicted. Here we take a common and difficult to treat pain condition, chronic low back pain, and use its presentation in clinical practice as a framework to highlight what is known about pathophysiological pain mechanisms and how we could potentially detect these to drive rational treatment choice. We discuss how present methods of assessment and management still fall well short, however, of any mechanism-based or precision-medicine approach. Nevertheless, substantial improvements in chronic pain management could be possible if a more strategic and coordinated approach were to evolve, one designed to identify the specific mechanisms driving the presenting pain phenotype. We present an analysis of such an approach, highlighting the major problems in identifying mechanisms in patients, and develop a framework for a pain diagnostic ladder that may prove useful in the future, consisting of successive identification of three steps: pain state, pain mechanism and molecular target. Such an approach could serve as the foundation for a new era of individualized/precision pain medicine. The Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION) and American Pain Society (APS) Pain Taxonomy (AAPT) includes pain mechanisms as one of the 5 dimensions that need to be considered when making a diagnostic classification. The diagnostic ladder proposed in this article is both consistent with and an extension of the AAPT. PMID:27586831

Regression Analysis of Optical Coherence Tomography Disc Variables for Glaucoma Diagnosis.

PubMed

Richter, Grace M; Zhang, Xinbo; Tan, Ou; Francis, Brian A; Chopra, Vikas; Greenfield, David S; Varma, Rohit; Schuman, Joel S; Huang, David

2016-08-01

To report diagnostic accuracy of optical coherence tomography (OCT) disc variables using both time-domain (TD) and Fourier-domain (FD) OCT, and to improve the use of OCT disc variable measurements for glaucoma diagnosis through regression analyses that adjust for optic disc size and axial length-based magnification error. Observational, cross-sectional. In total, 180 normal eyes of 112 participants and 180 eyes of 138 participants with perimetric glaucoma from the Advanced Imaging for Glaucoma Study. Diagnostic variables evaluated from TD-OCT and FD-OCT were: disc area, rim area, rim volume, optic nerve head volume, vertical cup-to-disc ratio (CDR), and horizontal CDR. These were compared with overall retinal nerve fiber layer thickness and ganglion cell complex. Regression analyses were performed that corrected for optic disc size and axial length. Area-under-receiver-operating curves (AUROC) were used to assess diagnostic accuracy before and after the adjustments. An index based on multiple logistic regression that combined optic disc variables with axial length was also explored with the aim of improving diagnostic accuracy of disc variables. Comparison of diagnostic accuracy of disc variables, as measured by AUROC. The unadjusted disc variables with the highest diagnostic accuracies were: rim volume for TD-OCT (AUROC=0.864) and vertical CDR (AUROC=0.874) for FD-OCT. Magnification correction significantly worsened diagnostic accuracy for rim variables, and while optic disc size adjustments partially restored diagnostic accuracy, the adjusted AUROCs were still lower. Axial length adjustments to disc variables in the form of multiple logistic regression indices led to a slight but insignificant improvement in diagnostic accuracy. Our various regression approaches were not able to significantly improve disc-based OCT glaucoma diagnosis. However, disc rim area and vertical CDR had very high diagnostic accuracy, and these disc variables can serve to complement additional OCT measurements for diagnosis of glaucoma.

The NCI Alliance for Nanotechnology in Cancer: achievement and path forward.

PubMed

Ptak, Krzysztof; Farrell, Dorothy; Panaro, Nicholas J; Grodzinski, Piotr; Barker, Anna D

2010-01-01

Nanotechnology is a 'disruptive technology', which can lead to a generation of new diagnostic and therapeutic products, resulting in dramatically improved cancer outcomes. The National Cancer Institute (NCI) of National Institutes of Health explores innovative approaches to multidisciplinary research allowing for a convergence of molecular biology, oncology, physics, chemistry, and engineering and leading to the development of clinically worthy technological approaches. These initiatives include programmatic efforts to enable nanotechnology as a driver of advances in clinical oncology and cancer research, known collectively as the NCI Alliance for Nanotechnology in Cancer (ANC). Over the last 5 years, ANC has demonstrated that multidisciplinary approach catalyzes scientific developments and advances clinical translation in cancer nanotechnology. The research conducted by ANC members has improved diagnostic assays and imaging agents, leading to the development of point-of-care diagnostics, identification and validation of numerous biomarkers for novel diagnostic assays, and the development of multifunctional agents for imaging and therapy. Numerous nanotechnology-based technologies developed by ANC researchers are entering clinical trials. NCI has re-issued ANC program for next 5 years signaling that it continues to have high expectations for cancer nanotechnology's impact on clinical practice. The goals of the next phase will be to broaden access to cancer nanotechnology research through greater clinical translation and outreach to the patient and clinical communities and to support development of entirely new models of cancer care.

Systematic review of the diagnosis of scabies in therapeutic trials.

PubMed

Thompson, M J; Engelman, D; Gholam, K; Fuller, L C; Steer, A C

2017-07-01

Human scabies (infestation with the mite Sarcoptes scabiei var hominis) causes a significant disease burden worldwide, yet there are no agreed diagnostic guidelines. We aimed to determine whether a consistent approach to diagnosing scabies has been used for published scabies therapeutic trials. The data sources used were the MEDLINE, Embase and Cochrane databases, from 1946 to 29 August 2013. Eligible studies were trials of therapeutic interventions against scabies in human subjects, published in English, enrolling patients with scabies, and using various therapeutic interventions. Language was a limitation of this study as some relevant trials published in languages other than English may have been excluded. Each study was reviewed by two independent authors, who assessed the clinical examination and testing approaches used for scabies diagnosis in the included studies. We found that of 71 included trials, 40 (56%) specified which clinical findings were used for diagnosis, which were predominantly rash, rash distribution, pruritus and mite burrows. Parasitological testing was used in 63% of trials (n = 45) and was used more frequently in clinic-based than in field studies. Nearly one-quarter of trials (24%, n = 17) did not define the diagnostic method used. Overall, the diagnostic approaches were poorly described, prohibiting accurate comparison of existing studies. This review further supports the need for consensus diagnostic guidelines for scabies. © 2017 British Association of Dermatologists.

NEBNext Direct: A Novel, Rapid, Hybridization-Based Approach for the Capture and Library Conversion of Genomic Regions of Interest.

PubMed

Emerman, Amy B; Bowman, Sarah K; Barry, Andrew; Henig, Noa; Patel, Kruti M; Gardner, Andrew F; Hendrickson, Cynthia L

2017-07-05

Next-generation sequencing (NGS) is a powerful tool for genomic studies, translational research, and clinical diagnostics that enables the detection of single nucleotide polymorphisms, insertions and deletions, copy number variations, and other genetic variations. Target enrichment technologies improve the efficiency of NGS by only sequencing regions of interest, which reduces sequencing costs while increasing coverage of the selected targets. Here we present NEBNext Direct ® , a hybridization-based, target-enrichment approach that addresses many of the shortcomings of traditional target-enrichment methods. This approach features a simple, 7-hr workflow that uses enzymatic removal of off-target sequences to achieve a high specificity for regions of interest. Additionally, unique molecular identifiers are incorporated for the identification and filtering of PCR duplicates. The same protocol can be used across a wide range of input amounts, input types, and panel sizes, enabling NEBNext Direct to be broadly applicable across a wide variety of research and diagnostic needs. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Detection of clinically relevant copy-number variants by exome sequencing in a large cohort of genetic disorders

PubMed Central

Pfundt, Rolph; del Rosario, Marisol; Vissers, Lisenka E.L.M.; Kwint, Michael P.; Janssen, Irene M.; de Leeuw, Nicole; Yntema, Helger G.; Nelen, Marcel R.; Lugtenberg, Dorien; Kamsteeg, Erik-Jan; Wieskamp, Nienke; Stegmann, Alexander P.A.; Stevens, Servi J.C.; Rodenburg, Richard J.T.; Simons, Annet; Mensenkamp, Arjen R.; Rinne, Tuula; Gilissen, Christian; Scheffer, Hans; Veltman, Joris A.; Hehir-Kwa, Jayne Y.

2017-01-01

Purpose: Copy-number variation is a common source of genomic variation and an important genetic cause of disease. Microarray-based analysis of copy-number variants (CNVs) has become a first-tier diagnostic test for patients with neurodevelopmental disorders, with a diagnostic yield of 10–20%. However, for most other genetic disorders, the role of CNVs is less clear and most diagnostic genetic studies are generally limited to the study of single-nucleotide variants (SNVs) and other small variants. With the introduction of exome and genome sequencing, it is now possible to detect both SNVs and CNVs using an exome- or genome-wide approach with a single test. Methods: We performed exome-based read-depth CNV screening on data from 2,603 patients affected by a range of genetic disorders for which exome sequencing was performed in a diagnostic setting. Results: In total, 123 clinically relevant CNVs ranging in size from 727 bp to 15.3 Mb were detected, which resulted in 51 conclusive diagnoses and an overall increase in diagnostic yield of ~2% (ranging from 0 to –5.8% per disorder). Conclusions: This study shows that CNVs play an important role in a broad range of genetic disorders and that detection via exome-based CNV profiling results in an increase in the diagnostic yield without additional testing, bringing us closer to single-test genomics. Genet Med advance online publication 27 October 2016 PMID:28574513

Paper-based microfluidic approach for surface-enhanced raman spectroscopy and highly reproducible detection of proteins beyond picomolar concentration.

PubMed

Saha, Arindam; Jana, Nikhil R

2015-01-14

Although microfluidic approach is widely used in various point of care diagnostics, its implementation in surface enhanced Raman spectroscopy (SERS)-based detection is challenging. This is because SERS signal depends on plasmonic nanoparticle aggregation induced generation of stable electromagnetic hot spots and in currently available microfluidic platform this condition is difficult to adapt. Here we show that SERS can be adapted using simple paper based microfluidic system where both the plasmonic nanomaterials and analyte are used in mobile phase. This approach allows analyte induced controlled particle aggregation and electromagnetic hot spot generation inside the microfluidic channel with the resultant SERS signal, which is highly reproducible and sensitive. This approach has been used for reproducible detection of protein in the pico to femtomolar concentration. Presented approach is simple, rapid, and cost-effective, and requires low sample volume. Method can be extended for SERS-based detection of other biomolecules.

Creation of a diagnostic wait times measurement framework based on evidence and consensus.

PubMed

Gilbert, Julie E; Dobrow, Mark J; Kaan, Melissa; Dobranowski, Julian; Srigley, John R; Jusko Friedman, Audrey; Irish, Jonathan C

2014-09-01

Public reporting of wait times worldwide has to date focused largely on treatment wait times and is limited in its ability to capture earlier parts of the patient journey. The interval between suspicion and diagnosis or ruling out of cancer is a complex phase of the cancer journey. Diagnostic delays and inefficient use of diagnostic imaging procedures can result in poor patient outcomes, both physical and psychosocial. This study was designed to develop a framework that could be adopted for multiple disease sites across different jurisdictions to enable the measurement of diagnostic wait times and diagnostic delay. Diagnostic benchmarks and targets in cancer systems were explored through a targeted literature review and jurisdictional scan. Cancer system leaders and clinicians were interviewed to validate the information found in the jurisdictional scan. An expert panel was assembled to review and, through a modified Delphi consensus process, provide feedback on a diagnostic wait times framework. The consensus process resulted in agreement on a measurement framework that identified suspicion, referral, diagnosis, and treatment as the main time points for measuring this critical phase of the patient journey. This work will help guide initiatives designed to improve patient access to health services by developing an evidence-based approach to standardization of the various waypoints during the diagnostic pathway. The diagnostic wait times measurement framework provides a yardstick to measure the performance of programs that are designed to manage and expedite care processes between referral and diagnosis or ruling out of cancer. Copyright © 2014 by American Society of Clinical Oncology.

Technological Innovations for High-Throughput Approaches to In Vitro Allergy Diagnosis.

PubMed

Chapman, Martin D; Wuenschmann, Sabina; King, Eva; Pomés, Anna

2015-07-01

Allergy diagnostics is being transformed by the advent of in vitro IgE testing using purified allergen molecules, combined with multiplex technology and biosensors, to deliver discriminating, sensitive, and high-throughput molecular diagnostics at the point of care. Essential elements of IgE molecular diagnostics are purified natural or recombinant allergens with defined purity and IgE reactivity, planar or bead-based multiplex systems to enable IgE to multiple allergens to be measured simultaneously, and, most recently, nanotechnology-based biosensors that facilitate rapid reaction rates and delivery of test results via mobile devices. Molecular diagnostics relies on measurement of IgE to purified allergens, the "active ingredients" of allergenic extracts. Typically, this involves measuring IgE to multiple allergens which is facilitated by multiplex technology and biosensors. The technology differentiates between clinically significant cross-reactive allergens (which could not be deduced by conventional IgE assays using allergenic extracts) and provides better diagnostic outcomes. Purified allergens are manufactured under good laboratory practice and validated using protein chemistry, mass spectrometry, and IgE antibody binding. Recently, multiple allergens (from dog) were expressed as a single molecule with high diagnostic efficacy. Challenges faced by molecular allergy diagnostic companies include generation of large panels of purified allergens with known diagnostic efficacy, access to flexible and robust array or sensor technology, and, importantly, access to well-defined serum panels form allergic patients for product development and validation. Innovations in IgE molecular diagnostics are rapidly being brought to market and will strengthen allergy testing at the point of care.

Mass spectrometry-based metabolomics: applications to biomarker and metabolic pathway research.

PubMed

Zhang, Aihua; Sun, Hui; Yan, Guangli; Wang, Ping; Wang, Xijun

2016-01-01

Mass spectrometry-based metabolomics has become increasingly popular in molecular medicine. High-definition mass spectrometry (MS), coupled with pattern recognition methods, have been carried out to obtain comprehensive metabolite profiling and metabolic pathway of large biological datasets. This sets the scene for a new and powerful diagnostic approach. Analysis of the key metabolites in body fluids has become an important part of improving disease diagnosis. With technological advances in analytical techniques, the ability to measure low-molecular-weight metabolites in bio-samples provides a powerful platform for identifying metabolites that are uniquely correlated with a specific human disease. MS-based metabolomics can lead to enhanced understanding of disease mechanisms and to new diagnostic markers and has a strong potential to contribute to improving early diagnosis of diseases. This review will highlight the importance and benefit with certain characteristic examples of MS-metabolomics for identifying metabolic pathways and metabolites that accurately screen for potential diagnostic biomarkers of diseases. Copyright © 2015 John Wiley & Sons, Ltd.

DNA methylation-based classification of central nervous system tumours.

PubMed

Capper, David; Jones, David T W; Sill, Martin; Hovestadt, Volker; Schrimpf, Daniel; Sturm, Dominik; Koelsche, Christian; Sahm, Felix; Chavez, Lukas; Reuss, David E; Kratz, Annekathrin; Wefers, Annika K; Huang, Kristin; Pajtler, Kristian W; Schweizer, Leonille; Stichel, Damian; Olar, Adriana; Engel, Nils W; Lindenberg, Kerstin; Harter, Patrick N; Braczynski, Anne K; Plate, Karl H; Dohmen, Hildegard; Garvalov, Boyan K; Coras, Roland; Hölsken, Annett; Hewer, Ekkehard; Bewerunge-Hudler, Melanie; Schick, Matthias; Fischer, Roger; Beschorner, Rudi; Schittenhelm, Jens; Staszewski, Ori; Wani, Khalida; Varlet, Pascale; Pages, Melanie; Temming, Petra; Lohmann, Dietmar; Selt, Florian; Witt, Hendrik; Milde, Till; Witt, Olaf; Aronica, Eleonora; Giangaspero, Felice; Rushing, Elisabeth; Scheurlen, Wolfram; Geisenberger, Christoph; Rodriguez, Fausto J; Becker, Albert; Preusser, Matthias; Haberler, Christine; Bjerkvig, Rolf; Cryan, Jane; Farrell, Michael; Deckert, Martina; Hench, Jürgen; Frank, Stephan; Serrano, Jonathan; Kannan, Kasthuri; Tsirigos, Aristotelis; Brück, Wolfgang; Hofer, Silvia; Brehmer, Stefanie; Seiz-Rosenhagen, Marcel; Hänggi, Daniel; Hans, Volkmar; Rozsnoki, Stephanie; Hansford, Jordan R; Kohlhof, Patricia; Kristensen, Bjarne W; Lechner, Matt; Lopes, Beatriz; Mawrin, Christian; Ketter, Ralf; Kulozik, Andreas; Khatib, Ziad; Heppner, Frank; Koch, Arend; Jouvet, Anne; Keohane, Catherine; Mühleisen, Helmut; Mueller, Wolf; Pohl, Ute; Prinz, Marco; Benner, Axel; Zapatka, Marc; Gottardo, Nicholas G; Driever, Pablo Hernáiz; Kramm, Christof M; Müller, Hermann L; Rutkowski, Stefan; von Hoff, Katja; Frühwald, Michael C; Gnekow, Astrid; Fleischhack, Gudrun; Tippelt, Stephan; Calaminus, Gabriele; Monoranu, Camelia-Maria; Perry, Arie; Jones, Chris; Jacques, Thomas S; Radlwimmer, Bernhard; Gessi, Marco; Pietsch, Torsten; Schramm, Johannes; Schackert, Gabriele; Westphal, Manfred; Reifenberger, Guido; Wesseling, Pieter; Weller, Michael; Collins, Vincent Peter; Blümcke, Ingmar; Bendszus, Martin; Debus, Jürgen; Huang, Annie; Jabado, Nada; Northcott, Paul A; Paulus, Werner; Gajjar, Amar; Robinson, Giles W; Taylor, Michael D; Jaunmuktane, Zane; Ryzhova, Marina; Platten, Michael; Unterberg, Andreas; Wick, Wolfgang; Karajannis, Matthias A; Mittelbronn, Michel; Acker, Till; Hartmann, Christian; Aldape, Kenneth; Schüller, Ulrich; Buslei, Rolf; Lichter, Peter; Kool, Marcel; Herold-Mende, Christel; Ellison, David W; Hasselblatt, Martin; Snuderl, Matija; Brandner, Sebastian; Korshunov, Andrey; von Deimling, Andreas; Pfister, Stefan M

2018-03-22

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.

Robust In-Flight Sensor Fault Diagnostics for Aircraft Engine Based on Sliding Mode Observers

PubMed Central

Chang, Xiaodong; Huang, Jinquan; Lu, Feng

2017-01-01

For a sensor fault diagnostic system of aircraft engines, the health performance degradation is an inevitable interference that cannot be neglected. To address this issue, this paper investigates an integrated on-line sensor fault diagnostic scheme for a commercial aircraft engine based on a sliding mode observer (SMO). In this approach, one sliding mode observer is designed for engine health performance tracking, and another for sensor fault reconstruction. Both observers are employed in in-flight applications. The results of the former SMO are analyzed for post-flight updating the baseline model of the latter. This idea is practical and feasible since the updating process does not require the algorithm to be regulated or redesigned, so that ground-based intervention is avoided, and the update process is implemented in an economical and efficient way. With this setup, the robustness of the proposed scheme to the health degradation is much enhanced and the latter SMO is able to fulfill sensor fault reconstruction over the course of the engine life. The proposed sensor fault diagnostic system is applied to a nonlinear simulation of a commercial aircraft engine, and its effectiveness is evaluated in several fault scenarios. PMID:28398255

Robust In-Flight Sensor Fault Diagnostics for Aircraft Engine Based on Sliding Mode Observers.

PubMed

Chang, Xiaodong; Huang, Jinquan; Lu, Feng

2017-04-11

For a sensor fault diagnostic system of aircraft engines, the health performance degradation is an inevitable interference that cannot be neglected. To address this issue, this paper investigates an integrated on-line sensor fault diagnostic scheme for a commercial aircraft engine based on a sliding mode observer (SMO). In this approach, one sliding mode observer is designed for engine health performance tracking, and another for sensor fault reconstruction. Both observers are employed in in-flight applications. The results of the former SMO are analyzed for post-flight updating the baseline model of the latter. This idea is practical and feasible since the updating process does not require the algorithm to be regulated or redesigned, so that ground-based intervention is avoided, and the update process is implemented in an economical and efficient way. With this setup, the robustness of the proposed scheme to the health degradation is much enhanced and the latter SMO is able to fulfill sensor fault reconstruction over the course of the engine life. The proposed sensor fault diagnostic system is applied to a nonlinear simulation of a commercial aircraft engine, and its effectiveness is evaluated in several fault scenarios.

78 FR 24425 - Assay Migration Studies for In Vitro Diagnostic Devices; Guidance for Industry and Food and Drug...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-25

... approach to gain FDA approval of Class III or certain licensed in vitro diagnostic devices in cases when a... approach to gain FDA approval of Class III or certain licensed in vitro diagnostic devices in cases when a... fulfilled in order for a sponsor to utilize the migration study approach in support of the change. The FDA...

Prosthetic joint infection development of an evidence-based diagnostic algorithm.

PubMed

Mühlhofer, Heinrich M L; Pohlig, Florian; Kanz, Karl-Georg; Lenze, Ulrich; Lenze, Florian; Toepfer, Andreas; Kelch, Sarah; Harrasser, Norbert; von Eisenhart-Rothe, Rüdiger; Schauwecker, Johannes

2017-03-09

Increasing rates of prosthetic joint infection (PJI) have presented challenges for general practitioners, orthopedic surgeons and the health care system in the recent years. The diagnosis of PJI is complex; multiple diagnostic tools are used in the attempt to correctly diagnose PJI. Evidence-based algorithms can help to identify PJI using standardized diagnostic steps. We reviewed relevant publications between 1990 and 2015 using a systematic literature search in MEDLINE and PUBMED. The selected search results were then classified into levels of evidence. The keywords were prosthetic joint infection, biofilm, diagnosis, sonication, antibiotic treatment, implant-associated infection, Staph. aureus, rifampicin, implant retention, pcr, maldi-tof, serology, synovial fluid, c-reactive protein level, total hip arthroplasty (THA), total knee arthroplasty (TKA) and combinations of these terms. From an initial 768 publications, 156 publications were stringently reviewed. Publications with class I-III recommendations (EAST) were considered. We developed an algorithm for the diagnostic approach to display the complex diagnosis of PJI in a clear and logically structured process according to ISO 5807. The evidence-based standardized algorithm combines modern clinical requirements and evidence-based treatment principles. The algorithm provides a detailed transparent standard operating procedure (SOP) for diagnosing PJI. Thus, consistently high, examiner-independent process quality is assured to meet the demands of modern quality management in PJI diagnosis.

Exploring miRNA based approaches in cancer diagnostics and therapeutics.

PubMed

Mishra, Shivangi; Yadav, Tanuja; Rani, Vibha

2016-02-01

MicroRNAs (miRNAs), a highly conserved class of tissue specific, small non-protein coding RNAs maintain cell homeostasis by negative gene regulation. Proper controlling of miRNA expression is required for a balanced physiological environment, as these small molecules influence almost every genetic pathway from cell cycle checkpoint, cell proliferation to apoptosis, with a wide range of target genes. Deregulation in miRNAs expression correlates with various cancers by acting as tumor suppressors and oncogenes. Although promising therapies exist to control tumor development and progression, there is a lack of efficient diagnostic and therapeutic approaches for delineating various types of cancer. The molecularly different tumors can be differentiated by specific miRNA profiling as their phenotypic signatures, which can hence be exploited to surmount the diagnostic and therapeutic challenges. Present review discusses the involvement of miRNAs in oncogenesis with the analysis of patented research available on miRNAs. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Silk-based blood stabilization for diagnostics.

PubMed

Kluge, Jonathan A; Li, Adrian B; Kahn, Brooke T; Michaud, Dominique S; Omenetto, Fiorenzo G; Kaplan, David L

2016-05-24

Advanced personalized medical diagnostics depend on the availability of high-quality biological samples. These are typically biofluids, such as blood, saliva, or urine; and their collection and storage is critical to obtain reliable results. Without proper temperature regulation, protein biomarkers in particular can degrade rapidly in blood samples, an effect that ultimately compromises the quality and reliability of laboratory tests. Here, we present the use of silk fibroin as a solid matrix to encapsulate blood analytes, protecting them from thermally induced damage that could be encountered during nonrefrigerated transportation or freeze-thaw cycles. Blood samples are recovered by simple dissolution of the silk matrix in water. This process is demonstrated to be compatible with a number of immunoassays and provides enhanced sample preservation in comparison with traditional air-drying paper approaches. Additional processing can remediate interactions with conformational structures of the silk protein to further enhance blood stabilization and recovery. This approach can provide expanded utility for remote collection of blood and other biospecimens empowering new modalities of temperature-independent remote diagnostics.

Chronic Lower Leg Pain in Athletes

PubMed Central

Brewer, Rachel Biber; Gregory, Andrew J. M.

2012-01-01

Context: Chronic lower leg pain in athletes can be a frustrating problem for patients and a difficult diagnosis for clinicians. Myriad approaches have been suggested to evaluate these conditions. With the continued evolution of diagnostic studies, evidence-based guidance for a standard approach is unfortunately sparse. Evidence Acquisition: PubMed was searched from January 1980 to May 2011 to identify publications regarding chronic lower leg pain in athletes (excluding conditions related to the foot), including differential diagnosis, clinical presentation, physical examination, history, diagnostic workup, and treatment. Results: Leg pain in athletes can be caused by many conditions, with the most frequent being medial tibial stress syndrome; chronic exertional compartment syndrome, stress fracture, nerve entrapment, and popliteal artery entrapment syndrome are also considerations. Conservative management is the mainstay of care for the majority of causes of chronic lower leg pain; however, surgical intervention may be necessary. Conclusion: Chronic lower extremity pain in athletes includes a wide differential and can pose diagnostic dilemmas for clinicians. PMID:23016078

Molecular diagnosis and precision medicine in allergy management.

PubMed

Riccio, Anna Maria; De Ferrari, Laura; Chiappori, Alessandra; Ledda, Sabina; Passalacqua, Giovanni; Melioli, Giovanni; Canonica, Giorgio Walter

2016-11-01

Precision medicine (PM) can be defined as a structural model aimed at customizing healthcare, with medical decisions/products tailored on an individual patient at a highly detailed level. In this sense, allergy diagnostics based on molecular allergen components allows to accurately define the patient's IgE repertoire. The availability of highly specialized singleplexed and multiplexed platforms support allergists with an advanced diagnostic armamentarium. The therapeutic intervention, driven by the standard diagnostic approach, but further supported by these innovative tools may result, for instance, in a more appropriate prescription of allergen immunotherapy (AIT). Also, the phenotyping of patients, which may have relevant effects on the treatment strategy, could be take advantage by the molecular allergy diagnosis.

Intraoral fiber optic-based diagnostic for periodontal disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, P W; Gutierrez, D M; Everett, M J

2000-01-21

The purpose of this initial study was to begin development of a new, objective diagnostic instrument that will allow simultaneous quantitation of multiple proteases within a single periodontal pocket using a chemical fiber optic sensor. This approach could potentially be adapted to use specific antibodies and chemiluminescence to detect and quantitate virtually any compound and compare concentrations of different compounds within the same periodontal pocket. The device could also be used to assay secretions in salivary ducts or from a variety of wounds. The applicability is, therefore, not solely limited to dentistry and the device would be important both formore » clinical diagnostics and as a research tool.« less

Diagnosis and therapy with CRISPR advanced CRISPR based tools for point of care diagnostics and early therapies.

PubMed

Uppada, Vanita; Gokara, Mahesh; Rasineni, Girish Kumar

2018-05-20

Molecular diagnostics is of critical importance to public health worldwide. It facilitates not only detection and characterization of diseases, but also monitors drug responses, assists in the identification of genetic modifiers and disease susceptibility. Based upon DNA variation, a wide range of molecular-based tests are available to assess/diagnose diseases. The CRISPR-Cas9 system has recently emerged as a versatile tool for biological and medical research. In this system, a single guide RNA (sgRNA) directs the endonuclease Cas9 to a targeted DNA sequence for site-specific manipulation. As designing CRISPR-guided nucleases can be done easily and relatively fast, the CRISPR/Cas9 system has evolved as widely used DNA editing tool. This technique led to a large number of gene editing studies in variety of organisms. CRISPR/Cas9-mediated diagnosis and therapy has picked up pace due to specificity and accuracy of CRISPR. The aim is not only to identify specific pathogens, especially virus but also to repair disease-causing alleles by changing the DNA sequence at the exact location on the chromosome. At present, PCR-based molecular diagnostic testing predominates; however, alternative technologies aimed at reducing genome complexity without PCR are anticipated to gain momentum in the coming years. Furthermore, development of integrated chip devices should allow point-of-care testing and facilitate genetic readouts from single cells and molecules. Together with molecular based therapy CRISPR based diagnostic testing will be a revolution in modern health care settings. In this review, we emphasize on current developing diagnostic techniques based upon CRISPR Cas approach along with short insights on its therapeutic usage. Copyright © 2018 Elsevier B.V. All rights reserved.

Review on diagnosis and management of urolithiasis in pregnancy: an ESUT practical guide for urologists.

PubMed

Somani, Bhaskar K; Dellis, Athanasios; Liatsikos, Evangellos; Skolarikos, Andreas

2017-11-01

Management of urolithiasis in pregnancy can be challenging for most urologists with diagnostic and treatment dilemma to ensure the best outcome for both mother and fetus. We wanted to review the literature for urolithiasis in pregnancy with a practical management guide for urologists. A non-systematic review of literature was carried out for all English language literature using Medline. To ensure a more comprehensive search, the review of diagnosis and management of pregnant patients with urolithiasis was carried out separately, by two authors independently. Due to diagnostic complexity, investigations (US, CT, MRI) carried out were assessed separately. Our search included diagnostic studies such as US, CT and MRI (73, 20 and 27 articles, respectively) and management studies (55 articles in total). Details on etiology, radiation risk, safety of various diagnostic modalities, medications and treatment options are covered through an evidence-based approach. We provide a practical guide for urologists in what is clearly a stressful situation for patient and physician alike. Urolithiasis in pregnancy needs a careful multidisciplinary management to achieve good outcomes for both mother and baby. Our review shows that a balanced approach for diagnosis and treatment seems to achieve the best outcomes in pregnancy.

A temporally and spatially resolved electron density diagnostic method for the edge plasma based on Stark broadening

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zafar, A., E-mail: zafara@ornl.gov; Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830; Martin, E. H.

2016-11-15

An electron density diagnostic (≥10{sup 10} cm{sup −3}) capable of high temporal (ms) and spatial (mm) resolution is currently under development at Oak Ridge National Laboratory. The diagnostic is based on measuring the Stark broadened, Doppler-free spectral line profile of the n = 6–2 hydrogen Balmer series transition. The profile is then fit to a fully quantum mechanical model including the appropriate electric and magnetic field operators. The quasi-static approach used to calculate the Doppler-free spectral line profile is outlined here and the results from the model are presented for H-δ spectra for electron densities of 10{sup 10}–10{sup 13} cm{supmore » −3}. The profile shows complex behavior due to the interaction between the magnetic substates of the atom.« less

Lyme disease: the promise of Big Data, companion diagnostics and precision medicine

PubMed Central

Stricker, Raphael B; Johnson, Lorraine

2016-01-01

Lyme disease caused by the spirochete Borrelia burgdorferi has become a major worldwide epidemic. Recent studies based on Big Data registries show that >300,000 people are diagnosed with Lyme disease each year in the USA, and up to two-thirds of individuals infected with B. burgdorferi will fail conventional 30-year-old antibiotic therapy for Lyme disease. In addition, animal and human evidence suggests that sexual transmission of the Lyme spirochete may occur. Improved companion diagnostic tests for Lyme disease need to be implemented, and novel treatment approaches are urgently needed to combat the epidemic. In particular, therapies based on the principles of precision medicine could be modeled on successful “designer drug” treatment for HIV/AIDS and hepatitis C virus infection featuring targeted protease inhibitors. The use of Big Data registries, companion diagnostics and precision medicine will revolutionize the diagnosis and treatment of Lyme disease. PMID:27672336

Comprehensive Social Skills Taxonomy: Development and Application.

PubMed

Kauffman, Nancy A; Kinnealey, Moya

2015-01-01

We developed a comprehensive social skills taxonomy based on archived children's social skill goal sheets, and we applied the taxonomy to 6,897 goals of children in 6 diagnostic categories to explore patterns related to diagnosis. We used a grounded theory approach to code and analyze social skill goals and develop the taxonomy. Multivariate analysis of variance and Tukey post hoc honestly significant difference test were used to analyze differences in social skill needs among diagnostic groups. We developed a taxonomy of 7 social skill constructs or categories, descriptions, and behavioral indicators. The 7 social skill categories were reflected across 6 diagnostic groups, and differences in social skill needs among groups were identified. This comprehensive taxonomy of social skills can be useful in developing research-based individual, group, or institutional programming to improve social skills. Copyright © 2015 by the American Occupational Therapy Association, Inc.

Systematic Sensor Selection Strategy (S4) User Guide

NASA Technical Reports Server (NTRS)

Sowers, T. Shane

2012-01-01

This paper describes a User Guide for the Systematic Sensor Selection Strategy (S4). S4 was developed to optimally select a sensor suite from a larger pool of candidate sensors based on their performance in a diagnostic system. For aerospace systems, selecting the proper sensors is important for ensuring adequate measurement coverage to satisfy operational, maintenance, performance, and system diagnostic criteria. S4 optimizes the selection of sensors based on the system fault diagnostic approach while taking conflicting objectives such as cost, weight and reliability into consideration. S4 can be described as a general architecture structured to accommodate application-specific components and requirements. It performs combinational optimization with a user defined merit or cost function to identify optimum or near-optimum sensor suite solutions. The S4 User Guide describes the sensor selection procedure and presents an example problem using an open source turbofan engine simulation to demonstrate its application.

Parent-based diagnosis of ADHD is as accurate as a teacher-based diagnosis of ADHD.

PubMed

Bied, Adam; Biederman, Joseph; Faraone, Stephen

2017-04-01

To review the literature evaluating the psychometric properties of parent and teacher informants relative to a gold-standard ADHD diagnosis in pediatric populations. We included studies that included both a parent and teacher informant, a gold-standard diagnosis, and diagnostic accuracy metrics. Potential confounds were evaluated. We also assessed the 'OR' and the 'AND' rules for combining informant reports. Eight articles met inclusion criteria. The diagnostic accuracy for predicting gold standard ADHD diagnoses did not differ between parents and teachers. Sample size, sample type, participant drop-out, participant age, participant gender, geographic area of the study, and date of study publication were assessed as potential confounds. Parent and teachers both yielded moderate to good diagnostic accuracy for ADHD diagnoses. Parent reports were statistically indistinguishable from those of teachers. The predictive features of the 'OR' and 'AND' rules are useful in evaluating approaches to better integrating information from these informants.

Standing of nucleic acid testing strategies in veterinary diagnosis laboratories to uncover Mycobacterium tuberculosis complex members

PubMed Central

Costa, Pedro; Botelho, Ana; Couto, Isabel; Viveiros, Miguel; Inácio, João

2014-01-01

Nucleic acid testing (NAT) designate any molecular approach used for the detection, identification, and characterization of pathogenic microorganisms, enabling the rapid, specific, and sensitive diagnostic of infectious diseases, such as tuberculosis. These assays have been widely used since the 90s of the last century in human clinical laboratories and, subsequently, also in veterinary diagnostics. Most NAT strategies are based in the polymerase chain reaction (PCR) and its several enhancements and variations. From the conventional PCR, real-time PCR and its combinations, isothermal DNA amplification, to the nanotechnologies, here we review how the NAT assays have been applied to decipher if and which member of the Mycobacterium tuberculosis complex is present in a clinical sample. Recent advances in DNA sequencing also brought new challenges and have made possible to generate rapidly and at a low cost, large amounts of sequence data. This revolution with the high-throughput sequencing (HTS) technologies makes whole genome sequencing (WGS) and metagenomics the trendiest NAT strategies, today. The ranking of NAT techniques in the field of clinical diagnostics is rising, and we provide a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis with our view of the use of molecular diagnostics for detecting tuberculosis in veterinary laboratories, notwithstanding the gold standard being still the classical culture of the agent. The complementary use of both classical and molecular diagnostics approaches is recommended to speed the diagnostic, enabling a fast decision by competent authorities and rapid tackling of the disease. PMID:25988157

Standing of nucleic acid testing strategies in veterinary diagnosis laboratories to uncover Mycobacterium tuberculosis complex members.

PubMed

Costa, Pedro; Botelho, Ana; Couto, Isabel; Viveiros, Miguel; Inácio, João

2014-01-01

Nucleic acid testing (NAT) designate any molecular approach used for the detection, identification, and characterization of pathogenic microorganisms, enabling the rapid, specific, and sensitive diagnostic of infectious diseases, such as tuberculosis. These assays have been widely used since the 90s of the last century in human clinical laboratories and, subsequently, also in veterinary diagnostics. Most NAT strategies are based in the polymerase chain reaction (PCR) and its several enhancements and variations. From the conventional PCR, real-time PCR and its combinations, isothermal DNA amplification, to the nanotechnologies, here we review how the NAT assays have been applied to decipher if and which member of the Mycobacterium tuberculosis complex is present in a clinical sample. Recent advances in DNA sequencing also brought new challenges and have made possible to generate rapidly and at a low cost, large amounts of sequence data. This revolution with the high-throughput sequencing (HTS) technologies makes whole genome sequencing (WGS) and metagenomics the trendiest NAT strategies, today. The ranking of NAT techniques in the field of clinical diagnostics is rising, and we provide a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis with our view of the use of molecular diagnostics for detecting tuberculosis in veterinary laboratories, notwithstanding the gold standard being still the classical culture of the agent. The complementary use of both classical and molecular diagnostics approaches is recommended to speed the diagnostic, enabling a fast decision by competent authorities and rapid tackling of the disease.

Feature construction can improve diagnostic criteria for high-dimensional metabolic data in newborn screening for medium-chain acyl-CoA dehydrogenase deficiency.

PubMed

Ho, Sirikit; Lukacs, Zoltan; Hoffmann, Georg F; Lindner, Martin; Wetter, Thomas

2007-07-01

In newborn screening with tandem mass spectrometry, multiple intermediary metabolites are quantified in a single analytical run for the diagnosis of fatty-acid oxidation disorders, organic acidurias, and aminoacidurias. Published diagnostic criteria for these disorders normally incorporate a primary metabolic marker combined with secondary markers, often analyte ratios, for which the markers have been chosen to reflect metabolic pathway deviations. We applied a procedure to extract new markers and diagnostic criteria for newborn screening to the data of newborns with confirmed medium-chain acyl-CoA dehydrogenase deficiency (MCADD) and a control group from the newborn screening program, Heidelberg, Germany. We validated the results with external data of the screening center in Hamburg, Germany. We extracted new markers by performing a systematic search for analyte combinations (features) with high discriminatory performance for MCADD. To select feature thresholds, we applied automated procedures to separate controls and cases on the basis of the feature values. Finally, we built classifiers from these new markers to serve as diagnostic criteria in screening for MCADD. On the basis of chi(2) scores, we identified approximately 800 of >628,000 new analyte combinations with superior discriminatory performance compared with the best published combinations. Classifiers built with the new features achieved diagnostic sensitivities and specificities approaching 100%. Feature construction methods provide ways to disclose information hidden in the set of measured analytes. Other diagnostic tasks based on high-dimensional metabolic data might also profit from this approach.

Radiation dose reduction through combining positron emission tomography/computed tomography (PET/CT) and diagnostic CT in children and young adults with lymphoma.

PubMed

Qi, Zhihua; Gates, Erica L; O'Brien, Maureen M; Trout, Andrew T

2018-02-01

Both [F-18]2-fluoro-2-deoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT) and diagnostic CT are at times required for lymphoma staging. This means some body segments are exposed twice to X-rays for generation of CT data (diagnostic CT + localization CT). To describe a combined PET/diagnostic CT approach that modulates CT tube current along the z-axis, providing diagnostic CT of some body segments and localization CT of the remaining body segments, thereby reducing patient radiation dose. We retrospectively compared total patient radiation dose between combined PET/diagnostic CT and separately acquired PET/CT and diagnostic CT exams. When available, we calculated effective doses for both approaches in the same patient; otherwise, we used data from patients of similar size. To confirm image quality, we compared image noise (Hounsfield unit [HU] standard deviation) as measured in the liver on both combined and separately acquired diagnostic CT images. We used t-tests for dose comparisons and two one-sided tests for image-quality equivalence testing. Mean total effective dose for the CT component of the combined and separately acquired diagnostic CT exams were 6.20±2.69 and 8.17±2.61 mSv, respectively (P<0.0001). Average dose savings with the combined approach was 24.8±17.8% (2.60±2.51 mSv [range: 0.32-4.72 mSv]) of total CT effective dose. Image noise was not statistically significantly different between approaches (12.2±1.8 HU vs. 11.7±1.5 HU for the combined and separately acquired diagnostic CT images, respectively). A combined PET/diagnostic CT approach as described offers dose savings at similar image quality for children and young adults with lymphoma who have indications for both PET and diagnostic CT examinations.

Fluorescence imaging of chromosomal DNA using click chemistry

NASA Astrophysics Data System (ADS)

Ishizuka, Takumi; Liu, Hong Shan; Ito, Kenichiro; Xu, Yan

2016-09-01

Chromosome visualization is essential for chromosome analysis and genetic diagnostics. Here, we developed a click chemistry approach for multicolor imaging of chromosomal DNA instead of the traditional dye method. We first demonstrated that the commercially available reagents allow for the multicolor staining of chromosomes. We then prepared two pro-fluorophore moieties that served as light-up reporters to stain chromosomal DNA based on click reaction and visualized the clear chromosomes in multicolor. We applied this strategy in fluorescence in situ hybridization (FISH) and identified, with high sensitivity and specificity, telomere DNA at the end of the chromosome. We further extended this approach to observe several basic stages of cell division. We found that the click reaction enables direct visualization of the chromosome behavior in cell division. These results suggest that the technique can be broadly used for imaging chromosomes and may serve as a new approach for chromosome analysis and genetic diagnostics.

A connectionist model for diagnostic problem solving

NASA Technical Reports Server (NTRS)

Peng, Yun; Reggia, James A.

1989-01-01

A competition-based connectionist model for solving diagnostic problems is described. The problems considered are computationally difficult in that (1) multiple disorders may occur simultaneously and (2) a global optimum in the space exponential to the total number of possible disorders is sought as a solution. The diagnostic problem is treated as a nonlinear optimization problem, and global optimization criteria are decomposed into local criteria governing node activation updating in the connectionist model. Nodes representing disorders compete with each other to account for each individual manifestation, yet complement each other to account for all manifestations through parallel node interactions. When equilibrium is reached, the network settles into a locally optimal state. Three randomly generated examples of diagnostic problems, each of which has 1024 cases, were tested, and the decomposition plus competition plus resettling approach yielded very high accuracy.

Benefit-risk Evaluation for Diagnostics: A Framework (BED-FRAME).

PubMed

Evans, Scott R; Pennello, Gene; Pantoja-Galicia, Norberto; Jiang, Hongyu; Hujer, Andrea M; Hujer, Kristine M; Manca, Claudia; Hill, Carol; Jacobs, Michael R; Chen, Liang; Patel, Robin; Kreiswirth, Barry N; Bonomo, Robert A

2016-09-15

The medical community needs systematic and pragmatic approaches for evaluating the benefit-risk trade-offs of diagnostics that assist in medical decision making. Benefit-Risk Evaluation of Diagnostics: A Framework (BED-FRAME) is a strategy for pragmatic evaluation of diagnostics designed to supplement traditional approaches. BED-FRAME evaluates diagnostic yield and addresses 2 key issues: (1) that diagnostic yield depends on prevalence, and (2) that different diagnostic errors carry different clinical consequences. As such, evaluating and comparing diagnostics depends on prevalence and the relative importance of potential errors. BED-FRAME provides a tool for communicating the expected clinical impact of diagnostic application and the expected trade-offs of diagnostic alternatives. BED-FRAME is a useful fundamental supplement to the standard analysis of diagnostic studies that will aid in clinical decision making. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

Systems biology-based diagnostic principles as pillars of the bridge between Chinese and Western medicine.

PubMed

van der Greef, Jan; van Wietmarschen, Herman; Schroën, Jan; Wang, Mei; Hankemeier, Thomas; Xu, Guowang

2010-12-01

Innovative systems approaches to develop medicine and health care are emerging from the integration of Chinese and Western medicine strategies, philosophies and practices. The two medical systems are highly complementary as the reductionist aspects of Western medicine are favourable in acute disease situations and the holistic aspects of Chinese medicine offer more opportunities in chronic conditions and for prevention. In this article we argue that diagnosis plays a key role in building the bridge between Chinese and Western medicine. Recent advances in the study of health, healing, placebo effects and patient-physician interactions will be discussed pointing out the development of a system-based diagnosis. Especially, a system biology-based diagnosis can be used to capture phenotype information, leading towards a scientific basis for a more refined patient characterization, new diagnostic tools and personalized heath strategies. Subtyping of rheumatoid arthritis patients based on Chinese diagnostic principles is discussed as an example. New insights from this process of integrating Western and Chinese medicine will pave the way for a patient-centred health care ecosystem. © Georg Thieme Verlag KG Stuttgart · New York.

New molecular medicine: Diagnomics and pharmacogenomics

NASA Astrophysics Data System (ADS)

Kauffman, Michael G.

1999-04-01

Millennium Predictive Medicine (MPMx), a subsidiary of Millennium Pharmaceuticals, is focusing on the discovery and clinical validation of Diagnomic and Pharmacogenomic Tests which will replace many of the subjective elements of clinical decision making. Diagnomics are molecular diagnostic markers with prognostic and economic impact. While the majority of currently available diagnostics represent data points, Diagnomics allow patients and physicians to make scientifically based, individualized decisions about their disease and its therapy. Pharmacogenomics are diagnostics that specify the use or avoidance of specific therapeutics based on an individual genotype and/or disease subtype. MPMx uses the broad Millennium genomics, proteomics, and bioinformatics technologies in the analysis of human disease and drug response. These technologies permit global and unbiased approaches towards the elucidation of disease pathways and mechanisms at the molecular level. Germline or somatic mutations, RNA levels, or protein levels comprising these pathways and mechanisms are currently being evaluated as markers for disease predisposition, stage, aggressiveness, and likely drug response or drug toxicity. Diagnomic and Pharmacogenomic Tests are part of the new molecular medicine that is transforming clinical practice forma symptom/pathology-based art into a pre-symptom, mechanism- based science.

A Computer-Based, Interactive Videodisc Job Aid and Expert System for Electron Beam Lithography Integration and Diagnostic Procedures.

ERIC Educational Resources Information Center

Stevenson, Kimberly

This master's thesis describes the development of an expert system and interactive videodisc computer-based instructional job aid used for assisting in the integration of electron beam lithography devices. Comparable to all comprehensive training, expert system and job aid development require a criterion-referenced systems approach treatment to…

Applying Evidence-Centered Design for the Development of Game-Based Assessments in Physics Playground

ERIC Educational Resources Information Center

Kim, Yoon Jeon; Almond, Russell G.; Shute, Valerie J.

2016-01-01

Game-based assessment (GBA) is a specific use of educational games that employs game activities to elicit evidence for educationally valuable skills and knowledge. While this approach can provide individualized and diagnostic information about students, the design and development of assessment mechanics for a GBA is a nontrivial task. In this…

Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data.

PubMed

Pesesky, Mitchell W; Hussain, Tahir; Wallace, Meghan; Patel, Sanket; Andleeb, Saadia; Burnham, Carey-Ann D; Dantas, Gautam

2016-01-01

The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitates initial use of empiric (frequently broad-spectrum) antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0 and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance factors and incomplete genome assembly confounded the rules-based algorithm, resulting in predictions based on gene family, rather than on knowledge of the specific variant found. Low-frequency resistance caused errors in the machine-learning algorithm because those genes were not seen or seen infrequently in the test set. We also identified an example of variability in the phenotype-based results that led to disagreement with both genotype-based methods. Genotype-based antimicrobial susceptibility testing shows great promise as a diagnostic tool, and we outline specific research goals to further refine this methodology.

Cost-effectiveness analysis of rapid diagnostic test, microscopy and syndromic approach in the diagnosis of malaria in Nigeria: implications for scaling-up deployment of ACT.

PubMed

Uzochukwu, Benjamin S C; Obikeze, Eric N; Onwujekwe, Obinna E; Onoka, Chima A; Griffiths, Ulla K

2009-11-23

The diagnosis and treatment of malaria is often based on syndromic presentation (presumptive treatment) and microscopic examination of blood films. Treatment based on syndromic approach has been found to be costly, and contributes to the development of drug resistance, while microscopic diagnosis of malaria is time-consuming and labour-intensive. Also, there is lack of trained microscopists and reliable equipment especially in rural areas of Nigeria. However, although rapid diagnostic tests (RDTs) have improved the ease of appropriate diagnosis of malaria diagnosis, the cost-effectiveness of RDTs in case management of malaria has not been evaluated in Nigeria. The study hence compares the cost-effectiveness of RDT versus syndromic diagnosis and microscopy. A total of 638 patients with fever, clinically diagnosed as malaria (presumptive malaria) by health workers, were selected for examination with both RDT and microscopy. Patients positive on RDT received artemisinin-based combination therapy (ACT) and febrile patients negative on RDT received an antibiotic treatment. Using a decision tree model for a hypothetical cohort of 100,000 patients, the diagnostic alternatives considered were presumptive treatment (base strategy), RDT and microscopy. Costs were based on a consumer and provider perspective while the outcome measure was deaths averted. Information on costs and malaria epidemiology were locally generated, and along with available data on effectiveness of diagnostic tests, adherence level to drugs for treatment, and drug efficacy levels, cost-effectiveness estimates were computed using TreeAge programme. Results were reported based on costs and effects per strategy, and incremental cost-effectiveness ratios. The cost-effectiveness analysis at 43.1% prevalence level showed an incremental cost effectiveness ratio (ICER) of 221 per deaths averted between RDT and presumptive treatment, while microscopy is dominated at that level. There was also a lesser cost of RDT ($0.34 million) compared to presumptive treatment ($0.37 million) and microscopy ($0.39 million), with effectiveness values of 99,862, 99,735 and 99,851 for RDT, presumptive treatment and microscopy, respectively. Cost-effectiveness was affected by malaria prevalence level, ACT adherence level, cost of ACT, proportion of non-malaria febrile illness cases that were bacterial, and microscopy and RDT sensitivity. RDT is cost-effective when compared to other diagnostic strategies for malaria treatment at malaria prevalence of 43.1% and, therefore, a very good strategy for diagnosis of malaria in Nigeria. There is opportunity for cost savings if rapid diagnostic tests are introduced in health facilities in Nigeria for case management of malaria.

Costs and clinical outcomes for non-invasive versus invasive diagnostic approaches to patients with suspected in-stent restenosis.

PubMed

Min, James K; Hasegawa, James T; Machacz, Susanne F; O'Day, Ken

2016-02-01

This study compared costs and clinical outcomes of invasive versus non-invasive diagnostic evaluations for patients with suspected in-stent restenosis (ISR) after percutaneous coronary intervention. We developed a decision model to compare 2 year diagnosis-related costs for patients who presented with suspected ISR and were evaluated by: (1) invasive coronary angiography (ICA); (2) non-invasive stress testing strategy of myocardial perfusion imaging (MPI) with referral to ICA based on MPI; (3) coronary CT angiography-based testing strategy with referral to ICA based on CCTA. Costs were modeled from the payer's perspective using 2014 Medicare rates. 56 % of patients underwent follow-up diagnostic testing over 2 years. Compared to ICA, MPI (98.6 %) and CCTA (98.1 %) exhibited lower rates of correct diagnoses. Non-invasive strategies were associated with reduced referrals to ICA and costs compared to an ICA-based strategy, with diagnostic costs lower for CCTA than MPI. Overall 2-year costs were highest for ICA for both metallic as well as BVS stents ($1656 and $1656, respectively) when compared to MPI ($1444 and $1411) and CCTA. CCTA costs differed based upon stent size and type, and were highest for metallic stents >3.0 mm followed by metallic stents <3.0 mm, BVS < 3.0 mm and BVS > 3.0 mm ($1466 vs. $1242 vs. $855 vs. $490, respectively). MPI for suspected ISR results in lower costs and rates of complications than invasive strategies using ICA while maintaining high diagnostic performance. Depending upon stent size and type, CCTA results in lower costs than MPI.

Strategies for diagnosing leg oedema in primary care: a qualitative study of GPs' approaches.

PubMed

Diederich, Judith; Hartel, Simone; Baum, Erika; Bösner, Stefan

2014-12-01

The symptom leg oedema represents a broad range of possible underlying aetiologies. The background of leg oedema is multifactorial and usually the GP is the first contact point for patients presenting with this symptom. GPs rely on patient history and physical examination as their main diagnostic tools. To identify GPs' diagnostic approaches and heuristics in patients presenting with leg oedema. Interviews with 15 GPs (20-30 min) using a semi-structured interview-guideline were conducted. GPs described their individual diagnostic strategies concerning all patients presenting with leg oedema they had prospectively identified during the previous four weeks. Interviews were taped and transcribed verbatim. Qualitative analysis was conducted by two independent raters. GPs applied a variety of diagnostic approaches, which can be grouped in active and passive strategies. Active strategies comprised the use of decision rules and guidelines, Bayesian arguing, problem dichotomisation and discrepancy heuristics. Passive approaches included test of time, therapy as diagnosis, and taking patient assumptions into account. When dealing with leg oedema, GPs use prior information of individual patients in a specific way. There is a broad variety of diagnostic approaches that can be grouped in 'active' and 'passive' behaviour. Approaches mostly match with established diagnostic strategies in primary care.

A Diagnostic Approach for Rodent Progressive Cardiomyopathy and Like Lesions in Toxicology Studies up to 28 Days in the Sprague Dawley Rat (Part 2 of 2).

PubMed

Hailey, James R; Maleeff, Beverly E; Thomas, Heath C; Pearse, Gail; Klapwijk, Jan C; Cristofori, Patrizia G; Berridge, Brian; Kimbrough, Carie L; Parker, George A; Morton, Daniel; Elmore, Susan; Hardisty, Jerry F; Dybdal, Noel O; Rehagen, David A; Fikes, James D; Lamb, Martin; Biddle, Kathleen; Buetow, Bernard S; Carreira, Vinicius; Nyska, Abraham; Tripathi, Niraj K; Workman, Heather C; Bienvenu, Jean-Guy; Brees, Ingrid; Turk, James R; Adler, Rick R

2017-12-01

To test the diagnostic approach described in part 1 of this article, 2 exercises were completed by pathologists from multiple companies/agencies. Pathologist's examination of whole slide image (WSI) heart sections from rats using personal diagnostic approaches (exercise #1) corroborated conclusions from study #1. Using the diagnostic approach described in part 1, these pathologists examined the same WSI heart sections (exercise #2) to determine whether that approach increased consistency of diagnosis of rodent progressive cardiomyopathy (PCM) lesions. In exercise #2, there was improved consistency of categorization of small borderline morphologies and mild lesions, but a decrement in consistency of categorizing minimal lesions. Exercises 1 and 2 suggest the described diagnostic approach is representative of that in use by the majority of toxicologic pathologists across companies/agencies and that application by all may improve diagnostic consistency of PCM/like lesions. Additionally, a criterion of approximately 5% heart section involvement is suggested for separating mild from moderate or greater severity. While evidence is not absolute, until further investigation shows otherwise, microscopic changes resembling PCM, but located in the epicardial and subepicardial region of the right ventricle, may be considered as part of the spectrum of PCM.

A fast Monte Carlo EM algorithm for estimation in latent class model analysis with an application to assess diagnostic accuracy for cervical neoplasia in women with AGC

PubMed Central

Kang, Le; Carter, Randy; Darcy, Kathleen; Kauderer, James; Liao, Shu-Yuan

2013-01-01

In this article we use a latent class model (LCM) with prevalence modeled as a function of covariates to assess diagnostic test accuracy in situations where the true disease status is not observed, but observations on three or more conditionally independent diagnostic tests are available. A fast Monte Carlo EM (MCEM) algorithm with binary (disease) diagnostic data is implemented to estimate parameters of interest; namely, sensitivity, specificity, and prevalence of the disease as a function of covariates. To obtain standard errors for confidence interval construction of estimated parameters, the missing information principle is applied to adjust information matrix estimates. We compare the adjusted information matrix based standard error estimates with the bootstrap standard error estimates both obtained using the fast MCEM algorithm through an extensive Monte Carlo study. Simulation demonstrates that the adjusted information matrix approach estimates the standard error similarly with the bootstrap methods under certain scenarios. The bootstrap percentile intervals have satisfactory coverage probabilities. We then apply the LCM analysis to a real data set of 122 subjects from a Gynecologic Oncology Group (GOG) study of significant cervical lesion (S-CL) diagnosis in women with atypical glandular cells of undetermined significance (AGC) to compare the diagnostic accuracy of a histology-based evaluation, a CA-IX biomarker-based test and a human papillomavirus (HPV) DNA test. PMID:24163493

Culture-independent diagnostic testing: have we opened Pandora's box for good?

PubMed

Janda, J Michael; Abbott, Sharon A

2014-11-01

The ability to accurately and quickly identify microbial agents associated with infectious diseases has been a longstanding and continuous goal of diagnostic microbiology laboratories. Over the course of several decades, technology and testing methodologies in this field have gradually evolved from traditional- or classic-based culture and identification approaches to antigen capture systems and more molecular-oriented applications. Recently, these molecular-based applications have signaled a new era in clinical diagnostic microbiology with the commercial introduction of culture-independent diagnostic testing (CIDT) systems. The first major commercial venture into the CIDT arena involves the detection of acute bacterial gastroenteritis. Several commercial products are now on the market globally with at least 4 Food and Drug Administration approved since January of 2013. These new systems offer the direct detection of a variety of enteropathogens quickly without the need for traditional culture. In Greek mythology, Pandora opened a "jar" or "box" out of curiosity thereby releasing all of humanity's evils most notably diseases and plagues according to Hesiod's Theogony. While not ill-intentioned the only thing left in the box was Hope. Copyright © 2014 Elsevier Inc. All rights reserved.

Adulticidal Susceptibility Evaluation of Aedes albopictus Using New Diagnostic Doses in Penang Island, Malaysia.

PubMed

Rahim, Junaid; Ahmad, Abu H; Ahmad, Hamdan; Ishak, Intan H; Rus, Adanan Che; Maimusa, Hamisu A

2017-09-01

Insecticide-based vector control approaches are facing challenges due to the development of resistance in vector mosquitoes. Therefore, a proper resistance surveillance program using baseline lethal concentrations is crucial for resistance management strategies. Currently, the World Health Organization's (WHO) diagnostic doses established for Aedes aegypti and Anopheles species are being used to study the resistance status of Aedes albopictus. In this study, we established the diagnostic doses for permethrin, deltamethrin, and malathion using a known susceptible reference strain. Five field-collected populations were screened against these doses, following the WHO protocol. This study established the diagnostic dose of malathion at 2.4%, permethrin at 0.95%, and deltamethrin at 0.28%, which differ from the WHO doses for Aedes aegypti and Anopheles spp. Among the insecticides tested on the 5 wild populations, only deltamethrin showed high effectiveness. Different susceptibility and resistance patterns were observed with permethrin, malathion, and dichloro-diphenyl-trichloroethane (DDT) at 4%. This study may assist the health authorities to improve future chemical-based vector control operations in dengue-endemic areas.

Vascular dementia: Diagnostic criteria and supplementary exams. Recommendations of the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology. Part I

PubMed Central

Engelhardt, Eliasz; Tocquer, Carla; André, Charles; Moreira, Denise Madeira; Okamoto, Ivan Hideyo; Cavalcanti, José Luiz de Sá

2011-01-01

Vascular dementia (VaD) is the most prevalent form of secondary dementia and the second most common of all dementias. The present paper aims to define guidelines on the basic principles for treating patients with suspected VaD (and vascular cognitive impairment - no dementia) using an evidence-based, systematized approach. The knowledge used to define these guidelines was retrieved from searches of several databases (Medline, Scielo, Lilacs) containing scientific articles, systematic reviews, meta-analyses, largely published within the last 15 years or earlier when pertinent. Information retrieved and selected for relevance was used to analyze diagnostic criteria and to propose a diagnostic system encompassing diagnostic criteria, anamnesis, as well as supplementary and clinical exams (neuroimaging and laboratory). Wherever possible, instruments were selected that had versions previously adapted and validated for use in Brazil that take into account both schooling and age. This task led to proposed protocols for supplementary exams based on degree of priority, for application in clinical practice and research settings. PMID:29213752

Electrochemistry-based Approaches to Low Cost, High Sensitivity, Automated, Multiplexed Protein Immunoassays for Cancer Diagnostics

PubMed Central

Dixit, Chandra K.; Kadimisetty, Karteek; Otieno, Brunah A.; Tang, Chi; Malla, Spundana; Krause, Colleen E.; Rusling, James F.

2015-01-01

Early detection and reliable diagnostics are keys to effectively design cancer therapies with better prognoses. Simultaneous detection of panels of biomarker proteins holds great promise as a general tool for reliable cancer diagnostics. A major challenge in designing such a panel is to decide upon a coherent group of biomarkers which have higher specificity for a given type of cancer. The second big challenge is to develop test devices to measure these biomarkers quantitatively with high sensitivity and specificity, such that there are no interferences from the complex serum or tissue matrices. Lastly, integrating all these tests into a technology that doesn’t require exclusive training to operate, and can be used at point-of-care (POC) is another potential bottleneck in futuristic cancer diagnostics. In this article, we review electrochemistry-based tools and technologies developed and/or used in our laboratories to construct low-cost microfluidic protein arrays for highly sensitive detection of the panel of cancer-specific biomarkers with high specificity and at the same time have the potential to be translated into a POC. PMID:26525998

Electrochemistry-based approaches to low cost, high sensitivity, automated, multiplexed protein immunoassays for cancer diagnostics.

PubMed

Dixit, Chandra K; Kadimisetty, Karteek; Otieno, Brunah A; Tang, Chi; Malla, Spundana; Krause, Colleen E; Rusling, James F

2016-01-21

Early detection and reliable diagnostics are keys to effectively design cancer therapies with better prognoses. The simultaneous detection of panels of biomarker proteins holds great promise as a general tool for reliable cancer diagnostics. A major challenge in designing such a panel is to decide upon a coherent group of biomarkers which have higher specificity for a given type of cancer. The second big challenge is to develop test devices to measure these biomarkers quantitatively with high sensitivity and specificity, such that there are no interferences from the complex serum or tissue matrices. Lastly, integrating all these tests into a technology that does not require exclusive training to operate, and can be used at point-of-care (POC) is another potential bottleneck in futuristic cancer diagnostics. In this article, we review electrochemistry-based tools and technologies developed and/or used in our laboratories to construct low-cost microfluidic protein arrays for the highly sensitive detection of a panel of cancer-specific biomarkers with high specificity which at the same time has the potential to be translated into POC applications.

Systems Biology and Mode of Action Based Risk Assessment

EPA Science Inventory

The application of systems biology has increased in the past decade largely as a consequence of the human genome project and technological advances in genomics and proteomics. Systems approaches have been used in the medical & pharmaceutical realm for diagnostic purposes and targ...

Introduction

NASA Technical Reports Server (NTRS)

Wotring, Virginia E.; Southern, Sarka O.; Mentzer, Mark A.; Rodriquez-Chavez, Isaac

2014-01-01

The 2014 SPIE Sensing Technologies for Global Health, Military Medicine and Environmental Monitoring conference embraced a wealth of state-of-the-art information in basic and applied science. This event covered the latest developments in the following areas: Non-invasive Disease Diagnostics for Global Health- This opening series of two consecutive sessions focused on oral biospecimen based rapid assays and point-of-care devices for the detection of pathogens causing infectious diseases, biomarkers for cancer, and analytes for noncommunicable diseases such as diabetes. They also covered presentations on the human proteasome and microbiome with linkage to human diseases and diagnostic approaches. The sessions were built on the past experience and expertise of the National Institutes of Health, National Institutes of Dental and Craniofacial Research. Military Medicine I: Traumatic Brain Injury and PTSD-This assembly covered oral-biomarker based diagnostics for brain damage and TBI as well as prevention and rehabilitation technologies. Neurorehabilitation and noninvasive neuromodulation were also discussed as critical approaches for effective functioning. Military Medicine II: Physiology and Medicine of Extreme Environments and Spaceflight-This scientific segment showcased physiological, pharmacological and diagnostic sensing methodologies during spaceflight per the National Aeronautics and Space Administration as well as military-relevant toxicans and future sensing trends per the Department of Defense. It also included latest technologies to determine hydration status in warfighters, eye surgery using the latest laser technologies, and sensing tools for blood analysis. ? Sensing Technologies for Disease Diagnostics and Environmental Monitoring-This closing series of two consecutive sessions provided the venues to learn and discuss more results on the next generation of diagnostic tools and field technologies for diseases, including biomarker detection by digital imaging, multiplex technologies, capillary electrophoresis and molecular platforms serving as labs-on-chips. This conference allowed cross-fertilization of ideas, projects and collaborative work by a multidisciplinary audience of national and international colleagues from the academia, industry and federal government: The National Institutes of Health, National Aeronautics and Space Administration, and the Department of Defense.

Diagnostic accuracy and applicability of a PCR system for the detection of Schistosoma mansoni DNA in human urine samples from an endemic area.

PubMed

Enk, Martin Johannes; Oliveira e Silva, Guilherme; Rodrigues, Nilton Barnabé

2012-01-01

Schistosomiasis caused by Schistosoma mansoni, one of the most neglected human parasitoses in Latin America and Africa, is routinely confirmed by microscopic visualization of eggs in stool. The main limitation of this diagnostic approach is its lack of sensitivity in detecting individual low worm burdens and consequently data on infection rates in low transmission settings are little reliable. According to the scientific literature, PCR assays are characterized by high sensitivity and specificity in detecting parasite DNA in biological samples. A simple and cost effective extraction method for DNA of Schistosoma mansoni from urine samples in combination with a conventional PCR assay was developed and applied in an endemic area. This urine based PCR system was tested for diagnostic accuracy among a population of a small village in an endemic area, comparing it to a reference test composed of three different parasitological techniques. The diagnostic parameters revealed a sensitivity of 100%, a specificity of 91.20%, positive and negative predictive values of 86.25% and 100%, respectively, and a test accuracy of 94.33%. Further statistical analysis showed a k index of 0.8806, indicating an excellent agreement between the reference test and the PCR system. Data obtained from the mouse model indicate the infection can be detected one week after cercariae penetration, opening a new perspective for early detection and patient management during this stage of the disease. The data indicate that this innovative PCR system provides a simple to handle and robust diagnostic tool for the detection of S. mansoni DNA from urine samples and a promising approach to overcome the diagnostic obstacles in low transmission settings. Furthermore the principals of this molecular technique, based on the examination of human urine samples may be useful for the diagnosis of other neglected tropical diseases that can be detected by trans-renal DNA.

The global burden of diagnostic errors in primary care

PubMed Central

Singh, Hardeep; Schiff, Gordon D; Graber, Mark L; Onakpoya, Igho; Thompson, Matthew J

2017-01-01

Diagnosis is one of the most important tasks performed by primary care physicians. The World Health Organization (WHO) recently prioritized patient safety areas in primary care, and included diagnostic errors as a high-priority problem. In addition, a recent report from the Institute of Medicine in the USA, ‘Improving Diagnosis in Health Care’, concluded that most people will likely experience a diagnostic error in their lifetime. In this narrative review, we discuss the global significance, burden and contributory factors related to diagnostic errors in primary care. We synthesize available literature to discuss the types of presenting symptoms and conditions most commonly affected. We then summarize interventions based on available data and suggest next steps to reduce the global burden of diagnostic errors. Research suggests that we are unlikely to find a ‘magic bullet’ and confirms the need for a multifaceted approach to understand and address the many systems and cognitive issues involved in diagnostic error. Because errors involve many common conditions and are prevalent across all countries, the WHO’s leadership at a global level will be instrumental to address the problem. Based on our review, we recommend that the WHO consider bringing together primary care leaders, practicing frontline clinicians, safety experts, policymakers, the health IT community, medical education and accreditation organizations, researchers from multiple disciplines, patient advocates, and funding bodies among others, to address the many common challenges and opportunities to reduce diagnostic error. This could lead to prioritization of practice changes needed to improve primary care as well as setting research priorities for intervention development to reduce diagnostic error. PMID:27530239

[Coagulation Monitoring and Bleeding Management in Cardiac Surgery].

PubMed

Bein, Berthold; Schiewe, Robert

2018-05-01

The transfusion of allogeneic blood products is associated with increased morbidity and mortality. An impaired hemostasis is frequently found in patients undergoing cardiac surgery and may in turn cause bleeding and transfusions. A goal directed coagulation management addressing the often complex coagulation disorders needs sophisticated diagnostics. This may improve both patients' outcome and costs. Recent data suggest that coagulation management based on a rational algorithm is more effective than traditional therapy based on conventional laboratory variables such as PT and INR. Platelet inhibitors, cumarins, direct oral anticoagulants and heparin need different diagnostic and therapeutic approaches. An algorithm specifically developed for use during cardiac surgery is presented. Georg Thieme Verlag KG Stuttgart · New York.

A file study of refugee children referred to specialized mental health care: from an individual diagnostic to an ecological perspective.

PubMed

Villanueva O'Driscoll, Julia; Serneels, Geertrui; Imeraj, Lindita

2017-11-01

The past years have been characterized by a large refugee crisis across the globe. The exposure to preflight, flight, and resettlement stressors puts refugee children and their families at risk of developing emotional and behavioral disorders. A unique Western-based approach of mental health problems seems to be insufficient to address the complexity of interactions between individual vulnerabilities and more ecological surrounding systems. We looked into (1) the reasons for referral; and (2) the process diagnostic outcomes after ethnopsychiatric and psychological assessment. We conducted a thematic content analysis on 93 files of refugee children. The findings suggest that mental health care professionals need to hold into account the multiplicity and intertwining of ongoing challenges to the well-being of refugee children. The integration of a Western-based psychiatric assessment with a more ecologically based view can lead to a more culturally sensitive approach in refugee children and their families. This way, both under- and overdiagnosis of psychiatric disorders could be avoided to further optimalise mental health care in this population.

Histology Verification Demonstrates That Biospectroscopy Analysis of Cervical Cytology Identifies Underlying Disease More Accurately than Conventional Screening: Removing the Confounder of Discordance

PubMed Central

Gajjar, Ketan; Ahmadzai, Abdullah A.; Valasoulis, George; Trevisan, Júlio; Founta, Christina; Nasioutziki, Maria; Loufopoulos, Aristotelis; Kyrgiou, Maria; Stasinou, Sofia Melina; Karakitsos, Petros; Paraskevaidis, Evangelos; Da Gama-Rose, Bianca; Martin-Hirsch, Pierre L.; Martin, Francis L.

2014-01-01

Background Subjective visual assessment of cervical cytology is flawed, and this can manifest itself by inter- and intra-observer variability resulting ultimately in the degree of discordance in the grading categorisation of samples in screening vs. representative histology. Biospectroscopy methods have been suggested as sensor-based tools that can deliver objective assessments of cytology. However, studies to date have been apparently flawed by a corresponding lack of diagnostic efficiency when samples have previously been classed using cytology screening. This raises the question as to whether categorisation of cervical cytology based on imperfect conventional screening reduces the diagnostic accuracy of biospectroscopy approaches; are these latter methods more accurate and diagnose underlying disease? The purpose of this study was to compare the objective accuracy of infrared (IR) spectroscopy of cervical cytology samples using conventional cytology vs. histology-based categorisation. Methods Within a typical clinical setting, a total of n = 322 liquid-based cytology samples were collected immediately before biopsy. Of these, it was possible to acquire subsequent histology for n = 154. Cytology samples were categorised according to conventional screening methods and subsequently interrogated employing attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy. IR spectra were pre-processed and analysed using linear discriminant analysis. Dunn’s test was applied to identify the differences in spectra. Within the diagnostic categories, histology allowed us to determine the comparative efficiency of conventional screening vs. biospectroscopy to correctly identify either true atypia or underlying disease. Results Conventional cytology-based screening results in poor sensitivity and specificity. IR spectra derived from cervical cytology do not appear to discriminate in a diagnostic fashion when categories were based on conventional screening. Scores plots of IR spectra exhibit marked crossover of spectral points between different cytological categories. Although, significant differences between spectral bands in different categories are noted, crossover samples point to the potential for poor specificity and hampers the development of biospectroscopy as a diagnostic tool. However, when histology-based categories are used to conduct analyses, the scores plot of IR spectra exhibit markedly better segregation. Conclusions Histology demonstrates that ATR-FTIR spectroscopy of liquid-based cytology identifies the presence of underlying atypia or disease missed in conventional cytology screening. This study points to an urgent need for a future biospectroscopy study where categories are based on such histology. It will allow for the validation of this approach as a screening tool. PMID:24404130

An Integrated Approach for Aircraft Engine Performance Estimation and Fault Diagnostics

NASA Technical Reports Server (NTRS)

imon, Donald L.; Armstrong, Jeffrey B.

2012-01-01

A Kalman filter-based approach for integrated on-line aircraft engine performance estimation and gas path fault diagnostics is presented. This technique is specifically designed for underdetermined estimation problems where there are more unknown system parameters representing deterioration and faults than available sensor measurements. A previously developed methodology is applied to optimally design a Kalman filter to estimate a vector of tuning parameters, appropriately sized to enable estimation. The estimated tuning parameters can then be transformed into a larger vector of health parameters representing system performance deterioration and fault effects. The results of this study show that basing fault isolation decisions solely on the estimated health parameter vector does not provide ideal results. Furthermore, expanding the number of the health parameters to address additional gas path faults causes a decrease in the estimation accuracy of those health parameters representative of turbomachinery performance deterioration. However, improved fault isolation performance is demonstrated through direct analysis of the estimated tuning parameters produced by the Kalman filter. This was found to provide equivalent or superior accuracy compared to the conventional fault isolation approach based on the analysis of sensed engine outputs, while simplifying online implementation requirements. Results from the application of these techniques to an aircraft engine simulation are presented and discussed.

Optical diagnostics in the oral cavity: an overview.

PubMed

Wilder-Smith, P; Holtzman, J; Epstein, J; Le, A

2010-11-01

As the emphasis shifts from damage mitigation to disease prevention or reversal of early disease in the oral cavity, the need for sensitive and accurate detection and diagnostic tools become more important. Many novel and emergent optical diagnostic modalities for the oral cavity are becoming available to clinicians with a variety of desirable attributes including: (i) non-invasiveness, (ii) absence of ionizing radiation, (iii) patient-friendliness, (iv) real-time information (v) repeatability, and (vi) high-resolution surface and subsurface images. In this article, the principles behind optical diagnostic approaches, their feasibility and applicability for imaging soft and hard tissues, and their potential usefulness as a tool in the diagnosis of oral mucosal lesions, dental pathologies, and other dental applications will be reviewed. The clinical applications of light-based imaging technologies in the oral cavity and of their derivative devices will be discussed to provide the reader with a comprehensive understanding of emergent diagnostic modalities. © 2010 John Wiley & Sons A/S.

Spinal meningioma, aortic aneurysms and the missing link of observation: the anchoring heuristic approach.

PubMed

Floros, Nikolaos; Papadakis, Marios; Schelzig, Hubert; Oberhuber, Alexander

2018-03-10

Over the last three decades, the development of systematic and protocol-based algorithms, and advances in available diagnostic tests have become the indispensable parts of practising medicine. Naturally, despite the implementation of meticulous protocols involving diagnostic tests or even trials of empirical therapies, the cause of one's symptoms may still not be obvious. We herein report a case of chronic back pain, which took about 5 years to get accurately diagnosed. The case challenges the diagnostic assumptions and sets ground of discussion for the diagnostic reasoning pitfalls and heuristic biases that mislead the caring physicians and cost years of low quality of life to our patient. This case serves as an example of how anchoring heuristics can interfere in the diagnostic process of a complex and rare entity when combined with a concurrent potentially life-threatening condition. © BMJ Publishing Group Ltd (unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Companion diagnostics and molecular imaging-enhanced approaches for oncology clinical trials.

PubMed

Van Heertum, Ronald L; Scarimbolo, Robert; Ford, Robert; Berdougo, Eli; O'Neal, Michael

2015-01-01

In the era of personalized medicine, diagnostic approaches are helping pharmaceutical and biotechnology sponsors streamline the clinical trial process. Molecular assays and diagnostic imaging are routinely being used to stratify patients for treatment, monitor disease, and provide reliable early clinical phase assessments. The importance of diagnostic approaches in drug development is highlighted by the rapidly expanding global cancer diagnostics market and the emergent attention of regulatory agencies worldwide, who are beginning to offer more structured platforms and guidance for this area. In this paper, we highlight the key benefits of using companion diagnostics and diagnostic imaging with a focus on oncology clinical trials. Nuclear imaging using widely available radiopharmaceuticals in conjunction with molecular imaging of oncology targets has opened the door to more accurate disease assessment and the modernization of standard criteria for the evaluation, staging, and treatment responses of cancer patients. Furthermore, the introduction and validation of quantitative molecular imaging continues to drive and optimize the field of oncology diagnostics. Given their pivotal role in disease assessment and treatment, the validation and commercialization of diagnostic tools will continue to advance oncology clinical trials, support new oncology drugs, and promote better patient outcomes.

An optimal transportation approach for nuclear structure-based pathology.

PubMed

Wang, Wei; Ozolek, John A; Slepčev, Dejan; Lee, Ann B; Chen, Cheng; Rohde, Gustavo K

2011-03-01

Nuclear morphology and structure as visualized from histopathology microscopy images can yield important diagnostic clues in some benign and malignant tissue lesions. Precise quantitative information about nuclear structure and morphology, however, is currently not available for many diagnostic challenges. This is due, in part, to the lack of methods to quantify these differences from image data. We describe a method to characterize and contrast the distribution of nuclear structure in different tissue classes (normal, benign, cancer, etc.). The approach is based on quantifying chromatin morphology in different groups of cells using the optimal transportation (Kantorovich-Wasserstein) metric in combination with the Fisher discriminant analysis and multidimensional scaling techniques. We show that the optimal transportation metric is able to measure relevant biological information as it enables automatic determination of the class (e.g., normal versus cancer) of a set of nuclei. We show that the classification accuracies obtained using this metric are, on average, as good or better than those obtained utilizing a set of previously described numerical features. We apply our methods to two diagnostic challenges for surgical pathology: one in the liver and one in the thyroid. Results automatically computed using this technique show potentially biologically relevant differences in nuclear structure in liver and thyroid cancers.

Differential diagnosis in inflammatory bowel disease colitis: State of the art and future perspectives

PubMed Central

Tontini, Gian Eugenio; Vecchi, Maurizio; Pastorelli, Luca; Neurath, Markus F; Neumann, Helmut

2015-01-01

Distinction between Crohn’s disease of the colon-rectum and ulcerative colitis or inflammatory bowel disease (IBD) type unclassified can be of pivotal importance for a tailored clinical management, as each entity often involves specific therapeutic strategies and prognosis. Nonetheless, no gold standard is available and the uncertainty of diagnosis may frequently lead to misclassification or repeated examinations. Hence, we have performed a literature search to address the problem of differential diagnosis in IBD colitis, revised current and emerging diagnostic tools and refined disease classification strategies. Nowadays, the differential diagnosis is an untangled issue, and the proper diagnosis cannot be reached in up to 10% of patients presenting with IBD colitis. This topic is receiving emerging attention, as medical therapies, surgical approaches and leading prognostic outcomes require more and more disease-specific strategies in IBD patients. The optimization of standard diagnostic approaches based on clinical features, biomarkers, radiology, endoscopy and histopathology appears to provide only marginal benefits. Conversely, emerging diagnostic techniques in the field of gastrointestinal endoscopy, molecular pathology, genetics, epigenetics, metabolomics and proteomics have already shown promising results. Novel advanced endoscopic imaging techniques and biomarkers can shed new light for the differential diagnosis of IBD, better reflecting diverse disease behaviors based on specific pathogenic pathways. PMID:25574078

An optimal transportation approach for nuclear structure-based pathology

PubMed Central

Wang, Wei; Ozolek, John A.; Slepčev, Dejan; Lee, Ann B.; Chen, Cheng; Rohde, Gustavo K.

2012-01-01

Nuclear morphology and structure as visualized from histopathology microscopy images can yield important diagnostic clues in some benign and malignant tissue lesions. Precise quantitative information about nuclear structure and morphology, however, is currently not available for many diagnostic challenges. This is due, in part, to the lack of methods to quantify these differences from image data. We describe a method to characterize and contrast the distribution of nuclear structure in different tissue classes (normal, benign, cancer, etc.). The approach is based on quantifying chromatin morphology in different groups of cells using the optimal transportation (Kantorovich-Wasserstein) metric in combination with the Fisher discriminant analysis and multidimensional scaling techniques. We show that the optimal transportation metric is able to measure relevant biological information as it enables automatic determination of the class (e.g. normal vs. cancer) of a set of nuclei. We show that the classification accuracies obtained using this metric are, on average, as good or better than those obtained utilizing a set of previously described numerical features. We apply our methods to two diagnostic challenges for surgical pathology: one in the liver and one in the thyroid. Results automatically computed using this technique show potentially biologically relevant differences in nuclear structure in liver and thyroid cancers. PMID:20977984

Premenstrual syndrome, premenstrual dysphoric disorder, and beyond: a clinical primer for practitioners.

PubMed

Johnson, Susan R

2004-10-01

The management of adverse premenstrual symptoms has presented a difficult challenge for clinicians. However, based on numerous well-designed research studies over the last decade, we now have diagnostic criteria for the severe form of the syndrome, premenstrual dysphoric disorder, and a variety of evidence-based therapeutic strategies. This review presents a comprehensive, practical description of what the clinician needs to know to diagnose and treat adverse premenstrual symptoms at all levels of severity. Diagnostic criteria are described in detail, including a discussion of the distinction between premenstrual dysphoric disorder and premenstrual syndrome (PMS). The rationale for including prospective symptom calendars as a routine part of the diagnostic evaluation of severe symptoms is presented. The differential diagnosis of cyclic symptoms, including depression and anxiety disorders, menstrual migraine, and mastalgia, and an approach for the management of each of these problems are presented. A treatment approach is recommended that matches the treatment to the degree of problems the woman is experiencing. Serotonin reuptake inhibitors are the treatment of choice for severe symptoms, and most women with PMS/premenstrual dysphoric disorder will respond to intermittent, luteal phase-only therapy. Ovulation suppression should be reserved for women who do not respond to other forms of therapy. The role of oophorectomy is limited, and guidelines for its use are presented.

Developing a semantic web model for medical differential diagnosis recommendation.

PubMed

Mohammed, Osama; Benlamri, Rachid

2014-10-01

In this paper we describe a novel model for differential diagnosis designed to make recommendations by utilizing semantic web technologies. The model is a response to a number of requirements, ranging from incorporating essential clinical diagnostic semantics to the integration of data mining for the process of identifying candidate diseases that best explain a set of clinical features. We introduce two major components, which we find essential to the construction of an integral differential diagnosis recommendation model: the evidence-based recommender component and the proximity-based recommender component. Both approaches are driven by disease diagnosis ontologies designed specifically to enable the process of generating diagnostic recommendations. These ontologies are the disease symptom ontology and the patient ontology. The evidence-based diagnosis process develops dynamic rules based on standardized clinical pathways. The proximity-based component employs data mining to provide clinicians with diagnosis predictions, as well as generates new diagnosis rules from provided training datasets. This article describes the integration between these two components along with the developed diagnosis ontologies to form a novel medical differential diagnosis recommendation model. This article also provides test cases from the implementation of the overall model, which shows quite promising diagnostic recommendation results.

Comparison of prognostic and diagnostic approached to modeling evapotranspiration in the Nile river basin

USDA-ARS?s Scientific Manuscript database

Actual evapotranspiration (ET) can be estimated using both prognostic and diagnostic modeling approaches, providing independent yet complementary information for hydrologic applications. Both approaches have advantages and disadvantages. When provided with temporally continuous atmospheric forcing d...

Whole-body multislice computed tomography (MSCT) improves trauma care in patients requiring surgery after multiple trauma.

PubMed

Wurmb, T E; Quaisser, C; Balling, H; Kredel, M; Muellenbach, R; Kenn, W; Roewer, N; Brederlau, J

2011-04-01

Whole-body multislice helical CT becomes increasingly important as a diagnostic tool in patients with multiple injuries. Time gain in multiple-trauma patients who require emergency surgery might improve outcome. The authors hypothesised that whole-body multislice computed tomography (MSCT) (MSCT trauma protocol) as the initial diagnostic tool reduces the interval to start emergency surgery (tOR) if compared to conventional radiography, combined with abdominal ultrasound and organ-focused CT (conventional trauma protocol). The second goal of the study was to investigate whether the diagnostic approach chosen has an impact on outcome. The authors' level 1 trauma centre uses whole-body MSCT for initial radiological diagnostic work-up for patients with suspected multiple trauma. Before the introduction of MSCT in 2004, a conventional approach was used. Group I: data of trauma patients treated with conventional trauma protocol from 2001 to 2003. Group II: data from trauma patients treated with whole-body MSCT trauma protocol from 2004 to 2006. tOR in group I (n=155) was 120 (90-150) min (median and IQR) and 105 (85-133) min (median and IQR) in group II (n=163), respectively (p<0.05). Patients of group II had significantly more serious injuries. No difference in outcome data was found. 14 patients died in both groups within the first 30 days; five of these died within the first 24 h. A whole-body MSCT-based diagnostic approach to multiple trauma shortens the time interval to start emergency surgery in patients with multiple injuries. Mortality remained unchanged in both groups. Patients of group II were more seriously injured; an improvement of outcome might be assumed.

Antibody-controlled actuation of DNA-based molecular circuits.

PubMed

Engelen, Wouter; Meijer, Lenny H H; Somers, Bram; de Greef, Tom F A; Merkx, Maarten

2017-02-17

DNA-based molecular circuits allow autonomous signal processing, but their actuation has relied mostly on RNA/DNA-based inputs, limiting their application in synthetic biology, biomedicine and molecular diagnostics. Here we introduce a generic method to translate the presence of an antibody into a unique DNA strand, enabling the use of antibodies as specific inputs for DNA-based molecular computing. Our approach, antibody-templated strand exchange (ATSE), uses the characteristic bivalent architecture of antibodies to promote DNA-strand exchange reactions both thermodynamically and kinetically. Detailed characterization of the ATSE reaction allowed the establishment of a comprehensive model that describes the kinetics and thermodynamics of ATSE as a function of toehold length, antibody-epitope affinity and concentration. ATSE enables the introduction of complex signal processing in antibody-based diagnostics, as demonstrated here by constructing molecular circuits for multiplex antibody detection, integration of multiple antibody inputs using logic gates and actuation of enzymes and DNAzymes for signal amplification.

Antibody-controlled actuation of DNA-based molecular circuits

NASA Astrophysics Data System (ADS)

Engelen, Wouter; Meijer, Lenny H. H.; Somers, Bram; de Greef, Tom F. A.; Merkx, Maarten

2017-02-01

DNA-based molecular circuits allow autonomous signal processing, but their actuation has relied mostly on RNA/DNA-based inputs, limiting their application in synthetic biology, biomedicine and molecular diagnostics. Here we introduce a generic method to translate the presence of an antibody into a unique DNA strand, enabling the use of antibodies as specific inputs for DNA-based molecular computing. Our approach, antibody-templated strand exchange (ATSE), uses the characteristic bivalent architecture of antibodies to promote DNA-strand exchange reactions both thermodynamically and kinetically. Detailed characterization of the ATSE reaction allowed the establishment of a comprehensive model that describes the kinetics and thermodynamics of ATSE as a function of toehold length, antibody-epitope affinity and concentration. ATSE enables the introduction of complex signal processing in antibody-based diagnostics, as demonstrated here by constructing molecular circuits for multiplex antibody detection, integration of multiple antibody inputs using logic gates and actuation of enzymes and DNAzymes for signal amplification.

Diagnostic approaches for diabetic cardiomyopathy and myocardial fibrosis

PubMed Central

Maya, Lisandro; Villarreal, Francisco J.

2009-01-01

In diabetes mellitus, alterations in cardiac structure/function in the absence of ischemic heart disease, hypertension or other cardiac pathologies is termed diabetic cardiomyopathy. In the United States, the prevalence of diabetes mellitus continues to rise and the disease currently affects about 8% of the general population. Hence, it is imperative the use of appropriate diagnostic strategies for diabetic cardiomyopathy, which may help correctly identify the disease at early stages and implement suitable corrective therapies. Currently, there is no single diagnostic method for the identification of diabetic cardiomyopathy. Diabetic cardiomyopathy is known to induce changes in cardiac structure such as, myocardial hypertrophy, fibrosis and fat droplet deposition. Early changes in cardiac function are typically manifested as abnormal diastolic function that with time leads to loss of contractile function. Echocardiography based methods currently stands as the preferred diagnostic approach for diabetic cardiomyopathy, due to its wide availability and economical use. In addition to conventional techniques, magnetic resonance imaging and spectroscopy along with contrast agents are now leading new approaches in the diagnosis of myocardial fibrosis, and cardiac and hepatic metabolic changes. These strategies can be complemented with serum biomarkers so they can offer a clear picture as to diabetes-induced changes in cardiac structure/function even at very early stages of the disease. This review article intends to provide a summary of experimental and routine tools currently available to diagnose diabetic cardiomyopathy induced changes in cardiac structure/function. These tools can be reliably used in either experimental models of diabetes or for clinical applications. PMID:19595694

Fiber-optic system for checking the acoustical parameters of gas-turbine engine flow-through passages

NASA Astrophysics Data System (ADS)

Vinogradov, Vasiliy Y.; Morozov, Oleg G.; Nureev, Ilnur I.; Kuznetzov, Artem A.

2015-03-01

In this paper we consider the integrated approach to development of the aero-acoustical methods for diagnostics of aircraft gas-turbine engine flow-through passages by using as the base the passive fiber-optic and location technologies.

Assessing clinical reasoning (ASCLIRE): Instrument development and validation.

PubMed

Kunina-Habenicht, Olga; Hautz, Wolf E; Knigge, Michel; Spies, Claudia; Ahlers, Olaf

2015-12-01

Clinical reasoning is an essential competency in medical education. This study aimed at developing and validating a test to assess diagnostic accuracy, collected information, and diagnostic decision time in clinical reasoning. A norm-referenced computer-based test for the assessment of clinical reasoning (ASCLIRE) was developed, integrating the entire clinical decision process. In a cross-sectional study participants were asked to choose as many diagnostic measures as they deemed necessary to diagnose the underlying disease of six different cases with acute or sub-acute dyspnea and provide a diagnosis. 283 students and 20 content experts participated. In addition to diagnostic accuracy, respective decision time and number of used relevant diagnostic measures were documented as distinct performance indicators. The empirical structure of the test was investigated using a structural equation modeling approach. Experts showed higher accuracy rates and lower decision times than students. In a cross-sectional comparison, the diagnostic accuracy of students improved with the year of study. Wrong diagnoses provided by our sample were comparable to wrong diagnoses in practice. We found an excellent fit for a model with three latent factors-diagnostic accuracy, decision time, and choice of relevant diagnostic information-with diagnostic accuracy showing no significant correlation with decision time. ASCLIRE considers decision time as an important performance indicator beneath diagnostic accuracy and provides evidence that clinical reasoning is a complex ability comprising diagnostic accuracy, decision time, and choice of relevant diagnostic information as three partly correlated but still distinct aspects.

Diagnosis and management of deep venous thrombosis and pulmonary embolism in neonates and children.

PubMed

Monagle, Paul

2012-10-01

Neonates and children represent a specific population that can suffer from deep venous thrombosis (DVT) and pulmonary embolism (PE). In considering how the diagnosis and management of DVT/PE in neonates and children differs from adults, one has to consider the fundamental differences in the general characteristics of the patient population, the specific differences in the disease entity, the differences in sensitivity or specificity of diagnostic strategies and risk/benefit profile of therapeutic options available, and then finally the practical applications of therapies, using an evidence-based approach. This review will articulate the key differences in the patient population, disease entity, diagnostic strategies, and drug therapies that must be understood to apply a rigorous evidence-based approach to diagnosis and management of DVT and PE in neonates and children. Finally, there will be a brief discussion of the latest American College of Chest Physician guidelines for antithrombotic treatment in neonates and children. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Advancing Patient-centered Outcomes in Emergency Diagnostic Imaging: A Research Agenda.

PubMed

Kanzaria, Hemal K; McCabe, Aileen M; Meisel, Zachary M; LeBlanc, Annie; Schaffer, Jason T; Bellolio, M Fernanda; Vaughan, William; Merck, Lisa H; Applegate, Kimberly E; Hollander, Judd E; Grudzen, Corita R; Mills, Angela M; Carpenter, Christopher R; Hess, Erik P

2015-12-01

Diagnostic imaging is integral to the evaluation of many emergency department (ED) patients. However, relatively little effort has been devoted to patient-centered outcomes research (PCOR) in emergency diagnostic imaging. This article provides background on this topic and the conclusions of the 2015 Academic Emergency Medicine consensus conference PCOR work group regarding "Diagnostic Imaging in the Emergency Department: A Research Agenda to Optimize Utilization." The goal was to determine a prioritized research agenda to establish which outcomes related to emergency diagnostic imaging are most important to patients, caregivers, and other key stakeholders and which methods will most optimally engage patients in the decision to undergo imaging. Case vignettes are used to emphasize these concepts as they relate to a patient's decision to seek care at an ED and the care received there. The authors discuss applicable research methods and approaches such as shared decision-making that could facilitate better integration of patient-centered outcomes and patient-reported outcomes into decisions regarding emergency diagnostic imaging. Finally, based on a modified Delphi process involving members of the PCOR work group, prioritized research questions are proposed to advance the science of patient-centered outcomes in ED diagnostic imaging. © 2015 by the Society for Academic Emergency Medicine.

Understanding Short-Term Nonmigrating Tidal Variability in the Ionospheric Dynamo Region from SABER Using Information Theory and Bayesian Statistics

NASA Astrophysics Data System (ADS)

Kumari, K.; Oberheide, J.

2017-12-01

Nonmigrating tidal diagnostics of SABER temperature observations in the ionospheric dynamo region reveal a large amount of variability on time-scales of a few days to weeks. In this paper, we discuss the physical reasons for the observed short-term tidal variability using a novel approach based on Information theory and Bayesian statistics. We diagnose short-term tidal variability as a function of season, QBO, ENSO, and solar cycle and other drivers using time dependent probability density functions, Shannon entropy and Kullback-Leibler divergence. The statistical significance of the approach and its predictive capability is exemplified using SABER tidal diagnostics with emphasis on the responses to the QBO and solar cycle. Implications for F-region plasma density will be discussed.

Invasive pulmonary aspergillosis: current diagnostic methodologies and a new molecular approach.

PubMed

Moura, S; Cerqueira, L; Almeida, A

2018-05-13

The fungus Aspergillus fumigatus is the main pathogenic agent responsible for invasive pulmonary aspergillosis. Immunocompromised patients are more likely to develop this pathology due to a decrease in the immune system's defense capacity. Despite of the low occurrence of invasive pulmonary aspergillosis, this pathology presents high rates of mortality, mostly due to late and unspecific diagnosis. Currently, the diagnostic methods used to detect this fungal infection are conventional mycological examination (direct microscopic examination, histological examination, and culture), imaging, non-culture-based tests for the detection of galactomannan, β(1,3)-glucan and an extracellular glycoprotein, and molecular tests based on PCR. However, most of these methods do not detect the species A. fumigatus; they only allow the identification of genus Aspergillus. The development of more specific detection methods is of extreme importance. Fluorescent in situ hybridization-based molecular methods can be a good alternative to achieve this purpose. In this review, it is intended to point out that most of the methods used for the diagnosis of invasive pulmonary aspergillosis do not allow to detect the fungus at the species level and that fluorescence in situ hybridization-based molecular method will be a promising approach in the A. fumigatus detection.

Nanotechnology in Urology

PubMed Central

Jayasimha, Sudhindra

2017-01-01

Introduction: Nanotechnology has revolutionized our approach to medical diagnostics as well as therapeutics and has spanned an entirely new branch of research. This review addresses the potential applications of Nanotechnology in Urology. This article is based on the Dr. Sitharaman Best Essay award of the Urological Society of India for 2016. Methods: A PubMed search was performed for all relevant articles using the terms, “nanotechnology, nanoparticles, nanoshells, nanoscaffolds, and nanofibers.” Results: The developments in diagnostics include novel techniques of imaging of genitourinary malignancies, prostate-specific antigen measurement, early detection of mutations that are diagnostic for polycystic kidney disease. The potential applications of nanotechnology are in the targeted therapy of genitourinary malignancies, erectile dysfunction, overactive bladder, bladder reconstruction, construction of artificial kidneys and biodegradable stents as well as in robotic surgery. Conclusions: Nanotechnology is a rapidly emerging branch of research in urology with diverse and clinically significant applications in diagnostics as well as therapeutics. PMID:28197024

Hybrid Neural-Network: Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics Developed and Demonstrated

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2002-01-01

As part of the NASA Aviation Safety Program, a unique model-based diagnostics method that employs neural networks and genetic algorithms for aircraft engine performance diagnostics has been developed and demonstrated at the NASA Glenn Research Center against a nonlinear gas turbine engine model. Neural networks are applied to estimate the internal health condition of the engine, and genetic algorithms are used for sensor fault detection, isolation, and quantification. This hybrid architecture combines the excellent nonlinear estimation capabilities of neural networks with the capability to rank the likelihood of various faults given a specific sensor suite signature. The method requires a significantly smaller data training set than a neural network approach alone does, and it performs the combined engine health monitoring objectives of performance diagnostics and sensor fault detection and isolation in the presence of nominal and degraded engine health conditions.

A Systems Approach to Diagnostic Prescriptive Instruction.

ERIC Educational Resources Information Center

Kozma, Robert B.; And Others

This five-part document presents three approaches to research on instructional improvement, with the final two sections concentrating on problems and implications for diagnostic prescriptive instruction. Part 1 reviews comparative instructional effectiveness studies. Part 2 discusses the Trait-Treatment Interaction Approach (TTI) which is…

Digital Pathology: Data-Intensive Frontier in Medical Imaging

PubMed Central

Cooper, Lee A. D.; Carter, Alexis B.; Farris, Alton B.; Wang, Fusheng; Kong, Jun; Gutman, David A.; Widener, Patrick; Pan, Tony C.; Cholleti, Sharath R.; Sharma, Ashish; Kurc, Tahsin M.; Brat, Daniel J.; Saltz, Joel H.

2013-01-01

Pathology is a medical subspecialty that practices the diagnosis of disease. Microscopic examination of tissue reveals information enabling the pathologist to render accurate diagnoses and to guide therapy. The basic process by which anatomic pathologists render diagnoses has remained relatively unchanged over the last century, yet advances in information technology now offer significant opportunities in image-based diagnostic and research applications. Pathology has lagged behind other healthcare practices such as radiology where digital adoption is widespread. As devices that generate whole slide images become more practical and affordable, practices will increasingly adopt this technology and eventually produce an explosion of data that will quickly eclipse the already vast quantities of radiology imaging data. These advances are accompanied by significant challenges for data management and storage, but they also introduce new opportunities to improve patient care by streamlining and standardizing diagnostic approaches and uncovering disease mechanisms. Computer-based image analysis is already available in commercial diagnostic systems, but further advances in image analysis algorithms are warranted in order to fully realize the benefits of digital pathology in medical discovery and patient care. In coming decades, pathology image analysis will extend beyond the streamlining of diagnostic workflows and minimizing interobserver variability and will begin to provide diagnostic assistance, identify therapeutic targets, and predict patient outcomes and therapeutic responses. PMID:25328166

An Artificial Intelligence Approach for Gears Diagnostics in AUVs

PubMed Central

Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano

2016-01-01

In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved. PMID:27077868

An Artificial Intelligence Approach for Gears Diagnostics in AUVs.

PubMed

Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano

2016-04-12

In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved.

An expert system-based approach to prediction of year-to-year climatic variations in the North Atlantic region

NASA Astrophysics Data System (ADS)

Rodionov, S. N.; Martin, J. H.

1999-07-01

A novel approach to climate forecasting on an interannual time scale is described. The approach is based on concepts and techniques from artificial intelligence and expert systems. The suitability of this approach to climate diagnostics and forecasting problems and its advantages compared with conventional forecasting techniques are discussed. The article highlights some practical aspects of the development of climatic expert systems (CESs) and describes an implementation of such a system for the North Atlantic (CESNA). Particular attention is paid to the content of CESNA's knowledge base and those conditions that make climatic forecasts one to several years in advance possible. A detailed evaluation of the quality of the experimental real-time forecasts made by CESNA for the winters of 1995-1996, 1996-1997 and 1997-1998 are presented.

Draw your assay: Fabrication of low-cost paper-based diagnostic and multi-well test zones by drawing on a paper.

PubMed

Oyola-Reynoso, Stephanie; Heim, Andrew P; Halbertsma-Black, Julian; Zhao, C; Tevis, Ian D; Çınar, Simge; Cademartiri, Rebecca; Liu, Xinyu; Bloch, Jean-Francis; Thuo, Martin M

2015-11-01

Interest in low-cost diagnostic devices has recently gained attention, in part due to the rising cost of healthcare and the need to serve populations in resource-limited settings. A major challenge in the development of such devices is the need for hydrophobic barriers to contain polar bio-fluid analytes. Key approaches in lowering the cost in diagnostics have centered on (i) development of low-cost fabrication techniques/processes, (ii) use of affordable materials, or, (iii) minimizing the need for high-tech tools. This communication describes a simple, low-cost, adaptable, and portable method for patterning paper and subsequent use of the patterned paper in diagnostic tests. Our approach generates hydrophobic regions using a ball-point pen filled with a hydrophobizing molecule suspended in a solvent carrier. An empty ball-point pen was filled with a solution of trichloro perfluoroalkyl silane in hexanes (or hexadecane), and the pen used to draw lines on Whatman® chromatography 1 paper. The drawn regions defined the test zones since the trichloro silane reacts with the paper to give a hydrophobic barrier. The formation of the hydrophobic barriers is reaction kinetic and diffusion-limited, ensuring well defined narrow barriers. We performed colorimetric glucose assays and enzyme-linked immuno-sorbent assay (ELISA) using the created test zones. To demonstrate the versatility of this approach, we fabricated multiple devices on a single piece of paper and demonstrated the reproducibility of assays on these devices. The overall cost of devices fabricated by drawing are relatively lower (

Capillary waveguide optrodes: an approach to optical sensing in medical diagnostics

NASA Astrophysics Data System (ADS)

Lippitsch, Max E.; Draxler, Sonja; Kieslinger, Dietmar; Lehmann, Hartmut; Weigl, Bernhard H.

1996-07-01

Glass capillaries with a chemically sensitive coating on the inner surface are used as optical sensors for medical diagnostics. A capillary simultaneously serves as a sample compartment, a sensor element, and an inhomogeneous optical waveguide. Various detection schemes based on absorption, fluorescence intensity, or fluorescence lifetime are described. In absorption-based capillary waveguide optrodes the absorption in the sensor layer is analyte dependent; hence light transmission along the inhomogeneous waveguiding structure formed by the capillary wall and the sensing layer is a function of the analyte concentration. Similarly, in fluorescence-based capillary optrodes the fluorescence intensity or the fluorescence lifetime of an indicator dye fixed in the sensing layer is analyte dependent; thus the specific property of fluorescent light excited in the sensing layer and thereafter guided along the inhomogeneous waveguiding structure is a function of the analyte concentration. Both schemes are experimentally demonstrated, one with carbon dioxide as the analyte and the other one with oxygen. The device combines optical sensors with the standard glass capillaries usually applied to gather blood drops from fingertips, to yield a versatile diagnostic instrument, integrating the sample compartment, the optical sensor, and the light-collecting optics into a single piece. This ensures enhanced sensor performance as well as improved handling compared with other sensors. waveguide, blood gases, medical diagnostics.

Screening for single nucleotide variants, small indels and exon deletions with a next-generation sequencing based gene panel approach for Usher syndrome

PubMed Central

Krawitz, Peter M; Schiska, Daniela; Krüger, Ulrike; Appelt, Sandra; Heinrich, Verena; Parkhomchuk, Dmitri; Timmermann, Bernd; Millan, Jose M; Robinson, Peter N; Mundlos, Stefan; Hecht, Jochen; Gross, Manfred

2014-01-01

Usher syndrome is an autosomal recessive disorder characterized both by deafness and blindness. For the three clinical subtypes of Usher syndrome causal mutations in altogether 12 genes and a modifier gene have been identified. Due to the genetic heterogeneity of Usher syndrome, the molecular analysis is predestined for a comprehensive and parallelized analysis of all known genes by next-generation sequencing (NGS) approaches. We describe here the targeted enrichment and deep sequencing for exons of Usher genes and compare the costs and workload of this approach compared to Sanger sequencing. We also present a bioinformatics analysis pipeline that allows us to detect single-nucleotide variants, short insertions and deletions, as well as copy number variations of one or more exons on the same sequence data. Additionally, we present a flexible in silico gene panel for the analysis of sequence variants, in which newly identified genes can easily be included. We applied this approach to a cohort of 44 Usher patients and detected biallelic pathogenic mutations in 35 individuals and monoallelic mutations in eight individuals of our cohort. Thirty-nine of the sequence variants, including two heterozygous deletions comprising several exons of USH2A, have not been reported so far. Our NGS-based approach allowed us to assess single-nucleotide variants, small indels, and whole exon deletions in a single test. The described diagnostic approach is fast and cost-effective with a high molecular diagnostic yield. PMID:25333064

Screening for single nucleotide variants, small indels and exon deletions with a next-generation sequencing based gene panel approach for Usher syndrome.

PubMed

Krawitz, Peter M; Schiska, Daniela; Krüger, Ulrike; Appelt, Sandra; Heinrich, Verena; Parkhomchuk, Dmitri; Timmermann, Bernd; Millan, Jose M; Robinson, Peter N; Mundlos, Stefan; Hecht, Jochen; Gross, Manfred

2014-09-01

Usher syndrome is an autosomal recessive disorder characterized both by deafness and blindness. For the three clinical subtypes of Usher syndrome causal mutations in altogether 12 genes and a modifier gene have been identified. Due to the genetic heterogeneity of Usher syndrome, the molecular analysis is predestined for a comprehensive and parallelized analysis of all known genes by next-generation sequencing (NGS) approaches. We describe here the targeted enrichment and deep sequencing for exons of Usher genes and compare the costs and workload of this approach compared to Sanger sequencing. We also present a bioinformatics analysis pipeline that allows us to detect single-nucleotide variants, short insertions and deletions, as well as copy number variations of one or more exons on the same sequence data. Additionally, we present a flexible in silico gene panel for the analysis of sequence variants, in which newly identified genes can easily be included. We applied this approach to a cohort of 44 Usher patients and detected biallelic pathogenic mutations in 35 individuals and monoallelic mutations in eight individuals of our cohort. Thirty-nine of the sequence variants, including two heterozygous deletions comprising several exons of USH2A, have not been reported so far. Our NGS-based approach allowed us to assess single-nucleotide variants, small indels, and whole exon deletions in a single test. The described diagnostic approach is fast and cost-effective with a high molecular diagnostic yield.

The Development of a Multi-Disciplinary Educational Programme in Biomedical Diagnostics: A Novel Approach

ERIC Educational Resources Information Center

MacCormac, Aoife; O'Brien, Emma; O'Kennedy, Richard

2011-01-01

This paper describes the development of a taught Master's course in biomedical diagnostics using a novel multi-disciplinary approach. This course, the first of its kind in Ireland, covers the science and technology underlying the development of medical diagnostic devices that detect early markers of diseases such as cancer. The ethical impact of…

Data mining approach to model the diagnostic service management.

PubMed

Lee, Sun-Mi; Lee, Ae-Kyung; Park, Il-Su

2006-01-01

Korea has National Health Insurance Program operated by the government-owned National Health Insurance Corporation, and diagnostic services are provided every two year for the insured and their family members. Developing a customer relationship management (CRM) system using data mining technology would be useful to improve the performance of diagnostic service programs. Under these circumstances, this study developed a model for diagnostic service management taking into account the characteristics of subjects using a data mining approach. This study could be further used to develop an automated CRM system contributing to the increase in the rate of receiving diagnostic services.

Diagnosis of CO2 Fluxes in the Coastal Ocean

NASA Astrophysics Data System (ADS)

Dai, M.; Cao, Z.; Yang, W.; Guo, X.; Yin, Z.; Zhao, Y.

2017-12-01

Coastal ocean carbon is an important component of the global carbon cycle. However, its mechanistic-based conceptualization, a prerequisite of coastal carbon modeling and its inclusion in the Earth System Model, remains difficult due to the highest variability in both time and space. Here we show that the inter-seasonal change of the global coastal pCO2 is more determined by non-temperature factors such as biological drawdown and water mass mixing, the latter of which features the dynamic boundary processes of the coastal ocean at both land-margin and margin-open ocean interfaces. Considering these unique features, we resolve the coastal CO2 fluxes using a semi-analytical approach coupling physics-biogeochemistry and carbon-nutrients and conceptualize the coastal carbon cycle into Ocean-dominated Margins (OceMar) and River-dominated Ocean Margins (RiOMar). The diagnostic result of CO2 fluxes in the South China Sea basin and the Arabian Sea as OceMars and in the Pearl River Plume as a RioMar is consistent with field observations. Our mechanistic-based diagnostic approach therefore helps better understand and model coastal carbon cycle yet the stoichiometry of carbon-nutrients coupling needs scrutiny when applying our approach.

Nanoparticle forming reactive plasmas: a multidiagnostic approach

NASA Astrophysics Data System (ADS)

Hinz, Alexander; Wahl, Erik von; Faupel, Franz; Strunskus, Thomas; Kersten, Holger

2018-05-01

With an ever increasing interest in functional materials based on nanoparticles a large amount of research in this field is dedicated to the development of new production methods for nanoparticles. A promising class of methods for the production of nanoparticles is reactive plasmas. However, since the particle formation process and the interaction between the particles and the plasma are so far not completely understood, it remains difficult to control the particle formation. As the interaction between the nanoparticles and the plasma in which they are dispersed is complex the use of one or two diagnostics often provides only an incomplete understanding of the involved processes. Thus a multidiagnostic approach is needed. This contribution reviews the latest results from the study of nanoparticle formation in a hydrocarbon-based reactive plasma by such a multidiagnostic approach. It is shown that the use of various diagnostics like an IV-probe, optical emission spectroscopy, and a multipole resonance probe in conjunction with an investigation of the particle formation provides a much more detailed picture of these interesting, yet challenging, systems. Contribution to the Topical Issue "Fundamentals of Complex Plasmas", edited by Jürgen Meichsner, Michael Bonitz, Holger Fehske, Alexander Piel.

A novel neural-wavelet approach for process diagnostics and complex system modeling

NASA Astrophysics Data System (ADS)

Gao, Rong

Neural networks have been effective in several engineering applications because of their learning abilities and robustness. However certain shortcomings, such as slow convergence and local minima, are always associated with neural networks, especially neural networks applied to highly nonlinear and non-stationary problems. These problems can be effectively alleviated by integrating a new powerful tool, wavelets, into conventional neural networks. The multi-resolution analysis and feature localization capabilities of the wavelet transform offer neural networks new possibilities for learning. A neural wavelet network approach developed in this thesis enjoys fast convergence rate with little possibility to be caught at a local minimum. It combines the localization properties of wavelets with the learning abilities of neural networks. Two different testbeds are used for testing the efficiency of the new approach. The first is magnetic flowmeter-based process diagnostics: here we extend previous work, which has demonstrated that wavelet groups contain process information, to more general process diagnostics. A loop at Applied Intelligent Systems Lab (AISL) is used for collecting and analyzing data through the neural-wavelet approach. The research is important for thermal-hydraulic processes in nuclear and other engineering fields. The neural-wavelet approach developed is also tested with data from the electric power grid. More specifically, the neural-wavelet approach is used for performing short-term and mid-term prediction of power load demand. In addition, the feasibility of determining the type of load using the proposed neural wavelet approach is also examined. The notion of cross scale product has been developed as an expedient yet reliable discriminator of loads. Theoretical issues involved in the integration of wavelets and neural networks are discussed and future work outlined.

Psychopharmacology in School-Based Mental Health Services.

ERIC Educational Resources Information Center

Del Mundo, Amor S.; Pumariega, Andres J.; Vance, Hubert R.

1999-01-01

Discusses issues regarding the use of a pharmacological approach to the treatment of children with serious emotional and mental disorders that interfere with learning. Addresses the current state of psychopharmacological treatment for diagnostic entities and behavioral symptomatology. Discusses the roles of the child, family, and health and…

Managing and monitoring tuberculosis using web-based tools in combination with traditional approaches

PubMed Central

Chapman, Ann LN; Darton, Thomas C; Foster, Rachel A

2013-01-01

Tuberculosis (TB) remains a global health emergency. Ongoing challenges include the coordination of national and international control programs, high levels of drug resistance in many parts of the world, and availability of accurate and rapid diagnostic tests. The increasing availability and reliability of Internet access throughout both affluent and resource-limited countries brings new opportunities to improve TB management and control through the integration of web-based technologies with traditional approaches. In this review, we explore current and potential future use of web-based tools in the areas of TB diagnosis, treatment, epidemiology, service monitoring, and teaching and training. PMID:24294008

SSME fault monitoring and diagnosis expert system

NASA Technical Reports Server (NTRS)

Ali, Moonis; Norman, Arnold M.; Gupta, U. K.

1989-01-01

An expert system, called LEADER, has been designed and implemented for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations in real time. LEADER employs a set of sensors to monitor engine component performance and to detect, identify, and validate abnormalities with respect to varying engine dynamics and behavior. Two diagnostic approaches are adopted in the architecture of LEADER. In the first approach fault diagnosis is performed through learning and identifying engine behavior patterns. LEADER, utilizing this approach, generates few hypotheses about the possible abnormalities. These hypotheses are then validated based on the SSME design and functional knowledge. The second approach directs the processing of engine sensory data and performs reasoning based on the SSME design, functional knowledge, and the deep-level knowledge, i.e., the first principles (physics and mechanics) of SSME subsystems and components. This paper describes LEADER's architecture which integrates a design based reasoning approach with neural network-based fault pattern matching techniques. The fault diagnosis results obtained through the analyses of SSME ground test data are presented and discussed.

A cDNA microarray gene expression data classifier for clinical diagnostics based on graph theory.

PubMed

Benso, Alfredo; Di Carlo, Stefano; Politano, Gianfranco

2011-01-01

Despite great advances in discovering cancer molecular profiles, the proper application of microarray technology to routine clinical diagnostics is still a challenge. Current practices in the classification of microarrays' data show two main limitations: the reliability of the training data sets used to build the classifiers, and the classifiers' performances, especially when the sample to be classified does not belong to any of the available classes. In this case, state-of-the-art algorithms usually produce a high rate of false positives that, in real diagnostic applications, are unacceptable. To address this problem, this paper presents a new cDNA microarray data classification algorithm based on graph theory and is able to overcome most of the limitations of known classification methodologies. The classifier works by analyzing gene expression data organized in an innovative data structure based on graphs, where vertices correspond to genes and edges to gene expression relationships. To demonstrate the novelty of the proposed approach, the authors present an experimental performance comparison between the proposed classifier and several state-of-the-art classification algorithms.

Iron deficiency anemia: diagnosis and management.

PubMed

Clark, Susan F

2009-03-01

Iron deficiency anemia (IDA) still remains universally problematic worldwide. The primary focus of this review is to critique articles published over the past 18 months that describe strategies for the diagnosis and management of this prevalent condition. The medical community continues to lack consensus when identifying the optimal approach for the diagnosis and management of IDA. Current diagnostic recommendations revolve around the validity and practicality of current biomarkers such as soluble transferrin-receptor concentrations and others, and cause-based diagnostics that potentially include endoscopy. Management of IDA is based on supplementation combined with effective etiological treatment. Advances in oral and parenteral low-molecular-weight iron preparations has expanded and improved treatment modalities for IDA. Since the introduction of low versus high-molecular-weight intravenous iron administration, there have been fewer serious adverse events associated with parenteral iron preparations. Best practice guidelines for diagnosing and managing IDA should include the design of an algorithm that is inclusive of multiple biomarkers and cause-based diagnostics, which will provide direction in managing IDA, and distinguish between IDA from the anemia of chronic disease.

When is acute persistent cough in school-age children and adults whooping cough? A prospective case series study.

PubMed

Philipson, Kathryn; Goodyear-Smith, Felicity; Grant, Cameron C; Chong, Angela; Turner, Nikki; Stewart, Joanna

2013-08-01

Pertussis is a vaccine modified disease in most age groups and hence subtle in its presentation. Current diagnostic approaches require relatively invasive sampling. To determine the incidence of B. pertussis infection among people aged 5-49 years identified in primary care with acute persistent cough using an oral fluid based diagnostic test. Active surveillance of acute persistent cough of 2 weeks duration or greater was established in Auckland, New Zealand from May to October 2011. The 15 participating primary care practices provided care for a socioeconomically diverse population. Recent B. pertussis infection was determined by measurement of IgG antibodies to pertussis toxin (PT) in an oral fluid sample. An IgG antibody titre to PT of ≥70 arbitrary units defined recent infection. Participants reported symptoms at presentation and kept a cough diary. A total of 226 participants were enrolled: 70 (31%) were children (5-16 years) and 156 (69%) were adults (17-49 years). Oral fluid samples were obtained from 225 participants. Ten per cent (23/225) had recent B. pertussis infection including a larger proportion of children than adults (17% versus 7%, P = 0.003). Neither cough duration nor any individual symptom discriminated between those with and without recent B. pertussis infection. Pertussis is a frequent cause of acute persistent cough presenting to primary care. Clinical differentiation of pertussis from other causes of acute persistent cough is difficult. An oral fluid based diagnostic test, which is less invasive than other diagnostic approaches, has high acceptability in primary care.

When is acute persistent cough in school-age children and adults whooping cough?

PubMed Central

Philipson, Kathryn; Goodyear-Smith, Felicity; Grant, Cameron C; Chong, Angela; Turner, Nikki; Stewart, Joanna

2013-01-01

Background Pertussis is a vaccine modified disease in most age groups and hence subtle in its presentation. Current diagnostic approaches require relatively invasive sampling. Aim To determine the incidence of B. pertussis infection among people aged 5–49 years identified in primary care with acute persistent cough using an oral fluid based diagnostic test. Design and setting Active surveillance of acute persistent cough of 2 weeks duration or greater was established in Auckland, New Zealand from May to October 2011. The 15 participating primary care practices provided care for a socioeconomically diverse population. Method Recent B. pertussis infection was determined by measurement of IgG antibodies to pertussis toxin (PT) in an oral fluid sample. An IgG antibody titre to PT of ≥70 arbitrary units defined recent infection. Participants reported symptoms at presentation and kept a cough diary. Results A total of 226 participants were enrolled: 70 (31%) were children (5–16 years) and 156 (69%) were adults (17–49 years). Oral fluid samples were obtained from 225 participants. Ten per cent (23/225) had recent B. pertussis infection including a larger proportion of children than adults (17% versus 7%, P = 0.003). Neither cough duration nor any individual symptom discriminated between those with and without recent B. pertussis infection. Conclusion Pertussis is a frequent cause of acute persistent cough presenting to primary care. Clinical differentiation of pertussis from other causes of acute persistent cough is difficult. An oral fluid based diagnostic test, which is less invasive than other diagnostic approaches, has high acceptability in primary care. PMID:23972198

Functional protease profiling for diagnosis of malignant disease.

PubMed

Findeisen, Peter; Neumaier, Michael

2012-01-01

Clinical proteomic profiling by mass spectrometry (MS) aims at uncovering specific alterations within mass profiles of clinical specimens that are of diagnostic value for the detection and classification of various diseases including cancer. However, despite substantial progress in the field, the clinical proteomic profiling approaches have not matured into routine diagnostic applications so far. Their limitations are mainly related to high-abundance proteins and their complex processing by a multitude of endogenous proteases thus making rigorous standardization difficult. MS is biased towards the detection of low-molecular-weight peptides. Specifically, in serum specimens, the particular fragments of proteolytically degraded proteins are amenable to MS analysis. Proteases are known to be involved in tumour progression and tumour-specific proteases are released into the blood stream presumably as a result of invasive progression and metastasis. Thus, the determination of protease activity in clinical specimens from patients with malignant disease can offer diagnostic and also therapeutic options. The identification of specific substrates for tumour proteases in complex biological samples is challenging, but proteomic screens for proteases/substrate interactions are currently experiencing impressive progress. Such proteomic screens include peptide-based libraries, differential isotope labelling in combination with MS, quantitative degradomic analysis of proteolytically generated neo-N-termini, monitoring the degradation of exogenous reporter peptides with MS, and activity-based protein profiling. In the present article, we summarize and discuss the current status of proteomic techniques to identify tumour-specific protease-substrate interactions for functional protease profiling. Thereby, we focus on the potential diagnostic use of the respective approaches. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Teaching dermatoscopy of pigmented skin tumours to novices: comparison of analytic vs. heuristic approach.

PubMed

Tschandl, P; Kittler, H; Schmid, K; Zalaudek, I; Argenziano, G

2015-06-01

There are two strategies to approach the dermatoscopic diagnosis of pigmented skin tumours, namely the verbal-based analytic and the more visual-global heuristic method. It is not known if one or the other is more efficient in teaching dermatoscopy. To compare two teaching methods in short-term training of dermatoscopy to medical students. Fifty-seven medical students in the last year of the curriculum were given a 1-h lecture of either the heuristic- or the analytic-based teaching of dermatoscopy. Before and after this session, they were shown the same 50 lesions and asked to diagnose them and rate for chance of malignancy. Test lesions consisted of melanomas, basal cell carcinomas, nevi, seborrhoeic keratoses, benign vascular tumours and dermatofibromas. Performance measures were diagnostic accuracy regarding malignancy as measured by the area under the curves of receiver operating curves (range: 0-1), as well as per cent correct diagnoses (range: 0-100%). Diagnostic accuracy as well as per cent correct diagnoses increased by +0.21 and +32.9% (heuristic teaching) and +0.19 and +35.7% (analytic teaching) respectively (P for all <0.001). Neither for diagnostic accuracy (P = 0.585), nor for per cent correct diagnoses (P = 0.298) was a difference between the two groups. Short-term training of dermatoscopy to medical students allows significant improvement in diagnostic abilities. Choosing a heuristic or analytic method does not have an influence on this effect in short training using common pigmented skin lesions. © 2014 European Academy of Dermatology and Venereology.

Principles for new optical techniques in medical diagnostics for mHealth applications

NASA Astrophysics Data System (ADS)

Balsam, Joshua Michael

Medical diagnostics is a critical element of effective medical treatment. However, many modern and emerging diagnostic technologies are not affordable or compatible with the needs and conditions found in low-income and middle-income countries and regions. Resource-poor areas require low-cost, robust, easy-to-use, and portable diagnostics devices compatible with telemedicine (i.e. mHealth) that can be adapted to meet diverse medical needs. Many suitable devices will need to be based on optical technologies, which are used for many types of biological analyses. This dissertation describes the fabrication and detection principles for several low-cost optical technologies for mHealth applications including: (1) a webcam based multi-wavelength fluorescence plate reader, (2) a lens-free optical detector used for the detection of Botulinum A neurotoxin activity, (3) a low cost micro-array reader that allows the performance of typical fluorescence based assays demonstrated for the detection of the toxin staphylococcal enterotoxin (SEB), and (4) a wide-field flow cytometer for high throughput detection of fluorescently labeled rare cells. This dissertation discusses how these technologies can be harnessed using readily available consumer electronics components such as webcams, cell phones, CCD cameras, LEDs, and laser diodes. There are challenges in developing devices with sufficient sensitivity and specificity, and approaches are presented to overcoming these challenges to create optical detectors that can serve as low cost medical diagnostics in resource-poor settings for mHealth.

The Application of the Monte Carlo Approach to Cognitive Diagnostic Computerized Adaptive Testing With Content Constraints

ERIC Educational Resources Information Center

Mao, Xiuzhen; Xin, Tao

2013-01-01

The Monte Carlo approach which has previously been implemented in traditional computerized adaptive testing (CAT) is applied here to cognitive diagnostic CAT to test the ability of this approach to address multiple content constraints. The performance of the Monte Carlo approach is compared with the performance of the modified maximum global…

An investigative framework to facilitate epidemiological thinking during herd problem-solving.

PubMed

More, Simon J; Doherty, Michael L; O'Grady, Luke

2017-01-01

Veterinary clinicians and students commonly use diagnostic approaches appropriate for individual cases when conducting herd problem-solving. However, these approaches can be problematic, in part because they make limited use of epidemiological principles and methods, which has clear application during the investigation of herd problems. In this paper, we provide an overview of diagnostic approaches that are used when investigating individual animal cases, and the challenges faced when these approaches are directly translated from the individual to the herd. Further, we propose an investigative framework to facilitate epidemiological thinking during herd problem-solving. A number of different approaches are used when making a diagnosis on an individual animal, including pattern recognition, hypothetico-deductive reasoning, and the key abnormality method. Methods commonly applied to individuals are often adapted for herd problem-solving: 'comparison with best practice' being a herd-level adaptation of pattern recognition, and 'differential diagnoses' a herd-level adaptation of hypothetico-deductive reasoning. These approaches can be effective, however, challenges can arise. Herds are complex; a collection of individual cows, but also additional layers relating to environment, management, feeding etc. It is unrealistic to expect seamless translation of diagnostic approaches from the individual to the herd. Comparison with best practice is time-consuming and prioritisation of actions can be problematic, whereas differential diagnoses can lead to 'pathogen hunting', particularly in complex cases. Epidemiology is the science of understanding disease in populations. The focus is on the population, underpinned by principles and utilising methods that seek to allow us to generate solid conclusions from apparently uncontrolled situations. In this paper, we argue for the inclusion of epidemiological principles and methods as an additional tool for herd problem-solving, and outline an investigative framework, with examples, to effectively incorporate these principles and methods with other diagnostic approaches during herd problem-solving. Relevant measures of performance are identified, and measures of case frequencies are calculated and compared across time, in space and among animal groupings, to identify patterns, clues and plausible hypotheses, consistent with potential biological processes. With this knowledge, the subsequent investigation (relevant on-farm activities, diagnostic testing and other examinations) can be focused, and actions prioritised (specifically, those actions that are likely to make the greatest difference in addressing the problem if enacted). In our experience, this investigative framework is an effective teaching tool, facilitating epidemiological thinking among students during herd problem-solving. It is a generic and robust process, suited to many herd-based problems.

Can-Evo-Ens: Classifier stacking based evolutionary ensemble system for prediction of human breast cancer using amino acid sequences.

PubMed

Ali, Safdar; Majid, Abdul

2015-04-01

The diagnostic of human breast cancer is an intricate process and specific indicators may produce negative results. In order to avoid misleading results, accurate and reliable diagnostic system for breast cancer is indispensable. Recently, several interesting machine-learning (ML) approaches are proposed for prediction of breast cancer. To this end, we developed a novel classifier stacking based evolutionary ensemble system "Can-Evo-Ens" for predicting amino acid sequences associated with breast cancer. In this paper, first, we selected four diverse-type of ML algorithms of Naïve Bayes, K-Nearest Neighbor, Support Vector Machines, and Random Forest as base-level classifiers. These classifiers are trained individually in different feature spaces using physicochemical properties of amino acids. In order to exploit the decision spaces, the preliminary predictions of base-level classifiers are stacked. Genetic programming (GP) is then employed to develop a meta-classifier that optimal combine the predictions of the base classifiers. The most suitable threshold value of the best-evolved predictor is computed using Particle Swarm Optimization technique. Our experiments have demonstrated the robustness of Can-Evo-Ens system for independent validation dataset. The proposed system has achieved the highest value of Area Under Curve (AUC) of ROC Curve of 99.95% for cancer prediction. The comparative results revealed that proposed approach is better than individual ML approaches and conventional ensemble approaches of AdaBoostM1, Bagging, GentleBoost, and Random Subspace. It is expected that the proposed novel system would have a major impact on the fields of Biomedical, Genomics, Proteomics, Bioinformatics, and Drug Development. Copyright © 2015 Elsevier Inc. All rights reserved.

Photolithography diagnostic expert systems: a systematic approach to problem solving in a wafer fabrication facility

NASA Astrophysics Data System (ADS)

Weatherwax Scott, Caroline; Tsareff, Christopher R.

1990-06-01

One of the main goals of process engineering in the semiconductor industry is to improve wafer fabrication productivity and throughput. Engineers must work continuously toward this goal in addition to performing sustaining and development tasks. To accomplish these objectives, managers must make efficient use of engineering resources. One of the tools being used to improve efficiency is the diagnostic expert system. Expert systems are knowledge based computer programs designed to lead the user through the analysis and solution of a problem. Several photolithography diagnostic expert systems have been implemented at the Hughes Technology Center to provide a systematic approach to process problem solving. This systematic approach was achieved by documenting cause and effect analyses for a wide variety of processing problems. This knowledge was organized in the form of IF-THEN rules, a common structure for knowledge representation in expert system technology. These rules form the knowledge base of the expert system which is stored in the computer. The systems also include the problem solving methodology used by the expert when addressing a problem in his area of expertise. Operators now use the expert systems to solve many process problems without engineering assistance. The systems also facilitate the collection of appropriate data to assist engineering in solving unanticipated problems. Currently, several expert systems have been implemented to cover all aspects of the photolithography process. The systems, which have been in use for over a year, include wafer surface preparation (HMDS), photoresist coat and softbake, align and expose on a wafer stepper, and develop inspection. These systems are part of a plan to implement an expert system diagnostic environment throughout the wafer fabrication facility. In this paper, the systems' construction is described, including knowledge acquisition, rule construction, knowledge refinement, testing, and evaluation. The roles played by the process engineering expert and the knowledge engineer are discussed. The features of the systems are shown, particularly the interactive quality of the consultations and the ease of system use.

Newer diagnostic approaches to intestinal protozoa.

PubMed

van Lieshout, Lisette; Verweij, Jaco J

2010-10-01

To update the reader on the latest developments in the laboratory diagnosis of intestinal protozoa. Correct identification of a diarrhoea causing pathogens is essential for the choice of treatment in an individual patient as well as to map the aetiology of diarrhoea in a variety of patient populations. Classical diagnosis of diarrhoea causing protozoa by microscopic examination of a stool sample lacks both sensitivity and specificity. Alternative diagnostic platforms are discussed. Recent literature on the diagnosis of intestinal protozoa has focused mainly on nucleic acid-based assays, in particular the specific detection of parasite DNA in stool samples using real-time PCR. In addition, the trend has been moving from single pathogen detection to a multiplex approach, allowing simultaneous identification of multiple parasites. Different combinations of targets can be used within a routine diagnostic setting, depending on the patient population, such as children, immunocompromised individuals and those who have been travelling to tropical regions. Large-scale monitoring and evaluation of control strategies become feasible due to automation and high-throughput facilities. Improved technology also has become available for differentiating protozoa subspecies, which facilitates outbreak investigations and extensive research in molecular epidemiology.

The global burden of diagnostic errors in primary care.

PubMed

Singh, Hardeep; Schiff, Gordon D; Graber, Mark L; Onakpoya, Igho; Thompson, Matthew J

2017-06-01

Diagnosis is one of the most important tasks performed by primary care physicians. The World Health Organization (WHO) recently prioritized patient safety areas in primary care, and included diagnostic errors as a high-priority problem. In addition, a recent report from the Institute of Medicine in the USA, 'Improving Diagnosis in Health Care ', concluded that most people will likely experience a diagnostic error in their lifetime. In this narrative review, we discuss the global significance, burden and contributory factors related to diagnostic errors in primary care. We synthesize available literature to discuss the types of presenting symptoms and conditions most commonly affected. We then summarize interventions based on available data and suggest next steps to reduce the global burden of diagnostic errors. Research suggests that we are unlikely to find a 'magic bullet' and confirms the need for a multifaceted approach to understand and address the many systems and cognitive issues involved in diagnostic error. Because errors involve many common conditions and are prevalent across all countries, the WHO's leadership at a global level will be instrumental to address the problem. Based on our review, we recommend that the WHO consider bringing together primary care leaders, practicing frontline clinicians, safety experts, policymakers, the health IT community, medical education and accreditation organizations, researchers from multiple disciplines, patient advocates, and funding bodies among others, to address the many common challenges and opportunities to reduce diagnostic error. This could lead to prioritization of practice changes needed to improve primary care as well as setting research priorities for intervention development to reduce diagnostic error. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Development of a South African integrated syndromic respiratory disease guideline for primary care.

PubMed

English, René G; Bateman, Eric D; Zwarenstein, Merrick F; Fairall, Lara R; Bheekie, Angeni; Bachmann, Max O; Majara, Bosielo; Ottmani, Salah-Eddine; Scherpbier, Robert W

2008-09-01

The Practical Approach to Lung Health in South Africa (PALSA) initiative aimed to develop an integrated symptom- and sign-based (syndromic) respiratory disease guideline for nurse care practitioners working in primary care in a developing country. A multidisciplinary team developed the guideline after reviewing local barriers to respiratory health care provision, relevant health care policies, existing respiratory guidelines, and literature. Guideline drafts were evaluated by means of focus group discussions. Existing evidence-based guideline development methodologies were tailored for development of the guideline. A locally-applicable guideline based on syndromic diagnostic algorithms was developed for the management of patients 15 years and older who presented to primary care facilities with cough or difficulty breathing. PALSA has developed a guideline that integrates and presents diagnostic and management recommendations for priority respiratory diseases in adults using a symptom- and sign-based algorithmic guideline for nurses in developing countries.

MITT writer and MITT writer advanced development: Developing authoring and training systems for complex technical domains

NASA Technical Reports Server (NTRS)

Wiederholt, Bradley J.; Browning, Elica J.; Norton, Jeffrey E.; Johnson, William B.

1991-01-01

MITT Writer is a software system for developing computer based training for complex technical domains. A training system produced by MITT Writer allows a student to learn and practice troubleshooting and diagnostic skills. The MITT (Microcomputer Intelligence for Technical Training) architecture is a reasonable approach to simulation based diagnostic training. MITT delivers training on available computing equipment, delivers challenging training and simulation scenarios, and has economical development and maintenance costs. A 15 month effort was undertaken in which the MITT Writer system was developed. A workshop was also conducted to train instructors in how to use MITT Writer. Earlier versions were used to develop an Intelligent Tutoring System for troubleshooting the Minuteman Missile Message Processing System.

Antibodies and antibody-derived analytical biosensors

PubMed Central

Sharma, Shikha; Byrne, Hannah

2016-01-01

The rapid diagnosis of many diseases and timely initiation of appropriate treatment are critical determinants that promote optimal clinical outcomes and general public health. Biosensors are now being applied for rapid diagnostics due to their capacity for point-of-care use with minimum need for operator input. Antibody-based biosensors or immunosensors have revolutionized diagnostics for the detection of a plethora of analytes such as disease markers, food and environmental contaminants, biological warfare agents and illicit drugs. Antibodies are ideal biorecognition elements that provide sensors with high specificity and sensitivity. This review describes monoclonal and recombinant antibodies and different immobilization approaches crucial for antibody utilization in biosensors. Examples of applications of a variety of antibody-based sensor formats are also described. PMID:27365031

DNA-based approaches to identify forest fungi in Pacific Islands: A pilot study

Treesearch

Anna E. Case; Sara M. Ashiglar; Phil G. Cannon; Ernesto P. Militante; Edwin R. Tadiosa; Mutya Quintos-Manalo; Nelson M. Pampolina; John W. Hanna; Fred E. Brooks; Amy L. Ross-Davis; Mee-Sook Kim; Ned B. Klopfenstein

2013-01-01

DNA-based diagnostics have been successfully used to characterize diverse forest fungi (e.g., Hoff et al. 2004, Kim et al. 2006, Glaeser & Lindner 2011). DNA sequencing of the internal transcribed spacer (ITS) and large subunit (LSU) regions of nuclear ribosomal DNA (rDNA) has proved especially useful (Sonnenberg et al. 2007, Seifert 2009, Schoch et al. 2012) for...

Heat exchanger expert system logic

NASA Technical Reports Server (NTRS)

Cormier, R.

1988-01-01

The reduction is described of the operation and fault diagnostics of a Deep Space Network heat exchanger to a rule base by the application of propositional calculus to a set of logic statements. The value of this approach lies in the ease of converting the logic and subsequently implementing it on a computer as an expert system. The rule base was written in Process Intelligent Control software.

Automated turbulence forecasts for aviation hazards

NASA Astrophysics Data System (ADS)

Sharman, R.; Frehlich, R.; Vandenberghe, F.

2010-09-01

An operational turbulence forecast system for commercial and aviation use is described that is based on an ensemble of turbulence diagnostics derived from standard NWP model outputs. In the U. S. this forecast product is named GTG (Graphical Turbulence Guidance) and has been described in detail in Sharman et al., WAF 2006. Since turbulence has many sources in the atmosphere, the ensemble approach of combining diagnostics has been shown to provide greater statistical accuracy than the use of a single diagnostic, or of a subgrid tke parameterization. GTG is sponsored by the FAA, and has undergone rigorous accuracy, safety, and usability evaluations. The GTG product is now hosted on NOAA's Aviation Data Service (ADDS), web site (http://aviationweather.gov/), for access by pilots, air traffic controllers, and dispatchers. During this talk the various turbulence diagnostics, their statistical properties, and their relative performance (based on comparisons to observations) will be presented. Importantly, the model output is ɛ1/3 (where ɛ is the eddy dissipation rate), so is aircraft independent. The diagnostics are individually and collectively calibrated so that their PDFs satisfy the expected log normal distribution of ɛ^1/3. Some of the diagnostics try to take into account the role of gravity waves and inertia-gravity waves in the turbulence generation process. Although the current GTG product is based on the RUC forecast model running over the CONUS, it is transitioning to a WRF based product, and in fact WRF-based versions are currently running operationally over Taiwan and has also been implemented for use by the French Navy in climatological studies. Yet another version has been developed which uses GFS model output to provide global turbulence forecasts. Thus the forecast product is available as a postprocessing program for WRF or other model output and provides 3D maps of turbulence likelihood of any region where NWP model data is available. Although the current GTG has been used mainly for large commercial aircraft, since the output is aircraft independent it could readily be scaled to smaller aircraft such as UAVs. Further, the ensemble technique allows the diagnostics to be used to form probabilistic forecasts, in a manner similar to ensemble NWP forecasts.

Combining Model-Based and Feature-Driven Diagnosis Approaches - A Case Study on Electromechanical Actuators

NASA Technical Reports Server (NTRS)

Narasimhan, Sriram; Roychoudhury, Indranil; Balaban, Edward; Saxena, Abhinav

2010-01-01

Model-based diagnosis typically uses analytical redundancy to compare predictions from a model against observations from the system being diagnosed. However this approach does not work very well when it is not feasible to create analytic relations describing all the observed data, e.g., for vibration data which is usually sampled at very high rates and requires very detailed finite element models to describe its behavior. In such cases, features (in time and frequency domains) that contain diagnostic information are extracted from the data. Since this is a computationally intensive process, it is not efficient to extract all the features all the time. In this paper we present an approach that combines the analytic model-based and feature-driven diagnosis approaches. The analytic approach is used to reduce the set of possible faults and then features are chosen to best distinguish among the remaining faults. We describe an implementation of this approach on the Flyable Electro-mechanical Actuator (FLEA) test bed.

Applying Diagnostics to Enhance Cable System Reliability (Cable Diagnostic Focused Initiative, Phase II)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hartlein, Rick; Hampton, Nigel; Perkel, Josh

2016-02-01

The Cable Diagnostic Focused Initiative (CDFI) played a significant and powerful role in clarifying the concerns and understanding the benefits of performing diagnostic tests on underground power cable systems. This project focused on the medium and high voltage cable systems used in utility transmission and distribution (T&D) systems. While many of the analysis techniques and interpretations are applicable to diagnostics and cable systems outside of T&D, areas such as generating stations (nuclear, coal, wind, etc.) and other industrial environments were not the focus. Many large utilities in North America now deploy diagnostics or have changed their diagnostic testing approach asmore » a result of this project. Previous to the CDFI, different diagnostic technology providers individually promoted their approach as the “the best” or “the only” means of detecting cable system defects.« less

Research planning for the future of psychiatric diagnosis.

PubMed

Regier, D A; Kuhl, E A; Narrow, W E; Kupfer, D J

2012-10-01

More than 10 years prior to the anticipated 2013 publication of DSM-5, processes were set in motion to assess the research and clinical issues that would best inform future diagnostic classification of mental disorders. These efforts intended to identify the clinical and research needs within various populations, examine the current state of the science to determine the empirical evidence for improving criteria within and across disorders, and stimulate research in areas that could potentially provide evidence for change. In the second phase of the revision process, the American Psychiatric Institute for Research and Education (APIRE) recently completed the 5-year international series of 13 diagnostic conferences convened by APA/APIRE in collaboration with the World Health Organization and the National Institutes of Health (NIH), under a cooperative grant funded by the NIH. From these conferences, the DSM-5 Task Force and Work Groups have developed plans for potential revisions for DSM-5, including the incorporation of dimensional approaches within and across diagnostic groups to clarify heterogeneity, improve diagnostic validity, and enhance clinical case conceptualization. Use of dimensions for measurement-based care has been shown to be feasible in psychiatric and primary care settings and may inform monitoring of disorder threshold, severity, and treatment outcomes. The integration of dimensions with diagnostic categories represents an exciting and potentially transformative approach for DSM-5 to simultaneously address DSM-IV's clinical short-comings and create novel pathways for research in neurobiology, genetics, and psychiatric epidemiology. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Multidimensional anatomy of ‘modern type depression’ in Japan: A proposal for a different diagnostic approach to depression beyond the DSM-5

PubMed Central

Kato, Takahiro A.; Hashimoto, Ryota; Hayakawa, Kohei; Kubo, Hiroaki; Watabe, Motoki; Teo, Alan R.; Kanba, Shigenobu

2017-01-01

Japan’s prototype of depression was traditionally a melancholic depression based on the premorbid personality known as shūchaku-kishitsu proposed by Mitsuzo Shimoda in the 1930s. However, since around 2000, a novel form of depression has emerged among Japanese youth. Called ‘modern type depression (MTD)’ by the mass media, the term has quickly gained popularity among the general public, though it has not been regarded as an official medical term. Likewise, lack of consensus guidelines for its diagnosis and treatment, and a dearth of scientific literature on MTD has led to confusion when dealing with it in clinical practice in Japan. In this review article, we summarize and discuss the present situation and issues regarding MTD by focusing on historical, diagnostic, psychosocial, and cultural perspectives. We also draw on international perspectives that begin to suggest that MTD is a phenomenon that may exist not only in Japan but also in many other countries with different sociocultural and historical backgrounds. It is therefore of interest to establish whether MTD is a culture-specific phenomenon in Japan or a syndrome that can be classified using international diagnostic criteria as contained in the ICD or the DSM. We propose a novel diagnostic approach for depression that addresses MTD in order to combat the current confusion about depression under the present diagnostic systems. PMID:26350304

Multidimensional anatomy of 'modern type depression' in Japan: A proposal for a different diagnostic approach to depression beyond the DSM-5.

PubMed

Kato, Takahiro A; Hashimoto, Ryota; Hayakawa, Kohei; Kubo, Hiroaki; Watabe, Motoki; Teo, Alan R; Kanba, Shigenobu

2016-01-01

Japan's prototype of depression was traditionally a melancholic depression based on the premorbid personality known as shūchaku-kishitsu proposed by Mitsuzo Shimoda in the 1930s. However, since around 2000, a novel form of depression has emerged among Japanese youth. Called 'modern type depression (MTD)' by the mass media, the term has quickly gained popularity among the general public, though it has not been regarded as an official medical term. Likewise, lack of consensus guidelines for its diagnosis and treatment, and a dearth of scientific literature on MTD has led to confusion when dealing with it in clinical practice in Japan. In this review article, we summarize and discuss the present situation and issues regarding MTD by focusing on historical, diagnostic, psychosocial, and cultural perspectives. We also draw on international perspectives that begin to suggest that MTD is a phenomenon that may exist not only in Japan but also in many other countries with different sociocultural and historical backgrounds. It is therefore of interest to establish whether MTD is a culture-specific phenomenon in Japan or a syndrome that can be classified using international diagnostic criteria as contained in the ICD or the DSM. We propose a novel diagnostic approach for depression that addresses MTD in order to combat the current confusion about depression under the present diagnostic systems. © 2015 The Authors. Psychiatry and Clinical Neurosciences © 2015 Japanese Society of Psychiatry and Neurology.

Recent advances in photodynamic diagnosis of gastric cancer using 5-aminolevulinic acid.

PubMed

Koizumi, Noriaki; Harada, Yoshinori; Minamikawa, Takeo; Tanaka, Hideo; Otsuji, Eigo; Takamatsu, Tetsuro

2016-01-21

Photodynamic diagnosis based on 5-aminolevulinic acid-induced protoporphyrin IX has been clinically applied in many fields based upon its evidenced efficacy and adequate safety. In order to establish a personalized medicine approach for treating gastric cancer patients, rapid intraoperative detection of malignant lesions has become important. Feasibility of photodynamic diagnosis using 5-aminolevulinic acid for gastric cancer patients has been investigated, especially for the detection of peritoneal dissemination and lymph node metastasis. This method enables intraoperative real-time fluorescence detection of peritoneal dissemination, exhibiting higher sensitivity than white light observation without histopathological examination. The method also enables detection of metastatic foci within excised lymph nodes, exhibiting a diagnostic accuracy comparable to that of a current molecular diagnostics technique. Although several complicating issues still need to be resolved, such as the effect of tissue autofluorescence and the insufficient depth penetration of excitation light, this simple and rapid method has the potential to become a useful diagnostic tool for gastric cancer, as well as urinary bladder cancer and glioma.

Design in Four Diagnostic Language Assessments

ERIC Educational Resources Information Center

Cumming, Alister

2015-01-01

The studies documented in the four articles in this special issue uniquely exemplify principles of design-based research as follows: by taking innovative approaches to significant problems in the contexts of real educational practices; by addressing fundamental pedagogical and policy issues related to language, learning, and teaching; and, in the…

Evidence-Based Assessment of Child Obsessive Compulsive Disorder: Recommendations for Clinical Practice and Treatment Research

ERIC Educational Resources Information Center

Lewin, Adam B.; Piacentini, John

2010-01-01

Obsessive-compulsive disorder (OCD) presents heterogeneously and can be difficult to assess in youth. This review focuses on research-supported assessment approaches for OCD in childhood. Content areas include pre-visit screening, diagnostic establishment, differential diagnosis, assessment of comorbid psychiatric conditions, tracking symptom…

Integrating Data-Based Decision Making, Assessment for Learning and Diagnostic Testing in Formative Assessment

ERIC Educational Resources Information Center

Van der Kleij, Fabienne M.; Vermeulen, Jorine A.; Schildkamp, Kim; Eggen, Theo J. H .M.

2015-01-01

Recent research has highlighted the lack of a uniform definition of formative assessment, although its effectiveness is widely acknowledged. This paper addresses the theoretical differences and similarities amongst three approaches to formative assessment that are currently most frequently discussed in educational research literature: data-based…

Decision-Making Accuracy of CBM Progress-Monitoring Data

ERIC Educational Resources Information Center

Hintze, John M.; Wells, Craig S.; Marcotte, Amanda M.; Solomon, Benjamin G.

2018-01-01

This study examined the diagnostic accuracy associated with decision making as is typically conducted with curriculum-based measurement (CBM) approaches to progress monitoring. Using previously published estimates of the standard errors of estimate associated with CBM, 20,000 progress-monitoring data sets were simulated to model student reading…

Potential Application of Digitally Linked Tuberculosis Diagnostics for Real-Time Surveillance of Drug-Resistant Tuberculosis Transmission: Validation and Analysis of Test Results.

PubMed

Ng, Kamela Charmaine; Meehan, Conor Joseph; Torrea, Gabriela; Goeminne, Léonie; Diels, Maren; Rigouts, Leen; de Jong, Bouke Catherine; André, Emmanuel

2018-02-27

Tuberculosis (TB) is the highest-mortality infectious disease in the world and the main cause of death related to antimicrobial resistance, yet its surveillance is still paper-based. Rifampicin-resistant TB (RR-TB) is an urgent public health crisis. The World Health Organization has, since 2010, endorsed a series of rapid diagnostic tests (RDTs) that enable rapid detection of drug-resistant strains and produce large volumes of data. In parallel, most high-burden countries have adopted connectivity solutions that allow linking of diagnostics, real-time capture, and shared repository of these test results. However, these connected diagnostics and readily available test results are not used to their full capacity, as we have yet to capitalize on fully understanding the relationship between test results and specific rpoB mutations to elucidate its potential application to real-time surveillance. We aimed to validate and analyze RDT data in detail, and propose the potential use of connected diagnostics and associated test results for real-time evaluation of RR-TB transmission. We selected 107 RR-TB strains harboring 34 unique rpoB mutations, including 30 within the rifampicin resistance-determining region (RRDR), from the Belgian Coordinated Collections of Microorganisms, Antwerp, Belgium. We subjected these strains to Xpert MTB/RIF, GenoType MTBDRplus v2.0, and Genoscholar NTM + MDRTB II, the results of which were validated against the strains' available rpoB gene sequences. We determined the reproducibility of the results, analyzed and visualized the probe reactions, and proposed these for potential use in evaluating transmission. The RDT probe reactions detected most RRDR mutations tested, although we found a few critical discrepancies between observed results and manufacturers' claims. Based on published frequencies of probe reactions and RRDR mutations, we found specific probe reactions with high potential use in transmission studies: Xpert MTB/RIF probes A, Bdelayed, C, and Edelayed; Genotype MTBDRplus v2.0 WT2, WT5, and WT6; and Genoscholar NTM + MDRTB II S1 and S3. Inspection of probe reactions of disputed mutations may potentially resolve discordance between genotypic and phenotypic test results. We propose a novel approach for potential real-time detection of RR-TB transmission through fully using digitally linked TB diagnostics and shared repository of test results. To our knowledge, this is the first pragmatic and scalable work in response to the consensus of world-renowned TB experts in 2016 on the potential of diagnostic connectivity to accelerate efforts to eliminate TB. This is evidenced by the ability of our proposed approach to facilitate comparison of probe reactions between different RDTs used in the same setting. Integrating this proposed approach as a plug-in module to a connectivity platform will increase usefulness of connected TB diagnostics for RR-TB outbreak detection through real-time investigation of suspected RR-TB transmission cases based on epidemiologic linking. ©Kamela Charmaine Ng, Conor Joseph Meehan, Gabriela Torrea, Léonie Goeminne, Maren Diels, Leen Rigouts, Bouke Catherine de Jong, Emmanuel André. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 27.02.2018.

Development of quantitative radioactive methodologies on paper to determine important lateral-flow immunoassay parameters.

PubMed

Mosley, Garrett L; Nguyen, Phuong; Wu, Benjamin M; Kamei, Daniel T

2016-08-07

The lateral-flow immunoassay (LFA) is a well-established diagnostic technology that has recently seen significant advancements due in part to the rapidly expanding fields of paper diagnostics and paper-fluidics. As LFA-based diagnostics become more complex, it becomes increasingly important to quantitatively determine important parameters during the design and evaluation process. However, current experimental methods for determining these parameters have certain limitations when applied to LFA systems. In this work, we describe our novel methods of combining paper and radioactive measurements to determine nanoprobe molarity, the number of antibodies per nanoprobe, and the forward and reverse rate constants for nanoprobe binding to immobilized target on the LFA test line. Using a model LFA system that detects for the presence of the protein transferrin (Tf), we demonstrate the application of our methods, which involve quantitative experimentation and mathematical modeling. We also compare the results of our rate constant experiments with traditional experiments to demonstrate how our methods more appropriately capture the influence of the LFA environment on the binding interaction. Our novel experimental approaches can therefore more efficiently guide the research process for LFA design, leading to more rapid advancement of the field of paper-based diagnostics.

Glycosylation-Based Serum Biomarkers for Cancer Diagnostics and Prognostics.

PubMed

Kirwan, Alan; Utratna, Marta; O'Dwyer, Michael E; Joshi, Lokesh; Kilcoyne, Michelle

2015-01-01

Cancer is the second most common cause of death in developed countries with approximately 14 million newly diagnosed individuals and over 6 million cancer-related deaths in 2012. Many cancers are discovered at a more advanced stage but better survival rates are correlated with earlier detection. Current clinically approved cancer biomarkers are most effective when applied to patients with widespread cancer. Single biomarkers with satisfactory sensitivity and specificity have not been identified for the most common cancers and some biomarkers are ineffective for the detection of early stage cancers. Thus, novel biomarkers with better diagnostic and prognostic performance are required. Aberrant protein glycosylation is well known hallmark of cancer and represents a promising source of potential biomarkers. Glycoproteins enter circulation from tissues or blood cells through active secretion or leakage and patient serum is an attractive option as a source for biomarkers from a clinical and diagnostic perspective. A plethora of technical approaches have been developed to address the challenges of glycosylation structure detection and determination. This review summarises currently utilised glycoprotein biomarkers and novel glycosylation-based biomarkers from the serum glycoproteome under investigation as cancer diagnostics and for monitoring and prognostics and includes details of recent high throughput and other emerging glycoanalytical techniques.

Glycosylation-Based Serum Biomarkers for Cancer Diagnostics and Prognostics

PubMed Central

Kirwan, Alan; Utratna, Marta; O'Dwyer, Michael E.; Joshi, Lokesh

2015-01-01

Cancer is the second most common cause of death in developed countries with approximately 14 million newly diagnosed individuals and over 6 million cancer-related deaths in 2012. Many cancers are discovered at a more advanced stage but better survival rates are correlated with earlier detection. Current clinically approved cancer biomarkers are most effective when applied to patients with widespread cancer. Single biomarkers with satisfactory sensitivity and specificity have not been identified for the most common cancers and some biomarkers are ineffective for the detection of early stage cancers. Thus, novel biomarkers with better diagnostic and prognostic performance are required. Aberrant protein glycosylation is well known hallmark of cancer and represents a promising source of potential biomarkers. Glycoproteins enter circulation from tissues or blood cells through active secretion or leakage and patient serum is an attractive option as a source for biomarkers from a clinical and diagnostic perspective. A plethora of technical approaches have been developed to address the challenges of glycosylation structure detection and determination. This review summarises currently utilised glycoprotein biomarkers and novel glycosylation-based biomarkers from the serum glycoproteome under investigation as cancer diagnostics and for monitoring and prognostics and includes details of recent high throughput and other emerging glycoanalytical techniques. PMID:26509158

[The inpatient treatment of patients with anorexia nervosa in German clinics].

PubMed

Föcker, Manuel; Heidemann-Eggert, Elke; Antony, Gisela; Becker, Katja; Egberts, Karin; Ehrlich, Stefan; Fleischhaker, Christian; Hahn, Freia; Jaite, Charlotte; Kaess, Michael; M E Schulze, Ulrike; Sinzig, Judith; Wagner, Catharina; Legenbauer, Tanja; Renner, Tobias; Wessing, Ida; Herpertz-Dahlmann, Beate; Hebebrand, Johannes; Bühren, Katharina

2017-09-01

The medium- and long-term effects and side effects of inpatient treatment of patients with anorexia nervosa is still a matter of debate. The German S3-guidelines underline the importance of providing specialized and competent treatment. In this article we focus on the inpatient service structure in German child and adolescent psychiatric clinics with regard to their diagnostic and therapeutic concepts. A self-devised questionnaire was sent to 163 German child and adolescent psychiatric clinics. The questionnaire focused on the characteristics of the respective clinic as well as its diagnostic and therapeutic strategies. All clinics with an inpatient service for patients with anorexia nervosa (N = 84) provide single-therapy, family-based interventions and psychoeducation. A target weight is defined in nearly all clinics, and the mean intended weight gain per week is 486 g (range: 200 g to 700 g/week; SD = 117). Certain diagnostic tests and therapeutic interventions are used heterogeneously. This is the first study investigating the inpatient service structure for patients with anorexia nervosa in German clinics. Despite the provision of guideline-based therapy in all clinics, heterogeneous approaches were apparent with respect to specific diagnostic and therapeutic concepts.

A Markov Chain-based quantitative study of angular distribution of photons through turbid slabs via isotropic light scattering

NASA Astrophysics Data System (ADS)

Li, Xuesong; Northrop, William F.

2016-04-01

This paper describes a quantitative approach to approximate multiple scattering through an isotropic turbid slab based on Markov Chain theorem. There is an increasing need to utilize multiple scattering for optical diagnostic purposes; however, existing methods are either inaccurate or computationally expensive. Here, we develop a novel Markov Chain approximation approach to solve multiple scattering angular distribution (AD) that can accurately calculate AD while significantly reducing computational cost compared to Monte Carlo simulation. We expect this work to stimulate ongoing multiple scattering research and deterministic reconstruction algorithm development with AD measurements.

Inter-rater reliability of twelve diagnostic systems of schizophrenia.

PubMed

Helmes, E; Landmark, J; Kazarian, S S

1983-05-01

The present and past symptomatology of 31 chronic schizophrenics was rated by four independent judges, two experienced clinical psychiatrists and two psychiatric residents, in a context more representative of actual clinical practice than most research studies. Ratings were made on 64 symptoms derived from 12 diagnostic systems, based on either live or videotaped interviews for present symptomatology and case records for past symptomatology. Inter-rater reliabilities were higher for present than for past symptoms, and in general did not approach those reported for highly trained raters. There were no differences between live and videotaped interviews. Diagnostic systems differed widely in rater agreement. The most consistent across both past and present symptomatology were the systems of Langfeldt, Schneider, and DSM-III, for which the level of reliability was consistent with other studies.

MSE commissioning and other major diagnostic updates on KSTAR

NASA Astrophysics Data System (ADS)

Ko, Jinseok; Kstar Team

2015-11-01

The motional Stark effect (MSE) diagnostic based on the photoelastic-modulator (PEM) approach has been commissioned for the Korea Superconducting Tokamak Advanced Research (KSTAR). The 25-channel MSE system with the polarization-preserving front optics and precise tilt-tuning narrow bandpass filters provides the spatial resolution less than 1 cm in most of the plasma cross section and about 10 millisecond of time resolution. The polarization response curves with the daily Faraday rotation correction provides reliable pitch angle profiles for the KSTAR discharges with the MSE-optimized energy combination in the three-ion-source neutral beam injection. Some major diagnostic advances such as the poloidal charge exchange spectroscopy, the improved Thomson-scatting system, and the divertor infrared TV are reported as well. Work supported by the Ministry of Science, ICT and Future Planning, Korea.

Combined use of laser Doppler flowmetry and skin thermometry for functional diagnostics of intradermal finger vessels.

PubMed

Zherebtsov, Evgeny A; Zherebtsova, Angelina I; Doronin, Alexander; Dunaev, Andrey V; Podmasteryev, Konstantin V; Bykov, Alexander; Meglinski, Igor

2017-04-01

We introduce a noninvasive diagnostic approach for functional monitoring of blood microflows in capillaries and thermoregulatory vessels within the skin. The measuring system is based on the combined use of laser Doppler flowmetry and skin contact thermometry. The obtained results suggest that monitoring of blood microcirculation during the occlusion, performed in conjunction with the skin temperature measurements in the thermally stabilized medium, has a great potential for quantitative assessment of angiospatic dysfunctions of the peripheral blood vessels. The indices of blood flow reserve and temperature response were measured and used as the primarily parameters of the functional diagnostics of the peripheral vessels of skin. Utilizing these parameters, a simple phenomenological model has been suggested to identify patients with angiospastic violations in the vascular system.

The challenges of oral-based diagnostics in extending the role of dentistry as a health care profession: property rights, privacy, and informed consent.

PubMed

Vernillo, Anthony; Welie, Jos V M; Naidoo, Sudeshni; Malamud, Daniel

2011-01-01

Saliva may be a legal and ethical counterpart of other bodily fluids in diagnostic testing to blood and urine, with regard to its role in diagnostic testing. Two paradigms that have been proposed in the literature to address these challenges are reviewed in this paper. The first is centered on ownership and property rights to saliva, including financial compensation from commercially developed products using saliva. The commodification of saliva as property is also discussed. The second paradigm is related to privacy and the potential for genetic discrimination, given the unwarranted disclosure of confidential information. The management of saliva specimens from dental patients and research participants will also require the implementation of innovative approaches to obtain informed consent.

Combined use of laser Doppler flowmetry and skin thermometry for functional diagnostics of intradermal finger vessels

NASA Astrophysics Data System (ADS)

Zherebtsov, Evgeny A.; Zherebtsova, Angelina I.; Doronin, Alexander; Dunaev, Andrey V.; Podmasteryev, Konstantin V.; Bykov, Alexander; Meglinski, Igor

2017-04-01

We introduce a noninvasive diagnostic approach for functional monitoring of blood microflows in capillaries and thermoregulatory vessels within the skin. The measuring system is based on the combined use of laser Doppler flowmetry and skin contact thermometry. The obtained results suggest that monitoring of blood microcirculation during the occlusion, performed in conjunction with the skin temperature measurements in the thermally stabilized medium, has a great potential for quantitative assessment of angiospatic dysfunctions of the peripheral blood vessels. The indices of blood flow reserve and temperature response were measured and used as the primarily parameters of the functional diagnostics of the peripheral vessels of skin. Utilizing these parameters, a simple phenomenological model has been suggested to identify patients with angiospastic violations in the vascular system.

Pulpal perio relations: Interdisciplinary diagnostic approach - I

PubMed Central

Nirola, Ashutosh; Grover, Sunanda; Sharma, Ajay; Kaur, Damanjeet

2011-01-01

Lesions of pulpal and periodontal origin may perpetuate from either the infections of dental pulp or periodontium or alveolar bone. This review focuses on interdisciplinary diagnostic approach towards lesions of periodontal or endodontic origin. PMID:21772729

Sugars Can Actually Be Good For Your Health (LBNL Science at the Theater)

ScienceCinema

Bertozzi, Carolyn

2018-05-25

Like peanut M&Ms, all cells are coated with sugars but the functions of these sugar coatings were a mystery until very recently. This presentation will highlight recent fascinating discoveries regarding why cells are coated with sugars, as well as new tools for cancer detection that take advantage of the cells sugar coating. Professor Bertozzis lab focuses on profiling changes in cell surface glycosylation associated with cancer, inflammation and bacterial infection, and exploiting this information for development of diagnostic and therapeutic approaches. In addition, her group develops nanoscience-based technologies for probing cell function and for medical diagnostics.

VLPs of HCV local isolates for HCV immunoassay diagnostic approach in Indonesia

NASA Astrophysics Data System (ADS)

Prasetyo, Afiono Agung

2017-01-01

Hepatitis C Virus (HCV) infection is a major global disease which often leads to morbidity and mortality. Low survival is related to the lack of adequate diagnostic because HCV infection is frequently asymptomatic and there are no specific diagnostic tests due to the fast transformation of the virus. Here, we investigated the VLPs (virus-like particles) of HCV local isolate as an immunoassay diagnostic approach to detect HCV infection, especially in Indonesia. The core, E1, and E2 of HCV local isolate genes were cloned and molecular analyzed, either as single or in recombinant-VLP form, to determine the molecular and chemical characteristics of each VLPs related to their potential use as an immunoassay detection method for HCV infection. The results indicated the molecular and chemical character of each VLPs are comparable. Conclusion: VLPs of HCV has the potential as an immunoassay diagnostic approach to detect HCV infection.

A new generation of cancer genome diagnostics for routine clinical use: overcoming the roadblocks to personalized cancer medicine.

PubMed

Heuckmann, J M; Thomas, R K

2015-09-01

The identification of 'druggable' kinase gene alterations has revolutionized cancer treatment in the last decade by providing new and successfully targetable drug targets. Thus, genotyping tumors for matching the right patients with the right drugs have become a clinical routine. Today, advances in sequencing technology and computational genome analyses enable the discovery of a constantly growing number of genome alterations relevant for clinical decision making. As a consequence, several technological approaches have emerged in order to deal with these rapidly increasing demands for clinical cancer genome analyses. Here, we describe challenges on the path to the broad introduction of diagnostic cancer genome analyses and the technologies that can be applied to overcome them. We define three generations of molecular diagnostics that are in clinical use. The latest generation of these approaches involves deep and thus, highly sensitive sequencing of all therapeutically relevant types of genome alterations-mutations, copy number alterations and rearrangements/fusions-in a single assay. Such approaches therefore have substantial advantages (less time and less tissue required) over PCR-based methods that typically have to be combined with fluorescence in situ hybridization for detection of gene amplifications and fusions. Since these new technologies work reliably on routine diagnostic formalin-fixed, paraffin-embedded specimens, they can help expedite the broad introduction of personalized cancer therapy into the clinic by providing comprehensive, sensitive and accurate cancer genome diagnoses in 'real-time'. © The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

QTL-seq approach identified genomic regions and diagnostic markers for rust and late leaf spot resistance in groundnut (Arachis hypogaea L.).

PubMed

Pandey, Manish K; Khan, Aamir W; Singh, Vikas K; Vishwakarma, Manish K; Shasidhar, Yaduru; Kumar, Vinay; Garg, Vanika; Bhat, Ramesh S; Chitikineni, Annapurna; Janila, Pasupuleti; Guo, Baozhu; Varshney, Rajeev K

2017-08-01

Rust and late leaf spot (LLS) are the two major foliar fungal diseases in groundnut, and their co-occurrence leads to significant yield loss in addition to the deterioration of fodder quality. To identify candidate genomic regions controlling resistance to rust and LLS, whole-genome resequencing (WGRS)-based approach referred as 'QTL-seq' was deployed. A total of 231.67 Gb raw and 192.10 Gb of clean sequence data were generated through WGRS of resistant parent and the resistant and susceptible bulks for rust and LLS. Sequence analysis of bulks for rust and LLS with reference-guided resistant parent assembly identified 3136 single-nucleotide polymorphisms (SNPs) for rust and 66 SNPs for LLS with the read depth of ≥7 in the identified genomic region on pseudomolecule A03. Detailed analysis identified 30 nonsynonymous SNPs affecting 25 candidate genes for rust resistance, while 14 intronic and three synonymous SNPs affecting nine candidate genes for LLS resistance. Subsequently, allele-specific diagnostic markers were identified for three SNPs for rust resistance and one SNP for LLS resistance. Genotyping of one RIL population (TAG 24 × GPBD 4) with these four diagnostic markers revealed higher phenotypic variation for these two diseases. These results suggest usefulness of QTL-seq approach in precise and rapid identification of candidate genomic regions and development of diagnostic markers for breeding applications. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

A probabilistic approach to segmentation and classification of neoplasia in uterine cervix images using color and geometric features

NASA Astrophysics Data System (ADS)

Srinivasan, Yeshwanth; Hernes, Dana; Tulpule, Bhakti; Yang, Shuyu; Guo, Jiangling; Mitra, Sunanda; Yagneswaran, Sriraja; Nutter, Brian; Jeronimo, Jose; Phillips, Benny; Long, Rodney; Ferris, Daron

2005-04-01

Automated segmentation and classification of diagnostic markers in medical imagery are challenging tasks. Numerous algorithms for segmentation and classification based on statistical approaches of varying complexity are found in the literature. However, the design of an efficient and automated algorithm for precise classification of desired diagnostic markers is extremely image-specific. The National Library of Medicine (NLM), in collaboration with the National Cancer Institute (NCI), is creating an archive of 60,000 digitized color images of the uterine cervix. NLM is developing tools for the analysis and dissemination of these images over the Web for the study of visual features correlated with precancerous neoplasia and cancer. To enable indexing of images of the cervix, it is essential to develop algorithms for the segmentation of regions of interest, such as acetowhitened regions, and automatic identification and classification of regions exhibiting mosaicism and punctation. Success of such algorithms depends, primarily, on the selection of relevant features representing the region of interest. We present color and geometric features based statistical classification and segmentation algorithms yielding excellent identification of the regions of interest. The distinct classification of the mosaic regions from the non-mosaic ones has been obtained by clustering multiple geometric and color features of the segmented sections using various morphological and statistical approaches. Such automated classification methodologies will facilitate content-based image retrieval from the digital archive of uterine cervix and have the potential of developing an image based screening tool for cervical cancer.

Script-theory virtual case: A novel tool for education and research.

PubMed

Hayward, Jake; Cheung, Amandy; Velji, Alkarim; Altarejos, Jenny; Gill, Peter; Scarfe, Andrew; Lewis, Melanie

2016-11-01

Context/Setting: The script theory of diagnostic reasoning proposes that clinicians evaluate cases in the context of an "illness script," iteratively testing internal hypotheses against new information eventually reaching a diagnosis. We present a novel tool for teaching diagnostic reasoning to undergraduate medical students based on an adaptation of script theory. We developed a virtual patient case that used clinically authentic audio and video, interactive three-dimensional (3D) body images, and a simulated electronic medical record. Next, we used interactive slide bars to record respondents' likelihood estimates of diagnostic possibilities at various stages of the case. Responses were dynamically compared to data from expert clinicians and peers. Comparative frequency distributions were presented to the learner and final diagnostic likelihood estimates were analyzed. Detailed student feedback was collected. Over two academic years, 322 students participated. Student diagnostic likelihood estimates were similar year to year, but were consistently different from expert clinician estimates. Student feedback was overwhelmingly positive: students found the case was novel, innovative, clinically authentic, and a valuable learning experience. We demonstrate the successful implementation of a novel approach to teaching diagnostic reasoning. Future study may delineate reasoning processes associated with differences between novice and expert responses.

[Critical evaluation of current diagnostic classification systems in psychiatry: the case of DSM-5].

PubMed

Luciano, Mario; Sampogna, Gaia; Del Vecchio, Valeria; De Rosa, Corrado; Albert, Umberto; Carrà, Giuseppe; Dell'Osso, Bernardo; Lorenzo, Giorgio Di; Ferrari, Silvia; Martinotti, Giovanni; Nanni, Maria Giulia; Pinna, Federica; Pompili, Maurizio; Volpe, Umberto; Catapano, Francesco; Fiorillo, Andrea

2016-01-01

Since its first edition, the Diagnostic and Statistical manual of Mental disorders (DSM) has had a great impact on the scientific community and the public opinion as well. In 2013, the American Psychiatric Association released the fifth edition of the manual and - as for the previous versions - several criticisms raised. In particular, the persistence of the categorical approach to mental disorders represents one of the main debated topics, as well as the introduction of new diagnostic syndromes, which are not based on an adequate evidences. Moreover, the threshold of diagnostic criteria for many mental disorders has been lowered, with the consequence that the boundaries between "normality" and "pathology" is not so clear. In this paper, we will: 1) report the historical development of the DSM from the publication of its first edition; 2) describe the main changes introduced in the DSM-5; 3) discuss critical elements in the DSM-5. The current debate regarding the validity of diagnostic manuals and its criteria is threatening the psychiatric discipline, but a possible solution should be represented by the integration of diagnostic criteria with the in-depth description of patient's psychopathological experiences.

Assessing organisational readiness for change: use of diagnostic analysis prior to the implementation of a multidisciplinary assessment for acute stroke care

PubMed Central

Hamilton, Sharon; McLaren, Susan; Mulhall, Anne

2007-01-01

Background Achieving evidence-based practice in health care is integral to the drive for quality improvement in the National Health Service in the UK. Encapsulated within this policy agenda are challenges inherent in leading and managing organisational change. Not least of these is the need to change the behaviours of individuals and groups in order to embed new practices. Such changes are set within a context of organisational culture that can present a number of barriers and facilitators to change. Diagnostic analysis has been recommended as a precursor to the implementation of change to enable such barriers and facilitators to be identified and a targeted implementation strategy developed. Although diagnostic analysis is recommended, there is a paucity of advice on appropriate methods to use. This paper addresses the paucity and builds on previous work by recommending a mixed method approach to diagnostic analysis comprising both quantitative and qualitative data. Methods Twenty staff members with strategic accountability for stroke care were purposively sampled to take part in semi-structured interviews. Six recently discharged patients were also interviewed. Focus groups were conducted with one group of registered ward-based nurses (n = 5) and three specialist registrars (n = 3) purposively selected for their interest in stroke care. All professional staff on the study wards were sent the Team Climate Inventory questionnaire (n = 206). This elicited a response rate of 72% (n = 148). Results A number of facilitators for change were identified, including stakeholder support, organisational commitment to education, strong team climate in some teams, exemplars of past successful organisational change, and positive working environments. A number of barriers were also identified, including: unidisciplinary assessment/recording practices, varying in structure and evidence-base; weak team climate in some teams; negative exemplars of organisational change; and uncertainty created by impending organisational merger. Conclusion This study built on previous research by proposing a mixed method approach for diagnostic analysis. The combination of qualitative and quantitative data were able to capture multiple perspectives on barriers and facilitators to change. These data informed the tailoring of the implementation strategy to the specific needs of the Trust. PMID:17629929

Assessing organisational readiness for change: use of diagnostic analysis prior to the implementation of a multidisciplinary assessment for acute stroke care.

PubMed

Hamilton, Sharon; McLaren, Susan; Mulhall, Anne

2007-07-14

Achieving evidence-based practice in health care is integral to the drive for quality improvement in the National Health Service in the UK. Encapsulated within this policy agenda are challenges inherent in leading and managing organisational change. Not least of these is the need to change the behaviours of individuals and groups in order to embed new practices. Such changes are set within a context of organisational culture that can present a number of barriers and facilitators to change. Diagnostic analysis has been recommended as a precursor to the implementation of change to enable such barriers and facilitators to be identified and a targeted implementation strategy developed. Although diagnostic analysis is recommended, there is a paucity of advice on appropriate methods to use. This paper addresses the paucity and builds on previous work by recommending a mixed method approach to diagnostic analysis comprising both quantitative and qualitative data. Twenty staff members with strategic accountability for stroke care were purposively sampled to take part in semi-structured interviews. Six recently discharged patients were also interviewed. Focus groups were conducted with one group of registered ward-based nurses (n = 5) and three specialist registrars (n = 3) purposively selected for their interest in stroke care. All professional staff on the study wards were sent the Team Climate Inventory questionnaire (n = 206). This elicited a response rate of 72% (n = 148). A number of facilitators for change were identified, including stakeholder support, organisational commitment to education, strong team climate in some teams, exemplars of past successful organisational change, and positive working environments. A number of barriers were also identified, including: unidisciplinary assessment/recording practices, varying in structure and evidence-base; weak team climate in some teams; negative exemplars of organisational change; and uncertainty created by impending organisational merger. This study built on previous research by proposing a mixed method approach for diagnostic analysis. The combination of qualitative and quantitative data were able to capture multiple perspectives on barriers and facilitators to change. These data informed the tailoring of the implementation strategy to the specific needs of the Trust.

Toward a Mechanism-Based Approach to Pain Diagnosis.

PubMed

Vardeh, Daniel; Mannion, Richard J; Woolf, Clifford J

2016-09-01

The past few decades have witnessed a huge leap forward in our understanding of the mechanistic underpinnings of pain, in normal states where it helps protect from injury, and also in pathological states where pain evolves from a symptom reflecting tissue injury to become the disease itself. However, despite these scientific advances, chronic pain remains extremely challenging to manage clinically. Although the number of potential treatment targets has grown substantially and a strong case has been made for a mechanism-based and individualized approach to pain therapy, arguably clinicians are not much more advanced now than 20 years ago, in their capacity to either diagnose or effectively treat their patients. The gulf between pain research and pain management is as wide as ever. We are still currently unable to apply an evidence-based approach to chronic pain management that reflects mechanistic understanding, and instead, clinical practice remains an empirical and often unsatisfactory journey for patients, whose individual response to treatment cannot be predicted. In this article we take a common and difficult to treat pain condition, chronic low back pain, and use its presentation in clinical practice as a framework to highlight what is known about pathophysiological pain mechanisms and how we could potentially detect these to drive rational treatment choice. We discuss how present methods of assessment and management still fall well short, however, of any mechanism-based or precision medicine approach. Nevertheless, substantial improvements in chronic pain management could be possible if a more strategic and coordinated approach were to evolve, one designed to identify the specific mechanisms driving the presenting pain phenotype. We present an analysis of such an approach, highlighting the major problems in identifying mechanisms in patients, and develop a framework for a pain diagnostic ladder that may prove useful in the future, consisting of successive identification of 3 steps: pain state, pain mechanism, and molecular target. Such an approach could serve as the foundation for a new era of individualized/precision pain medicine. The Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION)-American Pain Society (APS) Pain Taxonomy (AAPT) includes pain mechanisms as 1 of the 5 dimensions that need to be considered when making a diagnostic classification. The diagnostic ladder proposed in this article is consistent with and an extension of the AAPT. We discuss how identifying the specific mechanisms that operate in the nervous system to produce chronic pain in individual patients could provide the basis for a targeted and rational precision medicine approach to controlling pain, using chronic low back pain as our example. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

Diagnosis of prostate cancer via nanotechnological approach

PubMed Central

Kang, Benedict J; Jeun, Minhong; Jang, Gun Hyuk; Song, Sang Hoon; Jeong, In Gab; Kim, Choung-Soo; Searson, Peter C; Lee, Kwan Hyi

2015-01-01

Prostate cancer is one of the leading causes of cancer-related deaths among the Caucasian adult males in Europe and the USA. Currently available diagnostic strategies for patients with prostate cancer are invasive and unpleasant and have poor accuracy. Many patients have been overly or underly treated resulting in a controversy regarding the reliability of current conventional diagnostic approaches. This review discusses the state-of-the-art research in the development of novel noninvasive prostate cancer diagnostics using nanotechnology coupled with suggested diagnostic strategies for their clinical implication. PMID:26527873

Moving toward rapid and low-cost point-of-care molecular diagnostics with a repurposed 3D printer and RPA.

PubMed

Chan, Kamfai; Wong, Pui-Yan; Parikh, Chaitanya; Wong, Season

2018-03-15

Traditionally, the majority of nucleic acid amplification-based molecular diagnostic tests are done in centralized settings. In recent years, point-of-care tests have been developed for use in low-resource settings away from central laboratories. While most experts agree that point-of-care molecular tests are greatly needed, their availability as cost-effective and easy-to-operate tests remains an unmet goal. In this article, we discuss our efforts to develop a recombinase polymerase amplification reaction-based test that will meet these criteria. First, we describe our efforts in repurposing a low-cost 3D printer as a platform that can carry out medium-throughput, rapid, and high-performing nucleic acid extraction. Next, we address how these purified templates can be rapidly amplified and analyzed using the 3D printer's heated bed or the deconstructed, low-cost thermal cycler we have developed. In both approaches, real-time isothermal amplification and detection of template DNA or RNA can be accomplished using a low-cost portable detector or smartphone camera. Last, we demonstrate the capability of our technologies using foodborne pathogens and the Zika virus. Our low-cost approach does not employ complicated and high-cost components, making it suitable for resource-limited settings. When integrated and commercialized, it will offer simple sample-to-answer molecular diagnostics. Copyright © 2018 Elsevier Inc. All rights reserved.

Application of the denaturing gradient gel electrophoresis (DGGE) technique as an efficient diagnostic tool for ciliate communities in soil.

PubMed

Jousset, Alexandre; Lara, Enrique; Nikolausz, Marcell; Harms, Hauke; Chatzinotas, Antonis

2010-02-01

Ciliates (or Ciliophora) are ubiquitous organisms which can be widely used as bioindicators in ecosystems exposed to anthropogenic and industrial influences. The evaluation of the environmental impact on soil ciliate communities with methods relying on morphology-based identification may be hampered by the large number of samples usually required for a statistically supported, reliable conclusion. Cultivation-independent molecular-biological diagnostic tools are a promising alternative to greatly simplify and accelerate such studies. In this present work a ciliate-specific fingerprint method based on the amplification of a phylogenetic marker gene (i.e. the 18S ribosomal RNA gene) with subsequent analysis by denaturing gradient gel electrophoresis (DGGE) was developed and used to monitor community shifts in a polycyclic aromatic hydrocarbon (PAH) polluted soil. The semi-nested approach generated ciliate-specific amplification products from all soil samples and allowed to distinguish community profiles from a PAH-polluted and a non-polluted control soil. Subsequent sequence analysis of excised bands provided evidence that polluted soil samples are dominated by organisms belonging to the class Colpodea. The general DGGE approach presented in this study might thus in principle serve as a fast and reproducible diagnostic tool, complementing and facilitating future ecological and ecotoxicological monitoring of ciliates in polluted habitats. Copyright 2009 Elsevier B.V. All rights reserved.

Precision Oncology Medicine: The Clinical Relevance of Patient-Specific Biomarkers Used to Optimize Cancer Treatment.

PubMed

Schmidt, Keith T; Chau, Cindy H; Price, Douglas K; Figg, William D

2016-12-01

Precision medicine in oncology is the result of an increasing awareness of patient-specific clinical features coupled with the development of genomic-based diagnostics and targeted therapeutics. Companion diagnostics designed for specific drug-target pairs were the first to widely utilize clinically applicable tumor biomarkers (eg, HER2, EGFR), directing treatment for patients whose tumors exhibit a mutation susceptible to an FDA-approved targeted therapy (eg, trastuzumab, erlotinib). Clinically relevant germline mutations in drug-metabolizing enzymes and transporters (eg, TPMT, DPYD) have been shown to impact drug response, providing a rationale for individualized dosing to optimize treatment. The use of multigene expression-based assays to analyze an array of prognostic biomarkers has been shown to help direct treatment decisions, especially in breast cancer (eg, Oncotype DX). More recently, the use of next-generation sequencing to detect many potential "actionable" cancer molecular alterations is further shifting the 1 gene-1 drug paradigm toward a more comprehensive, multigene approach. Currently, many clinical trials (eg, NCI-MATCH, NCI-MPACT) are assessing novel diagnostic tools with a combination of different targeted therapeutics while also examining tumor biomarkers that were previously unexplored in a variety of cancer histologies. Results from ongoing trials such as the NCI-MATCH will help determine the clinical utility and future development of the precision-medicine approach. © 2016, The American College of Clinical Pharmacology.

Quantitative assessment of tumour extraction from dermoscopy images and evaluation of computer-based extraction methods for an automatic melanoma diagnostic system.

PubMed

Iyatomi, Hitoshi; Oka, Hiroshi; Saito, Masataka; Miyake, Ayako; Kimoto, Masayuki; Yamagami, Jun; Kobayashi, Seiichiro; Tanikawa, Akiko; Hagiwara, Masafumi; Ogawa, Koichi; Argenziano, Giuseppe; Soyer, H Peter; Tanaka, Masaru

2006-04-01

The aims of this study were to provide a quantitative assessment of the tumour area extracted by dermatologists and to evaluate computer-based methods from dermoscopy images for refining a computer-based melanoma diagnostic system. Dermoscopic images of 188 Clark naevi, 56 Reed naevi and 75 melanomas were examined. Five dermatologists manually drew the border of each lesion with a tablet computer. The inter-observer variability was evaluated and the standard tumour area (STA) for each dermoscopy image was defined. Manual extractions by 10 non-medical individuals and by two computer-based methods were evaluated with STA-based assessment criteria: precision and recall. Our new computer-based method introduced the region-growing approach in order to yield results close to those obtained by dermatologists. The effectiveness of our extraction method with regard to diagnostic accuracy was evaluated. Two linear classifiers were built using the results of conventional and new computer-based tumour area extraction methods. The final diagnostic accuracy was evaluated by drawing the receiver operating curve (ROC) of each classifier, and the area under each ROC was evaluated. The standard deviations of the tumour area extracted by five dermatologists and 10 non-medical individuals were 8.9% and 10.7%, respectively. After assessment of the extraction results by dermatologists, the STA was defined as the area that was selected by more than two dermatologists. Dermatologists selected the melanoma area with statistically smaller divergence than that of Clark naevus or Reed naevus (P = 0.05). By contrast, non-medical individuals did not show this difference. Our new computer-based extraction algorithm showed superior performance (precision, 94.1%; recall, 95.3%) to the conventional thresholding method (precision, 99.5%; recall, 87.6%). These results indicate that our new algorithm extracted a tumour area close to that obtained by dermatologists and, in particular, the border part of the tumour was adequately extracted. With this refinement, the area under the ROC increased from 0.795 to 0.875 and the diagnostic accuracy showed an increase of approximately 20% in specificity when the sensitivity was 80%. It can be concluded that our computer-based tumour extraction algorithm extracted almost the same area as that obtained by dermatologists and provided improved computer-based diagnostic accuracy.

Model-Based Diagnostics for Propellant Loading Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew John; Foygel, Michael; Smelyanskiy, Vadim N.

2011-01-01

The loading of spacecraft propellants is a complex, risky operation. Therefore, diagnostic solutions are necessary to quickly identify when a fault occurs, so that recovery actions can be taken or an abort procedure can be initiated. Model-based diagnosis solutions, established using an in-depth analysis and understanding of the underlying physical processes, offer the advanced capability to quickly detect and isolate faults, identify their severity, and predict their effects on system performance. We develop a physics-based model of a cryogenic propellant loading system, which describes the complex dynamics of liquid hydrogen filling from a storage tank to an external vehicle tank, as well as the influence of different faults on this process. The model takes into account the main physical processes such as highly nonequilibrium condensation and evaporation of the hydrogen vapor, pressurization, and also the dynamics of liquid hydrogen and vapor flows inside the system in the presence of helium gas. Since the model incorporates multiple faults in the system, it provides a suitable framework for model-based diagnostics and prognostics algorithms. Using this model, we analyze the effects of faults on the system, derive symbolic fault signatures for the purposes of fault isolation, and perform fault identification using a particle filter approach. We demonstrate the detection, isolation, and identification of a number of faults using simulation-based experiments.

Educational Diagnostic Assessment.

ERIC Educational Resources Information Center

Bejar, Isaac I.

1984-01-01

Approaches proposed for educational diagnostic assessment are reviewed and identified as deficit assessment and error analysis. The development of diagnostic instruments may require a reexamination of existing psychometric models and development of alternative ones. The psychometric and content demands of diagnostic assessment all but require test…

Considerations Underlying the Use of Mixed Group Validation

ERIC Educational Resources Information Center

Jewsbury, Paul A.; Bowden, Stephen C.

2013-01-01

Mixed Group Validation (MGV) is an approach for estimating the diagnostic accuracy of tests. MGV is a promising alternative to the more commonly used Known Groups Validation (KGV) approach for estimating diagnostic accuracy. The advantage of MGV lies in the fact that the approach does not require a perfect external validity criterion or gold…

Factory approach can streamline patient accounting.

PubMed

Rands, J; Muench, M

1991-08-01

Although they may seem fundamentally different, similarities exist between operations of factories and healthcare organizations' business offices. As a result, a patient accounting approach based on manufacturing firms' management techniques may help smooth healthcare business processes. Receivables performance management incorporates the Japanese techniques of "just-in-time" and total quality management to reduce unbilled accounts and information backlog and accelerate payment. A preliminary diagnostic assessment of a patient accounting process helps identify bottlenecks and set priorities for work flow.

Precision Medicine Approach to Anaplastic Thyroid Cancer: Advances in Targeted Drug Therapy Based on Specific Signaling Pathways.

PubMed

Samimi, Hilda; Fallah, Parviz; Naderi Sohi, Alireza; Tavakoli, Rezvan; Naderi, Mahmood; Soleimani, Masoud; Larijani, Bagher; Haghpanah, Vahid

2017-03-01

Personalized medicine is a set of diagnostic, prognostic and therapeutic approaches in which medical interventions are carried out based on individual patient characteristics. As life expectancy increases in developed and developing countries, the incidence of diseases such as cancer goes up among people in the community. Cancer is a disease that the response to treatment varies from one person to another and also it is costly for individuals, families, and society. Among thyroid cancers, anaplastic thyroid carcinoma (ATC) is the most aggressive, lethal and unresponsive form of the disease. Unfortunately, current drugs are not targetable, and therefore they have restricted role in ATC treatment. Consequently, mortality of this cancer, despite advances in the field of diagnosis and treatment, is one of the most important challenges in medicine. Cellular, molecular and genetic evidences play an important role in finding more effective diagnostic and therapeutic approaches. Review of these evidences confirms the application of personalized medicine in cancer treatment including ATC. A growing body of evidence has elucidated that cellular and molecular mechanisms of cancer would pave the way for defining new biomarkers for targeted therapy, taking into account individual differences. It should be noted that this approach requires further progress in the fields of basic sciences, pharmacogenetics and drug design. An overview of the most important aspects in individualized anaplastic thyroid cancer treatment will be discussed in this review.

Qualitative model-based diagnosis using possibility theory

NASA Technical Reports Server (NTRS)

Joslyn, Cliff

1994-01-01

The potential for the use of possibility in the qualitative model-based diagnosis of spacecraft systems is described. The first sections of the paper briefly introduce the Model-Based Diagnostic (MBD) approach to spacecraft fault diagnosis; Qualitative Modeling (QM) methodologies; and the concepts of possibilistic modeling in the context of Generalized Information Theory (GIT). Then the necessary conditions for the applicability of possibilistic methods to qualitative MBD, and a number of potential directions for such an application, are described.

Developing a CD-CBM Anticipatory Approach for Cavitation - Defining a Model-Based Descriptor Consistent Across Processes, Phase 1 Final Report Context-Dependent Prognostics and Health Assessment: A New Paradigm for Condition-based Maintenance SBIR Topic No. N98-114

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allgood, G.O.; Dress, W.B.; Kercel, S.W.

1999-06-01

The objective of this research, and subsequent testing, was to identify specific features of cavitation that could be used as a model-based descriptor in a context-dependent condition-based maintenance (CD-CBM) anticipatory prognostic and health assessment model. This descriptor is based on the physics of the phenomena, capturing the salient features of the process dynamics. The test methodology and approach were developed to make the cavitation features the dominant effect in the process and collected signatures. This would allow the accurate characterization of the salient cavitation features at different operational states. By developing such an abstraction, these attributes can be used asmore » a general diagnostic for a system or any of its components. In this study, the particular focus will be pumps. As many as 90% of pump failures are catastrophic. They seem to be operating normally and fail abruptly without warning. This is true whether the failure is sudden hardware damage requiring repair, such as a gasket failure, or a transition into an undesired operating mode, such as cavitation. This means that conventional diagnostic methods fail to predict 90% of incipient failures and that in addressing this problem, model-based methods can add value where it is actually needed.« less

Telemedicine-based system for quality management and peer review in radiology.

PubMed

Morozov, Sergey; Guseva, Ekaterina; Ledikhova, Natalya; Vladzymyrskyy, Anton; Safronov, Dmitry

2018-06-01

Quality assurance is the key component of modern radiology. A telemedicine-based quality assurance system helps to overcome the "scoring" approach and makes the quality control more accessible and objective. A concept for quality assurance in radiology is developed. Its realization is a set of strategies, actions, and tools. The latter is based on telemedicine-based peer review of 23,199 computed tomography (CT) and magnetic resonance imaging (MRI) images. The conception of the system for quality management in radiology represents a chain of actions: "discrepancies evaluation - routine support - quality improvement activity - discrepancies evaluation". It is realized by an audit methodology, telemedicine, elearning, and other technologies. After a year of systemic telemedicine-based peer reviews, the authors have estimated that clinically significant discrepancies were detected in 6% of all cases, while clinically insignificant ones were found in 19% of cases. Most often, problems appear in musculoskeletal records; 80% of the examinations have diagnostic or technical imperfections. The presence of routine telemedicine support and personalized elearning allowed improving the diagnostics quality. The level of discrepancies has decreased significantly (p < 0.05). The telemedicine-based peer review system allows improving radiology departments' network effectiveness. • "Scoring" approach to radiologists' performance assessment must be changed. • Telemedicine peer review and personalized elearning significantly decrease the number of discrepancies. • Teleradiology allows linking all primary-level hospitals to a common peer review network.

Surface plasmon resonance biosensing: Approaches for screening and characterising antibodies for food diagnostics.

PubMed

Yakes, B J; Buijs, J; Elliott, C T; Campbell, K

2016-08-15

Research in biosensing approaches as alternative techniques for food diagnostics for the detection of chemical contaminants and foodborne pathogens has increased over the last twenty years. The key component of such tests is the biorecognition element whereby polyclonal or monoclonal antibodies still dominate the market. Traditionally the screening of sera or cell culture media for the selection of polyclonal or monoclonal candidate antibodies respectively has been performed by enzyme immunoassays. For niche toxin compounds, enzyme immunoassays can be expensive and/or prohibitive methodologies for antibody production due to limitations in toxin supply for conjugate production. Automated, self-regenerating, chip-based biosensors proven in food diagnostics may be utilised as rapid screening tools for antibody candidate selection. This work describes the use of both single channel and multi-channel surface plasmon resonance (SPR) biosensors for the selection and characterisation of antibodies, and their evaluation in shellfish tissue as standard techniques for the detection of domoic acid, as a model toxin compound. The key advantages in the use of these biosensor techniques for screening hybridomas in monoclonal antibody production were the real time observation of molecular interaction and rapid turnaround time in analysis compared to enzyme immunoassays. The multichannel prototype instrument was superior with 96 analyses completed in 2h compared to 12h for the single channel and over 24h for the ELISA immunoassay. Antibodies of high sensitivity, IC50's ranging from 4.8 to 6.9ng/mL for monoclonal and 2.3-6.0ng/mL for polyclonal, for the detection of domoic acid in a 1min analysis time were selected. Although there is a progression for biosensor technology towards low cost, multiplexed portable diagnostics for the food industry, there remains a place for laboratory-based SPR instrumentation for antibody development for food diagnostics as shown herein. Copyright © 2016 Elsevier B.V. All rights reserved.

Economic evaluation of test-and-treat and empirical treatment strategies in the eradication of Helicobacter pylori infection; A Markov model in an Iranian adult population.

PubMed

Mazdaki, Alireza; Ghiasvand, Hesam; Sarabi Asiabar, Ali; Naghdi, Seyran; Aryankhesal, Aidin

2016-01-01

Helicobacter pylori may cause many gastrointestinal problems in developing countries such as Iran. We aimed to analyze the cost- effectiveness and cost- utility of the test-and-treat and empirical treatment strategies in managing Helicobacter pylori infection. This was a Markov based economic evaluation. Effectiveness was defined as the symptoms free numbers and QALYs in 100,000 hypothetical adults. The sensitivity analysis was based on Monte Carlo approach. In the test- and- treat strategy, if the serology is the first diagnostic test vs. histology, the cost per symptoms free number would be 291,736.1 Rials while the cost per QALYs would be 339,226.1 Rials. The cost per symptoms free number and cost per QALYs when the 13 C-UBT was used as the first diagnostic test vs. serology was 1,283,200 and 1,492,103 Rials, respectively. In the empirical strategy, if histology is used as the first diagnostic test vs. 13 CUBT, the cost per symptoms free numbers and cost per QALYs would be 793,234 and 955,698 Rials, respectively. If serology were used as the first diagnostic test vs. histology, the cost per symptoms free and QALYs would be 793,234 and 368941 Rials, respectively. There was no significant and considerable dominancy between the alternatives and the diagnostic tests.

Computational approaches for identification of conserved/unique binding pockets in the A chain of ricin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ecale Zhou, C L; Zemla, A T; Roe, D

2005-01-29

Specific and sensitive ligand-based protein detection assays that employ antibodies or small molecules such as peptides, aptamers, or other small molecules require that the corresponding surface region of the protein be accessible and that there be minimal cross-reactivity with non-target proteins. To reduce the time and cost of laboratory screening efforts for diagnostic reagents, we developed new methods for evaluating and selecting protein surface regions for ligand targeting. We devised combined structure- and sequence-based methods for identifying 3D epitopes and binding pockets on the surface of the A chain of ricin that are conserved with respect to a set ofmore » ricin A chains and unique with respect to other proteins. We (1) used structure alignment software to detect structural deviations and extracted from this analysis the residue-residue correspondence, (2) devised a method to compare corresponding residues across sets of ricin structures and structures of closely related proteins, (3) devised a sequence-based approach to determine residue infrequency in local sequence context, and (4) modified a pocket-finding algorithm to identify surface crevices in close proximity to residues determined to be conserved/unique based on our structure- and sequence-based methods. In applying this combined informatics approach to ricin A we identified a conserved/unique pocket in close proximity (but not overlapping) the active site that is suitable for bi-dentate ligand development. These methods are generally applicable to identification of surface epitopes and binding pockets for development of diagnostic reagents, therapeutics, and vaccines.« less

Comparing the economic and health benefits of different approaches to diagnosing Clostridium difficile infection.

PubMed

Bartsch, Sarah M; Umscheid, Craig A; Nachamkin, Irving; Hamilton, Keith; Lee, Bruce Y

2015-01-01

Accurate diagnosis of Clostridium difficile infection (CDI) is essential to effectively managing patients and preventing transmission. Despite the availability of several diagnostic tests, the optimal strategy is debatable and their economic values are unknown. We modified our previously existing C. difficile simulation model to determine the economic value of different CDI diagnostic approaches from the hospital perspective. We evaluated four diagnostic methods for a patient suspected of having CDI: 1) toxin A/B enzyme immunoassay, 2) glutamate dehydrogenase (GDH) antigen/toxin AB combined in one test, 3) nucleic acid amplification test (NAAT), and 4) GDH antigen/toxin AB combination test with NAAT confirmation of indeterminate results. Sensitivity analysis varied the proportion of those tested with clinically significant diarrhoea, the probability of CDI, NAAT cost and CDI treatment delay resulting from a false-negative test, length of stay and diagnostic sensitivity and specificity. The GDH/toxin AB plus NAAT approach leads to the timeliest treatment with the fewest unnecessary treatments given, resulted in the best bed management and generated the lowest cost. The NAAT-alone approach also leads to timely treatment. The GDH/toxin AB diagnostic (without NAAT confirmation) approach resulted in a large number of delayed treatments, but results in the fewest secondary colonisations. Results were robust to the sensitivity analysis. Choosing the right diagnostic approach is a matter of cost and test accuracy. GDH/toxin AB plus NAAT diagnosis led to the timeliest treatment and was the least costly. Copyright © 2014 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Clinical usefulness of a biomarker-based diagnostic test for acute stroke: the Biomarker Rapid Assessment in Ischemic Injury (BRAIN) study.

PubMed

Laskowitz, Daniel T; Kasner, Scott E; Saver, Jeffrey; Remmel, Kerri S; Jauch, Edward C

2009-01-01

One of the significant limitations in the evaluation and management of patients with suspected acute cerebral ischemia is the absence of a widely available, rapid, and sensitive diagnostic test. The objective of the current study was to assess whether a test using a panel of biomarkers might provide useful diagnostic information in the early evaluation of stroke by differentiating patients with cerebral ischemia from other causes of acute neurological deficit. A total of 1146 patients presenting with neurological symptoms consistent with possible stroke were prospectively enrolled at 17 different sites. Timed blood samples were assayed for matrix metalloproteinase 9, brain natriuretic factor, d-dimer, and protein S100beta. A separate cohort of 343 patients was independently enrolled to validate the multiple biomarker model approach. A diagnostic tool incorporating the values of matrix metalloproteinase 9, brain natriuretic factor, d-dimer, and S-100beta into a composite score was sensitive for acute cerebral ischemia. The multivariate model demonstrated modest discriminative capabilities with an area under the receiver operating characteristic curve of 0.76 for hemorrhagic stroke and 0.69 for all stroke (likelihood test P<0.001). When the threshold for the logistic model was set at the first quartile, this resulted in a sensitivity of 86% for detecting all stroke and a sensitivity of 94% for detecting hemorrhagic stroke. Moreover, results were reproducible in a separate cohort tested on a point-of-care platform. These results suggest that a biomarker panel may add valuable and time-sensitive diagnostic information in the early evaluation of stroke. Such an approach is feasible on a point-of-care platform. The rapid identification of patients with suspected stroke would expand the availability of time-limited treatment strategies. Although the diagnostic accuracy of the current panel is clearly imperfect, this study demonstrates the feasibility of incorporating a biomarker based point-of-care algorithm with readily available clinical data to aid in the early evaluation and management of patients at high risk for cerebral ischemia.

Breast Cancer Diagnostics Based on Spatial Genome Organization

DTIC Science & Technology

2012-07-01

using an already established imaging tool, called NMFA-FLO (Nuclei Manual and FISH automatic). In order to achieve accurate segmentation of nuclei...in tissue we used an artificial neuronal network (ANN)-based supervised pattern recognition approach to screen out well segmented nuclei, after image ... segmentation used to process images for automated nuclear segmentation . Part a) has been adapted from [15] and b) from [16]. Figure 4. Comparison of

Systematic assessment of cervical cancer initiation and progression uncovers genetic panels for deep learning-based early diagnosis and proposes novel diagnostic and prognostic biomarkers.

PubMed

Long, Nguyen Phuoc; Jung, Kyung Hee; Yoon, Sang Jun; Anh, Nguyen Hoang; Nghi, Tran Diem; Kang, Yun Pyo; Yan, Hong Hua; Min, Jung Eun; Hong, Soon-Sun; Kwon, Sung Won

2017-12-12

Although many outstanding achievements in the management of cervical cancer (CxCa) have obtained, it still imposes a major burden which has prompted scientists to discover and validate new CxCa biomarkers to improve the diagnostic and prognostic assessment of CxCa. In this study, eight different gene expression data sets containing 202 cancer, 115 cervical intraepithelial neoplasia (CIN), and 105 normal samples were utilized for an integrative systems biology assessment in a multi-stage carcinogenesis manner. Deep learning-based diagnostic models were established based on the genetic panels of intrinsic genes of cervical carcinogenesis as well as on the unbiased variable selection approach. Survival analysis was also conducted to explore the potential biomarker candidates for prognostic assessment. Our results showed that cell cycle, RNA transport, mRNA surveillance, and one carbon pool by folate were the key regulatory mechanisms involved in the initiation, progression, and metastasis of CxCa. Various genetic panels combined with machine learning algorithms successfully differentiated CxCa from CIN and normalcy in cross-study normalized data sets. In particular, the 168-gene deep learning model for the differentiation of cancer from normalcy achieved an externally validated accuracy of 97.96% (99.01% sensitivity and 95.65% specificity). Survival analysis revealed that ZNF281 and EPHB6 were the two most promising prognostic genetic markers for CxCa among others. Our findings open new opportunities to enhance current understanding of the characteristics of CxCa pathobiology. In addition, the combination of transcriptomics-based signatures and deep learning classification may become an important approach to improve CxCa diagnosis and management in clinical practice.

Systematic assessment of cervical cancer initiation and progression uncovers genetic panels for deep learning-based early diagnosis and proposes novel diagnostic and prognostic biomarkers

PubMed Central

Long, Nguyen Phuoc; Jung, Kyung Hee; Yoon, Sang Jun; Anh, Nguyen Hoang; Nghi, Tran Diem; Kang, Yun Pyo; Yan, Hong Hua; Min, Jung Eun; Hong, Soon-Sun; Kwon, Sung Won

2017-01-01

Although many outstanding achievements in the management of cervical cancer (CxCa) have obtained, it still imposes a major burden which has prompted scientists to discover and validate new CxCa biomarkers to improve the diagnostic and prognostic assessment of CxCa. In this study, eight different gene expression data sets containing 202 cancer, 115 cervical intraepithelial neoplasia (CIN), and 105 normal samples were utilized for an integrative systems biology assessment in a multi-stage carcinogenesis manner. Deep learning-based diagnostic models were established based on the genetic panels of intrinsic genes of cervical carcinogenesis as well as on the unbiased variable selection approach. Survival analysis was also conducted to explore the potential biomarker candidates for prognostic assessment. Our results showed that cell cycle, RNA transport, mRNA surveillance, and one carbon pool by folate were the key regulatory mechanisms involved in the initiation, progression, and metastasis of CxCa. Various genetic panels combined with machine learning algorithms successfully differentiated CxCa from CIN and normalcy in cross-study normalized data sets. In particular, the 168-gene deep learning model for the differentiation of cancer from normalcy achieved an externally validated accuracy of 97.96% (99.01% sensitivity and 95.65% specificity). Survival analysis revealed that ZNF281 and EPHB6 were the two most promising prognostic genetic markers for CxCa among others. Our findings open new opportunities to enhance current understanding of the characteristics of CxCa pathobiology. In addition, the combination of transcriptomics-based signatures and deep learning classification may become an important approach to improve CxCa diagnosis and management in clinical practice. PMID:29312619

Interrogating Bronchoalveolar Lavage Samples via Exclusion-Based Analyte Extraction.

PubMed

Tokar, Jacob J; Warrick, Jay W; Guckenberger, David J; Sperger, Jamie M; Lang, Joshua M; Ferguson, J Scott; Beebe, David J

2017-06-01

Although average survival rates for lung cancer have improved, earlier and better diagnosis remains a priority. One promising approach to assisting earlier and safer diagnosis of lung lesions is bronchoalveolar lavage (BAL), which provides a sample of lung tissue as well as proteins and immune cells from the vicinity of the lesion, yet diagnostic sensitivity remains a challenge. Reproducible isolation of lung epithelia and multianalyte extraction have the potential to improve diagnostic sensitivity and provide new information for developing personalized therapeutic approaches. We present the use of a recently developed exclusion-based, solid-phase-extraction technique called SLIDE (Sliding Lid for Immobilized Droplet Extraction) to facilitate analysis of BAL samples. We developed a SLIDE protocol for lung epithelial cell extraction and biomarker staining of patient BALs, testing both EpCAM and Trop2 as capture antigens. We characterized captured cells using TTF1 and p40 as immunostaining biomarkers of adenocarcinoma and squamous cell carcinoma, respectively. We achieved up to 90% (EpCAM) and 84% (Trop2) extraction efficiency of representative tumor cell lines. We then used the platform to process two patient BAL samples in parallel within the same sample plate to demonstrate feasibility and observed that Trop2-based extraction potentially extracts more target cells than EpCAM-based extraction.

Diagnostic Peptide Discovery: Prioritization of Pathogen Diagnostic Markers Using Multiple Features

PubMed Central

Carmona, Santiago J.; Sartor, Paula A.; Leguizamón, María S.; Campetella, Oscar E.; Agüero, Fernán

2012-01-01

The availability of complete pathogen genomes has renewed interest in the development of diagnostics for infectious diseases. Synthetic peptide microarrays provide a rapid, high-throughput platform for immunological testing of potential B-cell epitopes. However, their current capacity prevent the experimental screening of complete “peptidomes”. Therefore, computational approaches for prediction and/or prioritization of diagnostically relevant peptides are required. In this work we describe a computational method to assess a defined set of molecular properties for each potential diagnostic target in a reference genome. Properties such as sub-cellular localization or expression level were evaluated for the whole protein. At a higher resolution (short peptides), we assessed a set of local properties, such as repetitive motifs, disorder (structured vs natively unstructured regions), trans-membrane spans, genetic polymorphisms (conserved vs. divergent regions), predicted B-cell epitopes, and sequence similarity against human proteins and other potential cross-reacting species (e.g. other pathogens endemic in overlapping geographical locations). A scoring function based on these different features was developed, and used to rank all peptides from a large eukaryotic pathogen proteome. We applied this method to the identification of candidate diagnostic peptides in the protozoan Trypanosoma cruzi, the causative agent of Chagas disease. We measured the performance of the method by analyzing the enrichment of validated antigens in the high-scoring top of the ranking. Based on this measure, our integrative method outperformed alternative prioritizations based on individual properties (such as B-cell epitope predictors alone). Using this method we ranked 10 million 12-mer overlapping peptides derived from the complete T. cruzi proteome. Experimental screening of 190 high-scoring peptides allowed the identification of 37 novel epitopes with diagnostic potential, while none of the low scoring peptides showed significant reactivity. Many of the metrics employed are dependent on standard bioinformatic tools and data, so the method can be easily extended to other pathogen genomes. PMID:23272069

Current opinion in Alzheimer's disease therapy by nanotechnology-based approaches.

PubMed

Ansari, Shakeel Ahmed; Satar, Rukhsana; Perveen, Asma; Ashraf, Ghulam Md

2017-03-01

Nanotechnology typically deals with the measuring and modeling of matter at nanometer scale by incorporating the fields of engineering and technology. The most prominent feature of these engineered materials involves their manipulation/modification for imparting new functional properties. The current review covers the most recent findings of Alzheimer's disease (AD) therapeutics based on nanoscience and technology. Current studies involve the application of nanotechnology in developing novel diagnostic and therapeutic tools for neurological disorders. Nanotechnology-based approaches can be exploited for limiting/reversing these diseases for promoting functional regeneration of damaged neurons. These strategies offer neuroprotection by facilitating the delivery of drugs and small molecules more effectively across the blood-brain barrier. Nanotechnology based approaches show promise in improving AD therapeutics. Further replication work on synthesis and surface modification of nanoparticles, longer-term clinical trials, and attempts to increase their impact in treating AD are required.

Microfluidic microscopy-assisted label-free approach for cancer screening: automated microfluidic cytology for cancer screening.

PubMed

Jagannadh, Veerendra Kalyan; Gopakumar, G; Subrahmanyam, Gorthi R K Sai; Gorthi, Sai Siva

2017-05-01

Each year, about 7-8 million deaths occur due to cancer around the world. More than half of the cancer-related deaths occur in the less-developed parts of the world. Cancer mortality rate can be reduced with early detection and subsequent treatment of the disease. In this paper, we introduce a microfluidic microscopy-based cost-effective and label-free approach for identification of cancerous cells. We outline a diagnostic framework for the same and detail an instrumentation layout. We have employed classical computer vision techniques such as 2D principal component analysis-based cell type representation followed by support vector machine-based classification. Analogous to criminal face recognition systems implemented with help of surveillance cameras, a signature-based approach for cancerous cell identification using microfluidic microscopy surveillance is demonstrated. Such a platform would facilitate affordable mass screening camps in the developing countries and therefore help decrease cancer mortality rate.

Expanding the Taxonomy of the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD)

PubMed Central

Peck, Christopher C.; Goulet, Jean-Paul; Lobbezoo, Frank; Schiffman, Eric L.; Alstergren, Per; Anderson, Gary C.; de Leeuw, Reny; Jensen, Rigmor; Michelotti, Ambra; Ohrbach, Richard; Petersson, Arne; List, Thomas

2014-01-01

Background There is a need to expand the current temporomandibular disorder (TMD) classification to include less common, but clinically important disorders. The immediate aim was to develop a consensus-based classification system and associated diagnostic criteria that have clinical and research utility for less common TMDs. The long-term aim was to establish a foundation, vis-à-vis this classification system, that will stimulate data collection, validity testing, and further criteria refinement. Methods A working group [members of the International RDC/TMD Consortium Network of the International Association for Dental Research (IADR), members of the Orofacial Pain Special Interest Group (SIG) of the International Association for the Study of Pain (IASP), and members from other professional societies] reviewed disorders for inclusion based on clinical significance, the availability of plausible diagnostic criteria, and the ability to operationalize and study the criteria. The disorders were derived from the literature when possible and based on expert opinion as necessary. The expanded TMD taxonomy was presented for feedback at international meetings. Results Of 56 disorders considered, 37 were included in the expanded taxonomy and were placed into the following four categories: temporomandibular joint disorders, masticatory muscle disorders, headache disorders, and disorders affecting associated structures. Those excluded were extremely uncommon, lacking operationalized diagnostic criteria, not clearly related to TMDs, or not sufficiently distinct from disorders already included within the taxonomy. Conclusions The expanded TMD taxonomy offers an integrated approach to clinical diagnosis and provides a framework for further research to operationalize and test the proposed taxonomy and diagnostic criteria. PMID:24443898

Expanding the taxonomy of the diagnostic criteria for temporomandibular disorders.

PubMed

Peck, C C; Goulet, J-P; Lobbezoo, F; Schiffman, E L; Alstergren, P; Anderson, G C; de Leeuw, R; Jensen, R; Michelotti, A; Ohrbach, R; Petersson, A; List, T

2014-01-01

There is a need to expand the current temporomandibular disorders' (TMDs) classification to include less common but clinically important disorders. The immediate aim was to develop a consensus-based classification system and associated diagnostic criteria that have clinical and research utility for less common TMDs. The long-term aim was to establish a foundation, vis-à-vis this classification system, that will stimulate data collection, validity testing and further criteria refinement. A working group [members of the International RDC/TMD Consortium Network of the International Association for Dental Research (IADR), members of the Orofacial Pain Special Interest Group (SIG) of the International Association for the Study of Pain (IASP), and members from other professional societies] reviewed disorders for inclusion based on clinical significance, the availability of plausible diagnostic criteria and the ability to operationalise and study the criteria. The disorders were derived from the literature when possible and based on expert opinion as necessary. The expanded TMDs taxonomy was presented for feedback at international meetings. Of 56 disorders considered, 37 were included in the expanded taxonomy and were placed into the following four categories: temporomandibular joint disorders, masticatory muscle disorders, headache disorders and disorders affecting associated structures. Those excluded were extremely uncommon, lacking operationalised diagnostic criteria, not clearly related to TMDs, or not sufficiently distinct from disorders already included within the taxonomy. The expanded TMDs taxonomy offers an integrated approach to clinical diagnosis and provides a framework for further research to operationalise and test the proposed taxonomy and diagnostic criteria. © 2014 John Wiley & Sons Ltd.

Bacterial clonal diagnostics as a tool for evidence-based empiric antibiotic selection

PubMed Central

Tchesnokova, Veronika; Avagyan, Hovhannes; Rechkina, Elena; Chan, Diana; Muradova, Mariya; Haile, Helen Ghirmai; Radey, Matthew; Weissman, Scott; Riddell, Kim; Scholes, Delia; Johnson, James R.

2017-01-01

Despite the known clonal distribution of antibiotic resistance in many bacteria, empiric (pre-culture) antibiotic selection still relies heavily on species-level cumulative antibiograms, resulting in overuse of broad-spectrum agents and excessive antibiotic/pathogen mismatch. Urinary tract infections (UTIs), which account for a large share of antibiotic use, are caused predominantly by Escherichia coli, a highly clonal pathogen. In an observational clinical cohort study of urgent care patients with suspected UTI, we assessed the potential for E. coli clonal-level antibiograms to improve empiric antibiotic selection. A novel PCR-based clonotyping assay was applied to fresh urine samples to rapidly detect E. coli and the urine strain's clonotype. Based on a database of clonotype-specific antibiograms, the acceptability of various antibiotics for empiric therapy was inferred using a 20%, 10%, and 30% allowed resistance threshold. The test's performance characteristics and possible effects on prescribing were assessed. The rapid test identified E. coli clonotypes directly in patients’ urine within 25–35 minutes, with high specificity and sensitivity compared to culture. Antibiotic selection based on a clonotype-specific antibiogram could reduce the relative likelihood of antibiotic/pathogen mismatch by ≥ 60%. Compared to observed prescribing patterns, clonal diagnostics-guided antibiotic selection could safely double the use of trimethoprim/sulfamethoxazole and minimize fluoroquinolone use. In summary, a rapid clonotyping test showed promise for improving empiric antibiotic prescribing for E. coli UTI, including reversing preferential use of fluoroquinolones over trimethoprim/sulfamethoxazole. The clonal diagnostics approach merges epidemiologic surveillance, antimicrobial stewardship, and molecular diagnostics to bring evidence-based medicine directly to the point of care. PMID:28350870

Bacterial clonal diagnostics as a tool for evidence-based empiric antibiotic selection.

PubMed

Tchesnokova, Veronika; Avagyan, Hovhannes; Rechkina, Elena; Chan, Diana; Muradova, Mariya; Haile, Helen Ghirmai; Radey, Matthew; Weissman, Scott; Riddell, Kim; Scholes, Delia; Johnson, James R; Sokurenko, Evgeni V

2017-01-01

Despite the known clonal distribution of antibiotic resistance in many bacteria, empiric (pre-culture) antibiotic selection still relies heavily on species-level cumulative antibiograms, resulting in overuse of broad-spectrum agents and excessive antibiotic/pathogen mismatch. Urinary tract infections (UTIs), which account for a large share of antibiotic use, are caused predominantly by Escherichia coli, a highly clonal pathogen. In an observational clinical cohort study of urgent care patients with suspected UTI, we assessed the potential for E. coli clonal-level antibiograms to improve empiric antibiotic selection. A novel PCR-based clonotyping assay was applied to fresh urine samples to rapidly detect E. coli and the urine strain's clonotype. Based on a database of clonotype-specific antibiograms, the acceptability of various antibiotics for empiric therapy was inferred using a 20%, 10%, and 30% allowed resistance threshold. The test's performance characteristics and possible effects on prescribing were assessed. The rapid test identified E. coli clonotypes directly in patients' urine within 25-35 minutes, with high specificity and sensitivity compared to culture. Antibiotic selection based on a clonotype-specific antibiogram could reduce the relative likelihood of antibiotic/pathogen mismatch by ≥ 60%. Compared to observed prescribing patterns, clonal diagnostics-guided antibiotic selection could safely double the use of trimethoprim/sulfamethoxazole and minimize fluoroquinolone use. In summary, a rapid clonotyping test showed promise for improving empiric antibiotic prescribing for E. coli UTI, including reversing preferential use of fluoroquinolones over trimethoprim/sulfamethoxazole. The clonal diagnostics approach merges epidemiologic surveillance, antimicrobial stewardship, and molecular diagnostics to bring evidence-based medicine directly to the point of care.

An assessment of envelope-based demodulation in case of proximity of carrier and modulation frequencies

NASA Astrophysics Data System (ADS)

Shahriar, Md Rifat; Borghesani, Pietro; Randall, R. B.; Tan, Andy C. C.

2017-11-01

Demodulation is a necessary step in the field of diagnostics to reveal faults whose signatures appear as an amplitude and/or frequency modulation. The Hilbert transform has conventionally been used for the calculation of the analytic signal required in the demodulation process. However, the carrier and modulation frequencies must meet the conditions set by the Bedrosian identity for the Hilbert transform to be applicable for demodulation. This condition, basically requiring the carrier frequency to be sufficiently higher than the frequency of the modulation harmonics, is usually satisfied in many traditional diagnostic applications (e.g. vibration analysis of gear and bearing faults) due to the order-of-magnitude ratio between the carrier and modulation frequency. However, the diversification of the diagnostic approaches and applications shows cases (e.g. electrical signature analysis-based diagnostics) where the carrier frequency is in close proximity to the modulation frequency, thus challenging the applicability of the Bedrosian theorem. This work presents an analytic study to quantify the error introduced by the Hilbert transform-based demodulation when the Bedrosian identity is not satisfied and proposes a mitigation strategy to combat the error. An experimental study is also carried out to verify the analytical results. The outcome of the error analysis sets a confidence limit on the estimated modulation (both shape and magnitude) achieved through the Hilbert transform-based demodulation in case of violated Bedrosian theorem. However, the proposed mitigation strategy is found effective in combating the demodulation error aroused in this scenario, thus extending applicability of the Hilbert transform-based demodulation.

Using a Diagnosis-Based Approach to Individualize Instructional Explanations in Computer-Mediated Communication

ERIC Educational Resources Information Center

Wittwer, Jorg; Nuckles, Matthias; Renkl, Alexander

2010-01-01

To maximize the effectiveness of instructional explanations, they should be tailored to an individual learner. However, instructors are often not able to collect diagnostically relevant information about a learner to individualize their explanations. This is particularly true in computer-mediated settings where it is more difficult to thoroughly…

Development of a High Throughput Assay for Rapid and Accurate 10-Plex Detection of Citrus Pathogens

USDA-ARS?s Scientific Manuscript database

The need to reliably detect and identify multiple plant pathogens simultaneously, especially in woody perennial hosts, has led to development of new molecular diagnostic approaches. In this study, a Luminex-based system was developed that provided a robust and sensitive test for simultaneous detect...

Social and Legal Aspects of the Educational Support of Adolescents with Deviant Behavior

ERIC Educational Resources Information Center

Tolegen, Mukhtar A.; Seriev, Bolat A.; Akhatov, Ualikhan A.; Taubayev, Baurzhan R.; Balashov, Talgat T.

2016-01-01

The purpose of the study is to consider the problem of the organization of working with adolescents with deviant behavior through the development and implementation of their psychological and pedagogical support based on student-centered and system approaches. Holistic application of components of psychological and pedagogical support (diagnostic,…

A Generalized Approach to Defining Item Discrimination for DCMs

ERIC Educational Resources Information Center

Henson, Robert; DiBello, Lou; Stout, Bill

2018-01-01

Diagnostic classification models (DCMs, also known as cognitive diagnosis models) hold the promise of providing detailed classroom information about the skills a student has or has not mastered. Specifically, DCMs are special cases of constrained latent class models where classes are defined based on mastery/nonmastery of a set of attributes (or…

Sensitive detection of active Shiga toxin using low cost CCD based optical detector

USDA-ARS?s Scientific Manuscript database

To reduce the sources and incidence of food-borne illness there is a need to develop inexpensive sensitive devices for detection of active toxin, such as Shiga toxin type 2 (Stx2). This approach increases the availability of foodborne bacterial toxin diagnostics in regions where there are limited r...

Closing the Loop on Classroom Interventions

ERIC Educational Resources Information Center

McCue, Patrick

2010-01-01

No Child Left Behind's mandate to close the achievement gap for students with disabilities and the emergence of response to intervention (RTI) as a means to address students' learning needs have led many schools to use more preventive academic supports within the general education classroom. The use of a diagnostic, intervention-based approach to…

Miniaturized multiplex label-free electronic chip for rapid nucleic acid analysis based on carbon nanotube nanoelectrode arrays

NASA Technical Reports Server (NTRS)

Koehne, Jessica E.; Chen, Hua; Cassell, Alan M.; Ye, Qi; Han, Jie; Meyyappan, Meyya; Li, Jun

2004-01-01

BACKGROUND: Reducing cost and time is the major concern in clinical diagnostics, particularly in molecular diagnostics. Miniaturization technologies have been recognized as promising solutions to provide low-cost microchips for diagnostics. With the recent advancement in nanotechnologies, it is possible to further improve detection sensitivity and simplify sample preparation by incorporating nanoscale elements in diagnostics devices. A fusion of micro- and nanotechnologies with biology has great potential for the development of low-cost disposable chips for rapid molecular analysis that can be carried out with simple handheld devices. APPROACH: Vertically aligned multiwalled carbon nanotubes (MWNTs) are fabricated on predeposited microelectrode pads and encapsulated in SiO2 dielectrics with only the very end exposed at the surface to form an inlaid nanoelectrode array (NEA). The NEA is used to collect the electrochemical signal associated with the target molecules binding to the probe molecules, which are covalently attached to the end of the MWNTs. CONTENT: A 3 x 3 microelectrode array is presented to demonstrate the miniaturization and multiplexing capability. A randomly distributed MWNT NEA is fabricated on each microelectrode pad. Selective functionalization of the MWNT end with a specific oligonucleotide probe and passivation of the SiO2 surface with ethylene glycol moieties are discussed. Ru(bpy)2+ -mediator-amplified guanine oxidation is used to directly measure the electrochemical signal associated with target molecules. SUMMARY: The discussed MWNT NEAs have ultrahigh sensitivity in direct electrochemical detection of guanine bases in the nucleic acid target. Fewer than approximately 1000 target nucleic acid molecules can be measured with a single microelectrode pad of approximately 20 x 20 microm2, which approaches the detection limit of laser scanners in fluorescence-based DNA microarray techniques. MWNT NEAs can be easily integrated with microelectronic circuitry and microfluidics for development of a fully automated system for rapid molecular analysis with minimum cost.

Strategies for Characterization of Low-Abundant Intact or Truncated Low-Molecular-Weight Proteins From Human Plasma.

PubMed

Cai, Tanxi; Yang, Fuquan

2017-01-01

Low-molecular-weight region (LMW, MW≤30kDa) of human serum/plasma proteins, including small intact proteins, truncated fragments of larger proteins, along with some other small components, has been associated with the ongoing physiological and pathological events, and thereby represent a treasure trove of diagnostic molecules. Great progress in the mining of novel biomarkers from this diagnostic treasure trove for disease diagnosis and health monitoring has been achieved based on serum samples from healthy individuals and patients and powerful new approaches in biochemistry and systems biology. However, cumulative evidence indicates that many potential LMW protein biomarkers might still have escaped from detection due to their low abundance, the dynamic complexity of serum/plasma, and the limited efficiency of characterization approaches. Here, we provide an overview of the current state of knowledge with respect to strategies for the characterization of low-abundant LMW proteins (small intact or truncated proteins) from human serum/plasma, involving prefractionation or enrichment methods to reduce dynamic range and mass spectrometry-based characterization of low-abundant LMW proteins. © 2017 Elsevier Inc. All rights reserved.

Good stress, bad stress--the delicate balance in the vasculature.

PubMed

Wingler, Kirstin; Schmidt, Harald H H W

2009-10-01

Radicals have important physiological functions, for example, in immune defense and vasoprotection. However, they are also potentially dangerous waste products of cellular metabolism and they can contribute to the development of many different diseases. Selective literature review. The scientific understanding of radicals has not yet led to any therapeutic application. For many years, scavenging already formed radicals with antioxidants was considered to be the most promising therapeutic approach, but clinical trials based on this principle have yielded mostly negative results. Thus, entirely new approaches are needed. The goal should be to prevent the formation of harmful radicals, or to treat radical-related damage if it has already occurred. New diagnostic tools have the potential to identify those patients that are most likely to benefit from this form of treatment, as well as to document its success. A new generation of cardiovascular drugs is being developed for the prevention or the mechanism-based treatment of vascular damage caused by oxidative stress. This new therapy should go hand in hand with new diagnostics, in accordance with the principle of individualized medicine.

A nucleic acid strand displacement system for the multiplexed detection of tuberculosis-specific mRNA using quantum dots

NASA Astrophysics Data System (ADS)

Gliddon, H. D.; Howes, P. D.; Kaforou, M.; Levin, M.; Stevens, M. M.

2016-05-01

The development of rapid, robust and high performance point-of-care diagnostics relies on the advancement and combination of various areas of research. We have developed an assay for the detection of multiple mRNA molecules that combines DNA nanotechnology with fluorescent nanomaterials. The core switching mechanism is toehold-mediated strand displacement. We have used fluorescent quantum dots (QDs) as signal transducers in this assay, as they bring many benefits including bright fluorescence and multiplexing abilities. The resulting assay is capable of multiplexed detection of long RNA targets against a high concentration of background non-target RNA, with high sensitivity and specificity and limits of detection in the nanomolar range using only a standard laboratory plate reader. We demonstrate the utility of our QD-based system for the detection of two genes selected from a microarray-derived tuberculosis-specific gene expression signature. Levels of up- and downregulated gene transcripts comprising this signature can be combined to give a disease risk score, making the signature more amenable for use as a diagnostic marker. Our QD-based approach to detect these transcripts could pave the way for novel diagnostic assays for tuberculosis.The development of rapid, robust and high performance point-of-care diagnostics relies on the advancement and combination of various areas of research. We have developed an assay for the detection of multiple mRNA molecules that combines DNA nanotechnology with fluorescent nanomaterials. The core switching mechanism is toehold-mediated strand displacement. We have used fluorescent quantum dots (QDs) as signal transducers in this assay, as they bring many benefits including bright fluorescence and multiplexing abilities. The resulting assay is capable of multiplexed detection of long RNA targets against a high concentration of background non-target RNA, with high sensitivity and specificity and limits of detection in the nanomolar range using only a standard laboratory plate reader. We demonstrate the utility of our QD-based system for the detection of two genes selected from a microarray-derived tuberculosis-specific gene expression signature. Levels of up- and downregulated gene transcripts comprising this signature can be combined to give a disease risk score, making the signature more amenable for use as a diagnostic marker. Our QD-based approach to detect these transcripts could pave the way for novel diagnostic assays for tuberculosis. Electronic supplementary information (ESI) available: Base pair mismatch tuning of CProbes. Binding capacity of the QDs. Theoretical limit of detection (LOD) for the monoplex systems. Kinetics of strand displacement. Kinetics of QProbe-CProbe binding. LOD and saturation point calculations. See DOI: 10.1039/c6nr00484a

Software Tools to Support the Assessment of System Health

NASA Technical Reports Server (NTRS)

Melcher, Kevin J.

2013-01-01

This presentation provides an overview of three software tools that were developed by the NASA Glenn Research Center to support the assessment of system health: the Propulsion Diagnostic Method Evaluation Strategy (ProDIMES), the Systematic Sensor Selection Strategy (S4), and the Extended Testability Analysis (ETA) tool. Originally developed to support specific NASA projects in aeronautics and space, these software tools are currently available to U.S. citizens through the NASA Glenn Software Catalog. The ProDiMES software tool was developed to support a uniform comparison of propulsion gas path diagnostic methods. Methods published in the open literature are typically applied to dissimilar platforms with different levels of complexity. They often address different diagnostic problems and use inconsistent metrics for evaluating performance. As a result, it is difficult to perform a one ]to ]one comparison of the various diagnostic methods. ProDIMES solves this problem by serving as a theme problem to aid in propulsion gas path diagnostic technology development and evaluation. The overall goal is to provide a tool that will serve as an industry standard, and will truly facilitate the development and evaluation of significant Engine Health Management (EHM) capabilities. ProDiMES has been developed under a collaborative project of The Technical Cooperation Program (TTCP) based on feedback provided by individuals within the aircraft engine health management community. The S4 software tool provides a framework that supports the optimal selection of sensors for health management assessments. S4 is structured to accommodate user ]defined applications, diagnostic systems, search techniques, and system requirements/constraints. One or more sensor suites that maximize this performance while meeting other user ]defined system requirements that are presumed to exist. S4 provides a systematic approach for evaluating combinations of sensors to determine the set or sets of sensors that optimally meet the performance goals and the constraints. It identifies optimal sensor suite solutions by utilizing a merit (i.e., cost) function with one of several available optimization approaches. As part of its analysis, S4 can expose fault conditions that are difficult to diagnose due to an incomplete diagnostic philosophy and/or a lack of sensors. S4 was originally developed and applied to liquid rocket engines. It was subsequently used to study the optimized selection of sensors for a simulation ]based aircraft engine diagnostic system. The ETA Tool is a software ]based analysis tool that augments the testability analysis and reporting capabilities of a commercial ]off ]the ]shelf (COTS) package. An initial diagnostic assessment is performed by the COTS software using a user ]developed, qualitative, directed ]graph model of the system being analyzed. The ETA Tool accesses system design information captured within the model and the associated testability analysis output to create a series of six reports for various system engineering needs. These reports are highlighted in the presentation. The ETA Tool was developed by NASA to support the verification of fault management requirements early in the Launch Vehicle process. Due to their early development during the design process, the TEAMS ]based diagnostic model and the ETA Tool were able to positively influence the system design by highlighting gaps in failure detection, fault isolation, and failure recovery.

[Molecular and immunohistochemical diagnostics in melanoma].

PubMed

Schilling, B; Griewank, K G

2016-07-01

To provide appropriate therapy and follow-up to patients with malignant melanoma, proper diagnostics are of critical importance. Targeted therapy of advanced melanoma is based on the molecular genetic analyses of tumor tissue. In addition, sequencing of genes and other genetic approaches can provide insight into the origin of melanocytic tumors and can aid in distinguishing benign from malignant lesions. In this regard, spizoid neoplasms remain a challenging entity. Aside from genetic analyses of tumor tissue, immunohistochemistry remains an essential tool in melanoma diagnostics and TNM classification. With new immunotherapies being approved for advanced melanoma, immunohistochemistry to determine PD-L1 expression has gained clinical interest. While PD-L1 expression is associated with response to PD-1 blockade, a substantial number of patients without PD-L1 expression can still experience tumor remission upon treatment. In this review, current and future developments in melanoma diagnostics with regard to molecular genetics and immunohistochemistry are summarized. The utilization of such analyses in clinical decision making is also discussed.

Standardizing Plasmodium falciparum infection prevalence measured via microscopy versus rapid diagnostic test.

PubMed

Mappin, Bonnie; Cameron, Ewan; Dalrymple, Ursula; Weiss, Daniel J; Bisanzio, Donal; Bhatt, Samir; Gething, Peter W

2015-11-17

Large-scale mapping of Plasmodium falciparum infection prevalence relies on opportunistic assemblies of infection prevalence data arising from thousands of P. falciparum parasite rate (PfPR) surveys conducted worldwide. Variance in these data is driven by both signal, the true underlying pattern of infection prevalence, and a range of factors contributing to 'noise', including sampling error, differing age ranges of subjects and differing parasite detection methods. Whilst the former two noise components have been addressed in previous studies, the effect of different diagnostic methods used to determine PfPR in different studies has not. In particular, the majority of PfPR data are based on positivity rates determined by either microscopy or rapid diagnostic test (RDT), yet these approaches are not equivalent; therefore a method is needed for standardizing RDT and microscopy-based prevalence estimates prior to use in mapping. Twenty-five recent Demographic and Health surveys (DHS) datasets from sub-Saharan Africa provide child diagnostic test results derived using both RDT and microscopy for each individual. These prevalence estimates were aggregated across level one administrative zones and a Bayesian probit regression model fit to the microscopy- versus RDT-derived prevalence relationship. An errors-in-variables approach was employed to account for sampling error in both the dependent and independent variables. In addition to the diagnostic outcome, RDT type, fever status and recent anti-malarial treatment were extracted from the datasets in order to analyse their effect on observed malaria prevalence. A strong non-linear relationship between the microscopy and RDT-derived prevalence was found. The results of regressions stratified by the additional diagnostic variables (RDT type, fever status and recent anti-malarial treatment) indicate that there is a distinct and consistent difference in the relationship when the data are stratified by febrile status and RDT brand. The relationships defined in this research can be applied to RDT-derived PfPR data to effectively convert them to an estimate of the parasite prevalence expected using microscopy (or vice versa), thereby standardizing the dataset and improving the signal-to-noise ratio. Additionally, the results provide insight on the importance of RDT brands, febrile status and recent anti-malarial treatment for explaining inconsistencies between observed prevalence derived from different diagnostics.

Reduced gray matter volume in the anterior cingulate, orbitofrontal cortex and thalamus as a function of mild depressive symptoms: a voxel-based morphometric analysis.

PubMed

Webb, C A; Weber, M; Mundy, E A; Killgore, W D S

2014-10-01

Studies investigating structural brain abnormalities in depression have typically employed a categorical rather than dimensional approach to depression [i.e., comparing subjects with Diagnostic and Statistical Manual of Mental Disorders (DSM)-defined major depressive disorder (MDD) v. healthy controls]. The National Institute of Mental Health, through their Research Domain Criteria initiative, has encouraged a dimensional approach to the study of psychopathology as opposed to an over-reliance on categorical (e.g., DSM-based) diagnostic approaches. Moreover, subthreshold levels of depressive symptoms (i.e., severity levels below DSM criteria) have been found to be associated with a range of negative outcomes, yet have been relatively neglected in neuroimaging research. To examine the extent to which depressive symptoms--even at subclinical levels--are linearly related to gray matter volume reductions in theoretically important brain regions, we employed whole-brain voxel-based morphometry in a sample of 54 participants. The severity of mild depressive symptoms, even in a subclinical population, was associated with reduced gray matter volume in the orbitofrontal cortex, anterior cingulate, thalamus, superior temporal gyrus/temporal pole and superior frontal gyrus. A conjunction analysis revealed concordance across two separate measures of depression. Reduced gray matter volume in theoretically important brain regions can be observed even in a sample that does not meet DSM criteria for MDD, but who nevertheless report relatively elevated levels of depressive symptoms. Overall, these findings highlight the need for additional research using dimensional conceptual and analytic approaches, as well as further investigation of subclinical populations.

Gut Feelings as a Third Track in General Practitioners’ Diagnostic Reasoning

PubMed Central

Van de Wiel, Margje; Van Royen, Paul; Van Bokhoven, Marloes; Van der Weijden, Trudy; Dinant, Geert Jan

2010-01-01

Background General practitioners (GPs) are often faced with complicated, vague problems in situations of uncertainty that they have to solve at short notice. In such situations, gut feelings seem to play a substantial role in their diagnostic process. Qualitative research distinguished a sense of alarm and a sense of reassurance. However, not every GP trusted their gut feelings, since a scientific explanation is lacking. Objective This paper explains how gut feelings arise and function in GPs’ diagnostic reasoning. Approach The paper reviews literature from medical, psychological and neuroscientific perspectives. Conclusions Gut feelings in general practice are based on the interaction between patient information and a GP’s knowledge and experience. This is visualized in a knowledge-based model of GPs’ diagnostic reasoning emphasizing that this complex task combines analytical and non-analytical cognitive processes. The model integrates the two well-known diagnostic reasoning tracks of medical decision-making and medical problem-solving, and adds gut feelings as a third track. Analytical and non-analytical diagnostic reasoning interacts continuously, and GPs use elements of all three tracks, depending on the task and the situation. In this dual process theory, gut feelings emerge as a consequence of non-analytical processing of the available information and knowledge, either reassuring GPs or alerting them that something is wrong and action is required. The role of affect as a heuristic within the physician’s knowledge network explains how gut feelings may help GPs to navigate in a mostly efficient way in the often complex and uncertain diagnostic situations of general practice. Emotion research and neuroscientific data support the unmistakable role of affect in the process of making decisions and explain the bodily sensation of gut feelings.The implications for health care practice and medical education are discussed. PMID:20967509

An evaluation of consensus techniques for diagnostic interpretation

NASA Astrophysics Data System (ADS)

Sauter, Jake N.; LaBarre, Victoria M.; Furst, Jacob D.; Raicu, Daniela S.

2018-02-01

Learning diagnostic labels from image content has been the standard in computer-aided diagnosis. Most computer-aided diagnosis systems use low-level image features extracted directly from image content to train and test machine learning classifiers for diagnostic label prediction. When the ground truth for the diagnostic labels is not available, reference truth is generated from the experts diagnostic interpretations of the image/region of interest. More specifically, when the label is uncertain, e.g. when multiple experts label an image and their interpretations are different, techniques to handle the label variability are necessary. In this paper, we compare three consensus techniques that are typically used to encode the variability in the experts labeling of the medical data: mean, median and mode, and their effects on simple classifiers that can handle deterministic labels (decision trees) and probabilistic vectors of labels (belief decision trees). Given that the NIH/NCI Lung Image Database Consortium (LIDC) data provides interpretations for lung nodules by up to four radiologists, we leverage the LIDC data to evaluate and compare these consensus approaches when creating computer-aided diagnosis systems for lung nodules. First, low-level image features of nodules are extracted and paired with their radiologists semantic ratings (1= most likely benign, , 5 = most likely malignant); second, machine learning multi-class classifiers that handle deterministic labels (decision trees) and probabilistic vectors of labels (belief decision trees) are built to predict the lung nodules semantic ratings. We show that the mean-based consensus generates the most robust classi- fier overall when compared to the median- and mode-based consensus. Lastly, the results of this study show that, when building CAD systems with uncertain diagnostic interpretation, it is important to evaluate different strategies for encoding and predicting the diagnostic label.

Multi-complexity ensemble measures for gait time series analysis: application to diagnostics, monitoring and biometrics.

PubMed

Gavrishchaka, Valeriy; Senyukova, Olga; Davis, Kristina

2015-01-01

Previously, we have proposed to use complementary complexity measures discovered by boosting-like ensemble learning for the enhancement of quantitative indicators dealing with necessarily short physiological time series. We have confirmed robustness of such multi-complexity measures for heart rate variability analysis with the emphasis on detection of emerging and intermittent cardiac abnormalities. Recently, we presented preliminary results suggesting that such ensemble-based approach could be also effective in discovering universal meta-indicators for early detection and convenient monitoring of neurological abnormalities using gait time series. Here, we argue and demonstrate that these multi-complexity ensemble measures for gait time series analysis could have significantly wider application scope ranging from diagnostics and early detection of physiological regime change to gait-based biometrics applications.

Bio optofluidics cell sorter: cell-BOCS concept and applications

NASA Astrophysics Data System (ADS)

Roth, Tue; Glückstad, Jesper

2012-03-01

The cell-BOCS is a novel microfluidics based cell-sorting instrument utilizing next generation optical trapping technology developed at the Technical University of Denmark. It is targeted emerging bio-medical research and diagnostics markets where it for certain applications offers a number of advantages over conventional fluorescence activated cell-sorting (FACSTM) technology. Advantages include gentle handling of cells, sterile sorting, easy operation, small footprint and lower cost allowing out-of-core-facility use. Application examples are found within sorting of fragile transfected cells, high value samples and primary cell lines, where traditional FACS technology has limited application due to it's droplet-based approach to cell-sorting. In the diagnostics field, in particular applying the cell-BOCS for isolating pure populations of circulating tumor cells is an area that has generated a lot of interest.

Converting Radiology Operations in a Six-Hospital Healthcare System from Film-Based to Digital: Another Leadership Role for the Diagnostic Medical Physicist

NASA Astrophysics Data System (ADS)

Arreola, Manuel M.; Rill, Lynn N.

2004-09-01

As medical facilities across the United States continue to convert their radiology operations from film-based to digital environments, partially accomplished and failed endeavors are frequent because of the lack of competent and knowledgeable leadership. The diagnostic medical physicist is, without a doubt, in a privileged position to take such a leadership role, not only because of her/his understanding of the basics principles of new imaging modalities, but also because of her/his inherent participation in workflow design and educational/training activities. A well-structured approach by the physicist will certainly lead the project to a successful completion, opening, in turn, new opportunities for the medical physicist to become an active participant in the decision-making process for an institution.

Diagnostic grade wireless ECG monitoring.

PubMed

Garudadri, Harinath; Chi, Yuejie; Baker, Steve; Majumdar, Somdeb; Baheti, Pawan K; Ballard, Dan

2011-01-01

In remote monitoring of Electrocardiogram (ECG), it is very important to ensure that the diagnostic integrity of signals is not compromised by sensing artifacts and channel errors. It is also important for the sensors to be extremely power efficient to enable wearable form factors and long battery life. We present an application of Compressive Sensing (CS) as an error mitigation scheme at the application layer for wearable, wireless sensors in diagnostic grade remote monitoring of ECG. In our previous work, we described an approach to mitigate errors due to packet losses by projecting ECG data to a random space and recovering a faithful representation using sparse reconstruction methods. Our contributions in this work are twofold. First, we present an efficient hardware implementation of random projection at the sensor. Second, we validate the diagnostic integrity of the reconstructed ECG after packet loss mitigation. We validate our approach on MIT and AHA databases comprising more than 250,000 normal and abnormal beats using EC57 protocols adopted by the Food and Drug Administration (FDA). We show that sensitivity and positive predictivity of a state-of-the-art ECG arrhythmia classifier is essentially invariant under CS based packet loss mitigation for both normal and abnormal beats even at high packet loss rates. In contrast, the performance degrades significantly in the absence of any error mitigation scheme, particularly for abnormal beats such as Ventricular Ectopic Beats (VEB).

Incorporating uncertainty into medical decision making: an approach to unexpected test results.

PubMed

Bianchi, Matt T; Alexander, Brian M; Cash, Sydney S

2009-01-01

The utility of diagnostic tests derives from the ability to translate the population concepts of sensitivity and specificity into information that will be useful for the individual patient: the predictive value of the result. As the array of available diagnostic testing broadens, there is a temptation to de-emphasize history and physical findings and defer to the objective rigor of technology. However, diagnostic test interpretation is not always straightforward. One significant barrier to routine use of probability-based test interpretation is the uncertainty inherent in pretest probability estimation, the critical first step of Bayesian reasoning. The context in which this uncertainty presents the greatest challenge is when test results oppose clinical judgment. It is this situation when decision support would be most helpful. The authors propose a simple graphical approach that incorporates uncertainty in pretest probability and has specific application to the interpretation of unexpected results. This method quantitatively demonstrates how uncertainty in disease probability may be amplified when test results are unexpected (opposing clinical judgment), even for tests with high sensitivity and specificity. The authors provide a simple nomogram for determining whether an unexpected test result suggests that one should "switch diagnostic sides.'' This graphical framework overcomes the limitation of pretest probability uncertainty in Bayesian analysis and guides decision making when it is most challenging: interpretation of unexpected test results.

Development of a neural network technique for KSTAR Thomson scattering diagnostics.

PubMed

Lee, Seung Hun; Lee, J H; Yamada, I; Park, Jae Sun

2016-11-01

Neural networks provide powerful approaches of dealing with nonlinear data and have been successfully applied to fusion plasma diagnostics and control systems. Controlling tokamak plasmas in real time is essential to measure the plasma parameters in situ. However, the χ 2 method traditionally used in Thomson scattering diagnostics hampers real-time measurement due to the complexity of the calculations involved. In this study, we applied a neural network approach to Thomson scattering diagnostics in order to calculate the electron temperature, comparing the results to those obtained with the χ 2 method. The best results were obtained for 10 3 training cycles and eight nodes in the hidden layer. Our neural network approach shows good agreement with the χ 2 method and performs the calculation twenty times faster.

Potential applications of next generation DNA sequencing of 16S rRNA gene amplicons in microbial water quality monitoring

PubMed Central

Vierheilig, J.; Savio, D.; Ley, R. E.; Mach, R. L.; Farnleitner, A. H.

2016-01-01

The applicability of next generation DNA sequencing (NGS) methods for water quality assessment has so far not been broadly investigated. This study set out to evaluate the potential of an NGS-based approach in a complex catchment with importance for drinking water abstraction. In this multicompartment investigation, total bacterial communities in water, faeces, soil, and sediment samples were investigated by 454 pyrosequencing of bacterial 16S rRNA gene amplicons to assess the capabilities of this NGS method for (i) the development and evaluation of environmental molecular diagnostics, (ii) direct screening of the bulk bacterial communities, and (iii) the detection of faecal pollution in water. Results indicate that NGS methods can highlight potential target populations for diagnostics and will prove useful for the evaluation of existing and the development of novel DNA-based detection methods in the field of water microbiology. The used approach allowed unveiling of dominant bacterial populations but failed to detect populations with low abundances such as faecal indicators in surface waters. In combination with metadata, NGS data will also allow the identification of drivers of bacterial community composition during water treatment and distribution, highlighting the power of this approach for monitoring of bacterial regrowth and contamination in technical systems. PMID:26606090

Measures of Agreement Between Many Raters for Ordinal Classifications

PubMed Central

Nelson, Kerrie P.; Edwards, Don

2015-01-01

Screening and diagnostic procedures often require a physician's subjective interpretation of a patient's test result using an ordered categorical scale to define the patient's disease severity. Due to wide variability observed between physicians’ ratings, many large-scale studies have been conducted to quantify agreement between multiple experts’ ordinal classifications in common diagnostic procedures such as mammography. However, very few statistical approaches are available to assess agreement in these large-scale settings. Existing summary measures of agreement rely on extensions of Cohen's kappa [1 - 5]. These are prone to prevalence and marginal distribution issues, become increasingly complex for more than three experts or are not easily implemented. Here we propose a model-based approach to assess agreement in large-scale studies based upon a framework of ordinal generalized linear mixed models. A summary measure of agreement is proposed for multiple experts assessing the same sample of patients’ test results according to an ordered categorical scale. This measure avoids some of the key flaws associated with Cohen's kappa and its extensions. Simulation studies are conducted to demonstrate the validity of the approach with comparison to commonly used agreement measures. The proposed methods are easily implemented using the software package R and are applied to two large-scale cancer agreement studies. PMID:26095449

Automated tru-cut imaging-guided core needle biopsy of canine orbital neoplasia. A prospective feasibility study

PubMed Central

Cirla, A.; Rondena, M.; Bertolini, G.

2016-01-01

The purpose of this study was to evaluate the diagnostic value of imaging-guided core needle biopsy for canine orbital mass diagnosis. A second excisional biopsy obtained during surgery or necropsy was used as the reference standard. A prospective feasibility study was conducted in 23 canine orbital masses at a single centre. A complete ophthalmic examination was always followed by orbital ultrasound and computed tomography (CT) examination of the head. All masses were sampled with the patient still on the CT table using ultrasound (US) guided automatic tru-cut device. The most suitable sampling approach to the orbit was chosen each time based on the CT image analysis. One of the following different approaches was used: trans-orbital, trans-conjunctival or trans-masseteric. In all cases, the imaging-guided biopsy provided a sufficient amount of tissue for the histopathological diagnosis, which concurred with the biopsies obtained using the excisional technique. CT examination was essential for morphological diagnosis and provided detailed topographic information that allowed us to choose the safest orbital approach for the biopsy. US guided automatic tru-cut biopsy based on CT images, performed with patient still on the CT table, resulted in a minimally invasive, relatively easy, and accurate diagnostic procedure in dogs with orbital masses. PMID:27540512

Lymphomatoid papulosis - making sense of the alphabet soup: a proposal to simplify terminology.

PubMed

Kempf, Werner; Mitteldorf, Christina; Karai, Laszlo J; Robson, Alistair

2017-04-01

Clinically, lymphomatoid papulosis (LYP) is characterized by recurrent papulonodular lesions. Unlike this stereotypical clinical presentation, the histological spectrum of LYP is very wide, comprising distinct growth patterns, variably sized neoplastic cells, and different immunophenotypes. The revised 2016 WHO classification includes the histological LYP types A to E as well as another type characterized by a specific chromosomal alteration. In addition, new LYP types are going to be proposed, based not only on histological but also on clinical and genetic features. The ensuing expansion of the alphabetical list of histological types will add to the complexity of the terminology of LYP, thereby potentially increasing the risk of complicating rather than facilitating the diagnostic approach to the disease. Moreover, there may be overlap between individual disease types. This development raises the question as to how to simplify the terminology of LYP while still respecting its histological complexity. Herein, we advocate a practical approach to the terminology of LYP based on descriptive terms rather than the designation of LYP types by alphabetical characters. Our proposal aims to contribute to a pragmatic and user-friendly approach, thus not only facilitating the diagnostic process but also the communication between clinicians and pathologists. © 2017 Deutsche Dermatologische Gesellschaft (DDG). Published by John Wiley & Sons Ltd.

Enhancements in medicine by integrating content based image retrieval in computer-aided diagnosis

NASA Astrophysics Data System (ADS)

Aggarwal, Preeti; Sardana, H. K.

2010-02-01

Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic radiology. With cad, radiologists use the computer output as a "second opinion" and make the final decisions. Retrieving images is a useful tool to help radiologist to check medical image and diagnosis. The impact of contentbased access to medical images is frequently reported but existing systems are designed for only a particular context of diagnosis. The challenge in medical informatics is to develop tools for analyzing the content of medical images and to represent them in a way that can be efficiently searched and compared by the physicians. CAD is a concept established by taking into account equally the roles of physicians and computers. To build a successful computer aided diagnostic system, all the relevant technologies, especially retrieval need to be integrated in such a manner that should provide effective and efficient pre-diagnosed cases with proven pathology for the current case at the right time. In this paper, it is suggested that integration of content-based image retrieval (CBIR) in cad can bring enormous results in medicine especially in diagnosis. This approach is also compared with other approaches by highlighting its advantages over those approaches.

Automated tru-cut imaging-guided core needle biopsy of canine orbital neoplasia. A prospective feasibility study.

PubMed

Cirla, A; Rondena, M; Bertolini, G

2016-01-01

The purpose of this study was to evaluate the diagnostic value of imaging-guided core needle biopsy for canine orbital mass diagnosis. A second excisional biopsy obtained during surgery or necropsy was used as the reference standard. A prospective feasibility study was conducted in 23 canine orbital masses at a single centre. A complete ophthalmic examination was always followed by orbital ultrasound and computed tomography (CT) examination of the head. All masses were sampled with the patient still on the CT table using ultrasound (US) guided automatic tru-cut device. The most suitable sampling approach to the orbit was chosen each time based on the CT image analysis. One of the following different approaches was used: trans-orbital, trans-conjunctival or trans-masseteric. In all cases, the imaging-guided biopsy provided a sufficient amount of tissue for the histopathological diagnosis, which concurred with the biopsies obtained using the excisional technique. CT examination was essential for morphological diagnosis and provided detailed topographic information that allowed us to choose the safest orbital approach for the biopsy. US guided automatic tru-cut biopsy based on CT images, performed with patient still on the CT table, resulted in a minimally invasive, relatively easy, and accurate diagnostic procedure in dogs with orbital masses.

Kinematic fingerprint of core-collapsed globular clusters

NASA Astrophysics Data System (ADS)

Bianchini, P.; Webb, J. J.; Sills, A.; Vesperini, E.

2018-03-01

Dynamical evolution drives globular clusters towards core collapse, which strongly shapes their internal properties. Diagnostics of core collapse have so far been based on photometry only, namely on the study of the concentration of the density profiles. Here, we present a new method to robustly identify core-collapsed clusters based on the study of their stellar kinematics. We introduce the kinematic concentration parameter, ck, the ratio between the global and local degree of energy equipartition reached by a cluster, and show through extensive direct N-body simulations that clusters approaching core collapse and in the post-core collapse phase are strictly characterized by ck > 1. The kinematic concentration provides a suitable diagnostic to identify core-collapsed clusters, independent from any other previous methods based on photometry. We also explore the effects of incomplete radial and stellar mass coverage on the calculation of ck and find that our method can be applied to state-of-art kinematic data sets.

Development of laser-based technology for the routine first wall diagnostic on the tokamak EAST: LIBS and LIAS

NASA Astrophysics Data System (ADS)

Hu, Z.; Gierse, N.; Li, C.; Liu, P.; Zhao, D.; Sun, L.; Oelmann, J.; Nicolai, D.; Wu, D.; Wu, J.; Mao, H.; Ding, F.; Brezinsek, S.; Liang, Y.; Ding, H.; Luo, G.; Linsmeier, C.; EAST Team

2017-12-01

A laser based method combined with spectroscopy, such as laser-induced breakdown spectroscopy (LIBS) and laser-induced ablation spectroscopy (LIAS), is a promising technology for plasma-wall interaction studies. In this work, we report the development of in situ laser-based diagnostics (LIBS and LIAS) for the assessment of static and dynamic fuel retention on the first wall without removing the tiles between and during plasma discharges in the Experimental Advanced Superconducting Tokamak (EAST). The fuel retention on the first wall was measured after different wall conditioning methods and daily plasma discharges by in situ LIBS. The result indicates that the LIBS can be a useful tool to predict the wall condition in EAST. With the successful commissioning of a refined timing system for LIAS, an in situ approach to investigate fuel retention is proposed.

A Machine Learning-Based Analysis of Game Data for Attention Deficit Hyperactivity Disorder Assessment.

PubMed

Heller, Monika D; Roots, Kurt; Srivastava, Sanjana; Schumann, Jennifer; Srivastava, Jaideep; Hale, T Sigi

2013-10-01

Attention deficit hyperactivity disorder (ADHD) is found in 9.5 percent of the U.S. population and poses lifelong challenges. Current diagnostic approaches rely on evaluation forms completed by teachers and/or parents, although they are not specifically trained to recognize cognitive disorders. The most accurate diagnosis is by a psychiatrist, often only available to children with severe symptoms. Development of a tool that is engaging and objective and aids medical providers is needed in the diagnosis of ADHD. The goal of this research is to work toward the development of such a tool. The proposed approach takes advantage of two trends: The rapid adoption of tangible user interface devices and the popularity of interactive videogames. CogCubed Inc. (Minneapolis, MN) has created "Groundskeeper," a game on the Sifteo Cubes (Sifteo, Inc., San Francisco, CA) game system with elements that exercise skills affected by ADHD. "Groundskeeper" was evaluated for 52 patients, with and without ADHD. Gameplay data were mathematically transformed into ADHD-indicative feature variables and subjected to machine learning algorithms to develop diagnostic models to aid psychiatric clinical assessments of ADHD. The effectiveness of the developed model was evaluated against the diagnostic impressions of two licensed child/adolescent psychiatrists using semistructured interviews. Our predictive algorithms were highly accurate in correctly predicting diagnoses based on gameplay of "Groundskeeper." The F-measure, a measure of diagnosis accuracy, from the predictive models gave values as follows: ADHD, inattentive type, 78 percent (P>0.05); ADHD, combined type, 75 percent (P<0.05); anxiety disorders, 71%; and depressive disorders, 76%. This represents a promising new approach to screening tools for ADHD.

Development of a systematic approach to rapid classification and identification of notoginsenosides and metabolites in rat feces based on liquid chromatography coupled triple time-of-flight mass spectrometry.

PubMed

Xing, Rong; Zhou, Lijun; Xie, Lin; Hao, Kun; Rao, Tai; Wang, Qian; Ye, Wei; Fu, Hanxu; Wang, Xinwen; Wang, Guangji; Liang, Yan

2015-03-31

The present work contributes to the development of a powerful technical platform to rapidly identify and classify complicated components and metabolites for traditional Chinese medicines. In this process, notoginsenosides, the main active ingredients in Panaxnotoginseng, were chosen as model compounds. Firstly, the fragmental patterns, diagnostic product ions and neutral loss of each subfamily of notoginsenosides were summarized by collision-induced dissociation analysis of representative authentic standards. Next, in order to maximally cover low-concentration components which could otherwise be omitted from previous diagnostic fragment-ion method using only single product ion of notoginsenosides, a multiple product ions filtering strategy was proposed and utilized to identify and classify both non-target and target notoginsenosides of P.notoginseng extract (in vitro). With this strategy, 13 protopanaxadiol-type notoginsenosides and 30 protopanaxatriol-type notoginsenosides were efficiently extracted. Then, a neutral loss filtering technique was employed to trace prototype components and metabolites in rats (in vivo) since diagnostic product ions might shift therefore become unpredictable when metabolic reactions occurred on the mother skeleton of notoginsenosides. After comparing the constitute profiles in vitro with in vivo, 62 drug-related components were identified from rat feces, and these components were classified into 27 prototype compounds and 35 metabolites. Lastly, all the metabolites were successfully correlated to their parent compounds based on chemicalome-metabolome matching approach which was previously built by our group. This study provided a generally applicable approach to global metabolite identification for the complicated components in complex matrices. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimised Spectral Kurtosis for bearing diagnostics under electromagnetic interference

NASA Astrophysics Data System (ADS)

Smith, Wade A.; Fan, Zhiqi; Peng, Zhongxiao; Li, Huaizhong; Randall, Robert B.

2016-06-01

The selection of the optimal demodulation frequency band is a significant step in bearing fault diagnosis because it determines whether the fault information can be extracted from the demodulated signal via envelope analysis. Two well-known methods for selecting the demodulation band are the Fast Kurtogram, based on the kurtosis of the filtered time signal, and the Protrugram, which uses the kurtosis of the envelope (amplitude) spectrum. Although these two methods have been successfully applied in many cases, the authors have observed that they may fail in specific environments, such as in the presence of electromagnetic interference (EMI) or other impulsive masking signals. In this paper, a simple spectral kurtosis-based approach is proposed for selecting the best demodulation band to extract bearing fault-related impulsive content from vibration signals contaminated with strong EMI. The method is applied to vibration signals obtained from a planetary gearbox test rig with planet bearings seeded with inner and outer race faults. Results from the Fast Kurtogram and Protrugram methods are also included for comparison. The proposed approach is found to exhibit superior diagnostic performance in the presence of intense EMI. Another contribution of the paper is to introduce and explain the issue of EMI to the condition monitoring community. The paper outlines the characteristics of EMI arising from widely-used variable frequency drives, and these characteristics are used to simulate an EMI-contaminated vibration signal to further test the performance of the proposed approach. Although EMI has been acknowledged as a serious problem in many industrial cases, there have been very few studies showing its adverse effects on machine diagnostics. It is important for analysts to be able to identify EMI in measured vibration signals, lest it interfere with the analysis undertaken.

Molecular diagnostic testing for primary biliary cholangitis.

PubMed

Gatselis, Nikolaos K; Dalekos, George N

2016-09-01

A reliable liver autoimmune serology for the diagnosis of primary biliary cholangitis (PBC) is of particular importance. Recognition of patients at early stages and prompt treatment initiation may alter the outcome, slow progression, delays liver failure, and improves survival. In this review, we summarize and discuss the published data obtained from literature searches from PubMed and The National Library of Medicine (USA) and our own experience on the current and potential molecular based approaches to the diagnosis of PBC. Expert commentary: Standardization of liver diagnostic serology and clinical governance are two major points as antimitochondrial antibodies are the diagnostic hallmark of the disease and PBC-specific antinuclear antibodies could assist in the diagnosis and estimation of prognosis. New biomarkers such as novel autoantibodies, genetic polymorphisms, metabolomic profiling, micro-RNA and epigenetics may assist to the understanding, diagnosis and management of the disease.

Application of Dynamic Logic Algorithm to Inverse Scattering Problems Related to Plasma Diagnostics

NASA Astrophysics Data System (ADS)

Perlovsky, L.; Deming, R. W.; Sotnikov, V.

2010-11-01

In plasma diagnostics scattering of electromagnetic waves is widely used for identification of density and wave field perturbations. In the present work we use a powerful mathematical approach, dynamic logic (DL), to identify the spectra of scattered electromagnetic (EM) waves produced by the interaction of the incident EM wave with a Langmuir soliton in the presence of noise. The problem is especially difficult since the spectral amplitudes of the noise pattern are comparable with the amplitudes of the scattered waves. In the past DL has been applied to a number of complex problems in artificial intelligence, pattern recognition, and signal processing, resulting in revolutionary improvements. Here we demonstrate its application to plasma diagnostic problems. [4pt] Perlovsky, L.I., 2001. Neural Networks and Intellect: using model-based concepts. Oxford University Press, New York, NY.

[An approach to DSM-5: a breakthrough in psychiatry?].

PubMed

Heerlein, Andrés L

2014-01-01

One of the main problems of current psychiatry is that its diagnostic classification systems are not precise and reliable, they do not help to identify with certainty a specific type of mental disorder and they frequently overlap two or more diagnoses. This may conduce to over diagnosis and overtreatment, which is the main criticism of the DSM system. The American Psychiatric Association (APA) launched recently the DSM-5, the fifth edition of its diagnostic manual, which provides diagnostic criteria for thousands of psychiatrist, psychologist and researchers and who will be using it in the next coming years. DSM-5, like the preceding editions, placed disorders in discrete categories such as bipolar disorder or schizophrenia. The problem is that scientists have been unable to find yet a genetic or neurobiological evidence to support the theory of mental disorders as separate categories. Several authors wanted the latest DSM to move away from the category model towards a new "dimensional approach", where disorders can be measured and mental illnesses overlapping can be reduced. Recent findings supports this new dimensional strategy, suggesting that the disorders are a product of shared risk factors that lead to abnormalities in specific drives, which can be measured and used to place persons on one of several spectra. In some parts the DSM-5 entered changes aiming to achieve a greater objectivity. The door for new changes in each category, dimension or criteria has been opened, favoring an evidence-based development of the future versions. DSM-5 is presented as a "living document" that can be updated easily. However, the category model still remains for many disorders. The future research in psychiatric diagnostic systems requires more genetic-molecular and neurophysiological evidence and more objective multinational field trials, in order to confirm the existence of the new diagnostic entities, spectrums or dimensions. This approach may provide us reliable information about the pathogenesis, psychopathology, adequate taxonomy and treatment of mental disorders.

Candidate-based proteomics in the search for biomarkers of cardiovascular disease

PubMed Central

Anderson, Leigh

2005-01-01

The key concept of proteomics (looking at many proteins at once) opens new avenues in the search for clinically useful biomarkers of disease, treatment response and ageing. As the number of proteins that can be detected in plasma or serum (the primary clinical diagnostic samples) increases towards 1000, a paradoxical decline has occurred in the number of new protein markers approved for diagnostic use in clinical laboratories. This review explores the limitations of current proteomics protein discovery platforms, and proposes an alternative approach, applicable to a range of biological/physiological problems, in which quantitative mass spectrometric methods developed for analytical chemistry are employed to measure limited sets of candidate markers in large sets of clinical samples. A set of 177 candidate biomarker proteins with reported associations to cardiovascular disease and stroke are presented as a starting point for such a ‘directed proteomics’ approach. PMID:15611012

Rapid Clinical Bacteriology and Its Future Impact

PubMed Central

Durand, Géraldine; Peyret, Michel; Chatellier, Sonia; Zambardi, Gilles; Schrenzel, Jacques; Shortridge, Dee; Engelhardt, Anette; Dunne, William Michael

2013-01-01

Clinical microbiology has always been a slowly evolving and conservative science. The sub-field of bacteriology has been and still is dominated for over a century by culture-based technologies. The integration of serological and molecular methodologies during the seventies and eighties of the previous century took place relatively slowly and in a cumbersome fashion. When nucleic acid amplification technologies became available in the early nineties, the predicted "revolution" was again slow but in the end a real paradigm shift did take place. Several of the culture-based technologies were successfully replaced by tests aimed at nucleic acid detection. More recently a second revolution occurred. Mass spectrometry was introduced and broadly accepted as a new diagnostic gold standard for microbial species identification. Apparently, the diagnostic landscape is changing, albeit slowly, and the combination of newly identified infectious etiologies and the availability of innovative technologies has now opened new avenues for modernizing clinical microbiology. However, the improvement of microbial antibiotic susceptibility testing is still lagging behind. In this review we aim to sketch the most recent developments in laboratory-based clinical bacteriology and to provide an overview of emerging novel diagnostic approaches. PMID:23301218

pFlogger: The Parallel Fortran Logging Utility

NASA Technical Reports Server (NTRS)

Clune, Tom; Cruz, Carlos A.

2017-01-01

In the context of high performance computing (HPC), software investments in support of text-based diagnostics, which monitor a running application, are typically limited compared to those for other types of IO. Examples of such diagnostics include reiteration of configuration parameters, progress indicators, simple metrics (e.g., mass conservation, convergence of solvers, etc.), and timers. To some degree, this difference in priority is justifiable as other forms of output are the primary products of a scientific model and, due to their large data volume, much more likely to be a significant performance concern. In contrast, text-based diagnostic content is generally not shared beyond the individual or group running an application and is most often used to troubleshoot when something goes wrong. We suggest that a more systematic approach enabled by a logging facility (or 'logger)' similar to those routinely used by many communities would provide significant value to complex scientific applications. In the context of high-performance computing, an appropriate logger would provide specialized support for distributed and shared-memory parallelism and have low performance overhead. In this paper, we present our prototype implementation of pFlogger - a parallel Fortran-based logging framework, and assess its suitability for use in a complex scientific application.

A Practical Approach to the Diagnosis of Pelvic Inflammatory Disease

PubMed Central

Jaiyeoba, Oluwatosin; Soper, David E.

2011-01-01

The diagnosis of acute pelvic inflammatory disease (PID) is usually based on clinical criteria and can be challenging for even the most astute clinicians. Although diagnostic accuracy is advocated, antibiotic treatment should be instituted if there is a diagnosis of cervicitis or suspicion of acute PID. Currently, no single test or combination of diagnostic indicators have been found to reliably predict PID, and laparoscopy cannot be recommended as a first line tool for PID diagnosis. For this reason, the clinician is left with maintaining a high index of suspicion for the diagnosis as he/she evaluates the lower genital tract for inflammation and the pelvic organs for tenderness in women with genital tract symptoms and a risk for sexually transmitted infection. This approach should minimize treating women without PID with antibiotics and optimize the diagnosis in a practical and cost-effective way. PMID:21822367

Rhinoceros Feet Step Out of a Rule-of-Thumb: A Wildlife Imaging Pioneering Approach of Synchronized Computed Tomography-Digital Radiography

PubMed Central

Saragusty, Joseph; Göritz, Frank; Potier, Romain; Mulot, Baptiste; Maillot, Alexis; Etienne, Pascal; Bernardino, Rui; Fernandes, Teresa; Mews, Jurgen; Hildebrandt, Thomas Bernd

2014-01-01

Currently, radiography is the only imaging technique used to diagnose bone pathology in wild animals situated under “field conditions”. Nevertheless, while chronic foot disease in captive mega-herbivores is widely reported, foot radiographic imaging is confronted with scarcity of studies. Numerous hindrances lead to such limited numbers and it became very clear that the traditional perspective on bone imaging in domestic animals based on extensive studies and elaborated statistical evaluations cannot be extrapolated to their non-domestic relatives. For these reasons, the authors initiated a multi-modality imaging study and established a pioneering approach of synchronized computed tomography (CT) and digital radiography (DR), based on X-ray projections derived from three-dimensional CT reconstructed images. Whereas this approach can be applied in any clinical field, as a case of outstanding importance and great concern for zoological institutions, we selected foot bone pathologies in captive rhinoceroses to demonstrate the manifold applications of the method. Several advances were achieved, endowing the wildlife clinician with all-important tools: prototype DR exposure protocols and a modus operandi for foot positioning, advancing both traditional projections and, for the first-time, species-related radiographic views; assessment of radiographic diagnostic value for the whole foot and, in premiere, for each autopodial bone; together with additional insights into radiographic appearance of bone anatomy and pathology with a unique, simultaneous CT-DR correlation. Based on its main advantages in availing a wide range of keystone data in wildlife imaging from a limited number of examined subjects and combining advantages of CT as the golden standard method for bone diseases' diagnostic with DR's clinical feasibility under field conditions, synchronized CT-DR presents a new perspective on wildlife's health management. With this we hope to provide veterinary clinicians with concrete imaging techniques and substantial diagnostic tools, which facilitate straightforward attainment and interpretation of field radiography images taken worldwide. PMID:24963807

Rhinoceros feet step out of a rule-of-thumb: a wildlife imaging pioneering approach of synchronized computed tomography-digital radiography.

PubMed

Galateanu, Gabriela; Hermes, Robert; Saragusty, Joseph; Göritz, Frank; Potier, Romain; Mulot, Baptiste; Maillot, Alexis; Etienne, Pascal; Bernardino, Rui; Fernandes, Teresa; Mews, Jurgen; Hildebrandt, Thomas Bernd

2014-01-01

Currently, radiography is the only imaging technique used to diagnose bone pathology in wild animals situated under "field conditions". Nevertheless, while chronic foot disease in captive mega-herbivores is widely reported, foot radiographic imaging is confronted with scarcity of studies. Numerous hindrances lead to such limited numbers and it became very clear that the traditional perspective on bone imaging in domestic animals based on extensive studies and elaborated statistical evaluations cannot be extrapolated to their non-domestic relatives. For these reasons, the authors initiated a multi-modality imaging study and established a pioneering approach of synchronized computed tomography (CT) and digital radiography (DR), based on X-ray projections derived from three-dimensional CT reconstructed images. Whereas this approach can be applied in any clinical field, as a case of outstanding importance and great concern for zoological institutions, we selected foot bone pathologies in captive rhinoceroses to demonstrate the manifold applications of the method. Several advances were achieved, endowing the wildlife clinician with all-important tools: prototype DR exposure protocols and a modus operandi for foot positioning, advancing both traditional projections and, for the first-time, species-related radiographic views; assessment of radiographic diagnostic value for the whole foot and, in premiere, for each autopodial bone; together with additional insights into radiographic appearance of bone anatomy and pathology with a unique, simultaneous CT-DR correlation. Based on its main advantages in availing a wide range of keystone data in wildlife imaging from a limited number of examined subjects and combining advantages of CT as the golden standard method for bone diseases' diagnostic with DR's clinical feasibility under field conditions, synchronized CT-DR presents a new perspective on wildlife's health management. With this we hope to provide veterinary clinicians with concrete imaging techniques and substantial diagnostic tools, which facilitate straightforward attainment and interpretation of field radiography images taken worldwide.

Tailoring the Psychotherapy to the Borderline Patient

PubMed Central

HORWITZ, LEONARD; GABBARD, GLEN O.; ALLEN, JON G.; COLSON, DONALD B.; FRIESWYK, SIEBOLT; NEWSOM, GAVIN E.; COYNE, LOLAFAYE

1996-01-01

Views still differ as to the optimal psychodynamic treatment of borderline patients. Recommendations range from psychoanalysis and exploratory psychotherapy to an explicitly supportive treatment aimed at strengthening adaptive defenses. The authors contend that no single approach is appropriate for all patients in this wide-ranging diagnostic category, which spans a continuum from close-to-neurotic to close-to-psychotic levels of functioning. Careful differentiations based on developmental considerations, ego structures, and relationship patterns provide the basis for the optimal treatment approach. PMID:22700301

Peers without fears? Barriers to effective communication among primary care physicians and oncologists about diagnostic delays in cancer

PubMed Central

Lipitz-Snyderman, Allison; Kale, Minal; Robbins, Laura; Pfister, David; Fortier, Elizabeth; Pocus, Valerie; Chimonas, Susan; Weingart, Saul N

2018-01-01

Objective Relatively little attention has been devoted to the role of communication between physicians as a mechanism for individual and organisational learning about diagnostic delays. This study’s objective was to elicit physicians’ perceptions about and experiences with communication among physicians regarding diagnostic delays in cancer. Design, setting, participants Qualitative analysis based on seven focus groups. Fifty-one physicians affiliated with three New York-based academic medical centres participated, with six to nine subjects per group. We used content analysis to identify commonalities among primary care physicians and specialists (ie, medical and surgical oncologists). Primary outcome measure Perceptions and experiences with physician-to-physician communication about delays in cancer diagnosis. Results Our analysis identified five major themes: openness to communication, benefits of communication, fears about giving and receiving feedback, infrastructure barriers to communication and overcoming barriers to communication. Subjects valued communication about cancer diagnostic delays, but they had many concerns and fears about providing and receiving feedback in practice. Subjects expressed reluctance to communicate if there was insufficient information to attribute responsibility, if it would have no direct benefit or if it would jeopardise their existing relationships. They supported sensitive approaches to conveying information, as they feared eliciting or being subject to feelings of incompetence or shame. Subjects also cited organisational barriers. They offered suggestions that might facilitate communication about delays. Conclusions Addressing the barriers to communication among physicians about diagnostic delays is needed to promote a culture of learning across specialties and institutions. Supporting open and honest discussions about diagnostic delays may help build safer health systems. PMID:28655713

Ultrasonography of ovarian masses using a pattern recognition approach

PubMed Central

Jung, Sung Il

2015-01-01

As a primary imaging modality, ultrasonography (US) can provide diagnostic information for evaluating ovarian masses. Using a pattern recognition approach through gray-scale transvaginal US, ovarian masses can be diagnosed with high specificity and sensitivity. Doppler US may allow ovarian masses to be diagnosed as benign or malignant with even greater confidence. In order to differentiate benign and malignant ovarian masses, it is necessary to categorize ovarian masses into unilocular cyst, unilocular solid cyst, multilocular cyst, multilocular solid cyst, and solid tumor, and then to detect typical US features that demonstrate malignancy based on pattern recognition approach. PMID:25797108

Novel Applications of Radionuclide Imaging in Peripheral Vascular Disease

PubMed Central

Stacy, Mitchel R.; Sinusas, Albert J.

2015-01-01

Peripheral vascular disease (PVD) is a progressive atherosclerotic disease that leads to stenosis or occlusion of blood vessels supplying the lower extremities. Current diagnostic imaging techniques commonly focus on evaluation of anatomy or blood flow at the macrovascular level and do not permit assessment of the underlying pathophysiology associated with disease progression or treatment response. Molecular imaging with radionuclide-based approaches, such as PET and SPECT, can offer novel insight into PVD by providing non-invasive assessment of biological processes such as angiogenesis and atherosclerosis. This review discusses emerging radionuclide-based imaging approaches that have potential clinical applications in the evaluation of PVD progression and treatment. PMID:26590787

The polarization evolution of electromagnetic waves as a diagnostic method for a motional plasma

NASA Astrophysics Data System (ADS)

Shahrokhi, Alireza; Mehdian, Hassan; Hajisharifi, Kamal; Hasanbeigi, Ali

2017-12-01

The polarization evolution of electromagnetic (EM) radiation propagating through an electron beam-ion channel system is studied in the presence of self-magnetic field. Solving the fluid-Maxwell equations to obtain the medium dielectric tensor, the Stokes vector-Mueller matrix approach is employed to determine the polarization of the launched EM wave at any point in the propagation direction, applying the space-dependent Mueller matrix on the initial polarization vector of the wave at the plasma-vacuum interface. Results show that the polarization evolution of the wave is periodic in space along the beam axis with the specified polarization wavelength. Using the obtained results, a novel diagnostic method based on the polarization evolution of the EM waves is proposed to evaluate the electron beam density and velocity. Moreover, to use the mentioned plasma system as a polarizer, the fraction of the output radiation power transmitted through a motional plasma crossed with the input polarization is calculated. The results of the present investigation will greatly contribute to design a new EM amplifier with fixed polarization or EM polarizer, as well as a new diagnostic approach for the electron beam system where the polarimetric method is employed.

Tracking of multimodal therapeutic nanocomplexes targeting breast cancer in vivo.

PubMed

Bardhan, Rizia; Chen, Wenxue; Bartels, Marc; Perez-Torres, Carlos; Botero, Maria F; McAninch, Robin Ward; Contreras, Alejandro; Schiff, Rachel; Pautler, Robia G; Halas, Naomi J; Joshi, Amit

2010-12-08

Nanoparticle-based therapeutics with local delivery and external electromagnetic field modulation holds extraordinary promise for soft-tissue cancers such as breast cancer; however, knowledge of the distribution and fate of nanoparticles in vivo is crucial for clinical translation. Here we demonstrate that multiple diagnostic capabilities can be introduced in photothermal therapeutic nanocomplexes by simultaneously enhancing both near-infrared fluorescence and magnetic resonance imaging (MRI). We track nanocomplexes in vivo, examining the influence of HER2 antibody targeting on nanocomplex distribution over 72 h. This approach provides valuable, detailed information regarding the distribution and fate of complex nanoparticles designed for specific diagnostic and therapeutic functions.

Stationary microfluidics: molecular diagnostic assays by moving magnetic beads through non-moving liquids

NASA Astrophysics Data System (ADS)

Becker, Holger; Carstens, Cornelia; Kuhlmeier, Dirk; Sandetskaya, Natalia; Schröter, Nicole; Zilch, Christian; Gärtner, Claudia

2013-03-01

Commonly, microfluidic devices are based on the movement of fluids. For molecular diagnostics assays which often include steps like PCR, this practically always involves a more or less complicated set of external pumps, valves and liquid controls. In the presented paper, we follow a different approach in which the fluid after sample introduction remains stationary and the main bioactive sample molecules are moved through a chain of reaction compartments which contain the different reagents necessary for the assay. The big advantage of this concept is the lack of any external fluid actuation/control. Results on sample carry-over experiments and complete assays will be given.

Endoscopy as a diagnostic and therapeutic alternative technique of taeniasis.

PubMed

Canaval Zuleta, Héctor Julián; Company Campins, María M; Dolz Abadía, Carlos

2016-06-01

Despite a low incidence in developed countries, gastrointestinal taeniasis should be suspected in patients with abdominal pain, diarrhea, anemia, and/or malabsorption of unknown origin, even more so if they come from endemic regions or areas with poor hygienic and alimentary habits. Diagnosis is traditionally reached by identifying the parasite in stools, but more recently both serological and immunological approaches are also available. Based on a patient diagnosed by gastroscopy, a literature review was undertaken of patients diagnosed by endoscopy. We discuss endoscopy as diagnostic modality, and the effectiveness and safety that endoscopic treatment may provide in view of the potential risk for neurocysticercosis.

Tracking of Multimodal Therapeutic Nanocomplexes Targeting Breast Cancer in Vivo

PubMed Central

Bardhan, Rizia; Chen, Wenxue; Bartels, Marc; Perez-Torres, Carlos; Botero, Maria F.; McAninch, Robin Ward; Contreras, Alejandro; Schiff, Rachel; Pautler, Robia G.; Halas, Naomi J.; Joshi, Amit

2014-01-01

Nanoparticle-based therapeutics with local delivery and external electromagnetic field modulation holds extraordinary promise for soft-tissue cancers such as breast cancer; however, knowledge of the distribution and fate of nanoparticles in vivo is crucial for clinical translation. Here we demonstrate that multiple diagnostic capabilities can be introduced in photothermal therapeutic nanocomplexes by simultaneously enhancing both near-infrared fluorescence and magnetic resonance imaging (MRI). We track nanocomplexes in vivo, examining the influence of HER2 antibody targeting on nanocomplex distribution over 72 h. This approach provides valuable, detailed information regarding the distribution and fate of complex nanoparticles designed for specific diagnostic and therapeutic functions. PMID:21090693

Experimental nonlocality-based network diagnostics of multipartite entangled states.

PubMed

Ciampini, Mario A; Vigliar, Caterina; Cimini, Valeria; Paesani, Stefano; Sciarrino, Fabio; Crespi, Andrea; Corrielli, Giacomo; Osellame, Roberto; Mataloni, Paolo; Paternostro, Mauro; Barbieri, Marco

2017-12-07

We introduce a novel diagnostic scheme for multipartite networks of entangled particles, aimed at assessing the quality of the gates used for the engineering of their state. Using the information gathered from a set of suitably chosen multiparticle Bell tests, we identify conditions bounding the quality of the entangled bonds among the elements of a register. We illustrate the effectiveness of our proposal by characterizing a quantum resource engineered combining two-photon hyperentanglement and photonic-chip technology. Our approach opens up future studies on medium-sized networks due to the intrinsically modular nature of cluster states, and paves the way to section-by-section analysis of larger photonics resources.

ISACS-DOC: Monitoring and Diagnostic System for AKARI and HINODE

NASA Astrophysics Data System (ADS)

Mizutani, Mitsue; Hirose, Toshinori; Takaki, Ryoji; Honda, Hideyuki

ISACS-DOC (Intelligent Satellite Control Software-DOCtor), which is an automatic monitoring and diagnostic system for scientific satellites or spacecraft, aims to rapidly and accurately capture important changes and sign of anomaly during daily satellite operations. After three systems for deep space missions, the new generation of ISACS-DOC with a higher speed processing performance had been developed for the satellites in earth orbit, AKARI and HINODE. This paper reports on the newest ISACS-DOC about enhanced functions, operating status, and an approach to create standards to build and keep up the knowledge data base. Continuous enhancements through the actual operations are the advantage of ISACS-DOC.

Identification of mine rescue equipment reduction gears technical condition

NASA Astrophysics Data System (ADS)

Gerike, B. L.; Klishin, V. I.; Kuzin, E. G.

2017-09-01

The article presents the reasons for adopting intelligent service of mine belt conveyer drives concerning evaluation of their technical condition based on the diagnostic techniques instead of regular preventative maintenance. The article reveals the diagnostic results of belt conveyer drive reduction gears condition taking into account the parameters of lubricating oil, vibration and temperature. Usage of a complex approach to evaluate technical conditions allows reliability of the forecast to be improved, which makes it possible not only to prevent accidental breakdowns and eliminate unscheduled downtime, but also to bring sufficient economic benefits through reduction of the term and scope of work during overhauls.

Current molecular and emerging nanobiotechnology approaches for the detection of microbial pathogens.

PubMed

Theron, Jacques; Eugene Cloete, Thomas; de Kwaadsteniet, Michele

2010-11-01

Waterborne microbial diseases are escalating worldwide increasing the need for powerful and sensitive diagnostics tools. Molecular methodologies, including immunological and nucleic acid-based methods, have only recently been applied in the water sector. Advances in nanotechnology and nanomaterials have opened the door for the development of new diagnostic tools with increased sensitivity and speed, and reduced cost and labor. Quantum dots, flo dots, gold nanoparticles, magnetic nanoparticles, carbon nanotubes, nanowires, and nanocantilevers, with their unique optical and physical properties, have already been applied in nanodiagnostics. Nanobiotechnology, once remaining technical and practical problems has been addressed, will play an important role in the detection of microbial pathogens.

Problem-solving strategies in psychiatry: differences between experts and novices in diagnostic accuracy and reasoning.

PubMed

Gabriel, Adel; Violato, Claudio

2013-01-01

The purpose of this study was to examine and compare diagnostic success and its relationship with the diagnostic reasoning process between novices and experts in psychiatry. Nine volunteers, comprising five expert psychiatrists and four clinical clerks, completed a think-aloud protocol while attempting to make a DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) diagnosis of a selected case with both Axis I and Axis III diagnoses. Expert psychiatrists made significantly more successful diagnoses for both the primary psychiatric and medical diagnoses than clinical clerks. Expert psychiatrists also gave fewer differential options. Analyzing the think-aloud protocols, expert psychiatrists were much more organized, made fewer mistakes, and utilized significantly less time to access their knowledge than clinical clerks. Both novices and experts seemed to use the hypothetic-deductive and scheme-inductive approaches to diagnosis. However, experts utilized hypothetic-deductive approaches significantly more often than novices. The hypothetic-deductive diagnostic strategy was utilized more than the scheme-inductive approach by both expert psychiatrists and clinical clerks. However, a specific relationship between diagnostic reasoning and diagnostic success could not be identified in this small pilot study. The author recommends a larger study that would include a detailed analysis of the think-aloud protocols.

A diagnostic algorithm for atypical spitzoid tumors: guidelines for immunohistochemical and molecular assessment.

PubMed

Cho-Vega, Jeong Hee

2016-07-01

Atypical spitzoid tumors are a morphologically diverse group of rare melanocytic lesions most frequently seen in children and young adults. As atypical spitzoid tumors bear striking resemblance to Spitz nevus and spitzoid melanomas clinically and histopathologically, it is crucial to determine its malignant potential and predict its clinical behavior. To date, many researchers have attempted to differentiate atypical spitzoid tumors from unequivocal melanomas based on morphological, immonohistochemical, and molecular diagnostic differences. A diagnostic algorithm is proposed here to assess the malignant potential of atypical spitzoid tumors by using a combination of immunohistochemical and cytogenetic/molecular tests. Together with classical morphological evaluation, this algorithm includes a set of immunohistochemistry assays (p16(Ink4a), a dual-color Ki67/MART-1, and HMB45), fluorescence in situ hybridization (FISH) with five probes (6p25, 8q24, 11q13, CEN9, and 9p21), and an array-based comparative genomic hybridization. This review discusses details of the algorithm, the rationale of each test used in the algorithm, and utility of this algorithm in routine dermatopathology practice. This algorithmic approach will provide a comprehensive diagnostic tool that complements conventional histological criteria and will significantly contribute to improve the diagnosis and prediction of the clinical behavior of atypical spitzoid tumors.

European Respiratory Society guidelines for the diagnosis of primary ciliary dyskinesia.

PubMed

Lucas, Jane S; Barbato, Angelo; Collins, Samuel A; Goutaki, Myrofora; Behan, Laura; Caudri, Daan; Dell, Sharon; Eber, Ernst; Escudier, Estelle; Hirst, Robert A; Hogg, Claire; Jorissen, Mark; Latzin, Philipp; Legendre, Marie; Leigh, Margaret W; Midulla, Fabio; Nielsen, Kim G; Omran, Heymut; Papon, Jean-Francois; Pohunek, Petr; Redfern, Beatrice; Rigau, David; Rindlisbacher, Bernhard; Santamaria, Francesca; Shoemark, Amelia; Snijders, Deborah; Tonia, Thomy; Titieni, Andrea; Walker, Woolf T; Werner, Claudius; Bush, Andrew; Kuehni, Claudia E

2017-01-01

The diagnosis of primary ciliary dyskinesia is often confirmed with standard, albeit complex and expensive, tests. In many cases, however, the diagnosis remains difficult despite the array of sophisticated diagnostic tests. There is no "gold standard" reference test. Hence, a Task Force supported by the European Respiratory Society has developed this guideline to provide evidence-based recommendations on diagnostic testing, especially in light of new developments in such tests, and the need for robust diagnoses of patients who might enter randomised controlled trials of treatments. The guideline is based on pre-defined questions relevant for clinical care, a systematic review of the literature, and assessment of the evidence using the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) approach. It focuses on clinical presentation, nasal nitric oxide, analysis of ciliary beat frequency and pattern by high-speed video-microscopy analysis, transmission electron microscopy, genotyping and immunofluorescence. It then used a modified Delphi survey to develop an algorithm for the use of diagnostic tests to definitively confirm and exclude the diagnosis of primary ciliary dyskinesia; and to provide advice when the diagnosis was not conclusive. Finally, this guideline proposes a set of quality criteria for future research on the validity of diagnostic methods for primary ciliary dyskinesia. Copyright ©ERS 2017.

3D morphometry of red blood cells by digital holography.

PubMed

Memmolo, Pasquale; Miccio, Lisa; Merola, Francesco; Gennari, Oriella; Netti, Paolo Antonio; Ferraro, Pietro

2014-12-01

Three dimensional (3D) morphometric analysis of flowing and not-adherent cells is an important aspect for diagnostic purposes. However, diagnostics tools need to be quantitative, label-free and, as much as possible, accurate. Recently, a simple holographic approach, based on shape from silhouette algorithm, has been demonstrated for accurate calculation of cells biovolume and displaying their 3D shapes. Such approach has been adopted in combination with holographic optical tweezers and successfully applied to cells with convex shape. Nevertheless, unfortunately, the method fails in case of specimen with concave surfaces. Here, we propose an effective approach to achieve correct 3D shape measurement that can be extended in case of cells having concave surfaces, thus overcoming the limit of the previous technique. We prove the new procedure for healthy red blood cells (RBCs) (i.e., discocytes) having a concave surface in their central region. Comparative analysis of experimental results with a theoretical 3D geometrical model of RBC is discussed in order to evaluate accuracy of the proposed approach. Finally, we show that the method can be also useful to classify, in terms of morphology, different varieties of RBCs. © 2014 International Society for Advancement of Cytometry.

Approach to Operational Experimental Estimation of Static Stresses of Elements of Mechanical Structures

NASA Astrophysics Data System (ADS)

Sedov, A. V.; Kalinchuk, V. V.; Bocharova, O. V.

2018-01-01

The evaluation of static stresses and strength of units and components is a crucial task for increasing reliability in the operation of vehicles and equipment, to prevent emergencies, especially in structures made of metal and composite materials. At the stage of creation and commissioning of structures to control the quality of manufacturing of individual elements and components, diagnostic control methods are widely used. They are acoustic, ultrasonic, X-ray, radiation methods and others. The using of these methods to control the residual life and the degree of static stresses of units and parts during operation is fraught with great difficulties both in methodology and in instrumentation. In this paper, the authors propose an effective approach of operative control of the degree of static stresses of units and parts of mechanical structures which are in working condition, based on recording the changing in the surface wave properties of a system consisting of a sensor and a controlled environment (unit, part). The proposed approach of low-frequency diagnostics of static stresses presupposes a new adaptive-spectral analysis of a surface wave created by external action (impact). It is possible to estimate implicit stresses of structures in the experiment due to this approach.

Development of a neural network technique for KSTAR Thomson scattering diagnostics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Seung Hun, E-mail: leesh81@nfri.re.kr; Lee, J. H.; Yamada, I.

Neural networks provide powerful approaches of dealing with nonlinear data and have been successfully applied to fusion plasma diagnostics and control systems. Controlling tokamak plasmas in real time is essential to measure the plasma parameters in situ. However, the χ{sup 2} method traditionally used in Thomson scattering diagnostics hampers real-time measurement due to the complexity of the calculations involved. In this study, we applied a neural network approach to Thomson scattering diagnostics in order to calculate the electron temperature, comparing the results to those obtained with the χ{sup 2} method. The best results were obtained for 10{sup 3} training cyclesmore » and eight nodes in the hidden layer. Our neural network approach shows good agreement with the χ{sup 2} method and performs the calculation twenty times faster.« less

A comprehensive custom panel design for routine hereditary cancer testing: preserving control, improving diagnostics and revealing a complex variation landscape.

PubMed

Castellanos, Elisabeth; Gel, Bernat; Rosas, Inma; Tornero, Eva; Santín, Sheila; Pluvinet, Raquel; Velasco, Juan; Sumoy, Lauro; Del Valle, Jesús; Perucho, Manuel; Blanco, Ignacio; Navarro, Matilde; Brunet, Joan; Pineda, Marta; Feliubadaló, Lidia; Capellá, Gabi; Lázaro, Conxi; Serra, Eduard

2017-01-04

We wanted to implement an NGS strategy to globally analyze hereditary cancer with diagnostic quality while retaining the same degree of understanding and control we had in pre-NGS strategies. To do this, we developed the I2HCP panel, a custom bait library covering 122 hereditary cancer genes. We improved bait design, tested different NGS platforms and created a clinically driven custom data analysis pipeline. The I2HCP panel was developed using a training set of hereditary colorectal cancer, hereditary breast and ovarian cancer and neurofibromatosis patients and reached an accuracy, analytical sensitivity and specificity greater than 99%, which was maintained in a validation set. I2HCP changed our diagnostic approach, involving clinicians and a genetic diagnostics team from panel design to reporting. The new strategy improved diagnostic sensitivity, solved uncertain clinical diagnoses and identified mutations in new genes. We assessed the genetic variation in the complete set of hereditary cancer genes, revealing a complex variation landscape that coexists with the disease-causing mutation. We developed, validated and implemented a custom NGS-based strategy for hereditary cancer diagnostics that improved our previous workflows. Additionally, the existence of a rich genetic variation in hereditary cancer genes favors the use of this panel to investigate their role in cancer risk.

Diagnostic performance of 64-slice multidetector coronary computed tomographic angiography in women.

PubMed

Jug, Borut; Gupta, Mohit; Papazian, Jenny; Li, Dong; Tsang, Janet; Bhatia, Harpreet; Karlsberg, Ronald; Budoff, Matthew

2012-12-01

Diagnostic approach to chest pain in women is challenging, but still under-investigated. The purpose of this study was to assess the diagnostic performance of 64-slice multidetector coronary computed tomographic angiography (CCTA) in women with chest pain. We included 606 patients--255 women and 351 men (mean age 61 ± 12 years for both)--who had been referred for a CCTA and an invasive coronary angiography (diagnostic standard) because of chest pain, either as part of clinical work-up in two urban medical centers or as part of the multicenter ACCURACY trial. On a patient-based model, the sensitivity, specificity, and positive predictive value (PPV) and negative predictive value to detect ≥50% and ≥70% stenosis were 98%, 84%, 87%, and 97% and 96%, 83%, 77%, and 97%, respectively, for women and 97%, 83%, 89%, and 95% and 94%, 91%, 90%, and 94%, respectively, for men. There were no statistically significant differences between men and women in diagnostic performance measures except for the PPV of detecting a ≥70% stenosis (P = .007). In women with chest pain, 64-slice multidetector CCTA is at least as sensitive and specific as in men. Our findings suggest that CCTA is a promising diagnostic tool for timely detection and/or exclusion of CAD in symptomatic intermediate-risk female populations.

Diagnostic Challenges in Prostate Cancer and 68Ga-PSMA PET Imaging: A Game Changer?

PubMed

Zaman, Maseeh uz; Fatima, Nosheen; Zaman, Areeba; Sajid, Mahwsih; Zaman, Unaiza; Zaman, Sidra

2017-10-26

Prostate cancer (PC) is the most frequent solid tumor in men and the third most common cause of cancer mortality among men in developed countries. Current imaging modalities like ultrasound (US), computerized tomography (CT), magnetic resonance imaging (MRI) and choline based positron emission (PET) tracing have disappointing sensitivity for detection of nodal metastasis and small tumor recurrence. This poses a diagnostic challenge in staging of intermediate to high risk PC and restaging of patients with biochemical recurrence (PSA >0.2 ng/ml). Gallium-68 labeled prostate specific membrane antigen (68Ga-PSMA) PET imaging has now emerged with a higher diagnostic yield. 68Ga-PSMA PET/CT or PET/MRI can be expected to offer a one-stop-shop for staging and restaging of PC. PSMA ligands labeled with alpha and beta emitters have also shown promising therapeutic efficacy for nodal, bone and visceral metastasis. Therefore a PSMA based theranostics approach for detection, staging, treatment, and follow-up of PC would appear to be highly valuable to achieve personalized PC treatment. Creative Commons Attribution License

A Diagnostic Approach for Electro-Mechanical Actuators in Aerospace Systems

NASA Technical Reports Server (NTRS)

Balaban, Edward; Saxena, Abhinav; Bansal, Prasun; Goebel, Kai Frank; Stoelting, Paul; Curran, Simon

2009-01-01

Electro-mechanical actuators (EMA) are finding increasing use in aerospace applications, especially with the trend towards all all-electric aircraft and spacecraft designs. However, electro-mechanical actuators still lack the knowledge base accumulated for other fielded actuator types, particularly with regard to fault detection and characterization. This paper presents a thorough analysis of some of the critical failure modes documented for EMAs and describes experiments conducted on detecting and isolating a subset of them. The list of failures has been prepared through an extensive Failure Modes and Criticality Analysis (FMECA) reference, literature review, and accessible industry experience. Methods for data acquisition and validation of algorithms on EMA test stands are described. A variety of condition indicators were developed that enabled detection, identification, and isolation among the various fault modes. A diagnostic algorithm based on an artificial neural network is shown to operate successfully using these condition indicators and furthermore, robustness of these diagnostic routines to sensor faults is demonstrated by showing their ability to distinguish between them and component failures. The paper concludes with a roadmap leading from this effort towards developing successful prognostic algorithms for electromechanical actuators.

Sparsity-based super-resolved coherent diffraction imaging of one-dimensional objects.

PubMed

Sidorenko, Pavel; Kfir, Ofer; Shechtman, Yoav; Fleischer, Avner; Eldar, Yonina C; Segev, Mordechai; Cohen, Oren

2015-09-08

Phase-retrieval problems of one-dimensional (1D) signals are known to suffer from ambiguity that hampers their recovery from measurements of their Fourier magnitude, even when their support (a region that confines the signal) is known. Here we demonstrate sparsity-based coherent diffraction imaging of 1D objects using extreme-ultraviolet radiation produced from high harmonic generation. Using sparsity as prior information removes the ambiguity in many cases and enhances the resolution beyond the physical limit of the microscope. Our approach may be used in a variety of problems, such as diagnostics of defects in microelectronic chips. Importantly, this is the first demonstration of sparsity-based 1D phase retrieval from actual experiments, hence it paves the way for greatly improving the performance of Fourier-based measurement systems where 1D signals are inherent, such as diagnostics of ultrashort laser pulses, deciphering the complex time-dependent response functions (for example, time-dependent permittivity and permeability) from spectral measurements and vice versa.

A computer-human interaction model to improve the diagnostic accuracy and clinical decision-making during 12-lead electrocardiogram interpretation.

PubMed

Cairns, Andrew W; Bond, Raymond R; Finlay, Dewar D; Breen, Cathal; Guldenring, Daniel; Gaffney, Robert; Gallagher, Anthony G; Peace, Aaron J; Henn, Pat

2016-12-01

The 12-lead Electrocardiogram (ECG) presents a plethora of information and demands extensive knowledge and a high cognitive workload to interpret. Whilst the ECG is an important clinical tool, it is frequently incorrectly interpreted. Even expert clinicians are known to impulsively provide a diagnosis based on their first impression and often miss co-abnormalities. Given it is widely reported that there is a lack of competency in ECG interpretation, it is imperative to optimise the interpretation process. Predominantly the ECG interpretation process remains a paper based approach and whilst computer algorithms are used to assist interpreters by providing printed computerised diagnoses, there are a lack of interactive human-computer interfaces to guide and assist the interpreter. An interactive computing system was developed to guide the decision making process of a clinician when interpreting the ECG. The system decomposes the interpretation process into a series of interactive sub-tasks and encourages the clinician to systematically interpret the ECG. We have named this model 'Interactive Progressive based Interpretation' (IPI) as the user cannot 'progress' unless they complete each sub-task. Using this model, the ECG is segmented into five parts and presented over five user interfaces (1: Rhythm interpretation, 2: Interpretation of the P-wave morphology, 3: Limb lead interpretation, 4: QRS morphology interpretation with chest lead and rhythm strip presentation and 5: Final review of 12-lead ECG). The IPI model was implemented using emerging web technologies (i.e. HTML5, CSS3, AJAX, PHP and MySQL). It was hypothesised that this system would reduce the number of interpretation errors and increase diagnostic accuracy in ECG interpreters. To test this, we compared the diagnostic accuracy of clinicians when they used the standard approach (control cohort) with clinicians who interpreted the same ECGs using the IPI approach (IPI cohort). For the control cohort, the (mean; standard deviation; confidence interval) of the ECG interpretation accuracy was (45.45%; SD=18.1%; CI=42.07, 48.83). The mean ECG interpretation accuracy rate for the IPI cohort was 58.85% (SD=42.4%; CI=49.12, 68.58), which indicates a positive mean difference of 13.4%. (CI=4.45, 22.35) An N-1 Chi-square test of independence indicated a 92% chance that the IPI cohort will have a higher accuracy rate. Interpreter self-rated confidence also increased between cohorts from a mean of 4.9/10 in the control cohort to 6.8/10 in the IPI cohort (p=0.06). Whilst the IPI cohort had greater diagnostic accuracy, the duration of ECG interpretation was six times longer when compared to the control cohort. We have developed a system that segments and presents the ECG across five graphical user interfaces. Results indicate that this approach improves diagnostic accuracy but with the expense of time, which is a valuable resource in medical practice. Copyright © 2016 Elsevier Inc. All rights reserved.

Identifying species of moths (Lepidoptera) from Baihua Mountain, Beijing, China, using DNA barcodes

PubMed Central

Liu, Xiao F; Yang, Cong H; Han, Hui L; Ward, Robert D; Zhang, Ai-bing

2014-01-01

DNA barcoding has become a promising means for the identification of organisms of all life-history stages. Currently, distance-based and tree-based methods are most widely used to define species boundaries and uncover cryptic species. However, there is no universal threshold of genetic distance values that can be used to distinguish taxonomic groups. Alternatively, DNA barcoding can deploy a “character-based” method, whereby species are identified through the discrete nucleotide substitutions. Our research focuses on the delimitation of moth species using DNA-barcoding methods. We analyzed 393 Lepidopteran specimens belonging to 80 morphologically recognized species with a standard cytochrome c oxidase subunit I (COI) sequencing approach, and deployed tree-based, distance-based, and diagnostic character-based methods to identify the taxa. The tree-based method divided the 393 specimens into 79 taxa (species), and the distance-based method divided them into 84 taxa (species). Although the diagnostic character-based method found only 39 so-identifiable species in the 80 species, with a reduction in sample size the accuracy rate substantially improved. For example, in the Arctiidae subset, all 12 species had diagnostics characteristics. Compared with traditional morphological method, molecular taxonomy performed well. All three methods enable the rapid delimitation of species, although they have different characteristics and different strengths. The tree-based and distance-based methods can be used for accurate species identification and biodiversity studies in large data sets, while the character-based method performs well in small data sets and can also be used as the foundation of species-specific biochips. PMID:25360280

Isotope Cancer Treatment Research at LANL

ScienceCinema

Weidner, John; Nortier, Meiring

2018-02-13

Los Alamos National Laboratory has produced medical isotopes for diagnostic and imaging purposes for more than 30 years. Now LANL researchers have branched out into isotope cancer treatment studies. New results show that an accelerator-based approach can produce clinical trial quantities of actinium-225, an isotope that has promise as a way to kill tumors without damaging surrounding healthy cells.

[Idiopathic gynecomastia: our experience].

PubMed

Barbuscia, M; Di Pietro, N; Rizzo, A G; Catalfamo, A; Melita, G; Sanò, M; Mancuso, V; Gorgone, S

2003-04-01

The Authors reporting their experience, discuss some concepts about physiologic evolution of male and female breast. They distinguish between real and false gynaecomastia; stressing the causes of abnormal development of male breast and morphopathological characteristics of gynaecomastia. Careful diagnostic protocol is necessary for a therapeutic approach based on traditional surgery or liposuction: it depends on prevalence of glandular or adipose breast's tissue.

Network Approach to Autistic Traits: Group and Subgroup Analyses of ADOS Item Scores

ERIC Educational Resources Information Center

Anderson, George M.; Montazeri, Farhad; de Bildt, Annelies

2015-01-01

A network conceptualization might contribute to understanding the occurrence and interacting nature of behavioral traits in the autism realm. Networks were constructed based on correlations of item scores of the Autism Diagnostic Observation Schedule for Modules 1, 2 and 3 obtained for a group of 477 Dutch individuals with developmental disorders.…