- Keywords
- MB/BacT'TM' (OTI, Turnhout, Belgie),
- MeSH
- Automation methods supply & distribution MeSH
- Humans MeSH
- Microbiological Techniques methods MeSH
- Mycobacterium tuberculosis isolation & purification growth & development MeSH
- Nucleic Acid Probes MeSH
- Fluids and Secretions microbiology MeSH
- Tuberculosis diagnosis microbiology MeSH
- Check Tag
- Humans MeSH
Background: Tuberculosis (TB) is a major cause of illness and death in many countries, especially in Asia and Africa. Repeated tests of microscopic examination are needed to be performed for early detection of the disease. Hence there is a need to automate the diagnostic process for improvement in the sensitivity and accuracy of the test. Objective: To automate the decision support system for tuberculosis digital images using histogram based statistical features and evolutionary based extreme learning machines. Materials and methods: The sputum smear positive and negative images recorded under standard image acquisition protocol are subjected to histogram based feature extraction technique. Most significant features are selected using student ‘t’ test. These significant features are further used as input to the differential evolutionary extreme learning machine classifier. Results: Results demonstrate that the histogram based significant features are able to differentiate TB positive and negative images with a higher specificity and accuracy. Conclusion: The methodology used in this work seems to be useful for the automated analysis of TB sputum smear images in mass screening disorders such as pulmonary tuberculosis.
Easy, efficient and low demanding separation of mRNA from biological material is needed to study gene expression and to use in chip technologies. It is common knowledge that each mRNA molecule contains sequence of 25 adenines. This feature can be used for binding mRNA on the surface of the particles coated by thymine chains. The present work reports on suggesting and optimizing of mRNA separation and detection from biological material via paramagnetic microparticles coupled with electrochemical detection. Primarily we optimized cyclic and square wave voltammetric conditions to detect poly(A), which was used as standard to mimic behaviour of mRNA. Under the optimized square wave voltammetric conditions (frequency 280 Hz, accumulation time 200 s, supporting electrolyte and its temperature: acetate buffer 4.6 and 35 degrees C) we estimated detection limit down to 1 ng of poly(A) per ml. To enhance effectiveness and repeatability of isolation of nucleic acid automated approach for rinsing and hybridizing was proposed. We optimized the whole procedure and experimental conditions. Using automated way of isolation and under optimized conditions the yield of poly(A) (isolated concentration of poly(A)/given concentration of poly(A)*100) was approximately 75%. The suggested and optimized method for poly(A) isolation and detection was utilized for the analysis of brain tissues of patients with traumatic brain injury. The total amount of isolated mRNA varied from 40 to 760 g of mRNA per g of brain tissue. The isolation of mRNA from six samples per run was not longer than 2.5h. Moreover, we applied the optimized procedure on fully automated pipetting instrument to isolate mRNA. The instrument was successfully tested on the analysis of extracts from roots of maize plants treated with cadmium(II) ions.
- MeSH
- Adenine MeSH
- Automation MeSH
- Electrochemical Techniques methods MeSH
- Nucleic Acid Hybridization MeSH
- Zea mays genetics MeSH
- Humans MeSH
- Magnetics MeSH
- RNA, Messenger isolation & purification MeSH
- Brain Chemistry MeSH
- Nucleic Acids isolation & purification MeSH
- Base Pairing MeSH
- Brain Injuries genetics MeSH
- Thymine MeSH
- Particle Size MeSH
- Check Tag
- Humans MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
To ensure food safety and to prevent unnecessary foodborne complications this study reports fast, fully automated process for histamine determination. This method is based on magnetic separation of histamine with magnetic particles and quantification by the fluorescence intensity change of MSA modified CdSe Quantum dots. Formation of Fe2O3 particles was followed by adsorption of TiO2 on their surface. Magnetism of developed probe enabled rapid histamine isolation prior to its fluorescence detection. Quantum dots (QDs) of approx. 3 nm were prepared via facile UV irradiation. The fluorescence intensity of CdSe QDs was enhanced upon mixing with magnetically separated histamine, in concentration-dependent manner, with a detection limit of 1.6 μM. The linear calibration curve ranged between 0.07 and 4.5 mM histamine with a low LOD and LOQ of 1.6 μM and 6 μM. The detection efficiency of the method was confirmed by ion exchange chromatography. Moreover, the specificity of the sensor was evaluated and no cross-reactivity from nontarget analytes was observed. This method was successfully applied for the direct analysis of histamine in white wine providing detection limit much lower than the histamine maximum levels established by EU regulation in food samples. The recovery rate was excellent, ranging from 84 to 100% with an RSD of less than 4.0%. The main advantage of the proposed method is full automation of the analytical procedure that reduces the time and cost of the analysis, solvent consumption and sample manipulation, enabling routine analysis of large numbers of samples for histamine and highly accurate and precise results.
- MeSH
- Fluorescence MeSH
- Fluorescent Dyes chemistry MeSH
- Spectrometry, Fluorescence methods MeSH
- Histamine analysis MeSH
- Food Contamination analysis MeSH
- Metal Nanoparticles chemistry MeSH
- Quantum Dots chemistry MeSH
- Limit of Detection MeSH
- Magnetic Phenomena MeSH
- Silanes chemistry MeSH
- Cadmium Compounds chemistry MeSH
- Tellurium chemistry MeSH
- Titanium chemistry MeSH
- Wine analysis MeSH
- Ferric Compounds chemistry MeSH
- Publication type
- Journal Article MeSH
Cíl. Zjistit přesnost aplikace CAD v detekci periferní plicní embolizace při CTA plicnice a zhodnotit možný přínos pro mladého radiologa. Materiál a metoda. Zkoumaný soubor obsahoval 18 pacientů (9 žen) s pozitivním nálezem a 18 pacientů s negativním nálezem při CTA plicnice. Celkový počet embolů u těchto pacientů byl 78 (41 v segmentární a 37 v subsegmentární úrovni; 4,3 embolu na pacienta). Všech 36 vyšetření bylo analyzováno aplikací CAD (PE-CAD, Siemens Medical Solutions, Německo). Dále byl stejný soubor analyzován mladým radiologem (30 měsíců praxe), který nejdříve vyhodnotil vyšetření samostatně a poté výsledky porovnal s analýzou provedenou aplikací CAD. Pro kontrolu byl soubor zhodnocen samostatně ještě zkušeným radiologem. Výsledky. Aplikace CAD správně detekovala 44 embolů (57 %), průměrný počet falešně pozitivních nálezů na pacienta byl 3,1 (celkem 112). Analýza výsledků podle jednotlivých embolů prokázala celkovou (segmentární + subsegmentární) senzitivitu aplikace CAD 56 % (segmentární - 73 %, subsegmentární 38 %) a pozitivní prediktivní hodnotu (PPV) 42 %. Celková senzitivita mladého radiologa se po porovnání výsledků zvýšila z 83 % na 87 % (segmentární - z 95 % na 97 % + subsegmentární - z 70 % na 75 %). Senzitivita zkušeného radiologa dosáhla 92 % (segmentární - 100 %; subsegmentární 94 %). V analýze podle pacienta (alespoň 1 správně pozitivní embolus) dosáhla aplikace CAD senzitivity 83 % a negativní prediktivní hodnoty (NPV) 79 %. Závěr. Naše práce i výsledky ostatních studií prokazují potenciál systému automatické detekce zlepšit úspěšnost mladého radiologa v detekci periferní plicní embolizace při CTA plicnice; je tedy využitelný pro tzv. "druhé čtení".
Aim. Of our study was to evaluate the accuracy of CAD tool for automated detection of segmental and sub-segmental pulmonary embolism and the capability of this sofware to help junior radiologist in evaluation of CT pulmonary angiography (CTPA). Method. We selected 18 patients (9 women aged 17-79 years, men aged 58 years) from our set of CTPA´s with total of 78 emboli (41 segmental/37 subsegmental; 4.33 emboli per patient). As a control group we randomly picked 18 patients with negative CTPA. All 36 examinations were analysed by CAD tool (PE-CAD, Siemens Medical Solutions, Germany), by junior radiologist (2.5 years experience with CT) alone and in consensus with the CAD tool and finally by senior radiologist (14 years experience with CT). The findings of head senior radiologist (15 years practice of thorax CT) were considered as reference for presence of all of emboli. Results. CAD correctly detected 44 emboli (30 segmental, 14 subsegmental), the average false positive rate of the CAD was 3.1 per examination (overall 112). As for the analysis of segments, the overall (segmental + subsegmental) sensitivity of the CAD was 56.4% (segmental = 73.2%; subsegmental = 37.8%) and the positive predictive value (PPV) was 42.3%. Junior radiologist profited by the consensus with the CAD, their overall sensitivity increased from 83.3% to 87.2% (segmental - from 95.1% to 97.2%; subsegmental ? from 70.2 to 75.2%) and the PPV from 93.2% to 95.6%. Senior radiologist achieved the overall sensitivity of 92.3% (segmental = 100%; subsegmental = 94.1%) and PPV of 96.1%. As for the analyses of patients, the sensitivity of CAD was 83.3% and the negative predictive value (NPV) was 78.6%, the sensitivity of junior radiologist in consensus with the CAD was 94.5% and the NPV was 93.8%, the sensitivity and NPV of senior radiologist were 100%. Conclusion. Our own results show the capability of the CAD tool to improve performance of junior radiologist in detecting of segmental and subsegmental pulmonary embolism at CTPA. CAD is feasible as a "second reader" in the evaluation of CTPA, but low sensitivity in detecting subsegmental embolism and high false positive rate demand further improvement.
- MeSH
- Angiography methods instrumentation utilization MeSH
- Diagnostic Errors statistics & numerical data MeSH
- Diagnosis, Computer-Assisted methods instrumentation utilization MeSH
- Financing, Organized MeSH
- Data Interpretation, Statistical MeSH
- Pulmonary Embolism diagnosis MeSH
- Tomography, X-Ray Computed methods utilization MeSH
- Software standards trends MeSH
- Tomography, Spiral Computed methods instrumentation utilization MeSH
Equipment for fast and accurate detection of organophosphate nerve agents is developed and tested. The method is based on the spectrophotometric monitoring of the enzyme activity of butyrylcholinesterase after its contact with air in a special absorption unit (a “scrubber”) developed for the purpose. The scrubber was made from a glass tube filled with glass beads (diam. 3 mm) and filled with approx. 5 ml of butyrylcholinesterase in a phosphate buffer of pH 7.4. The air sample was bubbled through this solution for 20 s at a flow rate of 80 l hour-1. Thereafter 8 microl of the enzyme solution were aspirated into the micro-SIA-LOV analyzer and the activity of the enzymes were evaluated by using Ellman’s reagent, i.e. 2.5 mmol l-1 butyrylthiocholine iodide and 0.25 mmol 5,5’-dithiobis (2-nitrobenzoic acid). The absorbance of the coloured reaction product was measured at 412 nm after the reaction time of 60 s. The residue of the absorption liquid was washed away from the absorber and the system was washed with the enzyme solution prior to next analysis. The contaminated air caused partial inhibition of the enzyme activity of the absorption liquid. The activity of the contaminated sample was compared with the activity of the unaffected enzyme (blank measurement). The analysis was controlled by two PCs. The effect of the concentration of analyte in the absorption liquid on the enzyme activity was tested for 10-5-10-9 mol l-1 sarin. A single analysis (including the absorption step) took <130 s.
- MeSH
- Butyrylcholinesterase MeSH
- Chemical Warfare Agents MeSH
- Cholinesterase Inhibitors analysis MeSH
- Equipment Design MeSH
- Automation, Laboratory instrumentation MeSH
- Organophosphorus Compounds analysis MeSH
- Flow Injection Analysis * methods instrumentation statistics & numerical data MeSH
- Sarin * analysis MeSH
- Sequence Analysis methods MeSH
- Spectrophotometry methods MeSH
- Equipment and Supplies MeSH
- Air Pollution * analysis statistics & numerical data MeSH
- Publication type
- Evaluation Study MeSH
- Research Support, Non-U.S. Gov't MeSH
The objective of this clinical practice guideline (CPG) is to provide recommendations for healthcare personnel working with patients with epilepsy on the use of wearable devices for automated seizure detection in patients with epilepsy, in outpatient, ambulatory settings. The Working Group of the International League Against Epilepsy (ILAE) and the International Federation of Clinical Neurophysiology (IFCN) developed the CPG according to the methodology proposed by the ILAE Epilepsy Guidelines Working Group. We reviewed the published evidence using The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement and evaluated the evidence and formulated the recommendations following the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. We found high level of evidence for the accuracy of automated detection of generalized tonic-clonic seizures (GTCS) and focal-to-bilateral tonic-clonic seizures (FBTCS) and recommend the use of wearable automated seizure detection devices for selected patients when accurate detection of GTCS and FBTCS is recommended as a clinical adjunct. We also found a moderate level of evidence for seizure types without GTCS or FBTCS. However, it was uncertain whether the detected alarms resulted in meaningful clinical outcomes for the patients. We recommend using clinically validated devices for automated detection of GTCS and FBTCS, especially in unsupervised patients, where alarms can result in rapid intervention (weak/conditional recommendation). At present, we do not recommend clinical use of the currently available devices for other seizure types (weak/conditional recommendation). Further research and development are needed to improve the performance of automated seizure detection and to document their accuracy and clinical utility.
- MeSH
- Monitoring, Ambulatory instrumentation methods standards MeSH
- Child MeSH
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Wearable Electronic Devices * standards MeSH
- Child, Preschool MeSH
- Aged MeSH
- Seizures diagnosis physiopathology MeSH
- Check Tag
- Child MeSH
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Child, Preschool MeSH
- Aged MeSH
- Publication type
- Journal Article MeSH
- Practice Guideline MeSH
The objective of this clinical practice guideline (CPG) is to provide recommendations for healthcare personnel working with patients with epilepsy, on the use of wearable devices for automated seizure detection in patients with epilepsy, in outpatient, ambulatory settings. The Working Group of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology developed the CPG according to the methodology proposed by the ILAE Epilepsy Guidelines Working Group. We reviewed the published evidence using The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement and evaluated the evidence and formulated the recommendations following the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. We found high level of evidence for the accuracy of automated detection of generalized tonic-clonic seizures (GTCS) and focal-to-bilateral tonic-clonic seizures (FBTCS) and recommend use of wearable automated seizure detection devices for selected patients when accurate detection of GTCS and FBTCS is recommended as a clinical adjunct. We also found moderate level of evidence for seizure types without GTCs or FBTCs. However, it was uncertain whether the detected alarms resulted in meaningful clinical outcomes for the patients. We recommend using clinically validated devices for automated detection of GTCS and FBTCS, especially in unsupervised patients, where alarms can result in rapid intervention (weak/conditional recommendation). At present, we do not recommend clinical use of the currently available devices for other seizure types (weak/conditional recommendation). Further research and development are needed to improve the performance of automated seizure detection and to document their accuracy and clinical utility.
- MeSH
- Epilepsy diagnosis MeSH
- Consensus Development Conferences as Topic MeSH
- Humans MeSH
- Neurophysiological Monitoring instrumentation methods standards MeSH
- Wearable Electronic Devices standards MeSH
- Practice Guidelines as Topic * MeSH
- Societies, Medical MeSH
- Seizures diagnosis MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
