Distance-based detection (DbD) on paper-based microfluidic analytical devices (μPADs) has emerged as a promising, cost-effective, simple, and instrumentation-free assay method. Broadening the applicability of a new way of immobilization of reagent for DbD on μPADs (DμPADs) is presented, employing an ion exchange (IE) interaction of an anionic metallochromic reagent, 2-(5-bromo-2-pyridylazo)-5-[N-n-propyl-N-(3-sulfopropyl)amino]phenol (5-Br-PAPS), on the anion-exchange filter paper. The IE DμPADs demonstrate superiority over standard cellulose filter paper in terms of the degree of reagent immobilization, detection sensitivity, and clear detection endpoints due to the strong retention of 5-Br-PAPS. The study investigated various parameters influencing DbD, including 5-Br-PAPS concentrations (0.25-1 mM), buffer types (acetic acid-Tris, MES), buffer concentrations (20-500 mM), and auxiliary complexing agents (acetic, formic, and glycolic acids). Subsequently, the performance of 17 metals (Ag+, Cd2+, Co2+, Cr3+, Cu2+, Fe2+, Hg2+, La2+, Mn2+, Ni2+, Pb2+, Ti2+, Zn2+, Al3+, As3+, Fe3+, and V4+) was evaluated, with color formation observed for 12 metals. Additionally, the paper surface was examined using SEM and SEM-EDX to verify the suitability of certain areas in the detection channel for reagent immobilization and metal binding. This method demonstrates quantitation limits of metals in the low μg mL-1 range, showing great potential for the rapid screening of toxic metals commonly found in herbal supplements and cosmetics regulated by the Food and Drug Administration (FDA). Thus, it holds promise for enhancing safety and regulatory compliance in product quality assessment. Furthermore, this method offers a cost-effective, environmentally sustainable, and user-friendly approach for the rapid visual quantification of heavy metals for in-field analysis, eliminating the need for complex instrumentation.
- Publication type
- Journal Article MeSH
This work presents an affordable distance-based microfluidic paper-based device (μPAD), using polydiacetylene (PDA) liposome as a chromogenic substance with a smartphone-based photo editor, for rapid and in-field analysis of quaternary ammonium compounds (QACs) (e.g., didecyldimethylammonium chloride (DDAC), benzyldimethyltetradecyl ammonium chloride (BAC), and cetylpyridinium chloride (CPC)). In-field analysis of these compounds is important to ensure their antimicrobial activity and user safety since they are widely utilized as disinfectants in households and hospitals. The μPAD featured a thermometer-like shape consisting of a sample reservoir and a microchannel as the detection zone, which was pre-deposited with PDA liposome. The color change from blue to red appeared in the presence of QACs and the color bar lengths were proportional to the QAC concentrations. Reactions of QACs with the PDA required a specific pH range (from pH 4.0 to 10.0) and a readout time of 7 min. Analytical performance characteristics of the device were tested with DDAC, BAC, and CPC showing acceptable specificity, accuracy (96.1-109.4%), and precision (%RSDs ≤ 9.3%). Limits of detection and quantitation were in the ranges of 20 to 80 and 70 to 250 μM, respectively. Feasibility of the newly developed device was demonstrated for in-field analysis of QACs in fumigation solution providing comparable results with those obtained from a colorimetric assay (P > 0.05). The proposed device shows potentials for further applications of other analytes since it offers speed, simplicity, and affordability for in-field analysis, especially in remote areas where expertise, resources, and infrastructures are limited. Graphical abstract.
- Publication type
- Journal Article MeSH
The purpose of this study is (1) to introduce a new approach for edge detection in orthopantograms (OPGs) and an improved automatic parameter selector for common edge detectors, (2) to present a comparison between our novel approach with common edge detectors and (3) to provide faster outputs without compromising quality. A new approach for edge detection based on statistical measures was introduced: (1) a set of N edge detection results is calculated from a given input image and a selected type of edge detector, (2) N correspondence maps are constructed from N edge detection results, (3) probabilities and average probabilities are computed, (4) an overall correspondence is evaluated for each correspondence map and (5) the correspondence map providing the best overall correspondence is taken as the result of edge detection procedure. A comparison with common edge detectors (the Roberts, Prewitt, Sobel, Laplacian of the Gaussian and Canny methods) with various parameter settings (304 combinations for each test image) was carried out. The methods were assessed objectively [edge mismatch error (EME), modified Hausdorff distance (MHD) and principal component analysis] and subjectively by experts in dentistry and based on time demands. The suitability of the new approach for edge detection in OPGs was confirmed by experts. The current conventional methods in edge detection in OPGs are inadequate (none of the tested methods reach an EME value or MHD value below 0.1). Our proposed approach for edge detection shows promising potential for its implementation in clinical dentistry. It enhances the accuracy of OPG interpretation and advances diagnosis and treatment planning.
- MeSH
- Algorithms MeSH
- Principal Component Analysis MeSH
- Anatomic Landmarks radiography MeSH
- Artifacts MeSH
- Time Factors MeSH
- Jaw Cysts radiography MeSH
- Tooth Extraction MeSH
- Humans MeSH
- Normal Distribution MeSH
- Image Processing, Computer-Assisted statistics & numerical data MeSH
- Probability MeSH
- Radiography, Panoramic statistics & numerical data MeSH
- Radiographic Image Interpretation, Computer-Assisted methods MeSH
- Dental Caries radiography MeSH
- Tooth, Supernumerary radiography MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Comparative Study MeSH
Herein, we describe an ultrasensitive specific biosensing system for detection of sarcosine as a potential biomarker of prostate carcinoma based on Förster resonance energy transfer (FRET). The FRET biosensor employs anti-sarcosine antibodies immobilized on paramagnetic nanoparticles surface for specific antigen binding. Successful binding of sarcosine leads to assembly of a sandwich construct composed of anti-sarcosine antibodies keeping the Förster distance (Ro) of FRET pair in required proximity. The detection is based on spectral overlap between gold-functionalized green fluorescent protein and antibodies@quantum dots bioconjugate (λex 400 nm). The saturation curve of sarcosine based on FRET efficiency (F₆₀₄/F₅₁₀ ratio) was tested within linear dynamic range from 5 to 50 nM with detection limit down to 50 pM. Assembled biosensor was then successfully employed for sarcosine quantification in prostatic cell lines (PC3, 22Rv1, PNT1A), and urinary samples of prostate adenocarcinoma patients.
- MeSH
- Dextrans chemistry ultrastructure MeSH
- Humans MeSH
- Magnetite Nanoparticles chemistry ultrastructure MeSH
- Molecular Imaging methods MeSH
- Antibodies, Monoclonal chemistry immunology MeSH
- Biomarkers, Tumor analysis MeSH
- Cell Line, Tumor MeSH
- Prostatic Neoplasms chemistry diagnosis immunology MeSH
- Nanocapsules chemistry ultrastructure MeSH
- Reproducibility of Results MeSH
- Fluorescence Resonance Energy Transfer methods MeSH
- Sarcosine analysis immunology MeSH
- Sensitivity and Specificity MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Until recently, three spirochete genospecies were considered to be the causative agents of Lyme borreliosis (LB) in Europe: Borrelia burgdorferi sensu stricto, Borrelia afzelii and Borrelia garinii. However, the DNA of Borrelia valaisiana, Borrelia lusitaniae, Borrelia spielmanii and Borrelia bissettii has already been detected in samples of human origin, or the spirochetes were isolated from the patients with symptoms of LB. Molecular analysis of 12 selected serum samples collected in the regional hospital confirmed the presence of B. bissettii DNA in cases of single and multiple infection in patients with symptomatic borreliosis or chronic borrelial infection. The presence of B. bissettii as a single strain in patients provides strong support of the fact that B. bissettii might be a causative agent of the disease. After the first isolation of B. bissettii from the samples of human origin in Slovenia, following the detection of this species in cardiac valve tissue of the patient with endocarditis and aortic valve stenosis in the Czech Republic, here we present additional molecular data supporting the involvement of B. bissettii in LB in Europe.
- MeSH
- RNA, Bacterial genetics MeSH
- Borrelia genetics isolation & purification MeSH
- DNA, Bacterial genetics chemistry blood MeSH
- Financing, Organized MeSH
- Phylogeny MeSH
- Genes, rRNA MeSH
- Borrelia Infections diagnosis MeSH
- Humans MeSH
- Molecular Sequence Data MeSH
- Polymerase Chain Reaction methods MeSH
- DNA, Ribosomal genetics chemistry MeSH
- RNA, Ribosomal, 16S genetics MeSH
- Sequence Analysis, DNA MeSH
- Sequence Homology, Nucleic Acid MeSH
- Serum microbiology MeSH
- Check Tag
- Humans MeSH
- Geographicals
- Czech Republic MeSH
BACKGROUND: Statistical analysis, which has become an integral part of evidence-based medicine, relies heavily on data quality that is of critical importance in modern clinical research. Input data are not only at risk of being falsified or fabricated, but also at risk of being mishandled by investigators. OBJECTIVE: The urgent need to assure the highest data quality possible has led to the implementation of various auditing strategies designed to monitor clinical trials and detect errors of different origin that frequently occur in the field. The objective of this study was to describe a machine learning-based algorithm to detect anomalous patterns in data created as a consequence of carelessness, systematic error, or intentionally by entering fabricated values. METHODS: A particular electronic data capture (EDC) system, which is used for data management in clinical registries, is presented including its architecture and data structure. This EDC system features an algorithm based on machine learning designed to detect anomalous patterns in quantitative data. The detection algorithm combines clustering with a series of 7 distance metrics that serve to determine the strength of an anomaly. For the detection process, the thresholds and combinations of the metrics were used and the detection performance was evaluated and validated in the experiments involving simulated anomalous data and real-world data. RESULTS: Five different clinical registries related to neuroscience were presented-all of them running in the given EDC system. Two of the registries were selected for the evaluation experiments and served also to validate the detection performance on an independent data set. The best performing combination of the distance metrics was that of Canberra, Manhattan, and Mahalanobis, whereas Cosine and Chebyshev metrics had been excluded from further analysis due to the lowest performance when used as single distance metric-based classifiers. CONCLUSIONS: The experimental results demonstrate that the algorithm is universal in nature, and as such may be implemented in other EDC systems, and is capable of anomalous data detection with a sensitivity exceeding 85%.
- Publication type
- Journal Article MeSH
Grapevine Syrah virus-1 (GSyV-1) was identified by small-RNA deep sequencing in Slovak grapevine co-infected by several other viruses. The RT-PCR assays developed in this work substantially improved the virus detection and allowed the identification of GSyV-1 in tested grapevine samples from Slovakia and the Czech Republic at an unexpectedly high rate (ca. 30 %). Subsequently, complete genome sequences of 3 GSyV-1 isolates (2 Slovak and 1 Czech) were determined by Sanger sequencing, showing a typical marafivirus genome organization. Analyses of complete genome sequences showed a higher intra-group diversity among these 3 central European GSyV-1 isolates (differences reaching 7.1 % at the nucleotide level) in comparison to 3 previously characterized North American isolates (only 1.2 % intra-group divergence). A substantially higher divergence among central European isolates and their clustering into two major phylogenetic groups was further confirmed by the partial genome analysis of additional 26 isolates. The CP-centered study did not support the geography-based clustering among central European and American isolates. Nevertheless, the sequence data of the highly variable 5'-proximal portion of the genome obtained for few additional isolates from Slovakia and Czech Republic showed the presence of both, "European-" and "north American-like", GSyV-1 isolates in the analyzed grapevine samples.
- MeSH
- Phylogeny MeSH
- Genetic Variation MeSH
- Genome, Viral * MeSH
- Molecular Sequence Data MeSH
- Gene Order MeSH
- RNA, Viral genetics MeSH
- Sequence Analysis, DNA * MeSH
- Sequence Homology, Nucleic Acid MeSH
- Cluster Analysis MeSH
- Tymoviridae classification genetics isolation & purification MeSH
- Vitis virology MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Czech Republic MeSH
- Slovakia MeSH
BACKGROUND: FLASH radiotherapy necessitates the development of advanced Quality Assurance methods and detectors for accurate monitoring of the radiation field. This study introduces enhanced time-resolution detection systems and methods used to measure the delivered number of pulses, investigate temporal structure of individual pulses and dose-per-pulse (DPP) based on secondary radiation particles produced in the experimental room. METHODS: A 20 MeV electron beam generated from a linear accelerator (LINAC) was delivered to a water phantom. Ultra-high dose-per-pulse electron beams were used with a dose-per-pulse ranging from ̴ 1 Gy to over 7 Gy. The pulse lengths ranged from 1.18 μs to 2.88 μs at a pulse rate frequency of 5 Hz. A semiconductor pixel detector Timepix3 was used to track single secondary particles. Measurements were performed in the air, while the detector was positioned out-of-field at a lateral distance of 200 cm parallel with the LINAC exit window. The dose deposited was measured along with the pulse length and the nanostructure of the pulse. RESULTS: The time of arrival (ToA) of single particles was measured with a resolution of 1.56 ns, while the deposited energy was measured with a resolution of several keV based on the Time over Threshold (ToT) value. The pulse count measured by the Timepix3 detector corresponded with the delivered values, which were measured using an in-flange integrating current transformer (ICT). A linear response (R2 = 0.999) was established between the delivered beam current and the measured dose at the detector position (orders of nGy). The difference between the average measured and delivered pulse length was ∼0.003(30) μs. CONCLUSION: This simple non-invasive method exhibits no limitations on the delivered DPP within the range used during this investigation.
Objective. The aim of this study was to investigate the feasibility of online monitoring of irradiation time (IRT) and scan time for FLASH proton radiotherapy using a pixelated semiconductor detector.Approach. Measurements of the time structure of FLASH irradiations were performed using fast, pixelated spectral detectors based on the Timepix3 (TPX3) chips with two architectures: AdvaPIX-TPX3 and Minipix-TPX3. The latter has a fraction of its sensor coated with a material to increase sensitivity to neutrons. With little or no dead time and an ability to resolve events that are closely spaced in time (tens of nanoseconds), both detectors can accurately determine IRTs as long as pulse pile-up is avoided. To avoid pulse pile-up, the detectors were placed well beyond the Bragg peak or at a large scattering angle. Prompt gamma rays and secondary neutrons were registered in the detectors' sensors and IRTs were calculated based on timestamps of the first charge carriers (beam-on) and the last charge carriers (beam-off). In addition, scan times inx,y, and diagonal directions were measured. The experiment was carried out for various setups: (i) a single spot, (ii) a small animal field, (iii) a patient field, and (iv) an experiment using an anthropomorphic phantom to demonstratein vivoonline monitoring of IRT. All measurements were compared to vendor log files.Main results. Differences between measurements and log files for a single spot, a small animal field, and a patient field were within 1%, 0.3% and 1%, respectively.In vivomonitoring of IRTs (95-270 ms) was accurate within 0.1% for AdvaPIX-TPX3 and within 6.1% for Minipix-TPX3. The scan times inx,y, and diagonal directions were 4.0, 3.4, and 4.0 ms, respectively.Significance. Overall, the AdvaPIX-TPX3 can measure FLASH IRTs within 1% accuracy, indicating that prompt gamma rays are a good surrogate for primary protons. The Minipix-TPX3 showed a somewhat higher discrepancy, likely due to the late arrival of thermal neutrons to the detector sensor and lower readout speed. The scan times (3.4 ± 0.05 ms) in the 60 mm distance ofy-direction were slightly less than (4.0 ± 0.06 ms) in the 24 mm distance ofx-direction, confirming the much faster scanning speed of the Y magnets than that of X. Diagonal scan speed was limited by the slower X magnets.
- MeSH
- Neutrons MeSH
- Proton Therapy * methods MeSH
- Protons MeSH
- Radiometry * methods MeSH
- Gamma Rays MeSH
- Publication type
- Journal Article MeSH
A set of 204 taxonomically well-defined strains belonging to 17 Acinetobacter spp., including 11 recently described species (A. albensis, A. bohemicus, A. colistiniresistens, A. courvalinii. A. dispersus, A. gandensis, A. modestus, A. proteolyticus, A. seifertii, A. variabilis, and A. vivianii) and six species of the so-called haemolytic clade (A. beijerinckii, A. gyllenbergii, A. haemolyticus, A. junii, A. parvus, and A. venetianus), were subjected to MALDI-TOF mass spectrometric profiling. The identification outputs were evaluated using the current version (8.0.0.0) of the commercially available Bruker Daltonics, Biotyper database, which does not contain reference entries for six of the species tested. Up to 29% of the strains were falsely identified as different Acinetobacter spp. present in the Biotyper database, resulting mostly from the close phylogenetic relationship of species of the haemolytic clade. To obtain more reliable identification, extending the commercial database showed only partial improvement, while the use of an alternative MALDI matrix solution (strongly acidified ferulic acid) allowed correct identification of nearly all problematic strains.
- MeSH
- Acinetobacter classification genetics isolation & purification MeSH
- Genes, Bacterial MeSH
- Databases, Genetic MeSH
- Phylogeny MeSH
- Acinetobacter Infections diagnosis microbiology MeSH
- Limit of Detection * MeSH
- RNA, Ribosomal, 16S genetics MeSH
- Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization instrumentation methods MeSH
- Bacterial Typing Techniques instrumentation methods MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
