"LO1212"
Dotaz
Zobrazit nápovědu
The search for the "Holy Grail" in clinical diagnostic microbiology-a reliable, accurate, low-cost, real-time, easy-to-use method-has brought up several methods with the potential to meet these criteria. One is Raman spectroscopy, an optical, nondestructive method based on the inelastic scattering of monochromatic light. The current study focuses on the possible use of Raman spectroscopy for identifying microbes causing severe, often life-threatening bloodstream infections. We included 305 microbial strains of 28 species acting as causative agents of bloodstream infections. Raman spectroscopy identified the strains from grown colonies, with 2.8% and 7% incorrectly identified strains using the support vector machine algorithm based on centered and uncentred principal-component analyses, respectively. We combined Raman spectroscopy with optical tweezers to speed up the process and captured and analyzed microbes directly from spiked human serum. The pilot study suggests that it is possible to capture individual microbial cells from human serum and characterize them by Raman spectroscopy with notable differences among different species. IMPORTANCE Bloodstream infections are among the most common causes of hospitalizations and are often life-threatening. To establish an effective therapy for a patient, the timely identification of the causative agent and characterization of its antimicrobial susceptibility and resistance profiles are essential. Therefore, our multidisciplinary team of microbiologists and physicists presents a method that reliably, rapidly, and inexpensively identifies pathogens causing bloodstream infections-Raman spectroscopy. We believe that it might become a valuable diagnostic tool in the future. Combined with optical trapping, it offers a new approach where the microorganisms are individually trapped in a noncontact way by optical tweezers and investigated by Raman spectroscopy directly in a liquid sample. Together with the automatic processing of measured Raman spectra and comparison with a database of microorganisms, it makes the whole identification process almost real time.
- MeSH
- algoritmy MeSH
- lidé MeSH
- optická pinzeta MeSH
- pilotní projekty MeSH
- Ramanova spektroskopie * metody MeSH
- sepse * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
OBJECTIVES: Chemical Shift Encoded Magnetic Resonance Imaging (CSE-MRI)-based quantification of low-level (< 5% of proton density fat fraction-PDFF) fat infiltration requires highly accurate data reconstruction for the assessment of hepatic or pancreatic fat accumulation in diagnostics and biomedical research. MATERIALS AND METHODS: We compare three software tools available for water/fat image reconstruction and PDFF quantification with MRS as the reference method. Based on the algorithm exploited in the tested software, the accuracy of fat fraction quantification varies. We evaluate them in phantom and in vivo MRS and MRI measurements. RESULTS: The signal model of Intralipid 20% emulsion used for phantoms was established for 3 T and 9.4 T fields. In all cases, we noticed a high coefficient of determination (R-squared) between MRS and MRI-PDFF measurements: in phantoms <0.9924-0.9990>; and in vivo <0.8069-0.9552>. Bland-Altman analysis was applied to phantom and in vivo measurements. DISCUSSION: Multi-echo MRI in combination with an advanced algorithm including multi-peak spectrum modeling appears as a valuable and accurate method for low-level PDFF quantification over large FOV in high resolution, and is much faster than MRS methods. The graph-cut algorithm (GC) showed the fewest water/fat swaps in the PDFF maps, and hence stands out as the most robust method of those tested.
- MeSH
- algoritmy MeSH
- dospělí MeSH
- emulze MeSH
- fantomy radiodiagnostické MeSH
- játra diagnostické zobrazování MeSH
- lidé MeSH
- magnetická rezonanční spektroskopie metody MeSH
- počítačové zpracování obrazu metody MeSH
- software MeSH
- tuková tkáň diagnostické zobrazování MeSH
- voda MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- srovnávací studie MeSH
Manual and semi-automatic identification of artifacts and unwanted physiological signals in large intracerebral electroencephalographic (iEEG) recordings is time consuming and inaccurate. To date, unsupervised methods to accurately detect iEEG artifacts are not available. This study introduces a novel machine-learning approach for detection of artifacts in iEEG signals in clinically controlled conditions using convolutional neural networks (CNN) and benchmarks the method's performance against expert annotations. The method was trained and tested on data obtained from St Anne's University Hospital (Brno, Czech Republic) and validated on data from Mayo Clinic (Rochester, Minnesota, U.S.A). We show that the proposed technique can be used as a generalized model for iEEG artifact detection. Moreover, a transfer learning process might be used for retraining of the generalized version to form a data-specific model. The generalized model can be efficiently retrained for use with different EEG acquisition systems and noise environments. The generalized and specialized model F1 scores on the testing dataset were 0.81 and 0.96, respectively. The CNN model provides faster, more objective, and more reproducible iEEG artifact detection compared to manual approaches.
Representatives of Apicomplexa perform various kinds of movements that are linked to the different stages of their life cycle. Ancestral apicomplexan lineages, including gregarines, represent organisms suitable for research into the evolution and diversification of motility within the group. The vermiform trophozoites and gamonts of the archigregarine Selenidium pygospionis perform a very active type of bending motility. Experimental assays and subsequent light, electron, and confocal microscopic analyses demonstrated the fundamental role of the cytoskeletal proteins actin and tubulin in S. pygospionis motility and allowed us to compare the mechanism of its movement to the gliding machinery (the so-called glideosome concept) described in apicomplexan zoites. Actin-modifying drugs caused a reduction in the movement speed (cytochalasin D) or stopped the motility of archigregarines completely (jasplakinolide). Microtubule-disrupting drugs (oryzalin and colchicine) had an even more noticeable effect on archigregarine motility. The fading and disappearance of microtubules were documented in ultrathin sections, along with the formation of α-tubulin clusters visible after the immunofluorescent labelling of drug-treated archigregarines. The obtained data indicate that subpellicular microtubules most likely constitute the main motor structure involved in S. pygospionis bending motility, while actin has rather a supportive function.
- MeSH
- aktiny metabolismus MeSH
- Apicomplexa růst a vývoj fyziologie ultrastruktura MeSH
- cytoskelet metabolismus ultrastruktura MeSH
- mikrotubuly metabolismus MeSH
- paraziti MeSH
- protozoální proteiny metabolismus MeSH
- tomografie elektronová MeSH
- trofozoiti růst a vývoj metabolismus ultrastruktura MeSH
- tubulin metabolismus MeSH
- zvířata MeSH
- Check Tag
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
