Automatic phenotyping
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Syndrom geriatrické křehkosti značí fyzickou zranitelnost pacienta, náchylnost k řadě chorob i komplikací. Je jedním ze stěžejních geriatrických syndromů, které mají nízký výskyt u osob středního věku a narůstají ve stáří. V České republice jsou zavedená kritéria křehkosti podle Friedové, kde je však nevýhodou semikvantitativní výsledná hodnota. V tomto sdělení přinášíme překlad dotazníku Frailty Index podle Rockwooda spolu s odkazy na automatické zhodnocení. Výsledkem je kvantitativní škála od 0 do 1 vyjadřující závažnost geriatrické křehkosti, tzv. Frailty Index. Tento nástroj může být výhodný pro výzkumné týmy, kde kvantitativní povaha stanovené veličiny poskytne lepší statistické vyhodnocení získaných výsledků než veličina semikvantitativní.
The geriatric frailty syndrome refers to the physical vulnerability of the patient, susceptibility to a wide range of diseases and complications. It is one of the key geriatric syndromes, which have a low incidence in middle-aged people and increases with aging. In the Czech Republic, the Fried Frailty Phenotype criteria have been established. However, its semi-quantitative nature of the resulting value can be a disadvantage. In this communication, we present a translation of the Frailty Index questionnaire according to Rockwood along with hyperlinks to automatic evaluation. The result is a quantitative scale from 0 to 1, expressing the severity of geriatric frailty. This approach may be advantageous for research purposes, as the quantitative nature of the determined value provides better statistical evaluation of the results than semi-quantitative scores.
- Klíčová slova
- Frailty Index,
- MeSH
- křehkost * diagnóza MeSH
- lidé MeSH
- senioři MeSH
- ukazatele zdravotního stavu MeSH
- Check Tag
- lidé MeSH
- senioři MeSH
- Publikační typ
- práce podpořená grantem MeSH
Flow cytometry immunophenotyping is critical for the diagnostic classification of mature/peripheral B-cell neoplasms/B-cell chronic lymphoproliferative disorders (B-CLPD). Quantitative driven classification approaches applied to multiparameter flow cytometry immunophenotypic data can be used to extract maximum information from a multidimensional space created by individual parameters (e.g., immunophenotypic markers), for highly accurate and automated classification of individual patient (sample) data. Here, we developed and compared five diagnostic classification algorithms, based on a large set of EuroFlow multicentric flow cytometry data files from a cohort 659 B-CLPD patients. These included automatic population separators based on Principal Component Analysis (PCA), Canonical Variate Analysis (CVA), Neighbourhood Component Analysis (NCA), Support Vector Machine algorithms (SVM) and a variant of the CA(Canonical Analysis) algorithm, in which the number of SDs (Standard Deviations) varied for each of the comparisons of different pairs of diseases (CA-vSD). All five classification approaches are based on direct prospective interrogation of individual B-CLPD patients against the EuroFlow flow cytometry B-CLPD database composed of tumor B-cells of 659 individual patients stained in an identical way and classified a priori by the World Health Organization (WHO) criteria into nine diagnostic categories. Each classification approach was evaluated in parallel in terms of accuracy (% properly classified cases), precision (multiple or single diagnosis/case) and coverage (% cases with a proposed diagnosis). Overall, average rates of correct diagnosis (for the nine B-CLPD diagnostic entities) of between 58.9 % and 90.6 % were obtained with the five algorithms, with variable percentages of cases being either misclassified (4.1 %-14.0 %) or unclassifiable (0.3 %-37.0 %). Automatic population separators based on CA, SVM and PCA showed a high average level of correctness (90.6 %, 86.8 %, and 86.0 %, respectively). Nevertheless, this was at the expense of proposing a considerable number of multiple diagnoses for a significant proportion of the test cases (54.5 %, 53.5 %, and 49.6 %, respectively). The CA-vSD algorithm generated the smaller average misclassification rate (4.1 %), but with 37.0 % of cases for which no diagnosis was proposed. In contrast, the NCA algorithm left only 2.7 % of cases without an associated diagnosis but misclassified 14.0 %. Among correctly classified cases (83.3 % of total), 91.2 % had a single proposed diagnosis, 8.6 % had two possible diagnoses, and 0.2 % had three. We demonstrate that the proposed AI algorithms provide an acceptable level of accuracy for the diagnostic classification of B-CLPD patients and, in general, surpass other algorithms reported in the literature.
- MeSH
- algoritmy MeSH
- B-lymfocyty * patologie MeSH
- imunofenotypizace * metody MeSH
- lidé středního věku MeSH
- lidé MeSH
- lymfoproliferativní nemoci * diagnóza klasifikace MeSH
- průtoková cytometrie * metody MeSH
- senioři MeSH
- support vector machine MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- srovnávací studie MeSH
BACKGROUND: The prognostic significance of mast cells and different phenotypes of macrophages in the microenvironment of hepatocellular carcinoma (HCC) following resection is unclear. We aimed in this study to assess the local distribution of infiltrating macrophages and mast cells of specific phenotypes in tissues of HCC and to evaluate their prognostic values for survival of post-surgical patients. METHODS: The clinicopathological and follow-up data of 70 patients with HCC, who underwent curative resection of tumor from 1997 to 2019, were collected. The infiltration of CD68+ and CD163+ macrophages and CD117+ mast cells was assessed immunohistochemically in representative resected specimens of HCC and adjacent tissues. The area fraction (AF) of positively stained cells was estimated automatically using QuPath image analysis software in several regions, such as tumor center (TC), inner margin (IM), outer margin (OM), and peritumor (PT) area. The prognostic significance of immune cells, individually and in associations, for time to recurrence (TTR), disease-free survival (DFS), and overall survival (OS) was evaluated using Kaplan-Meier and Cox regression analyses. RESULTS: High AF of CD68+ macrophages in TC and IM and high AF of mast cells in IM and PT area were associated with a longer DFS. High AF of CD163+ macrophages in PT area correlated with a shorter DFS. Patients from CD163TChigh & CD68TClow group had a shorter DFS compared to all the rest of the groups, and cases with CD163IMlow & CD68IMhigh demonstrated significantly longer DFS compared to low AF of both markers. Patients from CD68IMhigh & CD163PTlow group, CD117IMhigh & CD163PTlow group, and CD117PThigh & CD163PTlow group had a significantly longer DFS compared to all other combinations of respective cells. CONCLUSIONS: The individual prognostic impact of CD68+ and CD163+ macrophages and mast cells in the microenvironment of HCC after resection depends on their abundance and location, whereas the cumulative impact is built upon combination of different cell phenotypes within and between regions.
The diagnosis of solid tumors of epithelial origin (carcinomas) represents a major part of the workload in clinical histopathology. Carcinomas consist of malignant epithelial cells arranged in more or less cohesive clusters of variable size and shape, together with stromal cells, extracellular matrix, and blood vessels. Distinguishing stroma from epithelium is a critical component of artificial intelligence (AI) methods developed to detect and analyze carcinomas. In this paper, we propose a novel automated workflow that enables large-scale guidance of AI methods to identify the epithelial component. The workflow is based on re-staining existing hematoxylin and eosin (H&E) formalin-fixed paraffin-embedded sections by immunohistochemistry for cytokeratins, cytoskeletal components specific to epithelial cells. Compared to existing methods, clinically available H&E sections are reused and no additional material, such as consecutive slides, is needed. We developed a simple and reliable method for automatic alignment to generate masks denoting cytokeratin-rich regions, using cell nuclei positions that are visible in both the original and the re-stained slide. The registration method has been compared to state-of-the-art methods for alignment of consecutive slides and shows that, despite being simpler, it provides similar accuracy and is more robust. We also demonstrate how the automatically generated masks can be used to train modern AI image segmentation based on U-Net, resulting in reliable detection of epithelial regions in previously unseen H&E slides. Through training on real-world material available in clinical laboratories, this approach therefore has widespread applications toward achieving AI-assisted tumor assessment directly from scanned H&E sections. In addition, the re-staining method will facilitate additional automated quantitative studies of tumor cell and stromal cell phenotypes.
- MeSH
- barvení a značení MeSH
- deep learning * MeSH
- eosin MeSH
- epitelové buňky MeSH
- hematoxylin MeSH
- keratiny * MeSH
- lidé MeSH
- umělá inteligence MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
The complex shape of embryonic cartilage represents a true challenge for phenotyping and basic understanding of skeletal development. X-ray computed microtomography (μCT) enables inspecting relevant tissues in all three dimensions; however, most 3D models are still created by manual segmentation, which is a time-consuming and tedious task. In this work, we utilised a convolutional neural network (CNN) to automatically segment the most complex cartilaginous system represented by the developing nasal capsule. The main challenges of this task stem from the large size of the image data (over a thousand pixels in each dimension) and a relatively small training database, including genetically modified mouse embryos, where the phenotype of the analysed structures differs from the norm. We propose a CNN-based segmentation model optimised for the large image size that we trained using a unique manually annotated database. The segmentation model was able to segment the cartilaginous nasal capsule with a median accuracy of 84.44% (Dice coefficient). The time necessary for segmentation of new samples shortened from approximately 8 h needed for manual segmentation to mere 130 s per sample. This will greatly accelerate the throughput of μCT analysis of cartilaginous skeletal elements in animal models of developmental diseases.
Precise classification of acute leukemia (AL) is crucial for adequate treatment. EuroFlow has previously designed an AL orientation tube (ALOT) to guide toward the relevant classification panel and final diagnosis. In this study, we designed and validated an algorithm for automated (database-supported) gating and identification (AGI tool) of cell subsets within samples stained with ALOT. A reference database of normal peripheral blood (PB, n = 41) and bone marrow (BM; n = 45) samples analyzed with the ALOT was constructed, and served as a reference for the AGI tool to automatically identify normal cells. Populations not unequivocally identified as normal cells were labeled as checks and were classified by an expert. Additional normal BM (n = 25) and PB (n = 43) and leukemic samples (n = 109), analyzed in parallel by experts and the AGI tool, were used to evaluate the AGI tool. Analysis of normal PB and BM samples showed low percentages of checks (<3% in PB, <10% in BM), with variations between different laboratories. Manual analysis and AGI analysis of normal and leukemic samples showed high levels of correlation between cell numbers (r2 > 0.95 for all cell types in PB and r2 > 0.75 in BM) and resulted in highly concordant classification of leukemic cells by our previously published automated database-guided expert-supervised orientation tool for immunophenotypic diagnosis and classification of acute leukemia (Compass tool). Similar data were obtained using alternative, commercially available tubes, confirming the robustness of the developed tools. The AGI tool represents an innovative step in minimizing human intervention and requirements in expertise, toward a "sample-in and result-out" approach which may result in more objective and reproducible data analysis and diagnostics. The AGI tool may improve quality of immunophenotyping in individual laboratories, since high percentages of checks in normal samples are an alert on the quality of the internal procedures.
- MeSH
- akutní myeloidní leukemie diagnóza MeSH
- algoritmy * MeSH
- imunofenotypizace metody MeSH
- leukocyty patologie MeSH
- lidé MeSH
- průtoková cytometrie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
OBJECTIVE: Disturbed sleep is common in epilepsy. The direct influence of nocturnal epileptic activity on sleep fragmentation remains poorly understood. Stereo-electroencephalography paired with polysomnography is the ideal tool to study this relationship. We investigated whether sleep-related epileptic activity is associated with sleep disruption. METHODS: We visually marked sleep stages, arousals, seizures, and epileptic bursts in 36 patients with focal drug-resistant epilepsy who underwent combined stereo-electroencephalography/polysomnography during presurgical evaluation. Epileptic spikes were detected automatically. Spike and burst indices (n/sec/channel) were computed across four 3-second time windows (baseline sleep, pre-arousal, arousal, and post-arousal). Sleep stage and anatomic localization were tested as modulating factors. We assessed the intra-arousal dynamics of spikes and their relationship with the slow wave component of non-rapid eye-movement sleep (NR) arousals. RESULTS: The vast majority of sleep-related seizures (82.4%; 76.5% asymptomatic) were followed by awakenings or arousals. The epileptic burst index increased significantly before arousals as compared to baseline and postarousal, irrespective of sleep stage or brain area. A similar pre-arousal increase was observed for the spike index in NR stage 2 and rapid eye-movement sleep. In addition, the spike index increased during the arousal itself in neocortical channels, and was strongly correlated with the slow wave component of NR arousals (r = 0.99, p < 0.0001). INTERPRETATION: Sleep fragmentation in focal drug-resistant epilepsy is associated with ictal and interictal epileptic activity. The increase in interictal epileptic activity before arousals suggests its participation in sleep disruption. An additional increase in the spike rate during arousals may result from a sleep-wake boundary instability, suggesting a bidirectional relationship. ANN NEUROL 2020;88:907-920.
- MeSH
- arousal MeSH
- dospělí MeSH
- elektroencefalografie MeSH
- epilepsie komplikace MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladý dospělý MeSH
- polysomnografie MeSH
- poruchy spánku a bdění etiologie MeSH
- refrakterní epilepsie MeSH
- spánek pomalých vln MeSH
- spánková deprivace etiologie MeSH
- stadia spánku MeSH
- záchvaty komplikace MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Gap junctional intercellular communication (GJIC) is a vital cellular process required for maintenance of tissue homeostasis. In vitro assessment of GJIC represents valuable phenotypic endpoint that could be effectively utilized as an integral component in modern toxicity testing, drug screening or biomedical in vitro research. However, currently available methods for quantifying GJIC with higher-throughputs typically require specialized equipment, proprietary software and/or genetically engineered cell models. To overcome these limitations, we present here an innovative adaptation of traditional, fluorescence microscopy-based scrape loading-dye transfer (SL-DT) assay, which has been optimized to simultaneously evaluate GJIC, cell density and viability. This multiparametric method was demonstrated to be suitable for various multiwell microplate formats, which facilitates an automatized image acquisition. The assay workflow is further assisted by an open source-based software tools for batch image processing, analysis and evaluation of GJIC, cell density and viability. Our results suggest that this approach provides a simple, fast, versatile and cost effective way for in vitro high-throughput assessment of GJIC and other related phenotypic cellular events, which could be included into in vitro screening and assessment of pharmacologically and toxicologically relevant compounds.
- MeSH
- fluorescenční mikroskopie metody MeSH
- krysa rodu rattus MeSH
- kultivované buňky MeSH
- mezerový spoj * MeSH
- mezibuněčná komunikace * MeSH
- molekulární zobrazování metody MeSH
- počet buněk * MeSH
- počítačové zpracování obrazu metody MeSH
- viabilita buněk * MeSH
- zvířata MeSH
- Check Tag
- krysa rodu rattus MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Calcium ions act like ubiquitous second messengers in a wide amount of cellular processes. In cardiac myocytes, Ca2+ handling regulates the mechanical contraction necessary to the heart pump function. The field of intracellular and intercellular Ca2+ handling, employing in vitro models of cardiomyocytes, has become a cornerstone to understand the role and adaptation of calcium signalling in healthy and diseased hearts. Comprehensive in vitro systems and cell-based biosensors are powerful tools to enrich and speed up cardiac phenotypic and drug response evaluation. We have implemented a combined setup to measure contractility and calcium waves in human embryonic stem cells-derived cardiomyocyte 3D clusters, obtained from embryoid body differentiation. A combination of atomic force microscopy to monitor cardiac contractility, and sensitive fast scientific complementary metal-oxide-semiconductor camera for epifluorescence video recording, provided correlated signals in real time. To speed up the integrated data processing, we tested several post-processing algorithms, to improve the automatic detection of relevant functional parameters. The validation of our proposed method was assessed by caffeine stimulation (10mM) and detection/characterization of the induced cardiac response. We successfully report the first simultaneous recording of cardiac contractility and calcium waves on the described cardiac 3D models. The drug stimulation confirmed the automatic detection capabilities of the used algorithms, measuring expected physiological response, such as elongation of contraction time and Ca2+ cytosolic persistence, increased calcium basal fluorescence, and transient peaks. These results contribute to the implementation of novel, integrated, high-information, and reliable experimental systems for cardiac models and drug evaluation.
- MeSH
- biofyzika metody MeSH
- kardiomyocyty metabolismus MeSH
- lidé MeSH
- vápník metabolismus MeSH
- vápníková signalizace fyziologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Taxonomic identifications in some groups of lichen-forming fungi have been challenge largely due to the scarcity of taxonomically relevant features and limitations of morphological and chemical characters traditionally used to distinguish closely related taxa. Delineating species boundaries in closely related species or species complexes often requires a range of multisource data sets and comprehensive analytical methods. Here we aim to examine species boundaries in a group of saxicolous lichen forming fungi, the Aspiciliella intermutans complex (Megasporaceae), widespread mainly in the Mediterranean. We gathered DNA sequences of the nuclear ribosomal internal transcribed spacer (nuITS), the nuclear large subunit (nuLSU), the mitochondrial small subunit (mtSSU) ribosomal DNA, and the DNA replication licensing factor MCM7 from 80 samples mostly from Iran, Caucasia, Greece and eastern Europe. We used a combination of phylogenetic strategies and a variety of empirical, sequence-based species delimitation approaches to infer species boundaries in this group. The latter included: the automatic barcode gap discovery (ABGD), the multispecies coalescent approach *BEAST and Bayesian Phylogenetics and Phylogeography (BPP) program. Different species delimitation scenarios were compared using Bayes factors species delimitation analysis. Furthermore, morphological, chemical, ecological and geographical features of the sampled specimens were examined. Our study uncovered cryptic species diversity in A. intermutans and showed that morphology-based taxonomy may be unreliable, underestimating species diversity in this group of lichens. We identified a total of six species-level lineages in the A. intermutans complex using inferences from multiple empirical operational criteria. We found little corroboration between morphological and ecological features with our proposed candidate species, while secondary metabolite data do not corroborate tree topology. The present study on the A. intermutans species-complex indicates that the genus Aspiciliella, as currently circumscribed, is more diverse in Eurasia than previously expected.
- MeSH
- Ascomycota klasifikace genetika MeSH
- buněčné jádro genetika MeSH
- DNA fungální genetika MeSH
- druhová specificita MeSH
- fenotyp MeSH
- fylogeneze MeSH
- fylogeografie MeSH
- lišejníky klasifikace genetika MeSH
- sekvenční analýza DNA MeSH
- taxonomické DNA čárové kódování metody MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Středomoří MeSH
