1,720,990 research outputs found
Out of distribution detection in deep learning-based scattering pattern classification
No full textIntrinsic biophysical cell properties hold an enormous potential for cell class and state classification in microfluidics, allowing to avoid the need of cost intensive fluorescence labelling. Several methods can accomplish cell identification, while convolutional neural networks show an outstanding performance compared to other state-of-the-art classification methods, regarding accuracy and speed. In fact, neural networks show high performance for known image class prediction but struggles when unknown (out of distribution) image classes need to be identified. In such a scenario no prior knowledge of the unknown cell class can be used for the model training, which inevitably results in image misclassification. In fact, to distinguish unknown cell classes, a neural network must first construct an in-distribution of known images to afterwards detect out of distribution as unknowns, which is also called open-set classification assumption. Ones, a new cell class is identified, the neural network can be retrained with the obtained knowledge to dynamically update its cell class database. This process can be simply repeated for each new detected cell class. We applied this open-set idea to scattering pattern snapshots of different classes of living cells obtained in microfluidics. Our outcome shows a proof-of-concept for open-set based convolutional neural network for cell image classification, which can be applied to a wide range of single cell classification approaches to reduce uncertainty in machine learning based technologies
Microgel-barcode readout for miRNA quantification in microfluidic flow
No full textA microfluidic based multiplex fluorescence signal readout system, able to fast, simply and accurately detect low concentrations of microRNA (miRNA) in small sample volumes is presented. Our ap-proach is able to simultaneously process several different miRNA types and moreover to measure their absolute amounts in a continuous microfluidic flow, without complex pre-treatments as PCR amplification steps. We additionally investigated the tendency of the utilized barcoded microgel parti-cles to be aligned, compared to rigid polystyrene particles. An improved 3D alignment has been ob-tained, according to the higher viscoelastic migration to the centreline due to the elasticity of the soft microgel particles
Microfluidic platform for cell classification from optical signatures via machine learning
No full textBiophysical cell properties are a powerful tool for the label-free classification of cells. Here, we report a single cell investigation approach to detect different peripheral blood cell classes in microfluidics using a machine learning based optical cell signatures detection. The utilized microfluidic platform aligns cells in flow and alternatively allows compression and subsequent investigations of cells in flow. In fact, the presented approach can be interesting for a wide spectrum of clinical and diagnostic single cell investigations, such as the detection of circulating tumour cells in liquid biopsy samples
Circulating tumour cells deformability measurement in microfluidics
No full textDuring the last years, the deformability characterization of non-adherent cells like circulating tumour cells (CTCs) and immune cells gained a lot of attention since mechanical forces regulate the deformation, organization, and translocation of cytoskeleton leading to changes in T-cell mobility, migration, and infiltration. However, deformability measurements on non-adherent cells is challenging since any kind of contact between a physical probe or substrate could induce alterations into the cell state and then deformability outcome. Thus, new strategies are needed to overcome such problems. Inflow viscoelastic compression represents a straightforward way to deform CTCs and immune cells in a controlled and contactless manner. Here, we present a study of cell deformability by application of such viscoelastic compression forces on CTCs and healthy lymphocytes, eliciting a higher deformability of cancer cells with respect to healthy lymphocytes. Thus, our approach opens up to the possibility to characterize and distinguish CTCs and healthy lymphocytes depending on the resulting deformability in a rapid and versatile way
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Demonstration that venous occlusion fails to release von Willebrand factor multimers.
No full textThe acute simultaneous release of tissue plasminogen activator (t-PA) and von Willebrand factor (vWF) from endothelial cells in response to a variety of agonists including thrombin, DDAVP, histamine and adrenalin has been described. In the present study we investigated the effect of venous occlusion on the circulating levels of t-PA and vWF, as well as the molecular organization of vWF in 20 normal subjects. After occlusion a significant increase in plasma t-PA levels was observed even after the values were corrected for haemoconcentration. Venous occlusion also enhanced plasma vWF values, but the increase was abolished when the correction for haemoconcentration was introduced. Following venous occlusion, no circulating abnormally large vWF multimers were detected in the subjects studied. These forms are normally not present in the circulation and are released from endothelial cells through the regulated vWF pathway; their absence therefore seems to demonstrate that this pathway is not activated after venous occlusion. Since occlusion does not enhance vWF synthesis, the increase in vWF observed in the subjects investigated may be fully attributed to haemoconcentration
EDTA dependent pseudothrombocytopenia caused by antibodies against the cytoadhesive receptor of platelet gpIIB-IIIA.
No full textAIMS:
To clarify the mechanisms involved in the development of EDTA dependent pseudothrombocytopenia, particularly the platelet receptors.
METHODS:
Platelets were measured in 33 patients with pseudothrombocytopenia, using different anticoagulants to collect blood samples (direct test). The results were compared with the counts obtained by adding patients' serum or immunoglobulins to normal blood samples (indirect test). The role of platelet function was explored using ASA, PGE1, and apyrase as platelet inhibitors. The contribution of platelet receptor/s was investigated using antigens to gpIb-IX and gpIIb-IIIa monoclonal antibodies. Immunoglobulin class was estimated by the ability of IgG, IgA, and IgM antibodies to prevent platelet clumping.
RESULTS:
Agglutinating antibodies were IgA in 40%, IgG in 30%, and IgM in 10% of patients studied. Both patients' serum and immunoglobulins induced platelet clumping in normal samples anticoagulated with EDTA (indirect test). This was prevented by incubation of blood samples at 37 degrees C and almost completely inhibited by the platelet inhibitors ASA, PGE1, and apyrase. Pseudothrombocytopenia was also entirely prevented by an antigen to gpIIb-IIIa monoclonal antibody that recognises fibrinogen and the von Willebrand factor binding site. Pseudothrombocytopenia was almost completely abolished after the addition of RGD peptide, the recognition sequence of cytoadhesive proteins.
CONCLUSIONS:
These findings suggest that EDTA dependent pseudothrombocytopenia is caused by agglutinating antibodies that recognise cytoadhesive receptors on platelet gpIIb-IIIa and that an efficient platelet metabolism is required
Characterization and 3D-localization of human white blood cells in microfluidic flows
No full textWe report a rapid and cost-effective system to analyze morphological properties and 3D alignment positions of human white blood cell in a viscoelastic induced microfluidic flow. Measurements have been performed in physiological conditions using light scattering for the investigation of the individu-al cell properties and digital holography for the accurate tracking of the cell position in 3D. Our re-sults confirm the possibility to obtain sub-micrometric individual cell details as dimension and refrac-tive index, together with detailed cell location in continuous measurement flows inside of a rectangular shaped channel
CD4+: Versus CD8+ T-lymphocyte identification in an integrated microfluidic chip using light scattering and machine learning
No full textT lymphocytes are a group of cells representing the main effectors of human adaptive immunity. Characterization of the most representative T-lymphocyte subclasses, CD4+ and CD8+, is challenging, but has a significant impact on clinical decisions. Up to now, T lymphocytes have been identified by quite complex cytometric assays, which are based on antibody labeling. However, a label-free approach based on pure biophysical evaluation at a single-cell level could enable the ability to distinguish between these subclasses. Here, we report a light-scattering approach, supported by accurate data mining, to evaluate cell biophysical properties on an integrated microfluidic chip. In order to perform single-cell optical analysis in viscoelastic fluids, such a chip is composed of mixing, alignment, readout and collection sections. In particular, we measured the cell dimensions, the refractive index of the cell nucleus, the refractive index of the cytosol, and the nucleus-to-cytosol ratio. Combining measurement of biophysical properties and machine learning allows us to both distinguish and count human CD4+ and CD8+ cells with an accuracy of 79%. An enhanced identification accuracy of 88% can be achieved by stimulating the cells with a selective anti-apoptotic protein, which results in increased biophysical differences between CD4+ and CD8+ cells. This approach has been successfully validated by analysis of samples that recapitulate physiological and pathological scenarios (CD4+/CD8+ ratios). The results are encouraging for the possible application of our approach in hematological clinical routines, as well as in diagnosis and follow-up of specific pathologies, such as human immunodeficiency virus (HIV) progression
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