Review on Photomicrography based Full Blood Count (FBC) Testing and Recent Advancements

With advancements in related sub-fields, research on photomicrography in life science is emerging and this is a review on its application towards human full blood count testing which is a primary test in medical practices. For a prolonged period of time, analysis of blood samples is the basis for bio medical observations of living creatures. Cell size, shape, constituents, count, ratios are few of the features identified using DIP based analysis and these features provide an overview of the state of human body which is important in identifying present medical conditions and indicating possible future complications. In addition, functionality of the immune system is observed using results of blood tests. In FBC tests, identification of different blood cell types and counting the number of cells of each type is required to obtain results. Literature discuss various techniques and methods and this article presents an insightful review on human blood cell morphology, photomicrography, digital image processing of photomicrographs, feature extraction and classification, and recent advances. Integration of emerging technologies such as microfluidics, micro-electromechanical systems, and artificial intelligence based image processing algorithms and classifiers with cell sensing have enabled exploration of novel research directions in blood testing applications.

New implementations of phase-contrast imaging

Phase-contrast imaging is a method of imaging widely used in biomedical research and applications. It is a label-free method that exploits intrinsic differences in the refractive index of different tissues to differentiate between biological structures under analysis. The basic principle of phase-contrast imaging has inspired a lot of implementations that are suited for different applications. This thesis explores multiple novel implementations of phase-contrast imaging in the following order. 1, We combined scanning Oblique Back-illumination Microscope (sOBM) and confocal microscope to produce phase and fluorescence contrast images in an endomicroscopy configuration. This dual-modality design provides co-registered, complementary labeled and unlabeled contrast of the sample. We further miniaturized the probe by dispensing the two optical fibers in our old design. And we presented proof of principle demonstrations with ex-vivo mouse colon tissue. 2, Then we explored sOBM-based phase and amplitude contrast imaging under different wavelengths. Hyperspectral imaging is achieved by multiplexing a wide-range supercontinuum laser with a Michaelson interferometer (similar to Fourier transform spectroscopy). It features simultaneous acquisition of hyperspectral phase and amplitude images with arbitrarily thick scattering biological samples. Proof-of-principle demonstrations are presented with chorioallantoic membrane of a chick embryo, illustrating the possibility of high-resolution hemodynamics imaging in thick tissue. 3, We focused on increasing the throughput of flow cytometry with principle of phase-contrast imaging and compressive sensing. By utilizing the linearity of scattered patterns under partially coherent illumination, our cytometer can detect multiple objects in the same field of view. By utilizing an optimized matched filter on pupil plane, it also provides increased information capacity of each measurement without sacrificing speed. We demonstrated a throughput of over 10,000 particles/s with accuracy over 91% in our results. 4, A fourth part, which describes the principle and preliminary results of a computational fluorescence endomicroscope is also included. It uses a numerical method to achieve sectioning effect and renders a pseudo-3D image stack with a single shot. The results are compared with true-3D image stack acquired with a confocal microscope

Objective assessment of stored blood quality by deep learning

Stored red blood cells (RBCs) are needed for life-saving blood transfusions, but they undergo continuous degradation. RBC storage lesions are often assessed by microscopic examination or biochemical and biophysical assays, which are complex, time-consuming, and destructive to fragile cells. Here we demonstrate the use of label-free imaging flow cytometry and deep learning to characterize RBC lesions. Using brightfield images, a trained neural network achieved 76.7% agreement with experts in classifying seven clinically relevant RBC morphologies associated with storage lesions, comparable to 82.5% agreement between different experts. Given that human observation and classification may not optimally discern RBC quality, we went further and eliminated subjective human annotation in the training step by training a weakly supervised neural network using only storage duration times. The feature space extracted by this network revealed a chronological progression of morphological changes that better predicted blood quality, as measured by physiological hemolytic assay readouts, than the conventional expert-assessed morphology classification system. With further training and clinical testing across multiple sites, protocols, and instruments, deep learning and label-free imaging flow cytometry might be used to routinely and objectively assess RBC storage lesions. This would automate a complex protocol, minimize laboratory sample handling and preparation, and reduce the impact of procedural errors and discrepancies between facilities and blood donors. The chronology-based machine-learning approach may also improve upon humans’ assessment of morphological changes in other biomedically important progressions, such as differentiation and metastasis

Experimental and computational analyses reveal that environmental restrictions shape HIV-1 spread in 3D cultures

Here, using an integrative experimental and computational approach, Imle et al. show how cell motility and density affect HIV cell-associated transmission in a three-dimensional tissue-like culture system of CD4+ T cells and collagen, and how different collagen matrices restrict infection by cell-free virions

Quantitative Optical Studies of Oxidative Stress in Rodent Models of Eye and Lung Injuries

Optical imaging techniques have emerged as essential tools for reliable assessment of organ structure, biochemistry, and metabolic function. The recognition of metabolic markers for disease diagnosis has rekindled significant interest in the development of optical methods to measure the metabolism of the organ. The objective of my research was to employ optical imaging tools and to implement signal and image processing techniques capable of quantifying cellular metabolism for the diagnosis of diseases in human organs such as eyes and lungs. To accomplish this goal, three different tools, cryoimager, fluorescent microscope, and optical coherence tomography system were utilized to study the physiological metabolic markers and early structural changes due to injury in vitro, ex vivo, and at cryogenic temperatures. Cryogenic studies of eye injuries in animal models were performed using a fluorescence cryoimager to monitor two endogenous mitochondrial fluorophores, NADH (nicotinamide adenine dinucleotide) and FAD (flavin adenine dinucleotide). The mitochondrial redox ratio (NADH/ FAD), which is correlated with oxidative stress level, is an optical biomarker. The spatial distribution of mitochondrial redox ratio in injured eyes with different durations of the disease was delineated. This spatiotemporal information was helpful to investigate the heterogeneity of the ocular oxidative stress in the eyes during diseases and its association with retinopathy. To study the metabolism of the eye tissue, the retinal layer was targeted, which required high resolution imaging of the eye as well as developing a segmentation algorithm to quantitatively monitor and measure the metabolic redox state of the retina. To achieve a high signal to noise ratio in fluorescence image acquisition, the imaging was performed at cryogenic temperatures, which increased the quantum yield of the intrinsic fluorophores. Microscopy studies of cells were accomplished by using an inverted fluorescence microscope. Fixed slides of the retina tissue as well as exogenous fluorophores in live lung cells were imaged using fluorescent and time-lapse microscopy. Image processing techniques were developed to quantify subtle changes in the morphological parameters of the retinal vasculature network for the early detection of the injury. This implemented image cytometry tool was capable of segmenting vascular cells, and calculating vasculature features including: area, caliber, branch points, fractal dimension, and acellular capillaries, and classifying the healthy and injured retinas. Using time-lapse microscopy, the dynamics of cellular ROS (Reactive Oxygen Species) concentration was quantified and modeled in ROS-mediated lung injuries. A new methodology and an experimental protocol were designed to quantify changes of oxidative stress in different stress conditions and to localize the site of ROS in an uncoupled state of pulmonary artery endothelial cells (PAECs). Ex vivo studies of lung were conducted using a spectral-domain optical coherence tomography (SD-OCT) system and 3D scanned images of the lung were acquired. An image segmentation algorithm was developed to study the dynamics of structural changes in the lung alveoli in real time. Quantifying the structural dynamics provided information to diagnose pulmonary diseases and to evaluate the severity of the lung injury. The implemented software was able to quantify and present the changes in alveoli compliance in lung injury models, including edema. In conclusion, optical instrumentation, combined with signal and image processing techniques, provides quantitative physiological and structural information reflecting disease progression due to oxidative stress. This tool provides a unique capability to identify early points of intervention, which play a vital role in the early detection of eye and lung injuries. The future goal of this research is to translate optical imaging to clinical settings, and to transfer the instruments developed for animal models to the bedside for patient diagnosis

Role of the extracellular matrix proteins in the resistance of SP6.5 uveal melanoma cells toward cisplatin

Uveal melanoma is the most frequent primary intraocular tumor in the adult population. This malignancy has a high mortality rate and responds poorly to existing chemotherapy. Recently, the tumor environment has been found to exert a profound influence on drug response through cell interaction with components from the extracellular matrix (ECM). In the present study, we investigated whether individual components from the ECM may affect cell survival and/or cell death induced by the cytotoxic agent cisplatin on the SP6.5 uveal melanoma cell line. Tumor cells were shown by immunofluorescence analyses to be surrounded by the ECM proteins fibronectin (FN), type IV collagen (CIV) and laminin (LM), both at the primary and metastatic sites. Binding of SP6.5 cells to FN, LM and CIV is primarily dictated by the expression of membrane bound integrins from the beta1 family as revealed by cell adhesion assays conducted on ECM-coated culture plates. Analysis of cell death by flow cytometry demonstrated that culturing SP6.5 cells in the presence of FN, CIV and LM, substantially reduced the percentage of cells undergoing apoptosis after cisplatin treatment when compared with those seeded on a non-permissive matrix. These results suggest that adhesion of the SP6.5 uveal melanoma cells to the ECM proteins FN, CIV and LM might therefore confer resistance to the chemotherapeutic agent cisplatin. The cellular resistance induced by the ECM proteins toward cisplatin could explain in part the local recurrence of metastasis derived from uveal melanoma often observed clinically after chemotherapy

Cannibalism of Live Lymphocytes by Human Metastatic but Not Primary Melanoma Cells

The phenomenon of cell cannibalism, which generally refers to the engulfment of cells within other cells, was described in malignant tumors, but its biological significance is still largely unknown. In the present study, we investigated the occurrence, the in vivo relevance, and the underlying mechanisms of cannibalism in human melanoma. As first evidence, we observed that tumor cannibalism was clearly detectable in vivo in metastatic lesions of melanoma and often involved T cells, which could be found in a degraded state within tumor cells. Then, in vitro experiments confirmed that cannibalism of T cells was a property of metastatic melanoma cells but not of primary melanoma cells. In particular, morphologic analyses, including time-lapse cinematography and electron microscopy, revealed a sequence of events, in which metastatic melanoma cells were able to engulf and digest live autologous melanoma-specific CD8+ T cells. Importantly, this cannibalistic activity significantly increased metastatic melanoma cell survival, particularly under starvation condition, supporting the evidence that tumor cells may use the eating of live lymphocytes as a way to ‘‘feed’’ in condition of low nutrient supply. The mechanism underlying cannibalism involved a complex framework, including lysosomal protease cathepsin B activity, caveolae formation, and ezrin cytoskeleton integrity and function. In conclusion, our study shows that human metastatic melanoma cells may eat live T cells, which are instead programmed to kill them, suggesting a novel mechanism of tumor immune escape. Moreover, our data suggest that cannibalism may represent a sort of ‘‘feeding’’ activity aimed at sustaining survival and progression of malignant tumor cells in an unfavorable microenvironment. (Cancer Res 2006; 66(7): 3629-38

Three-Dimensional GPU-Accelerated Active Contours for Automated Localization of Cells in Large Images

Cell segmentation in microscopy is a challenging problem, since cells are often asymmetric and densely packed. This becomes particularly challenging for extremely large images, since manual intervention and processing time can make segmentation intractable. In this paper, we present an efficient and highly parallel formulation for symmetric three-dimensional (3D) contour evolution that extends previous work on fast two-dimensional active contours. We provide a formulation for optimization on 3D images, as well as a strategy for accelerating computation on consumer graphics hardware. The proposed software takes advantage of Monte-Carlo sampling schemes in order to speed up convergence and reduce thread divergence. Experimental results show that this method provides superior performance for large 2D and 3D cell segmentation tasks when compared to existing methods on large 3D brain images

New Nrf2-Inducer Compound ITH12674 Slows the Progression of Retinitis Pigmentosa in the Mouse Model rd10

Background/Aims: It is well established that oxidative stress and inflammation are common pathogenic features of retinal degenerative diseases. ITH12674 is a novel compound that induces the transcription factor Nrf2; in so doing, the molecule exhibits anti-inflammatory, and antioxidant properties, and affords neuroprotection in rat cortical neurons subjected to oxidative stress. We here tested the hypothesis that ITH12674 could slow the retinal degeneration that causes blindness in rd10 mice, a model of retinitis pigmentosa. Methods: Animals were intraperitoneally treated with 1 or 10 mg/Kg ITH12674 or placebo from P16 to P30. At P30, retinal functionality and visual acuity were analyzed by electroretinography and optomotor test. By immunohistochemistry we quantified the photoreceptor rows and analyzed their morphology and connectivity. Oxidative stress and inflammatory state was studied by Western blot, and microglia reactivity was monitored by flow cytometry. The blood−brain barrier permeation of ITH12674 was evaluated using a PAMPA-BBB assay. Results: In rd10 mice treated with 10 mg/Kg of the compound, the following changes were observed (with respect to placebo): (i) a decrease of vision loss with higher scotopic a- and b-waves; (ii) increased visual acuity; (iii) preservation of cone photoreceptors morphology, as well as their synaptic connectivity; (iv) reduced expression of TNF-α and NF-κB; (v) increased expression of p38 MAPK and Atg12-Atg5 complex; and (vi) decreased CD11c, MHC class II and CD169 positive cell populations. Conclusion: These data support the view that a Nrf2 inducer compound may arise as a new therapeutic strategy to combat retinal neurodegeneration. At present, we are chemically optimising compound ITH12674 with the focus on improving its neuroprotective potential in retinal neurodegenerative diseases.This work was supported by grants from Bayer (Grats4Targets), from the Spanish Ministry of Economy and Competitiveness (MINECO-FEDER BFU2015-67139-R), Spanish Ministry of Education (FPU14/03166, FPU13/03737 and FPU16/04114), Instituto de Salud Carlos III co-financed by the European Regional Development’s funds (FEDER) (RETICS-FEDER RD16/0008/0016, Programa Miguel Servet II (CP16/00014) and research project (grant PI17/01700)), Asociación Retina Asturias, Fundación La Caixa, CaixaImpulse program (grant CI17-00048), Comunidad Autónoma de Madrid (grant B2017/BMD-3827), Generalitat Valenciana (PROMETEO/2016/158 and ACIF/2016/055) Generalitat Valenciana-FEDER IDIFEDER/2017/064