Detecção de leucócitos em imagens de vídeo de microscopia intravital usando a técnica de congruência de fase

A quantificação do número de leucócitos rolantes e aderidos presentes na microcirculação de pequenos animais é uma tarefa importante para elucidar os mecanismos de inflamações e avaliar os efeitos terapêuticos de novas drogas. Em geral, a contagem de leucócitos é realizada de maneira visual por um observador (técnico laboratorial ou especialista) usando uma sequência de imagens de microscopia intravital (MI). Entretanto, tal tarefa é demorada e suscetível a erros, devido a fadiga visual do observador e a variabilidades inter e intra observadores. Neste trabalho uma nova técnica computacional é proposta para a detecção automática de leucócitos em vídeos de MI. A técnica usa uma medida de blobness, calculada a partir da análise dos autovalores de matrizes locais de momentos de segunda-ordem da medida de congruência de fase, para realçar os leucócitos nas imagens. A detecção dos leucócitos é alcançada pela busca de máximos locais no mapa de medidas de blobness. Usando um conjunto de quadros com os centroides dos leucócitos manualmente marcados, os resultados da técnica proposta foram avaliados usando os valores das métricas medida-F1 e áreas sob as curvas precisão-revocação (AUCPRs) calculadas para cada quadro do vídeo. Uma comparação com a técnica de casamento de padrões também foi realizada. Os resultados obtidos para a técnica proposta (medida-F1=0,791, AUCPR=0,776) foram superiores em comparação com a técnica de casamento de padrões (medida-F1=0,746, AUCPR=0,670)

Behavioral immune landscapes of inflammation.

Transcriptional or proteomic profiling of individual cells have revolutionized interpretation of biological phenomena by providing cellular landscapes of healthy and diseased tissues. These approaches, however, fail to describe dynamic scenarios in which cells can change their biochemical properties and downstream “behavioral” outputs every few seconds or minutes. Here, we used 4D live imaging to record tens to hundreds of morpho-kinetic parameters describing the dynamism of individual leukocytes at sites of active inflammation. By analyzing over 100,000 reconstructions of cell shapes and tracks over time, we obtained behavioral descriptors of individual cells and used these high-dimensional datasets to build behavioral landscapes. These landscapes recognized leukocyte identities in the inflamed skin and trachea, and inside blood vessels uncovered a continuum of neutrophil states, including a large, sessile state that was embraced by the underlying endothelium and associated with pathogenic inflammation. Behavioral in vivo screening of thousands of cells from 24 different mouse mutants identified the kinase Fgr as a driver of this pathogenic state, and genetic or pharmacological interference of Fgr protected from inflammatory injury. Thus, behavioral landscapes report unique biological properties of dynamic environments at high cellular, spatial and temporal resolution.pre-print4302 K

Optical Imaging

Optical Coherence Tomography (OCT)We describe the fundamental concept of optical coherence tomography (OCT) and discuss the two main working principles time domain OCT and frequency domain OCT. Then, we review extended functionalities including spectrally and polarization-resolved OCT as well as Doppler-OCT and show concepts for contrast enhancement. Based on these fundamentals, we demonstrate the potential of OCT for small animal imaging on the basis of exemplary studies on retinal imaging and lung imaging.Optoacoustic ImagingThis chapter deals with the fascinating topic of optoacoustic imaging, a recent powerful addition to the arsenal of in vivo functional and molecular small animal imaging. Due to its hybrid nature, involving optical excitation and ultrasonic detection, optoacoustics overcomes the imaging depth limitations of optical microscopy related to light scattering in living tissues while further benefiting from the compelling advantages of optical contrast. To this end, optoacoustic imaging has been shown capable of delivering multiple types of imaging contrast (structural, functional, kinetic, molecular) within a single imaging modality. It can further deliver images with high spatiotemporal resolution that rivals performance of other well-established whole-body imaging modalities. As such, optoacoustics can play a vital role in biomedical research, from early disease detection and monitoring of dynamic phenomena noninvasively to accelerating drug discovery.Optical ProbesThis chapter is devoted to the properties and application of fluorescence dyes as probes for optical imaging. A variety of agents have been described to date, including nontargeting dyes, vascular agents, targeted conjugates, activatable dyes, and sensing probes. The major classes encompass polymethine dyes and xanthenes dyes, both of which are commercially available in broad variations. Addressing the purpose of optical animal imaging, the most relevant parameters to apply such probes are discussed, thereby supporting the reader in choosing reasonable imaging probes and in preparing bioconjugates for his studies

Red blood cell segmentation and classification method using MATLAB

Red blood cells (RBCs) are the most important kind of blood cell. Its diagnosis is very important process for early detection of related disease such as malaria and anemia before suitable follow up treatment can be proceed. Some of the human disease can be showed by counting the number of red blood cells. Red blood cell count gives the vital information that help diagnosis many of the patient’s sickness. Conventional method under blood smears RBC diagnosis is applying light microscope conducted by pathologist. This method is time-consuming and laborious. In this project an automated RBC counting is proposed to speed up the time consumption and to reduce the potential of the wrongly identified RBC. Initially the RBC goes for image pre-processing which involved global thresholding. Then it continues with RBCs counting by using two different algorithms which are the watershed segmentation based on distance transform, and the second one is the artificial neural network (ANN) classification with fitting application depend on regression method. Before applying ANN classification there are step needed to get feature extraction data that are the data extraction using moment invariant. There are still weaknesses and constraints due to the image itself such as color similarity, weak edge boundary, overlapping condition, and image quality. Thus, more study must be done to handle those matters to produce strong analysis approach for medical diagnosis purpose. This project build a better solution and help to improve the current methods so that it can be more capable, robust, and effective whenever any sample of blood cell is analyzed. At the end of this project it conducted comparison between 20 images of blood samples taken from the medical electronic laboratory in Universiti Tun Hussein Onn Malaysia (UTHM). The proposed method has been tested on blood cell images and the effectiveness and reliability of each of the counting method has been demonstrated

Resolving Inflammation after Stroke through Modulation of Formyl Peptide Receptor 2/The Lipoxin Receptor

Stroke kills 15 million people a year and causes disabilities in many more millions who survive. Most strokes are caused by a blood clot, yet only seven percent of patients qualify for early pharmacological clot removal. Damage is frequently exacerbated even as blood reperfuses an ischaemic brain region, through a concomitant inflammatory response to the damaged tissue. Following the continual failure in clinical trials of drugs intended to tackle both initial excitotoxic cell death and pro-­‐inflammatory mechanisms during ischaemia/reperfusion (I/R), this thesis is premised on enhancing 'pro-­‐resolving' anti-­‐inflammatory pathways. Formyl Peptide Receptor 2/the lipoxin receptor (FPR2/ALX; mouse orthologue Fpr2/3) and two of its ligands, Lipoxin A4 (LXA4) and Annexin A1 (AnxA1), are part of an endogenous anti-­‐ inflammatory system. They actively resolve inflammation through a reduction in characteristic leukocyte-­‐endothelial (L-­‐E) interactions, while promoting the production of anti-­‐inflammatory cytokines and non-­‐phlogistic phagocytosis of leukocytes already within tissue. Chapters 3-­‐5 of this thesis describe the development of mouse model of global cerebral I/R (5 min ischaemia/40 min or 2 h reperfusion) through which L-­‐E interactions are assessed using intravital microscopy. Substantial reductions in L-­‐E interactions following treatment with FPR2/ALX ligands (AnxA1 N-­‐ terminal peptide AnxA1Ac2-­‐26 and LXA4 analogue 15-­‐epi-­‐LXA4) are demonstrated along with variations in cytokine levels (MCP-­‐1, IL-­‐6 and IL-­‐10) after 2 h of reperfusion. The reductions are shown to be variable with respect to the duration of reperfusion, concentration of 15-­‐epi-­‐LXA4 and the time of treatment administration. In addition, the effects are abrogated by co-­‐treatment with FPR antagonists, which independently cause a highly pronounced acute inflammatory response in the model. Chapters 6 and 7 provide further investigation into the role of FPRs in stroke and inflammation, through chemotaxis studies on human monocytes (from stroke patients and healthy controls) and through use of an FPR1-­‐target MRI contrast agent in mice following lipopolysaccaride-­‐induced inflammation. Overall, the data provide evidence that Fpr2/3 ligands are able to reduce inflammation following cerebral I/R, that an FPR2/ALX-­‐targeted drug may therefore be effective in human stroke, and that its optimal use is likely to be administration time, dose and FPR2/ALX ligand-­‐dependent.Open Acces

Evaluation of drug release from Abraxane and Doxil in tumor tissue.

Currently, the clinical strategy to treat cancer consists of a combination of surgery, radiotherapy, and chemotherapy on the basis of clinical and molecular staging. Nanotechnology applied to biomedical sciences has paved the way for the development of novel strategies for early detection and more efficient treatment of diseases. Abraxane and Doxil are approved formulations that utilize nanoparticles carrying the drugs paclitaxel and doxorubicin, respectively; however, tumors are not completely eradicated in some patients. It is well known that inefficient vascularization may prevent optimal transport of oxygen, nutrients, and therapeutics to cells in solid tumors. In order to quantitatively evaluate therapy with Abraxane and Doxil, we apply a biocomputational cancer model to study nanoparticle drug release within tumor tissue. Both tumor cells and their microenvironment are represented in this model. Based on the specific characteristics of Abraxane and Doxil, we simulate drug release and diffusion at the tumor site. With the viable tumor region modeled as approximately 100 µm in diameter from blood vessels, and using IC50 data, the paclitaxel molecules of Abraxane were found to only penetrate 73 µm deep into the tumor, while although more efficient, doxorubicin molecules of Doxil only penetrate 93 µm of the tumor viable region. Therefore, we find that the modeling predicts that in the best case scenario, the drug concentrations delivered by these nanotherapies are insufficient to kill all of the tumor cells