Academic literature on the topic 'Cancer Cell Imaging'

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Journal articles on the topic "Cancer Cell Imaging"

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Ray, L. Bryan. "Imaging cancer cell by cell." Science 372, no. 6543 (May 13, 2021): 699.1–699. http://dx.doi.org/10.1126/science.372.6543.699-a.

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Roy, Catherine, Xavier Buy, and Sofiane el Ghali. "Imaging in Renal Cell Cancer." EAU Update Series 1, no. 4 (December 2003): 209–14. http://dx.doi.org/10.1016/s1570-9124(03)00058-8.

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Ponomarev, V. "Nuclear Imaging of Cancer Cell Therapies." Journal of Nuclear Medicine 50, no. 7 (June 12, 2009): 1013–16. http://dx.doi.org/10.2967/jnumed.109.064055.

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Heidenreich, Axel, and Vincent Ravery. "Preoperative imaging in renal cell cancer." World Journal of Urology 22, no. 5 (July 30, 2004): 307–15. http://dx.doi.org/10.1007/s00345-004-0411-2.

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Irshad, Abid, and James G. Ravenel. "Imaging of small-cell lung cancer." Current Problems in Diagnostic Radiology 33, no. 5 (September 2004): 200–211. http://dx.doi.org/10.1067/j.cpradiol.2004.06.003.

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PINNER, S., and E. SAHAI. "Imaging amoeboid cancer cell motilityin vivo." Journal of Microscopy 231, no. 3 (September 2008): 441–45. http://dx.doi.org/10.1111/j.1365-2818.2008.02056.x.

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Midde, Krishna, Nina Sun, Cristina Rohena, Linda Joosen, Harsharan Dhillon, and Pradipta Ghosh. "Single-Cell Imaging of Metastatic Potential of Cancer Cells." iScience 10 (December 2018): 53–65. http://dx.doi.org/10.1016/j.isci.2018.11.022.

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Yano, Shuya, and Robert Hoffman. "Real-Time Determination of the Cell-Cycle Position of Individual Cells within Live Tumors Using FUCCI Cell-Cycle Imaging." Cells 7, no. 10 (October 14, 2018): 168. http://dx.doi.org/10.3390/cells7100168.

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Most cytotoxic agents have limited efficacy for solid cancers. Cell-cycle phase analysis at the single-cell level in solid tumors has shown that the majority of cancer cells in tumors is not cycling and is therefore resistant to cytotoxic chemotherapy. Intravital cell-cycle imaging within tumors demonstrated the cell-cycle position and distribution of cancer cells within a tumor, and cell-cycle dynamics during chemotherapy. Understanding cell-cycle dynamics within tumors should provide important insights into novel treatment strategies.
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A. Rabinovich, Brian, and Caius G. Radu. "Imaging Adoptive Cell Transfer Based Cancer Immunotherapy." Current Pharmaceutical Biotechnology 11, no. 6 (September 1, 2010): 672–84. http://dx.doi.org/10.2174/138920110792246528.

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Liu, Gang, Magdalena Swierczewska, Gang Niu, Xiaoming Zhang, and Xiaoyuan Chen. "Molecular imaging of cell-based cancer immunotherapy." Molecular BioSystems 7, no. 4 (2011): 993. http://dx.doi.org/10.1039/c0mb00198h.

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Dissertations / Theses on the topic "Cancer Cell Imaging"

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Kosmacek, Elizabeth Anne Ianzini Fiorenza Mackey Michael A. "Live cell imaging technology development for cancer research." [Iowa City, Iowa] : University of Iowa, 2009. http://ir.uiowa.edu/etd/388.

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Kosmacek, Elizabeth Anne. "Live cell imaging technology development for cancer research." Diss., University of Iowa, 2009. https://ir.uiowa.edu/etd/388.

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Live cell imaging is a unique tool for cellular research with a wide variety of applications. By streaming digital microscopic images an investigator can observe the dynamic morphology of a cell, track cell movement on a surface, and measure quantities or localization patterns of fluorescently labeled proteins or molecules. Digital image sequences contain a vast amount of information in the form of visually detectable morphological changes in the cell. We designed computer programs that allow the manual identification of visible events in live cell digital image sequences [Davis et al. 2007]. Once identified, the data are analyzed using algorithms to calculate the yield of individual events per cell over the time course of image acquisition. The sequence of event data is also constructed into directed acyclic graphs and through the use of a subgraph isomorphism algorithm we are able to detect specified patterns of events originating from a single cell. Two projects in the field of cancer research are here discussed that describe and validate the application of the event analysis programs. In the first project, mitotic catastrophe (MC) research [Ianzini and Mackey, 1997; Ianzini and Mackey, 1998; reviewed by Ianzini and Mackey, 2007] is enhanced with the addition of live cell imaging to traditional laboratory experiments. The event analysis program is used to describe the yield of normal or abnormal divisions, fusions, and cell death, and to detect patterns of reductive division and depolyploidization in cells undergoing radiation-induced MC. Additionally, the biochemical and molecular data used in conjunction with live cell imaging data are presented to illustrate the usefulness of combining biology and engineering techniques to elucidate pathways involved in cell survival under different detrimental cell conditions. The results show that the timing of depolyploidization in MC cells correlates with increased multipolar divisions, up-regulation of meiosis-specific genes, and the production of mononucleated cell progeny. It was confirmed that mononucleated cells are produced from multipolar divisions and these cells are capable of resuming normal divisions [Ianzini et al., 2009]. The implications for the induction of meiosis as a mechanism of survival after radiation treatment are discussed. In the second project, the effects of long-term fluorescence excitation light exposure are examined through measurements of cell division and cell death. In the field of live cell imaging, probably the most modern and most widely utilized technique is fluorescence detection for intracellular organelles, proteins, and molecules. While the technologies required to label and detect fluorescent molecules in a cell are well developed, they are not idealized for long term measurements as both the probes and excitation light are toxic to the cells [Wang and Nixon, 1978; Bradley and Sharkey, 1977]. From the event analysis data it was determined that fluorescence excitation light is toxic to multiple cell lines observed as the reduction of normal cell division, induction of cell death, and apparent morphological aberrations.
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Agrawal, Vishesh. "Quantitative Imaging Analysis of Non-Small Cell Lung Cancer." Thesis, Harvard University, 2016. http://nrs.harvard.edu/urn-3:HUL.InstRepos:27007763.

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Quantitative imaging is a rapidly growing area of interest within the field of bioinformatics and biomarker discovery. Due to the routine nature of medical imaging, there is an abundance of high-quality imaging linked to clinical and genetic data. This data is particularly relevant for cancer patients who receive routine CT imaging for staging and treatment purposes. However, current analysis of tumor imaging is generally limited to two-dimensional diameter measurements and assessment of anatomic disease spread. This conventional tumor-node-metastasis (TNM) staging system stratifies patients to treatment protocols including decisions regarding adjuvant therapy. Recently there have been several studies suggesting that these images contain additional unique information regarding tumor phenotype that can further aid clinical decision-making. In this study I aimed to develop the predictive capability of medical imaging. I employed the principles of quantitative imaging and applied them to patients with non-small cell lung cancer (NSCLC). Quantitative imaging, also termed radiomics, seeks to extract thousands of imaging data points related to tumor shape, size and texture. These data points can potentially be consolidated to develop a tumor signature in the same way that a tumor might contain a genetic signature corresponding to mutational burden. To accomplish this I applied radiomics analyses to patients with early and late stage NSCLC and tested these for correlation with both histopathological data as well as clinical outcomes. Patients with both early and late stage NSCLC were assessed. For locally advanced NSCLC (LA-NSCLC), I analyzed patients treated with preoperative chemoradiation followed by surgical resection. To assess early stage NSCLC, I analyzed patients treated with stereotactic body radiation therapy (SBRT). Quantitative imaging features were extracted from CT imaging obtained prior to chemoradiation and post-chemoradiation prior to surgical resection. For patients who underwent SBRT, quantitative features were extracted from cone-beam CTs (CBCT) at multiple time points during therapy. Univariate and multivariate logistic regression were used to determine association with pathologic response. Concordance-index and Kaplan-Meier analyses were applied to time dependent endpoints of overall survival, locoregional recurrence-free and distant metastasis. In this study, 127 LA-NSCLC patients were identified and treated with preoperative chemoradiation and surgical resection. 99 SBRT patients were identified in a separate aim of this study. Reduction of CT-defined tumor volume (OR 1.06 [1.02-1.09], p=0.002) as continuous variables per percentage point was associated with pathologic complete response (pCR) and locoregional recurrence (LRR). Conventional response assessment determined by diameter (p=0.213) was not associated with pCR or any survival endpoints. Seven texture features on pre-treatment tumor imaging were associated with worse pathologic outcome (AUC 0.61-0.66). Quantitative assessment of lymph node burden demonstrated that pre-treatment and post-treatment volumes are significantly associated with both OS and LRR (CI 0.62-0.72). Textural analyses of these lymph nodes further identified 3 unique pre-treatment and 7 unique post-treatment features significantly associated with either LRR, DM or OS. Finally early volume change showed associated with overall survival in CBCT scans of early NSCLC. Quantitative assessment of NSCLC is thus strongly associated with pathologic response and survival endpoints. In contrast, conventional imaging response assessment was not predictive of pathologic response or survival endpoints. This study demonstrates the novel application of radiomics to lymph node texture, CBCT volume and patients undergoing neoadjuvant therapy for NSCLC. These examples highlight the potential within the rapidly growing field of quantitative imaging to better describe tumor phenotype. These results provide evidence to the growing radioimics literature that there is significant association between imaging, pathology and clinical outcomes. Further exploration will allow for more complete models describing tumor imaging phoentype with clinical outcomes.
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Kharin, Alexander. "Group IV nanoparticles for cell imaging and therapy." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSE1032/document.

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La biomédecine et la biophotonique sont des champs de recherches en plein expansion qui grandissent à vive allure, constituant un secteur entier d'activités novatrices. Ce secteur, vraiment interdisciplinaire, comprend le développement de nouveaux nanomatériaux, de sources lumineuses et l'élaboration de nouveaux concepts, de dispositifs/équipements pour quantifier la conversion de photons et leurs interactions. L'importance décisive du diagnostic précoce et du traitement individuel des patients exige des thérapies soigneusement ciblées et la capacité de provoquer sélectivement la mort cellulaire des cellules malades. Malgré les progrès spectaculaires réalisés en utilisant les points quantiques ou des molécules biologiques organiques pour l'imagerie biologique et la libération ciblée de médicaments, plusieurs problèmes restent à résoudre : obtenir une sélectivité accrue pour une accumulation spécifique dans les tumeurs et une amélioration de l'efficacité des traitements. D'autres problèmes incluent la cytotoxicité et la génotoxicité, l'élimination lente et la stabilité chimique imparfaite. Des espérances nouvelles sont portées par de nouvelles classes de matériaux inorganiques comme les nanoparticules à base de silicium ou à base de carbone, qui pourraient faire preuves de caractéristiques de stabilité plus prometteuses tant pour le diagnostic médical que pour la thérapie. Pour cette raison, la découverte de nouveaux agents de marquage et de transport de médicaments représente un champ important de la recherche avec un potentiel de croissance renforcé
Biomedicine and biophotonics related businesses are currently growing at a breathtaking pace, thereby comprising one of the fastest growing sectors of innovative economy. This sector is truly interdisciplinary, including, very prominently, the development of novel nanomaterials, light sources, or novel device/equipment concepts to carry out photon conversion or interaction. The great importance of disease diagnosis at a very early stage and of the individual treatment of patients requires a carefully targeted therapy and the ability to induce cell death selectively in diseased cells. Despite the tremendous progress achieved by using quantum dots or organic molecules for bio-imaging and drug delivery, some problems still remain to be solved: increased selectivity for tumor accumulation, and enhancement of treatment efficiency. Other potential problems include cyto- and genotoxicity, slow clearance and low chemical stability. Significant expectations are now related to novel classes of inorganic materials, such as silicon-based or carbon-based nanoparticles, which could exhibit more stable and promising characteristics for both medical diagnostics and therapy. For this reason, new labeling and drug delivery agents for medical application is an important field of research with strongly-growing potential.The 5 types of group IV nanoparticles had been synthesized by various methods. First one is the porous silicon, produced by the electrochemical etching of bulk silicon wafer. That well-known technique gives the material with remarkably bright photoluminescence and the complicated porous structure. The porous silicon particles are the agglomerates of the small silicon crystallites with 3nm size. Second type is 20 nm crystalline silicon particles, produced by the laser ablation of the bulk silicon in water. Those particles have lack of PL under UV excitation, but they can luminesce under 2photon excitation conditions. 3rd type of the particles is the 8 nm nanodiamonds
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PHADNGAM, SURATCHANEE. "In Cell Imaging Techniques to Monitor Glucose Uptake, Cell Migration, and Vesicular Traffic: A Functional Study in Cancer Cells." Doctoral thesis, Università del Piemonte Orientale, 2016. http://hdl.handle.net/11579/115172.

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Mickler, Frauke Martina. "Live-cell imaging elucidates cellular interactions of gene nanocarriers for cancer therapy." Diss., Ludwig-Maximilians-Universität München, 2013. http://nbn-resolving.de/urn:nbn:de:bvb:19-165829.

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Youniss, Fatma. "MULTI – MODALITY MOLECULAR IMAGING OF ADOPTIVE IMMUNE CELL THERAPY IN BREAST CANCER." VCU Scholars Compass, 2014. http://scholarscompass.vcu.edu/etd/3323.

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Cancer treatment by adoptive immune cell therapy (AIT) is a form of immunotherapy that relies on the in vitro activation and/or expansion of immune cells. In this approach, immune cells, particularly CD8+ T lymphocytes, can potentially be harvested from a tumor-bearing patient, then activated and/or expanded in vitro in the presence of cytokines and other growth factors, and then transferred back into the same patient to induce tumor regression. AIT allows the in vitro generation and activation of T-lymphocytes away from the immunosuppressive tumor microenvironment, thereby providing optimum conditions for potent anti-tumor activity. The overall objective of this study is to: a) develop multi-modality (optical- and radionuclide-based) molecular imaging approaches to study the overall kinetics of labeled adoptively transferred T- lymphocytes in vivo, b) to non-invasively image and assess in-vivo, targeting and retention of adoptively transferred labeled T-lymphocytes at the tumor site. T-lymphocytes obtained from draining lymph nodes of 4T1 (murine breast cancer cell) sensitized BALB/C mice were activated in vitro with Bryostatin/ Ionomycin for 18 hours, and were grown in either Interleukin-2 (IL-2) or combination of Interleukin-7 and Interleukin-15 (IL-7/IL-15) for 13 days, (cells grown in IL-2 called IL2 cells, and cells grown in IL7/15 called IL7/15 cells). In order to validate the methodology and to offer future clinical translation, both direct and indirect cell labeling methods were expanded and employed. The first method was based on direct in vitro cell labeling by lipophilic near-infrared (NIR) fluorescent probe, 1,1- dioctadecyltetramethyl indotricarbocyanine iodide, (DiR), followed by intravenous (i.v.) injection into BALB/C mice for multi-spectral fluorescence imaging (MSFI). The second method was based on indirect labeling of T- lymphocytes through transduction of a reporter gene (cell cytoplasm labeling Herpes Simplex Virus type 1- thymidine kinase (HSV-1 tk). The product of this reporter gene is an enzyme (HSV-1TK) which phosphorylates a radio labeled substrate 2-fluoro-2-deoxy-1 β- D- arabinofuranosyl-5-iodouracil ([124I]-FIAU) for Positron Emission tomography (PET) imaging. ATP based cell viability assay, flow cytometry and interferon-γ (IFN-γ) ELISA were used to investigate if there are any changes in cell viability, proliferation and function respectively, before and after direct and indirect labeling. The results showed that cell viability, proliferation, and function of labeled 4T1 specific T-lymphocytes were not affected by labeling for direct labeling methods at DiR concentration of 320µg/ml. For the indirect labeling method, the viability and proliferation results showed that cell viability decreases as multiplicity of infectious (MOI) increases. In particular, at MOI of 10 almost all cells die 3 days post transduction. At MOI of 5, cells viability was ≤ 30% and at MOI of 2 was ≤ 60%. Cell viability was 80% at MOI of 1. The results of optical imaging were as follows: when the recipient mice with established 4T1 tumors were injected with DiR labeled 4T1 specific T-lymphocytes, the 4T1 specific T-lymphocytes (IL2 cells) infused into tumor-bearing mice showed high tumor retention, which peaked 3 or 6 days post infusion depending on the tumor size and persisted at the tumor site for 3 weeks. In contrast, IL7/15 cells showed lower signal at the tumor site and this peaked on day 8. On the other case when 4T1 tumor cells were implanted 1-week post-infusion of labeled T-lymphocytes. IL2 T-lymphocytes moved out of lymphoid compartments to the site of subsequent 4T1 inoculation within two hours and peaked on day 3 and the signal persisted for 2 more weeks. In contrast with infusion of IL7/15 cells, the signal was barely detected and did not show a similar trafficking pattern as with IL2 cells. The results of the indirect labeling method, PET reporter gene (PRG) system (HSV-1tk / [124I ] FIAU ) showed that both IL2 and IL7/15 cells were successfully transduced as verified ex vivo by real time PCR and western blot. T Cells transduction efficiency was assessed from cell uptake study in comparison to stable transduced Jurkat cells which have transduction efficiency of 100 %. Both IL2 and IL7/15 cells showed lower transduction efficiency (≤ 30%) compared to Jurkat cells. Consequently, PET imaging did not show a detectable signal of transduced T cells in vivo. Biodistribution study was carried out on day 3 post [124I]-FIAU injections. Results were consistent with the optical imaging results, except for IL7/15 cells. Transduced and untransduced IL2 and IL7/15 cells were labeled with DiR and injected ( i.v.) into Balb / C mice and then imaged by both imaging modalities (MSFI and PET) at the same time. MSFI images of transduced IL2 cell showed detectable signal starting from 2 hours, peaked at 72 hours and persisted up to 2 weeks, while IL7/15 cells were detectable at the tumor site starting at 24 hours, peaked at 72 hours and persisted up to 2 weeks. By the end of this study animals were dissected and tissue activities were counted using gamma counting and expressed as % Injected dose/gram of tissue (%ID/gm). Transduced IL2 and IL7/15 cells showed higher %ID/gm than other organs at lungs, liver, spleen, tumor, lymph nodes and bone/bone marrow. IL7/15 cells compared to IL2 cells showed higher %ID/gm at same organs. Neither IL2 nor IL7/15 untransduced DiR labeled cells showed any activity at tumor site, and their activities at other organs was very low compared to transduced cells. To investigate whether labeled T-lymphocytes will localize at tumor metastases or not, and to study the difference in their migration patterns to the tumor site versus tumor metastases, 4T1 tumor cells were successfully transduced with HSV-1tk as confirmed by RT-PCR , western blot and cell uptake study. Transduced 4T1 cells were implanted in the right flank or in the mammary fat pad of the mouse. Serial PET imaging was carried out in the third and fourth week post tumor implantation to know when the tumor will metastasizes. PET imaging showed only signal at the tumor site and no metastasis were detected.
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Soldà, Alice <1986&gt. "Electrochemical imaging of living cell metabolism: investigation on Warburg effect in cancer." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/7072/1/Solda_Alice_tesi.pdf.

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Cancer is one of the principal causes of death in the world; almost 8.2 million of deaths were counted in 2012. Emerging evidences indicate that most of the tumors have an increased glycolytic rate and a detriment of oxidative phosphorylation to support abnormal cell proliferation; this phenomenon is known as aerobic glycolysis or Warburg effect. This switching toward glycolysis implies that cancer tissues metabolize approximately tenfold more glucose to lactate in a given time and the amount of lactate released from cancer tissues is much greater than from normal ones. In view of these fundamental discoveries alterations of the cellular metabolism should be considered a crucial hallmark of cancer. Therefore, the investigation of the metabolic differences between normal and transformed cells is important in cancer research and it might find clinical applications. The aim of the project was to investigate the cellular metabolic alterations at single cell level, by monitoring glucose and lactate, in order to provide a better insight in cancer research. For this purpose, electrochemical techniques have been applied. Enzyme-based electrode biosensors for lactate and glucose were –ad hoc- optimized within the project and used as probes for Scanning Electrochemical Microscopy (SECM). The UME biosensor manufacturing and optimization represented a consistent part of the work and a full description of the sensor preparation protocols and of the characterization methods employed is reported. This set-up (SECM used with microbiosensor probes) enabled the non-invasive study of cellular metabolism at single cell level. The knowledge of cancer cell metabolism is required to design more efficient treatment strategies.
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Soldà, Alice <1986&gt. "Electrochemical imaging of living cell metabolism: investigation on Warburg effect in cancer." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/7072/.

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Cancer is one of the principal causes of death in the world; almost 8.2 million of deaths were counted in 2012. Emerging evidences indicate that most of the tumors have an increased glycolytic rate and a detriment of oxidative phosphorylation to support abnormal cell proliferation; this phenomenon is known as aerobic glycolysis or Warburg effect. This switching toward glycolysis implies that cancer tissues metabolize approximately tenfold more glucose to lactate in a given time and the amount of lactate released from cancer tissues is much greater than from normal ones. In view of these fundamental discoveries alterations of the cellular metabolism should be considered a crucial hallmark of cancer. Therefore, the investigation of the metabolic differences between normal and transformed cells is important in cancer research and it might find clinical applications. The aim of the project was to investigate the cellular metabolic alterations at single cell level, by monitoring glucose and lactate, in order to provide a better insight in cancer research. For this purpose, electrochemical techniques have been applied. Enzyme-based electrode biosensors for lactate and glucose were –ad hoc- optimized within the project and used as probes for Scanning Electrochemical Microscopy (SECM). The UME biosensor manufacturing and optimization represented a consistent part of the work and a full description of the sensor preparation protocols and of the characterization methods employed is reported. This set-up (SECM used with microbiosensor probes) enabled the non-invasive study of cellular metabolism at single cell level. The knowledge of cancer cell metabolism is required to design more efficient treatment strategies.
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Ronteix, Gustave. "Inferring cell-cell interactions from quantitative analysis of microscopy images." Thesis, Institut polytechnique de Paris, 2021. http://www.theses.fr/2021IPPAX111.

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Les systèmes biologiques sont bien plus que la somme de leurs constituants. En effet, ils sont souvent caractérisés par des comportements macroscopiques complexes résultant de boucles d'interactions et de rétroactions. Par exemple, la régulation et le rejet éventuel des tumeurs par le système immunitaire est le résultat de multiples réseaux de régulation, influençant à la fois le comportement des cellules cancéreuses et immunitaires. Pour simuler ces effets complexes in-vitro, j'ai conçu une puce microfluidique permettant de confronter des sphéroïdes de mélanome à de multiples cellules T et d'observer les interactions qui en résultent avec une haute résolution spatio-temporelle et sur de longues périodes de temps. En utilisant de l'analyse d'images avancée, combinée à des modèles mathématiques, je démontre qu'une boucle de rétroaction positive conduit l'accumulation de cellules T sur la tumeur, ayant pour conséquence une fragmentation accrue des sphéroïdes. Cette étude met en lumière l'initiation de la réponse immunitaire à l'échelle de la cellule unique : elle montre que même le tout premier contact entre une cellule T et un sphéroïde tumoral augmente la probabilité que la cellule T suivante arrive sur la tumeur. Elle montre également qu'il est possible de récapituler des comportements antagonistes complexes in-vitro, ce qui ouvre la voie à l'élaboration de protocoles plus sophistiqués, impliquant par exemple un micro-environnement tumoral plus complexe.De nombreux processus biologiques sont le résultat d'interactions entre de multiples types de cellules, en particulier au cours du développement. Le foie fœtal est le lieu de la maturation et de l'expansion du système hématopoïétique, mais on sait peu de choses sur sa structure et son organisation. De nouveaux protocoles expérimentaux ont été récemment mis au point pour imager cet organe et j'ai développé des outils pour interpréter et quantifier ces données, permettant la construction d'un "réseau jumeau" de chaque foie fœtal. Cette méthode permet de combiner les échelles unicellulaire et de l'organe dans une seule analyse, révélant l'accumulation de cellules myéloïdes autour des vaisseaux sanguins irriguant le foie fœtal aux derniers stades du développement de l'organe. À l'avenir, cette technique permettra d'analyser précisément les environnements de cellules d'intérêt de manière quantitative. Ceci pourrait à son tour nous aider à comprendre les étapes du développement de types cellulaires cruciaux tels que les cellules souches hématopoïétiques.Les interactions entre les bactéries et leur environnement sont essentielles pour comprendre l'émergence de comportements collectifs complexes tels que la formation de biofilms. Un mécanisme d'intérêt est celui de la rhéotaxie, par lequel le mouvement bactérien est entraîné par les gradients de la contrainte de cisaillement du fluide dans lequel les cellules se déplacent. J'ai développé une méthode pour calculer les équations semi-analytiques guidant le mouvement des bactéries dans la contrainte de cisaillement. Ces équations prédisent des comportements qui ne sont pas observés expérimentalement, mais la divergence est résolue une fois que la diffusion rotationnelle est prise en compte. Les résultats expérimentaux correspondent bien à la prédiction théorique : les bactéries dans les gouttelettes se séparent de manière asymétrique lorsqu'un cisaillement est généré dans le milieu
In his prescient article “More is different”, P. W. Anderson counters the reductionist argument by highlighting the crucial role of emergent properties in science. This is particularly true in biology, where complex macroscopic behaviours stem from communication and interaction loops between much simpler elements. As an illustration, I hereby present three different instances in which I developed and used quantitative methods in order to learn new biological processes.For instance, the regulation and eventual rejection of tumours by the immune system is the result of multiple positive and negative regulation networks, influencing both the behaviour of the cancerous and immune cells. To mimic these complex effects in-vitro, I designed a microfluidic assay to challenge melanoma tumour spheroids with multiple T cells and observe the resulting interactions with high spatiotemporal resolution over long (>24h) periods of time. Using advanced image analysis combined with mathematical modelling I demonstrate that a positive feedback loop drives T cell accumulation to the tumour site, leading to enhanced spheroid fragmentation. This study sheds light on the initiation if the immune response at the single cell scale: showing that even the very first contact between T cell and tumour spheroid increases the probability of the next T cell to come to the tumour. It also shows that it is possible to recapitulate complex antagonistic behaviours in-vitro, which paves the way for the elaboration of more sophisticated protocols, involving for example a more complex tumour micro-environment.Many biological processes are the result of complex interactions between cell types, particularly so during development. The foetal liver is the locus of the maturation and expansion of the hematopoietic system, yet little is known about its structure and organisation. New experimental protocols have been recently developed to image this organ and I developed tools to interpret and quantify these data, enabling the construction of a “network twin” of each foetal liver. This method makes it possible to combine the single-cell scale and the organ scale in the analysis, revealing the accumulation of myeloid cells around the blood vessels irrigating the foetal liver at the final stages of organ development. In the future, this technique will make it possible to analyse precisely the environmental niches of cell types of interest in a quantitative manner. This in turn could help us understand the developmental steps of crucial cell types such as hematopoietic stem cells.The interactions between bacteria and their environment is key to understanding the emergence of complex collective behaviours such a biofilm formation. One mechanism of interest is that of rheotaxis, whereby bacterial motion is driven by gradients in the shear stress of the fluid the cells are moving in. I developed a framework to calculate the semi-analytical equations guiding bacteria movement in shear stress. These equations predict behaviours that aren’t observed experimentally, but the discrepancy is solved once rotational diffusion is taken into account. Experimental results are well-fitted by the theoretical prediction: bacteria in droplets segregate asymmetrically when a shear is generated in the media.Although relating to very different topics, these three studies highlight the pertinence of quantitative approaches for understanding complex biological phenomena: biological systems are more than the sum of their constituents.a
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Books on the topic "Cancer Cell Imaging"

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1962-, Hermans R., ed. Squamous cell cancer of the neck. Cambridge: Cambridge University Press, 2008.

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Gupta, Anubha, and Ritu Gupta, eds. ISBI 2019 C-NMC Challenge: Classification in Cancer Cell Imaging. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0798-4.

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1948-, Rankin Sheila, ed. Carcinoma of the esophagus. New York: Cambridge University Press, 2008.

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1943-, Ford Richard J., Maizel Abby L, and M.D. Anderson Hospital and Tumor Institute., eds. Mediators in cell growth and differentiation. New York: Published for the University of Texas M.D. Anderson Hospital and Tumor Institute at Houston, Houston, Tex., by Raven Press, 1985.

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1940-, Hayat M. A., ed. Lung and breast carcinomas. Amsterdam: Elsevier, Academic Press, 2008.

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National Cancer Institute (U.S.). Network for Translational Research (NTR): Optical imaging in multimodal platforms (U54) : imaging from the cellular to organ level. Washington, D.C.]: U.S. Dept. of Health and Human Services, National Institutes of Health, National Cancer Institute, 2011.

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National Cancer Institute (U.S.). Network for Translational Research (NTR): Optical imaging in multimodal platforms (U54). [Washington, D.C.]: U.S. Dept. of Health and Human Services, National Institutes of Health, National Cancer Institute, 2009.

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In vivo cellular imaging using fluorescent proteins: Methods and protocols. New York: Humana Press, 2012.

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W, Berger, ed. Metabolic control in diabetes mellitus ; Beta adrenoceptor blocking drugs ; NMR analysis of cancer cells ; Immunoassay in the clinical laboratory ; Cyclosporine. Berlin: Springer-Verlag, 1986.

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Hermans, R. Squamous Cell Cancer of the Neck. Cambridge University Press, 2008.

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Book chapters on the topic "Cancer Cell Imaging"

1

Martin, Francis L. "Stem Cell Imaging." In Encyclopedia of Cancer, 1–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-27841-9_7163-3.

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Carloni, Vinicio. "Live Cell Imaging." In Encyclopedia of Cancer, 1–5. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-27841-9_7167-4.

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Martin, Francis L. "Stem Cell Imaging." In Encyclopedia of Cancer, 4331–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-46875-3_7163.

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Carloni, Vinicio. "Live Cell Imaging." In Encyclopedia of Cancer, 2528–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-46875-3_7167.

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Ravenel, James G. "Small Cell Carcinoma." In Lung Cancer Imaging, 79–88. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-60761-620-7_7.

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Costa, Angela Margarida, and Maria José Oliveira. "Cancer cell invadopodia." In Fluorescence Imaging and Biological Quantification, 299–315. Boca Raton : Taylor & Francis, 2017.: CRC Press, 2017. http://dx.doi.org/10.1201/9781315121017-16.

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Costa, Angela, and Maria Oliveira. "Cancer cell invadopodia." In Fluorescence Imaging and Biological Quantification, 299–315. Taylor & Francis Group, 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742: CRC Press, 2017. http://dx.doi.org/10.1201/9781315121017-19.

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Yaddanapudi, Kavitha. "Non-small Cell Lung Cancer." In PET/MR Imaging, 81–82. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65106-4_35.

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Matthews, Robert, and Rajesh Gupta. "Invasive Small Cell Bladder Cancer." In PET/MR Imaging, 207–9. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65106-4_90.

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Yu, Jian Q., and Yamin Dou. "Molecular Imaging for Renal Cell Carcinoma." In Renal Cancer, 99–118. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24378-4_6.

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Conference papers on the topic "Cancer Cell Imaging"

1

Hosseini, Poorya, Sabia Z. Abidi, Gregory J. Kato, Ming Dao, Zahid Yaqoob, and Peter T. C. So. "Biophysical markers of Sickle Cell Disease at Individual Cell Level." In Cancer Imaging and Therapy. Washington, D.C.: OSA, 2016. http://dx.doi.org/10.1364/cancer.2016.jtu3a.44.

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Saklayen, Nabiha, Marinna Madrid, Marinus Huber, Bi Hai, Alexander Raun, Daryl I. Vulis, Valeria Nuzzo, and Eric Mazur. "Plasmonic Intracellular Delivery for Cell Therapy." In Cancer Imaging and Therapy. Washington, D.C.: OSA, 2016. http://dx.doi.org/10.1364/cancer.2016.cth2a.3.

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Weilguni, Michael, Walter Smetana, Michael Edetsberger, and Gottfried Kohler. "Bladder cancer cell imaging system." In 2009 32nd International Spring Seminar on Electronics Technology (ISSE). IEEE, 2009. http://dx.doi.org/10.1109/isse.2009.5206970.

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Alhallak, Kinan, Lisa Rebello, and Narasimhan Rajaram. "Optical Imaging of Cancer Cell Metabolism in Murine Metastatic Breast Cancer." In Cancer Imaging and Therapy. Washington, D.C.: OSA, 2016. http://dx.doi.org/10.1364/cancer.2016.jm3a.34.

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Zhang, Chi, Soumik Siddhanta, Chao Zheng, and Ishan Barman. "Probing nanoscopic cell surface areas for rapid and labelfree plasmon enhanced Raman detection." In Cancer Imaging and Therapy. Washington, D.C.: OSA, 2016. http://dx.doi.org/10.1364/cancer.2016.jm3a.53.

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Berzins, Juris, Talivaldis Freivalds, I. Springis, and Ilgar Zitare. "Computer modeling of lung-cancer cell populations: light microscopic cell nucleus structure image analysis." In Medical Imaging 1993, edited by R. Gilbert Jost. SPIE, 1993. http://dx.doi.org/10.1117/12.152921.

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Mathieu, Evelien, Pol Van Dorpe, Tim Stakenborg, Chengxun Liu, and Liesbet Lagae. "Confocal Raman imaging for cancer cell classification." In SPIE Photonics Europe, edited by Jürgen Popp, Valery V. Tuchin, Dennis L. Matthews, Francesco S. Pavone, and Paul Garside. SPIE, 2014. http://dx.doi.org/10.1117/12.2052340.

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Marvdashti, Tahereh, Lian Duan, Sumaira Z. Aasi, Jean Y. Tang, and Audrey K. Ellerbee Bowden. "Machine-learning detection of basal cell carcinoma in human skin using polarization sensitive optical coherence tomography." In Cancer Imaging and Therapy. Washington, D.C.: OSA, 2016. http://dx.doi.org/10.1364/cancer.2016.jm4a.5.

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Xu, Xiaochun, Lagnojita Sinha, Jialing Xiang, and Kenneth M. Tichauer. "Quantification of cell surface receptor in live tissue culture using a paired-agent stain and rinse approach." In Cancer Imaging and Therapy. Washington, D.C.: OSA, 2016. http://dx.doi.org/10.1364/cancer.2016.jm3a.52.

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Xing, Fuyong, and Lin Yang. "Robust cell segmentation for non-small cell lung cancer." In 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013). IEEE, 2013. http://dx.doi.org/10.1109/isbi.2013.6556493.

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Reports on the topic "Cancer Cell Imaging"

1

Balatoni, Julius A. New Positron-Emitting Probe for Imaging Cell Proliferation in Breast Cancer. Fort Belvoir, VA: Defense Technical Information Center, August 2005. http://dx.doi.org/10.21236/ada446271.

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Drescher, Charles. Targeting Cell Surface Proteins in Molecular Photoacoustic Imaging to Detect Ovarian Cancer Early. Fort Belvoir, VA: Defense Technical Information Center, July 2012. http://dx.doi.org/10.21236/ada567976.

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Drescher, Charles W. Targeting Cell Surface Proteins in Molecular Photoacoustic Imaging to Detect Ovarian Cancer Early. Fort Belvoir, VA: Defense Technical Information Center, July 2013. http://dx.doi.org/10.21236/ada591911.

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Drescher, Charles W. Targeting Cell Surface Proteins in Molecular Photoacoustic Imaging to Detect Ovarian Cancer Early. Fort Belvoir, VA: Defense Technical Information Center, July 2011. http://dx.doi.org/10.21236/ada553529.

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Deng, Chun, Zhenyu Zhang, Zhi Guo, Hengduo Qi, Yang Liu, Haimin Xiao, and Xiaojun Li. Assessment of intraoperative use of indocyanine green fluorescence imaging on the number of lymph node dissection during minimally invasive gastrectomy: a systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2021. http://dx.doi.org/10.37766/inplasy2021.11.0062.

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Review question / Objective: Whether is indocyanine green fluorescence imaging-guided lymphadenectomy feasible to improve the number of lymph node dissections during radical gastrectomy in patients with gastric cancer undergoing curative resection? Condition being studied: Gastric cancer was the sixth most common malignant tumor and the fourth leading cause of cancer-related death in the world. Radical lymphadenectomy was a standard procedure in radical gastrectomy for gastric cancer. The retrieval of more lymph nodes was beneficial for improving the accuracy of tumor staging and the long-term survival of patients with gastric cancer. Indocyanine green(ICG) near-infrared fluorescent imaging has been found to provide surgeons with effective visualization of the lymphatic anatomy. As a new surgical navigation technique, ICG near-infrared fluorescent imaging was a hot spot and had already demonstrated promising results in the localization of lymph nodes during surgery in patients with breast cancer, non–small cell lung cancer, and gastric cancer. In addition, ICG had increasingly been reported in the localization of tumor, lymph node dissection, and the evaluation of anastomotic blood supply during radical gastrectomy for gastric cancer. However, it remained unclear whether ICG fluorescence imaging would assist surgeons in performing safe and sufficient lymphadenectomy.
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Alavi, Abass. PET-FDG Imaging in Metastatic Breast Cancer Treated with High Dose Chemotherapy and Stem Cell Support. Fort Belvoir, VA: Defense Technical Information Center, September 1996. http://dx.doi.org/10.21236/ada319987.

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Venedicto, Melissa, and Cheng-Yu Lai. Facilitated Release of Doxorubicin from Biodegradable Mesoporous Silica Nanoparticles. Florida International University, October 2021. http://dx.doi.org/10.25148/mmeurs.009774.

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Cervical cancer is one of the most common causes of cancer death for women in the United States. The current treatment with chemotherapy drugs has significant side effects and may cause harm to healthy cells rather than cancer cells. In order to combat the potential side effects, nanoparticles composed of mesoporous silica were created to house the chemotherapy drug doxorubicin (DOX). The silica network contains the drug, and a pH study was conducted to determine the conditions for the nanoparticle to disperse the drug. The introduction of disulfide bonds within the nanoparticle created a framework to efficiently release 97% of DOX in acidic environments and 40% release in neutral environments. The denotation of acidic versus neutral environments was important as cancer cells are typically acidic. The chemistry was proved with the incubation of the loaded nanoparticle into HeLa cells for a cytotoxicity report and confocal imaging. The use of the framework for the anticancer drug was shown to be effective for the killing of cancerous cells.
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Tsourkas, Andrew. Magnetic Nanoparticle-Based Imaging of RNA Transcripts in Breast Cancer Cells. Fort Belvoir, VA: Defense Technical Information Center, June 2008. http://dx.doi.org/10.21236/ada487360.

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Tsourkas, Andrew. Magnetic Nanoparticle-Based Imaging of RNA Transcripts in Breast Cancer Cells. Fort Belvoir, VA: Defense Technical Information Center, June 2009. http://dx.doi.org/10.21236/ada537361.

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Sharp, Zelton D. Quantifying ER Function Using High-Throughput Imaging in Breast and Other Cancer Cells. Fort Belvoir, VA: Defense Technical Information Center, September 2008. http://dx.doi.org/10.21236/ada502583.

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