Publications by authors named "Jaena Park"

The control of antiferromagnets with ultrashort optical pulses has emerged as a prominent field of research. Tailored laser excitation can launch coherent spin waves at terahertz frequencies, yet a comprehensive description of their generation mechanisms is still lacking despite extensive efforts. Using terahertz emission spectroscopy, we investigate the generation of a coherent magnon mode in the van der Waals antiferromagnet NiPS_{3} under a range of photoexcitation conditions.

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Irreproducibility in molecular optical sectioning microscopy has hindered the transformation of acquired digital images from qualitative descriptions to quantitative data. Although numerous tools, metrics, and phantoms have been developed, accurate quantitative comparisons of data from different microscopy systems with diverse acquisition conditions remains a challenge. Here, we develop a simple tool based on an absolute measurement of bulk fluorophore solutions with related Poisson photon statistics, to overcome this obstacle.

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Controlling the functional properties of quantum materials with light has emerged as a frontier of condensed-matter physics, leading to the discovery of various light-induced phases of matter, such as superconductivity, ferroelectricity, magnetism and charge density waves. However, in most cases, the photoinduced phases return to equilibrium on ultrafast timescales after the light is turned off, limiting their practical applications. Here we use intense terahertz pulses to induce a metastable magnetization with a remarkably long lifetime of more than 2.

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Extracellular vesicles (EVs) serve as crucial mediators of cell-to-cell communication in normal physiology as well as in diseased states; they have been largely studied in regard to their role in cancer progression. However, the mechanisms by which their biogenesis and secretion are regulated by metabolic or endocrine factors remain unknown. Here, we delineate a mechanism by which EV secretion is regulated by a cholesterol metabolite, 27-hydroxycholesterol (27HC), where treatment of myeloid immune cells (RAW 264.

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Background: Although the effects on neural activation and glucose consumption caused by opiates such as morphine are known, the metabolic machinery underlying opioid use and misuse is not fully explored. Multiphoton microscopy (MPM) techniques have been developed for optical imaging at high spatial resolution. Despite the increased use of MPM for neural imaging, the use of intrinsic optical contrast has seen minimal use in neuroscience.

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Extracellular vesicles (EVs) serve as crucial mediators of cell-to-cell communication in normal physiology as well as in diseased states, and have been largely studied in regard to their role in cancer progression. However, the mechanisms by which their biogenesis and secretion are regulated by metabolic or endocrine factors remain unknown. Here, we delineate a mechanism by which EV secretion is regulated by a cholesterol metabolite, 27-Hydroxycholesterol (27HC), where treatment of myeloid immune cells (RAW 264.

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A polariton is a fundamental quasiparticle that arises from strong light-matter interaction and as such has attracted wide scientific and practical interest. When light is strongly coupled to the crystal lattice, it gives rise to phonon-polaritons (PPs), which have been proven useful in the dynamical manipulation of quantum materials and the advancement of terahertz technologies. Yet, current detection and characterization methods of polaritons are still limited.

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Extracellular vesicles (EVs) have been implicated in metastasis and proposed as cancer biomarkers. However, heterogeneity and small size makes assessments of EVs challenging. Often, EVs are isolated from biofluids, losing spatial and temporal context and thus lacking the ability to access EVs in situ in their native microenvironment.

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Nonlinear microscopy encompasses several imaging techniques that leverage laser technology to probe intrinsic molecules of biological specimens. These native molecules produce optical fingerprints that allow nonlinear microscopes to reveal the chemical composition and structure of cells and tissues in a label-free and non-destructive fashion, information that enables a plethora of applications, e.g.

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Pancreatic cancer is a devastating disease often detected at later stages, necessitating swift and effective chemotherapy treatment. However, chemoresistance is common and its mechanisms are poorly understood. Here, label-free multi-modal nonlinear optical microscopy was applied to study microstructural and functional features of pancreatic tumors in vivo to monitor inter- and intra-tumor heterogeneity and treatment response.

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Hematoxylin and eosin (H&E) staining, the century-old technique, has been the gold standard tool for pathologists to detect anomalies in tissues and diseases such as cancer. H&E staining is a cumbersome, time-consuming process that delays and wastes precious minutes during an intraoperative diagnosis. However, even in the modern era, real-time label-free imaging techniques such as simultaneous label-free autofluorescence multiharmonic (SLAM) microscopy have delivered several more layers of information to characterize a tissue with high precision.

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Article Synopsis
  • Recent advancements in optical bioimaging have generated detailed structural and functional data from biological samples, which require advanced computational tools for pattern recognition and relationship analysis in biomedical contexts.
  • A weakly supervised deep learning framework is introduced, which utilizes a multiple instance learning classifier and model interpretation techniques to identify regions of interest in images with coarsely labeled data, aiding in optical signature discovery.
  • Applied to breast cancer research, this framework achieved a high accuracy in cancer diagnosis and uncovered novel optical signatures in normal-appearing breast tissue, offering new insights into cancer biology and the potential for application in various imaging tasks.
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Strong interactions between different degrees of freedom lead to exotic phases of matter with complex order parameters and emergent collective excitations. Conventional techniques, such as scattering and transport, probe the amplitudes of these excitations, but they are typically insensitive to phase. Therefore, novel methods with phase sensitivity are required to understand ground states with phase modulations and interactions that couple to the phase of collective modes.

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Extracellular vesicles (EVs) have been studied for their potential applications in cancer screening, diagnosis, and treatment monitoring. Most studies have focused on the bulk content of EVs; however, it is also informative to investigate their metabolic status, and changes under different physiological and environmental conditions. In this study, noninvasive, multimodal, label-free nonlinear optical microscopy was used to evaluate the optical redox ratio of large EVs (microvesicles) isolated from the urine of 11 dogs in three cohorts (4 healthy, 4 transitional cell carcinoma (TCC) of the bladder, and 3 prostate cancer).

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A recent theranostic approach to address Alzheimer's disease (AD) utilizes multifunctional targets that both tag and negate the toxicity of AD biomarkers. These compounds, which emit fluorescence with both an activation and a spectral shift in the presence of Aβ, were previously characterized with traditional fluorescence imaging for binary characterization. However, these multifunctional compounds have broad and dynamic emission spectra that are dependent on factors such as the local environment, presence of Aβ deposits, etc.

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Significance: Needle biopsy (NB) procedures are important for the initial diagnosis of many types of cancer. However, the possibility of NB specimens being unable to provide diagnostic information, (i.e.

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Characterizing the performance of fluorescence microscopy and nonlinear imaging systems is an essential step required for imaging system optimization and quality control during longitudinal experiments. Emerging multimodal nonlinear imaging techniques require a new generation of microscopy calibration targets that are not susceptible to bleaching and can provide a contrast across the multiple modalities. Here, we present a nanodiamond-based calibration target for microscopy, designed for facilitating reproducible measurements at the object plane.

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Label-free intravital optical imaging is an emergent visualization tool that is not only useful for basic biological research, but also for preclinical research with potential translational clinical applications. The complete absence of exogenous labeling or genetic alterations avoids plausible harmful perturbation to biological processes and the pristine physiological environment, as the endogenous biomolecules enable intrinsic imaging contrasts to interrogate various live multicellular organisms of interest. This tool has evolved from single-modality, single-photon imaging into multimodal multiphoton imaging, in order to gain different contrasts simultaneously during imaging sessions, and permit long-term time-lapse studies that have begun to spawn more diverse applications.

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Cholesterol has been implicated in the clinical progression of breast cancer, a disease that continues to be the most commonly diagnosed cancer in women. Previous work has identified the cholesterol metabolite 27-hydroxycholesterol (27HC) as a major mediator of the effects of cholesterol on breast tumor growth and progression. 27HC can act as an estrogen receptor (ER) modulator to promote the growth of ERα+ tumors, and as a liver X receptor (LXR) ligand in myeloid immune cells to establish an immune-suppressive program.

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Intraoperative imaging in surgical oncology can provide information about the tumor microenvironment as well as information about the tumor margin. Visualizing microstructural features and molecular and functional dynamics may provide important diagnostic and prognostic information, especially when obtained in real-time at the point-of-procedure. A majority of current intraoperative optical techniques are based on the use of the labels, such as fluorescent dyes.

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Isolation of pure extracellular vesicles (EVs), especially from blood, has been a major challenge in the field of EV research. The presence of lipoproteins and soluble proteins often hinders the isolation of high purity EVs upon utilization of conventional separation methods. To circumvent such problems, we designed a single-step dual size-exclusion chromatography (dSEC) column for effective isolation of highly pure EVs from bone marrow derived human plasma.

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Recent advances in label-free virtual histology promise a new era for real-time molecular diagnosis in the operating room and during biopsy procedures. To take full advantage of the rich, multidimensional information provided by these technologies, reproducible and reliable computational tools that could facilitate the diagnosis are in great demand. In this study, we developed a deep-learning-based framework to recognize cancer versus normal human breast tissue from real-time label-free virtual histology images, with a tile-level AUC (area under receiver operating curve) of 95% and slide-level AUC of 100% on unseen samples.

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Despite extensive interest, extracellular vesicle (EV) research remains technically challenging. One of the unexplored gaps in EV research has been the inability to characterize the spatially and functionally heterogeneous populations of EVs based on their metabolic profile. In this paper, we utilize the intrinsic optical metabolic and structural contrast of EVs and demonstrate in vivo/in situ characterization of EVs in a variety of unprocessed (pre)clinical samples.

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Rapid diagnosis and quarantine of influenza virus mutant-infected people is critical to contain the fatal viral infection spread because effective antiviral drugs are normally not available. Conventional methods, however, cannot be used for the diagnosis because these methods need predefined labels, likely also unavailable for just emerging viruses. Here, we propose label-free identification of cells infected with different influenza viruses based on surface-enhanced Raman spectroscopy (SERS) and principal component analysis (PCA).

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Exosomes, which are nanovesicles secreted by cells, are promising biomarkers for cancer diagnosis and prognosis, based on their specific surface protein compositions. Here, we demonstrate the correlation of nonsmall cell lung cancer (NSCLC) cell-derived exosomes and potential protein markers by unique Raman scattering profiles and principal component analysis (PCA) for cancer diagnosis. On the basis of surface enhanced Raman scattering (SERS) signals of exosomes from normal and NSCLC cells, we extracted Raman patterns of cancerous exosomes by PCA and clarified specific patterns as unique peaks through quantitative analysis with ratiometric mixtures of cancerous and normal exosomes.

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