Diagnosis and classification of kidney transplant rejection using machine learning-assisted surface-enhanced Raman spectroscopy using a single drop of serum.

The quest to reduce kidney transplant rejection has emphasized the urgent requirement for the development of non-invasive, precise diagnostic technologies. These technologies aim to detect antibody-mediated rejection (ABMR) and T-cell-mediated rejection (TCMR), which are asymptomatic and pose a risk of potential kidney damage. The protocols for managing rejection caused by ABMR and TCMR differ, and diagnosis has traditionally relied on invasive biopsy procedures. Therefore, a convergence system using a nano-sensing chip, Raman spectroscopy, and AI technology was introduced to facilitate diagnosis using serum samples obtained from patients with no major abnormality, ABMR, and TCMR after kidney transplantation. Tissue biopsy and Banff score analysis were performed across the groups for validation, and 5 µL of serum obtained at the same time was added onto the Au-ZnO nanorod-based Surface-Enhanced Raman Scattering sensing chip to obtain Raman spectroscopy signals. The accuracy of machine learning algorithms for principal component-linear discriminant analysis and principal component-partial least squares discriminant analysis was 93.53% and 98.82%, respectively. The collagen (an indicative of kidney injury), creatinine, and amino acid-derived signals (markers of kidney function) contributed to this accuracy; however, the high accuracy was primarily due to the ability of the system to analyze a broad spectrum of various biomarkers.

Early-stage diagnosis of bladder cancer using surface-enhanced Raman spectroscopy combined with machine learning algorithms in a rat model.

Early diagnosis and accurate assessment of tumor development facilitate early bladder cancer resection and initiation of drug therapy. This study enabled an early, accurate, label-free, noninvasive diagnosis of bladder tumors by analyzing nano-biomarkers in a single drop of urine through surface-enhanced Raman spectroscopy (SERS). In a standard N-butyl-N-4-hydroxybutyl nitrosamine-induced rat model of bladder cancer, cancer stage and polyp tumor development were monitored using a small endoscope with a diameter of 1.2 mm in a minimally invasive manner without the need to kill the rats. Samples were divided into cancer-free, early-stage, and polyp-form cancer. Training data were classified according to micro-cystoscopic 5-aminolevulinic acid fluorescence diagnosis, and specimens were postmortem verified through histopathological analysis. A drop of urine from each sample group was placed on an Au-coated zinc oxide nanoporous chip to filter nano-biomaterials and selectively enhance the Raman signals of nanoscale analytes via SERS. Principal component analysis was used to reduce the dimensionality of the collected Raman spectra, and partial least squares discriminant analysis was used to find diagnostic clusters based on the labeled samples. The combination of SERS and machine learning achieved an accuracy ≥99.6% in diagnosing both early- and polyp-stage bladder tumors. With an area under the receiver operating characteristic curve greater than 0.996, the accuracy of the diagnosis in the rat model suggests that SERS-based diagnostic methods are promising when coupled with machine learning. Low-cost, label-free, and noninvasive surface-enhanced Raman spectra are ideal for developing clinically relevant point-of-care diagnostic techniques.

Deep Learning Assisted Surface-Enhanced Raman Spectroscopy (SERS) for Rapid and Direct Nucleic Acid Amplification and Detection: Toward Enhanced Molecular Diagnostics.

Surface-enhanced Raman scattering (SERS) has evolved into a robust analytical technique capable of detecting a variety of biomolecules despite challenges in securing a reliable Raman signal. Conventional SERS-based nucleic acid detection relies on hybridization assays, but reproducibility and signal strength issues have hindered research on directly amplifying nucleic acids on SERS surfaces. This study introduces a deep learning assisted ZnO-Au-SERS-based direct amplification (ZADA) system for rapid, sensitive molecular diagnostics. The system employs a SERS substrate fabricated by depositing gold on uniformly grown ZnO nanorods. These nanorods create hot spots for the amplification of the target nucleic acids directly on the SERS surface, eliminating the need for postamplification hybridization and Raman reporters. The limit of detection of the ZADA system was superior to those of the conventional amplification methods. Clinical validation of the ZADA system with coronavirus disease 2019 (COVID-19) samples from human patients yielded a sensitivity and specificity of 92.31% and 81.25%, respectively. The integration of a deep learning program further enhanced sensitivity and specificity to 100% and reduced SERS analysis time, showcasing the potential of the ZADA system for rapid, label-free disease diagnosis via direct nucleic acid amplification and detection within 20 min.

Smartphone-Based Rigid Endoscopy Device with Hemodynamic Response Imaging and Laser Speckle Contrast Imaging.

Modern smartphones have been employed as key elements in point-of-care (POC) devices due to remarkable advances in their form factor, computing, and display performances. Recently, we reported a combination of the smartphone with a handheld endoscope using laser speckle contrast imaging (LSCI), suggesting potential for functional POC endoscopy. Here, we extended our work to develop a smartphone-combined multifunctional handheld endoscope using dual-wavelength LSCI. Dual-wavelength LSCI is used to monitor the changes in dynamic blood flow as well as changes in the concentration of oxygenated (HbO2), deoxygenated (Hbr), and total hemoglobin (HbT). The smartphone in the device performs fast acquisition and computation of the raw LSCI data to map the blood perfusion parameters. The flow imaging performance of the proposed device was tested with a tissue-like flow phantom, exhibiting a speckle flow index map representing the blood perfusion. Furthermore, the device was employed to assess the blood perfusion status from an exteriorized intestine model of rat in vivo during and after local ischemia, showing that blood flow and HbO2 gradually decreased in the ischemic region whereas hyperemia and excess increases in HbO2 were observed in the same region right after reperfusion. The results indicate that the combination of LSCI with smartphone endoscopy delivers a valuable platform for better understanding of the functional hemodynamic changes in the vasculatures of the internal organs, which may benefit POC testing for diagnosis and treatment of vascular diseases.

Fabry-Perot Interferometric Fiber-Optic Sensor for Rapid and Accurate Thrombus Detection.

We present a fiber-optic sensor based on the principles of a Fabry-Perot interferometer (FPI), which promptly, sensitively, and precisely detects blood clot formation. This sensor has two types of sensor tips; the first was crafted by splicing a tapered fiber into a single-mode fiber (SMF), where fine-tuning was achieved by adjusting the tapered diameter and length. The second type is an ultra-compact blood FPI situated on the core of a single-mode fiber. The sensor performance was evaluated via clot-formation-indicating spectrum shifts induced by the varied quantities of a thrombin reagent introduced into the blood. The most remarkable spectral sensitivity of the micro-tip fiber type was approximately 7 nm/µL, with a power sensitivity of 4.1 dB/µL, obtained with a taper fiber diameter and length of 55 and 300 µm, respectively. For the SMF type, spectral sensitivity was observed to be 8.7 nm/µL, with an optical power sensitivity of 0.4 dB/µL. This pioneering fiber-optic thrombosis sensor has the potential for in situ applications, healthcare, medical monitoring, harsh environments, and chemical and biological sensing. The study underscores the scope of optical technology in thrombus detection, establishing a platform for future medical research and application.

Label-free atherosclerosis diagnosis through a blood drop of apolipoprotein E knockout mouse model using surface-enhanced Raman spectroscopy validated by machine learning algorithm.

The direct preventative detection of flow-induced atherosclerosis remains a significant challenge, impeding the development of early treatments and prevention measures. This study proposes a method for diagnosing atherosclerosis in the carotid artery using nanometer biomarker measurements through surface-enhanced Raman spectroscopy (SERS) from single-drop blood samples. Atherosclerotic acceleration is induced in apolipoprotein E knockout mice which underwent a partial carotid ligation and were fed a high-fat diet to rapidly induce disturbed flow-induced atherosclerosis in the left common carotid artery while using the unligated, contralateral right carotid artery as control. The progressive atherosclerosis development of the left carotid artery was verified by micro-magnetic resonance imaging (micro-MRI) and histology in comparison to the right carotid artery. Single-drop blood samples are deposited on chips of gold-coated ZnO nanorods grown on silicon wafers that filter the nanometer markers and provide strong SERS signals. A diagnostic classifier was established based on principal component analysis (PCA), which separates the resultant spectra into the atherosclerotic and control groups. Scoring based on the principal components enabled the classification of samples into control, mild, and severe atherosclerotic disease. The PCA-based analysis was validated against an independent test sample and compared against the PCA-PLS-DA machine learning algorithm which is known for applicability to Raman diagnosis. The accuracy of the PCA modification-based diagnostic criteria was 94.5%, and that of the machine learning algorithm 97.5%. Using a mouse model, this study demonstrates that diagnosing and classifying the severity of atherosclerosis is possible using a single blood drop, SERS technology, and machine learning algorithm, indicating the detectability of biomarkers and vascular factors in the blood which correlate with the early stages of atherosclerosis development.

Influence of Chemical and Genetic Manipulations on Cellular Organelles Quantified by Label-Free Optical Diffraction Tomography.

Label-free optical diffraction tomography provides three-dimensional imaging of cells and organelles, along with their refractive index (RI) and volume. These physical parameters are valuable for quantitative and accurate analysis of the subcellular microenvironment and its connections to intracellular biological properties. In biological and biochemical cell analysis, various invasive cell manipulations are used, such as temperature change, chemical fixation, live cell staining with fluorescent dye, and gene overexpression of exogenous proteins. However, it is not fully understood how these various manipulations affect the physicochemical properties of different organelles. In this study, we investigated the impact of these manipulations on the cellular properties of single HeLa cells. We found that after cell fixation and an increase in temperature, the RI value of organelles, such as the nucleus and cytoplasm, significantly decreased overall. Interestingly, unlike the cell nuclei, cytoplasmic RI values were hardly detected after membrane permeation, indicating that only intracytoplasmic components were largely lost. Additionally, our findings revealed that the expression of GFP and GFP-tagged proteins significantly increased the RI values of organelles in living cells compared to the less effective RI changes observed with chemical fluorescence staining for cell organelles. The result demonstrates that distinct types of invasive manipulations can alter the microenvironment of organelles in different ways. Our study sheds new light on how chemical and genetic manipulations affect organelles.

Ten-year prognostic value of coronary CT angiography in asymptomatic patients with type 2 diabetes.

INTRODUCTION AND OBJECTIVES: The United Kingdom Prospective Diabetes Study (UKPDS) risk score has limited value for predicting coronary artery disease (CAD) events. We investigated the additive value of coronary computed tomography angiography (CCTA) on top of the UKPDS risk score in predicting 10-year adverse cardiac events in asymptomatic patients with type 2 diabetes. METHODS: We evaluated 589 asymptomatic diabetic patients without a history of CAD who underwent CCTA. The primary outcome was a composite of cardiac death, nonfatal myocardial infarction, unstable angina requiring hospitalization, and revascularization. We estimated the discrimination and reclassification ability for the prediction models, which included combinations of the UKPDS category, severity of stenosis, and coronary artery calcium score by CCTA. RESULTS: The incidence of the primary outcome was 12.4%. During 10 years of follow-up, patients without plaque by CCTA tended to have a low CAD event rate, while those with obstructive CAD tended to have a high event rate, irrespective of the baseline UKPDS risk category. The model that included only the UKPDS category had a Harrell's c-index of 0.658; adding the degree of stenosis to the model significantly increased the c-index by 0.066 (P=.004), while adding coronary artery calcium score increased the c-index by only 0.039 (P=.056). Overall, CCTA information in addition to the UKPDS risk category improved the reclassification rate for predicting the primary outcome. CONCLUSIONS: In asymptomatic patients with type 2 diabetes, CCTA information for CAD provided significant incremental discriminatory power beyond the UKPDS risk score category for predicting 10-year adverse coronary events.

Diagnosis of Ischemic Renal Failure Using Surface-Enhanced Raman Spectroscopy and a Machine Learning Algorithm.

To diagnose renal function using a biochip capable of detecting SERS and to assess Raman measurements taken from a bilateral renal ischemia model and the feasibility of early diagnosis was done. After generating a bilateral renal ischemia rat model, blood and urine were collected. After confirming the presence of renal injury and function, liquid drops were placed onto a Raman chip whose surface had been enhanced with Au-ZnO nanorods. SERS biomarkers that diffused into the nanogaps were selectively amplified. Raman signals varied based on the severity of the renal function, and these differences were confirmed statistically. These results confirm that renal ischemia leads to renal dysfunction and that surface-enhanced Raman spectroscopy and a machine learning algorithm can be used to track signals in the urine from the release of SERS biomarkers.

Synthesis and Electrochemical Performance of Microporous Hollow Carbon from Milkweed Pappus as Cathode Material of Lithium-Sulfur Batteries.

Microtube-like porous carbon (MPC) and tube-like porous carbon-sulfur (MPC-S) composites were synthesized by carbonizing milkweed pappus with sulfur, and they were used as cathodes for lithium-sulfur batteries. The morphology and uniformity of these materials were characterized using X-ray powder diffraction, Raman spectroscopy, scanning electron microscopy, transmission electron microscopy with an energy-dispersive X-ray analyzer, thermogravimetric analysis, and X-ray photoelectron spectrometry. The electrochemical performance of the MPC-S cathodes was measured using the charge/discharge cycling performance, C rate, and AC impedance. The composite cathodes with 93.8 wt.% sulfur exhibited a stable specific capacity of 743 mAh g-1 after 200 cycles at a 0.5 C.

Fluorescence-Based Microendoscopic Sensing System for Minimally Invasive In Vivo Bladder Cancer Diagnosis.

Bladder cancer is commonly diagnosed by evaluating the tissue morphology through cystoscopy, and tumor resection is used as the primary treatment approach. However, these methods are limited by lesion site specificity and resection margin, and can thereby fail to detect cancer lesions at early stages. Nevertheless, rapid diagnosis without biopsy may be possible through fluorescence sensing. Herein, we describe a minimally invasive imaging system capable of sensing even small tumors through a 1.2 mm diameter flexible fiber bundle microprobe. We demonstrate that this new device can be used for the early diagnosis of bladder cancer in rats. Bladder cancer was induced in rats using the carcinogen N-butyl-N-(4-hydroxybutyl)nitrosamine (BBN), and a togglable filter capable of PpIX fluorescence sensing was installed in the microendoscopic system. Following 5-aminolevulinic acid administration, tissue in the early stages of bladder cancer was successfully identified with fluorescence detection and confirmed with hematoxylin/eosin and ferrochelatase staining. Although the time required for BBN to induce bladder cancer varied between 3 and 4 weeks among the rats, the microendoscopic system allowed the minimally invasive follow-up on cancer development.

Compact Smartphone-Based Laser Speckle Contrast Imaging Endoscope Device for Point-of-Care Blood Flow Monitoring.

Laser speckle contrast imaging (LSCI) is a powerful visualization tool for quantifying blood flow in tissues, providing simplicity of configuration, ease of use, and intuitive results. With recent advancements, smartphone and camera technologies are suitable for the development of smartphone-based LSCI applications for point-of-care (POC) diagnosis. A smartphone-based portable LSCI endoscope system was validated for POC diagnosis of vascular disorders. The endoscope consisted of compact LED and laser illumination, imaging optics, and a flexible fiberscope assembled in a 3D-printed hand-held cartridge for access to body cavities and organs. A smartphone's rear camera was mounted thereto, enabling endoscopy, LSCI image acquisition, and processing. Blood flow imaging was calibrated in a perfused tissue phantom consisting of a microparticle solution pumped at known rates through tissue-mimicking gel and validated in a live rat model of BBN-induced bladder cancer. Raw LSCI images successfully visualized phantom flow: speckle flow index showed linearity with the pump flow rate. In the rat model, healthy and cancerous bladders were distinguishable in structure and vasculature. The smartphone-based low-cost portable mobile endoscope for monitoring blood flow and perfusion shows promise for preclinical applications and may be suitable for primary diagnosis at home or as a cost-effective POC testing assay.

Minimizing Motion Artifacts in Intravital Microscopy Using the Sedative Effect of Dexmedetomidine.

Among intravital imaging instruments, the intravital two-photon fluorescence excitation microscope has the advantage of enabling real-time 3D fluorescence imaging deep into cells and tissues, with reduced photobleaching and photodamage compared with conventional intravital confocal microscopes. However, excessive motion of organs due to involuntary movement such as breathing may result in out-of-focus images and severe fluorescence intensity fluctuations, which hinder meaningful imaging and analysis. The clinically approved alpha-2 adrenergic receptor agonist dexmedetomidine was administered to mice during two-photon fluorescence intravital imaging to alleviate this problem. As dexmedetomidine blocks the release of the neurotransmitter norepinephrine, pain is suppressed, blood pressure is reduced, and a sedation effect is observed. By tracking the quality of focus and stability of detected fluorescence in two-photon fluorescence images of fluorescein isothiocyanate-sensitized liver vasculature in vivo, we demonstrated that intravascular dexmedetomidine can reduce fluorescence fluctuations caused by respiration on a timescale of minutes in mice, improving image quality and resolution. The results indicate that short-term dexmedetomidine treatment is suitable for reducing involuntary motion in preclinical intravital imaging studies. This method may be applicable to other animal models.

Automated counting of cerebral penetrating vessels using optical coherence tomography images of a mouse brain in vivo.

RATIONALE AND OBJECTIVES: Penetrating blood vessels emanating from cortical surface vasculature and lying deep in the cortex are essential vascular conduits for the shuttling of blood from superficial pial vessels to the capillary beds in parenchyma for the nourishment of neuronal brain tissues. Locating and counting the penetrating vessels is beneficial for the quantification of a course of ischemia in blood occlusive events such as stroke. This paper seeks to demonstrate and validate a method for automated penetrating vessel counting that uses optical coherence tomography (OCT). MATERIALS AND METHODS: This paper proposes an OCT method that effectively identifies and grades the cortical penetrating vessels in perfusion. The key to the proposed method is the harnessing of vascular features found in the penetrating vessels, which are distinctive from those of other vessels. In particular, with an increase in the light attenuation and flow turbulence, the contrast in the mean projection of the OCT datacube decreases, whereas that in the maximum projection of the Doppler frequency variance datacube increases. By multiplying the inversion of the former with the latter, its binary thresholding is sufficient to highlight the penetrating vessels and allows for their counting over the projection image. RESULTS: A computational method that leverages the decrease in mean OCT projection intensity and the increase in Doppler frequency variance at the penetrating vessel is developed. It successfully identifies and counts penetrating vessels with a high accuracy of over 87%. The penetrating vessel density is observed to be significantly reduced in the mouse model of focal ischemic stroke. CONCLUSION: The OCT analysis is effective for counting penetrating blood vessels in mice brains and may be applied to the rapid diagnosis and treatment of stroke in stroke models of small animals.

Low-Dose Three-Dimensional Rotational Angiography for Evaluating Intracranial Aneurysms: Analysis of Image Quality and Radiation Dose.

OBJECTIVE: This study aimed to evaluate the image quality and dose reduction of low-dose three-dimensional (3D) rotational angiography (RA) for evaluating intracranial aneurysms. MATERIALS AND METHODS: We retrospectively evaluated the clinical data and 3D RA datasets obtained from 146 prospectively registered patients (male:female, 46:100; median age, 58 years; range, 19-81 years). The subjective image quality of 79 examinations obtained from a conventional method and 67 examinations obtained from a low-dose (5-seconds and 0.10-µGy/frame) method was assessed by two neurointerventionists using a 3-point scale for four evaluation criteria. The total image quality score was then obtained as the average of the four scores. The image quality scores were compared between the two methods using a noninferiority statistical testing, with a margin of -0.2 (i.e., score of low-dose group - score of conventional group). For the evaluation of dose reduction, dose-area product (DAP) and air kerma (AK) were analyzed and compared between the two groups. RESULTS: The mean total image quality score ± standard deviation of the 3D RA was 2.97 ± 0.17 by reader 1 and 2.95 ± 0.20 by reader 2 for conventional group and 2.92 ± 0.30 and 2.95 ± 0.22, respectively, for low-dose group. The image quality of the 3D RA in the low-dose group was not inferior to that of the conventional group according to the total image quality score as well as individual scores for the four criteria in both readers. The mean DAP and AK per rotation were 5.87 Gy-cm² and 0.56 Gy, respectively, in the conventional group, and 1.32 Gy-cm² (p < 0.001) and 0.17 Gy (p < 0.001), respectively, in the low-dose group. CONCLUSION: Low-dose 3D RA was not inferior in image quality and reduced the radiation dose by 70%-77% compared to the conventional 3D RA in evaluating intracranial aneurysms.

Intravital imaging and single cell transcriptomic analysis for engraftment of mesenchymal stem cells in an animal model of interstitial cystitis/bladder pain syndrome.

Mesenchymal stem cell (MSC) therapy is a promising treatment for various intractable disorders including interstitial cystitis/bladder pain syndrome (IC/BPS). However, an analysis of fundamental characteristics driving in vivo behaviors of transplanted cells has not been performed, causing debates about rational use and efficacy of MSC therapy. Here, we implemented two-photon intravital imaging and single cell transcriptome analysis to evaluate the in vivo behaviors of engrafted multipotent MSCs (M-MSCs) derived from human embryonic stem cells (hESCs) in an acute IC/BPS animal model. Two-photon imaging analysis was performed to visualize the dynamic association between engrafted M-MSCs and bladder vasculature within live animals until 28 days after transplantation, demonstrating the progressive integration of transplanted M-MSCs into a perivascular-like structure. Single cell transcriptome analysis was performed in highly purified engrafted cells after a dual MACS-FACS sorting procedure and revealed expression changes in various pathways relating to pericyte cell adhesion and cellular stress. Particularly, FOS and cyclin dependent kinase-1 (CDK1) played a key role in modulating the migration, engraftment, and anti-inflammatory functions of M-MSCs, which determined their in vivo therapeutic potency. Collectively, this approach provides an overview of engrafted M-MSC behavior in vivo, which will advance our understanding of MSC therapeutic applications, efficacy, and safety.

Image Correlation-Based Method to Assess Ciliary Beat Frequency in Human Airway Organoids.

Ciliary movements within the human airway are essential for maintaining a clean lung environment. Motile cilia have a characteristic ciliary beat frequency (CBF). However, CBF measurement with current video microscopic techniques can be error-prone due to the use of the single-point Fourier transformation, which is often biased for ciliary measurements. Herein, we describe a new video microscopy technique that harnesses a metric of motion-contrast imaging and image correlation for CBF analysis. It can provide objective and selective CBF measurements for individual motile cilia and generate CBF maps for the imaged area. The measurement performance of our methodology was validated with in vitro human airway organoid models that simulated an actual human airway epithelium. The CBF determined for the region of interest (ROI) was equal to that obtained with manual counting. The signal redundancy problem of conventional methods was not observed. Moreover, the obtained CBF measurements were robust to optical focal shifts, and exhibited spatial heterogeneity and temperature dependence. This technique can be used to evaluate ciliary movement in respiratory tracts and determine whether it is non-synchronous or aperiodic in patients. Therefore, our observations suggest that the proposed method can be clinically adapted as a screening tool to diagnose ciliopathies.

Multimodal Imaging of Laser Speckle Contrast Imaging Combined With Mosaic Filter-Based Hyperspectral Imaging for Precise Surgical Guidance.

OBJECTIVE: To enable a real-time surgical guidance system that simultaneously monitors blood vessel perfusion, oxygen saturation, thrombosis, and tissue recovery by combining multiple optical imaging techniques into a single system: visible imaging, mosaic filter-based snapshot hyperspectral imaging (HSI), and laser speckle contrast imaging (LSCI). METHODS: The multimodal optical imaging system was demonstrated by clamping blood vessels in the small intestines of rats to create areas of restricted blood flow. Subsequent tissue damage and regeneration were monitored during procedures. Using LSCI, vessel perfusion was measured, revealing the biological activity and survival of organ tissues. Blood oxygen saturation was monitored using HSI in the near-infrared region. Principal component analysis was used over the spectral dimension to identify an HSI wavelength combination optimized for hemodynamic biomarker visualization. HSI and LSCI were complimentary, identifying thrombus generation and tissue recovery, which was not possible in either modalityalone. RESULTS AND CONCLUSION: By analyzing multimodal tissue information from visible imaging, LSCI perfusion imaging, and HSI, a recovery prognosis could be determined based on the blood supply to the organ. The unique combination of the complementary imaging techniques into a single surgical microscope holds promise for improving the real-time determination of blood supply and tissue prognosis during surgery. SIGNIFICANCE: Precise real-time monitoring for vascular anomalies promises to reduce the risk of organ damage in precise surgical operations such as tissue resection and transplantation. In addition, the convergence of label-free imaging technologies removes delays associated with the injection and diffusion of vascular monitoring dyes.

Spectral Multiplexing of Fluorescent Endoscopy for Simultaneous Imaging with Multiple Fluorophores and Multiple Fields of View.

Complex clinical procedures and small-animal research procedures can benefit from dual-site imaging provided by multiple endoscopic devices. Here, an endoscopic system is proposed which enables multiple fluorescence microendoscopes to be spectrally multiplexed on a single microscope base, enabling light sources and optical relays to be shared between endoscopes. The presented system is characterized for resolution using USAF-1951 resolution test charts and for modulation transfer function using the slanted edge method. Imaging is demonstrated both directly and with microendoscopes attached. Imaging of phantoms was demonstrated by targeting USAF charts and fiber tissues dyed for FITC and Texas Red fluorescence. Afterwards, simultaneous liver and kidney imaging was demonstrated in mice expressing mitochondrial Dendra2 and injected with Texas Red-dextran. The results indicate that the system achieves high channel isolation and submicron and subcellular resolution, with resolution limited by the endoscopic probe and by physiological movement during endoscopic imaging. Multi-channel microendoscopy provides a potentially low-cost means of simultaneous multiple endoscopic imaging during biological experiments, resulting in reduced animal harm and potentially increasing insight into temporal connections between connected biological systems.

Characterizing Organelles in Live Stem Cells Using Label-Free Optical Diffraction Tomography.

Label-free optical diffraction tomography (ODT), an imaging technology that does not require fluorescent labeling or other pre-processing, can overcome the limitations of conventional cell imaging technologies, such as fluorescence and electron microscopy. In this study, we used ODT to characterize the cellular organelles of three different stem cells-namely, human liver derived stem cell, human umbilical cord matrix derived mesenchymal stem cell, and human induced pluripotent stem cell-based on their refractive index and volume of organelles. The physical property of each stem cell was compared with that of fibroblast. Based on our findings, the characteristic physical properties of specific stem cells can be quantitatively distinguished based on their refractive index and volume of cellular organelles. Altogether, the method employed herein could aid in the distinction of living stem cells from normal cells without the use of fluorescence or specific biomarkers.