A Fully Automated Artificial Intelligence System to Assist Pathologists' Diagnosis to Predict Histologically High-grade Urothelial Carcinoma from Digitized Urine Cytology Slides Using Deep Learning.

BACKGROUND: Urine cytology, although a useful screening method for urothelial carcinoma, lacks sensitivity. As an emerging technology, artificial intelligence (AI) improved image analysis accuracy significantly. OBJECTIVE: To develop a fully automated AI system to assist pathologists in the histological prediction of high-grade urothelial carcinoma (HGUC) from digitized urine cytology slides. DESIGN, SETTING, AND PARTICIPANTS: We digitized 535 consecutive urine cytology slides for AI use. Among these slides, 181 were used for AI development, 39 were used as AI test data to identify HGUC by cell-level classification, and 315 were used as AI test data for slide-level classification. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Out of the 315 slides, 171 were collected immediately prior to bladder biopsy or transurethral resection of bladder tumor, and then outcomes were compared with the histological presence of HGUC in the surgical specimen. The primary aim was to compare AI prediction of the histological presence of HGUC with the pathologist's histological diagnosis of HGUC. Secondary aims were to compare the time required for AI evaluation and concordance between the AI's classification and pathologist's cytology diagnosis. RESULTS AND LIMITATIONS: The AI capability for predicting the histological presence of HGUC was 0.78 for the area under the curve. Comparing the AI predictive performance with pathologists' diagnosis, the AI sensitivity of 63% for histological HGUC prediction was superior to a pathologists' cytology sensitivity of 46% (p = 0.0037). On the contrary, there was no significant difference between the AI specificity of 83% and pathologists' specificity of 89% (p = 0.13), and AI accuracy of 74% and pathologists' accuracy of 68% (p = 0.08). The time required for AI evaluation was 139 s. With respect to the concordance between the AI prediction and pathologist's cytology diagnosis, the accuracy was 86%. Agreements with positive and negative findings were 92% and 84%, respectively. CONCLUSIONS: We developed a fully automated AI system to assist pathologists' histological diagnosis of HGUC using digitized slides. This AI system showed significantly higher sensitivity than a board-certified cytopathologist and may assist pathologists in making urine cytology diagnoses, reducing their workload. PATIENT SUMMARY: In this study, we present a deep learning-based artificial intelligence (AI) system that classifies urine cytology slides according to the Paris system. An automated AI system was developed and validated with 535 consecutive urine cytology slides. The AI predicted histological high-grade urothelial carcinoma from digitized urine cytology slides with superior sensitivity than pathologists, while maintaining comparable specificity and accuracy.

Deep UV-excited fluorescence microscopy installed with CycleGAN-assisted image translation enhances precise detection of lymph node metastasis towards rapid intraoperative diagnosis.

Rapid and precise intraoperative diagnosing systems are required for improving surgical outcomes and patient prognosis. Because of the poor quality and time-intensive process of the prevalent frozen section procedure, various intraoperative diagnostic imaging systems have been explored. Microscopy with ultraviolet surface excitation (MUSE) is an inexpensive, maintenance-free, and rapid imaging technique that yields images like thin-sectioned samples without sectioning. However, pathologists find it nearly impossible to assign diagnostic labels to MUSE images of unfixed specimens; thus, AI for intraoperative diagnosis cannot be trained in a supervised learning manner. In this study, we propose a deep-learning pipeline model for lymph node metastasis detection, in which CycleGAN translate MUSE images of unfixed lymph nodes to formalin-fixed paraffin-embedded (FFPE) sample, and diagnostic prediction is performed using deep convolutional neural network trained on FFPE sample images. Our pipeline yielded an average accuracy of 84.6% when using each of the three deep convolutional neural networks, which is a 18.3% increase over the classification-only model without CycleGAN. The modality translation to FFPE sample images using CycleGAN can be applied to various intraoperative diagnostic imaging systems and eliminate the difficulty for pathologists in labeling new modality images in clinical sites. We anticipate our pipeline to be a starting point for accurate rapid intraoperative diagnostic systems for new imaging modalities, leading to healthcare quality improvement.

Generation of myocyte agonal Ca2+ waves and contraction bands in perfused rat hearts following irreversible membrane permeabilisation.

Although irreversible cardiomyocyte injury provokes intracellular Ca2+ ([Ca2+]i) overload, the underlying dynamics of this response and its effects on cellular morphology remain unknown. We therefore visualised rapid-scanning confocal fluo4-[Ca2+]i dynamics and morphology of cardiomyocytes in Langendorff-perfused rat hearts following saponin-membrane permeabilisation. Our data demonstrate that 0.4% saponin-treated myocytes immediately exhibited high-frequency Ca2+ waves (131.3 waves/min/cell) with asynchronous, oscillatory contractions having a mean propagation velocity of 117.8 µm/s. These waves slowly decreased in frequency, developed a prolonged decay phase, and disappeared in 10 min resulting in high-static, fluo4-fluorescence intensity. The myocytes showing these waves displayed contraction bands, i.e., band-like actin-fibre aggregates with disruption of sarcomeric α-actinin. The contraction bands were not attenuated by the abolition of Ca2+ waves under pretreatment with ryanodine plus thapsigargin, but were partially attenuated by the calpain inhibitor MDL28170, while mechanical arrest of the myocytes by 2,3-butanedione monoxime completely attenuated contraction-band formation. The depletion of adenosine 5'-triphosphate by the mitochondrial electron uncoupler carbonyl cyanide 4-trifluoromethoxy phenylhydrazone also attenuated Ca2+ waves and contraction bands. Overall, saponin-induced myocyte [Ca2+]i overload provokes agonal Ca2+ waves and contraction bands. Contraction bands are not the direct consequence of the waves but are caused by cross-bridge interactions of the myocytes under calpain-mediated proteolysis.

5-Aminolevulinic Acid-Induced Protoporphyrin IX Fluorescence Imaging for Tumor Detection: Recent Advances and Challenges.

5-Aminolevulinic acid (5-ALA) is a natural amino acid and a precursor of heme and chlorophyll. Exogenously administered 5-ALA is metabolized into protoporphyrin IX (PpIX). PpIX accumulates in cancer cells because of the low activity of ferrochelatase, an enzyme that metabolizes PpIX to heme. High expression of 5-ALA influx transporters, such as peptide transporters 1/2, in cancer cells also enhances PpIX production. Because PpIX radiates red fluorescence when excited with blue/violet light, 5-ALA has been used for the visualization of various tumors. 5-ALA photodynamic diagnosis (PDD) has been shown to improve the tumor removal rate in high-grade gliomas and non-muscular invasive bladder cancers. However, 5-ALA PDD remains a challenge as a diagnostic method because tissue autofluorescence interferes with PpIX signals in cases where tumors emit only weak signals, and non-tumorous lesions, such as inflammatory sites, tend to emit PpIX fluorescence. Here, we review the current outline of 5-ALA PDD and strategies for improving its diagnostic applicability for tumor detection, focusing on optical techniques and 5-ALA metabolic pathways in both viable and necrotic tumor tissues.

Urine cell image recognition using a deep-learning model for an automated slide evaluation system.

OBJECTIVES: To develop a classification system for urine cytology with artificial intelligence (AI) using a convolutional neural network algorithm that classifies urine cell images as negative (benign) or positive (atypical or malignant). PATIENTS AND METHODS: We collected 195 urine cytology slides from consecutive patients with a histologically confirmed diagnosis of urothelial cancer (between January 2016 and December 2017). Two certified cytotechnologists independently evaluated and labelled each slide; 4637 cell images with concordant diagnoses were selected, including 3128 benign cells (negative), 398 atypical cells, and 1111 cells that were malignant or suspicious for malignancy (positive). This pathologically confirmed labelled dataset was used to represent the ground truth for AI training/validation/testing. Customized CutMix (CircleCut) and Refined Data Augmentation were used for image processing. The model architecture included EfficientNet B6 and Arcface. We used 80% of the data for training and validation (4:1 ratio) and 20% for testing. Model performance was evaluated with fivefold cross-validation. A receiver-operating characteristic (ROC) analysis was used to evaluate the binary classification model. Bayesian posterior probabilities for the AI performance measure (Y) and cytotechnologist performance measure (X) were compared. RESULTS: The area under the ROC curve was 0.99 (95% confidence interval [CI] 0.98-0.99), the highest accuracy was 95% (95% CI 94-97), sensitivity was 97% (95% CI 95-99), and specificity was 95% (95% CI 93-97). The accuracy of AI surpassed the highest level of cytotechnologists for the binary classification [Pr(Y > X) = 0.95]. AI achieved >90% accuracy for all cell subtypes. In the subgroup analysis based on the clinicopathological characteristics of patients who provided the test cells, the accuracy of AI ranged between 89% and 97%. CONCLUSION: Our novel AI classification system for urine cytology successfully classified all cell subtypes with an accuracy of higher than 90%, and achieved diagnostic accuracy of malignancy superior to the highest level achieved by cytotechnologists.

Accumulation of Uroporphyrin I in Necrotic Tissues of Squamous Cell Carcinoma after Administration of 5-Aminolevulinic Acid.

5-aminolevulinic acid (5-ALA)-induced protoporphyrin IX (PpIX) fluorescence is widely used for the intraoperative detection of malignant tumors. However, the fluorescence emission profiles of the accompanying necrotic regions of these tumors have yet to be determined. To address this, we performed fluorescence and high-performance liquid chromatography (HPLC) analyses of necrotic tissues of squamous cancer after 5-ALA administration. In resected human lymph nodes of metastatic squamous cell carcinoma, we found a fluorescence peak at approximately 620 nm in necrotic lesions, which was distinct from the PpIX fluorescence peak at 635 nm for viable cancer lesions. Necrotic lesions obtained from a subcutaneous xenograft model of human B88 oral squamous cancer also emitted the characteristic fluorescence peak at 620 nm after light irradiation: the fluorescence intensity ratio (620 nm/635 nm) increased with the energy of the irradiation light. HPLC analysis revealed a high content ratio of uroporphyrin I (UPI)/total porphyrins in the necrotic cores of murine tumors, indicating that UPI is responsible for the 620 nm peak. UPI accumulation in necrotic tissues after 5-ALA administration was possibly due to the failure of the heme biosynthetic pathway. Taken together, fluorescence imaging of UPI after 5-ALA administration may be applicable for the evaluation of tumor necrosis.

5-ALA-assistant automated detection of lymph node metastasis in gastric cancer patients.

BACKGROUND: 5-aminolevulinic acid (5-ALA) has been utilized for cancer diagnosis as a fluorescence probe. We have reported the feasibility of 5-ALA-induced protoporphyrin IX (PpIX) fluorescence for detecting lymph node (LN) metastasis in gastrointestinal malignancies. However, a major barrier to the fluorescence diagnosis has been that the evaluation has been highly dependent on the observers. In this study, we examined the validity of a developed device for automated detection without subjectivity. METHODS: Gastric cancer patients who received oral administration of 5-ALA (20 mg/kg) prior to surgery were enrolled. For a total of 323 LNs obtained from 64 patients, the diagnostic results of the device were compared to those of conventional histopathological examination based on hematoxylin-and-eosin-stained slides. The accuracy with the device was compared to that of stereoscopic detection with conventional fluorescence microscopy for 211 LNs from 42 patients. We used two types of image processing that we previously developed to eliminate autofluorescence of background tissues: differential and ratio methods. RESULTS: For detection of metastasis in 323 LNs, the areas under the receiver operating characteristic curves with the differential method and ratio method were 0.921 and 0.909, respectively. The sensitivity, specificity, and accuracy with the differential method were 78.0%, 96.8%, and 94.4%; while those with the ratio method were 78.0%, 96.1%, and 93.8%, respectively. In 211 LN analysis, the diagnostic accuracy with the device was comparable to that of stereoscopic examination. CONCLUSION: Our device for automated detection of LN metastasis using 5-ALA can be a useful tool for intraoperative diagnosis.

Deep-UV excitation fluorescence microscopy for detection of lymph node metastasis using deep neural network.

Deep-UV (DUV) excitation fluorescence microscopy has potential to provide rapid diagnosis with simple technique comparing to conventional histopathology based on hematoxylin and eosin (H&E) staining. We established a fluorescent staining protocol for DUV excitation fluorescence imaging that has enabled clear discrimination of nucleoplasm, nucleolus, and cytoplasm. Fluorescence images of metastasis-positive/-negative lymph nodes of gastric cancer patients were used for patch-based training with a deep neural network (DNN) based on Inception-v3 architecture. The performance on small patches of the fluorescence images was comparable with that of H&E images. Gradient-weighted class activation mapping analysis revealed the areas where the trained model identified metastatic lesions in the images containing cancer cells. We extended the method to large-size image analysis enabling accurate detection of metastatic lesions. We discuss usefulness of DUV excitation fluorescence imaging with the aid of DNN analysis, which is promising for assisting pathologists in assessment of lymph node metastasis.

Fluorescence-based discrimination of breast cancer cells by direct exposure to 5-aminolevulinic acid.

Protoporphyrin IX-fluorescence measurement is a powerful in situ approach for cancer detection after oral/topical administration of 5-aminolevulinic acid. However, this approach has not been clinically established for breast cancer, probably due to insufficient delivery of 5-aminolevulinic acid to the mammary glands. In the present study, we directly exposed breast cancer cells to 5-aminolevulinic acid to assess their discrimination via protoporphyrin IX-fluorescence. Fluorescence intensity (FI) was measured in the human breast cancer cell lines MCF7 and MDA-MB-231 and breast epithelial cell line MCF10A by confocal microscopy and flow cytometry. After 5-aminolevulinic acid exposure for 2 hours, protoporphyrin IX-FI in MCF7 and MDA-MB-231 cells significantly increased with marked cell-to-cell variability, whereas that in MCF10A cells increased moderately. Combined exposure of the cancer cells to 5-aminolevulinic acid and Ko143, a specific inhibitor of ATP-binding cassette transporter G2, further increased protoporphyrin IX-FI and alleviated the cell-to-cell variability in MCF7 and MDA-MB-231 cells, indicating improvement in the reproducibility and accuracy for fluorescence-based cancer detection. The increased FI by combined administration of these two drugs was also demonstrated in cells obtained via fine needle aspiration from mouse xenograft models inoculated with MDA-MB-231 cells. Furthermore, a cutoff value for increased protoporphyrin IX-FI ratio, before and after exposure to these drugs, clearly discriminated between cancer and noncancer cells. Taken together, direct exposure to 5-aminolevulinic acid and Ko143 may be a promising strategy for efficient fluorescence-based detection of breast cancer cells ex vivo using fine needle aspiration.

Terbium ion as RNA tag for slide-free pathology with deep-ultraviolet excitation fluorescence.

Deep-ultraviolet excitation fluorescence microscopy has enabled molecular imaging having an optical sectioning capability with a wide-field configuration and its usefulness for slide-free pathology has been shown in recent years. Here, we report usefulness of terbium ions as RNA-specific labeling probes for slide-free pathology with deep-ultraviolet excitation fluorescence. On excitation in the wavelength range of 250-300 nm, terbium ions emitted fluorescence after entering cells. Bright fluorescence was observed at nucleoli and cytoplasm while fluorescence became weak after RNA decomposition by ribonuclease prior to staining. It was also found that the fluorescence intensity at nucleoplasm increased with temperature during staining and that this temperature-dependent behavior resembled temperature-dependent hypochromicity of DNA due to melting. These findings indicated that terbium ions stained single-stranded nucleic acid more efficiently than double-stranded nucleic acid. We further combined terbium ions and DNA-specific dyes for dual-color imaging. In the obtained image, nucleolus, nucleoplasm, and cytoplasm were distinguished. We demonstrated the usefulness of dual-color imaging for rapid diagnosis of surgical specimen by showing optical sectioning of unsliced tissues. The present findings can enhance deep-ultraviolet excitation fluorescence microscopy and consequently expand the potential of fluorescence microscopy in life sciences.

Label-free Evaluation of Myocardial Infarct in Surgically Excised Ventricular Myocardium by Raman Spectroscopy.

Understanding the viability of the ischemic myocardial tissue is a critical issue in determining the appropriate surgical procedure for patients with chronic heart failure after myocardial infarction (MI). Conventional MI evaluation methods are; however, preoperatively performed and/or give an indirect information of myocardial viability such as shape, color, and blood flow. In this study, we realize the evaluation of MI in patients undergoing cardiac surgery by Raman spectroscopy under label-free conditions, which is based on intrinsic molecular constituents related to myocardial viability. We identify key signatures of Raman spectra for the evaluation of myocardial viability by evaluating the infarct border zone myocardium that were excised from five patients under surgical ventricular restoration. We also obtain a prediction model to differentiate the infarcted myocardium from the non-infarcted myocardium by applying partial least squares regression-discriminant analysis (PLS-DA) to the Raman spectra. Our prediction model enables identification of the infarcted tissues and the non-infarcted tissues with sensitivities of 99.98% and 99.92%, respectively. Furthermore, the prediction model of the Raman images of the infarct border zone enabled us to visualize boundaries between these distinct regions. Our novel application of Raman spectroscopy to the human heart would be a useful means for the detection of myocardial viability during surgery.

Label-free Molecular Imaging and Analysis by Raman Spectroscopy.

Raman scattering of a cell conveys the intrinsic information inherent to chemical structures of biomolecules. The spectroscopy of Raman scattering, or Raman spectroscopy, allows label-free and quantitative molecular sensing of a biological sample in situ without disruption. For the last five decades Raman spectroscopy has been widely utilized in biological research fields. However, it is just within the latest decade that molecular imaging and discrimination of living cells and tissues have become practically available. Here we overview recent progress in Raman spectroscopy and its application to life sciences. We discuss imaging of functional molecules in living cells and tissues; e.g., cancer cells and ischemic or infarcted hearts, together with a number of studies in the biomedical fields. We further explore comprehensive understandings of a complex spectrum by multivariate analysis for, e.g., accurate peripheral nerve detection, and characterization of the histological differences in the healing process of myocardial infarct. Although limitations still remain, e.g., weakness of the scattering intensity and practical difficulty in comprehensive molecular analysis, continuous progress in related technologies will allow wider use of Raman spectroscopy for biomedical applications.

Efficient fluorescence detection of protoporphyrin IX in metastatic lymph nodes of murine colorectal cancer stained with indigo carmine.

Protoporphyrin IX (PpIX), a biochemical converted from 5-aminolevulinc acid (5-ALA) in living cells, is useful for intraoperative fluorescent detection of cancer metastasis in lymph nodes (LNs). However, unknown is whether the fluorescence of PpIX can be detected in the LNs when they coexist with indigo carmine, a blue dye commonly used for identification of sentinel LNs during surgery. To address this issue, we sought to evaluate the diagnostic usefulness of PpIX fluorescence in the presence of indigo carmine in a mouse LN metastasis model of rectal cancer after administration of 5-ALA. Spectral analysis of pure chemicals revealed that the absorption spectrum of indigo carmine widely overlapped with the fluorescence spectrum of PpIX specifically at the peak of 632nm, a common emission wavelength for detecting PpIX, but not at the other peak of 700nm. Due to such spectral overlap, the PpIX fluorescence intensity was significantly attenuated by mixture with indigo carmine at 632nm, but not at 700nm. Accordingly, fluorescent measurements of the mouse metastatic LN revealed more intense presentation of PpIX at 700nm than at 632nm, indicating that the diagnostic usefulness is greater at 700nm than at 632nm for the indigo carmine-dyed LNs after administration of 5-ALA. From these observations, we propose that the fluorescence measurement is more efficient at 700nm than at 632nm for detection of PpIX in metastatic LNs stained with indigo carmine.

Rapid and accurate peripheral nerve imaging by multipoint Raman spectroscopy.

Raman spectroscopy allows label-free, minimally invasive, and accurate detection of peripheral nerves. However, the conventional Raman imaging technique is time-consuming when measuring a large area of a sample. Establishing a method for rapidly acquiring spatial distribution of a bundle of peripheral nerve fibers is an essential step for Raman spectroscopy towards application in clinical surgery. Here we present a multipoint Raman spectroscopic technique for rapid peripheral nerve imaging. In only 5 seconds, spectra at 32 points situated on ex vivo rat peripheral nerve bundles and adjoining connective tissues were acquired. Principal component regression and discriminant analysis of spectra revealed that the sensitivity, specificity and accuracy for nerve detection were 85.8%, 96.0%, and 90.8%, respectively. Of 158 peripheral nerves, 152 (96.2%) showed ratio of the number of nerve-positive prediction points to the total measurement points being 0.4 or larger, whereas 119 (99.2%) connective tissues among 120 showed ratio smaller than 0.4. Based on the ratio and a bright-field image of the sample, accurate visualization of peripheral nerves was implemented. The results indicated that the multipoint Raman spectroscopic technique is capable of rapid and accurate peripheral nerve imaging.

Simplified and optimized multispectral imaging for 5-ALA-based fluorescence diagnosis of malignant lesions.

5-aminolevulinic acid (5-ALA)-based fluorescence diagnosis is now clinically applied for accurate and ultrarapid diagnosis of malignant lesions such as lymph node metastasis during surgery. 5-ALA-based diagnosis evaluates fluorescence intensity of a fluorescent metabolite of 5-ALA, protoporphyrin IX (PPIX); however, the fluorescence of PPIX is often affected by autofluorescence of tissue chromophores, such as collagen and flavins. In this study, we demonstrated PPIX fluorescence estimation with autofluorescence elimination for 5-ALA-based fluorescence diagnosis of malignant lesions by simplified and optimized multispectral imaging. We computationally optimized observation wavelength regions for the estimation of PPIX fluorescence in terms of minimizing prediction error of PPIX fluorescence intensity in the presence of typical chromophores, collagen and flavins. By using the fluorescence intensities of the optimized wavelength regions, we verified quantitative detection of PPIX fluorescence by using chemical mixtures of PPIX, flavins, and collagen. Furthermore, we demonstrated detection capability by using metastatic and non-metastatic lymph nodes of colorectal cancer patients. These results suggest the potential and usefulness of the background-free estimation method of PPIX fluorescence for 5-ALA-based fluorescence diagnosis of malignant lesions, and we expect this method to be beneficial for intraoperative and rapid cancer diagnosis.

Recent advances in photodynamic diagnosis of gastric cancer using 5-aminolevulinic acid.

Photodynamic diagnosis based on 5-aminolevulinic acid-induced protoporphyrin IX has been clinically applied in many fields based upon its evidenced efficacy and adequate safety. In order to establish a personalized medicine approach for treating gastric cancer patients, rapid intraoperative detection of malignant lesions has become important. Feasibility of photodynamic diagnosis using 5-aminolevulinic acid for gastric cancer patients has been investigated, especially for the detection of peritoneal dissemination and lymph node metastasis. This method enables intraoperative real-time fluorescence detection of peritoneal dissemination, exhibiting higher sensitivity than white light observation without histopathological examination. The method also enables detection of metastatic foci within excised lymph nodes, exhibiting a diagnostic accuracy comparable to that of a current molecular diagnostics technique. Although several complicating issues still need to be resolved, such as the effect of tissue autofluorescence and the insufficient depth penetration of excitation light, this simple and rapid method has the potential to become a useful diagnostic tool for gastric cancer, as well as urinary bladder cancer and glioma.

Ex vivo peripheral nerve detection of rats by spontaneous Raman spectroscopy.

Nerve-sparing surgery is increasingly being applied to avoid functional deficits of the limbs and organs following surgery. Peripheral nerves that should be preserved are, however, sometimes misidentified due to similarity of shape and color to non-nerve tissues. To avoid misidentification of peripheral nerves, development of an in situ nerve detection method is desired. In this study, we report the label-free detection of ex vivo peripheral nerves of Wistar rats by using Raman spectroscopy. We obtained Raman spectra of peripheral nerves (myelinated and unmyelinated nerves) and their adjacent tissues of Wistar rats without any treatment such as fixation and/or staining. For the identification of tissue species and further analysis of spectral features, we proposed a principal component regression-based discriminant analysis with representative Raman spectra of peripheral nerves and their adjacent tissues. Our prediction model selectively detected myelinated nerves and unmyelinated nerves of Wistar rats with respective sensitivities of 95.5% and 88.3% and specificities of 99.4% and 93.5%. Furthermore, important spectral features for the identification of tissue species were revealed by detailed analysis of principal components of representative Raman spectra of tissues. Our proposed approach may provide a unique and powerful tool for peripheral nerve detection for nerve-sparing surgery in the future.

Interaction of Cx43 with Hsc70 regulates G1/S transition through CDK inhibitor p27.

Connexin 43 (Cx43) functions as a cell growth suppressor. We have demonstrated that Cx43 interacts with heat shock cognate protein 70 (Hsc70) for regulating cell proliferation. Hsc70 interacts with CDK inhibitor p27, which regulates the assembly and subcellular localization of cyclin D1-CDK4-p27 complex. However, the involvement of p27 with Cx43-mediated cell cycle suppression is still poorly understood. Here, we report that nuclear accumulation of p27 is reduced by overexpression of Cx43, and that this reduction is restored by co-overexpression with Hsc70. We found that Cx43 competes with p27 for binding to Hsc70, and as a result, decreases the level of Hsc70 in cyclin D1-CDK4-p27 complex, leading to prevention of the nuclear translocation of the complex and the G1/S transition. Collectively, our findings suggest that, in Cx43 up-regulation, which is most likely an emergency measure, Cx43-Hsc70 interaction regulates cell cycle G1/S progression through a novel mechanism by which Cx43-Hsc70 interaction prevents the nuclear accumulation of p27 through controlling the nuclear translocation of cyclin D1-CDK4-p27 complex.

Spectral fingerprinting of individual cells visualized by cavity-reflection-enhanced light-absorption microscopy.

The absorption spectrum of light is known to be a "molecular fingerprint" that enables analysis of the molecular type and its amount. It would be useful to measure the absorption spectrum in single cell in order to investigate the cellular status. However, cells are too thin for their absorption spectrum to be measured. In this study, we developed an optical-cavity-enhanced absorption spectroscopic microscopy method for two-dimensional absorption imaging. The light absorption is enhanced by an optical cavity system, which allows the detection of the absorption spectrum with samples having an optical path length as small as 10 µm, at a subcellular spatial resolution. Principal component analysis of various types of cultured mammalian cells indicates absorption-based cellular diversity. Interestingly, this diversity is observed among not only different species but also identical cell types. Furthermore, this microscopy technique allows us to observe frozen sections of tissue samples without any staining and is capable of label-free biopsy. Thus, our microscopy method opens the door for imaging the absorption spectra of biological samples and thereby detecting the individuality of cells.

Combining TGF-ß signal inhibition and connexin43 silencing for iPSC induction from mouse cardiomyocytes.

The reprogramming of differentiated cells into induced pluripotent stem cells (iPSCs) can be achieved by ectopic expression of defined transcription factors (Oct3/4, Sox2, Klf4 and c-Myc). However, to date, some iPSCs have been generated using viral vectors; thus, unexpected insertional mutagenesis in the target cells would be a potential risk. Here we report reprogramming of siPSCs (gene silencing-induced pluripotent stem cells) from mouse neonatal cardiomyocytes (CMs) by combining TGF-ß signal inhibition and connexin43 (Cx43) silencing, and show that siPSCs show pluripotency in vitro and in vivo. Our novel non-insertional mutagenesis technique may provide a means for iPSC generation.