Celastrol acts as a new histone deacetylase inhibitor to inhibit colorectal cancer cell growth via regulating macrophage polarity.

The tumorigenesis and progression of colorectal cancer are closely related to the tumor microenvironment, especially inflammatory response. Inhibitors of histone deacetylase (HDAC) have been reported as epigenetic regulators of the immune system to treat cancer and inflammatory diseases and our results demonstrated that Celastrol could act as a new HDAC inhibitor. Considering macrophages as important members of the tumor microenvironment, we further found that Celastrol could influence the polarization of macrophages to inhibit colorectal cancer cell growth. Specially, we used the supernatant of HCT116 and SW480 cells to induce Ana-1 cells in vitro and chose the spontaneous colorectal cancer model APCmin/+ mice as an animal model to validate in vivo. The results indicated that Celastrol could reverse the polarization of macrophages from M2 to M1 through impacting the colorectal tumor microenvironment both in vitro and in vivo. Furthermore, using bioinformatics analysis, we found that Celastrol might mechanistically polarize the macrophages through MAPK signaling pathway. In conclusion, our findings identified that Celastrol as a new HDAC inhibitor and suggested that Celastrol could modulate macrophage polarization, thus inhibiting colorectal cancer growth, which may provide some novel therapeutic strategies for colorectal cancer.

Achieving Verifiable Decision Tree Prediction on Hybrid Blockchains.

Machine learning has become increasingly popular in academic and industrial communities and has been widely implemented in various online applications due to its powerful ability to analyze and use data. Among all the machine learning models, decision tree models stand out due to their great interpretability and simplicity, and have been implemented in cloud computing services for various purposes. Despite its great success, the integrity issue of online decision tree prediction is a growing concern. The correctness and consistency of decision tree predictions in cloud computing systems need more security guarantees since verifying the correctness of the model prediction remains challenging. Meanwhile, blockchain has a promising prospect in two-party machine learning services as the immutable and traceable characteristics satisfy the verifiable settings in machine learning services. In this paper, we initiate the study of decision tree prediction services on blockchain systems and propose VDT, a Verifiable Decision Tree prediction scheme for decision tree prediction. Specifically, by leveraging the Merkle tree and hash function, the scheme allows the service provider to generate a verification proof to convince the client that the output of the decision tree prediction is correctly computed on a particular data sample. It is further extended to an update method for a verifiable decision tree to modify the decision tree model efficiently. We prove the security of the proposed VDT schemes and evaluate their performance using real datasets. Experimental evaluations show that our scheme requires less than one second to produce verifiable proof.

Harmonically decoupled gradient light interference microscopy (HD-GLIM).

Differential phase sensitive methods, such as Nomarski microscopy, play an important role in quantitative phase imaging due to their compatibility with partially coherent illumination and excellent optical sectioning ability. In this Letter, we propose a new system, to the best of our knowledge, to retrieve differential phase information from transparent samples. It is based on a 4f optical system with an amplitude-type spatial light modulator (SLM), which removes the need for traditional differential interference contrast (DIC) optics and specialized phase-only SLMs. We demonstrate the principle of harmonically decoupled gradient light interference microscopy using standard samples, as well as static and dynamic biospecimens.

Endoscopic diffraction phase microscopy.

In this Letter, we present, to our knowledge, the first endoscopic diffraction phase microscopy (eDPM) system. This instrument consists of a gradient-index-lens-based endoscope probe followed by a DPM module, which enables single-shot phase imaging at a single-cell-level resolution. Using the phase information provided by eDPM, we show that the geometric aberrations associated with the endoscope can be reduced by digitally applying a spectral phase filter to the raw data. The filter function is a linear combination of polynomials with weighting optimized to improve resolution. We validate the principle of the proposed method using reflective semiconductor samples and blood cells. This research extends the current scope of quantitative phase imaging applications, and proves its potential for future in vivo studies.

Physical significance of backscattering phase measurements.

Quantitative phase imaging of transparent objects in transmission allows for a direct interpretation of the results: the phase shift measured is linear in the refractive index contrast and object thickness. However, the same measurement in a backscattering geometry yields fundamentally different results, because the incident field component is absent from the detected field. As a result, the relationship between the measured phase and object properties is obscure. We derived analytical expressions for the propagating fields under the first-order Born approximation and studied the interpretation of the measured phase shifts in backscattering versus transmission geometries. Our analysis shows that the backscattering phase shift is the result of the plane wave superposition originating at various depths in the object, which makes it impossible to infer quantitative morphology or topography information of 3D transparent samples from a reflection phase image alone.

Upregulation of KLF4 by methylseleninic acid in human esophageal squamous cell carcinoma cells: Modification of histone H3 acetylation through HAT/HDAC interplay.

Esophageal squamous cell carcinoma (ESCC) occurs at a very high frequency in certain areas of China. Supplementation with selenium-containing compounds was associated with a significantly lower cancer mortality rate in a study conducted in Linxia, China. Thus, selenium could be a potential anti-esophageal cancer agent. In this study, methylseleninic acid (MSA) could inhibit cell growth of ESCC cells in vitro and in vivo. Upon treated with MSA, the activity of histone deacetylases (HDACs) was decreased and general control nonrepressed protein 5 (GCN5) was upregulated in ESCC cells. Meanwhile, a significant increase of H3K9 acetylation (H3K9ac) was detected. Upregulation of Krüppel-like factor 4 (KLF4) was also observed after MSA treatment. Additionally, the acetylated histone H3 located more at KLF4 promoter region after MSA treatment, shown by chromatin immunoprecipitation (ChIP) assay. Moreover, knockdown of GCN5 decreased the protein level of both H3K9ac and KLF4, along with less cell growth inhibition. Taken all, our results indicated that MSA could inhibit ESCC cell growth, at least in part, by MSA-HDAC/GCN5-H3K9ac-KLF4 axis. To our best knowledge, this is the first report that MSA induced acetylation of histone H3 at Lys9, which might depend on the activities and the balance between HDACs and HATs.

MicroRNA-mRNA functional pairs for cisplatin resistance in ovarian cancer cells.

Ovarian cancer is the leading cause of death in women worldwide. Cisplatin is the core of first-line chemotherapy for patients with advanced ovarian cancer. Many patients eventually become resistant to cisplatin, diminishing its therapeutic effect. MicroRNAs (miRNAs) have critical functions in diverse biological processes. Using miRNA profiling and polymerase chain reaction validation, we identified a panel of differentially expressed miRNAs and their potential targets in cisplatin-resistant SKOV3/DDP ovarian cancer cells relative to cisplatin-sensitive SKOV3 parental cells. More specifically, our results revealed significant changes in the expression of 13 of 663 miRNAs analyzed, including 11 that were up-regulated and 2 that were down-regulated in SKOV3/DDP cells with or without cisplatin treatment compared with SKOV3 cells with or without cisplatin treatment. miRNA array and mRNA array data were further analyzed using Ingenuity Pathway Analysis software. Bioinformatics analysis suggests that the genes ANKRD17, SMC1A, SUMO1, GTF2H1, and TP73, which are involved in DNA damage signaling pathways, are potential targets of miRNAs in promoting cisplatin resistance. This study highlights candidate miRNA-mRNA interactions that may contribute to cisplatin resistance in ovarian cancer.

miR-106a is frequently upregulated in gastric cancer and inhibits the extrinsic apoptotic pathway by targeting FAS.

Emerging evidence has shown the association of aberrantly expressed miR-106a with cancer development, however, little is known about its potential role in gastric carcinogenesis. In our present study, obviously overexpressed miR-106a was found in gastric cancer tissues compared with their nontumor counterparts. Suppression of miR-106a significantly inhibited gastric cancer cell proliferation and triggered apoptosis. Bioinformatic analysis combining with validation experiments identified FAS as a direct target of miR-106a. Rescue experiments and examination of caspase-8, PARP and caspase-3 further approved that miR-106a could inhibit gastric cancer cell apoptosis through interfering with FAS-mediated apoptotic pathway. Moreover, a significant inverse correlation was found between miR-106a and FAS expression not only in gastric cancer cell lines but also in gastric cancer specimens. Taken together, these findings suggest that ectopicly overexpressed miR-106a may play an oncogenic role in gastric carcinogenesis and impair extrinsic apoptotic pathway through targeting FAS.

Artificial confocal microscopy for deep label-free imaging.

Widefield microscopy of optically thick specimens typically features reduced contrast due to "spatial crosstalk", in which the signal at each point in the field of view is the result of a superposition from neighbouring points that are simultaneously illuminated. In 1955, Marvin Minsky proposed confocal microscopy as a solution to this problem. Today, laser scanning confocal fluorescence microscopy is broadly used due to its high depth resolution and sensitivity, but comes at the price of photobleaching, chemical, and photo-toxicity. Here, we present artificial confocal microscopy (ACM) to achieve confocal-level depth sectioning, sensitivity, and chemical specificity, on unlabeled specimens, nondestructively. We equipped a commercial laser scanning confocal instrument with a quantitative phase imaging module, which provides optical path-length maps of the specimen in the same field of view as the fluorescence channel. Using pairs of phase and fluorescence images, we trained a convolution neural network to translate the former into the latter. The training to infer a new tag is very practical as the input and ground truth data are intrinsically registered, and the data acquisition is automated. The ACM images present significantly stronger depth sectioning than the input (phase) images, enabling us to recover confocal-like tomographic volumes of microspheres, hippocampal neurons in culture, and 3D liver cancer spheroids. By training on nucleus-specific tags, ACM allows for segmenting individual nuclei within dense spheroids for both cell counting and volume measurements. In summary, ACM can provide quantitative, dynamic data, nondestructively from thick samples, while chemical specificity is recovered computationally.

Cell Cycle Stage Classification Using Phase Imaging with Computational Specificity.

Traditional methods for cell cycle stage classification rely heavily on fluorescence microscopy to monitor nuclear dynamics. These methods inevitably face the typical phototoxicity and photobleaching limitations of fluorescence imaging. Here, we present a cell cycle detection workflow using the principle of phase imaging with computational specificity (PICS). The proposed method uses neural networks to extract cell cycle-dependent features from quantitative phase imaging (QPI) measurements directly. Our results indicate that this approach attains very good accuracy in classifying live cells into G1, S, and G2/M stages, respectively. We also demonstrate that the proposed method can be applied to study single-cell dynamics within the cell cycle as well as cell population distribution across different stages of the cell cycle. We envision that the proposed method can become a nondestructive tool to analyze cell cycle progression in fields ranging from cell biology to biopharma applications.

Live-dead assay on unlabeled cells using phase imaging with computational specificity.

Existing approaches to evaluate cell viability involve cell staining with chemical reagents. However, the step of exogenous staining makes these methods undesirable for rapid, nondestructive, and long-term investigation. Here, we present an instantaneous viability assessment of unlabeled cells using phase imaging with computation specificity. This concept utilizes deep learning techniques to compute viability markers associated with the specimen measured by label-free quantitative phase imaging. Demonstrated on different live cell cultures, the proposed method reports approximately 95% accuracy in identifying live and dead cells. The evolution of the cell dry mass and nucleus area for the labeled and unlabeled populations reveal that the chemical reagents decrease viability. The nondestructive approach presented here may find a broad range of applications, from monitoring the production of biopharmaceuticals to assessing the effectiveness of cancer treatments.

High expression of survivin predicts poor prognosis in esophageal squamous cell carcinoma following radiotherapy.

Radiotherapy is one of the main treatments for esophageal squamous cell carcinoma, but there are still no biomarkers to differentiate patients who will benefit from radiation. Although treatment with a combination of radiotherapy with chemotherapy, and/or surgery improves the prognosis of patients, no biomarkers can distinguish between the responses obtained with the combined therapies. Therefore, in this study, we selected patients treated with radiotherapy alone to evaluate survivin as a predictor for radiotherapy. One hundred two biopsy samples collected by endoscopy were immunostained by survivin antibody. Positive staining for survivin was obtained in 60.8% tumor samples. Survivin expression, metastasis, and clinical stage correlated significantly with overall survival. In multivariate analysis, survivin was an independent prognostic factor for predicting overall survival of patients with esophageal cancer. Moreover, in esophageal cancer cell lines, overexpression of survivin reduced the percentage of cell death induced by radiation. Our data indicate that survivin could be a potential predictor to define those patients with esophageal squamous carcinoma who would benefit from radiotherapy.

Synthetic aperture interference light (SAIL) microscopy for high-throughput label-free imaging.

Quantitative phase imaging (QPI) is a valuable label-free modality that has gained significant interest due to its wide potentials, from basic biology to clinical applications. Most existing QPI systems measure microscopic objects via interferometry or nonlinear iterative phase reconstructions from intensity measurements. However, all imaging systems compromise spatial resolution for the field of view and vice versa, i.e., suffer from a limited space bandwidth product. Current solutions to this problem involve computational phase retrieval algorithms, which are time-consuming and often suffer from convergence problems. In this article, we presented synthetic aperture interference light (SAIL) microscopy as a solution for high-resolution, wide field of view QPI. The proposed approach employs low-coherence interferometry to directly measure the optical phase delay under different illumination angles and produces large space-bandwidth product label-free imaging. We validate the performance of SAIL on standard samples and illustrate the biomedical applications on various specimens: pathology slides, entire insects, and dynamic live cells in large cultures. The reconstructed images have a synthetic numeric aperture of 0.45 and a field of view of 2.6 × 2.6 mm2. Due to its direct measurement of the phase information, SAIL microscopy does not require long computational time, eliminates data redundancy, and always converges.

EGFR-IL-6 Signaling Axis Mediated the Inhibitory Effect of Methylseleninic Acid on Esophageal Squamous Cell Carcinoma.

Epidemiological and experimental evidence indicate that selenium is associated with a reduced risk of some cancers, including esophageal cancer. However, the exact mechanism is still unclear. In the present study, we used esophageal squamous cell carcinoma (ESCC) cell lines and animal models to explore the anti-cancer mechanism of methylseleninic acid (MSA). Firstly, MSA treatment dramatically attenuated Epidermal Growth Factor Receptor (EGFR) protein expression but did not alter mRNA levels in ESCC cells. On the contrary, EGFR overexpression partly abolished the inhibitory effect of MSA. With a microRNA-array, we found MSA up-regulated miR-146a which directly targeted EGFR, whereas miR-146a inhibitor antagonized MSA-induced decrease of EGFR protein. We further used 4-nitroquinoline-1-oxide (4NQO)-induced esophageal tumor mice model to evaluate the inhibitory effect of MSA in vivo. MSA treatment significantly decreased the tumor burden and EGFR protein expression in tumor specimens. Furthermore, MSA treatment inhibited EGFR pathway and subsequntly reduced Interleukin-6 (IL-6) secretion in the supernatant of cancer cell lines. MSA-induced IL-6 suppression was EGFR-dependent. To further evaluate the association of IL-6 and the anti-tumor effect of MSA on esophageal cancer, we established the 4NQO-induced esophageal tumor model in IL-6 knock-out (IL-6 KO) mice. The results showed that IL-6 deficiency did not affect esophageal tumorigenesis in mice, but the inhibitory effect of MSA was abolished in IL-6 KO mice. In conclusion, our study demonstrated that MSA upregulated miR-146a which directly targeted EGFR, and inhibited EGFR protein expression and pathway activity, subsequently decreased IL-6 secretion. The inhibitory effect of MSA on esophageal cancer was IL-6 dependent. These results suggested that MSA may serve as a potential drug treating esophageal cancer.

Wolf phase tomography (WPT) of transparent structures using partially coherent illumination.

In 1969, Emil Wolf proposed diffraction tomography using coherent holographic imaging to extract 3D information from transparent, inhomogeneous objects. In the same era, the Wolf equations were first used to describe the propagation correlations associated with partially coherent fields. Combining these two concepts, we present Wolf phase tomography (WPT), which is a method for performing diffraction tomography using partially coherent fields. WPT reconstruction works directly in the space-time domain, without the need for Fourier transformation, and decouples the refractive index (RI) distribution from the thickness of the sample. We demonstrate the WPT principle using the data acquired by a quantitative-phase-imaging method that upgrades an existing phase-contrast microscope by introducing controlled phase shifts between the incident and scattered fields. The illumination field in WPT is partially spatially coherent (emerging from a ring-shaped pupil function) and of low temporal coherence (white light), and as such, it is well suited for the Wolf equations. From three intensity measurements corresponding to different phase-contrast frames, the 3D RI distribution is obtained immediately by computing the Laplacian and second time derivative of the measured complex correlation function. We validate WPT with measurements of standard samples (microbeads), spermatozoa, and live neural cultures. The high throughput and simplicity of this method enables the study of 3D, dynamic events in living cells across the entire multiwell plate, with an RI sensitivity on the order of 10-5.

Harmonic optical tomography of nonlinear structures.

Second-harmonic generation microscopy is a valuable label-free modality for imaging non-centrosymmetric structures and has important biomedical applications from live-cell imaging to cancer diagnosis. Conventional second-harmonic generation microscopy measures intensity signals that originate from tightly focused laser beams, preventing researchers from solving the scattering inverse problem for second-order nonlinear materials. Here, we present harmonic optical tomography (HOT) as a novel modality for imaging microscopic, nonlinear and inhomogeneous objects. The HOT principle of operation relies on inter-ferometrically measuring the complex harmonic field and using a scattering inverse model to reconstruct the three-dimensional distribution of harmonophores. HOT enables strong axial sectioning via the momentum conservation of spatially and temporally broadband fields. We illustrate the HOT operation with experiments and reconstructions on a beta-barium borate crystal and various biological specimens. Although our results involve second-order nonlinear materials, we show that this approach applies to any coherent nonlinear process.

Electrothermal soft manipulator enabling safe transport and handling of thin cell/tissue sheets and bioelectronic devices.

"Living" cell sheets or bioelectronic chips have great potentials to improve the quality of diagnostics and therapies. However, handling these thin and delicate materials remains a grand challenge because the external force applied for gripping and releasing can easily deform or damage the materials. This study presents a soft manipulator that can manipulate and transport cell/tissue sheets and ultrathin wearable biosensing devices seamlessly by recapitulating how a cephalopod's suction cup works. The soft manipulator consists of an ultrafast thermo-responsive, microchanneled hydrogel layer with tissue-like softness and an electric heater layer. The electric current to the manipulator drives microchannels of the gel to shrink/expand and results in a pressure change through the microchannels. The manipulator can lift/detach an object within 10 s and can be used repeatedly over 50 times. This soft manipulator would be highly useful for safe and reliable assembly and implantation of therapeutic cell/tissue sheets and biosensing devices.

Optical excitation and detection of neuronal activity.

Optogenetics has emerged as an exciting tool for manipulating neural activity, which in turn, can modulate behavior in live organisms. However, detecting the response to the optical stimulation requires electrophysiology with physical contact or fluorescent imaging at target locations, which is often limited by photobleaching and phototoxicity. In this paper, we show that phase imaging can report the intracellular transport induced by optogenetic stimulation. We developed a multimodal instrument that can both stimulate cells with subcellular spatial resolution and detect optical pathlength (OPL) changes with nanometer scale sensitivity. We found that OPL fluctuations following stimulation are consistent with active organelle transport. Furthermore, the results indicate a broadening in the transport velocity distribution, which is significantly higher in stimulated cells compared to optogenetically inactive cells. It is likely that this label-free, contactless measurement of optogenetic response will provide an enabling approach to neuroscience.

Epi-illumination gradient light interference microscopy for imaging opaque structures.

Multiple scattering and absorption limit the depth at which biological tissues can be imaged with light. In thick unlabeled specimens, multiple scattering randomizes the phase of the field and absorption attenuates light that travels long optical paths. These obstacles limit the performance of transmission imaging. To mitigate these challenges, we developed an epi-illumination gradient light interference microscope (epi-GLIM) as a label-free phase imaging modality applicable to bulk or opaque samples. Epi-GLIM enables studying turbid structures that are hundreds of microns thick and otherwise opaque to transmitted light. We demonstrate this approach with a variety of man-made and biological samples that are incompatible with imaging in a transmission geometry: semiconductors wafers, specimens on opaque and birefringent substrates, cells in microplates, and bulk tissues. We demonstrate that the epi-GLIM data can be used to solve the inverse scattering problem and reconstruct the tomography of single cells and model organisms.

LKB1 and YAP phosphorylation play important roles in Celastrol-induced ß-catenin degradation in colorectal cancer.

Wnt/ß-catenin and Hippo pathways play essential roles in the tumorigenesis and development of colorectal cancer. We found that Celastrol, isolated from Tripterygium wilfordii plant, exerted a significant inhibitory effect on colorectal cancer cell growth in vitro and in vivo, and further unraveled the molecular mechanisms. Celastrol induced ß-catenin degradation through phosphorylation of Yes-associated protein (YAP), a major downstream effector of Hippo pathway, and also Celastrol-induced ß-catenin degradation was dependent on liver kinase B1 (LKB1). Celastrol increased the transcriptional activation of LKB1, partially through the heat shock factor 1 (HSF1). Moreover, LKB1 activated AMP-activated protein kinase α (AMPKα) and further phosphorylated YAP, which eventually promoted the degradation of ß-catenin. In addition, LKB1 deficiency promoted colorectal cancer cell growth and attenuated the inhibitory effect of Celastrol on colorectal cancer growth both in vitro and in vivo. Taken together, Celastrol inhibited colorectal cancer cell growth by promoting ß-catenin degradation via the HSF1-LKB1-AMPKα-YAP pathway. These results suggested that Celastrol may potentially serve as a future drug for colorectal cancer treatment.