Gemini Quaternary Ammonium Surfactants with Different Counterions-modified Montmorillonite for Efficient Removal of Methyl Orange.

Organic Na-montmorillonite (OMt-12-2-12·2Y - , Y=CH 3 CO 3 - , C 6 H 5 COO - and Br - ) modified by a series of Gemini quaternary ammonium surfactants with different counterions was prepared for enhancing the adsorption capacity of methyl orange. Compared with the initial adsorption capacity of 5.251 mg/g of Na-Mt, the adsorption effect of OMts under the optimal conditions increased by about 31~34 times. The adsorption isotherms and kinetics of all adsorption processes were respectively described by Langmuir and pseudo-second-order models. The structure, hydrophobicity and hydration of the counterions, as well as the affinity of the counterions with the long aliphatic chains, had a certain influence on the adsorption performance of OMts for methyl orange.

LTN1 promotes RLR degradation to inhibit immune response to RNA virus through the ESCRT pathway.

The excessive activation of immune responses will trigger autoimmune diseases or inflammatory injury. The endosomal sorting complexes required for transport (ESCRT) system can capture and mediate ubiquitinated protein degradation, which timely terminates signaling pathway hyperactivation. However, whether the ESCRT system participates in regulating RIGI-like receptor (RLR)-mediated antiviral responses remains unknown. In this study, we show that LTN1/listerin, a major component of RQC, can recruit E3 ubiquitin ligase TRIM27 to trigger K63-linked polyubiquitination of RIGI and IFIH1/MDA5. This K63-linked polyubiquitination facilitates the sorting and degradation of RIGI and IFIH1 proteins through the ESCRT-dependent pathway. Concordantly, LTN1 deficiency enhances the innate antiviral response to infection with RNA viruses. Thus, our work uncovers a new mechanism for RIGI and IFIH1 degradation and identifies the role of LTN1 in negatively regulating RLR-mediated antiviral innate immunity, which may provide new targets for the intervention of viral infection.Abbreviation: 5'-pppRNA: 5' triphosphate double stranded RNA; ATG5: autophagy related 5; ATG7: autophagy related 7; BafA1: bafilomycin A1; ESCRT: endosomal sorting complexes required for transport; CHX: cycloheximide; IFIH1/MDA5: interferon induced with helicase C domain 1; IFN: interferon; PIK3C3/VPS34: phosphatidylinositol 3-kinase catalytic subunit type 3; RIGI: RNA sensor RIG-I; RLR: RIGI-like receptors; RQC: ribosome-associated protein quality control; SeV: Sendai virus; TRIM27: tripartite motif-containing 27; VSV: vesicular stomatitis virus; VPS4: vacuolar protein sorting 4.

Listerin promotes cGAS protein degradation through the ESCRT pathway to negatively regulate cGAS-mediated immune response.

The enzyme cyclic GMP-AMP synthase (cGAS) is a key sensor for detecting misplaced double-stranded DNA (dsDNA) of genomic, mitochondrial, and microbial origin. It synthesizes 2'3'-cGAMP, which in turn activates the stimulator of interferon genes pathway, leading to the initiation of innate immune responses. Here, we identified Listerin as a negative regulator of cGAS-mediated innate immune response. We found that Listerin interacts with cGAS on endosomes and promotes its K63-linked ubiquitination through recruitment of the E3 ligase TRIM27. The polyubiquitinated cGAS is then recognized by the endosomal sorting complexes required for transport machinery and sorted into endosomes for degradation. Listerin deficiency enhances the innate antiviral response to herpes simplex virus 1 infection. Genetic deletion of Listerin also deteriorates the neuroinflammation and the ALS disease progress in an ALS mice model; overexpression of Listerin can robustly ameliorate disease progression in ALS mice. Thus, our work uncovers a mechanism for cGAS regulation and suggests that Listerin may be a promising therapeutic target for ALS disease.

Displacement and strain mapping for osteocytes under fluid shear stress using digital holographic microscopy and digital image correlation.

Osteocytes, as the mechano-sensors in bone, are always subjected to fluid shear stress (FSS) from the surrounding matrix. Quantification of FSS-induced cellular deformation is significant for clarifying the "perceive and transmit" process of cellular mechanotransduction. In this research, a label-free displacement and strain mapping method based on digital holographic microscopy (DHM) and digital image correlation (DIC) is introduced. The method, which is termed DHM-DIC, innovatively utilizes surface features extracted from holographic phase images instead of speckles as the metric for DIC searching. Simulation results on a hemisphere validate the feasibility of DHM-DIC. Displacement and strain maps of living osteocytes under 1.5 Pa FSS are evaluated from DHM-DIC and present good agreement with our previous finite element modeling results.

Sensing morphogenesis of bone cells under microfluidic shear stress by holographic microscopy and automatic aberration compensation with deep learning.

We present sensing time-lapse morphogenesis of living bone cells under micro-fluidic shear stress (FSS) by digital holographic (DH) microscopy. To remove the effect of aberrations on quantitative measurements, we propose a numerical and automatic method to compensate for aberrations based on a convolutional neural network (CNN). For the first time, the aberration compensation issue is considered as a regression task where optimal coefficients for constructing the phase aberration map act as responses corresponding to the input aberrated phase image. We adopted tens of thousands of living cells' phase images reconstructed from digital holograms for training the CNN. The experiments demonstrate that, based on the trained network, phase aberrations can be totally removed in real-time without any hypothesis of object and aberration phase, knowledge of the setup's physical parameters, and the operation of selecting background regions; hence, the morphogenesis of the bone cells under FSS is accurately detected and quantitatively analyzed. The results show that the proposed method could provide a highly efficient and versatile way to investigate the effects of micro-FSS on living biological cells in microfluidic lab-on-chip platforms thanks to the combination of phase-contrast label-free microcopy with artificial intelligence.

Spontaneous cellular vibratory motions of osteocytes are regulated by ATP and spectrin network.

Vibration at high frequency has been demonstrated to be anabolic for bone and embedded osteocytes. The response of osteocytes to vibration is frequency-dependent, but the mechanism remains unclear. Our previous computational study using an osteocyte finite element model has predicted a resonance effect involving in the frequency-dependent response of osteocytes to vibration. However, the cellular spontaneous vibratory motion of osteocytes has not been confirmed. In the present study, the cellular vibratory motions (CVM) of osteocytes were recorded by a custom-built digital holographic microscopy and quantitatively analyzed. The roles of ATP and spectrin network in the CVM of osteocytes were studied. Results showed the MLO-Y4 osteocytes displayed dynamic vibratory motions with an amplitude of ~80 nm, which is relied both on the ATP content and spectrin network. Spectrum analysis showed several frequency peaks in CVM of MLO-Y4 osteocytes at 30 Hz, 39 Hz, 83 Hz and 89 Hz. These peak frequencies are close to the commonly used effective frequencies in animal training and in-vitro cell experiments, and show a correlation with the computational predictions of the osteocyte finite element model. These results implicate that osteocytes are dynamic and the cellular dynamic motion is involved in the cellular mechanotransduction of vibration.

Adaptive frequency filtering based on convolutional neural networks in off-axis digital holographic microscopy.

Digital holographic microscopy (DHM) as a label-free quantitative imaging tool has been widely used to investigate the morphology of living cells dynamically. In the off-axis DHM, the spatial filtering in the frequency spectrum of the hologram is vital to the quality of the reconstructed images. In this paper, we propose an adaptive spatial filtering approach based on convolutional neural networks (CNN) to automatically extracts the optimal shape of frequency components. For achieving robust and precise recognition performance, the net model is trained by using the tens of thousands of frequency spectrums with a variety of specimens and imaging conditions. The experimental results demonstrate that the trained network produce an adaptive spatial filtering window which can accurately select the frequency components of the object term and eliminate the frequency components of the interference terms, especially the coherent noise that overlaps with the object term in the spatial frequency domain. We find that the proposed approach has a fast, robust, and outstanding frequency filtering capability without any manual intervention and initial input parameters compared to previous techniques. Furthermore, the applicability of the proposed method in off-axis DHM for dynamic analysis is demonstrated by real-time monitoring the morphologic changes of living MLO-Y4 cells that are constantly subject to Fluid Shear Stress (FSS).

An optical study of drug resistance detection in endometrial cancer cells by dynamic and quantitative phase imaging.

Platinum chemosensitivity detection plays a vital role during endometrial cancer treatment because chemotherapy responses have profound influences on patient's prognosis. Although several methods can be used to detect drug resistance characteristics, studies on detecting drug sensitivity based on dynamic and quantitative phase imaging of cancer cells are rare. In this study, digital holographic microscopy was applied to distinguish drug-resistant and nondrug-resistant endometrial cancer cells. Based on the reconstructed phase images, temporal evolutions of cell height (CH), cell projected area (CPA) and cell volume were quantitatively measured. The results show that change rates of CH and CPA were significantly different between drug-resistant and nondrug-resistant endometrial cancer cells. Furthermore, the results demonstrate that morphological characteristics have the potential to be utilized to distinguish the drug sensitivity of endometrial cancer cells, and it may provide new perspectives to establish optical methods to detect drug sensitivity and guide chemotherapy in endometrial cancer.

Quantitative observations on cytoskeleton changes of osteocytes at different cell parts using digital holographic microscopy.

Cytoskeletons such as F-actin have different distributions in different cell parts and they are the cause of different degrees of cell collapse when the F-actin is disrupted. It is challenging to use conventional methods such as fluorescence microscopy and atomic force microscopy to conduct real-time and three-dimensional observations on the dynamic processes at different cell parts due to the slow measuring speed and the need for live-cell staining. In this study, the morphological variations of different bone cell parts caused by F-actin disruption are dynamically measured by using digital holographic microscopy (DHM). We separately analyze local parameters (cell height and cell width) and global parameters (cell projected area and cell volume) of cells to address variations of specific cell areas and quantify the changing process of the whole cell. We found significant differences in temporal variations of both local and global cell parameters between the cell body and cell process, which is consistent with the qualitative observation by fluorescence staining. Our study not only validates the unique ability of DHM to simultaneously investigate the dynamic process at different cell parts, but also provides sufficient experimental bases for exploring the mechanism for F-actin disruption.