Mature microRNA-binding protein QKI promotes microRNA-mediated gene silencing.

Although Argonaute (AGO) proteins have been the focus of microRNA (miRNA) studies, we observed AGO-free mature miRNAs directly interacting with RNA-binding proteins, implying the sophisticated nature of fine-tuning gene regulation by miRNAs. To investigate microRNA-binding proteins (miRBPs) globally, we analyzed PAR-CLIP data sets to identify RBP quaking (QKI) as a novel miRBP for let-7b. Potential existence of AGO-free miRNAs were further verified by measuring miRNA levels in genetically engineered AGO-depleted human and mouse cells. We have shown that QKI regulates miRNA-mediated gene silencing at multiple steps, and collectively serves as an auxiliary factor empowering AGO2/let-7b-mediated gene silencing. Depletion of QKI decreases interaction of AGO2 with let-7b and target mRNA, consequently controlling target mRNA decay. This finding indicates that QKI is a complementary factor in miRNA-mediated mRNA decay. QKI, however, also suppresses the dissociation of let-7b from AGO2, and slows the assembly of AGO2/miRNA/target mRNA complexes at the single-molecule level. We also revealed that QKI overexpression suppresses cMYC expression at post-transcriptional level, and decreases proliferation and migration of HeLa cells, demonstrating that QKI is a tumour suppressor gene by in part augmenting let-7b activity. Our data show that QKI is a new type of RBP implicated in the versatile regulation of miRNA-mediated gene silencing.

T cell-specific siRNA delivery suppresses HIV-1 infection in humanized mice.

Evaluation of the therapeutic potential of RNAi for HIV infection has been hampered by the challenges of siRNA delivery and lack of suitable animal models. Using a delivery method for T cells, we show that siRNA treatment can dramatically suppress HIV infection. A CD7-specific single-chain antibody was conjugated to oligo-9-arginine peptide (scFvCD7-9R) for T cell-specific siRNA delivery in NOD/SCIDIL2rgamma-/- mice reconstituted with human lymphocytes (Hu-PBL) or CD34+ hematopoietic stem cells (Hu-HSC). In HIV-infected Hu-PBL mice, treatment with anti-CCR5 (viral coreceptor) and antiviral siRNAs complexed to scFvCD7-9R controlled viral replication and prevented the disease-associated CD4 T cell loss. This treatment also suppressed endogenous virus and restored CD4 T cell counts in mice reconstituted with HIV+ peripheral blood mononuclear cells. Moreover, scFvCD7-9R could deliver antiviral siRNAs to naive T cells in Hu-HSC mice and effectively suppress viremia in infected mice. Thus, siRNA therapy for HIV infection appears to be feasible in a preclinical animal model.

Endoplasmic reticulum stress increases LECT2 expression via ATF4.

Non-alcoholic fatty liver disease (NAFLD) is frequently associated with obesity, insulin resistance, and endoplasmic reticulum (ER) stress. Elevated circulating levels of the hepatokine leukocyte cell-derived chemotaxin-2 (LECT2) have also been noted in NAFLD; however, the mechanism underlying this association is unclear. To investigate a possible link between ER stress/unfolded protein response (UPR) signaling and LECT2 secretion, HepG2 cells were incubated with ER stress inducers with or without an ER stress-reducing chemical chaperone. Additionally, UPR pathway genes were knocked down and overexpressed, and a ChIP assay was performed. In diet-induced obese mice, hepatic expression of LECT2 and activating transcription factor 4 (ATF4) was measured. In HepG2 cells, LECT2 expression was increased by ER stressors, an effect blocked by the chemical chaperone. Among UPR pathway proteins, only knockdown of ATF4 suppressed ER stress-induced LECT2 expression, while overexpression of ATF4 enhanced LECT2 expression. The ChIP assay revealed that ATF4 binds to three putative binding sites on the LECT2 promoter and binding is promoted by an ER stress inducer. In steatotic livers of obese mice, LECT2 and ATF4 expression was concomitantly elevated. Our data indicate that activation of ER stress/UPR signaling induces LECT2 expression in steatotic liver; specifically, ATF4 appears to mediate upregulation of LECT2 transcription.

Transient Hydrodynamic Lattice Cooling by Picosecond Laser Irradiation of Graphite.

Recent theories and experiments have suggested hydrodynamic phonon transport features in graphite at unusually high temperatures. Here, we report a picosecond pump-probe thermal reflectance measurement of heat-pulse propagation in graphite. The measurement results reveal transient lattice cooling near the adiabatic center of a 15-µm-diameter ring-shape pump beam at temperatures between 80 and 120 K. While such lattice cooling has not been reported in recent diffraction measurements of second sound in graphite, the observation here is consistent with both hydrodynamic phonon transport theory and prior heat-pulse measurements of second sound in bulk sodium fluoride.

Development of a Human-Display Interface with Vibrotactile Feedback for Real-World Assistive Applications.

It is important to operate devices with control panels and touch screens assisted by haptic feedback in mobile environments such as driving automobiles and electric power wheelchairs. A lot of consideration is needed to give accurate haptic feedback, especially, presenting clear touch feedback to the elderly and people with reduced sensation is a very critical issue from healthcare and safety perspectives. In this study, we aimed to identify the perceptual characteristics for the frequency and direction of haptic vibration on the touch screen with vehicle-driving vibration and to propose an efficient haptic system based on these characteristics. As a result, we demonstrated that the detection threshold shift decreased at frequencies above 210 Hz due to the contact pressure during active touch, but the detection threshold shift increased at below 210 Hz. We found that the detection thresholds were 0.30-0.45 gpeak with similar sensitivity in the 80-270 Hz range. The haptic system implemented by reflecting the experimental results achieved characteristics suitable for use scenarios in automobiles. Ultimately, it could provide practical guidelines for the development of touch screens to give accurate touch feedback in the real-world environment.

Tyrosine phosphorylation of HDAC3 by Src kinase mediates proliferation of HER2-positive breast cancer cells.

The role of histone deacetylase 3 (HDAC3) is to repress the expression of various genes by eliminating acetyl group from histone. Thus, the regulation of HDAC3 activity is essential to maintain cellular homeostasis. In this study, we found that HDAC3 interacts with c-Src kinase. However, the interaction between HDAC3 and c-Src was previously reported, it has still been ambiguous whether c-Src phosphorylates HDAC3 and affects the function of HDAC3. First, we confirmed that HDAC3 directly binds to c-Src, and c-Src identified to interact with C-terminal domain (277-428 a.a.) of HDAC3. c-Src also phosphorylated three tyrosine sites of HDAC3 at tyrosine 325, 328, and 331. Importantly, wild-type c-Src increases HDAC3 activity, but not mutant c-SrcK298M (kinase inactive form). When these tyrosine residues are all substituted for alanine residues, the deacetylase activity of mutant HDAC3 was abolished. In addition, a proliferation of HER2-positive breast cancer cells expressing phosphorylation deficient mutant HDAC3 is decreased in comparison with control cells. Thus, our findings suggested that phosphorylation of HDAC3 by c-Src kinase regulates the HDAC3 activity and the proliferation of breast cancer cells.

Novel TGF-ß1 inhibitor antagonizes TGF-ß1-induced epithelial-mesenchymal transition in human A549 lung cancer cells.

Transforming growth factor ß1 (TGF-ß1), a multifunctional cytokine, is known to promote tumor invasion and metastasis and induce epithelial-mesenchymal transition (EMT) in various cancer cells. Inhibition of TGF-ß1 signaling is a new strategy for cancer therapy. Most cancer cells display altered or nonfunctional TGF-ß1 signaling; hence, TGF-ß1 inhibitors exert limited effects on these cells. Recent studies have suggested that developing a TGF-ß1 inhibitor from natural compounds is a key step to create novel therapeutic agents. This study aimed to develop a new anti-TGF-ß1 therapy for cancer. We found an improved analog of chalcones, compound 67, and investigated its effects in vitro. We demonstrated the inhibitory role of compound 67 through migration and invasion assays on TGF-ß1-induced EMT of human A549 lung cancer cells. Compound 67 inhibited TGF-ß1-induced smad2 phosphorylation, suppressed TGF-ß1-induced EMT markers, matrix metalloproteinase-2 (MMP-2) and MMP-9, and inhibited migration and invasion of A549 cells. The study results showed that compound 67 is useful to prevent tumor growth and metastasis.

Thermal Conductivity Enhancement in MoS_{2} under Extreme Strain.

Because of their weak interlayer bonding, van der Waals (vdW) solids are very sensitive to external stimuli such as strain. Experimental studies of strain tuning of thermal properties in vdW solids have not yet been reported. Under ∼9% cross-plane compressive strain created by hydrostatic pressure in a diamond anvil cell, we observed an increase of cross-plane thermal conductivity in bulk MoS_{2} from 3.5 to about 25 W m^{-1} K^{-1}, measured with a picosecond transient thermoreflectance technique. First-principles calculations and coherent phonon spectroscopy experiments reveal that this drastic change arises from the strain-enhanced interlayer interaction, heavily modified phonon dispersions, and decrease in phonon lifetimes due to the unbundling effect along the cross-plane direction. The contribution from the change of electronic thermal conductivity is negligible. Our results suggest possible parallel tuning of structural, thermal, and electrical properties of vdW solids with strain in multiphysics devices.

Jones calculus modeling and analysis of the thermal distortion in a Ti:sapphire laser amplifier: erratum.

Equations 41-44 in our paper [ Opt. Express26, 14362 (2016)] contain errors. We correct the equations in this erratum.

Numerical extension of Frantz-Nodvik equation for double-pass amplifiers with pulse overlap.

We developed a new numerical simulation method to calculate the amplification of arbitrary laser pulses in double-pass amplifiers in which two polarization-orthogonal pulses inside the gain medium overlap. The proposed method agrees very well with the experimental results given in this work for the pulse energy and temporal shape.

Jones calculus modeling and analysis of the thermal distortion in a Ti:sapphire laser amplifier.

The mathematical modeling of an anisotropic Ti:sapphire crystal with a significant thermal load is performed. The model is expressed by the differential Jones matrix. A thermally induced distortion in the chirped-pulse amplification process is shown by the solution of the differential Jones matrix. Using this model, the thermally distorted spatio-temporal laser beam shape is calculated for a high-power and high-repetition-rate Ti:sapphire amplifier.

Intracellular uptake and pH-dependent release of doxorubicin from the self-assembled micelles based on amphiphilic polyaspartamide graft copolymers.

Biodegradable and pH-sensitive graft copolymers based on polysuccinimide (PSI) were synthesized as intracellular drug carriers. Hydrophobic octadecylamine (C18) and hydrophilic O-(2-aminoethyl) polyethylene glycol (PEG, Mw 5000) were grafted on a PSI backbone for amphiphilicity, enabling the formation of a self-assembled micellar structure in aqueous medium. Biotin was conjugated at the end of the PEG segment as the cell penetrating ligand, and hydrazone hydrate was introduced as a cleavable linkage for the release of pH sensitive drug, doxorubicin. The chemical structure of the polymer and degree of substitution of the graft segments were confirmed by Fourier transform infrared (FTIR) and (1)H NMR spectroscopy. The size and distribution of the polymer micelles were investigated by dynamic light scattering. The average diameter of the polymer micelles was 290-310 nm with a narrow distribution. Less than 30% of the total DOX loaded in the polymeric micelles was released at pH 7.4, whereas >75% was released at pH 5 in 70 h because of the cleavage of the hydrazone bond in acidic conditions. For the cytotoxicity test, the MCF-7 cell viability in the presence of biotin-conjugated polymer was much lower than that in the presence of a nonconjugated one, as the former had higher probability of cell penetration aided by a biotin ligand. The DOX uptake in MCF-7 cells was analyzed by the confocal laser scanning microscopy. More DOX uptake was observed in acidic conditions because of the cleavage of hydrazone groups in the polymer.

DeepHealthNet: Adolescent Obesity Prediction System Based on a Deep Learning Framework.

The global prevalence of childhood and adolescent obesity is a major concern due to its association with chronic diseases and long-term health risks. Artificial intelligence technology has been identified as a potential solution to accurately predict obesity rates and provide personalized feedback to adolescents. This study highlights the importance of early identification and prevention of obesity-related health issues. To develop effective algorithms for the prediction of obesity rates and provide personalized feedback, factors such as height, weight, waist circumference, calorie intake, physical activity levels, and other relevant health information must be taken into account. Therefore, by collecting health datasets from 321 adolescents who participated in Would You Do It! application, we proposed an adolescent obesity prediction system that provides personalized predictions and assists individuals in making informed health decisions. Our proposed deep learning framework, DeepHealthNet, effectively trains the model using data augmentation techniques, even when daily health data are limited, resulting in improved prediction accuracy (acc: 0.8842). Additionally, the study revealed variations in the prediction of the obesity rate between boys (acc: 0.9320) and girls (acc: 0.9163), allowing the identification of disparities and the determination of the optimal time to provide feedback. Statistical analysis revealed that the performance of the proposed deep learning framework was more statistically significant (p 0.001) compared to the other general models. The proposed system has the potential to effectively address childhood and adolescent obesity.

Inhibitory effect of doxycycline conjugated with deoxycholic acid and polyethylenimine conjugate on nasal fibroblast differentiation and extracellular production.

BACKGROUND: Chronic rhinosinusitis (CRS) is an inflammatory disease affecting the sinuses or nose. Persistent inflammatory responses can lead to tissue remodeling, which is a pathological characteristics of CRS. Activation of fibroblasts in the nasal mucosal stroma, differentiation and collagen deposition, and subepithelial fibrosis have been associated with CRS. OBJECTIVES: We aimed to assess the inhibitory effects of doxycycline and deoxycholic acid-polyethyleneimine conjugate (DA3-Doxy) on myofibroblast differentiation and extracellular matrix (ECM) production in nasal fibroblasts stimulated with TGF-ß1. METHODS: To enhance efficacy, we prepared DA3-Doxy using a conjugate of low-molecular-weight polyethyleneimine (PEI) (MW 1800) and deoxycholic acid (DA) and Doxy. The synthesis of the DA3-Doxy polymer was confirmed using nuclear magnetic resonance, and the critical micelle concentration required for cationic micelle formation through self-assembly was determined. Subsequently, the Doxy loading efficiency of DA3 was assessed. The cytotoxicity of Doxy, DA3, PEI, and DA-Doxy in nasal fibroblasts was evaluated using the WST-1 assay. The anti-tissue remodeling and anti-inflammatory effects of DA3-Doxy and DA3 were examined using real-time polymerase chain reaction (Real-time PCR), immunocytochemistry, western blot, and Sircol assay. RESULTS: Both DA3 and DA3-Doxy exhibited cytotoxicity at 10 µg/ml in nasal fibroblasts. Doxy partially inhibited α-smooth muscle actin, collagen types I and III, and fibronectin. However, DA3-Doxy significantly inhibited α-SMA, collagen types I and III, and fibronectin at 5 µg/ml. DA3-Doxy also modulated TGF-ß1-induced changes in the expression of MMP 1, 2, and 9. Nonetheless, TGF-ß1-induced expression of MMP3 was further increased by DA3-Doxy. The expression of TIMP 1 and 2 was partially reduced with 5 µg/ml DA3-Doxy. CONCLUSIONS: Although initially developed for the delivery of genetic materials or drugs, DA3 exhibits inhibitory effects on myofibroblast differentiation and ECM production. Therefore, it holds therapeutic potential for CRS, and a synergistic effect can be expected when loaded with CRS treatment drugs.

Multi-Task Heterogeneous Ensemble Learning-Based Cross-Subject EEG Classification Under Stroke Patients.

Robot-assisted motor training is applied for neurorehabilitation in stroke patients, using motor imagery (MI) as a representative paradigm of brain-computer interfaces to offer real-life assistance to individuals facing movement challenges. However, the effectiveness of training with MI may vary depending on the location of the stroke lesion, which should be considered. This paper introduces a multi-task electroencephalogram-based heterogeneous ensemble learning (MEEG-HEL) specifically designed for cross-subject training. In the proposed framework, common spatial patterns were used for feature extraction, and the features according to stroke lesions are shared and selected through sequential forward floating selection. The heterogeneous ensembles were used as classifiers. Nine patients with chronic ischemic stroke participated, engaging in MI and motor execution (ME) paradigms involving finger tapping. The classification criteria for the multi-task were established in two ways, taking into account the characteristics of stroke patients. In the cross-subject session, the first involved a direction recognition task for two-handed classification, achieving a performance of 0.7419 (±0.0811) in MI and 0.7061 (±0.1270) in ME. The second task focused on motor assessment for lesion location, resulting in a performance of 0.7457 (±0.1317) in MI and 0.6791 (±0.1253) in ME. Comparing the specific-subject session, except for ME on the motor assessment task, performance on both tasks was significantly higher than the cross-subject session. Furthermore, classification performance was similar to or statistically higher in cross-subject sessions compared to baseline models. The proposed MEEG-HEL holds promise in improving the practicality of neurorehabilitation in clinical settings and facilitating the detection of lesions.

Automatic Sleep Stage Classification Using Nasal Pressure Decoding Based on a Multi-Kernel Convolutional BiLSTM Network.

Sleep quality is an essential parameter of a healthy human life, while sleep disorders such as sleep apnea are abundant. In the investigation of sleep and its malfunction, the gold-standard is polysomnography, which utilizes an extensive range of variables for sleep stage classification. However, undergoing full polysomnography, which requires many sensors that are directly connected to the heaviness of the setup and the discomfort of sleep, brings a significant burden. In this study, sleep stage classification was performed using the single dimension of nasal pressure, dramatically decreasing the complexity of the process. In turn, such improvements could increase the much needed clinical applicability. Specifically, we propose a deep learning structure consisting of multi-kernel convolutional neural networks and bidirectional long short-term memory for sleep stage classification. Sleep stages of 25 healthy subjects were classified into 3-class (wake, rapid eye movement (REM), and non-REM) and 4-class (wake, REM, light, and deep sleep) based on nasal pressure. Following a leave-one-subject-out cross-validation, in the 3-class the accuracy was 0.704, the F1-score was 0.490, and the kappa value was 0.283 for the overall metrics. In the 4-class, the accuracy was 0.604, the F1-score was 0.349, and the kappa value was 0.217 for the overall metrics. This was higher than the four comparative models, including the class-wise F1-score. This result demonstrates the possibility of a sleep stage classification model only using easily applicable and highly practical nasal pressure recordings. This is also likely to be used with interventions that could help treat sleep-related diseases.

Spectral Graph Neural Network-Based Multi-Atlas Brain Network Fusion for Major Depressive Disorder Diagnosis.

Major Depressive Disorder (MDD) imposes a substantial burden within the healthcare domain, impacting millions of individuals worldwide. Functional Magnetic Resonance Imaging (fMRI) has emerged as a promising tool for the objective diagnosis of MDD, enabling the investigation of functional connectivity patterns in the brain associated with this disorder. However, most existing methods focus on a single brain atlas, which limits their ability to capture the complex, multi-scale nature of functional brain networks. To address these limitations, we propose a novel multi-atlas fusion method that incorporates early and late fusion in a unified framework. Our method introduces the concept of the holistic Functional Connectivity Network (FCN), which captures both intra-atlas relationships within individual atlases and inter-regional relationships between atlases with different brain parcellation scales. This comprehensive representation enables the identification of potential disease-related patterns associated with MDD in the early stage of our framework. Moreover, by decoding the holistic FCN from various perspectives through multiple spectral Graph Convolutional Neural Networks and fusing their results with decision-level ensembles, we further improve the performance of MDD diagnosis. Our approach is easily implemented with minimal modifications to existing model structures and demonstrates a robust performance across different baseline models. Our method, evaluated on public resting-state fMRI datasets, surpasses the current multi-atlas fusion methods, enhancing the accuracy of MDD diagnosis. The proposed novel multi-atlas fusion framework provides a more reliable MDD diagnostic technique. Experimental results show our approach outperforms both single- and multi-atlas-based methods, demonstrating its effectiveness in advancing MDD diagnosis.

Targeting of CYP2E1 by miRNAs in alcohol-induced intestine injury.

Although binge alcohol-induced gut leakage has been studied extensively in the context of reactive oxygen species-mediated signaling, it was recently revealed that post-transcriptional regulation plays an essential role as well. Ethanol (EtOH)-inducible cytochrome P450-2E1 (CYP2E1), a key enzyme in EtOH metabolism, promotes alcohol-induced hepatic steatosis and inflammatory liver disease, at least in part by mediating changes in intestinal permeability. For instance, gut leakage and elevated intestinal permeability to endotoxins have been shown to be regulated by enhancing CYP2E1 mRNA and CYP2E1 protein levels. Although it is understood that EtOH promotes CYP2E1 induction and activation, the mechanisms that regulate CYP2E1 expression in the context of intestinal damage remain poorly defined. Specific miRNAs, including miR-132, miR-212, miR-378, and miR-552, have been shown to repress the expression of CYP2E1, suggesting that these miRNAs contribute to EtOH-induced intestinal injury. Here, we have shown that CYP2E1 expression is regulated post-transcriptionally through miRNA-mediated degradation, as follows: (1) the RNA-binding protein AU-binding factor 1 (AUF1) binds mature miRNAs, including CYP2E1-targeting miRNAs, and this binding modulates the degradation of corresponding target mRNAs upon EtOH treatment; (2) the serine/threonine kinase mammalian Ste20-like kinase 1 (MST1) mediates oxidative stress-induced phosphorylation of AUF1. Those findings suggest that reactive oxygen species-mediated signaling modulates AUF1/miRNA interaction through MST1-mediated phosphorylation. Thus, our study demonstrates the critical functions of AUF1 phosphorylation by MST1 in the decay of miRNAs targeting CYP2E1, the stabilization of CYP2E1 mRNA in the presence of EtOH, and the relationship of this pathway to subsequent intestinal injury.

Real-Time Deep Neurolinguistic Learning Enhances Noninvasive Neural Language Decoding for Brain-Machine Interaction.

Electroencephalogram (EEG)-based brain-machine interface (BMI) has been utilized to help patients regain motor function and has recently been validated for its use in healthy people because of its ability to directly decipher human intentions. In particular, neurolinguistic research using EEGs has been investigated as an intuitive and naturalistic communication tool between humans and machines. In this study, the human mind directly decoded the neural languages based on speech imagery using the proposed deep neurolinguistic learning. Through real-time experiments, we evaluated whether BMI-based cooperative tasks between multiple users could be accomplished using a variety of neural languages. We successfully demonstrated a BMI system that allows a variety of scenarios, such as essential activity, collaborative play, and emotional interaction. This outcome presents a novel BMI frontier that can interact at the level of human-like intelligence in real time and extends the boundaries of the communication paradigm.

ZBTB7A suppresses glioblastoma tumorigenesis through the transcriptional repression of EPB41L5.

Glioblastoma multiforme (GBM), the most aggressive and malignant glioma, has a poor prognosis. Although patients with GBM are treated with surgery, chemotherapy, and radiation therapy, GBM is highly resistant to treatment, making it difficult and expensive to treat. In this study, we analyzed the Gene Expression Profiling Interactive Analysis dataset, the Cancer Genome Atlas dataset, and Gene Expression Omnibus array data. ZBTB7A (also called FBI1/POKEMON/LRF) was found to be highly expressed in low-grade glioma but significantly downregulated in patients with GBM. ZBTB7A is a transcription factor that plays an important role in many developmental stages, including cell proliferation. The activation of epithelial-mesenchymal transition (EMT) is a key process in cancer progression and metastasis. Erythrocyte membrane protein band 4.1 like 5 (EPB41L5) is an essential protein for EMT progression and metastasis in various types of cancer. We found that ZBTB7A depletion in U87 cells induced GBM progression and metastasis. Based on RNA sequencing data, ZBTB7A directly binds to the promoter of the EPB41L5 gene, reducing its expression and inhibiting GBM progression. We demonstrated that ZBTB7A dramatically inhibits GBM tumor growth through transcriptional repression of EPB41L5. Thus, both ZBTB7A and EPB41L5 may be potential biomarkers and novel therapeutic targets for GBM treatment. Overall, we discovered the role of a novel tumor suppressor that directly inhibits GBM progression (ZBTB7A) and identified EPB41L5 as a therapeutic target protein for patients with GBM.