A Non-canonical Role of YAP/TEAD Is Required for Activation of Estrogen-Regulated Enhancers in Breast Cancer.

YAP/TEAD are nuclear effectors of the Hippo pathway, regulating organ size and tumorigenesis largely through promoter-associated function. However, their function as enhancer regulators remains poorly understood. Through an in vivo proximity-dependent labeling (BioID) technique, we identified YAP1 and TEAD4 protein as co-regulators of ERα on enhancers. The binding of YAP1/TEAD4 to ERα-bound enhancers is augmented upon E2 stimulation and is required for the induction of E2/ERα target genes and E2-induced oncogenic cell growth. Furthermore, their enhancer binding is a prerequisite for enhancer activation marked by eRNA transcription and for the recruitment of the enhancer activation machinery component MED1. The binding of TEAD4 on active ERE-containing enhancers is independent of its DNA-binding behavior, and instead, occurs through protein-tethering trans-binding. Our data reveal a non-canonical function of YAP1 and TEAD4 as ERα cofactors in regulating cancer growth, highlighting the potential of YAP/TEAD as possible actionable drug targets for ERα+ breast cancer.

Ensemble of kernel ridge regression-based small molecule-miRNA association prediction in human disease.

MicroRNAs (miRNAs) play crucial roles in human disease and can be targeted by small molecule (SM) drugs according to numerous studies, which shows that identifying SM-miRNA associations in human disease is important for drug development and disease treatment. We proposed the method of Ensemble of Kernel Ridge Regression-based Small Molecule-MiRNA Association prediction (EKRRSMMA) to uncover potential SM-miRNA associations by combing feature dimensionality reduction and ensemble learning. First, we constructed different feature subsets for both SMs and miRNAs. Then, we trained homogeneous base learners based on distinct feature subsets and took the average of scores obtained from these base learners as SM-miRNA association score. In EKRRSMMA, feature dimensionality reduction technology was employed in the process of construction of feature subsets to reduce the influence of noisy data. Besides, the base learner, namely KRR_avg, was the combination of two classifiers constructed under SM space and miRNA space, which could make full use of the information of SM and miRNA. To assess the prediction performance of EKRRSMMA, we conducted Leave-One-Out Cross-Validation (LOOCV), SM-fixed local LOOCV, miRNA-fixed local LOOCV and 5-fold CV based on two datasets. For Dataset 1 (Dataset 2), EKRRSMMA got the Area Under receiver operating characteristic Curves (AUCs) of 0.9793 (0.8871), 0.8071 (0.7705), 0.9732 (0.8586) and 0.9767 ± 0.0014 (0.8560 ± 0.0027). Besides, we conducted four case studies. As a result, 32 (5-Fluorouracil), 19 (17ß-Estradiol), 26 (5-Aza-2'-deoxycytidine) and 11 (cyclophosphamide) out of top 50 predicted potentially associated miRNAs were confirmed by database or experimental literature. Above evaluation results demonstrated that EKRRSMMA is reliable for predicting SM-miRNA associations.

New Hydroxyphenylacetic Acids and α-Pyrone Derivative from the Deep-Sea Cold Seep Sediment-Derived Fungus Penicillium corylophilum CS-682.

Two pairs of new enantiomeric hydroxyphenylacetic acid derivatives, (±)-corylophenols A and B ((±)-1 and (±)-2), a new α-pyrone analogue, corylopyrone A (3), and six andrastin-type meroterpenoids (4-9) were isolated and identified from the deep-sea cold-seep sediment-derived fungus Penicillium corylophilum CS-682. Their structures and stereo configurations were determined by detailed spectroscopic analysis of NMR and MS data, chiral HPLC analysis, J-based configuration analysis, and quantum chemical calculations of ECD, specific rotation, and NMR (with DP4+ probability analysis). Compound 3 showed inhibitory activity against some strains of pathogenic bacteria.

Deep-belief network for predicting potential miRNA-disease associations.

MicroRNA (miRNA) plays an important role in the occurrence, development, diagnosis and treatment of diseases. More and more researchers begin to pay attention to the relationship between miRNA and disease. Compared with traditional biological experiments, computational method of integrating heterogeneous biological data to predict potential associations can effectively save time and cost. Considering the limitations of the previous computational models, we developed the model of deep-belief network for miRNA-disease association prediction (DBNMDA). We constructed feature vectors to pre-train restricted Boltzmann machines for all miRNA-disease pairs and applied positive samples and the same number of selected negative samples to fine-tune DBN to obtain the final predicted scores. Compared with the previous supervised models that only use pairs with known label for training, DBNMDA innovatively utilizes the information of all miRNA-disease pairs during the pre-training process. This step could reduce the impact of too few known associations on prediction accuracy to some extent. DBNMDA achieves the AUC of 0.9104 based on global leave-one-out cross validation (LOOCV), the AUC of 0.8232 based on local LOOCV and the average AUC of 0.9048 ± 0.0026 based on 5-fold cross validation. These AUCs are better than other previous models. In addition, three different types of case studies for three diseases were implemented to demonstrate the accuracy of DBNMDA. As a result, 84% (breast neoplasms), 100% (lung neoplasms) and 88% (esophageal neoplasms) of the top 50 predicted miRNAs were verified by recent literature. Therefore, we could conclude that DBNMDA is an effective method to predict potential miRNA-disease associations.

Identification of miRNA-disease associations via multiple information integration with Bayesian ranking.

In recent years, increasing microRNA (miRNA)-disease associations were identified through traditionally biological experiments. These associations contribute to revealing molecular mechanism of diseases and preventing and curing diseases. To improve the efficiency of miRNA-disease association discovery, some calculation methods were developed as auxiliary tools for researchers. In the current study, we raised a novel model named Bayesian Ranking for MiRNA-Disease Association prediction (BRMDA) by improving Bayesian Personalized Ranking from three aspects: (i) taking advantage of similarity of diseases and miRNAs; (ii) incorporating miRNA bias for miRNAs associated with different number of diseases; and (iii) implementing neighborhood-based approach for new miRNAs and diseases. For each investigated disease, BRMDA used the set of triples (i.e. disease, labeled miRNA, unlabeled miRNA) that reflected association preference of the disease to miRNAs as training set, which made full use of unknown samples rather than simply considering them as negative samples. To investigate the predictive performance of BRMDA, we employed leave-one-out cross-validation and obtained Area Under the Curve of 0.8697, which outperformed many classical methods. Besides, we further implemented three distinct classes of case studies for three common Neoplasms. As a result, there are 44 (Colon Neoplasms), 49 (Esophageal Neoplasms) and 49 (Lung Neoplasms) among the top 50 predicted miRNAs validated through experiments. In short, BRMDA would be a trustable tool for inferring valuable associations.

Computational Modeling of Aortic Stenosis With a Reduced Degree-of-Freedom Fluid-Structure Interaction Valve Model.

In this study, a novel reduced degree-of-freedom (rDOF) aortic valve model is employed to investigate the fluid-structure interaction (FSI) and hemodynamics associated with aortic stenosis. The dynamics of the valve leaflets are determined by an ordinary differential equation with two parameters and this rDOF model is shown to reproduce key features of more complex valve models. The hemodynamics associated with aortic stenosis is studied for three cases: a healthy case and two stenosed cases. The focus of the study is to correlate the hemodynamic features with the source generation mechanism of systolic murmurs associated with aortic stenosis. In the healthy case, extremely weak flow fluctuations are observed. However, in the stenosed cases, simulations show significant turbulent fluctuations in the ascending aorta, which are responsible for the generation of strong wall pressure fluctuations after the aortic root mostly during the deceleration phase of the systole. The intensity of the murmur generation increases with the severity of the stenosis, and the source locations for the two diseased cases studied here lie around 1.0 inlet duct diameters (Do) downstream of the ascending aorta.

Pollution Characteristics and Health Risk Assessment of Phthalate Esters in PSW Recycling Sites: A Typical Case Study.

The concentrations of six priority phthalate esters (PAEs) in 700 soil samples and 110 sediment samples from an area in China containing plastic solid waste (PSW) recycling sites were determined. The total concentrations of the six PAEs in soil and sediment were not detected - 274 and not detected - 597 mg kg-1, respectively, and the mean concentrations in soil and sediment were 14.4 and 31.7 mg kg-1, respectively. The dominant PAEs were di(2-ethylhexyl) phthalate and di-n-butyl phthalate. PAEs were detected in soil collected from the surface to 0.5 m below ground level around the PSW recycling sites, and the concentrations were markedly higher in these areas than at other polluted sites. PSW recycling is an important source of PAEs to soil and sediment. The di(2-ethylhexyl)phthalate concentrations in soil were higher than the relevant concentrations that pose environmental risks for sensitive land uses and non-sensitive land uses (42 and 121 mg kg-1, respectively), indicating emissions of PAEs from PSW recycling sites may pose environmental risks. The results indicate that PAE pollution at PSW sites needs to be better controlled and managed.

Exploring Neurofeedback Training for BMI Power Augmentation of Upper Limbs: A Pilot Study.

Electroencephalography neurofeedback (EEG-NFB) training can induce changes in the power of targeted EEG bands. The objective of this study is to enhance and evaluate the specific changes of EEG power spectral density that the brain-machine interface (BMI) users can reliably generate for power augmentation through EEG-NFB training. First, we constructed an EEG-NFB training system for power augmentation. Then, three subjects were assigned to three NFB training stages, based on a 6-day consecutive training session as one stage. The subjects received real-time feedback from their EEG signals by a robotic arm while conducting flexion and extension movement with their elbow and shoulder joints, respectively. EEG signals were compared with each NFB training stage. The training results showed that EEG beta (12-40 Hz) power increased after the NFB training for both the elbow and the shoulder joints' movements. EEG beta power showed sustained improvements during the 3-stage training, which revealed that even the short-term training could improve EEG signals significantly. Moreover, the training effect of the shoulder joints was more obvious than that of the elbow joints. These results suggest that NFB training can improve EEG signals and clarify the specific EEG changes during the movement. Our results may even provide insights into how the neural effects of NFB can be better applied to the BMI power augmentation system and improve the performance of healthy individuals.

Ensemble of decision tree reveals potential miRNA-disease associations.

In recent years, increasing associations between microRNAs (miRNAs) and human diseases have been identified. Based on accumulating biological data, many computational models for potential miRNA-disease associations inference have been developed, which saves time and expenditure on experimental studies, making great contributions to researching molecular mechanism of human diseases and developing new drugs for disease treatment. In this paper, we proposed a novel computational method named Ensemble of Decision Tree based MiRNA-Disease Association prediction (EDTMDA), which innovatively built a computational framework integrating ensemble learning and dimensionality reduction. For each miRNA-disease pair, the feature vector was extracted by calculating the statistical measures, graph theoretical measures, and matrix factorization results for the miRNA and disease, respectively. Then multiple base learnings were built to yield many decision trees (DTs) based on random selection of negative samples and miRNA/disease features. Particularly, Principal Components Analysis was applied to each base learning to reduce feature dimensionality and hence remove the noise or redundancy. Average strategy was adopted for these DTs to get final association scores between miRNAs and diseases. In model performance evaluation, EDTMDA showed AUC of 0.9309 in global leave-one-out cross validation (LOOCV) and AUC of 0.8524 in local LOOCV. Additionally, AUC of 0.9192+/-0.0009 in 5-fold cross validation proved the model's reliability and stability. Furthermore, three types of case studies for four human diseases were implemented. As a result, 94% (Esophageal Neoplasms), 86% (Kidney Neoplasms), 96% (Breast Neoplasms) and 88% (Carcinoma Hepatocellular) of top 50 predicted miRNAs were confirmed by experimental evidences in literature.

Functional Evaluation of a Force Sensor-Controlled Upper-Limb Power-Assisted Exoskeleton with High Backdrivability.

A power-assisted exoskeleton should be capable of reducing the burden on the wearer's body or rendering his or her work improved and efficient. More specifically, the exoskeleton should be easy to wear, be simple to use, and provide power assistance without hindering the wearer's movement. Therefore, it is necessary to evaluate the backdrivability, range of motion, and power-assist capability of such an exoskeleton. This evaluation identifies the pros and cons of the exoskeleton, and it serves as the basis for its subsequent development. In this study, a lightweight upper-limb power-assisted exoskeleton with high backdrivability was developed. Moreover, a motion capture system was adopted to measure and analyze the workspace of the wearer's upper limb after the exoskeleton was worn. The results were used to evaluate the exoskeleton's ability to support the wearer's movement. Furthermore, a small and compact three-axis force sensor was used for power assistance, and the effect of the power assistance was evaluated by means of measuring the wearer's surface electromyography, force, and joint angle signals. Overall, the study showed that the exoskeleton could achieve power assistance and did not affect the wearer's movements.

The ProNGF/p75NTR pathway induces tau pathology and is a therapeutic target for FTLD-tau.

Tau pathology is characterized as a form of frontotemporal lobar degeneration (FTLD) known as FTLD-tau. The underlying pathogenic mechanisms are not known and no therapeutic interventions are currently available. Here, we report that the neurotrophin receptor p75NTR plays a critical role in the pathogenesis of FTLD-tau. The expression of p75NTR and the precursor of nerve growth factor (proNGF) were increased in the brains of FTLD-tau patients and mice (P301L transgenic). ProNGF-induced tau phosphorylation via p75NTR in vitro, which was associated with the AKT/glycogen synthase kinase (GSK)3ß pathway. Genetic reduction of p75NTR in P301L mice rescued the memory deficits, alleviated tau hyperphosphorylation and restored the activity of the AKT/GSK3ß pathway. Treatment of the P301L mice with the soluble p75NTR extracellular domain (p75ECD-Fc), which can antagonize neurotoxic ligands of p75NTR, effectively improved memory behavior and suppressed tau pathology. This suggests that p75NTR plays a crucial role in tau paGSKthology and represents a potential druggable target for FTLD-tau and related tauopathies.

Computational Modeling and Analysis of Murmurs Generated by Modeled Aortic Stenoses.

In this study, coupled hemodynamic-acoustic simulations are employed to study the generation and propagation of murmurs associated with aortic stenoses where the aorta with a stenosed aortic valve is modeled as a curved pipe with a constriction near the inlet. The hemodynamics of the poststenotic flow is investigated in detail in our previous numerical study (Zhu et al., 2018, "Computational Modelling and Analysis of Haemodynamics in a Simple Model of Aortic Stenosis," J. Fluid Mech., 851, pp. 23-49). The temporal history of the pressure on the aortic lumen is recorded during the hemodynamic study and used as the murmur source in the acoustic simulations. The thorax is modeled as an elliptic cylinder and the thoracic tissue is assumed to be homogeneous, linear and viscoelastic. A previously developed high-order numerical method that is capable of dealing with immersed bodies is applied in the acoustic simulations. To mimic the clinical practice of auscultation, the sound signals from the epidermal surface are collected. The simulations show that the source of the aortic stenosis murmur is located at the proximal end of the aortic arch and that the sound intensity pattern on the epidermal surface can predict the source location of the murmurs reasonably well. Spectral analysis of the murmur reveals the disconnect between the break frequency obtained from the flow and from the murmur signal. Finally, it is also demonstrated that the source locations can also be predicted by solving an inverse problem using the free-space Green's function. The implications of these results for cardiac auscultation are discussed.

Pd(II)-Catalyzed Carbonyl-Directing Activation of Alkenes: Selective Fluorosulfonylation and Aminosulfonylation of 1,7-Enynes.

A new Pd(II)-catalyzed carbonyl-directing activation of alkenes has been established, enabling radical-induced selective fluorosulfonylation and aminosulfonylation of carbonyl-tethered 1,7-enynes with sulfinic acids and N-fluorobenzenesulfonimide (NFSI) under mild and redox neutral conditions to access densely functionalized ( E)-3,4-dihydronaphthalen-1(2 H)-ones with generally good yields and high stereoselectivity. The selectivity of these bifunctionalizations relies on the electronic nature of substituents on both aryl rings of 1,7-enynes.

Edaravone alleviates Alzheimer's disease-type pathologies and cognitive deficits.

Alzheimer's disease (AD) is one of most devastating diseases affecting elderly people. Amyloid-ß (Aß) accumulation and the downstream pathological events such as oxidative stress play critical roles in pathogenesis of AD. Lessons from failures of current clinical trials suggest that targeting multiple key pathways of the AD pathogenesis is necessary to halt the disease progression. Here we show that Edaravone, a free radical scavenger that is marketed for acute ischemic stroke, has a potent capacity of inhibiting Aß aggregation and attenuating Aß-induced oxidation in vitro. When given before or after the onset of Aß deposition via i.p. injection, Edaravone substantially reduces Aß deposition, alleviates oxidative stress, attenuates the downstream pathologies including Tau hyperphosphorylation, glial activation, neuroinflammation, neuronal loss, synaptic dysfunction, and rescues the behavioral deficits of APPswe/PS1 mice. Oral administration of Edaravone also ameliorates the AD-like pathologies and memory deficits of the mice. These findings suggest that Edaravone holds a promise as a therapeutic agent for AD by targeting multiple key pathways of the disease pathogenesis.

Identification of FERM domain-containing protein 5 as a novel target of ß-catenin/TCF7L2 complex.

Deregulation of the canonical Wnt signaling pathway plays an important role in human tumorigenesis through the accumulation of ß-catenin and subsequent transactivation of TCF7L2. Although some of the consequences associated with the accumulated ß-catenin have been clarified, the comprehensive effect of activated ß-catenin/TCF7L2 transcriptional complex on tumorigenesis remains to be elucidated. To understand the precise molecular mechanisms underlying colorectal cancer, we searched for genes regulated by the complex in colorectal tumors. We performed expression profile analysis of HCT116 and SW480 colon cancer cells treated with ß-catenin siRNAs, and ChIP-sequencing using anti-TCF7L2 antibody. Combination of these data with public microarray data of LS174 cells with a dominant-negative form of TCF7L2 identified a total of 11 candidate genes. In this paper, we focused on FERM domain-containing protein 5 (FRMD5), and confirmed that it is regulated by both ß-catenin and TCF7L2. An additional reporter assay disclosed that a region in intron1 transcriptionally regulated the expression of FRMD5. ChIP assay also corroborated that TCF7L2 associates with this region. These data suggested that FRMD5 is a novel direct target of the ß-catenin/TCF7L2 complex.

Bidirectional reporter assay using HAL promoter and TOPFLASH improves specificity in high-throughput screening of Wnt inhibitors.

Constitutive activation of Wnt signaling plays an important role in colorectal and liver tumorigenesis. Cell-based assays using synthetic TCF/LEF (T-cell factor/lymphoid enhancer factor) reporters, as readouts of ß-catenin/TCF-dependent transcriptional activity, have contributed greatly to the discovery of small molecules that modulate Wnt signaling. In the present study, we report a novel screening method, called a bidirectional dual reporter assay. Integrated transcriptome analysis identified a histidine ammonia-lyase gene (HAL) that was negatively regulated by ß-catenin/TCF-dependent transcriptional activity. We leveraged a promoter region of the HAL gene as another transcriptional readout of Wnt signaling. Cells stably expressing both an optimized HAL reporter and the TCF/LEF reporter enabled bidirectional reporter activities in response to Wnt signaling. Increased HAL reporter activity and decreased TCF/LEF reporter activity were observed simultaneously in the cells when ß-catenin/TCF7L2 was inhibited. Notably, this method could decrease the number of false positives observed when screening an inhibitor library compared with the conventional TCF/LEF assay. We found that Brefeldin A, a disruptor of the Golgi apparatus, inhibited the Wnt/ß-catenin signaling pathway. The utility of our system could be expanded to examine other disease-associated pathways beyond the Wnt/ß-catenin signaling pathway.

A Computational Method for Analyzing the Biomechanics of Arterial Bruits.

A computational framework consisting of a one-way coupled hemodynamic-acoustic method and a wave-decomposition based postprocessing approach is developed to investigate the biomechanics of arterial bruits. This framework is then applied for studying the effect of the shear wave on the generation and propagation of bruits from a modeled stenosed artery. The blood flow in the artery is solved by an immersed boundary method (IBM) based incompressible flow solver. The sound generation and propagation in the blood volume are modeled by the linearized perturbed compressible equations, while the sound propagation through the surrounding tissue is modeled by the linear elastic wave equation. A decomposition method is employed to separate the acoustic signal into a compression/longitudinal component (curl free) and a shear/transverse component (divergence free), and the sound signals from cases with and without the shear modulus are monitored on the epidermal surface and are analyzed to reveal the influence of the shear wave. The results show that the compression wave dominates the detected sound signal in the immediate vicinity of the stenosis, whereas the shear wave has more influence on surface signals further downstream of the stenosis. The implications of these results on cardiac auscultation are discussed.

Physiological amyloid-beta clearance in the periphery and its therapeutic potential for Alzheimer's disease.

Amyloid-beta (Aß) plays a pivotal role in the pathogenesis of Alzheimer's disease (AD). The physiological capacity of peripheral tissues and organs in clearing brain-derived Aß and its therapeutic potential for AD remains largely unknown. Here, we measured blood Aß levels in different locations of the circulation in humans and mice, and used a parabiosis model to investigate the effect of peripheral Aß catabolism on AD pathogenesis. We found that blood Aß levels in the inferior/posterior vena cava were lower than that in the superior vena cava in both humans and mice. In addition, injected (125)I labeled Aß40 was located mostly in the liver, kidney, gastrointestinal tract, and skin but very little in the brain; suggesting that Aß derived from the brain can be cleared in the periphery. Parabiosis before and after Aß deposition in the brain significantly reduced brain Aß burden without alterations in the expression of amyloid precursor protein, Aß generating and degrading enzymes, Aß transport receptors, and AD-type pathologies including hyperphosphorylated tau, neuroinflammation, as well as neuronal degeneration and loss in the brains of parabiotic AD mice. Our study revealed that the peripheral system is potent in clearing brain Aß and preventing AD pathogenesis. The present work suggests that peripheral Aß clearance is a valid therapeutic approach for AD, and implies that deficits in the Aß clearance in the periphery might also contribute to AD pathogenesis.

[The Cross-sectional Study on the Influence Factors for Encrustation of Double J Stent in Patients with Urolithiasis].

OBJECTIVE: To study the influence factors for encrustation of double J stent in patients with urolithiasis. METHODS: In this study, there were 84 urolithiasis patients with double J stent included from February to July 2014 in our hospital. The encrustation on double J stent was evaluated by a PC stereo microscope. The nterrelated clinical data were obtained, then the factors which may affect the encrustation were studied by logistic regression analysis. RESULTS: The mean indwelling time was (17. 0±6. 0) d, and a thin encrustation formed on the stents for most cases [67/84(79. 8%)]. Compared with the cases who did not form a thin encrustation, those having a thin encrustation formation on the stent were younger [(44. 9±11. 5) vs. (54. 4±12. 6), P=0. 004]; The patients with proteinuria got a higher rate of encrustation [62/73(84. 9%) vs. 5/11 (45. 5%), P=0. 002]. The patients with urinary tract infection had a higher rate of encrustation [26/28(92. 9%) vs. 41/56(73. 2%), P 3. 035]. The patients with hematuriaalso got a higher rate of encrustation [67/80(83. 8%) vs. 0/4, P=0. 001]. Different sex, retention time,serum calcium,inorganic phosphorus, uric acid, urine pH,lithiasis component had no effects on encrustation (P>0. 05). Logistic regression analysis showed that age and proteinuria was retained as idependent correlated factors with encrustation (P<0. 05), while hematuria and urinary tract infections had a low ntensity correlation with encrustation (P>0. 05). CONCLUSION: For encrustation of double J stentin patients with urolithiasis, younger age, increased urinary protein, hematuria and infections are important risk-factors.