Hesperidin (HD) is a common flavanone glycoside isolated from citrus fruits and possesses great potential for cardiovascular protection. Hesperetin (HT) is an aglycone metabolite of HD with high ...bioavailability. Through the docking simulation, HD and HT have shown their potential to bind to two cellular proteins: transmembrane serine protease 2 (TMPRSS2) and angiotensin-converting enzyme 2 (ACE2), which are required for the cellular entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Our results further found that HT and HD suppressed the infection of VeroE6 cells using lentiviral-based pseudo-particles with wild types and variants of SARS-CoV-2 with spike (S) proteins, by blocking the interaction between the S protein and cellular receptor ACE2 and reducing ACE2 and TMPRSS2 expression. In summary, hesperidin is a potential TMPRSS2 inhibitor for the reduction of the SARS-CoV-2 infection.
Mutant p53 (mutp53) commonly loses its DNA binding affinity to p53 response elements (p53REs) and fails to induce apoptosis fully. However, the p53 mutation does not predict chemoresistance in all ...subtypes of breast cancers, and the critical determinants remain to be identified. In this study, mutp53 was found to mediate chemotherapy-induced long intergenic noncoding RNA-p21 (lincRNA-p21) expression by targeting the G-quadruplex structure rather than the p53RE on its promoter to promote chemosensitivity. However, estrogen receptor alpha (ERα) suppressed mutp53-mediated lincRNA-p21 expression by hijacking mutp53 to upregulate damaged DNA binding protein 2 (DDB2) transcription for subsequent DNA repair and chemoresistance. Levels of lincRNA-p21 positively correlated with the clinical responses of breast cancer patients to neoadjuvant chemotherapy and had an inverse correlation with the ER status and DDB2 level. In contrast, the carboplatin-induced DDB2 expression was higher in ER-positive breast tumor tissues. These results demonstrated that ER status determines the oncogenic function of mutp53 in chemoresistance by switching its target gene preference from lincRNA-p21 to DDB2 and suggest that induction of lincRNA-p21 and targeting DDB2 would be effective strategies to increase the chemosensitivity of mutp53 breast cancer patients.
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ER status determines the oncogenic function of mutp53 in chemoresistance by switching its target gene preference from lincRNA-p21 to DDB2. The co-treatment of chemotherapy with ER antagonists in a neoadjuvant setting may benefit luminal A/B patients through upregulation of lincRNA-p21 to enhance chemotherapy efficacy in mutp53-expressing breast cancers.
In this paper, a new Discontinuity Capturing Shallow Neural Network (DCSNN) for approximating d-dimensional piecewise continuous functions and for solving elliptic interface problems is developed. ...There are three novel features in the present network; namely, (i) jump discontinuities are accurately captured, (ii) it is completely shallow, comprising only one hidden layer, (iii) it is completely mesh-free for solving partial differential equations. The crucial idea here is that a d-dimensional piecewise continuous function can be extended to a continuous function defined in (d + 1)-dimensional space, where the augmented coordinate variable labels the pieces of each sub-domain. We then construct a shallow neural network to express this new function. Since only one hidden layer is employed, the number of training parameters (weights and biases) scales linearly with the dimension and the neurons used in the hidden layer. For solving elliptic interface problems, the network is trained by minimizing the mean square error loss that consists of the residual of the governing equation, boundary condition, and the interface jump conditions. We perform a series of numerical tests to demonstrate the accuracy of the present network. Our DCSNN model is efficient due to only a moderate number of parameters needed to be trained (a few hundred parameters used throughout all numerical examples), and the results indicate good accuracy. Compared with the results obtained by the traditional grid-based immersed interface method (IIM), which is designed particularly for elliptic interface problems, our network model shows a better accuracy than IIM. We conclude by solving a six-dimensional problem to demonstrate the capability of the present network for high-dimensional applications.
New nickel oxyhydroxide/palladium (NiOOH/Pd) nanocomposites was prepared and showed novel gasochromic characteristics for the first time. The NiOOH microparticles were obtained using the chemical ...bath synthesis method without stirring for 72h. The synthesized catalytic palladium nanoparticles (PdNPs) were added into the NiOOH microparticles and the NiOOH/Pd nanocomposites were readied for gasochromic application. The NiOOH/Pd nanocomposite thin film was obtained by using wet-coating methods. An obviously color change from black state NiOOH to white state Ni(OH)2 was observed after exposed to hydrogen (H2), the maximum transmittance change was 23.2% at 572nm. The white Ni(OH)2 state can be switched back to darken state by exposing to ozone (O3) on the thin film with its novel gasochromic property. Surface electron microscopy (SEM) images showed special surface morphology of NiOOH/Pd before and after gas treatments. X-ray photoelectron spectroscopy (XPS) analysis was used to confirm the changes in chemical bonding before/after gas treatment. XRD patterns and FT-IR spectra indicated the structure changes that occurred during film preparation and before/after exposed to H2.
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•A NiOOH/Pd nanocomposite showing novel gasochromic phenomena was reported.•Chemical structure and optical properties are controlled by exposure to hydrogen and ozone.•Gasochromic mechanism is proposed by XRD, XPS and IR analyses.•Thin film is switchable between black and white statues and the transmittance change in the visible range reached 23.2%.
Periostin (POSTN, PN, or osteoblast-specific factor OSF-2) is a multifunctional cytokine that signals between the cell and the extracellular matrix. Periostin plays an important role in tumor ...development and is involved in carcinoma cell epithelial-mesenchymal transition (EMT), whereby mature epithelial cells undergo phenotypic morphological changes and become invasive, motile cells. Here, we discuss the molecular mechanisms involved in periostin-induced promotion of EMT in lung cancer cells. Online TCGA datasets demonstrate the prognostic relevance of periostin in lung cancer; a higher periostin level correlates with poor overall survival. Similarly, our IHC results show that high periostin expression is positively correlated with the EMT markers Snail and Twist, as well as stage of lung cancer. We found that recombinant periostin induces the EMT phenotype in lung cancer cells through the p38/ERK pathway, while pretreatment with chemical inhibitors prevented periostin-induced EMT induction. Moreover, we found that periostin regulates EMT by repressing microRNA-381 (miR-381) expression, which targets both Snail and Twist. Using the miR-381 mimic, we dramatically reversed periostin-induced Snail and Twist expression. Furthermore, periostin knockdown dramatically affected EMT markers and cell migration potential. The role of periostin in lung cancer progression is elucidated by the
mouse model. Our findings indicate that changes in periostin expression in lung cancer may serve as a therapeutic target for the treatment of lung cancer metastasis.
In this study, electrochemical responses of inkjet-printed multicolored electrochromic devices (ECD) were studied to evaluate the feasibility of presenting multiple colors in one ECD. ...Metallo-supramolecular polymers (MEPE) solutions with two primary colors were inkjet-printed on flexible electrodes. By digitally controlling print dosages of each species, the colors of the printed EC thin film patterns can be adjusted directly without premixing or synthesizing new materials. The printed EC thin films were then laminated with a solid transparent thin film electrolyte and a transparent conductive thin film to form an ECD. After applying a dc voltage, the printed ECDs exhibited great contrast with a transmittance change (ΔT) of 40.1% and a high coloration efficiency of 445 cm2 C–1 within a short darkening time of 2 s. The flexible ECDs also showed the same darkening time of 2 s and still had a high ΔT of 30.1% under bending condition. This study demonstrated the feasibility to fabricate display devices with different color setups by an all-solution process and can be further extended to other types of displays.
In this paper, we propose a cusp-capturing physics-informed neural network (PINN) to solve discontinuous-coefficient elliptic interface problems whose solution is continuous but has discontinuous ...first derivatives on the interface. To find such a solution using neural network representation, we introduce a cusp-enforced level set function as an additional feature input to the network to retain the inherent solution properties; that is, capturing the solution cusps (where the derivatives are discontinuous) sharply. In addition, the proposed neural network has the advantage of being mesh-free, so it can easily handle problems in irregular domains. We train the network using the physics-informed framework in which the loss function comprises the residual of the differential equation together with certain interface and boundary conditions. We conduct a series of numerical experiments to demonstrate the effectiveness of the cusp-capturing technique and the accuracy of the present network model. Numerical results show that even using a one-hidden-layer (shallow) network with a moderate number of neurons and sufficient training data points, the present network model can achieve prediction accuracy comparable with traditional methods. Besides, if the solution is discontinuous across the interface, we can simply incorporate an additional supervised learning task for solution jump approximation into the present network without much difficulty.
•Cusp-capturing physics informed neural network for elliptic interface problems.•Our network can present continuous solutions that inherently have discontinuous first derivatives on interfaces.•A mesh-free approach for solving PDEs with interfaces is presented.•Our network can achieve high prediction accuracy with large contrast discontinuous coefficients.
The criteria outlined in the International Consensus Meeting (ICM) in 2018, which were prespecified and fixed, have been commonly practiced by clinicians to diagnose periprosthetic joint infection ...(PJI). We developed a machine learning (ML) system for PJI diagnosis and compared it with the ICM scoring system to verify the feasibility of ML.
We designed an ensemble meta-learner, which combined 5 learning algorithms to achieve superior performance by optimizing their synergy. To increase the comprehensibility of ML, we developed an explanation generator that produces understandable explanations of individual predictions. We performed stratified 5-fold cross-validation on a cohort of 323 patients to compare the ML meta-learner with the ICM scoring system.
Cross-validation demonstrated ML’s superior predictive performance to that of the ICM scoring system for various metrics, including accuracy, precision, recall, F1 score, Matthews correlation coefficient, and area under receiver operating characteristic curve. Moreover, the case study showed that ML was capable of identifying personalized important features missing from ICM and providing interpretable decision support for individual diagnosis.
Unlike ICM, ML could construct adaptive diagnostic models from the available patient data instead of making diagnoses based on prespecified criteria. The experimental results suggest that ML is feasible and competitive for PJI diagnosis compared with the current widely used ICM scoring criteria. The adaptive ML models can serve as an auxiliary system to ICM for diagnosing PJI.
•Developed an ensemble meta-learning system for PJI diagnosis.•Designed an explanation generator to provide comprehensible interpretations of the machine learning (ML) predictions as personalized decision support for PJI diagnosis.•Cross-validation demonstrated ML’s superior predictive performance to that of the scoring criteria outlined in the International Consensus Meeting (ICM) scoring system for various metrics.•The adaptive ML models can serve as an auxiliary system to the ICM scoring criteria for diagnosing PJI.
In this brief, the oxide characteristics and breakdown mechanism under forward gate bias in 4H-SiC MOS technologies are investigated. We found that the <inline-formula> <tex-math ...notation="LaTeX">{I}_{\text {G}} </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">{V}_{\text {G}} </tex-math></inline-formula> curves consist of two regions divided by a turning point. The region in the lower oxide fields is dominated by Pool-Frenkel (P-F) or Fowler-Nordheim (F-N) tunneling and the other in the higher oxide fields by impact ionization. MOS capacitors with three different oxide thicknesses (27.8, 44.4, and 69.0 nm) are fabricated and evaluated under different temperatures. Constant voltage stress was then conducted at <inline-formula> <tex-math notation="LaTeX">200~^{\circ }\text{C} </tex-math></inline-formula> to evaluate oxide integrity under the electric field where F-N tunneling dominates. Weibull plot and 63% failure times versus oxide field are shown for three oxide thicknesses. With the measure-stress-measure method, flat band voltage shift versus accumulative stress time and <inline-formula> <tex-math notation="LaTeX">{D}_{\text {it}} </tex-math></inline-formula> distribution are presented to understand the type of charge trapping. It was found that 27.8 nm oxide shows the highest electric field for a ten-year lifetime.
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