Heparin-binding epidermal growth factor inhibits apoptosis in cisplatin-resistant pancreatic cancer cells via upregulation of EGFR and ERCC 1 expressions

Purpose: To investigate the influence of heparin-binding epidermal growth factor (HB-EGF) on apoptosis in cisplatin-resistant pancreatic cancer cells, as well as its mechanism of action. Methods: Pancreatic cancer cisplatin-resistant cells (BXPC-3/CDDP) were transfected with HB-EGF small interfering RNA (siRNA). The cells were randomly assigned to four groups, namely, BXPC-3 group (group A), BXPC-3/CDDP group (group B), transfected group A (group Asi) and transfected group B (group Bsi). Cell proliferation was determined using MTT assay, and the levels of expression of HBEGF, epidermal growth factor receptor (EGFR) and excision repair cross-complementation group 1 (ERCC 1) were determined using Western blotting. The extent of apoptosis was determined by flow cytometry. Results: Cell proliferation was increased in group B, relative to group A, but was significantly decreased after transfection with HB-EGF siRNA (p < 0.05). The half-maximal inhibitory concentration (IC50) of group Bsi was reduced, relative to group Asi (p < 0.05). The expression of HB-EGF was significantly upregulated in group B, relative to group A (p < 0.05). In contrast, HB-EGF siRNA transfection of the cells significantly down-regulated HB-EGF expression (p < 0.05). Early apoptosis was significantly higher in group A than in groups B and Bsi. Higher levels of apoptosis were seen in group Bsi, relative to group B after inhibition of HB-EGF expression (p < 0.05). Conclusion: These results indicate that HB-EGF is resistant to cisplatin, and it inhibits apoptosis in pancreatic cancer cells via the upregulation of EGFR and ERCC 1 expressions

Epimorphin Regulates Bile Duct Formation via Effects on Mitosis Orientation in Rat Liver Epithelial Stem-Like Cells

Understanding how hepatic precursor cells can generate differentiated bile ducts is crucial for studies on epithelial morphogenesis and for development of cell therapies for hepatobiliary diseases. Epimorphin (EPM) is a key morphogen for duct morphogenesis in various epithelial organs. The role of EPM in bile duct formation (DF) from hepatic precursor cells, however, is not known. To address this issue, we used WB-F344 rat epithelial stem-like cells as model for bile duct formation. A micropattern and a uniaxial static stretch device was used to investigate the effects of EPM and stress fiber bundles on the mitosis orientation (MO) of WB cells. Immunohistochemistry of liver tissue sections demonstrated high EPM expression around bile ducts in vivo. In vitro, recombinant EPM selectively induced DF through upregulation of CK19 expression and suppression of HNF3α and HNF6, with no effects on other hepatocytic genes investigated. Our data provide evidence that EPM guides MO of WB-F344 cells via effects on stress fiber bundles and focal adhesion assembly, as supported by blockade EPM, β1 integrin, and F-actin assembly. These blockers can also inhibit EPM-induced DF. These results demonstrate a new biophysical action of EPM in bile duct formation, during which determination of MO plays a crucial role

HDAC Inhibitors Act with 5-aza-2′-Deoxycytidine to Inhibit Cell Proliferation by Suppressing Removal of Incorporated Abases in Lung Cancer Cells

5-aza-2′-deoxycytidine (5-aza-CdR) is used extensively as a demethylating agent and acts in concert with histone deacetylase inhibitors (HDACI) to induce apoptosis or inhibition of cell proliferation in human cancer cells. Whether the action of 5-aza-CdR in this synergistic effect results from demethylation by this agent is not yet clear. In this study we found that inhibition of cell proliferation was not observed when cells with knockdown of DNA methyltransferase 1 (DNMT1), or double knock down of DNMT1-DNMT3A or DNMT1-DNMT3B were treated with HDACI, implying that the demethylating function of 5-aza-CdR may be not involved in this synergistic effect. Further study showed that there was a causal relationship between 5-aza-CdR induced DNA damage and the amount of [3H]-5-aza-CdR incorporated in DNA. However, incorporated [3H]-5-aza-CdR gradually decreased when cells were incubated in [3H]-5-aza-CdR free medium, indicating that 5-aza-CdR, which is an abnormal base, may be excluded by the cell repair system. It was of interest that HDACI significantly postponed the removal of the incorporated [3H]-5-aza-CdR from DNA. Moreover, HDAC inhibitor showed selective synergy with nucleoside analog-induced DNA damage to inhibit cell proliferation, but showed no such effect with other DNA damage stresses such as γ-ray and UV, etoposide or cisplatin. This study demonstrates that HDACI synergistically inhibits cell proliferation with nucleoside analogs by suppressing removal of incorporated harmful nucleotide analogs from DNA

Saliency Preprocessing Locality-Constrained Linear Coding for Remote Sensing Scene Classification

Locality-constrained Linear Coding (LLC) shows superior image classification performance due to its underlying properties of local smooth sparsity and good construction. It encodes the visual features in remote sensing images and realizes the process of modeling human visual perception of an image through a computer. However, it ignores the consideration of saliency preprocessing in the human visual system. Saliency detection preprocessing can effectively enhance a computer’s perception of remote sensing images. To better implement the task of remote sensing image scene classification, this paper proposes a new approach by combining saliency detection preprocessing and LLC. This saliency detection preprocessing approach is realized using spatial pyramid Gaussian kernel density estimation. Experiments show that the proposed method achieved a better performance for remote sensing scene classification tasks

MSSRGO: A multimeta-model-based global optimization method using a selection-rank-based infill sampling strategy

In recent years, multimeta-model-based global optimization (MMGO) methods have received increasing attention due to their good performance in solving expensive black box problems. In this article, a multimeta-model-based global optimization method using the selection-rank-based infill sampling strategy (MSSRGO) algorithm is proposed to obtain more precise solutions with satisfactory computing costs for expensive black box problems. The MSSRGO utilizes three basic meta models (kriging (KRG), radial basis function (RBF) and polynomial response surface (PRS)) to capture the complex relationship between design variables and objective functions. In each iteration, first, two reduced subspaces are identified and used alternately with the whole design space. Then, a novel selection-rank-based sampling strategy and a greedy searching strategy in promising regions are proposed to obtain new potential points. Moreover, fifteen typical benchmark functions (six low-dimensional problems and nine high-dimensional problems) are employed to test the performance of MSSRGO. Compared with one well-known (EGO) and four recent (MSEGO, MGOSIC, MDSD and EMMGO) algorithms, the numerical experiments and engineering application show that the MSSRGO has superior searching precision, the same or lower computing costs and strong robustness

Stability Analysis of Bipedal Robots Using the Concept of Lyapunov Exponents

The dynamics and stability of passive bipedal robot have an important impact on the mass distribution, leg length, and the angle of inclination. Lyapunov’s second method is difficult to be used in highly nonlinear multibody systems, due to the lack of constructive methods for deriving Lyapunov fuction. The dynamics equation is established by Kane method, the relationship between the mass, length of leg, angle of inclination, and stability of passive bipedal robot by the largest Lyapunov exponent. And the Lyapunov exponents of continuous dynamical systems are estimated by numerical methods, which are simple and easy to be applied to the system stability simulation analysis, provide the design basis for passive bipedal robot prototype, and improve design efficiency

How Electroencephalogram Reference Influences the Movement Readiness Potential?

Readiness potential (RP) based on electroencephalograms (EEG) has been studied extensively in recent years, but no studies have investigated the influence of the reference electrode on RP. In order to investigate the reference effect, 10 subjects were recruited and the original vertex reference (Cz) was used to record the raw EEG signal when the subjects performed a motor preparation task. The EEG was then transformed to the common average reference (CAR) and reference electrode standardization technique (REST) reference, and we analyzed the RP waveform and voltage topographies and calculated the classification accuracy of idle and RP EEG segments. Our results showed that the RP waveform and voltage topographies were greatly influenced by the reference, but the classification accuracy was less affected if proper channels were selected as features. Since the Cz channel is near the primary motor cortex, where the source of RP is located, using the REST and CAR references is recommended to get accurate RP waveforms and voltage topographies

The Spectral Fingerprint of Excited-State Energy Transfer in Dendrimers through Polarization-Sensitive Transient-Absorption Pump-Probe Signals: On-the-Fly Nonadiabatic Dynamics Simulations

The time-resolved polarization-sensitive transient-absorption (TA) pump-probe (PP) spectra are simulated using on-the-fly surface-hopping nonadiabatic dynamics and the doorway-window (DW) representation of nonlinear spectroscopy. A typical dendrimer model system composed of two linear phenylene ethynylene units (2-ring, 3-ring) is taken as an example. The fewest switches trajectory surface hopping algorithm along with the TDDFT method is adopted in the nonadiabatic dynamics simulations. The ground-state bleach (GSB), stimulated emission (SE), excited-state absorption (ESA) contributions as well as the total TA PP signals are obtained and carefully analyzed. The correlations between these signals and the coupled nuclear-electronic dynamics are established. It is shown that intramolecular excited-state energy transfer from the 2-ring unit to the 3-ring unit can be conveniently monitored and accurately identified by employing pump and probe pulses with different polarizations. Our on-the-fly nonadiabatic simulation results demonstrate that time-resolved polarization-sensitive TA PP signals provide a powerful tool for the elucidation of excited-state energy transfer pathways, notably in molecular systems possessing several optically-bright nonadiabatically-coupled electronic states with different orientations of transition dipole moments

Site-Fixed Hydroboration of Alkenes under Metal-Free Conditions: Scope and Mechanistic Studies

An unprecedented and general metal-free hydroboration of alkenes with BBr3 as the boration reagent in the presence of iPr2NEt is reported. The addition of iPr2NEt not only suppresses alkene oligomerization and bromoboration side reactions, but also provides a proton source for hydroboration. More importantly, the site-fixed installation of a boryl group at the original position of the internal double-bond is easily achieved using our strategy as compared with traditional transition-metal-catalyzed hydroboration processes. Preliminary studies on the mechanism revealed a distinct reaction pathway that involves radical species and may operate through frustrated-Lewispair-type single-electron transfer

MGFKD: A semi-supervised multi-source domain adaptation algorithm for cross-subject EEG emotion recognition

Currently, most models rarely consider the negative transfer problem in the research field of cross-subject EEG emotion recognition. To solve this problem, this paper proposes a semi-supervised domain adaptive algorithm based on few labeled samples of target subject, which called multi-domain geodesic flow kernel dynamic distribution alignment (MGFKD). It consists of three modules: 1) GFK common feature extractor: projects the feature distribution of source and target subjects to the Grassmann manifold space, and obtains the latent common features of the two feature distributions through GFK method. 2) Source domain selector: obtains pseudo-labels of the target subject through weak classifier, finds ''golden source subjects'' by using few known labels of target subjects. 3) Label corrector: uses a dynamic distribution balance strategy to correct the pseudo-labels of the target subject. We conducted comparison experiments on the SEED and SEED-IV datasets, and the results show that MGFKD outperforms unsupervised and semi-supervised domain adaptation algorithms, achieving an average accuracy of 87.51±7.68% and 68.79±8.25% on the SEED and SEED-IV datasets with only one labeled sample per video for target subject. Especially when the number of source domains is set as 6 and the number of known labels is set as 5, the accuracy increase to 90.20±7.57% and 69.99±7.38%, respectively. The above results prove that our proposed algorithm can efficiently and quickly improve the cross-subject EEG emotion classification performance. Since it only need a small number of labeled samples of new subjects, making it has strong application value in future EEG-based emotion recognition applications