Circular photogalvanic effect induced by near-infrared radiation in InAs quantum wires patterned quasi two-dimensional electron system

In this work we investigated the InAs/InAlAs quantum wires (QWRs) superlattice by optically exciting the structure with near-infrared radiation. By varying the helicity of the radiation at room temperature we observed the circular photogalvanic effect related to the $C_{2v}$ symmetry of the structure, which could be attributed to the formation of a quasi two-dimensional system underlying in the vicinity of the QWRs pattern. The ratio of Rashba and Dresselhaus terms shows an evolution of the spin-orbit interaction in quasi two-dimensional structure with the QWR layer deposition thickness.Comment: 9 pages, 3 figure

Synchronization of stochastic genetic oscillator networks with time delays and Markovian jumping parameters

The official published version of the article can be found at the link below.Genetic oscillator networks (GONs) are inherently coupled complex systems where the nodes indicate the biochemicals and the couplings represent the biochemical interactions. This paper is concerned with the synchronization problem of a general class of stochastic GONs with time delays and Markovian jumping parameters, where the GONs are subject to both the stochastic disturbances and the Markovian parameter switching. The regulatory functions of the addressed GONs are described by the sector-like nonlinear functions. By applying up-to-date ‘delay-fractioning’ approach for achieving delay-dependent conditions, we construct novel matrix functional to derive the synchronization criteria for the GONs that are formulated in terms of linear matrix inequalities (LMIs). Note that LMIs are easily solvable by the Matlab toolbox. A simulation example is used to demonstrate the synchronization phenomena within biological organisms of a given GON and therefore shows the applicability of the obtained results.This work was supported in part by the Biotechnology and Biological Sciences Research Council (BBSRC) of the UK under Grants BB/C506264/1 and 100/EGM17735, the Royal Society of the UK, the National Natural Science Foundation of China under Grant 60804028, the Teaching and Research Fund for Excellent Young Teachers at Southeast University of China, the International Science and Technology Cooperation Project of China under Grant 2009DFA32050, and the Alexander von Humboldt Foundation of Germany

Cuproptosis-Related lncRNAs are Biomarkers of Prognosis and Immune Microenvironment in Head and Neck Squamous Cell Carcinoma

Background: Cuproptosis is a new type of cell death that induces protein toxic stress and eventually leads to cell death. Hence, regulating cuproptosis in tumor cells is a new therapeutic approach. However, studies on cuproptosis-related long noncoding RNA (lncRNA) in head and neck squamous cell carcinoma (HNSC) have not been found. This study aimed to explore the cuproptosis-related lncRNAs prognostic marker and their relationship to immune microenvironment in HNSC by using bioinformatics methods.Methods: RNA sequencing, genomic mutations, and clinical data of TCGA_HNSC were downloaded from The Cancer Genome Atlas. HNSC patients were randomly assigned to either a training group or a validation cohort. The least absolute shrinkage and selection operator Cox regression and multivariate Cox regression models were used to determine the prognostic model in the training cohort, and its independent prognostic effect was further confirmed in the validation and entire cohorts.Results: Based on previous literature, we collected 19 genes associated with cuproptosis. Afterward, 783 cuproptosis-related lncRNAs were obtained through coexpression. Cox model revealed and constructed eight cuproptosis-related lncRNAs prognostic marker (AL132800.1, AC090587.1, AC079160.1, AC011462.4, AL157888.1, GRHL3-AS1, SNHG16, and AC021148.2). Patients were divided into high- and low-risk groups based on the median risk score. The Kaplan–Meier survival curve revealed that the overall survival between the high- and low-risk groups was statistically significant. The receiver operating characteristic curve and principal component analysis demonstrated the accurate prognostic ability of the model. Univariate and multivariate Cox regression analysis showed that risk score was an independent prognostic factor. In addition, we used multivariate Cox regression to establish a nomogram of the predictive power of prognostic markers. The tumor mutation burden showed significant differences between the high- and low-risk groups. HNSC patients in the high-risk group responded better to immunotherapy than those in the low-risk group. We also found that risk scores were significantly associated with drug sensitivity in HNSC.Conclusion: In summary, our study identified eight cuprotosis-related lncRNAs signature of HNSC as the prognostic predictor, which may be promising biomarkers for predicting the benefit of HNSC immunotherapy as well as drug sensitivity

Suppression of growth, migration and invasion of highly-metastatic human breast cancer cells by berbamine and its molecular mechanisms of action

<p>Abstract</p> <p>Background</p> <p>Breast cancer is the second leading cause of cancer related deaths among females worldwide. Berbamine (BER), a kind of bis-benzylisoquinoline alkaloid, has been used to treat clinical patients with inflammation and cancer for many years in China. The purpose of this study is to investigate the activity of BER against highly-metastatic human breast cancer and its molecular mechanisms of action.</p> <p>Results</p> <p>In our study, we found that BER inhibits growth of highly-metastatic human breast cancer cell lines MDA-MB-231 and MDA-MB-435S cells dose-dependently and time-dependently. The sera from BER-treated rats suppress the growth of MDA-MB-231 cells. BER shows synergistic effects with some existing anticancer agents such as trichostatin A (TSA, the histone deacetylase inhibitor), celecoxib (the inhibitor of COX-2), and carmofur against the growth of MDA-MB-231 cells. BER also displays the strong activity of inducing apoptosis in both estrogen receptor-negative MDA-MB-231 cells and estrogen receptor-alpha-positive MCF-7 breast cancer cells, but not in normal human mammary epithelial cell line MCF10A. BER down-regulates anti-apoptotic protein Bcl-2 levels and up-regulates pro-apoptotic protein Bax expressions in MDA-MB-231 and MDA-MB-435S cells. BER also has synergistic effects with anticancer agents trichostatin A, celecoxib and/or carmofur on reducing Bcl-2/Bax ratios and VEGF secretions in MDA-MB-231 cells. In addition, BER significantly suppresses cell migration and invasion, as well as decreases pro-MMP-9/pro-MMP-2 activation in breast cancer cells. Furthermore, BER suppresses Akt and nuclear factor <it>κ</it>B signaling by reducing the phosphorylation of c-Met and Akt, and inhibiting their downstream targets such as nuclear factor <it>κ</it>B p-65, Bcl-2/Bax, osteopontin, VEGF, MMP-9 and MMP-2 on protein and/or mRNA levels in breast cancer cells.</p> <p>Conclusion</p> <p>Our findings have showed that BER suppresses the growth, migration and invasion in highly-metastatic human breast cancer cells by possibly inhibiting Akt and NF-<it>κ</it>B signaling with their upstream target c-Met and downstream targets Bcl-2/Bax, osteopontin, VEGF, MMP-9 and MMP-2. BER has synergistic effects with anticancer agents trichostatin A, celecoxib and carmofur on inhibiting the growth of MDA-MB-231 cells and reducing the ratio of Bcl-2/Bax and/or VEGF expressions in the cancer cells. These findings suggest that BER may have the wide therapeutic and/or adjuvant therapeutic application in the treatment of human breast cancer and other cancers.</p

An intelligent fault diagnosis method for PV arrays based on an improved rotation forest algorithm

With the exponential growth of global photovoltaic (PV) power capacity, it is essential to monitor, detect and diagnose the faults in PV arrays for optimal operation. This paper presents an improved rotation forest (RoF) algorithm classifiers ensemble hybridized with extreme learning machine (ELM) for fault diagnosis of PV arrays, which mainly consists of feature selection and classification. In the feature selection step, all the attributes are ranked by the ReliefF algorithm and the top-ranked attributes are chosen to create the new training data subset. In the classification step, the base classifier decision tree of the RoF is replaced by the extreme learning machine to form a new hybrid RoF-ELM ensemble classifier. In the RoF-ELM algorithm, the feature space is first split into several subspaces and the best number of feature subsets is found through the traversal search method. Then, the bootstrap algorithm is employed to carry out bootstrap resampling for each feature subspace, and the principal component analysis (PCA) is then used to transform the resampled samples. Finally, the ELM base classifier is exploited to build each classification model and the final decision is determined by the simple voting approach. By combining the RoF ensemble method with the ELM classifier, the proposed RoF-ELM algorithm not only overcomes the overfitting problem of the basic RoF algorithm, but also improves the generalization ability of the basic ELM. In order to experimentally verify the proposed approach, different types and levels of faults have been created in a laboratory small scale grid-connected PV power system to obtain the fault data samples. Experimental results demonstrate that the RoF-ELM can achieve higher diagnosis accuracy and reliability compared to the basic RoF and ELM algorithms

TAT-Ngn2 Enhances Cognitive Function Recovery and Regulates Caspase-Dependent and Mitochondrial Apoptotic Pathways After Experimental Stroke

Neurogenin-2 (Ngn2) is a basic helix-loop-helix (bHLH) transcription factor that contributes to the identification and specification of neuronal fate during neurogenesis. In our previous study, we found that Ngn2 plays an important role in alleviating neuronal apoptosis, which may be viewed as an attractive candidate target for the treatment of cerebral ischemia. However, novel strategies require an understanding of the function and mechanism of Ngn2 in mature hippocampal neurons after global cerebral ischemic injury. Here, we found that the expression of Ngn2 decreased in the hippocampus after global cerebral ischemic injury in mice and in primary hippocampal neurons after oxygen glucose deprivation (OGD) injury. Then, transactivator of transcription (TAT)-Ngn2, which was constructed by fusing a TAT domain to Ngn2, was effectively transported and incorporated into hippocampal neurons after intraperitoneal (i.p.) injection and enhanced cognitive functional recovery in the acute stage after reperfusion. Furthermore, TAT-Ngn2 alleviated hippocampal neuronal damage and apoptosis, and inhibited the cytochrome C (CytC) leak from the mitochondria to the cytoplasm through regulating the expression levels of brain-derived neurotrophic factor (BDNF), phosphorylation tropomyosin-related kinase B (pTrkB), Bcl-2, Bax and cleaved caspase-3 after reperfusion injury in vivo and in vitro. These findings suggest that the downregulation of Ngn2 expression may have an important role in triggering brain injury after ischemic stroke and that the neuroprotection of TAT-Ngn2 against stroke might involve the modulation of BDNF-TrkB signaling that regulates caspase-dependent and mitochondrial apoptotic pathways, which may be an attractive therapeutic strategy for cerebral ischemic injury

Genome of Crucihimalaya himalaica, a close relative of Arabidopsis, shows ecological adaptation to high altitude

Crucihimalaya himalaica is a close relative of Arabidopsis with typical Qinghai–Tibet Plateau (QTP) distribution. Here, by combining short- and long-read sequencing technologies, we provide a de novo genome sequence of C. himalaica. Our results suggest that the quick uplifting of the QTP coincided with the expansion of repeat elements. Gene families showing dramatic contractions and expansions, as well as genes showing clear signs of natural selection, were likely responsible for C. himalaica’s specific adaptation to the harsh environment of the QTP. We also show that the transition to self-pollination of C. himalaica might have enabled its occupation of the QTP. This study provides insights into how plants might adapt to extreme environmental conditions