Zobrazení zdroje stránky Korsholmdaley6392

High-dimensional signals, such as image signals and audio signals, usually have a sparse or low-dimensional manifold structure, which can be projected into a low-dimensional subspace to improve the efficiency and effectiveness of data processing. In this paper, we propose a linear dimensionality reduction method-minimum eigenvector collaborative representation discriminant projection-to address high-dimensional feature extraction problems. On the one hand, unlike the existing collaborative representation method, we use the eigenvector corresponding to the smallest non-zero eigenvalue of the sample covariance matrix to reduce the error of collaborative representation. On the other hand, we maintain the collaborative representation relationship of samples in the projection subspace to enhance the discriminability of the extracted features. Also, the between-class scatter of the reconstructed samples is used to improve the robustness of the projection space. The experimental results on the COIL-20 image object database, ORL, and FERET face databases, as well as Isolet database demonstrate the effectiveness of the proposed method, especially in low dimensions and small training sample size.Cardiovascular disease is the leading cause of death worldwide. Immediate and accurate diagnoses of cardiovascular disease are essential for saving lives. Although most of the previously reported works have tried to classify heartbeats accurately based on the intra-patient paradigm, they suffer from category imbalance issues since abnormal heartbeats appear much less regularly than normal heartbeats. Furthermore, most existing methods rely on data preprocessing steps, such as noise removal and R-peak location. In this study, we present a robust classification system using a multilevel discrete wavelet transform densely network (MDD-Net) for the accurate detection of normal, coronary artery disease (CAD), myocardial infarction (MI) and congestive heart failure (CHF). First, the raw ECG signals from different databases are divided into same-size segments using an original adaptive sample frequency segmentation algorithm (ASFS). Then, the fusion features are extracted from the MDD-Net to achieve great classification performance. We evaluated the proposed method considering the intra-patient and inter-patient paradigms. The average accuracy, positive predictive value, sensitivity and specificity were 99.74%, 99.09%, 98.67% and 99.83%, respectively, under the intra-patient paradigm, and 96.92%, 92.17%, 89.18% and 97.77%, respectively, under the inter-patient paradigm. Moreover, the experimental results demonstrate that our model is robust to noise and class imbalance issues.The larvicidal potential of crude leaf extracts of Rhizophora mucronata, the red mangrove, using diverse solvent extracts of the plant against the early fourth instar larvae of Anopheles stephensi, Culex quinquefasciatus and Aedes aegypti mosquito vectors was analyzed. The acetone extract of R. mucronata showed the greatest efficacy for Cx. quinquefasciatus (LC50 = 0.13 mg/mL; LC90 = 2.84 mg/mL), An. stephensi (LC50 = 0.34 mg/mL; LC90 = 6.03 mg/mL), and Ae. aegypti (LC50 = 0.11 mg/mL; LC90 = 1.35 mg/mL). The acetone extract was further fractionated into four fractions and tested for its larvicidal activity. Fraction 3 showed stronger larvicidal activity against all the three mosquito larvae. Chemical characterization of the acetone extract displayed the existence of several identifiable compounds like phytol, 3,7,11,15-tetramethyl-2-hexadecen-1-ol, 1-hexyl-2-nitrocyclohexane, eicosanoic acid etc. Enzyme assay displayed that R. mucronata active F3-fractions exert divergent effects on all three mosquitos' biochemical defensive mechanisms. The plant fractions displayed significant repellent activity against all the three mosquito vectors up to the maximum repellent time of 210 min. Thus, the bioactive molecules in the acetone extract of R. murconata leaves showed significant larvicidal and enzyme inhibitory activity and displayed novel eco-friendly tool for mosquito control.Kidney cancer is one of the most difficult cancers to treat by targeted and radiation therapy. Therefore, identifying key regulators in this cancer is especially important for finding new drugs. We focused on androgen receptor (AR) regulation by its epigenetic co-regulator lysine-specific histone demethylase 1 (LSD1) in kidney cancer development. LSD1 knock-down in kidney cancer cells decreased expression of AR target genes. Moreover, the binding of AR to target gene promoters was reduced and histone methylation status was changed in LSD1 knock-down kidney cancer cells. LSD1 knock-down also slowed growth and decreased the migration ability of kidney cancer cells. We found that pargyline, known as a LSD1 inhibitor, can reduce AR activity in kidney cancer cells. The treatment of kidney cancer cells with pargyline delayed growth and repressed epithelial-mesenchymal transition (EMT) markers. These effects were additively enhanced by co-treatment with the AR inhibitor enzalutamide. Down-regulation of LSD1 in renal cancer cells (RCC) attenuated in vivo tumor growth in a xenograft mouse model. These results provide evidence that LSD1 can regulate kidney cancer cell growth via epigenetic control of AR transcription factors and that LSD1 inhibitors may be good candidate drugs for treating kidney cancer.In the Panama context, energy consumption in the building sector is mostly related to the conditioning of indoor spaces for cooling and lighting. Different nature strategies can be mimic to strongly impact these two aspects in the building sector, such as the ones presented here. A comprehensive analysis regarding literature related to biomimicry-based approaches destined to improve buildings designs is presented here. This analysis is driven by the increasing energy regulations demands to meet future local goals and to propose a framework for applications in Panama. Such biomimicry-based approaches have been further analyzed and evaluated to propose the incorporation of organism-based design for three of the most climate types found in Panama. Consequently, a SWOT analysis helped realized the potential that biomimicry-based approaches might have in improving the odds of in meeting the local and global regulations demands. [https://www.selleckchem.com/products/gsk2578215a.html GSK2578215A] The need for multidisciplinary collaboration to accomplish biomimicry-based-designed buildings, brings an increment in the competitivity regarding more trained human-assets, widening the standard-construction-sector thinking. Finally, the analysis presented here can serve as the foundation for further technical assessment, via numerical and experimental means.The rise of three-dimensional bioprinting technology provides a new way to fabricate in tissue engineering in vitro, but how to provide sufficient nutrition for the internal region of the engineered printed tissue has become the main obstacle. In vitro perfusion culture can not only provide nutrients for the growth of internal cells but also take away the metabolic wastes in time, which is an effective method to solve the problem of tissue engineering culture in vitro. Aiming at user-defined tissue engineering with internal vascularized channels obtained by three-dimensional printing experiment in the early stage, a simulation model was established and the in vitro fluid-structure interaction finite element analysis of tissue engineering perfusion process was carried out. Through fluid-structure interaction simulation, the hydrodynamic behavior and mechanical properties of vascularized channels in the perfusion process was discussed when the perfusion pressure, hydrogel concentration, and crosslinking density changed. The effects of perfusion pressure, hydrogel concentration, and crosslinking density on the flow velocity, pressure on the vascularized channels, and deformation of vascularized channels were analyzed. The simulation results provide a method to optimize the perfusion parameters of tissue engineering, avoiding the perfusion failure caused by unreasonable perfusion pressure and hydrogel concentration and promoting the development of tissue engineering culture in vitro.Plant defensins are best known for their antifungal activity and contribution to the plant immune system. The defining feature of plant defensins is their three-dimensional structure known as the cysteine stabilized alpha-beta motif. This protein fold is remarkably tolerant to sequence variation with only the eight cysteines that contribute to the stabilizing disulfide bonds absolutely conserved across the family. Mature defensins are typically 46-50 amino acids in length and are enriched in lysine and/or arginine residues. Examination of a database of approximately 1200 defensin sequences revealed a subset of defensin sequences that were extended in length and were enriched in histidine residues leading to their classification as histidine-rich defensins (HRDs). Using these initial HRD sequences as a query, a search of the available sequence databases identified over 750 HRDs in solanaceous plants and 20 in brassicas. Histidine residues are known to contribute to metal binding functions in proteins leading to the hypothesis that HRDs would have metal binding properties. A selection of the HRD sequences were recombinantly expressed and purified and their antifungal and metal binding activity was characterized. Of the four HRDs that were successfully expressed all displayed some level of metal binding and two of four had antifungal activity. Structural characterization of the other HRDs identified a novel pattern of disulfide linkages in one of the HRDs that is predicted to also occur in HRDs with similar cysteine spacing. Metal binding by HRDs represents a specialization of the plant defensin fold outside of antifungal activity.This study aimed to identify the prognostic subgroups of stage 4 high-risk neuroblastoma based on metastatic burden and explore their distinct clinical and genomic features. Patients aged ≥18 months with stage 4 and metaiodobenzylguanidine-avid neuroblastoma were enrolled. One hundred and thirty eligible patients were treated under the tandem high-dose chemotherapy scheme. Prognostic significance of metastatic burden measured by the modified Curie score was analyzed using a competing risk approach, and the optimal cut-point was determined. Metastasis-specific subgroups (cut-point 26) were compared using clinicopathological variables, and differential gene expression analysis and gene set variation analysis (GSVA) were performed using RNA sequencing (RNA-seq). Metastatic burden at diagnosis showed a progressive association with relapse/progression. After applying the cut-point, patients with high metastatic burden showed &gt;3-fold higher risk of relapse/progression than those with low metastatic burden. Moreover, patients with high metastatic burden showed smaller primary tumors and higher biochemical marker levels than those with low metastatic burden. In the genomic analysis, 51 genes were found to be differentially expressed based on the set criteria. GSVA revealed 55 gene sets, which significantly distinguished patients with high metastatic burden from those with low metastatic burden at a false discovery rate less then 0.25. The results indicated the prognostic significance of metastatic burden in stage 4 high-risk neuroblastoma, and we identified the distinct clinicopathological and genomic features based on metastatic burden. This study may aid in the better understanding and risk-stratification of stage 4 high-risk neuroblastoma patients.