Traditional Herbal Formula NPC01 Exerts Antiangiogenic Effects through Inhibiting the PI3K/Akt/mTOR Signaling Pathway in Nasopharyngeal Carcinoma Cells

Antiangiogenic therapy is vital in nasopharyngeal carcinoma (NPC) treatment. NPC01 has already been successfully used in treating patients with NPC in clinical practice and exerted an excellent antiangiogenetic effect. However, the potential molecular mechanism underlying the antitumor effect of NPC01 has not been well explored. The present study demonstrated that NPC01 could significantly inhibit cell proliferation and induce cell apoptosis in a dose-dependent manner in human NPC cell lines. Furthermore, NPC01 exerted antiproliferative and antiangiogenic effects in NPC xenograft mice. Moreover, the study showed that NPC01 could significantly decrease the expression of angiogenesis-associated factors including hypoxia-inducible factor-1α and vascular endothelial growth factor. Additionally, the decreased expression of these angiogenesis-associated factors could be due to the inhibition of the phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) signaling pathway (PI3K/Akt/mTOR). In conclusion, the results proposed that NPC01 could exert its antitumor effect by suppressing the PI3K/Akt/mTOR signaling pathway. Further studies are warranted to elucidate the molecular mechanism

Optimizing the thermoelectric performance of zigzag and chiral carbon nanotubes

Using nonequilibrium molecular dynamics simulations and nonequilibrium Green's function method, we investigate the thermoelectric properties of a series of zigzag and chiral carbon nanotubes which exhibit interesting diameter and chirality dependence. Our calculated results indicate that these carbon nanotubes could have higher ZT values at appropriate carrier concentration and operating temperature. Moreover, their thermoelectric performance can be significantly enhanced via isotope substitution, isoelectronic impurities, and hydrogen adsorption. It is thus reasonable to expect that carbon nanotubes may be promising candidates for high-performance thermoelectric materials

Unraveling the mechanisms of NK cell dysfunction in aging and Alzheimer’s disease: insights from GWAS and single-cell transcriptomics

BackgroundAging is an important factor in the development of Alzheimer’s disease (AD). The senescent cells can be recognized and removed by NK cells. However, NK cell function is gradually inactivated with age. Therefore, this study used senescence as an entry point to investigate how NK cells affect AD.MethodsThe study validated the correlation between cognition and aging through a prospective cohort of the National Health and Nutrition Examination Survey database. A cellular trajectory analysis of the aging population was performed using single-cell nuclear transcriptome sequencing data from patients with AD and different ages. The genome-wide association study (GWAS) cohort of AD patients was used as the outcome event, and the expression quantitative trait locus was used as an instrumental variable. Causal associations between genes and AD were analyzed by bidirectional Mendelian randomization (MR) and co-localization. Finally, clinical cohorts were constructed to validate the expression of key genes.ResultsA correlation between cognition and aging was demonstrated using 2,171 older adults over 60 years of age. Gene regulation analysis revealed that most of the highly active transcription factors were concentrated in the NK cell subpopulation of AD. NK cell trajectories were constructed for different age populations. MR and co-localization analyses revealed that CHD6 may be one of the factors influencing AD.ConclusionWe explored different levels of AD and aging from population cohorts, single-cell data, and GWAS cohorts and found that there may be some correlations of NK cells between aging and AD. It also provides some basis for potential causation

Why are IPOs Always Underpriced? An Empirical Study of Behavioral Economics

IPO underpricing has become one of the most famous market anomalies in the modern financial market. This phenomenon, called the "New Issue Puzzle," stimulated a hot debate among economists. Many of them focused on explaining the cause of this anomaly using the classical economics models. It is relatively novel to explain this anomaly based on behavioral economics theories. This paper took a comprehensive perspective, considered two possible stages that the underpricing derived from: the pricing stage and the trading stage. For each stage, the paper proposed two hypotheses based on the behavioral economics theory and examined the hypotheses with the OLS regression model and the most up-to-date machine learning techniques (KNN, Decision Tree, Random Forests, and Gradient Boosting). The results demonstrate that the underpricing level of IPO is positively correlated to managerial confidence. This furtherly implies that the underpricing of IPOs is partially derived from the behaviors in the pricing stage. Besides, the result of four classification models validates that investor sentiments would contribute to the underpricing. Using company features and investor sentiments extracted from the online discussion could classify whether the IPO will be underpriced or not at a precision level of about 74%

Interactions among SARS-CoV accessory proteins revealed by bimolecular fluorescence complementation assay

The accessory proteins (3a, 3b, 6, 7a, 7b, 8a, 8b, 9b and ORF14), predicted unknown proteins (PUPs) encoded by the genes, are considered to be unique to the severe acute respiratory syndrome coronavirus (SARS-CoV) genome. These proteins play important roles in various biological processes mediated by interactions with their partners. However, very little is known about the interactions among these accessory proteins. Here, a EYFP (enhanced yellow fluorescent protein) bimolecular fluorescence complementation (BiFC) assay was used to detect the interactions among accessory proteins. 33 out of 81 interactions were identified by BiFC, much more than that identified by the yeast two-hybrid (Y2H) system. This is the first report describing direct visualization of interactions among accessory proteins of SARS-CoV. These findings attest to the general applicability of the BiFC system for the verification of protein-protein interactions

Speed up deep neural network based pedestrian detection by sharing features across multi-scale models

AbstractDeep neural networks (DNNs) have now demonstrated state-of-the-art detection performance on pedestrian datasets. However, because of their high computational complexity, detection efficiency is still a frustrating problem even with the help of Graphics Processing Units (GPUs). To improve detection efficiency, this paper proposes to share features across a group of DNNs that correspond to pedestrian models of different sizes. By sharing features, the computational burden for extracting features from an image pyramid can be significantly reduced. Simultaneously, we can detect pedestrians of several different scales on one single layer of an image pyramid. Furthermore, the improvement of detection efficiency is achieved with negligible loss of detection accuracy. Experimental results demonstrate the robustness and efficiency of the proposed algorithm