Quantification of propidium iodide delivery with millisecond electric pulses: A model study

A model study of propidium iodide delivery with millisecond electric pulses is presented; this work is a companion of the experimental efforts by Sadik et al. [1]. Both membrane permeabilization and delivery are examined with respect to six extra-cellular conductivities. The transmembrane potential of the permeabilized regions exhibits a consistent value, which corresponds to a bifurcation point in the pore-radius-potential relation. Both the pore area density and membrane conductance increase with an increasing extra-cellular conductivity. On the other hand, the inverse correlation between propidium iodide delivery and extra-cellular conductivity as observed in the experiments is quantitatively captured by the model. This agreement confirms that this behavior is primarily mediated by electrophoretic transport during the pulse. The results suggest that electrophoresis is important even for the delivery of small molecules such as propidium iodide. The direct comparison between model prediction and experimental data presented in this work helps validate the former as a robust predictive tool for the study of electroporation

Hedging, financing, and investment decisions: a simultaneous equations framework

The purpose of this paper is to empirically investigate the interaction between hedging, financing, and investment decisions. This work is relevant in that theoretical predictions are not necessarily identical to those in the case where only two decisions are being made. We argue that the way in which hedging affects the firms’ financing and investing decisions differs for firms with different growth opportunities. We empirically find that high-growth firms increase their investment, but not their leverage, by hedging. However, we also find that firms with few investment opportunities use derivatives to increase their leverage.

Generic Object Detection With Dense Neural Patterns and Regionlets

This paper addresses the challenge of establishing a bridge between deep convolutional neural networks and conventional object detection frameworks for accurate and efficient generic object detection. We introduce Dense Neural Patterns, short for DNPs, which are dense local features derived from discriminatively trained deep convolutional neural networks. DNPs can be easily plugged into conventional detection frameworks in the same way as other dense local features(like HOG or LBP). The effectiveness of the proposed approach is demonstrated with the Regionlets object detection framework. It achieved 46.1% mean average precision on the PASCAL VOC 2007 dataset, and 44.1% on the PASCAL VOC 2010 dataset, which dramatically improves the original Regionlets approach without DNPs

Hedging, financing, and investment decisions: A simultaneous equations framework

The purpose of this paper is to empirically investigate the interaction between hedging, financing, and investment decisions. This work is relevant in that theoretical predictions are not necessarily identical to those in the case where only two decisions are being made. We argue that the way in which hedging affects the firms’ financing and investing decisions differs for firms with different growth opportunities. We empirically find that high-growth firms increase their investment, but not their leverage, by hedging. However, we also find that firms with few investment opportunities use derivatives to increase their leverage

HSP90 inhibitors stimulate DNAJB4 protein expression through a mechanism involving N6-methyladenosine.

Small-molecule inhibitors for the 90-kDa heat shock protein (HSP90) have been extensively exploited in preclinical studies for the therapeutic interventions of human diseases accompanied with proteotoxic stress. By using an unbiased quantitative proteomic method, we uncover that treatment with three HSP90 inhibitors results in elevated expression of a large number of heat shock proteins. We also demonstrate that the HSP90 inhibitor-mediated increase in expression of DNAJB4 protein occurs partly through an epitranscriptomic mechanism, and is substantially modulated by the writer, eraser, and reader proteins of N6-methyladenosine (m6A). Furthermore, exposure to ganetespib leads to elevated modification levels at m6A motif sites in the 5'-UTR of DNAJB4 mRNA, and the methylation at adenosine 114 site in the 5'-UTR promotes the translation of the reporter gene mRNA. This m6A-mediated mechanism is also at play upon heat shock treatment. Cumulatively, we unveil that HSP90 inhibitors stimulate the translation of DNAJB4 through an epitranscriptomic mechanism

Holographic Gas as Dark Energy

We investigate the statistical nature of holographic gas, which may represent the quasi-particle excitations of a strongly correlated gravitational system. We find that the holographic entropy can be obtained by modifying degeneracy. We calculate thermodynamical quantities and investigate stability of the holographic gas. When applying to cosmology, we find that the holographic gas behaves as holographic dark energy, and the parameter $c$ in holographic dark energy can be calculated from our model. Our model of holographic gas generally predicts $c<1$, implying that the fate of our universe is phantom like.Comment: 13 page