Spin-dependent thermoelectric transport through double quantum dots

We study thermoelectric transport through double quantum dots system with spin-dependent interdot coupling and ferromagnetic electrodes by means of the non-equilibrium Green function in the linear response regime. It is found that the thermoelectric coefficients are strongly dependent on the splitting of interdot coupling, the relative magnetic configurations and the spin polarization of leads. In particular, the thermoelectric efficiency can achieve considerable value in parallel configuration when the effective interdot coupling and tunnel coupling between QDs and the leads for spin-down electrons are small. Moreover, the thermoelectric efficiency increases with the intradot Coulomb interactions increasing and can reach very high value at an appropriate temperature. In the presence of the magnetic field, the spin accumulation in leads strongly suppresses the thermoelectric efficiency and a pure spin thermopower can be obtained.Comment: 5 figure

A Binary-Medium Constitutive Model for Artificially Structured Soils Based on the Disturbed State Concept and Homogenization Theory

Triaxial compression tests were carried out on artificially structured soil samples at confining pressures of 25, 37.5, 50, 100, 200, and 400 kPa. A binary-medium constitutive model for artificially structured soils is proposed based on the experimental results, the disturbed state concept (DSC), and homogenization theory. A new constitutive model for artificially structured soils was formulated by regarding the structured soils as a binary medium consisting of bonded blocks and weakened bands. The bonded blocks are idealized as bonded elements whose deformation properties are described by elastic materials, and the weakened bands are idealized as frictional elements whose deformation properties are described by the Lade-Duncan model. By introducing the structural parameters of breakage ratio and local strain coefficient, the nonuniform distribution of stress and strain within a representative volume element can be given based on the homogenization theory of heterogeneous materials. The methods for determination of the model parameters are given on the basis of experimental results. Comparisons of predictions with experimental data demonstrate that the new model provides satisfactory qualitative and quantitative modeling of many important features of artificially structured soils

Modeling Robustness Tradeoffs in Yeast Cell Polarization Induced by Spatial Gradients

Cells localize (polarize) internal components to specific locations in response to external signals such as spatial gradients. For example, yeast cells form a mating projection toward the source of mating pheromone. There are specific challenges associated with cell polarization including amplification of shallow external gradients of ligand to produce steep internal gradients of protein components (e.g. localized distribution), response over a broad range of ligand concentrations, and tracking of moving signal sources. In this work, we investigated the tradeoffs among these performance objectives using a generic model that captures the basic spatial dynamics of polarization in yeast cells, which are small. We varied the positive feedback, cooperativity, and diffusion coefficients in the model to explore the nature of this tradeoff. Increasing the positive feedback gain resulted in better amplification, but also produced multiple steady-states and hysteresis that prevented the tracking of directional changes of the gradient. Feedforward/feedback coincidence detection in the positive feedback loop and multi-stage amplification both improved tracking with only a modest loss of amplification. Surprisingly, we found that introducing lateral surface diffusion increased the robustness of polarization and collapsed the multiple steady-states to a single steady-state at the cost of a reduction in polarization. Finally, in a more mechanistic model of yeast cell polarization, a surface diffusion coefficient between 0.01 and 0.001 µm2/s produced the best polarization performance, and this range is close to the measured value. The model also showed good gradient-sensitivity and dynamic range. This research is significant because it provides an in-depth analysis of the performance tradeoffs that confront biological systems that sense and respond to chemical spatial gradients, proposes strategies for balancing this tradeoff, highlights the critical role of lateral diffusion of proteins in the membrane on the robustness of polarization, and furnishes a framework for future spatial models of yeast cell polarization

Incorporating Existing Network Information into Gene Network Inference

One methodology that has met success to infer gene networks from gene expression data is based upon ordinary differential equations (ODE). However new types of data continue to be produced, so it is worthwhile to investigate how to integrate these new data types into the inference procedure. One such data is physical interactions between transcription factors and the genes they regulate as measured by ChIP-chip or ChIP-seq experiments. These interactions can be incorporated into the gene network inference procedure as a priori network information. In this article, we extend the ODE methodology into a general optimization framework that incorporates existing network information in combination with regularization parameters that encourage network sparsity. We provide theoretical results proving convergence of the estimator for our method and show the corresponding probabilistic interpretation also converges. We demonstrate our method on simulated network data and show that existing network information improves performance, overcomes the lack of observations, and performs well even when some of the existing network information is incorrect. We further apply our method to the core regulatory network of embryonic stem cells utilizing predicted interactions from two studies as existing network information. We show that including the prior network information constructs a more closely representative regulatory network versus when no information is provided

Identification of Enriched Driver Gene Alterations in Subgroups of Non-Small Cell Lung Cancer Patients Based on Histology and Smoking Status

BACKGROUND: Appropriate patient selection is needed for targeted therapies that are efficacious only in patients with specific genetic alterations. We aimed to define subgroups of patients with candidate driver genes in patients with non-small cell lung cancer. METHODS: Patients with primary lung cancer who underwent clinical genetic tests at Guangdong General Hospital were enrolled. Driver genes were detected by sequencing, high-resolution melt analysis, qPCR, or multiple PCR and RACE methods. RESULTS: 524 patients were enrolled in this study, and the differences in driver gene alterations among subgroups were analyzed based on histology and smoking status. In a subgroup of non-smokers with adenocarcinoma, EGFR was the most frequently altered gene, with a mutation rate of 49.8%, followed by EML4-ALK (9.3%), PTEN (9.1%), PIK3CA (5.2%), c-Met (4.8%), KRAS (4.5%), STK11 (2.7%), and BRAF (1.9%). The three most frequently altered genes in a subgroup of smokers with adenocarcinoma were EGFR (22.0%), STK11 (19.0%), and KRAS (12.0%). We only found EGFR (8.0%), c-Met (2.8%), and PIK3CA (2.6%) alterations in the non-smoker with squamous cell carcinoma (SCC) subgroup. PTEN (16.1%), STK11 (8.3%), and PIK3CA (7.2%) were the three most frequently enriched genes in smokers with SCC. DDR2 and FGFR2 only presented in smokers with SCC (4.4% and 2.2%, respectively). Among these four subgroups, the differences in EGFR, KRAS, and PTEN mutations were statistically significant. CONCLUSION: The distinct features of driver gene alterations in different subgroups based on histology and smoking status were helpful in defining patients for future clinical trials that target these genes. This study also suggests that we may consider patients with infrequent alterations of driver genes as having rare or orphan diseases that should be managed with special molecularly targeted therapies

Bioavailability of Orally Administered rhGM-CSF: A Single-Dose, Randomized, Open-Label, Two-Period Crossover Trial

BACKGROUND: Recombinant human granulocyte-macrophage colony-stimulating factor (rhGM-CSF) is usually administered by injection, and its oral administration in a clinical setting has been not yet reported. Here we demonstrate the bioavailability of orally administered rhGM-CSF in healthy volunteers. The rhGM-CSF was expressed in Bombyx mori expression system (BmrhGM-CSF). METHODS AND FINDINGS: Using a single-dose, randomized, open-label, two-period crossover clinical trial design, 19 healthy volunteers were orally administered with BmrhGM-CSF (8 microg/kg) and subcutaneously injected with rhGM-CSF (3.75 microg/kg) respectively. Serum samples were drawn at 0.0h, 0.5h ,0.75h,1.0h,1.5h,2.0h ,3.0h,4.0h,5.0h,6.0h,8.0h,10.0h and 12.0h after administrations. The hGM-CSF serum concentrations were determined by ELISA. The AUC was calculated using the trapezoid method. The relative bioavailability of BmrhGM-CSF was determined according to the AUC ratio of both orally administered and subcutaneously injected rhGM-CSF. Three volunteers were randomly selected from 15 orally administrated subjects with ELISA detectable values. Their serum samples at the 0.0h, 1.0h, 2.0h, 3.0h and 4.0h after the administrations were analyzed by Q-Trap MS/MS TOF. The different peaks were revealed by the spectrogram profile comparison of the 1.0h, 2.0h, 3.0h and 4.0h samples with that of the 0.0h sample, and further analyzed using both Enhanced Product Ion (EPI) scanning and Peptide Mass Fingerprinting Analysis. The rhGM-CSF was detected in the serum samples from 15 of 19 volunteers administrated with BmrhGM-CSF. Its bioavailability was observed at an average of 1.0%, with the highest of 3.1%. The rhGM-CSF peptide sequences in the serum samples were detected by MS analysis, and their sizes ranging from 2,039 to 7,336 Da. CONCLUSIONS: The results demonstrated that the oral administered BmrhGM-CSF was absorbed into the blood. This study provides an approach for an oral administration of rhGM-CSF protein in clinical settings. TRIAL REGISTRATION: www.chictr.orgChiCTR-TRC-00000107

Anti-α-Internexin Autoantibody from Neuropsychiatric Lupus Induce Cognitive Damage via Inhibiting Axonal Elongation and Promote Neuron Apoptosis

Neuropsychiatric systemic lupus erythematosus (NPSLE) is a major complication for lupus patients, which often leads to cognitive disturbances and memory loss and contributes to a significant patient morbidity and mortality. The presence of anti-neuronal autoantibodies (aAbs) has been identified; as examples, anti-NMDA receptors and anti-Ribsomal P aAbs have been linked to certain pathophysiological features of NPSLE.In the current study, we used a proteomic approach to identify an intermediate neurofilament alpha-internexin (INA) as a pathogenetically relevant autoantigen in NPSLE. The significance of this finding was then validated in an expanded of a cohort of NPSLE patients (n = 67) and controls (n = 270) by demonstrating that high titers of anti-INA aAb was found in both the serum and cerebrospinal fluid (CSF) of ∼50% NPSLE. Subsequently, a murine model was developed by INA immunization that resulted in pronounced cognitive dysfunction that mimicked features of NPSLE. Histopathology in affected animals displayed cortical and hippocampal neuron apoptosis. In vitro studies further demonstrated that anti-INA Ab mediated neuronal damage via inhibiting axonal elongation and eventually driving the cells to apoptosis.Taken together, this study identified a novel anti-neurofilament aAb in NPSLE, and established a hitherto undescribed mechanism of aAb-mediated neuron damage that could have relevance to the pathophysiology of NPSLE

Protein Scaffolds Can Enhance the Bistability of Multisite Phosphorylation Systems

The phosphorylation of a substrate at multiple sites is a common protein modification that can give rise to important structural and electrostatic changes. Scaffold proteins can enhance protein phosphorylation by facilitating an interaction between a protein kinase enzyme and its target substrate. In this work we consider a simple mathematical model of a scaffold protein and show that under specific conditions, the presence of the scaffold can substantially raise the likelihood that the resulting system will exhibit bistable behavior. This phenomenon is especially pronounced when the enzymatic reactions have sufficiently large KM, compared to the concentration of the target substrate. We also find for a closely related model that bistable systems tend to have a specific kinetic conformation. Using deficiency theory and other methods, we provide a number of necessary conditions for bistability, such as the presence of multiple phosphorylation sites and the dependence of the scaffold binding/unbinding rates on the number of phosphorylated sites