Miracle-dz/UniFAR-FTUs huggingface dataset:
MAGE-A family expression is correlated with poor survival of patients with lung adenocarcinoma: a retrospective clinical study based on tissue microarray

Objectives As the best characterised cancer/testis antigen family members, melanoma-associated antigens (MAGE) have been reported to be expressed in various malignant tumours. However, the expression pattern of MAGE-A family in lung adenocarcinoma (LAC) specimens and their prognostic and therapeutic significance for patients with LAC is still unclear. Materials and methods Tissue microarray-based immunohistochemistry analysis was used to examine the expression of MAGE-A family members (including MAGE-A1, A2, A3, A4, A6, A10, A11 and A12) in 105 paired LAC specimens and the corresponding pericarcinoma specimens. The association between MAGE-A expression and the clinicopathological parameters, and the 10-year overall survival of patients with LAC were analysed. In addition, the association between MAGE-A expression and the epithelial growth factor receptor (EGFR) amplification and ALK-EML4 rearrangements of patients with LAC were also analysed. Results The immunohistochemical evaluation revealed that MAGE-A family was expressed in 46.66% of LAC specimens, but not in the corresponding pericarcinoma specimens. MAGE-A expression was not associated with the clinicopathological factors but with worse 10-year survival, and was a poor prognostic marker for patients with LAC. MAGE-A expression was not correlated with EGFR amplification and ALK rearrangements. Interestingly, MAGE-A expression can affect the overall survival of patients with LAC without EGFR amplification or ALK rearrangements, but not affect the overall survival of patients with LAC and EGFR amplification or ALK rearrangements. Conclusions Molecular assessment of MAGE-A family members could be considered to improve the prognostic evaluation and to provide a new potential therapeutic strategy for patients with LAC.
Cross-Cultural Liaisons: Syndication Partner Choice by Foreign Venture Capital Firms in China March 2013

Cross-border venture capital investing has increased dramatically over the last two decades. Previous research has shown that foreign venture capitalists tend to partner with local venture capitalists as a strategy for offsetting information asymmetries and liabilities of foreignness. This paper examines the choice of co-investors by foreign venture capitalists investing in the Chinese market. We find that foreign investors are more likely to choose Chinese investors in later investment rounds and in more mature portfolio firms. More experienced foreign venture capital firms are less likely to co-invest with Chinese venture capitalists. Also, having a Chinese office made foreign venture capitalists less likely to co-invest. In seed-stage investments, when risks are the greatest, foreign firms are least likely to co-invest with Chinese venture capitalists, while at the later stage, when risks are presumably the lowest is when they are most likely to co-invest. During this period, the propensity to co-invest with Chinese venture capitalists increased significantly in every stage except the seed stage.
Comprehensive in vivo Mapping of the Human Basal Ganglia and Thalamic Connectome in Individuals Using 7T MRI

Basal ganglia circuits are affected in neurological disorders such as Parkinson's disease (PD), essential tremor, dystonia and Tourette syndrome. Understanding the structural and functional connectivity of these circuits is critical for elucidating the mechanisms of the movement and neuropsychiatric disorders, and is vital for developing new therapeutic strategies such as deep brain stimulation (DBS). Knowledge about the connectivity of the human basal ganglia and thalamus has rapidly evolved over recent years through non-invasive imaging techniques, but has remained incomplete because of insufficient resolution and sensitivity of these techniques. Here, we present an imaging and computational protocol designed to generate a comprehensive in vivo and subject-specific, three-dimensional model of the structure and connections of the human basal ganglia. High-resolution structural and functional magnetic resonance images were acquired with a 7-Tesla magnet. Capitalizing on the enhanced signal-to-noise ratio (SNR) and enriched contrast obtained at high-field MRI, detailed structural and connectivity representations of the human basal ganglia and thalamus were achieved. This unique combination of multiple imaging modalities enabled the in-vivo visualization of the individual human basal ganglia and thalamic nuclei, the reconstruction of seven white-matter pathways and their connectivity probability that, to date, have only been reported in animal studies, histologically, or group-averaged MRI population studies. Also described are subject-specific parcellations of the basal ganglia and thalamus into sub-territories based on their distinct connectivity patterns. These anatomical connectivity findings are supported by functional connectivity data derived from resting-state functional MRI (R-fMRI). This work demonstrates new capabilities for studying basal ganglia circuitry, and opens new avenues of investigation into the movement and neuropsychiatric disorders, in individual human subjects.
An Improved Face Detection Method in Low-resolution Video

In this study, an efficient face detection method is proposed for low-resolution video. The cascaded face detector proposed by Viola can achieve real-time detection and a high detection rate. However, the motion blurr of the face images in the low-resolution video usually exists. The detection rate in low-resolution video is lower than that in static images because the training set in the Adaboost algorithm only considers about normal face images. Therefore, the enhanced training set which contains the normal face images and the motion blurred face images is used to improve the detection rate. The simulation results show that the face images in low-resolution video can be efficiently extracted.
α1-Acid glycoprotein reduces local and remote injuries after intestinal ischemia in the rat.

The aim of this study was to look at the role of α1-acid glycoprotein as a natural anti-inflammatory agent with particular respect to its antineutrophil and anticomplement activity. A recombinantly engineered form of sialyl Lewisx(sLex)-bearing α1-acid glycoprotein (sAGP) was administered intravenously to pentobarbital-anesthetized rats after 50 min of intestinal ischemia just before 4 h of reperfusion. A non-sLex-bearing form of AGP (nsAGP) was used as control. sAGP-treated animals had a 62% reduction ( P < 0.05) in remote lung injury, assessed by 125I-albumin permeability, compared with those treated with nsAGP (permeability index of 3.61 ± 0.15 × 10-3 and 5.18 ± 0.67 × 10-3, respectively). There was a reduction in pulmonary myeloperoxidase levels in sAGP-treated rats compared with nsAGP-treated rats. Complement-dependent intestinal injury, assessed by 125I-albumin permeability was reduced by 28% ( P < 0.05) in animals treated with sAGP (7.58 ± 0.63) compared with those treated with nsAGP (10.4 ± 0.54). We conclude that sAGP ameliorates both complement- and neutrophil-mediated injuries.
Effects of ozone oxidative preconditioning on radiation-induced organ damage in rats

Because radiation-induced cellular damage is attributed primarily to harmful effects of free radicals, molecules with direct free radical scavenging properties are particularly promising as radioprotectors. It has been demonstrated that controlled ozone administration may promote an adaptation to oxidative stress, preventing the damage induced by reactive oxygen species. Thus, we hypothesized that ozone would ameliorate oxidative damage caused by total body irradiation (TBI) with a single dose of 6 Gy in rat liver and ileum tissues. Rats were randomly divided into groups as follows: control group; saline-treated and irradiated (IR) groups; and ozone oxidative preconditioning (OOP) and IR groups. Animals were exposed to TBI after a 5-day intraperitoneal pretreatment with either saline or ozone (1 mg/kg/day). They were decapitated at either 6 h or 72 h after TBI. Plasma, liver and ileum samples were obtained. Serum AST, ALT and TNF-α levels were elevated in the IR groups compared with the control group and were decreased after treatment with OOP. TBI resulted in a significant increase in the levels of MDA in the liver and ileal tissues and a decrease of SOD activities. The results demonstrated that the levels of MDA liver and ileal tissues in irradiated rats that were pretreated with ozone were significantly decreased, while SOD activities were significantly increased. OOP reversed all histopathological alterations induced by irradiation. In conclusion, data obtained from this study indicated that ozone could increase the endogenous antioxidant defense mechanism in rats and there by protect the animals from radiation-induced organ toxicity.
A Cycle-Based Formulation and Valid Inequalities for DC Power Transmission Problems with Switching

It is well known that optimizing network topology by switching on and off transmission lines improves the efficiency of power delivery in electrical networks. In fact, the USA Energy Policy Act of 2005 (Section 1223) states that the United States should “encourage, as appropriate, the deployment of advanced transmission technologies” including “optimized transmission line configurations. ” As such, many authors have studied the problem of determining an optimal set of transmission lines to switch off to minimize the cost of meeting a given power demand under the direct current (DC) model of power flow. This problem is known in the literature as the Direct-Current Optimal Transmission Switching Problem (DC-OTS). Most research on DC-OTS has focused on heuristic algorithms for generating quality solutions or on the application of DC-OTS to crucial operational and strategic problems such as contingency correction, real-time dispatch, and transmission expansion. The mathematical theory of the DC-OTS problem is .
Comparison of a Bayesian SOM with the EM algorithm for Gaussian mixtures

A Bayesian SOM (BSOM) [8], is proposed and applied to the unsupervised learning of Gaussian mixture distributions and its performance is compared with the expectation-maximisation (EM) algorithm. The BSOM is found to yield as good results as the well-known EM algorithm but with much fewer iterations and, more importantly it can be used as an on-line training method. The neighbourhood function and distance measures of the traditional SOM [3] are replaced by the neuron's on-line estimated posterior probabilities, which can be interpreted as a Bayesian inference of the neuron's opportunity to share in the winning response and so to adapt to the input pattern. Such posteriors starting from uniform priors are gradually sharpened when more and more data samples become available and so improve the estimation of model parameters. Each neuron then converges to one component of the mixture. Experimental results are compared with those of the EM algorithm.
Privacy-preserving Network Functionality Outsourcing

Since the advent of software defined networks ({SDN}), there have been many attempts to outsource the complex and costly local network functionality, i.e. the middlebox, to the cloud in the same way as outsourcing computation and storage. The privacy issues, however, may thwart the enterprises' willingness to adopt this innovation since the underlying configurations of these middleboxes may leak crucial and confidential information which can be utilized by attackers. To address this new problem, we use firewall as an sample functionality and propose the first privacy preserving outsourcing framework and schemes in SDN. The basic technique that we exploit is a ground-breaking tool in cryptography, the \textit{cryptographic multilinear map}. In contrast to the infeasibility in efficiency if a naive approach is adopted, we devise practical schemes that can outsource the middlebox as a blackbox after \textit{obfuscating} it such that the cloud provider can efficiently perform the same functionality without knowing its underlying private configurations. Both theoretical analysis and experiments on real-world firewall rules demonstrate that our schemes are secure, accurate, and practical.
Genetic associations with brain microbleeds

Objective: We performed a systematic review and meta-analyses to assess the evidence for genetic associations with brain microbleeds (BMBs). Methods: We sought all published studies of the association between any genetic polymorphism and BMBs studied in a total of >100 people. We critically appraised studies, and calculated pooled odds ratios (ORs) using the generic inverse variance fixed effects method. We used I2 and χ2 statistics to assess heterogeneity, and fail-safe N estimates to assess the robustness of our results. Results: Only the APOE ϵ2/3/4 polymorphism had been studied in >100 people (10 studies, 7,351 participants). Compared with people with the ϵ3/ϵ3 genotype, carriers of the ϵ4 allele (ϵ4+) were statistically significantly more likely to have BMBs in any location (ϵ4+ vs ϵ3/ϵ3: pooled OR 1.22, 95% confidence interval [CI] 1.05–1.41, p = 0.01). For strictly lobar BMBs, this association appeared slightly stronger (ϵ4+ vs ϵ3/ϵ3: pooled OR 1.35, 95% CI 1.10–1.66, p = 0.005). The association of ϵ4+ genotypes with strictly lobar BMBs was reasonably robust to potential publication and reporting biases. Conclusions: Given the known associations of APOE alleles with lobar intracerebral hemorrhage and cerebral amyloid angiopathy, these findings support the concept that strictly lobar BMBs may be an imaging biomarker of cerebral amyloid angiopathy.
Endocarditis Caused by Extended-Spectrum-β-Lactamase-Producing Klebsiella pneumoniae: Emergence of Resistance to Ciprofloxacin and Piperacillin-Tazobactam during Treatment despite Initial Susceptibility

ABSTRACT Three episodes of bacteremia occurred in the course of prosthetic valve endocarditis caused by an extended-spectrum-β-lactamase (ESBL)-producing Klebsiella pneumoniae strain. The second isolate developed resistance to ciprofloxacin and the third isolate to piperacillin-tazobactam (PIP-TZ) following sequential therapy with each agent. The first isolate was resistant to PIP-TZ only at high inocula, the second isolate acquired increased transcription of the acrA gene, and the third isolate became resistant to PIP-TZ due to loss of β-lactamase inhibition by TZ. We question if and how PIP-TZ susceptibility should be reported for ESBL-producing Enterobacteriaceae.
Defending Against False Data Injection Attacks on Power System State Estimation

This paper investigates the problem of defending against false data injection (FDI) attacks on power system state estimation. Although many research works have been previously reported on addressing the same problem, most of them made a very strong assumption that some meter measurements can be absolutely protected. To address the problem practically, a reasonable approach is to assume whether or not a meter measurement could be compromised by an adversary does depend on the defense budget deployed by the defender on the meter. From this perspective, our contributions focus on designing the least-budget defense strategy to protect power systems against FDI attacks. In addition, we also extend to investigate choosing which meters to be protected and determining how much defense budget to be deployed on each of these meters. We further formulate the meter selection problem as a mixed integer nonlinear programming problem, which can be efficiently tackled by Benders’ decomposition. Finally, extensive simulations are conducted on IEEE test power systems to demonstrate the advantages of the proposed approach in terms of computing time and solution quality, especially for large-scale power systems.
Information Flows between Eurodollar Spot and Futures Markets

The pattern of information flows between Eurodollar spot and futures markets is examined using a robust two-step procedure. This procedure allows for conditional mean and variance dynamics as well as conditional heteroskedasticity. We find spot rates affect futures data and vice versa. In addition, there is evidence of volatility spillover between the two markets. Our results also indicate that information conveyed by data on futures tends to have a more persistent impact on both the mean and volatility of cash market price movements than the other way around.
gp100/pmel 17 Is a Murine Tumor Rejection Antigen: Induction of “Self”-reactive, Tumoricidal T Cells Using High-affinity, Altered Peptide Ligand

Many tumor-associated antigens are nonmutated, poorly immunogenic tissue differentiation antigens. Their weak immunogenicity may be due to “self”-tolerance. To induce autoreactive T cells, we studied immune responses to gp100/pmel 17, an antigen naturally expressed by both normal melanocytes and melanoma cells. Although a recombinant vaccinia virus (rVV) encoding the mouse homologue of gp100 was nonimmunogenic, immunization of normal C57BL/6 mice with the rVV encoding the human gp100 elicited a specific CD8+ T cell response. These lymphocytes were cross-reactive with mgp100 in vitro and treated established B16 melanoma upon adoptive transfer. To understand the mechanism of the greater immunogenicity of the human version of gp100, we characterized a 9-amino acid (AA) epitope, restricted by H-2Db, that was recognized by the T cells. The ability to induce specific T cells with human but not mouse gp100 resulted from differences within the major histocompatibility complex (MHC) class I–restricted epitope and not from differences elsewhere in the molecule, as was evidenced by experiments in which mice were immunized with rVV containing minigenes encoding these epitopes. Although the human (hgp10025–33) and mouse (mgp10025–33) epitopes were homologous, differences in the three NH2-terminal AAs resulted in a 2-log increase in the ability of the human peptide to stabilize “empty” Db on RMA-S cells and a 3-log increase in its ability to trigger interferon γ release by T cells. Thus, the fortuitous existence of a peptide homologue with significantly greater avidity for MHC class I resulted in the generation of self-reactive T cells. High-affinity, altered peptide ligands might be useful in the rational design of recombinant and synthetic vaccines that target tissue differentiation antigens expressed by tumors.
Biochemical and functional properties of distinct nicotinic acetylcholine receptors in the superior cervical ganglion of mice with targeted deletions of nAChR subunit genes

Nicotinic acetylcholine receptors (nAChRs) mediate fast synaptic transmission in ganglia of the autonomic nervous system. Here, we determined the subunit composition of hetero‐pentameric nAChRs in the mouse superior cervical ganglion (SCG), the function of distinct receptors (obtained by deletions of nAChR subunit genes) and mechanisms at the level of nAChRs that might compensate for the loss of subunits. As shown by immunoprecipitation and Western blots, wild‐type (WT) mice expressed: α3β4 (55%), α3β4α5 (24%) and α3β4β2 (21%) nAChRs. nAChRs in β4 knockout (KO) mice were reduced to < 15% of controls and no longer contained the α5 subunit. Compound action potentials, recorded from the postganglionic (internal carotid) nerve and induced by preganglionic nerve stimulation, did not differ between α5β4 KO and WT mice, suggesting that the reduced number of receptors in the KO mice did not impair transganglionic transmission. Deletions of α5 or β2 did not affect the overall number of receptors and we found no evidence that the two subunits substitute for each other. In addition, dual KOs allowed us to study the functional properties of distinct α3β4 and α3β2 receptors that have previously only been investigated in heterologous expression systems. The two receptors strikingly differed in the decay of macroscopic currents, the efficacy of cytisine, and their responses to the α‐conotoxins AuIB and MII. Our data, based on biochemical and functional experiments and several mouse KO models, clarify and significantly extend previous observations on the function of nAChRs in heterologous systems and the SCG.
Stochastic parametric resonance in shear flows

Time-periodic shear flows can give rise to Para- metric Instability (PI), as in the case of the Mathieu equa- tion (Stoker, 1950; Nayfeh and Mook, 1995). This mech- anism results from a resonance between the oscillatory ba- sic state and waves that are superimposed on it. Farrell and Ioannou (1996a, b) explain that PI occurs because the snap- shots of the velocity profile are subject to transient growth. If the flows were purely steady the transient growth would subside and not have any long lasting effect. However, the coupling between transient growth and the time variation of the basic state create PI. Mathematically, transient growth, and therefore PI, are due to the nonorthogonal eigenspace in the linearized system. Poulin et al. (2003) studied a time-periodic barotropic shear flow that exhibited PI, and thereby produced mixing at the interface between Potential Vorticity (PV) fronts. The in- stability led to the formation of vortices that were stretched. A later study of an oscillatory current in the Cape Cod Bay illustrated that PI can occur in realistic shear flows (Poulin and Flierl, 2005) 1 . These studies assumed that the basic state was periodic with a constant frequency and amplitude. In this work we study a shear flow similar to that found in Poulin et al. (2003), but now where the magnitude of vorticity is a stochastic variable. We determine that in the case of stochas- tic shear flows the transient growth of perturbations of the snapshots of the basic state still generate PI.
Sparse additive models

Summary. We present a new class of methods for high dimensional non‐parametric regression and classification called sparse additive models. Our methods combine ideas from sparse linear modelling and additive non‐parametric regression. We derive an algorithm for fitting the models that is practical and effective even when the number of covariates is larger than the sample size. Sparse additive models are essentially a functional version of the grouped lasso of Yuan and Lin. They are also closely related to the COSSO model of Lin and Zhang but decouple smoothing and sparsity, enabling the use of arbitrary non‐parametric smoothers. We give an analysis of the theoretical properties of sparse additive models and present empirical results on synthetic and real data, showing that they can be effective in fitting sparse non‐parametric models in high dimensional data.
Comparative analysis of electrophysiological parameters of sural nerve in normal and type-2 diabetic subjects

The study was designed to evaluate sural nerve conduction of type-2 diabetes mellitus (T2DM) patients that were asymptomatic for neuropathy and compare their findings with age and sex matched healthy individuals. Using a standard technique, sural nerve conduction study was conducted on 100 T2DM patients with no clinical features suggestive of neuropathy and 100 healthy volunteers, matched for age and sex, serving as control. Sural nerve latency, Amplitude and Conduction Velocity (CV) were measured using Nihoen Kohden EMG Machine. On comparison of the sural nerve conduction parameters, sural nerve distal latencies were significantly lower in the control group while the sural nerve conduction velocities and amplitudes were significantly higher in the T2DM group. The study showed significant difference between the sural nerve conduction parameters in T2DM patients without clinical features suggestive of peripheral neuropathy when compared with apparently healthy individuals. Keywords: Sural nerve; Diabetic neuropathy; Electrophysiology