Miracle-dz/UniFAR-FTUs huggingface dataset:
Requirement for Both Shc and Phosphatidylinositol 3′ Kinase Signaling Pathways in Polyomavirus Middle T-Mediated Mammary Tumorigenesis

ABSTRACT Transgenic mice expressing the polyomavirus (PyV) middle T antigen (MT) develop multifocal mammary tumors which frequently metastasize to the lung. The potent transforming activity of PyV MT is correlated with its capacity to activate and associate with a number of signaling molecules, including the Src family tyrosine kinases, the 85-kDa Src homology 2 subunit of the phosphatidylinositol 3′ (PI-3′) kinase, and the Shc adapter protein. To uncover the role of these signaling proteins in MT-mediated mammary tumorigenesis, we have generated transgenic mice that express mutant PyV MT antigens decoupled from either the Shc or the PI-3′ kinase signaling pathway. In contrast to the rapid induction of metastatic mammary tumors observed in the strains expressing wild-type PyV MT, mammary epithelial cell-specific expression of either mutant PyV MT resulted in the induction of extensive mammary epithelial hyperplasias. The mammary epithelial hyperplasias expressing the mutant PyV MT defective in recruiting the PI-3′ kinase were highly apoptotic, suggesting that recruitment of PI-3′ kinase by MT affects cell survival. Whereas the initial phenotypes observed in both strains were global mammary epithelial hyperplasias, focal mammary tumors eventually arose in all female transgenic mice. Genetic and biochemical analyses of tumorigenesis in the transgenic strains expressing the PyV MT mutant lacking the Shc binding site revealed that a proportion of the metastatic tumors arising in these mice displayed evidence of reversion of the mutant Shc binding site. In contrast, no evidence of reversion of the PI-3′ kinase binding site was noted in tumors derived from the strains expressing the PI-3′ kinase binding site MT mutant. Tumor progression in both mutant strains was further correlated with upregulation of the epidermal growth factor receptor family members which are known to couple to the PI-3′ kinase and Shc signaling pathways. Taken together, these observations suggest that PyV MT-mediated tumorigenesis requires activation of both Shc and PI-3′ kinase, which appear to be required for stimulation of cell proliferation and survival signaling pathways, respectively.
International Students’ Perspectives on Online Interfaces, Identity, and Environment in a U.S. Writing Center

This article investigates the perspectives of international students in the United States who use writing centers to support their identities and to meet their writing needs and goals. Using survey and focus group data to look closely at how students use one writing center’s online Profile and more broadly at the accessibility and responsiveness of writing center services, this study found that students have much to say about their place within writing centers and how writing consultants can best support them. Listening to these international student voices reveals how writing centers and other student support services must take the initiative in opening up conversations with and among our students to create the conditions for their success.
A nearly optimal construction of flash codes

Flash memory is a non-volatile computer memory comprised of blocks of cells, wherein each cell can take on q different values or levels. While increasing the cell level is easy, reducing the level of a cell can be accomplished only by erasing an entire block. Since block erasures are highly undesirable, coding schemes—known as floating codes or flash codes—have been designed in order to maximize the number of times that information stored in a flash memory can be written (and re-written) prior to incurring a block erasure. An (n, k, t)q flash code ℂ is a coding scheme for storing k information bits in n cells in such a way that any sequence of up to t writes (where a write is a transition 0 → 1 or 1 → 0 in any one of the k bits) can be accommodated without a block erasure. The total number of available level transitions in n cells is n(q−1), and the write deficiency of ℂ, defined as δ(ℂ) = n(q−1)−t, is a measure of how close the code comes to perfectly utilizing all these transitions. For k ≫ 6 and large n, the best previously known construction of flash codes achieves a write defficiency of O(qk2). On the other hand, the best known lower bound on write deficiency is Ω(qk). In this paper, we present a new construction of flash codes that approaches this lower bound to within a factor logarithmic in k. To this end, we first improve upon the so-called “indexed” flash codes, due to Jiang and Bruck, by eliminating the need for index cells in the Jiang-Bruck construction. Next, we further increase the number of writes by introducing a new multi-stage (recursive) indexing scheme. We then show that the write defficiency of the resulting flash codes is O(qk log k) if q ⩾ log2 k, and at most O(k log2 k) otherwise.
Novel Ca2+ Dependence and Time Course of Somatodendritic Dopamine Release: Substantia Nigra versus Striatum

Somatodendritic release of dopamine (DA) in midbrain represents a novel form of intercellular signaling that inherently differs from classic axon-terminal release. Here we report marked differences in the Ca2+ dependence and time course of stimulated increases in extracellular DA concentration ([DA]o) between the substantia nigra pars compacta (SNc) and striatum. Evoked [DA]o was monitored with carbon-fiber microelectrodes and fast-scan cyclic voltammetry in brain slices. In striatum, pulse-train stimulation (10 Hz, 30 pulses) failed to evoke detectable [DA]o in 0 or 0.5 mmCa2+ but elicited robust release in 1.5 mm Ca2+. Release increased progressively in 2.0 and 2.4 mm Ca2+. In sharp contrast, evoked [DA]o in SNc was nearly half-maximal in 0 mm Ca2+ and increased significantly in 0.5 mm Ca2+. Surprisingly, somatodendritic release was maximal in 1.5 mmCa2+, with no change in 2.0 or 2.4 mmCa2+. Additionally, after single-pulse stimulation, evoked [DA]o in striatum reached a maximum (tmax) in <200 msec, whereas in SNc, [DA]o continued to rise for 2–3 sec. Similarly, the time for [DA]o to decay to 50% of maximum (t50) was 12-fold longer in SNc than striatum. A delayed tmax in SNc compared with striatum persisted when DA uptake was inhibited by GBR-12909 and D2 autoreceptors were blocked by sulpiride, although these agents eliminated the difference in t50. Together, these data implicate different release mechanisms in striatum and SNc, with minimal Ca2+ required to trigger prolonged DA release in SNc. Coupled with limited uptake, prolonged somatodendritic release would facilitate DA-mediated volume transmission in midbrain.
Scalable subband image coding with segmented orthogonal matching pursuit

In this paper, a novel algorithm for low bit-rate image compression is presented. In this technique, we use a new image representation algorithm called segmented orthogonal matching pursuit (SOMP) (Rabiee and Kashyap, 1998) to encode the subbands of an image. Our preliminary results show that our algorithm performs better than the segmentation based matching pursuit (QTMP) (Rabiee et al. 1996) and EZW (Shapiro 1993) encoders at lower bit rates, based on subjective image quality and peak signal-to-noise ratio (PSNR).
Power-aware automated hybrid pipelining of combinational circuits

Hybrid pipelining can help us achieve faster clock rates by combining the advantages of both flop and wave pipelining and has signal processing applications. In this paper we formulate this problem for acyclic combinational circuits as a mixed integer non linear programming (MINLP) problem and give three algorithms to obtain good solutions. The first method is a sensitivity based approach. The second method uses geometric programming (GP) that works well for smaller circuits. The third method uses a novel technique towards level based delay propagation model using GP. The algorithms are tested on ISCAS-85 benchmark circuits and combinational circuits generated by a method developed by us and compared for speed and efficiency. Our experimental observations show the existence of a minimum supply voltage and a threshold voltage at which the circuits generated have less latency and power consumption.
Outage analysis of coded cooperation with multiple relays and Nakagami-m fading

In this paper we analyze the outage behavior of a coded cooperative system for independent, flat, Nakagami-m fading channels and derive a closed form expression for outage probability. We further find the optimum number of relays with respect to outage probability for different channel conditions and threshold power. We also obtain graphically the minimum cooperation ratio required, and hence minimum number of bits to be transmitted in first phase transmission, with respect to channel statistics and threshold power.
Dosing intermittent haemodialysis in the intensive care unit patient with acute renal failure--estimation of urea removal and evidence for the regional blood flow model.

BACKGROUND Blood-side dosing methods may overestimate urea removal in comparison to dialysate-side measurements during intermittent HD (IHD) for acute renal failure (ARF). The present study sought to quantify this mass balance error (MBE) and explore potential explanatory factors. METHODS Prospective, formal, blood-side urea kinetic modelling was performed in serial sessions (n = 42) in 18 intensive care unit ARF patients. Three blood-side estimates of urea removal were calculated and these were compared to urea removal derived from fractional dialysate sampling and use of an on-line urea monitor. We also examined urea rebound in these patients, as expressed by the intercompartmental urea clearance (Kc), and in a subset of patients examined the relation of Kc to cardiac output and systemic vascular resistance (SVR). RESULTS The mean % MBE (MBE = blood - dialysate-estimated urea removal) was about 9% using conventional two-pool modelling based on a 60-min post-dialysis blood urea nitrogen (BUN) with or without the use of one or more intra-dialytic BUN values. The extent of MBE could not be explained by the clinical or dialytic variables that were measured. Part of the MBE error was due to overestimation of the intradialytic BUN profile, because model-independent profiling of intra-dialytic BUN values to compute urea removal reduced the MBE to approximately 6%. The log Kc was correlated with cardiac output and showed trends towards an inverse correlation with SVR. CONCLUSIONS Classical, two-pool, blood-side UKM produces a modest overestimate of urea removal in IHD for critically ill ARF patients. The source of this small, residual MBE is unknown. The amount of urea rebound, as reflected by Kc, varied among patients and associated with cardiac output and SVR, as predicted by the regional blood flow model.
Key Role of Bacterial NH4+ Metabolism in Rhizobium-Plant Symbiosis

SUMMARY Symbiotic nitrogen fixation is carried out in specialized organs, the nodules, whose formation is induced on leguminous host plants by bacteria belonging to the family Rhizobiaceae. Nodule development is a complex multistep process, which requires continued interaction between the two partners and thus the exchange of different signals and metabolites. NH4+ is not only the primary product but also the main regulator of the symbiosis: either as ammonium and after conversion into organic compounds, it regulates most stages of the interaction, from the production of nodule inducers to the growth, function, and maintenance of nodules. This review examines the adaptation of bacterial NH4+ metabolism to the variable environment generated by the plant, which actively controls and restricts bacterial growth by affecting oxygen and nutrient availability, thereby allowing a proficient interaction and at the same time preventing parasitic invasion. We describe the regulatory circuitry responsible for the downregulation of bacterial genes involved in NH4+ assimilation occurring early during nodule invasion. This is a key and necessary step for the differentiation of N2-fixing bacteroids (the endocellular symbiotic form of rhizobia) and for the development of efficient nodules.
Combination therapies with NS5A, NS3 and NS5B inhibitors on different genotypes of hepatitis C virus in human hepatocyte chimeric mice

Objective We recently demonstrated that combination treatment with NS3 protease and NS5B polymerase inhibitors succeeded in eradicating the virus in genotype 1b hepatitis C virus (HCV)-infected mice. In this study, we investigated the effect of combining an NS5A replication complex inhibitor (RCI) with either NS3 protease or NS5B inhibitors on elimination of HCV genotypes 1b, 2a and 2b. Design The effects of Bristol-Myers Squibb (BMS)-605339 (NS3 protease inhibitor; PI), BMS-788329 (NS5A RCI) and BMS-821095 (NS5B non-nucleoside analogue inhibitor) on HCV genotypes 1b and 2a were examined using subgenomic HCV replicon cells. HCV genotype 1b, 2a or 2b-infected human hepatocyte chimeric mice were also treated with BMS-605339, BMS-788329 or BMS-821095 alone or in combination with two of the drugs for 4 weeks. Genotypic analysis of viral sequences was achieved by direct and ultra-deep sequencing. Results Anti-HCV effects of BMS-605339 and BMS-821095 were more potent against genotype 1b than against genotype 2a. In in-vivo experiments, viral breakthrough due to the development of a high prevalence of drug-resistant variants was observed in mice treated with BMS-605339, BMS-788329 and BMS-821095 in monotherapy. In contrast to monotherapy, 4 weeks of combination therapy with the NS5A RCI and either NS3 PI or NS5B inhibitor succeeded in completely eradicating the virus in genotype 1b HCV-infected mice. Conversely, these combination therapies failed to eradicate the virus in mice infected with HCV genotypes 2a or 2b. Conclusions These oral combination therapies may serve as a Peg-alfa-free treatment for patients chronically infected with HCV genotype 1b.
Function changing mutations in glucocorticoid receptor evolution correlate with their relevance to mode coupling

Nonlinear effects in protein dynamics are expected to play role in function, particularly of allosteric nature, by facilitating energy transfer between vibrational modes. A recently proposed method focusing on the non‐Gaussian shape of the configurational population near equilibrium projects this information onto real space in order to identify the aminoacids relevant to function. We here apply this method to three ancestral proteins in glucocorticoid receptor (GR) family and show that the mutations that restrict functional activity during GR evolution correlate significantly with locations that are highlighted by the nonlinear contribution to the near‐native configurational distribution. Our findings demonstrate that the analysis of nonlinear effects in protein dynamics can be harnessed into a predictive tool for functional site determination. Proteins 2016; 84:655–665. © 2016 Wiley Periodicals, Inc.
To See or Not to See: The Need for Attention to Perceive Changes in Scenes

When looking at a scene, our impression as observers is that we see its entire structure in great detail and can immediately notice any changes in it. However, when brief blank fields are placed between alternating displays of an original and a modified scene, a striking failure of perception is induced: identification of changes becomes extremely difficult, even when changes are large and made repeatedly. Identification is much faster when a verbal cue is provided, showing that poor visibility is not the cause of this difficulty. Identification is also faster for objects mentioned in brief verbal descriptions of the scene. These results support the idea that observers never form a complete, detailed representation of their surroundings. In addition, results also indicate that attention is required to perceive change, and that in the absence of localized motion signals it is guided on the basis of high-level "interest".
Modeling of Cerebral Oxygen Transport Based on In vivo Microscopic Imaging of Microvascular Network Structure, Blood Flow, and Oxygenation

Oxygen is delivered to brain tissue by a dense network of microvessels, which actively control cerebral blood flow (CBF) through vasodilation and contraction in response to changing levels of neural activity. Understanding these network-level processes is immediately relevant for (1) interpretation of functional Magnetic Resonance Imaging (fMRI) signals, and (2) investigation of neurological diseases in which a deterioration of neurovascular and neuro-metabolic physiology contributes to motor and cognitive decline. Experimental data on the structure, flow and oxygen levels of microvascular networks are needed, together with theoretical methods to integrate this information and predict physiologically relevant properties that are not directly measurable. Recent progress in optical imaging technologies for high-resolution in vivo measurement of the cerebral microvascular architecture, blood flow, and oxygenation enables construction of detailed computational models of cerebral hemodynamics and oxygen transport based on realistic three-dimensional microvascular networks. In this article, we review state-of-the-art optical microscopy technologies for quantitative in vivo imaging of cerebral microvascular structure, blood flow and oxygenation, and theoretical methods that utilize such data to generate spatially resolved models for blood flow and oxygen transport. These “bottom-up” models are essential for the understanding of the processes governing brain oxygenation in normal and disease states and for eventual translation of the lessons learned from animal studies to humans.
World Journal of Gastroenterology

BACKGROUND Liver injury is common in severe acute pancreatitis (SAP). Excessive autophagy often leads to an imbalance of homeostasis in hepatocytes, which induces lipid peroxidation and mitochondrial iron deposition and ultimately leads to ferrop-tosis. Our previous study found that milk fat globule epidermal growth factor 8 (MFG-E8) alleviates acinar cell damage during SAP via binding to α v
Intelligent switching between multiple model-based adaptive controllers using data-driven control theory

Adaptive control theory is a promising technology to improve the performance and stability of nominal controllers in the presence of system uncertainties. However, conventional model reference adaptive control schemes are not robust in the presence of unmodeled dynamics, actuator constraints etc. To overcome the above limitations, recently various new adaptive control schemes are proposed in the literature. Since the underlying mathematical constructs of these schemes are different, each adaptive scheme might be efficient in handling a particular class of unanticipated disturbance. Instead of depending on a single scheme to provide robustness, the best strategy will be to run all the adaptive schemes parallel and optimally switch between them depending on the current state of the system. This paper proposes a stable data-driven supervisory algorithm to switch between various model-based adaptive control schemes. The optimal switching is achieved using a data-driven control concept called `Unfalsified adaptive control'. The resulting data-driven collaborative adaptive controller greatly improves the performance and robustness of the nominal controller compared to independent adaptive schemes. Simulation results demonstrate the efficacy of the proposed algorithm.
Anomalies in network traffic

We report the results of a search for anomalies in network traffic. Our data set consisted of two billion packets collected over four days at the gateways of our large corporate network. Analysis of the distributions of the packet metadata fields (IP addresses, ports, time-to-live and packet length) revealed anomalous activity including IP scans, port scans and hybrid scans as well as coordinated and synchronous activity. Analysis of such large amounts of data can be onerous; the use of Apache Hadoop to implement reliable, scalable, distributed computing enabled us to perform our computations rapidly on a small cluster of servers.
Universal Differential Equations as a Common Modeling Language for Neuroscience

The unprecedented availability of large-scale datasets in neuroscience has spurred the exploration of artificial deep neural networks (DNNs) both as empirical tools and as models of natural neural systems. Their appeal lies in their ability to approximate arbitrary functions directly from observations, circumventing the need for cumbersome mechanistic modeling. However, without appropriate constraints, DNNs risk producing implausible models, diminishing their scientific value. Moreover, the interpretability of DNNs poses a significant challenge, particularly with the adoption of more complex expressive architectures. In this perspective, we argue for universal differential equations (UDEs) as a unifying approach for model development and validation in neuroscience. UDEs view differential equations as parameterizable, differentiable mathematical objects that can be augmented and trained with scalable deep learning techniques. This synergy facilitates the integration of decades of extensive literature in calculus, numerical analysis, and neural modeling with emerging advancements in AI into a potent framework. We provide a primer on this burgeoning topic in scientific machine learning and demonstrate how UDEs fill in a critical gap between mechanistic, phenomenological, and data-driven models in neuroscience. We outline a flexible recipe for modeling neural systems with UDEs and discuss how they can offer principled solutions to inherent challenges across diverse neuroscience applications such as understanding neural computation, controlling neural systems, neural decoding, and normative modeling.
Aerosol direct radiative forcing at the top of atmosphere based on satellite remote sensing over China Seas: a preliminary study

Radiative forcing as an index of climate change can reflect the relative effect of climate factors. To understand climatic implications of aerosols over the China Seas, the aerosol direct radiative forcing at the top of atmosphere (TOA) is computed using three-year collocated Clouds and the Earth's Radiant Energy System (CERES) radiation fluxes and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness data on the platform Terra. The upward radiation flux for clear skies is a key for the aerosol radiative forcing at the TOA. A linear relationship is found between the solar radiation fluxes at the TOA from CERES and the aerosol optical thickness is at 550 nm from MODIS over the China Seas. In a linear regression Eq., the intercept for zero aerosol optical thickness is the radiation flux at the TOA for clear skies. Based on the definition of the aerosol direct radiative forcing at TOA and the diurnal correction factor from a simulated radiative forcing using radiation transfer model, the daily averaged aerosol direct radiative forcing at the TOA is estimated and its seasonal variations over the cloud-free China Seas are presented. In total, the aerosol radiative forcing over the China Seas is negative. It implies that the aerosol over the China Seas is mainly a cooling effect on climate change, which is opposite to the greenhouse effect. The largest aerosol radiative forcing is found in spring, while the smallest is in summer. The aerosol radiative forcing over the coastal region is always more than that in the open ocean in four seasons. The method in the study can be used for evaluation of the aerosols impact on global or region climate from satellite measurements.