Miracle-dz/UniFAR-FTUs huggingface dataset:
Eavesdropping on altered cell-to-cell signaling in cancer by secretome profiling

In the past decade, cumulative clinical experiences with molecular targeted therapies and immunotherapies for cancer have promoted a shift in our conceptual understanding of cancer. This view shifted from viewing solid tumors as a homogeneous mass of malignant cells to viewing tumors as heterogeneous structures that are dynamically shaped by intercellular interactions among the variety of stromal, immune, and malignant cells present within the tumor microenvironment. As in any dynamic system, identifying how cells communicate to maintain homeostasis and how this communication is altered during oncogenesis are key hurdles for developing therapies to restore normal tissue homeostasis. Here, I discuss tissues as dynamic systems, using the mammary gland as an example, and the evolutionary concepts applied to oncogenesis. Drawing from these concepts, I present 2 competing hypotheses for how intercellular communication might be altered during oncogenesis. As an initial test of these competing hypotheses, a recent secretome comparison between normal human mammary and HER2+ breast cancer cell lines suggested that the particular proteins secreted by the malignant cells reflect a convergent evolutionary path associated with oncogenesis in a specific anatomical niche, despite arising in different individuals. Overall, this study illustrates the emerging power of secretome proteomics to probe, in an unbiased way, how intercellular communication changes during oncogenesis.
Downscaling of ERA-Interim Temperature in the Contiguous United States and Its Implications for Rain–Snow Partitioning

Precipitation phase has an important influence on hydrological processes. The Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) uses temperature data from reanalysis products to implement rain–snow classification. However, the coarse resolution of reanalysis data may not reveal the spatiotemporal variabilities of temperature, necessitating appropriate downscaling methods. This study compares the performance of eight air temperature Ta downscaling methods in the contiguous United States and six mountain ranges using temperature from the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) as the benchmark. ERA-Interim Ta is downscaled from the original 0.75° to 0.1°. The results suggest that the two purely statistical downscaling methods [nearest neighbor (NN) and bilinear interpolation (BI)] show similar performance with each other. The five downscaling methods based on the free-air temperature lapse rate (TLR), which is calculated using temperature and geopotential heights at different pressure levels, notably improves the accuracy of Ta. The improvement is particularly obvious in mountainous regions. We further calculated wet-bulb temperature Tw, for rain–snow classification, using Ta and dewpoint temperature from ERA-Interim and PRISM. TLR-based downscaling methods result in more accurate Tw compared to NN and BI in the western United States, whereas the improvement is limited in the eastern United States. Rain–snow partitioning is conducted using a critical threshold of Tw with Snow Data Assimilation System (SNODAS) snowfall data serving as the benchmark. ERA-Interim-based Tw using TLR downscaling methods is better than that using NN/BI and IMERG precipitation phase. In conclusion, TLR-based downscaling methods show promising prospects in acquiring high-quality Ta and Tw with high resolution and improving rain–snow partitioning, particularly in mountainous regions.
Operational Semantics of Transactions

Mathematics is forcing towards a consistent framework of theory development. Computer Science is an engineering discipline and sometimes suffers from ad-hoc definitions. Transactions are a concept that is commonly used in the database area. It is often defined in the form: given a syntactic construct in an abstract form and declare a number of properties an engine should support which is not specified and invisible.This paper aims in providing an operational semantics for transactions. A DBMS implementation is then considered to be a faithful refinement of the operational semantics.
Autism: functional brain mapping of exceptional calendar capacity.

BACKGROUND 'Autistic savants' are individuals with autism who have extraordinary skills. Brain mechanisms underlying such capacities are still unknown. AIMS To map the exceptional calendar capacity of a man with primary autism. METHOD Positron emission tomography was used to map brain activity in a man who is able to associate a day of the week with the corresponding calendar date. RESULTS During the calendar task, the left hippocampus, the left frontal cortex and the left middle temporal lobe were activated. CONCLUSIONS The cerebral circuit involved in this man's prodigious calendar skill is similar to that normally involved in memory retrieval tasks. These results suggest that the prodigious capacities may be sustained by memory processing.
Differential roles for NMDA and non‐NMDA receptor subtypes in baroreceptor afferent integration in the nucleus of the solitary tract of the rat

1 Microinjection studies have established that both NMDA and non‐NMDA excitatory amino acid (EAA) receptor subtypes are involved in the integration of baroreceptor afferent inputs within the nucleus of the solitary tract (NTS). The present study was undertaken to determine which EAA receptor subtypes are involved in baroreceptor afferent integration by second and higher order NTS neurones. 2 Experiments utilizing intracellular recordings or extracellular recordings with microiontophoresis were performed in pentobarbitone‐anaesthetized, paralysed and artificially ventilated rats to determine the ionotropic EAA receptor subtypes involved in baroreceptor afferent integration in the NTS. NTS neurones were classified according to their responses to aortic depressor nerve (ADN) stimulation: monosynaptic neurones (MSNs), polysynaptic neurones (PSNs) and ADN‐non‐evoked neurones (NENs). 3 In the extracellular studies, the ADN‐evoked discharge of most MSNs was selectively reduced by microiontophoretic application of the non‐NMDA receptor antagonists 6‐cyano‐7‐nitroquinoxaline‐2,3‐dione (CNQX; n= 8, P < 0.05) or 1,2,3,4‐tetrahydro‐6‐nitro‐2,3‐dioxo‐benzo(f)quinoxaline‐7‐sulphonamide (NBQX; n= 9, P < 0.01), but not by the NMDA antagonist dl‐2‐amino‐5‐phosphonopentanoic acid (AP‐5; n= 6, P= 0.28). ADN‐evoked responses of PSNs were attenuated by microiontophoretic application of AP‐5 (n= 12, P < 0.001), CNQX (n= 13, P < 0.001) or NBQX (n= 11, P < 0.001). All EAA antagonists inhibited the spontaneous discharge of MSNs/PSNs and NENs (P < 0.01 for each group). 4 In the intracellular studies, ADN stimulation evoked faster rising and shorter duration excitatory postsynaptic potentials (EPSPs) in MSNs (n= 16) than in PSNs (n= 15) (P < 0.05 for each comparison). 5 Our results demonstrate that synaptic inputs from ADN to MSNs have faster rise times and shorter durations than those to PSNs, suggesting that baroreceptor inputs to MSNs and PSNs are mediated by different synaptic mechanisms. These more rapid synaptic events are selectively mediated by non‐NMDA receptors. In addition, synaptic integration of ADN inputs by PSNs is mediated by both NMDA and non‐NMDA receptors. Finally, the ADN‐evoked discharge of some MSNs and PSNs is not attenuated by ionotropic EAA antagonists, suggesting that another receptor or transmitter system may mediate synaptic excitation in these neurones.
Automatic virtual machine configuration for database workloads

Virtual machine monitors are becoming popular tools for the deployment of database management systems and other enterprise software applications. In this paper, we consider a common resource consolidation scenario, in which several database management system instances, each running in a virtual machine, are sharing a common pool of physical computing resources. We address the problem of optimizing the performance of these database management systems by controlling the configurations of the virtual machines in which they run. These virtual machine configurations determine how the shared physical resources will be allocated to the different database instances. We introduce a virtualization design advisor that uses information about the anticipated workloads of each of the database systems to recommend workload-specific configurations offine. Furthermore, runtime information collected after the deployment of the recommended configurations can be used to refine the recommendation. To estimate the effect of a particular resource allocation on workload performance, we use the query optimizer in a new what-if mode. We have implemented our approach using both PostgreSQL and DB2, and we have experimentally evaluated its effectiveness using DSS and OLTP workloads.
Phytoremediation Potential of Myriophyllum aquaticum and Pistia stratiotes to Modify Antibiotic Growth Promoters, Tetracycline, and Oxytetracycline, in Aqueous Wastewater Systems

Antibiotics are frequently used in the United States as feed efficiency promoters and medicines for livestock that is destined for human consumption. These antibiotics are released into the environment through the runoff and wastewater streams from animal feedlots and land applications of manure. The exposure of microorganisms to these antibiotics has reportedly resulted in the development of resistant species of microorganisms, which in turn can lead to human health hazards. Phytoremediation of these antibiotics can be a useful tool for countering this problem. Aquatic plants, Myriophyllum aquaticum (parrot feather) and Pistia stratiotes (water lettuce), were used for studying phytoremediation of tetracycline (TC) and oxytetracycline (OTC) from aqueous media. TC and OTC are two of the most commonly used tetracyclines in veterinary medicine. M. aquaticum and P. stratiotes gave high antibiotic modification rates of both antibiotics. Kinetic analyses dismiss direct enzyme catalysis; the modification rates decreased with increasing OTC concentrations. Sterile, cell-free root exudates (filtered through 0.2 μ m membranes) from both species also exhibited comparable antibiotic modification rates. The involvement of root-secreted metabolites in antibiotic modification is suggested. The changes in the UV absorbance spectra of OTC during treatment with the root exudates confirmed the modification.
Buffer allocation for real-time streaming on a multi-processor without back-pressure

The goal of buffer allocation for real-time streaming applications, modeled as dataflow graphs, is to minimize total memory consumption while reserving sufficient space for each production without overwriting any live tokens and guaranteeing the satisfaction of real-time constraints. We present a buffer allocation solution for dataflow graphs scheduled on a system without back-pressure. Our contributions are 1) We extend the available dataflow techniques by applying best-case analysis. 2) We introduce dominator based relative life-time analysis. For our benchmark set, it exhibits up to 12% savings on memory consumption compared to traditional absolute life-time analysis. 3) We investigate the effect of variation in execution times on the buffer sizes for systems without back-pressure. It turns out that reducing the variation in execution times reduces the buffer sizes. 4) We compare the buffer allocation techniques for systems with and without backpressure. For our benchmark set, we show that the system with back-pressure reduces the total memory consumption by as much as 28 % compared to the system without back-pressure. Our benchmark set includes wireless communications and multimedia applications.
Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models

We make several contributions in accelerating approximate Bayesian structural inference for non-decomposable GGMs. Our first contribution is to show how to efficiently compute a BIC or Laplace approximation to the marginal likelihood of non-decomposable graphs using convex methods for precision matrix estimation. This optimization technique can be used as a fast scoring function inside standard Stochastic Local Search (SLS) for generating posterior samples. Our second contribution is a novel framework for efficiently generating large sets of high-quality graph topologies without performing local search. This graph proposal method, which we call "Neighborhood Fusion" (NF), samples candidate Markov blankets at each node using sparse regression techniques. Our third contribution is a hybrid method combining the complementary strengths of NF and SLS. Experimental results in structural recovery and prediction tasks demonstrate that NF and hybrid NF/SLS out-perform state-of-the-art local search methods, on both synthetic and real-world datasets, when realistic computational limits are imposed.
Multi-timescale nexting in a reinforcement learning robot

The term ‘nexting’ has been used by psychologists to refer to the propensity of people and many other animals to continually predict what will happen next in an immediate, local, and personal sense. The ability to ‘next’ constitutes a basic kind of awareness and knowledge of one’s environment. In this paper we present results with a robot that learns to next in real time, making thousands of predictions about sensory input signals at timescales from 0.1 to 8 seconds. Our predictions are formulated as a generalization of the value functions commonly used in reinforcement learning, where now an arbitrary function of the sensory input signals is used as a pseudo reward, and the discount rate determines the timescale. We show that six thousand predictions, each computed as a function of six thousand features of the state, can be learned and updated online ten times per second on a laptop computer, using the standard temporal-difference(λ) algorithm with linear function approximation. This approach is sufficiently computationally efficient to be used for real-time learning on the robot and sufficiently data efficient to achieve substantial accuracy within 30 minutes. Moreover, a single tile-coded feature representation suffices to accurately predict many different signals over a significant range of timescales. We also extend nexting beyond simple timescales by letting the discount rate be a function of the state and show that nexting predictions of this more general form can also be learned with substantial accuracy. General nexting provides a simple yet powerful mechanism for a robot to acquire predictive knowledge of the dynamics of its environment.
Comparing the Skeletal Anatomy, Technology and Culture of Homo neanderthalensis and Early Modern Humans

This paper will compare the overall differences in skeletal anatomy, along with the technological and cultural adaptations, between Homo neanderthalensis and early modern humans, and will show that the Neanderthals were, at least physically, very well adapted to their harsh environmental conditions and physically strenuous lifeway. Several studies have shown that the shorter, stockier and more robust body shape of the Neanderthals was advantageous for maintenance of body temperature in the cold climate of the last glacial period (Porter, 1999). Also, due to a lower centre of gravity, locomotion on the uneven, snow-covered terrain of their territories would have been enhanced (Polk, 2004; Steudel-Numbers and Tilkens, 2004). According to Holliday (1997), the overall Neanderthal body shape falls “at the extreme end of modern higher latitude groups”, and suggests that they were more similar to modern “Eskimos” than any other group. The Neanderthals were both morphologically and physiologically well suited to their environment, as evidenced by their skeletal adaptations (Holliday, 1997), and hunting skills (Hoffecker & Cleghorn, 2000). With the exception of peoples inhabiting the Earth's polar regions, as mentioned above, modern humans generally show few morphological or physiological adaptations to a cold climate, other than a slightly reduced overall skin surface area, but there is ample evidence (Hoffecker, 1999), that early modern humans were better prepared, both culturally and technologically, compared to the Neanderthals, to survive and flourish in a harsh, physically demanding environment.
Red/green opponency in the rhesus macaque ERG spectral sensitivity is reduced by bicuculline

Abstract Spectral-sensitivity curves were derived from the a−, b−, and d−waves of rhesus monkey ERGs after injection of bicuculline, strychnine, or no drug. Without drug injection, the a− and d−wave curves were well-fit by an additive model of weighted photoreceptor absorption spectra, while the b−wave curve requires inhibitory terms to produce an adequate fit. Bicuculline, but not strychnine, reduced the weight assigned to the inhibitory terms in a dose-dependent fashion, to the point that no inhibition was evident. The results suggest that GABAergic synapses are required for the expression of red/green color opponency in primate bipolar cells.
Essential role of the T cell–specific adapter protein in the activation of LCK in peripheral T cells

T cell–specific adapter protein (TSAd) is a SRC-homology-2 (SH2) domain–containing intracellular signaling molecule that is required for T cell antigen receptor (TCR)–induced cytokine synthesis in T cells. How TSAd functions in TCR signal transduction is not clear. Previous work has suggested a nuclear role for this adapter. However, other evidence suggests that TSAd also functions in the cytoplasm. Using T cells from TSAd-deficient mice, we now show that the major role of TSAd in the cytoplasm is in activation of the LCK protein tyrosine kinase at the outset of TCR signal transduction. Consequently, TSAd regulates several downstream signaling events, including intracellular calcium mobilization and activation of the Ras–extracellular signal–regulated kinase signaling pathway. TSAd regulates LCK activity directly through physical interaction with LCK SH3 and SH2 domains. These studies reveal TSAd as a positive regulator of proximal TCR signal transduction and provide important new information on the mechanism of TCR-induced LCK activation.
Effects of exercise training on glucose homeostasis: the HERITAGE Family Study.

OBJECTIVE To determine the effect of a 20-week endurance training program in healthy, previously sedentary participants on measures derived from an intravenous glucose tolerance test (i.v.GTT). RESEARCH DESIGN AND METHODS An i.v. GTT was performed before and after a standardized training program in 316 women and 280 men (173 blacks and 423 whites). Participants exercised on cycle ergometers 3 days per week for 60 sessions. The exercise intensity was progressively increased from 55% VO2max for 30 min per session to 75% VO2max for 50 min per session. RESULTS Mean insulin sensitivity increased by 10% (P < 0.001) following the intervention, but the variability in the changes was high. Men had larger improvements than women (P = 0.02). Improvements in fasting insulin were transitory, disappearing 72 h after the last bout of exercise. There were also significant mean increases in the glucose disappearance index (3%, P = 0.02) and in glucose effectiveness (11%, P < 0.001), measures of glucose tolerance and of the capacity of glucose to mediate its own disposal, respectively. The acute insulin response to glucose, a measure of insulin secretion, increased by 7% in the quartile with the lowest baseline glucose tolerance and decreased by 14% in the quartile with the highest baseline glucose tolerance (P < 0.001). The glucose area below fasting levels during the i.v. GTT was reduced by 7% (P = 0.02). CONCLUSIONS Although the effects of structured regular exercise were highly variable, there were improvements in virtually all i.v. GTT-derived variables. In the absence of substantial weight loss, regular exercise is required for sustained improvements in glucose homeostasis.
The Complexity of Reasoning for Fragments of Autoepistemic Logic

Autoepistemic logic extends propositional logic by the modal operator L. A formula ϕ that is preceded by an L is said to be “believed. ” The logic was introduced by Moore in 1985 for modeling an ideally rational agent’s behavior and reasoning about his own beliefs. In this article we analyze all Boolean fragments of autoepistemic logic with respect to the computational complexity of the three most common decision problems expansion existence, brave reasoning and cautious reasoning. As a second contribution we classify the computational complexity of checking that a given set of formulae characterizes a stable expansion and that of counting the number of stable expansions of a given knowledge base. We improve the best known Δ2p-upper bound on the former problem to completeness for the second level of the Boolean hierarchy. To the best of our knowledge, this is the first paper analyzing counting problem for autoepistemic logic.
A Non-isolated Voltage Regulator Module with Integrating Coupled-Inductor

With lower output voltage and higher output current demands, today's VRM is almost based on interleaved multiphase buck converter, which requires strictly steady and dynamic performances to supply microprocessor. In this paper, a non-isolated multiphase VRM with integrating coupled magnetic is introduced to reduce magnetic component and improve steady state and dynamic performances. All these magnetic components can be coupled into a single ferrite core. By proper designing the gap of integrating coupled-inductor, this novel technique can greatly improve the performances of VRM with fast transient response and high efficiency. The simulation and experimental results of two-phase VRM show that integrating coupled-inductor can improve VRM's steady and dynamic performances, compared with the conventional VRM