Data reduction in the ITMS system through a data acquisition model with self-adaptive sampling rate

Long pulse or steady state operation of fusion experiments require data acquisition and processing systems that reduce the volume of data involved. The availability of self-adaptive sampling rate systems and the use of real-time lossless data compression techniques can help solve these problems. The former is important for continuous adaptation of sampling frequency for experimental requirements. The latter allows the maintenance of continuous digitization under limited memory conditions. This can be achieved by permanent transmission of compressed data to other systems. The compacted transfer ensures the use of minimum bandwidth. This paper presents an implementation based on intelligent test and measurement system (ITMS), a data acquisition system architecture with multiprocessing capabilities that permits it to adapt the system’s sampling frequency throughout the experiment. The sampling rate can be controlled depending on the experiment’s specific requirements by using an external dc voltage signal or by defining user events through software. The system takes advantage of the high processing capabilities of the ITMS platform to implement a data reduction mechanism based in lossless data compression algorithms which are themselves based in periodic deltas

Estimation of the noise emissions generated by a single vehicle while driving

This article presents a method of calculation that allows us to separate the contribution of a specific vehicle to the overall noise pollution in an urban environment. This method will provide local authorities with new operating models so that the cost of noise can be allocated to a vehicle according to factors such as the number of people it affects, the distance traveled and journey time, the driving style and the type of vehicle and tires. The proposed methodology can be adapted to different noise emission and propagation models, and we select as a basis the CNOSSOS-EU framework for compatibility with the European noise mapping strategy. This method will make it possible to reduce road traffic noise using two long-term strategies: (a) separate distributions of the costs of noise among the vehicles that generate it, with the aim of achieving (b) an increase in pro-environmental behavior with regard to this pollutant

Intrinsic gain modulation and adaptive neural coding

In many cases, the computation of a neural system can be reduced to a receptive field, or a set of linear filters, and a thresholding function, or gain curve, which determines the firing probability; this is known as a linear/nonlinear model. In some forms of sensory adaptation, these linear filters and gain curve adjust very rapidly to changes in the variance of a randomly varying driving input. An apparently similar but previously unrelated issue is the observation of gain control by background noise in cortical neurons: the slope of the firing rate vs current (f-I) curve changes with the variance of background random input. Here, we show a direct correspondence between these two observations by relating variance-dependent changes in the gain of f-I curves to characteristics of the changing empirical linear/nonlinear model obtained by sampling. In the case that the underlying system is fixed, we derive relationships relating the change of the gain with respect to both mean and variance with the receptive fields derived from reverse correlation on a white noise stimulus. Using two conductance-based model neurons that display distinct gain modulation properties through a simple change in parameters, we show that coding properties of both these models quantitatively satisfy the predicted relationships. Our results describe how both variance-dependent gain modulation and adaptive neural computation result from intrinsic nonlinearity.Comment: 24 pages, 4 figures, 1 supporting informatio

Clinical Practice: Giant Cell Tumour of the Jaw Mimicking Bone Malignancy on Three-Dimensional Computed Tomography (3D CT) Reconstruction

A wide range of diseases may present with radiographic features of osteolysis. Periapical inflammation, cysts and benign tumours, bone malignancies, all of these conditions may show bone resorption on radiograph. Features of the surrounding bone, margins of the lesion, and biological behaviour including tendency to infiltration and root resorption, may represent important criteria for distinguishing benign tumours from their malign counterpart, although the radiographic aspect of the lesion is not always predictive. Therefore a critical differential diagnosis has to be reached to choose the best management. Here, we report a case of giant cell tumour (GCT) whose radiological features by computed tomography (CT) suggested the presence of bone malignancy, whereas the evaluation of a routine OPT scan comforted us about the benign nature of the lesion. A brief review of the literature on such a benign but locally aggressive neoplasm is also provided

Clinical Practice: Giant Cell Tumour of the Jaw Mimicking Bone Malignancy on Three-Dimensional Computed Tomography (3D CT) Reconstruction

A wide range of diseases may present with radiographic features of osteolysis. Periapical inflammation, cysts and benign tumours, bone malignancies, all of these conditions may show bone resorption on radiograph. Features of the surrounding bone, margins of the lesion, and biological behaviour including tendency to infiltration and root resorption, may represent important criteria for distinguishing benign tumours from their malign counterpart, although the radiographic aspect of the lesion is not always predictive. Therefore a critical differential diagnosis has to be reached to choose the best management. Here, we report a case of giant cell tumour (GCT) whose radiological features by computed tomography (CT) suggested the presence of bone malignancy, whereas the evaluation of a routine OPT scan comforted us about the benign nature of the lesion. A brief review of the literature on such a benign but locally aggressive neoplasm is also provided

Representation of Dynamical Stimuli in Populations of Threshold Neurons

Many sensory or cognitive events are associated with dynamic current modulations in cortical neurons. This raises an urgent demand for tractable model approaches addressing the merits and limits of potential encoding strategies. Yet, current theoretical approaches addressing the response to mean- and variance-encoded stimuli rarely provide complete response functions for both modes of encoding in the presence of correlated noise. Here, we investigate the neuronal population response to dynamical modifications of the mean or variance of the synaptic bombardment using an alternative threshold model framework. In the variance and mean channel, we provide explicit expressions for the linear and non-linear frequency response functions in the presence of correlated noise and use them to derive population rate response to step-like stimuli. For mean-encoded signals, we find that the complete response function depends only on the temporal width of the input correlation function, but not on other functional specifics. Furthermore, we show that both mean- and variance-encoded signals can relay high-frequency inputs, and in both schemes step-like changes can be detected instantaneously. Finally, we obtain the pairwise spike correlation function and the spike triggered average from the linear mean-evoked response function. These results provide a maximally tractable limiting case that complements and extends previous results obtained in the integrate and fire framework

Repurposed floxacins targeting RSK4 prevent chemoresistance and metastasis in lung and bladder cancer

Lung and bladder cancers are mostly incurable because of the early development of drug resistance and metastatic dissemination. Hence, improved therapies that tackle these two processes are urgently needed to improve clinical outcome. We have identified RSK4 as a promoter of drug resistance and metastasis in lung and bladder cancer cells. Silencing this kinase, through either RNA interference or CRISPR, sensitized tumor cells to chemotherapy and hindered metastasis in vitro and in vivo in a tail vein injection model. Drug screening revealed several floxacin antibiotics as potent RSK4 activation inhibitors, and trovafloxacin reproduced all effects of RSK4 silencing in vitro and in/ex vivo using lung cancer xenograft and genetically engineered mouse models and bladder tumor explants. Through x-ray structure determination and Markov transient and Deuterium exchange analyses, we identified the allosteric binding site and revealed how this compound blocks RSK4 kinase activation through binding to an allosteric site and mimicking a kinase autoinhibitory mechanism involving the RSK4’s hydrophobic motif. Last, we show that patients undergoing chemotherapy and adhering to prophylactic levofloxacin in the large placebo-controlled randomized phase 3 SIGNIFICANT trial had significantly increased (P = 0.048) long-term overall survival times. Hence, we suggest that RSK4 inhibition may represent an effective therapeutic strategy for treating lung and bladder cancer

The effects of mutant Ras proteins on the cell signalome

The genetic alterations in cancer cells are tightly linked to signaling pathway dysregulation. Ras is a key molecule that controls several tumorigenesis-related processes, and mutations in RAS genes often lead to unbiased intensification of signaling networks that fuel cancer progression. In this article, we review recent studies that describe mutant Ras-regulated signaling routes and their cross-talk. In addition to the two main Ras-driven signaling pathways, i.e., the RAF/MEK/ERK and PI3K/AKT/mTOR pathways, we have also collected emerging data showing the importance of Ras in other signaling pathways, including the RAC/PAK, RalGDS/Ral, and PKC/PLC signaling pathways. Moreover, microRNA-regulated Ras-associated signaling pathways are also discussed to highlight the importance of Ras regulation in cancer. Finally, emerging data show that the signal alterations in specific cell types, such as cancer stem cells, could promote cancer development. Therefore, we also cover the up-to-date findings related to Ras-regulated signal transduction in cancer stem cells. © 2020, The Author(s)

Homocysteine and Coronary Heart Disease: Meta-analysis of MTHFR Case-Control Studies, Avoiding Publication Bias

Robert Clarke and colleagues conduct a meta-analysis of unpublished datasets to examine the causal relationship between elevation of homocysteine levels in the blood and the risk of coronary heart disease. Their data suggest that an increase in homocysteine levels is not likely to result in an increase in risk of coronary heart disease