Miracle-dz/UniFAR-FTUs huggingface dataset:
Long‐lasting potentiation of hippocampal synaptic transmission by direct cortical input is mediated via endocannabinoids

Key points • Hippocampal CA1 pyramidal neurons receive dual sensory inputs from the cortex directly through the perforant path (PP) and indirectly through the Schaffer collaterals (SC). • Direct cortical inputs to CA1 pyramidal neurons through the PP are important for synaptic plasticity and memory formation. • In this study, we show that long‐lasting potentiation of glutamatergic synaptic transmission at SC synapses by pairing of PP–SC inputs was suppressed by pharmacological and genetic inhibition of CB1 receptors. • Inhibition of the enzyme synthesizing the endocannabinoid 2‐arachidonoylglycerol (2‐AG) prevented the pairing‐induced potentiation, while inhibition of the enzyme hydrolysing 2‐AG facilitated the potentiation. • Our results indicate that 2‐AG functions as a signalling mediator tuning synaptic efficacy at the proximal synapses of hippocampal CA1 pyramidal neurons while direct and indirect cortical inputs to the same neurons are spatiotemporally primed, suggesting that endocannabinoids are involved in the information processing and storage in the hippocampus.
A comparative study of colloidal particles as imaging standards for microscopy

Colloidal particles have long been used as imaging standards for electron microscopy and, more recently, for scanning probe microscopy. We have analysed gold, polystyrene and silica colloidal particles by both transmission electron microscopy and atomic/scanning force microscopy in an attempt to determine if any can be truly used as ‘standards’ of shape and/or size. From the transmission electron micrographs, we have obtained precise information of the particle circumference and mean diameter. By comparing the ratio of these to the value for π, we obtained a measure of the sphericity of the particles. We have also shadowed the particles with metal at a known angle and have analysed the shadow length to determine the particles' heights and shapes. The height information obtained from the shadow length data collected from the transmission electron micrographs was then compared with that obtained by atomic/scanning force microscopy. Our results show that cleaned (washed) silica or polystyrene particles closely approach true spheres. In the case of gold particles, height data obtained from shadow lengths analysed in transmission electron micrographs show good agreement with that obtained from the atomic/scanning force microscopy images even without washing. However, the gold particles often deviate from sphericity. Based upon both the shape and the physical properties of the colloidal particles, silica would be the best choice as a standard. We also have noticed that metal shadowing of colloidal particle samples used for atomic/scanning force microscopy offers an advantage which we call a ‘nanoscale metric’ visible in the image directly at each particle site. This information can be important if one wishes to use samples prepared from colloidal particles simply and reliably to determine the probe shape for scanning probe microscopy from image deconvolution/restoration methods or as a calibration sample.
Identification and extraction of proteins that compose the triad junction of skeletal muscle

Treatment of both transverse tubules and terminal cisternae with a combination of Triton X-100 and hypertonic K cacodylate causes dissolution of nonjunctional proteins and selective retention of membrane fragments which are capable of junction formation. Treatment of vesicles with Triton X-100 and either KCl or K gluconate causes complete dissolution of all components. Therefore K cacodylate exerts a specific preservative action on the junctional material. The membrane fragment from treatment of transverse tubules with Triton X-100 + cacodylate contains a protein of Mr = 80,000 in SDS gel electrophoresis as the predominant protein while lipid composition is enriched in cholesterol. The membrane fragment retains in electron microscopy the trilaminar appearance of the intact vesicles. Freeze fracture of transverse tubule fragments reveals a high density of low-profile, intercalated particles, which frequently form strings or occasional small arrays. The fragments from Triton X-100 plus cacodylate treatment of terminal cisternae include the protein of Mr = 80,000 as well as the spanning protein of the triad, calsequestrin, and some minor proteins. The fragments are almost devoid of lipid and display an amorphous morphology suggesting membrane disruption. The ability of the transverse tubular fragment, which contains predominantly the Mr = 80,000 protein, to form junctions with terminal cisternae fragments suggests that it plays a role in anchoring the membrane to the junctional processes of the triad. The junctional proteins may be solubilized in a combination of nonionic detergent and hypertonic NaCl. Subsequent molecular sieve chromatography gives an enriched preparation of the spanning protein. This protein has subunits of Mr = 300,000, 270,000 and 140,000 and migrates in the gel as a protein of Mr = 1.2 X 10(6) indicating a polymeric structure.
Predicting Metacritic Film Reviews Using Linked Open Data and Semantic Technologies

Aristotle was quoted as saying that “the whole is more than the sum of its parts”. Using Linked Open Data, we are finally able to test and quantify Aristotle’s theory. By using the flexible data representation of RDF as well as the graph-oriented nature of SPARQL, we attempt to answer the questions: What makes a movie good? And more specifically, what makes a critic think that a movie is good? We take a novel approach to predictive analytics that is implemented entirely in SPARQL rather than using more traditional statistical machine learning platforms (e.g. Rapidminer, etc.).
Does globalization of water reduce societal resilience to drought?

Most food production depends, directly or indirectly, on freshwater resources. In the absence of importation of food commodities, population growth is constrained by the availability of local resources—including water—as well as by cultural and health‐related factors. The global trade of massive amounts of food makes societies less reliant on locally available water resources, thereby allowing some populations to exceed the limits posed by their local water budget. Thus, international trade implies a virtual transfer of water resources from areas of food production to importing regions. While it is recognized that in the short term this globalization of (virtual) water resources may prevent malnourishment, famine, and conflicts, its long‐term effects on the coupled human‐natural system remain poorly investigated. Here we develop a minimalist modeling framework to investigate the effect of the uncontrolled trade of food products on the resilience of human societies with respect to drought and famine. Our results suggest that in the long run the globalization of water resources reduces the societal resilience with respect to water limitations in that it leaves fewer options available to cope with exceptional droughts and crop failure.
Wearable Wireless Telemetry System for Implantable Bio-MEMS Sensors

In this paper, a telemetry and contact-less powering system consisting of an implantable bio-MEMS sensor with a miniature printed square spiral chip antenna and an external wearable garment with printed loop antenna is investigated. The implantable chip antenna and the wearable garment pick-up antenna are in close proximity to each other and hence couple inductively through their near-fields and behave as the primary and the secondary circuits of a transformer, respectively. The numerical and experimental results are graphically presented, and include the design parameter values as a function of the geometry and the relative magnetic near-field intensity as a function of the angle, for the implantable chip antenna
Association of Toll-Like Receptor 3 Single-Nucleotide Polymorphisms and Hepatitis C Virus Infection

Toll-like receptor 3 (TLR3) plays a key role in innate immunity by recognizing pathogenic, double-stranded RNAs. Thus, activation of TLR3 is a major factor in antiviral defense and tumor eradication. Although downregulation of TLR3 gene expression has been mainly reported in patients infected with hepatitis C virus (HCV), the influence of TLR3 genotype on the risk of HCV infection, HCV-related cirrhosis, and/or hepatocellular carcinoma (HCC) remains to be determined. Single-nucleotide polymorphisms (SNPs) within the TLR3 gene and their associations with HCV-related disease risk were investigated in a Saudi Arabian population in this study. Eight TLR3 SNPs were analyzed in 563 patients with HCV, which consisted of 437 patients with chronic HCV infections, 88 with HCV-induced liver cirrhosis, and 38 with HCC. A total of 599 healthy control subjects were recruited to the study. Among the eight TLR3 SNPs studied, the rs78726532 SNP was strongly associated with HCV infection when compared to that in healthy control subjects. The rs5743314 was also strongly associated with HCV-related liver disease progression (cirrhosis and HCC). In summary, these results indicate that distinct genetic variants of TLR3 SNPs are associated with HCV infection and HCV-mediated liver disease progression in the Saudi Arabian population.
Performance Awareness in Component Systems: Vision Paper

Resource awareness is a key requirement for dynamic adaptation in resource-constrained systems. Achieving resource awareness with clean separation of concerns and reasonable overhead is still a challenge - especially where this awareness concerns runtime performance. Among the difficult issues are for example transparent performance monitoring or platform independent performance evaluation. To advance the current state of the art in resource awareness, we propose a performance awareness framework for the domain of component-based systems. The framework is based on the Stochastic Performance Logic (SPL), which enables explicit description and automatic evaluation of assumptions about performance using logic formulas. We demonstrate the potential of the framework on multiple use-cases and outline extensions that facilitate the runtime resource awareness.
Single-Trial Analysis of Neuroimaging Data: Inferring Neural Networks Underlying Perceptual Decision-Making in the Human Brain

Advances in neural signal and image acquisition as well as in multivariate signal processing and machine learning are enabling a richer and more rigorous understanding of the neural basis of human decision-making. Decision-making is essentially characterized behaviorally by the variability of the decision across individual trials - e.g., error and response time distributions. To infer the neural processes that govern decision-making requires identifying neural correlates of such trial-to-trial behavioral variability. In this paper, we review efforts that utilize signal processing and machine learning to enable single-trial analysis of neural signals acquired while subjects perform simple decision-making tasks. Our focus is on neuroimaging data collected noninvasively via electroencephalograpy (EEG) and functional magnetic resonance imaging (fMRI). We review the specific framework for extracting decision-relevant neural components from the neuroimaging data, the goal being to analyze the trial-to-trial variability of the neural signal along these component directions and to relate them to elements of the decision-making process. We review results for perceptual decision-making and discrimination tasks, including paradigms in which EEG variability is used to inform an fMRI analysis. We discuss how single-trial analysis reveals aspects of the underlying decision-making networks that are unobservable using traditional trial-averaging methods.
Restoration of Peroxisomal Catalase Import in a Model of Human Cellular Aging

Peroxisomes play an important role in human cellular metabolism by housing enzymes involved in a number of essential biochemical pathways. Many of these enzymes are oxidases that transfer hydrogen atoms to molecular oxygen forming hydrogen peroxide. The organelle also contains catalase, which readily decomposes the hydrogen peroxide, a potentially damaging oxidant. Previous work has demonstrated that aging compromises peroxisomal protein import with catalase being particularly affected. The resultant imbalance in the relative ratio of oxidases to catalase was seen as a potential contributor to cellular oxidative stress and aging. Here we report that altering the peroxisomal targeting signal of catalase to the more effective serine‐lysine‐leucine (SKL) sequence results in a catalase molecule that more strongly interacts with its receptor and is more efficiently imported in both in vitro and in vivo assays. Furthermore, catalase‐SKL monomers expressed in cells interact with endogenous catalase subunits resulting in altered trafficking of the latter molecules. A dramatic reduction in cellular hydrogen peroxide levels accompanies this increased peroxisomal import of catalase. Finally, we show that catalase‐SKL stably expressed in cells by retroviral‐mediated transduction repolarizes mitochondria and reduces the number of senescent cells in a population. These results demonstrate the utility of a catalase‐SKL therapy for the restoration of a normal oxidative state in aging cells.
Autonomic Provisioning of Backend Databases in Dynamic Content Web Servers

In autonomic provisioning, a resource manager allocates resources to an application, on-demand, e.g., during load spikes. Modelling-based approaches have proved very successful for provisioning the web and application server tiers in dynamic content servers. On the other hand, accurately modelling the behavior of the back-end database server tier is a daunting task. Hence, automated provisioning of database replicas has received comparatively less attention. This paper introduces a novel pro-active scheme based on the classic K-nearest-neighbors (KNN) machine learning approach for adding database replicas to application allocations in dynamic content web server clusters. Our KNN algorithm uses lightweight monitoring of essential system and application metrics in order to decide how many databases it should allocate to a given workload. Our pro-active algorithm also incorporates awareness of system stabilization periods after adaptation in order to improve prediction accuracy and avoid system oscillations. We compare this pro-active self-configuring scheme for scaling the database tier with a reactive scheme. Our experiments using the industry-standard TPC-W e-commerce benchmark demonstrate that the pro-active scheme is effective in reducing both the frequency and peak level of SLA violations compared to the reactive scheme. Furthermore, by augmenting the pro-active approach with awareness and tracking of system stabilization periods induced by adaptation in our replicated system, we effectively avoid oscillations in resource allocation.
Mining biomedical images with density-based clustering

Density-based clustering algorithms have recently gained popularity in the data mining field due to their ability to discover arbitrary shaped clusters while preserving spatial proximity of data points. In this work we adapt a density-based clustering algorithm, DBSCAN, to a new problem domain: identification of homogenous color regions in biomedical images. Examples of specific problems of this nature include landscape segmentation of satellite imagery, object detection and, in our case, identification of significant color regions in images of skin lesions (tumors). Automated outer and inner boundary segmentation is a key step in segmentation of structures such as skin lesions, tumors of breast, bone, and brain. This step is important because the accuracy of the subsequent steps (extraction of various features, post-processing) crucially depends on the accuracy of this very first step. In this paper, we present an unsupervised approach to segmentation of pigmented skin lesion images based on DBSCAN clustering algorithm. The color regions identified by the algorithm are compared to those identified by the human subjects and the Kappa coefficient, a statistical indicator of computer-human agreement, is found to be significant.
A Role for Centrin 3 in Centrosome Reproduction

Centrosome reproduction by duplication is essential for the bipolarity of cell division, but the molecular basis of this process is still unknown. Mutations in Saccharomyces cerevisiae CDC31 gene prevent the duplication of the spindle pole body (SPB). The product of this gene belongs to the calmodulin super-family and is concentrated at the half bridge of the SPB. We present a functional analysis of HsCEN3, a human centrin gene closely related to the CDC31 gene. Tran- sient overexpression of wild-type or mutant forms of HsCen3p in human cells demonstrates that centriole localization depends on a functional fourth EF-hand, but does not produce mitotic phenotype. However, injection of recombinant HsCen3p or of RNA encoding HsCen3p in one blastomere of two-cell stage Xenopus laevis embryos resulted in undercleavage and inhibition of centrosome duplication. Furthermore, HsCEN3 does not complement mutations or deletion of CDC31 in S. cerevisiae, but specifically blocks SPB duplication, indicating that the human protein acts as a dominant negative mutant of CDC31. Several lines of evidence indicate that HsCen3p acts by titrating Cdc31p-binding protein(s). Our results demonstrate that, in spite of the large differences in centrosome structure among widely divergent species, the centrosome pathway of reproduction is conserved.
Combining link-based and content-based methods for web document classification

This paper studies how link information can be used to improve classification results for Web collections. We evaluate four different measures of subject similarity, derived from the Web link structure, and determine how accurate they are in predicting document categories. Using a Bayesian network model, we combine these measures with the results obtained by traditional content-based classifiers. Experiments on a Web directory show that best results are achieved when links from pages outside the directory are considered. Link information alone is able to obtain gains of up to 46 points in F1, when compared to a traditional content-based classifier. The combination with content-based methods can further improve the results, but too much noise may be introduced, since the text of Web pages is a much less reliable source of information. This work provides an important insight on which measures derived from links are more appropriate to compare Web documents and how these measures can be combined with content-based algorithms to improve the effectiveness of Web classification.
White Noise Analysis of Coupled Linear-Nonlinear Systems

We present an asymptotic analysis of two coupled linear-nonlinear systems. Through measuring first and second input-output statistics of the systems in response to white noise input, one can completely characterize the systems and their coupling. The proposed model is similar to a widely used phenomenological model of neurons in response to sensory stimulation and may be used to help characterize neural circuitry in sensory brain regions.
Comparison of Enzyme Immunoassay and Immunohistochemical Measurements of Estrogen and Progesterone Receptors in Breast Cancer Patients

Before replacing enzyme immunoassay of estrogen and progesterone receptors by immunohistochemistry, results of both methods were compared on 437 samples obtained from breast cancer patients (342 primary breast carcinomas, 16 local recurrences, 49 biopsies, and 30 tumor specimens obtained after neoadjuvant treatment). Immunohistochemistry (IHC) results were first assessed semiquantitatively on the basis of the estimated proportion of positive tumor cells, and then quantitatively using the “quick score. ” Semiquantitative IHC hormone receptors results (positive ≥10%) correlated well with enzyme immunoassay status (positive >15 fmol/mg protein) in 358 surgical samples (342 primary tumors and 16 recurrences), with overall concordance rates of 89.9% and 82.1%, respectively. Among the 100 discordant cases, a large intraductal carcinoma component was observed in 7 of 36 cases for estrogen receptor (ER) and 15 of 64 for progesterone receptor (PR). Thirty-five discordant cases also were observed near the cut-off values. Hormone receptor levels by enzyme immunoassay correlated strongly with the quantitative IHC “quick score. ” Whatever the method, hormone receptor status was associated with histologic grade (SBR) and tumor size, whereas age correlated strongly with ER positivity. Similar results were obtained for biopsy specimens and posttreatment samples. This comparison improved the reliability of the IHC technique, which is currently routinely used for ER and PR determination in the authors' institution.
CTCF facilitates DNA double-strand break repair by enhancing homologous recombination repair

A new role for the multifunctional protein CTCF in the repair of DNA double-strand breaks is discovered. The repair of DNA double-strand breaks (DSBs) is mediated via two major pathways, nonhomologous end joining (NHEJ) and homologous recombination (HR) repair. DSB repair is vital for cell survival, genome stability, and tumor suppression. In contrast to NHEJ, HR relies on extensive homology and templated DNA synthesis to restore the sequence surrounding the break site. We report a new role for the multifunctional protein CCCTC-binding factor (CTCF) in facilitating HR-mediated DSB repair. CTCF is recruited to DSB through its zinc finger domain independently of poly(ADP-ribose) polymers, known as PARylation, catalyzed by poly(ADP-ribose) polymerase 1 (PARP-1). CTCF ensures proper DSB repair kinetics in response to γ-irradiation, and the loss of CTCF compromises HR-mediated repair. Consistent with its role in HR, loss of CTCF results in hypersensitivity to DNA damage, inducing agents and inhibitors of PARP. Mechanistically, CTCF acts downstream of BRCA1 in the HR pathway and associates with BRCA2 in a PARylation-dependent manner, enhancing BRCA2 recruitment to DSB. In contrast, CTCF does not influence the recruitment of the NHEJ protein 53BP1 or LIGIV to DSB. Together, our findings establish for the first time that CTCF is an important regulator of the HR pathway.