Miracle-dz/UniFAR-FTUs huggingface dataset:
A Portable Device for Experimental Treatment of Neurogenic Detrusor Overactivity

The objective of this study was to evaluate the effect of automatic event‐driven electrical stimulation on the dorsal penile/clitoral nerve for management of neurogenic detrusor overactivity in spinal cord injured subjects. In order to reach the objectives it was necessary to design and realize a portable device for ambulatory urodynamic studies which was able to activate an electrical stimulator when the detrusor pressure exceeded a certain threshold. The developed device was repeatedly tested in a healthy subject and subsequently tested in a spinal cord injured subject. In testing the automatic event‐driven system in the spinal cord injured subject, detrusor contractions were successfully inhibited until a certain bladder volume was reached and no incontinence episodes were observed prior to disabling the system. The preliminary results indicate that automatic event‐driven electrical stimulation on the dorsal penile/clitoral nerve can inhibit involuntary detrusor contractions in spinal cord injured subjects and hereby restore continence and increase bladder capacity.
Integrated traffic control for mixed urban and freeway networks: A model predictive control approach

We develop a control method for networks containing both urban roads and freeways. These two road types are closely connected: congestion on the freeway often causes spill-back leading to urban queues, slowing down the urban traffic, and vice versa. As a consequence, control measures taken in one of the two areas can have a significant influence on the other area. We first develop a model that describes the evolution of the traffic flows in mixed networks. Next, we propose the control method that is used for the integrated control. This approach is based on model predictive control, in which the optimal control inputs are determined on-line using numerical optimisation and a prediction model in combination with a receding horizon approach. We also compare our newly developed control method with systems that are similar to existing dynamic traffic control systems like SCOOT and UTOPIA/SPOT, in a qualitative as well as in a quantitative way via a simple case study. The results illustrate the potential benefits of the proposed approach and motivate further development and improvement of the proposed control method.
Association of TLR5 Gene Polymorphisms in Ulcerative Colitis Patients of North India and Their Role in Cytokine Homeostasis

Background and Aim In health, TLR signaling protects the intestinal epithelial barrier and in disease, aberrant TLR signaling stimulates diverse inflammatory responses. Association of TLR polymorphisms is ethnicity dependent but how they impact the complex pathogenesis of IBD is not clearly defined. So we propose to study the status of polymorphisms in TLR family of genes and their effect on cytokines level in UC patients. Methods The genotypes of the six loci TLR1-R80T, TLR2-R753Q, TLR3-S258G, TLR5-R392X, TLR5-N592S and TLR6-S249P were determined in 350 controls and 328 UC patients by PCR-RFLP and sequencing. Cytokine levels were measured by ELISA in blood plasma samples. Data were analyzed statistically by SPSS software. Results TLR5 variants R392X and N592S showed significant association (p = 0.007, 0.021) with UC patients but TLR 1, 2, 3, 6 variants did not show any association. Unlike other studies carried out in different ethnic groups, TLR 6 (S249P) SNP was universally present in our population irrespective of disease. Genotype-phenotype correlation analysis revealed that the patients having combination of multiple SNPs both in TLR5 and TLR4 gene suffered from severe disease condition and diagnosed at an early age. The level of TNFα (p = 0.004), IL-6 (p = 0.0001) and IFNγ (p = 0.006) significantly increased in patients as compared to controls having wild genotypes for the studied SNPs. However, there was decreased level of TNFα (p = 0.014), IL-6 (p = 0.028) and IFNγ (p = 0.001) in patients carrying TLR5-R392X variant as compared to wild type patients. Patients carrying two simultaneous SNPs D299G in TLR4 gene and N592S in TLR5 gene showed significant decrease in the levels of TNFα (p = 0.011) and IFNγ (p = 0.016). Conclusion Polymorphisms in TLR 5 genes were significantly associated with the UC in North Indian population. The cytokine level was significantly modulated in patients with different genotypes of TLR4 and TLR5 SNPs.
The Signaling Petri Net-Based Simulator: A Non-Parametric Strategy for Characterizing the Dynamics of Cell-Specific Signaling Networks

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods. Several researchers have observed that the connectivity of a network alone can provide significant insights into its dynamics. Motivated by this fundamental observation, we present the signaling Petri net, a non-parametric model of cellular signaling networks, and the signaling Petri net-based simulator, a Petri net execution strategy for characterizing the dynamics of signal flow through a signaling network using token distribution and sampling. The result is a very fast method, which can analyze large-scale networks, and provide insights into the trends of molecules' activity-levels in response to an external stimulus, based solely on the network's connectivity. We have implemented the signaling Petri net-based simulator in the PathwayOracle toolkit, which is publicly available at http://bioinfo.cs. rice.edu/pathwayoracle. Using this method, we studied a MAPK1,2 and AKT signaling network downstream from EGFR in two breast tumor cell lines. We analyzed, both experimentally and computationally, the activity level of several molecules in response to a targeted manipulation of TSC2 and mTOR-Raptor. The results from our method agreed with experimental results in greater than 90% of the cases considered, and in those where they did not agree, our approach provided valuable insights into discrepancies between known network connectivities and experimental observations.
When Are Class I Metabotropic Glutamate Receptors Necessary for Long-Term Potentiation?

The involvement of metabotropic glutamate receptors (mGluRs) in hippocampal long-term potentiation (LTP) is a matter of controversial debate. Using [Ca2+]imeasurements by confocal laser scanning microscopy and field recordings of EPSPs (fEPSPs) in the hippocampal CA1-region, we found that the efficacy of the broad-spectrum mGluR-antagonist (S)-α-methyl-4-carboxyphenylglycine (MCPG) and of (S)-4-carboxy-phenylglycine (4-CPG), a selective antagonist at class I mGluRs, in LTP is contingent on the tetanization strength and the resulting [Ca2+]iresponse. As indicated by experiments in which we blocked voltage-dependent calcium channels (VDCCs) and intracellular Ca2+ stores (ICSs), the functional significance of class I mGluRs in LTP is confined to certain types of potentiation, which are induced by weak tetanization protocols and require the release of Ca2+ from ICSs for induction. During strong tetanic stimulation, this Ca2+ source is functionally bypassed by activating VDCCs.
Targeting Signaling Pathways in Epithelial Ovarian Cancer

Ovarian carcinoma (OC) is the most lethal gynecological malignancy. Response to platinum-based chemotherapy is poor in some patients and, thus, current research is focusing on new therapy options. The various histological types of OC are characterized by distinctive molecular genetic alterations that are relevant for ovarian tumorigenesis. The understanding of these molecular pathways is essential for the development of novel therapeutic strategies. Purpose We want to give an overview on the molecular genetic changes of the histopathological types of OC and their role as putative therapeutic targets. In Depth Review of Existing Data In 2012, the vascular endothelial growth factor (VEGF) inhibitor, bevacizumab, was approved for OC treatment. Bevacizumab has shown promising results as single agent and in combination with conventional chemotherapy, but its target is not distinctive when analyzed before treatment. At present, mammalian target of rapamycin (mTOR) inhibitors, poly-ADP-ribose polymerase (PARP) inhibitors and components of the EGFR pathway are in the focus of clinical research. Interestingly, some phytochemical substances show good synergistic effects when used in combination with chemotherapy. Conclusion Ongoing studies of targeted agents in conjunction with chemotherapy will show whether there are alternative options to bevacizumab available for OC patients. Novel targets which can be assessed before therapy to predict efficacy are needed. The assessment of therapeutic targets is continuously improved by molecular pathological analyses on tumor tissue. A careful selection of patients for personalized treatment will help to reduce putative side effects and toxicity.
Targeting Estrogen Receptor-β for the Prevention of Nonmelanoma Skin Cancer

The potential for targeting estrogen receptor (ER)-β in various cancer models has been gaining considerable attention in recent years. In this issue of the journal, Chaudhary and colleagues demonstrate markedly decreased ultraviolet B (UVB)-induced skin cancer in a mouse model using a highly specific ER-β agonist, ERB-041. The mechanisms that underlie this strong inhibitory effect are mediated by inhibition of proinflammatory signaling and epithelial–mesenchymal transition (EMT). The changes in EMT were due in part to modulation of WNT/β-catenin signaling. Collectively, the results from these studies provide important new insights into the mechanisms by which the ER-β agonist ERB-041 inhibits UVB-induced skin cancer and opens the door for future studies that could examine combinatorial approaches for UVB-dependent skin cancer chemoprevention. Cancer Prev Res; 7(2); 182–5. ©2014 AACR.
5-10 GeV neutrinos from gamma-Ray burst fireballs

A gamma-ray burst fireball is likely to contain an admixture of neutrons. Inelastic collisions between differentially streaming protons and neutrons in the fireball produce nu(&mgr;) (nu;(&mgr;)) of approximately 10 GeV as well as nu(e) (nu;(e)) of approximately 5 GeV, which could produce approximately 7 events/year in km(3) detectors, if the neutron abundance is comparable to that of protons. Photons of approximately 10 GeV from pi(0) decay and approximately 100 MeV nu;(e) from neutron decay are also produced, but will be difficult to detect. Photons with energies less, similar1 MeV from shocks following neutron decay produce a characteristic signal which may be distinguishable from the proton-related MeV photons.
Effects of PKC activation on the meiotic maturation, fertilization and early embryonic development of mouse oocytes

Protein kinase C (PKC) is a family of Ser/Thr protein kinase widely distributed in eukaryotes. There is evidence that PKC plays key roles in the meiotic maturation and activation of mammalian oocytes. However, the mechanism of PKC's actions and the PKC isoforms responsible for these actions are poorly understood. In this study, we reveal in mouse eggs and early embryos: (1) the effects of PKC on the meiotic and mitotic cell cycle progression during oocyte maturation, egg activation and embryonic cleavages; (2) the functional importance of classical PKC subclasses in these processes; and (3) the subcellular localization of the PKCα isoform during development from GV stage oocytes to the blastocyst stage embryos. The results indicate that the PKC activator phorbol 12-myristate 13-acetate (PMA) inhibits the meiotic resumption of cumulus-free mouse oocytes by a mechanism dependent not only on classical PKC activity but also on other PKC isoforms. PKC activation after germinal vesicle breakdown leads to the inhibition of mitogen-activated protein kinase phosphorylation and the arrest of cell cycle at MI stage. The second polar body emission and the cleavages of early embryos are blocked after prolonged PKC activation. The subcellular localization of PKCα isoform in mouse oocytes and embryos is developmental-stage associated. All these results suggest that PKC has multiple functional roles in the cell cycle progression of mouse oocytes and embryos.
Rethinking Race/Ethnicity, Income, and Childhood Asthma: Racial/Ethnic Disparities Concentrated among the Very Poor

Objective. Past studies of the prevalence of childhood asthma have yielded conflicting findings as to whether racial/ethnic disparities remain after other factors, such as income, are taken into account. The objective of this study was to examine the association of race/ethnicity and family income with the prevalence of childhood asthma and to assess whether racial/ethnic disparities vary by income strata. Methods. Cross-sectional data on 14,244 children aged <18 years old in the 1997 National Health Interview Survey were examined. The authors used logistic regression to analyze the independent and joint effects of race/ethnicity and income-to-federal poverty level (FPL) ratio, adjusting for demographic covariates. The main outcome measure was parental report of the child having ever been diagnosed with asthma. Results. Bivariate analyses, based on weighted percentages, revealed that asthma was more prevalent among non-Hispanic black children (13.6%) than among non-Hispanic white children (11.2%; p<0.01), but the prevalence of asthma did not differ significantly between Hispanic children (10.1 %) and non-Hispanic white children (11.2%; p=0.13). Overall, non-Hispanic black children were at higher risk for asthma than non-Hispanic white children (adjusted odds ratio [OR] = 1.20; 95% confidence interval [CI] 1.03, 1.40), after adjustment for sociodemographic variables, including the ratio of annual family income to the FPL. Asthma prevalence did not differ between Hispanic children and non-Hispanic white children in adjusted analyses (adjusted OR=0.85; 95% CI 0.71, 1.02). Analyses stratified by income revealed that only among children from families with incomes less than half the FPL did non-Hispanic black children have a higher risk of asthma than non-Hispanic white children (adjusted OR=1.99; 95% CI 1.09, 3.64). No black vs. white differences existed at other income levels. Subsequent analyses of these very poor children that took into account additional potentially explanatory variables did not attenuate the higher asthma risk for very poor non-Hispanic black children relative to very poor non-Hispanic white children. Conclusions. Non-Hispanic black children were at substantially higher risk of asthma than non-Hispanic white children only among the very poor. The concentration of racial/ethnic differences only among the very poor suggests that patterns of social and environmental exposures must overshadow any hypothetical genetic risk.
Is sperm motility maturation affected by static magnetic fields?

Kinematic parameters were evaluated in mouse epididymal extracts to monitor maturation of sperm movement in animals exposed to static magnetic fields using the Sperm-Class Analyzer computerized image analysis system. For this purpose, animals were exposed to a field of 0.7 T generated by a permanent magnet over 10 or 35 days for either 1 or 24 hr/day. The values of the motion endpoints were similar in animals used as controls and in those exposed to the nonionizing radiation, whatever the period of exposure or daily dosage. Changes in motility were observed in all groups: the percentage of total motile and progressive motile spermatozoa increased during passage through the epididymis, with major changes between the caput and corpus epididymides, and the pattern of swimming changed clearly towards more rapid and straighter trajectories. The processes of initiation of sperm motility and maturation of displacement patterns were not then affected by magnetic treatment. Moreover, it appears that sperm production is unaffected because no changes were observed in testicular or epididymal weights after exposure to static magnetic fields. ImagesFigure 1.Figure 2.Figure 3.
A convex optimization approach to fixed-order controller design for disturbance rejection in SISO systems

The problem of rejection of persistent unknown-but-bounded disturbances can be solved using the well-known l/sup 1/ design approach. However, in spite of its success, this theory suffers from the fact that the resulting controller may have arbitrarily high order, even in the state-feedback case. In addition, system performance is optimized under the assumption of zero initial conditions. In this paper we propose a new approach to the problem of synthesizing fixed order controllers to optimally reject persistent disturbances. The main result of the paper shows that this approach leads to a finite-dimensional convex optimization problem that can be efficiently solved.
UMass at TDT 2004

Topic Detection classifies stories into different topics, but HTD requires more than that. Is there any other entities between a story and a topic? [10] views a topic as a structure of inter-related events, which gives us a good hint for this new task. Experiments in [10] show that time locality is a very useful attribute in event organization, and it can also help to solve the complexity problem in TDT2004. The TDT-5 collection contains 407,503 stories in three different languages, and the running time for traditional clustering algorithms, which take ✂☎✄✝✆✟✞✡✠ , is not acceptable for such a huge collection. Since we know that stories in the same event tend to be close in time, we only need to compare a story to its “local” stories instead of the whole collection. The algorithm we use has two steps, bounded 1-NN for event formation and bounded agglomerative clustering for building the hierarchy. In the first step, all stories in the same original language and from the same source are taken out and time ordered. Stories are processed one by one and each incoming story is compared to a certain number of stories before it. This number is approximately the number of stories in a token file and the value is 100 for the baseline run. If the similarity (cosine similarity of tf-idf term vectors) of the current story and the most similar previous story is larger than a given threshold (0.3 in the baseline run), the current story will be assigned to the event that the most similar previous
Predicting tongue shapes from a few landmark locations

We present a method for predicting the midsagittal tongue contour from the locations of a few landmarks (metal pellets) on the tongue surface, as used in articulatory databases such as MOCHA and the Wisconsin XRDB. Our method learns a mapping using ground-truth tongue contours derived from ultrasound data and drastically improves over spline interpolation. We also determine the optimal locations of the landmarks, and the number of landmarks required to achieve a desired prediction error: 3-4 landmarks are enough to achieve 0.3-0.2 mm error per point on the tongue.
Inferring causality in networks of WSS processes by pairwise estimation methods

Inferring causal dependences in a family of dynamic systems from a finite set of observations is a problem encountered in many applications that arise in a diverse variety of fields; ranging from economics and finance to climatology and neuroscience. Given a set of random processes, the objective is to determine whether one process is influenced by the others and to investigate the nature of this influence in case a dependence relation is identified. The notion of Granger-causality may be used in this context to measure and quantify causal structures. Ideally, in order to infer the complete interdependence structure of a complex system, one should simultaneously consider the dynamic behaviour of all the processes involved. However, for large networks, such a method becomes exceedingly complicated. In this paper, we consider an interdependent group of jointly wide sense stationary real-valued stochastic processes and investigate the problem of determining Granger-causality by identifying pairwise causal relations. It is seen that while such methods may not reveal all details of a system, they can nonetheless provide useful and reasonably accurate information.
Short Communication Individual Differences in Nicotine Intake per Cigarette 1

The increase in levels of blood nicotine that occurs from smoking a single cigarette, sometimes referred to as a “nicotine boost,” is an individualized measure of how much nicotine has been extracted from smoking a cigarette. This study investigated the demographic, smoking status, and psychological predictors of nicotine boost in a sample of 190 treatment-seeking smokers. Boost was assessed by comparing plasma nicotine levels before and after participants smoked one of their own brand cigarettes ad libitum. Positive affect (mood) was a significant positive predictor of nicotine boost, controlling for baseline cotinine levels and cigarette brand (Federal Trade Commission) nicotine delivery. However the proportion of variability accounted for in the model was relatively small (5%). Future research on individual differences in nicotine boost is warranted to clarify the role of psychological, physiological, and cigarette-related determinants.
Using Anticipation to Create Believable Behaviour

Although anticipation is an important part of creating believable behaviour, it has had but a secondary role in the field of life-like characters. In this paper, we show how a simple anticipatory mechanism can be used to control the behaviour of a synthetic character implemented as a software agent, without disrupting the user's suspension of disbelief. We describe the emotivector, an anticipatory mechanism coupled with a sensor, that: (1) uses the history of the sensor to anticipate the next sensor state; (2) interprets the mismatch between the prediction and the sensed value, by computing its attention grabbing potential and associating a basic qualitative sensation with the signal; (3) sends its interpretation along with the signal. When a signal from the sensor reaches the processing module of the agent, it carries recommendations such as: "you should seriously take this signal into consideration, as it is much better than we had expected" or "Just forget about this one, it is as bad as we predicted". We delineate several strategies to manage several emotivectors at once and show how one of these strategies (meta-anticipation) transparently introduces the concept of uncertainty. Finally, we describe an experiment in which an emotivector-controlled synthetic character interacts with the user in the context of a word-puzzle game and present the evaluation supporting the adequacy of our approach.