Inhibitory Signals Mediated by Programmed Death-1 Are Involved With T-Cell Function in Chronic Periodontitis

Background: Inhibitory signals mediated via molecules such as programmed death-1 (PD-1) play a critical role in downmodulating immune responses and maintaining peripheral tolerance. We investigated the involvement of cytokines and PD-1 engagement in mediating the T-cell unresponsiveness to bacterial and ubiquitous antigens in periodontal diseases. Methods: Gingival and peripheral blood samples from healthy individuals and patients with chronic periodontitis were collected and used for the subsequent assays. Leukocytes in the lesion site and blood were evaluated using flow cytometry. The production of interferon-gamma, interleukin-10, and transforming growth factor-P proteins was evaluated by enzyme-linked immunosorbent assay (ELISA), and the presence of PD-1+cells in the inflamed gingiva was confirmed by immunofluorescence confocal microscopy for CD4 and PD-1 colocalization. Results: T cells from patients with chronic periodontitis proliferated poorly in response to Aggregatibacter actinomycetem comitans (previously Actinobacillus actinomycetemcomitans) antigen. T-cell unresponsiveness was not associated with imbalanced cytokine production. However, T cells from patients with chronic periodontitis expressed significantly higher levels of PD-1 either upon isolation or after culture with antigens. Moreover, PD-1 blocking did not result in significant T-cell proliferation in cells cultured with phytohemagglutinin or bacterial antigens. The blockade of PD-1 resulted in the increased production of IFN-gamma. In addition, CD4+ and CD8+ T cells expressing PD-1 accumulated in lesions with chronic periodontitis. Conclusion: These data show that PD-1 engagement could be involved in the modulation of IFN-gamma production by T cells in patients with chronic periodontitis. J Periodontol 2009,80:1833-1844.

Multiple Pathways Analysis of Brain Functional Networks from EEG Signals: An Application to Real Data

In the present study, we propose a theoretical graph procedure to investigate multiple pathways in brain functional networks. By taking into account all the possible paths consisting of h links between the nodes pairs of the network, we measured the global network redundancy R (h) as the number of parallel paths and the global network permeability P (h) as the probability to get connected. We used this procedure to investigate the structural and dynamical changes in the cortical networks estimated from a dataset of high-resolution EEG signals in a group of spinal cord injured (SCI) patients during the attempt of foot movement. In the light of a statistical contrast with a healthy population, the permeability index P (h) of the SCI networks increased significantly (P < 0.01) in the Theta frequency band (3-6 Hz) for distances h ranging from 2 to 4. On the contrary, no significant differences were found between the two populations for the redundancy index R (h) . The most significant changes in the brain functional network of SCI patients occurred mainly in the lower spectral contents. These changes were related to an improved propagation of communication between the closest cortical areas rather than to a different level of redundancy. This evidence strengthens the hypothesis of the need for a higher functional interaction among the closest ROIs as a mechanism to compensate the lack of feedback from the peripheral nerves to the sensomotor areas.

The Arabidopsis bZIP Gene AtbZIP63 Is a Sensitive Integrator of Transient Abscisic Acid and Glucose Signals

Glucose modulates plant metabolism, growth, and development. In Arabidopsis (Arabidopsis thaliana), Hexokinase1 (HXK1) is a glucose sensor that may trigger abscisic acid (ABA) synthesis and sensitivity to mediate glucose-induced inhibition of seedling development. Here, we show that the intensity of short-term responses to glucose can vary with ABA activity. We report that the transient (2 h/4 h) repression by 2% glucose of AtbZIP63, a gene encoding a basic-leucine zipper (bZIP) transcription factor partially involved in the Snf1-related kinase KIN10-induced responses to energy limitation, is independent of HXK1 and is not mediated by changes in ABA levels. However, high-concentration (6%) glucose-mediated repression appears to be modulated by ABA, since full repression of AtbZIP63 requires a functional ABA biosynthetic pathway. Furthermore, the combination of glucose and ABA was able to trigger a synergistic repression of AtbZIP63 and its homologue AtbZIP3, revealing a shared regulatory feature consisting of the modulation of glucose sensitivity by ABA. The synergistic regulation of AtbZIP63 was not reproduced by an AtbZIP63 promoter-5`-untranslated region:beta-glucuronidase fusion, thus suggesting possible posttranscriptional control. A transcriptional inhibition assay with cordycepin provided further evidence for the regulation of mRNA decay in response to glucose plus ABA. Overall, these results indicate that AtbZIP63 is an important node of the glucose-ABA interaction network. The mechanisms by which AtbZIP63 may participate in the fine-tuning of ABA-mediated abiotic stress responses according to sugar availability (i.e., energy status) are discussed.

Mitochondrial ATP-sensitive K(+) channels as redox signals to liver mitochondria in response to hypertriglyceridemia

We have recently demonstrated that hypertriglyceridemic (HTG) mice present both elevated body metabolic rates and mild mitochondrial uncoupling in the liver owing to stimulated activity of the ATP-sensitive potassium channel (mitoK(ATP)). Because lipid excess normally leads to cell redox imbalance, we examined the hepatic oxidative status in this model. Cell redox imbalance was evidenced by increased total levels of carbonylated proteins, malondialdehydes, and GSSG/GSH ratios in HTG livers compared to wild type. In addition, the activities of the extramitochondrial enzymes NADPH oxidase and xanthine oxidase were elevated in HTG livers. In contrast, Mn-superoxide dismutase activity and content, a mitochondrial matrix marker, were significantly decreased in HTG livers. isolated HTG liver mitochondria presented lower rates of H(2)O(2) production, which were reversed by mitoK(ATP) antagonists. In vivo antioxidant treatment with N-acetylcysteine decreased both mitoKATP activity and metabolic rates in HTG mice. These data indicate that high levels of triglycerides increase reactive oxygen generation by extramitochondrial enzymes that promote MitoK(ATP) activation. The mild uncoupling mediated by mitoK(ATP) increases metabolic rates and protects mitochondria against oxidative damage. Therefore, a biological role for mitoK(ATP) is a redox sensor is shown here for the first time in an in vivo model of systemic and cellular lipid excess, (C) 2009 Elsevier Inc. All rights reserved.

Metabotropic glutamate receptors transduce signals for neurite outgrowth after binding of the prion protein to laminin gamma 1 chain

The prion protein (PrP(C)) is highly expressed in the nervous system, and its abnormal conformer is associated with prion diseases. PrP(C) is anchored to cell membranes by glycosylphosphatidylinositol, and transmembrane proteins are likely required for PrP(C)-mediated intracellular signaling. Binding of laminin (Ln) to PrP(C) modulates neuronal plasticity and memory. We addressed signaling pathways triggered by PrP(C)-Ln interaction in order to identify transmembrane proteins involved in the transduction of PrP(C)-Ln signals. The Ln gamma 1-chain peptide, which contains the Ln binding site for PrP(C), induced neuritogenesis through activation of phospholipase C (PLC), Ca(2+) mobilization from intracellular stores, and protein kinase C and extracellular signal-regulated kinase (ERK1/2) activation in primary cultures of neurons from wild-type, but not PrP(C)-null mice. Phage display, coimmunoprecipitation, and colocalization experiments showed that group I metabotropic glutamate receptors (mGluR1/5) associate with PrP(C). Expression of either mGluR1 or mGluR5 in HEK293 cells reconstituted the signaling pathways mediated by PrP(C)-Ln gamma 1 peptide interaction. Specific inhibitors of these receptors impaired PrP(C)-Ln gamma 1 peptide-induced signaling and neuritogenesis. These data show that group I mGluRs are involved in the transduction of cellular signals triggered by PrP(C)-Ln, and they support the notion that PrP(C) participates in the assembly of multiprotein complexes with physiological functions on neurons.-Beraldo, F. H., Arantes, C. P., Santos, T. G., Machado, C. F., Roffe, M., Hajj, G. N., Lee, K. S., Magalhaes, A. C., Caetano, F. A., Mancini, G. L., Lopes, M. H., Americo, T. A., Magdesian, M. H., Ferguson, S. S. G., Linden, R., Prado, M. A. M., Martins, V. R. Metabotropic glutamate receptors trans-duce signals for neurite outgrowth after binding of the prion protein to laminin gamma 1 chain. FASEB J. 25, 265-279 (2011). www.fasebj.org

Nonstationary feature extraction techniques for automatic classification of impact acoustic signals

Condition monitoring of wooden railway sleepers applications are generallycarried out by visual inspection and if necessary some impact acoustic examination iscarried out intuitively by skilled personnel. In this work, a pattern recognition solutionhas been proposed to automate the process for the achievement of robust results. Thestudy presents a comparison of several pattern recognition techniques together withvarious nonstationary feature extraction techniques for classification of impactacoustic emissions. Pattern classifiers such as multilayer perceptron, learning cectorquantization and gaussian mixture models, are combined with nonstationary featureextraction techniques such as Short Time Fourier Transform, Continuous WaveletTransform, Discrete Wavelet Transform and Wigner-Ville Distribution. Due to thepresence of several different feature extraction and classification technqies, datafusion has been investigated. Data fusion in the current case has mainly beeninvestigated on two levels, feature level and classifier level respectively. Fusion at thefeature level demonstrated best results with an overall accuracy of 82% whencompared to the human operator.

Filmljudets funktioner i krigsfilm : En audio-visuell analys av Apocalypse Now och Saving Private Ryan

I denna uppsats har filmljudet i krigsfilmerna Apocalypse Now och Saving Private Ryan undersökts. Detta har gjorts för att försöka bidra med ökad förståelse för filmljudets användningsområde och funktioner, främst för filmerna i fråga, men även för krigsfilm rent generellt. Filmljud i denna kontext omfattar allt det ljud som finns i film, men utesluter dock all ickediegetisk musik. Båda filmerna har undersökts genom en audio-visuell analys. En sådan analys görs genom att detaljgranska båda filmernas ljud- och bildinnehåll var för sig, för att slutligen undersöka samma filmsekvens som helhet då ljudet och bilden satts ihop igen. Den audio-visuella analysmetod som nyttjats i uppsatsen är Michel Chions metod, Masking. De 30 minuter film som analyserades placerades sedan i olika filmljudzoner, där respektive filmljudzons ljudinnehåll bland annat visade vilka främsta huvudfunktioner somfilmljudet hade i dessa filmer. Dessa funktioner är till för att bibehålla åskådarens fokus och intresse, att skapa närhet till rollkaraktärerna, samt att tillföra en hög känsla av realism och närvaro. Intentionerna med filmljudet verkade vara att flytta åskådaren in i filmens verklighet, att låta åskådaren bli ett med filmen. Att återspegla denna känsla av realism, närvaro, fokus samt intresse, visade sig också vara de intentioner som funnits redan i de båda filmernas förproduktionsstadier. Detta bevisar att de lyckats åstadkomma det de eftersträvat. Men om filmljudet använts på samma sätt eller innehar samma funktioner i krigsfilm rent genrellt går inte att säga.I have for this bachelor’s thesis examined the movie sound of the classic warfare movies Apocalypse Now and Saving Private Ryan. This is an attempt to contribute to a more profound comprehension of the appliance and importance of movie sound. In this context movie sound implies all kinds of sounds within the movies, accept from non-diegetic music. These two movies have been examined by an audio-visual analysis. It's done by auditing the sound and picture content separately, and then combined to audit the same sequence as a whole. Michel Chion, which is the founder of this analysis, calls this method Masking. The sound in this 30 minute sequence was then divided into different zones, where every zone represented a certain main function. These functions are provided to create a stronger connection to the characters, sustain the viewers interest and bring a sense of realism and presence. It seems though the intention with the movies sound is to bring the viewers to the scene in hand, and let it become their reality. To mirror this sense of realism, presence, focus and interest, proves to be the intention from an early stage of the production. This bachelor’s thesis demonstrates a success in their endeavours. Although it can’t confirm whether the movie sound have been utilized in the same manner or if they posess the same functions to warefare movies in general.

Classification of Parkinson’s Disease using MultiPass Lvq,Logistic Model Tree,K-Star for Audio Data set : Classification of Parkinson Disease using Audio Dataset

Parkinson's disease (PD) is a degenerative illness whose cardinal symptoms include rigidity, tremor, and slowness of movement. In addition to its widely recognized effects PD can have a profound effect on speech and voice.The speech symptoms most commonly demonstrated by patients with PD are reduced vocal loudness, monopitch, disruptions of voice quality, and abnormally fast rate of speech. This cluster of speech symptoms is often termed Hypokinetic Dysarthria.The disease can be difficult to diagnose accurately, especially in its early stages, due to this reason, automatic techniques based on Artificial Intelligence should increase the diagnosing accuracy and to help the doctors make better decisions. The aim of the thesis work is to predict the PD based on the audio files collected from various patients.Audio files are preprocessed in order to attain the features.The preprocessed data contains 23 attributes and 195 instances. On an average there are six voice recordings per person, By using data compression technique such as Discrete Cosine Transform (DCT) number of instances can be minimized, after data compression, attribute selection is done using several WEKA build in methods such as ChiSquared, GainRatio, Infogain after identifying the important attributes, we evaluate attributes one by one by using stepwise regression.Based on the selected attributes we process in WEKA by using cost sensitive classifier with various algorithms like MultiPass LVQ, Logistic Model Tree(LMT), K-Star.The classified results shows on an average 80%.By using this features 95% approximate classification of PD is acheived.This shows that using the audio dataset, PD could be predicted with a higher level of accuracy.

Speech Assessment for the Classification of Hypokinetic Dysthria in Parkinson Disease

The aim of this thesis is to investigate computerized voice assessment methods to classify between the normal and Dysarthric speech signals. In this proposed system, computerized assessment methods equipped with signal processing and artificial intelligence techniques have been introduced. The sentences used for the measurement of inter-stress intervals (ISI) were read by each subject. These sentences were computed for comparisons between normal and impaired voice. Band pass filter has been used for the preprocessing of speech samples. Speech segmentation is performed using signal energy and spectral centroid to separate voiced and unvoiced areas in speech signal. Acoustic features are extracted from the LPC model and speech segments from each audio signal to find the anomalies. The speech features which have been assessed for classification are Energy Entropy, Zero crossing rate (ZCR), Spectral-Centroid, Mean Fundamental-Frequency (Meanf0), Jitter (RAP), Jitter (PPQ), and Shimmer (APQ). Naïve Bayes (NB) has been used for speech classification. For speech test-1 and test-2, 72% and 80% accuracies of classification between healthy and impaired speech samples have been achieved respectively using the NB. For speech test-3, 64% correct classification is achieved using the NB. The results direct the possibility of speech impairment classification in PD patients based on the clinical rating scale.

Filmljudets funktioner i dramafilm : En audio-visuell analys av filmen The King's Speech

Johansson, Fredrik (2012). Filmljudets funktioner i dramafilm – En audio-visuell analys av filmen The King´s Speech. Examensuppsats inom Ljudproduktion, Högskolan Dalarna, Akademin för språk och medier, Falun. I denna uppsats undersöktes filmljudet i dramafilmen The King´s Speech. Detta för att ta reda på vilka funktioner filmljudet fyller i de valda sekvenserna ur nämnda film, samt hur ljudet är placerat i filmens flerkanalsmix. Filmen granskades med hjälp av en audio-visuell analys. Denna metod går ut på att ljudet och bilden undersöks separat, för att sedan åter kombineras och analyseras som helhet. Den audio-visuella analysmetod som använts kommer från ljudteoretikern Michel Chion, och kallas Masking. Resultatet av den audio-visuella analysen pekade mot att ljudets huvudsakliga funktioner var att skapa en realistisk skildring av karaktärer och omgivningar, skapa en känsla av närvaro, samt att skapa och bibehålla olika perspektiv i den narrativa världen. Den stora majoriteten av ljud visade sig vara placerade i centerkanalen, medan främst ickediegetisk musik och ambiensljud var placerade i front- och surroundkanalerna. Detta kanalanvändande tycktes gynna de funna funktionerna, främst genom att bidra till känslan av närvaro och realism, genom att omsluta filmpubliken med ambienta ljud.

Game Audio in Audio Games : Towards a Theory on the Roles and Functions of Sound in Audio Games

For the past few decades, researchers have increased our understanding of how sound functions within various audio–visual media formats. With a different focus in mind, this study aims to identify the roles and functions of sound in relation to the game form Audio Games, in order to explore the potential of sound when acting as an autonomous narrative form. Because this is still a relatively unexplored research field, the main purpose of this study is to help establish a theoretical ground and stimulate further research within the field of audio games. By adopting an interdisciplinary approach to the topic, this research relies on theoretical studies, examinations of audio games and contact with the audio game community. In order to reveal the roles of sound, the gathered data is analyzed according to both a contextual and a functional perspective. The research shows that a distinction between the terms ‘function’ and ‘role’ is important when analyzing sound in digital games. The analysis therefore results in the identification of two analytical levels that help define the functions and roles of an entity within a social context, named the Functional and the Interfunctional levels. In addition to successfully identifying three main roles of sound within audio games—each describing the relationship between sound and the entities game system, player and virtual environment—many other issues are also addressed. Consequently, and in accordance with its purpose, this study provides a broad foundation for further research of sound in both audio games and video games.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.