930 resultados para Protein Array Analysis -- methods


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Résumé pour un large public: La vaccination a eu un impact énorme sur la santé mondiale. Mais, quel est le principe d'un vaccin? Il est basé sur la 'mémoire immunologique', qui est une particularité exclusive des systèmes immunitaires des organismes évolués. Suite à une infection par un pathogène, des cellules spécialisées de notre système immunitaire (les lymphocytes) le reconnaissent et initient une réaction immunitaire qui a pour but son élimination. Pendant cette réaction se développent aussi des cellules, appelées cellules lymphocytaires mémoire, qui persistent pour longue durée et qui ont la capacité de stimuler une réaction immunitaire très efficace immédiatement après une seconde exposition à ce même pathogène. Ce sont ces cellules mémoires (lymphocytes B et T) qui sont à la base de la 'mémoire immunologique' et qui sont stimulées lors de la vaccination. Chez l'homme, deux populations distinctes des lymphocytes T mémoires ont été identifiées: les cellules centrales (CM) et effectrices (EM) mémoires. Ces populations sont fonctionnellement hétérogènes et exercent des rôles distincts et essentiels dans l'immunité protectrice. Typiquement, les cellules effectrices mémoires sont capables de tuer immédiatement le pathogène tandis que les cellules centrales mémoires sont responsables d'initier une réponse immunitaire complète. Pourtant, les mécanismes biochimiques qui contrôlent les fonctions de ces cellules ont été jusqu'à présent peu étudiés à cause de la faible fréquence de ces cellules et de la quantité limitée de tissus humains disponibles pour les analyses. La compréhension de ces mécanismes est cruciale pour la réalisation de vaccins efficaces et pour le développement de nouveaux médicaments capables de moduler la réponse immunitaire lymphocytaire. Dans cette thèse, nous avons d'abord développé et amélioré une technologie appelée 'protéine array en phase inverse' qui possède un niveau de sensibilité beaucoup plus élevé par rapport aux technologies classiquement utilisées dans l'étude des protéines. Grâce à cette technique, nous avons pu comparer la composition protéique du système de transmission des signaux d'activation des cellules CM et EM humaines. L'analyse de 8 à 13 sujets sains a montré que ces populations des cellules mémoires possèdent un système de signalisation protéique différent. En effet, les cellules EM possèdent, par rapport aux cellules CM, des niveaux réduits d'une protéine régulatrice (appelée c-Cbl) que nous avons démontré comme étant responsable des fonctions spécifiques de ces cellules. En effet, en augmentant artificiellement l'expression de cette protéine régulatrice dans les cellules EM jusqu'au niveau de celui des cellules CM, nous avons induit dans les cellules EM des capacités fonctionnelles caractéristiques des cellules CM. En conclusion, notre étude a identifié, pour la première fois chez l'homme, un mécanisme biochimique qui contrôle les fonctions des populations des cellules mémoires. Résumé en Français: Les cellules mémoires persistent inertes dans l'organisme et produisent des réactions immunitaires rapides et robustes contre les pathogènes précédemment rencontrés. Deux populations distinctes des cellules mémoires ont été identifiées chez l'homme: les cellules centrales (CM) et effectrices (EM) mémoires. Ces populations sont fonctionnellement hétérogènes et exercent des rôles distincts et critiques dans l'immunité protectrice. Les mécanismes biochimiques qui contrôlent leurs fonctions ont été jusqu'à présent peu étudiés, bien que leur compréhension soit cruciale pour le développement des vaccins et des nouveaux traitements/médicaments. Les limites majeures à ces études sont la faible fréquence de ces populations et la quantité limitée de tissus humains disponibles. Dans cette thèse nous avons d'abord développé et amélioré la technologie de 'protéine array en phase inverse' afin d'analyser les molécules de signalisation des cellules mémoires CD4 et CD8 humaines isolées ex vivo. L'excellente sensibilité, la reproductibilité et la linéarité de la détection, ont permis de quantifier des variations d'expression protéiques supérieures à 20% dans un lysat équivalent à 20 cellules. Ensuite, grâce à l'analyse de 8 à 13 sujets sains, nous avons prouvé que les cellules mémoires CD8 ont une composition homogène de leur système de signalisation tandis que les cellules CD4 EM expriment significativement de plus grandes quantités de SLP-76 et des niveaux réduits de c-Cbl, Syk, Fyn et LAT par rapport aux cellules CM. En outre, l'expression réduite du régulateur négatif c-Cbl est corrélée avec l'expression des SLP-76, PI3K et LAT uniquement dans les cellules EM. L'évaluation des propriétés fonctionnelles des cellules mémoires a permis de démontrer que l'expression réduite du c-Cbl dans les cellules EM est associé à une diminution de leur seuil d'activation. En effet, grâce a la technique de transduction cytosolique, nous avons augmenté la quantité de c-Cbl des cellules EM à un niveau comparable à celui des cellules CM et constaté une réduction de la capacité des cellules EM à proliférer et sécréter des cytokines. Ce mécanisme de régulation dépend principalement de l'activité d'ubiquitine ligase de c-Cbl comme démontré par l'impact réduit du mutant enzymatiquement déficient de c-Cbl sur les fonctions de cellules EM. En conclusion, cette thèse identifie c-Cbl comme un régulateur critique des réponses fonctionnelles des populations de cellules T mémoires et fournit, pour la première fois chez l'homme, un mécanisme contrôlant l'hétérogénéité fonctionnelle des ces cellules. De plus, elle valide l'utilisation combinée des 'RPP arrays' et de la transduction cytosolique comme outil puissant d'analyse quantitative et fonctionnel des protéines de signalisation. Summary : Memory cells persist in a quiescent state in the body and mediate rapid and vigorous immune responses toward pathogens previously encountered. Two subsets of memory cells, namely central (CM) and effector (EM) memory cells, have been identified in humans. These subsets display high functional heterogeneity and assert critical and distinct roles in the control of protective immunity. The biochemical mechanisms controlling their functional properties remain so far poorly investigated, although their clarification is crucial for design of effective T-cell vaccine and drug development. Major limitations to these studies lie in the low frequency of memory T cell subsets and the limited amount of human specimen available. In this thesis we first implemented the innovative reverse phase protein array approach to profile 15 signalling components in human CD8 and CD4 memory T cells isolated ex vivo. The high degree of sensitivity, reproducibility and linearity achieved, allowed an excellent quantification of variations in protein expression higher than 20% in as few as 20-cell equivalent per spot. Based on the analysis of 8 to 13 healthy subjects, we showed that CD8 memory cells have a homogeneous composition of their signaling machinery while CD4 EM cells express statistically significant increased amounts of SLP-76 and reduced levels of c- Cbl, Syk, Fyn and LAT as compared to CM cells. Moreover, in EM but not CM cells, reduced expression of negative regulator c-Cbl correlated with the expression of SLP-76, PI3K and LAT. Subsequently, we demonstrated that the higher functional properties and the lower functional threshold of EM cells is associated with reduced expression of c-Cbl. Indeed, by increasing c-Cbl content of EM cells to the same level of CM cells using cytosolic transduction, we impaired their proliferation and cytokine production. This regulatory mechanism was primarily dependent on c-Cbl E3 ubiquitin ligase activity as evidenced by the weaker impact of enzymatically deficient c-Cbl C381A mutant on EM cell functions. Together, these results identify c-Cbl as a critical regulator of the functional responses of memory T cell subsets and provides, for the first time in humans, a mechanism controlling the functional heterogeneity of memory CD4 cells. Moreover it validates the combined use of RPP arrays and cytosolic transduction approaches as a powerful tool to quantitatively analyze signalling proteins and functionally assess their roles.

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Väitöstutkimuksessa on tarkasteltuinfrapunaspektroskopian ja monimuuttujaisten aineistonkäsittelymenetelmien soveltamista kiteytysprosessin monitoroinnissa ja kidemäisen tuotteen analysoinnissa. Parhaillaan kiteytysprosessitutkimuksessa maailmanlaajuisesti tutkitaan intensiivisesti erilaisten mittausmenetelmien soveltamista kiteytysprosessin ilmiöidenjatkuvaan mittaamiseen niin nestefaasista kuin syntyvistä kiteistäkin. Lisäksi tuotteen karakterisointi on välttämätöntä tuotteen laadun varmistamiseksi. Erityisesti lääkeaineiden valmistuksessa kiinnostusta tämäntyyppiseen tutkimukseen edistää Yhdysvaltain elintarvike- ja lääkeaineviraston (FDA) prosessianalyyttisiintekniikoihin (PAT) liittyvä ohjeistus, jossa määritellään laajasti vaatimukset lääkeaineiden valmistuksessa ja tuotteen karakterisoinnissa tarvittaville mittauksille turvallisten valmistusprosessien takaamiseksi. Jäähdytyskiteytyson erityisesti lääketeollisuudessa paljon käytetty erotusmenetelmä kiinteän raakatuotteen puhdistuksessa. Menetelmässä puhdistettava kiinteä raaka-aine liuotetaan sopivaan liuottimeen suhteellisen korkeassa lämpötilassa. Puhdistettavan aineen liukoisuus käytettävään liuottimeen laskee lämpötilan laskiessa, joten systeemiä jäähdytettäessä liuenneen aineen konsentraatio prosessissa ylittää liukoisuuskonsentraation. Tällaiseen ylikylläiseen systeemiin pyrkii muodostumaan uusia kiteitä tai olemassa olevat kiteet kasvavat. Ylikylläisyys on yksi tärkeimmistä kidetuotteen laatuun vaikuttavista tekijöistä. Jäähdytyskiteytyksessä syntyvän tuotteen ominaisuuksiin voidaan vaikuttaa mm. liuottimen valinnalla, jäähdytyprofiililla ja sekoituksella. Lisäksi kiteytysprosessin käynnistymisvaihe eli ensimmäisten kiteiden muodostumishetki vaikuttaa tuotteen ominaisuuksiin. Kidemäisen tuotteen laatu määritellään kiteiden keskimääräisen koon, koko- ja muotojakaumansekä puhtauden perusteella. Lääketeollisuudessa on usein vaatimuksena, että tuote edustaa tiettyä polymorfimuotoa, mikä tarkoittaa molekyylien kykyä järjestäytyä kidehilassa usealla eri tavalla. Edellä mainitut ominaisuudet vaikuttavat tuotteen jatkokäsiteltävyyteen, kuten mm. suodattuvuuteen, jauhautuvuuteen ja tabletoitavuuteen. Lisäksi polymorfiamuodolla on vaikutusta moniin tuotteen käytettävyysominaisuuksiin, kuten esim. lääkeaineen liukenemisnopeuteen elimistössä. Väitöstyössä on tutkittu sulfatiatsolin jäähdytyskiteytystä käyttäen useita eri liuotinseoksia ja jäähdytysprofiileja sekä tarkasteltu näiden tekijöiden vaikutustatuotteen laatuominaisuuksiin. Infrapunaspektroskopia on laajalti kemian alan tutkimuksissa sovellettava menetelmä. Siinä mitataan tutkittavan näytteenmolekyylien värähtelyjen aiheuttamia spektrimuutoksia IR alueella. Tutkimuksessa prosessinaikaiset mittaukset toteutettiin in-situ reaktoriin sijoitettavalla uppoanturilla käyttäen vaimennettuun kokonaisheijastukseen (ATR) perustuvaa Fourier muunnettua infrapuna (FTIR) spektroskopiaa. Jauhemaiset näytteet mitattiin off-line diffuusioheijastukseen (DRIFT) perustuvalla FTIR spektroskopialla. Monimuuttujamenetelmillä (kemometria) voidaan useita satoja, jopa tuhansia muuttujia käsittävä spektridata jalostaa kvalitatiiviseksi (laadulliseksi) tai kvantitatiiviseksi (määrälliseksi) prosessia kuvaavaksi informaatioksi. Väitöstyössä tarkasteltiin laajasti erilaisten monimuuttujamenetelmien soveltamista mahdollisimman monipuolisen prosessia kuvaavan informaation saamiseksi mitatusta spektriaineistosta. Väitöstyön tuloksena on ehdotettu kalibrointirutiini liuenneen aineen konsentraation ja edelleen ylikylläisyystason mittaamiseksi kiteytysprosessin aikana. Kalibrointirutiinin kehittämiseen kuuluivat aineiston hyvyyden tarkastelumenetelmät, aineiston esikäsittelymenetelmät, varsinainen kalibrointimallinnus sekä mallin validointi. Näin saadaan reaaliaikaista informaatiota kiteytysprosessin ajavasta voimasta, mikä edelleen parantaa kyseisen prosessin tuntemusta ja hallittavuutta. Ylikylläisyystason vaikutuksia syntyvän kidetuotteen laatuun seurattiin usein kiteytyskokein. Työssä on esitetty myös monimuuttujaiseen tilastolliseen prosessinseurantaan perustuva menetelmä, jolla voidaan ennustaa spontaania primääristä ytimenmuodostumishetkeä mitatusta spektriaineistosta sekä mahdollisesti päätellä ydintymisessä syntyvä polymorfimuoto. Ehdotettua menetelmää hyödyntäen voidaan paitsi ennakoida kideytimien muodostumista myös havaita mahdolliset häiriötilanteet kiteytysprosessin alkuhetkillä. Syntyvää polymorfimuotoa ennustamalla voidaan havaita ei-toivotun polymorfin ydintyminen,ja mahdollisesti muuttaa kiteytyksen ohjausta halutun polymorfimuodon saavuttamiseksi. Monimuuttujamenetelmiä sovellettiin myös kiteytyspanosten välisen vaihtelun määrittämiseen mitatusta spektriaineistosta. Tämäntyyppisestä analyysistä saatua informaatiota voidaan hyödyntää kiteytysprosessien suunnittelussa ja optimoinnissa. Väitöstyössä testattiin IR spektroskopian ja erilaisten monimuuttujamenetelmien soveltuvuutta kidetuotteen polymorfikoostumuksen nopeaan määritykseen. Jauhemaisten näytteiden luokittelu eri polymorfeja sisältäviin näytteisiin voitiin tehdä käyttäen tarkoitukseen soveltuvia monimuuttujaisia luokittelumenetelmiä. Tämä tarjoaa nopean menetelmän jauhemaisen näytteen polymorfikoostumuksen karkeaan arviointiin, eli siihen mitä yksittäistä polymorfia kyseinen näyte pääasiassa sisältää. Varsinainen kvantitatiivinen analyysi, eli sen selvittäminen paljonko esim. painoprosentteina näyte sisältää eri polymorfeja, vaatii kaikki polymorfit kattavan fysikaalisen kalibrointisarjan, mikä voi olla puhtaiden polymorfien huonon saatavuuden takia hankalaa.

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Tärkeä tehtävä ympäristön tarkkailussa on arvioida ympäristön nykyinen tila ja ihmisen siihen aiheuttamat muutokset sekä analysoida ja etsiä näiden yhtenäiset suhteet. Ympäristön muuttumista voidaan hallita keräämällä ja analysoimalla tietoa. Tässä diplomityössä on tutkittu vesikasvillisuudessa hai vainuja muutoksia käyttäen etäältä hankittua mittausdataa ja kuvan analysointimenetelmiä. Ympäristön tarkkailuun on käytetty Suomen suurimmasta järvestä Saimaasta vuosina 1996 ja 1999 otettuja ilmakuvia. Ensimmäinen kuva-analyysin vaihe on geometrinen korjaus, jonka tarkoituksena on kohdistaa ja suhteuttaa otetut kuvat samaan koordinaattijärjestelmään. Toinen vaihe on kohdistaa vastaavat paikalliset alueet ja tunnistaa kasvillisuuden muuttuminen. Kasvillisuuden tunnistamiseen on käytetty erilaisia lähestymistapoja sisältäen valvottuja ja valvomattomia tunnistustapoja. Tutkimuksessa käytettiin aitoa, kohinoista mittausdataa, minkä perusteella tehdyt kokeet antoivat hyviä tuloksia tutkimuksen onnistumisesta.

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The objective of this work was to combine the advantages of the dried blood spot (DBS) sampling process with the highly sensitive and selective negative-ion chemical ionization tandem mass spectrometry (NICI-MS-MS) to analyze for recent antidepressants including fluoxetine, norfluoxetine, reboxetine, and paroxetine from micro whole blood samples (i.e., 10 microL). Before analysis, DBS samples were punched out, and antidepressants were simultaneously extracted and derivatized in a single step by use of pentafluoropropionic acid anhydride and 0.02% triethylamine in butyl chloride for 30 min at 60 degrees C under ultrasonication. Derivatives were then separated on a gas chromatograph coupled with a triple-quadrupole mass spectrometer operating in negative selected reaction monitoring mode for a total run time of 5 min. To establish the validity of the method, trueness, precision, and selectivity were determined on the basis of the guidelines of the "Société Française des Sciences et des Techniques Pharmaceutiques" (SFSTP). The assay was found to be linear in the concentration ranges 1 to 500 ng mL(-1) for fluoxetine and norfluoxetine and 20 to 500 ng mL(-1) for reboxetine and paroxetine. Despite the small sampling volume, the limit of detection was estimated at 20 pg mL(-1) for all the analytes. The stability of DBS was also evaluated at -20 degrees C, 4 degrees C, 25 degrees C, and 40 degrees C for up to 30 days. Furthermore, the method was successfully applied to a pharmacokinetic investigation performed on a healthy volunteer after oral administration of a single 40-mg dose of fluoxetine. Thus, this validated DBS method combines an extractive-derivative single step with a fast and sensitive GC-NICI-MS-MS technique. Using microliter blood samples, this procedure offers a patient-friendly tool in many biomedical fields such as checking treatment adherence, therapeutic drug monitoring, toxicological analyses, or pharmacokinetic studies.

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BACKGROUND: Mitogen activated protein kinases (MAPK) play an essential role in integrating extra-cellular signals and intra-cellular cues to allow cells to grow, adapt to stresses, or undergo apoptosis. Budding yeast serves as a powerful system to understand the fundamental regulatory mechanisms that allow these pathways to combine multiple signals and deliver an appropriate response. To fully comprehend the variability and dynamics of these signaling cascades, dynamic and quantitative single cell measurements are required. Microscopy is an ideal technique to obtain these data; however, novel assays have to be developed to measure the activity of these cascades. RESULTS: We have generated fluorescent biosensors that allow the real-time measurement of kinase activity at the single cell level. Here, synthetic MAPK substrates were engineered to undergo nuclear-to-cytoplasmic relocation upon phosphorylation of a nuclear localization sequence. Combination of fluorescence microscopy and automated image analysis allows the quantification of the dynamics of kinase activity in hundreds of single cells. A large heterogeneity in the dynamics of MAPK activity between individual cells was measured. The variability in the mating pathway can be accounted for by differences in cell cycle stage, while, in the cell wall integrity pathway, the response to cell wall stress is independent of cell cycle stage. CONCLUSIONS: These synthetic kinase activity relocation sensors allow the quantification of kinase activity in live single cells. The modularity of the architecture of these reporters will allow their application in many other signaling cascades. These measurements will allow to uncover new dynamic behaviour that previously could not be observed in population level measurements.

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This thesis was focussed on statistical analysis methods and proposes the use of Bayesian inference to extract information contained in experimental data by estimating Ebola model parameters. The model is a system of differential equations expressing the behavior and dynamics of Ebola. Two sets of data (onset and death data) were both used to estimate parameters, which has not been done by previous researchers in (Chowell, 2004). To be able to use both data, a new version of the model has been built. Model parameters have been estimated and then used to calculate the basic reproduction number and to study the disease-free equilibrium. Estimates of the parameters were useful to determine how well the model fits the data and how good estimates were, in terms of the information they provided about the possible relationship between variables. The solution showed that Ebola model fits the observed onset data at 98.95% and the observed death data at 93.6%. Since Bayesian inference can not be performed analytically, the Markov chain Monte Carlo approach has been used to generate samples from the posterior distribution over parameters. Samples have been used to check the accuracy of the model and other characteristics of the target posteriors.

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Recent years have produced great advances in the instrumentation technology. The amount of available data has been increasing due to the simplicity, speed and accuracy of current spectroscopic instruments. Most of these data are, however, meaningless without a proper analysis. This has been one of the reasons for the overgrowing success of multivariate handling of such data. Industrial data is commonly not designed data; in other words, there is no exact experimental design, but rather the data have been collected as a routine procedure during an industrial process. This makes certain demands on the multivariate modeling, as the selection of samples and variables can have an enormous effect. Common approaches in the modeling of industrial data are PCA (principal component analysis) and PLS (projection to latent structures or partial least squares) but there are also other methods that should be considered. The more advanced methods include multi block modeling and nonlinear modeling. In this thesis it is shown that the results of data analysis vary according to the modeling approach used, thus making the selection of the modeling approach dependent on the purpose of the model. If the model is intended to provide accurate predictions, the approach should be different than in the case where the purpose of modeling is mostly to obtain information about the variables and the process. For industrial applicability it is essential that the methods are robust and sufficiently simple to apply. In this way the methods and the results can be compared and an approach selected that is suitable for the intended purpose. Differences in data analysis methods are compared with data from different fields of industry in this thesis. In the first two papers, the multi block method is considered for data originating from the oil and fertilizer industries. The results are compared to those from PLS and priority PLS. The third paper considers applicability of multivariate models to process control for a reactive crystallization process. In the fourth paper, nonlinear modeling is examined with a data set from the oil industry. The response has a nonlinear relation to the descriptor matrix, and the results are compared between linear modeling, polynomial PLS and nonlinear modeling using nonlinear score vectors.

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The papermaking industry has been continuously developing intelligent solutions to characterize the raw materials it uses, to control the manufacturing process in a robust way, and to guarantee the desired quality of the end product. Based on the much improved imaging techniques and image-based analysis methods, it has become possible to look inside the manufacturing pipeline and propose more effective alternatives to human expertise. This study is focused on the development of image analyses methods for the pulping process of papermaking. Pulping starts with wood disintegration and forming the fiber suspension that is subsequently bleached, mixed with additives and chemicals, and finally dried and shipped to the papermaking mills. At each stage of the process it is important to analyze the properties of the raw material to guarantee the product quality. In order to evaluate properties of fibers, the main component of the pulp suspension, a framework for fiber characterization based on microscopic images is proposed in this thesis as the first contribution. The framework allows computation of fiber length and curl index correlating well with the ground truth values. The bubble detection method, the second contribution, was developed in order to estimate the gas volume at the delignification stage of the pulping process based on high-resolution in-line imaging. The gas volume was estimated accurately and the solution enabled just-in-time process termination whereas the accurate estimation of bubble size categories still remained challenging. As the third contribution of the study, optical flow computation was studied and the methods were successfully applied to pulp flow velocity estimation based on double-exposed images. Finally, a framework for classifying dirt particles in dried pulp sheets, including the semisynthetic ground truth generation, feature selection, and performance comparison of the state-of-the-art classification techniques, was proposed as the fourth contribution. The framework was successfully tested on the semisynthetic and real-world pulp sheet images. These four contributions assist in developing an integrated factory-level vision-based process control.

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Tutkielma käyttää automaattista kuviontunnistusalgoritmia ja yleisiä kahden liukuvan keskiarvon leikkauspiste –sääntöjä selittääkseen Stuttgartin pörssissä toimivien yksityissijoittajien myynti-osto –epätasapainoa ja siten vastatakseen kysymykseen ”käyttävätkö yksityissijoittajat teknisen analyysin menetelmiä kaupankäyntipäätöstensä perustana?” Perusolettama sijoittajien käyttäytymisestä ja teknisen analyysin tuottavuudesta tehtyjen tutkimusten perusteella oli, että yksityissijoittajat käyttäisivät teknisen analyysin metodeja. Empiirinen tutkimus, jonka aineistona on DAX30 yhtiöiden data vuosilta 2009 – 2013, ei tuottanut riittävän selkeää vastausta tutkimuskysymykseen. Heikko todistusaineisto näyttää kuitenkin osoittavan, että yksityissijoittajat muuttavat kaupankäyntikäyttäytymistänsä eräiden kuvioiden ja leikkauspistesääntöjen ohjastamaan suuntaan.

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The pipeline for macro- and microarray analyses (PMmA) is a set of scripts with a web interface developed to analyze DNA array data generated by array image quantification software. PMmA is designed for use with single- or double-color array data and to work as a pipeline in five classes (data format, normalization, data analysis, clustering, and array maps). It can also be used as a plugin in the BioArray Software Environment, an open-source database for array analysis, or used in a local version of the web service. All scripts in PMmA were developed in the PERL programming language and statistical analysis functions were implemented in the R statistical language. Consequently, our package is a platform-independent software. Our algorithms can correctly select almost 90% of the differentially expressed genes, showing a superior performance compared to other methods of analysis. The pipeline software has been applied to 1536 expressed sequence tags macroarray public data of sugarcane exposed to cold for 3 to 48 h. PMmA identified thirty cold-responsive genes previously unidentified in this public dataset. Fourteen genes were up-regulated, two had a variable expression and the other fourteen were down-regulated in the treatments. These new findings certainly were a consequence of using a superior statistical analysis approach, since the original study did not take into account the dependence of data variability on the average signal intensity of each gene. The web interface, supplementary information, and the package source code are available, free, to non-commercial users at http://ipe.cbmeg.unicamp.br/pub/PMmA.

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The purpose of this study was to explore cytokine expression patterns and cytogenetic abnormalities of mesenchymal stem cells (MSCs) from the bone marrow microenvironment of Chinese patients with myelodysplastic syndromes (MDS). Bone marrow samples were obtained from 30 cases of MDS (MDS group) and 30 healthy donors (control group). The expression pattern of cytokines was detected by customized protein array. The karyotypes of MSCs were analyzed using fluorescence in situ hybridization. Compared with the control group, leukemia inhibitory factor, stem cell factor (SCF), stromal cell-derived factor (SDF-1), bone morphogenetic protein 4, hematopoietic stem cell (HSC) stimulating factor, and transforming growth factor-β in the MDS group were significantly downregulated (P<0.05), while interferon-γ (IFN-γ), tumor necrosis factor-α (TNF-α), and programmed death ligand (B7-H1) were significantly upregulated (P<0.05). For chromosome abnormality analysis, the detection rate of abnormal karyotypes (+8, -8, -20, 20q-, -Y, -7, 5q-) was 30% in the MDS group and 0% in the control group. In conclusion, the up- and downregulated expression of these cytokines might play a key role in the pathogenesis of MDS. Among them, SCF and SDF-1 may play roles in the apoptosis of HSCs in MDS; and IFN-γ, TNF-α, and B7-H1 may be associated with apoptosis of bone marrow cells in MDS. In addition, the abnormal karyotypes might be actively involved in the pathogenesis of MDS. Further studies are required to determine the role of abnormal karyotypes in the occurrence and development of MDS.

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The aim of this Master’s thesis is to find a method for classifying spare part criticality in the case company. Several approaches exist for criticality classification of spare parts. The practical problem in this thesis is the lack of a generic analysis method for classifying spare parts of proprietary equipment of the case company. In order to find a classification method, a literature review of various analysis methods is required. The requirements of the case company also have to be recognized. This is achieved by consulting professionals in the company. The literature review states that the analytic hierarchy process (AHP) combined with decision tree models is a common method for classifying spare parts in academic literature. Most of the literature discusses spare part criticality in stock holding perspective. This is relevant perspective also for a customer orientated original equipment manufacturer (OEM), as the case company. A decision tree model is developed for classifying spare parts. The decision tree classifies spare parts into five criticality classes according to five criteria. The criteria are: safety risk, availability risk, functional criticality, predictability of failure and probability of failure. The criticality classes describe the level of criticality from non-critical to highly critical. The method is verified for classifying spare parts of a full deposit stripping machine. The classification can be utilized as a generic model for recognizing critical spare parts of other similar equipment, according to which spare part recommendations can be created. Purchase price of an item and equipment criticality were found to have no effect on spare part criticality in this context. Decision tree is recognized as the most suitable method for classifying spare part criticality in the company.

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Conidia of the insect pathogenic fungus, Metarhizium anisopliae play an important role in pathogenicity because they are the infective propagules that adhere to the surface of the insect, then germinate and give rise to hyphal penetration of the insect cuticle. Conidia are produced in the final stages of insect infection as the mycelia emerge from the insect cadaver. The genes associated with conidiation have not yet been studied in this fiingus. hi this study we used the PCR-based technique, suppression subtractive hybridization (SSH) to selectively amplify conidial-associated genes in M. anisopliae. We then identified the presence of these differentially expressed genes using the National Center for Biotechnology Information database. One of the transcripts encoded an extracellular subtilisin-like protease, Prl, which plays a fundamental role in cuticular protein degradation. Analysis of the patterns of gene expression of the transcripts using RT-PCR indicated that conidial-associated cDNAs are expressed during the development of the mature conidium. RT-PCR analysis was also performed to examine in vivo expression of Prl during infection of waxworm larvae {Galleria mellonelld). Results showed expression of Prl as mycelia emerge and produce conidia on the surface of the cadaver. It is well documented that Prl is produced during the initial stages of transcuticular penetration by M. anisopliae. We suggest that upregulation of Prl is part of the mechanism by which reverse (from inside to the outside of the host) transcuticular penetration of the insect cuticle allows subsequent conidiation on the cadaver.

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The relative ease to concentrate and purify adenoviruses, their well characterized mid-sized genome, and the ability to delete non-essential regions from their genome to accommodate foreign gene, made adenoviruses a suitable candidate for the construction of vectors. The use of adenoviral vectors in gene therapy, vaccination, and as a general vector system for expressing foreign genes have been documented for some time. In this study, the objective was to rescue a BAV3 E1 or E3 recombinant vector carrying the kanamycin resistant gene, a dominant selectable marker with useful applications in studying vectored gene expression in mammalian cells. To accomplish the objective of this study, more information about BAV3 DNA sequences was required in order to make the manipulation of the virus genome accessible. Therefore, sequencing of the BAV3 genome from 1 1 .7% to 30.8% was carried out. Analysis of the determined sequences revealed the primary structure of important viral gene products coded by E2 including BAV3 DNA pol and precursor to terminal protein. Comparative analysis of these proteins with their counterparts from human and non human adenoviruses revealed important insights as to the evolutionary lineage of BAV3. In order to insert the kanamycin resistance gene in either E1 or E3, it was necessary to delete BAV3 sequences to accommodate the foreign gene so as not to exceed the limit of the packaging capacity of the virus. To construct a recombinant BAV3 in which a foreign gene was inserted in the deleted E1 region, an E1 shuttle vector was constructed. This involved the deletion from the viral sequences a region between 1.3% to 9% and inserting the kanamycin resistance gene to replace the deletion. The E1 shuttle vector contained the left (0%- 53.9%) segment of the genome and was expected to generate BAV3 recombinants that can be grown and propagated in cells that can complement the missing E1 functions. To construct a similar shuttle vector for E3 deletion, DNA sequences extending from 78.9% to 82.5% (1281 bp) were deleted from within the E3 region that had been cloned into a plasmid vector. The deleted region corresponds to those that have been shown to be non-essential for viral replication in cell culture. The resulting plasmid was used to construct another recombinant plasmid with BAV3 DNA sequences extending from 37.1% to 100% and with a deletion of E3 sequences that were replaced by kanamycin resistance gene. This shuttle plasmid was used in cotransfections with digested viral DNA in an attempt to rescue a recombinant BAV3 carrying the kanamycin resistance gene to replace the deleted E3. In spite of repeated attempts of transfection, El or E3 recombinant BAV3 were not isolated. It seems that other approaches should be applied to make a final conclusion on BAV3 infectivity.

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Medical fields requires fast, simple and noninvasive methods of diagnostic techniques. Several methods are available and possible because of the growth of technology that provides the necessary means of collecting and processing signals. The present thesis details the work done in the field of voice signals. New methods of analysis have been developed to understand the complexity of voice signals, such as nonlinear dynamics aiming at the exploration of voice signals dynamic nature. The purpose of this thesis is to characterize complexities of pathological voice from healthy signals and to differentiate stuttering signals from healthy signals. Efficiency of various acoustic as well as non linear time series methods are analysed. Three groups of samples are used, one from healthy individuals, subjects with vocal pathologies and stuttering subjects. Individual vowels/ and a continuous speech data for the utterance of the sentence "iruvarum changatimaranu" the meaning in English is "Both are good friends" from Malayalam language are recorded using a microphone . The recorded audio are converted to digital signals and are subjected to analysis.Acoustic perturbation methods like fundamental frequency (FO), jitter, shimmer, Zero Crossing Rate(ZCR) were carried out and non linear measures like maximum lyapunov exponent(Lamda max), correlation dimension (D2), Kolmogorov exponent(K2), and a new measure of entropy viz., Permutation entropy (PE) are evaluated for all three groups of the subjects. Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. The results shows that nonlinear dynamical methods seem to be a suitable technique for voice signal analysis, due to the chaotic component of the human voice. Permutation entropy is well suited due to its sensitivity to uncertainties, since the pathologies are characterized by an increase in the signal complexity and unpredictability. Pathological groups have higher entropy values compared to the normal group. The stuttering signals have lower entropy values compared to the normal signals.PE is effective in charaterising the level of improvement after two weeks of speech therapy in the case of stuttering subjects. PE is also effective in characterizing the dynamical difference between healthy and pathological subjects. This suggests that PE can improve and complement the recent voice analysis methods available for clinicians. The work establishes the application of the simple, inexpensive and fast algorithm of PE for diagnosis in vocal disorders and stuttering subjects.