Watermelon transformation with Zucchini yellow mosaic virus coat protein gene and comparison with parental cultivar

The objective of this work was to transfer Zucchini yellow mosaic virus coat protein (ZYMV-CP) and neomycin phosphotransferase II (NPT II) genes to the watermelon 'Crimson Sweet'(CS) genome, and to compare the transgenic progenies T1 and T2 with the nontransformed parental cultivar for morphological, pomological, growth and yield characteristics. The ZYMV-CP gene was transferred by Agrobacterium tumefaciens. The presence of the gene in transgenic T0, T1 and T2 plants was determined by polymerase chain reaction, and the results were confirmed by Southern blot. Two experiments were performed, one in the winter-spring and the other in the summer-autumn. In both experiments, the hypocotyl length of transgenic seedlings was significantly higher than that of nontransgenic parental ones. In the second experiment, the differences between transgenic and nontransgenic individuals were significant concerning fruit rind thickness, flesh firmness, fruit peduncle length, size of pistil scar, and a* values for fruit stripe or flesh color. Transferring ZYMV-CP gene to CS genome affected only a few characteristics from the 80 evaluated ones. The changes in rind thickness, flesh firmness and flesh color a* values are favorable, while the increase in the size of pistil scar is undesirable. The transgenic watermelon line having ZYMV-CP gene and the parental cultivar CS are very similar.

Quantitative multi-parameter mapping of R1, PD(*), MT, and R2(*) at 3T: a multi-center validation.

Multi-center studies using magnetic resonance imaging facilitate studying small effect sizes, global population variance and rare diseases. The reliability and sensitivity of these multi-center studies crucially depend on the comparability of the data generated at different sites and time points. The level of inter-site comparability is still controversial for conventional anatomical T1-weighted MRI data. Quantitative multi-parameter mapping (MPM) was designed to provide MR parameter measures that are comparable across sites and time points, i.e., 1 mm high-resolution maps of the longitudinal relaxation rate (R1 = 1/T1), effective proton density (PD(*)), magnetization transfer saturation (MT) and effective transverse relaxation rate (R2(*) = 1/T2(*)). MPM was validated at 3T for use in multi-center studies by scanning five volunteers at three different sites. We determined the inter-site bias, inter-site and intra-site coefficient of variation (CoV) for typical morphometric measures [i.e., gray matter (GM) probability maps used in voxel-based morphometry] and the four quantitative parameters. The inter-site bias and CoV were smaller than 3.1 and 8%, respectively, except for the inter-site CoV of R2(*) (<20%). The GM probability maps based on the MT parameter maps had a 14% higher inter-site reproducibility than maps based on conventional T1-weighted images. The low inter-site bias and variance in the parameters and derived GM probability maps confirm the high comparability of the quantitative maps across sites and time points. The reliability, short acquisition time, high resolution and the detailed insights into the brain microstructure provided by MPM makes it an efficient tool for multi-center imaging studies.

Genetic transformation of sweet oranges with the D4E1 gene driven by the AtPP2 promoter

The objective of this work was to produce transgenic 'Pêra' and 'Valência' sweet orange plants using the D4E1 gene driven by the Arabidopsis thaliana phloem protein (AtPP2) promoter and to quantify transgene expression in different transformation events. Genetic transformation experiments were carried out with epicotyl segments co‑cultivated with Agrobacterium tumefaciens. Six plants from 'Pêra' sweet orange and seven plants from 'Valência' sweet orange were confirmed as different transgenic events by means of the polymerase chain reaction (PCR) and the Southern blot techniques. Transgene expression was quantified using real‑time quantitative PCR. D4E1 gene expression levels vary from 5 up to 50 times among different transformation events.

Second-order parameter estimation

This work provides a general framework for the design of second-order blind estimators without adopting anyapproximation about the observation statistics or the a prioridistribution of the parameters. The proposed solution is obtainedminimizing the estimator variance subject to some constraints onthe estimator bias. The resulting optimal estimator is found todepend on the observation fourth-order moments that can be calculatedanalytically from the known signal model. Unfortunately,in most cases, the performance of this estimator is severely limitedby the residual bias inherent to nonlinear estimation problems.To overcome this limitation, the second-order minimum varianceunbiased estimator is deduced from the general solution by assumingaccurate prior information on the vector of parameters.This small-error approximation is adopted to design iterativeestimators or trackers. It is shown that the associated varianceconstitutes the lower bound for the variance of any unbiasedestimator based on the sample covariance matrix.The paper formulation is then applied to track the angle-of-arrival(AoA) of multiple digitally-modulated sources by means ofa uniform linear array. The optimal second-order tracker is comparedwith the classical maximum likelihood (ML) blind methodsthat are shown to be quadratic in the observed data as well. Simulationshave confirmed that the discrete nature of the transmittedsymbols can be exploited to improve considerably the discriminationof near sources in medium-to-high SNR scenarios.

Monte Carlo Methods in Parameter Estimation of Nonlinear Models

Yksi keskeisimmistä tehtävistä matemaattisten mallien tilastollisessa analyysissä on mallien tuntemattomien parametrien estimointi. Tässä diplomityössä ollaan kiinnostuneita tuntemattomien parametrien jakaumista ja niiden muodostamiseen sopivista numeerisista menetelmistä, etenkin tapauksissa, joissa malli on epälineaarinen parametrien suhteen. Erilaisten numeeristen menetelmien osalta pääpaino on Markovin ketju Monte Carlo -menetelmissä (MCMC). Nämä laskentaintensiiviset menetelmät ovat viime aikoina kasvattaneet suosiotaan lähinnä kasvaneen laskentatehon vuoksi. Sekä Markovin ketjujen että Monte Carlo -simuloinnin teoriaa on esitelty työssä siinä määrin, että menetelmien toimivuus saadaan perusteltua. Viime aikoina kehitetyistä menetelmistä tarkastellaan etenkin adaptiivisia MCMC menetelmiä. Työn lähestymistapa on käytännönläheinen ja erilaisia MCMC -menetelmien toteutukseen liittyviä asioita korostetaan. Työn empiirisessä osuudessa tarkastellaan viiden esimerkkimallin tuntemattomien parametrien jakaumaa käyttäen hyväksi teoriaosassa esitettyjä menetelmiä. Mallit kuvaavat kemiallisia reaktioita ja kuvataan tavallisina differentiaaliyhtälöryhminä. Mallit on kerätty kemisteiltä Lappeenrannan teknillisestä yliopistosta ja Åbo Akademista, Turusta.

Hes1 is a critical but context-dependent mediator of canonical Notch signaling in lymphocyte development and transformation.

Although canonical Notch signaling regulates multiple hematopoietic lineage decisions including T cell and marginal zone B cell fate specification, the downstream molecular mediators of Notch function are largely unknown. We showed here that conditional inactivation of Hes1, a well-characterized Notch target gene, in adult murine bone marrow (BM) cells severely impaired T cell development without affecting other Notch-dependent hematopoietic lineages such as marginal zone B cells. Competitive mixed BM chimeras, intrathymic transfer experiments, and in vitro culture of BM progenitors on Delta-like-expressing stromal cells further demonstrated that Hes1 is required for T cell lineage commitment, but dispensable for Notch-dependent thymocyte maturation through and beyond the beta selection checkpoint. Furthermore, our data strongly suggest that Hes1 is essential for the development and maintenance of Notch-induced T cell acute lymphoblastic leukemia. Collectively, our studies identify Hes1 as a critical but context-dependent mediator of canonical Notch signaling in the hematopoietic system.

Malignancy transformation of chronic osteomyelitis: description of 6 cases of Marjolin's ulcers

Marjolin's ulcer describes any malignant transformation of a chronic inflammatory lesion. In the majority of cases, a squamous cell carcinoma is diagnosed. Malignant transformation occurs usually after a long period of latency of chronic infection; it takes approximately 35 years on average. There are no typical clinical presentations, but several indirect signs may suggest the malignant transformation, such as increased or changed discharge, pathologic fracture, a slow-growing exophytic mass, or other suggestive signs of malignant transformation, which should prompt to biopsy for histological exam. The diagnosis of chronic osteomyelitis should not prevent to search for carcinoma. We present six patients with chronic osteomyelitis that developed well-differentiated squamous cell carcinoma. All patients were older than 50 years (mean 60 years, range 52-77 years). Five Marjolin's ulcers were located on the lower limb and one on the arm. The average time of the chronic discharging osteomyelitis before diagnosis of carcinoma ranged between 12 and 40 years. All patients were treated by amputation of the affected limb. None had metastasis, and one patient developed local recurrence and received palliative treatment. Our study emphasizes that Marjolin's ulcer should be considered as a rare but significant long-term complication of chronic osteomyelitis. The finding of microorganisms should not prevent from further diagnostic procedures by histopathological examination so that the correct surgical treatment can be performed.

Methods for Region Based Paper Surface Roughness Measurement

Paperin pinnan karheus on yksi paperin laatukriteereistä. Sitä mitataan fyysisestipaperin pintaa mittaavien laitteiden ja optisten laitteiden avulla. Mittaukset vaativat laboratorioolosuhteita, mutta nopeammille, suoraan linjalla tapahtuville mittauksilla olisi tarvetta paperiteollisuudessa. Paperin pinnan karheus voidaan ilmaista yhtenä näytteelle kohdistuvana karheusarvona. Tässä työssä näyte on jaettu merkitseviin alueisiin, ja jokaiselle alueelle on laskettu erillinen karheusarvo. Karheuden mittaukseen on käytetty useita menetelmiä. Yleisesti hyväksyttyä tilastollista menetelmää on käytetty tässä työssä etäisyysmuunnoksen lisäksi. Paperin pinnan karheudenmittauksessa on ollut tarvetta jakaa analysoitava näyte karheuden perusteella alueisiin. Aluejaon avulla voidaan rajata näytteestä selvästi karheampana esiintyvät alueet. Etäisyysmuunnos tuottaa alueita, joita on analysoitu. Näistä alueista on muodostettu yhtenäisiä alueita erilaisilla segmentointimenetelmillä. PNN -menetelmään (Pairwise Nearest Neighbor) ja naapurialueiden yhdistämiseen perustuvia algoritmeja on käytetty.Alueiden jakamiseen ja yhdistämiseen perustuvaa lähestymistapaa on myös tarkasteltu. Segmentoitujen kuvien validointi on yleensä tapahtunut ihmisen tarkastelemana. Tämän työn lähestymistapa on verrata yleisesti hyväksyttyä tilastollista menetelmää segmentoinnin tuloksiin. Korkea korrelaatio näiden tulosten välillä osoittaa onnistunutta segmentointia. Eri kokeiden tuloksia on verrattu keskenään hypoteesin testauksella. Työssä on analysoitu kahta näytesarjaa, joidenmittaukset on suoritettu OptiTopolla ja profilometrillä. Etäisyysmuunnoksen aloitusparametrit, joita muutettiin kokeiden aikana, olivat aloituspisteiden määrä ja sijainti. Samat parametrimuutokset tehtiin kaikille algoritmeille, joita käytettiin alueiden yhdistämiseen. Etäisyysmuunnoksen jälkeen korrelaatio oli voimakkaampaa profilometrillä mitatuille näytteille kuin OptiTopolla mitatuille näytteille. Segmentoiduilla OptiTopo -näytteillä korrelaatio parantui voimakkaammin kuin profilometrinäytteillä. PNN -menetelmän tuottamilla tuloksilla korrelaatio oli paras.