INTRODUÇÃO: A Síndrome de Rubinstein-Taybi (RTS) é uma doença genética rara, caracterizada por dismorfismos craniofaciais típicos, polegares e háluces alargados, deficiência mental e baixa estatura. A incidência estimada é de 1: 125 000 a 1: 330000 nativivos. A SRT geralmente ocorre esporadicamente, mas pode ser herdada com um padrão de herança autossômico dominante. O diagnóstico da SRT é essencialmente clínico. OBJETIVOS: Realizar o estudo genético-clínico e citogenético em 30 pacientes brasileiros com SRT, e descrever de forma sistematizada a freqüência de dismorfismos faciais e malformações múltiplas encontradas. MÉTODOS: Neste estudo observacional retrospectivo e prospectivo, os pacientes foram seguidos no período de agosto de 2005 a junho de 2009. O cariótipo com bandeamento G foi realizado em todos os pacientes. RESULTADOS: A maioria dos pacientes avaliados foi do sexo feminino (60%). As seguintes características foram observadas em todos os pacientes da nossa casuística: atraso de desenvolvimento neuropsicomotor, ponta nasal voltada para baixo, columela proeminente, sorriso característico, dificuldades alimentares na infância, persistência dos coxins fetais, falanges distais dos polegares alargadas e pés planos. A baixa estatura e a microcefalia foi observada em 80% e 76% dos casos, respectivamente. As principais características craniofaciais observadas foram: fronte proeminente (86%), ponte nasal larga (60%), hipertelorismo (70%), sobrancelhas espessas e arqueadas (96%) cílios longos em 93%, prega epicântica (76%), fissura palpebral infra vertidas (76%), abertura bucal estreita (93%), retrognatismo (76 %), sorriso característico em 100%, palato alto e estreito (93%), anomalias dentárias (83%). Outras anomalias identificadas foram: estrabismo, erros de refração, obstrução do canal lacrimal, háluces e polegares alargados, angulação de polegares, anomalias do pavilhão auricular (rotação/posição/tamanho/forma), angulação do hálux, clinodactilia, sobreposição dos pododáctilos, falanges distais alargadas de outros dedos, marcha rígida, hipotonia, sopro cardíaco, cardiopatia congênita, criptoquidia, hemangioma plano e hipertricose. Uma paciente apresentou translocação recíproca de novo 46, XX, t (2; 16)(q36.3; p13.3). CONCLUSÕES: A raridade da SRT e o amplo espectro das manifestações clínicas pode atrasar o diagnóstico clínico. A média da idade ao diagnóstico dos nossos pacientes com SRT foi de três anos e oito meses. Todas as crianças devem receber avaliação por geneticista pediátrico, cardiologista, oftalmologista, neuropediatra, e odontopediatra / INTRODUCTION: Rubinstein-Taybi syndrome (RTS) is a rare genetic disorder characterized by distinctive craniofacial dysmorphisms, broad thumbs and toes and mental and statural deficiency. The prevalence of RTS has been estimated to be 1 in 125000 to 1: 330000 live births. RTS usually occurs sporadically although it can be inherited as an autosomal dominant disorder. The diagnosis of RTS is primarily based on clinical features. OBJECTIVES: We performed a clinical and cytogenetic assay in a group of 30 Brazilian RTS patients. We also decribed the frequencies of facial dysmorphisms and multiple malformations. METHODS: In this observational retrospective and prospective study, the patients were followed from August 2005 to June 2009. Chromosomal analysis was performed by G-banding karyotype. RESULTS: Most of the patients were female (60%).The following abnormalities were present in all of the patients: delayed psychomotor development, beaked nose, proeminent collumel, typical facies, broad thumbs and toes, flat feet, joint laxity, feeding problems during the childhood, and finger pads. Short stature was present in 80%, and microcephalia in 76% of the cases, respectively. Main craniofacial characteristics are frontal bossing (86%), wide nasal bridge (60%), ocular hyperthelorism (70%), high arched eyebrows (96%), long eyelashes (93%), epicathal folds (76%), downslanting palpebral fissures (76%), small opening of the mouth (93%), retrognathism (76%), grimacing smile (100%), high arched palate (93%), and dental anomalies (83%). Other findings were: strabism, refractive error, lacrimal obstruction, wide thumb and halux, angulated thumbs, external ears anomalies (rotation, implantation and morfology), angulated halux, clinodactyly, crowded toes, broad distal falanges of other fingers, stiff gait, hipotonia, cardiac murmur, congenital heart defect, undescendent testis, hypertrichosis, and hemangioma. One female patient has found to have a reciprocal de novo translocation t(2;16)(q36.3;p13.3) on G-banding karyotype CONCLUSIONS: The rarity of RTS and the wide spectrum of clinical manifestations, may delay the clinical diagnosis of RTS. The average age at the diagnosis of our patients was 3 years and 8 months. All children of RTS should receive an evaluation by a pediatric geneticist, cardiologist, ophthalmologist, pediatric neurologist, and pediatric dentist

Thesis (MSc)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: The yeast species, Saccharomyces cerevisiae and S. bayanus are well known for the key role they play during alcoholic fermentation in both wine and beer industries. These yeasts are available in pure active dried form and can be used to produce different wine styles and to manage quality. There are more than 200 commercial wine yeast strains on the market and include naturally isolated strains and hybrids. With all these commercial yeasts available, strain authenticity is very important to the manufacturer of active dried wine yeasts (ADWY) because it can prevent commercial losses and maintain market credibility. It is as important to the winemaker as it may impact wine quality. Various traditional and molecular techniques have been successfully applied to perform quality control of wine yeast strains. The aims of this study were to evaluate electrophoretic karyotyping (CHEF) and PCRbased methods to distinguish between Saccharomyces wine yeast strains and to establish a database containing molecular profiles of commercial strains. CHEF karyotyping was chosen because it is generally used in the wine industry to distinguish between wine yeast strains, but can be time-consuming. Alternatively, PCR-based methods are considered to be reliable and fast. These PCR methods included the evaluation of interdelta regions, multiplex-PCR of miniand microsatellites, MET2 gene RFLP analysis and the use of several species-specific primers. In this study, 62 commercial wine yeast strains, were randomly selected from various manufacturers of ADWY, and two reference strains, S. bayanus CBS 380 and S. cerevisiae CBS 1171, were evaluated. CHEF karyotyping could successfully differentiate between all 64 yeast strains. The two primer sets used for interdelta amplifications, delta1-2 and delta12-21, yielded 59 and 62 profiles, respectively. Yeast strains considered to be similar or identical according to interdelta amplification results, were resolved with CHEF karyotyping. CHEF karyotyping was proven to be more accurate than interdelta amplifications in distinguishing between commercial wine yeast strains. However, the results of interdelta amplifications were very useful and less time-consuming. The multiplex-PCR of mini- and microsatellite primers only succeeded in identifying a specific band within 55 of the 64 yeast strains including the S. cerevisiae reference strain, a possible indication of species specificity. However, oenological designation using MET2 gene RFLP analysis and species-specific primers indicated that all the commercial strains in this study had a S. cerevisiae ancestry. Restriction analysis of the MET2 gene with EcoRI also successfully identified AWRI Fusion and Zymaflore X5 as hybrid yeast strains. A wine yeast database was created and contains three libraries, i.e. CHEF karyotypes, delta1-2 and delta12-21 electrophoretic profiles. The database was proven to be functional and showed great accuracy in grouping and identifying test strains. The database has many possible applications, but there is still some optimisation and refinement needed. / AFRIKAANSE OPSOMMING: Die Saccharomyces sensu stricto kompleks, is bekend vir die belangrike rol wat hierdie giste speel tydens alkoholiese fermentasie in biede wyn en bier industrieë. Dit is om hierdie rede dat kelders rein aktief gedroogte wyngis gebruik vir die produksie van spesifieke wynstyle, asook kwaliteit. Daar is meer as 200 kommersiële wyngiste op die mark beskikbaar en dit sluit natuurlike isolate en hibriede in. Daarom is gisras verifikasie baie belangrik vir die vervaardiger van aktief gedroogde wyngiste asook die wynmaker om finansiële verliese te voorkom en mark vertrouenswaardigheid te handhaaf. Verskeie tradisionele en molekulêre metodes word suksesvol toegepas vir gehalte beheer van die gisrasse. Die doel van hierdie studie was om elektroforetiese kariotipering (CHEF) en PKR gebaseerde tegnieke se vermoë om tussen Saccharomyces wyngiste te onderskei, te ondersoek. Ook deel van die doelwitte was om ‘n databasis te skep wat die verskillende elektroforetiese profiele van die kommersiële gisrasse bevat. Tydens hierdie studie is 62 kommersiële gisrasse van verskeie vervaardigers ewekansig geselekteer. Saccharomyces bayanus CBS 380 en S. cerevisiae CBS 1171 is as verwysingsrasse gebruik. Elektroforetiese kariotipering (CHEF) is gekies omdat dit een van die mees algemeenste tegnieke is wat gebruik word om tussen wyngiste te onderskei, maar dit word as tydrowend en arbeidsintensief beskou. As ‘n alternatief is daar na PKR gebaseerde tegnieke gekyk. Hierdie tegnieke word as betroubaar en vinnig beskou. Verskeie PKR gebaseerde tegnieke is ondersoek, naamlik PKR van interdelta areas, multipleks-PKR van mini- en mikrosatelliete, MET2 geen RFLP analise en die gebruik van spesie-spesifieke inleiers. Interdelta amplifikasies en mini- en makrosatelliet inleiers is geselekteer as gevolg van hul vermoë om Saccharomyces wyngiste tot op spesie en ras vlak te onderskei. Die MET2 geen en spesie-spesifieke inleiers is geselekteer om die kommersiele wyngis as S. cerevisiae, S. bayanus of as hibriede te klassifiseer. CHEF kariotipering kon tussen al 64 giste onderskeid tref. Die twee stelle inleiers wat vir interdelta amplifikasie gebruik was, delta1-2 en delta12-21, het onderskeidelik 59 en 62 profiele gelewer. Gis rasse wat identiese profiele met die delta inleiers gelewer het, kon egter met CHEF kariotipering onderskei word. Die resultate het getoon dat CHEF kariotipering beter tussen die kommersiële wyngiste kon onderskei as die interdelta amplifikasies, maar dat die interdelta amplifikasies nogsteeds goeie onderskeiding toon en dat dit minder tydrowend is. Die multipleks-PKR van mini- en mikrosatelliete kon slegs ‘n enkele band in 55 van die 64 giste uit lig. ‘n Moontlike aanduiding van spesie spesifiekheid. Die oenologiese groepering volgens MET2 geen analise en spesies-spesifieke inleiers dui aan dat al die kommersiele wyngiste wat in hierdie studie gebruik is, moontlik van S. cerevisiae afkomstig is. Restriksie analise van die MET2 geen met EcoRI het ook AWRI Fusion en Zymaflore X5 as hibriede geïdentifiseer. Die CHEF kariotipes en interdelta elektroforetiese profiele is gebruik om ‘n databasis van die kommersiële Saccharomyces wyngiste op te stel. Die databasis is funksioneel en het die toets rasse akkuraat geïdentifiseer en korrek gegroepeer. Die databasis moet egter nog verdere optimisering en verfyning ondergaan.

Changes in chromosome number and structure may cause serious diseases. Cytogenetic tests leadin to set of karyotype are done for detecting these abnormalities. Chromosomes are visualised with proper methods and karyotype is made up most often. Manual karyotyping is time-consuming and expensive task. Because of this, researchers have been developing automated karyotyping systems. Karyotyping systems classify chromosomes into classes based on their characteristic features. Overlapping and bent chromosomes are limitations for automatic classification since they ocur at almost every mitosis. Accuracy and reliability of karyotyping systems still depend on the human intervention. Overcoming of these problems and development of fully automated system is the aim of modern approaches.

Spectral karyotyping (SKY) is a widely used methodology to identify genetic aberrations. Multicolor fluorescence in situ hybridization using chromosome painting probes in individual colors for all metaphase chromosomes at once is combined with a unique spectral measurement and analysis system to automatically classify normal and aberrant chromosomes. Based on countless studies and investigations in many laboratories worldwide, numerous new chromosome translocations and other aberrations have been identified in clinical and tumor cytogenetics. Thus, gene identification studies have been facilitated resulting in the dissection of tumor development and progression. For example, different translocation partners of the TEL/ETV6 transcription factor that is specially required for hematopoiesis within the bone marrow were identified. Also, the correct classification of complex karyotypes of solid tumors supports the prognostication of cancer patients. Important accomplishments for patients with genetic diseases, leukemias and lymphomas, mesenchymal tumors and solid cancers are summarized and exemplified. Furthermore, studies of disease mechanisms such as centromeric DNA breakage, DNA double strand break repair, telomere shortening and radiation-induced neoplastic transformation have been accompanied by SKY analyses. Besides the hybridization of human chromosomes, mouse karyotyping has also contributed to the comprehensive characterization of mouse models of human disease and for gene therapy studies. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

Foi realizado um estudo para verificar a ocorrência de leveduras do gênero Rhodotorula, em hemocultura por um período de 8 anos. Os pacientes identificados foram descritos clinicamente segundo variáveis de interesse incluindo dados sobre terapêutica e desfecho. Determinou-se também as concentrações inibitórias mínimas de 20 cepas frente a diferentes antifúngicos de acordo com NCCLS e EUCAST. Realizou-se tipagem molecular através da cariotipagem eletroforética em campo pulsátil / A study was conducted to verify the frequency of occurrence of Rhodotorula spp. from blood cultures over an 8-year period, clinically and microbiologically characterizing patients affected, including data regarding antifungal treatment and outcome. The minimal inhibitory concentrations of antifungal agents were determined against 20 isolates. Molecular typing of the strains were performed using pulsed field gel electrophoresis method

Foi realizado um estudo para verificar a ocorrência de leveduras do gênero Rhodotorula, em hemocultura por um período de 8 anos. Os pacientes identificados foram descritos clinicamente segundo variáveis de interesse incluindo dados sobre terapêutica e desfecho. Determinou-se também as concentrações inibitórias mínimas de 20 cepas frente a diferentes antifúngicos de acordo com NCCLS e EUCAST. Realizou-se tipagem molecular através da cariotipagem eletroforética em campo pulsátil / A study was conducted to verify the frequency of occurrence of Rhodotorula spp. from blood cultures over an 8-year period, clinically and microbiologically characterizing patients affected, including data regarding antifungal treatment and outcome. The minimal inhibitory concentrations of antifungal agents were determined against 20 isolates. Molecular typing of the strains were performed using pulsed field gel electrophoresis method

Chromosome classification is one of the essential tasks in karyotyping to diagnose genetic abnormalities like some types of cancers and Down syndrome. Deep convolutional neural networks have been widely used in this task, and the accuracy of classification models is exceptionally critical to such sensitive medical diagnoses. However, it is not always possible to meet the expected accuracy rates for diagnosis. So, it is vital to tell how certain or uncertain a model is with its decision. In our work, we use two metrics, entropy and variance, as uncertainty measurements. Moreover, three additional metrics, fail rate, workload, and tolerance range, are used to measure uncertainty metrics’ quality. Four different non-Bayesian methods: deep ensembles, snapshot ensembles, Test Time Augmentation, and Test Time Dropout, are used in experiments. A negative correlation is observed between the accuracy and the uncertainty estimation; the higher the accuracy of the model, the lower the uncertainty. Densenet121 with deep ensembles as the uncertainty evaluation method and variance as the uncertainty metric gives the best outcomes. Densenet121 provides a wider tolerance range and better separation between uncertain and certain predictions. / Kromosomklassificering är en av de viktigaste uppgifterna i Karyotyping för att diagnostisera genetiska abnormiteter som vissa typer av cancer och Downs syndrom. Deep Convolutional Neural Networks har använts i stor utsträckning i denna uppgift, och noggrannheten hos klassificeringsmodeller är exceptionellt kritisk för sådana känsliga medicinska diagnoser. Det är dock inte alltid möjligt att uppfylla de förväntade noggrannhetsgraderna för diagnos. Så det är viktigt att berätta hur säker eller osäker en modell är med sitt beslut. Forskning har gjorts för att uppskatta osäkerheten med bayesiska metoder och icke-bayesiska neurala nätverk, medan lite är känt om kvaliteten på osäkerhetsuppskattningar. I vårt arbete använder vi två mått, entropi och varians, som osäkerhetsmätningar. Dessutom används ytterligare tre mätvärden, felfrekvens, arbetsbelastning och toleransintervall för att mäta osäkerhetsmätarnas kvalitet. Fyra olika icke-bayesiska metoder: djupa ensembler, ögonblicksbilder, Test Time Augmentation (TTA) och Test Time Dropout (TTD) används i experiment. En negativ korrelation observeras mellan noggrannheten och osäkerhetsuppskattningen; ju högre noggrannhet modellen är, desto lägre är osäkerheten. Densenet121 med djupa ensembler som osäkerhetsutvärderingsmetod och varians som osäkerhetsmätvärdet ger de bästa resultaten. De ger ett bredare toleransintervall och bättre separation mellan osäkra och vissa förutsägelser.