Segmentation of Cell Nuclei Regions in Epithelium of Prostate Glands

This paper proposes a method for segmentation of cell nuclei regions in epithelium of prostate glands. This structure provides information to diagnosis and prognosis of prostate cancer. In the initial step, the contrast stretching technique was applied in image in order to improve the contrast between regions of interest and other regions. After, the global thresholding technique was applied and the value of threshold was defined empirically. Finally, the false positive regions were removed using the connected components technique. The performance of the proposed method was compared with the Otsu technique and statistical measures of accuracy were calculated based on reference images (gold standard). The result of the mean value of accuracy of proposed method was 93% ± 0.07.

Modelo de Resposta à Intervenção (RTI) para desenvolvimento das habilidades fonológicas com tutoria instrucional em contexto escolar: elaboração e controle de eficácia

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Accuracy of positron emission tomography/computed tomography and clinical assessment in the detection of complete rectal tumor regression after neoadjuvant chemoradiation Long-Term Results of a Prospective Trial (National Clinical Trial 00254683)

BACKGROUND: Neoadjuvant chemoradiation (CRT) therapy may result in significant tumor regression in patients with rectal cancer. Patients who develop complete tumor regression have been managed by treatment strategies that are alternatives to standard total mesorectal excision. Therefore, assessment of tumor response with positron emission tomography/computed tomography (PET/CT) after neoadjuvant treatment may offer relevant information for the selection of patients to receive alternative treatment strategies. METHODS: Patients with clinical T2 (cT2) through cT4NxM0 rectal adenocarcinoma were included prospectively. Neoadjuvant therapy consisted of 54 grays of radiation and 5-fluorouracil-based chemotherapy. Baseline PET/CT studies were obtained before CRT followed by PET/CT studies at 6 weeks and 12 weeks after the completion of CRT. Clinical assessment was performed at 12 weeks after CRT completion. PET/CT results were compared with clinical and pathologic data. RESULTS: In total, 99 patients were included in the study. Twenty-three patients were complete responders (16 had a complete clinical response, and 7 had a complete pathologic response). The PET/CT response evaluation at 12 weeks indicated that 18 patients had a complete response, and 81 patients had an incomplete response. There were 5 false-negative and 10 false-positive PET/CT results. PET/CT for the detection of residual cancer had 93% sensitivity, 53% specificity, a 73% negative predictive value, an 87% positive predictive value, and 85% accuracy. Clinical assessment alone resulted in an accuracy of 91%. PET/CT information may have detected misdiagnoses made by clinical assessment alone, improving overall accuracy to 96%. CONCLUSIONS: Assessment of tumor response at 12 weeks after CRT completion with PET/CT imaging may provide a useful additional tool with good overall accuracy for the selection of patients who may avoid unnecessary radical resection after achieving a complete clinical response. Cancer 2012;35013511. (C) 2011 American Cancer Society.

Design and implementation of bioinformatics tools for large scale genome annotation

The continuous increase of genome sequencing projects produced a huge amount of data in the last 10 years: currently more than 600 prokaryotic and 80 eukaryotic genomes are fully sequenced and publically available. However the sole sequencing process of a genome is able to determine just raw nucleotide sequences. This is only the first step of the genome annotation process that will deal with the issue of assigning biological information to each sequence. The annotation process is done at each different level of the biological information processing mechanism, from DNA to protein, and cannot be accomplished only by in vitro analysis procedures resulting extremely expensive and time consuming when applied at a this large scale level. Thus, in silico methods need to be used to accomplish the task. The aim of this work was the implementation of predictive computational methods to allow a fast, reliable, and automated annotation of genomes and proteins starting from aminoacidic sequences. The first part of the work was focused on the implementation of a new machine learning based method for the prediction of the subcellular localization of soluble eukaryotic proteins. The method is called BaCelLo, and was developed in 2006. The main peculiarity of the method is to be independent from biases present in the training dataset, which causes the over‐prediction of the most represented examples in all the other available predictors developed so far. This important result was achieved by a modification, made by myself, to the standard Support Vector Machine (SVM) algorithm with the creation of the so called Balanced SVM. BaCelLo is able to predict the most important subcellular localizations in eukaryotic cells and three, kingdom‐specific, predictors were implemented. In two extensive comparisons, carried out in 2006 and 2008, BaCelLo reported to outperform all the currently available state‐of‐the‐art methods for this prediction task. BaCelLo was subsequently used to completely annotate 5 eukaryotic genomes, by integrating it in a pipeline of predictors developed at the Bologna Biocomputing group by Dr. Pier Luigi Martelli and Dr. Piero Fariselli. An online database, called eSLDB, was developed by integrating, for each aminoacidic sequence extracted from the genome, the predicted subcellular localization merged with experimental and similarity‐based annotations. In the second part of the work a new, machine learning based, method was implemented for the prediction of GPI‐anchored proteins. Basically the method is able to efficiently predict from the raw aminoacidic sequence both the presence of the GPI‐anchor (by means of an SVM), and the position in the sequence of the post‐translational modification event, the so called ω‐site (by means of an Hidden Markov Model (HMM)). The method is called GPIPE and reported to greatly enhance the prediction performances of GPI‐anchored proteins over all the previously developed methods. GPIPE was able to predict up to 88% of the experimentally annotated GPI‐anchored proteins by maintaining a rate of false positive prediction as low as 0.1%. GPIPE was used to completely annotate 81 eukaryotic genomes, and more than 15000 putative GPI‐anchored proteins were predicted, 561 of which are found in H. sapiens. In average 1% of a proteome is predicted as GPI‐anchored. A statistical analysis was performed onto the composition of the regions surrounding the ω‐site that allowed the definition of specific aminoacidic abundances in the different considered regions. Furthermore the hypothesis that compositional biases are present among the four major eukaryotic kingdoms, proposed in literature, was tested and rejected. All the developed predictors and databases are freely available at: BaCelLo http://gpcr.biocomp.unibo.it/bacello eSLDB http://gpcr.biocomp.unibo.it/esldb GPIPE http://gpcr.biocomp.unibo.it/gpipe

Diagnostic accuracy of coronary in-stent restenosis using 64-slice computed tomography: comparison with invasive coronary angiography

OBJECTIVES: This study sought to evaluate the diagnostic accuracy of coronary binary in-stent restenosis (ISR) with angiography using 64-slice multislice computed tomography coronary angiography (CTCA) compared with invasive coronary angiography (ICA). BACKGROUND: A noninvasive detection of ISR would result in an easier and safer way to conduct patient follow-up. METHODS: We performed CTCA in 81 patients after stent implantation, and 125 stented lesions were scanned. Two sets of images were reconstructed with different types of convolution kernels. On CTCA, neointimal proliferation was visually evaluated according to luminal contrast attenuation inside the stent. Lesions were graded as follows: grade 1, none or slight neointimal proliferation; grade 2, neointimal proliferation with no significant stenosis (<50%); grade 3, neointimal proliferation with moderate stenosis (> or =50%); and grade 4, neointimal proliferation with severe stenosis (> or =75%). Grades 3 and 4 were considered binary ISR. The diagnostic accuracy of CTCA compared with ICA was evaluated. RESULTS: By ICA, 24 ISRs were diagnosed. Sensitivity, specificity, positive predictive value, and negative predictive value were 92%, 81%, 54%, and 98% for the overall population, whereas values were 91%, 93%, 77%, and 98% when excluding unassessable segments (15 segments, 12%). For assessable segments, CTCA correctly diagnosed 20 of the 22 ISRs detected by ICA. Six lesions without ISR were overestimated as ISR by CTCA. As the grade of neointimal proliferation by CTCA increases, the median value of percent diameter stenosis increased linearly. CONCLUSIONS: Binary ISR can be excluded with high probability by CTCA, with a moderate rate of false-positive results.

Investigating the potential of reported cattle mortality data in Switzerland for syndromic surveillance

Systems for the identification and registration of cattle have gradually been receiving attention for use in syndromic surveillance, a relatively recent approach for the early detection of infectious disease outbreaks. Real or near real-time monitoring of deaths or stillbirths reported to these systems offer an opportunity to detect temporal or spatial clusters of increased mortality that could be caused by an infectious disease epidemic. In Switzerland, such data are recorded in the "Tierverkehrsdatenbank" (TVD). To investigate the potential of the Swiss TVD for syndromic surveillance, 3 years of data (2009-2011) were assessed in terms of data quality, including timeliness of reporting and completeness of geographic data. Two time-series consisting of reported on-farm deaths and stillbirths were retrospectively analysed to define and quantify the temporal patterns that result from non-health related factors. Geographic data were almost always present in the TVD data; often at different spatial scales. On-farm deaths were reported to the database by farmers in a timely fashion; stillbirths were less timely. Timeliness and geographic coverage are two important features of disease surveillance systems, highlighting the suitability of the TVD for use in a syndromic surveillance system. Both time series exhibited different temporal patterns that were associated with non-health related factors. To avoid false positive signals, these patterns need to be removed from the data or accounted for in some way before applying aberration detection algorithms in real-time. Evaluating mortality data reported to systems for the identification and registration of cattle is of value for comparing national data systems and as a first step towards a European-wide early detection system for emerging and re-emerging cattle diseases.

Genome-wide gene-gene interaction analysis for cardiovascular disease

Numerous studies have been carried out to try to better understand the genetic predisposition for cardiovascular disease. Although it is widely believed that multifactorial diseases such as cardiovascular disease is the result from effects of many genes which working alone or interact with other genes, most genetic studies have been focused on identifying of cardiovascular disease susceptibility genes and usually ignore the effects of gene-gene interactions in the analysis. The current study applies a novel linkage disequilibrium based statistic for testing interactions between two linked loci using data from a genome-wide study of cardiovascular disease. A total of 53,394 single nucleotide polymorphisms (SNPs) are tested for pair-wise interactions, and 8,644 interactions are found to be significant with p-values less than 3.5×10-11. Results indicate that known cardiovascular disease susceptibility genes tend not to have many significantly interactions. One SNP in the CACNG1 (calcium channel, voltage-dependent, gamma subunit 1) gene and one SNP in the IL3RA (interleukin 3 receptor, alpha) gene are found to have the most significant pair-wise interactions. Findings from the current study should be replicated in other independent cohort to eliminate potential false positive results.^

A STUDY OF DIVERSITY AND COMMUNITY COMPARISON INDICES BY BIOASSAY OF COPPER USING COLONIZED BENTHIC MACROINVERTEBRATES

A community bioassay of copper was performed using benthic macroinvertebrates colonized on multiplate substrate samplers. Five copper concentrations ranging from 0.080-2.20 mg/l total copper were administered to five artificial streams by a Mount and Brungs proportional dilutor. Free copper ion as Cu('++) ranged from .002-.053 mg/l. A sixth stream received no copper and served as a control. Substrates were sampled at days 0, 14, and 28, and the results were used to compare 13 indices used or proposed to assess aquatic environmental impact. Sensitivity of the indices to changes in communities with respect to concentration and time was the basis for the comparison.^ Results indicated that all of the 8 diversity or richness indices tested gave approximately the same result (with the exception of number of species); they increased over the first 2-3 concentrations, then declined. Included among these was the Shannon index which gave false positive results, i.e., it increased, indicating enrichment, when in fact perturbation had occurred. This result was due to the disproportionate effect on the most abundant taxa, which caused a more even distribution of individuals among species. Number of species and individuals declined with increased concentration and time, with only one exception in the case of species, indicating perturbation.^ Results of five community comparison indices were varied at day 14 but by day 28 the results indicated a clear, nearly monotonic, trend due to copper impact. It was assumed that day 28 observations, though probably still changing, were nearer stability than at day 14 and therefore more representative of natural conditions. The changes in community comparison indices showed good agreement at 28 days and reflected the general decline in species and individuals. No single community comparison index could be set apart as superior to the others. ^

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

False -positives and false-negatives in tests for trend

False-positive and false-negative values were calculated for five different designs of the trend test and it was demonstrated that a design suggested by Portier and Hoel in 1984 for a different problem produced the lowest false-positive and false-negative rates when applied to historical spontaneous tumor rate data for Fischer Rats. ^

Otimização dos valores de referência da 17OH-progesterona neonatal de acordo com o peso ao nascimento no programa de triagem neonatal da APAE DE SÃO PAULO

Introdução: A Hiperplasia Adrenal Congênita por deficiência da 21-hidroxilase (HAC) é uma doença com mortalidade neonatal elevada sendo elegível para programas públicos de Triagem Neonatal (TN). A HAC é causada por mutações no gene CYP21A2, as quais acarretam diferentes comprometimentos da atividade enzimática e resultam em espectro amplo de manifestações clínicas. Apesar da eficiência da TN para diagnosticar os casos graves, a taxa elevada de resultados falso-positivos (RFP), principalmente relacionados à prematuridade, é um dos maiores problemas. Porém, resultados falso-negativos também podem ocorrer em coletas antes de 24 horas de vida. No Brasil, a coleta da amostra neonatal difere entre os municípios, podendo ser no terceiro dia de vida como após. Objetivo: Avaliar se os valores da 17OH-progesterona neonatal (N17OHP) das coletas no terceiro dia de vida diferem significativamente das coletas a partir do quarto dia. Determinar qual percentil (99,5 ou 99,8) pode ser utilizado como valor de corte para a N17OHP, de acordo com o peso ao nascimento e tempo de vida na coleta, a fim de que proporcione taxa menor de RFP. Métodos: Foi avaliada, retrospectivamente, a N17OHP de 271.810 recém-nascidos (Rns) de acordo com o tempo de vida na coleta (G1: 48 - = 72h) e peso ao nascimento (P1: <= 1.500g, P2: 1.501-2.000g, P3: 2.001-2.500g e P4: >= 2.500g), pelo método imunofluorimétrico. Testes com resultados alterados foram confirmados no soro por Espectrometria de Massas em Tandem - LC-MS/MS. Rns afetados e/ou assintomáticos e com valores persistentemente elevados de 17OHP sérica foram submetidos ao estudo molécular, sequenciamento do gene CYP21A2. Resultados: os valores da N17OHP no grupo G1 foram significativamente menores do que em G2 em todos os grupos de peso (p < 0.001). A taxa de RFP em G1 e G2 foi de 0,2% para o percentil 99,8 e de 0,5% para o percentil 99,5 em ambos os grupos. O percentil 99,8 da N17OHP foi o melhor valor de corte para distinguir os Rns não afetados dos afetados, cujos valores são: G1 (P1: 120; P2: 71; P3: 39 e P4: 20 ng /mL) e em G2 (P1: 173; P2: 90; P3: 66 e P4: 25 ng/mL). Vinte e seis Rns do grupo G1 apresentaram a forma perdedora de sal (PS) (13H e 13M), nestes a N17OHP variou de 31 a 524 ng/mL e vinte Rns no grupo G2 (8H e 12M), nestes a N17OHP variou de 53 a 736 ng/mL. Para ambos os grupos foram encontrados três Rns com a forma virilizante simples (1H e 2M) e os valores da N17OHP variaram de 36 a 51 ng/mL. Resultados falso-negativos não foram relatados. O valor preditivo positivo (VPP) no teste do papel filtro foi de 5,6% e 14,1% nos grupos G1 e G2, respectivamente, ao se utilizar o percentil 99,8, e de 2,3% e 7% nos grupos G1 e G2 ao se utilizar o percentil 99,5. Dentre os casos com TN alterada (RFP), 29 deles também apresentaram 17OHP sérica elevada quando dosada por LC-MS/MS. Os casos assintomáticos foram acompanhados até normalização da 17OHP sérica e/ou submetidos ao estudo molecular, que identificou dois Rns com genótipo que prediz a forma não clássica. Conclusão: a melhor estratégia para otimização do diagnóstico da HAC na triagem neonatal é se padronizar valores de corte da N17OHP em dois grupos de acordo com o tempo de vida na coleta (antes e depois de 72 horas), subdivididos em quatro grupos de peso. A utilização dos valores de corte do percentil 99,8 se mantém eficaz no diagnóstico da HAC-21OH na triagem neonatal, reduzindo de forma significativa a taxa de RFP, sem perda do diagnóstico da forma PS

A new confirmatory Neisseria gonorrhoeae real-time PCR assay targeting the porA pseudogene

The Roche Cobas Amplicor system is widely used for the detection of Neisseria gonorrhoeae but is known to cross react with some commensal Neisseria spp. Therefore, a confirmatory test is required. The most common target for confirmatory tests is the cppB gene of N. gonorrhoeae. However, the cppB gene is also present in other Neisseria spp. and is absent in some N. gonorrhoeae isolates. As a result, laboratories targeting this gene run the risk of obtaining both false-positive and false-negative results. In the study presented here, a newly developed N. gonorrhoeae LightCycler assay (NGpapLC) targeting the N. gonorrhoeae porA pseudogene was tested. The NGpapLC assay was used to test 282 clinical samples, and the results were compared to those obtained using a testing algorithm combining the Cobas Amplicor System (Roche Diagnostics, Sydney, Australia) and an in-house LightCycler assay targeting the cppB gene (cppB-LC). In addition, the specificity of the NGpapLC assay was investigated by testing a broad panel of bacteria including isolates of several Neisseria spp. The NGpapLC assay proved to have comparable clinical sensitivity to the cppB-LC assay. In addition; testing of the bacterial panel showed the NGpapLC assay to be highly specific for N. gonorrhoeae DNA. The results of this study show the NGpapLC assay is a suitable alternative to the cppB-LC assay for confirmation of N. gonorrhoeae-positive results obtained with Cobas Amplicor.

A study of potential serum markers for a diagnosis of gram-positive and gram-negative bacterial sepsis

Sepsis continues to be a major cause of morbidity and mortality as it can readily lead tosevere sepsis, septic shock, multiple organ failure and death. The onset can be rapid and difficult to define clinically. Despite the numerous candidate markers proposed in the literature, to date a serum marker for sepsis has not been found. The aim of this study was to assay the serum of clinically diagnosed patients with eithera Gram-negative or Gram- positive bacterial sepsis for elevated levels of nine potentialmarkers of sepsis, using commercially produced enzyme linked immunosorbent assays(ELISA). The purpose was to find a test marker for sepsis that would be helpful toclinicians in cases of uncertain sepsis and consequently expose false positive BC'scaused by skin or environmental contaminants. Nine test markers were assayed including IL-6, IL-I 0, ILI2, TNF-α, lipopolysaccharide binding protein, procalcitonin, sE-selectin, sICAM -1 and a potential differential marker for Gram-positive sepsis- anti-lipid S antibody. A total of 445 patients were enrolled into this study from the Queen Elizabeth Hospital and Selly Oak Hospital (Birmingham). The results showed that all the markers were elevated in patients with sepsis and that patients with a Gram-negative sepsis consistently produced higher median/range serum levels than those with a Gram-positive sepsis. No single marker was able to identify all the septic patients. Combining two markers caused the sensitivities and specificities for a diagnosis of sepsis to increase to within a 90% to 100% range. By a process of elimination the markers that survived into the last phase were IL-6 with sICAM -1, and anti-lipid S IgG assays Defining cut-off levels for a diagnosis of sepsis became problematic and a semi-blind trial was devised to test the markers in the absence of both clinical details and positive blood cultures. Patients with pyrexia of unknown origin and negative BC were included in this phase (4). The results showed that IL-6 with sICAM-l are authentic markers of sepsis. There was 82% agreement between the test marker diagnosis and the clinical diagnosis for sepsis in patients with a Gram-positive BC and 78% agreement in cases of Gram-negative Be. In the PUO group the test markers identified 12 cases of sepsis and the clinical diagnosis 15. The markers were shown to differentiate between early sepsis and sepsis, inflammatory responses and infection. Anti-lipid S with IL-6 proved be a sensitive marker for Gram-positive infections/sepsis.

Is pregnancy a teachable moment for diet and physical activity behaviour change? An interpretative phenomenological analysis of the experiences of women during their first pregnancy

OBJECTIVES: Pregnancy may provide a 'teachable moment' for positive health behaviour change, as a time when women are both motivated towards health and in regular contact with health care professionals. This study aimed to investigate whether women's experiences of pregnancy indicate that they would be receptive to behaviour change during this period. DESIGN: Qualitative interview study. METHODS: Using interpretative phenomenological analysis, this study details how seven women made decisions about their physical activity and dietary behaviour during their first pregnancy. RESULTS: Two women had required fertility treatment to conceive. Their behaviour was driven by anxiety and a drive to minimize potential risks to the pregnancy. This included detailed information seeking and strict adherence to diet and physical activity recommendations. However, the majority of women described behaviour change as 'automatic', adopting a new lifestyle immediately upon discovering their pregnancy. Diet and physical activity were influenced by what these women perceived to be normal or acceptable during pregnancy (largely based on observations of others) and internal drivers, including bodily signals and a desire to retain some of their pre-pregnancy self-identity. More reasoned assessments regarding benefits for them and their baby were less prevalent and influential. CONCLUSIONS: Findings suggest that for women who conceived relatively easily, diet and physical activity behaviour during pregnancy is primarily based upon a combination of automatic judgements, physical sensations, and perceptions of what pregnant women are supposed to do. Health professionals and other credible sources appear to exert less influence. As such, pregnancy alone may not create a 'teachable moment'. Statement of contribution What is already known on this subject? Significant life events can be cues to action with relation to health behaviour change. However, much of the empirical research in this area has focused on negative health experiences such as receiving a false-positive screening result and hospitalization, and in relation to unequivocally negative behaviours such as smoking. It is often suggested that pregnancy, as a major life event, is a 'teachable moment' (TM) for lifestyle behaviour change due to an increase in motivation towards health and regular contact with health professionals. However, there is limited evidence for the utility of the TM model in predicting or promoting behaviour change. What does this study add? Two groups of women emerged from our study: the women who had experienced difficulties in conceiving and had received fertility treatment, and those who had conceived without intervention. The former group's experience of pregnancy was characterized by a sense of vulnerability and anxiety over sustaining the pregnancy which influenced every choice they made about their diet and physical activity. For the latter group, decisions about diet and physical activity were made immediately upon discovering their pregnancy, based upon a combination of automatic judgements, physical sensations, and perceptions of what is normal or 'good' for pregnancy. Among women with relatively trouble-free conception and pregnancy experiences, the necessary conditions may not be present to create a 'teachable moment'. This is due to a combination of a reliance on non-reflective decision-making, perception of low risk, and little change in affective response or self-concept.

False identification of other microorganisms as Staphylococcus aureus in Southern Nigeria

Purpose: Staphylococcus aureus is the causative agent of many infections and the advent MRSA has drawn much attention to it. However, some organisms have been noted to be wrongly identified as S. aureus through phenotypic identifications leading to wrong treatment of infections. This study is therefore undertaken to evaluate the rate of false identification of other organisms as S. aureus in Southern Nigeria. Methods: 507 microorganisms which have been previously identified as S. aureus in 8 States in Southern Nigeria through characteristic morphology on blood agar, Gram staining, growth and fermentation on Mannitol Salt Agar and coagulase formation were collected. All the isolates were identified in this study through sequencing of 16S rRNA and detection of spa gene. The percentages of true and false identities were determined. Results: Of the 507 isolates previously identified as S. aureus, only 54 (11 %) were confirmed as S. aureus while the rest were coagulase negative Staphylococci (85 % misidentification rate), Bacillus sp. (12 % misidentification rate), and Brevibacterium sp. (3 % misidentification rate). Conclusion: A high rate of false positive identification of S. aureus which could lead to the misuse of antibiotics in emergency situation has been identified in this study. The use of standard methods for the identification of S. aureus at all times is highly recommended.