12 resultados para Surgical-adjuvant-breast

em Instituto Politécnico do Porto, Portugal


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The post-surgical period is often critical for infection acquisition. The combination of patient injury and environmental exposure through breached skin add risk to pre-existing conditions such as drug or depressed immunity. Several factors such as the period of hospital staying after surgery, base disease, age, immune system condition, hygiene policies, careless prophylactic drug administration and physical conditions of the healthcare centre may contribute to the acquisition of a nosocomial infection. A purulent wound can become complicated whenever antimicrobial therapy becomes compromised. In this pilot study, we analysed Enterobacteriaceae strains, the most significant gram-negative rods that may occur in post-surgical skin and soft tissue infections (SSTI) presenting reduced β-lactam susceptibility and those presenting extended-spectrum β-lactamases (ESBL). There is little information in our country regarding the relationship between β-lactam susceptibility, ESBL and development of resistant strains of microorganisms in SSTI. Our main results indicate Escherichia coli and Klebsiella spp. are among the most frequent enterobacteria (46% and 30% respectively) with ESBL production in 72% of Enterobacteriaceae isolates from SSTI. Moreover, coinfection occurred extensively, mainly with Pseudomonas aeruginosa and Methicillin-resistant Staphylococcus aureus (18% and 13%, respectively). These results suggest future research to explore if and how these associations are involved in the development of antibiotic resistance.

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A maximização do potencial da abordagem cirúrgica conservadora da axila para o cancro da mama, como um método minimamente invasivo para a avaliação de metastização axilar, visando diminuir a morbilidade associada ao esvaziamento axilar completo, requer um método preciso para avaliação patológica intraoperatória. Esse método não foi ainda estabelecido. Imprints e corte de congelação do gânglio sentinela são os procedimentos comummente utilizados, apesar de uma sensibilidade e especificidade inferior à desejada. Actualmente, novas técnicas estão a ser desenvolvidas, que apesar da sua optimização, ainda não ultrapassam os resultados das utilizadas. Um total de 138 mulheres com cancro da mama, submetidas a cirurgia mamária por abordagem conservadora da axila, cuja utilização de imprints e cortes de congelação foram os métodos de avaliação intraoperatória do gânglio sentinela. Os diagnósticos dados pela observação dos cortes dos fragmentos do exame extemporâneo foram comparados com os obtidos nos cortes histológicos definitivos dos fragmentos fixados em formol e incluídos em parafina. Os resultados obtidos da avaliação do exame extemporâneo demonstraram sensibilidade de 79,1%, especificidade de 96,9%, com uma precisão de 91,4%. Não se obteve correlação entre os resultados do extemporâneo e os parâmetros de caracterização do exame extemporâneo e tumores. Os métodos, imprints e cortes de congelação, actualmente utilizados na nossa instituição apresentam bons resultados, mas a adopção de apenas um ou outro necessita de uma análise mais aprofundada dos dados relativos à metodologia utilizada nos extemporâneos, de forma a verificar a especificidade e sensibilidade individualizadas dos imprints e dos cortes de congelação. Se os imprints se revelarem semelhantes aos cortes de congelação, a sua utilização é preferencial uma vez que acarreta menores custos e são menos morosos. A implementação de novas técnicas será uma metodologia adoptar, pelos benefícios acrescidos, porém mais estudos e a optimização

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Background: An asynchronous eLearning system was developed for radiographers in order to promote a better knowledge about senology and mammography. Objectives: to assess the learners’ satisfaction. Methods: Target population included radiographers and radiogr aphy students, in order to assess eLearning satisfaction according to different experience levels in breast imaging. Satisfaction was measured through a questionnaire developed especially for eLearning systems, using a seven - point Likert scale. Main topics related are content, interface, personalization and learning community. Results: Overall, 85% of learners were satisfied with the course and 87,5% considered that the course is successful. Main areas that were evaluated by most learners in a positive way were interface and content (between six and seven - point); on the other hand, learning community presented a wider distribution of answers . Conclusions: The course provides an overall high degree of learner satisfaction, thus providing more effective knowle dge gain on breast imaging for radiographers.

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Tamoxifen is a selective estrogen receptor modulator that is used as an adjuvant and/or chemotherapeutic agent for the treatment of all stages of hormone-dependent breast cancer. Currently there is a deep interest in the study of tamoxifen biotransformation and identification of metabolites since they can significantly contribute to the overall pharmacological or adverse effects of the drug. Accordingly, the study of the electrochemical behavior of tamoxifen in aqueous solution is reported. To clarify the occurring oxidative process and to assess the influence of the functional groups on the oxidation mechanism, the voltammetric assessment was extended to the study of tamoxifen’s analogues (E)-tamoxifen and dihydrotamoxifen, and to its main phase I oxidative metabolite, N-desmethyl tamoxifen. The data found shows that the oxidative processes occurring in tamoxifen are essentially related with the two chemical moieties present in the molecule: the substituted aromatic nucleus and the tertiary amine group. Moreover, the results obtained suggest that the ethylenic linkage is not critical for tamoxifen’s oxidation although it could play an important role in the course of the oxidation process. These results could contribute to highlight some remaining questions regarding tamoxifen’s metabolic behavior and to the development of new analytical strategies, based on electrochemical approaches.

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Human epidermal growth factor receptor 2 (HER2) is a breast cancer biomarker that plays a major role in promoting breast cancer cell proliferation and malignant growth. The extracellular domain (ECD) of HER2 can be shed into the blood stream and its concentration is measurable in the serum fraction of blood. In this work an electrochemical immunosensor for the analysis of HER2 ECD in human serum samples was developed. To achieve this goal a screen-printed carbon electrode, modified with gold nanoparticles, was used as transducer surface. A sandwich immunoassay, using two monoclonal antibodies, was employed and the detection of the antibody–antigen interaction was performed through the analysis of an enzymatic reaction product by linear sweep voltammetry. Using the optimized experimental conditions the calibration curve (ip vs. log[HER2 ECD]) was established between 15 and 100 ng/mL and a limit of detection (LOD) of 4.4 ng/mL was achieved. These results indicate that the developed immunosensor could be a promising tool in breast cancer diagnostics, patient follow-up and monitoring of metastatic breast cancer since it allows quantification in a useful concentration range and has an LOD below the established cut-off value (15 ng/mL).

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Background: Mammography is considered the best imaging technique for breast cancer screening, and the radiographer plays an important role in its performance. Therefore, continuing education is critical to improving the performance of these professionals and thus providing better health care services. Objective: Our goal was to develop an e-learning course on breast imaging for radiographers, assessing its efficacy , effectiveness, and user satisfaction. Methods: A stratified randomized controlled trial was performed with radiographers and radiology students who already had mammography training, using pre- and post-knowledge tests, and satisfaction questionnaires. The primary outcome was the improvement in test results (percentage of correct answers), using intention-to-treat and per-protocol analysis. Results: A total of 54 participants were assigned to the intervention (20 students plus 34 radiographers) with 53 controls (19+34). The intervention was completed by 40 participants (11+29), with 4 (2+2) discontinued interventions, and 10 (7+3) lost to follow-up. Differences in the primary outcome were found between intervention and control: 21 versus 4 percentage points (pp), P<.001. Stratified analysis showed effect in radiographers (23 pp vs 4 pp; P=.004) but was unclear in students (18 pp vs 5 pp; P=.098). Nonetheless, differences in students’ posttest results were found (88% vs 63%; P=.003), which were absent in pretest (63% vs 63%; P=.106). The per-protocol analysis showed a higher effect (26 pp vs 2 pp; P<.001), both in students (25 pp vs 3 pp; P=.004) and radiographers (27 pp vs 2 pp; P<.001). Overall, 85% were satisfied with the course, and 88% considered it successful. Conclusions: This e-learning course is effective, especially for radiographers, which highlights the need for continuing education.

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More than ever, there is an increase of the number of decision support methods and computer aided diagnostic systems applied to various areas of medicine. In breast cancer research, many works have been done in order to reduce false-positives when used as a double reading method. In this study, we aimed to present a set of data mining techniques that were applied to approach a decision support system in the area of breast cancer diagnosis. This method is geared to assist clinical practice in identifying mammographic findings such as microcalcifications, masses and even normal tissues, in order to avoid misdiagnosis. In this work a reliable database was used, with 410 images from about 115 patients, containing previous reviews performed by radiologists as microcalcifications, masses and also normal tissue findings. Throughout this work, two feature extraction techniques were used: the gray level co-occurrence matrix and the gray level run length matrix. For classification purposes, we considered various scenarios according to different distinct patterns of injuries and several classifiers in order to distinguish the best performance in each case described. The many classifiers used were Naïve Bayes, Support Vector Machines, k-nearest Neighbors and Decision Trees (J48 and Random Forests). The results in distinguishing mammographic findings revealed great percentages of PPV and very good accuracy values. Furthermore, it also presented other related results of classification of breast density and BI-RADS® scale. The best predictive method found for all tested groups was the Random Forest classifier, and the best performance has been achieved through the distinction of microcalcifications. The conclusions based on the several tested scenarios represent a new perspective in breast cancer diagnosis using data mining techniques.

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This work presents the development of a low cost sensor device for the diagnosis of breast cancer in point-of-care, made with new synthetic biomimetic materials inside plasticized poly(vinyl chloride), PVC, membranes, for subsequent potentiometric detection. This concept was applied to target a conventional biomarker in breast cancer: Breast Cancer Antigen (CA15-3). The new biomimetic material was obtained by molecularly-imprinted technology. In this, a plastic antibody was obtained by polymerizing around the biomarker that acted as an obstacle to the growth of the polymeric matrix. The imprinted polymer was specifically synthetized by electropolymerization on an FTO conductive glass, by using cyclic voltammetry, including 40 cycles within -0.2 and 1.0 V. The reaction used for the polymerization included monomer (pyrrol, 5.0×10-3 mol/L) and protein (CA15-3, 100U/mL), all prepared in phosphate buffer saline (PBS), with a pH of 7.2 and 1% of ethylene glycol. The biomarker was removed from the imprinted sites by proteolytic action of proteinase K. The biomimetic material was employed in the construction of potentiometric sensors and tested with regard to its affinity and selectivity for binding CA15-3, by checking the analytical performance of the obtained electrodes. For this purpose, the biomimetic material was dispersed in plasticized PVC membranes, including or not a lipophilic ionic additive, and applied on a solid conductive support of graphite. The analytical behaviour was evaluated in buffer and in synthetic serum, with regard to linear range, limit of detection, repeatability, and reproducibility. This antibody-like material was tested in synthetic serum, and good results were obtained. The best devices were able to detect 5 times less CA15-3 than that required in clinical use. Selectivity assays were also performed, showing that the various serum components did not interfere with this biomarker. Overall, the potentiometric-based methods showed several advantages compared to other methods reported in the literature. The analytical process was simple, providing fast responses for a reduced amount of analyte, with low cost and feasible miniaturization. It also allowed the detection of a wide range of concentrations, diminishing the required efforts in previous sample pre-treating stages.

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To improve surgical safety, and to reduce the mortality and surgical complications incidence, the World Health Organization (WHO) developed the Surgical Safety Checklist (SSC). The SSC is a support of information that aids health professionals to reduce the number of complications, induction of anaesthesia, period before skin incision and period before leaving the operating room (OR). The SSC was tested in several countries of the world and their results shown that after introduction of the SSC the incidence of patient complication lowered from 11.0% to 7.0% (P<0.001), the rate of death declined from 1.5% to 0.8% (P = 0.003) and the nurses recognized that patients identity was more often con rmed (81.6% to 94.2%, P<0.01) in many institutions. Recently the SSC was also implemented in Portuguese hospitals, which led us to its study in the real clinical environment. An observational study was performed: several health professionals were observed and interviewed, to understand the functioning of the SSC in an OR, during the clinical routine. The objective of this study was to understand the current use of the SSC, and how it may be improved in terms of usability, taking advantage of the technological advancements such as mobile applications. During two days were observed 14 surgeries, only 2 surgeries met the requirements for the three phases of the SSC, as de ned by the WHO. Of the remaining 12 observed surgeries, 9 surgeries completed the last phase at the correct time. It was also observed that only in 2 surgeries all the phases of the SSC were read aloud to the team and that, in 7 surgeries, several items were read aloud and answered but no one was checking the SSC, only after the end of the phase. The observational study results disclose that several health professionals do not meet with rules of the WHO manual. This study demonstrates that it is urgent to change the mindset of health professionals, and that di erent features in the SSC may be useful to make it more easy to use. With the results of the observational study, a SSC application proposal was developed with new functionalities to improve and aid the health professional in its use. In this application the user can chose between a SSC already created to a speci c surgery or to create a new SSC, adding and adapting some questions from the WHO standard. To create a new SSC, the application is connected to an online questionnaire builder (JotForm). The choice for this online questionnaire builder went through three essential characteristics: number of types of questions, mainly checkbox, radio button and text; the possibility of to create sections inside sections and the API. In addition, in this proposal the improvements are focused in forcing the user to focus in the work ow of the SSC and to save the input timestamps and any actions made by them. Therefore, the following features was implemented to achieve that goal: display one item of the SSC at a time; display the stage where the SSC is; do not allow going back to the previous step; do not allow going forward to the next item if the current is not lled; do not allow going forward to the next item if the time it took to ll the item was too short and log any action made by the user.

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Human exposure to persistent organic pollutants (POPs) is a certainty, even to long banned pesticides like o,p′-dichlorodiphenyltrichloroethane (o,p′-DDT), and its metabolites p,p′-dichlorodiphenyldichloroethylene (p,p′-DDE), and p,p′-dichlorodiphenyldichloroethane (p,p′-DDD). POPs are known to be particularly toxic and have been associated with endocrine-disrupting effects in several mammals, including humans even at very low doses. As environmental estrogens, they could play a critical role in carcinogenesis, such as in breast cancer. With the purpose of evaluating their effect on breast cancer biology, o,p′-DDT, p,p′-DDE, and p,p′-DDD (50–1000 nM) were tested on two human breast adenocarcinoma cell lines: MCF-7 expressing estrogen receptor (ER) α and MDA-MB-231 negative for ERα, regarding cell proliferation and viability in addition to their invasive potential. Cell proliferation and viability were not equally affected by these compounds. In MCF-7 cells, the compounds were able to decrease cell proliferation and viability. On the other hand, no evident response was observed in treated MDA-MB-231 cells. Concerning the invasive potential, the less invasive cell line, MCF-7, had its invasion potential significantly induced, while the more invasive cell line MDA-MB-231, had its invasion potential dramatically reduced in the presence of the tested compounds. Altogether, the results showed that these compounds were able to modulate several cancer-related processes, namely in breast cancer cell lines, and underline the relevance of POP exposure to the risk of cancer development and progression, unraveling distinct pathways of action of these compounds on tumor cell biology.

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Allied to an epidemiological study of population of the Senology Unit of Braga’s Hospital that have been diagnosed with malignant breast cancer, we describe the progression in time of repeated measurements of tumor marker Carcinoembryonic antigen (CEA). Our main purpose is to describe the progression of this tumor marker as a function of possible risk factors and, hence, to understand how these risk factors influences that progression. The response variable, values of CEA, was analyzed making use of longitudinal models, testing for different correlation structures. The same covariates used in a previous survival analysis were considered in the longitudinal model. The reference time used was time from diagnose until death from breast cancer. For diagnostic of the models fitted we have used empirical and theoretical variograms. To evaluate the fixed term of the longitudinal model we have tested for a changing point on the effect of time on the tumor marker progression. A longitudinal model was also fitted only to the subset of patients that died from breast cancer, using the reference time as time from date of death until blood test.

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High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.