971 resultados para Early Detection of Cancer
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Cisplatin resistance remains one of the major obstacles when treating epithelial ovarian cancer. Because oxaliplatin and nedaplatin are effective against cisplatin-resistant ovarian cancer in clinical trials and signal transducer and activator of transcription 3 (STAT3) is associated with cisplatin resistance, we investigated whether overcoming cisplatin resistance by oxaliplatin and nedaplatin was associated with the STAT3 pathway in ovarian cancer. Alamar blue, clonogenic, and wound healing assays, and Western blot analysis were used to compare the effects of platinum drugs in SKOV-3 cells. At an equitoxic dose, oxaliplatin and nedaplatin exhibited similar inhibitory effects on colony-forming ability and greater inhibition on cell motility than cisplatin in ovarian cancer. Early in the time course of drug administration, cisplatin increased the expression of pSTAT3 (Tyr705), STAT3α, VEGF, survivin, and Bcl-XL, while oxaliplatin and nedaplatin exhibited the opposite effects, and upregulated pSTAT3 (Ser727) and STAT3β. The STAT3 pathway responded early to platinum drugs associated with cisplatin resistance in epithelial ovarian cancer and provided a rationale for new therapeutic strategies to reverse cisplatin resistance.
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Autism is a developmental disorder that is characterized by abnonnal social interactions and communications as well as repetitive and restricted activities and interests. There is evidence of a genetic component, as 5% of younger siblings are diagnosed if their older sibling has been diagnosed. Autism is generally not diagnosed until age 3 at the earliest, yet it has been shown that early intervention for children with autism can greatly increase their functioning. Because of this, it is important that symptoms of autism are identified as early as possible so that diagnosis can occur as soon as possible to allow these children the earliest intervention. This thesis was divided into two parts. The first looked at the psychometrics of two proposed measures, the Parent Observation Checklist (POC), administered monthly, and the Infant Behavior Summary Evaluation (mSE), administered bimonthly, to see if they can be used with the infant population to identify autistic symptoms in infants who are at high risk for autism or related problems because they have an older sibling with autism. Study 1 reported acceptable psychometric properties of both the POC and IBSE in terms of test-retest reliability, internal consistency, construct validity and predictive validity. These results provide preliminary evidence that parent report measures can help to detect early symptoms of ASD in infants. The POC was shown to differentiate infants who were diagnosed from a matched group that was not diagnosed by 3 years of age. The second part of this thesis involved a telephone interview of parents who reported developmental and/or behavior problems in their high-risk infants that may be early signs of Autism Spectrum Disorder (ASD). During the interview, a service questionnaire was administered to see what interventions (including strategies recommended by the researchers) their at risk infants and affected older siblings were receiving, how satisfied the parents were with them and how effective they felt the interventions were. 3 Study 2 also yielded promising results. Parents utilized a variety of services for at risk infants and children with ASD. The interventions included empirically validated early intervention (e.g., ABA) to non-empirically validated treatments (e.g., diet therapy). The large number of nonempirically validated treatments parents used was surprising, yet parents reported being involved and satisfied, and thought that the services were effective. Parents' perceptions of their stress levels went down slightly and feelings of competence rose when they accessed services for their infants. Overall, the results of this thesis provide new evidence that parent-report methods hold promise as early detection instruments for ASD in at-risk infants. More research is needed to further validate these instruments as well as to understand the variables related to the parents' choice of early intervention for their at risk and affected children.
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MicroRNAs (miRNAs) are a class of short (similar to 22nt), single stranded RNA molecules that function as post-transcriptional regulators of gene expression. MiRNAs can regulate a variety of important biological pathways, including: cellular proliferation, differentiation and apoptosis. Profiling of miRNA expression patterns was shown to be more useful than the equivalent mRNA profiles for characterizing poorly differentiated tumours. As such, miRNA expression "signatures" are expected to offer serious potential for diagnosing and prognosing cancers of any provenance. The aim of this study was to investigate the potential of using deregulation of urinary miRNAs in order to detect Prostate Cancer (PCa) among Benign Prostatic Hyperplasia (BPH). To identify the miRNA signatures specific for PCa, miRNA expression profiling of 8 PCa patients, 12 BPH patients and 10 healthy males was carried out using whole genome expression profiling. Differential expression of two individual miRNAs between healthy males and BPH patients was detected and found to possibly target genes related to PCa development and progression. The sensitivity and specificity of miR-1825 for detecting PCa among BPH individuals was found to be 60% and 69%, respectively. Whereas, the sensitivity and specificity of miR-484 were 80% and 19%, respectively. Additionally, the sensitivity and specificity for miR-1825/484 in tandem were 45% and 75%, respectively. The proposed PCa miRNA signatures may therefore be of great value for the accurate diagnosis of PCa and BPH. This exploratory study has identified several possible targets that merit further investigation towards the development and validation of diagnostically useful, non-invasive, urine-based tests that might not only help diagnose PCa but also possibly help differentiate it from BPH.
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A method for computer- aided diagnosis of micro calcification clusters in mammograms images presented . Micro calcification clus.eni which are an early sign of bread cancer appear as isolated bright spots in mammograms. Therefore they correspond to local maxima of the image. The local maxima of the image is lint detected and they are ranked according to it higher-order statistical test performed over the sub band domain data
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Active microwave imaging is explored as an imaging modality for early detection of breast cancer. When exposed to microwaves, breast tumor exhibits electrical properties that are significantly different from that of healthy breast tissues. The two approaches of active microwave imaging — confocal microwave technique with measured reflected signals and microwave tomographic imaging with measured scattered signals are addressed here. Normal and malignant breast tissue samples of same person are subjected to study within 30 minutes of mastectomy. Corn syrup is used as coupling medium, as its dielectric parameters show good match with that of the normal breast tissue samples. As bandwidth of the transmitter is an important aspect in the time domain confocal microwave imaging approach, wideband bowtie antenna having 2:1 VSWR bandwidth of 46% is designed for the transmission and reception of microwave signals. Same antenna is used for microwave tomographic imaging too at the frequency of 3000 MHz. Experimentally obtained time domain results are substantiated by finite difference time domain (FDTD) analysis. 2-D tomographic images are reconstructed with the collected scattered data using distorted Born iterative method. Variations of dielectric permittivity in breast samples are distinguishable from the obtained permittivity profiles.
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Cancer treatment is most effective when it is detected early and the progress in treatment will be closely related to the ability to reduce the proportion of misses in the cancer detection task. The effectiveness of algorithms for detecting cancers can be greatly increased if these algorithms work synergistically with those for characterizing normal mammograms. This research work combines computerized image analysis techniques and neural networks to separate out some fraction of the normal mammograms with extremely high reliability, based on normal tissue identification and removal. The presence of clustered microcalcifications is one of the most important and sometimes the only sign of cancer on a mammogram. 60% to 70% of non-palpable breast carcinoma demonstrates microcalcifications on mammograms [44], [45], [46].WT based techniques are applied on the remaining mammograms, those are obviously abnormal, to detect possible microcalcifications. The goal of this work is to improve the detection performance and throughput of screening-mammography, thus providing a ‘second opinion ‘ to the radiologists. The state-of- the- art DWT computation algorithms are not suitable for practical applications with memory and delay constraints, as it is not a block transfonn. Hence in this work, the development of a Block DWT (BDWT) computational structure having low processing memory requirement has also been taken up.
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The presence of microcalcifications in mammograms can be considered as an early indication of breast cancer. A fastfractal block coding method to model the mammograms fordetecting the presence of microcalcifications is presented in this paper. The conventional fractal image coding method takes enormous amount of time during the fractal block encoding.procedure. In the proposed method, the image is divided intoshade and non shade blocks based on the dynamic range, andonly non shade blocks are encoded using the fractal encodingtechnique. Since the number of image blocks is considerablyreduced in the matching domain search pool, a saving of97.996% of the encoding time is obtained as compared to theconventional fractal coding method, for modeling mammograms.The above developed mammograms are used for detectingmicrocalcifications and a diagnostic efficiency of 85.7% isobtained for the 28 mammograms used.
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In this paper, a novel fast method for modeling mammograms by deterministic fractal coding approach to detect the presence of microcalcifications, which are early signs of breast cancer, is presented. The modeled mammogram obtained using fractal encoding method is visually similar to the original image containing microcalcifications, and therefore, when it is taken out from the original mammogram, the presence of microcalcifications can be enhanced. The limitation of fractal image modeling is the tremendous time required for encoding. In the present work, instead of searching for a matching domain in the entire domain pool of the image, three methods based on mean and variance, dynamic range of the image blocks, and mass center features are used. This reduced the encoding time by a factor of 3, 89, and 13, respectively, in the three methods with respect to the conventional fractal image coding method with quad tree partitioning. The mammograms obtained from The Mammographic Image Analysis Society database (ground truth available) gave a total detection score of 87.6%, 87.6%, 90.5%, and 87.6%, for the conventional and the proposed three methods, respectively.
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Freehand sketching is both a natural and crucial part of design, yet is unsupported by current design automation software. We are working to combine the flexibility and ease of use of paper and pencil with the processing power of a computer to produce a design environment that feels as natural as paper, yet is considerably smarter. One of the most basic steps in accomplishing this is converting the original digitized pen strokes in the sketch into the intended geometric objects using feature point detection and approximation. We demonstrate how multiple sources of information can be combined for feature detection in strokes and apply this technique using two approaches to signal processing, one using simple average based thresholding and a second using scale space.
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BACKGROUND: Non-invasive diagnostic strategies aimed at identifying biomarkers of cancer are of great interest for early cancer detection. Urine is potentially a rich source of volatile organic metabolites (VOMs) that can be used as potential cancer biomarkers. Our aim was to develop a generally reliable, rapid, sensitive, and robust analytical method for screening large numbers of urine samples, resulting in a broad spectrum of native VOMs, as a tool to evaluate the potential of these metabolites in the early diagnosis of cancer. METHODS: To investigate urinary volatile metabolites as potential cancer biomarkers, urine samples from 33 cancer patients (oncological group: 14 leukaemia, 12 colorectal and 7 lymphoma) and 21 healthy (control group, cancer-free) individuals were qualitatively and quantitatively analysed. Dynamic solid-phase microextraction in headspace mode (dHS-SPME) using a carboxenpolydimethylsiloxane (CAR/PDMS) sorbent in combination with GC-qMS-based metabolomics was applied to isolate and identify the volatile metabolites. This method provides a potential non-invasive method for early cancer diagnosis as a first approach. To fulfil this objective, three important dHS-SPME experimental parameters that influence extraction efficiency (fibre coating, extraction time and temperature of sampling) were optimised using a univariate optimisation design. The highest extraction efficiency was obtained when sampling was performed at 501C for 60min using samples with high ionic strengths (17% sodium chloride, wv 1) and under agitation. RESULTS: A total of 82 volatile metabolites belonging to distinct chemical classes were identified in the control and oncological groups. Benzene derivatives, terpenoids and phenols were the most common classes for the oncological group, whereas ketones and sulphur compounds were the main classes that were isolated from the urine headspace of healthy subjects. The results demonstrate that compound concentrations were dramatically different between cancer patients and healthy volunteers. The positive rates of 16 patients among the 82 identified were found to be statistically different (Po0.05). A significant increase in the peak area of 2-methyl3-phenyl-2-propenal, p-cymene, anisole, 4-methyl-phenol and 1,2-dihydro-1,1,6-trimethyl-naphthalene in cancer patients was observed. On average, statistically significant lower abundances of dimethyl disulphide were found in cancer patients. CONCLUSIONS: Gas chromatographic peak areas were submitted to multivariate analysis (principal component analysis and supervised linear discriminant analysis) to visualise clusters within cases and to detect the volatile metabolites that are able to differentiate cancer patients from healthy individuals. Very good discrimination within cancer groups and between cancer and control groups was achieved.
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The aim of this study was to confirm the effectiveness of early physiotherapeutic stimulation for lymphatic flaw progression in patients with breast cancer undergoing axillary dissection This was a randomized experimental study oil 22 patients who underwent lymphoscintigraphy in their arms on two different occasions, firstly without stimulation and secondly after randomization into two groups without physiotherapeutic stimulation (WOPS, n=10) and with physiotherapeutic stimulation (WPS, n=12) The lymphoscintigraphy scan was performed with (99m)Tc-phytate administered into the second interdigital space of the hand, ipsilaterally to the dissected axilla, in three phases dynamic, static, and delayed whole body imaging Physiotherapeutic stimulation was earned out using Foldi's technique In both groups, images from the two examinations of each patient were compared Flow progression was considered positive when, on the second damnation, the radiopharmaceutical reached areas more distant from the injection site Statistical analysis was used to evaluate frequencies, percentages and central trend measurements, and non-parametric tests were conducted Descriptive analysis showed that the WPS and WOPS groups were similar M terms of mean age, weight, height, body mass index and number of lymph nodes removed There were statistically significant associations between physiotherapeutic stimulation and radiopharmaceutical progression at all three phases of the study (p < 0 0001) Early physiotherapeutic stimulation in beast cancer patients undergoing radical axillary dissection is effective, and can therefore be indicated as a preventive measure against lymphedema
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Aims Endometrial cancer is one of the most common cancers in women worldwide, but there is a lack of diagnostic markers for early detection of these tumours. The raf kinase inhibitory protein (RKIP) negatively regulates the Raf/MEK/ERK pathway, and the downregulation of RKIP is associated with tumour progression and metastasis in several human neoplasms. The aim of this study was to assess the expression levels of RKIP in endometrial cancer and determine whether this expression correlates with clinical outcome in these patients.Methods Tissue microarrays constructed using tissue samples from 209 endometrial adenocarcinomas, 49 endometrial polyps and 48 endometrial hyperplasias were analysed for RKIP expression by immunohistochemistry.Results The authors found that RKIP expression decreases significantly during malignant progression of endometrial cancer; it is highly expressed in non-neoplastic tissues (polyps 79.6%; hyperplasias 87.5%) and expressed at very low levels in endometrioid adenocarcinomas (29.7%). No correlations were observed between RKIP expression, clinicopathological data and survival.Conclusion This study demonstrated for the first time that RKIP expression is lost during the carcinogenic evolution of endometrial tumours and that the loss of RKIP expression is associated with a malignant phenotype. Functional studies are needed to address the biological role of RKIP downregulation in endometrial cancer.