980 resultados para endometrial neoplasia


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Long-term consumption of a high glycaemic index (GI) or glycaemic load (GL) diet may lead to chronic hyperinsulinaemia, which is a potential risk factor for cancer. To date, many studies have examined the association between GI, GL and cancer risk, although results have been inconsistent, therefore our objective was to conduct a systematic review of the literature. Medline and Embase were systematically searched using terms for GI, GL and cancer to identify studies published before December 2007. Random effects meta-analyses were performed for endometrial cancer, combining maximally adjusted results that compared risk for those in the highest versus the lowest category of intake. Separate analysis examined risk by body mass index categories. Five studies examining GI and/or GL intake and endometrial cancer risk were identified. Pooled effect estimates for endometrial cancer showed an increased risk for high GL consumers (RR 1.20; 95% CI: 1.06-1.37), further elevated in obese women (RR 1.54; 95% CI: 1.18-2.03). No significant associations were observed for GI. Only two studies examined ovarian cancer and therefore no meta-analysis was performed, but results indicate positive associations for GL also. A high GL, but not a high GI, diet is positively associated with the risk of endometrial cancer, particularly among obese women. © 2008 Cancer Research UK All rights reserved.

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Background: The work in this study appraised photodynamic treatment (PDT) as a treatment method for vulval intraepithelial neoplasia (VIN) using a novel bioadhesive patch to deliver aminolevulinic acid. An analysis of changes in expression of apoptotic and cell cycle proteins (p53, p21, Mdm2, Blc-2, Bax, Ki-67) in response to PDT was evaluated. Methods: PDT was performed using non-laser light, either as a one or two-cycle treatment, with clinical and pathological assessment following after 6 weeks. Twenty-three patients with 25 VIN lesions underwent 49 cycles of PDT Patches were designed to conform to uneven vulval skin and contained 38 mg cm(-2) aminolevulinic acid. Assessment was carried out at 6 weeks post-treatment. Patient-based treatment assessment, along with clinical and pathological changes, were monitored. Immunohistochemical staining was used to elucidate a possible biomolecular basis for induced cellular changes. Results: Most patients (52%) reported a symptomatic response, with normal pathology restored in 38% of lesions. The patch was easy to apply and remove, causing minimal discomfort. Fluorescence inspection confirmed protoporphyrin accumulation. Pain during implementation of PDT was problematic, necessitating some form of local analgesia. Changes in expression of cell cycle and apoptotic-related proteins suggested involvement of apoptotic pathways. Down regulation of p21 and inverse changes in Bcl-2 and Bax were key findings. Conclusion: Treatment of VIN lesions using a novel bioadhesive patch induced changes in cell cycle and apoptotic proteins in response to PDT with possible utilisation of apoptotic pathways. The efficacy of PDT in treating VIN could be improved by a better understanding of these apoptotic mechanisms, the influence of factors, such as HPV status, and of the need for effective pain management.

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This paper introduces an automated computer- assisted system for the diagnosis of cervical intraepithelial neoplasia (CIN) using ultra-large cervical histological digital slides. The system contains two parts: the segmentation of squamous epithelium and the diagnosis of CIN. For the segmentation, to reduce processing time, a multiresolution method is developed. The squamous epithelium layer is first segmented at a low (2X) resolution. The boundaries are further fine tuned at a higher (20X) resolution. The block-based segmentation method uses robust texture feature vectors in combination with support vector machines (SVMs) to perform classification. Medical rules are finally applied. In testing, segmentation using 31 digital slides achieves 94.25% accuracy. For the diagnosis of CIN, changes in nuclei structure and morphology along lines perpendicular to the main axis of the squamous epithelium are quantified and classified. Using multi-category SVM, perpendicular lines are classified into Normal, CIN I, CIN II, and CIN III. The robustness of the system in term of regional diagnosis is measured against pathologists' diagnoses and inter-observer variability between two pathologists is considered. Initial results suggest that the system has potential as a tool both to assist in pathologists' diagnoses, and in training.

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Background: Observational and epidemiologic data indicate that the use of aspirin reduces the risk of colorectal neoplasia; however, the effects of aspirin in the Lynch syndrome (hereditary nonpolyposis colon cancer) are not known. Resistant starch has been associated with an antineoplastic effect on the colon.

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The p53 family of transcription factors is made up of p53, p63 and p73, which share significant structural homology. In particular, transcriptional complexity and the expression of multiple protein isoforms are an emergent trait of all family members. p63 is the evolutionarily eldest member of the p53 family and the various isoforms have critical roles in the development of stratifying epithelia. Recent results have uncovered additional splice variants, adding to the complexity of the transcriptional architecture of p63. These observations and the emerging extensive interplay between p63 and p53 in development, proliferation and differentiation underline the importance of considering all isoforms and family members in studies of the function of p53 family members.

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Prostatic intraepithelial neoplasia (PIN) diagnosis and grading are affected by uncertainties which arise from the fact that almost all knowledge of PIN histopathology is expressed in concepts, descriptive linguistic terms, and words. A Bayesian belief network (BBN) was therefore used to reduce the problem of uncertainty in diagnostic clue assessment, while still considering the dependences between elements in the reasoning sequence. A shallow network was used with an open-tree topology, with eight first-level descendant nodes for the diagnostic clues (evidence nodes), each independently linked by a conditional probability matrix to a root node containing the diagnostic alternatives (decision node). One of the evidence nodes was based on the tissue architecture and the others were based on cell features. The system was designed to be interactive, in that the histopathologist entered evidence into the network in the form of likelihood ratios for outcomes at each evidence node. The efficiency of the network was tested on a series of 110 prostate specimens, subdivided as follows: 22 cases of non-neoplastic prostate or benign prostatic tissue (NP), 22 PINs of low grade (PINlow), 22 PINs of high grade (PINhigh), 22 prostatic adenocarcinomas with cribriform pattern (PACcri), and 22 prostatic adenocarcinomas with large acinar pattern (PAClgac). The results obtained in the benign and malignant categories showed that the belief for the diagnostic alternatives is very high, the values being in general more than 0.8 and often close to 1.0. When considering the PIN lesions, the network classified and graded most of the cases with high certainty. However, there were some cases which showed values less than 0.8 (13 cases out of 44), thus indicating that there are situations in which the feature changes are intermediate between contiguous categories or grades. Discrepancy between morphological grading and the BBN results was observed in four out of 44 PIN cases: one PINlow was classified as PINhigh and three PINhigh were classified as PINlow. In conclusion, the network can grade PlN lesions and differentiate them from other prostate lesions with certainty. In particular, it offers a descriptive classifier which is readily implemented and which allows the use of linguistic, fuzzy variables.

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Endometrial cancer risk has been directly associated with glycemic load. However, few studies have investigated this link, and the etiological role of specific dietary carbohydrate components remains unclear. Our aim was to investigate associations of carbohydrate intake, glycemic index, and glycemic load with endometrial cancer risk in the US Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Recruitment took place in 1993-2001. Over a median of 9.0 years of follow-up through 2009, 386 women developed endometrial cancer among 36,115 considered in the analysis. Dietary intakes were assessed using a 124-item diet history questionnaire. Cox proportional hazards models were applied to calculate hazard ratios and 95% confidence intervals. Significant inverse associations were detected between endometrial cancer risk and total available carbohydrate intake (hazard ratio (HR) = 0.66, 95% confidence interval (CI): 0.49, 0.90), total sugars intake (HR = 0.71, 95% CI: 0.52, 0.96), and glycemic load (HR = 0.63, 95% CI: 0.46, 0.84) when women in the highest quartile of intake were compared with those in the lowest. These inverse associations were strongest among overweight and obese women. No associations with endometrial cancer risk were observed for glycemic index or dietary fiber. Our findings contrast with previous evidence and suggest that high carbohydrate intakes and glycemic loads are protective against endometrial cancer development. Further clarification of these associations is warranted.

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Malignant tumors metabolize glucose to lactate even in the presence of oxygen (aerobic glycolysis). The metabolic switch from oxidative glycolysis to non-oxidative fermentation of glucose and proteins performed by the tumor cells seems to be associated with TKTL1 and pAkt overexpression. Therefore the aim of the present study was to investigate the expression of TKTL1 and pAkt in human specimens of endometrial cancer as compared to benign endometrium. Additionally, expression of the glucose transporter GLUT1 was also investigated as aerobic glycolysis is associated with an increased need for glucose.