PubMed · 13180797
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T B NOBLE. 1954. Sigmoid fixation.. https://doi.org/10.1016/s0002-9610(54)90513-9
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The putative oncogene, integrin-linked kinase (ILK) is a protein serine/threonine kinase that has been reported to regulate a number of biological properties including anchorage-independent cell cycle progression, tumour cell invasion and apoptosis. Overexpression of ILK has been documented in a wide variety of human malignancies including Ewing's sarcoma (ES), primitive neural ectodermal tumours (PNETs) and prostate tumours (PT). We recently reported that ILK signalling was also dysregulated in patients with the genetic condition familial adenomatous polyposis (FAP), a precursor to colon cancer. In this study, we extended our previous work by investigating the ILK-signalling pathway in sporadic human colon cancer and representative lymph node metastases. The data indicate that the ILK protein is significantly hyperexpressed in malignant acini in relation to normal crypts. Moreover, overexpression of ILK not only coincided with increased MBP phosphotransferase activity but as well with effects on downstream targets like GSK3beta. Based upon the presented data, we propose that ILK signalling is dysregulated early during the development of human colon cancer, and that selective inhibition of this molecule alone or in combination with the standard therapeutic modality might be a more effective means of treating colon cancer.
BACKGROUND: Extracting features from the colonoscopic images is essential for getting the features, which characterizes the properties of the colon. The features are employed in the computer-assisted diagnosis of colonoscopic images to assist the physician in detecting the colon status. METHODS: Endoscopic images contain rich texture and color information. Novel schemes are developed to extract new texture features from the texture spectra in the chromatic and achromatic domains, and color features for a selected region of interest from each color component histogram of the colonoscopic images. These features are reduced in size using Principal Component Analysis (PCA) and are evaluated using Backpropagation Neural Network (BPNN). RESULTS: Features extracted from endoscopic images were tested to classify the colon status as either normal or abnormal. The classification results obtained show the features' capability for classifying the colon's status. The average classification accuracy, which is using hybrid of the texture and color features with PCA (tau = 1%), is 97.72%. It is higher than the average classification accuracy using only texture (96.96%, tau = 1%) or color (90.52%, tau = 1%) features. CONCLUSION: In conclusion, novel methods for extracting new texture- and color-based features from the colonoscopic images to classify the colon status have been proposed. A new approach using PCA in conjunction with BPNN for evaluating the features has also been proposed. The preliminary test results support the feasibility of the proposed method.
The effect of particle size on the percent drug absorbed is computationally modeled for controlled-release dosage forms that deliver drug particles to the colon. The relative benefit of reducing particle size is mapped on a diagram of the drug's absorption rate constant (estimated from rat intestinal perfusion, CACO-2 or human intubation permeation rates) versus the drug's solubility. Some drugs fall into a limit of high percentage absorption even with large particles such that particle size reduction has little impact. Another group of drugs is solubility limited such that even with small particles, absorption is negligible. Between the two regions, only drugs with sufficiently high absorption rates are influenced by the drug dissolution rate and thereby the particle size. The size of this region is a function of dosing rate. Comparisons between calculated particle size effects on colon absorption as a function of colon volume suggest caution when using animal models to predict bioavailability from colonic drug delivery. This volume dependence also suggests that the particle size influence will vary as a function of the digestive cycle.