We investigated 48 normal patients and 25 diseased patients using our laser-induced autofluorescence spectra detection system during their regular colonoscopy. The colon and rectum mucosa autofluorescence were excited by 405 nm continue wavelength laser. We observed that cancer or diseased colorectal mucosa, their autofluorescence spectra are significantly different from normal area. The autofluorescence spectra intensity at about 500 nm was been used for our intensity ratio characteristics intensity for our diagnostic algorithm. The intensity ratios of RI-680/I-500 and RI-630/I-500 were performed to identify the detection area. From experimental result we concluded that both intensity ratios of RI-680/I-500 and RI-630/I-500 as guidelines can detect cancerous and polyps disease completely. Our investigation provided some useful insight for laser induced autofluorescence spectra as a diagnosis technique for clinical application.
Difference surface is a topography surface,which is an important tool of studying touch problems.The definition of the difference surface and the meaning of every order parameters(including the 0~(th),the 1~(st),and the 2~(nd) order) is discussed in the papers,In addition,the complete parameters for three global form deviations have been derived mathematically.The topograghy deviations of the spiral bevel gears are explained and characterized with every parameters of the difference surface.Finally,the application of spiral bevel gears on difference surface is introduced in detailed examples.
n this chapter, a new concept learning-based approach is presented for abnormal ECG beat detection to facilitate long-term monitoring of heart patients. The novelty in our approach is the use of complementary concept—"normal" for the learning task. The concept "normal" can be learned by a v-support vector classifier (v-SVC) using only normal ECG beats from aspecific patient to relieve the doctors from annotating the training data beat by beat to train a classifier. The learned model can then be used to detect abnormal beats in the long-term ECG recording of the same patient. We have compared with other methods, including multilayer feedforward neural networks, binary support vector machines, and so forth. Experimental results on MIT/BIH arrhythmia ECG database demonstrate that such a patient-adaptable concept learning model outperforms these classifiers even though they are trained using tens of thousands of ECG beats from a large group of patients.Request access from your librarian to read this chapter's full text.
Administration of chemically synthesized ghrelin (Ghr) peptide has been shown to increase food intake and body adiposity in most species. However, the biological role of endogenous Ghr in the molecular control of energy metabolism is far less understood. Mice deficient for either Ghr or its receptor (the growth hormone secretagogue receptor, GHS-R1a) seem to exhibit enhanced protection against high-fat diet-induced obesity but do not show a substantial metabolic phenotype on a standard diet. Here we present the first mouse mutant lacking both Ghr and the Ghr receptor. We demonstrate that simultaneous genetic disruption of both genes of the Ghr system leads to an enhanced energy metabolism phenotype. Ghr/Ghr receptor double knockout (dKO) mice exhibit decreased body weight, increased energy expenditure, and increased motor activity on a standard diet without exposure to a high caloric environment. Mice on the same genetic background lacking either the Ghr or the Ghr receptor gene did not exhibit such a phenotype on standard chow, thereby confirming earlier reports. No differences in food intake, meal pattern, or lean mass were observed between dKO, Ghr-deficient, Ghr receptor-deficient, and wild-type (WT) control mice. Only dKO showed a slight decrease in body length. In summary, simultaneous deletion of Ghr and its receptor enhances the metabolic phenotype of single gene-deficient mice compared with WT mice, possibly suggesting the existence of additional, as of yet unknown, molecular components of the endogenous Ghr system.
Plasma cell-free DNA levels correlate with disease severity in many conditions. Pretransplant cell-free DNA may risk stratify lung transplant candidates for post-transplant complications.
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