A Mouse Homolog of a Human TP53 Germline Mutation Reveals a Lipolytic Activity of p53

1. Download : Download high-res image (96KB)
2. Download : Download full-size image

     

Effects of detergents on catalytic activity of human endometase/matrilysin 2, a putative cancer biomarker

Matrix metalloproteinases (MMPs) are a family of hydrolytic enzymes that play significant roles in development, morphogenesis, inflammation, and cancer invasion. Endometase (matrilysin 2 or MMP-26) is a putative early biomarker for human carcinomas. The effects of the ionic and nonionic detergents on catalytic activity of endometase were investigated. The hydrolytic activity of endometase was detergent concentration dependent, exhibiting a bell-shaped curve with its maximum activity near the critical micelle concentration (CMC) of nonionic detergents tested. The effect of Brij-35 on human gelatinase B (MMP-9), matrilysin (MMP-7), and membrane-type 1 MMP (MT1-MMP) was further explored. Their maximum catalysis was observed near the CMC of Brij-35 (∼ 90 μM). Their IC₅₀ values were above the CMC. The inhibition mechanism of MMP-7, MMP-9, and MT1-MMP by Brij-35 was a mixed type as determined by Dixon’s plot; however, the inhibition mechanism of endometase was noncompetitive with a K_i value of 240 μM. The catalytic activities of MMPs are influenced by detergents. Monomer of detergents may activate and stabilize MMPs to enhance catalysis, but micelle of detergents may sequester enzyme and block the substrate binding site to impede catalysis. Under physiological conditions, a lipid or membrane microenvironment may regulate enzymatic activity.     

Exploration research on the fusion of multimodal spectrum technology to improve performance of rapid diagnosis scheme for thyroid dysfunction

The spectral fusion by Raman spectroscopy and Fourier infrared spectroscopy combined with pattern recognition algorithms is utilized to diagnose thyroid dysfunction serum, and finds the spectral segment with the highest sensitivity to further advance diagnosis speed. Compared with the single infrared spectroscopy or Raman spectroscopy, the proposal can improve the detection accuracy, and can obtain more spectral features, indicating greater differences between thyroid dysfunction and normal serum samples. For discriminating different samples, principal component analysis (PCA) was first used for feature extraction to reduce the dimension of high‐dimension spectral data and spectral fusion. Then, support vector machine (SVM), back propagation neural network, extreme learning machine and learning vector quantization algorithms were employed to establish the discriminant diagnostic models. The accuracy of spectral fusion of the best analytical model PCA‐SVM, single Raman spectral accuracy and single infrared spectral accuracy is 83.48%, 78.26% and 80%, respectively. The accuracy of spectral fusion is higher than the accuracy of single spectrum in five classifiers. And the diagnostic accuracy of spectral fusion in the range of 2000 to 2500 cm^?1 is 81.74%, which greatly improves the sample measure speed and data analysis speed than analysis of full spectra. The results from our study demonstrate that the serum spectral fusion technique combined with multivariate statistical methods have great potential for the screening of thyroid dysfunction.     

Autofluorescence imaging for recurrence detection in skin cancer postoperative scars

This clinical study is a first attempt to use autofluorescence for recurrence diagnosis of skin cancer in postoperative scars. The proposed diagnostic parameter is based on a reduction in scar autofluorescence, evaluated in the green spectral channel. The validity of the method has been tested on 110 postoperative scars from 56 patients suspected of non‐melanoma skin cancer, with eight patients (13 scars) available for the repeated examination. The recurrence diagnosis within a scar has been made after two subsequent autofluorescence check‐ups, representing the temporal difference between the scar autofluorescence amplitudes as a vector. The recognition of recurrence has been discussed to represent the significant deviations from the value of vector angle θ. This new autofluorescence‐based method can be easily integrated into the postoperative monitoring of surgical scars and can help diagnose the recurrence of skin cancer from the early stage of scar development.     

Bladder tissue characterization using probe‐based Raman spectroscopy: Evaluation of tissue heterogeneity and influence on the model prediction

Existing approaches for early‐stage bladder tumor diagnosis largely depend on invasive and time‐consuming procedures, resulting in hospitalization, bleeding, bladder perforation, infection and other health risks for the patient. The reduction of current risk factors, while maintaining or even improving the diagnostic precision, is an underlying factor in clinical instrumentation research. For example, for clinic surveillance of patients with a history of noninvasive bladder tumors real‐time tumor diagnosis can enable immediate laser‐based removal of tumors using flexible cystoscopes in the outpatient clinic. Therefore, novel diagnostic modalities are required that can provide real‐time in vivo tumor diagnosis. Raman spectroscopy provides biochemical information of tissue samples ex vivo and in vivo and without the need for complicated sample preparation and staining procedures. For the past decade there has been a rise in applications to diagnose and characterize early cancer in different organs, such as in head and neck, colon and stomach, but also different pathologies, for example, inflammation and atherosclerotic plaques. Bladder pathology has also been studied but only with little attention to aspects that can influence the diagnosis, such as tissue heterogeneity, data preprocessing and model development. The present study presents a clinical investigative study on bladder biopsies to characterize the tumor grading ex vivo, using a compact fiber probe‐based imaging Raman system, as a crucial step towards in vivo Raman endoscopy. Furthermore, this study presents an evaluation of the tissue heterogeneity of highly fluorescent bladder tissues, and the multivariate statistical analysis for discrimination between nontumor tissue, and low‐ and high‐grade tumor.     

Spontaneous regression of cancer: New insights

Suppression of oncogene expression and of host- or tumour-expressed growth factors and receptors may precipitate spontaneous regression or dormancy in human cancer. Loss of oncogenes necessary for progressive proliferation can lead to differentiation changes. Both natural factors and chemical agents can trigger such a change, and of the naturally occurring agents, growth factors and immunological factors have been most studied. We may find new clues to biological methods of prolonging arrest of cancer, by looking for cytogenetic abnormalities, alterations in oncogene expression and immunocytological composition, in patients showing prolonged dormancy of cancer.