In expression recognition, feature representation is critical for successful recognition since it contains distinctive information of expressions. In this paper, a new approach for representing facial expression featu...In expression recognition, feature representation is critical for successful recognition since it contains distinctive information of expressions. In this paper, a new approach for representing facial expression features is proposed with its objective to describe features in an effective and efficient way in order to improve the recognition performance. The method combines the facial action coding system(FACS) and 'uniform' local binary patterns(LBP) to represent facial expression features from coarse to fine. The facial feature regions are extracted by active shape models(ASM) based on FACS to obtain the gray-level texture. Then, LBP is used to represent expression features for enhancing the discriminant. A facial expression recognition system is developed based on this feature extraction method by using K nearest neighborhood(K-NN) classifier to recognize facial expressions. Finally, experiments are carried out to evaluate this feature extraction method. The significance of removing the unrelated facial regions and enhancing the discrimination ability of expression features in the recognition process is indicated by the results, in addition to its convenience.展开更多
Herein we develop a unique differentiated-uptake strategy capable of efficient and high-purity isolation of genuine drug-resistant(DR)cells from three types of drug-surviving cancer cells,which include paclitaxel-surv...Herein we develop a unique differentiated-uptake strategy capable of efficient and high-purity isolation of genuine drug-resistant(DR)cells from three types of drug-surviving cancer cells,which include paclitaxel-surviving human ovarian OVCAR-3 cancer cells and human lung carcinoma A549/Taxol cells,and doxorubicin-surviving human immortalized myelogenous leukemia K562/ADR cells.By using this strategy which relies on fluorescent glycan nanoparticle(FGNP)-based fluorescence-activated cell sorting(FACS)assays,two subpopulations with distinct fluorescences existing in drug-surviving OVCAR-3 cells were separated,and we found that the lower fluorescence(LF)subpopulation consisted of DR cells,while the higher fluorescence(HF)subpopulation was comprised of non-DR cells.Besides,the DR cells and their progenies were found distinct in their increased expression of drug-resistant genes.More intriguingly,by using the FGNP-based FACS assay to detect DR/non-DR phenotypes,we found that the DR phenotype had a potential to differentiate into the non-DR progeny,which demonstrates the differentiation feature of stem-like cancer cells.Further research disclosed that the assay can quantitatively detect the degree of drug resistance in DR cells,as well as the reversal of drug resistance that are tackled by various therapeutic methods.The strategy thus paves the way to develop theranostic approaches associated with chemotherapy-resistance and cancer stemness.展开更多
基金supported by National Natural Science Foundation of China(No.61273339)
文摘In expression recognition, feature representation is critical for successful recognition since it contains distinctive information of expressions. In this paper, a new approach for representing facial expression features is proposed with its objective to describe features in an effective and efficient way in order to improve the recognition performance. The method combines the facial action coding system(FACS) and 'uniform' local binary patterns(LBP) to represent facial expression features from coarse to fine. The facial feature regions are extracted by active shape models(ASM) based on FACS to obtain the gray-level texture. Then, LBP is used to represent expression features for enhancing the discriminant. A facial expression recognition system is developed based on this feature extraction method by using K nearest neighborhood(K-NN) classifier to recognize facial expressions. Finally, experiments are carried out to evaluate this feature extraction method. The significance of removing the unrelated facial regions and enhancing the discrimination ability of expression features in the recognition process is indicated by the results, in addition to its convenience.
基金supported by the National Natural Science Foundation of China(Nos.21871180 and 81872121)the“Shuguang Program”supported by the Shanghai Education Development Foundation and the Shanghai Municipal Education Commission(No.17SG12)+2 种基金the Program for Professor of Special Appointment(Eastern Scholar)at Shanghai Institutions of Higher Learning(No.SHDP201802)the Science and Technology Commission of Shanghai Municipality(No.18520710300 and 17ZR1404100)the Biomedical Interdisciplinary Research Foundation of SJTU(No.YG2019QNB34).
文摘Herein we develop a unique differentiated-uptake strategy capable of efficient and high-purity isolation of genuine drug-resistant(DR)cells from three types of drug-surviving cancer cells,which include paclitaxel-surviving human ovarian OVCAR-3 cancer cells and human lung carcinoma A549/Taxol cells,and doxorubicin-surviving human immortalized myelogenous leukemia K562/ADR cells.By using this strategy which relies on fluorescent glycan nanoparticle(FGNP)-based fluorescence-activated cell sorting(FACS)assays,two subpopulations with distinct fluorescences existing in drug-surviving OVCAR-3 cells were separated,and we found that the lower fluorescence(LF)subpopulation consisted of DR cells,while the higher fluorescence(HF)subpopulation was comprised of non-DR cells.Besides,the DR cells and their progenies were found distinct in their increased expression of drug-resistant genes.More intriguingly,by using the FGNP-based FACS assay to detect DR/non-DR phenotypes,we found that the DR phenotype had a potential to differentiate into the non-DR progeny,which demonstrates the differentiation feature of stem-like cancer cells.Further research disclosed that the assay can quantitatively detect the degree of drug resistance in DR cells,as well as the reversal of drug resistance that are tackled by various therapeutic methods.The strategy thus paves the way to develop theranostic approaches associated with chemotherapy-resistance and cancer stemness.
