Qualitative evaluation of the training program of the Project P.A.T.H.S. in Hong Kong

2010-2011 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Subjective outcome evaluation of the training program of the Project P.A.T.H.S. based on qualitative findings

2010-2011 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Downregulation of the Gli Transcription Factors Regulator Kif7 Facilitates Cell Survival and Migration of Choriocarcinoma Cells

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p21-Activated Kinases 1, 2 and 4 in Endometrial Cancers: Effects on Clinical Outcomes and Cell Proliferation

p21-activated kinases (Paks) are serine/threonine protein kinases involved in biological events linked to malignant tumor progression. In this study, expression of Pak1, p-Pak2 Ser20, Pak4, pPak4 Ser474 in 21 normal endometrium, 16 hyperplastic endometrium without atypia, 17 atypical complex hyperplasia and 67 endometrial cancers was assessed by immunohistochemistry and correlated with clinicopathological parameters. We also accessed the proliferative role and downstream targets of Pak1 in endometrial cancer. Pak1 was expressed in cytoplasm whereas Pak4 and p-Pak4 were expressed in both cytoplasm and nucleus of endometrial tissues. In normal endometrium, significantly higher Pak1 (P = 0.028) and cytoplasmic p-Pak2 (P = 0.048) expression was detected in proliferative endometrium than secretory endometrium. Pak1, cytoplasmic and nuclear Pak4 and nuclear p-Pak4 was significantly overexpressed in endometrial cancer when compared to atrophic endometrium (all P<0.05). Moreover, type I endometrioid carcinomas showed significantly higher Pak1 expression than type II non-endometrioid carcinomas (P<0.001). On the other hand, Pak1, Pak4 and p-Pak4 expression negatively correlated with histological grade (all P<0.05) while p-Pak2 and cytoplasmic Pak4 expression inversely correlated with myometrial invasion (all P<0.05). Furthermore, patients with endometrial cancers with lower cytoplasmic Pak4 expression showed poorer survival (P = 0.026). Multivariate analysis showed cytoplasmic Pak4 is an independent prognostic factor. Functionally, knockdown of Pak1, but not Pak4, in endometrial cancer cell line led to reduced cell proliferation along with reduced cyclin D1, estrogen receptor (ERα) and progestogen receptor (PR) expression. Significant correlation between Pak1 and PR expression was also detected in clinical samples. Our findings suggest that Pak1 and cytoplasmic p-Pak2 may promote cell proliferation in normal endometrium during menstral cycle. Pak1, cytoplasmic and nuclear Pak4 and nuclear p-Pak4 are involved in the pathogenesis of endometrial cancer especially in postmenopausal women. Pak1 promote endometrial cancer cell proliferation, particular in type I endometrioid carcinoma. Cytoplasmic Pak4 can be potential prognostic marker in endometrial cancer.published_or_final_versio

Stem cell transcription factor NANOG controls cell migration and invasion via dysregulation of E-cadherin and FoxJ1 and contributes to adverse clinical outcome in ovarian cancers

Ovarian cancer is the most lethal of all gynecological malignancies, and the identification of novel prognostic and therapeutic targets for ovarian cancer is crucial. It is believed that only a small subset of cancer cells are endowed with stem cell properties, which are responsible for tumor growth, metastatic progression and recurrence. NANOG is one of the key transcription factors essential for maintaining self-renewal and pluripotency in stem cells. This study investigated the role of NANOG in ovarian carcinogenesis and showed overexpression of NANOG mRNA and protein in the nucleus of ovarian cancers compared with benign ovarian lesions. Increased nuclear NANOG expression was significantly associated with high-grade cancers, serous histological subtypes, reduced chemosensitivity, and poor overall and disease-free survival. Further analysis showed NANOG is an independent prognostic factor for overall and disease-free survival. Moreover, NANOG was highly expressed in ovarian cancer cell lines with metastasis-associated property and in clinical samples of metastatic foci. Stable knockdown of NANOG impeded ovarian cancer cell proliferation, migration and invasion, which was accompanied by an increase in mRNA expression of E-cadherin, caveolin-1, FOXO1, FOXO3a, FOXJ1 and FOXB1. Conversely, ectopic NANOG overexpression enhanced ovarian cancer cell migration and invasion along with decreased E-cadherin, caveolin-1, FOXO1, FOXO3a, FOXJ1 and FOXB1 mRNA expression. Importantly, we found Nanog-mediated cell migration and invasion involved its regulation of E-cadherin and FOXJ1. This is the first report revealing the association between NANOG expression and clinical outcome of patients with ovarian cancers, suggesting NANOG to be a potential prognostic marker and therapeutic molecular target in ovarian cancer.Oncogene advance online publication, 3 September 2012; doi:10.1038/onc.2012.363.postprin

Stakeholders, Green Manufacturing, and Practice Performance: Empirical Evidence from Chinese Fashion Businesses

This study explores the relationship among stakeholders, green manufacturing, and practice performance in the fashion business in China and focuses on assisting companies to enhance environmental awareness and green manufacturing practices. We collect research data by developing questionnaires for various Chinese enterprises. A five-point Likert scale is adopted to enable respondents to indicate the extent to which they agree with the items. Through tests and analyses, the questionnaire is validated as reliable, the structural equation model has a good fitting degree, and hypotheses are proved true. Specifically, corporate stakeholders have a significant positive impact on green manufacturing and practice performance, and green manufacturing has a significant positive impact on practice performance in the context of Chinese fashion businesses. Moreover, corporate stakeholders can have a positive impact on practice performance through green manufacturing. We also propose some policy implications, including implementing compulsive policies and regulations and encouraging and establishing preferential policies, such as tax concessions. Moreover, enterprises should actively strive to improve green manufacturing technology and management level to ensure the smooth implementation of green manufacturing practices. To retain sustained earnings and development, green manufacturing should be the bottom line of involved firms. We also emphasize that the importance of corporate stakeholders should be promoted in consideration of enterprises’ practice performance and future development

Automatic target recognition based on cross-plot

Automatic target recognition that relies on rapid feature extraction of real-time target from photo-realistic imaging will enable efficient identification of target patterns. To achieve this objective, Cross-plots of binary patterns are explored as potential signatures for the observed target by high-speed capture of the crucial spatial features using minimal computational resources. Target recognition was implemented based on the proposed pattern recognition concept and tested rigorously for its precision and recall performance. We conclude that Cross-plotting is able to produce a digital fingerprint of a target that correlates efficiently and effectively to signatures of patterns having its identity in a target repository.Kelvin Kian Loong Wong and Derek Abbot

Modulation of the gene expression of N-methyl-D-aspartate receptor NR2B subunit in the rat neostriatum by a single dose of specific antisense oligodeoxynucleotide

N-methyl-D-aspartate receptors (NRs) are a group of ionotropic glutamate receptors in the brain and they are composed of heteromeric subunits (NR1, NR2A-D and NR3). In the neostriatum, a brain region that is associated with movement in animals, NMDA channels are known to involve in the motor control. Our previous report (Lai et al., 2000, Neuroscience 98, 493-500) has shown that a single dose of antisense oligodeoxynucleotides that are specific to NR1 subunit results in blockage of the gene expression of NR1 as well as NR2A subunits in the neostriatum. In the present study, antisense oligodeoxynucleotides that are specific to NR2B (ANR2B) were then employed as molecular tools to further investigate the molecular interactions of NMDA receptor subunits in the neostriatum. A single dose of ANR2B was injected unilaterally into the rat neostriatum. After one day of injection, no modification of motor behavior was found in the ANR2B-injected rats. The mRNA level of NR2B in the ANR2B-injected neostriatum was found to be decreased (-20.4%) by reverse transcriptase polymerase chain reaction (RT-PCR). However, the mRNA levels of NR1, NR2A, NR2C and NR2D in the ANR2B-treated neostriatum were found to be unchanged. After two days of injection, NR2B immunoreactivity was found to decrease in the ANR2B-treated neostriatum by immunofluorescence (-35.1%). At higher magnification, NR2B immunoreactivity was found to decrease in presumed spiny neurons of the neostriatum (-23.4%). No change in NR1 immunoreactivity was observed. These results indicate that a single dose of ANR2B can successfully block the gene expression of NR2B in neurons of the neostriatum and there is less effect on NR1 and other NR2 subunits. The blockage of the gene expression of NR2B is therefore specific and the present results may provide important implications in applications of antisense in research and in clinical therapy of neurological diseases. © 2001 Elsevier Science Ltd. All rights reserved.link_to_subscribed_fulltex

Training classifiers with shadow features for sensor-based human activity recognition

In this paper, a novel training/testing process for building/using a classification model based on human activity recognition (HAR) is proposed. Traditionally, HAR has been accomplished by a classifier that learns the activities of a person by training with skeletal data obtained from a motion sensor, such as Microsoft Kinect. These skeletal data are the spatial coordinates (x, y, z) of different parts of the human body. The numeric information forms time series, temporal records of movement sequences that can be used for training a classifier. In addition to the spatial features that describe current positions in the skeletal data, new features called ‘shadow features’ are used to improve the supervised learning efficacy of the classifier. Shadow features are inferred from the dynamics of body movements, and thereby modelling the underlying momentum of the performed activities. They provide extra dimensions of information for characterising activities in the classification process, and thereby significantly improve the classification accuracy. Two cases of HAR are tested using a classification model trained with shadow features: one is by using wearable sensor and the other is by a Kinect-based remote sensor. Our experiments can demonstrate the advantages of the new method, which will have an impact on human activity detection research