Group at Liang house [picture].
- Date: 1930
- Type: Still Image
- Full Text: false
- Description: A group of people are standing on the front steps of the Liang house in Camberwell about 1930. At the back is Frederick Tock Liang. In the middle is Thomas Chong, Rita Tock Liang, Ettie Tock Liang and Florence Chong. In front are Dorothy and Ray Chong and Maudie Ping.
- Description: Item held by Gippsland and Regional Studies Collection, Federation University Australia.
- Description: Record generated from title list.
- Description: 22-Apr-96
- Date: 1930
- Type: Still Image
- Full Text: false
- Description: A group of people are standing on the front steps of the Liang house in Camberwell about 1930. At the back is Frederick Tock Liang. In the middle is Thomas Chong, Rita Tock Liang, Ettie Tock Liang and Florence Chong. In front are Dorothy and Ray Chong and Maudie Ping.
- Description: Item held by Gippsland and Regional Studies Collection, Federation University Australia.
- Description: Record generated from title list.
- Description: 22-Apr-96
- Authors: Mestrom, Sanne
- Date: 2012
- Type: Text , Visual art work
- Full Text:
Specific humoral response of hosts with variable schistosomiasis susceptibility
- Driguez, Patrick, McWilliam, Hamish, Gaze, Soraya, Piedrafita, David, Pearson, Mark, Nakajima, Rie, Duke, Mary, Trieu, Angela, Doolan, Denise, Cardoso, Fernanda, Jasinskas, Algis, Gobert, Geoffrey, Felgner, Philip, Loukas, Alex, Meeusen, Els, McManus, Donald
- Authors: Driguez, Patrick , McWilliam, Hamish , Gaze, Soraya , Piedrafita, David , Pearson, Mark , Nakajima, Rie , Duke, Mary , Trieu, Angela , Doolan, Denise , Cardoso, Fernanda , Jasinskas, Algis , Gobert, Geoffrey , Felgner, Philip , Loukas, Alex , Meeusen, Els , McManus, Donald
- Date: 2016
- Type: Text , Journal article
- Relation: Immunology and Cell Biology Vol. 94, no. 1 (2016), p. 52-65
- Full Text:
- Reviewed:
- Description: The schistosome blood flukes are some of the largest global causes of parasitic morbidity. Further study of the specific antibody response during schistosomiasis may yield the vaccines and diagnostics needed to combat this disease. Therefore, for the purposes of antigen discovery, sera and antibody-secreting cell (ASC) probes from semi-permissive rats and sera from susceptible mice were used to screen a schistosome protein microarray. Following Schistosoma japonicum infection, rats had reduced pathology, increased antibody responses and broader antigen recognition profiles compared with mice. With successive infections, rat global serological reactivity and the number of recognized antigens increased. The local antibody response in rat skin and lung, measured with ASC probes, increased after parasite migration and contributed antigen-specific antibodies to the multivalent serological response. In addition, the temporal variation of anti-parasite serum antibodies after infection and reinfection followed patterns that appear related to the antigen driving the response. Among the 29 antigens differentially recognized by the infected hosts were numerous known vaccine candidates, drug targets and several S. japonicum homologs of human schistosomiasis resistance markers - the tegument allergen-like proteins. From this set, we prioritized eight proteins that may prove to be novel schistosome vaccine and diagnostic antigens. © 2016 Australasian Society for Immunology Inc. All rights reserved.
- Authors: Driguez, Patrick , McWilliam, Hamish , Gaze, Soraya , Piedrafita, David , Pearson, Mark , Nakajima, Rie , Duke, Mary , Trieu, Angela , Doolan, Denise , Cardoso, Fernanda , Jasinskas, Algis , Gobert, Geoffrey , Felgner, Philip , Loukas, Alex , Meeusen, Els , McManus, Donald
- Date: 2016
- Type: Text , Journal article
- Relation: Immunology and Cell Biology Vol. 94, no. 1 (2016), p. 52-65
- Full Text:
- Reviewed:
- Description: The schistosome blood flukes are some of the largest global causes of parasitic morbidity. Further study of the specific antibody response during schistosomiasis may yield the vaccines and diagnostics needed to combat this disease. Therefore, for the purposes of antigen discovery, sera and antibody-secreting cell (ASC) probes from semi-permissive rats and sera from susceptible mice were used to screen a schistosome protein microarray. Following Schistosoma japonicum infection, rats had reduced pathology, increased antibody responses and broader antigen recognition profiles compared with mice. With successive infections, rat global serological reactivity and the number of recognized antigens increased. The local antibody response in rat skin and lung, measured with ASC probes, increased after parasite migration and contributed antigen-specific antibodies to the multivalent serological response. In addition, the temporal variation of anti-parasite serum antibodies after infection and reinfection followed patterns that appear related to the antigen driving the response. Among the 29 antigens differentially recognized by the infected hosts were numerous known vaccine candidates, drug targets and several S. japonicum homologs of human schistosomiasis resistance markers - the tegument allergen-like proteins. From this set, we prioritized eight proteins that may prove to be novel schistosome vaccine and diagnostic antigens. © 2016 Australasian Society for Immunology Inc. All rights reserved.
Mandarin DP1-he-DP2 in the subject position
- Authors: Han, Weifeng , Shi, Dingxu
- Date: 2022
- Type: Text , Journal article
- Relation: SKASE Journal of Theoretical Linguistics Vol. 19, no. 1 (2022), p. 43-62
- Full Text:
- Reviewed:
- Description: Recent studies claim that, syntactically, he in DP1-he-DP2 can only be analyzed as a conjunction or as a preposition, but not both, in the subject position in Mandarin. This paper presents both empirical and theoretical arguments against such singular analyses of he. Drawn upon cross-linguistic evidence, we argue that he is open to both a conjunction and a proposition analyses. Under the Merge theory, it is argued that the prepositional phrase (PP) is derived through only EXTERNAL MERGE (EM), while the conjunction phrase (&P) is yielded through EM and then INTERNAL MERGE (IM). Therefore, PP and &P undergo different processes of labelling. The Phase Impenetrability Condition helps explain the topicalization and focus marking issues by the singular analysis of he as a preposition only. This paper illustrates how the same lexical item of he is used for both the conjunction and the comitative structures in Mandarin, and how both structures differ syntactically under the Merge theory. © 2022 Slovak Association for the Study of English. All rights reserved.
- Authors: Han, Weifeng , Shi, Dingxu
- Date: 2022
- Type: Text , Journal article
- Relation: SKASE Journal of Theoretical Linguistics Vol. 19, no. 1 (2022), p. 43-62
- Full Text:
- Reviewed:
- Description: Recent studies claim that, syntactically, he in DP1-he-DP2 can only be analyzed as a conjunction or as a preposition, but not both, in the subject position in Mandarin. This paper presents both empirical and theoretical arguments against such singular analyses of he. Drawn upon cross-linguistic evidence, we argue that he is open to both a conjunction and a proposition analyses. Under the Merge theory, it is argued that the prepositional phrase (PP) is derived through only EXTERNAL MERGE (EM), while the conjunction phrase (&P) is yielded through EM and then INTERNAL MERGE (IM). Therefore, PP and &P undergo different processes of labelling. The Phase Impenetrability Condition helps explain the topicalization and focus marking issues by the singular analysis of he as a preposition only. This paper illustrates how the same lexical item of he is used for both the conjunction and the comitative structures in Mandarin, and how both structures differ syntactically under the Merge theory. © 2022 Slovak Association for the Study of English. All rights reserved.
Hybridizing five neural-metaheuristic paradigms to predict the pillar stress in bord and pillar method
- Zhou, Jian, Chen, Yuxin, Chen, Hui, Khandelwal, Manoj, Monjezi, Masoud, Peng, Kang
- Authors: Zhou, Jian , Chen, Yuxin , Chen, Hui , Khandelwal, Manoj , Monjezi, Masoud , Peng, Kang
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Public Health Vol. 11, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Pillar stability is an important condition for safe work in room-and-pillar mines. The instability of pillars will lead to large-scale collapse hazards, and the accurate estimation of induced stresses at different positions in the pillar is helpful for pillar design and guaranteeing pillar stability. There are many modeling methods to design pillars and evaluate their stability, including empirical and numerical method. However, empirical methods are difficult to be applied to places other than the original environmental characteristics, and numerical methods often simplify the boundary conditions and material properties, which cannot guarantee the stability of the design. Currently, machine learning (ML) algorithms have been successfully applied to pillar stability assessment with higher accuracy. Thus, the study adopted a back-propagation neural network (BPNN) and five elements including the sparrow search algorithm (SSA), gray wolf optimizer (GWO), butterfly optimization algorithm (BOA), tunicate swarm algorithm (TSA), and multi-verse optimizer (MVO). Combining metaheuristic algorithms, five hybrid models were developed to predict the induced stress within the pillar. The weight and threshold of the BPNN model are optimized by metaheuristic algorithms, in which the mean absolute error (MAE) is utilized as the fitness function. A database containing 149 data samples was established, where the input variables were the angle of goafline (A), depth of the working coal seam (H), specific gravity (G), distance of the point from the center of the pillar (C), and distance of the point from goafline (D), and the output variable was the induced stress. Furthermore, the predictive performance of the proposed model is evaluated by five metrics, namely coefficient of determination (R2), root mean squared error (RMSE), variance accounted for (VAF), mean absolute error (MAE), and mean absolute percentage error (MAPE). The results showed that the five hybrid models developed have good prediction performance, especially the GWO-BPNN model performed the best (Training set: R2 = 0.9991, RMSE = 0.1535, VAF = 99.91, MAE = 0.0884, MAPE = 0.6107; Test set: R2 = 0.9983, RMSE = 0.1783, VAF = 99.83, MAE = 0.1230, MAPE = 0.9253). Copyright © 2023 Zhou, Chen, Chen, Khandelwal, Monjezi and Peng.
- Authors: Zhou, Jian , Chen, Yuxin , Chen, Hui , Khandelwal, Manoj , Monjezi, Masoud , Peng, Kang
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Public Health Vol. 11, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Pillar stability is an important condition for safe work in room-and-pillar mines. The instability of pillars will lead to large-scale collapse hazards, and the accurate estimation of induced stresses at different positions in the pillar is helpful for pillar design and guaranteeing pillar stability. There are many modeling methods to design pillars and evaluate their stability, including empirical and numerical method. However, empirical methods are difficult to be applied to places other than the original environmental characteristics, and numerical methods often simplify the boundary conditions and material properties, which cannot guarantee the stability of the design. Currently, machine learning (ML) algorithms have been successfully applied to pillar stability assessment with higher accuracy. Thus, the study adopted a back-propagation neural network (BPNN) and five elements including the sparrow search algorithm (SSA), gray wolf optimizer (GWO), butterfly optimization algorithm (BOA), tunicate swarm algorithm (TSA), and multi-verse optimizer (MVO). Combining metaheuristic algorithms, five hybrid models were developed to predict the induced stress within the pillar. The weight and threshold of the BPNN model are optimized by metaheuristic algorithms, in which the mean absolute error (MAE) is utilized as the fitness function. A database containing 149 data samples was established, where the input variables were the angle of goafline (A), depth of the working coal seam (H), specific gravity (G), distance of the point from the center of the pillar (C), and distance of the point from goafline (D), and the output variable was the induced stress. Furthermore, the predictive performance of the proposed model is evaluated by five metrics, namely coefficient of determination (R2), root mean squared error (RMSE), variance accounted for (VAF), mean absolute error (MAE), and mean absolute percentage error (MAPE). The results showed that the five hybrid models developed have good prediction performance, especially the GWO-BPNN model performed the best (Training set: R2 = 0.9991, RMSE = 0.1535, VAF = 99.91, MAE = 0.0884, MAPE = 0.6107; Test set: R2 = 0.9983, RMSE = 0.1783, VAF = 99.83, MAE = 0.1230, MAPE = 0.9253). Copyright © 2023 Zhou, Chen, Chen, Khandelwal, Monjezi and Peng.
Soil moisture, organic carbon, and nitrogen content prediction with hyperspectral data using regression models
- Datta, Dristi, Paul, Manoranjan, Murshed, Manzur, Teng, Shyh Wei, Schmidtke, Leigh
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2022
- Type: Text , Journal article
- Relation: Sensors (Basel, Switzerland) Vol. 22, no. 20 (2022), p.
- Full Text:
- Reviewed:
- Description: Soil moisture, soil organic carbon, and nitrogen content prediction are considered significant fields of study as they are directly related to plant health and food production. Direct estimation of these soil properties with traditional methods, for example, the oven-drying technique and chemical analysis, is a time and resource-consuming approach and can predict only smaller areas. With the significant development of remote sensing and hyperspectral (HS) imaging technologies, soil moisture, carbon, and nitrogen can be estimated over vast areas. This paper presents a generalized approach to predicting three different essential soil contents using a comprehensive study of various machine learning (ML) models by considering the dimensional reduction in feature spaces. In this study, we have used three popular benchmark HS datasets captured in Germany and Sweden. The efficacy of different ML algorithms is evaluated to predict soil content, and significant improvement is obtained when a specific range of bands is selected. The performance of ML models is further improved by applying principal component analysis (PCA), a dimensional reduction method that works with an unsupervised learning method. The effect of soil temperature on soil moisture prediction is evaluated in this study, and the results show that when the soil temperature is considered with the HS band, the soil moisture prediction accuracy does not improve. However, the combined effect of band selection and feature transformation using PCA significantly enhances the prediction accuracy for soil moisture, carbon, and nitrogen content. This study represents a comprehensive analysis of a wide range of established ML regression models using data preprocessing, effective band selection, and data dimension reduction and attempt to understand which feature combinations provide the best accuracy. The outcomes of several ML models are verified with validation techniques and the best- and worst-case scenarios in terms of soil content are noted. The proposed approach outperforms existing estimation techniques.
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2022
- Type: Text , Journal article
- Relation: Sensors (Basel, Switzerland) Vol. 22, no. 20 (2022), p.
- Full Text:
- Reviewed:
- Description: Soil moisture, soil organic carbon, and nitrogen content prediction are considered significant fields of study as they are directly related to plant health and food production. Direct estimation of these soil properties with traditional methods, for example, the oven-drying technique and chemical analysis, is a time and resource-consuming approach and can predict only smaller areas. With the significant development of remote sensing and hyperspectral (HS) imaging technologies, soil moisture, carbon, and nitrogen can be estimated over vast areas. This paper presents a generalized approach to predicting three different essential soil contents using a comprehensive study of various machine learning (ML) models by considering the dimensional reduction in feature spaces. In this study, we have used three popular benchmark HS datasets captured in Germany and Sweden. The efficacy of different ML algorithms is evaluated to predict soil content, and significant improvement is obtained when a specific range of bands is selected. The performance of ML models is further improved by applying principal component analysis (PCA), a dimensional reduction method that works with an unsupervised learning method. The effect of soil temperature on soil moisture prediction is evaluated in this study, and the results show that when the soil temperature is considered with the HS band, the soil moisture prediction accuracy does not improve. However, the combined effect of band selection and feature transformation using PCA significantly enhances the prediction accuracy for soil moisture, carbon, and nitrogen content. This study represents a comprehensive analysis of a wide range of established ML regression models using data preprocessing, effective band selection, and data dimension reduction and attempt to understand which feature combinations provide the best accuracy. The outcomes of several ML models are verified with validation techniques and the best- and worst-case scenarios in terms of soil content are noted. The proposed approach outperforms existing estimation techniques.
A guide to the short, long and circular RNAs in hypertension and cardiovascular disease
- Prestes, Priscilla, Maier, Michelle, Woods, Bradley, Charchar, Fadi
- Authors: Prestes, Priscilla , Maier, Michelle , Woods, Bradley , Charchar, Fadi
- Date: 2020
- Type: Text , Journal article , Review
- Relation: International Journal of Molecular Sciences Vol. 21, no. 10 (2020)
- Full Text:
- Reviewed:
- Description: Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in adults in developed countries. CVD encompasses many diseased states, including hypertension, coronary artery disease and atherosclerosis. Studies in animal models and human studies have elucidated the contribution of many genetic factors, including non-coding RNAs. Non-coding RNAs are RNAs not translated into protein, involved in gene expression regulation post-transcriptionally and implicated in CVD. Of these, circular RNAs (circRNAs) and microRNAs are relevant. CircRNAs are created by the back-splicing of pre-messenger RNA and have been underexplored as contributors to CVD. These circRNAs may also act as biomarkers of human disease, as they can be extracted from whole blood, plasma, saliva and seminal fluid. CircRNAs have recently been implicated in various disease processes, including hypertension and other cardiovascular disease. This review article will explore the promising and emerging roles of circRNAs as potential biomarkers and therapeutic targets in CVD, in particular hypertension. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Prestes, Priscilla , Maier, Michelle , Woods, Bradley , Charchar, Fadi
- Date: 2020
- Type: Text , Journal article , Review
- Relation: International Journal of Molecular Sciences Vol. 21, no. 10 (2020)
- Full Text:
- Reviewed:
- Description: Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in adults in developed countries. CVD encompasses many diseased states, including hypertension, coronary artery disease and atherosclerosis. Studies in animal models and human studies have elucidated the contribution of many genetic factors, including non-coding RNAs. Non-coding RNAs are RNAs not translated into protein, involved in gene expression regulation post-transcriptionally and implicated in CVD. Of these, circular RNAs (circRNAs) and microRNAs are relevant. CircRNAs are created by the back-splicing of pre-messenger RNA and have been underexplored as contributors to CVD. These circRNAs may also act as biomarkers of human disease, as they can be extracted from whole blood, plasma, saliva and seminal fluid. CircRNAs have recently been implicated in various disease processes, including hypertension and other cardiovascular disease. This review article will explore the promising and emerging roles of circRNAs as potential biomarkers and therapeutic targets in CVD, in particular hypertension. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
A zero-watermarking algorithm for privacy protection in biomedical signals
- Ali, Zulfiqar, Imran, Muhammad, Alsulaiman, Mansour, Zia, Tanveer, Shoaib, Muhammad
- Authors: Ali, Zulfiqar , Imran, Muhammad , Alsulaiman, Mansour , Zia, Tanveer , Shoaib, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 82, no. (2018), p. 290-303
- Full Text:
- Reviewed:
- Description: Confidentiality of health information is indispensable to protect privacy of an individual. However, recent advances in electronic healthcare systems allow transmission of sensitive information through the Internet, which is prone to various vulnerabilities, attacks and may leads to unauthorized disclosure. Such situations may not only create adverse effects for individuals but may also cause severe consequences such as hefty regulatory fines, bad publicity, legal fees, and forensics. To avoid such predicaments, a privacy protected healthcare system is proposed in this study that protects the identity of an individual as well as detects vocal fold disorders. The privacy of the developed healthcare system is based on the proposed zero-watermarking algorithm, which embeds a watermark in a secret key instead of the signals to avoid the distortion in an audio sample. The identity is protected by the generation of its secret shares through visual cryptography. The generated shares are embedded by finding the patterns into the audio with the application of one-dimensional local binary pattern. The proposed zero-watermarking algorithm is evaluated by using audio samples taken from the Massachusetts Eye and Ear Infirmary voice disorder database. Experimental results demonstrate that the proposed algorithm achieves imperceptibility and is reliable in its extraction of identity. In addition, the proposed algorithm does not affect the results of disorder detection and it is robust against noise attacks of various signal-to-noise ratios. © 2017 Elsevier B.V.
- Authors: Ali, Zulfiqar , Imran, Muhammad , Alsulaiman, Mansour , Zia, Tanveer , Shoaib, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 82, no. (2018), p. 290-303
- Full Text:
- Reviewed:
- Description: Confidentiality of health information is indispensable to protect privacy of an individual. However, recent advances in electronic healthcare systems allow transmission of sensitive information through the Internet, which is prone to various vulnerabilities, attacks and may leads to unauthorized disclosure. Such situations may not only create adverse effects for individuals but may also cause severe consequences such as hefty regulatory fines, bad publicity, legal fees, and forensics. To avoid such predicaments, a privacy protected healthcare system is proposed in this study that protects the identity of an individual as well as detects vocal fold disorders. The privacy of the developed healthcare system is based on the proposed zero-watermarking algorithm, which embeds a watermark in a secret key instead of the signals to avoid the distortion in an audio sample. The identity is protected by the generation of its secret shares through visual cryptography. The generated shares are embedded by finding the patterns into the audio with the application of one-dimensional local binary pattern. The proposed zero-watermarking algorithm is evaluated by using audio samples taken from the Massachusetts Eye and Ear Infirmary voice disorder database. Experimental results demonstrate that the proposed algorithm achieves imperceptibility and is reliable in its extraction of identity. In addition, the proposed algorithm does not affect the results of disorder detection and it is robust against noise attacks of various signal-to-noise ratios. © 2017 Elsevier B.V.
High CD26 and low CD94 expression identifies an IL-23 responsive Vδ2+ T Cell subset with a MAIT cell-like transcriptional profile
- Wragg, Kathleen, Tan, Hyon, Kristensen, Anne, Nguyen-Robertson, Catriona, Kelleher, Anthony, Parsons, Matthew, Wheatley, Adam, Berzins, Stuart, Pellicci, Daniel, Kent, Stephen, Juno, Jennifer
- Authors: Wragg, Kathleen , Tan, Hyon , Kristensen, Anne , Nguyen-Robertson, Catriona , Kelleher, Anthony , Parsons, Matthew , Wheatley, Adam , Berzins, Stuart , Pellicci, Daniel , Kent, Stephen , Juno, Jennifer
- Date: 2020
- Type: Text , Journal article
- Relation: Cell Reports Vol. 31, no. 11 (2020), p.
- Full Text:
- Reviewed:
- Description: Vδ2+ T cells play a critical role in immunity to micro-organisms and cancer but exhibit substantial heterogeneity in humans. Here, we demonstrate that CD26 and CD94 define transcriptionally, phenotypically, and functionally distinct Vδ2+ T cell subsets. Despite distinct antigen specificities, CD26hiCD94lo Vδ2+ cells exhibit substantial similarities to CD26hi mucosal-associated invariant T (MAIT) cells, although CD26− Vδ2+ cells exhibit cytotoxic, effector-like profiles. At birth, the Vδ2+Vγ9+ population is dominated by CD26hiCD94lo cells; during adolescence and adulthood, Vδ2+ cells acquire CD94/NKG2A expression and the relative frequency of the CD26hiCD94lo subset declines. Critically, exposure of the CD26hiCD94lo subset to phosphoantigen in the context of interleukin-23 (IL-23) and CD26 engagement drives the acquisition of a cytotoxic program and concurrent loss of the MAIT cell-like phenotype. The ability to modulate the cytotoxic potential of CD26hiCD94lo Vδ2+ cells, combined with their adenosine-binding capacity, may make them ideal targets for immunotherapeutic expansion and adoptive transfer. Wragg et al. identify a population of human gd T cells with striking similarities to MAIT cells. These cells dominate the cord blood Vd2 population and upregulate an effector-like program upon antigen and IL-23 stimulation, providing a potential mechanism by which cytotoxic Vd2 cells may accumulate during adolescence and adulthood. © 2020
- Description: National Health and Medical Research Council, NHMRC
- Authors: Wragg, Kathleen , Tan, Hyon , Kristensen, Anne , Nguyen-Robertson, Catriona , Kelleher, Anthony , Parsons, Matthew , Wheatley, Adam , Berzins, Stuart , Pellicci, Daniel , Kent, Stephen , Juno, Jennifer
- Date: 2020
- Type: Text , Journal article
- Relation: Cell Reports Vol. 31, no. 11 (2020), p.
- Full Text:
- Reviewed:
- Description: Vδ2+ T cells play a critical role in immunity to micro-organisms and cancer but exhibit substantial heterogeneity in humans. Here, we demonstrate that CD26 and CD94 define transcriptionally, phenotypically, and functionally distinct Vδ2+ T cell subsets. Despite distinct antigen specificities, CD26hiCD94lo Vδ2+ cells exhibit substantial similarities to CD26hi mucosal-associated invariant T (MAIT) cells, although CD26− Vδ2+ cells exhibit cytotoxic, effector-like profiles. At birth, the Vδ2+Vγ9+ population is dominated by CD26hiCD94lo cells; during adolescence and adulthood, Vδ2+ cells acquire CD94/NKG2A expression and the relative frequency of the CD26hiCD94lo subset declines. Critically, exposure of the CD26hiCD94lo subset to phosphoantigen in the context of interleukin-23 (IL-23) and CD26 engagement drives the acquisition of a cytotoxic program and concurrent loss of the MAIT cell-like phenotype. The ability to modulate the cytotoxic potential of CD26hiCD94lo Vδ2+ cells, combined with their adenosine-binding capacity, may make them ideal targets for immunotherapeutic expansion and adoptive transfer. Wragg et al. identify a population of human gd T cells with striking similarities to MAIT cells. These cells dominate the cord blood Vd2 population and upregulate an effector-like program upon antigen and IL-23 stimulation, providing a potential mechanism by which cytotoxic Vd2 cells may accumulate during adolescence and adulthood. © 2020
- Description: National Health and Medical Research Council, NHMRC
Interleukin-6 inhibition of peroxisome proliferator-activated receptor alpha expression is mediated by JAK2- and PI3K-induced STAT1/3 in HepG2 hepatocyte cells
- Chew, Guatsiew, Myers, Stephen, Shu-Chien, A. C., Muhammad, Tengku
- Authors: Chew, Guatsiew , Myers, Stephen , Shu-Chien, A. C. , Muhammad, Tengku
- Date: 2014
- Type: Text , Journal article
- Relation: Molecular and Cellular Biochemistry Vol. 388, no. 1-2 (2014), p. 25-37
- Full Text:
- Reviewed:
- Description: Interleukin-6 (IL-6) is the major activator of the acute phase response (APR). One important regulator of IL-6-activated APR is peroxisome proliferator-activated receptor alpha (PPAR
- Authors: Chew, Guatsiew , Myers, Stephen , Shu-Chien, A. C. , Muhammad, Tengku
- Date: 2014
- Type: Text , Journal article
- Relation: Molecular and Cellular Biochemistry Vol. 388, no. 1-2 (2014), p. 25-37
- Full Text:
- Reviewed:
- Description: Interleukin-6 (IL-6) is the major activator of the acute phase response (APR). One important regulator of IL-6-activated APR is peroxisome proliferator-activated receptor alpha (PPAR
Discovery of novel Schistosoma japonicum antigens using a targeted protein microarray approach
- McWilliam, Hamish, Driguez, Patrick, Piedrafita, David, McManus, Donald, Meeusen, Els
- Authors: McWilliam, Hamish , Driguez, Patrick , Piedrafita, David , McManus, Donald , Meeusen, Els
- Date: 2014
- Type: Text , Journal article
- Relation: Parasites and Vectors Vol. 7, no. 1 (2014), p. 1-11
- Full Text:
- Reviewed:
- Description: Background: Novel vaccine candidates against Schistosoma japonicum are required, and antigens present in the vulnerable larval developmental stage are attractive targets. Post-genomic technologies are now available which can contribute to such antigen discovery. Methods. A schistosome-specific protein microarray was probed using the local antibody response against migrating larvae. Antigens were assessed for their novelty and predicted larval expression and host-exposed features. One antigen was further characterised and its sequence and structure were analysed in silico. Real-time polymerase chain reaction was used to analyse transcript expression throughout development, and immunoblotting and enzyme-linked immunosorbent assays employed to determine antigen recognition by antibody samples. Results: Several known and novel antigens were discovered, two of which showed up-regulated transcription in schistosomula. One novel antigen, termed S. japonicum Ly-6-like protein 1 (Sj-L6L-1), was further characterised and shown to share structural and sequence features with the Ly-6 protein family. It was found to be present in the worm tegument and expressed in both the larval and adult worms, but was found to be antigenic only in the lungs that the larvae migrate to and traverse. Conclusions: This study represents a novel approach to vaccine antigen discovery and may contribute to schistosome vaccine development against this important group of human and veterinary pathogens. © 2014 McWilliam et al.; licensee BioMed Central Ltd.
- Authors: McWilliam, Hamish , Driguez, Patrick , Piedrafita, David , McManus, Donald , Meeusen, Els
- Date: 2014
- Type: Text , Journal article
- Relation: Parasites and Vectors Vol. 7, no. 1 (2014), p. 1-11
- Full Text:
- Reviewed:
- Description: Background: Novel vaccine candidates against Schistosoma japonicum are required, and antigens present in the vulnerable larval developmental stage are attractive targets. Post-genomic technologies are now available which can contribute to such antigen discovery. Methods. A schistosome-specific protein microarray was probed using the local antibody response against migrating larvae. Antigens were assessed for their novelty and predicted larval expression and host-exposed features. One antigen was further characterised and its sequence and structure were analysed in silico. Real-time polymerase chain reaction was used to analyse transcript expression throughout development, and immunoblotting and enzyme-linked immunosorbent assays employed to determine antigen recognition by antibody samples. Results: Several known and novel antigens were discovered, two of which showed up-regulated transcription in schistosomula. One novel antigen, termed S. japonicum Ly-6-like protein 1 (Sj-L6L-1), was further characterised and shown to share structural and sequence features with the Ly-6 protein family. It was found to be present in the worm tegument and expressed in both the larval and adult worms, but was found to be antigenic only in the lungs that the larvae migrate to and traverse. Conclusions: This study represents a novel approach to vaccine antigen discovery and may contribute to schistosome vaccine development against this important group of human and veterinary pathogens. © 2014 McWilliam et al.; licensee BioMed Central Ltd.
An investigation of the drivers of social commerce and e-word-of-mouth intentions : elucidating the role of social commerce in e-business
- Goraya, M. Awals, Jing, Zhu, Shareef, Mahmud, Imran, Muhammad, Malik, Aneela, Akram, M. Shakaib
- Authors: Goraya, M. Awals , Jing, Zhu , Shareef, Mahmud , Imran, Muhammad , Malik, Aneela , Akram, M. Shakaib
- Date: 2021
- Type: Text , Journal article
- Relation: Electronic Markets Vol. 31, no. 1 (2021), p. 181-195
- Full Text:
- Reviewed:
- Description: Building on social commerce (s-commerce) perspectives and the trust transfer theory, this study develops a theoretical model that explains the indirect effects of two types of s-commerce attributes (community and platform) on behavioral outcomes (s-commerce intentions and e-Word-of-Mouth (e-WOM) intentions) through trust in community and platform. We analyze data collected from s-commerce users on travel booking websites using structural equation modeling technique. Results confirm that s-commerce intentions and e-WOM intentions are contingent upon s-commerce community and platform attributes. Moreover, the results provide evidence for the mediating effects of trust in community and platform on the relationship between s-commerce attributes and behavioral outcomes. The study provides further insights about the impact of s-commerce experience on s-commerce intention and e-WOM intention. Moreover, this study contributes to s-commerce research and practice by developing and validating the role of s-commerce community and platform attributes in forming consumers’ s-commerce behavioral outcomes. © 2019, Institute of Applied Informatics at University of Leipzig.
- Authors: Goraya, M. Awals , Jing, Zhu , Shareef, Mahmud , Imran, Muhammad , Malik, Aneela , Akram, M. Shakaib
- Date: 2021
- Type: Text , Journal article
- Relation: Electronic Markets Vol. 31, no. 1 (2021), p. 181-195
- Full Text:
- Reviewed:
- Description: Building on social commerce (s-commerce) perspectives and the trust transfer theory, this study develops a theoretical model that explains the indirect effects of two types of s-commerce attributes (community and platform) on behavioral outcomes (s-commerce intentions and e-Word-of-Mouth (e-WOM) intentions) through trust in community and platform. We analyze data collected from s-commerce users on travel booking websites using structural equation modeling technique. Results confirm that s-commerce intentions and e-WOM intentions are contingent upon s-commerce community and platform attributes. Moreover, the results provide evidence for the mediating effects of trust in community and platform on the relationship between s-commerce attributes and behavioral outcomes. The study provides further insights about the impact of s-commerce experience on s-commerce intention and e-WOM intention. Moreover, this study contributes to s-commerce research and practice by developing and validating the role of s-commerce community and platform attributes in forming consumers’ s-commerce behavioral outcomes. © 2019, Institute of Applied Informatics at University of Leipzig.
The molecular epidemiology of influenza in Cambodia
- Authors: Suttie, Annika
- Date: 2019
- Type: Text , Thesis , PhD
- Full Text:
- Description: Avian influenza viruses (AIVs) represent a risk to the health of humans and animals. The prevalence of AIVs in live bird markets in Cambodia is among the highest in the world, being detected in 45.5% of tested poultry in 2015. To better understand the potential risk presented by AIVs, this thesis investigated the genetic characteristics of AIVs circulating in Cambodia between 2014 to 2018; focusing on subtypes that pose the greatest risk to human and animal health (H5, H7 and H9). Highly pathogenic (HP) H5N1 clade 2.3.2.1c viruses and low pathogenic H9N2 BJ/94-like h9-4.2.5 clade viruses were the most frequently detected subtypes, and circulate endemically in Cambodia’s domestic poultry. Co-infections were detected and facilitated the production of two novel reassortant H5N1 AIVs with single genes from H9N2 viruses. Additionally, numerous intrasubtypic reassortment events were detected for H5 and H9 AIVs. This is concerning as reassortment events can rapidly produce novel viruses of public health risk. Phylogenetic analyses showed some genes of the Cambodian H5, H7 and H9 AIVs clustered with zoonotic viruses, suggesting a common origin. There are parallels between H5N1 and H9N2 AIVs detected in Cambodia and Vietnam, likely facilitated through the illegal trade of live poultry and/or the migration of wild birds. Molecular analyses showed H9 AIVs have major markers associated with adaptation to mammals; though during the study period the only human AIV cases were the result of HP H5N1. Molecular markers of resistance to adamantine antivirals was observed in 3% of H5 and 41% of H9 AIVs; however, both subtypes remain susceptible to first line antiviral treatment, neuraminidase inhibitors. The data presented in this thesis demonstrates that circulation of Cambodian AIVs represents a risk for the emergence of novel viruses. Interventions are urgently needed to mitigate the threat posed to poultry and humans.
- Description: Doctor of Philosophy
- Authors: Suttie, Annika
- Date: 2019
- Type: Text , Thesis , PhD
- Full Text:
- Description: Avian influenza viruses (AIVs) represent a risk to the health of humans and animals. The prevalence of AIVs in live bird markets in Cambodia is among the highest in the world, being detected in 45.5% of tested poultry in 2015. To better understand the potential risk presented by AIVs, this thesis investigated the genetic characteristics of AIVs circulating in Cambodia between 2014 to 2018; focusing on subtypes that pose the greatest risk to human and animal health (H5, H7 and H9). Highly pathogenic (HP) H5N1 clade 2.3.2.1c viruses and low pathogenic H9N2 BJ/94-like h9-4.2.5 clade viruses were the most frequently detected subtypes, and circulate endemically in Cambodia’s domestic poultry. Co-infections were detected and facilitated the production of two novel reassortant H5N1 AIVs with single genes from H9N2 viruses. Additionally, numerous intrasubtypic reassortment events were detected for H5 and H9 AIVs. This is concerning as reassortment events can rapidly produce novel viruses of public health risk. Phylogenetic analyses showed some genes of the Cambodian H5, H7 and H9 AIVs clustered with zoonotic viruses, suggesting a common origin. There are parallels between H5N1 and H9N2 AIVs detected in Cambodia and Vietnam, likely facilitated through the illegal trade of live poultry and/or the migration of wild birds. Molecular analyses showed H9 AIVs have major markers associated with adaptation to mammals; though during the study period the only human AIV cases were the result of HP H5N1. Molecular markers of resistance to adamantine antivirals was observed in 3% of H5 and 41% of H9 AIVs; however, both subtypes remain susceptible to first line antiviral treatment, neuraminidase inhibitors. The data presented in this thesis demonstrates that circulation of Cambodian AIVs represents a risk for the emergence of novel viruses. Interventions are urgently needed to mitigate the threat posed to poultry and humans.
- Description: Doctor of Philosophy
Tracing the Pace of COVID-19 research : topic modeling and evolution
- Liu, Jiaying, Nie, Hansong, Li, Shihao, Ren, Jing, Xia, Feng
- Authors: Liu, Jiaying , Nie, Hansong , Li, Shihao , Ren, Jing , Xia, Feng
- Date: 2021
- Type: Text , Journal article
- Relation: Big Data Research Vol. 25, no. (2021), p.
- Full Text:
- Reviewed:
- Description: COVID-19 has been spreading rapidly around the world. With the growing attention on the deadly pandemic, discussions and research on COVID-19 are rapidly increasing to exchange latest findings with the hope to accelerate the pace of finding a cure. As a branch of information technology, artificial intelligence (AI) has greatly expedited the development of human society. In this paper, we investigate and visualize the on-going advancements of early scientific research on COVID-19 from the perspective of AI. By adopting the Latent Dirichlet Allocation (LDA) model, this paper allocates the research articles into 50 key research topics pertinent to COVID-19 according to their abstracts. We present an overview of early studies of the COVID-19 crisis at different scales including referencing/citation behavior, topic variation and their inner interactions. We also identify innovative papers that are regarded as the cornerstones in the development of COVID-19 research. The results unveil the focus of scientific research, thereby giving deep insights into how the academic society contributes to combating the COVID-19 pandemic. © 2021 Elsevier Inc. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Jing Ren and Feng Xia" is provided in this record**
- Description: COVID-19 has been spreading rapidly around the world. With the growing attention on the deadly pandemic, discussions and research on COVID-19 are rapidly increasing to exchange latest findings with the hope to accelerate the pace of finding a cure. As a branch of information technology, artificial intelligence (AI) has greatly expedited the development of human society. In this paper, we investigate and visualize the on-going advancements of early scientific research on COVID-19 from the perspective of AI. By adopting the Latent Dirichlet Allocation (LDA) model, this paper allocates the research articles into 50 key research topics pertinent to COVID-19 according to their abstracts. We present an overview of early studies of the COVID-19 crisis at different scales including referencing/citation behavior, topic variation and their inner interactions. We also identify innovative papers that are regarded as the cornerstones in the development of COVID-19 research. The results unveil the focus of scientific research, thereby giving deep insights into how the academic society contributes to combating the COVID-19 pandemic. © 2021 Elsevier Inc.
- Authors: Liu, Jiaying , Nie, Hansong , Li, Shihao , Ren, Jing , Xia, Feng
- Date: 2021
- Type: Text , Journal article
- Relation: Big Data Research Vol. 25, no. (2021), p.
- Full Text:
- Reviewed:
- Description: COVID-19 has been spreading rapidly around the world. With the growing attention on the deadly pandemic, discussions and research on COVID-19 are rapidly increasing to exchange latest findings with the hope to accelerate the pace of finding a cure. As a branch of information technology, artificial intelligence (AI) has greatly expedited the development of human society. In this paper, we investigate and visualize the on-going advancements of early scientific research on COVID-19 from the perspective of AI. By adopting the Latent Dirichlet Allocation (LDA) model, this paper allocates the research articles into 50 key research topics pertinent to COVID-19 according to their abstracts. We present an overview of early studies of the COVID-19 crisis at different scales including referencing/citation behavior, topic variation and their inner interactions. We also identify innovative papers that are regarded as the cornerstones in the development of COVID-19 research. The results unveil the focus of scientific research, thereby giving deep insights into how the academic society contributes to combating the COVID-19 pandemic. © 2021 Elsevier Inc. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Jing Ren and Feng Xia" is provided in this record**
- Description: COVID-19 has been spreading rapidly around the world. With the growing attention on the deadly pandemic, discussions and research on COVID-19 are rapidly increasing to exchange latest findings with the hope to accelerate the pace of finding a cure. As a branch of information technology, artificial intelligence (AI) has greatly expedited the development of human society. In this paper, we investigate and visualize the on-going advancements of early scientific research on COVID-19 from the perspective of AI. By adopting the Latent Dirichlet Allocation (LDA) model, this paper allocates the research articles into 50 key research topics pertinent to COVID-19 according to their abstracts. We present an overview of early studies of the COVID-19 crisis at different scales including referencing/citation behavior, topic variation and their inner interactions. We also identify innovative papers that are regarded as the cornerstones in the development of COVID-19 research. The results unveil the focus of scientific research, thereby giving deep insights into how the academic society contributes to combating the COVID-19 pandemic. © 2021 Elsevier Inc.
A new era of integration between multiomics and spatio-temporal analysis for the translation of EMT towards clinical applications in cancer
- Fonseca Teixeira, Adilson, Wu, Siqi, Luwor, Rodney, Zhu, Hong-Jian
- Authors: Fonseca Teixeira, Adilson , Wu, Siqi , Luwor, Rodney , Zhu, Hong-Jian
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Cells Vol. 12, no. 23 (2023), p.
- Full Text:
- Reviewed:
- Description: Epithelial-mesenchymal transition (EMT) is crucial to metastasis by increasing cancer cell migration and invasion. At the cellular level, EMT-related morphological and functional changes are well established. At the molecular level, critical signaling pathways able to drive EMT have been described. Yet, the translation of EMT into efficient diagnostic methods and anti-metastatic therapies is still missing. This highlights a gap in our understanding of the precise mechanisms governing EMT. Here, we discuss evidence suggesting that overcoming this limitation requires the integration of multiple omics, a hitherto neglected strategy in the EMT field. More specifically, this work summarizes results that were independently obtained through epigenomics/transcriptomics while comprehensively reviewing the achievements of proteomics in cancer research. Additionally, we prospect gains to be obtained by applying spatio-temporal multiomics in the investigation of EMT-driven metastasis. Along with the development of more sensitive technologies, the integration of currently available omics, and a look at dynamic alterations that regulate EMT at the subcellular level will lead to a deeper understanding of this process. Further, considering the significance of EMT to cancer progression, this integrative strategy may enable the development of new and improved biomarkers and therapeutics capable of increasing the survival and quality of life of cancer patients. © 2023 by the authors.
- Authors: Fonseca Teixeira, Adilson , Wu, Siqi , Luwor, Rodney , Zhu, Hong-Jian
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Cells Vol. 12, no. 23 (2023), p.
- Full Text:
- Reviewed:
- Description: Epithelial-mesenchymal transition (EMT) is crucial to metastasis by increasing cancer cell migration and invasion. At the cellular level, EMT-related morphological and functional changes are well established. At the molecular level, critical signaling pathways able to drive EMT have been described. Yet, the translation of EMT into efficient diagnostic methods and anti-metastatic therapies is still missing. This highlights a gap in our understanding of the precise mechanisms governing EMT. Here, we discuss evidence suggesting that overcoming this limitation requires the integration of multiple omics, a hitherto neglected strategy in the EMT field. More specifically, this work summarizes results that were independently obtained through epigenomics/transcriptomics while comprehensively reviewing the achievements of proteomics in cancer research. Additionally, we prospect gains to be obtained by applying spatio-temporal multiomics in the investigation of EMT-driven metastasis. Along with the development of more sensitive technologies, the integration of currently available omics, and a look at dynamic alterations that regulate EMT at the subcellular level will lead to a deeper understanding of this process. Further, considering the significance of EMT to cancer progression, this integrative strategy may enable the development of new and improved biomarkers and therapeutics capable of increasing the survival and quality of life of cancer patients. © 2023 by the authors.
Psychological distress, fear and coping strategies among hong kong people during the COVID-19 pandemic
- Chair, Sek, Chien, Wai, Liu, Ting, Lam, Louisa, Cross, Wendy, Banik, Biswajit, Rahman, Muhammad Aziz
- Authors: Chair, Sek , Chien, Wai , Liu, Ting , Lam, Louisa , Cross, Wendy , Banik, Biswajit , Rahman, Muhammad Aziz
- Date: 2023
- Type: Text , Journal article
- Relation: Current Psychology Vol. 42, no. 3 (2023), p. 2538-2557
- Full Text:
- Reviewed:
- Description: The COVID-19 pandemic contributed to potential adverse effects on the mental health status of a wide range of people. This study aimed to identify factors associated with psychological distress, fear and coping strategies during the COVID-19 pandemic in Hong Kong. A cross-sectional online survey was conducted among general population in Hong Kong. Psychological distress was assessed using the Kessler Psychological Distress Scale; level of fear was evaluated using the Fear of COVID-19 scale; and coping strategies were assessed using the Brief Resilient Coping Scale. Multivariable logistic regression was used to identify key factors associated with these mental health variables. Of the 555 participants, 53.9% experienced moderate to very high levels of psychological distress, 31.2% experienced a high level of fear of COVID-19, and 58.6% showed moderate to high resilient coping. Multivariable logistic regression indicated that living with family members, current alcohol consumption, and higher level of fear were associated with higher levels of psychological distress; perceived stress due to a change in employment condition, being a frontline worker, experiencing ‘moderate to very high’ distress, and healthcare service use to overcome the COVID-19 related stress in past 6 months were associated with a higher level of fear; and perceived better mental health status was associated with a moderate to high resilient coping. This study identified key factors associated with distress, fear and coping strategies during the pandemic in Hong Kong. Mental health support strategies should be provided continuously to prevent the mental impact of the pandemic from turning into long-term illness. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
- Authors: Chair, Sek , Chien, Wai , Liu, Ting , Lam, Louisa , Cross, Wendy , Banik, Biswajit , Rahman, Muhammad Aziz
- Date: 2023
- Type: Text , Journal article
- Relation: Current Psychology Vol. 42, no. 3 (2023), p. 2538-2557
- Full Text:
- Reviewed:
- Description: The COVID-19 pandemic contributed to potential adverse effects on the mental health status of a wide range of people. This study aimed to identify factors associated with psychological distress, fear and coping strategies during the COVID-19 pandemic in Hong Kong. A cross-sectional online survey was conducted among general population in Hong Kong. Psychological distress was assessed using the Kessler Psychological Distress Scale; level of fear was evaluated using the Fear of COVID-19 scale; and coping strategies were assessed using the Brief Resilient Coping Scale. Multivariable logistic regression was used to identify key factors associated with these mental health variables. Of the 555 participants, 53.9% experienced moderate to very high levels of psychological distress, 31.2% experienced a high level of fear of COVID-19, and 58.6% showed moderate to high resilient coping. Multivariable logistic regression indicated that living with family members, current alcohol consumption, and higher level of fear were associated with higher levels of psychological distress; perceived stress due to a change in employment condition, being a frontline worker, experiencing ‘moderate to very high’ distress, and healthcare service use to overcome the COVID-19 related stress in past 6 months were associated with a higher level of fear; and perceived better mental health status was associated with a moderate to high resilient coping. This study identified key factors associated with distress, fear and coping strategies during the pandemic in Hong Kong. Mental health support strategies should be provided continuously to prevent the mental impact of the pandemic from turning into long-term illness. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Mouse models for abdominal aortic aneurysm
- Golledge, Jonathan, Krishna, Smriti, Wang, Yutang
- Authors: Golledge, Jonathan , Krishna, Smriti , Wang, Yutang
- Date: 2022
- Type: Text , Journal article , Review
- Relation: British Journal of Pharmacology Vol. 179, no. 5 (2022), p. 792-810
- Relation: https://purl.org/au-research/grants/nhmrc/1062671
- Full Text:
- Reviewed:
- Description: Abdominal aortic aneurysm (AAA) rupture is estimated to cause 200,000 deaths each year. Currently, the only treatment for AAA is surgical repair; however, this is only indicated for large asymptomatic, symptomatic or ruptured aneurysms, is not always durable, and is associated with a risk of serious perioperative complications. As a result, patients with small asymptomatic aneurysms or who are otherwise unfit for surgery are treated conservatively, but up to 70% of small aneurysms continue to grow, increasing the risk of rupture. There is thus an urgent need to develop drug therapies effective at slowing AAA growth. This review describes the commonly used mouse models for AAA. Recent research in these models highlights key roles for pathways involved in inflammation and cell turnover in AAA pathogenesis. There is also evidence for long non-coding RNAs and thrombosis in aneurysm pathology. Further well-designed research in clinically relevant models is expected to be translated into effective AAA drugs. LINKED ARTICLES: This article is part of a themed issue on Preclinical Models for Cardiovascular disease research (BJP 75th Anniversary). To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v179.5/issuetoc. © 2020 The British Pharmacological Society
- Authors: Golledge, Jonathan , Krishna, Smriti , Wang, Yutang
- Date: 2022
- Type: Text , Journal article , Review
- Relation: British Journal of Pharmacology Vol. 179, no. 5 (2022), p. 792-810
- Relation: https://purl.org/au-research/grants/nhmrc/1062671
- Full Text:
- Reviewed:
- Description: Abdominal aortic aneurysm (AAA) rupture is estimated to cause 200,000 deaths each year. Currently, the only treatment for AAA is surgical repair; however, this is only indicated for large asymptomatic, symptomatic or ruptured aneurysms, is not always durable, and is associated with a risk of serious perioperative complications. As a result, patients with small asymptomatic aneurysms or who are otherwise unfit for surgery are treated conservatively, but up to 70% of small aneurysms continue to grow, increasing the risk of rupture. There is thus an urgent need to develop drug therapies effective at slowing AAA growth. This review describes the commonly used mouse models for AAA. Recent research in these models highlights key roles for pathways involved in inflammation and cell turnover in AAA pathogenesis. There is also evidence for long non-coding RNAs and thrombosis in aneurysm pathology. Further well-designed research in clinically relevant models is expected to be translated into effective AAA drugs. LINKED ARTICLES: This article is part of a themed issue on Preclinical Models for Cardiovascular disease research (BJP 75th Anniversary). To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v179.5/issuetoc. © 2020 The British Pharmacological Society
Tumour microenvironment and metabolic plasticity in cancer and cancer stem cells : Perspectives on metabolic and immune regulatory signatures in chemoresistant ovarian cancer stem cells
- Ahmed, Nuzhat, Escalona, Ruth, Leung, Dilys, Chan, Emily, Kannourakis, George
- Authors: Ahmed, Nuzhat , Escalona, Ruth , Leung, Dilys , Chan, Emily , Kannourakis, George
- Date: 2018
- Type: Text , Journal article , Review
- Relation: Seminars in Cancer Biology Vol. 53, no. (2018), p. 265-281
- Full Text:
- Reviewed:
- Description: Cancer stem cells (CSCs) are a sub-population of tumour cells, which are responsible to drive tumour growth, metastasis and therapy resistance. It has recently been proposed that enhanced glucose metabolism and immune evasion by tumour cells are linked, and are modulated by the changing tumour microenvironment (TME) that creates a competition for nutrient consumption between tumour and different sub-types of cells attracted to the TME. To facilitate efficient nutrient distribution, oncogene-induced inflammatory milieu in the tumours facilitate adaptive metabolic changes in the surrounding non-malignant cells to secrete metabolites that are used as alternative nutrient sources by the tumours to sustain its increasing energy needs for growth and anabolic functions. This scenario also affects CSCs residing at the primary or metastatic niches. This review summarises recent advances in our understanding of the metabolic phenotypes of cancer cells and CSCs and how these processes are affected by the TME. We also discuss how the evolving TME modulates tumour cells and CSCs in cancer progression. Using previously described proteomic and genomic platforms, ovarian cancer cell lines and a mouse xenograft model we highlight the existence of metabolic and immune regulatory signatures in chemoresistant ovarian CSCs, and discuss how these processes may affect recurrence in ovarian tumours. We propose that progress in cancer control and eradication may depend not only on the elimination of highly chemoresistant CSCs, but also in designing novel strategies which would intervene with the tumour-promoting TME factors.
- Authors: Ahmed, Nuzhat , Escalona, Ruth , Leung, Dilys , Chan, Emily , Kannourakis, George
- Date: 2018
- Type: Text , Journal article , Review
- Relation: Seminars in Cancer Biology Vol. 53, no. (2018), p. 265-281
- Full Text:
- Reviewed:
- Description: Cancer stem cells (CSCs) are a sub-population of tumour cells, which are responsible to drive tumour growth, metastasis and therapy resistance. It has recently been proposed that enhanced glucose metabolism and immune evasion by tumour cells are linked, and are modulated by the changing tumour microenvironment (TME) that creates a competition for nutrient consumption between tumour and different sub-types of cells attracted to the TME. To facilitate efficient nutrient distribution, oncogene-induced inflammatory milieu in the tumours facilitate adaptive metabolic changes in the surrounding non-malignant cells to secrete metabolites that are used as alternative nutrient sources by the tumours to sustain its increasing energy needs for growth and anabolic functions. This scenario also affects CSCs residing at the primary or metastatic niches. This review summarises recent advances in our understanding of the metabolic phenotypes of cancer cells and CSCs and how these processes are affected by the TME. We also discuss how the evolving TME modulates tumour cells and CSCs in cancer progression. Using previously described proteomic and genomic platforms, ovarian cancer cell lines and a mouse xenograft model we highlight the existence of metabolic and immune regulatory signatures in chemoresistant ovarian CSCs, and discuss how these processes may affect recurrence in ovarian tumours. We propose that progress in cancer control and eradication may depend not only on the elimination of highly chemoresistant CSCs, but also in designing novel strategies which would intervene with the tumour-promoting TME factors.
Efficient video coding using visual sensitive information for HEVC coding standard
- Podder, Pallab, Paul, Manoranjan, Murshed, Manzur
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 75695-75708
- Full Text:
- Reviewed:
- Description: The latest high efficiency video coding (HEVC) standard introduces a large number of inter-mode block partitioning modes. The HEVC reference test model (HM) uses partially exhaustive tree-structured mode selection, which still explores a large number of prediction unit (PU) modes for a coding unit (CU). This impacts on encoding time rise which deprives a number of electronic devices having limited processing resources to use various features of HEVC. By analyzing the homogeneity, residual, and different statistical correlation among modes, many researchers speed-up the encoding process through the number of PU mode reduction. However, these approaches could not demonstrate the similar rate-distortion (RD) performance with the HM due to their dependency on existing Lagrangian cost function (LCF) within the HEVC framework. In this paper, to avoid the complete dependency on LCF in the initial phase, we exploit visual sensitive foreground motion and spatial salient metric (FMSSM) in a block. To capture its motion and saliency features, we use the dynamic background and visual saliency modeling, respectively. According to the FMSSM values, a subset of PU modes is then explored for encoding the CU. This preprocessing phase is independent from the existing LCF. As the proposed coding technique further reduces the number of PU modes using two simple criteria (i.e., motion and saliency), it outperforms the HM in terms of encoding time reduction. As it also encodes the uncovered and static background areas using the dynamic background frame as a substituted reference frame, it does not sacrifice quality. Tested results reveal that the proposed method achieves 32% average encoding time reduction of the HM without any quality loss for a wide range of videos.
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 75695-75708
- Full Text:
- Reviewed:
- Description: The latest high efficiency video coding (HEVC) standard introduces a large number of inter-mode block partitioning modes. The HEVC reference test model (HM) uses partially exhaustive tree-structured mode selection, which still explores a large number of prediction unit (PU) modes for a coding unit (CU). This impacts on encoding time rise which deprives a number of electronic devices having limited processing resources to use various features of HEVC. By analyzing the homogeneity, residual, and different statistical correlation among modes, many researchers speed-up the encoding process through the number of PU mode reduction. However, these approaches could not demonstrate the similar rate-distortion (RD) performance with the HM due to their dependency on existing Lagrangian cost function (LCF) within the HEVC framework. In this paper, to avoid the complete dependency on LCF in the initial phase, we exploit visual sensitive foreground motion and spatial salient metric (FMSSM) in a block. To capture its motion and saliency features, we use the dynamic background and visual saliency modeling, respectively. According to the FMSSM values, a subset of PU modes is then explored for encoding the CU. This preprocessing phase is independent from the existing LCF. As the proposed coding technique further reduces the number of PU modes using two simple criteria (i.e., motion and saliency), it outperforms the HM in terms of encoding time reduction. As it also encodes the uncovered and static background areas using the dynamic background frame as a substituted reference frame, it does not sacrifice quality. Tested results reveal that the proposed method achieves 32% average encoding time reduction of the HM without any quality loss for a wide range of videos.
Design and analysis of an efficient energy algorithm in wireless social sensor networks
- Xiong, Naixue, Zhang, Longzhen, Zhang, Wei, Vasilakos, Athanasios, Imran, Muhammad
- Authors: Xiong, Naixue , Zhang, Longzhen , Zhang, Wei , Vasilakos, Athanasios , Imran, Muhammad
- Date: 2017
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 17, no. 10 (2017), p.
- Full Text:
- Reviewed:
- Description: Because mobile ad hoc networks have characteristics such as lack of center nodes, multi-hop routing and changeable topology, the existing checkpoint technologies for normal mobile networks cannot be applied well to mobile ad hoc networks. Considering the multi-frequency hierarchy structure of ad hoc networks, this paper proposes a hybrid checkpointing strategy which combines the techniques of synchronous checkpointing with asynchronous checkpointing, namely the checkpoints of mobile terminals in the same cluster remain synchronous, and the checkpoints in different clusters remain asynchronous. This strategy could not only avoid cascading rollback among the processes in the same cluster, but also avoid too many message transmissions among the processes in different clusters. What is more, it can reduce the communication delay. In order to assure the consistency of the global states, this paper discusses the correctness criteria of hybrid checkpointing, which includes the criteria of checkpoint taking, rollback recovery and indelibility. Based on the designed Intra-Cluster Checkpoint Dependence Graph and Inter-Cluster Checkpoint Dependence Graph, the elimination rules for different kinds of checkpoints are discussed, and the algorithms for the same cluster checkpoints, different cluster checkpoints, and rollback recovery are also given. Experimental results demonstrate the proposed hybrid checkpointing strategy is a preferable trade-off method, which not only synthetically takes all kinds of resource constraints of Ad hoc networks into account, but also outperforms the existing schemes in terms of the dependence to cluster heads, the recovery time compared to the pure synchronous, and the pure asynchronous checkpoint advantage. © 2017 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Xiong, Naixue , Zhang, Longzhen , Zhang, Wei , Vasilakos, Athanasios , Imran, Muhammad
- Date: 2017
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 17, no. 10 (2017), p.
- Full Text:
- Reviewed:
- Description: Because mobile ad hoc networks have characteristics such as lack of center nodes, multi-hop routing and changeable topology, the existing checkpoint technologies for normal mobile networks cannot be applied well to mobile ad hoc networks. Considering the multi-frequency hierarchy structure of ad hoc networks, this paper proposes a hybrid checkpointing strategy which combines the techniques of synchronous checkpointing with asynchronous checkpointing, namely the checkpoints of mobile terminals in the same cluster remain synchronous, and the checkpoints in different clusters remain asynchronous. This strategy could not only avoid cascading rollback among the processes in the same cluster, but also avoid too many message transmissions among the processes in different clusters. What is more, it can reduce the communication delay. In order to assure the consistency of the global states, this paper discusses the correctness criteria of hybrid checkpointing, which includes the criteria of checkpoint taking, rollback recovery and indelibility. Based on the designed Intra-Cluster Checkpoint Dependence Graph and Inter-Cluster Checkpoint Dependence Graph, the elimination rules for different kinds of checkpoints are discussed, and the algorithms for the same cluster checkpoints, different cluster checkpoints, and rollback recovery are also given. Experimental results demonstrate the proposed hybrid checkpointing strategy is a preferable trade-off method, which not only synthetically takes all kinds of resource constraints of Ad hoc networks into account, but also outperforms the existing schemes in terms of the dependence to cluster heads, the recovery time compared to the pure synchronous, and the pure asynchronous checkpoint advantage. © 2017 by the authors. Licensee MDPI, Basel, Switzerland.