Human action recognition from video sequences

This PhD research has proposed new machine learning techniques to improve human action recognition based on local features. Several novel video representation and classification techniques have been proposed to increase the performance with lower computational complexity. The major contributions are the construction of new feature representation techniques, based on advanced machine learning techniques such as multiple instance dictionary learning, Latent Dirichlet Allocation (LDA) and Sparse coding. A Binary-tree based classification technique was also proposed to deal with large amounts of action categories. These techniques are not only improving the classification accuracy with constrained computational resources but are also robust to challenging environmental conditions. These developed techniques can be easily extended to a wide range of video applications to provide near real-time performance.

Virtual Special Issue: “The impact of temperature on human health: new insights”

Ambient temperature is one of the basic parameters characterising human comfort: are we too hot, too cold, or just right? The impact of temperature goes beyond comfort: inadequate temperature and temperature variations have consequences on human health, as the increasing numbers of studies have demonstrated. The topic is of particular significance at the times when climate change shifts the traditional – as we know them- temperature zones, and brings much wider temperature variations. For these reasons the impact of temperature on health has been one of the most popular topics among the articles submitted and published in Science of the Total Environment over the last few years. This Virtual Special Issue compiles 18 articles published in our journal on this topic since 2012. It is worth briefly summarizing the rich scientific insights brought by these articles, as well as broader considerations, particularly those extending to management, discussed by the authors of the articles.

Distinct subpopulations of gamma delta T cells are present in normal and tumor-bearing human liver

Gamma delta T cells are thought to mediate immune responses at epithelial surfaces. We have quantified and characterized hepatic and peripheral blood gamma delta T cells from 11 normal and 13 unresolved tumor-bearing human liver specimens. gamma delta T cells are enriched in normal liver (6.6% of T cells) relative to matched blood (0.9%; P = 0.008). The majority express CD4(-)CD8(-) phenotypes and many express CD56 and/or CD161. In vitro, hepatic gamma delta T cells can be induced to kill tumor cell lines and release interferon-gamma, tumor necrosis factor-alpha, interleukin-2 and interleukin-4. Analysis of V gamma and V delta chain usage indicated that V delta 3(+) cells are expanded in normal livers (21.2% of gamma delta T cells) compared to blood (0.5%; P = 0.001). Tumor-bearing livers had significant expansions and depletions of gamma delta T cell subsets but normal cytolytic activity. This study identifies novel populations of liver T cells that may play a role in immunity against tumors.

NKT cells from normal and tumor-bearing human livers are phenotypically and functionally distinct from murine NKT cells

A major group of murine NK T (NKT) cells express an invariant Vα14Jα18 TCR α-chain specific for glycolipid Ags presented by CD1d. Murine Vα14Jα18+ account for 30–50% of hepatic T cells and have potent antitumor activities. We have enumerated and characterized their human counterparts, Vα24Vβ11+ NKT cells, freshly isolated from histologically normal and tumor-bearing livers. In contrast to mice, human NKT cells are found in small numbers in healthy liver (0.5% of CD3+ cells) and blood (0.02%). In contrast to those in blood, most hepatic Vα24+ NKT cells express the Vβ11 chain. They include CD4+, CD8+, and CD4−CD8− cells, and many express the NK cell markers CD56, CD161, and/or CD69. Importantly, human hepatic Vα24+ T cells are potent producers of IFN-γ and TNF-α, but not IL-2 or IL-4, when stimulated pharmacologically or with the NKT cell ligand, α-galactosylceramide. Vα24+Vβ11+ cell numbers are reduced in tumor-bearing compared with healthy liver (0.1 vs 0.5%; p < 0.04). However, hepatic cells from cancer patients and healthy donors release similar amounts of IFN-γ in response to α-galactosylceramide. These data indicate that hepatic NKT cell repertoires are phenotypically and functionally distinct in humans and mice. Depletions of hepatic NKT cell subpopulations may underlie the susceptibility to metastatic liver disease.

CD1 expression and CD1-restricted T cell activity in normal and tumour-bearing human liver

CD1d-restricted natural killer T (NKT) cells expressing invariant Valpha14Jalpha18 T cell receptor alpha-chains are abundant in murine liver and are implicated in the control of malignancy, infection and autoimmunity. Invariant NKT cells have potent anti-metastatic effects in mice and phase I clinical trials involving their homologues in humans are ongoing. However, invariant NKT cells are less abundant in human liver ( approximately 0.5% of hepatic T cells) than in murine liver (up to 50%) and it is not known if other hepatic T cells are CD1-restricted. We have examined expression of CD1a, CD1b, CD1c and CD1d mRNA and protein in human liver and evaluated the reactivity of mononuclear cells (MNC) from histologically normal and tumour-bearing human liver specimens against these CD1 isoforms. Messenger RNA for all CD1 isotypes was detectable in all liver samples. CD1c and CD1d were expressed at the protein level by hepatic MNC. CD1d, only, was detectable at the cell surface, but CD1c and CD1d were found at an intracellular location in significant numbers of liver MNC. CD1b was not expressed by MNC from healthy livers but was detectable within MNC in all tumour samples tested. Hepatic T cells exhibited reactivity against C1R cells expressing transfected CD1c and CD1d, but neither CD1a nor CD1b. These cells secreted interferon-gamma (IFN-gamma) but not interleukin-4 (IL-4) upon stimulation. In contrast, similar numbers of peripheral T cells released 13- and 16-fold less IFN-gamma in response to CD1c and CD1d, respectively. CD1c and CD1d expression and T cell reactivity were not altered in tumour-bearing liver specimens compared to histologically normal livers. These data suggest that, in addition to invariant CD1d-restricted NKT cells, autoreactive T cells that recognise CD1c and CD1d and release inflammatory cytokines are abundant in human liver.

Diverse populations of T cells with NK cell receptors accumulate in the human intestine in health and in colorectal cancer

T cells expressing NK cell receptors (NKR) display rapid MHC-unrestricted cytotoxicity and potent cytokine secretion and are thought to play roles in immunity against tumors. We have quantified and characterized NKR+ T cells freshly isolated from epithelial and lamina propria layers of duodenum and colon from 16 individuals with no evidence of gastrointestinal disease and from tumor and uninvolved tissue from 19 patients with colorectal cancer. NKR+ T cell subpopulations were differentially distributed in different intestinal compartments, and CD161+ T cells accounted for over one half of T cells at all locations tested. Most intestinal CD161+ T cells expressed alpha beta TCR and either CD4 or CD8. Significant proportions expressed HLA-DR,CD69 and Fas ligand. Upon stimulation in vitro, CD161+ T cells produced IFN-gamma and TNF-alpha but not IL-4. NKT cells expressing the Valpha24Vbeta11 TCR, which recognizes CD1d,were virtually absent from the intestine, but colonic cells produced IFN-gamma in response to the NKT cell agonist ligand alpha-galactosylceramide. NKR+ T cells were not expanded in colonic tumors compared to adjacent uninvolved tissue. The predominance, heterogeneity and differential distribution of NKR+ T cells at different intestinal locations suggests that they are central to intestinal immunity.

Realities on the ground: Human trafficking constructs in Thailand and the implications on NGO anti-trafficking prevention strategies

This thesis is a qualitative study that examines how participating staff from Thai based non-governmental organisations interpret and construct the notion of human trafficking; and how this impacts prevention methods. The research examined the impact of different socio-cultural, political and religious ideologies on anti-trafficking prevention and programme implementation. Findings highlighted that while a 'raid and rescue' approach to human trafficking was widely recognised by donors and the media; it was not suitable or complementary to sustainable and community focused anti-trafficking models. Rather, a holistic approach that considers contextual factors and inter-agency collaboration is essential for effective anti-trafficking prevention strategies.

LRP5 regulates human body fat distribution by modulating adipose progenitor biology in a dose- and depot-specific fashion

Summary Common variants in WNT pathway genes have been associated with bone mass and fat distribution, the latter predicting diabetes and cardiovascular disease risk. Rare mutations in the WNT co-receptors LRP5 and LRP6 are similarly associated with bone and cardiometabolic disorders. We investigated the role of LRP5 in human adipose tissue. Subjects with gain-of-function LRP5 mutations and high bone mass had enhanced lower-body fat accumulation. Reciprocally, a low bone mineral density-associated common LRP5 allele correlated with increased abdominal adiposity. Ex vivo LRP5 expression was higher in abdominal versus gluteal adipocyte progenitors. Equivalent knockdown of LRP5 in both progenitor types dose-dependently impaired β-catenin signaling and led to distinct biological outcomes: diminished gluteal and enhanced abdominal adipogenesis. These data highlight how depot differences in WNT/β-catenin pathway activity modulate human fat distribution via effects on adipocyte progenitor biology. They also identify LRP5 as a potential pharmacologic target for the treatment of cardiometabolic disorders. © 2015 The Authors.

Elliptical summary randomisation for sensor-based human activity recognition

Many conventional statistical machine learning al- gorithms generalise poorly if distribution bias ex- ists in the datasets. For example, distribution bias arises in the context of domain generalisation, where knowledge acquired from multiple source domains need to be used in a previously unseen target domains. We propose Elliptical Summary Randomisation (ESRand), an efficient domain generalisation approach that comprises of a randomised kernel and elliptical data summarisation. ESRand learns a domain interdependent projection to a la- tent subspace that minimises the existing biases to the data while maintaining the functional relationship between domains. In the latent subspace, ellipsoidal summaries replace the samples to enhance the generalisation by further removing bias and noise in the data. Moreover, the summarisation enables large-scale data processing by significantly reducing the size of the data. Through comprehensive analysis, we show that our subspace-based approach outperforms state-of-the-art results on several activity recognition benchmark datasets, while keeping the computational complexity significantly low.