The Metapopulation Dynamics of an Infectious Disease: Tuberculosis in Possums

An SEI metapopulation model is developed for the spread of an infectious agent by migration. The model portrays two age classes on a number of patches connected by migration routes which are used as host animals mature. A feature of this model is that the basic reproduction ratio may be computed directly, using a scheme that separates topography, demography, and epidemiology. We also provide formulas for individual patch basic reproduction numbers and discuss their connection with the basic reproduction ratio for the system. The model is applied to the problem of spatial spread of bovine tuberculosis in a possum population. The temporal dynamics of infection are investigated for some generic networks of migration links, and the basic reproduction ratio is computed—its value is not greatly different from that for a homogeneous model. Three scenarios are considered for the control of bovine tuberculosis in possums where the spatial aspect is shown to be crucial for the design of disease management operations

Trading spaces : on the lore and limitations of latent semantic analysis

Two decades after its inception, Latent Semantic Analysis(LSA) has become part and parcel of every modern introduction to Information Retrieval. For any tool that matures so quickly, it is important to check its lore and limitations, or else stagnation will set in. We focus here on the three main aspects of LSA that are well accepted, and the gist of which can be summarized as follows: (1) that LSA recovers latent semantic factors underlying the document space, (2) that such can be accomplished through lossy compression of the document space by eliminating lexical noise, and (3) that the latter can best be achieved by Singular Value Decomposition. For each aspect we performed experiments analogous to those reported in the LSA literature and compared the evidence brought to bear in each case. On the negative side, we show that the above claims about LSA are much more limited than commonly believed. Even a simple example may show that LSA does not recover the optimal semantic factors as intended in the pedagogical example used in many LSA publications. Additionally, and remarkably deviating from LSA lore, LSA does not scale up well: the larger the document space, the more unlikely that LSA recovers an optimal set of semantic factors. On the positive side, we describe new algorithms to replace LSA (and more recent alternatives as pLSA, LDA, and kernel methods) by trading its l2 space for an l1 space, thereby guaranteeing an optimal set of semantic factors. These algorithms seem to salvage the spirit of LSA as we think it was initially conceived.

Risk factors for Mycobacterium tuberculosis infection among children in Greenland

Objective To examine the risk factors for Mycobacterium tuberculosis infection (MTI) among Greenlandic children for the purpose of identifying those at highest risk of infection. Methods Between 2005 and 2007, 1797 Greenlandic schoolchildren in five different areas were tested for MTI with an interferon gamma release assay (IGRA) and a tuberculin skin test (TST). Parents or guardians were surveyed using a standardized self-administered questionnaire to obtain data on crowding in the household, parents’ educational level and the child’s health status. Demographic data for each child – i.e. parents’ place of birth, number of siblings, distance between siblings (next younger and next older), birth order and mother’s age when the child was born – were also extracted from a public registry. Logistic regression was used to check for associations between these variables and MTI, and all results were expressed as odds ratios (ORs) and 95% confidence intervals (CIs). Children were considered to have MTI if they tested positive on both the IGRA assay and the TST. Findings The overall prevalence of MTI was 8.5% (152/1797). MTI was diagnosed in 26.7% of the children with a known TB contact, as opposed to 6.4% of the children without such contact. Overall, the MTI rate was higher among Inuit children (OR: 4.22; 95% CI: 1.55–11.5) and among children born less than one year after the birth of the next older sibling (OR: 2.48; 95% CI: 1.33–4.63). Self-reported TB contact modified the profile to include household crowding and low mother’s education. Children who had an older MTI-positive sibling were much more likely to test positive for MTI themselves (OR: 14.2; 95% CI: 5.75–35.0) than children without an infected older sibling. Conclusion Ethnicity, sibling relations, number of household residents and maternal level of education are factors associated with the risk of TB infection among children in Greenland. The strong household clustering of MTI suggests that family sources of exposure are important.

Simulating a latent susceptible pool to examine the impact on cardiovascular mortality

The health effects of cold and hot temperatures are strongest in the frail and elderly. A large number of deaths in this "susceptible pool" after heat waves and cold snaps can cause mortality displacement, where an immediate increase in mortality is somewhat offset by a subsequent decrease in the following weeks. There may also be longer-term implications, as reductions in the pool caused by hot summers can reduce cold-related mortality in the following winter. A state-space model was used to simulate the numbers in the susceptible pool over time. We simulated the effects of harsh winters and heat waves, and varied the size of the susceptible pool. The larger the susceptible pool the smaller the mortality displacement. When 1% of the population were susceptible a harsh winter lead to an average of just 3 months of life lost per cold-related death, whereas a pool size of 10% meant that 24 months of life were lost per death. The impact of a cold spell on months of life lost was greater when the increased risk of death also applied to healthy people. The number of deaths caused by an August heat wave were reduced when there was a prior heat wave in June which reduced the susceptible pool. We were able to mimic some observed seasonal patterns in mortality using a simple state-space model. A better understanding of the size and dynamics of the susceptible pool will improve our understanding of the health effects of temperature.

Explicit, latent and meta-criteria : types of criteria at play in professional judgement practice

This paper engages with debates about whether comprehensive prior specification of criteria and standards is sufficient for informed professional judgement. A preoccupation has emerged with the specificity and explication of criteria intended to regulate judgement. This has resulted in criteria-compliance in the use of defined standards to validate judgements and improve reliability and consistency. Compliance has become a priority, the consequence being the prominence of explicit criteria, to the lack of acknowledgement of the operation of latent and meta-criteria within judgement practice. This paper examines judgement as a process involving three categories of assessment criteria in the context of standards-referenced systems: explicit, latent and meta-criteria. These are understood to be wholly interrelated and interdependent. A conceptualisation of judgement involving the interplay of the three criteria types is presented with an exploration of how they function to focus or alter assessments of quality in judgements of achievement in English and Mathematics.

Different in vitro activation methods for latent transforming growth factors (TGF)–β : considerable exogenous factors to promote higher mesenchymal-origin cell proliferation in a bioprocessing platform

Regenerative medicine includes two efficient techniques, namely tissue-engineering and cell-based therapy in order to repair tissue damage efficiently. Most importantly, huge numbers of autologous cells are required to deal these practices. Nevertheless, primary cells, from autologous tissue, grow very slowly while culturing in vitro; moreover, they lose their natural characteristics over prolonged culturing period. Transforming growth factors-beta (TGF-β) is a ubiquitous protein found biologically in its latent form, which prevents it from eliciting a response until conversion to its active form. In active form, TGF-β acts as a proliferative agent in many cell lines of mesenchymal origin in vitro. This article reviews on some of the important activation methods-physiochemical, enzyme-mediated, non-specific protein interaction mediated, and drug-induced- of TGF-β, which may be established as exogenous factors to be used in culturing medium to obtain extensive proliferation of primary cells.

Interactive content analysis : evaluating interactive variants of non-negative Matrix Factorisation and Latent Dirichlet Allocation as qualitative content analysis aids

This thesis addressed issues that have prevented qualitative researchers from using thematic discovery algorithms. The central hypothesis evaluated whether allowing qualitative researchers to interact with thematic discovery algorithms and incorporate domain knowledge improved their ability to address research questions and trust the derived themes. Non-negative Matrix Factorisation and Latent Dirichlet Allocation find latent themes within document collections but these algorithms are rarely used, because qualitative researchers do not trust and cannot interact with the themes that are automatically generated. The research determined the types of interactivity that qualitative researchers require and then evaluated interactive algorithms that matched these requirements. Theoretical contributions included the articulation of design guidelines for interactive thematic discovery algorithms, the development of an Evaluation Model and a Conceptual Framework for Interactive Content Analysis.

Latent class analysis reveals distinct subgroups of patients based on symptom occurrence and demographic and clinical characteristics

Context Cancer patients experience a broad range of physical and psychological symptoms as a result of their disease and its treatment. On average, these patients report ten unrelieved and co-occurring symptoms. Objectives To determine if subgroups of oncology outpatients receiving active treatment (n=582) could be identified based on their distinct experience with thirteen commonly occurring symptoms; to determine whether these subgroups differed on select demographic, and clinical characteristics; and to determine if these subgroups differed on quality of life (QOL) outcomes. Methods Demographic, clinical, and symptom data from one Australian and two U.S. studies were combined. Latent class analysis (LCA) was used to identify patient subgroups with distinct symptom experiences based on self-report data on symptom occurrence using the Memorial Symptom Assessment Scale (MSAS). Results Four distinct latent classes were identified (i.e., All Low (28.0%), Moderate Physical and Lower Psych (26.3%), Moderate Physical and Higher Psych (25.4%), All High (20.3%)). Age, gender, education, cancer diagnosis, and presence of metastatic disease differentiated among the latent classes. Patients in the All High class had the worst QOL scores. Conclusion Findings from this study confirm the large amount of interindividual variability in the symptom experience of oncology patients. The identification of demographic and clinical characteristics that place patients are risk for a higher symptom burden can be used to guide more aggressive and individualized symptom management interventions.

Supervised latent dirichlet allocation models for efficient activity representation

Local spatio-temporal features with a Bag-of-visual words model is a popular approach used in human action recognition. Bag-of-features methods suffer from several challenges such as extracting appropriate appearance and motion features from videos, converting extracted features appropriate for classification and designing a suitable classification framework. In this paper we address the problem of efficiently representing the extracted features for classification to improve the overall performance. We introduce two generative supervised topic models, maximum entropy discrimination LDA (MedLDA) and class- specific simplex LDA (css-LDA), to encode the raw features suitable for discriminative SVM based classification. Unsupervised LDA models disconnect topic discovery from the classification task, hence yield poor results compared to the baseline Bag-of-words framework. On the other hand supervised LDA techniques learn the topic structure by considering the class labels and improve the recognition accuracy significantly. MedLDA maximizes likelihood and within class margins using max-margin techniques and yields a sparse highly discriminative topic structure; while in css-LDA separate class specific topics are learned instead of common set of topics across the entire dataset. In our representation first topics are learned and then each video is represented as a topic proportion vector, i.e. it can be comparable to a histogram of topics. Finally SVM classification is done on the learned topic proportion vector. We demonstrate the efficiency of the above two representation techniques through the experiments carried out in two popular datasets. Experimental results demonstrate significantly improved performance compared to the baseline Bag-of-features framework which uses kmeans to construct histogram of words from the feature vectors.

Mycobacterium tuberculosis groE promoter controls the expression of the bicistronic groESL1 operon and shows differential regulation under stress conditions

Heat shock promoters of mycobacteria are strong promoters that become rapidly upregulated during macrophage infection and thus serve as valuable candidates for expressing foreign antigens in recombinant BCG vaccine. In the present study, a new heat shock promoter controlling the expression of the groESL1 operon was identified and characterized. Mycobacterium tuberculosis groESL1 operon codes for the immunodominant 10 kDa (Rv3418c, GroES/Cpn10/Hsp10) and 60 kDa (Rv3417c, GroEL1/Cpn60.1/Hsp60) heat shock proteins. The basal promoter region was 115 bp, while enhanced activity was seen only with a 277-bp fragment. No promoter element was seen in the groES-groEL1 intergenic region. This operon codes for a bicistronic mRNA transcript as determined by reverse transcriptase-PCR and Northern blot analysis. Primer extension analysis identified two transcriptional start sites (TSSs) TSS1 (-236) and TSS2 (-171), out of which one (TSS2) was heat inducible. The groE promoter was more active than the groEL2 promoter in Mycobacterium smegmatis. Further, it was found to be differentially regulated under stress conditions, while the groEL2 promoter was constitutive.

Characterization of novel immunodominant antigens of Mycobacterium tuberculosis

Seven novel antigens of Mycobacterium tuberculosis, which had previously been identified based on reactivity to sera from patients with tuberculosis, were characterized. Nucleotide sequence analysis of the genes encoding these seven antigens identified one of them as the FtsH and a second as the aminoimidazole ribotide synthase of M. tuberculosis. Antisera raised to the recombinant forms of each of these seven antigens were used to study the distribution of these proteins within mycobacterial species as well as to determine their subcellular localization and hydrophobicity. Four of the seven antigens were conserved only among pathogenic strains of mycobacteria. Of the seven proteins studied, FtsH and a second protein of unknown identity were localized in membranes. Two were cytosolic, while two others, which had a high proline content, were tightly associated with the cell wall. One protein was secreted. This secreted protein could be identified by serum from a majority of tuberculosis patients but not BCG-vaccinated individuals, suggesting its potential use in the immunodiagnosis of tuberculosis.

Analysis of a Genomic DNA Expression Library of Mycobacterium tuberculosis Using Tuberculosis Patient Sera: Evidence for Modulation of Host Immune Response

DNA obtained from a human sputum isolate of Mycobacterium tuberculosis, NTI-64719, which showed extensive dissemination in the guinea pig model resulting in a high score for virulence was used to construct an expression library in the lambda ZAP vector. The size of DNA inserts in the library ranged from 1 to 3 kb, and recombinants represented 60% of the total plaques obtained. When probed with pooled serum from chronically infected tuberculosis patients, the library yielded 176 recombinants with a range of signal intensities. Among these, 93 recombinants were classified into 12 groups on the basis of DNA hybridization experiments, The polypeptides synthesized by the recombinants were predominantly LacZ fusion proteins, Serum obtained from patients who were clinically diagnosed to be in the early phase of M. tuberculosis infection was used to probe the 176 recombinants obtained. interestingly, some recombinants that gave very strong signals in the original screen did not react with early-phase serum; conversely, others whose signals were extremely weak in the original screen gave very intense signals with serum from recently infected patients, This indicates the differential nature of either the expression of these antigens or the immune response elicited by them as a function of disease progression.

targetTB: A target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis

Background: Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results: We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion: The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes.

Mycobacterium tuberculosis pantothenate kinase: possible changes in location of ligands during enzyme action

The crystal structures of complexes of Mycobacterium tuberculosis pantothenate kinase with the following ligands have been determined: (i) citrate; (ii) the nonhydrolysable ATP analogue AMPPCP and pantothenate (the initiation complex); (iii) ADP and phosphopantothenate resulting from phosphorylation of pantothenate by ATP in the crystal (the end complex); (iv) ATP and ADP, each with half occupancy, resulting from a quick soak of crystals in ATP (the intermediate complex); (v) CoA; (vi) ADP prepared by soaking and cocrystallization, which turned out to have identical structures, and (vii) ADP and pantothenate. Solution studies on CoA binding and catalytic activity have also been carried out. Unlike in the case of the homologous Escherichia coli enzyme, AMPPCP and ADP occupy different, though overlapping, locations in the respective complexes; the same is true of pantothenate in the initiation complex and phosphopantothenate in the end complex. The binding site of MtPanK is substantially preformed, while that of EcPanK exhibits considerabl plasticity. The difference in the behaviour of the E. coli and M. tuberculosis enzymes could be explained in terms of changes in local structure resulting from substitutions. It is unusual for two homologous enzymes to exhibit such striking differences in action. Therefore, the results have to be treated with caution. However, the changes in the locations of ligands exhibited by M. tuberculosis pantothenate kinase are remarkable and novel.