A cross-sectional international study shows confidence in public health scientists predicts use of COVID-19 non-pharmaceutical interventions.

BACKGROUND: We examine the antecedents of COVID-19 phone tracking applications use, social distancing, and mask use, in the United States, Hong Kong and Japan. METHODS: We draw on online panel surveys of over 1000 respondents each in the USA, Hong Kong and Japan, using broadly representative quota sample selections. Results are tested by ordinal logistic regression for the two ordinal dependent variables and logistic regression for phone app use. RESULTS: Confidence in public health scientists predicts use of phone tracking applications, social distancing, and mask use, albeit statistically insignificant for tracer phone application use in Hong Kong. Trust in government predicts the use of a phone tracking application. Counterintuitively, trust in government is negatively and significantly associated with mask use and social distancing in Hong Kong and Japan. Women are more likely to wear masks and practice social distancing. Government employees are more likely to use a phone tracking application, but less likely to mask and social distance. Voting and civic participation are positively associated with trust in government and confidence in public health scientists, in all three countries. There are interesting variations across all three countries on other antecedents and controls. CONCLUSIONS: Building and maintaining confidence in public health scientists provides a key tool to manage pandemics. Credible, effectively communicative - and independent - medical and scientific leaders may be central to pandemic control success. For digital measures, trust in government and privacy protection is central. Political and social factors are important to understand successful public health policy implementation.

Classification of fish samples via an integrated proteomics and bioinformatics approach.

There is an increasing demand to develop cost-effective and accurate approaches to analyzing biological tissue samples. This is especially relevant in the fishing industry where closely related fish samples can be mislabeled, and the high market value of certain fish leads to the use of alternative species as substitutes, for example, Barramundi and Nile Perch (belonging to the same genus, Lates). There is a need to combine selective proteomic datasets with sophisticated computational analysis to devise a robust classification approach. This paper describes an integrated MS-based proteomics and bioinformatics approach to classifying a range of fish samples. A classifier is developed using training data that successfully discriminates between Barramundi and Nile Perch samples using a selected protein subset of the proteome. Additionally, the classifier is shown to successfully discriminate between test samples not used to develop the classifier, including samples that have been cooked, and to classify other fish species as neither Barramundi nor Nile Perch. This approach has applications to truth in labeling for fishmongers and restaurants, monitoring fish catches, and for scientific research into distances between species.

HIV/AIDS information by African companies: an empirical analysis.

This article investigates the extent of Human Immunodeficiency Virus/Acquired Immune Deficiency Syndrome Disclosures (HIV/AIDSD) in online annual reports by 200 listed companies from 10 African countries for the year ending 2006. Descriptive statistics reveal a very low level of overall HIV/AIDSD practices with a mean of 6 per cent disclosure, with half (100 out of 200) of the African companies making no disclosures at all. Logistic regression analysis reveals that company size and country are highly significant predictors of any disclosure of HIV/AIDS in annual reports. Profitability is also statistically significantly associated with the extent of disclosure.

Gene expression profiling of Japanese psoriatic skin reveals an increased activity in molecular stress and immune response signals.

Gene expression profiling was performed on biopsies of affected and unaffected psoriatic skin and normal skin from seven Japanese patients to obtain insights into the pathways that control this disease. HUG95A Affymetrix DNA chips that contained oligonucleotide arrays of approximately 12,000 well-characterized human genes were used in the study. The statistical analysis of the Affymetrix data, based on the ranking of the Student t-test statistic, revealed a complex regulation of molecular stress and immune gene responses. The majority of the 266 induced genes in affected and unaffected psoriatic skin were involved with interferon mediation, immunity, cell adhesion, cytoskeleton restructuring, protein trafficking and degradation, RNA regulation and degradation, signalling transduction, apoptosis and atypical epidermal cellular proliferation and differentiation. The disturbances in the normal protein degradation equilibrium of skin were reflected by the significant increase in the gene expression of various protease inhibitors and proteinases, including the induced components of the ATP/ubiquitin-dependent non-lysosomal proteolytic pathway that is involved with peptide processing and presentation to T cells. Some of the up-regulated genes, such as TGM1, IVL, FABP5, CSTA and SPRR, are well-known psoriatic markers involved in atypical epidermal cellular organization and differentiation. In the comparison between the affected and unaffected psoriatic skin, the transcription factor JUNB was found at the top of the statistical rankings for the up-regulated genes in affected skin, suggesting that it has an important but as yet undefined role in psoriasis. Our gene expression data and analysis suggest that psoriasis is a chronic interferon- and T-cell-mediated immune disease of the skin where the imbalance in epidermal cellular structure, growth and differentiation arises from the molecular antiviral stress signals initiating inappropriate immune responses.

Gap mapping: a paradigm for aligning two sequences.

Pairwise sequence alignment is one of the most essential tools in comparative genomic sequence analysis. It is used to compare the sequences of genes and proteins with the aim of inferring structural, functional and evolutionary relationships. However, current 'mainstream' alignment algorithms have optimisation criteria based primarily on computational efficiency using parameters such as gap penalties, which are not biologically motivated. In addition, current alignment algorithms such as the Smith and Waterman technique provide a single alignment that could be sensitive to rather arbitrary choices in parameters such as gap penalties. This paper explores the range of properties resulting from posing the alignment problem more as a 'mapping gaps in sequences' exercise. We argue that this approach is intuitive and provides greater control over the number of gaps placed within an alignment. This type of approach was proposed by Sankoff (1972), but unfortunately has not received much attention. We report and discuss our findings by comparing this approach to other techniques using structurally confirmed aligned sequences from a benchmark alignment database. Interestingly, this approach consistently provides optimal and near optimal alignments and is thus a viable approach to sequence alignment.

TLX1/HOX11 transcription factor inhibits differentiation and promotes a non-haemopoietic phenotype in murine bone marrow cells.

The TLX/HOX11 subfamily of divergent homeobox genes are involved in various aspects of embryogenesis and, in the case of TLX1/HOX11 and TLX3/HOX11L2, feature prominently as oncogenes in human T-cell acute lymphoblastic leukaemia. TLX1 possesses immortalising activity in a wide variety of blood cell lineages, however, the effect of this oncogene on haemopoietic cell differentiation has not been fully investigated. We therefore constitutively expressed TLX1 in murine bone marrow or fetal liver cells using retroviral transfer followed by transplantation and/or in vitro culture. TLX1 was found to dramatically alter haemopoiesis, promoting the emergence of a non-haemopoietic CD45(-) CD31(+) cell population while markedly inhibiting erythroid and granulocytic cell differentiation. To identify genetic programs perturbed by TLX1, a comparison of transcript profiles from J2E erythroid cells with and without enforced TLX1 expression was undertaken. This revealed a pattern of gene expression indicative of enhanced proliferation coupled to differentiation arrest. Of the genes identified, two, KIT and VEGFC, were found to be potential TLX1 targets based on transcriptional assays. These results demonstrate that TLX1 can act broadly to impair haemopoiesis and divert differentiation to an alternative fate. This may account for its ability to promote the pre-leukaemic state via perturbation of specific gene expression programs.

A microarray model system identifies potential new target genes of the proto-oncogene HOX11.

HOX11 is a homeobox gene originally identified at a chromosomal breakpoint in T-cell acute lymphoblastic leukemia (T-ALL). It is one of the most frequently deregulated genes in T-ALL, although the precise role of HOX11 in leukemogenesis as well as in normal development remains obscure. To gain more insight into the functional role of HOX11, we utilized a microarray model system to characterize the gene expression network that it directs. Using one of our T-ALL cell lines that had been stably transfected to express HOX11 and high-density oligonucleotide HG-U95A arrays, we identified a large number of differentially expressed genes in response to the enforced expression of HOX11. We focused on examining genes found to be up-regulated according to the microarray analysis and selected three putative target genes, NFKB2, SMARCD3, and NR4A3, for further investigation. We could not only confirm the up-regulation of NR4A3 by an independent method in all clones expressing HOX11, but luciferase reporter assays demonstrated that the effect that HOX11 exerted on the proximal promoter of NR4A3 was dependent on the presence of an intact homeodomain, providing support for the idea that HOX11 manifests its regulatory function via its action as a transcription factor.