Attitudes to living and working in pandemic conditions among emergency prehospital medical care personnel

Introduction: Little is known about the risk perceptions and attitudes of healthcare personnel, especially of emergency prehospital medical care personnel, regarding the possibility of an outbreak or epidemic event. Problem: This study was designed to investigate pre-event knowledge and attitudes of a national sample of the emergency prehospital medical care providers in relation to a potential human influenza pandemic, and to determine predictors of these attitudes. Methods: Surveys were distributed to a random, cross-sectional sample of 20% of the Australian emergency prehospital medical care workforce (n = 2,929), stratified by the nine services operating in Australia, as well as by gender and location. The surveys included: (1) demographic information; (2) knowledge of influenza; and (3) attitudes and perceptions related to working during influenza pandemic conditions. Multiple logistic regression models were constructed to identify predictors of pandemic-related risk perceptions. Results: Among the 725 Australian emergency prehospital medical care personnel who responded, 89% were very anxious about working during pandemic conditions, and 85% perceived a high personal risk associated with working in such conditions. In general, respondents demonstrated poor knowledge in relation to avian influenza, influenza generally, and infection transmission methods. Less than 5% of respondents perceived that they had adequate education/training about avian influenza. Logistic regression analyses indicate that, in managing the attitudes and risk perceptions of emergency prehospital medical care staff, particular attention should be directed toward the paid, male workforce (as opposed to volunteers), and on personnel whose relationship partners do not work in the health industry. Conclusions: These results highlight the potentially crucial role of education and training in pandemic preparedness. Organizations that provide emergency prehospital medical care must address this apparent lack of knowledge regarding infection transmission, and procedures for protection and decontamination. Careful management of the perceptions of emergency prehospital medical care personnel during a pandemic is likely to be critical in achieving an effective response to a widespread outbreak of infectious disease.

Transcutaneous immunization with novel lipid-based adjuvants induces protection against gastric Helicobacter pylori infection

The development of vaccines to combat pathogens that infect across mucosal surfaces has been a major goal of vaccine research. Successful mucosal vaccination requires the co-administration of adjuvants that can overcome the state of immune tolerance normally associated with mucosal application of proteins. In the case of oral immunization, delivery systems are also required to protect vaccine antigens against destruction by gastric pH and digestive enzymes. Furthermore, adjuvants used for mucosal delivery must be free of neurotoxic effects like those induced by the commonly used experimental mucosal adjuvant cholera toxin. Maintenance of the "cold chain" is also essential for the effectiveness of any vaccine and adjuvants/delivery systems that enhance the stability of a vaccine would offer a significant advantage. Needle-free methods of vaccination that induce protective immunity at multiple mucosal surfaces are also desirable for rapid vaccination of large populations. In the present study we show that transcutaneous immunization (TCI) using Lipid C, a novel lipid-based matrix originally developed for oral immunization, containing soluble Helicobacter sonicate significantly reduces the gastric bacterial burden in mice following gastric challenge with live Helicobacter pylori. Protection is associated with the production of splenic gamma interferon and gastric IgA and was achieved without the co-administration of potent and potentially toxic adjuvants, although protection was further enhanced by inclusion of CpG-ODN and cholera toxin in the lipid delivery system.

A collagen network phase improves cell seeding of open-pore structure scaffolds under perfusion

Scaffolds with open-pore morphologies offer several advantages in cell-based tissue engineering, but their use is limited by a low cell seeding efficiency. We hypothesized that inclusion of a collagen network as filling material within the open-pore architecture of polycaprolactone-tricalcium phosphate (PCL-TCP) scaffolds increases human bone marrow stromal cells (hBMSC) seeding efficiency under perfusion and in vivo osteogenic capacity of the resulting constructs. PCL-TCP scaffolds, rapid prototyped with a honeycomb-like architecture, were filled with a collagen gel and subsequently lyophilized, with or without final crosslinking. Collagen-free scaffolds were used as controls. The seeding efficiency was assessed after overnight perfusion of expanded hBMSC directly through the scaffold pores using a bioreactor system. By seeding and culturing freshly harvested hBMSC under perfusion for 3 weeks, the osteogenic capacity of generated constructs was tested by ectopic implantation in nude mice. The presence of the collagen network, independently of the crosslinking process, significantly increased the cell seeding efficiency (2.5-fold), and reduced the loss of clonogenic cells in the supernatant. Although no implant generated frank bone tissue, possibly due to the mineral distribution within the scaffold polymer phase, the presence of a non crosslinked collagen phase led to in vivo formation of scattered structures of dense osteoids. Our findings verify that the inclusion of a collagen network within open morphology porous scaffolds improves cell retention under perfusion seeding. In the context of cell-based therapies, collagen-filled porous scaffolds are expected to yield superior cell utilization, and could be combined with perfusion-based bioreactor devices to streamline graft manufacture.

A systematic review of environmental factors and obesogenic dietary intakes among adults : are we getting closer to understanding obesogenic environments?

This study examined whether physical, social, cultural and economical environmental factors are associated with obesogenic dietary behaviours and overweight/obesity among adults. Literature searches of databases (i.e. PubMed, CSA Illumina, Web of Science, PsychInfo) identified studies examining environmental factors and the consumption of energy, fat, fibre, fruit, vegetables, sugar-sweetened drinks, meal patterns and weight status. Twenty-eight studies were in-scope, the majority (n= 16) were conducted in the USA. Weight status was consistently associated with the food environment; greater accessibility to supermarkets or less access to takeaway outlets were associated with a lower BMI or prevalence of overweight/obesity. However, obesogenic dietary behaviours did not mirror these associations; mixed associations were found between the environment and obesogenic dietary behaviours. Living in a socioeconomically-deprived area was the only environmental factor consistently associated with a number of obesogenic dietary behaviours. Associations between the environment and weight status are more consistent than that seen between the environment and dietary behaviours. The environment may play an important role in the development of overweight/obesity, however the dietary mechanisms that contribute to this remain unclear and the physical activity environment may also play an important role in weight gain, overweight and obesity.

On the data consumption benefits of accepting increased uncertainty

In the context of learning paradigms of identification in the limit, we address the question: why is uncertainty sometimes desirable? We use mind change bounds on the output hypotheses as a measure of uncertainty and interpret ‘desirable’ as reduction in data memorization, also defined in terms of mind change bounds. The resulting model is closely related to iterative learning with bounded mind change complexity, but the dual use of mind change bounds — for hypotheses and for data — is a key distinctive feature of our approach. We show that situations exist where the more mind changes the learner is willing to accept, the less the amount of data it needs to remember in order to converge to the correct hypothesis. We also investigate relationships between our model and learning from good examples, set-driven, monotonic and strong-monotonic learners, as well as class-comprising versus class-preserving learnability.