The field of antibiotic drug discovery and the monitoring of new antibiotic resistance elements have yet to fully exploit the power of the genome revolution. Despite the fact that the first genomes sequenced of free living organisms were those of bacteria, there have been few specialized bioinformatic tools developed to mine the growing amount of genomic data associated with pathogens. In particular, there are few tools to study the genetics and genomics of antibiotic resistance and how it impacts bacterial populations, ecology, and the clinic. We have initiated development of such tools in the form of the Comprehensive Antibiotic Research Database (CARD; http://arpcard.mcmaster.ca). The CARD integrates disparate molecular and sequence data, provides a unique organizing principle in the form of the Antibiotic Resistance Ontology (ARO), and can quickly identify putative antibiotic resistance genes in new unannotated genome sequences. This unique platform provides an informatic tool that bridges antibiotic resistance concerns in health care, agriculture, and the environment.A ntibiotic resistance is an increasing crisis as both the range of microbial antibiotic resistance in clinical settings expands and the pipeline for development of new antibiotics contracts (1). This problem is compounded by the global genomic scope of the antibiotic resistome, such that antibiotic resistance spans a continuum from genes in pathogens found in the clinic to those of benign environmental microbes along with their proto-resistance gene progenitors (2, 3). The recent emergence of New Delhi metallo-ß-lactamase (NDM-1) in Gram-negative organisms (4), which can hydrolyze all ␤-lactams with the exception of monobactams, illustrates the capacity of new antibiotic resistance genes to emerge rapidly from as-yet-undetermined reservoirs. Surveys of genes originating from both clinical and environmental sources (microbes and metagenomes) will provide increasing insight into these reservoirs and offer predictive capacity for the emergence and epidemiology of antibiotic resistance.The increasing opportunity to prepare a broader and comprehensive antibiotic resistance gene census is facilitated by the power and falling costs of next-generation DNA sequencing. For example, whole-genome sequencing (WGS) is being increasingly used to examine new antibiotic-resistant isolates discovered in clinical settings (5). Additionally, culture-independent metagenomic surveys are adding tremendously to the pool of known genes and their distribution outside clinical settings (6, 7). These approaches have the advantage of providing a rapid survey of the antibiotic resistome of new strains, the discovery of newly emergent antibiotic resistance genes, the epidemiology of antibiotic resistance genes, and the horizontal gene transfer (HGT) of known antibiotic resistance genes through plasmids and transposable elements. However, despite the existence of tools for general annotation of prokaryotic genomes (see, e.g., reference 8), prediction of an antibiotic resista...

Background Patients with coexisting type 2 diabetes and hypertension generally exhibit poor adherence to self-management, which adversely affects their disease control. Therefore, identification of the factors related to patient adherence is warranted. In this study, we aimed to examine (i) the socio-demographic correlates of patient adherence to a set of self-management behaviors relevant to type 2 diabetes and hypertension, namely, medication therapy, diet therapy, exercise, tobacco and alcohol avoidance, stress reduction, and self-monitoring/self-care, and (ii) whether health attitudes and self-efficacy in performing self-management mediated the associations between socio-demographic characteristics and adherence. Methods We performed a secondary analysis of data collected in a randomized controlled trial. The sample comprised 148 patients with coexisting type 2 diabetes mellitus and hypertension. Data were collected by a questionnaire and analyzed using logistic regression. Results Female patients were found to be less likely to exercise regularly (odds ratio [OR] = 0.49, P = 0.03) and more likely to avoid tobacco and alcohol (OR = 9.87, P < 0.001) than male patients. Older patients were found to be more likely to adhere to diet therapy (OR = 2.21, P = 0.01) and self-monitoring/self-care (OR = 2.17, P = 0.02). Patients living with family or others (e.g., caregivers) were found to be more likely to exercise regularly (OR = 3.44, P = 0.02) and less likely to avoid tobacco and alcohol (OR = 0.10, P = 0.04) than those living alone. Patients with better perceived health status were found to be more likely to adhere to medication therapy (OR = 2.02, P = 0.03). Patients with longer diabetes duration (OR = 2.33, P = 0.01) were found to be more likely to adhere to self-monitoring/self-care. Self-efficacy was found to mediate the association between older age and better adherence to diet therapy, while no significant mediating effects were found for health attitudes. Conclusions Adherence to self-management was found to be associated with socio-demographic characteristics (sex, age, living status, perceived health status, and diabetes duration). Self-efficacy was an important mediator in some of these associations, suggesting that patient adherence may be improved by increasing patients’ self-management efficacy, such as by patient empowerment, collaborative care, or enhanced patient–physician interactions.

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The past decade has seen the proliferation of health information portals; however, consumer acceptance of the portals has proven difficult and rate of use has been limited. This study developed a consumer acceptance model by integrating usability and social cognitive theories with the technology acceptance model to explain young Internet users’ acceptance of health information portals. Participants (n = 201) completed a self-report questionnaire measuring model constructs after attending a usability testing with a typical health information portal. Results showed that the hypothesized model accounted for 56 percent of the variance in behavioral intention to use the portal and explained consumer acceptance well. Both subjective usability and application-specific self-efficacy served as significant antecedents in the model, while application-specific self-efficacy also moderated the effect of subjective usability on perceived ease of use. The findings can help practitioners with the design and implementation of health information portals and other health informatics applications in support of consumer acceptance.