12,920 research outputs found
Lessons from the Canadian Cattle Industry for Developing the National Animal Identification System
The primary focus of animal identification programs, which are rapidly developing throughout the world, is to effectively respond to animal health emergencies that have the potential to cause devastating consequences to animal and public health. Additional benefits of an animal identification program include maintaining or expanding international trade, increased consumer confidence, and improved supply chain management. The primary objective of this paper is to provide a series of recommendations for the U.S. to consider as it continues to develop the National Animal Identification System. The secondary objective is to explain how some progressive operations, spanning all sectors of the live cattle and beef industry supply chain complex in Canada, have utilized the technology of the mandatory cattle identification program to improve management intensity.Animal Identification, Canadian Cattle Identification Agency, National Animal Identification System, Research and Development/Tech Change/Emerging Technologies, Q10, Q16,
A pilot study of the S-MAP (Solutions for Medications Adherence Problems) intervention for older adults prescribed polypharmacy in primary care: Study protocol
Background: Adhering to multiple medications as prescribed is challenging for older patients (aged ≥ 65 years) and a difficult behaviour to improve. Previous interventions designed to address this have been largely complex in nature but have shown limited effectiveness and have rarely used theory in their design. It has been recognised that theory ('a systematic way of understanding events or situations') can guide intervention development and help researchers better understand how complex adherence interventions work. This pilot study aims to test a novel community pharmacy-based intervention that has been systematically developed using the Theoretical Domains Framework (12-domain version) of behaviour change. Methods: As part of a non-randomised pilot study, pharmacists in 12 community pharmacies across Northern Ireland (n = 6) and London, England (n = 6), will be trained to deliver the intervention to older patients who are prescribed ≥ 4 regular medicines and are non-adherent (self-reported). Ten patients will be recruited per pharmacy (n = 120) and offered up to four tailored one-to-one sessions, in the pharmacy or via telephone depending on their adherence, over a 3-4-month period. Guided by an electronic application (app) on iPads, the intervention content will be tailored to each patient's underlying reasons for non-adherence and mapped to the most appropriate solutions using established behaviour change techniques. This study will assess the feasibility of collecting data on the primary outcome of medication adherence (self-report and dispensing data) and secondary outcomes (health-related quality of life and unplanned hospitalisations). An embedded process evaluation will assess training fidelity for pharmacy staff, intervention fidelity, acceptability to patients and pharmacists and the intervention's mechanism of action. Process evaluation data will include audio-recordings of training workshops, intervention sessions, feedback interviews and patient surveys. Analysis will be largely descriptive. Discussion: Using pre-defined progression criteria, the findings from this pilot study will guide the decision whether to proceed to a cluster randomised controlled trial to test the effectiveness of the S-MAP intervention in comparison to usual care in community pharmacies. The study will also explore how the intervention components may work to bring about change in older patients' adherence behaviour and guide further refinement of the intervention and study procedures. Trial registration: This study is registered at ISRCTN: https://doi.org/10.1186/ISRCTN7383153
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Propagation of Pericentral Necrosis During Acetaminophen-Induced Liver Injury: Evidence for Early Interhepatocyte Communication and Information Exchange.
Acetaminophen (APAP)-induced liver injury is clinically significant, and APAP overdose in mice often serves as a model for drug-induced liver injury in humans. By specifying that APAP metabolism, reactive metabolite formation, glutathione depletion, and mitigation of mitochondrial damage within individual hepatocytes are functions of intralobular location, an earlier virtual model mechanism provided the first concrete multiattribute explanation for how and why early necrosis occurs close to the central vein (CV). However, two characteristic features could not be simulated consistently: necrosis occurring first adjacent to the CV, and subsequent necrosis occurring primarily adjacent to hepatocytes that have already initiated necrosis. We sought parsimonious model mechanism enhancements that would manage spatiotemporal heterogeneity sufficiently to enable meeting two new target attributes and conducted virtual experiments to explore different ideas for model mechanism improvement at intrahepatocyte and multihepatocyte levels. For the latter, evidence supports intercellular communication via exosomes, gap junctions, and connexin hemichannels playing essential roles in the toxic effects of chemicals, including facilitating or counteracting cell death processes. Logic requiring hepatocytes to obtain current information about whether downstream and lateral neighbors have triggered necrosis enabled virtual hepatocytes to achieve both new target attributes. A virtual hepatocyte that is glutathione-depleted uses that information to determine if it will initiate necrosis. When a less-stressed hepatocyte is flanked by at least two neighbors that have triggered necrosis, it too will initiate necrosis. We hypothesize that the resulting intercellular communication-enabled model mechanism is analogous to the actual explanation for APAP-induced hepatotoxicity at comparable levels of granularity
Prospective investigation of complementary and alternative medicine use and subsequent hospitalizations
<p>Abstract</p> <p>Background</p> <p>The prevalence of complementary and alternative medicine (CAM) use has been estimated to be as high as 65% in some populations. However, there has been little objective research into the possible risks or benefits of unmanaged CAM therapies.</p> <p>Methods</p> <p>In this prospective study of active duty US Navy and Marine Corps personnel, the association between self-reported practitioner-assisted or self-administered CAM use and future hospitalization was investigated. Cox regression models were used to examine risk of hospitalization due to any cause over the follow-up period from date of questionnaire submission, until hospitalization, separation from the military, or end of observation period (June 30, 2004), whichever occurred first.</p> <p>Results</p> <p>After adjusting for baseline health, baseline trust and satisfaction with conventional medicine, and demographic characteristics, those who reported self-administering two or more CAM therapies were significantly less likely to be hospitalized for any cause when compared with those who did not self-administer CAM (HR = 0.38; 95% CI = 0.17, 0.86). Use of multiple practitioner-assisted CAM was not associated with a significant decrease or increase of risk for future hospitalization (HR = 1.86; 95 percent confidence interval = 0.96-3.63).</p> <p>Conclusion</p> <p>While there were limitations to these analyses, this investigation utilized an objective measure of health to investigate the potential health effects of CAM therapies and found a modest reduction in the overall risk of hospitalization associated with self-administration of two or more CAM therapies. In contrast, use of practitioner-assisted CAM was not associated with a protective effect.</p
False discovery rate regression: an application to neural synchrony detection in primary visual cortex
Many approaches for multiple testing begin with the assumption that all tests
in a given study should be combined into a global false-discovery-rate
analysis. But this may be inappropriate for many of today's large-scale
screening problems, where auxiliary information about each test is often
available, and where a combined analysis can lead to poorly calibrated error
rates within different subsets of the experiment. To address this issue, we
introduce an approach called false-discovery-rate regression that directly uses
this auxiliary information to inform the outcome of each test. The method can
be motivated by a two-groups model in which covariates are allowed to influence
the local false discovery rate, or equivalently, the posterior probability that
a given observation is a signal. This poses many subtle issues at the interface
between inference and computation, and we investigate several variations of the
overall approach. Simulation evidence suggests that: (1) when covariate effects
are present, FDR regression improves power for a fixed false-discovery rate;
and (2) when covariate effects are absent, the method is robust, in the sense
that it does not lead to inflated error rates. We apply the method to neural
recordings from primary visual cortex. The goal is to detect pairs of neurons
that exhibit fine-time-scale interactions, in the sense that they fire together
more often than expected due to chance. Our method detects roughly 50% more
synchronous pairs versus a standard FDR-controlling analysis. The companion R
package FDRreg implements all methods described in the paper
Component Microenvironments and System Biogeography Structure Microorganism Distributions in Recirculating Aquaculture and Aquaponic Systems
ABSTRACT Flowthrough and pond aquaculture system microbiome management practices aim to mitigate fish disease and stress. However, the operational success of recirculating aquaculture systems (RAS) depends directly on system microbial community activities. In RAS, each component environment is engineered for a specific microbial niche for waste management, as the water continuously flowing through the system must be processed before returning to the rearing tank. In this study, we compared waste management component microbiomes (rearing tank water, pH correction tank, solid-waste clarifier, biofilter, and degassing tower) within a commercial-scale freshwater RAS by high-throughput 16S rRNA gene sequencing. To assess consistency among freshwater RAS microbiomes, we also compared the microbial community compositions of six aquaculture and aquaponic farms. Community assemblages reflected site and source water relationships, and the presence of a hydroponic subsystem was a major community determinant. In contrast to the facility-specific community composition, some sequence variants, mainly classified into Flavobacterium, Cetobacterium, the family Sphingomonadaceae, and nitrifying guilds of ammonia-oxidizing archaea and Nitrospira, were common across all facilities. The findings of this study suggest that, independently of system design, core taxa exist across RAS rearing similar fish species but that system design informs the individual aquatic microbiome assemblages. Future RAS design would benefit from understanding the roles of these core taxa and then capitalizing on their activities to further reduce system waste/added operational controls.
IMPORTANCE Recirculating aquaculture systems (RAS) are agroecosystems for intensive on-land cultivation of products of fisheries. Practitioners that incorporate edible plant production into RAS refer to these facilities as aquaponic systems (AP). RAS have the potential to offset declining production levels of wild global fisheries while reducing waste and product distance to market, but system optimization is needed to reduce costs. Both RAS and AP rely on microbial consortia for maintaining water quality and promoting fish/plant health, but little is known about the microorganisms actually present. This lack of knowledge prevents optimization of designs and operational controls to target the growth of beneficial microbial species or consortia. The significance of our research is in identifying the common microorganisms that inhabit production RAS and AP and the operational factors that influence which microorganisms colonize and become abundant. Identifying these organisms is a first step toward advanced control of microbial activities that improve reproducibility and reduce costs
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