Calcification of Rat Valve Allografts

Scanning electron microscopy (SEM) and energy dispersive X-ray microanalysis (EDS) have been used to quantify calcium deposition in bioprosthetic valves. To further characterize the calcification process as it pertains to allograft valve tissue, two models of tissue valve implantation were used. The first model used subcutaneous implantation of glutaraldehyde-preserved allogeneic aortic and pulmonary valve leaflets. The second model used syngeneic or allogeneic fresh aortic valve grafts implanted heterotopically into the abdominal aorta of recipient rats. Reference light microscopy was used to select sections for SEM and EDS. In the subcutaneous model, calcium content in both the pulmonary and aortic valves increased up to three weeks, followed by a plateau. The pulmonary leaflets showed greater calcium content than aortic leaflets. In the heterotopic implantation study, calcification occurred to a significantly greater degree in the allogeneic than in the syngeneic valves. This technique may be useful in analyzing the factors that contribute to deterioration of bioprosthetic and allograft valves

Expressions 1997

https://openspace.dmacc.edu/expressions/1017/thumbnail.jp

Effects of Eyjafjallajökull volcanic ash on innate immune system responses and bacterial growth in vitro.

To access publisher's full text version of this article click on the hyperlink at the bottom of the pageOn 20 March 2010, the Icelandic volcano Eyjafjallajökull erupted for the first time in 190 years. Despite many epidemiological reports showing effects of volcanic ash on the respiratory system, there are limited data evaluating cellular mechanisms involved in the response to ash. Epidemiological studies have observed an increase in respiratory infections in subjects and populations exposed to volcanic eruptions.We physicochemically characterized volcanic ash, finding various sizes of particles, as well as the presence of several transition metals, including iron. We examined the effect of Eyjafjallajökull ash on primary rat alveolar epithelial cells and human airway epithelial cells (20-100 µg/cm(2)), primary rat and human alveolar macrophages (5-20 µg/cm(2)), and Pseudomonas aeruginosa (PAO1) growth (3 µg/104 bacteria).Volcanic ash had minimal effect on alveolar and airway epithelial cell integrity. In alveolar macrophages, volcanic ash disrupted pathogen-killing and inflammatory responses. In in vitro bacterial growth models, volcanic ash increased bacterial replication and decreased bacterial killing by antimicrobial peptides.These results provide potential biological plausibility for epidemiological data that show an association between air pollution exposure and the development of respiratory infections. These data suggest that volcanic ash exposure, while not seriously compromising lung cell function, may be able to impair innate immunity responses in exposed individuals.National Institutes of Health (NIH) R01 HL079901 NIH RO1 HL096625 R21HL109589 National Science Foundation NSF-EAR0821615 National Institute of Environmental Health Sciences (NIEHS) through the University of Iowa Environmental Health Sciences Research Center NIEHS/NIH P30 ES005605 National Center for Research Resources, NI

Improving access for community health and sub-acute outpatient services: protocol for a stepped wedge cluster randomised controlled trial

BACKGROUND: Waiting lists for treatment are common in outpatient and community services, Existing methods for managing access and triage to these services can lead to inequities in service delivery, inefficiencies and divert resources from frontline care. Evidence from two controlled studies indicates that an alternative to the traditional &quot;waitlist and triage&quot; model known as STAT (Specific Timely Appointments for Triage) may be successful in reducing waiting times without adversely affecting other aspects of patient care. This trial aims to test whether the model is cost effective in reducing waiting time across multiple services, and to measure the impact on service provision, health-related quality of life and patient satisfaction. METHODS/DESIGN: A stepped wedge cluster randomised controlled trial has been designed to evaluate the impact of the STAT model in 8 community health and outpatient services. The primary outcome will be waiting time from referral to first appointment. Secondary outcomes will be nature and quantity of service received (collected from all patients attending the service during the study period and health-related quality of life (AQOL-8D), patient satisfaction, health care utilisation and cost data (collected from a subgroup of patients at initial assessment and after 12&nbsp;weeks). Data will be analysed with a multiple multi-level random-effects regression model that allows for cluster effects. An economic evaluation will be undertaken alongside the clinical trial. DISCUSSION: This paper outlines the study protocol for a fully powered prospective stepped wedge cluster randomised controlled trial (SWCRCT) to establish whether the STAT model of access and triage can reduce waiting times applied across multiple settings, without increasing health service costs or adversely impacting on other aspects of patient care. If successful, it will provide evidence for the effectiveness of a practical model of access that can substantially reduce waiting time for outpatient and community services with subsequent benefits for both efficiency of health systems and patient care.<br /

Factors associated with anxiety disorder comorbidity

Background Anxiety and depressive disorders often co-occur and the order of their emergence may be associated with different clinical outcomes. However, minimal research has been conducted on anxiety-anxiety comorbidity. This study examined factors associated with anxiety comorbidity and anxiety-MDD temporal sequence. Methods Online, self-report data were collected from the UK-based GLAD and COPING NBR cohorts (N = 38,775). Logistic regression analyses compared differences in sociodemographic, trauma, and clinical factors between single anxiety, anxiety-anxiety comorbidity, anxiety-MDD (major depressive disorder) comorbidity, and MDD-only. Additionally, anxiety-first and MDD-first anxiety-MDD were compared. Differences in familial risk were assessed in those participants with self-reported family history or genotype data. Results Anxiety-anxiety and anxiety-MDD had higher rates of self-reported anxiety or depressive disorder diagnoses, younger age of onset, and higher recurrence than single anxiety. Anxiety-MDD displayed greater clinical severity/complexity than MDD only. Anxiety-anxiety had more severe current anxiety symptoms, less severe current depressive symptoms, and reduced likelihood of self-reporting an anxiety/depressive disorder diagnosis than anxiety-MDD. Anxiety-first anxiety-MDD had a younger age of onset, more severe anxiety symptoms, and less likelihood of self-reporting a diagnosis than MDD-first. Minimal differences in familial risk were found. Limitations Self-report, retrospective measures may introduce recall bias. The familial risk analyses were likely underpowered. Conclusions Anxiety-anxiety comorbidity displayed a similarly severe and complex profile of symptoms as anxiety-MDD but distinct features. For anxiety-MDD, first-onset anxiety had an earlier age of onset and greater severity than MDD-first. Anxiety disorders and comorbidity warrant further investigation and attention in research and practice

An Integrated Approach to the Prediction of Chemotherapeutic Response in Patients with Breast Cancer

BACKGROUND: A major challenge in oncology is the selection of the most effective chemotherapeutic agents for individual patients, while the administration of ineffective chemotherapy increases mortality and decreases quality of life in cancer patients. This emphasizes the need to evaluate every patient's probability of responding to each chemotherapeutic agent and limiting the agents used to those most likely to be effective. METHODS AND RESULTS: Using gene expression data on the NCI-60 and corresponding drug sensitivity, mRNA and microRNA profiles were developed representing sensitivity to individual chemotherapeutic agents. The mRNA signatures were tested in an independent cohort of 133 breast cancer patients treated with the TFAC (paclitaxel, 5-fluorouracil, adriamycin, and cyclophosphamide) chemotherapy regimen. To further dissect the biology of resistance, we applied signatures of oncogenic pathway activation and performed hierarchical clustering. We then used mRNA signatures of chemotherapy sensitivity to identify alternative therapeutics for patients resistant to TFAC. Profiles from mRNA and microRNA expression data represent distinct biologic mechanisms of resistance to common cytotoxic agents. The individual mRNA signatures were validated in an independent dataset of breast tumors (P = 0.002, NPV = 82%). When the accuracy of the signatures was analyzed based on molecular variables, the predictive ability was found to be greater in basal-like than non basal-like patients (P = 0.03 and P = 0.06). Samples from patients with co-activated Myc and E2F represented the cohort with the lowest percentage (8%) of responders. Using mRNA signatures of sensitivity to other cytotoxic agents, we predict that TFAC non-responders are more likely to be sensitive to docetaxel (P = 0.04), representing a viable alternative therapy. CONCLUSIONS: Our results suggest that the optimal strategy for chemotherapy sensitivity prediction integrates molecular variables such as ER and HER2 status with corresponding microRNA and mRNA expression profiles. Importantly, we also present evidence to support the concept that analysis of molecular variables can present a rational strategy to identifying alternative therapeutic opportunities

PhagoSight: an open-source MATLAB® package for the analysis of fluorescent neutrophil and macrophage migration in a zebrafish model

Neutrophil migration in zebrafish larvae is increasingly used as a model to study the response of these leukocytes to different determinants of the cellular inflammatory response. However, it remains challenging to extract comprehensive information describing the behaviour of neutrophils from the multi-dimensional data sets acquired with widefield or confocal microscopes. Here, we describe PhagoSight, an open-source software package for the segmentation, tracking and visualisation of migrating phagocytes in three dimensions. The algorithms in PhagoSight extract a large number of measurements that summarise the behaviour of neutrophils, but that could potentially be applied to any moving fluorescent cells. To derive a useful panel of variables quantifying aspects of neutrophil migratory behaviour, and to demonstrate the utility of PhagoSight, we evaluated changes in the volume of migrating neutrophils. Cell volume increased as neutrophils migrated towards the wound region of injured zebrafish. PhagoSight is openly available as MATLAB® m-files under the GNU General Public License. Synthetic data sets and a comprehensive user manual are available from http://www.phagosight.org

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Psychology and aggression

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68264/2/10.1177_002200275900300301.pd

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas