Gene expression and matrix turnover in overused and damaged tendons

Chronic, painful conditions affecting tendons, frequently known as tendinopathy, are very common types of sporting injury. The tendon extracellular matrix is substantially altered in tendinopathy, and these changes are thought to precede and underlie the clinical condition. The tendon cell response to repeated minor injuries or “overuse” is thought to be a major factor in the development of tendinopathy. Changes in matrix turnover may also be effected by the cellular response to physical load, altering the balance of matrix turnover and changing the structure and composition of the tendon. Matrix turnover is relatively high in tendons exposed to high mechanical demands, such as the supraspinatus and Achilles, and this is thought to represent either a repair or tissue maintenance function. Metalloproteinases are a large family of enzymes capable of degrading all of the tendon matrix components, and these are thought to play a major role in the degradation of matrix during development, adaptation and repair. It is proposed that some metalloproteinase enzymes are required for the health of the tendon, and others may be damaging, leading to degeneration of the tissue. Further research is required to investigate how these enzyme activities are regulated in tendon and altered in tendinopathy. A profile of all the metalloproteinases expressed and active in healthy and degenerate tendon is required and may lead to the development of new drug therapies for these common and debilitating sports injuries

PCA-induced respiratory depression simulating stroke following endoluminal repair of abdominal aortic aneurysm: a case report

<p>Abstract</p> <p>Aim</p> <p>To report a case of severe respiratory depression with PCA fentanyl use simulating stroke in a patient who underwent routine elective endoluminal graft repair for abdominal aortic aneurysm (AAA)</p> <p>Case presentation</p> <p>A 78-year-old obese lady underwent routine endoluminal graft repair for AAA that was progressively increasing in size. Following an uneventful operation postoperative analgesia was managed with a patient-controlled analgesia (PCA) device with fentanyl. On the morning following operation the patient was found to be unusually drowsy and unresponsive to stimuli. Her GCS level was 11 with plantars upgoing bilaterally. A provisional diagnosis of stroke was made. Urgent transfer to a high-dependency unit (HDU) was arranged and she was given ventilatory support with a BiPap device. CT was performed and found to be normal. Arterial blood gas (ABG) analysis showed respiratory acidosis with PaCO₂81 mmHg, PaO₂140 mmHg, pH 7.17 and base excess -2 mmol/l. A total dose of 600 mcg of fentanyl was self-administered in the 16 hours following emergence from general anaesthesia. Naloxone was given with good effect. There was an increase in the creatinine level from 90 μmol/L preoperatively to 167 μmol/L on the first postoperative day. The patient remained on BiPap for two days that resulted in marked improvement in gas exchange. Recovery was complete.</p

Bivariate random-effects meta-analysis and the estimation of between-study correlation

BACKGROUND: When multiple endpoints are of interest in evidence synthesis, a multivariate meta-analysis can jointly synthesise those endpoints and utilise their correlation. A multivariate random-effects meta-analysis must incorporate and estimate the between-study correlation (ρ(B)). METHODS: In this paper we assess maximum likelihood estimation of a general normal model and a generalised model for bivariate random-effects meta-analysis (BRMA). We consider two applied examples, one involving a diagnostic marker and the other a surrogate outcome. These motivate a simulation study where estimation properties from BRMA are compared with those from two separate univariate random-effects meta-analyses (URMAs), the traditional approach. RESULTS: The normal BRMA model estimates ρ(B )as -1 in both applied examples. Analytically we show this is due to the maximum likelihood estimator sensibly truncating the between-study covariance matrix on the boundary of its parameter space. Our simulations reveal this commonly occurs when the number of studies is small or the within-study variation is relatively large; it also causes upwardly biased between-study variance estimates, which are inflated to compensate for the restriction on [Formula: see text] (B). Importantly, this does not induce any systematic bias in the pooled estimates and produces conservative standard errors and mean-square errors. Furthermore, the normal BRMA is preferable to two normal URMAs; the mean-square error and standard error of pooled estimates is generally smaller in the BRMA, especially given data missing at random. For meta-analysis of proportions we then show that a generalised BRMA model is better still. This correctly uses a binomial rather than normal distribution, and produces better estimates than the normal BRMA and also two generalised URMAs; however the model may sometimes not converge due to difficulties estimating ρ(B). CONCLUSION: A BRMA model offers numerous advantages over separate univariate synthesises; this paper highlights some of these benefits in both a normal and generalised modelling framework, and examines the estimation of between-study correlation to aid practitioners

Controlling infectious disease outbreaks: Lessons from mathematical modelling.

Accepted versio

Social, Structural and Behavioral Determinants of Overall Health Status in a Cohort of Homeless and Unstably Housed HIV-Infected Men

Background: Previous studies indicate multiple influences on the overall health of HIV-infected persons; however, few assess and rank longitudinal changes in social and structural barriers that are disproportionately found in impoverished populations. We empirically ranked factors that longitudinally impact the overall health status of HIV-infected homeless and unstably housed men. Methods and Findings: Between 2002 and 2008, a cohort of 288 HIV+ homeless and unstably housed men was recruited and followed over time. The population was 60 % non-Caucasian and the median age was 41 years; 67 % of study participants reported recent drug use and 20 % reported recent homelessness. At baseline, the median CD4 cell count was 349 cells/ml and 18 % of eligible persons (CD4,350) took antiretroviral therapy (ART). Marginal structural models were used to estimate the population-level effects of behavioral, social, and structural factors on overall physical and mental health status (measured by the SF-36), and targeted variable importance (tVIM) was used to empirically rank factors by their influence. After adjusting for confounding, and in order of their influence, the three factors with the strongest negative effects on physical health were unmet subsistence needs, Caucasian race, and no reported source of instrumental support. The three factors with the strongest negative effects on mental health were unmet subsistence needs, not having a close friend/confidant, and drug use. ART adherence.90 % ranked 5th for its positive influence on mental health, and viral loa

Effective, Robust Design of Community Mitigation for Pandemic Influenza: A Systematic Examination of Proposed US Guidance

BACKGROUND: The US government proposes pandemic influenza mitigation guidance that includes isolation and antiviral treatment of ill persons, voluntary household member quarantine and antiviral prophylaxis, social distancing of individuals, school closure, reduction of contacts at work, and prioritized vaccination. Is this the best strategy combination? Is choice of this strategy robust to pandemic uncertainties? What are critical enablers of community resilience? METHODS AND FINDINGS: We systematically simulate a broad range of pandemic scenarios and mitigation strategies using a networked, agent-based model of a community of explicit, multiply-overlapping social contact networks. We evaluate illness and societal burden for alterations in social networks, illness parameters, or intervention implementation. For a 1918-like pandemic, the best strategy minimizes illness to <1% of the population and combines network-based (e.g. school closure, social distancing of all with adults' contacts at work reduced), and case-based measures (e.g. antiviral treatment of the ill and prophylaxis of household members). We find choice of this best strategy robust to removal of enhanced transmission by the young, additional complexity in contact networks, and altered influenza natural history including extended viral shedding. Administration of age-group or randomly targeted 50% effective pre-pandemic vaccine with 7% population coverage (current US H5N1 vaccine stockpile) had minimal effect on outcomes. In order, mitigation success depends on rapid strategy implementation, high compliance, regional mitigation, and rigorous rescinding criteria; these are the critical enablers for community resilience. CONCLUSIONS: Systematic evaluation of feasible, recommended pandemic influenza interventions generally confirms the US community mitigation guidance yields best strategy choices for pandemic planning that are robust to a wide range of uncertainty. The best strategy combines network- and case-based interventions; network-based interventions are paramount. Because strategies must be applied rapidly, regionally, and stringently for greatest benefit, preparation and public education is required for long-lasting, high community compliance during a pandemic

Has education lost sight of children?

The reflections presented in this chapter are informed by clinical and personal experiences of school education in the UK. There are many challenges for children and young people in the modern education system and for the professionals who support them. In the UK, there are significant gaps between the highly selective education provided to those who pay privately for it and to the majority of those educated in the state-funded system. Though literacy rates have improved around the world, many children, particularly boys, do not finish their education for reasons such as boredom, behavioural difficulties or because education does not ‘pay’. Violence, bullying, and sexual harassment are issues faced by many children in schools and there are disturbing trends of excluding children who present with behavioural problems at school whose origins are not explored. Excluded children are then educated with other children who may also have multiple problems which often just make the situation worse. The experience of clinicians suggests that school-related mental health problems are increasing in severity. Are mental health services dealing with the consequences of an education system that is not meeting children’s needs? An education system that is testing- and performance-based may not be serving many children well if it is driving important decisions about them at increasingly younger ages. Labelling of children and setting them on educational career paths can occur well before they reach secondary schools, limiting potential very early on in their developmental trajectory. Furthermore, the emphasis at school on testing may come at the expense of creativity and other forms of intelligence, which are also valuable and important. Meanwhile the employment marketplace requires people with widely different skills, with an emphasis on innovation, creativity, and problem solving. Is education losing sight of the children it is educating

Using social media to support small group learning

Abstract Background Medical curricula are increasingly using small group learning and less didactic lecture-based teaching. This creates new challenges and opportunities in how students are best supported with information technology. We explored how university-supported and external social media could support collaborative small group working on our new undergraduate medical curriculum. Methods We made available a curation platform (Scoop.it) and a wiki within our virtual learning environment as part of year 1 Case-Based Learning, and did not discourage the use of other tools such as Facebook. We undertook student surveys to capture perceptions of the tools and information on how they were used, and employed software user metrics to explore the extent to which they were used during the year. Results Student groups developed a preferred way of working early in the course. Most groups used Facebook to facilitate communication within the group, and to host documents and notes. There were more barriers to using the wiki and curation platform, although some groups did make extensive use of them. Staff engagement was variable, with some tutors reviewing the content posted on the wiki and curation platform in face-to-face sessions, but not outside these times. A small number of staff posted resources and reviewed student posts on the curation platform. Conclusions Optimum use of these tools depends on sufficient training of both staff and students, and an opportunity to practice using them, with ongoing support. The platforms can all support collaborative learning, and may help develop digital literacy, critical appraisal skills, and awareness of wider health issues in society

Prognostic markers in cancer: the evolution of evidence from single studies to meta-analysis, and beyond

In oncology, prognostic markers are clinical measures used to help elicit an individual patient's risk of a future outcome, such as recurrence of disease after primary treatment. They thus facilitate individual treatment choice and aid in patient counselling. Evidence-based results regarding prognostic markers are therefore very important to both clinicians and their patients. However, there is increasing awareness that prognostic marker studies have been neglected in the drive to improve medical research. Large protocol-driven, prospective studies are the ideal, with appropriate statistical analysis and clear, unbiased reporting of the methods used and the results obtained. Unfortunately, published prognostic studies rarely meet such standards, and systematic reviews and meta-analyses are often only able to draw attention to the paucity of good-quality evidence. We discuss how better-quality prognostic marker evidence can evolve over time from initial exploratory studies, to large protocol-driven primary studies, and then to meta-analysis or even beyond, to large prospectively planned pooled analyses and to the initiation of tumour banks. We highlight articles that facilitate each stage of this process, and that promote current guidelines aimed at improving the design, analysis, and reporting of prognostic marker research. We also outline why collaborative, multi-centre, and multi-disciplinary teams should be an essential part of future studies