The glia response after peripheral nerve injury: A comparison between Schwann cells and olfactory ensheathing cells and their uses for neural regenerative therapies

The peripheral nervous system (PNS) exhibits a much larger capacity for regeneration than the central nervous system (CNS). One reason for this difference is the difference in glial cell types between the two systems. PNS glia respond rapidly to nerve injury by clearing debris from the injury site, supplying essential growth factors and providing structural support; all of which enhances neuronal regeneration. Thus, transplantation of glial cells from the PNS is a very promising therapy for injuries to both the PNS and the CNS. There are two key types of PNS glia: olfactory ensheathing cells (OECs), which populate the olfactory nerve, and Schwann cells (SCs), which are present in the rest of the PNS. These two glial types share many similar morphological and functional characteristics but also exhibit key differences. The olfactory nerve is constantly turning over throughout life, which means OECs are continuously stimulating neural regeneration, whilst SCs only promote regeneration after direct injury to the PNS. This review presents a comparison between these two PNS systems in respect to normal physiology, developmental anatomy, glial functions and their responses to injury. A thorough understanding of the mechanisms and differences between the two systems is crucial for the development of future therapies using transplantation of peripheral glia to treat neural injuries and/or disease.Griffith Health, School of Nursing and MidwiferyFull Tex

Limitations for change detection in multiple Gabor targets

We investigate the limitations on the ability to detect when a target has changed, using Gabor targets as simple quantifiable stimuli. Using a partial report technique to equalise response variables, we show that the log of the Weber fraction for detecting a spatial frequency change is proportional to the log of the number of targets, with a set-size effect that is greater than that reported for visual search. This is not a simple perceptual limitation, because pre-cueing a single target out of four restores performance to the level found when only one target is present. It is argued that the primary limitation on performance is the division of attention across multiple targets, rather than decay within visual memory. However in a simplified change detection experiment without cueing, where only one target of the set changed, not only was the set size effect still larger, but it was greater at 2000 msec ISI than at 250 msec ISI, indicating a possible memory component. The steepness of the set size effects obtained suggests that even moderate complexity of a stimulus in terms of number of component objects can overload attentional processes, suggesting a possible low-level mechanism for change blindness

Pharmacist-led management of chronic pain in primary care:results from a randomised controlled exploratory trial

To compare the effectiveness of pharmacist medication review, with or without pharmacist prescribing, with standard care, for patients with chronic pain

Developing and using ontologies in behavioural science: addressing issues raised [version 1; peer review: awaiting peer review]

Ontologies are ways of representing aspects of the world in terms of uniquely defined classes of ‘entities’ and relationships between them. They are widely used in biological science, data science and commerce because they provide clarity, consistency, and the ability to link information and data from different sources. Ontologies offer great promise as representational systems in behavioural science and could revolutionise descriptions of studies and findings, and the expression of models and theories. This paper discusses issues that have been raised about using ontologies in behavioural science and how these can be addressed. The issues arise partly from the way that ontologies represent information, which can be perceived as reductionist or simplistic, and partly from issues to do with their implementation. However, despite the simplicity of their structure, ontologies can represent complex entities that change over time, as well as their inter-relationships and highly nuanced information about them. Nevertheless, ontologies are only one of many ways of representing information and it is important to recognise when other forms are more efficient. With regard to implementation, it is important to build ontologies with involvement from the communities who will be using them. Far from constraining intellectual creativity, ontologies that are broadly-based can facilitate expression of nuance, comparison of findings and integration of different approaches and theories. Maintaining and updating ontologies remain significant challenges but can be achieved through establishing and coordinating communities of practice

Predicting outcomes of smoking cessation interventions in novel scenarios using ontology-informed, interpretable machine learning

Background Systematic reviews of effectiveness estimate the relative average effects of interventions and comparators in a set of existing studies e.g., using rate ratios. However, policymakers, planners and practitioners require predictions about outcomes in novel scenarios where aspects of the interventions, populations or settings may differ. This study aimed to develop and evaluate an ontology-informed, interpretable machine learning algorithm to predict smoking cessation outcomes using detailed information about interventions, their contexts and evaluation study methods. This is the second of two linked papers on the use of machine learning in the Human Behaviour-Change Project. Methods The study used a corpus of 405 reports of randomised trials of smoking cessation interventions from the Cochrane Library database. These were annotated using the Behaviour Change Intervention Ontology to classify, for each of 971 study arms, 82 features representing details of intervention content and delivery, population, setting, outcome, and study methodology. The annotated data was used to train a novel machine learning algorithm based on a set of interpretable rules organised according to the ontology. The algorithm was evaluated for predictive accuracy by performance in five-fold 80:20 cross-validation, and compared with other approaches. Results The machine learning algorithm produced a mean absolute error in prediction percentage cessation rates of 9.15% in cross-validation, outperforming other approaches including an uninterpretable ‘black-box’ deep neural network (9.42%), a linear regression model (10.55%) and a decision tree-based approach (9.53%). The rules generated by the algorithm were synthesised into a consensus rule set to create a publicly available predictive tool to provide outcome predictions and explanations in the form of rules expressed in terms of predictive features and their combinations. Conclusions An ontologically-informed, interpretable machine learning algorithm, using information about intervention scenarios from reports of smoking cessation trials, can predict outcomes in new smoking cessation intervention scenarios with moderate accuracy.</ns3:p

B-type natriuretic peptide-guided treatment for heart failure

Background Heart failure is a condition in which the heart does not pump enough blood to meet all the needs of the body. Symptoms of heart failure include breathlessness, fatigue and fluid retention. Outcomes for patients with heart failure are highly variable; however on average, these patients have a poor prognosis. Prognosis can be improved with early diagnosis and appropriate use of medical treatment, use of devices and transplantation. Patients with heart failure are high users of healthcare resources, not only due to drug and device treatments, but due to high costs of hospitalisation care. B‐type natriuretic peptide levels are already used as biomarkers for diagnosis and prognosis of heart failure, but could offer to clinicians a possible tool to guide drug treatment. This could optimise drug management in heart failure patients whilst allaying concerns over potential side effects due to drug intolerance. Objectives To assess whether treatment guided by serial BNP or NT‐proBNP (collectively referred to as NP) monitoring improves outcomes compared with treatment guided by clinical assessment alone. Search methods Searches were conducted up to 15 March 2016 in the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library; MEDLINE (OVID), Embase (OVID), the Database of Abstracts of Reviews of Effects (DARE) and the NHS Economic Evaluation Database in the Cochrane Library. Searches were also conducted in the Science Citation Index Expanded, the Conference Proceedings Citation Index on Web of Science (Thomson Reuters), World Health Organization International Clinical Trials Registry and ClinicalTrials.gov. We applied no date or language restrictions. Selection criteria We included randomised controlled trials of NP‐guided treatment of heart failure versus treatment guided by clinical assessment alone with no restriction on follow‐up. Adults treated for heart failure, in both in‐hospital and out‐of‐hospital settings, and trials reporting a clinical outcome were included. Data collection and analysis Two review authors independently selected studies for inclusion, extracted data and evaluated risk of bias. Risk ratios (RR) were calculated for dichotomous data, and pooled mean differences (MD) (with 95% confidence intervals (CI)) were calculated for continuous data. We contacted trial authors to obtain missing data. Using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach, we assessed the quality of the evidence and GRADE profiler (GRADEPRO) was used to import data from Review Manager to create a 'Summary of findings' table. Main results We included 18 randomised controlled trials with 3660 participants (range of mean age: 57 to 80 years) comparing NP‐guided treatment with clinical assessment alone. The evidence for all‐cause mortality using NP‐guided treatment showed uncertainty (RR 0.87, 95% CI 0.76 to 1.01; patients = 3169; studies = 15; low quality of the evidence), and for heart failure mortality (RR 0.84, 95% CI 0.54 to 1.30; patients = 853; studies = 6; low quality of evidence). The evidence suggested heart failure admission was reduced by NP‐guided treatment (38% versus 26%, RR 0.70, 95% CI 0.61 to 0.80; patients = 1928; studies = 10; low quality of evidence), but the evidence showed uncertainty for all‐cause admission (57% versus 53%, RR 0.93, 95% CI 0.84 to 1.03; patients = 1142; studies = 6; low quality of evidence). Six studies reported on adverse events, however the results could not be pooled (patients = 1144; low quality of evidence). Only four studies provided cost of treatment results, three of these studies reported a lower cost for NP‐guided treatment, whilst one reported a higher cost (results were not pooled; patients = 931, low quality of evidence). The evidence showed uncertainty for quality of life data (MD ‐0.03, 95% CI ‐1.18 to 1.13; patients = 1812; studies = 8; very low quality of evidence). We completed a 'Risk of bias' assessment for all studies. The impact of risk of bias from lack of blinding of outcome assessment and high attrition levels was examined by restricting analyses to only low 'Risk of bias' studies. Authors' conclusions In patients with heart failure low‐quality evidence showed a reduction in heart failure admission with NP‐guided treatment while low‐quality evidence showed uncertainty in the effect of NP‐guided treatment for all‐cause mortality, heart failure mortality, and all‐cause admission. Uncertainty in the effect was further shown by very low‐quality evidence for patient's quality of life. The evidence for adverse events and cost of treatment was low quality and we were unable to pool results.</p

Factors influencing the impact of pharmacogenomic prescribing on adherence to nicotine replacement therapy: A qualitative study of participants from a randomized controlled trial.

Pharmacogenomics may improve health outcomes in two ways: by more precise and therefore more effective prescribing, tailored to genotype, and by increasing perceived effectiveness of treatments and so motivation for adherence. Little is known about patients' experiences of, and reactions to, receiving pharmacogenomically tailored treatments. The aim of this study was to explore the impact of pharmacogenomic prescribing of nicotine replacement therapy (NRT) on smokers' initial expectations of quit success, adherence, and perceived important differences from previous quit attempts. Semi-structured interviews were conducted with 40 smokers, purposively sampled from the Personalized Extra Treatment (PET) trial (ISRCTN 14352545). Together with NRT patches, participants were prescribed doses of oral NRT based on either mu-opioid receptor (OPRM1) genotype or nicotine dependence questionnaire score (phenotype). Data were analyzed using framework analysis, comparing views of participants in the two trial arms. Although most participants understood the basis for their prescribed NRT dose, it little influenced their views. The salient features of this quit attempt were the individualized behavioral support and combined NRT, not pharmacogenomic tailoring. Participants' initial expectations of success were mostly based on prior experiences of quitting. They attributed taking medication to nurse advice to do so, and attributed reducing or stopping it to side effects, forgetfulness, or practical difficulties. Intentional nonadherence appeared very rare. Pharmacogenomic NRT prescribing was not especially remarkable to participants and did not seem to influence adherence. Where services already tailor prescriptions to phenotype and provide individualized behavioral support for treatment adherence, pharmacogenomic prescribing may have limited additional benefit

Pharmacokinetics in neonatal prescribing: evidence base, paradigms and the future

Paediatric patients, particularly preterm neonates, present many pharmacological challenges. Due to the difficulty in conducting clinical trials in these populations dosing information is often extrapolated from adult populations. As the processes of absorption, distribution, metabolism and excretion of drugs change throughout growth and development extrapolation presents risk of over or underestimating the doses required. Information about the development these processes, particularly drug metabolism pathways, is still limited with weight based dose adjustment presenting the best method of estimating pharmacokinetic changes due to growth and development. New innovations in pharmacokinetic research, such as population pharmacokinetic modelling, present unique opportunities to conduct clinical trials in these populations improving the safety and effectiveness of the drugs used. More research is required into this area to ensure the best outcomes for our most vulnerable patients

Development and management of systemic lupus erythematosus in an HIV-infected man with hepatitis C and B co-infection following interferon therapy: a case report

<p>Abstract</p> <p>Introduction</p> <p>The association of human immunodeficiency virus and immune dysfunction leading to development of autoimmune markers is well described, but human immunodeficiency virus infection is relatively protective for the development of systemic lupus erythematosus. In contrast, development of systemic lupus erythematosus with hepatitis C and with interferon therapy is well described in a number of case reports. We here describe the first case of systemic lupus erythematosus developing in a man infected with human immunodeficiency virus, hepatitis C and hepatitis B co-infection where the onset seems to have been temporally related to interferon therapy.</p> <p>Case presentation</p> <p>We report the occurrence of systemic lupus erythematosus complicating interferon-α therapy for hepatitis C in a 47-year-old asplenic male with haemophilia co-infected with human immunodeficiency virus and hepatitis B. He presented with a truncal rash, abdominal pains and headache and later developed grade IV lupus nephritis requiring haemodialysis, mycophenolate mofetil and steroid therapy. We were able to successfully withdraw dialysis and mycophenolate while maintaining stable renal function.</p> <p>Conclusion</p> <p>Interferon-α is critical in antiviral immunity against hepatitis C but also acts as a pathogenic mediator for systemic lupus erythematosus, a condition associated with activation of plasmacytoid dendritic cells that are depleted in human immunodeficiency virus infection. The occurrence of auto-antibodies and lupus-like features in the coinfections with hepatitis C require careful assessment. Immunosuppressant therapy for lupus risks exacerbating underlying infections in patients with concurrent human immunodeficiency virus, hepatitis B and C.</p