Electronic adherence monitoring device performance and patient acceptability: a randomized control trial

BACKGROUND: To investigate the performance and patient acceptability of an inhaler electronic monitoring device in a real-world childhood asthma population. METHODS: Children 6 to 15 years presenting with asthma to the hospital emergency department and prescribed inhaled corticosteroids were included. Participants were randomized to receive a device with reminder features enabled or disabled for use with their preventer. Device quality control tests were conducted. Questionnaires on device acceptability, utility and ergonomics were completed at six months. RESULTS: A total of 1306 quality control tests were conducted; 84% passed pre-issue and 87% return testing. The most common failure reason was actuation under-recording. Acceptability scores were high, with higher scores in the reminder than non-reminder group (median, 5th-95th percentile: 4.1, 3.1–5.0 versus 3.7, 2.3–4.8; p 90%) rated the device easy to use. Feedback was positive across five themes: device acceptability, ringtone acceptability, suggestions for improvement, effect on medication use, and effect on asthma control. CONCLUSIONS: This study investigates electronic monitoring device performance and acceptability in children using quantitative and qualitative measures. Results indicate satisfactory reliability, although failure rates of 13–16% indicate the importance of quality control. Favorable acceptability ratings support the use of these devices in children

Multiple FadD Acyl-CoA Synthetases Contribute to Differential Fatty Acid Degradation and Virulence in Pseudomonas aeruginosa

A close interconnection between nutrient metabolism and virulence factor expression contributes to the pathophysiology of Pseudomonas aeruginosa as a successful pathogen. P. aeruginosa fatty acid (FA) degradation is complicated with multiple acyl-CoA synthetase homologs (FadDs) expressed in vivo in lung tissue during cystic fibrosis infections. The promoters of two genetically linked P. aeruginosa fadD genes (fadD1 and fadD2) were mapped and northern blot analysis indicated they could exist on two different transcripts. These FadDs contain ATP/AMP signature and FA-binding motifs highly homologous to those of the Escherichia coli FadD. Upon introduction into an E. coli fadD-/fadR- double mutant, both P. aeruginosa fadDs functionally complemented the E. coli fadD-/fadR- mutant, allowing degradation of different chain-length FAs. Chromosomal mutagenesis, growth analysis, induction studies, and determination of kinetic parameters suggested that FadD1 has a substrate preference for long-chain FAs while FadD2 prefers shorter-chain FAs. When compared to the wild type strain, the fadD2 mutant exhibited decreased production of lipase, protease, rhamnolipid and phospholipase, and retardation of both swimming and swarming motilities. Interestingly, fadD1 mutant showed only increased swarming motility. Growth analysis of the fadD mutants showed noticeable deficiencies in utilizing FAs and phosphatidylcholine (major components of lung surfactant) as the sole carbon source. This defect translated into decreased in vivo fitness of P. aeruginosa in a BALB/c mouse lung infection model, supporting the role of lipids as a significant nutrient source for this bacterium in vivo

Recognising facial expressions in video sequences

We introduce a system that processes a sequence of images of a front-facing human face and recognises a set of facial expressions. We use an efficient appearance-based face tracker to locate the face in the image sequence and estimate the deformation of its non-rigid components. The tracker works in real-time. It is robust to strong illumination changes and factors out changes in appearance caused by illumination from changes due to face deformation. We adopt a model-based approach for facial expression recognition. In our model, an image of a face is represented by a point in a deformation space. The variability of the classes of images associated to facial expressions are represented by a set of samples which model a low-dimensional manifold in the space of deformations. We introduce a probabilistic procedure based on a nearest-neighbour approach to combine the information provided by the incoming image sequence with the prior information stored in the expression manifold in order to compute a posterior probability associated to a facial expression. In the experiments conducted we show that this system is able to work in an unconstrained environment with strong changes in illumination and face location. It achieves an 89\% recognition rate in a set of 333 sequences from the Cohn-Kanade data base

Measuring Inequalities in the Distribution of Health Workers: The case of Tanzania.

The overall human resource shortages and the distributional inequalities in the health workforce in many developing countries are well acknowledged. However, little has been done to measure the degree of inequality systematically. Moreover, few attempts have been made to analyse the implications of using alternative measures of health care needs in the measurement of health workforce distributional inequalities. Most studies have implicitly relied on population levels as the only criterion for measuring health care needs. This paper attempts to achieve two objectives. First, it describes and measures health worker distributional inequalities in Tanzania on a per capita basis; second, it suggests and applies additional health care needs indicators in the measurement of distributional inequalities. We plotted Lorenz and concentration curves to illustrate graphically the distribution of the total health workforce and the cadre-specific (skill mix) distributions. Alternative indicators of health care needs were illustrated by concentration curves. Inequalities were measured by calculating Gini and concentration indices.\ud There are significant inequalities in the distribution of health workers per capita. Overall, the population quintile with the fewest health workers per capita accounts for only 8% of all health workers, while the quintile with the most health workers accounts for 46%. Inequality is perceptible across both urban and rural districts. Skill mix inequalities are also large. Districts with a small share of the health workforce (relative to their population levels have an even smaller share of highly trained medical personnel. A small share of highly trained personnel is compensated by a larger share of clinical officers (a middle-level cadre) but not by a larger share of untrained health workers. Clinical officers are relatively equally distributed. Distributional inequalities tend to be more pronounced when under-five deaths are used as an indicator of health care needs. Conversely, if health care needs are measured by HIV prevalence, the distributional inequalities appear to decline. The measure of inequality in the distribution of the health workforce may depend strongly on the underlying measure of health care needs. In cases of a non-uniform distribution of health care needs across geographical areas, other measures of health care needs than population levels may have to be developed in order to ensure a more meaningful measurement of distributional inequalities of the health workforce

The utility of clinical decision tools for diagnosing osteoporosis in postmenopausal women with rheumatoid arthritis

BACKGROUND: Patients with rheumatoid arthritis have a higher risk of low bone mineral density than normal age matched populations. There is limited evidence to support cost effectiveness of population screening in rheumatoid arthritis and case finding strategies have been proposed as a means to increase cost effectiveness of diagnostic screening for osteoporosis. This study aimed to assess the performance attributes of generic and rheumatoid arthritis specific clinical decision tools for diagnosing osteoporosis in a postmenopausal population with rheumatoid arthritis who attend ambulatory specialist rheumatology clinics. METHODS: A cross-sectional study of 127 ambulatory post-menopausal women with rheumatoid arthritis was performed. Patients currently receiving or who had previously received bone active therapy were excluded. Eligible women underwent clinical assessment and dual-energy-xray absorptiometry (DXA) bone mineral density assessment. Clinical decision tools, including those specific for rheumatoid arthritis, were compared to seven generic post-menopausal tools to predict osteoporosis (defined as T score < -2.5). Sensitivity, specificity, positive predictive and negative predictive values and area under the curve were assessed. The diagnostic attributes of the clinical decision tools were compared by examination of the area under the receiver-operator-curve. RESULTS: One hundred and twenty seven women participated. The median age was 62 (IQR 56-71) years. Median disease duration was 108 (60-168) months. Seventy two (57%) women had no record of a previous DXA examination. Eighty (63%) women had T scores at femoral neck or lumbar spine less than -1. The area under the ROC curve for clinical decision tool prediction of T score <-2.5 varied between 0.63 and 0.76. The rheumatoid arthritis specific decision tools did not perform better than generic tools, however, the National Osteoporosis Foundation score could potentially reduce the number of unnecessary DXA tests by approximately 45% in this population. CONCLUSION: There was limited utility of clinical decision tools for predicting osteoporosis in this patient population. Fracture prediction tools that include risk factors independent of BMD are needed

Multi-disciplinary team directed analysis of whole genome sequencing reveals pathogenic non-coding variants in molecularly undiagnosed inherited retinal dystrophies

PURPOSE: To identify, using genome sequencing (GS), likely pathogenic non-coding variants in inherited retinal dystrophy (IRD) genes Methods: Patients with IRD were recruited to the study and underwent comprehensive ophthalmological evaluation and GS. The results of GS were investigated through virtual gene panel analysis and plausible pathogenic variants and clinical phenotype evaluated by multi-disciplinary team (MDT) discussion. For unsolved patients in whom a specific gene was suspected to harbour a missed pathogenic variant, targeted re-analysis of non-coding regions was performed on GS data. Candidate variants were functionally tested including by mRNA analysis, minigene and luciferase reporter assays. RESULTS: Previously unreported, likely pathogenic, non-coding variants, in 7 genes (PRPF31, NDP, IFT140, CRB1, USH2A, BBS10, and GUCY2D), were identified in 11 patients. These were shown to lead to mis-splicing (PRPF31, IFT140, CRB1, USH2A) or altered transcription levels (BBS10, GUCY2D). CONCLUSION: MDT-led, phenotype driven, non-coding variant re-analysis of GS is effective in identifying missing causative alleles

Collaborative research between academia and industry using a large clinical trial database: a case study in Alzheimer's disease

<p>Abstract</p> <p>Background</p> <p>Large clinical trials databases, developed over the course of a comprehensive clinical trial programme, represent an invaluable resource for clinical researchers. Data mining projects sponsored by industry that use these databases, however, are often not viewed favourably in the academic medical community because of concerns that commercial, rather than scientific, goals are the primary purpose of such endeavours. Thus, there are few examples of sustained collaboration between leading academic clinical researchers and industry professionals in a large-scale data mining project. We present here a successful example of this type of collaboration in the field of dementia.</p> <p>Methods</p> <p>The Donepezil Data Repository comprised 18 randomised, controlled trials conducted between 1991 and 2005. The project team at Pfizer determined that the data mining process should be guided by a diverse group of leading Alzheimer's disease clinical researchers called the "Expert Working Group." After development of a list of potential faculty members, invitations were extended and a group of seven members was assembled. The Working Group met regularly with Eisai/Pfizer clinicians and statisticians to discuss the data, identify issues that were currently of interest in the academic and clinical communities that might lend themselves to investigation using these data, and note gaps in understanding or knowledge of Alzheimer's disease that these data could address. Leadership was provided by the Pfizer Clinical Development team leader; Working Group members rotated responsibility for being lead and co-lead for each investigation and resultant publication.</p> <p>Results</p> <p>Six manuscripts, each published in a leading subspecialty journal, resulted from the group's work. Another project resulted in poster presentations at international congresses and two were cancelled due to resource constraints.</p> <p>Conclusions</p> <p>The experience represents a particular approach to optimising the value of data mining of large clinical trial databases for the combined purpose of furthering clinical research and improving patient care. Fruitful collaboration between industry and academia was fostered while the donepezil data repository was used to advance clinical and scientific knowledge. The Expert Working Group approach warrants consideration as a blueprint for conducting similar research ventures in the future.</p

Plasmid pP62BP1 isolated from an Arctic Psychrobacter sp. strain carries two highly homologous type II restriction-modification systems and a putative organic sulfate metabolism operon

The complete nucleotide sequence of plasmid pP62BP1 (34,467 bp), isolated from Arctic Psychrobacter sp. DAB_AL62B, was determined and annotated. The conserved plasmid backbone is composed of several genetic modules, including a replication system (REP) with similarities to the REP region of the iteron-containing plasmid pPS10 of Pseudomonas syringae. The additional genetic load of pP62BP1 includes two highly related type II restriction-modification systems and a set of genes (slfRCHSL) encoding enzymes engaged in the metabolism of organic sulfates, plus a putative transcriptional regulator (SlfR) of the AraC family. The pP62BP1 slflocus has a compact and unique structure. It is predicted that the enzymes SlfC, SlfH, SlfS and SlfL carry out a chain of reactions leading to the transformation of alkyl sulfates into acyl-CoA, with dodecyl sulfate (SDS) as a possible starting substrate. Comparative analysis of the nucleotide sequences of pP62BP1 and other Psychrobacter spp. plasmids revealed their structural diversity. However, the presence of a few highly conserved DNA segments in pP62BP1, plasmid 1 of P. cryohalolentis K5 and pRWF-101 of Psychrobacter sp. PRwf-1 is indicative of recombinational shuffling of genetic information, and is evidence of lateral gene transfer in the Arctic environment