Care homes education: what can we learn?

Medical care received by care home residents can be variable. Initiatives, such as matron-led community teams, ensure a timely response to alerts about unwell residents. But early recognition of deterioration is vital in accessing this help. The aim of this project was to design and deliver an education programme for carers. It was hypothesised that the implementation of a teaching programme may result in improved medical care for residents. By understanding the enablers and barriers to implementing teaching, we hoped to identify the components of a successful teaching programme. Four care homes in Enfield received training on topics such as deterioration recognition over a 1-year period. The project was evaluated at 3, 6 and 9 months. Each evaluation comprised: pre-and-post-teaching questionnaires, focus groups, analysis of percentages of staff trained, review of overall and potentially avoidable, hospital admission rates. A Plan-Do-Study-Act cycle structure was used. The programme was well-received by carers, who gave examples of application of learning. Modules about conditions frequently resulting in hospital admission, or concerning real cases, demonstrated the best pre-and-post lesson change scores. However, the reach of the programme was low, with attendance rates between 5% and 28%. Overall, the percentage of staff trained in deterioration recognition ranged from 35% (care home one) to 12% (care home three). Hospital admissions reduced from 37 hospital admissions to 20 over the duration of the project. Potentially avoidable admissions reduced from 16 to 5. Proving causality to the intervention was difficult. Factors facilitating delivery of training included a flexible approach, an activity-based curriculum, alignment of topics with real cases and embedding key messages in every tutorial. Barriers included: time pressures, shift work, low attendance rates, inequitable perception of the value of teaching and IT issues. Care home factors impacting on delivery included: stability of management and internal communication systems.please ensure space here

Duration of hospital participation in a nationwide stroke registry is associated with improved quality of care

BACKGROUND: There are several proven therapies for patients with ischemic stroke or transient ischemic attack (TIA), including prophylaxis of deep venous thrombosis (DVT) and initiation of antithrombotic medications within 48 h and at discharge. Stroke registries have been promoted as a means of increasing use of such interventions, which are currently underutilized. METHODS: From 1999 through 2003, 86 U.S. hospitals participated in Ethos, a voluntary web-based acute stroke treatment registry. Detailed data were collected on all patients admitted with a diagnosis of TIA or ischemic stroke. Rates of optimal treatment (defined as either receipt or a valid contraindication) were examined within each hospital as a function of its length of time in registry. Generalized estimating equations were used to adjust for patient and hospital characteristics. RESULTS: A total of 16,301 patients were discharged with a diagnosis of stroke or TIA from 50 hospitals that participated for more than 1 year. Rates of optimal treatment during the first 3 months of participation were as follows: 92.5% for antithrombotic medication within 48 h, 84.6% for antithrombotic medications at discharge, and 77.1% for DVT prophylaxis. Rates for all treatments improved with duration of participation in the registry (p < 0.05), with the most dramatic improvements in the first year. CONCLUSION: In a large cohort of patients with stroke or TIA, three targeted quality-improvement measures improved among hospitals participating in a disease-specific registry. Although the changes could be attributed to interventions other than the registry, these findings demonstrate the potential for hospital-level interventions to improve care for patients with stroke and TIA

Effect of oral fluconazole 1200 mg/day on QT interval in African adults with HIV-associated cryptococcal meningitis.

We assessed the effect of fluconazole 1200 mg/day on the QT interval in cryptococcal meningitis patients. Mean corrected QT (QTc) change from baseline to day 7 was 10.1 ms (IQR: -28 to 46 ms) in the fluconazole treatment group and -12.6 ms (IQR: -39 to 13.5 ms) in those not taking fluconazole (P = 0.04). No significant increase in QTc measurements over 500 ms was observed with fluconazole. Nevertheless, it remains important to correct any electrolyte imbalance and avoid concomitant drugs that may increase QTc

Monitoring Cognitive and Emotional Processes Through Pupil and Cardiac Response During Dynamic Versus Logical Task

The paper deals with the links between physiological measurements and cognitive and emotional functioning. As long as the operator is a key agent in charge of complex systems, the definition of metrics able to predict his performance is a great challenge. The measurement of the physiological state is a very promising way but a very acute comprehension is required; in particular few studies compare autonomous nervous system reactivity according to specific cognitive processes during task performance and task related psychological stress is often ignored. We compared physiological parameters recorded on 24 healthy subjects facing two neuropsychological tasks: a dynamic task that require problem solving in a world that continually evolves over time and a logical task representative of cognitive processes performed by operators facing everyday problem solving. Results showed that the mean pupil diameter change was higher during the dynamic task; conversely, the heart rate was more elevated during the logical task. Finally, the systolic blood pressure seemed to be strongly sensitive to psychological stress. A better taking into account of the precise influence of a given cognitive activity and both workload and related task-induced psychological stress during task performance is a promising way to better monitor operators in complex working situations to detect mental overload or pejorative stress factor of error

Combined In Silico, In Vivo, and In Vitro Studies Shed Insights into the Acute Inflammatory Response in Middle-Aged Mice

We combined in silico, in vivo, and in vitro studies to gain insights into age-dependent changes in acute inflammation in response to bacterial endotoxin (LPS). Time-course cytokine, chemokine, and NO2-/NO3- data from "middle-aged" (6-8 months old) C57BL/6 mice were used to re-parameterize a mechanistic mathematical model of acute inflammation originally calibrated for "young" (2-3 months old) mice. These studies suggested that macrophages from middle-aged mice are more susceptible to cell death, as well as producing higher levels of pro-inflammatory cytokines, vs. macrophages from young mice. In support of the in silico-derived hypotheses, resident peritoneal cells from endotoxemic middle-aged mice exhibited reduced viability and produced elevated levels of TNF-α, IL-6, IL-10, and KC/CXCL1 as compared to cells from young mice. Our studies demonstrate the utility of a combined in silico, in vivo, and in vitro approach to the study of acute inflammation in shock states, and suggest hypotheses with regard to the changes in the cytokine milieu that accompany aging. © 2013 Namas et al

BindN+ for accurate prediction of DNA and RNA-binding residues from protein sequence features

Abstract Background Understanding how biomolecules interact is a major task of systems biology. To model protein-nucleic acid interactions, it is important to identify the DNA or RNA-binding residues in proteins. Protein sequence features, including the biochemical property of amino acids and evolutionary information in terms of position-specific scoring matrix (PSSM), have been used for DNA or RNA-binding site prediction. However, PSSM is rather designed for PSI-BLAST searches, and it may not contain all the evolutionary information for modelling DNA or RNA-binding sites in protein sequences. Results In the present study, several new descriptors of evolutionary information have been developed and evaluated for sequence-based prediction of DNA and RNA-binding residues using support vector machines (SVMs). The new descriptors were shown to improve classifier performance. Interestingly, the best classifiers were obtained by combining the new descriptors and PSSM, suggesting that they captured different aspects of evolutionary information for DNA and RNA-binding site prediction. The SVM classifiers achieved 77.3% sensitivity and 79.3% specificity for prediction of DNA-binding residues, and 71.6% sensitivity and 78.7% specificity for RNA-binding site prediction. Conclusions Predictions at this level of accuracy may provide useful information for modelling protein-nucleic acid interactions in systems biology studies. We have thus developed a web-based tool called BindN+ (http://bioinfo.ggc.org/bindn+/) to make the SVM classifiers accessible to the research community

VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines

BACKGROUND: Vaccine development in the post-genomic era often begins with the in silico screening of genome information, with the most probable protective antigens being predicted rather than requiring causative microorganisms to be grown. Despite the obvious advantages of this approach – such as speed and cost efficiency – its success remains dependent on the accuracy of antigen prediction. Most approaches use sequence alignment to identify antigens. This is problematic for several reasons. Some proteins lack obvious sequence similarity, although they may share similar structures and biological properties. The antigenicity of a sequence may be encoded in a subtle and recondite manner not amendable to direct identification by sequence alignment. The discovery of truly novel antigens will be frustrated by their lack of similarity to antigens of known provenance. To overcome the limitations of alignment-dependent methods, we propose a new alignment-free approach for antigen prediction, which is based on auto cross covariance (ACC) transformation of protein sequences into uniform vectors of principal amino acid properties. RESULTS: Bacterial, viral and tumour protein datasets were used to derive models for prediction of whole protein antigenicity. Every set consisted of 100 known antigens and 100 non-antigens. The derived models were tested by internal leave-one-out cross-validation and external validation using test sets. An additional five training sets for each class of antigens were used to test the stability of the discrimination between antigens and non-antigens. The models performed well in both validations showing prediction accuracy of 70% to 89%. The models were implemented in a server, which we call VaxiJen. CONCLUSION: VaxiJen is the first server for alignment-independent prediction of protective antigens. It was developed to allow antigen classification solely based on the physicochemical properties of proteins without recourse to sequence alignment. The server can be used on its own or in combination with alignment-based prediction methods. It is freely-available online at the URL:

An exploration of ambigrammatic sequences in narnaviruses

Narnaviruses have been described as positive-sense RNA viruses with a remarkably simple genome of ~3 kb, encoding only a highly conserved RNA-dependent RNA polymerase (RdRp). Many narnaviruses, however, are 'ambigrammatic' and harbour an additional uninterrupted open reading frame (ORF) covering almost the entire length of the reverse complement strand. No function has been described for this ORF, yet the absence of stops is conserved across diverse narnaviruses, and in every case the codons in the reverse ORF and the RdRp are aligned. The >3 kb ORF overlap on opposite strands, unprecedented among RNA viruses, motivates an exploration of the constraints imposed or alleviated by the codon alignment. Here, we show that only when the codon frames are aligned can all stop codons be eliminated from the reverse strand by synonymous single-nucleotide substitutions in the RdRp gene, suggesting a mechanism for de novo gene creation within a strongly conserved amino-acid sequence. It will be fascinating to explore what implications this coding strategy has for other aspects of narnavirus biology. Beyond narnaviruses, our rapidly expanding catalogue of viral diversity may yet reveal additional examples of this broadly-extensible principle for ambigrammatic-sequence development

TGF-β Inducible Early Gene 1 Regulates Osteoclast Differentiation and Survival by Mediating the NFATc1, AKT, and MEK/ERK Signaling Pathways

TGF-β Inducible Early Gene-1 (TIEG1) is a Krüppel-like transcription factor (KLF10) that was originally cloned from human osteoblasts as an early response gene to TGF-β treatment. As reported previously, TIEG1−/− mice have decreased cortical bone thickness and vertebral bone volume and have increased spacing between the trabeculae in the femoral head relative to wildtype controls. Here, we have investigated the role of TIEG1 in osteoclasts to further determine their potential role in mediating this phenotype. We have found that TIEG1−/− osteoclast precursors differentiated more slowly compared to wildtype precursors in vitro and high RANKL doses are able to overcome this defect. We also discovered that TIEG1−/− precursors exhibit defective RANKL-induced phosphorylation and accumulation of NFATc1 and the NFATc1 target gene DC-STAMP. Higher RANKL concentrations reversed defective NFATc1 signaling and restored differentiation. After differentiation, wildtype osteoclasts underwent apoptosis more quickly than TIEG1−/− osteoclasts. We observed increased AKT and MEK/ERK signaling pathway activation in TIEG1−/− osteoclasts, consistent with the roles of these kinases in promoting osteoclast survival. Adenoviral delivery of TIEG1 (AdTIEG1) to TIEG1−/− cells reversed the RANKL-induced NFATc1 signaling defect in TIEG1−/− precursors and eliminated the differentiation and apoptosis defects. Suppression of TIEG1 with siRNA in wildtype cells reduced differentiation and NFATc1 activation. Together, these data provide evidence that TIEG1 controls osteoclast differentiation by reducing NFATc1 pathway activation and reduces osteoclast survival by suppressing AKT and MEK/ERK signaling

Comparison study on k-word statistical measures for protein: From sequence to 'sequence space'

<p>Abstract</p> <p>Background</p> <p>Many proposed statistical measures can efficiently compare protein sequence to further infer protein structure, function and evolutionary information. They share the same idea of using <it>k</it>-word frequencies of protein sequences. Given a protein sequence, the information on its related protein sequences hasn't been used for protein sequence comparison until now. This paper proposed a scheme to construct protein 'sequence space' which was associated with protein sequences related to the given protein, and the performances of statistical measures were compared when they explored the information on protein 'sequence space' or not. This paper also presented two statistical measures for protein: <it>gre.k </it>(generalized relative entropy) and <it>gsm.k </it>(gapped similarity measure).</p> <p>Results</p> <p>We tested statistical measures based on protein 'sequence space' or not with three data sets. This not only offers the systematic and quantitative experimental assessment of these statistical measures, but also naturally complements the available comparison of statistical measures based on protein sequence. Moreover, we compared our statistical measures with alignment-based measures and the existing statistical measures. The experiments were grouped into two sets. The first one, performed via ROC (Receiver Operating Curve) analysis, aims at assessing the intrinsic ability of the statistical measures to discriminate and classify protein sequences. The second set of the experiments aims at assessing how well our measure does in phylogenetic analysis. Based on the experiments, several conclusions can be drawn and, from them, novel valuable guidelines for the use of protein 'sequence space' and statistical measures were obtained.</p> <p>Conclusion</p> <p>Alignment-based measures have a clear advantage when the data is high redundant. The more efficient statistical measure is the novel <it>gsm.k </it>introduced by this article, the <it>cos.k </it>followed. When the data becomes less redundant, <it>gre.k </it>proposed by us achieves a better performance, but all the other measures perform poorly on classification tasks. Almost all the statistical measures achieve improvement by exploring the information on 'sequence space' as word's length increases, especially for less redundant data. The reasonable results of phylogenetic analysis confirm that <it>Gdis.k </it>based on 'sequence space' is a reliable measure for phylogenetic analysis. In summary, our quantitative analysis verifies that exploring the information on 'sequence space' is a promising way to improve the abilities of statistical measures for protein comparison.</p