Interaction of ARF-1.1 and neuronal calcium sensor-1 in the control of the temperature-dependency of locomotion in Caenorhabditis elegans

Neuronal calcium sensor-1 (NCS-1) mediates changes in cellular function by regulating various target proteins. Many potential targets have been identified but the physiological significance of only a few has been established. Upon temperature elevation, Caenorhabditis elegans exhibits reversible paralysis. In the absence of NCS-1, worms show delayed onset and a shorter duration of paralysis. This phenotype can be rescued by re-expression of ncs-1 in AIY neurons. Mutants with defects in four potential NCS-1 targets (arf-1.1, pifk-1, trp-1 and trp-2) showed qualitatively similar phenotypes to ncs-1 null worms, although the effect of pifk-1 mutation on time to paralysis was considerably delayed. Inhibition of pifk-1 also resulted in a locomotion phenotype. Analysis of double mutants showed no additive effects between mutations in ncs-1 and trp-1 or trp-2. In contrast, double mutants of arf-1.1 and ncs-1 had an intermediate phenotype, consistent with NCS-1 and ARF-1.1 acting in the same pathway. Over-expression of arf-1.1 in the AIY neurons was sufficient to rescue partially the phenotype of both the arf-1.1 and the ncs-1 null worms. These findings suggest that ARF-1.1 interacts with NCS-1 in AIY neurons and potentially pifk-1 in the Ca2+ signaling pathway that leads to inhibited locomotion at an elevated temperature

Sensitivity of stratospheric water vapour to variability in tropical tropopause temperatures and large-scale transport

Abstract. Concentrations of water vapour entering the tropical lower stratosphere are primarily determined by conditions that air parcels encounter as they are transported through the tropical tropopause layer (TTL). Here we quantify the relative roles of variations in TTL temperatures and transport in determining seasonal and interannual variations of stratospheric water vapour. Following previous studies, we use trajectory calculations with the water vapour concentration set by the Lagrangian dry point (LDP) along trajectories. To assess the separate roles of transport and temperatures, the LDP calculations are modified by replacing either the winds or the temperatures with those from different years to investigate the wind or temperature sensitivity of water vapour to interannual variations and, correspondingly, with those from different months to investigate the wind or temperature sensitivity to seasonal variations. Both ERA-Interim reanalysis data for the 1999–2009 period and data generated by a chemistry–climate model (UM-UKCA) are investigated. Variations in temperatures, rather than transport, dominate interannual variability, typically explaining more than 70 % of variability, including individual events such as the 2000 stratospheric water vapour drop. Similarly seasonal variation of temperatures, rather than transport, is shown to be the dominant driver of the annual cycle in lower stratospheric water vapour concentrations in both the model and reanalysis, but it is also shown that seasonal variation of transport plays an important role in reducing the seasonal cycle maximum (reducing the annual range by about 30 %). The quantitative role in dehydration of sub-seasonal and sub-monthly Eulerian temperature variability is also examined by using time-filtered temperature fields in the trajectory calculations. Sub-monthly temperature variability reduces annual mean water vapour concentrations by 40 % in the reanalysis calculation and 30 % in the model calculation. As with other aspects of dehydration, simple Eulerian measures of variability are not sufficient to quantify the implications for dehydration, and the Lagrangian sampling of the variability must be taken into account. These results indicate that, whilst capturing seasonal and interannual variation of temperature is a major factor in modelling realistic stratospheric water vapour concentrations, simulation of seasonal variation of transport and of sub-seasonal and sub-monthly temperature variability are also important and cannot be ignored. </jats:p

Optimal search strategies for identifying sound clinical prediction studies in EMBASE

BACKGROUND: Clinical prediction guides assist clinicians by pointing to specific elements of the patient's clinical presentation that should be considered when forming a diagnosis, prognosis or judgment regarding treatment outcome. The numbers of validated clinical prediction guides are growing in the medical literature, but their retrieval from large biomedical databases remains problematic and this presents a barrier to their uptake in medical practice. We undertook the systematic development of search strategies ("hedges") for retrieval of empirically tested clinical prediction guides from EMBASE. METHODS: An analytic survey was conducted, testing the retrieval performance of search strategies run in EMBASE against the gold standard of hand searching, using a sample of all 27,769 articles identified in 55 journals for the 2000 publishing year. All articles were categorized as original studies, review articles, general papers, or case reports. The original and review articles were then tagged as 'pass' or 'fail' for methodologic rigor in the areas of clinical prediction guides and other clinical topics. Search terms that depicted clinical prediction guides were selected from a pool of index terms and text words gathered in house and through request to clinicians, librarians and professional searchers. A total of 36,232 search strategies composed of single and multiple term phrases were trialed for retrieval of clinical prediction studies. The sensitivity, specificity, precision, and accuracy of search strategies were calculated to identify which were the best. RESULTS: 163 clinical prediction studies were identified, of which 69 (42.3%) passed criteria for scientific merit. A 3-term strategy optimized sensitivity at 91.3% and specificity at 90.2%. Higher sensitivity (97.1%) was reached with a different 3-term strategy, but with a 16% drop in specificity. The best measure of specificity (98.8%) was found in a 2-term strategy, but with a considerable fall in sensitivity to 60.9%. All single term strategies performed less well than 2- and 3-term strategies. CONCLUSION: The retrieval of sound clinical prediction studies from EMBASE is supported by several search strategies

Optimal search strategies for detecting cost and economic studies in EMBASE

BACKGROUND: Economic evaluations in the medical literature compare competing diagnosis or treatment methods for their use of resources and their expected outcomes. The best evidence currently available from research regarding both cost and economic comparisons will continue to expand as this type of information becomes more important in today's clinical practice. Researchers and clinicians need quick, reliable ways to access this information. A key source of this type of information is large bibliographic databases such as EMBASE. The objective of this study was to develop search strategies that optimize the retrieval of health costs and economics studies from EMBASE. METHODS: We conducted an analytic survey, comparing hand searches of journals with retrievals from EMBASE for candidate search terms and combinations. 6 research assistants read all issues of 55 journals indexed by EMBASE for the publishing year 2000. We rated all articles using purpose and quality indicators and categorized them into clinically relevant original studies, review articles, general papers, or case reports. The original and review articles were then categorized for purpose (i.e., cost and economics and other clinical topics) and depending on the purpose as 'pass' or 'fail' for methodologic rigor. Candidate search strategies were developed for economic and cost studies, then run in the 55 EMBASE journals, the retrievals being compared with the hand search data. The sensitivity, specificity, precision, and accuracy of the search strategies were calculated. RESULTS: Combinations of search terms for detecting both cost and economic studies attained levels of 100% sensitivity with specificity levels of 92.9% and 92.3% respectively. When maximizing for both sensitivity and specificity, the combination of terms for detecting cost studies (sensitivity) increased 2.2% over the single term but at a slight decrease in specificity of 0.9%. The maximized combination of terms for economic studies saw no change in sensitivity from the single term and only a 0.1% increase in specificity. CONCLUSION: Selected terms have excellent performance in the retrieval of studies of health costs and economics from EMBASE

Technology mediator: a new role for the reference librarian?

The Arizona Health Sciences Library has collaborated with clinical faculty to develop a federated search engine that is useful for meeting real-time clinical information needs. This article proposes a technology mediation role for the reference librarian that was inspired by the project, and describes the collaborative model used for developing technology-mediated services for targeted users

Teaching clinical informatics to third-year medical students: negative results from two controlled trials

BACKGROUND: Prior educational interventions to increase seeking evidence by medical students have been unsuccessful. METHODS: We report two quasirandomized controlled trials to increase seeking of medical evidence by third-year medical students. In the first trial (1997–1998), we placed computers in clinical locations and taught their use in a 6-hour course. Based on negative results, we created SUMSearch(TM), an Internet site that automates searching for medical evidence by simultaneous meta-searching of MEDLINE and other sites. In the second trial (1999–2000), we taught SUMSearch's use in a 5½-hour course. Both courses were taught during the medicine clerkship. For each trial, we surveyed the entire third-year class at 6 months, after half of the students had taken the course (intervention group). The students who had not received the intervention were the control group. We measured self-report of search frequency and satisfaction with search quality and speed. RESULTS: The proportion of all students who reported searching at least weekly for medical evidence significantly increased from 19% (1997–1998) to 42% (1999–2000). The proportion of all students who were satisfied with their search results increased significantly between study years. However, in neither study year did the interventions increase searching or satisfaction with results. Satisfaction with the speed of searching was 27% in 1999–2000. This did not increase between studies years and was not changed by the interventions. CONCLUSION: None of our interventions affected searching habits. Even with automated searching, students report low satisfaction with search speed. We are concerned that students using current strategies for seeking medical evidence will be less likely to seek and appraise original studies when they enter medical practice and have less time

Analysis of queries sent to PubMed at the point of care: Observation of search behaviour in a medical teaching hospital

Contains fulltext : 69801.pdf ( ) (Open Access)BACKGROUND: The use of PubMed to answer daily medical care questions is limited because it is challenging to retrieve a small set of relevant articles and time is restricted. Knowing what aspects of queries are likely to retrieve relevant articles can increase the effectiveness of PubMed searches. The objectives of our study were to identify queries that are likely to retrieve relevant articles by relating PubMed search techniques and tools to the number of articles retrieved and the selection of articles for further reading. METHODS: This was a prospective observational study of queries regarding patient-related problems sent to PubMed by residents and internists in internal medicine working in an Academic Medical Centre. We analyzed queries, search results, query tools (Mesh, Limits, wildcards, operators), selection of abstract and full-text for further reading, using a portal that mimics PubMed. RESULTS: PubMed was used to solve 1121 patient-related problems, resulting in 3205 distinct queries. Abstracts were viewed in 999 (31%) of these queries, and in 126 (39%) of 321 queries using query tools. The average term count per query was 2.5. Abstracts were selected in more than 40% of queries using four or five terms, increasing to 63% if the use of four or five terms yielded 2-161 articles. CONCLUSION: Queries sent to PubMed by physicians at our hospital during daily medical care contain fewer than three terms. Queries using four to five terms, retrieving less than 161 article titles, are most likely to result in abstract viewing. PubMed search tools are used infrequently by our population and are less effective than the use of four or five terms. Methods to facilitate the formulation of precise queries, using more relevant terms, should be the focus of education and research

EMBASE search strategies for identifying methodologically sound diagnostic studies for use by clinicians and researchers

BACKGROUND: Accurate diagnosis by clinicians is the cornerstone of decision making for recommending clinical interventions. The current best evidence from research concerning diagnostic tests changes unpredictably as science advances. Both clinicians and researchers need dependable access to published evidence concerning diagnostic accuracy. Bibliographic databases such as EMBASE provide the most widely available entrée to this literature. The objective of this study was to develop search strategies that optimize the retrieval of methodologically sound diagnostic studies from EMBASE for use by clinicians. METHODS: An analytic survey was conducted, comparing hand searches of 55 journals with retrievals from EMBASE for 4,843 candidate search terms and 6,574 combinations. All articles were rated using purpose and quality indicators, and clinically relevant diagnostic accuracy articles were categorized as 'pass' or 'fail' according to explicit criteria for scientific merit. Candidate search strategies were run in EMBASE, the retrievals being compared with the hand search data. The proposed search strategies were treated as "diagnostic tests" for sound studies and the manual review of the literature was treated as the "gold standard." The sensitivity, specificity, precision and accuracy of the search strategies were calculated. RESULTS: Of the 433 articles about diagnostic tests, 97 (22.4%) met basic criteria for scientific merit. Combinations of search terms reached peak sensitivities of 100% with specificity at 70.4%. Compared with best single terms, best multiple terms increased sensitivity for sound studies by 8.2% (absolute increase), but decreased specificity (absolute decrease 6%) when sensitivity was maximized. When terms were combined to maximize specificity, the single term "specificity.tw." (specificity of 98.2%) outperformed combinations of terms. CONCLUSION: Empirically derived search strategies combining indexing terms and textwords can achieve high sensitivity and specificity for retrieving sound diagnostic studies from EMBASE. These search filters will enhance the searching efforts of clinicians

Developing search strategies for clinical practice guidelines in SUMSearch and Google Scholar and assessing their retrieval performance

<p>Abstract</p> <p>Background</p> <p>Information overload, increasing time constraints, and inappropriate search strategies complicate the detection of clinical practice guidelines (CPGs). The aim of this study was to provide clinicians with recommendations for search strategies to efficiently identify relevant CPGs in SUMSearch and Google Scholar.</p> <p>Methods</p> <p>We compared the retrieval efficiency (retrieval performance) of search strategies to identify CPGs in SUMSearch and Google Scholar. For this purpose, a two-term GLAD (GuideLine And Disease) strategy was developed, combining a defined CPG term with a specific disease term (MeSH term). We used three different CPG terms and nine MeSH terms for nine selected diseases to identify the most efficient GLAD strategy for each search engine. The retrievals for the nine diseases were pooled. To compare GLAD strategies, we used a manual review of all retrievals as a reference standard. The CPGs detected had to fulfil predefined criteria, e.g., the inclusion of therapeutic recommendations. Retrieval performance was evaluated by calculating so-called diagnostic parameters (sensitivity, specificity, and "Number Needed to Read" [NNR]) for search strategies.</p> <p>Results</p> <p>The search yielded a total of 2830 retrievals; 987 (34.9%) in Google Scholar and 1843 (65.1%) in SUMSearch. Altogether, we found 119 unique and relevant guidelines for nine diseases (reference standard). Overall, the GLAD strategies showed a better retrieval performance in SUMSearch than in Google Scholar. The performance pattern between search engines was similar: search strategies including the term "guideline" yielded the highest sensitivity (SUMSearch: 81.5%; Google Scholar: 31.9%), and search strategies including the term "practice guideline" yielded the highest specificity (SUMSearch: 89.5%; Google Scholar: 95.7%), and the lowest NNR (SUMSearch: 7.0; Google Scholar: 9.3).</p> <p>Conclusion</p> <p>SUMSearch is a useful tool to swiftly gain an overview of available CPGs. Its retrieval performance is superior to that of Google Scholar, where a search is more time consuming, as substantially more retrievals have to be reviewed to detect one relevant CPG. In both search engines, the CPG term "guideline" should be used to obtain a comprehensive overview of CPGs, and the term "practice guideline" should be used if a less time consuming approach for the detection of CPGs is desired.</p

Evaluating the impact of MEDLINE filters on evidence retrieval: study protocol

<p>Abstract</p> <p>Background</p> <p>Rather than searching the entire MEDLINE database, clinicians can perform searches on a filtered set of articles where relevant information is more likely to be found. Members of our team previously developed two types of MEDLINE filters. The 'methods' filters help identify clinical research of high methodological merit. The 'content' filters help identify articles in the discipline of renal medicine. We will now test the utility of these filters for physician MEDLINE searching.</p> <p>Hypothesis</p> <p>When a physician searches MEDLINE, we hypothesize the use of filters will increase the number of relevant articles retrieved (increase 'recall,' also called sensitivity) and decrease the number of non-relevant articles retrieved (increase 'precision,' also called positive predictive value), compared to the performance of a physician's search unaided by filters.</p> <p>Methods</p> <p>We will survey a random sample of 100 nephrologists in Canada to obtain the MEDLINE search that they would first perform themselves for a focused clinical question. Each question we provide to a nephrologist will be based on the topic of a recently published, well-conducted systematic review. We will examine the performance of a physician's unaided MEDLINE search. We will then apply a total of eight filter combinations to the search (filters used in isolation or in combination). We will calculate the recall and precision of each search. The filter combinations that most improve on unaided physician searches will be identified and characterized.</p> <p>Discussion</p> <p>If these filters improve search performance, physicians will be able to search MEDLINE for renal evidence more effectively, in less time, and with less frustration. Additionally, our methodology can be used as a proof of concept for the evaluation of search filters in other disciplines.</p