9 research outputs found

    A double-blind randomized comparison of midazolam alone and midazolam combined with ketamine for sedation of pediatric dental patients

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    Purpose: The safety and efficacy of a new sedation technique for children having dental procedures under local anesthesia were evaluated. Materials and Methods: One hundred children between the ages of 2 and 7 years who required sedation for dental procedures were administered either a combination of midazolam (0.35 mg/kg) and ketamine (5 mg/kg) or midazolam alone (1 mg/kg) rectally 30 minutes before removal to the dental chair. Pulse rate, respiratory rate, arterial pressure, oxygen saturation, adverse reactions, postoperative recovery, and behavior were recorded. Results: Satisfactory sedation and anxiolysis were achieved with both drugs used in the study. When evaluating postoperative recovery, statistically significantly more children receiving midazolam alone were fully awake on admission to the recovery room and 30 minutes later. Results of physiologic monitoring, behavioral ratings, and adverse effects are reported. Excessive salivation occurred in 26% of children receiving the combination of drugs, compared with 14% receiving midazolam alone. Seven (14%) of the children receiving the combination of drugs hallucinated, compared with 21 (42%) receiving midazolam alone. Both drug groups had reliably good anxiolysis and sedation without loss of respiratory drive or protective airway reflexes. Conclusion: The use of a combination of midazolam and ketamine or midazolam alone is a safe, effective, and practical approach to managing children for minor dental procedures under local anesthesia. With this technique, advanced airway management proficiency is recommended.Articl

    Snake Venom Disintegrins: An Overview of their Interaction with Integrins

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    Interactions of Staphylococci with Osteoblasts and Phagocytes in the Pathogenesis of Implant-Associated Osteomyelitis

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    In spite of great advancements in the field of biomaterials and in surgical techniques, the implant of medical devices is still associated with a high risk of bacterial infection. Implant-associated osteomyelitis is a deep infection of bone around the implant. The continuous inflammatory destruction of bone tissues characterizes this serious bone infectious disease. Staphylococcus aureus and Staphylococcus epidermidis are the most prevalent etiologic agents of implant-associated infections, together with the emerging pathogen Staphylococcus lugdunensis. Various interactions between staphylococci, osteoblasts, and phagocytes occurring in the pen-prosthesis environment play a crucial role in the pathogenesis of implant-associated osteomyelitis. Here we focus on two main events: internalization of staphylococci into osteoblasts, and bacterial interactions with phagocytic cells

    Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson's disease

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    We conducted a meta-analysis of Parkinson's disease genome-wide association studies using a common set of 7,893,274 variants across 13,708 cases and 95,282 controls. Twenty-six loci were identified as having genome-wide significant association; these and 6 additional previously reported loci were then tested in an independent set of 5,353 cases and 5,551 controls. Of the 32 tested SNPs, 24 replicated, including 6 newly identified loci. Conditional analyses within loci showed that four loci, including GBA, GAK-DGKQ, SNCA and the HLA region, contain a secondary independent risk variant. In total, we identified and replicated 28 independent risk variants for Parkinson's disease across 24 loci. Although the effect of each individual locus was small, risk profile analysis showed substantial cumulative risk in a comparison of the highest and lowest quintiles of genetic risk (odds ratio (OR) = 3.31, 95% confidence interval (CI) = 2.55-4.30; P = 2 × 10-16). We also show six risk loci associated with proximal gene expression or DNA methylation. © 2014 Nature America, Inc. All rights reserved

    Exchange charge model of crystal field for 3d ions

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    Phylum XIV. Bacteroidetes phyl. nov.

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    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press

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