Teaching periodontal pocket charting to dental students: a comparison of computer assisted learning and traditional tutorials

AIM: The aim of this study was to compare the effectiveness of a computer assisted learning (CAL) programme with that of traditional small group tutorials in teaching theoretical and practical aspects of periodontal pocket charting. METHOD: Sixty-one third year undergraduate dental students were randomized to either receive a tutorial or to work through the CAL programme. Students using the CAL programme completed questionnaires relating to previous computer experience and the ease of use of the programme. All students were assessed immediately after the intervention by means of a confidence log, a practical exercise and a further confidence log. They were assessed again three weeks later by means of a confidence log and a multiple-choice written test. RESULTS: There were very few significant differences between groups for any of the assessments used. However, subjective comments indicated that students occasionally felt disadvantaged if they had not received a tutorial. CONCLUSION: CAL and traditional teaching methods are equally effective in teaching periodontal pocket charting to undergraduate dental students

SNPLims: a data management system for genome wide association studies

<p>Abstract</p> <p>Background</p> <p>Recent progresses in genotyping technologies allow the generation high-density genetic maps using hundreds of thousands of genetic markers for each DNA sample. The availability of this large amount of genotypic data facilitates the whole genome search for genetic basis of diseases.</p> <p>We need a suitable information management system to efficiently manage the data flow produced by whole genome genotyping and to make it available for further analyses.</p> <p>Results</p> <p>We have developed an information system mainly devoted to the storage and management of SNP genotype data produced by the Illumina platform from the raw outputs of genotyping into a relational database.</p> <p>The relational database can be accessed in order to import any existing data and export user-defined formats compatible with many different genetic analysis programs.</p> <p>After calculating family-based or case-control association study data, the results can be imported in SNPLims. One of the main features is to allow the user to rapidly identify and annotate statistically relevant polymorphisms from the large volume of data analyzed. Results can be easily visualized either graphically or creating ASCII comma separated format output files, which can be used as input to further analyses.</p> <p>Conclusions</p> <p>The proposed infrastructure allows to manage a relatively large amount of genotypes for each sample and an arbitrary number of samples and phenotypes. Moreover, it enables the users to control the quality of the data and to perform the most common screening analyses and identify genes that become “candidate” for the disease under consideration.</p

The Set of Measures on the Reduction of Agrarian Risks in the Conditions of Interstate Integration

Выполнен сравнительный анализ уровня самообеспеченности основными продуктами питания государств-участников ЕАЭС. Выявлены рискообразующие факторы в аграрной сфере и потенциальные угрозы продовольственной безопасности. Обоснована значимость производственных и финансовых аграрных рисков для целей производства необходимого количества сельскохозяйственного сырья и продовольствия в Республике Беларусь. Предложен комплекс мероприятий по снижению уровня аграрных рисков, реализация которых будет способствовать обеспечению необходимых параметров продовольственной безопасности.A comparative analysis of the level of self-provision with essential foods of the countries of Eurasian Economic Union is carried. Risk factors in the agrarian sphere and potential threats for the food security are revealed. The significance of production and financial agrarian risks for the purposes of producing necessary quantity of agricultural raw materials and food in the Republic of Belarus is justified. The set of measures for reducing the level of agrarian risks is proposed, the implementation of which will facilitate providing necessary parameters of food security

Dual-gated bilayer graphene hot electron bolometer

Detection of infrared light is central to diverse applications in security, medicine, astronomy, materials science, and biology. Often different materials and detection mechanisms are employed to optimize performance in different spectral ranges. Graphene is a unique material with strong, nearly frequency-independent light-matter interaction from far infrared to ultraviolet, with potential for broadband photonics applications. Moreover, graphene's small electron-phonon coupling suggests that hot-electron effects may be exploited at relatively high temperatures for fast and highly sensitive detectors in which light energy heats only the small-specific-heat electronic system. Here we demonstrate such a hot-electron bolometer using bilayer graphene that is dual-gated to create a tunable bandgap and electron-temperature-dependent conductivity. The measured large electron-phonon heat resistance is in good agreement with theoretical estimates in magnitude and temperature dependence, and enables our graphene bolometer operating at a temperature of 5 K to have a low noise equivalent power (33 fW/Hz1/2). We employ a pump-probe technique to directly measure the intrinsic speed of our device, >1 GHz at 10 K.Comment: 5 figure

Single Gene Deletions of Orexin, Leptin, Neuropeptide Y, and Ghrelin Do Not Appreciably Alter Food Anticipatory Activity in Mice

Timing activity to match resource availability is a widely conserved ability in nature. Scheduled feeding of a limited amount of food induces increased activity prior to feeding time in animals as diverse as fish and rodents. Typically, food anticipatory activity (FAA) involves temporally restricting unlimited food access (RF) to several hours in the middle of the light cycle, which is a time of day when rodents are not normally active. We compared this model to calorie restriction (CR), giving the mice 60% of their normal daily calorie intake at the same time each day. Measurement of body temperature and home cage behaviors suggests that the RF and CR models are very similar but CR has the advantage of a clearly defined food intake and more stable mean body temperature. Using the CR model, we then attempted to verify the published result that orexin deletion diminishes food anticipatory activity (FAA) but observed little to no diminution in the response to CR and, surprisingly, that orexin KO mice are refractory to body weight loss on a CR diet. Next we tested the orexigenic neuropeptide Y (NPY) and ghrelin and the anorexigenic hormone, leptin, using mouse mutants. NPY deletion did not alter the behavior or physiological response to CR. Leptin deletion impaired FAA in terms of some activity measures, such as walking and rearing, but did not substantially diminish hanging behavior preceding feeding time, suggesting that leptin knockout mice do anticipate daily meal time but do not manifest the full spectrum of activities that typify FAA. Ghrelin knockout mice do not have impaired FAA on a CR diet. Collectively, these results suggest that the individual hormones and neuropepetides tested do not regulate FAA by acting individually but this does not rule out the possibility of their concerted action in mediating FAA

Biomass and Burning Characteristics of Sugar Pine Cones

We investigated the physical and burning characteristics of sugar pine (Pinus lambertiana Douglas) cones and their contribution to woody surface fuel loadings. Field sampling was conducted at the Yosemite Forest Dynamics Plot (YFDP), a 25.6 ha mapped study plot in Yosemite National Park, California, USA. We developed a classification system to describe sugar pine cones of different sizes and decay conditions, and examined differences among cone classes in biomass, bulk density, flame length, burning time, consumption, and relative contribution to surface fuel loads. Sugar pine cones comprised 601 kg ha-1 of surface fuels. Mature cones comprised 54% of cone biomass, and aborted juvenile cones accounted for 44%. Cone biomass, diameter, and bulk density differed among cone condition classes, as did burning characteristics (one-way ANOVA, P \u3c 0.001 in all cases). Flame lengths ranged from 5 cm to 94 cm for juvenile cones, and 71 cm to 150 cm for mature cones. Our results showed that the developmental stage at which sugar pine cones become surface fuels determines their potential contribution to surface fire behavior in Sierra Nevada mixed-conifer forests. Sugar pine cones burn with greater flame lengths and flame times than the cones of other North American fire-tolerant pine species studied to date, indicating that cones augment the surface fire regime of sugar pine forests, and likely do so to a greater degree than do cones of other pine species

Lineage Divergence and Historical Gene Flow in the Chinese Horseshoe Bat (Rhinolophus sinicus)

PMCID: PMC3581519This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Allelic spectrum of the natural variation in CRP

With the recent completion of the International HapMap Project, many tools are in hand for genetic association studies seeking to test the common variant/common disease hypothesis. In contrast, very few tools and resources are in place for genotype–phenotype studies hypothesizing that rare variation has a large impact on the phenotype of interest. To create these tools for rare variant/common disease studies, much interest is being generated towards investing in re-sequencing either large sample sizes of random chromosomes or smaller sample sizes of patients with extreme phenotypes. As a case study for rare variant discovery in random chromosomes, we have re-sequenced ~1,000 chromosomes representing diverse populations for the gene C-reactive protein (CRP). CRP is an important gene in the fields of cardiovascular and inflammation genetics, and its size (~2 kb) makes it particularly amenable medical or deep re-sequencing. With these data, we explore several issues related to the present-day candidate gene association study including the benefits of complete SNP discovery, the effects of tagSNP selection across diverse populations, and completeness of dbSNP for CRP. Also, we show that while deep re-sequencing uncovers potentially medically relevant coding SNPs, these SNPs are fleetingly rare when genotyped in a population-based survey of 7,000 Americans (NHANES III). Collectively, these data suggest that several different types re-sequencing and genotyping approaches may be required to fully understand the complete spectrum of alleles that impact human phenotypes. ELECTRONIC SUPPLEMENTARY MATERIAL: Supplementary material is available for this article at http://dx.doi.org/10.1007/s00439-006-0160-y and is accessible for authorized users

FastTagger: an efficient algorithm for genome-wide tag SNP selection using multi-marker linkage disequilibrium

<p>Abstract</p> <p>Background</p> <p>Human genome contains millions of common single nucleotide polymorphisms (SNPs) and these SNPs play an important role in understanding the association between genetic variations and human diseases. Many SNPs show correlated genotypes, or linkage disequilibrium (LD), thus it is not necessary to genotype all SNPs for association study. Many algorithms have been developed to find a small subset of SNPs called tag SNPs that are sufficient to infer all the other SNPs. Algorithms based on the <it>r</it>²LD statistic have gained popularity because <it>r</it>²is directly related to statistical power to detect disease associations. Most of existing <it>r</it>²based algorithms use pairwise LD. Recent studies show that multi-marker LD can help further reduce the number of tag SNPs. However, existing tag SNP selection algorithms based on multi-marker LD are both time-consuming and memory-consuming. They cannot work on chromosomes containing more than 100 k SNPs using length-3 tagging rules.</p> <p>Results</p> <p>We propose an efficient algorithm called FastTagger to calculate multi-marker tagging rules and select tag SNPs based on multi-marker LD. FastTagger uses several techniques to reduce running time and memory consumption. Our experiment results show that FastTagger is several times faster than existing multi-marker based tag SNP selection algorithms, and it consumes much less memory at the same time. As a result, FastTagger can work on chromosomes containing more than 100 k SNPs using length-3 tagging rules.</p> <p>FastTagger also produces smaller sets of tag SNPs than existing multi-marker based algorithms, and the reduction ratio ranges from 3%-9% when length-3 tagging rules are used. The generated tagging rules can also be used for genotype imputation. We studied the prediction accuracy of individual rules, and the average accuracy is above 96% when <it>r</it>²≥ 0.9.</p> <p>Conclusions</p> <p>Generating multi-marker tagging rules is a computation intensive task, and it is the bottleneck of existing multi-marker based tag SNP selection methods. FastTagger is a practical and scalable algorithm to solve this problem.</p