Quantification of periodontal attachment at single-rooted teeth

. The measurement process of attachment Joss has been criticized in recent years. Problems with clinical interpretation, precision of the measurement, and statistical manipulation of the obtained data, are some of the problems associated with the present methodology. The purpose of the present study was to propose an alternative measurement process which addresses some of the existing problems by estimating the lost attachment surface area (LAS) and the remaining attachment surface area (RAS) from a combination of clinical measurements. The results show that a linear combination of several sources of clinical information can be used to predict RAS and LAS. A diagnostic model for LAS (R 2 =81.5%) predicts the square root of LAS with information obtained from bucco-lingual attachment level measurements, the radiographic lost attachment area, the gingivitis index and the radiographic tooth length. This model increases the precision of the estimate of LAS by a factor of 1.86 when compared to the estimate of LAS using only attachment level measurements, A diagnostic model for RAS (R 2 =75.5%) predicts the square root of RAS with the information obtained from the remaining radiographic attachment area, the gingivitis index and the mobility index. Both linear inference models are constructed with measurements of anatomical landmarks to avoid the discrepancy between anatomical and clinical measurements in the produced estimates. It is concluded that modeling of periodontal data provides a simple, inexpensive, and precise diagnostic tool for predicting the lost and the remaining periodontal attachment of single-rooted teeth. Measurement processes of this type could provide a convincing, basis for the evaluation of clinical decisions and research questions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72962/1/j.1600-051X.1989.tb01645.x.pd

Comparison of Randomly Cloned and Whole Genomic DNA Probes for the Detection of Porphyromonas Gingivalis and Bacteroides Forsythus

Whole genomic and randomly-cloned DNA probes for two fastidious periodontal pathogens, Porphyromonas gingivalis and Bacteroides forsythus were labeled with digoxigenin and detected by a colorimetric method. The specificity and sensitivity of the whole genomic and cloned probes were compared. The cloned probes were highly specific compared to the whole genomic probes. A significant degree of cross-reactivity with Bacteroides species. Capnocytophaga sp. and Prevotella sp. was observed with the whole genomic probes. The cloned probes were less sensitive than the whole genomic probes and required at least 106 target cells or a minimum of 10 ng of target DNA to be detected during hybridization. Although a ten-fold increase in sensitivity was obtained with the whole genomic probes, cross-hybridization to closely related species limits their reliability in identifying target bacteria in subgingival plaque samples

Greater power and computational efficiency for kernel-based association testing of sets of genetic variants

Motivation: Set-based variance component tests have been identified as a way to increase power in association studies by aggregating weak individual effects. However, the choice of test statistic has been largely ignored even though it may play an important role in obtaining optimal power. We compared a standard statistical test-a score test-with a recently developed likelihood ratio (LR) test. Further, when correction for hidden structure is needed, or gene-gene interactions are sought, state-of-the art algorithms for both the score and LR tests can be computationally impractical. Thus we develop new computationally efficient methods. Results: After reviewing theoretical differences in performance between the score and LR tests, we find empirically on real data that the LR test generally has more power. In particular, on 15 of 17 real datasets, the LR test yielded at least as many associations as the score test-up to 23 more associations-whereas the score test yielded at most one more association than the LR test in the two remaining datasets. On synthetic data, we find that the LR test yielded up to 12% more associations, consistent with our results on real data, but also observe a regime of extremely small signal where the score test yielded up to 25% more associations than the LR test, consistent with theory. Finally, our computational speedups now enable (i) efficient LR testing when the background kernel is full rank, and (ii) efficient score testing when the background kernel changes with each test, as for gene-gene interaction tests. The latter yielded a factor of 2000 speedup on a cohort of size 13 500. Availability: Software available at http://research.microsoft.com/en-us/um/redmond/projects/MSCompBio/Fastlmm/. Contact: [email protected] Supplementary Information: Supplementary data are available at Bioinformatics online

An exhaustive epistatic SNP association analysis on expanded Wellcome Trust data

We present an approach for genome-wide association analysis with improved power on the Wellcome Trust data consisting of seven common phenotypes and shared controls. We achieved improved power by expanding the control set to include other disease cohorts, multiple races, and closely related individuals. Within this setting, we conducted exhaustive univariate and epistatic interaction association analyses. Use of the expanded control set identified more known associations with Crohn's disease and potential new biology, including several plausible epistatic interactions in several diseases. Our work suggests that carefully combining data from large repositories could reveal many new biological insights through increased power. As a community resource, all results have been made available through an interactive web server

Further improvements to linear mixed models for genome-wide association studies

We examine improvements to the linear mixed model (LMM) that better correct for population structure and family relatedness in genome-wide association studies (GWAS). LMMs rely on the estimation of a genetic similarity matrix (GSM), which encodes the pairwise similarity between every two individuals in a cohort. These similarities are estimated from single nucleotide polymorphisms (SNPs) or other genetic variants. Traditionally, all available SNPs are used to estimate the GSM. In empirical studies across a wide range of synthetic and real data, we find that modifications to this approach improve GWAS performance as measured by type I error control and power. Specifically, when only population structure is present, a GSM constructed from SNPs that well predict the phenotype in combination with principal components as covariates controls type I error and yields more power than the traditional LMM. In any setting, with or without population structure or family relatedness, a GSM consisting of a mixture of two component GSMs, one constructed from all SNPs and another constructed from SNPs that well predict the phenotype again controls type I error and yields more power than the traditional LMM. Software implementing these improvements and the experimental comparisons are available at http://microsoft.com/science

Accurate Liability Estimation Improves Power in Ascertained Case Control Studies

Linear mixed models (LMMs) have emerged as the method of choice for confounded genome-wide association studies. However, the performance of LMMs in non-randomly ascertained case-control studies deteriorates with increasing sample size. We propose a framework called LEAP (Liability Estimator As a Phenotype, https://github.com/omerwe/LEAP) that tests for association with estimated latent values corresponding to severity of phenotype, and demonstrate that this can lead to a substantial power increase

The Role of Spirochetes in Periodontal Disease

The spirochetal accumulation in subgingival plaque appears to be a function of the clinical severity of periodontal disease. It is not known how many different spirochetal species colonize the plaque, but based upon size alone, there are small, intermediate-sized, and large spirochetes. Four species of small spirochetes are cultivable, and of these, T. denticola has been shown to possess proteolytic and keratinolytic enzymes as well as factors or mechanisms which suppress lymphocyte blastogenesis and inhibit fibroblast and polymorphonuclear leukocyte (PMNL) function. All of these attributes could contribute to periodontal tissue insult. Yet independent of these potential virulence mechanisms, the overgrowth of spirochetes can be clinically useful if simply interpreted as indicating the result of tissue damage. In this case, the spirochetes would be indicators of disease and could be easily monitored by microscopic examination of plaque, or possibly by the measurement of benzoyl-DL-arginine-2-naphthylamide (BANA) hydrolytic activity in the plaque.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68092/2/10.1177_08959374880020021201.pd

Dextran Penetration Through Nonkeratinized and Keratinized Epithelia in Monkeys

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142019/1/jper0424.pd

Rethinking drug design in the artificial intelligence era

Artificial intelligence (AI) tools are increasingly being applied in drug discovery. While some protagonists point to vast opportunities potentially offered by such tools, others remain sceptical, waiting for a clear impact to be shown in drug discovery projects. The reality is probably somewhere in-between these extremes, yet it is clear that AI is providing new challenges not only for the scientists involved but also for the biopharma industry and its established processes for discovering and developing new medicines. This article presents the views of a diverse group of international experts on the 'grand challenges' in small-molecule drug discovery with AI and the approaches to address them

Scaling and root planing with and without periodontal flap surgery

. Complete removal of calculus is a primary part of achieving a “biologically acceptable” tooth surface in the treatment of periodontitis. Rabbani et al. reported that a single episode of scaling did not completely remove subgingival calculus and that the deeper the periodontal pocket, the less complete the calculus removal. The purpose of the present study was to evaluate the effectiveness of scaling relative to calculus removal following reflection of a periodontal flap. Each of 21 patients who required multiple extractions had 2 teeth scaled, 2 teeth scaled following the reflection of a periodontal flap, and 2 teeth serve as controls. Local anesthesia was used. Following extraction, the % of subgingival tooth surfaces free of calculus was determined using the method described by Rabbani with a stereomicroscope. Results showed that while scaling only (SO) and scaling with a flap (SF) increased the % of root surface without calculus, scaling following the reflection of a flap aided calculus removal in pockets 4 mm and deeper. Comparison of SO versus SF at various pocket depths for % of tooth surfaces completely free of calculus showed 1 to 3 mm pockets to be 86% versus 86%, 4 to 6 mm pockets to be 43% versus 76% and >6 mm pockets to be 32% versus 50%. The extent of residual calculus was directly related to pocket depth, was greater following scaling only, and was greatest at the CEJ or in association with grooves, fossae or furcations. No differences were noted between anterior and posterior teeth or between different tooth surfaces.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73823/1/j.1600-051X.1986.tb01461.x.pd