Aim This study compared the subgingival microbiota of subjects with refractory periodontitis (RP) to those in subjects with treatable periodontitis (GR) or periodontal health (PH) using the Human Oral Microbe Identification Microarray (HOMIM). Methods At baseline, subgingival plaque samples were taken from 47 periodontitis and 20 PH individuals, and analyzed for the presence of 300 species by HOMIM. The periodontitis subjects were classified as RP (n=17) based on mean attachment loss (AL) and/or >3 sites with AL ≥2.5 mm after SRP, surgery and systemically administered amoxicillin and metronidazole or as GR (n=30) based on mean attachment gain and no sites with AL ≥2.5 mm after treatment. Significant differences in taxa among groups were sought using the Kruskal Wallis and Chi-square tests. Results More species were detected in diseased patients (GR or RP) than those without disease (PH). RP subjects were distinguished from GR and PH by a significantly high frequency of putative periodontal pathogens such as, Parvimonas micra, Campylobacter gracilis, Eubacterium nodatum, Selenomonas noxia, Tannerella forsythia, Porphyromonas gingivalis, Prevotella spp., Treponema spp., Eikenella corrodens, as well as “unusual” species (Pseudoramibacter alactolyticus, TM7 spp. oral taxon (OT) 346/356, Bacteroidetes spp. OT 272/274, Solobacterium moorei, Desulfobulbus sp. OT 041, Brevundimonas diminuta, Sphaerocytophaga sp. OT 337, Shuttleworthia satelles, Filifactor alocis, Dialister invisus/pneumosintes, Granulicatella adiacens, Mogibacterium tidmidum, Veillonella atypica, Mycoplasma salivarium, Synergistes sp. cluster II, Acidaminococcaceae [G-1] sp. OT 132/150/155/148/135) [p<0.05]. Species that were more prevalent in PH than in periodontitis patients included Actinomyces sp. OT 170, Actinomyces spp. cluster I, Capnocytophaga sputigena, Cardiobacterium hominis, Haemophilus parainfluenzae, Lautropia mirabilis, Propionibacterium propionicum, Rothia dentocariosa/mucilagenosa, Streptococcus sanguinis (p<0.05). Conclusion RP patients present a distinct microbial profile compared to patients in the GR and PH groups as determined by HOMIM.

It has been difficult to conduct large scale studies of microbiologically complex ecosystems using conventional microbiological techniques. Molecular identification techniques in new probe-target formats, such as checkerboard DNA-DNA hybridization, permit enumeration of large numbers of species in very large numbers of samples. Digoxigenin-labeled whole genomic probes to 40 common subgingival species were tested in a checkerboard hydridization format. Chemifluorescent signals resulting from the hybridization reactions were quantified using a Fluorimager and used to evaluate sensitivity and specificity of the probes. Sensitivity of the DNA probes was adjusted to detect 10(4) cells. In all, 93.5% of potential cross-reactions to 80 cultivable species exhibited signals <5% of that detected for the homologous probe signal. Competitive hybridization and probes prepared by subtraction hybridization and polymerase chain reaction were effective in minimizing cross-reactions for closely related taxa. To demonstrate utility, the technique was used to evaluate 8887 subgingival plaque samples from 79 periodontally healthy and 272 chronic periodontitis subjects and 8126 samples from 166 subjects taken prior to and after periodontal therapy. Significant differences were detected for many taxa for mean counts, proportion of total sample, and percentage of sites colonized between samples from periodontally healthy and periodontitis subjects. Further, significant reductions were observed post therapy for many subgingival species including periodontal pathogens. DNA probes used in the checkerboard DNA-DNA format provide a useful tool for the enumeration of bacterial species in microbiologically complex systems.

The most common forms of destructive periodontal disease have been thought to slowly and continuously progress until treatment or tooth loss. Recently, data have become available which are inconsistent with this "continuous disease" hypothesis. Data from longitudinal monitoring of periodontal attachment levels and alveolar bone in humans and in animals suggest that periodontal disease progresses by recurrent acute episodes. In addition, rates of attachment loss have been measured in individual sites which are faster than those consistent with the continuous disease hypothesis or slower than those expected from estimates of prior loss rates. To account for these observations, a model of destructive periodontal disease is described in which bursts of activity occur for short periods of time in individual sites. These bursts appear to occur randomly at periodontal sites throughout the mouth. Some sites demonstrate a brief active burst of destructive periodontal disease (which could take a few days to a few months) before going into a period of remission. Other sites appear to be free of destructive periodontal disease throughout the individual's life. The sites which demonstrate destructive periodontal activity may show no further activity or could be subject to one or more bursts of activity at later time periods. Comparison of monitored loss rates for a year with mean loss rates prior to monitoring suggested that there may be relatively short periods in an individual's life in which many sites undergo periodontal destruction followed by periods of extended remission. An extension of the random disease model is also suggested in which bursts of destructive periodontal disease activity occur with higher frequency during certain periods of an individual's life.

Attachment level at two sites on each tooth in 22 untreated subjects with existing periodontal pockets was measured every month for 1 year. Regression analysis was then applied to the data from each periodontal site to determine if statistically significant trends in attachment level change could be detected. 82.8% of the sites monitored did not significantly change during the year. 5.7% of the sites became significantly deeper and 11.5% of the sites became significantly shallower (P less than 0.01) during the period. Among those sites in which pocket depth increased, approximately half exhibited a cyclic deepening followed by spontaneous recovery to their original depth. In 15 of the subjects, sites were found which became significantly deeper while other sites within the same subject became significantly shallower. In six subjects, who might be considered to have an arrested form of periodontal disease, virtually no sites became deeper during the monitoring period whereas 11-36% of their sites became significantly shallower. The results of this investigation suggest that a dynamic condition of disease exacerbation and remission as well as periods of inactivity may be characteristic of periodontal disease.

The purpose of the present investigation was to evaluate methods to detect periods of destructive periodontal disease activity in individual sites using pairs of repeated attachment level measurements. Attachment level measurements were made at 6 sites on every tooth in 22 individuals with radiographic evidence of periodontal destruction, and were repeated within 7 days. A total of 3414 sites were monitored at 2-month intervals for approximately 1 year. 3 analytical procedures were used to test for significant changes in attachment level. For regression analysis, a linear least squares fit function of time in days vs attachment level was computed for each site and the slope tested for difference from 0. Running medians of 3 were used to smooth attachment level measurements and changes greater than 2 mm in the smoothed curves were considered significant. By the tolerance method, differences between pairs of attachment level measurements were used to compare the mean change and the site specific variability of that change. The proportion of specific agreement (Ps) for breaking down sites was highest between the tolerance and running median methods (Ps = 0.63). Overall agreement (kappa), which included sites which showed "loss", "gain", and no change was 0.56. By regression analysis (P less than 0.01), 175 sites were identified as having significant attachment loss and 79 sites were identified as improving. By running medians these figures were 90 and 50, and by tolerance 94 and 40, respectively. Each of the 3 methods had certain advantages. Regression analysis was particularly sensitive to gradual changes in slope whereas the running median method detected abrupt changes in attachment level. The tolerance method was well suited to detecting changes over a short period of time. The tolerance and running median methods detected more breaking down sites on the molars and lower incisors and on interproximal surfaces; whereas regression analysis did not show these differences.

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The world-wide explosion of overweight people has been called an epidemic. The inflammatory nature of obesity is widely recognized. Could it really be an epidemic involving an infectious agent? In this climate of concern over the increasing prevalence of overweight conditions in our society, we focus on the possible role of oral bacteria as a potential direct contributor to obesity. In order to investigate this possibility we measured salivary bacterial populations of overweight women. Saliva was collected from 313 women with a body mass index between 27 and 32 and bacterial populations measured by DNA probe analysis (Socransky and Haffajee, 2005). Levels in this group were compared with data from a population of 232 subjects that served as healthy normal subjects in periodontal disease studies. The median percentage difference of 7 of the 40 bacterial species measured was greater than 2% in the saliva of overweight women. Classification tree analysis of salivary microbiological composition revealed that 98.4% of the overweight women could be identified by the presence of a single bacterial species (Selenomonas noxia) at levels greater than 1.05% of the total salivary bacteria. These data suggest the composition of salivary bacteria change in overweight women. It seems likely that these bacterial species could serve as biological indicators of a developing overweight condition. Of even greater interest and the subject of future research is the possibility that oral bacteria, such as S. noxia, may participate in the pathology that leads to obesity.

The purpose of the present investigation was to evaluate the usefulness of clinical measurements of periodontal disease in predicting destructive periodontal disease activity. Periodontal status was monitored at 3414 sites in a total of 22 subjects. Repeat attachment level measurements recorded at 2‐month intervals were analyzed by the tolerance method to detect destructive periodontal disease activity. The number of sites that showed or did not show activity and the absence or presence of a clinical parameter before and after the monitoring period were computed. The diagnostic sensitivity of a clinical parameter in predicting disease was expressed as the proportion of sites showing attachment loss which exhibited that parameter. Diagnostic specificity was expressed as the proportion of sites not exhibiting the clinical parameter and not showing attachment loss. In addition, the probability of false positive and false negative diagnoses were computed, using the assumption that the destructive periodontal disease activity rate of sites at risk was 3%. The sensitivity of clinical measurements of gingival redness, plaque, suppuration and bleeding on probing ranged from 0.03 (suppuration) to 0.42 (plaque). Specificity of these measurements was better, ranging from 0.71 for plaque to 0,97 for‐suppuration. Disease activity was most often. associated with shallow pockets, but shallow pockets by far dominated she‐sites at risk‐. Thus; pocket‐depth: of <4mm was a sensitive diagnostic test for disease activity (0.69), but the measured specificity of 0.25 indicated that it would be a poor predictor of disease activity. Molar teeth and interproximal surfaces were more likely sites of disease activity than other teeth or surfaces with sensitivity values of 0.52 and 0.83, and specificity values of 0.2S and 0.34, respectively. The probability of detecting false positives was high using any of the clinical parameters ranging from 0.95–0.97. Because no clinical parameter demonstrated high sensitivity and high specificity values, none of the clinical parameters used individually or in combination were found useful in predicting disease activity at individual sites.