Background Subgingival microbiome in disease-associated subgingival sites is known to be dysbiotic and significantly altered. In patients with rheumatoid arthritis (RA), the extent of dysbiosis in disease- and health-associated subgingival sites is not clear. Methods 8 RA and 10 non-RA subjects were recruited for this pilot study. All subjects received full oral examination and underwent collection of subgingival plaque samples from both shallow (periodontal health-associated, probing depth ≤ 3mm) and deep subgingival sites (periodontal disease-associated, probing depth ≥ 4 mm). RA subjects also had rheumatological evaluation. Plaque community profiles were analyzed using 16 S rRNA sequencing. Results The phylogenetic diversity of microbial communities in both RA and non-RA controls was significantly higher in deep subgingival sites compared to shallow sites (p = 0.022), and the overall subgingival microbiome clustered primarily according to probing depth (i.e. shallow versus deep sites), and not separated by RA status. While a large number of differentially abundant taxa and gene functions was observed between deep and shallow sites as expected in non-RA controls, we found very few differentially abundant taxa and gene functions between deep and shallow sites in RA subjects. In addition, compared to non-RA controls, the UniFrac distances between deep and shallow sites in RA subjects were smaller, suggesting increased similarity between deep and shallow subgingival microbiome in RA. Streptococcus parasanguinis and Actinomyces meyeri were overabundant in RA subjects, while Gemella morbillorum, Kingella denitrificans, Prevotella melaninogenica and Leptotrichia spp. were more abundant in non-RA subjects. Conclusions The aggregate subgingival microbiome was not significantly different between individuals with and without rheumatoid arthritis. Although the differences in the overall subgingival microbiome was driven primarily by probing depth, in contrast to the substantial microbiome differences typically seen between deep and shallow sites in non-RA patients, the microbiome of deep and shallow sites in RA patients were more similar to each other. These results suggest that factors associated with RA may modulate the ecology of subgingival microbiome and its relationship to periodontal disease, the basis of which remains unknown but warrants further investigation.

Twenty-six anesthetic procedures involving 24 free-living mountain gorillas (Gorilla gorilla beringei) from Rwanda or the Democratic Republic of Congo were performed between February 1987 and October 1997. Sixteen procedures were performed to remove snares or to treat snare-related wounds, and four of the animals died without recovering consciousness because of their severe medical conditions. Ketamine was used for induction 19 times, tiletamine/zolazepam was used five times, and the agent was not recorded for two procedures. The mean (+/- SD) ketamine dosage for four animals of known weight was 7.1 +/- 0.9 mg/kg. All induction agents were delivered i.m. by remote injection, and mean induction times for ketamine and tiletamine/zolazepam were 5.5 +/- 2.6 min (n = 12) and 5.4 +/- 3.7 min (n = 5), respectively. Mean recovery times were significantly shorter with ketamine compared with tiletamine/zolazepam (42.0 +/- 24.9 min, n = 9 vs. 75.25 +/- 22.1 min, n = 4). Low hemoglobin oxygen saturation (mean = 86.7%) was recorded in three cases under ketamine anesthesia, and oxygen insufflation is therefore recommended to prevent hypoxemia. Gorillas induced with tiletamine/zolazepam had significantly higher respiratory rates compared with animals given ketamine. Successful anesthesia and recovery, in particular, depended on the assistance of local personnel.

Medical implants are being used extensively in the treatment of many types of medical ailments. Approximately 20% of adults in the U.S. have received an implant of one type or another. The U.S. Department of Commerce states that the global market for medical devices in 2016 was $339.5 billion and predicted that it would grow to $435.8 billion by 2020. As with any man-made device, some of these implants will fail. This paper provides the fundamental knowledge required by engineering and biomechanical professionals in order to analyze why an implanted orthopedic device has failed mechanically; generally by fracture. The focus will be limited to the failure of metals that are used to fabricate orthopedic implanted devices. Information regarding the biocompatibility of various engineered materials and their interaction with tissues is also presented.

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