The results suggest that dysregulation of miR-146 expression in PBMC may be associated with the ongoing autoimmune imbalance in T1D patients.

BackgroundPostnatal development of early life microbiota influences immunity, metabolism, neurodevelopment, and infant health. Microbiome development occurs at multiple body sites, with distinct community compositions and functions. Associations between microbiota at multiple sites represent an unexplored influence on the infant microbiome. Here, we examined co-occurrence patterns of gut and respiratory microbiota in pre- and full-term infants over the first year of life, a period critical to neonatal development.ResultsGut and respiratory microbiota collected as longitudinal rectal, throat, and nasal samples from 38 pre-term and 44 full-term infants were first clustered into community state types (CSTs) on the basis of their compositional profiles. Multiple methods were used to relate the occurrence of CSTs to temporal microbiota development and measures of infant maturity, including gestational age (GA) at birth, week of life (WOL), and post-menstrual age (PMA). Manifestation of CSTs followed one of three patterns with respect to infant maturity: (1) chronological, with CST occurrence frequency solely a function of post-natal age (WOL), (2) idiosyncratic to maturity at birth, with the interval of CST occurrence dependent on infant post-natal age but the frequency of occurrence dependent on GA at birth, and (3) convergent, in which CSTs appear first in infants of greater maturity at birth, with occurrence frequency in pre-terms converging after a post-natal interval proportional to pre-maturity. The composition of CSTs was highly dissimilar between different body sites, but the CST of any one body site was highly predictive of the CSTs at other body sites. There were significant associations between the abundance of individual taxa at each body site and the CSTs of the other body sites, which persisted after stringent control for the non-linear effects of infant maturity. Canonical correlations exist between the microbiota composition at each pair of body sites, with the strongest correlations between proximal locations.ConclusionThese findings suggest that early microbiota is shaped by neonatal innate and adaptive developmental responses. Temporal progression of CST occurrence is influenced by infant maturity at birth and post-natal age. Significant associations of microbiota across body sites reveal distal connections and coordinated development of the infant microbial ecosystem.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0566-5) contains supplementary material, which is available to authorized users.

False-positive mpMRI examinations may occur in up to 46.3% of patients with a prior negative biopsy. Thus, a multi-institutional nomogram has been developed and validated for predicting benign pathology after FB in patients with a prior negative biopsy, and this may help to reduce the number of unnecessary biopsies in the setting of abnormal mpMRI findings. Cancer 2018;124:278-85. © 2017 American Cancer Society.

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Aims/IntroductionTo investigate the typing for human leukocyte antigen (HLA) class I in Chinese patients with type 1 diabetes as a complement screening for HLA class II.Materials and MethodsA total of 212 type 1 diabetic patients and 200 healthy controls were enrolled. The genetic polymorphisms of HLA class I and II were examined with a high‐resolution polymerase chain reaction sequence‐based typing method.ResultsThe haplotype, A*33:03‐B*58:01‐C*03:02(A33), was associated with type 1 diabetes (P = 1.0 × 10−4, odds ratio 3.2 [1.738–5.843]). The A33‐DR3 and A33‐DR9 haplotypes significantly enhanced the risk of type 1 diabetes (A33‐DR3, odds ratio 5.1 [2.40–10.78], P = 4.0 × 10−6; A33‐DR9, odds ratio 13.0 [1.69–100.32], P = 0.004). In type 1 diabetic patients, compared with A33‐DR3‐negative carriers, A33‐DR3‐positive carriers had significantly lower percentages of CD3+ CD4+ T cells (42.5 ± 7.72 vs 37.0 ± 8.35%, P = 0.023), higher percentages of CD3+ CD8+ T cells (27.4 ± 7.09 vs 32.8 ± 5.98%, P = 0.005) and T‐cell receptor α/β T cells (70.0 ± 7.00 vs 73.6 ± 6.25%, P = 0.031), and lower CD4/CD8 ratios (1.71 ± 0.75 vs 1.16 ± 0.35, P = 0.003).ConclusionsIt is the first time that the haplotypes A33‐DR3 and A33‐DR9 were found with an enhanced predisposition to type 1 diabetes in Han Chinese. A33‐DR3 was associated with a reduction in the helper‐to‐cytotoxic cell ratio and preferential increase of T‐cell receptor α/β T cell. The typing for HLA class I and its immunogenetic effects are important for more accurate HLA class II haplotype risk prediction and etiology research in type 1 diabetic patients.

Background: Gingival recession and a thin or absent buccal plate occur frequently at maxillary anterior teeth and necessitate careful treatment planning to prevent future complications. However, the association between these two conditions is unclear and the ability of gingival recession to predict underlying buccal bone deficiencies is unknown. Therefore, the aim of this study is to use clinical and radiographic data to test this association and determine the influence of demographic and clinical parameters on both conditions. Methods: This investigation comprised a single-center, retrospective study. Data were derived from periodontal examinations performed on 66 adult subjects. Corresponding cone-beam computed tomography images were used to measure the width of buccal bone at two points along the root surface and the distance between the bone crest and cemento-enamel junction (CEJ). Results were then analyzed to determine the association between the presence of gingival recession and the condition of radiographic buccal bone, as well as the relative contribution of demographic parameters and other clinical findings to gingival recession and buccal bone conditions. Results: Gingival recession was present at 32.9% of maxillary anterior teeth and was most common at canines, followed by lateral incisors and central incisors. Mean buccal bone widths were significantly less, and the distance between the CEJ and bone crest was significantly greater for teeth with recession. Accordingly, gingival recession was a significant predictor for buccal bone thickness <1 mm at the level of 4 mm apical to the CEJ (odds ratio 2.733, 95% confidence interval 1.644 to 4.543, P < 0.0001). Probing depths were related to the presence or absence of gingival recession, while patient sex, age, and the apico-coronal height of the gingiva were related to buccal bone thickness. Conclusion:Within the limitations of this study, maxillary anterior teeth with preexisting gingival recession were more likely to have thin (<1 mm) buccal bone. K E Y W O R D Salveolar process, cone-beam computed tomography, gingiva, gingival recession, periodontium 484 How to cite this article: D'Silva E, Fraser D, Wang B, Barmak AB, Caton J, Tsigarida A. The association between gingival recession and buccal bone at maxillary anterior teeth. J Periodontol. 2020;91:484-492.

The p value has been widely used as a way to summarise the significance in data analysis. However, misuse and misinterpretation of the p value is common in practice. Our result shows that if the model specification is wrong, the distribution of the p value may be inappropriate, which makes the decision based on the p value invalid.

For moderate to large sample sizes, all tests yielded pvalues close to the nominal, except when models were misspecified. The signed-rank test generally had the lowest power. Within the current context of count outcomes, the signed-rank test shows subpar power when compared with tests that are contrasted based on full data, such as the GEE. Parametric models for count outcomes such as the GLMM with a Poisson for marginal count outcomes are quite sensitive to departures from assumed parametric models. There is some small bias for all the asymptotic tests, that is,the signed-ranktest, GLMM and GEE, especially for small sample sizes. Resampling methods such as permutation can help alleviate this.