A Meta-Analysis of Procedures to Change Implicit Measures

Using a novel technique known as network meta-analysis, we synthesized evidence from 492 studies (87,418 participants) to investigate the effectiveness of procedures in changing implicit measures, which we define as response biases on implicit tasks. We also evaluated these procedures’ effects on explicit and behavioral measures. We found that implicit measures can be changed, but effects are often relatively weak (|ds| \u3c .30). Most studies focused on producing short-term changes with brief, single-session manipulations. Procedures that associate sets of concepts, invoke goals or motivations, or tax mental resources changed implicit measures the most, whereas procedures that induced threat, affirmation, or specific moods/emotions changed implicit measures the least. Bias tests suggested that implicit effects could be inflated relative to their true population values. Procedures changed explicit measures less consistently and to a smaller degree than implicit measures and generally produced trivial changes in behavior. Finally, changes in implicit measures did not mediate changes in explicit measures or behavior. Our findings suggest that changes in implicit measures are possible, but those changes do not necessarily translate into changes in explicit measures or behavior

Microbial differences between dental plaque and historic dental calculus are related to oral biofilm maturation stage

Dental calculus, calcified oral plaque biofilm, contains microbial and host biomolecules that can be used to study historic microbiome communities and host responses. Dental calculus does not typically accumulate as much today as historically, and clinical oral microbiome research studies focus primarily on living dental plaque biofilm. However, plaque and calculus reflect different conditions of the oral biofilm, and the differences in microbial characteristics between the sample types have not yet been systematically explored. Here, we compare the microbial profiles of modern dental plaque, modern dental calculus, and historic dental calculus to establish expected differences between these substrates.- Background - Results -- Authentication of a preserved oral biofilm in calculus samples -- Dental calculus and plaque biofilm communities are distinct -- Health-associated communities of dental plaque and calculus are distinct -- Signatures of health and of disease are shared in modern and historic calculus samples -- Microbial community differences between health and disease in calculus are poorly resolved -- Absence of caries-specific microbial profiles in dental calculus -- Microbial co-exclusion patterns in plaque and calculus reflect biofilm maturity -- Microbial complexes in plaque and calculus -- Functional prediction in calculus is poorly predictive of health status -- Proteomic profiles of historic healthy site calculus -- Correlations between taxonomic, proteomic, and metabolomic profiles - Discussion - Conclusions - Materials and methods --Historic and modern calculus sample collection DNA extraction -- DNA library construction and high-throughput sequencing -- DNA sequence processing -- Genetic assessment of historic calculus sample preservation -- Genetic microbial taxonomic profiling -- Principal component analysis -- Assessment of differentially abundant taxa -- Sparse partial least squares-discriminant analysis -- Assessment of microbial co-exclusion patterns -- Gene functional categorization with SEED -- Proteomics -- Metabolomics -- Regularized canonical correlation analysi

The Alaska Arctic Vegetation Archive (AVA-AK)

The Alaska Arctic Vegetation Archive (AVA-AK, GIVD-ID: NA-US-014) is a free, publically available database archive of vegetation-plot data from the Arctic tundra region of northern Alaska. The archive currently contains 24 datasets with 3,026 non-overlapping plots. Of these, 74% have geolocation data with 25-m or better precision. Species cover data and header data are stored in a Turboveg database. A standardized Pan Arctic Species List provides a consistent nomenclature for vascular plants, bryophytes, and lichens in the archive. A web-based online Alaska Arctic Geoecological Atlas (AGA-AK) allows viewing and downloading the species data in a variety of formats, and provides access to a wide variety of ancillary data. We conducted a preliminary cluster analysis of the first 16 datasets (1,613 plots) to examine how the spectrum of derived clusters is related to the suite of datasets, habitat types, and environmental gradients. We present the contents of the archive, assess its strengths and weaknesses, and provide three supplementary files that include the data dictionary, a list of habitat types, an overview of the datasets, and details of the cluster analysis

Oral Microbiome and Gingival Gene Expression of Inflammatory Biomolecules with Aging and Periodontitis

Although data describe the presence and increase of inflammatory mediators in the local environment in periodontitis vs. health in humans, details regarding how these responses evolve in the transition from health to disease, changes during disease progression, and features of a resolved lesion remain unknown. This study used a nonhuman primate model of ligature-induced periodontitis in young, adolescent, adult, and aged animals to document features of inflammatory response affected by age. Rhesus monkeys had ligatures tied and provided gingival tissue biopsy specimens at baseline, 0.5, 1, and 3 months of disease and at 5 months of the study, which was 2 months post-ligature removal for clinically resolved tissues. The transcriptome was assessed using microarrays for chemokine (n = 41), cytokine (n = 45), chemokine receptor (n = 21), cytokine receptor (n = 37), and lipid mediator (n = 31) genes. Limited differences were noted in healthy tissues for chemokine expression with age; however, chemokine receptor genes were decreased in young but elevated in aged samples. IL1A, IL36A, and IL36G cytokines were decreased in the younger groups, with IL36A elevated in aged animals. IL10RA/IL10RB cytokine receptors were altered with age. Striking variation in the lipid mediator genes in health was observed with nearly 60% of these genes altered with age. A specific repertoire of chemokine and chemokine receptor genes was affected by the disease process, predominated by changes during disease initiation. Cytokine/cytokine receptor genes were also elevated with disease initiation, albeit IL36B, IL36G, and IL36RN were all significantly decreased throughout disease and resolution. Significant changes were observed in similar lipid mediator genes with disease and resolution across the age groups. Examination of the microbiome links to the inflammatory genes demonstrated that specific microbes, including Fusobacterium, P. gingivalis, F. alocis, Pasteurellaceae, and Prevotella are most frequently significantly correlated. These correlations were generally positive in older animals and negative in younger specimens. Gene expression and microbiome patterns from baseline were distinctly different from disease and resolution. These results demonstrate patterns of inflammatory gene expression throughout the phases of the induction of a periodontal disease lesion. The patterns show a very different relationship to specific members of the oral microbiome in younger compared with older animals

Gingival Transcriptome of Innate Antimicrobial Factors and the Oral Microbiome with Aging and Periodontitis

The epithelial barrier at mucosal sites comprises an important mechanical protective feature of innate immunity, and is intimately involved in communicating signals of infection/tissue damage to inflammatory and immune cells in these local environments. A wide array of antimicrobial factors (AMF) exist at mucosal sites and in secretions that contribute to this innate immunity. A non-human primate model of ligature-induced periodontitis was used to explore characteristics of the antimicrobial factor transcriptome (n = 114 genes) of gingival biopsies in health, initiation and progression of periodontal lesions, and in samples with clinical resolution. Age effects and relationship of AMF to the dominant members of the oral microbiome were also evaluated. AMF could be stratified into 4 groups with high (n = 22), intermediate (n = 29), low (n = 18) and very low (n = 45) expression in healthy adult tissues. A subset of AMF were altered in healthy young, adolescent and aged samples compared with adults (e.g., APP, CCL28, DEFB113, DEFB126, FLG2, PRH1) and were affected across multiple age groups. With disease, a greater number of the AMF genes were affected in the adult and aged samples with skewing toward decreased expression, for example WDC12, PGLYRP3, FLG2, DEFB128, and DEF4A/B, with multiple age groups. Few of the AMF genes showed a \u3e2-fold increase with disease in any age group. Selected AMF exhibited significant positive correlations across the array of AMF that varied in health and disease. In contrast, a rather limited number of the AMF significantly correlated with members of the microbiome; most prominent in healthy samples. These correlated microbes were different in younger and older samples and differed in health, disease and resolution samples. The findings supported effects of age on the expression of AMF genes in healthy gingival tissues showing a relationship to members of the oral microbiome. Furthermore, a dynamic expression of AMF genes was related to the disease process and showed similarities across the age groups, except for low/very low expressed genes that were unaffected in young samples. Targeted assessment of AMF members from this large array may provide insight into differences in disease risk and biomolecules that provide some discernment of early transition to disease

Oral Microbial Biofilm Stimulation of Epithelial Cell Responses

Oral bacterial biofilms trigger chronic inflammatory responses in the host that can result in the tissue destructive events of periodontitis. However, the characteristics of the capacity of specific host cell types to respond to these biofilms remain ill-defined. This report describes the use of a novel model of bacterial biofilms to stimulate oral epithelial cells and profile select cytokines and chemokines that contribute to the local inflammatory environment in the periodontium. Monoinfection biofilms were developed with Streptococcus sanguinis, Streptococcus oralis, Streptococcus gordonii, Actinomyces naeslundii, Fusobacterium nucleatum, and Porphyromonas gingivalis on rigid gas-permeable contact lenses. Biofilms, as well as planktonic cultures of these same bacterial species, were incubated under anaerobic conditions with a human oral epithelial cell line, OKF4, for up to 24 h. Gro-1α, IL1α, IL-6, IL-8, TGFα, Fractalkine, MIP-1α, and IP-10 were shown to be produced in response to a range of the planktonic or biofilm forms of these species. P. gingivalis biofilms significantly inhibited the production of all of these cytokines and chemokines, except MIP-1α. Generally, the biofilms of all species inhibited Gro-1α, TGFα, and Fractalkine production, while F. nucleatum biofilms stimulated significant increases in IL-1α, IL-6, IL-8, and IP-10. A. naeslundii biofilms induced elevated levels of IL-6, IL-8 and IP-10. The oral streptococcal species in biofilms or planktonic forms were poor stimulants for any of these mediators from the epithelial cells. The results of these studies demonstrate that oral bacteria in biofilms elicit a substantially different profile of responses compared to planktonic bacteria of the same species. Moreover, certain oral species are highly stimulatory when in biofilms and interact with host cell receptors to trigger pathways of responses that appear quite divergent from individual bacteria

Gingival transcriptomic patterns of macrophage polarization during initiation, progression, and resolution of periodontitis.

Phenotypic and functional heterogeneity of macrophages is clearly a critical component of their effective functions in innate and adaptive immunity. This investigation hypothesized that altered profiles of gene expression in gingival tissues in health, disease, and resolution would reflect changes in macrophage phenotypes occurring in these tissues. The study used a nonhuman primate model to evaluate gene expression profiles as footprints of macrophage variation using a longitudinal experimental model of ligature-induced periodontitis in animals from 3 to 23 years of age to identify aging effects on the gingival environment. Significant differences were observed in distribution of expressed gene levels for M0, M1, and M2 macrophages in healthy tissues with the younger animals showing the least expression. M0 gene expression increased with disease in all but the aged group, while M1 was increased in adult and young animals, and M2 in all age groups, as early as disease initiation (within 0.5 months). Numerous histocompatibility genes were increased with disease, except in the aged samples. An array of cytokines/chemokines representing both M1 and M2 cells were increased with disease showing substantial increases with disease initiation (e.g. IL1A, CXCL8, CCL19, CCL2, CCL18), although the aged tissues showed a more limited magnitude of change across these macrophage genes. The analytics of macrophage genes at sites of gingival health, disease, and resolution demonstrated distinct profiles of host response interactions that may help model the disease mechanisms occurring with the formation of a periodontal lesion