Proteomic signature of periodontal disease in pregnancy: Predictive validity for adverse outcomes

Permafrost viremia and immune tweening

The immune system, an exquisitely regulated physiological system, utilizes a wide spectrum of soluble factors and multiple cell populations and subpopulations at diverse states of maturation to monitor and protect the organism against foreign organisms. Immune surveillance is ensured by distinguishing self-antigens from self-associated with non-self (e.g., viral) peptides presented by major histocompatibility complexes (MHC). Pathology is often identified as unregulated inflammatory responses (e.g., cytokine storm), or recognizing self as a non-self entity (i.e., auto-immunity). Artificial intelligence (AI), and in particular specific machine learning (ML) paradigms (e.g., Deep Learning [DL]) proffer powerful algorithms to better understand and more accurately predict immune responses, immune regulation and homeostasis, and immune reactivity to challenges (i.e., immune allostasis) by their intrinsic ability to interpret immune parameters, pathways and events by analyzing large amounts of complex data and drawing predictive inferences (i.e., immune tweening). We propose here that DL models play an increasingly significant role in better defining and characterizing immunological surveillance to ancient and novel virus species released by thawing permafrost.

Methodological quality of meta-analyses of single-case experimental studies

BACKGROUND

Methodological rigor is a fundamental factor in the validity and credibility of the results of a meta-analysis.

AIM

Following an increasing interest in single-case experimental design (SCED) meta-analyses, the current study investigates the methodological quality of SCED meta-analyses.

METHODS AND PROCEDURES

We assessed the methodological quality of 178 SCED meta-analyses published between 1985 and 2015 through the modified Revised-Assessment of Multiple Systematic Reviews (R-AMSTAR) checklist.

OUTCOMES AND RESULTS

The main finding of the current review is that the methodological quality of the SCED meta-analyses has increased over time, but is still low according to the R-AMSTAR checklist. A remarkable percentage of the studies (93.80% of the included SCED meta-analyses) did not even reach the midpoint score (22, on a scale of 0-44). The mean and median methodological quality scores were 15.57 and 16, respectively. Relatively high scores were observed for "providing the characteristics of the included studies" and "doing comprehensive literature search". The key areas of deficiency were "reporting an assessment of the likelihood of publication bias" and "using the methods appropriately to combine the findings of studies".

CONCLUSIONS AND IMPLICATIONS

Although the results of the current review reveal that the methodological quality of the SCED meta-analyses has increased over time, still more efforts are needed to improve their methodological quality.

Periodontal Disease and Pregnancy Outcomes: Overview of Systematic Reviews

Periodontal disease is very common during pregnancy. Although it has been linked to adverse pregnancy outcomes, systematic reviews have reached discrepant conclusions on these links. Therefore, we conducted a systematic overview of systematic reviews studying the association between periodontal disease and adverse pregnancy outcomes. We searched 6 online databases up to November 2016 and hand-searched references and citations of eligible papers. Systematic reviews of studies comparing pregnancy outcomes among women with and without periodontal disease were eligible for inclusion. Primary outcomes were maternal mortality, preterm birth, and perinatal mortality. Two reviewers extracted data and assessed risk of bias of individual systematic reviews. Findings are described in tabular and narrative form. Twenty-three systematic reviews (including between 3 and 45 studies) were included. None reported the association between periodontal disease and maternal or perinatal mortality. Systematic reviews with the lowest risk of bias consistently demonstrated positive associations between periodontal disease and preterm birth (relative risk, 1.6; 95% confidence interval, 1.3 to 2.0; 17 studies, 6,741 participants), low birth weight (LBW; relative risk, 1.7; 95% CI, 1.3 to 2.1; 10 studies, 5,693 participants), preeclampsia (odds ratio, 2.2; 95% CI, 1.4 to 3.4; 15 studies, 5,111 participants), and preterm LBW (relative risk 3.4; 95% CI, 1.3 to 8.8; 4 studies, 2,263 participants). Based on these figures, estimated population-attributable fractions for periodontal disease were 5% to 38% for preterm birth, 6% to 41% for LBW, and 10% to 55% for preeclampsia. In terms of limitations, as several primary studies did not adjust for confounding, meta-analyses may have overestimated the strength of the associations under study. Due to substantial overlap in included primary studies, we could not aggregate results across reviews. Consistent evidence from systematic reviews with low risk of bias indicates that pregnant women with periodontal disease are at increased risk of developing preeclampsia and delivering a preterm and/or LBW baby (PROSPERO: CRD42015030132).

Knowledge Transfer Statement: This study highlights that periodontal disease is an important risk factor for several common adverse pregnancy outcomes. Clinicians should be aware of this link to guide risk selection. Research is needed to develop novel preventive and treatment strategies.

Limitations of A Measurement Tool to Assess Systematic Reviews (AMSTAR) and suggestions for improvement

A Measurement Tool to Assess Systematic Reviews (AMSTAR) is a commonly used tool to assess the quality of systematic reviews; however, modifications are needed to improve its usability, reliability, and validity. In this commentary, we summarize our experience and the experiences of others who have used AMSTAR and provide suggestions for its improvement. We propose that AMSTAR should modify a number of individual items and their instructions and responses to make them more congruent with an assessment of the methodologic quality of systematic reviews. We recommend adding new items and modifying existing items to assess the quality of the body of evidence and to address subgroup and sensitivity analyses. More detailed instructions are needed for scoring individual items across multiple reviewers, and we recommend that a total score should not be calculated. These suggestions need to be empirically tested prior to implementation.

Influenza 2009 pandemic: Cellular immunemediated surveillance modulated by TH17 & Tregs

Influenza A virus is a serious public health threat. Most recently the 2009/H1N1 pandemic virus had an inherent ability to evade the host's immune surveillance through genetic drift, shift, and genomic reassortment. Immune characterization of 2009/H1N1 utilized monoclonal antibodies, neutralizing sera, and proteomics. Increased age may have provided some degree of immunity, but vaccines against seasonal influenza viruses seldom yield cross-reactive immunity, exemplified by 2009/H1N1. Nonetheless, about 33% of individuals, over the age of 60, had cross-reactive neutralizing antibodies against 2009/H1N1, whereas only 6-9% young adults had these antibodies. Children characteristically had no detectable immunity against 2009/H1N1. Taken together, these observations suggest some degree of immune transference with at least certain strains of virus that have afflicted the human population in past decades. Because internal influenza proteins may exhibit less antigenic variation, it is possible that prior exposure to diverse strains of influenza virus provide some immunity to novel strains, including the recent pandemic strain (swine-avian A/H1N1). Current trends in immunological studies - specifically the modulation of cellular immune surveillance provided by TH17 and Tregs - also support the need for additional proteomic research for characterizing novel translational evidence-based treatment interventions based on cytokine function to help defeat the virus. Timely and critical research must characterize the impact of genetics and epigenetics of oral and systemic host immune surveillance responses to influenza A virus. The continued development and application of proteomics and gene expression across viral strains and human tissues increases our ability to combat the spread of influenza epidemics and pandemics.