Probable autoimmune causal relationship between periodontitis and Hashimotos thyroidits: A systemic review

Periodontitis is a multifactorial disease with microbial dental plaque as the initiator of periodontal disease. However, the manifestation and progression of the disease is influenced by a wide variety of determinants and factors. The strongest type of causal relationship is the association of systemic and periodontal disease. Hashimotos thyroiditis has also been considered as one of the causes of periodontal disease. As a matter of fact, on an autoimmune basis, in Hashimotos disease and periodontal disease, we have made an attempt to derive the common mechanisms, with an evidence base. The need for this kind of review was due to the fact that the outcome of periodontal therapy did not give the expected results in patients with Hashimoto’s thyroiditis. Hence, a possible link between Hashimotos thyroiditis and periodontitis was considered

User relationship classification of facebook messenger mobile data using WEKA

© Springer Nature Switzerland AG 2018. Mobile devices are a wealth of information about its user and their digital and physical activities (e.g. online browsing and physical location). Therefore, in any crime investigation artifacts obtained from a mobile device can be extremely crucial. However, the variety of mobile platforms, applications (apps) and the significant size of data compound existing challenges in forensic investigations. In this paper, we explore the potential of machine learning in mobile forensics, and specifically in the context of Facebook messenger artifact acquisition and analysis. Using Quick and Choo (2017)’s Digital Forensic Intelligence Analysis Cycle (DFIAC) as the guiding framework, we demonstrate how one can acquire Facebook messenger app artifacts from an Android device and an iOS device (the latter is, using existing forensic tools. Based on the acquired evidence, we create 199 data-instances to train WEKA classifiers (i.e. ZeroR, J48 and Random tree) with the aim of classifying the device owner’s contacts and determine their mutual relationship strength

Identification of Methanoculleus spp. as active methanogens during anoxic incubations of swine manure storage tank samples

Methane emissions represent a major environmental concern associated with manure management in the livestock industry. A more thorough understanding of how microbial communities function in manure storage tanks is a prerequisite for mitigating methane emissions. Identifying the microorganisms that are metabolically active is an important first step. Methanogenic archaea are major contributors to methanogenesis in stored swine manure, and we investigated active methanogenic populations by DNA stable isotope probing (DNA-SIP). Following a preincubation of manure samples under anoxic conditions to induce substrate starvation, [U-¹³C] acetate was added as a labeled substrate. Fingerprint analysis of density-fractionated DNA, using length-heterogeneity analysis of PCR-amplified mcrA genes (encoding the alpha subunit of methyl coenzyme M reductase), showed that the incorporation of ¹³C into DNA was detectable at in situ acetate concentrations (~7g/liter). Fingerprints of DNA retrieved from heavy fractions of the ¹³C treatment were primarily enriched in a 483-bp amplicon and, to a lesser extent, in a 481-bp amplicon. Analyses based on clone libraries of the mcrA and 16S rRNA genes revealed that both of these heavy DNA amplicons corresponded to Methanoculleus spp. Our results demonstrate that uncultivated methanogenic archaea related to Methanoculleus spp. were major contributors to acetate-C assimilation during the anoxic incubation of swine manure storage tank samples. Carbon assimilation and dissimilation rate estimations suggested that Methanoculleus spp. were also major contributors to methane emissions and that the hydrogenotrophic pathway predominated during methanogenesis

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Overstimulation of NMDA Receptors Impairs Early Brain Development in vivo

BACKGROUND: Brains of patients with schizophrenia show both neurodevelopmental and functional deficits that suggest aberrant glutamate neurotransmission. Evidence from both genetic and pharmacological studies suggests that glutamatergic dysfunction, particularly with involvement of NMDARs, plays a critical role in the pathophysiology of schizophrenia. However, how prenatal disturbance of NMDARs leads to schizophrenia-associated developmental defects is largely unknown. METHODOLOGY/PRINCIPAL FINDINGS: Glutamate transporter GLAST/GLT1 double-knockout (DKO) mice carrying the NMDA receptor 1 subunit (NR1)-null mutation were generated. Bouin-fixed and paraffin-embedded embryonic day 16.5 coronal brain sections were stained with hematoxylin, anti-microtubule-associated protein 2 (MAP2), and anti-L1 antibodies to visualize cortical, hippocampal, and olfactory bulb laminar structure, subplate neurons, and axonal projections. NR1 deletion in DKO mice almost completely rescued multiple brain defects including cortical, hippocampal, and olfactory bulb disorganization and defective corticothalamic and thalamocortical axonal projections. CONCLUSIONS/SIGNIFICANCE: Excess glutamatergic signaling in the prenatal stage compromises early brain development via overstimulation of NMDARs

Part 1: CT characterisation of pancreatic neoplasms: a pictorial essay

The pancreas is a site of origin of a diverse range of benign and malignant tumours, and these are frequently detected, diagnosed and staged with computed tomography (CT). Knowledge of the typical appearance of these neoplasms as well as the features of locoregional invasion is fundamental for all general and abdominal radiologists. This pictorial essay aims to outline the characteristic CT appearances of the spectrum of pancreatic neoplasms, as well as important demographic and clinical information that aids diagnosis. The second article in this series addresses common mimics of pancreatic neoplasia

The Intrinsic Resolution Limit in the Atomic Force Microscope: Implications for Heights of Nano-Scale Features

Background; Accurate mechanical characterization by the atomic force microscope at the highest spatial resolution requires that topography is deconvoluted from indentation. The measured height of nanoscale features in the atomic force microscope (AFM) is almost always smaller than the true value, which is often explained away as sample deformation, the formation of salt deposits and/or dehydration. We show that the real height of nano-objects cannot be obtained directly: a result arising as a consequence of the local probe-sample geometry. Methods and Findings; We have modeled the tip-surface-sample interaction as the sum of the interaction between the tip and the surface and the tip and the sample. We find that the dynamics of the AFM cannot differentiate between differences in force resulting from 1) the chemical and/or mechanical characteristics of the surface or 2) a step in topography due to the size of the sample; once the size of a feature becomes smaller than the effective area of interaction between the AFM tip and sample, the measured height is compromised. This general result is a major contributor to loss of height and can amount to up to ∼90% for nanoscale features. In particular, these very large values in height loss may occur even when there is no sample deformation, and, more generally, height loss does not correlate with sample deformation. DNA and IgG antibodies have been used as model samples where experimental height measurements are shown to closely match the predicted phenomena. Conclusions; Being able to measure the true height of single nanoscale features is paramount in many nanotechnology applications since phenomena and properties in the nanoscale critically depend on dimensions. Our approach allows accurate predictions for the true height of nanoscale objects and will lead to reliable mechanical characterization at the highest spatial resolution

Metabolic Network Topology Reveals Transcriptional Regulatory Signatures of Type 2 Diabetes

Type 2 diabetes mellitus (T2DM) is a disorder characterized by both insulin resistance and impaired insulin secretion. Recent transcriptomics studies related to T2DM have revealed changes in expression of a large number of metabolic genes in a variety of tissues. Identification of the molecular mechanisms underlying these transcriptional changes and their impact on the cellular metabolic phenotype is a challenging task due to the complexity of transcriptional regulation and the highly interconnected nature of the metabolic network. In this study we integrate skeletal muscle gene expression datasets with human metabolic network reconstructions to identify key metabolic regulatory features of T2DM. These features include reporter metabolites—metabolites with significant collective transcriptional response in the associated enzyme-coding genes, and transcription factors with significant enrichment of binding sites in the promoter regions of these genes. In addition to metabolites from TCA cycle, oxidative phosphorylation, and lipid metabolism (known to be associated with T2DM), we identified several reporter metabolites representing novel biomarker candidates. For example, the highly connected metabolites NAD+/NADH and ATP/ADP were also identified as reporter metabolites that are potentially contributing to the widespread gene expression changes observed in T2DM. An algorithm based on the analysis of the promoter regions of the genes associated with reporter metabolites revealed a transcription factor regulatory network connecting several parts of metabolism. The identified transcription factors include members of the CREB, NRF1 and PPAR family, among others, and represent regulatory targets for further experimental analysis. Overall, our results provide a holistic picture of key metabolic and regulatory nodes potentially involved in the pathogenesis of T2DM