Defined shapes of carotid artery calcifications on panoramic radiographs correlate with specific signs of cardiovascular disease on ultrasound examination.

OBJECTIVE: The aim was to optimize diagnostics for carotid artery calcifications (CACs) on panoramic radiographs (PRs) to identify cardiovascular disease (CVD) by investigating how 4 defined CAC shapes are associated with ultrasound (US) findings indicating CVD. STUDY DESIGN: The study included 414 participants (802 neck sides) from the Malmö Offspring Dental Study, examined with PRs. The PRs were assessed for CAC shapes stratified into 4 categories: single, scattered, vessel-width defining, and vessel-outlining. The carotid arteries were examined with US for signs of CVD: the presence of plaques, largest individual area of a plaque, number of plaques, and percentage reduction of the lumen. Associations between the different CAC categories and US characteristics were analyzed. RESULTS: All categories of CAC were significantly associated with a higher degree of US findings indicating CVD compared with no CAC (P < .001). The most significant differences were found for vessel-outlining CAC, with the mean of the largest individual plaque area of 17.9 vs 2.3 mm2, mean number of plaques 1.6 vs 0.2, and mean percentage reduction of the lumen 24.1% vs 3.5% (all P < .001). CONCLUSIONS: Independent of shape, CACs detected on PRs were associated with a higher degree of US findings of CVD. This was most pronounced for vessel-outlining CAC. With refined differential diagnostics of CACs in PRs, dentists may contribute to improved identification of patients in need of cardiovascular prevention.

Periodontitis is associated with airflow obstruction in the Malmö Offspring Dental Study.

AIM: To investigate the association between periodontitis and lung function in the Malmö Offspring Dental Study. MATERIALS AND METHODS: In all 1001 individuals (49.9% female, mean age: 44.6) from Malmö Offspring Dental Study were included. Periodontitis was assessed by a full-mouth examination protocol including bleeding on probing and classified according to the American Academy of Periodontology/Center for Disease Control definitions. Forced expiratory volume in 1 s (FEV1 ) and forced vital capacity (FVC) were expressed as absolute values and %predicted according to Global Lung Function Initiative reference values. FEV1 , FVC and FEV1 /FVC were analysed in relation to periodontal status using linear regression. RESULTS: Severe periodontitis was found in 7% of the population. Adjusted regression models showed significant associations between lung function and severe periodontitis with 2.1 unit lower FEV1 /FVC ratio (95% CI: -3.91, -0.23) and odds ratio (adjusted) of 2.56 (95% CI: 1.40, 4.75, p = .003) for airflow obstruction (FEV1 /FVC less than the lower limit of normal) if having severe periodontitis. Lower values of %predicted FEV1 and %predicted FVC, but not FEV1 /FVC, were found in individuals with >25% bleeding on probing. CONCLUSIONS: Severe periodontitis was associated with lower FEV1 /FVC ratio and airflow obstruction in the present cohort. More large-scale prospective studies and intervention studies are required for a comprehensive evaluation.

Streptococcus Species Abundance in the Gut Is Linked to Subclinical Coronary Atherosclerosis in 8973 Participants From the SCAPIS Cohort.

BACKGROUND: Gut microbiota have been implicated in atherosclerotic disease, but their relation with subclinical coronary atherosclerosis is unclear. This study aimed to identify associations between the gut microbiome and computed tomography-based measures of coronary atherosclerosis and to explore relevant clinical correlates. METHODS: We conducted a cross-sectional study of 8973 participants (50 to 65 years of age) without overt atherosclerotic disease from the population-based SCAPIS (Swedish Cardiopulmonary Bioimage Study). Coronary atherosclerosis was measured using coronary artery calcium score and coronary computed tomography angiography. Gut microbiota species abundance and functional potential were assessed with shotgun metagenomics sequencing of fecal samples, and associations with coronary atherosclerosis were evaluated with multivariable regression models adjusted for cardiovascular risk factors. Associated species were evaluated for association with inflammatory markers, metabolites, and corresponding species in saliva. RESULTS: The mean age of the study sample was 57.4 years, and 53.7% were female. Coronary artery calcification was detected in 40.3%, and 5.4% had at least 1 stenosis with >50% occlusion. Sixty-four species were associated with coronary artery calcium score independent of cardiovascular risk factors, with the strongest associations observed for Streptococcus anginosus and Streptococcus oralis subsp oralis (P<1×10-5). Associations were largely similar across coronary computed tomography angiography-based measurements. Out of the 64 species, 19 species, including streptococci and other species commonly found in the oral cavity, were associated with high-sensitivity C-reactive protein plasma concentrations, and 16 with neutrophil counts. Gut microbial species that are commonly found in the oral cavity were negatively associated with plasma indole propionate and positively associated with plasma secondary bile acids and imidazole propionate. Five species, including 3 streptococci, correlated with the same species in saliva and were associated with worse dental health in the Malmö Offspring Dental Study. Microbial functional potential of dissimilatory nitrate reduction, anaerobic fatty acid ß-oxidation, and amino acid degradation were associated with coronary artery calcium score. CONCLUSIONS: This study provides evidence of an association of a gut microbiota composition characterized by increased abundance of Streptococcus spp and other species commonly found in the oral cavity with coronary atherosclerosis and systemic inflammation markers. Further longitudinal and experimental studies are warranted to explore the potential implications of a bacterial component in atherogenesis.

Highly perturbed genes and hub genes associated with type 2 diabetes in different tissues of adult humans: a bioinformatics analytic workflow.

Type 2 diabetes (T2D) has a complex etiology which is not yet fully elucidated. The identification of gene perturbations and hub genes of T2D may deepen our understanding of its genetic basis. We aimed to identify highly perturbed genes and hub genes associated with T2D via an extensive bioinformatics analytic workflow consisting of five steps: systematic review of Gene Expression Omnibus and associated literature; identification and classification of differentially expressed genes (DEGs); identification of highly perturbed genes via meta-analysis; identification of hub genes via network analysis; and downstream analysis of highly perturbed genes and hub genes. Three meta-analytic strategies, random effects model, vote-counting approach, and p value combining approach, were applied. Hub genes were defined as those nodes having above-average betweenness, closeness, and degree in the network. Downstream analyses included gene ontologies, Kyoto Encyclopedia of Genes and Genomes pathways, metabolomics, COVID-19-related gene sets, and Genotype-Tissue Expression profiles. Analysis of 27 eligible microarrays identified 6284 DEGs (4592 downregulated and 1692 upregulated) in four tissue types. Tissue-specific gene expression was significantly greater than tissue non-specific (shared) gene expression. Analyses revealed 79 highly perturbed genes and 28 hub genes. Downstream analyses identified enrichments of shared genes with certain other diabetes phenotypes; insulin synthesis and action-related pathways and metabolomics; mechanistic associations with apoptosis and immunity-related pathways; COVID-19-related gene sets; and cell types demonstrating over- and under-expression of marker genes of T2D. Our approach provided valuable insights on T2D pathogenesis and pathophysiological manifestations. Broader utility of this pipeline beyond T2D is envisaged.

Causality of anthropometric markers associated with polycystic ovarian syndrome: Findings of a Mendelian randomization study.

INTRODUCTION: Using body mass index (BMI) as a proxy, previous Mendelian randomization (MR) studies found total causal effects of general obesity on polycystic ovarian syndrome (PCOS). Hitherto, total and direct causal effects of general- and central obesity on PCOS have not been comprehensively analyzed. OBJECTIVES: To investigate the causality of central- and general obesity on PCOS using surrogate anthropometric markers. METHODS: Summary GWAS data of female-only, large-sample cohorts of European ancestry were retrieved for anthropometric markers of central obesity (waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR)) and general obesity (BMI and its constituent variables-weight and height), from the IEU Open GWAS Project. As the outcome, we acquired summary data from a large-sample GWAS (118870 samples; 642 cases and 118228 controls) within the FinnGen cohort. Total causal effects were assessed via univariable two-sample Mendelian randomization (2SMR). Genetic architectures underlying causal associations were explored. Direct causal effects were analyzed by multivariable MR modelling. RESULTS: Instrumental variables demonstrated no weak instrument bias (F > 10). Four anthropometric exposures, namely, weight (2.69-77.05), BMI (OR: 2.90-4.06), WC (OR: 6.22-20.27), and HC (OR: 6.22-20.27) demonstrated total causal effects as per univariable 2SMR models. We uncovered shared and non-shared genetic architectures underlying causal associations. Direct causal effects of WC and HC on PCOS were revealed by two multivariable MR models containing exclusively the anthropometric markers of central obesity. Other multivariable MR models containing anthropometric markers of both central- and general obesity showed no direct causal effects on PCOS. CONCLUSIONS: Both and general- and central obesity yield total causal effects on PCOS. Findings also indicated potential direct causal effects of normal weight-central obesity and more complex causal mechanisms when both central- and general obesity are present. Results underscore the importance of addressing both central- and general obesity for optimizing PCOS care.

Do Probiotics Cause a Shift in the Microbiota of Dental Implants-A Systematic Review and Meta-Analysis.

Objective: The primary aim of this current systematic review and meta-analysis was to evaluate the potential microbiological effect of probiotics on the implant microbiota. The secondary aim was to evaluate if probiotics have any effect as an adjunct to non-surgical peri-implant treatment in reducing peri-implant mucositis and peri-implantitis clinical parameters-bleeding on probing, modified Gingival Index, and pocket depth. Methods: The research focus questions were constructed in accordance with the Participants, Intervention, Comparison, and Outcomes (PICO) criteria, and a PROSPERO protocol was registered. A comprehensive systematic search in MEDLINE via the PubMed, Scopus, and Web of Science Core Collection databases was conducted. Two independent reviewers screened the reports based on the PICO criteria-inclusion and exclusion criteria. Results: In total, 467 records were identified, and ultimately, 7 papers were included: 3 papers in the qualitative synthesis of microbiological effect and 4 in the meta-analysis synthesis on pocket depth. The data synthesis showed that probiotics had no detectable effect on the implant microflora, and in the following data synthesis, no clinical peri-implantitis variable showed a significantly beneficial effect from probiotics in the test group compared to the control group. Conclusion: Within the limitations of this review, the oral implant microflora is not affected by probiotics nor do probiotics add any effect to the conventional non-surgical treatment of peri-implant mucositis and peri-implantitis.

Calprotectin levels in amniotic fluid in relation to intra-amniotic inflammation and infection in women with preterm labor with intact membranes: A retrospective cohort study.

OBJECTIVE: To evaluate the concentrations of calprotectin in amniotic fluid with respect to intra-amniotic inflammation and infection and to assess the presence or absence of bacteria in the amnio-chorionic niche with respect to presence or absence of intra-amniotic inflammation. STUDY DESIGN: Seventy-nine women with singleton pregnancies and preterm labor with intact membranes (PTL) were included in the study. Amniotic fluid was collected at the time of admission by amniocentesis and calprotectin levels were analyzed from frozen/thawed samples using ELISA. Interleukin (IL)-6 concentration was measured by point-of-care test. Samples from amniotic fluid and the amnio-chorionic niche (space between amniotic and chorionic membranes) were microbiologically analyzed. Microbial invasion of the amniotic cavity (MIAC) was diagnosed based on a positive PCR result for Ureaplasma species, Mycoplasma hominis, 16S rRNA or positive culture. Intra-amniotic inflammation (IAI) was defined as amniotic fluid point-of-care IL-6 concentration ≥ 745 pg/mL. The cohort of included women was divided into 4 subgroups based on the presence or absence of IAI/MIAC; i) intra-amniotic infection, ii) sterile IAI, iii) intra-amniotic colonization and iv) neither MIAC nor IAI. RESULTS: Women with intra-amniotic infection had a significantly higher intra-amniotic calprotectin concentration (median; 101.6 µg/mL) compared with women with sterile IAI (median; 9.2 µg/mL), women with intra-amniotic colonization (median; 2.6 µg/mL) and women with neither MIAC nor IAI (median 4.6 µg/mL) (p = 0.001). Moreover, significantly higher amniotic fluid calprotectin concentration was seen in women who delivered within 7 days (p = 0.003). A significant negative correlation was found between amniotic fluid calprotectin and gestational age at delivery (rho = 0.32, p = 0.003). Relatively more bacteria in the amnio-chorionic niche were found in the sterile IAI group compared with the other groups. CONCLUSIONS: Calprotectin concentrations in amniotic fluid were significantly higher in the intra-amniotic infection group compared with the other groups. Moreover, the bacterial presence in the amnio-chorionic niche was higher in IAI group.

A data-driven biocomputing pipeline with meta-analysis on high throughput transcriptomics to identify genome-wide miRNA markers associated with type 2 diabetes.

BACKGROUND: MicroRNAs (miRNAs) are sought-after biomarkers of complex, polygenic diseases such as type 2 diabetes (T2D). Data-driven biocomputing provides robust and novel avenues for synthesizing evidence from individual miRNA seq studies. OBJECTIVE: To identify miRNA markers associated with T2D, via a data-driven, biocomputing approach on high throughput transcriptomics. MATERIALS AND METHODS: The pipeline consisted of five sequential steps using miRNA seq data retrieved from the National Center for Biotechnology Information Gene Expression Omnibus platform: systematic review; identification of differentially expressed miRNAs (DE-miRNAs); meta-analysis of DE-miRNAs; network analysis; and downstream analyses. Three normalization algorithms (trimmed mean of M-values; upper quartile; relative log expression) and two meta-analytic algorithms (robust rank aggregation; Fisher's method of p-value combining) were integrated into the pipeline. Network analysis was conducted on miRNet 2.0 while enrichment and over-representation analyses were conducted on miEAA 2.0. RESULTS: A total of 1256 DE-miRNAs (821 downregulated; 435 upregulated) were identified from 5 eligible miRNA seq datasets (3 circulatory; 1 adipose; 1 pancreatic). The meta-signature comprised 9 miRNAs (hsa-miR-15b-5p; hsa-miR-33b-5p; hsa-miR-106b-3p; hsa-miR-106b-5p; hsa-miR-146a-5p; hsa-miR-483-5p; hsa-miR-539-3p; hsa-miR-1260a; hsa-miR-4454), identified via the two meta-analysis approaches. Two hub nodes (hsa-miR-106b-5p; hsa-miR-15b-5p) with above-average degree and betweenness centralities in the miRNA-gene interactions network were identified. Downstream analyses revealed 5 highly conserved- (hsa-miR-33b-5p; hsa-miR-15b-5p; hsa-miR-106b-3p; hsa-miR-106b-5p; hsa-miR-146a-5p) and 7 highly confident- (hsa-miR-33b-5p; hsa-miR-15b-5p; hsa-miR-106b-3p; hsa-miR-106b-5p; hsa-miR-146a-5p; hsa-miR-483-5p; hsa-miR-539-3p) miRNAs. A total of 288 miRNA-disease associations were identified, in which 3 miRNAs (hsa-miR-15b-5p; hsa-miR-106b-3p; hsa-miR-146a-5p) were highly enriched. CONCLUSIONS: A meta-signature of DE-miRNAs associated with T2D was discovered via in-silico analyses and its pathobiological relevance was validated against corroboratory evidence from contemporary studies and downstream analyses. The miRNA meta-signature could be useful for guiding future studies on T2D. There may also be avenues for using the pipeline more broadly for evidence synthesis on other conditions using high throughput transcriptomics.

The inverse association between a fish consumption biomarker and gingival inflammation and periodontitis: A population-based study.

AIM: The metabolite 3-carboxy-4-methyl-5-propyl-2-furanpropionic acid (CMPF) is a fatty fish-intake biomarker. We investigated the association between plasma levels of CMPF in relation to gingival inflammation and periodontitis case definition, as well as the extent and severity variables. MATERIALS AND METHODS: The Malmö Offspring Study is a population-based study, and the Malmö Offspring Dental Study (MODS) is its dental arm, including periodontal charting. Plasma CMPF was measured using liquid chromatography-mass spectrometry and studied in relation to periodontal diagnosis and parameters using multivariable linear or logistic regression modelling adjusting for age, sex, education, body mass index, fasting glucose, and smoking. RESULTS: Metabolite data were available for 922 MODS participants. Higher CMPF levels were associated with less gingival inflammation (ß = -2.12, p = .002) and lower odds of severe periodontitis (odds ratio [OR] = 0.74, 95% confidence interval [CI]: 0.56 to 0.98). Higher CMPF levels were also associated with more teeth (ß = 0.19, p = .001), lower number of periodontal pockets (≥4 mm) (ß = -1.07, p = .007), and lower odds of having two or more periodontal pockets of ≥6 mm (OR = 0.80, 95% CI: 0.65 to 0.98) in fully adjusted models. CONCLUSIONS: CMPF, a validated biomarker of fatty fish consumption, is associated with less periodontal inflammation and periodontitis. Residual confounding cannot be ruled out, and future studies are warranted.

Direct Transmittance Estimation in Heterogeneous Participating Media Using Approximated Taylor Expansions.

Evaluating the transmittance between two points along a ray is a key component in solving the light transport through heterogeneous participating media and entails computing an intractable exponential of the integrated medium's extinction coefficient. While algorithms for estimating this transmittance exist, there is a lack of theoretical knowledge about their behaviour, which also prevent new theoretically sound algorithms from being developed. For this purpose, we introduce a new class of unbiased transmittance estimators based on random sampling or truncation of a Taylor expansion of the exponential function. In contrast to classical tracking algorithms, these estimators are non-analogous to the physical light transport process and directly sample the underlying extinction function without performing incremental advancement. We present several versions of the new class of estimators, based on either importance sampling or Russian roulette to provide finite unbiased estimators of the infinite Taylor series expansion. We also show that the well known ratio tracking algorithm can be seen as a special case of the new class of estimators. Lastly, we conduct performance evaluations on both the central processing unit (CPU) and the graphics processing unit (GPU), and the results demonstrate that the new algorithms outperform traditional algorithms for heterogeneous mediums.

Advanced Dental Cleaning is Associated with Reduced Risk of COPD Exacerbations - A Randomized Controlled Trial.

PURPOSE: Infections from the oral microbiome may lead to exacerbations of chronic obstructive pulmonary disease (COPD). We investigated whether advanced dental cleaning could reduce exacerbation frequency. Secondary outcomes were disease-specific health status, lung function, and whether the bacterial load and composition of plaque microbiome at baseline were associated with a difference in outcomes. PATIENTS AND METHODS: One-hundred-one primary and secondary care patients with COPD were randomized to intervention with advanced dental cleaning or to dental examination only, repeated after six months. At baseline and at 12 months, data of exacerbations, lung function, COPD Assessment Test (CAT) score, and periodontal status were collected from questionnaires, record review, and periodontal examination. Student's t-test and Mann-Whitney-U (MWU) test compared changes in outcomes. The primary outcome variable was also assessed using multivariable linear regression with adjustment for potential confounders. Microbiome analyses of plaque samples taken at baseline were performed using Wilcoxon signed ranks tests for calculation of alpha diversity, per mutational multivariate analysis of variance for beta diversity, and receiver operating characteristic curves for prediction of outcomes based on machine learning models. RESULTS: In the MWU test, the annual exacerbation frequency was significantly reduced in patients previously experiencing frequent exacerbations (p = 0.020) and in those with repeated advanced dental cleaning (p = 0.039) compared with the non-treated control group, but not in the total population including both patients with a single and repeated visits (p = 0.207). The result was confirmed in multivariable linear regression, where the risk of new exacerbations was significantly lower in patients both in the intention to treat analysis (regression coefficient 0.36 (95% CI 0.25-0.52), p < 0.0001) and in the population with repeated dental cleaning (0.16 (0.10-0.27), p < 0.0001). The composition of microbiome at baseline was moderately predictive of an increased risk of worsened health status at 12 months (AUC = 0.723). CONCLUSION: Advanced dental cleaning is associated with a reduced frequency of COPD exacerbations. Regular periodontal examination and dental cleaning may be of clinical importance to prevent COPD exacerbations.

Peri-implantitis: Summary and consensus statements of group 3. The 6th EAO Consensus Conference 2021.

OBJECTIVE: To evaluate the influence of implant and prosthetic components on peri-implant tissue health. A further aim was to evaluate peri-implant soft-tissue changes following surgical peri-implantitis treatment. MATERIALS AND METHODS: Group discussions based on two systematic reviews (SR) and one critical review (CR) addressed (i) the influence of implant material and surface characteristics on the incidence and progression of peri-implantitis, (ii) implant and restorative design elements and the associated risk for peri-implant diseases, and (iii) peri-implant soft-tissue level changes and patient-reported outcomes following peri-implantitis treatment. Consensus statements, clinical recommendations, and implications for future research were discussed within the group and approved during plenary sessions. RESULTS: Data from preclinical in vivo studies demonstrated significantly greater radiographic bone loss and increased area of inflammatory infiltrate at modified compared to non-modified surface implants. Limited clinical data did not show differences between modified and non-modified implant surfaces in incidence or progression of peri-implantitis (SR). There is some evidence that restricted accessibility for oral hygiene and an emergence angle of >30 combined with a convex emergence profile of the abutment/prosthesis are associated with an increased risk for peri-implantitis (CR). Reconstructive therapy for peri-implantitis resulted in significantly less soft-tissue recession, when compared with access flap. Implantoplasty or the adjunctive use of a barrier membrane had no influence on the extent of peri-implant mucosal recession following peri-implantitis treatment (SR). CONCLUSIONS: Prosthesis overcontouring and impaired access to oral hygiene procedures increases risk for peri-implantitis. When indicated, reconstructive peri-implantitis treatment may facilitate the maintenance of post-operative peri-implant soft-tissue levels.

Nutritional markers of undiagnosed type 2 diabetes in adults: Findings of a machine learning analysis with external validation and benchmarking.

OBJECTIVES: Using a nationally-representative, cross-sectional cohort, we examined nutritional markers of undiagnosed type 2 diabetes in adults via machine learning. METHODS: A total of 16429 men and non-pregnant women ≥ 20 years of age were analysed from five consecutive cycles of the National Health and Nutrition Examination Survey. Cohorts from years 2013-2016 (n = 6673) was used for external validation. Undiagnosed type 2 diabetes was determined by a negative response to the question "Have you ever been told by a doctor that you have diabetes?" and a positive glycaemic response to one or more of the three diagnostic tests (HbA1c > 6.4% or FPG >125 mg/dl or 2-hr post-OGTT glucose > 200mg/dl). Following comprehensive literature search, 114 potential nutritional markers were modelled with 13 behavioural and 12 socio-economic variables. We tested three machine learning algorithms on original and resampled training datasets built using three resampling methods. From this, the derived 12 predictive models were validated on internal- and external validation cohorts. Magnitudes of associations were gauged through odds ratios in logistic models and variable importance in others. Models were benchmarked against the ADA diabetes risk test. RESULTS: The prevalence of undiagnosed type 2 diabetes was 5.26%. Four best-performing models (AUROC range: 74.9%-75.7%) classified 39 markers of undiagnosed type 2 diabetes; 28 via one or more of the three best-performing non-linear/ensemble models and 11 uniquely by the logistic model. They comprised 14 nutrient-based, 12 anthropometry-based, 9 socio-behavioural, and 4 diet-associated markers. AUROC of all models were on a par with ADA diabetes risk test on both internal and external validation cohorts (p>0.05). CONCLUSIONS: Models performed comparably to the chosen benchmark. Novel behavioural markers such as the number of meals not prepared from home were revealed. This approach may be useful in nutritional epidemiology to unravel new associations with type 2 diabetes.

Clinical notes as prognostic markers of mortality associated with diabetes mellitus following critical care: A retrospective cohort analysis using machine learning and unstructured big data.

BACKGROUND: Clinical notes are ubiquitous resources offering potential value in optimizing critical care via data mining technologies. OBJECTIVE: To determine the predictive value of clinical notes as prognostic markers of 1-year all-cause mortality among people with diabetes following critical care. MATERIALS AND METHODS: Mortality of diabetes patients were predicted using three cohorts of clinical text in a critical care database, written by physicians (n = 45253), nurses (159027), and both (n = 204280). Natural language processing was used to pre-process text documents and LASSO-regularized logistic regression models were trained and tested. Confusion matrix metrics of each model were calculated and AUROC estimates between models were compared. All predictive words and corresponding coefficients were extracted. Outcome probability associated with each text document was estimated. RESULTS: Models built on clinical text of physicians, nurses, and the combined cohort predicted mortality with AUROC of 0.996, 0.893, and 0.922, respectively. Predictive performance of the models significantly differed from one another whereas inter-rater reliability ranged from substantial to almost perfect across them. Number of predictive words with non-zero coefficients were 3994, 8159, and 10579, respectively, in the models of physicians, nurses, and the combined cohort. Physicians' and nursing notes, both individually and when combined, strongly predicted 1-year all-cause mortality among people with diabetes following critical care. CONCLUSION: Clinical notes of physicians and nurses are strong and novel prognostic markers of diabetes-associated mortality in critical care, offering potentially generalizable and scalable applications. Clinical text-derived personalized risk estimates of prognostic outcomes such as mortality could be used to optimize patient care.

The Malmö Offspring Study (MOS): design, methods and first results.

As cardio metabolic disease manifestations tend to cluster in families there is a need to better understand the underlying mechanisms in order to further develop preventive strategies. In fact, genetic markers used in genetic risk scores, important as they are, will not be able alone to explain these family clusters. Therefore, the search goes on for the so called missing heritability to better explain these associations. Shared lifestyle and social conditions in families, but also early life influences may be of importance. Gene-environmental interactions should be explored. In recent years interest has grown for the role of diet-microbiota associations, as microbiota patterns may be shared by family members. In the Malmö Offspring Study that started in 2013, we have so far been able to examine about 4700 subjects (18-71 years) representing children and grandchildren of index subjects from the first generation, examined in the Malmö Diet Cancer Study during 1991 to 1996. This will provide rich data and opportunities to analyse family traits of chronic disease across three generations. We will provide extensive genotyping and phenotyping including cardiovascular and respiratory function, as well as markers of glucose metabolism. In addition, also cognitive function will be assessed. A 4-day online dietary recall will be conducted and gut as well as oral microbiota analysed. The ambition is to provide one of the first large-scale European family studies with individual data across three generations, which could deepen our knowledge about the role of family traits for chronic disease and its underlying mechanisms.

Structural Analysis of Experimentally Induced Disc Herniation-Like Changes in the Rat.

INTRODUCTION: A disc herniation has traditionally been considered as disc tissue that has slipped out from an intervertebral disc. However, it was recently suggested that the disc herniation mass is a product of bioactive substances from the disc and that the disc hernia would more likely be scar tissue than herniated disc material. In this study, we aimed to analyze the structural components of experimentally induced disc herniations and compare with scar tissue and nucleus pulposus, in the rat. METHODS: Twenty-eight rats had their L4-5 discs punctured. After three weeks, the nodule that had been formed over the puncture site, scar tissue from the spine musculature, and normal nucleus pulposus were harvested and processed for further analysis. RESULTS: Proteomics analysis demonstrated that the formed nodule was more similar to scar tissue than to nucleus pulposus. Gene expression analysis showed that there was no resemblance between any tissues when looking at inflammatory genes but that, there was a clear resemblance between the nodule and scar tissue when analyzing extracellular matrix-related genes. Analysis of the GAG and polysaccharide size distribution revealed that only the nodule and scar tissue contained the shorter versions, potentially short chain hyaluronic acid that is known to induce inflammatory responses. The hematoxylin and eosin stained sections of the nodule, disc tissue, and scar tissue indicated that the morphology of the nodule and scar tissue was very similar. CONCLUSIONS: The nodule formed after experimental disc puncture, and that resembles a disc hernia, has a more structural resemblance to scar tissue than disc tissue. The nodule is, therefore, more likely to be induced by disc-derived bioactive substances than being formed by herniated disc material.

Mid-trimester amniotic fluid proteome's association with spontaneous preterm delivery and gestational duration.

BACKGROUND: Amniotic fluid is clinically accessible via amniocentesis and its protein composition may correspond to birth timing. Early changes in the amniotic fluid proteome could therefore be associated with the subsequent development of spontaneous preterm delivery. OBJECTIVE: The main objective of this study was to perform unbiased proteomics analysis of the association between mid-trimester amniotic fluid proteome and spontaneous preterm delivery and gestational duration, respectively. A secondary objective was to validate and replicate the findings by enzyme-linked immunosorbent assay using a second independent cohort. METHODS: Women undergoing a mid-trimester genetic amniocentesis at Sahlgrenska University Hospital/Östra between September 2008 and September 2011 were enrolled in this study, designed in three analytical stages; 1) an unbiased proteomic discovery phase using LC-MS analysis of 22 women with subsequent spontaneous preterm delivery (cases) and 37 women who delivered at term (controls), 2) a validation phase of proteins of interest identified in stage 1, and 3) a replication phase of the proteins that passed validation using a second independent cohort consisting of 20 cases and 40 matched controls. RESULTS: Nine proteins were nominally significantly associated with both spontaneous preterm delivery and gestational duration, after adjustment for gestational age at sampling, but none of the proteins were significant after correction for multiple testing. Several of these proteins have previously been described as being associated with spontaneous PTD etiology and six of them were thus validated using enzyme linked immunosorbent assay. Two of the proteins passed validation; Neutrophil gelatinase-associated lipocalin and plasminogen activator inhibitor 1, but the results could not be replicated in a second cohort. CONCLUSIONS: Neutrophil gelatinase-associated lipocalin and Plasminogen activator inhibitor 1 are potential biomarkers of spontaneous preterm delivery and gestational duration but the findings could not be replicated. The negative findings are supported by the fact that none of the nine proteins from the exploratory phase were significant after correction for multiple testing.

A combined strategy of feature selection and machine learning to identify predictors of prediabetes.

OBJECTIVE: To identify predictors of prediabetes using feature selection and machine learning on a nationally representative sample of the US population. MATERIALS AND METHODS: We analyzed n = 6346 men and women enrolled in the National Health and Nutrition Examination Survey 2013-2014. Prediabetes was defined using American Diabetes Association guidelines. The sample was randomly partitioned to training (n = 3174) and internal validation (n = 3172) sets. Feature selection algorithms were run on training data containing 156 preselected exposure variables. Four machine learning algorithms were applied on 46 exposure variables in original and resampled training datasets built using 4 resampling methods. Predictive models were tested on internal validation data (n = 3172) and external validation data (n = 3000) prepared from National Health and Nutrition Examination Survey 2011-2012. Model performance was evaluated using area under the receiver operating characteristic curve (AUROC). Predictors were assessed by odds ratios in logistic models and variable importance in others. The Centers for Disease Control (CDC) prediabetes screening tool was the benchmark to compare model performance. RESULTS: Prediabetes prevalence was 23.43%. The CDC prediabetes screening tool produced 64.40% AUROC. Seven optimal (≥ 70% AUROC) models identified 25 predictors including 4 potentially novel associations; 20 by both logistic and other nonlinear/ensemble models and 5 solely by the latter. All optimal models outperformed the CDC prediabetes screening tool (P < 0.05). DISCUSSION: Combined use of feature selection and machine learning increased predictive performance outperforming the recommended screening tool. A range of predictors of prediabetes was identified. CONCLUSION: This work demonstrated the value of combining feature selection with machine learning to identify a wide range of predictors that could enhance prediabetes prediction and clinical decision-making.

Inviwo - A Visualization System with Usage Abstraction Levels.

The complexity of today's visualization applications demands specific visualization systems tailored for the development of these applications. Frequently, such systems utilize levels of abstraction to improve the application development process, for instance by providing a data flow network editor. Unfortunately, these abstractions result in several issues, which need to be circumvented through an abstraction-centered system design. Often, a high level of abstraction hides low level details, which makes it difficult to directly access the underlying computing platform, which would be important to achieve an optimal performance. Therefore, we propose a layer structure developed for modern and sustainable visualization systems allowing developers to interact with all contained abstraction levels. We refer to this interaction capabilities as usage abstraction levels, since we target application developers with various levels of experience. We formulate the requirements for such a system, derive the desired architecture, and present how the concepts have been exemplary realized within the Inviwo visualization system. Furthermore, we address several specific challenges that arise during the realization of such a layered architecture, such as communication between different computing platforms, performance centered encapsulation, as well as layer-independent development by supporting cross layer documentation and debugging capabilities.

Visual Analysis for Understanding Irritable Bowel Syndrome.

The cause of irritable bowel syndrome (IBS), a chronic disorder characterized by abdominal pain and disturbed bowel habits, is largely unknown. It is believed to be related to physical properties in the gut, central mechanisms in the brain, psychological factors, or a combination of these. To understand the relationships within the gut-brain axis with respect to IBS, large numbers of measurements ranging from stool samples to functional magnetic resonance imaging are collected from patients with IBS and healthy controls. As such, IBS is a typical example in medical research where research turns into a big data analysis challenge. In this chapter we demonstrate the power of interactive visual data analysis and exploration to generate an environment for scientific reasoning and hypothesis formulation for data from multiple sources with different character. Three case studies are presented to show the utility of the presented work.