A second order scheme for a Robin boundary condition in random walk algorithms

Random Walk (RW) is a common numerical tool for modeling the Advection-Diffusion equation. In this work, we develop a second order scheme for incorporating a heterogeneous reaction (i.e., a Robin boundary condition) in the RW model. In addition, we apply the approach in two test cases. We compare the second order scheme with the first order one as well as with analytical and other numerical solution. We show that the new scheme can reduce the computational error significantly, relative to the first order scheme. This reduction comes at no additional computational cost

The oral mucosal and salivary microbial community of Behçet's syndrome and recurrent aphthous stomatitis.

This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License, permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.Behçet's syndrome (BS) is a multisystem immune-related disease of unknown etiology. Recurrent aphthous stomatitis (RAS) is characterized by the presence of idiopathic oral ulceration without extraoral manifestation. The interplay between the oral microbial communities and the immune response could play an important role in the etiology and pathogenesis of both BS and RAS

Accurate Profiling of Microbial Communities from Massively Parallel Sequencing using Convex Optimization

We describe the Microbial Community Reconstruction ({\bf MCR}) Problem, which is fundamental for microbiome analysis. In this problem, the goal is to reconstruct the identity and frequency of species comprising a microbial community, using short sequence reads from Massively Parallel Sequencing (MPS) data obtained for specified genomic regions. We formulate the problem mathematically as a convex optimization problem and provide sufficient conditions for identifiability, namely the ability to reconstruct species identity and frequency correctly when the data size (number of reads) grows to infinity. We discuss different metrics for assessing the quality of the reconstructed solution, including a novel phylogenetically-aware metric based on the Mahalanobis distance, and give upper-bounds on the reconstruction error for a finite number of reads under different metrics. We propose a scalable divide-and-conquer algorithm for the problem using convex optimization, which enables us to handle large problems (with $\sim10^6$ species). We show using numerical simulations that for realistic scenarios, where the microbial communities are sparse, our algorithm gives solutions with high accuracy, both in terms of obtaining accurate frequency, and in terms of species phylogenetic resolution.Comment: To appear in SPIRE 1

Specified Species in Gingival Crevicular Fluid Predict Bacterial Diversity

BACKGROUND: Analysis of gingival crevicular fluid (GCF) samples may give information of unattached (planktonic) subgingival bacteria. Our study represents the first one targeting the identity of bacteria in GCF. METHODOLOGY/PRINCIPAL FINDINGS: We determined bacterial species diversity in GCF samples of a group of periodontitis patients and delineated contributing bacterial and host-associated factors. Subgingival paper point (PP) samples from the same sites were taken for comparison. After DNA extraction, 16S rRNA genes were PCR amplified and DNA-DNA hybridization was performed using a microarray for over 300 bacterial species or groups. Altogether 133 species from 41 genera and 8 phyla were detected with 9 to 62 and 18 to 64 species in GCF and PP samples, respectively, per patient. Projection to latent structures by means of partial least squares (PLS) was applied to the multivariate data analysis. PLS regression analysis showed that species of genera including Campylobacter, Selenomonas, Porphyromonas, Catonella, Tannerella, Dialister, Peptostreptococcus, Streptococcus and Eubacterium had significant positive correlations and the number of teeth with low-grade attachment loss a significant negative correlation to species diversity in GCF samples. OPLS/O2PLS discriminant analysis revealed significant positive correlations to GCF sample group membership for species of genera Campylobacter, Leptotrichia, Prevotella, Dialister, Tannerella, Haemophilus, Fusobacterium, Eubacterium, and Actinomyces. CONCLUSIONS/SIGNIFICANCE: Among a variety of detected species those traditionally classified as Gram-negative anaerobes growing in mature subgingival biofilms were the main predictors for species diversity in GCF samples as well as responsible for distinguishing GCF samples from PP samples. GCF bacteria may provide new prospects for studying dynamic properties of subgingival biofilms

Ligature-associated bacterial profiles are linked to type 2 diabetes mellitus in a rat model and influenced by antibody treatment against TNF-α or RAGE

There is a bidirectional relationship between periodontal disease (PD) and type 2 diabetes mellitus (T2D). T2D may lead to ecological perturbations in the oral environment, which may facilitate an altered microbiota. However, previous studies have been inconclusive in determining the effect of T2D on oral bacterial profiles. Therefore, we aimed to evaluate the influence of T2D on the ligature‐associated bacterial profile in a diabetic rat model with PD and investigated the impact of blocking inflammatory pathways with antibodies targeting either Tumor Necrosis Factor α (TNF‐α) or the receptor of advanced glycation end‐products (RAGE). A total of 62 Zucker obese rats (45 T2D) and 17 lean (non‐T2D) were divided into 4 treatment groups; lean with PD, obese with PD, obese with PD and anti‐TNF‐α treatment, and obese with PD with anti‐RAGE treatment. Periodontal disease was ligature induced. Ligature‐associated bacterial profiles were analyzed using Human Oral Microbe Identification Microarray (HOMIM). Ligature‐associated bacterial profiles differed between lean and obese rats. Furthermore, treatment with antibodies against TNF‐α or RAGE had an impact on subgingival bacterial profiles. T2D phenotypes are associated with different ligature‐associated bacterial profiles and influenced by treatment with antibodies against TNF‐α or RAGE

Correlation of Aggregatibacter actinomycetemcomitans Detection with Clinical/Immunoinflammatory Profile of Localized Aggressive Periodontitis Using a 16S rRNA Microarray Method: A Cross-Sectional Study

Objective The objective of this study was to determine whether the detection of Aggregatibacter actinomycetemcomitans (Aa) correlates with the clinical and immunoinflammatory profile of Localized Aggressive Periodontitis (LAP), as determined by by 16S rRNA gene-based microarray. Subjects and Methods Subgingival plaque samples from the deepest diseased site of 30 LAP patients [PD ≥ 5 mm, BoP and bone loss] were analyzed by 16S rRNA gene-based microarrays. Gingival crevicular fluid (GCF) samples were analyzed for 14 cyto/chemokines. Peripheral blood was obtained and stimulated in vitro with P.gingivalis and E.coli to evaluate inflammatory response profiles. Plasma lipopolysaccharide (LPS) levels were also measured. Results Aa was detected in 56% of LAP patients and was shown to be an indicator for different bacterial community structures (p\u3c0.01). Elevated levels of pro-inflammatory cyto/chemokines were detected in LPS-stimulated blood samples in both Aa-detected and Aa-non-detected groups (p\u3e0.05). Clinical parameters and serum LPS levels were similar between groups. However, Aa-non-detected GCF contained higher concentration of IL-8 than Aa-detected sites (p\u3c0.05). TNFα and IL1β were elevated upon E.coli LPS stimulation of peripheral blood cells derived from patients with Aa-detected sites. Conclusions Our findings demonstrate that the detection of Aa in LAP affected sites, did not correlate with clinical severity of the disease at the time of sampling in this cross-sectional study, although it did associate with lower local levels of IL-8, a different subgingival bacterial profile and elevated LPS-induced levels of TNFα and IL1β

Short-term memory binding and semantic network strength reinforce prospective memory in older adults

Objective Prospective memory (Pro-M), or remembering to carry out a future task, is critical to everyday functioning, but is not assessed by traditional neuropsychological measures. In this study, we investigated neurocognitive mechanisms underlying Pro-M ability in older adults. Participants and Methods 48 nondemented older adults (M age=75.2; SD=2.1) were recruited from the UCSD Alzheimer’s Disease Research Center (ADRC). Participants were 60% female and averaged 17.2 years (SD=2.1) of education. The Memory for Intentions Screening Test (MIST; Raskin et al., 2010) and a visual short-term memory (STM) binding task (Parra et al., 2017) were administered in a single session. Results were compared with scores on traditional neuropsychological measures from a recent ADRC annual assessment. Results Overall performance on the MIST was significantly correlated with shape-color binding accuracy (r=0.38; p 0.10). Analysis of errors on MIST time-cued tasks revealed the most common error was performing an incorrect task at the prescribed time (61%), whereas performing the prescribed task at the incorrect time was relatively infrequent (13%). Conclusions Performance of non-demented older adults on Pro-M was associated with STM binding and category fluency but not episodic memory or executive functioning. These results suggest that Pro-M is a unique aspect of memory functioning that is distinct from episodic memory and requires synthesizing multiple cognitive strategies. Participants with a stronger semantic network may be able to create a strong association for the intention at the time of encoding, while Pro-M failures could be explained by a failure to adequately bind the semantic components of the encoded intention and the future action

T Cell Activation Results in Conformational Changes in the Src Family Kinase Lck to Induce Its Activation

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Restoration of Posidonia oceanica meadows : means and limitations.

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