Vinayak Joshi

Tobacco smoking affects bacterial acquisition and colonization in oral biofilms.

ABSTRACT Recent evidence suggests that smoking affects the composition of the disease-associated subgingival biofilm, yet little is known about its effects during the formation of this biofilm. The present investigation was undertaken to examine the contributions of smoking to the composition and proinflammatory characteristics of the biofilm during de novo plaque formation. Marginal and subgingival plaque and gingival crevicular fluid samples were collected from 15 current smokers and from 15 individuals who had never smoked (nonsmokers) following 1, 2, 4, and 7 days of undisturbed plaque formation. 16S rRNA gene cloning and sequencing were used for bacterial identification, and multiplex bead-based flow cytometry was used to quantify the levels of 27 immune mediators. Smokers demonstrated a highly diverse, relatively unstable initial colonization of both marginal and subgingival biofilms, with lower niche saturation than that seen in nonsmokers. Periodontal pathogens belonging to the genera Fusobacterium, Cardiobacterium, Synergistes, and Selenomonas, as well as respiratory pathogens belonging to the genera Haemophilus and Pseudomonas, colonized the early biofilms of smokers and continued to persist over the observation period, suggesting that smoking favors early acquisition and colonization of pathogens in oral biofilms. Smokers also demonstrated an early proinflammatory response to this colonization, which persisted over 7 days. Further, a positive correlation between proinflammatory cytokine levels and commensal bacteria was observed in smokers but not in nonsmokers. Taken together, the data suggest that smoking influences both the composition of the nascent biofilm and the host response to this colonization.

Deep Sequencing Identifies Ethnicity-Specific Bacterial Signatures in the Oral Microbiome

Oral infections have a strong ethnic predilection; suggesting that ethnicity is a critical determinant of oral microbial colonization. Dental plaque and saliva samples from 192 subjects belonging to four major ethnicities in the United States were analyzed using terminal restriction fragment length polymorphism (t-RFLP) and 16S pyrosequencing. Ethnicity-specific clustering of microbial communities was apparent in saliva and subgingival biofilms, and a machine-learning classifier was capable of identifying an individual’s ethnicity from subgingival microbial signatures. The classifier identified African Americans with a 100% sensitivity and 74% specificity and Caucasians with a 50% sensitivity and 91% specificity. The data demonstrates a significant association between ethnic affiliation and the composition of the oral microbiome; to the extent that these microbial signatures appear to be capable of discriminating between ethnicities.

Automated Method for Identification and Artery-Venous Classification of Vessel Trees in Retinal Vessel Networks

The separation of the retinal vessel network into distinct arterial and venous vessel trees is of high interest. We propose an automated method for identification and separation of retinal vessel trees in a retinal color image by converting a vessel segmentation image into a vessel segment map and identifying the individual vessel trees by graph search. Orientation, width, and intensity of each vessel segment are utilized to find the optimal graph of vessel segments. The separated vessel trees are labeled as primary vessel or branches. We utilize the separated vessel trees for arterial-venous (AV) classification, based on the color properties of the vessels in each tree graph. We applied our approach to a dataset of 50 fundus images from 50 subjects. The proposed method resulted in an accuracy of 91.44 correctly classified vessel pixels as either artery or vein. The accuracy of correctly classified major vessel segments was 96.42.

Automated measurement of retinal blood vessel tortuosity

Abnormalities in the vascular pattern of the retina are associated with retinal diseases and are also risk factors for systemic diseases, especially cardiovascular diseases. The three-dimensional retinal vascular pattern is mostly formed congenitally, but is then modified over life, in response to aging, vessel wall dystrophies and long term changes in blood flow and pressure. A characteristic of the vascular pattern that is appreciated by clinicians is vascular tortuosity, i.e. how curved or kinked a blood vessel, either vein or artery, appears along its course. We developed a new quantitative metric for vascular tortuosity, based on the vessels angle of curvature, length of the curved vessel over its chord length (arc to chord ratio), number of curvature sign changes, and combined these into a unidimensional metric, Tortuosity Index (TI). In comparison to other published methods this method can estimate appropriate TI for vessels with constant curvature sign and vessels with equal arc to chord ratios, as well. We applied this method to a dataset of 15 digital fundus images of 8 patients with Facioscapulohumeral muscular dystrophy (FSHD), and to the other publically available dataset of 60 fundus images of normal cases and patients with hypertensive retinopathy, of which the arterial and venous tortuosities have also been graded by masked experts (ophthalmologists). The method produced exactly the same rank-ordered list of vessel tortuosity (TI) values as obtained by averaging the tortuosity grading given by 3 ophthalmologists for FSHD dataset and a list of TI values with high ranking correlation with the ophthalmologists grading for the other dataset. Our results show that TI has potential to detect and evaluate abnormal retinal vascular structure in early diagnosis and prognosis of retinopathies.

Host–Bacterial Interactions During Induction and Resolution of Experimental Gingivitis in Current Smokers

BACKGROUND Changes in clinical profiles, microbial succession, and immune mediator fluctuations have all been separately examined during onset and resolution of experimental gingivitis in smokers. However, because both the bacterial challenge and the host response contribute to periodontal disease, the purpose of this investigation is to simultaneously examine clinical, bacterial, and immune changes that occur during the onset and resolution of disease in smokers. METHODS Experimental gingivitis was induced in 15 smokers for 21 days, followed by treatment with a sonic toothbrush for 21 days. Marginal and subgingival plaque and gingival crevicular fluid samples were collected at baseline; after 7, 14, and 21 days of undisturbed plaque formation; and 21 days after reinstitution of brushing. 16S cloning and sequencing was used for bacterial quantification, and multiplexed bead-based flow cytometry was used to quantify the levels of 27 immune mediators. RESULTS Onset of clinical gingivitis was preceded by significant changes in the marginal and subgingival biofilms, with a decrease in the abundance of early colonizers, namely, Streptococcus, Veillonella, and Pseudomonas, and an increase in levels of periodontopathogens, such as Treponema, Selenomonas, Parvimonas, Dialister, and Campylobacter. This was accompanied by a decrease in anti-inflammatory, chemokine, and T-helper 2 (Th2) responses and altered Th1/Th2 ratios. Although the bacterial communities continued to shift in the same direction after onset of clinical gingivitis and returned to baseline levels after resolution of disease, the anti-inflammatory, chemokine, and Th2 profiles demonstrated an increase from day 14 that continued even after clinical health was evident. CONCLUSION Both marginal and subgingival biofilms in smokers are characterized by early acquisition of pathogenic organisms, which elicit a sustained host response that persists even after removal of the bacterial challenge.

Retinal arterial but not venous tortuosity correlates with facioscapulohumeral muscular dystrophy severity

BACKGROUND Facioscapulohumeral muscular dystrophy (FSHD) is an autosomal-dominant disease beginning with facial and shoulder girdle weakness with variable progression. Exudative retinal detachment, retinal vessel irregularities on fluorescein angiography, and retinal vessel tortuosity have been found in association with FSHD. METHODS In this retrospective study, muscle affectedness severity was rated as mild, moderate, or severe by a neurologist masked to the retinal images. Three ophthalmologists masked to disease severity graded the degree of arterial and venous tortuosity on a scale of 1 to 4. An automated method estimated an index of tortuosity for arteries and veins from color fundus photographs. Spearman rank correlation coefficients were used to describe the relationship between retinal vessel tortuosity and disease severity. RESULTS Seven patients with an average age of 13 years (range, 7-36 years) were selected. Correlation between the subjective tortuosity for arteries, and the severity of FSHD was 0.78 (p = 0.039). The correlation coefficient for venous tortuosity was -0.06 and was not significant (p = 0.882). The correlation coefficient between the average algorithmic computer-generated tortuosity indices for arteries and FSHD severity was high (0.85, p = 0.016), but for veins it was low and not significant (0.19, p = 0.662). CONCLUSIONS The authors of previous reports have shown retinal vascular abnormalities did not correlate to FSHD disease severity. Our results suggest a correlation between the tortuosity of arteries and the severity of disease in FSHD patients. These results suggest the tortuosity of arteries can serve as a biomarker of severity of disease in these FSHD patients, either as determined by human experts or by an automated method.

Automated method for the identification and analysis of vascular tree structures in retinal vessel network

Structural analysis of retinal vessel network has so far served in the diagnosis of retinopathies and systemic diseases. The retinopathies are known to affect the morphologic properties of retinal vessels such as course, shape, caliber, and tortuosity. Whether the arteries and the veins respond to these changes together or in tandem has always been a topic of discussion. However the diseases such as diabetic retinopathy and retinopathy of prematurity have been diagnosed with the morphologic changes specific either to arteries or to veins. Thus a method describing the separation of retinal vessel trees imaged in a two dimensional color fundus image may assist in artery-vein classification and quantitative assessment of morphologic changes particular to arteries or veins. We propose a method based on mathematical morphology and graph search to identify and label the retinal vessel trees, which provides a structural mapping of vessel network in terms of each individual primary vessel, its branches and spatial positions of branching and cross-over points. The method was evaluated on a dataset of 15 fundus images resulting into an accuracy of 92.87 % correctly assigned vessel pixels when compared with the manual labeling of separated vessel trees. Accordingly, the structural mapping method performs well and we are currently investigating its potential in evaluating the characteristic properties specific to arteries or veins.

Automated artery-venous classification of retinal blood vessels based on structural mapping method

Retinal blood vessels show morphologic modifications in response to various retinopathies. However, the specific responses exhibited by arteries and veins may provide a precise diagnostic information, i.e., a diabetic retinopathy may be detected more accurately with the venous dilatation instead of average vessel dilatation. In order to analyze the vessel type specific morphologic modifications, the classification of a vessel network into arteries and veins is required. We previously described a method for identification and separation of retinal vessel trees; i.e. structural mapping. Therefore, we propose the artery-venous classification based on structural mapping and identification of color properties prominent to the vessel types. The mean and standard deviation of each of green channel intensity and hue channel intensity are analyzed in a region of interest around each centerline pixel of a vessel. Using the vector of color properties extracted from each centerline pixel, it is classified into one of the two clusters (artery and vein), obtained by the fuzzy-C-means clustering. According to the proportion of clustered centerline pixels in a particular vessel, and utilizing the artery-venous crossing property of retinal vessels, each vessel is assigned a label of an artery or a vein. The classification results are compared with the manually annotated ground truth (gold standard). We applied the proposed method to a dataset of 15 retinal color fundus images resulting in an accuracy of 88.28% correctly classified vessel pixels. The automated classification results match well with the gold standard suggesting its potential in artery-venous classification and the respective morphology analysis.

A tale of two risks: smoking, diabetes and the subgingival microbiome

Although smoking and diabetes have been established as the only two risk factors for periodontitis, their individual and synergistic impacts on the periodontal microbiome are not well studied. The present investigation analyzed 2.7 million 16S sequences from 175 non-smoking normoglycemic individuals (controls), smokers, diabetics and diabetic smokers with periodontitis as well as periodontally healthy controls, smokers and diabetics to assess subgingival bacterial biodiversity and co-occurrence patterns. The microbial signatures of periodontally healthy smokers, but not diabetics, were highly aligned with the disease-associated microbiomes of their respective cohorts. Diabetics were dominated by species belonging to Fusobacterium, Parvimonas, Peptostreptococcus, Gemella, Streptococcus, Leptotrichia, Filifactor, Veillonella, TM7 and Terrahemophilus. These microbiomes exhibited significant clustering based on HbA1c levels (pre-diabetic (<6.5%), diabetic (6.5–9.9%), diabetics >10%). Smokers with periodontitis evidenced a robust core microbiome (species identified in at least 80% of individuals) dominated by anaerobes, with inter-individual differences attributable largely to the ‘rare biosphere’. Diabetics and diabetic smokers, on the other hand, were microbially heterogeneous and enriched for facultative species. In smokers, microbial co-occurrence networks were sparse and predominantly congeneric, while robust inter-generic networks were observed in diabetics and diabetic smokers. Smoking and hyperglycemia impact the subgingival microbiome in distinct ways, and when these perturbations intersect, their synergistic effect is greater than what would be expected from the sum of each effect separately. Thus, this study underscores the importance of early intervention strategies in maintaining health-compatible microbiomes in high-risk individuals, as well as the need to personalize these interventions based on the environmental perturbation.

Identification and reconnection of interrupted vessels in retinal vessel segmentation

The morphology of retinal blood vessels contains valuable information for the diagnosis of retinal dysfunctions. The vessels can be segmented from color fundus images but the connectivity of the segmented vessels is not always preserved because of low contrast, imaging noise and artifacts. If a continuous vessel is interpreted as multiple disjoint vessel segments, the morphological measurements such as tortuosity may not be representative of true properties of retinal vessels. We describe an algorithm to identify the vessel segment interruptions based on connected component analysis and then reconnect them using a graph based approach. The proposed method was evaluated on a dataset of 25 vessel segmentation images resulting into a reconnection performance measure of 81.63% compared to the gold standard obtained by the manual reconnection process. Our approach has allowed the complete vessel tree to be connected, and has potential in providing improved morphological measurements.