Publications by authors named "Shareef M Dabdoub"

16 Publications

  • Page 1 of 1

Acquisition, Divergence, and Personalization of the Female Perineal Microbiomes Are Driven by Developmental Milestones and Disrupted by Urinary Tract Infection: A Pilot Study.

Front Pediatr 2020 8;8:542413. Epub 2020 Dec 8.

Center for Microbial Pathogenesis, Research Institute at Nationwide Children's Hospital, Columbus, OH, United States.

The pediatric perineal microbiomes inhabit a dynamic environment with changes related to diet, toileting habits, and hormonal development. We hypothesized that next-generation sequencing would reveal different perineal bacterial signatures associated with developmental milestones in premenstrual females. Furthermore, we predicted that these microbial changes would be disrupted in premenstrual females with a history of urinary tract infection (UTI). Healthy females were recruited at well-child visits. Subjects were divided into 4 developmental groups: (1) 0-3 month old newborns; (2) 4-10 month old infants transitioning to solid foods; (3) 2-6 year old toddlers peri-toilet training; and (4) 7-12 year old premenstrual girls. A separate group of females with a history of culture proven UTI and off antibiotics >1 month was also recruited. DNA was isolated from swabs of the perineum and subjected to 16S rRNA sequencing. The diversity and species changes between developmental cohorts and age matched children with history of UTI was determined. A total of 75 subjects were recruited: 15 in each group. There was a clear evolution of the perineal microbiomes with development. There was a significant microbial disruption in girls with a history of UTI, irrespective of developmental milestone age group. The periurethral/perivaginal site displayed greater changes in microbiome structure than other sites in girls with a history of UTI. This pilot study evaluates the normal microbiome of the premenstrual girl at specific developmental milestones. Although the number of children per cohort was limited to 15, we observed statistical significance corresponding with developmental milestones. This study provides the first, culture independent delineation of the development of the perineal microbiome in girls. Furthermore, the sites closest to the site of infection appear to be more sensitive to antibiotic remodeling than those more distant. The factors that remodel the perineal microbiomes and predispose females, particularly girls, to UTIs (e.g., increase in uropathogen presence, absence of protective organisms) are unclear. Identification of specific signatures that increase susceptibility to UTI and their sequelae will improve patient care and promote personalized medicine.
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http://dx.doi.org/10.3389/fped.2020.542413DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7752998PMC
December 2020

Probing periodontal microbial dark matter using metataxonomics and metagenomics.

Periodontol 2000 2021 Feb 23;85(1):12-27. Epub 2020 Nov 23.

Department of Periodontics, College of Dentistry and Dental Clinics, The University of Iowa, Iowa City, Iowa, USA.

Our view of the periodontal microbial community has been shaped by a century or more of cultivation-based and microscopic investigations. While these studies firmly established the infection-mediated etiology of periodontal diseases, it was apparent from the very early days that periodontal microbiology suffered from what Staley and Konopka described as the "great plate count anomaly", in that these culturable bacteria were only a minor part of what was visible under the microscope. For nearly a century, much effort has been devoted to finding the right tools to investigate this uncultivated majority, also known as "microbial dark matter". The discovery that DNA was an effective tool to "see" microbial dark matter was a significant breakthrough in environmental microbiology, and oral microbiologists were among the earliest to capitalize on these advances. By identifying the order in which nucleotides are arranged in a stretch of DNA (DNA sequencing) and creating a repository of these sequences, sequence databases were created. Computational tools that used probability-driven analysis of these sequences enabled the discovery of new and unsuspected species and ascribed novel functions to these species. This review will trace the development of DNA sequencing as a quantitative, open-ended, comprehensive approach to characterize microbial communities in their native environments, and explore how this technology has shifted traditional dogmas on how the oral microbiome promotes health and its role in disease causation and perpetuation.
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http://dx.doi.org/10.1111/prd.12349DOI Listing
February 2021

Adverse effects of electronic cigarettes on the disease-naive oral microbiome.

Sci Adv 2020 May 27;6(22):eaaz0108. Epub 2020 May 27.

Division of Periodontology, The Ohio State University, Columbus, OH, USA.

Six percent of Americans, including 3 million high schoolers, use e-cigarettes, which contain potentially toxic substances, volatile organic compounds, and metals. We present the first human study on the effects of e-cigarette exposure in the oral cavity. By interrogating both immunoinflammatory responses and microbial functional dynamics, we discovered pathogen overrepresentation, higher virulence signatures, and a brisk proinflammatory signal in clinically healthy e-cigarette users, equivalent to patients with severe periodontitis. Using RNA sequencing and confocal and electron microscopy to validate these findings, we demonstrate that the carbon-rich glycol/glycerol vehicle is an important catalyst in transforming biofilm architecture within 24 hours of exposure. Last, a machine-learning classifier trained on the metagenomic signatures of e-cigarettes identified as e-cigarette users both those individuals who used e-cigarettes to quit smoking, and those who use both e-cigarettes and cigarettes. The present study questions the safety of e-cigarettes and the harm reduction narrative promoted by advertising campaigns.
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http://dx.doi.org/10.1126/sciadv.aaz0108DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7253170PMC
May 2020

Characterizing oral microbial communities across dentition states and colonization niches.

Microbiome 2018 04 10;6(1):67. Epub 2018 Apr 10.

Division of Periodontology, College of Dentistry, The Ohio State University, 4111 Postle Hall, 305, W 12th Avenue, Columbus, OH, 43210, USA.

Methods: The present study aimed to identify patterns and processes in acquisition of oral bacteria and to characterize the microbiota of different dentition states and habitats. Mucosal, salivary, supragingival, and subgingival biofilm samples were collected from orally and systemically healthy children and mother-child dyads in predentate, primary, mixed, and permanent dentitions. 16S rRNA gene sequences were compared to the Human Oral Microbiome Database (HOMD). Functional potential was inferred using PICRUSt.

Results: Unweighted and weighted UniFrac distances were significantly smaller between each mother-predentate dyad than infant-unrelated female dyads. Predentate children shared a median of 85% of species-level operational taxonomic units (s-OTUs) and 100% of core s-OTUs with their mothers. Maternal smoking, but not gender, mode of delivery, feeding habits, or type of food discriminated between predentate microbial profiles. The primary dentition demonstrated expanded community membership, structure, and function when compared to the predentate stage, as well as significantly lower similarity between mother-child dyads. The primary dentition also included 85% of predentate core s-OTUs. Subsequent dentitions exhibited over 90% similarity to the primary dentition in phylogenetic and functional structure. Species from the predentate mucosa as well as new microbial assemblages were identified in the primary supragingival and subgingival microbiomes. All individuals shared 65% of species between supragingival and subgingival habitats; however, the salivary microbiome exhibited less than 35% similarity to either habitat.

Conclusions: Within the limitations of a cross-sectional study design, we identified two definitive stages in oral bacterial colonization: an early predentate imprinting and a second wave with the eruption of primary teeth. Bacterial acquisition in the oral microbiome is influenced by the maternal microbiome. Personalization begins with the eruption of primary teeth; however, this is limited to phylogeny; functionally, individuals exhibit few differences, suggesting that microbial assembly may follow a defined schematic that is driven by the functional requirements of the ecosystem. This early microbiome forms the foundation upon which newer communities develop as more colonization niches emerge, and expansion of biodiversity is attributable to both introduction of new species and increase in abundance of predentate organisms.
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http://dx.doi.org/10.1186/s40168-018-0443-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5891995PMC
April 2018

Site-level risk predictors of peri-implantitis: A retrospective analysis.

J Clin Periodontol 2018 05 15;45(5):597-604. Epub 2018 Apr 15.

Division of Periodontology, College of Dentistry, The Ohio State University, Columbus, OH, USA.

Aim: The goal of the present investigation was to identify site-level factors that might allow prognostication of individual implants in partially dentate patients with multiple non-splinted restorations.

Methods: We analysed clinical and radiographic characteristics of 222 non-splinted single implants in function for at least 5 years in 86 partially dentate individuals at the time of functional loading and at follow-up, with the outcome variable being peri-implantitis. Principal component analysis identified factors contributing to greatest variability and linear discriminant analysis coupled with Random Forest Classifier used to identify risk predictors.

Results: After controlling for patient-level factors, the following characteristics were associated with significantly increased risk for peri-implantitis: Periodontal disease on adjoining teeth at the time of restoration (Odds Ratio (OR): 8.0), implant placement at a depth of 6 mm or more in relation to the CEJ of adjacent tooth (OR: 8.5), asymmetric prosthesis (OR: 4.3), history of tooth loss due to periodontitis (OR: 2.4) and a mean baseline plaque index of 1.6 or more (OR: 7.9).

Conclusions: Our findings suggest that a system that incorporates both subject level and implant-level factors is required to effectively prognosticate the success of individual implants.
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http://dx.doi.org/10.1111/jcpe.12892DOI Listing
May 2018

The making of a miscreant: tobacco smoke and the creation of pathogen-rich biofilms.

NPJ Biofilms Microbiomes 2017 24;3:26. Epub 2017 Oct 24.

Division of Periodontology, College of Dentistry, The Ohio State University, 4111 Postle Hall. 305, W 12th Avenue, Columbus, OH 43210 USA.

We have previously reported that oral biofilms in clinically healthy smokers are pathogen-rich, and that this enrichment occurs within 24 h of biofilm formation. The present investigation aimed to identify a mechanism by which smoking creates this altered community structure. By combining in vitro microbial-mucosal interface models of commensal (consisting of and and pathogen-rich (comprising and , and communities with metatranscriptomics, targeted proteomics and fluorescent microscopy, we demonstrate that smoke exposure significantly downregulates essential metabolic functions within commensal biofilms, while significantly increasing expression of virulence genes, notably lipopolysaccharide (LPS), flagella and capsule synthesis. By contrast, in pathogen-rich biofilms several metabolic pathways were over-expressed in response to smoke exposure. Under smoke-rich conditions, epithelial cells mounted an early and amplified pro-inflammatory and oxidative stress response to these virulence-enhanced commensal biofilms, and a muted early response to pathogen-rich biofilms. Commensal biofilms also demonstrated early and widespread cell death. Similar results were observed when smoke-free epithelial cells were challenged with smoke-conditioned biofilms, but not vice versa. In conclusion, our data suggest that smoke-induced transcriptional shifts in commensal biofilms triggers a florid pro-inflammatory response, leading to early commensal death, which may preclude niche saturation by these beneficial organisms. The cytokine-rich, pro-oxidant, anaerobic environment sustains inflammophilic bacteria, and, in the absence of commensal antagonism, may promote the creation of pathogen-rich biofilms in smokers.
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http://dx.doi.org/10.1038/s41522-017-0033-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5655325PMC
October 2017

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

ISME J 2017 09 23;11(9):2075-2089. Epub 2017 May 23.

Division of Periodontology, College of Dentistry, The Ohio State University, Coloumbus, OH, USA.

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.
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http://dx.doi.org/10.1038/ismej.2017.73DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5563960PMC
September 2017

Furcation Therapy With Enamel Matrix Derivative: Effects on the Subgingival Microbiome.

J Periodontol 2017 07 17;88(7):617-625. Epub 2017 Mar 17.

Division of Periodontology, College of Dentistry, The Ohio State University, Columbus, OH.

Background: Although enamel matrix derivative (EMD) has been used to promote periodontal regeneration, little is known of its effect on the microbiome. Therefore, this investigation aims to identify changes in periodontal microbiome after treatment with EMD using a deep-sequencing approach.

Methods: Thirty-nine patients with mandibular Class II buccal furcation defects were randomized to beta-tricalcium-phosphate/hydroxyapatite graft (BONE group), EMD+BONE, or EMD alone. Plaque was collected from furcation defects at baseline and 3 and 6 months post-treatment. Bacterial DNA was analyzed using terminal restriction fragment length polymorphism and 16S pyrotag sequencing, resulting in 169,000 classifiable sequences being compared with the Human Oral Microbiome Database. Statistical comparisons were made using parametric tests.

Results: At baseline, a total of 422 species were identified from the 39 defects, belonging to Fusobacterium, Pseudomonas, Streptococcus, Filifactor, and Parvimonas. All three regenerative procedures predictably altered the disease-associated microbiome, with a restitution of health-compatible species. However, EMD and BONE+EMD groups demonstrated more long-term reductions in a higher number of species than the BONE group (P <0.05), especially disease-associated species, e.g., Selenomonas noxia, F. alocis, and Fusobacterium.

Conclusions: EMD treatment predictably alters a dysbiotic subgingival microbiome, decreasing pathogen richness and increasing commensal abundance. Further investigations are needed to investigate how this impacts regenerative outcomes.
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http://dx.doi.org/10.1902/jop.2017.160542DOI Listing
July 2017

Comparative metagenomics reveals taxonomically idiosyncratic yet functionally congruent communities in periodontitis.

Sci Rep 2016 12 19;6:38993. Epub 2016 Dec 19.

Division of Periodontology, College of Dentistry, The Ohio State University, Columbus, Ohio, USA.

The phylogenetic characteristics of microbial communities associated with periodontitis have been well studied, however, little is known about the functional endowments of this ecosystem. The present study examined 73 microbial assemblages from 25 individuals with generalized chronic periodontitis and 25 periodontally healthy individuals using whole genome shotgun sequencing. Core metabolic networks were computed from taxa and genes identified in at least 80% of individuals in each group. 50% of genes and species identified in health formed part of the core microbiome, while the disease-associated core microbiome contained 33% of genes and only 1% of taxa. Clinically healthy sites in individuals with periodontitis were more aligned with sites with disease than with health. 68% of the health-associated metagenome was dedicated to energy utilization through oxidative pathways, while in disease; fermentation and methanogenesis were predominant energy transfer mechanisms. Expanded functionality was observed in periodontitis, with unique- or over-representation of genes encoding for fermentation, antibiotic resistance, detoxification stress, adhesion, invasion and intracellular resistance, proteolysis, quorum sensing, Type III/IV secretion systems, phages and toxins in the disease-associated core microbiome. However, different species or consortia contributed to these functions in each individual. Several genes, but not species, demonstrated robust discriminating power between health and disease.
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http://dx.doi.org/10.1038/srep38993DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5172196PMC
December 2016

PhyloToAST: Bioinformatics tools for species-level analysis and visualization of complex microbial datasets.

Sci Rep 2016 06 30;6:29123. Epub 2016 Jun 30.

Division of Periodontology, College of Dentistry, The Ohio State University, Columbus, Ohio, USA.

The 16S rRNA gene is widely used for taxonomic profiling of microbial ecosystems; and recent advances in sequencing chemistry have allowed extremely large numbers of sequences to be generated from minimal amounts of biological samples. Analysis speed and resolution of data to species-level taxa are two important factors in large-scale explorations of complex microbiomes using 16S sequencing. We present here new software, Phylogenetic Tools for Analysis of Species-level Taxa (PhyloToAST), that completely integrates with the QIIME pipeline to improve analysis speed, reduce primer bias (requiring two sequencing primers), enhance species-level analysis, and add new visualization tools. The code is free and open source, and can be accessed at http://phylotoast.org.
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http://dx.doi.org/10.1038/srep29123DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4928119PMC
June 2016

MoFlow: visualizing conformational changes in molecules as molecular flow improves understanding.

BMC Proc 2015 13;9(Suppl 6 Proceedings of the 5th Symposium on Biological Data):S5. Epub 2015 Aug 13.

The Research Institute at Nationwide Children's Hospital, Columbus, OH, USA.

Background: Current visualizations of molecular motion use a Timeline-analogous representation that conveys "first the molecule was shaped like this, then like this...". This scheme is orthogonal to the Pathline-like human understanding of motion "this part of the molecule moved from here to here along this path". We present MoFlow, a system for visualizing molecular motion using a Pathline-analogous representation.

Results: The MoFlow system produces high-quality renderings of molecular motion as atom pathlines, as well as interactive WebGL visualizations, and 3D printable models. In a preliminary user study, MoFlow representations are shown to be superior to canonical representations for conveying molecular motion.

Conclusions: Pathline-based representations of molecular motion are more easily understood than timeline representations. Pathline representations provide other advantages because they represent motion directly, rather than representing structure with inferred motion.
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http://dx.doi.org/10.1186/1753-6561-9-S6-S5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4547179PMC
September 2015

The subgingival microbiome of clinically healthy current and never smokers.

ISME J 2015 Jan 11;9(1):268-72. Epub 2014 Jul 11.

Division of Periodontology, College of Dentistry, The Ohio State University, Columbus, OH, USA.

Dysbiotic oral bacterial communities have a critical role in the etiology and progression of periodontal diseases. The goal of this study was to investigate the extent to which smoking increases risk for disease by influencing the composition of the subgingival microbiome in states of clinical health. Subgingival plaque samples were collected from 200 systemically and periodontally healthy smokers and nonsmokers. 16S pyrotag sequencing was preformed generating 1,623,713 classifiable sequences, which were compared with a curated version of the Greengenes database using the quantitative insights into microbial ecology pipeline. The subgingival microbial profiles of smokers and never-smokers were different at all taxonomic levels, and principal coordinate analysis revealed distinct clustering of the microbial communities based on smoking status. Smokers demonstrated a highly diverse, pathogen-rich, commensal-poor, anaerobic microbiome that is more closely aligned with a disease-associated community in clinically healthy individuals, suggesting that it creates an at-risk-for-harm environment that is primed for a future ecological catastrophe.
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http://dx.doi.org/10.1038/ismej.2014.114DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4274424PMC
January 2015

Aberrant community architecture and attenuated persistence of uropathogenic Escherichia coli in the absence of individual IHF subunits.

PLoS One 2012 25;7(10):e48349. Epub 2012 Oct 25.

Center for Microbial Pathogenesis, The Research Institute at Nationwide Children's Hospital, Columbus, Ohio, United States of America.

Uropathogenic Escherichia coli (UPEC) utilizes a complex community-based developmental pathway for growth within superficial epithelial cells of the bladder during cystitis. Extracellular DNA (eDNA) is a common matrix component of organized bacterial communities. Integration host factor (IHF) is a heterodimeric protein that binds to double-stranded DNA and produces a hairpin bend. IHF-dependent DNA architectural changes act both intrabacterially and extrabacterially to regulate gene expression and community stability, respectively. We demonstrate that both IHF subunits are required for efficient colonization of the bladder, but are dispensable for early colonization of the kidney. The community architecture of the intracellular bacterial communities (IBCs) is quantitatively different in the absence of either IhfA or IhfB in the murine model for human urinary tract infection (UTI). Restoration of Type 1 pili by ectopic production does not restore colonization in the absence of IhfA, but partially compensates in the absence of IhfB. Furthermore, we describe a binding site for IHF that is upstream of the operon that encodes for the P-pilus. Taken together, these data suggest that both IHF and its constituent subunits (independent of the heterodimer), are able to participate in multiple aspects of the UPEC pathogenic lifestyle, and may have utility as a target for treatment of bacterial cystitis.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0048349PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3485042PMC
May 2013

New paradigms of urinary tract infections: Implications for patient management.

Indian J Urol 2012 Apr;28(2):154-8

Center for Microbial Pathogenesis, The Research Institute at Nationwide Children's Hospital, Columbus, Ohio.

Urinary tract infections (UTIs) represent one of the most commonly acquired diseases among the general population as well as hospital in-patients, yet remain difficult to effectively and consistently treat. High rates of recurrence, anatomic abnormalities, and functional disturbances of the urinary tract all contribute to the difficulty in management of these infections. However, recent advances reveal important molecular and genetic factors that contribute to bacterial invasion and persistence in the urinary tract, particularly for the most common causative agent, uropathogenic Escherichia coli. Recent studies using animal models of experimental UTIs have recently provided mechanistic insight into the clinical observations that question the effectiveness of antibiotic therapy in treatment. Ultimately, continuing research will be necessary to identify the best targets for effective treatment of this costly and widespread infectious disease.
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http://dx.doi.org/10.4103/0970-1591.98455DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3424889PMC
April 2012

FIND: a new software tool and development platform for enhanced multicolor flow analysis.

BMC Bioinformatics 2011 May 10;12:145. Epub 2011 May 10.

Biophysics Program, The Ohio State University, Columbus, Ohio, USA.

Background: Flow Cytometry is a process by which cells, and other microscopic particles, can be identified, counted, and sorted mechanically through the use of hydrodynamic pressure and laser-activated fluorescence labeling. As immunostained cells pass individually through the flow chamber of the instrument, laser pulses cause fluorescence emissions that are recorded digitally for later analysis as multidimensional vectors. Current, widely adopted analysis software limits users to manual separation of events based on viewing two or three simultaneous dimensions. While this may be adequate for experiments using four or fewer colors, advances have lead to laser flow cytometers capable of recording 20 different colors simultaneously. In addition, mass-spectrometry based machines capable of recording at least 100 separate channels are being developed. Analysis of such high-dimensional data by visual exploration alone can be error-prone and susceptible to unnecessary bias. Fortunately, the field of Data Mining provides many tools for automated group classification of multi-dimensional data, and many algorithms have been adapted or created for flow cytometry. However, the majority of this research has not been made available to users through analysis software packages and, as such, are not in wide use.

Results: We have developed a new software application for analysis of multi-color flow cytometry data. The main goals of this effort were to provide a user-friendly tool for automated gating (classification) of multi-color data as well as a platform for development and dissemination of new analysis tools. With this software, users can easily load single or multiple data sets, perform automated event classification, and graphically compare results within and between experiments. We also make available a simple plugin system that enables researchers to implement and share their data analysis and classification/population discovery algorithms.

Conclusions: The FIND (Flow Investigation using N-Dimensions) platform presented here provides a powerful, user-friendly environment for analysis of Flow Cytometry data as well as providing a common platform for implementation and distribution of new automated analysis techniques to users around the world.
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http://dx.doi.org/10.1186/1471-2105-12-145DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3119067PMC
May 2011

A dynamically masked Gaussian can efficiently approximate a distance calculation for image segmentation.

Adv Exp Med Biol 2011 ;696:425-32

The Biophysics Program, The Ohio State University, Columbus, OH 43210, USA.

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http://dx.doi.org/10.1007/978-1-4419-7046-6_42DOI Listing
June 2011