Targeted deletion of Fgf9 in tendon disrupts mineralization of the developing enthesis.

The enthesis is a transitional tissue between tendon and bone that matures postnatally. The development and maturation of the enthesis involve cellular processes likened to an arrested growth plate. In this study, we explored the role of fibroblast growth factor 9 (Fgf9), a known regulator of chondrogenesis and vascularization during bone development, on the structure and function of the postnatal enthesis. First, we confirmed spatial expression of Fgf9 in the tendon and enthesis using in situ hybridization. We then used Cre-lox recombinase to conditionally knockout Fgf9 in mouse tendon and enthesis (Scx-Cre) and characterized enthesis morphology as well as mechanical properties in Fgf9ScxCre and wild-type (WT) entheses. Fgf9ScxCre mice had smaller calcaneal and humeral apophyses, thinner cortical bone at the attachment, increased cellularity, and reduced failure load in mature entheses compared to WT littermates. During postnatal development, we found reduced chondrocyte hypertrophy and disrupted type X collagen (Col X) in Fgf9ScxCre entheses. These findings support that tendon-derived Fgf9 is important for functional development of the enthesis, including its postnatal mineralization. Our findings suggest the potential role of FGF signaling during enthesis development.

Streptococcus gordonii Supragingival Bacterium Oral Infection-Induced Periodontitis and Robust miRNA Expression Kinetics.

Streptococcus gordonii (S. gordonii, Sg) is one of the early colonizing, supragingival commensal bacterium normally associated with oral health in human dental plaque. MicroRNAs (miRNAs) play an important role in the inflammation-mediated pathways and are involved in periodontal disease (PD) pathogenesis. PD is a polymicrobial dysbiotic immune-inflammatory disease initiated by microbes in the gingival sulcus/pockets. The objective of this study is to determine the global miRNA expression kinetics in S. gordonii DL1-infected C57BL/6J mice. All mice were randomly divided into four groups (n = 10 mice/group; 5 males and 5 females). Bacterial infection was performed in mice at 8 weeks and 16 weeks, mice were euthanized, and tissues harvested for analysis. We analyzed differentially expressed (DE) miRNAs in the mandibles of S. gordonii-infected mice. Gingival colonization/infection by S. gordonii and alveolar bone resorption (ABR) was confirmed. All the S. gordonii-infected mice at two specific time points showed bacterial colonization (100%) in the gingival surface, and a significant increase in mandible and maxilla ABR (p < 0.0001). miRNA profiling revealed 191 upregulated miRNAs (miR-375, miR-34b-5p) and 22 downregulated miRNAs (miR-133, miR-1224) in the mandibles of S. gordonii-infected mice at the 8-week mark. Conversely, at 16 weeks post-infection, 10 miRNAs (miR-1902, miR-203) were upregulated and 32 miRNAs (miR-1937c, miR-720) were downregulated. Two miRNAs, miR-210 and miR-423-5p, were commonly upregulated, and miR-2135 and miR-145 were commonly downregulated in both 8- and 16-week-infected mice mandibles. Furthermore, we employed five machine learning (ML) algorithms to assess how the number of miRNA copies correlates with S. gordonii infections in mice. In the ML analyses, miR-22 and miR-30c (8-week), miR-720 and miR-339-5p (16-week), and miR-720, miR-22, and miR-339-5p (combined 8- and 16-week) emerged as the most influential miRNAs.

Unique miRomics Expression Profiles in Tannerella forsythia-Infected Mandibles during Periodontitis Using Machine Learning.

T. forsythia is a subgingival periodontal bacterium constituting the subgingival pathogenic polymicrobial milieu during periodontitis (PD). miRNAs play a pivotal role in maintaining periodontal tissue homeostasis at the transcriptional, post-transcriptional, and epigenetic levels. The aim of this study was to characterize the global microRNAs (miRNA, miR) expression kinetics in 8- and 16-week-old T. forsythia-infected C57BL/6J mouse mandibles and to identify the miRNA bacterial biomarkers of disease process at specific time points. We examined the differential expression (DE) of miRNAs in mouse mandibles (n = 10) using high-throughput NanoString nCounter® miRNA expression panels, which provided significant advantages over specific candidate miRNA or pathway analyses. All the T. forsythia-infected mice at two specific time points showed bacterial colonization (100%) in the gingival surface, along with a significant increase in alveolar bone resorption (ABR) (p < 0.0001). We performed a NanoString analysis of specific miRNA signatures, miRNA target pathways, and gene network analysis. A total of 115 miRNAs were DE in the mandible tissue during 8 and 16 weeks The T. forsythia infection, compared with sham infection, and the majority (99) of DE miRNAs were downregulated. nCounter miRNA expression kinetics identified 67 downregulated miRNAs (e.g., miR-375, miR-200c, miR-200b, miR-34b-5p, miR-141) during an 8-week infection, whereas 16 upregulated miRNAs (e.g., miR-1902, miR-let-7c, miR-146a) and 32 downregulated miRNAs (e.g., miR-2135, miR-720, miR-376c) were identified during a 16-week infection. Two miRNAs, miR-375 and miR-200c, were highly downregulated with >twofold change during an 8-week infection. Six miRNAs in the 8-week infection (miR-200b, miR-141, miR-205, miR-423-3p, miR-141-3p, miR-34a-5p) and two miRNAs in the 16-week infection (miR-27a-3p, miR-15a-5p) that were downregulated have also been reported in the gingival tissue and saliva of periodontitis patients. This preclinical in vivo study identified T. forsythia-specific miRNAs (miR-let-7c, miR-210, miR-146a, miR-423-5p, miR-24, miR-218, miR-26b, miR-23a-3p) and these miRs have also been reported in the gingival tissues and saliva of periodontitis patients. Further, several DE miRNAs that are significantly upregulated (e.g., miR-101b, miR-218, miR-127, miR-24) are also associated with many systemic diseases such as atherosclerosis, Alzheimer's disease, rheumatoid arthritis, osteoarthritis, diabetes, obesity, and several cancers. In addition to DE analysis, we utilized the XGBoost (eXtreme Gradient boost) and Random Forest machine learning (ML) algorithms to assess the impact that the number of miRNA copies has on predicting whether a mouse is infected. XGBoost found that miR-339-5p was most predictive for mice infection at 16 weeks. miR-592-5p was most predictive for mice infection at 8 weeks and also when the 8-week and 16-week results were grouped together. Random Forest predicted miR-592 as most predictive at 8 weeks as well as the combined 8-week and 16-week results, but miR-423-5p was most predictive at 16 weeks. In conclusion, the expression levels of miR-375 and miR-200c family differed significantly during disease process, and these miRNAs establishes a link between T. forsythia and development of periodontitis genesis, offering new insights regarding the pathobiology of this bacterium.

Modeling Transport Regulation in Gene Regulatory Networks.

A gene regulatory network summarizes the interactions between a set of genes and regulatory gene products. These interactions include transcriptional regulation, protein activity regulation, and regulation of the transport of proteins between cellular compartments. DSGRN is a network modeling approach that builds on traditions of discrete-time Boolean models and continuous-time switching system models. When all interactions are transcriptional, DSGRN uses a combinatorial approximation to describe the entire range of dynamics that is compatible with network structure. Here we present an extension of the DGSRN approach to transport regulation across a boundary between compartments, such as a cellular membrane. We illustrate our approach by searching a model of the p53-Mdm2 network for the potential to admit two experimentally observed distinct stable periodic cycles.

An In Vivo Definition of Brain Histamine Dynamics Reveals Critical Neuromodulatory Roles for This Elusive Messenger.

Histamine is well known for mediating peripheral inflammation; however, this amine is also found in high concentrations in the brain where its roles are much less known. In vivo chemical dynamics are difficult to measure, thus fundamental aspects of histamine's neurochemistry remain undefined. In this work, we undertake the first in-depth characterization of real time in vivo histamine dynamics using fast electrochemical tools. We find that histamine release is sensitive to pharmacological manipulation at the level of synthesis, packaging, autoreceptors and metabolism. We find two breakthrough aspects of histamine modulation. First, differences in H3 receptor regulation between sexes show that histamine release in female mice is much more tightly regulated than in male mice under H3 or inflammatory drug challenge. We hypothesize that this finding may contribute to hormone-mediated neuroprotection mechanisms in female mice. Second, a high dose of a commonly available antihistamine, the H1 receptor inverse agonist diphenhydramine, rapidly decreases serotonin levels. This finding highlights the sheer significance of pharmaceuticals on neuromodulation. Our study opens the path to better understanding and treating histamine related disorders of the brain (such as neuroinflammation), emphasizing that sex and modulation (of serotonin) are critical factors to consider when studying/designing new histamine targeting therapeutics.

Autoreceptor control of serotonin dynamics.

BACKGROUND: Serotonin is a neurotransmitter that has been linked to a wide variety of behaviors including feeding and body-weight regulation, social hierarchies, aggression and suicidality, obsessive compulsive disorder, alcoholism, anxiety, and affective disorders. Full understanding involves genomics, neurochemistry, electrophysiology, and behavior. The scientific issues are daunting but important for human health because of the use of selective serotonin reuptake inhibitors and other pharmacological agents to treat disorders. This paper presents a new deterministic model of serotonin metabolism and a new systems population model that takes into account the large variation in enzyme and transporter expression levels, tryptophan input, and autoreceptor function. RESULTS: We discuss the steady state of the model and the steady state distribution of extracellular serotonin under different hypotheses on the autoreceptors and we show the effect of tryptophan input on the steady state and the effect of meals. We use the deterministic model to interpret experimental data on the responses in the hippocampus of male and female mice, and to illustrate the short-time dynamics of the autoreceptors. We show there are likely two reuptake mechanisms for serotonin and that the autoreceptors have long-lasting influence and compare our results to measurements of serotonin dynamics in the substantia nigra pars reticulata. We also show how histamine affects serotonin dynamics. We examine experimental data that show very variable response curves in populations of mice and ask how much variation in parameters in the model is necessary to produce the observed variation in the data. Finally, we show how the systems population model can potentially be used to investigate specific biological and clinical questions. CONCLUSIONS: We have shown that our new models can be used to investigate the effects of tryptophan input and meals and the behavior of experimental response curves in different brain nuclei. The systems population model incorporates individual variation and can be used to investigate clinical questions and the variation in drug efficacy. The codes for both the deterministic model and the systems population model are available from the authors and can be used by other researchers to investigate the serotonergic system.

An ontology for representing hematologic malignancies: the cancer cell ontology.

BACKGROUND: Within the cancer domain, ontologies play an important role in the integration and annotation of data in order to support numerous biomedical tools and applications. This work seeks to leverage existing standards in immunophenotyping cell types found in hematologic malignancies to provide an ontological representation of them to aid in data annotation and analysis for patient data. RESULTS: We have developed the Cancer Cell Ontology according to OBO Foundry principles as an extension of the Cell Ontology. We define classes in Cancer Cell Ontology by using a genus-differentia approach using logical axioms capturing the expression of cellular surface markers in order to represent types of hematologic malignancies. By adopting conventions used in the Cell Ontology, we have created human and computer-readable definitions for 300 classes of blood cancers, based on the EGIL classification system for leukemias, and relying upon additional classification approaches for multiple myelomas and other hematologic malignancies. CONCLUSION: We have demonstrated a proof of concept for leveraging the built-in logical axioms of the ontology in order to classify patient surface marker data into appropriate diagnostic categories. We plan to integrate our ontology into existing tools for flow cytometry data analysis to facilitate the automated diagnosis of hematologic malignancies.

OSCI: standardized stem cell ontology representation and use cases for stem cell investigation.

BACKGROUND: Stem cells and stem cell lines are widely used in biomedical research. The Cell Ontology (CL) and Cell Line Ontology (CLO) are two community-based OBO Foundry ontologies in the domains of in vivo cells and in vitro cell line cells, respectively. RESULTS: To support standardized stem cell investigations, we have developed an Ontology for Stem Cell Investigations (OSCI). OSCI imports stem cell and cell line terms from CL and CLO, and investigation-related terms from existing ontologies. A novel focus of OSCI is its application in representing metadata types associated with various stem cell investigations. We also applied OSCI to systematically categorize experimental variables in an induced pluripotent stem cell line cell study related to bipolar disorder. In addition, we used a semi-automated literature mining approach to identify over 200 stem cell gene markers. The relations between these genes and stem cells are modeled and represented in OSCI. CONCLUSIONS: OSCI standardizes stem cells found in vivo and in vitro and in various stem cell investigation processes and entities. The presented use cases demonstrate the utility of OSCI in iPSC studies and literature mining related to bipolar disorder.

Quantitative genetic analyses of postcanine morphological crown variation.

OBJECTIVES: This article presents estimates of narrow-sense heritability and bivariate genetic correlation for 14 tooth crown morphological variants scored on permanent premolars, first molars, and second molars. The objective is to inform data collection and analytical practices in dental biodistance and to provide insights on the development of molar crowns as integrated structures. MATERIALS AND METHODS: African American dental casts from the Menegaz-Bock collection were recorded for the Arizona State University Dental Anthropology System. Estimates of narrow-sense heritability and genetic correlation were generated using SOLAR v.8.1.1, which included assessment of age, sex, and birth year as covariates. Both continuous scale and dichotomized estimates are provided. RESULTS: Heritability estimates were nonsignificant for the majority of variables; however, for variables yielding significant estimates, values were moderate to high in magnitude and comparable to previous studies. Comparing left and right-side heritability estimates suggests directional asymmetry in the expression of environmental variance, something not seen in anterior tooth traits. Genetic correlations were moderate among antimeres and metameres and low for different traits scored on the same tooth crown. Although several negative correlations were noted, few reached statistical significance. Results affirm some of the current data cleaning and analytical practices in dental biodistance, but others are called into question. These include the pooling of males and females and combining left and right-side data into a single dataset. CONCLUSIONS: In comparison to anterior tooth crown traits, postcanine heritabilities were more often non-significant; however, those traits with significant heritability also tended to produce higher estimates. Genetic correlations were unremarkable, in part, because they were underpowered. However, M1 results may provide insight into the complex relationship between genes, environment, and development in determining ultimate crown form.

Protein Ontology (PRO): enhancing and scaling up the representation of protein entities.

The Protein Ontology (PRO; http://purl.obolibrary.org/obo/pr) formally defines and describes taxon-specific and taxon-neutral protein-related entities in three major areas: proteins related by evolution; proteins produced from a given gene; and protein-containing complexes. PRO thus serves as a tool for referencing protein entities at any level of specificity. To enhance this ability, and to facilitate the comparison of such entities described in different resources, we developed a standardized representation of proteoforms using UniProtKB as a sequence reference and PSI-MOD as a post-translational modification reference. We illustrate its use in facilitating an alignment between PRO and Reactome protein entities. We also address issues of scalability, describing our first steps into the use of text mining to identify protein-related entities, the large-scale import of proteoform information from expert curated resources, and our ability to dynamically generate PRO terms. Web views for individual terms are now more informative about closely-related terms, including for example an interactive multiple sequence alignment. Finally, we describe recent improvement in semantic utility, with PRO now represented in OWL and as a SPARQL endpoint. These developments will further support the anticipated growth of PRO and facilitate discoverability of and allow aggregation of data relating to protein entities.

Heritability and genetic integration of anterior tooth crown variants in the South Carolina Gullah.

OBJECTIVES: This article presents estimates of narrow-sense heritability and bivariate genetic correlation for a series of morphological crown variants of the anterior dentition. These results provide insight into the value of dental phenotypes as evolutionary proxies, as well as the development of tooth crowns as integrated or modular structures. MATERIALS AND METHODS: African American dental casts from the Menegaz-Bock collection were scored for a standard set of dental morphological variables using the Arizona State Dental Anthropology System. Estimates of narrow-sense heritability and genetic correlations were generated using SOLAR v. 8.1.1, controlling for the covariates of age, sex, and birth year. Analyses were run using ordinal/continuous scale variables that were then dichotomized at various breakpoints, consistent with standard practices in dental anthropology. RESULTS: Heritability estimates were low to moderate for most traits, and lower in magnitude than those reported for odontometric data from the same study sample. Only winging, canine shoveling, and canine double shoveling returned narrow-sense heritabilities that did not differ significantly from zero. Genetic correlations were high among antimeres and metameres and low for different traits scored on the same tooth crown. These results affirm standard data cleaning practices in dental biodistance. Double shoveling was atypical in returning strong negative correlations with other traits, shoveling in particular. CONCLUSIONS: Additive genetic variation contributes to dental morphological variation, although the estimates are uniformly lower than those observed for odontometrics. Patterns of genetic correlation affirm most standard practices in dental biodistance. Patterns of negative pleiotropy involving lingual and labial crown features suggest a genetic architecture and developmental complex that differentially constrain morphological variation of distinct surfaces of the same tooth crown. These patterns warrant greater consideration and cross-population validation.

Visualizing Calcium Flux in Freely Moving Nematode Embryos.

The lack of physiological recordings from Caenorhabditis elegans embryos stands in stark contrast to the comprehensive anatomical and gene expression datasets already available. Using light-sheet fluorescence microscopy to address the challenges associated with functional imaging at this developmental stage, we recorded calcium dynamics in muscles and neurons and developed analysis strategies to relate activity and movement. In muscles, we found that the initiation of twitching was associated with a spreading calcium wave in a dorsal muscle bundle. Correlated activity in muscle bundles was linked with early twitching and eventual coordinated movement. To identify neuronal correlates of behavior, we monitored brainwide activity with subcellular resolution and identified a particularly active cell associated with muscle contractions. Finally, imaging neurons of a well-defined adult motor circuit, we found that reversals in the eggshell correlated with calcium transients in AVA interneurons.

Heritability and genetic integration of tooth size in the South Carolina Gullah.

OBJECTIVES: This article provides estimates of narrow-sense heritability and genetic pleiotropy for mesiodistal tooth dimensions for a sample of 20th century African American individuals. Results inform biological distance analysis and offer insights into patterns of integration in the human dentition. MATERIALS AND METHODS: Maximum mesiodistal crown dimensions were measured using Hillson-FitzGerald calipers on 469 stone dental casts from the Menegaz-Bock Collection. Narrow-sense heritability estimates and genetic and phenotypic correlations were estimated using SOLAR 8.1.1 with covariate screening for age, sex, age*sex interaction, and birth year. RESULTS: Heritability estimates were moderate (∼0.10 - 0.90; h2 mean = 0.51) for most measured variables with sex as the only significant covariate. Patterns of genetic correlation indicate strong integration across tooth classes, except molars. Comparison of these results to previously published work suggests lower overall heritability relative to other human populations and much stronger genetic integration across tooth classes than obtained from nonhuman primate genetic pleiotropy estimates. CONCLUSIONS: These results suggest that the high heritabilities previously published may reflect overestimates inherent in previous study designs; as such the standard estimate of 0.55 used in biodistance analyses may not be appropriate. For the Gullah, isolation and endogamy coupled with elevated levels of physiological and economic stress may suppress narrow-sense heritability estimates. Pleiotropy analyses suggest a more highly integrated dentition in humans than in other mammals.

Engaging bodies in the public imagination: bioarchaeology as social science, science, and humanities.

Bioarchaeology is the contextual analysis of biological remains from past societies. It is a young and growing discipline born during the latter half of the twentieth century from its roots in physical anthropology and archaeology. Although often associated with the study of ancient diet and disease, bioarchaeology leverages variable temporal scales and its global scope to provide a uniquely comparative perspective on human life that transcends traditional boundaries of the natural sciences, social sciences, and humanities. Here, we explore the public face of bioarchaeology and consider the trends in publication practices that reflect diversifying research strategies. Bioarchaeology is a popular topic on web-based science news aggregators. However, we identify a disconnect between bioarchaeology's traditional research emphases, emerging research foci, and findings that actually spark the public imagination. A majority of popular news articles emphasize basic discovery or "natural curiosities." Publication data indicate the field also remains regionally focused with relatively little emphasis on nomothetic goals. Nevertheless, bioarchaeology can do more to leverage its historical perspective and corporeal emphasis to engage a number of topics with importance across traditional academic boundaries. Big data, comparative, multi-investigator, interdisciplinary projects on violence, colonialism, and health offer the most obvious potential for driving research narratives in the biological and social sciences. Humanistic approaches that explore emotional connections to the past can also have merit. The diversity of research outlets and products indicates the field must embrace the importance of nontraditional activities in its value structure to maximize our potential in public arenas.

MRIO: the Magnetic Resonance Imaging Acquisition and Analysis Ontology.

Magnetic resonance imaging of the brain is a useful tool in both the clinic and research settings, aiding in the diagnosis and treatments of neurological disease and expanding our knowledge of the brain. However, there are many challenges inherent in managing and analyzing MRI data, due in large part to the heterogeneity of data acquisition. To address this, we have developed MRIO, the Magnetic Resonance Imaging Acquisition and Analysis Ontology. MRIO provides well-reasoned classes and logical axioms for the acquisition of several MRI acquisition types and well-known, peer-reviewed analysis software, facilitating the use of MRI data. These classes provide a common language for the neuroimaging research process and help standardize the organization and analysis of MRI data for reproducible datasets. We also provide queries for automated assignment of analyses for given MRI types. MRIO aids researchers in managing neuroimaging studies by helping organize and annotate MRI data and integrating with existing standards such as Digital Imaging and Communications in Medicine and the Brain Imaging Data Structure, enhancing reproducibility and interoperability. MRIO was constructed according to Open Biomedical Ontologies Foundry principles and has contributed several classes to the Ontology for Biomedical Investigations to help bridge neuroimaging data to other domains. MRIO addresses the need for a "common language" for MRI that can help manage the neuroimaging research, by enabling researchers to identify appropriate analyses for sets of scans and facilitating data organization and reporting.

Survival analysis of posterior composite restorations in National Dental PBRN general dentistry practices.

OBJECTIVE: Quantify the survival of posterior composite restorations (PCR) placed during the study period in permanent teeth in United States (US) general dental community practices and factors predictive of that survival. METHODS: A retrospective cohort study was conducted utilizing de-identified electronic dental record (EDR) data of patients who received a PCR in 99 general dentistry practices in the National Dental Practice-Based Research Network (Network). The final analyzed data set included 700,885 PCRs from 200,988 patients. Descriptive statistics and Kaplan Meier (product limit) estimator were performed to estimate the survival rate (defined as the PCR not receiving any subsequent treatment) after the first PCR was observed in the EDR during the study time. The Cox proportional hazards model was done to account for patient- and tooth-specific covariates. RESULTS: The overall median survival time was 13.3 years. The annual failure rates were 4.5-5.8 % for years 1-5; 5.3-5.7 %, 4.9-5.5 %, and 3.3-5.2 % for years 6-10, 11-15, and 16-20, respectively. The failure descriptions recorded for < 7 % failures were mostly caries (54 %) and broken or fractured tooth/restorations (23 %). The following variables significantly predicted PCR survival: number of surfaces that comprised the PCR; having at least one interproximal surface; tooth type; type of prior treatment received on the tooth; Network region; patient age and sex. Based on the magnitude of the multivariable estimates, no single factor predominated. CONCLUSIONS: This study of Network practices geographically distributed across the US observed PCR survival rates and predictive factors comparable to studies done in academic settings and outside the US. CLINICAL SIGNIFICANCE: Specific baseline factors significantly predict the survival of PCRs done in US community dental practices.

Ontology-based modeling, integration, and analysis of heterogeneous clinical, pathological, and molecular kidney data for precision medicine.

Many data resources generate, process, store, or provide kidney related molecular, pathological, and clinical data. Reference ontologies offer an opportunity to support knowledge and data integration. The Kidney Precision Medicine Project (KPMP) team contributed to the representation and addition of 329 kidney phenotype terms to the Human Phenotype Ontology (HPO), and identified many subcategories of acute kidney injury (AKI) or chronic kidney disease (CKD). The Kidney Tissue Atlas Ontology (KTAO) imports and integrates kidney-related terms from existing ontologies (e.g., HPO, CL, and Uberon) and represents 259 kidney-related biomarkers. We also developed a precision medicine metadata ontology (PMMO) to integrate 50 variables from KPMP and CZ CellxGene data resources and applied PMMO for integrative kidney data analysis. The gene expression profiles of kidney gene biomarkers were specifically analyzed under healthy control or AKI/CKD disease statuses. This work demonstrates how ontology-based approaches support multi-domain data and knowledge integration in precision medicine.

Using a decline in serum hCG between days 0-4 to predict ectopic pregnancy treatment success after single-dose methotrexate: a retrospective cohort study.

BACKGROUND: The current measure of treatment efficacy of single-dose methotrexate for ectopic pregnancy, is a fall in serum hCG of ≥15% between days 4-7 of treatment, which has a positive predictive value of 93% for treatment success. Two small studies have proposed a fall in serum hCG between days 0-4 after treatment confers similar, earlier prognostic information, with positive predictive values of 100% and 88% for treatment success. We sought to validate this in a large, independent cohort because of the potentially significant clinical implications. METHODS: We conducted a retrospective study of women (n=206) treated with single-dose methotrexate for ectopic pregnancy (pre-treatment serum hCG levels ≤3000 IU/L) at Scottish hospitals between 2006-2011. Women were divided into two cohorts based on whether their serum hCG levels rose or fell between days 0-4 after methotrexate. Treatment outcomes of women in each cohort were compared, and the test performance characteristics calculated. This methodology was repeated for the current measure (≥15% fall in serum hCG between days 4-7 of treatment) and an alternate early measure (<20% fall in serum hCG between days 0-4 of treatment), and all three measures were compared for their ability to predict medical treatment success. RESULTS: In our cohort, the positive predictive value of the current clinical measure was 89% (95% CI 84-94%) (121/136). A falling serum hCG between days 0-4 predicted treatment success in 85% (95% CI 79-92%) of cases (94/110) and a <20% fall in serum hCG between days 0-4 predicted treatment success in 94% (95% CI 88-100%) of cases (59/63). There was no significant difference in the ability of these tests to predict medical treatment success. CONCLUSIONS: We have verified that a decline in serum hCG between days 0-4 after methotrexate treatment for ectopic pregnancies, with pre-treatment serum hCG levels ≤3000 IU/L, provides an early indication of likelihood of treatment success, and performs just as well as the existing measure, which only provides prognostic information on day 7.

Assessing biological network dynamics: comparing numerical simulations with analytical decomposition of parameter space.

Mathematical modeling of the emergent dynamics of gene regulatory networks (GRN) faces a double challenge of (a) dependence of model dynamics on parameters, and (b) lack of reliable experimentally determined parameters. In this paper we compare two complementary approaches for describing GRN dynamics across unknown parameters: (1) parameter sampling and resulting ensemble statistics used by RACIPE (RAndom CIrcuit PErturbation), and (2) use of rigorous analysis of combinatorial approximation of the ODE models by DSGRN (Dynamic Signatures Generated by Regulatory Networks). We find a very good agreement between RACIPE simulation and DSGRN predictions for four different 2- and 3-node networks typically observed in cellular decision making. This observation is remarkable since the DSGRN approach assumes that the Hill coefficients of the models are very high while RACIPE assumes the values in the range 1-6. Thus DSGRN parameter domains, explicitly defined by inequalities between systems parameters, are highly predictive of ODE model dynamics within a biologically reasonable range of parameters.

MRIO: The Magnetic Resonance Imaging Acquisition and Analysis Ontology.

Objective: Magnetic resonance imaging of the brain is a useful tool in both the clinic and research settings, aiding in the diagnosis and treatments of neurological disease and expanding our knowledge of the brain. However, there are many challenges inherent in managing and analyzing MRI data, due in large part to the heterogeneity of data acquisition. Materials and Methods: To address this, we have developed MRIO, the Magnetic Resonance Imaging Acquisition and Analysis Ontology. Results: MRIO provides well-reasoned classes and logical axioms for the acquisition of several MRI acquisition types and well-known, peer-reviewed analysis software, facilitating the use of MRI data. These classes provide a common language for the neuroimaging research process and help standardize the organization and analysis of MRI data for reproducible datasets. We also provide queries for automated assignment of analyses for given MRI types. Discussion: MRIO aids researchers in managing neuroimaging studies by helping organize and annotate MRI data and integrating with existing standards such as Digital Imaging and Communications in Medicine and the Brain Imaging Data Structure, enhancing reproducibility and interoperability. MRIO was constructed according to Open Biomedical Ontologies Foundry principals and has contributed several terms to the Ontology for Biomedical Investigations to help bridge neuroimaging data to other domains. Conclusion: MRIO addresses the need for a "common language" for MRI that can help manage the neuroimaging research, by enabling researchers to identify appropriate analyses for sets of scans and facilitating data organization and reporting.