Phenotypic characterization and ERIC-PCR based genotyping of Paenibacillus larvae isolates recovered from American foulbrood outbreaks in honey bees from Italy

BACKGROUND

Paenibacillus larvae is the etiological agent of American foulbrood (AFB), a widespread and severe bacterial brood disease of honey bees. The genomic characterization of P. larvae strains by enterobacterial repetitive intergenic consensus-polymerase chain reaction (ERIC-PCR) is able to differentiate four genotypes (ERIC I, ERIC II, ERIC III, ERIC IV). The information on the presence of P. larvae ERIC genotypes worldwide is few.

OBJECTIVES

We have characterized P. larvae strains isolated in Italy from AFB outbreaks to obtain information on ERIC genotypes and phenotypes of the strains circulating in the country.

METHODS

A total of 117 P. larvae isolates from 115 AFB outbreaks occurring in 2008-2012 were subjected to phenotypic and genetic characterization.

RESULTS

The genomic characterization allowed the identification of ERIC I and ERIC II genotypes. Examining the data of Northern and Central Italy separately it was noted that in Northern Italy most outbreaks were caused by the ERIC I genotype (78.6%), followed by the ERIC II genotype (18.6%) and by co-infections (ERIC I + ERIC II) (2.6%). In Central Italy, only outbreaks caused by the ERIC I genotype were observed. With regard to phenotypic characteristics all examined strains of ERIC II genotype fermented fructose while no strains of ERIC I genotype possessed this ability.

CONCLUSION

Both P. larvae ERIC I and ERIC II genotypes were isolated from the AFB outbreaks, but ERIC II genotype was isolated only in Northern Italy. The fermentation of fructose seems to be a genotype-specific biochemical marker.

Composition of lymphocyte subpopulations in normal canine lymph nodes

BACKGROUND

Flow cytometric immunophenotyping of lymph node aspirates has become a standard practice of canine lymphoma diagnostic workup. Ultimately, the combination of flow cytometry data, histopathology, and clinical signs allows consensus classification, and improves prognostic accuracy and therapeutic approaches.

OBJECTIVES

Although there is a growing body of information regarding lymphocyte population subsets in various types of lymphoma, only few studies provide information regarding the composition of the normal canine lymph node. The aim of this prospective study was to establish exploratory reference data for lymphocyte subpopulations in normal canine lymph nodes using an extended panel of antibodies.

METHODS

Popliteal lymph nodes excised from normal dogs were analyzed by cytology, multi-color flow cytometry using 11 different canine-specific and anti-human cross-reactive monoclonal antibodies, and polymerase chain reaction for antigen receptor rearrangement (PARR).

RESULTS

Subpopulations from lymph nodes of 26 dogs were classified according to the following positive antibody reactions: CD11a(+) 92.2 ± 12.3%, CD3(+) 55.0 ± 14.1%, CD3-12(+) 57.3 ± 14%, CD5(+) 52.3 ± 12.7%, CD21(+) 33.9 ± 11.8%, CD79αcγ(+) 46.9 ± 14.8%, CD56(+) 4.9 ± 5.9%, and CD14(+) 5.5 ± 6.8%. There were 58.7 ± 9% CD4(+) and 21.3 ± 7.8% CD8(+) cells inside the gate of CD3(+) cells. Cytology revealed a mixed population of mostly lymphoid cells in all samples. The absence of a monoclonal or oligoclonal neoplastic population was confirmed by PARR.

CONCLUSION

This study establishes for the first time flow cytometry data of lymphocyte populations in a larger group of normal canine lymph nodes, including populations positive for some new antibodies against CD3-12, CD5, CD11a, CD56, and CD79αcy.

The National Institutes of Health undiagnosed diseases program

PURPOSE OF REVIEW

To review the approach to undiagnosed patients and results of the National Institutes of Health (NIH) undiagnosed diseases program (UDP), and discuss its benefits to patients, academic medical centers, and the greater scientific community.

RECENT FINDINGS

The NIH UDP provides comprehensive and collaborative evaluations for patients with objective findings of disease whose diagnoses have long eluded the medical community. Intensive review of patient records, careful phenotyping, and new genomic technologies have resulted in the diagnosis of new and extremely rare conditions, expanded the phenotypes of rare disorders, and determined that symptoms are caused by more than one disorder in a family.

SUMMARY

Many children and adults with complex phenotypes remain undiagnosed despite years of searching. The most common undiagnosed disorders involve a neurologic phenotype. Comprehensive phenotyping and genomic analysis utilizing nuclear families can provide a diagnosis in some cases and provide good 'lead' candidate genes for others. A UDP can be important for patients, academic medical centers, the scientific community, and society.

The roots of future rice harvests

Rice production faces the challenge to be enhanced by 50% by year 2030 to meet the growth of the population in rice-eating countries. Whereas yield of cereal crops tend to reach plateaus and a yield is likely to be deeply affected by climate instability and resource scarcity in the coming decades, building rice cultivars harboring root systems that can maintain performance by capturing water and nutrient resources unevenly distributed is a major breeding target. Taking advantage of gathering a community of rice root biologists in a Global Rice Science Partnership workshop held in Montpellier, France, we present here the recent progresses accomplished in this area and focal points where an international network of laboratories should direct their efforts.

Image-based phenotyping for non-destructive screening of different salinity tolerance traits in rice

BACKGROUND

Soil salinity is an abiotic stress wide spread in rice producing areas, limiting both plant growth and yield. The development of salt-tolerant rice requires efficient and high-throughput screening techniques to identify promising lines for salt affected areas. Advances made in image-based phenotyping techniques provide an opportunity to use non-destructive imaging to screen for salinity tolerance traits in a wide range of germplasm in a reliable, quantitative and efficient way. However, the application of image-based phenotyping in the development of salt-tolerant rice remains limited.

RESULTS

A non-destructive image-based phenotyping protocol to assess salinity tolerance traits of two rice cultivars (IR64 and Fatmawati) has been established in this study. The response of rice to different levels of salt stress was quantified over time based on total shoot area and senescent shoot area, calculated from visible red-green-blue (RGB) and fluorescence images. The response of rice to salt stress (50, 75 and 100 mM NaCl) could be clearly distinguished from the control as indicated by the reduced increase of shoot area. The salt concentrations used had only a small effect on the growth of rice during the initial phase of stress, the shoot Na(+) accumulation independent phase termed the 'osmotic stress' phase. However, after 20 d of treatment, the shoot area of salt stressed plants was reduced compared with non-stressed plants. This was accompanied by a significant increase in the concentration of Na(+) in the shoot. Variation in the senescent area of the cultivars IR64 and Fatmawati in response to a high concentration of Na(+) in the shoot indicates variation in tissue tolerance mechanisms between the cultivars.

CONCLUSIONS

Image analysis has the potential to be used for high-throughput screening procedures in the development of salt-tolerant rice. The ability of image analysis to discriminate between the different aspects of salt stress (shoot ion-independent stress and shoot ion dependent stress) makes it a useful tool for genetic and physiological studies to elucidate processes that contribute to salinity tolerance in rice. The technique has the potential for identifying the genetic basis of these mechanisms and assisting in pyramiding different tolerance mechanisms into breeding lines.

DPPIV (CD26) as a novel stem cell marker in Ph+ chronic myeloid leukaemia

The concept of leukaemic stem cells (LSCs) has been developed to explain the complex cellular hierarchy and biology of leukaemias and to screen for pivotal targets that can be employed to improve drug therapies through LSC eradication in these patients. Some of the newly discovered LSC markers seem to be expressed in a disease-specific manner and may thus serve as major research tools and diagnostic parameters. A useful LSC marker in chronic myeloid leukaemia (CML) appears to be CD26, also known as dipeptidylpeptidase IV. Expression of CD26 is largely restricted to CD34(+) /CD38(-) LSCs in BCR/ABL1(+) CML, but is not found on LSCs in other myeloid or lymphoid neoplasms, with the exception of lymphoid blast crisis of CML, BCR/ABL1p210 + acute lymphoblastic leukaemia, and a very few cases of acute myeloid leukaemia. Moreover, CD26 usually is not expressed on normal bone marrow (BM) stem cells. Functionally, CD26 is a cytokine-targeting surface enzyme that may facilitate the mobilization of LSCs from the BM niche. In this article, we review our current knowledge about the biology and function of CD26 on CML LSCs and discuss the diagnostic potential of this new LSC marker in clinical haematology.

Modeling fragile X syndrome in the Fmr1 knockout mouse

Fragile X Syndrome (FXS) is a commonly inherited form of intellectual disability and one of the leading genetic causes for autism spectrum disorder. Clinical symptoms of FXS can include impaired cognition, anxiety, hyperactivity, social phobia, and repetitive behaviors. FXS is caused by a CGG repeat mutation which expands a region on the X chromosome containing the FMR1 gene. In FXS, a full mutation (> 200 repeats) leads to hypermethylation of FMR1, an epigenetic mechanism that effectively silences FMR1 gene expression and reduces levels of the FMR1 gene product, fragile X mental retardation protein (FMRP). FMRP is an RNA-binding protein that is important for the regulation of protein expression. In an effort to further understand how loss of FMR1 and FMRP contribute to FXS symptomology, several FXS animal models have been created. The most well characterized rodent model is the Fmr1 knockout (KO) mouse, which lacks FMRP protein due to a disruption in its Fmr1 gene. Here, we review the behavioral phenotyping of the Fmr1 KO mouse to date, and discuss the clinical relevance of this mouse model to the human FXS condition. While much remains to be learned about FXS, the Fmr1 KO mouse is a valuable tool for understanding the repercussions of functional loss of FMRP and assessing the efficacy of pharmacological compounds in ameliorating the molecular and behavioral phenotypes relevant to FXS.

Breeding drought-tolerant maize hybrids for the US corn-belt: discovery to product

Germplasm, genetics, phenotyping, and selection, combined with a clear definition of product targets, are the foundation of successful hybrid maize breeding. Breeding maize hybrids with superior yield for the drought-prone regions of the US corn-belt involves integration of multiple drought-specific technologies together with all of the other technology components that comprise a successful maize hybrid breeding programme. Managed-environment technologies are used to enable scaling of precision phenotyping in appropriate drought environmental conditions to breeding programme level. Genomics and other molecular technologies are used to study trait genetic architecture. Genetic prediction methodology was used to breed for improved yield performance for drought-prone environments. This was enabled by combining precision phenotyping for drought performance with genetic understanding of the traits contributing to successful hybrids in the target drought-prone environments and the availability of molecular markers distributed across the maize genome. Advances in crop growth modelling methodology are being used to evaluate the integrated effects of multiple traits for their combined effects and evaluate drought hybrid product concepts and guide their development and evaluation. Results to date, lessons learned, and future opportunities for further improving the drought tolerance of maize for the US corn-belt are discussed.

Short-term potentiation in the control of pharyngeal muscles in obstructive apnea patients

STUDY OBJECTIVES

To determine if activation of the genioglossus (GG) muscle during obstructive apnea events involves short-term potentiation (STP) and is followed by sustained activation beyond the obstructive phase (after-discharge).

DESIGN

Physiological study.

SETTING

Sleep laboratory in a tertiary hospital.

PARTICIPANTS

Twenty-one patients with obstructive apnea.

INTERVENTIONS

Polysomnography on continuous positive airway pressure (CPAP) with measurement of genioglossus activity. Brief dial-downs of CPAP to induce obstructive events.

MEASUREMENTS AND RESULTS

Peak, phasic, and tonic genioglossus activities were measured breath-by-breath before, during, and following three-breath obstructions. Tonic but not phasic activity increased immediately following the first obstructed breath (4.9 ± 1.6 versus 3.6 ± 1.2 %GGMAX; P = 0.01) under conditions where stimuli to genioglossus activation were likely constant, strongly implicating STP in mediating recruitment of tonic activity. Both phasic and tonic activities declined slowly after relief of obstruction (after-discharge). Decay time constants were systematically shorter for phasic than for tonic activity (7.5 ± 3.8 versus 18.1 ± 8.4 sec; P < 0.001). Decay time-constant of peak activity correlated with tonic, but not phasic, recruitment. Cortical arousal near the end of obstruction resulted in a lower after-discharge (P < 0.01). Contribution of tonic activity to the increase in peak activity (6-65%Peak), as well as the decay constant (6-30 sec), varied considerably among patients.

CONCLUSIONS

Short-term potentiation contributes to recruitment of the genioglossus during obstructive episodes and results in sustained tonic activity beyond the obstructive phase, thereby potentially preventing recurrence of obstruction. Wide response differences among subjects suggest that this mechanism may contribute to severity of the disorder. The after-discharge is inhibited following cortical arousal, potentially explaining arousals' destabilizing effect.

Stable phenotype of B-cell subsets following cryopreservation and thawing of normal human lymphocytes stored in a tissue biobank

BACKGROUND

Cryopreservation is an acknowledged procedure to store vital cells for future biomarker analyses. Few studies, however, have analyzed the impact of the cryopreservation on phenotyping.

METHODS

We have performed a controlled comparison of cryopreserved and fresh cellular aliquots prepared from individual healthy donors. We studied circulating B-cell subset membrane markers and global gene expression, respectively by multiparametric flow cytometry and microarray data. Extensive statistical analysis of the generated data tested the concept that "overall, there are no phenotypic differences between cryopreserved and fresh B-cell subsets." Subsequently, we performed an uncontrolled comparison of tonsil tissue samples.

RESULTS

By multiparametric flow analysis, we documented no significant changes following cryopreservation of subset frequencies or membrane intensity for the differentiation markers CD19, CD20, CD22, CD27, CD38, CD45, and CD200. By gene expression profiling following cryopreservation, across all samples, only 16 out of 18708 genes were significantly up or down regulated, including FOSB, KLF4, RBP7, ANXA1 or CLC, DEFA3, respectively. Implementation of cryopreserved tissue in our research program allowed us to present a performance analysis, by comparing cryopreserved and fresh tonsil tissue. As expected, phenotypic differences were identified, but to an extent that did not affect the performance of the cryopreserved tissue to generate specific B-cell subset associated gene signatures and assign subset phenotypes to independent tissue samples.

CONCLUSIONS

We have confirmed our working concept and illustrated the usefulness of vital cryopreserved cell suspensions for phenotypic studies of the normal B-cell hierarchy; however, storage procedures need to be delineated by tissue-specific comparative analysis.

Hemorheology in experimental research: is it necessary to consider blood fluidity differences in the laboratory rat?

This study was designed to identify whether blood fluidity differs between commercially available laboratory rat strains. The hemorheological profiles of seven clinically healthy wild-type rat strains were analyzed to determine whether any diversity in blood fluidity might affect the outcome of cardiovascular studies. Study 1: 65 healthy adult rats (Lewis, Long-Evans, Hairless, Wistar and Fisher; mixed gender and comparable ages) were compared. In order to determine the greatest possible difference, the two strains with the greatest hematocrit (HCT) differences were selected for more detailed evaluation. Red blood cell (RBC) deformability (maximum elongation index, shear stress for half-maximal deformation of RBC; both P < 0.0001), and the effect of plasma protein concentration upon plasma viscosity (P < 0.0001) were different between Lewis and Long-Evans strains. Whole blood viscosity - although different at native HCT (P < 0.004) - was unaltered following HCT standardization of samples. Differences in RBC aggregation were statistically significant but these were small and may not be clinically relevant. Study 2: these 65 animals were compared with 21 animals (10-16 weeks old; both sexes) from mutant strains (Dahl SS/JrHsdMcwiCrl, n = 10; ZDF-Lepr(fa)/Crl, n = 11). In both mutant strains, plasma and whole blood viscosity were increased compared with commonly used strains at native and standardized HCT (P < 0.001). Unusually high RBC aggregation values were seen in the ZDF rat strain (P < 0.001). It was concluded that the variability in blood fluidity among clinically healthy adult laboratory rat strains was both statistically and clinically significant. A hemorheological profile should be added to a routine phenotyping process, since both variables can significantly influence study outcomes.

Emerging microengineered tools for functional analysis and phenotyping of blood cells

The available techniques for assessing blood cell functions are limited considering the various types of blood cell and their diverse functions. In the past decade, rapid advances in microengineering have enabled an array of blood cell functional measurements that are difficult or impossible to achieve using conventional bulk platforms. Such miniaturized blood cell assay platforms also provide the attractive capabilities of reducing chemical consumption, cost, and assay time, as well as exciting opportunities for device integration, automation, and assay standardization. This review summarizes these contemporary microengineered tools and discusses their promising potential for constructing accurate in vitro models and rapid clinical diagnosis using minimal amounts of whole-blood samples.

Personalized medicine for chronic, complex diseases: chronic obstructive pulmonary disease as an example

Chronic, complex diseases represent the majority of healthcare utilization and spending in the USA today. Despite this, therapeutics that account for the heterogeneity of these diseases are lacking, begging for more personalized approaches. Improving our understanding of disease phenotypes through retrospective trials of electronic health record data will enable us to better categorize patients. Increased usage of next-generation sequencing will further our understanding of the genetic variants involved in chronic disease. Utilization of data warehousing will be necessary in order to securely handle, integrate and analyze the large sets of data produced with these methods. Finally, increased use of clinical decision support will enable the return of clinically actionable results that physicians can use to apply these personalized approaches.

World Endometriosis Research Foundation Endometriosis Phenome and Biobanking Harmonisation Project: I. Surgical phenotype data collection in endometriosis research. Fertil Steril. 2014;102:1213-1222. [PMID: 25150390 PMCID: PMC4230690 DOI: 10.1016/j.fertnstert.2014.07.709]

Objective

To standardize the recording of surgical phenotypic information on endometriosis and related sample collections obtained at laparoscopy, allowing large-scale collaborative research into the condition.

Design

An international collaboration involving 34 clinical/academic centers and three industry collaborators from 16 countries.

Setting

Two workshops were conducted in 2013, bringing together 54 clinical, academic, and industry leaders in endometriosis research and management worldwide.

Patient(s)

None.

Intervention(s)

A postsurgical scoring sheet containing general and gynecological patient and procedural information, extent of disease, the location and type of endometriotic lesion, and any other findings was developed during several rounds of review. Comments and any systematic surgical data collection tools used in the reviewers' centers were incorporated.

Main Outcome Measure(s)

The development of a standard recommended (SSF) and minimum required (MSF) form to collect data on the surgical phenotype of endometriosis.

Result(s)

SSF and MSF include detailed descriptions of lesions, modes of procedures and sample collection, comorbidities, and potential residual disease at the end of surgery, along with previously published instruments such as the revised American Society for Reproductive Medicine and Endometriosis Fertility Index classification tools for comparison and validation.

Conclusion(s)

This is the first multicenter, international collaboration between academic centers and industry addressing standardization of phenotypic data collection for a specific disease. The Endometriosis Phenome and Biobanking Harmonisation Project SSF and MSF are essential tools to increase our understanding of the pathogenesis of endometriosis by allowing large-scale collaborative research into the condition.

Structured evaluation of rodent behavioral tests used in drug discovery research

A large variety of rodent behavioral tests are currently being used to evaluate traits such as sensory-motor function, social interactions, anxiety-like and depressive-like behavior, substance dependence and various forms of cognitive function. Most behavioral tests have an inherent complexity, and their use requires consideration of several aspects such as the source of motivation in the test, the interaction between experimenter and animal, sources of variability, the sensory modality required by the animal to solve the task as well as costs and required work effort. Of particular importance is a test’s validity because of its influence on the chance of successful translation of preclinical results to clinical settings. High validity may, however, have to be balanced against practical constraints and there are no behavioral tests with optimal characteristics. The design and development of new behavioral tests is therefore an ongoing effort and there are now well over one hundred tests described in the contemporary literature. Some of them are well established following extensive use, while others are novel and still unproven. The task of choosing a behavioral test for a particular project may therefore be daunting and the aim of the present review is to provide a structured way to evaluate rodent behavioral tests aimed at drug discovery research.

A report on the use of animal models and phenotyping methods in pulmonary hypertension research

The failure to translate positive results from preclinical studies into new clinical therapies is a major problem throughout medical research. Specifically, in pulmonary hypertension, numerous research studies have shown beneficial effects of new therapies in experimental models, but these have largely failed to translate into clinical benefit in human trials. This is undoubtedly due, at least in part, to inadequacies of the models, but while monogenic animal models will never fully recapitulate human disease, they do still provide the best platform on which to test novel therapeutic agents. In the postgenomic era, there is emphasis on a greater understanding of disease pathogenesis, which has subsequently led to the development of both new targets and new models in which to test them. The evolution of new technologies means that we are now better equipped to phenotype these models, but the level of detail provided varies dramatically throughout the literature. However, subtle variances in experimental methods can make comparing data/findings between research laboratories difficult and are a possible contributing factor to variance between preclinical and clinical data. The aim of this report was to capture information on current practice for use of the growing array of animal models, to help movement toward developing guidelines and standards for the "best" use of animal models of pulmonary hypertension.

Human pluripotent stem cells on artificial microenvironments: a high content perspective

Self-renewing stem cell populations are increasingly considered as resources for cell therapy and tools for drug discovery. Human pluripotent stem (hPS) cells in particular offer a virtually unlimited reservoir of homogeneous cells and can be differentiated toward diverse lineages. Many diseases show impairment in self-renewal or differentiation, abnormal lineage choice or other aberrant cell behavior in response to chemical or physical cues. To investigate these responses, there is a growing interest in the development of specific assays using hPS cells, artificial microenvironments and high content analysis. Several hurdles need to be overcome that can be grouped into three areas: (i) availability of robust, homogeneous, and consistent cell populations as a starting point; (ii) appropriate understanding and use of chemical and physical microenvironments; (iii) development of assays that dissect the complexity of cell populations in tissues while mirroring specific aspects of their behavior. Here we review recent progress in the culture of hPS cells and we detail the importance of the environment surrounding the cells with a focus on synthetic material and suitable high content analysis approaches. The technologies described, if properly combined, have the potential to create a paradigm shift in the way diseases are modeled and drug discovery is performed.

Diagnostically relevant facial gestalt information from ordinary photos

Craniofacial characteristics are highly informative for clinical geneticists when diagnosing genetic diseases. As a first step towards the high-throughput diagnosis of ultra-rare developmental diseases we introduce an automatic approach that implements recent developments in computer vision. This algorithm extracts phenotypic information from ordinary non-clinical photographs and, using machine learning, models human facial dysmorphisms in a multidimensional 'Clinical Face Phenotype Space'. The space locates patients in the context of known syndromes and thereby facilitates the generation of diagnostic hypotheses. Consequently, the approach will aid clinicians by greatly narrowing (by 27.6-fold) the search space of potential diagnoses for patients with suspected developmental disorders. Furthermore, this Clinical Face Phenotype Space allows the clustering of patients by phenotype even when no known syndrome diagnosis exists, thereby aiding disease identification. We demonstrate that this approach provides a novel method for inferring causative genetic variants from clinical sequencing data through functional genetic pathway comparisons.DOI: http://dx.doi.org/10.7554/eLife.02020.001.

Diagnostically relevant facial gestalt information from ordinary photos

Craniofacial characteristics are highly informative for clinical geneticists when diagnosing genetic diseases. As a first step towards the high-throughput diagnosis of ultra-rare developmental diseases we introduce an automatic approach that implements recent developments in computer vision. This algorithm extracts phenotypic information from ordinary non-clinical photographs and, using machine learning, models human facial dysmorphisms in a multidimensional 'Clinical Face Phenotype Space'. The space locates patients in the context of known syndromes and thereby facilitates the generation of diagnostic hypotheses. Consequently, the approach will aid clinicians by greatly narrowing (by 27.6-fold) the search space of potential diagnoses for patients with suspected developmental disorders. Furthermore, this Clinical Face Phenotype Space allows the clustering of patients by phenotype even when no known syndrome diagnosis exists, thereby aiding disease identification. We demonstrate that this approach provides a novel method for inferring causative genetic variants from clinical sequencing data through functional genetic pathway comparisons.DOI: http://dx.doi.org/10.7554/eLife.02020.001.

Clinical data integration model. Core interoperability ontology for research using primary care data

INTRODUCTION

This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems".

BACKGROUND

Primary care data is the single richest source of routine health care data. However its use, both in research and clinical work, often requires data from multiple clinical sites, clinical trials databases and registries. Data integration and interoperability are therefore of utmost importance.

OBJECTIVES

TRANSFoRm's general approach relies on a unified interoperability framework, described in a previous paper. We developed a core ontology for an interoperability framework based on data mediation. This article presents how such an ontology, the Clinical Data Integration Model (CDIM), can be designed to support, in conjunction with appropriate terminologies, biomedical data federation within TRANSFoRm, an EU FP7 project that aims to develop the digital infrastructure for a learning healthcare system in European Primary Care.

METHODS

TRANSFoRm utilizes a unified structural / terminological interoperability framework, based on the local-as-view mediation paradigm. Such an approach mandates the global information model to describe the domain of interest independently of the data sources to be explored. Following a requirement analysis process, no ontology focusing on primary care research was identified and, thus we designed a realist ontology based on Basic Formal Ontology to support our framework in collaboration with various terminologies used in primary care.

RESULTS

The resulting ontology has 549 classes and 82 object properties and is used to support data integration for TRANSFoRm's use cases. Concepts identified by researchers were successfully expressed in queries using CDIM and pertinent terminologies. As an example, we illustrate how, in TRANSFoRm, the Query Formulation Workbench can capture eligibility criteria in a computable representation, which is based on CDIM.

CONCLUSION

A unified mediation approach to semantic interoperability provides a flexible and extensible framework for all types of interaction between health record systems and research systems. CDIM, as core ontology of such an approach, enables simplicity and consistency of design across the heterogeneous software landscape and can support the specific needs of EHR-driven phenotyping research using primary care data.

Mechanistic differences between phenotypes of chronic lung allograft dysfunction after lung transplantation

Distinct phenotypes of chronic lung allograft dysfunction (CLAD) after lung transplantation are emerging with lymphocytic bronchiolitis (LB)/azithromycin reversible allograft dysfunction (ARAD), classical or fibrotic bronchiolitis obliterans syndrome (BOS), and restrictive allograft syndrome (RAS) proposed as separate entities. We have additionally identified lung transplant recipients with prior LB, demonstrating persistent airway neutrophilia (PAN) despite azithromycin treatment. The aim of this study was to evaluate differences in the airway microenvironment in different phenotypes of CLAD. Bronchoalveolar lavage (BAL) from recipients identified as stable (control), LB/ARAD, PAN, BOS, and RAS were evaluated for differential cell counts and concentrations of IL-1α, IL-1β, IL-6, IL-8, and TNF-α. Primary human bronchial epithelial cells were exposed to BAL supernatants from different phenotypes and their viability measured. BOS and RAS showed increased BAL neutrophilia but no change in cytokine concentrations compared with prediagnosis. In both LB/ARAD and PAN, significant increases in IL-1α, IL-1β, and IL-8 were present. BAL IL-6 and TNF-α concentrations were increased in PAN and only this phenotype demonstrated decreased epithelial cell viability after exposure to BAL fluid. This study demonstrates clear differences in the airway microenvironment between different CLAD phenotypes. Systematic phenotyping of CLAD may help the development of more personalized approaches to treatment.

The emergent role of metabolic phenotyping in dynamic patient stratification

The role that metabolic phenotyping can increasingly play in patient stratification and personalised medicine is discussed. The background to the general approach, comprehensive and simultaneous analysis of small-molecule metabolites in biofluids, tissues and tissue extracts combined with suitable multivariate statistical models, is summarised. The main techniques used (NMR and mass spectrometry) are cited, and the implementation of dedicated phenome centres is explained. Finally, the advantages and limitations, opportunities and drawbacks of the approach are discussed.

Genome-wide mapping of cellular traits using yeast

Yeast has long enjoyed superiority as a genetic model because of its short generation time and ease of generating alleles for genetic analysis. However, recent developments of guided nucleases for genome editing in higher eukaryotes, and funding pressures for translational findings, force all model organism communities to reaffirm and rearticulate the advantages of their chosen creature. Here I examine the utility of budding yeast for understanding the genetic basis of cellular traits, using natural variation as well as classical genetic perturbations, and its future prospects compared to undertaking the work in human cell lines. Will yeast remain central, or will it join the likes of phage as an early model that is no longer widely used to answer the pressing questions?

The "diffuse-trickling" fundus autofluorescence phenotype in geographic atrophy

PURPOSE

To further characterize a subgroup of patients exhibiting the fundus autofluorescence (FAF) "diffuse-trickling" phenotype associated with geographic atrophy (GA).

METHODS

In the context of the Fundus Autofluorescence in Age-Related Macular Degeneration (FAM) Study, patients with diffuse-trickling GA were examined and characterized by FAF and spectral-domain optical coherence tomography imaging. Age, sex distribution, and medical history were compared with FAM study patients (n = 288, 60.1% female) with other GA phenotypes (non-diffuse-trickling). In a subset of patients, subfoveal choroidal thickness (SCT) was analyzed.

RESULTS

Patients with diffuse-trickling (n = 61), compared with patients with non-diffuse-trickling GA, had a significantly younger age at first presentation (68.2 ± 11.6 vs. 75.4 ± 8.1 years, P < 0.001), a shift in the proportion of men from 55% in the age group younger than 65 to 19% in the age group older than or equal to 65, and a significantly higher rate of myocardial infarction (MI) in the age group younger than 65 (24% vs. 0%, P = 0.011); all but one patient with MI were male. Further evaluation revealed that in the age group younger than 65, 54% of patients with diffuse-trickling had been hospitalized due to cardiovascular diseases including hypertensive crisis, angina, and MI. Analysis of choroidal thickness revealed a significantly thinner SCT in diffuse-trickling compared with non-diffuse-trickling GA (135.2 ± 56.4 vs. 191.4 ± 77.8 μm, P < 0.001).

CONCLUSIONS

The results indicate an association of diffuse-trickling GA with systemic cardiovascular disorders in the younger study population. Together with the ocular morphologic characteristics including a lobular appearance and a thin choroid, a vascular insufficiency at the level of the choroid may play a pathogenetic role in this distinct GA phenotype. (ClinicalTrials.gov number, NCT00393692.).

A scanner system for high-resolution quantification of variation in root growth dynamics of Brassica rapa genotypes

The potential exists to breed for root system architectures that optimize resource acquisition. However, this requires the ability to screen root system development quantitatively, with high resolution, in as natural an environment as possible, with high throughput. This paper describes the construction of a low-cost, high-resolution root phenotyping platform, requiring no sophisticated equipment and adaptable to most laboratory and glasshouse environments, and its application to quantify environmental and temporal variation in root traits between genotypes of Brassica rapa L. Plants were supplied with a complete nutrient solution through the wick of a germination paper. Images of root systems were acquired without manual intervention, over extended periods, using multiple scanners controlled by customized software. Mixed-effects models were used to describe the sources of variation in root traits contributing to root system architecture estimated from digital images. It was calculated that between one and 43 replicates would be required to detect a significant difference (95% CI 50% difference between traits). Broad-sense heritability was highest for shoot biomass traits (>0.60), intermediate (0.25-0.60) for the length and diameter of primary roots and lateral root branching density on the primary root, and lower (<0.25) for other root traits. Models demonstrate that root traits show temporal variations of various types. The phenotyping platform described here can be used to quantify environmental and temporal variation in traits contributing to root system architecture in B. rapa and can be extended to screen the large populations required for breeding for efficient resource acquisition.

Facial phenotyping by quantitative photography reflects craniofacial morphology measured on magnetic resonance imaging in Icelandic sleep apnea patients

STUDY OBJECTIVES

(1) To determine whether facial phenotype, measured by quantitative photography, relates to underlying craniofacial obstructive sleep apnea (OSA) risk factors, measured with magnetic resonance imaging (MRI); (2) To assess whether these associations are independent of body size and obesity.

DESIGN

Cross-sectional cohort.

SETTING

Landspitali, The National University Hospital, Iceland.

PARTICIPANTS

One hundred forty patients (87.1% male) from the Icelandic Sleep Apnea Cohort who had both calibrated frontal and profile craniofacial photographs and upper airway MRI. Mean ± standard deviation age 56.1 ± 10.4 y, body mass index 33.5 ± 5.05 kg/m(2), with on-average severe OSA (apnea-hypopnea index 45.4 ± 19.7 h(-1)).

INTERVENTIONS

N/A.

MEASUREMENTS AND RESULTS

Relationships between surface facial dimensions (photos) and facial bony dimensions and upper airway soft-tissue volumes (MRI) was assessed using canonical correlation analysis. Photo and MRI craniofacial datasets related in four significant canonical correlations, primarily driven by measurements of (1) maxillary-mandibular relationship (r = 0.8, P < 0.0001), (2) lower face height (r = 0.76, P < 0.0001), (3) mandibular length (r = 0.67, P < 0.0001), and (4) tongue volume (r = 0.52, P = 0.01). Correlations 1, 2, and 3 were unchanged when controlled for weight and neck and waist circumference. However, tongue volume was no longer significant, suggesting facial dimensions relate to tongue volume as a result of obesity.

CONCLUSIONS

Significant associations were found between craniofacial variable sets from facial photography and MRI. This study confirms that facial photographic phenotype reflects underlying aspects of craniofacial skeletal abnormalities associated with OSA. Therefore, facial photographic phenotyping may be a useful tool to assess intermediate phenotypes for OSA, particularly in large-scale studies.

Rapid determination of leaf area and plant height by using light curtain arrays in four species with contrasting shoot architecture

BACKGROUND

Light curtain arrays (LC), a recently introduced phenotyping method, yield a binary data matrix from which a shoot silhouette is reconstructed. We addressed the accuracy and applicability of LC in assessing leaf area and maximum height (base to the highest leaf tip) in a phenotyping platform. LC were integrated to an automated routine for positioning, allowing in situ measurements. Two dicotyledonous (rapeseed, tomato) and two monocotyledonous (maize, barley) species with contrasting shoot architecture were investigated. To evaluate if averaging multiple view angles helps in resolving self-overlaps, we acquired a data set by rotating plants every 10° for 170°. To test how rapid these measurements can be without loss of information, we evaluated nine scanning speeds. Leaf area of overlapping plants was also estimated to assess the possibility to scale this method for plant stands.

RESULTS

The relation between measured and calculated maximum height was linear and nearly the same for all species. Linear relations were also found between plant leaf area and calculated pixel area. However, the regression slope was different between monocotyledonous and dicotyledonous species. Increasing the scanning speed stepwise from 0.9 to 23.4 m s-1 did not affect the estimation of maximum height. Instead, the calculated pixel area was inversely proportional to scanning speed. The estimation of plant leaf area by means of calculated pixel area became more accurate by averaging consecutive silhouettes and/or increasing the angle between them. Simulations showed that decreasing plant distance gradually from 20 to 0 cm, led to underestimation of plant leaf area owing to overlaps. This underestimation was more important for large plants of dicotyledonous species and for small plants of monocotyledonous ones.

CONCLUSIONS

LC offer an accurate estimation of plant leaf area and maximum height, while the number of consecutive silhouettes that needs to be averaged is species-dependent. A constant scanning speed is important for leaf area estimations by using LC. Simulations of the effect of varying plant spacing gave promising results for method application in sets of partly overlapping plants, which applies also to field conditions during and after canopy closure for crops sown in rows.

Phenotyping date palm varieties via leaflet cross-sectional imaging and artificial neural network application

BACKGROUND

True date palms (Phoenix dactylifera L.) are impressive trees and have served as an indispensable source of food for mankind in tropical and subtropical countries for centuries. The aim of this study is to differentiate date palm tree varieties by analysing leaflet cross sections with technical/optical methods and artificial neural networks (ANN).

RESULTS

Fluorescence microscopy images of leaflet cross sections have been taken from a set of five date palm tree cultivars (Hewlat al Jouf, Khlas, Nabot Soltan, Shishi, Um Raheem). After features extraction from images, the obtained data have been fed in a multilayer perceptron ANN with backpropagation learning algorithm.

CONCLUSIONS

Overall, an accurate result in prediction and differentiation of date palm tree cultivars was achieved with average prediction in tenfold cross-validation is 89.1% and reached 100% in one of the best ANN.

A rigorous algorithm to detect and clean inaccurate adult height records within EHR systems

BACKGROUND

Height is a critical variable for many biomedical analyses because it is an important component of Body Mass Index (BMI). Transforming EHR height measures into meaningful research-ready values is challenging and there is limited information available on methods for "cleaning" these data.

OBJECTIVES

We sought to develop an algorithm to clean adult height data extracted from EHR using only height values and associated ages.

RESULTS

The algorithm we developed is sensitive to normal decreases in adult height associated with aging, is implemented using an open-source software tool and is thus easily modifiable, and is freely available. We checked the performance of our algorithm using data from the Northwestern biobank and a replication sample from the Marshfield Clinic biobank obtained through our participation in the eMERGE consortium. The algorithm identified 1262 erroneous values from a total of 33937 records in the Northwestern sample. Replacing erroneous height values with those identified as correct by the algorithm resulted in meaningful changes in height and BMI records; median change in recorded height after cleaning was 7.6 cm and median change in BMI was 2.9 kg/m(2). Comparison of cleaned EHR height values to observer measured values showed that 94.5% (95% C.I 93.8-% - 95.2%) of cleaned values were within 3.5 cm of observer measured values.

CONCLUSIONS

Our freely available height algorithm cleans EHR height data with only height and age inputs. Use of this algorithm will benefit groups trying to perform research with height and BMI data extracted from EHR.

Reaction phenotyping of vinblastine metabolism in dogs

Vinblastine is a vinca alkaloid used either as a single agent or in combination therapy for the treatment of canine mast cell tumours and lymphomas. The objective of this study was to determine which isoform of cytochrome P450 enzyme is responsible for the majority of vinblastine metabolism in dogs. A panel of eight recombinant canine cytochrome P450 enzymes (CYP1A1, CYP1A2, CYP3A12, CYP3A26, CYP2B11, CYP2C41, CYP2C21 and CYP2D15) were incubated in vitro with vinblastine. Findings were confirmed by the use of canine polyclonal antibodies of cytochrome P450 enzymes (CYP1A1, CYP3A12, CYP2B11 and CYP2C21) that were pre-incubated with individual and pooled hepatic microsomes that were purified from canine liver. Substrate depletion was observed in the presence of recombinant CYP3A12, whereas depletion did not substantially occur when microsomes were pre-incubated with polyclonal antibodies against CYP3A12. These findings confirmed that CYP3A12 is the major cytochrome P450 isoform responsible for the metabolism of vinblastine in dogs.

Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care

Background

Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection within the neonatal intensive care unit (NICU) environment.

Objective

This paper presents two phenotyping AE and ME detection algorithms (ie, IV infiltrations, narcotic medication oversedation and dosing errors) and describes manual annotation of airway management and medication/fluid AEs from NICU EHRs.

Methods

From 753 NICU patient EHRs from 2011, we developed two automatic AE/ME detection algorithms, and manually annotated 11 classes of AEs in 3263 clinical notes. Performance of the automatic AE/ME detection algorithms was compared to trigger tool and voluntary incident reporting results. AEs in clinical notes were double annotated and consensus achieved under neonatologist supervision. Sensitivity, positive predictive value (PPV), and specificity are reported.

Results

Twelve severe IV infiltrates were detected. The algorithm identified one more infiltrate than the trigger tool and eight more than incident reporting. One narcotic oversedation was detected demonstrating 100% agreement with the trigger tool. Additionally, 17 narcotic medication MEs were detected, an increase of 16 cases over voluntary incident reporting.

Conclusions

Automated AE/ME detection algorithms provide higher sensitivity and PPV than currently used trigger tools or voluntary incident-reporting systems, including identification of potential dosing and frequency errors that current methods are unequipped to detect.

Field high-throughput phenotyping: the new crop breeding frontier

Constraints in field phenotyping capability limit our ability to dissect the genetics of quantitative traits, particularly those related to yield and stress tolerance (e.g., yield potential as well as increased drought, heat tolerance, and nutrient efficiency, etc.). The development of effective field-based high-throughput phenotyping platforms (HTPPs) remains a bottleneck for future breeding advances. However, progress in sensors, aeronautics, and high-performance computing are paving the way. Here, we review recent advances in field HTPPs, which should combine at an affordable cost, high capacity for data recording, scoring and processing, and non-invasive remote sensing methods, together with automated environmental data collection. Laboratory analyses of key plant parts may complement direct phenotyping under field conditions. Improvements in user-friendly data management together with a more powerful interpretation of results should increase the use of field HTPPs, therefore increasing the efficiency of crop genetic improvement to meet the needs of future generations.

Field high-throughput phenotyping: the new crop breeding frontier

Constraints in field phenotyping capability limit our ability to dissect the genetics of quantitative traits, particularly those related to yield and stress tolerance (e.g., yield potential as well as increased drought, heat tolerance, and nutrient efficiency, etc.). The development of effective field-based high-throughput phenotyping platforms (HTPPs) remains a bottleneck for future breeding advances. However, progress in sensors, aeronautics, and high-performance computing are paving the way. Here, we review recent advances in field HTPPs, which should combine at an affordable cost, high capacity for data recording, scoring and processing, and non-invasive remote sensing methods, together with automated environmental data collection. Laboratory analyses of key plant parts may complement direct phenotyping under field conditions. Improvements in user-friendly data management together with a more powerful interpretation of results should increase the use of field HTPPs, therefore increasing the efficiency of crop genetic improvement to meet the needs of future generations.

Constitutional thinness and anorexia nervosa: a possible misdiagnosis?

Clinical and biological aspects of restrictive anorexia nervosa (R-AN) are well documented. More than 10,000 articles since 1911 and more than 600 in 2013 have addressed R-AN psychiatric, somatic, and biological aspects. Genetic background, ineffectiveness of appetite regulating hormones on refeeding process, bone loss, and place of amenorrhea in the definition are widely discussed and reviewed. Oppositely, constitutional thinness (CT) is an almost unknown entity. Only 32 articles have been published on this topic since 1953. Similar symptoms associating low body mass index, low fat, and bone mass are reported in both CT and R-AN subjects. Conversely, menses are preserved in CT women and almost the entire hormonal profile is normal, except for leptin and PYY. The aim of the present review is to alert the clinician on the confusing clinical presentation of these two situations, a potential source of misdiagnosis, especially since R-AN definition has changed in DSM5.

Identification of crop cultivars with consistently high lignocellulosic sugar release requires the use of appropriate statistical design and modelling

BACKGROUND

In this study, a multi-parent population of barley cultivars was grown in the field for two consecutive years and then straw saccharification (sugar release by enzymes) was subsequently analysed in the laboratory to identify the cultivars with the highest consistent sugar yield. This experiment was used to assess the benefit of accounting for both the multi-phase and multi-environment aspects of large-scale phenotyping experiments with field-grown germplasm through sound statistical design and analysis.

RESULTS

Complementary designs at both the field and laboratory phases of the experiment ensured that non-genetic sources of variation could be separated from the genetic variation of cultivars, which was the main target of the study. The field phase included biological replication and plot randomisation. The laboratory phase employed re-randomisation and technical replication of samples within a batch, with a subset of cultivars chosen as duplicates that were randomly allocated across batches. The resulting data was analysed using a linear mixed model that incorporated field and laboratory variation and a cultivar by trial interaction, and ensured that the cultivar means were more accurately represented than if the non-genetic variation was ignored. The heritability detected was more than doubled in each year of the trial by accounting for the non-genetic variation in the analysis, clearly showing the benefit of this design and approach.

CONCLUSIONS

The importance of accounting for both field and laboratory variation, as well as the cultivar by trial interaction, by fitting a single statistical model (multi-environment trial, MET, model), was evidenced by the changes in list of the top 40 cultivars showing the highest sugar yields. Failure to account for this interaction resulted in only eight cultivars that were consistently in the top 40 in different years. The correspondence between the rankings of cultivars was much higher at 25 in the MET model. This approach is suited to any multi-phase and multi-environment population-based genetic experiment.

Mutagenesis and phenotyping resources in zebrafish for studying development and human disease

The zebrafish (Danio rerio) is an important model organism for studying development and human disease. The zebrafish has an excellent reference genome and the functions of hundreds of genes have been tested using both forward and reverse genetic approaches. Recent years have seen an increasing number of large-scale mutagenesis projects and the number of mutants or gene knockouts in zebrafish has increased rapidly, including for the first time conditional knockout technologies. In addition, targeted mutagenesis techniques such as zinc finger nucleases, transcription activator-like effector nucleases and clustered regularly interspaced short sequences (CRISPR) or CRISPR-associated (Cas), have all been shown to effectively target zebrafish genes as well as the first reported germline homologous recombination, further expanding the utility and power of zebrafish genetics. Given this explosion of mutagenesis resources, it is now possible to perform systematic, high-throughput phenotype analysis of all zebrafish gene knockouts.

Poor prognosis of rare sarcomeric gene variants in patients with dilated cardiomyopathy

BACKGROUND

In dilated cardiomyopathy (DCM), the clinical and prognostic implications of rare variants in sarcomeric genes remain poorly understood. To address this question, we analyzed the outcome of rare sarcomeric gene variants in patients enrolled in our Familial Cardiomyopathy Registry.

METHODS

DCM families harboring rare sarcomeric variants in MYH6, MYH7, MYBPC3, TNNT2, and TTN were identified. Genotype-phenotype association analysis was performed, and long-term survival-free from death or heart transplant was compared between carriers and noncarriers.

RESULTS

We found 24 rare variants (3 in MYH6, 3 in MYH7, 3 in MYBPC3, 2 in TNNT2, and 13 in TTN) affecting 52 subjects in 25 families. The phenotypes of variant carriers were severe (3 sudden deaths, 6 heart failure deaths, 8 heart transplants, 2 ventricular fibrillations). There was no difference in the overall long-term survival between carriers and the 33 noncarriers (p = 0.322). However after 50 years of age, the combined endpoint of death or transplant was decreased in carriers as compared to noncarriers (p = 0.026).

CONCLUSIONS

Patients with DCM carrying rare variants in sarcomeric genes manifest a poorer prognosis as compared to noncarriers after the age of 50 years. These data further support the role of genetic testing in DCM for risk stratification.

Chlorophyll fluorescence analysis: a guide to good practice and understanding some new applications

Chlorophyll fluorescence is a non-invasive measurement of photosystem II (PSII) activity and is a commonly used technique in plant physiology. The sensitivity of PSII activity to abiotic and biotic factors has made this a key technique not only for understanding the photosynthetic mechanisms but also as a broader indicator of how plants respond to environmental change. This, along with low cost and ease of collecting data, has resulted in the appearance of a large array of instrument types for measurement and calculated parameters which can be bewildering for the new user. Moreover, its accessibility can lead to misuse and misinterpretation when the underlying photosynthetic processes are not fully appreciated. This review is timely because it sits at a point of renewed interest in chlorophyll fluorescence where fast measurements of photosynthetic performance are now required for crop improvement purposes. Here we help the researcher make choices in terms of protocols using the equipment and expertise available, especially for field measurements. We start with a basic overview of the principles of fluorescence analysis and provide advice on best practice for taking pulse amplitude-modulated measurements. We also discuss a number of emerging techniques for contemporary crop and ecology research, where we see continual development and application of analytical techniques to meet the new challenges that have arisen in recent years. We end the review by briefly discussing the emerging area of monitoring fluorescence, chlorophyll fluorescence imaging, field phenotyping, and remote sensing of crops for yield and biomass enhancement.

From "truly naïve" to "exhausted senescent" T cells: when markers predict functionality

The study of T cell biology has been accelerated by substantial progress at the technological level, particularly through the continuing advancement of flow cytometry. The conventional approach of observing T cells as either T helper or T cytotoxic is overly simplistic and does not allow investigators to clearly identify immune mechanisms or alterations in physiological processes that impact on clinical outcomes. The complexity of T cell sub-populations, as we understand them today, combined with the immunological and functional diversity of these subsets represent significant complications for the study of T cell biology. In this article, we review the use of classical markers in delineating T cell sub-populations, from "truly naïve" T cells (recent thymic emigrants with no proliferative history) to "exhausted senescent" T cells (poorly proliferative cells that display severe functional abnormalities) wherein the different phenotypes of these populations reflect their disparate functionalities. In addition, since persistent infections and chronological aging have been shown to be associated with significant alterations in human T cell distribution and function, we also discuss age-associated and cytomegalovirus-driven alterations in the expression of key subset markers.

A coming of age: advanced imaging technologies for characterising the developing mouse

The immense challenge of annotating the entire mouse genome has stimulated the development of cutting-edge imaging technologies in a drive for novel information. These techniques promise to improve understanding of the genes involved in embryo development, at least one third of which have been shown to be essential. Aligning advanced imaging technologies with biological needs will be fundamental to maximising the number of phenotypes discovered in the coming years. International efforts are underway to meet this challenge through an integrated and sophisticated approach to embryo phenotyping. We review rapid advances made in the imaging field over the past decade and provide a comprehensive examination of the relative merits of current and emerging techniques. The aim of this review is to provide a guide to state-of-the-art embryo imaging that will enable informed decisions as to which technology to use and fuel conversations between expert imaging laboratories, researchers, and core mouse production facilities.

P-TRAP: a Panicle TRAit Phenotyping tool

BACKGROUND

In crops, inflorescence complexity and the shape and size of the seed are among the most important characters that influence yield. For example, rice panicles vary considerably in the number and order of branches, elongation of the axis, and the shape and size of the seed. Manual low-throughput phenotyping methods are time consuming, and the results are unreliable. However, high-throughput image analysis of the qualitative and quantitative traits of rice panicles is essential for understanding the diversity of the panicle as well as for breeding programs.

RESULTS

This paper presents P-TRAP software (Panicle TRAit Phenotyping), a free open source application for high-throughput measurements of panicle architecture and seed-related traits. The software is written in Java and can be used with different platforms (the user-friendly Graphical User Interface (GUI) uses Netbeans Platform 7.3). The application offers three main tools: a tool for the analysis of panicle structure, a spikelet/grain counting tool, and a tool for the analysis of seed shape. The three tools can be used independently or simultaneously for analysis of the same image. Results are then reported in the Extensible Markup Language (XML) and Comma Separated Values (CSV) file formats. Images of rice panicles were used to evaluate the efficiency and robustness of the software. Compared to data obtained by manual processing, P-TRAP produced reliable results in a much shorter time. In addition, manual processing is not repeatable because dry panicles are vulnerable to damage. The software is very useful, practical and collects much more data than human operators.

CONCLUSIONS

P-TRAP is a new open source software that automatically recognizes the structure of a panicle and the seeds on the panicle in numeric images. The software processes and quantifies several traits related to panicle structure, detects and counts the grains, and measures their shape parameters. In short, P-TRAP offers both efficient results and a user-friendly environment for experiments. The experimental results showed very good accuracy compared to field operator, expert verification and well-known academic methods.

Diel leaf growth of soybean: a novel method to analyze two-dimensional leaf expansion in high temporal resolution based on a marker tracking approach (Martrack Leaf)

BACKGROUND

We present a novel method for quantitative analysis of dicot leaf expansion at high temporal resolution. Image sequences of growing leaves were assessed using a marker tracking algorithm. An important feature of the method is the attachment of dark beads that serve as artificial landmarks to the leaf margin. The beads are mechanically constricted to the focal plane of a camera. Leaf expansion is approximated by the increase in area of the polygon defined by the centers of mass of the beads surrounding the leaf. Fluctuating illumination conditions often pose serious problems for tracking natural structures of a leaf; this problem is circumvented here by the use of the beads.

RESULTS

The new method has been used to assess leaf growth in environmental situations with different illumination conditions that are typical in agricultural and biological experiments: Constant illumination via fluorescent light tubes in a climate chamber, a mix of natural and artificial illumination in a greenhouse and natural illumination of the situation on typical summer days in the field. Typical features of diel (24h) soybean leaf growth patterns were revealed in all three conditions, thereby demonstrating the general applicability of the method. Algorithms are provided to the entire community interested in using such approaches.

CONCLUSIONS

The implementation Martrack Leaf presented here is a robust method to investigate diel leaf growth rhythms both under natural and artificial illumination conditions. It will be beneficial for the further elucidation of genotype x environment x management interactions affecting leaf growth processes.

The classification and diagnostic algorithm for primary lymphatic dysplasia: an update from 2010 to include molecular findings

Historically, primary lymphoedema was classified into just three categories depending on the age of onset of swelling; congenital, praecox and tarda. Developments in clinical phenotyping and identification of the genetic cause of some of these conditions have demonstrated that primary lymphoedema is highly heterogenous. In 2010, we introduced a new classification and diagnostic pathway as a clinical and research tool. This algorithm has been used to delineate specific primary lymphoedema phenotypes, facilitating the discovery of new causative genes. This article reviews the latest molecular findings and provides an updated version of the classification and diagnostic pathway based on this new knowledge.

Influence of infection on the distribution patterns of NIH-Chronic Prostatitis Symptom Index scores in patients with chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS)

Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a complex condition for which the etiological determinants are still poorly defined. To better characterize the diagnostic and therapeutic profile of patients, an algorithm known as UPOINT was created, addressing six major phenotypic domains of CP/CPPS, specifically the urinary (U), psycho-social (P), organ-specific (O), infection (I), neurological/systemic (N) and muscular tenderness (T) domains. An additional sexual dysfunction domain may be included in the UPOINT(S) system. The impact of the infection domain on the severity of CP/CPPS symptoms is a controversial issue, due to the contradictory results of different trials. The aim of the present retrospective study was to further analyze the extent to which a positive infection domain of UPOINTS may modify the pattern of CP/CPPS symptom scores, assessed with the National Institutes of Health-Chronic Prostatitis Symptom Index (NIH-CPSI). In a cohort of 935 patients that was divided on the basis of the presence or absence of prostatic infection, more severe clinical symptoms were shown by the patients with infection (median NIH total score: 24 versus 20 points in uninfected patients; P<0.001). Moreover, NIH-CPSI score distribution curves were shifted towards more severe symptoms in patients with a positive infection domain. Division of the patients into the six most prominent phenotypic clusters of UPOINTS revealed that the ‘prostate infection-related sexual dysfunction’ cluster, including the highest proportion of patients with evidence of infection (80%), scored the highest number of NIH-CPSI points among all the clusters. To assess the influence of the infection domain on the severity of patients’ symptoms, all subjects with evidence of infection were withdrawn from the ‘prostate infection-related sexual dysfunction’ cluster. This modified cluster showed symptom scores significantly less severe than the original cluster, and the CPSI values became comparable to the scores of the five other clusters, which were virtually devoid of patients with evidence of infection. These results suggest that the presence of pathogens in the prostate gland may significantly affect the clinical presentation of patients affected by CP/CPPS, and that the infection domain may be a determinant of the severity of CP/CPPS symptoms in clusters of patients phenotyped with the UPOINTS system. This evidence may convey considerable therapeutic implications.

Extracellular Vesicle (EV) Array: microarray capturing of exosomes and other extracellular vesicles for multiplexed phenotyping

BACKGROUND

Exosomes are one of the several types of cell-derived vesicles with a diameter of 30-100 nm. These extracellular vesicles are recognized as potential markers of human diseases such as cancer. However, their use in diagnostic tests requires an objective and high-throughput method to define their phenotype and determine their concentration in biological fluids. To identify circulating as well as cell culture-derived vesicles, the current standard is immunoblotting or a flow cytometrical analysis for specific proteins, both of which requires large amounts of purified vesicles.

METHODS

Based on the technology of protein microarray, we hereby present a highly sensitive Extracellular Vesicle (EV) Array capable of detecting and phenotyping exosomes and other extracellular vesicles from unpurified starting material in a high-throughput manner. To only detect the exosomes captured on the EV Array, a cocktail of antibodies against the tetraspanins CD9, CD63 and CD81 was used. These antibodies were selected to ensure that all exosomes captured are detected, and concomitantly excluding the detection of other types of microvesicles.

RESULTS

The limit of detection (LOD) was determined on exosomes derived from the colon cancer cell line LS180. It clarified that supernatant from only approximately 10(4) cells was needed to obtain signals or that only 2.5×10(4) exosomes were required for each microarray spot (~1 nL). Phenotyping was performed on plasma (1-10 µL) from 7 healthy donors, which were applied to the EV Array with a panel of antibodies against 21 different cellular surface antigens and cancer antigens. For each donor, there was considerable heterogeneity in the expression levels of individual markers. The protein profiles of the exosomes (defined as positive for CD9, CD63 and CD81) revealed that only the expression level of CD9 and CD81 was approximately equal in the 7 donors. This implies questioning the use of CD63 as a standard exosomal marker since the expression level of this tetraspanin was considerably lower.

Genotypic and phenotypic characterization of methicillin-resistant Staphylococcus aureus (MRSA) isolated from milk of bovine mastitis

The aim of this study was to evaluate the presence of methicillin-resistant Staphylococcus aureus (MRSA) among a (S. aureus) collection (n = 430) isolated from milk of cows suffering from mastitis in Belgium and to compare their genotypic as well as phenotypic characteristics. Pulsed field gel electrophoresis (PFGE) and PCR-based typing techniques (MLST, spa, SCCmec, and agr typing) have been applied and supplemented by capsule serotyping, biofilm production quantification and antimicrobial susceptibility testing. Nineteen MRSA were isolated. Seven distinct ApaI PFGE patterns were observed. All isolates, except one, were identified as ST398 strains. Three spa types (t011, t567 and t108) and two SCCmec types (IV and V) were identified. All isolates belonged to agr type I and capsule type 5 and were Panton-Valentine leukocidin (PVL) negative. All isolates produced biofilm in TSBglc , whereas the majority did not in milk serum. Twelve resistance patterns were observed, with almost two-thirds of the isolates being resistant to at least six antibiotics, including penicillin and tetracycline. Our study confirms that the emerging ST398 LA-MRSA clone has attained Belgian cattle. With regard to genotypic and phenotypic typing, the 19 MRSA isolated in this study form a homogenous group and do not differ much from one another, neither from what has been previously described.

Phenotypic approaches to drought in cassava: review

Cassava is an important crop in Africa, Asia, Latin America, and the Caribbean. Cassava can be produced adequately in drought conditions making it the ideal food security crop in marginal environments. Although cassava can tolerate drought stress, it can be genetically improved to enhance productivity in such environments. Drought adaptation studies in over three decades in cassava have identified relevant mechanisms which have been explored in conventional breeding. Drought is a quantitative trait and its multigenic nature makes it very challenging to effectively manipulate and combine genes in breeding for rapid genetic gain and selection process. Cassava has a long growth cycle of 12-18 months which invariably contributes to a long breeding scheme for the crop. Modern breeding using advances in genomics and improved genotyping, is facilitating the dissection and genetic analysis of complex traits including drought tolerance, thus helping to better elucidate and understand the genetic basis of such traits. A beneficial goal of new innovative breeding strategies is to shorten the breeding cycle using minimized, efficient or fast phenotyping protocols. While high throughput genotyping have been achieved, this is rarely the case for phenotyping for drought adaptation. Some of the storage root phenotyping in cassava are often done very late in the evaluation cycle making selection process very slow. This paper highlights some modified traits suitable for early-growth phase phenotyping that may be used to reduce drought phenotyping cycle in cassava. Such modified traits can significantly complement the high throughput genotyping procedures to fast track breeding of improved drought tolerant varieties. The need for metabolite profiling, improved phenomics to take advantage of next generation sequencing technologies and high throughput phenotyping are basic steps for future direction to improve genetic gain and maximize speed for drought tolerance breeding.

Phenotyping and genotyping are both essential to identify and classify a probiotic microorganism

The use of probiotic products, especially for humans, requires an unequivocal taxonomical definition of their microbial content, in order to assign the probiotic effects to well identified and characterized microbial strains. In the absence of this, the labeling of some marketed probiotics may be misleading, both in terms of microbiological contents and possible beneficial effects. Currently, the ‘polyphasic taxonomy’ based on the integration of phenotypic and genotypic data seems to be the most appropriate approach. In fact, even if phenotypic characters often overlap among genetically different species, the molecular methods alone are frequently not able to establish distinct boundaries among phylogenetically related species. Thus, a valid scheme for the identification of a probiotic strain should be currently based on its morphological, physiological, and biochemical features as well as on aspects of its genetic profile. It is important that the identity of specific probiotic strains appearing on the product label is the result of a carefully selected combination of suitable phenotypic and genotypic analytical methods. Only adoption of such a policy could give the right emphasis to the significance of strain-specificity and thus provide health authorities with accurate tools to better evaluate the health benefits claimed by each probiotic-based product. The most common phenotypic and genotypic methods are briefly reviewed here with the aim of highlighting the suitable techniques which can be used to differentiate among microorganisms of probiotic interest, particularly those claiming beneficial health effects for humans.

Chronic obstructive pulmonary disease lost in translation: Why are the inhaled corticosteroids skeptics refusing to go?

A survey of pulmonologists attending a clinical meeting of the Saudi Thoracic Society found that only 55% of responders considered that inhaled corticosteroids (ICS) had a positive effect on quality of life in Chronic Obstructive Pulmonary Disease (COPD). Why the divergence of opinion when all the guidelines have concluded that ICS improve quality of life and produce significant bronchodilation? ICS unequivocally reduce the rate of exacerbations by a modest 20%, but this does not extend to serious exacerbations requiring hospitalization. Bronchodilatation with ICS is now documented to be restricted to some phenotypes of COPD. Withdrawal of ICS trials reported a modest decline of FEV₁ (<5%) in half the studies and no decline in the other half. In spite of the guidelines statements, there is no concurrence on whether ICS improve the quality of life and there is no conclusive evidence that the combination of long-acting ß2 agonists (LABA) with ICS is superior to LABA alone in that regard. The explanation for these inconclusive results may be related to the fact that COPD consists of three different phenotypes with divergent responses to LABA and ICS. Therapy tailored to phenotype is the future for COPD.