The Ontology of Biological Attributes (OBA) - Computational Traits for the Life Sciences

Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focused measurable trait data. Moreover, variations in gene expression in response to environmental disturbances even without any genetic alterations can also be associated with particular biological attributes. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos.

The impact of Covid-19 on the well-being of young people with conduct disorder and their families

Introduction

The Covid-19 pandemic has significantly changed family dynamics and parents experience greater psychological distress. Conduct problems in young people have increased by 35%. However, it is not known how Covid-19 associated stresses have affected parenting practice, conduct problems, and comorbidities and what additional support is needed for families at risk.

Objectives

This study uses self-report measures and semi-structured interviews to examine and explore the impact of Covid-19 on the families of young people with conduct problems and comorbid mental health conditions.

Methods

This is a sequential mixed-methods study. Eligible families with children aged between 11-18 years have participated. One-hundred-and-eighty-two families have completed eight online questionnaires and 12 have participated in semi-structured follow-up interviews.

Results

Analyses indicate that parental harshness, warmth, educational background, and employment have a significant impact on Covid-19 exposure and worries, as well as significantly higher scores of conduct disorder symptoms. Interview codes reveal that young peoples’ behaviour became more severe during the pandemic, and this was associated with reduced in-person support services, reduced personal space at home, and parents taking on the additional role of educator.

Conclusions

The findings suggest that Covid-19 is a significant risk factor to young people with conduct problems and their families. For example, reduced parental warmth and increased parental harshness increased conduct problems for young people during the lockdown. This study highlights that policies and services should work to better support such families. Future online psychosocial interventions are needed to empower families and improve parenting practice at home during the lockdown period and in general.

Disclosure

No significant relationships.

Peroxone activated persulfate oxidation of 1,4-Dioxane under column scale conditions

The research presented herein investigates a peroxone activated persulfate (PAP) oxidant, commercialized under the trade name OxyZone®, and its effects on 1,4-Dioxane (dioxane) contaminated water under column scale conditions in the presence of porous material. There is a limited understanding of the underlying processes that govern PAP oxidation, including the oxidation rates in the presence of aquifer material, and how these reactions proceed once the oxidant is injected into a contaminant plume. Initial batch experiments with porous material (e.g. sand) provided data on the reaction rates of dioxane oxidation as a function of the oxidant: contaminant ratio. The observed degradation rates were approximately 4 times lower than those reported for aqueous solutions containing no porous media. Subsequent column experiments simulated two PAP injections schemes along the flowpath of a dioxane plume to study if the injection of one oxidant slug may yield different results than injecting the same oxidant volume at two separate locations. The injection of one oxidant slug was found more effective, resulting in near complete destruction of dioxane over a prolonged time at a rate more than an order of magnitude greater than in the two-slug injection scenario. Tracer test results suggest that the prolonged oxidant reactivity was in part caused by the high density of the injected oxidant solution. Overall, the results underline the importance of accounting for the properties of both the oxidant solution and the porous material when considering the injection of PAP oxidant into an impacted aquifer.

The role of illicit drugs in developing medication-related osteonecrosis (MRONJ): a systematic review

Medication-related osteonecrosis of the jaw (MRONJ) is a challenging condition to treat. It has primarily been associated with anti-resorptive and anti-angiogenic drugs, which are increasingly being used to prevent adverse skeletally-related complications in patients with cancer and bone pathologies. Although these medications have been proven to cause osteonecrosis of the jaws (ONJ) there are also a number of other drugs that could potentially cause this condition. The aim of this systematic review is to ascertain whether there is an associated risk of osteonecrosis of the jaw (ONJ) in recreational drug users (RDU). Three authors independently searched PubMed, MEDLINE, EMBASE, CINAHL and the Cochrane Central Register of Controlled Trials for published reports of osteonecrosis of the jaw (ONJ) in recreational drug users (RDU) or illicit drug users (IDU) who had no history of treatment with anti-angiogenic or anti-resorptive agents. Only 30 studies were eligible for analysis, and all were independently assessed for risk of bias. There was a total of 101 patients with ONJ attributed solely to illicit drug consumption. The most common site of ONJ was the maxilla (n=54). The most common illicit drug related to ONJ was desmorphine, known as 'Krokodil', this was followed by cocaine, methamphetamine, anabolic steroids, and hydrocodone/acetaminophen. In 52 of the cases, the ONJ resolved following treatment, however, eight showed a recurrence. Although all the studies were judged to be at a high risk of bias, the limited data suggest that some patients are at risk of developing ONJ as a result of illicit drug usage. Studies of higher quality are needed to establish the relative risk of ONJ in this patient group.

Erratum: Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage Challenge

[This corrects the article DOI: 10.1148/ryai.2020190211.].

Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage Challenge

This dataset is composed of annotations of the five hemorrhage subtypes (subarachnoid, intraventricular, subdural, epidural, and intraparenchymal hemorrhage) typically encountered at brain CT.

Macrophage Exclusion after Radiation Therapy (MERT): A First in Human Phase I/II Trial using a CXCR4 Inhibitor in Glioblastoma

PURPOSE

Preclinical studies have demonstrated that postirradiation tumor revascularization is dependent on a stromal cell-derived factor-1 (SDF-1)/C-X-C chemokine receptor type 4 (CXCR4)-driven process in which myeloid cells are recruited from bone marrow. Blocking this axis results in survival improvement in preclinical models of solid tumors, including glioblastoma (GBM). We conducted a phase I/II study to determine the safety and efficacy of Macrophage Exclusion after Radiation Therapy (MERT) using the reversible CXCR4 inhibitor plerixafor in patients with newly diagnosed glioblastoma.

PATIENTS AND METHODS

We enrolled nine patients in the phase I study and an additional 20 patients in phase II using a modified toxicity probability interval (mTPI) design. Plerixafor was continuously infused intravenously via a peripherally inserted central catheter (PICC) line for 4 consecutive weeks beginning at day 35 of conventional treatment with concurrent chemoradiation. Blood serum samples were obtained for pharmacokinetic analysis. Additional studies included relative cerebral blood volume (rCBV) analysis using MRI and histopathology analysis of recurrent tumors.

RESULTS

Plerixafor was well tolerated with no drug-attributable grade 3 toxicities observed. At the maximum dose of 400 μg/kg/day, biomarker analysis found suprathreshold plerixafor serum levels and an increase in plasma SDF-1 levels. Median overall survival was 21.3 months [95% confidence interval (CI), 15.9-NA] with a progression-free survival of 14.5 months (95% CI, 11.9-NA). MRI and histopathology support the mechanism of action to inhibit postirradiation tumor revascularization.

CONCLUSIONS

Infusion of the CXCR4 inhibitor plerixafor was well tolerated as an adjunct to standard chemoirradiation in patients with newly diagnosed GBM and improves local control of tumor recurrences.

Development and Performance of the Pulmonary Embolism Result Forecast Model (PERFORM) for Computed Tomography Clinical Decision Support

IMPORTANCE

Pulmonary embolism (PE) is a life-threatening clinical problem, and computed tomographic imaging is the standard for diagnosis. Clinical decision support rules based on PE risk-scoring models have been developed to compute pretest probability but are underused and tend to underperform in practice, leading to persistent overuse of CT imaging for PE.

OBJECTIVE

To develop a machine learning model to generate a patient-specific risk score for PE by analyzing longitudinal clinical data as clinical decision support for patients referred for CT imaging for PE.

DESIGN, SETTING, AND PARTICIPANTS

In this diagnostic study, the proposed workflow for the machine learning model, the Pulmonary Embolism Result Forecast Model (PERFORM), transforms raw electronic medical record (EMR) data into temporal feature vectors and develops a decision analytical model targeted toward adult patients referred for CT imaging for PE. The model was tested on holdout patient EMR data from 2 large, academic medical practices. A total of 3397 annotated CT imaging examinations for PE from 3214 unique patients seen at Stanford University hospitals and clinics were used for training and validation. The models were externally validated on 240 unique patients seen at Duke University Medical Center. The comparison with clinical scoring systems was done on randomly selected 100 outpatient samples from Stanford University hospitals and clinics and 101 outpatient samples from Duke University Medical Center.

MAIN OUTCOMES AND MEASURES

Prediction performance of diagnosing acute PE was evaluated using ElasticNet, artificial neural networks, and other machine learning approaches on holdout data sets from both institutions, and performance of models was measured by area under the receiver operating characteristic curve (AUROC).

RESULTS

Of the 3214 patients included in the study, 1704 (53.0%) were women from Stanford University hospitals and clinics; mean (SD) age was 60.53 (19.43) years. The 240 patients from Duke University Medical Center used for validation included 132 women (55.0%); mean (SD) age was 70.2 (14.2) years. In the samples for clinical scoring system comparisons, the 100 outpatients from Stanford University hospitals and clinics included 67 women (67.0%); mean (SD) age was 57.74 (19.87) years, and the 101 patients from Duke University Medical Center included 59 women (58.4%); mean (SD) age was 73.06 (15.3) years. The best-performing model achieved an AUROC performance of predicting a positive PE study of 0.90 (95% CI, 0.87-0.91) on intrainstitutional holdout data with an AUROC of 0.71 (95% CI, 0.69-0.72) on an external data set from Duke University Medical Center; superior AUROC performance and cross-institutional generalization of the model of 0.81 (95% CI, 0.77-0.87) and 0.81 (95% CI, 0.73-0.82), respectively, were noted on holdout outpatient populations from both intrainstitutional and extrainstitutional data.

CONCLUSIONS AND RELEVANCE

The machine learning model, PERFORM, may consider multitudes of applicable patient-specific risk factors and dependencies to arrive at a PE risk prediction that generalizes to new population distributions. This approach might be used as an automated clinical decision-support tool for patients referred for CT PE imaging to improve CT use.

Can Natural Language Processing Improve the Efficiency of Vaccine Adverse Event Report Review?

BACKGROUND

Individual case review of spontaneous adverse event (AE) reports remains a cornerstone of medical product safety surveillance for industry and regulators. Previously we developed the Vaccine Adverse Event Text Miner (VaeTM) to offer automated information extraction and potentially accelerate the evaluation of large volumes of unstructured data and facilitate signal detection.

OBJECTIVE

To assess how the information extraction performed by VaeTM impacts the accuracy of a medical expert's review of the vaccine adverse event report.

METHODS

The "outcome of interest" (diagnosis, cause of death, second level diagnosis), "onset time," and "alternative explanations" (drug, medical and family history) for the adverse event were extracted from 1000 reports from the Vaccine Adverse Event Reporting System (VAERS) using the VaeTM system. We compared the human interpretation, by medical experts, of the VaeTM extracted data with their interpretation of the traditional full text reports for these three variables. Two experienced clinicians alternately reviewed text miner output and full text. A third clinician scored the match rate using a predefined algorithm; the proportion of matches and 95% confidence intervals (CI) were calculated. Review time per report was analyzed.

RESULTS

Proportion of matches between the interpretation of the VaeTM extracted data, compared to the interpretation of the full text: 93% for outcome of interest (95% CI: 91-94%) and 78% for alternative explanation (95% CI: 75-81%). Extracted data on the time to onset was used in 14% of cases and was a match in 54% (95% CI: 46-63%) of those cases. When supported by structured time data from reports, the match for time to onset was 79% (95% CI: 76-81%). The extracted text averaged 136 (74%) fewer words, resulting in a mean reduction in review time of 50 (58%) seconds per report.

CONCLUSION

Despite a 74% reduction in words, the clinical conclusion from VaeTM extracted data agreed with the full text in 93% and 78% of reports for the outcome of interest and alternative explanation, respectively. The limited amount of extracted time interval data indicates the need for further development of this feature. VaeTM may improve review efficiency, but further study is needed to determine if this level of agreement is sufficient for routine use.

Simulating adverse event spontaneous reporting systems as preferential attachment networks: application to the Vaccine Adverse Event Reporting System

BACKGROUND

Spontaneous Reporting Systems [SRS] are critical tools in the post-licensure evaluation of medical product safety. Regulatory authorities use a variety of data mining techniques to detect potential safety signals in SRS databases. Assessing the performance of such signal detection procedures requires simulated SRS databases, but simulation strategies proposed to date each have limitations.

OBJECTIVE

We sought to develop a novel SRS simulation strategy based on plausible mechanisms for the growth of databases over time.

METHODS

We developed a simulation strategy based on the network principle of preferential attachment. We demonstrated how this strategy can be used to create simulations based on specific databases of interest, and provided an example of using such simulations to compare signal detection thresholds for a popular data mining algorithm.

RESULTS

The preferential attachment simulations were generally structurally similar to our targeted SRS database, although they had fewer nodes of very high degree. The approach was able to generate signal-free SRS simulations, as well as mimicking specific known true signals. Explorations of different reporting thresholds for the FDA Vaccine Adverse Event Reporting System suggested that using proportional reporting ratio [PRR] > 3.0 may yield better signal detection operating characteristics than the more commonly used PRR > 2.0 threshold.

DISCUSSION

The network analytic approach to SRS simulation based on the principle of preferential attachment provides an attractive framework for exploring the performance of safety signal detection algorithms. This approach is potentially more principled and versatile than existing simulation approaches.

CONCLUSION

The utility of network-based SRS simulations needs to be further explored by evaluating other types of simulated signals with a broader range of data mining approaches, and comparing network-based simulations with other simulation strategies where applicable.

Automating case definitions using literature-based reasoning

BACKGROUND

Establishing a Case Definition (CDef) is a first step in many epidemiological, clinical, surveillance, and research activities. The application of CDefs still relies on manual steps and this is a major source of inefficiency in surveillance and research.

OBJECTIVE

Describe the need and propose an approach for automating the useful representation of CDefs for medical conditions.

METHODS

We translated the existing Brighton Collaboration CDef for anaphylaxis by mostly relying on the identification of synonyms for the criteria of the CDef using the NLM MetaMap tool. We also generated a CDef for the same condition using all the related PubMed abstracts, processing them with a text mining tool, and further treating the synonyms with the above strategy. The co-occurrence of the anaphylaxis and any other medical term within the same sentence of the abstracts supported the construction of a large semantic network. The 'islands' algorithm reduced the network and revealed its densest region including the nodes that were used to represent the key criteria of the CDef. We evaluated the ability of the "translated" and the "generated" CDef to classify a set of 6034 H1N1 reports for anaphylaxis using two similarity approaches and comparing them with our previous semi-automated classification approach.

RESULTS

Overall classification performance across approaches to producing CDefs was similar, with the generated CDef and vector space model with cosine similarity having the highest accuracy (0.825 ± 0.003) and the semi-automated approach and vector space model with cosine similarity having the highest recall (0.809 ± 0.042). Precision was low for all approaches.

CONCLUSION

The useful representation of CDefs is a complicated task but potentially offers substantial gains in efficiency to support safety and clinical surveillance.

The contribution of the vaccine adverse event text mining system to the classification of possible Guillain-Barré syndrome reports

BACKGROUND

We previously demonstrated that a general purpose text mining system, the Vaccine adverse event Text Mining (VaeTM) system, could be used to automatically classify reports of an-aphylaxis for post-marketing safety surveillance of vaccines.

OBJECTIVE

To evaluate the ability of VaeTM to classify reports to the Vaccine Adverse Event Reporting System (VAERS) of possible Guillain-Barré Syndrome (GBS).

METHODS

We used VaeTM to extract the key diagnostic features from the text of reports in VAERS. Then, we applied the Brighton Collaboration (BC) case definition for GBS, and an information retrieval strategy (i.e. the vector space model) to quantify the specific information that is included in the key features extracted by VaeTM and compared it with the encoded information that is already stored in VAERS as Medical Dictionary for Regulatory Activities (MedDRA) Preferred Terms (PTs). We also evaluated the contribution of the primary (diagnosis and cause of death) and secondary (second level diagnosis and symptoms) diagnostic VaeTM-based features to the total VaeTM-based information.

RESULTS

MedDRA captured more information and better supported the classification of reports for GBS than VaeTM (AUC: 0.904 vs. 0.777); the lower performance of VaeTM is likely due to the lack of extraction by VaeTM of specific laboratory results that are included in the BC criteria for GBS. On the other hand, the VaeTM-based classification exhibited greater specificity than the MedDRA-based approach (94.96% vs. 87.65%). Most of the VaeTM-based information was contained in the secondary diagnostic features.

CONCLUSION

For GBS, clinical signs and symptoms alone are not sufficient to match MedDRA coding for purposes of case classification, but are preferred if specificity is the priority.

Emerging outbreaks associated with equine coronavirus in adult horses

The purpose of this study was to describe clinical, hematological and fecal PCR results from 161 horses involved in outbreaks associated with ECoV. The outbreaks happened at four separate boarding facilities between November 2011 and April 2012 in the States of CA, TX, WI and MA. Following the molecular detection of ECoV in the feces from the initial index cases, the remaining herdmates were closely observed for the development of clinical signs. Fecal samples were collected from sick and healthy horses for the PCR detection of ECoV. All four outbreaks involved primarily adult horses. Fifty-nine horses developed clinical signs with 12–16 sick horses per outbreak. The main clinical signs reported were anorexia, lethargy and fever. Four horses from 3 different outbreaks were euthanized or died due to rapid progression of clinical signs. The cause of death could not be determined with necropsy evaluation in 2 horses, while septicemia secondary to gastrointestinal translocation was suspected in 2 horses. Blood work was available from 10 horses with clinical disease and common hematological abnormalities were leucopenia due to neutropenia and/or lymphopenia. Feces were available for ECoV testing by real-time PCR from 44 and 96 sick and healthy horses, respectively. 38/44 (86%) horses with abnormal clinical signs tested PCR positive for ECoV, while 89/96 (93%) healthy horses tested PCR negative for ECoV. The overall agreement between clinical status and PCR detection of ECoV was 91%. The study results suggest that ECoV is associated with self-limiting clinical and hematological abnormalities in adult horses.

Barley-derived β-glucans increases gut permeability, ex vivo epithelial cell binding to E. coli, and naive T-cell proportions in weanling pigs

Weaning in young animals is associated with an increased incidence of gastrointestinal infections. β-glucans exert numerous physiological effects, including altering immune function. The objective of this study was to determine the effects of feeding barley (Hordeum vulgare L.)-derived β-glucans on immune and intestinal function in weanling pigs (Sus scrofa). Thirty-one individually-housed Dutch Landrace pigs (21 d; initial BW, 6,298 ± 755 g) were weaned and fed a wheat-based diet (control) or a low (Lo-BG), medium (Med-BG), or high β-glucan-containing barley-based diet (Hi-BG) for 2 wk with 7 or 8 pigs/treatment. Intestinal segments were analyzed for permeability using Ussing chambers and K88 Escherichia coli adhesion to enterocytes was assessed ex vivo. Immune cells from mesenteric lymph nodes, peripheral blood, and Peyer's patches were analyzed for lymphocyte subsets by indirect immunofluorescence and the ability to respond ex vivo to mitogens by (3)H-thymidine incorporation. Hematology and neutrophil function were determined by flow cytometry. Neutrophil burst, size, and granularity, lymphocyte proliferation, and B-cell distribution in peripheral blood lymphocytes, Peyer's patches, and mesenteric lymph nodes were not affected by β-glucans content of the diet. The β-glucans content of the diet altered blood concentrations of erythrocytes and leukocytes, CD4, CD45RA, and CD8 blood cells (P < 0.05). In addition, feeding β-glucan resulted in increased (P < 0.05) percentage CD45RA positive cells in peripheral blood lymphocytes, Peyer's patches, and mesenteric lymph nodes. Mannitol permeability and tissue conductance were increased (P < 0.05) in Hi-BG fed pigs compared with control pigs. Percentage maximum K88-E.coli binding was increased in proportion to the β-glucan content of the diet (P < 0.05). Although β-glucan feeding during the weaning period increased blood lymphocytes and the proportion of naïve T-cells, it also increased E. coli-enterocyte binding and intestinal permeability. β-glucan may alter immune and intestinal function of weaning pigs.

Can network analysis improve pattern recognition among adverse events following immunization reported to VAERS?

Current methods of statistical data mining are limited in their ability to facilitate the identification of patterns of potential clinical interest from spontaneous reporting systems of medical product adverse events (AEs). Network analysis (NA) allows for simultaneous representation of complex connections among the key elements of such a system. The Vaccine Adverse Event Reporting System (VAERS) can be represented as a network of 6,428 nodes (74 vaccines and 6,354 AEs) with more than 1.4 million interlinkages. VAERS has the characteristics of a "scale-free" network, with certain vaccines and AEs acting as "hubs" in the network. Known safety signals were visualized using NA methods, including hub identification. NA offers a complementary approach to current statistical data-mining techniques for visualizing multidimensional patterns, providing a structural framework for evaluating AE data.

Reactivity of P-Glycoprotein Monoclonal Antibodies in Childhood Cancers

P-Glycoprotein (P-gp), the product of the mdr-1 gene, is implicated in the development of chemoresistance in a variety of, mostly adult, cancers. Its role in paediatric tumours, most of which are non-epithelial in origin, has yet to be fully elucidated. A study was undertaken to investigate reactivity of two P-gp monoclonal antibodies (MAbs), JBS-1 and MRK16, recognising cytoplasmic and surface epitopes, respectively, of the P-gp molecule, in a variety of newly diagnosed and relapsed childhood cancers. P-gp was not expressed in any of 36 tumours examined (neuroblastoma 13, nephroblastoma 12, rhabdomyosarcoma 6, lymphoma 3, teratoma 1, Ewings 1), 14 of whom had chemoresistant disease. Reactivity to both MAbs was also investigated in patients with acute leukaemia. Out of 10 diagnostic acute lymphoblastic leukaemia (ALL) samples, a positive reaction with JSB-1 was observed in 1 patient who failed to remit on standard induction therapy and in 3 of 6 patients in ALL relapse, only 1 of whom showed low grade positivity with MRK16. Both MAbs reacted positively in 1 patient with acute non-lymphocytic leukaemia (ANLL) at diagnosis who achieved remission with teniposide and cytosine arabinoside, but relapsed 7 months later and was again positive with both Mabs. JSB-1 also showed varying degrees of positivity in 4 out of 4 other patients in ANLL relapse. It would therefore appear that P-gp is unlikely to mediate chemoresistance in most solid tumours of childhood, but may well play a major role in the development of chemoresistance in acute leukaemia.

Comparison of military and civilian reporting rates for smallpox vaccine adverse events

INTRODUCTION

US smallpox vaccination (SMA) started most recently in December 2002. Military and civilian personnel report adverse events (AEs) to the Vaccine Adverse Event Reporting System (VAERS), a surveillance system that relies on spontaneous reports. Although reported rates of probable myo/pericarditis after SMA in the literature are similar between military personnel and civilian healthcare workers, some civilian AE reporting rates after SMA appeared higher than those in the military.

OBJECTIVE

Determine if SMA-associated reporting rates are different in civilians than in the military, considering age, sex, seriousness, and expectedness of the AE, as well as self-reporting.

METHODS

Numerators were SMA reports in VAERS from 12/12/02 to 3/1/04. Limitations of VAERS include underreporting and lack of diagnostic confirmation. Denominators were number of military and civilian vaccinees.

RESULTS

Reporting rates stratified by age and sex of serious and non-serious AEs were significantly higher in civilian than military personnel ages <55 years (rate ratios 4-27). These rate ratios decreased with increasing age.

CONCLUSIONS

Reporting rates in VAERS differed significantly and substantially in civilians compared to military personnel <55 years of age. Differences in stimulated passive surveillance systems, and AE reporting practices, including the 'threshold' for reporting most likely explain these findings. These results suggest that in the case of smallpox vaccine AEs, there may be systematic differences in reporting completeness between the civilian and military sectors, and that passive surveillance data should be interpreted with caution.

Complement levels before and after dives with a high risk of DCS

BACKGROUND

Previously, complement activation has been associated with decompression sickness (DCS). However data, both in humans and in animals, are controversial.

HYPOTHESIS

Complement activation and depletion occurs after exposure to the hyperbaric environment and is associated with increasing risk of DCS.

METHODS

We obtained serological samples from 102 dives (120-300 feet of seawater) with a constant partial pressure of O2 set at 1.3 ATA in thirty-five U.S. Navy diver volunteers. Blood was obtained within one hour of diving and within one hour of surfacing. Plasma was extracted and analyzed for complement depletion. The risk of DCS was estimated using a validated model of DCS risk.

RESULTS

Pre-post dive concentrations of C3a were significantly related to estimated risk of DCS (Figure 1), but the variation in predicted DCS explained by C3a was small (correlation co-efficient (r2 = 0.19, p < 0.0001).

CONCLUSIONS

There was a reduction in total Ca3 levels in divers after exposure to dives with a high estimated risk of DCS. This decomplementation appeared to increase as the estimated risk of DCS increased.

Inheritance of Time to Flowering in Chickpea in a Short-Season Temperate Environment

Time to flowering is central in determining the adaptation and productivity of chickpea in short-season temperate environments. We studied the genetic control of this trait in three crosses, 272-2 x CDC Anna, 298T-9 x CDC Anna, and 298T-9 x CDC Frontier. From each cross, 180 F2 plants and parents were evaluated for time to flowering under greenhouse conditions. In summer 2004, multiple generations including P1, F1, P2, F2, and F2:3 (also called MG5) were evaluated for time to flowering under field conditions. The data on time to flowering in the F(2) populations were continuous in distribution but deviated from normal distribution. The F2:3 families derived from this showed a bimodal distribution for time to flowering, a typical case of major-gene inheritance model with duplicate recessive epistasis. A joint segregation analysis of MG5 also revealed that time to flowering in chickpea was controlled by two major genes along with other polygenes. Late flowering was dominant over early flowering for both major genes with digenic interaction between them, mainly an additive x additive type. This information can be used to formulate the most efficient breeding strategy for improvement of time to flowering in chickpea in short-season temperate environments.

The effect of an imprecise map on interval mapping QTLs

The statistical analysis of quantitative trait locus (QTL) experiments relies on the use of a linkage map of the markers genotyped. Such a map is, at best, a good estimate of the true map. Resources might be diverted into developing better marker maps or improved maps become available after the analysis, raising concerns over the original analysis. It is therefore important to understand the sensitivity of QTL analysis to map inaccuracy. We have used simulation methods to investigate the consequences of an incorrect map on the results of a QTL analysis using interval mapping. Backcross data sets were generated with a particular map and then analysed with both the correct map and incorrect maps. If the incorrect maps maintained the true linkage groups (i.e. no markers were incorrectly assigned to another linkage group), the accuracy of the map had little or no impact on the ability to detect QTLs, the true significance levels of the tests or the relative placement of QTLs. When a marker was incorrectly placed on another linkage group, there was a small increase in the level of the test. After adjusting for this increase, there was a decrease in power to detect a QTL near the misplaced marker. This decrease was of a similar magnitude to that found when using a single-marker analysis compared with interval mapping. These results mean that QTL analyses can proceed without the need for very accurate marker maps, and that estimated QTL positions can be translated onto updated maps without the need for reanalysis.

Clinical value of obtaining sputum and cough swab samples following inhaled hypertonic saline in children with cystic fibrosis

Prompt detection and treatment of lower respiratory tract infection are essential in the management of patients with cystic fibrosis (CF), who often have signs or symptoms of respiratory infection without any pathogens being isolated from sputum or cough swab specimens. The aims of this study were to assess the efficacy and clinical value of obtaining sputum and oropharyngeal cough swab samples following induction with hypertonic saline (HS) in this group of patients. Forty-three outpatients with CF, mean age 7.2 years (range, 1.8-12.9 years), were recruited over a 2-year period. Nebulized salbutamol was administered, followed by 6% HS. Sputum was preferentially obtained before and after HS induction if possible. If the patient was not able to expectorate, oropharyngeal cough swabs were taken instead. Four patients were able to expectorate sputum before and 19 after HS induction. The procedure was tolerated in 41 of 43 patients. Pathogens were isolated from 13 patients' HS-induced samples, but not from their corresponding preinduced specimens, and 4 patients' preinduced specimens cultured organisms which were not identified from their HS-induced samples. Significant changes were made in the management of 13 (30.2%) patients directly resulting from the positive culture of pathogens only from HS-induced samples. Cultures from oropharyngeal cough swab or expectorated sputum specimens following inhalation of HS provide additional microbiological information which is of clinical value and may lead to changes in patient management.

Metamorphosis of plasma turbulence-shear-flow dynamics through a transcritical bifurcation

The structural properties of an economical model for a confined plasma turbulence governor are investigated through bifurcation and stability analyses. A close relationship is demonstrated between the underlying bifurcation framework of the model and typical behavior associated with low- to high-confinement transitions such as shear-flow stabilization of turbulence and oscillatory collective action. In particular, the analysis evinces two types of discontinuous transition that are qualitatively distinct. One involves classical hysteresis, governed by viscous dissipation. The other is intrinsically oscillatory and nonhysteretic, and thus provides a model for the so-called dithering transitions that are frequently observed. This metamorphosis, or transformation, of the system dynamics is an important late side-effect of symmetry breaking, which manifests as an unusual nonsymmetric transcritical bifurcation induced by a significant shear-flow drive.