DEIMoS GUI: An Open-Source User Interface for a High-Dimensional Mass Spectrometry Data Processing Tool

We report here the creation of a graphical user interface (GUI) for the Data Extraction for Integrated Multidimensional Spectrometry (DEIMoS) tool. DEIMoS is a Python package that processes data from high-dimensional mass spectrometry measurements. It is divided into several modules, each representing a data processing step such as peak detection, alignment, and tandem mass spectra extraction and deconvolution. The inputs for and outputs from DEIMoS can include millions of N-dimensional data points, which can be challenging to visualize in a way that is interactive, informative, and responsive. Here, we used the HoloViz Python data visualization stack, including DataShader and Param, to create an interactive visualization of the mass spectrometry data. We believe the GUI will increase the accessibility of DEIMoS and that the visualization methods could be useful for other open-source mass spectrometry tools.

Correction: Nielson et al. Similarity Downselection: Finding the n Most Dissimilar Molecular Conformers for Reference-Free Metabolomics. Metabolites 2023, 13, 105

There were missing figures and associated legends for Figure 3 and Figure 4 as published due to a publication error [...].

Impact of reduced nicotine content on behavioral economic measures of cigarette reinforcement in adolescents who smoke cigarettes

BACKGROUND

Public health officials in the U.S. and New Zealand are considering a reduced nicotine standard for cigarettes to reduce their addictive potential. This study's aim was to evaluate the effects of nicotine reduction on the reinforcing efficacy of cigarettes in adolescents who smoke, which has implications for this policy's potential for success.

METHODS

Adolescents who smoked cigarettes daily (n = 66; mean age: 18.6) participated in a randomized clinical trial assessing effects of assignment to very low nicotine content (VLNC; 0.4 mg/g nicotine) or normal nicotine content (NNC; 15.8 mg/g nicotine) cigarettes. Hypothetical cigarette purchase tasks were completed at baseline and the end of Week 3 and demand curves fit to the data. Linear regressions estimated effects of nicotine content on demand for study cigarettes at baseline and Week 3 and associations between baseline demand for cigarette consumption at Week 3.

RESULTS

An extra sum of squares F-test of fitted demand curves indicated that demand (α) was more elastic among VLNC participants at baseline and Week 3 (F(2, 1016)= 35.72, p < 0.001). Adjusted linear regressions indicated demand was more elastic (ß= 1.45, p < 0.01) and maximum expenditure (Omax) lower (ß= -1.42, p-0.03) among VLNC participants at Week 3. More elastic demand for study cigarettes at baseline predicted lower consumption of cigarettes at Week 3 (p's < 0.01).

CONCLUSIONS

A nicotine reduction policy may reduce the reinforcing value of combustible cigarettes among adolescents. Future work should investigate likely responses to such a policy among youth with other vulnerabilities and evaluate the potential for substitution to other nicotine containing products.

The unknown lipids project: harmonized methods improve compound identification and data reproducibility in an inter-laboratory untargeted lipidomics study

Untargeted lipidomics allows analysis of a broader range of lipids than targeted methods and permits discovery of unknown compounds. Previous ring trials have evaluated the reproducibility of targeted lipidomics methods, but inter-laboratory comparison of compound identification and unknown feature detection in untargeted lipidomics has not been attempted. To address this gap, five laboratories analyzed a set of mammalian tissue and biofluid reference samples using both their own untargeted lipidomics procedures and a common chromatographic and data analysis method. While both methods yielded informative data, the common method improved chromatographic reproducibility and resulted in detection of more shared features between labs. Spectral search against the LipidBlast in silico library enabled identification of over 2,000 unique lipids. Further examination of LC-MS/MS and ion mobility data, aided by hybrid search and spectral networking analysis, revealed spectral and chromatographic patterns useful for classification of unknown features, a subset of which were highly reproducible between labs. Overall, our method offers enhanced compound identification performance compared to targeted lipidomics, demonstrates the potential of harmonized methods to improve inter-site reproducibility for quantitation and feature alignment, and can serve as a reference to aid future annotation of untargeted lipidomics data.

Similarity Downselection: Finding the n Most Dissimilar Molecular Conformers for Reference-Free Metabolomics

Computational methods for creating in silico libraries of molecular descriptors (e.g., collision cross sections) are becoming increasingly prevalent due to the limited number of authentic reference materials available for traditional library building. These so-called "reference-free metabolomics" methods require sampling sets of molecular conformers in order to produce high accuracy property predictions. Due to the computational cost of the subsequent calculations for each conformer, there is a need to sample the most relevant subset and avoid repeating calculations on conformers that are nearly identical. The goal of this study is to introduce a heuristic method of finding the most dissimilar conformers from a larger population in order to help speed up reference-free calculation methods and maintain a high property prediction accuracy. Finding the set of the n items most dissimilar from each other out of a larger population becomes increasingly difficult and computationally expensive as either n or the population size grows large. Because there exists a pairwise relationship between each item and all other items in the population, finding the set of the n most dissimilar items is different than simply sorting an array of numbers. For instance, if you have a set of the most dissimilar n = 4 items, one or more of the items from n = 4 might not be in the set n = 5. An exact solution would have to search all possible combinations of size n in the population exhaustively. We present an open-source software called similarity downselection (SDS), written in Python and freely available on GitHub. SDS implements a heuristic algorithm for quickly finding the approximate set(s) of the n most dissimilar items. We benchmark SDS against a Monte Carlo method, which attempts to find the exact solution through repeated random sampling. We show that for SDS to find the set of n most dissimilar conformers, our method is not only orders of magnitude faster, but it is also more accurate than running Monte Carlo for 1,000,000 iterations, each searching for set sizes n = 3-7 out of a population of 50,000. We also benchmark SDS against the exact solution for example small populations, showing that SDS produces a solution close to the exact solution in these instances. Using theoretical approaches, we also demonstrate the constraints of the greedy algorithm and its efficacy as a ratio to the exact solution.

DEIMoS: An Open-Source Tool for Processing High-Dimensional Mass Spectrometry Data

We present DEIMoS: Data Extraction for Integrated Multidimensional Spectrometry, a Python application programming interface (API) and command-line tool for high-dimensional mass spectrometry data analysis workflows that offers ease of development and access to efficient algorithmic implementations. Functionality includes feature detection, feature alignment, collision cross section (CCS) calibration, isotope detection, and MS/MS spectral deconvolution, with the output comprising detected features aligned across study samples and characterized by mass, CCS, tandem mass spectra, and isotopic signature. Notably, DEIMoS operates on N-dimensional data, largely agnostic to acquisition instrumentation; algorithm implementations simultaneously utilize all dimensions to (i) offer greater separation between features, thus improving detection sensitivity, (ii) increase alignment/feature matching confidence among data sets, and (iii) mitigate convolution artifacts in tandem mass spectra. We demonstrate DEIMoS with LC-IMS-MS/MS metabolomics data to illustrate the advantages of a multidimensional approach in each data processing step.

Mass Spectrometry Adduct Calculator

We describe the Mass Spectrometry Adduct Calculator (MSAC), an automated Python tool to calculate the adduct ion masses of a parent molecule. Here, adduct refers to a version of a parent molecule [M] that is charged due to addition or loss of atoms and electrons resulting in a charged ion, for example, [M + H]⁺. MSAC includes a database of 147 potential adducts and adduct/neutral loss combinations and their mass-to-charge ratios (m/z) as extracted from the NIST/EPA/NIH Mass Spectral Library (NIST17), Global Natural Products Social Molecular Networking Public Spectral Libraries (GNPS), and MassBank of North America (MoNA). The calculator relies on user-selected subsets of the combined database to calculate expected m/z for adducts of molecules supplied as formulas. This tool is intended to help researchers create identification libraries to collect evidence for the presence of molecules in mass spectrometry data. While the included adduct database focuses on adducts typically detected during liquid chromatography-mass spectrometry analyses, users may supply their own lists of adducts and charge states for calculating expected m/z. We also analyzed statistics on adducts from spectra contained in the three selected mass spectral libraries. MSAC is freely available at https://github.com/pnnl/MSAC.

Associations Between Nicotine Knowledge and Smoking Cessation Behaviors among U.S. Adults Who Smoke

INTRODUCTION

Misperceptions about nicotine's contribution to smoking-related health harms could complicate efforts to reduce the public health burden of smoking. Study goals were to describe nicotine knowledge among adults who smoke and investigate whether misperceiving nicotine as a source of health harm was associated with beneficial health behaviors, or lower uptake of using less harmful sources of nicotine to support smoking cessation attempts.

METHOD

This study used longitudinal data from 9,140 adults who participated in four waves of the Population Assessment of Tobacco and Health Study and were current smokers during the first wave. Logistic regressions estimated odds ratios for correct responses across six aspects of nicotine knowledge assessed in Wave 4. Longitudinal models estimated associations between misperceptions and cigarette consumption, and odds of making a quit attempt; self-reported cessation; e-cigarette use; and use of NRT or e-cigarettes to support quit attempts.

RESULTS

Participants who were non-White, older, and had lower educational attainment or income tended to be least knowledgeable about nicotine. Misperceiving nicotine as harmful to health was associated with increased odds of quit attempts (AOR: 1.12, 95% CI: 1.03, 1.23), lower odds of cessation success (AOR: 0.84, 95% CI: 0.73, 0.98) and e-cigarette use (AOR: 0.79, 95% CI: 0.72, 0.86), and lower odds of using NRT (AOR: 0.84, 95% CI: 0.71, 0.99) or e-cigarettes to support quit attempts (AOR: 0.59, 95% CI: 0.49, 0.71).

CONCLUSION

Harm reduction efforts may be impeded by misperceptions about nicotine. Further work should evaluate the effects of correcting such misperceptions through public education.

IMPLICATIONS

This study provides longitudinal evidence that among adult smokers, misperceiving nicotine as a primary cause of smoking-related diseases may be associated with reduced cessation success and lower likelihood of using less harmful nicotine products. These misperceptions may therefore impede efforts to encourage smokers ready to quit to use evidence-based cessation support such as nicotine replacement during quit attempts and limit the success of policies designed to shift smokers to less harmful sources of nicotine. Further work should evaluate the longitudinal effects of correcting nicotine misperceptions through public education targeted toward adults who smoke.

Quantum Chemistry Calculations for Metabolomics

A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for "standards-free" identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.

Exploring the Impacts of Conformer Selection Methods on Ion Mobility Collision Cross Section Predictions

The prediction of structure dependent molecular properties, such as collision cross sections as measured using ion mobility spectrometry, are crucially dependent on the selection of the correct population of molecular conformers. Here, we report an in-depth evaluation of multiple conformation selection techniques, including simple averaging, Boltzmann weighting, lowest energy selection, low energy threshold reductions, and similarity reduction. Generating 50 000 conformers each for 18 molecules, we used the In Silico Chemical Library Engine (ISiCLE) to calculate the collision cross sections for the entire data set. First, we employed Monte Carlo simulations to understand the variability between conformer structures as generated using simulated annealing. Then we employed Monte Carlo simulations to the aforementioned conformer selection techniques applied on the simulated molecular property: the ion mobility collision cross section. Based on our analyses, we found Boltzmann weighting to be a good trade-off between precision and theoretical accuracy. Combining multiple techniques revealed that energy thresholds and root-mean-squared deviation-based similarity reductions can save considerable computational expense while maintaining property prediction accuracy. Molecular dynamic conformer generation tools like AMBER can continue to generate new lowest energy conformers even after tens of thousands of generations, decreasing precision between runs. This reduced precision can be ameliorated and theoretical accuracy increased by running density functional theory geometry optimization on carefully selected conformers.

Application and assessment of deep learning for the generation of potential NMDA receptor antagonists

Uncompetitive antagonists of the N-methyl d-aspartate receptor (NMDAR) have demonstrated therapeutic benefit in the treatment of neurological diseases such as Parkinson's and Alzheimer's, but some also cause dissociative effects that have led to the synthesis of illicit drugs. The ability to generate NMDAR antagonists in silico is therefore desirable for both new medication development and preempting and identifying new designer drugs. Recently, generative deep learning models have been applied to de novo drug design as a means to expand the amount of chemical space that can be explored for potential drug-like compounds. In this study, we assess the application of a generative model to the NMDAR to achieve two primary objectives: (i) the creation and release of a comprehensive library of experimentally validated NMDAR phencyclidine (PCP) site antagonists to assist the drug discovery community and (ii) an analysis of both the advantages conferred by applying such generative artificial intelligence models to drug design and the current limitations of the approach. We apply, and provide source code for, a variety of ligand- and structure-based assessment techniques used in standard drug discovery analyses to the deep learning-generated compounds. We present twelve candidate antagonists that are not available in existing chemical databases to provide an example of what this type of workflow can achieve, though synthesis and experimental validation of these compounds are still required.

A Practical Guide to Metabolomics Software Development

A growing number of software tools have been developed for metabolomics data processing and analysis. Many new tools are contributed by metabolomics practitioners who have limited prior experience with software development, and the tools are subsequently implemented by users with expertise that ranges from basic point-and-click data analysis to advanced coding. This Perspective is intended to introduce metabolomics software users and developers to important considerations that determine the overall impact of a publicly available tool within the scientific community. The recommendations reflect the collective experience of an NIH-sponsored Metabolomics Consortium working group that was formed with the goal of researching guidelines and best practices for metabolomics tool development. The recommendations are aimed at metabolomics researchers with little formal background in programming and are organized into three stages: (i) preparation, (ii) tool development, and (iii) distribution and maintenance.

Ligand- and Structure-Based Analysis of Deep Learning-Generated Potential α2a Adrenoceptor Agonists

The α2a adrenoceptor is a medically relevant subtype of the G protein-coupled receptor family. Unfortunately, high-throughput techniques aimed at producing novel drug leads for this receptor have been largely unsuccessful because of the complex pharmacology of adrenergic receptors. As such, cutting-edge in silico ligand- and structure-based assessment and de novo deep learning methods are well positioned to provide new insights into protein-ligand interactions and potential active compounds. In this work, we (i) collect a dataset of α2a adrenoceptor agonists and provide it as a resource for the drug design community; (ii) use the dataset as a basis to generate candidate-active structures via deep learning; and (iii) apply computational ligand- and structure-based analysis techniques to gain new insights into α2a adrenoceptor agonists and assess the quality of the computer-generated compounds. We further describe how such assessment techniques can be applied to putative chemical probes with a case study involving proposed medetomidine-based probes.

Who Is Metabolizing What? Discovering Novel Biomolecules in the Microbiome and the Organisms Who Make Them

Even as the field of microbiome research has made huge strides in mapping microbial community composition in a variety of environments and organisms, explaining the phenotypic influences on the host by microbial taxa-both known and unknown-and their specific functions still remain major challenges. A pressing need is the ability to assign specific functions in terms of enzymes and small molecules to specific taxa or groups of taxa in the community. This knowledge will be crucial for advancing personalized therapies based on the targeted modulation of microbes or metabolites that have predictable outcomes to benefit the human host. This perspective article advocates for the combined use of standards-free metabolomics and activity-based protein profiling strategies to address this gap in functional knowledge in microbiome research via the identification of novel biomolecules and the attribution of their production to specific microbial taxa.

Evaluation of In Silico Multifeature Libraries for Providing Evidence for the Presence of Small Molecules in Synthetic Blinded Samples

The current gold standard for unambiguous molecular identification in metabolomics analysis is comparing two or more orthogonal properties from the analysis of authentic reference materials (standards) to experimental data acquired in the same laboratory with the same analytical methods. This represents a significant limitation for comprehensive chemical identification of small molecules in complex samples. The process is time consuming and costly, and the majority of molecules are not yet represented by standards. Thus, there is a need to assemble evidence for the presence of small molecules in complex samples through the use of libraries containing calculated chemical properties. To address this need, we developed a Multi-Attribute Matching Engine (MAME) and a library derived in part from our in silico chemical library engine (ISiCLE). Here, we describe an initial evaluation of these methods in a blinded analysis of synthetic chemical mixtures as part of the U.S. Environmental Protection Agency's (EPA) Non-Targeted Analysis Collaborative Trial (ENTACT, Phase 1). For molecules in all mixtures, the initial blinded false negative rate (FNR), false discovery rate (FDR), and accuracy were 57%, 77%, and 91%, respectively. For high evidence scores, the FDR was 35%. After unblinding of the sample compositions, we optimized the scoring parameters to better exploit the available evidence and increased the accuracy for molecules suspected as present. The final FNR, FDR, and accuracy were 67%, 53%, and 96%, respectively. For high evidence scores, the FDR was 10%. This study demonstrates that multiattribute matching methods in conjunction with in silico libraries may one day enable reduced reliance on experimentally derived libraries for building evidence for the presence of molecules in complex samples.

ISiCLE: A Quantum Chemistry Pipeline for Establishing in Silico Collision Cross Section Libraries

High-throughput, comprehensive, and confident identifications of metabolites and other chemicals in biological and environmental samples will revolutionize our understanding of the role these chemically diverse molecules play in biological systems. Despite recent technological advances, metabolomics studies still result in the detection of a disproportionate number of features that cannot be confidently assigned to a chemical structure. This inadequacy is driven by the single most significant limitation in metabolomics, the reliance on reference libraries constructed by analysis of authentic reference materials with limited commercial availability. To this end, we have developed the in silico chemical library engine (ISiCLE), a high-performance computing-friendly cheminformatics workflow for generating libraries of chemical properties. In the instantiation described here, we predict probable three-dimensional molecular conformers (i.e., conformational isomers) using chemical identifiers as input, from which collision cross sections (CCS) are derived. The approach employs first-principles simulation, distinguished by the use of molecular dynamics, quantum chemistry, and ion mobility calculations, to generate structures and chemical property libraries, all without training data. Importantly, optimization of ISiCLE included a refactoring of the popular MOBCAL code for trajectory-based mobility calculations, improving its computational efficiency by over 2 orders of magnitude. Calculated CCS values were validated against 1983 experimentally measured CCS values and compared to previously reported CCS calculation approaches. Average calculated CCS error for the validation set is 3.2% using standard parameters, outperforming other density functional theory (DFT)-based methods and machine learning methods (e.g., MetCCS). An online database is introduced for sharing both calculated and experimental CCS values ( metabolomics.pnnl.gov ), initially including a CCS library with over 1 million entries. Finally, three successful applications of molecule characterization using calculated CCS are described, including providing evidence for the presence of an environmental degradation product, the separation of molecular isomers, and an initial characterization of complex blinded mixtures of exposure chemicals. This work represents a method to address the limitations of small molecule identification and offers an alternative to generating chemical identification libraries experimentally by analyzing authentic reference materials. All code is available at github.com/pnnl .

Isolation of Tryptanthrin and Reassessment of Evidence for Its Isobaric Isostere Wrightiadione in Plants of the Wrightia Genus

A series of Wrightia hanleyi extracts was screened for activity against Mycobacterium tuberculosis H37Rv. One active fraction contained a compound that initially appeared to be either the isoflavonoid wrightiadione or the alkaloid tryptanthrin, both of which have been previously reported in other Wrightia species. Characterization by NMR and MS, as well as evaluation of the literature describing these compounds, led to the conclusion that wrightiadione (1) was misidentified in the first report of its isolation from W. tomentosa in 1992 and again in 2015 when reported in W. pubescens and W. religiosa. Instead, the molecule described in these reports and in the present work is almost certainly the isobaric (same nominal mass) and isosteric (same number of atoms, valency, and shape) tryptanthrin (2), a well-known quinazolinone alkaloid found in a variety of plants including Wrightia species. Tryptanthrin (2) is also accessible synthetically via several routes and has been thoroughly characterized. Wrightiadione (1) has been synthesized and characterized and may have useful biological activity; however, this compound can no longer be said to be known to exist in Nature. To our knowledge, this misidentification of wrightiadione (1) has heretofore been unrecognized.

Relative permeability for water and gas through fractures in cement

Relative permeability is an important attribute influencing subsurface multiphase flow. Characterization of relative permeability is necessary to support activities such as carbon sequestration, geothermal energy production, and oil and gas exploration. Previous research efforts have largely neglected the relative permeability of wellbore cement used to seal well bores where risks of leak are significant. Therefore this study was performed to evaluate fracturing on permeability and relative permeability of wellbore cement. Studies of relative permeability of water and air were conducted using ordinary Portland cement paste cylinders having fracture networks that exhibited a range of permeability values. The measured relative permeability was compared with three models, 1) Corey-curve, often used for modeling relative permeability in porous media, 2) X-curve, commonly used to represent relative permeability of fractures, and 3) Burdine model based on fitting the Brooks-Corey function to fracture saturation-pressure data inferred from x-ray computed tomography (XCT) derived aperture distribution results. Experimentally-determined aqueous relative permeability was best described by the Burdine model. Though water phase tended to follow the Corey-curve for the simple fracture system while air relative permeability was best described by the X-curve.

Improving network inference algorithms using resampling methods

Background

Relatively small changes to gene expression data dramatically affect co-expression networks inferred from that data which, in turn, can significantly alter the subsequent biological interpretation. This error propagation is an underappreciated problem that, while hinted at in the literature, has not yet been thoroughly explored. Resampling methods (e.g. bootstrap aggregation, random subspace method) are hypothesized to alleviate variability in network inference methods by minimizing outlier effects and distilling persistent associations in the data. But the efficacy of the approach assumes the generalization from statistical theory holds true in biological network inference applications.

Results

We evaluated the effect of bootstrap aggregation on inferred networks using commonly applied network inference methods in terms of stability, or resilience to perturbations in the underlying expression data, a metric for accuracy, and functional enrichment of edge interactions.

Conclusion

Bootstrap aggregation results in improved stability and, depending on the size of the input dataset, a marginal improvement to accuracy assessed by each method’s ability to link genes in the same functional pathway.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2402-0) contains supplementary material, which is available to authorized users.

Comparison of realistic and idealized breathing patterns in computational models of airflow and vapor dosimetry in the rodent upper respiratory tract

CONTEXT

Computational fluid dynamics (CFD) simulations of airflows coupled with physiologically based pharmacokinetic (PBPK) modeling of respiratory tissue doses of airborne materials have traditionally used either steady-state inhalation or a sinusoidal approximation of the breathing cycle for airflow simulations despite their differences from normal breathing patterns.

OBJECTIVE

Evaluate the impact of realistic breathing patterns, including sniffing, on predicted nasal tissue concentrations of a reactive vapor that targets the nose in rats as a case study.

MATERIALS AND METHODS

Whole-body plethysmography measurements from a free-breathing rat were used to produce profiles of normal breathing, sniffing and combinations of both as flow inputs to CFD/PBPK simulations of acetaldehyde exposure.

RESULTS

For the normal measured ventilation profile, modest reductions in time- and tissue depth-dependent areas under the curve (AUC) acetaldehyde concentrations were predicted in the wet squamous, respiratory and transitional epithelium along the main airflow path, while corresponding increases were predicted in the olfactory epithelium, especially the most distal regions of the ethmoid turbinates, versus the idealized profile. The higher amplitude/frequency sniffing profile produced greater AUC increases over the idealized profile in the olfactory epithelium, especially in the posterior region.

CONCLUSIONS

The differences in tissue AUCs at known lesion-forming regions for acetaldehyde between normal and idealized profiles were minimal, suggesting that sinusoidal profiles may be used for this chemical and exposure concentration. However, depending upon the chemical, exposure system and concentration and the time spent sniffing, the use of realistic breathing profiles, including sniffing, could become an important modulator for local tissue dose predictions.

Detecting distance between injected microspheres and target tumor via 3D reconstruction of tissue sections

One treatment increasing in use for solid tumors in the liver is radioembolization via the delivery of (90)Y microspheres to the vascular bed within or near the location of the tumor. It is desirable as part of the treatment for the microspheres to embed preferentially in or near the tumor. This work details an approach for analyzing the deposition of microspheres with respect to the location of the tumor. The approach used is based upon thin-slice serial sectioning of the tissue sample, followed by high resolution imaging, microsphere detection, and 3-D reconstruction of the tumor surface. Distance from the microspheres to the tumor was calculated using a fast deterministic point inclusion method.

In situ casting and imaging of the rat airway tree for accurate 3D reconstruction

The use of anatomically accurate, animal-specific airway geometries is important for understanding and modeling the physiology of the respiratory system. One approach for acquiring detailed airway architecture is to create a bronchial cast of the conducting airways. However, typical casting procedures either do not faithfully preserve the in vivo branching angles or produce rigid casts that when removed for imaging are fragile and thus easily damaged. We address these problems by creating an in situ bronchial cast of the conducting airways in rats that can be subsequently imaged in situ using three-dimensional micro-CT imaging. We also demonstrate that deformations in airway branch angles resulting from the casting procedure are small, and that these angle deformations can be reversed through an interactive adjustment of the segmented cast geometry. Animal work was approved by the Institutional Animal Care and Use Committee of Pacific Northwest National Laboratory.

Validation of the Marijuana Effect Expectancy Questionnaire-Brief

The purpose of this study was to evaluate a brief version of the Marijuana Effect Expectancy Questionnaire (MEEQ; Schafer & Brown, 1991). The original MEEQ was reduced to 6 items (MEEQ-B). Principal component analysis (PCA) was performed and two factors were identified (positive effects and negative effects) accounting for 52.3% of the variance. Internal consistencies (0.42 to 0.60) were slightly lower than those of the original MEEQ. The negative effect expectancy scale correlated with criterion variables that assess marijuana use (p ≤ .05). This measure is a helpful tool for clinicians to use when assessing youth expectancies. Replication across different samples of adjudicated youth is recommended.

Naltrexone and cue exposure with coping and communication skills training for alcoholics: treatment process and 1-year outcomes

BACKGROUND

Promising treatments for alcoholics include naltrexone (NTX), cue exposure combined with urge-specific coping skills training (CET), and communication skills training (CST). This study investigated the effects of combining these elements as treatment adjuncts.

METHODS

A 2 x 2 design investigated the effects of CET combined with CST, as compared with an education and relaxation control treatment, during a 2-week partial hospital program (n = 165) followed by 12 weeks of NTX (50 mg/day) or placebo during aftercare (n = 128). Drinking outcomes were assessed at 3, 6, and 12 months after discharge from the partial hospital. Process measures included urge, self-efficacy (confidence about staying abstinent in risky situations), and self-reported coping skills. Medically eligible alcohol-dependent patients were recruited.

RESULTS

Among those compliant with medication on at least 70% of days, those who received NTX had significantly fewer heavy drinking days and fewer drinks on days that they drank than those receiving placebo during the medication phase but not during the subsequent 9 months. CET/CST-condition patients were significantly less likely to report a relapse day and reported fewer heavy drinking days at the 6- and 12-month follow-ups than patients in the control treatment. Interactions of medication with behavioral treatments were not significant. Process measures showed that NTX resulted in lower weekly urge ratings, and those in CET/CST used more of the prescribed coping skills after treatment, reported fewer cue-elicited urges, and reported more self-efficacy in a posttest role-play test. Drinking reductions at 3, 6, and 12 months correlated with more use of coping skills, lower urge, and higher self-efficacy.

CONCLUSIONS

The results suggest the probable value of keeping alcoholics on NTX for longer periods of time and the importance of increasing compliance with NTX. They also support the earlier promising effects of CET and CST as adjuncts to treatment programs for alcoholics by maintaining treatment gains over at least a year. The value of the urge-specific and general coping skills and of self-efficacy and urge constructs was demonstrated in their association with drinking outcomes.

Risks associated with alcohol-positive status among adolescents in the emergency department: a matched case-control study

OBJECTIVE

The purpose of this study was to examine alcohol use, alcohol-related problems, other risk-taking behaviors, and parental monitoring in adolescents who tested positive for alcohol in an emergency department.

STUDY DESIGN

A matched case-control design was implemented for adolescents presenting to a pediatric emergency department who were screened for alcohol use. An alcohol-positive sample (N = 150) was compared with a matched alcohol-negative sample (N = 150) for alcohol use, alcohol problems, depression, smoking, risk-taking behavior, and parental monitoring.

RESULTS

The alcohol-positive group reported significantly higher drinking frequency, drinking problems, prior alcohol-related injuries, and episodes of driving after drinking and riding with a drinking driver than the alcohol-negative adolescents. The same pattern was true for depressed mood, reckless behaviors, poor grades in school, and daily smoking. The parents of alcohol-positive teens reported their teens had come home intoxicated more often than parents of alcohol-negative teens. There were no differences between parent groups in monitoring of teens.

CONCLUSION

Adolescents who test positive for alcohol in an emergency department are a high-risk group who meet the criteria for indicated prevention. Screening for alcohol abuse is recommended.

Cue exposure with coping skills training and communication skills training for alcohol dependence: 6- and 12-month outcomes

AIMS

Cue exposure treatment (CET) has shown promise in preliminary studies with alcoholics, and Communication Skills Training (CST) has been found beneficial, especially in intensive treatment programs. The aim of the present study was to investigate the effects of CET and CST in a larger controlled study when both were added to intensive treatment programs.

DESIGN AND INTERVENTIONS

A 2 x 2 design investigated the effects of CET with urge coping skills training compared to a meditation-relaxation control, and CST compared to an education control when all were added to intensive treatment programs for alcoholics.

SETTING

The sites were the inpatient or partial hospital substance abuse treatment programs at a private psychiatric hospital, a state-funded residential facility and a VA medical center.

PARTICIPANTS

Patients diagnosed with alcohol dependence without active psychosis were eligible.

MEASUREMENTS

Participants were assessed for quantity and frequency of drinking, alcohol cue-reactivity, responses to high risk simulations and urge specific coping skills.

FINDINGS

Of 100 treated patients, 86% provided 6-month and 84% provided 12-month follow-up data. Patients who received either CET or CST had fewer heavy drinking days in the first 6 months than control patients. In the second 6 months, CET continued to result in fewer heavy drinking days among lapsers and interacted with CST to decrease quantity of alcohol consumed. CST resulted in fewer alcohol-related problems reported at 12 months. CET resulted in greater reductions in urge to drink in a measure of simulated high-risk situations. CET also resulted in greater reports of use of coping strategies during the follow-up, and many of the urge-specific strategies taught in CET were associated with reduced drinking.

CONCLUSIONS

Both CET and CST continue to show promise as elements of comprehensive alcohol treatment programs. Limitations and directions for future research are discussed.

A comparison of knee joint motion patterns between men and women in selected athletic tasks

BACKGROUND

Women have higher non-contact anterior cruciate ligament injury rate than men do in sport activities. Non-contact anterior cruciate ligament injuries frequently occur in sports requiring cutting tasks. Alternated motor control strategies have identified as a potential risk factor for the non-contact anterior cruciate ligament injuries. The purpose of this study was to compare the patterns of knee kinematics and electromyographic activities in running, side-cutting, and cross-cutting between men and women recreational athletes.

METHODS

Three-dimensional kinematic data of the knee and electromyographic data of selected muscles across the knee joint were collected for 11 men and 9 women recreational athletes in running, side-cutting, and cross-cutting. Regression analyses with dummy variables for comparison of knee motion patterns between men and women.

RESULTS

Women tend to have less knee flexion angles, more knee valgus angles, greater quadriceps activation, and lower hamstring activation in comparison to men during the stance phase of each of the three athletic tasks. Literatures suggest these alternated knee motion patterns of women tend to increase the load on the anterior cruciate ligament.

CONCLUSION

Women on average may have certain motor control strategies that may alter their knee motion patterns. Women's altered knee motion patterns may tend to increase the load on the anterior cruciate ligament in the selected athletic tasks, which may contribute to the increased anterior cruciate ligament injury rate among women.

RELEVANCE

Non-contact anterior cruciate ligament injuries frequently occur in sports. Altered motor control strategies and lower extremity motion patterns are likely to play an important role in non-contact anterior cruciate ligament injuries. Non-contact anterior cruciate ligament injuries may be prevented by correcting altered motor control strategies and associated lower extremity motion patterns through certain training programs.

Concurrent versus delayed smoking cessation treatment for persons in early alcohol recovery. A pilot study

This pilot study investigated the efficacy of initiating a smoking cessation intervention early in inpatient treatment for alcohol dependence versus shortly after an inpatient stay. Thirty-six male smokers recruited from an inpatient substance abuse treatment program were randomly assigned to begin smoking cessation either two weeks (concurrent treatment) or six weeks (delayed treatment) after admission to the substance abuse program. Smoking cessation treatment involved three sessions of individual smoking cessation treatment plus eight weeks of transdermal nicotine replacement. Significantly fewer participants began the delayed treatment than the concurrent treatment. Few participants were smoking-abstinent at follow-up, and the timing of treatment onset did not have an impact on smoking outcome. Clinical trials with larger samples may be needed to better evaluate the efficacy of concurrent versus delayed treatment and to test the efficacy of more aggressive interventions with smokers in early alcohol recovery.

Naltrexone's effects on reactivity to alcohol cues among alcoholic men

The mechanisms of naltrexone's effects on urges to drink during abstinence are unclear. Naltrexone may suppress either urges to drink specifically or appetitive responses in general. The effects of naltrexone on cue reactivity to alcoholic and sweet nonalcoholic beverages were investigated. Alcohol-dependent men (N = 53) in treatment received naltrexone (50 mg) or placebo. Four hours later, they received baseline assessment, exposure to fruit juice, and exposure to their usual alcoholic beverage in 3-min trials. Naltrexone reduced urge to drink and self-reported attention to the alcohol cues, not at the initial exposure but after repeated exposures to alcohol cues. Naltrexone reduced negative affect across baseline and alcohol trials. No effects of naltrexone on responses to the nonalcoholic appetitive beverage cues were found, suggesting that general appetite suppression does not mediate the effects of naltrexone on urges.

Predictors of compliance with naltrexone among alcoholics

OBJECTIVE

Naltrexone has been found to be an effective adjunct to treatment to reduce the rate of drinking among alcoholics. However, adherence to the medication has been of considerable concern; the high rates of noncompliance with the medication limits the benefits that could potentially be realized from this pharmacotherapy. Knowledge of predictors of noncompliance could result in interventions targeted at these variables.

METHOD

Participants were 128 alcohol-dependent patients who participated in a clinical placebo-controlled trial of naltrexone. Upon discharge from a 1- to 2-week partial hospital program, patients were randomly placed into 12 weeks of naltrexone (50 mg/day) or placebo (n = 64 per condition). Patients met with a physician and a research assistant weekly for 4 weeks then biweekly for 8 weeks.

RESULTS

Compliance (number of days taking medication) was not predicted by demographic or pretreatment alcohol use variables. Number and severity of side effects in the first week, particularly nausea and fatigue, predicted early termination. Compliance was not predicted by commitment to abstinence or self-efficacy about abstinence, but was greater among patients who believed more strongly that the medication would help them stay sober. Compliance was not predicted by general level of urge to drink during the first week on medication but compliance was greater among those with a higher urge to drink in response to alcohol stimuli in the laboratory.

CONCLUSIONS

Implications for approaches to increase compliance include reducing side effects and increasing patients' beliefs in the efficacy of naltrexone.

Screening adolescents for problem drinking: performance of brief screens against DSM-IV alcohol diagnoses

OBJECTIVE

The performance of three brief screens, the CAGE, TWEAK and Alcohol Use Disorders Identification Test (AUDIT), was evaluated against a DSM-IV diagnosis of alcohol abuse or dependence in an adolescent sample.

METHOD

Adolescents (13-19 years old) who presented to an emergency department for treatment of an injury, and who tested negative for blood alcohol concentration at time of admission, were administered a structured diagnostic interview and modified versions of the CAGE, TWEAK and AUDIT.

RESULTS

Of the 415 adolescents for whom complete data were available, 18% met criteria for a DSM-IV alcohol use disorder according to the Diagnostic Interview Schedule for Children (version 2.3). Teens who reported alcohol use in the last year (n = 261, 58% male, 71% white) were included in analyses that compared the performance of the three screening instruments. Receiver Operating Characteristic analysis indicated that the AUDIT demonstrated the best performance across the range of its cut-scores, with optimal performance at a cut-score of 4. The TWEAK performed optimally at a cut-score of 2 and the CAGE at a cut-score of 1.

CONCLUSIONS

Routine alcohol screening among adolescents seen in a hospital setting is indicated. Two important directions for future research include the identification of adolescent-specific alcohol screening items, and the validation of an adolescent-specific definition of problem drinking that addresses limitations of DSM-IV alcohol diagnoses when applied to adolescents.

Are adolescent smokers dependent on nicotine? A review of the evidence

This paper reviews the empirical literature on adolescent nicotine dependence, withdrawal, and their associated features. Data documenting nicotine dependence scores, diagnoses, and individual features among adolescents are reviewed in detail and compared to observations based on adult smokers. These data are derived from a broad variety of sources, including national surveys, school-based surveys, and smoking cessation studies. Overall, results indicate that one to three out of five adolescent smokers is dependent on nicotine, with some adolescent groups clearly at higher risk for dependence (those who are incarcerated, in vocational schools, daily smokers, and/or heavy smokers). Across studies, data consistently indicate that a large majority (two-thirds or more) of adolescent smokers report experiencing withdrawal symptoms during attempts to quit or reduce their smoking. Craving or strong desire to smoke was the most commonly reported withdrawal symptom in every study reviewed. Although analyses of concurrent validity generally support the dependence and withdrawal findings among adolescents, data on the predictive validity of measures used are needed. Moreover, studies of adolescent tobacco withdrawal rely almost exclusively on retrospective self-report data. Recommendations for enhancing methodology and advancing our understanding of adolescent nicotine dependence and withdrawal are offered.

Measuring nicotine dependence among youth: a review of available approaches and instruments

This paper reviews issues and concepts related to the measurement of nicotine dependence among youth. The primary objectives of this review are to: (1) review the measures of nicotine dependence currently being used; and (2) delineate a future research agenda in an attempt to advance the quality of measurement and instrumentation for this important research endeavor. Existing measures of nicotine dependence, including formal diagnostic interviews, related withdrawal assessments, brief self-report measures, and single-item indicators, are described. While formal diagnostic systems have been considered the 'gold standard' for evaluating dependence clinically, their specific limitations related to use for research purposes are outlined. Each broad class of measure is evaluated in terms of its rationale for use, strengths and limitations, and the extent to which it has successfully been applied to adolescent populations. A research agenda follows in the second section of the paper. In this section, the need for identification and inclusion of a standard set of optimal dependence measures, for enhancement of current measures, and for the onset of a new and comprehensive measures development program is outlined.

The relationship between anxiety levels and outcome of cocaine abuse treatment

Although a number of studies have examined the comorbidity of anxiety disorders and substance use disorders, much less is known about the impact of anxiety symptoms on substance use and on substance abuse treatment outcome. In the current study, we examined how self-reported anxiety levels, as measured by the Spielberger State-Trait Anxiety Inventory, were related to cocaine use variables and patterns following substance abuse treatment. There were 108 patients in substance abuse treatment who met DSM-III-R diagnostic criteria for cocaine abuse or dependence who completed an assessment battery at pretreatment, posttreatment, and 3-month follow-up. State anxiety scores significantly declined from pre- to posttreatment and remained stable into the 3-month follow-up period regardless of relapse status. Trait anxiety was correlated positively with negative consequences due to cocaine use and negatively correlated with days in treatment. State and trait anxiety both were correlated positively with the Alcohol Composite Index of the Addiction Severity Index (ASI). These findings suggest that elevated anxiety scores at pretreatment subside with time, do not require clinical management of associated anxiety symptoms, and may be a temporary by-product of experiencing negative consequences due to recent cocaine use.

Brief intervention for harm reduction with alcohol-positive older adolescents in a hospital emergency department

This study evaluated the use of a brief motivational interview (MI) to reduce alcohol-related consequences and use among adolescents treated in an emergency room (ER) following an alcohol-related event. Patients aged 18 to 19 years (N = 94) were randomly assigned to receive either MI or standard care (SC). Assessment and intervention were conducted in the ER during or after the patient's treatment. Follow-up assessments showed that patients who received the MI had a significantly lower incidence of drinking and driving, traffic violations, alcohol-related injuries, and alcohol-related problems than patients who received SC. Both conditions showed reduced alcohol consumption. The harm-reduction focus of the MI was evident in that MI reduced negative outcomes related to drinking, beyond what was produced by the precipitating event plus SC alone.

Smoking and drinking among alcoholics in treatment: cross-sectional and longitudinal relationships

OBJECTIVE

The relationship between tobacco dependence and alcohol dependence has received considerable scrutiny in the past few years. The present study of alcoholics in treatment for alcoholism extended previous work by investigating the cross-sectional and longitudinal relationships between drinking and smoking variables.

METHOD

Male and female alcoholics (N = 116) completed a standard assessment of smoking and drinking pretreatment followed by a laboratory assessment of reactivity to alcohol cues. Participants' drinking and smoking were evaluated again 6 months following treatment.

RESULTS

(1) Pretreatment tobacco dependence, pretreatment alcohol dependence, urge to smoke and urge to drink were positively correlated; (2) smoking rates and drinking rates were not correlated either before or following treatment; (3) pretreatment smoking history did not predict posttreatment drinking; (4) the rate of smoking declined following treatment for alcoholism for 45% of the smoking patients who completed a 6-month follow-up, independent of relapse status; and (5) relapsers who smoked more heavily also drank less frequently during follow up.

CONCLUSIONS

Consistent but modest cross-sectional relationships between drinking and smoking variables before alcohol treatment decrease after treatment for alcohol dependence. A spontaneous improvement in smoking rate occurs in many (45%), particularly among those who smoked more heavily pretreatment and thus benefit most by the reduction. Directions for future research are discussed.

Electromyographic analysis and energy expenditure of harness supported treadmill walking: implications for knee rehabilitation

Harness supported treadmill ambulation has been recommended for patients as a way of decreasing loads on the healing tissues, conserving energy and reducing pain. We quantified muscle activation levels around the knee and metabolic responses during harness supported treadmill walking. Ten healthy recreational athletes (age 28.9+/-7.8 years) walked on the treadmill (1.34 m/s) for 5 min each at full weight bearing (FWB), 20 and 40% body weight support (BWS). Electromyography (EMG) was monitored for the vastus lateralis, vastus medialis, rectus femoris, biceps femoris, medial hamstrings and the gastrocnemius. Oxygen consumption was collected by open circuit spirometry and the heart rate was collected by a heartwatch. A statistically significant reduction in EMG was found at 40% BWS for the quadriceps. Oxygen consumption decreased by 6% (20% BWS) and by 12% (40% BWS) from FWB (P<0.05). The heart rate was unchanged. BWS ambulation reduces energy cost, but does not significantly alter muscle activation, except for the quadriceps at 40% BWS.

Brief intervention for harm reduction with alcohol-positive older adolescents in a hospital emergency department

This study evaluated the use of a brief motivational interview (MI) to reduce alcohol-related consequences and use among adolescents treated in an emergency room (ER) following an alcohol-related event. Patients aged 18 to 19 years (N = 94) were randomly assigned to receive either MI or standard care (SC). Assessment and intervention were conducted in the ER during or after the patient's treatment. Follow-up assessments showed that patients who received the MI had a significantly lower incidence of drinking and driving, traffic violations, alcohol-related injuries, and alcohol-related problems than patients who received SC. Both conditions showed reduced alcohol consumption. The harm-reduction focus of the MI was evident in that MI reduced negative outcomes related to drinking, beyond what was produced by the precipitating event plus SC alone.

Lower limb stability with ACL impairment

STUDY DESIGN

Repeated measures (3 separate day sessions) to determine test reliability; single-session repeated measures to compare stability between limbs.

OBJECTIVES

To develop a functional test measuring dynamic stability that is capable of differentiating between the injured and uninjured lower limb in 2 populations: (1) people with anterior cruciate ligament deficiency (ACLd) and (2) people with anterior cruciate ligament reconstruction (ACLr), and to establish the reliability of this test.

BACKGROUND

Many functional tests of the lower limb used by clinicians, such as the 1-legged hop for distance, the 1-legged hop for time, the vertical jump, the triple hop for distance, shuttle run, and single-limb standing, do not allow the clinician to discern differences between function in the injured and uninjured limbs.

METHODS AND MEASURES

Twenty-five nonimpaired subjects (14 men, 11 women, aged 31.2 +/- 9.1 years), 11 subjects with ACLr (9 men, 2 women, aged 26.3 +/- 10.4 years), and 13 subjects with ACLd (5 men, 8 women, aged 40.4 +/- 12.6 years) were tested. Twelve nonimpaired subjects participated in 3 testing sessions to determine the reliability of the force plate measures. Ground reaction forces (vertical, medial-lateral, and anterior-posterior) were measured while the subjects performed 1-legged hop and step-down tests onto a force plate. Stability was defined as the ability to transfer the vertical projection of the center of gravity to the supporting base and keep the knee still. A repeated-measures analysis of variance (2-factor; limbs by trials) was used to compare the stability between limbs.

RESULTS

The majority of the measures used to calculate dynamic stability were reliable. Moreover, the data provide normal standards of functional knee stability for step-down and hop tests. In the step-down test, changes in vertical force did identify dysfunction in the injured limb (stabilization time = 1527 +/- 216 ms) compared to the uninjured limb (stabilization time = 892 +/- 498 ms) for subjects with ACLr.

CONCLUSIONS

The normal standards may serve as a reference for comparing functional differences in ACLr or ACLd populations. The vertical force parameter during a step-down may be useful as an outcome measure to monitor progress during rehabilitation.

Naltrexone's effect on cue-elicited craving among alcoholics in treatment

BACKGROUND

Advancing knowledge of biobehavioral effects of interventions can result in improved treatments. Thus, a standardized laboratory cue reactivity assessment has been developed and validated to assess the cognitive and psychophysiological responses to a simulated high-risk situation: alcohol cues. The present study investigates the effects of a pharmacotherapy (naltrexone) on a laboratory-based, cue-elicited urge to drink among abstinent alcoholics in treatment.

METHODS

Alcohol-dependent subjects were randomized to 12 weeks of naltrexone or placebo after completing a partial hospital program. After approximately 1 week on medication, all received cue reactivity assessment.

RESULTS

Significantly fewer patients taking naltrexone reported any urge to drink during alcohol exposure than did those on placebo. Those with any urges reported no decrement in level of the urges. Mean arterial pressure decreased significantly for those on placebo, but not for those on naltrexone, whereas cue-elicited decreases in heart rate were not affected by the medication.

CONCLUSIONS

The results have implications for models of relapse and naltrexone's effects. Cue reactivity methodology has utility for investigating hypothesized mediators of therapeutic effects of pharmacotherapies as well as behavioral treatments.

Effects of naltrexone with nicotine replacement on smoking cue reactivity: preliminary results

Although several studies have examined the effects of opioid antagonists on smoking behavior, there have been no reports of the potentially therapeutic combination of naltrexone and nicotine replacement therapy. The primary objective of the present study was to determine whether naltrexone reduced reactivity to smoking cues among abstinent smokers treated with nicotine replacement. Twenty participants were instructed to abstain from smoking cigarettes for 9 h while using nicotine replacement therapy. Participants were subsequently treated with either naltrexone (50 mg) or placebo before being exposed to smoking cues. Results indicated that the smokers who received the placebo responded to smoking cue exposure with increases in urge to smoke and increases in negative affect. Participants who received naltrexone did not show any increase in urge or negative affect and showed a decrease in withdrawal symptoms after exposure to smoking cues. Although preliminary, the findings suggest that naltrexone may work in combination with nicotine replacement therapies to block the effects of smoking stimuli in abstinent smokers.

Effect of inactivation of gtf genes on adherence of Streptococcus downei

The activity of glucosyltransferases (GTF), a group of enzymes that synthesize water-soluble and -insoluble glucans from sucrose, significantly contributes to the cariogenicity of mutans streptococci. Streptococcus downei produces four glucosyltransferases, GTFI, which produces insoluble glucan, and GTFS, GTFT, and GTFU, which synthesize soluble glucans. We have previously reported that inactivation of gtfS results in altered adherence and have now examined its interaction with other enzymes by constructing mutants which were gtfS, gtfS/gtfT, gtfS/gtfI and gtfI. The mutants were tested for their ability to accumulate on wires and on plastic microtiter trays in the presence of sucrose. The gtfS mutant displayed a reduced ability to adhere compared to the wild type but there was no further reduction of adherence in a gtfS/gtfT mutant. In contrast, the gtfS/gtfI double mutant showed a drastic reduction in adherence and when gtfI alone was inactivated, bacteria were unable to adhere to a hard surface. The results confirmed that insoluble glucan is required for strong adherence to a smooth surface but that the amount and structure of this glucan is dependent upon the availability of soluble glucans to act as primer molecules.

Brief motivational interviewing in a hospital setting for adolescent smoking: a preliminary study

This study tested the feasibility and efficacy of a brief smoking intervention for adolescents in a hospital setting. Forty adolescent patients were randomized to receive either brief advice or a motivational interview, a nonconfrontational therapeutic intervention. Feasibility of brief smoking interventions with teen patients was supported by high rates of recruitment, retention, and quit attempts, and long periods of continuous abstinence. Although between-groups differences on smoking measures were not significant at 3-month follow-up, an effect size of h = .28 was noted. The sample showed significant decreases in smoking dependence and number of days smoked. Baseline stage of change, smoking rate, and depression were significant prospective predictors of smoking outcome. Implications for smoking intervention research with adolescents are discussed.

Detection of alcohol use in adolescent patients in the emergency department

OBJECTIVES

To examine 3 methods of detecting alcohol use among adolescent patients visiting a Level-1 regional trauma center.

METHODS

Part 1 was a retrospective review of laboratory records and (13- to 19-year-old) patient medical records over the 1-year period from August 1993 to July 1994. Part 2 was a review of ICD-9 discharge diagnoses for the same age range during the same 1-year period. Part 3 involved prospective saliva alcohol testing of injured patients aged 13-17 years old.

RESULTS

Part 1: A total of 522 blood tests were conducted and 160 (30.6%) were positive for alcohol. More than one-third of the alcohol-positive sample had alcohol ingestion as the only reason for their visits, i.e., they were uninjured. The alcohol-positive group was more likely to be male and older. Part 2: A total of 99 alcohol-related discharge diagnoses were given to adolescent patients. Alcohol abuse was the most common diagnosis. With the 2 methods of detection combined, 186 patients were identified. Part 3: A total of 119 saliva alcohol tests were conducted. One patient tested positive but had been identified while in triage as having used alcohol.

CONCLUSION

In this study population, approximately one-third of adolescent patients tested for alcohol as part of routine clinical care were alcohol-positive but were not necessarily given an alcohol-related diagnosis. Thus, studies determining rates of alcohol-positive adolescents treated in EDs should use multiple methods of detection. Universal testing does not appear to be warranted for all injured adolescent patients.

Brief motivational interviewing in a hospital setting for adolescent smoking: a preliminary study

This study tested the feasibility and efficacy of a brief smoking intervention for adolescents in a hospital setting. Forty adolescent patients were randomized to receive either brief advice or a motivational interview, a nonconfrontational therapeutic intervention. Feasibility of brief smoking interventions with teen patients was supported by high rates of recruitment, retention, and quit attempts, and long periods of continuous abstinence. Although between-groups differences on smoking measures were not significant at 3-month follow-up, an effect size of h = .28 was noted. The sample showed significant decreases in smoking dependence and number of days smoked. Baseline stage of change, smoking rate, and depression were significant prospective predictors of smoking outcome. Implications for smoking intervention research with adolescents are discussed.

Germacrene C synthase from Lycopersicon esculentum cv. VFNT cherry tomato: cDNA isolation, characterization, and bacterial expression of the multiple product sesquiterpene cyclase

Germacrene C was found by GC-MS and NMR analysis to be the most abundant sesquiterpene in the leaf oil of Lycopersicon esculentum cv. VFNT Cherry, with lesser amounts of germacrene A, guaia-6,9-diene, germacrene B, beta-caryophyllene, alpha-humulene, and germacrene D. Soluble enzyme preparations from leaves catalyzed the divalent metal ion-dependent cyclization of [1-3H]farnesyl diphosphate to these same sesquiterpene olefins, as determined by radio-GC. To obtain a germacrene synthase cDNA, a set of degenerate primers was constructed based on conserved amino acid sequences of related terpenoid cyclases. With cDNA prepared from leaf epidermis-enriched mRNA, these primers amplified a 767-bp fragment that was used as a hybridization probe to screen the cDNA library. Thirty-one clones were evaluated for functional expression of terpenoid cyclase activity in Escherichia coli by using labeled geranyl, farnesyl, and geranylgeranyl diphosphates as substrates. Nine cDNA isolates expressed sesquiterpene synthase activity, and GC-MS analysis of the products identified germacrene C with smaller amounts of germacrene A, B, and D. None of the expressed proteins was active with geranylgeranyl diphosphate; however, one truncated protein converted geranyl diphosphate to the monoterpene limonene. The cDNA inserts specify a deduced polypeptide of 548 amino acids (Mr = 64,114), and sequence comparison with other plant sesquiterpene cyclases indicates that germacrene C synthase most closely resembles cotton delta-cadinene synthase (50% identity).