Gene Expression in Cord Blood and Tuberculosis in Early Childhood: A Nested Case-Control Study in a South African Birth Cohort.

BACKGROUND: Transcriptomic profiling of adults with tuberculosis (TB) has become increasingly common, predominantly for diagnostic and risk prediction purposes. However, few studies have evaluated signatures in children, particularly in identifying those at risk for developing TB disease. We investigated the relationship between gene expression obtained from umbilical cord blood and both tuberculin skin test conversion and incident TB disease through the first 5 years of life. METHODS: We conducted a nested case-control study in the Drakenstein Child Health Study, a longitudinal, population-based birth cohort in South Africa. We applied transcriptome-wide screens to umbilical cord blood samples from neonates born to a subset of selected mothers (N = 131). Signatures identifying tuberculin conversion and risk of subsequent TB disease were identified from genome-wide analysis of RNA expression. RESULTS: Gene expression signatures revealed clear differences predictive of tuberculin conversion (n = 26) and TB disease (n = 10); 114 genes were associated with tuberculin conversion and 30 genes were associated with the progression to TB disease among children with early infection. Coexpression network analysis revealed 6 modules associated with risk of TB infection or disease, including a module associated with neutrophil activation in immune response (P < .0001) and defense response to bacterium (P < .0001). CONCLUSIONS: These findings suggest multiple detectable differences in gene expression at birth that were associated with risk of TB infection or disease throughout early childhood. Such measures may provide novel insights into TB pathogenesis and susceptibility.

Getting the MOST out of follow-up: a randomized controlled trial comparing 3 monthly nurse led follow-up via telehealth, including monitoring CA125 and patient reported outcomes using the MOST (Measure of Ovarian Symptoms and Treatment concerns) with routine clinic based or telehealth follow-up, after completion of first line chemotherapy in patients with epithelial ovarian cancer.

BACKGROUND: Physical symptoms, anxiety, depression, fear of recurrence, sexual dysfunction, and social withdrawal are common in women after treatment for ovarian cancer. Most patients would like and need help dealing with these symptoms. The traditional model of follow-up care is unstructured and largely focused on diagnosing recurrent disease, and most oncologists lack skills to identify and manage psychosocial issues. No high quality prospective clinical trials have been conducted to determine the optimal follow-up regimen or the cost effectiveness of ovarian cancer surveillance strategies. PRIMARY OBJECTIVES: To assess emotional wellbeing, acceptability, safety, and cost effectiveness of nurse led follow-up via telehealth for women with ovarian cancer following completion of primary treatment. STUDY HYPOTHESIS: We hypothesize that compared with routine clinic based follow-up, nurse led follow-up via telehealth, including serum CA125 monitoring and completion of a patient reported outcome instrument, the Measure of Ovarian Symptoms and Treatment concerns-Surveillance (MOST-S26), will improve emotional wellbeing in women with ovarian cancer; be feasible, safe, acceptable, and not delay the time to diagnosis of recurrent disease; will result in greater patient satisfaction; will identify more patients with psychological distress, lead to better care, and improved psychological outcomes; and be cost-effective. TRIAL DESIGN: Phase II multicenter randomized trial comparing 3 monthly nurse led telehealth consultations that include serum CA125 monitoring and completion of the MOST-S26, with routine clinic based follow-up. The allocation ratio will be 1:1. MAJOR INCLUSION/EXCLUSION CRITERIA: Eligible patients will be women with high grade epithelial ovarian cancer who have normalized serum CA125 (to <35 kU/L) at completion of first line chemotherapy. PRIMARY ENDPOINTS: Emotional wellbeing at 12 months. SAMPLE SIZE: 150 patients. ESTIMATED DATES FOR COMPLETING ACCRUAL AND PRESENTING RESULTS: July 2023. Results expected in 2025, 24 months after the last participant is enrolled. TRIAL REGISTRATION: ACTRN12620000332921.

Mapping and Monitoring Zero-Deforestation Commitments.

A growing number of companies have announced zero-deforestation commitments (ZDCs) to eliminate commodities produced at the expense of forests from their supply chains. Translating these aspirational goals into forest conservation requires forest mapping and monitoring (M&M) systems that are technically adequate and therefore credible, salient so that they address the needs of decision makers, legitimate in that they are fair and unbiased, and scalable over space and time. We identify 12 attributes of M&M that contribute to these goals and assess how two prominent ZDC programs, the Amazon Soy Moratorium and the High Carbon Stock Approach, integrate these attributes into their M&M systems. These programs prioritize different attributes, highlighting fundamental trade-offs in M&M design. Rather than prescribe a one-size-fits-all solution, we provide policymakers and practitioners with guidance on the design of ZDC M&M systems that fit their specific use case and that may contribute to more effective implementation of ZDCs.

Investigating Bacterial Volatilome for the Classification and Identification of Mycobacterial Species by HS-SPME-GC-MS and Machine Learning.

Species of Mycobacteriaceae cause disease in animals and humans, including tuberculosis and leprosy. Individuals infected with organisms in the Mycobacterium tuberculosis complex (MTBC) or non-tuberculous mycobacteria (NTM) may present identical symptoms, however the treatment for each can be different. Although the NTM infection is considered less vital due to the chronicity of the disease and the infrequency of occurrence in healthy populations, diagnosis and differentiation among Mycobacterium species currently require culture isolation, which can take several weeks. The use of volatile organic compounds (VOCs) is a promising approach for species identification and in recent years has shown promise for use in the rapid analysis of both in vitro cultures as well as ex vivo diagnosis using breath or sputum. The aim of this contribution is to analyze VOCs in the culture headspace of seven different species of mycobacteria and to define the volatilome profiles that are discriminant for each species. For the pre-concentration of VOCs, solid-phase micro-extraction (SPME) was employed and samples were subsequently analyzed using gas chromatography-quadrupole mass spectrometry (GC-qMS). A machine learning approach was applied for the selection of the 13 discriminatory features, which might represent clinically translatable bacterial biomarkers.

Smallholder perceptions of land restoration activities: rewetting tropical peatland oil palm areas in Sumatra, Indonesia.

The Indonesian government committed to restoring over 2 million ha of degraded peatland by the end of 2020, mainly to reduce peat fires and greenhouse gas emissions. Although it is unlikely the government will meet this target, restoration projects are still underway. One restoration strategy involves blocking peatland drainage canals, but the consequences of this for smallholder farmers whose livelihoods are dependent on agriculture are unclear. This paper investigates perceived impacts of canal blocks on smallholder farmers and identifies factors that affect their willingness to accept canal blocks on their land. We use data from 181 household questionnaires collected in 2018 across three villages in Jambi province, Sumatra. We found that the majority of respondents would accept canal blocks on their farms, perceiving that the blocks would have no impact on yields or farm access, and would decrease fire risk. Respondents who would not accept blocks on their farms were more likely to use canals to access their farms and perceive that canal blocks would decrease yields. The majority of farmers unwilling to accept canal blocks did not change their mind when provided with an option of a block that would allow boat travel. Our results improve understanding of why some smallholders may be unwilling to engage with peatland restoration. Further research is needed to understand the impact of canal blocks on smallholders' yields. Engaging with stakeholders from the outset to understand farmers' concerns, and perceptions is key if the government is to succeed in meeting its peatland restoration target and to ensure that the costs and benefits of restoration are evenly shared between local stakeholders and other actors. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10113-020-01737-z.

Incorporating connectivity into conservation planning for the optimal representation of multiple species and ecosystem services.

Conservation planning tends to focus on protecting species' ranges or landscape connectivity but seldom both-particularly in the case of diverse taxonomic assemblages and multiple planning goals. Therefore, information on potential trade-offs between maintaining landscape connectivity and achieving other conservation objectives is lacking. We developed an optimization approach to prioritize the maximal protection of species' ranges, ecosystem types, and forest carbon stocks, while also including habitat connectivity for range-shifting species and dispersal corridors to link protected area. We applied our approach to Sabah, Malaysia, where the state government mandated an increase in protected-area coverage of approximately 305,000 ha but did not specify where new protected areas should be. Compared with a conservation planning approach that did not incorporate the 2 connectivity features, our approach increased the protection of dispersal corridors and elevational connectivity by 13% and 21%, respectively. Coverage of vertebrate and plant species' ranges and forest types were the same whether connectivity was included or excluded. Our approach protected 2% less forest carbon and 3% less butterfly range than when connectivity features were not included. Hence, the inclusion of connectivity into conservation planning can generate large increases in the protection of landscape connectivity with minimal loss of representation of other conservation targets.

Incorporación de la Conectividad a la Planeación de la Conservación para la Representación Óptima de Especies Múltiples y Servicios Ambientales Resumen Las tendencias de planeación de la conservación tienden a enfocarse en la protección de la distribución geográfica de las especies o en la conectividad de paisajes, pero rara vez se enfocan en ambas - particularmente para el caso de los ensamblajes taxonómicos y las metas múltiples de planeación. Por lo tanto, hay carencias en la información sobre las compensaciones potenciales entre mantener la conectividad de los paisajes y alcanzar otros objetivos de conservación. Desarrollamos una estrategia de optimización para priorizar la protección máxima de la distribución de las especies, los tipos de ecosistemas y los stocks de carbono de los bosques, a la vez que incluimos la conectividad del hábitat para las especies que modifican su distribución y los corredores de dispersión para conectar el área protegida. Aplicamos nuestra estrategia en Sabah, Malasia, en donde el gobierno estatal ordenó un incremento de ∼305, 000 ha en la cobertura de áreas protegidas sin especificar la ubicación de las nuevas áreas protegidas. En comparación con una estrategia de planeación de la conservación que no incorporó las dos características de la conectividad, nuestra estrategia incrementó la protección de los corredores de dispersión y la conectividad altitudinal en un 13% y 21% respectivamente. La cobertura de la distribución de las especies de plantas y vertebrados y de los tipos de bosque fue la misma con o sin la inclusión de la conectividad. Nuestra estrategia protegió 2% menos del carbono forestal y 3% menos de la distribución de mariposas que cuando no se incluyeron las características de conectividad en la estrategia. Por lo tanto, incluir a la conectividad en la planeación de la conservación puede generar grandes incrementos en la protección de la conectividad del paisaje con una pérdida mínima de representación para los demás objetivos de conservación.

Teacher perceptions of sun protection practices in the secondary school setting: Barriers, enablers and recommendations for future.

OBJECTIVE: This qualitative study aimed to explore sun protection barriers and enablers in secondary schools in Victoria. METHODS: Five focus groups were conducted with nominated Health or Physical Education (PE) Coordinators (or other staff representatives) from schools in metropolitan and regional Victoria. Discussions were audio-recorded, transcribed and coded thematically. RESULTS: Participants identified the need for regulatory influences that included minimum standards for sun protection policy, training and shade in the built environment. Participants perceived that sun protection is not always acknowledged to be a duty of care in secondary schools. A crowded health and well-being curriculum, a focus on fostering independence, and challenges overcoming peer norms were perceived to be important contextual influences. At an organisational level, strong leadership and a united approach among staff were identified as critical ingredients for successful policy implementation and organisational change. Several potentially effective strategies were proposed, including increased shade, leveraging from student leaders, normalising sun protection practices and prioritising staff role modelling. CONCLUSIONS: A cultural shift is required for many schools to accept and act on sun protection as a duty of care. A comprehensive approach that includes regulatory action, healthy school policies and leading by example may help protect students and staff from harmful UV exposure during school hours. SO WHAT?: Without regulatory support, strong leadership is required to implement and enforce sun protection practices within schools. Health promotion programs could assist schools to trial and evaluate the sun protection strategies that involve student-led solutions, role modelling and increasing shade.

Breath metabolome of mice infected with Pseudomonas aeruginosa.

INTRODUCTION: The measurement of specific volatile organic compounds in breath has been proposed as a potential diagnostic for a variety of diseases. The most well-studied bacterial lung infection in the breath field is that caused by Pseudomonas aeruginosa. OBJECTIVES: To determine a discriminatory core of molecules in the "breath-print" of mice during a lung infection with four strains of P. aeruginosa (PAO1, PA14, PAK, PA7). Furthermore, we attempted to extrapolate a strain-specific "breath-print" signature to investigate the possibility of recapitulating the genetic phylogenetic groups (Stewart et al. Pathog Dis 71(1), 20-25, 2014. https://doi.org/10.1111/2049-632X.12107 ). METHODS: Breath was collected into a Tedlar bag and shortly after drawn into a thermal desorption tube. The latter was then analyzed into a comprehensive multidimensional gas chromatography coupled with a time-of-flight mass spectrometer. Random forest algorithm was used for selecting the most discriminatory features and creating a prediction model. RESULTS: Three hundred and one molecules were significantly different between animals infected with P. aeruginosa, and those given a sham infection (PBS) or inoculated with UV-killed P. aeruginosa. Of those, nine metabolites could be used to discriminate between the three groups with an accuracy of 81%. Hierarchical clustering showed that the signature from breath was due to a specific response to live bacteria instead of a generic infection response. Furthermore, we identified ten additional volatile metabolites that could differentiate mice infected with different strains of P. aeruginosa. A phylogram generated from the ten metabolites showed that PAO1 and PA7 were the most distinct group, while PAK and PA14 were interspersed between the former two groups. CONCLUSIONS: To the best of our knowledge, this is the first study to report on a 'core' murine breath print, as well as, strain level differences between the compounds in breath. We provide identifications (by running commercially available analytical standards) to five breath compounds that are predictive of P. aeruginosa infection.

Tropical forests are thermally buffered despite intensive selective logging.

Tropical rainforests are subject to extensive degradation by commercial selective logging. Despite pervasive changes to forest structure, selectively logged forests represent vital refugia for global biodiversity. The ability of these forests to buffer temperature-sensitive species from climate warming will be an important determinant of their future conservation value, although this topic remains largely unexplored. Thermal buffering potential is broadly determined by: (i) the difference between the "macroclimate" (climate at a local scale, m to ha) and the "microclimate" (climate at a fine-scale, mm to m, that is distinct from the macroclimate); (ii) thermal stability of microclimates (e.g. variation in daily temperatures); and (iii) the availability of microclimates to organisms. We compared these metrics in undisturbed primary forest and intensively logged forest on Borneo, using thermal images to capture cool microclimates on the surface of the forest floor, and information from dataloggers placed inside deadwood, tree holes and leaf litter. Although major differences in forest structure remained 9-12 years after repeated selective logging, we found that logging activity had very little effect on thermal buffering, in terms of macroclimate and microclimate temperatures, and the overall availability of microclimates. For 1°C warming in the macroclimate, temperature inside deadwood, tree holes and leaf litter warmed slightly more in primary forest than in logged forest, but the effect amounted to <0.1°C difference between forest types. We therefore conclude that selectively logged forests are similar to primary forests in their potential for thermal buffering, and subsequent ability to retain temperature-sensitive species under climate change. Selectively logged forests can play a crucial role in the long-term maintenance of global biodiversity.

Investigation of mycobacteria fatty acid profile using different ionization energies in GC-MS.

Gas chromatography (GC) coupled with electron ionization (EI) mass spectrometry (MS) is a well-established technique for the analysis of volatile and semi-volatile compounds. The main advantage is the highly repeatable fragmentation of the compounds into the ion source, generating intense and diagnostic fragmentation when the ionization is performed at 70 eV; this is considered the standard ionization condition and has been used for creating many established databases, which are of great support in the analyte identification process. However, such an intense fragmentation often causes the loss of the molecular ion or more diagnostic ions, which can be detrimental for the identification of homologous series or isomers, as for instance fatty acids. To obtain this information chemical or soft ionization can be used, but dedicated ion sources and conditions are required. In this work, we explored different ionization voltages in GC-EI-MS to preserve the intensity of the molecular ion using a conventional quadrupole MS. Twenty, 30, 50, and 70 eV were tested using a mixture of fatty acid methyl esters standards. Intensity and repeatability of the most informative ions were compared. Twenty and 70 eV were then used to analyze the fatty acid composition of six different strains of mycobacteria. Two approaches were used for elaborating the data: (1) a single average spectrum of the entire chromatogram was derived, which can be considered (in terms of concept) as a direct EI-MS analysis; (2) the actual chromatographic separation of the compounds was considered after automatic alignment. The results obtained are discussed herein. Graphical abstract ᅟ.

Volatile metabolic diversity of Klebsiella pneumoniae in nutrient-replete conditions.

INTRODUCTION: Microorganisms catabolize carbon-containing compounds in their environment during growth, releasing a subset of metabolic byproducts as volatile compounds. However, the relationship between growth media and the production of volatile compounds has been largely unexplored to-date. OBJECTIVES: To assess the core and media-specific components of the Klebsiella pneumoniae volatile metabolome via growth in four in vitro culture media. METHODS: Headspace volatiles produced by cultures of K. pneumoniae after growth to stationary phase in four rich media (brain heart infusion broth, lysogeny broth, Mueller-Hinton broth, and tryptic soy broth) were analyzed using comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS). Differences in the composition of headspace volatiles as a function of growth media was assessed using hierarchical clustering analysis (HCA) and principal component analysis (PCA). RESULTS: A total of 365 volatile compounds were associated with the growth of K. pneumoniae across all media, of which 36 (10 %) were common to all growth media, and 148 (41 %) were specific to a single medium. In addition, utilizing all K. pneumoniae-associated volatile compounds, strains clustered as a function of growth media, demonstrating the importance of media in determining the metabolic profile of this organism. CONCLUSION: K. pneumoniae produces a core suite of volatile compounds across all growth media studied, although the volatile metabolic signature of this organism is fundamentally media-dependent.

Estimation of start and stop numbers for cluster resolution feature selection algorithm: an empirical approach using null distribution analysis of Fisher ratios.

Cluster resolution feature selection (CR-FS) is a hybrid feature selection algorithm which involves the evaluation of ranked variables via sequential backward elimination (SBE) and sequential forward selection (SFS). The implementation of CR-FS requires two main inputs, namely, start and stop number. The start number is the number of the highly ranked variables for the SBE while the stop number is the point at which the search for additional features during the SFS stage is halted. The setting of these critical parameters has always relied on trial and error which introduced subjectivity in the results obtained. The start and stop numbers are known to vary with each dataset. Drawing inspiration from overlapping coefficients, a method for comparing two probability density functions, empirical equations toward the estimation of start and stop number for a dataset were developed. All of the parameters in the empirical equations are obtained from the comparisons of the two probability density functions except the constant termed d. The equations were optimized using three real-world datasets. The optimum range of d was determined to be 0.48 to 0.57. An implementation of CR-FS using two new datasets demonstrated the validity of this approach. Partial least squares discriminant analysis (PLS-DA) model prediction accuracies increased from 90 and 96 to 100% for both datasets using start and stop numbers calculated with this approach. Additionally, there was a twofold increase in the explained variance captured in the first two principal components. Graphical abstract Here, we describe how to determine the start and stop numbers for an automated feature selection routine, ensuring that you get the best model you can for your data with minimal effort.

Mapping regional risks from climate change for rainfed rice cultivation in India.

Global warming is predicted to increase in the future, with detrimental consequences for rainfed crops that are dependent on natural rainfall (i.e. non-irrigated). Given that many crops grown under rainfed conditions support the livelihoods of low-income farmers, it is important to highlight the vulnerability of rainfed areas to climate change in order to anticipate potential risks to food security. In this paper, we focus on India, where ~ 50% of rice is grown under rainfed conditions, and we employ statistical models (climate envelope models (CEMs) and boosted regression trees (BRTs)) to map changes in climate suitability for rainfed rice cultivation at a regional level (~ 18 × 18 km cell resolution) under projected future (2050) climate change (IPCC RCPs 2.6 and 8.5, using three GCMs: BCC-CSM1.1, MIROC-ESM-CHEM, and HadGEM2-ES). We quantify the occurrence of rice (whether or not rainfed rice is commonly grown, using CEMs) and rice extent (area under cultivation, using BRTs) during the summer monsoon in relation to four climate variables that affect rice growth and yield namely ratio of precipitation to evapotranspiration (PER), maximum and minimum temperatures (Tmax and Tmin ), and total rainfall during harvesting. Our models described the occurrence and extent of rice very well (CEMs for occurrence, ensemble AUC = 0.92; BRTs for extent, Pearson's r = 0.87). PER was the most important predictor of rainfed rice occurrence, and it was positively related to rainfed rice area, but all four climate variables were important for determining the extent of rice cultivation. Our models project that 15%-40% of current rainfed rice growing areas will be at risk (i.e. decline in climate suitability or become completely unsuitable). However, our models project considerable variation across India in the impact of future climate change: eastern and northern India are the locations most at risk, but parts of central and western India may benefit from increased precipitation. Hence our CEM and BRT models agree on the locations most at risk, but there is less consensus about the degree of risk at these locations. Our results help to identify locations where livelihoods of low-income farmers and regional food security may be threatened in the next few decades by climate changes. The use of more drought-resilient rice varieties and better irrigation infrastructure in these regions may help to reduce these impacts and reduce the vulnerability of farmers dependent on rainfed cropping.

Use of a Multiplex Transcript Method for Analysis of Pseudomonas aeruginosa Gene Expression Profiles in the Cystic Fibrosis Lung.

The discovery of therapies that modulate Pseudomonas aeruginosa virulence or that can eradicate chronic P. aeruginosa lung infections associated with cystic fibrosis (CF) will be advanced by an improved understanding of P. aeruginosa behavior in vivo We demonstrate the use of multiplexed Nanostring technology to monitor relative abundances of P. aeruginosa transcripts across clinical isolates, in serial samples, and for the purposes of comparing microbial physiology in vitro and in vivo The expression of 75 transcripts encoded by genes implicated in CF lung disease was measured in a variety of P. aeruginosa strains as well as RNA serial sputum samples from four P. aeruginosa-colonized subjects with CF collected over 6 months. We present data on reproducibility, the results from different methods of normalization, and demonstrate high concordance between transcript relative abundance data obtained by Nanostring or transcriptome sequencing (RNA-Seq) analysis. Furthermore, we address considerations regarding sequence variation between strains during probe design. Analysis of P. aeruginosa grown in vitro identified transcripts that correlated with the different phenotypes commonly observed in CF clinical isolates. P. aeruginosa transcript profiles in RNA from CF sputum indicated alginate production in vivo, and transcripts involved in quorum-sensing regulation were less abundant in sputum than strains grown in the laboratory. P. aeruginosa gene expression patterns from sputum clustered closely together relative to patterns for laboratory-grown cultures; in contrast, laboratory-grown P. aeruginosa showed much greater transcriptional variation with only loose clustering of strains with different phenotypes. The clustering within and between subjects was surprising in light of differences in inhaled antibiotic and respiratory symptoms, suggesting that the pathways represented by these 75 transcripts are stable in chronic CF P. aeruginosa lung infections.

Macro- and microclimatic interactions can drive variation in species' habitat associations.

Many species are more restricted in their habitat associations at the leading edges of their range margins, but some species have broadened their habitat associations in these regions during recent climate change. We examine the effects of multiple, interacting climatic variables on spatial and temporal patterns of species' habitat associations, using the speckled wood butterfly, Pararge aegeria, in Britain, as our model taxon. Our analyses reveal that this species, traditionally regarded as a woodland-dependent insect, is less restricted to woodland in regions with warmer winters and warmer and wetter summers. In addition, over the past 40 years of climate change, the species has become less restricted to woodland in locations where temperature and summer rainfall have increased most. We show that these patterns arise mechanistically because larval growth rates are slower in open (i.e. nonwoodland) habitats associated with colder microclimates in winter and greater host plant desiccation in summer. We conclude that macro- and microclimatic interactions drive variation in species' habitat associations, which for our study species resulted predominantly in a widening of habitat associations under climate change. However, species vary in their climatic and nonclimatic requirements, and so complex spatial and temporal patterns of changes in habitat associations are likely to be observed in future as the climate changes.

Elastin degradation product isodesmosine is a chemoattractant for Pseudomonas aeruginosa.

Previous studies have demonstrated that Pseudomonas aeruginosa PAO1 is chemotactic towards proteinogenic amino acids, however, the chemotaxis response of this strain towards non-proteinogenic amino acids and the specific chemoreceptors involved in this response are essentially unknown. In this study, we analysed the chemotactic response of PAO1 towards two degradation products of elastin, the lysine-rich, non-proteinogenic amino acids, desmosine and isodesmosine. We observed that isodesmosine, a potential biomarker for different diseases, served as a chemoattractant for PAO1. A screen of 251methyl-accepting chemotaxis proteins mutants of PAO1 identified PctA as the chemoreceptor for isodesmosine. We also showed that the positive chemotactic response to isodesmosine is potentially common by demonstrating chemoattraction in 12 of 15 diverse (in terms of source of isolation) clinical isolates, suggesting that the chemotactic response to this non-proteinogenic amino acid might be a conserved feature of acute infection isolates and thus could influence the colonization of potential infection sites.

Breathprints of model murine bacterial lung infections are linked with immune response.

In this model study, we explored the host's contribution of breath volatiles to diagnostic secondary electrospray ionisation-mass spectrometry (SESI-MS) breathprints for acute bacterial lung infections, their correlation with the host's immune response, and their use in identifying the lung pathogen. Murine airways were exposed to Pseudomonas aeruginosa and Staphylococcus aureus bacterial cell lysates or to PBS (controls), and their breath and bronchoalveolar lavage fluid (BALF) were collected at six time points (from 6 to 120 h) after exposure. Five to six mice per treatment group and four to six mice per control group were sampled at each time. Breath volatiles were analysed using SESI-MS and the BALF total leukocytes, polymorphonuclear neutrophils, lactate dehydrogenase activity, and cytokine concentrations were quantified. Lysate exposure breathprints contain host volatiles that persist for up to 120 h; are pathogen specific; are unique from breathprints of controls, active infections and cleared infections; and are correlated with the host's immune response. Bacterial lung infections induce changes to the host's breath volatiles that are selective and specific predictors of the source of infection. Harnessing the pathogen-specific volatiles in the host's breath may provide useful information for detecting latent bacterial lung infections and managing the spread of respiratory diseases.

Editorial: new analytical and statistical approaches for interpreting the relationships among environmental stressors and biomarkers.

The broad topic of biomarker research has an often-overlooked component: the documentation and interpretation of the surrounding chemical environment and other meta-data, especially from visualization, analytical and statistical perspectives. A second concern is how the environment interacts with human systems biology, what the variability is in "normal" subjects, and how such biological observations might be reconstructed to infer external stressors. In this article, we report on recent research presentations from a symposium at the 248th American Chemical Society meeting held in San Francisco, 10-14 August 2014, that focused on providing some insight into these important issues.

The role of gluconate production by Pseudomonas spp. in the mineralization and bioavailability of calcium-phytate to Nicotiana tabacum.

Organic phosphorus (P) is abundant in most soils but is largely unavailable to plants. Pseudomonas spp. can improve the availability of P to plants through the production of phytases and organic anions. Gluconate is a major component of Pseudomonas organic anion production and may therefore play an important role in the mineralization of insoluble organic P forms such as calcium-phytate (CaIHP). Organic anion and phytase production was characterized in 2 Pseudomonas spp. soil isolates (CCAR59, Ha200) and an isogenic mutant of strain Ha200, which lacked a functional glucose dehydrogenase (Gcd) gene (strain Ha200 gcd::Tn5B8). Wild-type and mutant strains of Pseudomonas spp. were evaluated for their ability to solubilize and hydrolyze CaIHP and to promote the growth and assimilation of P by tobacco plants. Gluconate, 2-keto-gluconate, pyruvate, ascorbate, acetate, and formate were detected in Pseudomonas spp. supernatants. Wild-type pseudomonads containing a functional gcd could produce gluconate and mineralize CaIHP, whereas the isogenic mutant could not. Inoculation with Pseudomonas improved the bioavailability of CaIHP to tobacco plants, but there was no difference in plant growth response due to Gcd function. Gcd function is required for the mineralization of CaIHP in vitro; however, further studies will be needed to quantify the relative contribution of specific organic anions such as gluconate to plant growth promotion by soil pseudomonads.

Seasonal migration to high latitudes results in major reproductive benefits in an insect.

Little is known of the population dynamics of long-range insect migrants, and it has been suggested that the annual journeys of billions of nonhardy insects to exploit temperate zones during summer represent a sink from which future generations seldom return (the "Pied Piper" effect). We combine data from entomological radars and ground-based light traps to show that annual migrations are highly adaptive in the noctuid moth Autographa gamma (silver Y), a major agricultural pest. We estimate that 10-240 million immigrants reach the United Kingdom each spring, but that summer breeding results in a fourfold increase in the abundance of the subsequent generation of adults, all of which emigrate southward in the fall. Trajectory simulations show that 80% of emigrants will reach regions suitable for winter breeding in the Mediterranean Basin, for which our population dynamics model predicts a winter carrying capacity only 20% of that of northern Europe during the summer. We conclude not only that poleward insect migrations in spring result in major population increases, but also that the persistence of such species is dependent on summer breeding in high-latitude regions, which requires a fundamental change in our understanding of insect migration.