Changes in tropospheric air quality related to the protection of stratospheric ozone in a changing climate

Ultraviolet (UV) radiation drives the net production of tropospheric ozone (O3) and a large fraction of particulate matter (PM) including sulfate, nitrate, and secondary organic aerosols. Ground-level O3 and PM are detrimental to human health, leading to several million premature deaths per year globally, and have adverse effects on plants and the yields of crops. The Montreal Protocol has prevented large increases in UV radiation that would have had major impacts on air quality. Future scenarios in which stratospheric O3 returns to 1980 values or even exceeds them (the so-called super-recovery) will tend to ameliorate urban ground-level O3 slightly but worsen it in rural areas. Furthermore, recovery of stratospheric O3 is expected to increase the amount of O3 transported into the troposphere by meteorological processes that are sensitive to climate change. UV radiation also generates hydroxyl radicals (OH) that control the amounts of many environmentally important chemicals in the atmosphere including some greenhouse gases, e.g., methane (CH4), and some short-lived ozone-depleting substances (ODSs). Recent modeling studies have shown that the increases in UV radiation associated with the depletion of stratospheric ozone over 1980-2020 have contributed a small increase (~ 3%) to the globally averaged concentrations of OH. Replacements for ODSs include chemicals that react with OH radicals, hence preventing the transport of these chemicals to the stratosphere. Some of these chemicals, e.g., hydrofluorocarbons that are currently being phased out, and hydrofluoroolefins now used increasingly, decompose into products whose fate in the environment warrants further investigation. One such product, trifluoroacetic acid (TFA), has no obvious pathway of degradation and might accumulate in some water bodies, but is unlikely to cause adverse effects out to 2100.

Environmental effects of stratospheric ozone depletion, UV radiation, and interactions with climate change: UNEP Environmental Effects Assessment Panel, Update 2021

The Environmental Effects Assessment Panel of the Montreal Protocol under the United Nations Environment Programme evaluates effects on the environment and human health that arise from changes in the stratospheric ozone layer and concomitant variations in ultraviolet (UV) radiation at the Earth’s surface. The current update is based on scientific advances that have accumulated since our last assessment (Photochem and Photobiol Sci 20(1):1–67, 2021). We also discuss how climate change affects stratospheric ozone depletion and ultraviolet radiation, and how stratospheric ozone depletion affects climate change. The resulting interlinking effects of stratospheric ozone depletion, UV radiation, and climate change are assessed in terms of air quality, carbon sinks, ecosystems, human health, and natural and synthetic materials. We further highlight potential impacts on the biosphere from extreme climate events that are occurring with increasing frequency as a consequence of climate change. These and other interactive effects are examined with respect to the benefits that the Montreal Protocol and its Amendments are providing to life on Earth by controlling the production of various substances that contribute to both stratospheric ozone depletion and climate change.

Environmental effects of stratospheric ozone depletion, UV radiation, and interactions with climate change: UNEP Environmental Effects Assessment Panel, Update 2020

This assessment by the Environmental Effects Assessment Panel (EEAP) of the United Nations Environment Programme (UNEP) provides the latest scientific update since our most recent comprehensive assessment (Photochemical and Photobiological Sciences, 2019, 18, 595-828). The interactive effects between the stratospheric ozone layer, solar ultraviolet (UV) radiation, and climate change are presented within the framework of the Montreal Protocol and the United Nations Sustainable Development Goals. We address how these global environmental changes affect the atmosphere and air quality; human health; terrestrial and aquatic ecosystems; biogeochemical cycles; and materials used in outdoor construction, solar energy technologies, and fabrics. In many cases, there is a growing influence from changes in seasonality and extreme events due to climate change. Additionally, we assess the transmission and environmental effects of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is responsible for the COVID-19 pandemic, in the context of linkages with solar UV radiation and the Montreal Protocol.

Environmental effects of stratospheric ozone depletion, UV radiation and interactions with climate change: UNEP Environmental Effects Assessment Panel, update 2019

This assessment, by the United Nations Environment Programme (UNEP) Environmental Effects Assessment Panel (EEAP), one of three Panels informing the Parties to the Montreal Protocol, provides an update, since our previous extensive assessment (Photochem. Photobiol. Sci., 2019, 18, 595-828), of recent findings of current and projected interactive environmental effects of ultraviolet (UV) radiation, stratospheric ozone, and climate change. These effects include those on human health, air quality, terrestrial and aquatic ecosystems, biogeochemical cycles, and materials used in construction and other services. The present update evaluates further evidence of the consequences of human activity on climate change that are altering the exposure of organisms and ecosystems to UV radiation. This in turn reveals the interactive effects of many climate change factors with UV radiation that have implications for the atmosphere, feedbacks, contaminant fate and transport, organismal responses, and many outdoor materials including plastics, wood, and fabrics. The universal ratification of the Montreal Protocol, signed by 197 countries, has led to the regulation and phase-out of chemicals that deplete the stratospheric ozone layer. Although this treaty has had unprecedented success in protecting the ozone layer, and hence all life on Earth from damaging UV radiation, it is also making a substantial contribution to reducing climate warming because many of the chemicals under this treaty are greenhouse gases.

Interactive effects of changing stratospheric ozone and climate on tropospheric composition and air quality, and the consequences for human and ecosystem health

The composition of the air we breathe is determined by emissions, weather, and photochemical transformations induced by solar UV radiation. Photochemical reactions of many emitted chemical compounds can generate important (secondary) pollutants including ground-level ozone (O₃) and some particulate matter, known to be detrimental to human health and ecosystems. Poor air quality is the major environmental cause of premature deaths globally, and even a small decrease in air quality can translate into a large increase in the number of deaths. In many regions of the globe, changes in emissions of pollutants have caused significant changes in air quality. Short-term variability in the weather as well as long-term climatic trends can affect ground-level pollution through several mechanisms. These include large-scale changes in the transport of O₃ from the stratosphere to the troposphere, winds, clouds, and patterns of precipitation. Long-term trends in UV radiation, particularly related to the depletion and recovery of stratospheric ozone, are also expected to result in changes in air quality as well as the self-cleaning capacity of the global atmosphere. The increased use of substitutes for ozone-depleting substances, in response to the Montreal Protocol, does not currently pose a significant risk to the environment. This includes both the direct emissions of substitutes during use and their atmospheric degradation products (e.g. trifluoroacetic acid, TFA).

Integrative Genomics Identifies the Molecular Basis of Resistance to Azacitidine Therapy in Myelodysplastic Syndromes

Myelodysplastic syndromes and chronic myelomonocytic leukemia are blood disorders characterized by ineffective hematopoiesis and progressive marrow failure that can transform into acute leukemia. The DNA methyltransferase inhibitor 5-azacytidine (AZA) is the most effective pharmacological option, but only ∼50% of patients respond. A response only manifests after many months of treatment and is transient. The reasons underlying AZA resistance are unknown, and few alternatives exist for non-responders. Here, we show that AZA responders have more hematopoietic progenitor cells (HPCs) in the cell cycle. Non-responder HPC quiescence is mediated by integrin α5 (ITGA5) signaling and their hematopoietic potential improved by combining AZA with an ITGA5 inhibitor. AZA response is associated with the induction of an inflammatory response in HPCs in vivo. By molecular bar coding and tracking individual clones, we found that, although AZA alters the sub-clonal contribution to different lineages, founder clones are not eliminated and continue to drive hematopoiesis even in complete responders.

Comparison and visualisation of agreement for paired lists of rankings

Output from analysis of a high-throughput 'omics' experiment very often is a ranked list. One commonly encountered example is a ranked list of differentially expressed genes from a gene expression experiment, with a length of many hundreds of genes. There are numerous situations where interest is in the comparison of outputs following, say, two (or more) different experiments, or of different approaches to the analysis that produce different ranked lists. Rather than considering exact agreement between the rankings, following others, we consider two ranked lists to be in agreement if the rankings differ by some fixed distance. Generally only a relatively small subset of the k top-ranked items will be in agreement. So the aim is to find the point k at which the probability of agreement in rankings changes from being greater than 0.5 to being less than 0.5. We use penalized splines and a Bayesian logit model, to give a nonparametric smooth to the sequence of agreements, as well as pointwise credible intervals for the probability of agreement. Our approach produces a point estimate and a credible interval for k. R code is provided. The method is applied to rankings of genes from breast cancer microarray experiments.

Versatile, sensitive liquid chromatography mass spectrometry - Implementation of 10 μm OT columns suitable for small molecules, peptides and proteins

We have designed a versatile and sensitive liquid chromatographic (LC) system, featuring a monolithic trap column and a very narrow (10 μm ID) fused silica open tubular liquid chromatography (OTLC) separation column functionalized with C₁₈-groups, for separating a wide range of molecules (from small metabolites to intact proteins). Compared to today’s capillary/nanoLC approaches, our system provides significantly enhanced sensitivity (up to several orders) with matching or improved separation efficiency, and highly repeatable chromatographic performance. The chemical properties of the trap column and the analytical column were fine-tuned to obtain practical sample loading capacities (above 2 μg), an earlier bottleneck of OTLC. Using the OTLC system (combined with Orbitrap mass spectrometry), we could perform targeted metabolomics of sub-μg amounts of exosomes with 25 attogram detection limit of a breast cancer-related hydroxylated cholesterol. With the same set-up, sensitive bottom-up proteomics (targeted and untargeted) was possible, and high-resolving intact protein analysis. In contrast to state-of-the-art packed columns, our platform performs chromatography with very little dilution and is “fit-for-all”, well suited for comprehensive analysis of limited samples, and has potential as a tool for challenges in diagnostics.

Heritability

This article discusses certain aspects of determining heritability estimates from the genetic analyses of data. First, a brief review is given of the major statistical techniques for fitting models to quantitative family data. Then, by reference to a general schematic framework, the basic models that have been proposed for such data will be described. Some new environmental models are also developed. Finally, by reference to some data sets, the interactive approach to data analysis is proposed, advocating the determination of adequacy of fit of all reasonable models to available data.

Estimation of the methylation pattern distribution from deep sequencing data

BACKGROUND

Bisulphite sequencing enables the detection of cytosine methylation. The sequence of the methylation states of cytosines on any given read forms a methylation pattern that carries substantially more information than merely studying the average methylation level at individual positions. In order to understand better the complexity of DNA methylation landscapes in biological samples, it is important to study the diversity of these methylation patterns. However, the accurate quantification of methylation patterns is subject to sequencing errors and spurious signals due to incomplete bisulphite conversion of cytosines.

RESULTS

A statistical model is developed which accounts for the distribution of DNA methylation patterns at any given locus. The model incorporates the effects of sequencing errors and spurious reads, and enables estimation of the true underlying distribution of methylation patterns.

CONCLUSIONS

Calculation of the estimated distribution over methylation patterns is implemented in the R Bioconductor package MPFE. Source code and documentation of the package are also available for download at http://bioconductor.org/packages/3.0/bioc/html/MPFE.html .

Appearance of metastable B2 phase during solidification of Ni50Zr50 alloy: electrostatic levitation and molecular dynamics simulation studies

High-energy x-ray diffraction measurements of undercooled, electrostatically levitated Ni50Zr50 liquid droplets were performed. The observed solidification pathway proceeded through the nucleation and growth of the metastable B2 phase, which persisted for several seconds before the rapid appearance of the stable B33 phase. This sequence is shown to be consistent with predictions from classical nucleation theory using data obtained from molecular dynamics (MD) simulations. A plausible mechanism for the B2-B33 transformation is proposed and investigated through further MD simulations.

Theoretical calculation of the melting curve of Cu-Zr binary alloys

Helmholtz free energies of the dominant binary crystalline solids found in the Cu-Zr system at high temperatures close to the melting curve are calculated. Our theoretical approach combines fundamental measure density functional theory (applied to the hard-sphere reference system) and a perturbative approach to include the attractive interactions. The studied crystalline solids are Cu(fcc), Cu_{51}Zr_{14}(β), CuZr(B2), CuZr_{2}(C11b), Zr(hcp), and Zr(bcc). The calculated Helmholtz free energies of crystalline solids are in good agreement with results from molecular-dynamics (MD) simulations. Using the same perturbation approach, the liquid phase free energies are calculated as a function of composition and temperature, from which the melting curve of the entire composition range of this system can be obtained. Phase diagrams are determined in this way for two leading embedded atom method potentials, and the results are compared with experimental data. Theoretical melting temperatures are compared both with experimental values and with values obtained directly from MD simulations at several compositions.

Error estimates for the analysis of differential expression from RNA-seq count data

Background. A number of algorithms exist for analysing RNA-sequencing data to infer profiles of differential gene expression. Problems inherent in building algorithms around statistical models of over dispersed count data are formidable and frequently lead to non-uniform p-value distributions for null-hypothesis data and to inaccurate estimates of false discovery rates (FDRs). This can lead to an inaccurate measure of significance and loss of power to detect differential expression.

Results. We use synthetic and real biological data to assess the ability of several available R packages to accurately estimate FDRs. The packages surveyed are based on statistical models of overdispersed Poisson data and include edgeR, DESeq, DESeq2, PoissonSeq and QuasiSeq. Also tested is an add-on package to edgeR and DESeq which we introduce called Polyfit. Polyfit aims to address the problem of a non-uniform null p-value distribution for two-class datasets by adapting the Storey–Tibshirani procedure.

Conclusions. We find the best performing package in the sense that it achieves a low FDR which is accurately estimated over the full range of p-values, albeit with a very slow run time, is the QLSpline implementation of QuasiSeq. This finding holds provided the number of biological replicates in each condition is at least 4. The next best performing packages are edgeR and DESeq2. When the number of biological replicates is sufficiently high, and within a range accessible to multiplexed experimental designs, the Polyfit extension improves the performance DESeq (for approximately 6 or more replicates per condition), making its performance comparable with that of edgeR and DESeq2 in our tests with synthetic data.

Two-year weight-loss maintenance in primary care-based Diabetes Prevention Program lifestyle interventions

Objective:

To investigate whether the effects on weight loss and cardiometabolic risk factor reduction of two technology-mediated lifestyle interventions for 15 months in a primary care-based translation trial sustained at 24 months (that is, 9 months after the end of intervention).

Design:

This study analyzed data from an extended follow-up of participants in the original ‘E-LITE' (Evaluation of Lifestyle Interventions to Treat Elevated Cardiometabolic Risk in Primary Care)-randomized controlled trial, which demonstrated the effectiveness of two adapted Diabetes Prevention Program (DPP) lifestyle interventions compared with usual primary care.

Subjects:

E-LITE randomized 241 overweight or obese participants with pre-diabetes and/or metabolic syndrome to receive usual care alone (n=81) or usual care plus a coach-led (n=79) or self-directed intervention (n=81). The interventions provided coach-led group behavioral weight-loss treatment or a take-home, self-directed DVD using the same 12-week curriculum, followed by 12 additional months of technology-mediated coach contact and self-monitoring support. Participants received no further intervention after month 15. A blinded assessor conducted 24-month visits by following the measurement protocols of the original trial. Measurements include weight and cardiometabolic risk factors (waist circumference, fasting plasma glucose, resting blood pressure, triglycerides, high- and low-density lipoprotein cholesterol, total cholesterol and triglyceride to high-density lipoprotein cholesterol ratio).

Results:

At month 24, mean±s.e. changes in body mass index (trial primary outcome) and weight (kg) from baseline were –1.9±0.3 (P=0.001) and –5.4±0.9 (P<0.001) in the coach-led intervention, and –1.6±0.3 (P=0.03) and –4.5±0.9 (P=0.001) in the self-directed intervention, compared with –0.9±0.3 and 2.4±0.9 in the usual care group. In addition, both interventions led to a greater percentage of participants maintaining ⩾7% weight loss and sustained improvements in waist circumference and fasting plasma glucose levels than usual care.

Conclusion:

This study shows sustained benefits of the two primary care-based, technology-mediated DPP lifestyle interventions. The findings warrant replication in long-term studies involving diverse populations.

Guidelines and good clinical practice recommendations for contrast enhanced ultrasound (CEUS) in the liver--update 2012: a WFUMB-EFSUMB initiative in cooperation with representatives of AFSUMB, AIUM, ASUM, FLAUS and ICUS

Initially, a set of guidelines for the use of ultrasound contrast agents was published in 2004 dealing only with liver applications. A second edition of the guidelines in 2008 reflected changes in the available contrast agents and updated the guidelines for the liver, as well as implementing some non-liver applications. Time has moved on, and the need for international guidelines on the use of CEUS in the liver has become apparent. The present document describes the third iteration of recommendations for the hepatic use of contrast enhanced ultrasound (CEUS) using contrast specific imaging techniques. This joint WFUMB-EFSUMB initiative has implicated experts from major leading ultrasound societies worldwide. These liver CEUS guidelines are simultaneously published in the official journals of both organizing federations (i.e., Ultrasound in Medicine and Biology for WFUMB and Ultraschall in der Medizin/European Journal of Ultrasound for EFSUMB). These guidelines and recommendations provide general advice on the use of all currently clinically available ultrasound contrast agents (UCA). They are intended to create standard protocols for the use and administration of UCA in liver applications on an international basis and improve the management of patients worldwide.

Mass spectrometry-based protein identification by integrating de novo sequencing with database searching

BACKGROUND

Mass spectrometry-based protein identification is a very challenging task. The main identification approaches include de novo sequencing and database searching. Both approaches have shortcomings, so an integrative approach has been developed. The integrative approach firstly infers partial peptide sequences, known as tags, directly from tandem spectra through de novo sequencing, and then puts these sequences into a database search to see if a close peptide match can be found. However the current implementation of this integrative approach has several limitations. Firstly, simplistic de novo sequencing is applied and only very short sequence tags are used. Secondly, most integrative methods apply an algorithm similar to BLAST to search for exact sequence matches and do not accommodate sequence errors well. Thirdly, by applying these methods the integrated de novo sequencing makes a limited contribution to the scoring model which is still largely based on database searching.

RESULTS

We have developed a new integrative protein identification method which can integrate de novo sequencing more efficiently into database searching. Evaluated on large real datasets, our method outperforms popular identification methods.

Efficient experimental design and analysis strategies for the detection of differential expression using RNA-Sequencing

BACKGROUND

RNA sequencing (RNA-Seq) has emerged as a powerful approach for the detection of differential gene expression with both high-throughput and high resolution capabilities possible depending upon the experimental design chosen. Multiplex experimental designs are now readily available, these can be utilised to increase the numbers of samples or replicates profiled at the cost of decreased sequencing depth generated per sample. These strategies impact on the power of the approach to accurately identify differential expression. This study presents a detailed analysis of the power to detect differential expression in a range of scenarios including simulated null and differential expression distributions with varying numbers of biological or technical replicates, sequencing depths and analysis methods.

RESULTS

Differential and non-differential expression datasets were simulated using a combination of negative binomial and exponential distributions derived from real RNA-Seq data. These datasets were used to evaluate the performance of three commonly used differential expression analysis algorithms and to quantify the changes in power with respect to true and false positive rates when simulating variations in sequencing depth, biological replication and multiplex experimental design choices.

CONCLUSIONS

This work quantitatively explores comparisons between contemporary analysis tools and experimental design choices for the detection of differential expression using RNA-Seq. We found that the DESeq algorithm performs more conservatively than edgeR and NBPSeq. With regard to testing of various experimental designs, this work strongly suggests that greater power is gained through the use of biological replicates relative to library (technical) replicates and sequencing depth. Strikingly, sequencing depth could be reduced as low as 15% without substantial impacts on false positive or true positive rates.

Alignment-free sequence comparison for biologically realistic sequences of moderate length

The D(2) statistic, defined as the number of matches of words of some pre-specified length k, is a computationally fast alignment-free measure of biological sequence similarity. However there is some debate about its suitability for this purpose as the variability in D(2) may be dominated by the terms that reflect the noise in each of the single sequences only. We examine the extent of the problem and the effectiveness of overcoming it by using two mean-centred variants of this statistic, D(2)* and D(2c). We conclude that all three statistics are potentially useful measures of sequence similarity, for which reasonably accurate p-values can be estimated under a null hypothesis of sequences composed of identically and independently distributed letters. We show that D(2) and D(2)c, and to a somewhat lesser extent D(2)*, perform well in tests to classify moderate length query sequences as putative cis-regulatory modules.

LASSO model selection with post-processing for a genome-wide association study data set

Model selection procedures for simultaneous analysis of all single-nucleotide polymorphisms in genome-wide association studies are most suitable for making full use of the data for a complex disease study. In this paper we consider a penalized regression using the LASSO procedure and show that post-processing of the penalized-regression results with subsequent stepwise selection may lead to improved identification of causal single-nucleotide polymorphisms.

Safety in magnetic resonance units: an update

The number of anaesthetists who are involved in magnetic resonance (MR) units is increasing. Magnetic resonance systems are becoming more powerful and interventional procedures are now possible. This paper updates information relating to safety terminology, occupational exposure, reactions to gadolinium-based contrast agents and the risk of nephrogenic systemic fibrosis. Magnetic resonance examinations of patients with pacemakers are still generally contra-indicated but have been carried out in specialist centres under strictly controlled conditions. As availability of MR increases, so the education of anaesthetists, who are occasionally required to provide a service, must be considered.

Anaesthesia in MR units was first described in the 1980s. Guidelines on the provision of anaesthetic services in MR units were published by the Association of Anaesthetists of Great Britain and Ireland (AAGBI) in 2002 [1]. Since then, the number of hospitals with MR units, and hence the number of patients requiring anaesthesia for MR, has increased. While the issues relating to setting up anaesthetic services in MR have not changed, there have been a number of developments that warrant this update:

Safety terminology and guidelines have changed.

MR systems utilise higher magnetic-field strengths and more open designs are available.

Interventional and intra-operative MR are now routine in some centres.

Mobile MR scanners are increasingly used to reduce waiting lists.

Although still generally contra-indicated, some patients with pacemakers have been scanned under strictly controlled conditions in specialist centres.

‘MR safe’ medical implants are now being produced.

New equipment is now available for use in MR.

Out-of-hours availability of MR investigations has increased.

Reports of allergic reactions to MR contrast media have increased.

Gadolinium based contrast agents (Gd-CAs) are associated with a varying degree of risk of nephrogenic systemic fibrosis in patients with impaired renal function.

Chemical Scent Constituents in the Urine of the Red Fox (Vulpes vulpes L.) During the Winter Season

Four volatile chemical compounds have been identified as apparently unique constituents in urines of red foxes (both sexes) during the winter season when mating occurs. Quinaldine was found only in male fox urine. Several other compounds identified are found in other species also. Some or all of these compounds may function in olfactory communication in the red fox.

Cathepsin K activity-dependent regulation of osteoclast actin ring formation and bone resorption

Cathepsin K is responsible for the degradation of type I collagen in osteoclast-mediated bone resorption. Collagen fragments are known to be biologically active in a number of cell types. Here, we investigate their potential to regulate osteoclast activity. Mature murine osteoclasts were seeded on type I collagen for actin ring assays or dentine discs for resorption assays. Cells were treated with cathepsins K-, L-, or MMP-1-predigested type I collagen or soluble bone fragments for 24 h. The presence of actin rings was determined fluorescently by staining for actin. We found that the percentage of osteoclasts displaying actin rings and the area of resorbed dentine decreased significantly on addition of cathepsin K-digested type I collagen or bone fragments, but not with cathepsin L or MMP-1 digests. Counterintuitively, actin ring formation was found to decrease in the presence of the cysteine proteinase inhibitor LHVS and in cathepsin K-deficient osteoclasts. However, cathepsin L deficiency or the general MMP inhibitor GM6001 had no effect on the presence of actin rings. Predigestion of the collagen matrix with cathepsin K, but not by cathepsin L or MMP-1 resulted in an increased actin ring presence in cathepsin K-deficient osteoclasts. These studies suggest that cathepsin K interaction with type I collagen is required for 1) the release of cryptic Arg-Gly-Asp motifs during the initial attachment of osteoclasts and 2) termination of resorption via the creation of autocrine signals originating from type I collagen degradation.

Vascular microarray profiling in two models of hypertension identifies caveolin-1, Rgs2 and Rgs5 as antihypertensive targets

BACKGROUND

Hypertension is a complex disease with many contributory genetic and environmental factors. We aimed to identify common targets for therapy by gene expression profiling of a resistance artery taken from animals representing two different models of hypertension. We studied gene expression and morphology of a saphenous artery branch in normotensive WKY rats, spontaneously hypertensive rats (SHR) and adrenocorticotropic hormone (ACTH)-induced hypertensive rats.

RESULTS

Differential remodeling of arteries occurred in SHR and ACTH-treated rats, involving changes in both smooth muscle and endothelium. Increased expression of smooth muscle cell growth promoters and decreased expression of growth suppressors confirmed smooth muscle cell proliferation in SHR but not in ACTH. Differential gene expression between arteries from the two hypertensive models extended to the renin-angiotensin system, MAP kinase pathways, mitochondrial activity, lipid metabolism, extracellular matrix and calcium handling. In contrast, arteries from both hypertensive models exhibited significant increases in caveolin-1 expression and decreases in the regulators of G-protein signalling, Rgs2 and Rgs5. Increased protein expression of caveolin-1 and increased incidence of caveolae was found in both smooth muscle and endothelial cells of arteries from both hypertensive models.

CONCLUSION

We conclude that the majority of differences in gene expression found in the saphenous artery taken from rats with two different forms of hypertension reflect distinctive morphological and physiological alterations. However, changes in common to caveolin-1 expression and G protein signalling, through attenuation of Rgs2 and Rgs5, may contribute to hypertension through augmentation of vasoconstrictor pathways and provide potential targets for common drug development.

Impairment of organ-specific T cell negative selection by diabetes susceptibility genes: genomic analysis by mRNA profiling

BACKGROUND

T cells in the thymus undergo opposing positive and negative selection processes so that the only T cells entering circulation are those bearing a T cell receptor (TCR) with a low affinity for self. The mechanism differentiating negative from positive selection is poorly understood, despite the fact that inherited defects in negative selection underlie organ-specific autoimmune disease in AIRE-deficient people and the non-obese diabetic (NOD) mouse strain

RESULTS

Here we use homogeneous populations of T cells undergoing either positive or negative selection in vivo together with genome-wide transcription profiling on microarrays to identify the gene expression differences underlying negative selection to an Aire-dependent organ-specific antigen, including the upregulation of a genomic cluster in the cytogenetic band 2F. Analysis of defective negative selection in the autoimmune-prone NOD strain demonstrates a global impairment in the induction of the negative selection response gene set, but little difference in positive selection response genes. Combining expression differences with genetic linkage data, we identify differentially expressed candidate genes, including Bim, Bnip3, Smox, Pdrg1, Id1, Pdcd1, Ly6c, Pdia3, Trim30 and Trim12.

CONCLUSION

The data provide a molecular map of the negative selection response in vivo and, by analysis of deviations from this pathway in the autoimmune susceptible NOD strain, suggest that susceptibility arises from small expression differences in genes acting at multiple points in the pathway between the TCR and cell death.

Changes in tropospheric composition and air quality due to stratospheric ozone depletion and climate change

It is well-understood that reductions in air quality play a significant role in both environmental and human health. Interactions between ozone depletion and global climate change will significantly alter atmospheric chemistry which, in turn, will cause changes in concentrations of natural and human-made gases and aerosols. Models predict that tropospheric ozone near the surface will increase globally by up to 10 to 30 ppbv (33 to 100% increase) during the period 2000 to 2100. With the increase in the amount of the stratospheric ozone, increased transport from the stratosphere to the troposphere will result in different responses in polluted and unpolluted areas. In contrast, global changes in tropospheric hydroxyl radical (OH) are not predicted to be large, except where influenced by the presence of oxidizable organic matter, such as from large-scale forest fires. Recent measurements in a relatively clean location over 5 years showed that OH concentrations can be predicted by the intensity of solar ultraviolet radiation. If this relationship is confirmed by further observations, this approach could be used to simplify assessments of air quality. Analysis of surface-level ozone observations in Antarctica suggests that there has been a significant change in the chemistry of the boundary layer of the atmosphere in this region as a result of stratospheric ozone depletion. The oxidation potential of the Antarctic boundary layer is estimated to be greater now than before the development of the ozone hole. Recent modeling studies have suggested that iodine and iodine-containing substances from natural sources, such as the ocean, may increase stratospheric ozone depletion significantly in polar regions during spring. Given the uncertainty of the fate of iodine in the stratosphere, the results may also be relevant for stratospheric ozone depletion and measurements of the influence of these substances on ozone depletion should be considered in the future. In agreement with known usage and atmospheric loss processes, tropospheric concentrations of HFC-134a, the main human-made source of trifluoroacetic acid (TFA), is increasing rapidly. As HFC-134a is a potent greenhouse gas, this increasing concentration has implications for climate change. However, the risks to humans and the environment from substances, such as TFA, produced by atmospheric degradation of hydrochlorofluorocarbons (HCFCs) and hydrofluorocarbons (HFCs) are considered minimal. Perfluoropolyethers, commonly used as industrial heat transfer fluids and proposed as chlorohydrofluorocarbon (CHFC) substitutes, show great stability to chemical degradation in the atmosphere. These substances have been suggested as substitutes for CHFCs but, as they are very persistent in the atmosphere, they may be important contributors to global warming. It is not known whether these substances will contribute significantly to global warming and its interaction with ozone depletion but they should be considered for further evaluation.

SeqVis: visualization of compositional heterogeneity in large alignments of nucleotides

Most phylogenetic methods assume that the sequences evolved under homogeneous, stationary and reversible conditions. Compositional heterogeneity in data intended for studies of phylogeny suggests that the data did not evolve under these conditions. SeqVis, a Java application for analysis of nucleotide content, reads sequence alignments in several formats and plots the nucleotide content in a tetrahedron. Once plotted, outliers can be identified, thus allowing for decisions on the applicability of the data for phylogenetic analysis.

AVAILABILITY

http://www.bio.usyd.edu.au/jermiin/programs.htm.

Proteomic classification of pancreatic adenocarcinoma tissue using protein chip technology

BACKGROUND & AIMS

Pancreatic adenocarcinoma is a most devastating cancer that presents late and is rapidly progressive. This study aimed to identify unique, tissue-specific protein biomarkers capable of differentiating pancreatic adenocarcinoma (PC) from adjacent uninvolved pancreatic tissue (AP), benign pancreatic disease (B), and nonmalignant tumor tissue (NM).

METHODS

Tissue samples representing PC (n = 31), AP (n = 44), and B (n = 19) tissue were analyzed on hydrophobic protein chip arrays by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Training models were developed using logistic regression and validated using the 10-fold cross-validation approach.

RESULTS

The hydrophobic protein chip array revealed 13 protein peaks differentially expressed between PC and AP (receiver operating characteristic [ROC] area under the curve [AUC], 0.64-0.85), 8 between PC and B (ROC AUC, 0.67-0.78), and 12 between PC and NM tissue (ROC AUC, 0.63-0.81). Logistic regression and cross-validation identified overlapping panels of peaks to develop a training model that distinguished PC from AP (77.4% sensitivity, 84.1% specificity), B (83.9% sensitivity, 78.9% specificity), and NM tissue (58.1% sensitivity, 90.5% specificity). The final panels selected correctly classified 80.6% of PC and 88.6% of AP samples (ROC AUC, 0.92), 93.5% of PC and 89.5% of B samples (ROC AUC, 0.99), and 71.0% of PC and 92.1% of NM samples (ROC AUC, 0.91).

CONCLUSIONS

This study used surface-enhanced laser desorption/ionization time-of-flight mass spectrometry to discover a number of protein panels that can distinguish effectively between pancreatic adenocarcinoma, benign, and adjacent pancreatic tissue. Identification of these proteins will add to our understanding of the biology of pancreatic cancer. Furthermore, these protein panels may have important diagnostic implications.

Health-related quality of life in patients with idiopathic pulmonary fibrosis: a systematic review

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) profoundly affects the quality of patients' lives. A systematic review was performed to evaluate critically the published literature and to examine what is known about health-related quality of life (HRQL) in patients with IPF.

METHODS

The MEDLINE, EMBASE, Health and Psychosocial Instruments, and Cochrane Library databases were searched to 1 April 2004. Abstracts and bibliographies of published articles were scanned and contact was made with investigators. Included studies analysed HRQL (or quality of life) in at least 10 patients with IPF. Two reviewers independently selected studies, evaluated their quality according to predetermined criteria, and abstracted data on study design, patients' demographic and clinical characteristics, and quality of life outcome measures.

RESULTS

Seven studies met the inclusion criteria. The studies enrolled 512 patients with IPF and used three different instruments to measure HRQL. All studies had important limitations in methodological quality; none measured longitudinal changes in HRQL over time. Patients reported substantially impaired HRQL, especially in domains that measured physical health and level of independence. Patients with IPF appear to have similar impairments in HRQL to those with chronic obstructive pulmonary disease. Measures of dyspnoea were moderately correlated with scores from domains that measured physical health (R2 = 0.03-0.66) and energy/fatigue/pep (R2 = 0.19-0.55), but measures of pulmonary function and gas exchange did not correlate as strongly with these and other domains.

CONCLUSION

Studies of HRQL in patients with IPF suggest that, in addition to the obvious effect on physical health, general health, energy level, respiratory symptoms, and level of independence are also impaired. Variability in HRQL among patients is not fully explained by measures of dyspnoea or pulmonary function, suggesting that HRQL measures provide unique information. More research is needed to identify or design appropriate measurement instruments for patients with IPF and to examine changes in HRQL over time or in response to specific treatments.

Discussion of "A Bayesian approach to DNA sequence segmentation"

This article discusses the results in Boys and Henderson (2004, Biometrics 60, 573-581) in which the authors propose a new approach to the classification of genomic DNA into a number of hidden Markov states with a variable order of dependency, potentially allowing for the high-throughput detection of structure within genomic DNA. This article is likely to be an important point of departure for further modeling of this type. We question whether the genome of the bacteriophage lambda is the most appropriate example with which to demonstrate the method's effectiveness, whether it can be expected that the method will carry over to genomes where there is only one direction of transcription and no operon structure, and suggest a graphical display that seems to offer insight into the results. It would be interesting to see an analysis that uses the codon alphabet.

Optimizing microarray in experimental hypertension

BACKGROUND

Genetic noise between outbred animals can potentially be a major confounder in the use of microarray technology for gene expression profiling. The study of paired organs from the same animal offers an alternative approach (e.g., for studies of the kidney in experimental hypertension). The present study was undertaken to determine the level of genetic noise between outbred adult Sprague-Dawley (SD) rats, and to determine the effects of unilateral nephrectomy on changes in gene expression as a basis for the design of microarray studies in experimental hypertension.

METHODS

Male SD rats (approximately 130 g) were acclimatized before measurement of tail-cuff systolic blood pressure (SBP) for 6 control days and 4 days of saline treatment. Left kidney nephrectomy was performed, and the tissue snap-frozen in liquid nitrogen for subsequent RNA extraction. Two weeks later, SBP was measured over 4 control and 8 saline treatment days, and the remaining right kidney removed and frozen. Total RNA purification, preparation of cRNA, hybridization, and scanning of the Rat U34A Affymetrix arrays were performed, and data analyzed using MAS5 software Affymetrix Suite (v5), Bioconductor, as well as statistical methods motivated by relevant simulations.

RESULTS

Gene expression profiles in the left control kidney were extremely consistent across animals. The expression profiles of pairs of kidneys from the same animal were, however, more similar than those of kidneys from different animals. Nephrectomy had little effect on the gene expression profiles in the time frame examined.

CONCLUSION

Despite the outbred nature of the rats used in this study, they are useful for gene expression profiling comparisons. The use of paired organs from an individual animal ensures even further genetic identity, allowing determination of genes modified by the treatment of interest.

Use of Principal Component Analysis and theGE-Biplot for the Graphical Exploration of Gene Expression Data

This note is in response to Wouters et al. (2003, Biometrics 59, 1131-1139) who compared three methods for exploring gene expression data. Contrary to their summary that principal component analysis is not very informative, we show that it is possible to determine principal component analyses that are useful for exploratory analysis of microarray data. We also present another biplot representation, the GE-biplot (Gene Expression biplot), that is a useful method for exploring gene expression data with the major advantage of being able to aid interpretation of both the samples and the genes relative to each other.

Generalized resistance to thymic deletion in the NOD mouse; a polygenic trait characterized by defective induction of Bim

The cause of common polygenic autoimmune diseases is not understood because of genetic and cellular complexity. Here, we pinpoint the action of a subset of autoimmune susceptibility loci in the NOD mouse strain linked to D1mit181, D2mit490, D7mit101, and D15mit229, which cause a generalized resistance to thymic deletion in vivo that applies equally to Aire-induced organ-specific gene products in the thymic medulla and to systemic antigens expressed at high levels throughout the thymus and affects CD4(+), CD4(+)8(+), and CD4(+)25(+) thymocytes. Resistance to thymic deletion does not reflect a general deficit in TCR signaling to calcineurin- or ERK-induced genes, imbalance in constitutive regulators of apoptosis, nor excessive signaling to prosurvival genes but is distinguished by failure to induce the proapoptotic gene and protein, Bim, during in vivo encounter with high-avidity autoantigen. These findings establish defects in thymic deletion and Bim induction as a key mechanism in the pathogenesis of autoimmunity.

An efficient Z-score algorithm for assessing sequence alignments

We describe an alternative method for scoring of the pairwise alignment of two biological sequences. Designed to overcome the bias due to the composition of the alignment, it measures the distance (in standard deviations) between the given alignment and the mean value of all other alignments that can be obtained by a permutation of either sequence. We demonstrate that the standard deviation can be calculated efficiently. By concentrating upon the ungapped case, the mean and standard deviation can be calculated exactly and in two steps, the first being O(N) time, where N is the length of the sequence, the second in a fixed number of calculations, i.e., in O(1) time. We argue that this statistic is a more consistent measure than a similarity score based upon a standard scoring matrix. Even in the ungapped case, the statistic proves in many cases to be more accurate than the commonly used (FASTA) (Pearson and Lipman, 1988) gapped Z-score in which the sequence is matched against a random sample of the database. We demonstrate the use of the POZ-score as a secondary filter which screens out several well-known types of false positive, reducing the amount of manual screening to be done by the biologist.

Objective determination of appropriate reporting intervals

BACKGROUND

The reporting interval is the incremental value chosen in reporting analyte concentration. Reporting intervals for different analytes are often inappropriately narrow, when analytical imprecision and biological variability are considered.

METHODS

We have used statistical techniques to determine intervals for individual analytes at which there is 50% or 95% confidence that two results are analytically different, and compared these with the reporting intervals in use for a range of general chemistry analytes and analytes usually measured by immunoassay.

RESULTS

No analytes met the criteria for 95% confidence that the results are analytically different. Even at the 50% confidence level, 24 of 46 analytes failed at all concentrations examined. For some analytes, particularly hormones at high concentration, the reporting interval increment should be increased by a factor of at least ten.

CONCLUSIONS

The majority of analytes are inappropriately reported when analytical precision alone is considered. The concept of the 'uncertainty of measurement' has not been adequately addressed. A consensus should be reached and implemented on appropriate reporting intervals for all analytes.

Amplification of MMP-2 and MMP-9 production by prostate cancer cell lines via activation of protease-activated receptors

BACKGROUND

The matrix metalloproteinases (MMP) are a family of proteolytic enzymes involved in facilitating cancer metastasis. Protease-activated receptors (PARs) have previously been shown to be involved in pathways of MMP upregulation by tumor cells.

METHODS

Two androgen independent prostate cancer cell lines, PC3 and DU-145, and one androgen dependent prostate cancer line LNCaP, were investigated. PAR expression was detected using RT-PCR and immunofluorochemistry (IFC) techniques. MMP activity assays were used to quantify the levels of MMP-2 and -9 on all three prostate cell lines after PAR activation.

RESULTS

RT-PCR and IFC showed the presence of PAR-1 and PAR-2 in all cell lines investigated, only LNCaP showed PAR-3 and PAR-4 expression. Increased levels of MMP-2 and MMP-9 activity, up to sevenfold depending on prostate cancer cell line, following PAR activation by specific PAR peptides was shown.

CONCLUSION

Preliminary studies show the activation of PAR-1 or PAR-2 produced increased levels of MMP-2 and MMP-9 activity in prostate cancer cell lines, indicating their potential role in the metastasis of prostate cancer cells.

Statistical Analysis of Adsorption Models for Oligonucleotide Microarrays

Recent analyses have shown that the relationship between intensity measurements from high density oligonucleotide microarrays and known concentration is non linear. Thus many measurements of so-called gene expression are neither measures of transcript nor mRNA concentration as might be expected.

Intensity as measured in such microarrays is a measurement of fluorescent dye attached to probe-target duplexes formed during hybridization of a sample to the probes on the microarray. We develop several dynamic adsorption models relating fluorescent dye intensity to target RNA concentration, the simplest of which is the equilibrium Langmuir isotherm, or hyperbolic response function. Using data from the Affymerix HG-U95A Latin Square experiment, we evaluate various physical models, including equilibrium and non-equilibrium models, by applying maximum likelihood methods. We show that for these data, equilibrium Langmuir isotherms with probe dependent parameters are appropriate. We describe how probe sequence information may then be used to estimate the parameters of the Langmuir isotherm in order to provide an improved measure of absolute target concentration.

Visualisation of gene expression data - the GE-biplot, the Chip-plot and the Gene-plot

Visualisation methods for exploring microarray data are particularly important for gaining insight into data from gene expression experiments, such as those concerned with the development of an understanding of gene function and interactions. Further, good visualisation techniques are useful for outlier detection in microarray data and for aiding biological interpretation of results, as well as for presentation of overall summaries of the data. The biplot is particularly useful for the display of microarray data as both the genes and the chips can be simultaneously plotted. In this paper we describe several ordination techniques suitable for exploring microarray data, and we call these the GE-biplot, the Chip-plot and the Gene-plot. The general method is first evaluated on synthetic data simulated in accord with current biological interpretation of microarray data. Then it is applied to two well-known data sets, namely the colon data of Alon et al. (1999) and the leukaemia data of Golub et al. (1999). The usefulness of the approach for interpreting and comparing different analyses of the same data is demonstrated.