Specialized interferon action in COVID-19.

The impacts of interferon (IFN) signaling on COVID-19 pathology are multiple, with both protective and harmful effects being documented. We report here a multiomics investigation of systemic IFN signaling in hospitalized COVID-19 patients, defining the multiomics biosignatures associated with varying levels of 12 different type I, II, and III IFNs. The antiviral transcriptional response in circulating immune cells is strongly associated with a specific subset of IFNs, most prominently IFNA2 and IFNG. In contrast, proteomics signatures indicative of endothelial damage and platelet activation associate with high levels of IFNB1 and IFNA6. Seroconversion and time since hospitalization associate with a significant decrease in a specific subset of IFNs. Additionally, differential IFN subtype production is linked to distinct constellations of circulating myeloid and lymphoid immune cell types. Each IFN has a unique metabolic signature, with IFNG being the most associated with activation of the kynurenine pathway. IFNs also show differential relationships with clinical markers of poor prognosis and disease severity. For example, whereas IFNG has the strongest association with C-reactive protein and other immune markers of poor prognosis, IFNB1 associates with increased neutrophil to lymphocyte ratio, a marker of late severe disease. Altogether, these results reveal specialized IFN action in COVID-19, with potential diagnostic and therapeutic implications.

A comprehensive hierarchical comparison of structural connectomes in Major Depressive Disorder cases v. controls in two large population samples.

BACKGROUND: The brain can be represented as a network, with nodes as brain regions and edges as region-to-region connections. Nodes with the most connections (hubs) are central to efficient brain function. Current findings on structural differences in Major Depressive Disorder (MDD) identified using network approaches remain inconsistent, potentially due to small sample sizes. It is still uncertain at what level of the connectome hierarchy differences may exist, and whether they are concentrated in hubs, disrupting fundamental brain connectivity. METHODS: We utilized two large cohorts, UK Biobank (UKB, N = 5104) and Generation Scotland (GS, N = 725), to investigate MDD case-control differences in brain network properties. Network analysis was done across four hierarchical levels: (1) global, (2) tier (nodes grouped into four tiers based on degree) and rich club (between-hub connections), (3) nodal, and (4) connection. RESULTS: In UKB, reductions in network efficiency were observed in MDD cases globally (d = -0.076, pFDR = 0.033), across all tiers (d = -0.069 to -0.079, pFDR = 0.020), and in hubs (d = -0.080 to -0.113, pFDR = 0.013-0.035). No differences in rich club organization and region-to-region connections were identified. The effect sizes and direction for these associations were generally consistent in GS, albeit not significant in our lower-N replication sample. CONCLUSION: Our results suggest that the brain's fundamental rich club structure is similar in MDD cases and controls, but subtle topological differences exist across the brain. Consistent with recent large-scale neuroimaging findings, our findings offer a connectomic perspective on a similar scale and support the idea that minimal differences exist between MDD cases and controls.

Synthesis of 9-(substituted phenoxycarbonyl)-10-methylacridinium trifluoromethanesulfonates: Effects of the leaving group on chemiluminescent properties.

Various 9-(substituted phenoxycarbonyl)-10-methylacridinium trifluoromethanesulfonates possessing electron-withdrawing substituents have been synthesized. The effect of substituents on the stability of the acridinium esters (AEs) at various temperatures in different buffers and the chemiluminescent properties have been examined. There was little correlation between the chemiluminescent properties of AEs and the pKa values of their associated phenols, but the steric effects of the ortho-substituents in the phenoxy group, as well as their electron-withdrawing natures, seem to play an important role in determining the properties. In general, when two identical substituents are present in the 2- and 6-positions, the compound is significantly more stable than when only a single substituent is present, presumably because of greater steric hindrance from the second group. The exception is the 2,6-difluorophenyl ester, which is less stable than the 2-fluorophenyl ester, presumably because the fluoro group is small. Addition of a third electron-withdrawing substituent at the 4-position, where it has no steric influence, typically increases susceptibility to decomposition. The presence of a nitro group has a significant destabilizing effect on AEs. Of the AEs studied, the 4-chlorophenyl ester showed the greatest chemiluminescent yield, while the 2-iodo-6-(trifluoromethyl)phenyl ester group showed the greatest stability in low pH buffers.

Predicting sex, age, general cognition and mental health with machine learning on brain structural connectomes.

There is an increasing expectation that advanced, computationally expensive machine learning (ML) techniques, when applied to large population-wide neuroimaging datasets, will help to uncover key differences in the human brain in health and disease. We take a comprehensive approach to explore how multiple aspects of brain structural connectivity can predict sex, age, general cognitive function and general psychopathology, testing different ML algorithms from deep learning (DL) model (BrainNetCNN) to classical ML methods. We modelled N = 8183 structural connectomes from UK Biobank using six different structural network weightings obtained from diffusion MRI. Streamline count generally provided the highest prediction accuracies in all prediction tasks. DL did not improve on prediction accuracies from simpler linear models. Further, high correlations between gradient attribution coefficients from DL and model coefficients from linear models suggested the models ranked the importance of features in similar ways, which indirectly suggested the similarity in models' strategies for making predictive decision to some extent. This highlights that model complexity is unlikely to improve detection of associations between structural connectomes and complex phenotypes with the current sample size.

Benchmarking network-based gene prioritization methods for cerebral small vessel disease.

Network-based gene prioritization algorithms are designed to prioritize disease-associated genes based on known ones using biological networks of protein interactions, gene-disease associations (GDAs) and other relationships between biological entities. Various algorithms have been developed based on different mechanisms, but it is not obvious which algorithm is optimal for a specific disease. To address this issue, we benchmarked multiple algorithms for their application in cerebral small vessel disease (cSVD). We curated protein-gene interactions (PGIs) and GDAs from databases and assembled PGI networks and disease-gene heterogeneous networks. A screening of algorithms resulted in seven representative algorithms to be benchmarked. Performance of algorithms was assessed using both leave-one-out cross-validation (LOOCV) and external validation with MEGASTROKE genome-wide association study (GWAS). We found that random walk with restart on the heterogeneous network (RWRH) showed best LOOCV performance, with median LOOCV rediscovery rank of 185.5 (out of 19 463 genes). The GenePanda algorithm had most GWAS-confirmable genes in top 200 predictions, while RWRH had best ranks for small vessel stroke-associated genes confirmed in GWAS. In conclusion, RWRH has overall better performance for application in cSVD despite its susceptibility to bias caused by degree centrality. Choice of algorithms should be determined before applying to specific disease. Current pure network-based gene prioritization algorithms are unlikely to find novel disease-associated genes that are not associated with known ones. The tools for implementing and benchmarking algorithms have been made available and can be generalized for other diseases.

Plasma neurofilament light chain concentrations are elevated in youth-onset type 2 diabetes and associated with neuropathy.

BACKGROUND AND AIMS: The lack of easily measurable biomarkers remains a challenge in executing clinical trials for diabetic neuropathy (DN). Plasma Neurofilament light chain (NFL) concentration is a promising biomarker in immune-mediated neuropathies. Longitudinal studies evaluating NFL in DN have not been performed. METHODS: A nested case-control study was performed on participants with youth-onset type 2 diabetes enrolled in the prospective Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) study. Plasma NFL concentrations were measured at 4-year intervals from 2008 to 2020 in 50 participants who developed DN and 50 participants with type 2 diabetes who did not develop DN. RESULTS: NFL concentrations were similar in the DN and no DN groups at the first assessment. Concentrations were higher in DN participants at all subsequent assessment periods (all p < .01). NFL concentrations increased over time in both groups, with higher degrees of change in DN participants (interaction p = .045). A doubling of the NFL value at Assessment 2 in those without DN increased the odds of ultimate DN outcome by an estimated ratio of 2.86 (95% CI: [1.30, 6.33], p = .0046). At the final study visit, positive Spearman correlations (controlled for age, sex, diabetes duration, and BMI) were observed between NFL and HbA1c (0.48, p < .0001), total cholesterol (0.25, p = .018), and low-density lipoprotein (LDL (0.30, p = .0037)). Negative correlations were observed with measures of heart rate variability (-0.42 to -0.46, p = <.0001). INTERPRETATION: The findings that NFL concentrations are elevated in individuals with youth-onset type 2 diabetes, and increase more rapidly in those who develop DN, suggest that NFL could be a valuable biomarker for DN.

Synthesis and chemiluminescent characteristics of two new acridinium esters.

Two new acridinium esters with a 2-(succinimidyloxycarbonyl)ethyl side arm, namely, 9-(2,6-dibromophenoxycarbonyl)-10-methyl-2-(2-(succinimidyloxycarbonyl)ethyl)acridinium trifluoromethanesulfonate and 9-(4-(2-(succinimidyloxycarbonyl)ethyl)phenoxycarbonyl)-2,7-dimethoxy-10-methylacridinium triflate, have been produced and characterized. The chemiluminescent properties and hydrolytic stabilities of the new acridinium esters have been investigated.

Synthesis, structure elucidation, and chemiluminescent activity of new 9-substituted 10-(ω-(succinimidyloxycarbonyl)alkyl)acridinium esters.

Several new acridinium esters 2-9 having their central acridinium ring bearing a 9-(2,5-dimethylphenoxycarbonyl), 9-(2,6-bis(trifluoromethyl)phenoxycarbonyl) or 9-(2,6-dinitrophenoxycarbonyl) group, and a 10-methyl, 10-(3-(succinimidyloxycarbonyl)propyl), 10-(5-(succinimidyloxycarbonyl)pentyl), or 10-(10-(succinimidyloxycarbonyl)decyl) group, have been synthesized and their chemiluminescent properties have been tested. The 2,5-dimethylphenyl acridinium esters emit light slowly (glow) when treated with alkaline hydrogen peroxide, while the 2,6-dinitrophenyl and 2,6-bis(trifluoromethyl)phenyl esters emit light rapidly (flash). The substituent at the 10 position affects the hydrolytic stabilities of the compounds.

Hierarchical Complexity of the Macro-Scale Neonatal Brain.

The human adult structural connectome has a rich nodal hierarchy, with highly diverse connectivity patterns aligned to the diverse range of functional specializations in the brain. The emergence of this hierarchical complexity in human development is unknown. Here, we substantiate the hierarchical tiers and hierarchical complexity of brain networks in the newborn period, assess correspondences with hierarchical complexity in adulthood, and investigate the effect of preterm birth, a leading cause of atypical brain development and later neurocognitive impairment, on hierarchical complexity. We report that neonatal and adult structural connectomes are both composed of distinct hierarchical tiers and that hierarchical complexity is greater in term born neonates than in preterms. This is due to diversity of connectivity patterns of regions within the intermediate tiers, which consist of regions that underlie sensorimotor processing and its integration with cognitive information. For neonates and adults, the highest tier (hub regions) is ordered, rather than complex, with more homogeneous connectivity patterns in structural hubs. This suggests that the brain develops first a more rigid structure in hub regions allowing for the development of greater and more diverse functional specialization in lower level regions, while connectivity underpinning this diversity is dysmature in infants born preterm.

Trisomy 21 dysregulates T cell lineages toward an autoimmunity-prone state associated with interferon hyperactivity.

Trisomy 21 (T21) causes Down syndrome (DS), a condition characterized by high prevalence of autoimmune disorders. However, the molecular and cellular mechanisms driving this phenotype remain unclear. Building upon our previous finding that T cells from people with DS show increased expression of interferon (IFN)-stimulated genes, we have completed a comprehensive characterization of the peripheral T cell compartment in adults with DS with and without autoimmune conditions. CD8+ T cells from adults with DS are depleted of naïve subsets and enriched for differentiated subsets, express higher levels of markers of activation and senescence (e.g., IFN-γ, Granzyme B, PD-1, KLRG1), and overproduce cytokines tied to autoimmunity (e.g., TNF-α). Conventional CD4+ T cells display increased differentiation, polarization toward the Th1 and Th1/17 states, and overproduction of the autoimmunity-related cytokines IL-17A and IL-22. Plasma cytokine analysis confirms elevation of multiple autoimmunity-related cytokines (e.g., TNF-α, IL17A-D, IL-22) in people with DS, independent of diagnosis of autoimmunity. Although Tregs are more abundant in DS, functional assays show that CD8+ and CD4+ effector T cells with T21 are resistant to Treg-mediated suppression, regardless of Treg karyotype. Transcriptome analysis of white blood cells and T cells reveals strong signatures of T cell differentiation and activation that correlate positively with IFN hyperactivity. Finally, mass cytometry analysis of 8 IFN-inducible phosphoepitopes demonstrates that T cell subsets with T21 show elevated levels of basal IFN signaling and hypersensitivity to IFN-α stimulation. Therefore, these results point to T cell dysregulation associated with IFN hyperactivity as a contributor to autoimmunity in DS.

Preparation of a novel group of chemiluminescent N-substituted acridinium esters.

Several novel N-substituted acridinium esters 7-16 containing a 10-methyl, 10-dodecyl, or 10-(ω-[succinimidyloxycarbonyl]alkyl) group have been synthesized and their chemiluminescent properties have been tested. Their chemiluminescent efficiencies and hydrolytic stabilities have been found to be affected by the characteristics of the group on the nitrogen atom. Dibromo-substituted leaving groups slightly accelerate the chemiluminescence process.

Spectral clustering based on structural magnetic resonance imaging and its relationship with major depressive disorder and cognitive ability.

There is increasing interest in using data-driven unsupervised methods to identify structural underpinnings of common mental illnesses, including major depressive disorder (MDD) and associated traits such as cognition. However, studies are often limited to severe clinical cases with small sample sizes and most do not include replication. Here, we examine two relatively large samples with structural magnetic resonance imaging (MRI), measures of lifetime MDD and cognitive variables: Generation Scotland (GS subsample, N = 980) and UK Biobank (UKB, N = 8,900), for discovery and replication, using an exploratory approach. Regional measures of FreeSurfer derived cortical thickness (CT), cortical surface area (CSA), cortical volume (CV) and subcortical volume (subCV) were input into a clustering process, controlling for common covariates. The main analysis steps involved constructing participant K-nearest neighbour graphs and graph partitioning with Markov stability to determine optimal clustering of participants. Resultant clusters were (1) checked whether they were replicated in an independent cohort and (2) tested for associations with depression status and cognitive measures. Participants separated into two clusters based on structural brain measurements in GS subsample, with large Cohen's d effect sizes between clusters in higher order cortical regions, commonly associated with executive function and decision making. Clustering was replicated in the UKB sample, with high correlations of cluster effect sizes for CT, CSA, CV and subCV between cohorts across regions. The identified clusters were not significantly different with respect to MDD case-control status in either cohort (GS subsample: pFDR = .2239-.6585; UKB: pFDR = .2003-.7690). Significant differences in general cognitive ability were, however, found between the clusters for both datasets, for CSA, CV and subCV (GS subsample: d = 0.2529-.3490, pFDR  < .005; UKB: d = 0.0868-0.1070, pFDR  < .005). Our results suggest that there are replicable natural groupings of participants based on cortical and subcortical brain measures, which may be related to differences in cognitive performance, but not to the MDD case-control status.

Synthetic Antibody Mimics Based on Cancer-Targeting Immunostimulatory Peptides.

De novo cancer-targeting immunostimulatory peptides have been designed and developed as synthetic antibody mimics. A series of bifunctional peptides incorporating NKp30-binding and NK-cell-activating domains were synthesized as linear dimers and then extended into branching trimeric peptides by the incorporation of GRP78-targeting and tumor-cell-binding sequences. A selected trimeric peptide from this small set of peptides displayed binding capabilities on GRP78+ HepG2 and A549 target cells. Cell binding diminished in the presence of an anti-GRP78 peptide blocker, thus suggesting GRP78-binding dependence. Similarly, the selected trimeric peptide was also found to exhibit NK cell binding in an NKp30-dependent manner, which translated into NK cell activation as indicated by cytokine secretion. In co-culture, fluorescence microscopy revealed that the target GFP-expressing A549 cells were visibly associated with the effector NK cells when pre-activated with lead trimeric peptide. Accordingly, A549 cells were found to be compromised, as evidenced by the loss of GFP signal and notable detection of early-/late-stage apoptosis. Investigation of the immunological markers related to toxicity revealed detectable secretion of pro-inflammatory cytokines and chemokines, including IFN-γ, TNF-α, and IL-8. Furthermore, administration of peptide-activated NK cells into A549-tumor-bearing mice resulted in a consistent decrease in tumor growth when compared to the untreated control group. Taken together, the identification of a lead trimeric peptide capable of targeting and activating NK cells' immunotoxicity directly towards GRP78+ /B7H6- tumors provides a novel proof-of-concept for the development of cancer-targeting immunostimulatory peptide ligands that mimic antibody-targeting and -activating functions related to cancer immunotherapy applications.

Brain network reorganisation and spatial lesion distribution in systemic lupus erythematosus.

OBJECTIVE: This work investigates network organisation of brain structural connectivity in systemic lupus erythematosus (SLE) relative to healthy controls and its putative association with lesion distribution and disease indicators. METHODS: White matter hyperintensity (WMH) segmentation and connectomics were performed in 47 patients with SLE and 47 healthy age-matched controls from structural and diffusion MRI data. Network nodes were divided into hierarchical tiers based on numbers of connections. Results were compared between patients and controls to assess for differences in brain network organisation. Voxel-based analyses of the spatial distribution of WMH in relation to network measures and SLE disease indicators were conducted. RESULTS: Despite inter-individual differences in brain network organization observed across the study sample, the connectome networks of SLE patients had larger proportion of connections in the peripheral nodes. SLE patients had statistically larger numbers of links in their networks with generally larger fractional anisotropy weights (i.e. a measure of white matter integrity) and less tendency to aggregate than those of healthy controls. The voxels exhibiting connectomic differences were coincident with WMH clusters, particularly the left hemisphere's intersection between the anterior limb of the internal and external capsules. Moreover, these voxels also associated more strongly with disease indicators. CONCLUSION: Our results indicate network differences reflective of compensatory reorganization of the neural circuits, reflecting adaptive or extended neuroplasticity in SLE.

Studies on a catalytic version of the Matteson asymmetric homologation reaction.

Studies of a catalytic asymmetric version of the Matteson reaction between dichloromethylboronates and organolithium reagents have been undertaken. From several different chiral catalytic systems studied, only one based on a mannitol derivative has given substantial asymmetric induction close to that previously achieved with a bis(oxazoline) derivative and ytterbium triflate. More detailed study of the latter reaction revealed that fresh ytterbium triflate actually reduced the level of asymmetric induction, while "aged" ytterbium triflate, or a fresh sample that had been treated with water, brought about improved induction. The implications of these findings are discussed.

Hierarchical complexity of the adult human structural connectome.

The structural network of the human brain has a rich topology which many have sought to characterise using standard network science measures and concepts. However, this characterisation remains incomplete and the non-obvious features of this topology have largely confounded attempts towards comprehensive constructive modelling. This calls for new perspectives. Hierarchical complexity is an emerging paradigm of complex network topology based on the observation that complex systems are composed of hierarchies within which the roles of hierarchically equivalent nodes display highly variable connectivity patterns. Here we test the hierarchical complexity of the human structural connectomes of a group of seventy-nine healthy adults. Binary connectomes are found to be more hierarchically complex than three benchmark random network models. This provides a new key description of brain structure, revealing a rich diversity of connectivity patterns within hierarchically equivalent nodes. Dividing the connectomes into four tiers based on degree magnitudes indicates that the most complex nodes are neither those with the highest nor lowest degrees but are instead found in the middle tiers. Spatial mapping of the brain regions in each hierarchical tier reveals consistency with the current anatomical, functional and neuropsychological knowledge of the human brain. The most complex tier (Tier 3) involves regions believed to bridge high-order cognitive (Tier 1) and low-order sensorimotor processing (Tier 2). We then show that such diversity of connectivity patterns aligns with the diversity of functional roles played out across the brain, demonstrating that hierarchical complexity can characterise functional diversity strictly from the network topology.

Young Adults' Experience of Appearance-Altering Orthognathic Surgery: A Longitudinal Interpretative Phenomenologic Analysis.

OBJECTIVE: To gain an experiential account of the processes of change associated specifically with orthognathic surgery. DESIGN: A qualitative design was used. Semistructured interviews were carried out with 7 participants approximately 1 week before and 6-8 weeks after surgery. The data were analyzed using interpretative phenomenologic analysis (IPA). SETTING: Participants were recruited from a NHS Dental Hospital. PARTICIPANTS: Patients aged 16 to 25 years scheduled to undergo orthognathic surgery on both the upper and lower jaws were purposively sought to participate. Seven participants aged between 18 and 25 years and who had undergone a bimaxillary osteotomy completed interviews (5 females and 2 males). RESULTS: Themes were identified in connection with the overall journey of treatment being a rite of passage; the treatment's role in raising awareness about the anomalies in appearance; the initial shock at the changes that followed surgery; the uncertainty about treatment; the impact of actual negative reactions of others; and the role of significant others in the decision-making process. CONCLUSIONS: Participants described undergoing a much more complex process of adjustment to change in appearance than has been identified elsewhere within the literature, and the study highlights the nuanced fashion in which both medical and parental communication influence patient expectation and experience of surgery. There is a need to improve communication between clinicians, families, and young adults seeking orthognathic surgery. Further studies are needed to investigate the processes associated with seeking to change facial appearance resulting from other forms of dentofacial condition.

Desmoplakin Variants Are Associated with Idiopathic Pulmonary Fibrosis.

RATIONALE: Sequence variation, methylation differences, and transcriptional changes in desmoplakin (DSP) have been observed in patients with idiopathic pulmonary fibrosis (IPF). OBJECTIVES: To identify novel variants in DSP associated with IPF and to characterize the relationship of these IPF sequence variants with DSP gene expression in human lung. METHODS: A chromosome 6 locus (7,370,061-7,606,946) was sequenced in 230 subjects with IPF and 228 control subjects. Validation genotyping of disease-associated variants was conducted in 936 subjects with IPF and 936 control subjects. DSP gene expression was measured in lung tissue from 334 subjects with IPF and 201 control subjects. MEASUREMENTS AND MAIN RESULTS: We identified 23 sequence variants in the chromosome 6 locus associated with IPF. Genotyping of selected variants in our validation cohort revealed that noncoding intron 1 variant rs2744371 (odds ratio = 0.77, 95% confidence interval [CI] = 0.66-0.91, P = 0.002) is protective for IPF, and a previously described IPF-associated intron 5 variant (rs2076295) is associated with increased risk of IPF (odds ratio = 1.36, 95% CI = 1.19-1.56, P < 0.001) after controlling for sex and age. DSP expression is 2.3-fold increased (95% CI = 1.91-2.71) in IPF lung tissue (P < 0.0001). Only the minor allele at rs2076295 is associated with decreased DSP expression (P = 0.001). Staining of fibrotic and normal human lung tissue localized DSP to airway epithelia. CONCLUSIONS: Sequence variants in DSP are associated with IPF, and rs2076295 genotype is associated with differential expression of DSP in the lung. DSP expression is increased in IPF lung and concentrated in the airway epithelia, suggesting a potential role for DSP in the pathogenesis of IPF.

Genome-wide imputation study identifies novel HLA locus for pulmonary fibrosis and potential role for auto-immunity in fibrotic idiopathic interstitial pneumonia.

BACKGROUND: Fibrotic idiopathic interstitial pneumonias (fIIP) are a group of fatal lung diseases with largely unknown etiology and without definitive treatment other than lung transplant to prolong life. There is strong evidence for the importance of both rare and common genetic risk alleles in familial and sporadic disease. We have previously used genome-wide single nucleotide polymorphism data to identify 10 risk loci for fIIP. Here we extend that work to imputed genome-wide genotypes and conduct new RNA sequencing studies of lung tissue to identify and characterize new fIIP risk loci. RESULTS: We performed genome-wide genotype imputation association analyses in 1616 non-Hispanic white (NHW) cases and 4683 NHW controls followed by validation and replication (878 cases, 2017 controls) genotyping and targeted gene expression in lung tissue. Following meta-analysis of the discovery and replication populations, we identified a novel fIIP locus in the HLA region of chromosome 6 (rs7887 P meta = 3.7 × 10(-09)). Imputation of classic HLA alleles identified two in high linkage disequilibrium that are associated with fIIP (DRB1*15:01 P = 1.3 × 10(-7) and DQB1*06:02 P = 6.1 × 10(-8)). Targeted RNA-sequencing of the HLA locus identified 21 genes differentially expressed between fibrotic and control lung tissue (Q < 0.001), many of which are involved in immune and inflammatory response regulation. In addition, the putative risk alleles, DRB1*15:01 and DQB1*06:02, are associated with expression of the DQB1 gene among fIIP cases (Q < 1 × 10(-16)). CONCLUSIONS: We have identified a genome-wide significant association between the HLA region and fIIP. Two HLA alleles are associated with fIIP and affect expression of HLA genes in lung tissue, indicating that the potential genetic risk due to HLA alleles may involve gene regulation in addition to altered protein structure. These studies reveal the importance of the HLA region for risk of fIIP and a basis for the potential etiologic role of auto-immunity in fIIP.

Emission of methane, carbon monoxide, carbon dioxide and short-chain hydrocarbons from vegetation foliage under ultraviolet irradiation.

The original report that plants emit methane (CH4 ) under aerobic conditions caused much debate and controversy. Critics questioned experimental techniques, possible mechanisms for CH4 production and the nature of estimating global emissions. Several studies have now confirmed that aerobic CH4 emissions can be detected from plant foliage but the extent of the phenomenon in plants and the precise mechanisms and precursors involved remain uncertain. In this study, we investigated the role of environmentally realistic levels of ultraviolet (UV) radiation in causing the emission of CH4 and other gases from foliage obtained from a wide variety of plant types. We related our measured emissions to the foliar content of methyl esters and lignin and to the epidermal UV absorbance of the species investigated. Our data demonstrate that the terrestrial vegetation foliage sampled did emit CH4 , with a range in emissions of 0.6-31.8 ng CH4 g(-1) leaf DW h(-1) , which compares favourably with the original reports of experimental work. In addition to CH4 emissions, our data show that carbon monoxide, ethene and propane are also emitted under UV stress but we detected no significant emissions of carbon dioxide or ethane.