Current work emphasizes that peripheral tissue injury and inflammation results in a heightened sensitivity to subsequent noxious input (hyperalgesia) that is mediated in large part by the spinal synthesis and release of eicosanoids, in particular prostaglandins. Secreted phospholipase A(2)s (sPLA(2)s) form a class of structurally related enzymes that release arachidonic acid from cell membranes that is further processed to produce eicosanoids. We hypothesized that spinal sPLA(2)s may contribute to inflammation-induced hyperalgesia. Spinal cord tissue and cerebrospinal fluid were collected from rats for assessment of sPLA(2) protein expression and sPLA(2) activity. A basal sPLA(2) protein expression and activity was detected in spinal cord homogenate (87+/-17 pmol/min/mg), though no activity could be detected in cisternal cerebrospinal fluid, of naive rats. The sPLA(2) activity did not change in spinal cord tissue or cerebrospinal fluid assessed over 8 h after injection of carrageenan into the hind paw. However, the sPLA(2) activity observed in spinal cord homogenates was suppressed by addition of LY311727, a selective sPLA(2) inhibitor. To determine the role of this spinal sPLA(2) in hyperalgesia, we assessed the effects of lumbar intrathecal (IT) administration of LY311727 in rats with chronic IT catheters in three experimental models of hyperalgesia. IT LY311727 (3-30 microg) dose-dependently prevented intraplantar carrageenan-induced thermal hyperalgesia and formalin-induced flinching, at doses that had no effect on motor function. IT LY311727 also suppressed thermal hyperalgesia induced by IT injection of substance P (30 nmol). Using in vivo spinal microdialysis, we found that IT injection of LY311727 attenuated prostaglandin E(2) release into spinal dialysate otherwise evoked by the IT injection of substance P. Taken together, this work points to a role for constitutive sPLA(2)s in spinal nociceptive processing.

Asthma is a chronic inflammatory disease affecting the lung, characterized by breathing difficulty during an attack following exposure to an environmental trigger. Calcitonin gene-related peptide (CGRP) is a neuropeptide that may have a pathological role i

A commonly carried C677T polymorphism in a folate-related gene, MTHFR, is associated with higher plasma homocysteine, a well-known mediator of neuronal damage and brain atrophy. As homocysteine promotes brain atrophy, we set out to discover whether people

Background and purpose

Toll-like receptor 4 (TLR4) expressed on spinal microglia and astrocytes has been suggested to play an important role in the regulation of pain signalling. The purpose of the present work was to examine the links between TLR4, glial activation and spinal release of prostaglandin E(2) (PGE(2)) and tumour necrosis factor (TNF), and the role these factors play in TLR4-induced tactile allodynia.

Experimental approach

Toll-like receptor 4 was activated by intrathecal (i.t.) injection of lipopolysaccharide (LPS) and KDO(2)-Lipid A (KDO(2)) to rats. Tactile allodynia was assessed using von Frey filaments and cerebrospinal fluid collected through spinal dialysis and lumbar puncture. PGE(2) and TNF levels were measured by mass spectometry and elisa. Minocycline and pentoxifylline (glia inhibitors), etanercept (TNF-blocker) and ketorolac (COX-inhibitor) were given i.t. prior to injection of the TLR4-agonists, in order to determine if these agents alter TLR4-mediated nociception and the spinal release of PGE(2) and TNF.

Key results

Spinal administration of LPS and KDO(2) produced a dose-dependent tactile allodynia, which was attenuated by pentoxifylline, minocycline and etanercept but not ketorolac. Both TLR4 agonists induced the spinal release of PGE(2) and TNF. Intrathecal pentoxifylline blunted PGE(2) and TNF release, while i.t. minocycline only prevented the spinal release of TNF. The release of PGE(2) induced by LPS and KDO(2) was attenuated by i.t. administration of ketorolac.

Conclusions and implications

Activation of TLR4 induces tactile allodynia, which is probably mediated by TNF released by activated spinal glia.

High-quality draft genome sequences were determined for 10 Exiguobacterium strains in order to provide insight into their evolutionary strategies for speciation and environmental adaptation. The selected genomes include psychrotrophic and thermophilic species from a range of habitats, which will allow for a comparison of metabolic pathways and stress response genes.

Background

Two acute respiratory distress syndrome (ARDS) subphenotypes (hyperinflammatory and hypoinflammatory) with distinct clinical and biological features and differential treatment responses have been identified using latent class analysis (LCA) in seven individual cohorts. To facilitate bedside identification of subphenotypes, clinical classifier models using readily available clinical variables have been described in four randomised controlled trials. We aimed to assess the performance of these models in observational cohorts of ARDS.

Methods

In this observational, multicohort, retrospective study, we validated two machine-learning clinical classifier models for assigning ARDS subphenotypes in two observational cohorts of patients with ARDS: Early Assessment of Renal and Lung Injury (EARLI; n=335) and Validating Acute Lung Injury Markers for Diagnosis (VALID; n=452), with LCA-derived subphenotypes as the gold standard. The primary model comprised only vital signs and laboratory variables, and the secondary model comprised all predictors in the primary model, with the addition of ventilatory variables and demographics. Model performance was assessed by calculating the area under the receiver operating characteristic curve (AUC) and calibration plots, and assigning subphenotypes using a probability cutoff value of 0·5 to determine sensitivity, specificity, and accuracy of the assignments. We also assessed the performance of the primary model in EARLI using data automatically extracted from an electronic health record (EHR; EHR-derived EARLI cohort). In Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE; n=2813), a multinational, observational ARDS cohort, we applied a custom classifier model (with fewer variables than the primary model) to determine the prognostic value of the subphenotypes and tested their interaction with the positive end-expiratory pressure (PEEP) strategy, with 90-day mortality as the dependent variable.

Findings

The primary clinical classifier model had an area under receiver operating characteristic curve (AUC) of 0·92 (95% CI 0·90-0·95) in EARLI and 0·88 (0·84-0·91) in VALID. Performance of the primary model was similar when using exclusively EHR-derived predictors compared with manually curated predictors (AUC=0·88 [95% CI 0·81-0·94] vs 0·92 [0·88-0·97]). In LUNG SAFE, 90-day mortality was higher in patients assigned the hyperinflammatory subphenotype than in those with the hypoinflammatory phenotype (414 [57%] of 725 vs 694 [33%] of 2088; p<0·0001). There was a significant treatment interaction with PEEP strategy and ARDS subphenotype (p=0·041), with lower 90-day mortality in the high PEEP group of patients with the hyperinflammatory subphenotype (hyperinflammatory subphenotype: 169 [54%] of 313 patients in the high PEEP group vs 127 [62%] of 205 patients in the low PEEP group; hypoinflammatory subphenotype: 231 [34%] of 675 patients in the high PEEP group vs 233 [32%] of 734 patients in the low PEEP group).

Interpretation

Classifier models using clinical variables alone can accurately assign ARDS subphenotypes in observational cohorts. Application of these models can provide valuable prognostic information and could inform management strategies for personalised treatment, including application of PEEP, once prospectively validated.

Funding

US National Institutes of Health and European Society of Intensive Care Medicine.