A robust COVID-19 mortality prediction calculator based on Lymphocyte count, Urea, C-Reactive Protein, Age and Sex (LUCAS) with chest X-rays.

There have been numerous risk tools developed to enable triaging of SARS-CoV-2 positive patients with diverse levels of complexity. Here we presented a simplified risk-tool based on minimal parameters and chest X-ray (CXR) image data that predicts the survival of adult SARS-CoV-2 positive patients at hospital admission. We analysed the NCCID database of patient blood variables and CXR images from 19 hospitals across the UK using multivariable logistic regression. The initial dataset was non-randomly split between development and internal validation dataset with 1434 and 310 SARS-CoV-2 positive patients, respectively. External validation of the final model was conducted on 741 Accident and Emergency (A&E) admissions with suspected SARS-CoV-2 infection from a separate NHS Trust. The LUCAS mortality score included five strongest predictors (Lymphocyte count, Urea, C-reactive protein, Age, Sex), which are available at any point of care with rapid turnaround of results. Our simple multivariable logistic model showed high discrimination for fatal outcome with the area under the receiving operating characteristics curve (AUC-ROC) in development cohort 0.765 (95% confidence interval (CI): 0.738-0.790), in internal validation cohort 0.744 (CI: 0.673-0.808), and in external validation cohort 0.752 (CI: 0.713-0.787). The discriminatory power of LUCAS increased slightly when including the CXR image data. LUCAS can be used to obtain valid predictions of mortality in patients within 60 days of SARS-CoV-2 RT-PCR results into low, moderate, high, or very high risk of fatality.

Development of a Mortality Prediction Model in Hospitalised SARS-CoV-2 Positive Patients Based on Routine Kidney Biomarkers.

Acute kidney injury (AKI) is a prevalent complication in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive inpatients, which is linked to an increased mortality rate compared to patients without AKI. Here we analysed the difference in kidney blood biomarkers in SARS-CoV-2 positive patients with non-fatal or fatal outcome, in order to develop a mortality prediction model for hospitalised SARS-CoV-2 positive patients. A retrospective cohort study including data from suspected SARS-CoV-2 positive patients admitted to a large National Health Service (NHS) Foundation Trust hospital in the Yorkshire and Humber regions, United Kingdom, between 1 March 2020 and 30 August 2020. Hospitalised adult patients (aged ≥ 18 years) with at least one confirmed positive RT-PCR test for SARS-CoV-2 and blood tests of kidney biomarkers within 36 h of the RT-PCR test were included. The main outcome measure was 90-day in-hospital mortality in SARS-CoV-2 infected patients. The logistic regression and random forest (RF) models incorporated six predictors including three routine kidney function tests (sodium, urea; creatinine only in RF), along with age, sex, and ethnicity. The mortality prediction performance of the logistic regression model achieved an area under receiver operating characteristic (AUROC) curve of 0.772 in the test dataset (95% CI: 0.694-0.823), while the RF model attained the AUROC of 0.820 in the same test cohort (95% CI: 0.740-0.870). The resulting validated prediction model is the first to focus on kidney biomarkers specifically on in-hospital mortality over a 90-day period.

DenResCov-19: A deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays.

The global pandemic of coronavirus disease 2019 (COVID-19) is continuing to have a significant effect on the well-being of the global population, thus increasing the demand for rapid testing, diagnosis, and treatment. As COVID-19 can cause severe pneumonia, early diagnosis is essential for correct treatment, as well as to reduce the stress on the healthcare system. Along with COVID-19, other etiologies of pneumonia and Tuberculosis (TB) constitute additional challenges to the medical system. Pneumonia (viral as well as bacterial) kills about 2 million infants every year and is consistently estimated as one of the most important factor of childhood mortality (according to the World Health Organization). Chest X-ray (CXR) and computed tomography (CT) scans are the primary imaging modalities for diagnosing respiratory diseases. Although CT scans are the gold standard, they are more expensive, time consuming, and are associated with a small but significant dose of radiation. Hence, CXR have become more widespread as a first line investigation. In this regard, the objective of this work is to develop a new deep transfer learning pipeline, named DenResCov-19, to diagnose patients with COVID-19, pneumonia, TB or healthy based on CXR images. The pipeline consists of the existing DenseNet-121 and the ResNet-50 networks. Since the DenseNet and ResNet have orthogonal performances in some instances, in the proposed model we have created an extra layer with convolutional neural network (CNN) blocks to join these two models together to establish superior performance as compared to the two individual networks. This strategy can be applied universally in cases where two competing networks are observed. We have tested the performance of our proposed network on two-class (pneumonia and healthy), three-class (COVID-19 positive, healthy, and pneumonia), as well as four-class (COVID-19 positive, healthy, TB, and pneumonia) classification problems. We have validated that our proposed network has been able to successfully classify these lung-diseases on our four datasets and this is one of our novel findings. In particular, the AUC-ROC are 99.60, 96.51, 93.70, 96.40% and the F1 values are 98.21, 87.29, 76.09, 83.17% on our Dataset X-Ray 1, 2, 3, and 4 (DXR1, DXR2, DXR3, DXR4), respectively.

Co-Incubation with PPARß/δ Agonists and Antagonists Modeled Using Computational Chemistry: Effect on LPS Induced Inflammatory Markers in Pulmonary Artery.

Peroxisome proliferator activated receptor beta/delta (PPARß/δ) is a nuclear receptor ubiquitously expressed in cells, whose signaling controls inflammation. There are large discrepancies in understanding the complex role of PPARß/δ in disease, having both anti- and pro-effects on inflammation. After ligand activation, PPARß/δ regulates genes by two different mechanisms; induction and transrepression, the effects of which are difficult to differentiate directly. We studied the PPARß/δ-regulation of lipopolysaccharide (LPS) induced inflammation (indicated by release of nitrite and IL-6) of rat pulmonary artery, using different combinations of agonists (GW0742 or L-165402) and antagonists (GSK3787 or GSK0660). LPS induced release of NO and IL-6 is not significantly reduced by incubation with PPARß/δ ligands (either agonist or antagonist), however, co-incubation with an agonist and antagonist significantly reduces LPS-induced nitrite production and Nos2 mRNA expression. In contrast, incubation with LPS and PPARß/δ agonists leads to a significant increase in Pdk-4 and Angptl-4 mRNA expression, which is significantly decreased in the presence of PPARß/δ antagonists. Docking using computational chemistry methods indicates that PPARß/δ agonists form polar bonds with His287, His413 and Tyr437, while antagonists are more promiscuous about which amino acids they bind to, although they are very prone to bind Thr252 and Asn307. Dual binding in the PPARß/δ binding pocket indicates the ligands retain similar binding energies, which suggests that co-incubation with both agonist and antagonist does not prevent the specific binding of each other to the large PPARß/δ binding pocket. To our knowledge, this is the first time that the possibility of binding two ligands simultaneously into the PPARß/δ binding pocket has been explored. Agonist binding followed by antagonist simultaneously switches the PPARß/δ mode of action from induction to transrepression, which is linked with an increase in Nos2 mRNA expression and nitrite production.

Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population.

Since December 2019 the novel coronavirus SARS-CoV-2 has been identified as the cause of the pandemic COVID-19. Early symptoms overlap with other common conditions such as common cold and Influenza, making early screening and diagnosis are crucial goals for health practitioners. The aim of the study was to use machine learning (ML), an artificial neural network (ANN) and a simple statistical test to identify SARS-CoV-2 positive patients from full blood counts without knowledge of symptoms or history of the individuals. The dataset included in the analysis and training contains anonymized full blood counts results from patients seen at the Hospital Israelita Albert Einstein, at São Paulo, Brazil, and who had samples collected to perform the SARS-CoV-2 rt-PCR test during a visit to the hospital. Patient data was anonymised by the hospital, clinical data was standardized to have a mean of zero and a unit standard deviation. This data was made public with the aim to allow researchers to develop ways to enable the hospital to rapidly predict and potentially identify SARS-CoV-2 positive patients. We find that with full blood counts random forest, shallow learning and a flexible ANN model predict SARS-CoV-2 patients with high accuracy between populations on regular wards (AUC = 94-95%) and those not admitted to hospital or in the community (AUC = 80-86%). Here, AUC is the Area Under the receiver operating characteristics Curve and a measure for model performance. Moreover, a simple linear combination of 4 blood counts can be used to have an AUC of 85% for patients within the community. The normalised data of different blood parameters from SARS-CoV-2 positive patients exhibit a decrease in platelets, leukocytes, eosinophils, basophils and lymphocytes, and an increase in monocytes. SARS-CoV-2 positive patients exhibit a characteristic immune response profile pattern and changes in different parameters measured in the full blood count that are detected from simple and rapid blood tests. While symptoms at an early stage of infection are known to overlap with other common conditions, parameters of the full blood counts can be analysed to distinguish the viral type at an earlier stage than current rt-PCR tests for SARS-CoV-2 allow at present. This new methodology has potential to greatly improve initial screening for patients where PCR based diagnostic tools are limited.

Discovery of novel small molecule inhibitors of S100P with in vitro anti-metastatic effects on pancreatic cancer cells.

S100P, a calcium-binding protein, is known to advance tumor progression and metastasis in pancreatic and several other cancers. Herein is described the in silico identification of a putative binding pocket of S100P to identify, synthesize and evaluate novel small molecules with the potential to selectively bind S100P and inhibit its activation of cell survival and metastatic pathways. The virtual screening of a drug-like database against the S100P model led to the identification of over 100 clusters of diverse scaffolds. A representative test set identified a number of structurally unrelated hits that inhibit S100P-RAGE interaction, measured by ELISA, and reduce in vitro cell invasion selectively in S100P-expressing pancreatic cancer cells at 10 µM. This study establishes a proof of concept in the potential for rational design of small molecule S100P inhibitors for drug candidate development.

Thyroid Hormone Receptor Antagonists: From Environmental Pollution to Novel Small Molecules.

Thyroid hormone receptors (TRs) are nuclear receptors which control transcription, and thereby have effects in all cells within the body. TRs are an important regulator in many basic physiological processes including development, growth, metabolism, and cardiac function. The hyperthyroid condition results from an over production of thyroid hormones resulting in a continual stimulation of thyroid receptors which is detrimental for the patient. Therapies for hyperthyroidism are available, but there is a need for new small molecules that act as TR antagonists to treat hyperthyroidism. Many compounds exhibit TR antagonism and are considered detrimental to health. Some drugs in the clinic (most importantly, amiodarone) and environmental pollution exhibit TR antagonist properties and thus have the potential to induce hypothyroidism in some people. This chapter provides an overview of novel small molecules that have been specifically designed or screened for their TR antagonist activity as novel treatments for hyperthyroidism. While novel compounds have been identified, to date none have been developed sufficiently to enter clinical trials. Furthermore, a discussion on other sources of TR antagonists is discussed in terms of side effects of current drugs in the clinic as well as environmental pollution.

The Non-Genomic Effects of the PPARßγ Agonist GW0742 on Streptozotocin Treated Rat Aorta.

BACKGROUND: The ubiquitous nuclear receptor PPARß/δ is increasingly being studied in regards to numerous diseases including diabetes following on the finding that PPARß/δ agonist GW0742 controls Type 1 Diabetes in rats. Studies have shown that GW0742 has off target, non- PPARß/δ effects in the cell although there are some key questions that remain to be addressed in respect to the significance of this control on vascular tone. METHODS: Using isometric organ baths, rat aorta rings were exposed to ROCK inhibitors and the changes in contraction and dilation measured. RESULTS: Our data shows that the PPARß/δ agonist GW0742 (10-7M) inhibits contractile responses to U46619 and phenylephrine, and that these responses are similar in normal and Streptozotocin (STZ) diabetic rat aorta. ROCK inhibitors Fasudil and Y27632 significantly reduced GW0742 mediated dilation of naïve rat aorta, but Fasudil had no effect on GW0742 dilation in STZ diabetic rat aorta. In contrast, STZ diabetic rat aorta pre-contracted with high [K+] Krebs lacked a dilatory response to GW0742, which taken together indicates that the mechanism of action of GW0742 mediated dilation changes in the diabetic state compared to non-diabetic state. CONCLUSION: This is the first direct evidence demonstrating the non- PPARß/δ effect of GW0742 on contraction is irrespective to the diabetic state, and that GW0742 has the potential to induce vasodilation via multiple off-target mechanisms.

Methylglyoxal, A Metabolite Increased in Diabetes is Associated with Insulin Resistance, Vascular Dysfunction and Neuropathies.

BACKGROUND: Diabetes mellitus (DM) is a pandemic metabolic disease characterized by a chronically elevated blood glucose concentration (hyperglycemia) due to insulin dysfunction. Approximately 50% of diabetics show diabetes complications by the time they are diagnosed. Vascular dysfunction, nephropathy and neuropathic pain are common diabetes complications. Chronic hyperglycemia contributes to reactive oxygen species (ROS) generation such as methylglyoxal (MGO). METHODS: Peer reviewed research papers were studied through bibliographic databases searching focused on review questions and inclusion/exclusion criteria. The reviewed papers were appraised according to the searching focus. The characteristics of screened papers were described, and a deductive qualitative content analysis methodology was applied to the included studies using a conceptual framework to yield this comprehensive systematic review. RESULTS: Sixty-six papers were included in this review. Eleven papers related methylglyoxal generation to carbohydrates metabolism, ten papers related lipid metabolism to methylglyoxal and 5 papers showed the proteolytic pathways that contribute to methylglyoxal generation. Methylglyoxal metabolism was derived from 7 papers. Descriptive figure 1 was drawn to explain methylglyoxal sources and how diabetes increases methylglyoxal generation. Furthermore, twenty-six papers related methylglyoxal to diabetes complications from which 9 papers showed methylglyoxal ability to induce insulin dysfunction, an effect which was described in schematic figure 2. Additionally, fifteen papers revealed methylglyoxal contribution to vascular dysfunction and 3 papers showed methylglyoxal to cause neuropathic pain. Methylglyoxal-induced vascular dysfunction was drawn in a comprehensive figure 3. This review correlated methylglyoxal with diabetes and diabetes complications which were summarised in table 1. CONCLUSION: The findings of this review suggesting methylglyoxal as an essential therapeutic target for managing diabetes in the future.

A New NO-Releasing Nanoformulation for the Treatment of Pulmonary Arterial Hypertension.

Pulmonary arterial hypertension (PAH) is a chronic and progressive disease which continues to carry an unacceptably high mortality and morbidity. The nitric oxide (NO) pathway has been implicated in the pathophysiology and progression of the disease. Its extremely short half-life and systemic effects have hampered the clinical use of NO in PAH. In an attempt to circumvent these major limitations, we have developed a new NO-nanomedicine formulation. The formulation was based on hydrogel-like polymeric composite NO-releasing nanoparticles (NO-RP). The kinetics of NO release from the NO-RP showed a peak at about 120 min followed by a sustained release for over 8 h. The NO-RP did not affect the viability or inflammation responses of endothelial cells. The NO-RP produced concentration-dependent relaxations of pulmonary arteries in mice with PAH induced by hypoxia. In conclusion, NO-RP drugs could considerably enhance the therapeutic potential of NO therapy for PAH.

Evidence that diclofenac and celecoxib are thyroid hormone receptor beta antagonists.

UNLABELLED: Long term use of NSAIDs is linked to side effects such as gastric bleeding and myocardial infarction. AIMS: Use of in silico methods and pharmacology to investigate the potential for NSAIDs diclofenac, celecoxib and naproxen to bind to nuclear receptors. MATERIALS AND METHODS: In silico screening predicted that both diclofenac and celecoxib has the potential to bind to a number of different nuclear receptors; docking analysis confirmed a theoretical ability for diclofenac and celecoxib but not naproxen to bind to TRß. KEY FINDINGS: Results from TRß luciferase reporter assays confirmed that both diclofenac and celecoxib display TRß antagonistic properties; celecoxib, IC50 3.6 × 10(-6)M, and diclofenac IC50 5.3 × 10(-6)M, comparable to the TRß antagonist MLS (IC50 3.1 × 10(-6)M). In contrast naproxen, a cardio-sparing NSAID, lacked TRß antagonist effects. In order to determine the effects of NSAIDs in whole organ in vitro, we used isometric wire myography to measure the changes to Triiodothyronine (T3) induced vasodilation of rat mesenteric arteries. Incubation of arteries in the presence of the TRß antagonist MLS000389544 (10(-5)M), as well as diclofenac (10(-5)M) and celecoxib (10(-5)M) but not naproxen significantly inhibited T3 induced vasodilation compared to controls. SIGNIFICANCE: These results highlight the benefits of computational chemistry methods used to retrospectively analyse well known drugs for side effects. Using in silico and in vitro methods we have shown that both celecoxib and diclofenac but not naproxen exhibit off-target TRß antagonist behaviour, which may be linked to their detrimental side effects.

In silico modelling of prostacyclin and other lipid mediators to nuclear receptors reveal novel thyroid hormone receptor antagonist properties.

Prostacyclin (PGI2) is a key mediator involved in cardiovascular homeostasis, acting predominantly on two receptor types; cell surface IP receptor and cytosolic peroxisome proliferator activated receptor (PPAR) ß/δ. Having a very short half-life, direct methods to determine its long term effects on cells is difficult, and little is known of its interactions with nuclear receptors. Here we used computational chemistry methods to investigate the potential for PGI2, beraprost (IP receptor agonist), and GW0742 (PPARß/δ agonist), to bind to nuclear receptors, confirmed with pharmacological methods. In silico screening predicted that PGI2, beraprost, and GW0742 have the potential to bind to different nuclear receptors, in particular thyroid hormone ß receptor (TRß) and thyroid hormone α receptor (TRα). Docking analysis predicts a binding profile to residues thought to have allosteric control on the TR ligand binding site. Luciferase reporter assays confirmed that beraprost and GW0742 display TRß and TRα antagonistic properties; beraprost IC50 6.3 × 10(-5)mol/L and GW0742 IC50 4.9 × 10(-6) mol/L. Changes to triiodothyronine (T3) induced vasodilation of rat mesenteric arteries measured on the wire myograph were measured in the presence of the TR antagonist MLS000389544 (10(-5) mol/L), beraprost (10(-5) mol/L) and GW0742 (10(-5) mol/L); all significantly inhibited T3 induced vasodilation compared to controls. We have shown that both beraprost and GW0742 exhibit TRß and TRα antagonist behaviour, and suggests that PGI2 has the ability to affect the long term function of cells through binding to and inactivating thyroid hormone receptors.

Selective inhibition of NADPH oxidase reverses the over contraction of diabetic rat aorta.

Abnormal vascular responsiveness in diabetes has been attributed to a number of changes in contractile pathways, affected in part by the overproduction of reactive oxygen species (ROS). It has been reported that NADPH oxidase (NOX) is increased in diabetic (streptozotocin treated; STZ) rat arteries; however the pharmacological agents used to inhibit NOX activity are known to be unsuitable for in vitro studies and have a high level of non-selectivity. Here we have used the highly selective NOX inhibitor VAS2870 in diabetic rat aorta and compared its effects with apocynin, SOD, and allopurinol on phenylephrine and U46619 induced contraction. Male Wistar rats were injected intraperitoneally with 65mg/kg STZ and development of diabetes was confirmed by testing blood glucose levels. Rats were killed by CO2 asphyxiation, and the thoracic aorta removed and mounted in an organ bath under a tension of 1g. Diabetic rat aortas exhibit a greatly increased response to phenylephrine, which was reduced to a level consistent with control rat aorta by 10(-5)M VAS2870 and 150U/ml SOD. Incubation with VAS2870 led to an increase in normal rat aorta contraction, but led to a significant reduction in phenylephrine and U46619 induced tone in diabetic rat aorta, which indicates that ROS in diabetic rats directly contributes to these contractile responses. Apocynin and allopurinol had no effect on contraction in diabetic or normal rat aorta. This data is the first to show that selective inhibition of NOX reduces diabetic arterial contraction in direct comparison with inhibition of other known contributors of ROS.

Role of prostacyclin in pulmonary hypertension.

Prostacyclin is a powerful cardioprotective hormone released by the endothelium of all blood vessels. Prostacyclin exists in equilibrium with other vasoactive hormones and a disturbance in the balance of these factors leads to cardiovascular disease including pulmonary arterial hypertension. Since it's discovery in the 1970s concerted efforts have been made to make the best therapeutic utility of prostacyclin, particularly in the treatment of pulmonary arterial hypertension. This has centred on working out the detailed pharmacology of prostacyclin and then synthesising new molecules based on its structure that are more stable or more easily tolerated. In addition, newer molecules have been developed that are not analogues of prostacyclin but that target the receptors that prostacyclin activates. Prostacyclin and related drugs have without doubt revolutionised the treatment and management of pulmonary arterial hypertension but are seriously limited by side effects within the systemic circulation. With the dawn of nanomedicine and targeted drug or stem cell delivery systems it will, in the very near future, be possible to make new formulations of prostacyclin that can evade the systemic circulation allowing for safe delivery to the pulmonary vessels. In this way, the full therapeutic potential of prostacyclin can be realised opening the possibility that pulmonary arterial hypertension will become, if not curable, a chronic manageable disease that is no longer fatal. This review discusses these and other issues relating to prostacyclin and its use in pulmonary arterial hypertension.

Harnessing the benefits of PPARß/δ agonists.

Lipid mediators have complex effects on the cell; one of the key transcriptional factors that moderate proliferation and inflammatory effects is PPARß/δ. Following highly successful clinical trials using the PPARß/δ agonists GW501516 for treatment of diabetes, GSK announced that any further research would be discontinued due to preclinical trials in rodents which linked this drug to wide spread tumour development. In this review we outline the dual molecular functions of PPARß/δ and connect these to the diverse results from in vitro studies, and draw parallels with the outcomes of animal and human studies. The PPARß/δ agonists have a great potential in terms of therapy, and we hope to provide some insight into the reasons why such contrasting results have been published. The discussion presented here is important to the future development of PPARß/δ agonists for the clinic, and for a fuller understanding for their complex regulatory roles in the cell.

Linking phospholipase C isoforms with differentiation function in human vascular smooth muscle cells.

The phosphoinositol-phospholipase C (PLC) family of enzymes consists of a number of isoforms, each of which has different cellular functions. PLCγ1 is primarily linked to tyrosine kinase transduction pathways, whereas PLCδ1 has been associated with a number of regulatory proteins, including those controlling the cell cycle. Recent studies have shown a central role of PLC in cell organisation and in regulating a wide array of cellular responses. It is of importance to define the precise role of each isoform, and how this changes the functional outcome of the cell. Here we investigated differences in PLC isoform levels and activity in relation to differentiation of human and rat vascular smooth muscle cells. Using Western blotting and PLC activity assay, we show that PLCδ1 and PLCγ1 are the predominant isoforms in randomly cycling human vascular smooth muscle cells (HVSMCs). Growth arrest of HVSMCs for seven days of serum deprivation was consistently associated with increases in PLCδ1 and SM α-actin, whereas there were no changes in PLCγ1 immuno-reactivity. Organ culture of rat mesenteric arteries in serum free media (SFM), a model of de-differentiation, led to a loss of contractility as well as a loss of contractile proteins (SM α-actin and calponin) and PLCδ1, and no change in PLCγ1 immuno-reactivity. Taken together, these data indicate that PLCδ1 is the predominant PLC isoform in vascular smooth muscle, and confirm that PLCδ1 expression is affected by conditions that affect the cell cycle, differentiation status and contractile function.

LC-MS/MS confirms that COX-1 drives vascular prostacyclin whilst gene expression pattern reveals non-vascular sites of COX-2 expression.

There are two schools of thought regarding the cyclooxygenase (COX) isoform active in the vasculature. Using urinary prostacyclin markers some groups have proposed that vascular COX-2 drives prostacyclin release. In contrast, we and others have found that COX-1, not COX-2, is responsible for vascular prostacyclin production. Our experiments have relied on immunoassays to detect the prostacyclin breakdown product, 6-keto-PGF1α and antibodies to detect COX-2 protein. Whilst these are standard approaches, used by many laboratories, antibody-based techniques are inherently indirect and have been criticized as limiting the conclusions that can be drawn. To address this question, we measured production of prostanoids, including 6-keto-PGF1α, by isolated vessels and in the circulation in vivo using liquid chromatography tandem mass spectrometry and found values essentially identical to those obtained by immunoassay. In addition, we determined expression from the Cox2 gene using a knockin reporter mouse in which luciferase activity reflects Cox2 gene expression. Using this we confirm the aorta to be essentially devoid of Cox2 driven expression. In contrast, thymus, renal medulla, and regions of the brain and gut expressed substantial levels of luciferase activity, which correlated well with COX-2-dependent prostanoid production. These data are consistent with the conclusion that COX-1 drives vascular prostacyclin release and puts the sparse expression of Cox2 in the vasculature in the context of the rest of the body. In doing so, we have identified the thymus, gut, brain and other tissues as target organs for consideration in developing a new understanding of how COX-2 protects the cardiovascular system.

Aspirin-triggered 15-epi-lipoxin A4 predicts cyclooxygenase-2 in the lungs of LPS-treated mice but not in the circulation: implications for a clinical test.

Inhibition of cyclooxygenase (COX)-2 increases cardiovascular deaths. Identifying a biomarker of COX-2 is desirable but difficult, since COX-1 and COX-2 ordinarily catalyze formation of an identical product, prostaglandin H2. When acetylated by aspirin, however, COX-2 (but not COX-1) can form 15(R)-HETE, which is metabolized to aspirin-triggered lipoxin (ATL), 15-epi-lipoxin A4. Here we have used COX-1- and COX-2-knockout mice to establish whether plasma ATL could be used as a biomarker of vascular COX-2 in vivo. Vascular COX-2 was low but increased by LPS (10 mg/kg; i.p). Aspirin (10 mg/kg; i.v.) inhibited COX-1, measured as blood thromboxane and COX-2, measured as lung PGE2. Aspirin also increased the levels of ATL in the lungs of LPS-treated wild-type C57Bl6 mice (vehicle: 25.5±9.3 ng/ml; 100 mg/kg: 112.0±7.4 ng/ml; P<0.05). Despite this, ATL was unchanged in plasma after LPS and aspirin. This was true in wild-type as well as COX-1(-/-) and COX-2(-/-) mice. Thus, in mice in which COX-2 has been induced by LPS treatment, aspirin triggers detectable 15-epi-lipoxin A4 in lung tissue, but not in plasma. This important study is the first to demonstrate that while ATL can be measured in tissue, plasma ATL is not a biomarker of vascular COX-2 expression.