Expression and cellular localization of 15-hydroxy-prostaglandin-dehydrogenase in abdominal aortic aneurysm

PGE2 has been implicated in abdominal aortic aneurysm (AAA) associated hypervascularization. PGE2-metabolism involves 15-hydroxyprostaglandin-dehydrogenase (15-PGDH) the expression of which in AAA is unknown. The aim of this study was to examine the expression and cell distribution of 15-PGDH in AAA. Here, we show that 15-PGDH mRNA levels were significantly higher in aorta samples from patients undergoing AAA repair than in those from healthy multiorgan donors. Consequently, the ratio of metabolized PGE2 secreted by aortic samples was significantly higher in AAA. AAA production of total PGE2 and PGE2 metabolites correlated positively with PGI2 production, while the percentage of metabolized PGE2 correlated negatively with the total amount of PGE2 and with PGI2. Transcript levels of 15-PGDH were statistically associated with leukocyte markers but did not correlate with microvascular endothelial cell markers. Immunohistochemistry revealed 15-PGDH in the areas of leukocyte infiltration in AAA samples, mainly associated with CD45-positive cells, but not in normal aorta samples. We provide new data concerning 15-PGDH expression in human AAA, showing that 15-PGDH is upregulated in AAA and mainly expressed in infiltrating leukocytes. Our data suggest that microvasculature was not involved in PGE2 catabolism, reinforcing the potential role of microvasculature derived PGE2 in AAA-associated hypervascularization.This work was supported by grants SAF2010-21392 (LV), SAF2013-46707-R (LV, MC), SAF2012-40127 (JM-G) from the Spanish Ministry of Economy and Competiveness, PI12/01952 (CR) and Red de Investigación Cardiovascular RD12/0042/0051 (LV) and RD12/0042/0053 (JM-G) from the Instituto de Salud Carlos III. The study was cofunded by Fondo Europeo de Desarrollo Regional (FEDER), a way to make Europe. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer Reviewe

Automated detection of lupus white matter lesions in MRI

Brain magnetic resonance imaging provides detailed information which can be used to detect and segment white matter lesions (WML). In this work we propose an approach to automatically segment WML in Lupus patients by using T1w and fluid-attenuated inversion recovery (FLAIR) images. Lupus WML appear as small focal abnormal tissue observed as hyperintensities in the FLAIR images. The quantification of these WML is a key factor for the stratification of lupus patients and therefore both lesion detection and segmentation play an important role. In our approach, the T1w image is first used to classify the three main tissues of the brain, white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF), while the FLAIR image is then used to detect focal WML as outliers of its GM intensity distribution. A set of post-processing steps based on lesion size, tissue neighborhood, and location are used to refine the lesion candidates. The proposal is evaluated on 20 patients, presenting qualitative, and quantitative results in terms of precision and sensitivity of lesion detection [True Positive Rate (62%) and Positive Prediction Value (80%), respectively] as well as segmentation accuracy [Dice Similarity Coefficient (72%)]. Obtained results illustrate the validity of the approach to automatically detect and segment lupus lesions. Besides, our approach is publicly available as a SPM8/12 toolbox extension with a simple parameter configuration

Quantum equilibration of the double-proton transfer in a model system Porphine

There is a renewed interest in the derivation of statistical mechanics from the dynamics of closed quantum systems. A central part of this program is to understand how closed quantum systems, i.e., in the absence of a thermal bath, initialized far-from-equilibrium can share a dynamics that is typical to the relaxation towards thermal equilibrium. Equilibration dynamics has been traditionally studied with a focus on the so-called quenches of large-scale many-body systems. We consider here the equilibration of a two-dimensional molecular model system describing the double proton transfer reaction in porphine. Using numerical simulations, we show that equilibration indeed takes place very rapidly (about 200 fs) for initial states induced by pump-dump laser pulse control with energies well above the synchronous barrier. The resulting equilibration state is characterized by a strong delocalization of the probability density of the protons that can be explained, mechanistically, as the result of (i) an initial state consisting of a large superposition of vibrational states, and (ii) the presence of a very effective dephasing mechanism

Improving quality of care and clinical outcomes for rectal cancer through clinical audits in a multicentre cancer care organisation

Introduction: Colorectal cancer treatment requires a complex, multidisciplinary approach. Because of the potential variability, monitoring through clinical audits is advisable. This study assesses the effects of a quality improvement action plan in patients with locally advanced rectal cancer and treated with radiotherapy. Methods: Comparative, multicentre study in two cohorts of 120 patients each, selected randomly from patients diagnosed with rectal cancer who had initiated radiotherapy with a curative intent. Based on the results from a baseline clinical audit in 2013, a quality improvement action plan was designed and implemented; a second audit in 2017 evaluated its impact. Results: Standardised information was present on 77.5% of the magnetic resonance imaging (MRI) staging reports. Treatment strategies were similar in all three study centres. Of the patients whose treatment was interrupted, just 9.7% received a compensation dose. There was an increase in MRI re-staging from 32.5 to 61.5%, and a significant decrease in unreported circumferential resection margins following neoadjuvant therapy (ypCRM), from 34.5 to 5.6% (p < 0.001). Conclusions: The comparison between two clinical audits showed improvements in neoadjuvant radiotherapy in rectal cancer patients. Some indicators reveal areas in need of additional efforts, for example to reduce the overall treatment time

A protocol for annotation of total body photography for machine learning to analyze skin phenotype and lesion classification

IntroductionArtificial Intelligence (AI) has proven effective in classifying skin cancers using dermoscopy images. In experimental settings, algorithms have outperformed expert dermatologists in classifying melanoma and keratinocyte cancers. However, clinical application is limited when algorithms are presented with ‘untrained’ or out-of-distribution lesion categories, often misclassifying benign lesions as malignant, or misclassifying malignant lesions as benign. Another limitation often raised is the lack of clinical context (e.g., medical history) used as input for the AI decision process. The increasing use of Total Body Photography (TBP) in clinical examinations presents new opportunities for AI to perform holistic analysis of the whole patient, rather than a single lesion. Currently there is a lack of existing literature or standards for image annotation of TBP, or on preserving patient privacy during the machine learning process.MethodsThis protocol describes the methods for the acquisition of patient data, including TBP, medical history, and genetic risk factors, to create a comprehensive dataset for machine learning. 500 patients of various risk profiles will be recruited from two clinical sites (Australia and Spain), to undergo temporal total body imaging, complete surveys on sun behaviors and medical history, and provide a DNA sample. This patient-level metadata is applied to image datasets using DICOM labels. Anonymization and masking methods are applied to preserve patient privacy. A two-step annotation process is followed to label skin images for lesion detection and classification using deep learning models. Skin phenotype characteristics are extracted from images, including innate and facultative skin color, nevi distribution, and UV damage. Several algorithms will be developed relating to skin lesion detection, segmentation and classification, 3D mapping, change detection, and risk profiling. Simultaneously, explainable AI (XAI) methods will be incorporated to foster clinician and patient trust. Additionally, a publicly released dataset of anonymized annotated TBP images will be released for an international challenge to advance the development of new algorithms using this type of data.ConclusionThe anticipated results from this protocol are validated AI-based tools to provide holistic risk assessment for individual lesions, and risk stratification of patients to assist clinicians in monitoring for skin cancer

The Alkaline Hydrolysis of Sulfonate Esters: Challenges in Interpreting Experimental and Theoretical Data

Sulfonate ester hydrolysis has been the subject of recent debate, with experimental evidence interpreted in terms of both stepwise and concerted mechanisms. In particular, a recent study of the alkaline hydrolysis of a series of benzene arylsulfonates (Babtie et al., Org. Biomol. Chem. 10, 2012, 8095) presented a nonlinear Brønsted plot, which was explained in terms of a change from a stepwise mechanism involving a pentavalent intermediate for poorer leaving groups to a fully concerted mechanism for good leaving groups and supported by a theoretical study. In the present work, we have performed a detailed computational study of the hydrolysis of these compounds and find no computational evidence for a thermodynamically stable intermediate for any of these compounds. Additionally, we have extended the experimental data to include pyridine-3-yl benzene sulfonate and its N-oxide and N-methylpyridinium derivatives. Inclusion of these compounds converts the Brønsted plot to a moderately scattered but linear correlation and gives a very good Hammett correlation. These data suggest a concerted pathway for this reaction that proceeds via an early transition state with little bond cleavage to the leaving group, highlighting the care that needs to be taken with the interpretation of experimental and especially theoretical data

Bearing modeling in a multibody simulation software

Grado en Ingeniería Mecánic