Lipopolysaccharides from atherosclerosis-associated bacteria antagonize TLR4, induce formation of TLR2/1/CD36 complexes in lipid rafts and trigger TLR2-induced inflammatory responses in human vascular endothelial cells

Infection with bacteria such as Chlamydia pneumonia, Helicobacter pylori or Porphyromonas gingivalis may be triggering the secretion of inflammatory cytokines that leads to atherogenesis. The mechanisms by which the innate immune recognition of these pathogens could lead to atherosclerosis remain unclear. In this study, using human vascular endothelial cells or HEK-293 cells engineered to express pattern-recognition receptors (PRRs), we set out to determine Toll-like receptors (TLRs) and functionally associated PRRs involved in the innate recognition of and response to lipopolysaccharide (LPS) from H. pylori or P. gingivalis. Using siRNA interference or recombinant expression of cooperating PRRs, we show that H. pylori and P. gingivalis LPS-induced cell activation is mediated through TLR2. Human vascular endothelial cell activation was found to be lipid raft-dependent and to require the formation of heterotypic receptor complexes comprising of TLR2, TLR1, CD36 and CD11b/CD18. In addition, we report that LPS from these bacterial strains are able to antagonize TLR4. This antagonistic activity of H. pylori or P. gingivalis LPS, as well as their TLR2 activation capability may be associated with their ability to contribute to atherosclerosis.

Unifying energy minimization and mutual information maximization for robust 2D/3D registration of X-ray and CT images

Similarity measure is one of the main factors that affect the accuracy of intensity-based 2D/3D registration of X-ray fluoroscopy to CT images. Information theory has been used to derive similarity measure for image registration leading to the introduction of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. Previous attempt to incorporate spatial information into mutual information either requires computing the entropy of higher dimensional probability distributions, or is not robust to outliers. In this paper, we show how to incorporate spatial information into mutual information without suffering from these problems. Using a variational approximation derived from the Kullback-Leibler bound, spatial information can be effectively incorporated into mutual information via energy minimization. The resulting similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experimental results are presented on datasets of two applications: (a) intra-operative patient pose estimation from a few (e.g. 2) calibrated fluoroscopic images, and (b) post-operative cup alignment estimation from single X-ray radiograph with gonadal shielding.

Automatic Food Intake Assessment Using Camera Phones

Obesity is becoming an epidemic phenomenon in most developed countries. The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended. It is essential to monitor everyday food intake for obesity prevention and management. Existing dietary assessment methods usually require manually recording and recall of food types and portions. Accuracy of the results largely relies on many uncertain factors such as user's memory, food knowledge, and portion estimations. As a result, the accuracy is often compromised. Accurate and convenient dietary assessment methods are still blank and needed in both population and research societies. In this thesis, an automatic food intake assessment method using cameras, inertial measurement units (IMUs) on smart phones was developed to help people foster a healthy life style. With this method, users use their smart phones before and after a meal to capture images or videos around the meal. The smart phone will recognize food items and calculate the volume of the food consumed and provide the results to users. The technical objective is to explore the feasibility of image based food recognition and image based volume estimation. This thesis comprises five publications that address four specific goals of this work: (1) to develop a prototype system with existing methods to review the literature methods, find their drawbacks and explore the feasibility to develop novel methods; (2) based on the prototype system, to investigate new food classification methods to improve the recognition accuracy to a field application level; (3) to design indexing methods for large-scale image database to facilitate the development of new food image recognition and retrieval algorithms; (4) to develop novel convenient and accurate food volume estimation methods using only smart phones with cameras and IMUs. A prototype system was implemented to review existing methods. Image feature detector and descriptor were developed and a nearest neighbor classifier were implemented to classify food items. A reedit card marker method was introduced for metric scale 3D reconstruction and volume calculation. To increase recognition accuracy, novel multi-view food recognition algorithms were developed to recognize regular shape food items. To further increase the accuracy and make the algorithm applicable to arbitrary food items, new food features, new classifiers were designed. The efficiency of the algorithm was increased by means of developing novel image indexing method in large-scale image database. Finally, the volume calculation was enhanced through reducing the marker and introducing IMUs. Sensor fusion technique to combine measurements from cameras and IMUs were explored to infer the metric scale of the 3D model as well as reduce noises from these sensors.

Fenofibrate metabolism in the cynomolgus monkey using ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry-based metabolomics

Fenofibrate, widely used for the treatment of dyslipidemia, activates the nuclear receptor, peroxisome proliferator-activated receptor alpha. However, liver toxicity, including liver cancer, occurs in rodents treated with fibrate drugs. Marked species differences occur in response to fibrate drugs, especially between rodents and humans, the latter of which are resistant to fibrate-induced cancer. Fenofibrate metabolism, which also shows species differences, has not been fully determined in humans and surrogate primates. In the present study, the metabolism of fenofibrate was investigated in cynomolgus monkeys by ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOFMS)-based metabolomics. Urine samples were collected before and after oral doses of fenofibrate. The samples were analyzed in both positive-ion and negative-ion modes by UPLC-QTOFMS, and after data deconvolution, the resulting data matrices were subjected to multivariate data analysis. Pattern recognition was performed on the retention time, mass/charge ratio, and other metabolite-related variables. Synthesized or purchased authentic compounds were used for metabolite identification and structure elucidation by liquid chromatographytandem mass spectrometry. Several metabolites were identified, including fenofibric acid, reduced fenofibric acid, fenofibric acid ester glucuronide, reduced fenofibric acid ester glucuronide, and compound X. Another two metabolites (compound B and compound AR), not previously reported in other species, were characterized in cynomolgus monkeys. More importantly, previously unknown metabolites, fenofibric acid taurine conjugate and reduced fenofibric acid taurine conjugate were identified, revealing a previously unrecognized conjugation pathway for fenofibrate.

Low Mannan-binding lectin serum levels are associated with complicated Crohn's disease and reactivity to oligomannan (ASCA)

OBJECTIVES: Mannan-binding lectin (MBL) acts as a pattern-recognition molecule directed against oligomannan, which is part of the cell wall of yeasts and various bacteria. We have previously shown an association between MBL deficiency and anti-Saccharomyces cerevisiae mannan antibody (ASCA) positivity. This study aims at evaluating whether MBL deficiency is associated with distinct Crohn's disease (CD) phenotypes. METHODS: Serum concentrations of MBL and ASCA were measured using ELISA (enzyme-linked immunosorbent assay) in 427 patients with CD, 70 with ulcerative colitis, and 76 healthy controls. CD phenotypes were grouped according to the Montreal Classification as follows: non-stricturing, non-penetrating (B1, n=182), stricturing (B2, n=113), penetrating (B3, n=67), and perianal disease (p, n=65). MBL was classified as deficient (<100 ng/ml), low (100-500 ng/ml), and normal (500 ng/ml). RESULTS: Mean MBL was lower in B2 and B3 CD patients (1,503+/-1,358 ng/ml) compared with that in B1 phenotypes (1,909+/-1,392 ng/ml, P=0.013). B2 and B3 patients more frequently had low or deficient MBL and ASCA positivity compared with B1 patients (P=0.004 and P<0.001). Mean MBL was lower in ASCA-positive CD patients (1,562+/-1,319 ng/ml) compared with that in ASCA-negative CD patients (1,871+/-1,320 ng/ml, P=0.038). In multivariate logistic regression modeling, low or deficient MBL was associated significantly with B1 (negative association), complicated disease (B2+B3), and ASCA. MBL levels did not correlate with disease duration. CONCLUSIONS: Low or deficient MBL serum levels are significantly associated with complicated (stricturing and penetrating) CD phenotypes but are negatively associated with the non-stricturing, non-penetrating group. Furthermore, CD patients with low or deficient MBL are significantly more often ASCA positive, possibly reflecting delayed clearance of oligomannan-containing microorganisms by the innate immune system in the absence of MBL.

TLR2 and TLR4 agonists induce production of the vasoactive peptide endothelin-1 by human dendritic cells

Endothelin-1 (ET-1) is mainly secreted by endothelial cells and acts as a potent vasoconstrictor. In addition ET-1 has also been shown to have pleiotropic effects on a variety of other systems including adaptive immunity. There are two main ET-1 receptors, ET(A) and ET(B), which have different tissue and functional distributions. Dendritic cells (DC) are pivotal antigen-presenting cells linking the innate with the adaptive immune system. DC are sentinels expressing pattern-recognition receptors, e.g. the toll-like receptors (TLR) for detecting danger signals released from pathogens or tissue injury. Here we show for the first time that stimulation of human monocyte-derived DC with exogenous as well as endogenous selective TLR4 and TLR2 agonists induces the production of ET-1 in a dose- and time-dependent manner. 'Alternative' activation of DC in the presence of 1alpha,25-dihydroxyvitamin D(3) results in a marked potentiation of the endothelin response, whereas prostaglandin E(2) or dexamethasone do not increase ET-1 production. Furthermore, chetomin, an inhibitor of the transcription factor hypoxia-inducible factor 1alpha (HIF-1alpha), prevents TLR-mediated secretion of ET-1. Surprisingly, stimulation of human monocytes with LPS does not lead to secretion of detectable amounts of ET-1. These results suggest a role of ET-1 as an important player in human DC biology and innate immunity in general.