Milieu-adopted in vitro and in vivo differentiation of mesenchymal tissues derived from different adult human CD34-negative progenitor cell clones

Adult mesenchymal stem cells with multilineage differentiation potentially exist in the bone marrow, but have also been isolated from the peripheral blood. The differentiation of stem cells after leaving their niches depends predominately on the local milieu and its new microenvironment, and is facilitated by soluble factors but also by the close cell-cell interaction in a three-dimensional tissue or organ system. We have isolated CD34-negative, mesenchymal stem cell lines from human bone marrow and peripheral blood and generated monoclonal cell populations after immortalization with the SV40 large T-antigen. The cultivation of those adult stem cell clones in an especially designed in vitro environment, including self-constructed glass capillaries with defined growth conditions, leads to the spontaneous establishment of pleomorphic three-dimensional cell aggregates ( spheroids) from the monoclonal cell population, which consist of cells with an osteoblast phenotype and areas of mineralization along with well-vascularized tissue areas. Modifications of the culture conditions favored areas of bone-like calcifications. After the transplantation of the at least partly mineralized human spheroids into different murine soft tissue sites but also a dorsal skinfold chamber, no further bone formation could be observed, but angiogenesis and neovessel formation prevailed instead, enabling the transplanted cells and cell aggregates to survive. This study provides evidence that even monoclonal adult human CD34-negative stem cells from the bone marrow as well as peripheral blood can potentially differentiate into different mesenchymal tissues depending on the local milieu and responding to the needs within the microenvironment. Copyright (C) 2005 S. Karger AG, Basel

Classification of Weather Situations on Single Color Images

Present vision based driver assistance systems are designed to perform under good-natured weather conditions. However, limited visibility caused by heavy rain or fog strongly affects vision systems. To improve machine vision in bad weather situations, a reliable detection system is necessary as a ground base. We present an approach that is able to distinguish between multiple weather situations based on the classification of single monocular color images, without any additional assumptions or prior knowledge. The proposed image descriptor clearly outperforms existing descriptors for that task. Experimental results on real traffic images are characterized by high accuracy, efficiency, and versatility with respect to driver assistance systems

In vitro metabolism of the synthetic cannabinoid 3,5-AB-CHMFUPPYCA and its 5,3-regioisomer and investigation of their thermal stability.

Recently, the pyrazole-containing synthetic cannabinoid N-(1-amino-3-methyl-1-oxobutan-2-yl)-1-(cyclohexylmethyl)-3-(4-fluorophenyl)-1H-pyrazole-5-carboxamide (3,5-AB-CHMFUPPYCA) has been identified as a 'research chemical' both in powdered form and as an adulterant present in herbal preparations. Urine is the most common matrix used for abstinence control and the extensive metabolism of synthetic cannabinoids requires implementation of targeted analysis. The present study describes the investigation of the in vitro phase I metabolism of 3,5-AB-CHMFUPPYCA and its regioisomer 5,3-AB-CHMFUPPYCA using pooled human liver microsomes. Metabolic patterns of both AB-CHMFUPPYCA isomers were qualitatively similar and dominated by oxidation of the cyclohexylmethyl side chain. Biotransformation to monohydroxylated metabolites of high abundance confirmed that these species might serve as suitable targets for urine analysis. Furthermore, since synthetic cannabinoids are commonly administered by smoking and because some metabolites can also be formed as thermolytic artefacts, the stability of both isomers was assessed under smoking conditions. Under these conditions, pyrolytic cleavage of the amide bond occurred that led to approximately 3 % conversion to heat-induced degradation products that were also detected during metabolism. These artefactual 'metabolites' could potentially bias in vivo metabolic profiles after smoking and might have to be considered for interpretation of metabolite findings during hair analysis. This might be relevant to the analysis of hair samples where detection of metabolites is generally accepted as a strong indication of drug use rather than a potential external contamination. Copyright © 2016 John Wiley & Sons, Ltd

A gene expression predictor of response to EGFR-targeted therapy stratifies progression-free survival to cetuximab in KRAS wild-type metastatic colorectal cancer

<p>Abstract</p> <p>Background</p> <p>The anti-EGFR monoclonal antibody cetuximab is used in metastatic colorectal cancer (CRC), and predicting responsive patients garners great interest, due to the high cost of therapy. Mutations in the KRAS gene occur in ~40% of CRC and are a negative predictor of response to cetuximab. However, many KRAS-wildtype patients do not benefit from cetuximab. We previously published a gene expression predictor of sensitivity to erlotinib, an EGFR inhibitor. The purpose of this study was to determine if this predictor could identify KRAS-wildtype CRC patients who will benefit from cetuximab therapy.</p> <p>Methods</p> <p>Microarray data from 80 metastatic CRC patients subsequently treated with cetuximab were extracted from the study by Khambata-Ford et al. The study included KRAS status, response, and PFS for each patient. The gene expression data were scaled and analyzed using our predictive model. An improved predictive model of response was identified by removing features in the 180-gene predictor that introduced noise.</p> <p>Results</p> <p>Forty-three of eighty patients were identified as harboring wildtype-KRAS. When the model was applied to these patients, the predicted-sensitive group had significantly longer PFS than the predicted-resistant group (median 88 days vs. 56 days; mean 117 days vs. 63 days, respectively, p = 0.008). Kaplan-Meier curves were also significantly improved in the predicted-sensitive group (p = 0.0059, HR = 0.4109. The model was simplified to 26 of the original 180 genes and this further improved stratification of PFS (median 147 days vs. 56.5 days in the predicted sensitive and resistant groups, respectively, p < 0.0001). However, the simplified model will require further external validation, as features were selected based on their correlation to PFS in this dataset.</p> <p>Conclusion</p> <p>Our model of sensitivity to EGFR inhibition stratified PFS following cetuximab in KRAS-wildtype CRC patients. This study represents the first true external validation of a molecular predictor of response to cetuximab in KRAS-WT metastatic CRC. Our model may hold clinical utility for identifying patients responsive to cetuximab and may therefore minimize toxicity and cost while maximizing benefit.</p

Max-Margin Dictionary Learning for Multiclass Image Categorization

Abstract. Visual dictionary learning and base (binary) classifier train-ing are two basic problems for the recently most popular image cate-gorization framework, which is based on the bag-of-visual-terms (BOV) models and multiclass SVM classifiers. In this paper, we study new algo-rithms to improve performance of this framework from these two aspects. Typically SVM classifiers are trained with dictionaries fixed, and as a re-sult the traditional loss function can only be minimized with respect to hyperplane parameters (w and b). We propose a novel loss function for a binary classifier, which links the hinge-loss term with dictionary learning. By doing so, we can further optimize the loss function with respect to the dictionary parameters. Thus, this framework is able to further increase margins of binary classifiers, and consequently decrease the error bound of the aggregated classifier. On two benchmark dataset

Impact of the Specific Mutation in KRAS Codon 12 Mutated Tumors on Treatment Efficacy in Patients with Metastatic Colorectal Cancer Receiving Cetuximab-Based First-Line Therapy: A Pooled Analysis of Three Trials

Purpose: This study investigated the impact of specific mutations in codon 12 of the Kirsten-ras (KRAS) gene on treatment efficacy in patients with metastatic colorectal cancer (mCRC). Patients: Overall, 119 patients bearing a KRAS mutation in codon 12 were evaluated. All patients received cetuximab-based first-line chemotherapy within the Central European Cooperative Oncology Group (CECOG), AIO KRK-0104 or AIO KRK-0306 trials. Results: Patients with KRAS codon 12 mutant mCRC showed a broad range of outcome when treated with cetuximab-based first-line regimens. Patients with tumors bearing a KRAS p.G12D mutation showed a strong trend to a more favorable outcome compared to other mutations (overall survival 23.3 vs. 14-18 months; hazard ratio 0.66, range 0.43-1.03). An interaction model illustrated that KRAS p.G12C was associated with unfavorable outcome when treated with oxaliplatin plus cetuximab. Conclusion: The present analysis suggests that KRAS codon 12 mutation may not represent a homogeneous entity in mCRC when treated with cetuximab-based first-line therapy. Copyright (C) 2012 S. Karger AG, Base

Video classification with Densely extracted HOG/HOF/MBH features: an evaluation of the accuracy/computational efficiency trade-off

The current state-of-the-art in video classification is based on Bag-of-Words using local visual descriptors. Most commonly these are histogram of oriented gradients (HOG), histogram of optical flow (HOF) and motion boundary histograms (MBH) descriptors. While such approach is very powerful for classification, it is also computationally expensive. This paper addresses the problem of computational efficiency. Specifically: (1) We propose several speed-ups for densely sampled HOG, HOF and MBH descriptors and release Matlab code; (2) We investigate the trade-off between accuracy and computational efficiency of descriptors in terms of frame sampling rate and type of Optical Flow method; (3) We investigate the trade-off between accuracy and computational efficiency for computing the feature vocabulary, using and comparing most of the commonly adopted vector quantization techniques: k-means, hierarchical k-means, Random Forests, Fisher Vectors and VLAD

Colloquium: Mechanical formalisms for tissue dynamics

The understanding of morphogenesis in living organisms has been renewed by tremendous progressin experimental techniques that provide access to cell-scale, quantitative information both on theshapes of cells within tissues and on the genes being expressed. This information suggests that ourunderstanding of the respective contributions of gene expression and mechanics, and of their crucialentanglement, will soon leap forward. Biomechanics increasingly benefits from models, which assistthe design and interpretation of experiments, point out the main ingredients and assumptions, andultimately lead to predictions. The newly accessible local information thus calls for a reflectionon how to select suitable classes of mechanical models. We review both mechanical ingredientssuggested by the current knowledge of tissue behaviour, and modelling methods that can helpgenerate a rheological diagram or a constitutive equation. We distinguish cell scale ("intra-cell")and tissue scale ("inter-cell") contributions. We recall the mathematical framework developpedfor continuum materials and explain how to transform a constitutive equation into a set of partialdifferential equations amenable to numerical resolution. We show that when plastic behaviour isrelevant, the dissipation function formalism appears appropriate to generate constitutive equations;its variational nature facilitates numerical implementation, and we discuss adaptations needed in thecase of large deformations. The present article gathers theoretical methods that can readily enhancethe significance of the data to be extracted from recent or future high throughput biomechanicalexperiments.Comment: 33 pages, 20 figures. This version (26 Sept. 2015) contains a few corrections to the published version, all in Appendix D.2 devoted to large deformation

High-resolution and sensitivity bi-directional x-ray phase contrast imaging using 2D Talbot array illuminators

Two-dimensional (2D) Talbot array illuminators (TAIs) were designed, fabricated, and evaluated for high-resolution high-contrast x-ray phase imaging of soft tissue at 10–20 keV. The TAIs create intensity modulations with a high compression ratio on the micrometer scale at short propagation distances. Their performance was compared with various other wavefront markers in terms of period, visibility, flux efficiency, and flexibility to be adapted for limited beam coherence and detector resolution. Differential x-ray phase contrast and dark-field imaging were demonstrated with a one-dimensional, linear phase stepping approach yielding 2D phase sensitivity using unified modulated pattern analysis (UMPA) for phase retrieval. The method was employed for x-ray phase computed tomography reaching a resolution of 3 µm on an unstained murine artery. It opens new possibilities for three-dimensional, non-destructive, and quantitative imaging of soft matter such as virtual histology. The phase modulators can also be used for various other x-ray applications such as dynamic phase imaging, super-resolution structured illumination microscopy, or wavefront sensing