Enhanced CellClassifier: a multi-class classification tool for microscopy images

BACKGROUND: Light microscopy is of central importance in cell biology. The recent introduction of automated high content screening has expanded this technology towards automation of experiments and performing large scale perturbation assays. Nevertheless, evaluation of microscopy data continues to be a bottleneck in many projects. Currently, among open source software, CellProfiler and its extension Analyst are widely used in automated image processing. Even though revolutionizing image analysis in current biology, some routine and many advanced tasks are either not supported or require programming skills of the researcher. This represents a significant obstacle in many biology laboratories. RESULTS: We have developed a tool, Enhanced CellClassifier, which circumvents this obstacle. Enhanced CellClassifier starts from images analyzed by CellProfiler, and allows multi-class classification using a Support Vector Machine algorithm. Training of objects can be done by clicking directly "on the microscopy image" in several intuitive training modes. Many routine tasks like out-of focus exclusion and well summary are also supported. Classification results can be integrated with other object measurements including inter-object relationships. This makes a detailed interpretation of the image possible, allowing the differentiation of many complex phenotypes. For the generation of the output, image, well and plate data are dynamically extracted and summarized. The output can be generated as graphs, Excel-files, images with projections of the final analysis and exported as variables. CONCLUSION: Here we describe Enhanced CellClassifier which allows multiple class classification, elucidating complex phenotypes. Our tool is designed for the biologist who wants both, simple and flexible analysis of images without requiring programming skills. This should facilitate the implementation of automated high-content screening

Human Bone Marrow Mesenchymal Stem Cells Display Anti-Cancer Activity in SCID Mice Bearing Disseminated Non-Hodgkin's Lymphoma Xenografts

Abstract BACKGROUND: Although multimodality treatment can induce high rate of remission in many subtypes of non-Hodgkin's lymphoma (NHL), significant proportions of patients relapse with incurable disease. The effect of human bone marrow (BM) mesenchymal stem cells (MSC) on tumor cell growth is controversial, and no specific information is available on the effect of BM-MSC on NHL. METHODOLOGY/PRINCIPAL FINDINGS: The effect of BM-MSC was analyzed in two in vivo models of disseminated non-Hodgkin's lymphomas with an indolent (EBV(-) Burkitt-type BJAB, median survival = 46 days) and an aggressive (EBV(+) B lymphoblastoid SKW6.4, median survival = 27 days) behavior in nude-SCID mice. Intra-peritoneal (i.p.) injection of MSC (4 days after i.p. injection of lymphoma cells) significantly increased the overall survival at an optimal MSC:lymphoma ratio of 1:10 in both xenograft models (BJAB+MSC, median survival = 58.5 days; SKW6.4+MSC, median survival = 40 days). Upon MSC injection, i.p. tumor masses developed more slowly and, at the histopathological observation, exhibited a massive stromal infiltration coupled to extensive intra-tumor necrosis. In in vitro experiments, we found that: i) MSC/lymphoma co-cultures modestly affected lymphoma cell survival and were characterized by increased release of pro-angiogenic cytokines with respect to the MSC, or lymphoma, cultures; ii) MSC induce the migration of endothelial cells in transwell assays, but promoted endothelial cell apoptosis in direct MSC/endothelial cell co-cultures. CONCLUSIONS/SIGNIFICANCE: Our data demonstrate that BM-MSC exhibit anti-lymphoma activity in two distinct xenograft SCID mouse models of disseminated NHL

Extending the Southern Shore of the Island of Inversion to F-28

Detailed spectroscopy of the neutron-unbound nucleus F-28 has been performed for the first time following proton/neutron removal from Ne-29/F-29 beams at energies around 230 MeV=nucleon. The invariant-mass spectra were reconstructed for both the F-27((*)) + n and F-26((*)) + 2n coincidences and revealed a series of well-defined resonances. A near-threshold state was observed in both reactions and is identified as the F-28 ground state, with S-n(F-28) = -199(6) keV, while analysis of the 2n decay channel allowed a considerably improved S-n(F-27) = 1620(60) keV to be deduced. Comparison with shell-model predictions and eikonal-model reaction calculations have allowed spin-parity assignments to be proposed for some of the lower-lying levels of F-28. Importantly, in the case of the ground state, the reconstructed F-27 + n momentum distribution following neutron removal from F-29 indicates that it arises mainly from the 1p(3/2) neutron intruder configuration. This demonstrates that the island of inversion around N = 20 includes F-28, and most probably F-29, and suggests that O-28 is not doubly magic

Neuron-glial Interactions

Although lagging behind classical computational neuroscience, theoretical and computational approaches are beginning to emerge to characterize different aspects of neuron-glial interactions. This chapter aims to provide essential knowledge on neuron-glial interactions in the mammalian brain, leveraging on computational studies that focus on structure (anatomy) and function (physiology) of such interactions in the healthy brain. Although our understanding of the need of neuron-glial interactions in the brain is still at its infancy, being mostly based on predictions that await for experimental validation, simple general modeling arguments borrowed from control theory are introduced to support the importance of including such interactions in traditional neuron-based modeling paradigms.Junior Leader Fellowship Program by “la Caixa” Banking Foundation (LCF/BQ/LI18/11630006

Neuron-Glial Interactions

Although lagging behind classical computational neuroscience, theoretical and computational approaches are beginning to emerge to characterize different aspects of neuron-glial interactions. This chapter aims to provide essential knowledge on neuron-glial interactions in the mammalian brain, leveraging on computational studies that focus on structure (anatomy) and function (physiology) of such interactions in the healthy brain. Although our understanding of the need of neuron-glial interactions in the brain is still at its infancy, being mostly based on predictions that await for experimental validation, simple general modeling arguments borrowed from control theory are introduced to support the importance of including such interactions in traditional neuron-based modeling paradigms.Comment: 43 pages, 2 figures, 1 table. Accepted for publication in the "Encyclopedia of Computational Neuroscience," D. Jaeger and R. Jung eds., Springer-Verlag New York, 2020 (2nd edition

A new class of glycomimetic drugs to prevent free fatty acid-induced endothelial dysfunction

Background: Carbohydrates play a major role in cell signaling in many biological processes. We have developed a set of glycomimetic drugs that mimic the structure of carbohydrates and represent a novel source of therapeutics for endothelial dysfunction, a key initiating factor in cardiovascular complications. Purpose: Our objective was to determine the protective effects of small molecule glycomimetics against free fatty acid­induced endothelial dysfunction, focusing on nitric oxide (NO) and oxidative stress pathways. Methods: Four glycomimetics were synthesized by the stepwise transformation of 2,5­dihydroxybenzoic acid to a range of 2,5­substituted benzoic acid derivatives, incorporating the key sulfate groups to mimic the interactions of heparan sulfate. Endothelial function was assessed using acetylcholine­induced, endotheliumdependent relaxation in mouse thoracic aortic rings using wire myography. Human umbilical vein endothelial cell (HUVEC) behavior was evaluated in the presence or absence of the free fatty acid, palmitate, with or without glycomimetics (1µM). DAF­2 and H2DCF­DA assays were used to determine nitric oxide (NO) and reactive oxygen species (ROS) production, respectively. Lipid peroxidation colorimetric and antioxidant enzyme activity assays were also carried out. RT­PCR and western blotting were utilized to measure Akt, eNOS, Nrf­2, NQO­1 and HO­1 expression. Results: Ex vivo endothelium­dependent relaxation was significantly improved by the glycomimetics under palmitate­induced oxidative stress. In vitro studies showed that the glycomimetics protected HUVECs against the palmitate­induced oxidative stress and enhanced NO production. We demonstrate that the protective effects of pre­incubation with glycomimetics occurred via upregulation of Akt/eNOS signaling, activation of the Nrf2/ARE pathway, and suppression of ROS­induced lipid peroxidation. Conclusion: We have developed a novel set of small molecule glycomimetics that protect against free fatty acidinduced endothelial dysfunction and thus, represent a new category of therapeutic drugs to target endothelial damage, the first line of defense against cardiovascular disease