Heme oxygenase effect on mesenchymal stem cells action on experimental Alzheimer's disease

The objective is to evaluate the effect of heme oxygenase-1 (HO-1) enzyme inducer and inhibitor on Mesenchymal Stem Cells (MSCs) in Alzheimer disease. Materials and Methods: 70 female albino rats were divided equally into 7 groups as follows: group 1: healthy control; group 2: Aluminium chloride induced Alzheimer disease; group 3: induced Alzheimer rats that received intravenous injection of MSCs; group 4: induced Alzheimer rats that received MSCs and HO inducer cobalt protoporphyrin; group 5: induced Alzheimer rats that received MSCs and HO inhibitor zinc protoporphyrin; group 6: induced Alzheimer rats that received HO inducer; group7: induced Alzheimer rats that received HO inhibitor. Brain tissue was collected for HO-1, seladin-1 gene expression by real time polymerase chain reaction, heme oxygenase activity, cholesterol estimation and histopathological examination. Results: MSCs decreased the plaque lesions, heme oxygenase induction with stem cells also decreased plaque lesions however there was hemorrhage in the brain. Both heme oxygenase inducer alone or with stem cells increased seladin-1 expression and decreased cholesterol level. Conclusion: MSCs alone or with HO-1 induction exert a therapeutic effect against the brain lesion in Alzheimer’s disease possibly through decreasing the brain cholesterol level and increasing seladin-1 gene expression

Basal-like breast cancers: the phenotypic disparity between the cancer-initiating cells and tumor histology

Recent evidence suggests that a rare-cell population with a stem cell phenotype maintains breast tumors. Therefore, to devise breast cancer therapies that are more effective, we need to understand the unique biology of these cancer stem cells. Currently, very little is known about the origin of cancer stem cells and their relationship to the tumor phenotype. A recent study from Smalley's group demonstrates that targeting an inactivating Brca1 mutation to the luminal progenitors could yield basal-like breast cancers. This observation suggests that the inherent plasticity of the primitive cells can be hijacked by the tumorigenic processes to produce tumors with an unpredictable phenotype

The Isaac Newton Telescope Monitoring Survey of Local Group Dwarf Galaxies. I. Survey Overview and First Results for Andromeda I

An optical monitoring survey in nearby dwarf galaxies was carried out with the 2.5 m Isaac Newton Telescope. Fifty-five dwarf galaxies and four isolated globular clusters in the Local Group were observed with the Wide Field Camera. The main aims of this survey are to identify the most evolved asymptotic giant branch (AGB) stars and red supergiants at the end-point of their evolution based on their pulsational instability, use their distribution over luminosity to reconstruct the star formation history, quantify the dust production and mass loss from modeling the multiwavelength spectral energy distributions (SEDs), and relate this to luminosity and radius variations. In this first of a series of papers, we present the methodology of the variability survey and describe the photometric catalog of the Andromeda I (And I) dwarf galaxy as an example of the survey, and we discuss the identified long period variable (LPV) stars. We detected 5581 stars and identified 59 LPV candidates within two half-light radii of the center of And I. The amplitudes of these candidates range from 0.2 to 3 mag in the i-band. Seventy-five percent of detected sources and 98% of LPV candidates are detected at mid-infrared wavelengths. We show evidence for the presence of dust-producing AGB stars in this galaxy including five extreme AGB (x-AGB) stars, and we model some of their SEDs. A distance modulus of 24.41 mag for And I was determined based on the tip of the red giant branch. Also, a half-light radius of 3.′2 ± 0.′3 was calculated

Inhibition of somatosensory mechanotransduction by annexin A6

Mechanically activated, slowly adapting currents in sensory neurons have been linked to noxious mechanosensation. The conotoxin NMB-1 (noxious mechanosensation blocker-1) blocks such currents and inhibits mechanical pain. Using a biotinylated form of NMB-1 in mass spectrometry analysis, we identified 67 binding proteins in sensory neurons and a sensory neuron-derived cell line, of which the top candidate was annexin A6, a membrane-associated calcium-binding protein. Annexin A6-deficient mice showed increased sensitivity to mechanical stimuli. Sensory neurons from these mice showed increased activity of the cation channel Piezo2, which mediates a rapidly adapting mechano-gated current linked to proprioception and touch, and a decrease in mechanically activated, slowly adapting currents. Conversely, overexpression of annexin A6 in sensory neurons inhibited rapidly adapting currents that were partially mediated by Piezo2. Furthermore, overexpression of annexin A6 in sensory neurons attenuated mechanical pain in a mouse model of osteoarthritis, a disease in which mechanically evoked pain is particularly problematic. These data suggest that annexin A6 can be exploited to inhibit chronic mechanical pain

Mapping the cellular and molecular heterogeneity of normal and malignant breast tissues and cultured cell lines

Introduction: Normal and neoplastic breast tissues are comprised of heterogeneous populations of epithelial cells exhibiting various degrees of maturation and differentiation. While cultured cell lines have been derived from both normal and malignant tissues, it remains unclear to what extent they retain similar levels of differentiation and heterogeneity as that found within breast tissues. Methods: We used 12 reduction mammoplasty tissues, 15 primary breast cancer tissues, and 20 human breast epithelial cell lines (16 cancer lines, 4 normal lines) to perform flow cytometry for CD44, CD24, epithelial cell adhesion molecule (EpCAM), and CD49f expression, as well as immunohistochemistry, and in vivo tumor xenograft formation studies to extensively analyze the molecular and cellular characteristics of breast epithelial cell lineages. Results: Human breast tissues contain four distinguishable epithelial differentiation states (two luminal phenotypes and two basal phenotypes) that differ on the basis of CD24, EpCAM and CD49f expression. Primary human breast cancer tissues also contain these four cellular states, but in altered proportions compared to normal tissues. In contrast, cultured cancer cell lines are enriched for rare basal and mesenchymal epithelial phenotypes, which are normally present in small numbers within human tissues. Similarly, cultured normal human mammary epithelial cell lines are enriched for rare basal and mesenchymal phenotypes that represent a minor fraction of cells within reduction mammoplasty tissues. Furthermore, although normal human mammary epithelial cell lines exhibit features of bi-potent progenitor cells they are unable to differentiate into mature luminal breast epithelial cells under standard culture conditions. Conclusions: As a group breast cancer cell lines represent the heterogeneity of human breast tumors, but individually they exhibit increased lineage-restricted profiles that fall short of truly representing the intratumoral heterogeneity of individual breast tumors. Additionally, normal human mammary epithelial cell lines fail to retain much of the cellular diversity found in human breast tissues and are enriched for differentiation states that are a minority in breast tissues, although they do exhibit features of bi-potent basal progenitor cells. These findings suggest that collections of cell lines representing multiple cell types can be used to model the cellular heterogeneity of tissues

Global economic burden of unmet surgical need for appendicitis

Background: There is a substantial gap in provision of adequate surgical care in many low-and middle-income countries. This study aimed to identify the economic burden of unmet surgical need for the common condition of appendicitis. Methods: Data on the incidence of appendicitis from 170 countries and two different approaches were used to estimate numbers of patients who do not receive surgery: as a fixed proportion of the total unmet surgical need per country (approach 1); and based on country income status (approach 2). Indirect costs with current levels of access and local quality, and those if quality were at the standards of high-income countries, were estimated. A human capital approach was applied, focusing on the economic burden resulting from premature death and absenteeism. Results: Excess mortality was 4185 per 100 000 cases of appendicitis using approach 1 and 3448 per 100 000 using approach 2. The economic burden of continuing current levels of access and local quality was US $92 492 million using approach 1 and$73 141 million using approach 2. The economic burden of not providing surgical care to the standards of high-income countries was $95 004 million using approach 1 and$75 666 million using approach 2. The largest share of these costs resulted from premature death (97.7 per cent) and lack of access (97.0 per cent) in contrast to lack of quality. Conclusion: For a comparatively non-complex emergency condition such as appendicitis, increasing access to care should be prioritized. Although improving quality of care should not be neglected, increasing provision of care at current standards could reduce societal costs substantially

Feature Selection via Chaotic Antlion Optimization

Selecting a subset of relevant properties from a large set of features that describe a dataset is a challenging machine learning task. In biology, for instance, the advances in the available technologies enable the generation of a very large number of biomarkers that describe the data. Choosing the more informative markers along with performing a high-accuracy classification over the data can be a daunting task, particularly if the data are high dimensional. An often adopted approach is to formulate the feature selection problem as a biobjective optimization problem, with the aim of maximizing the performance of the data analysis model (the quality of the data training fitting) while minimizing the number of features used.This work was partially supported by the IPROCOM Marie Curie initial training network, funded through the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme FP7/2007-2013/ under REA grants agreement No. 316555, and by the Romanian National Authority for Scientific Research, CNDIUEFISCDI, project number PN-II-PT-PCCA-2011-3.2- 0917. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

A refined molecular taxonomy of breast cancer

The current histoclinical breast cancer classification is simple but imprecise. Several molecular classifications of breast cancers based on expression profiling have been proposed as alternatives. However, their reliability and clinical utility have been repeatedly questioned, notably because most of them were derived from relatively small initial patient populations. We analyzed the transcriptomes of 537 breast tumors using three unsupervised classification methods. A core subset of 355 tumors was assigned to six clusters by all three methods. These six subgroups overlapped with previously defined molecular classes of breast cancer, but also showed important differences, notably the absence of an ERBB2 subgroup and the division of the large luminal ER+ group into four subgroups, two of them being highly proliferative. Of the six subgroups, four were ER+/PR+/AR+, one was ER−/PR−/AR+ and one was triple negative (AR−/ER−/PR−). ERBB2-amplified tumors were split between the ER−/PR−/AR+ subgroup and the highly proliferative ER+ LumC subgroup. Importantly, each of these six molecular subgroups showed specific copy-number alterations. Gene expression changes were correlated to specific signaling pathways. Each of these six subgroups showed very significant differences in tumor grade, metastatic sites, relapse-free survival or response to chemotherapy. All these findings were validated on large external datasets including more than 3000 tumors. Our data thus indicate that these six molecular subgroups represent well-defined clinico-biological entities of breast cancer. Their identification should facilitate the detection of novel prognostic factors or therapeutical targets in breast cancer

Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features

Background Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk. Methods Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets. Results Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions. Conclusion This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast cancer