98 research outputs found

    FAK acts as a suppressor of RTK-MAP kinase signalling in Drosophila melanogaster epithelia and human cancer cells

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    Receptor Tyrosine Kinases (RTKs) and Focal Adhesion Kinase (FAK) regulate multiple signalling pathways, including mitogen-activated protein (MAP) kinase pathway. FAK interacts with several RTKs but little is known about how FAK regulates their downstream signalling. Here we investigated how FAK regulates signalling resulting from the overexpression of the RTKs RET and EGFR. FAK suppressed RTKs signalling in Drosophila melanogaster epithelia by impairing MAPK pathway. This regulation was also observed in MDA-MB-231 human breast cancer cells, suggesting it is a conserved phenomenon in humans. Mechanistically, FAK reduced receptor recycling into the plasma membrane, which resulted in lower MAPK activation. Conversely, increasing the membrane pool of the receptor increased MAPK pathway signalling. FAK is widely considered as a therapeutic target in cancer biology; however, it also has tumour suppressor properties in some contexts. Therefore, the FAK-mediated negative regulation of RTK/MAPK signalling described here may have potential implications in the designing of therapy strategies for RTK-driven tumours

    Breast cancer risk among women with psychiatric admission with affective or neurotic disorders: a nationwide cohort study in Denmark

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    There is a considerable interest in the possible relationship between psychosocial factors and the onset of breast cancer. This cohort study was based upon two nationwide and population-based central registers: The Danish Psychiatric Central Register, which contains all cases of psychiatric admissions, and The Danish Cancer Registry, which contains all cases of cancer. The register-linkage was accomplished by using a personal identification number. The study population comprised all women admitted to psychiatric departments or psychiatric hospitals in Denmark between 1969 and 1993 with an affective or a neurotic disorder. Overall, 66 648 women comprising 199 910 admissions and 775 522 person-years were included. The incidence of breast cancer in the cohort was compared with the national breast cancer incidence rates adjusted for age and calendar time. In all, 1270 women with affective or neurotic disorders developed breast cancer subsequent to the first admission as compared with the 1242 women expected, standardized incidence ratio (SIR) = 1.02 (95% confidence interval 0.97–1.08). None of the hypothetical risk factors: type of diagnosis, age or calendar period at cohort entry, age at breast cancer, alcohol abuse, alcohol/drug abuse without further specification, total number of admissions, total length of admissions, or time from first admission showed a statistically significant effect on the relative risk of breast cancer. We found no support for the hypothesis that women admitted to a psychiatric department with an affective or a neurotic disorder subsequently have an increased risk of breast cancer. © 1999 Cancer Research Campaig

    Genotypes and Toxin Gene Profiles of Staphylococcus aureus Clinical Isolates from China

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    A total of 108 S. aureus isolates from 16 major hospitals located in 14 different provinces in China were characterized for the profiles of 18 staphylococcal enterotoxin (SE) genes, 3 exfoliatin genes (eta, etb and etd), and the toxic shock syndrome toxin gene (tsst) by PCR. The genomic diversity of each isolate was also evaluated by pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), and accessory gene regulator (agr) typing. Of these strains, 90.7% (98/108) harbored toxin genes, in which tsst was the most prevalent toxin gene (48.1%), followed by sea (44.4%), sek (42.6%) and seq (40.7%). The see and etb genes were not found in any of the isolates tested. Because of high-frequency transfer of toxin gene-containing mobile genetic elements between S. aureus strains, a total of 47 different toxin gene combinations were detected, including a complete egc cluster in 19 isolates, co-occurrence of sea, sek and seq in 38 strains, and sec and sel together in 11 strains. Genetic typing by PFGE grouped all the strains into 25 clusters based on 80% similarity. MLST revealed 25 sequence types (ST) which were assigned into 16 clonal complexes (CCs) including 2 new singletons. Among these, 11 new and 6 known STs were first reported in the S. aureus strains from China. Overall, the genotyping results showed high genetic diversity of the strains regardless of their geographical distributions, and no strong correlation between genetic background and toxin genotypes of the strains. For genotyping S. aureus, PFGE appears to be more discriminatory than MLST. However, toxin gene typing combined with PFGE or MLST could increase the discriminatory power of genotyping S. aureus strains

    The development of socio-economic health differences in childhood: results of the Dutch longitudinal PIAMA birth cohort

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    Background: People with higher socio-economic status (SES) are generally in better health. Less is known about when these socio-economic health differences set in during childhood and how they develop over time. The goal of this study was to prospectively study the development of socio-economic health differences in the Netherlands, and to investigate possible explanations for socio-economic variation in childhood health. Methods: Data from the Dutch Prevention and Incidence of Asthma and Mite Allergy (PIAMA) birth cohort study were used for the analyses. The PIAMA study followed 3,963 Dutch children during their first eight years of life. Common childhood health problems (i.e. eczema, asthma symptoms, general health, frequent respiratory infections, overweight, and obesity) were assessed annually using questionnaires. Maternal educational level was used to indicate SES. Possible explanatory lifestyle determinants (breastfeeding, smoking during pregnancy, smoking during the first three months, and day-care centre attendance) and biological determinants (maternal age at birth, birthweight, and older siblings) were analysed using generalized estimating equations. Results: This study shows that socio-economic differences in a broad range of health problems are already present early in life, and persist during childhood. Children from families with low socio-economic backgrounds experience more asthma symptoms (odds ratio (OR) 1.27; 95% Confidence Interval (CI) 1.08-1.49), poorer general health (OR 1.36; 95% CI 1.16-1.60), more frequent respiratory infections (OR 1.57; 95% CI 1.35-1.83), more overweight (OR 1.42; 95% CI 1.16-1.73), and more obesity (OR 2.82; 95% CI 1.80-4.41). The most important contributors to the observed childhood socio-economic health disparities are socio-economic differences in maternal age at birth, breastfeeding, and day-care centre attendance. Conclusions: Socio-economic health disparities already occur very early in life. Socio-economic disadvantage takes its toll on child health before birth, and continues to do so during childhood. Therefore, action to reduce health disparities needs to start very early in life, and should also address socio-economic differences in maternal age at birth, breastfeeding habits, and day-care centre attendance

    Gaia data release 1, the photometric data

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    CONTEXT. This paper presents an overview of the photometric data that are part of the first Gaia data release. AIMS. The principles of the processing and the main characteristics of the Gaia photometric data are presented. METHODS. The calibration strategy is outlined briefly and the main properties of the resulting photometry are presented. RESULTS. Relations with other broadband photometric systems are provided. The overall precision for the Gaia photometry is shown to be at the milli-magnitude level and has a clear potential to improve further in future releases

    A Structure-Based Approach for Mapping Adverse Drug Reactions to the Perturbation of Underlying Biological Pathways

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    Adverse drug reactions (ADR), also known as side-effects, are complex undesired physiologic phenomena observed secondary to the administration of pharmaceuticals. Several phenomena underlie the emergence of each ADR; however, a dominant factor is the drug's ability to modulate one or more biological pathways. Understanding the biological processes behind the occurrence of ADRs would lead to the development of safer and more effective drugs. At present, no method exists to discover these ADR-pathway associations. In this paper we introduce a computational framework for identifying a subset of these associations based on the assumption that drugs capable of modulating the same pathway may induce similar ADRs. Our model exploits multiple information resources. First, we utilize a publicly available dataset pairing drugs with their observed ADRs. Second, we identify putative protein targets for each drug using the protein structure database and in-silico virtual docking. Third, we label each protein target with its known involvement in one or more biological pathways. Finally, the relationships among these information sources are mined using multiple stages of logistic-regression while controlling for over-fitting and multiple-hypothesis testing. As proof-of-concept, we examined a dataset of 506 ADRs, 730 drugs, and 830 human protein targets. Our method yielded 185 ADR-pathway associations of which 45 were selected to undergo a manual literature review. We found 32 associations to be supported by the scientific literature

    The Mass Distribution and Rotation Curve in the Galaxy

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    The mass distribution in the Galaxy is determined by dynamical and photometric methods. Rotation curves are the major tool for determining the dynamical mass distribution in the Milky Way and spiral galaxies. The photometric (statistical) method utilizes luminosity profiles from optical and infrared observations, and assumes empirical values of the mass-to-luminosity (M/L) ratio to convert the luminosity to mass. In this chapter the dynamical method is described in detail, and rotation curves and mass distribution in the Milky Way and nearby spiral galaxies are presented. The dynamical method is categorized into two methods: the decomposition method and direct method. The former fits the rotation curve by calculated curve assuming several mass components such as a bulge, disk and halo, and adjust the dynamical parameters of each component. Explanations are given of the mass profiles as the de Vaucouleurs law, exponential disk, and dark halo profiles inferred from numerical simulations. Another method is the direct method, with which the mass distribution can be directly calculated from the data of rotation velocities without employing any mass models. Some results from both methods are presented, and the Galactic structure is discussed in terms of the mass. Rotation curves and mass distributions in external galaxies are also discussed, and the fundamental mass structures are shown to be universal.Comment: 54 pages, 25 figures, in 'Planets, Stars and Stellar Systems', Springer, Vol. 5, ed. G. Gilmore, Chap. 19. Note: Preprint with full figures is available from http://www.ioa.s.u-tokyo.ac.jp/~sofue/htdocs/2013psss

    Multi-messenger observations of a binary neutron star merger

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    On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

    The neurobiological link between OCD and ADHD

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    Predicting plant diversity patterns in Madagascar : understanding the effects of climate and land cover change in a biodiversity hotspot

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    Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar's plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future
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