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Cartwright W.,ICA | Cartwright W.,RMIT University
GIM International | Year: 2010

The International Cartographic Association (ICA) which is the world authoritative body for cartography, the discipline dealing with the conception, production, dissemination and study of maps is making efforts for promoting and advancing the theory and praxis of cartography. ICA has brought together researchers, government mapping agencies, commercial cartographic publishers, software developers, educators, earth and environmental scientists, and those with a passion for maps. The ICA Strategic Plan includes many capacity-building activities in the fields of education, professional practice and society as a whole. Cartographic Heritage also attract (map-)librarians, book and map-keepers, archivists, town planners, architects working on historical urban cadastres and history of architecture, software developers working with image-assisted databases and web attachments. The use of free open-source geospatial tools through workshops, and to make accessible the latest developments to the wider cartographic community. Source


Merzouki T.,University of Orleans | Merzouki T.,University of Versailles | Blond E.,University of Orleans | Schmitt N.,Ecole Normale Superieure de Cachan | And 4 more authors.
Mechanics of Materials | Year: 2014

Silicon carbide-based refractory castables (SiC-RC) have high mechanical and chemical resistances at high temperature. Nevertheless when subjected to both high temperature and aggressive oxidizing environment, due to phase transformation, a chemical strain appears that leads to additional stresses in industrial parts and may cause degradation. In this paper, macroscopic constitutive equations are proposed to model the complex relationship between stress, strain, temperature and oxidizing atmosphere in porous SiC-RC. To model the kinetics of the chemical swelling, oxygen content in the porosity of the heterogeneous material is estimated. It depends on both the oxidation reaction of SiC-based grains and the diffusion of oxygen through the connected porosity in the castable. The macroscopic chemical strain associated to the local SiO2 formation takes only place when the local small voids cannot absorb the reaction product anymore. Besides, the reduction of porosity is accompanied by a reduction in the gas permeability and consequently a reduction in the diffusion of oxygen. The multi-physical model is implemented in the finite element code Abaqus®. It accounts for heat transfer,reactive oxygen transport and chemically induced strain. A validation test was carried out on a cylindrical sample subjected to high temperature with a thermal gradient in ambient air. Comparison between experimental results, microscopic observations and numerical results showed that the model provides a good description of the main physical phenomena. © 2013 Elsevier Ltd. All rights reserved. Source


Guedes E.M.S.,Federal Rural University of Amazonia | Fernandes A.R.,Federal Rural University of Amazonia | de Lima H.V.,ICA | Serra A.P.,EMBRAPA - Empresa Brasileira de Pesquisa Agropecuaria | And 2 more authors.
Revista Brasileira de Ciencia do Solo | Year: 2012

The physical quality of Amazonian soils is relatively unexplored, due to the unique characteristics of these soils. The index of soil physical quality is a widely accepted measure of the structural quality of soils and has been used to specify the structural quality of some tropical soils, as for example of the Cerrado ecoregion of Brazil. The research objective was to evaluate the physical quality index of an Amazonian dystrophic Oxisol under different management systems. Soils under five managements were sampled in Paragominas, State of Pará: 1) a 20-year-old second-growth forest (Forest); 2) Brachiaria sp pasture; 3) four years of no-tillage (NT4.); 4) eight years of no-tillage (NT8); and 5) two years of conventional tillage (CT2). The soil samples were evaluated for bulk density, macro and microporosity and for soil water retention. The physical quality index of the samples was calculated and the resulting value correlated with soil organic matter, bulk density and porosity. The surface layers of all systems were more compacted than those of the forest. The physical quality of the soil was best represented by the relations of the S index to bulk density and soil organic matter. Source


News Article
Site: http://www.greentechmedia.com/articles/category/solar

Shayle Kann and the GTM Research analyst team give GTM Squared members insight into our internal discussion and debate on the latest business developments across solar, grid, and energy storage markets in this monthly column. Shayle Kann Senior Vice President, Research: Grid Edge team, as you know, the California Public Utilities Commission (CPUC) has been under the gun to come up with a plan for merging the distribution resources plan (DRP) and the integration of distributed energy resources (IDER) into a cohesive whole. They recently held the first official joint workshop to hash out how it’s going to proceed, along with a straw proposal that helps clarify the timeline for certain key decisions over the next 12 months. There's required reading on the subject by Jeff St. John for GTM Squared that we published just last week. After reviewing the workshop proceedings and Jeff’s article, what did you learn about the plan? And do you think the CPUC is moving in the right direction to systemically remake energy procurement in California? Steve Propper Director, Grid Edge: To begin with, I think this is one of the first major attempts at combining large-scale integrated resource planning (the DRP proceeding) with utility/third-party and customer-owned assets (the IDER proceeding) into one regulatory conversation. For years, there have been a multitude of proceedings tackling each part of this separately -- there were solar and distributed generation (DG) proceedings, advanced metering infrastructure (AMI) and smart grid infrastructure proceedings, requests for cost recovery on various new technologies pilots, etc. There was also the infamous Integrated Demand-Side Management (IDSM) proceeding that languished out there and dates back more than five years, without tangible results at effectively merging overall distributed asset portfolio management at the regulatory level. So it's encouraging to see the CPUC take some more aggressive action and think more holistically about distribution planning and behind-the-meter resources (which, happily, includes demand response and other "non-generation" technologies). It's starting to sound a bit like New York REV, which isn't entirely surprising given recent talk from Albany on a New York-California distributed energy resource (DER) partnership. And, on the whole, the framework proposed by the CPUC makes logical sense from a business planning perspective. Shayle Kann Senior Vice President, Research: Steve Propper, you say it's encouraging, but will it be effective? First, I think the timeline for 2016 -- while ideal as a grid-edge technology enthusiast -- is quite aggressive. The January workshop to begin integrating in IDER aspects is what I see as one of the biggest challenges. Full agreement on how to measure benefits, assign compensation and get the methodology squared away for the locational net benefits analysis (LNBA) of the future pilots is key to effectively testing the pilot pipeline planned for the rest of the year (some of which don't have technology or vendor selection complete yet). I'm not totally skeptical, but have doubts on the timing given the amount of moving parts and the likely continued disconnect with how much data utilities are willing to share. Additionally, I think the goals of having advanced workshops by mid-2016 that detail pilot results and begin to integrate other proceedings like interconnection, storage and electric vehicles (EV) is a bit lofty without an unprecedented level of open dialogue and investor-owned utility-regulatory engagement. I'd be curious to get Ben Kellison's take on this. Ben Kellison Director, Grid Research: I would say this is a major step forward for the CPUC. The integrated nature of the conversation around integrated capacity analysis (ICA) and LNBA, if done right, could be a major leap forward in effective valuation and procurement of resources based on their value to the network. This would effectively address the value of solar, help determine optimal resource levels, and guide financial resources to more effective locations on the grid, all in one proceeding. This is a major shift for the CPUC; it has traditionally siloed all of these efforts into individual proceedings, sacrificing integration for faster implementation. This is a major advantage from an efficiency of capital perspective, but it creates a huge risk in the efficiency of negotiation. Workshops over the next year will have to make some major breakthroughs to set up the DRP pilots for success in the coming five years. The proceeding also hinges on several major technological and data management efforts to remake planning and simulation processes to incorporate DERs. Initial signs of the complexity involved with this process were shown in July with the release of the DRP plans that detailed the three IOUs' methodology to create an ICA. I am interested to see what compromises will have to be made to the vision of the proceeding in order to achieve value and meet milestones. For instance, will Southern California Edison be limited in its ability to determine the value of a particular resource on a single feeder because of its choice to utilize representational circuits? Will limitations like this force the CPUC to temper expectations to focus on the saturation and value of a resource deployment at the substation level in the short term and push out timelines for more detailed analysis? Omar Saadeh Senior Analyst, Grid Edge: Interestingly, DRP and IDER aren’t the only CPUC initiatives planned for full implementation by 2018. Two other CPUC initiatives are also scheduled for full implementation in two years: demand response direct participation and the demand response auction mechanism (DRAM). And coincidentally, both initiatives have also been featured in a past Jeff St. John thriller. On one hand, the commission’s direct participation initiative will require IOU demand response (DR) programs to be integrated as resources in the CAISO wholesale energy market. On the other, the CPUC’s demand response auction mechanism (DRAM) plans to create a competitive solicitation process for DR providers -- in this case, the IOUs -- to get paid today for future energy reductions. It’s essentially an open bidding DR capacity auction, very similar to PJM's structure. While all this is undoubtedly very progressive, there are still many questions on the table which may ultimately push back some of these deadlines. Andrew Mulherkar Analyst, Grid Research: I'm not sure that "progressive" fully captures the nature of the CPUC's work here. It appears to me that this effort is critical element of a tectonic shift in how California's electric utilities plan for, procure, and pay for energy resources. The CPUC is looking to transform traditional, centralized resource procurement into a next-generation procurement process that leverages the extraordinary growth of distributed solar PV, controllable loads, energy storage, electric vehicles and energy efficiency. The integration of the two proceedings will ideally give utilities both a way to value and plan for distributed energy resources (through the DRP) and to actually procure the resources (through the IDER). Now, as eager as I am to see a comprehensive approach here, the scope of the approach is daunting. As Steve Propper points out, the precursor to IDER languished -- and that's despite a relatively siloed and limited scope. One exciting idea to emerge from the IDER proceeding is incentives that reflect locational benefits. Once fully developed, it's not inconceivable that consumers could receive solar PV incentives just based on the characteristics of their local distribution feeder. Then we can look back and smile at the days when demand-side management (DSM) meant mailing compact fluorescent lamps (CFLs) to any and every customer. Steve Propper Director, Grid Edge: ​CFLs! I recall a few Saturdays educating customers about lighting with retail partners like Sears, Lowe's and Best Buy. I agree with previous comments, but as I was thinking about this last night, I can't seem to shake the importance of the CPUC getting the data-sharing and third-party access components "squared" away early on in these workshops next year beyond the A and B pilots, which look pretty straightforward. I might suggest they make sure to have some experts from the wireless, banking and/or consumer internet worlds playing an active role in these workshops to push some more aggressive thinking in how this can get accomplished. I understand the utilities' trepidation over security and customer data, but I also think you will see third parties and ultimately customers become more active in participating if it's clear what the benefits are related to DER procurement and ongoing distribution-level management. Also, as the end-user equation within this joint proceeding gets worked out, I'd hope there is also a realistic conversation about the notion of perceived privacy vs actual privacy over sharing more granular data points such as usage data and behind-the-meter DER asset performance. Think about all the apps that are collecting and sharing customer data today...a far cry from 10 years ago without that much ruckus around privacy. Omar Saadeh Senior Analyst, Grid Edge: Taking a look at vendor prospects, I think potential opportunities will go beyond incumbent vendors -- those with circuit-level modeling or control systems already deployed at the IOUs -- to companies offering utility distribution management support and third party DER fleet management. Think Enbala, Blue Pillar, Smarter Grid Solutions, Spirae, 1Energy Systems, etc. Moreover, it’s not surprising that DER providers like SolarCity, Sunverge and Enphase have been developing grid software that extends beyond asset management. Not to be overly bold, but I’d expect SolarCity’s GridLogic technology to eventually scale beyond just microgrids. With regards to DR -- it’s really interesting to see how the vendor community is reacting. As utilities become less dependent on third-party program implementation and with continued uncertainty in wholesale demand response markets, companies are clearly taking notice, some even shifting business models. For example, EnerNOC is diversifying away from market-based DR, which it deems to be higher-risk, and into enterprise and utility software-as-a-service -- a move pursued by Enbala not too long ago. On a bright note, similar to PG&E’s recent DERMS RFP, I’d expect project scopes to be left somewhat open-ended, providing vendors with opportunities to showcase platform strengths and -- very importantly -- expand capabilities while under utility support. Click here to learn more about the latest grid edge research from GTM Research. You can read bios for the analyst team here.


News Article
Site: http://www.nature.com/nature/current_issue/

All common chemicals were from Sigma. Pyrrolidinedithiocarbamic acid was from Santa Cruz Biotechnology. Exo-FBS exosome-depleted FBS was purchased from System Biosciences (SBI). PTEN (9188), pAkt(T308) (9275), pAkt(S473) (4060), Pan Akt (4691), and Bim (2933) antibodies were from Cell Signaling. CD9 (ab92726), Rab27a (ab55667), AMPK (ab3759), CCL2 (ab9899), MAP2 (ab11267), and pP70S6K (ab60948) antibodies were from Abcam. Tsg101 (14497-1-AP) and Rab27b (13412-1-AP) antibodies were from Proteintech. CD81 (104901) antibody was from BioLegend. E2F1 (NB600-210) and CCR2 (NBP1-48338) antibodies were from Novus. GFAP (Z0334) antibody was from DAKO. IBA1 antibody was from WAKO. Cre (969050) antibody was from Novagen. NF-κB p65 (SC-109) and CD63 (SC-15363) antibodies were from Santa Cruz. DMA (sc-202459) and CCR2 antagonist (sc-202525) were from Santa Cruz. MK2206 (S1078) was from Selleckchem. PDTC (P8765) was from Sigma-Aldrich. Human breast cancer cell lines (MDA-MB-231, HCC1954, BT474 and MDA-MB-435) and mouse cell lines (B16BL6 mouse melanoma and 4T1 mouse breast cancer) were purchased from ATCC and verified by the MD Anderson Cancer Center (MDACC) Cell Line Characterization Core Facility. All cell lines have been tested for mycoplasma contamination. Primary glia was isolated as described13. In brief, after homogenization of dissected brain from postnatal day (P)0–P2 neonatal mouse pups, all cells were seeded on poly-d-lysine coated flasks. After 7 days, flasks with primary culture were placed on an orbital shaker and shaken at 230 r.p.m. for 3 h. Warm DMEM 10:10:1 (10% of fetal bovine serum, 10% of horse serum, 1% penicillin/streptomycin) was added and flasks were shaken again at 260 r.p.m. overnight. After shaking, fresh trypsin was added into the flask and leftover cells were plated with warm DMEM 5:5:1 (5% of fetal bovine serum, 5% of horse serum, 1% penicillin/streptomycin) to establish primary astrocyte culture. More than 90% of isolated primary glial cells were GFAP+ astrocytes. Primary CAFs were isolated by digesting the mammary tumours from MMTV-neu transgenic mouse. 231-xenograft CAFs were isolated by digesting the mammary tumours from MDA-MB-231 xenograft. For the mixed co-culture experiments, tumour cells were mixed with an equal number of freshly isolated primary glia, CAFs or NIH3T3 fibroblast cells in six-well plate (1:3 ratio). Co-cultures were maintained for 2–5 days before magnetic-bead-based separation. For the trans-well co-culture experiments, tumour cells were seeded in the bottom well and freshly isolated primary glia, CAFs or NIH3T3 cells were seeded on the upper insert (1:3 ratio). Co-cultures were maintained for 2–5 days for the further experiments. Lentiviral-based packaging vectors (Addgene), pLKO.1 PTEN-targeting shRNAs and all siRNAs (Sigma), Human Cytokine Antibody Array 3 (Ray biotech), and lentiviral-based vector pTRIPZ-PTEN and pTRIPZ-CCL2 shRNAs (MDACC shRNA and ORFome Core, from Open Biosystems) were purchased. The human PTEN-targeting shRNA sequences in the lentiviral constructs were: 5′-CCGGAGGCGCTATGTGTATTATTATCTCGAGATAATAATACACATAGCGCCTTTTTT-3′ (targeting coding sequence); 5′-CCGGCCACAAATGAAGGGATATAAACTCGAGTTTATATCCCTTCATTTGTGGTTTTT-3′ (targeting 3′-UTR). The human PTEN-targeting siRNA sequences used were: 5′-GGUGUAAUGAUAUGUGCAU-3′ and 5′-GUUAAAGAAUCAUCUGGAU-3′. The human CCL2-targeting siRNA sequences used were: 5′-CAGCAAGUGUCCCAAAGAA-3′ and 5′-CCGAAGACUUGAACACUCA-3′. The mouse Rab27a-targeting siRNA sequences used were: 5′-CGAUUGAGAUGCUCCUGGA-3′ and 5′-GUCAUUUAGGGAUCCAAGA-3′. Mouse pLKO shRNA (shRab27a: TRCN0000381753; shRab27b: TRCN0000100429) were purchased from Sigma. For lentiviral production, lentiviral expression vector was co-transfected with the third-generation lentivirus packing vectors into 293T cells using Lipo293 DNA in vitro Transfection Reagent (SignaGen). Then, 48–72 h after transfection, cancer cell lines were stably infected with viral particles. Transient transfection with siRNA was performed using pepMute siRNA transfection reagent (SignaGen). For in vivo intracranial virus injection, lentivirus was collected from 15 cm plates 48 h after transfection of packaging vectors. After passing a 0.45 μm filter, all viruses were centrifuged at 25,000 r.p.m (111,000g) for 90 min at 4 °C. Viral pellet was suspended in PBS (~200-fold concentrated). The final virus titre (~1 × 109 UT ml−1) was confirmed by limiting dilution. Cell isolation was performed based on the magnetic bead-based cell sorting protocol according to manufacturer’s recommendation (Miltenyi Biotec Inc.). After preparation of a single-cell suspension, tumour cells (HCC1954 or BT474) were stained with primary EpCAM-FITC antibody (130-098-113) (50 μl per 107 total cells) and incubated for 30 min in the dark at 4 °C. After washing, the cell pellet was re-suspended and anti-FITC microbeads (50 μl per 107 total cells) were added before loading onto the magnetic column of a MACS separator. The column was washed twice and removed from the separator. The magnetically captured cells were flushed out immediately by firmly applying the plunger. The isolated and labelled cells were analysed on a Gallios flow cytometer (Beckman Coulter). For EpCAM-negative MDA-MB-231 tumour cells, FACS sorting (ARIAII, Becton Dickinson) was used to isolate green fluorescent protein (GFP)+ tumour cells from glia or CAFs. Isolation of primary glia was achieved by homogenization of dissected brain from P0–P2 mouse pups. After 7 days, trypsin was added and cells were collected. After centrifugation and re-suspension of cell pellet to a single-cell suspension, cells were incubated with CD11b+ microbeads (Miltenyl Biotec) (50 μl per 107 total cells) for 30 min at 4 °C. The cells were washed with buffer and CD11b+ cells were isolated by MACS Column. CD11b+ cells were analysed by flow cytometry and immunofluorescence staining. Western blotting was done as previously described. In brief, cells were lysed in lysis buffer (20 mM Tris, pH 7.0, 1% Triton X-100, 0.5% NP-40, 250 mM NaCl, 3 mM EDTA and protease inhibitor cocktail). Proteins were separated by SDS–PAGE and transferred onto a nitrocellulose membrane. After membranes were blocked with 5% milk for 30 min, they were probed with various primary antibodies overnight at 4 °C, followed by incubation with secondary antibodies for 1 h at room temperature, and visualized with enhanced chemiluminescence reagent (Thermo Scientific). In brief, total RNA was isolated using miRNeasy Mini Kit (Qiagen) and then reverse transcribed using reverse transcriptase kits (iScript cDNA synthesis Kit, Bio-rad). SYBR-based qRT–PCR was performed using pre-designed primers (Life Technologies). miRNA assay was conducted using Taqman miRNA assay kit (Life Technologies). For quantification of gene expression, real-time PCR was conducted using Kapa Probe Fast Universal qPCR, and SYBR Fast Universal qPCR Master Mix (Kapa Biosystems) on a StepOnePlus real-time PCR system (Applied Biosystems). The relative expression of mRNAs was quantified by 2−ΔΔCt with logarithm transformation. Primers used in qRT–PCR analyses are: mouse Ccl2: forward, 5′-GTTGGCTCAGCCAGATGCA-3′; reverse: 5′-AGCCTACTCATTGGGATCATCTTG-3′. Mouse Actb: forward: 5′-AGTGTGACGTTGACATCCGT3′; reverse: 5′-TGCTAGGAGCCAGAGCAGTA-3′. Mouse Pten: forward: 5′-AACTTGCAATCCTCAGTTTG-3′; reverse: 5′-CTACTTTGATATCACCACACAC-3′. Mouse Ccr2 primer: Cat: 4351372 ID: Mm04207877_m1 (Life technologies) Synthetic miRNAs were purchased from Sigma and labelled with Cy3 by Silencer siRNA labelling kit (Life Technologies). In brief, miRNAs were incubated with labelling reagent for 1 h at 37 °C in the dark, and then labelled miRNAs were precipitated by ethanol. Labelled miRNAs (100 pmoles) were transfected into astrocytes or CAFs in a 10-cm plate. After 48 h, astrocytes and CAFs containing Cy3-miRNAs were co-cultured with tumour cells (at 5:1 ratio). Genomic DNA was isolated by PreLink genomic DNA mini Kit (Invitrogen), bisulfite conversion was performed by EpiTect Bisulphite Kit and followed by EpiTect methylation-specific PCR (Qiagen). Primers for PTEN CpG island are 5′-TGTAAAACGACGGCCAGTTTGTTATTATTTTTAGGGTTGGGAA-3′ and 5′-CAGGAAACAGCTATGACCCTAAACCTACTTCTCCTCAACAACC-3′. Luciferase reporter assays were done as previously described27. The wild-type PTEN promoter driven pGL3-luciferase reporter was a gift from A. Yung. The pGL3-PTEN reporter and a control Renilla luciferase vector were co-transfected into tumour cells by Lipofectamine 2000 (Life Technologies). After 48 h, tumour cells were co-cultured with astrocytes or CAFs. Another 48 h later, luciferase activities were measured by Dual-Luciferase Report Assay Kit (Promega) on Luminometer 20/20 (Turner Biosystems). The PTEN 3′-UTRs with various miRNA binding-site mutations were generated by standard PCR-mediated mutagenesis method and inserted downstream of luciferase reporter gene in pGL3 vector. The activities of the luciferase reporter with the wild-type and mutated PTEN 3′-UTRs were assayed as described above. Astrocytes or CAFs were cultured for 48–72 h and exosomes were collected from their culture media after sequential ultracentrifugation as described previously. In brief, cells were collected, centrifuged at 300g for 10 min, and the supernatants were collected for centrifugation at 2,000g for 10 min, 10,000g for 30 min. The pellet was washed once with PBS and purified by centrifugation at 100,000g for 70 min. The final pellet containing exosomes was re-suspended in PBS and used for (1) transmission electron microscopy by fixing exosomes with 2% glutaraldehyde in 0.1 M phosophate buffer, pH 7.4; (2) measure of total exosome protein content using BCA Protein Assay normalized by equal number of primary astrocytes and CAF cells; (3) western blotting of exosome marker protein CD63, CD81 and Tsg101; and (4) qRT–PCR by extracting miRNAs with miRNeasy Mini Kit (Qiagen). Fixed samples were placed on 100-mesh carbon-coated, formvar-coated nickel grids treated with poly-l-lysine for about 30 min. After washing the samples on several drops of PBS, samples were incubated on drops of buffered 1% gluteraldehyde for 5 min, and then washed several times on drops of distilled water. Afterwards, samples were negatively stained on drops of millipore-filtered aqueous 4% uranyl acetate for 5 min. Stain was blotted dry from the grids with filter paper and samples were allowed to dry. Samples were then examined in a JEM 1010 transmission electron microscope (JEOL) at an accelerating voltage of 80 Kv. Digital images were obtained using the AMT Imaging System (Advanced Microscopy Techniques Corp.). For exosome detection, 100 μl exosomes isolated from 10-ml conditioned media of astrocytes or CAFs were incubated with 10 μl of aldehyde/sulfate latex beads (4 μm diameter, Life Technologies) for 15 min at 4 °C. After 15 min, PBS was added to make sample volume up to 400 μl, which was incubated overnight at 4 °C under gentle agitation. Exosome-coated beads were washed twice in FACS washing buffer (1% BSA and 0.1% NaN in PBS), and re-suspended in 400 μl FACS washing buffer, stained with 4 μg of phycoerythrin (PE)-conjugated anti-mouse CD63 antibody (BioLegend) or mouse IgG (Santa Cruz Biotechnology) for 3 h at 4 °C under gentle agitation and analysed on a FACS Canto II flow cytometer. Samples were gated on bead singlets based on FCS and SSC characteristics (4 μm diameter). For Annexin V apoptosis assay, after 24 h doxorubicin (2 μM) treatment, the cells were collected, labelled by APC-Annexin V antibody (Biolegend) and analysed on a FACS Canto II flow cytometer. CD11b+ and BV2 cells were stained with CCR2 antibody (Novus) at 4 °C overnight; they were then washed and stained with Alexa Fluor 488 anti-rabbit IgG (Life Technologies) at room temperature for 1 h. The cells were then analysed on a FACS Canto II flow cytometer. All animal experiments and terminal endpoints were carried out in accordance with approved protocols from the Institutional Animal Care and Use Committee of the MDACC. Animal numbers of each group were calculated by power analysis and animals are grouped randomly for each experiment. No blinding of experiment groups was conducted. MFP tumours were established by injection of 5 × 106 tumour cells in 100 μl of PBS:Matrigel mixture (1:1 ratio) orthotopically into the MFP of 8-week-old Swiss nude mice as done previously28. Brain metastasis tumours were established by ICA injection of tumour cells (250,000 cells in 0.1 ml HBSS for MDA-MB-231, HCC1954, MDA-MB-435, 4T1 and B16BL6, and 500,000 cells in 0.1 ml HBSS for BT474.m1 into the right common carotid artery as done previously29). Mice (6–8 weeks) were randomly grouped into designated groups. Female mice are used for breast cancer experiments, both female and male are used for melanoma experiments. Since the brain metastasis model does not result in visible tumour burdens in living animal, the endpoints of in vivo metastasis experiments are based on the presence of clinical signs of brain metastasis, including but not limited to, primary central nervous system disturbances, weight loss, and behavioural abnormalities. Animals are culled after showing the above signs or 1–2 weeks after surgery based on specific experimental designs. Brain metastasis lesions are enumerated as experimental readout. Brain metastases were counted as micromets and macromets. The definition of micromets and macromets are based on a comprehensive mouse and human comparison study previously published30. In brief, ten haematoxylin and eosin (H&E)-stained serial sagittal sections (300 μm per section) through the left hemisphere of the brain were analysed for the presence of metastatic lesions. We counted micrometastases (that is, those ≤ 50 μm in diameter) to a maximum of 300 micrometastases per section, and every large metastasis (that is, those > 50 μm in diameter) in each section. Brain-seeking cells from overt metastases and whole brains were dissected and disaggregated in DMEM/F-12 medium using Tenbroeck homogenizer briefly. Dissociated cell mixtures were plated on tissue culture dish. Two weeks later, tumours cells recovered from brain tissue were collected and expanded as brain-seeking sublines (Br.1). For the astrocyte miR-19 knockout mouse model, Mirc1tm1.1Tyj/J mice (Jax lab) (6–8 weeks) were intracranially injected with Ad5-GFAP-Cre virus (Iowa University, Gene Transfer Vector Core) 2 μl (MOI ~108 U μl−1) per point, total four points at the right hemisphere (n = 9). Control group (n = 7) was injected with the same dose Ad5-RSV-βGLuc (Ad-βGLuc) at the right hemisphere. All intracranial injections were performed by an implantable guide-screw system. One week after virus injection, mice were intracarotidly injected with 2 × 105 B16BL6 tumour cells. After two weeks, whole brains were dissected and fixed in 4% formaldehyde, and embedded in paraffin. Tumour formation, histological phenotypes of H&E-stained sections, and IHC staining were evaluated. Only parenchymal lesions, which are in close proximity of adenovirus injection, were included in our evaluation. Tumour size was calculated as (longest diameter) × (shortest diameter)2/2. For the intracranial tumour model, Mirc1tm1.1Tyj/J mice (Jax lab) (6–8 weeks) were intracranially injected as described above. Seven mice were used in the experiment. One week later, these mice were intracranially injected with 2.5 × 105 B16BL6 tumour cells at both sides where adenoviruses were injected. After another week, whole brains were dissected and fixed in 4% formaldehyde, and embedded in paraffin. Tumour formation and phenotype were analysed as above. For the Rab27a/b knockdown mouse model, seven C57BL6 mice (Jax lab) (6–8 weeks) were intracranially injected with concentrated lentivirus containing shRab27a and shRab27b (ratio 1:2) 2 μl per point, total three points at the right hemisphere; concentrated control lentivirus containing pLKO.1 scramble were injected at the left hemisphere. All intracranial injections were performed by an implantable guide-screw system. One week later, mice were intracranially injected with 5 × 104 B16BL6 tumour cells at both sides where they had been infected. After one week, whole brains were dissected and fixed in 4% formaldehyde, and embedded in paraffin. Tumour formation, histological phenotypes of H&E-stained sections, IHC staining were evaluated. When performing metastases size quantification, only parenchymal lesions that were in close proximity to the adenovirus injection sites were included in the analyses. Tumour size was calculated as (longest diameter) × (shortest diameter)2/2. For exosome rescue experiments, eight C57BL6 mice (Jax lab) (6–8 weeks) were intracranially injected with concentrated lentivirus containing shRab27a and shRab27b (ratio 1:2) 2 μl per point, total 3 points at both hemispheres. One week later, these mice were intracranially injected with 5 × 104 B16BL6 tumour cells with 10 μg exosome isolated from astrocyte media at the right sides where they had been injected with lentivirus; 5 × 104 B16BL6 tumour cells with vehicle were injected at the left sides where lentivirus had been injected. After another week, whole brains were dissected and fixed in 4% formaldehyde, and embedded in paraffin. Tumour formation and phenotype were analysed as above. For in vivo extravasation assay, equal numbers of cells labelled with GFP-control shRNA and RFP-PTEN shRNA (Open Biosystems) were mixed and ICA injected. After cardiac perfusion, brains were collected and sectioned through coronal plan on a vibrotome (Leica) into 50-μm slices. Fluorescent cells were then counted. For inducible PTEN expression in vivo, mice were given doxycycline (10 μg kg−1) every other day. To quantify brain metastasis incidence and tumour size, brains were excised for imaging and histological examination at the end of experiments. Ten serial sagittal sections every 300 μm throughout the brain were analysed by at least two pathologists who were blinded to animal groups in all above analyses. Reverse-phase protein array of PTEN-overexpressing cells was performed in the MDACC Functional Proteomics core facility. In brief, cellular proteins were denatured by 1% SDS, serial diluted and spotted on nitrocellulose-coated slides. Each slide was probed with a validated primary antibody plus a biotin-conjugated secondary antibody. The signal obtained was amplified using a Dako Cytomation-catalysed system and visualized by DAB colorimetric reaction. The slides were analysed using customized Microvigene software (VigeneTech Inc.). Each dilution curve was fitted with a logistic model (‘Super curve fitting’ developed at the MDACC) and normalized by median polish. Differential intensity of normalized log values of each antibody between RFP (control) and PTEN-overexpressed cells were compared in GenePattern (http://genepattern.broadinstitute.org). Antibodies with differential expression (P < 0.2) were selected for clustering and heat-map analysis. The data clustering was performed using GenePattern. Two studies in separate cohorts were conducted. The first one was a retrospective evaluation of PTEN in two cohorts. (1) Archived formalin-fixed and paraffin-embedded brain metastasis specimens (n = 131) from patients with a history of breast cancer who presented with metastasis to the brain parenchyma and had surgery at the MDACC (Supplementary Information). Tissues were collected under a protocol (LAB 02-486) approved by the Institutional Review Board (IRB) at the MDACC. (2) Archived unpaired primary breast cancer formalin-fixed and paraffin-embedded specimens (n = 139) collected under an IRB protocol (LAB 02-312) at the MDACC (Supplementary information). Formal consent was obtained from all patients. The second study was a retrospective evaluation of PTEN, CCL2 and IBA1 in the matched primary breast tumours and brain metastatic samples from 35 patients, of which there are 12 HER2-positive, 14 triple-negative and nine oestrogen-receptor-positive tumours according to clinical diagnostic criteria (Supplementary Information). Formalin-fixed, paraffin-embedded primary breast and metastatic brain tumour samples were obtained from the Pathology Department, University of Queensland Centre for Clinical Research. Tissues were collected with approval by human research ethics committees at the Royal Brisbane and Women’s Hospital (2005/022) and the University of Queensland (2005000785). For tissue microarray construction, tumour-rich regions (guided by histological review) from each case were sampled using 1-mm cores. All the archival paraffin-embedded tumour samples were coded with no patient identifiers. Standard IHC staining was performed as described previously28. In brief, after de-paraffinization and rehydration, 4 μm sections were subjected to heat-induced epitope retrieval (0.01 M citrate for PTEN). Slides were then incubated with various primary antibodies at 4 °C overnight, after blocking with 1% goat serum. Slides underwent colour development with DAB and haematoxylin counterstaining. Ten visual fields from different areas of each tumour were evaluated by two pathologists independently (blinded to experiment groups). Positive IBA1 and Ki-67 staining in mouse tumours were calculated as the percentage of positive cells per field (%) and normalized by the total cancer cell number in each field. TUNEL staining was counted as the average number of positive cells per field (10 random fields). We excluded necrotic areas in the tumours from evaluation. Immunofluorescence was performed following the standard protocol recommended by Cell Signaling. In brief, after washing with PBS twice, cells were fixed with 4% formaldehyde. Samples were blocked with 5% normal goat serum in PBS for 1 h before incubation with a primary antibody cocktail overnight at 4 °C, washed, then incubated with secondary antibodies before examination using confocal microscope. Pathologists were blinded to the group allocation during the experiment and when assessing the outcome. Publicly available GEO data sets GSE14020, GSE19184, GSE2603, GSE2034 and GSE12276 were used for bioinformatics analysis. The top 2 × 104 verified probes were subjected to analysis. Differentially expressed genes between metastases from brain and other sites (primary or other metastatic organ sites) were analysed by SAM analysis in R statistical software. The 54 commonly downregulated genes in brain metastases from GSE14020 and GSE19184 were depicted as a heat-map by Java Treeview. For staining of patient samples, we calculated the correlation by Fisher’s exact test. For survival analysis of GSE2603, the patient samples were mathematically separated into PTEN-low and -normal groups based on K-means (K = 2). Kaplan–Meier survival curves were generated by survival package in R. Multiple group IHC scores were compared by Chi-square test and Mantelhaen test in R. All quantitative experiments have been repeated using at least three independent biological repeats and are presented as mean ± s.e.m. or mean ± s.d.. Quantitative data were analysed either by one-way analysis of variance (ANOVA) (multiple groups) or t-test (two groups). P < 0.05 (two-sided) was considered statistically significant.

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