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    <title>Alexander Lab @ WHOI on Alexander Lab @ WHOI</title>
    <link>https://alexanderlabwhoi.github.io/</link>
    <description>Recent content in Alexander Lab @ WHOI on Alexander Lab @ WHOI</description>
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    <copyright>&amp;copy; 2019</copyright>
    <lastBuildDate>Mon, 01 Jan 2024 00:00:00 -0500</lastBuildDate>
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    <item>
      <title>Microeukaryote metabolism across the western North Atlantic Ocean revealed through autonomous underwater profiling</title>
      <link>https://alexanderlabwhoi.github.io/publication/cohen-2024-microeukaryote/</link>
      <pubDate>Mon, 01 Jan 2024 00:00:00 -0500</pubDate>
      
      <guid>https://alexanderlabwhoi.github.io/publication/cohen-2024-microeukaryote/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Molecular forecasting of toxic bloom events</title>
      <link>https://alexanderlabwhoi.github.io/publication/alexander-2024-molecular/</link>
      <pubDate>Mon, 01 Jan 2024 00:00:00 -0500</pubDate>
      
      <guid>https://alexanderlabwhoi.github.io/publication/alexander-2024-molecular/</guid>
      <description></description>
    </item>
    
    <item>
      <title>The Dawn of the BioGeoSCAPES Program</title>
      <link>https://alexanderlabwhoi.github.io/publication/saito-2024-dawn/</link>
      <pubDate>Mon, 01 Jan 2024 00:00:00 -0500</pubDate>
      
      <guid>https://alexanderlabwhoi.github.io/publication/saito-2024-dawn/</guid>
      <description></description>
    </item>
    
    <item>
      <title>sourmash v4: A multitool to quickly search, compare, and analyze genomic and metagenomic data sets</title>
      <link>https://alexanderlabwhoi.github.io/publication/irber-2024-sourmash/</link>
      <pubDate>Mon, 01 Jan 2024 00:00:00 -0500</pubDate>
      
      <guid>https://alexanderlabwhoi.github.io/publication/irber-2024-sourmash/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Reverse engineering environmental metatranscriptomes clarifies best practices for eukaryotic assembly</title>
      <link>https://alexanderlabwhoi.github.io/publication/krinos-2023/</link>
      <pubDate>Wed, 01 Mar 2023 00:00:00 -0500</pubDate>
      
      <guid>https://alexanderlabwhoi.github.io/publication/krinos-2023/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Using anvi&#39;o in interactive mode</title>
      <link>https://alexanderlabwhoi.github.io/post/2022-10-24_anvio/</link>
      <pubDate>Mon, 24 Oct 2022 15:25:12 -0400</pubDate>
      
      <guid>https://alexanderlabwhoi.github.io/post/2022-10-24_anvio/</guid>
      <description>

&lt;p&gt;Anvi&amp;rsquo;o is a powerful tool for analyzing and vizualizing &amp;lsquo;omics data, much of which relies on one&amp;rsquo;s ability to visualize those data. On Poseidon, it can sometimes be difficult to work with these kinds of plotting tools, because we&amp;rsquo;re working on the command line. To use anvi&amp;rsquo;o interactively on Poseidon, we need to go through a few extra steps.&lt;/p&gt;

&lt;p&gt;I&amp;rsquo;ll walk you through the whole installation of anvi&amp;rsquo;o here from start to finish! Most of these instructions are also available on anvio.org. The other half of these instructions are mostly in the posts &lt;a href=&#34;https://alexanderlabwhoi.github.io/post/2019-03-08_jpn_slurm/&#34; target=&#34;_blank&#34;&gt;here&lt;/a&gt; (for Mac) and &lt;a href=&#34;https://alexanderlabwhoi.github.io/post/2019-07-24-slurm-win/&#34; target=&#34;_blank&#34;&gt;here&lt;/a&gt; (for Windows) that we&amp;rsquo;ve previously uploaded to the blog!&lt;/p&gt;

&lt;h3 id=&#34;step-one-create-a-fresh-conda-environment-for-anvi-o-and-install-dependencies&#34;&gt;Step One: create a fresh &lt;code&gt;conda&lt;/code&gt; environment for anvi&amp;rsquo;o and install dependencies&lt;/h3&gt;

&lt;p&gt;I like using &lt;code&gt;mamba&lt;/code&gt;. That will make the rest of your installs much faster. So I&amp;rsquo;ve modified anvi&amp;rsquo;o&amp;rsquo;s installation instructions a little bit to fit that principle. After logging into Poseidon&amp;rsquo;s login node (and making sure that you have the most recent and/or your preferred anaconda module loaded), we&amp;rsquo;ll run:&lt;/p&gt;

&lt;pre&gt;&lt;code&gt;conda create -y --name anvio python=3.6 mamba
&lt;/code&gt;&lt;/pre&gt;

&lt;p&gt;We&amp;rsquo;ll wait for that to finish, then execute &lt;code&gt;conda activate anvio&lt;/code&gt; (or whatever you chose to name your environment! Next, we have a whole list of packages we&amp;rsquo;ll want mamba to go ahead and (efficiently) install for us in order for anvi&amp;rsquo;o to work. You should be able to just copy, paste, and execute this entire code block right in your terminal window.&lt;/p&gt;

&lt;pre&gt;&lt;code&gt;mamba install -y -c bioconda &amp;quot;sqlite&amp;gt;=3.31.1&amp;quot;
mamba install -y -c bioconda prodigal
mamba install -y -c bioconda mcl
mamba install -y -c bioconda muscle=3.8.1551
mamba install -y -c bioconda hmmer
mamba install -y -c bioconda diamond
mamba install -y -c bioconda blast
mamba install -y -c bioconda megahit
mamba install -y -c bioconda spades
mamba install -y -c bioconda bowtie2 tbb=2019.8
mamba install -y -c bioconda bwa
mamba install -y -c bioconda samtools=1.9
mamba install -y -c bioconda centrifuge
mamba install -y -c bioconda trimal
mamba install -y -c bioconda iqtree
mamba install -y -c bioconda trnascan-se
mamba install -y -c bioconda r-base
mamba install -y -c bioconda r-stringi
mamba install -y -c bioconda r-tidyverse
mamba install -y -c bioconda r-magrittr
mamba install -y -c bioconda r-optparse
mamba install -y -c bioconda bioconductor-qvalue
mamba install -y -c bioconda fasttree
mamba install -y -c bioconda vmatch
mamba install -y -c bioconda fastani ## anvio says you don&#39;t need this one
&lt;/code&gt;&lt;/pre&gt;

&lt;p&gt;Note: anvi&amp;rsquo;o&amp;rsquo;s website says that you don&amp;rsquo;t need the &lt;code&gt;fastani&lt;/code&gt; package installed for the software to work. The install went fine for me. The whole install process might take quite a while, depending on the speed of the connection. If you elect to use &lt;code&gt;conda&lt;/code&gt; over &lt;code&gt;mamba&lt;/code&gt;, it will take a &lt;em&gt;lot&lt;/em&gt; longer.&lt;/p&gt;

&lt;h3 id=&#34;step-two-actually-install-anvi-o&#34;&gt;Step Two: actually install anvi&amp;rsquo;o&lt;/h3&gt;

&lt;p&gt;You should execute this in a folder where you don&amp;rsquo;t mind software files being downloaded to:&lt;/p&gt;

&lt;pre&gt;&lt;code&gt;curl -L https://github.com/merenlab/anvio/releases/download/v7.1/anvio-7.1.tar.gz \
        --output anvio-7.1.tar.gz
pip install anvio-7.1.tar.gz
&lt;/code&gt;&lt;/pre&gt;

&lt;p&gt;Now, you should be good to go to run anvi&amp;rsquo;o!&lt;/p&gt;

&lt;h3 id=&#34;step-three-get-a-worker-node-spun-up-to-do-your-bidding&#34;&gt;Step Three: get a worker node spun up to do your bidding&lt;/h3&gt;

&lt;p&gt;We&amp;rsquo;ll run an interactive job on Poseidon using &lt;code&gt;srun&lt;/code&gt;. You can modify this command as needed if you want this job to go for longer than two hours&amp;hellip;or if people are hogging all the &lt;code&gt;compute&lt;/code&gt; nodes and you need to hedge your bets with a pre-empt-able &lt;code&gt;scavenger&lt;/code&gt; run, for example.&lt;/p&gt;

&lt;pre&gt;&lt;code&gt;srun -p compute --time=02:00:00 --mem=50gb --pty bash
&lt;/code&gt;&lt;/pre&gt;

&lt;p&gt;Eventually, this should log you into a clean worker node, so your prompt should change from &lt;username&gt;@poseidon-l&lt;1 or 2&gt;.whoi.edu to &lt;username&gt;@pn&amp;lt;# of node you were assigned&amp;gt;. Now, you&amp;rsquo;re ready to not annoy the IT department by executing expensive programs on the common login node! Make sure now to &lt;code&gt;conda activate anvio&lt;/code&gt;.&lt;/p&gt;

&lt;h3 id=&#34;step-four-run-anvi-o-interactive-but-make-sure-to-specify-a-port&#34;&gt;Step Four: run anvi&amp;rsquo;o interactive, but make sure to specify a port&lt;/h3&gt;

&lt;p&gt;In order to run this, I am going to use the example the &lt;a href=&#34;https://merenlab.org/2016/02/27/the-anvio-interactive-interface/&#34; target=&#34;_blank&#34;&gt;Eren lab&lt;/a&gt; provides, since I don&amp;rsquo;t use anvi&amp;rsquo;o much. Note that their link is broken on their tutorial website. I found one that works &lt;a href=&#34;https://github.com/meren/anvio/blob/master/anvio/tests/sandbox/example-newick-tree.txt&#34; target=&#34;_blank&#34;&gt;here&lt;/a&gt;. I just saved the Newick text at that link to a file called &lt;code&gt;meren_tree.txt&lt;/code&gt;, then (inside my interactive session!), I executed:&lt;/p&gt;

&lt;pre&gt;&lt;code&gt;anvi-interactive -t meren_tree.txt -p profile.db --title &#39;Simple tree test&#39; --server-only -P 5785
&lt;/code&gt;&lt;/pre&gt;

&lt;h3 id=&#34;step-five-log-into-your-node-and-forward-that-port-to-your-browser&#34;&gt;Step Five: log into your node and forward that port to your browser&lt;/h3&gt;

&lt;p&gt;All of these steps are straight out of our tutorial on running a Jupyter notebook remotely that I linked above. If you use Windows, be sure to check out that post - I&amp;rsquo;m only using the Mac command here.&lt;/p&gt;

&lt;pre&gt;&lt;code&gt;ssh -t -t &amp;lt;username&amp;gt;@poseidon-l1.whoi.edu -L 5785:localhost:5785 ssh &amp;lt;the name of the &amp;quot;pn&amp;quot; node from above that showed up when you ran srun&amp;gt; -L 5785:localhost:5785
&lt;/code&gt;&lt;/pre&gt;

&lt;p&gt;To summarize, above you need to swap out:
- your own username
- the port number if you changed it
- the name of the worker node you ssh&amp;rsquo;d into&lt;/p&gt;

&lt;p&gt;For example, if my username is &amp;ldquo;akrinos&amp;rdquo;, I used port 5786, and I ssh&amp;rsquo;d into &amp;ldquo;pn075&amp;rdquo;, I would type:&lt;/p&gt;

&lt;pre&gt;&lt;code&gt;ssh -t -t akrinos@poseidon-l1.whoi.edu -L 5786:localhost:5786 ssh pn075 -L 5786:localhost:5786
&lt;/code&gt;&lt;/pre&gt;

&lt;p&gt;Be sure to check out our more detailed post on ssh tunneling if you want shortcuts for doing this!&lt;/p&gt;

&lt;h3 id=&#34;step-six-access-your-interactive-session&#34;&gt;Step Six: access your interactive session&lt;/h3&gt;

&lt;p&gt;Simply type &lt;code&gt;localhost:5786&lt;/code&gt; into your web browser (replacing this second number with your present node), and you should be able to see your anvi&amp;rsquo;o interactive session! Feel free to use any &lt;code&gt;anvi-interactive&lt;/code&gt; command and accessory files that you want to after creating/uploading those files on Poseidon.&lt;/p&gt;

&lt;p&gt;Happy interacting!s&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>Bio-GO-SHIP: The Time Is Right to Establish Global Repeat Sections of Ocean Biology</title>
      <link>https://alexanderlabwhoi.github.io/publication/clayton-2022-bio/</link>
      <pubDate>Sat, 01 Jan 2022 00:00:00 -0500</pubDate>
      
      <guid>https://alexanderlabwhoi.github.io/publication/clayton-2022-bio/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Marine microeukaryote metatranscriptomics: sample processing and bioinformatic workflow recommendations for ecological applications</title>
      <link>https://alexanderlabwhoi.github.io/publication/cohen-2022-marine/</link>
      <pubDate>Sat, 01 Jan 2022 00:00:00 -0500</pubDate>
      
      <guid>https://alexanderlabwhoi.github.io/publication/cohen-2022-marine/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Microbiomes of bloom-forming Phaeocystis algae are stable and consistently recruited, with both symbiotic and opportunistic modes</title>
      <link>https://alexanderlabwhoi.github.io/publication/mars-2022-microbiomes/</link>
      <pubDate>Sat, 01 Jan 2022 00:00:00 -0500</pubDate>
      
      <guid>https://alexanderlabwhoi.github.io/publication/mars-2022-microbiomes/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Bio-GO-SHIP: Linking marine biodiversity and biogeochemistry</title>
      <link>https://alexanderlabwhoi.github.io/project/biogoship/</link>
      <pubDate>Fri, 02 Jul 2021 15:15:49 -0400</pubDate>
      
      <guid>https://alexanderlabwhoi.github.io/project/biogoship/</guid>
      <description>&lt;p&gt;The &lt;a href=&#34;http://biogoship.org/&#34; target=&#34;_blank&#34;&gt;Bio-GO-SHIP&lt;/a&gt; program aims to integrate the latest biological observing technologies into the Global Ocean Ship-based Hydrographic Investigation Program (GO-SHIP, &lt;a href=&#34;http://go-ship.org/&#34; target=&#34;_blank&#34;&gt;http://go-ship.org/&lt;/a&gt;). GO-SHIP runs a global repeat-section effort, wherein reference sections that transect major ocean regions are sampled every decade to observe global changes. Bio-GO-SHIP measurements will include optical, flow cytometric, metagenomic and metatranscriptomic, and particulate sampling. Compared to previous global ocean sequencing efforts, Bio-GO-SHIP will sample biological parameters at high spatial and vertical resolution, with ‘omic samples being taken approximately every degree, or approximately 26.5km on average between samples. My group is focused on the collection, sequencing, and preliminary assembly data product curation of the ‘omic dataset in conjunction with Adam Martiny’s lab&amp;ndash; with my lab taking the lead on the eukaryotic component.&lt;/p&gt;

&lt;p&gt;&lt;em&gt;Funding for this project provided by NOAA and the Simons Foundation&lt;/em&gt;&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>EUKulele: Taxonomic annotation</title>
      <link>https://alexanderlabwhoi.github.io/project/eukulele/</link>
      <pubDate>Fri, 02 Jul 2021 15:15:49 -0400</pubDate>
      
      <guid>https://alexanderlabwhoi.github.io/project/eukulele/</guid>
      <description>&lt;p&gt;Easy, accurate classification of the taxonomy of microbial eukaryotes in the environment is a persistent challenge. For metagenomic and metatranscriptomic data, annotation is imperfect, because genomic references for organisms isolated from the environment are lacking. By leveraging experimental transcriptomic references, we have designed a tool to estimate the taxonomy of marine microbial eukaryotes. The tool is a flexible and modular way to leverage the expanding amount of omics data on environmentally-isolated microbial eukaryotes in order to better annotate multi-organism omics datasets (meta-omics). The freely-available tool is implemented as a Python package and installable via both &lt;code&gt;pip&lt;/code&gt; and &lt;code&gt;conda&lt;/code&gt;.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Project Repository&lt;/strong&gt;: &lt;a href=&#34;https://github.com/AlexanderLabWHOI/eukulele&#34; target=&#34;_blank&#34;&gt;https://github.com/AlexanderLabWHOI/eukulele&lt;/a&gt;&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>Ecological Role of Eukaryotic Pangenomes</title>
      <link>https://alexanderlabwhoi.github.io/project/ehuxleyi/</link>
      <pubDate>Fri, 02 Jul 2021 15:15:49 -0400</pubDate>
      
      <guid>https://alexanderlabwhoi.github.io/project/ehuxleyi/</guid>
      <description>&lt;p&gt;Coccolithophores, a group of calcifying marine phytoplankton within the phylum Haptophyta, play a significant role in marine biogeochemical cycles, particularly in those of carbon and sulfur. &lt;em&gt;Emiliania huxleyi&lt;/em&gt; is one of the most abundant extant coccolithophore species in the ocean, typified by its cosmopolitan distribution and ability to form large blooms. Intra-specific variability in physiology (e.g. enzymatic rates, morphology, growth rates) of &lt;em&gt;E. huxleyi&lt;/em&gt; has long been known in cultured isolates. The capacity for this variability was revealed through the genome sequencing of many &lt;em&gt;E. huxleyi&lt;/em&gt; strains, the results of which suggested that &lt;em&gt;E. huxleyi&lt;/em&gt; has a ‘pan genome,’ with gene content varying across strains. Intensive study of another ecologically significant taxa with a pan genome, the cyanobacteria &lt;em&gt;Prochlorococcus&lt;/em&gt;, has connected the variability of the pan genome to its niche separation and biogeographical distribution. Similar to &lt;em&gt;Prochlorococcus&lt;/em&gt;, intra-specific genomic variability may underpin the success of &lt;em&gt;E. huxleyi&lt;/em&gt; across diverse environmental conditions and underlie its observed physiological variability. Here we are combining a series of genomic, computational field surveys, and laboratory-based experiments designed to identify the function of the pan genome in &lt;em&gt;E. huxleyi&lt;/em&gt; ecology and biogeography. Through this project, we will address the questions:&lt;/p&gt;

&lt;ol&gt;
&lt;li&gt;Is there structure to the variable gene content across strains in the pan genome of &lt;em&gt;E. huxleyi&lt;/em&gt;?&lt;/li&gt;
&lt;li&gt;Does the environment select for particular strains of &lt;em&gt;E. huxleyi&lt;/em&gt; based on the content of the variable portion of the pan genome?&lt;/li&gt;
&lt;li&gt;Does the composition of the variable gene set determine strain success under shifting environmental conditions?&lt;/li&gt;
&lt;/ol&gt;

&lt;p&gt;&lt;em&gt;Funding for this project provided by the National Science Foundation&lt;/em&gt;&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>EukHeist: Recovering Eukaryotic MAGs from Metagenomes</title>
      <link>https://alexanderlabwhoi.github.io/project/eukheist/</link>
      <pubDate>Fri, 02 Jul 2021 15:15:49 -0400</pubDate>
      
      <guid>https://alexanderlabwhoi.github.io/project/eukheist/</guid>
      <description>&lt;p&gt;Eukaryotic microbes, or protists, are key drivers of marine ecosystems, with roles ranging from primary producers (phytoplankton) to consumers (heterotrophs or mixotrophs). As with their bacteria and archaea, many protists are difficult or impossible to culture. This has limited our ability to directly interrogate their biology in the laboratory and has led us to underestimate their diversity across marine ecosystems. Molecular and genomic approaches, particularly those applied to whole, mixed communities (e.g. metagenomics, metatranscriptomics), have shed light on the ecological roles, evolutionary histories, and physiological capabilities of these organisms.&lt;/p&gt;

&lt;p&gt;EukHeist presents a scalable and reproducible bioinformatic pipeline to facilitate the retrieval of eukaryotic metagenome assembled genomes (MAGs) from mixed metagenomes, called EUKHeist (&lt;a href=&#34;https://github.com/AlexanderLabWHOI/EUKHeist&#34; target=&#34;_blank&#34;&gt;https://github.com/AlexanderLabWHOI/EUKHeist&lt;/a&gt;). EUKHeist streamlines and automates the discovery, recovery, quality assessment, and analysis of eukaryotic metagenome assembled genomes (MAGs) from mixed community metagenomes. EukHeist incorporates taxonoßßmic annotation through EUKulele (&lt;a href=&#34;https://github.com/AlexanderLabWHOI/EUKulele&#34; target=&#34;_blank&#34;&gt;https://github.com/AlexanderLabWHOI/EUKulele&lt;/a&gt;) as well as scalable structural and functional annotation of coding regions in eukaryotic MAGs with EukMetaSanity (&lt;a href=&#34;https://github.com/cjneely10/EukMetaSanity&#34; target=&#34;_blank&#34;&gt;https://github.com/cjneely10/EukMetaSanity&lt;/a&gt;).&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Project repository:&lt;/strong&gt; &lt;a href=&#34;https://github.com/AlexanderLabWHOI/EUKHeist&#34; target=&#34;_blank&#34;&gt;https://github.com/AlexanderLabWHOI/EUKHeist&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;&lt;em&gt;Funding for this project provided by the Simons Foundation and WHOI&lt;/em&gt;&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>Phaeocystis</title>
      <link>https://alexanderlabwhoi.github.io/project/phaeocystis/</link>
      <pubDate>Fri, 02 Jul 2021 15:15:49 -0400</pubDate>
      
      <guid>https://alexanderlabwhoi.github.io/project/phaeocystis/</guid>
      <description>&lt;p&gt;Phytoplankton blooms are central to the ecology of Cape Cod Bay, where historically spring blooms of diatoms have been rapidly grazed, shuttling biomass through the food web. In more recent years, blooms of a haptophyte, &lt;em&gt;Phaeocystis pouchetii&lt;/em&gt; have become more frequent in Cape Cod Bay. These organisms produce large gelatinous colonies, which prevents blooms of this haptophyte from being effectively grazed, hence reducing carbon cycling in the upper water column. We are partnering with the Center for Coastal Studies in Provincetown to find and study these blooms.&lt;/p&gt;

&lt;p&gt;&lt;em&gt;Funding from the Simons Foundation&lt;/em&gt;&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>SeqWell for Marine Microbes</title>
      <link>https://alexanderlabwhoi.github.io/project/seqwell/</link>
      <pubDate>Fri, 02 Jul 2021 15:15:49 -0400</pubDate>
      
      <guid>https://alexanderlabwhoi.github.io/project/seqwell/</guid>
      <description>&lt;p&gt;A central project aim is adaptation of a new single cell transcriptome (SCT) sequencing approach called &lt;a href=&#34;https://shaleklab.com/publication/seq-well-portable-low-cost-rna-sequencing-of-single-cells-at-high-throughput/&#34; target=&#34;_blank&#34;&gt;SeqWell&lt;/a&gt; for analysis of natural microbial communities. The method addresses two overarching obstacles to microbial symbiosis investigations: 1) the requirement that symbionts be brought into culture for ‘omics analyses, and 2) time resolution limits on bulk approaches because populations are asynchronous. With enough SCTs, pseudotime methods can establish the time course of host and symbiont interactions. SeqWell is a straightforward settling-chamber based system that can capture &amp;gt;10,000 SCTs in a single experiment. Compared to competing methods, it is also low-cost and readily adaptable for a broad range of protist shapes and sizes. We aim to address three major challenges inherent to scRNAseq of protist communities in the environment: 1) the morphological diversity (size/shapes) of protists across taxonomic groups; 2) cost; and 3) a need for bioinformatic pipelines that can analyze SCTs from natural microbial communities.&lt;/p&gt;

&lt;p&gt;&lt;em&gt;Funding for this project provided by the Moore Foundation&lt;/em&gt;&lt;/p&gt;
</description>
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