A Chromosome-Centric Analysis of Antibodies Directed toward the

Article pubs.acs.org/jpr

A Chromosome-Centric Analysis of Antibodies Directed toward the Human Proteome Using Antibodypedia Tove Alm,† Kalle von Feilitzen,† Emma Lundberg,† Åsa Sivertsson,† and Mathias Uhlén*,†,‡ †

Science for Life Laboratory, KTHRoyal Institute of Technology, SE-171 21 Stockholm, Sweden Department of Proteomics, KTHRoyal Institute of Technology, SE-10 91 Stockholm, Sweden

‡

ABSTRACT: Antibodies are crucial for the study of human proteins and have been defined as one of the three pillars in the human chromosome-centric Human Proteome Project (CHPP). In this article the chromosome-centric structure has been used to analyze the availability of antibodies as judged by the presence within the portal Antibodypedia, a database designed to allow comparisons and scoring of publicly available antibodies toward human protein targets. This public database displays antibody data from more than one million antibodies toward human protein targets. A summary of the content in this knowledge resource reveals that there exist more than 10 antibodies to over 70% of all the putative human genes, evenly distributed over the 24 human chromosomes. The analysis also shows that at present, less than 10% of the putative human protein-coding genes (n = 1882) predicted from the genome sequence lack antibodies, suggesting that focused efforts from the antibody-based and mass spectrometry-based proteomic communities should be encouraged to pursue the analysis of these missing proteins. We show that Antibodypedia may be used to track the development of available and validated antibodies to the individual chromosomes, and thus the database is an attractive tool to identify proteins with no or few antibodies yet generated. KEYWORDS: Human proteome, Affinity reagents, Antibodies, Antibodypedia

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and the Human Protein Atlas (HPA, www.proteinatlas.org).4 Antibodypedia is a searchable database cataloging antibodies against human gene products. The HPA is a knowledge-based virtual repository comprising information and images of well annotated antibodies against the human proteome. Within the project, the antibodies have been systematically generated and are validated for specificity and used for exploration of protein localization and expression using a multitude of tissues and cells. The two parts of HAI, i.e., Antibodypedia and HPA, are working together to promote and facilitate the use of antibodies in research. HUPO’s most recent initiative is the Human Proteome Project (HPP, www.thehpp.org), which had its working plan launched in 2010.5 HPP collaborates with the other HUPO initiatives (such as HAI) and is a worldwide cooperation to finalize the human proteome using a gene-centric approach.6 The HPP is built on a foundation of three pillars: mass spectrometry (MS), antibodies (Abs), and the knowledgebase (KB). The mass spectrometry pillar has decided to make proteotypic peptides for every human protein. A reference spectra is made for each peptide, and these serve as positive controls.7,8 For the antibody pillar, the HPA is working on the production of at least one antibody against a representative gene product for every human gene.4,9 The knowledgebase pillar is a database gathering information on human proteins

INTRODUCTION The proteomic landscape of the human body is being revealed, visualized, and explored through the use of antibodies, complementing mass spectrometry-based analysis. For some years, antibodies have been used to characterize the human proteome, as well as to discover potential protein biomarkers in clinical proteomic efforts. Antibodies can be used in numerous applications, on a wide range of samples and biological contexts, demanding great versatility of an antibody for it to be functional in each setting. However, most antibodies lack validation results across various applications, which often makes it necessary to perform cumbersome investigations to ensure specificity of a particular antibody before initiating a study.1 In 2008, a validation study using Western blot and immunohistochemistry to analyze more than 5000 commercially available antibodies from 51 different antibody providers showed that the average success rate was 49%.2 It became evident that a standardized system for sharing antibody validation data about publicly available antibodies was needed. The Human Proteome Organization (HUPO, www.hupo. org), which was launched in 2001, is an international organization promoting the development of new technologies, techniques, and training within the area of proteomics.3 Several initiatives have been launched by HUPO, all with a focus on proteomics and international collaborations. One of these initiatives is the Human Antibody Initiative (HAI, www.hupo. org/initiatives/human-antibody-initiative). HAI is structured into two activities: Antibodypedia (www.antibodypedia.com) © 2014 American Chemical Society

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Figure 1. (a) Principle for search and identify on Antibodypedia. A search on the first page of Antibodypedia (www.antibodypedia.com) returns a list with associated gene products for the search, here displaying four out of 16 gene products for the search EGFR. Details about the gene are presented: gene name and synonyms, description of the gene product, protein family, chromosome location, UniProt id,19 mouse ortholog, and number of antibodies and providers catalogued in Antibodypedia. (b) Principle for compare and select on Antibodypedia. Identifying and selecting the correct gene product from the list generated in (a) loads the summary page listing all antibodies from all providers, in this case 2468 anti-EGFR antibodies from 27 providers. The table on this page gives information about the type of antibody, the number of citations, and if the antibody is validated for a certain application (clearly displayed using partially or fully filled green circles), here displaying three different providers. In order to show additional information, such as host and reactivity, and to select which applications to display in the table, use the Show Additional Columns tab in the top right corner. The antibodies and providers are listed in an order determined by a score that is based on available primary data and citations. The filters on the left side allow refinement of the results. Interesting antibodies may be selected using the checkbox to the left of the antibody name, and crosscompared using the Compare Selected function in the top left corner.

structure the proteomic data and promote collaborations.14 The initiative is structured on chromosome-level, and every chromosome is curated by country-defined teams with the goal to identify at least one representative protein for every human gene.12,15 The C-HPP is thus divided into 25 projects, one for each chromosome including mitochondria, where every chromosome is “adopted” by a country, and the focus is on exploring the complete human proteome with a gene-centric approach. Antibodypedia is a searchable database containing annotated and scored affinity reagents generated by commercial or

such as HPP generated data, disease-related information, chromosomal location, number of annotated variants, splice isoforms and post-translational modifications, and existence of a 3D structure.10,11 To span all aspects of the human proteome, the HPP has defined two orthogonal groups on top of the three pillars: Biology/Disease Human Proteome Project (B/D-HPP, www.thehpp.org/BD-HPP.php) and Chromosome-based Human Proteome Project (C-HPP, www.c-hpp.org).12,13 The B/D-HPP explores the human proteome using biology-driven and disease-focused research, and the number of possible subprojects is almost infinite. The C-HPP is an effort to 1670

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explore. When searching for an antibody, a simple search using the gene name on Antibodypedia’s first page will generate a list of gene products as shown in Figure 1a. By using the Advanced Search function and selecting AND or NOT, it is possible to limit the search to, or exclude, a certain protein family or chromosome. This is particularly useful when searching for a gene product with recurring names. A list of all gene products in Antibodypedia with corresponding antibodies, if applicable, may be generated by generating a blank search. The genecentric structure of Antibodypedia returns a list organized by target proteins. Search results where a specific gene product is queried are sorted by relevance. The Antibodypedia algorithm takes into account names, synonyms, and descriptions of genes encoding the queried antigen, along with other terms, to determine the position in which an antigen result is displayed. A blank search, or parameter-based search (e.g., “protein_ family”:“Transcription factors”), displays the result in alphabetical order. The list gives the name of the gene product, including synonyms, and a description of the gene product, its protein family (e.g., enzymes, or kinases, etc.), chromosome location, UniProt id,19 and the name of the mouse ortholog, if available. In addition, the number of antibodies listed in Antibodypedia against each gene product and the number of providers are displayed. Clicking on the protein of interest will load a separate summary page, listing available antibodies including data regarding references and/or experimental data for individual applications (Figure 1b). The summary page also provides detailed gene product information and direct links to RefSeq, Ensembl, UniProt, and Entrez (not shown in Figure 1b). Antibody results are grouped by provider and ordered according to the quantity and nature of the citation and application data available. The search results display the commercial antibody name, number of relevant references, type of antibody, and a graphical overview of recommended and validated applications. The graphical overview can be altered by selecting Show additional columns. In total, 16 different applications are represented on Antibodypedia and used for antibody scoring. To further refine the antibody list, advanced filtering options can be used, e.g., restricting the listing to antibodies recommended for a certain application, presence of reference, a certain provider, host, antibody type/ clonality, or reactivity to a certain species. Checkboxes to the left of each antibody listing permit cross-comparison of their attributes. Antibodies can also be investigated in depth by clicking within each listing; this will load a dedicated page detailing the reagent’s reactivity, direct linking to provider product page, and any associated data and references. By switching the tabs on the left-hand side of this page, the publication list can be reviewed, and each publication is directly linked to PubMed for easy access. From this page, it is also possible to submit validation data, references, and comments by the community users.

academic providers. It allows antibody providers, as well as users, to contribute and edit experimental evidence data, including data on the antigen. The database aims at providing the research community with information to simplify the selection of antibodies tailored for specific biological settings and biomedical assays. Antibodies listed in the database may be compared using the submitted validation data. Antibodypedia is gene-centric in the sense that it is structured around human genes as defined by Ensembl;16,17 that is, all antibodies deposited in the database are directed against the product of a particular gene. The first version of Antibodypedia was released in 2008, containing information covering approximately 3900 antibodies and including four validation categories.18 Since then, several existing proteomic initiatives have continued to constantly evolve, and new ones have been initiated. The Human Protein Atlas initiative4,9 had its first release in 2005 with just over 700 antibodies. Today the HPA holds information on 21 984 antibodies against 16 621 human gene products. Another resource is NeXtProt (www.nextprot.org), which had its first release in 2011. NeXtProt provides a complete and curated mapping of the human proteins, integrating protein-related data from multiple sources.11 Like the field of proteomics, the Antibodypedia portal has progressed both in scope and content, and this article reports the status of Antibodypedia with focus on the availability of antibodies to the C-HPP.

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EXPERIMENTAL SECTION For software development of the Antibodypedia web portal, the standard open source web development tools from the LAMP concept (Linux, Apache, MySQL, and PHP) were used. A template-based design has been used to build the Antibodypedia database. This design allows selection of certain antibody parameters from the entire set of antibody parameters to create a specific antibody type. For validation data, the same model was used to create a specific validation type. The flexibility of the database model enables the addition or modification of sets of parameters, allowing future changes to be easily implemented. The web portal has three interfaces, one for each user group: antibody providers, internal reviewers, and the public part for end users. The public part of the web portal is open, meaning that no password is needed to use Antibodypedia. However, providers and reviewers need to sign in to the portal using their account before adding or modifying existing antibodies (providers) or reviewing antibodies (reviewers). Antibody provider accounts grant access to the part of the Antibodypedia portal where new antibodies may be submitted and previously submitted antibodies may be modified or enriched with more validation data. Internal reviewer accounts grant access to the part of the web portal where newly submitted or modified antibodies are reviewed. After the provider has submitted the antibodies, the antibodies and accompanying validation data will be reviewed to verify concordance with the standard of the Antibodypedia web portal. Thereafter, if the submission appears correct, the antibodies will be publicly available on Antibodypedia.

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The Antibodypedia Ranking System

One of the most important missions of the Antibodypedia site is to guide users of antibodies to select an antibody with high reliability. A new system for scoring of reliability has been developed on the basis of the availability of references in the literature on the use of a particular antibody, and the availability of experimental data in the portal to allow users to explore the use of the antibody for various applications. The reference citation weight is applied to the antibody as a whole, whereas

RESULTS

Search, Identify, Compare, and Select Antibodies to Be Explored

A new interface of the Antibodypedia portal was developed with three main functions; (i) search, (ii) identify, and (iii) 1671

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Number of Antibodies, Experimental Data, and References in Antibodypedia

the antibody receives a separate score in each application; the cumulative score is determined by summing all applicationspecific scores, together with the separate score based on an antibody’s literature citations. There are four distinct application scores: the top score is Supportive data in Antibodypedia, which is graphically represented with a full green circle, and the value is equal to 1; the second highest is Data presented on Provider Web site, which is represented with three-quarters of a circle, and the value is equal to 0.75; the third score is Data in Antibodypedia (inconclusive), which is represented with half a circle, and the value is equal to 0.5; the bottom score is Recommended by Provider (no primary data presented), which is represented with a quarter of a circle, and the value is equal to 0.25. All validations submitted to Antibodypedia must include an image and experimental details. In addition, the image must be filed as conclusive or inconclusive. Antibodypedia provides validation-specific guidelines to facilitate the distinction between conclusive and inconclusive results. The antibody validation guidlines are given under the Learn tab, in the section Validate an antibody under Validation Criteria. The citation score has six intervals: 1 citation, 2−3 citations, 4−10 citations, 11−20 citations, 21−50 citations, and >50 citations; the weight of the scores are 1, 2, 3, 4, 5, and 6, respectively. The weights of the application and citation scores are available in Table 1. These scores then

The first version of Antibodypedia was released in 2008, cataloging 3900 antibodies and supporting four research applications for validation (Protein Array, Western Blot, Immunohistochemistry, and Immunofluorescence). Since the first release, the Antibodypedia database has evolved and grown organically. In November 2011, approximately 100 000 antibodies were listed in Antibodypedia (Figure 2a). Less than a year later, more than half a million antibodies were cataloged, and in the current version, the number of antibodies in the Antibodypedia database have passed one million, covering approximately 91% of the human genome. Although the number of antibodies almost doubled in the past year, it should be noted that in many cases, the same original antibody is made available through different providers and thus can appear as more than one entry in the portal. An essential mission of Antibodypedia is to provide experimental verification of antibody functionality in a particular immuno-application. Therefore, providers and users are requested to submit primary data on their antibodies to the portal, which can then be visualized and compared to other antibodies against the same protein target. Figure 2b shows the number of images with experimental data available in Antibodypedia in recent years. In November 2011, there were approximately 30 000 experiments accessible in the portal, and this number was increased to 145 000 in September 2012, and even further increased to 457 000 in October 2013. An important validation criterion for many scientists is the availability of publications showing the use of a particular antibody. As a response to this, Antibodypedia has improved the ranking of antibodies and providers in terms of reported references. The possibility to add references in Antibodypedia was first implemented in version 5 (released in April 2010), and since then, the number of references has increase from 1480 listed references in November 2011, to 32 000 references in September 2012, and to more than 115 000 references in October 2013 (Figure 2c).

Table 1. Scoring Criteria for the Antibodiesa validation

weight

supportive data in Antibodypedia (per application) supportive data on provider Web site (per application) non-supportive data presented in Antibodypedia (per application) recommended by provider, no data available in Antibodypedia (per application) (no validation) citation weight

1 0.75 0.5 0.25

1 citation (per antibody) 2−3 citations (per antibody) 4−10 citations (per antibody) 11−20 citations (per antibody) 21−50 citations (per antibody) >50 citations (per antibody) (no references)

0

1 2 3 4 5 6 0

Comparison of Different Antibodies to the Same Protein Target

It is important to be able to compare the antibodies in a search result in order to make an enlightened selection. To distinguish the right antibody, and to be able to find antibody pairs, it is invaluable to have a function for cross-comparison. Therefore, a new function for comparing the results for different antibodies in an application-specific manner has been developed. A search for the gene ERBB2,20 a well-known gene associated with many types of cancer, returns 1209 antibodies from 26 providers. Checkboxes to the left of each listed antibody permit crosscomparison of their attributes. From the result page for ERBB2, three antibodies are selected for comparison. To be easily compared, the selected antibodies are displayed side by side with all provided information (Figure 3). The validation scoring, visualized by green circles, gives a quick overview of the primary data present for every application and has four intervals. Refer to Table 1 for the weight of the scores. In addition, a link to the supplier product page is provided. For ERBB2, the antigen data indicate that Antibody A and Antibody C are the same. However, without expanding the Applications section, the application scoring system indicates that the different antibodies are recommended for different applications, which could indicate three unique antibodies.

a

Antibodies are scored on the basis of validation and citation criteria. Each application is independently scored according to a specific weight system, and the sum of all application scores is added to the citation score. The resulting score determines the antibody’s rank. The table describes the weight of the validation scores and the weight of the citation scores.

determine the order in which both the providers and the antibodies are listed for any antigen. If two independent providers list antibodies with identical scores, the score of the second-most-efficacious antibody is taken into account, and so on, until rank is established (similar to the “Alternative vote” system). The number of citations present in Antibodypedia for each antibody is displayed on the summary page, and the weight of the application score is clearly displayed in the application columns as a green circle filled by one or more quarters depending on the nature of the validation data (Figure 1b). All together, the maximum total score an antibody may receive is 22. 1672

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Figure 2. Antibodypedia in numbers. Graphs a, b, and c show the yearly progress of Antibodypedia from November 2011 to October 2013. Numbers are in thousands: (a) the organic growth of Antibodypedia in terms of listed antibodies, (b) number of uploaded images, (c) number of uploaded references.

Figure 3. Comparison of primary data for selected antibodies. The cross-compare function is a powerful tool to elucidate redundant antibodies. Antibodies with applications that are displayed with a full green circle have primary data presented in Antibodypedia, and these applications are cross-compared in this view for antibody A, B, and C. Primary data images for the antibodies are displayed side by side: Western blot (WB), ELISA (E), immunocytochemistry (ICC), immunohistochemistry (IHC), flow cytometry (FC), and proximity ligation assay (PLA).

Analysis of Antibodies Available to the Various Human Chromosomes

Expanding the Application section shows all images for the applications represented by a full green circle: Western blot (WB), ELISA (E), immunocytochemistry (ICC), immunohistochemistry (IHC), flow cytometry (FC), and proximity ligation assay (PLA). The WB images and IHC images (three images in random order) are identical for two of the selected antibodies, supporting that Antibody A and Antibody C in the comparison are the same. On the contrary, validation data for Antibody B indicate that this antibody is unique from the other two.

Even though a vast number of antibodies are available on the market, there are still gene products not targeted by any antibodies. Antibodypedia data, extracted on a chromosomespecific level, gives an overview of the human genome showing a proportionally even distribution of antibodies to the gene products on every chromosome (Figure 4a). Chromosome 3 is closest to completion with a 95% coverage, and Chromosome 10, 6, and 2 follow with 93% coverage, respectively. The completion of the Y chromosome is only 65%. Nevertheless, Chromosome Y is the smallest chromosome with only 62 1673

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Figure 4. Chromosome-specific overview of gene and antibody details. (a) The antibody coverage of the human genome is graphically displayed on chromosome level. The full height of the bar represents the total number of genes on each chromosome. The green bars represent all genes targeted by at least one antibody, whereas the red bars represent the genes yet to be targeted with antibodies. (b) The antibody coverage across the human genome on chromosome level is grouped into three distinct intervals: highly targeted genes, moderately targeted genes, and untargeted genes. Dark green bars represent genes covered with 10 or more antibodies, green bars represent genes with single digit number of targeting antibodies, and red bars represent untargeted genes. The three categories are normalized against each other and sum up to 100% for each chromosome. (c) The antibodies in Antibodypedia may be divided into two distinct types: monoclonal and polyclonal antibodies. In this graph, the relationship of monoclonal (dark green bars) versus polyclonal (green bars) antibodies in Antibodypedia is graphically displayed on chromosome level.

The antibodies in Antibodypedia may be divided into two distinct types: monoclonal and polyclonal antibodies. Both variants have their advantages and disadvantages.21 Of the antibodies present in Antibodypedia, approximately one-third are monoclonal antibodies, and two-thirds are polyclonal antibodies (Figure 4c). When extracting the data on chromosome level, the percentage of monoclonal antibodies as compared to polyclonal antibodies ranges from 20 to 30% across the chromosomes, with an average of 27%.

genes, and thus there are only 22 untargeted gene products. In this perspective, looking at absolute numbers, Chromosome 19 is the least complete with 163 untargeted genes, closely followed by Chromosome 1 with 158 untargeted genes. As a summary, the average coverage of the human genome is 91%, with a total of 1882 genes yet to be addressed. To further structure the data, three distinct intervals are defined (Figure 4b): gene products targeted by 10 or more antibodies (deep green bars); gene products targeted with single digit number of antibodies (green bars); gene targets with no targeting antibodies (red bars). It becomes evident that many antibodies target the very same gene products. With a quite even distribution across the chromosomes, about 9% (1882 genes) of the gene products are still not targeted by an antibody, approximately 19% are covered with a single digit number of antibodies, and the remaining 72% of all the genes are linked to 10 or more antibodies.

Missing Proteins

While 9% of the human protein-coding genes lack antibodies targeting any gene product, there is a high redundancy in antibodies against certain proteins (Figure 5). The top five most frequently targeted proteins are EGFR, TP53, PTPRC, CD4, and AKT1, with 2468, 2233, 2168, 1661, and 1438 targeting antibodies, respectively. This redundancy should in some way be clearly visualized to the antibody users, and providers should be encouraged to include epitope or sequence 1674

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Figure 5. Gene-focused overview of antibodies covering the human genome. This graph displays the number of genes targeted by a specific number of antibodies. The genes are grouped into sets defined by number of antibodies targeting the gene; one gene-group per each single digit, followed by one group for genes targeted by 10−20 antibodies (Abs), 21−30, 31−40, 41−50, 51−100, 101−1000, and 1001−2468 Abs.

the approximately 5800 gene products with 0−9 available antibodies. It has been stated that 75% of the protein research focuses on the 10% of the human genome that was known before the human genome was completed, and that the research focus is where well-characterized probes are available.22 Since the purity and the concentration of the target protein may vary between applications, specific validation of each application is important. Still, antibodies do fail in the researchers’ experiment. The reasons may be many, such as batch to batch variation of the produced antibody or the biological environment may be different from the milieu where the antibody was tested. Because of the fact that most proteins are present in every tissue, and that the specificity of the tissue is determined by the local protein concentration, the validation of antibodies across various applications is even more essential.23−25 Therefore, an active research community, sharing both conclusive and inconclusive data, should be encouraged to fully cover the proteomic landscape.

details. Apart from the untargeted gene products, there are approximately 3900 gene products with single digit number of targeting antibodies, and it is interesting to target these two groups of gene products to obtain more independent antibodies against the corresponding protein targets.

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DISCUSSION Antibodypedia is a curated, searchable database of antibodies against human proteins. The database aims at providing the research community with information on the effectiveness of specific antibodies in specific applications. The open access of Antibodypedia allows full usability of the data in the portal; no password is required, and the database is completely free of charge. Since the launch in 2008, eight versions have been released, and in its current version special emphasis is put on validation and reference citations to support the antibodies available in the database. The validations and reference citations are the corner stones in the quality assessment and scoring of the antibodies. Academic and commercial providers, as well as users, are encouraged to include and submit data on the antibodies; both conclusive and inconclusive data is accepted. The gene-centric structure allows all antibodies linked to a certain gene to be displayed on the same page, and a direct link to the antibody provider page allows easy access of the antibody. In the current version of Antibodypedia, the portal catalogs annotated and scored affinity reagents against 91% of the human genome. Among the remaining gene products there may be difficult targets; still, full coverage of the human proteome is expected within the next two years. In the near future, Antibodypedia will continue its efforts to include more providers. In the longer perspective, the usability of the database will be in focus. Focusing on the feedback from the user community, future updates could include the addition of new functions and filters, such as the possibility to easily find antibody pairs or improving the quality control of the added data. With less than 10% of the human genome remaining to be covered with at least one antibody, joint efforts from the antibody-based and mass spectrometry-based proteomic communities should be encouraged to allow the analysis of the missing proteins. Future efforts should therefore focus on

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: +46 8 5537 8325. Fax: +46 8 5537 8482. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We acknowledge the entire staff of the Human Protein Atlas program and the Science for Life Laboratory for valuable contributions. Funding was provided by the Knut and Alice Wallenberg Foundation and Affinomics, a Seventh Framework Grant by the European Directorate.

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REFERENCES

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