Entropy and complexity unveil the landscape of memes evolution
On the Internet, information circulates fast and widely, and the form of content adapts to comply with users’ cognitive abilities. Memes are an emerging aspect of the internet system of signification, and their visual schemes evolve by adapting to a heterogeneous context. A fundamental question is whether they present culturally and temporally transcendent characteristics in their organizing principles. In this work, we study the evolution of 2 million visual memes published on Reddit over ten years, from 2011 to 2020, in terms of their statistical complexity and entropy. A combination of a deep neural network and a clustering algorithm is used to group memes according to the underlying templates.
The grouping of memes is the cornerstone to trace the growth curve of these objects. We observe an exponential growth of the number of new created templates with a doubling time of approximately 6 months, and find that long-lasting templates are associated with strong early adoption. Notably, the creation of new memes is accompanied with an increased visual complexity of memes content, in a continuous effort to represent social trends and attitudes, that parallels a trend observed also in painting art.
Memes: A motif analysis environment in R using tools from the MEME Suite
Identification of biopolymer motifs represents a key step in the analysis of biological sequences. The MEME Suite is a widely used toolkit for comprehensive analysis of biopolymer motifs; however, these tools are poorly integrated within popular analysis frameworks like the R/Bioconductor project, creating barriers to their use. Here we present memes, an R package that provides a seamless R interface to a selection of popular MEME Suite tools. memes provides a novel “data aware” interface to these tools, enabling rapid and complex discriminative motif analysis workflows.
In addition to interfacing with popular MEME Suite tools, memes leverages existing R/Bioconductor data structures to store the multidimensional data returned by MEME Suite tools for rapid data access and manipulation. Finally, memes provides data visualization capabilities to facilitate communication of results. memes is available as a Bioconductor package at https://bioconductor.org/packages/memes, and the source code can be found at github.com/snystrom/memes.
Other ways of communicating the pandemic – memes and stickers against COVID-19: a systematic review
Background: In the midst of the coronavirus disease 2019 (COVID-19) pandemic, there are many ways to communicate hygiene measures, such as memes and stickers that are widely used on social networks. We carried out a systematic review in order to determine the impact of stickers and memes as tools to face the COVID-19 pandemic, following the PRISMA guide. Methods: The search was carried out in scientific databases (MEDLINE / PubMed, ScientiDirect, Scielo, LILACS, and Latindex), and in public pre-publication servers (bioRxiv, SocArXiv, medRxiv and Preprints). The publications were identified using the terms (((meme) OR (sticker)) AND ((COVID-19) OR (SARS-COV-2)) AND (WhatsApp)) and the corresponding translations for Spanish and Portuguese. Results: In the initial search, 8434 studies were obtained, 7749 in Preprints, 446 in SocArXiv, 145 in ScientDirect, 82 in medRxiv, and 12 in PubMed. No studies were found in LILACS, Latindex, Scielo, or bioRxiv. Of the 51 studies included as eligible, all were eliminated for not meeting the study inclusion criteria. The majority (40 studies) were eliminated as studies were publications related to the social aspects related to COVID-19, but did not develop an analysis of stickers or memes. Conclusions: No studies were identified that met the inclusion criteria related to the role of stickers and memes as tools to face the COVID-19 pandemic. More studies are needed to estimate its role as a means of communication in health.
Eliminating onchocerciasis within the Meme River Basin of Cameroon: A social-ecological approach to understanding everyday realities and health systems
Background: Onchocerciasis affects some of the world’s most marginalized people, perpetuating poverty and inequalities. Mass Drug Administration (MDA) with Ivermectin has taken place within the Meme River basin region in Cameroon for over 15 years. Despite this, onchocerciasis is still prevalent in the region due to existing and emerging contextual challenges. Using a social-ecological approach we explore the everyday realities of communities, highlighting the challenges and potential solutions that could support Neglected Tropical Disease (NTD) programmes when transitioning from control to elimination of onchocerciasis in this highly endemic area and other similar communities.
Methodology/principal finding: In-depth interviews (71) with community members and Community Drug Distributors (CDDs) were conducted to understand current knowledge, attitudes, and behaviours in relation to transmission, prevention and treatment of onchocerciasis. Through application of the social-ecological model, four key themes were identified: 1. Contextual factors on health promotion interventions (Onchocerciasis history and understanding of the disease, prevention and mitigation strategies and MDA experience); 2. Social determinants (poverty and livelihoods, economic and social impacts on CDD volunteers and stigma); 3. Environmental determinants (exposure, housing, occupation and poverty); and 4. health seeking pathways and decision making for treatment (access, cost and preferable treatment routes). We discuss these core and cross cutting themes (gender differences and community participation/ownership) in relation to intersectoral collaboration, gender equity and health systems support, making recommendations for NTD programmes within the context of integrated and interdisciplinary approaches. These include the need for; intersectional and gender analysis at the local level, addressing environmental dimensions of onchocerciasis through integrated and regular health promotion, vector control strategies and access to safe water sources; reflection and action that embeds responses to social and economic barriers to MDA; integrated case detection and management that is responsive to onchocerciasis symptoms and related stigma and a fair and just support network for CDDs.
Conclusion/significance: NTD programmes need to respond to diverse community circumstances and behaviours. Communities are not a homogeneous risk group and treating them in this way will delay elimination. A deeper understanding of individual needs and their capacity to seek prevention and treatment must be considered if onchocerciasis is to be eliminated and the remaining impacts managed.
NAP1L1 (Nucleosome Assembly Protein 1-like 1, NRP, NAP1, NAP1L) (AP) |
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NAP1L1 (Nucleosome Assembly Protein 1-like 1, NRP, NAP1, NAP1L) (AP) |
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NAP1L1 (Nucleosome Assembly Protein 1-like 1, NRP, NAP1, NAP1L) (PE) |
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MBS6428189-01mL | MyBiosource | 0.1mL | 950 EUR |
NAP1L1 (Nucleosome Assembly Protein 1-like 1, NRP, NAP1, NAP1L) (PE) |
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NAP1L1 (Nucleosome Assembly Protein 1-like 1, NRP, NAP1, NAP1L) (APC) |
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NAP1L1 (Nucleosome Assembly Protein 1-like 1, NRP, NAP1, NAP1L) (APC) |
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MBS6428180-5x01mL | MyBiosource | 5x0.1mL | 4120 EUR |
NAP1L1 (Nucleosome Assembly Protein 1-like 1, NRP, NAP1, NAP1L) (HRP) |
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NAP1L1 (Nucleosome Assembly Protein 1-like 1, NRP, NAP1, NAP1L) (HRP) |
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MBS6428183-5x01mL | MyBiosource | 5x0.1mL | 4120 EUR |
NAP1L1 (Nucleosome Assembly Protein 1-like 1, NRP, NAP1, NAP1L) (FITC) |
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NAP1L1 (Nucleosome Assembly Protein 1-like 1, NRP, NAP1, NAP1L) (Biotin) |
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NAP1L1 (Nucleosome Assembly Protein 1-like 1, NRP, NAP1, NAP1L) (Biotin) |
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NAPSA, CT (NAPSA, NAP1, NAPA, Napsin-A, Aspartyl protease 4, Napsin-1, TA01/TA02) (AP) |
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NAPSA, CT (NAPSA, NAP1, NAPA, Napsin-A, Aspartyl protease 4, Napsin-1, TA01/TA02) (AP) |
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NAPSA, CT (NAPSA, NAP1, NAPA, Napsin-A, Aspartyl protease 4, Napsin-1, TA01/TA02) (PE) |
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Structure memes: Intuitive visualization of sequence logo and subfamily logo information in a 3D protein-structural context
The number of available protein sequences covering virtually all known species is tremendous and ever growing due to the feasibility of the underlying nucleotide sequencing. The speed at which protein structures are being determined is increasing, and as a result of refined cryo-electron microscopy the proportion of solved membrane protein folds is expanding. Sequence data are used to illustrate evolution and to group proteins into families with various levels of subfamilies. Structure data of prototypical proteins provide insight into function brought about by an interplay of specific amino acid residues that are dispersed throughout the sequence.
Visually combining rich sequence information with structure data in an intuitively comprehensible way would enhance the process of elucidating key protein aspects regarding evolution, sequence relations, and function. Here, a method is described that projects the information contained in sequence logos and subfamily logos onto protein structures. The amino acid composition at a site is encoded by a mix color in the red-yellow-blue (RYB) space and the information content is presented by the radius of a sphere at the α-carbon position. The resulting display is termed “structure meme”. The underlying sequence and atom coordinate data are retained in the file for simple retrieval on demand using a molecular structure visualization program. Structure memes are recognizable and convey extensive information in a human-discernable way that requires little training.