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Books | Ivan Coyote
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Ivan Coyote | Writer, storyteller & performer·2016
Ivan Coyote is the award-winning author of thirteen books. Care Of, Rebent Sinner, Tomboy Survival Guide, Gender Failure, and more.
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View paper →Streptocyclin BTW is a novel member of a diverse family of circular bacteriocins in the genus <i>Streptococcus</i>
Felipe Miceli de Farias, David Hourigan, Paula M. O'Connor, Colin Hill, Reynolds Paul Ross
Molecular Nutrition & Food Research·2025
<jats:title>ABSTRACT</jats:title>
<jats:p>
Members of the genus
<jats:italic>Streptococcus</jats:italic>
are gram‐positive bacteria, commonly found in humans and animals. This group of microorganisms has been associated with severe infections and the development of resistance to antibiotics and production of bacteriocins. Many class I bacteriocins, especially lanthipeptides, have been described for streptococci; however, only one circular bacteriocin has been described for the group (uberolysin). The objective of this study was to characterize streptocyclin BTW, a 64 amino acid circular bacteriocin produced by
<jats:italic>Streptococcus devriesei</jats:italic>
DSM 19639, as well as to assess the diversity of circular bacteriocins within the genus. Streptocyclin BTW displayed a broad inhibitory spectrum with pronounced activity against strains of streptococci. A colony mass spectrum of the strain revealed a 6118.75 Da mass, which matches the predicted mass from sequencing. The gene cluster is composed of five genes: a core peptide (
<jats:italic>stpA</jats:italic>
), a membrane protein (
<jats:italic>stpB</jats:italic>
), a DUF95 family protein (
<jats:italic>stpC</jats:italic>
), an ATP‐binding protein (
<jats:italic>stpD</jats:italic>
), and a putative immunity protein (
<jats:italic>stpE</jats:italic>
). Sequence Similarity Network (SSN) analysis revealed that streptocyclin BTW‐like circular bacteriocins were found in
<jats:italic>Streptococcus orisasini</jats:italic>
,
<jats:italic>Streptococcus equi</jats:italic>
,
<jats:italic>Streptococcus pneumoniae</jats:italic>
,
<jats:italic>Streptococcus pseudopneumoniae</jats:italic>
,
<jats:italic>Streptococcus mitis</jats:italic>
, and
<jats:italic>Streptococcus bouchesdurhonensis</jats:italic>
species. This is the first report of a bacteriocin produced by
<jats:italic>S. devriesei</jats:italic>
.
</jats:p>
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View paper →Evolution of Plasmid-Mediated Antibiotic Resistance in the Clinical Context
Alvaro San Millan
Trends in Microbiology·2018·370 citations
No abstract available
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View paper →No one asked: my thoughts on Artificial Intelligence
Substack
Substack·2025
Yapping about why I believe AI is awful and everyone should, too.
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View paper →Art and Cognitive Evolution
Merlin Donald
The Artful Mind·2006·67 citations
No abstract available
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View paper →Rethinking Load Growth: Assessing the Potential for Integration of Large Flexible Loads in US Power Systems
Norris, Tyler, Profeta, Timothy, Patino-Echeverri, Dalia, Cowie-Haskell, Adam
hdl.handle.net·2025
No abstract available
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View paper →Spontaneous Emergence of Symmetry in a Generative Model of Protein Structure
Anton Oresten, Kenta Sato, Aron Stålmarck, Lukas Billera, Hedwig Nora Nordlinder, Jack Collier Ryder, Mateusz Kaduk, Ben Murrell
bioRxiv·2025
Generative models are becoming powerful tools for protein design, enabling the creation of novel protein structures and sequences. Recent approaches have shown success using diffusion models and flow matching to sample realistic protein folds. Many methods explicitly incorporate structural biases or constraints—for example, enforcing symmetry during generation—to steer the design process. Here we report the spontaneous emergence of structural symmetry in a transformer-based generative model for proteins, without any symmetry-specific conditioning during training or constraints during generation. In our flow-matching model, a single attention head in an SE(3)-equivariant transformer layer was found to be primarily responsible for the model’s ability to generate symmetric arrangements of backbone residues across chains, or repeating motifs within a chain. Our results show that protein generative models can learn high-level structural patterns implicitly from training data. This opens new questions about interpretability and control in generative design: understanding how and why a single attention head can govern a complex global property like symmetry may inform future model architectures and help exploit emergent behaviors for better protein engineering.
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View paper →The Artification Hypothesis and Its Relevance to Cognitive Science, Evolutionary Aesthetics, and Neuroaesthetics
Ellen Dissanayake
No abstract available
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View paper →Suddendorf Et Corballis 1997 Mental Time Travel And The Evolution
Unknown Author
No abstract available
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View paper →Recalling fake news during real news corrections can impair or enhance memory updating: the role of recollection-based retrieval
Paige L. Kemp, Timothy R. Alexander, Christopher N. Wahlheim
Cognitive Research: Principles and Implications·2022·12 citations
<jats:title>Abstract</jats:title><jats:p>Fake news can impair memory leading to societal controversies such as COVID-19 vaccine efficacy. The pernicious influence of fake news is clear when ineffective corrections leave memories outdated. A key theoretical issue is whether people should recall fake news while reading corrections with contradictory details. The familiarity backfire view proposes that recalling fake news increases its familiarity, leading to interference. However, the integrative encoding view proposes that recalling fake news promotes co-activation and binding of contradictory details, leading to facilitation. Two experiments examined if one theory better accounts for memory updating after participants recalled actual fake news details when reading headlines that corrected misinformation. In Phase 1, participants read real and fake news headlines of unclear veracity taken from various internet sources. In Phase 2, participants read real news headlines that reaffirmed real news and corrected fake news from Phase 1. When they detected that Phase 2 real news corrected fake news, they attempted to recall Phase 1 fake news. In Phase 3, participants first recalled real news details. When they remembered that those details were corrections from Phase 2, they attempted to recall fake news from Phase 1. Recalling fake news when noticing corrections in Phase 2 led to better memory for real news in Phase 3 when fake news was recalled again and worse memory for real news in Phase 3 when fake news was not recalled again. Both views explain part of the memory differences associated with recalling fake news during corrections, but only when considering whether people recollected that fake news had been corrected.</jats:p>
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View paper →Mental time travel: a case for evolutionary continuity
Michael C. Corballis
Trends in Cognitive Sciences·2013·121 citations
No abstract available
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