The spectrin cytoskeleton is an integral target and crucial component of adherent, invasive triggering and invasive zippering bacterial diseases
Bibliographic record
Abstract
Entropathogenic Escherichia coli (EPEC), Salmonella Typhimurium ( S. Typhimurium), and Listeria monocytogenes ( L. monocytogenes ) all manipulate the host cell cytoskeleton at crucial stages of their disease processes. Although the actin cytoskeleton has been previously identified as a ubiquitous target of these pathogens, the examination of the spectrin cytoskeleton has been largely overlooked. Here we show that spectrin and the spectrin‐associated proteins adducin and protein 4.1 are recruited to sites of EPEC pedestals as well as sites of S . Typhimurium and L. monocytogenes invasion. Individual siRNA knockdowns of each spectrin cytoskeletal protein significantly impeded the ability of EPEC to form pedestals and inhibited the abilities of both S .Typhimurium and L.monocytogenes to invade host cells. Further studies identified spectrin cytoskeleton recruitment to later time‐points of S .Typhimurium and L. monocytogenes infections during the intercellular stage of pathogenesis, revealing novel cytoplasmic roles for the spectrin cytoskeleton. This work demonstrates that the spectrin cytoskeletal system is crucial for bacterial pathogenesis and represents a potential target for therapeutic treatment for a broad list of infections. Grant Funding Source : CIHR
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".