Sustained macrophage alterations during chronic injury regression beget increased susceptibility to infections
Bibliographic record
Abstract
The liver serves as the body’s central microbial filter preventing spread of blood-borne pathogens. To fulfil this critical task, the liver relies on a hub of immune surveillance, the liver sinusoids which contain the most abundant population of tissue resident macrophages, the Kupffer cells (KCs). In homeostasis, KCs filter>90% of disseminated bacteria within minutes from the blood. In contrast, during chronic liver injury and fibrosis KCs dramatically change their phenotype, lose their identity and their function. Furthermore, monocytes invade the liver with an individual functional profile and form KC-like syncytia that compensate for loss of KC function on the level of sinusoids. However, it is unclear how the liver macrophage compartment responds to injury regression which is seen in patients with chronic liver diseases. Using a mouse model of chronic toxicity and regression of hepatic injury, numerous monocyte and macrophage linage tracing tools, intravital microscopy and multiplex flow cytometry we investigated the liver macrophage compartment during injury regression. Liver architecture and liver damage completely normalized in regression. Surprisingly, we found sustained alterations macrophage compartment that included differences in KC identity molecules such as CRIg and TIM-4. Functionally, bacterial capture was reduced in regression compared to control mice. Flow cytometric profiling revealed an emerging population of monocyte-derived KCs. Furthermore, we found a novel macrophage subset expressing the markers MerTK, CD68, CD86 and PD-L1. Our results demonstrate sustained alteration of the liver macrophage compartment during injury regression, favoring injury repair over antimicrobial responses thus leaving the host vulnerable to infections. Publication History Article published online: 23 January 2024 © 2024. Thieme. All rights reserved. Georg Thieme Verlag Rüdigerstraße 14, 70469 Stuttgart, Germany
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".