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Abstract 14315: New Insights Into the Mechanisms of Sepsis: The Role of Proprotein Convertase Subtilisin/kexin Type 9 as a Key Regulator of Pathogen Toxin Clearance

2015· article· en· W2466070094 on OpenAlexaff
Elena Topchiy, Yingjin Wang, John H. Boyd, Keith R. Walley

Bibliographic record

VenueCirculation · 2015
Typearticle
Languageen
FieldMedicine
TopicClusterin in disease pathology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPCSK9LDL receptorKexinProprotein convertaseMedicineInternal medicineEndocrinologyInflammationLipoproteinPharmacologyCholesterol

Abstract

fetched live from OpenAlex

Background: To prevent severe inflammation during infection, the patient must quickly clear bacterial endotoxins from the circulation before they accumulate and are able to interact with immune cells and vascular endothelium, and induce inflammatory organ failure. Bacterial endotoxins are carried within lipoprotein particles. Thus, one mechanism of action for sepsis treatments could be acceleration of lipoprotein clearance by adipocytes and hepatocytes. Proprotein convertase subtilisin/kexin type 9 (PCSK9) decreases the rate of lipoprotein clearance. We have recently reported that reduced function of PCSK9 improves outcome and prevents cardiovascular complications associated with sepsis. Hypothesis: PCSK9 inhibits LDL associated LPS clearance through hepatic LDLR and VLDL associated LPS clearance through adipose VLDLR. Methods and Results: Using siRNA against the LDLR in HepG2 hepatocytes decreased uptake of fluorescently labeled LPS (fLPS) after 48 hours by 1.50±0.10 fold (n=3, p<0.05). Addition of recombinant PCSK9 in the absence of LDLR did not alter uptake of LPS. We confirmed that hepatic uptake of LPS is exclusively via the LDLR by fluorescent microscopy of ex vivo LPS treated primary hepatocytes isolated from LDLR -/- mice. To address the importance of the LDLR upon clearance of LPS from plasma, we injected fLPS into the portal vein of LDLR-/-, PCSK9-/- and wild type mice (WT). Compared to WT, LDLR-/- mice had 36±13% (n=9, p<0.001) increase in plasma LPS after 1 hour, whereas PCSK9-/- show a significant decrease (28±4%, n=9, p<0.001) in plasma LPS. LDLR-/-, but not PCSK9-/- mice showed 46±7% decrease (n=10, p<0.05) in hepatic uptake. On the other hand, compared to the WT PCSK9-/- mice had 200±35% (n=8, p<0.001) increase in LPS uptake by visceral adipose tissue whereas LDLR-/- had no effect compared to WT mice. To further investigate LPS uptake by adipose tissue we injected flLPS into the tail vein of VLDLR-/- and WT mice. VLDLR-/- mice had 33±6% (n=10, p<0.001) decrease in visceral adipose tissue uptake, with no significant change in hepatic uptake. Conclusions: Expression of hepatic LDLR and adipose VLDLR is mainly regulated by PCSK9 and both play important role in clearing LPS from circulation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.565
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.270
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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