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Record W3032425473 · doi:10.1186/s12964-020-00575-0

CAMKK2-CAMK4 signaling regulates transferrin trafficking, turnover, and iron homeostasis

2020· article· en· W3032425473 on OpenAlexaff
Mohammad Golam Sabbir

Bibliographic record

VenueCell Communication and Signaling · 2020
Typearticle
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsSt. Boniface Hospital
FundersSchool of Medicine, Indiana University
KeywordsCell biologyTransferrin receptorHEK 293 cellsBiologyReceptorDownregulation and upregulationFerroportinChemistryBiochemistryMetabolismGeneIron homeostasis

Abstract

fetched live from OpenAlex

Abstract Background Circulatory iron is a hazardous biometal. Therefore, iron is transported in a redox-safe state by a serum glycoprotein - transferrin (TF). Different organs acquire iron from the systemic circulation through a tightly regulated mechanism at the blood-tissue interface which involves receptor-mediated internalization of TF. Thus, abnormal TF trafficking may lead to iron dyshomeostasis associated with several diseases including neurodegeneration. Iron -induced toxicity can cause neuronal damage to iron-sensitive brain regions. Recently, it was discovered that CAMKK2, a calcium (Ca2+)/calmodulin-activated kinase, controls receptor-mediated TF trafficking in mouse tissues, specifically in the brain. The biological function of CAMKK2 is mediated through multiple downstream effectors. Both CAMKK2 and one of its downstream kinase, CAMK4, exhibit overlapping expression in mouse brain. The role of CAMK4 in vesicular transport has been reported and loss of CAMKK2 or CAMK4 leads to cognitive defects in mouse. Therefore, it was hypothesized that CAMKK2-CAMK4 signaling regulates receptor-mediated TF trafficking and iron homeostasis which may be responsible for the neuronal malfunction observed in CAMKK2- or CAMK4-deficient mice. Methods CAMK4−/−mouse was used to study tissue-specific turnover of TF, TF-receptor (TFRC) and iron. CRISPR/Cas9-based CAMKK2 and/or CAMK4 deleted human embryonic kidney-derived HEK293 cell clones were used to study the molecular defects in receptor-mediated TF trafficking. Further, a “zero functional G protein” condition in HEK293 cell was exploited to study CAMKK2-CAMK4 signaling-mediated regulation of intracellular Ca2+homeostasis which was linked to calcium signaling during TF trafficking. Results Loss of CAMK4 leads to abnormal post-translational modifications (PTMs) and turnover of TF in mouse cerebellum and liver which was associated with iron dyshomeostasis in these tissues. The HEK293 cell-based study revealed that the absence of CAMKK2-CAMK4 signaling altered intracellular Ca2+homeostasis and lead to abnormal calcium signaling during TF trafficking. Also, CAMKK2-CAMK4 signaling deficiency affected the molecular interaction of TF and TF-receptor-associated protein complexes which indicated a potential failure in the recruitment of interacting proteins due to differential PTMs in TF. Conclusion Overall, this study established a novel mechanistic link between intracellular Ca2+ level, receptor-mediated TF trafficking, and iron homeostasis, all regulated by CAMKK2-CAMK4 signaling. Graphical abstract

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.053
GPT teacher head0.303
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), 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

Citations26
Published2020
Admission routes1
Has abstractyes

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