Neuroprotective action of α-Klotho against LPS-activated glia conditioned medium in primary neuronal culture
Bibliographic record
Abstract
The α-Klotho is an anti-aging protein that, when overexpressed, extends the life span in humans and mice. It has an anti-inflammatory and protective action on renal cells by inhibiting NF-κB activation and production of inflammatory cytokines in response to TNF-α. Furthermore, studies have shown the neuroprotective effect of α-Klotho against neuroinflammation on different conditions, such as aging, animal models of neurodegenerative diseases, and ischemic brain injury. This work aimed to evaluate the effects of α-Klotho protein on primary glial cell culture against the proinflammatory challenge with LPS and how this could interfere with neuronal health. Cortical mixed glial cells and purified astrocytes were pretreated with α- α-Klotho and stimulated with LPS followed by TNFα, IL-1β, IL-6, IFN-γ levels, and NF-κB activity analysis. Conditioned medium from cortical mixed glia culture treated with LPS (glia conditioned medium (GCM) was used to induce neuronal death of primary cortical neuronal culture and evaluate if GCM-KL (medium from glia culture pretreated α-Klotho followed by LPS stimulation) or GCM + LPS in the presence of KL can reverse the effect. LPS treatment in glial cells induced an increase in proinflammatory mediators such as TNF-α, IL-1β, IL-6, and IFN-γ, and activation of astrocyte NF-κB. GCM treated-cortical neuronal culture induced a concentration-dependent neuronal death. Pretreatment with α-Klotho decreased TNF-α and IL-6 production, reverted NF-κB activation, and decreased neuronal death induced by GCM. In addition, KL incubation together with GCM + LPS completely reverts the neuronal toxicity induced by low concentration of GCM-LPS. These data suggest an anti-inflammatory and neuroprotective effect of α-Klotho protein in the CNS. This work demonstrated the therapeutic potential of α-Klotho in pathological processes which involves a neuroinflammatory component.
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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) | 0.001 | 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 | 0.000 |
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".