Endocrine dysregulation in COVID-19: molecular mechanisms and insights
Bibliographic record
Abstract
This review describes the impact of COVID-19 on the endocrine system, focusing on cortisol signaling and growth factor-induced endocrine resistance. As expected, SARS-CoV-2 infection induces systemic inflammation, resulting in stimulation of the adrenal glands leading to elevated cortisol levels with normal adrenocorticotropic hormone (ACTH) levels. The cytokine storm could also stimulate cortisol production. However, in some instances, cortisol levels rise independently of ACTH due to a phenomenon known as "pseudo-Cushing's syndrome," where adrenal glands become less responsive to ACTH. Plasma proteomic analyses showed that this pattern was variably observed among COVID-19 patients, potentially involving calcium dysregulation and GNAS-regulated activities, ultimately impacting the regulation of microvascular permeability. COVID-19 also exhibited a syndrome resembling endocrine resistance, governed by receptor tyrosine kinase signaling pathways. Mild cases displayed elevated activity of EGFR and MMP9, along with increased expression of survival factors like Bax and Bcl2. In contrast, more severe cases involved IGFR-I and enhanced NOTCH signaling, with altered expression of Bcl2, AKT1, and MAPK8. In summary, these findings describe the complex interplay between COVID-19 and endocrine pathology, particularly endocrine resistance. These insights suggest potential endocrine targets for therapeutic interventions to improve short- and long-term outcomes for COVID-19 patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".