Curdlan Limits Mycobacterium tuberculosis Survival Through STAT-1 Regulated Nitric Oxide Production
Bibliographic record
Abstract
Host-directed therapies have emerged as an innovative and promising approach in tuberculosis (TB) treatment due to the observed limitations of current TB regimen such as lengthy duration and emergence of drug resistance. Thus, we explored the role of curdlan (beta glucan polysaccharide) as a novel strategy to activate macrophages against Mycobacterium tuberculosis ( Mtb ). The aim of the study was to investigate the role of curdlan in restricting the Mtb growth both in vitro and in vivo . Further, the immunomodulatory potential of curdlan against Mtb and the underlying mechanism is largely unknown. We found that curdlan treatment enhanced the antigen presentation, pro-inflammatory cytokines, Mtb uptake and killing activity of macrophages. In vivo studies showed that curdlan therapy significantly reduced the Mtb burden in lung and spleen of mice. Administration of curdlan triggered the protective Th1 and Th17 immunity while boosting the central and effector memory response in Mtb infected mice. Curdlan mediated anti- Mtb activity is through signal transducer and activator of transcription-1 (STAT-1), which regulates nitric oxide (NO) production through inducible NO synthase (iNOS) induction; along with this activation of nuclear factor kappa B (NF-κB) was also evident in Mtb infected macrophages. Thus, we demonstrate that curdlan exerts effective anti-tuberculous activity anti-tuberculous activity. It can be used as a potential host-directed therapy against Mtb .
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 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".