O<scp>ral</scp> M<scp>icrobial</scp> H<scp>eat-shock</scp> P<scp>roteins and</scp> T<scp>heir</scp> P<scp>otential</scp> C<scp>ontributions to</scp> I<scp>nfections</scp>
Bibliographic record
Abstract
The oral cavity is a complex ecosystem in which several hundred microbial species normally cohabit harmoniously. However, under certain special conditions, the growth of some micro-organisms with a pathogenic potential is promoted, leading to infections such as dental caries, periodontal disease, and stomatitis. The physiology and pathogenic properties of micro-organisms are influenced by modifications in environmental conditions that lead to the synthesis of specific proteins known as the heat-shock proteins (HSPs). HSPs are families of highly conserved proteins whose main role is to allow micro-organisms to survive under stress conditions. HSPs act as molecular chaperones in the assembly and folding of proteins, and as proteases when damaged or toxic proteins have to be degraded. Several pathological functions have been associated with these proteins. Many HSPs of oral micro-organisms, particularly periodontopathogens, have been identified, and some of their properties-including location, cytotoxicity, and amino acid sequence homology with other HSPs-have been reported. Since these proteins are immunodominant antigens in many human pathogens, studies have recently focused on the potential contributions of HSPs to oral diseases. The cytotoxicity of some bacterial HSPs may contribute to tissue destruction, whereas the presence of common epitopes in host proteins and microbial HSPs may lead to autoimmune responses. Here, we review the current knowledge regarding HSPs produced by oral micro-organisms and discuss their possible contributions to the pathogenesis of oral infections.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.008 |
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".