The Inhibitory Interaction between Human Corneal and Conjunctival Sensory Channels
Bibliographic record
Abstract
PURPOSE: To explore human corneal and conjunctival sensory channels at suprathreshold level. METHODS: Ten healthy human subjects participated in the study. The Belmonte pneumatic esthesiometer was used to apply mechanical and chemical stimuli to the central cornea and temporal conjunctiva of the left eye. Stimuli were applied in a paired and unpaired way for conjunctival stimulation. A 100-point visual analog scale (VAS) was used to rate the intensity of the stimulus. RESULTS: The magnitudes of the sensation evoked from the conjunctiva were different when using different methods for presenting stimuli to the ocular surface. When stimuli were applied to the conjunctiva alone, the magnitude of the sensation was stronger than when the stimuli were applied in pairs to the cornea and conjunctiva for both mechanical (P = 0.04) and chemical (P = 0.02) stimulation. CONCLUSIONS: The relatively strong discomfort evoked from the cornea appears to suppress partially the relatively weaker conjunctival stimulation. This manifested as the conjunctival sensory transducer function being shallower (less intense sensation) when immediately preceded by corneal stimulation than when the conjunctival sensory transducer functions were measured alone (unpaired). The underlying mechanism could be adaptation or some other inhibitory effect, such as diffuse noxious inhibitory control. At some level therefore, corneal and conjunctival sensory channels are not independent.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".