The Role of <i>PIEZO2</i> in Human Mechanosensation
Bibliographic record
Abstract
BACKGROUND: The senses of touch and proprioception evoke a range of perceptions and rely on the ability to detect and transduce mechanical force. The molecular and neural mechanisms underlying these sensory functions remain poorly defined. The stretch-gated ion channel PIEZO2 has been shown to be essential for aspects of mechanosensation in model organisms. METHODS: We performed whole-exome sequencing analysis in two patients who had unique neuromuscular and skeletal symptoms, including progressive scoliosis, that did not conform to standard diagnostic classification. In vitro and messenger RNA assays, functional brain imaging, and psychophysical and kinematic tests were used to establish the effect of the genetic variants on protein function and somatosensation. RESULTS: Each patient carried compound-inactivating variants in PIEZO2, and each had a selective loss of discriminative touch perception but nevertheless responded to specific types of gentle mechanical stimulation on hairy skin. The patients had profoundly decreased proprioception leading to ataxia and dysmetria that were markedly worse in the absence of visual cues. However, they had the ability to perform a range of tasks, such as walking, talking, and writing, that are considered to rely heavily on proprioception. CONCLUSIONS: Our results show that PIEZO2 is a determinant of mechanosensation in humans. (Funded by the National Institutes of Health Intramural Research Program.).
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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) | 0.000 | 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) | 0.002 | 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".