Evidence map›Paper›PMID 42791851›Full record

ArticleBioengineering (Basel, Switzerland)2026

Shared-Scale Predictive Benchmarking of an Acoustic-Radiation-Force Model for Frequency-Dependent Retinal Ganglion Cell Responses.

Bingao Zhang, Shengyong Xu

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Bingao ZhangThe Key Laboratory for the Physics and Chemistry of Nanodevices, Institute of Physical Electronics, Department of Electronics, Peking University, Beijing 100871, China.ORCID 0009-0008-1269-3971
Shengyong XuThe Key Laboratory for the Physics and Chemistry of Nanodevices, Institute of Physical Electronics, Department of Electronics, Peking University, Beijing 100871, China.ORCID 0000-0001-9567-5980

Funding

National Key R&D Program of China 2024YFC3406302
6 · The paper itself

Abstract

Retinal responses to ultrasound depend on carrier frequency, but whether a constrained tissue-to-neuron model can predict this dependence on a common published response scale remains unclear. We developed an acoustic-radiation-force (ARF) modelling workflow that couples an effective tissue-scale stress proxy to a stochastic Hodgkin-Huxley retinal ganglion cell population. One non-negative affine observation model, shared across frequencies, linked raw simulated spike counts to the published three-frequency ex vivo RGC response scale without frequency-specific rescaling. In a nested leave-one-frequency-out model-selection assessment, the workflow achieved an overall Q2 of 0.915 and an RMSE of 0.0752 across 25 held-out observations. Mean-response transfer remained strong across frequencies, although probabilistic calibration was weakest at 1.9 MHz. An in-sample fixed-map sensitivity analysis using moment-matched log-normal, Gamma, and Weibull thresholds yielded overall RMSEs of 0.0434-0.0461 and preserved positive overall K-ablation NLPD differences of 0.219-0.238, with the effect concentrated at 43 MHz. These results show that shared-scale modelling captures the main cross-frequency response structure and that a high-threshold inhibitory functional component improves the description of high-intensity rolloff. Within the published three-frequency dataset, the workflow provides a reproducible benchmark for targeted comparisons of retinal ultrasound mechanisms.

Indexed as

acoustic radiation forcebiophysical simulationHodgkin–Huxley modelphenomenological inhibitory currentretinal ganglion cellsretinal prostheticsultrasonic neurostimulation

Identifiers

PMID42791851
PMCPMC13603775

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.