Evidence map›Paper›PMID 39464131›Full record

ArticlebioRxiv : the preprint server for biology2024

Machine vision based frailty assessment for genetically diverse mice.

Gautam S Sabnis, Gary A Churchill, Vivek Kumar

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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

5 · Who and what money

Authors and funding

3 authors.

Gautam S SabnisThe Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609.ORCID 0000-0002-9985-7463
Gary A ChurchillThe Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609.ORCID 0000-0001-9190-9284
Vivek KumarThe Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609.ORCID 0000-0001-6643-7465

Funding

Translational CoreP30AG038070 · NIA · JACKSON LABORATORY · PI John Matthew Mahoney · 2010 to 2026
$19.3M
Sequencing Mutant Mice With Altered Cocaine ResponsesU01DA041668 · NIDA · JACKSON LABORATORY · PI KUMAR, VIVEK · 2016 to 2020
$2.8M
Machine learning based frailty index for the genetically diverse miceR33AG078530 · NIA · JACKSON LABORATORY · PI VIVEK KUMAR · 2024 to 2026
$2.0M
Machine learning based frailty index for the genetically diverse miceR61AG078530 · NIA · JACKSON LABORATORY · PI KUMAR, VIVEK · 2022 to 2023
$946k
Application of Machine Vision to Determine the Influence of Sleep States and Social Interactions on Vulnerability to Drug AddictionR21DA048634 · NIDA · JACKSON LABORATORY · PI KUMAR, VIVEK · 2019 to 2020
$468k
NIA NIH HHS P30 AG038070NIA NIH HHS R33 AG078530NIA NIH HHS R61 AG078530NIDA NIH HHS R21 DA048634NIDA NIH HHS U01 DA041668
6 · The paper itself

Abstract

Frailty indexes (FIs) capture health status in humans and model organisms. To accelerate our understanding of biological aging and carry out scalable interventional studies, high-throughput approaches are necessary. We previously introduced a machine vision-based visual frailty index (vFI) that uses mouse behavior in the open field to assess frailty using C57BL/6J (B6J) data. Aging trajectories are highly genetic and are frequently modeled in genetically diverse animals. In order to extend the vFI to genetically diverse mouse populations, we collect frailty and behavior data on a large cohort of aged Diversity Outbred (DO) mice. Combined with previous data, this represents one of the largest video-based aging behavior datasets to date. Using these data, we build accurate predictive models of frailty, chronological age, and even the proportion of life lived. The extension of automated and objective frailty assessment tools to genetically diverse mice will enable better modeling of aging mechanisms and enable high-throughput interventional aging studies.

Identifiers

PMID39464131
PMCPMC11507677

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.