Evidence map›Paper›PMID 40191583›Full record

ArticleCurrent opinion in biomedical engineering2024

Regenerative rehabilitation measures to restore tissue function after arsenic exposure.

Adam A Jasper, Kush H Shah, Helmet Karim, Swathi Gujral, Iva Miljkovic, Caterina Rosano, Aaron Barchowsky, Amrita Sahu

Abstract read
In one paragraph

Article in Current opinion in biomedical engineering, 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

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

8 authors.

Adam A JasperDepartment of Physical Medicine and Rehabilitation, University of Pittsburgh, USA.
Kush H ShahThe Lake Erie College of Osteopathic Medicine (LECOM), Erie, PA, USA.
Helmet KarimDepartment of Psychiatry, University of Pittsburgh, USA.
Swathi GujralDepartment of Psychiatry, University of Pittsburgh, USA.
Iva MiljkovicDepartment of Epidemiology, University of Pittsburgh, USA.
Caterina RosanoDepartment of Epidemiology, University of Pittsburgh, USA.
Aaron BarchowskyDepartment of Environmental and Occupational Health, University of Pittsburgh, USA.
Amrita SahuDepartment of Physical Medicine and Rehabilitation, University of Pittsburgh, USA.

Funding

Dysfunctional skeletal muscle communication in arsenic-promoted cardiometabolic diseaseR01ES033519 · NIEHS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BARCHOWSKY, AARON · 2021 to 2025
$2.5M
NIEHS NIH HHS R01 ES033519
6 · The paper itself

Abstract

Environmental exposure of arsenic impairs the cardiometabolic profile, skeletal muscle health, and neurological function. Such declining tissue health is observed as early as in one's childhood, where the exposure is prevalent, thereby accelerating the effect of time's arrow. Despite the known deleterious effects of arsenic exposure, there is a paucity of specific treatment plans for restoring tissue function in exposed individuals. In this review, we propose to harness the untapped potential of existing regenerative rehabilitation programs, such as stem cell therapeutics with rehabilitation, acellular therapeutics, and artificial intelligence/robotics technologies, to address this critical gap in environmental toxicology. With regenerative rehabilitation techniques showing promise in other injury paradigms, fostering collaboration between these scientific realms offers an effective means of mitigating the detrimental effects of arsenic on tissue function.

Indexed as

Arsenic toxicologyCardiometabolic profileEnvironmental toxicologyNervous systemRegenerative rehabilitationSkeletal muscle

Identifiers

PMID40191583
PMCPMC11970924

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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.