Evidence map›Paper›PMID 41117889›Full record

ArticleMolecular biology reports2025

Transcriptomic analysis at 48 h postmortem: a proof of concept for the identification of biomarkers to estimate time since death.

Nahum Zepeta Flores, Luz María Garduño Zarazúa, Gabriela Piñón Zarate, Christian Adrian Cárdenas Monroy, Alejandra Mercado Salomon, Olivia Pérez Zamora, Carlos Pedraza Lara, Oliver Millán Catalán, Haydee Rosas Vargas, Silvia Jiménez Morales and 2 more

Abstract read
In one paragraph

Article in Molecular biology reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

12 authors.

Nahum Zepeta FloresLaboratorio de Genética, Escuela Nacional de Ciencias Forenses, Universidad Nacional Autónoma de México, Ciudad de México, México.
Luz María Garduño ZarazúaUnidad de Investigación Médica en Genética Humana, Unidad Médica de Alta Especialidad, Hospital de Pediatría, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Ciudad de México, Mexico.
Gabriela Piñón ZarateLaboratorio de Inmunoterapia e Ingeniería de tejidos, Departamento de Biología Celular y Tisular, Facultad de Medicina, UNAM, Ciudad de México, México.
Christian Adrian Cárdenas MonroyLaboratorio de Genética, Escuela Nacional de Ciencias Forenses, Universidad Nacional Autónoma de México, Ciudad de México, México.
Alejandra Mercado SalomonLaboratorio de Antropología y Odontología Forense, Escuela Nacional de Ciencias Forenses, Universidad Nacional Autónoma de México, Ciudad de México, México.
Olivia Pérez ZamoraLaboratorio de Genética, Escuela Nacional de Ciencias Forenses, Universidad Nacional Autónoma de México, Ciudad de México, México.
Carlos Pedraza LaraLaboratorio de Entomología Forense, Escuela Nacional de Ciencias Forenses, Universidad Nacional Autónoma de México, Ciudad de México, México.
Oliver Millán CatalánUnidad de Investigación Biomédica en Cáncer, Instituto Nacional de Cancerología, Ciudad de México, Mexico.
Haydee Rosas VargasUnidad de Investigación Médica en Genética Humana, Unidad Médica de Alta Especialidad, Hospital de Pediatría, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Ciudad de México, Mexico.
Silvia Jiménez MoralesLaboratorio de Innovación y Medicina de Precisión, Núcleo ″A″, Instituto Nacional de Medicina Genómica, Mexico, Mexico.
Carlos Pérez Plasencia, Laboratorio de Genómica, Unidad de Biomedicina, FES-IZTACALA, UNAM, Tlalnepantla, Mexico.
Mariano Guardado EstradaLaboratorio de Genética, Escuela Nacional de Ciencias Forenses, Universidad Nacional Autónoma de México, Ciudad de México, México. mguardado@enacif.unam.mx.

Funding

Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México IA204420
6 · The paper itself

Abstract

backgroundThe postmortem interval (PMI) refers to the time elapsed between an individual's death and the examination of the body. Tissues undergo a sequence of anatomical changes following death, which are routinely used to estimate the PMI.

methodsTo determine if these anatomical changes are associated with identifiable genomic adaptations that could characterize the PMI more accurately, we analyzed the rat skeletal muscle transcriptome at 0 and 48 h postmortem using Clariom™ S arrays. This study investigates whether specific transcriptomic changes correlate with PMI progression, offering a potential molecular tool to complement established anatomical methods.

resultsA total of 3,873 differentially expressed mRNAs were identified, of which 2,787 downregulated and 1,086 upregulated transcripts. The most significantly downregulated mRNA was Tnni1 (FC = -30.95, p = 1 × 10

conclusionOur results demonstrate significant transcriptomic changes at 48 h postmortem, highlighting specific genes and biological pathways that may serve as candidate biomarkers for PMI estimation.

Indexed as

Gene Expression ProfilingPostmortem ChangesTranscriptomeAnimalsBiomarkersGene OntologyMaleMuscle, SkeletalRatsRats, Sprague-DawleyRNA, MessengerTime FactorsBiomarkersRNA, MessengerMicroarrayMRNAPostmortem intervalTranscriptome

Identifiers

PMID41117889
PMCPMC12540568

What Socratic holds

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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 Socratic graph.