Evidence map›Paper›PMID 42713617›Full record

ArticlePRX life2026

Inheritance entropy: A model-independent method to probe the hereditary structure of cell lineage trees.

Alessandro Allegrezza, Riccardo Beschi, Domenico Caudo, Andrea Cavagna, Alessandro Corsi, Antonio Culla, Samantha Donsante, Giuseppe Giannicola, Irene Giardina, Giorgio Gosti and 7 more

Abstract read
In one paragraph

Article in PRX life, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

17 authors.

Alessandro AllegrezzaDipartimento di Fisica, Sapienza Università di Roma, Rome, Italy.
Riccardo BeschiDipartimento di Fisica, Sapienza Università di Roma, Rome, Italy.
Domenico CaudoDipartimento di Fisica, Sapienza Università di Roma, Rome, Italy.
Andrea CavagnaIstituto Sistemi Complessi, Consiglio Nazionale delle Ricerche, UOS Sapienza, Rome, Italy.
Alessandro CorsiDipartimento di Medicina Molecolare, Sapienza Università di Roma, Rome, Italy.
Antonio CullaIstituto Sistemi Complessi, Consiglio Nazionale delle Ricerche, UOS Sapienza, Rome, Italy.
Samantha DonsanteDipartimento di Medicina Molecolare, Sapienza Università di Roma, Rome, Italy.
Giuseppe GiannicolaDipartimento di Scienze Anatomiche, Istologiche, Medico Legali e dell'Apparato Locomotore, Sapienza Università di Roma, Rome, Italy.
Irene GiardinaDipartimento di Fisica, Sapienza Università di Roma, Rome, Italy.
Giorgio GostiCenter for Life Nano & Neuro Science, Italian Institute of Technology, Rome, Italy.
Tomás S GrigeraInstituto de Física de Líquidos y Sistemas Biológicos, CONICET and Universidad Nacional de La Plata, La Plata, Argentina.
Stefania MelilloIstituto Sistemi Complessi, Consiglio Nazionale delle Ricerche, UOS Sapienza, Rome, Italy.
Biagio PalmisanoDipartimento di Medicina Molecolare, Sapienza Università di Roma, Rome, Italy.
Leonardo ParisiIstituto Sistemi Complessi, Consiglio Nazionale delle Ricerche, UOS Sapienza, Rome, Italy.
Lorena PostiglioneIstituto Sistemi Complessi, Consiglio Nazionale delle Ricerche, UOS Sapienza, Rome, Italy.
Mara RiminucciDipartimento di Medicina Molecolare, Sapienza Università di Roma, Rome, Italy.
Francesco Saverio RotondiDipartimento di Fisica, Sapienza Università di Roma, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantifying the impact of hereditary transmission within lineage trees remains a fundamental challenge universal to a wide array of biological domains. Here, we introduce the new concept of inheritance entropy, a quantity designed to gauge the hereditary structure of inactive cells across a lineage. We measure this entropy in 32 human stem cell clonal colonies, obtained from high-definition single-cell lineage tracing experiments, and show that in the greatest majority of clones the entropy is decisively smaller than that of the corresponding nonhereditary ensemble, hence proving that variations in the proliferative power of stem cell lineages are determined by hereditary epigenetic factors that regulate cell-cycle exit. The method can also be employed to locate the specific node of the tree where a mutation in the probability of inactivity occurs, together with a determination of the lag between the mutation ultimately leading to inactivity and its actual expression. This framework can be used to assess in a robust, simple and model-agnostic way the hereditary origin of differential growth in any type of lineage trees.

Identifiers

PMID42713617
PMCPMC7619470

What Socratic holds

Textmetadata
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.