Evidence map›Paper›PMID 40862768›Full record

ArticleCells2025

Kisspeptin Mitigates Hepatic De Novo Lipogenesis in Metabolic Dysfunction-Associated Steatotic Liver Disease.

Kimberly Izarraras, Ankit Shah, Kavita Prasad, Helena Tan, Zhongren Zhou, Moshmi Bhattacharya

Abstract read
In one paragraph

Article in Cells, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Kimberly IzarrarasDepartment of Medicine, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ 08901, USA.ORCID 0000-0002-3486-630X
Ankit ShahDepartment of Medicine, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ 08901, USA.ORCID 0000-0002-6701-3258
Kavita PrasadDepartment of Medicine, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ 08901, USA.
Helena TanDepartment of Medicine, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ 08901, USA.
Zhongren ZhouDepartment of Pathology and Laboratory Medicine, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ 08901, USA.
Moshmi BhattacharyaDepartment of Medicine, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ 08901, USA.ORCID 0000-0002-9191-9877

Funding

TRANSCRIPTIONAL PROFILINGP30CA072720 · NCI · UNIV OF MED/DENT NJ-R W JOHNSON MED SCH · PI Tracie Saunders · 1997 to 2026
$94.5M
Hepatic fat accumulation in nonalcoholic fatty liver disease: critical regulation by kisspeptin signalingR01DK129870 · NIDDK · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI BHATTACHARYA, MOSHMI M · 2022 to 2025
$1.9M
NCI NIH HHS P30 CA072720NIDDK NIH HHS R01 DK129870NIH HHS 7R01DK129870-04Seed grant from the Rutgers NJ Institute for Food Nutrition and Health S.D.G
6 · The paper itself

Abstract

The peptide hormone kisspeptin, signaling via its receptor, KISS1R, decreases hepatic steatosis and protects against metabolic dysfunction-associated steatotic liver disease (MASLD). Enhanced de novo lipogenesis (DNL) contributes to MASLD. Here, we investigated whether kisspeptin treatment in obese, diabetic mice directly attenuates DNL. DNL was assessed in kisspeptin-treated mouse livers, using a mouse model of MASLD, (DIAMOND mice), employing

Indexed as

Fatty LiverKisspeptinsLipogenesisLiverAnimalsDisease Models, AnimalHepatocytesMaleMiceMice, Inbred C57BLReceptors, Kisspeptin-1Kiss1r protein, mouseKisspeptinsReceptors, Kisspeptin-1CIDEAde novo lipogenesisKISS1RkisspeptinliverMASLDSREBPsteatosis

Identifiers

PMID40862768
PMCPMC12384258

What OpenQuestion holds

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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 OpenQuestion graph.