Evidence map›Paper›PMID 31313125›Full record

ArticleMetabolic brain disease2019

High fat-low protein diet induces metabolic alterations and cognitive dysfunction in female rats.

Ravinder Naik Dharavath, Shiyana Arora, Mahendra Bishnoi, Kanthi Kiran Kondepudi, Kanwaljit Chopra

Abstract read
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In one paragraph

Article in Metabolic brain disease, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.9field-weighted citation impact, top 13% of its field
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

8 citing papers in PubMed, 23 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Ravinder Naik DharavathPharmacology Research Laboratory, University Institute of Pharmaceutical Sciences (UIPS), Panjab University, Chandigarh, 160014, India.
Shiyana AroraPharmacology Research Laboratory, University Institute of Pharmaceutical Sciences (UIPS), Panjab University, Chandigarh, 160014, India.
Mahendra BishnoiFood and Nutritional Biotechnology Laboratory, National Agri-food Biotechnology Institute (NABI), SAS Nagar, Punjab, 140306, India.
Kanthi Kiran KondepudiFood and Nutritional Biotechnology Laboratory, National Agri-food Biotechnology Institute (NABI), SAS Nagar, Punjab, 140306, India.
Kanwaljit ChopraPharmacology Research Laboratory, University Institute of Pharmaceutical Sciences (UIPS), Panjab University, Chandigarh, 160014, India. dr_chopra_k@yahoo.com.ORCID 0000-0002-2356-2458
Panjab University · INNational Agri-Food Biotechnology Institute · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Approximately one-third of the world population is suffering from MetS, and the same is expected to rise in the years to come. Worldwide, most of the staple diets contain high amounts of carbohydrates, fats and comparatively low quantities of proteins. The goal of this study was to evaluate the effect of high fat-low protein diet in the development of the metabolic syndrome and associated cognitive deficits in the female rats. The rats fed with high fat-low protein diet (HFLPD) and 15% oral fructose solution for 24 weeks. Body weight, food intake, water intake, fasting blood glucose, oral glucose tolerance, glycosylated hemoglobin (HbA

Indexed as

AnimalsBehavior, AnimalBlood GlucoseCognitive DysfunctionDiet, High-FatDiet, Protein-RestrictedFemaleHyperglycemiaInsulin ResistanceLipidsMemoryMetabolic SyndromeMotor ActivityOxidative StressRatsRats, WistarBlood GlucoseLipidsCognitive declineFructose feedingHigh calorific dietHypertensionInsulin resistanceMetabolic syndrome

Identifiers

PMID31313125
OpenAlexW2959119403

What OpenQuestion 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 OpenQuestion graph.