Evidence map›Paper›PMID 32997706›Full record

ArticlePloS one2020

Periodized versus non-periodized swimming training with equal total training load: Physiological, molecular and performance adaptations in Wistar rats.

Lucas D M Forte, Natália A Rodrigues, André V Cordeiro, Thais de Fante, Laís A P Simino, Adriana S Torsoni, Márcio A Torsoni, Claudio A Gobatto, Fúlvia B Manchado-Gobatto

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 11% 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, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Article
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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

9 authors at 1 institution in 1 country.

Lucas D M ForteLaboratory of Applied Sport Physiology, School of Applied Sciences, University of Campinas, Limeira, São Paulo, Brazil.ORCID 0000-0002-6496-0380
Natália A RodriguesLaboratory of Applied Sport Physiology, School of Applied Sciences, University of Campinas, Limeira, São Paulo, Brazil.
André V CordeiroLaboratory of Applied Sport Physiology, School of Applied Sciences, University of Campinas, Limeira, São Paulo, Brazil.
Thais de FanteLaboratory of Metabolic Disorders, School of Applied Sciences, University of Campinas, Limeira, Brazil.
Laís A P SiminoLaboratory of Metabolic Disorders, School of Applied Sciences, University of Campinas, Limeira, Brazil.
Adriana S TorsoniLaboratory of Metabolic Disorders, School of Applied Sciences, University of Campinas, Limeira, Brazil.
Márcio A TorsoniLaboratory of Metabolic Disorders, School of Applied Sciences, University of Campinas, Limeira, Brazil.
Claudio A GobattoLaboratory of Applied Sport Physiology, School of Applied Sciences, University of Campinas, Limeira, São Paulo, Brazil.
Fúlvia B Manchado-GobattoLaboratory of Applied Sport Physiology, School of Applied Sciences, University of Campinas, Limeira, São Paulo, Brazil.
Universidade Estadual de Campinas (UNICAMP) · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigated the effect of non-periodized training performed at 80, 100 and 120% of the anaerobic threshold intensity (AnT) and a linear periodized training model adapted for swimming rats on the gene expression of monocarboxylate transporters 1 and 4 (MCT1 and 4, in soleus and gastrocnemius muscles), protein contents, blood biomarkers, tissue glycogen, body mass, and aerobic and anaerobic capacities. Sixty Wistar rats were randomly divided into 6 groups (n = 10 per group): a baseline (BL; euthanized before training period), a control group (GC; not exercised during the training period), three groups exercised at intensities equivalent to 80, 100 and 120% of the AnT (G80, G100 and G120, respectively) at the equal workload and a linear periodized training group (GPE). Each training program lasted 12 weeks subdivided into three periods: basic mesocycle (6 weeks), specific mesocycle (5 weeks) and taper (1 week). Although G80, G100 and G120 groups were submitted to monotony workload (i.e. non-modulation at intensity or volume throughout the training program), rodents were evaluated during the same experimental timepoints as GPE to be able comparisons. Our main results showed that all training programs were capable to minimize the aerobic capacity decrease promoted by age, which were compared to control group. Rats trained in periodization model had reduced levels of lipid blood biomarkers and increased hepatic glycogen stores compared to all other trained groups. At the molecular level, only expressions of MCT1 in the muscle were modified by different training regimens, with MCT1 mRNA increasing in rats trained at lower intensities (G80), and MCT1 protein content showed higher values in non-periodized groups compared to pre-training and GPE. Here, training at different intensities but at same total workload promoted similar adaptations in rats. Nevertheless, our results suggested that periodized training seems to be optimize the physiological responses of rats.

Indexed as

Adaptation, PhysiologicalAnaerobic ThresholdAdipose Tissue, BrownAnimalsBiomarkersBody WeightGlycogenMaleMonocarboxylate Transport Protein 1Monocarboxylic Acid TransportersMuscle ProteinsMuscle, SkeletalRatsRats, WistarRNA, MessengerSwimmingBiomarkersGlycogenMonocarboxylate Transport Protein 1Monocarboxylic Acid TransportersMuscle ProteinsRNA, MessengerSlc16a3 protein, ratSymporters

Identifiers

PMID32997706
PMCPMC7526899
OpenAlexW3089458135

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.