Evidence map›Paper›PMID 35448545›Full record

ArticleMetabolites2022

ProBDNF as an Indicator of Improvement among Women with Depressive Episodes.

Weronika Zwolińska, Maria Skibinska, Agnieszka Słopień, Monika Dmitrzak-Węglarz

Abstract read
In one paragraph

Article in Metabolites, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
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  7. Review
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

4 authors.

Weronika ZwolińskaDepartment of Child and Adolescent Psychiatry, Karol Jonscher Clinical Hospital, Poznan University of Medical Sciences, Szpitalna 27/33 St., 60-572 Poznan, Poland.ORCID 0000-0001-5880-4202
Maria SkibinskaDepartment of Psychiatric Genetics, Medical Biology Center, Poznan University of Medical Sciences, Rokietnicka St. 8, 60-806 Poznan, Poland.ORCID 0000-0002-5634-1061
Agnieszka SłopieńDepartment of Child and Adolescent Psychiatry, Karol Jonscher Clinical Hospital, Poznan University of Medical Sciences, Szpitalna 27/33 St., 60-572 Poznan, Poland.
Monika Dmitrzak-WęglarzDepartment of Psychiatric Genetics, Medical Biology Center, Poznan University of Medical Sciences, Rokietnicka St. 8, 60-806 Poznan, Poland.ORCID 0000-0002-0493-8325

Funding

National Science Center 2016/23/B/NZ5/02634
6 · The paper itself

Abstract

Depression is a chronic psychiatric disorder with a heavy socioeconomic burden. Studies on biomarkers are needed to comprehend the pathophysiology of depression and to improve treatment outcomes. Research points to the importance of imbalance between mature brain-derived neurotrophic factor (BDNF) and its precursor, pro-brain-derived neurotrophic factor (proBDNF), in the pathophysiology of mood disorders and the potential neurodegenerative role of calcium-binding protein B (S100B). Our objective was to compare BDNF, proBDNF, and S100B serum levels before and after the treatment of acute depressive episodes and to assess their correlation with the severity of symptoms and history of stress. We also aimed to investigate the differences in BDNF, proBDNF, and S100B levels between depression in the course of bipolar disorder (BD) and major depressive disorder (MDD). We recruited 31 female patients diagnosed with BD or MDD who were hospitalized due to current depressive episodes. The patients had their serum BDNF, proBDNF, and S100B levels evaluated using the ELISA method upon admission and after the symptoms improved, at discharge. We found that proBDNF levels decreased significantly with the treatment (

Indexed as

biomarkersbipolar disorderbrain-derived neurotrophic factordepressionmood disorders

Identifiers

PMID35448545
PMCPMC9027259

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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 OpenQuestion graph.