Article in Diagnostics (Basel, Switzerland), 2024. 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
0.7field-weighted citation impact, top 32% 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
1 citing paper in PubMed, 2 citations in OpenAlex.
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
10 authors at 2 institutions in 1 country.
Vladislav Vladimirovich TsukanovFederal Research Center "Krasnoyarsk Science Center" of the Siberian Branch of the Russian Academy of Sciences, Scientific Research Institute of Medical Problems of the North, 660022 Krasnoyarsk, Russia.ORCID 0000-0002-9980-2294
Andrei Anatolyevich SavchenkoFederal Research Center "Krasnoyarsk Science Center" of the Siberian Branch of the Russian Academy of Sciences, Scientific Research Institute of Medical Problems of the North, 660022 Krasnoyarsk, Russia.ORCID 0000-0001-5829-672X
Mikhail Aleksandrovich CherepninFederal Research Center "Krasnoyarsk Science Center" of the Siberian Branch of the Russian Academy of Sciences, Scientific Research Institute of Medical Problems of the North, 660022 Krasnoyarsk, Russia.
Eduard Vilyamovich KasparovFederal Research Center "Krasnoyarsk Science Center" of the Siberian Branch of the Russian Academy of Sciences, Scientific Research Institute of Medical Problems of the North, 660022 Krasnoyarsk, Russia.
Elena Petrovna TikhonovaKrasnoyarsk State Medical University Named after Prof. V.F. Voino-Yasenetsky of the Ministry of Healthcare of Russian Federation, 660022 Krasnoyarsk, Russia.
Alexander Viktorovich VasyutinFederal Research Center "Krasnoyarsk Science Center" of the Siberian Branch of the Russian Academy of Sciences, Scientific Research Institute of Medical Problems of the North, 660022 Krasnoyarsk, Russia.
Julia Leongardovna TonkikhFederal Research Center "Krasnoyarsk Science Center" of the Siberian Branch of the Russian Academy of Sciences, Scientific Research Institute of Medical Problems of the North, 660022 Krasnoyarsk, Russia.
Anna Alexandrovna AnisimovaKrasnoyarsk State Medical University Named after Prof. V.F. Voino-Yasenetsky of the Ministry of Healthcare of Russian Federation, 660022 Krasnoyarsk, Russia.
Vasily Dmitrievich BelenyukFederal Research Center "Krasnoyarsk Science Center" of the Siberian Branch of the Russian Academy of Sciences, Scientific Research Institute of Medical Problems of the North, 660022 Krasnoyarsk, Russia.ORCID 0000-0003-2848-0846
Alexandr Gennadyevich BorisovFederal Research Center "Krasnoyarsk Science Center" of the Siberian Branch of the Russian Academy of Sciences, Scientific Research Institute of Medical Problems of the North, 660022 Krasnoyarsk, Russia.ORCID 0000-0002-9026-2615
Research Institute of Medical Problems of the North · RUKrasnoyarsk State Medical University · RU
Funding
No grant is acknowledged in the PubMed record.
6 · The paper itself
Abstract
backgroundNK cells phenotype and functional state in different genotypes of chronic viral hepatitis C (CVHC), depending on liver fibrosis severity, have not been sufficiently studied, which limits the possibilities for the development of pathology therapy.
methodsThe CVHC diagnosis was based on the EASL recommendations (2018). Clinical examination with liver elastometry was performed in 297 patients with genotype 1 and in 231 patients with genotype 3 CVHC. The blood NK cells phenotype was determined by flow cytometry in 74 individuals with genotype 1 and in 69 individuals with genotype 3 CVHC.
resultsThe frequency of METAVIR liver fibrosis stages F3-F4 was 32.5% in individuals with genotype 3, and 20.5% in individuals with genotype 1 CVHC (
conclusionsIn patients with both genotype 1 and genotype 3 CVHC, an imbalance in the ratio between cytokine-producing and cytotoxic NK cells and an increase in the content of NK cells that express inhibitory molecules were determined in patients with severe liver fibrosis.
Indexed as
liver fibrosisNK cellsphenotypereceptor expressionsubsetsviral hepatitis C
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.
Association of Blood NK Cell Phenotype with the Severity of Liver Fibrosis in Patients with Chronic Viral Hepatitis C with Genotype 1 or 3. · full record | OpenQuestion