Evidence map›Paper›PMID 25663099›Full record

ArticleMolecular biotechnology2015

New Strategies for Expression and Purification of Recombinant Human RNASET2 Protein in Pichia pastoris.

Marta Lualdi, Edoardo Pedrini, Francesca Petroni, Johnny Näsman, Christer Lindqvist, Debora Scaldaferri, Roberto Taramelli, Antonio Inforzato, Francesco Acquati

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Article in Molecular biotechnology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 38% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

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 3 institutions in 2 countries.

Marta LualdiDepartment of Theoretical and Applied Sciences, University of Insubria, Via JH Dunant 3, 21100, Varese, Italy, marta.lualdi@uninsubria.it.
Edoardo Pedrini
Francesca Petroni
Johnny Näsman
Christer Lindqvist
Debora Scaldaferri
Roberto Taramelli
Antonio Inforzato
Francesco Acquati
University of Insubria · ITÅbo Akademi University · FIHumanitas University · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ribonucleases form a large family of enzymes involved in RNA metabolism and are endowed with a broad range of biological functions. Among the different RNase proteins described in the last decades, those belonging to the Rh/T2/S subfamily show the highest degree of evolutionary conservation, suggesting the occurrence of a key critical ancestral role for this protein family. We have recently defined the human RNASET2 gene as a novel member of a group of oncosuppressors called "tumor antagonizing genes," whose activity in the control of cancer growth is carried out mainly in vivo. However, to better define the molecular pathways underlying the oncosuppressive properties of this protein, further structural and functional investigations are necessary, and availability of high-quality recombinant RNASET2 is of paramount importance. Here, we describe a multi-step strategy that allows production of highly pure, catalytically competent recombinant RNASET2 in both wild-type and mutant forms. The recombinant proteins that were produced with our purification strategy will be instrumental to perform a wide range of functional assays aimed at dissecting the molecular mechanisms of RNASET2-mediated tumor suppression.

Indexed as

Base SequenceChromatography, AffinityChromatography, GelCloning, MolecularDNA PrimersGlycosylationHumansPichiaRecombinant ProteinsRibonucleasesTumor Suppressor ProteinsDNA PrimersRecombinant ProteinsRibonucleasesRNASET2 protein, humanTumor Suppressor Proteins

Identifiers

PMID25663099
OpenAlexW2100874008

What OpenQuestion holds

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Registered trials

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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.