Evidence map›Paper›PMID 31318338›Full record

ArticleIET systems biology2019

Sliding mode controller-observer pair for p53 pathway.

Muhammad Rizwan Azam, Vadim I Utkin, Ali Arshad Uppal, Aamer Iqbal Bhatti

Open access · hybridAbstract read
In one paragraph

Article in IET systems biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

2 citing papers in PubMed, 9 citations in OpenAlex.

  1. Using sliding mode observers to estimateIET systems biology · 2020
    Article
  2. Article
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 at 3 institutions in 2 countries.

Muhammad Rizwan AzamCASPR, Department of Electronics Engineering, Capital University of Science & Technology, Islamabad, Pakistan.
Vadim I UtkinElectrical and Computer Engineering Department, The Ohio State University, Columbus, Ohio, USA.
Ali Arshad UppalDepartment of Electrical and Computer Engineering, COMSATS University Islamabad, Pakistan.
Aamer Iqbal BhattiCASPR, Department of Electronics Engineering, Capital University of Science & Technology, Islamabad, Pakistan. aamer987@gmail.com.
Capital University of Science and Technology · PKCOMSATS University Islamabad · PKThe Ohio State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A significant loss of p53 protein, an anti-tumour agent, is observed in early cancerous cells. Induction of small molecules based drug is by far the most prominent technique to revive and maintain wild-type p53 to the desired level. In this study, a sliding mode control (SMC) based robust non-linear technique is presented for the drug design of a control-oriented p53 model. The control input generated by conventional SMC is discontinuous; however, depending on the physical nature of the system, drug infusion needs to be continuous. Therefore, to obtain a smooth control signal, a dynamic SMC (DSMC) is designed. Moreover, the boundedness of the zero-dynamics is also proved. To make the model-based control design possible, the unknown states of the system are estimated using an equivalent control based, reduced-order sliding mode observer. The robustness of the proposed technique is assessed by introducing input disturbance and parametric uncertainty in the system. The effectiveness of the proposed control scheme is witnessed by performing

Indexed as

Models, BiologicalAlgorithmsComputer SimulationNonlinear DynamicsProto-Oncogene Proteins c-mdm2Tumor Suppressor Protein p53UncertaintyProto-Oncogene Proteins c-mdm2Tumor Suppressor Protein p53

Identifiers

PMID31318338
PMCPMC8687316
OpenAlexW2955249308

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.