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Record W3209896489 · doi:10.29169/1927-5129.2021.17.06

Modeling and Simulation in Cancer Nanomedicine

2021· article· en· W3209896489 on OpenAlexvenueno aff
Keka Talukdar

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2021
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMutationIonNanomedicineCancerFunction (biology)Molecular dynamicsIon channelBiophysicsProtein Data Bank (RCSB PDB)ChemistryChannel (broadcasting)Materials scienceChemical physicsNanotechnologyComputer scienceBiologyComputational chemistryGeneticsBiochemistryGeneNanoparticle

Abstract

fetched live from OpenAlex

There is a certain function of ion channels in cancer cell progression and proliferation. The mutation of ion channels is proved to have a clear influence on the same. The progress of nanomedicine research needs the proper concept of the exact role of ion channels in cancer and the cause of the disease. In this work, an ion channel protein residing in our stomach with PDB id 3ux4 is analyzed to get an idea about its structure-function relationship. The disordered region and mutation sensitivity of the channel causing cancer are analyzed in different ways. Eight disordered regions of the protein are found in the study. The pocket in the active site is found along with the position of the miss-sense mutation. The maximum mutation region is also found for a sample disordered region. The engineered ion channel is simulated in the environment of water and ions. The potential energy of the water-ion model of the protein calculated by molecular dynamics simulation is 20,412 kcal/mol after simulating the system for 1,00000 steps.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0080.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.322
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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