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Record W4388712457 · doi:10.32604/or.2023.030401

Biological, pathological, and multifaceted therapeutic functions of exosomes to target cancer

2023· article· en· W4388712457 on OpenAlexaff
Vignesh Balaji E, Divya Ramesh, MANISHA CHUNGAN SHAJU, Ajith Kumar, SAMYAK PANDEY, RAKSHA NAYAK, V. ALKA, SRISHTI MUNJAL, AMIR SALIMI, K. Sreedhara Ranganath Pai, Shankar M Bakkannavar

Bibliographic record

VenueOncology Research Featuring Preclinical and Clinical Cancer Therapeutics · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsDurham College
FundersManipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education
KeywordsMicrovesiclesExosomeIntracellularCell biologyFunction (biology)microRNABiologyBiochemistryGene

Abstract

fetched live from OpenAlex

Exosomes, small tiny vesicle contains a large number of intracellular particles that employ to cause various diseases and prevent several pathological events as well in the human body. It is considered a "double-edged sword", and depending on its biological source, the action of exosomes varies under physiological conditions. Also, the isolation and characterization of the exosomes should be performed accurately and the methodology also will vary depending on the exosome source. Moreover, the uptake of exosomes from the recipients' cells is a vital and initial step for all the physiological actions. There are different mechanisms present in the exosomes' cellular uptake to deliver their cargo to acceptor cells. Once the exosomal uptake takes place, it releases the intracellular particles that leads to activate the physiological response. Even though exosomes have lavish functions, there are some challenges associated with every step of their preparation to bring potential therapeutic efficacy. So, overcoming the pitfalls would give a desired quantity of exosomes with high purity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.741

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.295
GPT teacher head0.528
Teacher spread0.232 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations10
Published2023
Admission routes1
Has abstractyes

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