Evidence map›Paper›PMID 40628807›Full record

ArticleScientific reports2025

A branching bivariate weibull distribution model for evaluating exosomes in androgen-deprived agency in the presence of prostate cancer.

M Shanmugavalli, K Majella Jenvi Ignatia, Mary Jiny D, Raman Kumar, Ashok Kumar Bishoyi, S Renuka Jyothi, Harpreet Kaur Channi, Abhijit Bhowmik, Jasmina Lozanović

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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, 1 synthesis or guideline pooled it.

  1. Pooled it
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.

M ShanmugavalliDepartment of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, SIMATS University, Chennai, Tamil Nadu, 602105, India.
K Majella Jenvi IgnatiaDepartment of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, SIMATS University, Chennai, Tamil Nadu, 602105, India.
Mary Jiny DDepartment of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, SIMATS University, Chennai, Tamil Nadu, 602105, India.
Raman KumarDepartment of Mechanical and Production Engineering, Guru Nanak Dev Engineering College, Ludhiana, Punjab, 141006, India.ORCID http://orcid.org/0000-0003-2934-7609
Ashok Kumar BishoyiDepartment of Microbiology, Marwadi University Research Center, Faculty of Science, Marwadi University, Rajkot, Gujarat, 360003, India.
S Renuka JyothiDepartment of Biotechnology and Genetics, School of Sciences, JAIN (Deemed to be University), Bangalore, Karnataka, India.
Harpreet Kaur ChanniDepartment of Electrical Engineering, Chandigarh University, Mohali, 140413, India.ORCID http://orcid.org/0000-0002-9059-8821
Abhijit BhowmikDepartment of Mechanical Engineering, Graphic Era (Deemed to be University), Clement Town, Dehradun, 248002, India.ORCID http://orcid.org/0000-0001-9409-0972
Jasmina LozanovićDepartment of Engineering, FH Campus Wien - University of Applied Sciences, Favoritenstraße 226, 1100, Vienna, Austria. jasmina.lozanovic@fh-campuswien.ac.at.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Castration-resistant prostate cancer (CRPC) poses a significant challenge in the medical field. The study developed a novel model, the branching bivariate Weibull distribution (BBWD), tailored to address CRPC and stems from the maximum likelihood estimation (MLE) function. It considers a medicinal biosystem aimed at transitioning androgen-dependent prostate cancer into an androgen-independent state. The BBWD model is designed to optimize the solution for bio variables pertinent to CRPC and evaluate various treatment techniques for androgen-dependent and androgen-independent behaviour. Through rigorous analysis, the kinetics of LINC01213 in androgen-deprived mediums are highlighted as promising, showing superior efficacy in castration compared to other techniques. The model utilizes the joint effect on the log-likelihood function (JELF) as a crucial analytical tool to assess the impact of LINC01213 in both normal and androgen-deprived medium. The results affirm the veracity of statements made within the medical field and support the notion that LINC01213 may serve as a novel therapeutic target for CRPC patients. The analysis underscores the pivotal role of exosomal LINC01213 in androgen-dependent prostate cancer, demonstrating its significance in treatment efficacy. The BBWD model highlighting the efficacy of LINC01213 in androgen-deprived mediums provides compelling evidence for its potential as a therapeutic target. This study corroborates existing medical hypotheses and offers detailed clarification and reports on treatment techniques for prostate cancer patients. Ultimately, it emphasizes the critical role of exosomal LINC01213 in addressing the challenges posed by androgen-dependent prostate cancer, offering a pathway toward more effective treatments.

Indexed as

AndrogensExosomesProstatic NeoplasmsProstatic Neoplasms, Castration-ResistantRNA, Long NoncodingHumansLikelihood FunctionsMaleAndrogensRNA, Long NoncodingAndrogen deprived mediumBranching bivariate Weibull distribution (BBWD)ExosomesLog-likelihood functionMaximum likelihood estimation function (MLE)Prostate cancer

Identifiers

PMID40628807
PMCPMC12238568

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.