Evidence map›Paper›PMID 40935865›Full record

ArticleScientific reports2025

Raloxifene solubility in supercritical CO

Hadil Faris Alotaibi, Chou-Yi Hsu, Fadhil Faez Sead, Anupam Yadav, S Renuka Jyothi, Swati Mishra, Bilakshan Purohit, Anorgul Ashirova, Islom Khudayberganov, Ashish Singh Chauhan

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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

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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

10 authors.

Hadil Faris AlotaibiDepartment of Pharmaceutical Sciences, College of Pharmacy, Princess Nourah Bint AbdulRahman University, Riyadh, 11671, Saudi Arabia. Hfalotaibi@pnu.edu.sa.
Chou-Yi HsuThunderbird School of Global Management, Arizona State University Tempe Campus, Phoenix, AZ, 85004, USA.
Fadhil Faez SeadDepartment of Dentistry, College of Dentistry, The Islamic University, Najaf, Iraq.
Anupam YadavDepartment of Computer engineering and Application, GLA University, Mathura, 281406, India.
S Renuka JyothiDepartment of Biotechnology and Genetics, School of Sciences, JAIN (Deemed to be University), Bangalore, Karnataka, India.
Swati MishraDepartment of Pharmacology, IMS and SUM Hospital, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, 751003, Odisha, India.
Bilakshan PurohitCentre for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, 140401, Punjab, India.
Anorgul AshirovaDepartment of General Professional Sciences, Mamun University, Khiva, Uzbekistan.
Islom KhudayberganovDepartment of Chemistry, Urgench State University, Urgench, Khorezm Region, Uzbekistan.
Ashish Singh ChauhanDivision of research and innovation, Uttaranchal Institute of Pharmaceutical Sciences, Uttaranchal University, Dehradun, Uttarakhand, India.

Funding

Princess Nourah Bint Abdulrahman University PNURSP2025R205
6 · The paper itself

Abstract

One of the problems with new medications is their poor water solubility that is possible to be addressed by using supercritical method. This study aims to predict the solubility of raloxifene and the density of supercritical CO

Indexed as

Carbon DioxideMachine LearningRaloxifene HydrochlorideNanoparticlesSolubilityCarbon DioxideRaloxifene HydrochlorideDrug computationExtra treesGradient boostingMachine learningProcess modelingRandom forestSolubility

Identifiers

PMID40935865
PMCPMC12426225

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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.