Evidence map›Paper›PMID 38155321›Full record

ReviewBiotechnology letters2024

Aptamer-functionalized MOFs and AI-driven strategies for early cancer diagnosis and therapeutics.

Abhishek Futane, Pramod Jadhav, Abu Hasnat Mustafa, Arthi Srinivasan, Vigneswaran Narayanamurthy

Open access · bronzeAbstract readReview
PubMed Publisher
In one paragraph

Review in Biotechnology letters, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

4 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Review
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

5 authors at 2 institutions in 2 countries.

Abhishek FutaneDepartment of Engineering Technology, Faculty of Electronics and Computer Technology & Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100, Durian Tunggal, Melaka, Malaysia.
Pramod JadhavFaculty of Civil Engineering Technology, Universiti Malaysia Pahang (UMP) Lebuhraya Tun Razak, 26300, Gambang, Kuantan, Pahang, Malaysia.
Abu Hasnat MustafaFaculty of Industrial Science and Technology, Universiti Malaysia Pahang, 26300, Gambang, Pahang, Malaysia.
Arthi SrinivasanFaculty of Chemical and Process Engineering Technology, University Malaysia Pahang (UMP), Lebuhraya Tun Razak, 26300, Gambang, Kunatan, Pahang, Malaysia.
Vigneswaran NarayanamurthyDepartment of Engineering Technology, Faculty of Electronics and Computer Technology & Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100, Durian Tunggal, Melaka, Malaysia. vigneswaran@utem.edu.my.ORCID http://orcid.org/0000-0001-6076-0106
Universiti Malaysia Pahang Al-Sultan Abdullah · MYTechnical University of Malaysia Malacca · MY

Funding

Universiti Teknikal Malaysia Melaka (UTeM) Zamalah Scheme
6 · The paper itself

Abstract

Metal-Organic Frameworks (MOFs) have exceptional inherent properties that make them highly suitable for diverse applications, such as catalysis, storage, optics, chemo sensing, and biomedical science and technology. Over the past decades, researchers have utilized various techniques, including solvothermal, hydrothermal, mechanochemical, electrochemical, and ultrasonic, to synthesize MOFs with tailored properties. Post-synthetic modification of linkers, nodal components, and crystallite domain size and morphology can functionalize MOFs to improve their aptamer applications. Advancements in AI and machine learning led to the development of nonporous MOFs and nanoscale MOFs for medical purposes. MOFs have exhibited promise in cancer therapy, with the successful accumulation of a photosensitizer in cancer cells representing a significant breakthrough. This perspective is focused on MOFs' use as advanced materials and systems for cancer therapy, exploring the challenging aspects and promising features of MOF-based cancer diagnosis and treatment. The paper concludes by emphasizing the potential of MOFs as a transformative technology for cancer treatment and diagnosis.

Indexed as

Metal-Organic FrameworksNeoplasmsArtificial IntelligenceCatalysisHumansPhotosensitizing AgentsMetal-Organic FrameworksPhotosensitizing AgentsAptamersEarly-stage cancer treatmentMOFsNanoparticles

Identifiers

PMID38155321
OpenAlexW4390331228

What OpenQuestion holds

Textmetadata
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.