ReviewNaunyn-Schmiedeberg's archives of pharmacology2025
Advancements in nanotheranostics for glioma therapy.
Review in Naunyn-Schmiedeberg's archives of pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- Application and challenges of smart responsive multifunctional nanoplatforms in integrated diagnosis and treatment of bladder cancer and overcoming therapeutic resistance.Frontiers in oncology · 2026Review
- A Narrative Review of Theranostics in Neuro-Oncology: Advancing Brain Tumor Diagnosis and Treatment Through Nuclear Medicine and Artificial Intelligence.International journal of molecular sciences · 2025Review
- The blood-brain barriers: novel nanocarriers for central nervous system diseases.Journal of nanobiotechnology · 2025Review
- Multidimensional analysis reveals gene expression, cell interactions, and signaling networks in glioma and Alzheimer's disease.Discover oncology · 2025Article
- Multi-Omic Analysis of Glioma Identifies RRM2 as a Prognostic Biomarker Associated With Tumor Stemness and Cell Cycle-Related Pathways.Technology in cancer research & treatmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gliomas are brain tumors mainly derived from glial cells that are difficult to treat and cause high mortality. Radiation, chemotherapy, and surgical excision are the conventional treatments for gliomas. Patients who have surgery or have undergone chemotherapy for glioma treatment have poor prognosis with tumor recurrence. In particular, for glioblastoma, the 5-year average survival rate is 4-7%, and the median survival is 12-18 months. A number of issues hinder effective treatment such as, poor surgical resection, tumor heterogeneity, insufficient drug penetration across the blood-brain barrier, multidrug resistance, and difficulties with drug specificity. Nanotheranostic-mediated drug delivery is becoming a well-researched consideration, and an efficient non-invasive method for delivering chemotherapeutic drugs to the target area. Theranostic nanomedicines, which incorporate therapeutic drugs and imaging agents for personalized therapies, can be used for preventing overdose of non-responders. Through the identification of massive and complicated information from next-generation sequencing, machine learning enables for precise prediction of therapeutic outcomes and post-treatment management for patients with cancer. This article gives a thorough overview of nanocarrier-mediated drug delivery with a brief introduction to drug delivery challenges. In addition, this assessment offers a current summary of preclinical and clinical research on nanomedicines for gliomas. In the future, nanotheranostics will provide personalized treatment for gliomas and other treatable cancers.
Indexed as
Identifiers
39480526What Socratic holds
Registered trials
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.