ReviewNaunyn-Schmiedeberg's archives of pharmacology2023
A critical review on therapeutic approaches of CRISPR-Cas9 in diabetes mellitus.
Review in Naunyn-Schmiedeberg's archives of pharmacology, 2023. 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, 7 citations in OpenAlex.
- The Role of Gene Therapy and RNA-Based Therapeutic Strategies in Diabetes.International journal of molecular sciences · 2025Review
- Review
- Genome-edited rabbits: Unleashing the potential of a promising experimental animal model across diverse diseases.Zoological research · 2024Review
- Therapeutic potential of adiponectin in prediabetes: strategies, challenges, and future directions.Therapeutic advances in endocrinology and metabolism · 2024Review
- Understanding Type 2 Diabetes Mellitus Risk Parameters through Intermittent Fasting: A Machine Learning Approach.Nutrients · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetes mellitus (D.M.) is a common metabolic disorder caused mainly by combining two primary factors, which are (1) defects in insulin production by the pancreatic β-cells and (2) responsiveness of insulin-sensitive tissues towards insulin. Despite the rapid advancement in medicine to suppress elevated blood glucose levels (hyperglycemia) and insulin resistance associated with this hazard, a demand has undoubtedly emerged to find more effective and curative dimensions in therapeutic approaches against D.M. The administration of diabetes treatment that emphasizes insulin production and sensitivity may result in unfavorable side effects, reduced adherence, and potential treatment ineffectiveness. Recent progressions in genome editing technologies, for instance, in zinc-finger nucleases, transcription activator-like effector nucleases, and clustered regularly interspaced short palindromic repeat (CRISPR-Cas)-associated nucleases, have greatly influenced the gene editing technology from concepts to clinical practices. Improvements in genome editing technologies have also opened up the possibility to target and modify specific genome sequences in a cell directly. CRISPR/Cas9 has proven effective in utilizing ex vivo gene editing in embryonic stem cells and stem cells derived from patients. This application has facilitated the exploration of pancreatic beta-cell development and function. Furthermore, CRISPR/Cas9 enables the creation of innovative animal models for diabetes and assesses the effectiveness of different therapeutic strategies in treating the condition. We, therefore, present a critical review of the therapeutic approaches of the genome editing tool CRISPR-Cas9 in treating D.M., discussing the challenges and limitations of implementing this technology.
Indexed as
Identifiers
What 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.