AIMC Topic: RNA, Messenger

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AI-Validated Brain Targeted mRNA Lipid Nanoparticles with Neuronal Tropism.

ACS nano
Targeting therapeutic nanoparticles to the brain poses a challenge due to the restrictive nature of the blood-brain barrier (BBB). Here we report the development of mRNA-loaded lipid nanoparticles (LNPs) functionalized with BBB-interacting small mole...

Multi-omic assessment of mRNA translation dynamics in liver cancer cell lines.

Scientific data
The limited correlation between mRNA and protein levels within cells highlighted the need to study mechanisms of translational control. To decipher the factors that determine the rates of individual steps in mRNA translation, machine learning approac...

An attention-based mRNA transformer network for accurate prediction of melanoma response to immune checkpoint inhibitors.

Scientific reports
Melanoma immunotherapy urgently requires approaches that can accurately predict drug responses to minimize unnecessary treatments. Deep learning models have emerged as powerful tools in this domain due to their robust predictive capabilities. Integra...

Adipocyte-selective mRNA lipid nanoparticles for cell programming with machine learning analysis.

Journal of controlled release : official journal of the Controlled Release Society
Adipose tissue plays a crucial role in energy metabolism and endocrine signaling. White adipose tissue (WAT), in particular, is a compelling target for therapeutic interventions in metabolic diseases due to its secretory capacity and abundance. Gene ...

NetStart 2.0: prediction of eukaryotic translation initiation sites using a protein language model.

BMC bioinformatics
BACKGROUND: Accurate identification of translation initiation sites is essential for the proper translation of mRNA into functional proteins. In eukaryotes, the choice of the translation initiation site is influenced by multiple factors, including it...

Deep learning-based high-resolution time inference for deciphering dynamic gene regulation from fixed embryos.

Nature communications
Embryo development is driven by the spatiotemporal dynamics of complex gene regulatory networks. Uncovering these dynamics requires simultaneous tracking of multiple fluctuating molecular species over time, which exceeds the capabilities of tradition...

Multi-transcriptomics predicts clinical outcome in systemically untreated breast cancer patients with extensive follow-up.

Breast cancer research : BCR
BACKGROUND: Prognostic tools for determining patients with indolent breast cancers (BCs) are far from optimal, leading to extensive overtreatment. Several studies have demonstrated mRNAs, lncRNAs and miRNAs to have prognostic potential in BC. Because...

Integrated Nanopore and short-read RNA sequencing identifies dysregulation of METTL3- m6A modifications in endocrine therapy- sensitive and resistant breast cancer cells.

Functional & integrative genomics
The role of epitranscriptomic changes in the development of acquired endocrine therapy (ET)- resistance in estrogen receptor α (ER) expressing breast cancer (BC) is unknown. We tested the hypothesis that inhibition of METTL3, the methyltransferase re...

Decoding the diagnostic biomarkers of mitochondrial dysfunction related gene variants in pediatric T cell acute lymphoblastic leukemia.

Scientific reports
Mitochondrial dysfunction is crucial in the pathogenesis and drug resistance of pediatric T-cell acute lymphoblastic leukemia (T-ALL), a malignant hematological disorder with unrestrained proliferation of immature T-cells. Therefore, the primary obje...

Identification of key genes associated with cellular aging and mitochondria in acute myocardial infarction.

Scientific reports
Acute myocardial infarction (AMI) poses a significant global mortality burden. Utilizing bio informatics, this study explored cellular aging-related genes (CARGs) and mitochondrial-related genes (MRGs). in AMI Public AMI datasets were analyzed using ...