Aug 2026· Bioengineering & Translational Medicine· pp.
e70163
· 0 citations
Medicine
TL;DR
New insights into the precision treatment of endometrial cancer are provided by developing engineered, multifunctional, exosome-based therapeutic drugs that combine mechanism precision and translational feasibility in tumor treatment.
Abstract
Therapeutic challenges in endometrial carcinoma (EC) arise from the limited efficacy and toxicity of current treatments. Although exosome-based RNA interference shows promise, its clinical translation is hindered by inefficient cargo loading, low yields, and poor tumor targeting. We have engineered an exosome platform (cRGD-ExoM) that integrates the following innovations: Firstly, RNA motifs enable the enrichment of shRNA loading by over 80-fold for targeting of ferroptosis regulators (glutathione peroxidase 4/ferroptosis suppressor protein 1/ferritin heavy chain [GPX4/FSP1/FTH]). Secondly, Rab4 silencing amplifies exosome biogenesis via dysregulated endosomal recycling, enhancing tumor cell uptake by impairing endosome maturation-a dual-action mechanism that boosts both production and delivery. Thirdly, cRGD peptides confer αvβ3-integrin-specific targeting. cRGD-ExoM induces potent ferroptosis by increasing lipid peroxidation and downregulating GPX4/FSP1/FTH, significantly suppressing EC tumor growth in vivo without causing systemic toxicity. The platform's modular design allows for spatiotemporal control of loading, production, and targeting, demonstrating its scalability. This study provides new insights into the precision treatment of endometrial cancer by developing engineered, multifunctional, exosome-based therapeutic drugs that combine mechanism precision and translational feasibility in tumor treatment.
This study constructed a pH-responsive P-TN/SF@Fe-Cur composite coating that demonstrated significant anti-infective, anti-inflammatory, antioxidant, pro-angiogenic, and pro-osteogenic effects in rat subcutaneous infection and femoral defect models.
The results show that alternative transcript diversity extensively enters translation-supported proteoform space and establish a systematic link between transcript variation and protein functional diversification.
Felicia T. Jiang, Dengwang Chen, Ziwei Wang et al.· bioRxiv· 1 citation
Protein therapeutic design and property prediction are frequently hampered by data scarcity. Here we propose a model, DyAb, that addresses these issues by leveraging a pair-wise representation to predict differences in binding affinity, rather than absolute values. DyAb is built on top of a pre-trained protein language model and achieves a Spearman rank correlation of up to 0.85 on binding affinity prediction across monoclonal antibodies targeting three different antigens (EGFR, IL-6, and an internal target), given as few as 100 training data. We employ DyAb in two design contexts: as a ranking model to score combinations of known mutations, and combined with a genetic algorithm to generate new sequences. Our method consistently generates antibody variants with high binding rates, including designs that improve on the binding affinity of the lead molecule by more than ten-fold. DyAb represents a powerful tool for optimizing antibody binding affinity in low data regimes common in early-stage drug development.
Joshua Yao-Yu Lin, Jennifer L. Hofmann, Andrew Leaver‐Fay et al.· mAbs· 1 citation
Due to its importance and wide adoption, wheat cultivation is promptly required to shift towards sustainable practices, reducing the dependency on chemical components. Among bio-based solutions aimed at securing the sustainability of wheat cultivation, biostimulants offer a versatile platform of eco-friendly tools assuring sustainability and profitability. Microalgae present a concrete example of a biostimulant source due to their richness in metabolites and high value products. Therefore, this study evaluated the biostimulant potential of eleven eco-extracts prepared from soil-isolated microalgae strains. Eco-extracts applied via soil drench at low dose (0.1 g/L) were investigated for their biostimulant effects on wheat growth, physiology, yield, and quality under controlled conditions. Results demonstrated significant ameliorations in treated plants as compared to the control, with no phytoinhibitory effects. Remarkable enhancements were notable in growth parameters such as shoot and root lengths (+40-70%), physiological traits such as total chlorophyll and stomatal conductance (+7-52%), yield components in the example of grain number per spike and thousand grain weight (+17-103%), and grain quality namely protein and polyphenol content (+2-fold to 4-fold). Similarly, phosphorus accumulation and uptake were significantly improved, while soil physicochemical status was ameliorated, indicating enhanced fertility. Multivariate analysis and composite index ranking marked Chlorella sp. GA18, Chlorella sp. GA65, Scenedesmus sp. GA69, and Chlorococcum sp. GA63 as eco-extracts with consistent performances across all plant traits. These findings highlighted the promising potential of integrating microalgae-based eco-friendly extracts in sustainable wheat cultivation.
Amer Chabili, Z. Hakkoum, F. Minaoui et al.· Plant Science· 1 citation
ProteinReasoner is developed, a multimodal generative protein foundation model that sequentially connects amino acid sequence, evolutionary constraints and three-dimensional structure within a shared autoregressive architecture and suggests a general route towards reasoning across interdependent representations in other scientific domains.
Chaozhong Liu, Linlin Chao, Shaomin Ji et al.· bioRxiv· 1 citation
HydroGym is introduced, a solver-independent reinforcement learning platform providing more than 60 validated, openly available flow control environments spanning from canonical laminar flows to complex turbulent flows, with systematic progression in the Reynolds number up to Re = 4 × 105, and Mach number variations in two and three dimensions.
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