mRNA therapies: Pioneering a new era in rare genetic disease treatment.

Rare genetic diseases, often referred to as orphan diseases due to their low prevalence and limited treatment options, have long posed significant challenges to our medical system. In recent years, Messenger RNA (mRNA) therapy has emerged as a highly promising treatment approach for various diseases caused by genetic mutations. Chemically modified mRNA is introduced into cells using carriers like lipid-based nanoparticles (LNPs), producing functional proteins that compensate for genetic deficiencies. Given the advantages of precise dosing, biocompatibility, transient expression, and minimal risk of genomic integration, mRNA therapies can safely and effectively correct genetic defects in rare diseases and improve symptoms. Currently, dozens of mRNA drugs targeting rare diseases are undergoing clinical trials. This comprehensive review summarizes the progress of mRNA therapy in treating rare genetic diseases. It introduces the development, molecular design, and delivery systems of mRNA therapy, highlighting their research progress in rare genetic diseases based on protein replacement and gene editing. The review also summarizes research progress in various rare disease models and clinical trials. Additionally, it discusses the challenges and future prospects of mRNA therapy. Researchers are encouraged to join this field and collaborate to advance the clinical translation of mRNA therapy, bringing hope to patients with rare genetic diseases.

Cross-Modal Prostate Cancer Segmentation via Self-Attention Distillation.

The automatic and accurate segmentation of the prostate cancer from the multi-modal magnetic resonance images is of prime importance for the disease assessment and follow-up treatment plan. However, how to use the multi-modal image features more efficiently is still a challenging problem in the field of medical image segmentation. In this paper, we develop a cross-modal self-attention distillation network by fully exploiting the encoded information of the intermediate layers from different modalities, and the generated attention maps of different modalities enable the model to transfer significant and discriminative information that contains more details. Moreover, a novel spatial correlated feature fusion module is further employed for learning more complementary correlation and non-linear information of different modality images. We evaluate our model in five-fold cross-validation on 358 MRI images with biopsy confirmed. Without bells and whistles, our proposed network achieves state-of-the-art performance on extensive experiments.

Construction of an integrated multi-layer textile for solar-driven steam generation.

Solar steam generation has widespread application in wastewater treatment, seawater desalination, liquid-liquid separation, and other fields, providing potential opportunities for producing fresh water. Up until now, most researchers in this field focused on enhancing the evaporation rate of the solar steam generation device. However, problems in terms of its portability and flexibility still exist when it comes to real application scenarios. Herein, we propose a novel, to the best of our knowledge, integrated multi-layer textile composed of reduced graphene oxide/cotton (RGO/cotton) fabric, cotton yarn, and polypropylene (PP) fabric for solar-driven steam generation. The evaporation rate obtained by the integrated multi-layer textile as prepared is ${0.83}\;{{\rm kg\cdot m}^{- 2}}\cdot{{\rm h}^{- 1}}$ under one sun solar radiation, which is 3.16 times higher than that of blank experiment and is superior to many previously reported works. Its remarkable evaporation performance is mainly attributed to the inherent multi-layer structures, where porous RGO/cotton fabric exhibits ultra-water vapor permeability, hydrophilic cotton yarn supplies water continuously, and low-density hydrophobic PP fabric hinders heat sustainably. Based on the results of application performance evaluation, the integrated multi-layer textile with scalable manufacturability, portability, durability, and flexibility is expected to boost the development of solar-driven steam generation.