The Innovation最新文献

Nutrients from dietary foods not only provide energy and building blocks, but also play critical roles in modulating diverse pathophysiological functions. They achieve these, in part, by accelerating cell signaling transduction processes via modulating various types of protein post-translational modifications (PTMs). Notably, accumulating evidence has identified palmitic acid (PA), a major component of high-fat diets, as a significant contributor to various human disorders, including diabetes and cancer. Hence, further understanding the roles of PA and its involvement in protein palmitoylation, a key PTM, is crucial for uncovering the mechanisms underlying these diseases and exploring potential clinical applications in cancer therapy. This review comprehensively summarizes recent advances in the understanding of PA homeostasis and palmitoylation in tumorigenesis. Specifically, it highlights the connections between palmitoylation and key processes such as oncogenic signaling pathways, cell death mechanisms, innate immune responses, and the tumor microenvironment. The review also emphasizes potential therapeutic strategies, including targeting PA homeostasis, palmitoylation-associated processes, or specific palmitoylated proteins for cancer treatment. Finally, the challenges in the field, such as the regulation of PA homeostasis and the dynamic detection or targeting of palmitoylation, are discussed, underscoring the need for further research to address these critical issues.

Treating osteoarthritis (OA) presents a significant challenge due to the fact that conventional intra-articular injections only achieve superficial penetration and uncontrolled drug release. Here, the amino-modified cationic mesoporous silica nanoparticles were covalently conjugated with cartilage-targeted peptides to form a Trojan horse-like architecture for enveloping the prochondrogenic fucoidan. The hydrogel microsphere, consisting of photocurable GelMA and ChSMA, were fabricated using a microfluidic platform for cargo delivery. The cationic targeting nanoparticle-hydrogel microsphere@fucoidan (CTNM@FU) possess three-step programmable characteristics that enable responsive transport toward injured cartilage, effective penetration of the cartilage matrix and selective entry into chondrocytes, escape from lysosomes, and release of bio-activators. The impaired cartilage metabolism was significantly reversed upon co-culturing with CTNM@FU. Intra-articular administration of CTNM@FU not only mitigated cartilage degeneration but also expedited de novo cartilage formation. Mechanistically, CTNM@FU protected cartilage by activating SIRT3, enhancing mitochondrial energy and countering aging. Collectively, a spatiotemporally guided strategy enables more precise treatments for degenerative joint disorders.

With widespread public attention to long-duration energy storage technologies, redox flow batteries are attracting increasing interests of researchers due to their intrinsic safety and good design flexibility. Currently, high capital costs are constraining the widespread commercialization of this system, which calls for the further enhancement of the output performance in its power units. The power output in a redox flow battery is greatly influenced by macro-to-micro mass transport and electrochemical reactions, which are coupled with each other and together determine the performance of the battery. Therefore, exploring how to achieve a coupled enhancement of transport and electrochemical properties rather than focusing solely on one aspect is a current area of interest. This perspective emphasizes the importance of simultaneously enhancing the transport and electrochemical properties of flow batteries and points out the challenges in this regard.

Artificial intelligence (AI)-assisted approaches are powerful means for advancing catalyst design, as they can significantly accelerate the development of novel catalysts. However, the underlying mechanisms of these approaches often remain elusive, which may lead to unreliable results due to a lack of clear understanding of the involved processes. Herein, we present an AI strategy that combines machine learning (ML) and data mining (DM) to identify high-performance catalysts while elucidating the key factors that govern catalytic performance in complex reactions. Applying this AI strategy to evaluate the electrocatalytic oxygen reduction performance of 10,179 single-atom catalysts (SACs), we identified several high-performance SACs and determined the critical influencers of their activity. Experimental validations further confirm the effectiveness of the AI strategy, with the optimal target Co-S₂N₂/g-SAC achieving a high half-wave potential of 0.92 V. This AI-assisted approach significantly enhances the transparency and reliability of data-driven discoveries, providing new insights that benefit the rational design of materials.

In this single-arm, phase 2 study, we explored the efficacy and safety of hepatic arterial infusion chemotherapy (HAIC) combined with anlotinib and TQB2450 (an anti-PD-L1 antibody) as a postoperative adjuvant treatment in patients at high risk of hepatocellular carcinoma (HCC) recurrence. Patients with high-risk recurrence of HCC were treated with HAIC, anlotinib (4 or 8 cycles), and TQB2450 after curative surgery. The primary endpoint was disease-free survival (DFS), and the secondary endpoints included overall survival (OS) and safety. 77 patients who met the inclusion criteria were enrolled: 38 in the 4-cycle cohort and 39 in the 8-cycle cohort. As of the data cutoff on June 24, 2024, the median follow-up period was 21.19 months (95% confidence interval [CI], 20.49-21.89). The median DFS and OS of all patients were not reached. 1-year and 2-year DFS rates were 84.4% and 65.8%, respectively, while 1-year and 2-year OS rates were 96.1% and 89.8%, respectively. No significant differences in DFS and OS were observed in patients treated with 4 or 8 cycles of anlotinib. The incidence of grade 3/4 adverse events (AEs) was 28.6%. Postoperative adjuvant HAIC combined with anlotinib and TQB2450 demonstrated encouraging clinical benefits in reducing recurrence with manageable toxicities in patients at high risk of HCC recurrence. 4-cycle anlotinib combined with HAIC and TQB2450 is recommended as an adjuvant treatment for further investigation.

Atomically thin two-dimensional membranes are promising for osmotic energy generation. However, the trade-off between permeability and selectivity remains a long-standing bottleneck. Herein, we demonstrate that a cationic AB-stacking covalent-organic framework (COF) bilayer achieves high ion conductivity and selectivity. Through precise molecular design and the Langmuir-Blodgett (LB) technique, we fabricate an anion-selective COF bilayer (EB-COF) using tetradentate 4,4',4″,4'''-(porphyrin-5,10,15,20-tetrayl)tetrabenzaldehyde (TFPP) and bidentate ethidium bromide (EB) with a covalently tethered pyridinium moiety. The EB-COF bilayer shows a record-high output power density of 7,174 W m^-2 (0.5/0.01 M NaCl), significantly outperforming the AA-stacking PDA-COF bilayer constructed with TFPP and neutral p-phenylenediamine (PDA). This exceptional performance stems from highly ordered sub-2-nm nanopores, exceptional pore utilization efficiency, and a large surface charge density of 4.4 mC m^-2, which together synergistically enhance anion selectivity and ion permeability. This work not only provides fundamental insights into the structure-performance relationship of permselective membranes but also offers a promising strategy for high-efficiency osmotic energy harvesting.