BackgroundOne of the main problems in B cell lymphoma treatment is severe adverse effects and low therapeutic efficacy resulting from systemic chemotherapy. A pH-sensitive controlled drug release system based on mesoporous silica nanoparticles was constructed for targeted drug delivery to tumor cells to reduce systemic toxicity and improve the therapeutic efficacy.MethodsIn this study, the doxorubicin (DOX) was filled into the mesopores of the functional MSNs (DMSNs). Furthermore, rituximab was introduced as the targeted motif of functional DMSNs using an avidin-biotin bridging method to evaluate the targetability to tumor cells. Then, the cell viability and apoptosis efficiency after treatment with rituximab-conjugated DMSNs (RDMSNs) were estimated by using CCK-8 assay and flow cytometry, respectively. Additionally, the research in vivo was performed to evaluate the enhanced antitumor efficacy and the minimal toxic side effects of RDMSNs. Also, TUNEL staining assay was employed to explore the mechanism of antitumor effects of RDMSNs.ResultsThis targeted drug delivery system exhibited low premature drug release at a physiological pH and efficient pH-responsive intracellular release under weakly acidic conditions. The in vitro tests confirmed that targeted RDMSNs could selectively adhere to the surface of lymphoma B cells via specific binding with the CD20 antigen and be internalized into CD20 positive Raji cells but few CD20 negative Jurkat cells, which leads to increased cytotoxicity and apoptosis of the DOX in Raji cells due to the release of the entrapped DOX with high efficiency in the slightly acidic intracellular microenvironment. Furthermore, the in vivo investigations confirmed that RDMSNs could efficiently deliver DOX to lymphoma B cells by pH stimuli, thus inducing cell apoptosis and inhibiting tumor growth, while with minimal toxic side effects.ConclusionsThis targeted and pH-sensitive controlled drug delivery system has the potential for promising application to enhance the therapeutic index and reduce the side effects of B cell lymphoma therapy.

An iodine-mediated oxidative ring contraction of cyclobutanols has been developed. The reaction allows the synthesis of a wide range of aryl cyclopropyl ketones under mild and eco-friendly conditions. A variety of functional groups including aromatic or alkyl halides, ethers, esters, ketones, alkenes, and even aldehydes are nicely tolerated in the reaction. This is in contrast with traditional synthetic approaches for which poor functional group tolerance is often a problem. The practicality of the method is also highlighted by the tunability of iodine oxidation system. Specifically, combining the iodine(III) reagent with an appropriate base allows the reaction to accommodate a range of challenging electron-rich arene substrates. The facile scalability of this reaction is also exhibited herein.

The hydrogel demonstrated properties with high stretchability, self-healable and photothermal properties. Notably, photothermal therapy could be established due to its photothermal responsiveness, benefiting infected wound healing.

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Acute myocardial infarction (AMI) is a leading cause of death and disability worldwide. Early diagnosis of AMI and interventional treatment can significantly reduce myocardial damage. However, owing to limitations in sensitivity and specificity, existing myocardial markers are not efficient for early identification of AMI. Transcriptome-wide association studies (TWASs) have shown excellent performance in identifying significant gene–trait associations and several cardiovascular diseases (CVDs). Furthermore, ferroptosis is a major driver of ischaemic injury in the heart. However, its specific regulatory mechanisms remain unclear. In this study, we screened three Gene Expression Omnibus (GEO) datasets of peripheral blood samples to assess the efficiency of ferroptosis-related genes (FRGs) for early diagnosis of AMI. To the best of our knowledge, for the first time, TWAS and mRNA expression data were integrated in this study to identify 11 FRGs specifically expressed in the peripheral blood of patients with AMI. Subsequently, using multiple machine learning algorithms, an optimal prediction model for AMI was constructed, which demonstrated satisfactory diagnostic efficiency in the training cohort (area under the curve (AUC) = 0.794) and two external validation cohorts (AUC = 0.745 and 0.711). Our study suggests that FRGs are involved in the progression of AMI, thus providing a new direction for early diagnosis, and offers potential molecular targets for optimal treatment of AMI.