Simultaneous Protein Colorful Imaging via Raman Signal Classification.

Protein imaging aids diagnosis and drug development by revealing protein-drug interactions or protein levels. However, the challenges of imaging multiple proteins, reduced sensitivity, and high reliance on specific protein properties such as Raman peaks or refractive index hinder the understanding. Here, we introduce multiprotein colorful imaging through Raman signal classification. Our method utilized machine learning-assisted classification of Raman signals, which are the distinctive features of label-free proteins. As a result, three types of proteins could be imaged simultaneously. In addition, we could quantify individual proteins from a mixture of multiple proteins over a wide detection range (10 fg/mL-1 µg/mL). These results showed a 1000-fold improvement in sensitivity and a 30-fold increase in the upper limit of detection compared to existing methods. These advances will enhance our understanding of biology and facilitate the development of disease diagnoses and treatments.

Dose Calculation Accuracy of Beam Models in RadCalc for a 1.5 T MR-Linac.

The purpose of this study is to evaluate RadCalc, an independent dose verification software, for patient-specific quality assurance (PSQA) in online adaptive planning with a magnetic resonance linear accelerator (MR-linac) of a 1.5 T. Version 7.1.4 of RadCalc to introduce the capability to establish a beam model that incorporates MR field characteristics. A total of six models were established, with one using manufacturer-provided data and the others differing in percentage depth dose (PDD) data sources. Overall, two models utilized PDD data from the treatment planning system (TPS), and three used commissioned PDD data from gantry angles of 0° and 270°. Simple tests on a virtual water phantom assessed dose-calculation accuracy, revealing percentage differences ranging from -0.5% to -20.6%. Excluding models with significant differences, clinical tests on 575 adaptive plans (prostate, liver, and breast) showed percentage differences of -0.51%, 1.12%, and 4.10%, respectively. The doses calculated using RadCalc demonstrated similar trends to those of the PSQA-based measurements. The newly released version of RadCalc enables beam modeling that considers the characteristics of the 1.5 T magnetic field. The accuracy of the software in calculating doses at 1.5 T magnetic fields has been verified, thereby making it a reliable and effective tool for PSQA in adaptive plans.

Charge-Based Isolation of Extracellular Vesicles from Human Plasma.

Extracellular vesicles (EVs) have garnered significant attention due to their potential applications in disease diagnostics and management. However, the process of isolating EVs, primarily from blood samples, is still suboptimal. This is mainly attributed to the abundant nature of soluble proteins and lipoproteins, which are often separated together with EVs in the end products of conventional isolation methods. As such, we devise a single-step charge-based EV isolation method by utilizing positively charged beads to selectively remove negatively charged major impurities from human plasma via electrostatic interaction. By carefully controlling the buffer pH, we successfully collected EVs from undesired plasma components with superior purity and yield compared to conventional EV collection methods. Moreover, the developed process is rapid, taking only about 20 min for overall EV isolation. The charge-based isolation can ultimately benefit the EV-based liquid biopsy field for the early diagnosis of various diseases.

Targeted delivery of anti-miRNA21 sensitizes PD-L1high tumor to immunotherapy by promoting immunogenic cell death.

Rationale: Growing evidence has demonstrated that miRNA-21 (miR-21) upregulation is closely associated with tumor pathogenesis. However, the mechanisms by which miR-21 inhibition modulates the immunosuppressive tumor microenvironment (TME) and improves tumor sensitivity to immune checkpoint blockade therapies remain largely unexplored. In this study, we demonstrate the precise delivery of anti-miR-21 using a PD-L1-targeting peptide conjugate (P21) to the PD-L1high TME. Methods: Investigating miR-21 inhibition mechanisms involved conducting quantitative real-time PCR, western blot, flow cytometry, and confocal microscopy analyses. The antitumor efficacy and immune profile of P21 monotherapy, or combined with anti-PD-L1 immune checkpoint inhibitors, were assessed in mouse models bearing CT26.CL25 tumors and 4T1 breast cancer. Results Inhibition of oncogenic miR-21 in cancer cells by P21 efficiently activates tumor suppressor genes, inducing autophagy and endoplasmic reticulum stress. Subsequent cell-death-associated immune activation (immunogenic cell death) is initiated via the release of damage-associated molecular patterns. The in vivo results also illustrated that the immunogenic cell death triggered by P21 could effectively sensitize the immunosuppressive TME. That is, P21 enhances CD8+ T cell infiltration in tumor tissues by conferring immunogenicity to dying cancer cells and promoting dendritic cell maturation. Meanwhile, combining P21 with an anti-PD-L1 immune checkpoint inhibitor elicits a highly potent antitumor effect in a CT26.CL25 tumor-bearing mouse model and 4T1 metastatic tumor model. Conclusions: Collectively, we have clarified a miR-21-related immunogenic cell death mechanism through the precise delivery of anti-miR-21 to the PD-L1high TME. These findings highlight the potential of miR-21 as a target for immunotherapeutic interventions.