Hoshi University

Reactive oxygen species and reactive nitrogen species play roles in the pathogenesis of numerous diseases, but their presence is often assessed indirectly via analysis of specific biomarkers. Tyrosine-derived compounds such as ortho-tyrosine, meta-tyrosine, 3-chlorotyrosine, and 3-nitrotyrosine are considered markers of oxidative and nitrosative stress. However, these biomarkers are typically present in extremely low concentrations (in the low nanomolar range) and have structural isomers, making accurate quantification challenging. The aim of this study was to improve the sensitivity and chromatographic separation of these analytes using various commercially available derivatization reagents targeting amino groups. Selected reaction monitoring transitions were optimized by flow injection analysis of derivatized standards, and structural isomers were evaluated using LC-MS/MS. A Box-Behnken design and response surface methodology were employed to determine the optimal derivatization conditions for each reagent. Among the reagents tested, diethyl ethoxymethylenemalonate was most effective, enabling complete isomer separation and approximately 1000-fold signal enhancement compared with non-derivatized analytes, with a limit of quantification reaching 5 nM. The results of this study highlight the importance of selecting an appropriate derivatization strategy for sensitive and selective quantification of tyrosine-based biomarkers and offer a promising approach for the accurate assessment of oxidative and nitrosative stress in biological samples.

This systematic review aimed to evaluate the effectiveness of narrative-based interventions in correcting health-related misinformation and to identify key message-related, sender-related, and recipient-related factors influencing their success.

A comprehensive literature search was conducted in databases including PubMed, CINAHL, PsycINFO, Academic Search Complete, Communication Abstracts, and Web of Science. Eligible studies included quantitative intervention studies examining the impact of narrative-based corrections on health-related misinformation.

Twenty studies covering topics such as COVID-19, vaccination, tobacco use, and e-cigarette use were included. Among the 16 studies comparing narrative and nonnarrative corrections, only four showed that narratives were significantly more effective in reducing misinformation-related beliefs than other message types. Several factors influenced narrative effectiveness. Message-related factors include emotional language, social framing, and message sidedness. Sender-related factors, such as the credibility of the source and relational closeness with recipients, also affected outcomes. Recipient-related factors, including cognitive style, political ideology, and social media use motivation, moderated the intervention effects. Some studies have reported unintended backfire effects in which narratives reinforce misinformation.

Narrative-based corrections show the potential for addressing health-related misinformation; however, their effectiveness remains inconsistent. The variability in narrative design, media platforms, and insufficient theoretical grounding may explain these mixed results. Future research should focus on theoretically informed narratives and systematically examine the influencing factors to optimize misinformation correction strategies.

The effectiveness of narrative-based corrections on health misinformation depends on thoughtful design grounded in theoretical principles such as transportation, identification, and exemplification. Health communicators should consider narrative length, depth, and emotional content and adapt messages to different platforms (e.g., social media). Tailoring interventions to audience characteristics, such as cognitive styles and prior beliefs, can further enhance efforts to correct misinformation.

Gastric cancer with peritoneal metastasis is associated with a poor prognosis. Current treatments, including the first-line therapy of combination chemotherapy with nivolumab for advanced recurrent gastric cancer, have shown limited efficacy against peritoneal dissemination. In this study, we evaluated neoantigen (neoAg)-mRNA lipid nanoparticle (LNP) as a potential agent in combination with anti-PD-1 therapy, focusing on its effects on neoAg-specific CD8+ T cell responses and antitumor efficacy in a murine gastric cancer model.

The mRNA, comprising a tandem minigene encoding three neoAgs identified from the murine gastric cancer YTN16 cell line, was synthesized by in vitro transcription and encapsulated within LNPs. NeoAg-specific CD8+ T cells in the spleens and tumors were assessed by flow cytometry. The antitumor efficacy of the neoAg-mRNA-LNP vaccine, alone or in combination with anti-PD-1 antibody, was evaluated in both subcutaneous and peritoneal metastasis models of YTN16.

The neoAg-mRNA-LNP vaccine induced significantly higher frequencies of neoAg-specific CD8+ T cells than the neoAg-dendritic cell vaccine, confirming its enhanced immunogenicity. NeoAg-mRNA-LNP vaccination led to robust tumor regression, achieving complete eradication in all treated mice, especially when combined with anti-PD-1 therapy. This effect was associated with an increase in neoAg-specific progenitor-exhausted and intermediate-exhausted CD8+ T cells. In a peritoneal metastasis model, neoAg-mRNA-LNP monotherapy prevented peritoneal dissemination when administered prophylactically, and combination therapy with anti-PD-1 effectively suppressed tumor growth in a therapeutic setting.

NeoAg-mRNA-LNP vaccines elicit potent neoAg-specific CD8+ T cell responses and show enhanced antitumor efficacy with anti-PD-1 therapy in gastric cancer with peritoneal metastasis.