https://ir.ymlib.yonsei.ac.kr/handle/22282913/181701 2026-06-16T04:30:42Z https://ir.ymlib.yonsei.ac.kr/handle/22282913/211761 Title: A transferable SARS-CoV-2 IRES module enables dual translation initiation for enhanced antigen expression in COVID-19 mRNA vaccines Authors: Seo, Han Young; Jung, Haewon; Lee, Se-Young; Jung, Hae-Gwang; Son, Yu-Min; Bak, Yeonju; Hwang, Seo-Yeon; Kim, Jung-Hee; Park, In Ho; Shin, Jeon-Soo; Oh, Jong-Won Abstract: mRNA vaccines are a versatile platform for infectious disease prevention and therapeutic applications, yet their performance is limited by exclusive reliance on cap-dependent translation, which is markedly suppressed under hypoxia and cellular stress. Here, we report a hybrid 5 ' untranslated region (5 ' UTR) that enables dual translation initiation via both cap-dependent and internal ribosome entry site (IRES) mechanisms. This element integrates a minimal stem-loop 4.5-5 module (SL4.5-5) from the SARS-CoV-2 genomic 5 ' UTR, in which a conserved 5 '-UUUCGU-3 ' motif within the SL5 loops is essential for function. Incorporating the SL4.5-5 module downstream of conventional 5 ' UTRs confers cap-independent translation capacity and enhances overall translation efficiency under translation-restrictive conditions such as hypoxia. When applied to the 5 ' UTRs of clinically validated COVID-19 vaccines, this module improves antigen expression in both modified and unmodified mRNAs. Notably, unmodified Omicron BA.5 and XBB.1.5 mRNA vaccines containing this element elicited potent humoral and cellular immune responses at sub-microgram doses, comparable to those induced by the approved N1-methylpseu-douridine-incorporated mRNA vaccine, raxtozinameran. These findings identify SL4.5-5 as a modular IRES element that enables dual translation initiation, promoting efficient protein synthesis under cap-dependent translation-restrictive conditions and expanding the functional landscape of mRNA vaccines and therapeutics beyond cap-dependent limitations. 2026-06-01T00:00:00Z https://ir.ymlib.yonsei.ac.kr/handle/22282913/212475 Title: A responder-informed gut microbial consortium enhances anti-PD-1 efficacy in a mouse cancer model Authors: Jeong, Uk Jin; Ali, Mohammed; Park, Yun Jee; You, Jin Sun; Yoon, Sang Sun Abstract: Aim: Immune checkpoint inhibitors (ICIs), particularly anti-programmed cell death protein 1 (PD-1) therapy, have improved cancer treatment outcomes, yet durable benefit is achieved in only a subset of patients. Growing evidence implicates the gut microbiome as a modulator of ICI responsiveness, but defined and experimentally validated microbial strategies remain limited. This study aimed to identify responder-associated gut microbes and to evaluate a defined bacterial consortium for enhancing PD-1 blockade efficacy. Methods: Publicly available shotgun metagenomic datasets from anti-PD-1-treated cancer patients were re-analyzed to compare gut microbiome profiles between responders and non-responders. Bacterial taxa reproducibly enriched in responders were selected based on consistency across analytical criteria and cultivability and assembled into a four-strain consortium (UJ-04). The immune-adjuvant potential of UJ-04, alone or combined with anti-PD-1 therapy, was evaluated in a B16-F10 melanoma mouse model, with tumor growth and immune responses assessed by flow cytometry. Results: Metagenomic re-analysis identified four commensal bacterial taxa consistently enriched in responder patients, forming the defined UJ-04 consortium. While UJ-04 alone showed minimal antitumor activity, combination treatment with anti-PD-1 significantly enhanced tumor growth inhibition compared with anti-PD-1 monotherapy. This effect was accompanied by increased intratumoral CD8+T cells and natural killer cells, with concordant immune trends in peripheral compartments. Conclusion: A responder-informed, defined microbial consortium functionally translates clinical microbiome associations into in vivo validation and enhances PD-1 blockade efficacy by modulating host antitumor immunity. These findings support defined bacterial consortia as microbiome-based immunomodulatory adjuncts for immunotherapy. 2026-06-01T00:00:00Z https://ir.ymlib.yonsei.ac.kr/handle/22282913/212556 Title: Virtual reality-based cognitive assessment tools for mild cognitive impairment screening: comparison with traditional paper-and-pencil-based cognitive assessment tools Authors: Lee, Seungryul; Jang, Sooah; Kim, Eosu; Son, Sang Joon; Kim, Woo Jung; Lee, San; Hong, Chang Hyung; Roh, Hyun Woong; Seok, Jeong-Ho; Jung, Eunjin; 김지혜; Kim, In-young; Oh, Jooyoung; 장수아; 이산 Abstract: Background and Objectives Dementia is becoming increasingly prevalent, highlighting the need for early detection of mild cognitive impairment (MCI), a risk state for dementia. Traditional cognitive assessments often require trained examiners and lack ecological validity. This study examined the diagnostic accuracy of a virtual reality (VR)-based cognitive assessment tool, VARABOM.D, by comparing it with three standard tests: Seoul Neuropsychological Screening Battery (SNSB), Montreal Cognitive Assessment (MoCA), and Mini-Mental State Examination (MMSE).Research Design and Methods Seventy-seven participants, divided into normal (n = 44) and MCI (n = 33) groups based on their Clinical Dementia Rating scores, completed the VARABOM.D program, in addition to SNSB, MoCA, and MMSE. Correlation analyses were performed on the test results, and the specificity, sensitivity, and area under the curve (AUC) of VARABOM.D were compared to those of the other assessments. To monitor for any adverse reactions to the VR environment, the Simulator Sickness Questionnaire (SSQ) was administered both before and after the VR sessions.Results VARABOM.D scores showed significant positive associations with established cognitive assessments. Its AUC values were comparable to those of the MoCA, MMSE, and most SNSB subdomains except for attention, where VARABOM.D demonstrated greater discriminative ability. SSQ scores remained stable across pre- and post-VR sessions in both study groups, underscoring the VR platform's safety and feasibility.Discussion and Implications VARABOM.D demonstrated accuracy comparable to traditional cognitive assessments and even outperformed the attention subdomain of SNSB. Additionally, no adverse reactions were observed in the normal or MCI groups, further emphasizing the safety and stability of VARABOM.D. 2026-06-01T00:00:00Z https://ir.ymlib.yonsei.ac.kr/handle/22282913/212119 Title: Trends in cause-specific mortality among people with and without diabetes in high-income settings: a multinational, population-based study Authors: Magliano, Dianna J.; Morton, Jedidiah, I; Chen, Lei; Sacre, Julian W.; Salim, Agus; Gong, Joanna Y.; Carstensen, Bendix; Gregg, Edward W.; Arffman, Martti; Booth, Gillian L.; Braake, Jonne G. ter; Chu, Luan Manh; Eeg-Olofsson, Katarina; Eliasson, Bjorn; Fleetwood, Kelly; Fosse-Edorh, Sandrine; Garbuviene, Milda; Guion, Marie; Ha, Kyoung Hwa; Kaul, Padma; Ke, Calvin; Keskimaki, Ilmo; Kim, Dae Jung; Laurberg, Tinne; Stovring, Henrik; Vos, Rimke C.; Wild, Sarah H.; Shaw, Jonathan Abstract: Background Cardiovascular disease has historically been the most common cause of death (COD) among people with and without diabetes. However, substantial progress has been made in the management of cardiovascular disease. We conducted a multinational analysis to establish whether this trend is still the case. Methods In this multinational, population-based study, we assembled aggregated annual mortality data collected during routine clinical care from nationally or regionally representative administrative datasets in high-income jurisdictions between 2000 and 2023. For inclusion, datasets must have ongoing enrolment of new patients with diabetes, cause-specific death counts in people with and without diabetes, and sex-specific and age-specific data. We collected population size, counts of prevalent diabetes (type 1 and type 2), death counts, and person-years of follow-up in people with and without diagnosed diabetes by sex and 10-year age group. We estimated cause-specific trends in mortality rates, proportional mortality, and mortality rate ratios (MRR) for people with versus those without diabetes (type 1 and type 2) using Poisson models standardised for age and sex. Findings Using data from 11 jurisdictions, we identified 2 center dot 7 million deaths in people with diabetes and 11 center dot 0 million deaths in people without diabetes during a total of 1 center dot 7 billion person-years of follow-up. Cardiovascular disease mortality decreased in all jurisdictions in populations with and without diabetes. Mean 5-year declines in cardiovascular disease mortality among people with diabetes ranged from 8 center dot 3% (95% CI 5 center dot 9 to 10 center dot 7) to 25 center dot 4% (22 center dot 8 to 28 center dot 0). Mortality due to diabetes declined in most jurisdictions. Dementia mortality increased in people with and without diabetes in six (86%) of seven jurisdictions. Cancer mortality declined in people with diabetes in three (33%) of nine jurisdictions and in people without diabetes in six (67%). At the end of the observation period, cancer was the leading COD in people with diabetes in four (36%) of 11 jurisdictions. MRRs were generally stable for all CODs. Exceptions include Lithuania, where the mean 5-year change in MRR for cardiovascular disease was-7 center dot 6% (-10 center dot 1 to-5 center dot 1), indicating a more rapid fall in cardiovascular disease mortality in people with diabetes than in people without. For dementia, the MRR increased in Denmark (5-year change 8 center dot 0% [5 center dot 0 to 11 center dot 1]) and Scotland (11 center dot 4% [8 center dot 5 to 14 center dot 3]). Interpretation Mortality from cardiovascular disease and diabetes has declined among people with diabetes in most jurisdictions, whereas mortality from dementia has increased markedly, independent of age. Cardiovascular disease is no longer universally the most common COD among people with diabetes in high-income countries. Copyright (c) 2026 Published by Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies. 2026-05-01T00:00:00Z