Thermally activated delayed fluorescence (TADF) molecules have emerged as a promising class of third-generation organic light-emitting diode (OLED) emitters that can achieve 100% internal quantum efficiency without the use of noble metals. However, the design of high-efficiency red TADF materials has been challenging due to limitations imposed by the energy-gap law. To overcome this challenge, two new TADF emitters, namely, 6-(4-(diphenylamino)phenyl)-2-phenyl-1H-benzo[de]isoquinoline-1,3(2H)-dione (NI-TPA) and 6-(10H-phenothiazin-10-yl)-2-phenyl-1H-benzo[de]-isoquinoline-1,3(2H)-dione (NI-Pz), have been synthesized and characterized. These compounds exhibit strong TADF characteristics with a small energy gap (ΔE_ST) between the lowest excited singlet and triplet states, short delayed fluorescence lifetimes, high thermal stability, and high photoluminescence quantum yields. The OLED devices fabricated using NI-TPA and NI-Pz as emitters show orange and red electroluminescence with emission peaks at 593 nm and 665 nm, respectively, and maximum external quantum efficiencies (EQEs) of 11.3% and 7.6%, respectively. Furthermore, applying NI-TPA to cell imaging yielded excellent imaging results, indicating the potential of red TADF materials in the field of biological imaging.

BACKGROUND: EBV is associated with nasopharyngeal carcinoma (NPC), but the existence of a NPC protective antibody against EBV-associated antigens remains unclear. METHODS: Patients with NPC and matched controls were identified from prospective cohorts comprising 75,481 participants in southern China. ELISA and conditional logistic regression were applied to assess the effects of gp42-IgG on NPC. The expression of HLA-II, the gp42 receptor, in nasopharyngeal atypical dysplasia and its effect on EBV infection of epithelial cells were evaluated. FINDINGS: gp42-IgG titers were significantly lower in patients with NPC compared with controls across various follow-up years before NPC diagnosis ( P < 0.05). Individuals in the highest quartile for gp42-IgG titers had a 71% NPC risk reduction compared with those in the lowest quartile (ORs _Q4vsQ1 = 0.29, 95% CIs = 0·15 to 0.55, P < 0.001). Each unit antibody titer increase was associated with a 34% lower risk of NPC (OR = 0.66, 95% CI = 0.54–0.81, P _trend < 0.001). The protective effect of of gp42-IgG was observed in patients diagnosed 5 years or more, 1–5 years, and less than 1 year after blood collection ( P < 0.05). HLA-II expression was detected in 13 of 27 specimens of nasopharyngeal atypical dysplasia, and its overexpression substantially promoted epithelial cell–origin EBV infection. CONCLUSION: Elevated EBV gp42-IgG titers can reduce NPC risk, indicating that gp42 is a potential EBV prophylactic vaccine target. TRIAL REGISTRATION: NCT00941538, NCT02501980, ChiCTR2000028776, ChiCTR2100041628. FUNDING: Noncommunicable Chronic Diseases-National Science and Technology Major Project (2023ZD0501003), National Natural Science Foundation of China (82030046, 82073625, 81860601, 82373655), Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program (2019BT02Y198), and Central Financial Transfer Payment Projects of the Chinese Government, Cancer Research Grant of Zhongshan City.

Epstein-Barr Virus (EBV)–positive neuroendocrine carcinoma (NEC) is a rare neoplasm with limited histopathological and therapeutic data. This report presents 22 cases of EBV-positive NEC, analyzing age distribution, morphology, and immunophenotype. The median patient age was 47 years (range: 27–67 years), with a male-to-female ratio of 17:5. Most cases (86%, 19/22) were localized to the nasal cavity or nasopharynx, while the remaining three (14%, 3/22) involved the lung, eyelid, and chest wall. Tumors were identified as small cell neuroendocrine carcinoma (SCNEC) or large cell neuroendocrine carcinoma (LCNEC) based on cellular morphology. Immunohistochemical analysis showed positivity for at least one, but generally, two neuroendocrine markers and INI1, while negativity for NUT and squamous cell carcinoma markers, such as p63, p40, and CK5/6. In situ hybridization consistently revealed EBV early RNAs (EBERs) in all cases. Notably, eight patients benefited from chemoradiotherapy. Recognizing this rare tumor is essential for optimizing treatment strategies.

Immune checkpoint inhibitor-induced inflammatory arthritis (ICI-IA) significantly impairs cancer therapy and patient quality of life, yet its pathogenic mechanisms remain unclear. Through integrated single-cell multi-omics analysis of paired peripheral blood, synovial fluid, and tumor samples from longitudinal ICI-IA cohorts and matched controls, we identified a unique regulatory T-cell (Treg) population co-expressing CD137 and IL-6R (AtpTreg). These cells exhibited reduced immunosuppressive capacity while aberrantly producing high level of IL-17 and promoting proinflammatory responses of synoviocytes. AtpTreg exhibits shared clonotypes and phenotypes across tissue compartments. Notably, AtpTreg frequency correlates with increased arthritis severity yet paradoxically associates with improved overall survival. Anti-IL6R therapy reduced AtpTreg levels, corresponding with improved arthritis outcomes and quality of life, without compromising anti-tumor immunity. Our findings define a pathogenic Treg subset in ICI-IA and validate IL-6R blockade as a mechanism-based therapeutic strategy, bridging mechanistic discovery to clinical translation. This study is registered at ClinicalTrials.gov (NCT07357636).

Current survival prediction model for extra-nodal natural killer/T-cell lymphoma (ENKTL) have poor accuracy. We developed and validated a machine-learning (ML) algorithm using clinical and pathological co-variates. Data from 977 subjects with ENKTL from 4 cohorts were analyzed. Model performance was evaluated using Harrell’s c-index, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCAs). The Gradient Boosting Machine (GBM) outperformed the other 15 ML algorithms tested, leading to the development of the ENKTL-ML score. C-indexes of the evaluation and external validation cohorts were 0.82 (95% Confidence Interval [CI], 0.76, 0.87), 0.84 (0.81, 0.88) and 0.83 (0.72, 0.94). The ENKTL-ML score effectively stratified subjects into 3 groups with distinct survival outcomes. Our model was more accurate than the IPI, KPI, PINK-E, and NRI (all P < 0.001) models. An online calculator is available at https://highcloud.shinyapps.io/ENKTL_ML_Scores/. The ENKTL-ML score should help physicians predict survival of people with ENKTL.