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Abstract [Objective] The study aims to identify and describe a new species Cinnamomum huarum (Lauraceae), which was collected from Nanjian, Yunnan of China. [Methods] This species was confirmed as a new taxa by morphological comparison with morphologically similar species and molecular phylogenetic study based on chloroplast genome data. [Results] The new species was similar to C. chago: Pinnately veined, leaves opposite or subopposite, long acumen, branchlets sparsely puberulent, terminal bud densely pubescent, leaf blade gray white abaxially and puberulent, margin undulate and fruit oblate. The chloroplast genome size of this species was 154 078 bp, which was 1 325 bp longer than C. chago and 1 348 bp longer than C. pittosporoides, having an extra 678 bp fragment in the inverted repeat region compared to C. chago and C. pittosporoides. In the phylogenetic tree constructed with whole chloroplast genome of 36 Lauraceae species, C. huarum formed an independent parallel branch with C. pittosporoides and other species. [Conclusion] Both the morphological and phylogenetic research indicate that C. huarum is a distinct species.

Background: To determine the role of N6-methyladenosine (m6A) modification in the tumor immune microenvironment (TIME), as well as their association with lung adenocarcinoma (LUAD). Methods: Consensus clustering was performed to identify the subgroups with distinct immune or m6A modification patterns using profiles from TCGA. A risk score model was constructed using least absolute shrinkage and selection operator regression and validated in two independent cohorts and LUAD tissue microarrays. For experimental validation, the regulation of METTL3/m6A axis in the expression of candidate genes by RIP-qPCR assay in A549 and H460 cell lines. Co-culture experiments with human T cells were performed to evaluate the impact of METTL3 on the enhancement of anti-tumor immunity through in vitro experiments. Results: We identified 282 m6A regulator genes and 955 immune-related genes, selecting seven key genes (SFTPC, CYP24A1, KRT6A, PTTG1, S100P, FAM83A, and ANLN) to develop a risk score model using Lasso regression. High-risk patients, determined by this model, exhibited poorer prognosis, increased immune infiltration, higher tumor mutational burden, more neoantigens, and elevated PD-L1 expression. These findings were validated by two independent databases and LUAD tissue microarrays. METTL3 was found to impact the mRNA expression of these genes, with METTL3 deficiency abolishing these interactions. Inhibition of METTL3 enhanced anti-tumor immunity, T cell activation, exhaustion, and infiltration in vitro. Conclusion: This risk score system shows promise for prognostic prediction and the development of personalized treatment strategies for LUAD patients. [ABSTRACT FROM AUTHOR]

Small molecules as nanomedicine carriers offer advantages in drug loading and preparation. Selecting effective small molecules for stable nanomedicines is challenging. This study used artificial intelligence (AI) to screen drug combinations for self-assembling nanomedicines, employing physiochemical parameters to predict formation via machine learning. Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) are identified as effective carriers for antineoplastic drugs, with high drug loading. Nanomedicines, PEG-coated indomethacin/paclitaxel nanomedicine (PiPTX), and laminarin-modified indomethacin/paclitaxel nanomedicine (LiDOX), are developed with extended circulation and active targeting functions. Indomethacin/paclitaxel nanomedicine iDOX exhibits pH-responsive drug release in the tumor microenvironment. These nanomedicines enhance anti-tumor effects and reduce side effects, offering a rapid approach to clinical nanomedicine development., (© 2025 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Background: To determine the role of N 6 -methyladenosine (m 6 A) modification in the tumor immune microenvironment (TIME), as well as their association with lung adenocarcinoma (LUAD)., Methods: Consensus clustering was performed to identify the subgroups with distinct immune or m 6 A modification patterns using profiles from TCGA. A risk score model was constructed using least absolute shrinkage and selection operator regression and validated in two independent cohorts and LUAD tissue microarrays. For experimental validation, the regulation of METTL3/m 6 A axis in the expression of candidate genes by RIP-qPCR assay in A549 and H460 cell lines. Co-culture experiments with human T cells were performed to evaluate the impact of METTL3 on the enhancement of anti-tumor immunity through in vitro experiments., Results: We identified 282 m 6 A regulator genes and 955 immune-related genes, selecting seven key genes (SFTPC, CYP24A1, KRT6A, PTTG1, S100P, FAM83A, and ANLN) to develop a risk score model using Lasso regression. High-risk patients, determined by this model, exhibited poorer prognosis, increased immune infiltration, higher tumor mutational burden, more neoantigens, and elevated PD-L1 expression. These findings were validated by two independent databases and LUAD tissue microarrays. METTL3 was found to impact the mRNA expression of these genes, with METTL3 deficiency abolishing these interactions. Inhibition of METTL3 enhanced anti-tumor immunity, T cell activation, exhaustion, and infiltration in vitro ., Conclusion: This risk score system shows promise for prognostic prediction and the development of personalized treatment strategies for LUAD patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Chen, Wan, Zhao, Li, Xiong, Yuan, Tang, Wu, Xing, Guo, Lu, Ao, Xu and Ao.)