Aug 2026· Human Mutation· Vol 2026· 0 citations· 47 references
Medicine
Abstract
Introduction Posttranslational modification (PTM) plays an important role in protein regulation and may influence tumor initiation and progression. However, the role of PTM‐related programs in lung adenocarcinoma (LUAD) remains incompletely understood. Materials and Methods Single‐cell RNA sequencing (scRNA‐seq) data were analyzed to quantify the activity of PTM‐related gene set using the AUCell algorithm and to characterize intercellular communication using CellChat. Molecular subtypes and differentially expressed genes (DEGs) were identified using ConsensusClusterPlus and limma packages, respectively, followed by functional enrichment analysis. Univariate Cox regression, LASSO regression with 10‐fold cross‐validation, and stepwise multivariable Cox regression based on the Akaike information criterion (AIC) were used to construct a prognostic model. Immune infiltration was evaluated using ESTIMATE, CIBERSORT, MCP‐counter, and TIMER algorithms, and drug sensitivity was predicted using oncoPredict package. The IMvigor210 cohort was used for exploratory assessment of immunotherapy response. Quantitative real‐time reverse transcription PCR (qRT‐PCR) was used to measure the expressions of the model genes. CCK‐8, wound‐healing, and Transwell assays were performed to evaluate the effects of CDKN3 knockdown on LUAD cells. Results Comparison between two PTM groups revealed that receptor ligands such as MIF‐(CD74+CXCR4) and MIF‐(CD74+CD44) had higher communication probabilities in the high–PTM‐score group. Two molecular subtypes were identified, and a six‐gene risk model for LUAD was established based on CDKN3, PKP2, ADM, MS4A1, FAM83A, and DKK1. The high‐risk group showed a lower immune score, and drugs such as Docetaxel_1007 may have therapeutic potential for LUAD. Immunotherapy response prediction further demonstrated that the low‐risk group may be more likely to benefit from immunotherapy. In vitro experiments demonstrated that CDKN3, PKP2, ADM, FAM83A, and DKK1 were upregulated, whereas MS4A1 was downregulated in A549 cells compared with BEAS‐2B cells. Additionally, knockdown of CDKN3 significantly suppressed the viability, migration, and invasion of LUAD cells. Conclusion The PTM‐related six‐gene model showed potential for prognostic stratification and characterization of immune‐related features in LUAD. However, further prospective and experimental validation is required before direct clinical application.
This study constructed a pH-responsive P-TN/SF@Fe-Cur composite coating that demonstrated significant anti-infective, anti-inflammatory, antioxidant, pro-angiogenic, and pro-osteogenic effects in rat subcutaneous infection and femoral defect models.
The results show that alternative transcript diversity extensively enters translation-supported proteoform space and establish a systematic link between transcript variation and protein functional diversification.
Felicia T. Jiang, Dengwang Chen, Ziwei Wang et al.· bioRxiv· 1 citation
Protein therapeutic design and property prediction are frequently hampered by data scarcity. Here we propose a model, DyAb, that addresses these issues by leveraging a pair-wise representation to predict differences in binding affinity, rather than absolute values. DyAb is built on top of a pre-trained protein language model and achieves a Spearman rank correlation of up to 0.85 on binding affinity prediction across monoclonal antibodies targeting three different antigens (EGFR, IL-6, and an internal target), given as few as 100 training data. We employ DyAb in two design contexts: as a ranking model to score combinations of known mutations, and combined with a genetic algorithm to generate new sequences. Our method consistently generates antibody variants with high binding rates, including designs that improve on the binding affinity of the lead molecule by more than ten-fold. DyAb represents a powerful tool for optimizing antibody binding affinity in low data regimes common in early-stage drug development.
Joshua Yao-Yu Lin, Jennifer L. Hofmann, Andrew Leaver‐Fay et al.· mAbs· 1 citation
Due to its importance and wide adoption, wheat cultivation is promptly required to shift towards sustainable practices, reducing the dependency on chemical components. Among bio-based solutions aimed at securing the sustainability of wheat cultivation, biostimulants offer a versatile platform of eco-friendly tools assuring sustainability and profitability. Microalgae present a concrete example of a biostimulant source due to their richness in metabolites and high value products. Therefore, this study evaluated the biostimulant potential of eleven eco-extracts prepared from soil-isolated microalgae strains. Eco-extracts applied via soil drench at low dose (0.1 g/L) were investigated for their biostimulant effects on wheat growth, physiology, yield, and quality under controlled conditions. Results demonstrated significant ameliorations in treated plants as compared to the control, with no phytoinhibitory effects. Remarkable enhancements were notable in growth parameters such as shoot and root lengths (+40-70%), physiological traits such as total chlorophyll and stomatal conductance (+7-52%), yield components in the example of grain number per spike and thousand grain weight (+17-103%), and grain quality namely protein and polyphenol content (+2-fold to 4-fold). Similarly, phosphorus accumulation and uptake were significantly improved, while soil physicochemical status was ameliorated, indicating enhanced fertility. Multivariate analysis and composite index ranking marked Chlorella sp. GA18, Chlorella sp. GA65, Scenedesmus sp. GA69, and Chlorococcum sp. GA63 as eco-extracts with consistent performances across all plant traits. These findings highlighted the promising potential of integrating microalgae-based eco-friendly extracts in sustainable wheat cultivation.
Amer Chabili, Z. Hakkoum, F. Minaoui et al.· Plant Science· 1 citation
ProteinReasoner is developed, a multimodal generative protein foundation model that sequentially connects amino acid sequence, evolutionary constraints and three-dimensional structure within a shared autoregressive architecture and suggests a general route towards reasoning across interdependent representations in other scientific domains.
Chaozhong Liu, Linlin Chao, Shaomin Ji et al.· bioRxiv· 1 citation
HydroGym is introduced, a solver-independent reinforcement learning platform providing more than 60 validated, openly available flow control environments spanning from canonical laminar flows to complex turbulent flows, with systematic progression in the Reynolds number up to Re = 4 × 105, and Mach number variations in two and three dimensions.
Christian Lagemann, Sajeda Mokbel, Miro Gondrum et al.· Nature· 1 citation