Background: Phenotyping of atherosclerotic plaque vulnerability has largely relied on histopathology that captures structural features, but does not fully account for clinical presentation. Proteomic profiling could uncover molecular readouts of vulnerability that refine plaque phenotyping and provide mechanistic insights. Yet, the proteomic signatures associated with plaque rupture and symptomatic presentation are poorly characterized. Methods: We profiled paired carotid plaque tissue and preoperative plasma from 88 patients undergoing carotid endarterectomy (51 symptomatic, 37 asymptomatic) using the Olink Explore 3072 platform. We related plaque protein abundance to symptomatic presentation and quantitative histopathological features, and compared the performance of histopathology- vs. proteomics-based models for discriminating symptomatic disease. Next, we developed proteomic signatures of cellular abundance and explored their associations with plaque phenotypes by using plaque single-cell RNA-sequencing (scRNA-seq) data. Finally, we assessed plaque-plasma concordance across 2,837 shared proteins. Results: Across 2,837 plaque proteins, 19 were differentially expressed in symptomatic plaques related to distinct clinical events, highlighting pathways related to neutrophil degranulation and innate immune system. FGFBP1 showed the strongest association with symptomatic presentation (log2 fold change = 1.14; P = 1.82 x 10^-6). Proteins associated with a composite vulnerability index based on histopathology were enriched for inflammatory pathways, including TNF signaling through NF{kappa}B, complement activation, and IL6-JAK-STAT3 signaling. Individual proteins also mapped to specific histopathological features, including CXCL8 associated with macrophage burden and lipid core size, and EPHB4 and PKN3 with neovascularization. A proteomics-based model discriminated symptomatic from asymptomatic plaques substantially better than a histopathology-based model (AUC 0.83 vs. 0.66; P = 0.026). Integration with scRNA-seq data enabled the development of cell-class signatures that correlated with histopathology readouts, including macrophage burden, smooth muscle cell content, and neovascularization. Plaque and plasma protein levels showed limited overall correspondence (median {rho}=0.11), although selected proteins, including FGFBP1, demonstrated concordant associations in plasma. Conclusions: Deep proteomic profiling of human carotid plaques identifies molecular signatures of symptomatic atherosclerosis that extend beyond conventional histopathology. These signatures implicate neutrophil activation and inflammatory signaling pathways as key determinants of plaque vulnerability. Although plaque and plasma proteomes are largely distinct, selected proteins may represent promising circulating biomarkers for future risk stratification.
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