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Open access Jul 2026

Multiomics identifies a prognostic signature and SPIB as a potential regulator of gastric cancer lymph node metastasis

Summary The heterogeneity within the same AJCC TNM stage of gastric cancer necessitates robust prognostic biomarkers beyond conventional staging. By integrating transcriptomic data from 1,613 patients across eight cohorts, we developed an 11-gene lymph node metastasis gene signature (LMGS) using an ensemble learning strategy to overcome the instability of traditional models. LMGS robustly predicted survival (mean C-index = 0.619), providing incremental prognostic value beyond conventional AJCC staging. Single-cell and spatial transcriptomic analyses revealed LMGS enrichment in epithelial/immune cells at the tumor-normal interface. Integrative analysis nominated the transcription factor SPIB as a candidate regulator, which was specifically overexpressed in metastatic lesions. Our study provides a clinically relevant prognostic tool and identifies SPIB as a molecular marker associated with lymphatic dissemination.

Zhijie Duan, Keyu He, Dianjie Chen et al. · 0 citations
Open access Aug 2026

Data-Guided Physics-Informed Neural Network with Fourier Features Enhancement for Euler-Bernoulli Beam Analysis

The results demonstrate that PINN achieves more accurate and stable full-field vibration reconstructions than conventional PINNs, particularly under conditions involving high-frequency modes, and highlights the potential of hybrid data-physics neural frameworks as an efficient and reliable approach for solving complex PDE-governed dynamical systems.

Hailong Liu, S. Hedayatrasa, Yunpeng Zhu et al. · 0 citations