Background: Mucinous gastric carcinoma (MGC) is rare and often associated with an advanced stage. The clinicopathological features and prognosis of MGC and non-MGC (NMGC) are controversial. Methods: In total, 2637 gastric cancer (GC) patients receiving curative surgery were enrolled. The clinicopathological features and genetic alterations were compared between patients with MGC and NMGC. Results: Among the 2637 GC patients, 92 (3.5%) had MGC. After propensity score matching, compared to patients with NMGC, patients with MGC had more poorly differentiated tumors, medullary stromal reaction-type tumors, tumors with infiltrating Ming’s classification, diffuse-type tumors, more abnormal preoperative serum carbohydrate antigen 19-9 levels, and more advanced T categories. After propensity score matching, there were no significant differences between MGC and NMGC regarding the initial recurrence patterns, 5-year overall survival (OS), and disease-free survival (DFS) rates. Multivariate analysis demonstrated that the MGC cell type is not an independent prognostic factor of OS and DFS. No significant differences in microsatellite instability status, Epstein–Barr virus infection, Helicobacter pylori infection, or genetic mutations were observed between MGC and NMGC. The expression of programmed death-ligand 1 (PD-L1) was significantly higher in MGC than that in NMGC. MGC was diagnosed at a more advanced stage compared with NMGC. Conclusion: MGC itself was not an independent prognostic factor of worse survival. MGC was correlated with higher PD-L1 expression than NMGC, which may have a clinical impact on the treatment of MGC in the future.

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A unified quadratic semi-infinite programming approach is introduced to solve digital filter design problems with time or frequency-domain specification. An algorithm based on this approach is developed and the corresponding convergence result is presented. This computational method is then applied to the optimum filter design problems subject to time and frequency domain specifications, namely the time domain envelope constrained filter design problems and the frequencydomain least square FIR filter design problems. For illustration, two examples are given.