To satisfy the needs of a variety of demand-responsive transport, the multimodal transportation problem appeared. This paper focuses on network modeling with a hierarchical structure. The relationship between different levels is described in detail, and dynamic segmentation and linear referencing techniques are used to solve the overlay problem in multimodal network. Furthermore, a shortest path algorithm is proposed to solve the transfer problem with several public vehicle modes. Finally, the results simulated by Geographic Information System (GIS) are given to demonstrate the effectiveness of the proposed model and algorithm.

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Background: Establish patient-derived tumor xenograft (PDTX) from advanced GICs and assess the clinical value and applicability of PDTX for the treatment of advanced GICs. Method: Patients with advanced GICs were enrolled in a registered multi-center clinical study (ChiCTR-OOC-17012731). The performance of PDTX were evaluated includes: analyzing factors that affect the engraftment rate, comparing the histological consistency between primary tumors and tumorgrafts, examining the concordance between the drug effectiveness in PDTXs and clinical responses, and Identifying genetic variants and other factors associated with prognosis. Results: Thirty-three patients were enrolled in the study with the engraftment rate of 75.8% (25/33). The successfulness of engraftment was independent of age, cancer types, pathological stages of tumors, and particularly sampling methods. Tumorgrafts kept same histopathological characteristics as primary tumors. Forty-nine regimens involving twenty-eight drugs were tested in seventeen tumorgrafts. The median time for drug testing was 134.5 day. The follow up information of 10 regimens from 9 patients were obtained. The concordance of drug effectiveness in PDTXs and clinical responses was 100%. The tumor mutation burden (TMB) was correlated with the effectiveness of single drug regimens, while the outgrowth time of tumorgrafts was associated with the effectiveness of combined regimens. Conclusion: The engraftment rate in advanced GICs is higher than other cancers and meets the general acceptable standard of applying personalized therapeutic strategies. Tumorgrafts from PDTX kept attributes of primary tumor. Predictions from PDTX modeling highly agree with the clinical drug responses. PDTX may already be clinical applicable for the personalized medication in advanced GICs.