Although multidisciplinary treatment is widely applied in colorectal cancer (CRC), the prognosis of patients with advanced CRC remains poor. Immunotherapy blocking of programmed cell death ligand 1 (PD-L1) is a promising approach. Binding of the transmembrane protein PD-L1 expressed by tumor cells or tumor microenvironment cells to its receptor programmed cell death 1 (PD-1) induces immunosuppressive signals and reduces the proliferation of T cells, which is an important mechanism of tumor immune escape and a key issue in immunotherapy. However, the regulation of PD-L1 expression is poorly understood in CRC. Fibroblast growth factor (FGF) receptor (FGFR) 2 causes the tyrosine kinase domains to initiate a cascade of intracellular signals by binding to FGFs and dimerization (pairing of receptors), which is involved in tumorigenesis and progression. In this study, we showed that PD-L1 and FGFR2 were frequently overexpressed in CRC, and FGFR2 expression was significantly associated with lymph node metastasis, clinical stage, and poor survival. In the current study, PD-L1 expression was positively correlated with FGFR2 expression in CRC. Tumor-derived–activated FGFR2 induced PD-L1 expression via the JAK/STAT3 signaling pathway in human CRC cells (SW480 and NCI-H716), which induced the apoptosis of Jurkat T cells. FGFR2 also promoted the expression of PD-L1 in a xenograft mouse model of CRC. The results of our study reveal a novel mechanism of PD-L1 expression in CRC, thus providing a theoretical basis for reversing the immune tolerance of FGFR2 overexpression in CRC.
Background The COVID-19 epidemic is still spreading globally. Contact tracing is a vital strategy in epidemic emergency management; however, traditional contact tracing faces many limitations in practice. The application of digital technology provides an opportunity for local governments to trace the contacts of individuals with COVID-19 more comprehensively, efficiently, and precisely. Objective Our research aimed to provide new solutions to overcome the limitations of traditional contact tracing by introducing the organizational process, technical process, and main achievements of digital contact tracing in Hainan Province. Methods A graph database algorithm, which can efficiently process complex relational networks, was applied in Hainan Province; this algorithm relies on a governmental big data platform to analyze multisource COVID-19 epidemic data and build networks of relationships among high-risk infected individuals, the general population, vehicles, and public places to identify and trace contacts. We summarized the organizational and technical process of digital contact tracing in Hainan Province based on interviews and data analyses. Results An integrated emergency management command system and a multi-agency coordination mechanism were formed during the emergency management of the COVID-19 epidemic in Hainan Province. The collection, storage, analysis, and application of multisource epidemic data were realized based on the government’s big data platform using a centralized model. The graph database algorithm is compatible with this platform and can analyze multisource and heterogeneous big data related to the epidemic. These practices were used to quickly and accurately identify and trace 10,871 contacts among hundreds of thousands of epidemic data records; 378 closest contacts and a number of public places with high risk of infection were identified. A confirmed patient was found after quarantine measures were implemented by all contacts. Conclusions During the emergency management of the COVID-19 epidemic, Hainan Province used a graph database algorithm to trace contacts in a centralized model, which can identify infected individuals and high-risk public places more quickly and accurately. This practice can provide support to government agencies to implement precise, agile, and evidence-based emergency management measures and improve the responsiveness of the public health emergency response system. Strengthening data security, improving tracing accuracy, enabling intelligent data collection, and improving data-sharing mechanisms and technologies are directions for optimizing digital contact tracing.
BackgroundChina poverty reduction policy (PRP) addresses two important elements: the targeted poverty reduction (TPA) project since 2015 in line with social assistance policy as national policy; and reducing inequality in health services utilization by making provision of medical financial assistance (MFA). Therefore, this study aims to assess the effects of the PRP in health services utilization (both inpatient and outpatient services) among the central and western rural poor of China.MethodsThe study conducted household survey and applied propensity score matching (PSM) method to assess the effects of the PRP on health services utilization among the rural poor of Central and Western China. A sensitivity test was also performed on the PSM results to test their robustness.ResultsKey findings showed 17.6% of respondents were the beneficial of PRP. The average treatment effects on the treated (ATT) of the PRP on the inpatient visits within one year was found significantly positive (P = 0.026).ConclusionThere has been relationship between PRP with medical financial assistance and reduction of inequality in health services utilization by the poorer, in particular to accessing the inpatient services from the county or township hospitals of China. Policy makers should pay attention for making provision of improving responsiveness of supply, when subsidizing on the demand side.
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