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Locally advanced cervical cancer (LACC) is an early-stage cervical cancer characterized by a local tumor diameter of ≥4 cm. Patients with LACC have a relatively poor prognosis. Although preoperative radiochemotherapy (PRCT) might offer a valuable opportunity for subsequent radical surgery, surgeons should also consider the nonresponsive rate, the adverse effects of PRCT, and the surgical complications before designing a treatment plan. Therefore, biomarkers for predicting PRCT sensitivity and prognosis in patients with LACC are of high importance. We investigated the prognostic significance of vascular endothelial growth factor (VEGF) and hypoxia inducible factor-1α (HIF-1α) in patients with LACC. A total of 43 patients with LACC who underwent PRCT (one course each of intravenous chemotherapy and after-loading intracavitary brachytherapy followed by a radical hysterectomy) during the period 2009–2014 were included in this study. VEGF and HIF-1α expression levels were evaluated by immunohistochemistry in LACC lesions before and after PRCT. In addition, we analyzed the association of these proteins with the clinical response and pathological findings of pelvic lymph node metastasis (PLNM) after the subsequent surgery. The total clinical response rate was 81.39% after PRCT, including five complete responses and 30 partial responses. VEGF and HIF-1α expression before PRCT was significantly higher than after PRCT (VEGF: 85.71% vs 66.67%; HIF-1α: 83.33% vs 59.52%, P<0.05). In addition, the same trend was found in patients with PLNM compared to those without PLNM (VEGF: 100% vs 77.78%; HIF-1α: 100% vs 74.07%, P<0.05). The areas under the receiver operating characteristic curves were 0.896 and 0.835 when using pre-PRCT VEGF and HIF-1α expression levels, respectively, to diagnose PLNM in patients with LACC. Serial detection of VEGF and HIF-1α demonstrated a sensitivity of 66.67% and specificity of 88.89%. These findings suggest that VEGF and HIF-1α expressions are potential biomarkers for PRCT and have great clinical significance for the prediction of PRCT response and prognosis in patients with LACC.

Green credit policy is designed to address the global climate risk. However, few studies have investigated empirically whether green credit policy indeed reduces corporate carbon emission intensity. Based on firm‐level data in China and a difference‐in‐differences model, this study explores how corporate carbon emission intensity evolves following the green credit policy. We find that, on the whole, the green credit can effectively reduce corporate carbon emission intensity, while the dynamic negative effect tends to alleviate after 2017. Specifically, green credit reduces corporate carbon emission intensity mainly through lowering investment carbon intensity and enhancing environmental supervision. However, the signaling mechanism of green credit does not significantly alleviate corporate carbon emission intensity. The green credit has a stronger reduction effect on corporate carbon emission intensity with third‐party certification, non‐state‐owned ownership, and high financing constraint. We thereby suggest that innovations should be made to the standards and processes of green credit to ensure sustainability and stability. Quantitative and standardized corporate environmental information disclosure is essential for the low‐carbon effect on green finance innovation.

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