Emerging Trends in Electron Transport Layer Development for Stable and Efficient Perovskite Solar Cells.

Perovskite solar cells (PSCs) stand at the forefront of photovoltaic research, with current efficiencies surpassing 26.1%. This review critically examines the role of electron transport materials (ETMs) in enhancing the performance and longevity of PSCs. It presents an integrated overview of recent advancements in ETMs, like TiO2, ZnO, SnO2, fullerenes, non-fullerene polymers, and small molecules. Critical challenges are regulated grain structure, defect passivation techniques, energy level alignment, and interfacial engineering. Furthermore, the review highlights innovative materials that promise to redefine charge transport in PSCs. A detailed comparison of state-of-the-art ETMs elucidates their effectiveness in different perovskite systems. This review endeavors to inform the strategic enhancement and development of n-type electron transport layers (ETLs), delineating a pathway toward the realization of PSCs with superior efficiency and stability for potential commercial deployment.

A prognostic model using FIGO 2018 staging and MRI-derived tumor volume to predict long-term outcomes in patients with uterine cervical squamous cell carcinoma who received definitive radiotherapy.

BACKGROUND: Uterine cervical carcinoma is a severe health threat worldwide, especially in China. The International Federation of Gynecology and Obstetrics (FIGO) has revised the staging system, emphasizing the strength of magnetic resonance imaging (MRI). We aimed to investigate long-term prognostic factors for FIGO 2018 stage II-IIIC2r uterine cervical squamous cell carcinoma following definitive radiotherapy and establish a prognostic model using MRI-derived tumor volume. METHODS: Patients were restaged according to the FIGO 2018 staging system and randomly grouped into training and validation cohorts (7:3 ratio). Optimal cutoff values of squamous cell carcinoma antigen (SCC-Ag) and tumor volume derived from MRI were generated for the training cohort. A nomogram was constructed based on overall survival (OS) predictors, which were selected using univariate and multivariate analyses. The performance of the nomogram was validated and compared with the FIGO 2018 staging system. Risk stratification cutoff points were generated, and survival curves of low-risk and high-risk groups were compared. RESULTS: We enrolled 396 patients (training set, 277; validation set, 119). The SCC-Ag and MRI-derived tumor volume cutoff values were 11.5 ng/mL and 28.85 cm3, respectively. A nomogram was established based on significant prognostic factors, including SCC-Ag, poor differentiation, tumor volume, chemotherapy, and FIGO 2018 stage. Decision curve analysis indicated that the net benefits of our model were higher. The high-risk group had significantly shorter OS than the low-risk group in both the training (p < 0.0001) and validation sets (p = 0.00055). CONCLUSIONS: Our nomogram predicted long-term outcomes of patients with FIGO 2018 stage II-IIIC2r uterine cervical squamous cell carcinoma. This tool can assist gynecologic oncologists and patients in treatment planning and prognosis.

Prognostic factors and treatment of neuroendocrine tumors of the uterine cervix based on the FIGO 2018 staging system: a single-institution study of 172 patients.

OBJECTIVE: This study aimed to explore the prognostic factors and outcomes of patients with neuroendocrine tumors (NETs) of the cervix and to determine appropriate treatment. METHODS: A single-institution retrospective analysis of 172 patients with NETs was performed based on the new International Federation of Gynecology and Obstetrics (FIGO 2018) staging system. RESULTS: Among the 172 eligible patients, 161 were diagnosed with small cell neuroendocrine carcinoma (SCNEC), six with large cell neuroendocrine carcinoma, four with typical carcinoid tumors and one with SCNEC combined with an atypical carcinoid tumor. According to the FIGO 2018 staging guidelines, 31 were stage I, 66 were stage II, 57 were stage III, and 18 were stage IV. The 5-year survival rates of patients with stage I-IV disease were 74.8%, 56.2%, 41.4% and 0%, respectively. The 5-year progression-free survival rates of patients with stage I-IV disease were 63.8%, 54.5%, 30.8% and 0%, respectively. In the multivariate analysis, advanced FIGO stage, large tumor and older age were identified as independent variables for 5-year survival in patients with stage I-IV disease. FIGO stage, tumor size and para-aortic lymph node metastasis were independent prognostic factors for 5-year progression-free survival in patients with stage I-IV disease. For the patients receiving surgery (n = 108), tumor size and pelvic lymph node metastasis were independent prognostic factors for 5-year survival, and pelvic lymph node metastasis for 5-year progression-free survival. In stage IVB, at least six cycles of chemotherapy (n = 7) was associated with significantly better 2-year OS (83.3% vs. 9.1%, p < 0.001) and 2-year PFS (57.1% vs. 0%, p = 0.01) than fewer than six cycles of chemotherapy(n = 11). CONCLUSION: Advanced FIGO stage, large tumor, older age and lymph node metastasis are independent prognostic factors for NETs of the cervix. The TP/TC and EP regimens were the most commonly used regimens, with similar efficacies and toxicities. Standardized and complete multimodality treatment may improve the survival of patients with NETs.

Nomogram Predicting Overall Survival in Patients with FIGO II to III Squamous Cell Cervical Carcinoma Under Radical Radiotherapy: A Retrospective Analysis Based on 2018 FIGO Staging.

PURPOSE: To present a nomogram to predict overall survival in patients with FIGO-2018 II to III squamous cell cervical carcinoma undergoing radical radiotherapy. PATIENTS AND METHODS: Patients diagnosed with FIGO-2018 II to III squamous cell cervical cancer between December 2013 and December 2014 were analyzed retrospectively. The optimal cutoff point for tumor length and width were determined by R package. We identified prognostic factors by univariate and multivariate Cox proportional-hazard regression, then built a nomogram to visualize the prediction model. Our model was compared to the 2018 FIGO staging prediction model. Harrell's concordance index, receiver operating characteristic curve, calibration plot were used to evaluate the discriminability and accuracy of the predictive models, and decision curve analysis (DCA) was used to show the net benefits. RESULTS: Data from 469 patients were included in the final analyses. The cutoff values of tumor length and width were 5.10 cm and 4.13 cm, respectively. Four independent prognostic variables-tumor length, tumor width, lower one-third vaginal involvement, and lymph node metastases-were used to establish the nomogram. The C-index of the nomogram was 0.71 (95%, CI = 0.66-0.77), which was better than that of the 2018 FIGO stage prediction model (C-index: 0.62, 95% CI = 0.58-0.66, p = 0.009). The calibration plot of the nomogram was a good fit for both 3-year and 5-year overall survival predictions. And DCA curves showed that net benefits for our model were higher than FIGO-2018 staging system. CONCLUSION: A clinically useful nomogram for calculating overall survival probability in FIGO-2018 II to III squamous cell cervical cancer patients who had received radical radiotherapy was developed. Tumor length, tumor width, lower one-third vaginal involvement, and lymph node metastases were found to be independent prognostic factors. Our model performed better than the 2018 FIGO staging model. The findings could help clinicians in China to predict the survival of these patients in clinical care and research.

Early changes in apparent diffusion coefficients predict radiosensitivity of human nasopharyngeal carcinoma xenografts.

OBJECTIVES/HYPOTHESIS: Our objective was to predict the radiosensitivity of human nasopharyngeal carcinoma xenografts in nude mice models through an examination of early changes in apparent diffusion coefficient (ADC) values. STUDY DESIGN: Randomized. METHODS: BALB/c-nu nude mice (n = 20) were divided into two groups that were subcutaneously injected with CNE1 or CNE2 cell lines. Xenograft volumes were measured after tumor formation, mice were scanned with a diffusion-weighted imaging sequence, and the mean ADC values were measured (ADC(0) ). Fifteen to 20 hours after tumors received 15 Gy, mice were scanned again and ADC values (ADC(1) ) were measured. RESULTS: ADC(0) and ADC(1) values of the CNE1 group showed no significant difference (P = .692). The difference between the ADC(0) and ADC(1) values of the CNE2 group was statistically significant (P < .001). ADC(0) values of the two groups exhibited no statistically significant difference (P = .204). ADC(1) , ADC(1-0) , and ΔADC of the two groups exhibited statistically significant differences (P < .001; P = .001 and .002, respectively). After irradiation, volume changes ΔV(8) , ΔV(10) , and ΔV(12) of two groups were statistically different (all P < .001). Pearson correlation analysis showed ADC(1-0) and ΔADC were positively correlated with ΔV(8) , ΔV(10) , and ΔV(12) . The cut point was found by means of a receiver operating characteristic curve, and the ΔV(12) of the two redivided groups showed a statistically significant difference (P = .001). CONCLUSIONS: This study found that changes in ADC values correlated with volume changes after irradiation. Therefore, ADC values have the potential to predict the radiosensitivity of nasopharyngeal carcinoma xenografts.