Identification of an inflammatory response-related gene prognostic signature and immune microenvironment for cervical cancer.

Background: Cervical cancer (CC) is the fourth most common cancer among women worldwide. As part of the brisk cross-talk between the host and the tumor, prognosis can be affected through inflammatory responses or the tumor microenvironment. However, further exploration of the inflammatory response-related genes that have prognostic value, microenvironment infiltration, and chemotherapeutic therapies in CC is needed. Methods: The clinical data and mRNA expression profiles of CC patients were downloaded from a public database for this study. In the TCGA cohort, a multigene prognostic signature was constructed by least absolute shrinkage and selection operator (LASSO) and Cox analyses. CC patients from the GEO cohort were used for validation. K‒M analysis was used to compare overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors of OS. The immune cell infiltration and immune-related functional score were calculated by single-sample gene set enrichment analysis (GSEA). Immunohistochemistry was utilized to validate the protein expression of prognostic genes in CC tissues. Results: A genetic signature model associated with the inflammatory response was built by LASSO Cox regression analysis. Patients in the high-risk group had a significantly lower OS rate. The predictive ability of the prognostic genes was evaluated by means of receiver operating characteristic (ROC) curve analysis. The risk score was confirmed to be an independent predictor of OS by univariate and multivariate Cox analyses. The immune status differed between the high-risk and low-risk groups, and the cancer-related pathways were enriched in the high-risk group according to functional analysis. The risk score was significantly related to tumor stage and immune infiltration type. The expression levels of five prognostic genes (LCK, GCH1, TNFRSF9, ITGA5, and SLC7A1) were positively related to sensitivity to antitumor drugs. Additionally, the expression of prognostic genes was significantly different between CC tissues and myoma patient cervix (non-tumorous) tissues in the separate sample cohort. Conclusion: A model consisting of 5 inflammation-related genes can be used to predict prognosis and influence immune status in CC patients. Furthermore, the inhibition or enhancement of these genes may become a novel alternative therapy.

Corrigendum: The research progress on radiation resistance of cervical cancer.

[This corrects the article DOI: 10.3389/fonc.2024.1380448.].

In situ anchored ternary hierarchical hybrid nickel@cobaltous sulfide on poly(3,4-ethylenedioxythiophene)-reduced graphene oxide for highly efficient non-enzymatic glucose sensing.

A ternary hierarchical hybrid Ni@CoxSy/poly(3,4-ethylenedioxythiophene)-reduced graphene oxide (Ni@CoxSy/PEDOT-rGO) is rationally designed and in situ facilely synthesized as electrocatalyst to construct a binder-free sensing platform for non-enzymatic glucose monitoring through traditional electrodeposition procedure. The as-prepared Ni@CoxSy/PEDOT-rGO presents unique hierarchical structure and multiple valence states as well as strong and robust adhesion between Ni@CoxSy/PEDOT-rGO and GCE. Profiting from the aforementioned merits, the sensing platform constructed under optimal conditions achieved a wide detection range (0.2 µM ~ 2.0 mM) with high sensitivity (1546.32 µA cm-2 mM-1), a rapid response time (5 s), an ultralow detection limit (0.094 µM), superior anti-interference performance, excellent reproducibility and considerable stability. Furthermore, the sensor demonstrates an acceptable accuracy and appreciable recoveries ranging from 90.0 to 102.0% with less than 3.98% RSD in human blood serum samples, indicating the prospect of the sensor for the real samples analysis. It will provide a strategy to rationally design and fabricate ternary hierarchical hybrid as nanozyme for glucose assay.

The research progress on radiation resistance of cervical cancer.

Cervical carcinoma is the most prevalent gynecology malignant tumor and ranks as the fourth most common cancer worldwide, thus posing a significant threat to the lives and health of women. Advanced and early-stage cervical carcinoma patients with high-risk factors require adjuvant treatment following surgery, with radiotherapy being the primary approach. However, the tolerance of cervical cancer to radiotherapy has become a major obstacle in its treatment. Recent studies have demonstrated that radiation resistance in cervical cancer is closely associated with DNA damage repair pathways, the tumor microenvironment, tumor stem cells, hypoxia, cell cycle arrest, and epigenetic mechanisms, among other factors. The development of tumor radiation resistance involves complex interactions between multiple genes, pathways, and mechanisms, wherein each factor interacts through one or more signaling pathways. This paper provides an overview of research progress on an understanding of the mechanism underlying radiation resistance in cervical cancer.

A novel immune-related risk-scoring system associated with the prognosis and response of cervical cancer patients treated with radiation therapy.

Objective: The tumor microenvironment plays a critical role in the radiotherapy and immunotherapy response of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). Radioresistance is a key factor in treatment failure among patients who receive radical radiotherapy. Thus, new immune-related biomarkers associated with radiotherapy response in CESC are needed. Methods: In this study, the CIBERSORT and ESTIMATE methods were applied to determine the percentage of tumor-infiltrating cells and the number of immune components in 103 CESCs treated with radiotherapy from The Cancer Genome Atlas (TCGA) database. The main dysregulated genes were subjected to multivariate and univariate analyses. The prognostic value of this system was studied via receiver operating characteristic curve and survival analysis. For further confirmation, the biomarkers' expression levels and predictive value were validated by immunohistochemistry (IHC) and qRT-PCR. The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in cervical cancer patients treated with radiation therapy. Results: Data for 17 radioresistant and 86 radiosensitive tumors were obtained from the The Cancer Genome Atlas database. 53 immune-related DEGs were identified. GO and KEGG analyses revealed that the DEGs were enriched in protein kinase B signaling, growth factors in cytokines, the MAPK pathway and the PI3K-Akt pathway. Then, 14 key immune-related genes built a risk scoring model were deemed prognostic in CESC with radiotherapy. The area under the curve (AUC) of the model was 0.723, and the high-risk group presented worse outcomes than the low-risk group. In addition, the high-risk group tended to have persistent tumors (p = 0.001). The high expression of WT1 and SPOUYT4 were associated with relapse, the high expression of Angiotensinogen and MIEN1 were associated with nonrelapse. Analysis of the immune microenvironment indicated that M0 macrophages, M2 macrophages, activated mast cells and resting memory CD4+ T cells were positively correlated with the risk score (p < 0.05). Conclusion: The novel immune-related risk scoring system has some advantages in predicting the prognosis and treatment response of cervical cancer patients treated with radiotherapy. Moreover, it might provide novel clues for providing targeted immune therapy to these patients.

Bargaining power of new-energy enterprises in China's credit-financing market.

The new-energy industry, which is a key area for coping with climate change, faces serious credit-financing difficulties. This study used a bilateral stochastic frontier model to measure the bargaining power of new-energy companies in China's credit-financing market. We then examined the main factors affecting the bargaining power of new-energy enterprises by comparing the results of the firms in different groups, including corporate-related factors, government policies, and financial development levels. The results showed that the bargaining power of both banks and enterprises had an important influence on the final financing price. In the bargaining process, new-energy companies were at a disadvantage, and financing prices were 17.2% higher than fair prices. The nature of state-owned enterprises hinders the improvement of the bargaining power of new-energy enterprises. Technology competence and relationships with banks are useful ways for new-energy enterprises to improve their bargaining power. In solving the financing difficulties in the credit market of new-energy enterprises, government subsidies are usually ineffective, while improving the financial development level is effective.

Curly fish scales-like Ni2.5Mo6S6.7 electrodeposited on PEDOT-rGO with uneven surface as ultrafast response electrode for electrocatalytic glucose, nitrite and hydrogen peroxide.

The difficulty to achieve rapid detection is the limitation of many enzyme-free sensors today. Thus, designing tri-functionalsensors with ultra-fast and efficientdeterminationis a challenging taskin biological science. Herein, curly fish scales-like Ni2.5Mo6S6.7 active materials was anchored on poly (3,4-ethylenedioxythiophene)-reduced graphene oxide (PEDOT-rGO) hybrid membranes with uneven surface (Ni2.5Mo6S6.7/PEDOT-rGO) as a high-performance tri-functional catalyst for glucose, nitrite and hydrogen peroxide determination.The sensor constructed under optimal conditions exhibited ultrafast response performance towards glucose and nitrite within 2 s, and hydrogen peroxide within 1 s. Meanwhile, it provided the wide linear range with a low detection limit towards glucose (as low as 0.001 mM and up to 15.000 mM, and 0.33 µM), nitrite (as low as 0.001 mM and up to 10.000 mM, and 0.33 µM) and hydrogen peroxide (from 0.010 mM to 7.000 mM, and 0.79 µM), respectively. In addition, the sensor demonstrated satisfied selectivity, repeatability, reproducibility and stability. Furthermore, the sensor has potential application in real samples. This study may provide a new strategy for the construction of tri-functional electrode materials with the ultra-fast response.

Nickel sulfide nanoworm network architecture as a binder-free high-performance non-enzymatic glucose sensor.

Nickel sulfide nanoworm (Ni3S2 NW) network architecture was directly grown on the poly (3,4-ethylenedioxythiophene)-reduced graphene oxide hybrid films (PEDOT-rGO HFs) modified on glassy carbon electrode (GCE), acting as a binder-free sensor for high-performance non-enzymatic glucose monitoring. The sensor exhibited the satisfactory sensitivity (2123 µA mM-1 cm-2), wide linear range (15~9105 µM), low detection limit (0.48 µM), and rapid response time (< 1.5 s) at a potential of 0.5 V (vs. SCE) in 0.1 M NaOH and possessed good selectivity, reproducibility, and stability. The enhanced electrocatalytic activity of the sensor towards glucose oxidation was attributed to the particular morphology, satisfying hydrophilic nature, strong combination between Ni3S2 NWs, PEDOT-rGO, and bare GCE. Moreover, it can be used for assaying glucose in human serum samples without dilution, indicating potential for clinical diagnostic applications. Graphical abstract Nickel sulfide nanoworms (Ni3S2 NWs)/poly (3,4-ethylenedioxythiophene)-reduced graphene oxide hybrid films (PEDOT-rGO HFs) were used to construct a binder-free high-performance non-enzymatic glucose sensor with satisfactory sensitivity, wide linear range, low detection limit, good selectivity, amazing reproducibility, and stability.

A glassy carbon electrode modified with graphene oxide, poly(3,4-ethylenedioxythiophene), an antifouling peptide and an aptamer for ultrasensitive detection of adenosine triphosphate.

An antifouling aptasensor is described for voltammetric determination of adenosine triphosphate (ATP). A glassy carbon electrode (GCE) was modified with a graphene oxide and poly(3,4-ethylenedioxythiophene) (GO-PEDOT) composite film by electrodeposition. Next, the zwitterionic peptide (EKEKEKE) was attached. It forms an antifouling layer on the modified GCE and serves as the support for subsequent aptamer immobilization. The resulting aptasensor typically is operated at a potential of 0.18 V (vs. SCE) using hexacyanoferrate as the electrochemical probe. It has a linear response in the 0.1 pM to 1.0 µM ATP concentration range, a 0.03 pM detection limit and a sensitivity of 2674.7 µA·µM-1·cm-2. It has outstanding selectivity, satisfactory reproducibility and desired stability. It was used to quantify ATP in ATP-spiked 10% serum solutions. Graphical abstract Schematic presentation of the construction of the aptamer based electrode for voltammetric determination of ATP.

A controllable honeycomb-like amorphous cobalt sulfide architecture directly grown on the reduced graphene oxide-poly(3,4-ethylenedioxythiophene) composite through electrodeposition for non-enzyme glucose sensing.

A facile, controllable two-step electrodeposition synthesis route was developed, whereby a honeycomb-like amorphous cobalt sulfide architecture was obtained via direct growth on a glassy carbon electrode (GCE) functionalized by a reduced graphene oxide-poly(3,4-ethylenedioxythiophene) (rGO-PEDOT) composite film as an electrode for glucose detection. This electrodeposition method is binder-free, rapid, low-cost and preparation-controlled. The effects of the concentration ratio between CoCl2·6H2O and thiourea, deposition scanning rate and deposition cycles on glucose detection were investigated, and the optimum preparation conditions were determined. The characterization results indicated that the honeycomb-like cobalt sulfide architecture was formed by growing vertically amorphous CoxSy nanosheets with a thickness of about 20-50 nm on the rGO-PEDOT surface, and the morphology of cobalt sulfide could be controlled by regulating the deposition cycles. Under optimal conditions, the sensor exhibited a wide linear range from 0.2 to 1380 µM (R2 = 0.9976), a sensitivity of 113.46 µA mM-1 cm-2, a low detection limit of 0.079 µM and a response time of 3 s. This sensor also displayed good selectivity, reproducibility and repeatability for non-enzyme glucose sensing. More importantly, the sensor was successfully used to determine glucose in human blood serum samples, and the results were consistent with hospital test results.