Long-term 4-nonylphenol exposure drives cervical cell malignancy through MAPK-mediated ferroptosis inhibition.

4-NP (4-nonylphenol), a prevalent environmental endocrine disruptor with estrogenic properties, is commonly detected in drinking water and food sources. It poses a significant risk of endocrine disruption, thereby influencing the onset and progression of diverse diseases, including tumorigenesis. However, its specific impact on cervical cancer remains to be fully elucidated. Our study focused on the biological effects of sustained exposure to low-dose 4-NP on human normal cervical epithelial cells (HcerEpic). After a continuous 30-week exposure to 4-NP, the treated cells exhibited a significant malignant transformation, whereas the solvent control group showed limited malignant phenotypes. Subsequent analyses of the metabolomic profiles of the transformed cells unveiled marked irregularities in glutathione metabolism and unsaturated fatty acid metabolism. Analyses of transcriptomic profiles revealed significant activation of the MAPK signaling pathway and suppression of ferroptosis processes in these cells. Furthermore, the expression of MT2A was significantly upregulated following 4-NP exposure. Knockdown of MT2A restored the aberrant activation of the MAPK signaling pathway, elevated antioxidant capacity, ferroptosis inhibition, and ultimately the development of malignant phenotypes that induced by 4-NP in the transformed cells. Mechanistically, MT2A increased cellular antioxidant capabilities and facilitated the removal of toxic iron ions by enhancing the phosphorylation of ERK1/2 and JNK MAPK pathways. The administration of activators and inhibitors of the MAPK pathway confirmed that the MAPK pathway mediated the 4-NP-induced suppression of ferroptosis and, ultimately, the malignant transformation of cervical epithelial cells. Overall, our findings elucidated a dynamic molecular transformation induced by prolonged exposure to 4-NP, and delineated comprehensive biological perspectives underlying 4-NP-induced cervical carcinogenesis. This offers novel theoretical underpinnings for the assessment of the carcinogenic risks associated with 4-NP.

LINC00426, a novel m6A-regulated long non-coding RNA, induces EMT in cervical cancer by binding to ZEB1.

PURPOSE: To explore the function and molecular mechanism of LINC00426 in Cervical Cancer (CC), and to explore the clinical treatment strategy of LINC00426 for CC. METHODS: Bioinformatics analysis was used to explore the expression of LINC00426 and patient prognosis of CC. Cell function experiments were conducted to explore the potential effect of LINC00426 on CC malignant phenotypes. The difference in m6A modification level between the high and low expression groups of LINC00426 was analyzed by detecting the total m6A level. The luciferase reporter assay was used to confirm the binding of miR-200a-3p to LINC00426. The RIP assay was used to confirm the binding of LINC00426 to ZEB1. Cell viability assay was performed to detect the effect of LINC00426 on cellular drug resistance. RESULTS: LINC00426 is up-regulated in CC, which can enhance the proliferation, migration and invasion of CC cells. METTL3 promotes the expression of LINC00426 by m6A methylation modification. In addition, the LINC00426/miR-200a-3p/ZEB1 axis affects the proliferation, migration, and invasion of CC by regulating the expression of EMT markers. Through the detection of cell viability, we observed that overexpression LINC00426 in cells resulted in resistance to cisplatin and bleomycin, and more sensitive to imatinib. CONCLUSION: LINC00426 is a cancer-promoting lncRNA related to m6A modification. The process of EMT in CC is regulated by the LINC00426/miR-200a/3p/ZEB1 axis. LINC00426 can affect the sensitivity of CC cells to chemotherapy drugs, and is expected to become a therapeutic target for CC.

An improved UAV target detection algorithm based on ASFF-YOLOv5s.

Object detection in drone-captured scenarios is a recent popular task. Due to the high flight altitude of unmanned aerial vehicle (UAV), the large variation of target scales, and the existence of dense occlusion of targets, in addition to the high requirements for real-time detection. To solve the above problems, we propose a real-time UAV small target detection algorithm based on improved ASFF-YOLOv5s. Based on the original YOLOv5s algorithm, the new shallow feature map is passed into the feature fusion network through multi-scale feature fusion to improve the extraction capability for small target features, and the Adaptively Spatial Feature Fusion (ASFF) is improved to improve the multi-scale information fusion capability. To obtain anchor frames for the VisDrone2021 dataset, we improve the K-means algorithm to obtain four different scales of anchor frames on each prediction layer. The Convolutional Block Attention Module (CBAM) is added in front of the backbone network and each prediction network layer to improve the capture capability of important features and suppress redundant features. Finally, to address the shortcomings of the original GIoU loss function, the SIoU loss function is used to accelerate the convergence of the model and improve accuracy. Extensive experiments conducted on the dataset VisDrone2021 show that the proposed model can detect a wide range of small targets in various challenging environments. At a detection rate of 70.4 FPS, the proposed model obtained a precision value of 32.55%, F1-score of 39.62%, and a mAP value of 38.03%, which improved 2.77, 3.98, and 5.1%, respectively, compared with the original algorithm, for the detection performance of small targets and to meet the task of real-time detection of UAV aerial images. The current work provides an effective method for real-time detection of small targets in UAV aerial photography in complex scenes, and can be extended to detect pedestrians, cars, etc. in urban security surveillance.

Post-transcriptional regulation of tumor suppressor gene lncRNA CARMN via m6A modification and miRNA regulation in cervical cancer.

PURPOSE: The abnormal regulation of lncRNA CARMN has been proved to be a tumor suppressor gene of cervical cancer (CC). However, its role in CC is still elusive. The regulation of CARMN post-transcriptional level by m6A modification and miRNA has not been studied. This study aims to analyze the molecular mechanism of m6A modification and miRNA on the abnormal expression of CARMN in CC cells, so as to provide a new theoretical basis for the diagnosis and treatment of CC. METHODS: MeRIP-seq was used to identify the differential m6A-modified genes between tumor and normal cervical tissues. RT-qPCR assay was used to detect gene expression levels in tissues or cells. The m6A modification sites of CARMN was predicted by bioinformatics, and the modification of m6A and its regulatory effect on CARMN were analyzed by MeRIP-qPCR, Actinomycin D assay and RIP assay. RIP-microarray combined with bioinformatics methods to screen miRNAs that may target CARMN. The regulation mechanism between miRNA and CARMN was verified by RT-qPCR, nucleo-plasmic separation assay, mRNA stability assay, dual-luciferase reporter assay, and in vivo experiments. RESULTS: MeRIP-seq found that CARMN is a significant different gene in the abundance of m6A in CC, and the modification level of m6A in CC tissues was higher than that in normal cervical tissues. Further, this study verified that m6A reader YTHDF2 could recognize m6A-modified CARMN and promote its degradation in CC cells. miR-21-5p was proved to be the downstream target gene of CARMN, and miR-21-5p could negatively regulate the expression of CARMN. Further experiments showed that miR-21-5p could directly bind to CARMN and lead to the degradation of CARMN. The in vivo experimental results indicated that the level of miR-21-5p in the overexpressed CARMN group was significantly lower than that in the control group. CONCLUSION: m6A modification and miR-21-5p play important roles in promoting the occurrence and development of tumors by regulating CARMN, provide new potential targets for the treatment of CC.

Gene signature of m6A RNA regulators in diagnosis, prognosis, treatment, and immune microenvironment for cervical cancer.

Continuing studies imply that m6A RNA modification is involved in the development of cervical cancer (CC), but lack strong support on recurrence and diagnosis prediction. In this research, a comprehensive analysis of 33 m6A regulators was performed to fulfill them. Here, we performed diagnostic and prognosis models and identified key regulators, respectively. Then the CC patients were separated into two clusters in accordance with 33 regulators, and participants in the cluster 1 had a worse prognosis. Subsequently, the m6AScore was calculated to quantify the m6A modification pattern based on regulators and we found that patients in cluster 1 had higher m6AScore. Afterwards, immune microenvironment, cell infiltration, escape analyses and tumor burden mutation analyses were executed, and results showed that m6AScore was correlated with them, but to a limited extent. Interestingly, HLAs and immune checkpoint expression, and immunophenoscore in patients with high-m6AScores were significantly lower than those in the low-m6AScore group. These suggested the m6AScores might be used to predict the feasibility of immunotherapy in patients. Results provided a distinctive perspective on m6A modification and theoretical basis for CC diagnosis, prognosis, clinical treatment strategies, and potential mechanism exploration.

Comprehensive analysis of prognosis-related alternative splicing events in ovarian cancer.

Ovarian cancer (OV) is characterized by high incidence and poor prognosis. Increasing evidence indicates that aberrant alternative splicing (AS) events are associated with the pathogenesis of cancer. We examined prognosis-related alternative splicing events and constructed a clinically applicable model to predict patients' outcomes. Public database including The Cancer Genome Atlas (TCGA), TCGA SpliceSeq, and the Genomics of Drug Sensitivity in Cancer databases were used to detect the AS expression, immune cell infiltration and IC50. The prognosis-related AS model was constructed and validated by using Cox regression, LASSO regression, C-index, calibration plots, and ROC curves. A total of eight AS events (including FLT3LG|50942|AP) were selected to establish the prognosis-related AS model. Compared with high-risk group, low-risk group had a better outcome (P = 1.794e-06), was more sensitive to paclitaxel (P = 0.022), and higher proportions of plasma cells. We explored the upstream regulatory mechanisms of prognosis-related AS and found that two splicing factor and 156 tag single nucleotide polymorphisms may be involved in the regulation of prognosis-related AS. In order to assess patient prognosis more comprehensively, we constructed a clinically applicable model combining risk score and clinicopathological features, and the 1 -, and 3-year AUCs of the clinically applicable model were 0.812, and 0.726, which were 7.5% and 3.3% higher than that of the risk score. We constructed a prognostic signature for OV patients and comprehensively analysed the regulatory characteristics of the prognostic AS events in OV.

Construction of a hypoxia-immune-related prognostic model and targeted therapeutic strategies for cervical cancer.

Emerging evidence indicates that hypoxia and immunity play important roles in tumorigenesis and development. However, the hypoxia-immune-related prognostic risk model has not been established in cervical cancer (CC). We aimed to construct a hypoxia-immune-related prognostic risk model, which has potential application in predicting the prognosis of CC patients and the response to targeted therapy. The RNA-seq data and corresponding clinical information were retrieved from The Cancer Genome Atlas (TCGA) database. The hypoxia status and immune status of CC patients were evaluated using the Consensus Clustering method and single-sample gene set enrichment analysis (ssGSEA), respectively. The univariate Cox regression, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were applied to establish the prognostic risk model of CC. The chemotherapy response for six chemotherapeutic agents of each CC patient was calculated according to the Genomics of Drug Sensitivity in Cancer (GDSC). And the Connectivity Map (CMap) database was performed to screen candidate small-molecule drugs. In this study, we identified seven gene signatures (P4HA2, MSMO1, EGLN1, ZNF316, IKZF3, ISCU and MYO1B) with prognostic values. And the survival time of patients with low risk was significantly longer than those with high risk. Meanwhile, CC patients in the high-risk group yielded higher sensitivity to five chemotherapeutic agents. And we listed 10 candidate small-molecule drugs that exhibited a high correlation with the prognosis of CC. Thus, the prognostic model can accurately predict the prognosis of patients with CC and may be helpful for the development of new hypoxia-immune prognostic markers and therapeutic strategies for CC.

An excellent electrochemical aptasensor for amyloid-ß oligomers based on a triple-helix aptamer switch via target-triggered signal transduction DNA displacement events.

An excellent aptasensor for electrochemical detection of amyloid-ß oligomers (AßOs) at trace levels was fabricated based on a triple-helix aptamer switch (THAS) via target-triggered signal transduction DNA displacement events. Specifically, a single-stranded anti-AßO aptamer (Apt) carrying two symmetrical arm segments was first attached via Au-S binding to an Au electrode. Gold nanoparticle (GNP)-tagged signal transduction probes (GNP-STPs) were simultaneously hybridized with the two arm segments of the Apt, and a rigid THAS was formed on the Au electrode. Compared to the conventional hybrid, the number of GNPs on the Au electrode increased significantly with the THAS, effectively improving the stability of the Apt to avoid lodging. Trithiocyanuric acid (TA) was utilized to further gather the GNPs and form network-like TA/GNPs. As a result, the differential pulse voltammetry (DPV) response of GNPs was clearly enhanced. When AßOs were present, target-triggered signal transduction DNA displacement events were carried out from THAS via the reaction of the Apt with the AßOs, which caused the GNP-STP to dissociate from the Au electrode, and thus a significant reduction in the DPV response was observed. The assay was able to sensitively detect trace AßOs by monitoring the AßO-controlled DPV response change. It exhibited a wide linear range from 1 fM to 10 pM with a low detection limit of 0.5 fM, and was successfully employed for the determination of AßOs in 20 serum samples, with good recovery. Moreover, the developed assay can provide a sensitive and selective platform for many studies or investigations related to Alzheimer's disease (AD) monitoring and treatment.

Switchable electrochemical aptasensor for amyloid-ß oligomers detection based on triple helix switch coupling with AuNPs@CuMOF labeled signaling displaced-probe.

The aggregation of amyloid-ß oligomers (AßOs) with extremely strong neurotoxicity has been proved to be the main pathogenesis of Alzheimer's disease (AD). For sensitive quantification of AßOs, a switchable electrochemical aptasensor is proposed. Metal organic framework carrying Au nanoparticles (AuNPs@CuMOF) has been used to label signaling displaced-probe (SD), which formed triple helix switch (THS) by hybridizing with label-free anti-AßOs aptamer (Apt) on the electrodeposited palladium electrode (EPd). Thus, a relatively strong response of differential pulse voltammetry (DPV) was produced (switch on). With the specific binding between AßOs and Apt, the DPV response obviously decreased, owing to destroyed structure of THS and the separation of AuNPs@CuMOF/SD from the EPd (switch off). The mode of "switch on-off" can dramatically enhance the AßOs-dependent DPV intensity change. As a result, the switchable EA exhibited excellent selectivity and sensitivity with the linear range from 0.5 fM to 500 fM and the detection limit of 0.25 fM. When evaluating the AßOs of artificial cerebrospinal fluid (aCSF) samples, the switchable EA exhibited desirable feasibility, and the results are basically consistent with the enzyme linked immunosorbent assay (ELISA). The work could provide a potential tool of the AD diagnosis and a bright future in clinical applications.

Breakfast prevalence of medical students is higher than students from nonmedical faculties in Inner Mongolia Medical University.

BACKGROUND: Skipping breakfast is becoming common worldwide. Our previous studies showed that the breakfast prevalence was relatively low. METHODS: In three cross-sectional studies, breakfast prevalence in various populations in Inner Mongolia Medical University campus in 2011, 2013 and 2017 was investigated. Risk of skipping breakfast in 2017 was analyzed. In follow-up study, the incidence, RR, AR% and PAR% of eating and skipping breakfast from 2011 to 2013 were calculated. RESULTS: Data of 18,231 individuals were collected. Breakfast prevalence growth was 16.1% during the seven years. The annulus growth of breakfast prevalence was 9.3% (2013 vs 2011, P < 0.001) and 6.3% (2017 vs 2013, P < 0.001). The breakfast prevalence of three cross-sectional studies (73.0 vs 64.9%, P < 0.001; 79.5 vs 69.6%, P < 0.001; and 82.8 vs 77.4%, P < 0.001) and the breakfast incidence of a two-year follow-up study (70.6 vs 48.5% 95% CI: 1.12-1.90) both showed that breakfast consumption in medical students is higher than that in students from nonmedical faculties. The seven-year average breakfast prevalence of male and female medical students (70.0 and 82.5%) was 1.31 (95% CI: 1.23-1.39) and 1.09 (95% CI: 1.06-1.11) that of male and female students from nonmedical faculties (53.6 and 75.8%), respectively. CONCLUSION: Medical students have a higher breakfast consumption than nonmedical students. Male students from nonmedical faculties have the lowest breakfast prevalence and the highest breakfast skip risk in our university.