METTL14 decreases FTH1 mRNA stability via m6A methylation to promote sorafenib-induced ferroptosis of cervical cancer.

Cervical cancer (CC) is a prevalent malignancy among women worldwide. This study was designed to investigate the role of METTL14 in sorafenib-induced ferroptosis in CC. METTL14 expression and m6A methylation were determined in CC tissues, followed by analyzes correlating these factors with clinical features. Subsequently, METTL14 was knocked down in CC cell lines, and the effects on cell proliferation, mitochondrial morphology and ferroptosis were assessed using CCK-8, microscopy, and markers associated with ferroptosis, respectively. The regulatory relationship between METTL14 and FTH1 was verified using qRT-PCR and luciferase reporter assays. The functional significance of this interaction was further investigated both in vitro and in vivo by co-transfecting cells with overexpression vectors or shRNAs targeting METTL14 and FTH1 after sorafenib treatment. METTL14 expression and m6A methylation were significantly reduced in CC tissues, and lower METTL14 expression levels were associated with a poorer CC patients' prognosis. Notably, METTL14 expression increased during sorafenib-induced ferroptosis, and METTL14 knockdown attenuated the ferroptotic response induced by sorafenib in CC cells. FTH1 was identified as a direct target of METTL14, with METTL14 overexpression leading to increased m6A methylation of FTH1 mRNA, resulting in reduced stability and expression of FTH1 in CC. Furthermore, FTH1 overexpression or treatment with LY294002 partially counteracted the promotion of sorafenib-induced ferroptosis by METTL14. In vivo xenograft experiments demonstrated that inhibiting METTL14 reduced the anticancer effects of sorafenib, whereas suppression of FTH1 significantly enhanced sorafenib-induced ferroptosis and increased its anticancer efficacy. METTL14 reduces FTH1 mRNA stability through m6A methylation, thereby enhancing sorafenib-induced ferroptosis, which contributes to suppressing CC progression via the PI3K/Akt signaling pathway.

Neuron-Like Silicone Nanofilaments@Montmorillonite Nanofillers of PEO-Based Solid-State Electrolytes for Lithium Metal Batteries with Wide Operation Temperature.

Poly(ethylene oxide) (PEO)-based composite solid electrolytes (CSEs) are promising to accelerate commercialization of solid-state lithium metal batteries (SSLMBs). Nonetheless, this is hindered by the CSEs' limited ion conductivity at room temperature. Here, we propose design, synthesis, and application of the bioinspired neuron-like nanofillers for PEO-based CSEs. The neuron-like superhydrophobic nanofillers are synthesized by controllably grafting silicone nanofilaments onto montmorillonite nanosheets. Compared to various reported fillers, the nanofillers can greatly improve ionic conductivity (4.9×10-4 S cm-1, 30 °C), Li+ transference number (0.63), oxidation stability (5.3 V) and mechanical properties of the PEO-based CSEs because of the following facts. The distinctive neuron-like structure and the resulting synaptic-like connections establish numerous long-distance continuous channels over various directions in the PEO-based CSEs for fast and uniform Li+ transport. Consequently, the assembled SSLMBs with the CSEs and LiFePO4 or NCM811 cathodes display superior cycling stability over a wide temperature range of 50 °C to 0 °C. Surprisingly, the pouch batteries with the large-scale prepared CSEs kept working after being repeatedly bent, folded, cut or even punched in air. We believe that design of neuron-like nanofillers is a viable approach to produce CSEs with high room temperature ionic conductivity for SSLMBs.

Flavonoids From the Aerial Parts of Sophora tonkinensis and Their Potential Anti-Inflammatory Activities.

Four undescribed prenylated flavonoids, sophoratones A-D (1-4), and 17 known flavonoids, were obtained from the aerial parts of Sophora tonkinensis. Their structures with absolute configurations were elucidated by detailed interpretation of NMR spectroscopy, mass spectrometry, and ECD calculations. Meanwhile, the ability of these compounds to inhibit the release of nitric oxide (NO) by a lipopolysaccharide induced mouse in RAW 264.7 cells was assayed. The results indicated that some compounds exhibited clear inhibitory effects, with IC50 ranging from 19.91±1.08 to 35.72±2.92 µM. These results suggest that prenylated flavonoids from the aerial parts of S. tonkinensis could potentially be used as a latent source of anti-inflammatory agents.

Deep Learning Promotes Profiling of Multiple miRNAs in Single Extracellular Vesicles for Cancer Diagnosis.

Extracellular vesicle microRNAs (EV miRNAs) are critical noninvasive biomarkers for early cancer diagnosis. However, accurate cancer diagnosis based on bulk analysis is hindered by the heterogeneity among EVs. Herein, we report an approach for profiling single-EV multi-miRNA signatures by combining total internal reflection fluorescence (TIRF) imaging with a deep learning (DL) algorithm for the first time. This innovative technique allows for the precise characterization of EV miRNAs at the single-vesicle level, overcoming the challenges posed by EV heterogeneity. TIRF with high resolution and a signal-to-noise ratio can simultaneously detect multi-miRNAs in situ in individual EVs. DL algorithm avoids complicated and inaccurate artificial feature extraction, achieving automated high-resolution image analysis. Using this approach, we reveal that the main variation of EVs from 5 cancer cells and normal plasma is the triple-positive EV subpopulation, and the classification accuracy of single triple-positive EVs from 6 sources can reach above 95%. In the clinical cohort, 20 patients (5 lung cancer, 5 breast cancer, 5 cervical cancer, and 5 colon cancer) and 5 healthy controls are predicted with an overall accuracy of 100%. This single-EV strategy provides new opportunities for exploring more specific EV biomarkers to achieve cancer diagnosis and classification.

Colony-stimulating factor-1 receptor inhibition combined with paclitaxel exerts effective antitumor effects in the treatment of ovarian cancer.

Ovarian cancer is the tumor with the highest mortality among gynecological malignancies. Studies have confirmed that paclitaxel chemoresistance is associated with increased infiltration of tumor-associated macrophages (TAMs) in the microenvironment. Colony-stimulating factor 1 (CSF-1) receptor (CSF-1R) plays a key role in regulating the number and differentiation of macrophages in certain solid tumors. There are few reports on the effects of targeted inhibition of CSF-1R in combination with chemotherapy on ovarian cancer and the tumor microenvironment. Here, we explored the antitumor efficacy and possible mechanisms of the CSF - 1R inhibitor pexidartinib (PLX3397) when combined with the first-line chemotherapeutic agent paclitaxel in the treatment of ovarian cancer. We found that CSF-1R is highly expressed in ovarian cancer cells and correlates with poor prognosis. Treatment by PLX3397 in combination with paclitaxel significantly inhibited the growth of ovarian cancer both in vitro and in vivo. Blockade of CSF-1R altered the macrophage phenotype and reprogrammed the immunosuppressive cell population in the tumor microenvironment.

The proteolytic activity in inflammatory bowel disease: insight from gut microbiota.

Inflammatory bowel disease (IBD) is a chronic, recurrent inflammatory disease caused by the destruction of the intestinal mucosal epithelium that affects a growing number of people worldwide. Although the etiology of IBD is complex and still elucidated, the role of dysbiosis and dysregulated proteolysis is well recognized. Various studies observed altered composition and diversity of gut microbiota, as well as increased proteolytic activity (PA) in serum, plasma, colonic mucosa, and fecal supernatant of IBD compared to healthy individuals. The imbalance of intestinal microecology and intestinal protein hydrolysis were gradually considered to be closely related to IBD. Notably, the pivotal role of intestinal microbiota in maintaining proteolytic balance received increasing attention. In summary, we have speculated a mesmerizing story, regarding the hidden role of PA and microbiota-derived PA hidden in IBD. Most importantly, we provided the diagnosis and therapeutic targets for IBD as well as the formulation of new treatment strategies for other digestive diseases and protease-related diseases.

Gut microbiome: decision-makers in the microenvironment of colorectal cancer.

Colorectal cancer (CRC) is a common malignancy of the gastrointestinal tract, accounting for the second most common cause of gastrointestinal tumors. As one of the intestinal barriers, gut bacteria form biofilm, participate in intestinal work, and form the living environment of intestinal cells. Metagenomic next-generation sequencing (mNGS) of the gut bacteria in a large number of CRC patients has been established, enabling specific microbial signatures to be associated with colorectal adenomato-carcinoma. Gut bacteria are involved in both benign precursor lesions (polyps), in situ growth and metastasis of CRC. Therefore, the term tumorigenic bacteria was proposed in 2018, such as Escherichia coli, Fusobacterium nucleatum, enterotoxigenic Bacteroides fragilis, etc. Meanwhile, bacteria toxins (such as cytolethal distending toxin (CDT), Colibactin (Clb), B. fragilis toxin) affect the tumor microenvironment and promote cancer occurrence and tumor immune escape. It is important to note that there are differences in the bacteria of different types of CRC. In this paper, the role of tumorigenic bacteria in the polyp-cancer transformation and the effects of their secreted toxins on the tumor microenvironment will be discussed, thereby further exploring new ideas for the prevention and treatment of CRC.

Magnetocardiography-based coronary artery disease severity assessment and localization using spatiotemporal features.

Objective.This study aimed to develop an automatic and accurate method for severity assessment and localization of coronary artery disease (CAD) based on an optically pumped magnetometer magnetocardiography (MCG) system.Approach.We proposed spatiotemporal features based on the MCG one-dimensional signals, including amplitude, correlation, local binary pattern, and shape features. To estimate the severity of CAD, we classified the stenosis as absence or mild, moderate, or severe cases and extracted a subset of features suitable for assessment. To localize CAD, we classified CAD groups according to the location of the stenosis, including the left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA), and separately extracted a subset of features suitable for determining the three CAD locations.Main results.For CAD severity assessment, a support vector machine (SVM) achieved the best result, with an accuracy of 75.1%, precision of 73.9%, sensitivity of 67.0%, specificity of 88.8%, F1-score of 69.8%, and area under the curve of 0.876. The highest accuracy and corresponding model for determining locations LAD, LCX, and RCA were 94.3% for the SVM, 84.4% for a discriminant analysis model, and 84.9% for the discriminant analysis model.Significance. The developed method enables the implementation of an automated system for severity assessment and localization of CAD. The amplitude and correlation features were key factors for severity assessment and localization. The proposed machine learning method can provide clinicians with an automatic and accurate diagnostic tool for interpreting MCG data related to CAD, possibly promoting clinical acceptance.

Co-registration of OPM-MCG signals with CT using optical scanning.

Magnetocardiography (MCG) can be used to noninvasively measure the electrophysiological activity of myocardial cells. The high spatial resolution of magnetic source localization can precisely determine the location of cardiomyopathy, which is of great significance for the diagnosis and treatment of cardiovascular disease. To perform magnetic source localization, MCG data must be co-registered with anatomical images. We propose a co-registration method that can be applied to OPM-MCG systems. In this method, the sensor array and the trunk of the subject are scanned using structured light-scanning technology, and the scan results are registered with the reconstructed structure using computed tomography (CT). This can increase the number of effective cloud points acquired and reduce the interference from respiratory motion. The scanning bed of the OPM-MCG system was modified to be consistent with the CT device, ensuring that the state of the body remains consistent between the cardiac magnetometry measurements and CT scans.

Characteristics and statistical analysis of university accidents in China from 2017 to 2021.

University accidents in China are frequent, and to find out the relationship pattern of factors influencing accidents, 248 university accidents occurring within 2017-2021 were studied using difference analysis (Independent-samples T-test, Mann-Whitney U test), logistic regression analysis, and diagnostic analysis of receiver operating characteristic curves. The results show: The variability in time, space, and qualifications was statistically significant (p < 0.05), and when the number of university safety policies ≥77 would significantly reduce the frequency of university accidents, with an influence strength value of 0.884 and a diagnostic accuracy of 79.8 %. In addition, the perpetrators, the time and the location of the accidents were usually undergraduate students, first semester of university, and economically developed and educationally rich provinces, respectively, with influence strength value and diagnostic accuracy of greater than 1 and 70%, respectively. Finally, specific suggestions are offered for the future prevention and reduction of accidents at the University based on the findings of the studies.

Challenges and strategies for commercialization and widespread practical applications of superhydrophobic surfaces.

Superhydrophobic (SH) surfaces have progressed rapidly in fundamental research over the past 20 years, but their practical applications lag far behind. In this perspective, we first present the findings of a survey on the current state of SH surfaces including fundamental research, patenting, and commercialization. On the basis of the survey and our experience, this perspective explores the challenges and strategies for commercialization and widespread practical applications of SH surfaces. The comprehensive performances, preparation methods, and application scenarios of SH surfaces are the major constraints. These challenges should be addressed simultaneously, and the actionable strategies are provided. We then highlight the standard test methods of the comprehensive performances including mechanical stability, impalement resistance, and weather resistance. Last, the prospects of SH surfaces in the future are discussed. We anticipate that SH surfaces may be widely commercialized and used in practical applications around the year 2035 through combination of the suggested strategies and input from both academia and industry.