Design of Mineral Oil/Stearic Acid Hybrid Coatings for Reducing Hygroscopicity of Ammonium Nitrate.

Ammonium nitrate (AN) is a very promising high-energy oxidant for use in solid propellants but suffers from serious hygroscopicity. While various coating materials (e.g., surfactants) have been employed to mitigate the hygroscopicity of AN, the interaction mechanisms between AN and these coatings remain inadequately understood. Here, we report the preparation of a mineral oil/stearic acid (MO/SA) hybrid coating that significantly reduces the hygroscopicity of AN. The hygroscopicity of AN is efficiently inhibited through interactions between the NH4+ of AN molecules and the -COOH of SA molecules, resulting in the formation of a dense and hydrophobic coating. Additionally, the defects in the SA coating are compensated for by the MO film. Consequently, MO/SA@AN particles with a low mass ratio of the coating (1.35 wt %) exhibit a low hygroscopicity of 7.24% after being kept in a 90% relative humidity environment at 20 °C for 24 h, representing a 48.10% decline of the hygroscopicity. Furthermore, MO/SA@AN maintains a high rate of hygroscopicity decline, at 29.5%, even at 35 °C and 90% RH after 24 h. Additionally, the hybrid coating effectively accelerates the thermal decomposition reactions of AN. This study provides valuable insights into the development of hybrid coatings with excellent antihygroscopic properties for AN.

DNA methylation detection is a significant biomarker for screening endometrial cancer in premenopausal women with abnormal uterine bleeding.

OBJECTIVE: The aim of our study was to explore the value of DNA (CDO1m/CELF4m) methylation detection in exfoliated cervical cells collected for screening endometrial cancer in premenopausal women with abnormal uterine bleeding. METHODS: A total of 296 premenopausal women with abnormal uterine bleeding admitted to the Department of Obstetrics and Gynecology at the Third Xiangya Hospital of Central South University from November 2021 to October 2022 were selected. Clinical characteristics, endometrial thickness measured by transvaginal ultrasound and serum CA125 were collected. Exfoliated cervical cells from the thinPrep cytogic test were collected for DNA (CDO1m/CELF4m) methylation testing. Endometrial tissue was collected under hysteroscopy for pathological diagnosis as the gold standard. A univariate logistic regression model was used to analyze risk factors for endometrial cancer. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to measure the diagnostic efficacy of DNA methylation detection in endometrial cancer screening of women with abnormal uterine bleeding. RESULTS: Univariate logistic regression analysis showed that age, body mass index (BMI) ≥25 kg/m2, endometrial thickness ≥11 mm, CDO1 methylation (CDO1mΔCt≤8.4), CELF4 methylation (CELF4mΔCt≤8.8), and dual gene methylation (CDO1mΔCt≤8.4 or CELF4mΔCt≤8.8) were independent risk factors for endometrial cancer in women with abnormal uterine bleeding. The odds ratio (OR) values (95% confidence interval (CI) were 0.87 (0.80-0.95), 4.76 (1.89-11.96), 8.41 (3.13-22.59), 64.49 (20.46-203.33), 12.79 (4.91-33.30), and 42.53 (11.90-152.04), respectively. Among these indicators, dual gene methylation had the higher sensitivity and specificity for endometrial cancer screening (85.7% and 87.6%). Moreover, dual gene methylation combined with BMI or endometrial thickness could further improve the screening efficiency of endometrial cancer in women with abnormal uterine bleeding. CONCLUSIONS: In premenopausal women with abnormal uterine bleeding, the clinical efficacy of DNA (CDO1m/CELF4m) methylation detection in exfoliated cervical cells for endometrial cancer screening was better than that of other noninvasive clinical indicators. In addition, dual gene methylation combined with BMI or endometrial thickness was a good predictor of endometrial cancer screening.

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.

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.

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.

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.