Titanium Dioxide and Calcium Sulfate Whiskers Are Used for the Preparation of High Performance Polypropylene and Reduce White Pollution.

The anti-aging agent TiO2-polyacrylonitrile (PAN) and the mechanical strengthening agent CSW-PAN were prepared by radical polymerization using rutile nano-titanium dioxide (TiO2) and anhydrous calcium sulfate whisker (CSW) as raw materials. The structures of TiO2-PAN and CSW-PAN were characterized using Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS). Simultaneously, the mechanical properties, aging properties, and thermal stability of TiO2-PAN/CSW-PAN/polypropylene (PP) composites were studied, and the results showed that the surfaces of nano-titanium dioxide and calcium sulfate whiskers were successfully grafted with acrylonitrile. Owing to the introduction of new elements, such as acrylonitrile, nano-titanium dioxide and calcium sulfate whiskers have anti-aging properties. In comparison of the impact strength and tensile strength of TiO2-PAN/PP and TiO2-PAN/CSW-PAN/PP before aging, it can be proven that adding CSW-PAN can significantly enhance the mechanical properties of TiO2-PAN/CSW-PAN/PP. After 1000 h of aging, the tensile strength of the ternary composite TiO2-PAN/CSW-PAN/PP was 19.88 MPa when the addition amount of TiO2-PAN and CSW-PAN was 3%. Moreover, the impact strength of the ternary composite material TiO2-PAN/CSW-PAN/PP after 1000 h of aging is even better than that of non-aging pure PP materials, proving that the service life of improved PP products is extended, unnecessary waste and environmental pollution can be relieved, and the needs of specific engineering fields can be met.

Design, synthesis, and bioevaluation of SOS1 PROTACs derived from pyrido[2,3-d]pyrimidin-7-one-based SOS1 inhibitor.

Oncogenic KRAS mutations drive an approximately 25 % of all human cancers. Son of Sevenless 1 (SOS1), a critical guanine nucleotide exchange factor, catalyzes the activation of KRAS. Targeting SOS1 degradation has engaged as a promising therapeutic strategy for KRAS-mutant cancers. Herein, we designed and synthesized a series of novel CRBN-recruiting SOS1 PROTACs using the pyrido[2,3-d]pyrimidin-7-one-based SOS1 inhibitor as the warhead. One representative compound 11o effectively induced the degradation of SOS1 in three different KRAS-mutant cancer cell lines with DC50 values ranging from 1.85 to 7.53 nM. Mechanism studies demonstrated that 11o-induced SOS1 degradation was dependent on CRBN and proteasome. Moreover, 11o inhibited the phosphorylation of ERK and displayed potent anti-proliferative activities against SW620, A549 and DLD-1 cells. Further optimization of 11o may provide us promising SOS1 degraders with favorable drug-like properties for developing new chemotherapies targeting KRAS-driven cancers.

Effects of Lactobacillus acidophilus AC on the growth, intestinal flora and metabolism of zebrafish (Danio rerio).

The intensive aquaculture model has resulted in a heightened prevalence of diseases among farmed animals. It is imperative to identify healthy and efficacious alternatives to antibiotics for the sustainable progression of aquaculture. In this investigation, a strain of Lactobacillus acidophilus AC was introduced into the cultural water at varying concentrations (105 CFU/mL, 106 CFU/mL, 107 CFU/mL) to nourish zebrafish (Danio rerio). The findings revealed that L. acidophilus AC effectively increased the growth performance of zebrafish, improved the ion exchange capacity of gills, and enhanced hepatic antioxidant and immune-enzyme activities. Furthermore, L. acidophilus AC notably enhanced the intestinal morphology and augmented the activity of digestive enzymes within the intestinal tract. Analysis of intestinal flora revealed that L. acidophilus AC exerted a significant impact on the intestinal flora community, manifested by a reduction in the relative abundance of Burkholderiales, Candidatus_Saccharibacteria_bacterium, and Sutterellaceae, coupled with an increase in the relative abundance of Cetobacterium. Metabolomics analysis demonstrated that L. acidophilus AC significantly affected intestinal metabolism of zebrafish. PG (i-19:0/PGE2) and 12-Hydroxy-13-O-d-glucuronoside-octadec-9Z-enoate were the metabolites with the most significant up- and down-regulation folds, respectively. Finally, L. acidophilus AC increased the resistance of zebrafish to Aeromonas hydrophila. In conclusion, L. acidophilus AC was effective in enhancing the health and immunity of zebrafish. Thus, our findings suggested that L. acidophilus AC had potential applications and offered a reference for its use in aquaculture.

Unlocking the potential: T1-weighed MRI as a powerful predictor of levodopa response in Parkinson's disease.

BACKGROUND: The efficacy of levodopa, the most crucial metric for Parkinson's disease diagnosis and treatment, is traditionally gauged through the levodopa challenge test, which lacks a predictive model. This study aims to probe the predictive power of T1-weighted MRI, the most accessible modality for levodopa response. METHODS: This retrospective study used two datasets: from the Parkinson's Progression Markers Initiative (219 records) and the external clinical dataset from Ruijin Hospital (217 records). A novel feature extraction method using MedicalNet, a pre-trained deep learning network, along with three previous approaches was applied. Three machine learning models were trained and tested on the PPMI dataset and included clinical features, imaging features, and their union set, using the area under the curve (AUC) as the metric. The most significant brain regions were visualized. The external clinical dataset was further evaluated using trained models. A paired one-tailed t-test was performed between the two sets; statistical significance was set at p < 0.001. RESULTS: For 46 test set records (mean age, 62 ± 9 years, 28 men), MedicalNet-extracted features demonstrated a consistent improvement in all three machine learning models (SVM 0.83 ± 0.01 versus 0.73 ± 0.01, XgBoost 0.80 ± 0.04 versus 0.74 ± 0.02, MLP 0.80 ± 0.03 versus 0.70 ± 0.07, p < 0.001). Both feature sets were validated on the clinical dataset using SVM, where MedicalNet features alone achieved an AUC of 0.64 ± 0.03. Key responsible brain regions were visualized. CONCLUSION: The T1-weighed MRI features were more robust and generalizable than the clinical features in prediction; their combination provided the best results. T1-weighed MRI provided insights on specific regions responsible for levodopa response prediction. CRITICAL RELEVANCE STATEMENT: This study demonstrated that T1w MRI features extracted by a deep learning model have the potential to predict the levodopa response of PD patients and are more robust than widely used clinical information, which might help in determining treatment strategy. KEY POINTS: This study investigated the predictive value of T1w features for levodopa response. MedicalNet extractor outperformed all other previously published methods with key region visualization. T1w features are more effective than clinical information in levodopa response prediction.