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Traditional Chinese medicine (TCM) serves as a significant adjunct to chemical treatment for chronic diseases. For instance, the administration of Baitouweng decoction (BTWD) has proven effective in the treatment of ulcerative colitis. However, the limited understanding of its pharmacokinetics (PK) has impeded its widespread use. Chinese Bama miniature pigs possess anatomical and physiological similarities to the human body, making them a valuable model for investigating PK properties. Consequently, the identification of PK properties in Bama miniature pigs can provide valuable insights for guiding the clinical application of BTWD in humans. To facilitate this research, a rapid and sensitive UPLC-MS/MS method has been developed for the simultaneous quantification of eleven active ingredients of BTWD in plasma. Chromatographic separation was conducted using an Acquity UPLC HSS T3 C18 column and a gradient mobile phase comprising acetonitrile and water (containing 0.1% acetic acid). The methodology was validated in accordance with the FDA Bioanalytical Method Validation Guidance for Industry. The lower limit of quantitation fell within the range of 0.60–2.01 ng/mL. Pharmacokinetic studies indicated that coptisine chloride, berberine, columbamine, phellodendrine, and obacunone exhibited low C max , while fraxetin, esculin, fraxin, and pulchinenoside B 4 were rapidly absorbed and eliminated from the plasma. These findings have implications for the development of effective components in BTWD and the adjustment of clinical dosage regimens. [ABSTRACT FROM AUTHOR]

Brain tumors are the deadliest and most difficult to treat of all forms of cancer. Preoperative classification of brain tumors is conducive to the development of corresponding treatment plan. Take pituitary tumors as an example. Precisely judging the image data of pituitary tumor texture before surgery can provide a basis for the selection of surgical plan and prognosis. However, the existing methods require manual intervention, and the efficiency and accuracy are not high. In this paper, we proposed an automatic brain tumor texture diagnosis method for uneven sequence image data. First, for the small sample of pituitary tumor MRI image data, the T1 and T2 sequence data are uneven or missing; we used the CycleGAN model to perform data conversion between different domains to obtain a completely sampled MRI spatial sequence. Then, we used texture analysis+pseudo-label learning to label pituitary tumor data of some unknown labels. After that, we used the improved U-Net model based on CBAM to optimize feature extraction for pituitary tumor image data. Finally, we used the CRNN model to classify the degree of pituitary tumor texture based on the advantages of sequence data. The entire process only needs to provide labels for the entire sequence data, and the efficiency is greatly improved, with an accuracy rate of 94.23%. [ABSTRACT FROM AUTHOR]

According to the performance degradation problem of feature extraction from higher-order statistics in the context of alpha-stable noise, a new feature extraction method is proposed. Firstly, the nonstationary vibration signal of rolling bearings is decomposed into several product functions by LMD to realize signal stability. Then, the distribution properties of product functions in the time domain are discussed by the comparison of heavy tails and characteristic exponent estimation. Fractional lower-order p-function optimization is obtained by the calculation of the distance ratio based on K-means algorithms. Finally, a fault feature dataset is established by the optimal FLOS and lower-dimensional mapping matrix of covariation to accurately and intuitively describe various bearing faults. Since the alpha-stable noise is effectively suppressed and state described precisely, the presented method has shown better performance than the traditional methods in bearing experiments via fractional lower-order feature extraction. [ABSTRACT FROM AUTHOR]

The initiation and progression of allergic asthma (AA) are associated with complex interactions between inflammation and immune response. Herein, we report the specific mechanisms underlying the molecular action of interferon (IFN)-γ in AA regulation. We speculated that IFN-γ inhibits Th9 differentiation by regulating the secretion of interleukin (IL)-27 from dendritic cells (DCs), thereby suppressing airway inflammation in asthma. We constructed a mouse model of ovalbumin-induced AA and overexpressed IFN-γ to evaluate the effect on the IL-27/Th9 axis via the in vitro effect of IFN-γ on IL-27 secretion by DCs and their influence on Th9 differentiation and asthmatic inflammation. IFN-γ overexpression reduced the proportion of Th9 cells and DCs and altered lung morphology and cytokine production in AA-induced mice, thus suppressing the AA phenotype. In addition, exogenous IFN-γ stimulation promoted the secretion of IL-27 and suppressed Th9 differentiation of CD4+ T cells via signal transducer and activator of transcription 1/3 (STAT1/3) signaling in a time-dependent manner. This study aimed to clarify the regulatory effect and mechanism of the IFN-γ/DCs/IL-27/Th9 axis on AA and provide novel insights for effective targeted treatment of asthma. [ABSTRACT FROM AUTHOR]

Programmed cell death 1 ligand 1 ( PD-L1) is a promising therapeutic target for cancer immunotherapy. However, the correlation between PD-L1 and breast cancer survival remains unclear. Here, we present the first meta-analysis to investigate the prognostic value of PD-L1 in breast cancer. We searched Pubmed, Embase, and Cochrane Central Register of Controlled Trials databases for relevant studies evaluating PD-L1 expression and breast cancer survival. Fixed- and random-effect meta-analyses were conducted based on heterogeneity of included studies. Publication bias was evaluated by funnel plot and Begg's test. Overall, nine relevant studies with 8583 patients were included. PD-L1 overexpression was found in 25.8% of breast cancer patients. PD-L1 (+) associated with several high-risk prognostic indicators, such as ductal cancer (p = 0.037), high tumor grade (p = 0.000), ER negativity (p = 0.000), PR negativity (p = 0.000), HER2 positivity (p = 0.001) and aggressive molecular subtypes ( HER2-rich and Basal-like p = 0.000). PD-L1 overexpression had no significant impact on metastasis-free survival ( HR 0.924, 95% CI = 0.747-1.141, p = 0.462), disease-free survival ( HR 1.122, 95% CI = 0.878-1.434, p = 0.357) and overall specific survival ( HR 0.837, 95% CI = 0.640-1.093, p = 0.191), but significantly correlated with shortened overall survival ( HR 1.573, 95% CI = 1.010-2.451, p = 0.045). PD-L1 overexpression in breast cancer associates with multiple clinicopathological parameters that indicated poor outcome, and may increase the risk for mortality. Further standardization of PD-L1 assessment assay and well-controlled clinical trials are warranted to clarify its prognostic and therapeutic value. [ABSTRACT FROM AUTHOR]