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A good evidence guide of control of infantile epilepsy.
The ethanol extracts of five Origanum species O. majorana L., O. onites L., O. syriacum L., O. vulgare subsp. hirtum (Link) Ietsw., and O. vulgare subsp. viride (Boiss.) Hayek, collected annually (each month), were investigated for their cholinesterase inhibition and antioxidant effects. The phytochemical composition of a total of 60 extracts was assessed by HPLC-DAD-ESI/HRMS, revealing the presence of a total of 73 compounds. Possible correlation between the bioactivity and metabolite profiles during 12 months was monitored. Acetylcholinesterase (AChE) inhibitory activity was found to be the highest between April and November (50.29-75.95%, 200 μg/mL), while the highest inhibition towards butyrylcholinesterase (BChE) was observed for the extracts between April and October (71.68-88.97%). Aromadendrin showed good correlation with anti-AChE, anti-BChE and reducing power activities. Furthermore, molecular docking data with aromadendrin, caffeoylarbutin and eriodictyol indicated that caffeoylarbutin had the lowest binding energy against both enzymes.A smartphone-based colorimetric sensor array system was established for discrimination of rice varieties having different geographical origins. Purposely, aroma profiling of nine rice varieties was performed using solid-phase microextraction gas chromatography-mass spectrometry. Alcohols, aldehydes, alkanes, ketones, heterocyclic compounds, and organic acids represent the abundant compounds. Colorimetric sensor array system produced a characteristic color difference map upon its exposure to volatile compounds of rice. Discrimination of rice varieties was subsequently achieved using principal component analysis, hierarchical clustering analysis, and k-nearest neighbors. Rice varieties from same geographical source were clustered together in the scatter plot of principal component analysis and hierarchical clustering analysis dendrogram. The k-nearest neighbors algorithm delivered optimal results with discrimination rate of 100% for both calibration and prediction sets using sensor array system. The smartphone-based colorimetric sensor array system and gas chromatography technique were able to effectively differentiate rice varieties with the advantage of being simple, rapid, and low-cost.
The prediction of microvascular invasion (MVI) has increasingly been recognized to reflect prognosis involving local invasion and distant metastasis of hepatocellular carcinoma (HCC). The aim of this study was to assess a predictive model using preoperatively accessible clinical parameters and radiographic features developed and validated to predict MVI. This predictive model can distinguish clinical outcomes after liver transplantation (LT) for HCC patients.

In total, 455 HCC patients who underwent LT between January 1, 2015, and December 31, 2019, were retrospectively enrolled in two centers in China as a training cohort (ZFA center; n=244) and a test cohort (SLA center; n=211). Univariate and multivariate backward logistic regression analysis were used to select the significant clinical variables which were incorporated into the predictive nomogram associated with MVI. Receiver operating characteristic (ROC) curves based on clinical parameters were plotted to predict MVI in the training and test sets.

Univariate and multivariate backward logistic regression analysis identified four independent preoperative risk factors for MVI α-fetoprotein (AFP) level (p<0.001), tumor size ((p<0.001), peritumoral star node (p=0.003), and tumor margin (p=0.016). The predictive nomogram using these predictors achieved an area under curve (AUC) of 0.85 and 0.80 in the training and test sets. Furthermore, MVI could discriminate different clinical outcomes within the Milan criteria (MC) and beyond the MC.

The nomogram based on preoperatively clinical variables demonstrated good performance for predicting MVI. MVI may serve as a supplement to the MC.
The nomogram based on preoperatively clinical variables demonstrated good performance for predicting MVI. MVI may serve as a supplement to the MC.MAS related G-protein coupled receptor X2 (MRGPRX2) is a G-protein coupled receptor (GPCR) expressed in human mast cells that has been implicated to play an important role in causing pseudo-allergic reactions as well as exacerbating inflammation during asthma and other allergic diseases. Lactic acid, a byproduct of glucose metabolism, is abundantly present in inflamed tissues and has been shown to regulate functions of several immune cells. find more Because the endogenous ligands for MRGPRX2 (substance P and LL-37) are elevated during pathologic conditions, such as cancer and asthma, and given that lactic acid levels are also enhanced in these patients, we explored the role of lactic acid in regulating mast cells response via MRGPRX2 and MrgprB2, the mouse orthologue of the human receptor. We found that lactic acid suppressed both the early (Ca2+ mobilization and degranulation) and late (chemokine/cytokine release) phases of mast cell activation; this data was confirmed in LAD2, human skin and mouse peritoneal mast cells. In LAD2 cells, the reduction in degranulation and chemokine/cytokine production mediated by lactic acid was dependent on pH. In agreement with our in vitro studies, lactic acid also reduced passive systemic anaphylaxis to compound 48/80 (a known MRGPRX2/MrgprB2 ligand) and skin inflammation in a mouse model of rosacea that is dependent on MrgprB2 expression on skin mast cells. Our data thus suggest that lactic acid may serve to inhibit mast cell-mediated inflammation during asthma and reduce immune response during cancer by affecting mast cell activation through MRGPRX2.Triple-negative breast cancer (TNBC) is an invasive breast cancer with the characteristics of easy to develop distant metastasis. Immune escape is one of the main reasons for TNBC growth and metastasis. Enhancement of T cell-mediated anti-tumor activity may benefit to inhibit tumor metastasis and improve the efficacy of cancer therapy. As a natural bioactive substance, resveratrol shows potential capability to prevent or suppress the development of a variety of cancers through direct or indirect effects, including immunoregulatory effect. However, whether resveratrol might affect lung metastasis of TNBC, and whether the effect of resveratrol might be associated with resveratrol-regulated immune responses in tumor microenvironment is still unknown. In this study, by using an experimental metastatic mouse 4 T1 tumor model, we identified that resveratrol may suppress TNBC lung metastasis by elevating local anti-tumor immunity. Indeed, an increase in the cytotoxic activity of CD8+T cells as well as the levels of type 1 cytokine IFN-γ and IL-2 in the lungs of resveratrol-treated tumor bearing mice were observed. The enhanced CD8+T cell activity and Th1 immune responses by resveratrol administration might be related to the down-regulated PD-1 expression on pulmonary CD8+T cells and CD4+T cells. Resveratrol may also convert macrophages to M1 phenotype in the lungs of tumor bearing mice. However, it seems likely resveratrol has no effect on pulmonary myeloid-derived suppressor cell activation. Our results provide an evidence that resveratrol might be a promising candidate agent for adjuvant therapy in the process of TNBC metastasis.Obstructive Sleep Apnea (OSA) is a common disorder characterized by periodic cessation of breathing during sleep. OSA affects daily life and poses a severe threat to human health. The standard clinical method for identifying and predicting OSA events is the use of Polysomnography signals. In this paper, a novel scheme based on an ensemble of recurrence plots (RPs) and pre-trained convolutional neural networks (RPCNNs) is proposed to improve the prediction rate of OSA. First, RPs were used to represent the dynamic behavior of single electroencephalogram (EEG) and electrocardiogram (ECG) signals for 60 s before and during OSA events. Then, using RPs, three prompt CNNs named ResNet-50 were fine-tuned, and their classification results were fused via the Majority Voting (MV) method to produce a final result concerning prediction. Next, the subject-independent Leave-One-Subject-Out Cross-Validation (LOSO-CV) and subject-dependent 10-fold Cross-Validation (10-fold CV) methods were used to validate the prediction rate from signals derived from the University College Dublin Sleep Apnea Database. Finally, the highest achieved average accuracy for the fusion level was 91.74% and 89.45% at the 10-fold CV and LOSO-CV. Additionally, our results outperformed state-of-the-art findings and could be recommended to predict and detect other biomedical signals. As a result, this predictive system can also be used to adjust the air pressure in sleep apnea patients' Automatic Positive Airway Pressure (APAP) devices.Bayesian latent class models were used to estimate the test accuracy (sensitivity (Se), specificity (Sp), and predictive values (NPV and PPV)) of cow-level somatic cell counts (SCC) data, quarter-level Petrifilm® on-farm milk culture, and quarter-level standard milk bacteriology for the identification of quarters that should possibly be treated with antimicrobials at dry off in dairy cows. Data of 282 cows from 9 dairy herds in Québec, Canada, with bulk tank SCC  less then  250,000 cells/mL were used. Estimated median herd-prevalence of infections that should be treated was 16.2 % (95 % credibility interval (CI) 11.0-22.7). Se and Sp estimates for quarter-milk culture using Petrifilm® were 82.2 % (95 %CI 74.0-89.5) and 62.0 % (95 %CI 58.6-65.6), respectively. Se and Sp for quarter-milk standard bacteriology were 67.4 % (95 %CI 55.8-81.2) and 79.6 % (95 %CI 76.4-83.0), respectively. Se and Sp of different SCC scenarios and thresholds were estimated. For first parity cows, using only the last Dairy Herd Improve%CI 86.7-91.8). Considering the availability of SCC data, the easiness of using just the last DHI test, and the high NPV that could be achieved, producers may consider using just the last DHI test as a potential tool to identify cows that should be treated with antimicrobials at dry off. It may be used alone or in combination with quarter-level on-farm Petrifilm® milk culture on high SCC cows to further reduce the use of antimicrobials by identifying quarters that need to be treated.MicroRNA exhibits different levels of expression in cancer and can affect the transformation, metastasis, and carcinogenesis of the cancer cell. Herein, we developed a novel kind of electrochemical microRNA biosensor based on two-dimensional nanomaterial of antimonene nano-flakes (AMNFs) and carbon quantum dots (CQDs) which were used as substrating to cadmium ion (Cd2+) for specific detection of breast cancer-relevant biomarker-microRNA-21. Compared to graphene, the first principle energetic calculation shows that the AMNFs have completely a stronger force interaction with single strand (ssRNA), due to the antimonene has a more delocalized 5 s/5p orbital. After the addition of complementary microRNA, due to the low adsorption affinity of double-stranded RNA (dsRNA) to antimonene, the hybridized target is easy to desorb from the antimonene interface, and the oxidation peak of metal ions is significantly reduced. Results showed the microRNA-21 concentration can be detected from 100 aM to 1 nM, the limit of detection as low as 21 aM toward microRNA-21, which is 3 times lower than those of the established microRNA biosensors.
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