Correlation analysis and modeling application from objective indicators to subjective evaluation of scented tea: A case study of rose tea.

Different scented teas provide various choices for consumers from appearance, aroma, flavor and others. Aiming to define advantages and market positions of different scented teas and promote optimization of market structure, characteristics for scented tea favored by consumers and outstanding attributes of different scented teas should be clarified. Rose tea was taken as study object. Sensory evaluation and consumer acceptance were investigated. GC-MS and HPLC fingerprints were established. Physicochemical characteristics were determined. RGB integration analysis was inventively proposed for correlation analysis. The volatile compounds with spicy, green or herbal odor as camphene, ß-phenethyl acetate, eugenol, and physicochemical parameters as antioxidant capacity, reducing sugar content, pH showed positive correlation with popular sensory properties. Six models for consumer preference by objective description were built through GA-SVR (accuracy = 1), and APP was developed. The research mode of scented tea has been successfully established to study multiple subjective characteristics with measurable objective parameters.

Lycium barbarum Ameliorates Oral Mucositis via HIF and TNF Pathways: A Network Pharmacology Approach.

BACKGROUND: Oral mucositis is the most common and troublesome complication for cancer patients receiving radiotherapy or chemotherapy. Recent research has shown that Lycium barbarum, an important economic crop widely grown in China, has epithelial protective effects in several other organs. However, it is unknown whether or not Lycium barbarum can exert a beneficial effect on oral mucositis. Network pharmacology has been suggested to be applied in "multi-component-multi-target" functional food studies. The purpose of this study is to evaluate the effect of Lycium barbarum on oral mucositis through network pharmacology, molecular docking and experimental validation. AIMS: To explore the biological effects and molecular mechanisms of Lycium barbarum in the treatment of oral mucositis through network pharmacology and molecular docking combined with experimental validation. METHODS: Based on network pharmacology methods, we collected the active components and related targets of Lycium barbarum from public databases, as well as the targets related to oral mucositis. We mapped protein- protein interaction (PPI) networks, performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment, and constructed a 'components-disease-targets' network and 'components-pathways-targets' network using Cytoscape to further analyse the intrinsic molecular mechanisms of Lycium barbarum against oral mucositis. The affinity and stability predictions were performed using molecular docking strategies, and experiments were conducted to demonstrate the biological effects and possible mechanisms of Lycium barbarum against oral mucositis. RESULTS: A network was established between 49 components and 61 OM targets. The main active compounds were quercetin, beta-carotene, palmatine, and cyanin. The predicted core targets were IL-6, RELA, TP53, TNF, IL10, CTNNB1, AKT1, CDKN1A, HIF1A and MYC. The enrichment analysis predicted that the therapeutic effect was mainly through the regulation of inflammation, apoptosis, and hypoxia response with the involvement of TNF and HIF pathways. Molecular docking results showed that key components bind well to the core targets. In both chemically and radiation-induced OM models, Lycium barbarum significantly promoted healing and reduced inflammation. The experimental verification showed Lycium barbarum targeted the key genes (IL-6, RELA, TP53, TNF, IL10, CTNNB1, AKT1, CDKN1A, HIF1A, and MYC) through regulating the HIF and TNF signaling pathways, which were validated using the RT-qPCR, immunofluorescence staining and western blotting assays. CONCLUSION: In conclusion, the present study systematically demonstrated the possible therapeutic effects and mechanisms of Lycium barbarum on oral mucositis through network pharmacology analysis and experimental validation. The results showed that Lycium barbarum could promote healing and reduce the inflammatory response through TNF and HIF signaling pathways.

Enhanced coalbed methane well production prediction framework utilizing the CNN-BL-MHA approach.

As the mechanization of the CBM extraction process advances and geological conditions continuously evolve, the production data from CBM wells is deviating increasingly from linearity, thereby presenting a significant challenge in accurately predicting future gas production from these wells. When it comes to predicting the production of CBM, a single deep-learning model can face several drawbacks such as overfitting, gradient explosion, and gradient disappearance. These issues can ultimately result in insufficient prediction accuracy, making it important to carefully consider the limitations of any given model. It's impressive to see how advanced technology can enhance the prediction accuracy of CBM. In this paper, the use of a CNN model to extract features from CBM well data and combine it with Bi-LSTM and a Multi-Head Attention mechanism to construct a production prediction model for CBM wells-the CNN-BL-MHA model-is fascinating. It is even more exciting that predictions of gas production for experimental wells can be conducted using production data from Wells W1 and W2 as the model's database. We compared and analyzed the prediction results obtained from the CNN-BL-MHA model we constructed with those from single models like ARIMA, LSTM, MLP, and GRU. The results show that the CNN-BL-MHA model proposed in the study has shown promising results in improving the accuracy of gas production prediction for CBM wells. It's also impressive that this model demonstrated super stability, which is essential for reliable predictions. Compared to the single deep learning model used in this study, its prediction accuracy can be improved up to 35%, and the prediction results match the actual yield data with lower error.

Experimental research on the influence of acid on the chemical and pore structure evolution characteristics of Wenjiaba tectonic coal.

The chemical and pore structures of coal play a crucial role in determining the content of free gas in coal reservoirs. This study focuses on investigating the impact of acidification transformation on the micro-physical and chemical structure characteristics of coal samples collected from Wenjiaba No. 1 Mine in Guizhou. The research involves a semi-quantitative analysis of the chemical structure parameters and crystal structure of coal samples before and after acidification using Fourier Transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) experiments. Additionally, the evolution characteristics of the pore structure are characterized through high-pressure mercury injection (HP-MIP), low-temperature nitrogen adsorption (LT-N2A), and scanning electron microscopy (SEM). The experimental findings reveal that the acid solution modifies the structural features of coal samples, weakening certain vibrational structures and altering the chemical composition. Specifically, the asymmetric vibration structure of aliphatic CH2, the asymmetric vibration of aliphatic CH3, and the symmetric vibration of CH2 are affected. This leads to a decrease in the contents of -OH and -NH functional groups while increasing aromatic structures. The crystal structure of coal samples primarily dissolves transversely after acidification, affecting intergranular spacing and average height. Acid treatment corrodes mineral particles within coal sample cracks, augmenting porosity, average pore diameter, and the ratio of macro-pores to transitional pores. Moreover, acidification increases fracture width and texture, enhancing the connectivity of the fracture structure in coal samples. These findings provide theoretical insights for optimizing coalbed methane (CBM) extraction and gas control strategies.

Integrated pharmacokinetic-pharmacodynamic modeling and metabolomic research on polyphenol-rich fraction of Thymus quinquecostatus Celak. Alleviating cerebral ischemia-reperfusion injury.

ETHNOPHARMACOLOGICAL RELEVANCE: Thymus quinquecostatus Celak., a member of thymus genus in Lamiaceae family, has been used as a folk medicine for relieving exterior syndrome and alleviating pain in China. The polyphenol-rich fraction (PRF) derived from Thymus quinquecostatus Celak. had been validated that it can protect cerebral ischemia-reperfusion injury (CIRI) by activating Keap1/Nrf2/HO-1 signaling pathway. AIM OF THIS STUDY: To explore effective components and their pharmacokinetic and pharmacodynamic characteristics as well as possible mechanisms of PRF in treating CIRI. MATERIALS AND METHODS: Normal treated group (NTG) and tMCAO model treated group (MTG) rats were administrated PRF intragastrically. The prototype components and metabolites of PRF in plasma and brain were analyzed by the UPLC-Q-Exactive Orbitrap MSn method. Subsequently, the pharmacokinetics properties of indicative components were performed based on HPLC-QQQ-MS/MS. SOD and LDH activities were determined to study the pharmacodynamic (PD) properties of PRF. The PK-PD relationship of PRF was constructed. In addition, the effect of PRF on endogenous metabolites in plasma and brain was investigated using metabolomic method. RESULTS: Salvianic acid A, caffeic acid, rosmarinic acid, scutellarin, and apigenin-7-O-glucuronide were selected as indicative components based on metabolic analysis. The non-compartmental parameters were calculated for indicative components in plasma and brain of NTG and MTG rats. Furthermore, single-component and multi-component PK-PD modeling involved Emax, Imax PD models for effect indexes were fitted as well as ANN models were established, which indicated that these components can work together to regulate SOD and LDH activities in plasma and SOD activity in brain tissue to improve CIRI. Additionally, PRF may ameliorate CIRI by regulating the disorder of endogenous metabolites in lipid metabolism, amino acid metabolism, and purine metabolism pathways in vivo, among which lipid metabolism and purine metabolism are closely related to oxidative stress. CONCLUSION: The PK-PD properties of effect substances and mechanisms of PRF anti-CIRI were further elaborated. The findings provide a convincing foundation for the application of T. quinquecostatus Celak. in the maintenance of human health disorders.

Association between monocyte/high-density lipoprotein cholesterol ratio and carotid plaque in postmenopausal women: A cross-sectional study.

To investigate the relationship between carotid plaque and monocyte to high-density lipoprotein cholesterol ratio (MHR) in postmenopausal women. A cross-sectional study was conducted and 214 postmenopausal women who underwent physical examination at the Health Management Center of Heping Hospital affiliated to Changzhi Medical College between August 2018 and August 2022 were enrolled. The subjects were grouped according to the results of carotid ultrasound. The general information, blood pressure, biochemical markers, and routine blood indicators were compared between the 2 groups. Binary logistic regression was performed to analyze the correlation between MHR and carotid plaque in postmenopausal women, and receiver operating characteristics (ROC) curve was used to analyze the predictive value of MHR for carotid plaque in this population. The carotid plaque group showed a lower high-density lipoprotein cholesterol (HDL-C) (1.21 [1.08-1.425] vs 1.29 [1.15-1.445] mmol/L, Z = -2.115, P = .034) and a higher MHR [0.33 ±â€…0.1 vs 0.26 ±â€…0.1, t = -5.756, P < .001] when compared to the no carotid plaque group. After adjusting for potential confounders such height, weight, and HDL-C, binary logistic regression analysis revealed that MHR continued to be an independent risk factor for the formation of carotid plaque in postmenopausal women (odds ratio [OR] = 1.795, 95% confidence interval [CI] 1.198-2.689, P = .005). ROC curve analysis indicated that MHR had a 95% CI of 0.656 to 0.793 in predicting carotid plaque formation, an optimal cut-point of 0.265, and a sensitivity and specificity of 82.2% and 58.9%, respectively. MHR is a distinct risk factor for carotid plaque formation in postmenopausal women.

Bao Yuan decoction alleviates fatigue by restraining inflammation and oxidative stress via the AMPK/CRY2/PER1 signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Baoyuan Decoction (BYD) was initially recorded in the classic of "Bo Ai Xin Jian" in the Ming dynasty. It is traditionally used for treating weakness and cowardice, and deficiency of vital energy. In researches related to anti-fatigue effects, the reciprocal regulation of AMPK and circadian clocks likely plays an important role in anti-fatigue mechanism, while it has not yet been revealed. Therefore, we elucidated the anti-fatigue mechanism of BYD through AMPK/CRY2/PER1 pathway. AIM OF THE STUDY: To investigate the effect and mechanism of BYD in reducing fatigue, using pharmacodynamics, network pharmacology and transcriptomics through the AMPK/CRY2/PER1 signaling pathway. MATERIALS AND METHODS: Firstly, the chemical constituents of BYD were qualitatively identified by UHPLC-Q-Exactive Orbitrap/MS, establishing a comprehensive strategy with an in-house library, Xcalibur software and Pubchem combined. Secondly, a Na2SO3-induced fatigue model and 2,2'-Azobis (2-methylpropionamidine) dihydrochloride (AAPH)-induced oxidative stress model were developed to evaluate the anti-fatigue and anti-oxidant activities of BYD using AB zebrafish. The anti-inflammatory activity of BYD was evaluated using CuSO4-induced and tail cutting-induced Tg (lyz: dsRed) transgenic zebrafish inflammation models. Then, target screening was performed by Swiss ADME, GeneCards, OMIM and DrugBank databases, the network was constructed using Cytoscape 3.9.0. Transcriptome and network pharmacology technology were used to investigate the related signaling pathways and potential mechanisms after treatment with BYD, which were verified by real-time quantitative PCR (RT-qPCR). RESULTS: In total, 114 compounds from the water extract of BYD were identified as major compounds. Na2SO3-induced fatigue model and AAPH-induced oxidative stress model indicated that BYD has significant anti-fatigue and antioxidant effects. Meanwhile, BYD showed significant anti-inflammatory effects on CuSO4-induced and tail cutting-induced zebrafish inflammation models. The KEGG result of network pharmacology showed that the anti-fatigue function of BYD was mainly effected through AMPK signaling pathway. Besides, transcriptome analysis indicated that the circadian rhythm, AMPK and IL-17 signaling pathways were recommended as the main pathways related to the anti-fatigue effect of BYD. The RT-qPCR results showed that compared with a model control group, the treatment of BYD significantly elevated the expression mRNA of AMPK, CRY2 and PER1. CONCLUSION: Herein, we identified 114 chemical constituents of BYD, performed zebrafish activity validation, while demonstrated that BYD can relieve fatigue by AMPK/CRY2/PER1 signaling pathway through network pharmacology and transcriptome.

Contrastive learning of graphs under label noise.

In the domain of graph-structured data learning, semi-supervised node classification serves as a critical task, relying mainly on the information from unlabeled nodes and a minor fraction of labeled nodes for training. However, real-world graph-structured data often suffer from label noise, which significantly undermines the performance of Graph Neural Networks (GNNs). This problem becomes increasingly severe in situations where labels are scarce. To tackle this issue of sparse and noisy labels, we propose a novel approach Contrastive Robust Graph Neural Network (CR-GNN), Firstly, considering label sparsity and noise, we employ unsupervised contrastive loss and further incorporate homophily in the graph structure, thus introducing neighbor contrastive loss. Moreover, data augmentation is typically used to construct positive and negative samples in contrastive learning, which may result in inconsistent prediction outcomes. Based on this, we propose a dynamic cross-entropy loss, which selects the nodes with consistent predictions as reliable nodes for cross-entropy loss and benefits to mitigate the overfitting to labeling noise. Finally, we propose cross-space consistency to narrow the semantic gap between the contrast and classification spaces. Extensive experiments on multiple publicly available datasets demonstrate that CR-GNN notably outperforms existing methods in resisting label noise.

The association between plain water intake and periodontitis in the population aged over 45: a cross-sectional study based on NHANES 2009-2014.

BACKGROUND: Numerous studies have demonstrated the impact of beverage consumption on overall health and oral health. Specifically, high consumption of sugar-sweetened beverages and coffee has been associated with an increased risk of metabolic disorders and periodontitis. Conversely, high intake of plain water has been linked to various health benefits, including weight management and reduced energy intake. However, no previous studies have explored the potential association between plain water intake and the risk of periodontitis. OBJECTIVES: Our objective was to investigate the relationship between plain water consumption and periodontitis in a middle-aged and elderly population. METHODS: The present cross-sectional study was conducted among participants aged ≥ 45 in the 2009-2014 National Health and Nutrition Examination Surveys. Multivariable regression analysis, subgroup analysis and smooth fitting tests were conducted to explore the independent relationship between plain water intake and periodontitis. RESULTS: A total of 5,882 participants were enrolled,62.02% have periodontitis. Periodontitis patients have lower plain water intake. The multivariable regression tests showed that the risk of periodontitis decreased with increased plain water intake quartiles (Q4 OR = 0.78; 95%CI 0.62-0.96) after fully adjustment. Subgroup analysis and interaction tests showed that gender, age, smoking, diabetes, hypertension or BMI does not significantly interact with the association. However, the relation was significant in males (Q4 OR = 0.64; 95%CI 0.47-0.86) but not in females (Q4 OR = 0.97;95% CI 0.71-1.31). In the smoothed curve fits stratified by gender, the curve for male participants displayed as a U-shape, with an optimal plain water intake at 1200 ml/day. For males drinking plain water less than 1200 ml/day, the risk of periodontitis decreased by 24% with each increase of 500 ml plain water intake (OR = 0.76, 95%CI 0.66-0.87, p < 0.001). CONCLUSIONS: Together, the results showed that plain water intake is negatively associated with periodontitis risk in US middle aged and elderly population. Further studies are needed to investigate the mechanism unites this association. Attention should be given to adequate plain water intake when considering dietary suggestions to the population at high risk of developing periodontitis, especially for men.

Synthesis of CF3-Containing 2-Imidazolines and Imidazoles via a Iodide-Promoted [3 + 2] Cyclization Reaction.

We report herein a general and effective system achieving cyclization of ß-trifluoromethyl enones with amidines in the presence of 1,3-diiodo-5,5-dimethylhydantoin (DIH), which affords a range of trifluoromethylated 2-imidazolines in synthetically useful yields with good diastereoselectivities (up to 95% yield, up to 98:2 dr) and good functional group tolerance. Furthermore, the one-pot synthesis of trifluoromethylated imidazoles via sequential cyclization and oxidation is demonstrated. More significantly, the reaction mechanism was verified by ESI-MS studies of possible intermediates, and a reasonable reaction mechanism was proposed.

The novel role of IFITM1-3 in myogenic differentiation of C2C12 cells.

Interferon-induced transmembrane proteins (IFITMs 1, 2, and 3) play a critical role in preventing pathogen infection in vertebrates. They are also involved in the occurrence and prognosis of cancer. Myogenesis is a complex process regulated by several factors. This study disclosed that Ifitm1-3 were upregulated in the process of myogenic differentiation of C2C12 myoblasts on days 3, 5, and 7. This positively correlated with the expression of differentiation factors MyoD, myogenin, Mrf5, and desmin. Furthermore, knockdown of Ifitm1-3 by their individual siRNAs inhibited myogenesis of C2C12 myoblasts, with relative downregulation of MyoD, myogenin, Mrf5, and desmin. Subsequently, myotube formation and fusion percentage decreased. Co-immunoprecipitation combined with LC-MS/MS analysis uncovered the interaction proteins of IFITM1 and IFITM3 in C2C12 myoblasts. A total of 84 overlapped interaction proteins of IFITM1 and IFITM3 were identified, and one of the clusters was engaged in cytoskeletal and sarcomere proteins, including desmin, myosin, actin, vimentin, nestin, ankycorbin, and nucleolin. Hence, we hypothesize that these interacting proteins may function as scaffolds for IFITM1-3, possibly through the interaction protein desmin to initiate further interaction with other proteins to participate in myogenesis; however, the molecular mechanisms remain unclear. Our study may contribute to the development of novel therapeutics for myopathic diseases.

Syntaxin-6 promotes the progression of hepatocellular carcinoma and alters its sensitivity to chemotherapies by activating the USF2/LC3B axis.

Syntaxin-6 (STX6), a protein of the syntaxin family, is located in the trans-Golgi network and is involved in a variety of intracellular membrane transport events. STX6 is overexpressed in different human malignant tumors. However, little is known about its exact function and molecular mechanism in hepatocellular carcinoma (HCC). In this study, we found that the expression of STX6 was significantly increased in HCC tissues and was associated with poor survival. Gain- and loss-of-function experiments showed that STX6 promotes cell proliferation and metastasis of HCC cells both in vitro and in vivo. Mechanistically, STX6 was negatively regulated by the upstream stimulatory factor 2 (USF2). In addition, STX6 facilitates the association of autophagosomes with lysosomes. Importantly, we demonstrated that STX6 overexpression, despite enhanced resistance to lenvatinib, sensitizes HCC cells to the autophagy activator rapamycin. This study revealed that, under the control of USF2, STX6 accelerates the degradation of microtubule-associated protein 1 light chain 3 beta (LC3) by promoting autophagic flux, ultimately promoting HCC progression. Collectively, we suggest that the USF2-STX6-LC3B axis is a potential therapeutic target in liver cancer.

Discovery of hepatoprotective activity components from Thymus quinquecostatus celak. by molecular networking, biological evaluation and molecular dynamics studies.

Thymus quinquecostatus Celak. is an edible herb that widely cultivated in Asia and possesses hepatoprotective activity, but the underlying non-volatile components of this protective activity are not well studied. In this study, combining molecular networking visualization and bioassay-guided fractionation strategies, a pair of novel skeleton diterpenoid enantiomers, (+)- and (-)-thymutatusone A [(+)- and (-)-1], along with one new and one known biogenetically related compounds (2-3) and 16 other known compounds (4-19), were identified from T. quinquecostatus. Their structures were exhaustively characterized by comprehensive spectroscopic data, X-ray diffraction analysis, and ECD calculations. Compounds (±)-1, (-)-1, and (+)-1, with a rare tricyclo [7.3.1.02,7] tridecane skeleton, exhibited potent hepatoprotective activity in HepG2 cells injured by acetaminophen, with EC50 values of 11.5 ± 2.8, 8.4 ± 1.9, and 12.2 ± 0.3 µM respectively. They were more potent than positive drug bifendate (EC50 15.2 ± 1.3). Further, the underlying mechanism for the hepatoprotective activity of compound (-)-1 related to activating the Nrf 2 signaling pathway. What's more, molecular docking and molecular dynamics simulation analysis showed that compound (-)-1 could dock with the active site of Nrf 2 protein and form a stable system through hydrogen bonding. These results suggest that T. quinquecostatus can be used as a valuable source of hepatoprotective activity compounds.

Direct bilirubin: A predictor of hematoma expansion after intracerebral hemorrhage.

BACKGROUND: Previous evidence demonstrated that several biomarkers involved in the pathological process of coagulation/hemostasis dysfunction, impairment of brain vascular integrity and inflammation are associated with hematoma expansion (HE) after intracerebral hemorrhage (ICH). We aimed to explore whether there were unreported laboratory biomarkers associated with HE that were readily and commonly available in clinical practice. METHODS: We retrospectively analyzed consecutive acute ICH patients from 2012 to 2020 with admission laboratory tests and baseline and follow-up computed tomography (CT) scans. Univariate and multivariate regression analyses were used to evaluate associations between conventional laboratory indicators and HE. The results were verified in a prospective validation cohort. The relationship of candidate biomarker and 3-month outcomes was also investigated and mediation analysis was undertaken to determine causal associations among candidate biomarker, HE and outcome. RESULTS: Of 734 ICH patients, 163 (22.2%) presented HE. Among the included laboratory indicators, higher direct bilirubin (DBil) was associated with HE (adjusted odds ratio [OR] of per 1.0 µmol/L change 1.082; 95% confidence interval [CI] 1.011-1.158). DBil >5.65 µmol/L was a predictor of HE in validation cohort. Higher DBil was also associated with poor 3-month outcomes. The mediation analysis indicated that the association of higher DBil and poor outcomes was partially mediated by HE. CONCLUSIONS: DBil is a predictor of HE and poor 3-month outcomes after ICH. DBil's metabolic process and involvement in the pathological mechanism of HE are likely to contribute to the association between DBil and HE. Interventions targeting DBil to improve post-ICH prognosis may be meaningful and worthy of further exploration.

External validation and comparison of clinical scores for predicting late seizures after intracerebral hemorrhage in Chinese patients.

PURPOSE: Clinical scores have been established to predict the probability of late seizures following intracerebral hemorrhage (ICH) for individual patients, including the CAVE, CAVS and LANE scores. The purpose of this study was to compare these prediction scores in the Chinese population and undertake an independent external validation on them. METHODS: At one tertiary hospital in China, we retrospectively recruited consecutive inpatients who had been diagnosed with ICH. Medical records and tele interviews with a modified standardized questionnaire were used to identify late seizures. All the predictors of the prediction scores were collected from patient charts and databases by a standardized data collection protocol. The external validation of the prediction scores was quantified by the area under the curve (AUC), sensitivity, specificity, Youden index (YI), positive predictive value (PPV), and negative predictive value (NPV). RESULTS: 69 (5.4%) of 1276 patients experienced late seizures after ICH. There was no significant difference in the CAVE, CAVS, and LANE scores, which had AUCs of 0.75 (95% CI = 0.70-0.81), 0.74 (95% CI = 0.68-0.80), and 0.76 (95% CI = 0.70-0.82), respectively. At the optimal cutoff score, the LANE score had a lower sensitivity but a higher specificity than the CAVE and CAVS scores. Among the three prediction scores, the LANE score had a higher PPV than the others (0.145 vs. 0.088, 0.083), while the NPV was similar among the three prediction scores (0.989, 0.989, and 0.972). CONCLUSION: Our study showed that the CAVE, CAVS and LANE scores had similar AUCs for the occurrence of late seizures, but the LANE score had a relatively high PPV at the optimal cutoff score. Due to low evidence for using prophylactic antiseizure medications (ASM) in patients with ICH and poor availability of specialist stroke care in China, the LANE score with a cutoff score of 3 could be an applicable prediction tool in Chinese patients with ICH.

Biotransformation and metabolism of three methyl salicylate glycosides by gut microbiota in vitro.

MSTG-A, MSTG-B and Gualtherin are three natural methyl salicylate glycosides isolated from Dianbaizhu (Gaultheria leucocarpa var. yunnanensis), which is a traditional Chinese folk medicine widely used for the treatment of rheumatoid arthritis. They share the same mother nucleus with aspirin, exhibit similar activity and have fewer side effects. In this study, the incubation of MSTG-A, MSTG-B and gaultherin monomers with human fecal microbiota (HFM), microbiota in 4 intestinal segments (jejunum, ileum, cecal, and colon) and feces of rats in vitro was carried out to comprehensively and meticulously understand their metabolism by gut microbiota (GM) in the body. MSTG-A, MSTG-B and Gualtherin were hydrolyzed by GM to lose glycosyl moieties. The quantity and position of xylosyl moiety significantly affected the rate and extent of the three components being metabolized. The -glc-xyl fragments of these three components could not be hydrolyzed and broken by GM. In addition, the existence of terminal xylosyl moiety prolonged the degradation time. Different results appeared in metabolism of the three monomers by microbiota of different intestinal segments and feces due to the alternation of the species and abundance of microorganisms along the longitudinal axis of the intestinal lumen. Cecal microbiota had strongest degradation ability on these three components. The metabolic details of GM on MSTG-A, MSTG-B and Gualtherin were clarified in this study, providing data support and basis for clinical development and bioavailability improvement.

Relationship between gut microbiota and rheumatoid arthritis: A bibliometric analysis.

Introduction: Rheumatoid arthritis (RA) is a multifactorial autoimmune disease. Recently, growing evidence demonstrates that gut microbiota (GM) plays an important role in RA. But so far, no bibliometric studies pertaining to GM in RA have ever been published. This study attempts to depict the knowledge framework in this field from a holistic and systematic perspective based on the bibliometric analysis. Methods: Literature related to the involvement of GM in RA was searched and picked from the Web of Science Core Collection (WOSCC) database. The annual output, cooperation, hotspots, research status and development trend of this field were analyzed by bibliometric software (VOSviewer and Bibliometricx). Results: 255 original research articles and 204 reviews were included in the analysis. The articles in this field that can be retrieved in WOSCC were first published in 2004 and increased year by year since then. 2013 is a growth explosion point. China and the United States are the countries with the most contributions, and Harvard University is the affiliation with the most output. Frontiers in Immunology (total citations = 603) is the journal with the most publications and the fastest growth rate. eLife is the journal with the most citations (total citations = 1248). Scher, Jose U. and Taneja, Veena are the most productive and cited authors. The research in this field is mainly distributed in the evidence, mechanism and practical application of GM participating in RA through the analysis of keywords and documents. There is sufficient evidence to prove the close relationship between GM and RA, which lays the foundation for this field. This extended two colorful and tender branches of mechanism research and application exploration, which have made some achievements but still have broad exploration space. Recently, the keywords "metabolites", "metabolomics", "acid", "b cells", "balance", "treg cells", "probiotic supplementation" appeared most frequently, which tells us that research on the mechanism of GM participating in RA and exploration of its application are the hotspots in recent years. Discussion: Taken together, these results provide a data-based and objective introduction to the GM participating in RA, giving readers a valuable reference to help guide future research.

Development and validation of a novel radiomics-clinical model for predicting post-stroke epilepsy after first-ever intracerebral haemorrhage.

OBJECTIVES: Post-stroke epilepsy (PSE) is associated with increased morbidity and mortality. This study aimed to develop and validate a novel prediction model combining clinical factors and radiomics features to accurately identify patients at high risk of developing PSE after intracerebral haemorrhage (ICH). METHODS: Researchers performed a retrospective medical chart review to extract derivation and validation cohorts of patients with first-ever ICH that attended two tertiary hospitals in China between 2010 and 2020. Clinical data were extracted from electronic medical records and supplemented by tele-interview. Predictive clinical variables were selected by multivariable logistic regression to build the clinical model. Predictive radiomics features were identified, and a Rad-score was calculated according to the coefficient of the selected feature. Both clinical variables and radiomic features were combined to build the radiomics-clinical model. Performances of the clinical, Rad-score, and combined models were compared. RESULTS: A total of 1571 patients were included in the analysis. Cortical involvement, early seizures within 7 days of ICH, NIHSS score, and ICH volume were included in the clinical model. Rad-score, instead of ICH volume, was included in the combined model. The combined model exhibited better discrimination ability and achieved an overall better benefit against threshold probability than the clinical model in the decision curve analysis (DCA). CONCLUSIONS: The combined radiomics-clinical model was better able to predict ICH-associated PSE compared to the clinical model. This can help clinicians better predict an individual patient's risk of PSE following a first-ever ICH and facilitate earlier PSE diagnosis and treatment. KEY POINTS: • Radiomics has not been used in predicting the risk of developing PSE. • Higher Rad-scores were associated with higher risk of developing PSE. • The combined model showed better performance of PSE prediction ability.

Similarities and differences between Ziqin and Kuqin in anti-inflammatory, analgesic, and antioxidant activities and their core chemical composition based on the zebrafish model and spectrum-effect relationship.

ETHNOPHARMACOLOGICAL RELEVANCE: Scutellaria baicalensis (SB) is a traditional Chinese medicine (TCM). In the clinical application of TCM, SB has been divided into two specifications (Ziqin and Kuqin) for a long time. At present, the Chinese Pharmacopoeia Commission no longer distinguishes between the two. However, the two specifications of medicinal materials and pieces are still in circulation in the market. AIM OF THE STUDY: This work aimed at investigating the similarities and differences between Ziqin and Kuqin in anti-inflammatory, analgesic, and antioxidant activities and their material basis. It will provide a new angle for relevant regulations to formulate the specifications and standards of SB. MATERIALS AND METHODS: Here we investigated the similarities and differences between Ziqin and Kuqin in anti-inflammatory, analgesic, and antioxidant activities related to four zebrafish models and three chemical tests. The chemical fingerprints of SB (Ziqin and Kuqin) were profiled by HPLC. Meanwhile, UHPLC-Q-TOF/MS was used to identify the chemical constituents of Ziqin and Kuqin. The main effect-related compounds of SB, Ziqin, and Kuqin were screened out by spectrum-effect relationship. Finally, six monomeric compounds were validated experimentally using the zebrafish inflammation model induced by CuSO4. RESULTS: Both Ziqin and Kuqin had significant anti-inflammatory, analgesic, and antioxidant activities. Kuqin had better anti-inflammatory and analgesic activities, while Ziqin had better antioxidant activity. HPLC fingerprint and UHPLC-Q-TOF/MS evaluation showed that the chemical composition types and main components of Ziqin and Kuqin were basically the same, while the contents and proportions of chemical components in Ziqin and Kuqin were different. By spectrum-effect relationship, compounds X1, X2 (luteoloside), X3, X4 (baicalin), X6 (wogonoside), X7 (baicalein), X8 (wogonin), and X9 (oroxylin A) were the same active chemical constituents of Ziqin and Kuqin. The core components of anti-inflammatory and analgesia activities in Kuqin were compounds X1, X2, X3, X5, X6, X7, X8, and X9. The antioxidant core active components of Ziqin were compounds X2, X3, X4, X6, X7, and X9. Among them, luteoloside, baicalin, wogonoside, baicalein, wogonin, and oroxylin A were validated successfully with good anti-inflammatory effects. CONCLUSIONS: This study revealed that Ziqin and kuqin have high similarity in chemical composition, but their proportions and active core components are different. This may be one of the main reasons why they have the same activity but different activity trends. These findings will help to improve the understanding of the different clinical applications of Ziqin and Kuqin, and provide a reference for the formulation of quality standards and their further research.

SiamBAN: Target-Aware Tracking With Siamese Box Adaptive Network.

Variation of scales or aspect ratios has been one of the main challenges for tracking. To overcome this challenge, most existing methods adopt either multi-scale search or anchor-based schemes, which use a predefined search space in a handcrafted way and therefore limit their performance in complicated scenes. To address this problem, recent anchor-free based trackers have been proposed without using prior scale or anchor information. However, an inconsistency problem between classification and regression degrades the tracking performance. To address the above issues, we propose a simple yet effective tracker (named Siamese Box Adaptive Network, SiamBAN) to learn a target-aware scale handling schema in a data-driven manner. Our basic idea is to predict the target boxes in a per-pixel fashion through a fully convolutional network, which is anchor-free. Specifically, SiamBAN divides the tracking problem into classification and regression tasks, which directly predict objectiveness and regress bounding boxes, respectively. A no-prior box design is proposed to avoid tuning hyper-parameters related to candidate boxes, which makes SiamBAN more flexible. SiamBAN further uses a target-aware branch to address the inconsistency problem. Experiments on benchmarks including VOT2018, VOT2019, OTB100, UAV123, LaSOT and TrackingNet show that SiamBAN achieves promising performance and runs at 35 FPS.