Inhibition Effect of Okanin Toward Human Cytochrome P450 3A4 and 2D6 with Multi-spectroscopic Studies and Molecular Docking.

Okanin, a major flavonoid of a popular herb tea, Coreopsis tinctoria Nutt., showed strong inhibition on CYP3A4 and CYP2D6. The strong interaction between okanin and CYPs were determined by enzyme kinetics, multispectral technique and molecular docking. The inhibition type of two enzymes, CYP3A4 and CYP2D6, by okanin are mixed and non-competitive inhibition type, respectively. The IC50 values and the binding constant of okanin to CYP3A4 can be deduced that the interaction was stronger than that of CYP2D6. The Conformations of CYP3A4 and CYP2D6 were changed by okanin. The evidence from fluorescence measurement along with molecular docking verified that these two CYPs were bound with okanin by hydrogen bonds and hydrophobic forces. Our investigation suggested that okanin may lead to interactions between herb and drug by inhibiting CYP3A4 and CYP2D6 activities, thus its consumption should be taken with caution.

Radiomics-based discrimination of coronary chronic total occlusion and subtotal occlusion on coronary computed tomography angiography.

OBJECTIVES: Differentiating chronic total occlusion (CTO) from subtotal occlusion (SO) is often difficult to make from coronary computed tomography angiography (CCTA). We developed a CCTA-based radiomics model to differentiate CTO and SO. METHODS: A total of 66 patients with SO underwent CCTA before invasive angiography and were matched to 66 patients with CTO. Comprehensive imaging analysis was conducted for all lesioned vessels, involving the automatic identification of the lumen within the occluded segment and extraction of 1,904 radiomics features. Radiomics models were then constructed to assess the discriminative value of these features in distinguishing CTO from SO. External validation of the model was performed using data from another medical center. RESULTS: Compared to SO patients, CTO patients had more blunt stumps (internal: 53/66 (80.3%) vs. 39/66 (59.1%); external: 36/50 (72.0%) vs. 20/50 (40.0%), both p < 0.01), longer lesion length (internal: median length 15.4 mm[IQR: 10.4-22.3 mm] vs. 8.7 mm[IQR: 4.9-12.6 mm]; external:11.8 mm[IQR: 6.1-23.4 mm] vs. 6.2 mm[IQR: 3.5-9.1 mm]; both p < 0.001). Sixteen unique radiomics features were identified after the least absolute shrinkage and selection operator regression. When added to the combined model including imaging features, radiomics features provided increased value for distinguishing CTO from SO (AUC, internal: 0.772 vs. 0.846; p = 0.023; external: 0.718 vs. 0.781, p = 0.146). CONCLUSIONS: The occluded segment vessels of CTO and SO have different radiomics signatures. The combined application of radiomics features and imaging features based on CCTA extraction can enhance diagnostic confidence.

Interactions studies of CYP2D6 with quercetin and hyperoside by spectral analysis and molecular dynamics simulations.

Some ingredients from herbal medicine can significantly affect the activity of CYP2D6, thus leading to serious interactions between herbs and drugs. Quercetin and hyperoside are active ingredients widely found in vegetables, fruits, and herbal medicines. Quercetin and hyperoside have many biological activities. In this work, the characteristic bindings of CYP2D6 with quercetin/hyperoside are revealed by multi-spectroscopy analysis, molecular docking, and molecular dynamics simulations. The fluorescence of CYP2D6 is statically quenched by quercetin and hyperoside. The binding constant (Ka ) values of CYP2D6-quercetin/hyperoside range from 104 L mol-1 , which indicates that these two flavonoids bind moderately to CYP2D6. Meanwhile, quercetin has a stronger quenching ability to CYP2D6 than that of hyperoside. The secondary structure of CYP2D6 is obviously changed by binding with quercetin/hyperoside. The docking results reveal that the quercetin/hyperoside enters the active site of CYP2D6 near heme and binds to CYP2D6 by hydrogen bonds and van der Waals forces. The molecular dynamics simulation results indicate that the binding of quercetin/hyperoside can stabilize the two complexes, enhance the flexibility of CYP2D6 backbone atoms, and make a more unfolded and looser structure of CYP2D6.

Trend analysis and influencing factors of healthy aging in middle-aged population in China: a longitudinal study based on the China Health and Retirement Longitudinal Study.

OBJECTIVES: This study aimed to assess the trends of healthy aging and investigate its determinants in the middle-aged population. STUDY DESIGN: This was a longitudinal study. METHODS: The sample comprised 3043 participants aged 45-59 years from the China Longitudinal Study of Health and Retirement 2011-2018. We plotted the prevalence across four waves and used ordered logistic models to investigate the determinants of cumulative times of healthy aging. RESULTS: We enrolled 3043 middle-aged people in our study. The prevalence of healthy aging is 28.2% at baseline but subsequently decreased to 19.72% at wave 4. Active socializing consistently ranked the lowest among the five dimensions. Participants with older age (odds ratio [OR] = 0.95, 95% confidence interval [CI] = 0.94-0.97), low monthly income (OR = 0.82, 95% CI: 0.69-0.97) or lived in urban (OR = 0.81, 95% CI: 0.70-0.94) were less likely to have per time increase in healthy aging. Participants with more than primary school degree (OR = 1.79, 95% CI: 1.31-2.46), high life satisfaction (OR = 2.38, 95% CI: 1.86-3.06), and good self-report health (OR = 1.97, 95% CI: 1.66-2.34) were more likely to have healthy aging. CONCLUSION: The number of middle-aged individuals in China who achieved healthy aging is declining and eventually less than one in five, which was far from ideal. Particular attention should be paid to older, women, urban dwellers, individuals with low income, low life satisfaction or poor self-report health. It is urgent to develop public health policies to improve the health and well-being of the middle-aged population.

Multiple interface coupling on natural tourmaline enables high-efficiency removal of antibiotic: Superior property and mechanism.

Reasonably designing highly active, environmentally friendly, and cost-effective catalysts for efficient elimination of pollutants from water is desirable but challenging. Herein, an efficient heterogeneous photo-Fenton catalyst tourmaline (TM)/tungsten oxide (WO3-x) (named TW10) containing tungsten/boron/iron (W/B/Fe) synergistic active centers and 90% of cheap natural tourmaline (TM) mineral rich in Fe and B elements. The TW10 catalyst can quickly activate peroxymonosulfate (PMS) to generate massive active free radicals, which may induce the rapid and efficient degradation of tetracycline (TC). The TW10/PMS/Visible light system can effectively degrade up to 98.7% of tetracycline (TC) in actual waters (i.e. seawater, Yellow River, and Yangtze River water), and the catalytic degradation rates reach 1.65, 5.569, and 2.38 times higher than those of TM, WO3-x, and commercial P25 (Degussa, Germany), respectively. In addition, the catalyst can be recycled and reused multiple times. Electron spin resonance spectroscopy (EPR), X-ray photoelectron spectroscopy (XPS), and liquid chromatograph-mass spectrometer (LC-MS) analyses confirm that the synergistic catalytic effect of W/B/Fe sites on the TW10 catalyst accelerates the electron transfer between Fe(II) and Fe(III), as well as between W(V) and W(VI), and thus promotes the rapid degradation of TC. The catalytic reaction mechanism and degradation pathway of TC were explored. This work provides a feasible route for the design and development of new eco-friendly and efficient catalyst.

Structure and bonding of proximity-enforced main-group dimers stabilized by a rigid naphthyridine diimine ligand.

The development of ligands capable of effectively stabilizing highly reactive main-group species has led to the experimental realization of a variety of systems with fascinating properties. In this work, we computationally investigate the electronic, structural, energetic, and bonding features of proximity-enforced group 13-15 homodimers stabilized by a rigid expanded pincer ligand based on the 1,8-naphthyridine (napy) core. We show that the redox-active naphthyridine diimine (NDI) ligand enables a wide variety of structural motifs and element-element interaction modes, the latter ranging from isolated, element-centered lone pairs (e.g., E = Si, Ge) to cases where through-space π bonds (E = Pb), element-element multiple bonds (E = P, As) and biradical ground states (E = N) are observed. Our results hint at the feasibility of NDI-E2 species as viable synthetic targets, highlighting the versatility and potential applications of napy-based ligands in main-group chemistry.

A Machine Learning-Based Unenhanced Radiomics Approach to Distinguishing Between Benign and Malignant Breast Lesions Using T2-Weighted and Diffusion-Weighted MRI.

BACKGROUND: Breast MRI has been recommended as supplemental screening tool to mammography and breast ultrasound of breast cancer by international guidelines, but its long examination time and use of contrast material remains concerning. PURPOSE: To develop an unenhanced radiomics model with using non-gadolinium based sequences for detecting breast cancer based on T2-weighted (T2W) and diffusion-weighted (DW) MRI. STUDY TYPE: Retrospective analysis followed by retrospective and prospective cohorts study. POPULATION: 1760 patients: Of these, 1293 for model construction (n = 775 for training and 518 for validation). The remaining patients for model testing in internal retrospective (n = 167), internal prospective (n = 188), and external retrospective (n = 112) cohorts. FIELD STRENGTH/SEQUENCE: 3.0T MR scanners from two institution. T2WI, DWI, and first contrast-enhanced T1-weighted sequence. ASSESSMENT: AUCs in distinguishing breast cancer were compared between combined model with gadolinium agent sequence and unenhanced model. Subsequently, the AUCs in testing cohorts of unenhanced model was compared with two radiologists' diagnosis for this research. Finally, patient subgroup analysis in testing cohorts was performed based on clinical subgroups and different types of malignancies. STATISTICAL TESTS: Mann-Whitney U test, Kruskal-Wallis H test, chi-square test, weighted kappa test, and DeLong's test. RESULTS: The unenhanced radiomics model performed best under Gaussian process (GP) classifiers (AUC: training, 0.893; validation, 0.848) compared to support vector machine (SVM) and logistic, showing favorable prediction in testing cohorts (AUCs, 0.818-0.840). The AUCs for the unenhanced radiomics model were not statistically different in five cohorts from those of the combined radiomics model (P, 0.317-0.816), as well as the two radiologists (P, 0.181-0.918). The unenhanced radiomics model was least successful in identifying ductal carcinoma in situ, whereas did not show statistical significance in other subgroups. DATA CONCLUSION: An unenhanced radiomics model based on T2WI and DWI has comparable diagnostic accuracy to the combined model using the gadolinium agent. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

Two nomograms based on radiomics models using triphasic CT for differentiation of adrenal lipid-poor benign lesions and metastases in a cancer population: an exploratory study.

OBJECTIVES: To investigate the effectiveness of CT-based radiomics nomograms in differentiating adrenal lipid-poor benign lesions and metastases in a cancer population. METHODS: This retrospective study enrolled 178 patients with cancer history from three medical centres categorised as those with adrenal lipid-poor benign lesions or metastases. Patients were divided into training, validation, and external testing cohorts. Radiomics features were extracted from triphasic CT images (unenhanced, arterial, and venous) to establish three single-phase models and one triphasic radiomics model using logistic regression. Unenhanced and triphasic nomograms were established by incorporating significant clinico-radiological factors and radscores. The models were evaluated by the receiver operating characteristic curve, Delong's test, calibration curve, and decision curve. RESULTS: Lesion side, diameter, and enhancement ratio resulted as independent factors and were selected into nomograms. The areas under the curves (AUCs) of unenhanced and triphasic radiomics models in validation (0.878, 0.914, p = 0.381) and external testing cohorts (0.900, 0.893, p = 0.882) were similar and higher than arterial and venous models (validation: 0.842, 0.765; testing: 0.814, 0.806). Unenhanced and triphasic nomograms yielded similar AUCs in validation (0.903, 0.906, p = 0.955) and testing cohorts (0.928, 0.946, p = 0.528). The calibration curves showed good agreement and decision curves indicated satisfactory clinical benefits. CONCLUSION: Unenhanced and triphasic CT-based radiomics nomograms resulted as a useful tool to differentiate adrenal lipid-poor benign lesions from metastases in a cancer population. They exhibited similar predictive efficacies, indicating that enhanced examinations could be avoided in special populations. KEY POINTS: • All four radiomics models and two nomograms using triphasic CT images exhibited favourable performances in three cohorts to characterise the cancer population's adrenal benign lesions and metastases. • Unenhanced and triphasic radiomics models had similar predictive performances, outperforming arterial and venous models. • Unenhanced and triphasic nomograms also exhibited similar efficacies and good clinical benefits, indicating that contrast-enhanced examinations could be avoided when identifying adrenal benign lesions and metastases.

Risk stratification for 1- to 2-cm gastric gastrointestinal stromal tumors: visual assessment of CT and EUS high-risk features versus CT radiomics analysis.

OBJECTIVES: To investigate the ability of CT and endoscopic sonography (EUS) in predicting the malignant risk of 1-2-cm gastric gastrointestinal stromal tumors (gGISTs) and to clarify whether radiomics could be applied for risk stratification. METHODS: A total of 151 pathologically confirmed 1-2-cm gGISTs from seven institutions were identified by contrast-enhanced CT scans between January 2010 and March 2021. A detailed description of EUS morphological features was available for 73 gGISTs. The association between EUS or CT high-risk features and pathological malignant potential was evaluated. gGISTs were randomly divided into three groups to build the radiomics model, including 74 in the training cohort, 37 in validation cohort, and 40 in testing cohort. The ROIs covering the whole tumor volume were delineated on the CT images of the portal venous phase. The Pearson test and least absolute shrinkage and selection operator (LASSO) algorithm were used for feature selection, and the ROC curves were used to evaluate the model performance. RESULTS: The presence of EUS- and CT-based morphological high-risk features, including calcification, necrosis, intratumoral heterogeneity, irregular border, or surface ulceration, did not differ between very-low and intermediate risk 1-2-cm gGISTs (p > 0.05). The radiomics model consisting of five radiomics features showed favorable performance in discrimination of malignant 1-2-cm gGISTs, with the AUC of the training, validation, and testing cohort as 0.866, 0.812, and 0.766, respectively. CONCLUSIONS: Instead of CT- and EUS-based morphological high-risk features, the CT radiomics model could potentially be applied for preoperative risk stratification of 1-2-cm gGISTs. KEY POINTS: • The presence of EUS- and CT-based morphological high-risk factors, including calcification, necrosis, intratumoral heterogeneity, irregular border, or surface ulceration, did not correlate with the pathological malignant potential of 1-2-cm gGISTs. • The CT radiomics model could potentially be applied for preoperative risk stratification of 1-2-cm gGISTs.

Comparative Study of Binding Behaviors of Cyanidin, Cyanidin-3-Galactoside, Peonidin with Tyrosinase.

Cyanidin, peonidin and cyanidin-3-galactoside are the common anthocyanins with a variety of biological activities. Tyrosinase is a speed-limiting enzyme associated with melanin production. The inhibition of tyrosinase activity can prevent melanin disease while contributing to whitening. The interaction behaviors of the three anthocyanins against tyrosinase have been discussed in this paper. Cyanidin has strongest inhibitory effect on tyrosinase, and then peonidin, cyanidin-3-galactoside. Furthermore, the inhibition of tyrosinase by the three anthocyanins is mixed modes. The three anthocyanins can induce the static fluorescence quenching of tyrosinase. Cyanidin exhibits strongest binding affinity on tyrosinase, and then peonidin, cyanidin-3-galactoside based on Ka values obtain by fluorescence analysis. The binding of all anthocyanin to tyrosinase induce its conformation changes. According to molecular docking and fluorescence studies, they bind to tyrosinase by hydrogen bond and van der Waals force. In addition, the optimal modes of the three anthocyanins with tyrosinase are predicated by molecular docking. This work emphasizes that cyanidin, peonidin and cyanidin-3-galactoside may be potential drugs for the treatment of diseases caused by melanin.

Postoperative Relapse Prediction in Patients With Ewing Sarcoma Using Computed Tomography-Based Radiomics Models Covering Tumor Per Se and Peritumoral Signatures.

OBJECTIVE: We aimed to develop and validate a computed tomography (CT)-based radiomics model for early relapse prediction in patients with Ewing sarcoma (ES). METHODS: We recruited 104 patients in this study. Tumor areas and areas with a tumor expansion of 3 mm were used as regions of interest for radiomics analysis. Six different models were constructed: Pre-CT, CT enhancement (CTE), Pre-CT +3 mm , CTE +3 mm , Pre-CT and CTE combined (ComB), and Pre-CT +3 mm and CTE +3 mm combined (ComB +3 mm ). All 3 classifiers used a grid search with 5-fold cross-validation to identify their optimal parameters, followed by repeat 5-fold cross-validation to evaluate the model performance based on these parameters. The average performance of the 5-fold cross-validation and the best one-fold performance of each model were evaluated. The AUC (area under the receiver operating characteristic curve) and accuracy were calculated to evaluate the models. RESULTS: The 6 radiomics models performed well in predicting relapse in patients with ES using the 3 classifiers; the ComB and ComB +3 mm models performed better than the other models (AUC -best : 0.820-0.922/0.823-0.833 and 0.799-0.873/0.759-0.880 in the training and validation cohorts, respectively). Although the Pre-CT +3 mm , CTE +3 mm, and ComB +3 mm models covering tumor per se and peritumoral CT features preoperatively forecasted ES relapse, the model was not significantly improved. CONCLUSIONS: The radiomics model performed well for early recurrence prediction in patients with ES, and the ComB and ComB +3 mm models may be superior to the other models.

Radiomics analysis based on CT for the prediction of pulmonary metastases in ewing sarcoma.

OBJECTIVES: This study aimed to develop and validate radiomics models on the basis of computed tomography (CT) and clinical features for the prediction of pulmonary metastases (MT) in patients with Ewing sarcoma (ES) within 2 years after diagnosis. MATERIALS AND METHODS: A total of 143 patients with a histopathological diagnosis of ES were enrolled in this study (114 in the training cohort and 29 in the validation cohort). The regions of interest (ROIs) were handcrafted along the boundary of each tumor on the CT and CT-enhanced (CTE) images, and radiomic features were extracted. Six different models were built, including three radiomics models (CT, CTE and ComB models) and three clinical-radiomics models (CT_clinical, CTE_clinical and ComB_clinical models). The area under the receiver operating characteristic curve (AUC), and accuracy were calculated to evaluate the different models, and DeLong test was used to compare the AUCs of the models. RESULTS: Among the clinical risk factors, the therapeutic method had significant differences between the MT and non-MT groups (P＜0.01). The six models performed well in predicting pulmonary metastases in patients with ES, and the ComB model (AUC: 0.866/0.852 in training/validation cohort) achieved the highest AUC among the six models. However, no statistically significant difference was observed between the AUC of the models. CONCLUSIONS: In patients with ES, clinical-radiomics model created using radiomics signature and clinical features provided favorable ability and accuracy for pulmonary metastases prediction.

Clinical-radiomics models based on plain X-rays for prediction of lung metastasis in patients with osteosarcoma.

OBJECTIVES: Osteosarcoma (OS) is the most common primary malignant bone tumor in adolescents. Lung metastasis (LM) occurs in more than half of patients at different stages of the disease course, which is one of the important factors affecting the long-term survival of OS. To develop and validate machine learning radiomics model based on radiographic and clinical features that could predict LM in OS within 3 years. METHODS: 486 patients (LM = 200, non-LM = 286) with histologically proven OS were retrospectively analyzed and divided into a training set (n = 389) and a validation set (n = 97). Radiographic features and risk factors (sex, age, tumor location, etc.) associated with LM of patients were evaluated. We built eight clinical-radiomics models (k-nearest neighbor [KNN], logistic regression [LR], support vector machine [SVM], random forest [RF], Decision Tree [DT], Gradient Boosting Decision Tree [GBDT], AdaBoost, and extreme gradient boosting [XGBoost]) and compared their performance. The area under the receiver operating characteristic curve (AUC) and accuracy (ACC) were used to evaluate different models. RESULTS: The radscore, ALP, and tumor size had significant differences between the LM and non-LM groups (tradscore = -5.829, χ2ALP = 97.137, tsize = -3.437, P < 0.01). Multivariable LR analyses showed that ALP was an important indicator for predicting LM of OS (odds ratio [OR] = 7.272, P < 0.001). Among the eight models, the SVM-based clinical-radiomics model had the best performance in the validation set (AUC = 0.807, ACC = 0.784). CONCLUSION: The clinical-radiomics model had good performance in predicting LM in OS, which would be helpful in clinical decision-making.

A radiomics based approach using adrenal gland and periadrenal fat CT images to allocate COVID-19 health care resources fairly.

BACKGROUND: The value of radiomics features from the adrenal gland and periadrenal fat CT images for predicting disease progression in patients with COVID-19 has not been studied extensively. We assess the value of radiomics features from the adrenal gland and periadrenal fat CT images in predicting COVID-19 disease exacerbation. METHODS: A total of 1,245 patients (685 moderate and 560 severe patients) were enrolled in a retrospective study. We proposed a 3D V-net to segment adrenal glands in onset CT images automatically, and periadrenal fat was obtained using inflation operation around the adrenal gland. Next, we built a clinical model (CM), three radiomics models (adrenal gland model [AM], periadrenal fat model [PM], and fusion of adrenal gland and periadrenal fat model [FM]), and radiomics nomogram (RN) after radiomics features extracted. RESULTS: The auto-segmentation framework yielded a dice value 0.79 in the training set. CM, AM, PM, FM, and RN obtained AUCs of 0.717, 0.716, 0.736, 0.760, and 0.833 in the validation set. FM and RN had better predictive efficacy than CM (P < 0.0001) in the training set. RN showed that there was no significant difference in the validation set (mean absolute error [MAE] = 0.04) and test set (MAE = 0.075) between predictive and actual results. Decision curve analysis showed that if the threshold probability was between 0.4 and 0.8 in the validation set or between 0.3 and 0.7 in the test set, it could gain more net benefits using RN than FM and CM. CONCLUSIONS: Radiomics features extracted from the adrenal gland and periadrenal fat CT images are related to disease exacerbation in patients with COVID-19.

Comparison of MRI and CT-based radiomics for preoperative prediction of lymph node metastasis in pancreatic ductal adenocarcinoma.

BACKGROUND: The preoperative prediction of lymph node metastasis (LNM) in pancreatic ductal adenocarcinoma (PDAC) is essential in prognosis and treatment strategy formulation. PURPOSE: To compare the performance of computed tomography (CT) and magnetic resonance imaging (MRI) radiomics models for the preoperative prediction of LNM in PDAC. MATERIAL AND METHODS: In total, 160 consecutive patients with PDAC were retrospectively included, who were divided into the training and validation sets (ratio of 8:2). Two radiologists evaluated LNM basing on morphological abnormalities. Radiomics features were extracted from T2-weighted imaging, T1-weighted imaging, and multiphase contrast enhanced MRI and multiphase CT, respectively. Overall, 1184 radiomics features were extracted from each volume of interest drawn. Only features with an intraclass correlation coefficient ≥0.75 were included. Three sequential feature selection steps-variance threshold, variance thresholding and least absolute shrinkage selection operator-were repeated 20 times with fivefold cross-validation in the training set. Two radiomics models based on multiphase CT and multiparametric MRI were built with the five most frequent features. Model performance was evaluated using the area under the curve (AUC) values. RESULTS: Multiparametric MRI radiomics model achieved improved AUCs (0.791 and 0.786 in the training and validation sets, respectively) than that of the CT radiomics model (0.672 and 0.655 in the training and validation sets, respectively) and of the radiologists' assessment (0.600-0.613 and 0.560-0.587 in the training and validation sets, respectively). CONCLUSION: Multiparametric MRI radiomics model may serve as a potential tool for preoperatively evaluating LNM in PDAC and had superior predictive performance to multiphase CT-based model and radiologists' assessment.

Interaction of narcissoside with α-amylase from Bacillus subtilis and Porcine pancreatic by multi-spectral analysis and molecular dynamics simulation.

In this work, interaction mechanism of narcissoside with two α-amylase from Bacillus subtilis (BSA) and Porcine pancreatic (PPA) are comparatively studied by multi-spectral analysis, molecular docking and molecular dynamics simulation. The results prove that narcissoside can statically quench fluorescence of BSA/PPA. Two complexes are mainly formed by hydrogen bond and van der Waals force. With the increase of temperature, the two complexes formed by narcissoside and two enzymes become unstable. At the same experimental temperature, the binding force of narcissoside to PPA is higher than that of BSA. The binding of narcissoside to PPA/BSA increases the hydrophobicity of microenvironment. Moreover, the secondary structure of PPA/BSA is mainly changed by decreasing the α-helix. The optimal binding modes of narcissoside with BSA/PPA are predicted by molecular docking, and the stability of the two complexes is evaluated by molecular dynamics simulations.

Notoginsenoside R1 inhibits hepatitis B virus replication by modulating SIRT1 activity.

The hepatitis B virus (HBV) infection remains highly prevalent globally. The present study aimed to explore the possible therapeutic effect of notoginsenoside R1, which has attracted considerable attention due to its diverse pharmacological effects, on HBV infection. The HBV-containing hepatocellular carcinoma cell lines, HepG2 and MHCC97H, were used in this study. We first treated the two cell lines with different concentrations of notoginsenoside R1 and subsequently measured the relative levels of HBV DNA, HBV surface antigen, HBV core antigen, and sirtuin 1 (SIRT1) using reverse transcription-quantitative polymerase chain reaction and western blotting. Finally, an HBV hemodynamic replication model was created to test the effect of notoginsenoside R1 on HBV replication. Notoginsenoside R1 inhibited the replication of HBV. This inhibitory effect was mediated through the downregulation of SIRT1 activity. Additionally, the inhibition of SIRT1 activity by silencing its expression or treatment with the SIRT1 inhibitor, selisistat, suppressed HBV replication. Furthermore, our animal experiments demonstrated that notoginsenoside R1 was effective at suppressing HBV replication in vivo. Thus, notoginsenoside R1 suppresses HBV replication by downregulating SIRT1 activity in vitro and in vivo. Keywords: notoginsenoside R1; hepatitis B virus; SIRT1.

Simulated microgravity shapes the endophytic bacterial community by affecting wheat root metabolism.

To improve nutrient utilization and pathogenic resistance of plants in space, it is crucial to understand the effects of microgravity on the plant root microbiome. However, the finer details of whether and how microgravity affects the root microbiome remain unclear. Here, we found that simulated microgravity elicits no significant changes in fungal community composition and diversity, whether rhizosphere or endophytic. However, simulated microgravity caused a significant change in the composition and diversity of endophytic bacteria of wheat seedlings, but not in rhizosphere bacteria. The alteration of endophytic bacterial communities demonstrates that wheat seedlings adopt strategies to recruit additional endophytic Enterobacteriaceae and increase the stability of the endophytic bacterial network to respond to the challenge of simulated microgravity. Furthermore, our results also suggest that the corresponding changes in endophytic bacteria under simulated microgravity are closely related to a significant decrease in metabolites of the host's carbon metabolism, flavonoid biosynthesis, benzoxazinoid biosynthesis, and tryptophan metabolism pathways. Our findings reveal details important to our understanding of the impact of gravity on the microbial community of plant seedlings and the theoretical basis for manipulation of microorganisms to ensure efficient plant production in space.

Design, synthesis, and preclinical evaluation of a novel bifunctional macrocyclic chelator for theranostics of cancers.

PURPOSE: This study was to design and synthesize a novel bifunctional chelator, named Dar, primarily validated by conjugating to tumor targeting motifs, labeled with radiometals, and performed preclinical evaluation of tumor imaging and cancer therapy in murine tumor models. METHOD: The designed Dar was synthesized and characterized by X-ray crystallography, 1H/13C NMR, and mass spectrometry. Dar-PSMA-617 was conjugated and radiolabeled with 68Ga, 177Lu, and 89Zr. The in vivo behavior of 68 Ga/89Zr-labeled Dar-PSMA-617 were evaluated using micro-PET imaging and biodistribution from image quantitation and tissue radioactivity counting, with 68Ga/89Zr-labeled NOTA/DOTA/DFO-PSMA-617 analogs as controls, respectively. The [177Lu]-Dar-PSMA-617, with [177Lu]-DOTA-PSMA-617 as control, was evaluated in competitive cell uptake, tumor cell internalization, and efflux studies. The treatment efficacy of [177Lu]Lu-Dar-PSMA-617, with [177Lu]Lu-DOTA-PSMA-617 as control, was evaluated in PSMA-positive LNCaP tumor-bearing mice. In addition, the ability of Dar for radiolabeling nanobody was tested by conjugating Dar to KN035 nanobody. The resultant [89Zr]Zr-Dar-KN035 nanobody, with [89Zr]Zr-DFO-KN035 as control, was evaluated by micro-PET imaging and biodistribution in a mouse model bearing MC38&MC38-hPD-L1 colon cancer. RESULTS: 68Ga, 89Zr, and 177Lu-radiolabeled Dar-PSMA-617 complexes were able to be produced under mild condition with high radiochemical yield and purity successfully. [177Lu]Lu-Dar-PSMA-617 had higher cellular uptake yet similar internalization and efflux properties in LNCaP cells, as compared to [177Lu]Lu-DOTA-PSMA-617. Micro-PET images demonstrated significantly higher tumor uptake of [68Ga]Ga-Dar-PSMA-617, than that of the analog [68Ga]Ga-DOTA-PSMA-617. The tumor uptake values of [68Ga]Ga-Dar-PSMA-617 at multiple time points are comparable to that of [68Ga]Ga-NOTA-PSMA-617, although a higher and persistently prolonged kidney retention was resulted in during the study period. The Dar chelator can also successfully mediate the radiolabeling with 89Zr, while the resultant [89Zr]Zr-Dar-PSMA-617 demonstrated a similar biodistribution with [89Zr]Zr-DFO-PSMA-617 measured at 96 h p.i. The treatment with [177Lu]Lu-Dar-PSMA-617 significantly inhibited the tumor growth, showing much better efficacy than that of [177Lu]Lu-DOTA-PSMA-617 at the same injected radioactivity and mass dose. Dar was covalently linked to KN035 nanobody and enabled radiolabeling with 89Zr in high yield and radiochemical purity at room temperature. The resultant [89Zr]Zr-Dar-KN035, with [89Zr]Zr-DFO-KN035 as control, demonstrated superior tumor uptake and detection capability in PET imaging studies. CONCLUSION: The Dar, as a novel bifunctional chelator for medicating the labeling of radiometals onto tumor targeting carriers, was successfully synthesized and chemically characterized. Test radiolabeling, on PSMA-617 and a nanobody as tool targeting molecule carriers, demonstrated the Dar has potential as a universal bifunctional chelator for radiolabeling various radiometals (at least 68Ga, 177Lu, and 89Zr tested) commonly used for clinical imaging and therapy. Using a novel Dar chelator results in altered in vivo behavior of the carriers even though labeled with the same nuclide. This capability makes Dar an alternative to the existing choices for radiolabeling new carrier molecules with various radiometals, especially the radiometals with large radius.

The radiomics-based tumor heterogeneity adds incremental value to the existing prognostic models for predicting outcome in localized clear cell renal cell carcinoma: a multicenter study.

PURPOSE: Tumor heterogeneity, which is associated with poor outcomes, has not been exhibited in the University of California, Los Angeles, Integrated Staging System (UISS), and the Stage, Size, Grade and Necrosis (SSIGN) scores. Radiomics allows an in-depth characterization of heterogeneity across the tumor, but its incremental value to the existing prognostic models for clear cell renal cell carcinoma (ccRCC) outcome is unknown. The purpose of this study was to evaluate the association between the radiomics-based tumor heterogeneity and postoperative risk of recurrence in localized ccRCC, and to assess its incremental value to UISS and SSIGN. METHODS: A multicenter 866 ccRCC patients derived from 12 Chinese hospitals were studied. The endpoint was recurrence-free survival (RFS). A CT-based radiomics signature (RS) was developed and assessed in the whole cohort and in the subgroups stratified by UISS and SSIGN. Two combined nomograms, the R-UISS (combining RS and UISS) and R-SSIGN (combining RS and SSIGN), were developed. The incremental value of RS to UISS and SSIGN in RFS prediction was evaluated. R statistical software was used for statistics. RESULTS: Patients with low radiomics scores were 4.44 times more likely to experience recurrence than those with high radiomics scores (P<0.001). Stratified analysis suggested the association is significant among low- and intermediate-risk patients identified by UISS and SSIGN. The R-UISS and R-SSIGN showed better predictive capability than UISS and SSIGN did with higher C-indices (R-UISS vs. UISS, 0.74 vs. 0.64; R-SSIGN vs. SSIGN, 0.78 vs. 0.76) and higher clinical net benefit. CONCLUSIONS: The radiomics-based tumor heterogeneity can predict outcome and add incremental value to the existing prognostic models in localized ccRCC patients. Incorporating radiomics-based tumor heterogeneity in ccRCC prognostic models may provide the opportunity to better surveillance and adjuvant clinical trial design.