Prognostic assessment of 18F-boronophenylalanine positron emission tomography (BPA-PET) in salvage boron neutron capture therapy for malignant brain tumors.

Background: Boron neutron capture therapy (BNCT) stands out as a propitious anti-cancer modality. 18F-boronophenylalanine positron emission tomography (BPA-PET) holds the potential to ascertain the concentration of BPA within the tumor, enabling meticulous treatment planning and outcome evaluation. However, no studies have been conducted on comparing the outcomes of those treated with BNCT to those who did not undergo this therapy. This study endeavors to analyze the correlation between BPA-PET and BNCT in the context of malignant brain tumors, and assess the survival outcomes following BNCT. Methods: A cohort study was performed on patients who underwent BPA-PET between February 2017 and April 2022 in our hospital. Patients were stratified into two groups: those subjected to BNCT (Group 1) and those not (Group 2). The tumor to normal tissue (T/N) ratio derived from BPA-PET was set at 2.5. The findings were scrutinized based on clinical follow-up. Student's t-test and Chi-squared test were employed to discern differences between the groups. A cumulative survival curve was constructed employing the Kaplan-Meier method. Differences were considered statistically significant at P<0.05. Results: In total, 116 patients with T/N ratios obtained from BPA-PET were enrolled. BNCT was administered to 58 patients, while mortality was observed in 100 patients. The median overall survival (OS) for the two groups was 8.5 and 6.0 months, respectively. The cumulative OS exhibited no significant discrepancy between the two groups, nor in their T/N ratios. Within Group 1, 44 out of 58 (75.9%) patients exhibited T/N ratios exceeding 2.5. Excluding 3 patients who expired within 3 months, 55 out of 58 patients were evaluated for response after BNCT. The objective response rate (ORR) was 30.9%. Patients achieving ORR displayed substantially higher survival rates compared to those without (median OS 13.5 vs. 8.3 months, P=0.0021), particularly when T/N ratio exceeded 2.5 (median OS 14.8 vs. 9.0 months, P=0.0199). Conclusions: BNCT does not appear indispensable for prolonging the survival of patients afflicted with malignant brain tumors. Nevertheless, it proves advantageous when ORR is attained, a condition closely linked to the values of T/N ratio derived from BPA-PET.

Spatially Resolved Defect Characterization and Fidelity Assessment for Complex and Arbitrary Irregular 3D Printing Based on 3D P-OCT and GCode.

To address the challenges associated with achieving high-fidelity printing of complex 3D bionic models, this paper proposes a method for spatially resolved defect characterization and fidelity assessment. This approach is based on 3D printer-associated optical coherence tomography (3D P-OCT) and GCode information. This method generates a defect characterization map by comparing and analyzing the target model map from GCode information and the reconstructed model map from 3D P-OCT. The defect characterization map enables the detection of defects such as material accumulation, filament breakage and under-extrusion within the print path, as well as stringing outside the print path. The defect characterization map is also used for defect visualization, fidelity assessment and filament breakage repair during secondary printing. Finally, the proposed method is validated on different bionic models, printing paths and materials. The fidelity of the multilayer HAP scaffold with gradient spacing increased from 0.8398 to 0.9048 after the repair of filament breakage defects. At the same time, the over-extrusion defects on the nostril and along the high-curvature contours of the nose model were effectively detected. In addition, the finite element analysis results verified that the 60-degree filling model is superior to the 90-degree filling model in terms of mechanical strength, which is consistent with the defect detection results. The results confirm that the proposed method based on 3D P-OCT and GCode can achieve spatially resolved defect characterization and fidelity assessment in situ, facilitating defect visualization and filament breakage repair. Ultimately, this enables high-fidelity printing, encompassing both shape and function.

Deep learning in the precise assessment of primary Sjögren's Syndrome based on ultrasound images.

OBJECTIVES: This study aimed to investigate the value of a deep learning (DL) model based on greyscale ultrasound (US) images for precise assessment and accurate diagnosis of primary Sjögren's syndrome (pSS). METHODS: This was a multicentre prospective analysis. All pSS patients were diagnosed according to 2016 ACR/EULAR criteria. 72 pSS patients and 72 sex- and age-matched healthy controls recruited between January 2022 and April 2023, together with 41 patients and 41 healthy controls recruited from June 2023 to February 2024 were used for DL model development and validation, respectively. DL model was constructed based on the ResNet 50, input with preprocessed all participants' bilateral submandibular glands (SMGs), parotid glands (PGs), and lacrimal glands (LGs) greyscale US images. Diagnostic performance of the model was compared with two radiologists. The accuracy of prediction and identification performance of DL model were evaluated by calibration curve. RESULTS: 864 and 164 greyscale US images of SMGs, PGs, and LGs were collected for development and validation of the model. The AUCs of DL model in the SMG, PG, and LG were 0.92, 0.93, 0.91 in the model cohort, and were 0.90, 0.88, 0.87 in the validation cohort respectively, outperforming both radiologists. Calibration curves showed the prediction probability of DL model were consistent with the actual probability in both model cohort and validation cohort. CONCLUSION: DL model based on greyscale US images showed diagnostic potential in the precise assessment of pSS patients in the SMG, PG, and LG, outperforming conventional radiologist evaluation.

Battling Salmonella enteritidis infections: integrating proteomics and in vivo assessment of Galla Chinensis tannic acid.

Salmonella infections pose a significant threat to animal and human health. Phytochemicals present a potential alternative treatment. Galla chinensis tannic acid (GCTA), a hydrolyzable polyphenolic compound, inhibits bacterial growth and demonstrates potential as an alternative or supplement to antibiotics to prevent Salmonella infections. However, little is known about the antimicrobial mechanism of GCTA against Salmonella. Here, we revealed 456 differentially expressed proteins upon GCTA treatment, impacting pathways related to DNA replication, repair, genomic stability, cell wall biogenesis, and lipid metabolism using TMT-labeled proteomic analysis. TEM analysis suggested altered bacterial morphology and structure post-treatment. A Salmonella-infected-mouse model indicated that GCTA administration improved inflammatory markers, alleviated intestinal histopathological alterations, and reduced Salmonella enterica serovar Enteritidis (S. Enteritidis) colonization in the liver and spleen of Salmonella-infected mice. The LD50 of GCTA was 4100 mg/kg with an oral single dose, vastly exceeding the therapeutic dose. Thus, GCTA exhibited antibacterial and anti-infective activity against S. Enteritidis. Our results provided insight into the molecular mechanisms of these antibacterial effects, and highlights the potential of GCTA as an alternative to antibiotics.

An Expert-Knowledge-Based Graph Convolutional Network for Skeleton- Based Physical Rehabilitation Exercises Assessment.

Physical therapists play a crucial role in guiding patients through effective and safe rehabilitation processes according to medical guidelines. However, due to the therapist-patient imbalance, it is neither economical nor feasible for therapists to provide guidance to every patient during recovery sessions. Automated assessment of physical rehabilitation can help with this problem, but accurately quantifying patients' training movements and providing meaningful feedback poses a challenge. In this paper, an Expert-knowledge-based Graph Convolutional approach is proposed to automate the assessment of the quality of physical rehabilitation exercises. This approach utilizes experts' knowledge to improve the spatial feature extraction ability of the Graph Convolutional module and a Gated pooling module for feature aggregation. Additionally, a Transformer module is employed to capture long-range temporal dependencies in the movements. The attention scores and weight matrix obtained through this approach can serve as interpretability tools to help therapists understand the assessment model and assist patients in improving their exercises. The effectiveness of the proposed method is verified on the KIMORE dataset, achieving state-of-the-art performance compared to existing models. Experimental results also illustrate the interpretability of the method in both spatial and temporal dimensions.

Inter-rater variability and repeatability in the assessment of the Tanner-Whitehouse classification of hand radiographs for the estimation of bone age.

OBJECTIVE: To determine which bones and which grades had the highest inter-rater variability when employing the Tanner-Whitehouse (T-W) method. MATERIALS AND METHODS: Twenty-four radiologists were recruited and trained in the T-W classification of skeletal development. The consistency and skill of the radiologists in determining bone development status were assessed using 20 pediatric hand radiographs of children aged 1 to 18 years old. Four radiologists had a poor concordance rate and were excluded. The remaining 20 radiologists undertook a repeat reading of the radiographs, and their results were analyzed by comparing them with the mean assessment of two senior experts as the reference standard. Concordance rate, scoring, and Kendall's W were calculated to evaluate accuracy and consistency. RESULTS: Both the radius, ulna, and short finger (RUS) system (Kendall's W = 0.833) and the carpal (C) system (Kendall's W = 0.944) had excellent consistency, with the RUS system outperforming the C system in terms of scores. The repeatability analysis showed that the second rating test, performed after 2 months of further bone age assessment (BAA) practice, was more consistent and accurate than the first. The capitate had the lowest average concordance rate and scoring, as well as the lowest overall concordance rate for its D classification. Moreover, the G classifications of the seven carpal bones all had a concordance rate less than 0.6. The bones with lower Kendall's W were likewise those with lower scores and concordance rates. CONCLUSION: The D grade of the capitate showed the highest variation, and the use of the Tanner-Whitehouse 3rd edition (T-W3) to determine bone age (BA) was frequently inconsistent. A more comprehensive description with a focus on inaccuracy bones or ratings and a modification to the T-W3 approach would significantly advance BAA.

Neural substrates of the interaction between effort-expenditure reward decision-making and outcome anticipation.

OBJECTIVE: Reward anticipation is important for future decision-making, possibly due to re-evaluation of prior decisions. However, the exact relationship between reward anticipation and prior effort-expenditure decision-making, and its neural substrates are unknown. METHOD: Thirty-three healthy participants underwent fMRI scanning while performing the Effort-based Pleasure Experience Task (E-pet). Participants were required to make effort-expenditure decisions and anticipate the reward. RESULTS: We found that stronger anticipatory activation at the posterior cingulate cortex was correlated with slower reaction time while making decisions with a high-probability of reward. Moreover, the substantia nigra was significantly activated in the prior decision-making phase, and involved in reward-anticipation in view of its strengthened functional connectivity with the mammillary body and the putamen in trial conditions with a high probability of reward. CONCLUSIONS: These findings support the role of reward anticipation in re-evaluating decisions based on the brain-behaviour correlation. Moreover, the study revealed the neural interaction between reward anticipation and decision-making.

Development of a rapid tool for screening financial toxicity based on the comprehensive score for financial toxicity.

OBJECTIVE: This study aimed to use item response theory (IRT) to develop and validate a short version of the Chinese COmprehensive Score for financial Toxicity (COST-S-C) in patients with cancer. METHODS: A total of 500 patients with cancer participated in the survey. Confirmatory factor analysis (CFA) was used to assess the factor structure of the COST-S-C. A two-parameter IRT model was used to examine the item fit of the COST-S-C. Item discrimination, item characteristic curves (ICCs), item information curves (IICs), and item fit were estimated. Differential item functioning (DIF) was assessed for participants' gender and age. Reliability, convergent and discriminant validity was examined as well as estimating the optimal cut-off points of the COST-S-C. RESULTS: The CFA results supported the bi-factor structure of the COST-S-C. The IRT analysis findings revealed that several items showed problems with the ICCs, providing little information in terms of IICs as well as poor discrimination. Item 5 showed a negligible DIF problem with age. A valid 3-item COST-S-C scale and its optimal cut-off point was developed. CONCLUSIONS: The COST-S-C is a valid and quick screening tool used to distinguish patients with cancer who report significant financial toxicity in various medical settings.

A Bayesian approach based on discounting factor for consistency assessment in multi-regional clinical trial.

Multi-regional clinical trial (MRCT) has become an increasing trend for its supporting simultaneous global drug development. After MRCT, consistency assessment needs to be conducted to evaluate regional efficacy. The weighted Z-test approach is a common consistency assessment approach in which the weighting parameter W does not have a good practical significance; the discounting factor approach improved from the weighted Z-test approach by converting the estimation of W in original weighted Z-test approach to the estimation of discounting factor D. However, the discounting factor approach is an approach of frequency statistics, in which D was fixed as a certain value; the variation of D was not considered, which may lead to un-reasonable results. In this paper, we proposed a Bayesian approach based on D to evaluate the treatment effect for the target region in MRCT, in which the variation of D was considered. Specifically, we first took D random instead of fixed as a certain value and specified a beta distribution for it. According to the results of simulation, we further adjusted the Bayesian approach. The application of the proposed approach was illustrated by Markov Chain Monte Carlo simulation.

Assessment of the effectiveness of the BOPPPS model combined with case-based learning on nursing residency education for newly recruited nurses in China: a mixed methods study.

BACKGROUND: Expanding new nurse training and education is a priority for nursing educators as well as a critical initiative to stabilize the nursing workforce. Given that there is currently no standardized program for the training of new nurses in China, we investigated the effectiveness of the bridge-in, objective, pre-assessment, participatory learning, post-assessment, and summary model combined with case-based learning ((BOPPPS-CBL) for the standardized training of new nurses. METHODS: The mixed method approach with explanatory sequential (quantitative-qualitative) method was used. A questionnaire was used to compare the impact of the BOPPPS-CBL model and the Traditional Learning Model (TLM) on the core competencies of 185 new nurses for two years of standardized training. Quantitative data were analyzed using SPSS 22.0. Focus group interviews were used with four groups of new nurses and perceptions of BOPPPS-CBL training were recorded. Qualitative data were analyzed thematically. RESULTS: According to the quantitative data, more new nurses agreed that the BOPPPS-CBL model stimulated their learning and improved their core nursing competencies than the TLM. The BOPPPS-CBL group outperformed the TLM group on theoretical knowledge tests. Qualitative data revealed that 87.5% of new nurses agreed on the value of BOPPPS-CBL training, and three themes were extracted: (1) role promotion; (2) formation of new thinking to solve clinical problems; and (3) suggestions for improvement. CONCLUSION: BOPPPS-CBL training had a significant impact on improving new nurses' core competencies and promoting the transition of new nurses to clinical practice nurses in China. The study recommends BOPPPS-CBL training as an effective teaching model for the standardized training and education of new nurses.

Assessment of 3.0 Tesla magnetic resonance imaging in Madelung's deformity: findings and implications.

OBJECTIVE: The aim of the study was to investigate the 3.0 Tesla magnetic resonance imaging (MRI) features of Madelung's deformity. MATERIALS AND METHODS: The wrist MRI scans of 19 patients clinically diagnosed with Madelung's deformity and 20 patients without deformity were consecutively selected from Beijing Jishuitan Hospital between April 2019 and December 2022 for observation, in the case group and control group, respectively. Multiple linear regression was used to analyze the factors affecting tilting angle and width of central disc (CD, also termed as triangular fibrocartilage, the main component of triangular fibrocartilage complex), while the chi-square test was used to compare the occurrences of CD (radial) attachment displacement, VL, and RTL. p < 0.05 indicated statistical significance. RESULTS: Madelung's deformity significantly contributed to the tilting and thickening of the CD. In the case group, the tilting angle and thickness of CD were (51.46 ± 1.33)° and (0.23 ± 0.01) cm, respectively, which was statistically significant (p < 0.05); the radial attachment of the CD significantly shifted away from the distal articular surface level (χ2 = 39.00, p < 0.001), with a mean displacement of (0.97 ± 0.38) cm. Furthermore, the cases demonstrated abnormally developed Vickers ligament (χ2 = 35.19, p < 0.001) and radiotriquetral ligament (χ2 = 25.66, p < 0.001). CONCLUSION: MRI provides a notable advantage in diagnosing Madelung's deformity. Compared with the control group, patients with Madelung's deformity exhibited tilting and thickening of the CD. Additionally, the radial attachment of the CD was significantly shifted proximally with abnormal development of Vickers and radiotriquetral ligaments.

Coronary artery calcium scoring assessment in ultra-low-dose chest computed tomography.

OBJECTIVES: To investigate the effect of non-electrocardiogram (ECG) -triggered ultra-low-dose CT (ULD-CT) with different reconstruction protocols on coronary artery calcium (CAC) scoring assessment, compared with ECG-triggered CAC CT (CAC-CT). METHODS: This prospective study included 115 patients who underwent CAC-CT and ULD-CT scans under the same topogram images. CAC-CT adopted a prospective ECG-triggered sequential acquisition with a tube potential of 120 kV, and the reconstruction protocol was standard Qr36 + slice 3 mm (CACQr-3mm group). ULD-CT adopted a non-ECG-triggered high-pitch acquisition with a tube potential of Sn100 kV, and four groups of images (named ULDQr-3mm, ULDSa-3mm, ULDQr-1.5mm, and ULDSa-1.5mm) were reconstructed using different reconstruction algorithms (standard Qr36, kV-independent Sa36) and slice thicknesses (3 mm, 1.5 mm). The accuracy of CAC detection by ULD-CT was calculated. The agreement of the CAC score between ULD-CT and CAC-CT scans was assessed using intraclass correlation coefficients (ICC) and Bland-Altman plot, and the agreement of risk categorization was assessed using weighted kappa. RESULTS: The sensitivity and specificity of the ULDSa-1.5mm group for detecting positive CAC were 100% and 97.4%, respectively (k = 0.980). The CAC score for the ULDSa-3mm and ULDSa-1.5mm groups demonstrated excellent agreement with the CACQr-3mm group (ICC = 0.992, 0.990, respectively), with a mean difference of -12.3 and - 12.4. The agreement of risk categorization based on absolute and percentile CAC score between the ULDSa-1.5mm and CACQr-3mm groups was excellent (weighted k = 0.954, 0.983, respectively), and risk reclassification rates were low (3.5%, 2.8%, respectively). The effective dose was reduced by approximately 77.2% for the ULD-CT compared to the CAC-CT (0.18 mSv vs. 0.79 mSv, p < 0.001). CONCLUSION: Reconstruction with a 1.5-mm slice thickness and kV-independent iterative algorithmic protocol in ULD-CT yielded excellent agreement in CAC score quantification and risk categorization compared with ECG-triggered CAC-CT.

Association of carbohydrate intake from different sources with all-cause and cardiovascular mortality among chronic kidney disease populations: assessment of 1999-2018 National Health and Nutrition Examination Survey participation.

This study analysed the data from the NHANES (1999-2018) to examine how different sources of carbohydrate intake affected the all-cause and cardiovascular mortality of 11,302 chronic kidney disease (CKD) patients. The data were adjusted for other factors using various methods. The results showed that CKD patients (stages 1-2 and 3-5) who consumed more carbohydrates from whole grains, fruits, vegetables and less carbohydrates from fruit juice or sauces had lower mortality rates. Replacing fat intake with carbohydrates from whole grains (HR = 0.86[0.78-0.95]), fruits (raw) (HR = 0.79[0.70-0.88]) and non-starchy vegetables (HR = 0.82[0.70-0.96]), but not protein intake, was linked to lower all-cause mortality. The fibre content in carbohydrates might partly account for the benefits of selected carbohydrate intake. This study provided practical recommendations for optimising the carbohydrate sources in CKD patients.

Cost-Effectiveness of Osteoporosis Opportunistic Screening Using Computed Tomography in China.

OBJECTIVES: Underutilization and insufficient availability of dual-energy X-ray absorptiometry (DXA) in diagnosing osteoporosis in China could be changed by adopting unindicated quantitative computed tomography. We aimed to assess the cost-effectiveness of quantitative computed tomography (QCT) as a screening tool for osteoporosis in China. METHODS: A Markov microsimulation model was developed to assess the long-term costs and quality-adjusted life-years (QALYs) saved associated with 2 examinations as opportunistic screening for osteoporosis in a general population without prior histories of fracture. The diagnostic performance of both examinations was incorporated into the model. In lifetime modeling, opportunistically screened people may face the risk of experiencing hip, vertebral, and wrist fractures depending on their osteoporosis, age, and sex. Model parameters were informed by published literature. RESULTS: The base-case result showed that QCT was associated with higher costs ($6054 vs $5883) and higher benefits (10.081 vs 10.071 QALYs) in comparison with DXA, making QCT a cost-effective option for opportunistic screening (incremental cost-effectiveness ratio of US $16 430/QALY). Screening with QCT led to fewer fractures over the lifetime simulation: for every 10 000 people screened, 129 fractures (32 hip, 78 vertebral, and 19 wrist fractures) could be avoided because of the early initiation of antiosteoporotic treatment. CONCLUSIONS: Using QCT to screen people for osteoporosis is more cost-effective than standard practice in China, where access to DXA is minimal. This finding could support opportunistic osteoporosis screening using QCT in other countries with similar status.

Assessment of eHealth literacy to reduce financial toxicity and improve shared decision-making in cancer patients: A cross-sectional study.

Objectives: This study aimed to investigate the associations between eHealth literacy, preferences for financial decision-making, and financial toxicity (FT) in a sample of Chinese cancer patients. Methods: Eligible cancer patients were invited to participate in a cross-sectional survey from January to April 2021. Three measures (eHealth literacy scale, control preference scale, and COST) were used to analyze patients' eHealth literacy, decisional preferences, and FT, respectively. Wilcoxon signed-rank test and Kruskal-Wallis H test assessed the differences between population subgroups. Binary logistic and multivariate linear regression models were used to assess the relationships between eHealth literacy, decisional preferences, and FT. Results: A total of 590 cancer patients completed the questionnaire. We found that high FT was associated with poor ECOG performance, severe cancer stage, and longer cancer duration. Patients who preferred to adopt collaborative attitude toward decision-making showed a significantly higher eHealth literacy. However, there was an inverse relationship between eHealth literacy and a patient-driven attitude toward decision-making in female cancer patients. Regression analysis indicated that patients who were highly educated and actively employed might report a higher eHealth literacy. A significant relationship was found between high eHealth literacy and low FT. However, this relationship became insignificant when the background characteristics of cancer patients were taken into account. Conclusions: A relationship between enhanced eHealth literacy, preference for collaborative decision-making, and low risk of FT is identified. Practical implication: Interventions to improve patients' ability to use quality and reliable web-based information on cancer care should be encouraged.

CD38 deficiency promotes skeletal muscle and brown adipose tissue energy expenditure through activating NAD+-Sirt1-PGC1α signaling pathway.

Obesity is a metabolic syndrome characterized by abnormal lipid deposition and energy imbalance. CD38 is a single-chain transmembrane glycoprotein widely expressed in a variety of cell types. The roles of skeletal muscle and brown fat in CD38 deficiency under HFD-induced obesity remain unknown. In this study, we established obesity model with HFD and examined the changes in metabolites with metabonomics. Our results showed that CD38 expression was increased in muscle and brown fat after HFD treatment. Moreover, the results of metabonomics showed that CD38 deficiency significantly altered the metabolites in energy metabolism, cofactor generation, and redox homeostasis. Furthermore, CD38 deficiency reduced the expressions of NADPH oxidase 2 and FASN in mRNA level. We found that the expressions of Sirt1, Sirt3, and PGC1α were upregulated in CD38-deficient muscle tissue. In brown fat, the Sirt1-3, cell death inducing DFFA-like effector A, ELOVL3, and Dio2 expressions were increased in CD38-deficient mice. Our results showed the uncoupling protein 1 expression was upregulated. And NAD+ supplementation increased the expression of Sirt1 and PGC1α after palmitic acid treatment. Taken together, our results demonstrated that the protection of CD38 deficiency on HFD-induced obesity was related to the inhibition of oxidative stress and increasing energy expenditure via activating NAD+/Sirtuins signaling pathways in muscle and brown fat.

How about the evidence assessment tools used in education and management systematic reviews?

Objectives: To systematically analyze the use of evidence assessment tools in systematic reviews of management and education. Study design and setting: We systematically searched selected literature databases and websites to identify systematic reviews on management and education. We extracted general information of the included studies and information about the evidence assessment tool they applied, including whether it was used for methodological quality assessment, reporting quality assessment or evidence grading, as well as the name, reference, publication year, version and original intended use of the tool, the role of the tool in the systematic review, and whether the quality determination criteria were given. Results: A total of 299 systematic reviews were included, of which only 34.8% used evidence assessment tools. A total of 66 different evidence assessment tools were used, of which Risk of Bias (ROB) and its updated version (n = 16, 15.4%) were the most frequent. The specific roles of the evidence assessment tools were reported clearly in 57 reviews, and 27 reviews used two tools. Conclusion: Evidence assessment tools were seldom used in systematic reviews in social sciences. The understanding and reporting of evidence assessment tools among the researchers and users still needs improvement.

In vitro Assessment of the Effects of Silybin on CYP2B6-mediated Metabolism.

Silybin is a flavonol compound with a variety of physiological properties, such as hepatoprotective, anti-fibrogenic, and hypocholesterolemic effects. Although the in vivo and in vitro effects of silybin are frequently reported, studies on herb-drug interactions have yet to be performed. With the discovery of multiple important substrates of CYP2B6 recently, there is a growing body of evidence indicating that CYP2B6 plays a much larger role in human drug metabolism than previously thought.The purpose of this study is to determine how silybin affects the CYP2B6 enzyme's activity, as well as to clarify the molecular mechanisms for inhibition by silybin. The results showed that silybin inhibited CYP2B6 activity in liver microsomes in a non-competitive manner, with IC50 and Ki values of 13.9 µM and 38.4 µM, respectively. Further investigations revealed that silybin could down-regulate the expression of CYP2B6 protein in HepaRG cells. The hydrogen bond conformation of silybin in the active site of the CYP2B6 isoform was revealed by a molecular docking study. Collectively, our findings verify that silybin is an inhibitor of CYP2B6 and explain the molecular mechanism of inhibition. This can lead to a better understanding of the herb-drug interaction between silybin and the substrates of the CYP2B6 enzyme, as well as a more rational clinical use of silybin.

Soil contamination in nearby natural areas mirrors that in urban greenspaces worldwide.

Soil contamination is one of the main threats to ecosystem health and sustainability. Yet little is known about the extent to which soil contaminants differ between urban greenspaces and natural ecosystems. Here we show that urban greenspaces and adjacent natural areas (i.e., natural/semi-natural ecosystems) shared similar levels of multiple soil contaminants (metal(loid)s, pesticides, microplastics, and antibiotic resistance genes) across the globe. We reveal that human influence explained many forms of soil contamination worldwide. Socio-economic factors were integral to explaining the occurrence of soil contaminants worldwide. We further show that increased levels of multiple soil contaminants were linked with changes in microbial traits including genes associated with environmental stress resistance, nutrient cycling, and pathogenesis. Taken together, our work demonstrates that human-driven soil contamination in nearby natural areas mirrors that in urban greenspaces globally, and highlights that soil contaminants have the potential to cause dire consequences for ecosystem sustainability and human wellbeing.

Spatiotemporal differentiation of carbon emission efficiency and influencing factors: From the perspective of 136 countries.

The severity of the global climate issue is rising, primarily as a result of excessive carbon dioxide emissions. Climate change is a global problem. How to reduce carbon dioxide emissions while promoting social and economic development is a problem that all countries need to face. This study examines global carbon emission efficiency in order to make recommendations for comprehensively improving global low-carbon development level. We extend the research scale of carbon emission efficiency from countries, regions, economic belts and sectors to the world, which can show the differences of countries and has theoretical guiding significance for global low-carbon development. This study calculates the carbon emission efficiency for 136 countries from 2000 to 2019 using the Super-EBM model. The discussion that follows examines the temporal and spatial characteristics of carbon emissions efficiency in 136 countries from the perspective of countries, developed and developing countries, and regions. Finally, the Tobit model is used to comprehensively analyze the factors that affect carbon emission efficiency. The results show that: (1) There are great differences in carbon emission efficiency among countries and regions. Only a few countries reach the production frontier, mainly in Europe, which are Switzerland, Luxembourg, Iraq, Norway, Denmark and the United Kingdom. The carbon emission efficiency of most countries is not ideal, being mainly concentrated in Asia and Africa, and has not achieved significant improvement over time. Asia has the lowest carbon emission efficiency. Mongolia, Ukraine, Iran, Angola, Belarus and Uzbekistan are the key governance areas for global energy conservation and carbon emissions reduction. (2) Developed countries have the much higher average carbon emission efficiency than developing countries. Combined with the industrial development stages of developed and developing countries, this is in line with the environmental Kuznets curve (EKC) hypothesis. The average carbon emission efficiency gap between developing and developed countries shows a trend of "first narrowing and then widening", which demonstrates that developing countries' reliance on energy input to boost their economies will improve carbon emission efficiency, but only temporarily. (3) Urbanization level, foreign trade and proportion of renewable energy effectively improve the carbon emission efficiency, while industrial structure and proportion of electricity users have an inhibitory effect on the carbon emission efficiency. Global low-carbon development should be hastened by strengthening international cooperation, optimizing industrial structure, promoting urbanization and foreign trade, and adjusting the energy structure.