Analysis of Net Primary Productivity Variation and Quantitative Assessment of Driving Forces-A Case Study of the Yangtze River Basin.

Net primary productivity (NPP) can indirectly reflect vegetation's capacity for CO2 fixation, but its spatiotemporal dynamics are subject to alterations to some extent due to the influences of climate change and human activities. In this study, NPP is used as an indicator to investigate vegetarian carbon ability changes in the vital ecosystems of the Yangtze River Basin (YRB) in China. We also explored the NPP responses to climate change and human activities. We conducted a comprehensive analysis of the temporal dynamics and spatial variations in NPP within the YRB ecosystems from 2003 to 2020. Furthermore, we employed residual analysis to quantitatively assess the contributions of climate factors and human activities to NPP changes. The research findings are as follows: (1) Over the 18-year period, the average NPP within the basin amounted to 543.95 gC/m2, displaying a noticeable fluctuating upward trend with a growth rate of approximately 3.1 gC/m2; (2) The areas exhibiting an increasing trend in NPP account for 82.55% of the total study area. Regions with relatively high stability in the basin covered 62.36% of the total area, while areas with low stability accounted for 2.22%, mainly situated in the Hengduan Mountains of the western Sichuan Plateau; (3) NPP improvement was jointly driven by human activities and climate change, with human activities contributing more significantly to NPP growth. Specifically, the contributions were 65.39% in total, with human activities contributing 59.28% and climate change contributing 40.01%. This study provides an objective assessment of the contributions of human activities and climate change to vegetation productivity, offering crucial insights for future ecosystem development and environmental planning.

Serum proteome and metabolome uncover novel biomarkers for the assessment of disease activity and diagnosing of systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an autoimmune disease affecting thousands of people. There are still no effective biomarkers for SLE diagnosis and disease activity assessment. We performed proteomics and metabolomics analyses of serum from 121 SLE patients and 106 healthy individuals, and identified 90 proteins and 76 metabolites significantly changed. Several apolipoproteins and the metabolite arachidonic acid were significantly associated with disease activity. Apolipoprotein A-IV (APOA4), LysoPC(16:0), punicic acid and stearidonic acid were correlated with renal function. Random forest model using the significantly changed molecules identified 3 proteins including ATRN, THBS1 and SERPINC1, and 5 metabolites including cholesterol, palmitoleoylethanolamide, octadecanamide, palmitamide and linoleoylethanolamide, as potential biomarkers for SLE diagnosis. Those biomarkers were further validated in an independent cohort with high accuracy (AUC = 0.862 and 0.898 for protein and metabolite biomarkers respectively). This unbiased screening has led to the discovery of novel molecules for SLE disease activity assessment and SLE classification.

Research on Risk Assessment and Prediction of RMB Internationalization Based on the PCA-SA-BPNN Model.

This paper combines principal component analysis, a BP neural network, and a simulated annealing algorithm, to construct a PCA-SA-BPNN risk forecast model to evaluate and predict the RMB internationalization risk status of China. First, we analyze the risk of RMB internationalization and its transmission mechanism from the perspective of the economic characteristics of neighboring countries and trading partner countries. Second, we use the FASP index system construction method for reference to construct a forecast index system for macro- and microrisks brought about by RMB internationalization. Then, the weight of each index is determined through index common degree analysis and principal component analysis, and the risk of RMB internationalization is divided. On this basis, the risks of RMB internationalization in China from 2000 to 2019 are divided into four categories. Based on the BP neural network algorithm optimized by the simulated degradation algorithm, the PCA-SA-BPNN model of RMB internationalization risk forecast is constructed. Finally, the validity of the model is verified by experimental verification, and the risk status of RMB internationalization in 2020 is simulated and predicted. The research results show that the risk status of RMB internationalization in 2020 is basically safe, and the risks of RMB internationalization mainly come from macroeconomic growth risks and systemic risks of the financial system.

Risk assessment and molecular mechanism study of drug-drug interactions between rivaroxaban and tyrosine kinase inhibitors mediated by CYP2J2/3A4 and BCRP/P-gp.

Cancer patients generally has a high risk of thrombotic diseases. However, anticoagulant therapy always aggravates bleeding risks. Rivaroxaban is one of the most widely used direct oral anticoagulants, which is used as anticoagulant treatment or prophylaxis in clinical practice. The present study aimed to systemically estimate the combination safety of rivaroxaban with tyrosine kinase inhibitors (TKIs) based on human cytochrome P450 (CYPs) and efflux transporters and to explore the drug-drug interaction (DDI) mechanisms in vivo and in vitro. In vivo pharmacokinetic experiments and in vitro enzyme incubation assays and bidirectional transport studies were conducted. Imatinib significantly increased the rivaroxaban Cmax value by 90.43% (p < 0.05) and the area under the curve value by 119.96% (p < 0.01) by inhibiting CYP2J2- and CYP3A4-mediated metabolism and breast cancer resistance protein (BCRP)- and P-glycoprotein (P-gp)-mediated efflux transportation in the absorption phase. In contrast, the combination of sunitinib with rivaroxaban reduced the exposure in vivo by 62.32% (p < 0.05) and the Cmax value by 72.56% (p < 0.05). In addition, gefitinib potently inhibited CYP2J2- and CYP3A4-mediated rivaroxaban metabolism with Ki values of 2.99 µΜ and 4.91 µΜ, respectively; however, it almost did not affect the pharmacokinetics of rivaroxaban in vivo. Taken together, clinically significant DDIs were observed in the combinations of rivaroxaban with imatinib and sunitinib. Imatinib increased the bleeding risks of rivaroxaban, while sunitinib had a risk of reducing therapy efficiency. Therefore, more attention should be paid to aviod harmful DDIs in the combinations of rivaroxaban with TKIs.

Tumor Necrosis Factor-Related Apoptosis-Inducing Ligand (TRAIL): A Novel Biomarker for Prognostic Assessment and Risk Stratification of Acute Pulmonary Embolism.

BACKGROUND: Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) is associated with poor prognosis in cardiovascular diseases. However, the predictive value of TRAIL for the short-term outcome and risk stratification of acute pulmonary embolism (PE) remains unknown. METHODS: This study prospectively included 151 normotensive patients with acute PE. The study outcome was a composite of 30-day adverse events, defined as PE-related death, shock, mechanical ventilation, cardiopulmonary resuscitation, and major bleeding. RESULTS: Overall, nine of 151 (6.0%) patients experienced 30-day adverse composite events. Multivariable logistic regression showed that TRAIL was an independent predictor of study outcome (OR 0.19 per SD; 95% CI 0.04-0.90). An ROC curve revealed that TRAIL's area under the curve (AUC) was 0.83 (95% CI 0.76-0.88). The optimal cut-off value for TRAIL was 18 pg/mL, with a sensitivity, specificity, negative predictive value, positive predictive value, positive likelihood ratio, and negative likelihood ratio of 89%, 69%, 99%, 15%, 2.87, and 0.16, respectively. Compared with the risk stratification algorithm outlined in the 2019 ESC guidelines, our biomarker-based risk stratification strategy (combining TRAIL and hs-cTnI) has a similar risk classification effect. CONCLUSION: Reduced plasma TRAIL levels predict short-term adverse events in normotensive patients with acute PE. The combination of the 2019 ESC algorithm and TRAIL aids risk stratification in normotensive patients with acute PE.

Shelf-Life Prediction and Critical Value of Quality Index of Sichuan Sauerkraut Based on Kinetic Model and Principal Component Analysis.

Kinetic models and accelerated shelf-life testing were employed to estimate the shelf-life of Sichuan sauerkraut. The texture, color, total acid, microbe, near-infrared analysis, volatile components, taste, and sensory evaluation of Sichuan sauerkraut stored at 25, 35, and 45 °C were determined. Principal component analysis (PCA) and Fisher discriminant analysis (FDA) were used to analyze the e-tongue data. According to the above analysis, Sichuan sauerkraut with different storage times can be divided into three types: completely acceptable period, acceptable period, and unacceptable period. The model was found to be useful to determine the critical values of various quality indicators. Furthermore, the zero-order kinetic reaction model (R2, 0.8699-0.9895) was fitted better than the first-order kinetic reaction model. The Arrhenius model (Ea value was 47.23-72.09 kJ/mol, kref value was 1.076 × 106-9.220 × 1010 d-1) exhibited a higher fitting degree than the Eyring model. Based on the analysis of physical properties, the shelf-life of Sichuan sauerkraut was more accurately predicted by the combination of the zero-order kinetic reaction model and the Arrhenius model, while the error back propagation artificial neural network (BP-ANN) model could better predict the chemical properties. It is a better choice for dealers and consumers to judge the shelf life and edibility of food by shelf-life model.

A Novel Clinical Five-Risk Factor Panel for Individualized Recurrence Risk Assessment of Patients With Acute Anterior Uveitis.

Purpose: Detecting and managing relapses of acute anterior uveitis (AAU) is necessary for improving follow-up planning to minimize recurrences and further complications. However, reliable clinical and laboratory risk factors are lacking, as is a predictive model for use in clinical practice that is capable of identifying patients at high risk for recurrence after remission. Methods: We analyzed 38 laboratory parameters and clinical data from a large longitudinal retrospective cohort of 233 patients with AAU. Association of laboratory parameters with recurrence-free survival (RFS) was evaluated using univariate Cox proportional hazards regression. A clinically applicable predictive model was developed using a logistic regression model. Results: Of the 38 laboratory parameters studied, we identified 5 parameters (HDL, ankylosing spondylitis, HLA-B27, MO, and LDL) to be associated with RFS. We developed a clinical five-risk factor panel (5RF-panel), which was capable of effectively distinguishing recurrent patients from nonrelapsed patients (area under the curve [AUC] = 0.837), as well as between patients with high and low risks of AAU recurrence (hazard ratio [HR] = 45.874, 95% confidence interval [CI] = 5.232-402.2, P < 0.001). The robust performance of the 5RF-panel was further validated in the testing cohort (AUC = 0.725, and HR = 51.982, 95% CI = 4.438-608.9, P = 0.024). Furthermore, the 5RF-panel demonstrated superior performance in stratifying recurrence risk based on known risk factors. Conclusions: We identified and validated a novel clinical 5RF-panel to predict individualized risk of AAU recurrence and improved patient classification for clinical management. Translational Relevance: The present study identified and validated a 5RF-panel that is a promising individualized predictive tool to monitor recurrence risk and guide personalized management of patients with AAU.

Multi-task learning for quality assessment of fetal head ultrasound images.

It is essential to measure anatomical parameters in prenatal ultrasound images for the growth and development of the fetus, which is highly relied on obtaining a standard plane. However, the acquisition of a standard plane is, in turn, highly subjective and depends on the clinical experience of sonographers. In order to deal with this challenge, we propose a new multi-task learning framework using a faster regional convolutional neural network (MF R-CNN) architecture for standard plane detection and quality assessment. MF R-CNN can identify the critical anatomical structure of the fetal head and analyze whether the magnification of the ultrasound image is appropriate, and then performs quality assessment of ultrasound images based on clinical protocols. Specifically, the first five convolution blocks of the MF R-CNN learn the features shared within the input data, which can be associated with the detection and classification tasks, and then extend to the task-specific output streams. In training, in order to speed up the different convergence of different tasks, we devise a section train method based on transfer learning. In addition, our proposed method also uses prior clinical and statistical knowledge to reduce the false detection rate. By identifying the key anatomical structure and magnification of the ultrasound image, we score the ultrasonic plane of fetal head to judge whether it is a standard image or not. Experimental results on our own-collected dataset show that our method can accurately make a quality assessment of an ultrasound plane within half a second. Our method achieves promising performance compared with state-of-the-art methods, which can improve the examination effectiveness and alleviate the measurement error caused by improper ultrasound scanning.

Quantitative assessment of HR and NHEJ activities via CRISPR/Cas9-induced oligodeoxynucleotide-mediated DSB repair.

Homologous recombination (HR) and non-homologous end joining (NHEJ) are the two major mechanisms for the repair of DNA double-strand breaks (DSBs) in eukaryotic cells. Previously, we designed an assay for detecting NHEJ activity by using clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) system, however, this approach cannot be used to predict the activity of HR repair. Hence, we developed a novel method that is capable of quantitatively measuring both HR and NHEJ activities via CRISPR/Cas9-induced oligodeoxynucleotide (ODN)-mediated DSB repair. In the present experimental procedures, the CRISPR/Cas9 plasmid was cotransfected with single-stranded ODN (ssODN) or blunt-ended double-stranded ODN (dsODN), both of which harbored a unique marker sequence. After the induction of site-specific DSBs by CRISPR/Cas9 system, the ssODN, functioned as the donor template for HR repair, could insert the marker sequence into the DSB sites, while the dsODN was embedded in the DSB sites through NHEJ pathway. Next, by means of PCR analysis using a specific primer for the marker sequence and the primers that flank the DSB sites, the relative amount of integrated marker sequence in the genomic DNA could be quantitatively determined. The correlation between the marker sequence abundance and the HR and NHEJ activities was confirmed by using the selective HR and NHEJ inhibitors. This accessible and rapid quantitative assay for HR and NHEJ activities might be useful for the future research of the DSB repair mechanisms.

Comparison of very-high-frequency ultrasound assessment of radial arterial wall layers after first and repeated transradial coronary procedures.

BACKGROUND: Transradial coronary procedure (TRP) traumatizes the radial artery (RA), especially resulting in changes to arterial wall morphology. This study explored the significance of the early onset of traumatic effects to wall layers of the RA following the first TRP (FTRP) and repeat TRP (RTRP) using very-high-frequency ultrabiomicroscopy (VHFUBM). METHODS: A total of 1431 patients that received TRP were divided into the FTRP group that comprised 781 patients and the RTRP group that comprised 650 patients depending on the number of procedures. Two-dimensional RA images were acquired by 30-55 MHz ultrasound one day before and one day after the procedure. RESULTS: After TRP, the incidence of intimal tears, medial dissections and external elastic lamina fracture were greater in the RTRP (P < 0.001). The RTRP group showed significantly thicker intimal thickness (IT), media thickness (MT), adventitia thickness and all complex layer thicknesses as compared with the FTRP group (P < 0.001). CONCLUSIONS: Multivariate linear regression analysis discovered that repeated TRP and other observations were independent predictors of increased IT in post-operative RA. VHFUBM provides an approach to study structural and histopathological injury in the wall layers of RA which showed increased trauma to the RA following RTRP.

Assessment of early radial injury after transradial coronary intervention by high-resolution ultrasound biomicroscopy: innovative technology application.

BACKGROUND: Transradial coronary intervention (TRI) introduces injury to the radial artery (RA) which will affect repeat transradial coronary procedure and the quality as a bypass conduit. We sought to compare the early radial injury after TRI between first-TRI and repeat-TRI by ultrasound biomicroscopy (UBM). METHODS: A total of 1116 patients who underwent the transradial coronary procedures were enrolled. The patients depending on whether for the first time to accept transradial coronary procedure were divided into first-TRI group and repeat-TRI group. The RA was examined by UBM before and one day after the procedure. RESULTS: Compared with first-TRI group, the mean RA diameter of repeat-TRI one day after the procedure decreased significantly (P < 0.05). In first-TRI group, the mean RA diameter was (2.32 ± 0.53) and (1.93 ± 0.57) mm before procedure and one day after the procedure respectively (P < 0.05). In repeat-TRI group, the mean RA diameter was (2.37 ± 0.51) and (1.79 ± 0.54) mm before procedure and one day after the procedure, respectively (P < 0.01). Compared with first-TRI group, the mean RA diameter was reduced significantly in repeat-TRI group one day after the procedure (P < 0.05). The early radial injuries and intimal thickening were compared between first-TRI and repeat-TRI. The mean intima-media thickness of RA was (0.24 ± 0.13) mm and (0.59 ± 0.28) mm before procedure and one day after the procedure in first-TRI group. The mean intima-media thickness of RA was (0.29 ± 0.16) mm and (0.68 ± 0.32) mm before procedure and one day after the procedure in repeat-TRI group. Compared with first-TRI group, the mean intimal thickening was increased significantly in repeat-TRI group one day after the procedure (P < 0.05). Intimal dissection, stenosis and occlusion were all significantly greater in repeat-TRI RAs (P < 0.05). Linear regression analysis revealed that diameter, repeated TRI procedure and PCI procedure were the independent predictors of intimal thickening. CONCLUSIONS: RA early injuries were greater in repeat-TRI patients than in first-TRI patients. We first use high-resolution UBM imaging to demonstrate the rate of radial injury and revealed that diameter, repeated TRI procedure and PCI procedure were the independent predictors of intimal thickening.