Enhanced ß-glucosidase in Western flower thrips affects its interaction with the redox-based strategies of kidney beans under elevated CO2.

ß-Glucosidase is validated as an elicitor for early immune responses in plants and it was detected in the salivary glands of Frankliniella occidentalis in previous research. Seven differentially expressed genes encoding ß-glucosidase were obtained by comparing the transcriptomes of F. occidentalis adults grown under two different CO2 concentrations (800 vs. 400 ppm), which might be associated with the differences in the interaction between F. occidentalis adults and its host plant, Phaseolus vulgaris under different CO2 levels. To verify this speculation, changes in defense responses based on the production and elimination of reactive oxygen species (ROS) in P. vulgaris leaves treated with three levels of ß-glucosidase activity under ambient CO2 (aCO2 ) and elevated CO2 (eCO2 ) were measured in this study. According to the results, significantly higher levels of ROS were noticed under eCO2 compared to aCO2 , which was caused by the increased ß-glucosidase activity in thrips due to increased cellulose content in P. vulgaris leaves under eCO2 . Together with the lower activities of superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) in injured leaves under eCO2 , P. vulgaris leaves would be negatively affected on redox-based defense by eCO2 , thus facilitating thrips damage under climate change.

[Common Walking Fault of Multileaf Collimator in Linear Accelerator].

This paper introduces the failure phenomenon, failure analysis, maintenance process and method of SIEMENS PRIMUS linear accelerator.

An efficient method for rapid screening of triterpenoid saponins in three Glycyrrhiza species using rapid resolution liquid chromatography quadrupole time-of-flight mass spectrometry combined with mass defect filtering.

Triterpenoid saponins, a major bioactive component of liquorice, possess high hydrophilicity and often co-occur with other impurities of similar polarity. Additionally, subtle structural differences of some triterpenoid saponins bring challenges to comprehensive characterisation. In this study, triterpenoid saponins of three Glycyrrhiza species were systematically analysed using rapid resolution liquid chromatography quadrupole time-of-flight mass spectrometry (RRLC-Q-TOF-MS) coupled with mass defect filtering (MDF). Firstly, comprehensive date acquisition was achieved using RRLC-Q-TOF-MS. Secondly, a polygonal MDF method was established by summarizing known and speculated substituents and modifications based on the core structure to rapidly screen potential triterpenoid saponins. Thirdly, based on the fragmentation patterns of reference compounds, an identification strategy for characterisation of triterpenoid saponins was proposed. The strategy divided triterpenoid saponins into three distinct classes. By this strategy, 98 triterpenoid saponins including 10 potential new ones were tentatively characterised. Finally, triterpenoid saponins of three Glycyrrhiza species were further analysed using principle component analysis (PCA) and orthogonality partial least squares discriminant analysis (OPLS-DA). Among these, 18 compounds with variable importance in projections (VIP) > 1.0 and P values < 0.05 were selected to distinguish three Glycyrrhiza species. Overall, our study provided a reference for quality control and rational use of the three species.

Outcome Prediction of Spontaneous Supratentorial Intracerebral Hemorrhage after Surgical Treatment Based on Non-Contrast Computed Tomography: A Multicenter Study.

This study aims to explore the value of a machine learning (ML) model based on radiomics features and clinical features in predicting the outcome of spontaneous supratentorial intracerebral hemorrhage (sICH) 90 days after surgery. A total of 348 patients with sICH underwent craniotomy evacuation of hematoma from three medical centers. One hundred and eight radiomics features were extracted from sICH lesions on baseline CT. Radiomics features were screened using 12 feature selection algorithms. Clinical features included age, gender, admission Glasgow Coma Scale (GCS), intraventricular hemorrhage (IVH), midline shift (MLS), and deep ICH. Nine ML models were constructed based on clinical feature, and clinical features + radiomics features, respectively. Grid search was performed on different combinations of feature selection and ML model for parameter tuning. The averaged receiver operating characteristics (ROC) area under curve (AUC) was calculated and the model with the largest AUC was selected. It was then tested using multicenter data. The combination of lasso regression feature selection and logistic regression model based on clinical features + radiomics features had the best performance (AUC: 0.87). The best model predicted an AUC of 0.85 (95%CI, 0.75-0.94) on the internal test set and 0.81 (95%CI, 0.64-0.99) and 0.83 (95%CI, 0.68-0.97) on the two external test sets, respectively. Twenty-two radiomics features were selected by lasso regression. The second-order feature gray level non-uniformity normalized was the most important radiomics feature. Age is the feature with the greatest contribution to prediction. The combination of clinical features and radiomics features using logistic regression models can improve the outcome prediction of patients with sICH 90 days after surgery.

Saturation-Tolerant Prescribed Control for a Class of MIMO Nonlinear Systems.

This article proposes a saturation-tolerant prescribed control (SPC) for a class of multiinput and multioutput (MIMO) nonlinear systems simultaneously considering user-specified performance, unmeasurable system states, and actuator faults. To simplify the control design and decrease the conservatism, tunnel prescribed performance (TPP) is proposed not only with concise form but also smaller overshoot performance. By introducing non-negative modified signals into TPP as saturation-tolerant prescribed performance (SPP), we propose SPC to guarantee tracking errors not to violate SPP constraints despite the existence of saturation and actuator faults. Namely, SPP possesses the ability of enlarging or recovering the performance boundaries flexibly when saturations occur or disappear with the help of these non-negative signals. A novel auxiliary system is then constructed for these signals, which bridges the associations between input saturation errors and performance constraints. Considering nonlinearities and uncertainties in systems, a fuzzy state observer is utilized to approximate the unmeasurable system states under saturations and unknown actuator faults. Dynamic surface control is employed to avoid tedious computations incurred by the backstepping procedures. Furthermore, the closed-loop state errors are guaranteed to a small neighborhood around the equilibrium in finite time and evolved within SPP constraints although input saturations and actuator faults occur. Finally, comparative simulations are presented to demonstrate the feasibility and effectiveness of the proposed control scheme.

Risk factors for poor outcomes of spontaneous supratentorial cerebral hemorrhage after surgery.

OBJECTIVE: This study aimed to explore the factors affecting the outcomes of spontaneous supratentorial cerebral hemorrhage 90 days after surgery. METHODS: A total of 256 patients with spontaneous supratentorial intracerebral hemorrhage underwent craniotomy evacuation of hematoma. The control group included 120 patients who received conservative treatment. The patients were divided into two subgroups based on a bifurcation of the modified Rankin Scale (mRS) 90 days after clinical therapeutics: good outcome (mRS score 0-3) and poor outcome (mRS score 4-6). The differences in clinical and imaging data between the two subgroups were analyzed. Based on difference analysis results, a binary logistic regression model was constructed to analyze the influencing factors related to poor outcomes. RESULTS: The difference analysis results in the surgery group showed statistically significant differences in age, sex, Glasgow Coma Score (GCS) on admission, coronary atherosclerosis, smoking, stroke history, blood glucose, D-dimer, hematoma size, deep cerebral hemorrhage, midline shift, hematoma burst into the ventricle, vortex sign, island sign, and black hole sign. Binary logistic regression analysis showed that deep cerebral hemorrhage, midline shift, and age > 58 years independently correlated with the poor outcomes of patients after surgery. The binary logistic regression results of the control group showed that age > 58 years and GCS ≤ 8 independently correlated with the poor outcomes of patients. CONCLUSIONS: Deep cerebral hemorrhage, midline shift, and age > 58 years significantly increased the risk of adverse prognosis in patients after surgery. The findings might help select the clinical treatment plan and evaluate the postoperative prognosis of patients.

[Expression of nm23 genes in acute myeloid leukemia and its clinical significance].

OBJECTIVE: To explore nm23 gene mRNA expression and its clinical significance in acute leukemias (AML). METHODS: The levels of nm23-H1 and nm23-H2 transcripts in 22 patients with acute myeloid leukemia (AML), 9 AML in complete remission (AML-CR), 12 acute lymphoblastic leukemia (ALL) and 4 chronic myeloid leukemia in chronic phase (CML-CP) were assayed by reverse transcriptase-polymerase chain reaction (RT-PCR). RESULTS: The expression of nm23-H1 in AL especially in AML-M4 and AML-M5 was significantly higher than that in normal blood cells. An analysis of correlation between nm23 expression and clinicopathological parameters showed that increased nm23-H1 mRNA levels were associated with some poor-prognostic factors such as extramedullary infiltration, high white blood cell count (WBC), high lactate dehydrogenase (LDH) activity and high CD(7) expression, while inversely correlated with t(8; 21) and t(15; 17) which had a good-prognostic effect. The expression of nm23-H1 in AML patients in CR was significantly decreased compared with those untreated. CONCLUSION: nm23-H1 was overexpressed in AL, especially in AML-M4 and AML-M5. High expression of nm23-H1 may be a poor prognostic factor.