A clinical-radiomics model based on noncontrast computed tomography to predict hemorrhagic transformation after stroke by machine learning: a multicenter study.

OBJECTIVE: To build a clinical-radiomics model based on noncontrast computed tomography images to identify the risk of hemorrhagic transformation (HT) in patients with acute ischemic stroke (AIS) following intravenous thrombolysis (IVT). MATERIALS AND METHODS: A total of 517 consecutive patients with AIS were screened for inclusion. Datasets from six hospitals were randomly divided into a training cohort and an internal cohort with an 8:2 ratio. The dataset of the seventh hospital was used for an independent external verification. The best dimensionality reduction method to choose features and the best machine learning (ML) algorithm to develop a model were selected. Then, the clinical, radiomics and clinical-radiomics models were developed. Finally, the performance of the models was measured using the area under the receiver operating characteristic curve (AUC). RESULTS: Of 517 from seven hospitals, 249 (48%) had HT. The best method for choosing features was recursive feature elimination, and the best ML algorithm to build models was extreme gradient boosting. In distinguishing patients with HT, the AUC of the clinical model was 0.898 (95% CI 0.873-0.921) in the internal validation cohort, and 0.911 (95% CI 0.891-0.928) in the external validation cohort; the AUC of radiomics model was 0.922 (95% CI 0.896-0.941) and 0.883 (95% CI 0.851-0.902), while the AUC of clinical-radiomics model was 0.950 (95% CI 0.925-0.967) and 0.942 (95% CI 0.927-0.958) respectively. CONCLUSION: The proposed clinical-radiomics model is a dependable approach that could provide risk assessment of HT for patients who receive IVT after stroke.

Effects of Different Nanocarbon Materials on the Properties of Al/MoO3/NCM Thermite Prepared by Electrostatic Spinning.

In order to improve thermal conductivity, energy performance, and combustion performance of the aluminum-containing thermite, nanocarbon materials were added to thermite. Aluminum/molybdenum and trioxide/nanocarbon materials (Al/MoO3/NCM) were fabricated by electrostatic spinning technology. The Al and MoO3 particles of the nAl/MoO3/NCM thermite are much smaller than nitrocellulose (NC); thus, the two components can be better attached to NC fibers. Results on thermal conductivity demonstrated that the addition of NCM can improve the thermal conductivity of Al/MoO3, and the addition of reduced graphene oxide (RGO) has a more significant impact on thermal conductivity. Energy performance analysis results indicated that the energy performance of Al/MoO3/NCM thermite spinning is the best when the value of combustion oxygen equivalent ratio (Φ) is 0.90-1.00. The combustion performance results show that the addition of NCM can significantly increase the combustion rate of thermites, and the addition of RGO improves its combustion rate the most, followed by carbon nanotubes (CNT) and nanoflake graphite (NFG) being the lowest. By changing the shape of the Al/MoO3/NCM charge and the internal composition of the charge, the sensitivity of the agent can be adjusted, and the matching performance and use performance of the electric igniter can be improved.

Formation of highly graphitic char derived from phenolic resin carbonization by Ni-Zn-B alloy.

The formation of highly graphitic phenolic resin chars (GPFCs) during catalytic carbonization at relatively low reaction temperature (1200-1600 °C) using novel Ni-Zn-B alloy catalyst with small amount of addition (5-15%) was systematically studied. Only two kinds of graphites (turbostratic graphite and ordered graphite) can be found in GPFCs after catalytic carbonization with Ni-Zn-B and their proportions were changed with reaction conditions. When Ni-Zn-B was involved at 1200-1600 °C, the phenolic resin char was fully transformed to be graphite, and ordered graphite content increased to 28.42% at 1400 °C, which was also almost twice of ordered graphite content in the char catalyzed by pure Ni. But the order graphite content would decrease due to sintering at higher reaction temperature. The addition of Zn and B can promote nickel-based alloy catalytic action by reducing melt point and accelerating graphitization respectively. It was also found that ordered graphite content could be used as a key evaluation parameter to directly reflect the quality of GPFCs based on detailed characteristics analysis. The model between three reaction conditions (reaction temperature, retention time, catalyst content) and ordered graphite content was built with artificial neural network (ANN), and the prediction accuracy of ANN was high up to 91.48%.

Molecular magnetic resonance probe targeting VEGF165: preparation and in vitro and in vivo evaluation.

A new method for imaging the tumor human vascular endothelial growth factor 165 (VEGF 165) is presented. A magnetic resonance imaging (MRI) probe was prepared by crosslinking ultrasmall superparamagnetic iron oxide (USPIO) nanoparticles to the aptamer for tumor vascular endothelial growth factor 165 (VEGF165-aptamer). The molecular probe was evaluated for its in vitro and in vivo activities toward VEGF165. Enzyme-linked immunosorbent assay showed that the VEGF165-aptamer-USPIO nanoparticles conjugate specifically binds to VEGF165 in vitro. A cell proliferation test showed that VEGF165-aptamer-USPIO seems to block the proliferation of human umbilical vein endothelial cells induced by free VEGF165, suggesting that VEGF165 is an effective target of this molecular probe. In xenograft mice carrying liver cancer that expresses VEGF165, T2-weighted imaging of the tumor displayed marked negative enhancement 3 h after the intravenous administration of VEGF165-aptamer-USPIO. The enhancement disappeared 6 h after administration of the probe. These results suggest the targeted imaging effect of VEGF165-aptamer-USPIO probe in vivo for VEGF165-expressing tumors. This is the first report of a targeted MRI molecular probe based on USPIO and VEGF165-aptamer.