Graphitic carbon nitride (gCN) has a broad range of promising applications, from energy harvesting and storage to sensing. However, most of the applications are still restricted due to gCN poor ...dispersibility and limited functional groups. Herein, a direct photografting of gCN using various polymer brushes with tailorable functionalities via UV photopolymerization at ambient conditions is demonstrated. The systematic study of polymer brush-functionalized gCN reveals that the polymerization did not alter the inherent structure of gCN. Compared to the pristine gCN, the gCN-polymer composites show good dispersibility in various solvents such as water, ethanol, and tetrahydrofuran (THF). Patterned polymer brushes on gCN can be realized by employing photomask and microcontact printing technology. The polymer brushes with incorporated silver nanoparticles (AgNPs) on gCN can act as a multifunctional recyclable active sensing layer for surface-enhanced Raman spectroscopy (SERS) detection and photocatalysis. This multifunctionality is shown in consecutive cycles of SERS and photocatalytic degradation processes that can be applied to in situ monitor pollutants, such as dyes or pharmaceutical waste, with high chemical sensitivity as well as to water remediation. This dual functionality provides a significant advantage to our AgNPs/polymer-gCN with regard to state-of-the-art systems reported so far that only allow SERS pollutant detection but not their decomposition. These results may provide a new methodology for the covalent functionalization of gCN and may enable new applications in the field of catalysis, biosensors, and, most interestingly, environmental remediation.
The purpose of this study is to establish a novel pulmonary embolism (PE) risk prediction model based on machine learning (ML) methods and to evaluate the predictive performance of the model and the ...contribution of variables to the predictive performance. We conducted a retrospective study at the Shanghai Tenth People's Hospital and collected the clinical data of in-patients that received pulmonary computed tomography imaging between January 1, 2014 and December 31, 2018. We trained several ML models, including logistic regression (LR), support vector machine (SVM), random forest (RF), and gradient boosting decision tree (GBDT), compared the models with representative baseline algorithms, and investigated their predictability and feature interpretation. A total of 3619 patients were included in the study. We discovered that the GBDT model demonstrated the best prediction with an area under the curve value of 0.799, whereas those of the RF, LR, and SVM models were 0.791, 0.716, and 0.743, respectively. The sensibilities of the GBDT, LR, RF, and SVM models were 63.9%, 68.1%, 71.5%, and 75%, respectively; the specificities were 81.1%, 66.1, 72.7%, and 65.1%, respectively; and the accuracies were 77.8%, 66.5%, 72.5%, and 67%, respectively. We discovered that the maximum D-dimer level contributed the most to the outcome prediction, followed by the extreme growth rate of the plasma fibrinogen level, in-hospital duration, and extreme growth rate of the D-dimer level. The study demonstrates the superiority of the GBDT model in predicting the risk of PE in hospitalized patients. However, in order to be applied in clinical practice and provide support for clinical decision-making, the predictive performance of the model needs to be prospectively verified.
Poly(2‐oxazoline)s (POx) bottle‐brush brushes have excellent biocompatible and lubricious properties, which are promising for the functionalization of surfaces for biomedical devices. Herein, a ...facile synthesis of POx is reported which is based bottle‐brush brushes (BBBs) on solid substrates. Initially, backbone brushes of poly(2‐isopropenyl‐2‐oxazoline) (PIPOx) were fabricated via surface initiated Cu0 plate‐mediated controlled radical polymerization (SI‐Cu0CRP). Poly(2‐methyl‐2‐oxazoline) (PMeOx) side chains were subsequently grafted from the PIPOx backbone via living cationic ring opening polymerization (LCROP), which result in ≈100 % increase in brush thickness (from 58 to 110 nm). The resultant BBBs shows tunable thickness up to 300 nm and high grafting density (σ) with 0.42 chains nm−2. The synthetic procedure of POx BBBs can be further simplified by using SI‐Cu0CRP with POx molecular brush as macromonomer (Mn=536 g mol−1, PDI=1.10), which results in BBBs surface up to 60 nm with well‐defined molecular structure. Both procedures are significantly superior to the state‐of‐art approaches for the synthesis of POx BBBs, which are promising to design bio‐functional surfaces.
The facile fabrication of POx BBBs with high layer thickness (up to ≈300 nm) and grafting density (σ=0.42 chains nm−2) via surface‐initiated Cu‐mediated controlled radical polymerization (SI‐Cu0CRP) is presented. The patterned and gradient POx BBB surfaces were fabricated in a straightforward manner. The dual functionalities of POx BBBs were demonstrated by fluorescent labelling.
The aim of this study was to determine the proportion of hidden blood loss (HBL) in patients treated with minimally invasive surgery, and to compare the HBL between patients treated with percutaneous ...pedicle screw fixation (PPSF) and the mini-open Wiltse approach with pedicle screw fixation (MWPSF).
From January 2017 to January 2019, a total of 119 patients with thoracolumbar fractures were included in the analysis, of which 58 cases received PPSF and 61 cases received MWPSF. The clinical information and demographic results were collected and compared. And the HBL of the patients is calculated by the combination formulas of Nadler, Gross and Sehat.
Compared with the PPSF group, operation time of MWPSF is shorter. The fluoroscopy times are 13.6 ± 3.0 in PPSF group and 5.6 ± 1.6 in MWPSF group (p < 0.001). As shown in Table 3, the intraoperative blood loss in PPSF group is 31.9 ± 9.6 ml, which is significantly less than that in the MWPSF group (44.0 ± 14.9 ml). The HBL (445.7 ± 228.9 ml), and HBL% (91.2 ± 7.7%) of the PPSF group are significantly higher than that in the MWPSF group (P < 0.05). And the total blood loss (TBL) of the PPSF group (477.6 ± 228.8 ml) is also more than that in the MWPSF group (401.0 ± 171.3 ml).
Our results suggest that in the minimally invasive surgical treatment of thoracolumbar fractures, the perioperative HBL is much higher than visible blood loss (VBL). Although PPSF has less intraoperative blood loss, it has higher TBL and HBL than those of MWPSF. Compared with MWPSF, we should pay more attention to the postoperative anemia status of patients with thoracolumbar fractures undergoing PPSF surgery.
•The PDA nanospheres with uniform diameter of 150–200nm were used to remove Hg2+ efficiently and selectively.•The desorption capacity of PDA nanospheres was 100% in pH 1.•The structure and removal ...capacity of PDA nanospheres remained almost unchanged after recycling five times.
This study reported a new method for efficient removal of Hg2+ from contaminated water using highly selective adsorptive polydopamine (PDA) nanospheres, which were uniform and had a small diameter (150–200nm). The adsorption isotherms, kinetics, thermodynamics were investigated. Also, the effects of ionic strength, co-existing ions on removing ability of PDA nanospheres for Hg2+ were studied. Adsorption of Hg2+ was very fast and efficient as adsorption equilibrium was completed within 4h and the maximum adsorption capacities were 1861.72mg/g, 2037.22mg/g, and 2076.81mg/g at 298K, 313K, and 328K respectively, increasing with increasing of temperature. The PDA nanospheres exhibited highly selective adsorption of Hg2+ and had a total desorption capacity of 100% in hydrochloric acid solution, pH 1. The results showed that the structure of PDA nanospheres remained almost unchanged after recycling five times. Furthermore, X-ray photoelectron spectroscopy (XPS) was employed to determine the elements of PDA nanospheres before and after Hg2+ adsorption. Considering their efficient and highly Hg2+ selective adsorption, total recycle capacity, and high stability, PDA nanospheres will be feasible in a number of practical applications.
Introduction
Venous thromboembolism (VTE) risk assessment at admission is of great importance for early screening and timely prophylaxis and management during hospitalization. The purpose of this ...study is to develop and validate novel risk assessment models at admission based on machine learning (ML) methods.
Methods
In this retrospective study, a total of 3078 individuals were included with their Caprini variables within 24 hours at admission. Then several ML models were built, including logistic regression (LR), random forest (RF), and extreme gradient boosting (XGB). The prediction performance of ML models and the Caprini risk score (CRS) was then validated and compared through a series of evaluation metrics.
Results
The values of AUROC and AUPRC were 0.798 and 0.303 for LR, 0.804 and 0.360 for RF, and 0.796 and 0.352 for XGB, respectively, which outperformed CRS significantly (0.714 and 0.180,
P
< 0.001). When prediction scores were stratified into three risk levels for application, RF could obtain more reasonable results than CRS, including smaller false positive alerts and larger lower-risk proportions. The boosting results of stratification were further verified by the net-reclassification-improvement (NRI) analysis.
Discussion
This study indicated that machine learning models could improve VTE risk prediction at admission compared with CRS. Among the ML models, RF was found to have superior performance and great potential in clinical practice.
Despite extensive efforts in designing and preparing switchable underwater adhesives, it is not easy to regulate the underwater adhesion strength locally and remotely. Here, we design and synthesize ...photoreversible copolymer of polydopamine methacrylamide‐co‐methoxyethyl‐acrylate‐co‐7‐(2‐methacryloyloxyethoxy)‐4‐methylcoumarin. Due to the dynamic formation and breaking of chemical crosslinking networks within the smart adhesives, the material shows widely tunable adhesion strength from ∼150 to ∼450 kPa and long‐range reversible maneuverability under orthogonal 254 and 365 nm ultraviolet light stimulation via the coumarin dimerization and cycloreversion. Moreover, the adhesive exhibits good circulation performance and stability in an acid–base environment. It also demonstrated that the bolt can be coated with the smart adhesive material for on‐demand bonding. This design principle opens the door to the development of remotely controllable high‐performance smart underwater adhesives.
We design and synthesize photoreversible copolymer of polydopamine methacrylamide‐co‐methoxyethyl‐acrylate‐co‐7‐(2‐methacryloyloxyethoxy)‐4‐methylcoumarin. The material has a widely tunable adhesion strength from ∼150 to ∼450 kPa and long‐range reversible maneuverability under orthogonal 254 and 365 nm ultraviolet stimulation. The adhesive exhibits good circulation performance and stability in an acid–base environment. This design principle opens the door for developing remotely controllable high‐performance smart underwater adhesives.
A two‐dimensional (2D) sp2‐carbon‐linked conjugated polymer framework (2D CCP‐HATN) has a nitrogen‐doped skeleton, a periodical dual‐pore structure and high chemical stability. The polymer backbone ...consists of hexaazatrinaphthalene (HATN) and cyanovinylene units linked entirely by carbon–carbon double bonds. Profiting from the shape‐persistent framework of 2D CCP‐HATN integrated with the electrochemical redox‐active HATN and the robust sp2 carbon‐carbon linkage, 2D CCP‐HATN hybridized with carbon nanotubes shows a high capacity of 116 mA h g−1, with high utilization of its redox‐active sites and superb cycling stability (91 % after 1000 cycles) and rate capability (82 %, 1.0 A g−1 vs. 0.1 A g−1) as an organic cathode material for lithium‐ion batteries.
Doping for performance: A 2D sp2‐carbon‐linked conjugated polymer (2D CCP) framework with a nitrogen‐doped skeleton and multiple redox‐active sites consists of hexaazatrinaphthalene (HATN) and cyanovinylene units linked entirely by carbon–carbon double bonds. Hybridization with carbon nanotubes results in an excellent cathode material for lithium‐ion batteries.
Structural electronics, as well as flexible and wearable devices are applications that are possible by merging polymers with metal nanoparticles. However, using conventional technologies, it is ...challenging to fabricate plasmonic structures that remain flexible. We developed three-dimensional (3D) plasmonic nanostructures/polymer sensors via single-step laser processing and further functionalization with 4-nitrobenzenethiol (4-NBT) as a molecular probe. These sensors allow ultrasensitive detection with surface-enhanced Raman spectroscopy (SERS). We tracked the 4-NBT plasmonic enhancement and changes in its vibrational spectrum under the chemical environment perturbations. As a model system, we investigated the sensor's performance when exposed to prostate cancer cells' media over 7 days showing the possibility of identifying the cell death reflected in the environment through the effects on the 4-NBT probe. Thus, the fabricated sensor could have an impact on the monitoring of the cancer treatment process. Moreover, the laser-driven nanoparticles/polymer intermixing resulted in a free-form electrically conductive composite that withstands over 1000 bending cycles without losing electrical properties. Our results bridge the gap between plasmonic sensing with SERS and flexible electronics in a scalable, energy-efficient, inexpensive, and environmentally friendly way.
This article proposes an approach to identify fractional-order systems with sparse interaction structures and high dimensions when observation data are supposed to be experimentally available. This ...approach includes two steps: first, it is to estimate the value of the fractional order by taking into account the solution properties of fractional-order systems; second, it is to identify the interaction coefficients among the system variables by employing the compressed sensing technique. An error analysis is provided analytically for this approach and a further improved approach is also proposed. Moreover, the applicability of the proposed approach is fully illustrated by two examples: one is to estimate the mutual interactions in a complex dynamical network described by fractional-order systems, and the other is to identify a high fractional-order and homogeneous sequential differential equation, which is frequently used to describe viscoelastic phenomena. All the results demonstrate the feasibility of figuring out the system mechanisms behind the data experimentally observed in physical or biological systems with viscoelastic evolution characters.
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