Dual-functional lanthanide-MOF probe nanocomposite based on hydroxyapatite nanowires as fluorescent sensor for ascorbic acid.

A dual-functional lanthanide-MOF nanocomposite probe was designed and constructed for the detection of ascorbic acid (AA). The magnetically functionalized hydroxyapatite nanowires are selected as the carriers and simultaneously loaded with ciprofloxacin (CIP) and terbium metal organic framework to form the internal reference fluorescence probe nanocomposite (Fe3O4-HAPNWs-Tb/MOF-CIP). This dual-functional lanthanide-MOF probe not only combines the respectively unique fluorescence properties of lanthanide MOFs and CIP, but also takes full advantage of the rapid separation properties of the magnetic component. Structural and spectroscopic characterization results have demonstrated the successful synthesis of probe material and the fluorescence mechanism. At a suitable excitation wavelength (295 nm), the probe can simultaneously emit characteristic fluorescence of CIP (445 nm) and Tb3+ (543 nm). In the presence of AA, the ratio of I543/I445 decreases rapidly with increasing of AA concentration. The linear range of determination is 0.3-40 µM with a detection limit of 20.4 nM. The contents of AA in vitamin C tablets and four fruit juice samples were detected by the composite probe. The spiked recoveries ranged from 82.6 to 104.2% with relative standard deviations (RSD) less than 2.1%, revealing the practical application value of the developed sensor in healthcare and food fields. A novel internal reference fluorescence sensor (Fe O -HAPNWs-Tb/MOF-CIP) was constructed for detecting ascorbic acid by solvothermal and self-assembly techniques, showing excellent selectivity and sensitivity based on the different responses of Tb/MOF and CIP to the target.

Human mobility description by physical analogy of electric circuit network based on GPS data.

Human mobility in an urban area is complicated; the origins, destinations, and transportation modes of each person differ. The quantitative description of urban human mobility has recently attracted the attention of researchers, and it highly related to urban science problems. Herein, combined with physics inspiration, we introduce a revised electric circuit model (RECM) in which moving people are regarded as charged particles and analogical concepts of electromagnetism such as human conductivity and human potential enable us to capture the characteristics of urban human mobility. We introduce the unit system, ensure the uniqueness of the calculation result, and reduce the computation cost of the algorithm to 1/10,000 compared with the original ECM, making the model more universal and easier to use. We compared features including human conductivity and potential between different major cities in Japan to show our improvement of the universality and the application range of the model. Furthermore, based on inspiration of physics, we propose a route generation model (RGM) to simulate a human flow pattern that automatically determines suitable routes between a given origin and destination as a source and sink, respectively. These discoveries are expected to lead to new approaches to the solution of urban science problems.

Can software-defined vehicles never roll over: A perspective of active structural transformation.

The revolution of physical structure is highly significant for future software defined vehicles (SDV). Active structural transformation is a promising feature of the next generation of vehicle physical structure. It can enhance the dynamic performance of vehicles, thus providing safer and more comfortable ride experiences, such as the ability to avoid rollover in critical situations. Based on the active structural transformation technology, this study proposes a novel approach to improve the dynamic performance of a vehicle. The first analytical motion model of a vehicle with active structural transformation capability is established. Then, a multi-objective optimization problem with the adjustable parameters as design variables is abstracted and solved with an innovative scenario specific optimization method. Simulation results under different driving scenarios revealed that the active transformable vehicle applying the proposed method could significantly improve the handling stability without sacrificing the ride comfort, compared with a conventional vehicle with a fixed structure. The proposed method pipeline is defined by the software and supported by the hardware. It fully embodies the characteristics of SDV, and inspires the improvement of multiple types of vehicle performance based on the concept of "being defined by software" and the revolution of the physical structure.

Magnetic resin composites for the enrichment of proteins, peptides and phosphopeptides.

There is growing interest in the development of materials for enriching proteins and phosphoproteins from complex sample matrices for mass spectrometric analysis. Herein, we designed and synthesized two types of magnetic resin composites, i.e., MTS9200@Fe3O4 and FPA90CL@Fe3O4, and assessed their applications as adsorbents for enriching proteins, peptides and phosphopeptides. With the combination of Fe3+-IMAC interaction (MTS9200) or electrostatic attraction (FPA90CL) of resins and the adsorption of Fe3O4, the prepared composites exhibited higher capacities for adsorbing a protein (bovine serum albumin, at 195.71 and 135.03 mg g-1 for MTS9200@Fe3O4 and FPA90CL@Fe3O4, respectively) than MTS9200, FPA90CL and Fe3O4. In addition, due to the contributions of the hydrophobic skeleton of resins and Fe3O4, the magnetic resin composites allowed for efficient enrichment of peptides. Moreover, through Fe3+-IMAC interaction or electrostatic attraction of resins and Fe-O MOAC interaction of Fe3O4 with phosphate groups, phosphopeptides could also be captured. Furthermore, we employed the prepared composites for enriching proteins and phosphopeptides from human serum, where 466 and 506 proteins, and 434 and 356 phosphorylation sites, were detected from human serum after being processed with FPA90CL@Fe3O4 and MTS9200@Fe3O4, respectively. Together, our work revealed the great potential of magnetic resin composites as enrichment materials for proteomics and phosphoproteomics analysis.

[Trapping array-based preparative two-dimensional liquid chromatography for the purification of four components in tobacco leaves].

Two-dimensional liquid chromatography (2D-LC) has gained increased attention because of its high peak capacity for separating complex samples. However, preparative 2D-LC aimed at isolating compounds is significantly different compared with one-dimensional liquid chromatography (1D-LC) in terms of method development and system configuration; thus, it is less developed than its analytical counterpart. The use of 2D-LC in large-scale product preparation has rarely been reported. Hence, a preparative 2D-LC system was developed in this study. The system was composed of one set of preparative LC modules as a separation system, with a dilution pump, switch valves, and trap column array as the interface, to enable the simultaneous isolation of several compounds. Tobacco was used as a sample, and the developed system was applied to isolate nicotine, chlorogenic acid, rutin, and solanesol. The chromatographic conditions were developed by investigating the trapping efficiency of different types of trap column packings, and chromatographic behaviors under different overload conditions. The four compounds were isolated in one 2D-LC run with high purity. The developed system features low cost because it employs medium-pressure isolation, excellent automation owing to its use of an online column switch, high stability, and capability for large-scale production. The isolation of chemicals from tobacco leaves as pharmaceutical raw materials could aid in the development of the tobacco industry and promote the local agricultural economy.

Macroscopic volume change of dynamic hydrogels induced by reversible DNA hybridization.

Molecular recognition is fundamental to the specific interactions between molecules, of which the best known examples are antibody-antigen binding and cDNA hybridization. Reversible manipulation of the molecular recognition events is still a very challenging topic, and such studies are often performed at the molecular level. An important consideration is the collection of changes at the molecular level to provide macroscopic observables. This research makes use of photoresponsive molecular recognition for the fabrication of novel photoregulated dynamic materials. Specifically, a dynamic hydrogel was prepared by grafting azobenzene-tethered ssDNA and its cDNA to the hydrogel network. The macroscopic volume of the hydrogel can be manipulated through the photoreversible DNA hybridization controlled by alternate irradiation of UV and visible light. The effects of synthetic parameters including the concentration of DNA, polymer monomer, and permanent cross-linker are also discussed.

Prognostic value of hyperuricemia for patients with sepsis in the intensive care unit.

This study evaluated the relationship between hyperuricemia at admission and the clinical prognosis of patients with sepsis. The data were obtained from the Intensive Care Medical Information Database III. The patients were divided into a normal serum uric acid group and a hyperuricemia group. The main outcome was 90-day mortality, and the secondary outcomes were hospital mortality, 30-day mortality, and acute kidney injury. Propensity score matching was used to balance the baseline characteristics of the groups. Our study retrospectively included 954 patients. Before and after propensity score matching, the incidence of AKI, the 30-day and 90-day mortality rates were significantly higher in the hyperuricemia group. Cox regression analysis showed that hyperuricemia was significantly associated with 90-day mortality (HR 1.648, 95% CI 1.215-2.234, p = 0.006), and hyperuricemia was significantly associated with the incidence of AKI (HR 1.773, 95% CI 1.107-2.841, p = 0.017). The Kaplan-Meier survival curve showed that the 90-day survival rate was significantly lower in the hyperuricemia group. In patients with sepsis in the intensive care unit, hyperuricemia was significantly associated with increased risk 90-day all-cause mortality and the incidence of AKI.

Correlation between glycaemic variability and prognosis in diabetic patients with CKD.

INTRODUCTION: Glycaemic variability (GV), rather than glucose level, has been shown to be an important factor associated with in-hospital mortality. The coefficient of variation of glucose (GLUCV) is one of the methods used to evaluate GV. However, the clinical significance of GLUCV in diabetes mellitus (DM) patients diagnosed with chronic kidney disease (CKD) as a risk factor for long-term adverse changes is unknown. MATERIAL AND METHODS: In this retrospective study, we extracted data of adult DM patients diagnosed with CKD from the Medical Information Mart for Intensive Care (MIMIC-IV). We sought to investigate the relationship between GV and in-hospital mortality as well as 30-day mortality. A non-parametric test was used to compare baseline characteristics between groups. Kaplan-Meier analysis and Cox regression model were used to analyse the risk factors associated with in-hospital and 30-day mortality. RESULTS: A total of 1572 DM patients with CKD were included in our data analysis. The quartile of the GLUCV values was used to assign subjects to 4 groups: GLUCV1 (GLUCV < 24), GLUCV2 (24 ≤ GLUCV < 31), GLUCV3 (31 ≤ GLUCV < 39) and GLUCV 4 (GLUCV ≥ 39). COX regression analysis revealed that the GLUCV was an independent risk factor for in-hospital and 30-day mortality [GLUCV2 group (HR = 0.639, 95% CI: 0.454-0.899, p = 0.010), GLUCV3 group (HR = 0.668, 95% CI: 0.476-0.936, p = 0.019), and GLUCV3 group (HR = 0.726, 95% CI: 0.528-0.999, p = 0.049)]. The Kaplan-Meier survival curve was steeper in the GLUCV1 and GLUCV4 groups, and the survival rate decreased in a time-dependent manner. CONCLUSIONS: Herein, we validated GV as a mortality risk factor for DM patients with CKD. Therefore, monitoring and adjusting GV in hospitalized patients might have a significant treatment benefit.

Preparation and evaluation of ultra-long open-tubular capillary columns modified with zeolitic imidazolate framework-8 incorporated polymeric porous layer for liquid chromatography.

An ultra-long (5 m) open tubular capillary liquid chromatographic column was prepared by incorporating Metal Organic Framework (MOF), zeolitic imidazolate framework-8 (ZIF-8), directly into polymer coating, which was synthesized by the copolymerization of 4-vinylbenzyl chloride and divinylbenzene, on the capillary inner surface. The prepared ZIF-8 incorporate polymeric open tubular capillary column (denoted as ZIF-8-p(VBC/DVB) OTCC) was evaluated with thiourea, alkylbenzenes and polycyclic aromatic hydrocarbons as probe molecules. The results showed that the ultra-long column achieved absolute column efficiency of 130,000 plates for thiourea, and the incorporation of ZIF-8 effectively improved the chromatography performance of the OTCC. Baseline separation of aromatic compounds and position isomers was achieved based on multiple interactions provided by the zeolitic imidazolate framework and polymer, including hydrophobic interaction, π-π stacking interaction and the coordination effect. The RSD values (run-to-run, day-to-day, column-to-column, n = 3) of retention time of phenylenediamine isomers and propylbenzene isomers were less than 0.7%, 1.2% and 4.0% respectively, suggesting excellent repeatability. Finally, the prepared ZIF-8-p(VBC/DVB) OTCC was applied to the separation of hydroxyacetophenone isomers with satisfied results.

The Association of Coagulation Indicators and Coagulant Agents With 30-Day Mortality of Critical Diabetics.

Diabetes, regarded as a global health concerned disease, was focused by the World Health Organization (WHO). Patients with diabetes may have a hypercoagulable and hypo-fibrinolysis state. There is lots of research about cardiovascular effects on diabetes patients, but less about the coagulation system. This study is designed to investigate the relationship between coagulation indicators and 30-day mortality of critical diabetes patients. In this retrospective, single-center study, we included adult patients diagnosed with diabetes. Data, including demographic, complication, laboratory tests, scoring system, and anticoagulant treatment, were extracted from Medical Information Mart for Intensive Care (MIMIC-III). The receiver operating characteristic (ROC) curve and Kaplan-Meier curve were applied to predict the association of mortality and coagulation indicators. Cox hazard regression model and subgroup analysis were used to analyze the risk factors associated with 30-day mortality. A total of 4026 patients with diabetes mellitus were included in our study, of whom 3312 survived after admitted to the hospital and 714 died. Cox hazard regression showed anticoagulant therapy might decrease the risk of 30-day mortality after adjusted. In age <70 subgroup analysis, we found that patients with PTT <26.8 s or lightly increased PT may increase odds of 30-day hospital death (HR, 95%CI, 2.044 (1.376, 3.034), 1.562 (1.042, 2.343)). When age >70, lightly increased PTT may reduce the risk of mortality, but PT >16.3 s, a high level of hypo-coagulation state, increase risk of mortality (HR, 95%CI, 0.756 (0.574, 0.996), 1.756 (1.129, 2.729)). Critical diabetes patients may benefit from anticoagulant agents. The abnormal coagulant function is related to the risk of 30-day mortality.

The separation characteristics and performance evaluation of the silica-based poly(pentabromostyrene) stationary phase in capillary electrochromatography.

A mixed-mode capillary column packed with silica-based poly(pentabromostyrene) particles (denoted as SiO2@pPBS) was prepared and applied to capillary electrochromatography (CEC) separation. With the presence of benzene rings and bromine atoms in polymer chains, the SiO2@pPBS column provides a reversed-phase/hydrophilic mixed-mode retention mechanism owing to hydrophilic, hydrophobic and π-π interactions between the stationary phase and various analytes, including alkylbenzenes, polycyclic aromatic hydrocarbons, nucleosides, phenols and anilines. In CEC mode, the separation behavior of charged solutes is not only related to the interaction with the stationary phase, but also influenced by electrophoretic effects, which may lead to different selectivities compared to high performance liquid chromatography (HPLC). A column efficiency of up to 1.22 × 105 N m-1 was achieved for p-chloroaniline. Besides, the RSDs of retention time of anilines for run to run (n = 5), day to day (n = 5) and column to column (n = 3) were all less than 4.4%. Finally, the SiO2@pPBS capillary column was applied to the separation of coking wastewater with satisfactory results. All the results demonstrated that the SiO2@pPBS capillary packed column with RP/HILIC mixed-mode has great application potential.

Machine learning prediction models for prognosis of critically ill patients after open-heart surgery.

We aimed to build up multiple machine learning models to predict 30-days mortality, and 3 complications including septic shock, thrombocytopenia, and liver dysfunction after open-heart surgery. Patients who underwent coronary artery bypass surgery, aortic valve replacement, or other heart-related surgeries between 2001 and 2012 were extracted from MIMIC-III databases. Extreme gradient boosting, random forest, artificial neural network, and logistic regression were employed to build models by utilizing fivefold cross-validation and grid search. Receiver operating characteristic curve, area under curve (AUC), decision curve analysis, test accuracy, F1 score, precision, and recall were applied to access the performance. Among 6844 patients enrolled in this study, 215 patients (3.1%) died within 30 days after surgery, part of patients appeared liver dysfunction (248; 3.6%), septic shock (32; 0.5%), and thrombocytopenia (202; 2.9%). XGBoost, selected to be our final model, achieved the best performance with highest AUC and F1 score. AUC and F1 score of XGBoost for 4 outcomes: 0.88 and 0.58 for 30-days mortality, 0.98 and 0.70 for septic shock, 0.88 and 0.55 for thrombocytopenia, 0.89 and 0.40 for liver dysfunction. We developed a promising model, presented as software, to realize monitoring for patients in ICU and to improve prognosis.

Evasive behavior-based method for threat assessment in different scenarios: A novel framework for intelligent vehicle.

The threat assessment process is a crucial part of intelligent vehicles (IVs) for evaluating the levels of criticality and taking possible measures to avoid the collision, especially for the collision avoidance systems (CAS). In this study, a novel threat assessment framework based on the driver's evasive behavior, namely the CPIC, is proposed, which integrates the crash probability (CP) and inevitable crash (IC) state to be widely used by different CAS in different scenarios. In the first step of the CPIC framework, the detailed evasive driver behavior models (E-DBMs) in the form of probability density functions (PDFs) were introduced to generate more realistic collision-avoidance trajectories. Two techniques for sampling these trajectories, namely the Markov Chain Monte Carlo (MCMC) and adaptive Gaussian mixture framework (GMM) methods, were utilized to ensure the samples were from the area of high probability density in the E-DBMs. The CP value could be derived by considering multiple collision-avoidance trajectories. To confirm the IC state in step 2, the CPIC framework employed the driving limit-based approach for IC checking, which combined the CP value to double-check the unavoidable collision. A total of 82 critical events from the real-world naturalistic driving study, the Strategic Highway Research Program 2 (SHRP2), were extracted to verify the performance of the CPIC framework in different scenarios. Results show that the proposed method clearly revealed the risk levels when two vehicles were approaching, and 80 events were successfully identified as near crashes/crashes. Moreover, the real-time performance of the CPIC framework was also demonstrated. The findings indicate this CPIC framework could be used in practical applications of IVs in different scenarios.

Determining the steering direction in critical situations: A decision tree-based method.

Objective: Factors related to the driver-vehicle-environment system have a significant influence on a driver's decision to perform evasive maneuvers, especially the decision of steering direction (DSD) in critical situations. However, few studies have systematically investigated the relationships between these factors and DSD. The objective of this study is to analyze and model drivers' DSD in critical situations.Methods: Data from the NASS-CDS from 1995 to 2015 were utilized in this study. The decision tree (DT) classifier was utilized to model a driver's DSD for both intersection-related and non-intersection-related subsets, combined with a 10-fold cross-validation technique and grid search approach to evaluate and optimize the model. An analysis of variable importance was also conducted.Results: Two separate DT models of drivers' DSD were obtained based on the optimized hyperparameters, with test accuracies of 84.6% (intersection-related) and 79.2% (non-intersection-related). The variable DIFFANGLE (angle difference between 2 vehicles) ranked as the most important factor influencing drivers' DSD in both models. The variables, in order of importance, were SPEED (travel speed of the subject vehicle) and AGE (driver's age) for the intersection-related model and SPEED, PREMOVE (pre-event movement), TRAFFLOW (trafficway flow), and AGE for the non-intersection-related model. Moreover, an interesting same direction pattern was observed in both DT models.Conclusions: This study employed NASS-CDS data and DT classifiers to analyze and model drivers' DSD behavior. The test accuracies for both classifiers were acceptable. Potential variables influencing drivers' DSD were explored, which improves the research on evasive behavior in lateral movement and promotes further applications for intelligent vehicles using the constructed models.

Protective effect of 2-deoxy-D-glucose on the cytotoxicity of cyclosporin A in vitro.

The present study aimed to investigate the mechanism underlying the protective effect of 2-deoxy-D-glucose (2-DG) on the cytotoxicity of cyclosporin A (CsA) in vitro using NRK-52E cells. Staining with Hoechst 33342/propidium iodide prior to flow cytometric analysis was performed to assess the rate of cellular apoptosis and necrosis induced by CsA. The expression levels of lactate dehydrogenase (LDH), caspase 3, receptor-interacting protein kinase 3 (RIP3), reactive oxygen species (ROS), glutathione (GSH) and malondialdehyde (MDA) were detected using colorimetry, ELISA, western blotting or flow cytometric analysis to determine the protective effects of 2-DG on CsA-induced cell death. The results demonstrated that 2-DG inhibited the release of LDH, the activation of caspase 3 and the generation of ROS induced by CsA, but had no effect on the expression of RIP3. Treatment with 2-DG increased the expression of GSH and decreased the expression of MDA in dose-dependent manner, and reduced the rate of the cellular apoptosis and necrosis induced by CsA. Therefore, 2-DG inhibited CsA-induced cellular apoptosis and necrosis, possibly by reducing the production of ROS. Inhibiting the activation of caspase 3 is one of the protective mechanisms of 2-DG, however, the expression of RIP3 remained unaltered following treatment with 2-DG. Whether 2-DG inhibits the CsA-induced necrosis and apoptosis by inhibiting the RIP3 signaling pathway remains to be elucidated.

Protective effects of 2-deoxy-D-glucose on nephrotoxicity induced by cyclosporine A in rats.

OBJECTIVE: This study aims to explore the protective effect mechanism of 2-deoxy-D-glucose on nephrotoxicity of cyclosporin A in vivo. METHOD: Renal toxicity of SD rats model induced by CsA was established. Serum creatinine, blood urea nitrogen, urine NAG, GSH and MDA were determined and the histopathological changes of rat renal cortex were observed to explore the protective effects of 2-DG on CsA-induced nephrotoxicity. RESULTS: Serum creatinine, BUN and urinary NAG of rats were significantly changed in experimental groups. Pathological results showed that there was obvious renal tubular injury in model group, however, the renal injury was significantly reduced in pre-treated with 2-DG. CONCLUSIONS: 2-DG had obvious protective effect on nephrotoxicity especially with high dose. This protective effect could be related to the reduction of ROS induced by CsA. However, 2-DG had no effect on the expression of RIP3.