Inulin Reduces Kidney Damage in Type 2 Diabetic Mice by Decreasing Inflammation and Serum Metabolomics.

This study is aimed at assessing the impact of soluble dietary fiber inulin on the treatment of diabetes-related chronic inflammation and kidney injury in mice with type 2 diabetes (T2DM). The T2DM model was created by feeding the Institute of Cancer Research (ICR) mice a high-fat diet and intraperitoneally injecting them with streptozotocin (50 mg/kg for 5 consecutive days). The thirty-six ICR mice were divided into three dietary groups: the normal control (NC) group, the T2DM (DM) group, and the DM + inulin diet (INU) group. The INU group mice were given inulin at the dose of 500 mg/kg gavage daily until the end of the 12th week. After 12 weeks, the administration of inulin resulted in decreased serum levels of fasting blood glucose (FBG), low-density lipoprotein cholesterol (LDL-C), blood urea nitrogen (BUN), and creatinine (CRE). The administration of inulin not only ameliorated renal injury but also resulted in a reduction in the mRNA expressions of inflammatory factors in the spleen and serum oxidative stress levels, when compared to the DM group. Additionally, inulin treatment in mice with a T2DM model led to a significant increase in the concentrations of three primary short-chain fatty acids (SCFAs) (acetic acid, propionic acid, and butyric acid), while the concentration of advanced glycation end products (AGEs), a prominent inflammatory factor in diabetes, exhibited a significant decrease. The results of untargeted metabolomics indicate that inulin has the potential to alleviate inflammatory response and kidney damage in diabetic mice. This beneficial effect is attributed to its impact on various metabolic pathways, including glycerophospholipid metabolism, taurine and hypotaurine metabolism, arginine biosynthesis, and tryptophan metabolism. Consequently, oral inulin emerges as a promising treatment option for diabetes and kidney injury.

Exploration of a machine learning approach for diagnosing sarcopenia among Chinese community-dwelling older adults using sEMG-based data.

BACKGROUND: In the practical application of sarcopenia screening, there is a need for faster, time-saving, and community-friendly detection methods. The primary purpose of this study was to perform sarcopenia screening in community-dwelling older adults and investigate whether surface electromyogram (sEMG) from hand grip could potentially be used to detect sarcopenia using machine learning (ML) methods with reasonable features extracted from sEMG signals. The secondary aim was to provide the interpretability of the obtained ML models using a novel feature importance estimation method. METHODS: A total of 158 community-dwelling older residents (≥ 60 years old) were recruited. After screening through the diagnostic criteria of the Asian Working Group for Sarcopenia in 2019 (AWGS 2019) and data quality check, participants were assigned to the healthy group (n = 45) and the sarcopenic group (n = 48). sEMG signals from six forearm muscles were recorded during the hand grip task at 20% maximal voluntary contraction (MVC) and 50% MVC. After filtering recorded signals, nine representative features were extracted, including six time-domain features plus three time-frequency domain features. Then, a voting classifier ensembled by a support vector machine (SVM), a random forest (RF), and a gradient boosting machine (GBM) was implemented to classify healthy versus sarcopenic participants. Finally, the SHapley Additive exPlanations (SHAP) method was utilized to investigate feature importance during classification. RESULTS: Seven out of the nine features exhibited statistically significant differences between healthy and sarcopenic participants in both 20% and 50% MVC tests. Using these features, the voting classifier achieved 80% sensitivity and 73% accuracy through a five-fold cross-validation. Such performance was better than each of the SVM, RF, and GBM models alone. Lastly, SHAP results revealed that the wavelength (WL) and the kurtosis of continuous wavelet transform coefficients (CWT_kurtosis) had the highest feature impact scores. CONCLUSION: This study proposed a method for community-based sarcopenia screening using sEMG signals of forearm muscles. Using a voting classifier with nine representative features, the accuracy exceeds 70% and the sensitivity exceeds 75%, indicating moderate classification performance. Interpretable results obtained from the SHAP model suggest that motor unit (MU) activation mode may be a key factor affecting sarcopenia.

Dose-effect of exercise intervention on heart rate variability of acclimatized young male lowlanders at 3,680 m.

This study investigated whether exercise could improve the reduced HRV in an environment of high altitude. A total of 97 young, healthy male lowlanders living at 3,680 m for >1 year were recruited. They were randomized into four groups, of which three performed-low-, moderate-, and high-intensity (LI, MI, HI) aerobic exercise for 4 weeks, respectively. The remaining was the control group (CG) receiving no intervention. For HI, compared to other groups, heart rate (p = 0.002) was significantly decreased, while standard deviation of RR intervals (p < 0.001), SD2 of Poincaré plot (p = 0.046) and the number of successive RR interval pairs that differ by > 50 ms divided by total number of RR (p = 0.032), were significantly increased after intervention. For MI, significantly increase of trigonometric interpolation in NN interval (p = 0.016) was observed after exercise. Further, a decrease in systolic blood pressure (SBP) after high-intensity exercise was found significantly associated with an increase in SD2 (r = - 0.428, p = 0.042). These results indicated that there was a dose effect of different intensities of aerobic exercise on the HRV of acclimatized lowlanders. Moderate and high-intensity aerobic exercise would change the status of the autonomic nervous system (ANS) and decrease the blood pressure of acclimatized lowlanders exposed to high altitude.

From Forearm to Wrist: Deep Learning for Surface Electromyography-Based Gesture Recognition.

Though the forearm is the focus of the prostheses, myoelectric control with the electrodes on the wrist is more comfortable for general consumers because of its unobtrusiveness and incorporation with the existing wrist-based wearables. Recently, deep learning methods have gained attention for myoelectric control but their performance is unclear on wrist myoelectric signals. This study compared the gesture recognition performance of myoelectric signals from the wrist and forearm between a state-of-the-art method, TDLDA, and four deep learning models, including convolutional neural network (CNN), temporal convolutional network (TCN), gate recurrent unit (GRU) and Transformer. It was shown that with forearm myoelectric signals, the performance between deep learning models and TDLDA was comparable, but with wrist myoelectric signals, the deep learning models outperformed TDLDA significantly with a difference of at least 9%, while the performance of TDLDA was close between the two signal modalities. This work demonstrated the potential of deep learning for wrist-based myoelectric control and would facilitate its application into more sections.

Variation Minimization Based Electrocardiogram Artifacts Removal for Local Field Potentials From Neurostimulator.

Local field potential (LFP) recorded by sensing-enabled neurostimulators provided chronic observation of deep brain activities for the research of brain disorders. However, the contamination from the electrocardiogram (ECG) deteriorated the extraction of effective information from LFP. This study proposed a novel algorithm based on minimizing the variance combining template subtraction to improve the performance of ECG artifact removal for LFP. Four patients with implanted electrodes were recruited, and eight real LFP records were collected from their left and right hemispheres, respectively. The results showed that the proposed method improved the accuracy of artifact peak detection in LFP, and the subsequent signal quality after template subtraction compared to the traditional Pan-Tompkins (PT) method. The outcome of this study benefited the LFP-based brain research, promoting the application of sensing-enabled neurostimulators in more areas.

Comparison of Wrist and Forearm EMG for Multi-day Biometric Authentication.

Recently, electromyography (EMG) has been established as a promising new biometric trait that provides a unique dual mode security: biometrics and knowledge. For authentication that is used daily and long-term by general consumers, the wrist is a suitable location, which could be easily integrated into the existing form of smartwatches and fitness trackers. However, current EMG-based biometrics still follow the historical path of powered prosthetics research, where EMG signals were usually recorded from forearm positions. Moreover, the robustness of EMG processing algorithms across multiple days is still an open problem that needs to be addressed before for long-term reliable use. This study intends to investigate the difference in authentication performance between wrist and forearm EMG signals, in a within-day and two cross-day analyses. Our open dataset (GRABMyo dataset) was used to examine this difference, which contains forearm and wrist EMG data collected from 43 participants over three different days with long separation (Days 1, 8, and 29). The results showed wrist EMG signals led to at least comparable with forearm EMG signals in within-day Equal-error rate (EER). In cross-day analysis, the EER of the wrist EMG signals was higher than that of forearm signals. In general, the low median EER (<0.1) of wrist EMG in cumulative cross-day analysis demonstrates the promise of using wrist EMG signals for authentication in long-term applications.

Cross-day analysis of Multicode Surface Electromyography based Biometrics for Personal Identification.

Recently, surface electromyography (sEMG) has emerged as a novel biometric trait for personal identification, potentially providing a superior spoof-resistant solution over existing traits. The sEMG possesses a unique dual-mode security: they differ between individuals (biometric-mode), and different gestures have different sEMG characteristics (knowledge-mode). To leverage the knowledge-mode facet of the dual-mode security, the previous studies have utilized a multicode framework involving the fusion of codes (gestures), however, the analysis involved data recorded on a single day and from a small subject-pool. In this study, wrist EMG data collected from 43 participants over three different days while performing static hand/wrist gestures was utilized in two cross-day analyses, where the training and testing data were from different days. Three levels of fusion, score, rank, and decision were investigated to determine the optimal fusion scheme. The results showed that the score-level fusion scheme resulted in a median rank-1 accuracy of 77.9% and rank-5 accuracy of 99.6%, all significantly higher (p<0.001) than the respective single-code gesture. Our results showed that the multicode sEMG biometric framework provides superior identification performance in a more realistic cross-day scenario.

Constructing electrochemical sensor using molecular-imprinted polysaccharide for rapid identification and determination of l-tryptophan in diet.

An imbalance of l-tryptophan (l-Trp), a basic component of a healthy diet, is harmful to human health. Traditional methods for detecting l-Trp have many limitations. To correct a deficiency or excess of l-Trp in human diets, it is necessary to develop a novel method that is rapid, low-cost, and high-sensitivity. Herein, a molecularly imprinted polysaccharide electrochemical sensor termed MIP/CS/MWCNTs/GCE (molecularly imprinted polymer/chitosan/multiwalled carbon nanotubes/glassy carbon electrode) targeting l-Trp was first constructed on a glassy carbon electrode, which was modified with multiwalled carbon nanotubes and chitosan using bifunctional monomers. The MIP/CS/MWCNTs/GCE obtained a wide linear range (1-300 µM) for detecting l-Trp and accurately detected the proportion of l-Trp in mixtures of Trp enantiomers. In milk samples, the spiked recoveries of l-Trp were 86.50 to 99.65%. The MIP/CS/MWCNTs/GCE electrochemical sensor possessed good recognition and detection performance for l-Trp and has promising potential for practical application.

Fracability Evaluation Method of a Fractured-Vuggy Carbonate Reservoir in the Shunbei Block.

The fracability of carbonate reservoirs is a key indicator for evaluating whether reservoirs can be effectively fractured. Taking the fractured-vuggy carbonate reservoir in the Shunbei block as an example, the microscopic characteristics and mechanical properties of this reservoir were analyzed. The test results showed that the core microstructure is relatively dense, the micropores and microfractures are developed, and the mineral composition is characterized by "high carbonate and few impurities". The compressive strength, Young's modulus, and Poisson's ratio of the rock increased with the increase in the confining pressure. Poisson's ratio is more sensitive to confining pressure than Young's modulus and shows the ductile transformation tendency from a low confining pressure to a high confining pressure. Considering the difficulty of forming a complex fracture network, we put forward a "fracture propagation factor" equation constructed with five main factors, including brittleness, fracture toughness, natural fracture, hole size, and horizontal stress difference, and then the fracture propagation factor of Yijianfang formation is calculated to be greater than 0.5. It is known that the Yijianfang formation has higher fracability. On this basis, combined with the construction parameters, a model for evaluating the fracability of a fractured-vuggy carbonate reservoir was established. The comprehensive fracability of four wells in the Shunbei block was calculated by the model. From the calculation results, the comprehensive fracability index of SHB43X was 0.5406 and greater than that of the other three wells, which has a high correlation with the production after fracturing.

Lactiplantibacillus plantarum NKK20 Alleviates High-Fat-Diet-Induced Nonalcoholic Fatty Liver Disease in Mice through Regulating Bile Acid Anabolism.

Nonalcoholic fatty liver disease (NAFLD) is the most prevalent chronic disease in modern society. It is characterized by an accumulation of lipids in the liver and an excessive inflammatory response. Clinical trials have provided evidence that probiotics may prevent the onset and relapse of NAFLD. The aim of this study was to explore the effect of Lactiplantibacillus plantarum NKK20 strain (NKK20) on high-fat-diet-induced NAFLD in an ICR murine model and propose the underlying mechanism whereby NKK20 protects against NAFLD. The results showed that the administration of NKK20 ameliorated hepatocyte fatty degeneration, reduced total cholesterol and triglyceride concentrations, and alleviated inflammatory reactions in NAFLD mice. In addition, the 16S rRNA sequencing results indicated that NKK20 could decrease the abundance of Pseudomonas and Turicibacter and increase the abundance of Akkermansia in NAFLD mice. LC-MS/MS analysis showed that NKK20 could significantly increase the concentration of short-chain fatty acids (SCFAs) in the colon contents of mice. The obtained non-targeted metabolomics results revealed a significant difference between the metabolites in the colon contents of the NKK20 administration group and those in the high-fat diet group, in which a total of 11 different metabolites that were significantly affected by NKK20 were observed, and these metabolites were mainly involved in bile acid anabolism. UPLC-MS technical analysis revealed that NKK20 could change the concentrations of six conjugated and free bile acids in mouse liver. After being treated with NKK20, the concentrations of cholic acid, glycinocholic acid, and glycinodeoxycholic acid in livers of the NAFLD mice were significantly decreased, while the concentration of aminodeoxycholic acid was significantly increased. Thus, our findings indicate that NKK20 can regulate bile acid anabolism and promote the production of SCFA, which can inhibit inflammation and liver damage and thus prevent the development of NAFLD.

Bio-robotics research for non-invasive myoelectric neural interfaces for upper-limb prosthetic control: a 10-year perspective review.

A decade ago, a group of researchers from academia and industry identified a dichotomy between the industrial and academic state-of-the-art in upper-limb prosthesis control, a widely used bio-robotics application. They proposed that four key technical challenges, if addressed, could bridge this gap and translate academic research into clinically and commercially viable products. These challenges are unintuitive control schemes, lack of sensory feedback, poor robustness and single sensor modality. Here, we provide a perspective review on the research effort that occurred in the last decade, aiming at addressing these challenges. In addition, we discuss three research areas essential to the recent development in upper-limb prosthetic control research but were not envisioned in the review 10 years ago: deep learning methods, surface electromyogram decomposition and open-source databases. To conclude the review, we provide an outlook into the near future of the research and development in upper-limb prosthetic control and beyond.

The instant effect of embodiment via mirror visual feedback on electroencephalogram-based brain connectivity changes: A pilot study.

The therapeutic efficacy of mirror visual feedback (MVF) is attributed to the perception of embodiment. This study intends to investigate the instantaneous effect of embodiment on brain connectivity. Twelve healthy subjects were required to clench and open their non-dominant hands and keep the dominant hands still during two experimental sessions. In the first session, the dominant hand was covered and no MVF was applied, named the sham-MVF condition. Random vibrotactile stimulations were applied to the non-dominant hand with MVF in the subsequent session. Subjects were asked to pedal while having embodiment perception during motor tasks. As suggested by previous findings, trials of no vibration and continuous vibration were selected for this study, named the condition of MVF and vt-MVF. EEG signals were recorded and the alterations in brain connectivity were analyzed. The average node degrees of sham-MVF, MVF, and vt-MVF conditions were largely different in the alpha band (9.94, 11.19, and 17.37, respectively). Further analyses showed the MVF and vt-MVF had more nodes with a significantly large degree, which mainly occurred in the central and the visual stream involved regions. Results of network metrics showed a significant increment of local and global efficiency, and a reduction of characteristic path length for the vt-MVF condition in the alpha and beta bands compared to sham-MVF, and in the alpha band compared to MVF. Similar trends were found for MVF condition in the beta band compared to sham-MVF. Moreover, significant leftward asymmetry of global efficiency and rightward asymmetry of characteristic path length was reported in the vt-MVF condition in the beta band. These results indicated a positive impact of embodiment on network connectivity and neural communication efficiency, which reflected the potential mechanisms of MVF for new insight into neural modulation.

Berberine-Based Carbon Quantum Dots Improve Intestinal Barrier Injury and Alleviate Oxidative Stress in C57BL/6 Mice with 5-Fluorouracil-Induced Intestinal Mucositis by Enhancing Gut-Derived Short-Chain Fatty Acids Contents.

This study aims to evaluate the effect of berberine-based carbon quantum dots (Ber-CDs) on improving 5-fluorouracil (5-FU)-induced intestinal mucositis in C57BL/6 mice, and explored the mechanisms behind this effect. Thirty-two C57BL/6 mice were divided into four groups: normal control (NC), 5-FU-induced intestinal mucositis model (5-FU), 5-FU + Ber-CDs intervention (Ber-CDs), and 5-FU + native berberine intervention (Con-CDs). The Ber-CDs improved body weight loss in 5-FU-induced mice with intestinal mucositis compared to the 5-FU group. The expressions of IL-1ß and NLRP3 in spleen and serum in Ber-CDs and Con-Ber groups were significantly lower than those in the 5-FU group, and the decrease was more significant in the Ber-CDs group. The expressions of IgA and IL-10 in the Ber-CDs and Con-Ber groups were higher than those in the 5-FU group, but the up-regulation was more significant in the Ber-CDs group. Compared with the 5-FU group, the relative contents of Bifidobacterium, Lactobacillus and the three main SCFAs in the colon contents were significantly increased the Ber-CDs and Con-Ber groups. Compared with the Con-Ber group, the concentrations of the three main short-chain fatty acids in the Ber-CDs group were significantly increased. The expressions of Occludin and ZO-1 in intestinal mucosa in the Ber-CDs and Con-Ber groups were higher than those in the 5-FU group, and the expressions of Occludin and ZO-1 in the Ber-CDs group were more higher than that in the Con-Ber group. In addition, compared with the 5-FU group, the damage of intestinal mucosa tissue in the Ber-CDs and Con-Ber groups were recovered. In conclusion, berberine can attenuate intestinal barrier injury and oxidative stress in mice to mitigate 5-fluorouracil-induced intestinal mucositis, moreover, the above effects of Ber-CDs were more significant than those of native berberine. These results suggest that Ber-CDs may be a highly effective substitute for natural berberine.

Specific capture and determination of glycoprotein using a hybrid epitopes and monomers-mediated molecular-imprinted polymer enzyme-free electrochemical biosensor.

A novel molecular-imprinted polymer (MIP)-based enzyme-free biosensor was created for the selective detection of glycoprotein transferrin (Trf). For this purpose, MIP-based biosensor for Trf was prepared by electrochemical co-polymerization of novel hybrid monomers 3-aminophenylboronic acid (M-APBA) and pyrrole on a glassy carbon electrode (GCE) modified with carboxylated multi-walled carbon nanotubes (cMWCNTs). Hybrid epitopes of Trf (C-terminal fragment and glycan) have been selected as templates. The produced sensor exhibited great selective recognition ability toward Trf under optimal preparation conditions, offering good analytical range (0.125-1.25 µM) with a detection limit of 0.024 µM. The proposed hybrid epitope in combination with hybrid monomer-mediated imprinting strategy was successfully applied to detect Trf in spiked human serum samples, with recoveries and relative standard deviations ranging from 94.7 to 106.0% and 2.64 to 5.32%, respectively. This study provided a reliable protocol for preparing hybrid epitopes and monomers-mediated MIP for the synergistic and effective determination of glycoprotein in complicated biological samples.

Sodium Butyrate Attenuates AGEs-Induced Oxidative Stress and Inflammation by Inhibiting Autophagy and Affecting Cellular Metabolism in THP-1 Cells.

In recent years, sodium butyrate has gained increased attention for its numerous beneficial properties. However, whether sodium butyrate could alleviate inflammatory damage by macrophage activation and its underlying mechanism remains unclear. The present study used an advanced glycosylation products- (AGEs-) induced inflammatory damage model to study whether sodium butyrate could alleviate oxidative stress, inflammation, and metabolic dysfunction of human monocyte-macrophage originated THP-1 cells in a PI3K-dependent autophagy pathway. The results indicated that sodium butyrate alleviated the AGEs-induced oxidative stress, decreased the level of reactive oxygen species (ROS), increased malondialdehyde (MDA) and mRNA expression of pro-inflammatory cytokines of interleukin (IL)-1ß and tumor necrosis factor (TNF)-α, and increased the content of superoxide dismutase (SOD). Sodium butyrate reduced the protein expression of the NLR family, pyrin domain-containing protein 3 (NLRP3) and Caspase-1, and decreased the nucleus expression of nuclear factor-kappaB (NF-κB). Sodium butyrate decreased the expression of light-chain-associated protein B (LC3B) and Beclin-1, and inhibited autophagy. Moreover, sodium butyrate inhibited the activation of the PI3K/Akt pathway in AGEs-induced THP-1 cells. In addition, the metabolomics analysis showed that sodium butyrate could affect the production of phosphatidylcholine, L-glutamic acid, UDP-N-acetylmuraminate, biotinyl-5'-AMP, and other metabolites. In summary, these results revealed that sodium butyrate inhibited autophagy and NLRP3 inflammasome activation by blocking the PI3K/Akt/NF-κB pathway, thereby alleviating oxidative stress, inflammation, and metabolic disorder induced by AGEs.

Multi-day dataset of forearm and wrist electromyogram for hand gesture recognition and biometrics.

Surface electromyography (sEMG) signals have been used for advanced prosthetics control, hand-gesture recognition (HGR), and more recently as a novel biometric trait. For these sEMG-based applications, the translation from laboratory research setting to real-life scenarios suffers from two major limitations: (1) a small subject pool, and (2) single-session data recordings, both of which prevents acceptable generalization ability. In this longitudinal database, forearm and wrist sEMG data were collected from 43 participants over three different days with long separation (Days 1, 8, and 29) while they performed static hand/wrist gestures. The objective of this dataset is to provide a comprehensive dataset for the development of robust machine learning algorithms of sEMG, for both HGR and biometric applications. We demonstrated the high quality of the current dataset by comparing with the Ninapro dataset. And we presented its usability for both HGR and biometric applications. Among other applications, the dataset can also be used for developing electrode-shift invariant generalized models, which can further bolster the development of wristband and forearm-bracelet sensors.

Swelling of Multilayered Calcium Alginate Microspheres for Drug-Loaded Dressing Induced Rapid Lidocaine Release for Better Pain Control.

The development of effective drug-loaded dressings has been considered a hot research topic for biomedical therapeutics, including the use of botanical compounds. For wound healing, adequate dressings can provide a good microenvironment for drug release, such as lidocaine. Biological macromolecular materials such as alginate show excellent properties in wound management. This study involves the preparation and evaluation of biocompatible multilayered-structure microspheres composed of chitosan, porous gelatin, and calcium alginate microspheres. The multilayered structure microspheres were named chitosan@ porous gelatin@ calcium alginate microspheres (CPAMs) and the drugs were rapidly released by the volume expansion of the calcium alginate microspheres. The in vitro release curve revealed that the peak release of lidocaine from CPAMs was reached within 18[Formula: see text]min. After 21[Formula: see text]min, the remaining lidocaine was then slowly released, and the active drug release was converted to a passive drug release phase. The initial release effect of lidocaine was much better than that reported in the published studies. Additionally, blood coagulation experiments showed that CPAMs coagulated blood in 60[Formula: see text]s, and the blood liquidity of the CPAMs group was worse than that of the woundplast group. Therefore, the coagulation characteristics of CPAMs were superior to the commonly used woundplast containing lidocaine healing gel. These study outcomes indicated that the CPAMs acted as fast-release dressings for faster pain control and better coagulation properties.

Molecular Insights into the Effect of Nitrogen Bubbles on the Formation of Tetrahydrofuran Hydrates.

In this work, a molecular dynamics simulation was conducted to study the microscopic mechanism of how nitrogen bubbles affect the formation of THF hydrates at the molecular level. The results obtained reveal that the nitrogen bubble can promote the formation of THF hydrates. In the system with a nitrogen bubble, more THF-filled cages were generated, and the crystal structure was more orderly. The promotion of nitrogen bubbles on hydrate crystallization comes from the dissolution of nitrogen molecules. Some of dissolved nitrogen molecules can be enclosed in small hydrate cages near the nitrogen bubble, which can serve as stable sites for hydrate crystal growth, resulting in the fact that THF-filled cages connected with N2-filled cages are much more stable and have a long lifetime. The results in this work can help to understand the promotion effect of micro- and nano-air bubbles on the crystallization of THF hydrates.

An edible molecularly imprinted material prepared by a new environmentally friendly deep eutectic solvent for removing oxalic acid from vegetables and human blood.

A novel deep eutectic solvent-magnetic molecularly imprinted polymer (DES-MMIP) for the specific removal of oxalic acid (OA) was prepared by an environmentally friendly deep eutectic solvent, consisting of betaine, citric acid, and glycerol, which acted as the functional monomer for polymerization. The structure and morphology of DES-MMIPs were studied by X-ray diffraction, scanning and transmission electron microscopy, thermal gravimetric analysis, Fourier transform infrared spectroscopy, and vibrating sample magnetometer. DES-MMIPs had a core-shell structure, with magnetic iron oxide as the core, and showed good thermal stability and high adsorption capacity (18.73 mg/g) for OA. The adsorption process of OA by DES-MMIPs followed the pseudo-second-order kinetic model and Langmuir isotherm model. DES-MMIPs had significant selectivity for OA and their imprinting factor was 3.26. When applied to real samples, high performance liquid chromatography analysis showed that DES-MMIPs could remove OA from both spinach and blood serum. These findings provide potential methods for removal of OA from vegetables and for specific removal of OA in renal dialysis.

Reactive molecular dynamics simulations on thermal decomposition of 3-methyl-2,6-dinitrophenol.

In this paper, we simulated the decomposition mechanism of 3-methyl-2,6-dinitrophenol (MDNP) based on reaction molecular dynamics using ReaxFF force field. In addition, the evolution of some main products over time at different heating rates (10, 15, and 20 K·ps-1) was studied. As indicated by the simulation results, with the elevation at different heating rates, the time required for the system to reach equilibrium was shortened, and more products were obtained. At three heating rates, C7H7O5N2, C7H6O4N2, C7H5O5N2, C7H5O4N2, HON, NO, and NO2 were the main intermediate products, and N2, CO2, H2O, H2, and NH3 were the primary final products. To be specific, C7H5O5N2 was the first produced intermediate product, and H2O was the first produced final product with the largest abundance. The intermediate products first increased and then decreased to zero. Moreover, the primary chemistry reactions in the MDNP pyrolysis were simulated through ReaxFF MD simulations.