Bagasse cellulose grafted with an amino-terminated hyperbranched polymer for the removal of Cr(VI) from aqueous solution

A novel bio-adsorbent was fabricated via grafting an amino-terminated hyperbranched polymer (HBP-NH2) onto bagasse cellulose. The morphology and microstructure of the HBP-NH2-grafted bagasse cellulose (HBP-g-BC) were characterized and its adsorption capacity for Cr(VI) ions in aqueous solutions was investigated. The rough surface structure of HBP-g-BC that is beneficial for improving the adsorption capacity was observed by scanning electron microscopy (SEM). The grafting reaction was confirmed by Fourier-transform infrared (FT-IR) spectroscopy. The adsorbent performance was shown to be better with a lower pH value, a higher adsorbent dosage, or a higher initial Cr(VI) concentration. Moreover, the kinetics study revealed that the adsorption behavior followed a pseudo-second-order model. The isotherm results showed that the adsorption data could be well-fitted by the Langmuir, Freundlich, or Temkin models. Moreover, HBP-g-BC could maintain 74.4% of the initial removal rate even after five cycles of regeneration. Thus, the high potential of HBP-g-BC as a bio-adsorbent for heavy metal removal has been demonstrated. View Full-Tex

Mechanism of Wenyang Shengji Ointment in treating diabetic wounds based on network pharmacology and animal experiments

Objective: To explore the mechanism of Wenyang Shengji Ointment (温阳生肌膏, WYSJO) in the treatment of diabetic wounds from the perspective of network pharmacology, and to verify it by animal experiments. Methods: The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and related literature were used to screen active compounds in WYSJO and their corresponding targets. GeneCards, Online Mendelian Inheritance in Man (OMIM), DrugBank, PharmGkb, and Therapeutic Target Database (TTD) databases were employed to identify the targets associated with diabetic wounds. Cytoscape 3.9.0 was used to map the active ingredients in WYSJO, which was the diabetic wound target network. Search Tool for the Retrieval of Interaction Gene/Proteins (STRING) platform was utilized to construct protein-protein interaction (PPI) network. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed to identify signaling pathways between WYSJO and diabetic wounds. AutoDock 1.5.6 was used for molecular docking of core components in WYSJO to their targets. Eighteen rats were randomly divided into control, model, and WYSJO groups (n = 6). The model and WYSJO groups were used to prepare the model of refractory wounds in diabetes rats. The wound healing was observed on day 0, 5, 9, and 14 after treatment, and the wound tissue morphology was observed by hematoxylin-eosin (HE) staining. The expression levels of core genes were detected by quantitative real-time polymerase chain reaction (qPCR). Results: A total of 76 active compounds in WYSJO, 206 WYSJO drug targets, 3 797 diabetic wound targets, and 167 diabetic wound associated WYSJO targets were screened out through network pharmacology. With the use of WYSJO-diabetic wound target network, core targets of seven active compounds encompassing quercetin, daidzein, kaempferol, rhamnetin, rhamnocitrin, strictosamide, and diisobutyl phthalate (DIBP) in WYSJO were found. GO enrichment analysis showed that the treatment of diabetes wounds with WYSJO may involve lipopolysaccharide, bacteria-derived molecules, metal ions, foreign stimuli, chemical stress, nutrient level, hypoxia, and oxidative stress in the biological processes. KEGG enrichment analysis showed that the treatment of diabetes wounds with WYSJO may involve advanced glycation end products (AGE-RAGE), p53, interleukin (IL)-17, tumor necrosis factor (TNF), hypoxia inducible factor-1 (HIF-1), apoptosis, lipid, atherosclerosis, etc. The results of animal experiments showed that WYSJO could significantly accelerate the healing process of diabetic wounds (P < 0.05), alleviate inflammatory response, promote the growth of granulation tissues, and down-regulate the expression levels of eight core genes [histone crotonyltransferase p300 (EP300), protoc gene-oncogene c-Jun (JUN), myelocytomatosis (MYC), hypoxia inducible factor 1A (HIF1A), mitogen-activated protein kinase 14 (MAPK14), specificity protein 1 (SP1), tumor protein p53 (TP53), and estrogen receptor 1 (ESR1)] predicted by the network pharmacology (P < 0.05). Conclusion: The mechanism of WYSJO in treating diabetes wounds may be closely related to AGE-RAGE, p53, HIF-1, and other pathways. This study can provide new ideas for the pharmacological research of WYSJO, and provide a basis for its further transformation and application

Study of the influence of meteorological factors on HFMD and prediction based on the LSTM algorithm in Fuzhou, China

Abstract Background This study adopted complete meteorological indicators, including eight items, to explore their impact on hand, foot, and mouth disease (HFMD) in Fuzhou, and predict the incidence of HFMD through the long short-term memory (LSTM) neural network algorithm of artificial intelligence. Method A distributed lag nonlinear model (DLNM) was used to analyse the influence of meteorological factors on HFMD in Fuzhou from 2010 to 2021. Then, the numbers of HFMD cases in 2019, 2020 and 2021 were predicted using the LSTM model through multifactor single-step and multistep rolling methods. The root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and symmetric mean absolute percentage error (SMAPE) were used to evaluate the accuracy of the model predictions. Results Overall, the effect of daily precipitation on HFMD was not significant. Low (4 hPa) and high (≥ 21 hPa) daily air pressure difference (PRSD) and low ( 12 °C) daily air temperature difference (TEMD) were risk factors for HFMD. The RMSE, MAE, MAPE and SMAPE of using the weekly multifactor data to predict the cases of HFMD on the following day, from 2019 to 2021, were lower than those of using the daily multifactor data to predict the cases of HFMD on the following day. In particular, the RMSE, MAE, MAPE and SMAPE of using weekly multifactor data to predict the following week's daily average cases of HFMD were much lower, and similar results were also found in urban and rural areas, which indicating that this approach was more accurate. Conclusion This study’s LSTM models combined with meteorological factors (excluding PRE) can be used to accurately predict HFMD in Fuzhou, especially the method of predicting the daily average cases of HFMD in the following week using weekly multifactor data

Design of a Flexible Wearable Smart sEMG Recorder Integrated Gradient Boosting Decision Tree Based Hand Gesture Recognition

This paper proposed a wearable smart sEMG recorder integrated gradient boosting decision tree (GBDT) based hand gesture recognition. A hydrogel-silica gel based flexible surface electrode band is used as the tissue interface. The sEMG signal is collected using a neural signal acquisition analog front end (AFE) chip. A quantitative analysis method is proposed to balance the algorithm complexity and recognition accuracy. A parallel GBDT implementation is proposed featuring a low latency. The proposed GBDT based neural signal processing unit (NSPU) is implemented on an FPGA near the AFE. A RF module is used for wireless communication. A hand gesture set including 12 gestures is designed for human-computer interaction. Experimental results show an overall hand gesture recognition accuracy of 91

High-Efficiency Lithium-Ion Transport in a Porous Coordination Chain-Based Hydrogen-Bonded Framework

Fast and selective Li+ transport in solid plays a key role for the development of high-performance solid-state electrolytes (SSEs) of lithium metal batteries. Porous compounds with tunable Li+ transport pathways are promising SSEs, but the comprehensive performances in terms of Li+ transport kinetics, electrochemical stability window, and interfacial compatibility are difficult to be achieved simultaneously. Herein, we report a porous coordination chain-based hydrogen-bonded framework (NKU-1000) containing arrayed electronegative sites for Li+ transport, exhibiting a superior Li+ conductivity of 1.13 × 10–3 S cm–1, a high Li+ transfer number of 0.87, and a wide electrochemical window of 5.0 V. The assembled solid-state battery with NKU-1000-based SSE shows a high discharge capacity with 94.4% retention after 500 cycles and can work over a wide temperature range without formation of lithium dendrites, which derives from the linear hopping sites that promote a uniformly high-rate Li+ flux and the flexible structure that can buffer the structural variation during Li+ transport