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The impact of water quality on the formation of halogenated benzoquinones and the adsorption efficiency by activated carbon

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Journal of Environmental Sciences 2024年第1期135卷 693-702页

作者： Yongjing Wang song Gao Xinyu yan songtao Wang Ruolin zhang yan Zhou Lianhai Ren Cheng Li State Environmental Protection Key Laboratory of Food Chain Pollution Control Beijing Technology and Business UniversityBeijing 100048China Institute of Scientific and Technical Information of China Beijing 100038China Institute of Quality Standard and Testing Technology Beijing Academy of Agriculture and Forestry SciencesBeijing 100097China Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry Beijing Technology and Business UniversityBeijing 100048China

Halogenated benzoquinones(HBQs)could cause bladder cancer,but there were few related studies on the generation and control.In this study,the impact of different precursors,pH,bromide concentration,and algae-derived organic matters on the formation of HBQs and the removal efficiency by activated carbon were investigated.It was found that the chlorination of bisphenol A produced the most 2,6-dichloro-1,4-benzoquinone(2,6-DCBQ),reaching 14.86μg/L at 1 hr,followed by tyrosine,2-chlorophenol,P-hydroxybenzoic acid,trichlorophenol,and N-methylaniline.The production of 2,6-DCBQ increased first and then decreased from 0 to 36 hr(chlorination doses 0-20 mg/L),indicating that HBQs were unstable in water.Trihalomethanes(THMs)were detected during chlorination,and the concentration increased with prolongation of reaction time.2,6-DCBQ production decreased and 2,6-dibromo-1,4-benzoquinone(2,6-DBBQ)production increased with increment bromide concentration and the bromide promoted the formation of tribromomethane.The production of 2,6-DCBQ decreased with increase of pH,and the maximum production was 141.38μg/L at pH of 5.Microcystis aeruginosa,Chlorella algae cells,and intracellular organic matters(IOM)could be chlorinated as potential precursors for HBQs.The most amount of 2,6-DCBQ was generated from algae cells of Microcystis aeruginosa,followed by Chlorella algae cells,Microcystis aeruginosa IOM,and Chlorella IOM.This study compared the removal efficiency of HBQs by granular activated carbon(GAC)and columnar activated carbon(CAC)under different carbon doses and initial concentrations of HBQs.It was found that the removal efficiency by GAC(80.1%)was higher than that by CAC(51.8%),indicating that GAC has better control for HBQs.

关键词： HBQS DBPS Drinking water Algae derived organic matters Activated carbon

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Deep neural network based on multi-level wavelet and attention for structured illumination microscopy

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Journal of Innovative Optical Health Sciences 2024年第2期17卷 12-23页

作者： yanwei zhang song Lang Xuan Cao Hanqing Zheng yan Gong School of Biomedical Engineering(Suzhou)Division of Life Sciencesand Medicine University of Science and Technology of China Hefei Anhui230026P.R.China Suzhou Institute of Biomedical Engineering and Technology Chinese Academy of Sciences Suzhou Jiangsu 215163P.R.China School of Physical Science and Technology Suzhou University of Science and Technology Suzhou Jiangsu 215009P.R.China

Structured illumination microscopy(SIM)is a popular and powerful super-resolution(SR)technique in biomedical research.However,the conventional reconstruction algorithm for SIM heavily relies on the accurate prior knowledge of illumination patterns and signal-to-noise ratio(SNR)of raw images.To obtain high-quality SR images,several raw images need to be captured under high fluorescence level,which further restricts SIM’s temporal resolution and its applications.Deep learning(DL)is a data-driven technology that has been used to expand the limits of optical microscopy.In this study,we propose a deep neural network based on multi-level wavelet and attention mechanism(MWAM)for SIM.Our results show that the MWAM network can extract high-frequency information contained in SIM raw images and accurately integrate it into the output image,resulting in superior SR images compared to those generated using wide-field images as input data.We also demonstrate that the number of SIM raw images can be reduced to three,with one image in each illumination orientation,to achieve the optimal tradeoff between temporal and spatial resolution.Furthermore,our MWAM network exhibits superior reconstruction ability on low-SNR images compared to conventional SIM algorithms.We have also analyzed the adaptability of this network on other biological samples and successfully applied the pretrained model to other SIM systems.

关键词： Super-resolution reconstruction multi-level wavelet packet transform residual channel attention selective kernel attention

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Chinese Medicine Combined with Adjuvant Chemotherapy for Improving Myelosuppression in Colorectal Cancer Patients: A Systematic Review and Network Meta-Analysis

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Chinese Journal of Integrative Medicine 2024年第7期30卷 643-652页

作者： LI Rui zhang Tong yan Shao-hua yan Yun-zi DING Ya-cong WANG yan-song yanG Yu-fei Department of Oncology China Academy of Chinese Medical Sciences Xiyuan Hospital Department of Oncology Dongfang Hospital Beijing University of Chinese Medicine Graduate School Beijing University of Chinese Medicine

Objective: To assess the effectiveness of Chinese herbal medicine(CHM) combined with adjuvant chemotherapy on myelosuppression for colorectal cancer(CRC) patients using network meta-analysis(NMA). Methods: Literature searches in both international(PubMed, Embase, Web of Science, and Cochrane Library) and Chinese(China Science and Technology Journal Database, Wanfang Data, China National Knowledge Infrastructure) databases for relevant randomized controlled trials(RCTs) were conducted from inception until October 10, 2022. We included RCTs of patients who received CHM combined with chemotherapy, including FOLFOX, XELOX, FOLFIRI, and other relevant regimens in the CHM treatment group. The outcomes included the incidence of myelosuppression, leukopenia, hemoglobin reduction, and thrombocytopenia. Two reviewers independently screened the databases, extracted the data, and assessed the risk of bias and credibility of evidence. RevMan 5.4.1 software and STATA 14.0 were used to perform the NMA. Results: A total of 31 RCTs were included, published from 2008 to 2021 in Chinese. Among these, 2,314 participants comparing the following 9 CHMs were identified: Shengbai Recipe(SBR), Bazhen Decoction(BZD), Jianpi Jiedu Recipe(JJR), Jianpi Recipe(JR), Compound Cantharis Capsule(CCC), Zaofan Pill(ZFP), Guilu Erxian Gel(GL), Buzhong Tiaogan Decoction(BZ), and Qiamagu Capsule(QM). The results of NMA found an indirect comparison. Based on the surface under the cumulative ranking curve(SUCRA), the ZFP+ chemotherapy group had the lowest incidence of myelosuppression, with an odds ratio(OR) of 0.08 [95% confidence interval(CI): 0.01, 0.76], whereas the GL+ chemotherapy group had the lowest incidence of leukopenia, hemoglobin reduction, and thrombocytopenia, with an OR of 5.25(95% CI: 2.41, 11.43), 4.66(95% CI: 2.23, 9.72), and 0.27(95% CI: 0.13, 0.54), respectively. Moreover, BZD + chemotherapy could alleviate leukopenia, hemoglobin reduction, and thrombocytopenia(P<0.01). Pairwise comparison showed that there was no difference in the

关键词： Chinese herbal medicine colorectal cancer network meta-analysis systematic review myelosuppression chemotherapy

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A novel mechanism of PHB2-mediated mitophagy participating in the development of Parkinson's disease

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Neural Regeneration Research 2024年第8期19卷 1828-1834页

作者： Yongjiang zhang Shiyi Yin Run song Xiaoyi Lai Mengmeng Shen Jiannan Wu Junqiang yan Key Laboratory of Neuromolecular Biology The First Affiliated HospitalCollege of Clinical Medicine of Henan University of Science and TechnologyLuoyangHenan ProvinceChina Department of Neurology The First Affiliated HospitalCollege of Clinical Medicine of Henan University of Science and TechnologyLuoyangHenan ProvinceChina

Endoplasmic reticulum stress and mitochondrial dysfunction play important roles in Parkinson s disease,but the regulato ry mechanism remains elusive.Prohibitin-2(PHB2)is a newly discove red autophagy receptor in the mitochondrial inner membrane,and its role in Parkinson’s disease remains unclear.Protein kinase R(PKR)-like endoplasmic reticulum kinase(PERK)is a factor that regulates cell fate during endoplasmic reticulum stress.Parkin is regulated by PERK and is a target of the unfolded protein response.It is unclear whether PERK regulates PHB2-mediated mitophagy thro ugh Parkin.In this study,we established a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine(MPTP)-induced mouse model of Parkinson’s disease.We used adeno-associated virus to knockdown PHB2 expression.Our res ults showed that loss of dopaminergic neurons and motor deficits were aggravated in the MPTP-induced mouse model of Parkinson’s disease.Ove rexpression of PHB2 inhibited these abnormalities.We also established a 1-methyl-4-phenylpyridine(MPP+)-induced SH-SY5Y cell model of Parkinson’s disease.We found that ove rexpression of Parkin increased co-localization of PHB2 and microtubule-associated protein 1 light chain 3,and promoted mitophagy.In addition,MPP+regulated Parkin involvement in PHB2-mediated mitophagy through phosphorylation of PERK.These findings suggest that PHB2 participates in the development of Parkinson’s disease by intera cting with endoplasmic reticulum stress and Parkin.

关键词： endoplasmic reticulum dopaminergic neuron microtubule-associated protein 1 light chain 3 mitophagy oxidative stress Parkin Parkinson’s disease PKR-like endoplasmic reticulum kinase reactive oxygen species prohibitin-2

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Network Intrusion Traffic Detection Based on Feature Extraction

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Computers, Materials & Continua 2024年第1期78卷 473-492页

作者： Xuecheng Yu yan Huang Yu zhang Mingyang song Zhenhong Jia College of Information Science and Engineering Xinjiang UniversityUrumqi830046China Network Department China Mobile Communications Group Xinjiang CoLtd.UrumqiUrumqi830011China Xinjiang Signal Detection and Processing Key Laboratory Xinjiang UniversityUrumqi830000China

With the increasing dimensionality of network traffic,extracting effective traffic features and improving the identification accuracy of different intrusion traffic have become critical in intrusion detection systems(IDS).However,both unsupervised and semisupervised anomalous traffic detection methods suffer from the drawback of ignoring potential correlations between features,resulting in an analysis that is not an optimal set.Therefore,in order to extract more representative traffic features as well as to improve the accuracy of traffic identification,this paper proposes a feature dimensionality reduction method combining principal component analysis and Hotelling’s T^(2) and a multilayer convolutional bidirectional long short-term memory(MSC_BiLSTM)classifier model for network traffic intrusion detection.This method reduces the parameters and redundancy of the model by feature extraction and extracts the dependent features between the data by a bidirectional long short-term memory(BiLSTM)network,which fully considers the influence between the before and after features.The network traffic is first characteristically downscaled by principal component analysis(PCA),and then the downscaled principal components are used as input to Hotelling’s T^(2) to compare the differences between groups.For datasets with outliers,Hotelling’s T^(2) can help identify the groups where the outliers are located and quantitatively measure the extent of the outliers.Finally,a multilayer convolutional neural network and a BiLSTM network are used to extract the spatial and temporal features of network traffic data.The empirical consequences exhibit that the suggested approach in this manuscript attains superior outcomes in precision,recall and F1-score juxtaposed with the prevailing techniques.The results show that the intrusion detection accuracy,precision,and F1-score of the proposed MSC_BiLSTM model for the CIC-IDS 2017 dataset are 98.71%,95.97%,and 90.22%.

关键词： Network intrusion traffic detection PCA Hotelling’s T^(2) BiLSTM

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Missing Value Imputation for Radar-Derived Time-Series Tracks of Aerial Targets Based on Improved Self-Attention-Based Network

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Computers, Materials & Continua 2024年第3期78卷 3349-3376页

作者： Zihao song yan Zhou Wei Cheng Futai Liang Chenhao zhang Department of Early Warning Intelligence Early Warning AcademyWuhan430019China

The frequent missing values in radar-derived time-series tracks of aerial targets(RTT-AT)lead to significant challenges in subsequent data-driven tasks.However,the majority of imputation research focuses on random missing(RM)that differs significantly from common missing patterns of RTT-AT.The method for solving the RM may experience performance degradation or failure when applied to RTT-AT imputation.Conventional autoregressive deep learning methods are prone to error accumulation and long-term dependency loss.In this paper,a non-autoregressive imputation model that addresses the issue of missing value imputation for two common missing patterns in RTT-AT is proposed.Our model consists of two probabilistic sparse diagonal masking self-attention(PSDMSA)units and a weight fusion unit.It learns missing values by combining the representations outputted by the two units,aiming to minimize the difference between the missing values and their actual values.The PSDMSA units effectively capture temporal dependencies and attribute correlations between time steps,improving imputation quality.The weight fusion unit automatically updates the weights of the output representations from the two units to obtain a more accurate final representation.The experimental results indicate that,despite varying missing rates in the two missing patterns,our model consistently outperforms other methods in imputation performance and exhibits a low frequency of deviations in estimates for specific missing entries.Compared to the state-of-the-art autoregressive deep learning imputation model Bidirectional Recurrent Imputation for Time Series(BRITS),our proposed model reduces mean absolute error(MAE)by 31%~50%.Additionally,the model attains a training speed that is 4 to 8 times faster when compared to both BRITS and a standard Transformer model when trained on the same dataset.Finally,the findings from the ablation experiments demonstrate that the PSDMSA,the weight fusion unit,cascade network design,and imputation loss enhance imputation performa

关键词： Missing value imputation time-series tracks probabilistic sparsity diagonal masking self-attention weight fusion

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Research on high energy efficiency and low bit-width floating-point type data for abnormal object detection of transmission lines

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Global Energy Interconnection 2024年第3期7卷 324-335页

作者： Chen Wang Guozheng Peng Rui song Jun zhang Li yan China Electric Power Research Institute Beijing 100192P.R.China Information&Telecommunications Company State Grid Shandong Electric Power CompanyJinan 250001P.R.China

Achieving a balance between accuracy and efficiency in target detection applications is an important research topic.To detect abnormal targets on power transmission lines at the power edge,this paper proposes an effective method for reducing the data bit width of the network for floating-point quantization.By performing exponent prealignment and mantissa shifting operations,this method avoids the frequent alignment operations of standard floating-point data,thereby further reducing the exponent and mantissa bit width input into the training process.This enables training low-data-bit width models with low hardware-resource consumption while maintaining accuracy.Experimental tests were conducted on a dataset of real-world images of abnormal targets on transmission lines.The results indicate that while maintaining accuracy at a basic level,the proposed method can significantly reduce the data bit width compared with single-precision data.This suggests that the proposed method has a marked ability to enhance the real-time detection of abnormal targets in transmission circuits.Furthermore,a qualitative analysis indicated that the proposed quantization method is particularly suitable for hardware architectures that integrate storage and computation and exhibit good transferability.

关键词： Power edge Data format Quantification Compute-in-memory

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Hepatomegaly and jaundice as the presenting symptoms of systemic light-chain amyloidosis: A case report

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World Journal of Gastrointestinal Oncology 2024年第2期16卷 550-556页

作者： Xu zhang Fei Tang yan-Ying Gao De-Zhao song Jing Liang Department of Gastroenterology and Hepatology The Third Central Hospital of TianjinTianjin 300170China Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases Artificial Cell Engineering Technology Research CenterTianjin Institute of Hepatobiliary DiseaseTianjin 300170China Department of Interventional Radiology The Third Central Hospital of TianjinTianjin 300170China

BACKGROUND Light chain(AL)amyloidosis is a plasma cell dyscrasia characterized by the pathologic production and extracellular tissue deposition of fibrillar proteins derived from immunoglobulin AL fragments secreted by a clone of plasma cells,which leads to progressive dysfunction of the affected organs.The two most commonly affected organs are the heart and kidneys,and liver is rarely the dominant affected organ with only 3.9%of cases,making them prone to misdia-gnosis and missed diagnosis.CASE SUMMARY A 65-year-old woman was admitted with a 3-mo history of progressive jaundice and marked hepatomegaly.Initially,based on enhanced computed tomography scan and angiography,Budd-Chiari syndrome was considered and balloon dilatation of significant hepatic vein stenoses was performed.However,addi-tional diagnostic procedures,including liver biopsy and bone marrow-exami-nation,revealed immunoglobulin kapa AL amyloidosis with extensive liver involvement and hepatic vascular compression.The disease course was progre-ssive and fatal,and the patient eventually died 5 mo after initial presentation of symptoms.CONCLUSION AL amyloidosis with isolated liver involvement is very rare,and can be easily misdiagnosed as a vascular disease.

关键词： Jaundice Hepatomegaly Liver amyloidosis Kappa light chain Pseudo-Budd-Chiari syndrome Case report

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Monotropein Induced Apoptosis and Suppressed Cell Cycle Progression in Colorectal Cancer Cells

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Chinese Journal of Integrative Medicine 2024年第1期30卷 25-33页

作者： GAO Quan LI Lin zhang Qi-man SHENG Qin-song zhang Ji-liang JIN Li-jun SHANG Rui-yan School of Pharmacy and Department of Medical Oncology the Affiliated Hospital of Hangzhou Normal UniversityHangzhou Normal UniversityHangzhou(311121)China Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines Engineering Laboratory of Development and Application of Traditional Chinese MedicinesCollaborative Innovation Center of Traditional Chinese Medicines of Zhejiang ProvinceHangzhou Normal UniversityHangzhou(311121)China Department of Colorectal Surgery the First Affiliated HospitalSchool of MedicineZhejiang UniversityHangzhouChina Beijing Tong Ren Tang Chinese Medicine Co. Ltd.Beijing(100000)China Department of Traditional Chinese Medicine Hangzhou Shangcheng District People's HospitalHangzhou(310006)China Department of Gynecology Hangzhou Women's HospitalHangzhou(310008)China

Objective: To determine whether monotropein has an anticancer effect and explore its potential mechanisms against colorectal cancer(CRC) through network pharmacology and molecular docking combined with experimental verification. Methods: Network pharmacology and molecular docking were used to predict potential targets of monotropein against CRC. Cell counting kit assay, plate monoclonal assay and microscopic observation were used to investigate the antiproliferative effects of monotropein on CRC cells HCT116, HT29 and LoVo. Flow cytometry and scratch assay were used to analyze apoptosis and cell cycle, as well as cell migration, respectively in HCT116, HT29, and LoVo cells. Western blotting was used to detect the expression of proteins related to apoptosis, cell cycle, and cell migration, and the expression of proteins key to the Akt pathway. Results: The Gene Ontology and Reactome enrichment analyses indicated that the anticancer potential of monotropein against CRC might be involved in multiple cancer-related signaling pathways. Among these pathways, RAC-beta serine/threonine-protein kinase(Akt1, Akt2), cyclin-dependent kinase 6(CDK6), matrix metalloproteinase-9(MMP9), epidermal growth factor receptor(EGFR), cell division control protein 42 homolog(CDC42) were shown as the potential anticancer targets of monotropein against CRC. Molecular docking suggested that monotropein may interact with the 6 targets(Akt1, Akt2, CDK6, MMP9, EGFR, CDC42). Subsequently, cell activity of HCT116, HT29 and LoVo cell lines were significantly suppressed by monotropein(P<0.05). Furthermore, our research revealed that monotropein induced cell apoptosis by inhibiting Bcl-2 and increasing Bax, induced G_1–S cycle arrest in colorectal cancer by decreasing the expressions of CyclinD1, CDK4 and CDK6, inhibited cell migration by suppressing the expressions of CDC42 and MMP9(P<0.05), and might play an anticancer role through Akt signaling pathway. Conclusions: Monotropein exerts its antitumor effects primarily by arresting the cell cycle,

关键词： monotropein Chinese medicine anticancer activity colorectal cancer cells network pharmacology

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Boron nitride nanofibers enhanced composite PEO-based solid-state polymer electrolytes for lithium metal batteries

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Chinese Chemical Letters 2024年第6期35卷 216-221页

作者： Qianqian song Yunting zhang Jianli Liang Si Liu Jian Zhu Xingbin yan School of Materials Science and Engineering Sun Yat-Sen UniversityGuangzhou 510275China College of Physics and Materials Science Tianjin Normal UniversityTianjin 300387China Department of Chemistry&Center of Super-Diamond and Advanced Films(COSDAF) City University of Hong KongHong Kong 999077China Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology School of Physics and Optoelectronic EngineeringFoshan UniversityFoshan 528225China

Polyethylene oxide(PEO)-based solid-state polymer electrolytes(SPEs)are limited by their poor cyclic stability and inferior ionic conductivity for applicating in high-safety,long-cycling and high-energy-density lithium metal batteries.Herein,porous boron nitride nanofibers(BNNFs)are filled into PEO-based SPE,which significantly suppresses Li dendrites growth and enhances the electrochemical performance of Li metal battery.BNNFs with high porosity have more active sites to connect with PEO,which can effectively reduce the crystallinity of the PEO matrix and enhance its ionic conductivity.Moreover,owing to the hardness and good stability of BNNFs,BNNFs/PEO/Li TFSI electrolyte exhibits a wider electrochemical window,better mechanical property and higher thermal stability compared with PEO/Li TFSI electrolyte.Consequently,the Li symmetric cell composed of 1%BNNFs/PEO/Li TFSI performs good cyclic stability(>1800 h),and the Li||1%BNNFs/PEO/Li TFSI||LFP full battery shows obviously improved performances in charge-discharge polarization voltage,discharge specific capacity,rate performance and cyclic stability than the Li||PEO/Li TFSI||LFP battery.

关键词： Solid-state polymer electrolyte Boron nitride nanofibers Lithium metal battery Ionic conductivity Li dendrite

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