Publications by authors named "Chengyan Wang"

89 Publications

Dynamic R2' Imaging can Be a Biomarker for Diagnosing and Staging Early Acute Kidney Injury in Animals.

Front Med (Lausanne) 2021 24;8:775042. Epub 2021 Dec 24.

Department of Interventional Radiology and Vascular Surgery, Peking University First Hospital, Beijing, China.

Early diagnosis of acute kidney injury (AKI) is essential in clinical settings. None of the current biomarkers are widely applied. The combination of pulse-shifting multi-echo asymmetric spin-echo sequence (psMASE) and a modified hemodynamic response imaging (HRI) technique is promising. The purpose of this study was to evaluate the feasibility of psMASE combined with HRI in detecting early ischemic AKI in animal models of different severities. Twenty rabbits were divided into four groups (mild, moderate, and severe AKI and control groups). Transarterial embolization with different doses of microspheres was performed to establish AKI animal models of different severities. The 3T psMASE and HRI scans of kidneys were conducted. The R2, R2, and R2' during room air and gas stimulation were acquired and the difference of R2' (dR2') was evaluated in different AKI groups. The values were not different in R2 and R2 during room air and in R2 and R2, and R2' during gas stimulation. The value of R2' was significantly different during room air ( = 0.014), but the difference was only found between control and moderate/severe AKI groups ( = 0.032 and 0.022). The values of dR2' were different among groups ( < 0.0001) and differences between every two groups except comparison of moderate and severe AKI groups were significant ( < 0.01). The dR2' imaging acquired by a combination of renal psMASE and HRI technique can serve as a potential quantitative biomarker for early detection and staging of AKI.
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http://dx.doi.org/10.3389/fmed.2021.775042DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8739497PMC
December 2021

Insights into the effect of cations on cathodic behavior and microstructure in cadmium electrochemical recovery process.

Chemosphere 2021 Dec 24;292:133423. Epub 2021 Dec 24.

State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing, 100083, China; School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing, 100083, China. Electronic address:

Secondary resources provide an essential source for cadmium recovery, but also bring severe environmental problems. Due to the short process and high product purity, electrodeposition is suitable for realizing the reduction, reuse, and recycling of cadmium, while the complex composition of the resources contributes to a complicated electrochemical system. In this work, the effect of common cations (Cu, Ni, Fe, and Zn) on cadmium electrochemical recovery was investigated from the perspective of electrochemical behavior and microstructure. The results indicated that Cu affected the electrochemical process most prominently, which was deposited on the cathode and formed microcell with Cd, not only impeding the recovery of Cd, but also influencing the purity severely. Comparatively, Ni showed a relatively minor effect, which made the formal potential more negative and alleviated cathodic polarization to some degree. Besides, Fe was oxidized by the oxygen released from the anode, and followed by the reaction with Cd, resulting in the redissolution of Cd. With respect to Zn, a low concentration of Zn (≤1 g L) had little influence on electrochemical behavior of Cd, while it was deposited simultaneously with Cd on the cathode at a high concentration (5 g L). Based on the microstructural characterization, the lithops-like cathode cadmium grew up in the presence of Cu, while dendritic Cd was formed affected by Zn, Fe, and Ni, especially Fe.
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http://dx.doi.org/10.1016/j.chemosphere.2021.133423DOI Listing
December 2021

Long non-coding RNA MIR31HG as a prognostic predictor for malignant cancers: A meta- and bioinformatics analysis.

J Clin Lab Anal 2022 Jan 27;36(1):e24082. Epub 2021 Nov 27.

NHC Key Laboratory of Prevention and Treatment of Central Asia High Incidence Diseases (First Affiliated Hospital, School of Medicine, Shihezi University), Shihezi, China.

Background: The possible regulatory mechanism of MIR31HG in human cancers remains unclear, and reported results of the prognostic significance of MIR31HG expression are inconsistent.

Methods: The meta-analysis and related bioinformatics analysis were conducted to evaluate the role of MIR31HG in tumor progression.

Results: The result showed that high MIR31HG expression was not related to prognosis. However, in the stratified analysis, we found that the overexpression of MIR31HG resulted in worse OS, advanced TNM stage, and tumor differentiation in respiratory system cancers. Moreover, our results also found that MIR31HG overexpression was related to shorter OS in cervical cancer patients and head and neck tumors. In contrast, the MIR31HG was lower in digestive system tumors which contributed to shorter overall survival, advanced TNM stage, and distant metastasis. Furthermore, the bioinformatics analysis showed that MIR31HG was highly expressed in normal urinary bladder, small intestine, esophagus, stomach, and duodenum and low in colon, lung, and ovary. The results obtained from FireBrowse indicated that MIR31HG was highly expressed in LUSC, CESC, HNSC, and LUAD and low in STAD and BLCA. Gene Ontology analysis showed that the co-expressed genes of MIR31HG were most enriched in the biological processes of peptide metabolism and KEGG pathways were most enriched in Ras, Rap1, and PI3K-Akt signaling pathway.

Conclusion: MIR31HG may serve as a potential biomarker in human cancers.
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http://dx.doi.org/10.1002/jcla.24082DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8761471PMC
January 2022

Meta-Analysis on the Improvement of Symptoms and Prognosis of Gastrointestinal Tumors Based on Medical Care and Exercise Intervention.

J Healthc Eng 2021 12;2021:5407664. Epub 2021 Nov 12.

Oncology Department, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200071, China.

Gastric cancer is a malignant tumor that originates from the epithelium of the gastric mucosa. It is the result of a combination of multiple factors, but the current research has not yet clarified its pathogenesis, so further research and exploration are needed. This article is mainly based on the meta-analysis of the improvement of gastrointestinal tumor-related symptoms and prognosis based on medical care and exercise intervention. The control group followed routine care after enrollment. In addition to routine care, patients in the intervention group exercised through assessment, formulation of exercise prescriptions, implementation of supervision, and adjustment. By viewing the subjects' physical examination reports, determine their blood routine, urine routine, blood lipids, blood sugar, liver and kidney function, and electrocardiogram examination. In this experiment, dual-contrast ultrasound in each T staging was greater than 0.8, indicating that the diagnostic method is very accurate in the preoperative diagnosis of gastric cancer T staging. The results show that exercise intervention can improve the pain of patients with gastrointestinal tumors after chemotherapy, relieve cancer-induced fatigue, and improve the quality of life.
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http://dx.doi.org/10.1155/2021/5407664DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8604603PMC
December 2021

MAGnitude-Image-to-Complex -space (MAGIC-K) Net: A Data Augmentation Network for Image Reconstruction.

Diagnostics (Basel) 2021 Oct 19;11(10). Epub 2021 Oct 19.

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.

Deep learning has demonstrated superior performance in image reconstruction compared to most conventional iterative algorithms. However, their effectiveness and generalization capability are highly dependent on the sample size and diversity of the training data. Deep learning-based reconstruction requires multi-coil raw -space data, which are not collected by routine scans. On the other hand, large amounts of magnitude images are readily available in hospitals. Hence, we proposed the MAGnitude Images to Complex -space (MAGIC-K) Net to generate multi-coil -space data from existing magnitude images and a limited number of required raw -space data to facilitate the reconstruction. Compared to some basic data augmentation methods applying global intensity and displacement transformations to the source images, the MAGIC-K Net can generate more realistic intensity variations and displacements from pairs of anatomical Digital Imaging and Communications in Medicine (DICOM) images. The reconstruction performance was validated in 30 healthy volunteers and 6 patients with different types of tumors. The experimental results demonstrated that the high-resolution Diffusion Weighted Image (DWI) reconstruction benefited from the proposed augmentation method. The MAGIC-K Net enabled the deep learning network to reconstruct images with superior performance in both healthy and tumor patients, qualitatively and quantitatively.
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http://dx.doi.org/10.3390/diagnostics11101935DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534839PMC
October 2021

Deep learning based multiplexed sensitivity-encoding (DL-MUSE) for high-resolution multi-shot DWI.

Neuroimage 2021 12 7;244:118632. Epub 2021 Oct 7.

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China; Human Phenome Institute, Fudan University, Shanghai, China. Electronic address:

Purpose: A phase correction method for high-resolution multi-shot (MSH) diffusion weighted imaging (DWI) is proposed. The efficacy and generalization capability of the method were validated on both healthy volunteers and patients.

Theory And Methods: Conventionally, inter-shot phase variations for MSH echo-planar imaging (EPI) DWI are corrected by model-based algorithms. However, many acquisition imperfections are hard to measure accurately for conventional model-based methods, making the phase estimation and artifacts suppression unreliable. We propose a deep learning multiplexed sensitivity-encoding (DL-MUSE) framework to improve the phase estimations based on convolutional neural network (CNN) reconstruction. Aliasing-free single-shot (SSH) DW images, which have been used routinely in clinical settings, were used for training before the aliasing correction of MSH-DWI images. A dual-channel U-net comprising multiple convolutional layers was used for the phase estimation of MSH-EPI. The network was trained on a dataset containing 30 healthy volunteers and tested on another dataset of 52 healthy subjects and 15 patients with lesions or tumors with different shot numbers (4, 6 and 8). To further validate the generalization capability of our network, we acquired a dataset with different numbers of shots, TEs, partial Fourier factors, resolutions, ETLs, FOVs, coil numbers, and image orientations from two sites. We also compared the reconstruction performance of our proposed method with that of the conventional MUSE and SSH-EPI qualitatively and quantitatively.

Results: Our results show that DL-MUSE is capable of correcting inter-shot phase errors with high and robust performance. Compared to conventional model-based MUSE, our method, by applying deep learning-based phase corrections, showed reduced distortion, noise level, and signal loss in high b-value DWIs. The improvements of image quality become more evident as the shot number increases from 4 to 8, especially in those central regions of the images, where g-factor artifacts are severe. Furthermore, the proposed method could provide the information about the orientation of the white matter with better consistency and achieve finer fibers delineation compared to the SSH-EPI method. Besides, the experiments on volunteers and patients from two different sites demonstrated the generalizability of our proposed method preliminarily.

Conclusion: A deep learning-based reconstruction algorithm for MSH-EPI images, which helps improve image quality greatly, was proposed. Results from healthy volunteers and tumor patients demonstrated the feasibility and generalization performances of our method for high-resolution MSH-EPI DWI, which can be used for routine clinical applications as well as neuroimaging research.
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http://dx.doi.org/10.1016/j.neuroimage.2021.118632DOI Listing
December 2021

A Biofilm Microenvironment-Activated Single-Atom Iron Nanozyme with NIR-Controllable Nanocatalytic Activities for Synergetic Bacteria-Infected Wound Therapy.

Adv Healthc Mater 2021 11 7;10(22):e2101374. Epub 2021 Oct 7.

Key Laboratory of Pollution Control Chemistry and Environmental Functional Materials for Qinghai-Tibet Plateau of the National Ethnic Affairs Commission, School of Chemistry and Environment, Southwest Minzu University, Chengdu, 610041, China.

Biofilm microenvironment (BME)-activated antimicrobial agents display great potential for improved biofilm-related infection therapy because of their superior specificities and sensitivities, effective eliminations, and minimal side effects. Herein, BME-activated Fe-doped polydiaminopyridine nanofusiform-mediated single-atom nanozyme (FePN SAzyme) is presented for photothermal/chemodynamic synergetic bacteria-infected wound therapy. The photothermal therapy (PTT) function of SAzyme can be specifically initiated by the high level of H O and further accelerated through mild acid within the inflammatory environment through "two-step rocket launching-like" process. Additionally, the enhanced chemodynamic therapy (CDT) for the FePN SAzyme can also be endowed by producing hydroxyl radicals through reacting with H O and consuming glutathione (GSH) of the BME, thereby contributing to more efficient synergistic therapeutic effect. Meanwhile, FePN SAzyme could catalyze biofilm-overexpressed H O decomposing into O and overcome the hypoxia of biofilm, which significantly enhances the susceptibility of biofilm and increases the synergistic efficacy. Most importantly, the synergistic therapy of bacterial-induced infection diseases can be switched on by the internal and external stimuli simultaneously, resulting in minimal nonspecific damage to healthy tissue. These remarkable characteristics of FePN SAzyme not only develop an innovative strategy for the BME-activated combination therapy but also open a new avenue to explore other nanozyme-involved nanoplatforms for bacterial biofilm infections.
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http://dx.doi.org/10.1002/adhm.202101374DOI Listing
November 2021

Simultaneous image reconstruction and lesion segmentation in accelerated MRI using multitasking learning.

Med Phys 2021 Nov 30;48(11):7189-7198. Epub 2021 Sep 30.

Human Phenome Institute, Fudan University, Shanghai, China.

Purpose: Magnetic resonance imaging (MRI) serves as an important medical imaging modality for a variety of clinical applications. However, the problem of long imaging time limited its wide usage. In addition, prolonged scan time will cause discomfort to the patient, leading to severe image artifacts. On the other hand, manually lesion segmentation is time consuming. Algorithm-based automatic lesion segmentation is still challenging, especially for accelerated imaging with low quality.

Methods: In this paper, we proposed a multitask learning-based method to perform image reconstruction and lesion segmentation simultaneously, called "RecSeg". Our hypothesis is that both tasks can benefit from the usage of the proposed combined model. In the experiment, we validated the proposed multitask model on MR k-space data with different acceleration factors (2×, 4×, and 6×). Two connected U-nets were used for the tasks of liver and renal image reconstruction and segmentation. A total of 50 healthy subjects and 100 patients with hepatocellular carcinoma were included for training and testing. For the segmentation part, we use healthy subjects to verify organ segmentation, and hepatocellular carcinoma patients to verify lesion segmentation. The organs and lesions were manually contoured by an experienced radiologist.

Results: Experimental results show that the proposed RecSeg yielded the highest PSNR (RecSeg: 32.39 ± 1.64 vs. KSVD: 29.53 ± 2.74 and single U-net: 31.18 ± 1.68, respectively, p < 0.05) and highest structural similarity index measure (SSIM) (RecSeg: 0.93 ± 0.01 vs. KSVD: 0.88 ± 0.02 and single U-net: 0.90 ± 0.01, respectively, p < 0.05) under 6× acceleration. Moreover, in the task of lesion segmentation, it is proposed that RecSeg produced the highest Dice score (RecSeg: 0.86 ± 0.01 vs. KSVD: 0.82 ± 0.01 and single U-net: 0.84 ± 0.01, respectively, p < 0.05).

Conclusions: This study focused on the simultaneous reconstruction of medical images and the segmentation of organs and lesions. It is observed that the multitask learning-based method can improve performances of both image reconstruction and lesion segmentation.
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http://dx.doi.org/10.1002/mp.15213DOI Listing
November 2021

Co-treatment of copper smelting flue dust and arsenic sulfide residue by a pyrometallurgical approach for simultaneous removal and recovery of arsenic.

J Hazard Mater 2021 08 24;416:126149. Epub 2021 May 24.

State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing 100083, China; School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, China. Electronic address:

As the typical hazardous arsenic pollutants, copper smelting flue dust (CSFD) and arsenic sulfide residue (ASR) are produced extensively during copper smelting process, which pose significant pressure on environmental protection and green development of the copper industry. This work proposed an economic, efficient, and applicable approach to treat waste with waste, in which the simultaneous removal and recovery of As from CSFD and ASR were realized by a roasting process, with adding sulfuric acid, at a relatively low temperature (300-350 ℃). The thermodynamic analysis and experiments confirmed that the main phases of AsS and S in the ASR were used as a reductant for reducing As(Ⅴ) in the CSFD, and the introduction of sulfuric acid favorably enhanced the thermodynamic driving force and greatly lowered the reaction temperature. The results indicated that removal and behavior of As were highly dependent on the mass ratio of ASR to CSFD, roasting temperature, and HSO dosage. By regulating the parameters, the species AsS, AsO, and arsenate were all converted to volatile AsO, which could be captured and deposited in cold water. In the optimized co-treatment, a satisfied As removal efficiency of 96.12% was achieved, while getting the 97.03% pure AsO.
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http://dx.doi.org/10.1016/j.jhazmat.2021.126149DOI Listing
August 2021

Eco-Friendly and Scalable Synthesis of Fullerenols with High Free Radical Scavenging Ability for Skin Radioprotection.

Small 2021 09 1;17(37):e2102035. Epub 2021 Aug 1.

CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, 100049, China.

Radiation dermatitis is a common but torturous side effect during radiotherapy, which greatly decreases the life quality of patients and potentially results in detrimental cessation of tumor treatment. Fullerenol, known as "free radical sponge," is a great choice for skin radioprotection because of its broad-spectrum free radical scavenging performance, good chemical stability, and biosafety. In this work, a facile scalable and eco-friendly synthetic method of fullerenols by catalyst assistant mechanical chemistry strategy is provided. As no organic solvent or high concentration of acid and alkali is introduced to this synthetic system, large-scale (>20 g) production of fullerenols with high yield (>95%) is obtained and no complicated purification is required. Then, the skin radioprotective performance of fullerenols is systematically explored for the first time. In vitro results indicate that fullerenols significantly block the reactive oxygen species-induced damage and enhance the viability of irradiated human keratinocyte cells. In vivo experiments suggest that medical sodium hyaluronate hydrogels loaded with fullerenols are suitable for skin administration and powerfully mitigate radiodermatitis via effectively protecting epidermal stem cells. The work not only provides an efficient gram-scale and eco-friendly synthetic method of fullerenols, but also promotes the development of fullerenols as potential skin radioprotectors.
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http://dx.doi.org/10.1002/smll.202102035DOI Listing
September 2021

Human pluripotent stem cell-derived eosinophils reveal potent cytotoxicity against solid tumors.

Stem Cell Reports 2021 07 1;16(7):1697-1704. Epub 2021 Jul 1.

School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, and the MOE Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100191, China. Electronic address:

Eosinophils are attractive innate immune cells to use to potentiate T cell antitumor efficacy because they are capable of infiltrating tumors at early stages and modulating the tumor microenvironment. However, the limited number of functional eosinophils caused by the scarcity and short life of primary eosinophils in peripheral blood has greatly impeded the development of eosinophil-based immunotherapy. In this study, we established an efficient chemically defined protocol to generate a large quantity of functional eosinophils from human pluripotent stem cells (hPSCs) with nearly 100% purity expressing eosinophil peroxidase. These hPSC-derived eosinophils transcriptionally resembled their primary counterpart. Moreover, hPSC-derived eosinophils showed competent tumor killing capacity in established solid tumors. Furthermore, the combination of hPSC-derived eosinophils with CAR-T cells exhibited potential synergistic effects, inhibiting tumor growth and enhancing mouse survival. Our study opens up new avenues for the development of eosinophil-based immunotherapies to treat cancer.
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http://dx.doi.org/10.1016/j.stemcr.2021.06.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8282466PMC
July 2021

Deep learning-based identification of acute ischemic core and deficit from non-contrast CT and CTA.

J Cereb Blood Flow Metab 2021 11 8;41(11):3028-3038. Epub 2021 Jun 8.

Human Phenome Institute, Fudan University, Shanghai, China.

The accurate identification of irreversible infarction and salvageable tissue is important in planning the treatments for acute ischemic stroke (AIS) patients. Computed tomographic perfusion (CTP) can be used to evaluate the ischemic core and deficit, covering most of the territories of anterior circulation, but many community hospitals and primary stroke centers do not have the capability to perform CTP scan in emergency situation. This study aimed to identify AIS lesions from widely available non-contrast computed tomography (NCCT) and CT angiography (CTA) using deep learning. A total of 345AIS patients from our emergency department were included. A multi-scale 3D convolutional neural network (CNN) was used as the predictive model with inputs of NCCT, CTA, and CTA+ (8 s delay after CTA) images. An external cohort with 108 patients was included to further validate the generalization performance of the proposed model. Strong correlations with CTP-RAPID segmentations ( = 0.84 for core,  = 0.83 for deficit) were observed when NCCT, CTA, and CTA+ images were all used in the model. The diagnostic decisions according to DEFUSE3 showed high accuracy when using NCCT, CTA, and CTA+ (0.90±0.04), followed by the combination of NCCT and CTA (0.87±0.04), CTA-alone (0.76±0.06), and NCCT-alone (0.53±0.09).
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http://dx.doi.org/10.1177/0271678X211023660DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8756471PMC
November 2021

Transfer learning enhanced generative adversarial networks for multi-channel MRI reconstruction.

Comput Biol Med 2021 07 26;134:104504. Epub 2021 May 26.

Cardiovascular Research Centre, Royal Brompton Hospital, London, SW3 6NP, UK; National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK. Electronic address:

Deep learning based generative adversarial networks (GAN) can effectively perform image reconstruction with under-sampled MR data. In general, a large number of training samples are required to improve the reconstruction performance of a certain model. However, in real clinical applications, it is difficult to obtain tens of thousands of raw patient data to train the model since saving k-space data is not in the routine clinical flow. Therefore, enhancing the generalizability of a network based on small samples is urgently needed. In this study, three novel applications were explored based on parallel imaging combined with the GAN model (PI-GAN) and transfer learning. The model was pre-trained with public Calgary brain images and then fine-tuned for use in (1) patients with tumors in our center; (2) different anatomies, including knee and liver; (3) different k-space sampling masks with acceleration factors (AFs) of 2 and 6. As for the brain tumor dataset, the transfer learning results could remove the artifacts found in PI-GAN and yield smoother brain edges. The transfer learning results for the knee and liver were superior to those of the PI-GAN model trained with its own dataset using a smaller number of training cases. However, the learning procedure converged more slowly in the knee datasets compared to the learning in the brain tumor datasets. The reconstruction performance was improved by transfer learning both in the models with AFs of 2 and 6. Of these two models, the one with AF = 2 showed better results. The results also showed that transfer learning with the pre-trained model could solve the problem of inconsistency between the training and test datasets and facilitate generalization to unseen data.
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http://dx.doi.org/10.1016/j.compbiomed.2021.104504DOI Listing
July 2021

Efficient removal and recovery of arsenic from copper smelting flue dust by a roasting method: Process optimization, phase transformation and mechanism investigation.

J Hazard Mater 2021 06 25;412:125232. Epub 2021 Jan 25.

State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing 100083, China; School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, China. Electronic address:

The efficient removal and recovery of arsenic from copper smelting flue dust have received widespread attention due to its extremely high toxicity and carcinogenicity. In this research, a roasting method used for treating the dust at a relatively low temperature (300-400 ℃), with adding sulfuric acid and bitumite, was proposed, in which the reduction of As(Ⅴ) and oxidation of arsenic sulfides were achieved simultaneously. It was proved by thermodynamic analysis and experiments that adding sulfuric acid was favorable for the removal of arsenic, through enhancing the thermodynamic driving force and promoting the transformation of arsenate and arsenic sulfides to AsO. The phase transformation of arsenic was analyzed using XRD, SEM-EDS and XPS, which indicated that coal addition, roasting temperature and HSO dosage play essential roles in arsenic removal. Based on the lab-scale experiments, the optimal conditions for arsenic removal were found to be at the roasting temperature of 300-400 °C, roasting time of 2-3 h, coal addition of 5% and HSO dosage of 0.2-0.3 mL/g. Around 98% of arsenic was volatilized from the dust, while arsenic content in the residue was decreased to 0.57%. Eventually, arsenic was recovered as AsO with a high purity of 99.05%.
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http://dx.doi.org/10.1016/j.jhazmat.2021.125232DOI Listing
June 2021

Brain Development From Newborn to Adolescence: Evaluation by Neurite Orientation Dispersion and Density Imaging.

Front Hum Neurosci 2021 15;15:616132. Epub 2021 Mar 15.

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.

Neurite orientation dispersion and density imaging (NODDI) is a diffusion model specifically designed for brain magnetic resonance imaging. Despite recent studies suggesting that NODDI modeling might be more sensitive to brain development than diffusion tensor imaging (DTI), these studies were limited to a relatively small age range and mainly based on the manually operated region of interest analysis. Therefore, this study applied NODDI to investigate brain development in a large sample size of 214 subjects ranging in ages from 0 to 14. The whole brain was automatically segmented into 122 regions. The maturation trajectory of each region was characterized by the time course of diffusion metrics and further quantified using nonlinear regression. The NODDI-derived metrics, neurite density index (NDI) and orientation dispersion index (ODI), increased with age. And these two metrics were superior to the DTI-derived metrics in SVM regression models of age. The NDI in white matter exhibited a more rapid growth than that in gray matter (including the cortex and deep nucleus). These diffusion indicators experienced conspicuous increases during early childhood and the growth speed slowed down in adolescence. Region-specific maturation patterns were described throughout the brain, including white matter, cortical and deep gray matter. These development patterns were evaluated and discussed on the basis of NODDI's model assumptions. To summarize, this study verified the high sensitivity of NODDI to age over a crucial developmental period from newborn to adolescence. Moreover, the existing knowledge of brain development has been complemented, suggesting that NODDI has a potential capability in the investigation of brain development.
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http://dx.doi.org/10.3389/fnhum.2021.616132DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8005551PMC
March 2021

Feasibility of automatic detection of small hepatocellular carcinoma (≤2 cm) in cirrhotic liver based on pattern matching and deep learning.

Phys Med Biol 2021 04 16;66(8). Epub 2021 Apr 16.

Department of Radiology, Ruijin Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, People's Republic of China.

Early detection of hepatocellular carcinoma (HCC) is crucial for clinical management. Current studies have reported large HCC detections using automatic algorithms, but there is a lack of research on automatic detection of small HCCs (sHCCs). This study is to investigate the feasibility of automatic detection of sHCC (≤2 cm) based on pattern matching and deep learning (PM-DL) model.. A retrospective study included 5376 image sets from 56 cirrhosis patients (28 sHCC patients with 32 pathologically confirmed lesions and 28 non-HCC cirrhosis patients) in the training-validation cohort to build and validate the model through five-fold cross-validation. In addition, an external test cohort including 6144 image sets from 64 cirrhosis patients (32 sHCC patients with 38 lesions and 32 non-HCC cirrhosis patients) was applied to further verify the generalization ability of the model. The proposed PM-DL model consisted of three main steps: 3D co-registration and liver segmentation, screening of suspicious lesions on diffusion-weighted imaging images based on pattern matching algorithm, and identification/segmentation of sHCC lesions on dynamic contrast-enhanced images with convolutional neural network.The PM-DL model achieved a sensitivity of 89.74% and a positive predictive value of 85.00% in the external test cohort for per-lesion analysis. No significant difference was observed in volumes (= 0.13) and the largest sizes (= 0.89) between manually delineated and segmented lesions. The DICE coefficient reached 0.77 ± 0.16. Similar performances were identified in the validation cohort. Moreover, the PM-DL model outperformed Liver Imaging Reporting and Data System (LI-RADS) in sensitivity (probable HCCs: LR-5 or LR-4,= 0.18; definite HCCs: LR-5,< 0.001), with a similar high specificity for per-patient analysis.. The PM-DL model may be feasible for accurate automatic detection of sHCC in cirrhotic liver.
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http://dx.doi.org/10.1088/1361-6560/abf2f8DOI Listing
April 2021

Imaging-Based Staging of Hepatic Fibrosis in Patients with Hepatitis B: A Dynamic Radiomics Model Based on Gd-EOB-DTPA-Enhanced MRI.

Biomolecules 2021 02 18;11(2). Epub 2021 Feb 18.

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.

Accurate grading of liver fibrosis can effectively assess the severity of liver disease and help doctors make an appropriate diagnosis. This study aimed to perform the automatic staging of hepatic fibrosis on patients with hepatitis B, who underwent gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging with dynamic radiomics analysis. The proposed dynamic radiomics model combined imaging features from multi-phase dynamic contrast-enhanced (DCE) images and time-domain information. Imaging features were extracted from the deep learning-based segmented liver volume, and time-domain features were further explored to analyze the variation in features during contrast enhancement. Model construction and evaluation were based on a 132-case data set. The proposed model achieved remarkable performance in significant fibrosis (fibrosis stage S1 vs. S2-S4; accuracy (ACC) = 0.875, area under the curve (AUC) = 0.867), advanced fibrosis (S1-S2 vs. S3-S4; ACC = 0.825, AUC = 0.874), and cirrhosis (S1-S3 vs. S4; ACC = 0.850, AUC = 0.900) classifications in the test set. It was more dominant compared with the conventional single-phase or multi-phase DCE-based radiomics models, normalized liver enhancement, and some serological indicators. Time-domain features were found to play an important role in the classification models. The dynamic radiomics model can be applied for highly accurate automatic hepatic fibrosis staging.
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http://dx.doi.org/10.3390/biom11020307DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7922315PMC
February 2021

Rational Design of Nanomaterials for Various Radiation-Induced Diseases Prevention and Treatment.

Adv Healthc Mater 2021 03 27;10(6):e2001615. Epub 2021 Jan 27.

Center of Materials Science and Optoelectronics Engineering, College of Materials Science and Optoelectronic Technology, University of Chinese Academy of Sciences, Beijing, 100049, China.

Radiation treatments often unfavorably damage neighboring healthy organs and cause a series of radiation sequelae, such as radiation-induced hematopoietic system diseases, radiation-induced gastrointestinal diseases, radiation-induced lung diseases, and radiation-induced skin diseases. Recently, emerging nanomaterials have exhibited good superiority for these radiation-induced disease treatments. Given this background, the rational design principle of nanomaterials, which helps to optimize the therapeutic efficiency, has been an increasing need. Consequently, it is of great significance to perform a systematic summarization of the advances in this field, which can trigger the development of new high-performance nanoradioprotectors with drug efficiency maximization. Herein, this review highlights the advances and perspectives in the rational design of nanomaterials for preventing and treating various common radiation-induced diseases. Furthermore, the sources, clinical symptoms, and pathogenesis/injury mechanisms of these radiation-induced diseases will also be introduced. Furthermore, current challenges and directions for future efforts in this field are also discussed.
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http://dx.doi.org/10.1002/adhm.202001615DOI Listing
March 2021

Iron Content in Deep Gray Matter as a Function of Age Using Quantitative Susceptibility Mapping: A Multicenter Study.

Front Neurosci 2020 6;14:607705. Epub 2021 Jan 6.

Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Purpose: To evaluate the effect of resolution on iron content using quantitative susceptibility mapping (QSM); to verify the consistency of QSM across field strengths and manufacturers in evaluating the iron content of deep gray matter (DGM) of the human brain using subjects from multiple sites; and to establish a susceptibility baseline as a function of age for each DGM structure using both a global and regional iron analysis.

Methods: Data from 623 healthy adults, ranging from 20 to 90 years old, were collected across 3 sites using gradient echo imaging on one 1.5 Tesla and two 3.0 Tesla MR scanners. Eight subcortical gray matter nuclei were semi-automatically segmented using a full-width half maximum threshold-based analysis of the QSM data. Mean susceptibility, volume and total iron content with age correlations were evaluated for each measured structure for both the whole-region and RII (high iron content regions) analysis. For the purpose of studying the effect of resolution on QSM, a digitized model of the brain was applied.

Results: The mean susceptibilities of the caudate nucleus (CN), globus pallidus (GP) and putamen (PUT) were not significantly affected by changing the slice thickness from 0.5 to 3 mm. But for small structures, the susceptibility was reduced by 10% for 2 mm thick slices. For global analysis, the mean susceptibility correlated positively with age for the CN, PUT, red nucleus (RN), substantia nigra (SN), and dentate nucleus (DN). There was a negative correlation with age in the thalamus (THA). The volumes of most nuclei were negatively correlated with age. Apart from the GP, THA, and pulvinar thalamus (PT), all the other structures showed an increasing total iron content despite the reductions in volume with age. For the RII regional high iron content analysis, mean susceptibility in most of the structures was moderately to strongly correlated with age. Similar to the global analysis, apart from the GP, THA, and PT, all structures showed an increasing total iron content.

Conclusion: A reasonable estimate for age-related iron behavior can be obtained from a large cross site, cross manufacturer set of data when high enough resolutions are used. These estimates can be used for correcting for age related iron changes when studying diseases like Parkinson's disease, Alzheimer's disease, and other iron related neurodegenerative diseases.
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http://dx.doi.org/10.3389/fnins.2020.607705DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7815653PMC
January 2021

Combined Effects of Elevated Temperature and Crude Oil Pollution on Oxidative Stress and Apoptosis in Sea Cucumber (, Selenka).

Int J Environ Res Public Health 2021 01 19;18(2). Epub 2021 Jan 19.

College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026, China.

Currently, global climate change and oil pollution are two main environmental concerns for sea cucumber () aquaculture. However, no study has been conducted on the combined effects of elevated temperature and oil pollution on sea cucumber. Therefore, in the present study, we treated sea cucumber with elevated temperature (26 °C) alone, water-accommodated fractions (WAF) of Oman crude oil at an optimal temperature of 16 °C, and Oman crude oil WAF at an elevated temperature of 26 °C for 24 h. Results showed that reactive oxygen species (ROS) level and total antioxidant capacity in WAF at 26 °C treatment were higher than that in WAF at 16 °C treatment, as evidenced by 6.03- and 1.31-fold-higher values, respectively. Oxidative damage assessments manifested that WAF at 26 °C treatment caused much severer oxidative damage of the biomacromolecules (including DNA, proteins, and lipids) than 26 °C or WAF at 16 °C treatments did. Moreover, compared to 26 °C or WAF at 16 °C treatments, WAF at 26 °C treatment induced a significant increase in cellular apoptosis by detecting the caspase-3 activity. Our results revealed that co-exposure to elevated temperature and crude oil could simulate higher ROS levels and subsequently cause much severer oxidative damage and cellular apoptosis than crude oil alone on sea cucumber.
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http://dx.doi.org/10.3390/ijerph18020801DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7832845PMC
January 2021

PIC-GAN: A Parallel Imaging Coupled Generative Adversarial Network for Accelerated Multi-Channel MRI Reconstruction.

Diagnostics (Basel) 2021 Jan 2;11(1). Epub 2021 Jan 2.

Cardiovascular Research Centre, Royal Brompton Hospital, London SW3 6NP, UK.

In this study, we proposed a model combing parallel imaging (PI) with generative adversarial network (GAN) architecture (PIC-GAN) for accelerated multi-channel magnetic resonance imaging (MRI) reconstruction. This model integrated data fidelity and regularization terms into the generator to benefit from multi-coils information and provide an "end-to-end" reconstruction. Besides, to better preserve image details during reconstruction, we combined the adversarial loss with pixel-wise loss in both image and frequency domains. The proposed PIC-GAN framework was evaluated on abdominal and knee MRI images using 2, 4 and 6-fold accelerations with different undersampling patterns. The performance of the PIC-GAN was compared to the sparsity-based parallel imaging (L1-ESPIRiT), the variational network (VN), and conventional GAN with single-channel images as input (zero-filled (ZF)-GAN). Experimental results show that our PIC-GAN can effectively reconstruct multi-channel MR images at a low noise level and improved structure similarity of the reconstructed images. PIC-GAN has yielded the lowest Normalized Mean Square Error (in ×10-5) (PIC-GAN: 0.58 ± 0.37, ZF-GAN: 1.93 ± 1.41, VN: 1.87 ± 1.28, L1-ESPIRiT: 2.49 ± 1.04 for abdominal MRI data and PIC-GAN: 0.80 ± 0.26, ZF-GAN: 0.93 ± 0.29, VN:1.18 ± 0.31, L1-ESPIRiT: 1.28 ± 0.24 for knee MRI data) and the highest Peak Signal to Noise Ratio (PIC-GAN: 34.43 ± 1.92, ZF-GAN: 31.45 ± 4.0, VN: 29.26 ± 2.98, L1-ESPIRiT: 25.40 ± 1.88 for abdominal MRI data and PIC-GAN: 34.10 ± 1.09, ZF-GAN: 31.47 ± 1.05, VN: 30.01 ± 1.01, L1-ESPIRiT: 28.01 ± 0.98 for knee MRI data) compared to ZF-GAN, VN and L1-ESPIRiT with an under-sampling factor of 6. The proposed PIC-GAN framework has shown superior reconstruction performance in terms of reducing aliasing artifacts and restoring tissue structures as compared to other conventional and state-of-the-art reconstruction methods.
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http://dx.doi.org/10.3390/diagnostics11010061DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7824530PMC
January 2021

is a potential marker for the diagnosis of human cervical cancer.

Biomark Med 2021 01 14;15(1):57-67. Epub 2020 Dec 14.

Department of Pathology & Key Laboratory for Xinjiang Endemic & Ethnic Diseases (Ministry of Education) /Department of Pathology, the First Affiliated Hospital, Shihezi University School of Medicine, Xinjiang, 832000, China.

The aim is to study ANXA2 biomarkers for early diagnosis of cervical cancer. The study used bioinformatics analysis and experimental verification of expression in cervical cancer. expression was higher in cancer tissues than in non-cancer tissues (p = 0.002). was expressed in cell membranes of non-cancer tissues, whereas in cancer tissues it was expressed in both the cell membranes and the cytoplasm. Moreover, expression was more pronounced in squamous cell carcinomas. expression decreased overall survival of patients, and the data suggested that protein expression was associated with invasion and migration of tumors. has high specificity and sensitivity as a detection marker for cervical cancer and can assist in the diagnosis of cervical cancer.
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http://dx.doi.org/10.2217/bmm-2020-0629DOI Listing
January 2021

Parallel imaging with a combination of sensitivity encoding and generative adversarial networks.

Quant Imaging Med Surg 2020 Dec;10(12):2260-2273

Human Phenome Institute, Fudan University, Shanghai, China.

Background: Magnetic resonance imaging (MRI) has the limitation of low imaging speed. Acceleration methods using under-sampled k-space data have been widely exploited to improve data acquisition without reducing the image quality. Sensitivity encoding (SENSE) is the most commonly used method for multi-channel imaging. However, SENSE has the drawback of severe g-factor artifacts when the under-sampling factor is high. This paper applies generative adversarial networks (GAN) to remove g-factor artifacts from SENSE reconstructions.

Methods: Our method was evaluated on a public knee database containing 20 healthy participants. We compared our method with conventional GAN using zero-filled (ZF) images as input. Structural similarity (SSIM), peak signal to noise ratio (PSNR), and normalized mean square error (NMSE) were calculated for the assessment of image quality. A paired student's t-test was conducted to compare the image quality metrics between the different methods. Statistical significance was considered at P<0.01.

Results: The proposed method outperformed SENSE, variational network (VN), and ZF + GAN methods in terms of SSIM (SENSE + GAN: 0.81±0.06, SENSE: 0.40±0.07, VN: 0.79±0.06, ZF + GAN: 0.77±0.06), PSNR (SENSE + GAN: 31.90±1.66, SENSE: 22.70±1.99, VN: 31.35±2.01, ZF + GAN: 29.95±1.59), and NMSE (×10) (SENSE + GAN: 0.95±0.34, SENSE: 4.81±1.33, VN: 0.97±0.30, ZF + GAN: 1.60±0.84) with an under-sampling factor of up to 6-fold.

Conclusions: This study demonstrated the feasibility of using GAN to improve the performance of SENSE reconstruction. The improvement of reconstruction is more obvious for higher under-sampling rates, which shows great potential for many clinical applications.
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http://dx.doi.org/10.21037/qims-20-518DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7596399PMC
December 2020

Bacteria responsive polyoxometalates nanocluster strategy to regulate biofilm microenvironments for enhanced synergetic antibiofilm activity and wound healing.

Theranostics 2020 8;10(22):10031-10045. Epub 2020 Aug 8.

College of Chemistry and Environment Protection Engineering, Southwest Minzu University, Chengdu 610041, China.

Nowadays, biofilms that are generated as a result of antibiotic abuse cause serious threats to global public health. Such films are the primary factor that contributes to the failure of antimicrobial treatment. This is due to the fact that the films prevent antibiotic infiltration, escape from innate immune attacks by phagocytes and consequently generate bacterial resistance. Therefore, exploiting novel antibacterial agents or strategies is extremely urgent. Herein, we report a rational construction of a novel biofilm microenvironment (BME)-responsive antibacterial platform that is based on tungsten (W)-polyoxometalate clusters (POMs) to achieve efficient bactericidal effects. On one hand, the acidity and reducibility of a BME could lead to the self-assembly of POMs to produce large aggregates, which favor biofilm accumulation and enhance photothermal conversion under near-infrared (NIR) light irradiation. On the other hand, reduced POM aggregates with BME-induced photothermal-enhanced efficiency also exhibit surprisingly high peroxidase-like activity in the catalysis of bacterial endogenous hydrogen peroxide (HO) to produce abundant reactive oxygen species (ROS). This enhances biofilm elimination and favors antibacterial effects. Most importantly, reduced POMs exhibit the optimal peroxidase-like activity in an acidic BME. Therefore, in addition to providing a prospective antibacterial agent, intelligent acid/reductive dual-responsive POMs will establish a new representative paradigm for the areas of healthcare with minimal side effects.
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http://dx.doi.org/10.7150/thno.49008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7481423PMC
May 2021

A TCM Formula YYWY Inhibits Tumor Growth in Non-Small Cell Lung Cancer and Enhances Immune-Response Through Facilitating the Maturation of Dendritic Cells.

Front Pharmacol 2020 9;11:798. Epub 2020 Jun 9.

Department of Oncology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.

In worldwide, lung cancer has a major socio-economic impact and is one of the most common causes of cancer-related deaths. Current therapies for lung cancer are still quite unsatisfactory, urging for alternative new treatments. Traditional Chinese Medicine (TCM) is currently increasingly popular and exhibits a complicated intervention in cancers therapy. In this study, we evaluated the anti-tumor effect and explored the mechanisms of a TCM formula Yangyinwenyang (YYWY) in non-small cell lung cancer (NSCLC) models. YYWY induced the apoptosis of lung cancer cells . In Lewis NSCLC-bearing mice model, YYWY significantly inhibited the tumor growth. Further, RNA-seq analysis and immunostaining of the tumor tissue implied the critical role of YYWY in the regulation of immune response, especially the dendritic cells (DCs) in the effect of YYWY. Therefore, we focused on DCs, which were the initiator and modulator of the immune response. YYWY facilitated the maturation of DCs through MAPK and NF-κB signaling pathways and promoted the release of the cytokines IFN-γ, interleukin (IL)-1β, IL-2, IL-12, and tumor necrosis factor (TNF)-α by DCs. Moreover, the YYWY-matured DCs enhanced the proliferation of T cells and promoted the differentiation of T cells into T helper Th1 and cytotoxic T cell (CTL). In addition, YYWY increased the ratio of Th1/Th2 (IFN-γ/IL-4 radio). Collectively, our findings clearly suggested that YYWY exerted an anti-tumor effect on NSCLC, at least partially through facilitating the mature DCs to activate the proliferation and differentiation of T cells.
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http://dx.doi.org/10.3389/fphar.2020.00798DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7301756PMC
June 2020

Novel cucurmosin-based immunotoxin targeting programmed cell death 1-ligand 1 with high potency against human tumor in vitro and in vivo.

Cancer Sci 2020 Sep 28;111(9):3184-3194. Epub 2020 Jul 28.

Department of Pharmacology, School of Pharmacy, Fujian Provincial Key Laboratory of Natural Medicine Pharmacology, Fujian Medical University, Fuzhou, China.

Immunotoxins are Ab-cytotoxin chimeric molecules with mighty cytotoxicity. Programmed cell death 1-ligand 1 (PD-L1), is a transmembrane protein expressed mainly in inflammatory tumor tissues and plays a pivotal role in immune escape and tumor progression. Although PD-L1 immune checkpoint therapy has been successful in some cases, many patients have not benefited enough due to primary/secondary resistance. In order to optimize the therapeutic efficacy of anti-PD-L1 mAb, we used durvalumab as the payload and CUS , a type I ribosome-inactivating protein isolated from Cucurbita moschata, as the toxin moiety, to construct PD-L1-specific immunotoxin (named D-CUS ) through the engineered cysteine residue. In vitro, D-CUS selectively killed PD-L1 tumor cells. In vivo studies also showed that D-CUS had obvious antitumor effect on PD-L1 human xenograft tumors in nude mice. In conclusion, in the combination of the toxin with mAb, this study developed a new immunotoxin targeting PD-L1, emphasizing a novel and promising treatment strategy and providing a valuable way to optimize cancer immunotherapy.
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http://dx.doi.org/10.1111/cas.14549DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7469839PMC
September 2020

Correction of out-of-FOV motion artifacts using convolutional neural network.

Magn Reson Imaging 2020 09 25;71:93-102. Epub 2020 May 25.

Institute for Medical Imaging Technology (IMIT), School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China. Electronic address:

Purpose: Subject motion during MRI scan can result in severe degradation of image quality. Existing motion correction algorithms rely on the assumption that no information is missing during motions. However, this assumption does not hold when out-of-FOV motion happens. Currently available algorithms are not able to correct for image artifacts introduced by out-of-FOV motion. The purpose of this study is to demonstrate the feasibility of incorporating convolutional neural network (CNN) derived prior image into solving the out-of-FOV motion problem.

Methods And Materials: A modified U-net network was proposed to correct out-of-FOV motion artifacts by incorporating motion parameters into the loss function. A motion model based data fidelity term was applied in combination with the CNN prediction to further improve the motion correction performance. We trained the CNN on 1113 MPRAGE images with simulated oscillating and sudden motion trajectories, and compared our algorithm to a gradient-based autofocusing (AF) algorithm in both 2D and 3D images. Additional experiment was performed to demonstrate the feasibility of transferring the networks to different dataset. We also evaluated the robustness of this algorithm by adding Gaussian noise to the motion parameters. The motion correction performance was evaluated using mean square error (NMSE), peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM).

Results: The proposed algorithm outperformed AF-based algorithm for both 2D (NMSE: 0.0066 ± 0.0009 vs 0.0141 ± 0.008, P < .01; PSNR: 29.60 ± 0.74 vs 21.71 ± 0.27, P < .01; SSIM: 0.89 ± 0.014 vs 0.73 ± 0.004, P < .01) and 3D imaging (NMSE: 0.0067 ± 0.0008 vs 0.070 ± 0.021, P < .01; PSNR: 32.40 ± 1.63 vs 22.32 ± 2.378, P < .01; SSIM: 0.89 ± 0.01 vs 0.62 ± 0.03, P < .01). Robust reconstruction was achieved with 20% data missed due to the out-of-FOV motion.

Conclusion: In conclusion, the proposed CNN-based motion correction algorithm can significantly reduce out-of-FOV motion artifacts and achieve better image quality compared to AF-based algorithm.
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http://dx.doi.org/10.1016/j.mri.2020.05.004DOI Listing
September 2020

Interfacial modification by multifunctional octocrylene for high efficiency and stable planar perovskite solar cells.

Chem Commun (Camb) 2020 Jun;56(49):6731-6734

School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, China. and Beijing Key Laboratory of Special Melting and Preparation of High-End Metal Materials, University of Science and Technology Beijing, Beijing 100083, China.

Interfacial modification of the perovskite surface with octocrylene (2-ethylhexyl-2-cyano-3,3-diphenyl-2-propenoate, OCT) is capable of enhancing humidity stability and passivating the defects of perovskite films. In this study, octocrylene can be attached to the surface of the perovskite, and the carbonyl group (C[double bond, length as m-dash]O) in octocrylene achieved excellent passivation through the Lewis base electron passivation of Pb2+ ions. By increasing the concentration of the octocrylene/IPA solution, the modified device exhibited an optimal PCE of 20.54% and a steady state output PCE of 19.75%. This study shows that the introduction of octocrylene in the preparation of perovskite could effectively enhance the performance of perovskite solar cells.
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http://dx.doi.org/10.1039/c9cc09075dDOI Listing
June 2020

Prognostic Significance of Matrix Metalloproteinase 14 in Patients with Cancer: a Systematic Review and Meta-Analysis.

Clin Lab 2020 May;66(5)

Background: There is increasing evidence that matrix metalloproteinase 14 (MMP-14) is involved in tumor progression and prognosis. MMP-14 exhibits different expression in patients with various cancers, suggesting that it may be considered as a potential prognostic biomarker for cancer.

Methods: Therefore, this meta-analysis was performed to elucidate the prognostic value and association of MMP-14 over-expression in several types of cancers. Eligible studies based on eligibility criteria from various online databases were searched. The pooled hazard ratios (HRs) with 95% confidence intervals (CIs) for overall survival (OS) were analyzed to determine the prognostic value of MMP-14 using STATA software 12.0.

Results: We identified sixteen applicable studies in this meta-analysis comprising 2,766 samples. Over-expression MMP-14 was significantly correlated with a poor overall survival (OS) outcome in multiple cancers (HR: 2.22; 95% CI: 1.72 - 2.87). Moreover, high levels of MMP-14 were markedly associated with tumor progression and metastasis (HR: 1.83; 95% CI: 1.36 - 2.46). MMP-14 expression was also associated with histological differentiation (OR: 0.37; 95% CI: 0.18 - 0.77).

Conclusions: MMP-14 over-expression suggested aggressive biological behaviors and implied that MMP-14 may be a useful prognostic biomarker in human cancers.
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http://dx.doi.org/10.7754/Clin.Lab.2019.190831DOI Listing
May 2020
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