Publications by authors named "Jie Tian"

1,144 Publications

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Overexpression of the PLK4 Gene as a Novel Strategy for the Treatment of Autosomal Recessive Microcephaly by Improving Centrosomal Dysfunction.

J Mol Neurosci 2021 Jul 16. Epub 2021 Jul 16.

Center of Prenatal Diagnosis, Women and Children's Hospital, Xiamen University, Siming District, 10 Zhenhai Road, 361001, P.R. China, Xiamen, Fujian.

Autosomal recessive microcephaly and chorioretinopathy (MCCRP) is a neurodevelopmental disorder characterized by delayed psychomotor development, growth retardation with dwarfism, and ocular abnormalities, and its occurrence has been found to be closely related to variants of the gene encoding centrosomes. However, the association between centrosomal duplication defects and the etiology of microcephaly syndromes is poorly understood. It is well known that polo-like kinase 4 (PLK4) is a key regulator of centriole duplication, and the abnormalities of centrosomal function caused by its protein variation need to be further explored in the pathogenesis of microcephaly. In our study, we found that a patient with microcephaly and chorioretinopathy harbored compound heterozygous missense variants NM_014264.4: c.2221C > T (p.Gln741*) and NM_014264.4: c.2062 T > C (p.Tyr688His) in the PLK4 gene. Overexpression experiments of the variant PLK4 proteins then showed that the G741 variant rather than the T688H variant had lost centrosomal amplification ability, and the G741 variant but not the T688H variant induced centrosomal replication disorder, which further inhibited cell proliferation, cycle division and cytoskeleton morphology in HeLa cells. Moreover, the overexpression of the two variant proteins had inconsistent effects on the target protein PLK4 by western blot analysis, also indicating that T688H variant overexpression is not functionally equivalent to WT-PLK4 overexpression. Therefore, all data support the idea that the PLK4 mutation induces centriolar duplication disorder and reduces the efficiency of mitosis inducing cell death or cell proliferation in the etiology of microcephaly disorder.
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http://dx.doi.org/10.1007/s12031-021-01881-zDOI Listing
July 2021

Radiopharmaceutical and Eu doped gadolinium oxide nanoparticles mediated triple-excited fluorescence imaging and image-guided surgery.

J Nanobiotechnology 2021 Jul 16;19(1):212. Epub 2021 Jul 16.

CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.

Cerenkov luminescence imaging (CLI) is a novel optical imaging technique that has been applied in clinic using various radionuclides and radiopharmaceuticals. However, clinical application of CLI has been limited by weak optical signal and restricted tissue penetration depth. Various fluorescent probes have been combined with radiopharmaceuticals for improved imaging performances. However, as most of these probes only interact with Cerenkov luminescence (CL), the low photon fluence of CL greatly restricted it's interaction with fluorescent probes for in vivo imaging. Therefore, it is important to develop probes that can effectively convert energy beyond CL such as β and γ to the low energy optical signals. In this study, a Eu doped gadolinium oxide (GdO:Eu) was synthesized and combined with radiopharmaceuticals to achieve a red-shifted optical spectrum with less tissue scattering and enhanced optical signal intensity in this study. The interaction between GdO:Eu and radiopharmaceutical were investigated using F-fluorodeoxyglucose (F-FDG). The ex vivo optical signal intensity of the mixture of GdO:Eu and F-FDG reached 369 times as high as that of CLI using F-FDG alone. To achieve improved biocompatibility, the GdO:Eu nanoparticles were then modified with polyvinyl alcohol (PVA), and the resulted nanoprobe PVA modified GdO:Eu (GdO:[email protected]) was applied in intraoperative tumor imaging. Compared with F-FDG alone, intraoperative administration of GdO:[email protected] and F-FDG combination achieved a much higher tumor-to-normal tissue ratio (TNR, 10.24 ± 2.24 vs. 1.87 ± 0.73, P = 0.0030). The use of GdO:[email protected] and F-FDG also assisted intraoperative detection of tumors that were omitted by preoperative positron emission tomography (PET) imaging. Further experiment of image-guided surgery demonstrated feasibility of image-guided tumor resection using GdO:[email protected] and F-FDG. In summary, GdO:Eu can achieve significantly optimized imaging property when combined with F-FDG in intraoperative tumor imaging and image-guided tumor resection surgery. It is expected that the development of the GdO:Eu nanoparticle will promote investigation and application of novel nanoparticles that can interact with radiopharmaceuticals for improved imaging properties. This work highlighted the impact of the nanoprobe that can be excited by radiopharmaceuticals emitting CL, β, and γ radiation for precisely imaging of tumor and intraoperatively guide tumor resection.
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http://dx.doi.org/10.1186/s12951-021-00920-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8283963PMC
July 2021

Polyacrylamide/Chitosan-Based Conductive Double Network Hydrogels with Outstanding Electrical and Mechanical Performance at Low Temperatures.

ACS Appl Mater Interfaces 2021 Jul 16. Epub 2021 Jul 16.

CAS Key Laboratory of Mechanical Behavior and Design of Materials, Department of Modern Mechanics, University of Science and Technology of China, Hefei 230027, China.

Hydrogel-based electronics have received growing attention because of their great flexibility and stretchability. However, the fabrication of conductive hydrogels with high stretchability, excellent toughness, outstanding sensitivity, and low-temperature stability still remains a great challenge. In this study, a type of conductive hydrogels consisting of a double network (DN) structure is synthesized. The dynamically cross-linked chitosan (CS) and the flexible polyacrylamide network doped with polyaniline constitute the DN through the hydrogen bonds between the hydroxyl, amide, and aniline groups. This type of hydrogels displays excellent mechanical performance, striking conductivity, and remarkable freezing tolerance. The flexible electronic sensors based on the double-network hydrogels demonstrate superior strain sensitivity and linear response on various deformations. Additionally, the good antifreezing property of the hydrogels allows the sensors to exhibit excellent performance at -20 °C.
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http://dx.doi.org/10.1021/acsami.1c08421DOI Listing
July 2021

Association of Plasma Fibrinogen Levels on Postoperative Day 1 with 2-Year Survival of Orthotopic Liver Transplantation for HBV-Related HCC.

Lab Med 2021 Jul 16. Epub 2021 Jul 16.

Department of Intensive Care Unit, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.

Objective: To clarify the prognostic values of hemostatic parameters to predict the survival of patients undergoing orthotopic liver transplantation (OLT) for hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC).

Methods: The data of 182 consecutive adult patients who underwent OLT for HBV-related HCC were subjected to univariate and multivariate analyses.

Results: Ascites and fibrinogen levels on postoperative day (POD) 1 were independent predictors of postoperative 2-year mortality (both P <.05). Kaplan-Meier survival analysis showed that the higher the fibrinogen level on POD 1, the better the 1- and 2-year survival of patients with ascites (P <.05), whereas the fibrinogen level on POD 1 was associated with 1-year (P <.05) but not 2-year survival of patients without ascites.

Conclusion: Fibrinogen on POD 1 is a predictor of 2-year post-OLT survival of patients with HBV-related HCC with ascites.
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http://dx.doi.org/10.1093/labmed/lmab052DOI Listing
July 2021

A review of the application of machine learning in molecular imaging.

Ann Transl Med 2021 May;9(9):825

Peking University First Hospital, Beijing, China.

Molecular imaging (MI) is a science that uses imaging methods to reflect the changes of molecular level in living state and conduct qualitative and quantitative studies on its biological behaviors in imaging. Optical molecular imaging (OMI) and nuclear medical imaging are two key research fields of MI. OMI technology refers to the optical information generated by the imaging target (such as tumors) due to drug intervention and other reasons. By collecting the optical information, researchers can track the motion trajectory of the imaging target at the molecular level. Owing to its high specificity and sensitivity, OMI has been widely used in preclinical research and clinical surgery. Nuclear medical imaging mainly detects ionizing radiation emitted by radioactive substances. It can provide molecular information for early diagnosis, effective treatment and basic research of diseases, which has become one of the frontiers and hot topics in the field of medicine in the world today. Both OMI and nuclear medical imaging technology require a lot of data processing and analysis. In recent years, artificial intelligence technology, especially neural network-based machine learning (ML) technology, has been widely used in MI because of its powerful data processing capability. It provides a feasible strategy to deal with large and complex data for the requirement of MI. In this review, we will focus on the applications of ML methods in OMI and nuclear medical imaging.
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http://dx.doi.org/10.21037/atm-20-5877DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8246214PMC
May 2021

The active sites of Cu-ZnO catalysts for water gas shift and CO hydrogenation reactions.

Nat Commun 2021 Jul 15;12(1):4331. Epub 2021 Jul 15.

Hefei National Laboratory for Physical Sciences at the Microscale, Key Laboratory of Surface and Interface Chemistry and Energy Catalysis of Anhui Higher Education Institutes, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, China.

Cu-ZnO-AlO catalysts are used as the industrial catalysts for water gas shift (WGS) and CO hydrogenation to methanol reactions. Herein, via a comprehensive experimental and theoretical calculation study of a series of ZnO/Cu nanocrystals inverse catalysts with well-defined Cu structures, we report that the ZnO-Cu catalysts undergo Cu structure-dependent and reaction-sensitive in situ restructuring during WGS and CO hydrogenation reactions under typical reaction conditions, forming the active sites of Cu-hydroxylated ZnO ensemble and CuZn alloy, respectively. These results provide insights into the active sites of Cu-ZnO catalysts for the WGS and CO hydrogenation reactions and reveal the Cu structural effects, and offer the feasible guideline for optimizing the structures of Cu-ZnO-AlO catalysts.
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http://dx.doi.org/10.1038/s41467-021-24621-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8282834PMC
July 2021

Boosting photoelectrochemical efficiency by near-infrared-active lattice-matched morphological heterojunctions.

Nat Commun 2021 Jul 14;12(1):4296. Epub 2021 Jul 14.

Department of Electrical and Computer Engineering, University of Toronto, 35 St George Street, Toronto, ON, Canada.

Photoelectrochemical catalysis is an attractive way to provide direct hydrogen production from solar energy. However, solar conversion efficiencies are hindered by the fact that light harvesting has so far been of limited efficiency in the near-infrared region as compared to that in the visible and ultraviolet regions. Here we introduce near-infrared-active photoanodes that feature lattice-matched morphological hetero-nanostructures, a strategy that improves energy conversion efficiency by increasing light-harvesting spectral range and charge separation efficiency simultaneously. Specifically, we demonstrate a near-infrared-active morphological heterojunction comprised of BiSeTe ternary alloy nanotubes and ultrathin nanosheets. The heterojunction's hierarchical nanostructure separates charges at the lattice-matched interface of the two morphological components, preventing further carrier recombination. As a result, the photoanodes achieve an incident photon-to-current conversion efficiency of 36% at 800 nm in an electrolyte solution containing hole scavengers without a co-catalyst.
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http://dx.doi.org/10.1038/s41467-021-24569-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8280183PMC
July 2021

Specific Borrmann classification in advanced gastric cancer by an ensemble multilayer perceptron network: a multi-center research.

Med Phys 2021 Jul 14. Epub 2021 Jul 14.

CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.

Purpose: Borrmann classification in advanced gastric cancer (AGC) is necessarily associated with personalized surgical strategy and prognosis. But few radiomics researches have focused on specific Borrmann classification, and there is yet no consensus regarding what machine learning methods should be the most effective.

Methods: A combined size of 889 AGC patients were retrospectively enrolled from two centers. Radiomic features were extracted from tumors manually delineated on preoperative computed tomography images. Two classification experiments (Borrmann I/II/III vs. IV and Borrmann II vs. III) were conducted. In each task, we combined three common feature selection methods and five typical machine learning classifiers to construct 15 basic classification models, and then fed the 15 predictions to a designed multilayer perceptron (MLP) network.

Results: In internal and external validation cohorts, the proposed ensemble MLP yielded good performance with area under curves of 0.767 and 0.702 for Borrmann I/II/III vs. IV, as well as 0.768 and 0.731 for Borrmann II vs. III. Considering the imbalanced distribution of four Borrmann types (I, 2.9%; II, 12.8%; III, 69.5%; IV, 14.7%), the ensemble MLP surpassed the overfitting barrier and attained fine specificity (0.667 and 0.750 for Borrmann I/II/III vs. IV; 0.714 and 0.620 for Borrmann II vs. III) and sensitivity (0.795 and 0.610 for Borrmann I/II/III vs. IV; 0.652 and 0.703 for Borrmann II vs. III). Also, survival analysis showed that patients could be significantly risk stratified by MLP predicted types in both experiments (P < 0.0001, log-rank test).

Conclusions: This study proposed an MLP-based ensemble learning architecture, which could identify Borrmann type IV automatically and improve the differentiation of Borrmann type II from III. The study provided a new view for specific Borrmann classification in clinical practice.
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http://dx.doi.org/10.1002/mp.15094DOI Listing
July 2021

Intrinsic Room-Temperature Ferromagnetism in VC MXene Nanosheets.

ACS Appl Mater Interfaces 2021 Jul 8;13(28):33363-33370. Epub 2021 Jul 8.

National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei 230029, P. R. China.

Two-dimensional (2D) materials with intrinsic magnetic properties are intensively explored due to their potential applications in low-power-consumption electronics and spintronics. To date, only a handful of intrinsic magnetic 2D materials have been reported. Here, we report a realization of intrinsic ferromagnetic behavior in 2D VC MXene nanosheets through layer mismatch engineering. The VC MXene nanosheets with a small-angle twisting show a robust intrinsic ferromagnetic response with a saturation magnetic moment of 0.013 emu/g at room temperature. An in-depth study has been performed by X-ray absorption spectroscopy as well as electron paramagnetic resonance (EPR) and photoelectron spectroscopy analyses. It has been revealed that the symmetry-broken interlayer twisting reduced the degeneracy of V 3d states and the van Hove singularity. This led to a redistribution of the density of electronic states near the Fermi level and consequently activated the Stoner ferromagnetism with improved density of itinerant d electrons. This work highlights VC MXene as a promising intrinsic room-temperature ferromagnetic material with potential applications in spintronics or spin-based electronics.
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http://dx.doi.org/10.1021/acsami.1c07906DOI Listing
July 2021

3D deep learning model for the pretreatment evaluation of treatment response in locally advanced TESCC: A prospective study.

Int J Radiat Oncol Biol Phys 2021 Jul 3. Epub 2021 Jul 3.

Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, China; Shandong Medical Imaging and Radiotherapy Engineering Center (SMIREC), Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, China. Electronic address:

Purpose: To develop and validate a pretreatment CT-based deep-learning (DL) model for predicting the treatment response to concurrent chemoradiotherapy (CCRT) among patients with locally advanced thoracic esophageal squamous cell carcinoma (TESCC).

Materials And Methods: We conducted a prospective, multicenter study on the therapeutic efficacy of CCRT among TESCC patients across 9 hospitals in China (ChiCTR**********). A total of 306 patients with locally advanced TESCC diagnosed by histopathology from August 2015 to May 2020 were included in this study. A 3D deep-learning radiomics model (3D-DLRM) was developed and validated based on pretreatment CT images to predict the response to CCRT. Furthermore, the prediction performance of the newly developed 3D-DLRM was analyzed according to 3 categories: radiotherapy plan, radiation field, and prescription dose used.

Results: The 3D-DLRM achieved good prediction performance, with areas under the receiver operating characteristic curve (AUCs) of 0.897 (95% CI 0.840-0.959) for the training cohort and 0.833 (95% CI 0.654-1.000) for the validation cohort. Specifically, the 3D-DLRM accurately predicted patients who would not respond to CCRT, with a positive predictive value (PPV) of 100% for the validation cohort. Moreover, the 3D-DLRM performed well in all 3 categories, each with AUCs > 0.8 and PPVs of approximately 100%.

Conclusion: The proposed pretreatment CT-based 3D-DLRM provides a potential tool for predicting the response to CCRT among patients with locally advanced TESCC. With the help of precise pretreatment prediction, we may guide the individualized treatment of patients and improve survival.
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http://dx.doi.org/10.1016/j.ijrobp.2021.06.033DOI Listing
July 2021

Structure-Based Optimization of 3-Phenyl--(2-(3-phenylureido)ethyl)thiophene-2-sulfonamide Derivatives as Selective Mcl-1 Inhibitors.

J Med Chem 2021 Jul 6;64(14):10260-10285. Epub 2021 Jul 6.

Department of Medicinal Chemistry, School of Pharmacy, Fudan University, 826 Zhangheng Road, Shanghai 201203, People's Republic of China.

Selective Mcl-1 inhibitors may overcome the drug resistance caused by current anti-apoptotic Bcl-2 protein inhibitors in tumors with Mcl-1 overexpression. Based on previously discovered compounds with a 3-phenylthiophene-2-sulfonamide core moiety, in this work, we have obtained new compounds with improved binding affinity and/or selectivity under the guidance of structure-based design. The most potent compounds achieved sub-micromolar binding affinities to Mcl-1 ( ∼ 0.4 μM) and good cytotoxicity (IC < 10 μM) on several tumor cells. N-heteronuclear single-quantum coherence NMR spectra suggested that these compounds bound to the BH3-binding groove on Mcl-1. Several cellular assays revealed that as well as its precursor effectively induced caspase-dependent apoptosis, and their target engagement at Mcl-1 was confirmed by co-immunoprecipitation experiments. Treatment with at 50 mg/kg every 2 days on an RS4;11 xenograft mouse model for 22 days led to 75% reduction in tumor volume without body weight loss.
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http://dx.doi.org/10.1021/acs.jmedchem.1c00690DOI Listing
July 2021

The burden of hand, foot, and mouth disease among children under different vaccination scenarios in China: a dynamic modelling study.

BMC Infect Dis 2021 Jul 5;21(1):650. Epub 2021 Jul 5.

School of Public Health, Fudan University, Shanghai, 200032, China.

Background: Hand, foot, and mouth disease (HFMD) is a common illness in young children. A monovalent vaccine has been developed in China protecting against enterovirus-71, bivalent vaccines preventing HFMD caused by two viruses are under development.

Objective: To predict and compare the incidence of HFMD under different vaccination scenarios in China.

Methods: We developed a compartmental model to capture enterovirus transmission and the natural history of HFMD in children aged 0-5, and calibrated to reported cases in the same age-group from 2015 to 2018. We compared the following vaccination scenarios: different combinations of monovalent and bivalent vaccine; a program of constant vaccination to that of pulse vaccination prior to seasonal outbreaks.

Results: We estimate 1,982,819, 2,258,846, 1,948,522 and 2,398,566 cases from 2015 to 2018. Increased coverage of monovalent vaccine from 0 to 80% is predicted to decrease the cases by 797,262 (49.1%). Use of bivalent vaccine at an 80% coverage level would decrease the cases by 828,560. Use of a 2.0× pulse vaccination for the bivalent vaccine in addition to 80% coverage would reduce cases by over one million. The estimated R for HFMD in 2015-2018 was 1.08, 1.10, 1.35 and 1.17.

Conclusions: Our results point to the benefit of bivalent vaccine and using a pulse vaccination in specific months over routine vaccination. Other ways to control HFMD include isolation of patients in the early stage of dissemination, more frequent hand-washing and ventilation, and better treatment options for patients.
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http://dx.doi.org/10.1186/s12879-021-06157-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8259139PMC
July 2021

Deep Learning with Quantitative Features of Magnetic Resonance Images to Predict Biochemical Recurrence of Radical Prostatectomy: A Multi-Center Study.

Cancers (Basel) 2021 Jun 21;13(12). Epub 2021 Jun 21.

Department of Urology, Peking University Third Hospital, Peking University, Beijing 100191, China.

Biochemical recurrence (BCR) occurs in up to 27% of patients after radical prostatectomy (RP) and often compromises oncologic survival. To determine whether imaging signatures on clinical prostate magnetic resonance imaging (MRI) could noninvasively characterize biochemical recurrence and optimize treatment. We retrospectively enrolled 485 patients underwent RP from 2010 to 2017 in three institutions. Quantitative and interpretable features were extracted from T2 delineated tumors. Deep learning-based survival analysis was then applied to develop the deep-radiomic signature (DRS-BCR). The model's performance was further evaluated, in comparison with conventional clinical models. The model achieved C-index of 0.802 in both primary and validating cohorts, outweighed the CAPRA-S score (0.677), NCCN model (0.586) and Gleason grade group systems (0.583). With application analysis, DRS-BCR model can significantly reduce false-positive predictions, so that nearly one-third of patients could benefit from the model by avoiding overtreatments. The deep learning-based survival analysis assisted quantitative image features from MRI performed well in prediction for BCR and has significant potential in optimizing systemic neoadjuvant or adjuvant therapies for prostate cancer patients.
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http://dx.doi.org/10.3390/cancers13123098DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8234539PMC
June 2021

Flexible four-dimensional optical data storage enabled by single-pulse femtosecond laser irradiation in thermoplastic polyurethane.

Opt Lett 2021 Jul;46(13):3211-3214

Herein, a flexible four-dimensional optical data storage technique is demonstrated by harnessing ultrafast laser-induced fluorophores in thermoplastic polyurethane. By modulating the pulse energy of a 515 nm laser, data voxels with multilevel fluorescence signals can be generated and encoded. The readout accuracy of the encoded multilayer information remains at 92.2% after 50 bending cycles, demonstrating the feasibility of our technology for data recording based on a roll-to-roll method. The generation of fluorophores by only a single femtosecond laser pulse provides the ability to record data beyond 20 MB/s.
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http://dx.doi.org/10.1364/OL.432092DOI Listing
July 2021

Left Anterior Fascicular Block After Transcatheter Closure of Ventricular Septal Defect in Children.

Front Cardiovasc Med 2021 11;8:609531. Epub 2021 Jun 11.

Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China.

Arrhythmia is the most common complication after transcatheter closure of a ventricular septal defect (VSD). However, the effects of postprocedural left anterior fascicular block are not clear. This study presents the clinical characteristics, prognosis, and related risk factors of left anterior fascicular block after transcatheter closure of a VSD in children. The clinical and follow-up data of the patients in the Heart Center of Children's Hospital of Chongqing Medical University from June 2009 to October 2018 were reviewed. And 30 cases were eligible out of all 1,371 cases. An electrocardiogram showed a left anterior fascicular block within 3 days, and most patients gradually returned to normal within 1-2 years, showing a dynamic change. Left ventricular end-diastolic dimension -score ranged from -2 to 2 in all children, and no decrease of left ventricular ejection fraction was found in all children. The high ratio between VSD size and body surface area [ < 0.05, odds ratio (OR) 2.6, 95% CI: 1.136-6.113] and large diameter difference between the occluder size and VSD size ( < 0.05, OR 2.1, 95% CI: 1.036-4.609) were independent risk factors for postprocedural left anterior fascicular block. The incidence of postprocedural left anterior fascicular block is not that low, and the overall prognosis is quite good at the current follow-up stage. No progressive severity has been found, such as complete left bundle branch block, double (triple) bundle branch block, and atrioventricular block, to have an influence on cardiac systolic and diastolic function.
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http://dx.doi.org/10.3389/fcvm.2021.609531DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8226158PMC
June 2021

Deep learning radiomics-based prediction of distant metastasis in patients with locally advanced rectal cancer after neoadjuvant chemoradiotherapy: A multicentre study.

EBioMedicine 2021 Jun 19;69:103442. Epub 2021 Jun 19.

Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China; CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing 100191, China; Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology, Beijing 100191, China. Electronic address:

Background: Accurate predictions of distant metastasis (DM) in locally advanced rectal cancer (LARC) patients receiving neoadjuvant chemoradiotherapy (nCRT) are helpful in developing appropriate treatment plans. This study aimed to perform DM prediction through deep learning radiomics.

Methods: We retrospectively sampled 235 patients receiving nCRT with the minimum 36 months' postoperative follow-up from three hospitals. Through transfer learning, a deep learning radiomic signature (DLRS) based on multiparametric magnetic resonance imaging (MRI) was constructed. A nomogram was established integrating deep MRI information and clinicopathologic factors for better prediction. Harrell's concordance index (C-index) and time-dependent receiver operating characteristic (ROC) were used as performance metrics. Furthermore, the risk of DM in patients with different response to nCRT was evaluated with the nomogram.

Findings: DLRS performed well in DM prediction, with a C-index of 0·747 and an area under curve (AUC) at three years of 0·894 in the validation cohort. The performance of nomogram was better, with a C-index of 0·775. In addition, the nomogram could stratify patients with different responses to nCRT into high- and low-risk groups of DM (P < 0·05).

Interpretation: MRI-based deep learning radiomics had potential in predicting the DM of LARC patients receiving nCRT and could help evaluate the risk of DM in patients who have different responses to nCRT.

Funding: The funding bodies that contributed to this study are listed in the Acknowledgements section.
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http://dx.doi.org/10.1016/j.ebiom.2021.103442DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8237293PMC
June 2021

Non-invasive measurement of PD-L1 status and prediction of immunotherapy response using deep learning of PET/CT images.

J Immunother Cancer 2021 Jun;9(6)

Department of Thoracic Oncology, Moffitt Cancer Center, Tampa, Florida, USA

Background: Currently, only a fraction of patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) experience a durable clinical benefit (DCB). According to NCCN guidelines, Programmed death-ligand 1 (PD-L1) expression status determined by immunohistochemistry (IHC) of biopsies is the only clinically approved companion biomarker to trigger the use of ICI therapy. Based on prior work showing a relationship between quantitative imaging and gene expression, we hypothesize that quantitative imaging (radiomics) can provide an alternative surrogate for PD-L1 expression status in clinical decision support.

Methods: F-FDG-PET/CT images and clinical data were curated from 697 patients with NSCLC from three institutions and these were analyzed using a small-residual-convolutional-network (SResCNN) to develop a deeply learned score (DLS) to predict the PD-L1 expression status. This developed model was further used to predict DCB, progression-free survival (PFS), and overall survival (OS) in two retrospective and one prospective test cohorts of ICI-treated patients with advanced stage NSCLC.

Results: The PD-L1 DLS significantly discriminated between PD-L1 positive and negative patients (area under receiver operating characteristics curve ≥0.82 in the training, validation, and two external test cohorts). Importantly, the DLS was indistinguishable from IHC-derived PD-L1 status in predicting PFS and OS, suggesting the utility of DLS as a surrogate for IHC. A score generated by combining the DLS with clinical characteristics was able to accurately (C-indexes of 0.70-0.87) predict DCB, PFS, and OS in retrospective training, prospective testing and external validation cohorts.

Conclusion: Hence, we propose DLS as a surrogate or substitute for IHC-determined PD-L1 measurement to guide individual pretherapy decisions pending in larger prospective trials.
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http://dx.doi.org/10.1136/jitc-2020-002118DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8211060PMC
June 2021

Multi-focus Network to Decode Imaging Phenotype for Overall Survival Prediction of Gastric Cancer Patients.

IEEE J Biomed Health Inform 2021 Jun 8;PP. Epub 2021 Jun 8.

Gastric cancer (GC) is the third leading cause of cancer-associated deaths globally. Accurate risk prediction of the overall survival (OS) for GC patients shows significant prognostic value, which helps identify and classify patients into different risk groups to benefit from personalized treatment. Many methods based on machine learning algorithms have been widely explored to predict the risk of OS accurately. However, the accuracy of risk prediction has been limited and remains a challenge with existing methods. Few studies have proposed a framework and pay attention to the low-level and high-level features separately for the risk prediction of OS based on computed tomography images of GC patients. To achieve high accuracy, we propose a multi-focus fusion convolutional neural network. The network focuses on low-level and high-level features, where a subnet to focus on lower-level features and the other enhanced subnet with lateral connection to focus on higher-level semantic features. Three independent datasets of 640 GC patients are used to assess our method. Our proposed network is evaluated by metrics of the concordance index and hazard ratio. Our network outperforms existing methods with the highest concordance index and hazard ratio in independent validation and test sets. Our results prove that our architecture can unify the separate low-level and high-level features into a single framework, and can be a powerful method for accurate risk prediction of OS.
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http://dx.doi.org/10.1109/JBHI.2021.3087634DOI Listing
June 2021

An enhanced method for nucleic acid detection with CRISPR-Cas12a using phosphorothioate modified primers and optimized gold-nanopaticle strip.

Bioact Mater 2021 Dec 15;6(12):4580-4590. Epub 2021 May 15.

Yaneng Biotech, Co., Ltd, Fosun Pharma, Shenzhen 518100, China.

CRISPR-Cas12a system has been shown promising for nucleic acid diagnostics due to its rapid, portable and accurate features. However, cleavage of the amplicons and primers by the - and -activity of Cas12a hinders the attempts to integrate the amplification and detection into a single reaction. Through phosphorothioate modification of primers, we realized onepot detection with high sensitivity using plasmids of SARS-CoV-2, HPV16 and HPV18. We also identified the activated Cas12a has a much higher affinity to C nucleotide-rich reporter than others. By applying such reporters, the reaction time required for a lateral-flow readout was significantly reduced. Furthermore, to improve the specificity of the strip-based assay, we created a novel reporter and, when combined with a customized gold-nanopaticle strip, the readout was greatly enhanced owing to the elimination of the nonspecific signal. This established system, termed argeting DNA by Cas12a-based ye ight esting in an nepot eaction (TESTOR), was validated using clinical cervical scrape samples for human papillomaviruses (HPVs) detection. Our system represents a general approach to integrating the nucleic acid amplification and detection into a single reaction in CRISPR-Cas systems, highlighting its potential as a rapid, portable and accurate detection platform of nucleic acids.
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http://dx.doi.org/10.1016/j.bioactmat.2021.05.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8141609PMC
December 2021

Prediction of Microvascular Invasion in Hepatocellular Carcinoma via Deep Learning: A Multi-Center and Prospective Validation Study.

Cancers (Basel) 2021 May 14;13(10). Epub 2021 May 14.

Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

Microvascular invasion (MVI) is a critical risk factor for postoperative recurrence of hepatocellular carcinoma (HCC). Preknowledge of MVI would assist tailored surgery planning in HCC management. In this multicenter study, we aimed to explore the validity of deep learning (DL) in MVI prediction using two imaging modalities-contrast-enhanced computed tomography (CE-CT) and gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI). A total of 750 HCCs were enrolled from five Chinese tertiary hospitals. Retrospective CE-CT ( = 306, collected between March, 2013 and July, 2019) and EOB-MRI ( = 329, collected between March, 2012 and March, 2019) data were used to train two DL models, respectively. Prospective external validation ( = 115, collected between July, 2015 and February, 2018) was performed to assess the developed models. Furthermore, DL-based attention maps were utilized to visualize high-risk MVI regions. Our findings revealed that the EOB-MRI-based DL model achieved superior prediction outcome to the CE-CT-based DL model (area under receiver operating characteristics curve (AUC): 0.812 vs. 0.736, = 0.038; sensitivity: 70.4% vs. 57.4%, = 0.015; specificity: 80.3% vs. 86.9%, = 0.052). DL attention maps could visualize peritumoral high-risk areas with genuine histopathologic confirmation. Both DL models could stratify high and low-risk groups regarding progression free survival and overall survival ( < 0.05). Thus, DL can be an efficient tool for MVI prediction, and EOB-MRI was proven to be the modality with advantage for MVI assessment than CE-CT.
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http://dx.doi.org/10.3390/cancers13102368DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8156235PMC
May 2021

Two generation reproduction toxicity study of GmDREB3 gene modified wheat in Wistar rats.

Food Chem Toxicol 2021 Jul 29;153:112310. Epub 2021 May 29.

Hubei Provincial Key Laboratory for Applied Toxicology, Hubei Provincial Center for Disease Control and Prevention, Wuhan, 430079, China. Electronic address:

To study reproductive toxicity of gene modified wheat generated by introducing DREB3 (drought response element binding protein 3) gene, Wistar rats of were allocated into 3 groups and fed with DREB3 gene modified wheat mixture diet (GM group), non-gene modified wheat mixture diet (Non-GM group) and AIN-93 diet (Control group) from parental generation (F0) to the second offspring (F2). GM wheat and Non-GM wheat, Jimai22, were both formulated into diets at a ratio of 69.55% according to AIN93 diet for rodent animals. Compared with non-GM group, no biologically related differences were observed in GM group rats with respect to reproductive performance such as fertility rate, gestation rate, mean duration, hormone level, reproductive organ pathology and developmental parameters such as body weight, body length, food consumption, neuropathy, behavior, immunotoxicity, hematology and serum chemistry. In conclusion, no adverse effect were found relevant to GM wheat in the two generation reproduction toxicity study, indicating the GM wheat is a safe alternative for its counterpart wheat regarding to reproduction toxicity.
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http://dx.doi.org/10.1016/j.fct.2021.112310DOI Listing
July 2021

Mix Contrast for COVID-19 Mild-to-critical Prediction.

IEEE Trans Biomed Eng 2021 Jun 1;PP. Epub 2021 Jun 1.

Objective: In a few patients with mild COVID-19, there is a possibility of the infection becoming severe or critical in the future. This work aims to identify high-risk patients who have a high probability of changing from mild to critical COVID-19 (only account for 5% of cases). Methods: Using traditional convolutional neural networks for classification may not be suitable to identify this 5% of high-risk patients from an entire dataset due to the highly imbalanced label distribution. To address this problem, we propose a Mix Contrast (MixCo) model, which matches original features with mixed features for contrastive learning. Three modules are proposed for training MixCo: 1) a cumulative learning strategy for synthesizing the mixed feature; 2) a commutative feature combination module for learning the commutative law of feature concatenation; 3) a united pairwise loss assigning adaptive weights for sample pairs with different class anchors based on their current optimization status. Results: We collect a multi-center computed tomography dataset including 918 confirmed COVID-19 patients from four hospitals and evaluate the proposed method on both the COVID-19 mild-to-critical prediction and COVID-19 diagnosis tasks. For mild-to-critical prediction, the experimental results show a recall of 0.80 and a specificity of 0.815. For diagnosis, the model shows comparable results with deep neural networks using a large dataset. Our method demonstrates improvements when the amount of training data is small or imbalanced. Significance: Identifying mild-to-critical COVID-19 patients is important for early prevention and personalized treatment planning.
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http://dx.doi.org/10.1109/TBME.2021.3085576DOI Listing
June 2021

Drug preconcentration and direct quantification in biofluids using 3D-Printed paper cartridge.

Biosens Bioelectron 2021 Oct 13;189:113266. Epub 2021 May 13.

School of Life Science and Technology, Xidian University, Xi'an, 710126, Shaanxi, PR China; Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, PR China. Electronic address:

Drug detection in biofluids has always been great importance for clinical diagnosis. Many detection technologies such as chromatography-mass spectrometry, have been applied to the detection of drugs. However, these technologies required multi-step operations, including complicated and time-consuming pretreatment processes and operations of bulky detection instruments, significantly limiting development of drug detection in clinical diagnosis. Herein, a portable 3D-printed paper cartridge was fabricated for fast sample preconcentration and direct drugs quantitative detection in biofluids by a portable Raman spectrometer. This cartridge contained both paper tip with silver nanowires to preconcentrate samples and achieve surface-enhanced Raman Scattering (SERS) measurement, and 3D-printed cartridge to build enclosed environment for the improvement of detection, which cost only one dollar. The preconcentration ability of the cartridge was up to 18.13-fold fluorescence enhancement and compared to the non-preconcentration method, it achieved 9.93-fold improvement of SERS performance. The anticancer drug of epirubicin hydrochloride, cyclophosphamide and their mixtures were quantitatively detected in the bovine serum or artificial urine. The integrated detection procedure required only 1 h, including sample pretreatment and preconcentration, drying, SERS measurements, and quantification analysis. This 3D-printed paper cartridge constituted a portable detection platform that would be potentially a practical and point-of-care detection tool for drug preconcentration and quantification on the clinical diagnosis.
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http://dx.doi.org/10.1016/j.bios.2021.113266DOI Listing
October 2021

Visualizing Tumors in Real Time: A Highly Sensitive PSMA Probe for NIR-II Imaging and Intraoperative Tumor Resection.

J Med Chem 2021 06 28;64(11):7735-7745. Epub 2021 May 28.

Key Laboratory of Radiopharmaceuticals, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China.

Owing to the complex anatomical structure, precise resection of a tumor while maintaining adjacent tissue is a challenge in radical prostatectomy for prostate cancer (PCa). Optical imaging in near-infrared window II (NIR-II) is a promising technology for intraoperative guidance, whereas there is no available probe for PCa yet. In this article, a novel probe () bearing two prostate-specific membrane antigen (PSMA) binding motifs was developed, displaying excellent optical properties (λ = 1092 nm) and ultrahigh affinity ( = 80 pM) toward PSMA. The tumor was visualized with high resolution (tissue-to-normal tissue ratio = 7.62 ± 1.05) and clear margin by NIR-II imaging using in a mouse model. During the tumor resection, residual tumors missed by visible inspection were detected by the real-time imaging. Overall, displayed excellent performance in delineating the tumor margin and detecting residual tumors, demonstrating promising potential for precise PCa tumor resection in clinical practice.
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http://dx.doi.org/10.1021/acs.jmedchem.1c00444DOI Listing
June 2021

Active steering control based on preview theory for articulated heavy vehicles.

PLoS One 2021 25;16(5):e0252098. Epub 2021 May 25.

School of Public Administration, Nanjing University of Finance and Economics, Nanjing, China.

This paper investigates the active steering control of the tractor and the trailer for the articulated heavy vehicle (AHV) to improve its high-speed lateral stability and low-speed path following. The four-degree-of-freedom (4-DOF) single track dynamic model of the AHV with a front-wheel steered trailer is established. Considering that the road information at the driver's focus is the most clear and those away from the focus blurred, a new kind controller based on the fractional calculus, i.e., a focus preview controller is designed to provide the steering input for the tractor to make it travel along the desired path. In addition, the active steering controllers based on the linear quadratic regulator (LQR) and single-point preview controller respectively are also proposed for the trailer. However, the latter is designed on the basis of the articulation angle between the tractor and trailer, inspired by the idea of the driver's single-point preview controller. Finally, the single lane change maneuver and 90o turn maneuver are carried out. And the simulation results show that compared with the single-point preview controller, the new kind preview controller for the tractor can have good high speed maneuvering stability and low speed path tracking ability by adjusting the fractional order of the controller. On this basis, three different AHVs with the same tractor are simulated and the simulation results show that the AHV whose trailer adopts the single-point preview controller has better high-speed lateral stability and low-speed path tracking than the AHV whose trailer adopts the LQR controller.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0252098PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8148313PMC
May 2021

Patient-level Prediction of Multi-classification Task at Prostate MRI based on End-to-End Framework learning from Diagnostic Logic of Radiologists.

IEEE Trans Biomed Eng 2021 May 20;PP. Epub 2021 May 20.

The grade groups (GGs) of Gleason scores (Gs) is the most critical indicator in the clinical diagnosis and treatment system of prostate cancer. End-to-end method for stratifying the patient-level pathological appearance of prostate cancer (PCa) in magnetic resonance (MRI) are of high demand for clinical decision. Existing methods typically employ a statistical method for integrating slice-level results to a patient-level result, which ignores the asymmetric use of ground truth (GT) and overall optimization. Therefore, more domain knowledge (e.g. diagnostic logic of radiologists) needs to be incorporated into the design of the framework. The patient-level GT is necessary to be logically assigned to each slice of a MRI to achieve joint optimization between slice-level analysis and patient-level decision-making. In this paper, we propose a framework (PCa-GGNet-v2) that learns from radiologists to capture signs in a separate two-dimensional (2-D) space of MRI and further associate them for the overall decision, where all steps are optimized jointly in an end-to-end trainable way. In the training phase, patient-level prediction is transferred from weak supervision to supervision with GT. An association route records the attentional slice for reweighting loss of MRI slices and interpretability. We evaluate our method in an in-house multi-center dataset (N=570) and PROSTATEx (N=204), which yields five-classification accuracy over 80% and AUC of 0.804 at patient-level respectively. Our method reveals the state-of-the-art performance for patient-level multi-classification task to personalized medicine.
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http://dx.doi.org/10.1109/TBME.2021.3082176DOI Listing
May 2021

Contrast-enhanced ultrasound molecular imaging of activated platelets in the progression of atherosclerosis using microbubbles bearing the von Willebrand factor A1 domain.

Exp Ther Med 2021 Jul 3;22(1):721. Epub 2021 May 3.

Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China.

Platelet-endothelial interactions have been linked to increased inflammatory activation and a prothrombotic state in atherosclerosis. The interaction between von Willebrand factor (vWF)-A1 domain and platelet glycoprotein (GP) Ib/IX plays a significant role in mediating the adhesion of platelets to the injured endothelium. In the present study, contrast-enhanced ultrasound (CEU) molecular imaging with microbubbles bearing the vWF-A1 domain was performed to non-invasively monitor activated platelets on the vascular endothelium in the procession of atherosclerosis. A targeted CEU contrast agent was prepared by attaching the vWF-A1 domain to the shell of microbubbles (Mb). Rat isotype control antibody was used to produce control (Mb) microbubbles. The binding of Mb and Mb to activated platelets was assessed in flow chamber experiments. Apolipoprotein E (ApoE) deficient mice were studied as a model of atherosclerosis. At 8, 16 and 32 weeks of age, CEU molecular imaging of the proximal aorta with Mb and Mb was performed and the imaging signals from microbubbles were quantified. Atherosclerotic lesion severity and platelets on the endothelial surface were assessed by histology and immunohistochemistry. In flow chamber studies, attachment of Mb to activated platelets on culture dishes was significantly greater than that of Mb across a range of shear stresses (P<0.05). The attachment of Mb was sparse and not related to the aggregated platelets. As lesion development progressed in the ApoE mice, molecular imaging of activated platelets demonstrated selective signal enhancement of Mb (P<0.05 vs. Mb) at all ages. Selective signal enhancement from Mb increased from 8 to 32 weeks of age. Immunohistochemistry for GPIIb revealed the presence of platelets on the endothelial cell surface in each group of ApoE mice and that the degree of platelet deposits was age-dependent. The results of the present study indicated that non-invasive CEU molecular imaging with targeted microbubbles bearing the vWF-A1 domain could not only detect activated platelets on the vascular endothelium but also indicate lesion severity in atherosclerosis.
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http://dx.doi.org/10.3892/etm.2021.10153DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8120515PMC
July 2021

Intraoperative molecular imaging clinical trials: a review of 2020 conference proceedings.

J Biomed Opt 2021 May;26(5)

Perelman School of Medicine, Univ. of Pennsylvania, United States.

Significance: Surgery is often paramount in the management of many solid organ malignancies because optimal resection is a major factor in disease-specific survival. Cancer surgery has multiple challenges including localizing small lesions, ensuring negative surgical margins around a tumor, adequately staging patients by discriminating positive lymph nodes, and identifying potential synchronous cancers. Intraoperative molecular imaging (IMI) is an emerging potential tool proposed to address these issues. IMI is the process of injecting patients with fluorescent-targeted contrast agents that highlight cancer cells prior to surgery. Over the last 5 to 7 years, enormous progress has been achieved in tracer development, near-infrared camera approvals, and clinical trials. Therefore, a second biennial conference was organized at the University of Pennsylvania to gather surgical oncologists, scientists, and experts to discuss new investigative findings in the field. Our review summarizes the discussions from the conference and highlights findings in various clinical and scientific trials.

Aim: Recent advances in IMI were presented, and the importance of each clinical trial for surgical oncology was critically assessed. A major focus was to elaborate on the clinical endpoints that were being utilized in IMI trials to advance the respective surgical subspecialties.

Approach: Principal investigators presenting at the Perelman School of Medicine Abramson Cancer Center's second clinical trials update on IMI were selected to discuss their clinical trials and endpoints.

Results: Multiple phase III, II, and I trials were discussed during the conference. Since the approval of 5-ALA for commercial use in neurosurgical malignancies, multiple tracers and devices have been developed to address common challenges faced by cancer surgeons across numerous specialties. Discussants also presented tracers that are being developed for delineation of normal anatomic structures that can serve as an adjunct during surgical procedures.

Conclusions: IMI is increasingly being recognized as an improvement to standard oncologic surgical resections and will likely advance the art of cancer surgery in the coming years. The endpoints in each individual surgical subspecialty are varied depending on how IMI helps each specialty solve their clinical challenges.
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http://dx.doi.org/10.1117/1.JBO.26.5.050901DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8126806PMC
May 2021

Phosphatidylserine-exposing tumor-derived microparticles exacerbate coagulation and cancer cell transendothelial migration in triple-negative breast cancer.

Theranostics 2021 19;11(13):6445-6460. Epub 2021 Apr 19.

Department of Ultrasound, The First Hospital, Harbin Medical University, Harbin, China.

Neoadjuvant chemotherapy is relevant to the formation of thromboembolism and secondary neoplasms in triple-negative breast cancer (TNBC). Chemotherapy-induced breast cancer cell-derived microparticles (BCMPs) may have important thrombogenic and pro-metastatic effects on platelets and endothelium, which may be related to the expression and distribution of phosphatidylserine (PS). However, investigating these interactions is challenging due to technical limitations. A study was conducted in 20 healthy individuals and 18 patients who had been recently diagnosed with TNBC and were undergoing neoadjuvant chemotherapy with doxorubicin and cyclophosphamide. BCMPs were isolated from patient blood samples and doxorubicin-treated breast cancer cell lines. Their structure and morphology were studied by electron microscopy and antigen levels were measured by fluorescence-activated cell sorting. In an inhibition assay, isolated BCMPs were pretreated with lactadherin or tissue factor antibodies. Platelets isolated from healthy subjects were treated with BCMPs and coagulation time, fibrin formation, and expression of intrinsic/extrinsic factor Xase (FXa) and thrombin were evaluated. The effects of BCMPs on endothelial thrombogenicity and integrity were assessed by confocal microscopy, electron microscopy, measurement of intrinsic/extrinsic FXa, prothrombinase assay, and transwell permeability assay. Neoadjuvant chemotherapy significantly increased the expression of PS+ BCMPs in patient plasma. Its expression was associated with a rapid increase in procoagulant activity. Treatment with lactadherin, a PS-binding scavenging molecule, markedly reduced the adhesion of BCMPs and abolished their procoagulant activity, but this was not observed with tissue factor antibody treatment. Intravenous injection of BCMPs in mice induced a significant hypercoagulable state, reducing the extent of plasma fibrinogen and promoting the appearance of new thrombus. Cancer cells incubated with doxorubicin released large numbers of PS+ BCMPs, which stimulated and transformed endothelial cells into a procoagulant phenotype and increased the aggregation and activation of platelets. Moreover, cancer cells exploited this BCMP-induced endothelial leakiness and showed promoted metastasis. Pretreatment with lactadherin increased uptake of both PS+ BCMPs and cancer cells by endothelial cells and limited the transendothelial migration of cancer cells. Lactadherin, a biosensor that we developed, was used to study the extracellular vesicle distribution of PS, which revealed a novel PS+ BCMPs administrative axis that initiated a local coagulation cascade and facilitated metastatic colonization of circulating cancer cells.
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http://dx.doi.org/10.7150/thno.53637DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8120203PMC
April 2021

SLAM/SAP Decreased Follicular Regulatory T Cells in Patients with Graves' Disease.

J Immunol Res 2021 19;2021:5548463. Epub 2021 Apr 19.

Department of Laboratory Medicine, Affiliated People's Hospital, Jiangsu University, Zhenjiang, China.

Signaling lymphocytic activation molecule (SLAM) and SLAM-associated protein (SAP) play important role in inflammatory and autoimmune diseases. Our study is aimed at detecting the expression of SLAM and SAP in patients with Graves' disease (GD) and analyzing the effect of SLAM/SAP on circulating blood CD4CXCR5Foxp3 follicular regulatory T (Tfr) cells. The level of SAP in CD4CXCR5 T cells and the level of SLAM on CD19 B cells were significantly increased in the patients with GD, but no significant difference in the level of SLAM on CD4CXCR5 T cells was observed between the patients with GD and the healthy controls. A decrease in the percentage of Foxp3 cells in CD4CXCR5 T cells was observed following anti-SLAM treatment, but the percentages of IFN- cells, IL-4 cells, and IL-17 cells showed no obvious differences. The proportion of circulating Tfr cells was decreased in the patients with GD, and the proportion of circulating Tfr cells had a negative correlation with the level of SAP in CD4CXCR5 T cells and the levels of autoantibodies in the serum of the patients with GD. Our results suggested that the SLAM/SAP signaling pathway is involved in the decrease of circulating Tfr cells in Graves' disease.
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http://dx.doi.org/10.1155/2021/5548463DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8079219PMC
April 2021