Showing papers by "Xi'an Jiaotong University published in 2018"
Jeffrey D. Stanaway1, Ashkan Afshin1, Emmanuela Gakidou1, Stephen S Lim1 +1050 more•Institutions (346)
TL;DR: This study estimated levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs) by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017 and explored the relationship between development and risk exposure.
2,910 citations
TL;DR: It is reported that metastatic melanomas release extracellular vesicles, mostly in the form of exosomes, that carry PD-L1 on their surface, suggesting a mechanism by which tumours could evade the immunesystem, and the potential application ofExosomal PD- L1 to monitor patient responses to checkpoint therapies.
Abstract: Tumour cells evade immune surveillance by upregulating the surface expression of programmed death-ligand 1 (PD-L1), which interacts with programmed death-1 (PD-1) receptor on T cells to elicit the immune checkpoint response1,2. Anti-PD-1 antibodies have shown remarkable promise in treating tumours, including metastatic melanoma2–4. However, the patient response rate is low4,5. A better understanding of PD-L1-mediated immune evasion is needed to predict patient response and improve treatment efficacy. Here we report that metastatic melanomas release extracellular vesicles, mostly in the form of exosomes, that carry PD-L1 on their surface. Stimulation with interferon-γ (IFN-γ) increases the amount of PD-L1 on these vesicles, which suppresses the function of CD8 T cells and facilitates tumour growth. In patients with metastatic melanoma, the level of circulating exosomal PD-L1 positively correlates with that of IFN-γ, and varies during the course of anti-PD-1 therapy. The magnitudes of the increase in circulating exosomal PD-L1 during early stages of treatment, as an indicator of the adaptive response of the tumour cells to T cell reinvigoration, stratifies clinical responders from non-responders. Our study unveils a mechanism by which tumour cells systemically suppress the immune system, and provides a rationale for the application of exosomal PD-L1 as a predictor for anti-PD-1 therapy. Melanoma cells release programmed death-ligand 1 (PD-L1) on the surface of circulating exosomes, suggesting a mechanism by which tumours could evade the immunesystem, and the potential application of exosomal PD-L1 to monitor patient responses to checkpoint therapies.
1,591 citations
French Institute of Health and Medical Research1, Paris Descartes University2, Pierre-and-Marie-Curie University3, Mayo Clinic4, Providence Portland Medical Center5, University of Bern6, University Hospital of Bern7, Radboud University Nijmegen8, University of Erlangen-Nuremberg9, Université catholique de Louvain10, University Health Network11, University of Toronto12, Memorial Sloan Kettering Cancer Center13, Karolinska Institutet14, First Faculty of Medicine, Charles University in Prague15, Humanitas University16, Keio University17, Yamaguchi University18, Kindai University19, Sapporo Medical University20, Kurume University21, Xi'an Jiaotong University22, Qatar Airways23, Oregon Health & Science University24
TL;DR: The immunoscore provides a reliable estimate of the risk of recurrence in patients with colon cancer and supports the implementation of the consensus Immunoscore as a new component of a TNM-Immune classification of cancer.
1,326 citations
TL;DR: This paper attempts to present a comprehensive review of AI algorithms in rotating machinery fault diagnosis, from both the views of theory background and industrial applications.
1,287 citations
TL;DR: This study assesses the state-of-the-art machine learning methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018, and investigates the challenge of identifying the best ML algorithms for each of these tasks.
Abstract: Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumoris a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses thestate-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross tota lresection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset.
1,165 citations
TL;DR: A review on machinery prognostics following its whole program, i.e., from data acquisition to RUL prediction, which provides discussions on current situation, upcoming challenges as well as possible future trends for researchers in this field.
1,116 citations
TL;DR: In vivo experiments indicated that curcumin loaded hydrogels significantly accelerated wound healing rate with higher granulation tissue thickness and collagen disposition and upregulated vascular endothelial growth factor (VEGF) in a full-thickness skin defect model.
1,102 citations
TL;DR: A comprehensive survey, analyzing how edge computing improves the performance of IoT networks and considers security issues in edge computing, evaluating the availability, integrity, and the confidentiality of security strategies of each group, and proposing a framework for security evaluation of IoT Networks with edge computing.
Abstract: The Internet of Things (IoT) now permeates our daily lives, providing important measurement and collection tools to inform our every decision. Millions of sensors and devices are continuously producing data and exchanging important messages via complex networks supporting machine-to-machine communications and monitoring and controlling critical smart-world infrastructures. As a strategy to mitigate the escalation in resource congestion, edge computing has emerged as a new paradigm to solve IoT and localized computing needs. Compared with the well-known cloud computing, edge computing will migrate data computation or storage to the network “edge,” near the end users. Thus, a number of computation nodes distributed across the network can offload the computational stress away from the centralized data center, and can significantly reduce the latency in message exchange. In addition, the distributed structure can balance network traffic and avoid the traffic peaks in IoT networks, reducing the transmission latency between edge/cloudlet servers and end users, as well as reducing response times for real-time IoT applications in comparison with traditional cloud services. Furthermore, by transferring computation and communication overhead from nodes with limited battery supply to nodes with significant power resources, the system can extend the lifetime of the individual nodes. In this paper, we conduct a comprehensive survey, analyzing how edge computing improves the performance of IoT networks. We categorize edge computing into different groups based on architecture, and study their performance by comparing network latency, bandwidth occupation, energy consumption, and overhead. In addition, we consider security issues in edge computing, evaluating the availability, integrity, and the confidentiality of security strategies of each group, and propose a framework for security evaluation of IoT networks with edge computing. Finally, we compare the performance of various IoT applications (smart city, smart grid, smart transportation, and so on) in edge computing and traditional cloud computing architectures.
1,008 citations
TL;DR: This Perspective presents major progress in several key areas of the OER field such as theoretical understanding, activity trend, in situ and operando characterization, active site determination, and novel materials.
Abstract: Water splitting is the essential chemical reaction to enable the storage of intermittent energies such as solar and wind in the form of hydrogen fuel. The oxygen evolution reaction (OER) is often considered as the bottleneck in water splitting. Though metal oxides had been reported as OER electrocatalysts more than half a century ago, the recent interest in renewable energy storage has spurred a renaissance of the studies of transition metal oxides as Earth-abundant and nonprecious OER catalysts. This Perspective presents major progress in several key areas of the field such as theoretical understanding, activity trend, in situ and operando characterization, active site determination, and novel materials. A personal overview of the past achievements and future challenges is also provided.
1,004 citations
TL;DR: Wang et al. as mentioned in this paper introduced a new CT image denoising method based on the generative adversarial network (GAN) with Wasserstein distance and perceptual similarity, which is capable of not only reducing the image noise level but also trying to keep the critical information at the same time.
Abstract: The continuous development and extensive use of computed tomography (CT) in medical practice has raised a public concern over the associated radiation dose to the patient. Reducing the radiation dose may lead to increased noise and artifacts, which can adversely affect the radiologists’ judgment and confidence. Hence, advanced image reconstruction from low-dose CT data is needed to improve the diagnostic performance, which is a challenging problem due to its ill-posed nature. Over the past years, various low-dose CT methods have produced impressive results. However, most of the algorithms developed for this application, including the recently popularized deep learning techniques, aim for minimizing the mean-squared error (MSE) between a denoised CT image and the ground truth under generic penalties. Although the peak signal-to-noise ratio is improved, MSE- or weighted-MSE-based methods can compromise the visibility of important structural details after aggressive denoising. This paper introduces a new CT image denoising method based on the generative adversarial network (GAN) with Wasserstein distance and perceptual similarity. The Wasserstein distance is a key concept of the optimal transport theory and promises to improve the performance of GAN. The perceptual loss suppresses noise by comparing the perceptual features of a denoised output against those of the ground truth in an established feature space, while the GAN focuses more on migrating the data noise distribution from strong to weak statistically. Therefore, our proposed method transfers our knowledge of visual perception to the image denoising task and is capable of not only reducing the image noise level but also trying to keep the critical information at the same time. Promising results have been obtained in our experiments with clinical CT images.
916 citations
Xi'an Jiaotong University1, Huazhong University of Science and Technology2, Fudan University3, China Medical University (PRC)4, Guangzhou Medical University5, Zhejiang University6, Sichuan University7, Capital Medical University8, Peking University9, Peking Union Medical College10, China-Japan Friendship Hospital11, Beijing Jishuitan Hospital12, Tulane University13
TL;DR: Prevalence of spirometry-defined COPD is highly prevalent in the Chinese adult population and prevention and early detection of COPD using spirometry should be a public health priority in China to reduce COPD-related morbidity and mortality.
TL;DR: This research provides a new paradigm for designing material properties through engineering local structural heterogeneity, expected to benefit a wide range of functional materials.
Abstract: Piezoelectric materials, which respond mechanically to applied electric field and vice versa, are essential for electromechanical transducers. Previous theoretical analyses have shown that high piezoelectricity in perovskite oxides is associated with a flat thermodynamic energy landscape connecting two or more ferroelectric phases. Here, guided by phenomenological theories and phase-field simulations, we propose an alternative design strategy to commonly used morphotropic phase boundaries to further flatten the energy landscape, by judiciously introducing local structural heterogeneity to manipulate interfacial energies (that is, extra interaction energies, such as electrostatic and elastic energies associated with the interfaces). To validate this, we synthesize rare-earth-doped Pb(Mg1/3Nb2/3)O3-PbTiO3 (PMN-PT), as rare-earth dopants tend to change the local structure of Pb-based perovskite ferroelectrics. We achieve ultrahigh piezoelectric coefficients d33 of up to 1,500 pC N-1 and dielectric permittivity e33/e0 above 13,000 in a Sm-doped PMN-PT ceramic with a Curie temperature of 89 °C. Our research provides a new paradigm for designing material properties through engineering local structural heterogeneity, expected to benefit a wide range of functional materials.
TL;DR: The authors report on the development of injectable, biocompatible carbon nanotube reinforced quaternized chitosan cryogels with shape memory, conductivity and antibacterial properties for hemostatic control for lethal noncompressible hemorrhage hemostasis and wound healing.
Abstract: Developing injectable antibacterial and conductive shape memory hemostatic with high blood absorption and fast recovery for irregularly shaped and noncompressible hemorrhage remains a challenge. Here we report injectable antibacterial conductive cryogels based on carbon nanotube (CNT) and glycidyl methacrylate functionalized quaternized chitosan for lethal noncompressible hemorrhage hemostasis and wound healing. These cryogels present robust mechanical strength, rapid blood-triggered shape recovery and absorption speed, and high blood uptake capacity. Moreover, cryogels show better blood-clotting ability, higher blood cell and platelet adhesion and activation than gelatin sponge and gauze. Cryogel with 4 mg/mL CNT (QCSG/CNT4) shows better hemostatic capability than gauze and gelatin hemostatic sponge in mouse-liver injury model and mouse-tail amputation model, and better wound healing performance than Tegaderm™ film. Importantly, QCSG/CNT4 presents excellent hemostatic performance in rabbit liver defect lethal noncompressible hemorrhage model and even better hemostatic ability than Combat Gauze in standardized circular liver bleeding model.
Washington University in St. Louis1, Baylor College of Medicine2, Xi'an Jiaotong University3, Ontario Institute for Cancer Research4, Institute for Systems Biology5, Broad Institute6, University of Texas MD Anderson Cancer Center7, Mayo Clinic8, Kuwait University9, University of Toronto10, Princeton University11, Wake Forest University12
TL;DR: The largest investigation of predisposition variants in cancer to date finds 853 pathogenic or likely pathogenic variants in 8% of 10,389 cases from 33 cancer types, informing future guidelines of variant classification and germline genetic testing in cancer.
TL;DR: It is concluded that metformin acts in part through a B. fragilis–GUDCA–intestinal FXR axis to improve metabolic dysfunction, including hyperglycemia, and improves the metabolic health of humans and mice.
Abstract: The anti-hyperglycemic effect of metformin is believed to be caused by its direct action on signaling processes in hepatocytes, leading to lower hepatic gluconeogenesis. Recently, metformin was reported to alter the gut microbiota community in humans, suggesting that the hyperglycemia-lowering action of the drug could be the result of modulating the population of gut microbiota. However, the critical microbial signaling metabolites and the host targets associated with the metabolic benefits of metformin remained elusive. Here, we performed metagenomic and metabolomic analysis of samples from individuals with newly diagnosed type 2 diabetes (T2D) naively treated with metformin for 3 d, which revealed that Bacteroides fragilis was decreased and the bile acid glycoursodeoxycholic acid (GUDCA) was increased in the gut. These changes were accompanied by inhibition of intestinal farnesoid X receptor (FXR) signaling. We further found that high-fat-diet (HFD)-fed mice colonized with B. fragilis were predisposed to more severe glucose intolerance, and the metabolic benefits of metformin treatment on glucose intolerance were abrogated. GUDCA was further identified as an intestinal FXR antagonist that improved various metabolic endpoints in mice with established obesity. Thus, we conclude that metformin acts in part through a B. fragilis-GUDCA-intestinal FXR axis to improve metabolic dysfunction, including hyperglycemia.
TL;DR: The conductive biomaterials used in tissue engineering including conductive composite films, conductive nanofibers, Conductive hydrogels, and Conductive composite scaffolds fabricated by various methods such as electrospinning, coating, or deposition by in situ polymerization are summarized.
TL;DR: The newly developed capacitor exhibits a wide temperature usage range of -60 to 120 °C, with an energy-density variation of less than 10%, and satisfactory cycling reliability, with degradation of more than 8% over 106 cycles demonstrate that the NBT-0.45SBT multilayer ceramic is a promising candidate for high-power energy storage applications.
Abstract: The utilization of antiferroelectric (AFE) materials is thought to be an effective approach to enhance the energy density of dielectric capacitors. However, the high energy dissipation and inferior reliability that are associated with the antiferroelectric-ferroelectric phase transition are the main issues that restrict the applications of antiferroelectric ceramics. Here, simultaneously achieving high energy density and efficiency in a dielectric ceramic is proposed by combining antiferroelectric and relaxor features. Based on this concept, a lead-free dielectric (Na0.5 Bi0.5 )TiO3 -x(Sr0.7 Bi0.2 )TiO3 (NBT-xSBT) system is investigated and the corresponding multilayer ceramic capacitors (MLCCs) are fabricated. A record-high energy density of 9.5 J cm-3 , together with a high energy efficiency of 92%, is achieved in NBT-0.45SBT multilayer ceramic capacitors, which consist of ten dielectric layers with the single-layer thickness of 20 µm and the internal electrode area of 6.25 mm2 . Furthermore, the newly developed capacitor exhibits a wide temperature usage range of -60 to 120 °C, with an energy-density variation of less than 10%, and satisfactory cycling reliability, with degradation of less than 8% over 106 cycles. These characteristics demonstrate that the NBT-0.45SBT multilayer ceramic is a promising candidate for high-power energy storage applications.
TL;DR: In this article, the authors present an overview of recent progress in the field of nanostructured dielectric materials targeted for high-temperature capacitive energy storage applications, including polymer nanocomposites, and bulk ceramics and thin films.
Abstract: The demand for high-temperature dielectric materials arises from numerous emerging applications such as electric vehicles, wind generators, solar converters, aerospace power conditioning, and downhole oil and gas explorations, in which the power systems and electronic devices have to operate at elevated temperatures. This article presents an overview of recent progress in the field of nanostructured dielectric materials targeted for high-temperature capacitive energy storage applications. Polymers, polymer nanocomposites, and bulk ceramics and thin films are the focus of the materials reviewed. Both commercial products and the latest research results are covered. While general design considerations are briefly discussed, emphasis is placed on material specifications oriented toward the intended high-temperature applications, such as dielectric properties, temperature stability, energy density, and charge-discharge efficiency. The advantages and shortcomings of the existing dielectric materials are identif...
TL;DR: This work presents self-healing conductive hydrogels based on β-cyclodextrin, N-isopropylacrylamide, NIPAM, multiwalled carbon nanotubes and nanostructured polypyrrole, which exhibit high conductivity, self- healing property, flexible and elastic mechanical property and rapid stimuli-responsive property both to temperature and near-infrared (NIR)-light together.
Abstract: Self-healing hydrogels with multifunctionality as a type of fascinating material show potential application in various fields, such as biomedicine, tissue engineering, and wearable electronic devices. However, to combine the properties of autonomous self-healing property, high conductivity, excellent mechanical properties, and stimuli-responsive properties for hydrogel is still a great challenge. Herein, we present self-healing conductive hydrogels based on β-cyclodextrin (β-CD), N-isopropylacrylamide (NIPAM), multiwalled carbon nanotubes (CNT) and nanostructured polypyrrole (PPY). Among them, β-CD served as the host molecule, and NIPAM served as the guest molecule, CNT as the physical cross-linker and conducting substrate, and PPY as the highly conductive component, respectively. The obtained hydrogels exhibit high conductivity, self-healing property, flexible and elastic mechanical property and rapid stimuli-responsive property both to temperature and near-infrared (NIR)-light together. The excellent ch...
TL;DR: Two novel wide-bandgap copolymers, PBDT-TDZ and PBDTS- TDZ, are developed based on 1,3,4-thiadiazole (TDZ) and benzo[1,2-b:4,5-b']dithiophene (BDT) building blocks, which exhibit the stronger optical absorption, lower-lying HOMO level, and higher crystallinity.
Abstract: Two novel wide-bandgap copolymers, PBDT-TDZ and PBDTS-TDZ, are developed based on 1,3,4-thiadiazole (TDZ) and benzo[1,2-b:4,5-b']dithiophene (BDT) building blocks. These copolymers exhibit wide bandgaps over 2.07 eV and low-lying highest occupied molecular orbital (HOMO) levels below -5.35 eV, which match well with the typical low-bandgap acceptor of ITIC, resulting in a good complementary absorption from 300 to 900 nm and a low HOMO level offset (≤0.13 eV). Compared to PBDT-TDZ, PBDTS-TDZ with alkylthio side chains exhibits the stronger optical absorption, lower-lying HOMO level, and higher crystallinity. By using a single green solvent of o-xylene, PBDTS-TDZ:ITIC devices exhibit a large open-circuit voltage (Voc ) up to 1.10 eV and an extremely low energy loss (Eloss ) of 0.48 eV. At the same time, the desirable high short-circuit current density (Jsc ) of 17.78 mA cm-2 and fill factor of 65.4% are also obtained, giving rise to a high power conversion efficiency (PCE) of 12.80% without any additive and post-treatment. When adopting a homotandem device architecture, the PCE is further improved to 13.35% (certified as 13.19%) with a much larger Voc of 2.13 V, which is the best value for any type of homotandem organic solar cells reported so far.
TL;DR: The results indicate that the learned features of NSAE are meaningful and dissimilar, and LCN helps to produce shift-invariant features and recognizes mechanical health conditions effectively, and the superiority of the proposed NSAE-LCN is verified.
TL;DR: By analyzing the kernels of the convolutional layers of DNCNN via NAM algorithm, it is found that these kernels act as filters and they become complex when the layers go deeper, which may help to understand what DNCNN has learned in intelligent fault diagnosis of machinery.
TL;DR: AramcoMech 3.0 has been developed to describe the combustion of 1,3-butadiene and is validated by a comparison of simulation results to the new experimental measurements.
TL;DR: A good understanding and smart engineering of the defects in MTP have been demonstrated to be a key factor for the fabrication of high-efficiency PSCs and progress on the state-of-the-art defect engineering approaches for the optimization of PSC devices is summarized.
Abstract: The rapid development of solar cells (SCs) based on organic–inorganic hybrid metal triiodide perovskite (MTP) materials holds great promise for next-generation photovoltaic devices. The demonstrated power conversion efficiency of the SCs based on MTP (PSCs for short) has reached over 20%. An MTP material is a kind of soft ionic solid semiconductor. The intrinsic optoelectronic properties of MTP are greatly determined by several factors, such as the crystalline phase, doping type, impurities, elemental composition, and defects in its crystal structure. In the development of PSCs, a good understanding and smart engineering of the defects in MTP have been demonstrated to be a key factor for the fabrication of high-efficiency PSCs. In this review, we start with a brief introduction to the types of defects and the mechanisms for their formation in MTP. Then, the positive and negative impacts of defects on the important optoelectronic features of MTP are presented. The optoelectronic properties mainly include charge recombination, charge transport, ion migration, and structural stability. Moreover, commonly used techniques for the characterization of the defects in MTP are systematically summarized. Recent progress on the state-of-the-art defect engineering approaches for the optimization of PSC devices is also summarized, and we also provide some perspectives on the development of high-efficiency PSCs with long-term stability through the optimization of the defects in MTP.
TL;DR: A washable skin-touch-actuated textile-based triboelectric nanogenerator for harvesting mechanical energy from both voluntary and involuntary body motions, and is incorporable onto cloths/skin to capture the low output of 60 V from subtle involuntary friction with skin, well suited for users’ motion or daily operations.
Abstract: Textiles that are capable of harvesting biomechanical energy via triboelectric effects are of interest for self-powered wearable electronics. Fabrication of conformable and durable textiles with high triboelectric outputs remains challenging. Here we propose a washable skin-touch-actuated textile-based triboelectric nanogenerator for harvesting mechanical energy from both voluntary and involuntary body motions. Black phosphorus encapsulated with hydrophobic cellulose oleoyl ester nanoparticles serves as a synergetic electron-trapping coating, rendering a textile nanogenerator with long-term reliability and high triboelectricity regardless of various extreme deformations, severe washing, and extended environmental exposure. Considerably high output (~250–880 V, ~0.48–1.1 µA cm−2) can be attained upon touching by hand with a small force (~5 N) and low frequency (~4 Hz), which can power light-emitting diodes and a digital watch. This conformable all-textile-nanogenerator is incorporable onto cloths/skin to capture the low output of 60 V from subtle involuntary friction with skin, well suited for users’ motion or daily operations. Incorporation of triboelectric nanogenerators into textiles is attractive for self-powered wearable electronics. Here the authors employ black phosphorus with a hydrophobic coating in a durable, washable, and air permeable textile-based device that converts biomechanical motion into electricity.
TL;DR: In this article, the authors provided a facile method to development of band width electromagnetic absorber via loading magnetic quantum dots on the mono-dispersed amorphous carbon sphere.
TL;DR: This paper reviews recent modeling developments of the Wiener-process-based methods for degradation data analysis and RUL estimation, as well as their applications in the field of prognostics and health management (PHM).
TL;DR: LCAR-B38M CAR T cell therapy displayed a manageable safety profile and demonstrated deep and durable responses in patients with R/R MM, and median overall survival for all patients was not reached.
Abstract: Chimeric antigen receptor (CAR) T cell therapy has demonstrated proven efficacy in some hematologic cancers. We evaluated the safety and efficacy of LCAR-B38M, a dual epitope-binding CAR T cell therapy directed against 2 distinct B cell maturation antigen epitopes, in patients with relapsed/refractory (R/R) multiple myeloma (MM). This ongoing phase 1, single-arm, open-label, multicenter study enrolled patients (18 to 80 years) with R/R MM. Lymphodepletion was performed using cyclophosphamide 300 mg/m2. LCAR-B38M CAR T cells (median CAR+ T cells, 0.5 × 106 cells/kg [range, 0.07 to 2.1 × 106]) were infused in 3 separate infusions. The primary objective is to evaluate the safety of LCAR-B38M CAR T cells; the secondary objective is to evaluate the antimyeloma response of the treatment based on the general guidelines of the International Myeloma Working Group. At data cutoff, 57 patients had received LCAR-B38M CAR T cells. All patients experienced ≥ 1 adverse events (AEs). Grade ≥ 3 AEs were reported in 37/57 patients (65%); most common were leukopenia (17/57; 30%), thrombocytopenia (13/57; 23%), and aspartate aminotransferase increased (12/57; 21%). Cytokine release syndrome occurred in 51/57 patients (90%); 4/57 (7%) had grade ≥ 3 cases. One patient reported neurotoxicity of grade 1 aphasia, agitation, and seizure-like activity. The overall response rate was 88% (95% confidence interval [CI], 76 to 95); 39/57 patients (68%) achieved a complete response, 3/57 (5%) achieved a very good partial response, and 8/57 (14%) achieved a partial response. Minimal residual disease was negative for 36/57 (63%) patients. The median time to response was 1 month (range, 0.4 to 3.5). At a median follow-up of 8 months, median progression-free survival was 15 months (95% CI, 11 to not estimable). Median overall survival for all patients was not reached. LCAR-B38M CAR T cell therapy displayed a manageable safety profile and demonstrated deep and durable responses in patients with R/R MM. ClinicalTrials.gov
, NCT03090659
; Registered on March 27, 2017, retrospectively registered
TL;DR: In this paper, a lead-free relaxor ferroelectric ceramics for energy storage has been proposed, which can simultaneously deliver a high recoverable energy density of 2.9 and energy efficiency of 86.8%.