Showing papers by "Tongji University published in 2018"

Osimertinib in Untreated EGFR-Mutated Advanced Non–Small-Cell Lung Cancer

Abstract: BackgroundOsimertinib is an oral, third-generation, irreversible epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) that selectively inhibits both EGFR-TKI–sensitizing and EGFR T790M resistance mutations. We compared osimertinib with standard EGFR-TKIs in patients with previously untreated, EGFR mutation–positive advanced non–small-cell lung cancer (NSCLC). MethodsIn this double-blind, phase 3 trial, we randomly assigned 556 patients with previously untreated, EGFR mutation–positive (exon 19 deletion or L858R) advanced NSCLC in a 1:1 ratio to receive either osimertinib (at a dose of 80 mg once daily) or a standard EGFR-TKI (gefitinib at a dose of 250 mg once daily or erlotinib at a dose of 150 mg once daily). The primary end point was investigator-assessed progression-free survival. ResultsThe median progression-free survival was significantly longer with osimertinib than with standard EGFR-TKIs (18.9 months vs. 10.2 months; hazard ratio for disease progression or death, 0.46; 95% confi...

Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response

Abstract: Cancer treatment by immune checkpoint blockade (ICB) can bring long-lasting clinical benefits, but only a fraction of patients respond to treatment. To predict ICB response, we developed TIDE, a computational method to model two primary mechanisms of tumor immune evasion: the induction of T cell dysfunction in tumors with high infiltration of cytotoxic T lymphocytes (CTL) and the prevention of T cell infiltration in tumors with low CTL level. We identified signatures of T cell dysfunction from large tumor cohorts by testing how the expression of each gene in tumors interacts with the CTL infiltration level to influence patient survival. We also modeled factors that exclude T cell infiltration into tumors using expression signatures from immunosuppressive cells. Using this framework and pre-treatment RNA-Seq or NanoString tumor expression profiles, TIDE predicted the outcome of melanoma patients treated with first-line anti-PD1 or anti-CTLA4 more accurately than other biomarkers such as PD-L1 level and mutation load. TIDE also revealed new candidate ICB resistance regulators, such as SERPINB9, demonstrating utility for immunotherapy research.

Promises, Challenges, and Recent Progress of Inorganic Solid-State Electrolytes for All-Solid-State Lithium Batteries

Abstract: All-solid-state lithium batteries (ASSLBs) have the potential to revolutionize battery systems for electric vehicles due to their benefits in safety, energy density, packaging, and operable temperature range. As the key component in ASSLBs, inorganic lithium-ion-based solid-state electrolytes (SSEs) have attracted great interest, and advances in SSEs are vital to deliver the promise of ASSLBs. Herein, a survey of emerging SSEs is presented, and ion-transport mechanisms are briefly discussed. Techniques for increasing the ionic conductivity of SSEs, including substitution and mechanical strain treatment, are highlighted. Recent advances in various classes of SSEs enabled by different preparation methods are described. Then, the issues of chemical stabilities, electrochemical compatibility, and the interfaces between electrodes and SSEs are focused on. A variety of research addressing these issues is outlined accordingly. Given their importance for next-generation battery systems and transportation style, a perspective on the current challenges and opportunities is provided, and suggestions for future research directions for SSEs and ASSLBs are suggested.

Tumor-derived exosomal miR-1247-3p induces cancer-associated fibroblast activation to foster lung metastasis of liver cancer.

Abstract: The communication between tumor-derived elements and stroma in the metastatic niche has a critical role in facilitating cancer metastasis. Yet, the mechanisms tumor cells use to control metastatic niche formation are not fully understood. Here we report that in the lung metastatic niche, high-metastatic hepatocellular carcinoma (HCC) cells exhibit a greater capacity to convert normal fibroblasts to cancer-associated fibroblasts (CAFs) than low-metastatic HCC cells. We show high-metastatic HCC cells secrete exosomal miR-1247-3p that directly targets B4GALT3, leading to activation of β1-integrin–NF-κB signaling in fibroblasts. Activated CAFs further promote cancer progression by secreting pro-inflammatory cytokines, including IL-6 and IL-8. Clinical data show high serum exosomal miR-1247-3p levels correlate with lung metastasis in HCC patients. These results demonstrate intercellular crosstalk between tumor cells and fibroblasts is mediated by tumor-derived exosomes that control lung metastasis of HCC, providing potential targets for prevention and treatment of cancer metastasis.

Learning to Optimize: Training Deep Neural Networks for Interference Management

Abstract: Numerical optimization has played a central role in addressing key signal processing (SP) problems Highly effective methods have been developed for a large variety of SP applications such as communications, radar, filter design, and speech and image analytics, just to name a few However, optimization algorithms often entail considerable complexity, which creates a serious gap between theoretical design/analysis and real-time processing In this paper, we aim at providing a new learning-based perspective to address this challenging issue The key idea is to treat the input and output of an SP algorithm as an unknown nonlinear mapping and use a deep neural network (DNN) to approximate it If the nonlinear mapping can be learned accurately by a DNN of moderate size, then SP tasks can be performed effectively—since passing the input through a DNN only requires a small number of simple operations In our paper, we first identify a class of optimization algorithms that can be accurately approximated by a fully connected DNN Second, to demonstrate the effectiveness of the proposed approach, we apply it to approximate a popular interference management algorithm, namely, the WMMSE algorithm Extensive experiments using both synthetically generated wireless channel data and real DSL channel data have been conducted It is shown that, in practice, only a small network is sufficient to obtain high approximation accuracy, and DNNs can achieve orders of magnitude speedup in computational time compared to the state-of-the-art interference management algorithm

Integral Human Pose Regression

Abstract: State-of-the-art human pose estimation methods are based on heat map representation. In spite of the good performance, the representation has a few issues in nature, such as non-differentiable post-processing and quantization error. This work shows that a simple integral operation relates and unifies the heat map representation and joint regression, thus avoiding the above issues. It is differentiable, efficient, and compatible with any heat map based methods. Its effectiveness is convincingly validated via comprehensive ablation experiments under various settings, specifically on 3D pose estimation, for the first time.

Prussian Blue Cathode Materials for Sodium-Ion Batteries and Other Ion Batteries

Abstract: Sodium-ion batteries (SIBs) are considered to be a low-cost complement or competitor to Li-ion batteries for large-scale electric energy storage applications; however, their development has been less successful due to the lack of suitable host materials to enable reversible Na+ insertion reactions. Prussian blue analogs (PBAs) appear to be attractive candidates for SIB cathodes because of their open channel structure, compositional and electrochemical tunability. In this paper, the authors present a comprehensive review on the recent advances in the development of PBA frameworks as SIB cathodes with particular attention to the structure-performance correlation of the PBA materials, and discuss the possible strategies to address the problems present in the SIB applications of PBAs. Also, the development of the PBA frameworks for the insertion cathodes of other monovalent and multivalent ions is briefly introduced, with the aim of providing a new insight into the design and development of new host materials for the next-generation advanced batteries.

CNS Response to Osimertinib Versus Standard Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in Patients With Untreated EGFR-Mutated Advanced Non–Small-Cell Lung Cancer

Abstract: Purpose We report CNS efficacy of osimertinib versus standard epidermal growth factor receptor ( EGFR) tyrosine kinase inhibitors (TKIs) in patients with untreated EGFR-mutated advanced non-small-cell lung cancer from the phase III FLAURA study. Patients and Methods Patients (N = 556) were randomly assigned to osimertinib or standard EGFR-TKIs (gefitinib or erlotinib); brain scans were not mandated unless clinically indicated. Patients with asymptomatic or stable CNS metastases were included. In patients with symptomatic CNS metastases, neurologic status was required to be stable for ≥ 2 weeks after completion of definitive therapy and corticosteroids. A preplanned subgroup analysis with CNS progression-free survival as primary objective was conducted in patients with measurable and/or nonmeasurable CNS lesions on baseline brain scan by blinded independent central neuroradiologic review. The CNS evaluable-for-response set included patients with ≥ one measurable CNS lesion. Results Of 200 patients with available brain scans at baseline, 128 (osimertinib, n = 61; standard EGFR-TKIs, n = 67) had measurable and/or nonmeasurable CNS lesions, including 41 patients (osimertinib, n = 22; standard EGFR-TKIs, n = 19) with ≥ one measurable CNS lesion. Median CNS progression-free survival in patients with measurable and/or nonmeasurable CNS lesions was not reached with osimertinib (95% CI, 16.5 months to not calculable) and 13.9 months (95% CI, 8.3 months to not calculable) with standard EGFR-TKIs (hazard ratio, 0.48; 95% CI, 0.26 to 0.86; P = .014 [nominally statistically significant]). CNS objective response rates were 91% and 68% in patients with ≥ one measurable CNS lesion (odds ratio, 4.6; 95% CI, 0.9 to 34.9; P = .066) and 66% and 43% in patients with measurable and/or nonmeasurable CNS lesions (odds ratio, 2.5; 95% CI, 1.2 to 5.2; P = .011) treated with osimertinib and standard EGFR-TKIs, respectively. Probability of experiencing a CNS progression event was consistently lower with osimertinib versus standard EGFR-TKIs. Conclusion Osimertinib has CNS efficacy in patients with untreated EGFR-mutated non-small-cell lung cancer. These results suggest a reduced risk of CNS progression with osimertinib versus standard EGFR-TKIs.

Thermal Conductivity of Polymers and Their Nanocomposites.

Abstract: Polymers are usually considered as thermal insulators, and their applications are limited by their low thermal conductivity. However, recent studies have shown that certain polymers have surprisingly high thermal conductivity, some of which are comparable to that in poor metals or even silicon. Here, the experimental achievements and theoretical progress of thermal transport in polymers and their nanocomposites are outlined. The open questions and challenges of existing theories are discussed. Special attention is given to the mechanism of thermal transport, the enhancement of thermal conductivity in polymer nanocomposites/fibers, and their potential application as thermal interface materials.

Observation of Pseudocapacitive Effect and Fast Ion Diffusion in Bimetallic Sulfides as an Advanced Sodium-Ion Battery Anode

Abstract: Lithium-ion batteries (LIBs) have permeated energy storage market from portable electronics to electric vehicles in view of their high energy density and long cycle life.[1] Nevertheless, it is still expensive to scale up due to the limited Li sources.[2] In contrast, sodium-ion batteries (SIBs), with similar energy Sodium-ion batteries (SIBs) are promising next-generation alternatives due to the low cost and abundance of sodium sources. Yet developmental electrodes in SIBs such as transition metal sulfides have huge volume expansion, sluggish Na+ diffusion kinetics, and poor electrical conductivity. Here bimetallic sulfide (Co9S8/ZnS) nanocrystals embedded in hollow nitrogen-doped carbon nanosheets are demonstrated with a high sodium diffusion coefficient, pseudocapacitive effect, and excellent reversibility. Such a unique composite structure is designed and synthesized via a facile sulfidation of the CoZn-MOFs followed by calcination and is highly dependant on the reaction time and temperature. The optimized Co1Zn1-S(600) electrode exhibits excellent sodium storage performance, including a high capacity of 542 mA h g−1 at 0.1 A g−1, good rate capability at 10 A g−1, and excellent cyclic stability up to 500 cycles for half-cell. It also shows potential in full-cell configuration. Such capabilities will accelerate the adoption of sodium-ion batteries for electrical energy applications.

Gefitinib versus vinorelbine plus cisplatin as adjuvant treatment for stage II-IIIA (N1-N2) EGFR-mutant NSCLC (ADJUVANT/CTONG1104): a randomised, open-label, phase 3 study.

Abstract: Summary Background Cisplatin-based adjuvant chemotherapy is the standard of care for patients with resected stage II–IIIA non-small-cell lung cancer (NSCLC). RADIANT and SELECT trial data suggest patients with EGFR-mutant stage IB–IIIA resected NSCLC could benefit from adjuvant EGFR tyrosine kinase inhibitor treatment. We aimed to compare the efficacy of adjuvant gefitinib versus vinorelbine plus cisplatin in patients with completely resected EGFR-mutant stage II–IIIA (N1–N2) NSCLC. Methods We did a randomised, open-label, phase 3 trial at 27 centres in China. We enrolled patients aged 18–75 years with completely resected (R0), stage II–IIIA (N1–N2), EGFR-mutant (exon 19 deletion or exon 21 Leu858Arg) NSCLC. Patients were stratified by N stage and EGFR mutation status and randomised (1:1) by Pocock and Simon minimisation with a random element to either gefitinib (250 mg once daily) for 24 months or intravenous vinorelbine (25 mg/m 2 on days 1 and 8) plus intravenous cisplatin (75 mg/m 2 on day 1) every 3 weeks for four cycles. The primary endpoint was disease-free survival in the intention-to-treat population, which comprised all randomised patients; the safety population included all randomised patients who received at least one dose of study medication. Enrolment to the study is closed but survival follow-up is ongoing. The study is registered with ClinicalTrials.gov, number NCT01405079. Findings Between Sept 19, 2011, and April 24, 2014, 483 patients were screened and 222 patients were randomised, 111 to gefitinib and 111 to vinorelbine plus cisplatin. Median follow-up was 36·5 months (IQR 23·8–44·8). Median disease-free survival was significantly longer with gefitinib (28·7 months [95% CI 24·9–32·5]) than with vinorelbine plus cisplatin (18·0 months [13·6–22·3]; hazard ratio [HR] 0·60, 95% CI 0·42–0·87; p=0·0054). In the safety population, the most commonly reported grade 3 or worse adverse events in the gefitinib group (n=106) were raised alanine aminotransferase and asparate aminotransferase (two [2%] patients with each event vs none with vinorelbine plus cisplatin). In the vinorelbine plus cisplatin group (n=87), the most frequently reported grade 3 or worse adverse events were neutropenia (30 [34%] patients vs none with gefitinib), leucopenia (14 [16%] vs none), and vomiting (eight [9%] vs none). Serious adverse events were reported for seven (7%) patients who received gefitinib and 20 (23%) patients who received vinorelbine plus cisplatin. No interstitial lung disease was noted with gefitinib. No deaths were treatment related. Interpretation Adjuvant gefitinib led to significantly longer disease-free survival compared with that for vinorelbine plus cisplatin in patients with completely resected stage II–IIIA (N1–N2) EGFR-mutant NSCLC. Based on the superior disease-free survival, reduced toxicity, and improved quality of life, adjuvant gefitinib could be a potential treatment option compared with adjuvant chemotherapy in these patients. However, the duration of benefit with gefitinib after 24 months might be limited and overall survival data are not yet mature. Funding Guangdong Provincial Key Laboratory of Lung Cancer Translational Medicine; National Health and Family Planning Commission of People's Republic of China; Guangzhou Science and Technology Bureau; AstraZeneca China.

Ultrahigh Piezoelectric Properties in Textured (K,Na)NbO3-Based Lead-Free Ceramics

Abstract: High-performance lead-free piezoelectric materials are in great demand for next-generation electronic devices to meet the requirement of environmentally sustainable society. Here, ultrahigh piezoelectric properties with piezoelectric coefficients (d33 ≈700 pC N-1 , d33 * ≈980 pm V-1 ) and planar electromechanical coupling factor (kp ≈76%) are achieved in highly textured (K,Na)NbO3 (KNN)-based ceramics. The excellent piezoelectric properties can be explained by the strong anisotropic feature, optimized engineered domain configuration in the textured ceramics, and facilitated polarization rotation induced by the intermediate phase. In addition, the nanodomain structures with decreased domain wall energy and increased domain wall mobility also contribute to the ultrahigh piezoelectric properties. This work not only demonstrates the tremendous potential of KNN-based ceramics to replace lead-based piezoelectrics but also provides a good strategy to design high-performance piezoelectrics by controlling appropriate phase and crystallographic orientation.

Repulsion Loss: Detecting Pedestrians in a Crowd

Abstract: Detecting individual pedestrians in a crowd remains a challenging problem since the pedestrians often gather together and occlude each other in real-world scenarios. In this paper, we first explore how a state-of-the-art pedestrian detector is harmed by crowd occlusion via experimentation, providing insights into the crowd occlusion problem. Then, we propose a novel bounding box regression loss specifically designed for crowd scenes, termed repulsion loss. This loss is driven by two motivations: the attraction by target, and the repulsion by other surrounding objects. The repulsion term prevents the proposal from shifting to surrounding objects thus leading to more crowd-robust localization. Our detector trained by repulsion loss outperforms the state-of-the-art methods with a significant improvement in occlusion cases.

Nuclear cGAS suppresses DNA repair and promotes tumorigenesis.

Abstract: Accurate repair of DNA double-stranded breaks by homologous recombination preserves genome integrity and inhibits tumorigenesis. Cyclic GMP–AMP synthase (cGAS) is a cytosolic DNA sensor that activates innate immunity by initiating the STING–IRF3–type I IFN signalling cascade1,2. Recognition of ruptured micronuclei by cGAS links genome instability to the innate immune response3,4, but the potential involvement of cGAS in DNA repair remains unknown. Here we demonstrate that cGAS inhibits homologous recombination in mouse and human models. DNA damage induces nuclear translocation of cGAS in a manner that is dependent on importin-α, and the phosphorylation of cGAS at tyrosine 215—mediated by B-lymphoid tyrosine kinase—facilitates the cytosolic retention of cGAS. In the nucleus, cGAS is recruited to double-stranded breaks and interacts with PARP1 via poly(ADP-ribose). The cGAS–PARP1 interaction impedes the formation of the PARP1–Timeless complex, and thereby suppresses homologous recombination. We show that knockdown of cGAS suppresses DNA damage and inhibits tumour growth both in vitro and in vivo. We conclude that nuclear cGAS suppresses homologous-recombination-mediated repair and promotes tumour growth, and that cGAS therefore represents a potential target for cancer prevention and therapy.

Co-Estimation of State of Charge and State of Health for Lithium-Ion Batteries Based on Fractional-Order Calculus

Abstract: Lithium-ion batteries have emerged as the state-of-the-art energy storage for portable electronics, electrified vehicles, and smart grids. An enabling Battery Management System holds the key for efficient and reliable system operation, in which State-of-Charge (SOC) estimation and State-of-Health (SOH) monitoring are of particular importance. In this paper, an SOC and SOH co-estimation scheme is proposed based on the fractional-order calculus. First, a fractional-order equivalent circuit model is established and parameterized using a Hybrid Genetic Algorithm/Particle Swarm Optimization method. This model is capable of predicting the voltage response with a root-mean-squared error less than 10 mV under various driving-cycle-based tests. Comparative studies show that it improves the modeling accuracy appreciably from its second- and third-order counterparts. Then, a dual fractional-order extended Kalman filter is put forward to realize simultaneous SOC and SOH estimation. Extensive experimental results show that the maximum steady-state errors of SOC and SOH estimation can be achieved within 1%, in the presence of initial deviation, noise, and disturbance. The resilience of the co-estimation scheme against battery aging is also verified through experimentation.

Electrode Materials, Electrolytes, and Challenges in Nonaqueous Lithium-Ion Capacitors.

Abstract: Among the various energy-storage systems, lithium-ion capacitors (LICs) are receiving intensive attention due to their high energy density, high power density, long lifetime, and good stability. As a hybrid of lithium-ion batteries and supercapacitors, LICs are composed of a battery-type electrode and a capacitor-type electrode and can potentially combine the advantages of the high energy density of batteries and the large power density of capacitors. Here, the working principle of LICs is discussed, and the recent advances in LIC electrode materials, particularly activated carbon and lithium titanate, as well as in electrolyte development are reviewed. The charge-storage mechanisms for intercalative pseudocapacitive behavior, battery behavior, and conventional pseudocapacitive behavior are classified and compared. Finally, the prospects and challenges associated with LICs are discussed. The overall aim is to provide deep insights into the LIC field for continuing research and development of second-generation energy-storage technologies.

Metal–Organic Framework-Based Sensors for Environmental Contaminant Sensing

Abstract: Increasing demand for timely and accurate environmental pollution monitoring and control requires new sensing techniques with outstanding performance, i.e., high sensitivity, high selectivity, and reliability. Metal-organic frameworks (MOFs), also known as porous coordination polymers, are a fascinating class of highly ordered crystalline coordination polymers formed by the coordination of metal ions/clusters and organic bridging linkers/ligands. Owing to their unique structures and properties, i.e., high surface area, tailorable pore size, high density of active sites, and high catalytic activity, various MOF-based sensing platforms have been reported for environmental contaminant detection including anions, heavy metal ions, organic compounds, and gases. In this review, recent progress in MOF-based environmental sensors is introduced with a focus on optical, electrochemical, and field-effect transistor sensors. The sensors have shown unique and promising performance in water and gas contaminant sensing. Moreover, by incorporation with other functional materials, MOF-based composites can greatly improve the sensor performance. The current limitations and future directions of MOF-based sensors are also discussed.

m 6 A facilitates hippocampus-dependent learning and memory through YTHDF1

Abstract: N6-methyladenosine (m6A), the most prevalent internal RNA modification on mammalian messenger RNAs, regulates the fates and functions of modified transcripts through m6A-specific binding proteins1–5. In the nervous system, m6A is abundant and modulates various neural functions6–11. Whereas m6A marks groups of mRNAs for coordinated degradation in various physiological processes12–15, the relevance of m6A for mRNA translation in vivo remains largely unknown. Here we show that, through its binding protein YTHDF1, m6A promotes protein translation of target transcripts in response to neuronal stimuli in the adult mouse hippocampus, thereby facilitating learning and memory. Mice with genetic deletion of Ythdf1 show learning and memory defects as well as impaired hippocampal synaptic transmission and long-term potentiation. Re-expression of YTHDF1 in the hippocampus of adult Ythdf1-knockout mice rescues the behavioural and synaptic defects, whereas hippocampus-specific acute knockdown of Ythdf1 or Mettl3, which encodes the catalytic component of the m6A methyltransferase complex, recapitulates the hippocampal deficiency. Transcriptome-wide mapping of YTHDF1-binding sites and m6A sites on hippocampal mRNAs identified key neuronal genes. Nascent protein labelling and tether reporter assays in hippocampal neurons showed that YTHDF1 enhances protein synthesis in a neuronal-stimulus-dependent manner. In summary, YTHDF1 facilitates translation of m6A-methylated neuronal mRNAs in response to neuronal stimulation, and this process contributes to learning and memory. Neuronal stimulation induces protein translation of m6A-methylated neuronal mRNAs facilitated by YTHDF1, and this process contributes to learning and memory.

Developing High-Performance Lithium Metal Anode in Liquid Electrolytes: Challenges and Progress.

Abstract: Lithium metal anodes are potentially key for next-generation energy-dense batteries because of the extremely high capacity and the ultralow redox potential. However, notorious safety concerns of Li metal in liquid electrolytes have significantly retarded its commercialization: on one hand, lithium metal morphological instabilities (LMI) can cause cell shorting and even explosion; on the other hand, breaking of the grown Li arms induces the so-called "dead Li"; furthermore, the continuous consumption of the liquid electrolyte and cycleable lithium also shortens cell life. The research community has been seeking new strategies to protect Li metal anodes and significant progress has been made in the last decade. Here, an overview of the fundamental understandings of solid electrolyte interphase (SEI) formation, conceptual models, and advanced real-time characterizations of LMI are presented. Instructed by the conceptual models, strategies including increasing the donatable fluorine concentration (DFC) in liquid to enrich LiF component in SEI, increasing salt concentration (ionic strength) and sacrificial electrolyte additives, building artificial SEI to boost self-healing of natural SEI, and 3D electrode frameworks to reduce current density and delay Sand's extinction are summarized. Practical challenges in competing with graphite and silicon anodes are outlined.

Review on landslide susceptibility mapping using support vector machines

Abstract: Landslides are natural phenomena that can cause great loss of life and damage to property. A landslide susceptibility map is a useful tool to help with land management in landslide-prone areas. A support vector machine (SVM) is a machine learning algorithm that uses a small number of samples for prediction and has been widely used in recent years. This paper presents a review of landslide susceptibility mapping using SVM. It presents the basic concept of SVM and its application in landslide susceptibility assessment and mapping. Then it compares the SVM method with four other methods (analytic hierarchy process, logistic regression, artificial neural networks and random forests) used in landslide susceptibility mapping. The application of SVM in landslide susceptibility assessment and mapping is discussed and suggestions for future research are presented. Compared with some of the methods commonly used in landslide susceptibility assessment and mapping, SVM has its strengths and weaknesses owing to its unique theoretical basis. The combination of SVM and other techniques may yield better performance in landslide susceptibility assessment and mapping. A high-quality informative database is essential and classification of landslide types prior to landslide susceptibility assessment is important to help improve model performance.

Investigating Novel Resistance Mechanisms to Third-Generation EGFR Tyrosine Kinase Inhibitor Osimertinib in Non–Small Cell Lung Cancer Patients

Abstract: Purpose: The third-generation EGFR tyrosine kinase inhibitor osimertinib is approved to treat patients with EGFR T790M-positive non-small cell lung cancer (NSCLC) who have developed resistance to earlier-generation drugs. Acquired EGFR C797S mutation has been reported to mediate osimertinib resistance in some patients. However, the remaining resistance mechanisms are largely unknown.Experimental Design: We performed mutation profiling using targeted next-generation sequencing (NGS) for 416 cancer-relevant genes on 93 osimertinib-resistant lung cancer patients' samples, mainly cell-free DNAs (cfDNAs), and matched pretreatment samples of 12 patients. In vitro experiments were conducted to functionally study the secondary EGFR mutations identified.Results:EGFR G796/C797, L792, and L718/G719 mutations were identified in 24.7%, 10.8%, and 9.7% of the cases, respectively, with certain mutations coexisting in one patient with different prevalence. L792 and L718 mutants markedly increased the half inhibitory concentration (IC50) of osimertinib in vitro, among which the L718Q mutation conferred the greatest resistance to osimertinib, as well as gefitinib resistance when not coexisting with T790M. Further analysis of the 12 matched pretreatment samples confirmed that these EGFR mutations were acquired during osimertinib treatment. Alterations in parallel or downstream oncogenes such as MET, KRAS, and PIK3CA were also discovered, potentially contributing to the osimertinib-resistance in patients without EGFR secondary mutations.Conclusions: We present comprehensive mutation profiles of a large cohort of osimertinib-resistance lung cancer patients using mainly cfDNA. Besides C797 mutations, novel secondary mutations of EGFR L718 and L792 residues confer osimertinib resistance, both in vitro and in vivo, and are of great clinical and pharmaceutical relevance. Clin Cancer Res; 24(13); 3097-107. ©2018 AACR.

Microbiota-derived short-chain fatty acids promote Th1 cell IL-10 production to maintain intestinal homeostasis

Abstract: T-cells are crucial in maintanence of intestinal homeostasis, however, it is still unclear how microbiota metabolites regulate T-effector cells. Here we show gut microbiota-derived short-chain fatty acids (SCFAs) promote microbiota antigen-specific Th1 cell IL-10 production, mediated by G-protein coupled receptors 43 (GPR43). Microbiota antigen-specific Gpr43−/− CBir1 transgenic (Tg) Th1 cells, specific for microbiota antigen CBir1 flagellin, induce more severe colitis compared with wide type (WT) CBir1 Tg Th1 cells in Rag−/− recipient mice. Treatment with SCFAs limits colitis induction by promoting IL-10 production, and administration of anti-IL-10R antibody promotes colitis development. Mechanistically, SCFAs activate Th1 cell STAT3 and mTOR, and consequently upregulate transcription factor B lymphocyte-induced maturation protein 1 (Blimp-1), which mediates SCFA-induction of IL-10. SCFA-treated Blimp1−/− Th1 cells produce less IL-10 and induce more severe colitis compared to SCFA-treated WT Th1 cells. Our studies, thus, provide insight into how microbiota metabolites regulate Th1 cell functions to maintain intestinal homeostasis. T cells play a critical role in intestinal homeostasis, with increasing evidence suggesting a role for the microbiome metabolome in modulating this response. Here the authors show short-chain fatty acids promote IL-10 production in Th1 cells.

Nanocarbon‐Based Materials for Flexible All‐Solid‐State Supercapacitors

Abstract: Because of the rapid development of flexible electronics, it is important to develop high-performance flexible energy-storage devices, such as supercapacitors and metal-ion batteries. Compared with metal-ion batteries, supercapacitors exhibit higher power density, longer cycling life, and excellent safety, and they can be easily fabricated into all-solid-state devices by using polymer gel electrolytes. All-solid-state supercapacitors (ASSSCs) have the advantages of being lightweight and flexible, thus showing great potential to be used as power sources for flexible portable electronics. Because of their high specific surface area and excellent electrical and mechanical properties, nanocarbon materials (such as carbon nanotubes, graphene, carbon nanofibers, and so on) have been widely used as efficient electrode materials for flexible ASSSCs, and great achievements have been obtained. Here, the recent advances in flexible ASSSCs are summarized, from design strategies to fabrication techniques for nanocarbon electrodes and devices. Current challenges and future perspectives are also discussed.

Manipulation of Phonon Transport in Thermoelectrics.

Abstract: For several decades, thermoelectric advancements have largely relied on the reduction of lattice thermal conductivity (κL ). According to the Boltzmann transport theory of phonons, κL mainly depends on the specific heat, the velocity, and the scattering of phonons. Intensifying the scattering rate of phonons is the focus for reducing the lattice thermal conductivity. Effective scattering sources include 0D point defects, 1D dislocations, and 2D interfaces, each of which has a particular range of frequencies where phonon scattering is most effective. Because acoustic phonons are generally the main contributors to κL due to their much higher velocities compared to optical phonons, many low-κL thermoelectrics rely on crystal structure complexity leading to a small fraction of acoustic phonons and/or weak chemical bonds enabling an overall low phonon propagation velocity. While these thermal strategies are successful for advancing thermoelectrics, the principles used can be integrated with approaches such as band engineering to improve the electronic properties, which can promote this energy technology from niche applications into the mainstream.

DeepCRISPR: optimized CRISPR guide RNA design by deep learning

Abstract: A major challenge for effective application of CRISPR systems is to accurately predict the single guide RNA (sgRNA) on-target knockout efficacy and off-target profile, which would facilitate the optimized design of sgRNAs with high sensitivity and specificity. Here we present DeepCRISPR, a comprehensive computational platform to unify sgRNA on-target and off-target site prediction into one framework with deep learning, surpassing available state-of-the-art in silico tools. In addition, DeepCRISPR fully automates the identification of sequence and epigenetic features that may affect sgRNA knockout efficacy in a data-driven manner. DeepCRISPR is available at http://www.deepcrispr.net/ .