Browsing by Author "Ding, Li"

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    Animal Models and Their Role in Imaging-Assisted Co-Clinical Trials
    (Tomography) Peehl, Donna M; Badea, Cristian T; Chenevert, Thomas L; Daldrup-Link, Heike E; Ding, Li; Dobrolecki, Lacey E; Houghton, A McGarry; Kinahan, Paul E; Kurhanewicz, John; Lewis, Michael T; Li, Shunqiang; Luker, Gary D; Ma, Cynthia X; Manning, H Charles; Mowery, Yvonne M; O'Dwyer, Peter J; Pautler, Robia G; Rosen, Mark A; Roudi, Raheleh; Ross, Brian D; Shoghi, Kooresh I; Sriram, Renuka; Talpaz, Moshe; Wahl, Richard L; Zhou, Rong
    The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients’ tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials.
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    CMOS-based carbon nanotube pass-transistor logic integrated circuits.
    (Nature communications, 2012-02) Ding, Li; Zhang, Zhiyong; Liang, Shibo; Pei, Tian; Wang, Sheng; Li, Yan; Zhou, Weiwei; Liu, Jie; Peng, Lian-Mao
    Field-effect transistors based on carbon nanotubes have been shown to be faster and less energy consuming than their silicon counterparts. However, ensuring these advantages are maintained for integrated circuits is a challenge. Here we demonstrate that a significant reduction in the use of field-effect transistors can be achieved by constructing carbon nanotube-based integrated circuits based on a pass-transistor logic configuration, rather than a complementary metal-oxide semiconductor configuration. Logic gates are constructed on individual carbon nanotubes via a doping-free approach and with a single power supply at voltages as low as 0.4 V. The pass-transistor logic configurarion provides a significant simplification of the carbon nanotube-based circuit design, a higher potential circuit speed and a significant reduction in power consumption. In particular, a full adder, which requires a total of 28 field-effect transistors to construct in the usual complementary metal-oxide semiconductor circuit, uses only three pairs of n- and p-field-effect transistors in the pass-transistor logic configuration.
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    The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution.
    (Cell, 2020-04) Rozenblatt-Rosen, Orit; Regev, Aviv; Oberdoerffer, Philipp; Nawy, Tal; Hupalowska, Anna; Rood, Jennifer E; Ashenberg, Orr; Cerami, Ethan; Coffey, Robert J; Demir, Emek; Ding, Li; Esplin, Edward D; Ford, James M; Goecks, Jeremy; Ghosh, Sharmistha; Gray, Joe W; Guinney, Justin; Hanlon, Sean E; Hughes, Shannon K; Hwang, E Shelley; Iacobuzio-Donahue, Christine A; Jané-Valbuena, Judit; Johnson, Bruce E; Lau, Ken S; Lively, Tracy; Mazzilli, Sarah A; Pe'er, Dana; Santagata, Sandro; Shalek, Alex K; Schapiro, Denis; Snyder, Michael P; Sorger, Peter K; Spira, Avrum E; Srivastava, Sudhir; Tan, Kai; West, Robert B; Williams, Elizabeth H; Human Tumor Atlas Network
    Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.