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Your search keyword '"Luo, Yuling"' showing total 24 results
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24 results on '"Luo, Yuling"'

1. An image compression-then-encryption algorithm using piecewise asymptotic deterministic random measurement matrix.

Author

Luo, Yuling, Huang, Xianya, Zhang, Shunsheng, and Liu, Junxiu

Subjects
RANDOM matrices, IMAGE encryption, DISCRETE wavelet transforms, TIME complexity, ALGORITHMS, PUBLIC key cryptography, COMPRESSED sensing
Abstract

A digital Image Compression Encryption Method (ICEM) is proposed in this work by using the Compressed Sensing (CS), two-dimensional Logistic-adjusted-Sine map, the piecewise asymptotic deterministic system, dynamic diffusion and Hilbert-Logistic permutation. The plain image is pre-processed by a two-dimensional discrete wavelet transform to obtain four kinds of frequency components HH , HL , LH and LL . Dynamic diffusion and the CS are used to process low and high-frequency components, respectively, and then the results are combined to obtain an intermediate cryptographic image. In the process of CS, a measurement matrix is generated by a piecewise asymptotic deterministic random system and a chaotic sequence. To obtain the encrypted image, an improved Hilbert-Logistic permutation method is used to disturb the pixel position of the intermediate cryptographic image. The SHA-256 is utilized to generate the required keys for the encryption process. The proposed ICEM has the ability to resist chosen-plaintext and known-plaintext attacks as the key is selected dynamically. By using the CS the time and space complexity of the algorithm are reduced. It is shown in experimental results that the proposed scheme has good key sensitivity, decryption speed, fast encryption and large key space, and high robustness and security. [ABSTRACT FROM AUTHOR]

Published
2024
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2. Hardware Spiking Neural Networks with Pair-Based STDP Using Stochastic Computing.

Author

Liu, Junxiu, Wang, Yanhu, Luo, Yuling, Zhang, Shunsheng, Jiang, Dong, Hua, Yifan, Qin, Sheng, and Yang, Su

Subjects
ARTIFICIAL neural networks, STANDARD deviations, COMPUTATIONAL complexity
Abstract

Spiking Neural Networks (SNNs) can closely mimic the biological neural network systems. Recently, the SNNs have been developed in hardware circuits to emulate the time encoding and information-processing aspects of the human brain in real-time. However, the hardware SNN systems are suffering from large hardware resource consumption due to the high complexity of computational units. In this paper, a novel hardware SNN system based on stochastic computing is proposed to address this problem. Pair-based spiking-timing-dependent plasticity, coupled with integrate-and-fire neurons are employed to design the SNN. Stochastic computing can simplify the computational components of multipliers, adders, and subtractors in conventional hardware SNNs, hence reduce the hardware resource cost. Experimental results show that compared with the state-of-the-art approaches the proposed SNN system reduces the resource consumption by 58.0% (especially registers by ≥ 65.6%). In the meantime, the maximum normalized root mean square error between the proposed hardware and others is only 0.0097, which can maintain the behaviours of SNN. This work provides a beneficial alternative to the large-scale hardware SNN implementations. [ABSTRACT FROM AUTHOR]

Published
2023
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3. A grape disease identification and severity estimation system.

Author

Shu, Haiping, Liu, Junxiu, Hua, Yifan, Chen, Jian, Zhang, Shunsheng, Su, Min, and Luo, Yuling

Subjects
PLANT diseases, PLURALITY voting, ECONOMIC forecasting, SYSTEM identification, DATABASES, FOOD crops
Abstract

It is an important research of automatically identifying the type and severity level of crop diseases, which affects food production, disease control, and economic loss prediction. Deep learning-based methods have achieved successful application for disease identification. However, the method of only using a single network model to identify crop disease is simple and limited since networks vary in complexity and architecture. Furthermore, to measure the effectiveness of the measures taken, precisely quantifying the level of severity is necessary, instead of simply dividing the level into serious or not. In response to these problems, a novel system of disease identification and severity estimation is proposed in this paper. Firstly, an ensemble learning model is proposed to recognize crop diseases, which consider the comprehensive outputs of ResNet50, Inceptionv3, and DenseNet121. The relative majority voting is used as the ensemble classifier to obtain the final identification result. Second, a pixel-level segmentation model is proposed to precisely estimate disease severity after the disease is identified, which can track small changes in infected areas and obtain fine-grained resolutions. DeepLab architecture, encoder-decoder, and dilated convolution are integrated into the proposed segmentation model. Furthermore, an attention mechanism is applied to DeepLabv3+ to improve the performance of severity estimation, which can give more weight to disease areas to achieve more precise segmentation. A public grape disease database is used to verify the performance of the proposed system. Experimental results show that compared with an individual model and other existing studies, the proposed disease identification model has stronger robustness and higher identification accuracy. Furthermore, the proposed severity estimation model also achieves a lower severity error and a higher classification accuracy than baseline models of DeepLabv3+, PspNet, and SegNet. [ABSTRACT FROM AUTHOR]

Published
2023
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4. An image encryption scheme based on block compressed sensing and Chen's system.

Author

Luo, Yuling, Liang, Yuting, Zhang, Shunsheng, Liu, Junxiu, and Wang, Fangxiao

Abstract

Image encryption is a common way of information protection. However, most of the existing image encryption schemes have a low transmission efficiency and large memory consumption due to ciphertext redundancy. A highly-efficient and secure image algorithm with block compressed sensing (BCS) is designed in this paper to protect image information and reduce redundant data. Firstly, the original image is sparsely processed by discrete wavelet transform (DWT), and then pixel positions in the global scope are scrambled by chaotic sequence. Secondly, several image blocks are obtained by dividing scrambled images. Then, the image blocks are measured by a key-controlled partial Hadamard matrix to reduce the dimension. Finally, image blocks are merged and a proposed randomly selected pixel diffusion (RSPD) is used to further enhance security performance and the anti-statistic analysis ability. Specifically, the SHA-512 values of the original image are used for the key generation, and then the plaintext sensitivity is improved. The pseudo-random sequences that are required for scrambling and diffusion are produced by the Chen's system and logistic map. Results show that the proposed mechanism can effectively reduce the redundant information and has a lower computational complexity and higher security performance than existing methods. [ABSTRACT FROM AUTHOR]

Published
2023
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5. COVER: A Secure Blind Image Watermarking Scheme.

Author

Luo, Yuling, Wang, Fangxiao, Liu, Junxiu, Li, Liangjia, Yang, Su, and Zhang, Shunsheng

Subjects
*DIGITAL image watermarking, *DIGITAL watermarking, *DISCRETE wavelet transforms, *SIGNAL-to-noise ratio, *COMPUTATIONAL complexity, *ERROR rates
Abstract

The robustness and imperceptibility of the watermarking algorithm are a pair of contradictory properties. When the robustness increases, the imperceptibility decreases. Most strategies proposed in the literature usually concentrate on improving robustness, but few consider the relationship between robustness and imperceptibility. To deal with this problem, a robust blind image watermarking method is proposed in this work, which is composed of a logistic-sine-COupling map, discrete waVElet transform, and appRoximate maximum eigenvalue of Schur decomposition, namely COVER. In the proposed COVER, an objective function and a two-stage search method are designed to determine the optimal embedding coefficient, thus balancing the imperceptibility and robustness of this work. Specifically, the host image is transformed into four sub-bands by discrete wavelet transform, and the low-low sub-band is further separated into non-overlapping blocks which can be calculated to get the approximate maximum eigenvalues (AMEs) of Schur decomposition. Especially, each AME is not contained in the real Schur decomposition, which effectively reduces the computational complexity. Then, the original AMEs of the host image are updated to complete the embedding process according to the binary feature of encrypted watermark and the proposed embedding method. Finally, the watermarked image is obtained. The experimental results show that all peak signal noise ratio values are above 42 dB, structural similarity index measure values are above 0.98, normalized correlation values are above 0.9, and all bit errors rates are less than 0.14. Compared with six state-of-the-art schemes, the proposed COVER has strong robustness, good imperceptibility, large capacity, and low computational complexity. [ABSTRACT FROM AUTHOR]

Published
2022
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6. Image encryption using chaotic map and cellular automata.

Author

Li, Lanhang, Luo, Yuling, Qiu, Senhui, Ouyang, Xue, Cao, Lvchen, and Tang, Shunbin

Subjects
IMAGE encryption, CELLULAR automata, COLUMNS
Abstract

Recent encryption schemes are not sensitive enough to plain-images, which leads to low robustness and easy vulnerability to attacks. By employing chaotic maps and Cellular Automata, a novel image encryption algorithm is proposed in this work to increase the sensitivity to plain-images and improve security. Firstly, initial values of the two-dimensional Logistic-Sine-Coupling Map and the Logistic-Sine-Cosine Map are calculated by the SHA-256 of the original image, and the process of diffusion is conducted. Secondly, the key matrices are produced by iterating chaotic maps in the process of permutation. The diffused image is scrambled by the index matrices, which are produced by sorting every row or column of the key matrices. Finally, the scrambled image is transformed into cipher-image by using Cellular Automata. Experimental results and theoretical analysis show that the proposed scheme has good security as it can effectively resist various attacks. [ABSTRACT FROM AUTHOR]

Published
2022
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7. A Blind and Robust Image Watermarking Algorithm in the Spatial Domain using Two-level Partition.

Author

Li, Liangjia, Luo, Yuling, Liu, Junxiu, and Qiu, Senhui

Subjects
*DIGITAL image watermarking, *DISCRETE cosine transforms, *SIGNAL-to-noise ratio, *STANDARD deviations, *INVISIBILITY
Abstract

To improve the performance of the blind image watermarking technique, a novel blind and robust image watermarking scheme in the spatial-domain by applying a two-level partition is proposed in this work. Specifically, the host image is firstly partitioned into non-overlapping 4 × 4 sub-blocks, and the standard deviations of all sub-blocks are computed in the meanwhile. Then, the sub-blocks with lower standard deviation are selected, and each selected block is partitioned into four non-overlapping 2 × 2 sub-blocks. Thereafter, the direct current coefficients of three 2 × 2 sub-blocks (i.e., top-left, top-right, and bottom-left sub-blocks) are computed in the spatial-domain without carrying out the two-dimensional discrete cosine transform. Lastly, utilizing the correlation principle between adjacent 2 × 2 sub-blocks, two bits of watermark are embedded into a 4 × 4 sub-block via adjusting the direct current coefficients of the three 2 × 2 sub-blocks. Experimental results show that the proposed image watermarking scheme is suitable for gray-scale and color images, and possesses a good performance in terms of invisibility and robustness. In particular, all peak signal noise ratios are greater than 42 dB, all structural similarity index measures are more than 0.96, and the normalized correlations are greater than 0.85 under various attacks. [ABSTRACT FROM AUTHOR]

Published
2024
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8. Efficacy of administrative intervention for neurosurgical patients with off-label use of alprostadil lipid microsphere.

Author

Luo, Yuling, Fan, Qingze, Yu, Yongqi, Zhang, Lunhui, Dong, Limei, and Luo, Hongli

Subjects
*OFF-label use (Drugs), *PROSTAGLANDIN E1, *NEUROSURGERY, *REWARD (Psychology), *DRUG utilization
Abstract

As an adjuvant drug, alprostadil lipid microsphere injection (Lipo-PGE1) is one of the best-selling drugs in China in recent years. However, the off-label use of Lipo-PGE1 is very common. This study aimed to investigate the use of Lipo-PGE1 and evaluate the clinical effects and economic benefits after administrative intervention on inappropriate use of Lipo-PGE1 in neurosurgical patients in a Chinese tertiary hospital. Administrative interventions were implemented from January to December 2018 by reducing the procurement volume of Lipo-PGE1, judging the rationality of medical records, and establishing reward and punishment mechanisms. Administrative interventions significantly decreased prescription rate (49.98% vs 22.49%), utilization (22,311 DDDs vs 8334 DDDs), drug use density (43.52 DDDs/TID vs 15.84 DDDs/TID), total expenditure (3.58 million RMB vs 1.30 million RMB), and average expenditure (2025.04 RMB vs 1466.49 RMB) of Lipo-PGE1. To our delight, these intervention effects were maintained or even better in the 1-year post-intervention period. Moreover, in the intervention and post-intervention phases, the Lipo-PGE1 use for no indications as well as inappropriate drug dose, frequency, menstruum type, combination, and contraindication were markedly reduced. Besides, the mean costs (P < 0.001), and mean duration (P < 0.001) of Lipo-PGE1 were also obviously decreased. The administrative intervention obviously reduced the off-label use of Lipo-PGE1. However, there still remains a number of inappropriate uses of Lipo-PGE1. To further improve the rational use of Lipo-PGE1, combination of administrative intervention and real-time clinical pharmacists intervention should be implemented. [ABSTRACT FROM AUTHOR]

Published
2022
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9. An image encryption scheme based on particle swarm optimization algorithm and hyperchaotic system.

Author

Luo, Yuling, Ouyang, Xue, Liu, Junxiu, Cao, Lvchen, and Zou, Yanli

Subjects
*IMAGE encryption, *PARTICLE swarm optimization, *MATHEMATICAL optimization, *PARTICLE motion, *DIGITAL images, *CRYPTOGRAPHY
Abstract

Protecting digital images is crucial, and image encryption schemes based on chaotic systems have been extensively studied where image permutation is a critical process. The updating processes of particle swarm optimization algorithm have the ability to change the rules of particles motion, and it can be employed to permutate image. In this work, an image encryption scheme based on the updating processes of particle swarm optimization algorithm and hyperchaotic system is proposed. Specifically, a key generation mechanism combined with secure hash algorithm 256 hash is first introduced to generate the initial values of hyperchaotic complex Lü system. Then, the plain image is confused by the position and velocity updating processes of particle swarm optimization algorithm. In addition, an adaptive diffusion mechanism is designed and applied to the confused image to obtain the final cipher image. Simulation results and security analysis show that the proposed scheme exhibits good performance of sophisticated dynamic behavior, high sensitivity to key, and effectively resisting the typical cryptanalysis attacks, and provides an alternative to real-time image encryption application. [ABSTRACT FROM AUTHOR]

Published
2022
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10. Minimally buffered deflection router for spiking neural network hardware implementations.

Author

Liu, Junxiu, Jiang, Dong, Luo, Yuling, Qiu, Senhui, and Huang, Yongchuang

Subjects
ELECTRONIC circuits, ENERGY consumption, SCALABILITY, HARDWARE, INFORMATION processing
Abstract

Spiking neural networks (SNNs) have the potential to closely mimic the information processing of biological brains, by using massive neurons that are interconnected in a complex network. Recent researches have considered using electronic hardware circuits to SNN implementations to meet real-time processing requirements. Network-on-Chips (NoCs) have been widely used to develop such SNN circuits as their interconnections can offer stable interconnectivity for neuron communications with high throughput and real-time execution. However, its scalability is limited due to expensive and complex NoC routers which leads to high energy consumption and large area utilization. Therefore, a minimally buffered deflection router (MBDR) is proposed in this work to address the scalability challenge of the hardware SNNs. It employs a deflection router technique to remove most of the inter-buffers and other expensive components of the conventional routers. Moreover, a novel flow controller is developed in MBDR to further reduce power consumption. Compared to existing approaches, experimental results show that based on 90-nm CMOS technology the area and power consumption of the proposed router are reduced by ~ 86% and ~ 88%, respectively. In the meantime, system throughput is maintained at a high level. [ABSTRACT FROM AUTHOR]

Published
2021
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11. An Efficient, Low-Cost Routing Architecture for Spiking Neural Network Hardware Implementations.

Author

Luo, Yuling, Wan, Lei, Liu, Junxiu, Harkin, Jim, and Cao, Yi

Subjects
ARTIFICIAL neural networks, NEURAL computers, ARTIFICIAL intelligence, INFORMATION processing, INFORMATION science
Abstract

The basic processing units in brain are neurons and synapses that are interconnected in a complex pattern and show many surprised information processing capabilities. The researchers attempt to mimic this efficiency and build artificial neural systems in hardware device to emulate the key information processing principles of the brain. However, the neural network hardware system has a challenge of interconnecting neurons and synapses efficiently. An efficient, low-cost routing architecture (ELRA) is proposed in this paper to provide a communication infrastructure for the hardware spiking neuron networks (SNN). A dynamic traffic arbitration strategy is employed in ELRA, where the traffic status weights of input ports are calculated in real-time according to the channel traffic statuses and the port with the largest traffic status weight is given a high priority to forward packets. This strategy enables the router to serve congested ports preferentially, which can balance the overall network traffic loads. Experimental results show the feasibility of ELRA under various traffic scenarios, and the hardware synthesis result using SAED 90 nm technology demonstrates it has a low hardware area overhead which maintains scalability for large-scale SNN hardware implementations. [ABSTRACT FROM AUTHOR]

Published
2018
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13. An efficient and self-adapting colour-image encryption algorithm based on chaos and interactions among multiple layers.

Author

Luo, Yuling, Zhou, Ronglong, Liu, Junxiu, Qiu, Senhui, and Cao, Yi

Subjects
DATA encryption, ALGORITHMS, CRYPTOSYSTEMS, COLOR image processing, ENCODING
Abstract

In this paper, we propose an efficient and self-adapting colour-image encryption algorithm based on chaos and the interactions among multiple red, green and blue (RGB) layers. Our study uses two chaotic systems and the interactions among the multiple layers to strengthen the cryptosystem for the colour-image encryption, which can achieve better confusion and diffusion performances. In the confusion process, we use the novel Rubik’s Cube Scheme (RCS) to scramble the image. The significant advantage of this approach is that it sufficiently destroys the correlation among the different layers of colour image, which is the most important feature of the randomness for the encryption. The theoretical analysis and experimental results show that the proposed algorithm can improve the encoding efficiency, enhances the security of the cipher-text, has a large key space and high key sensitivity, and is also able to resist statistical and exhaustive attacks. [ABSTRACT FROM AUTHOR]

Published
2018
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14. A parallel image encryption algorithm based on the piecewise linear chaotic map and hyper-chaotic map.

Author

Luo, Yuling, Zhou, Ronglong, Liu, Junxiu, Cao, Yi, and Ding, Xuemei

Abstract

This paper proposes a parallel digital image encryption algorithm based on a piecewise linear chaotic map (PWLCM) and a four-dimensional hyper-chaotic map (FDHCM). Firstly, two decimals are obtained based on the plain-image and external keys, using a novel parallel quantification method. They are used as the initial value and control parameter for the PWLCM. Then, an encryption matrix and four chaotic sequences are constructed using the PWLCM and FDHCM, which control the permutation and diffusion processes. The proposed algorithm is implemented and tested in parallel based on a graphics processing unit device. Numerical analysis and experimental results show that the proposed algorithm achieves a high encryption speed and a good security performance, which provides a potential solution for real-time image encryption applications. [ABSTRACT FROM AUTHOR]

Published
2018
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18. A chaotic map-control-based and the plain image-related cryptosystem.

Author

Luo, Yuling, Cao, Lvchen, Qiu, Senhui, Lin, Hui, Harkin, Jim, and Liu, Junxiu

Abstract

A novel image encryption algorithm based on the total plain image and tent map is proposed in this work. The pixels' value of a plain image and an initial key are firstly quantified to be a decimal to be used as the initial value of tent map. The quantification algorithm is mainly based on multiplication operation. Therefore, the tiny changes of the plain image can lead to very different quantification results. Then, a digital sequence generated from tent map is transformed to two ergodic sequences which are used for the following permutation, and the diffusion is controlled at the same time. In the diffusion process, the pixel values are modified based on the division and modulus operations according to eight special chaotic values. Finally, the performance analysis and test experiments are achieved, and the results illustrate that there is a high security against several common attacks. [ABSTRACT FROM AUTHOR]

Published
2016
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21. Extensive HPV-Related Carcinoma In Situ of the Upper Aerodigestive Tract with 'Nonkeratinizing' Histologic Features.

Author

Chernock, Rebecca, Nussenbaum, Brian, Thorstad, Wade, Luo, Yuling, Ma, Xiao-Jun, El-Mofty, Samir, and Lewis, James

Abstract

Over the past several decades, it has become clear that human papillomavirus (HPV) is important for the development and progression of many head and neck squamous cell carcinomas, particularly those arising in the oropharyngeal tonsillar crypts. Yet, our understanding of HPV's role in premalignant squamous lesions remains relatively poor. This is in part because premalignant lesions of the oropharyngeal tonsillar crypt tissue, where most HPV-related carcinomas arise, are difficult if not impossible to identify. Recent evidence does suggest a role for HPV in a subset of premalignant lesions of the surface epithelium, especially the oral cavity, despite the rarity of HPV-related invasive squamous cell carcinomas at this site. Furthermore, these HPV-related oral cavity dysplasias appear to have unique, bowenoid histologic features described as 'basaloid' with full-thickness loss of squamous maturation, mitotic figures and apoptosis throughout. Here, we present a unique case of an HPV-related premalignant lesion (squamous cell carcinoma in situ) extensively involving the surface epithelium of the oral cavity, oropharynx and larynx that had 'nonkeratinizing' histologic features typical of HPV-related invasive squamous cell carcinoma. This case was strongly p16 positive by immunohistochemistry and harbored transcriptionally active HPV as demonstrated by E6/E7 RNA in situ hybridization. Furthermore, the patient had an excellent response to radiation treatment. [ABSTRACT FROM AUTHOR]

Published
2014
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22. Adenosquamous Carcinoma of the Head and Neck: Relationship to Human Papillomavirus and Review of the Literature.

Author

Masand, Ramya, El-Mofty, Samir, Ma, Xiao-Jun, Luo, Yuling, Flanagan, John, and Lewis, James

Abstract

denosquamous carcinoma (ADSC) of the head and neck is an aggressive variant of squamous cell carcinoma (SCC). Certain variants of head and neck SCC are human papillomavirus (HPV)-related and have better prognosis. The relationship of HPV to head and neck ADSC has not been investigated. We searched our files for the term 'adenosquamous' and head and neck subsites and found cases from 1998 to 2009. The requisite histologic criteria were the presence of SCC combined with distinct gland formation and/or intracellular mucin. DNA in situ hybridization for high-risk HPV, RNA in situ hybridization for high risk HPV E6 and E7 transcripts, and immunohistochemistry for p16 and p53 were performed. The existing literature on ADSC was also reviewed. Of the 18 cases, eight were from the larynx and hypopharynx, four from the oral cavity, three from the oropharynx, and three from the nasal cavity. Three cases (16%) showed both high risk HPV E6 and E7 and p16 expression, one from the nasal cavity and two from the oropharynx. Both oropharyngeal carcinoma patients were alive and disease free at 34 and 103 months, respectively. ADSCs of the head and neck are a heterogeneous group of tumors. A small minority of cases harbor HPV and most of these, particularly those occurring at sites with known high prevalence of HPV, show active viral transcription with detectable E6 and E7 and overexpression of p16. The HPV-related oropharyngeal cases, though rare, appear to do very well clinically, while the remaining cohort of ADSC patients do quite poorly. Head and neck ADSC appears to be a mixed variant that can be further classified according to its HPV status. [ABSTRACT FROM AUTHOR]

Published
2011
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23. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements.

Author

Shi, Leming, Reid, Laura H., Jones, Wendell D., Shippy, Richard, Warrington, Janet A., Baker, Shawn C., Collins, Patrick J., de Longueville, Francoise, Kawasaki, Ernest S., Lee, Kathleen Y., Luo, Yuling, Sun, Yongming Andrew, Willey, James C., Setterquist, Robert A., Fischer, Gavin M., Tong, Weida, Dragan, Yvonne P., Dix, David J., Frueh, Felix W., and Goodsaid, Federico M.

Abstract

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings. [ABSTRACT FROM AUTHOR]

Published
2006
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24. 31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016): part one

Author

Lundqvist, Andreas, van Hoef, Vincent, Zhang, Xiaonan, Wennerberg, Erik, Lorent, Julie, Witt, Kristina, Sanz, Laia Masvidal, Liang, Shuo, Murray, Shannon, Larsson, Ola, Kiessling, Rolf, Mao, Yumeng, Sidhom, John-William, Bessell, Catherine A., Havel, Jonathan, Schneck, Jonathan, Chan, Timothy A., Sachsenmeier, Eliot, Woods, David, Berglund, Anders, Ramakrishnan, Rupal, Sodre, Andressa, Weber, Jeffrey, Zappasodi, Roberta, Li, Yanyun, Qi, Jingjing, Wong, Philip, Sirard, Cynthia, Postow, Michael, Newman, Walter, Koon, Henry, Velcheti, Vamsidhar, Callahan, Margaret K., Wolchok, Jedd D., Merghoub, Taha, Lum, Lawrence G., Choi, Minsig, Thakur, Archana, Deol, Abhinav, Dyson, Gregory, Shields, Anthony, Haymaker, Cara, Uemura, Marc, Murthy, Ravi, James, Marihella, Wang, Daqing, Brevard, Julie, Monaghan, Catherine, Swann, Suzanne, Geib, James, Cornfeld, Mark, Chunduru, Srinivas, Agrawal, Sudhir, Yee, Cassian, Wargo, Jennifer, Patel, Sapna P., Amaria, Rodabe, Tawbi, Hussein, Glitza, Isabella, Woodman, Scott, Hwu, Wen-Jen, Davies, Michael A., Hwu, Patrick, Overwijk, Willem W., Bernatchez, Chantale, Diab, Adi, Massarelli, Erminia, Segal, Neil H., Ribrag, Vincent, Melero, Ignacio, Gangadhar, Tara C., Urba, Walter, Schadendorf, Dirk, Ferris, Robert L., Houot, Roch, Morschhauser, Franck, Logan, Theodore, Luke, Jason J., Sharfman, William, Barlesi, Fabrice, Ott, Patrick A., Mansi, Laura, Kummar, Shivaani, Salles, Gilles, Carpio, Cecilia, Meier, Roland, Krishnan, Suba, McDonald, Dan, Maurer, Matthew, Gu, Xuemin, Neely, Jaclyn, Suryawanshi, Satyendra, Levy, Ronald, Khushalani, Nikhil, Wu, Jennifer, Zhang, Jinyu, Basher, Fahmin, Rubinstein, Mark, Bucsek, Mark, Qiao, Guanxi, MacDonald, Cameron, Hylander, Bonnie, Repasky, Elizabeth, Chatterjee, Shilpak, Daenthanasanmak, Anusara, Chakraborty, Paramita, Toth, Kyle, Meek, Megan, Garrett-Mayer, Elizabeth, Nishimura, Michael, Paulos, Chrystal, Beeson, Craig, Yu, Xuezhong, Mehrotra, Shikhar, Zhao, Fei, Evans, Kathy, Xiao, Christine, Holtzhausen, Alisha, Hanks, Brent A., Scharping, Nicole, Menk, Ashley V., Moreci, Rebecca, Whetstone, Ryan, Dadey, Rebekah, Watkins, Simon, Ferris, Robert, Delgoffe, Greg M., Peled, Jonathan, Devlin, Sean, Staffas, Anna, Lumish, Melissa, Rodriguez, Kori Porosnicu, Ahr, Katya, Perales, Miguel, Giralt, Sergio, Taur, Ying, Pamer, Eric, van den Brink, Marcel R. M., Jenq, Robert, Annels, Nicola, Pandha, Hardev, Simpson, Guy, Mostafid, Hugh, Harrington, Kevin, Melcher, Alan, Grose, Mark, Davies, Bronwyn, Au, Gough, Karpathy, Roberta, Shafren, Darren, Ricca, Jacob, Zamarin, Dmitriy, Batista, Luciana, Marliot, Florence, Vasaturo, Angela, Carpentier, Sabrina, Poggionovo, Cécile, Frayssinet, Véronique, Fieschi, Jacques, Van den Eynde, Marc, Pagès, Franck, Galon, Jérôme, Hermitte, Fabienne, Smith, Sean G., Nguyen, Khue, Ravindranathan, Sruthi, Koppolu, Bhanu, Zaharoff, David, Schvartsman, Gustavo, Bassett, Roland, McQuade, Jennifer L., Haydu, Lauren E., Kline, Douglas, Chen, Xiufen, Fosco, Dominick, Kline, Justin, Overacre, Abigail, Chikina, Maria, Brunazzi, Erin, Shayan, Gulidanna, Horne, William, Kolls, Jay, Bruno, Tullia C., Workman, Creg, Vignali, Dario, Adusumilli, Prasad S., Ansa-Addo, Ephraim A, Li, Zihai, Gerry, Andrew, Sanderson, Joseph P., Howe, Karen, Docta, Roslin, Gao, Qian, Bagg, Eleanor A. L., Tribble, Nicholas, Maroto, Miguel, Betts, Gareth, Bath, Natalie, Melchiori, Luca, Lowther, Daniel E., Ramachandran, Indu, Kari, Gabor, Basu, Samik, Binder-Scholl, Gwendolyn, Chagin, Karen, Pandite, Lini, Holdich, Tom, Amado, Rafael, Zhang, Hua, Glod, John, Bernstein, Donna, Jakobsen, Bent, Mackall, Crystal, Wong, Ryan, Silk, Jonathan D., Adams, Katherine, Hamilton, Garth, Bennett, Alan D., Brett, Sara, Jing, Junping, Quattrini, Adriano, Saini, Manoj, Wiedermann, Guy, Brewer, Joanna, Duong, MyLinh, Lu, An, Chang, Peter, Mahendravada, Aruna, Shinners, Nicholas, Slawin, Kevin, Spencer, David M., Foster, Aaron E., Bayle, J. Henri, Bergamaschi, Cristina, Ng, Sinnie Sin Man, Nagy, Bethany, Jensen, Shawn, Hu, Xintao, Alicea, Candido, Fox, Bernard, Felber, Barbara, Pavlakis, George, Chacon, Jessica, Yamamoto, Tori, Garrabrant, Thomas, Cortina, Luis, Powell, Daniel J., Donia, Marco, Kjeldsen, Julie Westerlin, Andersen, Rikke, Westergaard, Marie Christine Wulff, Bianchi, Valentina, Legut, Mateusz, Attaf, Meriem, Dolton, Garry, Szomolay, Barbara, Ott, Sascha, Lyngaa, Rikke, Hadrup, Sine Reker, Sewell, Andrew Kelvin, Svane, Inge Marie, Fan, Aaron, Kumai, Takumi, Celis, Esteban, Frank, Ian, Stramer, Amanda, Blaskovich, Michelle A., Wardell, Seth, Fardis, Maria, Bender, James, Lotze, Michael T., Goff, Stephanie L., Zacharakis, Nikolaos, Assadipour, Yasmine, Prickett, Todd D., Gartner, Jared J., Somerville, Robert, Black, Mary, Xu, Hui, Chinnasamy, Harshini, Kriley, Isaac, Lu, Lily, Wunderlich, John, Robbins, Paul F., Rosenberg, Steven, Feldman, Steven A., Trebska-McGowan, Kasia, Malekzadeh, Parisa, Payabyab, Eden, Sherry, Richard, Gokuldass, Aishwarya, Kopits, Charlene, Rabinovich, Brian, Green, Daniel S., Kamenyeva, Olena, Zoon, Kathryn C., Annunziata, Christina M., Hammill, Joanne, Helsen, Christopher, Aarts, Craig, Bramson, Jonathan, Harada, Yui, Yonemitsu, Yoshikazu, Mwawasi, Kenneth, Denisova, Galina, Giri, Rajanish, Jin, Benjamin, Campbell, Tracy, Draper, Lindsey M., Stevanovic, Sanja, Yu, Zhiya, Weissbrich, Bianca, Restifo, Nicholas P., Trimble, Cornelia L., Hinrichs, Christian S., Tsang, Kwong, Fantini, Massimo, Hodge, James W., Fujii, Rika, Fernando, Ingrid, Jochems, Caroline, Heery, Christopher, Gulley, James, Soon-Shiong, Patrick, Schlom, Jeffrey, Jing, Weiqing, Gershan, Jill, Blitzer, Grace, Weber, James, McOlash, Laura, Johnson, Bryon D., Kiany, Simin, Gangxiong, Huang, Kleinerman, Eugenie S., Klichinsky, Michael, Ruella, Marco, Shestova, Olga, Kenderian, Saad, Kim, Miriam, Scholler, John, June, Carl H., Gill, Saar, Moogk, Duane, Zhong, Shi, Liadi, Ivan, Rittase, William, Fang, Victoria, Dougherty, Janna, Perez-Garcia, Arianne, Osman, Iman, Zhu, Cheng, Varadarajan, Navin, Frey, Alan, Krogsgaard, Michelle, Landi, Daniel, Fousek, Kristen, Mukherjee, Malini, Shree, Ankita, Joseph, Sujith, Bielamowicz, Kevin, Byrd, Tiara, Ahmed, Nabil, Hegde, Meenakshi, Lee, Sylvia, Byrd, David, Thompson, John, Bhatia, Shailender, Tykodi, Scott, Delismon, Judy, Chu, Liz, Abdul-Alim, Siddiq, Ohanian, Arpy, DeVito, Anna Marie, Riddell, Stanley, Margolin, Kim, Magalhaes, Isabelle, Mattsson, Jonas, Uhlin, Michael, Nemoto, Satoshi, Villarroel, Patricio Pérez, Nakagawa, Ryosuke, Mule, James J., Mailloux, Adam W., Mata, Melinda, Nguyen, Phuong, Gerken, Claudia, DeRenzo, Christopher, Gottschalk, Stephen, Mathieu, Mélissa, Pelletier, Sandy, Stagg, John, Turcotte, Simon, Minutolo, Nicholas, Sharma, Prannda, Tsourkas, Andrew, Mockel-Tenbrinck, Nadine, Mauer, Daniela, Drechsel, Katharina, Barth, Carola, Freese, Katharina, Kolrep, Ulrike, Schult, Silke, Assenmacher, Mario, Kaiser, Andrew, Mullinax, John, Hall, MacLean, Le, Julie, Kodumudi, Krithika, Royster, Erica, Richards, Allison, Gonzalez, Ricardo, Sarnaik, Amod, Pilon-Thomas, Shari, Nielsen, Morten, Krarup-Hansen, Anders, Hovgaard, Dorrit, Petersen, Michael Mørk, Loya, Anand Chainsukh, Junker, Niels, Rivas, Charlotte, Parihar, Robin, Rooney, Cliona M., Qin, Haiying, Nguyen, Sang, Su, Paul, Burk, Chad, Duncan, Brynn, Kim, Bong-Hyun, Kohler, M. Eric, Fry, Terry, Rao, Arjun A., Teyssier, Noam, Pfeil, Jacob, Sgourakis, Nikolaos, Salama, Sofie, Haussler, David, Richman, Sarah A., Nunez-Cruz, Selene, Gershenson, Zack, Mourelatos, Zissimos, Barrett, David, Grupp, Stephan, Milone, Michael, Rodriguez-Garcia, Alba, Robinson, Matthew K., Adams, Gregory P., Santos, João, Havunen, Riikka, Siurala, Mikko, Cervera-Carrascón, Víctor, Parviainen, Suvi, Antilla, Marjukka, Hemminki, Akseli, Sethuraman, Jyothi, Santiago, Laurelis, Chen, Jie Qing, Dai, Zhimin, Sha, Huizi, Su, Shu, Ding, Naiqing, Liu, Baorui, Pasetto, Anna, Helman, Sarah R., Rosenberg, Steven A., Burgess, Melissa, Zhang, Hui, Lee, Tien, Klingemann, Hans, Nghiem, Paul, Kirkwood, John M., Rossi, John M., Sherman, Marika, Xue, Allen, Shen, Yueh-wei, Navale, Lynn, Kochenderfer, James N., Bot, Adrian, Veerapathran, Anandaraman, Wiener, Doris, Waller, Edmund K., Li, Jian-Ming, Petersen, Christopher, Blazar, Bruce R., Li, Jingxia, Giver, Cynthia R., Wang, Ziming, Grossenbacher, Steven K., Sturgill, Ian, Canter, Robert J., Murphy, William J., Zhang, Congcong, Burger, Michael C., Jennewein, Lukas, Waldmann, Anja, Mittelbronn, Michel, Tonn, Torsten, Steinbach, Joachim P., Wels, Winfried S., Williams, Jason B., Zha, Yuanyuan, Gajewski, Thomas F., Williams, LaTerrica C., Krenciute, Giedre, Kalra, Mamta, Louis, Chrystal, Xin, Gang, Schauder, David, Jiang, Aimin, Joshi, Nikhil, Cui, Weiguo, Zeng, Xue, Zhao, Zeguo, Hamieh, Mohamad, Eyquem, Justin, Gunset, Gertrude, Bander, Neil, Sadelain, Michel, Askmyr, David, Abolhalaj, Milad, Lundberg, Kristina, Greiff, Lennart, Lindstedt, Malin, Angell, Helen K., Kim, Kyoung-Mee, Kim, Seung-Tae, Kim, Sung, Sharpe, Alan D., Ogden, Julia, Davenport, Anna, Hodgson, Darren R., Barrett, Carl, Lee, Jeeyun, Kilgour, Elaine, Hanson, Jodi, Caspell, Richard, Karulin, Alexey, Lehmann, Paul, Ansari, Tameem, Schiller, Annemarie, Sundararaman, Srividya, Roen, Diana, Ayers, Mark, Levitan, Diane, Arreaza, Gladys, Liu, Fang, Mogg, Robin, Bang, Yung-Jue, O’Neil, Bert, Cristescu, Razvan, Friedlander, Philip, Wassman, Karl, Kyi, Chrisann, Oh, William, Bhardwaj, Nina, Bornschlegl, Svetlana, Gustafson, Michael P., Gastineau, Dennis A., Parney, Ian F., Dietz, Allan B., Carvajal-Hausdorf, Daniel, Mani, Nikita, Schalper, Kurt, Rimm, David, Chang, Serena, Kurland, John, Ahlers, Christoph Matthias, Jure-Kunkel, Maria, Cohen, Lewis, Maecker, Holden, Kohrt, Holbrook, Chen, Shuming, Crabill, George, Pritchard, Theresa, McMiller, Tracee, Pardoll, Drew, Pan, Fan, Topalian, Suzanne, Danaher, Patrick, Warren, Sarah, Dennis, Lucas, White, Andrew M., D’Amico, Leonard, Geller, Melissa, Disis, Mary L., Beechem, Joseph, Odunsi, Kunle, Fling, Steven, Derakhshandeh, Roshanak, Webb, Tonya J., Dubois, Sigrid, Conlon, Kevin, Bryant, Bonita, Hsu, Jennifer, Beltran, Nancy, Müller, Jürgen, Waldmann, Thomas, Duhen, Rebekka, Duhen, Thomas, Thompson, Lucas, Montler, Ryan, Weinberg, Andrew, Kates, Max, Early, Brandon, Yusko, Erik, Schreiber, Taylor H., Bivalacqua, Trinity J., Lunceford, Jared, Nebozhyn, Michael, Murphy, Erin, Loboda, Andrey, Kaufman, David R., Albright, Andrew, Cheng, Jonathan, Kang, S. Peter, Shankaran, Veena, Piha-Paul, Sarina A., Yearley, Jennifer, Seiwert, Tanguy, Ribas, Antoni, McClanahan, Terrill K., Sher, Xinwei, Liu, Xiao Qiao, Joe, Andrew, Plimack, Elizabeth, Forrest-Hay, Alex, Guyre, Cheryl A., Narumiya, Kohei, Delcommenne, Marc, Hirsch, Heather A., Deshpande, Amit, Reeves, Jason, Shu, Jenny, Zi, Tong, Michaelson, Jennifer, Law, Debbie, Trehu, Elizabeth, Sathyanaryanan, Sriram, Hodkinson, Brendan P., Hutnick, Natalie A., Schaffer, Michael E., Gormley, Michael, Hulett, Tyler, Ballesteros-Merino, Carmen, Dubay, Christopher, Afentoulis, Michael, Reddy, Ashok, David, Larry, Jayant, Kumar, Agrawal, Swati, Agrawal, Rajendra, Jeyakumar, Ghayathri, Kim, Seongho, Kim, Heejin, Silski, Cynthia, Suisham, Stacey, Heath, Elisabeth, Vaishampayan, Ulka, Vandeven, Natalie, Viller, Natasja Nielsen, O’Connor, Alison, Chen, Hui, Bossen, Bolette, Sievers, Eric, Uger, Robert, Johnson, Lisa, Kao, Hsiang-Fong, Hsiao, Chin-Fu, Lai, Shu-Chuan, Wang, Chun-Wei, Ko, Jenq-Yuh, Lou, Pei-Jen, Lee, Tsai-Jan, Liu, Tsang-Wu, Hong, Ruey-Long, Kearney, Staci J., Black, Joshua C., Landis, Benjamin J., Koegler, Sally, Hirsch, Brooke, Gianani, Roberto, Kim, Jeffrey, He, Ming-Xiao, Zhang, Bingqing, Su, Nan, Luo, Yuling, Ma, Xiao-Jun, Park, Emily, Kim, Dae Won, Copploa, Domenico, Kothari, Nishi, doo Chang, Young, Kim, Richard, Kim, Namyong, Lye, Melvin, Wan, Ee, Knaus, Hanna A., Berglund, Sofia, Hackl, Hubert, Karp, Judith E., Gojo, Ivana, Luznik, Leo, Hong, Henoch S., Koch, Sven D., Scheel, Birgit, Gnad-Vogt, Ulrike, Kallen, Karl-Josef, Wiegand, Volker, Backert, Linus, Kohlbacher, Oliver, Hoerr, Ingmar, Fotin-Mleczek, Mariola, Billingsley, James M., Koguchi, Yoshinobu, Conrad, Valerie, Miller, William, Gonzalez, Iliana, Poplonski, Tomasz, Meeuwsen, Tanisha, Howells-Ferreira, Ana, Rattray, Rogan, Campbell, Mary, Bifulco, Carlo, Bahjat, Keith, Curti, Brendan, Vetsika, E-K, Kallergi, G., Aggouraki, Despoina, Lyristi, Z., Katsarlinos, P., Koinis, Filippos, Georgoulias, V., Kotsakis, Athanasios, Martin, Nathan T., Aeffner, Famke, Cerkovnik, Logan, Pratte, Luke, Kim, Rebecca, Krueger, Joseph, Martínez-Usatorre, Amaia, Jandus, Camilla, Donda, Alena, Carretero-Iglesia, Laura, Speiser, Daniel E., Zehn, Dietmar, Rufer, Nathalie, Romero, Pedro, Panda, Anshuman, Mehnert, Janice, Hirshfield, Kim M., Riedlinger, Greg, Damare, Sherri, Saunders, Tracie, Sokol, Levi, Stein, Mark, Poplin, Elizabeth, Rodriguez-Rodriguez, Lorna, Silk, Ann, Chan, Nancy, Frankel, Melissa, Kane, Michael, Malhotra, Jyoti, Aisner, Joseph, Kaufman, Howard L., Ali, Siraj, Ross, Jeffrey, White, Eileen, Bhanot, Gyan, Ganesan, Shridar, Monette, Anne, Bergeron, Derek, Amor, Amira Ben, Meunier, Liliane, Caron, Christine, Morou, Antigoni, Kaufmann, Daniel, Liberman, Moishe, Jurisica, Igor, Mes-Masson, Anne-Marie, Hamzaoui, Kamel, Lapointe, Rejean, Mongan, Ann, Ku, Yuan-Chieh, Tom, Warren, Sun, Yongming, Pankov, Alex, Looney, Tim, Au-Young, Janice, Hyland, Fiona, Conroy, Jeff, Morrison, Carl, Glenn, Sean, Burgher, Blake, Ji, He, Gardner, Mark, Omilian, Angela R., Bshara, Wiam, Angela, Omilian, Obeid, Joseph M., Erdag, Gulsun, Smolkin, Mark E., Deacon, Donna H., Patterson, James W., Chen, Lieping, Bullock, Timothy N., Slingluff, Craig L., Loffredo, John T., Vuyyuru, Raja, Beyer, Sophie, Spires, Vanessa M., Fox, Maxine, Ehrmann, Jon M., Taylor, Katrina A., Korman, Alan J., Graziano, Robert F., Page, David, Sanchez, Katherine, Martel, Maritza, De Macedo, Mariana Petaccia, Qin, Yong, Reuben, Alex, Spencer, Christine, Guindani, Michele, Racolta, Adriana, Kelly, Brian, Jones, Tobin, Polaske, Nathan, Theiss, Noah, Robida, Mark, Meridew, Jeffrey, Habensus, Iva, Zhang, Liping, Pestic-Dragovich, Lidija, Tang, Lei, Sullivan, Ryan J., Olencki, Thomas, Hutson, Thomas, Roder, Joanna, Blackmon, Shauna, Roder, Heinrich, Stewart, John, Amin, Asim, Ernstoff, Marc S., Clark, Joseph I., Atkins, Michael B., Sosman, Jeffrey, McDermott, David F., Kluger, Harriet, Halaban, Ruth, Snzol, Mario, Asmellash, Senait, Steingrimsson, Arni, Wang, Chichung, Roman, Kristin, Clement, Amanda, Downing, Sean, Hoyt, Clifford, Harder, Nathalie, Schmidt, Guenter, Schoenmeyer, Ralf, Brieu, Nicolas, Yigitsoy, Mehmet, Madonna, Gabriele, Botti, Gerardo, Grimaldi, Antonio, Ascierto, Paolo A., Huss, Ralf, Athelogou, Maria, Hessel, Harald, Buchner, Alexander, Stief, Christian, Binnig, Gerd, Kirchner, Thomas, Sellappan, Shankar, Thyparambil, Sheeno, Schwartz, Sarit, Cecchi, Fabiola, Nguyen, Andrew, Vaske, Charles, Hembrough, Todd, Spacek, Jan, Vocka, Michal, Zavadova, Eva, Skalova, Helena, Dundr, Pavel, Petruzelka, Lubos, Francis, Nicole, Tilman, Rau T., Hartmann, Arndt, Netikova, Irena, Stump, Julia, Tufman, Amanda, Berger, Frank, Neuberger, Michael, Hatz, Rudolf, Lindner, Michael, Sanborn, Rachel E., Handy, John, Huber, Rudolf M., Winter, Hauke, Reu, Simone, Sun, Cheng, Xiao, Weihua, Tian, Zhigang, Arora, Kshitij, Desai, Niyati, Kulkarni, Anupriya, Rajurkar, Mihir, Rivera, Miguel, Deshpande, Vikram, Ting, David, Tsai, Katy, Nosrati, Adi, Goldinger, Simone, Hamid, Omid, Algazi, Alain, Tumeh, Paul, Hwang, Jimmy, Liu, Jacqueline, Chen, Lawrence, Dummer, Reinhard, Rosenblum, Michael, Daud, Adil, Tsao, Tsu-Shuen, Ashworth-Sharpe, Julia, Johnson, Donald, Bhaumik, Srabani, Bieniarz, Christopher, Couto, Joseph, Farrell, Michael, Ghaffari, Mahsa, Hubbard, Antony, Kosmeder, Jerome, Lee, Cleo, Marner, Erin, Uribe, Diana, Zhang, Hongjun, Zhang, Jian, Zhang, Wenjun, Zhu, Yifei, Morrison, Larry, Tsujikawa, Takahiro, Borkar, Rohan N., Azimi, Vahid, Kumar, Sushil, Thibault, Guillaume, Mori, Motomi, El Rassi, Edward, Clayburgh, Daniel R., Kulesz-Martin, Molly F., Flint, Paul W., Coussens, Lisa M., Villabona, Lisa, Masucci, Giuseppe V., Geiss, Gary, Birditt, Brian, Mei, Qian, Huang, Alan, Eagan, Maribeth A., Ignacio, Eduardo, Elliott, Nathan, Dunaway, Dwayne, Jung, Jaemyeong, Merritt, Chris, Sprague, Isaac, Webster, Philippa, Liang, Yan, Wenthe, Jessica, Enblad, Gunilla, Karlsson, Hannah, Essand, Magnus, Savoldo, Barbara, Dotti, Gianpietro, Höglund, Martin, Brenner, Malcolm K., Hagberg, Hans, Loskog, Angelica, Bernett, Matthew J., Moore, Gregory L., Hedvat, Michael, Bonzon, Christine, Chu, Seung, Rashid, Rumana, Avery, Kendra N., Muchhal, Umesh, Desjarlais, John, Kraman, Matthew, Kmiecik, Katarzyna, Allen, Natalie, Faroudi, Mustapha, Zimarino, Carlo, Wydro, Mateusz, Doody, Jacqueline, Srinivasa, Sreesha P., Govindappa, Nagaraja, Reddy, Praveen, Dubey, Aparajita, Periyasamy, Sankar, Adekandi, Madhukara, Dey, Chaitali, Joy, Mary, van Loo, Pieter Fokko, Veninga, Henrike, Shamsili, Setareh, Throsby, Mark, Dolstra, Harry, Bakker, Lex, Alva, Ajjai, Gschwendt, Juergen, Loriot, Yohann, Bellmunt, Joaquim, Feng, Dai, Poehlein, Christian, Powles, Thomas, Antonarakis, Emmanuel S., Drake, Charles G., Wu, Haiyan, De Bono, Johann, Bannerji, Rajat, Byrd, John, Gregory, Gareth, Opat, Stephen, Shortt, Jake, Yee, Andrew J., Raje, Noopur, Thompson, Seth, Balakumaran, Arun, Kumar, Shaji, Rini, Brian I., Choueiri, Toni K., Mariani, Mariangela, Albiges, Laurence, Haanen, John B., Larkin, James, Schmidinger, Manuela, Magazzù, Domenico, di Pietro, Alessandra, Motzer, Robert J., Borch, Troels Holz, Kongsted, Per, Pedersen, Magnus, Met, Özcan, Boudadi, Karim, Wang, Hao, Vasselli, James, Baughman, Jan E., Wigginton, Jon, Abdallah, Rehab, Ross, Ashley, Park, Jiwon, Grossenbacher, Steven, Luna, Jesus I., Withers, Sita, Culp, William, Chen, Mingyi, Monjazeb, Arta, Kent, Michael S., Chandran, Smita, Danforth, David, Yang, James, Klebanoff, Christopher, Goff, Stephanie, Paria, Biman, Sabesan, Arvind, Srivastava, Abhishek, Kammula, Udai, Richards, Jon, Faries, Mark, Andtbacka, Robert H. I., Diaz, Luis A., Le, Dung T., Yoshino, Takayuki, André, Thierry, Bendell, Johanna, Koshiji, Minori, Zhang, Yayan, Kang, S Peter, Lam, Bao, Jäger, Dirk, Bauer, Todd M., Wang, Judy S., Lee, Jean K., Manji, Gulam A., Kudchadkar, Ragini, Kauh, John S., Tang, Shande, Laing, Naomi, Falchook, Gerald, Garon, Edward B., Halmos, Balazs, Rina, Hui, Leighl, Natasha, Lee, Sung Sook, Walsh, William, Dragnev, Konstanin, Piperdi, Bilal, Rodriguez, Luis Paz-Ares, Shinwari, Nabeegha, Wei, Ziewn, Maas, Mary L, Deeds, Michael, Armstrong, Adam, Peterson, Tim, Steinmetz, Sue, Herzog, Thomas, Backes, Floor J., Copeland, Larry, Del Pilar Estevez Diz, Maria, Hare, Thomas W., Huh, Warner, Kim, Byoung-Gie, Moore, Kathleen M., Oaknin, Ana, Small, William, Tewari, Krishnansu S., Monk, Bradley J., Kamat, Ashish M., Nam, Kijoeng, De Santis, Maria, Dreicer, Robert, Hahn, Noah M., Perini, Rodolfo, Siefker-Radtke, Arlene, Sonpavde, Guru, de Wit, Ronald, Witjes, J. Alfred, Keefe, Stephen, Bajorin, Dean, Armand, Philippe, Kuruvilla, John, Moskowitz, Craig, Hamadani, Mehdi, Zinzani, Pier Luigi, Chlosta, Sabine, Bartlett, Nancy, Sabado, Rachel, Saenger, Yvonne, William, Loging, Donovan, Michael Joseph, Sacris, Erlinda, Mandeli, John, Salazar, Andres M., Powderly, John, Brody, Joshua, Nemunaitis, John, Emens, Leisha, Patnaik, Amita, McCaffery, Ian, Miller, Richard, Laport, Ginna, Coveler, Andrew L., Smith, David C., Grilley-Olson, Juneko E., Goel, Sanjay, Gardai, Shyra J., Law, Che-Leung, Means, Gary, Manley, Thomas, Marrone, Kristen A., Rosner, Gary, Anagnostou, Valsamo, Riemer, Joanne, Wakefield, Jessica, Zanhow, Cynthia, Baylin, Stephen, Gitlitz, Barbara, Brahmer, Julie, Signoretti, Sabina, Li, Wenting, Schloss, Charles, Michot, Jean-Marie, Ding, Wei, Christian, Beth, Marinello, Patricia, Shipp, Margaret, Najjar, Yana G., Lin, Butterfield, Lisa H., Tarhini, Ahmad A., Davar, Diwakar, Zarour, Hassane, Rush, Elizabeth, Sander, Cindy, Fu, Siqing, Bauer, Todd, Molineaux, Chris, Bennett, Mark K., Orford, Keith W., Papadopoulos, Kyriakos P., Padda, Sukhmani K., Shah, Sumit A., Colevas, A Dimitrios, Narayanan, Sujata, Fisher, George A., Supan, Dana, Wakelee, Heather A., Aoki, Rhonda, Pegram, Mark D., Villalobos, Victor M., Liu, Jie, Takimoto, Chris H., Chao, Mark, Volkmer, Jens-Peter, Majeti, Ravindra, Weissman, Irving L., Sikic, Branimir I., Yu, Wendy, Conlin, Alison, Ruzich, Janet, Lewis, Stacy, Acheson, Anupama, Kemmer, Kathleen, Perlewitz, Kelly, Moxon, Nicole M., Mellinger, Staci, McArthur, Heather, Juhler-Nøttrup, Trine, Desai, Jayesh, Markman, Ben, Sandhu, Shahneen, Gan, Hui, Friedlander, Michael L., Tran, Ben, Meniawy, Tarek, Lundy, Joanne, Colyer, Duncan, Ameratunga, Malaka, Norris, Christie, Yang, Jason, Li, Kang, Wang, Lai, Luo, Lusong, Qin, Zhen, Mu, Song, Tan, Xuemei, Song, James, Millward, Michael, Katz, Matthew H. G., Bauer, Todd W., Varadhachary, Gauri R., Acquavella, Nicolas, Merchant, Nipun, Petroni, Gina, Rahma, Osama E., Chen, Mei, Song, Yang, Puhlmann, Markus, Khattri, Arun, Brisson, Ryan, Harvey, Christopher, Shah, Jatin, Mateos, Maria Victoria, Matsumoto, Morio, Blacklock, Hilary, Rocafiguera, Albert Oriol, Goldschmidt, Hartmut, Iida, Shinsuke, Yehuda, Dina Ben, Ocio, Enrique, Rodríguez-Otero, Paula, Jagannath, Sundar, Lonial, Sagar, Kher, Uma, San-Miguel, Jesus, de Oliveira, Moacyr Ribeiro, Yimer, Habte, Rifkin, Robert, Schjesvold, Fredrik, Ghori, Razi, Spreafico, Anna, Lee, Victor, Ngan, Roger K. C., To, Ka Fai, Ahn, Myung Ju, Ng, Quan Sing, Lin, Jin-Ching, Swaby, Ramona F., Gause, Christine, Saraf, Sanatan, Chan, Anthony T. C., Lam, Elaine, Tannir, Nizar M., Meric-Bernstam, Funda, Gross, Matt, MacKinnon, Andy, Whiting, Sam, Voss, Martin, Yu, Evan Y., Albertini, Mark R., Ranheim, Erik A., Hank, Jacquelyn A., Zuleger, Cindy, McFarland, Thomas, Collins, Jennifer, Clements, Erin, Weber, Sharon, Weigel, Tracey, Neuman, Heather, Hartig, Greg, Mahvi, David, Henry, MaryBeth, Gan, Jacek, Yang, Richard, Carmichael, Lakeesha, Kim, KyungMann, Gillies, Stephen D., Sondel, Paul M., Subbiah, Vivek, Noffsinger, Lori, Hendricks, Kyle, Bosch, Marnix, Lee, Jay M., Lee, Mi-Heon, Goldman, Jonathan W., Baratelli, Felicita E., Schaue, Dorthe, Wang, Gerald, Rosen, Frances, Yanagawa, Jane, Walser, Tonya C., Lin, Ying Q., Adams, Sharon, Marincola, Franco M., Tumeh, Paul C., Abtin, Fereidoun, Suh, Robert, Reckamp, Karen, Wallace, William D., Zeng, Gang, Elashoff, David A., Sharma, Sherven, Dubinett, Steven M., Pavlick, Anna C., Gastman, Brian, Hanks, Brent, Keler, Tibor, Davis, Tom, Vitale, Laura A., Sharon, Elad, Morishima, Chihiro, Cheever, Martin, Heery, Christopher R., Kim, Joseph W., Lamping, Elizabeth, Marte, Jennifer, McMahon, Sheri, Cordes, Lisa, Fakhrejahani, Farhad, Madan, Ravi, Salazar, Rachel, Zhang, Maggie, Helwig, Christoph, Gulley, James L, Li, Roger, Amrhein, John, Cohen, Zvi, Champagne, Monique, Kamat, Ashish, Aznar, M. Angela, Labiano, Sara, Diaz-Lagares, Angel, Esteller, Manel, Sandoval, Juan, Barbee, Susannah D., Bellovin, David I., Timmer, John C., Wondyfraw, Nebiyu, Johnson, Susan, Park, Johanna, Chen, Amanda, Mkrtichyan, Mikayel, Razai, Amir S., Jones, Kyle S., Hata, Chelsie Y., Gonzalez, Denise, Deveraux, Quinn, Eckelman, Brendan P., Borges, Luis, Bhardwaj, Rukmini, Puri, Raj K., Suzuki, Akiko, Leland, Pamela, Joshi, Bharat H., Bartkowiak, Todd, Jaiswal, Ashvin, Ager, Casey, Ai, Midan, Budhani, Pratha, Chin, Renee, Hong, David, Curran, Michael, Hastings, William D., Pinzon-Ortiz, Maria, Murakami, Masato, Dobson, Jason R., Quinn, David, Wagner, Joel P., Rong, Xianhui, Shaw, Pamela, Dammassa, Ernesta, Guan, Wei, Dranoff, Glenn, Cao, Alexander, Fulton, Ross B., Leonardo, Steven, Fraser, Kathryn, Kangas, Takashi O., Ottoson, Nadine, Bose, Nandita, Huhn, Richard D., Graff, Jeremy, Lowe, Jamie, Gorden, Keith, Uhlik, Mark, O’Neill, Thomas, Widger, Jenifer, Crocker, Andrea, He, Li-Zhen, Weidlick, Jeffrey, Sundarapandiyan, Karuna, Ramakrishna, Venky, Storey, James, Thomas, Lawrence J., Goldstein, Joel, Marsh, Henry C., Grailer, Jamison, Gilden, Julia, Stecha, Pete, Garvin, Denise, Hartnett, Jim, Fan, Frank, Cong, Mei, Cheng, Zhi-jie Jey, Hinner, Marlon J., Aiba, Rachida-Siham Bel, Schlosser, Corinna, Jaquin, Thomas, Allersdorfer, Andrea, Berger, Sven, Wiedenmann, Alexander, Matschiner, Gabriele, Schüler, Julia, Moebius, Ulrich, Rothe, Christine, Shane, Olwill A., Horton, Brendan, Spranger, Stefani, Moreira, Dayson, Adamus, Tomasz, Zhao, Xingli, Swiderski, Piotr, Pal, Sumanta, Kortylewski, Marcin, Kosmides, Alyssa, Necochea, Kevin, Mahoney, Kathleen M., Shukla, Sachet A., Patsoukis, Nikolaos, Chaudhri, Apoorvi, Pham, Hung, Hua, Ping, Bu, Xia, Zhu, Baogong, Hacohen, Nir, Wu, Catherine J., Fritsch, Edward, Boussiotis, Vassiliki A., Freeman, Gordon J., Moran, Amy E., Polesso, Fanny, Lukaesko, Lisa, Rådestad, Emelie, Egevad, Lars, Sundberg, Berit, Henningsohn, Lars, Levitsky, Victor, Rafelson, William, Reagan, John L., Fast, Loren, Sasikumar, Pottayil, Sudarshan, Naremaddepalli, Ramachandra, Raghuveer, Gowda, Nagesh, Samiulla, Dodheri, Chandrasekhar, Talapaneni, Adurthi, Sreenivas, Mani, Jiju, Nair, Rashmi, Dhudashia, Amit, Gowda, Nagaraj, Ramachandra, Murali, Sankin, Alexander, Gartrell, Benjamin, Cumberbatch, Kerwin, Huang, Hongying, Stern, Joshua, Schoenberg, Mark, Zang, Xingxing, Swanson, Ryan, Kornacker, Michael, Evans, Lawrence, Rickel, Erika, Wolfson, Martin, Valsesia-Wittmann, Sandrine, Shekarian, Tala, Simard, François, Nailo, Rodrigo, Dutour, Aurélie, Jallas, Anne-Catherine, Caux, Christophe, and Marabelle, Aurélien

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