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2. On the Stability of Expressive Positional Encodings for Graphs

Author

Huang, Yinan, Lu, William, Robinson, Joshua, Yang, Yu, Zhang, Muhan, Jegelka, Stefanie, and Li, Pan

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Designing effective positional encodings for graphs is key to building powerful graph transformers and enhancing message-passing graph neural networks. Although widespread, using Laplacian eigenvectors as positional encodings faces two fundamental challenges: (1) \emph{Non-uniqueness}: there are many different eigendecompositions of the same Laplacian, and (2) \emph{Instability}: small perturbations to the Laplacian could result in completely different eigenspaces, leading to unpredictable changes in positional encoding. Despite many attempts to address non-uniqueness, most methods overlook stability, leading to poor generalization on unseen graph structures. We identify the cause of instability to be a ``hard partition'' of eigenspaces. Hence, we introduce Stable and Expressive Positional Encodings (SPE), an architecture for processing eigenvectors that uses eigenvalues to ``softly partition'' eigenspaces. SPE is the first architecture that is (1) provably stable, and (2) universally expressive for basis invariant functions whilst respecting all symmetries of eigenvectors. Besides guaranteed stability, we prove that SPE is at least as expressive as existing methods, and highly capable of counting graph structures. Finally, we evaluate the effectiveness of our method on molecular property prediction, and out-of-distribution generalization tasks, finding improved generalization compared to existing positional encoding methods. Our code is available at \url{https://github.com/Graph-COM/SPE}., Comment: ICLR 2024

Published
2023

3. Permutation Capacity Region of Adder Multiple-Access Channels

Author

Lu, William and Makur, Anuran

Subjects
Computer Science - Information Theory, Mathematics - Statistics Theory
Abstract

Point-to-point permutation channels are useful models of communication networks and biological storage mechanisms and have received theoretical attention in recent years. Propelled by relevant advances in this area, we analyze the permutation adder multiple-access channel (PAMAC) in this work. In the PAMAC network model, $d$ senders communicate with a single receiver by transmitting $p$-ary codewords through an adder multiple-access channel whose output is subsequently shuffled by a random permutation block. We define a suitable notion of permutation capacity region $\mathcal{C}_\mathsf{perm}$ for this model, and establish that $\mathcal{C}_\mathsf{perm}$ is the simplex consisting of all rate $d$-tuples that sum to $d(p - 1) / 2$ or less. We achieve this sum-rate by encoding messages as i.i.d. samples from categorical distributions with carefully chosen parameters, and we derive an inner bound on $\mathcal{C}_\mathsf{perm}$ by extending the concept of time sharing to the permutation channel setting. Our proof notably illuminates various connections between mixed-radix numerical systems and coding schemes for multiple-access channels. Furthermore, we derive an alternative inner bound on $\mathcal{C}_\mathsf{perm}$ for the binary PAMAC by analyzing the root stability of the probability generating function of the adder's output distribution. Using eigenvalue perturbation results, we obtain error bounds on the spectrum of the probability generating function's companion matrix, providing quantitative estimates of decoding performance. Finally, we obtain a converse bound on $\mathcal{C}_\mathsf{perm}$ matching our achievability result., Comment: 28 pages, 6 figures

Published
2023
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7. Deep object detection for waterbird monitoring using aerial imagery

Author

Kabra, Krish, Xiong, Alexander, Li, Wenbin, Luo, Minxuan, Lu, William, Garcia, Raul, Vijay, Dhananjay, Yu, Jiahui, Tang, Maojie, Yu, Tianjiao, Arnold, Hank, Vallery, Anna, Gibbons, Richard, and Barman, Arko

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Monitoring of colonial waterbird nesting islands is essential to tracking waterbird population trends, which are used for evaluating ecosystem health and informing conservation management decisions. Recently, unmanned aerial vehicles, or drones, have emerged as a viable technology to precisely monitor waterbird colonies. However, manually counting waterbirds from hundreds, or potentially thousands, of aerial images is both difficult and time-consuming. In this work, we present a deep learning pipeline that can be used to precisely detect, count, and monitor waterbirds using aerial imagery collected by a commercial drone. By utilizing convolutional neural network-based object detectors, we show that we can detect 16 classes of waterbird species that are commonly found in colonial nesting islands along the Texas coast. Our experiments using Faster R-CNN and RetinaNet object detectors give mean interpolated average precision scores of 67.9% and 63.1% respectively., Comment: Longer version of accepted short paper at 21st IEEE International Conference on Machine Learning and Applications (ICMLA'22). 7 pages, 5 figures

Published
2022

8. Neoantigen-targeted CD8+ T cell responses with PD-1 blockade therapy

Author

Puig-Saus, Cristina, Sennino, Barbara, Peng, Songming, Wang, Clifford L, Pan, Zheng, Yuen, Benjamin, Purandare, Bhamini, An, Duo, Quach, Boi B, Nguyen, Diana, Xia, Huiming, Jilani, Sameeha, Shao, Kevin, McHugh, Claire, Greer, John, Peabody, Phillip, Nayak, Saparya, Hoover, Jonathan, Said, Sara, Jacoby, Kyle, Dalmas, Olivier, Foy, Susan P, Conroy, Andrew, Yi, Michael C, Shieh, Christine, Lu, William, Heeringa, Katharine, Ma, Yan, Chizari, Shahab, Pilling, Melissa J, Ting, Marc, Tunuguntla, Ramya, Sandoval, Salemiz, Moot, Robert, Hunter, Theresa, Zhao, Sidi, Saco, Justin D, Perez-Garcilazo, Ivan, Medina, Egmidio, Vega-Crespo, Agustin, Baselga-Carretero, Ignacio, Abril-Rodriguez, Gabriel, Cherry, Grace, Wong, Deborah J, Hundal, Jasreet, Chmielowski, Bartosz, Speiser, Daniel E, Bethune, Michael T, Bao, Xiaoyan R, Gros, Alena, Griffith, Obi L, Griffith, Malachi, Heath, James R, Franzusoff, Alex, Mandl, Stefanie J, and Ribas, Antoni

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Immunology, Cancer, Minority Health, Immunotherapy, Clinical Research, Genetics, 2.1 Biological and endogenous factors, 5.2 Cellular and gene therapies, 5.1 Pharmaceuticals, Good Health and Well Being, Humans, Antigens, Neoplasm, CD8-Positive T-Lymphocytes, Melanoma, Receptors, Antigen, T-Cell, Immune Checkpoint Inhibitors, HLA Antigens, Neoplasm Metastasis, Precision Medicine, Gene Editing, CRISPR-Cas Systems, Mutation, General Science & Technology
Abstract

Neoantigens are peptides derived from non-synonymous mutations presented by human leukocyte antigens (HLAs), which are recognized by antitumour T cells1-14. The large HLA allele diversity and limiting clinical samples have restricted the study of the landscape of neoantigen-targeted T cell responses in patients over their treatment course. Here we applied recently developed technologies15-17 to capture neoantigen-specific T cells from blood and tumours from patients with metastatic melanoma with or without response to anti-programmed death receptor 1 (PD-1) immunotherapy. We generated personalized libraries of neoantigen-HLA capture reagents to single-cell isolate the T cells and clone their T cell receptors (neoTCRs). Multiple T cells with different neoTCR sequences (T cell clonotypes) recognized a limited number of mutations in samples from seven patients with long-lasting clinical responses. These neoTCR clonotypes were recurrently detected over time in the blood and tumour. Samples from four patients with no response to anti-PD-1 also demonstrated neoantigen-specific T cell responses in the blood and tumour to a restricted number of mutations with lower TCR polyclonality and were not recurrently detected in sequential samples. Reconstitution of the neoTCRs in donor T cells using non-viral CRISPR-Cas9 gene editing demonstrated specific recognition and cytotoxicity to patient-matched melanoma cell lines. Thus, effective anti-PD-1 immunotherapy is associated with the presence of polyclonal CD8+ T cells in the tumour and blood specific for a limited number of immunodominant mutations, which are recurrently recognized over time.

Published
2023

9. Non-viral precision T cell receptor replacement for personalized cell therapy

Author

Foy, Susan P, Jacoby, Kyle, Bota, Daniela A, Hunter, Theresa, Pan, Zheng, Stawiski, Eric, Ma, Yan, Lu, William, Peng, Songming, Wang, Clifford L, Yuen, Benjamin, Dalmas, Olivier, Heeringa, Katharine, Sennino, Barbara, Conroy, Andy, Bethune, Michael T, Mende, Ines, White, William, Kukreja, Monica, Gunturu, Swetha, Humphrey, Emily, Hussaini, Adeel, An, Duo, Litterman, Adam J, Quach, Boi Bryant, Ng, Alphonsus HC, Lu, Yue, Smith, Chad, Campbell, Katie M, Anaya, Daniel, Skrdlant, Lindsey, Huang, Eva Yi-Hsuan, Mendoza, Ventura, Mathur, Jyoti, Dengler, Luke, Purandare, Bhamini, Moot, Robert, Yi, Michael C, Funke, Roel, Sibley, Alison, Stallings-Schmitt, Todd, Oh, David Y, Chmielowski, Bartosz, Abedi, Mehrdad, Yuan, Yuan, Sosman, Jeffrey A, Lee, Sylvia M, Schoenfeld, Adam J, Baltimore, David, Heath, James R, Franzusoff, Alex, Ribas, Antoni, Rao, Arati V, and Mandl, Stefanie J

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Immunology, Gene Therapy, Genetics, Cancer Genomics, Clinical Research, Human Genome, Clinical Trials and Supportive Activities, Immunotherapy, Cancer, Health Disparities, Precision Medicine, Biotechnology, Minority Health, Gene Therapy Clinical Trials, Rare Diseases, 5.2 Cellular and gene therapies, 2.1 Biological and endogenous factors, Inflammatory and immune system, Good Health and Well Being, Humans, Antigens, Neoplasm, Biopsy, Cell- and Tissue-Based Therapy, Cytokine Release Syndrome, Disease Progression, Encephalitis, Gene Editing, Gene Knock-In Techniques, Gene Knockout Techniques, Genes, T-Cell Receptor alpha, Genes, T-Cell Receptor beta, Mutation, Neoplasms, Patient Safety, Receptors, Antigen, T-Cell, T-Lymphocytes, Transgenes, HLA Antigens, CRISPR-Cas Systems, General Science & Technology
Abstract

T cell receptors (TCRs) enable T cells to specifically recognize mutations in cancer cells1-3. Here we developed a clinical-grade approach based on CRISPR-Cas9 non-viral precision genome-editing to simultaneously knockout the two endogenous TCR genes TRAC (which encodes TCRα) and TRBC (which encodes TCRβ). We also inserted into the TRAC locus two chains of a neoantigen-specific TCR (neoTCR) isolated from circulating T cells of patients. The neoTCRs were isolated using a personalized library of soluble predicted neoantigen-HLA capture reagents. Sixteen patients with different refractory solid cancers received up to three distinct neoTCR transgenic cell products. Each product expressed a patient-specific neoTCR and was administered in a cell-dose-escalation, first-in-human phase I clinical trial ( NCT03970382 ). One patient had grade 1 cytokine release syndrome and one patient had grade 3 encephalitis. All participants had the expected side effects from the lymphodepleting chemotherapy. Five patients had stable disease and the other eleven had disease progression as the best response on the therapy. neoTCR transgenic T cells were detected in tumour biopsy samples after infusion at frequencies higher than the native TCRs before infusion. This study demonstrates the feasibility of isolating and cloning multiple TCRs that recognize mutational neoantigens. Moreover, simultaneous knockout of the endogenous TCR and knock-in of neoTCRs using single-step, non-viral precision genome-editing are achieved. The manufacture of neoTCR engineered T cells at clinical grade, the safety of infusing up to three gene-edited neoTCR T cell products and the ability of the transgenic T cells to traffic to the tumours of patients are also demonstrated.

Published
2023

14. Morphological Operation Residual Blocks: Enhancing 3D Morphological Feature Representation in Convolutional Neural Networks for Semantic Segmentation of Medical Images

Author

Li, Chentian, Ma, Chi, and Lu, William W.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

The shapes and morphology of the organs and tissues are important prior knowledge in medical imaging recognition and segmentation. The morphological operation is a well-known method for morphological feature extraction. As the morphological operation is performed well in hand-crafted image segmentation techniques, it is also promising to design an approach to approximate morphological operation in the convolutional networks. However, using the traditional convolutional neural network as a black-box is usually hard to specify the morphological operation action. Here, we introduced a 3D morphological operation residual block to extract morphological features in end-to-end deep learning models for semantic segmentation. This study proposed a novel network block architecture that embedded the morphological operation as an infinitely strong prior in the convolutional neural network. Several 3D deep learning models with the proposed morphological operation block were built and compared in different medical imaging segmentation tasks. Experimental results showed the proposed network achieved a relatively higher performance in the segmentation tasks comparing with the conventional approach. In conclusion, the novel network block could be easily embedded in traditional networks and efficiently reinforce the deep learning models for medical imaging segmentation.

Published
2021

21. Sleep-wake body temperature regulates tau secretion in mice and correlates with CSF and plasma tau in humans

Author

Canet, Geoffrey, primary, Monteiro, Felipe Da Gama, additional, Rocaboy, Emma, additional, Diego-Diaz, Sofia, additional, Khelaifia, Boutheyna, additional, Kim, Jessica, additional, Valencia, Daphne, additional, Yin, Audrey, additional, Wu, Hau-Tieng, additional, Howell, Jordan, additional, Blank, Emily, additional, Laliberté, Francis, additional, Fortin, Nadia, additional, Boscher, Emmanuelle, additional, Fereydouni-Forouzandeh, Parissa, additional, Champagne, Stéphanie, additional, Guisle, Isabelle, additional, Hébert, Sébastien, additional, Pernet, Vincent, additional, Liu, Haiyan, additional, Lu, William, additional, Debure, Ludovic, additional, Rapoport, David, additional, Ayappa, Indu, additional, Varga, Andrew, additional, Parekh, Ankit, additional, Osorio, Ricardo, additional, Lacroix, Steve, additional, Lucey, Brendan, additional, Blessing, Esther, additional, and Planel, Emmanuel, additional

Published
2024
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22. Tibial Cortex Transverse Transport Facilitates Severe Diabetic Foot Wound Healing via HIF-1α-Induced Angiogenesis

Author

Liu, Jie, primary, Huang, Xiajie, additional, Su, Hongjie, additional, Yu, Jie, additional, Nie, Xinyu, additional, Liu, Kaibing, additional, Qin, Wencong, additional, Zhao, Yongxin, additional, Su, Yongfeng, additional, Kuang, Xiaocong, additional, Chen, Di, additional, Lu, William, additional, Chen, Yan, additional, and Hua, Qikai, additional

Published
2024
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27. Decreased expression of miR-195 mediated by hypermethylation promotes osteosarcoma

Author

Sun Tianhao, Liu Dongning, Wu Jun, Lu William W., Zhao Xiaoli, Wong Tak Man, and Liu Zhi-Li

Subjects
osteosarcoma, fatty acid synthase, mir-195, dna methylation, Medicine
Abstract

Osteosarcoma (OS) is the most common type of primary malignant bone tumor. The early lung metastasis of osteosarcoma is one of the main factors of poor prognosis. Therefore, searching for new targets and new mechanisms of osteosarcoma metastasis is essential for the prevention and treatment of osteosarcoma. Our previous studies suggested that fatty acid synthase (FASN) was an oncogene and promoted osteosarcoma. In addition, it is reported that the expression of miR-195 was negatively correlated with osteosarcoma. Aberrant DNA methylation can reversely regulate the expression of miRNAs. However, whether miR-195 could target FASN in osteosarcoma and whether ectopic DNA methylation is the upstream regulatory mechanism of miR-195 in metastasis of osteosarcoma are not fully studied. The expressions were detected by qPCR and western blot, and methylation level was determined by methylation-specific PCR. Luciferase reporter assay, MTT, wound healing, and Transwell assay were used. We found that the expression of miR-195 was low in osteosarcoma. The methylation of miR-195 was high. miR-195 targeted and decreased the expression of FASN. In osteosarcoma, miR-195 inhibited cell proliferation, cell migration, and invasion. The methylation of miR-195 was related to decreased miR-195, it might promote osteosarcoma.

Published
2022
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43. One Novel Phantom-Less Quantitative Computed Tomography System for Auto-Diagnosis of Osteoporosis Utilizes Low-Dose Chest Computed Tomography Obtained for COVID-19 Screening

Author

Tang Xiongfeng, Zhang Cheng, He Meng, Ma Chi, Guo Deming, Qi Huan, Chen Bo, Yang Kedi, Shen Xianyue, Wong Tak-Man, Lu William Weijia, and Qin Yanguo

Subjects
osteoporosis, phantom-less QCT, dual-energy X-ray, low-dose CT, COVID-19, Biotechnology, TP248.13-248.65
Abstract

Background: The diagnosis of osteoporosis is still one of the most critical topics for orthopedic surgeons worldwide. One research direction is to use existing clinical imaging data for accurate measurements of bone mineral density (BMD) without additional radiation.Methods: A novel phantom-less quantitative computed tomography (PL-QCT) system was developed to measure BMD and diagnose osteoporosis, as our previous study reported. Compared with traditional phantom-less QCT, this tool can conduct an automatic selection of body tissues and complete the BMD calibration with high efficacy and precision. The function has great advantages in big data screening and thus expands the scope of use of this novel PL-QCT. In this study, we utilized lung cancer or COVID-19 screening low-dose computed tomography (LDCT) of 649 patients for BMD calibration by the novel PL-QCT, and we made the BMD changes with age based on this PL-QCT.Results: The results show that the novel PL-QCT can predict osteoporosis with relatively high accuracy and precision using LDCT, and the AUC values range from 0.68 to 0.88 with DXA results as diagnosis reference. The relationship between PL-QCT BMD with age is close to the real trend population (from ∼160 mg/cc in less than 30 years old to ∼70 mg/cc in greater than 80 years old for both female and male groups). Additionally, the calculation results of Pearson’s r-values for correlation between CT values with BMD in different CT devices were 0.85–0.99.Conclusion: To our knowledge, it is the first time for automatic PL-QCT to evaluate the performance against dual-energy X-ray absorptiometry (DXA) in LDCT images. The results indicate that it may be a promising tool for individuals screened for low-dose chest computed tomography.

Published
2022
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