Faster Sparse Matrix Inversion and Rank Computation in Finite Fields

We improve the current best running time value to invert sparse matrices over finite fields, lowering it to an expected $O\big(n^{2.2131}\big)$ time for the current values of fast rectangular matrix multiplication. We achieve the same running time for the computation of the rank and nullspace of a sparse matrix over a finite field. This improvement relies on two key techniques. First, we adopt the decomposition of an arbitrary matrix into block Krylov and Hankel matrices from Eberly et al. (ISSAC 2007). Second, we show how to recover the explicit inverse of a block Hankel matrix using low displacement rank techniques for structured matrices and fast rectangular matrix multiplication algorithms. We generalize our inversion method to block structured matrices with other displacement operators and strengthen the best known upper bounds for explicit inversion of block Toeplitz-like and block Hankel-like matrices, as well as for explicit inversion of block Vandermonde-like matrices with structured blocks. As a further application, we improve the complexity of several algorithms in topological data analysis and in finite group theory

PCACE: A Statistical Approach to Ranking Neurons for CNN Interpretability

In this paper we introduce a new problem within the growing literature of interpretability for convolution neural networks (CNNs). While previous work has focused on the question of how to visually interpret CNNs, we ask what it is that we care to interpret, that is, which layers and neurons are worth our attention? Due to the vast size of modern deep learning network architectures, automated, quantitative methods are needed to rank the relative importance of neurons so as to provide an answer to this question. We present a new statistical method for ranking the hidden neurons in any convolutional layer of a network. We define importance as the maximal correlation between the activation maps and the class score. We provide different ways in which this method can be used for visualization purposes with MNIST and ImageNet, and show a real-world application of our method to air pollution prediction with street-level images

eIF4A dependency: the hidden key to unlock KRAS mutant non-small cell lung cancer’s vulnerability

MYC; Non-small cell lung cancerMYC; Càncer de pulmó de cèl·lules no petitesMYC; Cáncer de pulmón de células no pequeñasThe authors received funding support by the “Proyectos de I+D+i en Líneas Estratégicas” (PLEC2021-007959) grant from the Spanish Ministry of Economy and Competitiveness; La Marató TV3 grant [2019429]; and the 2nd BBVA Foundation Comprehensive Program of Cancer Immunotherapy & Immunology (CAIMI-II) grant. I.G.L. was supported by a grant from the University Teacher Training Program (FPU), Ministry of Universities (FPU20/04812). Authors from VHIO acknowledge the State Agency for Research (Agencia Estatal de Investigación) the financial support as a Center of Excellence Severo Ochoa (CEX2020-001024-S/AEI/10.13039/501100011033)

Obvious Independence of Clones

The Independence of Clones (IoC) criterion for social choice functions (voting rules) measures a function's robustness to strategic nomination. However, prior literature has established empirically that individuals cannot always recognize whether or not a mechanism is strategy-proof and may still submit costly, distortionary misreports even in strategy-proof settings. The intersection of these issues motivates the search for mechanisms which are Obviously Independent of Clones (OIoC): where strategic nomination or strategic exiting of clones obviously have no effect on the outcome of the election. We examine three IoC ranked-choice voting mechanisms and the pre-existing proofs that they are independent of clones: Single Transferable Vote (STV), Ranked Pairs, and the Schulze method. We construct a formal definition of a voting system being Obviously Independent of Clones based on a reduction to a clocked election by considering a bounded agent. Finally, we show that STV and Ranked Pairs are OIoC, whereas we prove an impossibility result for the Schulze method showing that this voting system is not OIoC

SoK: Oblivious Pseudorandom Functions

In recent years, oblivious pseudorandom functions (OPRFs) have become a ubiquitous primitive used in cryptographic protocols and privacy-preserving technologies. The growing interest in OPRFs, both theoretical and applied, has produced a vast number of different constructions and functionality variations. In this paper, we provide a systematic overview of how to build and use OPRFs. We first categorize existing OPRFs into essentially four families based on their underlying PRF (Naor-Reingold, Dodis-Yampolskiy, Hashed Diffie-Hellman, and generic constructions). This categorization allows us to give a unified presentation of all oblivious evaluation methods in the literature, and to understand which properties OPRFs can (or cannot) have. We further demonstrate the theoretical and practical power of OPRFs by visualizing them in the landscape of cryptographic primitives, and by providing a comprehensive overview of how OPRFs are leveraged for improving the privacy of internet users. Our work systematizes 15 years of research on OPRFs and provides inspiration for new OPRF constructions and applications thereof

Quantum and Classical Algorithms for Bounded Distance Decoding

In this paper, we provide a comprehensive overview of a recent debate over the quantum versus classical solvability of bounded distance decoding (BDD). Specifically, we review the work of Eldar and Hallgren [EH22], [Hal21] demonstrating a quantum algorithm solving $\lambda_1 2^{-\Omega(\sqrt{k \log q})}$-BDD in polynomial time for lattices of periodicity $q$, finite group rank $k$, and shortest lattice vector length $\lambda_1$. Subsequently, we prove the results of [DvW21a], [DvW21b] with far greater detail and elaboration than in the original work. Namely, we show that there exists a deterministic, classical algorithm achieving the same result

MYC targeting by OMO-103 in solid tumors: a phase 1 trial

MYC; Solid tumorsMYC; Tumores sólidosMYC; Tumors sòlidsAmong the ‘most wanted’ targets in cancer therapy is the oncogene MYC, which coordinates key transcriptional programs in tumor development and maintenance. It has, however, long been considered undruggable. OMO-103 is a MYC inhibitor consisting of a 91-amino acid miniprotein. Here we present results from a phase 1 study of OMO-103 in advanced solid tumors, established to examine safety and tolerability as primary outcomes and pharmacokinetics, recommended phase 2 dose and preliminary signs of activity as secondary ones. A classical 3 + 3 design was used for dose escalation of weekly intravenous, single-agent OMO-103 administration in 21-day cycles, encompassing six dose levels (DLs). A total of 22 patients were enrolled, with treatment maintained until disease progression. The most common adverse events were grade 1 infusion-related reactions, occurring in ten patients. One dose-limiting toxicity occurred at DL5. Pharmacokinetics showed nonlinearity, with tissue saturation signs at DL5 and a terminal half-life in serum of 40 h. Of the 19 patients evaluable for response, 12 reached the predefined 9-week time point for assessment of drug antitumor activity, eight of those showing stable disease by computed tomography. One patient defined as stable disease by response evaluation criteria in solid tumors showed a 49% reduction in total tumor volume at best response. Transcriptomic analysis supported target engagement in tumor biopsies. In addition, we identified soluble factors that are potential pharmacodynamic and predictive response markers. Based on all these data, the recommended phase 2 dose was determined as DL5 (6.48 mg kg−1). ClinicalTrials.gov identifier: NCT04808362.The authors from Vall d’Hebron Institute of Oncology (VHIO) thank the Cellex Foundation for providing research facilities and equipment, and the CERCA Program from the Generalitat de Catalunya for their support on this research. They also acknowledge the State Agency for Research (Agencia Estatal de Investigación) for financial support as Center of Excellence Severo Ochoa (no. CEX2020-001024-S/AEI/10.13039/501100011033). We thank the teams at Abzu and Biognosys for their valuable service and feedback, and M.-A. Morcillo for his help in the interpretation of PK data. This research has received funding from the Generalitat de Catalunya (AGAUR grant no. 2021/SGR 01509); from the European Union Horizon 2020 research and innovation program under grant agreement nos. 872212 and 101144681; from the Ministerio de Ciencia e Innovación, grant no. RTC2019-007067; from the Ministerio de Ciencia, Innovación y Universidades, grant nos. CPP2022-009808 and PLEC2021-007959 by MCIN/AEI/10.13039/501100011033 and European Union NextGenerationEU/PRTR

Reducing MYC's transcriptional footprint unveils a good prognostic gene signature in melanoma

MYC; Omomyc; MelanomaMYC; Omomyc; MelanomaMYC; Omomyc; MelanomaMYC's key role in oncogenesis and tumor progression has long been established for most human cancers. In melanoma, its deregulated activity by amplification of 8q24 chromosome or by upstream signaling coming from activating mutations in the RAS/RAF/MAPK pathway—the most predominantly mutated pathway in this disease—turns MYC into not only a driver but also a facilitator of melanoma progression, with documented effects leading to an aggressive clinical course and resistance to targeted therapy. Here, by making use of Omomyc, the most characterized MYC inhibitor to date that has just successfully completed a phase I clinical trial, we show for the first time that MYC inhibition in melanoma induces remarkable transcriptional modulation, resulting in severely compromised tumor growth and a clear abrogation of metastatic capacity independently of the driver mutation. By reducing MYC's transcriptional footprint in melanoma, Omomyc elicits gene expression profiles remarkably similar to those of patients with good prognosis, underlining the therapeutic potential that such an approach could eventually have in the clinic in this dismal disease.M.F.Z.-F. was supported by the Juan de la Cierva Programme of the Spanish Ministry of Economy and Competitiveness (IJCI-2014-22403) and Fundació La Marató de TV3 (grant 474/C/2019); F.G. was supported by Spanish Ministry of Science and Innovation Contratos Predoctorales de Formación en Investigación en Salud (PFIS; FI20/00274); I.G.-L. was supported by a grant from the University Teacher Training Program (FPU), Ministry of Universities (FPU20/04812); and S.M.-M. was supported by the Generalitat de Catalunya “Contractació de Personal Investigador Novell (FI-DGR)” 2016 fellowship (2016FI_B 00592). This project was funded by grants from the Spanish Ministry of Science and Innovation (Fondo de Inversión en Salud [FIS] PI19/01277, which also supported I.G.-L. and S.M.-M, and Retos-Colaboración 2019 RTC2019-007067-1), La Marató TV3, the Generalitat de Catalunya AGAUR 2017 grant SGR-3193, and the European Research Council (ERC-PoC II/3079/SYST-iMYC [813132]). We thank the rest of the Soucek laboratory for critical reading of the manuscript, and the personnel at Vall d'Hebron Research Institute (VHIR) High Technology Unit. We acknowledge Vall d'Hebron Institute of Oncology and the Cellex Foundation for providing research facilities and equipment