The Impact of Hash Primitives and Communication Overhead for Hardware-Accelerated SPHINCS+

SPHINCS+ is a signature scheme included in the first NIST post-quantum standard, that bases its security on the underlying hash primitive. As most of the runtime of SPHINCS+ is caused by the evaluation of several hash- and pseudo-random functions, instantiated via the hash primitive, offloading this computation to dedicated hardware accelerators is a natural step. In this work, we evaluate different architectures for hardware acceleration of such a hash primitive with respect to its use-case and evaluate them in the context of SPHINCS+. We attach hardware accelerators for different hash primitives (SHAKE256 and Asconxof for both full and round-reduced versions) to CPU interfaces having different transfer speeds. We show, that for most use-cases, data transfer determines the overall performance if accelerators are equipped with FIFOs

Post-Quantum Signatures on RISC-V with Hardware Acceleration

CRYSTALS-Dilithium and Falcon are digital signature algorithms based on cryptographic lattices, that are considered secure even if large-scale quantum computers will be able to break conventional public-key cryptography. Both schemes have been selected for standardization in the NIST post-quantum competition. In this work, we present a RISC-V HW/SW odesign that aims to combine the advantages of software- and hardware implementations, i.e. flexibility and performance. It shows the use of lexible hardware accelerators, which have been previously used for Public-Key Encryption (PKE) and Key-Encapsulation Mechanism (KEM), for post-quantum signatures. It is optimized for Dilithium as a generic signature cheme but also accelerates applications that require fast verification of Falcon’s compact signatures. We provide a comparison with previous works showing that for Dilithium and Falcon, cycle counts are significantly reduced, such that our design is faster than previous software implementations or other HW/SW codesigns. In addition to that, we present a compact Globalfoundries 22 nm ASIC design that runs at 800MHz. By using hardware acceleration, energy consumption for Dilithium is reduced by up to 92.2%, and up to 67.5% for Falcon’s signature verification

FuLeeca: A Lee-based Signature Scheme

In this work we introduce a new code-based signature scheme, called \textsf{FuLeeca}, based on the NP-hard problem of finding codewords of given Lee-weight. The scheme follows the Hash-and-Sign approach applied to quasi-cyclic codes. Similar approaches in the Hamming metric have suffered statistical attacks, which revealed the small support of the secret basis. Using the Lee metric, we are able to thwart such attacks. We use existing hardness results on the underlying problem and study adapted statistical attacks. We propose parameters for \textsf{FuLeeca}~and compare them to an extensive list of proposed post-quantum secure signature schemes including the ones already standardized by NIST. This comparison reveals that \textsf{FuLeeca}~is competitive. For example, for NIST category I, i.e., 160 bit of classical security, we obtain an average signature size of 1100 bytes and public key sizes of 1318 bytes. Comparing the total communication cost, i.e., the sum of the signature and public key size, we see that \textsf{FuLeeca} is only outperformed by Falcon while the other standardized schemes Dilithium and SPHINCS+ show larger communication costs than \textsf{FuLeeca}

Profiling the mouse brain endothelial transcriptome in health and disease models reveals a core blood-brain barrier dysfunction module.

Blood vessels in the CNS form a specialized and critical structure, the blood-brain barrier (BBB). We present a resource to understand the molecular mechanisms that regulate BBB function in health and dysfunction during disease. Using endothelial cell enrichment and RNA sequencing, we analyzed the gene expression of endothelial cells in mice, comparing brain endothelial cells with peripheral endothelial cells. We also assessed the regulation of CNS endothelial gene expression in models of stroke, multiple sclerosis, traumatic brain injury and seizure, each having profound BBB disruption. We found that although each is caused by a distinct trigger, they exhibit strikingly similar endothelial gene expression changes during BBB disruption, comprising a core BBB dysfunction module that shifts the CNS endothelial cells into a peripheral endothelial cell-like state. The identification of a common pathway for BBB dysfunction suggests that targeting therapeutic agents to limit it may be effective across multiple neurological disorders

Clarifying the Transcriptional Profiles of Malignant Clones and Nonmalignant Cells of the Microenvironment through Multiscale and Multiomic Analysis of Individual Tumors

Understanding the transcriptional consequences of oncogenic mutations is an important goal that may reveal new therapeutic targets for diverse cancers. Although single-cell methods hold promise for this task, it remains non-trivial to isolate and sequence DNA and RNA from the same cell at scale. Here we present a statistically motivated strategy that utilizes multiscale and multiomic analysis of individual human tumor specimens to deconstruct intra-tumoral heterogeneity by clarifying clonal populations of malignant cells and their transcriptional profiles. By combining deep, multiscale sampling of IDH-mutant astrocytomas with integrative, multiomic analysis, we reconstruct and validate the phylogenies, spatial distributions, and transcriptional profiles of distinct malignant clones. We identify a core set of genes that is consistently expressed by the truncal clone, including AKR1C3, whose expression is associated with poor outcomes in several types of cancer. Some derived clones exhibit significant enrichment with gene sets representing glioblastoma subtypes and nonmalignant cell types, including ependymal cells. Importantly, by genotyping nuclei for truncal mutations, we show that existing strategies for inferring malignancy from gene expression profiles of single cells may be inaccurate. Furthermore, we find that transcriptional phenotypes of malignancy persist despite loss of the mutant IDH1 protein following chr2q deletion in a subset of malignant cells. In summary, our study provides a generalizable strategy for precisely deconstructing intra-tumoral heterogeneity and clarifying the molecular profiles of malignant clones in any kind of solid tumor.We extend this approach to a metaanalysis of the cell-type specific dysregulation in the glioma microenvironment. Using the same statistically motivated approach to take advantage of inherent patterns of cell-type specific coexpression, we characterize the differentially expressed cell-type specific transcriptome. We perform this process on thousands of samples and hundreds of datasets from both glioma and normal samples. Finally by taking the difference in the in silico derived differential expression metrics for each cell type in glioma and normal contexts, we identify ideal markers of each cell type specifically in glioma but not normal and validate and filter them using orthogonal datasets. In summary, our study provides a generalizable strategy for precise identification of cell-type specific dysregulated genes using abundant bulk transcriptome data for any disease state involving solid tissues

Profiling the mouse brain endothelial transcriptome in health and disease models reveals a core blood-brain barrier dysfunction module

Blood vessels in the CNS form a specialized and critical structure, the blood-brain barrier (BBB). We present a resource to understand the molecular mechanisms that regulate BBB function in health and dysfunction during disease. Using endothelial cell enrichment and RNA sequencing, we analyzed the gene expression of endothelial cells in mice, comparing brain endothelial cells with peripheral endothelial cells. We also assessed the regulation of CNS endothelial gene expression in models of stroke, multiple sclerosis, traumatic brain injury and seizure, each having profound BBB disruption. We found that although each is caused by a distinct trigger, they exhibit strikingly similar endothelial gene expression changes during BBB disruption, comprising a core BBB dysfunction module that shifts the CNS endothelial cells into a peripheral endothelial cell-like state. The identification of a common pathway for BBB dysfunction suggests that targeting therapeutic agents to limit it may be effective across multiple neurological disorders

The sponge microbiome project.

Marine sponges (phylum Porifera) are a diverse, phylogenetically deep-branching clade known for forming intimate partnerships with complex communities of microorganisms. To date, 16S rRNA gene sequencing studies have largely utilised different extraction and amplification methodologies to target the microbial communities of a limited number of sponge species, severely limiting comparative analyses of sponge microbial diversity and structure. Here, we provide an extensive and standardised dataset that will facilitate sponge microbiome comparisons across large spatial, temporal, and environmental scales. Samples from marine sponges (n = 3569 specimens), seawater (n = 370), marine sediments (n = 65) and other environments (n = 29) were collected from different locations across the globe. This dataset incorporates at least 268 different sponge species, including several yet unidentified taxa. The V4 region of the 16S rRNA gene was amplified and sequenced from extracted DNA using standardised procedures. Raw sequences (total of 1.1 billion sequences) were processed and clustered with (i) a standard protocol using QIIME closed-reference picking resulting in 39 543 operational taxonomic units (OTU) at 97% sequence identity, (ii) a de novo clustering using Mothur resulting in 518 246 OTUs, and (iii) a new high-resolution Deblur protocol resulting in 83 908 unique bacterial sequences. Abundance tables, representative sequences, taxonomic classifications, and metadata are provided. This dataset represents a comprehensive resource of sponge-associated microbial communities based on 16S rRNA gene sequences that can be used to address overarching hypotheses regarding host-associated prokaryotes, including host specificity, convergent evolution, environmental drivers of microbiome structure, and the sponge-associated rare biosphere

The sponge microbiome project

Marine sponges (phylum Porifera) are a diverse, phylogenetically deep-branching clade known for forming intimate partnerships with complex communities of microorganisms. To date, 16S rRNA gene sequencing studies have largely utilised different extraction and amplification methodologies to target the microbial communities of a limited number of sponge species, severely limiting comparative analyses of sponge microbial diversity and structure. Here, we provide an extensive and standardised dataset that will facilitate sponge microbiome comparisons across large spatial, temporal, and environmental scales. Samples from marine sponges (n = 3569 specimens), seawater (n = 370), marine sediments (n = 65) and other environments (n = 29) were collected from different locations across the globe. This dataset incorporates at least 268 different sponge species, including several yet unidentified taxa. The V4 region of the 16S rRNA gene was amplified and sequenced from extracted DNA using standardised procedures. Raw sequences (total of 1.1 billion sequences) were processed and clustered with (i) a standard protocol using QIIME closed-reference picking resulting in 39 543 operational taxonomic units (OTU) at 97% sequence identity, (ii) a de novo clustering using Mothur resulting in 518 246 OTUs, and (iii) a new high-resolution Deblur protocol resulting in 83 908 unique bacterial sequences. Abundance tables, representative sequences, taxonomic classifications, and metadata are provided. This dataset represents a comprehensive resource of sponge-associated microbial communities based on 16S rRNA gene sequences that can be used to address overarching hypotheses regarding host-associated prokaryotes, including host specificity, convergent evolution, environmental drivers of microbiome structure, and the sponge-associated rare biosphere