The Ketogenic Diet Suppresses the Cathepsin E Expression Induced by Kainic Acid in the Rat Brain

*These authors equally contributed to this work. ∙The authors have no financial conflicts of interest. Purpose: The ketogenic diet has long been used to treat epilepsy, but its mechanism is not yet clearly understood. To explore the potential mechanism, we analyzed the changes in gene expression induced by the ketogenic diet in the rat kainic acid (KA) epilepsy model. Materials and Methods: KA-administered rats were fed the ketogenic diet or a normal diet for 4 weeks, and microarray analysis was performed with their brain tissues. The effects of the ketogenic diet on cathepsin E messenger ribonucleic acid (mRNA) expression were analyzed in KA-administered and normal saline-administered groups with semi-quantitative and real-time reverse transcription polymerase chain reaction (RT-PCR). Brain tissues were dissected into 8 regions to compare differential effects of the ketogenic diet on cathepsin E mRNA expression. Immunohistochemistry with an anti-cathepsin E antibody was performed on slide

CG dinucleotide clustering is a species-specific property of the genome

Cytosines at cytosine-guanine (CG) dinucleotides are the near-exclusive target of DNA methyltransferases in mammalian genomes. Spontaneous deamination of methylcytosine to thymine makes methylated cytosines unusually susceptible to mutation and consequent depletion. The loci where CG dinucleotides remain relatively enriched, presumably due to their unmethylated status during the germ cell cycle, have been referred to as CpG islands. Currently, CpG islands are solely defined by base compositional criteria, allowing annotation of any sequenced genome. Using a novel bioinformatic approach, we show that CG clusters can be identified as an inherent property of genomic sequence without imposing a base compositional a priori assumption. We also show that the CG clusters co-localize in the human genome with hypomethylated loci and annotated transcription start sites to a greater extent than annotations produced by prior CpG island definitions. Moreover, this new approach allows CG clusters to be identified in a species-specific manner, revealing a degree of orthologous conservation that is not revealed by current base compositional approaches. Finally, our approach is able to identify methylating genomes (such as Takifugu rubripes) that lack CG clustering entirely, in which it is inappropriate to annotate CpG islands or CG clusters

An Integrative Genomic and Epigenomic Approach for the Study of Transcriptional Regulation

The molecular heterogeneity of acute leukemias and other tumors constitutes a major obstacle towards understanding disease pathogenesis and developing new targeted-therapies. Aberrant gene regulation is a hallmark of cancer and plays a central role in determining tumor phenotype. We predicted that integration of different genome-wide epigenetic regulatory marks along with gene expression levels would provide greater power in capturing biological differences between leukemia subtypes. Gene expression, cytosine methylation and histone H3 lysine 9 (H3K9) acetylation were measured using high-density oligonucleotide microarrays in primary human acute myeloid leukemia (AML) and acute lymphocytic leukemia (ALL) specimens. We found that DNA methylation and H3K9 acetylation distinguished these leukemias of distinct cell lineage, as expected, but that an integrative analysis combining the information from each platform revealed hundreds of additional differentially expressed genes that were missed by gene expression arrays alone. This integrated analysis also enhanced the detection and statistical significance of biological pathways dysregulated in AML and ALL. Integrative epigenomic studies are thus feasible using clinical samples and provide superior detection of aberrant transcriptional programming than single-platform microarray studies

Collision Resistant Hashing from Sub-exponential Learning Parity with Noise

The Learning Parity with Noise (LPN) problem has recently found many cryptographic applications such as authentication protocols, pseudorandom generators/functions and even asymmetric tasks including public-key encryption (PKE) schemes and oblivious transfer (OT) protocols. It however remains a long-standing open problem whether LPN implies collision resistant hash (CRH) functions. Based on the recent work of Applebaum et al. (ITCS 2017), we introduce a general framework for constructing CRH from LPN for various parameter choices. We show that, just to mention a few notable ones, under any of the following hardness assumptions (for the two most common variants of LPN) 1) constant-noise LPN is $2^{n^{0.5+\epsilon}}$-hard for any constant $\epsilon>0$; 2) constant-noise LPN is $2^{\Omega(n/\log n)}$-hard given $q=poly(n)$ samples; 3) low-noise LPN (of noise rate $1/\sqrt{n}$) is $2^{\Omega(\sqrt{n}/\log n)}$-hard given $q=poly(n)$ samples. there exists CRH functions with constant (or even poly-logarithmic) shrinkage, which can be implemented using polynomial-size depth-3 circuits with NOT, (unbounded fan-in) AND and XOR gates. Our technical route LPN$\rightarrow$bSVP$\rightarrow$CRH is reminiscent of the known reductions for the large-modulus analogue, i.e., LWE$\rightarrow$SIS$\rightarrow$CRH, where the binary Shortest Vector Problem (bSVP) was recently introduced by Applebaum et al. (ITCS 2017) that enables CRH in a similar manner to Ajtai\u27s CRH functions based on the Short Integer Solution (SIS) problem. Furthermore, under additional (arguably minimal) idealized assumptions such as small-domain random functions or random permutations (that trivially imply collision resistance), we still salvage a simple and elegant collision-resistance-preserving domain extender that is (asymptotically) more parallel and efficient than previously known. In particular, assume $2^{n^{0.5+\epsilon}}$-hard constant-noise LPN or $2^{n^{0.25+\epsilon}}$-hard low-noise LPN, we obtain a polynomially shrinking collision resistant hash function that evaluates in parallel only a single layer of small-domain random functions (or random permutations) and produces their XOR sum as output

Renal vein tumor thrombus from metastatic anal gland adenocarcinoma

A 62-year-old female with a history of anal gland adenocarcinoma presents with metastatic disease to the kidney with renal vein tumor thrombus extending into the inferior vena cava (IVC). Metastatic disease to the kidney with renal vein tumor thrombus is extremely rare with only several cases described in the literature. We present the first reported case of metastatic anal gland adenocarcinoma to the kidney with renal vein tumor thrombus. Keywords: Tumor thrombus, Renal vein, Anal gland adenocarcinoma, Metastasi