Placement-Driven Technology Mapping for LUT-Based FPGAs

In this paper, we study the problem of placement-driven technology mapping for table-lookup based FPGA architectures to optimize circuit performance. Early work on technology mapping for FPGAs such as Chortle-d[14] and Flowmap[3] aim to optimize the depth of the mapped solution without consideration of interconnect delay. Later works such as Flowmap-d[7], Bias-Clus[4] and EdgeMap consider interconnect delays during mapping, but do not take into consideration the effects of their mapping solution on the final placement. Our work focuses on the interaction between the mapping and placement stages. First, the interconnect delay information is estimated from the placement, and used during the labeling process. A placement-based mapping solution which considers both global cell congestion and local cell congestion is then developed. Finally, a legalization step and detailed placement is performed to realize the design. We have implemented our algorithm in a LUT based FPGA technology mapping package named PDM (Placement-Driven Mapping) and tested the implementation on a set of MCNC benchmarks. We use the tool VPR[1][2] for placement and routing of the mapped netlist. Experimental results show the longest path delay on a set of large MCNC benchmarks decreased by 12.3 % on the average

The Relationship between Inflammatory Biomarkers and Telomere Length in an Occupational Prospective Cohort Study

Background: Chronic inflammation from recurring trauma is an underlying pathophysiological basis of numerous diseases. Furthermore, it may result in cell death, scarring, fibrosis, and loss of tissue function. In states of inflammation, subsequent increases in oxidative stress and cellular division may lead to the accelerated erosion of telomeres, crucial genomic structures which protect chromosomes from decay. However, the association between plasma inflammatory marker concentrations and telomere length has been inconsistent in previous studies. Objective: The purpose of this study was to determine the longitudinal association between telomere length and plasma inflammatory biomarker concentrations including: CRP, SAA, sICAM-1, sVCAM-1, VEGF, TNF-α, IL-1β, IL-2, IL-6, IL-8, and IL-10. Methods: The longitudinal study population consisted of 87 subjects. The follow-up period was approximately 2 years. Plasma inflammatory biomarker concentrations were assessed using highly sensitive electrochemiluminescent assays. Leukocyte relative telomere length was assessed using Real-Time qPCR. Linear mixed effects regression models were used to analyze the association between repeated-measurements of relative telomere length as the outcome and each inflammatory biomarker concentration as continuous exposures separately. The analyses controlled for major potential confounders and white blood cell differentials. Results: At any follow-up time, each incremental ng/mL increase in plasma CRP concentration was associated with a decrease in telomere length of −2.6×10−2 (95%CI: −4.3×10−2, −8.2×10−3, p = 0.004) units. Similarly, the estimate for the negative linear association between SAA and telomere length was −2.6×10−2 (95%CI:−4.5×10−2, −6.1×10−3, p = 0.011). No statistically significant associations were observed between telomere length and plasma concentrations of pro-inflammatory interleukins, TNF-α, and VEGF. Conclusions: Findings from this study suggest that increased systemic inflammation, consistent with vascular injury, is associated with decreased leukocyte telomere length

Time series classification with ensembles of elastic distance measures

Several alternative distance measures for comparing time series have recently been proposed and evaluated on time series classification (TSC) problems. These include variants of dynamic time warping (DTW), such as weighted and derivative DTW, and edit distance-based measures, including longest common subsequence, edit distance with real penalty, time warp with edit, and move–split–merge. These measures have the common characteristic that they operate in the time domain and compensate for potential localised misalignment through some elastic adjustment. Our aim is to experimentally test two hypotheses related to these distance measures. Firstly, we test whether there is any significant difference in accuracy for TSC problems between nearest neighbour classifiers using these distance measures. Secondly, we test whether combining these elastic distance measures through simple ensemble schemes gives significantly better accuracy. We test these hypotheses by carrying out one of the largest experimental studies ever conducted into time series classification. Our first key finding is that there is no significant difference between the elastic distance measures in terms of classification accuracy on our data sets. Our second finding, and the major contribution of this work, is to define an ensemble classifier that significantly outperforms the individual classifiers. We also demonstrate that the ensemble is more accurate than approaches not based in the time domain. Nearly all TSC papers in the data mining literature cite DTW (with warping window set through cross validation) as the benchmark for comparison. We believe that our ensemble is the first ever classifier to significantly outperform DTW and as such raises the bar for future work in this area

Ischemic axonal injury up-regulates MARK4 in cortical neurons and primes tau phosphorylation and aggregation.

Ischemic injury to white matter tracts is increasingly recognized to play a key role in age-related cognitive decline, vascular dementia, and Alzheimer's disease. Knowledge of the effects of ischemic axonal injury on cortical neurons is limited yet critical to identifying molecular pathways that link neurodegeneration and ischemia. Using a mouse model of subcortical white matter ischemic injury coupled with retrograde neuronal tracing, we employed magnetic affinity cell sorting with fluorescence-activated cell sorting to capture layer-specific cortical neurons and performed RNA-sequencing. With this approach, we identified a role for microtubule reorganization within stroke-injured neurons acting through the regulation of tau. We find that subcortical stroke-injured Layer 5 cortical neurons up-regulate the microtubule affinity-regulating kinase, Mark4, in response to axonal injury. Stroke-induced up-regulation of Mark4 is associated with selective remodeling of the apical dendrite after stroke and the phosphorylation of tau in vivo. In a cell-based tau biosensor assay, Mark4 promotes the aggregation of human tau in vitro. Increased expression of Mark4 after ischemic axonal injury in deep layer cortical neurons provides new evidence for synergism between axonal and neurodegenerative pathologies by priming of tau phosphorylation and aggregation

Sustained microglial depletion with CSF1R inhibitor impairs parenchymal plaque development in an Alzheimer's disease model.

Many risk genes for the development of Alzheimer's disease (AD) are exclusively or highly expressed in myeloid cells. Microglia are dependent on colony-stimulating factor 1 receptor (CSF1R) signaling for their survival. We designed and synthesized a highly selective brain-penetrant CSF1R inhibitor (PLX5622) allowing for extended and specific microglial elimination, preceding and during pathology development. We find that in the 5xFAD mouse model of AD, plaques fail to form in the parenchymal space following microglial depletion, except in areas containing surviving microglia. Instead, Aβ deposits in cortical blood vessels reminiscent of cerebral amyloid angiopathy. Altered gene expression in the 5xFAD hippocampus is also reversed by the absence of microglia. Transcriptional analyses of the residual plaque-forming microglia show they exhibit a disease-associated microglia profile. Collectively, we describe the structure, formulation, and efficacy of PLX5622, which allows for sustained microglial depletion and identify roles of microglia in initiating plaque pathogenesis

Pseudoprogression After Proton Therapy of Pediatric Spinal Pilocytic Astrocytoma and Myxopapillary Ependymoma

https://openworks.mdanderson.org/sumexp23/1025/thumbnail.jp

Molecular and Microbial Microenvironments in Chronically Diseased Lungs Associated with Cystic Fibrosis.

To visualize the personalized distributions of pathogens and chemical environments, including microbial metabolites, pharmaceuticals, and their metabolic products, within and between human lungs afflicted with cystic fibrosis (CF), we generated three-dimensional (3D) microbiome and metabolome maps of six explanted lungs from three cystic fibrosis patients. These 3D spatial maps revealed that the chemical environments differ between patients and within the lungs of each patient. Although the microbial ecosystems of the patients were defined by the dominant pathogen, their chemical diversity was not. Additionally, the chemical diversity between locales in the lungs of the same individual sometimes exceeded interindividual variation. Thus, the chemistry and microbiome of the explanted lungs appear to be not only personalized but also regiospecific. Previously undescribed analogs of microbial quinolones and antibiotic metabolites were also detected. Furthermore, mapping the chemical and microbial distributions allowed visualization of microbial community interactions, such as increased production of quorum sensing quinolones in locations where Pseudomonas was in contact with Staphylococcus and Granulicatella, consistent with in vitro observations of bacteria isolated from these patients. Visualization of microbe-metabolite associations within a host organ in early-stage CF disease in animal models will help elucidate the complex interplay between the presence of a given microbial structure, antibiotics, metabolism of antibiotics, microbial virulence factors, and host responses.IMPORTANCE Microbial infections are now recognized to be polymicrobial and personalized in nature. Comprehensive analysis and understanding of the factors underlying the polymicrobial and personalized nature of infections remain limited, especially in the context of the host. By visualizing microbiomes and metabolomes of diseased human lungs, we reveal how different the chemical environments are between hosts that are dominated by the same pathogen and how community interactions shape the chemical environment or vice versa. We highlight that three-dimensional organ mapping methods represent hypothesis-building tools that allow us to design mechanistic studies aimed at addressing microbial responses to other microbes, the host, and pharmaceutical drugs

Topoisomerase 1 Inhibition in MYC-Driven Cancer Promotes Aberrant R-Loop Accumulation to Induce Synthetic Lethality

CRISPR screening reveals topoisomerase 1 as an immediately actionable vulnerability in cancers harboring MYC as a driver oncoprotein that can be targeted with clinically approved inhibitors. MYC is a central regulator of gene transcription and is frequently dysregulated in human cancers. As targeting MYC directly is challenging, an alternative strategy is to identify specific proteins or processes required for MYC to function as a potent cancer driver that can be targeted to result in synthetic lethality. To identify potential targets in MYC-driven cancers, we performed a genome-wide CRISPR knockout screen using an isogenic pair of breast cancer cell lines in which MYC dysregulation is the switch from benign to transformed tumor growth. Proteins that regulate R-loops were identified as a potential class of synthetic lethal targets. Dysregulated MYC elevated global transcription and coincident R-loop accumulation. Topoisomerase 1 (TOP1), a regulator of R-loops by DNA topology, was validated to be a vulnerability in cells with high MYC activity. Genetic knockdown of TOP1 in MYC-transformed cells resulted in reduced colony formation compared with control cells, demonstrating synthetic lethality. Overexpression of RNaseH1, a riboendonuclease that specifically degrades R-loops, rescued the reduction in clonogenicity induced by TOP1 deficiency, demonstrating that this vulnerability is driven by aberrant R-loop accumulation. Genetic and pharmacologic TOP1 inhibition selectively reduced the fitness of MYC-transformed tumors in vivo. Finally, drug response to TOP1 inhibitors (i.e., topotecan) significantly correlated with MYC levels and activity across panels of breast cancer cell lines and patient-derived organoids. Together, these results highlight TOP1 as a promising target for MYC-driven cancers.Significance: CRISPR screening reveals topoisomerase 1 as an immediately actionable vulnerability in cancers harboring MYC as a driver oncoprotein that can be targeted with clinically approved inhibitors