gebhart/patrepeval huggingface dataset:
Proteogenomic characterization of pancreatic ductal adenocarcinoma (2021)

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications. In addition, whole-genome sequencing, whole-exome sequencing, methylation, RNA sequencing (RNA-seq), and microRNA sequencing (miRNA-seq) were performed on the same tissues to facilitate an integrated proteogenomic analysis and determine the impact of genomic alterations on protein expression, signaling pathways, and post-translational modifications. To ensure robust downstream analyses, tumor neoplastic cellularity was assessed via multiple orthogonal strategies using molecular features and verified via pathological estimation of tumor cellularity based on histological review. This integrated proteogenomic characterization of PDAC will serve as a valuable resource for the community, paving the way for early detection and identification of novel therapeutic targets.
Silicon Photonics Integration for Future Generation Optical Network (2018)

The high power of photonic elements is now impeding the scalability of silicon photonic-based platforms. We show approaches based on novel materials as well as novel multiplexing approaches that alleviate this scalability challenge and enable large scale silicon photonic systems.
Docetaxel Skin Exposure and Micronucleation Contributes to Skin Toxicity Caused by CPC634 (2021)

Docetaxel entrapped nanoparticle CPC634 is associated with dose-related skin toxicity that resembles conventional docetaxel (Cd)-related skin toxicity. This study compared the cutaneous pharmacokinetics and pharmacodynamics of docetaxel and CPC634. In this randomised cross-over study, patients with solid tumours received one cycle of CPC634 and Cd (both at 75 mg/m<sup>2</sup>). Skin biopsies were taken at baseline and at day 8 of both cycles. Released and total docetaxel (released docetaxel plus entrapped docetaxel) concentrations and histopathological changes in the skin biopsies were evaluated. Twenty patients underwent paired skin biopsies for pharmacokinetic analysis and 10 patients had biopsies available for histopathological assessment. The total skin docetaxel concentration was 369% (95%CI: 229% to 569%, <i>p</i> < 0.001) higher after CPC634 administration compared to Cd while the released docetaxel concentrations were not statistically different (95%CI: -9% to 63%, <i>p</i> = 0.169). The CPC634 released docetaxel concentration in the skin was positively correlated with plasma concentrations (Pearson's correlation 0.48, <i>p</i> = 0.03). Histopathological examination revealed increased apoptosis, mitotic cells with nuclear atypia, and micronucleation with an enhanced Ki-67 index for both compounds. In conclusion, both CPC634 and Cd treatment result in docetaxel exposure in the skin causing cutaneous anti-mitotic effects such as micronucleation, which could induce an inflammatory reaction leading to skin toxicity.
MicroPET imaging of prostate cancer in LNCAP‐SR39TK‐GFP mouse xenografts (2003)

We demonstrated the feasibility of monitoring prostate cancer xenografts in a mouse model using microPET and the HSV1-sr39tk PET reporter gene/(18)F-FHBG reporter probe system. Extension of this approach may allow repetitive imaging of tumor metastases.
Nanobiotechnology II (2007)

Nanobiotechnology II More Concepts and Applications , Nanobiotechnology II More Concepts and Applications , کتابخانه الکترونیک و دیجیتال - آذرسا
Transcription of the Stationary-Phase-Associated hspX Gene of Mycobacterium tuberculosis Is Inversely Related to Synthesis of the 16-Kilodalton Protein (1999)

The 16-kDa protein, an alpha-crystallin homologue, is one of the most abundant proteins in stationary-phase Mycobacterium tuberculosis. Here, transcription and translation of the hspX gene, which encodes the 16-kDa protein, have been investigated by Northern blotting analysis, primer extension, and sodium dodecyl sulfate-polyacrylamide gel electrophoresis with a microaerophilic stationary-phase model. Two transcripts of about 2.5 and 1.1 kb were demonstrated by Northern blot analysis and hybridized to the hspX gene probe. Primer extension analysis revealed that the transcription start site is located 33 nucleotides upstream of the hspX gene start codon. The cellular level of the hspX mRNA was maximum in log-phase bacilli and was markedly reduced after 20 days in unagitated culture, when the organisms had entered the stationary phase. A third transcript of 0.5 kb was detected 0.6 kb downstream of the hspX gene; this transcript has a transcriptional pattern completely different from that of the 1.1- and 2.5-kb products, suggesting that there may be another gene in this region. In contrast to the high level of hspX mRNA in log-phase bacilli, 16-kDa protein synthesis was low in log-phase bacteria and rose to its maximum after 20 days. In both log-phase and stationary-phase bacteria the mRNA was unstable, with a half-life of 2 min, which indicated that the transcript stability was growth rate independent and not a general means for controlling the gene expression. However, the cellular content of 16-kDa protein, while low in log-phase bacteria, rose to a maximum at 10 days and remained at this high level for up to 50 days, which indicates that this protein is a stable molecule with a low turnover rate. These data suggest that the regulation of hspX expression during entry into and maintenance of stationary phase involves translation initiation efficiency and protein stability as potential mechanisms.
Cell proliferation and tissue remodeling are major determinants of cancer metabolism and the response to drugs targeting metabolism (2014)

Background

Alterations in cell proliferation and tissue remodeling are major hallmarks of cancer. Given that these two physiological processes require a significant investment of metabolic resources, we hypothesize that the metabolism of cancer cells is, in a first approximation, determined by the magnitude of cell proliferation and tissue remodeling.

Materials and methods

To address this question in further detail we have analyzed in vitro data characterizing cancer cell lines and gene expression profiles of human cancers.

Results

We show that the metabolism of cancer cells is strongly correlated with cell proliferation and tissue remodeling. Based on in vitro data, cancer cell lines align from an extreme of highly proliferating cells of relatively small size to another extreme of slowly proliferating cells with large size and mesenchymal properties [1]. Similarly, in human cancers we detect a strong negative correlation between gene signatures associated with cell proliferation and tissue remodeling [2]. The stratification of human cancers based on the cell-proliferation/ tissue-remodeling signatures results in divergence in the survival plots as significant as those obtained using current site-specific classifications. Furthermore, in vitro data suggest that these different subtypes have a differential sensitivity to diverse drug classes targeting metabolism [1].

Conclusions

We conclude that human cancers can be subject to a universal cell-proliferation/tissue-remodeling classification independent of their site of origin that can guide personalized treatment targeting cancer metabolism.
Bovine Pericardium for Portal Vein Reconstruction in Abdominal Surgery: A Surgical Guide and First Experiences in a Single Center (2015)

Our experience suggests a surgical procedure for an individual size-matched portal vein reconstruction using bovine pericardium. Although first results appear promising, prospective studies are required to objectively assess the patency of bovine pericardium compared with autologous and synthetic interposition grafts for portal vein reconstruction.
Identifying early pulmonary arterial hypertension biomarkers in systemic sclerosis: machine learning on proteomics from the DETECT cohort (2020)

Pulmonary arterial hypertension (PAH) is a devastating complication of systemic sclerosis (SSc). Screening for PAH in SSc has increased detection, allowed early treatment for PAH and improved patient outcomes. Blood-based biomarkers that reliably identify SSc patients at risk of PAH, or with early disease, would significantly improve screening, potentially leading to improved survival, and provide novel mechanistic insights into early disease. The main objective of this study was to identify a proteomic biomarker signature that could discriminate SSc patients with and without PAH using a machine learning approach and to validate the findings in an external cohort.Serum samples from patients with SSc and PAH (n=77) and SSc without pulmonary hypertension (non-PH) (n=80) were randomly selected from the clinical DETECT study and underwent proteomic screening using the Myriad RBM Discovery platform consisting of 313 proteins. Samples from an independent validation SSc cohort (PAH n=22 and non-PH n=22) were obtained from the University of Sheffield (Sheffield, UK).Random forest analysis identified a novel panel of eight proteins, comprising collagen IV, endostatin, insulin-like growth factor binding protein (IGFBP)-2, IGFBP-7, matrix metallopeptidase-2, neuropilin-1, N-terminal pro-brain natriuretic peptide and RAGE (receptor for advanced glycation end products), that discriminated PAH from non-PH in SSc patients in the DETECT Discovery Cohort (average area under the receiver operating characteristic curve 0.741, 65.1% sensitivity/69.0% specificity), which was reproduced in the Sheffield Confirmatory Cohort (81.1% accuracy, 77.3% sensitivity/86.5% specificity).This novel eight-protein biomarker panel has the potential to improve early detection of PAH in SSc patients and may provide novel insights into the pathogenesis of PAH in the context of SSc.
Fast τ-p transforms by chirp modulation (2018)

We have developed simple, fast, and accurate algorithms for the linear Radon ([Formula: see text]-[Formula: see text]) transform and its inverse. The algorithms have an [Formula: see text] computational complexity in contrast to the [Formula: see text] cost of a direct implementation in 2D and an [Formula: see text] computational complexity compared to the [Formula: see text] cost of a direct implementation in 3D. The methods use Bluestein’s algorithm to evaluate discrete nonstandard Fourier sums, and they need, apart from the fast Fourier transform (FFT), only multiplication of chirp functions and their Fourier transforms. The computational cost and accuracy are thus reduced to that inherited by the FFT. Fully working algorithms can be implemented in a couple of lines of code. Moreover, we find that efficient graphics processing unit (GPU) implementations could achieve processing speeds of approximately [Formula: see text], implying that the algorithms are I/O bound rather than compute bound.
Far-Field Generation of Localized Light Fields using Absorbance Modulation (2007)

In this Letter, we report the confinement of a uniform beam of light (lambda(1) = 400 nm) at the nodes of a standing wave (lambda(2) = 532 nm) via absorbance modulation. In the present implementation of absorbance modulation, a thin polymer film containing a photochromic azobenzene side chain is exposed to a standing wave at lambda(2) and a uniform beam at lambda(1), resulting in alternate regions of high and low absorbance. Light at lambda(1) is localized around the low-absorbance regions. Using photoresist exposures, we mapped out the localized light intensity distribution, which agrees well with our theoretical model. Since the width of this distribution is primarily determined by the ratio of the intensities at the two wavelengths, this technique opens up the possibility of localizing light fields below the diffraction limit using far-field optics.
Microsoft FlashMeta SDK A Framework for Creating Inductive Synthesizers (2015)

Talks at Dagstuhl seminar on Approaches and Applications of Inductive Programming, Oct 2015
Issues in Boundary Control (1996)

State plane analysis is used to study large-signal properties and control strategies for dc-dc converters. A general load line is defined and interpreted. The concept of a switching boundary is convenient for generalizing hysteretic controls. Boundaries are classified according to their local dynamics. Requirements for large-signal stability are established. It is shown that stable boundary controllers always require frequency limits or timing constraints to avoid chattering. Limit cycles occur under certain conditions when discontinuous mode adds a second boundary
Color Purity in Polymer Electrochromic Window Devices on Indium−Tin Oxide and Single-Walled Carbon Nanotube Electrodes (2009)

Dual polymer absorptive/transmissive electrochromic (EC) window devices have been assembled using the solution-processable and high-EC-contrast polymer PProDOT-(CH(2)OEtHx)(2) as the EC material, along with a non-color-changing electroactive polymer, poly(2,2,6,6-tetramethylpiperidinyloxy-4-yl methacrylate) (PTMA), as the counter electrode material. Indium-tin oxide (ITO) and highly transmissive single-walled carbon nanotube (SWNT) film coated glass electrodes are used as electrode substrates. The use of the EC/non-color-changing polymer combination allowed us to construct window devices that rapidly switch between magenta and highly transmissive (>95% T for ITO and approximately 79% T for SWNT) states with large optical modulation (>71% DeltaT for ITO and 66% DeltaT for SWNT). The devices showed effective coloration and bleaching: the lightness parameter (L*) changing from 67 to 95 for ITO (approximately 50-92 for SWNT), essentially reaching a diffuse white upon oxidation. The color modulates from highly pure magenta with a* = 28 (red hue) and b* = -28 (blue chroma) for ITO (a* = 40 and b* = -36 for SWNT) to nearly colorless with a* = 1 and b* = -1 for ITO (a* = -2 and b* = -3 for SWNT) devices. Increasing the switching voltage from 2.55 V up to 3.5 V resulted in faster SWNT-based window device performance.
Lysine Deacetylation by HDAC6 Regulates the Kinase Activity of AKT in Human Neural Progenitor Cells (2017)

The AKT family of serine-threonine kinases functions downstream of phosphatidylinositol 3-kinase (PI3K) to transmit signals by direct phosphorylation of a number of targets, including the mammalian target of rapamycin (mTOR), glycogen synthase kinase 3β (GSK3β), and β-catenin. AKT binds to phosphatidylinositol (3,4,5)-triphosphate (PIP<sub>3</sub>) generated by PI3K activation, which results in its membrane localization and subsequent activation through phosphorylation by phosphoinositide-dependent protein kinase 1 (PDK1). Together, the PI3K-AKT signaling pathway plays pivotal roles in many cellular systems, including in the central nervous system where it governs both neurodevelopment and neuroplasticity. Recently, lysine residues (Lys<sup>14</sup> and Lys<sup>20</sup>) on AKT, located within its pleckstrin homology (PH) domain that binds to membrane-bound PIP<sub>3</sub>, have been found to be acetylated under certain cellular contexts in various cancer cell lines. These acetylation modifications are removed by the enzymatic action of the class III lysine deacetylases, SIRT1 and SIRT2, of the sirtuin family. The extent to which reversible acetylation regulates AKT function in other cell types remains poorly understood. We report here that AKT kinase activity is modulated by a class IIb lysine deacetylase, histone deacetylase 6 (HDAC6), in human neural progenitor cells (NPCs). We find that HDAC6 and AKT physically interact with each other in the neuronal cells, and in the presence of selective HDAC6 inhibition, AKT is acetylated at Lys<sup>163</sup> and Lys<sup>377</sup> located in the kinase domain, two novel sites distinct from the acetylation sites in the PH-domain modulated by the sirtuins. Measurement of the functional effect of HDAC6 inhibition on AKT revealed decreased binding to PIP<sub>3</sub>, a correlated decrease in AKT kinase activity, decreased phosphorylation of Ser<sup>552</sup> on β-catenin, and modulation of neuronal differentiation trajectories. Taken together, our studies implicate the deacetylase activity of HDAC6 as a novel regulator of AKT signaling and point to novel mechanisms for regulating AKT activity with small-molecule inhibitors of HDAC6 currently under clinical development.
Dependable software needs pervasive debugging (2002)

Nobody would claim that debugging computer software is easy: all too often it proceeds by trial-and-error experiments in which programmers examine the behaviour of the system and form hypotheses that could explain what they see. These problems are exacerbated when developing distributed, peer-to-peer or multi-processor applications, or when unreliable network links form part of the system under test. Environments for pervasive computing take this to an extreme, allowing user-supplied code to run or migrate within and around the network.In this paper we show how to perform pervasive debugging, enabling complex multi-process applications to be debugged and controlled as single entities and their robustness to changes in network performance to be evaluated. We do this by virtualizing the resources used by the system, allowing the threads that it involves and the network links that it uses to be modelled within a single controllable process.
Convolutional neural networks for automated microseismic detection in downhole distributed acoustic sensing data and comparison to a surface geophone array (2020)

ABSTRACT Distributed acoustic sensing is a growing technology that enables affordable downhole recording of strain wavefields from microseismic events with spatial sampling down to ∼1 m. Exploiting this high spatial information density motivates different detection approaches than typically used for downhole geophones. A new machine learning method using convolutional neural networks is described that operates on the full strain wavefield. The method is tested using data recorded in a horizontal observation well during hydraulic fracturing in the Eagle Ford Shale, Texas, and the results are compared to a surface geophone array that simultaneously recorded microseismic activity. The neural network was trained using synthetic microseismic events injected into real ambient noise, and it was applied to detect events in the remaining data. There were 535 detections found and no false positives. In general, the signal‐to‐noise ratio of events recorded by distributed acoustic sensing was lower than the surface array and 368 of 933 surface array events were found. Despite this, 167 new events were found in distributed acoustic sensing data that had no detected counterpart in the surface array. These differences can be attributed to the different detection threshold that depends on both magnitude and distance to the optical fibre. As distributed acoustic sensing data quality continues to improve, neural networks offer many advantages for automated, real‐time microseismic event detection, including low computational cost, minimal data pre‐processing, low false trigger rates and continuous performance improvement as more training data are acquired.
Viral taxonomy derived from evolutionary genome relationships (2019)

We describe a new genome alignment-based model for understanding the diversity of viruses based on evolutionary genetic relationships. This approach uses information theory and a physical model to determine the information shared by the genes in two genomes. Pairwise comparisons of genes from the viruses are created from alignments using NCBI BLAST, and their match scores are combined to produce a metric between genomes, which is in turn used to determine a global classification using the 5,817 viruses on RefSeq. In cases where there is no measurable alignment between any genes, the method falls back to a coarser measure of genome relationship: the mutual information of 4-mer frequency. This results in a principled model which depends only on the genome sequence, which captures many interesting relationships between viral families, and which creates clusters which correlate well with both the Baltimore and ICTV classifications. The incremental computational cost of classifying a novel virus is low and therefore newly discovered viruses can be quickly identified and classified. The model goes beyond alignment-free classifications by producing a full phylogeny similar to those constructed by virologists using qualitative features, while relying only on objective genes. These results bolster the case for mathematical models in microbiology which can characterize organisms using only their genetic material and provide an independent check for phylogenies constructed by humans, considerably faster and more cheaply than less modern approaches.
DNA methylation profiling in the Carolina Breast Cancer Study defines cancer subclasses differing in clinicopathologic characteristics and survival (2014)

This study demonstrates that epigenetic patterns are strongly associated with HR status, subtype, and p53 mutation status and may show heterogeneity within tumor subclass. Among HR+ breast tumors, a subset exhibiting a gene signature characterized by hypermethylation of developmental genes and poorer clinicopathologic features may have prognostic value and requires further study. Genes differentially methylated between clinically important tumor subsets have roles in differentiation, development, and tumor growth and may be critical to establishing and maintaining tumor phenotypes and clinical outcomes.
Characterizing smoking-induced transcriptional heterogeneity in the human bronchial epithelium at single-cell resolution (2019)

The human bronchial epithelium is composed of multiple distinct cell types that cooperate to defend against environmental insults. While studies have shown that smoking alters bronchial epithelial function and morphology, its precise effects on specific cell types and overall tissue composition are unclear. We used single-cell RNA sequencing to profile bronchial epithelial cells from six never and six current smokers. Unsupervised analyses led to the characterization of a set of toxin metabolism genes that localized to smoker ciliated cells, tissue remodeling associated with a loss of club cells and extensive goblet cell hyperplasia, and a previously unidentified peri-goblet epithelial subpopulation in smokers who expressed a marker of bronchial premalignant lesions. Our data demonstrate that smoke exposure drives a complex landscape of cellular alterations that may prime the human bronchial epithelium for disease.
Leveraging Player Knowledge in Combinatorial Auctions (and Implementation in Surviving Strategies) (2008)

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