gebhart/patrepeval huggingface dataset:
Regulation of Retinoic Acid Receptor Expression by Peroxisome Proliferator- activated Receptor Ligands in Cancer Cells 1 (2003)

The peroxisome proliferator-activated receptor (PPAR) is a nuclear receptor family member that can form a heterodimeric complex with retinoid X receptor (RXR) and initiate transcription of target genes. In this study, we have examined the effects of the PPAR ligand ciglitazone and the RXR ligand SR11237 on growth and induction of retinoic acid receptor (RAR) expression in breast and lung cancer cells. Our results demonstrated that ciglitazone and SR11237 cooperatively inhibited the growth of ZR-75-1 and T-47D breast cancer and Calu-6 lung cancer cells. Gel shift analysis indicated that PPAR, in the presence of RXR, formed a strong complex with a retinoic acid response element ( retinoic acid response element) in the RAR promoter. In reporter gene assays, RXR ligands and ciglitazone, but not the PPAR ligand 15d-PGJ2, coopera- tively promoted the transcriptional activity of the retinoic acid response element. Ciglitazone, but not 15d-PGJ2, strongly induced RAR expres- sion in human breast and lung cancer cell lines when used together with SR11237. The induction of RAR expression by the ciglitazone and SR11237 combination was diminished by a PPAR-selective antagonist, bisphenol A diglycidyl ether. All-trans-retinoic acid or the combination of ciglitazone and SR11237 was able to induce RAR in all-trans-retinoic acid-resistant MDA-MB-231 breast cancer cells only when the orphan receptor chick ovalbumin upstream promoter transcription factor was expressed, or in the presence of the histone deacetylase inhibitor trichos- tatin A. These studies indicate the existence of a novel RAR-mediated signaling pathway of PPAR action, which may provide a molecular basis for developing novel therapies involving RXR and PPAR ligands in potentiating antitumor responses.
Lymphatic and blood vasculature in primary cutaneous melanomas of the scalp and neck (2014)

IHC allows accurate assessment of lymphovascular invasion in scalp/neck melanomas. In these tumors, we observed a high incidence of BVI, which deserves further investigations.
Protein Transduction Domain Mimics Facilitate Rapid Antigen Delivery into Monocytes (2019)

Delivering peptides and proteins with intracellular function represents a promising avenue for therapeutics, but remains a challenge due to the selective permeability of the plasma membrane. The successful delivery of cytosolically active proteins would enable many opportunities, including improved vaccine development through major histocompatibility complex (MHC) class I antigen display. Extended research using cell-penetrating peptides (CPPs) has aimed to facilitate intracellular delivery of exogenous proteins with some success. A new class of polymer-based mimics termed protein transduction domain mimics (PTDMs), which maintain the positive charge and amphiphilic nature displayed by many CPPs, was developed using a poly-norbornene-based backbone. Herein, we use a previously characterized PTDM to investigate delivery of the model antigen SIINFEKL into leukocytes. Peptide delivery into over 90% of CD14+ monocytes was detected in less than 15 min with nominal inflammatory cytokine response and high cell viability. The co-delivery of a TLR9 agonist and antigen using the PTDM into antigen-presenting cells in vitro showed presentation of SIINFEKL in association with MHC class I molecules, in addition to upregulation of classical differentiation markers revealing the ability of the PTDM to successfully deliver cargo intracellularly and show application in the field of immunotherapy.
Trust models in ubiquitous computing (2008)

We recapture some of the arguments for trust-based technologies in ubiquitous computing, followed by a brief survey of some of the models of trust that have been introduced in this respect. Based on this, we argue for the need of more formal and foundational trust models.
Efficient algorithm selection for packet classification using machine learning (2016)

Many packet classification algorithms with variable performances and capabilities are available. However, no single algorithm is guaranteed to outperform every other one in every case. Meta-Learning is a subfield in Machine Learning that aims to apply statistical techniques to automate the algorithm selection process. In this work, we propose a novel framework for efficient, automatic packet classification algorithm selection. By utilizing Meta-Learning and Artificial Neural Networks (ANNs) we are able to achieve an average accuracy of 90% when automatically choosing the most appropriate algorithm when applied to over a hundred different rulesets ranging in size from 1K to 5K.
Poor post-induction outcomes in patients with acute myeloid leukemia previously treated with hypomethylating agents (2023)

Patients with acute myeloid leukemia (AML) who have failed hypomethylating agents (HMA) have a poor prognosis. We examined whether high intensity induction chemotherapy could abrogate negative outcomes in 270 patients with AML or other high-grade myeloid neoplasms. Prior HMA therapy was significantly associated with a lower overall survival (OS) as compared to a reference group of patients with secondary disease without prior HMA therapy (median 7.2 vs 13.1 months). In patients with prior HMA therapy, high intensity induction was associated with a non-significant trend toward longer OS (median 8.2 vs 4.8 months) and decreased rates of treatment failure (39% vs 64%). These results redemonstrate poor outcomes in patients with prior HMA and suggest possible benefit of high intensity induction that should be evaluated in future studies.
Reduction of NOx Emissions in Alamo Area Council of Government Projects (2004)

This reports summarizes the electricity, natural gas and NOx emissions reductions from retrofit measures reported as part of the AACOG emissions reduction effort. The electricity and natural gas savings were collected by the Brooks Energy and Sustainability Laboratory (BESL), and reported to the Energy Systems Laboratory (ESL). The ESL then assembled these data for processing by eGRID. The results from BESL’s data collection efforts and the eGRID analysis are contained in this report.
Transformational IoT sensing for air pollution and thermal exposures (2022)

Cities today encounter significant challenges pertaining to urbanization and population growth, resource availability, and climate change. Concurrently, unparalleled datasets are generated through Internet of Things (IoT) sensing implemented at urban, building, and personal scales that serve as a potential tool for understanding and overcoming these issues. Focusing on air pollution and thermal exposure challenges in cities, we reviewed and summarized the literature on IoT environmental sensing on urban, building, and human scales, presenting the first integrated assessment of IoT solutions from the data convergence perspective on all three scales. We identified that there is a lack of guidance on what to measure, where to measure, how frequently to measure, and standards for the acceptable measurement quality on all scales of application. The current literature review identified a significant disconnect between applications on each scale. Currently, the research primarily considers urban, building, and personal scale in isolation, leading to significant data underutilization. We addressed the scientific and technological challenges and opportunities related to data convergence across scales and detailed future directions of IoT sensing along with short- and long-term research and engineering needs. IoT application on a personal scale and integration of information on all scales opens up the possibility of developing personal thermal comfort and exposure models. The development of personal models is a vital promising area that offers significant advancements in understanding the relationship between environment and people that requires significant further research.
Structure‐based discovery of novel US28 small molecule ligands with different modes of action (2016)

The human cytomegalovirus-encoded G protein-coupled receptor US28 is a constitutively active receptor, which can recognize various chemokines. Despite the recent determination of its 2.9 Å crystal structure, potent and US28-specific tool compounds are still scarce. Here, we used structural information from a refined US28:VUF2274 complex for virtual screening of >12 million commercially available small molecule compounds. Using a combined receptor- and ligand-based approach, we tested 98 of the top 0.1% ranked compounds, revealing novel chemotypes as compared to the ~1.45 million known ligands in the ChEMBL database. Two compounds were confirmed as agonist and inverse agonist, respectively, in both IP accumulation and Ca<sup>2+</sup> mobilization assays. The screening setup presented in this work is computationally inexpensive and therefore particularly useful in an academic setting as it enables simultaneous testing in binding as well as in different functional assays and/or species without actual chemical synthesis.
Lithography Assisted Fiber-Drawing Nanomanufacturing (2016)

We present a high-throughput and scalable technique for the production of metal nanowires embedded in glass fibres by taking advantage of thin film properties and patterning techniques commonly used in planar microfabrication. This hybrid process enables the fabrication of single nanowires and nanowire arrays encased in a preform material within a single fibre draw, providing an alternative to costly and time-consuming iterative fibre drawing. This method allows the combination of materials with different thermal properties to create functional optoelectronic nanostructures. As a proof of principle of the potential of this technique, centimetre long gold nanowires (bulk T<sub>m</sub> = 1064 °C) embedded in silicate glass fibres (T<sub>g</sub> = 567 °C) were drawn in a single step with high aspect ratios (>10<sup>4</sup>); such nanowires can be released from the glass matrix and show relatively high electrical conductivity. Overall, this fabrication method could enable mass manufacturing of metallic nanowires for plasmonics and nonlinear optics applications, as well as the integration of functional multimaterial structures for completely fiberised optoelectronic devices.
Affordable Large Scale Active-Phased Array Antenna for Ka-Band Mobile SATCOM Applications (2019)

This paper presents the design aspects and the implementation Of an electronically scanned active-phased array antenna (A-PAA) for high throughput Ka-band mobile satellite communication (SATCOM) applications. First, an A-PAA which consists of 64 (4×16) elements is presented as a first step in the evolution towards the final modular design concept. Next, a low cost/complexity solution based on a modular architecture is proposed. With this approach, A-PAAs of any size, shape, and configuration can be made of the same intelligent building block (active sub-array module). The measured results of the modular array show that the antenna’s main beam can be steered to ± 70° off the boresight.
Esterification of PQQ Enhances Blood-Brain Barrier Permeability and Inhibitory Activity against Amyloidogenic Protein Fibril Formation (2018)

Several neurodegenerative diseases have a common pathophysiology where selective damage to neurons results from the accumulation of amyloid oligomer proteins formed via fibrilization. Considering that the formation of amyloid oligomers leads to cytotoxicity, the development of chemical compounds that are able to effectively cross the blood-brain barrier (BBB) and inhibit this conversion to oligomers and/or fibrils is essential for neurodegenerative disease therapy. We previously reported that pyrroloquinoline quinone (PQQ) prevented aggregation and fibrillation of α-synuclein, amyloid β<sub>1-42</sub> (Aβ<sub>1-42</sub>), and mouse prion protein. To develop a novel drug against neurodegenerative diseases based on PQQ, it is necessary to improve the insufficient BBB permeability of PQQ. Here, we show that an esterified compound of PQQ, PQQ-trimethylester (PQQ-TME), has twice the BBB permeability than PQQ in vitro. Moreover, PQQ-TME exhibited greater inhibitory activity against fibrillation of α-synuclein, Aβ<sub>1-42</sub>, and prion protein. These results indicated that esterification of PQQ could be a useful approach in developing a novel PQQ-based amyloid inhibitor.
Improving Robustness of Helmet ANC with Auxiliary Filter-based Virtual Sensing for Head Rotation (2021)

Noise is a very important issue when riding a motorcycle. This is because prolonged exposure to noise can cause health problems such as tinnitus and hearing loss, which in turn can lead to traffic accidents. In order to solve this problem, several ANC systems have been proposed and studied. In addition to this, the head rotates from side to side while driving a motorcycle. Therefore, the positional relationship of the ANC system to the noise source changes, and the control filter used in ANC system also changes. In this paper, we investigate an appropriate method of switching noise control filters that can improve robustness against such head rotation, and verify its effectiveness through computer experiments based on real data.
Putting hornets on the genomic map (2023)

Hornets are the largest of the social wasps, and are important regulators of insect populations in their native ranges. Hornets are also very successful as invasive species, with often devastating economic, ecological and societal effects. Understanding why these wasps are such successful invaders is critical to managing future introductions and minimising impact on native biodiversity. Critical to the management toolkit is a comprehensive genomic resource for these insects. Here we provide the annotated genomes for two hornets, Vespa crabro and Vespa velutina. We compare their genomes with those of other social Hymenoptera, including the northern giant hornet Vespa mandarinia. The three hornet genomes show evidence of selection pressure on genes associated with reproduction, which might facilitate the transition into invasive ranges. Vespa crabro has experienced positive selection on the highest number of genes, including those putatively associated with molecular binding and olfactory systems. Caste-specific brain transcriptomic analysis also revealed 133 differentially expressed genes, some of which are associated with olfactory functions. This report provides a spring-board for advancing our understanding of the evolution and ecology of hornets, and opens up opportunities for using molecular methods in the future management of both native and invasive populations of these over-looked insects.
Control Over Gaussian Channels With and Without Source–Channel Separation (2019)

We consider the problem of controlling an unstable linear plant with Gaussian disturbances over an additive white Gaussian noise channel with an average transmit power constraint, where the signaling rate of communication may be different from the sampling rate of the underlying plant. Such a situation is quite common since sampling is done at a rate that captures the dynamics of the plant and that is often lower than the signaling rate of the communication channel. This rate mismatch offers the opportunity of improving the system performance by using coding over multiple channel uses to convey a single control action. In a traditional, separation-based approach to source and channel coding, the analog message is first quantized down to a few bits and then mapped to a channel codeword whose length is commensurate with the number of channel uses per sampled message. Applying the separation-based approach to control meets its challenges: first, the quantizer needs to be capable of zooming in and out to be able to track unbounded system disturbances, and second, the channel code must be capable of improving its estimates of the past transmissions exponentially with time, a characteristic known as anytime reliability. We implement a separated scheme by leveraging recently developed techniques for control over quantized-feedback channels and for efficient decoding of anytime-reliable codes. We further propose an alternative, namely, to perform analog joint source-channel coding, by this avoiding the digital domain altogether. For the case where the communication signaling rate is twice the sampling rate, we employ analog linear repetition as well as Shannon-Kotel'nikov maps to show a significant improvement in stability margins and linear-quadratic costs over separation-based schemes. We conclude that such analog coding performs better than separation, and can stabilize all moments as well as guarantee almost-sure stability.
Interleukin-17A/F1 Deficiency Reduces Antimicrobial Gene Expression and Contributes to Microbiome Alterations in Intestines of Japanese medaka (Oryzias latipes) (2020)

In mammals, interleukin (IL)-17A and F are hallmark inflammatory cytokines that play key roles in protection against infection and intestinal mucosal immunity. In the gastrointestinal tract (GI), the induction of antimicrobial peptide (AMP) production via Paneth cells is a fundamental role of IL-17A and F in maintaining homeostasis of the GI microbiome and health. Although mammalian IL-17A and F homologs (referred to as IL-17A/F1-3) have been identified in several fish species, their function in the intestine is poorly understood. Additionally, the fish intestine lacks Paneth cells, and its GI structure is very different from that of mammals. Therefore, the GI microbiome modulatory mechanism via IL-17A/F genes has not been fully elucidated. In this study, Japanese medaka (<i>Oryzias latipes</i>) were used as a teleost model, and IL-17A/F1-knockout (IL-17A/F1-KO) medaka were established using the CRISPR/Cas9 genome editing technique. Furthermore, two IL-17A/F1-deficient medaka strains were generated, including one strain containing a 7-bp deletion (-7) and another with an 11-bp addition (+11). After establishing F2 homozygous KO medaka, transcriptome analysis (RNA-seq) was conducted to elucidate IL-17A/F1-dependent gene induction in the intestine. Results of RNA-seq and real-time PCR (qPCR) demonstrated down-regulation of immune-related genes, including interleukin-1β (<i>IL-1</i>β), complement 1q subunit C (<i>C1qc</i>), transferrin a (<i>Tfa</i>), and G-type lysozyme (<i>LyzG</i>), in IL-17A/F1-KO medaka. Interestingly, protein and lipid digestive enzyme genes, including phospholipase A2, group IB (<i>pla2g1b</i>), and elastase-1-like (<i>CELA1</i>), were also downregulated in the intestines of IL-17A/F1-KO medaka. Furthermore, to reveal the influence of these downregulated genes on the gut microbiome in IL-17A/F1-KO, 16S rRNA-based metagenomic sequencing analysis was conducted to analyze the microbiome constitution. Under a non-exposed state, the intestinal microbiome of IL-17A/F1-KO medaka differed at the phylum level from wild-type, with significantly higher levels of Verrucomicrobia and Planctomycetes. Additionally, at the operational taxonomic unit (OTU) level of the human and fish pathogens, the Enterobacteriaceae <i>Plesiomonas shigelloides</i> was the dominant species in IL-17A/F1-KO medaka. These findings suggest that IL-17A/F1 is involved in the maintenance of a healthy gut microbiome.
Learning mappings onto regularized latent spaces for biometric\n authentication (2019)

We propose a novel architecture for generic biometric authentication based on\ndeep neural networks: RegNet. Differently from other methods, RegNet learns a\nmapping of the input biometric traits onto a target distribution in a\nwell-behaved space in which users can be separated by means of simple and\ntunable boundaries. More specifically, authorized and unauthorized users are\nmapped onto two different and well behaved Gaussian distributions. The novel\napproach of learning the mapping instead of the boundaries further avoids the\nproblem encountered in typical classifiers for which the learnt boundaries may\nbe complex and difficult to analyze. RegNet achieves high performance in terms\nof security metrics such as Equal Error Rate (EER), False Acceptance Rate (FAR)\nand Genuine Acceptance Rate (GAR). The experiments we conducted on publicly\navailable datasets of face and fingerprint confirm the effectiveness of the\nproposed system.\n
Merging Models of Hepatitis C Virus Pathogenesis (2005)

Chronic hepatitis C virus (HCV) infection is one of the major causes for development of liver cirrhosis and end-stage liver disease. This article reviews two contrasting models of HCV pathogenesis, discusses the merits of each, and presents a rationale for combining the two models into one. Any successful model of HCV pathogenesis must explain how the characteristic features of cirrhosis and end-stage liver disease arise. These features include the loss of hepatocyte function (low serum albumin and reduced clotting ability); the presence of regenerative nodules; and the deposition of excessive extracellular matrix material, especially collagen (fibrosis), which is associated with the transformation of the liver sinusoids to capillary-like structures leading to portal hypertension. A successful model should explain several observations about the rate of disease progression. HCV is characterized by slow progression of fibrogenesis and, importantly, cirrhosis seems to develop only after a long latency (and only in a subset of patients). Among the prognostic factors of disease progression, the age at infection with the HCV virus and the presence of fibrosis appear to be highly relevant in predicting the development of progressive fibrosis. Traditional models of HCV pathogenesis propose that fibrogenesis is the predominant process. Fibrogenesis is induced by activation of fibrogenic cells, such as stellate cells, which results in excessive collagen deposition. By altering the normal architecture and vasculature, the collagen bands finally lead to cirrhosis and loss of organ function. Activation of stellate cells is induced by inflammation, cytokine signaling, and possibly by hepatocyte apoptosis. The telomere model of HCV pathogenesis suggests that hepatocyte damage plays an essential role in the development of cirrhosis. According to this model, hepatocyte damage leads to increased cell turnover, and to the accelerated shortening of hepatocyte telomeres. Critical telomere shortening leads to hepatocyte senescence, loss of hepatocyte function, exhaustion of hepatocellular regeneration, and to a greatly enhanced fibrotic response to injury. This review summarizes both models and presents evidence that these models are not mutually exclusive but rather can be merged into a comprehensive pathogenesis model that outlines the pathway of HCV-induced cirrhosis.
Menos insegurança hoje, mais liberdade amanhã. O passado ensina (2020)

Este ensaio está divido em duas partes intimamente interligadas. A primeira delas – “A burocracia da destruição” – refere-se ao mais contundente episódio de aniquilação sistemática do “inimigo”, a partir da negação dos seus direitos e da subestimação de seus atributos humanos. Na outra parte – “Homo homini lupus” – procura-se mostrar que a índole das pessoas e a trajetória histórica dos povos podem convergir em uma resultante que possibilita acontecer aquilo que os homens normais não imaginam que aconteça, cujo exemplo maior – embora não único – é o holocausto, o qual foi promovido pelo movimento totalitário nacional-socialista e sistematizado por um grupo burocrático-ideológico fanatizado. A breve consideração final, à guisa de conclusão, diz respeito à crença no aprendizado da geração atual com as que lhes antecederam no conturbado século XX. A maior estabilidade sociopolítica, nomeadamente na Europa de hoje, contribui para uma melhor convivência entre pessoas, maior confiança entre países e mais liberdade para todos.