gebhart/patrepeval huggingface dataset:
Transcriptional modulation of pattern recognition receptors in chronic colitis in mice is accompanied with Th1 and Th17 response (2017)

Pattern recognition receptors (PRRs) may contribute to inflammatory bowel diseases (IBD) development due to their microbial-sensing ability and the unique microenvironment in the inflamed gut. In this study, the PRR mRNA expression profile together with T cell-associated factors in the colon was examined using a chronic colitis mice model. 8-12 week old C57BL/6 mice were exposed to multiple dextran sodium sulfate (DSS) treatments interspersed with a rest period to mimic the course of chronic colitis. The clinical features and histological data were collected. The mRNA expressions of colonic PRRs, T cell-associated components were measured. Finally, the colons were scored for Foxp3+ cells. During chronic colitis, the histological data, but not the clinical manifestations demonstrated characteristic inflammatory symptoms in the distal colon. In contrast to acute colitis, the expression of all <i>Toll-like receptors (Tlrs)</i>, except <i>Tlr5</i> and <i>Tlr9</i>, was unaffected after repeated DSS treatments. The expression of <i>Nod1</i> was decreased, while <i>Nod2</i> increased. After third DSS treatment, only the expressions of <i>Tlr3</i> and <i>Tlr4</i> were significantly enhanced. Unlike other PRRs, decreased <i>Tlr5</i> and increased <i>Tlr9</i> mRNA expression persisted during the chronic colitis period. As the colitis progress, only the mRNA expression of <i>Ifnγ</i> and <i>Il17</i> staid increased during chronic colitis, while the acute colitis-associated increase of <i>Il23,</i> and <i>Il10</i> and <i>Il12</i> was abolished. Finally, increased histological score of Foxp3+ cell in colon was found during the chronic colitis period. This study provides an expression pattern of PRRs during chronic colitis that is accompanied by a Th1- and Th17 cell-mediated immune response.
Evidence of Tetrahedral and Octahedral Aluminum Coordination in Rare‐Earth Aluminates (1991)

Abstract The local order around the aluminum atoms in a series of rare‐earth aluminates with perovskite and garnet structure is characterized by X‐ray diffractometry and by near K‐edge X‐ray absorption. The aluminate samples are elaborated by an original sol‐gel technique. The Al XANES spectra contain features which appear to be similar to those recorded on other aluminum fluorites with similar structure. In both systems, K edge clearly demonstrat a structure showing the octahedral metal–oxygen coordination for the perovskite stoichiometry and a mixture of tetrahedral and octahedral coordination for the garnet stoichiometry.
Going Deep: Using deep learning techniques with simplified mathematical\n models against XOR BR and TBR PUFs (Attacks and Countermeasures) (2020)

This paper contributes to the study of PUFs vulnerability against modeling\nattacks by evaluating the security of XOR BR PUFs, XOR TBR PUFs, and obfuscated\narchitectures of XOR BR PUF using a simplified mathematical model and deep\nlearning (DL) techniques. Obtained results show that DL modeling attacks could\neasily break the security of 4-input XOR BR PUFs and 4-input XOR TBR PUFs with\nmodeling accuracy $\\sim$ 99%. Similar attacks were executed using single-layer\nneural networks (NN) and support vector machines (SVM) with polynomial kernel\nand the obtained results showed that single NNs failed to break the PUF\nsecurity. Furthermore, SVM results confirmed the same modeling accuracy\nreported in previous research ($\\sim$ 50%). For the first time, this research\nempirically shows that DL networks can be used as powerful modeling techniques\nagainst these complex PUF architectures for which previous conventional machine\nlearning techniques had failed. Furthermore, a detailed scalability analysis is\nconducted on the DL networks with respect to PUFs' stage size and complexity.\nThe analysis shows that the number of layers and hidden neurons inside every\nlayer has a linear relationship with PUFs' stage size, which agrees with the\ntheoretical findings in deep learning. Consequently, A new obfuscated\narchitecture is introduced as a first step to counter DL modeling attacks and\nit showed significant resistance against such attacks (16% - 40% less\naccuracy). This research provides an important step towards prioritizing the\nefforts to introduce new PUF architectures that are more secure and\ninvulnerable to modeling attacks. Moreover, it triggers future discussions on\nthe removal of influential bits and the level of obfuscation needed to confirm\nthat a specific PUF architecture is resistant against powerful DL modeling\nattacks.\n
Continuous health monitoring: An opportunity for precision health (2021)

Continuous health monitoring and integrated diagnostic devices, worn on the body and used in the home, will help to identify and prevent early manifestations of disease. However, challenges lie ahead in validating new health monitoring technologies and in optimizing data analytics to extract actionable conclusions from continuously obtained health data.
Be Prepared When Network Goes Bad: An Asynchronous View-Change Protocol (2021)

The popularity of permissioned blockchain systems demands BFT SMR protocols that are efficient under good network conditions (synchrony) and robust under bad network conditions (asynchrony). The state-of-the-art partially synchronous BFT SMR protocols provide optimal linear communication cost per decision under synchrony and good leaders, but lose liveness under asynchrony. On the other hand, the state-of-the-art asynchronous BFT SMR protocols are live even under asynchrony, but always pay quadratic cost even under synchrony. In this paper, we propose a BFT SMR protocol that achieves the best of both worlds -- optimal linear cost per decision under good networks and leaders, optimal quadratic cost per decision under bad networks, and remains always live.
Gluing Interfaces with Soft Nanoparticles (2019)

Nanoparticles have been recently shown to be able to act as effective adhesives capable of binding two soft materials together. We performed coarse-grained molecular dynamics simulations to study contact mechanics of soft nanoparticles at the interfaces between two elastic surfaces. Depending on the nanoparticle size as well as the substrates' elastic and interfacial properties, a nanoparticle at the interface between two elastic substrates could be in a bridging or Pickering state. The degree of penetration of a nanoparticle into a substrate is shown to be determined by nanoparticle size, strength of nanoparticle-substrate interactions, and nanoparticle and substrate elastic properties. Using the weighted histogram analysis method, we calculated the potential of mean force for separation of two substrates whose interface was reinforced by deformable nanoparticles. These simulations show that interface reinforcement is a function of nanoparticle size and elastic modulus. The most effective reinforcement of the interface was observed for the softest nanoparticles which could result in close to 8 times increase in the work of adhesion.
An Electrochemical Impedimetric Aptasensing Platform for Sensitive and Selective Detection of Small Molecules Such as Chloramphenicol (2014)

We report on the aptadetection of chloramphenicol (CAP) using electrochemical impedance spectroscopy. The detection principle is based on the changes of the interfacial properties of the electrode after the interaction of the ssDNA aptamers with the target molecules. The electrode surface is partially blocked due to the formation of the aptamer-CAP complex, resulting in an increase of the interfacial electron-transfer resistance of the redox probe detected by electrochemical impedance spectroscopy or cyclic voltammetry. We observed that the ratio of polarization resistance had a linear relationship with the concentrations of CAP in the range of 1.76-127 nM, and a detection limit of 1.76 nM was obtained. The covalent binding of CAP-aptamer on the electrode surface combined with the unique properties of aptamers and impedimetric transduction leads to the development of a stable and sensitive electrochemical aptasensor for CAP.
The Identification of Myosin in Rabbit Hepatocytes (1976)

A myosin-like protein was identified in isolated rabbit liver cells. It was extracted with high-ionic-strength buffer containing ATP, and purified by gel filtration in the presence of iodide. The myosin polypeptide was indistinguishable in size from the heavy chain of muscle myosin as determined by electrophoresis on polyacrylamide gels and gel filtration in the presence of sodium dodecyl sulfate. The hepatic myosin had an amino acid composition similar to that of muscle myosin, but lacked 3-methylhistidine. The Mg2+ -ATPase of the myosin was not activated by muscle actin. At low ionic strength, in the presence of Mg2+, the protein aggregated to form bipolar filaments 0.3 mum in length. A protein which resembled muscle actin in size and amino acid composition was extracted along with the myosin. Based on scans of stained sodium dodecyl sulfate polyacrylamide gels, the myosin content was estimated as 0.3% to 0.4% of the cell protein. The actin-like component was present in approximately ten-fold excess by weight. This ratio suggests that the organization and function of myosin in the hepatocyte is very different from that in the muscle cell.
사이버범죄에 대한 미디어의존과 위험 심각성 및 주관적 지식이 예방행동 의도에 미치는 영향 (2014)

본 연구는 공중의 행위적 차원에 초점을 두고, 문헌검토를 통해 다양한 심리학적 요인들을 추출, 공중의 사이버범죄에 대한 예방행동 의도에 영향을 미치는 요인들을 탐색, 검증하였다. 이에 가설검증 결과를 제시하면 다음과 같다. 첫째, 사이버범죄에 대한 미디어의존은 공중의 위험 심각성에 통계적으로 유의한 정적 영향을 미치는 것으로 나타났다. 둘째, 공중의 사이버범죄 관련 정보에 대한 미디어의존은 주관적 지식에 통계적으로 유의한 정적 영향을 미치는 것으로 나타났다. 셋째, 공중의 위험 심각성은 주관적 지식에 대해 통계적으로 유의한 정적 영향을 미치는 것으로 나타났다. 넷째, 공중의 위험 심각성은 사이버범죄 예방행동 의도에 통계적으로 유의한 정적 영향을 미치는 것으로 나타났다. 다섯째, 공중의 주관적 지식은 예방행동 의도에 통계적으로 유의한 정적 영향을 미치는 것으로 나타났다. 이상의 결과를 고려할 때, 미디어는 새로운 기술적 위험에 대해 공중이 올바르게 위험을 평가하고 대처할 수 있도록 정확한 정보와 지식을 제공하고, 이해당사자들(정부, 공중, 전문가)의 소통과 참여를 유도하며, 과학적 지식이 특정 집단의 이익을 위해 배타적으로 이용되거나 전달되지 않도록 정보와 지식의 다원성을 추구하고 넓힐 필요가 있을 것이다.
Lymphocyte markers, serum thymic factor and IgE in IgA deficiency. (1979)

Eleven patients having a selective IgA deficiency had very low T-cell percentages assessed by using E-rosettes, active E-rosetts and an anti-human anti-T-lymphocyte antigen serum. B-cells were normal or slightly decreased. IgE concentrations were often low. Patients with serum IgA under 50 IU/ml often had elevated serum IgE values and low T-cell percentages. Serum thymic factor dosages were correlated with the E-rosette assay.
Circulating Adiponectin Levels Are Paradoxically Associated With Mortality Rate: A Systematic Review and Meta-Analysis (2018)

Our results strongly points to a paradoxical association between high adiponectin levels and increased mortality rate, which is partly modulated by natriuretic peptides.
In Vivo Studies on Mouse Erythrocytes Linked to Transferrin (2002)

Transferrin (Tf), a plasma protein with numerous, highly specific receptors in proliferating and differentiating cells was already discussed as a targeting ligand for drugs and liposomes in previous studies. In this paper, we deal with erythrocytes linked to Tf as possible physiological targeting carrier systems for delivering anticancer drugs. For that purpose we have used glutaraldehyde (0.1%) as a coupling agent between Tf and erythrocytes. The highest amount of Tf linked to erythrocytes turned out to be 0.76 +/- 0.13 microg Tf/10(6) cells, while reaching 65% of cell recovery. After 13 days, the Tf-erythrocytes hemolysis reached 50%, with transferrin still coupled to erythrocytes. The in vivo kinetic behaviour of intravenously injected 51Cr-Tf-erythrocytes showed a reduced half-life to hours as compared to days of controls. However, a considerable percentage of Tf-erythrocytes (close to 20%) remained circulating for a relatively long period (around 2 days), which made possible the specific targeting by these carrier systems. In vivo biodistribution studies indicated that 51Cr-Tf-erythrocytes rapidly accumulated in the different studied organs (liver, spleen, lungs, kidneys, femur-tibia, and heart), suggesting a selective removal of Tf-erythrocytes by the cells of the mononuclear phagocytic system present mainly in liver and spleen. On the other hand, Tf-erythrocytes showed a poor targeting of heart tissue, therefore a reduced cardiac toxicity should be expected after administration of erythrocyte-encapsulated drugs. The presence of Tf-erythrocytes in femur-tibia and spleen could be related to the Tf-specific binding to the hematopoietic cells containing Tf receptors. The final results of this study encourage additional research on Tf-erythrocyte to investigate the relationship between transferrin-mediated targeting by carrier erythrocytes and uptake of different erythrocyte-encapsulated drugs. Consequently, the current study showed possible use of these carriers as a potential therapeutic tool for drug targeting in animal models with alterations affecting mononuclear phagocytic system or carcinomas of various origins whose cells show elevated number of Tf receptors.
Contribution of traffic-originated nanoparticle emissions to regional and local aerosol levels (2021)

Abstract. Sub-50 nm particles originating from traffic emissions pose risks to human health due to their high lung deposition efficiency and potentially harmful chemical composition. We present a modelling study using an updated EUCAARI number emission inventory, incorporating a more realistic, empirically justified particle size distribution (PSD) for sub-50 nm particles from road traffic. We present experimental PSDs and CO2 concentrations, measured in a highly trafficked street canyon in Helsinki, Finland, as an emission factor particle size distribution (EFPSD), which was then used in updating the EUCAARI inventory. We applied the updated inventory in a simulation using the regional chemical transport model PMCAMx-UF over Europe for May 2008 to test the effect of updated emissions in regional and local scales and in contrast to atmospheric new particle formation (NPF). Updating the inventory increased simulated average total particle number concentrations by only 1 %, although the total particle number emissions were increased to a 3-fold level. The concentrations increased up to 11 % when only 1.3–3 nm-sized particles (nanocluster aerosol, NCA) were considered. These values indicate that the effect of updating overall is insignificant in a regional scale during this photochemically active period, during which the fraction of the total particle number originating through atmospheric NPF processes was 91 %. These simulations give a lower limit for the contribution of traffic to the aerosol levels. Nevertheless, the situation is different when examining the effect of the update spatially or temporally, or when focusing to the chemical composition or the origin of the particles. For example, daily average NCA concentrations increased by a factor of several hundreds or thousands in some locations on certain days. Overall, the most significant effects–reaching several orders of magnitude–from updating the inventory are observed when examining specific particle sizes (especially 7–20 nm), particle components, and specific urban areas. While the model still has a tendency to predict more sub-50 nm particles compared to the observations, the most notable underestimations in the concentrations of sub-10 nm particles are, after updating, overcome and the simulated distributions now agree better with the data observed at locations having high traffic densities. The findings of this study highlight the need to consider emissions, PSDs, and composition of sub-50 nm particles from road traffic in studies focusing on urban air quality. Updating this emission source brings the simulated aerosol levels particularly in urban locations closer to observations, which highlights its importance for calculations of human exposure to nanoparticles.
Genetic diversity within and between European pig breeds using microsatellite markers (2006)

"Chantier qualité spécifique "Auteurs Externes" département de Génétique animale : uniquement liaison auteur au référentiel HR-Access "
Convolutional Neural Network-based Speech Enhancement for Cochlear\n Implant Recipients (2019)

Attempts to develop speech enhancement algorithms with improved speech\nintelligibility for cochlear implant (CI) users have met with limited success.\nTo improve speech enhancement methods for CI users, we propose to perform\nspeech enhancement in a cochlear filter-bank feature space, a feature-set\nspecifically designed for CI users based on CI auditory stimuli. We leverage a\nconvolutional neural network (CNN) to extract both stationary and\nnon-stationary components of environmental acoustics and speech. We propose\nthree CNN architectures: (1) vanilla CNN that directly generates the enhanced\nsignal; (2) spectral-subtraction-style CNN (SS-CNN) that first predicts noise\nand then generates the enhanced signal by subtracting noise from the noisy\nsignal; (3) Wiener-style CNN (Wiener-CNN) that generates an optimal mask for\nsuppressing noise. An important problem of the proposed networks is that they\nintroduce considerable delays, which limits their real-time application for CI\nusers. To address this, this study also considers causal variations of these\nnetworks. Our experiments show that the proposed networks (both causal and\nnon-causal forms) achieve significant improvement over existing baseline\nsystems. We also found that causal Wiener-CNN outperforms other networks, and\nleads to the best overall envelope coefficient measure (ECM). The proposed\nalgorithms represent a viable option for implementation on the CCi-MOBILE\nresearch platform as a pre-processor for CI users in naturalistic environments.\n
Seismic Modeling and Imaging with the Complete Wave Equation (1997)

“Seismic modeling and imaging of the earth's subsurface are complex and difficult computational tasks. The authors present general numerical methods based on the complete wave equation for solving these important seismic exploration problems.”
Nano-Sized Particles for EOR (2010)

Abstract During the last decades colloidal dispersion gels (CDG) have been applied as an EOR method, providing sweep improvement in reservoirs with unfavourable mobility ratio. Our core flood results also indicate an improved microscopic sweep or microscopic diversion by CDG. This paper investigates the oil mobilization properties of nano-sized silica particles in comparison to nano-sized CDG particles and discusses the underlying mechanisms of microscopic flow diversion. Improved microscopic displacement efficiency has traditionally been coupled to changes in capillary number. However, this approach is insufficient to describe processes like low salinity injection, colloid dispersion gels, and microbial enhanced oil recovery. This paper presents a new concept of EOR by improved microscopic displacement defined as microscopic diversion. This method involves pore blocking and diversion of injection fluids. Multi-phase flow experiments using nano-sized silica particles attempts to investigate the effect (inelastic) nano-sized fines migration can have on oil mobilization by microscopic diversion. The oil mobilization properties were investigated by core floods using well-defined nano-sized silica particles in comparison with injection of CDG, polymer or silica particles dispersed in a polymer solution. Core floods were performed on water-wet Berea sandstone cores with permeabilities of approx. 500 mD. The comparison of inelastic silica particles, polymer solutions and nano-sized CDG particles allowed an evaluation of the importance of viscoelastic properties for microscopic diversion.
MicroRNAs as Key Players in Melanoma Cell Resistance to MAPK and Immune Checkpoint Inhibitors (2020)

Advances in the use of targeted and immune therapies have revolutionized the clinical management of melanoma patients, prolonging significantly their overall and progression-free survival. However, both targeted and immune therapies suffer limitations due to genetic mutations and epigenetic modifications, which determine a great heterogeneity and phenotypic plasticity of melanoma cells. Acquired resistance of melanoma patients to inhibitors of BRAF (BRAFi) and MEK (MEKi), which block the mitogen-activated protein kinase (MAPK) pathway, limits their prolonged use. On the other hand, immune checkpoint inhibitors improve the outcomes of patients in only a subset of them and the molecular mechanisms underlying lack of responses are under investigation. There is growing evidence that altered expression levels of microRNAs (miRNA)s induce drug-resistance in tumor cells and that restoring normal expression of dysregulated miRNAs may re-establish drug sensitivity. However, the relationship between specific miRNA signatures and acquired resistance of melanoma to MAPK and immune checkpoint inhibitors is still limited and not fully elucidated. In this review, we provide an updated overview of how miRNAs induce resistance or restore melanoma cell sensitivity to mitogen-activated protein kinase inhibitors (MAPKi) as well as on the relationship existing between miRNAs and immune evasion by melanoma cell resistant to MAPKi.
Development and Validation of Sex-Specific Hip Fracture Prediction Models using Electronic Health Records (2022)

Summary Background Hip fracture is associated with immobility, morbidity, mortality, and high medical cost. Due to limited availability of dual-energy X-ray absorptiometry (DXA), hip fracture prediction models without using bone mineral density (BMD) data are essential. We aimed to develop and validate 10-year sex-specific hip fracture prediction models using electronic health records (EHR) without BMD. Methods In this population-based study, the derivation cohort comprised 161,051 public healthcare service users (91,926 female; 69,125 male) in Hong Kong aged≥60. Sex-stratified derivation cohort was randomly split to 80% training and 20% internal testing datasets. An external validation cohort comprised 3,046 community-dwelling participants. With 395 potential predictors (age, diagnosis and drug prescription records from EHR), 10-year sex-specific hip fracture prediction models were developed using stepwise selection by logistic regression (LR) and four machine learning (ML) algorithms (gradient boosting machine, random forest, eXtreme gradient boosting, and single-layer neural networks) in the training cohort. Model performance was evaluated in both internal and external validation cohorts. Findings In female, the LR model had the highest AUC (0.815) and adequate calibration in internal validation. Reclassification metrics showed ML algorithms could not further improve the performance of the LR model. Similar performance was attained by the LR model in external validation, with high AUC (0.841) comparable to other ML algorithms. In internal validation for male, LR model had high AUC (0.818) and it outperformed all ML models as indicated by reclassification metrics, with adequate calibration. In external validation, the LR model had high AUC (0.898) comparable to ML algorithms. Reclassification metrics demonstrated that LR model had the best discrimination performance. Interpretation Even without using BMD data, the 10-year hip fracture prediction models developed by conventional LR had better discrimination performance than the models developed by ML algorithms. Upon further validation in independent cohorts, the LR models could be integrated into the routine clinical workflow, aiding the identification of people at high risk for DXA scan. Funding This study was funded by the Health and Medical Research Fund, Food and Health Bureau, Hong Kong SAR Government (reference: 17181381).