Miracle-dz/UniFAR-FTUs huggingface dataset:
Proteomic analysis of endosomes from genetically modified p14/MP1 mouse embryonic fibroblasts

The p14/MP1 scaffold complex binds MEK1 and ERK1/2 on late endosomes, thus regulating the strength, duration and intracellular location of MAPK signaling. By organelle proteomics we have compared the protein composition of endosomes purified from genetically modified p14−/−, p14+/− and p14rev mouse embryonic fibroblasts. The latter ones were reconstituted retrovirally from p14−/− mouse embryonic fibroblasts by reexpression of pEGFP‐p14 at equimolar ratios with its physiological binding partner MP1, as shown here by absolute quantification of MP1 and p14 proteins on endosomes by quantitative MS using the Equimolarity through Equalizer Peptide strategy. A combination of subcellular fractionation, 2‐D DIGE and MALDI‐TOF/TOF MS revealed 31 proteins differentially regulated in p14−/− organelles, which were rescued by reexpression of pEGFP‐p14 in p14−/− endosomes. Regulated proteins are known to be involved in actin remodeling, endosomal signal transduction and trafficking. Identified proteins and their in silico interaction networks suggested that endosomal signaling might regulate such major cellular functions such as proliferation, differentiation, migration and survival.
Cocaine Disinhibits Dopamine Neurons by Potentiation of GABA Transmission in the Ventral Tegmental Area

Drugs, Dopamine, and Disinhibition Drugs often change the neuronal circuitry in the brain and thereby cause a long-lasting change in behavior. Using a wide range of in vivo and in vitro techniques in mice, Bocklisch et al. (p. 1521) observed that cocaine profoundly altered dopamine neuron function and that drug-evoked synaptic plasticity in a specific set of neurons represents a crucial step in circuit remodeling. Changes in specific neuronal circuits suggest that drug-evoked synaptic plasticity facilitates drug-adaptive behavior. Drug-evoked synaptic plasticity in the mesolimbic system reshapes circuit function and drives drug-adaptive behavior. Much research has focused on excitatory transmission in the ventral tegmental area (VTA) and the nucleus accumbens (NAc). How drug-evoked synaptic plasticity of inhibitory transmission affects circuit adaptations remains unknown. We found that medium spiny neurons expressing dopamine (DA) receptor type 1 (D1R-MSNs) of the NAc project to the VTA, strongly preferring the GABA neurons of the VTA. Repeated in vivo exposure to cocaine evoked synaptic potentiation at this synapse, occluding homosynaptic inhibitory long-term potentiation. The activity of the VTA GABA neurons was thus reduced and DA neurons were disinhibited. Cocaine-evoked potentiation of GABA release from D1R-MSNs affected drug-adaptive behavior, which identifies these neurons as a promising target for novel addiction treatments.
Building temperature control using an enhanced MRAC approach

One crucial aspect in building engineering is to accomplish the trade-off between reduction of energy consumption and high level thermal comfort for the occupants. To this aim, advanced control algorithms are fundamental to guarantee a certain optimality of the system performance in working conditions that can be quite different from the nominal ones due to the presence, for example, of variable external wheatear conditions or parameter uncertainties. To impose an optimal behavior of the indoor air temperature while assuring robustness to plant parameter uncertainties and external disturbances, in this paper we propose an extension of the optimal model reference adaptive scheme presented in [6] that embeds additional adaptive actions to improve tracking performance. Performance of the novel strategy are investigated both analytically, by exploiting hyperstability theory, and numerically. In particular the numerical validation has been carried out by using a detailed thermal-hygrometric simulation code (DETEC 2.1). Results confirm the effectiveness of the control in exemplar case of studies referred to buildings of different sizes and located in different European weather zones.
Micro Hypervisor Verification: Possible Approaches and Relevant Properties

The SoS-group at the Radboud University Nijmegen participates in the Robin project. The goal of this project is to develop a minimal trusted computing base for virtualizing (multiple instances of different) distrusted legacy operating systems in a secure way. With the resulting system it shall be possible to use, for instance, Word on Microsoft Windows for composing classified documents in a secure way. Thereby it is not necessary to trust Windows in any way, the Windows instance that is used could even have been compromised by an attacker already. In this paper I give an short overview about the Nizza architecture that is further developed in the Robin project. I further elaborate on our task at Radboud University: To develop a verification approach for the underlying micro hypervisor for relevant security properties.
Mitochondrial DNA in ancient human populations of Europe.

10 Thesis declaration . 11 Acknowledgments . 12 General Introduction . 14 RECONSTRUCTING PAST HUMAN POPULATION HISTORY USING MODERN MITOCHONDRIAL DNA . 15 Mitochondrial DNA: presentation . 15 Studying mitochondrial variation . 16 Genetic variation . 16 Phylogenetics and phylogeography . 16 Dating using molecular data, and its limits . 17 Population genetics . 19 The coalescent theory and coalescent simulations . 21 Reconstructing past genetic history of Europeans using mitochondrial data . 23 African origins of humans . 23 Out-of-Africa . 25 Genetic origins of Europeans . 26 Limits of modern DNA studies . 29 RECONSTRUCTING PAST HUMAN POPULATION HISTORY USING ANCIENT DNA . 29 First ancient DNA studies . 30 The nature of ancient DNA . 30 Post-mortem degradation of DNA . 31 Contamination . 33 Authenticating ancient DNA data . 34 Survival of DNA. 38 Applications of ancient DNA . 39 Phylogeny and phylogeography of extant and extinct species . 40
A Prediction Study of Path Loss Models from 2-73.5 GHz in an Urban-Macro Environment

It is becoming clear that 5G wireless systems will encompass frequencies from around 500 MHz all the way to around 100 GHz. To adequately assess the performance of 5G systems in these different bands, path loss (PL) models will need to be developed across this wide frequency range. The PL models can roughly be broken into two categories, ones that have some anchor in physics, and ones that curve- match only over the data set without any physical anchor. In this paper we use both real-world measurements from 2 to 28 GHz and ray-tracing studies from 2 to 73.5 GHz, both in an urban-macro environment, to assess the prediction performance of the two PL modeling techniques. In other words, we look at how the two different PL modeling techniques perform when the PL model is applied to a prediction set which is different in distance, frequency, or environment from a measurement set where the parameters of the respective models are determined. We show that a PL model with a physical anchor point can be a better predictor of PL performance in the prediction sets while also providing a parameterization which is more stable over a substantial number of different measurement sets.
Design for Testability in Software Systems

Building reliable software is becoming more and more important considering that software applications are becoming pervasive in our daily lives. The need for more reliable software requires that, amongst others, it is adequately tested to give greater confidence in its ability to perform as expected. However, testing software becomes a tedious task as the size and complexity of software increases, therefore, the next logical step is to make the task of testing easier and more effective. In other words, improving on the testability of the software. Improvement of testability can be achieved through applying certain tactics in practice that improve on a tester’s ability to better manipulate the software and to better observe and interpret the results from the execution of tests. Graduation Committee: Chair: Prof. Dr. Arie van Deursen, Faculty EEMCS, TU Delft University supervisor: Dr. Andy Zaidman, Faculty EEMCS, TU Delft Company supervisor: Nico van Rooijen, MR Software, Philips Medical Systems
Tissue engineering: current state and prospects.

Organ shortage and suboptimal prosthetic or biological materials for repair or replacement of diseased or destroyed human organs and tissues are the main motivation for increasing research in the emerging field of tissue engineering. No organ or tissue is excluded from this multidisciplinary research field, which aims to provide vital tissues with the abilities to function, grow, repair, and remodel. There are several approaches to tissue engineering, including the use of cells, scaffolds, and the combination of the two. The most common approach is biodegradable or resorbable scaffolds configured to the shape of the new tissue (e.g. a heart valve). This scaffold is seeded with cells, potentially derived from either biopsies or stem cells. The seeded cells proliferate, organize, and produce cellular and extracellular matrix. During this matrix formation, the starter matrix is degraded, resorbed, or metabolized. First clinical trials using skin or cartilage substitutes are currently under way. Both the current state of the field and future prospects are discussed.
Comparative Effectiveness of Carotid Artery Stenting Versus Carotid Endarterectomy Among Medicare Beneficiaries

Background—Effectiveness of carotid artery stenting (CAS) relative to carotid endarterectomy (CEA) among Medicare patients has not been established. We compared effectiveness of CAS versus CEA among Medicare beneficiaries. Methods and Results—We linked Medicare data (2000–2009) to the Society for Vascular Surgery’s Vascular Registry (2005–2008) and the National Cardiovascular Data Registry's (NCDR) Carotid Artery Revascularization and Endarterectomy Registry (2006–2008/2009). Medicare patients were followed up from procedure date until death, stroke/transient ischemic attack, periprocedural myocardial infarction, or a composite end point for these outcomes. We derived high-dimensional propensity scores using registry and Medicare data to control for patient factors and adjusted for provider factors in a Cox regression model comparing CAS with CEA. Among 5254 Society for Vascular Surgery’s Vascular Registry (1999 CAS; 3255 CEA) and 4055 Carotid Artery Revascularization and Endarterectomy Registry (2824 CAS; 1231 CEA) Medicare patients, CAS patients had a higher comorbidity burden and were more likely to be at high surgical risk (Society for Vascular Surgery’s Vascular Registry: 96.7% versus 44.5%; Carotid Artery Revascularization and Endarterectomy Registry: 71.3% versus 44.7%). Unadjusted outcome risks were higher for CAS. Mortality risks remained elevated for CAS after adjusting for patient-level factors (hazard ratio, 1.24; 95% confidence interval, 1.06–1.46). After further adjustment for provider factors, differences between CAS and CEA were attenuated or no longer present (hazard ratio for mortality, 1.13; 95% confidence interval, 0.94–1.37). Performance was comparable across subgroups defined by sex and degree of carotid stenosis, but there was a nonsignificant trend suggesting a higher risk of adverse outcomes in older (>80) and symptomatic patients undergoing CAS. Conclusions—Outcomes after CAS and CEA among Medicare beneficiaries were comparable after adjusting for both patient- and provider-level factors.
Releasing Network Isolation Problem in Group-Based Industrial Wireless Sensor Networks

In this paper, we propose a cross-layer optimization scheme named Adjusting the Transmission Radius (ATR), which is based on the Energy Consumed uniformly Connected <inline-formula><tex-math notation="LaTeX">$K$</tex-math></inline-formula>-Neighborhood (EC-CKN) sleep scheduling algorithm in wireless sensor networks (WSNs). In particular, we discovered two important problems, namely, the <italic>death acceleration problem</italic> and the <italic>network isolation problem</italic>, in EC-CKN-based WSNs. Furthermore, we solve these two problems in ATR, which creates sleeping opportunities for the nodes that cannot get a chance to sleep in the EC-CKN algorithm. Simulation and experimental results show that the network lifetime of ATR-Connected-<inline-formula><tex-math notation="LaTeX">$K$</tex-math></inline-formula>-Neighborhood-based WSNs increases by 19%, on average, and the maximum increment is 41%. In addition, four important insights were discovered through this research work and presented in this paper.
GANs for Biological Image Synthesis

In this paper, we propose a novel application of Generative Adversarial Networks (GAN) to the synthesis of cells imaged by fluorescence microscopy. Compared to natural images, cells tend to have a simpler and more geometric global structure that facilitates image generation. However, the correlation between the spatial pattern of different fluorescent proteins reflects important biological functions, and synthesized images have to capture these relationships to be relevant for biological applications. We adapt GANs to the task at hand and propose new models with casual dependencies between image channels that can generate multichannel images, which would be impossible to obtain experimentally. We evaluate our approach using two independent techniques and compare it against sensible baselines. Finally, we demonstrate that by interpolating across the latent space we can mimic the known changes in protein localization that occur through time during the cell cycle, allowing us to predict temporal evolution from static images.
Selective Tumor Necrosis Factor Receptor I Blockade Is Antiinflammatory and Reveals Immunoregulatory Role of Tumor Necrosis Factor Receptor II in Collagen‐Induced Arthritis

Tumor necrosis factor (TNF) signals via 2 receptors, TNFR type I (TNFRI) and TNFRII, with distinct cellular distribution and signaling functions. In rheumatoid arthritis (RA), the net effect of TNFR signaling favors inflammatory responses while inhibiting the activity of regulatory T cells. TNFRII signaling has been shown to promote Treg cell function. To assess the relative contributions of TNFRI and TNFRII signaling to inflammatory and regulatory responses in vivo, we compared the effect of TNF blockade, hence TNFRI/II, versus TNFRI alone in collagen‐induced arthritis (CIA) as a model of RA.
Predictive Inference Under Model Misspecification with an Application to Assessing the Marginal Predictive Content of Money for Output

In this chapter we discuss model selection and predictive accuracy tests in the context of parameter and model uncertainty under recursive and rolling estimation schemes. We begin by summarizing some recent theoretical findings, with particular emphasis on the construction of valid bootstrap procedures for calculating the impact of parameter estimation error. We then discuss the Corradi and Swanson (CS: 2002) test of (non)linear out-of-sample Granger causality. Thereafter, we carry out a series of Monte Carlo experiments examining the properties of the CS and a variety of other related predictive accuracy and model selection type tests. Finally, we present the results of an empirical investigation of the marginal predictive content of money for income, in the spirit of Stock and Watson (1989), Swanson (1998) and Amato and Swanson (2001).
Differential gene expression in healing rat corneal epithelium.

PURPOSE The authors used and validated a recently developed method, mRNA differential display, to detect and clone genes that are differentially expressed in healing compared to stationary corneal epithelium. METHODS RNAs from unwounded and 18-hour postwound corneal epithelia were isolated and subjected to mRNA differential display analysis. The generated cDNAs were used as probes in Northern blot analysis and in situ hybridization to confirm their differential expression and to clone longer or full-length cDNAs from a healing corneal epithelial cDNA library. RESULTS Changes in the pattern of gene expression in healing epithelium, compared with that in stationary cells, were noted. To date, 15 combinations of 5'- and 3'- primers were used with approximately 1500 mRNA species screened. Differential expression of nine mRNA species were observed. These included four known proteins. They are nonmuscle tropomyosin TM-1, cytokeratin K14, small GTP binding protein rab 11, and amyloid beta-A4 precursor-like protein-2. One is a sequence with homology to type II cytokeratin, and four represent genes with sequences that are unreported. The differential expression of five of these genes was confirmed by Northern blot analysis, in situ hybridization, or both. CONCLUSION mRNA differential display provides a unique and powerful experimental system to study differential gene expression in wound healing and cell migration. Using this system, differential expression of nine genes was observed. Detection of genes differentially expressed in healing epithelium may prompt studies that will define the specific role of each of the proteins in wound healing.
Pharmacokinetics and Pharmacodynamics of Recombinant FGF‐2 in a Phase I Trial in Coronary Artery Disease

Fibroblast growth factor‐2 (FGF‐2) is a heparin‐binding protein capable of inducing angiogenesis in multiple animal models of chronic ischemia. The pharmacokinetics and pharmacodynamics of a single dose of recombinant FGF‐2 (rFGF‐2) administered by intracoronary or intravenous infusion were evaluated in a Phase I trial in 66 patients with severe coronary artery disease. rFGF‐2 displayed biphasic elimination with a mean studywide distribution t1/2 of 21 minutes and a mean apparent terminal elimination t1/2 of 7.6 hours. Systemic exposure to rFGF‐2 was comparable following intracoronary or intravenous administration. Peak plasma concentration and area under the concentration‐time curve increased proportionally with dose, indicating linear pharmacokinetics over the dose range examined (0.33 to 48.0 μg/kg). Greater systemic exposure was observed when heparin was administered closer to rFGF‐2 infusion, consistent with slower clearance of heparin/rFGF‐2 complexes. Infusion of rFGF‐2 was associated with changes in acute hemodynamics. While a clear PK/PD dose‐response relationship was not established, a trend toward hypotension and tachycardia with higher rFGF‐2 doses was observed.
Antiamnesic Activity of an Ayurvedic Formulation Chyawanprash in Mice

Chyawanprash (Chy) is an ayurvedic formulation commonly consumed in Indian households. Chy is a comprehensive herbal tonic, prepared from around 50 herbs employing anwala (Emblica officinalis) as the basic ingredient. The present study was undertaken to explore the beneficial effects of Chy (at the dose of 1 and 2% w/w of diet) administered daily for 15 successive days in mice with memory deficits. A total of 228 mice divided in 38 groups were employed in this study. Morris water maze, Hebb-Williams maze and elevated plus maze served as exteroceptive memory models, whereas scopolamine (Sco)-induced amnesia and alprazolam (Alp)-induced amnesia served as interoceptive memory models. The brain acetylcholinesterase activity, brain thiobarbituric acid reactive substances (TBARS) and reduced glutathione levels (GSH) were also estimated. The administration of Chy for 15 consecutive days significantly protected the animals from developing memory impairment. Furthermore, there was a significant decrease in brain TBARS and increase in GSH levels after administration of Chy (2% w/w), thereby indicating decreased free radical generation and increased scavenging of free radical, respectively. Thus, Chy may prove to be a useful remedy for the management of Alzheimer's disease owing to its antioxidant effect, pro-cholinergic action and/or antiamnesic potential.
Engagement of CD44 modulates cyclooxygenase induction, VEGF generation, and cell proliferation in human vascular endothelial cells

CD44 is a receptor for hyaluronic acid and is found on the surface of hematopoetic cells and in mesenchymal tissue. It is also expressed on endothelial cells (EC). Cyclooxygenase (COX) is the rate‐limiting enzyme in the production of prostaglandins in EC. Here we show that engagement of CD44 with signaling monoclonal antibodies (mAbs) or its natural ligand hyaluronic acid induces COX‐2 and prostacyclin (PGI2) formation in human EC. This induction was blocked by mAbs that have been shown to inhibit CD44‐mediated intracellular signaling. COX‐1 induction was not observed after CD44 ligation. CD44‐stimulated COX‐2 activation/PGI2 production was accompanied by the production of the potent endothelial mitogen, vascular endothelial growth factor (VEGF) and was inhibited by a neutralizing VEGF antibody. Moreover, this COX‐2 induction was also associated with an increase in EC proliferation that was inhibited by the blocking anti‐CD44 mAbs and a COX‐2‐specific inhibitor. This is the first study to show that engagement of CD44 with mAbs or its natural ligand induces COX‐2, generates VEGF, and thus leads to an increase in EC proliferation. Results from this study may have important and widespread implications for the development of novel therapeutic agents for modulating blood vessel growth during ischemic heart disease, during inflammation, or around solid tumors.
Similarity networks for classification: a case study in the Horse Colic problem

This paper develops a two-layer neural network in which the neuron model computes a user-defined similarity function between inputs and weights. The neuron transfer function is formed by composition of an adapted logistic function with the mean of the partial input-weight similarities. The resulting neuron model is capable of dealing directly with variables of potentially different nature (continuous, fuzzy, ordinal, categorical). There is also provision for missing values. The network is trained using a two-stage procedure very similar to that used to train a radial basis function (RBF) neural network. The network is compared to two types of RBF networks in a non-trivial dataset: the Horse Colic problem, taken as a case study and analyzed in detail.
Detecting nearly duplicated records in location datasets

The quality of a local search engine, such as Google and Bing Maps, heavily relies on its geographic datasets. Typically, these datasets are obtained from multiple sources, e.g., different vendors or public yellow-page websites. Therefore, the same location entity, like a restaurant, might have multiple records with slightly different presentations of title and address in different data sources. For instance, 'Seattle Premium Outlets' and 'Seattle Premier Outlet Mall' describe the same Outlet located in the same place while their titles are not identical. This will cause many nearly-duplicated records in a location database, which would bring trouble to data management and make users confused by the various search results of a query. To detect these nearly duplicated records, we propose a machine-learning-based approach, which is comprised of three steps: candidate selection, feature extraction and training/inference. Three key features consisting of name similarity, address similarity and category similarity, as well as corresponding metrics, are proposed to model the differences between two entity records. We evaluate our method with intensive experiments based on a large-scale real dataset. As a result, both the precision and recall of our method exceeded 90%.