Miracle-dz/UniFAR-FTUs huggingface dataset:
Defining Elastic Fiber Interactions by Molecular Fishing

Deciphering interacting networks of the extracellular matrix is a major challenge. We describe an affinity purification and mass spectrometry strategy that has provided new insights into the molecular interactions of elastic fibers, essential extracellular assemblies that provide elastic recoil in dynamic tissues. Using cell culture models, we defined primary and secondary elastic fiber interaction networks by identifying molecular interactions with the elastic fiber molecules fibrillin-1, MAGP-1, fibulin-5, and lysyl oxidase. The sensitivity and validity of our method was confirmed by identification of known interactions with the bait proteins. Our study revealed novel extracellular protein interactions with elastic fiber molecules and delineated secondary interacting networks with fibronectin and heparan sulfate-associated molecules. This strategy is a novel approach to define the macromolecular interactions that sustain complex extracellular matrix assemblies and to gain insights into how they are integrated into their surrounding matrix.
Nonconvex proximal splitting with computational errors ∗

Throughout this chapter, ‖·‖ denotes the standard Euclidean norm. Problem (1) generalizes the more thoroughly studied class of composite convex optimization problems [30], a class that has witnessed huge interest in machine learning, signal processing, statistics, and other related areas. We refer the interested reader to [2, 3, 21, 37] for several convex examples and recent references. A thread common to existing algorithms for solving composite problems is the remarkably fruitful idea of proximal-splitting [9]. Here, nonsmoothness is handled via proximity operators [29], which allows one to treat the nonsmooth objective f + r essentially as a smooth one. But leveraging proximal-splitting methods is considerably harder for nonconvex problems, especially without compromising scalability. Numerous important problems have appealing nonconvex formulations: matrix factorization [25, 27], blind deconvolution [24], dictionary learning and sparse reconstruction [23, 27], and neural networks [4, 19, 28], to name a few. Regularized optimization within these problems requires handling nonconvex composite objectives, which motivates the material of this chapter. The focus of this chapter is on a new proximal splitting framework called: Nonconvex Inexact Proximal Splitting, hereafter Nips. The Nips framework is inexact because it allows for computational errors, a feature that helps it scale to large-data problems. In contrast to typical incremental methods [5] and to most stochastic gradient methods [16, 18] that assume vanishing errors, Nips allows the computational errors to be nonvanishing. Nips inherits this capability from the remarkable framework of Solodov [33]. But Nips not only builds on [33], it strictly generalizes it: Unlike [33], Nips allows r 6= 0 in (1). To our knowledge, Nips is the first nonconvex proximal splitting method that has both batch and incremental incarnations; this claim remains true, even if we were to exclude the nonvanishing error capability.1 We mention some more related work below. Among batch nonconvex splitting methods an early paper is [14]. Another batch method can be found in the pioneering paper on composite minimization by Nesterov [30], who solves (1) via a splitting-like algorithm. Both [14] and [30] rely on monotonic descent (using line-search or otherwise) to ensure convergence. Very recently, [1] introduced a powerful class of “descent-methods” based on Kurdyka-Łojasiewicz theory. In general, the insistence on descent, while theoretically convenient,
Scutellaria barbate extract induces apoptosis of hepatoma H22 cells via the mitochondrial pathway involving caspase-3.

AIM To study the growth inhibitory and apoptotic effects of Scutellaria barbata D.Don (S. barbata) and to determine the underlying mechanism of its antitumor activity in mouse liver cancer cell line H22. METHODS Proliferation of H22 cells was examined by MTT assay. Cellular morphology of PC-2 cells was observed under fluorescence microscope and transmission electron microscope (EM). Mitochondrial transmembrane potential was determined under laser scanning confocal microscope (LSCM) with rhodamine 123 staining. Flow cytometry was performed to analyze the cell cycle of H22 cells with propidium iodide staining. Protein level of cytochrome C and caspase-3 was measured by semi-quantitive RT-PCR and Western blot analysis. Activity of caspase-3 enzyme was measured by spectrofluorometry. RESULTS MTT assay showed that extracts from S. barbata (ESB) could inhibit the proliferation of H22 cells in a time-dependent manner. Among the various phases of cell cycle, the percentage of cells in S phase was significantly decreased, while the percentage of cells in G(1) phase was increased. Flow cytometry assay also showed that ESB had a positive effect on apoptosis. Typical apoptotic morphologies such as condensation and fragmentation of nuclei and blebbing membrane of apoptotic cells could be observed under transmission electron microscope and fluorescence microscope. To further investige the molecular mechanism behind ESB-induced apoptosis, ESB-treated cells rapidly lost their mitochondrial transmembrane potential, released mitochondrial cytochrome C into cytosol, and induced caspase-3 activity in a dose-dependent manner. CONCLUSION ESB can effectively inhibit the proliferation and induce apoptosis of H22 cells involving loss of mitochondrial transmembrane potential, release of cytochrome C, and activation of caspase-3.
Abstract 16080: Chronic Akt Blockade Aggravates Pathological Hypertrophy and Inhibits Physiological Hypertrophy

Background: Attenuation of adverse myocardial remodeling contributes to improved prognosis after pathological injury of the heart. Activation of Akt in the heart seems to exert positive or negative effects on cardiac function depending on the stimulus which leads to its activation. Here, we investigated the effect of chronic Akt blockade by Deguelin (DEG) on myocardial remodeling and the development of hypertrophy following a pathological stimulus (myocardial infarction and aortic banding) and following exercise training (controlled treadmill running). Methods: Wistar rats were orally treated with DEG (4.0 mg/kg) for 4 weeks starting one day after induction of myocardial infarction (MI) or aortic banding. Exercise animals received DEG for 4 weeks during the training period. Results: DEG treatment leads to a significant reduction of phosphorylation of Akt in all groups. 4 weeks after MI, DEG treated animals showed impaired LV function with enhanced LVEDD (12±0,3mm vs 11.1±0,4mm, p<0.05), EDV (439±8μl vs 38.
Utilising redundant voltage levels for circulating current control in modular multilevel converters

Control of the circulating current in the modular multilevel converter (MMC) is one of the major tasks for the proper operation of the converter topology. This paper develops a controller for the circulating current of the MMC that utilises the redundant voltage levels in 2N+1 modulated MMCs in order to regulate the current to its reference. The main advantages of the approach are the elimination of control loops that generate the voltages for the control of the circulating current, simple implementation and very fast dynamic performance. The application of the control is also independent of the circulating current reference. The simplicity and effectiveness of the proposed controller is illustrated through simulations and experimental results.
Probabilistic Logic Learning via Active Advice Seeking

Machine learning approaches that utilize human experts combine domain experience with data to generate novel knowledge. Unfortunately, most methods either provide only a limited form of communication with the human expert and/or are overly reliant on the human expert to specify their knowledge upfront. Thus, the expert is unable to understand what the system could learn without their involvement. Allowing the learning algorithm to query the human expert in the most useful areas takes full advantage of the data as well as the expert. We introduce active advice-seeking for relation domains. Relational logic allows for compact, but expressive interaction between the human expert and the learning algorithm. We demonstrate our algorithm empirically on several standard relational datasets.
Diagnosis and treatment of bacterial endometritis in Arabian mares.

Endometritis remains a major clinical problem in broodmare practice. The diagnosis of endometritis is based on the presence of inflammation, the mareâ€™s history, physical and reproductive examination including transrectal ultrasonography and laboratory diagnostic aids. In this study, eighteen repeat breeder mares were suspected to be suffering from endometritis through their examination by ultrasonography. A total of 18 uterine swabs from these mares were evaluated and the bacterial isolates were identified. The bacterial species most frequently isolated was E. coli (9 isolates, 50%), Staphylococcus aureus (5 isolates, 27.8%) and Klebsiella pneumoniae (3 isolates, 16.7%),citrobacter freundii and Streptococci (2 isolates, 11.1%). The study also revealed that other Klebsiella oxytoca, Providencia alcalifaciens and Proteus mirabilis were found in the uterine culture but in very lower frequencies. Ciprofloxacin and enrofloxacin was the most effective antimicrobial agent inhibiting most of uterine bacterial isolates in our work.
A 122 GHz Sub-Harmonic Mixer With a Modified APDP Topology for IC Integration

This letter presents a modified passive subharmonic mixer (SHM) topology based on an anti-parallel-diode-pair (APDP). It features a differential intermediate frequency output facilitating IC integration and improving common-mode noise rejection. An example 122 GHz SHM has been designed and tested in a 0.13 μm SiGe BiCMOS technology for a 122 GHz radar IC. SiGe HBT transistors have been diode-connected to form the APDP. The example SHM exhibits a conversion loss of 8 dB with a 5 dBm LO pumping power. The measured bandwidth extends from 117 to 124 GHz, adequately covering the 122-123 GHz ISM band, while the input 1 dB compression point and noise figure were measured to be -5 dBm and 8.5 dB respectively. Due to its superior 1/f noise performance and high linearity, the mixer is especially well suited to zero intermediate frequency radars.
Psychometric Assessment of the Neurobehavioral Symptom Inventory-22: The Structure of Persistent Postconcussive Symptoms Following Deployment-Related Mild Traumatic Brain Injury Among Veterans

ILD TRAUMATIC BRAIN INJURY (mTBI),also known as concussion, has been labeled asthe “signature injury” of Operations Enduring Free-dom/Iraqi Freedom (OEF/OIF). The persistent effectsof concussion are a focus of both research and reha-bilitation interventions, not only within the VeteransHealth Administration (VA), but in the general med-ical community.
Impact of Relays on LTE-Advanced Performance

This paper studies the performance and coverage improvements introduced by relay deployment in LTE-Advanced systems. Different relay deployment strategies are investigated, namely, amplify-and-forward (AF) repeaters and decode-and-forward (DF) relays (orthogonal and non-orthogonal modes). First, the expressions of peak throughput (i.e., assuming allocate all resources in a cell to one user) for different relay deployment strategies are derived. Next, the calculation of resource partition between e-Node B (eNB) and relay nodes for the repeater and relay scenarios are detailed. A capacity evaluation method for relay deployment is then proposed; this includes the analysis of user-perceived Quality of Service (QoS) based on cell traffic. In addition, we investigate a more advanced adaptive resource sharing strategy for more efficient resource utilization among relays in a cell. Finally, the performances of the different relay deployment strategies are compared using simulation results.
Basic Thresholding Classification

In this thesis, we propose a light-weight sparsity-based algorithm, basic thresholding classifier (BTC), for classification applications (such as face identification, hyper-spectral image classification, etc.) which is capable of identifying test samples extremely rapidly and performing high classification accuracy. Originally BTC is a linear classifier which works based on the assumption that the samples of the classes of a given dataset are linearly separable. However, in practice those samples may not be linearly separable. In this context, we also propose another algorithm namely kernel basic thresholding classifier (KBTC) which is a non-linear kernel version of the BTC algorithm. KBTC can achieve promising results especially when the given samples are linearly non-separable. For both proposals, we introduce sufficient identification conditions (SICs) under which BTC and KBTC can identify any test sample in the range space of a given dictionary. By using SICs, we develop parameter estimation procedures which do not require any cross validation. Both BTC and KBTC algorithms provide efficient classifier fusion schemes in which individual classifier outputs are combined to produce better classification results. For instance, for the application of face identification, this is done by combining the residuals having different random projectors. For spatial applications such as hyper-spectral image classification, the fusion is carried out by incorporating the spatial information, in which the output residual maps are filtered using a smoothing filter. Numerical results on publicly available face and hyper-spectral datasets show that our proposal outperforms well-known support vector machines (SVM)-based techniques, multinomial logistic regression (MLR)-based methods, and sparsity-based approaches like $l_1$-minimization and simultaneous orthogonal matching pursuit (SOMP).
Combined T and B Cell Immunodeficiencies 2

The first description of a child with a deficiency in cellular immunity was made by Glanzmann and Riniker in 1950 [162]. Some years later, Hitzig et al. identified patients with a combined deficiency of the cellular and humoral immunity, the so called “Swiss Type” agammaglobulinemia with the clinical triad of mucocutaneous candidiasis, intractable diarrhea and interstitial pneumonia [187]. As immunodeficiencies with autosomal recessive and also X-linked transmission were observed subsequently, a heterogeneous etiology was soon suspected. In the meantime, about 150 different primary immunodeficiency diseases (PID) have been described [133, 152], and more than 120 genes could be identified, whose mutations generate inborn immunodeficiencies [152, 258]. The analysis of the molecular basis of the different PID has contributed to a better understanding of the physiological development of the immune system, allowing a precise molecular diagnosis, genetic counseling and prenatal diagnosis, and is the basis for the development of innovative therapeutical options like gene therapy. The overall incidence of all inborn immunodeficiencies is 1:10,000 newborns. Even today, in some patients, the diagnosis of PID is made only late or not all. Recurrent infections with often severe and protracted evolution lead to growth delay and organ damage, and can, if untreated, lead promptly to death in the case of severe PID. Combined immunodeficiencies are a heterogeneous group of immunodeficiencies (Table 2.1) that are characterized by defects of the T cell development and/or T cell function, and that can be associated to variable defects of B or natural killer cells. Due to the missing T cell help, the B cell function is altered even in case of normal B cell maturation. Chapter 2
Poly-dipeptides encoded by the C9orf72 repeats bind nucleoli, impede RNA biogenesis, and kill cells

Dipeptide repeat peptides on the attack Certain neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), are associated with expanded dipeptides translated from RNA transcripts of disease-associated genes (see the Perspective by West and Gitler). Kwon et al. show that the peptides encoded by the expanded repeats in the C9orf72 gene interfere with the way cells make RNA and kill cells. These effects may account for how this genetic form of ALS causes disease. Working in Drosophila, Mizielinska et al. aimed to distinguish between the effects of repeat-containing RNAs and the dipeptide repeat peptides that they encode. The findings provide evidence that dipeptide repeat proteins can cause toxicity directly. Science, this issue p. 1139 and p. 1192; see also p. 1118 Repeated structural motifs encoded by disease genes impair RNA metabolism and cause cell death. [Also see Perspective by West and Gitler] Many RNA regulatory proteins controlling pre–messenger RNA splicing contain serine:arginine (SR) repeats. Here, we found that these SR domains bound hydrogel droplets composed of fibrous polymers of the low-complexity domain of heterogeneous ribonucleoprotein A2 (hnRNPA2). Hydrogel binding was reversed upon phosphorylation of the SR domain by CDC2-like kinases 1 and 2 (CLK1/2). Mutated variants of the SR domains changing serine to glycine (SR-to-GR variants) also bound to hnRNPA2 hydrogels but were not affected by CLK1/2. When expressed in mammalian cells, these variants bound nucleoli. The translation products of the sense and antisense transcripts of the expansion repeats associated with the C9orf72 gene altered in neurodegenerative disease encode GRn and PRn repeat polypeptides. Both peptides bound to hnRNPA2 hydrogels independent of CLK1/2 activity. When applied to cultured cells, both peptides entered cells, migrated to the nucleus, bound nucleoli, and poisoned RNA biogenesis, which caused cell death.
Protein arginine methylation of SERBP1 by protein arginine methyltransferase 1 affects cytoplasmic/nuclear distribution

Protein arginine methylation regulates a broad array of cellular processes. SERBP1 implicated in tumor progression through its putative involvement in the plaminogen activator protease cascade, is an RNA‐binding protein containing an RG‐rich domain and an RGG box domain that might be methylated by protein arginine N‐methyltransferases (PRMTs). Asymmetric dimethylarginine (aDMA) was detected in SERBP1 and an indirect methyltransferase inhibitor adenosine dialdehyde (AdOx) significantly reduced the methylation signals. Arginines in the middle RG and C‐terminal RGG region of SERBP1 are methylated based on the analyses of different deletion constructs. The predominant type I protein arginine methyltransferase PRMT1 co‐immunoprecipitated with SERBP1 and the level of bound PRMT1 decreased upon the addition of AdOx. Recombinant PRMT1 methylated SERBP1 and knockdown of PRMT1 significantly reduced the aDMA level of SERBP1, indicating that SERBP1 is specifically methylated by PRMT1. Immunofluorescent analyses of endogenous SERBP1 showed predominant cytoplasmic localization of SERBP1. Treatment of AdOx or PRMT1 siRNA increased the nuclear localization of SERBP1. Analyses of different deletions indicated that the middle RG region is important for the nuclear localization while both N‐ and C‐ terminus are required for nuclear export. Low methylation of the C‐terminal RGG region also favors nuclear localization. In conclusion, the RG‐rich and RGG box of SERBP1 is asymmetrically dimethylated by PRMT1 and the modification affects protein interaction and intracellular localization of the protein. These findings provide the basis for dissecting the roles of SERBP1. J. Cell. Biochem. 113: 2721–2728, 2012. © 2012 Wiley Periodicals, Inc.
Gene expression changes in thalamus and inferior colliculus associated with inflammation, cellular stress, metabolism and structural damage in thiamine deficiency

Identification of gene expression changes that promote focal neuronal death and neurological dysfunction can further our understanding of the pathophysiology of these disease states and could lead to new pharmacological and molecular therapies. Impairment of oxidative metabolism is a pathogenetic mechanism underlying neuronal death in many chronic neurodegenerative diseases as well as in Wernicke's encephalopathy (WE), a disorder induced by thiamine deficiency (TD). To identify functional pathways that lead to neuronal damage in this disorder, we have examined gene expression changes in the vulnerable thalamus and inferior colliculus of TD rats using Affymetrix Rat Genome GeneChip analysis in combination with gene ontology and functional categorization assessment utilizing the NetAffx GO Mining Tool. Of the 15 927 transcripts analysed, 125 in thalamus and 141 in inferior colliculus were more abundantly expressed in TD rats compared with control animals. In both regions, the major functional categories of transcripts that were increased in abundance after TD were those associated with inflammation (∼33%), stress (∼20%), cell death and repair (∼26%), and metabolic perturbation (∼19%), together constituting ∼98% of all transcripts up‐regulated. These changes occurred against a background of neuronal cell loss and reactive astro‐ and microgliosis in both structures. Our results indicate that (i) TD produces changes in gene expression that are consistent with the observed dysfunction and pathology, and (ii) similar alterations in expression occur in thalamus and inferior colliculus, brain regions previously considered to differ in pathology. These findings provide important new insight into processes responsible for lesion development in TD, and possibly WE.
Localization in an Industrial Environment: A Case Study on the Difficulties for Positioning in a Harsh Environment

While indoor localization has become a highly growing application domain in the last few years, it is hardly investigated in industrial environments. Interferences of magnetic fields, shadowing, and multipath propagation discourage positioning system vendors from porting their techniques to these harsh environments. However, the actual influence of these interferences on the positioning accuracy and the differences between an industrial and a nonindustrial environment have never been evaluated. This paper analyzes the actual differences for a positioning technique that is based on Wi-Fi fingerprinting, map matching, dead reckoning, filtering, and a plausibility determination. An investigation of the Wi-Fi signal strengths and compass sensor values in an industrial and a nonindustrial environment thereby showed that the differences between them are significant. In fact, it shows that more interferences and shadowing in the industrial environment resulted in even more accurate positioning.