2,311 research outputs found

    Analysis of intracellular transport and functionality of human kidney anion exchanger 1 (kAE1) in yeast and mammalian cells

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    Anion exchanger proteins facilitate chloride-bicarbonate movement across the plasma membrane and play an important role in maintaining acid-base homeostasis in the human body. Kidney anion exchanger 1 (kAE1) is one of the major bicarbonate transporters among this group and helps to reabsorb bicarbonate for chloride in distal nephrons. Defects of this protein result in functional impairment of the anion exchange process that eventually leads to the development of a clinical condition known as distal renal tubular acidosis (dRTA). Although the genetic basis of kAE1 mutants leading to disease is largely known, the precise molecular processes of dRTA pathophysiology are still inadequately understood. Here, the potential of baker’s yeast was evaluated to address various cellular aspects of kAE1 physiology. For the first time, unmodified and tagged full-length versions of kAE1 were successfully expressed in yeast. Moreover, partial localization of the anion exchanger at the plasma membrane was validated by accomplishing several light and confocal microscopy techniques and biochemical assays. Subsequently, biological activity of the protein was demonstrated by performing intracellular pH measurements and chloride uptake assays. Additionally, a set of novel dRTA mutants was characterized in mIMCD3 cells, resembling the closest cellular model to α-intercalated cells. In sum, this study highlights novel possibilities to investigate kAE1-related physiology and pathology in more detail.Anionenaustauscherproteine erleichtern die Bewegung von Chlorid-Bicarbonat durch die Plasmamembran und spielen eine wichtige Rolle bei der Aufrechterhaltung der SĂ€ure-Base-Homöostase im menschlichen Körper. Der Anionenaustauscher 1 (kAE1) der Niere ist einer der wichtigsten Bicarbonat-Transporter, der die Resorption von Bicarbonat für Chlorid im distalen Nephron unterstützt. Defekte dieses Proteins führen zu einer BeeintrĂ€chtigung des Anionen-Austauschprozesses und zur Entwicklung der distalen renalen tubulĂ€ren Azidose (dRTA). Obwohl der genetische Hintergrund der krankmachenden kAE1-Mutanten weitgehend bekannt ist, sind die molekularen Prozesse der dRTA-Pathophysiologie nur unzureichend verstanden. In dieser Studie wurde die BĂ€ckerhefe zur Untersuchung zellulĂ€rer Aspekte der kAE1-Physiologie eingesetzt. Erstmalig wurden eine unmodifizierte und getaggte kAE1-VolllĂ€ngenversion erfolgreich in Hefe exprimiert. Darüber hinaus wurde die partielle Lokalisierung des Anionenaustauschers in der Plasmamembran durch Mikroskopietechniken und biochemische Assays validiert. Anschließend wurde die biologische ProteinaktivitĂ€t durch intrazellulĂ€re pH-Messungen und Chlorid-Aufnahmestudien nachgewiesen. ZusĂ€tzlich wurde eine Reihe von neuen dRTA-Mutanten in mIMCD3-Zellen charakterisiert, die als zellulĂ€res Modell den α-interkalierten Zellen am nĂ€chsten kommen. Damit eröffnet die vorliegende Dissertation neue Möglichkeiten, die kAE1-Physiologie und -Pathologie genauer untersuchen zu können

    Masked Supervised Learning for Semantic Segmentation

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    Self-attention is of vital importance in semantic segmentation as it enables modeling of long-range context, which translates into improved performance. We argue that it is equally important to model short-range context, especially to tackle cases where not only the regions of interest are small and ambiguous, but also when there exists an imbalance between the semantic classes. To this end, we propose Masked Supervised Learning (MaskSup), an effective single-stage learning paradigm that models both short- and long-range context, capturing the contextual relationships between pixels via random masking. Experimental results demonstrate the competitive performance of MaskSup against strong baselines in both binary and multi-class segmentation tasks on three standard benchmark datasets, particularly at handling ambiguous regions and retaining better segmentation of minority classes with no added inference cost. In addition to segmenting target regions even when large portions of the input are masked, MaskSup is also generic and can be easily integrated into a variety of semantic segmentation methods. We also show that the proposed method is computationally efficient, yielding an improved performance by 10\% on the mean intersection-over-union (mIoU) while requiring 3×3\times less learnable parameters

    Learning to recognize occluded and small objects with partial inputs

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    Recognizing multiple objects in an image is challenging due to occlusions, and becomes even more so when the objects are small. While promising, existing multi-label image recognition models do not explicitly learn context-based representations, and hence struggle to correctly recognize small and occluded objects. Intuitively, recognizing occluded objects requires knowledge of partial input, and hence context. Motivated by this intuition, we propose Masked Supervised Learning (MSL), a single-stage, model-agnostic learning paradigm for multi-label image recognition. The key idea is to learn context-based representations using a masked branch and to model label co-occurrence using label consistency. Experimental results demonstrate the simplicity, applicability and more importantly the competitive performance of MSL against previous state-of-the-art methods on standard multi-label image recognition benchmarks. In addition, we show that MSL is robust to random masking and demonstrate its effectiveness in recognizing non-masked objects. Code and pretrained models are available on GitHub

    Risk Management of Non-bank Home Ownership Financing

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    The Ministry of Public Works and Housing through General Directorate of Housing Financing (2016) estimated that housing demand by 2025 will reach more than 30 million units, so that this demand of new housing estimated will reach 1,2 million unit per year. This condition shows that the demand of houses is an important need for society. On the other hand, the amount of moslem in Indonesia per 2010, according to BPS, has reached 85%. Both of these conditions show that there is a demand of houses by applying Islamic values which one of them is by using istishna’ financing scheme. But, the implementation of Islamic housing in Indonesia does not have standardized system yet in general, so that it causes some risks that need to find out. Therefore, this research is meant to find out the risk management of non-bank-house ownership financing by Sabrina Azzura.     Keywords: Risk management, syariah housing, Sabrina Azzura, istishna’ financin

    Powder removal from Ti-6Al-4V cellular structures fabricated via electron beam melting

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    Direct metal fabrication systems like electron beam melting (EBM) and direct metal laser sintering (also called selective laser melting) are gaining popularity. One reason is the design and fabrication freedom that these technologies offer over traditional processes. One specific feature that is of interest is mesh or lattice structures that can be produced using these powder-bed systems. One issue with the EBM process is that the powder trapped within the structure during the fabrication process is sintered and can be hard to remove as the mesh density increases. This is usually not an issue for the laser-based systems since most of them work at a low temperature and the sintering of the powder is less of an issue. Within the scope of this project, a chemical etching process was evaluated for sintered powder removal using three different cellular structures with varying mesh densities. All meshes were fabricated via EBM using Ti6Al4V Footnote Information powder. The results are promising, but the larger the structures, the more difficult it is to completely remove the sintered powder without affecting the integrity of the mesh structure

    Analisis Komponen Volatil Dan Laju Alir Lava Pada Erupsi Gunung Semeru, Jawa Timur

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    Gunung Semeru merupakan salah satu gunung aktif di Indonesia dan telah mengalami Perubahan tipe erupsi sejak tahun 1967. Sehingga penting untuk dilakukan penelitian mengenai analisis erupsi berdasarkan komponen volatil dan penentuan laju alir lava Gunung Semeru dengan tujuan untuk memperkirakan mekanisme sifat erupsi pada masa sekarang dan untuk mengetahui potensi daerah berbahaya aliran lava G. Semeru bila terjadi letusan eksplosif.Analisis erupsi didasarkan pada parameter fisika terhadap analisis geokimia batuan sedangkan laju alir lava didasarkan pada kemiringan topografi yang dilaluinya. Hasil penelitian menunjukkan berkurangnya tekanan akan mengakibatkan lepasnya gas dari magma dengan cepat, Hal ini memicu terjadinya sifat hembusan. Daerah yang memiliki laju alir lava G. Semeru paling cepat adalah Desa Oro oro Ombo, Kecamatan Pronojiwo, Kabupaten Lumajang

    Top quark pair​production cross​section measurements with the ATLAS detector

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    Measurements of the inclusive and differential top­quark pair cross sections in proton­proton collisions at both 8 and 13 TeV with the ATLAS detector at the Large Hadron Collider are presented. The inclusive measurements reach high precision and are compared to the best available theoretical calculations. Differential measurements of the kinematic properties of the top quark production are also discussed. These measurements, including results using boosted tops, probe our understanding of top pair production in the TeV regime. The results, unfolded to particle and parton level, are compared to Monte Carlo generators implementing LO and NLO matrix elements matched with parton showers and NNLO QCD calculations

    Approximate Analytical Solutions of Space-Fractional Telegraph Equations by Sumudu Adomian Decomposition Method

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    The main goal in this work is to establish a new and efficient analytical scheme for space fractional telegraph equation (FTE) by means of fractional Sumudu decomposition method (SDM). The fractional SDM gives us an approximate convergent series solution. The stability of the analytical scheme is also studied. The approximate solutions obtained by SDM show that the approach is easy to implement and computationally very much attractive. Further, some numerical examples are presented to illustrate the accuracy and stability for linear and nonlinear cases