Hospital-acquired invasive pulmonary aspergillosis in patients with hepatic failure

<p>Abstract</p> <p>Background</p> <p>Invasive pulmonary aspergillosis (IPA) is a rapid, progressive, fatal disease that occurs mostly in immunocompromised patients. Patients with severe liver disease are at a heightened risk for infections. Little is known about the clinical presentation including predisposing factors and treatment of IPA in patients with hepatic failure.</p> <p>Methods</p> <p>Medical records of patients with hepatic failure between November 2005 and February 2007 were reviewed for lung infection. Nine medical records of definitive diagnosis of IPA and three of probable IPA were identified.</p> <p>Results</p> <p>The main predisposing factors were found to be prolonged antibiotic therapy and steroid exposure. Clinical signs and radiological findings were non-specific and atypical. Timely use of caspofungin was found to reduce the mortality due to the disease.</p> <p>Conclusion</p> <p>A high index of suspicion is required for early IPA diagnosis in patients with hepatic failure.</p

Gene ontology based transfer learning for protein subcellular localization

<p>Abstract</p> <p>Background</p> <p>Prediction of protein subcellular localization generally involves many complex factors, and using only one or two aspects of data information may not tell the true story. For this reason, some recent predictive models are deliberately designed to integrate multiple heterogeneous data sources for exploiting multi-aspect protein feature information. Gene ontology, hereinafter referred to as <it>GO</it>, uses a controlled vocabulary to depict biological molecules or gene products in terms of biological process, molecular function and cellular component. With the rapid expansion of annotated protein sequences, gene ontology has become a general protein feature that can be used to construct predictive models in computational biology. Existing models generally either concatenated the <it>GO </it>terms into a flat binary vector or applied majority-vote based ensemble learning for protein subcellular localization, both of which can not estimate the individual discriminative abilities of the three aspects of gene ontology.</p> <p>Results</p> <p>In this paper, we propose a Gene Ontology Based Transfer Learning Model (<it>GO-TLM</it>) for large-scale protein subcellular localization. The model transfers the signature-based homologous <it>GO </it>terms to the target proteins, and further constructs a reliable learning system to reduce the adverse affect of the potential false <it>GO </it>terms that are resulted from evolutionary divergence. We derive three <it>GO </it>kernels from the three aspects of gene ontology to measure the <it>GO </it>similarity of two proteins, and derive two other spectrum kernels to measure the similarity of two protein sequences. We use simple non-parametric cross validation to explicitly weigh the discriminative abilities of the five kernels, such that the time & space computational complexities are greatly reduced when compared to the complicated semi-definite programming and semi-indefinite linear programming. The five kernels are then linearly merged into one single kernel for protein subcellular localization. We evaluate <it>GO-TLM </it>performance against three baseline models: <it>MultiLoc, MultiLoc-GO </it>and <it>Euk-mPLoc </it>on the benchmark datasets the baseline models adopted. 5-fold cross validation experiments show that <it>GO-TLM </it>achieves substantial accuracy improvement against the baseline models: 80.38% against model <it>Euk-mPLoc </it>67.40% with <it>12.98% </it>substantial increase; 96.65% and 96.27% against model <it>MultiLoc-GO </it>89.60% and 89.60%, with <it>7.05% </it>and <it>6.67% </it>accuracy increase on dataset <it>MultiLoc plant </it>and dataset <it>MultiLoc animal</it>, respectively; 97.14%, 95.90% and 96.85% against model <it>MultiLoc-GO </it>83.70%, 90.10% and 85.70%, with accuracy increase <it>13.44%</it>, <it>5.8% </it>and <it>11.15% </it>on dataset <it>BaCelLoc plant</it>, dataset <it>BaCelLoc fungi </it>and dataset <it>BaCelLoc animal </it>respectively. For <it>BaCelLoc </it>independent sets, <it>GO-TLM </it>achieves 81.25%, 80.45% and 79.46% on dataset <it>BaCelLoc plant holdout</it>, dataset <it>BaCelLoc plant holdout </it>and dataset <it>BaCelLoc animal holdout</it>, respectively, as compared against baseline model <it>MultiLoc-GO </it>76%, 60.00% and 73.00%, with accuracy increase <it>5.25%</it>, <it>20.45% </it>and <it>6.46%</it>, respectively.</p> <p>Conclusions</p> <p>Since direct homology-based <it>GO </it>term transfer may be prone to introducing noise and outliers to the target protein, we design an explicitly weighted kernel learning system (called Gene Ontology Based Transfer Learning Model, <it>GO-TLM</it>) to transfer to the target protein the known knowledge about related homologous proteins, which can reduce the risk of outliers and share knowledge between homologous proteins, and thus achieve better predictive performance for protein subcellular localization. Cross validation and independent test experimental results show that the homology-based <it>GO </it>term transfer and explicitly weighing the <it>GO </it>kernels substantially improve the prediction performance.</p

Application of functionalized nanofluid in thermosyphon

A water-based functionalized nanofluid was made by surface functionalizing the ordinary silica nanoparticles. The functionalized nanofluid can keep long-term stability. and no sedimentation was observed. The functionalized nanofluid as the working fluid is applied in a thermosyphon to understand the effect of this special nanofluid on the thermal performance of the thermosyphon. The experiment was carried out under steady operating pressures. The same work was also explored for traditional nanofluid (consisting of water and the same silica nanoparticles without functionalization) for comparison. Results indicate that a porous deposition layer exists on the heated surface of the evaporator during the operating process using traditional nanofluid; however, no coating layer exists for functionalized nanofluid. Functionalized nanofluid can enhance the evaporating heat transfer coefficient, while it has generally no effect on the maximum heat flux. Traditional nanofluid deteriorates the evaporating heat transfer coefficient but enhances the maximum heat flux. The existence of the deposition layer affects mainly the thermal performance, and no meaningful nanofluid effect is found in the present study

Natural disasters in the history of the eastern Turk empire

This article analyzes the effect of climate extremes on the historical processes that took place (AD 536, 581, 601, 626 and 679) in the Eastern Turk Empire (AD 534–745) in Inner Asia. Climate extremes are sharp, strong and sometimes protracted periods of cooling and drought caused by volcanic eruptions that in this case resulted in a negative effect on the economy of a nomadic society and were often accompanied by famine and illness. In fact, many of these natural catastrophes coincided with the Black Death pandemics among the Eastern Turks and the Chinese living in the north of China. The Turk Empire can be split into several chronological periods during which significant events that led to changes in the course of history of the nomadic state took place: AD 534–545—the rise of the Turk Empire; AD 581–583—the division of the Turk Empire into theWestern and the Eastern Empires; AD 601–603—the rise of Qimin Qaghan; AD 627–630—the Eastern Turks are conquered by China; AD 679–687—the second rise of the Eastern Turk Empire. The research shows that there is clearly-discernable interplay between important historical events and climate extremes in the history of the Turk Empire. This interplay has led us to the conclusion that the climatic factor did have an impact on the historical processes that took place in the eastern part of Inner Asia, especially on the territories with a nomadic economy. © The Author(s) 2019

Atomically dispersed nickel-nitrogen-sulfur species anchored on porous carbon nanosheets for efficient water oxidation

Developing low-cost electrocatalysts to replace precious Ir-based materials is key for oxygen evolution reaction (OER). Here, we report atomically dispersed nickel coordinated with nitrogen and sulfur species in porous carbon nanosheets as an electrocatalyst exhibiting excellent activity and durability for OER with a low overpotential of 1.51 V at 10 mA cm(-2) and a small Tafel slope of 45 mV dec(-1) in alkaline media. Such electrocatalyst represents the best among all reported transition metal- and/or heteroatom-doped carbon electrocatalysts and is even superior to benchmark Ir/C. Theoretical and experimental results demonstrate that the well-dispersed molecular S vertical bar NiNx species act as active sites for catalyzing OER. The atomic structure of S vertical bar NiNx centers in the carbon matrix is clearly disclosed by aberration-corrected scanning transmission electron microscopy and synchrotron radiation X-ray absorption spectroscopy together with computational simulations. An integrated photoanode of nanocarbon on a Fe2O3 nanosheet array enables highly active solar-driven oxygen production

A Multiwell Platform for Studying Stiffness-Dependent Cell Biology

Adherent cells are typically cultured on rigid substrates that are orders of magnitude stiffer than their tissue of origin. Here, we describe a method to rapidly fabricate 96 and 384 well platforms for routine screening of cells in tissue-relevant stiffness contexts. Briefly, polyacrylamide (PA) hydrogels are cast in glass-bottom plates, functionalized with collagen, and sterilized for cell culture. The Young's modulus of each substrate can be specified from 0.3 to 55 kPa, with collagen surface density held constant over the stiffness range. Using automated fluorescence microscopy, we captured the morphological variations of 7 cell types cultured across a physiological range of stiffness within a 384 well plate. We performed assays of cell number, proliferation, and apoptosis in 96 wells and resolved distinct profiles of cell growth as a function of stiffness among primary and immortalized cell lines. We found that the stiffness-dependent growth of normal human lung fibroblasts is largely invariant with collagen density, and that differences in their accumulation are amplified by increasing serum concentration. Further, we performed a screen of 18 bioactive small molecules and identified compounds with enhanced or reduced effects on soft versus rigid substrates, including blebbistatin, which abolished the suppression of lung fibroblast growth at 1 kPa. The ability to deploy PA gels in multiwell plates for high throughput analysis of cells in tissue-relevant environments opens new opportunities for the discovery of cellular responses that operate in specific stiffness regimes

Mechanically assisted electrochemical degradation of alumina-TiC composites

Alumina-TiC composite material is a tough ceramic composite with excellent hardness, wear resistance and oxidation resistance in dry and high-temperature conditions. In aqueous conditions, however, it is likely to be electrochemically active facilitating charge transfer processes due to the conductive nature of TiC. For application as an orthopedic biomaterial, it is crucial to assess the electrochemical behavior of this composite, especially under a combined mechanical and electrochemical environment. In this study, we examined the mechanically assisted electrochemical performance of alumina-TiC composite in an aqueous environment. The spontaneous electrochemical response to brushing abrasion was measured. Changes in the magnitude of electrochemical current with abrasion test conditions and possible causal relationship to the alteration in surface morphology were examined. Results showed that the alumina matrix underwent abrasive wear with evidence of microploughing and grain boundary damage. Chemical analysis revealed TiO2 formation in the abraded region, indicating oxidation of the conductive TiC domain. Furthermore, wear debris from alumina abrasion appeared to affect reaction kinetics at the composite-electrolyte interface. From this work, we established that the composite undergoes abrasion assisted electrochemical degradation even in gentle abrasive conditions and the severity of degradation is related to temperature and conditions of test environment

Identification of a Phytase Gene in Barley (Hordeum vulgare L.)

Background: Endogenous phytase plays a crucial role in phytate degradation and is thus closely related to nutrient efficiency in barley products. The understanding of genetic information of phytase in barley can provide a useful tool for breeding new barley varieties with high phytase activity. Methodology/Principal Findings: Quantitative trait loci (QTL) analysis for phytase activity was conducted using a doubled haploid population. Phytase protein was purified and identified by the LC-ESI MS/MS Shotgun method. Purple acid phosphatase (PAP) gene was sequenced and the position was compared with the QTL controlling phytase activity. A major QTL for phytase activity was mapped to chromosome 5 H in barley. The gene controlling phytase activity in the region was named as mqPhy. The gene HvPAP a was mapped to the same position as mqPhy, supporting the colinearity between HvPAP a and mqPhy. Conclusions/Significance: It is the first report on QTLs for phytase activity and the results showed that HvPAP a, which shares a same position with the QTL, is a major phytase gene in barley grains

Quantum coherent control of a hybrid superconducting circuit made with graphene-based van der Waals heterostructures

Quantum coherence and control is foundational to the science and engineering of quantum systems. In van der Waals (vdW) materials, the collective coherent behavior of carriers has been probed successfully by transport measurements. However, temporal coherence and control, as exemplified by manipulating a single quantum degree of freedom, remains to be verified. Here we demonstrate such coherence and control of a superconducting circuit incorporating graphene-based Josephson junctions. Furthermore, we show that this device can be operated as a voltage-tunable transmon qubit, whose spectrum reflects the electronic properties of massless Dirac fermions traveling ballistically. In addition to the potential for advancing extensible quantum computing technology, our results represent a new approach to studying vdW materials using microwave photons in coherent quantum circuits