Sequence clustering strategies improve remote homology recognitions while reducing search times

Sequence databases are rapidly growing, thereby increasing thecoverage of protein sequence space, but this coverage is unevenbecause most sequencing efforts have concentrated on a smallnumber of organisms. The resulting granularity of sequence spacecreates many problems for profile-based sequence comparisonprograms. In this paper, we suggest several strategies thataddress these problems, and at the same time speed up the searchesfor homologous proteins and improve the ability of profile methodsto recognize distant homologies. One of our strategies combinesdatabase clustering, which removes highly redundant sequence,and a two-step PSI-BLAST (PDB-BLAST), which separates sequencespaces of profile composition and space of homology searching.The combination of these strategies improves distant homologyrecognitions by more than 100%, while using only 10% of theCPU time of the standard PSI-BLAST search. Another method, intermediateprofile searches, allows for the exploration of additional searchdirections that are normally dominated by large protein sub-familieswithin very diverse families. All methods are evaluated witha large fold-recognition benchmark.     

Na+ and/or Cl− Toxicities Determine Salt Sensitivity in Soybean (Glycine max (L.) Merr.), Mungbean (Vigna radiata (L.) R. Wilczek), Cowpea (Vigna unguiculata (L.) Walp.), and Common Bean (Phaseolus vulgaris L.)

Grain legumes are important crops, but they are salt sensitive. This research dissected the responses of four (sub)tropical grain legumes to ionic components (Na⁺ and/or Cl⁻) of salt stress. Soybean, mungbean, cowpea, and common bean were subjected to NaCl, Na⁺ salts (without Cl⁻), Cl⁻ salts (without Na⁺), and a “high cation” negative control for 57 days. Growth, leaf gas exchange, and tissue ion concentrations were assessed at different growing stages. For soybean, NaCl and Na⁺ salts impaired seed dry mass (30% of control), more so than Cl⁻ salts (60% of control). All treatments impaired mungbean growth, with NaCl and Cl⁻ salt treatments affecting seed dry mass the most (2% of control). For cowpea, NaCl had the greatest adverse impact on seed dry mass (20% of control), while Na⁺ salts and Cl⁻ salts had similar intermediate effects (~45% of control). For common bean, NaCl had the greatest adverse effect on seed dry mass (4% of control), while Na⁺ salts and Cl⁻ salts impaired seed dry mass to a lesser extent (~45% of control). NaCl and Na⁺ salts (without Cl⁻) affected the photosynthesis (P_n) of soybean more than Cl⁻ salts (without Na⁺) (50% of control), while the reverse was true for mungbean. Na⁺ salts (without Cl⁻), Cl⁻ salts (without Na⁺), and NaCl had similar adverse effects on P_n of cowpea and common bean (~70% of control). In conclusion, salt sensitivity is predominantly determined by Na⁺ toxicity in soybean, Cl⁻ toxicity in mungbean, and both Na⁺ and Cl⁻ toxicity in cowpea and common bean.     

Toward Better Understanding of Task Difficulty during Physicians’ Interaction with Electronic Health Record System (EHRs)

ABSTRACT

The goal of this study was to assess the relationship of task difficulty and mental effort with performance during physicians’ interaction with electronic health records (EHRs). A total of 38 physicians were asked to identify abnormal results and take follow-up action to “close the loop” on care delivery. Task difficulty was quantified via task-flow strategies and computer mouse-click patterns. Mental effort was quantified using eye movements based on changes in pupillary dilations (task evoked pupillary response or TEPR) and blink rate. Performance was quantified based on commission errors (error vs. no-error). Results indicated that physicians had different task-flow strategies; however, with improved awareness of the patient status, they exhibited an optimal task-flow strategy. Overall, performance was related to task-flow strategies, computer mouse-click patterns, and blink rate, indicating that physicians had lower task-difficulty and experienced lower mental effort with improved awareness of patient follow-up status. This is an important finding demonstrating that task-flows are a dominant predictor of physician performance when comparing between EHR designs. On the contrary, mouse-click patterns and blink rate are both useful predictors of physician performance when assessment was done within an EHR.     

Identification of tubulin drug binding sites and prediction of relative differences in binding affinities to tubulin isotypes using digital signal processing

Microtubules are involved in numerous cellular processes including chromosome segregation during mitosis and, as a result, their constituent protein, tubulin, has become a successful target of several chemotherapeutic drugs. In general, these drugs bind indiscriminately to tubulin within both cancerous and healthy cells, resulting in unwanted side effects. However, differences between beta-tubulin isotypes expressed in a wide range of cell types may aid in the development of anti-tubulin drugs having increased specificity for only certain types of cells. Here, we describe a digital signal processing (DSP) method that is capable of predicting hot spots for the tubulin family of proteins as well as determining relative differences in binding affinities to these hot spots based only on the primary sequence of 10 human tubulin isotypes. Due to the fact that several drug binding sites have already been characterized within beta-tubulin, we are able to correlate hot spots with the binding sites for known chemotherapy drugs. We have also verified the accuracy of this method using the correlation between the binding affinities of characterized drugs and the tubulin isotypes. Additionally, the DSP method enables the rapid estimation of relative differences in binding affinities within the binding sites of tubulin isotypes that are yet to be experimentally determined.     

Eucalyptol is an Attractant of the Redbay Ambrosia Beetle,Xyleborus Glabratus

The redbay ambrosia beetle, Xyleborus glabratus, is an invasive wood-boring beetle that has become established in the southeastern United States. The beetle transmits the causal pathogen of lethal laurel wilt to susceptible host trees, which include redbay, an important forest community species, and avocado, a valuable food crop. By examining odors of redbay wood, we developed an artificial lure that captured X. glabratus in redbay forests. Eucalyptol was a critical component of the blend for beetle attraction, and eucalyptol alone in large quantities attracted X. glabratus. Furthermore, eucalyptol stimulated boring by X. glabratus into paper arenas. The results suggest that eucalyptol contributes to host selection behavior of X. glabratus and may be useful for management of this pathogen vector.     

Effect of Ti,Nb, and Ti + Nb Coatings on the Bond Strength-Structure Relationship in Al/Al<Subscript>2</Subscript>O<Subscript>3</Subscript> Joints

There is a growing interest in metal-ceramic bonding for wide range of applications in electronic devices and high technology industry for fabrication of metal matrix composites and bonding of ceramic components to metals. The object of the work was to study the effect of Ti, Nb, and Ti + Nb thin films deposited by PVD method on alumina substrates on structure and bond strength properties of Al/Al₂O₃ joints. The joints were fabricated using the results of a wetting experiment and the sessile drop method at a temperature of 1223 K in a vacuum of 0.2 MPa for 30 min of contact. The structure of the metal/ceramic interface was investigated using scanning electron microscopy. The elemental distribution at the metal-ceramic interface was analyzed using energy dispersive x-ray spectroscopy. Transmission electron microscopy was also used to investigate some aspects of the metal/ceramic interface. The bond strength properties of joints were measured using shear test. The shear strength results demonstrated significant improvement of shear strength of Al/Al₂O₃ joints due to the application of Ti + Nb thin film on alumina substrate. Microstructural investigations of the interface indicated that Al/coating/Al₂O₃ couples have diffusion transition interface which influences the strengthening of these joints. A conclusion could be drawn that the presence of thin film layers changes the character of interaction and leads to the formation of new reaction products in the bonding layer.     

Toughening of syndiotactic polypropylene with chalk

We hypothesized that polymer crystal anisotropy is advantageous for toughening of polymer composites involving easy slip network of oriented crystalline layers around filler particles. To this end, composites of syndiotactic polypropylene (sPP) with high concentration of submicrometer calcium carbonate particles were prepared and examined because usual sPP crystals exhibit high packing anisotropy. The specific orientation of sPP lamellae around chalk grains was found, which is supposed to facilitate the plastic deformation of polymer matrices. The compression molded bars of the composite exhibited markedly higher Izod impact strength than those of neat sPP. Toughening was even enhanced in the injection molded composite, for which 4.5‐fold increase in the impact strength was achieved. Injection‐induced orientation of the disordered form I sPP crystals was enhanced in the composite. The injection molded tensile specimens exhibited also a good drawability. Debonding at chalk–sPP interface occurred both during the impact and tensile tests facilitating the plastic deformation of sPP matrix. Chalk did not have any significant influence on the thermal properties of the composites but it affected the rheological behavior, increasing the loss and storage moduli, and the viscosity. Highly filled sPP composite exhibited solid‐like behavior in a molten state with the storage modulus exceeding the loss modulus in the entire frequency range. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43651.     

Label-Free Quantitative Proteomics Reveals Differences in Molecular Mechanism of Atherosclerosis Related and Non-Related to Chronic Kidney Disease

The major cause of mortality in patients with chronic kidney disease (CKD) is atherosclerosis related to traditional and non-traditional risk factors. However, the understanding of the molecular specificity that distinguishes the risk factors for classical cardiovascular disease (CVD) and CKD-related atherosclerosis (CKD-A) is far from complete. In this study we investigated the disease-related differences in the proteomes of patients with atherosclerosis related and non-related to CKD. Plasma collected from patients in various stages of CKD, CVD patients without symptoms of kidney dysfunction, and healthy volunteers (HVs), were analyzed by a coupled label-free and mass spectrometry approach. Dysregulated proteins were confirmed by an enzyme-linked immunosorbent assay (ELISA). All proteomic data were correlated with kidney disease development and were subjected to bioinformatics analysis. One hundred sixty-two differentially expressed proteins were identified. By directly comparing the plasma proteomes from HVs, CKD, and CVD patients in one study, we demonstrated that proteins involved in inflammation, blood coagulation, oxidative stress, vascular damage, and calcification process exhibited greater alterations in patients with atherosclerosis related with CKD. These data indicate that the above nontraditional risk factors are strongly specific for CKD-A and appear to be less essential for the development of “classical” CVD.     

Measurement of mechanical properties in a 316L stainless steel welded joint

The aim of this study was to measure the mechanical properties of weld material taken from a single weld bead laid down on a 316L steel plate. Due to the low available volume of weld material, microsamples with a total length of 5.5 mm were used. The Digital Image Correlation method (DIC), which enables measurement of mechanical properties of very small samples, was employed for the strain measurements in a uniaxial tensile test. Samples were cut out from three different zones of the specimen: plate, weld, and the heat affected zone. The material from heat affected zone showed the highest value of the Ultimate Tensile Strength (UTS) (580 ± 7 MPa) and yield strength (339 ± 6 MPa). Plate material had lower UTS (559 ± 5 MPa) and yield strength (304 ± 7 MPa). The lowest values of UTS (526 ± 6 MPa) and yield strength (291 ± 8 MPa) have been revealed for the weld. The values obtained for UTS, yield strength and elongation to failure for the plate material were compared with data obtained using standard test specimens. No significant differences between results obtained for the microsamples and standard samples have been found.     

Highly scalable and robust rule learner: performance evaluation and comparison.

Business intelligence and bioinformatics applications increasingly require the mining of datasets consisting of millions of data points, or crafting real-time enterprise-level decision support systems for large corporations and drug companies. In all cases, there needs to be an underlying data mining system, and this mining system must be highly scalable. To this end, we describe a new rule learner called DataSqueezer. The learner belongs to the family of inductive supervised rule extraction algorithms. DataSqueezer is a simple, greedy, rule builder that generates a set of production rules from labeled input data. In spite of its relative simplicity, DataSqueezer is a very effective learner. The rules generated by the algorithm are compact, comprehensible, and have accuracy comparable to rules generated by other state-of-the-art rule extraction algorithms. The main advantages of DataSqueezer are very high efficiency, and missing data resistance. DataSqueezer exhibits log-linear asymptotic complexity with the number of training examples, and it is faster than other state-of-the-art rule learners. The learner is also robust to large quantities of missing data, as verified by extensive experimental comparison with the other learners. DataSqueezer is thus well suited to modern data mining and business intelligence tasks, which commonly involve huge datasets with a large fraction of missing data.