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Umbu (Spondias tuberosa Arruda, Anacardiaceae) is a fruit species native to the semi-arid region of Brazil and economically important for several regions. The objective of this study was to determine equations to estimate the leaflet area of S. tuberosa genotypes. A total of 1,000 leaflets was collected from four genotypes (250 leaflets of each genotype) of S. tuberosa. In each leaflet collected, the length, width, and leaflet area were measured, and the product between length and width was calculated. Linear, linear with intercept, power, and exponential regression models were used to fit the equations. The criteria for choosing the best equation were based on Pearson's correlation coefficients, Akaike's information criteria, Willmott's concordance indices, and root mean square error. The product-adjusted equations between length and width can be used to estimate the leaflet area of all S. tuberosa genotypes. The leaflet area of the species (pooled data) can be estimated accurately and quickly from equations obtained with the linear models without intercept (ŷ = 0.6911*LW) and power (ŷ = 0.7127*LW0.9888). [ABSTRACT FROM AUTHOR]

AbstractLectins that bind to HIV envelope glycoprotein can inhibit virus-cell fusion and be used for rational drug design. This paper presents the results of an in silicoapproach to improve affinity interaction between the cyanobacterial lectin microvirin and its ligand Manα(1-2)Man. Comparative modeling and molecular dynamics tools were used. Additionally, the alanine scanning webserver was used to study the importance of protein residues in the binding site and to guide mutant production. The model obtained presented two homologous domains designated as domains A and B, each consisting of a single strand with triple and antiparallel β-sheets of (β1-β3 and β6-β8). Disulfide bonds between the cysteines (Cys60-Cys80, Cys63-Cys78 and Cys8-Cys24) were also found. The highly conserved binding site, including residues Asn44, Ile45, Asp46, Gln54, Asn55, Glu58, Thr59, Gln81, Thr82 and Met83. The RMSD values of the di-mannose and the interaction site were very stable during the molecular dynamics. Calculations of the occupation time of the hydrogen bonds were made for the residues that showed interaction in the complex lectin and ligand. The residue that contributed most to the interaction with Manα(1-2)Man was Asn55. After validation, the model generated remained stable during the entire simulation. Despite its structural similarity with the template we used, our mutant (Thr82Arg) showed a higher affinity interaction with Manα(1-2)Man. Communicated by Ramaswamy H. Sarma

Introduction The Oxfordshire Community Stroke Project (OCSP) proposed a clinical classification for Stroke patients. This classification has proved helpful to predict the risk of neurological complications. However, the OCSP was initially based on findings on the neurological assesment, which can pose difficulties for classifying patients. We aimed to describe the development and the validation step of a computer-based algorithm based on the OCSP classification.Materials and methods A flow-chart was created which was reviewed by five board-certified vascular neurologists from which a computer-based algorithm (COMPACT) was developed. Neurology residents from 12 centers were invited to participate in a randomized trial to assess the effect of using COMPACT. They answered a 20-item questionnaire for classifying the vignettes according to the OCSP classification. Each correct answer has been attributed to 1-point for calculating the final score.Results Six-two participants agreed to participate and answered the questionnaire. Thirty-two were randomly allocated to use our algorithm, and thirty were allocated to adopt a list of symptoms alone. The group who adopted our algorithm had a median score of correct answers of 16.5[14.5, 17]/20 versus 15[13, 16]/20 points, p = 0.014. The use of our algorithm was associated with the overall rate of correct scores (p = 0.03).Discussion Our algorithm seemed a useful tool for any postgraduate year Neurology resident. A computer-based algorithm may save time and improve the accuracy to classify these patients.Conclusion An easy-to-use computer-based algorithm improved the accuracy of the OCSP classification, with the possible benefit of further improvement of the prediction of neurological complications and prognostication.

The influenza M2 proton channel is a major drug target, but unfortunately, the acquisition of resistance mutations greatly reduces the functional life span of a drug in influenza treatment. New M2 inhibitors that inhibit mutant M2 channels otherwise resistant to the early adamantine-based drugs have been reported, but it remains unclear whether and how easy resistance could arise to such inhibitors. We have combined a newly developed proton conduction assay with an established method for selection and screening, both Escherichia coli-based, to enable the study of M2 function and inhibition. Combining this platform with two groups of structurally different M2 inhibitors allowed us to isolate drug resistant M2 channels from a mutant library. Two groups of M2 variants emerged from this analysis. A first group appeared almost unaffected by the inhibitor, M_089 (N13I, I35L, and F47L) and M_272 (G16C and D44H), and the single-substitution variants derived from these (I35L, L43P, D44H, and L46P). Functionally, these resemble the known drug resistant M2 channels V27A, S31N, and swine flu. In addition, a second group of tested M2 variants were all still inhibited by drugs but to a lesser extent than wild type M2. Molecular dynamics simulations aided in distinguishing the two groups where drug binding to the wild type and the less resistant M2 group showed a stable positioning of the ligand in the canonical binding pose, as opposed to the drug resistant group in which the ligand rapidly dissociated from the complex during the simulations.

The M2 protein is an important target for drugs in the fight against the influenza virus. Because of the emergence of resistance against antivirals directed toward the M2 proton channel, the search for new drugs against resistant M2 variants is of high importance. Robust and sensitive assays for testing potential drug compounds on different M2 variants are valuable tools in this search for new inhibitors. In this work, we describe a fluorescence sensor-based assay, which we termed “pHlux”, that measures proton conduction through M2 when synthesized from an expression vector in Escherichia coli. The assay was compared to a previously established bacterial potassium ion transport complementation assay, and the results were compared to simulations obtained from analysis of a computational model of M2 and its interaction with inhibitor molecules. The inhibition of M2 was measured for five different inhibitors, including Rimantadine, Amantadine, and spiro type compounds, and the drug resistance of the M2 mutant variants (swine flu, V27A, and S31N) was confirmed. We demonstrate that the pHlux assay is robust and highly sensitive and shows potential for high-throughput screening.

This study reports on the microstructure of Portland cement pastes with nanosilica (NS) and amino-functionalized nanosilica (NSF). For this, NSF dispersion was prepared in a two-phase reaction system, consisting of an aqueous dispersion with dichloromethane, using 3-aminopropyltriethoxysilane (APTES):NS molar ratio 1:28.62. Cement pastes were analyzed in the fresh state by consistency and in the hardness state by compressive strength, conduction calorimetry, X-ray diffraction (XRD), thermal analysis (TGA), infrared spectroscopy (FTIR) and mercury intrusion porosimetry (MIP). It was verified that the functionalized nanoparticles affected the hydration kinetic properties, indicating the extension of the induction period. Through microstructural analysis, it was observed that NSF increased the amount of the main mineralogical phases generated during Portland cement hydration or the pozzolanic reaction. Therefore, the NSF improves the Portland cement hydration and contributes to the densification of the microstructure of the cement pastes at 28 days.

Perioperative Goal-Directed Therapy (PGDT) has significantly showed to decrease complications and risk of death in high-risk patients according to numerous meta-analyses. The main goal of PGDT is to individualize the therapy with fluids, inotropes, and vasopressors, during and after surgery, according to patients’ needs in order to prevent organic dysfunction development. In this opinion paper we aimed to focus a discussion on possible alternatives to invasive hemodynamic monitoring in low resource settings.

This paper shows the results of a sensing system for an autonomous mobile robot. The sensing system is based on the paraconsistent neural network. The type of artificial neural network used in this work is based on the paraconsistent evidential logic (Eτ). The objective of the sensing system is to inform the other robot components the obstacle position. The reached results have been satisfactory.

Biological processes are regulated mainly by the binding of small molecules into cavities distributed throughout the biomolecular structure. Computational tools to detect these cavities have an essential role in rational drug design. With the exponential availability of high-order 3D atomic structures and large sets of atomic models, the tools must balance accuracy and speed. In this sense, we developed parKVFinder, a parallelized software for geometry-based cavity detection. Here, we described its functionalities and presented its easy-to-use PyMOL plugin and command-line interface. Finally, we demonstrated parKVFinder by identifying an important HIV-1 protease cavity and compared it with other geometry-based programs.