Prediction and optimization of hardened properties of concrete prepared with granite dust and scrapped copper wire using response surface methodology.

Urban growth in the developing world has prompted researchers to seek alternatives to fine aggregate due to the severe environmental impact of extensive natural sand depletion. On top of that, the accumulation of non-biodegradable dumps, solid trash such as scrapped copper wire (SCW), and industrial remnants like granite dust (GD) have reached alarming levels. Therefore, incorporating these two waste materials in concrete offers a potentially sustainable solution. The study aims at substituting natural fine aggregate with GD as well as incorporating SCW for predicting and optimizing the compressive and splitting tensile strength of concrete using response surface methodology (RSM). Two independent variables, the volumetric percentages of GD (10 %, 20 %, and 30 %) and SCW (0.1 %, 0.3 %, and 0.5 %) in a concrete mix ratio of 1:1.5:3, were utilized to create probabilistic models for compressive and splitting tensile strength at 7 and 28 days. The experimental design employed central composite design (CCD) of RSM and the results of both ANOVA and regression analysis in terms of several statistical functions demonstrated a strong correlation between the predicted values of the responses and the actual experimental results. The developed models were validated by conducting experiments using optimized proportions of GD (23.32 %) and SCW (0.37 %). Finally, the strengths of the optimum content mix yielding 25.12 MPa and 3.266 MPa, respectively for compressive and splitting tensile at 28 days ensure the efficiency of the models due to the substantial similarity between experimental and predicted values. Therefore, integrating GD and SCW for higher-strength concrete in mass production can be a cost-effective alternative, fostering increased recycling of waste and supporting sustainable growth in building construction.

Novel multi-objective affinity approach allows to identify pH-specific µ-opioid receptor agonists.

Opioids are essential pharmaceuticals due to their analgesic properties, however, lethal side effects, addiction, and opioid tolerance are extremely challenging. The development of novel molecules targeting the [Formula: see text]-opioid receptor (MOR) in inflamed, but not in healthy tissue, could significantly reduce these unwanted effects. Finding such novel molecules can be achieved by maximizing the binding affinity to the MOR at acidic pH while minimizing it at neutral pH, thus combining two conflicting objectives. Here, this multi-objective optimal affinity approach is presented, together with a virtual drug discovery pipeline for its practical implementation. When applied to finding pH-specific drug candidates, it combines protonation state-dependent structure and ligand preparation with high-throughput virtual screening. We employ this pipeline to characterize a set of MOR agonists identifying a morphine-like opioid derivative with higher predicted binding affinities to the MOR at low pH compared to neutral pH. Our results also confirm existing experimental evidence that NFEPP, a previously described fentanyl derivative with reduced side effects, and recently reported [Formula: see text]-fluorofentanyls and -morphines show an increased specificity for the MOR at acidic pH when compared to fentanyl and morphine. We further applied our approach to screen a >50K ligand library identifying novel molecules with pH-specific predicted binding affinities to the MOR. The presented differential docking pipeline can be applied to perform multi-objective affinity optimization to identify safer and more specific drug candidates at large scale.

Prediction and optimization of properties of concrete containing crushed stone dust and nylon fiber using response surface methodology.

Over-extraction of aggregates from natural sources with rapid urbanization as well as massive waste generation in construction industry have imposed the need to utilize waste material as concrete constituent. Crushed Stone Dust (CSD) is such a supplementary material that can be utilized for the production of sustainable concrete. This study attempts to predict and optimize fresh and hardened properties of concrete utilizing CSD as a partial replacement of natural fine aggregate and Nylon Fiber (NF) as fiber reinforcement using Response Surface Methodology (RSM). A three-level factorial design of Box-Behnken was incorporated to investigate the effect of CSD, NF and W/C as three independent variables on compressive strength, splitting tensile strength, fresh density and workability of concrete as desired responses. All the developed probabilistic models were found to be significant in predicting the responses at 95% confidence level. Regression analysis in terms of correlation coefficient, coefficient of determination, coefficient of variation, adequate precision, chi-square, mean square error, root mean square error, and mean absolute error also indicated the accuracy and functionality of the developed models. The results reveal that both compressive and splitting tensile strength increase with increased NF content, but the rise in CSD percentages beyond a certain level has negative impact on strength of concrete. However, fresh density and workability of concrete show a declining trend with rise in both CSD and NF levels. From multi-objective optimization, 20% CSD, 0.75% NF and W/C of 0.49 have been found to be the optimum proportions for concrete mixture with a desirability of 0.915. Finally, an experimental validation was carried out with optimum mixture contents and relative error between the experimental and predicted optimized values was observed to be less than 5%.

Modelling altered signalling of G-protein coupled receptors in inflamed environment to advance drug design.

We previously reported the successful design, synthesis and testing of the prototype opioid painkiller NFEPP that does not elicit adverse side effects. The design process of NFEPP was based on mathematical modelling of extracellular interactions between G-protein coupled receptors (GPCRs) and ligands, recognizing that GPCRs function differently under pathological versus healthy conditions. We now present an additional and novel stochastic model of GPCR function that includes intracellular dissociation of G-protein subunits and modulation of plasma membrane calcium channels and their dependence on parameters of inflamed and healthy tissue (pH, radicals). The model is validated against in vitro experimental data for the ligands NFEPP and fentanyl at different pH values and radical concentrations. We observe markedly reduced binding affinity and calcium channel inhibition for NFEPP at normal pH compared to lower pH, in contrast to the effect of fentanyl. For increasing radical concentrations, we find enhanced constitutive G-protein activation but reduced ligand binding affinity. Assessing the different effects, the results suggest that, compared to radicals, low pH is a more important determinant of overall GPCR function in an inflamed environment. Future drug design efforts should take this into account.

Predicting the strength of concrete made with stone dust and nylon fiber using artificial neural network.

Excessive demand of concrete is causing depletion of natural sand resources. Especially, the extraction of river sand negatively affects its surrounding environment. A sustainable solution to this problem can be the proper utilization of waste materials and by-products like stone dust (SD) as fine aggregate replacement in concrete. The recycling of stone dust as a construction material lessens the use of natural resources and helps to solve landfill scarcity as well as environmental problems. Addition of nylon fiber (NF) as fiber reinforcement can also attribute to enhance the properties of concrete. This research aims at utilizing SD as fine aggregate along with NF, and assessing the compressive strength and splitting tensile strength of concrete. Although the individual effects of incorporating stone dust and nylon fiber in concrete have been investigated in previous researches, their combined effects, as well as effects of water cement (WC) ratio on concrete strength, have not been studied yet. In this study, volumetric percentages of stone dust (20%-50%) and nylon fiber (0.25%-0.75%) and three different water cement ratio (0.45, 0.50 and 0.55) have been considered as three independent variables to develop probabilistic models for compressive strength and splitting tensile strength of concrete using artificial neural network (ANN). The values of coefficient of determination (R2) and other statistical parameters of the developed probabilistic models indicate the accuracy of the models to predict the concrete strength. In terms of compressive strength at early age, the optimal percentages of SD and NF have been found as 20% and 0.25%, respectively. However, the strength gradually drops as water cement ratio elevates from 0.45 to 0.55. The reduction of the splitting tensile strength has been observed for increasing SD from 20% to 50%, whereas, strength increases for rising NF and WC up to mid-level.

Secondary Structure Transitions for a Family of Amyloidogenic, Antimicrobial Uperin 3 Peptides in Contact with Sodium Dodecyl Sulfate.

Secondary structure changes are an inherent part of antimicrobial (AMP) and amyloidogenic peptide activity, especially in close proximity to membranes, and impact the peptides' function and dysfunction roles. The formation, and stability of α-helical components are regarded as essential 'intermediates' for both these functions. To illuminate the conformational transitions leading to amyloid formation we use short cationic AMPs, from an Australian toadlet, Uperoleia mjobergii, (Uperin 3 family, U3) and assess the impact on secondary structural elements in the presence of a membrane mimetic surfactant, sodium dodecyl sulfate (SDS). Specifically, Uperin 3.x, where x=4, 5, 6 wild-type peptides and position seven variants for each, R7A or K7A, were investigated using a combination of experimental and simulation approaches. In water, U3 peptides remain largely unstructured as random coils, with the addition of salts initiating structural transitions leading to assembly towards amyloid. Solution NMR data show that an unstructured U3.5 wt peptide transitions in the presence of SDS to a well-defined α-helical structure that spans nearly the entire sequence. Circular dichroism (CD) and ThT fluorescence studies show that all six U3 peptides aggregate in solution, albeit with vastly varying rates, and a dynamic equilibrium between soluble aggregates rich in either α-helices or ß-sheets may exist in solution. However, the addition of SDS leads to a rapid disaggregation for all peptides and stabilisation of predominantly α-helical content in all the U3 peptides. Molecular dynamics (MD) simulations show that the adsorption of U3.5 wt/R7A peptides onto the SDS micelle is driven by Coulombic attraction between peptide cationic residues and the negatively charged sulfate head-groups on SDS. Simulating the interactions of various kinds of ß-sheet dimers (of both U3.5 wt and its variant U3.5 R7A) with SDS micelles confirmed ß-sheet content decreases in the dimers after their attachment to the SDS micelle. Adsorbed peptides interact favourably with the hydrophobic core of the micelle, promoting intramolecular hydrogen bonds leading to stabilisation of the α-helical structure in peptides, and resulting in a corresponding decrease in intermolecular hydrogen bonds responsible for ß-sheets.

Conflict and performance in channels: a meta-analysis.

Conflict between channel members is of great interest to marketers given its presumed negative impact on the channel's business performance. In a comprehensive meta-analysis of the empirical literature spanning six decades between 1960 and 2020, we observe channel performance is indeed negatively linked to channel conflict. However, we find that this conflict-performance link has evolved significantly over time, roughly in keeping with the growth and maturing of e-commerce technologies. Further, the damage caused by conflict appears to be more pronounced for channels with international operations, and for channels with greater dependency between channel members. Additionally, businesses in North America seem to suffer the consequences of channel conflict more than others. Our results also show several study characteristics related to measurement and sampling significantly impact the empirical conflict-performance links reported in the literature. We base our conclusions on correlational analyses, two-stage meta-analytic structural equation modeling (TSSEM), and meta-analytic regression analyses (MARA). SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s11747-020-00751-1) contains supplementary material, which is available to authorized users.

Exploring the Role of Peptide Helical Stability in the Propensity of Uperin 3.x Peptides toward Beta-Aggregation.

Antimicrobial peptides of the uperin 3.x family, obtained from the skin secretions of Uperoleia mjobergii, have an inherent ability to form amyloid with possible functional roles and can serve as model peptides to understand mechanistic aspects of amyloidogenesis. The substitution of a positively charged amino acid with a nonpolar alanine residue increased aggregation, fibril content, and propensity for ß-sheet formation for the uperin 3.5 R7A variant when compared with the uperin 3.5 wild-type peptides. We use molecular dynamics (MD) simulations and circular dichroism (CD) measurements on three uperin 3.x peptides and their corresponding seventh position alanine variants to understand the effect of substitution of a positively charged amino acid with a nonpolar alanine residue on the process of ß-aggregation. Both CD experiments and simulations show that the uperin 3.x wild-type peptides demonstrated lower ß-sheet content and propensity than with the corresponding alanine variants. Significantly, simulations of helix-to-coil transitions in individual peptides show an inverse relationship between the helical stability of peptides and their propensity to form structures rich in ß-sheets as observed in CD experiments. A simulation scheme based on a conformational search of helix-to-coil transition trajectories to select peptide conformers was used to assemble propagating peptide oligomers. Whereas octamers consisting of lower helical stability peptide conformers evolve into compact aggregates with a large ß-sheet component, octamers composed of high helical stability conformers disintegrate and show the least amounts of ß-sheet components. The highlight of the current work is that MD simulations are able to predict the correct order of ß-sheet propensity among the six peptides derived from the CD experiments and indicate the importance of helical intermediates in the amyloidogenesis pathway for uperin 3.x peptides.

ISOKANN: Invariant subspaces of Koopman operators learned by a neural network.

The problem of determining the rate of rare events in dynamical systems is quite well-known but still difficult to solve. Recent attempts to overcome this problem exploit the fact that dynamic systems can be represented by a linear operator, such as the Koopman operator. Mathematically, the rare event problem comes down to the difficulty in finding invariant subspaces of these Koopman operators K. In this article, we describe a method to learn basis functions of invariant subspaces using an artificial neural network.

Cutaneous granular cell tumor with epidermal involvement: a potential mimic of melanocytic neoplasia.

BACKGROUND: Cutaneous granular cell tumor (GCT) may present with extension into the junctional region of the epidermis and thus may mimic melanocytic neoplasms. METHODS: We reviewed three cases of cutaneous GCT where a melanocytic neoplasm was either initially diagnosed or considered in the differential diagnosis. Histopathology was evaluated in regards to features associated with melanocytic neoplasms. Immunohistochemistry was performed to delineate a panel useful in the distinction of these and other entities. RESULTS: All cases consisted of spindle and epithelioid cells with granular cytoplasm and bland nuclei and were centered in the superficial dermis with extension into the epidermis. Two cases resembled Spitz nevi and one case demonstrated lentiginous growth. All cases stained positively with calretinin and inhibin. Two of the three cases stained diffusely with S100 and 2/2 cases with CD56. HAM56 and CD68 were positive in one case and another showed positivity for NSE and PGP9.5. HMB-45, tyrosinase, and Melan-A were non-reactive in all cases tested. CONCLUSIONS: GCT may involve the epidermis and has a growth pattern similar to melanocytic neoplasms. An immunohistochemical (IHC) panel including S100, Melan-A, tyrosinase, HMB-45, CD56, CD68, calretinin, inhibin, and PGP9.5 may aid in the distinction and may spare the patient from unnecessary morbidity.

Abnormal patterns of antigenic expression in follicular lymphoma: a flow cytometric study.

In order to distinguish follicular lymphoma (FL) from reactive hyperplasia (RH), flow cytometric (FC) immunophenotypic studies have been used primarily to look for monotypic CD5- CD10(+) B cells with much more limited use of bcl-2 stains. We studied what additional diagnostic information could be extracted from routine FC studies in a retrospective study of 90 FL and 91 RH cases. The following significant differences were identified: dimmer CD19 on CD10+ B cells in FL (P < .0001), brighter CD10 and more numerous CD10(+) B cells in FL (P < .0001), and brighter CD20 on neoplastic B cells than on other B cells in FL (P = .002) or in RH (P = .05). In the FL cases, no correlations could be documented between any phenotypic findings. Grade 3 FL had significantly dimmer CD10 expression than lower grades (P = .05). Visual analysis of CD10(+) vs CD10(-) smaller B cells showed dimmer CD19 on the CD10(+) cells in 28 (44%) of 64 evaluable FL cases and 0 of 87 evaluable RH cases. These findings expand the ways in which FC studies can be used to help diagnose FL and suggest that the phenotypic aberrations identified do not represent normal developmental pathways.

Clear cell ductal adenocarcinoma of pancreas: a case report and review of the literature.

We present a unique carcinoma of the pancreas with predominantly clear cell morphology (>95% clear cells). Mucicarmine stain revealed abundant intraluminal and intracytoplasmic mucin. Immunohistochemically, the cells were positive for the epithelial markers cytokeratin 7 and CAM 5.2, and were focally positive for cytokeratin 20. These cells also expressed monoclonal carcinoembryonic antigen. Stains for the neuroendocrine markers synaptophysin and chromogranin were negative, as were stains for vimentin, p53, HMB-45, and CD10. An additional outstanding feature was the presence of dense intraluminal and intracytoplasmic hyaline globules, which were immunohistochemically positive for alpha1-antitrypsin. Sequencing of the K-ras oncogene revealed a point mutation in codon 12, providing molecular evidence of ductal origin. In the proper morphologic context supported by immunohistochemistry, clear cell carcinoma can be regarded as a rare variant of ductal adenocarcinoma.