Search Results (8)

Fluorinated chalcones are molecules reported to possess potent anticancer properties against triple-negative breast cancer (TNBC) cells. However, their molecular mechanisms have not yet been fully explored. Using bioinformatics tools, we analyzed the transcriptomes of MDA-MB-231 cells treated with either a novel fluorinated chalcone (compound 3) or a control in order to identify differentially expressed (DE) genes associated with its anticancer activity and determine the biological processes in which these genes are involved. A fluorinated chalcone was synthesized using the Claisen–Schmidt method. The transcriptome of MDA-MB-231 cells was then analyzed on an Illumina NextSeq500, and DE genes with significant changes in expression were identified using the DESeq2 v1.38.0 bioinformatics tool under the strict detection criteria of |log2FC| ≥  2 and adjusted p < 0.05. We identified 504 DE genes, which were enriched in terms related to “regulation of cell death”, “cation transport”, “response to topologically incorrect proteins”, and “response to unfolded proteins”. Surprisingly, these genes were involved in “the HSF1-dependent transactivation pathway” and “the attenuation phase pathway”. This bioinformatics-based study suggests that the tested fluorinated chalcone could influence HSF-1 silencing in addition to promoting the up-regulation of several genes involved in stress-induced apoptosis. Therefore, the tested compound could have enormous potential as a novel approach for TNBC treatment. Full article

Geometrical optics stability analysis has proven effective in deriving analytical instability criteria for 3D flows in ideal hydrodynamics and magnetohydrodynamics, encompassing both compressible and incompressible fluids. The method models perturbations as high-frequency wavelets, evolving along fluid trajectories. Detecting local instabilities reduces to solving ODEs for the wave vector and amplitude of the wavelet envelope along streamlines, with coefficients derived from the background flow. While viscosity and diffusivity were traditionally regarded as stabilizing factors, recent extensions of the geometrical optics framework have revealed their destabilizing potential in visco-diffusive and multi-diffusive flows. This review highlights these advancements, with a focus on their application to the azimuthal magnetorotational instability in magnetohydrodynamics and the McIntyre instability in lenticular vortices and swirling differentially heated flows. It introduces new analytical instability criteria, applicable across a wide range of Prandtl, Schmidt, and magnetic Prandtl numbers, which still remains beyond the reach of numerical methods in many important physical and industrial applications. Full article

A green method to synthesize cyclobutane derivatives has been developed over the past three decades in the form of solid-state [2+2] photochemical reactions. These solid-state reactions also play a major role in the structural transformation of hybrid materials. In this regard, crystal engineering has played a major role in designing photoreactive molecular systems. Here, we report three novel binuclear Cd(II) complexes with the molecular formula [Cd₂(4spy)₄L₄], where 4spy = 4-styryl pyridine and L = p-toluate (1); 4-fluorobenzoate (2); and 3-fluorobenzoate (3). Although three different benzoates are used, all three complexes are isostructural, as corroborated through SCXRD experiments. Structural analysis also helped in identifying two potential photoreactions. These are both intra- and intermolecular in nature and are driven by the head-to-head (HH) and head-to-tail (HT) alignment of 4spy linkers within these metal complexes. ¹H NMR spectroscopy studies showed evidence of a quantitative head-to-head photoreaction in all these three complexes, and SCXRD analysis of the recrystallization of the photoproducts also provided confirmation. TGA studies of these photoreactive complexes showed an increase in the thermal stability of the complexes due to the solid-state photoreaction. Photoluminescence studies of these complexes have been conducted, showing a blue shift in emission spectra across all three cases after the photoreaction. Full article

A combination of 4-styrylpyridine (spy) and 1-adamantanecarboxylic acid (Hadc) was employed in the assembly reactions with Zn(II) and Cu(II) nitrates. The photoreactivity of the products was compared and discussed on the basis of the structure–function relationship. Zinc(II) complex 1 is a trinuclear species of type [Zn₃(spy)₂(adc)₆] in which three zinc(II) atoms are linearly arranged, with two adjacent zinc(II) atoms linked by three bridging carboxylates. Two spy ligands occupy both terminal positions, yielding the overall structure of a six-bladed windmill. Copper(II) complex 2, [Cu(spy)₂(adc)₂][Cu₂(spy)₂(adc)₄]·2DMF, is an inorganic cocrystal comprising a mononuclear complex with a trans square planar geometry and a dinuclear complex with a paddle-wheel structure. In the photoreaction experiments characterized by ¹H NMR spectroscopy, the zinc(II) complex was found to be photoinert, while the copper(II) complex was photoreactive to form a cyclobutene ring via the [2+2] photodimerization between two spy ligands, resulting in the preparation of a one-dimensional chain as a coordination polymer. The separations of the C=C bond pair obtained from the crystal structures for both products also support their photoreactivity. For example, the spy ligands from two adjacent monocopper(II) complexes are aligned in a head-to-tail manner with the separation of 3.899 Å between the C=C bond pair, satisfying the so-called Schmidt criteria (<4.2 Å). However, no other products satisfy this condition. Full article

In environmental flows, field and laboratory measurements of suspended sediments show two kinds of concentration profiles. For coarse sediments, a near-bed upward convex profile is observed beneath the main upward concave profile. In this study, we consider two 1-DV models, namely, the classical advection–diffusion equation (ADE) based on the gradient diffusion model, and the kinetic model. Both need sediment diffusivity, which is related to the eddy viscosity, and an y-dependent β-function (i.e., the inverse of the turbulent Schmidt number). Our study shows that the kinetic model reverts to the classical ADE with an “apparent” settling velocity or sediment diffusivity. For the numerical resolution of the ADE, simple and accurate tools are provided for both the sediment diffusivity and hindered settling. The results for the concentration profiles show good agreement with the experimental data. An interpretation of the concentration profiles is provided by two “criteria” for shapes. The main for steady open-channel flows shows that the shape of the concentration profiles in the Cartesian coordinate depends on the vertical distribution of the derivative of $R$ (the ratio between the sediment diffusivity and the settling velocity of the sediments): dR/dy > −1 for the upward concave concentration profile while dR/dy < −1 for the near-bed upward convex profile. A generalization is proposed for oscillatory flows over sand ripples, where the time-averaged concentration profiles in the semi-log plots are interpreted by a relation between the second derivative of the logarithm of the concentration and the derivative of the product between the sediment diffusivity and an additional parameter related to the convective sediment entrainment process. Full article

The fusion of multi-spectral and synthetic aperture radar (SAR) images could retain the advantages of each data, hence benefiting accurate land cover classification. However, some current image fusion methods face the challenge of producing unexpected noise. To overcome the aforementioned problem, this paper proposes a novel fusion method based on weighted median filter and Gram–Schmidt transform. In the proposed method, Sentinel-2A images and GF-3 images are respectively subjected to different preprocessing processes. Since weighted median filter does not strongly blur edges while filtering, it is applied to Sentinel-2A images for reducing noise. The processed Sentinel images are then transformed by Gram–Schmidt with GF-3 images. Two popular methods, principal component analysis method and traditional Gram–Schmidt transform, are used as the comparison methods in the experiment. In addition, random forest, a powerful ensemble model, is adopted as the land cover classifier due to its fast training speed and excellent classification performance. The overall accuracy, Kappa coefficient and classification map of the random forest are used as the evaluation criteria of the fusion method. Experiments conducted on five datasets demonstrate the superiority of the proposed method in both objective metrics and visual impressions. The experimental results indicate that the proposed method can improve the overall accuracy by up to 5% compared to using the original Sentinel-2A and has the potential to improve the satellite-based land cover classification accuracy. Full article

Currently, a lack of consensus exists in the literature on the link between performance and corporate social responsibility disclosure (CSRD). A meta-analysis was carried out to shed light on this controversial topic, using the ABI/Inform Complete and EconLit databases as search tools. To isolate articles with substantive, methodological relevance, various filters were used. In addition to other criteria, all articles had to contain certain keywords related to the study’s variables and at least one of the seven keywords indicating empirical data analysis. As a result of this procedure, the meta-analysis included only 95 articles. To process the sample, we employed the procedure developed by Hunter and Schmidt. The results show that the CSRD-performance relationship is not significant enough for practical purposes. However, an analysis of moderating variables revealed that the connection becomes of practical importance when moderated by three key variables: region, type of disclosure, and measures of organization size. This research’s findings make a significant contribution by clarifying the links between CSRD and performance and identifying which variables can explain the diverse results of previous research. Regarding limitations, the meta-analysis was subject to the availability of published research and included only studies that reported Pearson correlation coefficients and standardized beta coefficients. Full article

Physico-chemical modelling and predictive simulation are becoming key for modern process engineering. Rigorous models rely on the separation of different effects (e.g., fluid dynamics, kinetics, mass transfer) by distinct experimental parameter determination on lab-scale. The equations allow the transfer of the lab-scale data to any desired scale, if characteristic numbers like e.g., Reynolds, Péclet, Sherwood, Schmidt remain constant and fluid-dynamics of both scales are known and can be described by the model. A useful model has to be accurate and therefore match the experimental data at different scales and combinations of process and operating parameters. Besides accuracy as one quality attribute for the modelling depth, model precision also has to be evaluated. Model precision is considered as the combination of modelling depth and the influence of experimental errors in model parameter determination on the simulation results. A model is considered appropriate if the deviation of the simulation results is in the same order of magnitude as the reproducibility of the experimental data to be substituted by the simulation. Especially in natural product extraction, the accuracy of the modelling approach can be shown through various studies including different feedstocks and scales, as well as process and operating parameters. Therefore, a statistics-based quantitative method for the assessment of model precision is derived and discussed in detail in this paper to complete the process engineering toolbox. Therefore a systematic workflow including decision criteria is provided. Full article