Search Results (52)

The increasing threat of zoonotic malaria parasites of humans, such as Plasmodium knowlesi, make the search for improved pharmacotherapy imperative. Using protein sequence and structural analyses, phylogenetics, protein network mapping, protein–ligand interaction, and small molecule docking studies, we have identified for the first time the predicted structure, function, and druggability of the P. knowlesi heat shock protein 90s (PkHsp90s). Four isoforms were identified (in the cytosol, endoplasmic reticulum, mitochondrion, and apicoplast), and key structural differences were elucidated compared to human Hsp90s. In particular, the glycine-rich helix loop (GHL) motif of cytosolic PkHsp90 was predicted to have a straight conformation that forms a plasmodial-specific hydrophobic extension of the lid domain of the ATP-binding site, which was not observed for the cytosolic human Hsp90s, HSPC1 (Hsp90α), and HSPC3 (Hsp90β). Virtual screening identified for the first time a number of compounds from the ZINC database (ZINC22007970, ZINC724661072, and ZINC724661078) that were predicted to bind strongly to the GHL-associated pocket of PkHsp90, with weak or no binding to HSPC1. This study has provided a molecular framework in support of rational drug design, targeting PkHsp90s as a promising route for antimalarial drug development in the fight against zoonotic malaria. Full article

There are 25 crystal structures of Lipase B from Candida antarctica (CalB) that have been previously reported. In this study, we report the first CalB crystal structure that shows the assumed pro-peptide region at the N-terminus (Ala19–Arg25). This 1.45 Å structure shows that this segment of seven amino acids is an extension of the N-terminal loop and that it does not interact with or effect conformational changes in the flexible lid domain, which covers the active site of the enzyme. As such, this region is unlikely to be a classical pro-peptide. Full article

An ambit of enhancing heat transfer throughout thermal convection in a cavity is explored numerically in this study, contemplating the heat dispersal from a segmental heat source circumscribed in a square-vented porous cavity with a moving lid. The cavity can be used as a heat sink for electronic cooling, material processing, and convective drying. Aluminum $10$ PPI metal foam saturated by aluminum oxide–water nanofluid is occupied in this lid-driven vented cavity system. The bottom cavity wall is fully and partially heated by a heat source of specific length $L_H$, and the left wall and inlet fluid are kept at the same cold temperature, while the right wall and top-driven wall are thermally insulated. Thermal dispersion and local thermal non-equilibrium effects are included in an energy equation, and continuity and Darcy–Brinkmann–Forchheimer momentum equations are implemented and resolved by utilizing the finite volume method with the aid of a vorticity–stream function approach operation. The inspirations behind pertinent parameters, including the Reynolds number ($Re=10–50$), Grashof number ($Gr={10}^3–{10}^6$), inlet and outlet ports’ aspect ratio ($D/H=0.1–0.4$), outlet port location ratio ($S/H=0.25–0.75$), and discrete partial heating ratio ($L_H/L=0.25–1$) are scrutinized. The baseline circumstance corresponds to full-length heating $L_H/L=1$ and the outlet port location ratio $S/H=0.25$. The results reveal that the fluid and heat flow domains are addressed mostly via these specification alterations. For $Gr={10}^3$, increasing $Re$ from $10$ to $40$ does not alter streamlines or the isotherm field, but when $Re=50$ it is detected that streamlines increase monotonically. Streamlines are not altered when $L_H/L$ and $S/H$ are amplified but strengthened more when the opening vent aspect ratio is increased. A greater temperature difference occurs as $L_H/L$ is raised from $0.25–0.75$ and isotherms are intensified, and the thermal boundary layer becomes more distinct when $S/H$ is augmented. The average Nusselt number rises as $Re$, $Gr$, $L_H/L$, and $D/H$ are increased by about $30\%$, $3.5\%$, $23\%$, and $19.4\%$, respectively, and it decreases with $S/H$ amplifying is increased by around $5.5\%$. Full article

With the growing demand for natural and intelligent human–machine interaction in multilingual environments, automatic language identification (LID) has emerged as a crucial component in voice-enabled systems, particularly in the automotive domain. This study proposes an audio-based LID model that identifies the spoken language directly from voice input without requiring manual language selection. The model architecture leverages two types of feature extraction pipelines: a Variational Autoencoder (VAE) and a pre-trained Wav2Vec model, both used to obtain latent speech representations. These embeddings are then fed into a multi-layer perceptron (MLP)-based classifier to determine the speaker’s language among five target languages: Korean, Japanese, Chinese, Spanish, and French. The model is trained and evaluated using a dataset preprocessed into Mel-Frequency Cepstral Coefficients (MFCCs) and raw waveform inputs. Experimental results demonstrate the effectiveness of the proposed approach in achieving accurate and real-time language detection, with potential applications in in-vehicle systems, speech translation platforms, and multilingual voice assistants. By eliminating the need for predefined language settings, this work contributes to more seamless and user-friendly multilingual voice interaction systems. Full article

A systems-oriented review of machine learning (ML) over the entire flood management spectrum, encompassing fluvial flood control, pluvial flood management, and resiliency-risk characterization was undertaken. Deep learners like long short-term memory (LSTM) networks perform well in predicting reservoir inflows and outflows. Convolution neural networks (CNNs) and other object identification algorithms are being explored in assessing levee and flood wall failures. The use of ML methods in pump station operations is limited due to lack of public-domain datasets. Reinforcement learning (RL) has shown promise in controlling low-impact development (LID) systems for pluvial flood management. Resiliency is defined in terms of the vulnerability of a community to floods. Multi-criteria decision making (MCDM) and unsupervised ML methods are used to capture vulnerability. Supervised learning is used to model flooding hazards. Conventional approaches perform better than deep learners and ensemble methods for modeling flood hazards due to paucity of data and large inter-model predictive variability. Advances in satellite-based, drone-facilitated data collection and Internet of Things (IoT)-based low-cost sensors offer new research avenues to explore. Transfer learning at ungauged basins holds promise but is largely unexplored. Explainable artificial intelligence (XAI) is seeing increased use and helps the transition of ML models from black-box forecasters to knowledge-enhancing predictors. Full article

p53 functions as a critical guardian of the genome, orchestrating tumor suppression pathways and ensuring the integrity of chromosomal stability. Mdm2 and MdmX, homologous proteins, serve as negative feedback regulators of p53. In approximately half of tumor cases, overexpression of Mdm2/MdmX results in the inhibition of p53 activity. Current research focuses on designing Mdm2 and MdmX inhibitors based on the structure of lidless N-terminal forms of these proteins. However, growing evidence suggests that the lid of Mdm2 and MdmX plays a key role in the selective binding of p53 and inhibitors. Therefore, targeting the lid in the screening and design of Mdm2/MdmX inhibitors may offer a novel strategy for developing anti-cancer drugs. This review examines the impact of the Mdm2/MdmX lid on ligand binding, providing valuable insights for future research and guiding new approaches to the screening and design of innovative anti-cancer therapeutics. Full article

The study of entropy generation in thermal non-equilibrium (TNE) states has significant implications for optimizing thermal management systems and understanding heat transfer mechanisms in permeable media. This study investigates the entropy properties in a thermal non-equilibrium (TNE) state within double-lid-driven enclosures filled with a permeable medium. Unlike the temperature equilibrium state, the entropy approach is described by two equations: one for the irreversibility of the mixture phase and one for the irreversibility of the medium phase. High mixed convection is considered due to the motion of the non-facing edges (left-side and upper edges). Four cases based on the direction of motion are examined: Case 1, where the left-side and top edges move in the negative and positive directions of the Y- and X-axes, respectively; Case 2, where the upper and left-side edges move in the negative and positive directions of the X- and Y-axes, respectively; and Cases 3 and 4, where the edges move in the positive and negative directions of the respective axes. Heat generation within the flow domain is considered for both the suspension and medium phases. The governing system is solved numerically using finite volume techniques with the SIMPLER algorithm. The obtained data are used to predict key quantities, such as the heat transfer rate, under the influence of major factors using an effective artificial neural network (ANN) analysis. The main findings show that the solid phase entropy is higher in Case 3 compared to the other cases. Additionally, Case 2 results in a minimum solid phase Nusselt coefficient at the center of the active boundary. Full article

Lipase, a type of enzyme that decomposes and synthesizes triglycerides, plays an important role in lipid processing. In this study, a heat-resisting lipase gene (lip4) from Thermomyces lanuginosus was subcloned into the pPICZαA vector and then transformed into Pichia pastoris X33. The recombinant yeast cell concentration reached the maximum (119.5 g/L) at 144 h, and the lipase (Lip4) activity reached the maximum (3900 U/mL) at 168 h in 10 L bioreactor. Through bioinformatics analysis, S168, as the key site of Lip4, participated in the formation of the catalytic triads S168-D223-H280 and G166-H167-S168-L169-G170. Furthermore, S168 and seven conserved amino acids of G104/288, S105, A195, P196, V225 and I287 constitute the active center of Lip4. Specifically, the structure modeling showed two α-helices of the lid domain, outside the active pocket domain, controlling the entry of the substrate on Lip4. The potential glycosylation of Asn-33 may be involved in exhibiting the high stable temperature for lipase activity. Therefore, the eukaryotic system was constructed to express Lip4 efficiently, and the amino acid sites related to the catalytic efficiency of Lip4 were clarified, providing a new way for its subsequent property research and industrial application. Full article

The lid-driven cavity flow problem stands as a widely recognized benchmark in fluid dynamics, serving to validate CFD algorithms. Despite its geometric simplicity, the lid-driven cavity flow problem exhibits a complex flow regime primarily characterized by the formation of vortices at the centre and corners of the square domain. This study evaluates the accuracy of the 2D velocity-driven adaptive mesh refinement (2D VDAMR) method in estimating vortex centres in a steady incompressible flow within a 2D square cavity. The VDAMR algorithm allows for an arbitrary number of finite mesh refinements. Increasing the number of successive mesh refinements results in more accurate outcomes. In this paper, the initial coarse uniform grid mesh was refined ten times for Reynolds numbers $100\le Re\le 7500$. Results show that VDAMR accurately identifies vortex centres, with its findings closely aligning with benchmark data from six literature sources. Full article

Cytosolic sulfotransferases (SULTs) are Phase 2 drug-metabolizing enzymes that catalyze the conjugation of sulfonate to endogenous and xenobiotic compounds, increasing their hydrophilicity and excretion from cells. To date, 13 human SULTs have been identified and classified into five families. SULT4A1 mRNA encodes two variants: (1) the wild type, encoding a 284 amino acid, ~33 kDa protein, and (2) an alternative spliced variant resulting from a 126 bp insert between exon 6 and 7, which introduces a premature stop codon that enhances nonsense-mediated decay. SULT4A1 is classified as an SULT based on sequence and structural similarities, including PAPS-domains, active-site His, and the dimerization domain; however, the catalytic pocket lid ‘Loop 3’ size is not conserved. SULT4A1 is uniquely expressed in the brain and localized in the cytosol and mitochondria. SULT4A1 is highly conserved, with rare intronic polymorphisms that have no outward manifestations. However, the SULT4A1 haplotype is correlated with Phelan–McDermid syndrome and schizophrenia. SULT4A1 knockdown revealed potential SULT4A1 functions in photoreceptor signaling and knockout mice display hampered neuronal development and behavior. Mouse and yeast models revealed that SULT4A1 protects the mitochondria from endogenously and exogenously induced oxidative stress and stimulates cell division, promoting dendritic spines’ formation and synaptic transmission. To date, no physiological enzymatic activity has been associated with SULT4A1. Full article

This research work presents a study on the flow behaviour in the lid-driven cavity (LDC) flows with triangular blocks using computational fluid dynamics techniques. The LDC flow is a widely studied problem that remains a standard for viscous incompressible fluid flows, with a range of parameters, including the Reynolds number, being explored. The finite volume method was used to discretize the domain, and simulations were computed using ANSYS FLUENT 2021 R1. The fluid flow started when the top wall is moved in the +X direction, whereas the other three walls are kept stationary. A grid independence test was performed to determine the optimum grid size and to obtain a grid-independent solution. Quantitative elements of the 2D flows in lid-driven cavities were explored for Reynolds numbers ranging from 1000 to 8000, and the results were validated against the existing literature. The consequence of different values of the Reynolds number (Re) were analyzed and examined through vorticity, streamline patterns, and kinetic energy contours. The velocity profile at the centerline was enhanced, and the vortex number and size increased with an increase in Re. The behaviour of the isolines of the vortices and the kinetic energy contours was also analyzed. The kinetic energy contours show that the high velocity of the fluid particles close to the upper wall is a significant factor affecting the maximum kinetic energy values. As the Reynolds number increased, the kinetic energy gradually increased at the boundary. This suggests that the Re considerably affects the energy values. Overall, this study provides valuable insights into the flow behaviour of lid-driven cavities and the effects of obstacles on flow patterns, contributing to the existing literature and being useful for researchers and engineers working in the field of fluid dynamics. Full article

The presence of particles with a small but finite size, suspended in viscous fluids with low volumetric concentrations, is observed in many applications. The present study focuses on the tridimensional and incompressible lid-driven flow of Newtonian fluids through the application of the immersed boundary method and the Euler–Lagrange approach. These methods are used to numerically predict three-dimensional particle motion by considering nearly neutrally buoyant conditions as well as all relevant elementary processes (drag and lift forces, particle rotation, particle–wall interactions, and coupling between phases). Considering the current stage of the numerical platform, two coupling approaches between phases are considered: one-way and two-way coupling. A single particle is inserted in the cavity after steady-state conditions are achieved. Its three-dimensional motion is obtained from numerical simulations and compared with research data, considering the same conditions, evidently showing that the particle trajectory follows the experimental data until the first collision with a solid surface. After this first contact, there is a deviation between the results, with the two-way coupling results better representing the experimental data than the one-way coupling results. The dimensionless forces’ peaks acting on the particles are associated with the relative velocity of the particle near the wall–particle collision position. In terms of magnitude, in general, the drag force has shown greater influence on the particle’s motion, followed by the rotation-induced and shear-induced lift forces. Finally, a special application is presented, in which 4225 particles are released into the domain and their dynamic is evaluated throughout dimensionless time, showing similar behavior for both couplings between phases, with variations in local concentrations observed in certain regions. The mean square displacement used to quantify the dispersion evolution of the particles showed that the particulate flow reaches an approximately homogeneous distribution from the moment of dimensionless time tU/S = 130. Full article

As an improved method of the lattice Boltzmann method (LBM), the regularized lattice Boltzmann method (RLBM) has been widely used to simulate fluid flow. For solving high Reynolds number problems, large eddy simulation (LES) and RLBM can be combined. The computation of fluid flow problems often requires a large number of computational grids and large-scale parallel clusters. Therefore, the high scalability parallel algorithm of RLBM with LES on a large-scale cluster has been proposed in this paper. The proposed parallel algorithm can solve complex flow problems with large-scale Cartesian grids and high Reynolds numbers. In order to achieve computational load balancing, the domain decomposition method (DDM) has been used in large-scale mesh generation. Three mesh generation strategies are adopted, namely 1D, 2D and 3D. Then, the buffer on the grid interface is introduced and the corresponding 1D, 2D and 3D parallel data exchange strategies are proposed. For the 3D lid-driven cavity flow and incompressible flow around a sphere under a high Reynolds number, the given parallel algorithm is analyzed in detail. Experimental results show that the proposed parallel algorithm has a high scalability and accuracy on hundreds of thousands of cores. Full article

In single phase flows, benchmarks like the lid driven cavity have become recognized as fundamental tests for newly developed computational fluid dynamics, CFD, codes. For multiphase free surface flows with variable surface tension, the presently studied pool with isothermal sidewalls is suggested as it is the simplest domain where Marangoni effects can dominate. It was also chosen due to its strange sensitivity to the initial setup which is discussed at length from a chosen number of ‘scenarios’. It was found that the fluid interface can reverse deformation by a change in the top boundary condition, the liquid equation of state, and the gravity level. For the top boundary condition, this reversal is due to vapor expansion within the closed volume, creating an additional convection mechanism. Not only does the interface reverse, but the peak height changes by more than an order of magnitude at the same Marangoni number. When including gravity, the peak velocity can increase significantly, but it can also cause a decrease when done in combination with a change in the top wall boundary condition. Finally, thermal expansion of the liquid phase causes the peak velocity to be reduced, with additional reductions from the gravity and top wall condition. The differences in each scenario could lead to significant errors in analyzing a practical application of Marangoni flows. Therefore, it is important to demonstrate that a new CFD code can not only resolve Marangoni convection, but also has the capability to resolve the scenario most relevant to the application at hand. Full article

Lipases have valuable potential for industrial use, particularly those mostly active against water-insoluble substrates, such as triglycerides composed of long-carbon chain fatty acids. However, in most cases, engineered variants often need to be constructed to achieve optimal performance for such substrates. Protein engineering techniques have been reported as strategies for improving lipase characteristics by introducing specific mutations in the cap domain of esterases or in the lid domain of lipases or through lid domain swapping. Here, we improved the lipase activity of a lipase (WP_075743487.1, or Lip_MRD) retrieved from the Marine Metagenomics MarRef Database and assigned to the Actinoalloteichus genus. The improvement was achieved through site-directed mutagenesis and by substituting its lid domain (FRGTEITQIKDWLTDA) with that of Rhizopus delemar lipase (previously R. oryzae; UniProt accession number, I1BGQ3) (FRGTNSFRSAITDIVF). The results demonstrated that the redesigned mutants gain activity against bulkier triglycerides, such as glyceryl tridecanoate and tridodecanoate, olive oil, coconut oil, and palm oil. Residue W89 (Lip_MRD numbering) appears to be key to the increase in lipase activity, an increase that was also achieved with lid swapping. This study reinforces the importance of the lid domains and their amino acid compositions in determining the substrate specificity of lipases, but the generalization of the lid domain swapping between lipases or the introduction of specific mutations in the lid domain to improve lipase activity may require further investigation. Full article