Favorable Regions Research Articles

Distribution patterns of Phytoseiulus persimilis in response to climate change.

The biological control agent Phytoseiulus persimilis is a commercialized specialist predator of two agricultural pest mite species Tetranychus urticae and Tetranychus evansi. Biocontrol of these pest species by P. persimilis has achieved success in biological control in some areas. However, the lack of precise information about the influence of global climate change on the worldwide distribution of this biocontrol agent hampers international efforts to manage pest mites with P. persimilis. With 276 occurrence records and 19 bioclimatic variables, this study investigated the potential global distribution of P. persimilis. The results demonstrated that the Maximum Entropy (MaxEnt) model performed well, with the area under the curve being 0.956, indicating the high accuracy of this model. Two variables, the minimum temperature of the coldest month (Bio_6) and precipitation of the coldest quarter (Bio_19) were the most important environmental variables that influenced the distribution of P. persimilis, contributing more than 30% to the model, respectively. The suitable area currently occupies 21.67% of the world's land area, spanning latitudes between 60°S and 60°N. Under shared socio-economic pathway (SSP) 5-8.5 (high-carbon emissions), the low suitable area would increase by 1.31% until the 2050s. This study successfully identified that south-eastern China, parts of countries in the Mediterranean coastal regions, including Libya, Algeria, Portugal, Spain, and France, are climatically favorable regions for P. persimilis, providing valuable information about the potential areas where it can be effectively exploited as biocontrol agents in classical biological control programs to manage pest spider mites environmentally friendly. © 2024 Society of Chemical Industry.

Machine learning-based optimization and 4E analysis of renewable-based polygeneration system by integration of GT-SRC-ORC-SOFC-PEME-MED-RO using multi-objective grey wolf optimization algorithm and neural networks

This study introduces a new solar-methane-driven setup that recovers waste heat from flue gases to produce electricity, hydrogen, oxygen, fresh water (FW), and domestic hot water (DHW) while reducing the environmental impact of gas turbines. This integration includes the Brayton cycle and solid oxide fuel cell as motive cycles, the steam and organic Rankine cycle, a parabolic trough solar collector (PTC), a proton exchange membrane electrolyzer, multi-effect distillation, and reverse osmosis. Using Engineering Equation Solver software, analyses in energy, exergy, exergoeconomic, and exergoenvironment (4E) are conducted to identify critical system evaluation parameters in thermodynamics, economics, and the environment. Additionally, the proposed system is optimized using an artificial neural network and the multi-objective grey wolf optimizer algorithm, utilizing decision variables identified through sensitivity analysis to enhance system performance. The results of six-objective optimization show energy and exergy efficiencies at 49.48 % and 47.21 %, with a net power production of 133 MW and a total cost rate of $7903/h. Among all the components, the combustion chamber and PTC have the maximum exergy destruction, with values of 58.87 MW and 17.29 MW, respectively. Also, hydrogen, FW, and DHW production rates are 201.6 kg/h, 43.88 kg/s, and 40.98 kg/s, respectively. Moreover, the costs of hydrogen, FW, and DHW are $953.64/h, $57.35/h, and $82.48/h, respectively. Finally, Bloemfontein, Las Vegas, and Tunis are the most favorable regions economically, with a low levelized cost of electricity of $0.05931, $0.06006, and $0.05932 per kWh, along with payback periods of 0.6144, 0.5524, and 1.069 years, respectively.

Energy Consumption at Accommodation Buildings: A Case Study of a Boutique Hotel-Abdera

Global environmental problems such as decreasing biodiversity, natural disasters, climate change, and energy consumption are among the main concerns of the countries. Approximately 50% of the energy consumed worldwide is spent on architectural construction, use, and operation. The increase in energy consumption in buildings especially has taken the reduction of carbon footprint and the importance of energy efficiency to the fore. Physical environment, climate, orientation, envelope, and material properties are among the different factors in determining energy consumption in buildings. The share of tourism activities in total emissions is estimated to be 5%. However, it is also stated that tourism buildings have a share of 21 % of C02 emissions. This work aimed to research the energy consumption of a boutique hotel in Abdera, Greece. ArchiCAD, Graphisoft, and EcoDesigner software were used in the analysis of findings, and suggestions were put forward. Energy consumption and environmental effects were investigated when active solar systems (Solar Thermal Panel /STP (30 m2), Photovoltaic Panel/PV (30 m2)) were added to the roof surface (total 60 m2 Panel) of the building. The analysis showed that the addition of active solar systems by 30% could reduce emissions. In Greece, which is located in a very favorable region in terms of geographical features, it is very important to use solar potential with integrated systems in buildings to provide energy needs.

Predictions of Immunodominant Epitope Peptides From the AsaA Type VI Secretion System in Acinetobacter baumannii: A Computational Approach.

Introduction Acinetobacter baumannii, designated as a priority pathogen by the World Health Organization (WHO), is responsible for recalcitrant infections in immunocompromised patients. The type VI secretion system (T6SS) is a class of macromolecular secretion machines, contributing to its virulence. The aim of this study is thus to predict the immune-dominant epitope peptides from theAcinetobacter T6SS-associated protein of A. baumannii(AsaA). Methods AsaA protein retrieval from the bacteria was carried out using computational platforms and the evaluation of antigenicity and allergenicitywas performed. The T-cell epitopes of major histocompatibility complex class II binders were identified followed by molecular docking of the immune-dominant epitopes with human leukocyte antigen alleles using the ClusterPro server (https://cluspro.org/help.php). Additionally, the B-cell epitopes were predicted. Results Immune-informatic analysis showed immune-dominant peptides in the most favored regions with promising interactions with HLAalleles DP, DQ, DR, and toll-like receptor showing high binding capacity. Conclusion In the present investigation, epitope 1 (LILFLIGNY) was found to be a promising candidate for the synthesis of vaccines. However, it requires further experimentation for its immunological memory and response.

Statistical optimized production of Phytase from Hanseniaspora guilliermondii S1 and studies on purification, homology modelling and growth promotion effect

This investigation was performed to obtain a promising phytase enzyme producing yeast. In this regard, the PSM was used to isolate the phytase-producing Hanseniaspora guilliermondii S1 (MG663578) from sugarcane juice. The SSF optimum conditions for phytase generation were optimized using (OVAT) one-variable-at-a-time strategy using both Box-Behnken design and shake flask method (g/100 ml: 0.05 yeast extract, 0.15 Peptone, 0.05 malt extract 0.50 dextrose, pH 5.8 and 28ᵒC). The protein model developed was shown to be adequate for phytase production (91% accuracy), with the greatest phytase productivity in shake flask with substrate jack fruit seed powder being 395 ± 0.43 U/ml compared to 365U/ml for the BBD projected value. Crude Phytase was partially purified with a protein recovery of 43%, revealing a molecular weight of 120 kDa. It had an enzyme kinetic value of Km 3.3 mM and a Vmax of 19.1 mol/min. The 3D structure of PhyS1 amino acid sequences (PhyS1. B99990002) was simulated using Modeler 9.23, and the validated result revealed that 86.7% were in the favored region by Ramachandran plot. The SAVES server verified the 3D PDB file as satisfactory, and the model (in.pdb format) was uploaded in the PMDB database with the accession number ID: PM0082974. At the lab level, Hanseniaspora guilliermondii S1 (MG663578) producing phytase exhibited successful plant growth promotion activity in Ragi - CO 19 (Eleusine coracana L.) and Rice -Navarai - IR 64 (Oryza sativa L.). As a result, a phytase-based formulation for sustainable agriculture must be developed and tested on a large scale in diverse geographical areas of agricultural lands to determine its effect and potential on plant development.

The Third Plasma Density Peak at Poleward of EIA Crest: Swarm and ICON Observations

AbstractIn this study, we focus on the presence of the ionospheric third plasma density peak associated with the equatorial ionization anomaly (EIA) based on observations from the ESA's Swarm constellation. By statistically analyzing the third peaks observed by the Swarm A and B at two different altitudes, we found that such structure appears mainly around ±20° magnetic latitude (Mlat), namely the poleward of the EIA crests. In the meanwhile, the third peak shows prominent season and local time dependences, that are mainly observed in the summer hemisphere during solstice seasons and with the highest occurrence in the afternoon hours. However, no clear solar flux and magnetic activity dependences are found. By further analyzing the simultaneous neutral wind measurements from the ionospheric connection explorer satellites, we found that the summer‐to‐winter hemispheric meridional wind is responsible for causing the third peak as well as its seasonal dependence (higher occurrence in the summer hemisphere). In addition, the third‐peak structure shows prominent longitudinal dependence. In regions where the magnetic declination directs eastward, it has a larger occurrence in the southern hemisphere, while in regions where the magnetic declination reverses, it has a larger occurrence in the northern hemisphere. Such a longitudinal dependence suggests that the zonal wind, which has a magnetic field‐aligned component at favorable magnetic declination regions, contributes also to the formation of the third‐peak structure.

A streamline coordinate analysis of a turbulent boundary layer subject to pressure gradients and curvature on the windward side of a bump

Direct numerical simulation (DNS) of a turbulent boundary layer over the Gaussian (Boeing) bump is performed. This boundary layer exhibits a series of adverse and favourable pressure gradients and convex and concave curvature effects before separating. These effects on turbulent boundary layers are characterised and compared with a lower-Reynolds-number flow over the same geometry. The momentum budgets are analysed in the streamline-aligned coordinate system upstream of the separation region. These momentum budgets allow the simplification of equations to facilitate an integral analysis. Integral-analysis-based approximations for Reynolds stresses in the inner and outer regions of the boundary layer are also formulated. The shear and wall-normal Reynolds stress profiles normalised by these approximations exhibit a better collapse compared with friction velocity and Zagarola–Smits normalisations in the strong favourable pressure gradient region and in the mild adverse pressure region that precedes it in this flow. Simplification of these Reynolds stress approximations along with results from the DNS are used to obtain semi-empirical approximations that are able to provide stress closure in terms of wall solution fields for the turbulent boundary layer under consideration.

Surfactant-based supramolecular dye assembly: A highly selective and economically viable platform for quantification of heparin antidote

Herein, we have employed a supramolecular assembly of a cationic dye, LDS-698 and a common surfactant sodium dodecyl sulfate (SDS) as a turn-on fluorescent sensor for protamine (Pr) detection. Addition of cationic Pr to the solution of dye-surfactant complex brings negatively charged SDS molecules together through strong electrostatic interaction, assisting aggregation of SDS way before its critical micellar concentration (CMC). These aggregates encapsulate the dye molecules within their hydrophobic region, arresting non-radiative decay channels of the excited dye. Thus, the LDS-698•SDS assembly displays substantial enhancement in fluorescence intensity that follows a nice linear trend with Pr concentration, providing limit of detection (LOD) for Pr as low as 3.84(±0.11) nM in buffer, 124.4(±6.7) nM in 1% human serum and 28.3(±0.5) nM in 100% human urine. Furthermore, high selectivity, low background signal, large stokes shift, and emission in the biologically favorable deep-red region make the studied assembly a promising platform for Pr sensing. As of our knowledge it is the first ever Pr sensory platform, using a very common surfactant (SDS), which is economically affordable and very easily available in the market. This innovative approach can replace the expensive, exotic and specialized chemicals considered for the purpose and thus showcase its potential in practical applications.

Development of a novel multi‑epitope vaccine against the pathogenic human polyomavirus V6/7 using reverse vaccinology.

Human polyomaviruses contribute to human oncogenesis through persistent infections, but currently there is no effective preventive measure against the malignancies caused by this virus. Therefore, the development of a safe and effective vaccine against HPyV is of high priority. First, the proteomes of 2 polyomavirus species (HPyV6 and HPyV7) were downloaded from the NCBI database for the selection of the target proteins. The epitope identification process focused on selecting proteins that were crucial, associated with virulence, present on the surface, antigenic, non-toxic, and non-homologous with the human proteome. Then, the immunoinformatic methods were used to identify cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes from the target antigens, which could be used to create epitope-based vaccine. The physicochemical features of the designed vaccine were predicted through various online servers. The binding pattern and stability between the vaccine candidate and Toll-like receptors were analyzed through molecular docking and molecular dynamics (MD) simulation, while the immunogenicity of the designed vaccines was assessed using immune simulation. Online tools were utilized to forecast the most optimal epitope from the immunogenic targets, including LTAg, VP1, and VP1 antigens of HPyV6 and HPyV7. A multi-epitope vaccine was developed by combining 10 CTL, 7 HTL, and 6 LBL epitopes with suitable linkers and adjuvant. The vaccine displayed 98.35% of the world's population coverage. The 3D model of the vaccine structure revealed that the majority of residues (87.7%) were located in favored regions of the Ramachandran plot. The evaluation of molecular docking and MD simulation revealed that the constructed vaccine exhibits a strong binding (-1414.0 kcal/mol) towards the host's TLR4. Moreover, the vaccine-TLR complexes remained stable throughout the dynamic conditions present in the natural environment. The immune simulation results demonstrated that the vaccine design had the capacity to elicit robust immune responses in the host. The multi-parametric analysis revealed that the designed vaccine is capable of inducing sustained immunity against the selected polyomaviruses, although further in-vivo investigations are needed to verify its effectiveness.

Operating Behavior of Pulse Jet‐Cleaned Filters Regarding Energy Demand and Particle Emissions – Part 2: Modeling

AbstractBaghouse filters applied for gas cleaning are subject to digitalization concepts, including process modeling and the development of digital twins in order to improve energy efficiency and lower particle emissions. Modeling equations from literature were adapted to match experimental data from part 1 of this study to calculate the effect of varying filter face velocities, dust concentrations, or tank pressures on energy demand and particle emissions. Based on the model approaches, an operation curve that enables the evaluation of filter operation regarding the trade‐off between energy demand and particle emissions can be constructed. The identification of energetically optimal cycle times and favorable operation regions is possible due to the extensive experimental framework of the model.

Immunoinformatic Analysis of Leishmania Major gp46 Protein and Potential Targets for Vaccination against Leishmaniasis.

Cutaneous leishmaniasis (CL) is a parasitic disease with a significant burden in the Old World countries. In the current study, some of the primary biochemical properties and IFN-γ inducing epitopes with specific binding capacity to human and mouse MHC alleles were predicted for Leishmania major gp46 antigenic protein. Several online servers were used to predict physico-chemical traits, allergenicity, antigenicity, transmembrane domain and signal peptide, subcellular localization, post-translational modifications (PTMs), secondary and tertiary structures, tertiary model refining with validations. Also, IEDB web server was used to predict mouse/human cytotoxic T-lymphocyte (CTL) and helper T-lymphocyte (HTL) epitopes. The 33.25 kDa protein was stable, hydrophilic, antigenic, while non-allergenic, with enhanced thermotolerance and 45 PTM sites. The secondary structure encompassed a random coil, followed by extended strands and helices. Ramachandran-based analysis of the refined model showed 73.1%, 21.6%, 3.4% and 1.9% of residues in the most favored, additional allowed, generously-allowed and disallowed regions, respectively. Epitope screening demonstrated 4 HTL epitopes against seemingly protective HLA alleles, 5 HTL epitopes against the HLA reference set, 3 human CTL epitopes and a number of mouse MHC-restricted epitopes. This paper provides insights into the bioinformatics characteristics of the L. major gp46 protein as a promising vaccine candidate.

In silico characterization of GbPAL, GbCHS, GbDFR and GbANS structural genes involved in the biosynthesis of flavonoids in Gynura bicolor DC

Gynura bicolor is a member of the Asteraceae family, possessing important pharmaceutical compounds such as flavonoids, anthocyanins, and terpenoids. Genetic and molecular studies focusing on the biosynthesis of flavonoids are indispensable to determining their regulation. GbPAL, GbCHS, GbDFR, and GbANS are genes encoding Phenylalanine ammonia lyase, Chalcone synthase, Dihydroflavonol reductase, and Anthocyanidin synthase enzymes, resepectively and are involved in the biosynthesis of flavonoids in G. bicolor, resepectively. There are still a few studies concerning the characterization of these genes. In this study, the structural enzyme sequences were selected to be characterized in silico using bioinformatics software. The phylogenetic analysis demonstrated that the genes in question were closely related to several species of the Asteraceae family. Our data revealed that the G. bicolor PAL, CHS, DFR and ANS genes are closely related to the sequence of genes found in Chrysanthemum morifolium. Furthermore, the CHS, DFR and ANS of G. bicolor also tightly correlated with sequence from Callistephus chinensis. Further analysis also demonstrated that all conserved motifs contain active functional and catalytic domain supporting the flavonoid-related enzyme functions. All physicochemical parameters used in this study also meet the prediction criteria. The investigation of secondary structure prediction using two instruments (PSIPRED and SOPMA) revealed that all enzymes tested possess similar α-helix (H), β-sheet (E), and coil (C) composition. GbPAL showed a secondary structure dominated by helix (mainly alpha), GbCHS and GbDFR (Alpha-beta), and GbANS (mainly beta). Each enzyme was modeled, with RMSD values superimposed on the template: 0.125 Å (GbPAL), 0.061 Å (GbCHS), 0.065 Å (GbDFR), and 0.089 Å (GbANS). The 3D model evaluation was checked using four parameters, including PROCHECK, Verify3D, ERRAT, and QMEAN-Z score. All the parameters verified that the model showed a high quality (more than 90 % of the favored region), high ressemblence of the 3D and 1D amino acid sequence, the 3D modeles were acceptable since they possesed high resolution of the protein structure (2.5 – 3 Å), and the enzyme models have Z-Score values in the permissible range. The accuracy and reliability of the generated models met Ramachandran value in comparison to experimentally resolved protein templates. The molecular docking analysis showed that each substrate compound docked at the real binding site in every tested enzyme. Furthermore, they also showed similar results compared to other experimentally observed proteins. The overall findings provide an insight into the molecular characteristics of flavonoid-related genes, which might enrich our understanding for further genomic application of the Gynura bicolor.

The industry transformation from fossil fuels to hydrogen will reorganize value chains: Big picture and case studies for Germany

In many industries, low-carbon hydrogen will substitute fossil fuels in the course of the transformation to climate neutrality. This paper contributes to understanding this transformation. This paper provides an overview of energy- and emission-intensive industry sectors with great potential to defossilize their production processes with hydrogen. An assessment of future hydrogen demand for various defossilization strategies in Germany that rely on hydrogen as a feedstock or as an energy carrier to a different extent in the sectors steel, chemicals, cement, lime, glass, as well as pulp and paper is carried out. Results indicate that aggregate industrial hydrogen demand in those industries would range between 197 TWh and 298 TWh if production did not relocate abroad for any industry sector. The range for hydrogen demand is mainly due to differences in the extent of hydrogen utilization as compared to alternative transformation paths for example based on electrification. The attractiveness of production abroad is then assessed based on the prospective comparative cost advantage of relocating parts of the value chain to excellent production sites for low-carbon hydrogen. Case studies are provided for the steel industry, as well as the chemical industry with ethylene production through methanol and the production of urea on the basis of ammonia. The energy cost of the respective value chains in Germany is then compared to the case of value chains partly located in regions with excellent conditions for renewable energies and hydrogen production. The results illustrate, that at least for some processes – as ammonia production – relocation to those favorable regions may occur due to substantial comparative cost advantages.

GEOMETRIC CONTROL OF BONE TISSUE GROWTH AND ORGANIZATION

Cells typically respond to a variety of geometrical cues in their environment, ranging from nanoscale surface topography to mesoscale surface curvature. The ability to control cellular organisation and fate by engineering the shape of the extracellular milieu offers exciting opportunities within tissue engineering. Despite great progress, however, many questions regarding geometry-driven tissue growth remain unanswered.Here, we combine mathematical surface design, high-resolution microfabrication, in vitro cell culture, and image-based characterization to study spatiotemporal cell patterning and bone tissue formation in geometrically complex environments. Using concepts from differential geometry, we rationally designed a library of complex mesostructured substrates (101-103 µm). These substrates were accurately fabricated using a combination of two-photon polymerisation and replica moulding, followed by surface functionalisation. Subsequently, different cell types (preosteoblasts, fibroblasts, mesenchymal stromal cells) were cultured on the substrates for varying times and under varying osteogenic conditions. Using imaging-based methods, such as fluorescent confocal microscopy and second harmonic generation imaging, as well as quantitative image processing, we were able to study early-stage spatiotemporal cell patterning and late-stage extracellular matrix organisation. Our results demonstrate clear geometry-dependent cell patterning, with cells generally avoiding convex regions in favour of concave domains. Moreover, the formation of multicellular bridges and collective curvature-dependent cell orientation could be observed. At longer time points, we found clear and robust geometry-driven orientation of the collagenous extracellular matrix, which became apparent with second harmonic generation imaging after ∼2 weeks of culture.Our results highlight a key role for geometry as a cue to guide spatiotemporal cell and tissue organisation, which is relevant for scaffold design in tissue engineering applications. Our ongoing work aims at understanding the underlying principles of geometry-driven tissue growth, with a focus on the interactions between substrate geometry and mechanical forces.

Virtual Screening, Docking, and Designing of New VEGF Inhibitors as Anti-cancer Agents.

VEGFR-2 tyrosine kinase inhibitors are receiving a lot of attention as prospective anticancer medications in the current drug discovery process. This work aims to explore the PubChem library for novel VEGFR-2 kinase inhibitors. 1H-Indazole-containing drug AXITINIB, or AG-013736 (FDA approved), is chosen as a rational molecule for drug design. This scaffold proved its efficiency in treating cancer and other diseases as well. The present study used the virtual screening of the database, protein preparation, grid creation, and molecular docking analyses. The protein was validated on different parameters like the Ramachandran plot, the ERRAT score, and the ProSA score. The Ramachandran plot revealed that 92.1% of the amino acid residues were located in the most favorable region; this was complemented by an ERRAT score (overall quality factor) of 96.24 percent and a ProSA (Z score) of -9.24 percent. The Lipinski rule of five was used as an additional filter for screening molecules. The docking results showed values of binding affinity between -14.08 and -12.34 kcal/mol. The molecule C1 showed the highest docking value of -14.08 Kcal/mol with the maximum number of strong H-bonds by -NH of pyridine to amino acid Cys104 (4.22Å), -NH of indazole to Glu108 (4.72), and Glu70 to bridge H of -NH. These interactions are similar to Axitinib docking interactions like Glu70, Cys104, and Glu102. The docking studies revealed that pi-alkyl bonds are formed with unsubstituted pyridine, whereas important H-bonds are observed with different substitutions around -NH. Based on potential findings, we designed new molecules, and molecular docking studies were performed on the same protein along with ADMET studies. The designed molecules (M1-M4) also showed comparable docking results similar to Axitinib, along with a synthetic accessibility score of less than 4.5. The docking method employed in this work opens up new possibilities for the design and synthesis of novel compounds that can act as VEGFR-2 tyrosine kinase inhibitors and treat cancer.

Homology modeling, binding site identification, molecular docking and molecular dynamics simulation study of emerging and promising drug target of Wnt signaling – Human Porcupine enzyme

Wnt signaling is a critical pathway involved in cell proliferation, differentiation and cellular homeostasis. To address treatment need of diseases associated with the dysregulated Wnt signaling like cancer, Alzheimer’s disease, Osteoporosis, Myocardial infarction etc.; small molecules that target the very first and unique component of the Wnt pathway, Porcupine enzyme, have been proven to be effective. Till date, none of the Porcupine inhibitor has reached to market. To design the novel Porcupine inhibitors, there was a need of crystal structure of Porcupine but in 2019, it was not resolved and deposited in the protein data bank. So, with an aim to predict its 3D structure, homology modeling study was performed using two distinct platforms; I-TASSER and Molsoft ICMPro so that we could use the best validated model for the designing of NCEs. Both the generated homology models were compared through Ramachandran plot, Protein health tool of Molsoft ICM and other tools available on metaserver, SAVES v6.0. Molsoft model was found better with 84.6 % residues in most favored region and only 0.3 % residues in disallowed region in Ramachandran plot in comparison to 75.9 % and 1.7 % residues respectively in I-TASSER model. The ICM model was further refined for 50 ns under MD simulation where it got stabilized after 36 ns. Quantification of protein was done by Radius of Gyration (ROG) where model showed larger ROG value of 23.25°A which indicated closely packed structure. Binding site in the predicted structure of Porcupine was identified using ICM binding pocket identifier and used for molecular docking of known Porcupine inhibitors like IWP-2, IWP-3, IWP-L6, and LKG974. Key binding site residues; Arg124, Phe257, Leu261, Val302, Trp305, Asn306, Ser310, Leu313, His341, Phen345, Ala349, Val350 etc. involved in the interaction were identified after MD simulation which can be useful in designing of novel porcupine inhibitors in future.

Development of Alpha-Synuclein protein model against therapeutic aspects of Parkinson's disease.

JOURNAL/ijpha/04.03/01363791-202456010-00007/figure1/v/2024-03-07T095025Z/r/image-tiff Parkinson's disease (PD) is the most common neurodegenerative disease caused by the steady depletion of dopamine in the striatum due to the loss of dopaminergic neurons. Most of the current therapeutics work on rebuilding the striatal dopamine level through oral administration of levodopa which stops the symptoms of PD. But there is a long-term motor complication with these dopamine precursors. Moreover, no preventive treatment is available for PD. Thus, before finding a therapeutic treatment for PD, it is necessary to first understand the basic cause of PD. Moreover, alpha-synuclein oligomerization can be the major factor in PD. From the UniProt database, protein information was extracted, and the model was designed by homology modeling technique and validated by the model validation server. Hence, the designed model has 96.5% most favored region and 0% disallowed region. Therefore, the model is stable based on RC plot parameters.

Climate Suitability for the Cultivation of Olive Trees in Iraq

Objectives: This research aims to assess the suitability and availability of climatic conditions for olive cultivation in Iraq. The study identifies the most and least suitable areas, along with intermediate areas, utilizing the ArcMap program for mapping and delineating agriculturally favorable regions.
 Methods: A descriptive approach was employed in this research, as an analytical approach was deemed essential for describing and analyzing data to attain scientific accuracy.
 Results: The research findings indicate that certain areas, namely Mosul, Erbil, Sulaymaniyah, and Kirkuk, exhibit high suitability for olive tree cultivation. The station at Al-Rutba demonstrates moderate feasibility, while Basra, Nasiriyah, Amarah, Baghdad, Diwaniyah, and Al-Hay are deemed unsuitable due to the absence of necessary climatic conditions for olive cultivation.
 Conclusions: The study concludes that climatic factors vary in their impact on olive cultivation and production. Temperature emerges as a significant contributor, while other factors such as humidity and wind play a limited role. Light is identified as a crucial factor affecting fruit size, composition, and color.

Design of Inhibitors That Target the Menin–Mixed-Lineage Leukemia Interaction

The prognosis of mixed-lineage leukemia (MLL) has remained a significant health concern, especially for infants. The minimal treatments available for this aggressive type of leukemia has been an ongoing problem. Chromosomal translocations of the KMT2A gene are known as MLL, which expresses MLL fusion proteins. A protein called menin is an important oncogenic cofactor for these MLL fusion proteins, thus providing a new avenue for treatments against this subset of acute leukemias. In this study, we report results using the structure-based drug design (SBDD) approach to discover potential novel MLL-mediated leukemia inhibitors from natural products against menin. The three-dimensional (3D) protein model was derived from Protein Databank (Protein ID: 4GQ4), and EasyModeller 4.0 and I-TASSER were used to fix missing residues during rebuilding. Out of the ten protein models generated (five from EasyModeller and I-TASSER each), one model was selected. The selected model demonstrated the most reasonable quality and had 75.5% of residues in the most favored regions, 18.3% of residues in additionally allowed regions, 3.3% of residues in generously allowed regions, and 2.9% of residues in disallowed regions. A ligand library containing 25,131 ligands from a Chinese database was virtually screened using AutoDock Vina, in addition to three known menin inhibitors. The top 10 compounds including ZINC000103526876, ZINC000095913861, ZINC000095912705, ZINC000085530497, ZINC000095912718, ZINC000070451048, ZINC000085530488, ZINC000095912706, ZINC000103580868, and ZINC000103584057 had binding energies of −11.0, −10.7, −10.6, −10.2, −10.2, −9.9, −9.9, −9.9, −9.9, and −9.9 kcal/mol, respectively. To confirm the stability of the menin–ligand complexes and the binding mechanisms, molecular dynamics simulations including molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) computations were performed. The amino acid residues that were found to be potentially crucial in ligand binding included Phe243, Met283, Cys246, Tyr281, Ala247, Ser160, Asn287, Asp185, Ser183, Tyr328, Asn249, His186, Leu182, Ile248, and Pro250. MI-2-2 and PubChem CIDs 71777742 and 36294 were shown to possess anti-menin properties; thus, this justifies a need to experimentally determine the activity of the identified compounds. The compounds identified herein were found to have good pharmacological profiles and had negligible toxicity. Additionally, these compounds were predicted as antileukemic, antineoplastic, chemopreventive, and apoptotic agents. The 10 natural compounds can be further explored as potential novel agents for the effective treatment of MLL-mediated leukemia.

(Invited) Mixed Conduction in Ceramic Electrolytes For Intermediate-Temperature Fuel Cells and Electrolyzers

High-temperature fuel cells and electrolyzers (e.g., T > 700 ˚C) rely on oxide electrolytes such as stabilized cubic zirconia that conduct a single defect, oxygen vacancies. Intermediate-temperature electrochemical cells (e.g., T < 650 ˚C) utilize mixed conducting ceramic electrolytes, that conduct multiple defects. Operating at T < 600 ˚C facilitates lower-cost interconnect materials and balance-of-plant components, but the mixed conductor behavior can reduce fuel cell voltages and lower electrolyzer faradaic efficiencies. Predicting behavior of these mixed conductors, even at open-circuit voltage, requires modeling the coupled transport of the multiple conducting defects in the electrolyte. Detailed models of mixed conductors coupled to porous electrode models can simulate cell performance over a broad range of operating conditions. This presentation highlights models of two types of cells with mixed conducting oxide electrolytes. Firstly, gadolinium-doped ceria (GDC) primarily conducts oxygen vacancies but also some electrons via a reduced-ceria small polaron, but it performs well in intermediate temperature solid-oxide fuel cells [1]. Secondly, yttrium-doped barium zirconates (BZY) primarily conducts protons but also oxygen vacancies and small polarons, which contribute to electronic leakage. Variants of BZY electrolytes perform well in fuel cells and electrolyzers [2-4]. This paper focuses on cell-level models of these mixed-conductors and how to identify favorable regions for high performance in fuel cells and electrolyzers. Zhu, A. Ashar, R.J. Kee, R.J. Braun, G.S. Jackson, “Physics-based model to represent the membrane-electrode assemblies of solid-oxide fuel cells based on gadolinium-doped ceria,” J. Electrochem. Soc., Under revision, 2023.J. Kee, S. Ricote, H. Zhu, R.J. Braun, G. Carins, J.E. Persky, “Perspectives on technical challenges and scaling considerations for tubular protonic-ceramic electrolysis cells and stacks ,” J. Electrochem. Soc. 169:054525 (2022).Zhu, Y. Shin, S. Ricote, R.J. Kee, “Defect incorporation and transport in dense BaZr0.8Y0.2O3-d membranes and their impact on hydrogen separation and compression,” J. Electrochem. Soc., Under revision, 2023.Zhu, S. Ricote, R.J. Kee, “Thermodynamics, transport, and electrochemistry in proton-conducting ceramic electrolysis cells,” in High Temperature Electrolysis, W. Sitte and R. Merkle, Editors, IOP Publishing, 2023.