Favorable Regions Research Articles

Sodium Enrichment of Mercury's Subsurface Through Diffusion

AbstractMercury's surface undergoes large temperature gradients between day and night, which repeats periodically over the same longitudes due to its 3:2 spin‐orbit resonance. This effect combined with the orbit's eccentricity, creates hot and cold geographic longitudes. The planet is covered with a highly porous regolith, allowing exospheric atoms to diffuse in depth. By using a 1‐D diffusion model, we studied the subsurface precipitation of gas over the cold and hot longitudes to understand gas retention. This work identifies the cold longitudes as favorable regions to form subsurface reservoirs closer to the surface. Moreover, subsurface reservoirs of adsorbates increase two to three times faster over cold longitudes than over hot longitudes, depending on the surface binding energy distribution of the atoms. We suggest that this result may be related to the observation that Mercury's sodium exosphere persists at later local times over the cold pole.

Design and computational analysis of a novel Azurin-BR2 chimeric protein against breast cancer.

Cancer is one of most lethal diseases worldwide. Chemotherapeutics and surgeries are among the treatment facilities available for curing cancer. However due to their negative impact on normal cells and drug resistance development, new treatment strategies have yet to be developed. Some microbial products exhibit therapeutic potential for treating cancer. Pseudomonas aeruginosa Azurins have shown anticancer effects against breast cancer without affecting normal cells. To enhance its cytotoxic effect and targeted delivery, we fused Azurin with a cell-penetrating peptide (BR2) through a rigid linker and evaluated its anticancer potential via in silico analysis. The prediction of the secondary and the tertiary structures and analysis of physiochemical properties of chimeric proteins were computationally performed. The Azurin-BR2 chimeric protein has a basic nature with a molecular weight of 16.8kDa. The quality indices and validation of chimeric proteins were performed with ERRAT2 and Ramachandran plot values, respectively. The quality index of the chimeric protein was predicted to be 81% to 84.6%, and residues residing in the most favoured region were identified. The HDOCK bioinformatics tool was used for docking a chimeric protein with a cancer suppressor protein p53. The results of the current study support that an Azurin-BR2 fusion protein has a high binding affinity for p53 can induce apoptosis in cancerous cells, and can be used in tumor-targeting therapy.

Sedimentary Environment and Organic Matter Accumulation of Continental Shales in Xiahuayuan Formation in Xuanlong Depression, Yanshan Area

The shale sedimentary environment is crucial for evaluating shale gas reservoirs and sweet spot zones. The Xiahuayuan Formation in the Xuanlong Depression of the Yanshan area is an important exploration and development region for shale gas due to its multi-layer dark shale. The paleosedimentary environment and organic matter accumulation mechanism of organic-rich shale were discussed through geochemical methods such as total organic carbon (TOC) content and elemental analysis. The results indicate that the shale exhibits a high TOC content. The Mo content and the P/Al and P/Ti ratios indicate that the primary productivity of the ancient lake is high. The Ceanom, V/(V + Ni) ratio and MoEF-UEF covariation model reveal that the sedimentary environment of shale is characterized by anoxic conditions. The ratios of K/Al and Ti/Al suggest significant variations in the input of fine-grained clay clastics and terrigenous clastics. The Ca/(Fe + Ca) and Sr/Ba ratios suggest that the paleowater was a freshwater environment. The paleoclimatic conditions, as indicated by CIA, Sr/Cu, and C-value, suggest a range from semi-humid to humid. The ratios of Rb/K and Mn/Ti reflect that the water primarily existed in a shore–shallow lake environment. The correlation analysis between organic matter accumulation and sedimentary environment parameters indicates that the primary factors influencing the organic matter accumulation in the Xiahuayuan Formation shale are redox conditions, terrigenous clastic input, paleoclimate conditions, and paleowater depth. The organic matter accumulation is characterized by a “preservation condition” pattern. This study provides theoretical support for the accumulation mechanism, potential evaluation of resources, and optimal selection of favorable regions for Jurassic shale gas in the Xuanlong Depression.

Strongly Enhanced Electronic Bandstructure Renormalization by Light in Nanoscale Strained Regions of Monolayer MoS2/Au(111) Heterostructures.

Understanding and controlling the photoexcited quasiparticle (QP) dynamics in monolayer (ML) transition metal dichalcogenides (TMDs) lays the foundation for exploring the strongly interacting, nonequilibrium two-dimensional (2D) QP and polaritonic states in these quantum materials and for harnessing the properties emerging from these states for optoelectronic applications. In this study, scanning tunneling microscopy/spectroscopy (STM/scanning tunneling spectroscopy) with light illumination at the tunneling junction is performed to investigate the QP dynamics in ML MoS2 on an Au(111) substrate with nanoscale corrugations. The corrugations on the surface of the substrate induce nanoscale local strain in the overlaying ML MoS2 single crystal, which result in energetically favorable spatial regions where photoexcited QPs, including excitons, trions, and electron-hole plasmas, accumulate. These strained regions exhibit pronounced electronic bandstructure renormalization as a function of the photoexcitation wavelength and intensity as well as the strain gradient, implying strong interplay among nanoscale structures, strain, and photoexcited QPs. In conjunction with the experimental work, we construct a theoretical framework that integrates nonuniform nanoscale strain into the electronic bandstructure of a ML MoS2 lattice using a tight-binding approach combined with first-principle calculations. This methodology enables better understanding of the experimental observation of photoexcited QP localization in the nanoscale strain-modulated electronic bandstructure landscape. Our findings illustrate the feasibility of utilizing nanoscale architectures and optical excitations to manipulate the local electronic bandstructure of ML TMDs and to enhance the many-body interactions of excitons, which is promising for the development of nanoscale energy-adjustable optoelectronic and photonic technologies, including quantum emitters and solid-state quantum simulators for interacting exciton polaritons based on engineered periodic nanoscale trapping potentials.

Genomic estimated selection criteria and parental contributions in parent selection increase genetic gain of maternal haploid inducers in maize.

Parental combinations determined by genomic estimated usefulness and parental contributions of the lines in bridging population can enhance the genetic gain of traits of interest in maternal haploid inducer breeding. Parent selection in crosses aligns well with the quantitative trait performance in the progenies. We herein take advantage of estimated genetic values (EGV) and usefulness criteria (UC) of bi-parental combinations by genomic prediction (GP) to compare the empirical performance of doubled haploid inducer (DHI) progenies of eight elite inducers crosses in a half-diallel. We used parental contribution and discovery of superiors from elite-by-historical bridging populations to enhance genetic gain for long-term selection. In this empirical study, the narrow-sense heritabilities of four traits of interest (Days to flowering, DTF; haploid induction rate, HIR; plant height, PHT; Total primary branch length, PBL) in DHI population were 0.81, 0.71, 0.45 and 0.46, respectively. The genomic estimated EGV_Mid/Mean and EGV/UC_Inferior was significantly correlated with the sample mean of progenies and inferiors in four traits in the breeding and bridging population. EGV/UC_Superior were significantly correlated with the mean of superiors in DTF, PHT, and PBL in breeding and bridging populations. The genomic estimated parent contributions in DH progenies of bridging populations enabled discovery of favorable genome region from historical inducers to improve the genetic gain of HIR for long-term selection.

Designing of a Novel Aerolysin-based Multiepitope Vaccine against Aeromonas hydrophila Isolated from Osphronemus goramy Using Reverse Vaccinology: an in Silico Approaches

Graphical Abstract Highlight Research The study aims to develop a multi-epitope vaccine (MEV) against A. hydrophila by targeting the aerolysin toxin, a key virulence factor responsible for infections in fish and humans. Computational methods identified and optimized B-cell and T-cell epitopes, focusing on their ability to trigger immune responses without causing toxicity or allergenicity. In silico simulations demonstrated that the MEV has a strong binding affinity to immune receptors like TLR-4, MHC-I, and MHC-II, indicating its potential to induce robust cellular and humoral immunity. Structural analysis of the MEV showed a stable 3D conformation, with most residues in favorable regions, ensuring stability during immune activation. The MEV could enhance disease control in aquaculture and reduce human infection risks, offering a promising solution to address antibiotic resistance and the absence of effective vaccines. Abstract Aeromonas hydrophila, gram-negative, is a major pathogen responsible for various diseases in mammals, reptiles, amphibia, and vertebrates, including fish and humans. Targeting the specific toxin aerolysin in A. hydrophila is crucial to address antibiotic resistance and the lack of adequate and protective vaccines against this intracellular pathogen. This study aimed to identify a multi-epitope vaccination (MEV) candidate targeting A. hydrophila aerolysin toxin to combat the disease effectively. Standard biochemical characterization methods and sequencing of the 16S rRNA, rpoB, and aerA genes identified the isolate AHSA1 as A. hydrophila. Subsequently, we identified B and T cell epitopes on the aerolysin protein and separately predicted MHC-I and MHC-II epitopes. The epitopes are then evaluated for toxicity, antigenicity, allergenicity, and solubility. The vaccine design integrated multi-epitope-based constructs, utilizing specialized linkers (GPGPG) and EAAAK linkers to connect epitope peptides with adjuvants in the cholera toxin B component, thereby enhancing immunogenicity. Ramachandran plots showed that 85.25% of the residues were located in the most favorable regions, which was followed by the generously allowed zone (1.30%), the additional allowed regions (10.80%), and the forbidden regions (2.65%), thus confirming the feasibility of the modeled vaccine design. Based on docking simulations, MEV had the highest binding and interaction energies with TLR-4, TLR-9, MHC-I, and MHC-II (-1081.4, -723.2, 866.2, -9043.3 kcal/mol). Based on computational modelling, we expect the Aerolysin MEV candidate design to activate diverse immune mechanisms, stimulate robust responses against A. hydrophila, and maintain safety. The significant solubility, absence of toxicity or allergic response, and minimal side effects in animal testing all contribute to the potential clinical utility of this vaccine candidate.

Fueling Costa Rica’s green hydrogen future: A financial roadmap for global leadership

This study evaluates the financial viability and scalability of green hydrogen production in Costa Rica, focusing on solar and wind energy. The research analyzes seven key provinces using Global Horizontal Irradiance (GHI) and wind speed data to assess energy potential. Monte Carlo simulations were employed to calculate the Net Present Value (NPV), hydrogen production costs, and economic sustainability over multiple project lifetimes. Guanacaste, with solar irradiance of 5.49 kWh/m2/day and wind speeds of 6.59 m/s, emerges as the most favorable region. The analysis reveals an NPV of $1,519.79 USD for onshore wind and $2,320.24 USD for offshore wind over 10 years. These values increase significantly for longer lifetimes, with 25-year NPVs of $3,687.40 USD for onshore wind and $5,890.72 USD for offshore wind, and 50-year NPVs reaching $7,456.21 USD and $11,560.38 USD, respectively. Hydrogen production costs are estimated at $49,696.75 USD from solar and $14,923.19 USD from wind energy. Despite its potential, high costs remain a challenge, requiring policy incentives, international cooperation, and green bonds to drive down costs and scale production. The study offers crucial insights for policymakers, investors, and researchers to support Costa Rica’s leadership in the global green hydrogen economy. Statement of SignificanceThe global shift toward renewable energy is critical for meeting decarbonization goals, and green hydrogen is emerging as a vital solution for sectors that are hard to electrify, such as transportation and heavy industry. However, the high cost of green hydrogen production poses a significant barrier to its widespread adoption. This study tackles the critical research problem of how to make green hydrogen economically viable by evaluating the potential of Costa Rica’s renewable energy resources—specifically solar PV and wind energy—to support large-scale hydrogen production.By integrating Monte Carlo simulations with region-specific financial analysis, this study provides a thorough assessment of hydrogen production costs and infrastructure requirements across Costa Rica’s provinces. The significance of this work lies in its localized approach, offering actionable insights into how a developing country with abundant renewable energy can position itself as a global leader in green hydrogen production. This research provides evidence that while current hydrogen production costs are higher than global targets, Costa Rica’s renewable resources present a strong foundation for future growth with the right policy interventions.The study’s findings have substantial implications for future research, policy, and investment strategies. By highlighting the financial and technological challenges, as well as offering potential solutions through international partnerships and innovative financing models, this research paves the way for Costa Rica and similar countries to contribute meaningfully to the global green hydrogen economy.

Computational Analysis and Inhibition Study of Carbonic Anhydrase from Azadirachta indica Leaves

Introduction: Carbonic anhydrase (CA) has been an enzyme of great interest for its application in carbon dioxide sequestration. A total of 66 protein sequences of plant CAs were computationally analyzed and submitted to bioinformatics for motif and domain identification, multiple sequence alignment, and phylogenetic analysis. Method: The current work aims to extend knowledge among researchers in better understanding the structure of AZDI CA by analyzing its physicochemical properties, secondary structure prediction, 3D modeling of protein sequence, and its validation using a variety of conventional computational methods. Results: The accuracy of the predicted 3D structure checked by the Ramachandran plot generated by PROCHECK showed that for the CA protein sequence 93.1%, was observed in the most favored regions, VERIFY 3D 69.44% and ERRAT 98.09%. AZDI CA was docked with various anions and sulphonamide derivatives to study their inhibitory effect and calculate binding energy by using Autodock 4.2. Ethoxzolamide is found to be a better inhibitor of AZDI CA with binding energy -8.71 kCal/mol and KI value 0.0004 mM. Further MD simulation of the docked complex of ethoxzolamide with AZDI CA was done using SCHRODINGER DESMOND software. Conclusion: The outcomes of this research will have a significant influence on biochemistry, biotechnology, and potential applications of AZDI CA and similar plant CAs in determining potent inhibitors for drug targets in treating various diseases.

Structural Prediction and Antigenic Analysis of ROP18, MIC4, and SAG1 Proteins to Improve Vaccine Design against Toxoplasma gondii: An In silico Approach.

Toxoplasmosis is a cosmopolitan infectious disease in warm-blooded mammals that poses a serious worldwide threat due to the lack of effective medications and vaccines. The purpose of this study was to design a multi-epitope vaccine using several bioinfor-matics approaches against the antigens of Toxoplasma gondii (T. gondii). Three proteins of T. gondii, including ROP18, MIC4, and SAG1, were analyzed to predict the most dominant B- and T-cell epitopes. Finally, we designed a chimeric immunogen RMS (ROP18, MIC4, and SAG1) using some domains of ROP18 (N377-E546), MIC4 (D302-G471), and SAG1 (T130-L299) linked by rigid linker A (EAAAK) A. Physicochemical prop-erties, secondary and tertiary structures, antigenicity, and allergenicity of RMS were predicted utilizing immunoinformatic tools and servers. RMS protein had 545 amino acids with a molecular weight (MW) of 58,833.46 Da and a theoretical isoelectric point (IP) of 6.47. The secondary structure of RMS protein con-tained 21.28% alpha-helix, 24.59% extended strand, and 54.13% random coil. In addition, eval-uation of antigenicity and allergenicity showed the protein to be an immunogen and non-aller-gen. The results of the Ramachandran plot indicated that 76.4%, 12.9%, and 10.7% of amino acid residues were incorporated in the favored, allowed, and outlier regions, respectively. ΔG of the best-predicted mRNA secondary structure was -593.80 kcal/mol, which indicated that a stable loop was not formed at the 5' end. Finally, the accuracy and precision of the in silico analysis must be confirmed by successful heterologous expression and experimental studies.

Numerical analysis of blood flow in a branched modular stent-graft for aneurysms covering all zones of the aortic arch.

Due to the anatomical complexity of the aortic arch for the development of stent-grafts for total repair, this region remains without a validated and routinely used endovascular option. In this work, a modular stent-graft for aneurysms that covers all aortic arch zones, proposed by us and previously structurally evaluated, was evaluated from the point of view of haemodynamics using fluid-structural numerical simulations. Blood was assumed to be non-Newtonian shear-thinning using the Carreau model, and the arterial wall was assumed to be anisotropic hyperelastic using the Holzapfel model. Nitinol and expanded polytetrafluoroethylene (PTFE-e) were used as materials for the stents and the graft, respectively. Nitinol was modelled as a superelastic material with shape memory by the Auricchio model, and PTFE-e was modelled as an isotropic linear elastic material. To validate the numerical model, a silicone model representative of the aneurysmal aorta was subjected to tests on an experimental bench representative of the circulatory system. The numerical results showed that the stent-graft restored flow behaviour, making it less oscillatory, but increasing the strain rate, turbulence kinetic energy, and viscosity compared to the pathological case. Taking the mean of the entire cycle, the increase in turbulence kinetic energy was 198.82% in the brachiocephalic trunk, 144.63% in the left common carotid artery and 284.03% in the left subclavian artery after stent-graft implantation. Based on wall shear stress parameters, it was possible to identify that the internal branches of the stent-graft and the stent-graft fixation sites in the artery were the most favourable regions for the deposition and accumulation of thrombus. In these regions, the oscillating shear index reached the maximum value of 0.5 and the time-averaged wall shear stress was close to zero, which led the relative residence time to reach values above 15 Pa-1. The stent-graft was able to preserve flow in the supra-aortic branches.

From fringe to basin: unravelling the survival strategies of Calanus hyperboreus and C. glacialis in the Arctic Ocean

The large calanoids Calanus hyperboreus and C. glacialis dominate the zooplankton biomass in the central Arctic Ocean (CAO), but the absence of early life stages has raised speculation whether they complete their life cycle there, or whether they represent expatriates advected from adjacent regions. Our study, conducted across 2 transects of the CAO during fall 2011, focused on the distribution, stage composition, dry weight, individual lipid content, and egg production of these species. Although reproductive activity and early developmental stages were observed only on the fringes of the deep basins, late-stage copepodite and adult female abundances remained steady across the study area for C. glacialis and increased away from the shelves for C. hyperboreus. We found no decline in lipid content or dry weight in adult C. glacialis away from productive regions and only a minor reduction in adult C. hyperboreus. However, the lipid content and dry weight in C5 copepodites significantly decreased away from the shelf break, particularly in C. hyperboreus. This suggests that although early life stages struggle to survive in the resource-limited conditions of the deep CAO and even subadults remain vulnerable to starvation, adults have the resilience to survive long enough to be eventually transported by ocean currents to more favourable regions for reproduction. As such, we suggest that both species of Calanus are neither ‘residents’ nor ‘expatriates’ in the Arctic basins, but rather ontogenetic migrants that take advantage of different habitats within the Arctic Ocean to maximise their survival and reproductive success.

Design and computational analysis of a novel Leptulipin-p28 fusion protein as a multitarget anticancer therapy in breast cancer.

The search for novel therapeutic agents to treat breast cancer has compelled the development of fusion proteins that synergize the functional benefits of different bioactive peptides. Leptulipin, derived from scorpion venom, exhibits antitumor properties. On the other hand, p28, a peptide from the bacterial protein azurin, enhances cell penetration. The current study investigated the design and computational evaluation of a Leptulipin-p28 fusion protein for breast cancer treatment. The amino acid sequences of Leptulipin and p28 were joined via a rigid linker to maintain structural and functional integrity. Secondary and tertiary structure predictions were performed using online servers of GOR-IV and I-TASSER. Physicochemical properties and solubility were analyzed using ProtParam and Protein-Sol. Validation and quality assessment of the fusion protein were confirmed through Rampage and ERRAT2. Finally, the fusion protein was docked with 2 receptors (VEGFR and Cadherin) and docked complexes were simulated on GROMACS. The Leptulipin-p28 fusion protein exhibited a stable structure exhibiting a high quality score of 92 on ERRAT and Ramachandran plot analysis highlighting 76.3% of residues in the favorable region. Docking studies with VEGFR and Cadherin receptors followed by 100ns simulations on GROMACS showed stable complex formation. Molecular dynamics simulations confirmed the stability and robust interaction of the fusion protein-receptor complexes over time. The computational analysis indicates that the Leptulipin-p28 fusion protein holds promise as a multitarget therapeutic agent in breast cancer. The current findings warrant further investigation through in vitro and in vivo studies to validate the current outcomes.

Identification of feasible regions for managed aquifer recharge in the Republic of Cyprus using a co-participative multi-criteria decision analysis

This study proposes an integrated approach that aims at finding locations which are eligible for Managed Aquifer Recharge (MAR) installation in Cyprus via the active involvement of key stakeholders of MAR-related sectors during all stages of the decision process to ensure the validity of the outcomes. The MAR problem is jointly formulated with the key stakeholders according to the site needs by introducing the so-called "MAR typology" concept, consisting of the recharge objective, the recharge method, and the available water sources. Tertiary-treated wastewater is adapted as the water source, which is recharged in aquifers via recharge ponds for irrigation. Various sources of information have been considered for assessing the degree of feasibility, aggregated in three thematic clusters (feasibility components), namely intrinsic site-suitability, the availability of water resources for MAR purposes, and water demand. Twelve criteria have been selected jointly with key stakeholders to evaluate the feasibility components via a GIS-MCDA process. Seven of these criteria are associated with the intrinsic suitability of a region (aquifer, land-use, and topographical properties), and five criteria are associated with the amount of water available for MAR (characteristics of the water source and evapotranspiration) and the crop irrigation needs. Stakeholder meetings were conducted to determine weights for each criterion and thematic cluster, leading to thematic and feasibility maps. The results demonstrate large discrepancies among the feasibility components in terms of their spatial variation and the location where the most favourable regions are present. Smoother profiles are observed for intrinsic suitability compared to the other thematic layers, partly attributed to the use of a larger number of criteria. Sensitivity analysis demonstrates that the MAR-favourable regions are weakly influenced by the variation of the relevant importance among the thematic layers, being mostly present in the vicinity of the southern and south-eastern coastlines.

Analysis of suitable regions for microalgae cultivation and harvesting potential for carbon capture: A global feasibility study

Microalgae, have the ability to capture CO2 and the potential for biofuel production. However, scaling up capturing carbon by microalgae is not feasible worldwide because of difference in weather conditions. Hence, identifying favorable regions for capturing carbon by microalgae is the initial step in commercializing this industry. In this research, a global feasibility study has been conducted to analyse the potential of microalgae cultivation and harvesting to capture CO2, based on carbon emissions, weather conditions, and the boundary of countries. A total of 454 cities were selected for this research, and the amount of microalgae productivity and carbon capture rate in each area was calculated according to the optimal environmental conditions for microalgae growth. Methodology and results have been illustrated using Geographical Information System (ArcGIS 10.8) to provide better visual insight for researchers. The results showed that the average microalgae productivity in Open Ponds (OP) and Tubular Photobioreactors (TPBR) is 132.63 T/ha/y and 78.26 kg/m3/y, respectively. Additionally, the average carbon capture rate by microalgae in OP and TPBR is 37.60 T/ha/y and 40.83 kg/m3/y, respectively. The study also revealed that microalgae will have a higher productivity in OP than in TPBR for 158 regions according to the first scenario, while the number of these areas will decrease to 58 and 29 under the second and third scenarios, respectively. Moreover, the global average potential energy content resulting from microalgae cultivation in OP is 4.854*106 MJ/ha/y. Therefore, selecting suitable regions regarding weather condition and type of cultivation system, is the most significant factors in outdoor commercial scaling up of carbon capture by microalgae.

Implementation and validation of a generalized wall stress function

The generalized wall function by Shih et al. [Report No. M-1999-209398 (1999)], which accounts for non-equilibrium effects by the presence of favorable and adverse pressure gradients in turbulent flows, is addressed with the aim of performing high Reynolds number large-eddy simulations of the wall-bounded flow. The model uses a corrected law of the wall with a pressure gradient contribution to approximate the wall stress and applies to the entire viscous layer, buffer layer, and inertial region. A fully developed channel flow is first tested to validate the solver and model implementation, and then the wall function is assessed for the flow over a periodic hill. Wall-resolved simulations are in good agreement with reference results. A priori investigation with own experimental results corroborates the mathematical form of the model and suggests using different coefficients. The wall-modeled simulations show that the implemented wall model is able to improve the wall shear stress predictions compared to a standard equilibrium wall model. It corrects the underestimation of wall shear stresses by equilibrium models in the favorable pressure gradient region and the overestimation of wall shear stresses in the adverse pressure gradient region. The positions of the separation and reattachment points are also in good agreement with reference results. Furthermore, the prediction of the wall shear stress maximum in the favorable pressure gradient zone at the windward side of the hill is quite robust against coarsening the wall-normal grid spacing.

Structural characterization and biological activity evaluation of Magnoflorine alkaloid, a potential anticonvulsant agent

Magnoflorine (MGF), an isoquinoline alkaloid, emerges as a quaternary aporphine alkaloid derived from L-tyrosine amino acid, found in families Magnoliaceae plants and it presents important biological activity being noted for its effect on the nervous system. In this work, a deep study of structural, vibrational and electronic properties has been carried out for the MGF. From Potential Energy Surface (PES) scan the most stable conformer of alkaloid was identified and geometrical parameters were determined by Density Functional Theory (DFT) using B3LYP/6–311++G** method. A complete vibrational assignment of the normal modes was theoretical and experimentally achieved from FT-IR and Raman spectroscopies and scaled SQM methodology. Electronic transitions observed in UV–visible spectrum in aqueous medium were identified using TD-DFT methodology, with the π→π* transition being the most probable UV signal. The MEPs, the electric charge distribution along with the HOMO and LUMO frontier orbitals were analyzed and the GAP energy values justified the stability of the molecule in aqueous medium. The molecular electrostatic potential map reveals the most favourable region for electrophilic attack on MGF. Molecular docking was used to analyze the anxiolytic biological activity of the title molecule on the GABAA receptor. The results suggest an intermolecular binding capability of MFG toward both intracellular and extracellular domains of GABAA receptor, and the extracellular domain presents a higher affinity by alkaloid. Finally, the biological study infers that MGF could be used as a potential anxiolytic compound.

Virtual Discovery of Immune-Stimulating Epitopes in Chikungunya Virus for Vaccine Design

Epitope identification is a key step in vaccine development, and this can be achieved much faster and less expensively with in silico methods, compared to traditional methods for vaccine production. In silico methods applied in this research utilised both bioinformatics and immunoinformatics approaches for chikungunya virus vaccine design, which involved the retrieval of sequences from databases, and identification of conserved regions within the sequences by multiple sequence alignment on the MEGA X software (Pennsylvania State University, State College, USA). The epitopes in the conserved regions were selected, and various immunological predictions and screenings were carried out by employing immunological databases and tools. This process identifies epitopes such as conservation of cytotoxic T lymphocyte, helper T lymphocytes, and B cell epitopes. The primary, secondary, and tertiary structure of the vaccine was also predicted using structure predicting servers, and finally, the vaccine candidate was docked to toll-like receptor 4 to study its binding affinity and configuration. A total of 125 conserved antigenic epitopes were selected from capsid, 6K, and E1 proteins, which were found to be non-allergens and conform to acceptable physicochemical standards, as reported by other authors with similar work. The epitopes were predicted to be capable of inducing cytotoxic T lymphocytes, helper T lymphocytes, and B cell production. Construction of secondary structure was done using the Self-Optimized Prediction Method with Alignment (SOPMA), which predicted 17.96% α-helices, and 4.69% β-turns, among others. Predicting the tertiary structure provided five models, of which Model 1 was selected on the bases of its confidential score of 0.59, estimated TM-score of 0.79±0.09, and root mean square deviation of 8.0±4.4Å. Validity analysis revealed a Ramachandran plot where 97.2% of the vaccine residue was within the favoured region, and the peptide showed a Z-score of -1.52. The predicted peptide effectively docked with toll-like receptor 4 with a binding energy of -1,072.8. From the data obtained, it was revealed that the selected epitopes are highly immunogenic, non-allergenic, conform to native protein, and form a peptide capable of vaccine application. The authors can conclude this is a promising candidate for vaccine design and development.

Self-interacting forbidden dark matter under a cannibally co-decaying phase

In a usual dark matter (DM) model without a huge mass difference between the DM and lighter mediator, using the coupling strength suitable for having the correct relic density, the resulting self-interaction becomes several orders of magnitude smaller than that required to interpret the small-scale structures. We present a framework that can offer a solution for this point. We consider a model that contains the vector DM and a heavier but unstable Higgs-like scalar in the hidden sector. When the temperature drops below ~ mDM, the hidden sector, which is thermally decoupled from the visible sector, enters a cannibal phase, during which the DM density is depleted with the out-of-equilibrium decay of the scalar. The favored parameter region, giving the correct relic density and the proper size of self-interactions, shows the scalar-to-DM mass ratio ∈ [1.1, 1.33] and the scalar mass ∈ [9, 114] MeV. A sizable parameter space still survives the most current constraints and can be further probed by the near future NA62 beam dump experiment.

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.