Computer Simulation Model Research Articles

Measurement variability of radiologists when measuring brain tumors.

In oncology trials, response evaluation criteria are pivotal in developing new treatments. This study examines the influence of measurement variability in brain lesions on response classification, considering long-standing cut-offs for progression and response were determined before the era of submillimeter resolutions of medical imaging. We replicate a key study using modern radiological tools. Sixteen radiologists were tasked with measuring twelve near-spherical brain tumors using visual estimation (eyeballing), diameter measurements and artificial intelligence (AI) assisted segmentations. Analyses for inter- and intraobserver variability from the original were replicated. Additionally, we researched the effect of measurement error on the misclassification of progressive disease using a computer simulation model. The combined effect of intra- and interobserver error varied between 13.6 and 22.2% for eyeballing and 6.8-7.2% for diameter measurement, using AI-assisted segmentation as reference. We observed erroneously declared progression (cut-off at 20% increase) in repeat measurements of the same tumor in 25.5% of instances for eyeballing and in 1.1% for diameter measurements. Response (cut-off at 30% decrease) was erroneously declared in 12.3% for eyeballing and in 0% for diameter measurements. The simulation model demonstrated a more pronounced impact of measurement error on cases with fewer total number of lesions. This study provides a minimum expected measurement error using real-world data. The impact of measurement error on response evaluation criteria misclassification in brain lesions was most pronounced for eyeballing. Future research should focus on measurement error for different tumor types and assess its impact on response classification during patient follow-up.

Identification of 8-(2-methyl phenyl)-9H-benzo[f]indeno[2,1-c]quinolin-9-one (C-5635020) as a novel and selective TGFβ RII kinase inhibitor for breast cancer therapy.

Transforming growth factor-beta (TGF-β) plays a pivotal role in breast development by modulating tissue composition during the developmental phase. The TGFβ type II receptor (TGFβ RII) is implicated in breast cancer and represents a valuable therapeutic target. Due to the off-target side effects of many existing TGFβI/TGFβ RII inhibitors, a more targeted approach to drug discovery is necessary. This study used computational modeling and molecular dynamics simulations to screen the ChemBridge small molecule library against TGFβ RII. This study employed high-throughput virtual screening, molecular dynamics simulations, and binding free energy calculations to identify potential inhibitors targeting TGF-β RII. MDA-MB 231 and MCF-7 breast cancer cells were used in anti-proliferative, tans-endothelial migration, and flow cytometric assays for in vitro validations. We identified 8-(2-methylphenyl)-9H-benzo[f]indeno[2,1-c]quinolin-9-one (C-5635020) as a potent and selective inhibitor. Protein-ligand modeling analysis revealed that C-5635020 targets the kinase domain of TGFβ RII with superior binding affinities compared to the standard drug, staurosporine. Computational results suggest that C-5635020 selectively binds and inhibits TGFβ RII activity, thereby controlling cell proliferation in breast cancer. In vitro, experiments corroborated these predictions, where C-5635020 inhibited TGFβ RII and p-Smad 2/3 positive population in MDAMB-231 and MCF-7cells. The compound dose-dependently inhibited cell proliferation, trans-endothelial migration, and increased apoptosis in both breast cancer cell lines. The strong binding affinity, stability, and favorable thermodynamics of C-5635020 with established in vitro efficacy highlight its potential as a lead compound for further preclinical and clinical developments for breast cancer treatment.

Computer simulation model for estimating the number of ship collision candidates in the randomly distributed sailing directions scenario

Computer simulation model for estimating the number of ship collision candidates in the randomly distributed sailing directions scenario

Concurrent Micra Leadless Pacemaker Implantation and AVN Ablation: Computer Modeling of Novel Risk Mitigation Strategy.

Concurrent Micra leadless pacemaker (Medtronic, Minneapolis, Minnesota) implantation and atrioventricular node (AVN) ablation has been shown to be feasible and safe in patients with symptomatic, drug-refractory atrial fibrillation (AF). However, major complications within the 30 days after concurrent Micra implantation and AVN ablation have been reported. We evaluated the efficacy and safety of the concurrent procedure at our institution. We conducted a single-center, retrospective case series of patients who underwent concurrent Micra implantation and radiofrequency (RF) AVN ablation from January 2019 to May 2023. A simulated computer model was created to characterize the interaction between the dissipated power at the Micra cathodal electrode as a function of the distance between the RF ablation catheter and the location of the return electrode. Fifteen patients were included. Most were elderly, White, female, and had persistent AF. One had transient, acute loss of ventricular capture that resulted in asystole and required emergent pacing from the ablation catheter. A proposed strategy of moving the RF return electrode to a cranial position from a caudal position was shown by computer modeling to direct more RF current away from the Micra and lower the dissipated power at the Micra cathodal electrode. Concurrent Micra implantation and AVN ablation is feasible and safe and has high procedural success. An acute rise in pacing threshold can occur from RF energy, resulting in asystole. Computer modeling showed that placing the RF return electrode in the cranial position resulted in lower dissipated power at the Micra cathodal electrode.

Systematization of steam cultivators

BACKGROUND: When exposed to the soil during cultivation, the moisture and air permeability of the formation improves, which favor the activity of microorganisms and the growth and development of plants. The increase in the production of agricultural crop production directly depends on the level of technology of the new generation. Therefore, the improvement of their designs in order to increase the level of technology of the new generation is an urgent task of the agro-industrial complex. METHODS: The method of monographic examination of the structures of steam cultivators, both of the machine as a whole and separately of the main working bodies, was used on the basis of well-known scientific research and the results of state tests. Thus, the really working steam cultivators recommended for use in agricultural production were considered. In addition, the patented designs of the working bodies of steam cultivators were analyzed. The efficiency of steam cultivators was determined based on the results of state tests of the Volga, Northwestern, Siberian, Kuban, North Caucasian, Central Chernozem, Kirov, Vladimir MIS over the past 10 years. RESULTS: The article provides an overview of steam cultivators and their designs. The classification of cultivators by 3 types is given: by the type of main working bodies (paws); by the type of additional working bodies (rollers, harrows, rods); by the type of attachment to the tractor (trailed, mounted). Their advantages and disadvantages are considered. An overview of research on improving the designs of steam cultivators to improve the quality and reduce energy consumption for tillage is given. The working bodies (paws), the frame in terms of the placement of the main working bodies, the rack and the design of additional working bodies of steam cultivators are being modernized. Theoretical studies on improving the efficiency of cultivators are considered. The conditions for achieving and improving the quality of tillage with a steam cultivator are revealed by determining the relationship of parameters with the indicators of the technological process. The application of computer simulation modeling in solving theoretical problems of research of new working bodies is considered, advantages and disadvantages are revealed. CONCLUSIONS: The systematization of steam cultivators presented in this article will allow us to determine ways to further improve them.

Analysis of Mechanisms of Mandible Fractures by Lateral Impact: A Biomechanical Approach Using Finite Element Models

Background/Aim: The purpose of this study was to reproduce a lateral fall using a computer simulation model and to clarify the circumstances of mandible fracture caused by a lateral impact. Material and methods: Fall scenarios were reconstructed using a computer simulation with finite element models. The fall condition was set as a fall from the head direction, which would cause facial injuries. In each simulation, the effective plastic strain of the mandible and its site were determined. Analysis of variance was performed to determine which factors had a significant effect on the maximum effective plastic strain of the mandible. Results: Significant differences with p-values less than 0.001 were found for the following factors: pitch angle, lateral bending angle, impact object, combination of pitch angle and lateral bending angle, and combination of pitch angle and impact object. In most cases with higher values of effective plastic strain, which can cause mandibular fractures, the site was found at the condylar process or mandibular angle of the attacked side. Conclusion: If the patient falls laterally and their face makes contact with a protruding object, medical professionals can predict fractures of the upper part of the mandibular angle and the condyle of the affected side.

Computational simulation study of flow dynamics in plga microsphere generation using lab-on-a-chip for prostatic embolisation

Abstract Introduction Transarterial chemoembolisation is a therapeutic approach for vascularised tumours, such as prostate tumours, involving the administration of drug-eluting microspheres. Its efficacy arises from the combined effects of anti-tumour drugs and blood flow occlusion. Microspheres are now commonly generated using lab-on-a-chip systems. This study presents a computational simulation model to evaluate the input flow conditions required to produce PLGA microspheres of specific sizes. Methods The simulations were conducted using COMSOL Multiphysics 5.5, with rheological data for PLGA and the continuous phase derived from prior studies. The chip design was based on standard commercial double-T models, featuring 300 µm inlet and 500 µm outlet channels. Eight simulations were performed, varying the input velocity ratio (Rv = Vc/Vd) while maintaining a constant Vd of 8 mm/s. The evaluated ratios included: 1.500, 1.750, 1.875, 2.000, 2.125, 2.250, 2.375, and 2.500. Results The findings indicate that no microspheres are generated at Rv values below 1.875 or above 2.375. For intermediate ratios, microsphere sizes ranged from 240 to 275 µm, with droplet generation rates of 32 to 37 spheres per second for Rv values between 1.750 and 2.250, respectively. Conclusion This computational simulation system provides a rapid method for evaluating flow conditions. For the proposed chip geometry, it is possible to generate an average of 35 microspheres per second with a diameter of 250 µm in PLGA.

The Current and Future Burden of Long COVID in the United States (U.S.).

Long COVID, which affects an estimated 44.69-48.04 million people in the U.S., is an ongoing public health concern that will continue to grow as SARS-CoV-2 continues to spread. We developed a computational simulation model representing the clinical course, the health effects, and the associated costs of a person with Long COVID. Simulations show that the average total cost of a Long COVID case can range from $5,084-$11,646 (assuming symptoms only last 1 year) with 92.5%-95.2% of these costs being productivity losses. Therefore, the current number of Long COVID cases could end up costing society at least $2.01-$6.56 billion, employers at least $1.99-$6.49 billion in productivity losses, and third-party payers $21-68.5 million annually (6%-20% probability of developing Long COVID). These cases would accrue 35,808-121,259 QALYs lost and 13,484-45,468 DALYs. Moreover, each year, there may be an additional $698.5 million in total costs, 14,685 QALYs lost, and 5,628 DALYs, if the incidence of COVID is 100 per 10,000 persons (similar to that seen in 2023). Every 10-point increase in COVID incidence results in an additional $365 million in total costs, 5,070 QALYs lost, and 1,900 DALYs each year. The current health and economic burden of Long COVID may already exceed that of a number of other chronic disease and will continue to grow each year as there are more and more COVID-19 cases. This could be a significant drain on businesses, third party payers, the healthcare system, and all of society.

Outer hair cells stir cochlear fluids.

We hypothesized that active outer hair cells drive cochlear fluid circulation. The hypothesis was tested by delivering the neurotoxin, kainic acid, to the intact round window of young gerbil cochleae while monitoring auditory responses in the cochlear nucleus. Sounds presented at a modest level significantly expedited kainic acid delivery. When outer-hair-cell motility was suppressed by salicylate, the facilitation effect was compromised. A low-frequency tone was more effective than broadband noise, especially for drug delivery to apical locations. Computational model simulations provided the physical basis for our observation, which incorporated solute diffusion, fluid advection, fluid-structure interaction, and outer-hair-cell motility. Active outer hair cells deformed the organ of Corti like a peristaltic tube to generate apically streaming flows along the tunnel of Corti and basally streaming flows along the scala tympani. Our measurements and simulations coherently suggest that active outer hair cells in the tail region of cochlear traveling waves drive cochlear fluid circulation.

Comparative Analysis of Spreader Grafts and Spreader Flaps on Intranasal Drug Delivery Efficiency to Posterolateral Nasal Wall

Background: This study compared the impact of spreader grafts (SG) and spreader flaps (SF) on the transport of intranasal drug delivery to target the posterolateral nasal wall. Method: SG and SF were each performed in sequence on two cadaveric specimens after soft tissue elevation technique. Computed tomography scans were acquired following each procedure to generate anatomic models for computational fluid dynamics simulation of intranasal sprays under the following conditions: inhalation rate (15 and 30 L/min), spray velocity (1, 5, and 10 m/s), spray released location (center, lateral, medial, top, and bottom), head position (upright, tilted-forward, tilted-backward, and supine), and particle diameter (1-100 µm). Percentage of particles deposited on the posterolateral nasal wall were calculated. Results: For Specimen 1, highest posterolateral wall depositions were Pre-Op: left = 74%, right = 74%; SF: left = 53%, right = 22%; SG: left = 60%, right = 61%. For Specimen 2, highest posterolateral wall depositions were Pre-Op: left = 25%, right = 83%; SF: left = 29%, right = 76%; SG: left = 14%, right = 72%. In general, posterolateral wall deposition was higher at 30 L/min inhalation rate and at 1 m/s spray velocity. Conclusions: Drug delivery targeting the posterolateral nasal wall appears to be dependent on many factors. However, midvault nasal reconstruction does not increase drug delivery to the posterolateral nasal wall.

Research on Artificial Intelligence Neural Model Based on Human Neuroscience Simulation: A Case Study of Orthopedic Medical Robots and Economic Discussion

Simulation computer models of human neuroscience are widely used in artificial intelligence. The extensive use of surgical robots in China makes the simulation model of neuroscience have a broader stage in economic development. We have more usage for medical image recognition and surgical robot programming. We try to analyze the neural network model commonly used by orthopedic medical robots from the simulation of human neuroscience. The discussion is based on economic principles.

Analyzing numerical simulation of ventilation system and filter membrane: The exposure of airborne nanoparticles in health interior Space

Improving air quality in indoor areas or interior spaces is a vital need. High PM 2.5 concentration or excessive air pollution causes severe damage to human health and the respiratory system. Air ventilation systems in health spaces are more necessary as there is a higher human crowd flow in viral-susceptible areas. The recent COVID situation has made us rethink the re-arrangement of hospitals' interior space and air ventilation systems. For that reason, improving high-efficiency particulate air filters is the need of the hour. The main objective of this research is the optimization and redesign of the air filtration system in health centers by integrating a hybrid combination system of HEPA filters based on computer modeling and numerical simulation. To analyze the effectiveness of the hybrid system, first, we simulated the existing air filtration system by using a successful and proven air filtering computational model in COMSOL Multiphysics. After that, we generated comparative numerical results and graphical analysis obtained by COMSOL to demonstrate the competency of the hybrid system over the conventional air filtration system. Finally, we have shown the most optimum and effective way to implement the hybrid system in health centers by analyzing the Computational Fluid Dynamics of different types of opening and ventilation systems. This research will play an essential role in future interior air quality improvement and effective anti-viral design of health spaces.

Biomechanics based computer simulation of rural landscape design using remote sensing image technology

Introduction: The strategy and restoration of rural areas and landscape in biomechanics, with a particular emphasis on cellular and molecular biomechanics, is crucial for sustainable rural landscape design. At the cellular and molecular level, plants’ biomechanical properties, such as the rigidity and elasticity of cell walls, determine their growth patterns and responses to environmental factors. These properties are essential in understanding how plants can be effectively incorporated into the rural landscape to enhance its stability and functionality. Aim: The objective of this research is to develop a novel computer simulation model for rural landscape planning using remote sensing imaging technology. Research methodology: We introduce a novel Adaptive YOLOv7 method driven by Starling Murmuration search. UAVs are used to collect extensive visual data for training the model. By considering cellular and molecular biomechanics, we can analyze how the mechanical forces within plants affect their ability to resist wind, retain water, and interact with the surrounding soil and other organisms. This knowledge can be integrated into the model to better predict the long-term viability and adaptability of different plant species in the rural landscape. The combination of the 3D GIS virtual image strategy model and our proposed model, along with SM optimization, not only improves object identification but also takes into account the biomechanical aspects for more accurate simulations. Crowdsourcing helps in precisely mapping rural landscapes and structures, while the incorporation of biomechanical principles ensures better adaptability to changing environmental and ecological conditions. Findings and Conclusion: Implemented in Python software, our SM-AYOLOv7 model shows excellent performance, with metrics like f1 score (93.64%), recall (92.34%), accuracy (91.72%), and IoU (90.23%). Our method outperforms conventional ones, demonstrating enhanced accuracy and flexibility, especially in handling changing configurations, due to the integration of cellular and molecular biomechanical insights.

Study results of the stress-strain states of the crown parts of molars restored with composite, ceramic and zirconium onlays

The relevance of the research is determined by the significant need for effective restorative treatment of caries decayed teeth. The purpose of the study is comparison of the stress-strain states in simulated models of non-homogeneous composite structural elements for typical geometric characteristics of onlays made of composite, ceramic, and zirconium dioxide in the restoration of the decayed mandibular molar. Computer simulation models of biomechanical systems were obtained by digital scanning of the mandibular molar in STEP format. Control was carried out in the form of numerical characteristics and graphical visualization in the EXOCAD program. The numerical method of finite elements, information technologies and program codes of the ANSYS Workbench 12.1 system were used to solve applied problems of biomechanics. After testing the developed discrete models, they were checked for adequacy and coincidence of numerical results in areas of high voltage gradients using the tools and methods of the ANSYS 12.1 code system. The maximum displacements, gradients, and amplitudes of the Mises-equivalent stress in the structural elements of each biomechanical system were evaluated. The stress values were calculated using the method of linear scaling of the results of the numerical solution of the boundary value problems of the theory of elasticity for small deformations to correspond to the functional force load of the mandibular molar of 100 N. The estimated values of the coefficients of the strength reserve of the structural elements were calculated as the ratio of the strength limit values to the maximum calculated values of the Mises-equivalent stress, scaled by a coefficient of 10 for a force load of 100 N. It was established that the largest voltage gradients are registered at the border of the cement layer. However, the nature of force transmission, as well as stress distribution, was different for different structural materials. The maximum stress was observed in the model with a composite onlay in the local area of the surface of the force load in the cement layer. For the ceramic onlay, the maximum stress was found on the lower support surface of contact with the onlay, where its values were 1.4 times higher than on other surfaces. The analysis of the zones of maximum stress for the zirconium onlay revealed their predominant localization in the center of its occlusal surface and in the zone of change in its spatial configuration at the border with cement. The highest stress values, along with the lowest coefficients of safety margin, were found for the molar model restored with a composite onlay, which indicated the lowest endurance of this material to functional load. While the zirconium onlay provided optimal stress distribution and it was characterized by the largest safety factor, which makes this method the most acceptable for molar restoration. The obtained results should be taken into account when choosing a material for the prosthetics of lateral teeth with onlays.

Finite element analysis of modified pedicle screw fixation and traditional lumbopelvic fixation for the treatment of sacroiliac joint disruption

IntroductionThe modified pedicle screw fixation (PSF) was designed to simulate an integrated framework structure to ameliorate the resistance to vertical and shearing forces of the disrupted sacroiliac complex, and the aim of this study was to compare the biomechanical characteristics of PSF and traditional lumbopelvic fixation (LPF) for the treatment of sacroiliac joint disruption.MethodsThe digital computer simulation model of an intact spine-pelvis-femur complex with main ligaments was built from clinical images. A left sacroiliac joint disruption model was mimicked by removing the concerned ligaments. After model validation, the two fixation models (modified PSF and traditional LPF) were established, and assembled with the disruption model. Under five loading scenarios (compression, flexion, extension, right bending, and left twisting), the finite element simulation was implemented. The maximum von Mises stress (VMS) of internal fixations and pelvises, maximum deformations on the Z-, Y-, X-axes and overall deformation of the sacrum were evaluated and compared.ResultsUnder all loading conditions, the maximum VMS of internal fixations and pelvises in the modified PSF model were lower than those in the traditional LPF model. Under flexion, right bending, and left twisting, the maximum Z-axis deformation of the sacrum for the modified PSF model was smaller than that of the traditional LPF model. For compression, the maximum Y-axis deformation of the sacrum was smaller than that of the traditional LPF model. During various loading modes, the maximum X-axis, and overall deformations of the sacrum for the modified PSF model were smaller than those in the traditional LPF model.ConclusionsCompared with the traditional LPF, the modified PSF shows superior biomechanical stability, with satisfied resistance to vertical and shearing forces, which might be potentially suitable for treating sacroiliac joint disruption.

Development of elements of an informational-and-mathematical model of hydrodynamic processes in a ceramic catalytic converter for developing an enterprise computer simulation model

Development of elements of an informational-and-mathematical model of hydrodynamic processes in a ceramic catalytic converter for developing an enterprise computer simulation model

Forecast assessment of water regime efficiency and changes in water consumption on drained lands of Western Polissia of Ukraine in a changing climate

The article presents forecast data on the impact of changing weather and climatic conditions on evaporation and water demand on the drained lands of Western Polissia of Ukraine in different periods of their development. These data are the basis for the development of appropriate adaptive measures aimed at reducing the negative impact of changing weather and climate conditions on drained lands and increasing the efficiency of their use. Computer simulation modeling of various climatic scenarios was planned to accomplish the objective. The forecast was made through a machining experiment based on the implementation of a corresponding complex of forecast-simulation models regarding the main regime-technological variable parameters of drainage systems, local climatic conditions, water regime, water management technologies, and productivity of drained lands for schematized natural, agrotechnical, and meliorative conditions. Vegetation values of total evaporation and water demand formation of drained lands were determined for the long-term forecast module of water supply regarding variable climatic and agro-meliorative conditions. The technological efficiency of different irrigation technologies (subsoil irrigation, sprinkler irrigation) of drained lands was evaluated. The research showed that in the Western Polissia of Ukraine, the water supply module for irrigating drained lands varies significantly depending on the type of crops, drained soil (mineral, peat), irrigation technologies, and heat and moisture supply conditions during the vegetation period. It has been experimentally determined that under current climatic conditions, the value of the water supply module is 2.9 times higher than the existing recommended design values, and under the predicted conditions of their change, this excess is 5.2 times. At the same time, the water demand of cultivated crops increases almost 2–3 times and determines the need to increase water consumption for moistening drained lands in conditions of sufficient water shortage. It has been established that the main content of the necessary adaptive measures is to increase the moisture availability of soils with regulated water regime by switching from periodic to regular moistening of them through the use of appropriate resource-saving technologies for regulating the water regime.

Deposition Contribution Rates and Simulation Model Refinement for Polysilicon Films Deposited by Large-Sized Tubular Low-Pressure Chemical Vapor Deposition Reactors.

Tunnel oxide passivating contact cells have become the mainstream form of high-performance photovoltaic cells; however, the key factor restricting the further improvement of tunnel oxide passivating contact cell performance lies in the deposition process technology of high-quality polysilicon films. The experimental optimization cost for the deposition of large-sized polysilicon films in low-pressure chemical vapor deposition reactors is enormous when conducted in the temperature range of 800-950 K; hence, the necessity to develop effective computer simulation models becomes urgent. In recent years, our research group has conducted two-dimensional simulation research on large-sized, low-pressure chemical vapor deposition. This article focuses on analyzing the influence of gas-phase chemical reactions on the contribution rate of polysilicon film deposition under a mixed atmosphere of H2 and SiH4. The findings indicate that when using SiH4 as the precursor reactants with a gas pressure not exceeding 100 Pa, SiH4 contributes more than 99.6% to the deposition of polysilicon films, while the contribution rate of intermediates from chemical reactions to film deposition is less than 0.5% with 860-900 K. The influence of temperature on the contribution rate of gas-phase intermediates is negligible. It is found that simulating complex multi-step chemical reactions is highly resource-intensive, making it difficult to achieve the three-dimensional simulations of large-sized tubular LPCVD reactors. Based on the in-depth analysis of the mechanism and simulation results, a simplified model neglecting the complex multi-step chemical reaction process has been proposed. Through employing this refined and simplified model, the two-dimensional simulation of the polysilicon thin films deposition process in the large-sized tubular low pressure chemical vapor deposition reactor will become more effective and resource efficient.

Deep Learning-Based Reservoir Simulation Proxy Models

The behavior of oil reservoirs, characterized by geophysical, geochemical, and geological properties, can be understood through the simulation of computational models, involving the construction of meshes of finite volume elements with equations derived from fundamental principles. However, the execution of multiple simulations for activities such as optimization and uncertainty assessment results in substantial computational costs.To overcome this challenge, proxy models are proposed, aiming to replace reservoir simulators with adequate precision. This work proposes the implementation of data-based proxies for reservoir simulators using Artificial Neural Networks (ANNs). This approach utilizes time series of well controls as inputs, generating responses for Bottom Hole Pressures (BHPs) and/or flow rates.In recent years, proxy models based on neural networks have been applied to obtain predictions of flows and/or pressures in reservoirs. For example, Recurrent Neural Networks (RNNs), specialized in handling sequential data, were used by [1] to predict water flows in the Xiluodu hydroelectric reservoir in China. Convolutional Neural Networks (CNNs), specialized in pattern recognition in images and videos, were also employed by [2] to predict pressures and flow rates of injector and producer wells, respectively.In the scope of this study, distinct neural network architectures were evaluated to predict outputs of a synthetic two-phase model with partial faults. Given the adoption of mixed controls, where producer wells are controlled by BHP and injector wells by flow rate, the use of Multihead Neural Networks [3] was also investigated. This approach allows differentiated processing of input data, contributing to more robust and efficient learning.For each considered architecture, the impact of the number of timesteps in the samples and their size on the accuracy of predictions was analyzed. The results indicate that parallel hybrid architectures exhibit the best performance, forming a complementary mutual network where each architecture contributes with different learning approaches. Additionally, a higher number of samples contributes to reducing result dispersion, while an increase in the number of timesteps does not show a significant contribution to reducing mean error.We gratefully acknowledge the support provided by PETROBRAS, ANP, FINEP, PRH, EMBRAPII, FACEPE, CNPq, and CAPES, which has been instrumental in the successful execution of this work.

Introducing glutamic acid residues to acyl-ACP reductase to enhance alka(e)ne production in Escherichia coli: Computer-aided design and subsequent experimental validation.

Acyl-acyl carrier protein (acyl-ACP) reductase (AAR) is a crucial enzyme in alka(e)ne production by recombinant Escherichia coli (E. coli). Engineered AAR expressed in E. coli holds great promise for the production of alka(e)nes, which are a valuable bio-based alternative to fossil fuels. However, its effectiveness is significantly limited by its low solubility and stability. The aim of this study is to enhance the solubility and stability of AAR to improve the production of alka(e)nes in E. coli. In this study, an integrated computational approach was employed for combining solubility prediction, aggregation propensity prediction, structural modeling, and molecular dynamics (MD) simulations. This multi-faceted approach provides new insights and tools for enzyme engineering. Through this approach, the C-terminus of AAR was identified as the sole significant hydrophobic patch and aggregation-prone regions (APR). Three strategies were evaluated experimentally: direct deletion of these hydrophobic residues; substitution of these residues with negatively charged amino acids, such as glutamic acid (Glu) or aspartic acid (Asp); and the introduction of additional negatively charged amino acids at the C-terminus to shield the hydrophobic patches. The results showed that AAR mutants with additional Glu residues at the C-terminus exhibited improved performance. Specifically, the AAR-E3 mutant, containing three consecutive Glu residues, demonstrated significantly enhanced solubility and stability, with alka(e)ne production (159.25mg/L) being 6.3 times higher than that of the wild-type AAR (25.37mg/L). Subsequent computational modeling and molecular dynamics simulations further validated the experimental findings. This study highlights the potential of enzyme engineering to significantly enhance biofuel production efficiency.