Experimental Approach Research Articles

Magnetite in the abdomen and antennae of Apis mellifera honeybees.

The detection of magnetic fields by animals is known as magnetoreception. The ferromagnetic hypothesis explains magnetoreception assuming that magnetic nanoparticles are used as magnetic field transducers. Magnetite nanoparticles in the abdomen of Apis mellifera honeybees have been proposed in the literature as the magnetic field transducer. However, studies with ants and stingless bees have shown that the whole body of the insect contain magnetic material, and that the largest magnetization is in the antennae. The aim of the present study is to investigate the magnetization of all the body parts of honeybees as has been done with ants and stingless bees. To do that, the head without antennae, antennae, thorax, and abdomen obtained from Apis mellifera honeybees were analyzed using magnetometry and Ferromagnetic Resonance (FMR) techniques. The magnetometry and FMR measurements show the presence of magnetic material in all honeybee body parts. Our results present evidence of the presence of biomineralized magnetite nanoparticles in the honeybee abdomen and, for the first time, magnetite in the antennae. FMR measurements permit to identify the magnetite in the abdomen as biomineralized. As behavioral experiments reported in the literature have shown that the abdomen is involved in magnetoreception, new experimental approaches must be done to confirm or discard the involvement of the antennae in magnetoreception.

Trace element (Be, Zn, Ga, Rb, Nb, Cs, Ta, W) partitioning between mica and Li-rich granitic melt: Experimental approach and implications for W mineralization

Mica is the most important carrier of rare alkalis (Li, Rb and Cs) and volatiles, and also a major host of rare metals such as Sn, W, Nb and Ta. Thus, the knowledge of trace element partitioning between mica and silicate melt is crucial to understand enrichment mechanisms of ore metals in evolved silicic systems. However, experimental data are scarce, mainly because the synthesis of large mica grains which can be analyzed with laser ablation techniques is challenging. To address this issue, we conducted two-step experiments, using a high-temperature step at 800 °C, and a low-temperature step at 600 °C with a temperature cycling interval of 30 °C, and variable run durations from 21 to 60 days. The experimental products, at 600 °C, 200 MPa, are mainly composed of mica and alkali feldspars. Ferroholmquistite (Fhlm; a Li-bearing amphibole) was also observed in the Li-bearing systems.Beryllium, Zn and Cs are highly incompatible in all run products with mineral/melt partitioning of mineral/meltDBe between 0.01 and 0.08, mineral/meltDZn between < 0.01 and 0.24 and mineral/meltDCs between <0.01 and 0.19. Gallium is mildly incompatible in mica and feldspars with mica/meltDGa, K-feld/meltDGa and Na-feld/meltDGa of 0.24–0.35, 0.60–0.67 and 0.69–0.72, respectively, whereas Fhlm/meltDGa is nearly 1. Rubidium is characterized by a slight enrichment in mica and K-rich feldspar with respect to melt. Niobium and Ta are highly incompatible in feldspars, while they are compatible in ferroholmquistite. Li-mica crystallization would cause Nb/Ta fractionation with mica/meltDNb and mica/meltDTa of 4.46 and 0.88, respectively. Tungsten is preferentially incorporated in Li-rich mica with mica/meltDW > 22. The strong partitioning of W into Li-rich mica implies that minor Li-rich mica fractionation (>5 %) will strongly deplete W in the residual melt, thus inhibiting transfer to the magmatic fluid at the magmatic-hydrothermal transition. Based on the observed mineral/meltD value, a multi-stage quantitative fractionation model for the behavior of metals during the crystallization of Li-bearing granitic magmas was developed. The results suggest that crystal fractionation is an effective mechanism that could further enrich Be, Ga, Rb, Cs, Nb and Ta in residual melts. Li-rich mica and muscovite are more effective in causing Nb/Ta fractionation as compared with biotite. The very low Nb/Ta ratios found in natural granite may have resulted via extreme, i.e., >99 wt% of fractional crystallization, even if without the precipitation of columbite-group minerals or increasing hydrothermal activity. Due to the very high Li-mica/meltDW value, water saturation in the melt and subsequent magmatic fluid exsolution should occur before Li-mica starts to crystallize to avoid W sequestration in the magma. At 175 MPa, the efficiency of extracting W from Li-poor granitic system is at least 15 % higher than that from Li-rich granitic system. Li-poor granitic systems are thus expected to have a greater W-mineralization potential than Li-rich system, which is consistent with the fact that most parental magmas of large/giant W deposits are Li-poor in composition.

Growth and Redox Properties of Boron on Al(111): Competing Affinities in the Case of Honeycomb AlB2.

The complexity of the geometric and electronic structure of boron allotropes is associated with the multicentric bonding character and the consequent B polymorphism. When growth is limited to two-dimensions (2D), the structural and electronic confinement yields the borophenes family, where the interaction with the templating substrate actually determines the stability of inequivalent boron phases. We report here a detailed study of the growth of the honeycomb AlB2 phase on Al(111), followed by an investigation of its oxidation and reduction properties. By means of a combined experimental and theoretical approach, we show that the structure of the B/Al interface is affected by the complex interplay between B, Al, and common reactive agents like oxygen and hydrogen. While kinetic effects associated with diffusion and strain release influence the AlB2 growth in vacuo, Al, B, O, and H chemical affinities determine its redox behavior. Reduction with atomic hydrogen involves the B layer and yields an ordered honeycomb borophane H/AlB2 phase. Instead, oxidation takes place at the Al interface, giving origin to buried and 1D surface aluminum oxide phases.

Tailoring the Electronic Structures and Spectral Properties of ZnO with Irradiation Defects Generated Under Intense Electronic Excitation: A Combined Experimental and DFT Approach

AbstractThe relationship between the composition of the internal defect states, spectral properties, and correlated electronic structures of wurtzite zinc oxide (ZnO) crystals under 645 MeV Xe35+ irradiation is systematically investigated, employing experimental characterizations combined with first‐principle calculations. Based on the ion irradiation‐induced thermal expansion and relaxation processes, the high concentration of vacancy/interstitial defects produced from the transient disordered phase in molten track states trigger photoelectric changes, as follows: i) the generation of internal defect states effectively reduces the intrinsic bandgap (3.25 eV → 2.66 eV); ii) a large number of defective active sites inhibits the recombination between electron–hole pairs, causing dark conductance and photoconductance to increase with increasing damage levels until optimal fluence is achieved. Based on the density functional theory (DFT) with the GGA + U (GGA = generalized gradient approximation) method, the defective models associated with the different electronic structures, density of states, formation energy, and the nature of the chemical bonding are established. The narrowing of the bandgap observed experimentally and the enhancement of carrier concentration originating from the internal electron defect states are qualitatively verified, therefore laying the foundation for designing future nanoscale photoelectronic devices and microelectronics applications.

Synthesis and evaluation of benzo[1,2,3]selenadiazole-isoxazoles as corrosion inhibitors for copper in NaCl: An integrated experimental and theoretical approach

In this study, we investigate the protective capabilities of two synthetic compounds, 5-methyl-5-(4-methylbenzo[d][1,2,3]selenadiazol-7-yl)-3-phenyl-4,5-dihydro-isoxazole (BHP) and 5-methyl-5-(4-methylbenzo[d][1,2,3]selenadiazol-7-yl)-3-(4-nitrophenyl)-4,5-dihydro-isoxazole (BNP), as corrosion inhibitors for copper in a 3.5 wt% NaCl solution. The chemical structure of these benzo[1,2,3]selenadiazolyl-isoxazole derivatives combines a benzo[1,2,3]selenadiazole core, which to our knowledge has not been previously studied for its anticorrosive activity on copper, with an isoxazole nucleus known in the literature as one of the most effective azoles in preventing copper corrosion. The efficiency and mechanism of copper corrosion inhibition were evaluated through electrochemical, theoretical, and morphological studies. Potentiodynamic polarization (PDP) showed that both BHP and BNP were effective in inhibiting copper corrosion. At 10−3 M, BHP showed a maximum inhibition efficiency of 80.24 %, while BNP achieved an even higher efficiency of 89.83 %. Adsorption behavior analysis indicated that both compounds followed the Langmuir isotherm. In addition, the high value of Kads (103 M−1) indicates a strong adsorption capacity of our molecules on the copper surface. The negative adsorption free energy (ΔG°ads=−34.14kJ/mol for BHP and ΔG°ads=−34.00kJ/mol for BNP) indicates a spontaneous adsorption process. Electrochemical impedance spectroscopy (EIS) showed that both compounds formed a thin protective layer on the copper surface, a finding further supported by surface morphology studies using scanning electron microscopy (SEM-EDX) and ATR-FTIR analysis.

From deep learning to the discovery of promising VEGFR-2 inhibitors.

Vascular endothelial growth factor receptor 2 (VEGFR-2) stands as a prominent therapeutic target in oncology, playing a critical role in angiogenesis, tumor growth, and metastasis. FDA-approved VEGFR-2 inhibitors are associated with diverse side effects. Thus, finding novel and more effective inhibitors is of utmost importance. In this study, a deep learning (DL) classification model was first developed and then employed to select putative active VEGFR-2 inhibitors from an in-house chemical library including 187 druglike compounds. A pool of 18 promising candidates was shortlisted and screened against VEGFR-2 by using molecular docking. Finally, two compounds, RHE-334 and EA-11, were prioritized as promising VEGFR-2 inhibitors by employing PLATO, our target fishing and bioactivity prediction platform. Based on this rationale, we prepared RHE-334 and EA-11 and successfully tested their anti-proliferative potential against MCF-7 human breast cancer cells with IC50 values of 26.78±4.02 and 38.73±3.84 µM, respectively. Their toxicities were instead challenged against the WI-38. Interestingly, expression studies indicated that, in the presence of RHE-334, VEGFR-2 was equal to 0.52±0.03, thus comparable to imatinib equal to 0.63±0.03. In conclusion, this workflow based on theoretical and experimental approaches demonstrates effective in identifying VEGFR-2 inhibitors and can be easily adapted to other medicinal chemistry goals.

Enhancing Domestic Wastewater Treatment: A Study on the Efficacy of Tiered Filtration and a Combined Photocatalytic Ozonation Methods

This study aimed to construct an optimized reactor using photocatalytic ozonation, and its effectiveness was determined using PermenLHK No. 86/2016. The Tanjung Uma housing estate in Batam city was selected as the study sample site for domestic wastewater because of its role as a significant water body that receives liquid waste from a majority of activities across the city. The experiment employed a quantitative research approach and a true experimental approach, testing variables (catalyst weight, UV irradiation time, and ozonation duration) in a laboratory setting (25°C and 40-70% Humidity). The study found that the optimized parameter (a combination of 2 h of irradiation, with 2 g of TiO2 along with 5 min of ozonation) resulted in a significant difference in water quality parameters compared to before treatment with 92% effectivity. It can be concluded that this Reactor prototype was highly successful in reducing environmental impacts based on its effectiveness

Band-gap tuning in Mn-doped Er2Ti2O7: Insight from the experimental and theoretical approach

We report the studies of electronic and optical properties of Er2Ti2−xMnxO7 (x = 0, 0.1, & 0.2) through combined theoretical insights from density functional theory (DFT) calculations and experimental approaches, including ultraviolet-visible absorption, photoluminescence emission spectroscopy, and Raman spectroscopy. For quantitatively correct optical bandgaps through DFT calculations, we considered the LDA-1/2 technique for the exchange-correlation interactions. The energy bandgap values obtained using theoretical formulations are in close accordance with the experimental results. The bandgap value obtained using the LDA-1/2 approach indicates the insulated ground state of the Er2Ti2−xMnxO7 (x = 0, 0.1, & 0.2) system. The band gap value obtained experimentally reduces from 3.82 eV to 2.45 eV as the level of Mn doping increases from 0 to 0.2. This reduction in the experimental band gap is attributed to the fact that inclusion of Mn atoms into the crystal lattice alters the electronic structure of the system. Substituting the Mn atom introduces additional electronic states within the band structure, leading to a modification of the band gap. Crystallographic data indicates that inclusion of Mn reduces the Ti-O bond length as in indicated in the table which reduces to 1.939(0) Å for x = 0.2 from 1.947(0) Å for x = 0. This results in the reduction of the extent of hybridization between O-2p and Ti-3d states, thereby reducing the band gap.

Indonesia-Malaysia Batik Pattern Collaboration Creation with Artificial Intelligence Platform

The problem with making batik in Indonesia and Malaysia so far is that it is still very manual and has not taken much advantage of technological advances. The development of Artificial Intelligence (AI) technology is currently very advanced, continues to innovate, and has even touched various aspects of human life. Limitations in ideas, human resources, knowledge, tools, and internet networks are the dominant conditions that cause problems in Indonesian and Malaysian batik creations. This study aims to use Artificial Intelligence to describe the combination of Indonesian and Malaysian batik patterns. This paper uses a descriptive-qualitative method with an experimental approach in the form of trials for the creation of batik patterns using the Imagine Artificial Intelligence platform; each trial is based on three basic patterns of batik, namely Sawat and Gurdha (Indonesia) and Orchid and Tiger (Malaysia). The results of this paper generated eight totally new Indonesian-Malaysian batik patterns. Artificial Intelligence (AI) was very helpful for the development of batik patterns. Through the creation of new batik patterns with the support of Artificial Intelligence (AI), it certainly creates new opportunities for the creation and business of batik to become more advanced. It is hoped that this paper will succeed in solving the problem of limited ideas in creating Indonesian-Malaysian batik motifs. Keywords: Artificial Intelligence, batik, creation, Indonesia-Malaysia

A Short Paper about Fundamental Pedagogical Concepts of Constructivism Theory in Relation to TPACK Framework

The influence of constructivism as a pedagogical theory is mainly concentrated on adult education. Its main concepts stem from significant conclusions coming from other theories related to pedagogical and philosophical school practice. The key point is that knowledge is the desired learning outcome that can be accomplished through active learning participation which is closely related to construct. Also, some basic ideas of constructivism rely on idea-based interactions and ideas produced by learners. Certain aspects of the above-mentioned theory in learning and teaching seem to be very helpful for learners to develop their ideas and achieve learning outcomes. The basic aim of this paper is to examine the influence of Constructivism on adult education by utilising Technological Pedagogical Content Knowledge Framework’s (TPACK) dimensions in learning and teaching everyday practice. A mixed method analysis was conducted which contains a theoretical analysis, and experimentation through a quiz game. Our experimental approach through the quiz game was to study Newtonian physics and specifically the Law of Gravitation and the 2nd Law of Motion, finding that the mass terms cancel, and ending up making a prediction that all objects fall at the same rate. The experiment would then involve verifying the prediction and explaining any deviations from the prediction in terms of the intuitive idea of air resistance. The findings showed that students after answering the quizzes of the quiz game, were able to discuss their results using logical argument as opposed to when they did the experiment before the theory and their discussion was little more than guesswork. Thus, we could see how students performed on each question and use that information to figure out what needs to be readdressed or retaught.

Experimental approach for characterizing the nonlinear, time and temperature‐dependent constitutive response of open‐cell polyurethane foams

AbstractElastomeric foams are composite materials comprising of a polymeric elastomer and interconnected gas‐filled pores, endowing them with exceptional compliance and the ability to undergo large, reversible deformations along with substantial volume change. These foams find extensive utility in contexts demanding compliance and compressibility, such as impact protection and cushioning, spanning a diverse range of applications. Changing temperature can dramatically alter foam stiffness, strength and deformation characteristics specifically around the material's glassy‐rubbery transition temperature (). With the aim of informing new constitutive model developments for elastomeric foams, we conducted a comprehensive series of large deformation, homogeneous compression and tension tests across strain rates from 10−2 s−1 to 100 s−1 and ambient temperatures ranging from −10°C to 50°C covering an even range around the material's of 20°C. To achieve precise control of ambient temperatures during mechanical testing, we constructed a custom‐designed environmental chamber for controlling the ambient temperature from −10°C to 50°C with a variation of less than 1°C. The obtained digital image correlation based stress‐strain data shows significant tension‐compression asymmetry as well as significant dependence on strain rate and ambient temperature, especially above and below the glass transition temperature. We provide full access to these data sets for the future development of rate‐ and temperature‐dependent constitutive models.

Participatory mapping in exploratory scenario planning: Necessity or luxury?

Exploratory scenarios based on participatory approaches proved helpful in dealing with uncertainty and complexity in urban and transport systems. Such scenarios usually create coherent and manageable narratives that capture broad patterns and trends at global scales. However, significant difficulties exist in bridging exploratory scenario narratives with spatial and local realities, which is crucial for guiding policymaking in urban, regional, and mobility planning. This paper explores whether and how exploratory scenario narratives and participatory mapping processes can establish a reciprocal relationship, wherein narrative-based maps contribute to spatially shaping scenario narratives. It uses an experimental approach involving three participatory workshops with experts and local stakeholders specifically tailored to the mapping of land use and transportation-related scenario narratives for the year 2050 in the Henares Corridor (Madrid, Spain). The spatial transformations mapped during workshops have indicated that participatory mapping processes have an impact on scenario narratives in different ways, enabling the identification of three categories of mapping episodes with different meanings: (i) complementing narratives, (ii) expanding narratives, and (iii) modifying narratives. The paper closes by examining the implications of the obtained findings for policymaking, including a reflection on the research’s limitations and potential for application in real-world planning processes.

Accounting learning outcomes from problem-based learning

The main objective of this study is to examine and compare the educational achievements between problem-based learning and discovery learning approaches in the field of accounting. Understanding the concept is an important part of the process of learning and solving problems, both in the learning process itself and in day-to-day environments. Research using a quantitative method with an experimental approach is a true experimental design. The model of the experiment is the pretest-posttest control group design. According to earlier studies have shown that student’s learn better through discovery learning (DL). It is evident that both methods contribute to the improvement of student outcomes. Being active, thinking critically, and increasing learner achievement are essential factors in the process of learning. In this study, it was discovered that the learning outcomes of problem-based learning models and discovery learning have notable disparities, with problem-based learning producing better learning outcomes. The conclusions from the study offer suggestions or input that can be conveyed and considered for future research. Schools should consider applying a problem-based learning (PBL) model. Students using PBL are required to find their own answers to problems by using their own thinking abilities to form a concept about the material being studied, so during learning activities, students will use their thinking abilities to the maximum.

Evolving Improved Sampling Protocols for Dose–Response Modelling Using Genetic Algorithms with a Profile-Likelihood Metric

Practical limitations of quality and quantity of data can limit the precision of parameter identification in mathematical models. Model-based experimental design approaches have been developed to minimise parameter uncertainty, but the majority of these approaches have relied on first-order approximations of model sensitivity at a local point in parameter space. Practical identifiability approaches such as profile-likelihood have shown potential for quantifying parameter uncertainty beyond linear approximations. This research presents a genetic algorithm approach to optimise sample timing across various parameterisations of a demonstrative PK-PD model with the goal of aiding experimental design. The optimisation relies on a chosen metric of parameter uncertainty that is based on the profile-likelihood method. Additionally, the approach considers cases where multiple parameter scenarios may require simultaneous optimisation. The genetic algorithm approach was able to locate near-optimal sampling protocols for a wide range of sample number (n = 3–20), and it reduced the parameter variance metric by 33–37% on average. The profile-likelihood metric also correlated well with an existing Monte Carlo-based metric (with a worst-case r > 0.89), while reducing computational cost by an order of magnitude. The combination of the new profile-likelihood metric and the genetic algorithm demonstrate the feasibility of considering the nonlinear nature of models in optimal experimental design at a reasonable computational cost. The outputs of such a process could allow for experimenters to either improve parameter certainty given a fixed number of samples, or reduce sample quantity while retaining the same level of parameter certainty.

Catalyzing hydrogen production: Exploring plasmonic effects in self-assembled CuO/Cu2O thin films via pulsed laser deposition

Plasmonic catalysis triggers the dissociation of H2 or adsorbed O2 (sluggish processes) under continuous wave excitation via plasmon decay. This is coupled to interband or intraband excitation of d-band or sp-band, respectively, to levels above fermi level of metals. Here, we have studied the plasmonic and photocatalytic behavior in an environment friendly medium with AM 1.5 G sunlight of CuO/Cu2O thin films fabricated by pulsed laser deposition technique in vacuum with varying thickness. We have achieved ∼0.59 kmol h−1g−1H2 production in the CuO/Cu2O film with a thickness of ∼27 nm. The role of plasmons with metal–dielectric and semiconductor–semiconductor interfaces is conducted through both experimental and theoretical approaches. The results suggest that the impact of plasmonic catalysis/synthesis is subject to the dimension, composition, and band alignment of two interface materials.

Enhanced antioxidant activity in Imidazolium-based protic organic salts: An insight into structure activity relationship via experimental and modelling approaches

Sulfonyl hydroxide functionalized imidazolium based protic ionic liquids (PILs) have been evaluated as a new form of antioxidants. The antioxidant activity was performed using free radical quenching using UV–visible spectroscopy and cyclic voltammetry. The studies confirmed that the investigated ILs with variable anions exhibited substantial radical scavenging activity. In UV–Visible study, Glutamine based-IL ([1MeimPS][Gln]) showed least IC50 value of 95 µM indicating maximum radical quenching activity as an oxidant, while proline based-IL ([1MeimPS]Pro]) exhibited highest IC50 value of 675 µM, demonstrating least anti-oxidant activity. Moreover, cyclic voltammetry results complemented well the UV–visible findings with least IC50 value of 90 µM for [1MeimPS][Gln], showing maximum antioxidant activity, and highest IC50 value of 593 µM for [1MeimPS]Pro], exhibiting the least antioxidant activity. The presence of two primary amines moieties in glutaminate anion may be responsible for enhanced antioxidant activity by providing more active sites for radical quenching. Contrarily, lack of primary amine functionality in prolinate anion may contribute to reduced antioxidant activity of respective IL. The Density Functional Theory (DFT) calculations predicted that the trend of radical scavenging potential was comparable with the experimentally obtained IC50 values. Molecular Electrostatic Potential (MESP) Maps illustrated that [1MeimPS][Pro] has the maximum red zones indicating a poor potential against electron scavenging capacity among all the studied ILs, while blue region in [1MeimPS][Gln], corresponding to low electron density, suggested strong attraction for the incoming electrons. Also, the high electronic distribution of HOMO orbital, appreciable stability, and significant chemical potential to attack on radical species provided by [1MeimPS][Gln] with the maximum radical scavenging potential. Furthermore, the associated LUMO energy for [1MeimPS][Pro] (−1.297 eV) is quite higher than that of [1MeimPS][Gln] (−1.422 eV) which reduced the ability of [1MeimPS][Pro] to attack free radicals of 2,2-diphenyl-1-picrylhydrazyl (DPPH) and thus have higher associated IC50 values. This is also supported by the results of chemical hardness (η) and chemical potential (μ) descriptors values indicating [1MeimPS][Pro] is least stable and reactive than [1MeimPS][Gln]. These findings further explain the least IC50 values observed experimentally and consequent enhanced antioxidant potential of [1MeimPS][Gln].

Assessment of the Efficiency of a Hybrid Photovoltaic and Photovoltaic Heating System (PV–Solar) in the Context of a Warehouse for a Housing Community in Poland

In light of global challenges such as the war in Ukraine and the depletion of fossil fuel resources, it is essential to explore sustainable energy solutions. Hybrid energy systems represent a potential solution, offering energy independence to urban housing estates and reducing CO2 emissions. This article aims to explore the feasibility of integrating photovoltaic systems (utilizing vacuum collectors) and combined utilities (system heat and electricity) in a hybrid setup, leveraging existing technical infrastructure with necessary modifications. A key aspect is to perform calculations on the amount of heat and electricity generated from these systems. The study analyzes the demand for heat and electricity among consumers compared to the estimated production from renewable sources. Calculations also include the potential energy savings and CO2 emission reductions achievable through the proposed solutions. The findings indicate that hybrid photovoltaic systems with heat storage could effectively address energy issues in urban housing estates, given adequate support and community involvement. The innovative methodology employed in this study encompasses both analytical and experimental research approaches. The analysis employs advanced statistical techniques and data integration to enhance understanding of the phenomena studied, while the experimental research provides robust results through controlled variable manipulation and precise measurement tools, thereby verifying the study’s objectives.

A Computational Pipeline for Accurate Prioritization of Protein-Protein Binding Candidates in High-Throughput Protein Libraries.

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners but often include false positives. Furthermore, they provide no information about what the binding region is (e.g., the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competitive Binding Assay (AF-CBA) to identify proteins that bind a target of interest from a pull-down experiment and the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide-protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies of AF and AF-CBA to help users identify scenarios where the approach will be most useful. Given the method's speed and accuracy, we anticipate its broad applicability to identify binding epitope regions among potential partners, setting the stage for experimental verification.

Advances in computational and experimental approaches for deciphering transcriptional regulatory networks: Understanding the roles of cis-regulatory elements is essential, and recent research utilizing MPRAs, STARR-seq, CRISPR-Cas9, and machine learning has yielded valuable insights.

Understanding the influence of cis-regulatory elements on gene regulation poses numerous challenges given complexities stemming from variations in transcription factor (TF) binding, chromatin accessibility, structural constraints, and cell-type differences. This review discusses the role of gene regulatory networks in enhancing understanding of transcriptional regulation and covers construction methods ranging from expression-based approaches to supervised machine learning. Additionally, key experimental methods, including MPRAs and CRISPR-Cas9-based screening, which have significantly contributed to understanding TF binding preferences and cis-regulatory element functions, are explored. Lastly, the potential of machine learning and artificial intelligence to unravel cis-regulatory logic is analyzed. These computational advances have far-reaching implications for precision medicine, therapeutic target discovery, and the study of genetic variations in health and disease.

A Computational Pipeline for Accurate Prioritization of Protein‐Protein Binding Candidates in High‐Throughput Protein Libraries

AbstractIdentifying the interactome for a protein of interest is challenging due to the large number of possible binders. High‐throughput experimental approaches narrow down possible binding partners but often include false positives. Furthermore, they provide no information about what the binding region is (e.g., the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competitive Binding Assay (AF‐CBA) to identify proteins that bind a target of interest from a pull‐down experiment and the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide‐protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies of AF and AF‐CBA to help users identify scenarios where the approach will be most useful. Given the method‘s speed and accuracy, we anticipate its broad applicability to identify binding epitope regions among potential partners, setting the stage for experimental verification.