Sequence Selectivity Research Articles

Mainshock-Aftershock Ground Motion Sequences Selection and its Implication on Bridge Seismic Fragility

ABSTRACT In seismic-prone regions, the evaluation of structural performance of bridges under mainshock-aftershock ground motion sequences is imperative for ensuring their safety and facilitating effective response measures. However, the limited availability of real-recorded mainshock-aftershock ground motion sequences for region-specific condition results in the adoption of artificially generated sequences for seismic fragility assessment of bridges. This study presents a new approach for the artificial generation of ground motion sequences by quantifying the relationship between parameters of real-recorded mainshock-aftershock sequences, while also considering regional seismicity. The proposed framework is employed to obtain a suite of region-specific mainshock-aftershock sequences for the Himalayan region, and is subsequently applied to a case-study bridge for vulnerability assessment. An experimentally validated bridge numerical model is developed to simulate the degradation caused by multiple cyclic loadings of mainshock-aftershock sequences. An optimal engineering demand parameter is identified to capture the cumulative damage under mainshock-aftershock sequences and seismic fragility curves are developed using incremental dynamic analysis-based approach. Results reveal a higher seismic fragility under ground motion sequences compared to mainshocks alone, with similar trends observed across different bridge geometries. Notably, the finding indicates a close match between the seismic fragility curves developed using mainshock-aftershock sequences selected through the proposed framework and those derived using real-recorded sequences.

A CRISPR view on genetic screens inToxoplasma gondii.

Genome editing technologies, such as CRISPR-Cas9, have revolutionised the study of genes in a variety of organisms, including unicellular parasites. Today, the CRISPR-Cas9 technology is vastly applied in high-throughput screens to investigate interactions between the Apicomplexan parasite Toxoplasma gondii and its hosts. In vitro and in vivo T. gondii screens performed in naive and restrictive conditions have led to the discovery of essential and fitness-conferring T. gondii genes, as well as factors important for virulence and dissemination. Recent studies have adapted the CRISPR-Cas9 screening technology to study T. gondii genes based on phenotypes unrelated to parasite survival. These advances were achieved by using conditional systems coupled with imaging, as well as single-cell RNA sequencing and phenotypic selection. Here, we review the state-of-the-art of CRISPR-Cas9 screening technologies with a focus on T. gondii, highlighting strengths, current limitations and future avenues for its development, including its application to other Apicomplexan species.

Angular motion of the thorax during the golf swing: a comparison of two orientation angle sequences

ABSTRACT Orientation angles are commonly used to describe complex angular motions of the body. Selecting the most appropriate rotation sequence for a given segment’s motion is crucial. The purpose of this study was to develop a set of generalisable, primary axis-centric sequence selection strategies and to compare the lean direction-lean-rotation (LDLR) sequence, selected for thoracic motion during golf driving based on the strategies, with the conventional rotation-bend-side bend (RBSB) sequence in assessing the level of inter-angle cross-talk. The RBSB method consistently revealed a higher level of inter-angle cross-talk, with substantially larger bi-angle ICC values across all angle combinations. The rotation-side bend and bend-side bend pairs in the RBSB method exhibited the largest ICC values (≥0.837). In contrast, the rotation-lean and lean direction-lean pairs in the LDLR method showed the smallest ICC values (≤0.063). The RBSB sequence demonstrated significantly larger RMS angle ranges (p < .001), indicating a deterioration of the major angle and inflation of the minor angles due to cross-talk. The LDLR sequence realistically portrayed the axial rotation-dominant thoracic motion during the golf drive. The strategies outlined in this study can serve as general guidelines and substantially enhance the applicability of the orientation angle method.

Optimization of Single Relaxin B-Chain Peptide Leads to the Identification of R2R01, a Potent, Long-Acting RXFP1 Agonist for Cardiovascular and Renal Diseases.

Peptide 1, a C18 fatty acid-modified single-chain relaxin analogue, was recently identified as a potent, selective, and long-lasting relaxin family peptide receptor 1 (RXFP1) agonist. Further advanced pharmacokinetic profiling of this compound highlighted elevated levels of oxidative metabolism occurring in dogs and mini pigs but only marginally in rats. This study aimed to design long-lasting relaxin analogues with increased stability against metabolic oxidation while securing subnanomolar RXFP1 potency. Key structural elements, including fatty acid chain length, attachment position, and linker structure, were modified to reduce oxidative metabolism and improve pharmacokinetic parameters. Additionally, incorporating α-methyl lysine (Mly) at position 30, alongside other selective sequence mutations, resulted in several analogues with subnanomolar RXFP1 potency and improved duration of action compared to 1. Compound 21 (R2R01) was then selected as a candidate for an in-depth characterization. It is currently undergoing phase 2 clinical development for renal and cardiovascular diseases.

Crop rotation effects on the population density of soybean soilborne pathogens under no-till cropping system.

Soilborne diseases are persistent problems in soybean production. Long-term crop rotation can contribute to soilborne disease management. However, the response of soilborne pathogens to crop rotation is inconsistent, and rotation efficacy is highly variable. Selection of proper crop plants and crop sequences for disease management is needed. In this research, the effects of crop rotation on soybean soilborne pathogens were evaluated in a long-term no-till crop rotation field trial in South Dakota. Five rotation treatments were evaluated in this field trial, including corn-soybean (CS; Zea mays L., Glycine max (L.) Merr.), corn-soybean-spring wheat-pea (CSSwP; wheat: Triticum aestivum L., pea: Pisum sativum subsp. arvense (L.) Asch.), corn-soybean-spring wheat-sunflower (CSSwSf; sunflower: Helianthus annus L.), corn-oat-winter wheat-soybean (COWwS; oat: Avena sativa L.), and corn-pea-winter wheat-soybean (CPWwS). Six soilborne pathogens that consistently threaten the United States soybean production were quantified in the field soils using quantitative PCR or egg extraction for soybean cyst nematode. Three soilborne pathogens, Macrophomina phaseolina, Fusarium oxysporum, and Pythium irregulare, were detected, whereas the population density of F. graminearum and F. virguliforme was not measurable in the soil samples. The number of soybean cyst nematode eggs or juveniles was zero or very low in all soil samples. Overall, crop rotation treatments affected the population density of three detected pathogens but varied by crop phase, year, and pathogen species. The population density of three detected pathogens was positively correlated with soil temperature but negatively correlated with soil volumetric water content. Notably, the CPWwS rotation treatment had a consistently lower M. phaseolina population compared with the other rotation treatments, regardless of crop phase and year. This study provided potential crop sequences that limit soilborne pathogen populations in the soil and may reduce disease incidence on the host crops.

Mutations to transcription factor MAX allosterically increase DNA selectivity by altering folding and binding pathways

Understanding how proteins discriminate between preferred and non-preferred ligands (‘selectivity’) is essential for predicting biological function and a central goal of protein engineering efforts, yet the biophysical mechanisms underpinning selectivity remain poorly understood. Towards this end, we study how variants of the promiscuous transcription factor (TF) MAX (H. sapiens) alter DNA specificity and selectivity, yielding >1700 Kds and >500 rate constants in complex with multiple DNA sequences. Twenty-two of the 240 assayed MAX point mutations enhance selectivity, yet none of these mutations occur at residues that contact nucleotides in published structures. By applying thermodynamic and kinetic models to these results and previous observations for the highly similar yet far more selective TF Pho4 (S. cerevisiae), we find that these mutations enhance selectivity by altering partitioning between or affinity within conformations with different intrinsic selectivity, providing a mechanistic basis for allosteric modulation of ligand selectivity. These results highlight the importance of conformational heterogeneity in determining sequence selectivity and can guide future efforts to engineer selective proteins.

How Binding Site Flexibility Promotes RNA Scanning by TbRGG2 RRM: A Molecular Dynamics Simulation Study.

RNA recognition motifs (RRMs) are a key class of proteins that primarily bind single-stranded RNAs. In this study, we applied standard atomistic molecular dynamics simulations to obtain insights into the intricate binding dynamics between uridine-rich RNAs and TbRGG2 RRM using the recently developed OL3-Stafix AMBER force field, which improves the description of single-stranded RNA molecules. Complementing structural experiments that unveil a primary binding mode with a single uridine bound, our simulations uncover two supplementary binding modes in which adjacent nucleotides encroach upon the binding pocket. This leads to a unique molecular mechanism through which the TbRGG2 RRM is capable of rapidly transitioning the U-rich sequence. In contrast, the presence of non-native cytidines induces stalling and destabilization of the complex. By leveraging extensive equilibrium dynamics and a large variety of binding states, TbRGG2 RRM effectively expedites diffusion along the RNA substrate while ensuring robust selectivity for U-rich sequences despite featuring a solitary binding pocket. We further substantiate our description of the complex dynamics by simulating the fully spontaneous association process of U-rich sequences to the TbRGG2 RRM. Our study highlights the critical role of dynamics and auxiliary binding states in interface dynamics employed by RNA-binding proteins, which is not readily apparent in traditional structural studies but could represent a general type of binding strategy employed by many RNA-binding proteins.

Effective removal of heavy metal ions (Pb, Cu, and Cd) from contaminated water by limestone mine wastes

Limestone mining waste and its derived CaO were checked as an adsorbents of pb2+, Cu2+, and Cd2+ ions from water solution. The characterization of Limestone and calcined limestone was studied by using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), Scanning Electron Microscope (SEM), and Surface area measurements (BET). The optimum conditions of sorbent dosage, pH, initial concentration, and contact time factors were investigated for pristine limestone and calcined limestone absorbents. The results indicate that the optimum initial concentrations of (Ci) were 1200, 500, and 300 ppm for Pb, Cu, and Cd, respectively, using calcined limestone adsorbent, while using the pristine limestone adsorbent, the corresponding optimum initial concentrations were 700, 110, and 50 ppm. In the ternary system sorption, the results indicated that the selectivity sequence of the studied metals by limestone can be expressed as Pb2+ > Cd2+ > Cu2+, while calcined limestone exhibits a higher selectivity for Pb2+ compared to Cu2+ and Cd2+. Hence, various adsorption isotherm and kinetic models were examined to explore different patterns and behaviors of adsorption. So, the results indicate that calcined limestone has great potential for eliminating cationic heavy metal species from industrial water solutions.

Research on flexible weaving planning based on NSGA-II algorithm

Facing the shift in the weaving industry from mass production to a more diversified, small-batch production model, traditional production scheduling systems are no longer capable of meeting the demand for rapid market response. To address this issue, this paper first analyzes the production process of a weaving workshop, identifying key scheduling challenges such as order allocation, equipment selection, and operation sequencing. Based on this analysis, a flexible job shop multi-objective scheduling model tailored for weaving workshops is developed. To handle the multiple constraints and optimization goals inherent in the model, an improved NSGA-II algorithm is proposed. This algorithm combines artificial bee colony (ABC) algorithm for population initialization with simulated annealing (SA) for population filtering. Simulation examples and case studies from actual workshops demonstrate that the improved NSGA-II algorithm outperforms other algorithms in solving the scheduling problem for weaving workshops. The proposed multi-objective scheduling model and its improved algorithm provide accurate and efficient optimization solutions for workshop scheduling.

In Silico Method for ssDNA Aptamer Binding with Aurora Kinase A Protein.

While traditional assay methods face challenges in detecting specific proteins, aptamers, known for their high specificity and affinity, are emerging as a valuable biomarker detection tool. Aurora kinase A (AURKA) plays a role in cell division and influences stem cell reprogramming. In this study, an in silico approach method was conducted for a random ssDNA aptamer sequence selection and its binding with AURKA. The aptamer was designed based on AURKA's structure and nucleic acid sequence, obtained from PDB RCSB. Using RNAfold and RNA composer, we predicted the aptamer's secondary and tertiary structures. Protein-aptamer binding was analyzed via HDOCK and HADDOCK, with 2D interactions visualized in LIGPLOT+ v1.4. Autodock 4 and NAMD 2.3 tools were used to conduct docking and MD simulation studies.

Accurate sequence-to-affinity models for SH2 domains from multi-round peptide binding assays coupled with free-energy regression.

Short linear peptide motifs play important roles in cell signaling. They can act as modification sites for enzymes and as recognition sites for peptide binding domains. SH2 domains bind specifically to tyrosine-phosphorylated proteins, with the affinity of the interaction depending strongly on the flanking sequence. Quantifying this sequence specificity is critical for deciphering phosphotyrosine-dependent signaling networks. In recent years, protein display technologies and deep sequencing have allowed researchers to profile SH2 domain binding across thousands of candidate ligands. Here, we present a concerted experimental and computational strategy that improves the predictive power of SH2 specificity profiling. Through multi-round affinity selection and deep sequencing with large randomized phosphopeptide libraries, we produce suitable data to train an additive binding free energy model that covers the full theoretical ligand sequence space. Our models can be used to predict signaling network connectivity and the impact of missense variants in phosphoproteins on SH2 binding.

Peptide design to control protein-protein interactions.

Targeting of protein-protein interactions has become of huge interest in every aspect of medicinal and biological sciences. The control of protein interactions selectively offers the opportunity to control biological processes while limiting off target effects. This interest has massively increased with the development of cryo-EM and protein structure prediction with tools such as RosettaFold and AlphaFold. When designing molecules to control protein interactions, either inhibition or stabilisation, a starting point is commonly peptide design. This tutorial review describes that process, highlighting the selection of an initial sequence with and without structural information. Subsequently, methods for how the sequence can be analysed for key residues and how this information can be used to optimise the ligand efficiency are highlighted. Finally a discussion on how peptides can be further modified to increase their affinity and cell permeability, improving their drug-like properties, is presented.

TCR transgenic clone selection guided by immune receptor analysis and single-cell RNA expression of polyclonal responders

Since the precursor frequency of naive T cells is extremely low, investigating the early steps of antigen-specific T cell activation is challenging. To overcome this detection problem, adoptive transfer of a cohort of T cells purified from T cell receptor (TCR) transgenic donors has been extensively used but is not readily available for emerging pathogens. Constructing TCR transgenic mice from T cell hybridomas is a labor-intensive and sometimes erratic process, since the best clones are selected based on antigen-induced CD69 upregulation or IL-2 production in vitro, and TCR chains are polymerase chain reaction (PCR)-cloned into expression vectors. Here, we exploited the rapid advances in single-cell sequencing and TCR repertoire analysis to select the best clones without hybridoma selection, and generated CORSET8 mice (CORona Spike Epitope specific CD8 T cell), carrying a TCR specific for the Spike protein of SARS-CoV-2. Implementing newly created DALI software for TCR repertoire analysis in single-cell analysis enabled the rapid selection of the ideal responder CD8 T cell clone, based on antigen reactivity, proliferation, and immunophenotype in vivo. Identified TCR sequences were inserted as synthetic DNA into an expression vector and transgenic CORSET8 donor mice were created. After immunization with Spike/CpG-motifs, mRNA vaccination or SARS-CoV-2 infection, CORSET8 T cells strongly proliferated and showed signs of T cell activation. Thus, a combination of TCR repertoire analysis and scRNA immunophenotyping allowed rapid selection of antigen-specific TCR sequences that can be used to generate TCR transgenic mice.

TCR transgenic clone selection guided by immune receptor analysis and single-cell RNA expression of polyclonal responders.

Since the precursor frequency of naive T cells is extremely low, investigating the early steps of antigen-specific T cell activation is challenging. To overcome this detection problem, adoptive transfer of a cohort of T cells purified from T cell receptor (TCR) transgenic donors has been extensively used but is not readily available for emerging pathogens. Constructing TCR transgenic mice from T cell hybridomas is a labor-intensive and sometimes erratic process, since the best clones are selected based on antigen-induced CD69 upregulation or IL-2 production in vitro, and TCR chains are polymerase chain reaction (PCR)-cloned into expression vectors. Here, we exploited the rapid advances in single-cell sequencing and TCR repertoire analysis to select the best clones without hybridoma selection, and generated CORSET8 mice (CORona Spike Epitope specific CD8 T cell), carrying a TCR specific for the Spike protein of SARS-CoV-2. Implementing newly created DALI software for TCR repertoire analysis in single-cell analysis enabled the rapid selection of the ideal responder CD8 T cell clone, based on antigen reactivity, proliferation, and immunophenotype in vivo. Identified TCR sequences were inserted as synthetic DNA into an expression vector and transgenic CORSET8 donor mice were created. After immunization with Spike/CpG-motifs, mRNA vaccination or SARS-CoV-2 infection, CORSET8 T cells strongly proliferated and showed signs of T cell activation. Thus, a combination of TCR repertoire analysis and scRNA immunophenotyping allowed rapid selection of antigen-specific TCR sequences that can be used to generate TCR transgenic mice.

Understanding Localized Current Leakage in Silicon‐Based Heterojunction Solar Cells

ABSTRACTCurrent leakage through localized stacked structures, comprising opposite types of carrier‐selective transport layers, is a prevalent issue in silicon‐based heterojunction solar cells. Nevertheless, the behavior of this leakage region remains unclear, leading to a lack of guidance for structural design, material selection and process sequence control, thereby causing fluctuations of device performance. This study elucidates current‐voltage characteristics, influential factors, and underlying carrier transport mechanism of the leakage region with different stacking sequences and explores their impact on various configurations of solar cells. Characteristics of the leakage region resembling Esaki diodes or reverse diodes are revealed, along with the bias conditions of the leakage region at different locations across the solar cell. The findings suggest that modulating the behavior of the leakage region is feasible for improving device performance or serving specific purposes. This work provides guidance for the design and assessment of current leakage in the edge region of front and back contact cells, in the gap region of conventional back‐contacted cells, as well as in the tunneling region of tunneling back‐contacted cells and tandem cells.

Probing mechanical selection in diverse eukaryotic genomes through accurate prediction of 3D DNA mechanics.

Connections between the mechanical properties of DNA and biological functions have been speculative due to the lack of methods to measure or predict DNA mechanics at scale. Recently, a proxy for DNA mechanics, cyclizability, was measured by loop-seq and enabled genome-scale investigation of DNA mechanics. Here, we use this dataset to build a computational model predicting bias-corrected intrinsic cyclizability, with near-perfect accuracy, solely based on DNA sequence. Further, the model predicts intrinsic bending direction in 3D space. Using this tool, we aimed to probe mechanical selection - that is, the evolutionary selection of DNA sequence based on its mechanical properties - in diverse circumstances. First, we found that the intrinsic bend direction of DNA sequences correlated with the observed bending in known protein-DNA complex structures, suggesting that many proteins co-evolved with their DNA partners to capture DNA in its intrinsically preferred bent conformation. We then applied our model to large-scale yeast population genetics data and showed that centromere DNA element II, whose consensus sequence is unknown, leaving its sequence-specific role unclear, is under mechanical selection to increase the stability of inner-kinetochore structure and to facilitate centromeric histone recruitment. Finally, in silico evolution under strong mechanical selection discovered hallucinated sequences with cyclizability values so extreme that they required experimental validation, yet, found in nature in the densely packed mitochondrial(mt) DNA of Namystynia karyoxenos, an ocean-dwelling protist with extreme mitochondrial gene fragmentation. The need to transmit an extraordinarily large amount of mtDNA, estimated to be > 600 Mb, in combination with the absence of mtDNA compaction proteins may have pushed mechanical selection to the extreme. Similarly extreme DNA mechanics are observed in bird microchromosomes, although the functional consequence is not yet clear. The discovery of eccentric DNA mechanics in unrelated unicellular and multicellular eukaryotes suggests that we can predict extreme natural biology which can arise through strong selection. Our methods offer a way to study the biological functions of DNA mechanics in any genome and to engineer DNA sequences with desired mechanical properties.

A Critical Review of Primary School Students’ Difficulties in Learning Programming Through Educational Games

This study critically reviews sixteen empirical studies that investigate the various difficulties that primary school students encounter while learning programming through educational games. Specifically, the challenges that students face in understanding basic programming concepts and the game elements that contribute to these difficulties, as well as the extent to which students can transfer the knowledge gained to contexts beyond games are analyzed. The results indicate that students primarily struggle with understanding loops (both simple and nested), while difficulties with selection structures and sequence structures are less pronounced. Regarding game elements, students face difficulties in interpreting command symbols representing directions, understanding graphical interface elements representing programming constructs, and managing complex user interfaces. The results imply a need for further empirical studies to explore how well students can apply their acquired programming knowledge to contexts beyond games. Although the need for further research is highlighted, the findings of the study provide valuable implications both to educators and game designers for a more effective incorporation of educational games to the teaching of programming, and a more straightforward depiction of programming concepts and a more user-friendly graphical user interface respectively.

Analysis of the MODIST Sequence for Selective Proton-Proton Recoupling.

Theoretical and simulated analyses of selective homonuclear dipolar recoupling sequences serve as primary tools for understanding and determining the robustness of these sequences under various conditions. In this article, we investigate the recently proposed first-order dipolar recoupling sequence known as MODIST (Modest Offset Difference Internuclear Selective Transfer). We evaluate the MODIST transfer efficiency, assessing its dependence on rf-field strengths and the number of simulated spins, extending up to 10 spins. This helps to identify conditions that enhance polarization transfer among spins that are nearby in frequency, particularly among aliphatic protons. The exploration uncovers a novel effect for first-order selective recoupling sequences that we term "facilitated dipolar recoupling". This effect amplifies the recoupled dipolar interaction between distant spins due to the presence of additional strongly dipolar-coupled spins. Unlike the third spin-assisted recoupling mechanism, facilitated dipolar recoupling only requires a coupling to one of the two distant spins of interest. Experimental demonstration of MODIST, including at different rf-field strengths, was carried out with the membrane protein influenza A M2 in lipid bilayers using 55 kHz magic-angle spinning (MAS). Reducing MODIST rf-field strength by a factor of 2 unveils possibilities for detecting Hα-Hα and HMeth-HMeth correlations with a 3D (H)C(H)(H)CH experiment under fast MAS rates, all achievable without specific spin labeling.

ESR Essentials: Image evaluation of patients with seizures and epilepsy-practice recommendations by the European Society of Neuroradiology.

Epilepsy, a neurological disorder characterised by recurrent seizures, poses significant challenges in diagnosis, treatment, and management. Understanding the underlying causes and identifying precise anatomical locations of epileptogenic foci are critical for effective management strategies, particularly in drug-resistant patients. Neuroimaging techniques, particularly magnetic resonance (MR), play a pivotal role in the evaluation of epilepsy patients, offering insights into structural abnormalities, epileptogenic lesions, and functional alterations within the brain. Diverse clinical scenarios that warrant neuroimaging in epilepsy patients, ranging from first-onset seizures to drug-resistant epilepsy, will be presented, elucidating the considerations and recommendations for imaging modalities. The dedicated MR protocol for epilepsy patients will be discussed, justifying the rationale behind sequence selection and optimisation strategies and providing clues about how to read these magnetic resonance imaging (MRI) exams. Finally, MR findings associated with common epileptogenic lesions, such as hippocampal sclerosis, focal cortical dysplasia, and long-term epilepsy-associated tumours, will be described. This article reviews essential concepts, including definitions, classification, imaging indications, protocols, and neuroradiological findings, aiming to understand how neuroimaging contributes to diagnosing and managing epilepsy comprehensively. KEY POINTS: MR should be performed in adults and children with a recent diagnosis of epilepsy of unknown aetiology, a first seizure, and a negative CT. Performing a dedicated MR protocol in focal epilepsy is essential for increasing the detection of potentially epileptogenic lesions. For presurgical evaluations, MR abnormalities should correlate with the electric pattern, semiology data, or other neuroimaging examination to be considered the epileptogenic lesion.

A Small-Molecule Approach Enables RNA Aptamers to Function as Sensors for Reactive Inorganic Targets.

Fluorescent light-up aptamer (FLAP) systems are promising (bio)sensing platforms that are genetically encodable. However, FLAP-mediated detection of each distinct target necessitates either in vitro selection or engineering of nucleic acid sequences. Furthermore, an aptamer that binds an inorganic target or a chemical species with a short lifetime is challenging to realize. Here, we describe a small-molecule approach that makes it possible for a single FLAP system to detect chemically unique, non-fluorogenic, and reactive inorganics. We developed functionalized pre-ligands of RNA aptamers that bind benzylidene imidazolinones (Baby Spinach, Broccolli, Squash). Reactive inorganics, hydrogen sulfide (H2S/HS-) and hydrogen peroxide (H2O2), can specifically convert these pre-ligands into native ligands that fluoresce with FLAPs. Adaptation of this platform to live cells opened an opportunity for constructing whole-cell sensors: Escherichia coli transformed with a Baby Spinach-encoding plasmid and incubated with pre-ligands generated fluorescence in response to exogenous H2S/HS- or H2O2. Leveraging the functional group reactivity of small molecules eliminates the requirement of in vitro selection of a new aptamer sequence or oligonucleotide scaffold engineering for distinct molecular targets. Our method allows for detecting inorganic, short-lived species, thereby advancing FLAP systems beyond their current capabilities.