Experimental Design Considerations Research Articles

Motion Artifacts in Dynamic EEG Recordings: Experimental Observations, Electrical Modelling, and Design Considerations

Despite the progress in the development of innovative EEG acquisition systems, their use in dynamic applications is still limited by motion artifacts compromising the interpretation of the collected signals. Therefore, extensive research on the genesis of motion artifacts in EEG recordings is still needed to optimize existing technologies, shedding light on possible solutions to overcome the current limitations. We identified three potential sources of motion artifacts occurring at three different levels of a traditional biopotential acquisition chain: the skin-electrode interface, the connecting cables between the detection and the acquisition systems, and the electrode-amplifier system. The identified sources of motion artifacts were modelled starting from experimental observations carried out on EEG signals. Consequently, we designed customized EEG electrode systems aiming at experimentally disentangling the possible causes of motion artifacts. Both analytical and experimental observations indicated two main residual sites responsible for motion artifacts: the connecting cables between the electrodes and the amplifier and the sudden changes in electrode-skin impedance due to electrode movements. We concluded that further advancements in EEG technology should focus on the transduction stage of the biopotentials amplification chain, such as the electrode technology and its interfacing with the acquisition system.

Ubiquitylomics: An Emerging Approach for Profiling Protein Ubiquitylation in Skeletal Muscle.

Skeletal muscle is a highly adaptable tissue, finely tuned by various physiological and pathological factors. Whilst the pivotal role of skeletal muscle in overall health is widely acknowledged, unravelling the underlying molecular mechanisms poses ongoing challenges. Protein ubiquitylation, a crucial post-translational modification, is involved in regulating most biological processes. This widespread impact is achieved through a diverse set of enzymes capable of generating structurally and functionally distinct ubiquitin modifications on proteins. The complexity of protein ubiquitylation has presented significant challenges in not only identifying ubiquitylated proteins but also characterising their functional significance. Mass spectrometry enables in-depth analysis of proteins and their post-translational modification status, offering a powerful tool for studying protein ubiquitylation and its biological diversity: an approach termed ubiquitylomics. Ubiquitylomics has been employed to tackle different perspectives of ubiquitylation, including but not limited to global quantification of substrates and ubiquitin linkages, ubiquitin site recognition and crosstalk with other post-translational modifications. As the field of mass spectrometry continues to evolve, the usage of ubiquitylomics has unravelled novel insights into the regulatory mechanisms of protein ubiquitylation governing biology. However, ubiquitylomics research has predominantly been conducted in cellular models, limiting our understanding of ubiquitin signalling events driving skeletal muscle biology. By integrating the intricate landscape of protein ubiquitylation with dynamic shifts in muscle physiology, ubiquitylomics promises to not only deepen our understanding of skeletal muscle biology but also lay the foundation for developing transformative muscle-related therapeutics. This review aims to articulate how ubiquitylomics can be utilised by researchers to address different aspects of ubiquitylation signalling in skeletal muscle. We explore methods used in ubiquitylomics experiments, highlight relevant literature employing ubiquitylomics in the context of skeletal muscle and outline considerations for experimental design.

Considerations for event-related gamma-aminobutyric acid functional magnetic resonance spectroscopy.

The use of sequential proton magnetic resonance spectroscopy (MRS) to follow glutamate and gamma-aminobutyric acid (GABA) changes during functional task-based paradigms, functional MRS (fMRS), has increased. This technique has been used to investigate GABA dynamics during both sensory and behavioural tasks, usually with long 'block design' paradigms. Recently, there has been an increase in interest in the use of short stimuli and 'event-related' tasks. While changes in glutamate can be readily followed by collecting multiple individual transients (or shots), measurement of GABA, especially at 3 T, is usually performed using editing techniques like Mescher-Garwood point-resolved spectroscopy (MEGA-PRESS), which by its nature is a dual shot approach. This poses problems when considering an event-related experiment, where it is unclear when GABA may change, or how this may affect the individual subspectra of the MEGA-PRESS acquisition. To address this issue, MEGA-PRESS data were simulated to reflect the effect of a transient change in GABA concentration due to a short event-related stimulus. The change in GABA was simulated for both the ON and OFF subspectra, and the effect of three different conditions (increase only during ON acquisition, increase during OFF acquisition and increase across both) on the corresponding edited GABA spectrum was modelled. Results show that a transient increase in GABA that only occurs during the ON subspectral acquisition, while not changing the results much from when GABA is changed across both conditions, will give a much larger change in the edited GABA spectrum than a transient increase that occurs only during the OFF subspectral acquisition. These results suggest that researchers should think carefully about the design of any event-related fMRS studies using MEGA-PRESS, as well as the analysis of other functional paradigms where transient changes in GABA may be expected. Experimental design considerations are therefore discussed, and suggestions are made.

Drug-Drug Interactions and Synergy: From Pharmacological Models to Clinical Application.

This review explores the concept of synergy in pharmacology, emphasizing its importance in optimizing treatment outcomes through the combination of drugs with different mechanisms of action. Synergy, defined as an effect greater than the expected additive effect elicited by individual agents according to specific predictive models, offers a promising approach to enhance therapeutic efficacy while minimizing adverse events. The historical evolution of synergy research, from ancient civilizations to modern pharmacology, highlights the ongoing quest to understand and harness synergistic interactions. Key concepts, such as concentration-response curves, additive effects, and predictive models, are discussed in detail, emphasizing the need for accurate assessment methods throughout translational drug development. Although various mathematical models exist for synergy analysis, selecting the appropriate model and software tools remains a challenge, necessitating careful consideration of experimental design and data interpretation. Furthermore, this review addresses practical considerations in synergy assessment, including preclinical and clinical approaches, mechanism of action, and statistical analysis. Optimizing synergy requires attention to concentration/dose ratios, target site localization, and timing of drug administration, ensuring that the benefits of combination therapy detected bench-side are translatable into clinical practice. Overall, the review advocates for a systematic approach to synergy assessment, incorporating robust statistical analysis, effective and simplified predictive models, and collaborative efforts across pivotal sectors, such as academic institutions, pharmaceutical companies, and regulatory agencies. By overcoming critical challenges and maximizing therapeutic potential, effective synergy assessment in drug development holds promise for advancing patient care. SIGNIFICANCE STATEMENT: Combining drugs with different mechanisms of action for synergistic interactions optimizes treatment efficacy and safety. Accurate interpretation of synergy requires the identification of the expected additive effect. Despite innovative models to predict the additive effect, consensus in drug-drug interactions research is lacking, hindering the bench-to-bedside development of combination therapies. Collaboration among science, industry, and regulation is crucial for advancing combination therapy development, ensuring rigorous application of predictive models in clinical settings.

Orientation selectivity mapping in the visual cortex

The orientation map is one of the most well-studied functional maps of the visual cortex. However, results from the literature are of different qualities. Clear boundaries among different orientation domains and blurred uncertain distinctions were shown in different studies. These unclear imaging results will lead to an inaccuracy in depicting cortical structures, and the lack of consideration in experimental design will also lead to biased depictions of the cortical features. How we accurately define orientation domains will impact the entire field of research. In this study, we test how spatial frequency (SF), stimulus size, location, chromatic, and data processing methods affect the orientation functional maps (including a large area of dorsal V4, and parts of dorsal V1) acquired by intrinsic signal optical imaging. Our results indicate that, for large imaging fields, large grating stimuli with mixed SF components should be considered to acquire the orientation map. A diffusion model image enhancement based on the difference map could further improve the map quality. In addition, the similar outcomes of achromatic and chromatic gratings indicate two alternative types of afferents from LGN, pooling in V1 to generate cue-invariant orientation selectivity.

RNA-Seq Data Analysis: A Practical Guide for Model and Non-Model Organisms.

RNA sequencing (RNA-seq) has emerged as a powerful tool for assessing genome-wide gene expression, revolutionizing various fields of biology. However, analyzing large RNA-seq datasets can be challenging, especially for students or researchers lacking bioinformatics experience. To address these challenges, we present a comprehensive guide to provide step-by-step workflows for analyzing RNA-seq data, from raw reads to functional enrichment analysis, starting with considerations for experimental design. This is designed to aid students and researchers working with any organism, irrespective of whether an assembled genome is available. Within this guide, we employ various recognized bioinformatics tools to navigate the landscape of RNA-seq analysis and discuss the advantages and disadvantages of different tools for the same task. Our protocol focuses on clarity, reproducibility, and practicality to enable users to navigate the complexities of RNA-seq data analysis easily and gain valuable biological insights from the datasets. Additionally, all scripts and a sample dataset are available in a GitHub repository to facilitate the implementation of the analysis pipeline. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Analysis of data from a model plant with an available reference genome Basic Protocol 2: Gene ontology enrichment analysis Basic Protocol 3: De novo assembly of data from non-model plants.

Prime-induced illusion of control: The influence of unconscious priming on self-initiated actions and the role of regression to the mean

To what degree human cognition is influenced by subliminal stimuli is a controversial empirical question. One striking example was reported by Linser and Goschke (2007): participants overestimated how much control they had over objectively uncontrollable stimuli when masked congruent primes were presented immediately before the action. Critically, however, unawareness of the masked primes was established by post hoc data selection. In our preregistered study we sought to explore these findings while adjusting prime visibility based on individual thresholds, so that each participant underwent both visible and non-visible conditions. In experiment 1, N = 39 participants engaged in a control judgement task: following the presentation of a semantic prime, they freely selected between two keys, which triggered the appearance of a colored circle. The color of the circles, however, was independent of the key-press. Subsequently, participants assessed their perceived control over the circle’s color, based on their key-presses, via a rating scale that ranged from 0 % (no control) to 100 % (complete control). Contrary to Linser and Goschke (2007)'s findings, this experiment demonstrated that predictive information influenced the experience of agency only when primes were consciously processed. In experiment 2, utilizing symbolic (arrow) primes, N = 35 participants had to rate their feeling of control over the effect-stimulus’ identity during a two-choice identification paradigm (i.e., they were instructed to press a key corresponding to a target stimulus; with a contingency between target and effect stimulus of 75 %/25 %). The results revealed no significant influence of subliminal priming on agency perceptions. In summary, this study implies that unconscious stimuli may not exert a substantial influence on the conscious experience of agency, underscoring the need for careful consideration of methodological aspects and experimental design's impact on observed phenomena.

A randomized controlled trial of intermittent theta burst stimulation to the medial prefrontal cortex for tobacco use disorder: Clinical efficacy and safety

ObjectiveThis study aimed to evaluate the clinical efficacy and safety of administering intermittent theta burst stimulation (iTBS) to the medial prefrontal cortex for tobacco use disorder. MethodsA randomized sham-controlled trial was conducted, with 38 participants receiving 28 sessions of active (n=25) or sham (n=13) iTBS (2 sessions/day, 600 pulses/session, 110% resting motor threshold, AFz target) along with smoking cessation education (Forever Free © booklets) over 14 visits. Primary outcomes included self-reported cigarette consumption and abstinence, verified by urinary cotinine tests. Secondary outcomes included symptoms of tobacco use disorder, negative mood, and safety/tolerability. ResultsBoth active and sham groups reported reduced cigarette consumption (β = −0.12, p = 0.015), cigarette craving (β = −0.16, p = 0.002), and tobacco withdrawal symptoms (β = −0.05, p < 0.001). However, there were no significant time x group interaction effects for any measure. Similarly, the two groups had no significant differences in urinary cotinine-verified abstinence. Adverse events occurred with similar frequency in both groups. ConclusionThere were no differences in cigarette consumption between the active and sham iTBS groups, both groups decreased cigarette consumption similarly. Further research is needed to compare iTBS to standard high-frequency rTMS and explore the potential differences in efficacy. Despite limitations, this study contributes to experimental design considerations for TMS as a novel intervention for tobacco and other substance use disorders, emphasizing the need for a more comprehensive understanding of the stimulation parameters and target sites.

Cortisol as a Marker of Pain and Distress After Acute Musculoskeletal Trauma.

The best available predictors of chronic pain development broadly encompass baseline metrics of cognition (ie, beliefs/expectations) about the trauma and resulting symptoms. In the context of musculoskeletal trauma, we have previously shown the Traumatic Injuries Distress Scale (TIDS) capable of risk-stratifying cohorts for chronic pain development. Here, we explore whether the physiological marker cortisol shows meaningful associations with cognitions predictive of pain outcomes. Data for these cross-sectional analyses were drawn from an observational study that recruited 130 participants presenting to the hospital with pain related to a recent noncatastrophic Musculoskeletal trauma. Cortisol was measured from the participant's hair, saliva, and blood. In addition to pain and distress questionnaires, metadata such as age, sex, body mass index (BMI), adverse childhood events, pretrauma stress levels, and pre-existing physical/psychological comorbidities were collected. We found no significant associations between cortisol levels and pain or distress in isolation. When stratified by person-level variables, associations were revealed with distress (TIDS) in young age and low pretrauma stress subgroups (hair cortisol) and low BMI (blood cortisol). Through hierarchical regression analysis, we found the "cortisol X age" or "cortisol X stress" interaction terms significantly improved TIDS prediction beyond either variable in isolation (Age: ∆ R2 =15.1%; pretrauma stress: ∆ R2 =9.1%). Our findings suggest that while linear correlations between pain-related distress and cortisol may be overly simplistic, certain person-level variables such as age, pretrauma stress, and BMI are worthy of consideration for experimental design or confounder characterization in future studies of pain and distress following musculoskeletal injuries especially when "trait" (hair) cortisol is the predictor variable.

Methods for the Design and Analysis of Analytical Ultracentrifugation Experiments.

Analytical ultracentrifugation experiments play an integral role in the solution-phase characterization of biological macromolecules and their interactions. This unit discusses the design of sedimentation velocity and sedimentation equilibrium experiments performed with a Beckman Proteomelab XL-A or XL-I analytical ultracentrifuge and with a Beckman Optima AUC. Instrument settings and experimental design considerations are explained, and strategies for the analysis of experimental data with the UltraScan data analysis software package are presented. Special attention is paid to the strengths and weaknesses of the available detectors, and guidance is provided on how to extract maximum information from analytical ultracentrifugation experiments. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC.

Production and use of antigen tetramers to study antigen-specific B cells.

B cells generate antibodies that provide protection from infection, but also cause pathology in autoimmune and allergic conditions. Antigen-specific B cells can be detected by binding their surface antibody receptors with native antigens conjugated to fluorescent probes, a technique that has revealed substantial insight into B cell activation and function. This protocol describes the process of generating fluorescent antigen tetramer probes and delineates a process of enriching large samples based on antigen-specificity for high-resolution analyses of the antigen-specific B cell repertoire. Enrichment of tetramer-binding cells allows for detection of antigen-specific B cells as rare as 1 in 100 million cells, providing sufficient resolution to study naive B cells and IgE-expressing cells by flow cytometry. The generation of antigen tetramers involves antigen biotinylation, assessment of biotin:antigen ratio for optimal tetramer loading and polymerization around a streptavidin-fluorophore backbone. We also describe the construction of a control tetramer to exclude B cells binding to the tetramer backbone. We provide a framework to validate whether tetramer probes are detecting true antigen-specific B cells and discuss considerations for experimental design. This protocol can be performed by researchers trained in basic biomedical/immunological research techniques, using instrumentation commonly found in most laboratories. Constructing the antigen and control tetramers takes 9 h, though their specificity should be assessed before experimentation and may take weeks to months depending on the method of validation. Sample enrichment requires ~2 h but is generally time and cost neutral as fewer cells are run through the flow cytometer.

A protocol to simultaneously examine cardiorespiratory, cerebrovascular and neurophysiological responses inside a hypobaric chamber.

We describe a protocol to examine neurophysiological (electroencephalography, EEG), cerebrovascular (ultrasound assessments of middle cerebral artery blood velocity, MCAv) and cardiorespiratory (blood pressure, oxygen saturation, end-tidal gases, respiratory rate) responses inside a hypobaric chamber. This procedure aims to standardize the methodology in experiments conducted within a hypobaric chamber such as comparing normobaric and hypobaric hypoxia. This is important because current understanding of relationships between neurophysiological activity, and cerebrovascular and cardiorespiratory responses under varying environmental conditions remains limited. This procedure combines simultaneous neurophysiological, cardiorespiratory and cerebrovascular evaluations, allowing a comprehensive understanding of electro-neurophysiological activity. Our protocol requires an hour and a half of equipment setup, 1-1.5 hours of participant set-up, and 30 minutes of experimental data collection. Since multiple simultaneous physiological recordings, including EEG in this environment, can be fraught with pitfalls, we also provide practical considerations for experimental design and recording setup. Advanced knowledge of hypobaric chamber operation is required, alongside expertise in EEG and transcranial Doppler ultrasonography. Following our procedure one will acquire simultaneous recordings of neurophysiological, cerebrovascular and cardiorespiratory data.

Precise surface functionalization of PLGA particles for human T cell modulation.

The biofunctionalization of synthetic materials has extensive utility for biomedical applications, but approaches to bioconjugation typically show insufficient efficiency and controllability. We recently developed an approach by building synthetic DNA scaffolds on biomaterial surfaces that enables the precise control of cargo density and ratio, thus improving the assembly and organization of functional cargos. We used this approach to show that the modulation and phenotypic adaptation of immune cells can be regulated using our precisely functionalized biomaterials. Here, we describe the three key procedures, including the fabrication of polymeric particles engrafted with short DNA scaffolds, the attachment of functional cargos with complementary DNA strands, and the surface assembly control and quantification. We also explain the critical checkpoints needed to ensure the overall quality and expected characteristics of the biological product. We provide additional experimental design considerations for modifying the approach by varying the material composition, size or cargo types. As an example, we cover the use of the protocol for human primary T cell activation and for the identification of parameters that affect ex vivo T cell manufacturing. The protocol requires users with diverse expertise ranging from synthetic materials to bioconjugation chemistry to immunology. The fabrication procedures and validation assays to design high-fidelity DNA-scaffolded biomaterials typically require 8 d.

An Overview of the Untargeted Analysis Using LC–MS (QTOF): Experimental Process and Design Considerations

Untargeted analysis using liquid chromatography with tandem mass spectrometry (LC–MS/MS) chemical profiling has become a valuable tool for providing insight into the variations found in a sample set. However, the large data sets often generated, frequently yielding upwards of 20,000 features or more, can be overwhelming. Key elements in creating an experimental design are one of the most pivotal aspects of verifying statistical variance in a sample set. Therefore, care should be taken when an experimental design is developed and when statistical tools are used to perform data reduction and processing.

An Integrated Multi-Omics and Artificial Intelligence Framework for Advance Plant Phenotyping in Horticulture.

This review discusses the transformative potential of integrating multi-omics data and artificial intelligence (AI) in advancing horticultural research, specifically plant phenotyping. The traditional methods of plant phenotyping, while valuable, are limited in their ability to capture the complexity of plant biology. The advent of (meta-)genomics, (meta-)transcriptomics, proteomics, and metabolomics has provided an opportunity for a more comprehensive analysis. AI and machine learning (ML) techniques can effectively handle the complexity and volume of multi-omics data, providing meaningful interpretations and predictions. Reflecting the multidisciplinary nature of this area of research, in this review, readers will find a collection of state-of-the-art solutions that are key to the integration of multi-omics data and AI for phenotyping experiments in horticulture, including experimental design considerations with several technical and non-technical challenges, which are discussed along with potential solutions. The future prospects of this integration include precision horticulture, predictive breeding, improved disease and stress response management, sustainable crop management, and exploration of plant biodiversity. The integration of multi-omics and AI holds immense promise for revolutionizing horticultural research and applications, heralding a new era in plant phenotyping.

Heterochronic Plasma Transfer: Experimental Design, Considerations, and Technical Challenges.

Experimental approaches such as Heterochronic Plasma Transfer (HPT) provide insights into the aging process and help identify the factors that impact aging, with the aim of developing anti-aging therapies. HPT involves the transfer of plasma from an animal of one age to an animal of a different age and highlights the effects of the systemic environment on aging. Despite its importance as an aging research tool, HPT is not without limitations and HPT experiments across various studies differ in key experimental designs considerations, presenting a challenge in obtaining comparable outcomes. In this review, we examine the caveats and experimental design considerations of HPT as a research tool. We provide insights into plasma preparation procedures, route of administration, dosing regimen, and appropriate controls to assist investigators in achieving their experimental goals.

Microscale dynamics in thermoreversible hydrogels: Impact of probe size and concentration

Passive microrheology techniques using dynamic light scattering (DLS) and X-ray photon correlation spectroscopy (XPCS) have emerged as important techniques for characterizing the dynamics and viscoelastic properties of soft polymeric biomaterials. However, the impact of probe particle type, size, and concentration are important considerations in interpretation of results and comparison to properties obtained from bulk rheology measurements. In this work, we investigate a model thermoreversible polymeric hydrogel and compare results from DLS-microrheology with different size and concentrations of polystyrene probe particles and XPCS-microrheology with inorganic nanoparticles. We obtained trends that aligned most closely with the macroscopic rheology with probe particles that are slightly larger than the characteristic length scale of the gel structure, but within the same order of magnitude. By contrast, larger probe particles yielded microrheology data that are more dominated by elastic behavior than what we might expect from bulk rheology experiments, while use of small inorganic nanoparticles in XPCS-microrheology resulted in a more a more viscous response than would be expected based on the bulk rheology. This study demonstrates the utility of passive DLS- and XPCS-based microrheology in characterizing the rheological properties of complex polymeric biomaterials, while also highlighting important considerations in experimental design and choice of type, size, and concentration of probe particles used.

A biofunctional review of C-reactive protein (CRP) as a mediator of inflammatory and immune responses: differentiating pentameric and modified CRP isoform effects.

C-reactive protein (CRP) is an acute phase, predominantly hepatically synthesized protein, secreted in response to cytokine signaling at sites of tissue injury or infection with the physiological function of acute pro-inflammatory response. Historically, CRP has been classified as a mediator of the innate immune system, acting as a pattern recognition receptor for phosphocholine-containing ligands. For decades, CRP was envisioned as a single, non-glycosylated, multi-subunit protein arranged non-covalently in cyclic symmetry around a central void. Over the past few years, however, CRP has been shown to exist in at least three distinct isoforms: 1.) a pentamer of five identical globular subunits (pCRP), 2.) a modified monomer (mCRP) resulting from a conformational change when subunits are dissociated from the pentamer, and 3.) a transitional isoform where the pentamer remains intact but is partially changed to express mCRP structural characteristics (referred to as pCRP* or mCRPm). The conversion of pCRP into mCRP can occur spontaneously and is observed under commonly used experimental conditions. In careful consideration of experimental design used in published reports of in vitro pro- and anti-inflammatory CRP bioactivities, we herein provide an interpretation of how distinctive CRP isoforms may have affected reported results. We argue that pro-inflammatory amplification mechanisms are consistent with the biofunction of mCRP, while weak anti-inflammatory mechanisms are consistent with pCRP. The interplay of each CRP isoform with specific immune cells (platelets, neutrophils, monocytes, endothelial cells, natural killer cells) and mechanisms of the innate immune system (complement), as well as differences in mCRP and pCRP ligand recognition and effector functions are discussed. This review will serve as a revised understanding of the structure-function relationship between CRP isoforms as related to inflammation and innate immunity mechanisms.

Experimental simulation of enhanced oil recovery on shale rocks using gas injection from material to Characterization: challenges and solutions

To assess the effect of gas injection as a technique for enhancing oil recovery (EOR) in shale rocks, extensive simulations have been carried out over the past few decades. However, the varied experimental conditions and inconsistent results have led to confusion and misinterpretation among researchers. To address this issue, we conducted a thorough literature review to examine the experimental materials, treatment methods, simulation designs, and characterization techniques used in previous studies. The experimental conditions of these studies were then carefully compared and analyzed. Based on our findings, we established a rigorous, precise, and reliable experimental workflow to minimize deviation and reduce uncertainty in simulation. Our updated description of the experimental design and operational considerations serves as a valuable resource for researchers working in this field, providing a clearer understanding of the critical role of experimental simulation in the success of EOR.

Study of molecular interactions by nonequilibrium capillary electrophoresis of equilibrium mixtures: Originations, developments, and applications.

Molecular interactions play a vital role in regulating various physiological and biochemical processes in vivo. Kinetic capillary electrophoresis (KCE) is an analytical platform that offers significant advantages in studying the thermodynamic and kinetic parameters of molecular interactions. It enables the simultaneous analysis of these parameters within an interaction pattern and facilitates the screening of binding ligands with predetermined kinetic parameters. Nonequilibrium capillary electrophoresis of equilibrium mixtures (NECEEM) was the first proposed KCE method, and it has found widespread use in studying molecular interactions involving proteins/aptamers, proteins/small molecules, and peptides/small molecules. The successful applications of NECEEM have demonstrated its promising potential for further development and broader application. However, there has been a dearth of recent reviews on NECEEM. To address this gap, our study provides a comprehensive description of NECEEM, encompassing its origins, development, and applications from 2015 to 2022. The primary focus of the applications section is on aptamer selection and screening of small-molecule ligands. Furthermore, we discuss important considerations in NECEEM experimental design, such as buffer suitability, detector selection, and protein adsorption. By offering this thorough review, we aim to contribute to the understanding, advancement, and wider utilization of NECEEM as a valuable tool for studying molecular interactions and facilitating the identification of potential ligands and targets.