Clinical trials with mechanism evaluation of intervention(s): mind the power and sample size calculation.

BACKGROUND: Mediation analysis, often completed as secondary analysis to estimating the main treatment effect, investigates situations where an exposure may affect an outcome both directly and indirectly through intervening mediator variables. Although there has been much research on power in mediation analyses, most of this has focused on the power to detect indirect effects. Little consideration has been given to the extent to which the strength of the mediation pathways, i.e., the intervention-mediator path and the mediator-outcome path respectively, may affect the power to detect the total effect, which would correspond to the intention-to-treat effect in a randomized trial. METHODS: We conduct a simulation study to evaluate the relation between the mediation pathways and the power of testing the total treatment effect, i.e., the intention-to-treat effect. Consider a sample size that is computed based on the usual formula for testing the total effect in a two-arm trial. We generate data for a continuous mediator and a normal outcome using the conventional mediation models. We estimate the total effect using simple linear regression and evaluate the power of a two-sided test. We explore multiple data generating scenarios by varying the magnitude of the mediation paths whilst keeping the total effect constant. RESULTS: Simulations show the estimated total effect is unbiased across the considered scenarios as expected, but the mean of its standard error increases with the magnitude of the mediator-outcome path and the variability in the residual error of the mediator, respectively. Consequently, this affects the power of testing the total effect, which is always lower than planned when the mediator-outcome path is non-trivial and a naive sample size was employed. Analytical explanation confirms that the intervention-mediator path does not affect the power of testing the total effect but the mediator-outcome path. The usual effect size consideration can be adjusted to account for the magnitude of the mediator-outcome path and its residual error. CONCLUSIONS: The sample size calculation for studies with efficacy and mechanism evaluation should account for the mediator-outcome association or risk the power to detect the total effect/intention-to-treat effect being lower than planned.

Management of neonatal and infant aortic thrombosis: A single-center case series.

Neonatal and infant aortic thrombosis is a rare albeit life-threatening thrombotic event, particularly seen in premature infants with an arterial catheter in place. We describe our institutional experience and approach to the management of 11 infants with occlusive or nearly occlusive aortic thrombosis. We observed at least partial thrombus resolution in all patients. Complications related to our management included minor bleeding in two children receiving thrombolytic therapy, and two major bleeding events in children receiving anticoagulation alone. Our experience adds to the growing body of evidence that thrombolysis and thrombectomy should be considered in managing neonatal/infant aortic thrombosis.

The impact of heterogeneity on the analysis of platform trials with normally distributed outcomes.

BACKGROUND: A platform trial approach allows adding arms to on-going trials to speed up intervention discovery programs. A control arm remains open for recruitment in a platform trial while intervention arms may be added after the onset of the study and could be terminated early for efficacy and/or futility when early stopping is allowed. The topic of utilising non-concurrent control data in the analysis of platform trials has been explored and discussed extensively. A less familiar issue is the presence of heterogeneity, which may exist for example due to modification of enrolment criteria and recruitment strategy. METHOD: We conduct a simulation study to explore the impact of heterogeneity on the analysis of a two-stage platform trial design. We consider heterogeneity in treatment effects and heteroscedasticity in outcome data across stages for a normally distributed endpoint. We examine the performance of some hypothesis testing procedures and modelling strategies. The use of non-concurrent control data is also considered accordingly. Alongside standard regression analysis, we examine the performance of a novel method that was known as the pairwise trials analysis. It is similar to a network meta-analysis approach but adjusts for treatment comparisons instead of individual studies using fixed effects. RESULTS: Several testing strategies with concurrent control data seem to control the type I error rate at the required level when there is heteroscedasticity in outcome data across stages and/or a random cohort effect. The main parameter of treatment effects in some analysis models correspond to overall treatment effects weighted by stage wise sample sizes; while others correspond to the effect observed within a single stage. The characteristics of the estimates are not affected significantly by the presence of a random cohort effect and/ or heteroscedasticity. CONCLUSION: In view of heterogeneity in treatment effect across stages, the specification of null hypotheses in platform trials may need to be more subtle. We suggest employing testing procedure of adaptive design as opposed to testing the statistics from regression models; comparing the estimates from the pairwise trials analysis method and the regression model with interaction terms may indicate if heterogeneity is negligible.

Standardizing the evaluation and management of iron deficiency anemia secondary to heavy menstrual bleeding in the emergency department.

BACKGROUND: Comprehensive guidelines for the management of iron deficiency anemia (IDA) in adolescents with heavy menstrual bleeding (HMB) presenting to the emergency department (ED) are lacking, leading to variability in care. We aimed to standardize the evaluation and management of these patients through the development and implementation of an evidence-based algorithm using quality improvement methodology. METHODS: Baseline data of the target population identified variability across four key measures of clinical management: therapy choice and administration, laboratory evaluation, hematology service consultation, and patient disposition. Literature review and consensus from pediatric hematology and gynecology providers informed a draft algorithm that was refined in an iterative multidisciplinary process. From December 2022 to July 2023, we aimed to achieve a 25% relative increase in patients to receive optimal management per the algorithm, while using sequential Plan-Do-Study-Act (PDSA) cycles. Process measures focusing on provider documentation and balancing measures, such as ED length of stay, were assessed concurrently. RESULTS: Forty-nine patients were evaluated during four PDSA cycles. Improvement of ≥40% above baseline regarding recommended therapy administration was achieved across four PDSA cycles. Adherence to recommended therapy choice improved from 57% (baseline) to 100%, minimal laboratory evaluation from 14% to 83%, hematology consultation from 36% to 100%, and appropriate disposition from 71% to 100%. ED length of stay remained stable. CONCLUSION: Implementation of a standardized algorithm for management of IDA secondary to HMB in adolescents in the ED increased adherence to evidence-based patient care.

Determining sample size in a personalized randomized controlled (PRACTical) trial.

In clinical settings with no commonly accepted standard-of-care, multiple treatment regimens are potentially useful, but some treatments may not be appropriate for some patients. A personalized randomized controlled trial (PRACTical) design has been proposed for this setting. For a network of treatments, each patient is randomized only among treatments which are appropriate for them. The aim is to produce treatment rankings that can inform clinical decisions about treatment choices for individual patients. Here we propose methods for determining sample size in a PRACTical design, since standard power-based methods are not applicable. We derive a sample size by evaluating information gained from trials of varying sizes. For a binary outcome, we quantify how many adverse outcomes would be prevented by choosing the top-ranked treatment for each patient based on trial results rather than choosing a random treatment from the appropriate personalized randomization list. In simulations, we evaluate three performance measures: mean reduction in adverse outcomes using sample information, proportion of simulated patients for whom the top-ranked treatment performed as well or almost as well as the best appropriate treatment, and proportion of simulated trials in which the top-ranked treatment performed better than a randomly chosen treatment. We apply the methods to a trial evaluating eight different combination antibiotic regimens for neonatal sepsis (NeoSep1), in which a PRACTical design addresses varying patterns of antibiotic choice based on disease characteristics and resistance. Our proposed approach produces results that are more relevant to complex decision making by clinicians and policy makers.

Glutamine induces lateral root initiation, stress responses, and disease resistance in Arabidopsis.

The production of glutamine (Gln) from NO3- and NH4+ requires ATP, reducing power, and carbon skeletons. Plants may redirect these resources to other physiological processes using Gln directly. However, feeding Gln as the sole nitrogen (N) source has complex effects on plants. Under optimal concentrations, Arabidopsis (Arabidopsis thaliana) seedlings grown on Gln have similar primary root lengths, more lateral roots, smaller leaves, and higher amounts of amino acids and proteins compared to those grown on NH4NO3. While high levels of Gln accumulate in Arabidopsis seedlings grown on Gln, the expression of GLUTAMINE SYNTHETASE1;1 (GLN1;1), GLN1;2, and GLN1;3 encoding cytosolic GS1 increases and expression of GLN2 encoding chloroplastic GS2 decreases. These results suggest that Gln has distinct effects on regulating GLN1 and GLN2 gene expression. Notably, Arabidopsis seedlings grown on Gln have an unexpected gene expression profile. Compared with NH4NO3, which activates growth-promoting genes, Gln preferentially induces stress- and defense-responsive genes. Consistent with the gene expression data, exogenous treatment with Gln enhances disease resistance in Arabidopsis. The induction of Gln-responsive genes, including PATHOGENESIS-RELATED1, SYSTEMIC ACQUIRED RESISTANCE DEFICIENT1, WRKY54, and WALL ASSOCIATED KINASE1, is compromised in salicylic acid (SA) biosynthetic and signaling mutants under Gln treatments. Together, these results suggest that Gln may partly interact with the SA pathway to trigger plant immunity.

Convergence of coronary artery disease genes onto endothelial cell programs.

Linking variants from genome-wide association studies (GWAS) to underlying mechanisms of disease remains a challenge1-3. For some diseases, a successful strategy has been to look for cases in which multiple GWAS loci contain genes that act in the same biological pathway1-6. However, our knowledge of which genes act in which pathways is incomplete, particularly for cell-type-specific pathways or understudied genes. Here we introduce a method to connect GWAS variants to functions. This method links variants to genes using epigenomics data, links genes to pathways de novo using Perturb-seq and integrates these data to identify convergence of GWAS loci onto pathways. We apply this approach to study the role of endothelial cells in genetic risk for coronary artery disease (CAD), and discover 43 CAD GWAS signals that converge on the cerebral cavernous malformation (CCM) signalling pathway. Two regulators of this pathway, CCM2 and TLNRD1, are each linked to a CAD risk variant, regulate other CAD risk genes and affect atheroprotective processes in endothelial cells. These results suggest a model whereby CAD risk is driven in part by the convergence of causal genes onto a particular transcriptional pathway in endothelial cells. They highlight shared genes between common and rare vascular diseases (CAD and CCM), and identify TLNRD1 as a new, previously uncharacterized member of the CCM signalling pathway. This approach will be widely useful for linking variants to functions for other common polygenic diseases.

Mineral composition, crystallinity and dielectric evaluation of Bamboo Salt, Himalaya Salt, and Ba'kelalan salt content.

The mineral composition, crystallinity, and dielectric properties of salts can provide valuable insights into the quality and suitability of different types of salt for various applications. In this study, comprehensive analysis of the X-Ray Diffraction (XRD), X-ray fluorescence (XRF) and dielectric analysis of the Ba'kelalan salt, Himalaya salt and Bamboo salt have been investigated. The mineral composition of these salts, encompassing vital elements such as iodine and other trace minerals, significantly influences the salt's nutritional profile and overall excellence. Nonetheless, gauging the dispersion and density of these minerals poses difficulties due to conventional techniques that can be arduous, damaging, and expensive. Sample preparation is carried out before conducting X-ray diffraction (XRD), X-ray fluorescence (XRF), and dielectric analysis. XRD measurements are performed using the Bruker D2 Phaser to identify crystalline material phases. XRD operates on the principle of constructive X-ray interference within crystalline samples. For elemental analysis across a broad spectrum of materials, XRF is employed. Elemental peaks are scanned, starting from the lowest to the highest angle of incidence. The X-ray intensity at characteristic peaks is compared to the standard series. Dielectric spectroscopy analysis examines the dielectric behaviour of Ba'kelalan salt, Himalaya salt, and Bamboo salt. The setup involves a vector network analyser (VNA) paired with an open-ended coaxial probe, utilizing the microwave method. This approach ensures rapid, efficient, and non-destructive measurements of dielectric constants (ε') and loss factors (ε"). The dielectric permittivity spectra are acquired within the frequency range of 4 GHz-20 GHz. ε' of these salts increase with frequency. Meanwhile, ε" seem varies insignificantly over frequency. Mineral contents and crystallinity are the crucial factors lead to these responses. Based on the study, the quality and suitability of the selected salts for specific applications can be determined by considering their mineral composition, crystallinity, and dielectric properties in the context of the intended use. This gives an insight for some applications that may benefit from certain minerals or crystalline structures, others may require specific dielectric properties for effective use. Therefore, understanding these properties allows for decision-making in choosing the right type of salt for a given purpose, whether it's for foods, medical, industrial, healthcare, and technological applications.

The meaning that people with severe mental illnesses ascribe to e-health in encounters with healthcare professionals - A repeat interview study.

This study sought to explore the meaning that people with severe mental illnesses attribute to e-health solutions regarding user involvement and encounters with healthcare professionals. A qualitative design with a social phenomenological approach was applied, and data were collected via repeat interviews. Using a purposive sampling strategy, eight people with severe mental illness were interviewed two times between August 2021 to May 2022, at three different treatment sites in southern Denmark. To be included, participants needed to be 18-65 years of age, diagnosed with severe mental illness (schizophrenia, bipolar disorder, or depression), and using an e-health solution in collaboration with a health professional. The interviews lasted between 20 and 70 min and were audio recorded and then transcribed. The data were analysed with Braun and Clarke's 6-step thematic analysis. Participants experienced the use of an e-health solution as helpful for structuring their everyday lives, and e-health used together with healthcare professionals was considered to have a positive impact on the collaboration. The participants experienced feeling involved and in control when e-health solutions were used, which engaged them in their treatment. Furthermore, the participants found it important to have had some in-person meetings with healthcare professionals to build trust before the e-health solutions could be implemented successfully. E-health solutions used in collaboration with a trusted healthcare professional whom the participants had met in person tended to affect treatment engagement positively.

Complementary CRISPR screen highlights the contrasting role of membrane-bound and soluble ICAM-1 in regulating antigen-specific tumor cell killing by cytotoxic T cells.

Cytotoxic CD8 +T lymphocytes (CTLs) are key players of adaptive anti-tumor immunity based on their ability to specifically recognize and destroy tumor cells. Many cancer immunotherapies rely on unleashing CTL function. However, tumors can evade killing through strategies which are not yet fully elucidated. To provide deeper insight into tumor evasion mechanisms in an antigen-dependent manner, we established a human co-culture system composed of tumor and primary immune cells. Using this system, we systematically investigated intrinsic regulators of tumor resistance by conducting a complementary CRISPR screen approach. By harnessing CRISPR activation (CRISPRa) and CRISPR knockout (KO) technology in parallel, we investigated gene gain-of-function as well as loss-of-function across genes with annotated function in a colon carcinoma cell line. CRISPRa and CRISPR KO screens uncovered 187 and 704 hits, respectively, with 60 gene hits overlapping between both. These data confirmed the role of interferon-γ (IFN-γ), tumor necrosis factor α (TNF-α) and autophagy pathways and uncovered novel genes implicated in tumor resistance to killing. Notably, we discovered that ILKAP encoding the integrin-linked kinase-associated serine/threonine phosphatase 2 C, a gene previously unknown to play a role in antigen specific CTL-mediated killing, mediate tumor resistance independently from regulating antigen presentation, IFN-γ or TNF-α responsiveness. Moreover, our work describes the contrasting role of soluble and membrane-bound ICAM-1 in regulating tumor cell killing. The deficiency of membrane-bound ICAM-1 (mICAM-1) or the overexpression of soluble ICAM-1 (sICAM-1) induced resistance to CTL killing, whereas PD-L1 overexpression had no impact. These results highlight the essential role of ICAM-1 at the immunological synapse between tumor and CTL and the antagonist function of sICAM-1.

Response-adaptive randomization in clinical trials: from myths to practical considerations.

Response-Adaptive Randomization (RAR) is part of a wider class of data-dependent sampling algorithms, for which clinical trials are typically used as a motivating application. In that context, patient allocation to treatments is determined by randomization probabilities that change based on the accrued response data in order to achieve experimental goals. RAR has received abundant theoretical attention from the biostatistical literature since the 1930's and has been the subject of numerous debates. In the last decade, it has received renewed consideration from the applied and methodological communities, driven by well-known practical examples and its widespread use in machine learning. Papers on the subject present different views on its usefulness, and these are not easy to reconcile. This work aims to address this gap by providing a unified, broad and fresh review of methodological and practical issues to consider when debating the use of RAR in clinical trials.

A Perilous Combination: Streptococcus Coinfection with Human Plague-Report of Two Cases and Review of the Literature, 1937-2022.

Background: Plague in humans and animals is caused by Yersinia pestis, a zoonotic gram-negative bacterium endemic in certain regions of Asia, Africa, and the United States. Coinfection with both Y. pestis and Streptococci species has been anecdotally reported in humans and associated with severe and rapidly fatal disease. Methods: This report presents two cases of patients who died following Y. pestis and Streptococcus coinfection. Additional cases of previously published Y. pestis-Streptococcus coinfection were identified and reviewed using a search of electronic databases. Results: The first case patient developed cough and dyspnea following 4 days of fever, malaise, and back pain and died before receiving medical care. Postmortem blood cultures were positive for Y. pestis, Streptococcus pyogenes, and Streptococcus dysgalactiae. The second case patient was hospitalized with fever, vomiting, diarrhea, and dyspnea and died of sepsis and respiratory failure on the day of admission. Y. pestis and Streptococcus pneumoniae were isolated from blood cultures drawn on admission. Seven additional cases of Y. pestis and Streptococcus coinfection were identified, dating between 1948 and 2009. These patients were healthy overall before their illness, with ages ranging from 9 to 60 years. The majority of patients had primary bubonic plague with associated pneumonia or septicemia. None of the patients who died received timely antimicrobial therapy directed against gram-negative pathogens. In every case but one, an occupational or environmental risk factor for plague was later identified. Conclusion: Y. pestis infection begins with a pre-inflammatory phase, during which Y. pestis and other pathogens can rapidly proliferate. Streptococci, which are frequently asymptomatic colonizers, may become invasive in this environment, leading to coinfection. The challenges of diagnosing Y. pestis in the context of coinfection may delay effective treatment. This case series and literature review illustrate the importance of clinicians remaining alert to environmental and occupational exposures in patients presenting with an infectious syndrome, especially in those who have an unexpectedly severe clinical presentation.

Glutamine Metabolism, Sensing and Signaling in Plants.

Glutamine (Gln) is the first amino acid synthesized in nitrogen (N) assimilation in plants. Gln synthetase (GS), converting glutamate (Glu) and NH4+ into Gln at the expense of ATP, is one of the oldest enzymes in all life domains. Plants have multiple GS isoenzymes that work individually or cooperatively to ensure that the Gln supply is sufficient for plant growth and development under various conditions. Gln is a building block for protein synthesis and an N-donor for the biosynthesis of amino acids, nucleic acids, amino sugars and vitamin B coenzymes. Most reactions using Gln as an N-donor are catalyzed by Gln amidotransferase (GAT) that hydrolyzes Gln to Glu and transfers the amido group of Gln to an acceptor substrate. Several GAT domain-containing proteins of unknown function in the reference plant Arabidopsis thaliana suggest that some metabolic fates of Gln have yet to be identified in plants. In addition to metabolism, Gln signaling has emerged in recent years. The N regulatory protein PII senses Gln to regulate arginine biosynthesis in plants. Gln promotes somatic embryogenesis and shoot organogenesis with unknown mechanisms. Exogenous Gln has been implicated in activating stress and defense responses in plants. Likely, Gln signaling is responsible for some of the new Gln functions in plants.

Memories of nursing in Singapore - an oral history approach.

Background: Documentation of the voices of nurses provided valuable insight and a greater understanding of the nursing experience in Singapore. Aim: To record nurses' experiences of journey of nursing profession in the acute care setting in Singapore from the early days of formalisation of nursing education to today's practice as a profession with various specialisation and career tracks. Method: An oral history research approach was adopted, with purposive and snowball sampling to recruit nurses (both current and retired) who had trained in Singapore from 1956 which marked the beginning of the founding of the School of Nursing to current. Interviews were conducted with an interview guide. Thematic analysis was utilised to analyse the audio-recorded data. Results: The 54 participants with a range of 10-54 years of nursing experience were interviewed and they completed their nursing training between 1952 and 2006. Four themes were generated: essence of nursing, inevitable changes across nursing profession, resilience and future outlook in nursing. Conclusions: Understanding the experiences of these nurses generated an in-depth understanding of the personal, social and historical events that were at play in fostering today's nursing practice. With the evolution of the roles in nursing, compassion in current practice needs to be re-evaluated. Continuous learning is essential to meet the needs of the changing healthcare landscape.

Multiomic Analysis and CRISPR Perturbation Screens Identify Endothelial Cell Programs and Novel Therapeutic Targets for Coronary Artery Disease.

Endothelial cells (EC) are an important mediator of atherosclerosis and vascular disease. Their exposure to atherogenic risk factors such as hypertension and serum cholesterol leads to endothelial dysfunction and many disease-associated processes. Identifying which of these multiple EC functions is causally related to disease risk has been challenging. There is evidence from in vivo models and human sequencing studies that dysregulation of nitric oxide production directly affects risk of coronary artery disease. Human genetics can help prioritize the other EC functions with causal relationships because germline mutations are acquired at birth and serve as a randomized test of which pathways affect disease risk. Though several coronary artery disease risk variants have been linked to EC function, this process has been slow and laborious. Unbiased analyses of EC dysfunction using multiomic approaches promise to identify the causal genetic mechanisms responsible for vascular disease. Here, we review the data from genomic, epigenomic, and transcriptomic studies that prioritize EC-specific causal pathways. New methods that CRISPR (clustered regularly interspaced short palindromic repeats) perturbation technology with genomic, epigenomic, and transcriptomic analysis promise to speed up the characterization of disease-associated genetic variation. We summarize several recent studies in ECs which use high-throughput genetic perturbation to identify disease-relevant pathways and novel mechanisms of disease. These genetically validated pathways can accelerate the identification of drug targets for the prevention and treatment of atherosclerosis.

The Personalised Randomized Controlled Trial: Evaluation of a new trial design.

In some clinical scenarios, for example, severe sepsis caused by extensively drug resistant bacteria, there is uncertainty between many common treatments, but a conventional multiarm randomized trial is not possible because individual participants may not be eligible to receive certain treatments. The Personalised Randomized Controlled Trial design allows each participant to be randomized between a "personalised randomization list" of treatments that are suitable for them. The primary aim is to produce treatment rankings that can guide choice of treatment, rather than focusing on the estimates of relative treatment effects. Here we use simulation to assess several novel analysis approaches for this innovative trial design. One of the approaches is like a network meta-analysis, where participants with the same personalised randomization list are like a trial, and both direct and indirect evidence are used. We evaluate this proposed analysis and compare it with analyses making less use of indirect evidence. We also propose new performance measures including the expected improvement in outcome if the trial's rankings are used to inform future treatment rather than random choice. We conclude that analysis of a personalized randomized controlled trial can be performed by pooling data from different types of participants and is robust to moderate subgroup-by-intervention interactions based on the parameters of our simulation. The proposed approach performs well with respect to estimation bias and coverage. It provides an overall treatment ranking list with reasonable precision, and is likely to improve outcome on average if used to determine intervention policies and guide individual clinical decisions.

Complex Impedance and Modulus Analysis on Porous and Non-Porous Scaffold Composites Due to Effect of Hydroxyapatite/Starch Proportion.

This study aims to investigate the electric responses (complex modulus and complex impedance analysis) of hydroxyapatite/starch bone scaffold as a function of hydroxyapatite/starch proportion and the microstructural features. Hence, the non-porous and porous hydroxyapatite/starch composites were fabricated with various hydroxyapatite/starch proportions (70/30, 60/40, 50/50, 40/60, 30/70, 20/80, and 10/90 wt/wt%). Microstructural analysis of the porous hydroxyapatite/starch composites was carried out by using scanning electron microscopy. It shows that the formation of hierarchical porous microstructures with high porosity is more significant at a high starch proportion. The complex modulus and complex impedance analysis were conducted to investigate the electrical conduction mechanism of the hydroxyapatite/starch composites via dielectric spectroscopy within a frequency range from 5 MHz to 12 GHz. The electrical responses of the hydroxyapatite/starch composites are highly dependent on the frequency, material proportion, and microstructures. High starch proportion and highly porous hierarchical microstructures enhance the electrical responses of the hydroxyapatite/starch composite. The material proportion and microstructure features of the hydroxyapatite/starch composites can be indirectly reflected by the simulated electrical parameters of the equivalent electrical circuit models.

Lumped-Element Circuit Modeling for Composite Scaffold with Nano-Hydroxyapatite and Wangi Rice Starch.

Mechanistic studies of the interaction of electromagnetic (EM) fields with biomaterials has motivated a growing need for accurate models to describe the EM behavior of biomaterials exposed to these fields. In this paper, biodegradable bone scaffolds were fabricated using Wangi rice starch and nano-hydroxyapatite (nHA). The effects of porosity and composition on the fabricated scaffold were discussed via electrical impedance spectroscopy analysis. The fabricated scaffold was subjected to an electromagnetic field within the X-band and Ku-band (microwave spectrum) during impedance/dielectric measurement. The impedance spectra were analyzed with lumped-element models. The impedance spectra of the scaffold can be embodied in equivalent circuit models composed of passive components of the circuit, i.e., resistors, inductors and capacitors. It represents the morphological, structural and chemical characteristics of the bone scaffold. The developed models describe the impedance characteristics of plant tissue. In this study, it was found that the ε' and ε″ of scaffold composites exhibited up and down trends over frequencies for both X-band and Ku-band. The circuit models presented the lowest mean percentage errors of Z' and Z″, i.e., 3.60% and 13.80%, respectively.