Electrographic monitoring for seizure detection in the neonatal unit: current status and future direction.

Neonatal neurocritical intensive care is dedicated to safeguarding the newborn brain by prioritising clinical practices that promote early identification, diagnosis and treatment of brain injuries. The most common newborn neurological emergency is neonatal seizures, which may also be the initial clinical indication of neurological disease. A high seizure burden in the newborn period independently contributes to increased mortality and morbidity. The majority of seizures in newborns are subclinical (without clinical presentation), and hence identification may be difficult. Neuromonitoring techniques most frequently used to monitor brain wave activity include conventional electroencephalography (cEEG) or amplitude-integrated EEG (aEEG). cEEG with video is the gold standard for diagnosing and treating seizures. Many neonatal units do not have access to cEEG, and frequently those that do, have little access to real-time interpretation of monitoring. IMPACT: EEG monitoring is of no benefit to an infant without expert interpretation. Whilst EEG is a reliable cot-side tool and of diagnostic and prognostic use, both conventional EEG and amplitude-integrated EEG have strengths and limitations, including sensitivity to seizure activity and ease of interpretation. Automated seizure detection requires a sensitive and specific algorithm that can interpret EEG in real-time and identify seizures, including their intensity and duration.

Characteristics of water quality mitigation measures that lead to greater adoption on farms.

Globally, agriculture is a significant pressure on water quality. While nutrient and sediment loss from agricultural land to water can be scientifically complex, mitigation measures primarily focus on reducing farm nutrient stocks or blocking loss pathways. The appropriateness of mitigation measures is dependent on the identification of specific context-related risks on individual farms. However, advisers also need to consider the likelihood of uptake of measures by farmers. Past research has looked at uptake of particular mitigation measures or a small range of measures. This research expands the literature with an analysis of uptake of a broad and diverse range of measures. Farm characteristics, farmer norms, knowledge required and costs (direct and indirect) associated with individual mitigation measures are investigated to identify factors that could influence greater adoption. Results show that alignment to farmer norms and lower specific costs were associated with high adoption rates. These results have implications for advisers in relation to the selection of measures most likely to be adopted by farmers, and also for policy-makers in relation to the need to incentivise the adoption of high-cost measures.

Extensive photochemical restructuring of molecule-metal surfaces under room light.

The molecule-metal interface is of paramount importance for many devices and processes, and directly involved in photocatalysis, molecular electronics, nanophotonics, and molecular (bio-)sensing. Here the photostability of this interface is shown to be sensitive even to room light levels for specific molecules and metals. Optical spectroscopy is used to track photoinduced migration of gold atoms when functionalised with different thiolated molecules that form uniform monolayers on Au. Nucleation and growth of characteristic surface metal nanostructures is observed from the light-driven adatoms. By watching the spectral shifts of optical modes from nanoparticles used to precoat these surfaces, we identify processes involved in the photo-migration mechanism and the chemical groups that facilitate it. This photosensitivity of the molecule-metal interface highlights the significance of optically induced surface reconstruction. In some catalytic contexts this can enhance activity, especially utilising atomically dispersed gold. Conversely, in electronic device applications such reconstructions introduce problematic aging effects.

Correction to "Searching for the Rules of Electrochemical Nitrogen Fixation".

[This corrects the article DOI: 10.1021/acscatal.3c03951.].

Role of Electrolyte pH on Water Oxidation for Iridium Oxides.

Understanding the effect of noncovalent interactions of intermediates at the polarized catalyst-electrolyte interface on water oxidation kinetics is key for designing more active and stable electrocatalysts. Here, we combine operando optical spectroscopy, X-ray absorption spectroscopy (XAS), and surface-enhanced infrared absorption spectroscopy (SEIRAS) to probe the effect of noncovalent interactions on the oxygen evolution reaction (OER) activity of IrOx in acidic and alkaline electrolytes. Our results suggest that the active species for the OER (Ir4.x+-*O) binds much stronger in alkaline compared with acid at low coverage, while the repulsive interactions between these species are higher in alkaline electrolytes. These differences are attributed to the larger fraction of water within the cation hydration shell at the interface in alkaline electrolytes compared to acidic electrolytes, which can stabilize oxygenated intermediates and facilitate long-range interactions between them. Quantitative analysis of the state energetics shows that although the *O intermediates bind more strongly than optimal in alkaline electrolytes, the larger repulsive interaction between them results in a significant weakening of *O binding with increasing coverage, leading to similar energetics of active states in acid and alkaline at OER-relevant potentials. By directly probing the electrochemical interface with complementary spectroscopic techniques, our work goes beyond conventional computational descriptors of the OER activity to explain the experimentally observed OER kinetics of IrOx in acidic and alkaline electrolytes.

Group sequential two-stage preference designs.

The two-stage preference design (TSPD) enables inference for treatment efficacy while allowing for incorporation of patient preference to treatment. It can provide unbiased estimates for selection and preference effects, where a selection effect occurs when patients who prefer one treatment respond differently than those who prefer another, and a preference effect is the difference in response caused by an interaction between the patient's preference and the actual treatment they receive. One potential barrier to adopting TSPD in practice, however, is the relatively large sample size required to estimate selection and preference effects with sufficient power. To address this concern, we propose a group sequential two-stage preference design (GS-TSPD), which combines TSPD with sequential monitoring for early stopping. In the GS-TSPD, pre-planned sequential monitoring allows investigators to conduct repeated hypothesis tests on accumulated data prior to full enrollment to assess study eligibility for early trial termination without inflating type I error rates. Thus, the procedure allows investigators to terminate the study when there is sufficient evidence of treatment, selection, or preference effects during an interim analysis, thereby reducing the design resource in expectation. To formalize such a procedure, we verify the independent increments assumption for testing the selection and preference effects and apply group sequential stopping boundaries from the approximate sequential density functions. Simulations are then conducted to investigate the operating characteristics of our proposed GS-TSPD compared to the traditional TSPD. We demonstrate the applicability of the design using a study of Hepatitis C treatment modality.

Adherence to key recommendations for design and analysis of stepped-wedge cluster randomized trials: A review of trials published 2016-2022.

BACKGROUND/AIMS: The stepped-wedge cluster randomized trial (SW-CRT), in which clusters are randomized to a time at which they will transition to the intervention condition - rather than a trial arm - is a relatively new design. SW-CRTs have additional design and analytical considerations compared to conventional parallel arm trials. To inform future methodological development, including guidance for trialists and the selection of parameters for statistical simulation studies, we conducted a review of recently published SW-CRTs. Specific objectives were to describe (1) the types of designs used in practice, (2) adherence to key requirements for statistical analysis, and (3) practices around covariate adjustment. We also examined changes in adherence over time and by journal impact factor. METHODS: We used electronic searches to identify primary reports of SW-CRTs published 2016-2022. Two reviewers extracted information from each trial report and its protocol, if available, and resolved disagreements through discussion. RESULTS: We identified 160 eligible trials, randomizing a median (Q1-Q3) of 11 (8-18) clusters to 5 (4-7) sequences. The majority (122, 76%) were cross-sectional (almost all with continuous recruitment), 23 (14%) were closed cohorts and 15 (9%) open cohorts. Many trials had complex design features such as multiple or multivariate primary outcomes (50, 31%) or time-dependent repeated measures (27, 22%). The most common type of primary outcome was binary (51%); continuous outcomes were less common (26%). The most frequently used method of analysis was a generalized linear mixed model (112, 70%); generalized estimating equations were used less frequently (12, 8%). Among 142 trials with fewer than 40 clusters, only 9 (6%) reported using methods appropriate for a small number of clusters. Statistical analyses clearly adjusted for time effects in 119 (74%), for within-cluster correlations in 132 (83%), and for distinct between-period correlations in 13 (8%). Covariates were included in the primary analysis of the primary outcome in 82 (51%) and were most often individual-level covariates; however, clear and complete pre-specification of covariates was uncommon. Adherence to some key methodological requirements (adjusting for time effects, accounting for within-period correlation) was higher among trials published in higher versus lower impact factor journals. Substantial improvements over time were not observed although a slight improvement was observed in the proportion accounting for a distinct between-period correlation. CONCLUSIONS: Future methods development should prioritize methods for SW-CRTs with binary or time-to-event outcomes, small numbers of clusters, continuous recruitment designs, multivariate outcomes, or time-dependent repeated measures. Trialists, journal editors, and peer reviewers should be aware that SW-CRTs have additional methodological requirements over parallel arm designs including the need to account for period effects as well as complex intracluster correlations.

Probing Degradation in Lithium Ion Batteries with On-Chip Electrochemistry Mass Spectrometry.

The rapid uptake of lithium ion batteries (LIBs) for large scale electric vehicle and energy storage applications requires a deeper understanding of the degradation mechanisms. Capacity fade is due to the complex interplay between phase transitions, electrolyte decomposition and transition metal dissolution; many of these poorly understood parasitic reactions evolve gases as a side product. Here we present an on-chip electrochemistry mass spectrometry method that enables ultra-sensitive, fully quantified and time resolved detection of volatile species evolving from an operating LIB. The technique's electrochemical performance and mass transport is described by a finite element model and then experimentally used to demonstrate the variety of new insights into LIB performance. We show the versatility of the technique, including (a) observation of oxygen evolving from a LiNiMnCoO2 cathode and (b) the solid electrolyte interphase formation reaction on graphite in a variety of electrolytes, enabling the deconvolution of lithium inventory loss (c) the first direct evidence, by virtue of the improved time resolution of our technique, that carbon dioxide reduction to ethylene takes place in a lithium ion battery. The emerging insight will guide and validate battery lifetime models, as well as inform the design of longer lasting batteries.

Neurodevelopmental outcome of low-risk moderate to late preterm infants at 18 months.

Background: Of the 15 million preterm births that occur worldwide each year, approximately 80% occur between 32 and 36 + 6 weeks gestational age (GA) and are defined as moderate to late preterm (MLP) infants. This percentage substantiates a need for a better understanding of the neurodevelopmental outcome of this group. Aim: To describe neurodevelopmental outcome at 18 months in a cohort of healthy low-risk MLP infants admitted to the neonatal unit at birth and to compare the neurodevelopmental outcome to that of a healthy term-born infant group. Study design and method: This single-centre observational study compared the neurodevelopmental outcome of healthy MLP infants to a group of healthy term control (TC) infants recruited during the same period using the Griffith's III assessment at 18 months. Results: Seventy-five MLP infants and 92 TC infants were included. MLP infants scored significantly lower in the subscales: Eye-hand coordination (C), Personal, Social and Emotional Development (D), Gross Motor Development (E) and General Developmental (GD) (p < 0.001 for each) and Foundations of Learning (A), (p = 0.004) in comparison to the TC infant group with Cohen's d effect sizes ranging from 0.460 to 0.665. There was no statistically significant difference in mean scores achieved in subscale B: Language and Communication between groups (p = 0.107). Conclusion: MLP infants are at risk of suboptimal neurodevelopmental outcomes. Greater surveillance of the neurodevelopmental trajectory of this group of at-risk preterm infants is required.

Searching for the Rules of Electrochemical Nitrogen Fixation.

Li-mediated ammonia synthesis is, thus far, the only electrochemical method for heterogeneous decentralized ammonia production. The unique selectivity of the solid electrode provides an alternative to one of the largest heterogeneous thermal catalytic processes. However, it is burdened with intrinsic energy losses, operating at a Li plating potential. In this work, we survey the periodic table to understand the fundamental features that make Li stand out. Through density functional theory calculations and experimentation on chemistries analogous to lithium (e.g., Na, Mg, Ca), we find that lithium is unique in several ways. It combines a stable nitride that readily decomposes to ammonia with an ideal solid electrolyte interphase, balancing reagents at the reactive interface. We propose descriptors based on simulated formation and binding energies of key intermediates and further on hard and soft acids and bases (HSAB principle) to generalize such features. The survey will help the community toward electrochemical systems beyond Li for nitrogen fixation.

Non-randomised feasibility study of training workshops for Talking Therapies service high-intensity therapists to optimise depression and anxiety outcomes for individuals with co-morbid personality difficulties: a study protocol.

BACKGROUND: The NHS Talking Therapies for Anxiety and Depression programme ('TTad'; formerly Improving Access to Psychological Therapies 'IAPT') delivers high-intensity cognitive behavioural therapy (CBT) to over 200,000 individuals each year for common mental health problems like depression and anxiety. More than half of these individuals experience comorbid personality difficulties, who show poorer treatment outcomes. TTad therapists report feeling unskilled to work with clients with personality difficulties, and enhancing the training of TTad therapists may lead to improved treatment outcomes for individuals presenting with secondary personality difficulties alongside depression and anxiety. METHODS: This is a pre-post non-randomised mixed-method feasibility study, exploring the feasibility and acceptability of a 1-day training workshop for high-intensity (HI) CBT therapists. The workshop is focused on understanding and assessing personality difficulties and adapting HICBT treatments for anxiety and depression to accommodate client needs. The feasibility and acceptability of the workshop and the evaluation procedures will be investigated. It will be examined to what extent the workshop provision leads to improvements in therapist skills and confidence and explored to what extent the training has the potential to enhance clinical outcomes for this client group. DISCUSSION: This feasibility study will provide data on the acceptability and feasibility of delivering brief therapist training to adapt usual HICBT to optimise care for individuals with secondary personality difficulties seeking treatment in TTad services for a primary problem of depression and/or anxiety. The study will also evaluate proof of concept that such an approach has the potential to improve clinical outcomes for those with secondary personality difficulties and report any possible harms identified. The study will inform the design of a future randomised controlled trial designed to test the effectiveness and cost-effectiveness of the training. TRIAL REGISTRATION: ISRCTN81104604 . Submitted on 6th June 2022. Registration date: 3rd January 2023.

Observed Parenting and Adolescent Brain Structure.

Parent-youth relationships and parenting are critically important to adolescents' development. The present study examined associations between parenting behaviors (which included observed parent emotion expression and negative and positive parenting behaviors during a parent-adolescent interaction) and adolescent brain structure, and sex differences in associations, in 66 12-14 year-olds. The study found that 1) among all adolescents in the sample, greater parent negative emotion expression in parent-youth interactions was associated with greater adolescent gray matter volume (GMV) in the left hippocampus, 2) parent positive emotion expression was not associated with adolescent GMV, 3) several associations differed by sex. These findings suggest that parenting is important for adolescent brain structure and future work should consider this by sex.

Evaluation of Sleep Practices and Knowledge in Neonatal Healthcare.

BACKGROUND: Developmental care is designed to optimize early brain maturation by integrating procedures that support a healing environment. Protecting preterm sleep is important in developmental care. However, it is unclear to what extent healthcare professionals are aware of the importance of sleep and how sleep is currently implemented in the day-to-day care in the neonatal intensive care unit (NICU). PURPOSE: Identifying the current state of knowledge among healthcare professionals regarding neonatal sleep and how this is transferred to practice. METHODS: A survey was distributed among Dutch healthcare professionals. Three categories of data were sought, including (1) demographics of respondents; (2) questions relating to sleep practices; and (3) objective knowledge questions relating to sleep physiology and importance of sleep. Data were analyzed using Spearman's rho test and Cramer's V test. Furthermore, frequency tables and qualitative analyses were employed. RESULTS: The survey was completed by 427 participants from 34 hospitals in 25 Dutch cities. While healthcare professionals reported sleep to be especially important for neonates admitted in the NICU, low scores were achieved in the area of knowledge of sleep physiology. Most healthcare professionals (91.8%) adapted the timing of elective care procedures to sleep. However, sleep assessments were not based on scientific knowledge. Therefore, the difference between active sleep and wakefulness may often be wrongly assessed. Finally, sleep is rarely discussed between colleagues (27.4% regularly/always) and during rounds (7.5%-14.3% often/always). IMPLICATIONS: Knowledge about sleep physiology should be increased through education among neonatal healthcare professionals. Furthermore, sleep should be considered more often during rounds and handovers.

Maximin optimal cluster randomized designs for assessing treatment effect heterogeneity.

Cluster randomized trials (CRTs) are studies where treatment is randomized at the cluster level but outcomes are typically collected at the individual level. When CRTs are employed in pragmatic settings, baseline population characteristics may moderate treatment effects, leading to what is known as heterogeneous treatment effects (HTEs). Pre-specified, hypothesis-driven HTE analyses in CRTs can enable an understanding of how interventions may impact subpopulation outcomes. While closed-form sample size formulas have recently been proposed, assuming known intracluster correlation coefficients (ICCs) for both the covariate and outcome, guidance on optimal cluster randomized designs to ensure maximum power with pre-specified HTE analyses has not yet been developed. We derive new design formulas to determine the cluster size and number of clusters to achieve the locally optimal design (LOD) that minimizes variance for estimating the HTE parameter given a budget constraint. Given the LODs are based on covariate and outcome-ICC values that are usually unknown, we further develop the maximin design for assessing HTE, identifying the combination of design resources that maximize the relative efficiency of the HTE analysis in the worst case scenario. In addition, given the analysis of the average treatment effect is often of primary interest, we also establish optimal designs to accommodate multiple objectives by combining considerations for studying both the average and heterogeneous treatment effects. We illustrate our methods using the context of the Kerala Diabetes Prevention Program CRT, and provide an R Shiny app to facilitate calculation of optimal designs under a wide range of design parameters.

Asking about self-harm during risk assessment in psychosocial assessments in the emergency department: questions that facilitate and deter disclosure of self-harm.

BACKGROUND: Emergency departments are key settings for suicide prevention. Most people are deemed to be at no or low risk in final contacts before death. AIM: To micro-analyse how clinicians ask about suicidal ideation and/or self-harm in emergency department psychosocial assessments and how patients respond. METHOD: Forty-six psychosocial assessments between mental health clinicians and people with suicidal ideation and/or self-harm were video-recorded. Verbal and non-verbal features of 55 question-answer sequences about self-harm thoughts and/or actions were micro-analysed using conversation analysis. Fisher's exact test was used to test the hypothesis that question type was associated with patient disclosure. RESULTS: (a) Eighty-four per cent of initial questions (N = 46/55) were closed yes/no questions about self-harm thoughts and/or feelings, plans to self-harm, potential for future self-harm, predicting risk of future self-harm and being okay or keeping safe. Patients disclosed minimal information in response to closed questions, whereas open questions elicited ambivalent and information rich responses. (b) All closed questions were leading, with 54% inviting no and 46% inviting yes. When patients were asked no-inviting questions, the disclosure rate was 8%, compared to 65% when asked yes-inviting questions (P < 0.05 Fisher's exact test). (c) Patients struggled to respond when asked to predict future self-harm or guarantee safety. (d) Half of closed questions had a narrow timeframe (e.g. at the moment, overnight) or were tied to possible discharge. CONCLUSION: Across assessments, there is a bias towards not uncovering thoughts and plans of self-harm through the cumulative effect of leading questions that invite a no response, their narrow timeframe and tying questions to possible discharge. Open questions, yes-inviting questions and asking how people feel about the future facilitate disclosure.

ORTH.Ord: An R package for analyzing correlated ordinal outcomes using alternating logistic regressions with orthogonalized residuals.

BACKGROUND AND OBJECTIVES: Marginal models with generalized estimating equations (GEE) are usually recommended for analyzing correlated ordinal outcomes which are commonly seen in a longitudinal study or clustered randomized trial (CRT). Within-cluster association is often of interest in longitudinal studies or CRTs, and can be estimated with paired estimating equations. However, the estimators for within-cluster association parameters and variances may be subject to finite-sample biases when the number of clusters is small. The objective of this article is to introduce a newly developed R package ORTH.Ord for analyzing correlated ordinal outcomes using GEE models with finite-sample bias corrections. METHODS: The R package ORTH.Ord implements a modified version of alternating logistic regressions with estimation based on orthogonalized residuals (ORTH), which use paired estimating equations to jointly estimate parameters in marginal mean and association models. The within-cluster association between ordinal responses is modeled by global pairwise odds ratios (POR). The R package also provides a finite-sample bias correction to POR parameter estimates based on matrix multiplicative adjusted orthogonalized residuals (MMORTH) for correcting estimating equations, and bias-corrected sandwich estimators with different options for covariance estimation. RESULTS: A simulation study shows that MMORTH provides less biased global POR estimates and coverage of their 95% confidence intervals closer to the nominal level than uncorrected ORTH. An analysis of patient-reported outcomes from an orthognathic surgery clinical trial illustrates features of ORTH.Ord. CONCLUSIONS: This article provides an overview of the ORTH method with bias-correction on both estimating equations and sandwich estimators for analyzing correlated ordinal data, describes the features of the ORTH.Ord R package, evaluates the performance of the package using a simulation study, and finally illustrates its application in an analysis of a clinical trial.

A scoping review described diversity in methods of randomization and reporting of baseline balance in stepped-wedge cluster randomized trials.

OBJECTIVES: In stepped-wedge cluster randomized trials (SW-CRTs), clusters are randomized not to treatment and control arms but to sequences dictating the times of crossing from control to intervention conditions. Randomization is an essential feature of this design but application of standard methods to promote and report on balance at baseline is not straightforward. We aimed to describe current methods of randomization and reporting of balance at baseline in SW-CRTs. STUDY DESIGN AND SETTING: We used electronic searches to identify primary reports of SW-CRTs published between 2016 and 2022. RESULTS: Across 160 identified trials, the median number of clusters randomized was 11 (Q1-Q3: 8-18). Sixty-three (39%) used restricted randomization-most often stratification based on a single cluster-level covariate; 12 (19%) of these adjusted for the covariate(s) in the primary analysis. Overall, 50 (31%) and 134 (84%) reported on balance at baseline on cluster- and individual-level characteristics, respectively. Balance on individual-level characteristics was most often reported by condition in cross-sectional designs and by sequence in cohort designs. Authors reported baseline imbalances in 72 (45%) trials. CONCLUSION: SW-CRTs often randomize a small number of clusters using unrestricted allocation. Investigators need guidance on appropriate methods of randomization and assessment and reporting of balance at baseline.

Capturing epistemic reflexivity for teacher educators teaching about/to/for diversity in teacher education.

Internationally, there is a growing body of evidence which shows that newly graduated teachers do not feel prepared to teach the increasingly diverse student body in contemporary classrooms. However, to date, we have limited understanding of the ways in which teacher educators work with preservice teachers to enhance their knowledge about diversity and how to address the diverse needs of students in their classrooms. To further understand teacher educators' pedagogical decision making in the context of preparing preservice teachers for diverse classrooms, a way of capturing epistemic thinking in this space is required. The current study used the Epistemic Reflexivity Survey for Teacher Educators (ERS-TE) to explore the relationships between teacher educators' Epistemic Aims, Reliable epistemic processes (REPs), Criteria for Knowledge (Epistemic Ideals), Reflexivity (decision making) and Teaching Practices. Two hundred and eighty-six teacher educators across Australia and New Zealand completed the survey. Results indicated that epistemic aims related to understanding critical connections predicted engagement with reliable epistemic thinking processes, reflexivity, and teaching practices related to critical thinking and social justice. Findings are discussed in terms of implications for teacher educators' work with preservice teachers with respect to teaching about, to and for diversity.

Abbreviated lipid guidelines for clinical practice : Based on ESC lipid guidelines 2019 and ESC cardiovascular disease prevention in clinical practice guidelines 2021.

BACKGROUND: Lipid disorders are now considered causal for atherosclerotic cardiovascular disease (ASCVD) which remains one of the most important contributors to morbidity and mortality in the developed world. Identification and early treatment of lipid disarrays remains the cornerstone of good clinical practice to prevent, halt and even reverse ASCVD. Guidelines for lipid management are imperative to help promote good clinical practice. Given the detail involved in comprehensive guidelines and the multiple areas of knowledge required by clinical practitioners, abbreviated, easy to understand, practical versions of guidelines are required to ensure dissemination of the most important information. The recent ESC lipid guidelines 2019 and the ESC guidelines on CVD prevention in clinical practice 2021 (1,2), provide an excellent detailed summary of all the latest evidence supporting lipid interventions that reduce ASCVD. METHOD: We therefore developed a single-page document with hyperlinks to help practitioners gain easy access to practical information on lipid management. It has been developed for future electronic use in clinical practice. CONCLUSION: It is presented here in a tabular format together with printable versions of the associated hyperlinks that provide the additional information required in decision making. It is hoped to audit the impact of this approach to help guide future ways of disseminating the latest clinical guideline updates.

Modeling Au Nanostar Geometry in Bulk Solutions.

The findings within make it possible to reference gold nanostars based on their geometric properties, similar to how a radius describes a nanosphere, rather than just the LSPR of the structure-the current practice. The average tip approximation presented reduces the complexity of nanostars in discrete dipole approximation simulations. By matching the projected area and LSPR of the modeled nanostars to synthesized nanostars, the volume, surface area, and number of tips can be approximated without a lengthy characterization process. Knowing the nanoparticle geometry can determine drug carrier capacity, an approximate number of hot spots for EM imaging, and how the particle will interact with cells. The geometric data obtained will drive the biological application and increase the usability of this particle class.