Biology subjects

Robertson, I. H.

Publications and source records attributed to Robertson, I. H..

12 recordsLinked to original sources

bioRxiv2026

From Fill to Freeze: Redesigning homeRNA to Enable Robust Sampling and Scalable Downstream Processing Workflows for Remote Blood Transcriptomics

In-person research can introduce barriers to participation, including proximity to a study site and scheduling constraints. Our lab developed the homeRNA platform to address these barriers, enabling remote blood collection and RNA stabilization for transcriptomic research. To increase the applicability of homeRNA for large-scale studies, a redesigned version was developed with modifications to 1) improve usability for both participants and downstream processing laboratories, 2) allow for high-throughput manufacturing, and 3) extend the shelf life of the stabilizer tube. In this work, we systematically tested this design against anticipated stresses that can occur throughout a remote study (e.g., high temperature exposure during shipment) to identify and characterize its limitations. We found that the homeRNA device can be prepared and stored at room temperature at least three months in advance of sampling with continued shelf life analysis underway. We also found that the homeRNA platform produces RNA of sufficient quality for downstream transcriptomic analysis under standard shipping durations (i.e., 2 days in transit) and ambient-to-high temperature conditions (i.e., 25-40 {degrees}C) and that RNA quality is unaffected by variable blood volumes collected by participants (mean RIN=7.8 in blood volumes 0.25-1 mL). Lastly, we also found that samples can be stored in typical cold storage temperatures and even up to standard room temperature for at least 4 weeks (mean RIN=8.1 after 4 weeks of storage at -80 to 20 {degrees}C). This work validates that the new homeRNA platform is robust to many of the expected stresses that samples can experience during remote studies.

bioengineering↗

bioRxiv2026

homeRNA Just Dropped! Streamlining Remote Blood Collection and RNA Stabilization for Smaller Sample Volumes with homeRNAdrop

At-home sampling can address obstacles to participation in transcriptomics research. We previously developed the homeRNA and homeRNAmax platforms; these custom-designed tubes containing RNA stabilizer interface with a blood tube compatible with upper-arm blood collection devices, allowing for blood collection and RNA stabilization to occur from a participant's home. In this work we introduce homeRNAdrop, an insert for a commercially available blood tube (BD Microtainer) that divides the tube into two compartments: the top compartment holds 200 L blood and the bottom compartment holds ~590 L liquid stabilizer (RNAlater). By combining blood collection and RNA stabilization into the same tube, homeRNAdrop streamlines sample preparation for participants and allows for more compact sample storage for the lab. In a remote pilot study, n=25 participants from across the United States tested the homeRNAdrop kit. The n=23 samples successfully received by the lab show that samples collected using homeRNAdrop are of sufficient RNA quality (all RINs > 6, a common cutoff for analysis) and yield (mean yield=1.44 g) for downstream gene expression analysis. Almost all participants who successfully collected blood using the Tasso Mini device found the homeRNAdrop device easy to use (n=23/24). Overall, this work adds a simplified, user-friendly platform to the growing suite of tools for remote blood RNA stabilization.

bioengineering↗

bioRxiv2026

Modeling and validation of parallel co-flows layer widths in open-capillary trigger valve systems

Control of fluids is a hallmark of microfluidic systems and fundamental for the successful application of microfluidic devices. Trigger valves use geometric features to autonomously control the release of fluids in microfluidic devices. Our previous work has adapted geometries used in closed trigger valve systems to enable use in open systems, allowing for open microfluidic devices with up to three trigger valves. Here, we focus on the parallel co-flows produced by sequential release of trigger valves and present a model that predicts their layer widths as a function of the geometric characteristics of the different side channels of each trigger valve. We show layered co-flows with widths as low as 50 microns. Additionally, we expand the use of trigger valves in open microfluidic devices by incorporating 1) varied step heights, 2) devices with up to seven trigger valves, and 3) use of varied fluids and plastics. To validate the implementation and use of these trigger valves in open systems, we have developed a theoretical framework to compare predicted outcomes (i.e., fluid travel distance, velocity, and layering width) with our experimental values. This theoretical work offers applications in various fields, including hydrogel patterning for 3D cell culture, organ-on-a-chip models, at-home sample preparation, and autonomous microfluidic systems for biosensing.

bioengineering↗

bioRxiv2025

From Home to Transcriptome: Comparing the transcriptomic profile of induced immune response via lipopolysaccharide stimulation in homeRNA and venous blood

Remote blood sampling offers multiple advantages over traditional clinic-based blood sampling studies, including greater patient inclusion, more frequent sampling, and broader geographical reach. Combining remote blood sampling with transcriptomic analysis opens potential in translational applications for capturing acute and dynamic immune responses to various exposures. In this study, we establish the feasibility of homeRNA, a capillary blood collection and RNAlater-based stabilization kit, for use in downstream bulk RNA-sequencing applications via capturing a lipopolysaccharide (LPS)-induced inflammatory response. We also compared the baseline gene expression profiles and induced inflammatory response following LPS stimulation between homeRNA-stabilized samples and venous blood stabilized with RNAlater or PAXgene. We found that homeRNA was successfully able to capture an inflammatory response to LPS, specifically targeting various cytokines (e.g., IL6, IL12B, IL1B), chemokines (e.g., CCL3, CXCL10, CCL4), and other transcriptional factors in the toll-like receptor pathway, the primary pathway activated during LPS stimulation. Importantly, we also found that homeRNA captured a LPS-induced inflammatory response comparable to that of venous blood samples stabilized with either RNAlater or PAXgene. Overall, this work demonstrates that the homeRNA platform is compatible with downstream bulk RNA-sequencing analysis and can capture transcriptomic immune responses to a known stimulus which are analogous to results in traditional stabilized venous blood samples.

bioengineering↗

bioRxiv2025

CandyCollect Open to Closed (O2C) Microfluidic System for Rapid and User-Centric Detection of Group A Streptococcus

We created CandyCollect, a lollipop-inspired, child-friendly saliva sampling device that provides enhanced comfort compared to common throat and mouth swabs. The device has an open microchannel and a functionalized surface that effectively captures and stores the saliva and pathogens. We recently demonstrated the ability to combine the CandyCollect with rapid antigen detection tests (RADTs) for fast and accessible detection of group A streptococcus (GAS). However, the current procedure necessitates manual steps to elute and transfer captured antigens from the lollipop to RADTs, which relies on the user to follow complex instructions, increasing the likelihood of error. In this work, we developed the CandyCollect Open to Closed (O2C) microfluidic system to automate antigen elution and streamline detection with RADTs. The O2C system securely seals the open microchannels of the CandyCollect device to create a continuous closed channel for seamless delivery of elution reagents to release antigens at the press of a button for subsequent lateral flow detection. Our system leverages and combines the unique benefits of both open channel and closed channel microfluidics into one platform, further enhancing the potential of both methods. We performed experiments with GAS bacteria spiked into saliva and compared the manual and O2C elution methods. Both the manual and O2C methods showed clear test lines on the RADT strips at clinically relevant GAS concentrations (between 5 x105 and 109 CFU/mL). The O2C provided comparable or better results than the manual procedure in a more convenient form factor. The O2C platform has the potential to enable user-friendly screening for respiratory pathogens by minimally trained users in decentralized settings.

bioengineering↗

bioRxiv2024

CandyCollect: An Open-Microfluidic Device for the Direct Capture and Enumeration of Salivary-Extracellular Vesicles

Extracellular vesicles (EVs) are promising biomarkers for disease detection using a liquid biopsy approach, in which they are enriched and analyzed directly from biofluids. However, implementing EV biomarker technologies in the clinic remains limited by the need for practical and patient-centric biofluid collection methods that are compatible with downstream EV processing and analysis. While saliva offers a non-invasive source of EVs, its complexity and heterogeneity--cells, debris, and other non-EV proteins--can present hurdles when using traditional analytical platforms. Here, we present the CandyCollect, a lollipop-inspired sampling device with open microfluidic channels, as a patient-friendly approach for rapid salivary EV capture. CandyCollect simplifies sample preparation by effectively pre-concentrating EVs in oxygen-plasma treated open microfluidic channels. In this proof-of-principle study, we show that following a 3-5 minute-oral sampling period, EVs collected by the CandyCollect can be released with high purity within minutes and subsequently quantified and analyzed for cargo content. We observed consistent EV capture across repeated collections within individuals and expected variability across healthy participants. Additionally, single and pooled collections of EVs from a healthy participant resulted in a concordant protein profile. Overall, the CandyCollect is a new platform for rapid, non-invasive salivary EV collection and analysis for clinical diagnostics.

bioengineering↗

bioRxiv2024

The dynamics of capillary flow in an open-channel system featuring trigger valves

Trigger valves are fundamental features in capillary-driven microfluidic systems that stop fluid at an abrupt geometric expansion and release fluid when there is flow in an orthogonal channel connected to the valve. The concept was originally demonstrated in closed-channel capillary circuits. We show here that trigger valves can be successfully implemented in open channels. We also show that a series of open-channel trigger valves can be placed alongside or opposite a main channel resulting in a layered capillary flow. We developed a closed form model for the dynamics of the flow at trigger valves based on the concept of average friction length and successfully validated the model against experiments. For the main channel, we discuss layered flow behavior in the light of the Taylor-Aris dispersion theory and in the channel turns by considering Dean theory of mixing. This work has potential applications in autonomous microfluidics systems for biosensing, at-home or point-of-care sample preparation devices, hydrogel patterning for 3D cell culture and organ-on-a-chip models.

bioengineering↗

bioRxiv2023

Distinct Electrophysiological Signatures of Intentional and Unintentional Mind-Wandering Revealed by Low-Frequency EEG Markers

Mind-wandering is typically characterized by the common experience wherein attention veers off into thoughts unrelated to the task at hand. Recent research highlights the intentionality dimension of mind-wandering as a key predictor of adverse functional outcomes with intentional and unintentional task-unrelated thought (TUT) differentially linked to neural, behavioral, clinical, and functional correlates. We here aimed to elucidate the electrophysiological underpinnings of intentional and unintentional TUT by systematically examining the individual and collective discriminative power of a large set of EEG markers to distinguish between attentional states. Univariate and multivariate analyses were conducted on 54 predefined markers belonging to four conceptual families: ERP, spectral, information theory and connectivity measures, extracted from scalp EEG recordings prior to multidimensional reports of ongoing thought from participants performing a sustained attention task. We report here that on-task, intentional and unintentional TUT exhibit distinct electrophysiological signatures in the low frequency range. More specifically, increased features of the theta frequency range were found to be most discriminative between on-task and off-task states, while features within the alpha band were characteristic of intentional TUT when compared to unintentional TUT. This result is theoretically well aligned with contemporary accounts describing alpha activity as an index of internally oriented attention and a potential mechanism to shield internal processes from sensory input. Our study verifies the validity of the intentionality dimension of mind-wandering and represents a step forward towards real-time detection and mitigation of maladaptive mind-wandering.

neuroscience↗

bioRxiv2022

Connectome-based predictive modeling of cognitive reserve using task-based functional connectivity

Cognitive reserve supports cognitive function in the presence of pathology or atrophy. Functional neuroimaging may enable direct and accurate measurement of cognitive reserve which could have considerable clinical potential. The present study aimed to develop and validate a measure of cognitive reserve using task-based fMRI data that could then be applied to independent resting-state data. Connectome-based predictive modeling with leave-one-out cross-validation was applied to predict a residual measure of cognitive reserve using task-based functional connectivity from the Cognitive Reserve/Reference Ability Neural Network studies (n = 220, mean age = 51.91 years, SD = 17.04 years). Three network-strength predicted cognitive reserve measures were generated that accurately predicted the residual measures of unseen participants. The theoretical validity of these measures was established via a positive correlation with a socio-behavioural proxy of cognitive reserve (verbal intelligence) and a positive correlation with global cognition, independent of brain structure. This fitted model was then applied to external test data: resting-state functional connectivity data from The Irish Longitudinal Study on Ageing (TILDA, n = 294, mean age = 68.3 years, SD = 7.18 years). The network-strength predicted measures were not positively associated with a residual measure of cognitive reserve nor with measures of verbal intelligence and global cognition. The present study demonstrated that task-based functional connectivity data can be used to generate theoretically valid measures of cognitive reserve. Further work is needed to establish if, and how, measures of cognitive reserve derived from task-based functional connectivity can be applied to independent resting-state data.

neuroscience↗

bioRxiv2019

Predicting intentional and unintentional task unrelated thought with EEG

Our attention seldom remains on a singular activity, instead veering off into thoughts unrelated to the task at hand. Studies adopting a component process view of off-task thought have begun to identify the underlying mechanisms and associated electrophysiological correlates underlying ongoing thought. In the present study, we developed subject-independent classification algorithms based on electroencephalographic (EEG) markers to discriminate on-task vs off-task as well as intentional vs unintentional off-task thought. To that end, spatio-temporal and spectral features extracted from EEG activity prior to reports of ongoing thought during a test of sustained attention were ranked according to their discriminative power. Using data collected from 26 participants, average classification accuracies of 83.4% and 71.6% were achieved using a regularized linear model for on-task vs off-task and intentional vs unintentional off-task thought, respectively. Our results identified gamma oscillations as the most discriminative feature to distinguish on-task from off-task states, and alpha synchronization as the most prominent feature when off-task states are engaged in deliberately rather than when experienced as arising spontaneously. Our work represents the first successful attempt at reliably discriminating the degree of intentionality experienced during task-unrelated thought and highlights the importance of recognizing the heterogeneous nature of off-task states.

neuroscience↗

bioRxiv2019

Distinct neural markers for intentional and unintentional task unrelated thought

Studies suggest that generating thought unrelated to the task in hand is accompanied by a reduction of attention to external task-relevant information. This observations led contemporary theory to suggest multiple component processes contribute to patterns of ongoing thought. The present study used EEG to seek support for these component-process accounts by examining the neural correlates of deliberate and spontaneous task unrelated thought. EEG activity was compared prior to reports of ongoing thought during a test of sustained attention. Event-related potentials, such as the P3, were attenuated during off-task states, regardless of whether they were intentional or not. In contrast, increased alpha power and cortical phase-locking were linked to deliberate off-task thoughts, while reductions of evoked sensory response were prevalent in spontaneous off-task episodes. These data suggest off-task thought shares common and distinct neural features that are differentiated through their relationship to intention, supporting component process accounts of ongoing thought.

neuroscience↗

bioRxiv2019

Brain-predicted age difference score is related to specific cognitive functions: A multi-site replication analysis

Brain-predicted age difference scores are calculated by subtracting chronological age from brain age, which is estimated using neuroimaging data. Positive scores reflect accelerated ageing and are associated with increased mortality risk and poorer physical function. To date, however, the relationship between brain-predicted age difference scores and specific cognitive functions has not been systematically examined using appropriate statistical methods. First, applying machine learning to 1,359 T1-weighted MRI scans, we predicted the relationship between chronological age and voxel-wise grey matter data. This model was then applied to MRI data from three independent datasets, significantly predicting chronological age in each dataset: Dokuz Eylul University (n=175), the Cognitive Reserve/Reference Ability Neural Network study (n=380), and The Irish Longitudinal Study on Ageing (n=487). Each independent dataset had rich neuropsychological data. Brain-predicted age difference scores were significantly negatively correlated with performance on measures of general cognitive status (two datasets); processing speed, visual attention, and cognitive flexibility (three datasets); visual attention and cognitive flexibility (two datasets); and semantic verbal fluency (two datasets). As such, there is firm evidence of correlations between increased brain-predicted age differences and reduced cognitive function in some domains that are implicated in cognitive ageing.

neuroscience↗