2,726 research outputs found

    Bidirectional interactions between neuronal and hemodynamic responses to transcranial direct current stimulation (tDCS): challenges for brain-state dependent tDCS

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    Transcranial direct current stimulation (tDCS) has been shown to modulate cortical neural activity. During neural activity, the electric currents from excitable membranes of brain tissue superimpose in the extracellular medium and generate a potential at scalp, which is referred as the electroencephalogram (EEG). Respective neural activity (energy demand) has been shown to be closely related, spatially and temporally, to cerebral blood flow (CBF) that supplies glucose (energy supply) via neurovascular coupling. The hemodynamic response can be captured by near-infrared spectroscopy (NIRS), which enables continuous monitoring of cerebral oxygenation and blood volume. This neurovascular coupling phenomenon led to the concept of neurovascular unit (NVU) that consists of the endothelium, glia, neurons, pericytes, and the basal lamina. Here, recent works suggest NVU as an integrated system working in concert using feedback mechanisms to enable proper brain homeostasis and function where the challenge remains in capturing these mostly nonlinear spatiotemporal interactions within NVU during tDCS. Therefore, we propose EEG-NIRS-based whole-head monitoring of tDCS-induced neuronal and hemodynamic alterations for brain-state dependent tDCS

    Identification of Human Postnatal Progenitor Cells with Multifaceted Regenerative Functions

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    Regenerative medicine is a multidisciplinary effort to regenerate or replace a deficiency of functional cells/tissues, such as deteriorated vasculature in cardiovascular pathologies or depleted -cell mass in diabetes. The transplantation of pro-regenerative progenitor cell populations has demonstrated therapeutic benefits in pre-clinical models, although translation to clinical efficacy is limited by the paradoxical balance between cell expansion ex vivo and loss of regenerative functions in vivo. Herein, this thesis encompasses two distinct approaches to circumvent translational deficiencies; 1) prevention of hematopoietic progenitor cell differentiation during ex vivo expansion and 2) utilizing the secretome of pancreas-derived multipotent stromal cell as a biotherapeutic agent. Across the first two studies, I investigated whether the inhibition of retinoic acid (RA)-signaling would limit HPC differentiation and retain pro-vascular and islet regenerative functions in vivo. These studies identified a bias of HPC towards megakaryopoiesis with prolonged culture; however, also demonstrated that the reversible inhibition of RA-signaling enhances the expansion of HPC progeny that retain a primitive phenotype and multifaceted pro-regenerative functions in vivo. Albeit, cell transplantation is limited by transplanted cell survival and subsequent secretion of pro-regenerative stimuli. Accordingly, we have demonstrated the transplantation of conditioned media generated by therapeutic cells by-passes these limitations while stimulating endogenous mechanisms of tissue regeneration. To this end, I isolated a heterogenous Panc-MSC population during culture of human islets in vitro. Using label-free mass spectrometry and flow cytometry analyses, I provide the first in-depth characterization of human Panc-MSC in comparison to BM-MSC. Specifically, I demonstrated the proteome of Panc-MSC restricts adipogenesis and RA-signaling; albeit, is competent to pro-neural stimuli and primed for robust expansion ex vivo. Next, I determined that Panc-MSC secrete pro-angiogenic and islet regenerative stimuli which are harbored within extracellular vesicles. Collectively, this body of work provides novel insights towards multifaceted therapeutic cell populations and lays a foundation to explore the cell-free biotherapeutics for applications of regenerative medicine

    Dutkat: A Privacy-Preserving System for Automatic Catch Documentation and Illegal Activity Detection in the Fishing Industry

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    United Nations' Sustainable Development Goal 14 aims to conserve and sustainably use the oceans and their resources for the benefit of people and the planet. This includes protecting marine ecosystems, preventing pollution, and overfishing, and increasing scientific understanding of the oceans. Achieving this goal will help ensure the health and well-being of marine life and the millions of people who rely on the oceans for their livelihoods. In order to ensure sustainable fishing practices, it is important to have a system in place for automatic catch documentation. This thesis presents our research on the design and development of Dutkat, a privacy-preserving, edge-based system for catch documentation and detection of illegal activities in the fishing industry. Utilising machine learning techniques, Dutkat can analyse large amounts of data and identify patterns that may indicate illegal activities such as overfishing or illegal discard of catch. Additionally, the system can assist in catch documentation by automating the process of identifying and counting fish species, thus reducing potential human error and increasing efficiency. Specifically, our research has consisted of the development of various components of the Dutkat system, evaluation through experimentation, exploration of existing data, and organization of machine learning competitions. We have also implemented it from a compliance-by-design perspective to ensure that the system is in compliance with data protection laws and regulations such as GDPR. Our goal with Dutkat is to promote sustainable fishing practices, which aligns with the Sustainable Development Goal 14, while simultaneously protecting the privacy and rights of fishing crews

    Computer Simulation of a Nitric Oxide-Releasing Catheter with a Novel Stable Convection-Diffusion Equation Solver and Automatic Quantification of Lung Ultrasound Comets by Machine Learning

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    Biological transport processes often involve a boundary acting as separation of flow, most commonly in transport involving blood-contacting medical devices. The separation of flow creates two different scenarios of mass transport across the interface. No flow exists within the medical device and diffusion governs mass transport; both convection and diffusion exist when flow is present. The added convection creates a large concentration gradient around the interface. Computer simulation of such cases prove to be difficult and require proper shock capturing methods for the solutions to be stable, which is typically lacking in commercial solvers. In this thesis, we propose a second-order accurate numerical method for solving the convection-diffusion equation by using a gradient-limited Godunov-type convective flux and the multi-point flux approximation (MPFA) L-Method for the diffusion flux. We applied our solver towards simulation of a nitric oxide-releasing intravascular catheter. Intravascular catheters are essential for long-term vascular access in both diagnosis and treatment. Use of catheters are associated with risks for infection and thrombosis. Because infection and thrombosis lead to impaired flow and potentiality life threatening systemic infections, this leads to increased morbidity and mortality, requiring catheters to be replaced among other treatments for these complications. Nitric oxide (NO) is a potent antimicrobial and antithrombotic agent produced by vascular endothelial cells. The production level in vivo is so low that the physiological effects can only be seen around the endothelial cells. The catheter can incorporate a NO source in two major ways: by impregnating the catheter with NO-releasing compounds such as S-nitroso-N-acetyl penicillamine (SNAP) or using electrochemical reactions to generate NO from nitrites. We applied our solver to both situations to guide the design of the catheter. Simulations revealed that dissolved NO inside the catheter is depleted after 12 minutes without resupplying, and electrochemical release of NO requires 10.5 minutes to reach steady state. Lung edema is often present in patients with end-stage renal disease due to reduced filtration functions of the kidney. These patients require regular dialysis sessions to manage their fluid status. The clinical gold standard to quantify lung edema is to use CT, which exposes patients to high amounts of radiation and is not cost efficient. Fluid management in such patients becomes very challenging without a clear guideline of fluid to be removed during dialysis sessions. Hypotension during dialysis can limit fluid removal, even in the setting of ongoing fluid overload or congestive heart failure. Accurate assessment of the pulmonary fluid status is needed, so that fluid overload and congestive heart failure can be detected, especially in the setting of hypotension, allowing dialysis to be altered to improve fluid removal. Recently, reverberations in ultrasound signals, referred to as ``lung comets'' have emerged as a potential quantitative way to measure lung edema. Increased presence of lung comets is associated with higher amounts of pulmonary edema, higher mortality, and more adverse cardiac events. However, the lung comets are often counted by hand by physicians with single frames in lung ultrasound and high subjectivity has been found to exist among the counting by physicians. We applied image processing and neural network techniques as an attempt to provide an objective and accurate measurement of the amount of lung comets present. Our quantitative results are significantly correlated with diastolic blood pressure and ejection fraction.PHDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163182/1/micw_1.pd

    The effects of morning preconditioning protocols on testosterone, cortisol and afternoon sprint cycling performance [conference presentation]

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    Opportunities exist for athletes to undertake morning exercise protocols in an attempt to potentate afternoon performance. Four sub elite track sprint cyclists completed a morning cycling (Cyc) or weights-based protocol (WP) prior to an afternoon cycling time trial (500m) in a repeated measures, counterbalance crossover design. Measured variables included heart rate, blood lactate, cycling peak power, salivary testosterone (T) and cortisol levels along with time trial performance. Standardised differences in means via magnitude-based inferences were calculated using paired samples T-tests in SPSS version 24 with statistical significance set at p < 0.05. The WP produced significantly faster times in the final 250m in comparison to CycP. The anticipated circadian decline of T was observed after the CycP but was however mitigated following the WP. While slight decreases in 500m times were experienced during the WP, they were not significant and were considered within the normal variations experienced between performances by elite athletes. The effect of the WP on the circadian rhythm of T could be linked to a greater recruitment of muscle fibres. Results suggest a morning resistance protocol can positively affect testosterone levels for afternoon performance. Possible gender and individual responses from conducting a W over Cyc protocol were observed and require further investigation

    GPS analysis of a team competing at a national Under 18 field hockey tournament

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    The purpose of this study was to utilise global-positioning system (GPS) technology to quantify the running demands of national Under 18 field hockey players competing in a regional field hockey tournament. Ten male players (mean ± SD; age 17.2 ± 0.4 years; stature 178.1 ± 5.2 cm; body mass 78.8 ± 8.8 kg) wore GPS units while competing in six matches over seven days at the 2018 New Zealand national under 18 field hockey tournament. GPS enabled the measurement of total distance (TD), low-speed activity (LSA; 0 -14.9 km/hr), and high-speed running (HSR; ≥ 15 km/hr) distances. Differences in running demands (TD, LSA, HSR) between positions were assessed using effect size and percent difference ± 90% confidence intervals. Midfielders covered the most TD and LSA per game and strikers the most HSR during the 6 matches. There were “very large” differences between strikers and midfielders for TD and LSA, strikers and defenders for LSA and HSR, and defenders and midfielders for LSA. These results suggest that these playing positions are sufficiently different to warrant specialised position-specific conditioning training leading into a field hockey tournament

    MATIS: Masked-Attention Transformers for Surgical Instrument Segmentation

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    We propose Masked-Attention Transformers for Surgical Instrument Segmentation (MATIS), a two-stage, fully transformer-based method that leverages modern pixel-wise attention mechanisms for instrument segmentation. MATIS exploits the instance-level nature of the task by employing a masked attention module that generates and classifies a set of fine instrument region proposals. Our method incorporates long-term video-level information through video transformers to improve temporal consistency and enhance mask classification. We validate our approach in the two standard public benchmarks, Endovis 2017 and Endovis 2018. Our experiments demonstrate that MATIS' per-frame baseline outperforms previous state-of-the-art methods and that including our temporal consistency module boosts our model's performance further
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