Integrable Magnetic Fluid Hyperthermia Systems for 3D Magnetic Particle Imaging.

Background: Combining magnetic particle imaging (MPI) and magnetic fluid hyperthermia (MFH) offers the ability to perform localized hyperthermia and magnetic particle imaging-assisted thermometry of hyperthermia treatment. This allows precise regional selective heating inside the body without invasive interventions. In current MPI-MFH platforms, separate systems are used, which require object transfer from one system to another. Here, we present the design, development and evaluation process for integrable MFH platforms, which extends a commercial MPI scanner with the functionality of MFH. Methods: The biggest issue of integrating magnetic fluid hyperthermia platforms into a magnetic particle imaging system is the magnetic coupling of the devices, which induces high voltage in the imaging system, and is harming its components. In this paper, we use a self-compensation approach derived from heuristic algorithms to protect the magnetic particle imaging scanner. The integrable platforms are evaluated regarding electrical and magnetic characteristics, cooling capability, field strength, the magnetic coupling to a replica of the magnetic particle imaging system's main solenoid and particle heating. Results: The MFH platforms generate suitable magnetic fields for the magnetic heating of particles and are compatible with a commercial magnetic particle imaging scanner. In combination with the imaging system, selective heating with a gradient field and steerable heating positioning using the MPI focus fields are possible. Conclusion: The proposed MFH platforms serve as a therapeutic tool to unlock the MFH functionality of a commercial magnetic particle imaging scanner, enabling its use in future preclinical trials of MPI-guided, spatially selective magnetic hyperthermia therapy.

In situ theranostic platform combining highly localized magnetic fluid hyperthermia, magnetic particle imaging, and thermometry in 3D.

Theranostic platforms, combining diagnostic and therapeutic approaches within one system, have garnered interest in augmenting invasive surgical, chemical, and ionizing interventions. Magnetic particle imaging (MPI) offers a quite recent alternative to established radiation-based diagnostic modalities with its versatile tracer material (superparamagnetic iron oxide nanoparticles, SPION). It also offers a bimodal theranostic framework that can combine tomographic imaging with therapeutic techniques using the very same SPION. Methods: We show the interleaved combination of MPI-based imaging, therapy (highly localized magnetic fluid hyperthermia (MFH)) and therapy safety control (MPI-based thermometry) within one theranostic platform in all three spatial dimensions using a commercial MPI system and a custom-made heating insert. The heating characteristics as well as theranostic applications of the platform were demonstrated by various phantom experiments using commercial SPION. Results: We have shown the feasibility of an MPI-MFH-based theranostic platform by demonstrating high spatial control of the therapeutic target, adequate MPI-based thermometry, and successful in situ interleaved MPI-MFH application. Conclusions: MPI-MFH-based theranostic platforms serve as valuable tools that enable the synergistic integration of diagnostic and therapeutic approaches. The transition into in vivo studies will be essential to further validate their potential, and it holds promising prospects for future advancements.

Advanced electrochemical potential monitoring for improved understanding of electrical neurostimulation protocols.

Objective.Current-controlled neurostimulation is increasingly used in the clinical treatment of neurological disorders and widely applied in neural prostheses such as cochlear implants. Despite its importance, time-dependent potential traces of electrodes during microsecond-scale current pulses, especially with respect to a reference electrode (RE), are not precisely understood. However, this knowledge is critical to predict contributions of chemical reactions at the electrodes, and ultimately electrode stability, biocompatibility, and stimulation safety and efficacy.Approach.We assessed the electrochemistry of neurostimulation protocolsin vitrowith Pt microelectrodes from millisecond (classical electroanalysis) to microsecond (neurostimulation) timescales. We developed a dual-channel instrumentation amplifier to include a RE in neurostimulation setups. Uniquely, we combined potential measurements with potentiostatic prepolarization to control and investigate the surface status, which is not possible in typical stimulation setups.Main results.We thoroughly validated the instrumentation and highlighted the importance of monitoring individual electrochemical electrode potentials in different configurations of neurostimulation. We investigated electrode processes such as oxide formation and oxygen reduction by chronopotentiometry, bridging the gap between milli- and microsecond timescales. Our results demonstrate how much impact on potential traces the electrode's initial surface state and electrochemical surface processes have, even on a microsecond scale.Significance.Our unique use of preconditioning in combination with stimulation reveals that interpreting potential traces with respect to electrode processes is misleading without rigorous control of the electrode's surface state. Especiallyin vivo, where the microenvironment is unknown, simply measuring the voltage between two electrodes cannot accurately reflect the electrode's state and processes. Potential boundaries determine charge transfer, corrosion, and alterations of the electrode/tissue interface such as pH and oxygenation, particularly in long-termin vivouse. Our findings are relevant for all use-cases of constant-current stimulation, strongly advocating for electrochemicalin situinvestigations in many applications like the development of new electrode materials and stimulation methods.

A case for hybrid BCIs: combining optical and electrical modalities improves accuracy.

Near-infrared spectroscopy (NIRS) is a promising research tool that found its way into the field of brain-computer interfacing (BCI). BCI is crucially dependent on maximized usability thus demanding lightweight, compact, and low-cost hardware. We designed, built, and validated a hybrid BCI system incorporating one optical and two electrical modalities ameliorating usability issues. The novel hardware consisted of a NIRS device integrated with an electroencephalography (EEG) system that used two different types of electrodes: Regular gelled gold disk electrodes and tri-polar concentric ring electrodes (TCRE). BCI experiments with 16 volunteers implemented a two-dimensional motor imagery paradigm in off- and online sessions. Various non-canonical signal processing methods were used to extract and classify useful features from EEG, tEEG (EEG through TCRE electrodes), and NIRS. Our analysis demonstrated evidence of improvement in classification accuracy when using the TCRE electrodes compared to disk electrodes and the NIRS system. Based on our synchronous hybrid recording system, we could show that the combination of NIRS-EEG-tEEG performed significantly better than either single modality only.

Adaptive Micro-liter Fiducials for Pre-clinical MPI and MRI Imaging.

Magnetic Particle imaging (MPI) allows to measure and quantify background-free tracer distribution with a high temporal resolution. Anatomical structures are not displayed in MPI, rendering orientation within a sample error-prone and necessitating co-registration with other imaging modalities such as MRI. To support this challenge, defined external landmarks (fiducials) made from materials visible in each of the imaging modalities respectively were used in this work. Resulting signals can be aligned with the merged image containing both anatomical data and information about the tracer distribution. Defining the optimal fiducial placement is demanding and can drastically impact the 3D MPI-MRI image presentation. Here we present an adaptable 3D-printed fiducial system for preclinical co-registration of MRI and MPI data designed for easy visualisation. Clinical relevance- MPI is a promising imaging modality with many conceivable clinical applications. Simple and reliable co-registration with other imaging modalities will be crucial for a seamless transition into the clinic.

Machine Learning Approaches to Classify Anatomical Regions in Rodent Brain from High Density Recordings.

Identifying different functional regions during a brain surgery is a challenging task usually performed by highly specialized neurophysiologists. Progress in this field may be used to improve in situ brain navigation and will serve as an important building block to minimize the number of animals in preclinical brain research required by properly positioning implants intraoperatively. The study at hand aims to correlate recorded extracellular signals with the volume of origin by deep learning methods. Our work establishes connections between the position in the brain and recorded high-density neural signals. This was achieved by evaluating the performance of BLSTM, BGRU, QRNN and CNN neural network architectures on multisite electrophysiological data sets. All networks were able to successfully distinguish cortical and thalamic brain regions according to their respective neural signals. The BGRU provides the best results with an accuracy of 88.6 % and demonstrates that this classification task might be solved in higher detail while minimizing complex preprocessing steps.

Spatially resolved multi-omics deciphers bidirectional tumor-host interdependence in glioblastoma.

Glioblastomas are malignant tumors of the central nervous system hallmarked by subclonal diversity and dynamic adaptation amid developmental hierarchies. The source of dynamic reorganization within the spatial context of these tumors remains elusive. Here, we characterized glioblastomas by spatially resolved transcriptomics, metabolomics, and proteomics. By deciphering regionally shared transcriptional programs across patients, we infer that glioblastoma is organized by spatial segregation of lineage states and adapts to inflammatory and/or metabolic stimuli, reminiscent of the reactive transformation in mature astrocytes. Integration of metabolic imaging and imaging mass cytometry uncovered locoregional tumor-host interdependence, resulting in spatially exclusive adaptive transcriptional programs. Inferring copy-number alterations emphasizes a spatially cohesive organization of subclones associated with reactive transcriptional programs, confirming that environmental stress gives rise to selection pressure. A model of glioblastoma stem cells implanted into human and rodent neocortical tissue mimicking various environments confirmed that transcriptional states originate from dynamic adaptation to various environments.

T-cell dysfunction in the glioblastoma microenvironment is mediated by myeloid cells releasing interleukin-10.

Despite recent advances in cancer immunotherapy, certain tumor types, such as Glioblastomas, are highly resistant due to their tumor microenvironment disabling the anti-tumor immune response. Here we show, by applying an in-silico multidimensional model integrating spatially resolved and single-cell gene expression data of 45,615 immune cells from 12 tumor samples, that a subset of Interleukin-10-releasing HMOX1+ myeloid cells, spatially localizing to mesenchymal-like tumor regions, drive T-cell exhaustion and thus contribute to the immunosuppressive tumor microenvironment. These findings are validated using a human ex-vivo neocortical glioblastoma model inoculated with patient derived peripheral T-cells to simulate the immune compartment. This model recapitulates the dysfunctional transformation of tumor infiltrating T-cells. Inhibition of the JAK/STAT pathway rescues T-cell functionality both in our model and in-vivo, providing further evidence of IL-10 release being an important driving force of tumor immune escape. Our results thus show that integrative modelling of single cell and spatial transcriptomics data is a valuable tool to interrogate the tumor immune microenvironment and might contribute to the development of successful immunotherapies.

Transcriptional characterization of the glial response due to chronic neural implantation of flexible microprobes.

Long term implantation of (micro-)probes into neural tissue causes unique and disruptive responses. In this study, we investigate the transcriptional trajectory of glial cells responding to chronic implantation of 380 µm flexible micro-probes for up to 18 weeks. Transcriptomic analysis shows a rapid activation of microglial cells and a strong reactive astrocytic polarization, both of which are lost over the chronic of the implant duration. Animals that were implanted for 18 weeks show a transcriptional profile similar to non-implanted controls, with increased expression of genes associated with wound healing and angiogenesis, which raises hope of a normalization of the neuropil to the pre-injury state when using flexible probes. Nevertheless, our data shows that a subset of genes upregulated after 18 weeks belong to the family of immediate early genes, which indicates that structural and functional remodeling is not complete at this time point. Our results confirm and extend previous work on the molecular changes resulting from the presence of neural probes and provide a rational basis for developing interventional strategies to control them.

Removal of ECG Artifacts Affects Respiratory Muscle Fatigue Detection-A Simulation Study.

This work investigates elimination methods for cardiogenic artifacts in respiratory surface electromyographic (sEMG) signals and compares their performance with respect to subsequent fatigue detection with different fatigue algorithms. The analysis is based on artificially constructed test signals featuring a clearly defined expected fatigue level. Test signals are additively constructed with different proportions from sEMG and electrocardiographic (ECG) signals. Cardiogenic artifacts are eliminated by high-pass filtering (HP), template subtraction (TS), a newly introduced two-step approach (TSWD) consisting of template subtraction and a wavelet-based damping step and a pure wavelet-based damping (DSO). Each method is additionally combined with the exclusion of QRS segments (gating). Fatigue is subsequently quantified with mean frequency (MNF), spectral moments ratio of order five (SMR5) and fuzzy approximate entropy (fApEn). Different combinations of artifact elimination methods and fatigue detection algorithms are tested with respect to their ability to deliver invariant results despite increasing ECG contamination. Both DSO and TSWD artifact elimination methods displayed promising results regarding the intermediate, "cleaned" EMG signal. However, only the TSWD method enabled superior results in the subsequent fatigue detection across different levels of artifact contamination and evaluation criteria. SMR5 could be determined as the best fatigue detection algorithm. This study proposes a signal processing chain to determine neuromuscular fatigue despite the presence of cardiogenic artifacts. The results furthermore underline the importance of selecting a combination of algorithms that play well together to remove cardiogenic artifacts and to detect fatigue. This investigation provides guidance for clinical studies to select optimal signal processing to detect fatigue from respiratory sEMG signals.

Bilateral Intracranial Beta Activity During Forced and Spontaneous Movements in a 6-OHDA Hemi-PD Rat Model.

Cortico-basal ganglia beta oscillations (13-30 Hz) are assumed to be involved in motor impairments in Parkinson's Disease (PD), especially in bradykinesia and rigidity. Various studies have utilized the unilateral 6-hydroxydopamine (6-OHDA) rat PD model to further investigate PD and test novel treatments. However, a detailed behavioral and electrophysiological characterization of the model, including analyses of popular PD treatments such as DBS, has not been documented in the literature. We hence challenged the 6-OHDA rat hemi-PD model with a series of experiments (i.e., cylinder test, open field test, and rotarod test) aimed at assessing the motor impairments, analyzing the effects of Deep Brain Stimulation (DBS), and identifying under which conditions excessive beta oscillations occur. We found that 6-OHDA hemi-PD rats presented an impaired performance in all experiments compared to the sham group, and DBS could improve their overall performance. Across all the experiments and behaviors, the power in the high beta band was observed to be an important biomarker for PD as it showed differences between healthy and lesioned hemispheres and between 6-OHDA-lesioned and sham rats. This all shows that the 6-OHDA hemi-PD model accurately represents many of the motor and electrophysiological symptoms of PD and makes it a useful tool for the pre-clinical testing of new treatments when low ß (13-21 Hz) and high ß (21-30 Hz) frequency bands are considered separately.

Inhibition of metabotropic glutamate receptor III facilitates sensitization to alkylating chemotherapeutics in glioblastoma.

Glioblastoma (GBM), the most malignant tumor of the central nervous system, is marked by its dynamic response to microenvironmental niches. In particular, this cellular plasticity contributes to the development of an immediate resistance during tumor treatment. Novel insights into the developmental trajectory exhibited by GBM show a strong capability to respond to its microenvironment by clonal selection of specific phenotypes. Using the same mechanisms, malignant GBM do develop intrinsic mechanisms to resist chemotherapeutic treatments. This resistance was reported to be sustained by the paracrine and autocrine glutamate signaling via ionotropic and metabotropic receptors. However, the extent to which glutamatergic signaling modulates the chemoresistance and transcriptional profile of the GBM remains unexplored. In this study we aimed to map the manifold effects of glutamate signaling in GBM as the basis to further discover the regulatory role and interactions of specific receptors, within the GBM microenvironment. Our work provides insights into glutamate release dynamics, representing its importance for GBM growth, viability, and migration. Based on newly published multi-omic datasets, we explored the and characterized the functions of different ionotropic and metabotropic glutamate receptors, of which the metabotropic receptor 3 (GRM3) is highlighted through its modulatory role in maintaining the ability of GBM cells to evade standard alkylating chemotherapeutics. We addressed the clinical relevance of GRM3 receptor expression in GBM and provide a proof of concept where we manipulate intrinsic mechanisms of chemoresistance, driving GBM towards chemo-sensitization through GRM3 receptor inhibition. Finally, we validated our findings in our novel human organotypic section-based tumor model, where GBM growth and proliferation was significantly reduced when GRM3 inhibition was combined with temozolomide application. Our findings present a new picture of how glutamate signaling via mGluR3 interacts with the phenotypical GBM transcriptional programs in light of recently published GBM cell-state discoveries.

Meclofenamate causes loss of cellular tethering and decoupling of functional networks in glioblastoma.

BACKGROUND: Glioblastoma cells assemble to a syncytial communicating network based on tumor microtubes (TMs) as ultra-long membrane protrusions. The relationship between network architecture and transcriptional profile remains poorly investigated. Drugs that interfere with this syncytial connectivity such as meclofenamate (MFA) may be highly attractive for glioblastoma therapy. METHODS: In a human neocortical slice model using glioblastoma cell populations of different transcriptional signatures, three-dimensional tumor networks were reconstructed, and TM-based intercellular connectivity was mapped on the basis of two-photon imaging data. MFA was used to modulate morphological and functional connectivity; downstream effects of MFA treatment were investigated by RNA sequencing and fluorescence-activated cell sorting (FACS) analysis. RESULTS: TM-based network morphology strongly differed between the transcriptional cellular subtypes of glioblastoma and was dependent on axon guidance molecule expression. MFA revealed both a functional and morphological demolishment of glioblastoma network architectures which was reflected by a reduction of TM-mediated intercellular cytosolic traffic as well as a breakdown of TM length. RNA sequencing confirmed a downregulation of NCAM and axon guidance molecule signaling upon MFA treatment. Loss of glioblastoma communicating networks was accompanied by a failure in the upregulation of genes that are required for DNA repair in response to temozolomide (TMZ) treatment and culminated in profound treatment response to TMZ-mediated toxicity. CONCLUSION: The capacity of TM formation reflects transcriptional cellular heterogeneity. MFA effectively demolishes functional and morphological TM-based syncytial network architectures. These findings might pave the way to a clinical implementation of MFA as a TM-targeted therapeutic approach.

Long-termin vivomonitoring of gliotic sheathing of ultrathin entropic coated brain microprobes with fiber-based optical coherence tomography.

Objective.Microfabricated neuroprosthetic devices have made possible important observations on neuron activity; however, long-term high-fidelity recording performance of these devices has yet to be realized. Tissue-device interactions appear to be a primary source of lost recording performance. The current state of the art for visualizing the tissue response surrounding brain implants in animals is immunohistochemistry + confocal microscopy, which is mainly performed after sacrificing the animal. Monitoring the tissue response as it develops could reveal important features of the response which may inform improvements in electrode design.Approach.Optical coherence tomography (OCT), an imaging technique commonly used in ophthalmology, has already been adapted for imaging of brain tissue. Here, we use OCT to achieve real-time,in vivomonitoring of the tissue response surrounding chronically implanted neural devices. The employed tissue-response-provoking implants are coated with a plasma-deposited nanofilm, which has been demonstrated as a biocompatible and anti-inflammatory interface for indwelling devices. We evaluate the method by comparing the OCT results to traditional histology qualitatively and quantitatively.Main results.The differences in OCT signal across the implantation period between the plasma group and the control reveal that the plasma-type coating of otherwise rigid brain probes (glass) only slightly improve the glial encapsulation in the brain parenchyma indicating that geometrical or mechanical influences are dominating the encapsulation process.Significance.Our approach can long-term monitor and compare the tissue-response to chronically-implanted neural probes with and withour plasma coating in living animal models. Our findings provide valuable insigh to the well acknowledged yet not solved challenge.

Systematic Evaluation of DBS Parameters in the Hemi-Parkinsonian Rat Model.

Electrical stimulation of the subthalamic nucleus (STN) is clinically employed to ameliorate several symptoms of manifest Parkinson's Disease (PD). Stimulation parameters utilized by chronically implanted pulse generators comprise biphasic rectangular short (60-100 µs) pulses with a repetition frequency between 130 and 180 Hz. A better insight into the effect of electrical stimulation parameters could potentially reveal new possibilities for the improvement of deep brain stimulation (DBS) as a treatment. To this end, we employed single-sided 6-hydroxidopamine (6-OHDA) lesioning of the medial forebrain bundle (MFB) in rats to systematically investigate alternative stimulation parameters. These hemi-parkinsonian (hemi-PD) rats underwent individualized, ipsilateral electrical stimulation to the STN of the lesioned hemisphere, while the transiently induced contralateral rotational behavior was quantified to assess the effect of DBS parameter variations. The number of induced rotations during 30 s of stimulation was strongly correlated with the amplitude of the stimulation pulses. Despite a general linear relation between DBS frequency and rotational characteristics, a plateau effect was observed in the rotation count throughout the clinically used frequency range. Alternative waveforms to the conventional biphasic rectangular (Rect) pulse shapes [Triangular (Tri), Sinusoidal (Sine), and Sawtooth (Lin.Dec.)] required higher charges per phase to display similar behavior in rats as compared to the conventional pulse shape. The Euclidean Distance (ED) was used to quantify similarities between different angular trajectories. Overall, our study confirmed that the effect of different amplitude and frequency parameters of STN-DBS in the hemi-PD rat model was similar to those in human PD patients. This shows that induced contralateral rotation is a valuable readout in testing stimulation parameters. Our study supports the call for more pre-clinical studies using this measurement to assess the effect of other DBS parameters such as pulse-width and interphase intervals.

Modular Current Stimulation System for Pre-clinical Studies.

Electric stimulators with precise and reliable outputs are an indispensable part of electrophysiological research. From single cells to deep brain or neuromuscular tissue, there are diverse targets for electrical stimulation. Even though commercial systems are available, we state the need for a low-cost, high precision, functional, and modular (hardware, firmware, and software) current stimulation system with the capacity to generate stable and complex waveforms for pre-clinical research. The system presented in this study is a USB controlled 4-channel modular current stimulator that can be expanded and generate biphasic arbitrary waveforms with 16-bit resolution, high temporal precision (µs), and passive charge balancing: the NES STiM (Neuro Electronic Systems Stimulator). We present a detailed description of the system's structural design, the controlling software, reliability test, and the pre-clinical studies [deep brain stimulation (DBS) in hemi-PD rat model] in which it was utilized. The NES STiM has been tested with MacOS and Windows operating systems. Interfaces to MATLAB source codes are provided. The system is inexpensive, relatively easy to build and can be assembled quickly. We hope that the NES STiM will be used in a wide variety of neurological applications such as Functional Electrical Stimulation (FES), DBS and closed loop neurophysiological research.

Learning and Tracking the 3D Body Shape of Freely Moving Infants from RGB-D sequences.

Statistical models of the human body surface are generally learned from thousands of high-quality 3D scans in predefined poses to cover the wide variety of human body shapes and articulations. Acquisition of such data requires expensive equipment, calibration procedures, and is limited to cooperative subjects who can understand and follow instructions, such as adults. We present a method for learning a statistical 3D Skinned Multi-Infant Linear body model (SMIL) from incomplete, low-quality RGB-D sequences of freely moving infants. Quantitative experiments show that SMIL faithfully represents the RGB-D data and properly factorizes the shape and pose of the infants. To demonstrate the applicability of SMIL, we fit the model to RGB-D sequences of freely moving infants and show, with a case study, that our method captures enough motion detail for General Movements Assessment (GMA), a method used in clinical practice for early detection of neurodevelopmental disorders in infants. SMIL provides a new tool for analyzing infant shape and movement and is a step towards an automated system for GMA.

A Newcomer's Guide to Functional Near Infrared Spectroscopy Experiments.

This review presents a practical primer for functional near-infrared spectroscopy (fNIRS) with respect to technology, experimentation, and analysis software. Its purpose is to jump-start interested practitioners considering utilizing a non-invasive, versatile, nevertheless challenging window into the brain using optical methods. We briefly recapitulate relevant anatomical and optical foundations and give a short historical overview. We describe competing types of illumination (trans-illumination, reflectance, and differential reflectance) and data collection methods (continuous wave, time domain and frequency domain). Basic components (light sources, detection, and recording components) of fNIRS systems are presented. Advantages and limitations of fNIRS techniques are offered, followed by a list of very practical recommendations for its use. A variety of experimental and clinical studies with fNIRS are sampled, shedding light on many brain-related ailments. Finally, we describe and discuss a number of freely available analysis and presentation packages suited for data analysis. In conclusion, we recommend fNIRS due to its ever-growing body of clinical applications, state-of-the-art neuroimaging technique and manageable hardware requirements. It can be safely concluded that fNIRS adds a new arrow to the quiver of neuro-medical examinations due to both its great versatility and limited costs.