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  • A novel method for dynamically altering the surface area of intracranial EEG electrodes.

    Remakanthakurup Sindhu, Kavyakantha; Ngo, Duy; Ombao, Hernando; Olaya, Joffre E; Shrey, Daniel W; Lopour, Beth A (Journal of neural engineering, IOP Publishing, 2023-01-31) [Article]
    Intracranial EEG (iEEG) plays a critical role in the treatment of neurological diseases, such as epilepsy and Parkinson's disease, as well as the development of neural prostheses and brain computer interfaces. While electrode geometries vary widely across these applications, the impact of electrode size on iEEG features and morphology is not well understood. Some insight has been gained from computer simulations, as well as experiments in which signals are recorded using electrodes of different sizes concurrently in different brain regions. Here, we introduce a novel method to record from electrodes of different sizes in the exact same location by changing the size of iEEG electrodes after implantation in the brain. We first present a theoretical model and an in vitro validation of the method. We then report the results of an in vivo implementation in three human subjects with refractory epilepsy. We recorded iEEG data from three different electrode sizes and compared the amplitudes, power spectra, inter-channel correlations, and signal-to-noise ratio (SNR) of interictal epileptiform discharges, i.e., epileptic spikes. We found that iEEG amplitude and power decreased as electrode size increased, while inter-channel correlation did not change significantly with electrode size. The SNR of epileptic spikes was generally highest in the smallest electrodes, but 39% of spikes had maximal SNR in larger electrodes. This likely depends on the precise location and spatial spread of each spike. Overall, this new method enables multi-scale measurements of electrical activity in the human brain that can facilitate our understanding of neurophysiology, treatment of neurological disease, and development of novel technologies.
  • Riemannian Geometry for Scientific Visualization

    Hadwiger, Markus; Theußl, Thomas; Rautek, Peter (ACM, 2023-01-31) [Conference Paper]
    This tutorial introduces the most important basics of Riemannian geometry and related concepts with a specific focus on applications in scientific visualization. The main concept in Riemannian geometry is the presence of a Riemannian metric on a differentiable manifold, comprising a second-order tensor field that defines an inner product in each tangent space that varies smoothly from point to point. Technically, the metric is what allows defining and computing distances and angles in a coordinate-independent manner. However, even more importantly, it in a sense is really the major structure (on top of topological considerations) that defines the space where scientific data, such as scalar, vector, and tensor fields live.
  • Portable and Efficient Dense Linear Algebra in the Beginning of the Exascale Era

    Gates, Mark; YarKhan, Asim; Sukkari, Dalal; Akbudak, Kadir; Cayrols, Sebastien; Bielich, Daniel; Abdelfattah, Ahmad; Al Farhan, Mohammed; Dongarra, Jack (IEEE, 2023-01-30) [Conference Paper]
    The SLATE project is implementing a distributed dense linear algebra library for highly-scalable distributed-memory accelerator-based computer systems. The goal is to provide a library that can be easily ported to different hardware (CPUs, GPUs, accelerators) and will provide high performance for machines into the future. Current ports include CPUs, CUDA, ROCm, and oneAPI. We achieve both performance and portability by leveraging several layers and abstractions, including OpenMP tasks to track data dependencies, MPI for distributed communication, and the BLAS++ and LAPACK++ libraries developed as a portable layer across vendor-optimized CPU and GPU BLAS and LAPACK functionality. We rely on the C++ standard library and templating to reduce code duplication for better maintainability. The few kernels not present in BLAS are implemented in CUDA, HIP, and OpenMP target offload, and are easily ported to new platforms.
  • Flame Synthesis of Carbon and Metal-Oxide Nanoparticles: Flame Types, Effects of Combustion Parameters on Properties and Measurement Methods

    Serrano-Bayona, Raul; Chu, Carson Noel; Liu, Peng; Roberts, William L. (Materials, MDPI AG, 2023-01-30) [Article]
    Carbon and metal-oxide nanoparticles (NP) are currently synthesized worldwide for various applications in the solar-energy, optical, pharmaceutical, and biomedical industries, among many others. Gas phase methods comprise flame synthesis and flame spray pyrolysis (FSP), which provide high efficiency, low cost, and the possibility of large-scale applications. The variation of combustion operation parameters exerts significant effects on the properties of the NPs. An analysis of the latest research results relevant to NP flame synthesis can provide new insight into the optimization of these methods and the development of these techniques for a large scale. This review offers insight into the current status of flame synthesis for carbon and metal-oxide NPs—specifically containing analysis and comparison of the most common carbon and metal-oxide NP production techniques. The burner configurations used at the laboratory scale and large scale are also discussed, followed by the assessment of the influence of combustion parameters on the properties of NPs. Finally, the features of the measurement techniques applied for determining NP properties were described.
  • Harnessing Folate-Functionalized Nasal Delivery of Dox–Erlo-Loaded Biopolymeric Nanoparticles in Cancer Treatment: Development, Optimization, Characterization, and Biodistribution Analysis

    Farheen, Ms; Akhter, Md Habban; Chitme, Havagiray; Akhter, Md Sayeed; Tabassum, Fauzia; Jaremko, Mariusz; Emwas, Abdul-Hamid M. (Pharmaceuticals, MDPI AG, 2023-01-30) [Article]
    The aim of the present study is to develop Doxorubicin–Erlotinib nanoparticles (Dox–Erlo NPs) and folate-armored Dox–Erlo-NP conjugates for targeting glioma cancer. Glioma is one of the most common progressive cancerous growths originating from brain glial cells. However, the blood–brain barrier (BBB) is only semi-permeable and is highly selective as to which compounds are let through; designing compounds that overcome this constraint is therefore a major challenge in the development of pharmaceutical agents. We demonstrate that the NP conjugates studied in this paper may ameliorate the BBB penetration and enrich the drug concentration in the target bypassing the BBB. NPs were prepared using a biopolymer with a double-emulsion solvent evaporation technique and functionalized with folic acid for site-specific targeting. Dox–Erlo NPs and Dox–Erlo-NP conjugates were extensively characterized in vitro for various parameters. Dox–Erlo NPs and Dox–Erlo-NP conjugates incurred a z-average of 95.35 ± 10.25 nm and 110.12 ± 9.2 nm, respectively. The zeta potentials of the Dox–Erlo NPs and Dox–Erlo-NP conjugates were observed at −18.1 mV and −25.1 mV, respectively. A TEM image has shown that the NPs were well-dispersed, uniform, de-aggregated, and consistent. A hemolytic assay confirmed hemocompatibility with the developed formulation and that it can be safely administered. Dox–Erlo-NP conjugates significantly reduced the number of viable cells to 24.66 ± 2.08% and 32.33 ± 2.51% in U87 and C6 cells, respectively, and IC50 values of 3.064 µM and 3.350 µM in U87 and C6 cells were reported after 24 h, respectively. A biodistribution study revealed that a significant concentration of Dox and Erlo were estimated in the brain relative to drug suspension. Dox–Erlo-NP conjugates were also stable for three months. The findings suggest that the developed Dox–Erlo-NP conjugates may be a promising agent for administration in glioma therapy.

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