Feasibility of combining functional near-infrared spectroscopy with electroencephalography to identify chronic stroke responders to cerebellar transcranial direct current stimulation-a computational modeling and portable neuroimaging methodological study.

Feasibility of portable neuroimaging of cerebellar transcranial direct current stimulation (ctDCS) effects on the cerebral cortex has not been investigated vis-à-vis cerebellar lobular electric field strength. We studied functional near-infrared spectroscopy (fNIRS) in conjunction with electroencephalography (EEG) to measure changes in the brain activation at the prefrontal cortex (PFC) and the sensorimotor cortex (SMC) following ctDCS as well as virtual reality-based balance training (VBaT) before and after ctDCS treatment in 12 hemiparetic chronic stroke survivors. We performed general linear modeling (GLM) that putatively associated the lobular electric field strength with the changes in the fNIRS-EEG measures at the ipsilesional and contra-lesional PFC and SMC. Here, fNIRS-EEG measures were found in the latent space from canonical correlation analysis (CCA) between the changes in total hemoglobin (tHb) concentrations (0.01-0.07Hz and 0.07-0.13Hz bands) and log10-transformed EEG bandpower within 1-45 Hz where significant (Wilks' lambda>0.95) canonical correlations were found only for the 0.07-0.13-Hz band. Also, the first principal component (97.5% variance accounted for) of the mean lobular electric field strength was a good predictor of the latent variables of oxy-hemoglobin (O2Hb) concentrations and log10-transformed EEG bandpower. GLM also provided insights into non-responders to ctDCS who also performed poorly in the VBaT due to ideomotor apraxia. Future studies should investigate fNIRS-EEG joint-imaging in a larger cohort to identify non-responders based on GLM fitting to the fNIRS-EEG data.

Resting-State NIRS-EEG in Unresponsive Patients with Acute Brain Injury: A Proof-of-Concept Study.

BACKGROUND: Neurovascular-based imaging techniques such as functional MRI (fMRI) may reveal signs of consciousness in clinically unresponsive patients but are often subject to logistical challenges in the intensive care unit (ICU). Near-infrared spectroscopy (NIRS) is another neurovascular imaging technique but low cost, can be performed serially at the bedside, and may be combined with electroencephalography (EEG), which are important advantages compared to fMRI. Combined NIRS-EEG, however, has never been evaluated for the assessment of neurovascular coupling and consciousness in acute brain injury. METHODS: We explored resting-state oscillations in eight-channel NIRS oxyhemoglobin and eight-channel EEG band-power signals to assess neurovascular coupling, the prerequisite for neurovascular-based imaging detection of consciousness, in patients with acute brain injury in the ICU (n = 9). Conscious neurological patients from step-down units and wards served as controls (n = 14). Unsupervised adaptive mixture-independent component analysis (AMICA) was used to correlate NIRS-EEG data with levels of consciousness and clinical outcome. RESULTS: Neurovascular coupling between NIRS oxyhemoglobin (0.07-0.13 Hz) and EEG band-power (1-12 Hz) signals at frontal areas was sensitive and prognostic to changing consciousness levels. AMICA revealed a mixture of five models from EEG data, with the relative probabilities of these models reflecting levels of consciousness over multiple days, although the accuracy was less than 85%. However, when combined with two channels of bilateral frontal neurovascular coupling, weighted k-nearest neighbor classification of AMICA probabilities distinguished unresponsive patients from conscious controls with > 90% accuracy (positive predictive value 93%, false discovery rate 7%) and, additionally, identified patients who subsequently failed to recover consciousness with > 99% accuracy. DISCUSSION: We suggest that NIRS-EEG for monitoring of acute brain injury in the ICU is worthy of further exploration. Normalization of neurovascular coupling may herald recovery of consciousness after acute brain injury.

Clinical VMAT machine parameter optimization for localized prostate cancer using deep reinforcement learning.

BACKGROUND: Volumetric modulated arc therapy (VMAT) machine parameter optimization (MPO) remains computationally expensive and sensitive to input dose objectives creating challenges for manual and automatic planning. Reinforcement learning (RL) involves machine learning through extensive trial-and-error, demonstrating performance exceeding humans, and existing algorithms in several domains. PURPOSE: To develop and evaluate an RL approach for VMAT MPO for localized prostate cancer to rapidly and automatically generate deliverable VMAT plans for a clinical linear accelerator (linac) and compare resultant dosimetry to clinical plans. METHODS: We extended our previous RL approach to enable VMAT MPO of a 3D beam model for a clinical linac through a policy network. It accepts an input state describing the current control point and predicts continuous machine parameters for the next control point, which are used to update the input state, repeating until plan termination. RL training was conducted to minimize a dose-based cost function for prescription of 60 Gy in 20 fractions using CT scans and contours from 136 retrospective localized prostate cancer patients, 20 of which had existing plans used to initialize training. Data augmentation was employed to mitigate over-fitting, and parameter exploration was achieved using Gaussian perturbations. Following training, RL VMAT was applied to an independent cohort of 15 patients, and the resultant dosimetry was compared to clinical plans. We also combined the RL approach with our clinical treatment planning system (TPS) to automate final plan refinement, and creating the potential for manual review and edits as required for clinical use. RESULTS: RL training was conducted for 5000 iterations, producing 40 000 plans during exploration. Mean ± SD execution time to produce deliverable VMAT plans in the test cohort was 3.3 ± 0.5 s which were automatically refined in the TPS taking an additional 77.4 ± 5.8 s. When normalized to provide equivalent target coverage, the RL+TPS plans provided a similar mean ± SD overall maximum dose of 63.2 ± 0.6 Gy and a lower mean rectum dose of 17.4 ± 7.4 compared to 63.9 ± 1.5 Gy (p = 0.061) and 21.0 ± 6.0 (p = 0.024) for the clinical plans. CONCLUSIONS: An approach for VMAT MPO using RL for a clinical linac model was developed and applied to automatically generate deliverable plans for localized prostate cancer patients, and when combined with the clinical TPS shows potential to rapidly generate high-quality plans. The RL VMAT approach shows promise to discover advanced linac control policies through trial-and-error, and algorithm limitations and future directions are identified and discussed.

FARCI: Fast and Robust Connectome Inference.

The inference of neuronal connectome from large-scale neuronal activity recordings, such as two-photon Calcium imaging, represents an active area of research in computational neuroscience. In this work, we developed FARCI (Fast and Robust Connectome Inference), a MATLAB package for neuronal connectome inference from high-dimensional two-photon Calcium fluorescence data. We employed partial correlations as a measure of the functional association strength between pairs of neurons to reconstruct a neuronal connectome. We demonstrated using in silico datasets from the Neural Connectomics Challenge (NCC) and those generated using the state-of-the-art simulator of Neural Anatomy and Optimal Microscopy (NAOMi) that FARCI provides an accurate connectome and its performance is robust to network sizes, missing neurons, and noise levels. Moreover, FARCI is computationally efficient and highly scalable to large networks. In comparison with the best performing connectome inference algorithm in the NCC, Generalized Transfer Entropy (GTE), and Fluorescence Single Neuron and Network Analysis Package (FluoroSNNAP), FARCI produces more accurate networks over different network sizes, while providing significantly better computational speed and scaling.

A proof of concept 'phase zero' study of neurodevelopment using brain organoid models with Vis/near-infrared spectroscopy and electrophysiology.

Homeostatic control of neuronal excitability by modulation of synaptic inhibition (I) and excitation (E) of the principal neurons is important during brain maturation. The fundamental features of in-utero brain development, including local synaptic E-I ratio and bioenergetics, can be modeled by cerebral organoids (CO) that have exhibited highly regular nested oscillatory network events. Therefore, we evaluated a 'Phase Zero' clinical study platform combining broadband Vis/near-infrared(NIR) spectroscopy and electrophysiology with studying E-I ratio based on the spectral exponent of local field potentials and bioenergetics based on the activity of mitochondrial Cytochrome-C Oxidase (CCO). We found a significant effect of the age of the healthy controls iPSC CO from 23 days to 3 months on the CCO activity (chi-square (2, N = 10) = 20, p = 4.5400e-05), and spectral exponent between 30-50 Hz (chi-square (2, N = 16) = 13.88, p = 0.001). Also, a significant effect of drugs, choline (CHO), idebenone (IDB), R-alpha-lipoic acid plus acetyl-L-carnitine (LCLA), was found on the CCO activity (chi-square (3, N = 10) = 25.44, p = 1.2492e-05), spectral exponent between 1 and 20 Hz (chi-square (3, N = 16) = 43.5, p = 1.9273e-09) and 30-50 Hz (chi-square (3, N = 16) = 23.47, p = 3.2148e-05) in 34 days old CO from schizophrenia (SCZ) patients iPSC. We present the feasibility of a multimodal approach, combining electrophysiology and broadband Vis-NIR spectroscopy, to monitor neurodevelopment in brain organoid models that can complement traditional drug design approaches to test clinically meaningful hypotheses.

Computational Modeling of the Photon Transport, Tissue Heating, and Cytochrome C Oxidase Absorption during Transcranial Near-Infrared Stimulation.

Transcranial near-infrared stimulation (tNIRS) has been proposed as a tool to modulate cortical excitability. However, the underlying mechanisms are not clear where the heating effects on the brain tissue needs investigation due to increased near-infrared (NIR) absorption by water and fat. Moreover, the risk of localized heating of tissues (including the skin) during optical stimulation of the brain tissue is a concern. The challenge in estimating localized tissue heating is due to the light interaction with the tissues' constituents, which is dependent on the combination ratio of the scattering and absorption properties of the constituent. Here, apart from tissue heating that can modulate the cortical excitability ("photothermal effects"); the other mechanism reported in the literature is the stimulation of the mitochondria in the cells which are active in the adenosine triphosphate (ATP) synthesis. In the mitochondrial respiratory chain, Complex IV, also known as the cytochrome c oxidase (CCO), is the unit four with three copper atoms. The absorption peaks of CCO are in the visible (420-450 nm and 600-700 nm) and the near-infrared (760-980 nm) spectral regions, which have been shown to be promising for low-level light therapy (LLLT), also known as "photobiomodulation". While much higher CCO absorption peaks in the visible spectrum can be used for the photobiomodulation of the skin, 810 nm has been proposed for the non-invasive brain stimulation (using tNIRS) due to the optical window in the NIR spectral region. In this article, we applied a computational approach to delineate the "photothermal effects" from the "photobiomodulation", i.e., to estimate the amount of light absorbed individually by each chromophore in the brain tissue (with constant scattering) and the related tissue heating. Photon migration simulations were performed for motor cortex tNIRS based on a prior work that used a 500 mW cm - 2 light source placed on the scalp. We simulated photon migration at 630 nm and 700 nm (red spectral region) and 810 nm (near-infrared spectral region). We found a temperature increase in the scalp below 0.25 °C and a minimal temperature increase in the gray matter less than 0.04 °C at 810 nm. Similar heating was found for 630 nm and 700 nm used for LLLT, so photothermal effects are postulated to be unlikely in the brain tissue.

GnT-V expression and metastatic phenotypes in macrophage-melanoma fusion hybrids is down-regulated by 5-Aza-dC: evidence for methylation sensitive, extragenic regulation of GnT-V transcription.

Beta1,6-acetylglucosaminyltransferase V (GnT-V) forms beta1,6 branching on the trimannosyl terminus of N-glycans, allowing for the production of beta1,6Glc-NAc-bearing oligosaccharides. These are used by healthy myeloid cells and cancer cells alike for systemic migration. GnT-V has multiple glycoprotein substrates and thereby exerts global effects on cancer progression, characteristic of a master regulator of metastasis. Yet little is known of the regulation of GnT-V expression by tumor cells. It was previously reported that fusion of macrophages with Cloudman S91 mouse melanoma cells produced macrophage-melanoma hybrids with up-regulated GnT-V expression regarding mRNA and enzymatic activity. Majority of these hybrids showed increased chemotactic motility in vitro and elevated metastatic potential in vivo. Here we attempted to understand this at the molecular genetic level focusing on DNA hypermethylation as a potentially key step. Treatment of cells with 5-Aza-dC, an inhibitor of DNA methylation, resulted in decreased expression of GnT-V mRNA and beta1,6-branched oligosaccharides along with reduced glycosylation of LAMP-1, a major substrate for GnT-V. This was accompanied by reduced chemotactic motility of the cells. The results suggested that DNA hypermethylation in some fashion stimulated GnT-V expression. We thus investigated the promoter region of the GnT-V gene for hypermethylation of CpG islands, comparing macrophage-melanoma hybrids of low and high metastatic potential with the parental melanoma cell line. Genomic DNA after bisulfite modification amplified from this region showed identical sequences between the cell lines. The findings indicated that differential methylation of the promoter region of GnT-V gene was not responsible for its transcriptional control, rather, appeared to be controlled through a negative regulator, nm23, whose own expression was regulated by hypermethylation. Although our studies involved a highly experimental system, the results further suggest that by whatever mechanism, reduction of GnT-V activity through 5-Aza-dC treatment might provide a new approach towards prevention of metastatic progression.

The N-terminal lysine residue-rich domain II and the 340-430 amino acid segment of eukaryotic initiation factor 2-associated glycoprotein p67 are the binding sites for the gamma-subunit of eIF2.

Eukaryotic initiation factor 2 (eIF2)-associated glycoprotein, p67, plays an important role in protecting eIF2alpha from phosphorylation by eIF2alpha-specific kinases. To understand the molecular details of interaction between p67 and the subunits of eIF2, we applied several biochemical and mutational analyses to identify interacting domains within p67 and eIF2gamma. These studies were combined with functional in vivo and in vitro assays to address the importance of the interactions between p67 and eIF2gamma in eIF2alpha phosphorylation. Studies from yeast two-hybrid assays show that p67 interacts strongly with eIF2gamma, relatively weakly with eIF2alpha, and no interaction with eIF2beta. Further mutational analyses provided evidence that the N-terminal lysine-rich domain II and the 340-430 amino acid segment of p67 interact strongly with the C-terminal 409-472 amino acid segment of eIF2gamma. GST pull-down assays show that the interaction between p67 and eIF2gamma is direct. From co-immunoprecipitation studies, we find that the interaction between p67 and eIF2gamma could not only be detected in mammalian cells growing in growth medium, it could also be detected in transiently transfected cells with expression plasmids encoding p67 and eIF2gamma. However, this interaction could not be detected in p67 mutants lacking lysine-rich domain II and the 340-430 amino acid segment. We also find a very good correlation between p67 binding to eIF2gamma and the protection of eIF2alpha from phosphorylation. Altogether, our data provide genetic evidence for the interaction between p67 and eIF2gamma and that this interaction modulates the phosphorylation of eIF2alpha.