Comparing the performance potential of speckle contrast optical spectroscopy and diffuse correlation spectroscopy for cerebral blood flow monitoring using Monte Carlo simulations in realistic head geometries.

Significance: The non-invasive measurement of cerebral blood flow based on diffuse optical techniques has seen increased interest as a research tool for cerebral perfusion monitoring in critical care and functional brain imaging. Diffuse correlation spectroscopy (DCS) and speckle contrast optical spectroscopy (SCOS) are two such techniques that measure complementary aspects of the fluctuating intensity signal, with DCS quantifying the temporal fluctuations of the signal and SCOS quantifying the spatial blurring of a speckle pattern. With the increasing interest in the use of these techniques, a thorough comparison would inform new adopters of the benefits of each technique. Aim: We systematically evaluate the performance of DCS and SCOS for the measurement of cerebral blood flow. Approach: Monte Carlo simulations of dynamic light scattering in an MRI-derived head model were performed. For both DCS and SCOS, estimates of sensitivity to cerebral blood flow changes, coefficient of variation of the measured blood flow, and the contrast-to-noise ratio of the measurement to the cerebral perfusion signal were calculated. By varying complementary aspects of data collection between the two methods, we investigated the performance benefits of different measurement strategies, including altering the number of modes per optical detector, the integration time/fitting time of the speckle measurement, and the laser source delivery strategy. Results: Through comparison across these metrics with simulated detectors having realistic noise properties, we determine several guiding principles for the optimization of these techniques and report the performance comparison between the two over a range of measurement properties and tissue geometries. We find that SCOS outperforms DCS in terms of contrast-to-noise ratio for the cerebral blood flow signal in the ideal case simulated here but note that SCOS requires careful experimental calibrations to ensure accurate measurements of cerebral blood flow. Conclusion: We provide design principles by which to evaluate the development of DCS and SCOS systems for their use in the measurement of cerebral blood flow.

scatterBrains: an open database of human head models and companion optode locations for realistic Monte Carlo photon simulations.

Significance: Monte Carlo (MC) simulations are currently the gold standard in the near-infrared and diffuse correlation spectroscopy (NIRS/DCS) communities for generating light transport paths through tissue. However, realistic and diverse models that capture complex tissue layers are not easily available to all; moreover, manually placing optodes on such models can be tedious and time consuming. Such limitations may hinder the adoption of representative models for basic simulations and the use of these models for large-scale simulations, e.g., for training machine learning algorithms. Aim: We aim to provide the NIRS/DCS communities with an open-source, user-friendly database of morphologically and optically realistic head models, as well as a succinct software pipeline to prepare these models for mesh-based Monte Carlo simulations of light transport. Approach: Sixteen anatomical models were created from segmented T1-weighted magnetic resonance imaging (MRI) head scans and converted to tetrahedral mesh volumes. Approximately 800 companion scalp surface locations were distributed on each model, comprising full head coverage. A pipeline was created to place custom source and optical detectors at each location, and guidance is provided on how to use these parameters to set up MC simulations. Results: The models, head surface locations, and all associated code are freely available under the scatterBrains project on Github. Conclusions: The NIRS/DCS community benefits from having shared resources for conducting MC simulations on realistic head geometries. We hope this will make MRI-based head models and virtual optode placement easily accessible to all. Contributions to the database are welcome and encouraged.

Facilitating positive birth experience when preferences are not met: A qualitative analysis.

INTRODUCTION: High-quality health systems rely on care that centers on patient preferences. Realization of patient preferences can improve the birth experience. However, in the dynamic setting of birth, birth preferences can diverge from what is medically indicated. Through studying women and birthing peoples' experiences of unplanned labor procedures, we aimed to identify ways in which practitioners can support women and birthing people through unexpected or unwanted aspects of their delivery. Specifically, we focused on labor induction. METHODS: In one large US academic center, women and birthing people participated in prenatal and postpartum surveys regarding their desires, expectations, and experiences of labor induction. From April to November 2021, participants were eligible if they showed discordance between having labor induction and whether it was initially wanted or expected. Interviews focused on attitudes toward birth preferences and outcomes, with attention to discordances. We analyzed interviews through a modified grounded theory approach. RESULTS: Of 22 participants, our sample was predominantly white (91%). Participants in this sample reported discordance between wanting and experiencing (73%) and/or expecting and experiencing (54%) an induction. We identified two themes: "Discordance without mitigation is perceived as a negative experience" and "Practitioner interaction can buffer against negative experience" which includes three ways in which participants prefer support in instances of discordance: preparation, communication, and care and comfort. These methods of support foster patient autonomy and can lead to positive patient experiences. CONCLUSIONS: While medical systems should work to support patient preferences, our results suggest that patients can still have positive birth experiences, even when preferences are not fulfilled. Early practitioner preparation, positive communication, and responsive care and comfort may help to improve patient birth experience when challenges arise.

maskNMF: A denoise-sparsen-detect approach for extracting neural signals from dense imaging data.

A number of calcium imaging methods have been developed to monitor the activity of large populations of neurons. One particularly promising approach, Bessel imaging, captures neural activity from a volume by projecting within the imaged volume onto a single imaging plane, therefore effectively mixing signals and increasing the number of neurons imaged per pixel. These signals must then be computationally demixed to recover the desired neural activity. Unfortunately, currently-available demixing methods can perform poorly in the regime of high imaging density (i.e., many neurons per pixel). In this work we introduce a new pipeline (maskNMF) for demixing dense calcium imaging data. The main idea is to first denoise and temporally sparsen the observed video; this enhances signal strength and reduces spatial overlap significantly. Next we detect neurons in the sparsened video using a neural network trained on a library of neural shapes. These shapes are derived from segmented electron microscopy images input into a Bessel imaging model; therefore no manual selection of "good" neural shapes from the functional data is required here. After cells are detected, we use a constrained non-negative matrix factorization approach to demix the activity, using the detected cells' shapes to initialize the factorization. We test the resulting pipeline on both simulated and real datasets and find that it is able to achieve accurate demixing on denser data than was previously feasible, therefore enabling faithful imaging of larger neural populations. The method also provides good results on more "standard" two-photon imaging data. Finally, because much of the pipeline operates on a significantly compressed version of the raw data and is highly parallelizable, the algorithm is fast, processing large datasets faster than real time.

Erratum: Complete head cerebral sensitivity mapping for diffuse correlation spectroscopy using subject-specific magnetic resonance imaging models: errata.

[This corrects the article on p. 1131 in vol. 13, PMID: 35414976.].

Simulated redistricting plans for the analysis and evaluation of redistricting in the United States.

This article introduces the 50STATESIMULATIONS, a collection of simulated congressional districting plans and underlying code developed by the Algorithm-Assisted Redistricting Methodology (ALARM) Project. The 50STATESIMULATIONS allow for the evaluation of enacted and other congressional redistricting plans in the United States. While the use of redistricting simulation algorithms has become standard in academic research and court cases, any simulation analysis requires non-trivial efforts to combine multiple data sets, identify state-specific redistricting criteria, implement complex simulation algorithms, and summarize and visualize simulation outputs. We have developed a complete workflow that facilitates this entire process of simulation-based redistricting analysis for the congressional districts of all 50 states. The resulting 50STATESIMULATIONS include ensembles of simulated 2020 congressional redistricting plans and necessary replication data. We also provide the underlying code, which serves as a template for customized analyses. All data and code are free and publicly available. This article details the design, creation, and validation of the data.

Complete head cerebral sensitivity mapping for diffuse correlation spectroscopy using subject-specific magnetic resonance imaging models.

We characterize cerebral sensitivity across the entire adult human head for diffuse correlation spectroscopy, an optical technique increasingly used for bedside cerebral perfusion monitoring. Sixteen subject-specific magnetic resonance imaging-derived head models were used to identify high sensitivity regions by running Monte Carlo light propagation simulations at over eight hundred uniformly distributed locations on the head. Significant spatial variations in cerebral sensitivity, consistent across subjects, were found. We also identified correlates of such differences suitable for real-time assessment. These variations can be largely attributed to changes in extracerebral thickness and should be taken into account to optimize probe placement in experimental settings.

Erratum: Improved accuracy of cerebral blood flow quantification in the presence of systemic physiology cross-talk using multi-layer Monte Carlo modeling.

[This corrects the article DOI: 10.1117/1.NPh.8.1.015001.].

Optimization of time domain diffuse correlation spectroscopy parameters for measuring brain blood flow.

Significance: Time domain diffuse correlation spectroscopy (TD-DCS) can offer increased sensitivity to cerebral hemodynamics and reduced contamination from extracerebral layers by differentiating photons based on their travel time in tissue. We have developed rigorous simulation and evaluation procedures to determine the optimal time gate parameters for monitoring cerebral perfusion considering instrumentation characteristics and realistic measurement noise. Aim: We simulate TD-DCS cerebral perfusion monitoring performance for different instrument response functions (IRFs) in the presence of realistic experimental noise and evaluate metrics of sensitivity to brain blood flow, signal-to-noise ratio (SNR), and ability to reject the influence of extracerebral blood flow across a variety of time gates to determine optimal operating parameters. Approach: Light propagation was modeled on an MRI-derived human head geometry using Monte Carlo simulations for 765- and 1064-nm excitation wavelengths. We use a virtual probe with a source-detector separation of 1 cm placed in the pre-frontal region. Performance metrics described above were evaluated to determine optimal time gate(s) for different IRFs. Validation of simulation noise estimates was done with experiments conducted on an intralipid-based liquid phantom. Results: We find that TD-DCS performance strongly depends on the system IRF. Among Gaussian pulse shapes, ∼ 300 ps pulse length appears to offer the best performance, at wide gates (500 ps and larger) with start times 400 and 600 ps after the peak of the TPSF at 765 and 1064 nm, respectively, for a 1-s integration time at photon detection rates seen experimentally (600 kcps at 765 nm and 4 Mcps at 1064 nm). Conclusions: Our work shows that optimal time gates satisfy competing requirements for sufficient sensitivity and sufficient SNR. The achievable performance is further impacted by system IRF with ∼ 300 ps quasi-Gaussian pulse obtained using electro-optic laser shaping providing the best results.

Deep learning-based point-scanning super-resolution imaging.

Point-scanning imaging systems are among the most widely used tools for high-resolution cellular and tissue imaging, benefiting from arbitrarily defined pixel sizes. The resolution, speed, sample preservation and signal-to-noise ratio (SNR) of point-scanning systems are difficult to optimize simultaneously. We show these limitations can be mitigated via the use of deep learning-based supersampling of undersampled images acquired on a point-scanning system, which we term point-scanning super-resolution (PSSR) imaging. We designed a 'crappifier' that computationally degrades high SNR, high-pixel resolution ground truth images to simulate low SNR, low-resolution counterparts for training PSSR models that can restore real-world undersampled images. For high spatiotemporal resolution fluorescence time-lapse data, we developed a 'multi-frame' PSSR approach that uses information in adjacent frames to improve model predictions. PSSR facilitates point-scanning image acquisition with otherwise unattainable resolution, speed and sensitivity. All the training data, models and code for PSSR are publicly available at 3DEM.org.

Improved accuracy of cerebral blood flow quantification in the presence of systemic physiology cross-talk using multi-layer Monte Carlo modeling.

Significance: Contamination of diffuse correlation spectroscopy (DCS) measurements of cerebral blood flow (CBF) due to systemic physiology remains a significant challenge in the clinical translation of DCS for neuromonitoring. Tunable, multi-layer Monte Carlo-based (MC) light transport models have the potential to remove extracerebral flow cross-talk in cerebral blood flow index ( CBF i ) estimates. Aim: We explore the effectiveness of MC DCS models in recovering accurate CBF i changes in the presence of strong systemic physiology variations during a hypercapnia maneuver. Approach: Multi-layer slab and head-like realistic (curved) geometries were used to run MC simulations of photon propagation through the head. The simulation data were post-processed into models with variable extracerebral thicknesses and used to fit DCS multi-distance intensity autocorrelation measurements to estimate CBF i timecourses. The results of the MC CBF i values from a set of human subject hypercapnia sessions were compared with CBF i values estimated using a semi-infinite analytical model, as commonly used in the field. Results: Group averages indicate a gradual systemic increase in blood flow following a different temporal profile versus the expected rapid CBF response. Optimized MC models, guided by several intrinsic criteria and a pressure modulation maneuver, were able to more effectively separate CBF i changes from scalp blood flow influence than the analytical fitting, which assumed a homogeneous medium. Three-layer models performed better than two-layer ones; slab and curved models achieved largely similar results, though curved geometries were closer to physiological layer thicknesses. Conclusion: Three-layer, adjustable MC models can be useful in separating distinct changes in scalp and brain blood flow. Pressure modulation, along with reasonable estimates of physiological parameters, can help direct the choice of appropriate layer thicknesses in MC models.

Mechanical and hemodynamic responses of breast tissue under mammographic-like compression during functional dynamic optical imaging.

Studying tissue hemodynamics following breast compression has the potential to reveal new contrast mechanisms for evaluating breast cancer. However, how compression will be distributed and, consequently, how hemodynamics will be altered inside the compressed breast remain unclear. To explore the effect of compression, 12 healthy volunteers were studied by applying a step compression increase (4.5-53.4 N) using an optical imaging system capable of concurrently measuring pressure distribution and hemodynamic responses. Finite element analysis was used to predict the distribution of internal fluid pressure (IFP) in breast models. Comparisons between the measured pressure distribution and the reconstructed hemodynamic images for the healthy volunteers indicated significant (p < 0.05) negative correlations. The findings from a breast cancer patient showed that IFP distribution during compression strongly correlates with the observed differential hemodynamic images. We concluded that dynamic breast compression results in non-uniform internal pressure distribution throughout the breast that could potentially drive directed blood flow. The encouraging results obtained highlight the promise of developing dynamic optical imaging biomarkers for breast cancer by interpreting differential hemodynamic images of breast tissue during compression in the context of measured pressure distribution and predicted IFP.

Actin chromobody imaging reveals sub-organellar actin dynamics.

The actin cytoskeleton plays multiple critical roles in cells, from cell migration to organelle dynamics. The small and transient actin structures regulating organelle dynamics are challenging to detect with fluorescence microscopy, making it difficult to determine whether actin filaments are directly associated with specific membranes. To address these limitations, we developed fluorescent-protein-tagged actin nanobodies, termed 'actin chromobodies' (ACs), targeted to organelle membranes to enable high-resolution imaging of sub-organellar actin dynamics.

Portable System for Time-Domain Diffuse Correlation Spectroscopy.

We introduce a portable system for clinical studies based on time-domain diffuse correlation spectroscopy (DCS). After evaluating different lasers and detectors, the final system is based on a pulsed laser with about 550 ps pulsewidth, a coherence length of 38 mm, and two types of single-photon avalanche diodes (SPAD). The higher efficiency of the red-enhanced SPAD maximizes detection of the collected light, increasing the signal-to-noise ratio, while the better timing response of the CMOS SPAD optimizes the selection of late photons and increases spatial resolution. We discuss component selection and performance, and we present a full characterization of the system, measurement stability, a phantom-based validation study, and preliminary in vivo results collected from the forearms and the foreheads of four healthy subjects. With this system, we are able to resolve blood flow changes 1 cm below the skin surface with improved depth sensitivity and spatial resolution with respect to continuous wave DCS.

Aryl-NHC-group 13 trimethyl complexes: structural, stability and bonding insights.

Treatment of aromatic N-substituted N-heterocyclic carbenes (NHCs) with trimethyl-gallium and -indium yielded the new Lewis acid-base adducts, IMes·GaMe3 (1), SIMes·GaMe3 (2), IPr·GaMe3 (3), SIPr·GaMe3 (4), IMes·InMe3 (5), SIMes·InMe3 (6), IPr·InMe3 (7), and SIPr·InMe3 (8), with all complexes being identified by X-ray diffraction, IR, and multinuclear NMR analyses. Complex stability was found to be largely dependent on the nature of the constituent NHC ligands. Percent buried volume (%VBur) and topographic steric map analyses were employed to quantify and elucidate the observed trends. Additionally, a detailed bond snapping energy (BSE) decomposition analysis focusing on both steric and orbital interactions of the M-NHC bond (M = Al, Ga and In) has been performed.

G-protein coupled receptor 56 promotes myoblast fusion through serum response factor- and nuclear factor of activated T-cell-mediated signalling but is not essential for muscle development in vivo.

Mammalian muscle cell differentiation is a complex process of multiple steps for which many of the factors involved have not yet been defined. In a screen to identify the regulators of myogenic cell fusion, we found that the gene for G-protein coupled receptor 56 (GPR56) was transiently up-regulated during the early fusion of human myoblasts. Human mutations in the gene for GPR56 cause the disease bilateral frontoparietal polymicrogyria; however, the consequences of receptor dysfunction on muscle development have not been explored. Using knockout mice, we defined the role of GPR56 in skeletal muscle. GPR56(-/-) myoblasts have decreased fusion and smaller myotube sizes in culture. In addition, a loss of GPR56 expression in muscle cells results in decreases or delays in the expression of myogenic differentiation 1, myogenin and nuclear factor of activated T-cell (NFAT)c2. Our data suggest that these abnormalities result from decreased GPR56-mediated serum response element and NFAT signalling. Despite these changes, no overt differences in phenotype were identified in the muscle of GPR56 knockout mice, which presented only a mild but statistically significant elevation of serum creatine kinase compared to wild-type. In agreement with these findings, clinical data from 13 bilateral frontoparietal polymicrogyria patients revealed mild serum creatine kinase increase in only two patients. In summary, targeted disruption of GPR56 in mice results in myoblast abnormalities. The absence of a severe muscle phenotype in GPR56 knockout mice and human patients suggests that other factors may compensate for the lack of this G-protein coupled receptor during muscle development and that the motor delay observed in these patients is likely not a result of primary muscle abnormalities.

Carbamylated erythropoietin does not alleviate signs of dystrophy in mdx mice.

Erythropoietin promotes myoblast proliferation and inhibits fibrosis and thus it could impede the pathogenesis of muscle degenerative diseases. However, its stimulation of erythropoiesis limits its use as a therapeutic agent. An erythropoietin analog, carbamylated erythropoietin (C-EPO), retains these protective actions, yet it does not interact with the erythropoietin receptor. To determine whether treatment with C-EPO alleviates the signs of muscular dystrophy in an animal model of Duchenne muscular dystrophy, we treated mdx mice with intraperitoneal injections of 50 µg/kg and 100 µg/kg C-EPO for 4 and 12 weeks, and we monitored weight, serum creatine kinase levels, and changes in muscle histology. Moderate histological improvement was observed at 4 weeks, which did not translate into a significantly decreased level of serum creatine kinase. At the doses tested, C-EPO is not an effective therapeutic for the treatment of a mouse model of Duchenne muscular dystrophy.

Synaptic plasticity and NO-cGMP-PKG signaling regulate pre- and postsynaptic alterations at rat lateral amygdala synapses following fear conditioning.

In vertebrate models of synaptic plasticity, signaling via the putative "retrograde messenger" nitric oxide (NO) has been hypothesized to serve as a critical link between functional and structural alterations at pre- and postsynaptic sites. In the present study, we show that auditory Pavlovian fear conditioning is associated with significant and long-lasting increases in the expression of the postsynaptically-localized protein GluR1 and the presynaptically-localized proteins synaptophysin and synapsin in the lateral amygdala (LA) within 24 hrs following training. Further, we show that rats given intra-LA infusion of either the NR2B-selective antagonist Ifenprodil, the NOS inhibitor 7-Ni, or the PKG inhibitor Rp-8-Br-PET-cGMPS exhibit significant decreases in training-induced expression of GluR1, synaptophysin, and synapsin immunoreactivity in the LA, while those rats infused with the PKG activator 8-Br-cGMP exhibit a significant increase in these proteins in the LA. In contrast, rats given intra-LA infusion of the NO scavenger c-PTIO exhibit a significant decrease in synapsin and synaptophysin expression in the LA, but no significant impairment in the expression of GluR1. Finally, we show that intra-LA infusions of the ROCK inhibitor Y-27632 or the CaMKII inhibitor KN-93 impair training-induced expression of GluR1, synapsin, and synaptophysin in the LA. These findings suggest that the NO-cGMP-PKG, Rho/ROCK, and CaMKII signaling pathways regulate fear memory consolidation, in part, by promoting both pre- and post-synaptic alterations at LA synapses. They further suggest that synaptic plasticity in the LA during auditory fear conditioning promotes alterations at presynaptic sites via NO-driven "retrograde signaling".

Synaptic plasticity and NO-cGMP-PKG signaling coordinately regulate ERK-driven gene expression in the lateral amygdala and in the auditory thalamus following Pavlovian fear conditioning.

We have recently hypothesized that NO-cGMP-PKG signaling in the lateral nucleus of the amygdala (LA) during auditory fear conditioning coordinately regulates ERK-driven transcriptional changes in both auditory thalamic (MGm/PIN) and LA neurons that serve to promote pre- and postsynaptic alterations at thalamo-LA synapses, respectively. In the present series of experiments, we show that N-methyl-D-aspartate receptor (NMDAR)-driven synaptic plasticity and NO-cGMP-PKG signaling in the LA regulate the training-induced expression of ERK and the ERK-driven immediate early genes (IEGs) Arc/Arg3.1, c-Fos, and EGR-1 in the LA and the MGm/PIN. Rats receiving intra-LA infusion of the NR2B selective antagonist Ifenprodil, the NOS inhibitor 7-Ni, or the PKG inhibitor Rp-8-Br-PET-cGMPS exhibited significant decreases in ERK activation and in the training-induced expression of all three IEGs in the LA and MGm/PIN while intra-LA infusion of the PKG activator 8-Br-cGMP had the opposite effect. Remarkably, those rats given intra-LA infusion of the membrane impermeable NO scavenger c-PTIO exhibited significant decreases in ERK activation and ERK-driven IEG expression in the MGm/PIN, but not in the LA. Together with our previous experiments, these results suggest that synaptic plasticity and the NO-cGMP-PKG signaling pathway promote fear memory consolidation, in part, by regulating ERK-driven transcription in both the LA and the MGm/PIN. They further suggest that synaptic plasticity in the LA during fear conditioning promotes ERK-driven transcription in MGm/PIN neurons via NO-driven "retrograde signaling."