Abscisic acid-induced H2O2 production positively regulates the activity of SAPK8/9/10 through oxidation of the type one protein phosphatase OsPP47.

Subclass III sucrose nonfermenting1-related protein kinase 2s (SnRK2s) are positive regulators of abscisic acid (ABA) signaling and abiotic stress responses. However, the underlying activation mechanisms of osmotic stress/ABA-activated protein kinase 8/9/10 (SAPK8/9/10) of rice (Oryza sativa) subclass III SnRK2s in ABA signaling remain to be elucidated. In this study, we employed biochemical, molecular biology, cell biology, and genetic approaches to identify the molecular mechanism by which OsPP47, a type one protein phosphatase in rice, regulates SAPK8/9/10 activity in ABA signaling. We found that OsPP47 not only physically interacted with SAPK8/9/10 but also interacted with ABA receptors PYLs. OsPP47 negatively regulated ABA sensitivity in seed germination and root growth. In the absence of ABA, OsPP47 directly inactivated SAPK8/9/10 by dephosphorylation. In the presence of ABA, ABA-bound OsPYL2 formed complexes with OsPP47 and inhibited its phosphatase activity, partially releasing the inhibition of SAPK8/9/10. SAPK8/9/10-mediated H2O2 production inhibited OsPP47 activity by oxidizing Cys-116 and Cys-256 to form OsPP47 oligomers, resulting in not only preventing the OsPP47-SAPK8/9/10 interaction but also blocking the inhibition of SAPK8/9/10 activity by OsPP47. Our results reveal novel pathways for the inhibition of SAPK8/9/10 in the basal state and for the activation of SAPK8/9/10 induced by ABA in rice.

Formulation and Characterization of Ethosomes for Transdermal Delivery of Prinsepia Utilis Rogle Seed Oil with Ameliorative Effects against UVB-Induced Skin Damage.

Prinsepia utilis seed oil (PUSO) is a natural medication obtained from Prinsepia utilis Rogle seed, which has been used for the treatment of skin diseases. The study aims to prepare ethosomes with high drug loading as a water-soluble transdermal vehicle to enhance the transdermal delivery of PUSO. PUSO-loaded ethosomes (PEs) were prepared using a cold method, and optimized by an orthogonal experimental design with entrapment efficiency (EE) as the dependent variable. The PEs prepared with the optimized formulation showed good stability, with a spherical shape under transmission electron microscopy (TEM), average particle size of 39.12 ± 0.85 nm, PDI of 0.270 ± 0.01, zeta potential of -11.3 ± 0.24 mV, and EE of 95.93 ± 0.43%. PEs significantly increased the skin deposition of PUSO compared to the PUSO suspension (P < 0.001). Moreover, the optimum formula showed significant ameliorative effects on ultraviolet B (UVB) irradiation-associated macroscopic and histopathological changes in mice skin. Therefore, PEs represent a promising therapeutic approach for the treatment of UVB-induced skin inflammation, with the potential for industrialization.

Identification of small-molecule inhibitors of human MUS81-EME1/2 by FRET-based high-throughput screening.

The MUS81-EME1/2 structure-specific endonucleases play a crucial role in the processing of stalled replication forks and recombination intermediates, and have been recognized as an attractive drug target to potentiate the anti-cancer efficacy of DNA-damaging agents. Currently, no bioactive small-molecule inhibitors of MUS81 are available. Here, we performed a high-throughput small-molecule inhibitors screening, using the FRET-based DNA cleavage assay. From 7920 compounds, we identified dyngo-4a as a potent inhibitor of MUS81 complexes. Dyngo-4a effectively inhibits the endonuclease activities of both MUS81-EME1 and MUS81-EME2 complexes, with IC50 values of 0.57 µM and 2.90 µM, respectively. Surface plasmon resonance (SPR) and electrophoretic mobility shift assay (EMSA) assays reveal that dyngo-4a directly binds to MUS81 complexes (KD âˆ¼ 0.61 µM) and prevents them from binding to DNA substrates. In HeLa cells, dyngo-4a significantly suppresses bleomycin-triggered H2AX serine 139 phosphorylation (γH2AX). Together, our results demonstrate that dyngo-4a is a potent MUS81 inhibitor, which could be further developed as a potentially valuable chemical tool to explore more physiological roles of MUS81 in the cells.

Global increase of colorectal cancer in young adults over the last 30 years: an analysis of the Global Burden of Disease Study 2019.

OBJECTIVES: The US Preventive Services Task Force lowered the recommended starting age for colorectal cancer (CRC) screening in average-risk adults from 50 to 45 years. We aimed to estimate the global burden and trends of colorectal cancer in adults aged 20-49 years (early-onset CRC). METHODS: This is an analysis of the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019). The GBD 2019 estimation methods were used to describe the incidence, mortality, and disability-adjusted life years (DALYs) of early CRC from 1990 to 2019. Data from 204 countries and geographic areas were available. RESULTS: The global incidence rate of early-onset CRC increased from 4.2/100 000 to 6.7/100 000 from 1990 to 2019. Mortality and DALYs of early-onset CRC also increased. The CRC incidence rate increased faster in younger adults (1.6%) than in adults aged 50-74 years (0.6%) as measured by the annual percentage change. The increase in early-onset CRC incidence was consistently observed in all five socio-demographic index (SDI) regions and 190 out of 204 countries and territories. Middle and high-middle SDI regions had faster annual increases in early-onset CRC, which warrants further attention. CONCLUSIONS: The global incidence, mortality, and DALYs of early-onset CRC increased from 1990 to 2019. The increase in early-onset CRC incidence was prevalent worldwide. Several countries were found to have higher incidence rates than the United States or fast increase in early-onset CRC, which warrants further attention.

Phosphorylation of DUF1639 protein by osmotic stress/ABA-activated protein kinase 10 regulates abscisic acid-induced antioxidant defense in rice.

In rice (Oryza Sativa), Osmotic Stress/ABA-activated Protein Kinase 10 (SAPK10) has been shown to be induced by hyperosmotic stress and abscisic acid (ABA). However, the molecular function of SAPK10 and its downstream targets in ABA-induced antioxidant defense is poorly understood. Here, we identified an unknown function DUF1639 family protein, OsDUF1639.1, which interacts with SAPK10 in vitro and in vivo. OsDUF1639.1 positively regulates ABA responses in seed germination and tolerance to drought stress. We found that SAPK10 directly phosphorylates OsDUF1639.1 at Thr-80 in vitro. The transient expression analysis in combination with mutant analysis in rice protoplasts showed that Thr-80 is essential for ABA-induced stimulation of antioxidant defense by SAPK10. These results suggest that SAPK10 functions upstream of OsDUF1639.1 to regulate the activities of antioxidant enzymes, and Thr-80 phosphorylation of OsDUF1639.1 has a crucial role in ABA-induced antioxidant defense.

EIEN: Endoscopic Image Enhancement Network Based on Retinex Theory.

In recent years, deep convolutional neural network (CNN)-based image enhancement has shown outstanding performance. However, due to the problems of uneven illumination and low contrast existing in endoscopic images, the implementation of medical endoscopic image enhancement using CNN is still an exploratory and challenging task. An endoscopic image enhancement network (EIEN) based on the Retinex theory is proposed in this paper to solve these problems. The structure consists of three parts: decomposition network, illumination correction network, and reflection component enhancement algorithm. First, the decomposition network model of pre-trained Retinex-Net is retrained on the endoscopic image dataset, and then the images are decomposed into illumination and reflection components by this decomposition network. Second, the illumination components are corrected by the proposed self-attention guided multi-scale pyramid structure. The pyramid structure is used to capture the multi-scale information of the image. The self-attention mechanism is based on the imaging nature of the endoscopic image, and the inverse image of the illumination component is fused with the features of the green and blue channels of the image to be enhanced to generate a weight map that reassigns weights to the spatial dimension of the feature map, to avoid the loss of details in the process of multi-scale feature fusion and image reconstruction by the network. The reflection component enhancement is achieved by sub-channel stretching and weighted fusion, which is used to enhance the vascular information and image contrast. Finally, the enhanced illumination and reflection components are multiplied to obtain the reconstructed image. We compare the results of the proposed method with six other methods on a test set. The experimental results show that EIEN enhances the brightness and contrast of endoscopic images and highlights vascular and tissue information. At the same time, the method in this paper obtained the best results in terms of visual perception and objective evaluation.

PRAPNet: A Parallel Residual Atrous Pyramid Network for Polyp Segmentation.

In a colonoscopy, accurate computer-aided polyp detection and segmentation can help endoscopists to remove abnormal tissue. This reduces the chance of polyps developing into cancer, which is of great importance. In this paper, we propose a neural network (parallel residual atrous pyramid network or PRAPNet) based on a parallel residual atrous pyramid module for the segmentation of intestinal polyp detection. We made full use of the global contextual information of the different regions by the proposed parallel residual atrous pyramid module. The experimental results showed that our proposed global prior module could effectively achieve better segmentation results in the intestinal polyp segmentation task compared with the previously published results. The mean intersection over union and dice coefficient of the model in the Kvasir-SEG dataset were 90.4% and 94.2%, respectively. The experimental results outperformed the scores achieved by the seven classical segmentation network models (U-Net, U-Net++, ResUNet++, praNet, CaraNet, SFFormer-L, TransFuse-L).

Comparison of diagnostic accuracy between linear EUS and miniprobe EUS for submucosal invasion in suspected cases of early gastric cancer.

OBJECTIVE: This study assessed the accuracy of linear endoscopic ultrasound (EUS) to diagnose submucosal (SM) invasion and compared linear EUS with mini-probe EUS in suspected early gastric cancer (EGC) patients. METHODS: Patients diagnosed with biopsy-verified suspected EGC were analyzed retrospectively. All cases were examined by linear EUS or miniprobe EUS for preoperative diagnosis of invasion depth and underwent endoscopic or surgical treatment for radical resection. The invasion depth evaluated by EUS and pathology were categorized as no invasion of SM and invasion of SM or deeper. The diagnosis of EUS was compared with postoperative pathology results. RESULTS: A total of 105 patients were included in the final analysis. The overall prediction accuracy of linear EUS (n = 57) for SM invasion in suspected EGC was higher than that of mini-probe EUS (n = 48), although no statistically significant differences were noted (82.5% vs 72.9%, p = 0.344). The negative predictive value (NPV) of linear EUS was significantly higher than that of mini-probe EUS (100% vs 82.8%, p = 0.037). The binary logistic regression analysis showed that tumor size (p = 0.036), the presence of ulceration (p < 0.001) and EUS type (p = 0.027) were independent risk factors for the diagnosis of SM invasion by EUS. The area under the receiver operating curve (ROC) was 0.889 and 0.719 for linear and mini-probe EUS, respectively. CONCLUSION: Linear EUS diagnosed suspected EGC for SM invasion with a higher accuracy than mini-probe EUS. In addition, large and ulcerative lesions may lead to overestimation.

Accelerating Monte Carlo modeling of structured-light-based diffuse optical imaging via "photon sharing".

The increasing use of spatially modulated imaging and single-pixel detection techniques demands computationally efficient methods for light transport modeling. Herein, we report an easy-to-implement yet significantly more efficient Monte Carlo (MC) method for simultaneously simulating spatially modulated illumination and detection patterns accurately in 3D complex domains. We have implemented this accelerated algorithm, named "photon sharing," in our open-source MC simulators, reporting 13.6× and 5.5× speedups in mesh- and voxel-based MC benchmarks, respectively. In addition, the proposed algorithm is readily used to accelerate the solving of inverse problems in spatially modulated imaging systems by building Jacobians of all illumination-detection pattern pairs concurrently, resulting in a 12.4-fold speed improvement.

Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging.

Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders and a growing number of other indications are investigated in clinical trials. To ensure optimal treatment outcome, exact electrode placement is required. Moreover, to analyze the relationship between electrode location and clinical results, a precise reconstruction of electrode placement is required, posing specific challenges to the field of neuroimaging. Since 2014 the open source toolbox Lead-DBS is available, which aims at facilitating this process. The tool has since become a popular platform for DBS imaging. With support of a broad community of researchers worldwide, methods have been continuously updated and complemented by new tools for tasks such as multispectral nonlinear registration, structural/functional connectivity analyses, brain shift correction, reconstruction of microelectrode recordings and orientation detection of segmented DBS leads. The rapid development and emergence of these methods in DBS data analysis require us to revisit and revise the pipelines introduced in the original methods publication. Here we demonstrate the updated DBS and connectome pipelines of Lead-DBS using a single patient example with state-of-the-art high-field imaging as well as a retrospective cohort of patients scanned in a typical clinical setting at 1.5T. Imaging data of the 3T example patient is co-registered using five algorithms and nonlinearly warped into template space using ten approaches for comparative purposes. After reconstruction of DBS electrodes (which is possible using three methods and a specific refinement tool), the volume of tissue activated is calculated for two DBS settings using four distinct models and various parameters. Finally, four whole-brain tractography algorithms are applied to the patient's preoperative diffusion MRI data and structural as well as functional connectivity between the stimulation volume and other brain areas are estimated using a total of eight approaches and datasets. In addition, we demonstrate impact of selected preprocessing strategies on the retrospective sample of 51 PD patients. We compare the amount of variance in clinical improvement that can be explained by the computer model depending on the preprocessing method of choice. This work represents a multi-institutional collaborative effort to develop a comprehensive, open source pipeline for DBS imaging and connectomics, which has already empowered several studies, and may facilitate a variety of future studies in the field.

Sensitive detection of antibiotics using aptamer conformation cooperated enzyme-assisted SERS technology.

Serious healthcare concerns have been raised on the issue of antibiotic residues after overuse, especially by accumulation in the human body through food webs. Here, we report a methodological development for sensitive detection of antibiotics with aptamer conformation cooperated enzyme-assisted SERS (ACCESS) technology. We design and integrate a set of nucleic acid oligos, realizing specific recognition of chloramphenicol (CAP) and efficient exonuclease III-assisted DNA amplification. It features a "signal-on" analysis of CAP with the limit of detection (15 fM), the lowest concentration detectable in the literature. Our method exhibits a high selectivity on the target analyte, free of interference of other potential antibiotic contaminants. The ACCESS assay promises an ultrasensitive and specific detection tool for trace amounts of antibiotic residues in samples of our daily life.

Connectivity Predicts deep brain stimulation outcome in Parkinson disease.

OBJECTIVE: The benefit of deep brain stimulation (DBS) for Parkinson disease (PD) may depend on connectivity between the stimulation site and other brain regions, but which regions and whether connectivity can predict outcome in patients remain unknown. Here, we identify the structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) and test its ability to predict outcome in an independent cohort. METHODS: A training dataset of 51 PD patients with STN DBS was combined with publicly available human connectome data (diffusion tractography and resting state functional connectivity) to identify connections reliably associated with clinical improvement (motor score of the Unified Parkinson Disease Rating Scale [UPDRS]). This connectivity profile was then used to predict outcome in an independent cohort of 44 patients from a different center. RESULTS: In the training dataset, connectivity between the DBS electrode and a distributed network of brain regions correlated with clinical response including structural connectivity to supplementary motor area and functional anticorrelation to primary motor cortex (p < 0.001). This same connectivity profile predicted response in an independent patient cohort (p < 0.01). Structural and functional connectivity were independent predictors of clinical improvement (p < 0.001) and estimated response in individual patients with an average error of 15% UPDRS improvement. Results were similar using connectome data from normal subjects or a connectome age, sex, and disease matched to our DBS patients. INTERPRETATION: Effective STN DBS for PD is associated with a specific connectivity profile that can predict clinical outcome across independent cohorts. This prediction does not require specialized imaging in PD patients themselves. Ann Neurol 2017;82:67-78.

Optical dosimetry probes to validate Monte Carlo and empirical-method-based NIR dose planning in the brain: publisher's note.

This note points out additional funding information that was not added to [Appl. Opt.55, 9875 (2016)APOPAI0003-693510.1364/AO.55.009875] during production.

Quantifying the microvascular origin of BOLD-fMRI from first principles with two-photon microscopy and an oxygen-sensitive nanoprobe.

The blood oxygenation level-dependent (BOLD) contrast is widely used in functional magnetic resonance imaging (fMRI) studies aimed at investigating neuronal activity. However, the BOLD signal reflects changes in blood volume and oxygenation rather than neuronal activity per se. Therefore, understanding the transformation of microscopic vascular behavior into macroscopic BOLD signals is at the foundation of physiologically informed noninvasive neuroimaging. Here, we use oxygen-sensitive two-photon microscopy to measure the BOLD-relevant microvascular physiology occurring within a typical rodent fMRI voxel and predict the BOLD signal from first principles using those measurements. The predictive power of the approach is illustrated by quantifying variations in the BOLD signal induced by the morphological folding of the human cortex. This framework is then used to quantify the contribution of individual vascular compartments and other factors to the BOLD signal for different magnet strengths and pulse sequences.

Optical dosimetry probes to validate Monte Carlo and empirical-method-based NIR dose planning in the brain.

A three-dimensional photon dosimetry in tissues is critical in designing optical therapeutic protocols to trigger light-activated drug release. The objective of this study is to investigate the feasibility of a Monte Carlo-based optical therapy planning software by developing dosimetry tools to characterize and cross-validate the local photon fluence in brain tissue, as part of a long-term strategy to quantify the effects of photoactivated drug release in brain tumors. An existing GPU-based 3D Monte Carlo (MC) code was modified to simulate near-infrared photon transport with differing laser beam profiles within phantoms of skull bone (B), white matter (WM), and gray matter (GM). A novel titanium-based optical dosimetry probe with isotropic acceptance was used to validate the local photon fluence, and an empirical model of photon transport was developed to significantly decrease execution time for clinical application. Comparisons between the MC and the dosimetry probe measurements were on an average 11.27%, 13.25%, and 11.81% along the illumination beam axis, and 9.4%, 12.06%, 8.91% perpendicular to the beam axis for WM, GM, and B phantoms, respectively. For a heterogeneous head phantom, the measured % errors were 17.71% and 18.04% along and perpendicular to beam axis. The empirical algorithm was validated by probe measurements and matched the MC results (R2>0.99), with average % error of 10.1%, 45.2%, and 22.1% relative to probe measurements, and 22.6%, 35.8%, and 21.9% relative to the MC, for WM, GM, and B phantoms, respectively. The simulation time for the empirical model was 6 s versus 8 h for the GPU-based Monte Carlo for a head phantom simulation. These tools provide the capability to develop and optimize treatment plans for optimal release of pharmaceuticals in the treatment of cancer. Future work will test and validate these novel delivery and release mechanisms in vivo.

Revisiting equivalent optical properties for cerebrospinal fluid to improve diffusion-based modeling accuracy in the brain.

Significance: The diffusion approximation (DA) is used in functional near-infrared spectroscopy (fNIRS) studies despite its known limitations due to the presence of cerebrospinal fluid (CSF). Nearly all of these studies rely on a set of empirical CSF optical properties, recommended by a previous simulation study, that were not selected for the purpose of minimizing DA modeling errors. Aim: We aim to directly quantify the accuracy of DA solutions in brain models by comparing those with the gold-standard solutions produced by the mesh-based Monte Carlo (MMC), based on which we derive updated recommendations. Approach: For both a 5-layer head and Colin27 atlas models, we obtain DA solutions by independently sweeping the CSF absorption ( µ a ) and reduced scattering ( µ s ' ) coefficients. Using an MMC solution with literature CSF optical properties as reference, we compute the errors for surface fluence, total brain sensitivity and brain energy-deposition, and identify the optimized settings where the such error is minimized. Results: Our results suggest that previously recommended CSF properties can cause significant errors (8.7% to 52%) in multiple tested metrics. By simultaneously sweeping µ a and µ s ' , we can identify infinite numbers of solutions that can exactly match DA with MMC solutions for any single tested metric. Furthermore, it is also possible to simultaneously minimize multiple metrics at multiple source/detector separations, leading to our new recommendation of setting µ s ' = 0.15 mm-1 while maintaining physiological µ a for CSF in DA simulations. Conclusion: Our new recommendation of CSF equivalent optical properties can greatly reduce the model mismatches between DA and MMC solutions at multiple metrics without sacrificing computational speed. We also show that it is possible to eliminate such a mismatch for a single or a pair of metrics of interest.

Medium-adaptive compressive diffuse optical tomography.

The low spatial resolution of diffuse optical tomography (DOT) has motivated the development of high-density DOT systems utilizing spatially-encoded illumination and detection strategies. Data compression methods, through the application of Fourier or Hadamard patterns, have been commonly explored for both illumination and detection but were largely limited to pre-determined patterns regardless of imaging targets. Here, we show that target-optimized detection patterns can yield significantly improved DOT reconstructions in both in silico and experimental tests. Applying reciprocity, we can further iteratively optimize both illumination and detection patterns and show that these simultaneously optimized source/detection patterns outperform predetermined patterns in simulation settings. In addition, we show media-adaptive measurement data compression methods enable wide-field DOT systems to recover highly complex inclusions inside optically-thick media with reduced background artifacts. Furthermore, using truncated optimized patterns shows an improvement of 2-4× in increased speed of data acquisition and reconstruction without significantly losing image quality. The proposed method can be readily extended for additional data dimensions such as spectrum and time.

Creating anatomically-derived, standardized, customizable, and three-dimensional printable head caps for functional neuroimaging.

Significance: Consistent and accurate probe placement is a crucial step towards enhancing the reproducibility of longitudinal and group-based functional neuroimaging studies. While the selection of headgear is central to these efforts, there does not currently exist a standardized design that can accommodate diverse probe configurations and experimental procedures. Aim: We aim to provide the community with an open-source software pipeline for conveniently creating low-cost, 3-D printable neuroimaging head caps with anatomically significant landmarks integrated into the structure of the cap. Approach: We utilize our advanced 3-D head mesh generation toolbox and 10-20 head landmark calculations to quickly convert a subject's anatomical scan or an atlas into a 3-D printable head cap model. The 3-D modeling environment of the open-source Blender platform permits advanced mesh processing features to customize the cap. The design process is streamlined into a Blender add-on named "NeuroCaptain". Results: Using the intuitive user interface, we create various head cap models using brain atlases, and share those with the community. The resulting mesh-based head cap designs are readily 3-D printable using off-the-shelf printers and filaments while accurately preserving the head topology and landmarks. Conclusions: The methods developed in this work result in a widely accessible tool for community members to design, customize and fabricate caps that incorporate anatomically derived landmarks. This not only permits personalized head cap designs to achieve improved accuracy, but also offers an open platform for the community to propose standardizable head caps to facilitate multi-centered data collection and sharing.

Feasibility and clinical value of linear endoscopic ultrasonography imaging in the lower gastrointestinal subepithelial lesions.

Linear endoscopic ultrasonography (EUS) has been extensively utilized as a novel diagnostic and therapeutic modality across various fields. However, there have been relatively few studies focusing on lower gastrointestinal lesions. The aim of our study was to investigate the feasibility, safety and clinical value of linear EUS in the lower gastrointestinal subepithelial lesions. This was a retrospective study involving patients with lower gastrointestinal subepithelial lesions diagnosed by linear EUS from August 2019 to April 2023 at the Second Affiliated Hospital of Anhui Medical University. The data, including basic clinical information, linear EUS features, technical success rate, complications, and follow-up, were retrospectively collected and analyzed. A total of 69 patients with lower gastrointestinal subepithelial lesions underwent examination by linear EUS. Excluding the rectum, the technical success rate of linear EUS was 90.6% (29/32). Apart from the 7 patients whose diagnosis remained unknown, 3 patients with no abnormal EUS findings, and 3 patients failed the procedure, 56 patients were included in the final diagnostic performance analysis. The most common locations of the lesions were the rectum (37/56, 66.1%) and sigmoid colon (7/56, 12.5%). Based on endoscopy findings and pathological results, the most prevalent types of subepithelial lesions in the lower gastrointestinal tract were neuroendocrine tumor (NET) (12/56, 20.3%), lipoma (8/56, 13.6%) and extraluminal compression (8/56, 13.6%). The majority of lesions ranged in diameter from 1 to 3 cm (χ2 = 18.750, p < 0.001). After undergoing linear EUS examination, 36 patients received EUS-FNA (3/36), biopsy (5/36), endoscopic resection (25/36), or surgical excision (3/36) respectively. The pathological results of 29 patients were entirely consistent with the diagnosis made using linear EUS, with an 80.6% (29/36) diagnostic accuracy rate. Follow-up indicated that the lesions remained unchanged within 6-36 months. All patients tolerated the procedure well without any complications. In conclusion, linear EUS demonstrates technical feasibility, safety, and a high diagnostic accuracy for subepithelial lesions in the lower gastrointestinal tract.

Flexible-circuit-based 3-D aware modular optical brain imaging system for high-density measurements in natural settings.

Significance: Functional near-infrared spectroscopy (fNIRS) presents an opportunity to study human brains in everyday activities and environments. However, achieving robust measurements under such dynamic condition remains a significant challenge. Aim: The modular optical brain imaging (MOBI) system is designed to enhance optode-to-scalp coupling and provide real-time probe 3-D shape estimation to improve the use of fNIRS in everyday conditions. Approach: The MOBI system utilizes a bendable and lightweight modular circuit-board design to enhance probe conformity to head surfaces and comfort for long-term wearability. Combined with automatic module connection recognition, the built-in orientation sensors on each module can be used to estimate optode 3-D positions in real-time to enable advanced tomographic data analysis and motion tracking. Results: Optical characterization of the MOBI detector reports a noise equivalence power (NEP) of 8.9 and 7.3 pW / H z at 735 nm and 850 nm, respectively, with a dynamic range of 88 dB. The 3-D optode shape acquisition yields an average error of 4.2 mm across 25 optodes in a phantom test compared to positions acquired from a digitizer. Results for initial in vivo validations, including a cuff occlusion and a finger-tapping test, are also provided. Conclusions: To the best of our knowledge, the MOBI system is the first modular fNIRS system featuring fully flexible circuit boards. The self-organizing module sensor network and automatic 3-D optode position acquisition, combined with lightweight modules (18 g/module) and ergonomic designs, would greatly aid emerging explorations of brain function in naturalistic settings.