Publications by authors named "Shi Gu"

59 Publications

Fasting Blood Glucose and 2-h Postprandial Blood Glucose Predict Hypertension: A Report from the REACTION Study.

Diabetes Ther 2021 Apr 4;12(4):1117-1128. Epub 2021 Mar 4.

Department of Endocrinology, Chinese PLA General Hospital, Beijing, China.

Introduction: Although diabetes is associated with hypertension, whether high blood glucose levels promote hypertension remains controversial. In this study we compared the predictive power of fasting plasma glucose (FPG), 2-h postprandial blood glucose (2hPG), and glycated hemoglobin (HbA1c) for the development of hypertension.

Methods: This study was a substudy of the REACTION study, an ongoing longitudinal cohort study investigating the relationship of prediabetes and type 2 diabetes with the risk of cancer in an urban Northern Chinese population in Beijing. Logistic regression analysis was used to calculate odds ratios (ORs) after adjustment for risk factors for hypertension, including age, sex, body mass index, and triglycerides.

Results: Among the 3437 participants, 497 developed hypertension during the 4-year follow-up. The logistic regression analysis showed that elevated FPG and 2hPG levels (FPG: OR 1.529; 95% confidence interval [CI] 1.348-1.735; 2hPG: OR 1.144; 95% CI 1.100-1.191), but not HbA1c, were independent risk factors for the development of hypertension. In the highest quartile of FPG and 2hPG levels, the multivariable-corrected ORs were 2.115 (95% CI 1.612-2.777) and 2.346 (95% CI 1.787-3.080), respectively, compared with the lowest quartile. The adjusted models showed no significant correlations between quartile HbA1c levels and the development of hypertension.

Conclusion: Higher FPG and 2hPG levels, but not HbA1c levels, are independent risk factors for developing hypertension in an urban Northern Chinese population.

Trial Registration: ClinicalTrials.gov NCT01206869.
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http://dx.doi.org/10.1007/s13300-021-01019-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7994488PMC
April 2021

Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states.

Commun Biol 2021 Feb 16;4(1):210. Epub 2021 Feb 16.

Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA.

A major challenge in neuroscience is determining a quantitative relationship between the brain's white matter structural connectivity and emergent activity. We seek to uncover the intrinsic relationship among brain regions fundamental to their functional activity by constructing a pairwise maximum entropy model (MEM) of the inter-ictal activation patterns of five patients with medically refractory epilepsy over an average of ~14 hours of band-passed intracranial EEG (iEEG) recordings per patient. We find that the pairwise MEM accurately predicts iEEG electrodes' activation patterns' probability and their pairwise correlations. We demonstrate that the estimated pairwise MEM's interaction weights predict structural connectivity and its strength over several frequencies significantly beyond what is expected based solely on sampled regions' distance in most patients. Together, the pairwise MEM offers a framework for explaining iEEG functional connectivity and provides insight into how the brain's structural connectome gives rise to large-scale activation patterns by promoting co-activation between connected structures.
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http://dx.doi.org/10.1038/s42003-021-01700-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7887247PMC
February 2021

Scalable Logic Circuits with Multiple Outputs and an Automatic Reset Function Based on DNAzyme-Mediated Branch Migration.

Anal Chem 2021 02 2;93(6):3273-3279. Epub 2021 Feb 2.

National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China, Guangdong Key Laboratory of Integrated Agro-Environmental Pollution Control and Management, Institute of Eco-Environmental and Soil Sciences, Guangdong Academy of Sciences, Guangzhou 510650, China.

A scalable logic platform made up of multilayer DNA circuits was constructed using Pb, Cu, and Zn as the three inputs and three different fluorescent signals as the outputs. DNAzyme-guided cyclic cleavage reactions and DNA toehold-mediated strand branch migration were utilized to organize and connect nucleic acid probes for building the high-level logic architecture. The sequence communications between each circuit enable the logic network to work as a keypad lock, which is an information protection model at the molecular level. The multi-output mode was used to monitor the gradual unlocking process of the security system, from which one can determine which password is correct or not immediately. The autocatalytic cleavage of DNAzyme makes the biocomputing circuit feasible to realize the reset function automatically without external stimuli. Importantly, the logic platform is robust and can work effectively even in complex environmental samples.
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http://dx.doi.org/10.1021/acs.analchem.0c05173DOI Listing
February 2021

Association between obesity and urinary albumin-creatinine ratio in the middle-aged and elderly population of Southern and Northern China: a cross-sectional study.

BMJ Open 2021 01 5;11(1):e040214. Epub 2021 Jan 5.

Department of Endocrinology, The First Medical Center, Chinese People's Liberation Army General Hospital, Beijing, China

Objective: The relationship between obesity and albuminuria has not been clarified. This study aimed to investigate the correlation between obesity and the urinary albumin-creatinine ratio (UACR) in Southern and Northern China.

Design: A descriptive, cross-sectional study.

Setting: Eight regional centres in REACTION (China's Risk Evaluation of cAncers in Chinese diabeTic Individuals, a lONgitudinal study), including Dalian, Lanzhou, Zhengzhou, Guangzhou, Guangxi, Luzhou, Shanghai and Wuhan.

Participants: A total of 41 085 patients who were not diagnosed with chronic kidney disease (CKD) and had good compliance were selected according to the inclusion criteria. Patients who were diagnosed with CKD, who had other kidney diseases that could lead to increased urinary protein excretion, who were using angiotensin-converting-enzyme inhibitors or angiotensin II receptor blockers and whose important data were missing were excluded.

Results: Participants with both, central and peripheral obesity, had a higher risk of elevated UACR, even after adjusting for multiple factors (OR: 1.14, 95% CI: 1.07 to 1.12, p<0.001), and the risk of high UACR in the South was more prominent than that in the North (OR : 1.22, 95% CI: 1.11 to 1.34; OR : 1.13, 95% CI: 1.04 to 1.22, p<0.001). The risk was also elevated in the male population, hypertensive individuals, glycosylated haemoglobin (HbA1c)≥6.5% and age ≥60 years in the South. Besides the above groups, diabetes was also a risk factor for the Northern population.

Conclusions: In China, people with both central and peripheral obesity are prone to a high UACR, and the southern population has a higher risk than northern population. Factors such as male sex, hypertension, HbA1c≥6.5% and an age ≥60 years are also risk factors for CKD.
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http://dx.doi.org/10.1136/bmjopen-2020-040214DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7786798PMC
January 2021

A Unified Framework for Generalized Low-Shot Medical Image Segmentation with Scarce Data.

IEEE Trans Med Imaging 2020 Dec 18;PP. Epub 2020 Dec 18.

Medical image segmentation has achieved remarkable advancements using deep neural networks (DNNs). However, DNNs often need big amounts of data and annotations for training, both of which can be difficult and costly to obtain. In this work, we propose a unified framework for generalized low-shot (one- and few-shot) medical image segmentation based on distance metric learning (DML). Unlike most existing methods which only deal with the lack of annotations while assuming abundance of data, our framework works with extreme scarcity of both, which is ideal for rare diseases. Via DML, the framework learns a multimodal mixture representation for each category, and performs dense predictions based on cosine distances between the pixels' deep embeddings and the category representations. The multimodal representations effectively utilize the inter-subject similarities and intraclass variations to overcome overfitting due to extremely limited data. In addition, we propose adaptive mixing coefficients for the multimodal mixture distributions to adaptively emphasize the modes better suited to the current input. The representations are implicitly embedded as weights of the fc layer, such that the cosine distances can be computed efficiently via forward propagation. In our experiments on brain MRI and abdominal CT datasets, the proposed framework achieves superior performances for low-shot segmentation towards standard DNN-based (3D U-Net) and classical registration-based (ANTs) methods, e.g., achieving mean Dice coefficients of 81%/69% for brain tissue/abdominal multi-organ segmentation using a single training sample, as compared to 52%/31% and 72%/35% by the U-Net and ANTs, respectively.
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http://dx.doi.org/10.1109/TMI.2020.3045775DOI Listing
December 2020

Measurement reliability for individual differences in multilayer network dynamics: Cautions and considerations.

Neuroimage 2021 01 24;225:117489. Epub 2020 Oct 24.

Center for Biomedical Imaging and Neuromodulation, The Nathan S. Kline Institute for Psychiatric Research, 140 Old Orangeburg Rd, Orangeburg, NY 10962, United States; Center for the Developing Brain, The Child Mind Institute, 101 East 56th Street, New York, NY 10022, United States. Electronic address:

Multilayer network models have been proposed as an effective means of capturing the dynamic configuration of distributed neural circuits and quantitatively describing how communities vary over time. Beyond general insights into brain function, a growing number of studies have begun to employ these methods for the study of individual differences. However, test-retest reliabilities for multilayer network measures have yet to be fully quantified or optimized, potentially limiting their utility for individual difference studies. Here, we systematically evaluated the impact of multilayer community detection algorithms, selection of network parameters, scan duration, and task condition on test-retest reliabilities of multilayer network measures (i.e., flexibility, integration, and recruitment). A key finding was that the default method used for community detection by the popular generalized Louvain algorithm can generate erroneous results. Although available, an updated algorithm addressing this issue is yet to be broadly adopted in the neuroimaging literature. Beyond the algorithm, the present work identified parameter selection as a key determinant of test-retest reliability; however, optimization of these parameters and expected reliabilities appeared to be dataset-specific. Once parameters were optimized, consistent with findings from the static functional connectivity literature, scan duration was a much stronger determinant of reliability than scan condition. When the parameters were optimized and scan duration was sufficient, both passive (i.e., resting state, Inscapes, and movie) and active (i.e., flanker) tasks were reliable, although reliability in the movie watching condition was significantly higher than in the other three tasks. The minimal data requirement for achieving reliable measures for the movie watching condition was 20 min, and 30 min for the other three tasks. Our results caution the field against the use of default parameters without optimization based on the specific datasets to be employed - a process likely to be limited for most due to the lack of test-retest samples to enable parameter optimization.
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http://dx.doi.org/10.1016/j.neuroimage.2020.117489DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7829665PMC
January 2021

Semi-automated shear stress measurements in developing embryonic hearts.

Biomed Opt Express 2020 Sep 27;11(9):5297-5305. Epub 2020 Aug 27.

Department of Pediatrics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA.

Blood-induced shear stress influences gene expression. Abnormal shear stress patterns on the endocardium of the early-stage heart tube can lead to congenital heart defects. To have a better understanding of these mechanisms, it is essential to include shear stress measurements in longitudinal cohort studies of cardiac development. Previously reported approaches are computationally expensive and nonpractical when assessing many animals. Here, we introduce a new approach to estimate shear stress that does not rely on recording 4D image sets and extensive post processing. Our method uses two adjacent optical coherence tomography frames (B-scans) where lumen geometry and flow direction are determined from the structural data and the velocity is measured from the Doppler OCT signal. We validated our shear stress estimate by flow phantom experiments and applied it to live quail embryo hearts where observed shear stress patterns were similar to previous studies.
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http://dx.doi.org/10.1364/BOE.395952DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7510878PMC
September 2020

Optimization of energy state transition trajectory supports the development of executive function during youth.

Elife 2020 03 27;9. Epub 2020 Mar 27.

Departments of Psychiatry, University of Pennsylvania, Philadelphia, United States.

Executive function develops during adolescence, yet it remains unknown how structural brain networks mature to facilitate activation of the fronto-parietal system, which is critical for executive function. In a sample of 946 human youths (ages 8-23y) who completed diffusion imaging, we capitalized upon recent advances in linear dynamical network control theory to calculate the energetic cost necessary to activate the fronto-parietal system through the control of multiple brain regions given existing structural network topology. We found that the energy required to activate the fronto-parietal system declined with development, and the pattern of regional energetic cost predicts unseen individuals' brain maturity. Finally, energetic requirements of the cingulate cortex were negatively correlated with executive performance, and partially mediated the development of executive performance with age. Our results reveal a mechanism by which structural networks develop during adolescence to reduce the theoretical energetic costs of transitions to activation states necessary for executive function.
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http://dx.doi.org/10.7554/eLife.53060DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7162657PMC
March 2020

Insulin resistance is associated with urinary albumin-creatinine ratio in normal weight individuals with hypertension and diabetes: The REACTION study.

J Diabetes 2020 May 10;12(5):406-416. Epub 2020 Jan 10.

Chinese PLA General Hospital, Beijing, China.

Background: The relationship between albuminuria and insulin resistance (IR) has not been clarified in previous studies. This study was conducted to examine whether IR is associated with albuminuria in subjects with diverse blood pressure and glycometabolism statuses.

Methods: This study included 34 136 participants whose data were drawn from a cross-sectional survey named the 2011 REACTION study. The participants were divided into six groups. The urinary albumin-creatinine ratio (UACR) and glomerular filtration rate (GFR) were used as markers of chronic kidney disease (CKD). Variance tests and logistic regression models were performed for homeostatic model assessment of insulin resistance (HOMA-IR) in relation to UACR and eGFR.

Results: First, UACR levels and HOMA-IR exhibited a positive correlation among participants (P < 0.05), and a negative correlation existed between GFR and HOMA-IR (P < 0.05). Second, in the hypertension with diabetes group, in individuals whose body mass index (BMI) was 18.5-24.0 kg/m , age was 50-60 years old, low density lipoprotein cholesterol (LDL-C) was 2.6-3.4 mmol/L or high density lipoprotein cholesterol (HDL-C) was 0.9-1.55 mmol/L, HOMA-IR was positively associated with UACR (P < 0.05). However, there was a negative correlation between GFR and HOMA-IR in the hypertension with diabetes group in individuals whose BMI was 18.5-24.0 kg/m or whose age was over 65 years old (P < 0.05).

Conclusions: In the context of different blood pressure and glycometabolism statuses, the positive correlation between UACR levels and HOMA-IR was affected by BMI, age, LDL-C, HDL-C, and GFR. In patients with hypertension and diabetes, the early detection and intervention of IR and related risk factors in patients with normal BMI may reduce the occurrence of microalbuminuria and delay the progression of CKD.
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http://dx.doi.org/10.1111/1753-0407.13010DOI Listing
May 2020

The Association between Resting Heart Rate and Urinary Albumin/Creatinine Ratio in Middle-Aged and Elderly Chinese Population: A Cross-Sectional Study.

J Diabetes Res 2019 25;2019:9718370. Epub 2019 Aug 25.

Department of Endocrinology, Chinese People's Liberation Army General Hospital, No. 28 Fuxing Road, Beijing 100853, China.

Objective: In general population, resting heart rate (RHR) is associated with cardiovascular disease. However, its relation to chronic kidney disease (CKD) is debated. We therefore investigated the relationship between RHR and urinary albumin/creatinine ratio (UACR, an indicator of early kidney injury) in general population at different levels of blood pressure and blood glucose.

Methods: We screened out 32,885 subjects from the REACTION study after excluding the subjects with primary kidney disease, heart disease, tumor history, related drug application, and important data loss. The whole group was divided into four groups (Q1: RHR ≤ 71, Q2: 72 ≤ RHR ≤ 78, Q3: 79 ≤ RHR ≤ 86, and Q4: 87 ≤ RHR) according to the quartile of average resting heart rate. The renal function was evaluated by UACR (divided by quartiles of all data in the center to which the subject belonged). Ordinary logistic regression was carried out to explore the association between RHR and UACR at diverse blood pressure and blood glucose levels.

Results: The subjects with higher RHR quartile tend to have a higher UACR, even multifactors were adjusted. After stratifying the subjects according to blood pressure and blood glucose, the positive relationship between RHR and UACR remained in the subjects with normal blood pressure and normal glucose tolerance, while in the hypertension (SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg) group and the diabetic mellitus (FPG ≥ 7.0 mmol/L and/or PPG ≥ 11.1 mmol/L) group, the relationship disappeared. In the subjects without hypertension, compared with the Q1 group, the UACR is significant higher in the Q3 group (OR: 1.11) and the Q4 group (OR: 1.22). In the subjects with normal glucose tolerance (NGT), compared with the Q1 group, the UACR is significantly higher in the Q3 group (OR: 1.13) and the Q4 group (OR: 1.19).

Conclusions: The population with higher RHR tend to have a higher UACR in the normal blood pressure group and the normal glucose tolerance group.
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http://dx.doi.org/10.1155/2019/9718370DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6732617PMC
February 2020

Unifying the Notions of Modularity and Core-Periphery Structure in Functional Brain Networks during Youth.

Cereb Cortex 2020 03;30(3):1087-1102

Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.

At rest, human brain functional networks display striking modular architecture in which coherent clusters of brain regions are activated. The modular account of brain function is pervasive, reliable, and reproducible. Yet, a complementary perspective posits a core-periphery or rich-club account of brain function, where hubs are densely interconnected with one another, allowing for integrative processing. Unifying these two perspectives has remained difficult due to the fact that the methodological tools to identify modules are entirely distinct from the methodological tools to identify core-periphery structure. Here, we leverage a recently-developed model-based approach-the weighted stochastic block model-that simultaneously uncovers modular and core-periphery structure, and we apply it to functional magnetic resonance imaging data acquired at rest in 872 youth of the Philadelphia Neurodevelopmental Cohort. We demonstrate that functional brain networks display rich mesoscale organization beyond that sought by modularity maximization techniques. Moreover, we show that this mesoscale organization changes appreciably over the course of neurodevelopment, and that individual differences in this organization predict individual differences in cognition more accurately than module organization alone. Broadly, our study provides a unified assessment of modular and core-periphery structure in functional brain networks, offering novel insights into their development and implications for behavior.
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http://dx.doi.org/10.1093/cercor/bhz150DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7132934PMC
March 2020

RE: Warnings and caveats in brain controllability.

Neuroimage 2019 08 8;197:586-588. Epub 2019 May 8.

Departments of Bioengineering, Physics & Astronomy, Neurology, Psychiatry, Electrical & Systems Engineering, University of Pennsylvania, USA. Electronic address:

The use of network control theory to analyze the organization of white matter fibers in the human brain has the potential to enable mechanistic theories of cognition, and to inform the development of novel diagnostics and treatments for neurological disease and psychiatric disorders (Gu et al., 2015). The recent article (Tu et al., 2018) aims to challenge several of the contributions of (Gu et al., 2015), and particularly the conclusions that brain networks are theoretically controllable from single regions, and that brain networks feature no specific controllability profiles when compared to random network models. Here we provide additional theoretical arguments in support of (Gu et al., 2015) and against the results and methodologies used in (Tu et al., 2018), thus settling that (i) brain networks are controllable from a single region, (ii) brain networks require large control energy, and (iii) brain networks feature distinctive controllability properties with respect to a class of random network models.
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http://dx.doi.org/10.1016/j.neuroimage.2019.05.001DOI Listing
August 2019

Temporal lobe epilepsy: Hippocampal pathology modulates connectome topology and controllability.

Neurology 2019 05 19;92(19):e2209-e2220. Epub 2019 Apr 19.

From the Neuroimaging of Epilepsy Laboratory (B.C.B., F.F., M.L., B.C., A.B., N.B.) and Multimodal Imaging and Connectome Analysis Laboratory (B.C.B.), McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Canada; Department of Bioengineering and Electrical and Systems Engineering (S.G., D.S.B.), University of Pennsylvania, Philadelphia; and York Neuroimaging Center (E.J., J.S.), University of York, UK.

Objective: To assess whether hippocampal sclerosis (HS) severity is mirrored at the level of large-scale networks.

Methods: We studied preoperative high-resolution anatomical and diffusion-weighted MRI of 44 temporal lobe epilepsy (TLE) patients with histopathologic diagnosis of HS (n = 25; TLE-HS) and isolated gliosis (n = 19; TLE-G) and 25 healthy controls. Hippocampal measurements included surface-based subfield mapping of atrophy and T2 hyperintensity indexing cell loss and gliosis, respectively. Whole-brain connectomes were generated via diffusion tractography and examined using graph theory along with a novel network control theory paradigm that simulates functional dynamics from structural network data.

Results: Compared to controls, we observed markedly increased path length and decreased clustering in TLE-HS compared to controls, indicating lower global and local network efficiency, while TLE-G showed only subtle alterations. Similarly, network controllability was lower in TLE-HS only, suggesting limited range of functional dynamics. Hippocampal imaging markers were positively associated with macroscale network alterations, particularly in ipsilateral CA1-3. Systematic assessment across several networks revealed maximal changes in the hippocampal circuity. Findings were consistent when correcting for cortical thickness, suggesting independence from gray matter atrophy.

Conclusions: Severe HS is associated with marked remodeling of connectome topology and structurally governed functional dynamics in TLE, as opposed to isolated gliosis, which has negligible effects. Cell loss, particularly in CA1-3, may exert a cascading effect on brain-wide connectomes, underlining coupled disease processes across multiple scales.
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http://dx.doi.org/10.1212/WNL.0000000000007447DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6537128PMC
May 2019

Noninvasive Assessment of Corneal Crosslinking With Phase-Decorrelation Optical Coherence Tomography.

Invest Ophthalmol Vis Sci 2019 01;60(1):41-51

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, United States.

Purpose: There is strong evidence that abnormalities in corneal biomechanical play a causal role in corneal ectasias, such as keratoconus. Additionally, corneal crosslinking (CXL) treatment, which halts progression of keratoconus, directly appeals to corneal biomechanics. However, existing methods of corneal biomechanical assessment have various drawbacks: dependence on IOP, long acquisition times, or limited resolution. Here, we present a method that may avoid these limitations by using optical coherence tomography (OCT) to detect the endogenous random motion within the cornea, which can be associated with stromal crosslinking.

Methods: Phase-decorrelation OCT (PhD-OCT), based in the theory of dynamic light scattering, is a method to spatially resolve endogenous random motion by calculating the decorrelation rate, Γ, of the temporally evolving complex-valued OCT signal. PhD-OCT images of ex vivo porcine globes were recorded during CXL and control protocols. In addition, human patients were imaged with PhD-OCT using a clinical OCT system.

Results: In both the porcine cornea and the human cornea, crosslinking results in a reduction of Γ (P < 0.0001), indicating more crosslinks. This effect was repeatable in ex vivo porcine corneas (change in average Γ = -41.55 ± 9.64%, n = 5) and not seen after sham treatments (change in average Γ = 2.83 ± 12.56%, n = 5). No dependence of PhD-OCT on IOP was found, and correctable effects were caused by variations in signal-to-noise ratio, hydration, and motion.

Conclusions: PhD-OCT may be a useful and readily translatable tool for investigating biomechanical properties of the cornea and for enhancing the diagnosis and treatment of patients.
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http://dx.doi.org/10.1167/iovs.18-25535DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6322634PMC
January 2019

Network changes associated with transdiagnostic depressive symptom improvement following cognitive behavioral therapy in MDD and PTSD.

Mol Psychiatry 2018 12 13;23(12):2314-2323. Epub 2018 Aug 13.

Center for Neuromodulation in Depression and Stress, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA.

Despite widespread use of cognitive behavioral therapy (CBT) in clinical practice, its mechanisms with respect to brain networks remain sparsely described. In this study, we applied tools from graph theory and network science to better understand the transdiagnostic neural mechanisms of this treatment for depression. A sample of 64 subjects was included in a study of network dynamics: 33 patients (15 MDD, 18 PTSD) received longitudinal fMRI resting state scans before and after 12 weeks of CBT. Depression severity was rated on the Montgomery-Asberg Depression Rating Scale (MADRS). Thirty-one healthy controls were included to determine baseline network roles. Univariate and multivariate regression analyses were conducted on the normalized change scores of within- and between-system connectivity and normalized change score of the MADRS. Penalized regression was used to select a sparse set of predictors in a data-driven manner. Univariate analyses showed greater symptom reduction was associated with an increased functional role of the Ventral Attention (VA) system as an incohesive provincial system (decreased between- and decreased within-system connectivity). Multivariate analyses selected between-system connectivity of the VA system as the most prominent feature associated with depression improvement. Observed VA system changes are interesting in light of brain controllability descriptions: attentional control systems, including the VA system, fall on the boundary between-network communities, and facilitate integration or segregation of diverse cognitive systems. Thus, increasing segregation of the VA system following CBT (decreased between-network connectivity) may result in less contribution of emotional attention to cognitive processes, thereby potentially improving cognitive control.
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http://dx.doi.org/10.1038/s41380-018-0201-7DOI Listing
December 2018

Linked dimensions of psychopathology and connectivity in functional brain networks.

Nat Commun 2018 08 1;9(1):3003. Epub 2018 Aug 1.

Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.

Neurobiological abnormalities associated with psychiatric disorders do not map well to existing diagnostic categories. High co-morbidity suggests dimensional circuit-level abnormalities that cross diagnoses. Here we seek to identify brain-based dimensions of psychopathology using sparse canonical correlation analysis in a sample of 663 youths. This analysis reveals correlated patterns of functional connectivity and psychiatric symptoms. We find that four dimensions of psychopathology - mood, psychosis, fear, and externalizing behavior - are associated (r = 0.68-0.71) with distinct patterns of connectivity. Loss of network segregation between the default mode network and executive networks emerges as a common feature across all dimensions. Connectivity linked to mood and psychosis becomes more prominent with development, and sex differences are present for connectivity related to mood and fear. Critically, findings largely replicate in an independent dataset (n = 336). These results delineate connectivity-guided dimensions of psychopathology that cross clinical diagnostic categories, which could serve as a foundation for developing network-based biomarkers in psychiatry.
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http://dx.doi.org/10.1038/s41467-018-05317-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6070480PMC
August 2018

Complex regression Doppler optical coherence tomography.

J Biomed Opt 2018 04;23(4):1-8

Case Western Reserve Univ., United States.

We introduce a new method to measure Doppler shifts more accurately and extend the dynamic range of Doppler optical coherence tomography (OCT). The two-point estimate of the conventional Doppler method is replaced with a regression that is applied to high-density B-scans in polar coordinates. We built a high-speed OCT system using a 1.68-MHz Fourier domain mode locked laser to acquire high-density B-scans (16,000 A-lines) at high enough frame rates (∼100  fps) to accurately capture the dynamics of the beating embryonic heart. Flow phantom experiments confirm that the complex regression lowers the minimum detectable velocity from 12.25  mm  /  s to 374  μm  /  s, whereas the maximum velocity of 400  mm  /  s is measured without phase wrapping. Complex regression Doppler OCT also demonstrates higher accuracy and precision compared with the conventional method, particularly when signal-to-noise ratio is low. The extended dynamic range allows monitoring of blood flow over several stages of development in embryos without adjusting the imaging parameters. In addition, applying complex averaging recovers hidden features in structural images.
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http://dx.doi.org/10.1117/1.JBO.23.4.046009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5920204PMC
April 2018

The Energy Landscape of Neurophysiological Activity Implicit in Brain Network Structure.

Sci Rep 2018 02 6;8(1):2507. Epub 2018 Feb 6.

Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.

A critical mystery in neuroscience lies in determining how anatomical structure impacts the complex functional dynamics of the brain. How does large-scale brain circuitry constrain states of neuronal activity and transitions between those states? We address these questions using a maximum entropy model of brain dynamics informed by white matter tractography. We demonstrate that the most probable brain states - characterized by minimal energy - display common activation profiles across brain areas: local spatially-contiguous sets of brain regions reminiscent of cognitive systems are co-activated frequently. The predicted activation rate of these systems is highly correlated with the observed activation rate measured in a separate resting state fMRI data set, validating the utility of the maximum entropy model in describing neurophysiological dynamics. This approach also offers a formal notion of the energy of activity within a system, and the energy of activity shared between systems. We observe that within- and between-system energies cleanly separate cognitive systems into distinct categories, optimized for differential contributions to integrated versus segregated function. These results support the notion that energetic and structural constraints circumscribe brain dynamics, offering insights into the roles that cognitive systems play in driving whole-brain activation patterns.
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http://dx.doi.org/10.1038/s41598-018-20123-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5802783PMC
February 2018

Detecting hierarchical genome folding with network modularity.

Nat Methods 2018 02 15;15(2):119-122. Epub 2018 Jan 15.

Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Mammalian genomes are folded in a hierarchy of compartments, topologically associating domains (TADs), subTADs and looping interactions. Here, we describe 3DNetMod, a graph theory-based method for sensitive and accurate detection of chromatin domains across length scales in Hi-C data. We identify nested, partially overlapping TADs and subTADs genome wide by optimizing network modularity and varying a single resolution parameter. 3DNetMod can be applied broadly to understand genome reconfiguration in development and disease.
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http://dx.doi.org/10.1038/nmeth.4560DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029251PMC
February 2018

Developmental increases in white matter network controllability support a growing diversity of brain dynamics.

Nat Commun 2017 11 1;8(1):1252. Epub 2017 Nov 1.

Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.

As the human brain develops, it increasingly supports coordinated control of neural activity. The mechanism by which white matter evolves to support this coordination is not well understood. Here we use a network representation of diffusion imaging data from 882 youth ages 8-22 to show that white matter connectivity becomes increasingly optimized for a diverse range of predicted dynamics in development. Notably, stable controllers in subcortical areas are negatively related to cognitive performance. Investigating structural mechanisms supporting these changes, we simulate network evolution with a set of growth rules. We find that all brain networks are structured in a manner highly optimized for network control, with distinct control mechanisms predicted in child vs. older youth. We demonstrate that our results cannot be explained by changes in network modularity. This work reveals a possible mechanism of human brain development that preferentially optimizes dynamic network control over static network architecture.
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http://dx.doi.org/10.1038/s41467-017-01254-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5665937PMC
November 2017

Supplementation with the Methyl Donor Betaine Prevents Congenital Defects Induced by Prenatal Alcohol Exposure.

Alcohol Clin Exp Res 2017 Nov 11;41(11):1917-1927. Epub 2017 Oct 11.

Department of Pediatrics, Congenital Heart Collaborative, UH Rainbow Babies and Children's Hospital, School of Medicine, Case Western Reserve University, Cleveland, Ohio.

Background: Despite decades of public education about dire consequences of prenatal alcohol exposure (PAE), drinking alcohol during pregnancy remains prevalent. As high as 40% of live-born infants exposed to alcohol during gestation and diagnosed with fetal alcohol syndrome have congenital heart defects that can be life-threatening. In animal models, the methyl donor betaine, found in foods such as wheat bran, quinoa, beets, and spinach, ameliorated neurobehavioral deficits associated with PAE, but effects on heart development are unknown.

Methods: Previously, we modeled a binge drinking episode during the first trimester in avian embryos. Here, we investigated whether betaine could prevent adverse effects of alcohol on heart development. Embryos exposed to ethanol (EtOH) with and without an optimal dose of betaine (5 μM) were analyzed at late developmental stages. Cardiac morphology parameters were rapidly analyzed and quantified using optical coherence tomography. DNA methylation at early stages was detected by immunofluorescent staining for 5-methylcytosine in sections of embryos treated with EtOH or cotreated with betaine.

Results: Compared to EtOH-exposed embryos, betaine-supplemented embryos had higher late-stage survival rates and fewer gross head and body defects than seen after alcohol exposure alone. Betaine also reduced the incidence of late-stage cardiac defects such as absent vessels, abnormal atrioventricular (AV) valves, and hypertrophic ventricles. Furthermore, betaine cotreatment brought measurements of great vessel diameters, interventricular septum thickness, and AV leaflet volumes in betaine-supplemented embryos close to control values. Early-stage 5-methycytosine staining revealed that DNA methylation levels were reduced by EtOH exposure and normalized by co-administration with betaine.

Conclusions: This is the first study demonstrating efficacy of the methyl donor betaine in alleviating cardiac defects associated with PAE. These findings highlight the therapeutic potential of low-concentration betaine doses in mitigating PAE-induced birth defects and have implications for prenatal nutrition policies, especially for women who may not be responsive to folate supplementation.
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http://dx.doi.org/10.1111/acer.13495DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5659922PMC
November 2017

Complex decorrelation averaging in optical coherence tomography: a way to reduce the effect of multiple scattering and improve image contrast in a dynamic scattering medium.

Opt Lett 2017 Jul;42(14):2738-2741

We demonstrate that complex decorrelation averaging can reduce the effect of multiple scattering and improve optical coherence tomography (OCT) imaging contrast. Complex decorrelation averaging calculates the product of an A-scan and the complex conjugate of a subsequent A-scan. The resultant signal is the product of the amplitudes and the phase difference. All these resulting complex signals at a particular location are then averaged. We take advantage of the fact that complex averaging, in contrast to conventional magnitude averaging, is sensitive to phase decorrelation. Sample motion that increases signal phase variance results in lower signal magnitude after complex averaging. Such motion preferentially results in a faster decorrelation of the multiple scattering signal when compared to the single scattering signal with each scattering event spreading the phase. This indicates that we may reduce multiple scattering by implementing complex decorrelation averaging to preferentially reduce the magnitude of the multiply scattered light signal in OCT images. By adjusting the time between phase-differenced A-scans, one can regulate the amount of measured decorrelation. We have performed experiments on liquid phantoms that give experimental evidence for this hypothesis. A substantial improvement in OCT image contrast using complex decorrelation averaging is demonstrated.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5997261PMC
http://dx.doi.org/10.1364/OL.42.002738DOI Listing
July 2017

Embryonic aortic arch hemodynamics are a functional biomarker for ethanol-induced congenital heart defects [Invited].

Biomed Opt Express 2017 Mar 24;8(3):1823-1837. Epub 2017 Feb 24.

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106, USA.

The great arteries develop from symmetrical aortic arch arteries which are extensively remodeled. These events are vulnerable to perturbations. Hemodynamic forces have a significant role in this remodeling. In this study, optical coherence tomography (OCT) visualized live avian embryos for staging and measuring pharyngeal arch morphology. Measurements acquired with our orientation-independent, dual-angle Doppler OCT technique revealed that ethanol exposure leads to higher absolute blood flow, shear stress, and retrograde flow. Ethanol-exposed embryos had smaller cardiac neural crest (CNC) derived pharyngeal arch mesenchyme and fewer migrating CNC-derived cells. These differences in forces and CNC cell numbers could explain the abnormal aortic arch remodeling.
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http://dx.doi.org/10.1364/BOE.8.001823DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5480583PMC
March 2017

Selective inhibition of small-diameter axons using infrared light.

Sci Rep 2017 06 12;7(1):3275. Epub 2017 Jun 12.

Department of Pediatrics, Case Western Reserve University, Cleveland, OH, USA.

Novel clinical treatments to target peripheral nerves are being developed which primarily use electrical current. Recently, infrared (IR) light was shown to inhibit peripheral nerves with high spatial and temporal specificity. Here, for the first time, we demonstrate that IR can selectively and reversibly inhibit small-diameter axons at lower radiant exposures than large-diameter axons. We provide a mathematical rationale, and then demonstrate it experimentally in individual axons of identified neurons in the marine mollusk Aplysia californica, and in axons within the vagus nerve of a mammal, the musk shrew Suncus murinus. The ability to selectively, rapidly, and reversibly control small-diameter sensory fibers may have many applications, both for the analysis of physiology, and for treating diseases of the peripheral nervous system, such as chronic nausea, vomiting, pain, and hypertension. Moreover, the mathematical analysis of how IR affects the nerve could apply to other techniques for controlling peripheral nerve signaling.
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http://dx.doi.org/10.1038/s41598-017-03374-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5468240PMC
June 2017

The energy landscape underpinning module dynamics in the human brain connectome.

Neuroimage 2017 08 7;157:364-380. Epub 2017 Jun 7.

Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address:

Human brain dynamics can be viewed through the lens of statistical mechanics, where neurophysiological activity evolves around and between local attractors representing mental states. Many physically-inspired models of these dynamics define brain states based on instantaneous measurements of regional activity. Yet, recent work in network neuroscience has provided evidence that the brain might also be well-characterized by time-varying states composed of locally coherent activity or functional modules. We study this network-based notion of brain state to understand how functional modules dynamically interact with one another to perform cognitive functions. We estimate the functional relationships between regions of interest (ROIs) by fitting a pair-wise maximum entropy model to each ROI's pattern of allegiance to functional modules. This process uses an information theoretic notion of energy (as opposed to a metabolic one) to produce an energy landscape in which local minima represent attractor states characterized by specific patterns of modular structure. The clustering of local minima highlights three classes of ROIs with similar patterns of allegiance to community states. Visual, attention, sensorimotor, and subcortical ROIs are well-characterized by a single functional community. The remaining ROIs affiliate with a putative executive control community or a putative default mode and salience community. We simulate the brain's dynamic transitions between these community states using a random walk process. We observe that simulated transition probabilities between basins are statistically consistent with empirically observed transitions in resting state fMRI data. These results offer a view of the brain as a dynamical system that transitions between basins of attraction characterized by coherent activity in groups of brain regions, and that the strength of these attractors depends on the ongoing cognitive computations.
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http://dx.doi.org/10.1016/j.neuroimage.2017.05.067DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5600845PMC
August 2017

Functional hypergraph uncovers novel covariant structures over neurodevelopment.

Hum Brain Mapp 2017 08 11;38(8):3823-3835. Epub 2017 May 11.

Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania.

Brain development during adolescence is marked by substantial changes in brain structure and function, leading to a stable network topology in adulthood. However, most prior work has examined the data through the lens of brain areas connected to one another in large-scale functional networks. Here, we apply a recently developed hypergraph approach that treats network connections (edges) rather than brain regions as the unit of interest, allowing us to describe functional network topology from a fundamentally different perspective. Capitalizing on a sample of 780 youth imaged as part of the Philadelphia Neurodevelopmental Cohort, this hypergraph representation of resting-state functional MRI data reveals three distinct classes of subnetworks (hyperedges): clusters, bridges, and stars, which respectively represent homogeneously connected, bipartite, and focal architectures. Cluster hyperedges show a strong resemblance to previously-described functional modules of the brain including somatomotor, visual, default mode, and salience systems. In contrast, star hyperedges represent highly localized subnetworks centered on a small set of regions, and are distributed across the entire cortex. Finally, bridge hyperedges link clusters and stars in a core-periphery organization. Notably, developmental changes within hyperedges are ordered in a similar core-periphery fashion, with the greatest developmental effects occurring in networked hyperedges within the functional core. Taken together, these results reveal a novel decomposition of the network organization of human brain, and further provide a new perspective on the role of local structures that emerge across neurodevelopment. Hum Brain Mapp 38:3823-3835, 2017. © 2017 Wiley Periodicals, Inc.
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http://dx.doi.org/10.1002/hbm.23631DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323637PMC
August 2017

Autaptic Connections Shift Network Excitability and Bursting.

Sci Rep 2017 03 7;7:44006. Epub 2017 Mar 7.

Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA.

We examine the role of structural autapses, when a neuron synapses onto itself, in driving network-wide bursting behavior. Using a simple spiking model of neuronal activity, we study how autaptic connections affect activity patterns, and evaluate if controllability significantly affects changes in bursting from autaptic connections. Adding more autaptic connections to excitatory neurons increased the number of spiking events and the number of network-wide bursts. We observed excitatory synapses contributed more to bursting behavior than inhibitory synapses. We evaluated if neurons with high average controllability, predicted to push the network into easily achievable states, affected bursting behavior differently than neurons with high modal controllability, thought to influence the network into difficult to reach states. Results show autaptic connections to excitatory neurons with high average controllability led to higher burst frequencies than adding the same number of self-looping connections to neurons with high modal controllability. The number of autapses required to induce bursting was lowered by adding autapses to high degree excitatory neurons. These results suggest a role of autaptic connections in controlling network-wide bursts in diverse cortical and subcortical regions of mammalian brain. Moreover, they open up new avenues for the study of dynamic neurophysiological correlates of structural controllability.
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http://dx.doi.org/10.1038/srep44006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5339801PMC
March 2017

Increased regurgitant flow causes endocardial cushion defects in an avian embryonic model of congenital heart disease.

Congenit Heart Dis 2017 May 17;12(3):322-331. Epub 2017 Feb 17.

Department of Pediatric Cardiology, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.

Background: The relationship between changes in endocardial cushion and resultant congenital heart diseases (CHD) has yet to be established. It has been shown that increased regurgitant flow early in embryonic heart development leads to endocardial cushion defects, but it remains unclear how abnormal endocardial cushions during the looping stages might affect the fully septated heart. The goal of this study was to reproducibly alter blood flow in vivo and then quantify the resultant effects on morphology of endocardial cushions in the looping heart and on CHDs in the septated heart.

Methods: Optical pacing was applied to create regurgitant flow in embryonic hearts, and optical coherence tomography (OCT) was utilized to quantify regurgitation and morphology. Embryonic quail hearts were optically paced at 3 Hz (180 bpm, well above intrinsic rate 60-110 bpm) at stage 13 of development (3-4 weeks human) for 5 min. Pacing fatigued the heart and led to at least 1 h of increased regurgitant flow. Resultant morphological changes were quantified with OCT imaging at stage 19 (cardiac looping-4-5 weeks human) or stage 35 (4 chambered heart-8 weeks human).

Results: All paced embryos imaged at stage 19 displayed structural changes in cardiac cushions. The amount of regurgitant flow immediately after pacing was inversely correlated with cardiac cushion size 24-h post pacing (P value < .01). The embryos with the most regurgitant flow and smallest cushions after pacing had a decreased survival rate at 8 days (P < .05), indicating that those most severe endocardial cushion defects were lethal. Of the embryos that survived to stage 35, 17/18 exhibited CHDs including valve defects, ventricular septal defects, hypoplastic ventricles, and common AV canal.

Conclusion: The data illustrate a strong inverse relationship in which regurgitant flow precedes abnormal and smaller cardiac cushions, resulting in the development of CHDs.
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http://dx.doi.org/10.1111/chd.12443DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5467887PMC
May 2017

Optimal trajectories of brain state transitions.

Neuroimage 2017 03 11;148:305-317. Epub 2017 Jan 11.

Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address:

The complexity of neural dynamics stems in part from the complexity of the underlying anatomy. Yet how white matter structure constrains how the brain transitions from one cognitive state to another remains unknown. Here we address this question by drawing on recent advances in network control theory to model the underlying mechanisms of brain state transitions as elicited by the collective control of region sets. We find that previously identified attention and executive control systems are poised to affect a broad array of state transitions that cannot easily be classified by traditional engineering-based notions of control. This theoretical versatility comes with a vulnerability to injury. In patients with mild traumatic brain injury, we observe a loss of specificity in putative control processes, suggesting greater susceptibility to neurophysiological noise. These results offer fundamental insights into the mechanisms driving brain state transitions in healthy cognition and their alteration following injury.
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http://dx.doi.org/10.1016/j.neuroimage.2017.01.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5489344PMC
March 2017

Volumetric optical mapping in early embryonic hearts using light-sheet microscopy.

Biomed Opt Express 2016 Dec 15;7(12):5120-5128. Epub 2016 Nov 15.

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106, USA.

Optical mapping (OM) of electrical activity using voltage-sensitive fluorescent dyes is a powerful tool for the investigation of embryonic cardiac electrophysiology. However, because conventional OM integrates the signal in depth and projects it to a two-dimensional plane, information acquired is incomplete and dependent upon the orientation of the sample. This complicates interpretation of data, especially when comparing one heart to another. To overcome this limitation, we present volumetric OM using light-sheet microscopy, which enables high-speed capture of optically sectioned slices. Voltage-sensitive fluorescence images from multiple planes across entire early embryonic quail hearts were acquired, and complete, orientation-independent, four-dimensional maps of transmembrane potential are demonstrated. Volumetric OM data were collected while using optical pacing to control the heart rate, paving the way for physiological measurements and precise manipulation of the heartbeat in the future.
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http://dx.doi.org/10.1364/BOE.7.005120DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5175556PMC
December 2016