Biology subjects

Fang, Q.

Publications and source records attributed to Fang, Q..

At least 55 records · Page 3Linked to original sources

bioRxiv2022

Signal and Measurement Considerations for Human Translation of Diffuse in vivo Flow Cytometry

SignificanceDiffuse in vivo flow cytometry (DiFC) is an emerging technology for fluorescence detection of rare circulating cells directly in large deep-seated blood vessels in mice. Because DiFC uses highly scattered light, in principle it could be translated to human use. However, an open question is whether fluorescent signals from single cells would be detectable in human-scale anatomies. AimSuitable blood vessels in a human wrist or forearm are at a depth of approximately 2-4 mm. The aim of this work was to study the impact of DiFC instrument geometry and wavelength on the detected DiFC signal and on the maximum depth of detection of a moving cell. ApproachWe used Monte Carlo simulations to compute Jacobian (sensitivity) matrices for a range of source-detector separations and tissue optical properties over the visible and near infrared (NIR) spectrum. We performed experimental measurements with three available versions of DiFC (488 nm, 640 nm, and 780 nm), fluorescent microspheres, and tissue mimicking optical flow phantoms. We used both computational and experimental data to estimate the maximum depth of detection at each combination of settings. Results and ConclusionsFor the DiFC detection problem, our analysis showed that for deep-seated blood vessels, the maximum sensitivity was obtained with NIR light (780 nm) and 3 mm source-and-detector separation. These results suggest that - in combination with a suitable molecularly targeted fluorescent probes - circulating cells and nanosensors could in principle be detectable in circulation in humans.

bioengineering↗

bioRxiv2022

Framework for Denoising Monte Carlo Photon Transport Simulations Using Deep Learning

SignificanceThe Monte Carlo (MC) method is widely used as the gold-standard for modeling light propagation inside turbid media like human tissues, but combating its inherent stochastic noise requires one to simulate large number photons, resulting in high computational burdens. AimWe aim to develop an effective image denoising technique using deep learning (DL) to dramatically improve low-photon MC simulation result quality, equivalently bringing further acceleration to the MC method. ApproachWe have developed a cascade-network combining DnCNN with UNet, in the meantime, extended a range of established image denoising neural-network architectures, including DnCNN, UNet, DRUNet, and ResMCNet, in handling three-dimensional (3-D) MC data and compared their performances against model-based denoising algorithms. We have also developed a simple yet effective approach to create synthetic datasets that can be used to train DL based MC denoisers. ResultsOverall, DL based image denoising algorithms exhibit significantly higher image quality improvements over traditional model-based denoising algorithms. Among the tested DL denoisiers, our Cascade network yields a 14 - 19 dB improvement in signal-noise ratio (SNR), which is equivalent to simulating 25 x to 78 x more photons. Other DL-based methods yielded similar results, with our method performing noticeably better with low-photon inputs, and ResMCNet along with DRUNet performing better with high-photon inputs. Our Cascade network achieved the highest quality when denoising complex domains, including brain and mouse atlases. ConclusionIncorporating state-of-the-art DL denoising techniques can equivalently reduce the computation time of MC simulations by one to two orders of magnitude. Our open-source MC denoising codes and data can be freely accessed at http://mcx.space/.

biophysics↗

bioRxiv2022

Graphics processing unit-accelerated Monte Carlo simulation of polarized light in complex three-dimensional media

SignificanceMonte Carlo (MC) methods have been applied for studying interactions between polarized light and biological tissues, but most existing MC codes supporting polarization modeling can only simulate homogeneous or multi-layered domains, resulting in approximations when handling realistic tissue structures. AimOver the past decade, the speed of MC simulations has seen dramatic improvement with massively-parallel computing techniques. Developing hardware-accelerated MC simulation algorithms that can accurately model polarized light inside 3-D heterogeneous tissues can greatly expand the utility of polarization in biophotonics applications. ApproachHere we report a highly efficient polarized MC algorithm capable of modeling arbitrarily complex media defined over a voxelated domain. Each voxel of the domain can be associated with spherical scatters of various radii and densities. The Stokes vector of each simulated photon packet is updated through photon propagation, creating spatially resolved polarization measurements over the detectors or domain surface. ResultsWe have implemented this algorithm in our widely disseminated MC simulator, Monte Carlo eXtreme (MCX). It is validated by comparing with a reference CPU-based simulator in both homogeneous and layered domains, showing excellent agreement and a 931-fold speedup. ConclusionThe polarization-enabled MCX (pMCX) offers biophotonics community an efficient tool to explore polarized light in bio-tissues, and is freely available at http://mcx.space/.

biophysics↗

bioRxiv2022

BlenderPhotonics - a versatile environment for 3-D complex bio-tissue modeling and light transport simulations based on Blender

SignificanceRapid advances in biophotonics techniques require quantitative, model-based computational approaches to obtain functional and structural information from increasingly complex and multi-scaled anatomies. The lack of efficient tools to accurately model tissue structures and subsequently perform quantitative multi-physics modeling greatly impedes the clinical translation of these modalities. AimWhile the mesh-based Monte Carlo (MMC) method expands our capabilities in simulating complex tissues by using tetrahedral meshes, the generation of such domains often requires specialized meshing tools such as Iso2Mesh. Creating a simplified and intuitive interface for tissue anatomical modeling and optical simulations is essential towards making these advanced modeling techniques broadly accessible to the user community. ApproachWe responded to the above challenge by combining the powerful, open-source 3-D modeling software, Blender, with state-of-the-art 3-D mesh generation and MC simulation tools, utilizing the interactive graphical user interface (GUI) in Blender as the front-end to allow users to create complex tissue mesh models, and subsequently launch MMC light simulations. ResultsHere we present a tutorial to our newly developed Python-based Blender add-on - BlenderPhotonics - to interface with Iso2Mesh and MMC, allowing users to create, configure and refine complex simulation domains and run hardware-accelerated 3-D light simulations with only a few clicks. We provide a comprehensive introduction to this new tool and walk readers through 5 examples, ranging from simple shapes to sophisticated realistic tissue models. ConclusionBlenderPhotonics is user-friendly and open-source, leveraging the vastly rich ecosystem of Blender. It wraps advanced modeling capabilities within an easy-to-use and interactive interface. The latest software can be downloaded at http://mcx.space/bp.

bioengineering↗

bioRxiv2021

Involvement of sensory neuron-TRPV4 in acute and chronic itch behaviors

Itch, particularly chronic itch, negatively impacts patients physical, social, and psychological well-being, leading to deterioration in their quality of life. Limited understanding of itch mechanisms hinders the development of effective antipruritic treatments.TRPV4, a multimodally activated nonselective cation channel, has been detected in sensory neurons of dorsal root and trigeminal ganglion (DRG, TG) and skin cells (e.g. keratinocytes, mast cells, and macrophages). Recent evidence from experimental and clinical relevant studies has implicated that TRPV4 in skin cells plays an important role in both acute and chronic itch. In contrast, little is known whether TRPV4 in sensory neurons directly contributes to scratching behaviors. Here we used sensory neuron-Trpv4 conditional knockout (cKO) mice to address this question. Our results showed that TRPV4 in sensory neurons contributes to scratching behavior evoked by histaminergic (histamine and 48/80) and partial histaminergic (5-HT), but not non-histaminergic (SLIGRL and CQ) pruritogens. Moreover, we observed that TRPV4 in sensory neurons is required for dry skin, but not allergic contact dermatitis, -associated chronic itch. These findings suggest that neuronal-TRPV4 might be specific for some forms of acute and chronic itch.

neuroscience↗

bioRxiv2021

MCX Cloud - a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing

SignificanceDespite the ample progress made towards faster and more accurate Monte Carlo (MC) simulation tools over the past decade, the limited usability and accessibility of these advanced modeling tools remain key barriers towards widespread use among the broad user community. AimAn open-source, high-performance, web-based MC simulator that builds upon modern cloud computing architectures is highly desirable to deliver state-of-the-art MC simulations and hardware acceleration to general users without the need for special hardware installation and optimization. ApproachWe have developed a configuration-free, in-browser 3-D MC simulation platform - MCX Cloud - built upon an array of robust and modern technologies, including a Docker Swarm-based cloud-computing backend and a web-based graphical user interface (GUI) that supports in-browser 3-D visualization, asynchronous data communication, and automatic data validation via JavaScript Object Notation (JSON) schemas. ResultsThe front-end of the MCX Cloud platform offers an intuitive simulation design, fast 3-D data rendering, and convenient simulation sharing. The Docker Swarm container orchestration backend is highly scalable and can support high-demand GPU MC simulations using Monte Carlo eXtreme (MCX) over a dynamically expandable virtual cluster. ConclusionMCX Cloud makes fast, scalable, and feature-rich MC simulations readily available to all biophotonics researchers without overhead. It is fully open-source and can be freely accessed at http://mcx.space/cloud.

biophysics↗

bioRxiv2021

Designing, optimizing, and assessing modular functional near-infrared brain imaging probes using an automated software workflow

SignificanceThe exponential growth of research utilizing functional near-infrared spectroscopy (fNIRS) systems has led to the emergence of modular fNIRS systems composed of repeating optical source/detector modules. Compared to conventional fNIRS systems, modular fNIRS systems are more compact and flexible, making wearable and long-time monitoring possible. However, the large number of design parameters makes designing a modular probe a daunting task. AimWe aim to create a systematic software platform to facilitate the design, characterization, and comparison of modular fNIRS probes. ApproachOur algorithm automatically tessellates any region-of-interest using user-specified module design parameters and outputs performance metrics such as spatial channel distributions, average brain sensitivity, and sampling rate estimates of the resulting probe. Automated algorithms for spatial coverage, orientation, and routing of repeated modules are also developed. ResultsWe developed a software platform to help explore a wide range of modular probe features and quantify their performances. We compare full-head probes using three different module shapes and highlight the trade-offs resulting from various module settings. Additionally, we show that one can apply this workflow to improve existing modular probes without needing to re-design or re-manufacture them. ConclusionOur flexible modular probe design platform shows promise in optimizing existing modular probes and investigating future modular designs.

bioengineering↗

bioRxiv2021

Temporal dynamics of base excision / single-strand break repair protein complex assembly and disassembly are modulated by the PARP1/NAD+/SIRT6 axis

Assembly and disassembly of DNA repair protein complexes at sites of DNA damage is essential to maintain genomic integrity. We investigated factors coordinating assembly of the base excision repair (BER) proteins, DNA polymerase {beta} (Pol{beta}) and XRCC1, to DNA lesion sites, identifying a new role for Pol{beta} in regulating XRCC1 disassembly from DNA repair complexes and conversely, demonstrating Pol{beta}s dependence on XRCC1 for complex assembly. RealPAR, a genetically-encoded probe for live cell imaging of poly(ADP-ribose) (PAR), reveals that Pol{beta} and XRCC1 require PAR for repair complex assembly and PAR degradation for disassembly. We find that BER complex assembly is further modulated by attenuation / augmentation of NAD+ biosynthesis. Finally, SIRT6 does not regulate PARP1 activation but impairs XRCC1 recruitment, leading to diminished Pol{beta} abundance at sites of DNA damage. These findings highlight coordinated yet independent roles for both PARP1 and SIRT6 and their regulation by NAD+ bioavailability to facilitate BER.

cancer biology↗

bioRxiv2021

Structural basis of substrate recognition and translocation by human ABCA4

Human ATP-binding cassette (ABC) subfamily A (ABCA) transporters mediate the transport of various lipid compounds across the membrane. Mutations in human ABCA transporters have been described to cause severe hereditary disorders associated with impaired lipid transport. However, little is known about the mechanistic details of substrate recognition and translocation by ABCA transporters. Here, we present three cryo-EM structures of human ABCA4, a retinal-specific ABCA transporter, in distinct functional states at resolutions of 3.3-3.4 [A]. In the nucleotide-free state, the two transmembrane domains (TMDs) exhibited a lateral-opening conformation, allowing the lateral entry of substrate from the lipid bilayer. N-retinylidene-phosphatidylethanolamine (NRPE), the physiological lipid substrate of ABCA4, is sandwiched between the two TMDs in the luminal leaflet and is further stabilized by an extended loop from extracellular domain 1. In the ATP-bound state, the two TMDs displayed an unprecedented closed conformation, which precludes the substrate binding. Our study provides a molecular basis to understand the mechanism of ABCA4-mediated NRPE recognition and translocation, and suggests a common lateral access and extrusion mechanism for ABCA-mediated lipid transport.

biochemistry↗

bioRxiv2021

Structure of the human SAGA coactivator complex

Human SAGA is an essential co-activator complex that regulates gene expression by interacting with enhancer-bound activators, recruiting transcriptional machinery, and modifying chromatin near promoters. Subunit variations and the metazoan-specific requirement of SAGA in development hinted at unique structural features of the human complex. Our 2.9 [A] structure of human SAGA reveals intertwined functional modules flexibly connected to a core that distinctively integrates mammalian paralogs, incorporates U2 splicing subunits, and features a unique interface between the core and the activator-binding TRRAP. Our structure sheds light on unique roles and regulation of human coactivators with implications for transcription and splicing that have relevance in genetic diseases and cancer.

biophysics↗

bioRxiv2020

Light transport modeling in highly complex tissues using implicit mesh-based Monte Carlo algorithm

The mesh-based Monte Carlo (MMC) technique has grown tremendously since its initial publication nearly a decade ago. It is now recognized as one of the most accurate Monte Carlo (MC) methods, providing accurate reference solutions for the development of novel biophotonics techniques. In this work, we aim to further advance MMC to address a major challenge in biophotonics modeling, i.e. light transport within highly complex tissues, such as dense microvascular networks, porous media and multi-scale tissue structures. Although the current MMC framework is capable of simulating light propagation in such media given its generality, the run-time and memory usage grow rapidly with increasing media complexity and size. This greatly limits our capability to explore complex and multi-scale tissue structures. Here, we propose a highly efficient implicit mesh-based Monte Carlo (iMMC) method that incorporates both mesh- and shape-based tissue representations to create highly complex yet memory efficient light transport simulations. We demonstrate that iMMC is capable of providing accurate solutions for dense vessel networks and porous tissues while reducing memory usage by greater than a hundred- or even thousand-fold. In a sample network of microvasculature, the reduced shape complexity results in nearly 3x speed acceleration. The proposed algorithm is now available in our open-source MMC software at http://mcx.space/#mmc.

biophysics↗

bioRxiv2020

A hybrid mesh and voxel based Monte Carlo algorithm for accurate and efficient photon transport modeling in complex bio-tissues

Over the past decade, an increasing body of evidence has suggested that threedimensional (3-D) Monte Carlo (MC) light transport simulations are affected by the inherent limitations and errors of voxel-based domain boundaries. In this work, we specifically address this challenge using a hybrid MC algorithm, namely split-voxel MC or SVMC, that combines both mesh and voxel domain information to greatly improve MC simulation accuracy while remaining highly flexible and efficient in parallel hardware, such as graphics processing units (GPU). We achieve this by applying a marching-cubes algorithm to a pre-segmented domain to extract and encode sub-voxel information of curved surfaces, which is then used to inform ray-tracing computation within boundary voxels. This preservation of curved boundaries in a voxel data structure demonstrates significantly improved accuracy in several benchmarks, including a human brain atlas. The accuracy of the SVMC algorithm is comparable to that of mesh-based MC (MMC), but runs 2x-6x faster and requires only a lightweight preprocessing step. The proposed algorithm has been implemented in our open-source software and is freely available at http://mcx.space.

biophysics↗

bioRxiv2020

Chronic morphine administration differentially modulates viral reservoirs in SIVmac251 infected rhesus macaque model

HIV persists in cellular reservoirs despite effective anti-retroviral therapy with rebound of viremia upon therapy interruption. Opioids modulate the immune system and suppress antiviral gene responses, which significantly impact people living with HIV (PLWH). However, the effects of opioids on viral reservoir remains elusive. Herein, we describe a morphine dependent SIVmac251 infected Rhesus macaque (RM) model to study the impact of opioids on HIV reservoirs. RMs were ramped up with morphine (n=10) or saline (n=9) for two weeks to a final dosage of 5mg/kg administered twice daily, which was maintained for seven weeks, and then infected with SIVmac251. Combined anti-retroviral therapy (cART) was initiated in approximately half the animals in each group five weeks post-infection and morphine/saline administration continued for 10 months. Among drug naive macaques, there were no differences in plasma/CSF viral load nor in cell-associated DNA/RNA loads. However, within the cART-suppressed macaques, there was a reduction in cell-associated DNA load, intact proviral DNA copy numbers, and inducible SIV reservoir in both peripheral blood and lymph nodes (LNs) of morphine-administered RMs compared to saline controls. Further, PBMCs of morphine administered RMs, a reduction in Th1 polarized CD4+ T cells and in LNs there was a reduction in the total Tfh and Th1 like Tfh cells were observed, indicating probably have impact on reduction of viral reservoirs. In distinction to PBMC and LNs, within the CNS size of latent SIV reservoirs was higher in the CD11b+ microglia/macrophages of morphine-dependent RMs. These data suggest that morphine plays a role in modulating SIV reservoirs, reduces the CD4+ T-cell reservoir in both peripheral blood and LNs, and increases microglia/macrophage reservoirs in CNS. These findings will aid in understanding of molecular mechanism(s) of opioid-mediated differential modulation of viral reservoirs and evaluation of therapeutic strategies to reduce/eliminate HIV reservoirs in opioid-dependent PLWH. Author summaryOpioids are commonly used as well as abused by HIV infected individuals, are known to suppress immune responses. However, their effects on modulating viral reservoir dynamics is not known. Here we developed a morphine dependent SIVmac251 infected rhesus macaque (RM) model to study the impact of opioids on HIV reservoirs and immune cells. We found that there was no difference in viral loads or cell-associated DNA/RNA loads among morphine dependent vs. saline treated control macaques. On the other hand, when macaques were treated with cART, there was a reduction in SIV reservoirs both in periphery and lymphoid tissues in morphine administered RMs, and the size of latent SIV reservoir was higher in the CNS CD11b+ microglia/macrophages as compared to control macaques. Therefore, these new data form macaque models suggest that PLWH who suffering from opioid use disorders have higher reservoirs in CNS as compared to lymphoid system. Thus, through understanding these reservoirs among PLWH who uses opioids are critical for better designing HIV cure strategies.

molecular biology↗

bioRxiv2020

A high-quality de novo genome assembly from a single parasitoid wasp

Sequencing and assembling a genome with a single individual have several advantages, such as lower heterozygosity and easier sample preparation. However, the amount of genomic DNA of some small sized organisms might not meet the standard DNA input requirement for current sequencing pipelines. Although few studies sequenced a single small insect with about 100 ng DNA as input, it may still be challenging for many small organisms to obtain such amount of DNA from a single individual. Here, we use 20 ng DNA as input, and present a high-quality genome assembly for a single haploid male parasitoid wasp (Habrobracon hebetor) using Nanopore and Illumina. Because of the low input DNA, a whole genome amplification (WGA) method is used before sequencing. The assembled genome size is 131.6 Mb with a contig N50 of 1.63 Mb. A total of 99% Benchmarking Universal Single-Copy Orthologs are detected, suggesting the high level of completeness of the genome assembly. Genome comparison between H. hebetor and its relative Bracon brevicornis shows a high-level genome synteny, indicating the genome of H. hebetor is highly accurate and contiguous. Our study provides an example for de novo assembling a genome from ultra-low input DNA, and will be used for sequencing projects of small sized species and rare samples, haploid genomics as well as population genetics of small sized species.

genomics↗

bioRxiv2020

The Nucleocapsid Protein of SARS-CoV-2 Abolished Pluripotency in Human Induced Pluripotent Stem Cells

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is raging across the world, leading to a global mortality rate of 3.4% (estimated by World Health Organization in March 2020). As a potential vaccine and therapeutic target, the nucleocapsid protein of SARS-CoV-2 (nCoVN) functions in packaging the viral genome and viral self-assembly. To investigate the biological effects of nCoVN to human stem cells, genetically engineered human induced pluripotent stem cells (iPSC) expressing nCoVN (iPSC-nCoVN) were generated by lentiviral expression systems, in which the expression of nCoVN could be induced by the doxycycline. The proliferation rate of iPSC-nCoVN was decreased. Unexpectedly, the morphology of iPSC started to change after nCoVN expression for 7 days. The pluripotency marker TRA-1-81 were not detectable in iPSC-nCoVN after a four-day induction. Meanwhile, iPSC-nCoVN lost the ability for differentiation into cardiomyocytes with a routine differentiation protocol. The RNA-seq data of iPSC-nCoVN (induction for 30 days) and immunofluorescence assays illustrated that iPSC-nCoVN were turning to fibroblast-like cells. Our data suggested that nCoVN disrupted the pluripotent properties of iPSC and turned them into other types of cells, which provided a new insight to the pathogenic mechanism of SARS-CoV-2.

cell biology↗

bioRxiv2020

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 3-D complex domains. We have implemented this accelerated algorithm, named "photon sharing", in our open-source MC simulators, reporting 13.6x and 5.5x speedups in mesh- and voxel-based MC benchmarks, respectively. In addition, the proposed algorithm is readily used for accelerating the solving of inverse problems in spatially-modulated imaging systems by building Jaco-bians of all illumination-detection pattern pairs concurrently, resulting in a 12.4-fold speed improvement. https://doi.org/10.1101/2020.02.16.951590

biophysics↗

bioRxiv2020

Improving model-based fNIRS analysis using mesh-based anatomical and light-transport models

SignificanceFunctional near-infrared spectroscopy (fNIRS) has become an important research tool in studying human brains. Accurate quantification of brain activities via fNIRS relies upon solving computational models that simulate the transport of photons through complex anatomy. AimWe aim to highlight the importance of accurate anatomical modeling in the context of fNIRS, and propose a robust method for creating high-quality brain/full-head tetrahedral mesh models for neuroimaging analysis. ApproachWe have developed a surface-based brain meshing pipeline that can produce significantly better brain mesh models compared to conventional meshing techniques. It can convert segmented volumetric brain scans into multi-layered surfaces and tetrahedral mesh models, with typical processing times of only a few minutes and broad utilities, such as in Monte Carlo or finite-element based photon simulations for fNIRS studies. ResultsA variety of high quality brain mesh models have been successfully generated by processing publicly available brain atlases. In addition, we compare 3 brain anatomical models - the voxel-based brain segmentation, tetrahedral brain mesh and layered-slab brain model, and demonstrate noticeable discrepancies in brain partial-pathlengths when using approximated brain anatomies, ranging between -1.5-23% with the voxelated brain and 36-166% with the layered-slab brain. ConclusionThe generation and utility of high-quality brain meshes can lead to more accurate brain quantification in fNIRS studies. Our open-source meshing toolboxes "Brain2Mesh" and "Iso2Mesh" are freely available at http://mcx.space/brain2mesh.

neuroscience↗

bioRxiv2020

Transcranial Photobiomodulation with Near-Infrared Light from Childhood to Elderliness: Simulation of Dosimetry

SignificanceMajor depressive disorder (MDD) affects over 40 million US adults in their lifetimes. Transcranial photobiomodulation (t-PBM) has been shown to be effective in treating MDD, but the current treatment dosage does not account for anatomical head and brain changes due to aging. AimWe study effective t-PBM dosage and its variations across age groups using state-of-the-art Monte Caxrlo (MC) simulations and age-dependent brain atlases ranging between 5 to 85 years of age. ApproachAge-dependent brain models are derived from 18 MRI brain atlases. Two extracranial source positions, F3-F4 and Fp1-Fpz-Fp2 in the EEG 10-20 system, are simulated at five selected wavelengths and energy depositions at two MDD-relevant cortical regions - dorsolateral prefrontal cortex (dlPFC) and ventromedial prefrontal cortex (vmPFC) - are quantified. ResultsAn overall decrease of energy deposition was found with increasing age. A strong negative correlation between the thickness of extra-cerebral tissues (ECT) and energy deposition, suggesting that increasing ECT thickness over age is primarily responsible for reduced energy delivery. The F3-F4 position appears to be more efficient in reaching dlPFC compared to treating vmPFC via the Fp1-Fpz-Fp2 position. ConclusionQuantitative simulations revealed age-dependent light delivery across the lifespan of human brains, suggesting the needs for personalized and age-adaptive t-PBM treatment planning.

biophysics↗