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You, Q.

Publications and source records attributed to You, Q..

15 recordsLinked to original sources

Multimodal AI for Single cfDNA Profiling and Cancer Screening

Cell-free DNA (cfDNA) serves as a non-invasive biomarker for cancer detection, but conventional methods face challenges due to the ultra-low abundance of tumor-derived cfDNA (ctDNA) among normal cfDNA. Though nucleosome-bound cfDNA harbors rich epigenomic features that could enable ctDNA identification by single-molecule multi-omics cross-validation, this remains unexplored due to methodological limits. Here, we developed a cfDNA sequencing approach integrating methylation, fragmentomics, and histone modifications at the single-molecule level; together with gene semantics and epigenomic annotations, these modalities were vectorized and fused to represent each cfDNA molecule. We trained a Transformer-based model (cfAI) to profile and evaluate ctDNA likelihood at molecule, gene, and sample levels. cfAI achieved [~]10-fold enrichment of cancer-derived signals over noise and reached 72.6% sensitivity at 93.1% specificity for multi-cancer detection. Our study establishes an innovative framework that overcomes the inherent signal-to-noise limitations of conventional assays and reveals biological features at molecular resolution for cancer detection.

bioinformatics↗

Microbubble Backscattering Intensity Improves the Sensitivity of Three-dimensional (3D) Functional Ultrasound Localization Microscopy (fULM)

Functional ultrasound localization microscopy (fULM) enables brain-wide mapping of neural activity at micron-scale resolution but suffers from limited sensitivity due to sparse and noisy microbubble (MB) detections. Extending fULM into three dimensions (3D) further exacerbates these challenges because of low-frequency matrix arrays, reduced localization efficiency, and severe data sparsity. To address these limitations, we developed a statistical framework that models MB arrivals in 3D as a Poisson process accounting for localization efficiency, detection probability, and backscattered amplitude. This analysis predicts that integrating amplitude with count-based fULM improves functional sensitivity, particularly under high MB concentrations where localization saturates. Three-dimensional MB advection simulations confirmed these predictions, showing that backscattering fULM (B-fULM) maintains sensitivity at higher MB concentrations where conventional fULM fails. In rat brain experiments, B-fULM yielded stronger and more robust stimulus-evoked responses, with SNR gains of 18% in the somatosensory cortex and 61% in the thalamus, while preserving super-resolved spatial detail (33.4 m for B-fULM vs 35.7 m for fULM). These results establish B-fULM as a practical and sensitive approach for super-resolved 3D functional neuroimaging

bioengineering↗

Improved Microbubble Tracking for Super-Resolution Ultrasound Localization Microscopy using a Bi-Directional Long Short-term Memory Neural Network

Ultrasound localization microscopy (ULM) enabled high-accuracy measurements of microvessel flow beyond the resolution limit of conventional ultrasound imaging by utilizing contrast microbubbles (MBs) as point targets. Robust tracking of MBs is an essential task for fast and high-quality ULM image reconstruction. Existing MB tracking methods suffer from challenging imaging scenarios such as high-density MB distributions, fast blood flow, and complex flow dynamics. Here we present a deep learning-based MB pairing and tracking method based on a bi-directional long short-term memory neural network for ULM. The proposed method integrates multiparametric MB characteristics to facilitate more robust and accurate MB pairing and tracking. The method was validated on a simulation data set, a tissue-mimicking flow phantom, and in vivo on a mouse and rat brain.

bioengineering↗

Combined Nanodrops Imaging and Ultrasound Localization Microscopy for Detecting Intracerebral Hemorrhage

ObjectiveAdvanced imaging methods are crucial for understanding stroke mechanisms and discovering effective treatments to reduce bleeding and enhance recovery. In preclinical in vivo stroke imaging, MRI, CT, and optical imaging are commonly used to evaluate stroke outcomes in rodent models. However, MRI and CT have limited spatial resolution for rodent brains, and optical imaging is hindered by limited imaging depth of penetration. Here we introduce a novel contrast-enhanced ultrasound imaging method to overcome these challenges and characterize intracerebral hemorrhage with unique insights. MethodsWe combined microbubble (MB)-based ultrasound localization microscopy (ULM) and nanodrop (ND)- based vessel leakage imaging to achieve simultaneous microvascular imaging and hemorrhage detection. ULM maps brain-wide cerebral vasculature with high spatial resolution and identifies microvascular impairments around hemorrhagic areas. NDs are sub-micron liquid-core particles which can extravasate due to blood-brain barrier (BBB) breakdown, serving as positive contrast agents to detect hemorrhage sites. ResultsOur findings demonstrate that NDs could effectively accumulate in the hemorrhagic site and reveal the location of the bleeding areas upon activation by focused ultrasound beams. ULM further reveals the microvascular damage manifested in the form of reduced vascularity and decreased blood flow velocity across areas affected by the hemorrhagic stroke. ConclusionThe results demonstrate that sequential ULM combined with ND imaging is a useful imaging tool for basic in vivo research in stroke with rodent models where brain-wide detection of active bleeding and microvascular impairment are essential.

bioengineering↗

Longitudinal Awake Imaging of Deep Mouse Brain Microvasculature with Super-resolution Ultrasound Localization Microscopy

Ultrasound localization microscopy (ULM) is an emerging imaging modality that resolves microvasculature in deep tissues with high spatial resolution. However, existing preclinical ULM applications are largely constrained to anesthetized animals, introducing confounding vascular effects such as vasodilation and altered hemodynamics. As such, ULM quantifications (e.g., vessel diameter, density, and flow velocity) may be confounded by the use of anesthesia, undermining the usefulness of ULM in practice. Here we introduce a method to address this limitation and achieve ULM imaging in awake mouse brain. Pupillary monitoring was used to support the presence of the awake state during ULM imaging. Vasodilation induced by isoflurane was observed by ULM. Upon recovery to the awake state, reductions in vessel density and flow velocity were observed across different brain regions. In the cortex, the effects induced by isoflurane are more pronounced on venous flow than on arterial flow. In addition, serial in vivo imaging of the same animal brain at weekly intervals demonstrated the highly robust longitudinal imaging capability of the proposed technique. The consistency was further verified through quantitative analysis on individual vessels, cortical regions of arteries and veins, and subcortical regions. This study demonstrates longitudinal ULM imaging in the awake mouse brain, which is crucial for many ULM brain applications that require awake and behaving animals.

biophysics↗

Context-Aware Deep Learning Enables High-Efficacy Localization of High Concentration Microbubbles for Super-Resolution Ultrasound Localization Microscopy

Ultrasound localization microscopy (ULM) is an emerging super-resolution imaging technique for deep tissue microvascular imaging. However, conventional localization methods are constrained by low microbubble (MB) concentration, as accurate localization requires a strict separation of MB point spread functions (PSFs). Furthermore, deep learning-based localization techniques are often limited in their ability to generalize to in vivo ultrasound data due to challenges in accurately modeling highly variable MB PSF distributions and ultrasound imaging conditions. To address these limitations, we propose a novel deep learning-pipeline, LOcalization with Context Awareness (LOCA)-ULM, which employs simulation that incorporates MB context to generate synthetic data that closely resemble real MB signals, and a loss function that considers both MB count and localization loss. In in silico experiments, LOCA-ULM outperformed conventional localization with superior MB detection accuracy (94.0% vs. 74.9%) and a significantly lower MB missing rate (13.2% vs 74.8%). In vivo, LOCA-ULM achieved up to three-fold increase in MB localization efficiency and a x 9.5 faster vessel saturation rate than conventional ULM.

bioengineering↗

High Volume Rate 3-D Ultrasound Imaging Using Fast-Tilting and Redirecting Reflectors

3-D ultrasound imaging has many advantages over 2-D imaging such as more comprehensive tissue evaluation and less operator dependence. Although many 3-D ultrasound imaging techniques have been developed in the last several decades, a low-cost and accessible solution with high imaging volume rate and imaging quality remains elusive. Recently we proposed a new, high volume rate 3-D ultrasound imaging technique: Fast Acoustic Steering via Tilting Electromechanical Reflectors (FASTER), which uses a water-immersible and fast-tilting acoustic reflector to steer ultrafast plane waves in the elevational direction to achieve high volume rate 3-D ultrasound imaging with conventional 1-D array transducers. However, the initial implementation of FASTER imaging only involves a single fast-tilting acoustic reflector, which is inconvenient to use because the probe cannot be held in the regular upright position. Also, conventional FASTER imaging can only be performed inside a water tank because of the necessity of using water for acoustic conduction. To address these limitations of conventional FASTER, here we developed a novel ultrasound probe clip-on device that encloses a fast-tilting reflector, a redirecting reflector, and an acoustic wave conduction medium. The new FASTER 3-D imaging device can be easily attached to or removed from clinical ultrasound transducers, allowing rapid transformation from 2-D to 3-D ultrasound imaging. In vitro B-mode imaging studies demonstrated that the proposed method provided comparable imaging quality (e.g., spatial resolution and contrast-to-noise ratio) to conventional, mechanical-translation-based 3-D imaging while providing a much faster 3-D volume rate (e.g., 300 Hz vs [~]10 Hz). In addition to B-mode imaging, we also demonstrated 3-D power Doppler imaging and 3-D super-resolution ultrasound localization microscopy with the newly developed FASTER device. An in vivo imaging study showed that the FASTER device could clearly visualize the 3-D anatomy of the basilic vein of a healthy volunteer, and customized beamforming was implemented to accommodate the speed of sound difference between the acoustic medium and the imaging object (e.g., soft tissue). These results suggest that the newly developed redirecting reflector and the clip-on device could overcome key hurdles for future clinical translation of the FASTER 3-D imaging technology.

bioengineering↗

Super-resolution ultrasound imaging of cerebrovascular impairment in a mouse model of Alzheimer's disease

Increasing evidence has suggested a link between cerebrovascular disease and the cognitive impairment of patients with Alzheimers disease. However, cerebrovascular disease and Alzheimers disease share several risk factors making it unclear whether cerebrovascular deficiency and Alzheimers disease pathology have additive effects on cognition or if cerebrovascular impairment merely exacerbates existing Alzheimers disease-associated cognitive decline. Additionally, early-stage Alzheimers disease typically involves hippocampal atrophy, complicating most efforts to elucidate the interplay between cerebral microvascular function and Alzheimers disease progression due to the necessity of probing deep-brain structures. The purpose of this study was to demonstrate the use of ultrasound localization microscopy on the 5xFAD mouse model of Alzheimers disease (3-month and 6-month-old cohorts) in comparison to age-matched wild-type controls, revealing microvascular scale reconstructions throughout the whole brain depth, to visualize and quantify Alzheimers disease-associated vascular impairments. We found that functional decreases in hippocampal and entorhinal flow velocity preceded structural derangements in regional vascular density. In addition to providing global vascular quantifications of deep brain structures with a high local resolution, this technology also permitted hierarchical analysis of individual vessels and, in some cases, potentially allowed for decoupling of arteriole and venous flow contributions. Co-registered histological sectioning confirmed the regionalized hypo-perfusion deficits seen on ultrasound imaging, which were co-localized with amyloid beta plaque deposition. Significance statementThe study of the impact of cerebrovascular disease on Alzheimers disease pathology is complicated by the need to image deep-brain structures with high vascular fidelity. We demonstrate that ultrasound localization microscopy, a super-resolution acoustic imaging technique, is capable of imaging cerebrovasculature throughout the entire depth of the brain at a microvascular scale. This technology was applied to the 5xFAD mouse model of Alzheimers disease, where it was found that 5xFAD animals have significant impairments in vascular function in the entorhinal cortex and hippocampal region in comparison to age matched controls at the 3-month timepoint. Structural derangements in cerebrovasculature were only observed in the 6-month-old animal cohorts, with a maintained impairment in vascular function.

neuroscience↗

Contrast-free Super-resolution Doppler (CS Doppler) based on Deep Generative Neural Networks

Super-resolution ultrasound microvessel imaging based on ultrasound localization microscopy (ULM) is an emerging imaging modality that is capable of resolving micron-scaled vessels deep into tissue. In practice, ULM is limited by the need for contrast injection, long data acquisition, and computationally expensive post-processing times. In this study, we present a contrast-free super-resolution Doppler (CS Doppler) technique that uses deep generative networks to achieve super-resolution with short data acquisition. The training dataset is comprised of spatiotemporal ultrafast ultrasound signals acquired from in vivo mouse brains, while the testing dataset includes in vivo mouse brain, chicken embryo chorioallantoic membrane (CAM), and healthy human subjects. The in vivo mouse imaging studies demonstrate that CS Doppler could achieve an approximate 2-fold improvement in spatial resolution when compared with conventional power Doppler. In addition, the microvascular images generated by CS Doppler showed good agreement with the corresponding ULM images as indicated by a structural similarity index of 0.7837 and a peak signal-to-noise ratio of 25.52. Moreover, CS Doppler was able to preserve the temporal profile of the blood flow (e.g., pulsatility) that is similar to conventional power Doppler. Finally, the generalizability of CS Doppler was demonstrated on testing data of different tissues using different imaging settings. The fast inference time of the proposed deep generative network also allows CS Doppler to be implemented for real-time imaging. These features of CS Doppler offer a practical, fast, and robust microvascular imaging solution for many preclinical and clinical applications of Doppler ultrasound.

bioengineering↗

Curvelet Transform-based Sparsity Promoting Algorithm for Fast Ultrasound Localization Microscopy

Ultrasound localization microscopy (ULM) based on microbubble (MB) localization was recently introduced to overcome the resolution limit of conventional ultrasound. However, ULM is currently challenged by the requirement for long data acquisition times to accumulate adequate MB events to fully reconstruct vasculature. In this study, we present a curvelet transform-based sparsity promoting (CTSP) algorithm that improves ULM imaging speed by recovering missing MB localization signal from data with very short acquisition times. CTSP was first validated in a simulated microvessel model, followed by the chicken embryo chorioallantoic membrane (CAM), and finally, in the mouse brain. In the simulated microvessel study, CTSP robustly recovered the vessel model to achieve an 86.94% vessel filling percentage from a corrupted image with only 4.78% of the true vessel pixels. In the chicken embryo CAM study, CTSP effectively recovered the missing MB signal within the vasculature, leading to marked improvement in ULM imaging quality with a very short data acquisition. Taking the optical image as reference, the vessel filling percentage increased from 2.7% to 42.2% using 50ms of data acquisition after applying CTSP. CTSP used 80% less time to achieve the same 90% maximum saturation level as compared with conventional MB localization. We also applied CTSP on the microvessel flow speed maps and found that CTSP was able to use only 1.6s of microbubble data to recover flow speed images that have similar qualities as those constructed using 33.6s of data. In the mouse brain study, CTSP was able to reconstruct the majority of the cerebral vasculature using 1-2s of data acquisition. Additionally, CTSP only needed 3.2s of microbubble data to generate flow velocity maps that are comparable to those using 129.6s of data. These results suggest that CTSP can facilitate fast and robust ULM imaging especially under the circumstances of inadequate microbubble localizations.

bioengineering↗

Remodeling of dermal adipose tissue alleviates cutaneous toxicity induced by anti-EGFR therapy

Anti-epidermal growth factor receptor (EGFR) therapy-associated cutaneous toxicity is a syndrome characterized by papulopustular rash, local inflammation, folliculitis and microbial infection, resulting in a decrease in quality of life and dose interruption. However, no effective clinical intervention is available for this adverse effect. Here, we report the atrophy of dermal white adipose tissue (dWAT), a highly plastic adipose tissue with various skin-specific functions, correlates with rash occurrence and exacerbation in a murine model of EGFR inhibitor-induced rash. The reduction in dWAT is due to the inhibition of adipogenic differentiation by defects in peroxisome proliferator-activated receptor {gamma} (PPAR{gamma}) signaling, and increased lipolysis by the induced expression of the lipolytic cytokine IL6. The activation of PPAR{gamma} by rosiglitazone maintains adipogenic differentiation and represses the transcription of IL6, eventually improving skin functions and ameliorating the severity of rash without altering the antitumor effects. Thus, activation of PPAR{gamma} represents a promising approach to ameliorate cutaneous toxicity in patients with cancer who receive anti-EGFR therapy. Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

pharmacology and toxicology↗

Structural basis of the P4B ATPase lipid flippase activity

P4 ATPases are lipid flippases that are phylogenetically grouped into P4A, P4B and P4C clades. The P4A ATPases are heterodimers composed of a catalytic -subunit and accessory {beta}-subunit, and the structures of several heterodimeric flippases have been reported. The S. cerevisiae Neo1 and its orthologs represent the P4B ATPases, which function as monomeric flippases without a {beta}-subunit. It has been unclear whether monomeric flippases retain the architecture and transport mechanism of the dimeric flippases. Here we report the first structure of a P4B ATPase, Neo1, in its E1-ATP, E2P-transition, and E2P states. The structure reveals a conserved architecture as well as highly similar functional intermediate states relative to dimeric flippases. Consistently, structure-guided mutagenesis of residues in the proposed substrate translocation path disrupted Neo1s ability to establish membrane asymmetry. These observations indicate that evolutionarily distant P4 ATPases use a structurally conserved mechanism for substrate transport.

biochemistry↗

Assembly of the amphibian microbiome is influenced by the effects of land-use change on environmental reservoirs

0A growing focus in microbial ecology is understanding of how beneficial microbiome function is created and maintained through both stochastic and deterministic assembly mechanisms. This study explores the role of both the environment and disease in regulating the composition of microbial species pools in the soil and local communities of an amphibian host. To address this, we compared the microbiomes of over 200 Plethodon cinereus salamanders along a 65km land-use gradient in the greater New York metropolitan area and paired these with associated soil cores. Additionally, we characterized the diversity of bacterial and fungal symbionts that putatively inhibit the pathogenic fungus Batrachochytrium dendrobatidis. We predicted that if soil functions as the main regional species pool to amphibian skin, variation in skin microbial community composition would correlate with changes seen in soil. We found that salamanders share many microbial taxa with their soil environment but that these two microbiomes exhibit key differences, especially in the relative abundances of the bacteria phyla Acidobacteria, Actinobacteria, and Proteobacteria and the fungal phyla Ascomycota and genus Basidiobolus. Microbial community composition varied with changes in land-use associated factors such as canopy cover, impervious surface, and concentrations of the soil elements Al, Ni, and Hg, creating site-specific compositions. In addition, high dissimilarity among individual amphibian microbiomes across and within sites suggest that both stochastic and deterministic mechanisms guide assembly of microbes onto amphibian skin, with likely consequences in disease preventative function.

ecology↗

Transport mechanism of class-3 P4 ATPase lipid flippases

The P4 ATPases are a large family of membrane-embedded enzymes that use ATP hydrolysis to transport large lipid substrates across lipid bilayers. P4 ATPases differ in their cellular membrane location and their substrates. The structures of the endosome- and Golgi-localized class-1 phosphatidylserine flippases--such as the yeast Drs2 and human ATP8A1--have recently been reported, revealing a substrate binding site on the lumenal side and several transport states. However, a substrate binding site on the cytosolic side has not been found, and the transport mechanisms of P4 ATPases in other classes are still unknown. Here we report a systematic structural and functional study on two plasma-membrane localized, class-3 P4 ATPases that have broader substrate specificity, the S. cerevisiae Dnf1-Lem3 and Dnf2-Lem3 complexes. We have captured substrate lipids on both the exoplasmic and cytosolic sides, and we found that these two enzymes have very similar structures, consistent with their high sequence identity and redundant function. Unexpectedly, Lem3 contributes to substrate binding near the cytosolic surface. We found that the conformational transitions through the substrate transport cycle of these two class-3 enzymes match those of the class-1 enzymes, suggesting a conserved lipid-flipping mechanism among all classes of the P4 ATPases. Our study also revealed a helix-turn-helix insertion in the cytosolic P domain that is unique to the class-3 enzymes and plays a crucial role in their function. Therefore, the P4 ATPases may have retained an overall transport mechanism while evolving distinct features for cellular membrane localization, regulatory mechanisms, and transporting different lipid substrates.

biochemistry↗

A large-scale whole-genome sequencing analysis reveals highly specific genome editing by both Cas9 and Cpf1 nucleases in rice

Targeting specificity has been an essential issue for applying genome editing systems in functional genomics, precise medicine and plant breeding. Understanding the scope of off-target mutations in Cas9 or Cpf1-edited crops is critical for research and regulation. In plants, only limited studies had used whole-genome sequencing (WGS) to test off-target effects of Cas9. However, the cause of numerous discovered mutations is still controversial. Furthermore, WGS based off-target analysis of Cpf1 has not been reported in any higher organism to date. Here, we conducted a WGS analysis of 34 plants edited by Cas9 and 15 plants edited by Cpf1 in T0 and T1 generations along with 20 diverse control plants in rice, a major food crop with a genome size of ~380 Mb. The sequencing depth ranged from 45X to 105X with reads mapping rate above 96%. Our results clearly show that most mutations in edited plants were created by tissue culture process, which caused ~102 to 148 single nucleotide variations (SNVs) and ~32 to 83 insertions/deletions (indels) per plant. Among 12 Cas9 single guide RNAs (sgRNAs) and 3 Cpf1 CRISPR RNAs (crRNAs) assessed by WGS, only one Cas9 sgRNA resulted in off-target mutations in T0 lines at sites predicted by computer programs. Moreover, we cannot find evidence for bona fide off-target mutations due to continued expression of Cas9 or Cpf1 with guide RNAs in T1 generation. Taken together, our comprehensive and rigorous analysis of WGS big data across multiple sample types suggests both Cas9 and Cpf1 nucleases are very specific in generating targeted DNA modifications and off-targeting can be avoided by designing guide RNAs with high specificity.

molecular biology↗