Biology subjects

Zu, Z.

Publications and source records attributed to Zu, Z..

6 recordsLinked to original sources

bioRxiv2025

White-Matter BOLD Mediates Time-Varying Cortico-Cortical Functional Connectivity

Functional connectivity (FC) measurements in the brain using BOLD fMRI have largely focused on correlations between gray-matter (GM) BOLD signals, ignoring the possible relevance of white-matter (WM) in delineating neural networks. We first employed a tract-informed mediation framework to test whether WM pathways contribute indirect, bundle-specific effects to cortico-cortical coupling. Using resting-state fMRI data from the Human Connectome Project, we quantified pathway-level mediation effects across GM-WM-GM units and found that WM BOLD signals significantly mediated GM-GM associations, with clear tract-dependent heterogeneity. Building upon this, we examined how dynamic features of WM BOLD signals relate to time-varying intra-cortical FC. We found that temporal variability of WM signals, rather than their mean amplitudes, more closely tracked fluctuations in GM-GM dynamic connectivity, with correlations reaching approximately 0.4 across specific tracts. Together, these results indicate that WM BOLD signals are related to how cortical regions interact, underscoring their integral role in large-scale brain network organization.

neuroscience↗

bioRxiv2024

A Denoising Convolutional Autoencoder for SNR Enhancement in Chemical Exchange Saturation Transfer imaging: (DCAE-CEST)

PurposeTo develop a SNR enhancement method for chemical exchange saturation transfer (CEST) imaging using a denoising convolutional autoencoder (DCAE), and compare its performance with state-of-the-art denoising methods. MethodThe DCAE-CEST model encompasses an encoder and a decoder network. The encoder learns features from the input CEST Z-spectrum via a series of 1D convolutions, nonlinearity applications and pooling. Subsequently, the decoder reconstructs an output denoised Z-spectrum using a series of up-sampling and convolution layers. The DCAE-CEST model underwent multistage training in an environment constrained by Kullback-Leibler divergence, while ensuring data adaptability through context learning using Principal Component Analysis processed Z-spectrum as a reference. The model was trained using simulated Z-spectra, and its performance was evaluated using both simulated data and in-vivo data from an animal tumor model. Maps of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) effects were quantified using the multiple-pool Lorentzian fit, along with an apparent exchange-dependent relaxation metric. ResultsIn digital phantom experiments, the DCAE-CEST method exhibited superior performance, surpassing existing denoising techniques, as indicated by the peak SNR and Structural Similarity Index. Additionally, in vivo data further confirms the effectiveness of the DCAE-CEST in denoising the APT and NOE maps when compared to other methods. While no significant difference was observed in APT between tumors and normal tissues, there was a significant difference in NOE, consistent with previous findings. ConclusionThe DCAE-CEST can learn the most important features of the CEST Z-spectrum and provide the most effective denoising solution compared to other methods.

bioengineering↗

bioRxiv2023

Assignment of molecular origins of NOE signal at -3.5 ppm in the brain

PurposeNuclear Overhauser Enhancement mediated saturation transfer effect, termed NOE(-3.5 ppm), is a major source of chemical exchange saturation transfer (CEST) MRI contrasts at 3.5 ppm in the brain. Previous phantom experiments have demonstrated that both proteins and lipids, two major components in tissues, have substantial contributions to NOE(-3.5 ppm) signals. Their relative contributions in tissues are informative for the interpretation of NOE(-3.5 ppm) contrasts that could provide potential imaging biomarkers for relevant diseases, which remain incompletely understood. MethodsExperiments on homogenates and supernatants of brain tissues collected from healthy rats, that could isolate proteins from lipids, were performed to evaluate the relative contribution of lipids to NOE(-3.5 ppm) signals. On the other hand, experiments on ghost membranes with varied pH, and reconstituted phospholipids with different chemical compositions were conducted to study the dependence of NOE(-3.5 ppm) on physiological conditions. Besides, CEST imaging on rat brains bearing 9L tumors and healthy rat brains was performed to analyze the causes of the NOE(-3.5 ppm) contrast variations between tumors and normal tissues, and between gray matter and white matter. ResultsOur experiments reveal that lipids have dominant contributions to the NOE (-3.5 ppm) signals. Further analysis suggests that decreased NOE(-3.5 ppm) signals in tumors and higher NOE(-3.5 ppm) signals in white matter than in gray matter are mainly explained by changes in membrane lipids, rather than proteins. ConclusionNOE(-3.5 ppm) could be exploited as a highly sensitive MRI contrast for imaging membrane lipids in the brain.

bioengineering↗

bioRxiv2022

A new method for quantifying APT and NOE(-3.5) using chemical exchange saturation transfer with double saturation powers (DSP-CEST)

PurposeQuantifications of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE(-3.5)) mediated transfer with high specificity are challenging since their signals measured in a Z-spectrum are overlapped with confounding signals from direct water saturation (DS), semi-solid magnetization transfer (MT) and chemical exchange saturation transfer (CEST) of fast-exchange pools. In this study, based on two canonical CEST acquisitions with double saturation powers (DSP), a new data-postprocessing method is proposed to specifically quantify the effects of APT and NOE. MethodsFor CEST imaging with relatively low saturation powers [Formula], both the fast-exchange CEST effect and the semi-solid MT effect increase linearly with [Formula] whereas the slow-exchange APT/NOE(-3.5) effect has no such a dependence on [Formula], which is exploited to isolate the APT and NOE effects from the confounding signals in this study. After a mathematical derivation for the establishment of the proposed method, numerical simulations based on Bloch equations are then performed to demonstrate its specificity to detections of the APT and NOE effects. Finally, an in vivo validation of the proposed method is conducted using an animal tumor model at a 4.7-T MRI scanner. ResultsThe simulations show that DSP-CEST can quantify the effects of APT and NOE and substantially eliminate the confounding signals. The in vivo experiments demonstrate that the prosed DSP-CEST method is feasible for the imaging of tumors. ConclusionThe data-postprocessing method proposed in this study can quantify the APT and NOE effects with considerably increased specificities and a reduced cost of imaging time.

biophysics↗

bioRxiv2022

Detection of functional activity in brain white matter using fiber architecture informed synchrony mapping

A general linear model is widely used for analyzing fMRI data, in which the blood oxygenation-level dependent (BOLD) signals in gray matter (GM) evoked in response to neural stimulation are modeled by convolving the time course of the expected neural activity with a canonical hemodynamic response function (HRF) obtained a priori. The maps of brain activity produced reflect the magnitude of local BOLD responses. However, detecting BOLD signals in white matter (WM) is more challenging as the BOLD signals are weaker and the HRF is different, and may vary more across the brain. Here we propose a model-free approach to detect changes in BOLD signals in WM by measuring task-evoked increases of BOLD signal synchrony in WM fibers. The proposed approach relies on a simple assumption that, in response to a functional task, BOLD signals in relevant fibers are modulated by stimulus-evoked neural activity and thereby show greater synchrony than when measured in a resting state, even if their magnitudes do not change significantly. This approach is implemented in two technical stages. First, for each voxel a fiber-architecture-informed spatial window is created with orientation distribution functions constructed from diffusion imaging data. This provides the basis for defining neighborhoods in WM that share similar local fiber architectures. Second, a modified principal component analysis (PCA) is used to estimate the synchrony of BOLD signals in each spatial window. The proposed approach is validated using a 3T fMRI dataset from the Human Connectome Project (HCP) at a group level. The results demonstrate that neural activity can be reliably detected as increases in fMRI signal synchrony within WM fibers that are engaged in a task with high sensitivities and reproducibility.

neuroscience↗

bioRxiv2020

SCFCdc4 ubiquitin ligase regulates synaptonemal complex formation during meiosis

Homologous chromosomes pair with each other during meiosis, culminating in the formation of the synaptonemal complex (SC), which is coupled with meiotic recombination. In this study, we showed that a meiosis-specific depletion mutant of a cullin (Cdc53) of the SCF (Skp-Cullin-F-box) ubiquitin ligase, which plays a critical role in cell cycle regulation during mitosis, is deficient in SC formation, but is proficient in the formation of crossovers, indicating uncoupling of meiotic recombination with SC formation in the mutant. Furthermore, the deletion of the PCH2 gene encoding a meiosis-specific AAA+ ATPase suppresses SC-assembly defect induced by CDC53 depletion. On the other hand, the pch2 cdc53 double mutant is defective in meiotic crossover formation, suggesting the SC assembly with unrepaired DSBs. A temperature-sensitive mutant of the CDC4, which encodes a F-box protein of the SCF, shows similar meiotic defects to the CDC53 depletion mutant. These suggest that SCFCdc4, probably SCFCdc4-dependnet protein ubiquitylation, regulates and collaborates with Pch2 in SC assembly and meiotic recombination. SummaryDuring meiosis, homologous chromosomes pair with each other and form the synaptonemal complex (SC). In this study, components of the SCF (Skp-Cullin-F-box) ubiquitin ligase, Cdc53 and Cdc4, are required for SC formation. A meiosis-specific AAA+ ATPase Pch2 antagonize the functions of Cdc53 and Cdc4 for proper SC assembly.

molecular biology↗