Liver diseases are the primary reason for morbidity and mortality in the world. Owing to a shortage of organ donors and postoperative immune rejection, patients routinely suffer from liver failure. Unlike 2D cell models, animal models, and organoids, 3D bioprinting can be successfully employed to print living tissues and organs that contain blood vessels, bone, and kidney, heart, and liver tissues and so on. 3D bioprinting is mainly classified into four types: inkjet 3D bioprinting, extrusion-based 3D bioprinting, laser-assisted bioprinting (LAB), and vat photopolymerization. Bioinks for 3D bioprinting are composed of hydrogels and cells. For liver 3D bioprinting, hepatic parenchymal cells (hepatocytes) and liver nonparenchymal cells (hepatic stellate cells, hepatic sinusoidal endothelial cells, and Kupffer cells) are commonly used. Compared to conventional scaffold-based approaches, marked by limited functionality and complexity, 3D bioprinting can achieve accurate cell settlement, a high resolution, and more efficient usage of biomaterials, better mimicking the complex microstructures of native tissues. This method will make contributions to disease modeling, drug discovery, and even regenerative medicine. However, the limitations and challenges of this method cannot be ignored. Limitation include the requirement of diverse fabrication technologies, observation of drug dynamic response under perfusion culture, the resolution to reproduce complex hepatic microenvironment, and so on. Despite this, 3D bioprinting is still a promising and innovative biofabrication strategy for the creation of artificial multi-cellular tissues/organs.

Despite regional brain structural changes having been reported in patients with chronic low back pain (CLBP), the topological properties of structural covariance networks (SCNs), which refer to the organization of the SCNs, remain unclear. This study applied graph theoretical analysis to explore the alterations of the topological properties of SCNs, aiming to comprehend the integration and separation of SCNs in patients with CLBP. A total of 38 patients with CLBP and 38 healthy controls (HCs), balanced for age and sex, were scanned using three-dimensional T1-weighted magnetic resonance imaging. The cortical thickness was extracted from 68 brain regions, according to the Desikan-Killiany atlas, and used to reconstruct the SCNs. Subsequently, graph theoretical analysis was employed to evaluate the alterations of the topological properties in the SCNs of patients with CLBP. In comparison to HCs, patients with CLBP had less cortical thickness in the left superior frontal cortex. Additionally, the cortical thickness of the left superior frontal cortex was negatively correlated with the Visual Analogue Scale scores of patients with CLBP. Furthermore, patients with CLBP, relative to HCs, exhibited lower global efficiency and small-worldness, as well as a longer characteristic path length. This indicates a decline in the brain's capacity to transmit and process information, potentially impacting the processing of pain signals in patients with CLBP and contributing to the development of CLBP. In contrast, there were no significant differences in the clustering coefficient, local efficiency, nodal efficiency, nodal betweenness centrality, or nodal degree between the two groups. From the regional cortical thickness to the complex brain network level, our study demonstrated changes in the cortical thickness and topological properties of the SCNs in patients with CLBP, thus aiding in a better understanding of the pathophysiological mechanisms of CLBP.

Background: Neuroimaging studies have suggested a pivotal role for the amygdala involvement in chronic low back pain (CLBP). However, the relationship between the amygdala subregions and CLBP has not yet been delineated. This study aimed to analyze whether the amygdala subregions were linked to the development of CLBP.Methods: A total of 45 patients with CLBP and 45 healthy controls (HCs) were included in this study. All subjects were asked to complete a three-dimensional T1-weighted magnetic resonance imaging (3D-T1 MRI) scan. FreeSurfer 7.3.2 was applied to preprocess the structural MRI images and segment the amygdala into nine subregions. Afterwards, comparisons were made between the two groups in terms of the volumes of the amygdala subregions. Correlation analysis is utilized to examine the relationship between the amygdala subregion and the scale scores, as well as the pain duration in patients with CLBP. Additionally, logistic regression was used to explore the risk of the amygdala and its subregions for CLBP.Results: In comparison to HCs, patients with CLBP exhibited a significant enlargement of the left central nucleus (Ce) and left cortical nucleus (Co). Furthermore, the increased volume of the left Ce was associated with a higher risk of CLBP.Conclusion: Our study suggests that the left Ce and left Co may be involved in the pathophysiological processes of CLBP. Moreover, the volume of the left Ce may be a biomarker for detecting the risk of CLBP.

Background: The pathophysiology of primary blepharospasm (BSP) remains incompletely understood. This study aimed to characterize whole-brain functional network topology in treatment-naive BSP patients.Methods: Thirty-nine treatment-naive BSP patients and 39 matched healthy controls (HCs) underwent resting-state fMRI. Graph theoretical analysis was applied to assess global and nodal network metrics. Network-Based Statistics (NBS) identified subnetworks with altered functional connectivity (FC). Correlations between network metrics and clinical variables [Jankovic Rating Scale (JRS), illness duration] were explored.Results: Compared to HCs, BSP patients exhibited significantly lower local efficiency [p = 0.0002, false discovery rate (FDR) corrected], while global efficiency, characteristic path length, clustering coefficient, normalized clustering coefficient, normalized characteristic path length, or small-worldness were preserved (all p > 0.05, FDR corrected). Nodal analysis revealed decreased efficiency/degree in the bilateral thalamus and left supplementary motor area, and increased efficiency/degree in the bilateral precentral gyri, right postcentral gyrus, and left insula (all p < 0.05, FDR corrected). NBS identified subnetworks with altered FC across sensorimotor, limbic-subcortical, frontoparietal, and default mode networks, featuring both hyper- and hypo-connectivity (p < 0.05, NBS-corrected). Notably, left thalamic efficiency negatively correlated with illness duration (r = −0.481, p = 0.0019), and right precentral gyrus efficiency positively correlated with JRS total score (r = 0.395, p = 0.0129).Conclusion: BSP is characterized by complex functional network disruptions, including impaired local information processing, altered nodal importance in key motor and relay hubs, and widespread connectivity changes. These findings reinforce BSP as a network disorder. These network alterations may serve as objective markers for disease progression and could guide the development of targeted neuromodulation therapies.

Introduction: The neurobiological basis of gray matter (GM) alterations in juvenile myoclonic epilepsy (JME) remains poorly understood. This study aimed to identify robust GM changes and their underlying molecular signatures. Methods: We performed an updated coordinate-based meta-analysis of 15 voxel-based morphometry studies (394 JME patients, 448 healthy controls) and integrated the resulting GM alteration map with data from the Allen Human Brain Atlas and neurotransmitter atlases using advanced spatial correlation, gene enrichment, and network analysis approaches. Results: Our analysis revealed a consistent pattern of GM decreases in the sensorimotor areas and increases in regions implicated in emotion and cognition. These structural changes were spatially correlated with a set of 926 genes enriched for pathways related to ion channel activity, synaptic function, neuronal processes, and cellular metabolism, which showed peak expression during neurodevelopmental periods coinciding with JME onset. Protein–protein interaction analysis identified hub genes from two key functional classes: transcriptional regulators linked to circadian rhythms, and cellular signaling molecules including established monogenic epilepsy genes. Furthermore, the GM map correlated significantly with the spatial distributions of the serotonin, dopamine, and acetylcholine neurotransmitter systems. Discussion: While these associations are based on data from healthy donors and require further validation, our findings bridge the gap between macroscopic brain alterations and their underlying molecular architecture in JME. This provides an integrated model of its pathophysiology and highlights potential therapeutic avenues.

Objective: The central pathophysiology of chronic low back pain (CLBP) secondary to lumbar disc herniation (LDH) remains poorly understood, particularly the link between macroscale brain network dysfunction and its microscale biological underpinnings. This study aimed to bridge this critical gap by integrating resting-state fMRI, graph theory, and imaging transcriptomics. Methods: Resting-state fMRI data were acquired from 62 CLBP patients with LDH and 67 matched healthy controls (HCs). Whole-brain functional networks were constructed for each participant by calculating functional connectivity (FC) between 90 anatomical regions. Graph theoretical analysis was employed to derive global and nodal topological metrics. Group differences were identified and correlated with clinical variables. Crucially, these neuroimaging phenotypes were spatially mapped against the Allen Human Brain Atlas (AHBA) to uncover potential spatial molecular vulnerabilities. Results: At the connectional level, CLBP patients with LDH exhibited widespread hypoconnectivity across sensorimotor, ventral attention, and default mode networks. Further topological analysis revealed a profound focal degradation of hub function in the cingulate cortex, characterized by significantly reduced nodal degree, efficiency, and betweenness centrality ( p < 0.001), alongside decreased nodal efficiency in the right supplementary motor area, while global network architecture was preserved. Critically, these deficits in cingulate hub topology were significantly correlated with pain intensity. Imaging transcriptomics linked this focal topological failure to genes enriched for neuroinflammatory and synaptic plasticity pathways. Conclusion: These findings reveal multi-level functional network alterations in CLBP with LDH, linking focal hub failure to potential spatial molecular vulnerabilities associated with neuroinflammation and synaptic remodeling.