Shuhua Ma

Background: Gouty arthritis (GA) is a common inflammatory disease characterized by severe pain and hyperuricemia (HUA). To date, the interaction between GA and cognitive function has remained unclear. This study aimed to investigate the cognitive impairment and related brain function changes in GA patients. Methods: A total of 21 male GA patients and 21 age-, gender-, and education-matched healthy controls (HC) were recruited. All participants underwent multimodal functional magnetic resonance imaging (fMRI) examinations and completed the Montreal Cognitive Assessment (MoCA) scale. We utilized supervised machine learning (ML) models based on whole-brain functional connectivity of resting-state fMRI (rs-fMRI) to distinguish GA patients from HC and exported the significantly neuroanatomical regions as functional connectivity matrices features. Meanwhile, task-state fMRI (ts-fMRI) performed during a mental rotation task (MRT) was used to investigate brain functional alterations associated with visuospatial working memory (VSWM) in GA patients. Results: GA patients performed worse on MoCA scores and MRT behavioral performance than the HC group (PConclusions: This study comprehensively reveals VSWM impairment in GA patients and identifies the related brain activation differences in the frontoparietal network and diagnosis of cognitive impairment in GA patients and for further research on the underlying neural mechanisms.

Background: We aimed to explore changes in decision-related brain microstructure, brain functional activities, and functional connectivity, and their correlations with cognitive function in end-stage kidney disease (ESKD) patients undergoing peritoneal dialysis (PD). Furthermore, the impact of dialysis on these changes was examined. Methods: Thirty ESKD patients undergoing PD, 20 predialysis patients with chronic kidney disease (CKD) stage 5 (predialysis CKD stage 5), and 30 healthy controls (HC) were recruited in this study. Various assessments have been conducted, including neuropsychological scale testing, decision-related behavioral tests, and structural and functional magnetic resonance imaging (MRI) scans. Results: Compared to the HC group, PD and predialysis patients performed poorly in the neuropsychology and Iowa Gambling Task (IGT), PD patients showed decreased functional activation and gray matter volume in multiple decision-related brain areas, including the ventromedial prefrontal cortex (vmPFC), orbitofrontal cortex (OFC), and anterior cingulate cortex (ACC). The default mode network (DMN) and salience network (SAN) were the main brain regions with decreased functional connectivity to vmPFC and ACC. Additionally, compared to the predialysis group, PD patients showed enhanced brain activation in decision-related brain regions such as the ACC, vmPFC, and insula. The structure and function variabilities of the vmPFC were correlated with IGT and Montreal Cognitive Assessment score, and the activation of OFC was negatively associated with blood creatinine, cystatin, and parathyroid hormone levels. Conclusion: In summary, PD can change the structure and function of decision-related brain circuits (vmPFC-OFC-ACC) and reduce integration within DMN and SAN, which is correlated with cognitive function and clinical features. These suggest that PD can improve patients’ cognitive function and disease progression to a certain extent.

Background: Irritable bowel syndrome (IBS) is a disorder characterized by signaling dysregulation between the brain and gut, leading to gastrointestinal dysfunction. Symptoms such as abdominal pain and constipation can manifest periodically or persistently, and negative emotions may exacerbate the symptoms. Previous studies have shown that the pathogenesis of IBS is closely related to the brain-gut axis and brain function, but there are still difficulties in disease diagnosis. Therefore, this study applied a machine-learning approach based on resting-state functional magnetic resonance imaging (rs-fMRI) whole-brain functional connectivity (FC) to distinguish IBS patients from healthy controls (HCs). Methods: A total of 176 subjects, comprising 88 consecutive patients with IBS and 88 age-, sex- and education-matched HCs, were enrolled in this study between January 2020 and January 2024 at the First Affiliated Hospital of Shantou University Medical College. All the subjects underwent rs-fMRI and high-resolution anatomical T1-weighted imaging (T1WI) examinations. Following the preprocessing of the rs-fMRI image data, FC matrices between all regions of interest (ROIs) were extracted using automated anatomical labeling (AAL). Subsequently, supervised machine learning was performed using whole-brain FC for classification features to identify the best-performing model. Finally, weights of the optimal model’s features were exported to confirm the neuroanatomical regions significantly influencing model establishment. Results: Compared with other supervised learning models, the support vector machine (SVM) model had significantly higher classification accuracy and performed significantly better than the other models (PConclusions: The SVM was the optimal machine-learning model for effectively classifying IBS patients and HCs based on whole-brain resting-state FC matrices. The FC features between the emotion-related brain regions significantly affected the construction of the machine-learning models. As a classification feature in machine learning, whole-brain resting-state FC holds the potential to achieve precision medicine in IBS and enhance disease diagnostic efficacy.

Background: Inflammatory Bowel Disease (IBD) patients may experience cognitive impairments in Visuospatial Working Memory (VSWM), significantly impacting their quality of life. However, the mechanisms underlying these impairments remain poorly understood. Methods: We studied functional MRI and graph theory analysis to investigate changes in functional connectivity networks during the Mental Rotation Task (MRT) in IBD patients. Twenty IBD patients (13 males, 7 females; mean age = 34.95 ± 13.80 years; mean disease duration = 2.43 ± 2.37 years) participated in the study. Exclusion criteria encompassed recent use of analgesics, 5-Aminosalicylate, corticosteroids, or immunosuppressants within the past three months. Additionally, we recruited 20 age-, gender-, and education-matched healthy controls for comparison. Results: Compared to a control group, IBD patients exhibited significantly longer reaction times and reduced accuracy during the MRT. Our analysis revealed abnormalities in multiple nodal attributes within the functional connectivity network, particularly in regions such as the bilateral orbitofrontal cortex, right supplementary motor area, bilateral parahippocampal gyrus, and bilateral anterior temporal lobe. We observed that the nodal efficiency in the left temporal pole is negatively correlated with Red Blood Cell Distribution Width (RDW) and positively correlated with response time of MRT. Conclusion: Our findings revealed notable abnormalities in multiple node attributes among IBD patients during MRT, providing evidence of cognitive impairments in VSWM in IBD patients. This study found RDW maybe can serve as a clinical indicator for predicting early VSWM impairment in patients with IBD.

Objective: To identify the potential diagnostic biomarkers of rheumatoid arthritis (RA) and assess the relation between visuospatial dysfunction and disease activity in RA patients using mental rotation task (MRT)-based functional magnetic resonance imaging (fMRI). Methods: A total of 27 RA patients (11 in remission, 16 in active) and 27 well-matched controls were enrolled. The visuospatial function of the subjects was measured by MRT. Brain activity data were collected using blood oxygen level dependent fMRI technique under MRT. Disease activity score 28 (DAS28) was used to evaluate the disease severity of RA patients. An analysis of the correlations between abnormal visuospatial-related brain regions, MRT performance, and DAS28 was conducted. Results: RA patients performed worse on MRT than controls. Compared to the control group, RA patients showed enhanced activation in the left precuneus, left superior frontal gyrus and right cingulate gyrus during the rotation task, with left hemisphere dominance. RA patients in active showed enhanced activation in the left precuneus, left middle frontal gyrus and right cingulate gyrus compared to the patients in remission. The left precuneus activation was negatively correlated with MRT accuracy (r = −0.621, p = 0.01) and positively correlated with DAS28 (r = 0.710, p = 0.002), and MRT accuracy was negatively correlated with DAS28 in RA patients (r = −0.702, p = 0.002). Conclusion: Enhanced activation of the left precuneus in RA patients affects visuospatial function and is closely related to disease activity. These changes may provide a valuable diagnostic neuroimaging biomarker of RA.