White Matter Engagement in Brain Networks Assessed by Integration of Functional and Structural Connectivity.

Current models of brain networks may potentially be improved by integrating our knowledge of structural connections, within and between circuits, with metrics of functional interactions between network nodes. The former may be obtained from diffusion MRI of white matter (WM), while the latter may be derived by measuring correlations between resting state BOLD signals from pairs of gray matter (GM) regions. From inspection of diffusion MRI data, it is clear that each WM voxel within a 3D image array may be traversed by multiple WM structural tracts, each of which connects a pair of GM nodes. We hypothesized that by appropriately weighting and then integrating the functional connectivity of each such connected pair, the overall engagement of any WM voxel in brain functions could be evaluated. This model introduces a structural constraint to earlier studies of WM engagement and addresses some limitations of previous efforts to relate structure and function. Using concepts derived from graph theory, we obtained spatial maps of WM engagement which highlight WM regions critical for efficient communications across the brain. The distributions of WM engagement are highly reproducible across subjects and depict a notable interdependence between the distribution of GM activities and the detailed organization of WM. Additionally, we provide evidence that the engagement varies over time and shows significant differences between genders. These findings suggest the potential of WM engagement as a measure of the integrity of normal brain functions and as a biomarker for neurological and cognitive disorders.

Functional correlation tensors in brain white matter and the effects of normal aging.

Resting state correlations between blood oxygenation level dependent (BOLD) MRI signals from voxels in white matter (WM) are demonstrably anisotropic, so that functional correlation tensors (FCT) may be used to quantify the underlying microstructure of BOLD effects in WM tracts. However, the overall spatial distribution of FCTs and their metrics in specific populations has not yet been established, and the factors that affect their precise arrangements remain unclear. Changes in WM occur with normal aging, and these may be expected to affect FCTs. We hypothesized that FCTs exhibit a characteristic spatial pattern and may show systematic changes with aging or other factors. Here we report our analyses of the FCT characteristics of fMRI images of a large cohort of 461 cognitively normal subjects (190 females, 271 males) sourced from the Open Access Series of Imaging Studies (OASIS), with age distributions of 42 y/o - 95 y/o. Group averages and statistics of FCT indices, including axial functional correlations, radial functional correlations, mean functional correlations and fractional anisotropy, were quantified in WM bundles defined by the JHU ICBM-DTI-81 WM atlas. In addition, their variations with normal aging were examined. The results revealed a dimorphic distribution of changes in FCT metrics with age, with decreases of the functional correlations in some regions and increases in others. Supplementary analysis revealed that females exhibited significant age effects on a greater number of WM areas, but the interaction between age and sex was not significant. The findings demonstrate the reproducibility of the spatial distribution of FCT metrics and reveal subtle regional changes with age.

Identification of functional white matter networks in BOLD fMRI.

White matter signals in resting state blood oxygen level dependent functional magnetic resonance (BOLD-fMRI) have been largely discounted, yet there is growing evidence that these signals are indicative of brain activity. Understanding how these white matter signals capture function can provide insight into brain physiology. Moreover, functional signals could potentially be used as early markers for neurological changes, such as in Alzheimer's Disease. To investigate white matter brain networks, we leveraged the OASIS-3 dataset to extract white matter signals from resting state BOLD-FMRI data on 711 subjects. The imaging was longitudinal with a total of 2,026 images. Hierarchical clustering was performed to investigate clusters of voxel-level correlations on the timeseries data. The stability of clusters was measured with the average Dice coefficients on two different cross fold validations. The first validated the stability between scans, and the second validated the stability between populations. Functional clusters at hierarchical levels 4, 9, 13, 18, and 24 had local maximum stability, suggesting better clustered white matter. In comparison with JHU-DTI-SS Type-I Atlas defined regions, clusters at lower hierarchical levels identified well-defined anatomical lobes. At higher hierarchical levels, functional clusters mapped motor and memory functional regions, identifying 50.00%, 20.00%, 27.27%, and 35.14% of the frontal, occipital, parietal, and temporal lobe regions respectively.

Remote Ischemic Preconditioning Before Drug-Coated Balloon Implantation can Improve the Long-Term Prognosis of Patients with CAD.

Background: Drug-coated balloons (DCBs) have become increasingly vital to percutaneous coronary intervention, offering many advantages. However, a significant challenge is that many patients are intolerant to the myocardial ischemia caused by DCB dilation. Remote ischemic preconditioning (RIPC) is known to enhance heart's tolerance to ischemia and hypoxia. This study investigated whether preoperative RIPC could extend the tolerated DCB inflation time and improve the long-term prognosis of patients with coronary artery disease (CAD). Methods: A total of 653 patients with CAD were recruited and randomized into a RIPC group (n = 323) and a control (n = 330) group. The RIPC group underwent RIPC on the left upper limb twice daily, starting three days before the DCB implantation. The patients were followed up for one year after the operation, and 197 patients returned for coronary angiography (CAG) examination where the quantitative flow ratio (QFR) of the target vessels was measured. The primary endpoint of the study was the incidence of target lesion failure (TLF), which included target lesion revascularization (TLR), target vessel myocardial infarction, and cardiac death. The secondary endpoint was the rate of QFR loss in the target vessels. Results: The findings revealed a significantly lower incidence of TLR in the RIPC group compared to the control group. Additionally, at the one-year follow-up, the rate of QFR loss in target vessels was lower in the RIPC group than in the control group. Conclusions: The preoperative application of RIPC effectively extended the duration patients could tolerate DCB inflation. Furthermore, this approach positively impacted the long-term prognosis of CAD patients undergoing DCB treatment. Clinical Trial Registration Information: NCT04766749.

The association between different levels of depression and overactive bladder: A cross-sectional study of the 2005-2018 National Health and Nutrition Examination Survey.

BACKGROUND: There is growing evidence of a possible correlation between depression and overactive bladder (OAB). However, few studies have classified depression according to its severity. Whether there is an association between different levels of depression and OAB symptoms remains unclear. METHODS: Participants with complete information about depression, OAB, and covariates in the National Health and Nutrition Examination Survey (NHANES) 2005-2018 were included in this study. Depression symptoms were assessed by the Patient Health Questionnaire-9. OAB symptoms were evaluated by the Overactive Bladder Symptom Score. Weighted multivariate logistic regression models were applied to analyze the relationship between depression and OAB. RESULTS: A total of 30 359 participants were included in this study, consisting of 6245 OAB patients and 24 114 non-OAB participants. The multivariate logistic regression suggested depression independently correlated with OAB (odds ratio [OR] = 2.764, 95% confidence interval [CI] = 2.429-3.146, p < 0.001). Further, mild (OR = 2.355, 95% CI = 2.111-2.627, p < 0.001), moderate (OR = 3.262, 95% CI = 2.770-3.841, p < 0.001), and moderately severe to severe depression (OR = 3.927, 95% CI = 3.246-4.752, p < 0.001) were all associated with OAB. Additionally, depression was also correlated with urgency urinary incontinence (OR = 2.249, 95% CI = 1.986-2.548, p < 0.001) and nocturia (OR = 2.166, 95% CI = 1.919-2.446, p < 0.001). CONCLUSION: This study indicated different levels of depression, even mild depression, were independent risk factors for OAB. Given the frequent coexistence and potential interactions between depression and OAB, clinicians should be aware of the importance of assessing both physical and psychological symptoms in these patients. Early diagnosis and holistic treatment may improve the treatment outcomes, particularly for those suffering from both conditions.

Age and gender mediated the association between anemia and 30-day outcomes in patients with ST-segment elevated myocardial infarction.

Background: The higher prevalence of anemia in females and elderly may be attributed to its association with worsened outcomes in ST-elevation myocardial infarction (STEMI) patients. We aimed to evaluate the precise effects of age and gender on the association between anemia and 30-day outcomes. Method: We identified 4350 STEMI patients and divided into anemia and non-anemia. Effects were analyzed as categories using Cox proportional-hazards regression and as continuous using restricted cubic splines. Propensity score matching (PSM) and mediation analysis were applied to identify intermediate effects. Results: Anemic patients were older, more likely to be female, and experienced doubled all-cause death (7.3 % versus 15.0 %), main adverse cardiovascular and cerebrovascular events (MACCE, 11.1 % versus 20.2 %), heart failure (HF, 5.1 % versus 8.6 %), and bleeding events (2.7 % versus 5.4 %). After adjustment, the association between anemia and all-cause death (Hazard ratio (HR) 1.15, 95 % confidence interval (95 %CI) 0.93-1.14), MACCE (HR 1.14, 95 %CI 0.95-1.36) and HF (HR 1.19, 95 %CI 0.92-1.55) were insignificant, the effects persisted nullified across age classes (P-interaction > 0.05) and PSM (P > 0.05). Ulteriorly, age mediated 77.6 %, 66.2 %, 48.0 %, gender mediated 38.1 %, 15.0 %, 3.2 %, age and gender together mediated 99.8 % 72.9 %, 48.1 % of the relationship. Anemia was independently associated with bleeding events (HR 2.02, 95 %CI 1.42-2.88), the effects consisted significant regardless of PSM (P < 0.05), age, and gender classes (P-interaction > 0.05), and no mediating role of age and gender were observed. Conclusions: In STEMI patients, age and gender largely mediated the relationship between anemia and all-cause death, MACCE, and HF, anemia was independently associated with bleeding complications.

Quantification of mediation effects of white matter functional characteristics on cognitive decline in aging.

Cognitive decline with aging involves multifactorial processes, including changes in brain structure and function. This study focuses on the role of white matter functional characteristics, as reflected in blood oxygenation level-dependent signals, in age-related cognitive deterioration. Building on previous research confirming the reproducibility and age-dependence of blood oxygenation level-dependent signals acquired via functional magnetic resonance imaging, we here employ mediation analysis to test if aging affects cognition through white matter blood oxygenation level-dependent signal changes, impacting various cognitive domains and specific white matter regions. We used independent component analysis of resting-state blood oxygenation level-dependent signals to segment white matter into coherent hubs, offering a data-driven view of white matter's functional architecture. Through correlation analysis, we constructed a graph network and derived metrics to quantitatively assess regional functional properties based on resting-state blood oxygenation level-dependent fluctuations. Our analysis identified significant mediators in the age-cognition relationship, indicating that aging differentially influences cognitive functions by altering the functional characteristics of distinct white matter regions. These findings enhance our understanding of the neurobiological basis of cognitive aging, highlighting the critical role of white matter in maintaining cognitive integrity and proposing new approaches to assess interventions targeting cognitive decline in older populations.

Association between circulating immune cells and the risk of prostate cancer: a Mendelian randomization study.

Background: There is still limited research on the association between immune cells and the risk of prostate cancer. Further investigations are warranted to comprehend the intricate associations at play. Methods: We used a bidirectional two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between immune cell phenotypes and prostate cancer. The summary data for immune cell phenotypes was derived from a study cohort, including 3,757 individuals from Sardinia with data on 731 immune cell phenotypes. The summary data for prostate cancer were obtained from the UK Biobank database. Sensitivity analyses were conducted, and the combination of MR-Egger and MR-Presso was used to assess horizontal pleiotropy. Cochran's Q test was employed to evaluate heterogeneity, and the results were subjected to FDR correction. Results: Our study identified two immune cell phenotypes significantly associated with the risk of prostate cancer, namely CD25 on naive-mature B cells (OR = 0.998, 95% CI, 0.997-0.999, P = 2.33E-05, FDR = 0.017) and HLA DR on CD14- CD16- cells (OR = 1.001, 95% CI, 1.000-1.002, P = 8.01E-05, FDR = 0.03). When adjusting FDR to 0.2, we additionally found six immune cell phenotypes influencing the incidence of prostate cancer. These include FSC-A on B cells (OR = 1.002, 95% CI, 1.001-1.002, P = 7.77E-04, FDR = 0.133), HLA DR on plasmacytoid dendritic cells (OR = 1.001, 95% CI, 1.000-1.001, P = 0.001, FDR = 0.133), CD14+ CD16- monocyte % monocytes (OR = 1.002, 95% CI, 1.001-1.003, P = 0.001, FDR = 0.133), and HVEM on effector memory CD4+ T cells (OR = 1.001, 95% CI, 1.000-1.002, P = 0.002, FDR = 0.169), which are positively correlated with the risk of prostate cancer. Conversely, CD25 on IgD+ B cells (OR = 0.998, 95% CI, 0.997-0.999, P = 0.002, FDR = 0.169) and Monocytic Myeloid-Derived Suppressor Cells AC (OR = 0.999, 95% CI, 0.999-1.000, P = 0.002, FDR = 0.17) are negatively correlated with the risk of prostate cancer. Conclusion: This study has revealed causal relationships between immune cell phenotypes and prostate cancer, supplying novel insights that might aid in identifying potential therapeutic targets of prostate cancer.

Age shock index and age-modified shock index are valuable bedside prognostic tools for postdischarge mortality in ST-elevation myocardial infarction patients.

BACKGROUND: The incidence of mortality is considerable after ST-elevation myocardial infarction (STEMI) hospitalization; risk assessment is needed to guide postdischarge management. Age shock index (SI) and age modified shock index (MSI) were described as useful prognosis instruments; nevertheless, their predictive effect on short and long-term postdischarge mortality has not yet been sufficiently confirmed. METHODS: This analysis included 3389 prospective patients enrolled from 2016 to 2018. Endpoints were postdischarge mortality within 30 days and from 30 days to 1 year. Hazard ratios (HRs) were evaluated by Cox proportional-hazards regression. Predictive performances were assessed by area under the curve (AUC), integrated discrimination improvement (IDI), net reclassification improvement (NRI) and decision curve analysis (DCA) and compared with TIMI risk score and GRACE score. RESULTS: The AUCs were 0.753, 0.746 for age SI and 0.755, 0.755 for age MSI for short- and long-term postdischarge mortality. No significant AUC differences and NRI were observed compared with the classic scores; decreased IDI was observed especially for long-term postdischarge mortality. Multivariate analysis revealed significantly higher short- and long-term postdischarge mortality for patients with high age SI (HR: 5.44 (2.73-10.85), 5.34(3.18-8.96)), high age MSI (HR: 4.17(1.78-9.79), 5.75(3.20-10.31)) compared to counterparts with low indices. DCA observed comparable clinical usefulness for predicting short-term postdischarge mortality. Furthermore, age SI and age MSI were not significantly associated with postdischarge prognosis for patients who received fibrinolysis. CONCLUSIONS: Age SI and age MSI were valuable instruments to identify high postdischarge mortality with comparable predictive ability compared with the classic scores, especially for events within 30 days after hospitalization.

USF1 transcriptionally activates USP14 to drive atherosclerosis by promoting EndMT through NLRC5/Smad2/3 axis.

BACKGROUND: Endothelial-to-Mesenchymal Transformation (EndMT) plays key roles in endothelial dysfunction during the pathological progression of atherosclerosis; however, its detailed mechanism remains unclear. Herein, we explored the biological function and mechanisms of upstream stimulating factor 1 (USF1) in EndMT during atherosclerosis. METHODS: The in vivo and in vitro atherosclerotic models were established in high fat diet-fed ApoE-/- mice and ox-LDL-exposed human umbilical vein endothelial cells (HUVECs). The plaque formation, collagen and lipid deposition, and morphological changes in the aortic tissues were evaluated by hematoxylin and eosin (HE), Masson, Oil red O and Verhoeff-Van Gieson (EVG) staining, respectively. EndMT was determined by expression levels of EndMT-related proteins. Target molecule expression was detected by RT-qPCR and Western blotting. The release of pro-inflammatory cytokines was measured by ELISA. Migration of HUVECs was detected by transwell and scratch assays. Molecular mechanism was investigated by dual-luciferase reporter assay, ChIP, and Co-IP assays. RESULTS: USF1 was up-regulated in atherosclerosis patients. USF1 knockdown inhibited EndMT by up-regulating CD31 and VE-Cadherin, while down-regulating α-SMA and vimentin, thereby repressing inflammation, and migration in ox-LDL-exposed HUVECs. In addition, USF1 transcriptionally activated ubiquitin-specific protease 14 (USP14), which promoted de-ubiquitination and up-regulation of NLR Family CARD Domain Containing 5 (NLRC5) and subsequent Smad2/3 pathway activation. The inhibitory effect of sh-USF1 or sh-USP14 on EndMT was partly reversed by USP14 or NLRC5 overexpression. Finally, USF1 knockdown delayed atherosclerosis progression via inhibiting EndMT in mice. CONCLUSION: Our findings indicate the contribution of the USF1/USP14/NLRC5 axis to atherosclerosis development via promoting EndMT, which provide effective therapeutic targets.

Identification of functional white matter networks in BOLD fMRI.

White matter signals in resting state blood oxygen level dependent functional magnetic resonance (BOLD-fMRI) have been largely discounted, yet there is growing evidence that these signals are indicative of brain activity. Understanding how these white matter signals capture function can provide insight into brain physiology. Moreover, functional signals could potentially be used as early markers for neurological changes, such as in Alzheimer's Disease. To investigate white matter brain networks, we leveraged the OASIS-3 dataset to extract white matter signals from resting state BOLD-FMRI data on 711 subjects. The imaging was longitudinal with a total of 2,026 images. Hierarchical clustering was performed to investigate clusters of voxel-level correlations on the timeseries data. The stability of clusters was measured with the average Dice coefficients on two different cross fold validations. The first validated the stability between scans, and the second validated the stability between subject populations. Functional clusters at hierarchical levels 4, 9, 13, 18, and 24 had local maximum stability, suggesting better clustered white matter. In comparison with JHU-DTI-SS Type-I Atlas defined regions, clusters at lower hierarchical levels identified well defined anatomical lobes. At higher hierarchical levels, functional clusters mapped motor and memory functional regions, identifying 50.00%, 20.00%, 27.27%, and 35.14% of the frontal, occipital, parietal, and temporal lobe regions respectively.

The missing third dimension-Functional correlations of BOLD signals incorporating white matter.

Correlations between magnetic resonance imaging (MRI) blood oxygenation level-dependent (BOLD) signals from pairs of gray matter areas are used to infer their functional connectivity, but they are unable to describe how white matter is engaged in brain networks. Recently, evidence that BOLD signals in white matter are robustly detectable and are modulated by neural activities has accumulated. We introduce a three-way correlation between BOLD signals from pairs of gray matter volumes (nodes) and white matter bundles (edges) to define the communication connectivity through each white matter bundle. Using MRI images from publicly available databases, we show, for example, that the three-way connectivity is influenced by age. By integrating functional MRI signals from white matter as a third component in network analyses, more comprehensive descriptions of brain function may be obtained.

Assessing White Matter Engagement in Brain Networks through Functional and Structural Connectivity Mapping.

Understanding the intricate interplay between gray matter (GM) and white matter (WM) is crucial for deciphering the complex activities of the brain. While diffusion tensor imaging (DTI) has advanced the mapping of these structural pathways, the relationship between structural connectivity (SC) and functional connectivity (FC) remains inadequately understood. This study addresses the need for a more integrative approach by mapping the importance of the inter-GM functional link to its structural counterparts in WM. This mapping yields a spatial distribution of engagement that is not only highly reproducible but also aligns with direct structural, functional, and bioenergetic measures within WM, illustrating a notable interdependence between the function of GM and the characteristics of WM. Additionally, our research has uncovered a set of unique engagement modes through a clustering analysis of window-wise engagement maps, highlighting the dyanmic nature of the engagement. The engagement along with their temporal variations revealed significant differences across genders and age groups. These findings suggest the potential of WM engagement as a biomarker for neurological and cognitive conditions, offering a more nuanced understanding of individualized brain activity and connectivity patterns.

Unlocking the link: how hippocampal glutathione-glutamate coupling predicts cognitive impairment in multiple sclerosis patients.

Cognitive impairment is a common symptom of multiple sclerosis and profoundly impacts quality of life. Glutathione (GSH) and glutamate (Glu) are tightly linked in the brain, participating in cognitive function. However, GSH-Glu couplings in cognitive brain regions and their relationship with cognitive impairment in relapsing-remitting multiple sclerosis (RRMS) remains unclear. Forty-one RRMS patients and 43 healthy controls underwent magnetic resonance spectroscopy to measure GSH and Glu levels in the posterior cingulate cortex, medial prefrontal cortex and left hippocampus. Neuropsychological tests were used to evaluate the cognitive function. The Glu/GSH ratio was used to indicate the coupling between GSH and Glu and was tested as a predictor of cognitive performance. The results show that RRMS patients exhibited reduced hippocampal GSH and Glu levels, which were found to be significant predictors of worse verbal and visuospatial memory, respectively. Moreover, GSH levels were dissociated from Glu levels in the left hippocampus of RRMS patients. Hippocampal Glu/GSH ratio is significantly correlated with processing speed and has a greater predictive effect. Here we show the hippocampal Glu/GSH ratio could serve as a new potential marker for characterizing cognitive impairment in RRMS, providing a new direction for clinical detection of cognitive impairment.

Abnormal white and gray matter functional connectivity is associated with cognitive dysfunction in presbycusis.

Presbycusis is characterized by high-frequency hearing loss and is closely associated with cognitive decline. Previous studies have observed functional reorganization of gray matter in presbycusis, but the information transmission between gray matter and white matter remains ill-defined. Using resting-state functional magnetic resonance imaging, we investigated differences in functional connectivity (GM-GM, WM-WM, and GM-WM) between 60 patients with presbycusis and 57 healthy controls. Subsequently, we examined the correlation between these connectivity differences with high-frequency hearing loss as well as cognitive impairment. Our results revealed significant alterations in functional connectivity involving the body of the corpus callosum, posterior limbs of the internal capsule, retrolenticular region of the internal capsule, and the gray matter regions in presbycusis. Notably, disrupted functional connectivity was observed between the body of the corpus callosum and ventral anterior cingulate cortex in presbycusis, which was associated with impaired attention. Additionally, enhanced functional connectivity was found in presbycusis between the internal capsule and the ventral auditory processing stream, which was related to impaired cognition in multiple domains. These two patterns of altered functional connectivity between gray matter and white matter may involve both bottom-up and top-down regulation of cognitive function. These findings provide novel insights into understanding cognitive compensation and resource redistribution mechanisms in presbycusis.

Comparative efficacy of olaparib in combination with or without novel antiandrogens for treating metastatic castration-resistant prostate cancer.

Background: Studies using novel antiandrogens (NAA) in patients with metastatic castration-resistant prostate cancer (mCRPC) have shown overall survival benefit. As patients develop resistance to NAA therapy, the poly(ADP-ribose) polymerase inhibitor (PARPi) olaparib in combination with NAA may become a promising therapy. However the overall benefit of olaparib monotherapy or combination therapy still needs to be evaluated. Therefore, we performed a network meta-analysis to assess the efficacy and toxicity between olaparib, olaparib combined with abiraterone and NAA. Methods: We searched PubMed, EMBASE, the Cochrane Library and American Society of Clinical Oncology (ASCO) University Meeting abstracts for randomized controlled trials reporting olaparib and NAA from 2010 up to March, 2023. Network meta-analysis using Stata 16.0 and R 4.4.2, hazard ratios (HR) with 95% confidence intervals (CI) were used to assess the results. Results: Four trials reported olaparib, olaparib plus abiraterone and apalutamide plus abiraterone. radiographic progression-free survival (rPFS) was significantly lower in patients on apalutamide plus abiraterone compared to olaparib (HR, 1.43; 95% CI, 1.06-1.93). rPFS was similar for olaparib plus abiraterone and olaparib (HR, 1.35; 95% CI, 0.99-1.84); likewise, olaparib plus abiraterone and apalutamide plus abiraterone were similar (HR, 1.06; 95% CI, 0.83-1.35). In addition, there was no significant difference between the three interventions for OS. But olaparib has the highest probability of being a preferred treatment for improving rPFS and OS. Conclusion: rPFS was in favor of olaparib compared with apalutamide plus abiraterone. But there were no difference between olaparib plus abiraterone and either olaparib or apalutamide plus abiraterone. Apalutamide plus abiraterone might be the most preferred intervention in cases where AEs are involved. Systematic review registration: https://inplasy.com, identifier INPLASY2023100072.

White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan.

Characterizing how, when and where the human brain changes across the lifespan is fundamental to our understanding of developmental processes of childhood and adolescence, degenerative processes of aging, and divergence from normal patterns in disease and disorders. We aimed to provide detailed descriptions of white matter pathways across the lifespan by thoroughly characterizing white matter microstructure, white matter macrostructure, and morphology of the cortex associated with white matter pathways. We analyzed 4 large, high-quality, publicly-available datasets comprising 2789 total imaging sessions, and participants ranging from 0 to 100 years old, using advanced tractography and diffusion modeling. We first find that all microstructural, macrostructural, and cortical features of white matter bundles show unique lifespan trajectories, with rates and timing of development and degradation that vary across pathways - describing differences between types of pathways and locations in the brain, and developmental milestones of maturation of each feature. Second, we show cross-sectional relationships between different features that may help elucidate biological changes occurring during different stages of the lifespan. Third, we show unique trajectories of age-associations across features. Finally, we find that age associations during development are strongly related to those during aging. Overall, this study reports normative data for several features of white matter pathways of the human brain that will be useful for studying normal and abnormal white matter development and degeneration.

Whole-brain, gray, and white matter time-locked functional signal changes with simple tasks and model-free analysis.

Recent studies have revealed the production of time-locked blood oxygenation level-dependent (BOLD) functional MRI (fMRI) signals throughout the entire brain in response to tasks, challenging the existence of sparse and localized brain functions and highlighting the pervasiveness of potential false negative fMRI findings. "Whole-brain" actually refers to gray matter, the only tissue traditionally studied with fMRI. However, several reports have demonstrated reliable detection of BOLD signals in white matter, which have previously been largely ignored. Using simple tasks and analyses, we demonstrate BOLD signal changes across the whole brain, in both white and gray matters, in similar manner to previous reports of whole brain studies. We investigated whether white matter displays time-locked BOLD signals across multiple structural pathways in response to a stimulus in a similar manner to the cortex. We find that both white and gray matter show time-locked activations across the whole brain, with a majority of both tissue types showing statistically significant signal changes for all task stimuli investigated. We observed a wide range of signal responses to tasks, with different regions showing different BOLD signal changes to the same task. Moreover, we find that each region may display different BOLD responses to different stimuli. Overall, we present compelling evidence that, just like all gray matter, essentially all white matter in the brain shows time-locked BOLD signal changes in response to multiple stimuli, challenging the idea of sparse functional localization and the prevailing wisdom of treating white matter BOLD signals as artifacts to be removed.

Bioinformatics analysis of potential common pathogenic mechanisms for systemic lupus erythematosus and acute myocardial infarction.

BACKGROUND: Systemic lupus erythematosus (SLE) patients have a higher risk of acute myocardial infarction (AMI) compared to the general population. However, the underlying common mechanism of this association is not fully understood. This study aims to investigate the molecular mechanism of this complication. METHODS: Gene expression profiles of SLE (GSE50772) and AMI (GSE66360) were obtained from the Gene Expression Omnibus (GEO) database. Common differentially expressed genes (DEGs) in SLE and AMI were identified, and functional annotation, protein-protein interaction (PPI) network analysis, module construction, and hub gene identification were performed. Additionally, transcription factor (TF)-gene regulatory network and TF-miRNA regulatory network were constructed for the hub genes. RESULTS: 70 common DEGs (7 downregulated genes and 63 upregulated genes) were identified and were mostly enriched in signaling pathways such as the IL-17 signaling pathway, TNF signaling pathway, lipid metabolism, and atherosclerosis. Using cytoHubba, 12 significant hub genes were identified, including IL1B, TNF, FOS, CXCL8, JUN, PTGS2, FN1, EGR1, CXCL1, DUSP1, MMP9, and ZFP36. CONCLUSIONS: This study reveals a common pathogenesis of SLE and AMI and provides new perspectives for further mechanism research. The identified common pathways and hub genes may have important clinical implications for the prevention and treatment of AMI in SLE patients.