Predicting node degree centrality with the node prominence profile

To Investigate the Mechanism of Qinpi Tongfeng Formula in Treating Acute Gouty Arthritis by UHPLC-Q-Orbitrap-MS, Network Pharmacology and Experimental Validation

Background

Acute gouty arthritis (AGA) is characterized by the accumulation of monosodium urate crystals within the joints, leading to inflammation and severe pain. Western medicine treatments have limitations in addressing this condition. Previous studies have shown the efficacy of Qinpi Tongfeng formula (QPTFF) in treating AGA, but further investigation is needed to understand its mechanism of action.

Methods

We used ultra-high-performance liquid chromatography tandem Q-Exactive Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap-MS) to identify compounds in QPTFF. Target proteins regulated by these compounds were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, Chemistry Database, and Swiss Target Prediction Database. AGA-related targets were searched and screened from various databases, including Genecards, PharmGKB, Drugbank, etc. Intersection targets of QPTFF and AGA were analyzed for protein-protein interaction networks, GO function enrichment, and KEGG pathway enrichment. We then verified QPTFF's mechanism of action using an AGA rat model, assessing pathological changes via H&E staining and target expression via ELISA, RT-qPCR, and Western blot.

Results

UHPLC-Q-Orbitrap-MS identified 207 compounds in QPTFF, with 55 selected through network pharmacology. Of 589 compound-regulated targets and 1204 AGA-related targets, 183 potential targets were implicated in QPTFF's treatment of AGA. Main target proteins included IL-1β, NFKBIA, IL-6, TNF, CXCL8, and MMP9, with the IL-17 signaling pathway primarily regulated by QPTFF. Experimental results showed that medium and high doses of QPTFF significantly reduced serum inflammatory factors and MMP-9 expression, and inhibited IL-17A, IL-6, IKK-β, and NF-κB p65 mRNA and protein expression in AGA rats compared to the model group.

Conclusion

Key targets of QPTFF include IL-1β, NFKBIA, IL-6, TNF-α, CXCL8, and MMP9. QPTFF effectively alleviates joint inflammation in AGA rats, with high doses demonstrating no liver or kidney toxicity. Its anti-inflammatory mechanism in treating AGA involves the IL-17A/NF-κB p65 signaling pathway.

Flight training changes the brain functional pattern in cadets

Introduction

To our knowledge, this is the first study to use MRI (Magnetic Resonance Imaging) before and after an intensive flight training. This study aimed to investigate the effectiveness of flight training in civil flying cadets.

Methods

The civil flying cadets and controls completed two study visits. Visit 1 was performed in 2019, and high spatial resolution structural image and resting-state functional MRI data were collected. The second visit was completed in 2022. In addition to the MRI data mentioned above, participants completed the cognitive function assessment at the second visit.

Results

Mixed-effect regression model analysis found that flight training enhanced the degree centrality (DC) values of the left middle frontal gyrus and left lingual gyrus. The subsequent correlation calculation analysis suggested a possible relationship between these alterations and cognitive function.

Discussion

These results suggest that flight training might promote the DC value of the prefrontal and occipital cortices and, in turn, enhance their executive function.

The functional connectivity of the middle frontal cortex predicts ketamine’s outcome in major depressive disorder

Background

Ketamine, a robust antidepressant, has promising potential in the treatment of major depressive disorder (MDD). However, it does not work for all MDD patients, and the mechanism underlying its anti-depressive effects is unclear. Researchers have explored the mechanisms of ketamine action in MDD patients through MRI, a technique that measures brain activity intuitively. Notably, many MRI results were inconsistent because they selected different brain regions as seeds, particularly with respect to functional connectivity (FC) analysis. To eliminate the influence of prior seeds as much as possible, we used the significantly different results in degree centrality (DC) analysis as seeds to explore the FC changes in MDD patients to identify an imaging biomarker of ketamine’s effect.

Methods

Forty-four MDD patients and 45 healthy controls (HCs) were included in the study. Patients, aged 18–65, received six intravenous ketamine injections over 12 days. Depressive symptoms were estimated and MRI scans were performed at baseline and the day after the sixth infusion. We estimated FC differences between responders, non-responders and HCs using the region that showed significant differences between responders and non-responders in DC analysis as the seed. The correlation between the MADRS changes and zFC values was performed, and the potential of zFC values to be a neuroimaging biomarker was explored using the receiver operating characteristic curve.

Result

Compared with non-responders, responders had significantly decreased DC values in the right middle frontal gyrus (MFG). In the analysis of FC using the region that showed significant differences in DC as a seed, there was a significant difference in the region of the right supplementary motor area (SMA) among responders, non-responders, and HCs. This region also overlapped with the bilateral median cingulate gyrus. In post hoc analysis, responders had higher FC than non-responders and HCs, and non-responders had lower FC than HCs. Importantly, the FC between the MFG and SMA (overlapping bilateral median cingulate gyrus) was correlated with the improvement of symptoms, which was estimated by the Mongomery-Asberg Depression Scale (MADRS). FC has the potential to be an imaging biomarker that can predict the ketamine effect in MDD patients according to the receiver operating characteristic curve analysis.

Conclusion

Our results revealed that FC between the SMG and SMA and mACC was highly correlated with depressive symptoms and has the potential to be a neuroimaging biomarker to predict the effect of ketamine in MDD.

Shared and Unique Effects of Long-Term Administration of Methylphenidate and Atomoxetine on Degree Centrality in Medication-Naïve Children With Attention-Deficit/Hyperactive Disorder

BACKGROUND

Although methylphenidate (MPH) and atomoxetine (ATX) can improve clinical symptoms and functional impairments in attention deficit/hyperactive disorder (ADHD), the underlying psychopharmacological mechanisms have not been clearly elucidated. Therefore, we aimed to explore the shared and unique neurologic basis of these 2 medications in alleviating the clinical symptoms and functional impairments observed in ADHD.

METHODS

Sixty-seven ADHD and 44 age-matched children with typical development were included and underwent resting-state functional magnetic resonance imaging scans at baseline. Then patients were assigned to MPH, ATX, or untreated subgroups, based on the patients' and their parents' choice, for a 12-week follow-up and underwent a second functional magnetic resonance imaging scan. The treatment effect on degree centrality (DC) was identified and correlated with clinical symptoms and functional impairments in the ADHD group.

RESULTS

Both MPH and ATX normalized the DC value in extensive brain regions mainly involving fronto-cingulo-parieto-cerebellum circuits. However, ATX showed limited significant effects on the cerebellum compared with ADHD at baseline. The improvements in clinical symptoms were correlated with increased DC in the right inferior temporal gyrus in both MPH and ATX subgroups but showed opposite effects. The alleviation of functional impairments in the school/learning domain negatively correlated with decreased DC in the bilateral cerebellum after MPH treatment, and the family functional domain positively correlated with decreased DC in the cerebellum and negatively correlated with decreased DC in the postcentral gyrus after ATX treatment.

CONCLUSIONS

Both MPH and ATX can normalize abnormal brain functions that mainly involve the fronto-cingulo-parieto-cerebellum circuit in ADHD. Furthermore, the 2 medications showed shared and unique effects on brain functions to alleviate clinical symptoms and functional impairment.

The alterations of degree centrality in the frontal lobe of patients with panic disorder

Objective: The brain network in panic disorder (PD) is still an intriguing issue for research. In this study, we hoped to investigate the role of DC (degree centrality) for the pathophysiology of PD, especially for the fear network. Methods: We enrolled 60 patients with PD and 60 controls in the current study. The gender and age were matched for two groups. All participants received the resting-state functional magnetic resonance imaging to survey the baseline brain activity. Then the DC values of all participants were using REST toolbox. We also compared the DC values between PD and controls. The statistical threshold was set as FDR (false discovery rate) < 0.05. Results: The DC values were significantly lower in the right superior frontal gyrus of PD patients compared to controls (FDR < 0.05). In addition, a negative correlation between the DC values and panic severity was observed in the right superior frontal gyrus and left inferior frontal gyrus. However, there was no significant association between the DC values and illness duration. Conclusion: The DC seemed significantly altered in the frontal lobe of PD patients. The role of the frontal lobe might be more emphasized in the pathophysiology research for PD.

Alterations in Degree Centrality and Functional Connectivity in Parkinson's Disease Patients With Freezing of Gait: A Resting-State Functional Magnetic Resonance Imaging Study

Objective

Freezing of gait (FOG) is a common disabling motor symptom in Parkinson's disease (PD), but the potential pathogenic mechanisms are still unclear.

Methods

A total of 22 patients with PD with FOG (PD-FOG), 28 patients with PD without FOG (PD-nFOG), and 33 healthy controls (HCs) were recruited in this study. Degree centrality (DC)-a graph theory-based measurement of global connectivity at the voxel level by measuring the number of instantaneous functional connections between one region and the rest of the brain-can map brain hubs with high sensitivity, specificity, and reproducibility. DC was used to explore alterations in the centrality of PD-FOG correlated with brain node levels. PD-FOG cognitive network dysfunction was further revealed via a seed-based functional connectivity (FC) analysis. In addition, correlation analyses were carried out between clinical symptoms and acquired connectivity measurement.

Results

Compared to the PD-nFOG group, the PD-FOG group showed remarkably increased DC values in the right middle frontal gyrus (RMFG). There were no significant differences in other gray matter regions. Importantly, the clinical severity of FOG was related to the mean DC values in the RMFG. This brain region served as a seed in secondary seed-based FC analysis, and we further found FC changes in the right precuneus, right inferior frontal gyrus, right superior frontal gyrus (SFG), and cerebellum.

Conclusion

Increased RMFG activity and FC network alterations in the middle frontal cortex with the precuneus, inferior, and SFG, and the cerebellum may have great potential in brain dysfunction in PD with FOG.

Alteration in topological properties of brain functional network after 2-year high altitude exposure: A panel study

INTRODUCTION

High altitude (HA) exposure leads to cognitive impairment while the underlying mechanism is still unclear. Brain functional network is crucial for advanced functions, and its alteration is implicated in cognitive decline in multiple diseases. The aim of current study was to investigate the topological changes in HA-exposed brain functional network.

METHODS

Based on Shaanxi-Tibet immigrant cohort, neuropsychological tests and resting-state functional MRI were applied to evaluate the participants' cognitive function and functional connection (FC) changes, respectively. GRETNA toolbox was used to construct the brain functional network. The gray matter was parcellated into 116 anatomically defined regions according to Automated Anatomical Labeling atlas. Subsequently, the mean time series for each of the 116 regions were extracted and computed for Pearson's correlation coefficients. The relation matrix was further processed and seen as brain functional network. Correlation between functional network changes and neuropsychological results was also examined.

RESULTS

The cognitive performance was impaired by HA exposure as indicated by neuropsychological test. HA exposure led to alterations of degree centrality and nodal efficiency in multiple brain regions. Moreover, two subnetworks were extracted in which the FCs significantly decreased after exposure. In addition, the alterations in FCs within above two subnetworks were significantly correlated with changes of memory and reaction time.

CONCLUSIONS

Our results suggest that HA exposure modulates the topological property of functional network and FCs of some important regions, which may impair the attention, perception, memory, motion ignition, and modulation processes, finally decreasing cognitive performance in neuropsychological tests.

Neurocognitive Graphs of First-Episode Schizophrenia and Major Depression Based on Cognitive Features

Neurocognitive deficits are frequently observed in patients with schizophrenia and major depressive disorder (MDD). The relations between cognitive features may be represented by neurocognitive graphs based on cognitive features, modeled as Gaussian Markov random fields. However, it is unclear whether it is possible to differentiate between phenotypic patterns associated with the differential diagnosis of schizophrenia and depression using this neurocognitive graph approach. In this study, we enrolled 215 first-episode patients with schizophrenia (FES), 125 with MDD, and 237 demographically-matched healthy controls (HCs). The cognitive performance of all participants was evaluated using a battery of neurocognitive tests. The graphical LASSO model was trained with a one-vs-one scenario to learn the conditional independent structure of neurocognitive features of each group. Participants in the holdout dataset were classified into different groups with the highest likelihood. A partial correlation matrix was transformed from the graphical model to further explore the neurocognitive graph for each group. The classification approach identified the diagnostic class for individuals with an average accuracy of 73.41% for FES vs HC, 67.07% for MDD vs HC, and 59.48% for FES vs MDD. Both of the neurocognitive graphs for FES and MDD had more connections and higher node centrality than those for HC. The neurocognitive graph for FES was less sparse and had more connections than that for MDD. Thus, neurocognitive graphs based on cognitive features are promising for describing endophenotypes that may discriminate schizophrenia from depression.