Altered functional-structural coupling may predict Parkinson's patient's depression.

We aimed to elucidate the neurobiological basis of depression in Parkinson's disease and identify potential imaging markers for depression in patients with Parkinson's disease. We recruited 43 normal controls (NC), 46 depressed Parkinson's disease patients (DPD) and 56 non-depressed Parkinson's disease (NDPD). All participants underwent routine T2-weighted, T2Flair, and resting-state scans on the same 3.0 T magnetic resonance imaging (MRI) scanner at our hospital. Pre-processing includes calculating surface-based Regional Homogeneity (2DReHo) and cortical thickness. Then we defined the correlation coefficient between 2DReHo and cortical thickness as the functional-structural coupling index. Between-group comparisons were conducted on the Fisher's Z-transformed correlation coefficients. To identify specific regions of decoupling, the 2DReHo for each participant were divided by cortical thickness at each vertex, followed by threshold-free cluster enhancement (TFCE) multiple comparison correction. Binary logistic regression analysis was performed with DPD as the dependent variable, and significantly altered indicators as the independent variables. Receiver operating characteristic curves were constructed to compare the diagnostic performance of individual predictors and combinations using R and MedCalc software. DPD patients exhibited a significantly lower whole-brain functional-structural coupling index than NDPD patients and NC. Abnormal functional-structural coupling was primarily observed in the left inferior parietal lobule and right primary and early visual cortices in DPD patients. Receiver operating characteristic analysis revealed that the combination of cortical functional-structural coupling, surface-based ReHo, and thickness had the best diagnostic performance, achieving a sensitivity of 65% and specificity of 77.7%. This is the first study to explore the relationship between functional and structural changes in DPD patients and evaluate the diagnostic performance of these altered correlations to predict depression in Parkinson's disease patients. We posit that these changes in functional-structural relationships may serve as imaging biomarkers for depression in Parkinson's disease patients, potentially aiding in the classification and diagnosis of Parkinson's disease. Additionally, our findings provide functional and structural imaging evidence for exploring the neurobiological basis of depression in Parkinson's disease.

Alterations in cortical volume and complexity in Parkinson's disease with depression.

AIMS: The aim of this study is to investigate differences in gray matter volume and cortical complexity between Parkinson's disease with depression (PDD) patients and Parkinson's disease without depression (PDND) patients. METHODS: A total of 41 PDND patients, 36 PDD patients, and 38 healthy controls (HC) were recruited and analyzed by Voxel-based morphometry (VBM) and surface-based morphometry (SBM). Differences in gray matter volume and cortical complexity were compared using the one-way analysis of variance (ANOVA) and correlated with the Hamilton Depression Scale-17 (HAMD-17) scores. RESULTS: PDD patients exhibited significant cortical atrophy in various regions, including bilateral medial parietal-occipital-temporal lobes, right dorsolateral temporal lobes, bilateral parahippocampal gyrus, and bilateral hippocampus, compared to HC and PDND groups. A negative correlation between the GMV of left precuneus and HAMD-17 scores in the PDD group tended to be significant (r = -0.318, p = 0.059). Decreased gyrification index was observed in the bilateral insular and dorsolateral temporal cortex. However, there were no significant differences found in fractal dimension and sulcal depth. CONCLUSION: Our research shows extensive cortical structural changes in the insular cortex, parietal-occipital-temporal lobes, and hippocampal regions in PDD. This provides a morphological perspective for understanding the pathophysiological mechanism underlying depression in Parkinson's disease.

Cortical gyrification pattern of depression in Parkinson's disease: a neuroimaging marker for disease severity?

Background: Although the study of the neuroanatomical correlates of depression in Parkinson's Disease (PD) is gaining increasing interest, up to now the cortical gyrification pattern of PD-related depression has not been reported. This study was conducted to investigate the local gyrification index (LGI) in PD patients with depression, and its associations with the severity of depression. Methods: LGI values, as measured using FreeSurfer software, were compared between 59 depressed PD (dPD), 27 non-depressed PD (ndPD) patients and 43 healthy controls. The values were also compared between ndPD and mild-depressed PD (mi-dPD), moderate-depressed PD (mo-dPD) and severe-depressed PD (se-dPD) patients as sub-group analyses. Furthermore, we evaluated the correlation between LGI values and depressive symptom scores within dPD group. Results: Compared to ndPD, the dPD patients exhibited decreased LGI in the left parietal, the right superior-frontal, posterior cingulate and paracentral regions, and the LGI values within these areas negatively correlated with the severity of depression. Specially, reduced gyrification was observed in mo-dPD and involving a larger region in se-dPD, but not in mi-dPD group. Conclusion: The present study demonstrated that cortical gyrification is decreased within specific brain regions among PD patients with versus without depression, and those changes were associated with the severity of depression. Our findings suggested that cortical gyrification might be a potential neuroimaging marker for the severity of depression in patients with PD.

Surface-Based Functional Alterations in Early-Onset and Late-Onset Parkinson's Disease: A Multi-Modal MRI Study.

This study used a surface-based method to investigate brain functional alteration patterns in early-onset Parkinson's disease (EOPD) and late-onset Parkinson's disease (LOPD) to provide more reliable imaging indicators for the assessment of the two subtypes. A total of 58 patients with Parkinson's disease were divided into two groups according to age at onset: EOPD (≤50 years; 16 males and 15 females) and LOPD (>50 years; 17 males and 10 females) groups. Two control groups were recruited from the community: young adults (YC; ≤50 years; 8 males and 19 females) and older adults (OC; >50 years; 12 males and 10 females). No significant differences were observed between the EOPD and YC groups or the LOPD and OC groups in terms of age, sex, education, and MMSE scores (p > 0.05). No statistically significant differences were observed between the EOPD and LOPD groups in terms of education, H-Y scale, UPDRS score, or HAMD score (p > 0.05). Data preprocessing and surface-based regional homogeneity (2D-ReHo) calculations were subsequently performed using the MATLAB-based DPABIsurf software. The EOPD group showed decreased 2D-ReHo values in the left premotor area and right dorsal stream visual cortex, along with increased 2D-ReHo values in the left dorsolateral prefrontal cortex. In patients with LOPD, 2D-ReHo values were decreased in bilateral somatosensory and motor areas and the right paracentral lobular and mid-cingulate. The imaging characterization of surface-based regional changes may serve useful as monitoring indicators and will help to better understand the mechanisms underlying divergent clinical presentations.

Neural functional network of early Parkinson's disease based on independent component analysis.

This work explored neural network changes in early Parkinson's disease: Resting-state functional magnetic resonance imaging was used to investigate functional alterations in different stages of Parkinson's disease (PD). Ninety-five PD patients (50 early/mild and 45 early/moderate) and 37 healthy controls (HCs) were included. Independent component analysis revealed significant differences in intra-network connectivity, specifically in the default mode network (DMN) and right frontoparietal network (RFPN), in both PD groups compared to HCs. Inter-network connectivity analysis showed reduced connectivity between the executive control network (ECN) and DMN, as well as ECN-left frontoparietal network (LFPN), in early/mild PD. Early/moderate PD exhibited decreased connectivity in ECN-LFPN, ECN-RFPN, ECN-DMN, and DMN-auditory network, along with increased connectivity in LFPN-cerebellar network. Correlations were found between ECN-DMN and ECN-LFPN connections with UPDRS-III scores in early/mild PD. These findings suggest that PD progression involves dysfunction in multiple intra- and inter-networks, particularly implicating the ECN, and a wider range of abnormal functional networks may mark the progression of the disease.

Abnormal intra- and inter-network functional connectivity of brain networks in early-onset Parkinson's disease and late-onset Parkinson's disease.

Objective: The purpose of this study is to look into the altered functional connectivity of brain networks in Early-Onset Parkinson's Disease (EOPD) and Late-Onset Parkinson's Disease (LOPD), as well as their relationship to clinical symptoms. Methods: A total of 50 patients with Parkinson' disease (28 EOPD and 22 LOPD) and 49 healthy controls (25 Young Controls and 24 Old Controls) were admitted to our study. Employing independent component analysis, we constructed the brain networks of EOPD and Young Controls, LOPD and Old Controls, respectively, and obtained the functional connectivity alterations in brain networks. Results: Cerebellar network (CN), Sensorimotor Network (SMN), Executive Control Network (ECN), and Default Mode Network (DMN) were selected as networks of interest. Compared with their corresponding health controls, EOPD showed increased functional connectivity within the SMN and ECN and no abnormalities of inter-network functional connectivity were found, LOPD demonstrated increased functional connectivity within the ECN while decreased functional connectivity within the CN. Furthermore, in LOPD, functional connectivity between the SMN and DMN was increased. The functional connectivity of the post-central gyrus within the SMN in EOPD was inversely correlated with the Unified Parkinson's Disease Rating Scale Part III scores. Age, age of onset, and MMSE scores are significantly different between EOPD and LOPD (p < 0.05). Conclusion: There is abnormal functional connectivity of networks in EOPD and LOPD, which could be the manifestation of the associated pathological damage or compensation.

Diagnosing cervical lymph node metastasis in oral squamous cell carcinoma based on third-generation dual-source, dual-energy computed tomography.

OBJECTIVES: To investigate the potential of dual-energy computed tomography (DECT) parameters in identifying metastatic cervical lymph nodes in oral squamous cell carcinoma (OSCC) patients and to explore the relationships between DECT and pathological features. METHODS: Clinical and DECT data were collected from patients who underwent radical resection of OSCC and cervical lymph node dissection between November 2019 and June 2021. Microvascular density was assessed using the Weidner counting method. The electron density (ED) and effective atomic number (Zeff) in non - contrast phase and iodine concentration (IC), normalized IC, slope of the energy spectrum curve (λHU), and dual-energy index (DEI) in parenchymal phase were compared between metastatic and non - metastatic lymph nodes. Student's t-test, Pearson's rank correlation, and receiver operating characteristic curves were performed. RESULTS: The inclusion criteria were met in 399 lymph nodes from 103 patients. Metastatic nodes (n = 158) displayed significantly decreased ED, IC, normalized IC, λHU, and DEI values compared with non-metastatic nodes (n = 241) (all p < 0.01). Strong correlations were found between IC (r = 0.776), normalized IC (r = 0.779), λHU (r = 0.738), DEI (r = 0.734), and microvascular density. Area under the curve (AUC) for normalized IC performed the highest (0.875) in diagnosing metastatic nodes. When combined with the width of nodes, AUC increased to 0.918. CONCLUSION: DECT parameters IC, normalized IC, λHU, and DEI reflect pathologic changes in lymph nodes to a certain extent, and aid for detection of metastatic cervical lymph nodes from OSCC. KEY POINTS: • Electron density, iodine concentration, normalized iodine concentration, λHU, and dual-energy index values showed significant differences between metastatic and non-metastatic nodes. • Strong correlations were found between iodine concentration, normalized iodine concentration, slope of the spectral Hounsfield unit curve, dual-energy index, and microvascular density. • DECT qualitative parameters reflect the pathologic changes in lymph nodes to a certain extent, and aid for the detection of metastatic cervical lymph nodes from oral squamous cell carcinoma.

Resting-state brain network in Parkinson's disease with different degrees of depression.

Objective: The aim of this study is to explore the neural network mechanism of Parkinson's disease (PD) with different degrees of depression using independent component analysis (ICA) of the functional connectivity changes in the forehead, limbic system, and basal ganglia regions. Methods: A total of 106 patients with PD were divided into three groups: PD with moderate-severe depression (PDMSD, n = 42), PD with mild depression (PDMD, n = 29), and PD without depression (PDND, n = 35). Fifty gender- and age-matched healthy subjects were recruited as a control group (HC). Three-dimensional T1-weighted image and resting-state functional magnetic resonance imaging (RS-fMRI) data were collected. Results: Different functional connectivity was observed in the left precentral gyrus, right precuneus, right inferior frontal gyrus, right medial and paracingulate gyrus, left supplementary motor area, right brain insula, and the inferior frontal gyrus of the left orbit among the four groups (ANOVA, P < 0.05, Voxel size > 5). Both PDMD and PDMSD exhibited increased functional connectivity in the superior-posterior default-mode network (spDMN) and left frontoparietal network (LFPN); they also exhibited a decreased functional connectivity in the interior Salience Network (inSN) when compared with the PDND group. The functional connectivity within the inSN network was decreased in the PDMSD group when compared with the PDMD group (Alphasim correction, P < 0.05, voxel size > 5). Conclusion: PD with different degrees of depression has abnormal functional connectivity in multiple networks, which is an important neurobiological basis for the occurrence and development of depression in PD. The degree of decreased functional connectivity in the inSN network is related to the degree of depression in patients with PD-D, which can be an imaging marker for PD to judge the severity of depression.

Abnormalities in the Fractional Amplitude of Low-Frequency Fluctuation and Functional Connectivity in Parkinson's Disease With Excessive Daytime Sleepiness.

Background: Excessive daytime sleepiness (EDS) is one of the most important non-motor symptoms of Parkinson's disease (PD), and its neuropathologic basis is still unclear. Objective: This study investigated the changes of neuronal activity in PD patients with EDS (PD-EDS) in the resting state. Methods: Forty-three PD patients were recruited and divided into the PD-EDS group (n = 21) and PD-NEDS group (PD patients without excessive daytime sleepiness, n = 22) according to the Epworth sleepiness scale (ESS) scores. Patients in both groups received resting-state functional magnetic resonance imaging (rs-fMRI). The differences in fractional amplitude of low-frequency fluctuation (fALFF) between the two groups, correlations between fALFF and ESS, and functional connection (FC) between the brain regions with different fALFF values and the whole brain were analyzed. Results: PD-EDS patients exhibited a decreased fALFF in the Cingulum-Ant-R, but an increased fALFF in the Putamen-R and Thalamus-L when compared with PD-NEDS patients; an increased functional connectivity between these three seed regions with different fALFF values and the right medial frontal gyrus, bilateral superior temporal gyrus, left insular, and right precuneus was observed (p < 0.05), but a deceased functional connectivity between these three seed regions and the right cerebellum anterior lobe/right brainstem, right middle temporal gyrus and inferior temporal gyrus, right hippocampus/parahippocampal gyrus, right medial cingulate gyrus and bilateral middle occipital gyrus was observed (p < 0.05). The value of fALFF was negatively correlated with the ESS score in the Cingulum-Ant-R, but positively correlated with the ESS score in the Putamen-R and Thalamus-L. Conclusions: EDS in PD patients may be associated with changes in brain neuron activity and functional connectivity.

Selective antibacterial activities and storage stability of curcumin-loaded nanoliposomes prepared from bovine milk phospholipid and cholesterol.

Present study prepared curcumin-loaded nanoliposomes using bovine milk, krill phospholipids and cholesterol; and investigated the effects of cholesterol on membrane characteristics, storage stability and antibacterial properties of the curcumin nanoliposomes. Bovine milk phospholipids which have higher saturation than krill phospholipids resulted in formation of curcumin-loaded nanoliposomes with higher encapsulation efficiency (84.78%), larger absolute value of zeta potential and vesicle size (size: 159.15 ± 5.27 nm, zeta potential: -28.3 ± 0.62 mV). Cholesterol helps to formation of a more hydrophobic, compact and tighter bilayer membrane structure which improved the storage stability of nanoliposomes under alkaline (66.25 ± 0.46%), heat (43.25 ± 0.69%) and sunlight (49.44 ± 1.78%) conditions. In addition, curcumin-loaded nanoliposomes can effectively target infectious bacteria which secrete pore-forming toxins such as Staphylococcus aureus by causing the bacterial cell wall to lysis. Findings from present work can guide future development of novel antibacterial agents for use in food preservation.

Changes in Degree Centrality of Network Nodes in Different Frequency Bands in Parkinson's Disease With Depression and Without Depression.

BACKGROUND: Depression induces an early onset of Parkinson's disease (PD), aggravates dyskinesia and cognitive impairment, and accelerates disease progression. However, it is very difficult to identify and diagnose PD with depression (PDD) in the early clinical stage. Few studies have suggested that the changes in neural networks are associated with PDD, while degree centrality (DC) has been documented to be effective in detecting brain network changes. OBJECTIVES: The objectives of this study are to explore DC changes between patients with PDD and without depression (PDND) and to find the key brain hubs involved with depression in PD patients. METHODS: One hundred and four PD patients and 54 healthy controls (HCs) underwent brain resting-state functional magnetic resonance imaging. The Data Processing and Analysis of Brain Imaging and Resting-State Functional Magnetic Resonance Data Analysis Toolkit were used for processing and statistical analysis. The DC value of each frequency band was calculated. One-way analysis of variance and a two-sample t-test for post hoc comparison were used to compare the differences of the DC values in different frequency bands among PDD, PDND, and healthy control group. Gaussian random field was used for multiple comparison correction. Pearson correlation analysis was performed between each individual's DC map and clinical indicators. RESULTS: The DC value of different brain regions changed in PDD and PDND in different frequency bands. The prefrontal lobe, limbic system, and basal ganglia were the main brain regions involved. PDD patients showed a wider range and more abnormal brain areas in the slow-4 frequency band (0.027-0.073 Hz) compared to the HCs. PDD showed a decreased DC value in the medial frontal gyrus, bilateral cuneus gyrus, right lingual gyrus, bilateral supplementary motor area (SMA), bilateral superior frontal gyrus, and left paracentral lobule, but an increased DC value in the bilateral brainstem, midbrain, bilateral parahippocampal gyrus, cerebellum, left superior temporal gyrus, bilateral insula, left fusiform gyrus, and left caudate nucleus in the traditional frequency band (0.01-0.08 Hz) compared to PDND patients. PDND patients displayed more abnormal functions in the basal ganglia in the slow-4 frequency band. CONCLUSION: The DC changes in PDD and PDND are frequency dependent and frequency specific. The medial frontal gyrus, SMA, and limbic system may be the key hubs for depression in PD.