Spatiotemporal discoordination of brain spontaneous activity in major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a widespread mental health issue, impacting spatial and temporal aspects of brain activity. The neural mechanisms behind MDD remain unclear. To address this gap, we introduce a novel measure, spatiotemporal topology (SPT), capturing both the hierarchy and dynamic attributes of brain activity in depressive disorder patients. METHODS: We analyzed fMRI data from 285 MDD inpatients and 141 healthy controls (HC). SPT was assessed by coupling brain gradient measurement and time delay estimation. A nested machine learning process distinguished between MDD and HC using SPT. Person's correlation tested the link between SPT's and symptom severity, and another machine learning method predicted the gap between patients' chronological and brain age. RESULTS: SPT demonstrated significant differences between patients and healthy controls (F = 2.944, p < 0.001). Machine learning approaches revealed SPT's ability to discriminate between patients and healthy controls (Accuracy = 0.65, Sensitivity = 0.67, Specificity = 0.64). Moreover, SPT correlated with the severity of depression symptom (r = 0.32. pFDR = 0.045) and predicted the gap between patients' chronological age and brain age (r = 0.756, p < 0.001). LIMITATIONS: Evaluation of brain dynamics was constrained by MRI temporal resolution. CONCLUSIONS: Our study introduces SPT as a promising metric to characterize the spatiotemporal signature of brain function, providing insights into deviant brain activity associated with depressive disorders and advancing our understanding of their psychopathological mechanisms.

Spatio-temporal learning and explaining for dynamic functional connectivity analysis: Application to depression.

BACKGROUND: Functional connectivity has been shown to fluctuate over time. The present study aimed to identifying major depressive disorders (MDD) with dynamic functional connectivity (dFC) from resting-state fMRI data, which would be helpful to produce tools of early depression diagnosis and enhance our understanding of depressive etiology. METHODS: The resting-state fMRI data of 178 subjects were collected, including 89 MDD and 89 healthy controls. We propose a spatio-temporal learning and explaining framework for dFC analysis. A yet effective spatio-temporal model is developed to classifying MDD from healthy controls with dFCs. The model is a stacking neural network model, which learns network structure information by a multi-layer perceptron based spatial encoder, and learns time-varying patterns by a Transformer based temporal encoder. We propose to explain the spatio-temporal model with a two-stage explanation method of importance feature extracting and disorder-relevant pattern exploring. The layer-wise relevance propagation (LRP) method is introduced to extract the most relevant input features in the model, and the attention mechanism with LRP is applied to extract the important time steps of dFCs. The disorder-relevant functional connections, brain regions, and brain states in the model are further explored and identified. RESULTS: We achieved the best classification performance in identifying MDD from healthy controls with dFC data. The top important functional connectivity, brain regions, and dynamic states closely related to MDD have been identified. LIMITATIONS: The data preprocessing may affect the classification performance of the model, and this study needs further validation in a larger patient population. CONCLUSIONS: The experimental results demonstrate that the proposed spatio-temporal model could effectively classify MDD, and uncover structural and temporal patterns of dFCs in depression.

Reduced myelin content in bipolar disorder: A study of inhomogeneous magnetization transfer.

BACKGROUND: Previous neuroimaging and pathological studies have found myelin-related abnormalities in bipolar disorder (BD), which prompted the use of magnetic resonance (MR) imaging technology sensitive to neuropathological changes to explore its neuropathological basis. We holistically investigated alterations in myelin within BD patients by inhomogeneous magnetization transfer (ihMT), which is sensitive and specific to myelin content. METHODS: Thirty-one BD and 42 healthy controls (HC) were involved. Four MR metrics, i.e., ihMT ratio (ihMTR), pseudo-quantitative ihMT (qihMT), magnetization transfer ratio and pseudo-quantitative magnetization transfer (qMT), were compared between groups using analysis methods based on whole-brain voxel-level and white matter regions of interest (ROI), respectively. RESULTS: The voxel-wise analysis showed significantly inter-group differences of ihMTR and qihMT in the corpus callosum. The ROI-wise analysis showed that ihMTR, qihMT, and qMT values in BD group were significantly lower than that in HC group in the genu and body of corpus callosum, left anterior limb of the internal capsule, left anterior corona radiate, and bilateral cingulum (p < 0.001). And the qihMT in genu of corpus callosum and right cingulum were negatively correlated with depressive symptoms in BD group. LIMITATIONS: This study is based on cross-sectional data and the sample size is limited. CONCLUSION: These findings suggest the reduced myelin content of anterior midline structure in the bipolar patients, which might be a critical pathophysiological feature of BD.

Reduced coupling between global signal and cerebrospinal fluid inflow in patients with depressive disorder: A resting state functional MRI study.

BACKGROUND: Depressed patients often suffer from sleep disturbance, which has been recognized to be responsible for glymphatic dysfunction. The purpose of this study was to investigate the coupling strength of global blood­oxygen-level-dependent (gBOLD) signals and cerebrospinal fluid (CSF) inflow dynamics, which is a biomarker for glymphatic function, in depressed patients and to explore its potential relationship with sleep disturbance by using resting-state functional MRI. METHODS: A total of 138 depressed patients (112 females, age: 34.70 ± 13.11 years) and 84 healthy controls (29 females, age: 36.6 ± 11.75 years) participated in this study. The gBOLD-CSF coupling strength was calculated to evaluate glymphatic function. Sleep disturbance was evaluated using the insomnia items (item 4 for insomnia-early, item 5 for insomnia-middle, and item 6 for insomnia-late) of The 17-item Hamilton Depression Rating Scale for depressed patients, which was correlated with the gBOLD-CSF coupling strength. RESULTS: The depressed patients exhibited weaker gBOLD-CSF coupling relative to healthy controls (p = 0.022), possibly due to impairment of the glymphatic system. Moreover, the gBOLD-CSF coupling strength correlated with insomnia-middle (r = 0.097, p = 0.008) in depressed patients. Limitations This study is a cross-sectional study. CONCLUSION: Our findings shed light on the pathophysiology of depression, indicating that cerebral waste clearance system deficits are correlated with poor sleep quality in depressed patients.

Connectome architecture modulates the gray matter atrophy in major depression disorder patients with diverse suicidal ideations.

Gray matter (GM) atrophy is well documented in patients with major depressive disorder (MDD), but its underlying mechanism remains unknown. This study aimed to examine the GM atrophy in MDD patients with diverse suicidal ideations (SIs) and to explore whether those alterations were driven by connections. GM volume was estimated in 163 patients with recurrent MDD (comprising 122 with SI [MDDSI] and 41 without SI [MDDNSI]) and 134 health controls (HCs). A two-sample t-test was used to identify GM volume abnormalities in MDD patients and their subgroups. Functional connectivity was computed between pairs of aberrant GM in both patients and HCs, which were further compared with the connectivity of random brain regions. A permutation test was performed to assess its significance. Propensity score matching (PSM) was further performed to validate the main results. Compared with HCs, the MDDNSI group exhibited GM atrophy in 24 regions, with the largest effect sizes found in the frontal and parietal lobes, while the MDDSI group exhibited more widespread GM atrophy involving 49 regions, with the largest effect sizes in the frontal lobe, parietal lobe, temporal lobe, and the limbic system. Furthermore, patients and HCs exhibited significantly increased functional connectivity between regions with GM atrophy compared with randomly selected regions (p < 0.05). PSM analysis presented similar results to the main analysis. MDD patients had diverse GM atrophy features according to their SI tendency. Moreover, connectome architecture modulates the GM atrophy in MDD patients, implying the possibility that connections drive these pathological changes.

Association between gaming disorder and regional homogeneity in highly involved male adult gamers: A pilot resting-state fMRI study.

BACKGROUND: Gaming behavior can induce cerebral changes that may be related to the neurobiological features of gaming disorder (GD). Additionally, individuals with higher levels of depression or impulsivity are more likely to experience GD. Therefore, the present pilot study explored potential neurobiological correlates of GD in the context of depression and impulsivity, after accounting for video gaming behavior. METHODS: Using resting-state functional magnetic resonance imaging (fMRI), a cross-sectional study was conducted with 35 highly involved male adult gamers to examine potential associations between GD severity and regional homogeneity (ReHo) in the entire brain. A mediation model was used to test the role of ReHo in the possible links between depression/impulsivity and GD severity. RESULTS: Individuals with greater GD severity showed increased ReHo in the right Heschl's gyrus and decreased ReHo in the right hippocampus (rHip). Furthermore, depression and impulsivity were negatively correlated with ReHo in the rHip, respectively. More importantly, ReHo in the rHip was found to mediate the associations between depression/impulsivity and GD. CONCLUSIONS: These preliminary findings suggest that GD severity is related to ReHo in brain regions associated with learning/memory/mood and auditory function. Higher levels of depression or impulsivity may potentiate GD through the functional activity of the hippocampus. Our findings advance our understanding of the neurobiological differences behind GD symptoms in highly involved gamers.

A scientometric study of tobacco and alcohol use as risk factors for oral cavity health.

Background/purpose: Tobacco and alcohol are the well-known carcinogenic agents of oral cavity health. The purpose of this study was to investigate the scientometric characteristics of alcohol and tobacco use and oral health. Materials and methods: The papers on alcohol and tobacco use and oral cavity were published since 1885 and 1895, respectively. All the eligible papers were retrieved on March 20, 2023 from the Scopus database. Results: There are 2529 and 1545 papers on tobacco smoking and alcohol drinking and oral cavity in the Scopus database, respectively. Based on the frequency of keywords in all included papers, both smoking and drinking are involved in mouth neoplasms, oral cancer, leukoplakia, and periodontal diseases. In the papers on tobacco and alcohol use and oral cavity, the same research keywords confirm tobacco and alcohol use associate with oral cancer risk possibly through influencing genetics and gene and protein expression. For the distinctive keywords, nicotine, smoking cessation, and electronic cigarette are unique keywords of tobacco use. Acetaldehyde, alcohol dehydrogenase, and alcohol metabolism are unique ones of alcohol use. Conclusion: This study for the first time reports the scientometric characteristics of tobacco and alcohol use and oral health, which might aid healthcare authorities to promote tobacco and alcohol control measures focused on the necessities of their population.

Shared and specific neurobiology in bipolar disorder and unipolar disorder: Evidence based on the connectome gradient and a transcriptome-connectome association study.

BACKGROUND: Distinguishing bipolar disorder (BD) and unipolar disorder (UD) remains challenging. To identify the common and diagnosis-specific neuropathological alterations and their potential molecular mechanisms in patients with UD and BD (with a current depressive episode). METHODS: Resting-state functional magnetic resonance imaging was obtained from 279 participants (95 BD patients, 107 UD patients and 77 health controls). Connectome gradients analysis was performed to explore the shared and diagnosis-specific gradient alterations in BD and UD. The Allen Human Brain Atlas data was used to explore the potential gene mechanisms of the gradient alterations. RESULTS: BD and UD had shared hierarchical disorganisation, including downgrading and contraction from the unimodal sensory networks (vision and sensorimotor) to the transmodal cognitive networks (limbic, frontoparietal, dorsal attention, and default) (all P < 0.05, FDR corrected) in gradient 1 and gradient 2. The BD patients had specific connectome gradient dysfunction in the subcortical network. Moreover, the hierarchical disorganisation was closely correlated with profiles of gene expression specific to the neuroglial cells in the prefrontal cortex in BD and UD, while the most correlated gene ontology biological processes and function were concentrated in synaptic signalling, calcium ion binding, and transmembrane transporter activity. CONCLUSION: These findings reveal the shared and diagnosis-specific neurobiological mechanism underlying BD and UD patients, which advances our understanding of the neuromechanisms of these disorders.

Food Thermal Labels are a Source of Dietary Exposure to Bisphenol S and Other Color Developers.

To test the hypothesis that migration from the thermal labels on plastic film packaging is a major source of exposure to bisphenols and alternative color developers in food, we analyzed 140 packaging materials from packaged fresh food purchased in North America. No bisphenol A (BPA) was detected in either the packaging samples or thermal labels. However, significant amounts of bisphenol S (BPS) and alternative color developers (up to 214 µg/cm2) were present in thermal labels; their relative occurrence varied among stores. In a controlled experiment, we wrapped fish in film with a thermal label for 5 days at 4 °C. The fish in contact with the label contained BPS (≤1140 ng/g wet weight [ww]), 4-hydroxyphenyl 4-isoprooxyphenylsulfone (D-8) (≤230 ng/g ww), bis(2-chloroethyl)ether-4,4'-dihydroxydiphenyl sulfone monomer (D-90) (≤3.41 ng/g ww), and/or Pergafast-201 (≤1.87 ng/g ww). The corresponding film samples were then tested using migration cells for 10 days; significantly higher BPS migration was observed systematically from the films with thermal labels compared to plain films. This study provides evidence, for the first time, that BPS and alternative thermal label color developers migrate from packaging materials into food. Further, BPS migration significantly exceeded the European Union Specific Migration Limit (50 ng/g ww), suggesting that further risk assessment studies are warranted.

Identifying suicide attempts, ideation, and non-ideation in major depressive disorder from structural MRI data using deep learning.

The present study aims to identify suicide risks in major depressive disorders (MDD) patients from structural MRI (sMRI) data using deep learning. In this paper, we collected the sMRI data of 288 MDD patients, including 110 patients with suicide ideation (SI), 93 patients with suicide attempts (SA), and 85 patients without suicidal ideation or attempts (NS). And we developed interpretable deep neural network models to classify patients in three tasks including SA-versus-SI, SA-versus-NS, and SI-versus-NS, respectively. Furthermore, we interpreted the models by extracting the important features that contributed most to the classification, and further discussed these features or ROI/brain regions.

Suicide risk stratification among major depressed patients based on a machine learning approach and whole-brain functional connectivity.

BACKGROUND: Suicide risk stratification and individual-level prediction among major depressive disorder (MDD) is important but unrecognized. Here, we construct models to detect suicidality in MDD using machine learning (ML) and whole-brain functional connectivity (FC). METHODS: A cross-sectional assessment was conducted on 200 subjects, including 126 MDD with high suicide risk (HSR; 73 patients with suicidal ideation [SI], 53 patients with suicidal attempts [SA]), 36 patients with low suicide risk (LSR) and 38 healthy controls (HCs). Whole-brain FC features were calculated, the least absolute shrinkage and selection operator (LASSO) method was used for feature selection. A support vector machine (SVM) was performed to build models to distinguish MDD from HCs, and for suicide risk stratification among MDD. Leave-one-out cross-validation (LOOCV) was performed for validation. RESULTS: The models constructed using SVM on whole-brain FC had powerful classification efficiency in screening MDD from HCs (accuracy = 88.50 %), and in suicide risk stratification among MDD patients (with accuracy = 84.56 % and 74.60 % in classifying patients with HSR or LSR, and SA or SI, respectively). Subsequent analysis demonstrated that intra-network dysconnectivity in the sensorimotor network and inter-network dysconnectivity between the default and dorsal attention network could characterize HSR and SA in MDD, separately. LIMITATIONS: This study was a single center cohort study without external validation. CONCLUSION: These findings indicate ML approaches are useful in suicide risk stratification among MDD based on whole-brain FC, which may help to identify individuals with different suicide risks in MDD and provide an individual-level prediction.

Development of quantitative structure-retention relationship models to improve the identification of leachables in food packaging using non-targeted analysis.

Quantitative structure-retention relationship (QSRR) models can be used to predict the chromatographic retention time of chemicals and facilitate the identification of unknown compounds, notably with non-targeted analysis. In this study, QSRR models were developed from the data obtained for 178 pure chemical standards and four types of analytical columns (C18, phenylhexyl, pentafluorophenyl, cyano) in liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS). First, different data partitioning ratios and feature selection methods [random forest (RF) and support vector machine (SVM)] were tested to build models to predict chromatographic retention times based on 2D molecular descriptors. The internal and external performances of the non-linear (RF) and corresponding linear predictive models were systematically compared, and RF models resulted in better predictive capacities [p < 0.05, with an average PVE (proportion of variance explained) value of 0.89 ± 0.02] than linear models (0.79 ± 0.03). For each column, the resulting model was applied to identify leachables from actual plastic packaging samples. An in-depth investigation of the top 20 most intense molecular features revealed that all false-positives could be identified as outliers in the QSRR models (outside of the 95% prediction bands). Furthermore, analyzing a sample on multiple chromatographic columns and applying the associated QSRR models increased the capacity to filter false positives. Such an approach will contribute to a more effective identification of unknown or unexpected leachables in plastics (e.g. non-intended added substances), therefore refining our understanding of the chemical risks associated with food contact materials.

Exploring possible benefits of Litsea cubeba Pers. extract on growth, meat quality, and gut flora in white-feather broilers.

White-feather broiler chickens are the dominant species in global poultry meat production. Yet there is growing concern about their health, quality, and growth efficiency. While feed additives, often antibiotics or synthetic chemicals, are used to maintain the health of the animals, drug resistance limits their use. Litsea cubeba (Lour.) Pers., a traditional Chinese herb with antibiotic-like benefits but without the risk of drug resistance, has not yet been explored as an additive to broiler diets. In the present study, broilers of the AA+ hybrid strain were randomly divided into three groups of 16: a control group (regular feed), a low-dose group (1.25 g/kg added L. cubeba extract), and a high-dose group (2.50 g/kg added L. cubeba extract). After 35 days, we found that the extract had no effect on growth. However, gut flora analysis revealed that both doses of the extract had a positive influence on amino acid content and minor unsaturated fatty acids, thus improving the flavor and nutritional value of the meat. These findings suggest that L. cubeba extract, at either dose, could serve as a sustainable alternative to antibiotics, thus reducing the risk of drug resistance while improving meat quality, nutrition, and flavor.

Corrigendum: PHLDA1 Suppresses TLR4-Triggered Proinflammatory Cytokine Production by Interaction With Tollip.

[This corrects the article DOI: 10.3389/fimmu.2022.731500.].

PHLDA1 Suppresses TLR4-Triggered Proinflammatory Cytokine Production by Interaction With Tollip.

Pleckstrin homology-like domain, family A, member 1 (PHLDA1) has been reported to be expressed in many mammalian tissues and cells. However, the functions and exact mechanisms of PHLDA1 remain unclear. In this study, we found that PHLDA1 expression was significantly altered in macrophages after exposure to lipopolysaccharide (LPS) in vitro, suggesting that PHLDA1 may be involved in the regulation of TLR4 signaling pathway activated by LPS. PHLDA1 attenuated the production of LPS-stimulated proinflammatory cytokines (TNF-α, IL-6, and IL-1ß). Further research showed that the phosphorylation levels of some important signal molecules in TLR4/MyD88-mediated MAPK and NF-κB signaling pathways were reduced by PHLDA1, which in turn impaired the transcription factors NF-κB and AP1 nuclear translocation and their responsive element activities. Furthermore, we found that PHLDA1 repressed LPS-induced proinflammatory cytokine production via binding to Tollip which restrained TLR4 signaling pathway. A mouse model of endotoxemia was established to confirm the above similar results. In brief, our findings demonstrate that PHLDA1 is a negative regulator of LPS-induced proinflammatory cytokine production by Tollip, suggesting that PHLDA1 plays an anti-inflammatory role through inhibiting the TLR4/MyD88 signaling pathway with the help of Tollip. PHLDA1 may be a novel therapeutic target in treating endotoxemia.

Reversible splenial lesion syndrome with mental disorders as only manifestation.

BACKGROUND: Reversible splenial lesion syndrome (RESLES) was reported to be associated with variable entities. However, much less is known about the cases in which the mental disorders act as the only manifestation. METHOD: Total ten patients of RESLES were obtained in this retrospective study from Shenzhen Kangning Hospital. T1-fluid attenuated inversion recovery (T1-FLAIR), T2-weighted images, T2-FLAIR, diffusion-weighted images and apparent diffusion coefficient map were performed on all the patients. Clinical manifestations, laboratory examination results, magnetic resonance imaging (MRI) findings, treatments and outcomes were analyzed. RESULT: All patients showed different mental disorders as the only manifestation. There were two cases of alcohol abuse, one of Asperger's syndrome with malnutrition, one of infection and one of invasive pituitary adenoma. The other cases were diagnosis as major depressive disorder, dissociative and conversion disorders, undifferentiated somatoform disorder, unspecified psychosis and bipolar disorder, respectively. Three patients were completely recovered while the clinical symptoms of rest seven patients partially recovered at the follow-up three months later. Oval-shaped lesion centered on the splenial of corpus callosum (SCC) was observed in all patients using MRI. The lesions of SCC of all patients were completely resolved within five weeks. CONCLUSIONS: We found that RESLES might only showed mental symptoms. On the one hand, for the patients with acute mental disorders, clinicians should be alert to the possibility of RESLES caused by physical disease. On the other hand, we suggest that mental disorder might be a precipitating factor of RESLES.

Different patterns of functional and structural alterations of hippocampal sub-regions in subcortical vascular mild cognitive impairment with and without depression symptoms.

In addition to cognitive impairments, depression symptoms were reported in subcortical vascular mild cognitive impairment. Although hippocampal alterations were associated with cognitive decline in subcortical vascular mild cognitive impairment, the neural mechanism underlying depression symptoms remains unclear. Thus, a cohort of 18 patients with depression symptoms, 17 patients without depression symptoms, and 23 normal controls was used. Functionally, significantly altered resting-state functional connectivity between hippocampal emotional sub-region and right posterior cingulate cortex, between hippocampal cognitive sub-region and right inferior parietal gyrus and between hippocampal perceptual sub-region and left inferior temporal gyrus were identified among three groups. Structurally, significantly altered structural associations between hippocampal emotional sub-region and 6 frontal regions/right pole part of superior temporal gyrus/right inferior occipital gyrus, between hippocampal cognitive sub-region and right orbital part of inferior frontal gyrus /right anterior cingulate cortex, and between hippocampal perceptual and right orbital part of inferior frontal gyrus / left inferior temporal gyrus / left thalamus were identified among the three groups. Further analyses also showed correlations between functional connectivity and depression symptoms and/or cognitive impairments of patients. Together, these results showed different patterns of functional and structural alterations of the hippocampal sub-regions in the subcortical vascular mild cognitive impairment with and without depression, which might be specially associated with the depression symptoms and cognitive impairments in these patients.

Variation of soil organic carbon and physical properties in relation to land uses in the Yellow River Delta, China.

Soil physical properties and soil organic carbon (SOC) are considered as important factors of soil quality. Arable land, grassland, and forest land coexist in the saline-alkali reclamation area of the Yellow River Delta (YRD), China. Such different land uses strongly influence the services of ecosystem to induce soil degradation and carbon loss. The objective of this study is to evaluate the variation of soil texture, aggregates stability, and soil carbon affected by land uses. For each land use unit, we collected soil samples from five replicated plots from "S" shape soil profiles to the depth of 50 cm (0-5, 5-10, 10-20, 20-30, and 30-50 cm). The results showed that the grassland had the lowest overall sand content of 39.98-59.34% in the top 50 cm soil profile. The content of soil aggregates > 0.25 mm (R0.25), mean weight diameter and geometric mean diameter were significantly higher in grassland than those of the arable and forest land. R0.25, aggregate stability in arable land in the top 30 cm were higher than that of forest land, but lower in the soil profile below 20 cm, likely due to different root distribution and agricultural practices. The carbon management index (CMI) was considered as the most effective indicator of soil quality. The overall SOC content and CMI in arable land were almost the lowest among three land use types. In combination with SOC, CMI and soil physical properties, we argued that alfalfa grassland had the advantage to promote soil quality compared with arable land and forest land. This result shed light on the variations of soil properties influenced by land uses and the importance to conduct proper land use for the long-term sustainability of the saline-alkali reclamation region.

Comparative Study on Phytochemical Profiles and Antioxidant Capacities of Chestnuts Produced in Different Geographic Area in China.

This study aimed to systematically assess the phenolic profiles and antioxidant capacities of 21 chestnut samples collected from six geographical areas of China. All these samples exhibit significant differences (p < 0.05) in total phenolic contents (TPC), total flavonoids content (TFC), condensed tannin content (CTC) and antioxidant capacities assessed by DPPH free radical scavenging capacity (DPPH), ABTS free radical scavenging capacities (ABTS), ferric reducing antioxidant power (FRAP), and 14 free phenolic acids. Chestnuts collected from Fuzhou, Jiangxi (East China) exhibited the maximum values for TPC (2.35 mg GAE/g), CTC (13.52 mg CAE/g), DPPH (16.74 µmol TE/g), ABTS (24.83 µmol TE/g), FRAP assays (3.20 mmol FE/100g), and total free phenolic acids (314.87 µg/g). Vanillin and gallic acids were found to be the most abundant free phenolic compounds among other 14 phenolic compounds detected by HPLC. Overall, the samples from South China revealed maximum mean values for TPC, CTC, DPPH, and ABTS assays. Among the three chestnut varieties, Banli presented prominent mean values for all the assays. These finding will be beneficial for production of novel functional food and developing high-quality chestnut varieties.

Alterations of White Matter Microstructure in Subcortical Vascular Mild Cognitive Impairment with and without Depressive Symptoms.

BACKGROUND: Depressive symptoms were thought to increase the risk of vascular dementia. Previous studies reported widespread white matter damages in the subcortical vascular mild cognitive impairment (svMCI), but little is known about the mechanism of depressive symptoms in svMCI. OBJECTIVE: In the current study, we aim to explore the white matter microstructural alterations in svMCI with depressive symptoms, and their associations with clinical measurements. METHODS: Fifty-eight subjects including 18 svMCI with depression (svMCI+D), 17 svMCI without depression (svMCI-D), and 23 normal controls (NC) were included in the study. Voxel-based analyses were performed on fractional anisotropy (FA) and mean diffusivity (MD). RESULTS: Compared to NC, both svMCI groups showed decreased FA in the bilateral insula and the left precentral gyrus, and increased MD in the cerebellum. Compared to svMCI-D, svMCI+D showed increased FA in left precentral gyrus. Moreover, svMCI+D showed significant correlation between the increased MD in the cerebellum and the Hamilton Depression Rating Scale (HAMD) scores. CONCLUSION: Our findings of white matter alterations might be associated with executive function and memory performance in the svMCI patients. Moreover, the structural alterations in the cerebellum might underlie the mechanism of depressive symptoms in svMCI patients.