Yuqun Zhang

Impact Factors Analysis of the Enthalpy Method and the Effective Heat Capacity Method on the Transient Nonlinear Heat Transfer in Phase Change Materials (PCMs)

An experimental method was used for validating the heat transfer within phase change materials (PCMs). The two models, enthalpy and effective heat capacity models, were implemented and three impact factors were analyzed. The results showed that it should not calculate using the same temperature range for the PCMs with different melting and freezing ranges. Narrower temperature range can make the enthalpy method more accurate. Also, the liquid fraction should be taken into account if the phase change had not completed. In addition, the proper treatment of latent heat made the effective heat capacity method more accurate than the enthalpy method.

Divergent topological architecture of the default mode network as a pretreatment predictor of early antidepressant response in major depressive disorder

Identifying a robust pretreatment neuroimaging marker would be helpful for the selection of an optimal therapy for major depressive disorder (MDD). We recruited 82 MDD patients [n = 42 treatment-responsive depression (RD) and n = 40 non-responding depression (NRD)] and 50 healthy controls (HC) for this study. Based on the thresholded partial correlation matrices of 58 specific brain regions, a graph theory approach was applied to analyse the topological properties. When compared to HC, both RD and NRD patients exhibited a lower nodal degree (Dnodal) in the left anterior cingulate gyrus; as for RD, the Dnodal of the left superior medial orbitofrontal gyrus was significantly reduced, but the right inferior orbitofrontal gyrus was increased (all P < 0.017, FDR corrected). Moreover, the nodal degree in the right dorsolateral superior frontal cortex (SFGdor) was significantly lower in RD than in NRD. Receiver operating characteristic curve analysis demonstrated that the λ and nodal degree in the right SFGdor exhibited a good ability to distinguish nonresponding patients from responsive patients, which could serve as a specific maker to predict an early response to antidepressants. The disrupted topological configurations in the present study extend the understanding of pretreatment neuroimaging predictors for antidepressant medication.

Amygdala Atrophy and Its Functional Disconnection with the Cortico-Striatal-Pallidal-Thalamic Circuit in Major Depressive Disorder in Females

Background Major depressive disorder (MDD) is approximately twice as common in females than males. Furthermore, female patients with MDD tend to manifest comorbid anxiety. Few studies have explored the potential anatomical and functional brain changes associated with MDD in females. Therefore, the purpose of the present study was to investigate the anatomical and functional changes underlying MDD in females, especially within the context of comorbid anxiety. Methods In this study, we recruited antidepressant-free females with MDD (N = 35) and healthy female controls (HC; N = 23). The severity of depression and anxiety were evaluated by the Hamilton Depression Rating Scale (HAM-D) and the Hamilton Anxiety Rating Scale (HAM-A), respectively. Structural and resting-state functional images were acquired on a Siemens 3.0 Tesla scanner. We compared the structural volumetric differences between patients and HC with voxel-based morphometry (VBM) analyses. Seed-based voxel-wise correlative analyses were used to identify abnormal functional connectivity. Regions with structural deficits showed a significant correlation between gray matter (GM) volume and clinical variables that were selected as seeds. Furthermore, voxel-wise functional connectivity analyses were applied to identify the abnormal connectivity relevant to seed in the MDD group. Results Decreased GM volume in patients was observed in the insula, putamen, amygdala, lingual gyrus, and cerebellum. The right amygdala was selected as a seed to perform connectivity analyses, since its GM volume exhibited a significant correlation with the clinical anxiety scores. We detected regions with disrupted connectivity relevant to seed primarily within the cortico-striatal-pallidal-thalamic circuit. Conclusions Amygdaloid atrophy, as well as decreased functional connectivity between the amygdala and the cortico-striatal-pallidal-thalamic circuit, appears to play a role in female MDD, especially in relation to comorbid anxiety.

Prognostic value of imbalanced interhemispheric functional coordination in early therapeutic efficacy in major depressive disorder

This study aims to explore the early response of antidepressant therapy by measuring the voxel-mirrored homotopic connectivity (VMHC) in major depressive disorder (MDD). Eighty-two MDD patients [n=42 treatment-responsive depression (RD) and n=40 non-responding depression (NRD)] and n=50 normal controls (NC) underwent clinical measures and a magnetic resonance imaging scan, and the VMHC values were calculated. Receiver operating characteristic (ROC) curve analysis was applied to determine the capability of altered VMHC to distinguish NRD. The NRD showed significantly decreased VMHC in bilateral precuneus (PCU) and inferior temporal gyrus (ITG), and increased VMHC in middle frontal gyrus (MFG) and caudate nucleus as compared to RD. When compared with NC, the NRD exhibited reduced VMHC in bilateral cerebellum anterior lobe, thalamus and postcentral gyrus. Moreover, VHMC in medial frontal gyrus, postcentral gyrus and precentral gyrus were significantly decreased in RD. Correlation analysis showed that reduced VMHC in PCU was negatively correlated with the baseline HAMD score of the NRD group. The ROC curve indicated that the combined changes of the three regional VMHC (PCU, ITG and MFG) could effectively identify NRD. The current study suggests that interhemispheric asynchrony may represents a novel neural trait underlying the prediction of early therapeutic outcome in MDD.

Abnormal brain functional connectivity leads to impaired mood and cognition in hyperthyroidism: a resting-state functional MRI study

Patients with hyperthyroidism frequently have neuropsychiatric complaints such as lack of concentration, poor memory, depression, anxiety, nervousness, and irritability, suggesting brain dysfunction. However, the underlying process of these symptoms remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), we depicted the altered graph theoretical metric degree centrality (DC) and seed-based resting-state functional connectivity (FC) in 33 hyperthyroid patients relative to 33 healthy controls. The peak points of significantly altered DC between the two groups were defined as the seed regions to calculate FC to the whole brain. Then, partial correlation analyses were performed between abnormal DC, FC and neuropsychological performances, as well as some clinical indexes. The decreased intrinsic functional connectivity in the posterior lobe of cerebellum (PLC) and medial frontal gyrus (MeFG), as well as the abnormal seed-based FC anchored in default mode network (DMN), attention network, visual network and cognitive network in this study, possibly constitutes the latent mechanism for emotional and cognitive changes in hyperthyroidism, including anxiety and impaired processing speed.

Structural and Functional Connectivity of Default Mode Network underlying the Cognitive Impairment in Late-onset Depression

To identify the association between the functional and structural changes of default mode network (DMN) underlying the cognitive impairment in Late-onset depression (LOD), 32 LOD patients and 39 normal controls were recruited and underwent resting-state fMRI, DTI scans, and cognitive assessments. Seed-based correlation analysis was conducted to explore the functional connectivity (FC) of the DMN. Deterministic tractography between FC-impaired regions was performed to examine the structural connectivity (SC). Partial correlation analyses were employed to evaluate the cognitive association of those altered FC and SC. Compared with controls, LOD patients showed decreased FC between DMN and the cingulo-opercular network (CON), as well as the thalamus. Decreased FA and increased RD of these fiber tracts connecting DMN with CON were found in LOD patient. The DMN-CON FC and the FA, RD of the fiber tracts were both significantly correlated with the cognitive performance. Therefore, the cognitive impairment in LOD might be associated with the decreased FC between the DMN and the CON, which probably resulted from the demyelination of the white matter.

Towards a multi protein and mRNA expression of biological predictive and distinguish model for post stroke depression

Previous studies suggest that neurotrophic factors participate in the development of stroke and depression. So we investigated the utility of these biomarkers as predictive and distinguish model for post stroke depression (PSD). 159 individuals including PSD, stroke without depression (Non-PSD), major depressive disorder (MDD) and normal control groups were recruited and examined the protein and mRNA expression levels of vascular endothelial growth factor (VEGF), vascular endothelial growth factor receptors (VEGFR2), placental growth factor (PIGF), insulin-like growth factor (IGF-1) and insulin-like growth factor receptors (IGF-1R). The chi-square test was used to evaluate categorical variable, while nonparametric test and one-way analysis of variance were applied to continuous variables of general characteristics, clinical and biological changes. In order to explore the predictive and distinguish role of these factors in PSD, discriminant analysis and receiver operating characteristic curve were calculated. The four groups had statistical differences in these neurotrophic factors (all P < 0.05) except VEGF concentration and IGF-1R mRNA (P = 0.776, P = 0.102 respectively). We identified these mRNA expression and protein analytes with general predictive performance for PSD and Non-PSD groups [area under the curve (AUC): 0.805, 95% CI, 0.704-0.907, P < 0.001]. Importantly, there is an excellent predictive performance (AUC: 0.984, 95% CI, 0.964-1.000, P < 0.001) to differentiate PSD patients from MDD patients. This was the first study to explore the changes of neurotrophic factors family in PSD patients, the results intriguingly demonstrated that the combination of protein and mRNA expression of biological factors could use as a predictive and discriminant model for PSD.

Triple templating of graphitic carbon nitride to enhance photocatalytic properties

Graphitic carbon nitride materials show some promising properties for applications such as photocatalytic water splitting. However, the conversion efficiency is still low due to factors such as a low surface area and limited light absorption. In this paper, we describe a “triple templating” approach to generating porous graphitic carbon nitride. The introduction of pores on several length-scales results in enhanced photocatalytic properties.

The protein and mRNA expression levels of glial cell line-derived neurotrophic factor in post stroke depression and major depressive disorder

Previous studies have indicated that the level of glial cell line-derived neurotrophic factor (GDNF) may be correlated with stroke and depression. Here, we investigated whether GDNF can be a discriminant indicator for post stroke depression (PSD). 159 participants were divided into four groups: PSD, stroke without depression (Non-PSD), major depressive disorder (MDD) and normal control (NC) group, and the protein and mRNA expression levels of GDNF in serum were measured. The results showed that only MDD group had statistical difference in protein and mRNA levels compared with the other three groups (Bonferroni test, P < 0.05). The results of receiver operating curve (ROC) analysis supported GDNF as general distinguishing models in PSD and MDD groups with the area under the curve (AUC) at 0.797 (P < 0.001) and 0.831 (P < 0.001) respectively. In addition, the Spearman analysis demonstrated that the GDNF protein level negatively correlated with the value of Hamilton depression rating scale (HAMD) in PSD patients (correlation coefficient = −0.328, P = 0.047). Together, these findings suggest the protein and mRNA expression levels of GDNF decreased in patients with depression. GDNF may serve as a potential biomarker for differential diagnosis of PSD from MDD patients.

Distinctive pretreatment features of bilateral nucleus accumbens networks predict early response to antidepressants in major depressive disorder

The pretreatment neuroimaging markers from the resting-state brain network that could predict the early response to antidepressants are still unclear. The aim of the present study was to identify the performance of reward network features for discriminating patients with a dampened response to antidepressants. A total of 81 major depressive disorder (MDD) patients (44 patients with treatment-responsive depression (RD) and 37 patients with non-responding depression (NRD)) and 43 healthy controls (HC) underwent resting-state functional magnetic resonance imaging scans and clinical estimates. Bilateral nucleus accumbens (NAcc)-based networks were constructed for further functional connectivity (FC) analysis. The FC of the right superior frontal gyrus (SFG) (area under curve (AUC) = 0.837) and left parahippocampus (AUC = 0.770) within the left NAcc reward network, as well as the FC of the left SFG (AUC = 0.827) within the right NAcc reward network, could distinguish NRD subjects from RD subjects relatively well. Taken together, when considering the distinctive connectional pattern of the bilateral reward circuits, the synthetical differentiating effect was achieved to an optimal performance for discriminating NRD patients (AUC = 0.869), with balanced sensitivity (0.838) and specificity (0.818). The distinct pretreatment characteristics of the reward network make specific contributions to the early response to antidepressants and establish a promising imaging predictor for the classification of early efficacy.