The increasing flood disasters have led to serious losses and damage around the world, especially in the developing countries. Nanjing, China, has suffered from the frequent urban flood in recent ...years, which has hindered its sustainable development. This study assessed urban flood resilience in Nanjing based on the resilience dimensions of social, economic, natural, physical, human, political and institutional resilience. Results revealed that urban flood resilience and subdomain resilience showed the increasing trend from 1990 to 2017. Natural, social, natural, physical and political resilience influenced urban flood resilience a lot before 2006, while economic institutional, human and physical resilience made significant contributions after 2006. Economic, political and physical resilience showed the significant direct effect on urban flood resilience and political resilience had the mediating effect in economic and physical resilience.
Gut bacteria play an important role in the pathogenesis of Parkinson's disease (PD). However, the alteration of fecal microbiota in PD with cognitive impairment remains unexplored. This study aimed ...to explore whether the gut microbiota of patients with PD having mild cognitive impairment (PD-MCI) were different from those with PD having normal cognition (PD-NC) and from healthy controls (HC). Also, the study probed the association between altered gut microbiota and cognitive ability in patients with PD.
The fecal bacteria composition and short-chain fatty acids of 13 patients with PD-MCI, 14 patients with PD-NC, and 13 healthy spouses were analyzed using 16S ribosomal RNA sequencing and gas chromatography-mass spectrometry.
Compared with HC, the fecal microbial diversities increased in patients with PD-MCI and PD-NC. After adjusting the influence of age, sex, body mass index, education, and constipation using the statistical method, the relative abundances of two families (Rikenellaceae and Ruminococcaceae) and four genera (
, and
) were found to be higher in the feces of the PD-MCI group compared with the other two groups. Moreover, the abundance of genus
and
decreased obviously in the PD-MCI group compared with the PD-NC group. Further, the abundance of genera
, and
negatively correlated with cognition ability.
Compared with HC and patients with PD-NC, the gut microbiota of patients with PD-MCI was significantly altered, particularly manifesting in enriched genera from Porphyromonadaceae family and decreased the abundance of genera
and
.
To investigate the molecular mechanism of communication network factor 1 (CCN1) regulating pentylenetetrazol (PTZ)-induced epileptogenesis, deepen the understanding of epilepsy seizure pathogenesis, ...and provide new drug action targets for its clinical prevention and treatment. Differentially expressed genes (DEGs) on microarrays GSE47516 and GSE88992 were analyzed online using GEO2R. Pathway enrichment and protein–protein interaction network (PPI) analysis of DEGs were carried out using Metascape. Brain tissue samples of severe traumatic brain injury patients (named Healthy group) and refractory epilepsy patients (named Epilepsy group) were obtained and analyzed by qRT-PCR and immunohistochemistry (IHC) staining. A PTZ-induced epilepsy mouse model was established and verified. Morphological changes of neurons in mouse brain tissue were detected using hematoxylin and eosin (HE) staining. qRT-PCR was conducted to detect the mRNA expressions of apoptosis-associated proteins Bax, Caspase-3 and bcl2. TUNEL staining was performed to detect brain neuron apoptosis. The levels of myocardial enzymology, GSH, MDA and ROS in blood of mouse were detected by biochemical assay. CCN1 expression was increased in epilepsy brain tissue samples. CCN1 decreasing effectively prolongs seizure incubation period and decreases seizure duration. Silencing of CCN1 also reduces neuronal damage and apoptosis, decreases mRNA and protein expression of proapoptotic proteins Bax and Caspase-3, increases mRNA expression of antiapoptotic protein Bcl2. Moreover, decrease of CCN1 decreases myocardial enzymatic indexes CK and CK-MB levels, reduces myocardial tissue hemorrhage, and relieves oxidative stress response in hippocampal and myocardial tissue. CCN1 expression is increased in epileptic samples. CCN1 decreasing protects brain tissue by attenuating oxidative stress and inhibiting neuronal apoptosis triggered by PTZ injection, which probably by regulating Nrf2/HO-1 pathway.
Graphical Abstract
The dichotomized brain system is a concept that was generalized from the 'dual syndrome hypothesis' to explain the heterogeneity of cognitive impairment, in which anterior and posterior brain systems ...are independent but partially overlap. The dopaminergic system acts on the anterior brain and is responsible for executive function, working memory, and planning. In contrast, the cholinergic system acts on the posterior brain and is responsible for semantic fluency and visuospatial function. Evidence from dopaminergic/cholinergic imaging or functional neuroimaging has shed significant insight relating to the involvement of the cerebellum in the cognitive process of patients with Parkinson's disease. Previous research has reported evidence that the cerebellum receives both dopaminergic and cholinergic projections. However, whether these two neurotransmitter systems are associated with cognitive function has yet to be fully elucidated. Furthermore, the precise role of the cerebellum in patients with Parkinson's disease and cognitive impairment remains unclear. Therefore, in this review, we summarize the cerebellar dopaminergic and cholinergic projections and their relationships with cognition, as reported by previous studies, and investigated the role of the cerebellum in patients with Parkinson's disease and cognitive impairment, as determined by functional neuroimaging. Our findings will help us to understand the role of the cerebellum in the mechanisms underlying cognitive impairment in Parkinson's disease.
Abstract
Background
Chorea-acanthocytosis (ChAc) is a rare hereditary autosomal recessive neurodegenerative disorder caused by pathogenic variants of the Vacuolar Protein Sorting 13 homolog A (
...VPS13A
) gene. The variant spectrum of
VPS13A
has not been completely elucidated. This study reports two novel heterozygous
VPS13A
pathogenic variants in ChAc that expand the variant spectrum of
VPS13A
.
Case presentation
We described a case of a 29-year-old man with typical clinical manifestations of ChAc, including chorea, orofacial lingual dyskinesia, vocal tics, elevated serum biochemical indicators, increased acanthocytes in peripheral blood, and caudate nucleus atrophy. Next-generation sequencing revealed two heterozygous variants of
VPS13A
: a nonsense variant (NM_033305.2: c.8215G > T, p. Glu2739Ter) and a deletion variant in the exons 25–31.
Conclusion
The identified nonsense variant gives rise to premature translation termination, while the deletion variant is expected to cause a significant in-frame deletion of amino acid residues in the encoded protein. Both variants are considered to be pathogenic and result in loss-of-function proteins. These findings have implications for the genetic counseling of patients with
VPS13A
variants.
•Wetland Degradation Index (WDI) was constructed on a pixel-by-pixel basis.•WDI incorporates lake shrinkage index (LSI), vegetation/soil degradation index.•LSI considers long-term continuous ...variations of water extent with Landsat images.•First assessment on lake wetland degradation in Bashang Plateau, China.
Continuous monitoring of wetland dynamics and regional-scale assessment of wetland degradation are important to understand wetland ecosystem processes and to formulate restoration measures. The lake wetlands in Bashang Plateau play vital roles in providing essential resources and maintaining biodiversity in North China, while they were not fully investigated in previous studies. In addition, previous studies on wetland degradation assessment mostly relied on wetland area change every five or ten years. Continuous dynamics of wetlands was rarely considered. In this study, we developed a new wetland degradation index (WDI) to assess lake wetland degradation in Bashang Plateau based on time series Landsat imagery from 1985 to 2020 on Google Earth Engine platform. WDI integrates three indicators, namely lake shrinkage index (LSI), vegetation degradation index (VDI) and soil degradation index (SDI), which represents hydrodynamics of wetland inundation, vegetation, and soil conditions of wetlands, respectively. Different from previous research that utilized remotely sensed image to extract wetland every five or ten years, the LSI considers time-series continuous dynamics of lake water inundations and the transitions between water and non-water on a pixel-by-pixel basis. Our results showed that small lake wetlands with area less than 8 ha are dominant in Bashang Plateau. Both the number and the area of lake wetlands showed large interannual variations. The number (area) of lake wetlands reached 1715 (31,419 ha) in 1995–1996 and were only 493 (7,717 ha) in 2009–2010. The total area of the lake wetlands in 2019–2020 was only around 1/3 of that in 1995–1996. The LSI, VDI, SDI, as well as WDI demonstrate large spatial variations among the lake wetlands and within the lake wetlands. Wetlands in the western and central subregions experienced more severe degradation than those in the eastern subregion, and the edge of the wetlands normally showed more severe degradation. The resulted degradation grades are consistent with our field investigations. Among the 11 counties in Bashang Plateau, Zhangbei (ZB) county in the western subregion has the largest area with severe and very severe degradation grades. Degradation of lake wetlands was mainly associated with groundwater level declination which was induced by anthropogenic activities and economic development. The proposed WDI in this study can be widely applicable for regional-scale wetland degradation assessment using remote sensing techniques and thus further help decision making in lake wetland conservation and restoration.
Macrophage migration inhibitory factor (MIF) is a pro-inflammatory cytokine. Chronic inflammation induced by amyloid β proteins (Aβ) is one prominent neuropathological feature in Alzheimer's disease ...(AD) brain.
Elisa, Western blot, and immunohistochemical staining analysis were performed to examine the level of MIF protein in CSF and brain tissues. MTT and LDH assays were used to examine the neurotoxicity, and the Morris Water Maze test was performed to examine the cognitive function in the MIF
/APP23 transgenic mice.
MIF expression was upregulated in the brain of AD patients and AD model mice. Elevated MIF concentration was detected in the cerebrospinal fluid of AD patients but not in that of the patients suffering from mild cognitive impairment and vascular dementia. Reduced MIF expression impaired learning and memory in the AD model mice. MIF expression largely associates with Aβ deposits and microglia. The binding assay revealed a direct association between MIF and Aβ oligomers. Neurons instead of glial cells were responsible for the secretion of MIF upon stimulation by Aβ oligomers. In addition, overexpression of MIF significantly protected neuronal cells from Aβ-induced cytotoxicity.
Our study suggests that neuronal secretion of MIF may serve as a defense mechanism to compensate for declined cognitive function in AD, and increased MIF level could be a potential AD biomarker.
Introduction
Previous studies have found that white matter (WM) alterations might be correlated in Parkinson’s disease (PD) patients with cognitive impairment. This study aimed to investigate WM ...structural network connectome alterations in PD patients with mild cognitive impairment (PD-MCI) and assess the relationship between cognitive impairment and structural topological network changes in PD patients.
Methods
All 31 healthy controls (HCs) and 71 PD patients (43 PD-NC and 28 PD-MCI) matched for age, sex and education underwent 3.0 T MRI and diffusion tensor imaging (DTI) scan. Graph theoretical analyses and network-based statistical (NBS) analyses were performed to identify the structural WM networks and subnetwork changes in PD-MCI.
Results
PD-MCI patients showed significantly decreased global efficiency (
E
glob
) and increased shortest path length (
L
p
) compared with the HC group. Several nodal efficiencies showed significant differences in multiple brain regions among the three groups. The nodal efficiency of the orbitofrontal part was closely related to the overall cognitive ability and multiple sub-cognitive domains. Moreover, NBS analyses identified eight one-connect subnetworks, three two-connect subnetworks and two multi-connect subnetworks with reduced connectivity that characterizes the WM structural organization in PD-MCI patients. The two multi-connect subnetworks were located on the bilateral lobe, and both were centered on the orbitofrontal part.
Conclusions
This study provided new evidence that PD with cognitive dysfunction is associated with WM structural alterations. The nodal efficiency and sub-network analyses focusing on the orbitofrontal part might provide new ideas to explore the physiological mechanism of PD-MCI.
Precise global solar radiation (GSR) data are indispensable to the design, planning, operation, and management of solar radiation utilization equipment. Some examples prove that the uncertainty of ...the prediction of solar radiation provides more value than deterministic ones in the management of power systems. This study appraises the potential of random forest (RF), V-support vector regression (V-SVR), and a resilient backpropagation artificial neural network (Rprop-ANN) for daily global solar radiation (DGSR) point prediction from average relative humidity (RHU), daily average temperature (AT), and daily sunshine duration (SD). To acquire more accurate predictions of DGSR and examine the influence of historical DGSR on the performance of point prediction models, two different model inputs are considered: (1) three meteorological variables and (2) the lags of DGSR and three meteorological variables. Then, two interval prediction methods are developed by introducing the KDE to out-of-bag (OOB), introducing kernel density estimation (KDE) to split conformal (SC) based on the three machine learning models. The two methods for interval prediction are denoted as OOB-KDE and SC-KDE. The mean absolute error (MAE), mean relative error (MRE), and Kendall rank correlation (Kendall) are used to assess the point prediction models. The performance of interval prediction methods is evaluated by the prediction interval coverage probability (PICP), prediction interval normalized average width (PINAW), and coverage width criteria (CWC). The following conclusions are drawn from this study. First, the V-SVR model performs best with the lowest mean absolute error (MAE) of 0.016 and mean relative error (MRE) of 0.001. Second, the lags of DGSR improve the prediction accuracy by about 30%. Third, the OOB-KDE and SC-KDE methods improved the quality of the prediction interval (PI). OOB-KDE improved CWC by 81%, and SC-KDE improved CWC by 99.99%. Fourth, the best interval prediction result is obtained using the SC-KDE method using the V-SVR model. The average difference between its PICP and prediction interval nominal coverage (PINC) is only 3% of the PINC, and its PINAW is less than 0.007.
Recently, there has been an increasing emphasis on applications of pattern recognition and neuroimaging techniques in the effective and accurate diagnosis of psychiatric or neurological disorders. In ...the present study, we investigated the whole-brain resting-state functional connectivity patterns of Parkinson's disease (PD), which are expected to provide additional information for the clinical diagnosis and treatment of this disease. First, we computed the functional connectivity between each pair of 116 regions of interest derived from a prior atlas. The most discriminative features based on Kendall tau correlation coefficient were then selected. A support vector machine classifier was employed to classify 21 PD patients with 26 demographically matched healthy controls. This method achieved a classification accuracy of 93.62% using leave-one-out cross-validation, with a sensitivity of 90.47% and a specificity of 96.15%. The majority of the most discriminative functional connections were located within or across the default mode, cingulo-opercular and frontal-parietal networks and the cerebellum. These disease-related resting-state network alterations might play important roles in the pathophysiology of this disease. Our results suggest that analyses of whole-brain resting-state functional connectivity patterns have the potential to improve the clinical diagnosis and treatment evaluation of PD.
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