The Dynamic Change in Wage Gap between Urban Residents and Rural Migrants in Chinese Cities

Although a significant wage gap has been found in many previous studies between urban workers and rural migrants in Chinese cities, it is still not clear how such a wage gap may evolve over time. This paper uses both a dynamic wage decomposition method and economic assimilation model with pooled cross-sectional data from the China Household Income Project Survey (CHIPS) of 1999 and 2002 to investigate the change in the wage gap between urban workers and rural migrants over time and its determinants in Chinese cities. The estimation results show that (1) there is a widening on-average wage gap between urban workers and rural migrants across the two surveyed years in Chinese cities, mainly caused by the decline in the return to education for rural migrants; (2) rural migrants can catch up with the wage level of their urban counterparts as the time they reside in the host cities increases, but because of the decline in the speed of catching-up over time, rural migrants cannot obtain wages comparable totheir urban counterparts in their life time, and more importantly well-educated rural migrants do not seem to have a significant advantage in this wage assimilation process than the lowlypoorly-educated ones. Both findings suggest that there might be discrimination against well-educated rural migrants which prevents them from obtaining a fair wage in the Chinese urban labour market.Wage differential, Migration

Using neuroimaging to understand cognitive impairment in patients with symptomatic carotid artery disease

Introduction Patients with symptomatic carotid artery disease have increased risk of cognitive impairment. Multiple mechanisms of cognitive impairment have been proposed. However, the contribution of each mechanism to cognitive impairment and the interrelation between these mechanisms remain unclear. Lesional and non-lesional damage of brain tissues may lead to cognitive impairment in patients with symptomatic carotid artery disease. The research presented aims to use whole brain statistical brain mapping and quantitative neuroimaging techniques to understand vascular cognitive impairment (VCI) in a group of patients with symptomatic carotid artery disease. Methods Studies presented in this thesis were based on available multimodal MRI and cognitive performance data from a study in patients with symptomatic carotid artery disease. Totally 108 subjects had FLAIR and diffusion MRI scans and 62 of them had resting-state fMRI scans in a 3T MRI scanner. All participants (n=108) underwent cognitive assessments using Addrenbrooke’s cognitive examination-revised (ACE-R). Voxel-based lesion symptom mapping (VLSM) technique was used to identify the contribution of ischaemic lesion presence to cognitive performance. Tract-based spatial statistics (TBSS) approach was used to investigate the association between microscopic damage of white matter and cognitive performance. Independent component analysis (ICA) and seed-based analysis approaches were used to investigate functional disconnection of large-scale cognitive networks and its contribution on cognitive impairment. The association between cognitive performance and ischaemic lesions volumes and microscopic damage of brain tissues were also assessed. Results The presence of chronic subcortical ischaemic lesions located in strategic white matter tracts including anterior thalamic radiation, forceps minor and forceps major contributed to global cognitive impairment in patients with symptomatic carotid artery disease. Ischaemic lesion volumes and microscopic damage of brain tissues including strategic brain areas, strategic white matter tracts, normal appearing white matter and white matter tract skeleton were related to cognitive impairment. Functional disconnection of large-scale cognitive networks including default mode network (DMN), dorsal attention network (DAN), left fronto-parietal network and salience network was found in patients with probable vascular mild cognitive impairment (VaMCI). Functional disconnection beyond the large-scale cognitive networks, showing as decreased functional connectivity between bilateral hippocampi, bilateral dorsal lateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC) with the rest of the brain, was also found in patients with probable VaMCI. Also, the thesis presented preliminary results of the role of lesional and non-lesion brain damage in fluency performance in patients with symptomatic carotid artery disease. Conclusions This thesis provides further evidence for the role and to the nature of disconnection in VCI and proposes several disconnection related imaging biomarkers

Altered nucleus basalis connectivity predicts treatment response in mild cognitive impairment

Purpose: To determine whether functional connectivity (FC) mapping of nucleus basalis of Meynert (NBM) cholinergic network (hereafter, NBM FC) could provide a biomarker of central cholinergic deficits with predictive potential for response to cholinesterase inhibitor (ChEI) treatment.Materials and Methods: The Alzheimer’s Disease Neuroimaging Initiative (ADNI) was approved by the institutional review boards of all participating sites. All participants and their representatives gave written informed consent prior to data collection. NBM FC was examined in 33 healthy control participants, 102 patients with mild cognitive impairment (MCI), and 33 patients with AD by using resting-state functional MRI data from the ADNI database. NBM FC was compared between groups before and after 6 months of ChEI treatment in MCI. Associations between baseline NBM FC and baseline cognitive performance as well as cognitive outcomes after treatment were investigated.Results: Compared with the healthy control group, NBM FC was decreased in patients with untreated MCI and increased in patients with AD treated with ChEI (corrected P ˂ .05). Global cognition (Alzheimer’s Disease Assessment Scale-Cognitive subscale score) was associated with NBM FC (r = −0.349; P ˂ .001). NBM FC was higher 6 months after ChEI compared with before ChEI in treated MCI (corrected P ˂ .05), but did not change at 6 months in patients with untreated MCI (corrected P ˂ .05). Baseline NBM FC in MCI strongly predicted cognitive outcomes 6 months after ChEI (R2 = 0.458; P = .001).Conclusion: Functional dissociation of the nucleus basalis of Meynert from a cortical network may explain the cognitive deficits in dementia and allow for the selection of individuals who are more likely to respond to cholinesterase inhibitors at early disease stages

Lesion topography and microscopic white matter tract damage contribute to cognitive impairment in symptomatic carotid artery disease

Purpose: To investigate associations between neuroimaging markers of cerebrovascular disease, including lesion topography and extent and severity of strategic and global cerebral tissue injury, and cognition in carotid artery disease (CAD). Materials and Methods: All participants gave written informed consent to undergo brain magnetic resonance imaging and the Addenbrooke’s Cognitive Examination–Revised. One hundred eight patients with symptomatic CAD but no dementia were included, and a score less than 82 represented cognitive impairment. Group comparison and interrelations between global cognitive and fluency performance, lesion topography, and ultrastructural damage were assessed with voxel-based statistics. Associations between cognition, medial temporal lobe atrophy (MTA), lesion volumes, and global white matter ultrastructural damage indexed as increased mean diffusivity were tested with regression analysis by controlling for age. Diagnostic accuracy of imaging markers selected from a multivariate prediction model was tested with receiver operating characteristic analysis. Results: Cognitively impaired patients (n = 53 [49.1%], classified as having probable vascular cognitive disorder) were older than nonimpaired patients (P = .027) and had more frequent MTA (P<.001), more cortical infarctions (P = .016), and larger volumes of acute (P = .028) and chronic (P = .009) subcortical ischemic lesions. Lesion volumes did not correlate with global cognitive performance (lacunar infarctions, P = .060; acute lesions, P = .088; chronic subcortical ischemic lesions, P = .085). In contrast, cognitive performance correlated with presence of chronic ischemic lesions within the interhemispheric tracts and thalamic radiation (P< .05, false discovery rate corrected). Skeleton mean diffusivity showed the closest correlation with cognition (R2 = 0.311, P< .001) and promising diagnostic accuracy for vascular cognitive disorder (area under the curve, 0.82 [95% confidence interval: 0.75, 0.90]). Findings were confirmed in subjects with a low risk of preclinical Alzheimer disease indexed by the absence of MTA (n = 85). Conclusion: Subcortical white matter ischemic lesion locations and severity of ultrastructural tract damage contribute to cognitive impairment in symptomatic CAD, which suggests that subcortical disconnection within large-scale cognitive neural networks is a key mechanism of vascular cognitive disorder

Automated segmentation of haematoma and perihaematomal oedema in MRI of acute spontaneous intracerebral haemorrhage

BackgroundSpontaneous intracerebral haemorrhage (SICH) is a common condition with high morbidity and mortality. Segmentation of haematoma and perihaematoma oedema on medical images provides quantitative outcome measures for clinical trials and may provide important markers of prognosis in people with SICH.MethodsWe take advantage of improved contrast seen on magnetic resonance (MR) images of patients with acute and early subacute SICH and introduce an automated algorithm for haematoma and oedema segmentation from these images. To our knowledge, there is no previously proposed segmentation technique for SICH that utilises MR images directly. The method is based on shape and intensity analysis for haematoma segmentation and voxel-wise dynamic thresholding of hyper-intensities for oedema segmentation.ResultsUsing Dice scores to measure segmentation overlaps between labellings yielded by the proposed algorithm and five different expert raters on 18 patients, we observe that our technique achieves overlap scores that are very similar to those obtained by pairwise expert rater comparison. A further comparison between the proposed method and a state-of-the-art Deep Learning segmentation on a separate set of 32 manually annotated subjects confirms the proposed method can achieve comparable results with very mild computational burden and in a completely training-free and unsupervised way.ConclusionOur technique can be a computationally light and effective way to automatically delineate haematoma and oedema extent directly from MR images. Thus, with increasing use of MR images clinically after intracerebral haemorrhage this technique has the potential to inform clinical practice in the future

Using neuroimaging to understand cognitive impairment in patients with symptomatic carotid artery disease

Introduction Patients with symptomatic carotid artery disease have increased risk of cognitive impairment. Multiple mechanisms of cognitive impairment have been proposed. However, the contribution of each mechanism to cognitive impairment and the interrelation between these mechanisms remain unclear. Lesional and non-lesional damage of brain tissues may lead to cognitive impairment in patients with symptomatic carotid artery disease. The research presented aims to use whole brain statistical brain mapping and quantitative neuroimaging techniques to understand vascular cognitive impairment (VCI) in a group of patients with symptomatic carotid artery disease. Methods Studies presented in this thesis were based on available multimodal MRI and cognitive performance data from a study in patients with symptomatic carotid artery disease. Totally 108 subjects had FLAIR and diffusion MRI scans and 62 of them had resting-state fMRI scans in a 3T MRI scanner. All participants (n=108) underwent cognitive assessments using Addrenbrooke’s cognitive examination-revised (ACE-R). Voxel-based lesion symptom mapping (VLSM) technique was used to identify the contribution of ischaemic lesion presence to cognitive performance. Tract-based spatial statistics (TBSS) approach was used to investigate the association between microscopic damage of white matter and cognitive performance. Independent component analysis (ICA) and seed-based analysis approaches were used to investigate functional disconnection of large-scale cognitive networks and its contribution on cognitive impairment. The association between cognitive performance and ischaemic lesions volumes and microscopic damage of brain tissues were also assessed. Results The presence of chronic subcortical ischaemic lesions located in strategic white matter tracts including anterior thalamic radiation, forceps minor and forceps major contributed to global cognitive impairment in patients with symptomatic carotid artery disease. Ischaemic lesion volumes and microscopic damage of brain tissues including strategic brain areas, strategic white matter tracts, normal appearing white matter and white matter tract skeleton were related to cognitive impairment. Functional disconnection of large-scale cognitive networks including default mode network (DMN), dorsal attention network (DAN), left fronto-parietal network and salience network was found in patients with probable vascular mild cognitive impairment (VaMCI). Functional disconnection beyond the large-scale cognitive networks, showing as decreased functional connectivity between bilateral hippocampi, bilateral dorsal lateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC) with the rest of the brain, was also found in patients with probable VaMCI. Also, the thesis presented preliminary results of the role of lesional and non-lesion brain damage in fluency performance in patients with symptomatic carotid artery disease. Conclusions This thesis provides further evidence for the role and to the nature of disconnection in VCI and proposes several disconnection related imaging biomarkers