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Previous studies have confirmed that miR-146a-5p overexpression suppresses neurogenesis, thereby enhancing depression-like behaviors. However, it remains unclear how miR-146a-5p dysregulation produces in vivo brain structural abnormalities in patients with major depressive disorder (MDD).
In this case–control study, we combined cortical morphology analysis of magnetic resonance imaging (MRI) and miR-146a-5p quantification to investigate the neuropathological effect of miR-146a-5p on cortical thickness in MDD patients. Serum-derived exosomes that were considered to readily cross the blood-brain barrier and contain miR-146a-5p were isolated for miRNA quantification. Moreover, follow-up MRI scans were performed in the MDD patients after 6 weeks of antidepressant treatment to further validate the clinical relevance of the relationship between miR-146a-5p and brain structural abnormalities.
In total, 113 medication-free MDD patients and 107 matched healthy controls were included. Vertex-vise general linear model revealed miR-146a-5p-dependent cortical thinning in MDD patients compared with healthy individuals, i.e., overexpression of miR-146a-5p was associated with reduced cortical thickness in the left orbitofrontal cortex (OFC), anterior cingulate cortex, bilateral lateral occipital cortices (LOCs), etc. Moreover, this relationship between baseline miR-146a-5p and cortical thinning was nonsignificant for all regions in the patients who had received antidepressant treatment, and higher baseline miR-146a-5p expression was found to be related to greater longitudinal cortical thickening in the left OFC and right LOC.
The findings of this study reveal a relationship between miR-146a-5p overexpression and cortical atrophy and thus may help specify the in vivo mediating effect of miR-146a-5p dysregulation on brain structural abnormalities in patients with MDD.
As the US-led global “War on Terror” enters its third decade, the structural, physical, and epistemological violence it has wrought continues to shape lives and landscapes in Afghanistan and Iraq. At present, the scholarship of an entire generation of Middle Eastern Studies has been embedded in the geopolitical realities of this indefinite war, even those whose work does not directly confront it. Yet despite the war's enduring presence, scholars working on Afghanistan and Iraq rarely find the opportunity to reflect with one another on how the global assemblage of international military intervention and the creation of a shifting target of terrorism has narrowed our foci. Instead, these geographies are yoked together in often destructive and superficial ways, erasing older forms of interregional connectivity and longer genealogies of violence.
Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia.
To identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers.
We used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites.
We found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19–85.74%; sensitivity, 75.31–89.29% and area under the receiver operating characteristic curve, 0.797–0.909.
These results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.
COVID-19 has long-term impacts on public mental health, while few research studies incorporate multidimensional methods to thoroughly characterise the psychological profile of general population and little detailed guidance exists for mental health management during the pandemic. This research aims to capture long-term psychological profile of general population following COVID-19 by integrating trajectory modelling approaches, latent trajectory pattern identification and network analyses.
Longitudinal data were collected from a nationwide sample of 18 804 adults in 12 months after COVID-19 outbreak in China. Patient Health Questionnaire-9, Generalised Anxiety Disorder-7 and Insomnia Severity Index were used to measure depression, anxiety and insomnia, respectively. The unconditional and conditional latent growth curve models were fitted to investigate trajectories and long-term predictors for psychological symptoms. We employed latent growth mixture model to identify the major psychological symptom trajectory patterns, and ran sparse Gaussian graphical models with graphical lasso to explore the evolution of psychopathological network.
At 12 months after COVID-19 outbreak, psychological symptoms generally alleviated, and five psychological symptom trajectories with different demographics were identified: normal stable (63.4%), mild stable (15.3%), mild-increase to decrease (11.7%), mild-decrease to increase (4.0%) and moderate/severe stable (5.5%). The finding indicated that there were still about 5% individuals showing consistently severe distress and approximately 16% following fluctuating psychological trajectories, who should be continuously monitored. For individuals with persistently severe trajectories and those with fluctuating trajectories, central or bridge symptoms in the network were mainly ‘motor abnormality’ and ‘sad mood’, respectively. Compared with initial peak and late COVID-19 phase, aftermath of initial peak might be a psychologically vulnerable period with highest network connectivity. The central and bridge symptoms for aftermath of initial peak (‘appetite change’ and ‘trouble of relaxing’) were totally different from those at other pandemic phases (‘sad mood’).
This research identified the overall growing trend, long-term predictors, trajectory classes and evolutionary pattern of psychopathological network of psychological symptoms in 12 months after COVID-19 outbreak. It provides a multidimensional long-term psychological profile of the general population after COVID-19 outbreak, and accentuates the essentiality of continuous psychological monitoring, as well as population- and time-specific psychological management after COVID-19. We believe our findings can offer reference for long-term psychological management after pandemics.
Matsu in early times was not an immigrant society but rather a stopover or temporary place to live, with people coming and going in a constant state of flux. Lying beyond the reaches of state power, the islands were almost deserted, becoming a lawless place where “the strongest fist took everything.” The island society during this period was characterized by transience and brokenness. The history of Matsu in this period is reviewed.
During the army’s warzone administration of Matsu, the fishing economy of the islands faced severe challenges. Taiwan started the process of industrialization in the 1970s and required a larger labor force, and many Matsu locals moved there—mostly to Taoyuan—to work in factories. Those who stayed behind on the islands shifted their forms of livelihood toward offering goods and services to the military.
Although many of the individual imaginations discussed in previous chapters have not developed into social imaginaries, the imagining subjects do not easily fade away; they remain latent and may garner renewed power at unexpected moments.
This introductory chapter focuses on theoretical issues related to the imagining subject, discussing its subjectification processes and varied uses of mediating technologies to constitute new social imaginaries.
This chapter discusses the newly invented religious practices that are the imaginary reconstitutions of cross-strait realities. I consider that the significances of these new rituals, myths, and material practices rests not on whether they succeed, but rather on the subjectivity they convey when people are faced with predicaments; they mediate social relations, rescale regional interactions, and forge possible developments for the islands in the future.
This chapter probes how old, conflicted, and fragmented social units in an island settlement came to be integrated after the era of military control ended, and how they formed a new community through the process of temple building.
In 1949, the Nationalist army abruptly arrived in Matsu and indelibly changed the fate of the islands. This chapter analyzes how military rule dramatically transformed the lives of the local people from a spatial perspective.