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The age-related heterogeneity in major depressive disorder (MDD) has received significant attention. However, the neural mechanisms underlying such heterogeneity still need further investigation. This study aimed to explore the common and distinct functional brain abnormalities across different age groups of MDD patients from a large-sample, multicenter analysis.
The analyzed sample consisted of a total of 1238 individuals including 617 MDD patients (108 adolescents, 12–17 years old; 411 early-middle adults, 18–54 years old; and 98 late adults, > = 55 years old) and 621 demographically matched healthy controls (60 adolescents, 449 early-middle adults, and 112 late adults). MDD-related abnormalities in brain functional connectivity (FC) patterns were investigated in each age group separately and using the whole pooled sample, respectively.
We found shared FC reductions among the sensorimotor, visual, and auditory networks across all three age groups of MDD patients. Furthermore, adolescent patients uniquely exhibited increased sensorimotor-subcortical FC; early-middle adult patients uniquely exhibited decreased visual-subcortical FC; and late adult patients uniquely exhibited wide FC reductions within the subcortical, default-mode, cingulo-opercular, and attention networks. Analysis of covariance models using the whole pooled sample further revealed: (1) significant main effects of age group on FCs within most brain networks, suggesting that they are decreased with aging; and (2) a significant age group × MDD diagnosis interaction on FC within the default-mode network, which may be reflective of an accelerated aging-related decline in default-mode FCs.
To summarize, these findings may deepen our understanding of the age-related biological and clinical heterogeneity in MDD.
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.
Network approach has been applied to a wide variety of psychiatric disorders. The aim of the present study was to identify network structures of remitters and non-remitters in patients with first-episode psychosis (FEP) at baseline and the 6-month follow-up.
Participants (n = 252) from the Korean Early Psychosis Study (KEPS) were enrolled. They were classified as remitters or non-remitters using Andreasen's criteria. We estimated network structure with 10 symptoms (three symptoms from the Positive and Negative Syndrome Scale, one depressive symptom, and six symptoms related to schema and rumination) as nodes using a Gaussian graphical model. Global and local network metrics were compared within and between the networks over time.
Global network metrics did not differ between the remitters and non-remitters at baseline or 6 months. However, the network structure and nodal strengths associated with positive-self and positive-others scores changed significantly in the remitters over time. Unique central symptoms for remitters and non-remitters were cognitive brooding and negative-self, respectively. The correlation stability coefficients for nodal strength were within the acceptable range.
Our findings indicate that network structure and some nodal strengths were more flexible in remitters. Negative-self could be an important target for therapeutic intervention.
There is growing interest globally in using real-world data (RWD) and real-world evidence (RWE) for health technology assessment (HTA). Optimal collection, analysis, and use of RWD/RWE to inform HTA requires a conceptual framework to standardize processes and ensure consistency. However, such framework is currently lacking in Asia, a region that is likely to benefit from RWD/RWE for at least two reasons. First, there is often limited Asian representation in clinical trials unless specifically conducted in Asian populations, and RWD may help to fill the evidence gap. Second, in a few Asian health systems, reimbursement decisions are not made at market entry; thus, allowing RWD/RWE to be collected to give more certainty about the effectiveness of technologies in the local setting and inform their appropriate use. Furthermore, an alignment of RWD/RWE policies across Asia would equip decision makers with context-relevant evidence, and improve timely patient access to new technologies. Using data collected from eleven health systems in Asia, this paper provides a review of the current landscape of RWD/RWE in Asia to inform HTA and explores a way forward to align policies within the region. This paper concludes with a proposal to establish an international collaboration among academics and HTA agencies in the region: the REAL World Data In ASia for HEalth Technology Assessment in Reimbursement (REALISE) working group, which seeks to develop a non-binding guidance document on the use of RWD/RWE to inform HTA for decision making in Asia.
Our previous genome-wide association study (CONVERGE sample) identified significant association between single nucleotide polymorphisms (SNPs) near the SIRT1 gene and major depressive disorder (MDD) in Chinese populations.
To investigate whether SNPs across the SIRT1 gene locus affect regional grey matter density in the Han Chinese population.
T1-weighted structural magnetic resonance imaging was conducted on 92 healthy participants from Eastern China. Grey matter was segmented from the image, which consisted of voxel-wise grey matter density. The effect of SIRT1 SNPs on grey matter density was determined by a multiple linear regression framework.
SNP rs4746720 was significantly associated with grey matter density in two brain cortical regions: the orbital part of the right inferior frontal gyrus and the orbital part of the left inferior frontal gyrus (family-wise error-corrected P < 0.05; voxel-wise P < 0.001). Also, rs4746720 exceeded genome-wide significance in association with MDD in our CONVERGE sample (P = 3.32 × 10−08, odds ratio 1.161).
Our results provided evidence for a potential role of the SIRT1 gene in the brain, implying a possible pathophysiological mechanism underlying susceptibility to MDD.
This paper presents new water-soluble bio-polyelectrolyte-based nanoparticles, formed from lanthanide-induced polysaccharide aggregates (LIPAs). These new nano-aggregates are formed by coordinating a photoluminescent lanthanide–ligand complex to a single polyelectrolyte [i.e. polyanionic hyaluronic acid (HA)] or to two oppositely charged polyelectrolytes [i.e. HA and polycationic chitosan (CHI)]. We demonstrate that photoluminescent Eu3+–ligand complexes, which are dispersed homogeneously in aqueous solution by the association with water-soluble HA. The polysaccharide supermolecular assembly can be tuned to obtain nanoparticles of different sizes and surface charges. The preparation of stable and water-soluble lanthanide complexes via Eu3+–LIPAs opens opportunities for use of luminescent lanthanides in aqueous environments, for biosensing and bioimaging applications.
Fusion of nucleoli or nucleolus precursor bodies (NPBs) has been observed during somatic cell interphase and pronuclear development of human zygotes; however, the underlying mechanism is unknown. NPB fusion and its regulation by mitogen-activated protein kinase (MAPK) and maturation-promoting factor (MPF) were studied in activated mouse oocytes. Small NPBs appeared about 4 h after ethanol activation, and took about 1.5 h to fuse into a large NPB, which persisted for about 10 h before disappearance. Analysis of the temporal windows for kinase action indicated that a high MAPK activity during the first 2 h and a low MPF activity during the first 3–4 h after activation were essential for subsequent NPB fusion. A preactivation decline in MAPK activity was associated with decreased NPB fusion following activation of aged oocytes. While MAPK inactivation by regulator U0126 prevented NPB fusion in oocytes activated by ethanol or 5 min Sr2+ treatments, it had no effect on oocytes fertilized or activated by 6 h Sr2+ treatment. In most cases, while rates of pronuclear formation did not differ, rates of NPB fusion differed significantly between different treatments. Our results suggest that: (i) the MAPK and MPF activities at the initial stage of activation regulate NPB fusion after pronuclear formation; (ii) pronuclear assembly and NPB fusion are two separable events that might be controlled by different mechanisms; and (iii) high MAPK activity and low MPF activity at the initial stage of activation is essential for NPB fusion when only one calcium rise is induced by ethanol, while inhibition of MAPK activity does not affect NPB fusion when the repetitive intracellular Ca2+ rises are induced after fertilization.
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