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Connectome mapping studies have documented a principal primary-to-transmodal gradient in the adult brain network, capturing a functional spectrum that ranges from perception and action to abstract cognition. However, how this gradient pattern develops and whether its development is linked to cognitive growth, topological reorganization, and gene expression profiles remain largely unknown. Using longitudinal resting-state functional magnetic resonance imaging data from 305 children (aged 6-14 years), we describe substantial changes in the primary-to-transmodal gradient between childhood and adolescence, including emergence as the principal gradient, expansion of global topography, and focal tuning in primary and default-mode regions. These gradient changes are mediated by developmental changes in network integration and segregation, and are associated with abstract processing functions such as working memory and expression levels of calcium ion regulated exocytosis and synaptic transmission-related genes. Our findings have implications for understanding connectome maturation principles in normal development and developmental disorders.

Functional brain networks require dynamic reconfiguration to support flexible cognitive function. However, the developmental principles shaping brain network dynamics remain poorly understood. Here, we report the longitudinal development of large-scale brain network dynamics during childhood and adolescence, and its connection with gene expression profiles. Using a multilayer network model, we show the temporally varying modular architecture of child brain networks, with higher network switching primarily in the association cortex and lower switching in the primary regions. This topographical profile exhibits progressive maturation, which manifests as reduced modular dynamics, particularly in the transmodal (e.g., default-mode and frontoparietal) and sensorimotor regions. These developmental refinements mediate age-related enhancements of global network segregation and are linked with the expression profiles of genes associated with the enrichment of ion transport and nucleobase-containing compound transport. These results highlight a progressive stabilization of brain dynamics, which expand our understanding of the neural mechanisms that underlie cognitive development.

Human brain connectomes include sets of densely connected hub regions. However, the consistency and reproducibility of functional connectome hubs have not been established to date and the genetic signatures underlying robust hubs remain unknown. Here, we conduct a worldwide harmonized meta-connectomic analysis by pooling resting-state functional MRI data of 5212 healthy young adults across 61 independent cohorts. We identify highly consistent and reproducible connectome hubs in heteromodal and unimodal regions both across cohorts and across individuals, with the greatest effects observed in lateral parietal cortex. These hubs show heterogeneous connectivity profiles and are critical for both intra- and inter-network communications. Using post-mortem transcriptome datasets, we show that as compared to non-hubs, connectome hubs have a spatiotemporally distinctive transcriptomic pattern dominated by genes involved in the neuropeptide signaling pathway, neurodevelopmental processes, and metabolic processes. These results highlight the robustness of macroscopic connectome hubs and their potential cellular and molecular underpinnings, which markedly furthers our understanding of how connectome hubs emerge in development, support complex cognition in health, and are involved in disease.

Human cognition and behaviors depend upon the brain’s functional connectomes, which vary remarkably across individuals. However, whether and how the functional connectome individual variability architecture is structurally constrained remains largely unknown. Using tractography- and morphometry-based network models, we observed the spatial convergence of structural and functional connectome individual variability, with higher variability in heteromodal association regions and lower variability in primary regions. We demonstrated that functional variability is significantly predicted by a unifying structural variability pattern and that this prediction follows a primary-to-heteromodal hierarchical axis, with higher accuracy in primary regions and lower accuracy in heteromodal regions. We further decomposed group-level connectome variability patterns into individual unique contributions and uncovered the structural-functional correspondence that is associated with individual cognitive traits. These results advance our understanding of the structural basis of individual functional variability and suggest the importance of integrating multimodal connectome signatures for individual differences in cognition and behaviors.

The median cleft of the mandible and lower lip is an extremely rare congenital maxillofacial deformity, and the therapeutic options are controversial. To evaluate the clinical characteristics and identify a better choice of treatment modes used among us and others, we reviewed 34 relevant literature and herein describe a 17-year follow-up of a case with a median cleft of the mandible and lower lip. Based on the literature and our case with good functional and aesthetical outcomes, we propose a prospective clinical treatment: Patients of Tessier 30 cleft associated with cleft of the mandible could undergo mandibular repair after puberty in conditions of a good occlusal relationship and normal maxillofacial development, even with mild masticatory dysfunction.

The functional connectome is highly distinctive in adults and adolescents, underlying individual differences in cognition and behavior. However, it remains unknown whether the individual uniqueness of the functional connectome is present in neonates, who are far from mature. Here, we utilized the multiband resting-state functional magnetic resonance imaging data of 40 healthy neonates from the Developing Human Connectome Project and a split-half analysis approach to characterize the uniqueness of the functional connectome in the neonatal brain. Through functional connectome-based individual identification analysis, we found that all the neonates were correctly identified, with the most discriminative regions predominantly confined to the higher-order cortices (e.g., prefrontal and parietal regions). The connectivities with the highest contributions to individual uniqueness were primarily located between different functional systems, and the short- (0–30 mm) and middle-range (30–60 mm) connectivities were more distinctive than the long-range (>60 mm) connectivities. Interestingly, we found that functional data with a scanning length longer than 3.5 min were able to capture the individual uniqueness in the functional connectome. Our results highlight that individual uniqueness is present in the functional connectome of neonates and provide insights into the brain mechanisms underlying individual differences in cognition and behavior later in life.

The human brain undergoes explosive growth during the prenatal period and the first few postnatal years, establishing an early infrastructure for the later development of behaviors and cognitions. Revealing the developmental rules during the early phase is essential for understanding the emergence of brain functions and the origin of developmental disorders. Graph-theoretical network modeling in combination with multiple neuroimaging probes provides an important research framework to explore the early development of the topological wiring and organizational paradigms of the brain. Here, we reviewed studies that employed neuroimaging and graph-theoretical modeling to investigate brain network development from approximately 20 gestational weeks to 2 years of age. Specifically, the structural and functional brain networks have evolved to highly efficient topological architectures in the early stage; where the structural network remains ahead and paves the way for the development of the functional network. The brain network develops in a heterogeneous order, from primary to higher-order systems and from a tendency of network segregation to network integration in the prenatal and postnatal periods. The early brain network topologies show abilities in predicting certain cognitive and behavior performance in later life, and their impairments are likely to continue into childhood and even adulthood. These macroscopic topological changes may be associated with possible microstructural maturations, such as axonal growth and myelinations. Collectively, this review provides a detailed delineation of the early changes in the baby brains in a graph-theoretical modeling framework, which opens up a new avenue for understanding the developmental principles of the connectome.

During the 3rd trimester, large-scale of neural circuits are formed in the human brain, resulting in the adult-like brain networks at birth. However, how the brain circuits develop into a highly efficient and segregated connectome during this period is unknown. We hypothesized that faster increases of connectivity efficiency and strength at the brain hubs and rich-club are critical for emergence of an efficient and segregated brain connectome. Here, using high resolution diffusion MRI of 77 preterm-born and term-born neonates scanned at 31-42 postmenstrual weeks (PMW), we constructed the structural connectivity matrices and performed graph-theory-based analyses. We found faster increases of nodal efficiency mainly at the brain hubs, distributed in primary sensorimotor regions, superior-middle frontal and posterior cingulate gyrus during 31-42PMW. The rich-club and within-module connections were characterized by higher rates of edge strength increases. Edge strength of short-range connections increased faster than that of long-range connections. The nodal efficiencies of the hubs predicted individual postmenstrual ages more accurately than those of non-hubs. Collectively, these findings revealed regionally differentiated maturation in the baby brain structural connectome and more rapid increases of the hub and rich-club connections, which underlie network segregation and differentiated brain function emergence.

This study aims to determine whether and how diffusion alteration occurs in the earliest stage of multiple sclerosis (MS) and the differences in diffusion metrics between CIS and MS by using the tract-based spatial statistics (TBSS) method based on diffusion tensor imaging (DTI). Thirty-six CIS patients (mean age ± SD: 34.0 years ± 12.6), 36 relapsing-remitting multiple sclerosis (RRMS) patients (mean age ± SD: 35.0 years ± 9.4) and 36 age- and gender-matched normal controls (NCs) were included in this study. Voxel-wise analyses were performed with TBSS using multiple diffusion metrics, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ1) and radial diffusivity (λ23). In the CIS patients, TBSS analyses revealed diffusion alterations in a few white matter (WM) regions including the anterior thalamic radiation, corticospinal tract, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, body and splenium of the corpus callosum, internal capsule, external capsule, and cerebral peduncle. MS patients showed more widespread diffusion changes (decreased FA, increased λ1, λ23 and MD) than CIS. Exploratory analyses also revealed the possible associations between WM diffusion metrics and clinical variables (Expanded Disability Status Scale and disease duration) in the patients. This study provided imaging evidence for DTI abnormalities in CIS and MS and suggested that DTI can improve our knowledge of the path physiology of CIS and MS and clinical progression.

Tongue squamous cell carcinoma (TSCC) is highly malignant and poorly differentiated, resulting in a high frequency of local recurrence and distant metastases. Sox2 (Sry-box2), an important factor in embryonic development and cell differentiation, has been shown to associate with malignant phenotypes and epithelial-mesenchymal transition (EMT) progression in numerous types of human tumors. However, the clinical relevance and molecular mechanisms of Sox2 in TSCC remain unclear. In the present study, the expression levels of Sox2 were assessed in 61 pairs of TSCC samples and corresponding adjacent non-cancerous tissues using immunohistochemical methods. Associations between Sox2 expression and clinicopathological features were evaluated. Furthermore, Sox2 was overexpressed and inhibited using full-length Sox2 cDNA and short hairpin RNA (shRNA) transfection in UM2 and Cal27 cell lines, respectively. The malignant phenotypes were assessed by plate clone formation assays, wound-healing assays and Transwell assays. EMT markers (E-cadherin, vimentin, Twist, Slug and Snail) and β-catenin were detected by reverse transcription-polymerase chain reaction and western blot analysis following the alterations of Sox2 expression. The results indicated that Sox2 expression was markedly upregulated in TSCC samples and was significantly associated with tumor growth (pT stage), cell differentiation, lymphatic metastasis (pN stage) and clinical stage (pTNM stage). Cal27-shRNA-Sox2 cells not only exhibited a decreased capacity for cell proliferation, but also suppressed cell migration and invasion, and an attenuated colony formation capacity. By contrast, UM2-Sox2 cells exhibited accelerated cell malignant phenotypes and EMT progression. Moreover, when the expression of Sox2 was decreased by shRNA transduction, β-catenin expression was attenuated. An opposing phenomenon was observed in UM2-Sox2 cells. In conclusion, this study suggests that Sox2 expression serves a role in TSCC malignant phenotypes and EMT progression, and that β-catenin may act as a modulated factor in this progression.

Purpose To determine whether individuals with subjective cognitive decline (SCD), which is defined by memory complaints with normal performance at objective neuropsychologic examinations, exhibit disruptions of white matter (WM) connectivity and topologic alterations of the brain structural connectome. Materials and Methods Diffusion-tensor magnetic resonance imaging and graph theory approaches were used to investigate the topologic organization of the brain structural connectome in 36 participants with SCD (21 women: mean age, 62.0 years ± 8.6 [standard deviation]; age range, 42-76 years; 15 men: mean age, 65.5 years ± 8.9; age range, 51-80 years) and 51 age-, sex-, and years of education-matched healthy control participants (33 women: mean age, 63.7 years ± 8.8; age range, 46-83 years; 18 men: mean age, 59.4 years ± 9.3; age range, 43-75 years). Individual WM networks were constructed for each participant, and the network properties between two groups were compared with a linear regression model. Results Graph theory analyses revealed that the participants with SCD had less global efficiency (P = .001) and local efficiency (P = .008) compared with the healthy control participants. Lower regional efficiency was mainly distributed in the bilateral prefrontal regions and left thalamus (P.05, corrected). Furthermore, a disrupted subnetwork was observed that consisted of widespread anatomic connections (P.05, corrected), which has the potential to discriminate individuals with SCD from control participants. Moreover, similar hub distributions and less connection strength between the hub regions (P = .023) were found in SCD. Importantly, diminished strength of the rich-club and local connections was correlated with the impaired memory performance in patients with SCD (rich-club connection: r = 0.43, P = .011; local connection: r = 0.36, P = .037). Conclusion This study demonstrated disrupted topologic efficiency of the brain's structural connectome in participants with SCD and provided potential connectome-based biomarkers for the early detection of cognitive impairment in elderly individuals.

The default-mode network (DMN) is a set of functionally connected regions that play crucial roles in internal cognitive processing. Previous resting-state fMRI studies have demonstrated that the intrinsic functional organization of the DMN undergoes remarkable reconfigurations during childhood and adolescence. However, these studies have mainly focused on cross-sectional designs with small sample sizes, limiting the consistency and interpretations of the findings. Here, we used a large sample of longitudinal resting-state fMRI data comprising 305 typically developing children (6–12 years of age at baseline, 491 scans in total) and graph theoretical approaches to delineate the developmental trajectories of the functional architecture of the DMN. For each child, the DMN was constructed according to a prior parcellation with 32 brain nodes. We showed that the overall connectivity increased in strength from childhood to adolescence and became spatially similar to that in the young adult group (N = 61, 18–28 years of age). These increases were primarily located in the midline structures. Global and local network efficiency in the DMN also increased with age, indicating an enhanced capability in parallel information communication within the brain system. Based on the divergent developmental rates of nodal centrality, we identified three subclusters within the DMN, with the fastest rates in the cluster mainly comprising the anterior medial prefrontal cortex and posterior cingulate cortex. Together, our findings highlight the developmental patterns of the functional architecture in the DMN from childhood to adolescence, which has implications for the understanding of network mechanisms underlying the cognitive development of individuals.

Cognitive behavioral therapy (CBT) is considered a first-line treatment for patients with obsessive-compulsive disorder (OCD), and it possesses advantages over pharmacological treatments in stronger tolerance to distress, lower rates of drop out and relapse, and no physical “side-effects”. Previous studies have reported CBT-related alterations in focal brain regions and connections. However, the effects of CBT on whole-brain structural networks have not yet been elucidated. Here, we collected diffusion MRI data from 34 unmedicated OCD patients before and after 12 weeks of CBT. Fifty healthy controls (HCs) were also scanned twice at matched intervals. We constructed individual brain white matter connectome and performed a graph-theoretical network analysis to investigate the effects of CBT on whole-brain structural topology. We observed significant group-by-time interactions on the global network clustering coefficient and the nodal clustering of the left lingual gyrus, the left middle temporal gyrus, the left precuneus, and the left fusiform gyrus of 26 CBT responders in OCD patients. Further analysis revealed that these CBT responders showed prominently higher global and nodal clustering compared to HCs at baseline and reduced to normal levels after CBT. Such significant changes in the nodal clustering of the left lingual gyrus were also found in 8 CBT non-responders. The pre-to-post decreases in nodal clustering of the left lingual gyrus and the left fusiform gyrus positively correlated with the improvements in obsessive-compulsive symptoms in the CBT-responding patients. These findings indicated that the network segregation of the whole-brain white matter network in OCD patients was abnormally higher and might recover to normal after CBT, which provides mechanistic insights into the CBT response in OCD and potential imaging biomarkers for clinical practice.

Background Head and neck squamous cell carcinoma (HNSCC) is the six leading cancer by incidence worldwide. The 5-year survival rate of HNSCC patients remains less than 65% due to lack of symptoms in the early stage. Hence, biomarkers which can improve detection of HNSCC should improve clinical outcome. Methods Gene expression profiles (GSE6631, GSE58911) and the Cancer Genome Atlas (TCGA) HNSCC data were used for integrated bioinformatics analysis; the differentially expressed genes (DEGs) were then subjected to functional and pathway enrichment analysis, protein–protein interaction (PPI) network construction. Subsequently, module analysis of the PPI network was performed and overall survival (OS) analysis of hub genes in subnetwork was studied. Finally, immunohistochemistry was used to verify the selected markers. Results A total of 52 up-regulated and 80 down-regulated DEGs were identified, which were mainly associated with ECM–receptor interaction and focal adhesion signaling pathways. Importantly, a set of prognostic signatures including SERPINE1, PLAU and ACTA1 were screened from DEGs, which could predict OS in HNSCC patients from TCGA cohort. Experiment of clinical samples further successfully validated that these three signature genes were aberrantly expressed in the oral epithelial dysplasia and HNSCC, and correlated with aggressiveness of HNSCC patients. Conclusions SERPINE1, PLAU and ACTA1 played important roles in regulating the initiation and progression of HNSCC, and could be identified as key biomarkers for precise diagnosis and prognosis of HNSCC, which will provide potential targets for clinical therapies. Electronic supplementary material The online version of this article (10.1007/s10147-019-01435-9) contains supplementary material, which is available to authorized users.

In magnetic resonance (MR) imaging studies of child brain development, structural brain atlases usually serve as important references for the pediatric population, in which individual images are spatially normalized into a common or standard stereotactic space. However, the popular existing pediatric brain atlases (e.g., National Institutes of Health pediatric atlases, NIH-PD) are mostly based on MR images obtained from Caucasian populations and thus are not ideal for the characterization of the brains of Chinese children due to neuroanatomical differences related to genetic and environmental factors. Here, we use an unbiased template construction algorithm to create a set of age-specific Chinese pediatric (CHN-PD) atlases based on high-quality T1-and T2-weighted MR images from 328 cognitively normal Chinese children aged 6–12 years. The CHN-PD brain atlases include asymmetric and symmetric templates, sex-specific templates and tissue probability templates, and contain multiple age-specific templates at one-year intervals. A direct comparison of the CHN-PD and NIH-PD atlases reveals dramatic anatomical differences mainly in the bilateral frontal and parietal regions. After applying the CHN-PD and NIH-PD atlases to two independent Chinese pediatric datasets (N = 114 and N = 71), we find that the CHN-PD atlases result in significantly higher accuracy than the NIH-PD atlases in both predicting “brain age” and guiding brain tissue segmentation. These results suggest that the CHN-PD brain atlases are necessary for studies of the typical and atypical development of the Chinese pediatric population. These CHN-PD atlases have been released on the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) website (https://www.nitrc.org/projects/chn-pd).

Purpose This retrospective study aimed to identify the clinical characteristics of radiation-induced sarcoma of the head and neck (RISHN) that could help in the early diagnosis of this rare disease. Materials and Methods From August 1995 through October 2014, 15 cases of RISHN presenting at the authors' department and 323 cases in the literature were reviewed. Results The incidence of RISHN was higher in men than in women (male-to-female ratio, 2.4:1). The mean latency was long (9.3 yr), and the tumor often occurred in middle age (50.0 yr old). Osteosarcoma was the predominant pathologic diagnosis (34.1%). The prognosis of RISHN was poor. Conclusion RISHN is a serious long-term complication of radiotherapy and its incidence has been increasing in recent years. Owing to the long latency period, its early diagnosis is difficult to make. RISHN should be considered when a patient who has undergone radiotherapy presents with a mass, pain, or trismus in the irradiated field.

Amnestic mild cognitive impairment (aMCI) is accompanied by the accelerated cognitive decline and rapid brain degeneration with aging. However, the age-related alterations of the topological organization of the brain connectome in aMCI patients remained largely unknown. In this study, we constructed the brain structural connectome in 51 aMCI patients and 51 healthy controls by diffusion magnetic resonance imaging and deterministic tractography. The different age-related alteration patterns of the global and regional network metrics between aMCI patients and healthy controls were assessed by a linear regression model. Compared with healthy controls, significantly decreased global and local network efficiency in aMCI patients were found. When correlating network efficiency with age, we observed a significant decline in network efficiency with aging in the aMCI patients, while not in the healthy controls. The age-related decreases of nodal efficiency in aMCI patients were mainly distributed in the key regions of the default-mode network, such as precuneus, anterior cingulate gyrus, and parahippocampal gyrus. In addition, age-related decreases in the connection strength of the edges between peripheral nodes were observed in aMCI patients. Moreover, the decreased regional efficiency of the parahippocampal gyrus was correlated with impaired memory performances in patients. The present study suggests an age-related disruption of the topological organization of the brain structural connectome in aMCI patients, which may provide evidence for different neural mechanisms underlying aging in aMCI and may serve as a potential imaging marker for the early diagnosis of Alzheimer's disease.

White matter (WM) degeneration has been found during the course of cognitive decline in both Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI), however, it is unclear whether there are different WM microstructural abnormalities between two subtypes of aMCI, including single domain aMCI (aMCI-s) and multiple domain aMCI (aMCI-m). Thirty-two patients of aMCI single-domain (aMCI-s), twenty-three patients of aMCI multiple-domain (aMCI-m) and twenty-three healthy normal controls (NC) participated in this study. Neuropsychological measures and diffusion tensor imaging (DTI) data were acquired from each subject and tract-based spatial statistics (TBSS) was implemented. It was found that both aMCI groups showed significantly reduced fractional anisotropy (FA) in the right superior longitudinal fasciculus (SLF) than NC. It was also identified that, as compared to aMCI-m, aMCI-s showed significantly decreased FA in the left SLF, left uncinate fasciculus (UF) and left inferior longitudinal fasciculus (ILF), while significantly increased FA in the left anterior thalamic radiation (ATR). The correlation analysis showed that FA values in the regions with group difference were significantly correlated with cognitive functions as measured by Boston naming test and trail making test. These results suggested that the variations of aMCI may be differentiated by FA indexes and DTI may help to understand why specific signs and symptoms occur in patients.

Head and Neck squamous cell carcinomas (HNSCC), characterized by the high frequency of local recurrence and distant metastases, is mostly related to highly malignant and resistant to apoptosis, resulting in significant insensitivity to chemotherapy. Telomerase reverse transcriptase (TERT), as the catalytic subunit of telomerase, was implicated in the telomerase-mediated cellular transformation, proliferation, stemness and cell survival. Moreover, overexpression of human TERT (hTERT) is reported to be correlated with advanced invasive stage of the tumor progression and poor prognosis. Here, we show that hTERT potentially mediated the apoptotic resistance and blockade of telomerase reverse transcriptase could enhance chemosensitivity in head and neck cancers. Mechanistically, hTERT interacts with the phosphorylation of AKT and ERK to suppress the expression of p53, ultimately, leading to modulation of the cellular sensitivity to chemotherapy. Thus, these findings suggest that hTERT targeting could be an attractive approach in combination with conventional chemotherapies for patients suffering from chemoinsensitivity or refractory HNSCC.

Lifespan is a dynamic process with remarkable changes in brain structure and function. Previous neuroimaging studies have indicated age‐related microstructural changes in specific white matter tracts during development and aging. However, the age‐related alterations in the topological architecture of the white matter structural connectome across the human lifespan remain largely unknown. Here, a cohort of 113 healthy individuals (ages 9–85) with both diffusion and structural MRI acquisitions were examined. For each participant, the high‐resolution white matter structural networks were constructed by deterministic fiber tractography among 1024 parcellation units and were quantified with graph theoretical analyses. The global network properties, including network strength, cost, topological efficiency, and robustness, followed an inverted U‐shaped trajectory with a peak age around the third decade. The brain areas with the most significantly nonlinear changes were located in the prefrontal and temporal cortices. Different brain regions exhibited heterogeneous trajectories: the posterior cingulate and lateral temporal cortices displayed prolonged maturation/degeneration compared with the prefrontal cortices. Rich‐club organization was evident across the lifespan, whereas hub integration decreased linearly with age, especially accompanied by the loss of frontal hubs and their connections. Additionally, age‐related changes in structural connections were predominantly located within and between the prefrontal and temporal modules. Finally, based on the graph metrics of structural connectome, accurate predictions of individual age were obtained (r = 0.77). Together, the data indicated a dynamic topological organization of the brain structural connectome across human lifespan, which may provide possible structural substrates underlying functional and cognitive changes with age. Hum Brain Mapp 36:3777–3792, 2015. © 2015 Wiley Periodicals, Inc.

In recent years, researchers have found the critical role of telomerase in cellular transformation, proliferation, stemness and cell survival. High levels of telomerase reverse transcriptase (TERT) expression and telomerase activation have been reported in most cancer cells. Moreover, overexpression of human TERT (hTERT) is reported to be correlated with advanced invasive stage of the tumor progression and poor prognosis. Epithelial-mesenchymal transition (EMT), characterized by the loss of the cell-cell contact of epithelial cells and the acquisition of migratory and motile properties, is known to be a central mechanism responsible for invasiveness and metastasis of various cancers. Thus, we investigated whether hTERT plays a potential role in the development of EMT. As we expected, our clinical results showed that hTERT is overexpressed in oral epithelial dysplasia (OED) and OSCC tissues and correlates with clinical aggressiveness of oral squamous cell carcinoma (OSCC) patients. We then overexpressed hTERT in primary human oral epithelial cells (HOECS) and found that hTERT has the potential to prolong the lifespan, a process confering the characteristics of EMT by activating the Wnt/β-catenin pathway. Our findings provided an explanation for the aggressive nature of human tumors overexpressing hTERT and the possibly mechanism that links hTERT to EMT property, which represents a possible therapeutic target in highly metastatic cancers.

To investigate the test-retest (TRT) reliability of the diffusion measures in cerebral white matter obtained from the diffusion MRI dataset acquired with multiband acceleration.With the multiband diffusion MRI dataset with two repeated scanning sessions, the TRT reliability of diffusion measures (fractional anisotropy [FA], mean diffusivity [MD], primary diffusivity [PD] and transverse diffusivity [TD]) was investigated through several fully automated analysis methods, including two voxel-level analyses (voxel-based analysis [VBA] and tract-based spatial statistics [TBSS]) and an atlas ROI-based analysis. The reproducibility was assessed by the intra-class correlation coefficient (ICC).Our results demonstrated moderate to high reproducibility (ICC 0.4) of diffusion measures from the multiband EPI sequence with different analysis approaches. Across different measures, FA exhibited the highest reproducibility (mean ICC = 0.70), while MD showed the lowest reliability (mean ICC = 0.55) (P = 0.006). Additionally, ICCs varied across different tract ROIs: Commissural tracts showed higher reproducibility than other categories of tracts (projection, association and brainstem), while the brainstem tracts exhibited the poorest reliability (P = 0.004).Our findings suggest a potential utility of the multiband EPI sequence for exploring individual differences of cerebral white matter and provide reference for future white matter studies.

Previous studies have demonstrated that Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) exhibited anatomical and functional abnormalities in the anterior cingulate cortex (ACC) and accumulating evidence supported the hypothesis that changes in the ACC predict the progression from aMCI to AD. In this study, we aimed to explore how the two functional and structural heterogeneous sub-regions of ACC, namely the dorsal ACC (dACC) and the ventral ACC (vACC), changed in aMCI and whether the structural connectivity affects the functional connectivity between the two ACC subregions. To investigate this hypothesis, we studied resting-state fMRI and DTI images in a group of 24 aMCIs and 29 healthy controls. The dACC exhibited a significantly increased functional connectivity in the Salience Network (SN) and a decreased functional connectivity with the vACC in aMCI. The DTI results showed that the bilateral cingulum fibers were the most damaged tracts in aMCI and that the fractional anisotrophy of the left anterior cingulum was significantly correlated with the functional connectivity between the two ACC sub-regions. In conclusion, this study revealed the pathological changes in the intrinsic functional connectivity of the ACC within SN, as well as the connectivity between the dACC and vACC in aMCI. Our study also revealed that disrupted white matter integrity of the anterior regions of the cingulum was associated with the alterations in subregional connectivity in the ACC.

Background Obsessive–compulsive disorder (OCD) is a chronic psychiatric disorder defined by recurrent thoughts, intrusive and distressing impulses, or images and ritualistic behaviors. Although focal diverse regional abnormalities white matter integrity in specific brain regions have been widely studied in populations with OCD, alterations in the structural connectivities among them remain poorly understood. Objective The aim was to investigate the abnormalities in the topological efficiency of the white matter networks and the correlation between the network metrics and Yale–Brown Obsessive–Compulsive Scale scores in unmedicated OCD patients, using diffusion tensor tractography and graph theoretical approaches. Methods This study used diffusion tensor imaging and deterministic tractography to map the white matter structural networks in 26 OCD patients and 39 age- and gender-matched healthy controls; and then applied graph theoretical methods to investigate abnormalities in the global and regional properties of the white matter network in these patients. Results The patients and control participants both showed small-world organization of the white matter networks. However, the OCD patients exhibited significant abnormal global topology, including decreases in global efficiency (t = − 2.32, p = 0.02) and increases in shortest path length, Lp (t = 2.30, p = 0.02), the normalized weighted shortest path length, λ (t = 2.08, p = 0.04), and the normalized clustering coefficient, γ (t = 2.26, p = 0.03), of their white matter structural networks compared with healthy controls. Further, the OCD patients showed a reduction in nodal efficiency predominately in the frontal regions, the parietal regions and caudate nucleus. The normalized weighted shortest path length of the network metrics was significantly negatively correlated with obsessive subscale of the Yale–Brown Obsessive–Compulsive Scale (r = − 0.57, p = 0.0058). Conclusions These findings demonstrate the abnormal topological efficiency in the white matter networks in OCD patients.

Recent research has demonstrated the feasibility of combining functional near-infrared spectroscopy (fNIRS) and graph theory approaches to explore the topological attributes of human brain networks. However, the test-retest (TRT) reliability of the application of graph metrics to these networks remains to be elucidated. Here, we used resting-state fNIRS and a graph-theoretical approach to systematically address TRT reliability as it applies to various features of human brain networks, including functional connectivity, global network metrics and regional nodal centrality metrics. Eighteen subjects participated in two resting-state fNIRS scan sessions held ∼20 min apart. Functional brain networks were constructed for each subject by computing temporal correlations on three types of hemoglobin concentration information (HbO, HbR, and HbT). This was followed by a graph-theoretical analysis, and then an intraclass correlation coefficient (ICC) was further applied to quantify the TRT reliability of each network metric. We observed that a large proportion of resting-state functional connections (∼90%) exhibited good reliability (0.6< ICC

BackgroundThe human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics.ResultsWe utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques.ConclusionsOur results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.