Downregulation of miR-503-5p Promotes the Development of Pancreatic Cancer by Targeting Cyclin E2.

This study aimed to elucidate the role of microRNA-503 (miR-503) in pancreatic cancer (PC) progression and the underlying regulatory mechanisms. We acquired miR-503-3p and miR-503-5p expression data along with survival times of PC and normal samples from the UCSC Xena database. Using the t-test, we compared the expression of miR-503-3p and miR-503-5p between PC and normal samples, and evaluated their prognostic significance via Kaplan-Meier survival analysis. The expression of miR-503-5p in PC cells was detected by quantitative PCR. We subsequently overexpressed miR-503-5p in PC cells and examined cell viability, apoptosis, and migration through CCK8 assay, flow cytometry, and Transwell assay, respectively. Potential functional targets were identified using miRTarBase and validated by dual-luciferase reporter assay. Both miR-503-3p and miR-503-5p expression were found to be downregulated in PC; however, only miR-503-5p was linked to cancer prognosis based on public data. In vitro experiments demonstrated that overexpression of miR-503-5p substantially decreased cell viability, induced apoptosis, caused G0/G1 arrest, and inhibited cell migration. miR-503-5p was found to target cyclin E2 (CCNE2), and overexpression of CCNE2 could counteract the effects of miR-503-5p on PC cells. Conclusion: The downregulation of miR-503-5p enhances the progression of PC by targeting CCNE2. The detection of miR-503-5p expression may provide valuable insights for the prevention and prognostic evaluation of PC.

Ultrahigh-Flux Water Nanopumps Generated by Asymmetric Terahertz Absorption.

Controlling active transport of water through membrane channels is essential for advanced nanofluidic devices. Despite advancements in water nanopump design using techniques like short-range invasion and subnanometer-level control, challenges remain facilely and remotely realizing massive waters active transport. Herein, using molecular dynamic simulations, we propose an ultrahigh-flux nanopump, powered by frequency-specific terahertz stimulation, capable of unidirectionally transporting massive water through asymmetric-wettability membrane channels at room temperature without any external pressure. The key physics behind this terahertz-powered water nanopump is revealed to be the energy flow resulting from the asymmetric optical absorption of water.

Altered controllability of white matter networks and related brain function changes in first-episode drug-naive schizophrenia.

Understanding how structural connectivity alterations affect aberrant dynamic function using network control theory will provide new mechanistic insights into the pathophysiology of schizophrenia. The study included 140 drug-naive schizophrenia patients and 119 healthy controls (HCs). The average controllability (AC) quantifying capacity of brain regions/networks to shift the system into easy-to-reach states was calculated based on white matter connectivity and was compared between patients and HCs as well as functional network topological and dynamic properties. The correlation analysis between AC and duration of untreated psychosis (DUP) were conducted to characterize the controllability progression pattern without treatment effects. Relative to HCs, patients exhibited reduced AC in multiple nodes, mainly distributed in default mode network (DMN), visual network (VN), and subcortical regions, and increased AC in somatomotor network. These networks also had impaired functional topology and increased temporal variability in dynamic functional connectivity analysis. Longer DUP was related to greater reductions of AC in VN and DMN. The current study highlighted potential structural substrates underlying altered functional dynamics in schizophrenia, providing a novel understanding of the relationship of anatomic and functional network alterations.

Expression of tyrosine phosphatases in relation to PTTH-stimulated ecdysteroidogenesis in prothoracic glands of the silkworm, Bombyx mori.

Protein tyrosine phosphorylation is a reversible, dynamic process regulated by the activities of tyrosine kinases and tyrosine phosphatases. Although the involvement of tyrosine kinases in the prothoracicotropic hormone (PTTH)-stimulated ecdysteroidogenesis in insect prothoracic glands (PGs) has been documented, few studies have been conducted on the involvement of protein tyrosine phosphatases (PTPs) in PTTH-stimulated ecdysteroidogenesis. In the present study, we investigated the correlation between PTPs and PTTH-stimulated ecdysteroidogenesis in Bombyx mori PGs. Our results showed that the basal PTP enzymatic activities exhibited development-specific changes during the last larval instar and pupation stage, with high activities being detected during the later stages of the last larval instar. PTP enzymatic activity was stimulated by PTTH treatment both in vitro and in vivo. Pretreatment with phenylarsine oxide (PAO) and benzylphosphonic acid (BPA), two chemical inhibitors of tyrosine phosphatase, reduced PTTH-stimulated enzymatic activity. Determination of ecdysteroid secretion showed that treatment with PAO and BPA did not affect basal ecdysteroid secretion, but greatly inhibited PTTH-stimulated ecdysteroid secretion, indicating that PTTH-stimulated PTP activity is indeed involved in ecdysteroid secretion. PTTH-stimulated phosphorylation of the extracellular signal-regulated kinase (ERK) and 4E-binding protein (4E-BP) was partially inhibited by pretreatment with either PAO or BPA, indicating the potential link between PTPs and phosphorylation of ERK and 4E-BP. In addition, we also found that in vitro treatment with 20-hydroxyecdysone did not affect PTP enzymatic activity. We further investigated the expressions of two important PTPs (PTP 1B (PTP1B) and the phosphatase and tension homologue (PTEN)) in Bombyx PGs. Our immunoblotting analysis showed that B. mori PGs contained the proteins of PTP1B and PTEN, with PTP1B protein undergoing development-specific changes. Protein levels of PTP1B and PTEN were not affected by PTTH treatment. The gene expression levels of PTP1B and PTEN showed development-specific changes. From these results, we suggest that PTTH-regulated PTP signaling may crosstalk with ERK and target of rapamycin (TOR) signaling pathways and is a necessary component for stimulation of ecdysteroid secretion.

Age-associated network controllability changes in first episode drug-naïve schizophrenia.

BACKGROUND: Recent neuroimaging studies revealed dysregulated neurodevelopmental, or/and neurodegenerative trajectories of both structural and functional connections in schizophrenia. However, how the alterations in the brain's structural connectivity lead to dynamic function changes in schizophrenia with age remains poorly understood. METHODS: Combining structural magnetic resonance imaging and a network control theory approach, the white matter network controllability metric (average controllability) was mapped from age 16 to 60 years in 175 drug-naïve schizophrenia patients and 155 matched healthy controls. RESULTS: Compared with controls, the schizophrenia patients demonstrated the lack of age-related decrease on average controllability of default mode network (DMN), as well as the right precuneus (a hub region of DMN), suggesting abnormal maturational development process in schizophrenia. Interestingly, the schizophrenia patients demonstrated an accelerated age-related decline of average controllability in the subcortical network, supporting the neurodegenerative model. In addition, compared with controls, the lack of age-related increase on average controllability of the left inferior parietal gyrus in schizophrenia patients also suggested a different pathway of brain development. CONCLUSIONS: By applying the control theory approach, the present study revealed age-related changes in the ability of white matter pathways to control functional activity states in schizophrenia. The findings supported both the developmental and degenerative hypotheses of schizophrenia, and suggested a particularly high vulnerability of the DMN and subcortical network possibly reflecting an illness-related early marker for the disorder.

Measurement reliability for individual differences in multilayer network dynamics: Cautions and considerations.

Multilayer network models have been proposed as an effective means of capturing the dynamic configuration of distributed neural circuits and quantitatively describing how communities vary over time. Beyond general insights into brain function, a growing number of studies have begun to employ these methods for the study of individual differences. However, test-retest reliabilities for multilayer network measures have yet to be fully quantified or optimized, potentially limiting their utility for individual difference studies. Here, we systematically evaluated the impact of multilayer community detection algorithms, selection of network parameters, scan duration, and task condition on test-retest reliabilities of multilayer network measures (i.e., flexibility, integration, and recruitment). A key finding was that the default method used for community detection by the popular generalized Louvain algorithm can generate erroneous results. Although available, an updated algorithm addressing this issue is yet to be broadly adopted in the neuroimaging literature. Beyond the algorithm, the present work identified parameter selection as a key determinant of test-retest reliability; however, optimization of these parameters and expected reliabilities appeared to be dataset-specific. Once parameters were optimized, consistent with findings from the static functional connectivity literature, scan duration was a much stronger determinant of reliability than scan condition. When the parameters were optimized and scan duration was sufficient, both passive (i.e., resting state, Inscapes, and movie) and active (i.e., flanker) tasks were reliable, although reliability in the movie watching condition was significantly higher than in the other three tasks. The minimal data requirement for achieving reliable measures for the movie watching condition was 20 min, and 30 min for the other three tasks. Our results caution the field against the use of default parameters without optimization based on the specific datasets to be employed - a process likely to be limited for most due to the lack of test-retest samples to enable parameter optimization.

Detecting hierarchical genome folding with network modularity.

Mammalian genomes are folded in a hierarchy of compartments, topologically associating domains (TADs), subTADs and looping interactions. Here, we describe 3DNetMod, a graph theory-based method for sensitive and accurate detection of chromatin domains across length scales in Hi-C data. We identify nested, partially overlapping TADs and subTADs genome wide by optimizing network modularity and varying a single resolution parameter. 3DNetMod can be applied broadly to understand genome reconfiguration in development and disease.

Identification of hub genes and signaling pathways related to gastric cells infected by Helicobacter pylori.

BACKGROUND: Helicobacter pylori is a pathogen involved in several gastroduodenal diseases, whose infection mechanisms have not been completely confirmed. To study the specific mechanism of gastropathy caused by H. pylori, we analyzed the gene microarray of gastric mucosa and gastric cells infected by H. pylori through bioinformatics analysis. METHODS: We downloaded GSE60427 and GSE74492 from the Gene Expression Omnibus (GEO) database, screened differentially expressed genes (DEGs), and identified the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) through R software. The Search Tool for the Retrieval of Interacting Genes (STRING) was applied to establish a protein-protein interaction (PPI) network and Cytoscape was used to identify the top seven hub genes. Besides, we also constructed the gene-microRNA(gene-miRNA) interaction through the miRTarBase v8.0 database by using the NetworkAnalyst tool. RESULTS: One hundred and fifteen DEGs were screened out, with 54 genes up-regulated and 61 genes down-regulated, among which seven hub genes, including "IGF1R," "APOE," "IRS1," "ATF3," "LCN2," "IL2RG," and "PI3," were considered as the main regulatory proteins in gastric cells when infected by H. pylori. CONCLUSION: In this study, hub genes and related signal enrichment pathways of gastropathy infected by H. pylori were analyzed through bioinformatics analysis based on the GSE60427 and GSE74492 datasets.

Unifying the Notions of Modularity and Core-Periphery Structure in Functional Brain Networks during Youth.

At rest, human brain functional networks display striking modular architecture in which coherent clusters of brain regions are activated. The modular account of brain function is pervasive, reliable, and reproducible. Yet, a complementary perspective posits a core-periphery or rich-club account of brain function, where hubs are densely interconnected with one another, allowing for integrative processing. Unifying these two perspectives has remained difficult due to the fact that the methodological tools to identify modules are entirely distinct from the methodological tools to identify core-periphery structure. Here, we leverage a recently-developed model-based approach-the weighted stochastic block model-that simultaneously uncovers modular and core-periphery structure, and we apply it to functional magnetic resonance imaging data acquired at rest in 872 youth of the Philadelphia Neurodevelopmental Cohort. We demonstrate that functional brain networks display rich mesoscale organization beyond that sought by modularity maximization techniques. Moreover, we show that this mesoscale organization changes appreciably over the course of neurodevelopment, and that individual differences in this organization predict individual differences in cognition more accurately than module organization alone. Broadly, our study provides a unified assessment of modular and core-periphery structure in functional brain networks, offering novel insights into their development and implications for behavior.

RE: Warnings and caveats in brain controllability.

The use of network control theory to analyze the organization of white matter fibers in the human brain has the potential to enable mechanistic theories of cognition, and to inform the development of novel diagnostics and treatments for neurological disease and psychiatric disorders (Gu et al., 2015). The recent article (Tu et al., 2018) aims to challenge several of the contributions of (Gu et al., 2015), and particularly the conclusions that brain networks are theoretically controllable from single regions, and that brain networks feature no specific controllability profiles when compared to random network models. Here we provide additional theoretical arguments in support of (Gu et al., 2015) and against the results and methodologies used in (Tu et al., 2018), thus settling that (i) brain networks are controllable from a single region, (ii) brain networks require large control energy, and (iii) brain networks feature distinctive controllability properties with respect to a class of random network models.

Network changes associated with transdiagnostic depressive symptom improvement following cognitive behavioral therapy in MDD and PTSD.

Despite widespread use of cognitive behavioral therapy (CBT) in clinical practice, its mechanisms with respect to brain networks remain sparsely described. In this study, we applied tools from graph theory and network science to better understand the transdiagnostic neural mechanisms of this treatment for depression. A sample of 64 subjects was included in a study of network dynamics: 33 patients (15 MDD, 18 PTSD) received longitudinal fMRI resting state scans before and after 12 weeks of CBT. Depression severity was rated on the Montgomery-Asberg Depression Rating Scale (MADRS). Thirty-one healthy controls were included to determine baseline network roles. Univariate and multivariate regression analyses were conducted on the normalized change scores of within- and between-system connectivity and normalized change score of the MADRS. Penalized regression was used to select a sparse set of predictors in a data-driven manner. Univariate analyses showed greater symptom reduction was associated with an increased functional role of the Ventral Attention (VA) system as an incohesive provincial system (decreased between- and decreased within-system connectivity). Multivariate analyses selected between-system connectivity of the VA system as the most prominent feature associated with depression improvement. Observed VA system changes are interesting in light of brain controllability descriptions: attentional control systems, including the VA system, fall on the boundary between-network communities, and facilitate integration or segregation of diverse cognitive systems. Thus, increasing segregation of the VA system following CBT (decreased between-network connectivity) may result in less contribution of emotional attention to cognitive processes, thereby potentially improving cognitive control.

Role of protein phosphatase 2A in PTTH-stimulated prothoracic glands of the silkworm, Bombyx mori.

In the present study, the roles of a major serine/threonine protein phosphatase 2A (PP2A) in prothoracicotropic hormone (PTTH)-stimulated prothoracic glands (PGs) of Bombyx mori were evaluated. Immunoblotting analysis showed that Bombyx PGs contained a structural A subunit (A), a regulatory B subunit (B), and a catalytic C subunit (C), with each subunit undergoing development-specific changes. The protein levels of each subunit were not affected by PTTH treatment. However, the highly conserved tyrosine dephosphorylation of PP2A C subunit (PP2Ac), which appears to be related to activity, was increased by PTTH treatment in a time-dependent manner. We further demonstrated that phospholipase C (PLC), Ca2+, and reactive oxygen species (ROS) are upstream signaling for the PTTH-stimulated dephosphorylation of PP2Ac. The determination of PP2A enzymatic activity showed that PP2A enzymatic activity was stimulated by PTTH treatment both in vitro and in vivo. Okadaic acid (OA), a specific PP2A inhibitor, prevented the PTTH-stimulated dephosphorylation of PP2Ac and reduced both basal and PTTH-stimulated PP2A enzymatic activity. The determination of ecdysteroid secretion showed that treatment with OA did not affect basal ecdysteroid secretion but did significantly inhibit PTTH-stimulated ecdysteroid secretion, indicating that PTTH-stimulated PP2A activity is involved in ecdysteroidogenesis. Treatment with OA stimulated the basal phosphorylation of the extracellular signal-regulated kinase (ERK) and 4E-binding protein (4E-BP) without affecting PTTH-stimulated ERK and 4E-BP phosphorylation. From these results, we hypothesize that PTTH-regulated PP2A signaling is a necessary component for the stimulation of ecdysteroidogenesis, potentially by mediating the link between ERK and TOR signaling pathways.

Expression of calcineurin in relation to the embryonic diapause process in the silkworm, Bombyx mori.

Calcineurin (CN) is a Ca2+/calmodulin-activated serine/threonine protein phosphatase that is essential for translating Ca2+ signals into changes in cell function and development. In the present study, we investigated changes in CN expression during the process of embryonic diapause in the silkworm, Bombyx mori. An immunoblot analysis showed that Bombyx eggs contained a 59-kDa catalytic A subunit (CNA), a 19-kDa regulatory B subunit (CNB), and a 27-kDa calcipressin; the CNA, CNB, and calcipressin were found to undergo differential changes between diapause and developing eggs during the diapause process. In developing eggs, protein levels of CNA and calcipressin were high during the first stages and then gradually decreased with embryonic development. However, CNB protein levels showed inverse temporal changes, with increased levels being detected during later embryonic stages of developing eggs. In diapause eggs, protein levels of CNA and calcipressin remained at relatively high levels during the first 8 days after oviposition, but CNB levels remained at low levels. CN enzymatic activity was directly determined and results showed that it remained at low levels in diapause eggs during the first 8 days after oviposition. However, in developing eggs, CN enzymatic activity sharply increased during the first several days, reached a peak during middle embryonic development, and then greatly decreased 5 or 6 days before hatching. Examination of temporal changes in mRNA expression levels of CNB also showed differences between diapause and HCl-treated eggs. These results demonstrated that protein levels of CNA, CNB, and calcipressin, transcriptional levels of CNB, and CN enzymatic activity between diapause and developing eggs are differentially regulated, and these regulated changes are likely related to the embryonic diapause process of B. mori.

Emergence of system roles in normative neurodevelopment.

Adult human cognition is supported by systems of brain regions, or modules, that are functionally coherent at rest and collectively activated by distinct task requirements. However, an understanding of how the formation of these modules supports evolving cognitive capabilities has not been delineated. Here, we quantify the formation of network modules in a sample of 780 youth (aged 8-22 y) who were studied as part of the Philadelphia Neurodevelopmental Cohort. We demonstrate that the brain's functional network organization changes in youth through a process of modular evolution that is governed by the specific cognitive roles of each system, as defined by the balance of within- vs. between-module connectivity. Moreover, individual variability in these roles is correlated with cognitive performance. Collectively, these results suggest that dynamic maturation of network modules in youth may be a critical driver for the development of cognition.

20-Hydroxyecdysone (20E) Primary Response Gene E75 Isoforms Mediate Steroidogenesis Autoregulation and Regulate Developmental Timing in Bombyx.

The temporal control mechanisms that precisely control animal development remain largely elusive. The timing of major developmental transitions in insects, including molting and metamorphosis, is coordinated by the steroid hormone 20-hydroxyecdysone (20E). 20E involves feedback loops to maintain pulses of ecdysteroid biosynthesis leading to its upsurge, whereas the underpinning molecular mechanisms are not well understood. Using the silkworm Bombyx mori as a model, we demonstrated that E75, the 20E primary response gene, mediates a regulatory loop between ecdysteroid biosynthesis and 20E signaling. E75 isoforms A and C directly bind to retinoic acid receptor-related response elements in Halloween gene promoter regions to induce gene expression thus promoting ecdysteroid biosynthesis and developmental transition, whereas isoform B antagonizes the transcriptional activity of isoform A/C through physical interaction. As the expression of E75 isoforms is differentially induced by 20E, the E75-mediated regulatory loop represents a fine autoregulation of steroidogenesis, which contributes to the precise control of developmental timing.

The energy landscape underpinning module dynamics in the human brain connectome.

Human brain dynamics can be viewed through the lens of statistical mechanics, where neurophysiological activity evolves around and between local attractors representing mental states. Many physically-inspired models of these dynamics define brain states based on instantaneous measurements of regional activity. Yet, recent work in network neuroscience has provided evidence that the brain might also be well-characterized by time-varying states composed of locally coherent activity or functional modules. We study this network-based notion of brain state to understand how functional modules dynamically interact with one another to perform cognitive functions. We estimate the functional relationships between regions of interest (ROIs) by fitting a pair-wise maximum entropy model to each ROI's pattern of allegiance to functional modules. This process uses an information theoretic notion of energy (as opposed to a metabolic one) to produce an energy landscape in which local minima represent attractor states characterized by specific patterns of modular structure. The clustering of local minima highlights three classes of ROIs with similar patterns of allegiance to community states. Visual, attention, sensorimotor, and subcortical ROIs are well-characterized by a single functional community. The remaining ROIs affiliate with a putative executive control community or a putative default mode and salience community. We simulate the brain's dynamic transitions between these community states using a random walk process. We observe that simulated transition probabilities between basins are statistically consistent with empirically observed transitions in resting state fMRI data. These results offer a view of the brain as a dynamical system that transitions between basins of attraction characterized by coherent activity in groups of brain regions, and that the strength of these attractors depends on the ongoing cognitive computations.

Optimal trajectories of brain state transitions.

The complexity of neural dynamics stems in part from the complexity of the underlying anatomy. Yet how white matter structure constrains how the brain transitions from one cognitive state to another remains unknown. Here we address this question by drawing on recent advances in network control theory to model the underlying mechanisms of brain state transitions as elicited by the collective control of region sets. We find that previously identified attention and executive control systems are poised to affect a broad array of state transitions that cannot easily be classified by traditional engineering-based notions of control. This theoretical versatility comes with a vulnerability to injury. In patients with mild traumatic brain injury, we observe a loss of specificity in putative control processes, suggesting greater susceptibility to neurophysiological noise. These results offer fundamental insights into the mechanisms driving brain state transitions in healthy cognition and their alteration following injury.

Functional hypergraph uncovers novel covariant structures over neurodevelopment.

Brain development during adolescence is marked by substantial changes in brain structure and function, leading to a stable network topology in adulthood. However, most prior work has examined the data through the lens of brain areas connected to one another in large-scale functional networks. Here, we apply a recently developed hypergraph approach that treats network connections (edges) rather than brain regions as the unit of interest, allowing us to describe functional network topology from a fundamentally different perspective. Capitalizing on a sample of 780 youth imaged as part of the Philadelphia Neurodevelopmental Cohort, this hypergraph representation of resting-state functional MRI data reveals three distinct classes of subnetworks (hyperedges): clusters, bridges, and stars, which respectively represent homogeneously connected, bipartite, and focal architectures. Cluster hyperedges show a strong resemblance to previously-described functional modules of the brain including somatomotor, visual, default mode, and salience systems. In contrast, star hyperedges represent highly localized subnetworks centered on a small set of regions, and are distributed across the entire cortex. Finally, bridge hyperedges link clusters and stars in a core-periphery organization. Notably, developmental changes within hyperedges are ordered in a similar core-periphery fashion, with the greatest developmental effects occurring in networked hyperedges within the functional core. Taken together, these results reveal a novel decomposition of the network organization of human brain, and further provide a new perspective on the role of local structures that emerge across neurodevelopment. Hum Brain Mapp 38:3823-3835, 2017. © 2017 Wiley Periodicals, Inc.

Complex decorrelation averaging in optical coherence tomography: a way to reduce the effect of multiple scattering and improve image contrast in a dynamic scattering medium.

We demonstrate that complex decorrelation averaging can reduce the effect of multiple scattering and improve optical coherence tomography (OCT) imaging contrast. Complex decorrelation averaging calculates the product of an A-scan and the complex conjugate of a subsequent A-scan. The resultant signal is the product of the amplitudes and the phase difference. All these resulting complex signals at a particular location are then averaged. We take advantage of the fact that complex averaging, in contrast to conventional magnitude averaging, is sensitive to phase decorrelation. Sample motion that increases signal phase variance results in lower signal magnitude after complex averaging. Such motion preferentially results in a faster decorrelation of the multiple scattering signal when compared to the single scattering signal with each scattering event spreading the phase. This indicates that we may reduce multiple scattering by implementing complex decorrelation averaging to preferentially reduce the magnitude of the multiply scattered light signal in OCT images. By adjusting the time between phase-differenced A-scans, one can regulate the amount of measured decorrelation. We have performed experiments on liquid phantoms that give experimental evidence for this hypothesis. A substantial improvement in OCT image contrast using complex decorrelation averaging is demonstrated.

Stimulation-Based Control of Dynamic Brain Networks.

The ability to modulate brain states using targeted stimulation is increasingly being employed to treat neurological disorders and to enhance human performance. Despite the growing interest in brain stimulation as a form of neuromodulation, much remains unknown about the network-level impact of these focal perturbations. To study the system wide impact of regional stimulation, we employ a data-driven computational model of nonlinear brain dynamics to systematically explore the effects of targeted stimulation. Validating predictions from network control theory, we uncover the relationship between regional controllability and the focal versus global impact of stimulation, and we relate these findings to differences in the underlying network architecture. Finally, by mapping brain regions to cognitive systems, we observe that the default mode system imparts large global change despite being highly constrained by structural connectivity. This work forms an important step towards the development of personalized stimulation protocols for medical treatment or performance enhancement.