Trait and plasticity evolution under competition and mutualism in evolving pairwise yeast communities.

Although we have a good understanding of how phenotypic plasticity evolves in response to abiotic environments, we know comparatively less about responses to biotic interactions. We experimentally tested how competition and mutualism affected trait and plasticity evolution of pairwise communities of genetically modified brewer's yeast. We quantified evolutionary changes in growth rate, resource use efficiency (RUE), and their plasticity in strains evolving alone, with a competitor, and with a mutualist.

Dynamical changes of interaction across functional brain communities during propofol-induced sedation.

It is crucial to understand how anesthetics disrupt information transmission within the whole-brain network and its hub structure to gain insight into the network-level mechanisms underlying propofol-induced sedation. However, the influence of propofol on functional integration, segregation, and community structure of whole-brain networks were still unclear. We recruited 12 healthy subjects and acquired resting-state functional magnetic resonance imaging data during 5 different propofol-induced effect-site concentrations (CEs): 0, 0.

Tracking the Immediate and Short-Term Effects of Continuous Theta Burst Stimulation on Dynamic Brain States.

Continuous Theta Burst Stimulation (cTBS) has been shown to modulate cortical oscillations and induce cortical inhibitory effects. Electroencephalography (EEG) studies have shown some immediate effects of cTBS on brain activity. To investigate both immediate effects and short-term effects of cTBS on dynamic brain changes, cTBS was applied to 22 healthy participants over their left motor cortex.

Disrupted brain structural networks associated with depression and cognitive dysfunction in cerebral small vessel disease with microbleeds.

Emerging evidence highlights cerebral microbleeds (CMBs) as hallmarks of cerebral small vessel disease (CSVD) underlying depression and cognitive dysfunction. This study aimed to reveal how depression and cognition-related white matter (WM) abnormalities are topologically presented, and the network-level structural disruptions associated with CMBs in CSVD. We used probabilistic diffusion tractography and graph theory to investigate brain WM network topology in CSVD patients with (n = 64, CSVD-c) and without (n = 138, CSVD-n) CMBs and 90 healthy controls.

Disrupted Gray Matter Networks Associated with Cognitive Dysfunction in Cerebral Small Vessel Disease.

This study aims to investigate the disrupted topological organization of gray matter (GM) structural networks in cerebral small vessel disease (CSVD) patients with cerebral microbleeds (CMBs). Subject-wise structural networks were constructed from GM volumetric features of 49 CSVD patients with CMBs (CSVD-c), 121 CSVD patients without CMBs (CSVD-n), and 74 healthy controls. The study used graph theory to analyze the global and regional properties of the network and their correlation with cognitive performance.

Topical Management of Pediatric Psoriasis: A Review of New Developments and Existing Therapies.

Psoriasis is a chronic immune-mediated disorder that commonly affects adults and children. In recent years, pediatric psoriasis has increased in prevalence and the disease is often associated with various comorbidities and psychological distress. The conventional topical treatments for psoriasis, such as corticosteroids, calcineurin inhibitors, vitamin D analogs, anthralin, and coal tar, are often limited by their side effects, tolerability, and/or efficacy, particularly for use in children and on sensitive and intertriginous areas.

Decreased Local Specialization of Brain Structural Networks Associated with Cognitive Dysfuntion Revealed by Probabilistic Diffusion Tractography for Different Cerebral Small Vessel Disease Burdens.

To reveal the network-level structural disruptions associated with cognitive dysfunctions in different cerebral small vessel disease (CSVD) burdens, we used probabilistic diffusion tractography and graph theory to investigate the brain network topology in 67 patients with a severe CSVD burden (CSVD-s), 133 patients with a mild CSVD burden (CSVD-m) and 89 healthy controls. We used one-way analysis of covariance to assess the altered topological measures between groups, and then evaluated their Pearson correlation with cognitive parameters. Both the CSVD and control groups showed efficient small-world organization in white matter (WM) networks.

Characterization of white matter microstructural abnormalities associated with cognitive dysfunction in cerebral small vessel disease with cerebral microbleeds.

Background: Diffusion tensor imaging (DTI) is recommended as a sensitive method to explore white matter (WM) microstructural alterations. Cerebral small vessel disease (CSVD) may be accompanied by extensive WM microstructural deterioration, while cerebral microbleeds (CMBs) are an important factor affecting CSVD.

Methods: Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) images from 49 CSVD patients with CMBs (CSVD-c), 114 CSVD patients without CMBs (CSVD-n), and 83 controls were analyzed using DTI-derived tract-based spatial statistics to detect WM diffusion changes among groups.

Multi-View Multi-Label Fine-Grained Emotion Decoding From Human Brain Activity.

Decoding emotional states from human brain activity play an important role in the brain-computer interfaces. Existing emotion decoding methods still have two main limitations: one is only decoding a single emotion category from a brain activity pattern and the decoded emotion categories are coarse-grained, which is inconsistent with the complex emotional expression of humans; the other is ignoring the discrepancy of emotion expression between the left and right hemispheres of the human brain. In this article, we propose a novel multi-view multi-label hybrid model for fine-grained emotion decoding (up to 80 emotion categories) which can learn the expressive neural representations and predict multiple emotional states simultaneously.

Altered Intrinsic Brain Activity Related to Neurologic and Motor Dysfunction in Diabetic Peripheral Neuropathy Patients.

Context: Brain functional alterations in type 2 diabetes with diabetic peripheral neuropathy (DPN) related to motor dysfunction remain largely unknown.

Objective: We aimed to explore intrinsic resting brain activity in DPN.

Methods: A total of 28 patients with DPN, 43 patients with diabetes and without DPN (NDPN), and 32 healthy controls (HCs) were recruited and underwent resting-state functional magnetic resonance imaging.

Driving brain state transitions in major depressive disorder through external stimulation.

Major depressive disorder (MDD) as a dysfunction of neural circuits and brain networks has been established in modern neuroimaging sciences. However, the brain state transitions between MDD and health through external stimulation remain unclear, which limits translation to clinical contexts and demonstrable clinical utility. We propose a framework of the large-scale whole-brain network model for MDD linking the underlying anatomical connectivity with functional dynamics obtained from diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI).

Morphological brain changes between active and inactive phases of thyroid-associated ophthalmopathy: A voxel-based morphometry study.

Aim: To explore the morphological brain changes among active thyroid-associated ophthalmopathy (TAO) patients, inactive TAO patients and healthy controls and to investigate the neuropathological relationship of TAO using magnetic resonance imaging (MRI) data.

Methods: In this observational case-control study, we included 35 inactive TAO patients, 37 active TAO patients and 23 healthy controls. Voxel-based morphometry (VBM) analysis was conducted to evaluate the gray matter volume (GMV) changes among groups, and the correlations between GMV alterations and clinical parameters in active and inactive TAO groups were investigated.

Continuous theta-burst stimulation modulates resting-state EEG microstates in healthy subjects.

Unlabelled: Continuous theta-burst stimulation (cTBS) induces long-lasting inhibitory effects on cortical excitability. Although cTBS has been reported to modulate neural oscillations and functional connectivity, it is still unclear how cTBS affects brain dynamics that could be captured by the resting-sate EEG microstate sequences. This study aims to investigate how cTBS over the left motor cortex affects brain dynamics.

Altered Brain Morphometry in Cerebral Small Vessel Disease With Cerebral Microbleeds: An Investigation Combining Univariate and Multivariate Pattern Analyses.

Purpose: The objective of this study was to evaluate whether altered gray matter volume (GMV) and white matter volume (WMV) are associated with the presence of cerebral microbleeds (CMBs) in cerebral small vessel disease (CSVD).

Materials And Methods: In this study, we included 26 CSVD patients with CMBs (CSVD-c), 43 CSVD patients without CMBs (CSVD-n) and 39 healthy controls. All participants underwent cognitive assessment testing.

Symmetry breaking of tissue mechanics in wound induced hair follicle regeneration of laboratory and spiny mice.

Tissue regeneration is a process that recapitulates and restores organ structure and function. Although previous studies have demonstrated wound-induced hair neogenesis (WIHN) in laboratory mice (Mus), the regeneration is limited to the center of the wound unlike those observed in African spiny (Acomys) mice. Tissue mechanics have been implicated as an integral part of tissue morphogenesis.

Boundary Aware U-Net for Retinal Layers Segmentation in Optical Coherence Tomography Images.

Retinal layers segmentation in optical coherence tomography (OCT) images is a critical step in the diagnosis of numerous ocular diseases. Automatic layers segmentation requires separating each individual layer instance with accurate boundary detection, but remains a challenging task since it suffers from speckle noise, intensity inhomogeneity, and the low contrast around boundary. In this work, we proposed a boundary aware U-Net (BAU-Net) for retinal layers segmentation by detecting accurate boundary.

Target Detection Using Ternary Classification During a Rapid Serial Visual Presentation Task Using Magnetoencephalography Data.

The rapid serial visual presentation (RSVP) paradigm is a high-speed paradigm of brain-computer interface (BCI) applications. The target stimuli evoke event-related potential (ERP) activity of odd-ball effect, which can be used to detect the onsets of targets. Thus, the neural control can be produced by identifying the target stimulus.

Tissue Mechanics in Haired Murine Skin: Potential Implications for Skin Aging.

During aging, the skin undergoes changes in architecture and composition. Skin aging phenotypes occur due to accumulated changes in the genome/epigenome, cytokine/cell adhesion, cell distribution/extracellular matrix (ECM), etc. Here we review data suggesting that tissue mechanics also plays a role in skin aging.

Changes of resting-state EEG microstates induced by low-frequency repetitive transcranial magnetic stimulation.

Repetitive Transcranial magnetic stimulation (rTMS) is a noninvasive brain stimulation technique that can influence cortical excitability. Low-frequency rTMS (stimulation frequency ≤1Hz) induces long-lasting inhibitory effects on cortical excitability. At the same time, EEG microstates have been studied and have been thought to corresponding to functional relevant brain-states.

Temporal Dynamics on Decoding Target Stimuli in Rapid Serial Visual Presentation using Magnetoencephalography.

Rapid serial visual presentation (RSVP) is a high efficient paradigm in brain-computer interface (BCI). Target detection accuracy is the first consideration of RSVP-BCI. But the influence of different frequency bands and time ranges on decoding accuracy are still an open questions.

CSU-Net: A Context Spatial U-Net for Accurate Blood Vessel Segmentation in Fundus Images.

Blood vessel segmentation in fundus images is a critical procedure in the diagnosis of ophthalmic diseases. Recent deep learning methods achieve high accuracy in vessel segmentation but still face the challenge to segment the microvascular and detect the vessel boundary. This is due to the fact that common Convolutional Neural Networks (CNN) are unable to preserve rich spatial information and a large receptive field simultaneously.

Transition and Dynamic Reconfiguration of Whole-Brain Network in Major Depressive Disorder.

Major depressive disorder (MDD) has been characterized by abnormal brain activity and interactions across the whole-brain functional networks. However, the underlying alteration of brain dynamics remains unclear. Here, we aim to investigate in detail the temporal dynamics of brain activity for MDD, and to characterize the spatiotemporal specificity of whole-brain networks and transitions across them.