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, 0.5, 1.0, 1.5, and 2.0 µg/ml. We constructed whole-brain functional networks for each subject under different conditions and identify community structures. Subsequently, we calculated the global and local topological properties of whole-brain network to investigate the alterations in functional integration and segregation with deepening propofol sedation. Additionally, we assessed the alteration of key nodes within the whole-brain community structure at each effect-site concentrations level. We found that global participation was significantly increased at high effect-site concentrations, which was mediated by bilateral postcentral gyrus. Meanwhile, connector hubs appeared and were located in posterior cingulate cortex and precentral gyrus at high effect-site concentrations. Finally, nodal participation coefficients of connector hubs were closely associated to the level of sedation. These findings provide valuable insights into the relationship between increasing propofol dosage and enhanced functional interaction within the whole-brain networks.

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. We recorded eyes-open, resting-state EEG and performance in the Nine-Hole Peg Test (NHPT) before cTBS, immediately after cTBS, and 80 minutes after cTBS. We identified nine states using a Hidden Markov Model (HMM)-based approach to describe the process of dynamic brain changes. The spatial activation, temporal profiles of HMM states and behavioral performance of NHPT were assessed and compared. cTBS altered the temporal profiles of S1-S5 immediately after cTBS and the temporal profiles of S5, S6 and S7 80 min after cTBS. Moreover, cTBS improved motor function of the left hand. State 1 was characterized as the activation of right occipito-temporal area, and NHPT behavioral performance of the left hand positively correlated with the occurrence of state 1, and negatively correlated with the interval time of state 1 after cTBS. The transitions between S1 or S7 and other states showed dynamic reconfiguration during after-effect sustained time after cTBS. These results suggest that the dynamic characteristics of state 1 are potential biomarkers for characterizing the aftereffect changes of cTBS.

Impact of climate change on atopic dermatitis: A review by the International Eczema Council.

Atopic dermatitis (AD), the most burdensome skin condition worldwide, is influenced by climatic factors and air pollution; however, the impact of increasing climatic hazards on AD remains poorly characterized. Leveraging an existing framework for 10 climatic hazards related to greenhouse gas emissions, we identified 18 studies with evidence for an impact on AD through a systematic search. Most climatic hazards had evidence for aggravation of AD the impact ranged from direct effects like particulate matter-induced AD exacerbations from wildfires to the potential for indirect effects like drought-induced food insecurity and migration. We then created maps comparing the past, present, and future projected burden of climatic hazards to global AD prevalence data. Data are lacking, especially from those regions most likely to experience more climatic hazards. We highlight gaps important for future research: understanding the synergistic impacts of climatic hazards on AD, long-term disease activity, the differential impact on vulnerable populations, and how basic mechanisms explain population-level trends.

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. Then we evaluated the Pearson's correlations between disrupted network metrics and neuropsychological parameters. For global topology, the CSVD-c group exhibited significantly decreased global (Eglob) and local (Eloc) efficiency and increased shortest path length compared with the controls, while no significant difference was found between the CSVD-c and CSVD-n groups. For regional topology, although all groups showed highly similar hub distributions, compare with control group, the CSVD-c group exhibited significantly decreased nodal efficiency mainly in the bilateral supplementary motor area (SMA), median cingulate gyrus (DCG) and right orbital middle frontal gyrus, while the CSVD-n group showed significantly decreased nodal efficiency only in the right SMA. Notably, Eglob, Eloc and nodal efficiency of the right anterior cingulate gyrus, DCG, middle temporal gyrus and left insula showed significantly negative correlations with depression score, significantly positive correlations with Rey auditory verbal learning test and symbol digit modalities test scores in CSVD-n group, as well as significantly negative correlations with Stroop color-word test scores in CSVD-c group. The WM networks of CSVD patients are characterized by decreased global integration and local specialization, and decreased nodal efficiency highly related to depression and cognitive dysfunction in the attention, default mode network and sensorimotor regions. These findings provide new insight into the neurobiological mechanisms of CSVD and concomitant affective and cognitive disorders.

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. However, compared with CSVD-m patients and controls, CSVD-s patients exhibited significantly decreased local efficiency, with partially reorganized hub distributions. For regional topology, CSVD-s patients showed significantly decreased nodal efficiency in the bilateral anterior cingulate gyrus, caudate nucleus, right opercular inferior frontal gyrus (IFGoperc), supplementary motor area (SMA), insula and left orbital superior frontal gyrus and angular gyrus. Intriguingly, global/local efficiency and nodal efficiency of the bilateral caudate nucleus, right IFGoperc, SMA and left angular gyrus showed significant correlations with cognitive parameters in the CSVD-s group, while only the left pallidum showed significant correlations with cognitive metrics in the CSVD-m group. In conclusion, the decreased local specialization of brain structural networks in patients with different CSVD burdens provides novel insights into understanding the brain structural alterations in relation to CSVD severity. Cognitive correlations with brain structural network efficiency suggest their potential use as neuroimaging biomarkers to assess the severity of CSVD.

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. Recently, the US Food and Drug Administration approved two new topical non-steroidal agents for treating psoriasis that target different pathogenic pathways than the conventional treatments. Roflumilast is a phosphodiesterase type 4 inhibitor approved for the treatment of plaque psoriasis in patients aged 12 years and older. Tapinarof is a novel aryl hydrocarbon receptor modulator approved for adult psoriasis and currently undergoing studies for pediatric psoriasis. Ongoing efforts are also being made to optimize conventional treatments, for instance, a new foam formulation of halobetasol propionate was recently approved for pediatric psoriasis. Clinical trials of various new drugs targeting one or multiple pathogenic pathways of psoriasis, such as Janus kinase inhibitors, different formulations of phosphodiesterase type 4 inhibitors, and aryl hydrocarbon receptor modulators have also been explored. The recent emergence of novel topical agents provides promising new options for managing pediatric psoriasis with the potential to improve clinical outcomes and quality of life. In this article, we review the mechanism of action, efficacy, and safety profile of novel topical agents and discuss their potential roles in the management of pediatric psoriasis.

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. We found that both the control and CSVD groups exhibited efficient small-world organization in GM networks. However, compared to controls, CSVD-c and CSVD-n patients exhibited increased global and local efficiency (Eglob/Eloc) and decreased shortest path lengths (Lp), indicating increased global integration and local specialization in structural networks. Although there was no significant global topology change, partially reorganized hub distributions were found between CSVD-c and CSVD-n patients. Importantly, regional topology in nonhub regions was significantly altered between CSVD-c and CSVD-n patients, including the bilateral anterior cingulate gyrus, left superior parietal gyrus, dorsolateral superior frontal gyrus, and right MTG, which are involved in the default mode network (DMN) and sensorimotor functional modules. Intriguingly, the global metrics (Eglob, Eloc, and Lp) were significantly correlated with MoCA, AVLT, and SCWT scores in the control group but not in the CSVD-c and CSVD-n groups. In contrast, the global metrics were significantly correlated with the SDMT score in the CSVD-s and CSVD-n groups but not in the control group. Patients with CSVD show a disrupted balance between local specialization and global integration in their GM structural networks. The altered regional topology between CSVD-c and CSVD-n patients may be due to different etiological contributions, which may offer a novel understanding of the neurobiological processes involved in CSVD with CMBs.

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. RESULTS: Compared with the CSVD-n and control groups, the CSVD-c group showed a significant FA decrease and AD, RD and MD increases mainly in the cognitive and sensorimotor-related WM tracts. There was no significant difference in any diffusion metric between the CSVD-n and control groups. Furthermore, the widespread regional diffusion alterations among groups were significantly correlated with cognitive parameters in both the CSVD-c and CSVD-n groups. Notably, we applied the multiple kernel learning technique in multivariate pattern analysis to combine multiregion and multiparameter diffusion features, yielding an average accuracy >77 % for three binary classifications, which showed a considerable improvement over the single modality approach. LIMITATIONS: We only grouped the study according to the presence or absence of CMBs. CONCLUSIONS: CSVD patients with CMBs have extensive WM microstructural deterioration. Combining DTI-derived diffusivity and anisotropy metrics can provide complementary information for assessing WM alterations associated with cognitive dysfunction and serve as a potential discriminative pattern to detect CSVD at the individual level.

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. We calculated the amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo). One-way analysis of covariance was applied to evaluate the above indicators among the 3 groups, and the mean ALFF/fALFF/ReHo values of altered brain regions were then correlated with clinical features of patients. RESULTS: Compared with the NDPN group, the DPN group showed significantly decreased ALFF values in the right orbital superior frontal gyrus (ORBsup) and medial superior frontal gyrus (SFGmed), and increased ALFF values in the left inferior temporal gyrus (ITG) and decreased fALFF values in the right SFGmed. Compared with HCs, the NDPN group showed increased ALFF values in the right ORBsup, middle frontal gyrus, and left orbital middle frontal gyrus, and decreased fALFF values in the right middle temporal gyrus. Notably, the mean ALFF values of the right ORBsup were significantly negatively correlated with Toronto Clinical Scoring System scores and gait speed in diabetics. The mean ALFF/fALFF values of right SFGmed and the mean ALFF values of left ITG and right ORBsup were significantly differentiated between DPN and patients witht NDPN in receiver operating characteristic curve analysis. CONCLUSION: Patients with DPN have abnormal brain activity in sensorimotor and cognitive brain areas, which may implicate the underlying neurophysiological mechanisms in intrinsic brain activity.

Early Cutaneous Manifestations of COVID-19: A Systematic Review and Public Health Implications.

INTRODUCTION: Cutaneous manifestations before other symptoms have great potential for early COVID-19 diagnosis to prevent surge. METHODS: We conducted a search of PubMed and Embase databases through April 11, 2021 to include 39 studies reporting skin manifestations occurring prior to any other COVID-19 symptoms in laboratory-confirmed cases. RESULTS: Ninety-seven patients were included. Urticarial (24.7%) and maculopapular (22.7%) lesions were most common, followed by pernio (17.5%), vesicular (14.4%), papulosquamous (8.2%), and purpuric (5.1%) lesions. Cutaneous to systemic symptom latency ranged from 2 to 20 days in cases that reported it (26%), while skin lesions were the only presentation in 23 cases (23.7%). Skin lesions were the only COVID-19 manifestation in 58.8% of pernio, 40% of vesicular, 16.6% of urticarial, 18.2% of maculopapular, and 12.5% of papulosquamous presymptomatic cases. Although sample size is limited, all purpuric cases developed other symptom(s) later. CONCLUSIONS: Pernio and purpuric lesions have been well-associated with COVID-19, but papulosquamous, vesicular, mild maculopapular, and urticarial lesions can easily be dismissed as unrelated to COVID-19. Pernio lesions are thought to be related to strong immune response and low contagiousness, while purpuric and vesicular cases are speculated to be related to higher SARS-CoV2 viral load, severity, and contagiousness. All rashes, even without other symptoms, should necessitate high level of suspicion for isolation or contact tracing.

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. Specifically, the generative component of our hybrid model is parameterized by a multi-view variational autoencoder, in which we regard the brain activity of left and right hemispheres and their difference as three distinct views and use the product of expert mechanism in its inference network. The discriminative component of our hybrid model is implemented by a multi-label classification network with an asymmetric focal loss. For more accurate emotion decoding, we first adopt a label-aware module for emotion-specific neural representation learning and then model the dependency of emotional states by a masked self-attention mechanism. Extensive experiments on two visually evoked emotional datasets show the superiority of our method.

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). Then, we further explored the optimal brain regions to promote the transition of brain states between MDD and health through external stimulation of the model. Based on the whole-brain model successfully fitting the brain state space in MDD and the health, we demonstrated that the transition from MDD to health is achieved by the excitatory activation of the limbic system and from health to MDD by the inhibitory stimulation of the reward circuit. Our finding provides novel biophysical evidence for the neural mechanism of MDD and its recovery and allows the discovery of new stimulation targets for MDD recovery.

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. RESULTS: Active TAO patients showed significantly increased GMV in the right inferior frontal gyrus, left superior frontal gyrus (SFG), orbital superior frontal gyrus, orbital middle frontal gyrus, precuneus and postcentral gyrus compared with controls and significantly increased GMV in the right middle temporal gyrus, left SFG and precuneus compared with the inactive TAO group. No significant differences were observed between the inactive TAO group and healthy controls. Notably, the receiver operating characteristic (ROC) curve analysis demonstrated altered GMV among groups and significantly (p < 0.001) differentiated active TAO from inactive TAO and healthy controls. In addition, the mean GMV in precuneus and postcentral gyrus were significantly associated with clinical parameters in active TAO. CONCLUSION: Our findings suggested the localized GMV alterations among groups were associated with the pathophysiology of TAO and served as a potential discriminative pattern to detect clinical phases of TAO at the individual level. The altered brain morphometry may suggest a corresponding process of self-repair and remodeling of the brain structure as the disease progresses in TAO.

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

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. We applied 40 s-long cTBS over the left motor cortex of 28 healthy participants. Before and in multi-sessions up to 90 min after cTBS, their performance in a Nine-Hole Peg Test (NHPT), that measures the hand dexterity, and resting state EEG were recorded. Resting-sate EEG data were clustered into four microstates (namely A, B, C, and D) using k-means clustering algorithms. cTBS-induced changes in NHPT performance, microstate dynamics and functional connectivity networks were comprehensively assessed. As compared with baseline, the completion time of NHPT became shorter immediately after cTBS, suggesting cTBS-induced motor function improvement. After cTBS, the topography of microstate B revealed a greater change compared with other three topographies. Importantly, cTBS-induced decrease in completion time of NHPT correlated with cTBS-induced decrease of the mean occurrence of microstate B. Functional connectivity analysis further revealed that cTBS led to an increase of the node efficiency at C4 electrode in microstate B. These results indicated the specific modulation of cTBS over the motor cortex on the dynamics of microstate B. This work provided the evidence of the association between B and motor function, and it also implies the modulation of cTBS over the motor network. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-021-09726-6.

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. Both univariate analysis and multivariate pattern analysis (MVPA) approaches were applied to investigate differences in brain morphometry among groups. Results: In univariate analysis, GMV and WMV differences were compared among groups using voxel-based morphometry (VBM) with diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL). Compared to healthy controls, the CSVD-c group and CSVD-n group showed significantly lower GMV than the control group in similar brain clusters, mainly including the right superior frontal gyrus (medial orbital), left anterior cingulate gyrus, right inferior frontal gyrus (triangular part) and left superior frontal gyrus (medial), while the CSVD-n group also showed significantly lower WMV in the cluster of the left superior frontal gyrus (medial). No significant GMV or WMV differences were found between the CSVD-c group and the CSVD-n group. Specifically, we applied the multiple kernel learning (MKL) technique in MVPA to combine GMV and WMV features, yielding an average of >80% accuracy for three binary classification problems, which was a considerable improvement over the individual modality approach. Consistent with the univariate analysis, the MKL weight maps revealed default mode network and subcortical region damage associated with CSVD compared to controls. On the other hand, when classifying the CSVD-c group and CSVD-n group in the MVPA analysis, we found that some WMVs were highly weighted regions (left olfactory cortex and right middle frontal gyrus), which hinted at the presence of different white matter alterations in the CSVD-c group. Conclusion: Our findings not only suggested that the localized alterations in GMV and WMV appeared to be associated with the pathophysiology of CSVD but also indicated that altered brain morphometry could be a potential discriminative pattern to detect CSVD at the individual level.

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. Here, we use the WIHN model to investigate the mechanical and molecular responses of laboratory and African spiny mice, and report these models demonstrate opposing trends in spatiotemporal morphogenetic field formation with association to wound stiffness landscapes. Transcriptome analysis and K14-Cre-Twist1 transgenic mice show the Twist1 pathway acts as a mediator for both epidermal-dermal interactions and a competence factor for periodic patterning, differing from those used in development. We propose a Turing model based on tissue stiffness that supports a two-scale tissue mechanics process: (1) establishing a morphogenetic field within the wound bed (mm scale) and (2) symmetry breaking of the epidermis and forming periodically arranged hair primordia within the morphogenetic field (µm scale). Thus, we delineate distinct chemo-mechanical events in building a Turing morphogenesis-competent field during WIHN of laboratory and African spiny mice and identify its evo-devo advantages with perspectives for regenerative medicine.

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. While mouse and human skin share some similarities, their skin architectures differ in some respects. However, we use recent research in haired murine skin because of the available experimental data. Skin suffers from changes in both its appendages and inter-appendage regions. The elderly exhibit wrinkles and loose dermis and are more likely to suffer from wounds and superficial abrasions with poor healing. They also have a reduction in the number of skin appendages. While telogen is prolonged in aging murine skin, hair follicle stem cells can be rejuvenated to enter anagen if transplanted to a young skin environment. We highlight recent single-cell analyses performed on epidermis and aging human skin which identified new basal cell subpopulations that shift in response to wounding. This may be due to alterations of basement membrane stiffness which would change tissue mechanics in aging skin, leading to altered homeostatic dynamics. We propose that the extracellular matrix (ECM) may play a key role as a chemo-mechanical integrator of the multi-layered senescence-associated signaling pathways, dictating the tissue mechanical landscape of niche microenvironments in aging phenotypes. We show examples where failed chemo-mechanical signaling leads to deteriorating homeostasis during skin aging and suggest potential therapeutic strategies to guide future research to delay the aging processes.

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

Background: 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. However, the ERPs in single trials vary in latency and length, which makes it difficult to accurately discriminate the targets against their neighbors, the near-non-targets. Thus, it reduces the efficiency of the BCI paradigm. Methods: To overcome the difficulty of ERP detection against their neighbors, we proposed a simple but novel ternary classification method to train the classifiers. The new method not only distinguished the target against all other samples but also further separated the target, near-non-target, and other, far-non-target samples. To verify the efficiency of the new method, we performed the RSVP experiment. The natural scene pictures with or without pedestrians were used; the ones with pedestrians were used as targets. Magnetoencephalography (MEG) data of 10 subjects were acquired during presentation. The SVM and CNN in EEGNet architecture classifiers were used to detect the onsets of target. Results: We obtained fairly high target detection scores using SVM and EEGNet classifiers based on MEG data. The proposed ternary classification method showed that the near-non-target samples can be discriminated from others, and the separation significantly increased the ERP detection scores in the EEGNet classifier. Moreover, the visualization of the new method suggested the different underling of SVM and EEGNet classifiers in ERP detection of the RSVP experiment. Conclusion: In the RSVP experiment, the near-non-target samples contain separable ERP activity. The ERP detection scores can be increased using classifiers of the EEGNet model, by separating the non-target into near- and far-targets based on their delay against targets.

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. Based on encoder-decoder architecture, we design a dual tasks framework with low-level outputs for boundary detection and high-level outputs for layers segmentation. Specifically, we first use the multi-scale input strategy to enrich the spatial information in the deep features of encoder. For low-level features from encoder, we design an edge aware (EA) module in skip connection to extract the pure edge features. Then, a U-structure feature enhanced (UFE) module is designed in all skip connections to enlarge the features receptive fields from the encoder. Besides, a canny edge fusion (CEF) module is introduced to aforementioned architecture, which can fuse the priory edge information from segmentation task to boundary detection branch for a better predication. Furthermore, we model each boundary as a vertical coordinates distribution for boundary detection. Based on this distribution, a topology guarantee loss with combined A-scan regression loss and structure loss is proposed to make an accurate and guaranteed topological boundary set. The method is evaluated on two public datasets and the results demonstrate that the BAU-Net achieves promising performance than other state-of-the-art methods.