Abnormal Topological Organization of Human Brain Connectome in Primary Dysmenorrhea Patients Using Graph Theoretical Analysis.

Background: Accumulating studies have revealed altered brain function and structure in regions linked to sensory, pain and emotion in individuals with primary dysmenorrhea (PD). However, the changes in the topological properties of the brain's functional connectome in patients with PD experiencing chronic pain remain poorly understood. Purpose: Our study aimed to explore the mechanism of functional brain network impairment in individuals withPD through a graph-theoretic analysis. Material and Methods: This study was a randomized controlled trial that included individuals with PD and healthy controls (HC) from June 2021 to June 2022. The experiment took place in the magnetic resonance imaging facility at Jiangxi Provincial People's Hospital. Static MRI scans were conducted on 23 female patients with PD and 23 healthy female controls. A two-sample t-test was conducted to compare the global and nodal indices between the two groups, while the Network-Based Statistics (NBS) method was utilized to explore the functional connectivity alterations between the groups. Results: In the global index, The PD group exhibited decreased Sigma (p = 0.0432) and Gamma (p = 0.0470) compared to the HC group among the small-world network properties.(p<0.05) In the nodal index, the PD group displayed reduced betweenness centrality and increased degree centrality in the default mode network (DMN), along with decreased nodal efficiency and increased degree centrality in the visual network (VN). (P < 0.05, Bonferroni-corrected) Furthermore, in the connection analysis, PD patients showed altered functional connectivity in the basal ganglia network (BGN), VN, and DMN.(NBS corrected). Conclusion: Our results indicate that individuals with PD showed abnormal brain network efficiency and abnormal connection within DMN, VN and BGN related to pain matrix. These findings have important references for understanding the neural mechanism of pain in PD.

Specific static and dynamic functional network connectivity changes in thyroid-associated ophthalmopathy and it predictive values using machine learning.

Background: Thyroid-associated ophthalmopathy (TAO) is a prevalent autoimmune disease characterized by ocular symptoms like eyelid retraction and exophthalmos. Prior neuroimaging studies have revealed structural and functional brain abnormalities in TAO patients, along with central nervous system symptoms such as cognitive deficits. Nonetheless, the changes in the static and dynamic functional network connectivity of the brain in TAO patients are currently unknown. This study delved into the modifications in static functional network connectivity (sFNC) and dynamic functional network connectivity (dFNC) among thyroid-associated ophthalmopathy patients using independent component analysis (ICA). Methods: Thirty-two patients diagnosed with thyroid-associated ophthalmopathy and 30 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning. ICA method was utilized to extract the sFNC and dFNC changes of both groups. Results: In comparison to the HC group, the TAO group exhibited significantly increased intra-network functional connectivity (FC) in the right inferior temporal gyrus of the executive control network (ECN) and the visual network (VN), along with significantly decreased intra-network FC in the dorsal attentional network (DAN), the default mode network (DMN), and the left middle cingulum of the ECN. On the other hand, FNC analysis revealed substantially reduced connectivity intra- VN and inter- cerebellum network (CN) and high-level cognitive networks (DAN, DMN, and ECN) in the TAO group compared to the HC group. Regarding dFNC, TAO patients displayed abnormal connectivity across all five states, characterized by notably reduced intra-VN connectivity and CN connectivity with high-level cognitive networks (DAN, DMN, and ECN), alongside compensatory increased connectivity between DMN and low-level perceptual networks (VN and basal ganglia network). No significant differences were observed between the two groups for the three dynamic temporal metrics. Furthermore, excluding the classification outcomes of FC within VN (with an accuracy of 51.61% and area under the curve of 0.35208), the FC-based support vector machine (SVM) model demonstrated improved performance in distinguishing between TAO and HC, achieving accuracies ranging from 69.35 to 77.42% and areas under the curve from 0.68229 to 0.81667. The FNC-based SVM classification yielded an accuracy of 61.29% and an area under the curve of 0.57292. Conclusion: In summary, our study revealed that significant alterations in the visual network and high-level cognitive networks. These discoveries contribute to our understanding of the neural mechanisms in individuals with TAO, offering a valuable target for exploring future central nervous system changes in thyroid-associated eye diseases.

Altered dynamic large-scale brain networks and combined machine learning in primary angle-closure glaucoma.

Primary angle-closure glaucoma (PACG) is a severe and irreversible blinding eye disease characterized by progressive retinal ganglion cell death. However, prior research has predominantly focused on static brain activity changes, neglecting the exploration of how PACG impacts the dynamic characteristics of functional brain networks. This study enrolled forty-four patients diagnosed with PACG and forty-four age, gender, and education level-matched healthy controls (HCs). The study employed Independent Component Analysis (ICA) techniques to extract resting-state networks (RSNs) from resting-state functional magnetic resonance imaging (rs-fMRI) data. Subsequently, the RSNs was utilized as the basis for examining and comparing the functional connectivity variations within and between the two groups of resting-state networks. To further explore, a combination of sliding time window and k-means cluster analyses identified seven stable and repetitive dynamic functional network connectivity (dFNC) states. This approach facilitated the comparison of dynamic functional network connectivity and temporal metrics between PACG patients and HCs for each state. Subsequently, a support vector machine (SVM) model leveraging functional connectivity (FC) and FNC was applied to differentiate PACG patients from HCs. Our study underscores the presence of modified functional connectivity within large-scale brain networks and abnormalities in dynamic temporal metrics among PACG patients. By elucidating the impact of changes in large-scale brain networks on disease evolution, researchers may enhance the development of targeted therapies and interventions to preserve vision and cognitive function in PACG.

Scalable Fabrication of Black Phosphorous Films for Infrared Photodetector Arrays.

Bulk black phosphorous (bP) exhibits excellent infrared (IR) optoelectronic properties, but most reported bP IR photodetectors are fabricated from single exfoliated flakes with lateral sizes of < 100 µm. Here, scalable thin films of bP suitable for IR photodetector arrays are realized through a tailored solution-deposition method. The properties of the bP film and their protective capping layers are optimized to fabricate bP IR photoconductors exhibiting specific detectivities up to 4.0 × 108 cm Hz1/2 W-1 with fast 30/60 µs rise/fall times under λ = 2.2 µm illumination. The scalability of the bP thin film fabrication is demonstrated by fabricating a linear array of 25 bP photodetectors and obtaining 25 × 25 pixel IR images at ≈203 ppi with good spatial fidelity. This research demonstrates a commercially viable method of fabricating scalable bP thin films for optoelectronic devices including room temperature-operable IR photodetector arrays.

Aberrant Neurovascular Coupling in Diabetic Retinopathy Using Arterial Spin Labeling (ASL) and Functional Magnetic Resonance Imaging (fMRI) methods.

Background: Previous imaging studies have demonstrated that diabetic retinopathy (DR) is linked to structural and functional abnormalities in the brain. However, the extent to which DR patients exhibit abnormal neurovascular coupling remains largely unknown. Methods: Thirty-one patients with DR and 31 sex- and age-matched healthy controls underwent resting-state functional magnetic resonance imaging (rs-fMRI) to calculate functional connectivity strength (FCS) and arterial spin-labeling imaging (ASL) to calculate cerebral blood flow (CBF). The study compared CBF-FCS coupling across the entire grey matter and CBF/FCS ratios (representing blood supply per unit of connectivity strength) per voxel between the two groups. Additionally, a support vector machine (SVM) method was employed to differentiate between diabetic retinopathy (DR) patients and healthy controls (HC). Results: In DRpatients compared to healthy controls, there was a reduction in CBF-FCS coupling across the entire grey matter. Specifically, DR patients exhibited elevated CBF/FCS ratios primarily in the primary visual cortex, including the right calcarine fissure and surrounding cortex. On the other hand, reduced CBF/FCS ratios were mainly observed in premotor and supplementary motor areas, including the left middle frontal gyrus. Conclusion: An elevated CBF/FCS ratio suggests that patients with DR may have a reduced volume of gray matter in the brain. A decrease in its ratio indicates a decrease in regional CBF in patients with DR. These findings suggest that neurovascular decoupling in the visual cortex, as well as in the supplementary motor and frontal gyrus, may represent a neuropathological mechanism in diabetic retinopathy.

Zeolitic imidazole framework-derived rich-Zn-Co3O4/N-doped porous carbon with multiple enzyme-like activities for synergistic cancer therapy.

Reactive oxygen species (ROS)-centered chemodynamic therapy (CDT) holds significant potential for tumor-specific treatment. However, insufficient endogenous H2O2 and extra glutathione within tumor microenvironment (TME) severely deteriorate the CDT's effectiveness. Herein, rich-Zn-Co3O4/N-doped porous carbon (Zn-Co3O4/NC) was fabricated by two-step pyrolysis, and applied to build high-efficiency nano-platform for synergistic cancer therapy upon combination with glucose oxidase (GOx), labeled Zn-Co3O4/NC-GOx for clarity. Specifically, the multiple enzyme-like activities of the Zn-Co3O4/NC were scrutinously investigated, including peroxidase-like activity to convert H2O2 to O2∙-, catalase-like activity to decompose H2O2 into O2, and oxidase-like activity to transform O2 to O2∙-, which achieved the CDT through the catalytic cascade reaction. Simultaneously, GOx reacted with intracellular glucose to produce gluconic acid and H2O2, realizing starvation therapy. In the acidic TME, the Zn-Co3O4/NC-GOx rapidly caused intracellular Zn2+ pool overload and disrupted cellular homeostasis for ion-intervention therapy. Additionally, the Zn-Co3O4/NC exhibited glutathione peroxidase-like activity, which consumed glutathione in tumor cells and reduced the ROS consumption for ferroptosis. The tumor treatments offer some constructive insights into the nanozyme-mediated catalytic medicine, coupled by avoiding the TME limitations.

Machine Learning Analysis Classifies Patients with Primary Angle-Closure Glaucoma Using Abnormal Brain White Matter Function.

Objective: Primary angle-closure glaucoma (PACG) is a globally prevalent, irreversible eye disease leading to blindness. Previous neuroimaging studies demonstrated that PACG patients were associated with gray matter function changes. However, whether the white matter(WM) function changes in PACG patients remains unknown. The purpose of the study is to investigate WM function changes in the PACG patients. Methods: In total, 40 PACG patients and 40 well-matched HCs participated in our study and underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. We compared between-group differences between PACG patients and HC in the WM function using amplitude of low-frequency fluctuations (ALFF). In addition, the SVM method was applied to the construction of the PACG classification model. Results: Compared with the HC group, ALFF was attenuated in right posterior thalamic radiation (include optic radiation), splenium of corpus callosum, and left tapetum in the PACG group, the results are statistically significant (GRF correction, voxel-level P < 0.001, cluster-level P < 0.05). Furthermore, the SVM classification had an accuracy of 80.0% and an area under the curve (AUC) of 0.86 for distinguishing patients with PACG from HC. Conclusion: The findings of our study uncover abnormal WM functional alterations in PACG patients and mainly involves vision-related regions. These findings provide new insights into widespread brain damage in PACG from an alternative WM functional perspective.

Exploring the Roles of Single Atom in Hydrogen Peroxide Photosynthesis.

This comprehensive review provides a deep exploration of the unique roles of single atom catalysts (SACs) in photocatalytic hydrogen peroxide (H2O2) production. SACs offer multiple benefits over traditional catalysts such as improved efficiency, selectivity, and flexibility due to their distinct electronic structure and unique properties. The review discusses the critical elements in the design of SACs, including the choice of metal atom, host material, and coordination environment, and how these elements impact the catalytic activity. The role of single atoms in photocatalytic H2O2 production is also analysed, focusing on enhancing light absorption and charge generation, improving the migration and separation of charge carriers, and lowering the energy barrier of adsorption and activation of reactants. Despite these advantages, several challenges, including H2O2 decomposition, stability of SACs, unclear mechanism, and low selectivity, need to be overcome. Looking towards the future, the review suggests promising research directions such as direct utilization of H2O2, high-throughput synthesis and screening, the creation of dual active sites, and employing density functional theory for investigating the mechanisms of SACs in H2O2 photosynthesis. This review provides valuable insights into the potential of single atom catalysts for advancing the field of photocatalytic H2O2 production.

Pathways to Next-Generation Fire-Safe Alkali-Ion Batteries.

High energy and power density alkali-ion (i.e., Li+ , Na+ , and K+ ) batteries (AIBs), especially lithium-ion batteries (LIBs), are being ubiquitously used for both large- and small-scale energy storage, and powering electric vehicles and electronics. However, the increasing LIB-triggered fires due to thermal runaways have continued to cause significant injuries and casualties as well as enormous economic losses. For this reason, to date, great efforts have been made to create reliable fire-safe AIBs through advanced materials design, thermal management, and fire safety characterization. In this review, the recent progress is highlighted in the battery design for better thermal stability and electrochemical performance, and state-of-the-art fire safety evaluation methods. The key challenges are also presented associated with the existing materials design, thermal management, and fire safety evaluation of AIBs. Future research opportunities are also proposed for the creation of next-generation fire-safe batteries to ensure their reliability in practical applications.

Effect of shape deprivation on retinal thickness in myopic mice using an OCT method.

Purpose: The purpose of this study was to study in retina thickness changes in myopic mice using optical coherence tomography (OCT). Methods: There were 18 mice in the form-deprivation myopia (FDM) group，in which the left eye was not treated as a control;18 untreated mice served as a normal control group. The diopter of all mice was measured 21 days after birth (P21), before form deprivation. After 4 weeks of form deprivation (P49), the refraction, fundus, and retinal sublayer thickness of all mice were measured. Results: After 4 weeks of form deprivation, the refractive power of the right eye in the FDM group was significantly higher than that in the left eye (p < 0.05). There was no significant change in the refractive power of the left eye in the FDM group compared with the normal control group. The retina, nerve fiber layer (NFL), inner nuclear layer (INL), and outer nuclear layer (ONL) in the right eye of the FDM group were significantly thinner than those of both the FDM and control groups (p < 0.05). There was no significant change in photoreceptor (PR). Conclusion: Our study highlights that the myopic mice have decreased R thickness, which might reflect the potential pathological mechanism of myopia.

A Liquid Metal Microdroplets Initialized Hemicellulose Composite for 3D Printing Anode Host in Zn-Ion Battery.

Maintaining a steady affinity between gallium-based liquid metals (LM) and polymer binders, particularly under continuous mechanical deformation, such as extrusion-based 3D printing or plating/stripping of Zinc ion (Zn2+ ), is very challenging. Here, an LM-initialized polyacrylamide-hemicellulose/EGaIn microdroplets hydrogel is used as a multifunctional ink to 3D-print self-standing scaffolds and anode hosts for Zn-ion batteries. The LM microdroplets initiate acrylamide polymerization without additional initiators and cross-linkers, forming a double-covalent hydrogen-bonded network. The hydrogel acts as a framework for stress dissipation, enabling recovery from structural damage due to the cyclic plating/stripping of Zn2+ . The LM-microdroplet-initialized polymerization with hemicelluloses can facilitate the production of 3D printable inks for energy storage devices.

Altered functional connectivity between the default mode network in diabetic retinopathy patients.

OBJECTIVES: Previous studies have demonstrated that diabetic retinopathy is associated with cognitive impairment. This study aimed to investigate the intrinsic functional connectivity pattern within the default mode network (DMN) and its associations with cognitive impairment in diabetic retinopathy patients using resting-state functional MRI (rs-fMRI). METHODS: A total of 34 diabetic retinopathy patients and 37 healthy controls were recruited for rs-fMRI scanning. Both groups were age, gender, and education level matched. The posterior cingulate cortex (PCC) was chosen as the region of interest for detecting functional connectivity changes. RESULTS: Compared with the healthy control group, diabetic retinopathy patients showed increased functional connectivity between PCC and left medial superior frontal gyrus and increased functional connectivity between PCC and right precuneus. CONCLUSION: Our study highlights that diabetic retinopathy patients show enhanced functional connectivity within DMN, suggesting that a compensatory increase of neural activity might occur in DMN, which offers new insight into the potential neural mechanism of cognitive impairment in diabetic retinopathy patients.

Artificial intelligence method based on multi-feature fusion for automatic macular edema (ME) classification on spectral-domain optical coherence tomography (SD-OCT) images.

Purpose: A common ocular manifestation, macular edema (ME) is the primary cause of visual deterioration. In this study, an artificial intelligence method based on multi-feature fusion was introduced to enable automatic ME classification on spectral-domain optical coherence tomography (SD-OCT) images, to provide a convenient method of clinical diagnosis. Methods: First, 1,213 two-dimensional (2D) cross-sectional OCT images of ME were collected from the Jiangxi Provincial People's Hospital between 2016 and 2021. According to OCT reports of senior ophthalmologists, there were 300 images with diabetic (DME), 303 images with age-related macular degeneration (AMD), 304 images with retinal-vein occlusion (RVO), and 306 images with central serous chorioretinopathy (CSC). Then, traditional omics features of the images were extracted based on the first-order statistics, shape, size, and texture. After extraction by the alexnet, inception_v3, resnet34, and vgg13 models and selected by dimensionality reduction using principal components analysis (PCA), the deep-learning features were fused. Next, the gradient-weighted class-activation map (Grad-CAM) was used to visualize the-deep-learning process. Finally, the fusion features set, which was fused from the traditional omics features and the deep-fusion features, was used to establish the final classification models. The performance of the final models was evaluated by accuracy, confusion matrix, and the receiver operating characteristic (ROC) curve. Results: Compared with other classification models, the performance of the support vector machine (SVM) model was best, with an accuracy of 93.8%. The area under curves AUC of micro- and macro-averages were 99%, and the AUC of the AMD, DME, RVO, and CSC groups were 100, 99, 98, and 100%, respectively. Conclusion: The artificial intelligence model in this study could be used to classify DME, AME, RVO, and CSC accurately from SD-OCT images.

Altered synchronous neural activities in retinal vein occlusion patients: A resting-state fMRI study.

Objective: Retinal vein occlusion (RVO) is the second most common retinal vascular disorder after diabetic retinopathy, which is the main cause of vision loss. Retinal vein occlusion might lead to macular edema, causing severe vision loss. Previous neuroimaging studies of patients with RVO demonstrated that RVO was accompanied by cerebral changes, and was related to stroke. The purpose of the study is to investigate synchronous neural activity changes in patients with RVO. Methods: A total of 50 patients with RVO and 48 healthy subjects with matched sex, age, and education were enrolled in the study. The ReHo method was applied to investigate synchronous neural activity changes in patients with RVO. Results: Compared with HC, patients with RVO showed increased ReHo values in the bilateral cerebellum_4_5. On the contrary, patients with RVO had decreased ReHo values in the bilateral middle occipital gyrus, right cerebelum_crus1, and right inferior temporal gyrus. Conclusion: Our study demonstrated that patients with RVO were associated with abnormal synchronous neural activities in the cerebellum, middle occipital gyrus, and inferior temporal gyrus. These findings shed new insight into neural mechanisms of vision loss in patients with RVO.

Spontaneous internal carotid artery pseudoaneurysm complicated with ischemic stroke in a young man: A case report and review of literature.

BACKGROUND: Carotid artery pseudoaneurysm (PSA) is infrequently encountered in clinical settings. Internal carotid artery (ICA) PSA complicated with ischemic stroke is rare. PSAs are typically caused by iatrogenic injury, trauma, or infection. The underlying mechanisms of spontaneous PSA formation are not well characterized. We report a healthy young man who presented with stroke as a complication of spontaneous PSA of the left ICA. CASE SUMMARY: A 30-year-old man working as a ceiling decoration worker was hospitalized due to sudden-onset speech disorder and right lower extremity weakness. Medical history was unremarkable. Brain computed tomography revealed ischemic stroke. Digital subtraction angiography showed a left ICA PSA with mild stenosis. The patient was conservatively managed with oral anticoagulation and antiplatelet therapy. He recovered well and was discharged. The patient was in good condition during follow-up. CONCLUSION: The occupational history of patient should be taken into consideration while evaluating the etiology of spontaneous ICA PSA in young people with stroke.

Ultrastable Zinc Anode Enabled by CO2-Induced Interface Layer.

Aqueous Zn-ion batteries (AZIBs), being safe, inexpensive, and pollution-free, are a promising candidate for future large-scale sustainable energy storage. However, in a conventional AZIBs setup, the Zn metal anode suffers oxidative corrosion, side reactions with electrolytes, disordered dendrite growth during operation, and consequently low efficiency and short lifespan. In this work, we discover that purging CO2 gas into the electrolyte could address these issues by eliminating dissolved O2, inhibiting side reactions by buffering the local pH change, and preventing dendrite growth by inducing the in situ formation of a ZnCO3 solid electrolyte interphase layer. Moreover, the CO2-purged electrolyte could enable a highly reversible plating/stripping behavior with a high Coulombic efficiency of 99.97% and an ultralong lifespan of 32,000 cycles (1600 h) even under an ultrahigh current density of 40 mA cm-2. Consequently, the CO2-purged symmetrical cells deliver long cycling stability at a high depth of discharge of 57%, while the CO2-purged Zn/V2O5 full cells exhibit outstanding capacity retention of 66% after 1000 cycles at a high current density of 5 A g-1. Our strategy, the simple introduction of CO2 gas into the electrolyte, could effectively mediate the zinc anode's critical issues and provide a scalable and cost-effective pathway for the commercialization of AZIBs.

Disrupted interhemispheric functional connectivity in primary angle-closure glaucoma: a functional MRI study: voxel-mirrored homotopic connectivity in primary angle-closure glaucoma patients.

The purpose of the study is to use the voxel-mirrored homotopic connectivity (VMHC) technique to explore the pattern of the interhemispheric functional connectivity in patients with primary angle-closure glaucoma (PACG). The interhemispheric functional connectivity was compared between 31 individuals with PACG and 31 healthy controls closely matched with sex, age, and educational level using the VMHC technique. Significant differences in VMHC between two groups were selected to be classification features for classifying individuals with PACG from healthy controls using the support vector machine algorithm of the machine learning. We used the permutation test analysis to assess the classification performance. In addition, the Pearson analysis was applied to explore the relationship between changed VMHC and clinical varieties in patients with PACG. Compared with healthy controls, individuals with PACG exhibited significantly lower VMHC signal values in the right calcarine, right cuneus, right superior occipital gyrus, and right postcentral gyrus [voxel level: P < 0.001, Gaussian random field correction, cluster level: P < 0.05]. Moreover, the results displayed that the total accuracy, sensitivity, and specificity of the machine learning classification were 0.758, 0.710, and 0.807, respectively (P < 0.001, nonparametric permutation test). The findings demonstrated that there is disturbed interhemispheric resting-state functional connectivity in the vision-related brain areas of individuals with PACG; and the VMHC variability can classify individuals with PACG from healthy controls with high accuracy, which provided novel evidence for understanding the neuropathological mechanism of PACG.

Machine learning analysis reveals abnormal functional network hubs in the primary angle-closure glaucoma patients.

Background: Primary angle-closure glaucoma (PACG) is a serious and irreversible blinding eye disease. Growing studies demonstrated that PACG patients were accompanied by vision and vision-related brain region changes. However, whether the whole-brain functional network hub changes occur in PACG patients remains unknown. Purpose: The purpose of the study was to investigate the brain function network hub changes in PACG patients using the voxel-wise degree centrality (DC) method. Materials and methods: Thirty-one PACG patients (21 male and 10 female) and 31 healthy controls (HCs) (21 male and 10 female) closely matched in age, sex, and education were enrolled in the study. The DC method was applied to investigate the brain function network hub changes in PACG patients. Moreover, the support vector machine (SVM) method was applied to distinguish PACG patients from HC patients. Results: Compared with HC, PACG patients had significantly higher DC values in the right fusiform, left middle temporal gyrus, and left cerebelum_4_5. Meanwhile, PACG patients had significantly lower DC values in the right calcarine, right postcentral gyrus, left precuneus gyrus, and left postcentral gyrus. Furthermore, the SVM classification reaches a total accuracy of 72.58%, and the ROC curve of the SVM classifier has an AUC value of 0.85 (r = 0.25). Conclusion: Our results showed that PACG patients showed widespread brain functional network hub dysfunction relative to the visual network, auditory network, default mode network, and cerebellum network, which might shed new light on the neural mechanism of optic atrophy in PACG patients.

Altered Temporal Dynamics of the Amplitude of Low-Frequency Fluctuations in Comitant Exotropia Patients.

Purpose: Growing evidence reported that patients with comitant exotropia (CE) were accompanied by static cerebral neural activity changes. However, whether the dynamic time-varying of neural activity changes in patients with CE remains unknown. Methods: A total of 36 patients with CE (25 men and 11 women) and 36 well-matched healthy controls are enrolled in the study. The dynamic amplitude of low-frequency fluctuation (dALFF) combined with the sliding window method was used to assess the dynamic neural activity changes in patients with CE. Results: Compared with HCs, patients with CE had decreased dALFF values in the right superior parietal lobule (SPL) and right precuneus gyrus (PreCUN). Moreover, we found that the dALFF maps showed an accuracy of 48.61% and an area under the curve of.54 for distinguishing the patients with CE from HCs. Conclusion: Our study demonstrated that patients with CE showed altered dynamic neural activity changes in the right SPL and right PreCUN, which might indicate the neuropathological mechanism of stereoscopic dysfunction in patients with CE.

Cytomembrane-Inspired MXene Ink with Amphiphilic Surfactant for 3D Printed Microsupercapacitors.

Two-dimensional (2D) material-based hydrogels have been widely utilized as the ink for extrusion-based 3D printing in various electronics. However, the viscosity of the hydrogel ink is not high enough to maintain the self-supported structure without architectural deformation. It is also difficult to tune the microstructure of the printed devices using a low-viscosity hydrogel ink. Herein, by mimicking a phospholipid bilayer in a cytomembrane, the amphiphilic surfactant nonaethylene glycol monododecyl ether (C12E9) was incorporated into MXene hydrogel. The incorporation of C12E9 offers amphiphilicity to the MXene flakes and produces a 3D interlinked network of the MXene flakes. The 3D interlinked network offers a high-viscosity, homogenized flake distribution and enhanced printability to the ink. This ink facilitates the alignment of the MXene flakes during extrusion as well as the formation of the aligned micro- and sub-microsized porous structures, leading to the improved electrochemical performance of the printed microsupercapacitor. This study provides an example for the preparation of microelectronics with tunable microstructures.