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.

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.

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.

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.

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.

The Effect of Long-Term Menstrual Pain on Large-Scale Brain Network in Primary Dysmenorrhea Patients.

Purpose: Primary dysmenorrhea (PD) is a common gynecological disease, characterized by crampy and suprapubic pain occurring with menses. Growing evidences demonstrated that PD patients were associated with abnormalities in brain function and structure. However, little is known regarding whether the large-scale brain network changes in PD patients. The purpose of this study was to investigate the effect of long-term menstrual pain on large-scale brain network in PD patients using independent component analysis (ICA) method. Methods: Twenty-eight PD patients (female, mean age, 24.25±1.00 years) and twenty-eight healthy controls (HCs) (mean age, 24.46±1.31 years), closely matched for age, sex, and education, underwent resting-state magnetic resonance imaging scans. ICA was applied to extract the resting-state networks (RSNs) in two groups. Then, two-sample t-tests were conducted to investigate different intranetwork FCs within RSNs and interactions among RSNs between two groups. Results: Compared to the HC group, PD patients showed significant increased intra-network FCs within the auditory network (AN), sensorimotor network (SMN), right executive control network (RECN). However, PD patients showed significant decreased intra-network FCs within ventral default mode network (vDMN) and salience network (SN). Moreover, FNC analysis showed increased VN-AN and decreased VN-SMN functional connectivity between two groups. Conclusion: Our study highlighted that PD patients had abnormal brain networks related to auditory, sensorimotor and higher cognitive network. Our results offer important insights into the altered large-scale brain network neural mechanisms of pain in PD patients.

Decreased spontaneous brain activity in the dorsal visual pathway in age-related macular degeneration patients revealed by fractional amplitude of low-frequency fluctuation.

BACKGROUND: Age-related macular degeneration (AMD) is the leading cause of visual loss in the developed world and damages the central retina. Growing evidences demonstrated that AMD patients were associated with brain structure changes in visual pathway. However, it remains unknown whether alterations of spontaneous brain activity changes occur in AMD patients. PURPOSE: The purpose of this study was to investigate the effect of central vision loss on spontaneous brain activity in AMD patients. MATERIAL AND METHODS: Seventeen AMD patients and 17 healthy controls (HCs) underwent resting-state MRI scans. The fractional amplitude of low-frequency fluctuations (fALFFs) was applied to investigate the spontaneous brain activity changes in AMD patients. RESULTS: Compared with HC group, AMD patients showed significant decreased fALFF values in the right calcarine/cuneus (brodmann area 17,8) and right superior parietal lobule (brodmann area 7). CONCLUSION: Our results showed that AMD patients had decreased brain activities in the dorsal visual pathway, which offer important insights into the neural mechanisms of central visual field defect in AMD patients.

The predictive value of local to remote functional connectivity changes in comitant exotropia patients.

BACKGROUND: Comitant exotropia (CE) is a common eye disease with abnormal eye movement, whereas altered synchronous neural activity in CE patients is poorly understood. The purpose of our study was to investigate local to remote functional connectivity of blood oxygen level-dependent (BOLD) signals changes in CE patients. MATERIAL AND METHODS: Thirty-four patients and thirty-four healthy controls (HCs) underwent resting-state MRI scans. The ReHo and FC method was applied to investigate the local to remote functional connectivity changes in CE patients. RESULTS: Compared to the HC group, CE patients showed significant increased ReHo values in the left cerebellar_crus2 and left middle frontal gyrus. Meanwhile, CE patients showed significant decreased ReHo values in the right middle temporal gyrus, left postcentral gyrus and right angular. Moreover, CE patients showed an increased FC between the cerebellar network, sensorimotor network (SMN) and default-mode network (DMN). The support vector machine (SVM) classification was up to a total accuracy of 94.12%. The AUC of the classification model was 0.99 on the basis of ReHo map. CONCLUSION: Our result highlights that CE patients had abnormal local to remote functional connectivity in the cerebellar network, SMN, DMN, which might indicate the neural mechanism of eye movements and stereo vision dysfunction in CE patients. Moreover, the SVM algorithm reveals ReHo maps as a potential biomarker for predicting clinical outcomes in CE patients.

Effect of Impaired Stereoscopic Vision on Large-Scale Resting-State Functional Network Connectivity in Comitant Exotropia Patients.

Background: Comitant exotropia (CE) is a common eye movement disorder, characterized by impaired eye movements and stereoscopic vision. CE patients reportedly exhibit changes in the central nervous system. However, it remains unclear whether large-scale brain network changes occur in CE patients. Purpose: This study investigated the effects of exotropia and stereoscopic vision dysfunction on large-scale brain networks in CE patients via independent component analysis (ICA). Methods: Twenty-eight CE patients (mean age, 15.80 ± 2.46 years) and 27 healthy controls (HCs; mean age, 16.00 ± 2.68 years; closely matched for age, sex, and education) underwent resting-state magnetic resonance imaging. ICA was applied to extract resting-state networks (RSNs) in both groups. Two-sample's t-tests were conducted to investigate intranetwork functional connectivity (FC) within RSNs and interactions among RSNs between the two groups. Results: Compared with the HC group, the CE group showed increased intranetwork FC in the bilateral postcentral gyrus of the sensorimotor network (SMN). The CE group also showed decreased intranetwork FC in the right cerebellum_8 of the cerebellum network (CER), the right superior temporal gyrus of the auditory network (AN), and the right middle occipital gyrus of the visual network (VN). Moreover, functional network connectivity (FNC) analysis showed that CER-AN, SMN-VN, SN-DMN, and DMN-VN connections were significantly altered between the two groups. Conclusion: Comitant exotropia patients had abnormal brain networks related to the CER, SMN, AN, and VN. Our results offer important insights into the neural mechanisms of eye movements and stereoscopic vision dysfunction in CE patients.

Echocardiographic study of myocardial work in patients with type 2 diabetes mellitus.

BACKGROUND: A noninvasive left ventricular (LV) pressure-strain loop (PSL) provides a new method to quantify myocardial work (MW) by combining global longitudinal strain (GLS) and LV pressure, which exerts potential advantages over traditional GLS. We studied the LV PSL and MW in patients with type 2 diabetes mellitus (T2DM). METHODS: This cross-sectional study included 201 subjects (54 healthy controls and 147 T2DM patients) who underwent complete two-dimensional echocardiography (2DE), including 2D speckle-tracking echocardiography (STE), as well as brachial artery pulse pressure measurement. The PSL was used to determine the global myocardial work index (GWI), global constructive work (GCW), global wasted work (GWW), and global work efficiency (GWE) of all study participants. The association between T2DM and LV function was evaluated according to these MW indices. RESULTS: The GLS was significantly lower in the T2DM group than in the control group (P < 0.001), indicating that the LV myocardium had been damaged, although the LV ejection fraction (LVEF) was still normal. The GWI and GWE were decreased (P = 0.022) and the GWW was increased (P < 0.001) in diabetic patients compared with controls, but the GCW was comparable in the two groups (P = 0.160). In all diabetic patients, age, body mass index, systolic blood pressure, smoking history, and LVEF were correlated with GWI, GWW and GWE. CONCLUSIONS: The use of LV PSL is a novel noninvasive technique that could help to depict the relationship between LV myocardial damage and MW in patients with T2DM.

Application of artificial intelligence models for detecting the pterygium that requires surgical treatment based on anterior segment images.

Background and aim: A pterygium is a common ocular surface disease, which not only affects facial appearance but can also grow into the tissue layer, causing astigmatism and vision loss. In this study, an artificial intelligence model was developed for detecting the pterygium that requires surgical treatment. The model was designed using ensemble deep learning (DL). Methods: A total of 172 anterior segment images of pterygia were obtained from the Jiangxi Provincial People's Hospital (China) between 2017 and 2022. They were divided by a senior ophthalmologist into the non-surgery group and the surgery group. An artificial intelligence model was then developed based on ensemble DL, which was integrated with four benchmark models: the Resnet18, Alexnet, Googlenet, and Vgg11 model, for detecting the pterygium that requires surgical treatment, and Grad-CAM was used to visualize the DL process. Finally, the performance of the ensemble DL model was compared with the classical Resnet18 model, Alexnet model, Googlenet model, and Vgg11 model. Results: The accuracy and area under the curve (AUC) of the ensemble DL model was higher than all of the other models. In the training set, the accuracy and AUC of the ensemble model was 94.20% and 0.978, respectively. In the testing set, the accuracy and AUC of the ensemble model was 94.12% and 0.980, respectively. Conclusion: This study indicates that this ensemble DL model, coupled with the anterior segment images in our study, might be an automated and cost-saving alternative for detection of the pterygia that require surgery.

Machine Learning Analysis Reveals Abnormal Static and Dynamic Low-Frequency Oscillations Indicative of Long-Term Menstrual Pain in Primary Dysmenorrhea Patients.

BACKGROUND: Previous neuroimaging studies demonstrated that patients with primary dysmenorrhea (PD) exhibited dysfunctional resting-state brain activity. However, alterations of dynamic brain activity in PD patients have not been fully characterized. PURPOSE: Our study aimed to assess the effect of long-term menstrual pain on changes in static and dynamic neural activity in PD patients. MATERIAL AND METHODS: Twenty-eight PD patients and 28 healthy controls (HCs) underwent resting-state magnetic resonance imaging scans. The amplitude of low-frequency fluctuations (ALFF) and dynamic ALFF was used as classification features in a machine learning approach involving a support vector machine (SVM) classifier. RESULTS: Compared with the HC group, PD patients showed significantly increased ALFF values in the right cerebellum_crus2, right rectus, left supplementary motor area, right superior frontal gyrus, right supplementary motor area, and left superior frontal medial gyrus. Additionally, PD patients showed significantly decreased ALFF values in the right middle temporal gyrus and left thalamus. PD patients also showed significantly increased dALFF values in the right fusiform, Vermis_10, right middle temporal gyrus, right putamen, right insula, left thalamus, right precentral gyrus, and right postcentral gyrus. Based on ALFF and dALFF values, the SVM classifier achieved respective overall accuracies of 96.36% and 85.45% and respective areas under the curve of 1.0 and 0.95. CONCLUSION: PD patients demonstrated abnormal static and dynamic brain activities that involved the default mode network, sensorimotor network, and pain-related subcortical nuclei. Moreover, ALFF and dALFF may offer sensitive biomarkers for distinguishing patients with PD from HCs.

Abnormal Low-Frequency Oscillations Reflect Abnormal Eye Movement and Stereovision in Patients With Comitant Exotropia.

Background: Patients with comitant exotropia (CE) are accompanied by abnormal eye movements and stereovision. However, the neurophysiological mechanism of impaired eye movements and stereovision in patient with CE is still unclear. Purpose: The purpose of this study is to investigate spontaneous neural activity changes in patients with CE using the amplitude of low-frequency fluctuation (ALFF) method and the machine learning method. Materials and Methods: A total of 21 patients with CE and 21 healthy controls (HCs) underwent resting-state magnetic resonance imaging scans. The ALFF and fractional amplitude of low-frequency fluctuation (fALFF) values were chosen as classification features using a machine learning method. Results: Compared with the HC group, patients with CE had significantly decreased ALFF values in the right angular (ANG)/middle occipital gyrus (MOG)/middle temporal gyrus (MTG) and bilateral supplementary motor area (SMA)/precentral gyrus (PreCG). Meanwhile, patients with CE showed significantly increased fALFF values in the left putamen (PUT) and decreased fALFF values in the right ANG/MOG. Moreover, patients with CE showed a decreased functional connectivity (FC) between the right ANG/MOG/MTG and the bilateral calcarine (CAL)/lingual (LING) and increased FC between the left PUT and the bilateral cerebellum 8/9 (CER 8/9). The support vector machine (SVM) classification reaches a total accuracy of 93 and 90% and the area under the curve (AUC) of 0.93 and 0.90 based on ALFF and fALFF values, respectively. Conclusion: Our result highlights that patients with CE had abnormal brain neural activities including MOG and supplementary motor area/PreCG, which might reflect the neural mechanism of eye movements and stereovision dysfunction in patients with CE. Moreover, ALFF and fALFF could be sensitive biomarkers for distinguishing patients with CE from HCs.

Altered brain network centrality in patients with late monocular blindness: a resting-state fMRI study.

INTRODUCTION: The aim of the study was to investigate the underlying functional network brain activity changes in patients with late monocular blindness (MB) and the relationship with their clinical features using the voxel-wise degree centrality (DC) method. MATERIAL AND METHODS: A total of 32 patients with MB (25 males and 7 females), and 32 healthy controls (HCs) (25 males and 7 females) closely matched in age, sex, and education, underwent resting-state functional magnetic resonance imaging scans. The DC method was used to assess local features of spontaneous brain activity. Correlation analysis was performed to explore the relationships between the observed mean DC signal values of the different areas and clinical features in these patients. RESULTS: Compared with HCs, MB patients had significantly lower DC values in the bilateral cuneus/V1/V2, and significantly higher DC values in the left inferior temporal gyrus and bilateral medial frontal gyrus. However, there was no relationship between the observed mean DC values of the different brain areas and the behavioral performance. CONCLUSIONS: Late monocular blindness involves brain function network dysfunction in many regions, which might indicate impairment of the visual cortex and other vision-related brain regions in the MBs.

Encapsulation of Plasmid DNA by Nanoscale Metal-Organic Frameworks for Efficient Gene Transportation and Expression.

The intracellular delivery and functionalization of genetic molecules play critical roles in gene-based theranostics. In particular, the delivery of plasmid DNA (pDNA) with safe nonviral vectors for efficient intracellular gene expression has received increasing attention; however, it still has some limitations. A facile one-pot method is employed to encapsulate pDNA into zeolitic imidazole framework-8 (ZIF-8) and ZIF-8-polymer vectors via biomimetic mineralization and coprecipitation. The pDNA molecules are found to be well distributed inside both nanostructures and benefit from their protection against enzymatic degradation. Moreover, through the use of a polyethyleneimine (PEI) 25 kD capping agent, the nanostructures exhibit enhanced loading capacity, better pH responsive release, and stronger binding affinity to pDNA. From in vitro experiments, the cellular uptake and endosomal escape of the protected pDNA are greatly improved with the superior ZIF-8-PEI 25 kD vector, leading to successful gene expression with high transfection efficacy, comparable to expensive commercial agents. New cost-effective avenues to develop metal-organic-framework-based nonviral vectors for efficient gene delivery and expression are provided.

Abnormal resting-state functional network centrality in patients with high myopia: evidence from a voxel-wise degree centrality analysis.

AIM: To investigate the functional networks underlying the brain-activity changes of patients with high myopia using the voxel-wise degree centrality (DC) method. METHODS: In total, 38 patients with high myopia (HM) (17 males and 21 females), whose binocular refractive diopter were -6.00 to -7.00 D, and 38 healthy controls (17 males and 21 females), closely matched in age, sex, and education levels, participated in the study. Spontaneous brain activities were evaluated using the voxel-wise DC method. The receiver operating characteristic curve was measured to distinguish patients with HM from healthy controls. Correlation analysis was used to explore the relationship between the observed mean DC values of the different brain areas and the behavioral performance. RESULTS: Compared with healthy controls, HM patients had significantly decreased DC values in the right inferior frontal gyrus/insula, right middle frontal gyrus, and right supramarginal/inferior parietal lobule (P<0.05). In contrast, HM patients had significantly increased DC values in the right cerebellum posterior lobe, left precentral gyrus/postcentral gyrus, and right middle cingulate gyrus (P<0.05). However, no relationship was found between the observed mean DC values of the different brain areas and the behavioral performance (P>0.05). CONCLUSION: HM is associated with abnormalities in many brain regions, which may indicate the neural mechanisms of HM. The altered DC values may be used as a useful biomarker for the brain activity changes in HM patients.

Ultrathin Nitrogen-Doped Holey Carbon@Graphene Bifunctional Electrocatalyst for Oxygen Reduction and Evolution Reactions in Alkaline and Acidic Media.

Efficient nonprecious-metal oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) electrocatalysts are key for the commercial viability of fuel cells, metal-air batteries, and water-splitting systems. Thus, high-performance ORR and OER electrocatalysts in acidic electrolytes are needed to support high-efficiency proton exchange membrane (PEM)-based systems. Herein, we report a new approach to design and prepare an ultrathin N-doped holey carbon layer (HCL) on a graphene sheet that exhibits outstanding bifunctional ORR/OER activities in both alkaline and acidic media. The edge sites of HCL are utilized to achieve selective doping of highly active pyridinic-N. The sandwiched graphene sheet provides mechanical support, stabilizes HCL structure and promotes charge transfer. The synergetic effect of the catalyst structure overcomes the drawbacks of holey graphene approaches. The resulting ORR and OER performances are equal to or better than the top-ranked electrocatalysts.