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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: P0.001, Gaussian random field correction, cluster level: P0.05]. 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 (P0.001, 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.

Renewable and low-cost biomass is an ideal sustainable alternative to petroleum-based resources, but producing biomass-based carbon electrode with high performances remains a challenge. Herein, we propose a facile self-assembly strategy to fabricate a biomass-derived N, S co-doping carbon electrode from lignosulfonate without any activation or template process. Taking advantage of the coordination between Fe ions and lignosulfonate, the resultant carbon exhibits a spherical structure with abundant graphitized nanosheets, leading to a high specific surface area with rational pore structure, which are beneficial to the electron/ion transport and storage. The high contents of doping N (8.47 wt%) and S (2.56 wt%) significantly boost the electrochemical performances. As a supercapacitor electrode, the carbon material displays high specific capacitance of 390 F g−1, excellent cycling stability and high energy density of 14.7 W h kg−1 at a power density of 450 W kg−1. This study provides a potential strategy for synthesizing cost-effective heteroatom-doped carbon materials from biomass with abundant functional groups and heteroatom sources, such as chitosan, collagen, and gelatin. Graphical Abstract

PurposeThe purpose of this study was to study in retina thickness changes in myopic mice using optical coherence tomography (OCT).MethodsThere 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.ResultsAfter 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 p ConclusionOur study highlights that the myopic mice have decreased R thickness, which might reflect the potential pathological mechanism of myopia.

Shao-Gao Gui,1,2,* Ri-Bo Chen,2,* Yu-Lin Zhong,1 Xin Huang1 1Department of Ophthalmology, Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang, 330006, Jiangxi, People’s Republic of China; 2Department of Radiology, Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang, 330006, Jiangxi, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xin HuangDepartment of Ophthalmology, Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, No. 152, Ai Guo Road, Dong Hu District, Nanchang, 330006, Jiangxi, People’s Republic of ChinaTel +86 15879215294Email 334966891@qq.comBackground: 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.Keywords: primary dysmenorrhea, amplitude of low-frequency fluctuations, support vector machine

Background and aimA 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).MethodsA 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.ResultsThe 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.ConclusionThis 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.

Photosensitized heterogeneous CO2 reduction (PHCR) has emerged as a promising means to convert CO2 into valuable chemicals, however, challenged by the relatively low carbonaceous product selectivity caused by the competing hydrogen evolution reaction (HER). Here, we report a PHCR system that couples Ru(bpy)32+ photosensitizer with {001} faceted LiCoO2 nanosheets photocatalyst to simultaneously yield 21.2 and 722 µmol·g−1·h−1 of CO, and 4.42 and 108 µmol·g−1·h−1 of CH4 under the visible light and the simulated sunlight irradiations, respectively, with completely suppressed HER. The experimental and theoretical studies reveal that the favored CO2 adsorption on the exposed Li sites on {001} faceted LiCoO2 surface is responsible for the completely suppressed HER.

Sodium-ion batteries (SIBs) are emerging as an inexpensive and more sustainable alternative to lithium-ion batteries in the energy storage market. To advance their commercialization, one major scientific undertaking is to develop low-cost, reliable anode materials from abundant resources, like the success of graphite in the lithium-ion batteries. However, graphite is chemically inactive in storing sodium ions and, to render it viable in sodium-ion batteries, additional modification of graphite is required. Herein, we demonstrate a green and facile method to prepare cost-effective and stable graphitic SIB anodes. The modification process started with the electrochemical oxidation of expanded graphite to widen the interlayer and functionalize graphite layers, followed by a fast (20 min) thermal treatment at 150 °C to achieve controlled deoxygenation. The thermally processed electrochemical graphite oxide could provide a high reversible capacity of 268 mAh g−1 at 100 mA g−1 and 163 mAh g−1 at 500 mA g−1 as well as low fading in capacity (in average 0.0198% loss per cycle) over 2000 cycles. The electrochemical route eliminates the need for the harsh chemical oxidation of graphite, offering a promising approach for industrial production of low-cost anodes for sodium-ion batteries.

BackgroundPrimary 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.PurposeThe 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 methodsThirty-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.ResultsCompared 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).ConclusionOur 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.

One of the most unique properties of two-dimensional carbides and nitrides of transition metals (MXenes) is their excellent water dispersibility and yet possessing superior electrical conductivity but their industrial-scale application is limited by their costly chemical synthesis methods. In this work, the niche feature of MXene was capitalized in the packed-bed electrochemical reactor (PBER) to produce MXene at an unprecedented reaction rate and yield with minimal chemical waste. A simple NH4F solution was employed as the green electrolyte which could be used repeatedly without any loss in its efficacy. Surprisingly, both fluoride and ammonium were found to play critical roles in the electrochemical etching, functionalization, and expansion of the layered parent materials (MAXs) through which the liberation of ammonia gas was observed. The electrochemically produced MXenes (eMXenes) with excellent conductivity, applied as supercapacitor electrodes, could deliver an ultra-high volumetric capacity (1408 F cm-3) and volumetric energy density (75.8 Wh L-1). This revolutionary green, energy efficient and scalable electrochemical route will not only pave the way for industrial-scale production of MXene but also open up a myriad of versatile electrochemical modifications for improved functional MXenes.

PurposeGrowing 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.MethodsA 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.ResultsCompared 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.ConclusionOur 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.

Lithium sulfur (Li–S) battery is considered as one of the most promising energy storage devices, because of its low cost, high energy density, and environmental friendliness. However, the practical...

An inorganic-salt-assisted synthesis of non-metallic heteroatom (phosphorus and sulfur) co-doped cobaltous oxide (P/S-CoO) has been reported. Potassium sulphate (K2 SO4 ) was used as inorganic source of sulfur (S), while triphenyl phosphine (PPh3 ) was used as phosphorus (P) source. A stepwise mechanistic investigation into the doping process revealed that the decomposition of PPh3 triggered the release of both the elemental sulfur and phosphorus because of the reducing reaction environment. The transformation of cobalt-PPh3 complex into cubic cobalt (II) oxide along with the successful co-doping (P and S) was achieved by high temperature calcination at 800 °C but preserved the bulk CoO crystalline structure. The as synthesized P/S-CoO demonstrated an unprecedented enhancement on the oxygen evolution activity compare to that of pristine CoO with the current density of 10 mA/cm2 at the overpotential of 293 mV in 1.0 M KOH electrolyte and profound stability at different current densities.

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.The purpose of this study was to investigate the effect of central vision loss on spontaneous brain activity in AMD patients.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.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).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.

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.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.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.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.

Si-Jie Yi,1,* Ri-Bo Chen,2,* Yu-Lin Zhong,3 Xin Huang3 1Department of Gynecology and Obstetrics, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, 330006, People’s Republic of China; 2Department of Radiology, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, 330006, People’s Republic of China; 3Department of Ophthalmology, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, 330006, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xin Huang, Department of Ophthalmology, Jiangxi Provincial People’s Hospital, No. 152, Ai Guo Road, Dong Hu District, Nanchang, Jiangxi, 330006, People’s Republic of China, Tel +86 15879215294, Email 2017103020035@whu.edu.cnPurpose: 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.Keywords: primary dysmenorrhea, independent component analysis, resting-state networks