Glioma-Induced Disruption of Resting-State Functional Connectivity and Amplitude of Low-Frequency Fluctuations in the Salience Network

BACKGROUND AND PURPOSE:Cognitive challenges are prevalent in survivors of glioma, but their neurobiology is incompletely understood. The purpose of this study was to investigate the effect of glioma presence and tumor characteristics on resting-state functional connectivity and amplitude of low-frequency fluctuations of the salience network, a key neural network associated with cognition.MATERIALS AND METHODS:Sixty-nine patients with glioma (mean age, 48.74 [SD, 14.32] years) who underwent resting-state fMRI were compared with 31 healthy controls (mean age, 49.68 [SD, 15.54] years). We identified 4 salience network ROIs: left/right dorsal anterior cingulate cortex and left/right anterior insula. Average salience network resting-state functional connectivity and amplitude of low-frequency fluctuations within the 4 salience network ROIs were computed.RESULTS:Patients with gliomas showed decreased overall salience network resting-state functional connectivity (P = .001) and increased amplitude of low-frequency fluctuations in all salience network ROIs (P < .01) except in the left dorsal anterior cingulate cortex. Compared with controls, patients with left-sided gliomas showed increased amplitude of low-frequency fluctuations in the right dorsal anterior cingulate cortex (P = .002) and right anterior insula (P < .001), and patients with right-sided gliomas showed increased amplitude of low-frequency fluctuations in the left anterior insula (P = .002). Anterior tumors were associated with decreased salience network resting-state functional connectivity (P < .001) and increased amplitude of low-frequency fluctuations in the right anterior insula, left anterior insula, and right dorsal anterior cingulate cortex. Patients with high-grade gliomas had decreased salience network resting-state functional connectivity compared with healthy controls (P < .05). The right anterior insula showed increased amplitude of low-frequency fluctuations in patients with grade II and IV gliomas compared with controls (P < .01).CONCLUSIONS:By demonstrating decreased resting-state functional connectivity and an increased amplitude of low-frequency fluctuations related to the salience network in patients with glioma, this study adds to our understanding of the neurobiology underpinning observable cognitive deficits in these patients. In addition to more conventional functional connectivity, amplitude of low-frequency fluctuations is a promising functional-imaging biomarker of tumor-induced vascular and neural pathology.

Detrimental effects of cancer on cognitive function and, consequently, on the quality of life are emerging as a key focus of cancer survivorship both in research and clinical practice.^1,2 Brain tumors have been shown to affect memory, processing, and attention in patients; however, their underlying neurobiology is incompletely understood.³ Using resting-state functional MR imaging (rsfMRI) to evaluate changes in cognitive resting-state networks may provide a better understanding of the pathology underlying the observable cognitive disruptions in gliomas, the most common primary brain tumor in adults.A “triple network model” of neurocognitive pathology has been proposed, which encompasses the default mode network, involved in mind wandering; the central executive network, involved in decision-making; and the salience network (SN), implicated in modulating activation of the default mode network and central executive network by detecting the presence of salient stimuli.^4-8 While previous rsfMRI research has largely focused on tumor-induced changes in the default mode network,^9,10 our study examined the less-studied SN, a network rooted in the anterior insula and the dorsal anterior cingulate cortex.⁶Prior studies evaluating gliomas and SN resting-state functional connectivity (RSFC) provided conflicting results in small patient samples: Maesawa et al¹⁰ found no significant differences in the SN in 12 patients, while Liu et al¹¹ more recently found decreased SN connectivity in 13 patients. Gliomas impact the integrity of the neurovascular unit to varying degrees, resulting in neurovascular uncoupling that has been reported to confound fMRI interpretations in patients with brain tumors.^12-14 Additionally, research has reported neuronal plasticity manifested by structural reorganization and functional remodeling of neural networks in patients with gliomas with possible alterations in clinically observable cognitive manifestations.^15-17 An rsfMRI metric, the amplitude of low-frequency fluctuations (ALFF), has recently shown promise as a biomarker for brain plasticity and hemodynamic characterization, including neurovascular uncoupling in patients with gliomas.^15-19The purpose of this study was to investigate the effect of glioma presence and tumor characteristics on overall RSFC and regional normalized ALFF within the SN in a large patient population. We hypothesized that there would be decreased average SN RSFC and altered ALFF in patients with gliomas compared with healthy controls. Recent studies have acknowledged that gliomas have variable effects on network integrity based on lesion location and proximity to network ROIs,^20-22 and unilateral gliomas can be associated with plasticity in both the ipsilateral and contralateral hemispheres.^11,17 Research also supports differences in resting-state network reorganization in aggressive high-grade gliomas compared with slower-growing low-grade gliomas.^20,23 Therefore, we also hypothesized that there would be differences in average SN RSFC and regional ALFF in patients based on the anterior-versus-posterior location, hemispheric side, and grade of glioma.     

Effect of corneal stromal pocket irrigation in small-incision lenticule extraction

ObjectivesTo investigate the effect of corneal stromal pocket irrigation after small-incision lenticule extraction (SMILE) on visual acuity, intraocular pressure (IOP), corneal parameters and complications after surgery.MethodsA total of 242 eyes of 121 patients undergoing SMILE were enrolled in this prospective controlled study, and it was designed for one eye to randomly undergo SMILE with balanced salt solution irrigation of the corneal stromal pocket, while the other eye was not. The uncorrected distance visual acuity (UDVA) and slit lamp examination were recorded at 1 hour, 1 day, 1 week, and 1 month. Postoperative corneal density, corneal biomechanical, corneal endothelial cell number, and anterior OCT images were compared at 1 day, 1 week, and 1 month.ResultsCompared with the nonirrigation group, the irrigation group showed significantly higher UDVA at 1 day postoperatively (P < 0.05), but there was no significant difference during the rest of the postoperative period (1 hour, 1 week, and 1 month). In addition, no significant differences were found in IOP, corneal density, corneal biomechanics, corneal endothelial cells, and corneal morphology. No visual decline or severe postoperative complications were found in the patients in this study.ConclusionsInterlamellar irrigation did not affect IOP, corneal parameters, morphology, complications, or UDVA at 1 hour, 1 week, and 1 month after the operation, but it may promote UDVA 1 day after the operation.Subject terms: Refractive errors, Outcomes research, Surgery     

Role of macrophages in peripheral nerve injury and repair

Resident and inflammatory macrophages are essential effectors of the innate immune system. These cells provide innate immune defenses and regulate tissue and organ homeostasis. In addition to their roles in diseases such as cancer, obesity and osteoarthritis, they play vital roles in tissue repair and disease rehabilitation. Macrophages and other inflammatory cells are recruited to tissue injury sites where they promote changes in the microenvironment. Among the inflammatory cell types, only macrophages have both pro-inflammatory(M1) and anti-inflammatory(M2) actions, and M2 macrophages have four subtypes. The co-action of M1 and M2 subtypes can create a favorable microenvironment, releasing cytokines for damaged tissue repair. In this review, we discuss the activation of macrophages and their roles in severe peripheral nerve injury. We also describe the therapeutic potential of macrophages in nerve tissue engineering treatment and highlight approaches for enhancing M2 cell-mediated nerve repair and regeneration.     

A novel DDC gene deletion mutation in two Chinese mainland siblings with aromatic l-amino acid decarboxylase deficiency

Background

Aromatic l-amino acid decarboxylase (AADC) deficiency (OMIM #608643) is a rare and severe disorder of biogenic amine synthesis caused by mutations in the DDC gene. The phenomenology of the movement disorder includes intermittent oculogyric crises and limb dystonia, generalized athetosis, and impaired voluntary movement.

肛肠疾病手术前后肛管直肠压力测定的应用

目的:探讨肛肠疾病手术前后肛管直肠压力测定的应用。方法:将2018年5月-2019年5月在上海市松江区方塔中医医院及上海中医药大学附属曙光医院肛肠科行手术治疗的826例肛肠疾病患者作为研究对象,其中,选择性痔上黏膜吻合术246例、单纯外剥内扎术115例、外剥内扎结合内痔套扎术(Automatic Ligation of Hemorrhoids,RPH)153例、低位肛瘘切除术177例、高位肛瘘切开挂线术135例,分别于术前及术后1个月测定肛管直肠压力。结果:选择性痔上黏膜吻合术后直肠静息压、肛管静息压明显低于术前,肛管舒张压高于术前(P<0.05),但肛管最大收缩压与术前相比无明显差异(P>0.05);单纯外剥内扎术术后直肠静息压、肛管静息压明显低于术前,肛管舒张压、肛管最大收缩压明显高于术前(P<0.05);外剥内扎结合内痔套扎术术后直肠静息压、肛管静息压明显低于术前,肛管舒张压、肛管最大收缩压明显高于术前(P<0.05);低位肛瘘切除术术后直肠静息压、肛管静息压、肛管舒张压均高于术前(P<0.05),而肛管最大收缩压与术前相比无明显差异(P>0.05);高位肛瘘切开挂线术术后直肠静息压高于术前,肛管静息压、肛管舒张压低于术前(P<0.05),而与肛管最大收缩压术前相比无明显差异(P>0.05)。结论:肛肠疾病手术前后肛管直肠压力测定的应用效果显著,能准确判断手术效果及患者恢复情况,为医师的进一步诊治奠定了良好基础。     

Decoding attention control and selection in visual spatial attention

Event‐related potentials (ERPs) are used extensively to investigate the neural mechanisms of attention control and selection. The univariate ERP approach, however, has left important questions inadequately answered. We addressed two questions by applying multivariate pattern classification to multichannel ERPs in two cued visual spatial attention experiments (N = 56): (a) impact of cueing strategies (instructional vs. probabilistic) on attention control and selection and (b) neural and behavioral effects of individual differences. Following cue onset, the decoding accuracy (cue left vs. cue right) began to rise above chance level earlier and remained higher in instructional cueing (~80 ms) than in probabilistic cueing (~160 ms), suggesting that unilateral attention focus leads to earlier and more distinct formation of the attention control set. A similar temporal sequence was also found for target‐related processing (cued target vs. uncued target), suggesting earlier and stronger attention selection under instructional cueing. Across the two experiments: (a) individuals with higher cue‐related decoding accuracy showed higher magnitude of attentional modulation of target‐evoked N1 amplitude, suggesting that better formation of anticipatory attentional state leads to stronger modulation of target processing, and (b) individuals with higher target‐related decoding accuracy showed faster reaction times (or larger cueing effects), suggesting that stronger selection of task‐relevant information leads to better behavioral performance. Taken together, multichannel ERPs combined with machine learning decoding yields new insights into attention control and selection that complement the univariate ERP approach, and along with the univariate ERP approach, provides a more comprehensive methodology to the study of visual spatial attention.     

Graph Convolutional Network Based on Manifold Similarity Learning

In the area of large-scale graph data representation and semi-supervised learning, deep graph-based convolutional neural networks have been widely applied. However, typical graph convolutional network (GCN) aggregates information of neighbor nodes based on binary neighborhood similarity (adjacency matrix). It treats all neighbor nodes of one node equally, which does not suppress the influence of dissimilar neighbor nodes. In this paper, we investigate GCN based on similarity matrix instead of adjacency matrix of graph nodes. Gaussian heat kernel similarity in Euclidean space is first adopted, which is named EGCN. Then biologically inspired manifold similarity is trained in reproducing kernel Hilbert space (RKHS), based on which a manifold GCN (named MGCN) is proposed for graph data representation and semi-supervised learning with four different kernel types. The proposed method is evaluated with extensive experiments on four benchmark document citation network datasets. The objective function of manifold similarity learning converges very quickly on different datasets using various kernel functions. Compared with state-of-the-art methods, our method is very competitive in terms of graph node recognition accuracy. In particular, the recognition rates of MGCN (Gaussian kernel) and MGCN (Polynomial Kernel) outperform that of typical GCN about 3.8% on Cora dataset, 3.5% on Citeseer dataset, 1.3% on Pubmed dataset and 4% on Cora_ML dataset, respectively. Although the proposed MGCN is relatively simple and easy to implement, it can discover local manifold structure by manifold similarity learning and suppress the influence of dissimilar neighbor nodes, which shows the effectiveness of the proposed MGCN.