中国县级及以上医疗机构青光眼诊疗服务 现状分析

目的：统计分析中国县级及以上医疗机构青光眼亚专科建设、诊疗设备配备和服务提供情况，为进 一步推动我国青光眼防治工作提供理论依据。方法：调查研究。2015年对全国提供眼科服务的县级 及以上医疗机构通过网上填报的方式进行普查，采用描述性统计方法，对我国县级及以上医疗机构 青光眼亚专科建设、诊疗设备配备和服务提供情况进行系统整理和统计分析。结果：本次调查覆盖 全国6 341家县级及以上医疗机构，其中设立青光眼亚专科的医疗机构有672家（10.60%）。在青光眼 检查和治疗相关设备中，视力表配置率最高（99.30%），平均每家医疗机构配置3.28台；超声生物显 微镜配置率最低（11.50%），平均每家医疗机构配置0.13台。眼压测量、白内障手术和小梁切开术是 青光眼主要的诊疗服务类型。结论：我国县级及以上医疗机构青光眼亚专科建设亟待加强，诊疗设 备配备不全，诊疗服务能力需要全面提升。     

A Multi-Scale DNN Algorithm for Nonlinear Elliptic Equations with Multiple Scales

Algorithms based on deep neural networks (DNNs) have attracted increasing attention from the scientific computing community. DNN based algorithms are easy to implement, natural for nonlinear problems, and have shown great potential to overcome the curse of dimensionality. In this work, we utilize the multi-scale DNN-based algorithm (MscaleDNN) proposed by Liu, Cai and Xu (2020) to solve multi-scale elliptic problems with possible nonlinearity, for example, the p-Laplacian problem. We improve the MscaleDNN algorithm by a smooth and localized activation function. Several numerical examples of multi-scale elliptic problems with separable or non-separable scales in low-dimensional and high-dimensional Euclidean spaces are used to demonstrate the effectiveness and accuracy of the MscaleDNN numerical scheme.     

嘉兴市新居民儿童心理发育行为问题及影响因素分析

目的调查嘉兴市新居民儿童心理发育行为问题及影响因素，为改善新居民儿童心理健康提供理论依据。方法随机抽取新居民儿童548例，本地儿童1248例，采用自编量表评估儿童家庭影响因素，长处与困难问卷评估儿童心理发育行为问题，心理痛苦温度计评估主观心理痛苦程度，儿童心理虐待与忽视量表评估家庭教养方式，社会支持量表评估社会支持程度。结果新居民儿童主观评定心理痛苦程度高于本地儿童（P=0.002）。新居民儿童亲社会化行为低于本地儿童（P=0.000），多动/注意缺陷问题高于本地儿童（P=0.011）。儿童忽视虐待量表本地儿童5个因子得分低于新居民儿童：责骂因子（P=0.000）、恐吓因子（P=0.000）、情感忽视因子（P=0.000）、教育忽视因子（P=0.000）、身体忽视因子（P=0.000）。社会支持量表本地儿童3个因子得分均高于新居民儿童：客观支持（P=0.032）、主观支持（P=0.000）、对支持的利用度（P=0.000）。新居民儿童在新居民儿童学校、混合学校、本地儿童学校的3类学校中亲社会化行为、忽视因子、虐待因子、社会支持均有统计学差异（均P＜0.05）。结论新居民儿童较本地儿童心理发育行为明显落后，良好的家庭教养方式和有效的社会支持系统能够更快更好地促进其身心发育。     

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.