Women in visual neural regeneration research

The year 2024 marks the 60^(th)anniversary of Title IX and 25 years since the New York Times revealed bias against female faculty members at the Massachusetts Institute of Technology.We take an opportunity here to examine the state of gender bias in a relatively new yet already prominent field,neural regeneration in the visual system,for which there is a well-defined context useful for this purpose.The National Eye Institute(NEI)provided the first round of research funding for its Audacious Goals Initiative(AGI)on visual neural regeneration in 2013 and the last round in 2021.Therefore,we focus on this timespan.Data sources included PubMed,the National Science Foundation(NSF),the NEI,the Blue Ridge Institute for Medical Research and data from the major professional organization for eye and vision research,the Association for Research in Vision and Ophthalmology(ARVO).

C反应蛋白/白蛋白比值对2型糖尿病合并急性心肌梗死患者远期不良心脑血管事件的预测价值研究

背景急性心肌梗死(AMI)是威胁全球公众健康的主要原因之一。虽然已有相应的再灌注治疗策略,但AMI相关的主要不良心脑血管事件(MACCEs)仍然是全世界人口死亡的原因之一。尤其合并糖尿病的AMI患者,因冠状动脉病变复杂,病变程度严重,尽早发现和判断该部分患者远期预后相对困难,因此寻找相对简便、易获得的实验室指标,有利于为2型糖尿病(T2DM)合并AMI患者经皮冠状动脉介入(PCI)术后MACCEs的预测提供依据。目的探讨血清C反应蛋白(CRP)/白蛋白(Alb)比值(CAR)对T2DM合并AMI患者PCI术后远期MACCEs的预测价值。方法纳入2014—2019年就诊于宁夏医科大学总医院心血管内科1683例T2DM合并AMI患者为研究对象,收集患者的一般临床资料与检查结果。对所有患者进行电话或门诊随访,以全因死亡、非致死性心肌梗死、再发不稳定型心绞痛、非致死性脑卒中、新发心力衰竭或心力衰竭加重再入院、再次血运重建作为MACCEs。根据患者随访期间是否发生MACCEs分为MACCEs组(508例)和非MACCEs组(1175例)。采用单因素及多因素Logistic回归分析探讨T2DM合并AMI患者MACCEs事件的影响因素。采用Kaplan-Meier法绘制患者的生存曲线,生存曲线的比较采用Log-rank检验。采用受试者工作特征(ROC)曲线分析CAR对T2DM合并AMI患者远期发生MACCEs的预测效能,使用净重分类改善指标(NRI)和综合判别指数(IDI)评价CAR对T2DM合并AMI患者预后评估的改善效果。结果1683例患者中508例(30.18%)患者发生MACCEs。多因素Logistic回归分析显示高血压病[OR(95%CI)=1.994(1.142~3.483)]、冠状动脉植入支架长度[OR(95%CI)=1.031(1.002~1.062)]、CRP[OR(95%CI)=0.950(0.915~0.986)]、Alb[OR(95%CI)=0.933(0.880~0.989)]及CAR[OR(95%CI)=5.582(1.705~18.277)]是T2DM合并AMI患者PCI术后发生MACCEs的影响因素(P<0.05)。根据CAR中位表达水平(0.86),将患者分为CAR<0.86组和CAR≥0.86组,Log-rank检验结果显示,CAR≥0.86组MACCEs发生率高于CAR<0.86组(52.68%与22.92%;χ^(2)=65.65,P<0.001)。ROC曲线显示CAR预测T2DM合并AMI患者发生MACCEs的ROC曲线下面积为0.728(95%CI=0.702~0.754),最佳截断值为0.576,灵敏度为0.617,特异度为0.747。在基线模型基础上,与CRP、Alb相比,CAR能明显改善对患者发生MACCEs的预测效果(NRI=0.377,IDI=0.166,C指数=0.690;P<0.05)。结论CAR是T2DM合并AMI患者PCI术后远期MACCEs发生风险的有效预测指标。

Visual Semantic Segmentation Based on Few/Zero-Shot Learning:An Overview

Visual semantic segmentation aims at separating a visual sample into diverse blocks with specific semantic attributes and identifying the category for each block,and it plays a crucial role in environmental perception.Conventional learning-based visual semantic segmentation approaches count heavily on largescale training data with dense annotations and consistently fail to estimate accurate semantic labels for unseen categories.This obstruction spurs a craze for studying visual semantic segmentation with the assistance of few/zero-shot learning.The emergence and rapid progress of few/zero-shot visual semantic segmentation make it possible to learn unseen categories from a few labeled or even zero-labeled samples,which advances the extension to practical applications.Therefore,this paper focuses on the recently published few/zero-shot visual semantic segmentation methods varying from 2D to 3D space and explores the commonalities and discrepancies of technical settlements under different segmentation circumstances.Specifically,the preliminaries on few/zeroshot visual semantic segmentation,including the problem definitions,typical datasets,and technical remedies,are briefly reviewed and discussed.Moreover,three typical instantiations are involved to uncover the interactions of few/zero-shot learning with visual semantic segmentation,including image semantic segmentation,video object segmentation,and 3D segmentation.Finally,the future challenges of few/zero-shot visual semantic segmentation are discussed.

Heterogeneous Image Knowledge Driven Visual Perception

Dear Editor,This letter is concerned with visual perception closely related to heterogeneous images.Facing the huge challenge brought by different image modalities,we propose a visual perception framework based on heterogeneous image knowledge,i.e.,the domain knowledge associated with specific vision tasks,to better address the corresponding visual perception problems.

Prevalence of visual impairment and estimation of refractive errors among school children in Kakamega,Kenya

AIM:To investigate the prevalence of visual impairment(VI)and provide an estimation of uncorrected refractive errors in school-aged children,conducted by optometry students as a community service.METHODS:The study was cross-sectional.Totally 3343 participants were included in the study.The initial examination involved assessing the uncorrected distance visual acuity(UDVA)and visual acuity(VA)while using a+2.00 D lens.The inclusion criteria for a subsequent comprehensive cycloplegic eye examination,performed by an optometrist,were as follows:a UDVA<0.6 decimal(0.20 logMAR)and/or a VA with+2.00 D≥0.8 decimal(0.96 logMAR).RESULTS:The sample had a mean age of 10.92±2.13y(range 4 to 17y),and 51.3%of the children were female(n=1715).The majority of the children(89.7%)fell within the age range of 8 to 14y.Among the ethnic groups,the highest representation was from the Luhya group(60.6%)followed by Luo(20.4%).Mean logMAR UDVA choosing the best eye for each student was 0.29±0.17(range 1.70 to 0.22).Out of the total,246 participants(7.4%)had a full eye examination.The estimated prevalence of myopia(defined as spherical equivalent≤-0.5 D)was found to be 1.45%of the total sample.While around 0.18%of the total sample had hyperopia value exceeding+1.75 D.Refractive astigmatism(cil<-0.75 D)was found in 0.21%(7/3343)of the children.The VI prevalence was 1.26%of the total sample.Among our cases of VI,76.2%could be attributed to uncorrected refractive error.Amblyopia was detected in 0.66%(22/3343)of the screened children.There was no statistically significant correlation observed between age or gender and refractive values.CONCLUSION:The primary cause of VI is determined to be uncorrected refractive errors,with myopia being the most prevalent refractive error observed.These findings underscore the significance of early identification and correction of refractive errors in school-aged children as a means to alleviate the impact of VI.

Morphological disruption and visual tuning alterations in the primary visual cortex in glaucoma(DBA/2J)mice

Glaucoma is a leading cause of irreve rsible blindness wo rldwide,and previous studies have shown that,in addition to affecting the eyes,it also causes abnormalities in the brain.However,it is not yet clear how the primary visual cortex(V1)is altered in glaucoma.This study used DBA/2J mice as a model for spontaneous secondary glaucoma.The aim of the study was to compare the electrophysiological and histomorphological chara cteristics of neurons in the V1between 9-month-old DBA/2J mice and age-matched C57BL/6J mice.We conducted single-unit recordings in the V1 of light-anesthetized mice to measure the visually induced responses,including single-unit spiking and gamma band oscillations.The morphology of layerⅡ/Ⅲneurons was determined by neuronal nuclear antigen staining and Nissl staining of brain tissue sections.Eighty-seven neurons from eight DBA/2J mice and eighty-one neurons from eight C57BL/6J mice were examined.Compared with the C57BL/6J group,V1 neurons in the DBA/2J group exhibited weaker visual tuning and impaired spatial summation.Moreove r,fewer neuro ns were observed in the V1 of DBA/2J mice compared with C57BL/6J mice.These findings suggest that DBA/2J mice have fewer neurons in the VI compared with C57BL/6J mice,and that these neurons have impaired visual tuning.Our findings provide a better understanding of the pathological changes that occur in V1 neuron function and morphology in the DBA/2J mouse model.This study might offer some innovative perspectives regarding the treatment of glaucoma.

A Concise and Varied Visual Features-Based Image Captioning Model with Visual Selection

Image captioning has gained increasing attention in recent years.Visual characteristics found in input images play a crucial role in generating high-quality captions.Prior studies have used visual attention mechanisms to dynamically focus on localized regions of the input image,improving the effectiveness of identifying relevant image regions at each step of caption generation.However,providing image captioning models with the capability of selecting the most relevant visual features from the input image and attending to them can significantly improve the utilization of these features.Consequently,this leads to enhanced captioning network performance.In light of this,we present an image captioning framework that efficiently exploits the extracted representations of the image.Our framework comprises three key components:the Visual Feature Detector module(VFD),the Visual Feature Visual Attention module(VFVA),and the language model.The VFD module is responsible for detecting a subset of the most pertinent features from the local visual features,creating an updated visual features matrix.Subsequently,the VFVA directs its attention to the visual features matrix generated by the VFD,resulting in an updated context vector employed by the language model to generate an informative description.Integrating the VFD and VFVA modules introduces an additional layer of processing for the visual features,thereby contributing to enhancing the image captioning model’s performance.Using the MS-COCO dataset,our experiments show that the proposed framework competes well with state-of-the-art methods,effectively leveraging visual representations to improve performance.The implementation code can be found here:https://github.com/althobhani/VFDICM(accessed on 30 July 2024).

Bioactive material promotes longdistance regeneration of optic nerve to restore visual functions

Visual system is vital to human beings.Unfortunately,the optic nerve lacks the ability to regenerate after injury.Therefo re,long-distance regeneration of the optic nerve is a major unsolved medical problem in the world(Laha et al.,2017).Recently,Li and So groups' study showed that the bioactive material(ciliary neurotrophic factor[CNTF]-chitosan) could promote long-distance regeneration of the completely transected optic nerve in adult rats and partially restored the visual functions(Liu et al.,2023).This study sheds light on the clinical potential for repairing the severely injured optic nerve.

Effect of capsule treatment on visual acuity and quality after phacoemulsification lens implantation in myopic patients with cataract

BACKGROUND Cataracts pose a significant clinical burden due to their complex pathogenesis.In recent years,an increase in cataracts coexisting with myopia has heightened the incidence of retinopathy and posterior vitreous detachment.Additionally,symptoms of ocular axis elongation,lens nucleus hardening,and vitreous liquefaction have become more prevalent.While conventional extracapsular cataract extraction is commonly employed,it often yields suboptimal visual outcomes.Subsequent advancements in cataract phacoemulsification and lens implantation surgeries have gained widespread acceptance for their ability to improve refraction and significantly improve uncorrected visual acuity.AIM To investigate the effect of capsular treatment after phacoemulsification lens implantation in myopic patients with cataract.METHODS We selected 110 patients(with 134 eyes)with myopia and cataracts treated.These patients were categorized into two groups:an observation group(57 patients with 70 eyes)and a control group(53 patients with 64 eyes).The control group underwent cataract phacoemulsification and lens implantation,while the observation group received a refined capsular treatment based on the control group’s procedure.We assessed the differences in visual acuity and quality between the two groups before and after surgery.RESULTS At six months post-operation,the observation group exhibited significantly improved far vision,intermediate vision,near vision,lower objective scattering index,higher Modulation transfer function cut-off frequency,and overall vision metrics at different contrast levels(100%,20%and 9%)compared to the control group(P<0.05).The total score of the National Eye Institute Visual Function Questionnaire in the observation group at 6 months after operation was significantly higher than that in the control group(P<0.05).No significant difference in the incidence of adverse reactions was observed between the observation group and control group(P>0.05).CONCLUSION Capsular treatment demonstrates efficacy in improving visual acuity and quality after phacoemulsification lens implantation in myopic patients with cataracts,warranting its clinical application.

RMPC-Based Visual Servoing for Trajectory Tracking of Quadrotor UAVs With Visibility Constraints

Dear Editor,This letter deals with the tracking problem of quadrotors subject to external disturbances and visibility constraints by designing a robust model predictive control(RMPC) scheme. According to the imagebased visual servoing(IBVS) method, a virtual camera is constructed to express image moments of the tracking target.

SR9009联合吲哚丙酸通过核因子κB信号通路减轻C2C12成肌细胞的炎症反应

背景:钟基因Rev-erbα参与调节炎症,但激活Rev-erbα会增加心脑血管疾病风险。为降低相关风险,探索Rev-erbα激动剂SR9009联合其他药物来减轻骨骼肌成肌细胞炎症,奠定治疗炎症相关性骨骼肌萎缩的理论基础。目的:探讨脂多糖刺激C2C12成肌细胞时吲哚丙酸、SR9009与核因子κB信号通路的关系。方法:①1μg/mL脂多糖刺激C2C12成肌细胞,RNA转录组测序结合KEGG通路富集分析信号通路。②CCK-8法检测C2C12成肌细胞活性,筛选吲哚丙酸的最佳给药浓度;然后将细胞分为空白对照组、脂多糖(1μg/mL)组、SR9009(10μmol/L)+脂多糖组、吲哚丙酸(80μmol/L)+脂多糖组、吲哚丙酸+SR9009+脂多糖组,ELISA检测细胞上清液中白细胞介素6水平,RT-qPCR检测白细胞介素6、肿瘤坏死因子α、Toll样受体4、CD14 mRNA表达,Western blot检测NF-κB p65、p-NF-κB p65蛋白表达。③siRNA敲减Rev-erbα,RT-qPCR评估敲减效率,检测白细胞介素6、肿瘤坏死因子αmRNA表达。结果与结论:①与空白对照组比较,脂多糖时间依赖性抑制成肌细胞融合形成肌管,白细胞介素6、肿瘤坏死因子αmRNA表达水平升高,细胞上清液中白细胞介素6水平显著升高;KEGG通路分析支持脂多糖刺激激活核因子κB信号通路。②吲哚丙酸浓度>80μmol/L时抑制C2C12成肌细胞活性;吲哚丙酸和SR9009通过抑制核因子κB信号通路发挥抗炎作用,降低白细胞介素6、肿瘤坏死因子α、Toll样受体4、CD14 mRNA表达水平,p-NF-κB p65/NF-κB p65蛋白表达比值低于脂多糖组。SR9009联合吲哚丙酸显著降低脂多糖诱导的炎症,Toll样受体4、CD14、白细胞介素6和肿瘤坏死因子αmRNA表达水平进一步下调,p-NF-κB p65/NF-κB p65蛋白表达比值显著低于吲哚丙酸+脂多糖组和SR9009+脂多糖组。③Rev-erbα随脂多糖刺激时间依赖性升高;siRNA敲减Rev-erbα效率达58%以上,成功敲减Rev-erbα后添加脂多糖,白细胞介素6和肿瘤坏死因子αmRNA表达较脂多糖组显著上调。④结果说明,Rev-erbα可以作为调节炎症反应的靶点,SR9009靶向激活Rev-erbα联合吲哚丙酸能抑制核因子κB信号通路显著减轻C2C12成肌细胞的炎症反应,联合抗炎效果优于单独干预。

A New Perspective in the Study of Medical History through Visuals

In pre-modern cultural history,both textual and visual documentation played crucial roles,each possessing its own narrative logic.Historically,text has been a dominant medium for cultural documentation,whereas images,which predate text,have often been undervalued.

CICARE based communication technique:A passage to faster and smoother visual rehabilitation in post cataract surgery patients

Visual rehabilitation following cataract surgery is often an overlooked aspect.Healthcare providers have an important role in the counselling of the patients undergoing cataract surgery in clearing all their doubts thus alleviating all their fears and anxiety related to the procedure which will eventually lead to faster and smoother visual rehabilitation.Using standardised communication techniques like CICARE combined with conventional nursing and pain scoring systems can provide an objective and effective method in patient counselling and building a rapport with the patient for a faster visual recovery.

Recent progress in visualization and digitization of coherent transformation structures and application in high-strength steel

High-strength steels are mainly composed of medium-or low-temperature microstructures,such as bainite or martensite,with coherent transformation characteristics.This type of microstructure has a high density of dislocations and fine crystallographic structural units,which ease the coordinated matching of high strength,toughness,and plasticity.Meanwhile,given its excellent welding perform-ance,high-strength steel has been widely used in major engineering constructions,such as pipelines,ships,and bridges.However,visual-ization and digitization of the effective units of these coherent transformation structures using traditional methods(optical microscopy and scanning electron microscopy)is difficult due to their complex morphology.Moreover,the establishment of quantitative relationships with macroscopic mechanical properties and key process parameters presents additional difficulty.This article reviews the latest progress in microstructural visualization and digitization of high-strength steel,with a focus on the application of crystallographic methods in the development of high-strength steel plates and welding.We obtained the crystallographic data(Euler angle)of the transformed microstruc-tures through electron back-scattering diffraction and combined them with the calculation of inverse transformation from bainite or martensite to austenite to determine the reconstruction of high-temperature parent austenite and orientation relationship(OR)during con-tinuous cooling transformation.Furthermore,visualization of crystallographic packets,blocks,and variants based on actual OR and digit-ization of various grain boundaries can be effectively completed to establish quantitative relationships with alloy composition and key process parameters,thereby providing reverse design guidance for the development of high-strength steel.

Application of Landscape Engineering based on BIM Visualization Technology

The rapid advancement of building information modeling(BIM)technology has garnered significant interest regarding its application within the domain of landscape engineering.BIM technology,as a construction and management tool that integrates digitization and visualization,has demonstrated considerable advantages in enhancing project quality,reducing costs,and improving collaborative efficiency.This study aims to systematically investigate the application and developmental trends of BIM visualization technology within the field of landscape engineering.Through an analysis of technological advancements and industry dynamics over the past decade,it has been observed that BIM visualization technology is intricately linked with green building practices,sustainable construction methods,and the development of smart cities within the context of landscape engineering projects.The technology also possesses significant potential for application in the planning and design of landscape engineering,construction management,and project maintenance.The convenience of visualization enhances the expressive capacity of the design scheme,improves communication efficiency between the involved parties,and mitigates the costs and time inefficiencies associated with design modifications.By drawing on the successful experiences of other industries and integrating them with the unique characteristics of landscape engineering,BIM visualization technology is poised to assume a more significant role within this field.This integration is expected to advance the entire industry towards greater intelligence and informatization,while simultaneously enhancing the efficiency and quality of design,construction,and maintenance processes.

Vein visualization enhancement by dual-wavelength phase-locked denoising technology

Visual near-infrared imaging equipment has broad applications in various fields such as venipuncture,facial injections,and safety verification due to its noncontact,compact,and portable design.Currently,most studies utilize near-infrared single-wavelength for image acquisition of veins.However,many substances in the skin,including water,protein,and melanin can create significant background noise,which hinders accurate detection.In this paper,we developed a dual-wavelength imaging system with phase-locked denoising technology to acquire vein image.The signals in the effective region are compared by using the absorption valley and peak of hemoglobin at 700nm and 940nm,respectively.The phase-locked denoising algorithm is applied to decrease the noise and interference of complex surroundings from the images.The imaging results of the vein are successfully extracted in complex noise environment.It is demonstrated that the denoising effect on hand veins imaging can be improved with 57.3%by using our dual-wavelength phase-locked denoising technology.Consequently,this work proposes a novel approach for venous imaging with dual-wavelengths and phase-locked denoising algorithm to extract venous imaging results in complex noisy environment better.

SMSTracker:A Self-Calibration Multi-Head Self-Attention Transformer for Visual Object Tracking

Visual object tracking plays a crucial role in computer vision.In recent years,researchers have proposed various methods to achieve high-performance object tracking.Among these,methods based on Transformers have become a research hotspot due to their ability to globally model and contextualize information.However,current Transformer-based object tracking methods still face challenges such as low tracking accuracy and the presence of redundant feature information.In this paper,we introduce self-calibration multi-head self-attention Transformer(SMSTracker)as a solution to these challenges.It employs a hybrid tensor decomposition self-organizing multihead self-attention transformermechanism,which not only compresses and accelerates Transformer operations but also significantly reduces redundant data,thereby enhancing the accuracy and efficiency of tracking.Additionally,we introduce a self-calibration attention fusion block to resolve common issues of attention ambiguities and inconsistencies found in traditional trackingmethods,ensuring the stability and reliability of tracking performance across various scenarios.By integrating a hybrid tensor decomposition approach with a self-organizingmulti-head self-attentive transformer mechanism,SMSTracker enhances the efficiency and accuracy of the tracking process.Experimental results show that SMSTracker achieves competitive performance in visual object tracking,promising more robust and efficient tracking systems,demonstrating its potential to providemore robust and efficient tracking solutions in real-world applications.

Dynamic SLAM Visual Odometry Based on Instance Segmentation:A Comprehensive Review

Dynamic Simultaneous Localization and Mapping(SLAM)in visual scenes is currently a major research area in fields such as robot navigation and autonomous driving.However,in the face of complex real-world envi-ronments,current dynamic SLAM systems struggle to achieve precise localization and map construction.With the advancement of deep learning,there has been increasing interest in the development of deep learning-based dynamic SLAM visual odometry in recent years,and more researchers are turning to deep learning techniques to address the challenges of dynamic SLAM.Compared to dynamic SLAM systems based on deep learning methods such as object detection and semantic segmentation,dynamic SLAM systems based on instance segmentation can not only detect dynamic objects in the scene but also distinguish different instances of the same type of object,thereby reducing the impact of dynamic objects on the SLAM system’s positioning.This article not only introduces traditional dynamic SLAM systems based on mathematical models but also provides a comprehensive analysis of existing instance segmentation algorithms and dynamic SLAM systems based on instance segmentation,comparing and summarizing their advantages and disadvantages.Through comparisons on datasets,it is found that instance segmentation-based methods have significant advantages in accuracy and robustness in dynamic environments.However,the real-time performance of instance segmentation algorithms hinders the widespread application of dynamic SLAM systems.In recent years,the rapid development of single-stage instance segmentationmethods has brought hope for the widespread application of dynamic SLAM systems based on instance segmentation.Finally,possible future research directions and improvementmeasures are discussed for reference by relevant professionals.

Classification of congenital cataracts based on multidimensional phenotypes and its association with visual outcomes

●AIM:To establish a classification for congenital cataracts that can facilitate individualized treatment and help identify individuals with a high likelihood of different visual outcomes.●METHODS:Consecutive patients diagnosed with congenital cataracts and undergoing surgery between January 2005 and November 2021 were recruited.Data on visual outcomes and the phenotypic characteristics of ocular biometry and the anterior and posterior segments were extracted from the patients’medical records.A hierarchical cluster analysis was performed.The main outcome measure was the identification of distinct clusters of eyes with congenital cataracts.●RESULTS:A total of 164 children(299 eyes)were divided into two clusters based on their ocular features.Cluster 1(96 eyes)had a shorter axial length(mean±SD,19.44±1.68 mm),a low prevalence of macular abnormalities(1.04%),and no retinal abnormalities or posterior cataracts.Cluster 2(203 eyes)had a greater axial length(mean±SD,20.42±2.10 mm)and a higher prevalence of macular abnormalities(8.37%),retinal abnormalities(98.52%),and posterior cataracts(4.93%).Compared with the eyes in Cluster 2(57.14%),those in Cluster 1(71.88%)had a 2.2 times higher chance of good best-corrected visual acuity[<0.7 logMAR;OR(95%CI),2.20(1.25–3.81);P=0.006].●CONCLUSION:This retrospective study categorizes congenital cataracts into two distinct clusters,each associated with a different likelihood of visual outcomes.This innovative classification may enable the personalization and prioritization of early interventions for patients who may gain the greatest benefit,thereby making strides toward precision medicine in the field of congenital cataracts.