基于RNA-Seq技术对不同品种猪排卵前卵泡差异表达基因的筛选与注释

[目的]筛选淮猪和大约克猪排卵前卵泡组织差异表达基因。[方法]采集淮猪和大约克猪各3头的排卵前卵泡,提取RNA,个体独立建库。采用RNA测序技术以及GO和pathway方法对所获序列进行显著性富集分析。[结果]测序后,获得的淮猪clean reads数分别为85958912、91701082、84448828,其中有效Reads数分别达到98.39%、98.59%、96.04%;获得的大约克猪clean reads数分别为87914166、80480542、85994612,其中有效reads数分别达到98.61%、96.95%、98.80%,测序饱和度良好(证明测序数据真实可靠)。结果表明,筛选到上调基因67个,下调基因54个。GO和Pathway分析发现,差异表达基因富集在繁殖过程、生长过程和代谢过程及WNT信号通路、卵巢类固醇生成通路和类固醇生物合成通路等。[结论]获得了猪排卵前卵泡基因表达谱,并筛选到与繁殖性状相关的关键候选基因。

基于RNA-seq对复合益生菌作用于肉鸡回肠中新转录本预测及可变剪接、SNP分析

为分析复合益生菌饲喂肉鸡回肠转录组中的新转录本预测、可变剪接事件和SNP,选择200只1日龄黄麻肉鸡随机分为2组,每组5个重复,每个重复20只。对照组正常饮水,益生菌组饮用水中补充1%复合菌制剂,试验分为生长前期(1~21 d)、后期(22~42 d)两个阶段。42日龄时进行肉鸡屠宰试验,取对照组和益生菌组回肠各3个样本进行转录组测序。对测序数据进行分析,共发现1047个新基因,20176个新转录本,276个新基因在GO数据库中得到归类注释。对转录组数据进行可变剪接分析,外显子跳跃(SE)占可变剪接类型的比例最高,共筛选到1131个显著的差异剪接基因,在外显子跳跃(SE)、第一个外显子可变剪接(A5SS)、最后一个外显子可变剪接(A3SS)、外显子选择性跳跃(MXE)、内含子滞留(RI)事件中鉴定到的差异剪接基因数分别为588、139、176、136、92。对获得的差异剪接基因进行GO富集分析,主要富集在代谢和免疫GO term。KEGG富集到了胞吞作用、MAPK信号通路等。在各样品中大多数碱基取代均为转换大于颠换,其中转换单核苷酸多态性(SNP)所占百分比为73.53%~73.94%;颠换型SNP所占百分比为26.05%~26.47%。试验对对照组、益生菌组肉鸡的回肠进行了RNA-seq测序分析,为发掘复合益生菌作用于肉鸡回肠中的可变剪接事件提供基础,为进一步了解复合益生菌作用于肉鸡回肠中新转录本的发现和SNP位点提供了数据支撑。

基于MobileNetV3Small-ECA的水稻病害轻量级识别研究

为实现水稻病害的轻量化识别与检测,使用ECA注意力机制改进MobileNetV3Small模型,并使用共享参数迁移学习对水稻病害进行智能化轻量级识别和检测。在PlantVillage数据集上进行预训练,将预训练得到的共享参数迁移到对水稻病害识别模型上微调优化。在开源水稻病害数据集上进行试验测试,试验结果表明,在非迁移学习下,识别准确率达到97.47%,在迁移学习下识别准确率达到99.92%,同时参数量减少26.69%。其次,通过Grad-CAM进行可视化,本文方法与其他注意力机制CBAM和SENET相比,ECA模块生成的结果与图像中病斑的位置和颜色更加一致,表明网络可以更好地聚焦水稻病害的特征,并且通过可视化和各水稻病害分析了误分类原因。本文方法实现了水稻病害识别模型的轻量化,使其能够在移动设备等资源受限的场景中部署,达到快速、高效、便携的目的。同时开发了基于Android的水稻病害识别系统,方便于在边缘端进行水稻病害识别分析。

BSA-Seq结合RNA-Seq技术挖掘大豆叶片提前黄化衰老基因

大豆产量与其生殖生长的持续时间呈正相关,延缓其开花后叶片的衰老,提高其生理功能,有利于增加植物的粒重。叶片黄化是植物衰老的显著特征之一。关于在大豆鼓粒后期叶片黄化的研究鲜见报道。本研究对鼓粒后期叶片提前黄化突变体ly和野生型ofc杂交组合进行遗传分析,结果表明,大豆鼓粒后期叶片提前黄化性状受单隐性核基因控制。通过BSA-Seq在19号染色体得到一个2.23Mb的初定位区间,经开发标记图位克隆后将区间缩短至1.75 Mb,区间内有219个基因,再结合RNA-Seq分析,得到了区间内12个候选基因,其中有4个SNP变异基因和8个差异表达基因。本研究结果为大豆鼓粒后期叶片黄化衰老基因的克隆奠定了基础。

基于RNA-Seq分析大白猪和巴马香猪背最长肌组织基因表达差异

以180日龄的大白猪(n=6)与巴马香猪(n=6)为研究对象,屠宰后测定肌内脂肪、肉色、嫩度、pH、滴水损失等肉质性状,采集背最长肌组织提取总RNA,利用RNA-Seq技术鉴定大白猪和巴马香猪背最长肌组织中的表达差异基因及其功能富集通路。结果发现,以大白猪为对照组,在巴马香猪和大白猪背最长肌组织中共鉴定到5 037个差异表达基因,其中有3 326个上调表达基因,1 711个下调表达基因。经过KEGG富集通路分析,发现巴马香猪和大白猪一共有168条显著富集通路,其中上调DEGs有92条富集路径,下调DEGs有76条富集路径;GO功能分析中上调表达基因富集到BP有3 058条、CC有413条、MF有559条,下调表达基因富集到BP有3 050条、CC有415条、MF有557条。大白猪与巴马香猪肉色的亮度L在45min时呈极显著差异;大白猪与巴马香猪之间的肌内脂肪、水分均呈现显著差异。本文对大白猪与巴马香猪肌内脂肪含量进行转录组测序分析,初步认为CAPN3、MTM1、TMOD4等基因在巴马香猪肉质中发挥重要作用。

基于RNA-Seq探究蔗糖影响黑果枸杞枝刺发生的机理

【目的】黑果枸杞Lycium ruthenicum是集生态、经济和药用价值等为一体的灌木。然而,其密集的枝刺严重阻碍其作为经济林推广,本研究旨在探究蔗糖(Suc)促进黑果枸杞(黑杞)枝刺的发生机理,为培育其无刺优良品种提供依据。【方法】在证明Suc通过能量和信号路径促进黑杞枝刺发生的基础上,利用RNA-Seq对无刺茎顶芽(TleCK)、有刺茎顶芽(ThoCK)、黑暗处理的有刺茎顶芽(ThoDCK)、减少内源Suc处理后有刺变无刺茎顶芽(TleDPL)和喷施外源Suc后无刺变有刺茎顶芽(ThoSuc)5种样品的差异表达基因(DEG)和叶绿体差异基因(cpDEG)进行筛选和分析,并采用RT-qPCR验证了9个DEG的表达情况。【结果】5组有刺和无刺材料顶芽之间(ThoCK vs.TleCK、ThoCK vs.TleDPL、ThoDCK vs.TleDPL、TleCK vs.ThoSuc和TleDPL vs.ThoSuc)的DEG分别为5281、4363、3125、5226和3278个,这5组DEG共同显著富集在9个GO条目和4个KEGG通路(“类黄酮生物合成”“二萜生物合成”“苯丙烷生物合成”、“芪类、二芳基庚烷和姜辣素生物合成”)。韦恩图显示5组比较组共有的DEG是196个,其中33个被预测为转录因子基因,较多转录因子基因被预测为NAC和WRKY家族。5组比较组有3个共有DEG注释在植物激素信号转导KEGG通路,分别参与生长素、茉莉酸和水杨酸信号传导。3个关键有刺和无刺比较组(ThoCK vs.TleCK、ThoCK vs.TleDPL和TleCK vs.ThoSuc)中共有2个DEG被预测为TCP转录因子基因,这3个比较组均有cpDEG被注释到光合作用KEGG通路。9个DEG的RT-qPCR验证了RNA-Seq结果的可靠性。【结论】Suc可能通过影响生长素、茉莉酸和水杨酸信号传导以及赤霉素合成基因表达来促进黑杞枝刺发生,枝刺发生也可能与类黄酮积累和木质素减少有关,而且增施外源和减少内源Suc并非通过简单地逆转cpDEG的表达来影响枝刺发生。注释到WRKY、TCP和NAC转录因子家族的共有DEG可能是调控枝刺发生的关键基因。本研究建立了Suc影响黑杞枝刺发生的机理模型图。

Revealing the role of honokiol in human glioma cells by RNA-seq analysis

Background:Glioma is a kind of tumor that easily deteriorates and originates from glial cells in nerve tissue.Honokiol is a bisphenol compound that is an essential monomeric compound extracted from the roots and bark of Magnoliaceae plants.It also has anti-infection,antitumor,and immunomodulatory effects.In this study,we found that honokiol induces cell apoptosis in the human glioma cell lines U87-MG and U251-MG.However,the mechanism through which honokiol regulates glioma cell apoptosis is still unknown.Methods:We performed RNA-seq analysis of U251-MG cells treated with honokiol and control cells.Protein-protein interaction(PPI)network analysis was performed,and the 10 top hub unigenes were examined via real-time quantitative PCR.Furthermore,MAPK signaling and ferroptosis were detected via western blotting.Results:332 differentially expressed genes(DEGs)were found,comprising 163 increased and 169 decreased genes.Analysis of the DEGs revealed that various biological processes were enriched,including‘response to hypoxia’,‘cerebellum development cellular response to hypoxia,’‘iron ion binding,’‘oxygen transporter activity,’‘oxygen binding,’‘ferric iron binding,’and‘structural constituent of cytoskeleton.’Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis revealed that the DEGs were enriched in the following pathways:‘mitogen-activated protein kinases(MAPK)’,‘Hypoxia-inducible factor 1(HIF-1)’,‘ferroptosis,’‘Peroxisome proliferator-activated receptor(PPAR),’‘Phosphatidylinositol-4,5-bisphosphate 3-kinase(PI3K)-protein kinase B(Akt),’and‘phagosome.’Among these pathways,the MAPK signaling pathway and ferroptosis were verified.Conclusion:This study revealed the potential mechanism by which honokiol induces apoptosis and provided a comprehensive analysis of DEGs in honokiol-treated U251-MG cells and the associated signaling pathways.These data could lead to new ideas for future research and therapy for patients with glioma.

Meiotic transcriptional reprogramming mediated by cell-cell communications in humans and mice revealed by scATACseq and scRNA-seq

Meiosis is a highly complex process significantly influenced by transcriptional regulation.However,studies on the mechanisms that govern transcriptomic changes during meiosis,especially in prophase I,are limited.Here,we performed single-cell ATAC-seq of human testis tissues and observed reprogramming during the transition from zygotene to pachytene spermatocytes.This event,conserved in mice,involved the deactivation of genes associated with meiosis after reprogramming and the activation of those related to spermatogenesis before their functional onset.Furthermore,we identified 282 transcriptional regulators(TRs)that underwent activation or deactivation subsequent to this process.Evidence suggested that physical contact signals from Sertoli cells may regulate these TRs in spermatocytes,while secreted ENHO signals may alter metabolic patterns in these cells.Our results further indicated that defective transcriptional reprogramming may be associated with non-obstructive azoospermia(NOA).This study revealed the importance of both physical contact and secreted signals between Sertoli cells and germ cells in meiotic progression.

H-and J-aggregation of conjugated small molecules in organic solar cells

As H-and J-aggregation receive more and more attention in the research of organic solar cells(OSCs),especially in small molecular systems,deep understanding of aggregation behavior is needed to guide the design of conjugated small molecular structure and the fabrication process of OSC device.For this end,this review is written.Here,the review firstly introduced the basic information about H-and J-aggregation of conjugated small molecules in OSCs.Then,the characteristics of H-and J-aggregation and the methods to identify them were summarized.Next,it reviewed the research progress of H-and J-aggregation of conjugated small molecules in OSCs,including the factors influencing H-and J-aggregation in thin film and the effects of H-and J-aggregation on OPV performance.

Small nucleolar RNA and its potential role in the oncogenesis and development of colorectal cancer

Small nucleolar RNAs(snoRNAs)represent a class of non-coding RNAs that play pivotal roles in post-transcriptional RNA processing and modification,thereby contributing significantly to the maintenance of cellular functions related to protein synthesis.SnoRNAs have been discovered to possess the ability to influence cell fate and alter disease progression,holding immense potential in controlling human diseases.It is suggested that the dysregulation of snoRNAs in cancer exhibits differential expression across various cancer types,stages,metastasis,treatment response and/or prognosis in patients.On the other hand,colorectal cancer(CRC),a prevalent malignancy of the digestive system,is characterized by high incidence and mortality rates,ranking as the third most common cancer type.Recent research indicates that snoRNA dysregulation is associated with CRC,as snoRNA expression significantly differs between normal and cancerous conditions.Consequently,assessing snoRNA expression level and function holds promise for the prognosis and diagnosis of CRC.Nevertheless,current comprehension of the potential roles of snoRNAs in CRC remains limited.This review offers a comprehensive survey of the aberrant regulation of snoRNAs in CRC,providing valuable insights into the discovery of novel biomarkers,therapeutic targets,and potential tools for the diagnosis and treatment of CRC and furnishing critical cues for advancing research into CRC and the judicious selection of therapeutic targets.

Stage Ⅳ non-small cell lung cancer with multiple metastases to the small intestine leading to intussusception: A case report

BACKGROUND Gastrointestinal tract metastasis from lung cancer is rare and compared to small cell lung cancer(SCLC),non-SCLC(NSCLC)is even less likely to metastasize in this manner.Additionally,small intestinal tumors can also present with diverse complications,some of which require urgent intervention.CASE SUMMARY In this report,we detail a unique case of stage IV lung cancer,where the presence of small intestine tumors led to intussusception.Subsequent to a small intestine resection,pathology confirmed that all three tumors within the small intestine were metastases from adenocarcinoma of the lung.The postoperative follow-up period extended beyond 14 mo.CONCLUSION In patients with stage IV NSCLC,local tumor control can be achieved with various treatments.However,if small intestinal metastasis occurs,surgical intervention remains necessary,as it may improve survival.

RNA-seq技术在虾蟹研究中的应用

基于高通量测序技术的RNA-seq技术已被广泛应用于较高经济价值的虾蟹类动物研究中,从分子水平剖析虾蟹类生命周期中相关基因的调控功能和遗传信息。本文综述了对虾蟹类动物转录组研究现状,包括虾蟹类的生长发育、生殖繁育、环境胁迫、免疫应答、营养代谢和分子标记开发等,分析了RNA-seq技术在虾蟹类研究中面临的局限与挑战,以期为更深入开展虾蟹类分子生物学研究提供参考。

Ten-year observation of corneal densitometry and associated factors following small incision lenticule extraction

●AIM:To investigate the long-term changes of corneal densitometry(CD)and its contributing elements after small incision lenticule extraction(SMILE).●METHODS:Totally 31 eyes of 31 patients with mean spherical equivalent of-6.46±1.50 D and mean age 28.23±7.38y were enrolled.Full-scale examinations were conducted on all patients preoperatively and during followup.Visual acuity,manifest refraction,axial length,corneal thickness,corneal higher-order aberrations,and CD were evaluated.●RESULTS:All surgeries were completed successfully without complications or adverse events.Ten-year safety index was 1.17±0.20 and efficacy 1.04±0.28.CD value of 0–6 mm zones in central layer was statistically significantly lower 10y postoperatively,compared with preoperative values(0–2 mmΔ=-1.62,2–6 mmΔ=-1.24,P<0.01).There were no correlations between CD values and factors evaluated.●CONCLUSION:SMILE is a safe and efficient procedure for myopia on a long-term basis.CD values get lower 10y postoperatively,whose mechanism is to be further discussed.

Enhancing Dense Small Object Detection in UAV Images Based on Hybrid Transformer

Transformer-based models have facilitated significant advances in object detection.However,their extensive computational consumption and suboptimal detection of dense small objects curtail their applicability in unmanned aerial vehicle(UAV)imagery.Addressing these limitations,we propose a hybrid transformer-based detector,H-DETR,and enhance it for dense small objects,leading to an accurate and efficient model.Firstly,we introduce a hybrid transformer encoder,which integrates a convolutional neural network-based cross-scale fusion module with the original encoder to handle multi-scale feature sequences more efficiently.Furthermore,we propose two novel strategies to enhance detection performance without incurring additional inference computation.Query filter is designed to cope with the dense clustering inherent in drone-captured images by counteracting similar queries with a training-aware non-maximum suppression.Adversarial denoising learning is a novel enhancement method inspired by adversarial learning,which improves the detection of numerous small targets by counteracting the effects of artificial spatial and semantic noise.Extensive experiments on the VisDrone and UAVDT datasets substantiate the effectiveness of our approach,achieving a significant improvement in accuracy with a reduction in computational complexity.Our method achieves 31.9%and 21.1%AP on the VisDrone and UAVDT datasets,respectively,and has a faster inference speed,making it a competitive model in UAV image object detection.

MSC-YOLO:Improved YOLOv7 Based on Multi-Scale Spatial Context for Small Object Detection in UAV-View

Accurately identifying small objects in high-resolution aerial images presents a complex and crucial task in thefield of small object detection on unmanned aerial vehicles(UAVs).This task is challenging due to variations inUAV flight altitude,differences in object scales,as well as factors like flight speed and motion blur.To enhancethe detection efficacy of small targets in drone aerial imagery,we propose an enhanced You Only Look Onceversion 7(YOLOv7)algorithm based on multi-scale spatial context.We build the MSC-YOLO model,whichincorporates an additional prediction head,denoted as P2,to improve adaptability for small objects.We replaceconventional downsampling with a Spatial-to-Depth Convolutional Combination(CSPDC)module to mitigatethe loss of intricate feature details related to small objects.Furthermore,we propose a Spatial Context Pyramidwith Multi-Scale Attention(SCPMA)module,which captures spatial and channel-dependent features of smalltargets acrossmultiple scales.This module enhances the perception of spatial contextual features and the utilizationof multiscale feature information.On the Visdrone2023 and UAVDT datasets,MSC-YOLO achieves remarkableresults,outperforming the baseline method YOLOv7 by 3.0%in terms ofmean average precision(mAP).The MSCYOLOalgorithm proposed in this paper has demonstrated satisfactory performance in detecting small targets inUAV aerial photography,providing strong support for practical applications.

A Real-Time Small Target Vehicle Detection Algorithm with an Improved YOLOv5m Network Model

To address the challenges of high complexity,poor real-time performance,and low detection rates for small target vehicles in existing vehicle object detection algorithms,this paper proposes a real-time lightweight architecture based on You Only Look Once(YOLO)v5m.Firstly,a lightweight upsampling operator called Content-Aware Reassembly of Features(CARAFE)is introduced in the feature fusion layer of the network to maximize the extraction of deep-level features for small target vehicles,reducing the missed detection rate and false detection rate.Secondly,a new prediction layer for tiny targets is added,and the feature fusion network is redesigned to enhance the detection capability for small targets.Finally,this paper applies L1 regularization to train the improved network,followed by pruning and fine-tuning operations to remove redundant channels,reducing computational and parameter complexity and enhancing the detection efficiency of the network.Training is conducted on the VisDrone2019-DET dataset.The experimental results show that the proposed algorithmreduces parameters and computation by 63.8% and 65.8%,respectively.The average detection accuracy improves by 5.15%,and the detection speed reaches 47 images per second,satisfying real-time requirements.Compared with existing approaches,including YOLOv5m and classical vehicle detection algorithms,our method achieves higher accuracy and faster speed for real-time detection of small target vehicles in edge computing.

Responses of Nutrients to the Precipitation Variation and Land Use in Subtropical Monsoonal Small Mountainous Rivers:A Case Study of Baixi Watershed

Small mountainous rivers are characterized by large instantaneous fluxes and susceptible to extreme weather events,which can rapidly transport materials into the sea and have a significant impact on the ecological environment of estuaries and bays.In order to investigate the seasonal characteristics of nutrients in small mountainous rivers in the subtropical monsoon region and the output pattern to the sea during heavy precipitation,surveys on the mountainous rivers were carried out in Baixi watershed in August 2020(wet season),March 2021(dry season)and June 2021(Meiyu period).The results showed that the dissolved inorganic nitrogen(DIN)of the rivers has an average concentration of 752μg L^(−1)in the wet season and 1472μg L^(−1)in the dry season.The concentrations of dissolved inorganic phosphorus(DIP)in wet season and dry season were 63μg L^(−1)and 51μg L^(−1),respectively.Influenced by the changes of land use in sub-watersheds,DIN concentrations in the mainstream increased from 701μg L^(−1)in the upper reaches to 1284μg L^(−1)in the middle reaches.Two rainstorms during the Meiyu period in the watershed caused the pulse runoff in the river.The maximum daily runoff reached 70 times that before rains.The maximum daily fluxes of DIN and DIP were 109 and 247 times that before rains,respectively.In view that the watershed experienced several rainstorms in the wet season,the river,with pulse runoff,carries a large amount of nutrients into the sea in a short time,which will have a significant impact on the environment of Sanmen bay and its adjacent sea.

A Simple and Effective Surface Defect Detection Method of Power Line Insulators for Difficult Small Objects

Insulator defect detection plays a vital role in maintaining the secure operation of power systems.To address the issues of the difficulty of detecting small objects and missing objects due to the small scale,variable scale,and fuzzy edge morphology of insulator defects,we construct an insulator dataset with 1600 samples containing flashovers and breakages.Then a simple and effective surface defect detection method of power line insulators for difficult small objects is proposed.Firstly,a high-resolution featuremap is introduced and a small object prediction layer is added so that the model can detect tiny objects.Secondly,a simplified adaptive spatial feature fusion(SASFF)module is introduced to perform cross-scale spatial fusion to improve adaptability to variable multi-scale features.Finally,we propose an enhanced deformable attention mechanism(EDAM)module.By integrating a gating activation function,the model is further inspired to learn a small number of critical sampling points near reference points.And the module can improve the perception of object morphology.The experimental results indicate that concerning the dataset of flashover and breakage defects,this method improves the performance of YOLOv5,YOLOv7,and YOLOv8.In practical application,it can simply and effectively improve the precision of power line insulator defect detection and reduce missing detection for difficult small objects.

CAW-YOLO:Cross-Layer Fusion and Weighted Receptive Field-Based YOLO for Small Object Detection in Remote Sensing

In recent years,there has been extensive research on object detection methods applied to optical remote sensing images utilizing convolutional neural networks.Despite these efforts,the detection of small objects in remote sensing remains a formidable challenge.The deep network structure will bring about the loss of object features,resulting in the loss of object features and the near elimination of some subtle features associated with small objects in deep layers.Additionally,the features of small objects are susceptible to interference from background features contained within the image,leading to a decline in detection accuracy.Moreover,the sensitivity of small objects to the bounding box perturbation further increases the detection difficulty.In this paper,we introduce a novel approach,Cross-Layer Fusion and Weighted Receptive Field-based YOLO(CAW-YOLO),specifically designed for small object detection in remote sensing.To address feature loss in deep layers,we have devised a cross-layer attention fusion module.Background noise is effectively filtered through the incorporation of Bi-Level Routing Attention(BRA).To enhance the model’s capacity to perceive multi-scale objects,particularly small-scale objects,we introduce a weightedmulti-receptive field atrous spatial pyramid poolingmodule.Furthermore,wemitigate the sensitivity arising from bounding box perturbation by incorporating the joint Normalized Wasserstein Distance(NWD)and Efficient Intersection over Union(EIoU)losses.The efficacy of the proposedmodel in detecting small objects in remote sensing has been validated through experiments conducted on three publicly available datasets.The experimental results unequivocally demonstrate the model’s pronounced advantages in small object detection for remote sensing,surpassing the performance of current mainstream models.

Changes in posterior corneal elevation after small incision lenticule extraction for different myopic diopters

●AIM:To study the changes and effect factors of posterior corneal surface after small incision lenticule extraction(SMILE)with different myopic diopters.●METHODS:Ninety eyes of 90 patients who underwent SMILE were included in this retrospective study.Patients were allocated into three groups based on the preoperative spherical equivalent(SE):low myopia(SE≥-3.00 D),moderate myopia(-3.00 D>SE>-6.00 D)and high myopia(SE≤-6.00 D).Posterior corneal surfaces were measured by a Scheimpflug camera preoperatively and different postoperative times(1wk,1,3,6mo,and 1y).Posterior mean elevation(PME)at 25 predetermined points of 3 concentric circles(2-,4-,and 6-mm diameter)above the best fit sphere was analyzed.●RESULTS:All surgeries were completed uneventfully and no ectasia was found through the observation.The difference of myopia group was significant at the 2-mm ring at 1 and 3mo postoperatively(1mo:P=0.017;3mo:P=0.018).The effect of time onΔPME was statistically significant(2-mm ring:P=0.001;4-mm ring:P<0.001;6-mm ring:P<0.001).The effect of different corneal locations onΔPME was significant except 1wk postoperatively(1mo:P=0.000;3mo:P=0.000;6mo:P=0.001;1y:P=0.001).Posterior corneal stability was linearly correlated with SE,central corneal thickness,ablation depth,residual bed thickness,percent ablation depth and percent stromal bed thickness.●CONCLUSION:The posterior corneal surface changes dynamically after SMILE.No protrusion is observed on the posterior corneal surface in patients with different degrees of myopia within one year after surgery.SMILE has good stability,accuracy,safety and predictability.