Improved multi-scale inverse bottleneck residual network based on triplet parallel attention for apple leaf disease identification

Accurate diagnosis of apple leaf diseases is crucial for improving the quality of apple production and promoting the development of the apple industry. However, apple leaf diseases do not differ significantly from image texture and structural information. The difficulties in disease feature extraction in complex backgrounds slow the related research progress. To address the problems, this paper proposes an improved multi-scale inverse bottleneck residual network model based on a triplet parallel attention mechanism, which is built upon ResNet-50, while improving and combining the inception module and ResNext inverse bottleneck blocks, to recognize seven types of apple leaf(including six diseases of alternaria leaf spot, brown spot, grey spot, mosaic, rust, scab, and one healthy). First, the 3×3 convolutions in some of the residual modules are replaced by multi-scale residual convolutions, the convolution kernels of different sizes contained in each branch of the multi-scale convolution are applied to extract feature maps of different sizes, and the outputs of these branches are multi-scale fused by summing to enrich the output features of the images. Second, the global layer-wise dynamic coordinated inverse bottleneck structure is used to reduce the network feature loss. The inverse bottleneck structure makes the image information less lossy when transforming from different dimensional feature spaces. The fusion of multi-scale and layer-wise dynamic coordinated inverse bottlenecks makes the model effectively balances computational efficiency and feature representation capability, and more robust with a combination of horizontal and vertical features in the fine identification of apple leaf diseases. Finally, after each improved module, a triplet parallel attention module is integrated with cross-dimensional interactions among channels through rotations and residual transformations, which improves the parallel search efficiency of important features and the recognition rate of the network with relatively small computational costs while the dimensional dependencies are improved. To verify the validity of the model in this paper, we uniformly enhance apple leaf disease images screened from the public data sets of Plant Village, Baidu Flying Paddle, and the Internet. The final processed image count is 14,000. The ablation study, pre-processing comparison, and method comparison are conducted on the processed datasets. The experimental results demonstrate that the proposed method reaches 98.73% accuracy on the adopted datasets, which is 1.82% higher than the classical ResNet-50 model, and 0.29% better than the apple leaf disease datasets before preprocessing. It also achieves competitive results in apple leaf disease identification compared to some state-ofthe-art methods.

A semi-analytical model for coupled flow in stress-sensitive multi-scale shale reservoirs with fractal characteristics

A large number of nanopores and complex fracture structures in shale reservoirs results in multi-scale flow of oil. With the development of shale oil reservoirs, the permeability of multi-scale media undergoes changes due to stress sensitivity, which plays a crucial role in controlling pressure propagation and oil flow. This paper proposes a multi-scale coupled flow mathematical model of matrix nanopores, induced fractures, and hydraulic fractures. In this model, the micro-scale effects of shale oil flow in fractal nanopores, fractal induced fracture network, and stress sensitivity of multi-scale media are considered. We solved the model iteratively using Pedrosa transform, semi-analytic Segmented Bessel function, Laplace transform. The results of this model exhibit good agreement with the numerical solution and field production data, confirming the high accuracy of the model. As well, the influence of stress sensitivity on permeability, pressure and production is analyzed. It is shown that the permeability and production decrease significantly when induced fractures are weakly supported. Closed induced fractures can inhibit interporosity flow in the stimulated reservoir volume (SRV). It has been shown in sensitivity analysis that hydraulic fractures are beneficial to early production, and induced fractures in SRV are beneficial to middle production. The model can characterize multi-scale flow characteristics of shale oil, providing theoretical guidance for rapid productivity evaluation.

Multi-scale physics-informed neural networks for solving high Reynolds number boundary layer flows based on matched asymptotic expansions

Multi-scale system remains a classical scientific problem in fluid dynamics,biology,etc.In the present study,a scheme of multi-scale Physics-informed neural networks is proposed to solve the boundary layer flow at high Reynolds numbers without any data.The flow is divided into several regions with different scales based on Prandtl's boundary theory.Different regions are solved with governing equations in different scales.The method of matched asymptotic expansions is used to make the flow field continuously.A flow on a semi infinite flat plate at a high Reynolds number is considered a multi-scale problem because the boundary layer scale is much smaller than the outer flow scale.The results are compared with the reference numerical solutions,which show that the msPINNs can solve the multi-scale problem of the boundary layer in high Reynolds number flows.This scheme can be developed for more multi-scale problems in the future.

Study on Multi-Scale Blending Initial Condition Perturbations for a Regional Ensemble Prediction System

An initial conditions （ICs） perturbation method was developed with the aim to improve an operational regional ensemble prediction system （REPS）. Three issues were identified and investigated： （1） the impacts of perturbation scale on the ensemble spread and forecast skill of the REPS; （2） the scale characteristic of the IC perturbations of the REPS; and （3） whether the REPS＇s skill could be improved by adding large-scale information to the IC perturbations. Numerical experiments were conducted to reveal the impact of perturbation scale on the ensemble spread and forecast skill. The scales of IC perturbations from the REPS and an operational global ensemble prediction system （GEPS） were analyzed. A ＂multi-scale blending＂ （MSB） IC perturbation scheme was developed, and the main findings can be summarized as follows： The growth rates of the ensemble spread of the REPS are sensitive to the scale of the IC perturbations; the ensemble forecast skills can benefit from large-scale perturbations; the global ensemble IC perturbations exhibit more power at larger scales, while the regional ensemble IC perturbations contain more power at smaller scales; the MSB method can generate IC perturbations by combining the small-scale component from the REPS and the large-scale component from the GEPS; the energy norm growth of the MSB-generated perturbations can be appropriate at all forecast lead times; and the MSB-based REPS shows higher skill than the original system, as determined by ensemble forecast verification.

Sutured scleral fixation of existing subluxated/dislocated acrylic one-piece intraocular lenses

AIM:To evaluate the visual and refractive outcomes in cases after sutured scleral fixation of existing subluxated or dislocated acrylic one-piece intraocular lenses(IOLs).METHODS:This study retrospectively enrolled a consecutive series of patients who underwent a surgery of sutured existing subluxated or dislocated IOLs from October 2018 to June 2020.All patients underwent comprehensive preoperative and postoperative ophthalmologic examination,and data were collected including age,sex,surgical indications,best-corrected visual acuity,refractive error,intraocular pressure.Presence of intraoperative and postoperative surgical complications was documented.RESULTS:A total of 20 consecutive cases were enrolled for analysis with mean final follow-up period 9.8±5.3mo.Visual acuity improved from a mean of 0.35(0.46±0.32 logMAR)preoperatively to 0.61(0.21±0.18 logMAR)at the 3-month follow-up(P=0.002).The mean amount of preoperative keratometric astigmatism and total postoperative refractive astigmatism was-1.24±0.80 diopters(D)and-1.42±0.97 D,respectively.There was no statistically significant difference between preoperative and postoperative astigmatism(P=0.156).The mean IOL-induced astigmatism was-0.23±0.53 D.The mean spherical equivalent at the 3-month follow-up was-0.1±0.94 D.No major complications were noted during the follow-up period.CONCLUSION:Surgical techniques using sutured scleral fixation of existing subluxated or dislocated acrylic one-piece IOLs result in favorable visual and refractive outcomes without major complications.

Early clinical outcome with lens position adjustment following implantable collamer lens surgery

AIM:To observe early clinical outcome with lens position adjustment following the implantable collamer lens(ICL)surgery.METHODS:Sixty patients were selected for this retrospective study.One eye from each patient received Toric ICL for astigmatism correction,and the other received non-astigmatic ICL surgery using horizontal position.Patients with higher postoperative arch height were selected,and their non-astigmatic eye clinical outcome were observed after ICL surgery at 1wk,1,and 3mo.The clinical measurements included uncorrected visual acuity(UCVA),intraocular pressure(IOP),refractive state,corneal endothelium cell count,and arch height.Three months later,the ICL in each patient’s non-astigmatic eye was adjusted to the vertical from the horizontal position.The results were compared before and 1wk,1,and 3mo after adjustment.RESULTS:UCVA and IOP were significantly reduced 1wk after position adjustment compared to 1wk after ICL implantation(P<0.05).The patients demonstrated significantly reduced arch height and corneal endothelium cell count 1wk,1,and 3mo after adjusting position compared to 1wk,1,and 3mo after ICL implantation(P<0.05).However,there was no significant difference in refraction between 1wk,1,and 3mo after ICL implantation and position adjustment(P>0.05).CONCLUSION:Early positioning adjustment postphakic ICL implantation can benefit patients with adjusted arch height or higher IOP.Despite the good clinical effects,the doctors should pay attention to the potential for adverse effects on UCVA and corneal endothelium cells following early position adjustment after posterior chamber phakic ICL implantation.

Multi-scale Fractal Characteristics of Atmospheric Boundary-Layer Turbulence

The turbulence data are decomposed to multi-scales and its respective fractal dimensions are computed. The conclusions are drawn from investigating the variation of fractal dimensions. With the level of decomposition increasing, the low-frequency part extracted from the turbulence signals tends to be simple and smooth, the dimensions decrease; the high-frequency part shows complex, the dimensions are fixed, about 1.70 on the average, which indicates clear self-similarity characteristics.

Evaluating the Effects of Graviton Redshift upon Spiral Galaxy Rotation Curves, Surface Brightness Magnitudes and Gravitational Lensing

The effects of the gravitational redshift of gravitons upon spiral galaxy rotation energy are compared to the standard mass to light analyses in obtaining rotation curves. The derivation of the total baryonic matter compares well with the standard theory and the rotation velocity is matched to a high precision. The stellar mass distributions obtained from the fit with graviton energy loss are used to derive the surface brightness magnitudes for the galaxies, which agree well with the observed measurements. In a new field of investigation, the graviton theory is applied to the observations of gravitational lenses. The results of these applications of the theory suggest that it can augment the standard methods and may eliminate the need for dark matter.

Experimental study on spectrum and multi-scale nature of wall pressure and velocity in turbulent boundary layer

When using a miniature single sensor boundary layer probe, the time sequences of the stream-wise velocity in the turbulent boundary layer （TBL） are measured by using a hot wire anemometer. Beneath the fully developed TBL, the wall pressure fluctuations are attained by a microphone mechanism with high spatial resolution. Analysis on the statistic and spectrum properties of velocity and wall pressure reveals the relationship between the wall pressure fluctuation and the energy-containing structure in the buffer layer of the TBL. Wavelet transform shows the multi-scale natures of coherent structures contained in both signals of velocity and pressure. The most intermittent wall pressure scale is associated with the coherent structure in the buffer layer. Meanwhile the most energetic scale of velocity fluctuation at y＋ = 14 provides a specific frequency f9 ≈ 147 Hz for wall actuating control with Ret = 996.

MSD-Net: Pneumonia Classification Model Based on Multi-Scale Directional Feature Enhancement

Computer-aided diagnosis of pneumonia based on deep learning is a research hotspot.However,there are some problems that the features of different sizes and different directions are not sufficient when extracting the features in lung X-ray images.A pneumonia classification model based on multi-scale directional feature enhancement MSD-Net is proposed in this paper.The main innovations are as follows:Firstly,the Multi-scale Residual Feature Extraction Module(MRFEM)is designed to effectively extract multi-scale features.The MRFEM uses dilated convolutions with different expansion rates to increase the receptive field and extract multi-scale features effectively.Secondly,the Multi-scale Directional Feature Perception Module(MDFPM)is designed,which uses a three-branch structure of different sizes convolution to transmit direction feature layer by layer,and focuses on the target region to enhance the feature information.Thirdly,the Axial Compression Former Module(ACFM)is designed to perform global calculations to enhance the perception ability of global features in different directions.To verify the effectiveness of the MSD-Net,comparative experiments and ablation experiments are carried out.In the COVID-19 RADIOGRAPHY DATABASE,the Accuracy,Recall,Precision,F1 Score,and Specificity of MSD-Net are 97.76%,95.57%,95.52%,95.52%,and 98.51%,respectively.In the chest X-ray dataset,the Accuracy,Recall,Precision,F1 Score and Specificity of MSD-Net are 97.78%,95.22%,96.49%,95.58%,and 98.11%,respectively.This model improves the accuracy of lung image recognition effectively and provides an important clinical reference to pneumonia Computer-Aided Diagnosis.

Multi-scale context-aware network for continuous sign language recognition

The hands and face are the most important parts for expressing sign language morphemes in sign language videos.However,we find that existing Continuous Sign Language Recognition(CSLR)methods lack the mining of hand and face information in visual backbones or use expensive and time-consuming external extractors to explore this information.In addition,the signs have different lengths,whereas previous CSLR methods typically use a fixed-length window to segment the video to capture sequential features and then perform global temporal modeling,which disturbs the perception of complete signs.In this study,we propose a Multi-Scale Context-Aware network(MSCA-Net)to solve the aforementioned problems.Our MSCA-Net contains two main modules:(1)Multi-Scale Motion Attention(MSMA),which uses the differences among frames to perceive information of the hands and face in multiple spatial scales,replacing the heavy feature extractors;and(2)Multi-Scale Temporal Modeling(MSTM),which explores crucial temporal information in the sign language video from different temporal scales.We conduct extensive experiments using three widely used sign language datasets,i.e.,RWTH-PHOENIX-Weather-2014,RWTH-PHOENIX-Weather-2014T,and CSL-Daily.The proposed MSCA-Net achieve state-of-the-art performance,demonstrating the effectiveness of our approach.

YOLO-MFD:Remote Sensing Image Object Detection with Multi-Scale Fusion Dynamic Head

Remote sensing imagery,due to its high altitude,presents inherent challenges characterized by multiple scales,limited target areas,and intricate backgrounds.These inherent traits often lead to increased miss and false detection rates when applying object recognition algorithms tailored for remote sensing imagery.Additionally,these complexities contribute to inaccuracies in target localization and hinder precise target categorization.This paper addresses these challenges by proposing a solution:The YOLO-MFD model(YOLO-MFD:Remote Sensing Image Object Detection withMulti-scale Fusion Dynamic Head).Before presenting our method,we delve into the prevalent issues faced in remote sensing imagery analysis.Specifically,we emphasize the struggles of existing object recognition algorithms in comprehensively capturing critical image features amidst varying scales and complex backgrounds.To resolve these issues,we introduce a novel approach.First,we propose the implementation of a lightweight multi-scale module called CEF.This module significantly improves the model’s ability to comprehensively capture important image features by merging multi-scale feature information.It effectively addresses the issues of missed detection and mistaken alarms that are common in remote sensing imagery.Second,an additional layer of small target detection heads is added,and a residual link is established with the higher-level feature extraction module in the backbone section.This allows the model to incorporate shallower information,significantly improving the accuracy of target localization in remotely sensed images.Finally,a dynamic head attentionmechanism is introduced.This allows themodel to exhibit greater flexibility and accuracy in recognizing shapes and targets of different sizes.Consequently,the precision of object detection is significantly improved.The trial results show that the YOLO-MFD model shows improvements of 6.3%,3.5%,and 2.5%over the original YOLOv8 model in Precision,map@0.5 and map@0.5:0.95,separately.These results illustrate the clear advantages of the method.

Transfer learning framework for multi-scale crack type classification with sparse microseismic networks

Rock fracture mechanisms can be inferred from moment tensors(MT)inverted from microseismic events.However,MT can only be inverted for events whose waveforms are acquired across a network of sensors.This is limiting for underground mines where the microseismic stations often lack azimuthal coverage.Thus,there is a need for a method to invert fracture mechanisms using waveforms acquired by a sparse microseismic network.Here,we present a novel,multi-scale framework to classify whether a rock crack contracts or dilates based on a single waveform.The framework consists of a deep learning model that is initially trained on 2400000+manually labelled field-scale seismic and microseismic waveforms acquired across 692 stations.Transfer learning is then applied to fine-tune the model on 300000+MT-labelled labscale acoustic emission waveforms from 39 individual experiments instrumented with different sensor layouts,loading,and rock types in training.The optimal model achieves over 86%F-score on unseen waveforms at both the lab-and field-scale.This model outperforms existing empirical methods in classification of rock fracture mechanisms monitored by a sparse microseismic network.This facilitates rapid assessment of,and early warning against,various rock engineering hazard such as induced earthquakes and rock bursts.

Biocompatibility of light responsive materials prepared for accommodative intraocular lenses manufacturing

AIM:To investigate the biocompatibility and bacterial adhesion properties of light responsive materials(LRM)and analyze the feasibility and biosafety of employing LRM in the preparation of accommodative intraocular lenses(AIOLs).METHODS:Employing fundamental experimental research techniques,LRM with human lens epithelial cells(hLECs)and human retinal pigment epithelium cells(ARPE-19 cells)were co-cultured.Commercially available intraocular lenses(IOLs)were used as controls to perform cell counting kit-8(CCK-8),cell staining under varying light intensities,cell adhesion and bacterial adhesion experiments.RESULTS:LRM exhibited a stronger inhibitory effect on the proliferation of ARPE19 cells than commercially available IOLs when co-cultured with the undiluted extract for 96h(P<0.05).Under other culturing conditions,the effects on the proliferation of hLECs and ARPE-19 cells were not significantly different between the two materials.Under the influence of light irradiation at intensities of 200 and 300 mW/cm^(2),LRM demonstrated a markedly higher inhibitory effect on the survival of hLECs compared to commercially available IOLs(P<0.0001).They also showed a stronger suppressive effect on the survival rate of ARPE-19 cells,with significant differences observed at 200 mW/cm^(2)(P<0.001)and extremely significant differences at 300 mW/cm^(2)(P<0.0001).Additionally,compared to commercially available IOLs,LRM had a higher number of cells adhering to their surface(P<0.05),as well as a significantly greater number of adherent bacterium(P<0.0001).CONCLUSION:LRM,characterized by their excellent non-contact tunable deformability and low cytotoxicity to ocular tissues,show considerable potential for use in the fabrication of AIOLs.These materials demonstrate strong cell adhesion;however,during photothermal conversion processes involving shape deformation under various light intensities,the resultant temperature rise may harm surrounding cells.These factors suggest that while the material plays a positive role in reducing the incidence of posterior capsule opacification(PCO),it also poses potential risks for retinal damage.Additionally,the strong bacterial adhesion of these materials indicates an increased risk of endophthalmitis.

Modeling monocular form deprivation in rabbits using a simulated-cataract intraocular lens

AIM:To establish an animal model of form deprivation amblyopia based on a simulated cataract intraocular lens(IOLs).METHODS:Poly(dimethyl siloxane)-SiO_(2) thin films(PSF)with different degrees of opacity as IOL materials were prepared.The light transmission of the PSF-IOL was measured,and its in vitro biosafety was determined by cell counting kit(CCK)-8 assay using the HLEC-B3 cell line and ARPE-19 cell line.Subsequently,the in vivo safety was determined by implanting the PSF-IOL with 10%wt SiO_(2) into the right eyes of New Zealand white rabbits(PSF-IOL group),and compared with two control groups:contralateral comparison group and normal control(NC)group(Contralateral comparison group:the fellow eye;NC group:a group of binocular normal rabbits without intervention).The flash visual-evoked potentials(F-VEPs)were measured to verify amblyopia.RESULTS:PSFs containing 0,2%,and 10%wt SiO_(2) were successfully constructed.The 0 SiO_(2) PSF was transparent,while the 10%wt SiO_(2) PSF was completely opaque.It was found that PSF did not induce unwanted cytotoxicity in HLECs and ARPE19 cells in vitro.In vitro,PSF-IOL with 10%wt SiO_(2) was also non-toxic,and no significant inflammation or structural changes occurred after four weeks of PSF-IOL implantation.Finally,our IOL-simulated congenital cataract rabbit detected by F-VEPs suggested tentative amblyopia.CONCLUSION:A PSF-IOL that mimics cataracts is created.A novel form deprivation model is created by the IOL-simulated congenital cataract rabbit.It can be developed fast and stable and holds great potential for future study.

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.

Clinical prediction of insufficient vaults after implantable collamer lens implantation

AIM:To determine the factors related to preoperative ocular characters that are predictive of insufficient vault(<250μm)after implantable collamer lens(ICL V4c;STAAR Surgical)implantation.METHODS:The participants underwent ICL surgery and were divided into the low(<250μm)and normal(250-1000μm)vault groups based on the postoperative vault at 3mo.The preoperative biometric parameters and clinical outcomes were compared between the two groups.The relationship between the 3-month vault values and preoperative ocular parameters were evaluated by Generalized estimating equations.RESULTS:Sixteen(23 eyes)and 36 patients(63 eyes)were in the low and normal vault groups,respectively.All implantation procedures were uneventful with no cataract formation in the early postoperative period.The sulcusto-sulcus lens rise(STSL)and iris ciliary angle(ICA)were correlated with vault at 3mo after surgery.Every 0.1 mm increase in STSL was associated with 38.9μm decrease in the postoperative 3-month vault.A rise of 1 degree in ICA is associated with a reduction of 4μm in vault.CONCLUSION:Eyes with a narrow ciliary sulcus are associated with a higher rate of low vault after ICL implantation,suggesting a need for adjustments to the ICL size in these patients.Evaluating the characteristics of the ciliary sulcus contributes valuable information to predict low vault after surgery.

Intraocular lens selection in diabetic patients:How to increase the odds for success

The incidence of cataracts is significantly higher in diabetic individuals,particularly in younger age groups,with rates quadrupled in those under 65 and doubled in those over 65 compared to non-diabetics.Cataract surgery in diabetic patients poses many challenges:Poor epithelial healing,decreased corneal sensitivity,increased central corneal thickness,decreased endothelial cell count,variable topography,poor pupillary dilatation,anterior capsular phimosis,posterior capsular opacification(PCO),chances of progression of diabetic retinopathy(DR),zonular weakness,and vitreous prolapse and diabetic macular edema.Selection of an appropriate intraocular lens(IOL)is crucial for visual rehabilitation and monitoring DR.The choice of IOL in diabetic cataract patients is a challenging scenario.Square-edge IOLs are favored for their capacity to mitigate PCO,whereas hydrophilic counterparts may incur calcification in the setting of proliferative DR.The advisability of premium IOLs for achieving spectacle independence warrants judicious evaluation,particularly in the presence of advanced retinopathy.Optimal IOL placement within the capsular bag is advocated to minimize postoperative complications.Rigorous preoperative assessment and informed patient counseling regarding IOL options are indispensable for optimizing surgical outcomes.This review article covers various aspects regarding the choice of IOLs in different case scenarios and complications in the diabetic population.

Impact of multifocal gas-permeable lens designs on short-term choroidal response, axial length, and retinal defocus profile

AIM:To investigate the impact of multifocal gas permeable contact lens(MFGPCL)in various add power and distance/near area allocation on short-term changes of choroidal thickness(ChT),axial length(AL),and retinal defocus profile in young adults.METHODS:Seventeen young adults(2 males and 15 females;age 23.17±4.48y)were randomly assigned to wear two designs binocularly with a one-week washout period in between.Total of four MFGPCL designs were assessed.All designs were distance-center that varied in two add power(+1.50 and 3.00 D)and/or two distance zone(DZ)diameters(1.50 and 3.00 mm;design A:DZ 1.5/add 3.0,B:DZ 1.5/add 1.5,C:DZ 3.0/add 3.0,D:DZ 3.0/add 1.5).ChT,AL,and peripheral refraction data were collected on each subject at baseline,on days 1 and 7 of MFGPCL daily wear.ChT was assessed in four quadrants using a spectraldomain optical coherence tomography.RESULTS:AL was shortened by-26±44μm with lens C,-18±27μm with lens D,-13±29μm with lens A,and-8±30μm with lens B(all P<0.05).A significant overall increase in ChT was observed with all 4 designs(lens A:+6±6μm,B:+3±7μm,C:+8±7μm,and D:+8±7μm).Temporal and superior choroid exhibited more choroidal thickening associated with MFGPCL.All designs induced significant relative peripheral myopia(RPM)beyond the central 20o across the horizontal meridian in both nasal and temporal fields(P<0.05).CONCLUSION:MFGPCLs show a significant influence on ChT and AL,which are associated with significant increase in RPM after short-term wear.The reliability and feasibility of quantifying short-term changes in ChT support its use as a promising marker for the long-term efficacy of myopia-controlling treatments.

Rhegmatogenous retinal detachment in highly myopic eyes with implantable collamer lens

AIM:To investigate the clinical characteristics,treatment methods and outcomes of rhegmatogenous retinal detachment(RRD)in highly myopic eyes with implantable collamer lens(ICL).METHODS:High myopia patients who received treatment for nontraumatic RRD after ICL implantation surgery at the Retinal Department of Zhongshan Ophthalmic Center from Jan 2018 to Dec 2022 were reviewed.Comprehensive ophthalmologic examinations including visual acuity measurement and digital fundus photography were performed in each patient.RESULTS:A total of nine RRD eyes from nine patients who received V4c-ICL implantation were included.The mean time from ICL implantation surgery to the diagnosis of RRD was 32.44±22.56mo(range,1-60mo).At the initial visit for RRD,giant retinal tear(GRT),horseshoe tear,simple round hole,and horseshoe tear combined with round hole were detected in 3,3,2,and 1 eye(s),respectively,with maculaoff in eyes.Eight patients received surgical treatment,and one patient was treated by retinal laser photocoagulation alone.The ICL was preserved in 7 eyes.At the last followup,the mean best corrected visual acuity(BCVA)improved significantly from 1.76±1.06 logMAR at presentation to 0.81±1.01 logMAR(P=0.035),and no case of recurrent retinal detachment was found.CONCLUSION:The morphological presentation of retinal breaks is diverse in this study.The ICL can be preserved in most cases during the course of retinal detachment repair surgery in our data,companied with acceptable visual and anatomical outcomes.