Effects of Contact Surface Shape on Dynamic Lifetime and Strength of Molecular Bond Clusters under Displacement- and Force-Controlled Loading Conditions.

Many experimental and theoretical studies have shown that the mechanical properties of cells and the extracellular matrix can significantly affect the lifetime and strength of the adhesion clusters of molecular bonds. However, there are few studies on how the shape of the contact surface affects the lifetime and strength of the adhesion clusters of molecular bonds, especially theoretical studies in this area. An idealized model of focal adhesion is adopted, in which two rigid media are bonded together by an array of receptor-ligand bonds modeled as Hookean springs on a complex surface topography, which is described by three parameters: the surface shape factor ß, the length of a single identical surface shape L, and the amplitude of surface shapes w. In this study, systematic Monte Carlo simulations of this model are conducted to study the lifetime of the molecular bond cluster under linear incremental force loading and the strength of the molecular bond cluster under linear incremental displacement loading. We find that both small surface shape amplitudes and large surface shape factors will increase the lifetime and strength of the adhesion cluster, whereas the length of a single surface shape causes oscillations in the lifetime and strength of the cluster, and this oscillation amplitude is affected by the surface shape amplitude and the factor. At the same time, we also find that the pretension in the cluster will play a dominant role in the adhesion strength under large amplitudes and small factors of surface shapes. The physical mechanisms behind these phenomena are that the changes of the length of a single surface shape, the amplitude of surface shapes, and the surface shape factor cause the changes of stress concentration in the adhesion region, bond affinity, and the number of similar affinity bonds.

Serum Amyloid A 4 as a Common Marker of Persistent Inflammation in Patients with Neovascular Age-Related Macular Degeneration and Polypoidal Choroidal Vasculopathy.

Background: Neovascular age-related macular degeneration (nAMD) and its subtype, polypoidal choroidal vasculopathy (PCV), are common choroidal vasculopathies. Although they share many common clinical manifestations and treatment strategies, a lack of comprehensive analysis of these conditions means that it is difficult for researchers to further explore the common pathomechanisms of nAMD and PCV. The aim of this study was to characterize aqueous humor (AH) proteome alterations and identify a novel biomarker related to both nAMD and PCV. Methods: Liquid Chromatography with tandem mass spectrometry (LC-MS/MS) was adopted to analyze the AH proteomes of nAMD, PCV and controls. The target protein was validated using the enzyme-linked immunosorbent assay (ELISA) and subjected to receiver operating characteristic (ROC) curve analysis. Results: A total of 737 different proteins were identified in all the groups, of which 544 were quantifiable. The bioinformatics analysis suggested that immune response activation is the essential event in both nAMD and PCV. Serum amyloid A (SAA) 4 is closely associated with a number of chronic inflammatory diseases, and it was enriched as the hub protein. ROC analysis showed that SAA4 could distinguish both nAMD and PCV from the controls. Conclusion: This comprehensive study provides insights into, and furthers our understanding of, the pathological mechanism of nAMD and PCV. Additionally, the SAA4 level alteration may serve as a common biomarker of nAMD and PCV.

Deep learning-based postoperative visual acuity prediction in idiopathic epiretinal membrane.

BACKGROUND: To develop a deep learning (DL) model based on preoperative optical coherence tomography (OCT) training to automatically predict the 6-month postoperative visual outcomes in patients with idiopathic epiretinal membrane (iERM). METHODS: In this retrospective cohort study, a total of 442 eyes (5304 images in total) were enrolled for the development of the DL and multimodal deep fusion network (MDFN) models. All eyes were randomized into a training dataset with 265 eyes (60.0%), a validation dataset with 89 eyes (20.1%), and an internal testing dataset with the remaining 88 eyes (19.9%). The input variables for prediction consisted of macular OCT images and diverse clinical data. Inception-Resnet-v2 network was utilized to estimate the 6-month postoperative best-corrected visual acuity (BCVA). Concurrently, a regression model was developed using the clinical data and OCT parameters in the training data set for predicting postoperative BCVA. The reliability of the models was subsequently evaluated using the testing dataset. RESULTS: The prediction DL algorithm exhibited a mean absolute error (MAE) of 0.070 logMAR and root mean square error (RMSE) of 0.11 logMAR in the testing dataset. The DL model demonstrated a robust promising performance with R2 = 0.80, notably superior to R2 = 0.49 of the regression model. The percentages of BCVA prediction errors within ± 0.20 logMAR amounted to 94.32% in the testing dataset. CONCLUSIONS: The OCT-based DL model demonstrated sensitivity and accuracy in predicting postoperative BCVA in iERM patients. This innovative DL model exhibits substantial potential for integration into surgical planning protocols.

Data quantity governance for machine learning in materials science.

Data-driven machine learning (ML) is widely employed in the analysis of materials structure-activity relationships, performance optimization and materials design due to its superior ability to reveal latent data patterns and make accurate prediction. However, because of the laborious process of materials data acquisition, ML models encounter the issue of the mismatch between a high dimension of feature space and a small sample size (for traditional ML models) or the mismatch between model parameters and sample size (for deep-learning models), usually resulting in terrible performance. Here, we review the efforts for tackling this issue via feature reduction, sample augmentation and specific ML approaches, and show that the balance between the number of samples and features or model parameters should attract great attention during data quantity governance. Following this, we propose a synergistic data quantity governance flow with the incorporation of materials domain knowledge. After summarizing the approaches to incorporating materials domain knowledge into the process of ML, we provide examples of incorporating domain knowledge into governance schemes to demonstrate the advantages of the approach and applications. The work paves the way for obtaining the required high-quality data to accelerate materials design and discovery based on ML.

Auto-MatRegressor: liberating machine learning alchemists.

Machine learning (ML) is widely used to uncover structure-property relationships of materials due to its ability to quickly find potential data patterns and make accurate predictions. However, like alchemists, materials scientists are plagued by time-consuming and labor-intensive experiments to build high-accuracy ML models. Here, we propose an automatic modeling method based on meta-learning for materials property prediction named Auto-MatRegressor, which automates algorithm selection and hyperparameter optimization by learning from previous modeling experience, i.e., meta-data on historical datasets. The meta-data used in this work consists of 27 meta-features that characterize the datasets and the prediction performances of 18 algorithms commonly used in materials science. To recommend optimal algorithms, a collaborative meta-learning method embedded with domain knowledge quantified by a materials categories tree is designed. Experiments on 60 datasets show that compared with the traditional modeling method from scratch, Auto-MatRegressor automatically selects appropriate algorithms at lower computational cost, which accelerates constructing ML models with good prediction accuracy. Auto-MatRegressor supports dynamic expansion of meta-data with the increase of the number of materials datasets and other required algorithms and can be applied to any ML materials discovery and design task.

Crystal-Liquid-Glass Transition and Near-Unity Photoluminescence Quantum Yield in Low Melting Point Hybrid Metal Halides.

Hybrid metal halides (HMHs) are a class of materials that combine extraordinary photophysical properties and excellent processability. Their chemical variability allows for the solid-liquid transition toward melt-processable HMHs. Herein, we report the design and synthesis of zero-dimensional HMHs [M(DMSO)6][SbCl6], where the isolated octahedra of [M(DMSO)6]3+ and [SbCl6]3- are alternatively aligned in the crystal structure. The luminescent center of [SbCl6]3- enables the photogeneration of self-trapped excitons, resulting in broadband photoluminescence with a large Stokes shift and a nearly 100% quantum yield. Meanwhile, the release of DMSO ligands from [M(DMSO)6]3+ is controlled by the M-O coordination and thus a low melting point of ∼90 °C is achieved for HMHs. Interestingly, the glass phase is obtained by melt quenching, with a sharp change in photoluminescence colors compared to the crystal phase of melt-processable HMHs. The robust crystal-liquid-glass transition opens a new avenue to tailoring structural disorder and optoelectronic performance in organic-inorganic materials.

Risk of diabetic retinopathy and retinal neurodegeneration in individuals with type 2 diabetes: Beichen Eye Study.

Objective: Our aim was to evaluate associations of different risk factors with odds of diabetic retinopathy (DR) diagnosis and retinal neurodegeneration represented by macular ganglion cell-inner plexiform layer (mGCIPL). Methods: This cross-sectional study analyzed data from individuals aged over 50 years examined between June 2020 and February 2022 in the community-based Beichen Eye Study on ocular diseases. Baseline characteristics included demographic data, cardiometabolic risk factors, laboratory findings, and medications at enrollment. Retinal thickness in both eyes of all participants was measured automatically via optical coherence tomography. Risk factors associated with DR status were investigated using multivariable logistic regression. Multivariable linear regression analysis was performed to explore associations of potential risk factors with mGCIPL thickness. Results: Among the 5037 included participants with a mean (standard deviation, SD) age of 62.6 (6.7) years (3258 women [64.6%]), 4018 (79.8%) were control individuals, 835 (16.6%) were diabetic individuals with no DR, and 184 (3.7%) were diabetic individuals with DR. The risk factors significantly associated with DR status were family history of diabetes (odds ratio [OR], 4.09 [95% CI, 2.44-6.85]), fasting plasma glucose (OR, 5.88 [95% CI, 4.66-7.43]), and statins (OR, 2.13 [95% CI, 1.03-4.43]) relative to the control individuals. Compared with the no DR, diabetes duration (OR, 1.17 [95% CI, 1.13-1.22]), hypertension (OR, 1.60 [95% CI, 1.26-2.45]), and glycated hemoglobin A1C (HbA1c) (OR, 1.27 [95% CI, 1.00-1.59]) were significantly correlated with DR status. Furthermore, age (adjusted ß = -0.19 [95% CI, -0.25 to -0.13] µm; P < 0.001), cardiovascular events (adjusted ß = -0.95 [95% CI, -1.78 to -0.12] µm; P = 0.03), and axial length (adjusted ß = -0.82 [95% CI, -1.29 to -0.35] µm; P = 0.001) were associated with mGCIPL thinning in diabetic individuals with no DR. Conclusion: Multiple risk factors were associated with higher odds of DR development and lower mGCIPL thickness in our study. Risk factors affecting DR status varied among the different study populations. Age, cardiovascular events, and axial length were identified as potential risk factors for consideration in relation to retinal neurodegeneration in diabetic patients.

Win-Win by Competition: Auxiliary-Free Cloth-Changing Person Re-Identification.

Recent person Re-IDentification (ReID) systems have been challenged by changes in personnel clothing, leading to the study of Cloth-Changing person ReID (CC-ReID). Commonly used techniques involve incorporating auxiliary information (e.g., body masks, gait, skeleton, and keypoints) to accurately identify the target pedestrian. However, the effectiveness of these methods heavily relies on the quality of auxiliary information and comes at the cost of additional computational resources, ultimately increasing system complexity. This paper focuses on achieving CC-ReID by effectively leveraging the information concealed within the image. To this end, we introduce an Auxiliary-free Competitive IDentification (ACID) model. It achieves a win-win situation by enriching the identity (ID)-preserving information conveyed by the appearance and structure features while maintaining holistic efficiency. In detail, we build a hierarchical competitive strategy that progressively accumulates meticulous ID cues with discriminating feature extraction at the global, channel, and pixel levels during model inference. After mining the hierarchical discriminative clues for appearance and structure features, these enhanced ID-relevant features are crosswise integrated to reconstruct images for reducing intra-class variations. Finally, by combing with self- and cross-ID penalties, the ACID is trained under a generative adversarial learning framework to effectively minimize the distribution discrepancy between the generated data and real-world data. Experimental results on four public cloth-changing datasets (i.e., PRCC-ReID, VC-Cloth, LTCC-ReID, and Celeb-ReID) demonstrate the proposed ACID can achieve superior performance over state-of-the-art methods. The code is available soon at: https://github.com/BoomShakaY/Win-CCReID.

Oxygen doping of cobalt-single-atom coordination enhances peroxymonosulfate activation and high-valent cobalt-oxo species formation.

The high-valent cobalt-oxo species (Co(IV)=O) is being increasingly investigated for water purification because of its high redox potential, long half-life, and antiinterference properties. However, generation of Co(IV)=O is inefficient and unsustainable. Here, a cobalt-single-atom catalyst with N/O dual coordination was synthesized by O-doping engineering. The O-doped catalyst (Co-OCN) greatly activated peroxymonosulfate (PMS) and achieved a pollutant degradation kinetic constant of 73.12 min-1 g-2, which was 4.9 times higher than that of Co-CN (catalyst without O-doping) and higher than those of most reported single-atom catalytic PMS systems. Co-OCN/PMS realized Co(IV)=O dominant oxidation of pollutants by increasing the steady-state concentration of Co(IV)=O (1.03 × 10-10 M) by 5.9 times compared with Co-CN/PMS. A competitive kinetics calculation showed that the oxidation contribution of Co(IV)=O to micropollutant degradation was 97.5% during the Co-OCN/PMS process. Density functional theory calculations showed that O-doping influenced the charge density (increased the Bader charge transfer from 0.68 to 0.85 e), optimized the electron distribution of the Co center (increased the d-band center from -1.14 to -1.06 eV), enhanced the PMS adsorption energy from -2.46 to -3.03 eV, and lowered the energy barrier for generation of the key reaction intermediate (*O*H2O) during Co(IV)=O formation from 1.12 to 0.98 eV. The Co-OCN catalyst was fabricated on carbon felt for a flow-through device, which achieved continuous and efficient removal of micropollutants (degradation efficiency of >85% after 36 h operation). This study provides a new protocol for PMS activation and pollutant elimination through single-atom catalyst heteroatom-doping and high-valent metal-oxo formation during water purification.

Spider-Silk-Inspired Nanocomposite Polymers for Durable Daytime Radiative Cooling.

Passive daytime radiative cooling (PDRC) materials, that strongly reflect sunlight and emit thermal radiation to outer space, demonstrate great potential in energy-saving for sustainable development. Particularly, polymer-based PDRC materials, with advantages of easy-processing, low cost, and outstanding cooling performance, have attracted intense attention. However, just like other polymer devices (for example polymer solar cells) working under sunlight, the issue of durability related to mechanical and UV properties needs to be addressed for large-scale practical applications. Here, a spider-silk-inspired design of nanocomposite polymers with potassium titanate (K2 Ti6 O13 ) nanofiber dopants is proposed for enhancing the durability without compromising their cooling performance. The formed tough interface of nanofiber/polymer effectively disperses stress, enhancing the mechanical properties of the polymer matrix; while the K2 Ti6 O13 can absorb high-energy UV photons and transform them into less harmful heat, thereby improving the UV stabilities. Taking poly(ethylene oxide) radiative cooler as an example for demonstration, its Young's modulus and UV resistance increase by 7 and 12 times, respectively. Consequently, the solar reflectance of nanocomposite poly(ethylene oxide) is maintained as constant in a continuous aging test for 720 h under outdoor sunlight. The work provides a general strategy to simultaneously enhance both the mechanical stability and the UV durability of polymer-based PDRC materials toward large-scale applications.

Chlorination of isothiazolinone biocides: kinetics, reactive species, pathway, and toxicity evolution.

Due to the Covid-19 pandemic, the worldwide biocides application has been increased, which will eventually result in enhanced residuals in treated wastewater. At the same time, chlorine disinfection of secondary effluents and hospital wastewaters has been intensified. With respect to predicted elevated exposure in wastewater, the chlorination kinetics, transformation pathways and toxicity evolution were investigated in this study for two typical isothiazolinone biocides, methyl-isothiazolinone (MIT) and chloro-methyl-isothiazolinone (CMIT). Second-order rate constants of 0.13 M-1·s-1, 1.95 × 105 M-1·s-1 and 5.14 × 105 M-1·s-1 were determined for the reaction of MIT with HOCl, Cl2O and Cl2, respectively, while reactivity of CMIT was around 1-2 orders of magnitude lower. While chlorination of isothiazolinone biocides at pH 7.1 was dominated by Cl2O-oxidation, acidic pH and elevated Cl- concentration favored free active chlorine (FAC) speciation into Cl2 and increased overall isothiazolinone removal. Regardless of the dominant FAC species, the elimination of MIT and CMIT resulted in an immediate loss of acute toxicity under all experimental conditions, which was attributed to a preferential attack at the S-atom resulting in subsequent formation of sulfoxides and sulfones and eventually an S-elimination. However, chlorination of isothiazolinone biocides in secondary effluent only achieved <10% elimination at typical disinfection chlorine exposure 200 mg·L-1·min, but was predicted to be remarkably increased by acidizing solution to pH 5.5. Alternative measures might be needed to minimize the discharge of these toxic chemicals into the aquatic environment.

Near-real-time MODIS-derived vegetation index data products and online services for CONUS based on NASA LANCE.

This paper describes a set of Near-Real-Time (NRT) Vegetation Index (VI) data products for the Conterminous United States (CONUS) based on Moderate Resolution Imaging Spectroradiometer (MODIS) data from Land, Atmosphere Near-real-time Capability for EOS (LANCE), an openly accessible NASA NRT Earth observation data repository. The data set offers a variety of commonly used VIs, including Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Mean-referenced Vegetation Condition Index (MVCI), Ratio to Median Vegetation Condition Index (RMVCI), and Ratio to previous-year Vegetation Condition Index (RVCI). LANCE enables the NRT monitoring of U.S. cropland vegetation conditions within 24 hours of observation. With more than 20 years of observations, this continuous data set enables geospatial time series analysis and change detection in many research fields such as agricultural monitoring, natural resource conservation, environmental modeling, and Earth system science. The complete set of VI data products described in the paper is openly distributed via Web Map Service (WMS) and Web Coverage Service (WCS) as well as the VegScape web application ( https://nassgeodata.gmu.edu/VegScape/ ).

Synergistic dual conversion reactions assisting Pb-S electrochemistry for energy storage.

SignificanceBased on the analysis of three thermodynamic parameters of various M-S systems (solubility of metal sulfides [MxSy] in aqueous solution, volume change of the metal-sulfur [M-S] battery system, and the potential of S/MxSy cathode redox couple), an aqueous Pb-S battery operated by synergistic dual conversion reactions (cathode: S⇄PbS, anode: Pb2+⇄PbO2) has been officially reported. Benefitting from the inherent insolubility of PbS and a conversion-type counter electrode, the aqueous Pb-S battery exhibited two advantages: it is shuttle effect free and has a dendrite-free nature. Moreover, the practical value of the Pb-S battery was further certified by the prototype S|Pb(NO3)2ǁZn(NO3)2|Zn hybrid cell, which afforded an energy density of 930.9 Wh kg-1sulfur.

Synergistic effects of ozone/peroxymonosulfate for isothiazolinone biocides degradation: Kinetics, synergistic performance and influencing factors.

Synergistic effects of ozone (O3) and peroxymonosulfate (PMS, HSO5-) for isothiazolinone biocides degradation was studied. The synergistic ozonation process (O3/PMS) increased the efficiency of methyl-isothiazolinone (MIT) and chloro-methyl-isothiazolinone (CMIT) degradation to 91.0% and 81.8%, respectively, within 90 s at pH 7.0. This is 30.6% and 62.5% higher than the corresponding ozonation efficiency, respectively. Total radical formation value (Rct,R) for the O3/PMS process was 24.6 times that of ozonation alone. Calculated second-order rate constants for the reactions between isothiazolinone biocides and (kSO4-,MIT and kSO4-,CMIT) were 8.15 × 109 and 4.49 × 109 M-1 s-1, respectively. Relative contributions of O3, hydroxyl radical (OH) and oxidation to MIT and CMIT removal were estimated, which were 15%, 45%, and 40% for O3, OH and oxidation to MIT, and 1%, 67%, and 32% for O3, OH and oxidation to CMIT at pH 7.0, respectively. Factors influencing the O3/PMS process, namely the solution pH, chloride ions (Cl-), and bicarbonate (HCO3-), were evaluated. Increasing the solution pH markedly accelerated O3 decay and OH and formation, thus weakening the relative contribution of O3 oxidation while enhancing that of OH and . Cl- had a negligible effect on MIT and CMIT degradation. Under the dual effect of bicarbonate (HCO3-) as inhibitor and promoter, low concentrations (1-2 mM) of bicarbonate weakly promoted MIT and CMIT degradation, while high concentrations (10-20 mM) induced strong inhibition. Lastly, oxidation performance of O3 and O3/PMS processes for MIT and CMIT degradation in different water matrices was compared.

Outcomes of a novel bubble ultra-wide field viewing system for vitreoretinal surgery.

PURPOSE: To report the clinical outcomes and evaluate the efficacy of a novel bubble ultra-wide field viewing system for vitreoretinal surgery. DESIGN: Prospective, noncomparative, interventional case series. PARTICIPANTS: One hundred and fifty-one eyes of 146 consecutive patients with proliferative diabetic retinopathy (PDR), vitreous haemorrhage originating from retinal vein occlusion (VH-RVO), epiretinal membrane (EM), macular hole (MH) or retinal detachment (RD) who underwent vitreoretinal surgery using the bubble ultra-wide field viewing system were included. METHODS: A standard phacoemulsification was performed on each patient. Core humour and mid-peripheral vitreous humour were removed using a planoconcave lens. A suitably sized bubble was infused to attach to the posterior capsule or the anterior chamber depending on the integrity of the posterior capsule. The planoconcave lens and the air bubble formed the wide-angle viewing system, through which peripheral vitrectomy was performed. MAIN OUTCOME MEASURES: Range of applications, field of view, model validation and complications were recorded. RESULTS: The new ultra-wide field viewing system was successfully applied in all eyes, including 34 with PDR, 28 VH-RVO, 28 EM, 25 MH and 36 RD. Peripheral vitrectomy, local or panretinal laser photocoagulation, and removal of the peripheral proliferative membrane were successfully performed while viewing through this system. Maximum peripheral retinal area observable during the procedure was positively correlated with pupil diameter. Model analysis results showed that when the pupil diameter was 6 mm, the maximum field of view was approximately 128.1- 148.0 degrees with this system. Of 142 eyes, the main intraoperative complication was iatrogenic retinal breaks (IRBs) in 8 eyes (5.3%) and posterior capsule injury by vitreous cutter during bubble removal in 6 eyes (4.2%). The postsurgery mean best-corrected visual acuity (BCVA) (0.48 ± 0.39 logMAR) was significantly improved compared with the preoperative mean BCVA (1.60 ± 1.08 logMAR, p < 0.001). No incidents of postoperative choroidal detachment, secondary glaucoma or endophthalmitis were recorded. CONCLUSIONS: For patients with lens excision or absence, vitreoretinal surgery can be successfully performed using the novel viewing system described here. The system is a safe, convenient and economical ultra-wide field viewing system with a wide range of applications.

Promotive effects of vacuum-UV/UV (185/254 nm) light on elimination of recalcitrant trace organic contaminants by UV-AOPs during wastewater treatment and reclamation: A review.

The use of vacuum-UV/UV (185/254 nm) for trace organic contaminants (TOrCs) elimination during wastewater treatments has attracted much attention. Advanced oxidation processes which combine VUV/UV and additional oxidants (vacuum-UV/UV-based advanced oxidation processes, VUV/UV-AOPs) provide a promising method for eliminating recalcitrant and toxic TOrCs for wastewater reclamation. Researches in this area are increasing but the promoting effects, mechanisms, and influencing factors have not been well summarized. A comprehensive discussion of the limitations of this technique and future research directions is needed. VUV/UV-AOPs have considerable synergistic effects by increasing usage of VUV/UV photons and the oxidant, which increases radical generation. In terms of elimination kinetics, VUV/UV-AOPs outperform conventional UV-AOPs and VUV/UV processes in most cases; a 1.2-87.7-fold increase of the fluence-based kinetic constant is achieved. In terms of energy efficiency per order (EE/O) of TOrCs elimination, the EE/O of VUV/UV-AOPs only accounts for 4% of UV-AOPs and 63% of VUV/UV. However, VUV/UV-AOPs still need to be further investigated. Firstly, although VUV and UV processes have similar radical formation pathways, limited information is available on the quantum yields of photolysis and radical formation of oxidants under VUV irradiation. Secondly, optimization of VUV/UV-AOPs operating conditions, especially oxidant dosage and water-flow patterns, is needed. Thirdly, VUV/UV-AOPs are significantly inhibited by organic and inorganic matters, but the mechanisms of inhibition on VUV/UV scattering, radical quenching, and radical conversion are not well understood. Such inhibition suggests that the use of VUV/UV-AOPs would be limited to relatively clear water treatment, e.g., reverse osmosis effluent for potable water reuse and ultrapure water production. Related research is needed to establish a clearer scheme for VUV/UV-AOPs in terms of the spatial distribution of radical species in the VUV/UV irradiation system and the relevant optimization method for promoting oxidation performance.

Classification of diabetic retinopathy: Past, present and future.

Diabetic retinopathy (DR) is a leading cause of visual impairment and blindness worldwide. Since DR was first recognized as an important complication of diabetes, there have been many attempts to accurately classify the severity and stages of disease. These historical classification systems evolved as understanding of disease pathophysiology improved, methods of imaging and assessing DR changed, and effective treatments were developed. Current DR classification systems are effective, and have been the basis of major research trials and clinical management guidelines for decades. However, with further new developments such as recognition of diabetic retinal neurodegeneration, new imaging platforms such as optical coherence tomography and ultra wide-field retinal imaging, artificial intelligence and new treatments, our current classification systems have significant limitations that need to be addressed. In this paper, we provide a historical review of different classification systems for DR, and discuss the limitations of our current classification systems in the context of new developments. We also review the implications of new developments in the field, to see how they might feature in a future, updated classification.

Prussian Blue Analogues in Aqueous Batteries and Desalination Batteries.

In the applications of large-scale energy storage, aqueous batteries are considered as rivals for organic batteries due to their environmentally friendly and low-cost nature. However, carrier ions always exhibit huge hydrated radius in aqueous electrolyte, which brings difficulty to find suitable host materials that can achieve highly reversible insertion and extraction of cations. Owing to open three-dimensional rigid framework and facile synthesis, Prussian blue analogues (PBAs) receive the most extensive attention among various host candidates in aqueous system. Herein, a comprehensive review on recent progresses of PBAs in aqueous batteries is presented. Based on the application in different aqueous systems, the relationship between electrochemical behaviors (redox potential, capacity, cycling stability and rate performance) and structural characteristics (preparation method, structure type, particle size, morphology, crystallinity, defect, metal atom in high-spin state and chemical composition) is analyzed and summarized thoroughly. It can be concluded that the required type of PBAs is different for various carrier ions. In particular, the desalination batteries worked with the same mechanism as aqueous batteries are also discussed in detail to introduce the application of PBAs in aqueous systems comprehensively. This report can help the readers to understand the relationship between physical/chemical characteristics and electrochemical properties for PBAs and find a way to fabricate high-performance PBAs in aqueous batteries and desalination batteries.