Rapid detection of guttae area using aniline blue staining in Fuchs endothelial corneal dystrophy mouse model.

Fuchs endothelial corneal dystrophy (FECD) is a leading cause of corneal endothelial degeneration resulting in impaired visual acuity. Excessive deposition of extracellular matrix (guttae) on Descemet's membrane (DM) is the hallmark of FECD. We sought to detect the guttae area rapidly using aniline blue (AB) staining in FECD mouse model. FECD mouse model was established via ultraviolet A (UVA) exposure. Masson's trichrome staining was utilized to stain the corneal sections. AB staining was utilized to stain both whole cornea tissues and stripped Descemet's membrane-endothelium complex (DMEC) flat mounts, while immunofluorescence staining of collagen I was employed to stain guttae areas. In Masson's trichrome staining, corneal collagen fibrils were stained blue with AB. The DMEC flat mounts were stained into relative dark blue areas and relative light blue areas using 2% AB staining. The areas of dark blue could almost overlap with collagen I-positive areas, and have an acellular centre and a moderately distinct boundary line with the surrounding corneal endothelial cells. In conclusion, AB staining is a rapid and effective method for the evaluation of the guttae areas in the FECD mouse model.

Benchmarking four large language models' performance of addressing Chinese patients' inquiries about dry eye disease: A two-phase study.

Purpose: To evaluate the performance of four large language models (LLMs)-GPT-4, PaLM 2, Qwen, and Baichuan 2-in generating responses to inquiries from Chinese patients about dry eye disease (DED). Design: Two-phase study, including a cross-sectional test in the first phase and a real-world clinical assessment in the second phase. Subjects: Eight board-certified ophthalmologists and 46 patients with DED. Methods: The chatbots' responses to Chinese patients' inquiries about DED were assessed by the evaluation. In the first phase, six senior ophthalmologists subjectively rated the chatbots' responses using a 5-point Likert scale across five domains: correctness, completeness, readability, helpfulness, and safety. Objective readability analysis was performed using a Chinese readability analysis platform. In the second phase, 46 representative patients with DED asked the two language models (GPT-4 and Baichuan 2) that performed best in the in the first phase questions and then rated the answers for satisfaction and readability. Two senior ophthalmologists then assessed the responses across the five domains. Main outcome measures: Subjective scores for the five domains and objective readability scores in the first phase. The patient satisfaction, readability scores, and subjective scores for the five-domains in the second phase. Results: In the first phase, GPT-4 exhibited superior performance across the five domains (correctness: 4.47; completeness: 4.39; readability: 4.47; helpfulness: 4.49; safety: 4.47, p < 0.05). However, the readability analysis revealed that GPT-4's responses were highly complex, with an average score of 12.86 (p < 0.05) compared to scores of 10.87, 11.53, and 11.26 for Qwen, Baichuan 2, and PaLM 2, respectively. In the second phase, as shown by the scores for the five domains, both GPT-4 and Baichuan 2 were adept in answering questions posed by patients with DED. However, the completeness of Baichuan 2's responses was relatively poor (4.04 vs. 4.48 for GPT-4, p < 0.05). Nevertheless, Baichuan 2's recommendations more comprehensible than those of GPT-4 (patient readability: 3.91 vs. 4.61, p < 0.05; ophthalmologist readability: 2.67 vs. 4.33). Conclusions: The findings underscore the potential of LLMs, particularly that of GPT-4 and Baichuan 2, in delivering accurate and comprehensive responses to questions from Chinese patients about DED.

Evaluating the effectiveness of large language models in patient education for conjunctivitis.

AIMS: To evaluate the quality of responses from large language models (LLMs) to patient-generated conjunctivitis questions. METHODS: A two-phase, cross-sectional study was conducted at the Eye and ENT Hospital of Fudan University. In phase 1, four LLMs (GPT-4, Qwen, Baichuan 2 and PaLM 2) responded to 22 frequently asked conjunctivitis questions. Six expert ophthalmologists assessed these responses using a 5-point Likert scale for correctness, completeness, readability, helpfulness and safety, supplemented by objective readability analysis. Phase 2 involved 30 conjunctivitis patients who interacted with GPT-4 or Qwen, evaluating the LLM-generated responses based on satisfaction, humanisation, professionalism and the same dimensions except for correctness from phase 1. Three ophthalmologists assessed responses using phase 1 criteria, allowing for a comparative analysis between medical and patient evaluations, probing the study's practical significance. RESULTS: In phase 1, GPT-4 excelled across all metrics, particularly in correctness (4.39±0.76), completeness (4.31±0.96) and readability (4.65±0.59) while Qwen showed similarly strong performance in helpfulness (4.37±0.93) and safety (4.25±1.03). Baichuan 2 and PaLM 2 were effective but trailed behind GPT-4 and Qwen. The objective readability analysis revealed GPT-4's responses as the most detailed, with PaLM 2's being the most succinct. Phase 2 demonstrated GPT-4 and Qwen's robust performance, with high satisfaction levels and consistent evaluations from both patients and professionals. CONCLUSIONS: Our study showed LLMs effectively improve patient education in conjunctivitis. These models showed considerable promise in real-world patient interactions. Despite encouraging results, further refinement, particularly in personalisation and handling complex inquiries, is essential prior to the clinical integration of these LLMs.

Effects of riparian pioneer plants on soil aggregate stability: Roles of root traits and rhizosphere microorganisms.

Pioneer plants are vital in stabilizing soil structure while restoring reservoir drawdown areas. However, uncertainties persist regarding the mechanism of pioneer plants to soil stability in these delicate ecosystems. This study aims to unravel the plant-soil feedback mechanisms from the roles of root traits and rhizosphere microorganisms. We conducted a mesocosm experiment focusing on four common pioneer plants from the drawdown area of Three Gorges Reservoir, China. Using the wet sieving methodology, trait-based approach and high-throughput sequencing technology, we explored soil aggregate stability parameters, plant root traits and rhizosphere microbial communities in experimental plant groups. The interacting effect of pioneer plant species richness, root traits, and rhizosphere microbial communities on soil aggregate stability was quantified by statistical and machine-learning models. Our results demonstrate that diverse pioneer plant communities significantly enhance soil aggregate stability. Notably, specific species, such as Cynodon dactylon (L.) Pers. and Xanthium strumarium L., exert a remarkably strong influence on soil stability due to their distinctive root traits. Root length density (RLD) and root specific surface area (RSA) were identified as crucial root traits mediating the impact of plant diversity on soil aggregate stability. Additionally, our study highlights the link between increased rhizosphere fungal richness, accompanied by plant species richness, and enhanced soil aggregate stability, likely attributable to elevated RLD and RSA. These insights deepen our understanding of the role of pioneer vegetation in soil structure and stability, providing valuable implications for ecological restoration and management practices in reservoir drawdown areas.

Synergistic Radiation Effects in PPD CMOS Image Sensors Induced by Neutron Displacement Damage and Gamma Ionization Damage.

The synergistic effects on the 0.18 µm PPD CISs induced by neutron displacement damage and gamma ionization damage are investigated. The typical characterizations of the CISs induced by the neutron displacement damage and gamma ionization damage are presented separately. The CISs are irradiated by reactor neutron beams up to 1 × 1011 n/cm2 (1 MeV neutron equivalent fluence) and 60Co γ-rays up to the total ionizing dose level of 200 krad(Si) with different sequential order. The experimental results show that the mean dark signal increase in the CISs induced by reactor neutron radiation has not been influenced by previous 60Co γ-ray radiation. However, the mean dark signal increase in the CISs induced by 60Co γ-ray radiation has been remarkably influenced by previous reactor neutron radiation. The synergistic effects on the PPD CISs are discussed by combining the experimental results and the TCAD simulation results of radiation damage.

Employing hybrid deep learning for near-real-time forecasts of sensor-based algal parameters in a Microcystis bloom-dominated lake.

Harmful cyanobacterial blooms (CyanoHABs) are increasingly impacting the ecosystem of lakes, reservoirs and estuaries globally. The integration of real-time monitoring and deep learning technology has opened up new horizons for early warnings of CyanoHABs. However, unlike traditional methods such as pigment quantification or microscopy counting, the high-frequency data from in-situ fluorometric sensors display unpredictable fluctuations and variability, posing a challenge for predictive models to discern underlying trends within the time-series sequence. This study introduces a hybrid framework for near-real-time CyanoHABs predictions in a cyanobacterium Microcystis-dominated lake - Lake Dianchi, China. The proposed model was validated using hourly Chlorophyll-a (Chl a) concentrations and algal cell densities. Our results demonstrate that applying decomposition-based singular spectrum analysis (SSA) significantly enhances the prediction accuracy of subsequent CyanoHABs models, particularly in the case of temporal convolutional network (TCN). Comparative experiments revealed that the SSA-TCN model outperforms other SSA-based deep learning models for predicting Chl a (R2 = 0.45-0.93, RMSE = 2.29-5.89 µg/L) and algal cell density (R2 = 0.63-0.89, RMSE = 9489.39-16,015.37 cells/mL) at one to four steps ahead predictions. The forecast of bloom intensities achieved a remarkable accuracy of 98.56 % and an average precision rate of 94.04 % ± 0.05 %. In addition, scenarios involving various input combinations of environmental factors demonstrated that water temperature emerged as the most effective driver for CyanoHABs predictions, with a mean RMSE of 2.94 ± 0.12 µg/L, MAE of 1.55 ± 0.09 µg/L, and R2 of 0.83 ± 0.01. Overall, the newly developed approach underscores the potential of a well-designed hybrid deep-learning framework for accurately predicting sensor-based algal parameters. It offers novel perspectives for managing CyanoHABs through online monitoring and artificial intelligence in aquatic ecosystems.

Long noncoding RNA ZFAS1: A novel anti-apoptotic target in Fuchs endothelial corneal dystrophy.

Fuchs endothelial corneal dystrophy (FECD) is the leading cause of endothelial keratoplasty without efficacious drug treatment. Recent studies have emphasized the involvement of epigenetic regulation in FECD development. Long non-coding RNAs (lncRNAs) are recognized as crucial epigenetic regulators in diverse cellular processes and ocular diseases. In this study, we revealed the expression patterns of lncRNAs using high-throughput sequencing technology in FECD mouse model, and identified 979 significantly dysregulated lncRNAs. By comparing the data from FECD human cell model, we obtained a series of homologous lncRNAs with similar expression patterns, and revealed that these homologous lncRNAs were enriched in FECD related biological functions, with apoptosis (mmu04210) showing the highest enrichment score. In addition, we investigated the role of lncRNA zinc finger antisense 1 (ZFAS1) in apoptotic process. This study would broaden our understanding of epigenetic regulation in FECD development, and provide potential anti-apoptotic targets for FECD therapy.

Changes in CO2 concentration drive a succession of toxic and non-toxic strains of Microcystis blooms.

The dynamic changes between toxic and non-toxic strains of Microcystis blooms have always been a hot topic. Previous studies have found that low CO2 favors toxic strains, but how changing dissolved CO2 (CO2 [aq]) in water body influences the succession of toxic and non-toxic strains in Microcystis blooms remains uncertain. Here, we combined laboratory competition experiments, field observations, and a machine learning model to reveal the links between CO2 changes and the succession. Laboratory experiments showed that under low CO2 conditions (100-150 ppm), the toxic strains could make better use of CO2 (aq) and be dominant. The non-toxic strains demonstrated a growth advantage as CO2 concentration increased (400-1000 ppm). Field observations from June to November in Lake Taihu showed that the percentage of toxic strains increased as CO2 (aq) decreased. Machine learning highlighted links between the inorganic carbon concentration and the proportion of advantageous strains. Our findings provide new insights for cyanoHABs prediction and prevention.

Heparanase inhibitor OGT 2115 induces prostate cancer cell apoptosis via the downregulation of MCL­1.

Heparanase (HPSE), an endo-ß-D-glucuronidase, cleaves heparan sulfate and serves an important role in the tumor microenvironment and thus in tumorigenesis. HPSE is known to promote tumor cell evasion of apoptosis. However, the underlying mechanism of this requires further study. In the present study, the results demonstrated that myeloid cell leukemia-1 (MCL-1), an antiapoptotic protein, and HPSE were upregulated in prostate cancer tissues compared with adjacent normal tissues. In addition, the HPSE inhibitor, OGT 2115, inhibited PC-3 and DU-145 prostate cancer cell viability in a dose-dependent manner, with IC50 values of 20.2 and 97.2 µM, respectively. Furthermore, annexin V/PI double-staining assays demonstrated that OGT 2115 induced apoptosis in prostate cancer cells. OGT 2115 treatment markedly decreased MCL-1 protein expression levels, whereas RNA interference-mediated downregulation of MCL-1 and OGT 2115 drug treatment synergistically induced apoptosis in PC-3 and DU-145 cells. In vivo, OGT 2115 40 mg/kg (ig) significantly inhibited PC-3 cell xenograft growth in nude mice and increased the positive TUNEL staining rate of xenograft tissues. It was therefore hypothesized that MCL-1 was an important signaling molecule in OGT 2115-induced apoptosis. The results of the present study also demonstrated that the proteasome inhibitor, MG-132, markedly inhibited the downregulation of MCL-1 protein expression levels induced by OGT 2115. However, the protein synthesis inhibitor, cycloheximide, did not affect the role of OGT 2115 in regulating MCL-1. In summary, the results of the present study demonstrated that the proapoptotic activity of OGT 2115 was achieved by downregulating MCL-1.

Single-cell RNA sequencing reveals the complex cellular niche of pterygium.

PURPOSE: Pterygium is a vision-threatening conjunctival fibrovascular degenerated disease with a high global prevalence up to 12 %, while no absolute pharmacotherapy has been applied in clinics. In virtue of single-cell RNA sequencing (scRNA-seq) technique, our study investigated underlying pathogeneses and potential therapeutic targets of pterygium from the cellular transcriptional level. METHODS: A total of 45605 cells from pterygium of patients and conjunctiva of normal controls (NC) were conducted with scRNA-seq, and then analyzed via integrated analysis, pathway enrichment, pseudotime trajectory, and cell-cell communications. Besides, immunofluorescence and western blot were performed in vivo and in vitro to verify our findings. RESULTS: In brief, 9 major cellular types were defined, according to canonical markers. Subsequently, we further determined the subgroups of each major cell lineages. Several newly identified cell sub-clusters could promote pterygium, including immuno-fibroblasts, epithelial mesenchymal transition (EMT)-epithelial cells, and activated vascular endothelial cells (activated-vEndo). Besides, we also probed the enrichment of immune cells in pterygium. Particularly, macrophages, recruited by ACKR1+activated-vEndo, might play an important role in the development of pterygium by promoting angiogenesis, immune suppression, and inflammation. CONCLUSION: An intricate cellular niche was revealed in pterygium via scRNA-seq analysis and the interactions between macrophages and ACKR1+ activated-vEndo might be the key part in the development of pterygia.

Surface Roughness Prediction of Titanium Alloy during Abrasive Belt Grinding Based on an Improved Radial Basis Function (RBF) Neural Network.

Titanium alloys have become an indispensable material for all walks of life because of their excellent strength and corrosion resistance. However, grinding titanium alloy is exceedingly challenging due to its pronounced material characteristics. Therefore, it is crucial to create a theoretical roughness prediction model, serving to modify the machining parameters in real time. To forecast the surface roughness of titanium alloy grinding, an improved radial basis function neural network model based on particle swarm optimization combined with the grey wolf optimization method (GWO-PSO-RBF) was developed in this study. The results demonstrate that the improved neural network developed in this research outperforms the classical models in terms of all prediction parameters, with a model-fitting R2 value of 0.919.

Focal lymphoblastic transformation of chronic myelogenous leukemia develops into erythroid leukemia: A case report.

BACKGROUND: We present a case of focal lymphoblastic transformation to erythroid leukemia following acute myeloblastic transformation in a patient with chronic myelogenous leukemia (CML) and discuss its mechanism of occurrence and development. CASE SUMMARY: The presence of the Philadelphia (Ph) chromosome was identified through karyotype analysis, while the BCR-ABL fusion gene was detected using quantitative real-time polymerase chain reaction of the peripheral blood sample. Fluorescence in situ hybridization was used to detect the expression of the BCR-ABL gene in the lymphoma. Antigen expression and gene mutations in the primitive cells were detected by flow cytometry. The analysis confirmed the presence of CML along with focal lymphoblastic transformation to erythroid leukemia. Additionally, the patient was found to have secondary erythroid leukemia, along with multiple new gene mutations and abnormalities in complex karyotypes of chromosomes. CONCLUSION: Our findings suggest a possible molecular basis for the focal lymphoblastic transformation secondary to myeloblastic transformation in patients with CML.

Cigarette Smoke Mediates Nasal Epithelial Barrier Dysfunction via TNF-α.

BACKGROUND: Extensive data suggest that exposure to cigarette smoke can induce pulmonary epithelial barrier dysfunction. However, the effects of cigarette smoke on the nasal epithelial barrier are still unclear. Here, we investigated the consequence and mechanism of cigarette smoke on the nasal epithelial barrier. METHODS: Sprague Dawley rats were exposed to cigarette smoke for 3 or 6 months, and changes in inflammatory markers and nasal barrier function were evaluated. Moreover, underlying mechanisms were explored. Finally, normal human bronchial epithelial cells were cultured with or without tumor necrosis factor-alpha (TNF-α) in vitro, and the levels of continuity and tight junction-associated proteins were measured. RESULTS: In vivo experiments showed that the nasal mucosal barrier function of rats exposed to cigarette smoke was disturbed. Indeed, proteins associated with tight junctions were decreased, and the levels of inflammatory factors, such as IL-8, IL-6, and TNF-α, were dramatically increased in comparison to those of control animals. In vitro, TNF-α was shown to disrupt the continuity of proteins associated with tight junctions and to downregulate the expression of these proteins in bronchial epithelial cells. CONCLUSIONS: We found that cigarette smoke disrupted the nasal mucosal barrier, and the extent of the damage was correlated with the duration of cigarette smoke exposure. We showed that TNF-α can disrupt the continuity and attenuate the expression of tight junction proteins in human bronchial epithelial cells. Therefore, cigarette smoke may induce nasal epithelial barrier dysfunction through TNF-α.

Nutrient reduction mitigated the expansion of cyanobacterial blooms caused by climate change in Lake Taihu according to Bayesian network models.

Although nutrient reduction has been used for lake eutrophication mitigation worldwide, the use of this practice alone has been shown to be less effective in combatting cyanobacterial blooms, primarily because of climate change. In addition, quantifying the climate change contribution to cyanobacterial blooms is difficult, further complicating efforts to set nutrient reduction goals for mitigating blooms in freshwater lakes. This study employed a continuous variable Bayesian modeling framework to develop a model to predict spring cyanobacterial bloom areas and frequencies (the responses) using nutrient levels and climatic factors as predictors. Our results suggested that both spring climatic factors (e.g., increasing temperature and decreasing wind speed) and nutrients (e.g., total phosphorus) played vital roles in spring blooms in Lake Taihu, with climatic factors being the primary drivers for both bloom areas and frequencies. Climate change in spring had a 90% probability of increasing the bloom area from 35 km2 to 180 km2 during our study period, while nutrient reduction limited the bloom area to 170 km2, which helped mitigate expansion of cyanobacterial blooms. For lake management, to ensure a 90% probability of the mean spring bloom areas remaining under 154 km2 (the 75th percentile of the bloom areas in spring), the total phosphorus should be maintained below 0.073 mg·L-1 under current climatic conditions, which is a 46.3% reduction from the current level. Our modeling approach is an effective method for deriving dynamic nutrient thresholds for lake management under different climatic scenarios and management goals.

[Research Advances on the Relationship between Overt Hyperthyroidism and Risk of Erectile Dysfunction].

Studies have demonstrated the detrimental effects of overt hyperthyroidism on sexual functioning.Here,we comprehensively reviewed the studies that focused on the association between overt hyperthyroidism and erectile dysfunction (ED).After the systematic searching for relevant studies,we find that overt hyperthyroidism is significantly associated with the high risk of ED.The prevalence of ED in patients with hyperthyroidism ranges from 3.05% to 85%,while that in general population is 2.16% to 33.8%.A study reported that the erectile functioning of the hyperthyroidism patients was improved (International Index of Erectile Function:22.1±6.9 vs. 25.2±5.1) after the achievement of euthyroidism.The underlying mechanism of the increase in the risk of ED by overt hyperthyroidism might be correlated to the dysfunction of hypothalamus-pituitary-thyroid axis,dysregulation of sex hormones,abnormal expression of thyroid hormone receptors,and psychiatric or psychological disturbances (e.g.,depression,anxiety,and irritability).Since limited clinical trials have been conducted,additional well-designed cohorts with sizable samples are warranted to elucidate the evidence and mechanism of hyperthyroidism predisposing to ED.The present review indicates that overt hyperthyroidism and the risk of ED are associated,which reminds the clinicians should assess the thyroid stimulating hormone in hyperthyroidism patients presenting with ED,especially in those without positive conventional laboratory findings for causing ED.

Harmful cyanobacteria-diatom/dinoflagellate blooms and their cyanotoxins in freshwaters: A nonnegligible chronic health and ecological hazard.

Human and ecological health depends on the vitality of freshwater systems, but these are increasingly threatened by cyanotoxins released from harmful algal blooms (HABs). Periodic cyanotoxin production, although undesirable, may be tolerable when there is enough time for cyanotoxins to degrade and dissipate in the environment, but the year-round presence of these toxins will be a chronic health for humans and ecosystems. The purpose of this critical review is to document the seasonal shifts of algal species and their ecophysiological acclimatation to dynamic environmental conditions. We discuss how these conditions will create successive occurrences of algal blooms and the release of cyanotoxins into freshwater. We first review the most common cyanotoxins, and evaluate the multiple ecological roles and physiological functions of these toxins for algae. Then, the annual recurring patterns HABs are considered in the context of global change, which demonstrates the capacity for algal blooms to shift from seasonal to year-round growth regimes that are driven by abiotic and biotic factors, leading to chronic loading of freshwaters with cyanotoxins. At last, we illustrate the impacts of HABs on the environment by compiling four health issues and four ecology issues emanating from their presence in the that covers atmosphere, aquatic ecosystems and terrestrial ecosystems. Our study highlights the annual patterns of algal blooms, and proposes that a "perfect storm" of events is lurking that will cause the 'seasonal toxicity' to become a full-blown, 'chronic toxicity' in the context of the deterioration of HABs, highlighting a non-negligible chronic health and ecological hazard.

Type 2 Diabetes Mellitus Makes Corneal Endothelial Cells Vulnerable to Ultraviolet A-Induced Oxidative Damage Via Decreased DJ-1/Nrf2/NQO1 Pathway.

Purpose: The purpose of this study was to investigate whether type 2 diabetes mellitus (T2DM) makes corneal endothelial cells (CECs) suffer from more severe ultraviolet A (UVA)-induced oxidative damage and explore its mechanisms via measuring the oxidant level and the antioxidant level in vitro. Methods: Corneas of spontaneous T2DM db/db mice and non-diabetes littermate control mice were irradiated with UVA, leading to oxidative damage of CECs. Anterior segment-optical coherence tomography, corneal image, and CECs immunohistochemistry staining were taken thereafter to measure central corneal thickness, corneal edema degree, and damage extent of CECs. In vitro, human corneal endothelial cells line B4G12 (HCECs) treated with high glucose (HG) and low glucose (LG) were exposed to UVA light separately. Subsequently, cellular proliferation, apoptosis, pro-oxidant factors, such as reactive oxygen species (ROS), antioxidant factors including Parkinson's disease protein 7 (DJ-1), nuclear factor-erythroid 2 related factor 2 (Nrf2), phosphorylated-Nrf2, and NAD(P)H: quinone oxidoreductase 1 (NQO1) were measured. Results: T2DM mice presented greater oxidant damage of CECs and more distinct corneal edema compared with control mice when they were irradiated with the 150 J/cm2 UVA light. In vitro, HCECs in HG condition showed a significant decrease of proliferation, higher apoptosis extent, more ROS generation, lower expressions of DJ-1/Nrf2/NQO1, and distinct reduction of Nrf2 nuclear translocation compared to those in LG condition after exposing to 5 J/cm2 UVA light. Conclusions: Increase of ROS, downregulation of DJ-1/Nrf2/NQO1 expressions, and decrease of Nrf2 nuclear translocation could result in that T2DM makes CECs more vulnerable to oxidative damage.

Comprehensive Analysis of circRNA-Associated-ceRNA Networks in Human Corneal Endothelial Dysfunction.

PURPOSE: Circular RNAs (circRNAs) are a novel class of endogenous noncoding RNAs that regulate gene expression through the competitive endogenous RNA (ceRNA) mechanism. CircRNA-associated-ceRNA networks are closely related to oxidative stress-related diseases. Oxidative stress-induced dysfunction of the corneal endothelium (CE) is a major pathological feature in many corneal diseases. This study was aimed to analyze circRNA-associated-ceRNA networks in oxidative stress-induced CE dysfunction. METHODS: A CE dysfunction model was established using human corneal endothelial cells (HCECs) treated with H 2 O 2 at a concentration of 250 µM for 4 hours at 37°C. High-throughput sequencing was conducted to determine the expression profiles of circRNA, miRNA, and mRNA. Bioinformatic analyses, including Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes analysis, were conducted to identify the potential biological modules and pathologic pathways of dysregulated circRNAs. CircRNA-associated-ceRNA networks were established based on the data of sequencing and bioinformatic analyses. RESULTS: We obtained 108 differentially expressed circRNAs, including 77 upregulated and 31 downregulated circRNAs. GO analysis suggested that dysregulated circRNAs were mainly targeted to protein quality control for misfolded or incompletely synthesized proteins (biologic process), nuclear chromatin (cellular component), and ubiquitin protein ligase binding (molecular function). GO terms related to CE functions responding to oxidative stress were also identified. Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that dysregulated circRNAs were mostly enriched in the adherens junction pathway. Network analysis identified several potential therapeutic targets for CE dysfunction. CONCLUSIONS: CircRNAs are significantly dysregulated in HCECs under oxidative stress. The circRNA-associated-ceRNA networks are closely related to HCEC functions. Targeting these networks might provide novel therapies for CE dysfunction.

Revealing Physiochemical Factors and Zooplankton Influencing Microcystis Bloom Toxicity in a Large-Shallow Lake Using Bayesian Machine Learning.

Toxic cyanobacterial blooms have become a severe global hazard to human and environmental health. Most studies have focused on the relationships between cyanobacterial composition and cyanotoxins production. Yet, little is known about the environmental conditions influencing the hazard of cyanotoxins. Here, we analysed a unique 22 sites dataset comprising monthly observations of water quality, cyanobacterial genera, zooplankton assemblages, and microcystins (MCs) quota and concentrations in a large-shallow lake. Missing values of MCs were imputed using a non-negative latent factor (NLF) analysis, and the results achieved a promising accuracy. Furthermore, we used the Bayesian additive regression tree (BART) to quantify how Microcystis bloom toxicity responds to relevant physicochemical characteristics and zooplankton assemblages. As expected, the BART model achieved better performance in Microcystis biomass and MCs concentration predictions than some comparative models, including random forest and multiple linear regression. The importance analysis via BART illustrated that the shade index was overall the best predictor of MCs concentrations, implying the predominant effects of light limitations on the MCs content of Microcystis. Variables of greatest significance to the toxicity of Microcystis also included pH and dissolved inorganic nitrogen. However, total phosphorus was found to be a strong predictor of the biomass of total Microcystis and toxic M. aeruginosa. Together with the partial dependence plot, results revealed the positive correlations between protozoa and Microcystis biomass. In contrast, copepods biomass may regulate the MC quota and concentrations. Overall, our observations arouse universal demands for machine-learning strategies to represent nonlinear relationships between harmful algal blooms and environmental covariates.