Self-Assembled and Wavelength-Tunable Quantum Dot Whispering-Gallery-Mode Lasers for Backlight Displays.

Thanks to the narrow line width and high brightness, colloidal quantum dot (CQD) lasers show promising applications in next-generation displays. However, CQD laser-based displays have yet to be demonstrated because of two challenges in integrating red, green, and blue (RGB) lasers: absorption from red CQDs deteriorates the optical gain of blue and green CQDs, and imbalanced white spectra lack blue lasing due to the high lasing threshold of blue CQDs. Herein, we introduce a facile surfactant-free self-assembly method to assemble RGB CQDs into high-quality whispering-gallery-mode (WGM) RGB lasers with close lasing thresholds among them. Moreover, these RGB lasers can lase nearly independently even when they are closely integrated, and they can construct an ultrawide color space whose color gamut is 105% of that of the BT.2020 standard. These combined strategies allow us to demonstrate the first full-color liquid crystal displays using CQD lasers as the backlight source.

Preparation of ß-Cyclodextrin Functionalized Platform for Monitoring Changes in Potassium Content in Perspiration.

The monitoring of potassium ion (K+) levels in human sweat can provide valuable insights into electrolyte balance and muscle fatigue non-invasively. However, existing laboratory techniques for sweat testing are complex, while wearable sensors face limitations like drift, fouling and interference from ions such as Na+. This work develops printed electrodes using ß-cyclodextrin functionalized reduced graphene oxide (ß-CD-RGO) for selective K+ quantification in sweat. The ß-CD prevents the aggregation of RGO sheets while also providing selective binding sites for K+ capture. Electrodes were fabricated by screen printing the ß-CD-RGO ink onto conductive carbon substrates. Material characterization confirmed the successful functionalization of RGO with ß-CD. Cyclic voltammetry (CV) showed enhanced electrochemical behavior for ß-CD-RGO-printed electrodes compared with bare carbon and RGO. Sensor optimization resulted in a formulation with 30% ß-CD-RGO loading. The printed electrodes were drop-casted with an ion-selective polyvinyl chloride (PVC) membrane. A linear range from 10 µM to 100 mM was obtained along with a sensitivity of 54.7 mV/decade. The sensor showed good reproducibility over 10 cycles in 10 mM KCl. Minimal interference from 100 mM Na+ and other common sweat constituents validated the sensor's selectivity. On-body trials were performed by mounting the printed electrodes on human subjects during exercise. The K+ levels measured in sweat were found to correlate well with serum analysis, demonstrating the sensor's ability for non-invasive electrolyte monitoring. Overall, the facile synthesis of stable ß-CD-RGO inks enables the scalable fabrication of wearable sensors for sweat potassium detection.

BIOMASS YIELD 1 regulates sorghum biomass and grain yield via the shikimate pathway.

Biomass and grain yield are key agronomic traits in sorghum (Sorghum bicolor); however, the molecular mechanisms that regulate these traits are not well understood. Here, we characterized the biomass yield 1 (by1) mutant, which displays a dramatically altered phenotype that includes reduced plant height, narrow stems, erect and narrow leaves, and abnormal floral organs. Histological analysis suggested that these phenotypic defects are mainly caused by inhibited cell elongation and abnormal floral organ development. Map-based cloning revealed that BY1 encodes a 3-deoxy-D-arabino-heptulosonate-7-phosphate synthase (DAHPS) that catalyses the first step of the shikimate pathway. BY1 was localized in chloroplasts and was ubiquitously distributed in the organs examined, particularly in the roots, stems, leaves, and panicles, which was consistent with its role in biomass production and grain yield. Transcriptome analysis and metabolic profiling revealed that BY1 was involved in primary metabolism and that it affected the biosynthesis of various secondary metabolites, especially flavonoids. Taken together, these findings demonstrate that BY1 affects biomass and grain yield in sorghum by regulating primary and secondary metabolism via the shikimate pathway. Moreover, our results provide important insights into the relationship between plant development and metabolism.

Convergent degeneration of olfactory receptor gene repertoires in marine mammals.

BACKGROUND: Olfactory receptors (ORs) can bind odor molecules and play a crucial role in odor sensation. Due to the frequent gains and losses of genes during evolution, the number of OR members varies greatly among different species. However, whether the extent of gene gains/losses varies between marine mammals and related terrestrial mammals has not been clarified, and the factors that might underlie these variations are unknown. RESULTS: To address these questions, we identified more than 10,000 members of the OR family in 23 mammals and classified them into 830 orthologous gene groups (OGGs) and 281 singletons. Significant differences occurred in the number of OR repertoires and OGGs among different species. We found that all marine mammals had fewer OR genes than their related terrestrial lineages, with the fewest OR genes found in cetaceans, which may be closely related to olfactory degradation. ORs with more gene duplications or loss events tended to be under weaker purifying selection. The average gain and loss rates of OR genes in terrestrial mammals were higher than those of mammalian gene families, while the average gain and loss rates of OR genes in marine mammals were significantly lower and much higher than those of mammalian gene families, respectively. Additionally, we failed to detect any one-to-one orthologous genes in the focal species, suggesting that OR genes are not well conserved among marine mammals. CONCLUSIONS: Marine mammals have experienced large numbers of OR gene losses compared with their related terrestrial lineages, which may result from the frequent birth-and-death evolution under varied functional constrains. Due to their independent degeneration, OR genes present in each lineage are not well conserved among marine mammals. Our study provides a basis for future research on the olfactory receptor function in mammals from the perspective of evolutionary trajectories.

ZmGA3ox2, a candidate gene for a major QTL, qPH3.1, for plant height in maize.

Maize plant height is closely associated with biomass, lodging resistance and grain yield. Determining the genetic basis of plant height by characterizing and cloning plant height genes will guide the genetic improvement of crops. In this study, a quantitative trait locus (QTL) for plant height, qPH3.1, was identified on chromosome 3 using populations derived from a cross between Zong3 and its chromosome segment substitution line, SL15. The plant height of the two lines was obviously different, and application of exogenous gibberellin A(3) removed this difference. QTL mapping placed qPH3.1 within a 4.0 cM interval, explaining 32.3% of the phenotypic variance. Furthermore, eight homozygous segmental isolines (SILs) developed from two larger F(2) populations further narrowed down qPH3.1 to within a 12.6 kb interval. ZmGA3ox2, an ortholog of OsGA3ox2, which encodes a GA3 ß-hydroxylase, was positionally cloned. Association mapping identified two polymorphisms in ZmGA3ox2 that were significantly associated with plant height across two experiments. Quantitative RT-PCR showed that SL15 had higher ZmGA3ox2 expression relative to Zong3. The resultant higher GA(1) accumulation led to longer internodes in SL15 because of increased cell lengths. Moreover, a large deletion in the coding region of ZmGA3ox2 is responsible for the dwarf mutant d1-6016. The successfully isolated qPH3.1 enriches our knowledge on the genetic basis of plant height in maize, and provides an opportunity for improvement of plant architecture in maize breeding.

[Effect of parent training in combination with methylphenidate treatment on family relationships for children with attention deficit/hyperactivity disorder].

OBJECTIVE: To investigate the effect of parent training combined with methylphenidate treatment on family relationships in children with attention deficit/hyperactivity disorder (ADHD). METHODS: Fifty-nine parents of children with ADHD under methylphenidate treatment participated in a modified 5-week training program. The intervention effect was evaluated using the Conners Parent Symptom Questionnaire, ADHD Rating Scale-IV Home Version (ADHD-RS-IV Home Version), Caregiver Strain Questionnaire, Parent-Child Relationship Self-rating Scale and Piers-Harris Children's Self-Concept Scale. Parents also completed the training satisfaction survey before and after the intervention. RESULTS: After the 5-week parent training, compared with the baseline values, total scores of Conners Parent Symptom Questionnaire and scores of conduct problems and anxiety significantly decreased, and scores of attention deficit, hyperactivity, impulsivity and oppositional defiant behaviors of ADHD-RS-IV Home Version, and Caregiver Strain Questionnaire total scores were all significantly decreased (P<0.05), while total scores of the Parent-Child Relationship Self-Rating Scale and Piers-Harris Children's Self-Concept Scale were significantly increased (P<0.05). CONCLUSIONS: Modified 5-week parent training program may improve parent-child relationship and reduce parenting stress in ADHD families.

Enhanced Spin Polarization from Biaxially Strained Colloidal Quantum Dots.

Electron and hole spin polarization is crucial for quantum dots to be used in spin lasers and quantum information processing. However, the degree of spin polarization in II-VI and III-V semiconductor quantum dots is low because of the degenerated valence band. Here, we increase the light and heavy hole degeneracy by introducing biaxial strain into CdSe-based quantum dots, enabling the degree of spin polarization to be increased from 20% to 50% under photoexcitation. The optical gain threshold measurement further reveals that the increase in polarization helps to reduce the gain threshold.

ERTNet: an interpretable transformer-based framework for EEG emotion recognition.

Background: Emotion recognition using EEG signals enables clinicians to assess patients' emotional states with precision and immediacy. However, the complexity of EEG signal data poses challenges for traditional recognition methods. Deep learning techniques effectively capture the nuanced emotional cues within these signals by leveraging extensive data. Nonetheless, most deep learning techniques lack interpretability while maintaining accuracy. Methods: We developed an interpretable end-to-end EEG emotion recognition framework rooted in the hybrid CNN and transformer architecture. Specifically, temporal convolution isolates salient information from EEG signals while filtering out potential high-frequency noise. Spatial convolution discerns the topological connections between channels. Subsequently, the transformer module processes the feature maps to integrate high-level spatiotemporal features, enabling the identification of the prevailing emotional state. Results: Experiments' results demonstrated that our model excels in diverse emotion classification, achieving an accuracy of 74.23% ± 2.59% on the dimensional model (DEAP) and 67.17% ± 1.70% on the discrete model (SEED-V). These results surpass the performances of both CNN and LSTM-based counterparts. Through interpretive analysis, we ascertained that the beta and gamma bands in the EEG signals exert the most significant impact on emotion recognition performance. Notably, our model can independently tailor a Gaussian-like convolution kernel, effectively filtering high-frequency noise from the input EEG data. Discussion: Given its robust performance and interpretative capabilities, our proposed framework is a promising tool for EEG-driven emotion brain-computer interface.

Application of LightGBM hybrid model based on TPE algorithm optimization in sleep apnea detection.

Introduction: Sleep apnoea syndrome (SAS) is a serious sleep disorder and early detection of sleep apnoea not only reduces treatment costs but also saves lives. Conventional polysomnography (PSG) is widely regarded as the gold standard diagnostic tool for sleep apnoea. However, this method is expensive, time-consuming and inherently disruptive to sleep. Recent studies have pointed out that ECG analysis is a simple and effective diagnostic method for sleep apnea, which can effectively provide physicians with an aid to diagnosis and reduce patients' suffering. Methods: To this end, in this paper proposes a LightGBM hybrid model based on ECG signals for efficient detection of sleep apnea. Firstly, the improved Isolated Forest algorithm is introduced to remove abnormal data and solve the data sample imbalance problem. Secondly, the parameters of LightGBM algorithm are optimised by the improved TPE (Tree-structured Parzen Estimator) algorithm to determine the best parameter configuration of the model. Finally, the fusion model TPE_OptGBM is used to detect sleep apnoea. In the experimental phase, we validated the model based on the sleep apnoea ECG database provided by Phillips-University of Marburg, Germany. Results: The experimental results show that the model proposed in this paper achieves an accuracy of 95.08%, a precision of 94.80%, a recall of 97.51%, and an F1 value of 96.14%. Discussion: All of these evaluation indicators are better than the current mainstream models, which is expected to assist the doctor's diagnostic process and provide a better medical experience for patients.

[Influential factors for methylphenidate treatment compliance in children with attention deficit hyperactivity disorder].

OBJECTIVE: To investigate influential factors for the tendency to medicate and medication compliance in children with attention deficit hyperactivity disorder (ADHD). METHODS: A total of 188 children aged from 5 to 16 years, who were initially diagnosed with ADHD according to DSM-IV criteria, were included in the study. They underwent symptom assessment and cognitive function test. The compliance of methylphenidate treatment was evaluated. RESULTS: Patients with better emotional state, and fewer oppositional and hyperactive behaviors and those who had a family history of psychiatric diseases and who obtained lower scores in the number cancellation test (NCT), were more prone to medication and/or exhibited better medication compliance. Logistic regression analysis showed that fewer oppositional and hyperactive behaviors and lower NCT scores were the predictive factors for a higher tendency to medicate, and a better emotional state was the predictive factor for better medication compliance. Patients of predominantly inattentive type were more prone to medication and showed better medication compliance, as compared with those of combined type. Gender, age and symptom severity were not associated with the tendency to medicate and/or medication compliance. CONCLUSIONS: There is a need to enhance medication compliance in children with ADHD who have hyperactive, impulsive and oppositional behaviors, and to improve their long-term social functions.

[Study on attention-deficit hyperactivity disorder in children based on resting-state functional magnetic resonance imaging].

OBJECTIVE: To compare resting-state functional magnetic resonance imaging (fMRI) findings of children with attention-deficit hyperactivity disorder (ADHD) and normal children, and to investigate the possible mechanism of brain dysfunction in children with ADHD. METHODS: Resting-state fMRI was performed on 18 children who met the DSM-IV diagnostic criteria for ADHD (ADHD group) and 18 normal children (control group) matched for age, sex, IQ, degree of education and handedness. The two groups were compared in terms of amplitude of low frequency fluctuation (ALFF) and regional homogeneity (ReHo). RESULTS: Compared with the control group, the ADHD group had decreased ALFF in the bilateral posterior lobes of the cerebellum and the left side of the pons, increased ALFF in the right precentral gyrus, decreased ReHo in the left medial frontal gyrus, right superior frontal gyrus, and left precuneus, and increased ReHo in the left anterior lobe of the cerebellum, left caudate nucleus, right parahippocampal gyrus, left precentral gyrus, and right middle frontal gyrus. CONCLUSIONS: In resting state, children with ADHD have decreased brain activity in some regions, including the cerebellum and frontal cortex, compared with normal children, which supports the hypothesis of dysfunctional fronto-cerebellar circuits in ADHD.

Development of a travel recommendation algorithm based on multi-modal and multi-vector data mining.

Given the rise of the tourism industry, there is an increasing urgency among tourists to access information about various tourist attractions. To address this challenge, innovative solutions have emerged, utilizing recommendation algorithms to offer customers personalized product recommendations. Nonetheless, existing recommendation algorithms predominantly rely on textual data, which is insufficient to harness the full potential of online tourism data. The most valuable tourism information is often found in the multi-modal data on social media, characterized by its voluminous and content-rich nature. Against this backdrop, our article posits a groundbreaking travel recommendation algorithm that leverages multi-modal data mining techniques. The proposed algorithm uses a travel recommendation platform, designed using multi-vector word sense segmentation and multi-modal data fusion, to improve the recommendation performance by introducing topic words. In our final experimental comparison, we verify the recommendation performance of the proposed algorithm on the real data set of TripAdvisor. Our proposed algorithm has the best degree of confusion with various topics. With a LOP of 20, the Precision and MAP values reach 0.0026 and 0.0089, respectively. It has the potential to better serve the tourism industry in terms of tourist destination recommendations. It can effectively mine the multi-modal data of the tourism industry to generate more excellent economic and social value.

Automatic Penaeus Monodon Larvae Counting via Equal Keypoint Regression with Smartphones.

Today, large-scale Penaeus monodon farms no longer incubate eggs but instead purchase larvae from large-scale hatcheries for rearing. The accurate counting of tens of thousands of larvae in these transactions is a challenging task due to the small size of the larvae and the highly congested scenes. To address this issue, we present the Penaeus Larvae Counting Strategy (PLCS), a simple and efficient method for counting Penaeus monodon larvae that only requires a smartphone to capture images without the need for any additional equipment. Our approach treats two different types of keypoints as equip keypoints based on keypoint regression to determine the number of shrimp larvae in the image. We constructed a high-resolution image dataset named Penaeus_1k using images captured by five smartphones. This dataset contains 1420 images of Penaeus monodon larvae and includes general annotations for three keypoints, making it suitable for density map counting, keypoint regression, and other methods. The effectiveness of the proposed method was evaluated on a real Penaeus monodon larvae dataset. The average accuracy of 720 images with seven different density groups in the test dataset was 93.79%, outperforming the classical density map algorithm and demonstrating the efficacy of the PLCS.

High risks adverse events associated with trastuzumab emtansine and trastuzumab deruxtecan for the treatment of HER2-positive/mutated malignancies: a pharmacovigilance study based on the FAERS database.

BACKGROUND: T-DM1 and T-DXd are two promising antibody-drug conjugates for treating advanced HER2-positive breast cancer and HER2-mutated lung cancer. Understanding the differences in the adverse events (AEs) profile of both drugs may help clinicians make an appropriate treatment decision. RESEARCH DESIGN AND METHODS: All data obtained from the FDA Adverse Event Reporting System (FAERS) database from Q1 2004 to Q3 2022 underwent disproportionality analysis and Bayesian analysis to detect and assess the AE signals of T-DM1 and T-DXd for comparison. RESULTS: A total of 2,113 and 1,269 AE reports associated with T-DM1 and T-Dxd, respectively, were retrieved from FAERS database, in which, respondents were mostly elderly women. Their statistical differences (p < 0.001), poses high incidence of thrombocytopenia, including cardiotoxicity (p < 0.05) for T-DM1, while myelosuppression, interstitial lung disease (ILD), and pneumonitis for T-DXd. Splenomegaly, nodular regenerative hyperplasia, hepatic cirrhosis, portal hypertension, neuropathy peripheral, and spider nevus, are particular to T-DM1. Similarly, febrile neutropenia, pneumocystis jirovecii pneumonia, neutrophil count decreased, and KL-6 increased, are unique to T-DXd. CONCLUSIONS: T-DXd is more likely to induce ILD/pneumonia and myelosuppression than T-DM1, whereas T-DM1 has higher risk of hepatotoxicity, cardiotoxicity, and thrombocytopenia than T-DXd. T-DM1-related hepatotoxicity may need redefinition. Clinicians may need to balance the benefits and risks of antibody-drug conjugates treatment for certain patients.

Improved HHT-microstate analysis of EEG in nicotine addicts.

Background: Substance addiction is a chronic disease which causes great harm to modern society and individuals. At present, many studies have applied EEG analysis methods to the substance addiction detection and treatment. As a tool to describe the spatio-temporal dynamic characteristics of large-scale electrophysiological data, EEG microstate analysis has been widely used, which is an effective method to study the relationship between EEG electrodynamics and cognition or disease. Methods: To study the difference of EEG microstate parameters of nicotine addicts at each frequency band, we combine an improved Hilbert Huang Transformation (HHT) decomposition with microstate analysis, which is applied to the EEG of nicotine addicts. Results: After using improved HHT-Microstate method, we notice that there is significant difference in EEG microstates of nicotine addicts between viewing smoke pictures group (smoke) and viewing neutral pictures group (neutral). Firstly, there is a significant difference in EEG microstates at full-frequency band between smoke and neutral group. Compared with the FIR-Microstate method, the similarity index of microstate topographic maps at alpha and beta bands had significant differences between smoke and neutral group. Secondly, we find significant class × group interactions for microstate parameters at delta, alpha and beta bands. Finally, the microstate parameters at delta, alpha and beta bands obtained by the improved HHT-microstate analysis method are selected as features for classification and detection under the Gaussian kernel support vector machine. The highest accuracy is 92% sensitivity is 94% and specificity is 91%, which can more effectively detect and identify addiction diseases than FIR-Microstate and FIR-Riemann methods. Conclusion: Thus, the improved HHT-Microstate analysis method can effectively identify substance addiction diseases and provide new ideas and insights for the brain research of nicotine addiction.

Evaluating the Genetic Background Effect on Dissecting the Genetic Basis of Kernel Traits in Reciprocal Maize Introgression Lines.

Maize yield is mostly determined by its grain size. Although numerous quantitative trait loci (QTL) have been identified for kernel-related traits, the application of these QTL in breeding programs has been strongly hindered because the populations used for QTL mapping are often different from breeding populations. However, the effect of genetic background on the efficiency of QTL and the accuracy of trait genomic prediction has not been fully studied. Here, we used a set of reciprocal introgression lines (ILs) derived from 417F × 517F to evaluate how genetic background affects the detection of QTLassociated with kernel shape traits. A total of 51 QTL for kernel size were identified by chromosome segment lines (CSL) and genome-wide association studies (GWAS) methods. These were subsequently clustered into 13 common QTL based on their physical position, including 7 genetic-background-independent and 6 genetic-background-dependent QTL, respectively. Additionally, different digenic epistatic marker pairs were identified in the 417F and 517F ILs. Therefore, our results demonstrated that genetic background strongly affected not only the kernel size QTL mapping via CSL and GWAS but also the genomic prediction accuracy and epistatic detection, thereby enhancing our understanding of how genetic background affects the genetic dissection of grain size-related traits.

ZmBSK1 positively regulates BR-induced H2O2 production via NADPH oxidase and functions in oxidative stress tolerance in maize.

Brassinosteroid (BR) has been indicated to induce the production of hydrogen peroxide (H2O2) in plants in response to various environmental stimuli. However, it remains largely unknown how BR induces H2O2 production. In this study, we found that BR treatment significantly raised the kinase activity of maize (Zea mays L.) brassinosteroid-signaling kinase 1 (ZmBSK1) using the immunoprecipitation kinase assay. ZmBSK1 could modulate the gene expressions and activities of nicotinamide adenine dinucleotide phosphate (NADPH) oxidases (EC 1.6.3.1) to modulate BR-induced H2O2 production. BR could enhance the interaction between ZmBSK1 and maize calcium/calmodulin-dependent protein kinase (ZmCCaMK), a previously identified substrate of ZmBSK1. The BR-induced phosphorylation and kinase activity of ZmCCaMK are dependent on ZmBSK1. Moreover, we showed that ZmBSK1 regulated the NADPH oxidase gene expression and activity via directly phosphorylating ZmCCaMK. Genetic analysis suggested that ZmBSK1-ZmCCaMK module strengthened plant tolerance to oxidative stress induced by exogenous application of H2O2 through improving the activities of antioxidant defense enzyme and alleviating the malondialdehyde (MDA) accumulation and electrolyte leakage rate. In conclusion, these findings provide the new insights of ZmBSK1 functioning in BR-induced H2O2 production and the theoretical supports for breeding stress-tolerant crops.

Enhanced emission directivity from asymmetrically strained colloidal quantum dots.

Current state-of-the-art quantum dot light-emitting diodes have reached close to unity internal quantum efficiency. Further improvement in external quantum efficiency requires more efficient photon out-coupling. Improving the directivity of the photon emission is considered to be the most feasible approach. Here, we report improved emission directivity from colloidal quantum dot films. By growing an asymmetric compressive shell, we are able to lift their band-edge state degeneracy, which leads to an overwhelming population of exciton with in-plane dipole moment, as desired for high-efficiency photon out-coupling. The in-plane dipole proportion determined by back-focal plane imaging method is 88%, remarkably higher than 70% obtained from conventional hydrostatically strained colloidal quantum dots. Enhanced emission directivity obtained here opens a path to increasing the external quantum efficiencies notably.

Plant growth-promoting effect and genomic analysis of the P. putida LWPZF isolated from C. japonicum rhizosphere.

Plant growth-promoting rhizobacteria are a type of beneficial bacteria which inhabit in the rhizosphere and possess the abilities to promote plant growth. Pseudomonas putida LWPZF is a plant growth-promoting bacterium isolated from the rhizosphere soil of Cercidiphyllum japonicum. Inoculation treatment with LWPZF could significantly promote the growth of C. japonicum seedlings. P. putida LWPZF has a variety of plant growth-promoting properties, including the ability to solubilize phosphate, synthesize ACC deaminase and IAA. The P. putida LWPZF genome contained a circular chromosome (6,259,530 bp) and a circular plasmid (160,969 bp) with G+C contents of 61.75% and 58.25%, respectively. There were 5632 and 169 predicted protein-coding sequences (CDSs) on the chromosome and the plasmid respectively. Genome sequence analysis revealed lots of genes associated with biosynthesis of IAA, pyoverdine, ACC deaminase, trehalose, volatiles acetoin and 2,3-butanediol, 4-hydroxybenzoate, as well as gluconic acid contributing phosphate solubilization. Additionally, we identified many heavy metal resistance genes, including arsenate, copper, chromate, cobalt-zinc-cadmium, and mercury. These results suggest that P. putida LWPZF shows strong potential in the fields of biofertilizer, biocontrol and heavy metal contamination soil remediation. The data presented in this study will allow us to better understand the mechanisms of plant growth promotion, biocontrol, and anti-heavy metal of P. putida LWPZF.

Ocular adverse events associated with anti-VEGF therapy: A pharmacovigilance study of the FDA adverse event reporting system (FAERS).

Background: The purpose of this study is to identify and characterize ocular adverse events (AEs) that are significantly associated with anti-VEGF drugs for treatment of neovascular age-related macular degeneration and compare the differences between each drug, and provide clinical reference. Methods: Ocular AEs submitted to the US Food and Drug Administration were analyzed to map the safety profile of anti-VEGF drugs. The Pharmacovigilance tools used for the quantitative detection of signals were reporting odds ratio and bayesian confidence propagation neural network. Results: A total of 10,608,503 AE reports were retrieved from FAERS, with 20,836 for ranibizumab, 19,107 for aflibercept, and 2,442 for brolucizumab between the reporting period of Q1, 2004 and Q3, 2021. We found and analyzed the different AEs with the strongest signal in each drug-ranibizumab-macular ischaemia (ROR = 205.27, IC-2SD = 3.70), retinal pigment epithelial tear (ROR = 836.54, IC-2SD = 7.19); aflibercept-intraocular pressure increased (ROR = 31.09, IC-2SD = 4.61), endophthalmitis (ROR = 178.27, IC-2SD = 6.70); brolucizumab-retinal vasculitis (ROR = 2930.41, IC-2SD = 7.47) and/or retinal artery occlusion (ROR = 391.11, IC-2SD = 6.10), dry eye (ROR = 12.48, IC-2SD = 2.88). Conclusion: The presence of AEs should bring clinical attention. The use of anti-VEGF drugs should be based on the patient's underlying or present medical condition to reduce any adverse event associated with the treatment.