Innate immune cells in tumor microenvironment: A new frontier in cancer immunotherapy.

Innate immune cells, crucial in resisting infections and initiating adaptive immunity, play diverse and significant roles in tumor development. These cells, including macrophages, granulocytes, dendritic cells (DCs), innate lymphoid cells, and innate-like T cells, are pivotal in the tumor microenvironment (TME). Innate immune cells are crucial components of the TME, based on which various immunotherapy strategies have been explored. Immunotherapy strategies, such as novel immune checkpoint inhibitors, STING/CD40 agonists, macrophage-based surface backpack anchoring, ex vivo polarization approaches, DC-based tumor vaccines, and CAR-engineered innate immune cells, aim to enhance their anti-tumor potential and counteract cancer-induced immunosuppression. The proximity of innate immune cells to tumor cells in the TME also makes them excellent drug carriers. In this review, we will first provide a systematic overview of innate immune cells within the TME and then discuss innate cell-based therapeutic strategies. Furthermore, the research obstacles and perspectives within the field will also be addressed.

Impact of transforming karst mountainous forests into urban parks on plant diversity patterns.

The conversion of urban montane forest resources into urban parks requires careful assessment to understand its impacts on plant diversity over time. This study aims to enhance urban biodiversity conservation strategies by analyzing how habitat type and park age affect woody plant diversity. We surveyed woody plant species in 60 sample plots across two different habitats (remnant forest vs. artificial green space) within three mountain parks in Guiyang, China, established at different times. The alpha diversity of saplings/seedlings was significantly higher in remnant forests than in artificial green spaces. Artificial green spaces exhibited more homogenous woody plant composition compared with remnant forests. Newer parks showed greater variation in plant composition between the two habitats than older parks. Indicative species in remnant forests were predominantly native, whereas those in artificial green spaces were mainly ornamental species. The transformation of karst mountainous forests into urban parks leads to the homogenization of woody plant composition and impedes the regeneration of saplings/seedlings. Therefore, it is crucial to manage these conversions carefully and strive to preserve as many native species as possible to support urban plant diversity conservation.

Prediction of Two-Dimensional Janus Transition-Metal Chalcogenides: Robust Ferromagnetic Semiconductor with High Curie Temperature.

Two-dimensional (2D) ferromagnetic semiconductors (FM SCs) provide an ideal platform for the development of quantum information technology in nanoscale devices. However, many developed 2D FM materials present a very low Curie temperature (TC), greatly limiting their application in spintronic devices. In this work, we predict two stable 2D transition metal chalcogenides, V3Se3X2 (X = S, Te) monolayers, by using first-principles calculations. Our results show that the V3Se3Te2 monolayer is a robust bipolar magnetic SC with a moderate bandgap of 0.53 eV, while V3Se3S2 is a direct band-gap FM SC with a bandgap of 0.59 eV. Interestingly, the ferromagnetisms of both monolayers are robust due to the V-S/Se/Te-V superexchange interaction, and TCs are about 406 K and 301 K, respectively. Applying biaxial strains, the FM SC to antiferromagnetic (AFM) SC transition is revealed at 5% and 3% of biaxial tensile strain. In addition, their high mechanical, dynamical, and thermal stabilities are further verified by phonon dispersion calculations and ab initio molecular dynamics (AIMD) calculations. Their outstanding attributes render the V3Se3Y2 (Y = S, Te) monolayers promising candidates as 2D FM SCs for a wide range of applications.

0.01% Atropine Eye Drops in Children With Myopia and Intermittent Exotropia: The AMIXT Randomized Clinical Trial.

Importance: Exotropia and myopia are commonly coexistent. However, evidence is limited regarding atropine interventions for myopia control in children with myopia and intermittent exotropia (IXT). Objective: To evaluate the efficacy and safety of 0.01% atropine eye drops on myopia progression, exotropia conditions, and binocular vision in individuals with myopia and IXT. Design, Setting, and Participants: This placebo-controlled, double-masked, randomized clinical trial was conducted from December 2020 to September 2023. Children aged 6 to 12 years with basic-type IXT and myopia of -0.50 to -6.00 diopters (D) after cycloplegic refraction in both eyes were enrolled. Intervention: Participants were randomly assigned in a 2:1 ratio to 0.01% atropine or placebo eye drops administered in both eyes once at night for 12 months. Main Outcomes and Measures: The primary outcome was change in cycloplegic spherical equivalent from baseline at 1 year. Secondary outcomes included change in axial length (AL), accommodative amplitude (AA), exotropia conditions, and binocular vision at 1 year. Results: Among 323 screened participants, 300 children (mean [SD] age, 9.1 [1.6] years; 152 male [50.7%]) were included in this study. A total of 200 children (66.7%) were in the atropine group, and 100 (33.3%) were in the placebo group. At 1 year, the 0.01% atropine group had slower spherical equivalent progression (-0.51 D vs -0.75 D; difference = 0.24 D; 95% CI, 0.11-0.37 D; P < .001) and AL elongation (0.31 mm vs 0.42 mm; difference = -0.11 mm; 95% CI, -0.17 to -0.06 mm; P < .001) than the placebo group. The mean AA change was -3.06 D vs 0.12 D (difference = -3.18 D; 95% CI, -3.92 to -2.44 D; P < .001) in the atropine and placebo groups, respectively. The 0.01% atropine group had a decrease in near magnitude of exodeviation whereas the placebo group had an increase (-1.25 prism diopters [PD] vs 0.74 PD; difference = -1.99 PD; 95% CI, -3.79 to -0.19 PD; P = .03). In the atropine vs placebo group, respectively, the incidence of study drug-related photophobia was 6.0% (12 of 200 participants) vs 8.0% (8 of 100 participants; difference = -2.0%; 95% CI, -9.4% to 3.7%; P = .51) and for blurred near vision was 6.0% (12 of 200 participants) vs 7.0% (7 of 100 participants) (difference = -1.0%; 95% CI, -8.2% to 4.5%; P = .74). Conclusions and Relevance: The findings of this randomized clinical trial support use of 0.01% atropine eye drops, although compromising AA to some extent, for slowing myopia progression without interfering with exotropia conditions or binocular vision in children with myopia and IXT. Trial Registration: Chinese Clinical Trial Registry Identifier: ChiCTR2000039827.

Exploratory analysis of injury severity under different levels of driving automation (SAE Levels 2 and 4) using multi-source data.

Vehicles equipped with automated driving capabilities have shown potential to improve safety and operations. Advanced driver assistance systems (ADAS) and automated driving systems (ADS) have been widely developed to support vehicular automation. Although the studies on the injury severity outcomes that involve automated vehicles are ongoing, there is limited research investigating the difference between injury severity outcomes for the ADAS and ADS equipped vehicles. To ensure a comprehensive analysis, a multi-source dataset that includes 1,001 ADAS crashes (SAE Level 2 vehicles) and 548 ADS crashes (SAE Level 4 vehicles) is used. Two random parameters multinomial logit models with heterogeneity in the means of random parameters are considered to gain a better understanding of the variables impacting the crash injury severity outcomes for the ADAS (SAE Level 2) and ADS (SAE Level 4) vehicles. It was found that while 67 percent of crashes involving the ADAS equipped vehicles in the dataset took place on a highway, 94 percent of crashes involving ADS took place in more urban settings. The model estimation results also reveal that the weather indicator, driver type indicator, differences in the system sophistication that are captured by both manufacture year and high/low mileage as well as rear and front contact indicators all play a role in the crash injury severity outcomes. The results offer an exploratory assessment of safety performance of the ADAS and ADS equipped vehicles using the real-world data and can be used by the manufacturers and other stakeholders to dictate the direction of their deployment and usage.

Variations in surface area and biogeochemistry of subarctic-arctic lakes established through satellite and in-situ observations: An overview of published research from the past 30 years.

Human activities have strongly impacted the global climate, and during the last few decades the global average temperature has risen at a rate faster than at any time on record. High latitude lakes in the subarctic and arctic permafrost regions have particularly been vulnerable given the "Arctic amplification" phenomenon and acceleration in warming rate in the northern hemisphere (0.2-0.8 °C/decade). This paper presents a comprehensive overview of the last 30 years of research investigating how subarctic and Arctic lakes respond to climate warming. The review focused on studies where remote sensing technology was used to quantify these responses. The difference between summer lake water temperature and air temperature varied between 1.7 and 5.4 °C in subarctic lakes and 2.4-3.2 °C in Arctic lakes. Overall, the freezing date of lake ice is generally delayed and the date of lake thawing occurs earlier. Lake surface area (4-48.5 %), and abundance in the subarctic and Arctic region have increased significantly due to rising temperature, permafrost thawing, increased precipitation and other localized surface disturbances. However, in recent years, instances of lake shrinkage (between -0.4 % and -40 %) have also been reported, likely due to riparian overflow, groundwater infiltration and lateral drainage. Furthermore, in subarctic and Arctic lakes, climate change and permafrost thawing would release CO2 and CH4, and alter carbon dynamics in impacted lakes through various interconnected processes which could potentially affect the quality of carbon (terrestrial, algae) entering a lake system. The review also highlighted a potential intersection between permafrost melting and public health through human exposure to long-buried viruses. Subarctic and arctic ecosystems' responses to climate change will continue to be an area of intense research interest, and this review has highlighted priority areas for research and how remote sensing technologies can facilitate the pursuit of such a research agenda.

Circ_0053943 complexed with IGF2BP3 drives uveal melanoma progression via regulating N6-methyladenosine modification of Epidermal growth factor receptor.

Numerous studies have characterized the critical role of circular RNAs (circRNAs) as regulatory factors in the progression of multiple cancers. However, the biological functions of circRNAs and their underlying molecular mechanisms in the progression of uveal melanoma (UM) remain enigmatic. In this study, we identified a novel circRNA, circ_0053943, through re-analysis of UM microarray data and quantitative RT-PCR. Circ_0053943 was found to be upregulated in UM and to promote the proliferation and metastatic ability of UM cells in both in vitro and in vivo settings. Mechanistically, circ_0053943 was observed to bind to the KH1 and KH2 domains of insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3), thereby enhancing the function of IGF2BP3 by stabilizing its target mRNA. RNA sequencing assays identified epidermal growth factor receptor (EGFR) as a target gene of circ_0053943 and IGF2BP3 at the transcriptional level. Rescue assays demonstrated that circ_0053943 exerts its biological function by stabilizing EGFR mRNA and regulating the downstream mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) signaling pathway. Collectively, circ_0053943 may promote UM progression by stabilizing EGFR mRNA and activating the MAPK/ERK signaling pathway through the formation of a circ_0053943/IGF2BP3/EGFR RNA-protein ternary complex, thus providing a potential biomarker and therapeutic target for UM.

Hydrogen Sulfide Splitting into Hydrogen and Sulfur through Off-Field Electrocatalysis.

Hydrogen sulfide (H2S), a toxic gas abundant in natural gas fields and refineries, is currently being removed mainly via the Claus process. However, the emission of sulfur-containing pollutants is hard to be prevented and the hydrogen element is combined to water. Herein, we report an electron-mediated off-field electrocatalysis approach (OFEC) for complete splitting of H2S into H2 and S under ambient conditions. Fe(III)/Fe(II) and V(II)/V(III) redox mediators are used to fulfill the cycles for H2S oxidation and H2 production, respectively. Fe(III) effectively removes H2S with almost 100% conversion during its oxidation process. The H+ ions are reduced by V(II) on a nonprecious metal catalyst, tungsten carbide. The mediators are regenerated in an electrolyzer at a cell voltage of 1.05 V, close to the theoretical potential difference (1.02 V) between Fe(III)/Fe(II) and V(II)/V(III). In a laboratory bench-scale plant, the energy consumption for the production of H2 from H2S is estimated to be 2.8 kWh Nm-3 H2 using Fe(III)/Fe(II) and V(II)/V(III) mediators and further reduced to about 0.5 kWh Nm-3 H2 when employing well-designed heteropolyacid/quinone mediators. OFEC presents a cost-effective approach for the simultaneous production of H2 and elemental sulfur from H2S, along with the complete removal of H2S from industrial processes. It also provides a practical platform for electrochemical reactions involving solid precipitation and organic synthesis.

Neutrophils in cancer: dual roles through intercellular interactions.

Neutrophils, the most abundant immune cells in human blood, play crucial and diverse roles in tumor development. In the tumor microenvironment (TME), cancer cells regulate the recruitment and behaviors of neutrophils, transforming some of them into a pro-tumor phenotype. Pro-tumor neutrophils interact with cancer cells in various ways to promote cancer initiation, growth, and metastasis, while anti-tumor neutrophils interact with cancer cells to induce senescence and death. Neutrophils can also interact with other cells in TME, including T cells, macrophages, stromal cells, etc. to exert anti- or pro-tumor functions. In this review, we will analyze the anti- and pro-tumor intercellular interactions mediated by neutrophils, with a focus on generalizing the mechanisms underlying the interaction of neutrophils with tumor cells and T cells. Furthermore, we will provide an overview of cancer treatment strategies targeting neutrophil-mediated cellular interactions.

Analysis of taiga and tundra lake browning trends from 2002 to 2021 using MODIS data.

Lakes in taiga and tundra regions may be silently undergoing changes due to global warming. One of those changes is browning in lake color. The browning interacts with the carbon cycle, ecosystem dynamics, and water quality in freshwater systems. However, spatiotemporal variabilities of browning in these regions have not been well documented. Using MODIS remote sensing reflectance at near ultraviolet wavelengths from 2002 to 2021 on the Google Earth Engine platform, we quantified long-term browning trends across 7616 lakes (larger than 10 km2) in taiga and tundra biomes. These lakes showed an overall decreased trend in browning (Theil-Sen Slope = 0.00015), with ∼36% of these lakes showing browning trends, and ∼1% of these lakes showing statistically significant (p-value <0.05) browning trends. The browning trends more likely occurred in small lakes in high latitude, low ground ice content regions, where air temperature increased and precipitation decreased. While temperature is projected to increase in response to climate change, our results provide one means to understand how biogeochemical cycles and ecological dynamics respond to climate change.

Causal Effects of COVID-19 on the Risk of Thrombosis: A Two-Sample Mendel Randomization Study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) and thrombosis are linked, but the biomolecular mechanism is unclear. We aimed to investigate the causal relationship between COVID-19 and thrombotic biomarkers. METHODS: We used two-sample Mendelian randomization (MR) to assess the effect of COVID-19 on 20 thrombotic biomarkers. We estimated causality using inverse variance weighting with multiplicative random effect, and performed sensitivity analysis using weighted median, MR-Egger regression and MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) methods. All the results were examined by false discovery rate (FDR) with the Benjamin and Hochberg method for this correction to minimize false positives. We used R language for the analysis. RESULTS: All COVID-19 classes showed lower levels of tissue factor pathway inhibitor (TFPI) and interleukin-1 receptor type 1 (IL-1R1). COVID-19 significantly reduced TFPI (odds ratio [OR] = 0.639, 95% confidence interval [CI]: 0.435-0.938) and IL-1R1 (OR = 0.603, 95% CI = 0.417-0.872), nearly doubling the odds. We also found that COVID-19 lowered multiple coagulation factor deficiency protein 2 and increased C-C motif chemokine 3. Hospitalized COVID-19 cases had less plasminogen activator, tissue type (tPA) and P-selectin glycoprotein ligand 1 (PSGL-1), while severe cases had higher mean platelet volume (MPV) and lower platelet count. These changes in TFPI, tPA, IL-1R1, MPV, and platelet count suggested a higher risk of thrombosis. Decreased PSGL-1 indicated a lower risk of thrombosis. CONCLUSION: TFPI, IL-1R, and seven other indicators provide causal clues of the pathogenesis of COVID-19 and thrombosis. This study demonstrated that COVID-19 causally influences thrombosis at the biomolecular level.

Bioinformatics analysis proposes a possible role for long noncoding RNA MIR17HG in retinoblastoma.

BACKGROUND: Retinoblastoma (RB) is the most common prevalent intraocular malignancy among infants and children, particularly in underdeveloped countries. With advancements in genomics and transcriptomics, noncoding RNAs have been increasingly utilized to investigate the molecular pathology of diverse diseases. AIMS: This study aims to establish the competing endogenous RNAs network associated with RB, analyse the function of mRNAs and lncRNAs, and finds the relevant regulatory network. METHODS AND RESULTS: This study establishes a network of competing endogenous RNAs by Spearman correlation analysis and prediction based on RB patients and healthy children. Enrichment analyzes based on Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes are conducted to analyze the potential biological functions of lncRNA and mRNA networks. Weighted gene co-expression network analysis (WGCNA) is employed to identify gene cluster modules exhibiting the strongest correlation with RB. The results indicate a significant correlation between the lncRNA MIR17HG (R = .73, p = .02) and the RB phenotype. ceRNA networks reveal downstream miRNAs (hsa-mir-425-5p and hsa-mir455-5p) and mRNAs (MDM2, IPO11, and ITGA1) associated with MIR17Hg. As an inhibitor of the p53 signaling pathway, MDM2 can suppress the development of RB. CONCLUSION: In conclusion, lncRNAs play a role in RB, and the MIR17HG/hsa-mir-425-5p/MDM2 pathway may contribute to RB development by inhibiting the p53 signaling pathway.

Insights into vehicle conflicts based on traffic flow dynamics.

The utilization of traffic conflict indicators is crucial for assessing traffic safety, especially when the crash data is unavailable. To identify traffic conflicts based on traffic flow characteristics across various traffic states, we propose a framework that utilizes unsupervised learning to automatically establish surrogate safety measures (SSM) thresholds. Different traffic states and corresponding transitions are identified with the three-phase traffic theory using high-resolution trajectory data. Meanwhile, the SSMs are mapped to the corresponding traffic states from the perspectives of time, space, and deceleration. Three models, including k-means, GMM, and Mclust, are investigated and compared to optimize the identification of traffic conflicts. It is observed that Mclust outperforms the others based on the evaluation metrics. According to the results, there is a variation in the distribution of traffic conflicts among different traffic states, wide moving jam (phase J) has the highest conflict risk, followed by synchronous flow (phase S), and free flow (phase F). Meanwhile, the thresholds of traffic conflicts cannot be fully represented by the same value through different traffic states. It reveals that the heterogeneity of thresholds is exhibited across traffic state transitions, which justifies the necessity of dynamic thresholds for traffic conflict analysis.

[Outcomes and measurements of randomized controlled trial for traditional Chinese medicine in treatment of endometriosis].

This study aims to analyze the outcomes and measurements of randomized controlled trial(RCT) for traditional Chinese medicine(TCM) treatment of endometriosis(EM) and provide a basis for the building of the core outcome set(COS) of EM. The RCT for TCM treatment of EM was retrieved from medical literature databases with the time interval from inception to February 3, 2022. The Cochrane risk of bias assessment tool was employed to evaluate the risk of bias of the included RCT, and descriptive analyses of the extracted information were carried out. A total of 519 RCTs were included, with the sample sizes ranging from 28-582 patients and 239 outcome indicators(8 outcome indicators per RCT on average). According to the functional properties, the reported outcome indicators were classified into 7 indicators: clinical efficacy assessment, indicators of clinical symptoms and signs, TCM symptom efficacy indicators, physical and chemical examinations, quality of life, long-term prognosis, and safety events. All the 519 RCTs had problems, such as the lack of differentiation between primary and secondary outcome indicators(1.73% RCTs reported such differen-tiation), poor quality, confused criteria for composite outcome indicators and arbitrary combination of indicators(45 criteria for the single outcome indicator of efficiency), and messy measurements(as many as 18 measurements for TCM symptom score). In addition, as a chronic disease, EM requires long-term management. The outcome indicators vary for the patients in different disease stages, such as EM pain, EM infertility, and post-operative EM, while the specific outcome indicator sets for different EM populations remain to be developed. In addition, the time point of measurement for EM long-term outcomes remains unclear, and the definition of TCM syndromes lacks standards. The RCT for TCM treatment had a variety of problems, such as the lack of differentiation of outcome indicators, confusion in criteria and measurements, lack of specific outcome indicator sets for different EM populations, and unclear time points for long-term outcomes. Therefore, the studies about COS need to be carried out urgently.

Woody plant functional traits and phylogenetic signals correlate with urbanization in remnant forest patches.

Exploring the alterations in functional traits of urban remnant vegetation offers a more comprehensive perspective on plant assembly within the context of urbanization. While plant functional traits are influenced by both environmental gradients and the evolutionary history of plant species, the specific mechanisms by which urbanization mediates the combination of functional traits and the evolutionary history of remnant vegetation remain unclear. To examine the relationship between functional traits and phylogenies of remnant vegetation and urbanization, we classified the woody plant species surveyed in 72 sample plots in nine remnant forest patches in Guiyang, China, into four groups (urban, rural, middle and general groups) according to their location under different levels of urbanization and measured nine functional traits of these species. The phylogenetic signals of each functional trait of the four species groups were then quantified based on Blomberg's K. Furthermore, we analysed the correlations between functional traits and species abundance using phylogenetic generalized least squares. The results showed that significant phylogenetic signals were detected in more functional traits of the urban group than other groups. Thirteen and three significant relationships between functional traits and species abundance were detected for tree and shrub species after removing phylogenies. Tall tree species were more abundant in the urban group, while the general group favoured the species with adaptable traits (low height and high leaf area and C/N). Overall, we demonstrate that urbanization drove shifts in plant functional traits in remnant forests after combining the phylogenetic patterns.

ChatGPT for shaping the future of dentistry: the potential of multi-modal large language model.

The ChatGPT, a lite and conversational variant of Generative Pretrained Transformer 4 (GPT-4) developed by OpenAI, is one of the milestone Large Language Models (LLMs) with billions of parameters. LLMs have stirred up much interest among researchers and practitioners in their impressive skills in natural language processing tasks, which profoundly impact various fields. This paper mainly discusses the future applications of LLMs in dentistry. We introduce two primary LLM deployment methods in dentistry, including automated dental diagnosis and cross-modal dental diagnosis, and examine their potential applications. Especially, equipped with a cross-modal encoder, a single LLM can manage multi-source data and conduct advanced natural language reasoning to perform complex clinical operations. We also present cases to demonstrate the potential of a fully automatic Multi-Modal LLM AI system for dentistry clinical application. While LLMs offer significant potential benefits, the challenges, such as data privacy, data quality, and model bias, need further study. Overall, LLMs have the potential to revolutionize dental diagnosis and treatment, which indicates a promising avenue for clinical application and research in dentistry.

Advances and applications of computer vision techniques in vehicle trajectory generation and surrogate traffic safety indicators.

The application of Computer Vision (CV) techniques massively stimulates microscopic traffic safety analysis from the perspective of traffic conflicts and near misses, which is usually measured using Surrogate Safety Measures (SSM). However, as video processing and traffic safety modeling are two separate research domains and few research have focused on systematically bridging the gap between them, it is necessary to provide transportation researchers and practitioners with corresponding guidance. With this aim in mind, this paper focuses on reviewing the applications of CV techniques in traffic safety modeling using SSM and suggesting the best way forward. The CV algorithms that are used for vehicle detection and tracking from early approaches to the state-of-the-art models are summarized at a high level. Then, the video pre-processing and post-processing techniques for vehicle trajectory extraction are introduced. A detailed review of SSMs for vehicle trajectory data along with their application on traffic safety analysis is presented. Finally, practical issues in traffic video processing and SSM-based safety analysis are discussed, and the available or potential solutions are provided. This review is expected to assist transportation researchers and engineers with the selection of suitable CV techniques for video processing, and the usage of SSMs for various traffic safety research objectives.

Prognostic values of Annexins and validation of the influence on cell proliferation, migration, and invasion in uveal melanoma.

OBJECTIVES: Uveal melanoma (UVM), the leading type of intraocular malignant tumor in adults, has an aggressive course with poor prognoses, high mortality, and lacking effective therapeutic targets and prognostic markers. Annexins are well known as dysregulated and correlated with aggressiveness and prognosis of various cancers. However, little is known about the expression pattern of Annexins in UVM and their prognostic value. This study aimed to investigate and verify the role of Annexins in the pathogenesis of metastatic UVM. METHODS: The mRNA expression of Annexins in UVM was analyzed from The Cancer Genome Atlas (TCGA) database and validated in three independent datasets (GSE22138, GSE27831, and GSE156877). The bioinformatics analysis and experimental verification of ANXA2 expression in UVM were performed to evaluate its influence on clinical prognosis, cell proliferation, migration, and invasion. RESULTS: Prognostic analysis suggested that high ANXA2/4 expression levels were significantly correlated with worse overall survival (OS), progress-free interval (PFI), and metastasis-free survival (MFS) prognoses. Meanwhile, the prognostic model (ANXA2/4) was built using the PFI-based LASSO analysis in TCGA-UVM and validated in GSE22138 and GSE27831. Multivariate Cox regression analyses indicated that the ANXA2/4 model is an independent prognostic factor associated with UVM. The expression analysis confirmed that ANXA2 was upregulated in metastatic patients. Then, ANXA2 mRNA was confirmed positive and expressed higher in four human UVM cell lines compared with ARPE19 cells, especially in two highly invasive metastatic types (C918 and MUM2B). Moreover, silencing ANXA2 blocked cell proliferation, migration, and invasion abilities of C918 and MUM2B while upregulating ANXA2 enhanced these cell functions remarkably in vitro, suggesting that ANXA2 had a positive effect on malignant biological properties of UVM cells. In addition, flow cytometry analysis showed that the knockdown of ANXA2 had a higher apoptotic rate than the control groups in C918 and MUM2B cells. ANXA2 overexpression had a lower apoptotic rate than those in the control group in OCM-1. In addition, ANXA2 expression had significant correlations with the tumor microenvironment and multiple tumor-infiltrating immune cells. CONCLUSIONS: ANXA2 is a novel potential prognostic biomarker for the metastatic diagnosis of UVM.

Fundus Tessellated Density Assessed by Deep Learning in Primary School Children.

Purpose: To explore associations of fundus tessellated density (FTD) and compare characteristics of different fundus tessellation (FT) distribution patterns, based on artificial intelligence technology using deep learning. Methods: Comprehensive ocular examinations were conducted in 577 children aged 7 years old from a population-based cross-sectional study, including biometric measurement, refraction, optical coherence tomography angiography, and 45° nonmydriatic fundus photography. FTD was defined as the average exposed choroid area per unit area of the fundus, and obtained by artificial intelligence technology. The distribution of FT was classified into the macular pattern and the peripapillary pattern according to FTD. Results: The mean FTD was 0.024 ± 0.026 in whole fundus. Multivariate regression analysis showed that greater FTD was significantly correlated with thinner subfoveal choroidal thickness, larger parapapillary atrophy, greater vessel density inside the optic disc, larger vertical diameter of optic disc, thinner retinal nerve fiber layer, and longer distance from optic disc center to macular fovea (all P < 0.05). The peripapillary distributed group had larger parapapillary atrophy (0.052 ± 0.119 vs 0.031 ± 0.072), greater FTD (0.029 ± 0.028 vs 0.015 ± 0.018), thinner subfoveal choroidal thickness (297.66 ± 60.61 vs 315.33 ± 66.46), and thinner retinal thickness (285.55 ± 10.89 vs 288.03 ± 10.31) than the macular distributed group (all P < 0.05). Conclusions: FTD can be applied as a quantitative biomarker to estimate subfoveal choroidal thickness in children. The role of blood flow inside optic disc in FT progression needs further investigation. The distribution of FT and the peripapillary pattern correlated more with myopia-related fundus changes than the macular pattern. Translational Relevance: Artificial intelligence can evaluate FT quantitatively in children, and has potential value for assisting in myopia prevention and control.

Closed-loop seizure modulation via extreme learning machine based extended state observer.

Neuromodulation is a promising way in clinical treatment of epilepsy, but the existing methods cannot adjust stimulations according to patients' real-time reactions. Therefore, it is necessary to acquire a systematic and a scientific regulation method based on patients' real-time reactions. The linear active disturbance rejection control can adapt to complex epileptic dynamics and improve the epilepsy regulation, even if little model information is available, and various uncertainties and external disturbances exist. However, a linear extended state observer estimates the time-varying total disturbance with a steady-state error. To improve regulation, it is crucial to estimate the total disturbance in a more accurate manner. An extreme learning machine is capable of approximating any nonlinear function. Its initial parameter generation is more convenient, adjustable parameters are fewer, and learning speed is faster. Thus, a nonlinear time-varying function can be estimated more timely and accurately. Then, an extreme learning machine based extended state observer is proposed to get a more satisfactory total disturbance estimation and more desired closed-loop regulation. The convergence of the extreme learning machine based extended state observer is verified and the stability of the closed-loop system is analyzed. Numerical results show that the proposed extended state observer is much better than a linear extended state observer in estimating the total disturbance. It guarantees a more satisfied closed-loop neuromodulation.