Lattice Oxygen Activation through Deep Oxidation of Co4N by Jahn-Teller-active Dopants for Improved Electrocatalytic Oxygen Evolution.

Triggering the lattice oxygen oxidation mechanism is crucial for improving oxygen evolution reaction (OER) performance, because it could bypass the scaling relation limitation associated with the conventional adsorbate evolution mechanism through the directly formation of oxygen-oxygen bond. High-valence transition metal sites are favorable for activating the lattice oxygen, but the deep oxidation of pre-catalysts suffers from a high thermodynamic barrier. Here, taking advantage of the Jahn-Teller (J-T) distortion induced structural instability, we incorporate high-spin Mn3+ (t2g3eg1) dopant into Co4N. Mn dopants enable a surface structural transformation from Co4N to CoOOH, and finally to CoO2, as observed by various in-situ spectroscopic investigations. Furthermore, the reconstructed surface on Mn doped Co4N triggers the lattice oxygen activation, as evidenced experimentally by pH-dependent OER, tetramethylammonium cation adsorption and on-line electrochemical mass spectrometry measurements of 18O-labelled catalysts. In general, this work not only offers the introducing J-T effect approach to regulate the structural transition, but also provides an understanding about the influence of catalyst's electronic configuration on determining the reaction route, which may inspire the design of more efficient catalysts with activated lattice oxygen.

Correction: Establishment of a prediction model for prehospital return of spontaneous circulation in out-of-hospital patients with cardiac arrest.

[This corrects the article on p. 508 in vol. 15, PMID: 37900904.].

Deep Learning-Based Design Method for Acoustic Metasurface Dual-Feature Fusion.

Existing research in metasurface design was based on trial-and-error high-intensity iterations and requires deep acoustic expertise from the researcher, which severely hampered the development of the metasurface field. Using deep learning enabled the fast and accurate design of hypersurfaces. Based on this, in this paper, an integrated learning approach was first utilized to construct a model of the forward mapping relationship between the hypersurface physical structure parameters and the acoustic field, which was intended to be used for data enhancement. Then a dual-feature fusion model (DFCNN) based on a convolutional neural network was proposed, in which the first feature was the high-dimensional nonlinear features extracted using a data-driven approach, and the second feature was the physical feature information of the acoustic field mined using the model. A convolutional neural network was used for feature fusion. A genetic algorithm was used for network parameter optimization. Finally, generalization ability verification was performed to prove the validity of the network model. The results showed that 90% of the integrated learning models had an error of less than 3 dB between the real and predicted sound field data, and 93% of the DFCNN models could achieve an error of less than 5 dB in the local sound field intensity.

DGPRI, a new liver fibrosis assessment index, predicts recurrence of AFP-negative hepatocellular carcinoma after hepatic resection: a single-center retrospective study.

Although patients with alpha-fetoprotein-negative hepatocellular carcinoma (AFPNHCC) have a favorable prognosis, a high risk of postoperative recurrence remains. We developed and validated a novel liver fibrosis assessment index, the direct bilirubin-gamma-glutamyl transpeptidase-to-platelet ratio (DGPRI). DGPRI was calculated for each of the 378 patients with AFPNHCC who underwent hepatic resection. The patients were divided into high- and low-score groups using the optimal cutoff value. The Lasso-Cox method was used to identify the characteristics of postoperative recurrence, followed by multivariate Cox regression analysis to determine the independent risk factors associated with recurrence. A nomogram model incorporating the DGPRI was developed and validated. High DGPRI was identified as an independent risk factor (hazard ratio = 2.086) for postoperative recurrence in patients with AFPNHCC. DGPRI exhibited better predictive ability for recurrence 1-5 years after surgery than direct bilirubin and the gamma-glutamyl transpeptidase-to-platelet ratio. The DGPRI-nomogram model demonstrated good predictive ability, with a C-index of 0.674 (95% CI 0.621-0.727). The calibration curves and clinical decision analysis demonstrated its clinical utility. The DGPRI nomogram model performed better than the TNM and BCLC staging systems for predicting recurrence-free survival. DGPRI is a novel and effective predictor of postoperative recurrence in patients with AFPNHCC and provides a superior assessment of preoperative liver fibrosis.

Construction and Validation of a Nomogram to Predict the Postoperative Venous Thromboembolism Risk in Patients with HGSOC.

Venous thromboembolism (VTE) is a common complication in patients with high-grade serous ovarian cancer (HGSOC) after surgery. This study aims to establish a comprehensive risk assessment model to better identify the potential risk of postoperative VTE in HGSOC. Clinical data from 587 HGSOC patients who underwent surgical treatment were retrospectively collected. Univariate and multivariate logistic regression analyses were performed to identify independent factors influencing the occurrence of postoperative VTE in HGSOC. A nomogram model was constructed in the training set and further validated in the verification set. Logistic regression identified age (odds ratio [OR] = 1.063, P = .002), tumor size (OR = 3.815, P < .001), postoperative transfusion (OR = 5.646, P = .001), and postoperative D-dimer (OR = 1.246, P = .003) as independent risk factors for postoperative VTE in HGSOC patients. A nomogram was constructed using these factors. The receiver operating characteristic curve showed an area under the curve (AUC) of 0.840 (95% confidence interval [CI]: 0.782, 0.898) in the training set and 0.793 (95% CI: 0.704, 0.882) in the validation set. The calibration curve demonstrated a good consistency between model predictions and actual results. The decision curve analysis indicated the model benefits at a threshold probability of less than 70%. A nomogram predicting postoperative VTE in HGSOC was established and validated. This model will assist clinicians in the early identification of high-risk patients, enabling the implementation of appropriate preventive measures.

Photo-thermal synergistic CO2 hydrogenation towards CO over PtRh bimetal-decorated GaN nanowires/Si.

Photo-thermal-synergistic hydrogenation is a promising strategy for upcycling carbon dioxide into fuels and chemicals by maximally utilizing full-spectrum solar energy. Herein, by immobilizing Pt-Rh bimetal onto a well-developed GaN NWs/Si platform, CO2 was photo-thermo-catalytically hydrogenated towards CO under concentrated light illumination without extra energies. The as-designed architecture demonstrates a considerable CO evolution rate of 11.7 mol gGaN-1 h-1 with a high selectivity of 98.5% under concentrated light illumination of 5.3 W cm-2, leading to a benchmark turnover frequency of 26 486 mol CO per mol PtRh per hour. It is nearly 2-3 orders of magnitude higher than that of pure thermal catalysis under the same temperature by external heating without light. Control experiments, various spectroscopic characterization methods, and density functional theory calculations are correlatively conducted to reveal the origin of the remarkable performance as well as the photo-thermal enhanced mechanism. It is found that the recombination of photogenerated electron-hole pairs is dramatically inhibited under high temperatures arising from the photothermal effect. More critically, the synergy between photogenerated carriers arising from ultraviolet light and photoinduced heat arising from visible- and infrared light enables a sharp reduction of the apparent activation barrier of CO2 hydrogenation from 2.09 downward to 1.18 eV. The evolution pathway of CO2 hydrogenation towards CO is also disclosed at the molecular level. Furthermore, compared to monometallic Pt, the introduction of Rh further reduces the desorption energy barrier of *CO by optimizing the electronic properties of Pt, thus enabling the achievement of excellent activity and selectivity. This work provides new insights into CO2 hydrogenation by maximally utilizing full-spectrum sunlight via photo-thermal synergy.

Personalized prediction of postoperative complication and survival among Colorectal Liver Metastases Patients Receiving Simultaneous Resection using machine learning approaches: A multi-center study.

BACKGROUND: To predict clinical important outcomes for colorectal liver metastases (CRLM) patients receiving colorectal resection with simultaneous liver resection by integrating demographic, clinical, laboratory, and genetic data. METHODS: Random forest (RF) models were developed to predict postoperative complications and major complications (binary outcomes), as well as progression-free survival (PFS) and overall survival (OS) (time-to-event outcomes) of the CRLM patients based on data from two hospitals. The models were validated on an external dataset from an independent hospital. The clinical utility of the models was assessed via decision curve analyses (DCA). RESULTS: There were 1067 patients included in survival prediction analyses and 1070 patients included in postoperative complication prediction analyses. The RF models provided an assessment of the model contributions of features for outcomes and suggested KRAS, BRAF, and MMR status were salient for the PFS or OS predictions. RF model of PFS showed that the Brier scores at 1-, 3-, and 5-year PFS were 0.213, 0.202 and 0.188; and the AUCs of 1-, 3- and 5-year PFS were 0.702, 0.720 and 0.743. RF model of OS revealed that Brier scores of 1-,3-, and 5-year OS were 0.040, 0.183 and 0.211; and the AUCs of 1-, 3- and 5-year OS were 0.737, 0.706 and 0.719. RF model for postoperative complication resulted in an AUC of 0.716 and a Brier score of 0.196. DCA curves clearly demonstrated that the RF models for these outcomes exhibited a superior net benefit across a wide range of threshold probabilities, signifying their favorable clinical utility. The RF models consistently exhibited robust performance in both internal cross-validation and external validation. The individualized risk profile predicted by the models closely aligned with the actual survival outcomes observed for the patients. A web-based tool (https://kanli.shinyapps.io/CRLMRF/) was provided to demonstrate the practical use of the prediction models for new patients in the clinical setting. CONCLUSION: The predictive models and a web-based tool for personalized prediction demonstrated a moderate predictive performance and favorable clinical utilities on several key clinical outcomes of CRLM patients receiving simultaneous resection, which could facilitate the clinical decision-making and inform future interventions for CRLM patients.

Metallofullerenol alleviates alcoholic liver damage via ROS clearance under static magnetic and electric fields.

Alcoholic liver disease (ALD) is a common chronic redox disease caused by increased alcohol consumption. Abstinence is a major challenge for people with alcohol dependence, and approved drugs have limited efficacy. Therefore, this study aimed to explore a new treatment strategy for ALD using ferroferric oxide endohedral fullerenol (Fe3O4@C60(OH)n) in combination with static magnetic and electric fields (sBE). The primary hepatocytes of 8-9-week-old female BALB/c mice were used to evaluate the efficacy of the proposed combination treatment. A mouse chronic binge ethanol feeding model was established to determine the alleviatory effect of Fe3O4@C60(OH)n on liver injury under sBE exposure. Furthermore, the ability of Fe3O4@C60(OH)n to eliminate •OH was evaluated. Alcohol-induced hepatocyte and mitochondrial damage were reversed in vitro. Additionally, the combination therapy reduced liver damage, alleviated oxidative stress by improving antioxidant levels, and effectively inhibited liver lipid accumulation in animal experiments. Here, we used a combination of magnetic derivatives of fullerenol and sBE to further improve the ROS clearance rate, thereby alleviating ALD. The developed combination treatment may effectively improve alcohol-induced liver damage and maintain redox balance without apparent toxicity, thereby enhancing therapy aimed at ALD and other redox diseases.

Research on carbon dioxide capture materials used for carbon dioxide capture, utilization, and storage technology: a review.

In recent years, climate change has increasingly become one of the major challenges facing mankind today, seriously threatening the survival and sustainable development of mankind. Dramatically increasing carbon dioxide concentrations are thought to cause a severe greenhouse effect, leading to severe and sustained global warming, associated climate instability and unwelcome natural disasters, melting glaciers and extreme weather patterns. The treatment of flue gas from thermal power plants uses carbon capture, utilization, and storage (CCUS) technology, one of the most promising current methods to accomplish significant CO2 emission reduction. In order to implement the technological and financial system of CO2 capture, which is the key technology of CCUS technology and accounts for 70-80% of the overall cost of CCUS technology, it is crucial to create more effective adsorbents. Nowadays, with the development and application of various carbon dioxide capture materials, it is necessary to review and summarize carbon dioxide capture materials in time. In this paper, the main technologies of CO2 capture are reviewed, with emphasis on the latest research status of CO2 capture materials, such as amines, zeolites, alkali metals, as well as emerging MOFs and carbon nanomaterials. More and more research on CO2 capture materials has used a variety of improved methods, which have achieved high CO2 capture performance. For example, doping of layered double hydroxides (LDH) with metal atoms significantly increases the active site on the surface of the material, which has a significant impact on improving the CO2 capture capacity and performance stability of LDH. Although many carbon capture materials have been developed, high cost and low technology scale remain major obstacles to CO2 capture. Future research should focus on designing low-cost, high-availability carbon capture materials.

Weakening Mn-O Bond Strength in Mn-Based Perovskite Catalysts to Enhance Propane Catalytic Combustion.

Exploring highly efficient and robust non-noble metal catalysts for VOC abatement is crucial but challenging. Mn-based perovskites are a class of redox catalysts with good thermal stability, but their activity in the catalytic combustion of light alkanes is insufficient. In this work, we modulated the Mn-O bond strength in a Mn-based perovskite via defect engineering, over which the catalytic activity of propane combustion was significantly enhanced. It demonstrates that the oxygen vacancy concentration and the Mn-O bond strength can be efficiently modulated by finely tuning the Ni content in SmNixMn1-xO3 perovskite catalysts (SNxM1-x), which in turn can enhance the redox ability and generate more active oxygen species. The SN0.10M0.90 catalyst with the lowest Mn-O bond strength exhibits the lowest apparent activation energy, over which the propane conversion rate increases by 3.6 times compared to that on the SmMnO3 perovskite catalyst (SM). In addition, a SN0.10M0.90/cordierite monolithic catalyst can also exhibit a remarkable catalytic performance and deliver excellent long-term durability (1000 h), indicating broad prospects in industrial applications. Moreover, the promotional effect of Ni substitution was further unveiled by density functional theory (DFT) calculations. This work brings a favorable guidance for the exploration of highly efficient perovskite catalysts for light alkane elimination.

Porosity and pore structure evolution during the weathering of black shale.

Pore type and pore structure evolves systematically across continuous black shale weathering profile. However, the extend and process of pore structure change is still an enigma. In this study, we try to unveil the pore structure evolution during weathering process through studying Cambrian Hetang shales in southern China. Fourteen shale samples, from protolith zone (PZ), fractured and weathered shale zone (FWZ), and saprolite zone (SZ), were collected to elucidate how porosity and pore structure develop during black shale weathering under subtropical condition. Through low pressure argon (Ar) gas adsorption (LP-ArGA), high pressure mercury intrusion (HPMI), nuclear magnetic resonance(NMR) and field emission scanning electron microscope (FESEM) observation, the results reveal significant differences in physical properties and pore structures among the PZ, FWZ, and SZ samples. Specifically, compared to PZ, FWZ and SZ samples are characterized by higher clay mineral content, lower organic matter (OM), and the absence of carbonates and pyrite. Total porosity, determined through HPMI and NMR, exhibits a gradual increase from PZ (6.70 % and 6.41 %) to FWZ (20.47 % and 13.45 %) and SZ (23.22 % and 12.48 %). Ar adsorption isotherms indicate a change in pore type from predominantly ink-bottle and slit-shaped in the PZ to mainly slit-shaped in FWZ and SZ. Integrated analysis of LP-ArGA, HPMI, NMR and SEM observation suggests a substantial decrease in the contribution of micropores to total pore volume (PV) and a concurrent increase in larger pores (meso-macropores) with the increase of weathering intensity. This results in smoother surfaces of micro-transition pores but rougher surfaces of macropores. Changes in mineralogy composition during weathering play a crucial role in influencing pore structure of shales and further accelerating the release and migration of toxic elements in black shale. Our study provides the essential theoretical foundation for the remediation of soil and water environmental pollution caused by black shale weathering.

Fe-Co heteronuclear atom pairs as catalytic sites for efficient oxygen electroreduction.

Single-site Fe-N-C catalysts are the most promising Pt-group catalyst alternatives for the oxygen reduction reaction, but their application is impeded by their relatively low activity and unsatisfactory stability as well as production costs. Here, cobalt atoms are introduced into an Fe-N-C catalyst to enhance its catalytic activity by utilizing the synergistic effect between Fe and Co atoms. Meanwhile, phenanthroline is employed as the ligand, which favours stable pyridinic N-coordinated Fe-Co sites. The obtained catalysts exhibit excellent ORR performance with a half-wave potential of 0.892 V and good stability under alkaline conditions. In addition, the excellent ORR activity and durability of FeCo-N-C enabled the constructed zinc-air battery to exhibit a high power density of 247.93 mW cm-2 and a high capacity of 768.59 mA h gZn-1. Moreover, the AEMFC based on FeCo-N-C also achieved a high open circuit voltage (0.95 V) and rated power density (444.7 mW cm-2), surpassing those of many currently reported transition metal-based cathodes. This work emphasizes the feasibility of this non-precious metal catalyst preparation strategy and its practical applicability in fuel cells and metal-air batteries.

Study on static and dynamic mechanical behavior of expansive soil modified by oyster shell powder.

To investigate the effect of oyster shell powder (OSP) on the static and dynamic properties of expansive soil, the mechanical properties of modified soil were obtained. Taking Ningming expansive soil as the research object, triaxial shear test, dynamic triaxial test and scanning electron microscope test were carried out on plain soil and 9 % expansive soil modified by oyster shell powder (ESMO). The results show that compared with plain soil, the effective cohesion of modified expansive soil with dosp < 1 mm (ESMO (dosp < 1 mm)) and dosp < 0.075 mm (ESMO (dosp < 0.075 mm)) is increased by 15.4 % and 32.8 %, respectively. Under cyclic loading, compared with plain soil, the plastic strain stability value of ESMO (dosp<0.075 mm) is reduced by 40.2 %, the pore water pressure stability value is reduced, and the stiffness is increased. The dynamic mechanical properties of ESMO (dosp<1 mm) showed the opposite trend. Through microscopic experimental analysis, the main reasons for this phenomenon are the particle size distribution, bonding form, and cementation of the two. The results can provide a theoretical basis for the practical application of ESMO and the establishment of constitutive model.

Small RNA sequencing highlights a potential regulatory network mediated by Gecko miRNA affecting the prognosis of hepatocellular carcinoma.

BACKGROUND: Gecko has been widely documented in Chinese scientific literature as an anti-tumor agent for various illnesses for thousands of years, and more recently, it has been examined for its anti-tumor effects on several cancers. The effect of Gecko microRNAs (miRNAs) on hepatocellular carcinoma (HCC) has not yet been reported. OBJECTIVES: This study was designed to identify miRNAs in Gecko through small RNA sequencing and utilize bioinformatics techniques to construct a potential regulatory network and explore the possible mechanisms of exogenous miRNAs involved in HCC. MATERIAL AND METHODS: RNA was extracted from Gecko tablets, and we screened the Gecko miRNA expression dataset after high-throughput sequencing. Bioinformatics analysis was used to identify novel Gecko and HCC survival-related miRNA-mRNA cross-species regulation networks. RESULTS: miR-100-5p, miR-99a-5p and miR-101-3p were identified as critical for the role of Geckos in HCC. Nine downstream mRNAs (EZH2, KPNA2, LMNB1, LRRC1, MRGBP, SMARCD1, STMN1, SUB1, and UBE2A) were identified as target genes for critical miRNAs. A miRNA-mRNA regulatory network was constructed, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed these key mRNAs might be associated with both the suppression and progression of HCC. The novel network significantly correlated with the abundance of multiple immune cells, as determined with immune infiltration analysis. CONCLUSIONS: These findings suggest that Gecko may inhibit progression and exert a therapeutic effect on HCC by targeting critical miRNA-mRNA networks for cross-species regulation. It also provides a reference for future research and development of traditional Chinese medicine (TCM).

Baseline characteristics including blood and urine metal levels in the Trial to Assess Chelation Therapy 2 (TACT2).

BACKGROUND: The reduction in cardiovascular disease (CVD) events with edetate disodium (EDTA) in the Trial to Assess Chelation Therapy (TACT) suggested that chelation of toxic metals might provide novel opportunities to reduce CVD in patients with diabetes. Lead and cadmium are vasculotoxic metals chelated by EDTA. We present baseline characteristics for participants in TACT2, a randomized, double-masked, placebo-controlled trial designed as a replication of the TACT trial limited to patients with diabetes. METHODS: TACT2 enrolled 1,000 participants with diabetes and prior myocardial infarction, age 50 years or older between September 2016 and December 2020. Among 959 participants with at least one infusion, 933 had blood and/or urine metals measured at the Centers for Diseases Control and Prevention using the same methodology as in the National Health and Nutrition Examination Survey (NHANES). We compared metal levels in TACT2 to a contemporaneous subset of NHANES participants with CVD, diabetes and other inclusion criteria similar to TACT2's participants. RESULTS: At baseline, the median (interquartile range, IQR) age was 67 (60, 72) years, 27% were women, 78% reported white race, mean (SD) BMI was 32.7 (6.6) kg/m2, 4% reported type 1 diabetes, 46.8% were treated with insulin, 22.3% with GLP1-receptor agonists or SGLT-2 inhibitors, 90.2% with aspirin, warfarin or P2Y12 inhibitors, and 86.5% with statins. Blood lead was detectable in all participants; median (IQR) was 9.19 (6.30, 13.9) µg/L. Blood and urine cadmium were detectable in 97% and median (IQR) levels were 0.28 (0.18, 0.43) µg/L and 0.30 (0.18, 0.51) µg/g creatinine, respectively. Metal levels were largely similar to those in the contemporaneous NHANES subset. CONCLUSIONS: TACT2 participants were characterized by high use of medication to treat CVD and diabetes and similar baseline metal levels as in the general US population. TACT2 will determine whether chelation therapy reduces the occurrence of subsequent CVD events in this high-risk population. CLINICAL TRIALS REGISTRATION: ClinicalTrials.gov. Identifier: NCT02733185. https://clinicaltrials.gov/study/NCT02733185.

Research progress of dual-atom site catalysts for photocatalysis.

Dual-atom site catalysts (DASCs) have sparked considerable interest in heterogeneous photocatalysis as they possess the advantages of excellent photoelectronic activity, photostability, and high carrier separation efficiency and mobility. The DASCs involved in these important photocatalytic processes, especially in the photocatalytic hydrogen evolution reaction (HER), CO2 reduction reaction (CO2RR), N2/nitrate reduction, etc., have been extensively investigated in the past few years. In this review, we highlight the recent progress in DASCs that provides fundamental insights into the photocatalytic conversion of small molecules. The controllable preparation and characterization methods of various DASCs are discussed. Subsequently, the reaction mechanisms of the formation of several important molecules (hydrogen, hydrocarbons and ammonia) on DASCs are introduced in detail, in order to probe the relationship between DASCs's structure and photocatalytic activity. Finally, some challenges and outlooks of DASCs in the photocatalytic conversion of small molecules are summarized and prospected. We hope that this review can provide guidance for in-depth understanding and aid in the design of efficient DASCs for photocatalysis.

Evidence that Alzheimer's Disease Is a Disease of Competitive Synaptic Plasticity Gone Awry.

 Mounting evidence indicates that a physiological function of amyloid-ß (Aß) is to mediate neural activity-dependent homeostatic and competitive synaptic plasticity in the brain. I have previously summarized the lines of evidence supporting this hypothesis and highlighted the similarities between Aß and anti-microbial peptides in mediating cell/synapse competition. In cell competition, anti-microbial peptides deploy a multitude of mechanisms to ensure both self-protection and competitor elimination. Here I review recent studies showing that similar mechanisms are at play in Aß-mediated synapse competition and perturbations in these mechanisms underpin Alzheimer's disease (AD). Specifically, I discuss evidence that Aß and ApoE, two crucial players in AD, co-operate in the regulation of synapse competition. Glial ApoE promotes self-protection by increasing the production of trophic monomeric Aß and inhibiting its assembly into toxic oligomers. Conversely, Aß oligomers, once assembled, promote the elimination of competitor synapses via direct toxic activity and amplification of "eat-me" signals promoting the elimination of weak synapses. I further summarize evidence that neuronal ApoE may be part of a gene regulatory network that normally promotes competitive plasticity, explaining the selective vulnerability of ApoE expressing neurons in AD brains. Lastly, I discuss evidence that sleep may be key to Aß-orchestrated plasticity, in which sleep is not only induced by Aß but is also required for Aß-mediated plasticity, underlining the link between sleep and AD. Together, these results strongly argue that AD is a disease of competitive synaptic plasticity gone awry, a novel perspective that may promote AD research.

Quantitative assessment of choroidal parameters and retinal thickness in central serous chorioretinopathy using ultra-widefield swept-source optical coherence tomography: a cross-sectional study.

OBJECTIVE: In this study, we used ultra-wide field swept-source optical coherence tomography angiography (UWF SS-OCTA) to assess changes in retinal thickness (RT) and choroidal parameters in individuals who had received a diagnosis of central serous chorioretinopathy (CSC). METHODS: The study encompassed the evaluation of 59 eyes from 47 patients with a diagnosis of CSC, alongside 33 fellow eyes and 31 eyes from healthy individuals (controls). The parameters assessed included RT, choroidal thickness (CT), choriocapillaris density, vascular density of the large choroidal vessel layer, three-dimensional choroidal vascularity index (3D-CVI), choroidal vessel volume per unit area (mCVV/a), and choroidal stroma volume per unit area (mCSV/a). RESULTS: Metrics including mCVV/a, mCSV/a, 3D-CVI, CT, and RT exhibited significantly elevated values in the eyes affected by CSC compared to those of the control group across nine subfields. Moreover, a substantial number of the subfields in both CSC-affected and fellow eyes exhibited increased values for mCVV/a, mCSV/a, 3D-CVI, CT, and RT when compared with the control group. Additionally, acute and chronic CSC subfields demonstrated significantly elevated values for mCVV/a, mCSV/a, 3D-CVI, CT, and RT in comparison to healthy control eyes. Notably, specific subfields associated with complex and atypical forms of CSC revealed higher metrics compared to those of the control group. CONCLUSION: In conclusion, the UWF SS-OCTA proved to be a valuable tool for exploring the anatomical etiology and clinical classification and diagnosis of CSC.