The Zn−polyiodide redox flow battery is considered to be a promising aqueous energy storage system. However, in its charging process, the electrode kinetics of I − oxidation often suffer from an intrinsically generated iodine film (I 2 −F) on the cathode of the battery. Therefore, it is critical to both understand and enhance the observed slow electrode kinetics of I − oxidation by an electrochemically generated I 2 −F. In this article, we introduced an electrogenerated N-methyl-N-ethyl pyrrolidinium iodide (MEPI)−iodine (I 2 ) solution, designated as MEPIS, and demonstrated that the electrode kinetics of I − oxidation were dramatically enhanced compared to an I 2 −F under conventional electrolyte conditions, such as NaI. We showed that this result mainly contributed to the fast electro-oxidation of triiodide (I 3 − ), which exists in the shape of a I 3Raman spectroscopic and electrochemical analyses showed that the composition of electrogenerated MEPIS changed from I 3 − to [I 3 − •(I 2 ) n ] via I 5 − as the anodic overpotential increased. We also confirmed that I − was electrochemically oxidized on a MEPIS-modified Pt electrode with fast electrode kinetics, which is clearly contrary to the nature of an I 2 −F derived from a NaI solution as a kinetic barrier of I − oxidation. Through stochastic MEPIS−particle impact electrochemistry and electrochemical impedance spectroscopy, we revealed that the enhanced electrode kinetics of I − oxidation in MEPIS can be attributed to the facilitated charge transfer of I 3 − oxidation in [I 3 − •(I 2 ) n ]. In addition, we found that the degree of freedom of I 3 − in a quaternary ammonium-based I 2 −F can also be critical to determine the kinetics of the electro-oxidation of I − , which is that MEPIS showed more enhanced charge-transfer kinetics of I − oxidation compared to tetrabutylammonium I 3 − due to the higher degree of freedom of I 3 − .

Background Currently in the United Kingdom, cardiovascular disease (CVD) risk assessment is based on the QRISK3 score, in which 10% 10-year CVD risk indicates clinical intervention. However, this benchmark has limited efficacy in clinical practice and the need for a more simple, non-invasive risk stratification tool is necessary. Retinal photography is becoming increasingly acceptable as a non-invasive imaging tool for CVD. Previously, we developed a novel CVD risk stratification system based on retinal photographs predicting future CVD risk. This study aims to further validate our biomarker, Reti-CVD, (1) to detect risk group of ≥ 10% in 10-year CVD risk and (2) enhance risk assessment in individuals with QRISK3 of 7.5–10% (termed as borderline-QRISK3 group) using the UK Biobank. Methods Reti-CVD scores were calculated and stratified into three risk groups based on optimized cut-off values from the UK Biobank. We used Cox proportional-hazards models to evaluate the ability of Reti-CVD to predict CVD events in the general population. C-statistics was used to assess the prognostic value of adding Reti-CVD to QRISK3 in borderline-QRISK3 group and three vulnerable subgroups. Results Among 48,260 participants with no history of CVD, 6.3% had CVD events during the 11-year follow-up. Reti-CVD was associated with an increased risk of CVD (adjusted hazard ratio [HR] 1.41; 95% confidence interval [CI], 1.30–1.52) with a 13.1% (95% CI, 11.7–14.6%) 10-year CVD risk in Reti-CVD-high-risk group. The 10-year CVD risk of the borderline-QRISK3 group was greater than 10% in Reti-CVD-high-risk group (11.5% in non-statin cohort [n = 45,473], 11.5% in stage 1 hypertension cohort [n = 11,966], and 14.2% in middle-aged cohort [n = 38,941]). C statistics increased by 0.014 (0.010–0.017) in non-statin cohort, 0.013 (0.007–0.019) in stage 1 hypertension cohort, and 0.023 (0.018–0.029) in middle-aged cohort for CVD event prediction after adding Reti-CVD to QRISK3. Conclusions Reti-CVD has the potential to identify individuals with ≥ 10% 10-year CVD risk who are likely to benefit from earlier preventative CVD interventions. For borderline-QRISK3 individuals with 10-year CVD risk between 7.5 and 10%, Reti-CVD could be used as a risk enhancer tool to help improve discernment accuracy, especially in adult groups that may be pre-disposed to CVD.

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Despite the importance of preventing chronic kidney disease (CKD), predicting high-risk patients who require active intervention is challenging, especially in people with preserved kidney function. In this study, a predictive risk score for CKD (Reti-CKD score) was derived from a deep learning algorithm using retinal photographs. The performance of the Reti-CKD score was verified using two longitudinal cohorts of the UK Biobank and Korean Diabetic Cohort. Validation was done in people with preserved kidney function, excluding individuals with eGFR <90 mL/min/1.73 m2 or proteinuria at baseline. In the UK Biobank, 720/30,477 (2.4%) participants had CKD events during the 10.8-year follow-up period. In the Korean Diabetic Cohort, 206/5014 (4.1%) had CKD events during the 6.1-year follow-up period. When the validation cohorts were divided into quartiles of Reti-CKD score, the hazard ratios for CKD development were 3.68 (95% Confidence Interval [CI], 2.88–4.41) in the UK Biobank and 9.36 (5.26–16.67) in the Korean Diabetic Cohort in the highest quartile compared to the lowest. The Reti-CKD score, compared to eGFR based methods, showed a superior concordance index for predicting CKD incidence, with a delta of 0.020 (95% CI, 0.011–0.029) in the UK Biobank and 0.024 (95% CI, 0.002–0.046) in the Korean Diabetic Cohort. In people with preserved kidney function, the Reti-CKD score effectively stratifies future CKD risk with greater performance than conventional eGFR-based methods.

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