Fractal Analysis of Left Ventricular Trabeculae in Patients with End-Stage Renal Disease: A Random Survival Tree Analysis.

BACKGROUND: The complexity of left ventricular (LV) trabeculae is related to the prognosis of several cardiovascular diseases. PURPOSE: To evaluate the prognostic value of LV trabecular complexity in patients with end-stage renal disease (ESRD). STUDY TYPE: Prospective outcome study. POPULATION: 207 participants on maintenance dialysis, divided into development (160 patients from 2 centers) and external validation (47 patients from a third center) cohorts, and 72 healthy controls. FIELD STRENGTH: 3.0T, steady-state free precession (SSFP) and modified Look-Locker imaging sequences. ASSESSMENT: All participants had their trabecular complexity quantified by fractal analysis using cine SSFP images. Patients were followed up every 2 weeks until April 2023, or endpoint events happened. Random Forest (RF) and Cox regression models including age, diabetes, LV mass index, mean basal fractal dimension (FD), and left atrial volume index, were developed to predict major adverse cardiac events (MACE). Patients were divided into low- and high-risk groups based on scores derived from the RF model and survival compared. STATISTICAL TESTS: Receiver operating characteristic curve analysis; Kaplan-Meier survival analysis with log rank tests; Harrel's C-index to assess model performance. A P value <0.05 was considered statistically significant. RESULTS: Fifty-five patients (26.57%) experienced MACE during a median follow-up time of 21.83 months. An increased mean basal FD (≥1.324) was associated with a significantly higher risk of MACE. The RF model (C-index: 0.81) had significantly better discrimination than the Cox regression model (C-index: 0.74). Participants of the external validation dataset classified into the high-risk group had a hazard of experiencing MACE increased by 12.29 times compared to those in the low-risk group. DATA CONCLUSION: LV basal FD was an independent predictor for MACE in patients with ESRD. Reliable risk stratification models could be generated based on LV basal FD and other MRI variables using RF analysis. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Evaluating the Effectiveness of a Generative Pretrained Transformer-Based Dietary Recommendation System in Managing Potassium Intake for Hemodialysis Patients.

OBJECTIVE: Despite adequate dialysis, the prevalence of hyperkalemia in Chinese hemodialysis (HD) patients remains elevated. This study aims to evaluate the effectiveness of a dietary recommendation system driven by generative pretrained transformers (GPTs) in managing potassium levels in HD patients. METHODS: We implemented a bespoke dietary guidance tool utilizing GPT technology. Patients undergoing HD at our center were enrolled in the study from October 2023 to November 2023. The intervention comprised of two distinct phases. Initially, patients were provided with conventional dietary education focused on potassium management in HD. Subsequently, in the second phase, they were introduced to a novel GPT-based dietary guidance tool. This artificial intelligence (AI)-powered tool offered real-time insights into the potassium content of various foods and personalized dietary suggestions. The effectiveness of the AI tool was evaluated by assessing the precision of its dietary recommendations. Additionally, we compared predialysis serum potassium levels and the proportion of patients with hyperkalemia among patients before and after the implementation of the GPT-based dietary guidance system. RESULTS: In our analysis of 324 food photographs uploaded by 88 HD patients, the GPTs system evaluated potassium content with an overall accuracy of 65%. Notably, the accuracy was higher for high-potassium foods at 85%, while it stood at 48% for low-potassium foods. Furthermore, the study examined the effect of GPT-based dietary advice on patients' serum potassium levels, revealing a significant reduction in those adhering to GPTs recommendations compared to recipients of traditional dietary guidance (4.57 ± 0.76 mmol/L vs. 4.84 ± 0.94 mmol/L, P = .004). Importantly, compared to traditional dietary education, dietary education based on the GPTs tool reduced the proportion of hyperkalemia in HD patients from 39.8% to 25% (P = .036). CONCLUSION: These results underscore the promising role of AI in improving dietary management for HD patients. Nonetheless, the study also points out the need for enhanced accuracy in identifying low potassium foods. It paves the way for future research, suggesting the incorporation of extensive nutritional databases and the assessment of long-term outcomes. This could potentially lead to more refined and effective dietary management strategies in HD care.

Activation of lipophagy is required for RAB7 to regulate ferroptosis in sepsis-induced acute kidney injury.

Sepsis-induced acute kidney injury (S-AKI) is the most common type of acute kidney injury (AKI), accompanied by elevated morbidity and mortality rates. This study investigated the mechanism by which lipid droplets (LDs) degraded via autophagy (lipophagy)required for RAB7 regulated ferroptosis in the pathogenesis of S-AKI. Here, we constructed the S-AKI model in vitro and in vivo to elucidate the potential relationship of lipophagy and ferroptosis, and we first confirmed that the activation of lipophagy promoted renal tubular epithelial cell ferroptosis and renal damage in S-AKI. The results showed that lipopolysaccharide (LPS) induced a marked increase in lipid peroxidation and ferroptosis, which were rescued by ferrstain-1 (Fer-1), an inhibitor of ferroptosis. In addition, LPS induced the remarkable activation of RAB7-mediated lipophagy. Importantly, silencing RAB7 alleviated LPS-induced lipid peroxidation and ferroptosis. Thus, the present study demonstrated the potential significant role of ferroptosis and lipophagy in sepsis-induced AKI, and contributed to better understanding of the pathogenesis and treatment targets of AKI.

DDRGK1-mediated ER-phagy attenuates acute kidney injury through ER-stress and apoptosis.

Acute kidney injury (AKI) constitutes a prevalent clinical syndrome characterized by elevated morbidity and mortality rates, emerging as a significant public health issue. This study investigates the interplay between endoplasmic reticulum (ER) stress, unfolded protein response (UPR), and ER-associated degradation (ER-phagy) in the pathogenesis of AKI. We employed four distinct murine models of AKI-induced by contrast media, ischemia-reperfusion injury, cisplatin, and folic acid-to elucidate the relationship between ER-phagy, ER stress, and apoptosis. Our findings reveal a marked decrease in ER-phagy coinciding with an accumulation of damaged ER, elevated ER stress, and increased apoptosis across all AKI models. Importantly, overexpression of DDRGK1 in HK-2 cells enhanced ER-phagy levels, ameliorating contrast-induced ER stress and apoptosis. These findings unveil a novel protective mechanism in AKI, wherein DDRGK1-UFL1-mediated ER-phagy mitigates ER stress and apoptosis in renal tubular epithelial cells. Our results thereby contribute to understanding the molecular underpinnings of AKI and offer potential therapeutic targets for its treatment.