Disentangling and quantifying the relative cognitive impact of concurrent mixed neurodegenerative pathologies.

Neurodegenerative pathologies such as Alzheimer disease neuropathologic change (ADNC), Lewy body disease (LBD), limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC), and cerebrovascular disease (CVD) frequently coexist, but little is known about the exact contribution of each pathology to cognitive decline and dementia in subjects with mixed pathologies. We explored the relative cognitive impact of concurrent common and rare neurodegenerative pathologies employing multivariate logistic regression analysis adjusted for age, gender, and level of education. We analyzed a cohort of 6,262 subjects from the National Alzheimer's Coordinating Center database, ranging from 0 to 6 comorbid neuropathologic findings per individual, where 95.7% of individuals had at least 1 neurodegenerative finding at autopsy and 75.5% had at least 2 neurodegenerative findings. We identified which neuropathologic entities correlate most frequently with one another and demonstrated that the total number of pathologies per individual was directly correlated with cognitive performance as assessed by Clinical Dementia Rating (CDR®) and Mini-Mental State Examination (MMSE). We show that ADNC, LBD, LATE-NC, CVD, hippocampal sclerosis, Pick disease, and FTLD-TDP significantly impact overall cognition as independent variables. More specifically, ADNC significantly affected all assessed cognitive domains, LBD affected attention, processing speed, and language, LATE-NC primarily affected tests related to logical memory and language, while CVD and other less common pathologies (including Pick disease, progressive supranuclear palsy, and corticobasal degeneration) had more variable neurocognitive effects. Additionally, ADNC, LBD, and higher numbers of comorbid neuropathologies were associated with the presence of at least one APOE ε4 allele, and ADNC and higher numbers of neuropathologies were inversely correlated with APOE ε2 alleles. Understanding the mechanisms by which individual and concomitant neuropathologies affect cognition and the degree to which each contributes is an imperative step in the development of biomarkers and disease-modifying therapeutics, particularly as these medical interventions become more targeted and personalized.

Distinguishing neonatal culture-negative sepsis from rule-out sepsis with artificial intelligence-derived graphs.

IMPACT: Novel artificial intelligence methods can aide in identification of cases of conditions using only unstructured electronic health record data. This graph-based method compares comprehensive electronic health records among neonates using temporal data. This provides a scalable solution to distinguish culture negative sepsis from rule out sepsis using a data-driven method.

Spatial proteomics of hippocampal subfield-specific pathology in Alzheimer's disease and primary age-related tauopathy.

INTRODUCTION: Alzheimer's disease (AD) and primary age-related tauopathy (PART) both harbor 3R/4R hyperphosphorylated-tau (p-tau)-positive neurofibrillary tangles (NFTs) but differ in the spatial p-tau development in the hippocampus. METHODS: Using Nanostring GeoMx Digital Spatial Profiling, we compared protein expression within hippocampal subregions in NFT-bearing and non-NFT-bearing neurons in AD (n = 7) and PART (n = 7) subjects. RESULTS: Proteomic measures of synaptic health were inversely correlated with the subregional p-tau burden in AD and PART, and there were numerous differences in proteins involved in proteostasis, amyloid beta (Aß) processing, inflammation, microglia, oxidative stress, and neuronal/synaptic health between AD and PART and between definite PART and possible PART. DISCUSSION: These results suggest subfield-specific proteome differences that may explain some of the differences in Aß and p-tau distribution and apparent pathogenicity. In addition, hippocampal neurons in possible PART may have more in common with AD than with definite PART, highlighting the importance of Aß in the pathologic process. HIGHLIGHTS: Synaptic health is inversely correlated with local p-tau burden. The proteome of NFT- and non-NFT-bearing neurons is influenced by the presence of Aß in the hippocampus. Neurons in possible PART cases share more proteomic similarities with neurons in ADNC than they do with neurons in definite PART cases.

Histopathologic brain age estimation via multiple instance learning.

Understanding age acceleration, the discordance between biological and chronological age, in the brain can reveal mechanistic insights into normal physiology as well as elucidate pathological determinants of age-related functional decline and identify early disease changes in the context of Alzheimer's and other disorders. Histopathological whole slide images provide a wealth of pathologic data on the cellular level that can be leveraged to build deep learning models to assess age acceleration. Here, we used a collection of digitized human post-mortem hippocampal sections to develop a histological brain age estimation model. Our model predicted brain age within a mean absolute error of 5.45 ± 0.22 years, with attention weights corresponding to neuroanatomical regions vulnerable to age-related changes. We found that histopathologic brain age acceleration had significant associations with clinical and pathologic outcomes that were not found with epigenetic based measures. Our results indicate that histopathologic brain age is a powerful, independent metric for understanding factors that contribute to brain aging.

Comparison of predicting cardiovascular disease hospitalization using individual, ZIP code-derived, and machine learning model-predicted educational attainment in New York City.

BACKGROUND: Area-level social determinants of health (SDOH) based on patients' ZIP codes or census tracts have been commonly used in research instead of individual SDOHs. To our knowledge, whether machine learning (ML) could be used to derive individual SDOH measures, specifically individual educational attainment, is unknown. METHODS: This is a retrospective study using data from the Mount Sinai BioMe Biobank. We included participants that completed a validated questionnaire on educational attainment and had home addresses in New York City. ZIP code-level education was derived from the American Community Survey matched for the participant's gender and race/ethnicity. We tested several algorithms to predict individual educational attainment from routinely collected clinical and demographic data. To evaluate how using different measures of educational attainment will impact model performance, we developed three distinct models for predicting cardiovascular (CVD) hospitalization. Educational attainment was imputed into models as either survey-derived, ZIP code-derived, or ML-predicted educational attainment. RESULTS: A total of 20,805 participants met inclusion criteria. Concordance between survey and ZIP code-derived education was 47%, while the concordance between survey and ML model-predicted education was 67%. A total of 13,715 patients from the cohort were included into our CVD hospitalization prediction models, of which 1,538 (11.2%) had a history of CVD hospitalization. The AUROC of the model predicting CVD hospitalization using survey-derived education was significantly higher than the model using ZIP code-level education (0.77 versus 0.72; p < 0.001) and the model using ML model-predicted education (0.77 versus 0.75; p < 0.001). The AUROC for the model using ML model-predicted education was also significantly higher than that using ZIP code-level education (p = 0.003). CONCLUSION: The concordance of survey and ZIP code-level educational attainment in NYC was low. As expected, the model utilizing survey-derived education achieved the highest performance. The model incorporating our ML model-predicted education outperformed the model relying on ZIP code-derived education. Implementing ML techniques can improve the accuracy of SDOH data and consequently increase the predictive performance of outcome models.

Glutathione oxidation unmasks proarrhythmic vulnerability of chronically hyperglycemic guinea pigs.

Chronic hyperglycemia in type-1 diabetes mellitus is associated with oxidative stress (OS) and sudden death. Mechanistic links remain unclear. We investigated changes in electrophysiological (EP) properties in a model of chronic hyperglycemia before and after challenge with OS by GSH oxidation and tested reversibility of EP remodeling by insulin. Guinea pigs survived for 1 mo following streptozotocin (STZ) or saline (sham) injection. A treatment group received daily insulin for 2 wk to reverse STZ-induced hyperglycemia (STZ + Ins). EP properties were measured using high-resolution optical action potential mapping before and after challenge of hearts with diamide. Despite elevation of glucose levels in STZ compared with sham-operated (P = 0.004) and STZ + Ins (P = 0.002) animals, average action potential duration (APD) and arrhythmia propensity were not altered at baseline. Diamide promoted early (<10 min) formation of arrhythmic triggers reflected by a higher arrhythmia scoring index in STZ (P = 0.045) and STZ + Ins (P = 0.033) hearts compared with sham-operated hearts. APD heterogeneity underwent a more pronounced increase in response to diamide in STZ and STZ + Ins hearts compared with sham-operated hearts. Within 30 min, diamide resulted in spontaneous incidence of ventricular tachycardia and ventricular fibrillation (VT/VF) in 3/6, 2/5, 1/5, and 0/4 STZ, STZ + Ins, sham-operated, and normal hearts, respectively. Hearts prone to VT/VF exhibited greater APD heterogeneity (P = 0.010) compared with their VT/VF-free counterparts. Finally, altered EP properties in STZ were not rescued by insulin. In conclusion, GSH oxidation enhances APD heterogeneity and increases arrhythmia scoring index in a guinea pig model of chronic hyperglycemia. Despite normalization of glycemic levels by insulin, these proarrhythmic properties are not reversed, suggesting the importance of targeting antioxidant defenses for arrhythmia suppression.

Impact of Vaccination on Major Adverse Cardiovascular Events in Patients With COVID-19 Infection.

Taken from the largest U.S. cohort of patients with SARS-CoV2, our results demonstrate the association of even partial vaccination with lower risk of MACE after SARS-CoV-2 infection.

Postmortem changes in brain cell structure: a review.

Brain cell structure is a key determinant of neural function that is frequently altered in neurobiological disorders. Following the global loss of blood flow to the brain that initiates the postmortem interval (PMI), cells rapidly become depleted of energy and begin to decompose. To ensure that our methods for studying the brain using autopsy tissue are robust and reproducible, there is a critical need to delineate the expected changes in brain cell morphometry during the PMI. We searched multiple databases to identify studies measuring the effects of PMI on the morphometry (i.e. external dimensions) of brain cells. We screened 2119 abstracts, 361 full texts, and included 172 studies. Mechanistically, fluid shifts causing cell volume alterations and vacuolization are an early event in the PMI, while the loss of the ability to visualize cell membranes altogether is a later event. Decomposition rates are highly heterogenous and depend on the methods for visualization, the structural feature of interest, and modifying variables such as the storage temperature or the species. Geometrically, deformations of cell membranes are common early events that initiate within minutes. On the other hand, topological relationships between cellular features appear to remain intact for more extended periods. Taken together, there is an uncertain period of time, usually ranging from several hours to several days, over which cell membrane structure is progressively lost. This review may be helpful for investigators studying human postmortem brain tissue, wherein the PMI is an unavoidable aspect of the research.

Proteomic Characterization of Acute Kidney Injury in Patients Hospitalized with SARS-CoV2 Infection.

Background Acute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using biological specimens can lead to improved risk stratification and discover pathophysiological mechanisms. Methods Using measurements of ~4000 plasma proteins in two cohorts of patients hospitalized with COVID-19, we discovered and validated markers of COVID-associated AKI (stage 2 or 3) and long-term kidney dysfunction. In the discovery cohort (N= 437), we identified 413 higher plasma abundances of protein targets and 40 lower plasma abundances of protein targets associated with COVID-AKI (adjusted p <0.05). Of these, 62 proteins were validated in an external cohort (p <0.05, N =261). Results We demonstrate that COVID-AKI is associated with increased markers of tubular injury ( NGAL ) and myocardial injury. Using estimated glomerular filtration (eGFR) measurements taken after discharge, we also find that 25 of the 62 AKI-associated proteins are significantly associated with decreased post-discharge eGFR (adjusted p <0.05). Proteins most strongly associated with decreased post-discharge eGFR included desmocollin-2 , trefoil factor 3 , transmembrane emp24 domain-containing protein 10 , and cystatin-C indicating tubular dysfunction and injury. Conclusions Using clinical and proteomic data, our results suggest that while both acute and long-term COVID-associated kidney dysfunction are associated with markers of tubular dysfunction, AKI is driven by a largely multifactorial process involving hemodynamic instability and myocardial damage.

Peripheral Transcriptomics in Acute and Long-Term Kidney Dysfunction in SARS-CoV2 Infection.

Background: Acute kidney injury (AKI) is common in hospitalized patients with SARS-CoV2 infection despite vaccination and leads to long-term kidney dysfunction. However, peripheral blood molecular signatures in AKI from COVID-19 and their association with long-term kidney dysfunction are yet unexplored. Methods: In patients hospitalized with SARS-CoV2, we performed bulk RNA sequencing using peripheral blood mononuclear cells(PBMCs). We applied linear models accounting for technical and biological variability on RNA-Seq data accounting for false discovery rate (FDR) and compared functional enrichment and pathway results to a historical sepsis-AKI cohort. Finally, we evaluated the association of these signatures with long-term trends in kidney function. Results: Of 283 patients, 106 had AKI. After adjustment for sex, age, mechanical ventilation, and chronic kidney disease (CKD), we identified 2635 significant differential gene expressions at FDR<0.05. Top canonical pathways were EIF2 signaling, oxidative phosphorylation, mTOR signaling, and Th17 signaling, indicating mitochondrial dysfunction and endoplasmic reticulum (ER) stress. Comparison with sepsis associated AKI showed considerable overlap of key pathways (48.14%). Using follow-up estimated glomerular filtration rate (eGFR) measurements from 115 patients, we identified 164/2635 (6.2%) of the significantly differentiated genes associated with overall decrease in long-term kidney function. The strongest associations were 'autophagy', 'renal impairment via fibrosis', and 'cardiac structure and function'. Conclusions: We show that AKI in SARS-CoV2 is a multifactorial process with mitochondrial dysfunction driven by ER stress whereas long-term kidney function decline is associated with cardiac structure and function and immune dysregulation. Functional overlap with sepsis-AKI also highlights common signatures, indicating generalizability in therapeutic approaches. SIGNIFICANCE STATEMENT: Peripheral transcriptomic findings in acute and long-term kidney dysfunction after hospitalization for SARS-CoV2 infection are unclear. We evaluated peripheral blood molecular signatures in AKI from COVID-19 (COVID-AKI) and their association with long-term kidney dysfunction using the largest hospitalized cohort with transcriptomic data. Analysis of 283 hospitalized patients of whom 37% had AKI, highlighted the contribution of mitochondrial dysfunction driven by endoplasmic reticulum stress in the acute stages. Subsequently, long-term kidney function decline exhibits significant associations with markers of cardiac structure and function and immune mediated dysregulation. There were similar biomolecular signatures in other inflammatory states, such as sepsis. This enhances the potential for repurposing and generalizability in therapeutic approaches.

Proteomic characterization of acute kidney injury in patients hospitalized with SARS-CoV2 infection.

BACKGROUND: Acute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using biological specimens can lead to improved risk stratification and discover pathophysiological mechanisms. METHODS: Using measurements of ~4000 plasma proteins in two cohorts of patients hospitalized with COVID-19, we discovered and validated markers of COVID-associated AKI (stage 2 or 3) and long-term kidney dysfunction. In the discovery cohort (N = 437), we identified 413 higher plasma abundances of protein targets and 30 lower plasma abundances of protein targets associated with COVID-AKI (adjusted p < 0.05). Of these, 62 proteins were validated in an external cohort (p < 0.05, N = 261). RESULTS: We demonstrate that COVID-AKI is associated with increased markers of tubular injury (NGAL) and myocardial injury. Using estimated glomerular filtration (eGFR) measurements taken after discharge, we also find that 25 of the 62 AKI-associated proteins are significantly associated with decreased post-discharge eGFR (adjusted p < 0.05). Proteins most strongly associated with decreased post-discharge eGFR included desmocollin-2, trefoil factor 3, transmembrane emp24 domain-containing protein 10, and cystatin-C indicating tubular dysfunction and injury. CONCLUSIONS: Using clinical and proteomic data, our results suggest that while both acute and long-term COVID-associated kidney dysfunction are associated with markers of tubular dysfunction, AKI is driven by a largely multifactorial process involving hemodynamic instability and myocardial damage.

Acute kidney injury (AKI) is a sudden, sometimes fatal, episode of kidney failure or damage. It is a known complication of COVID-19, albeit through unclear mechanisms. COVID-19 is also associated with kidney dysfunction in the long term, or chronic kidney disease (CKD). There is a need to better understand which patients with COVID-19 are at risk of AKI or CKD. We measure levels of several thousand proteins in the blood of hospitalized COVID-19 patients. We discover and validate sets of proteins associated with severe AKI and CKD in these patients. The markers identified suggest that kidney injury in COVID-19 patients involves damage to kidney cells that reabsorb fluid from urine and reduced blood flow to the heart, causing damage to heart muscles. Our findings might help clinicians to predict kidney injury in patients with COVID-19, and to understand its mechanisms.

Artificial intelligence-derived neurofibrillary tangle burden is associated with antemortem cognitive impairment.

Tauopathies are a category of neurodegenerative diseases characterized by the presence of abnormal tau protein-containing neurofibrillary tangles (NFTs). NFTs are universally observed in aging, occurring with or without the concomitant accumulation of amyloid-beta peptide (Aß) in plaques that typifies Alzheimer disease (AD), the most common tauopathy. Primary age-related tauopathy (PART) is an Aß-independent process that affects the medial temporal lobe in both cognitively normal and impaired subjects. Determinants of symptomology in subjects with PART are poorly understood and require clinicopathologic correlation; however, classical approaches to staging tau pathology have limited quantitative reproducibility. As such, there is a critical need for unbiased methods to quantitatively analyze tau pathology on the histological level. Artificial intelligence (AI)-based convolutional neural networks (CNNs) generate highly accurate and precise computer vision assessments of digitized pathology slides, yielding novel histology metrics at scale. Here, we performed a retrospective autopsy study of a large cohort (n = 706) of human post-mortem brain tissues from normal and cognitively impaired elderly individuals with mild or no Aß plaques (average age of death of 83.1 yr, range 55-110). We utilized a CNN trained to segment NFTs on hippocampus sections immunohistochemically stained with antisera recognizing abnormal hyperphosphorylated tau (p-tau), which yielded metrics of regional NFT counts, NFT positive pixel density, as well as a novel graph-theory based metric measuring the spatial distribution of NFTs. We found that several AI-derived NFT metrics significantly predicted the presence of cognitive impairment in both the hippocampus proper and entorhinal cortex (p < 0.0001). When controlling for age, AI-derived NFT counts still significantly predicted the presence of cognitive impairment (p = 0.04 in the entorhinal cortex; p = 0.04 overall). In contrast, Braak stage did not predict cognitive impairment in either age-adjusted or unadjusted models. These findings support the hypothesis that NFT burden correlates with cognitive impairment in PART. Furthermore, our analysis strongly suggests that AI-derived metrics of tau pathology provide a powerful tool that can deepen our understanding of the role of neurofibrillary degeneration in cognitive impairment.

Proteomic Characterization of Acute Kidney Injury in Patients Hospitalized with SARS-CoV2 Infection.

Acute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using biological specimens can lead to improved risk stratification and discover pathophysiological mechanisms. Using measurements of ∼4000 plasma proteins in two cohorts of patients hospitalized with COVID-19, we discovered and validated markers of COVID-associated AKI (stage 2 or 3) and long-term kidney dysfunction. In the discovery cohort (N= 437), we identified 413 higher plasma abundances of protein targets and 40 lower plasma abundances of protein targets associated with COVID-AKI (adjusted p <0.05). Of these, 62 proteins were validated in an external cohort (p <0.05, N =261). We demonstrate that COVID-AKI is associated with increased markers of tubular injury (NGAL) and myocardial injury. Using estimated glomerular filtration (eGFR) measurements taken after discharge, we also find that 25 of the 62 AKI-associated proteins are significantly associated with decreased post-discharge eGFR (adjusted p <0.05). Proteins most strongly associated with decreased post-discharge eGFR included desmocollin-2, trefoil factor 3, transmembrane emp24 domain-containing protein 10, and cystatin-C indicating tubular dysfunction and injury. Using clinical and proteomic data, our results suggest that while both acute and long-term COVID-associated kidney dysfunction are associated with markers of tubular dysfunction, AKI is driven by a largely multifactorial process involving hemodynamic instability and myocardial damage.

Biophysical properties and functional consequences of reactive oxygen species (ROS)-induced ROS release in intact myocardium.

Reactive oxygen species (ROS)-induced ROS release (RIRR) is a fundamental mechanism by which cardiac mitochondria respond to elevated ROS levels by stimulating endogenous ROS production in a regenerative, autocatalytic process that ultimately results in global oxidative stress (OS), cellular dysfunction and death. Despite elegant studies describing the phenomenon of RIRR under artificial conditions such as photo-induced oxidation of discrete regions within cardiomyocytes, the existence, biophysical properties and functional consequences of RIRR in intact myocardium remain unclear. Here, we used a semi-quantitative approach of optical superoxide (O(2)(-)) mapping using dihydroethidium (DHE) fluorescence to explore RIRR, its arrhythmic consequences and underlying mechanisms in intact myocardium. Initially, perfusion of rat hearts with 200 µM H(2)O(2) for 40 min (n = 4) elicited two distinct O(2)(-) peaks that were readily distinguished by their timing and amplitude. The first peak (P1), which was generated rapidly (within 5-8 min of H(2)O(2) perfusion) was associated with a relatively limited (10 ± 2%) rise in normalized O(2)(-) levels relative to baseline. In contrast, the second peak (P2) occurred 19-26 min following onset of H(2)O(2) perfusion and was associated with a significantly greater amplitude compared to P1. Spatio-temporal ROS mapping during P2 revealed active O(2)(-) propagation across the myocardium at a velocity of ~20 µm s(-1). Exposure of hearts (n = 18) to a short (10 min) episode of H(2)O(2) perfusion revealed consistent generation of P2 by high (≥200 µM, 8/8) but not lower (≤100 µM, 3/8) H(2)O(2) concentrations (P < 0.03). In these hearts, onset of P2 occurred following, not during, the 10 min OS protocol, consistent with RIRR. Importantly, P2 (+) hearts exhibited a markedly greater (by 3.8-fold, P < 0.001) arrhythmia score compared to P2 (-) hearts. To explore the mechanism underlying RIRR in intact myocardium, hearts were perfused with either cyclosporin A (CsA) or 4-chlorodiazepam (4-Cl-DZP) to inhibit the mitochondrial permeability transition pore (mPTP) or the inner membrane anion channel (IMAC), respectively. Surprisingly, perfusion with CsA failed to suppress (P = 0.75, n.s.) or even delay H(2)O(2)-induced P2 or the incidence of arrhythmias compared to untreated hearts. In sharp contrast, perfusion with 4-Cl-DZP markedly blunted O(2)(-) levels during P2, and suppressed the incidence of sustained ventricular tachycardia or ventricular fibrillation (VT/VF). Finally, perfusion of hearts with the synthetic superoxide dismutase/catalase mimetic EUK-134 completely abolished the H(2)O(2)-mediated RIRR response as well as the incidence of arrhythmias. These findings extend the concept of RIRR to the level of the intact heart, establish regenerative O(2)(-) production as the mediator of RIRR-related arrhythmias and reveal their strong dependence on IMAC and not the mPTP in this acute model of OS.

Functional crosstalk between the mitochondrial PTP and KATP channels determine arrhythmic vulnerability to oxidative stress.

BACKGROUND: Mitochondrial permeability transition pore (mPTP) opening is a terminal event leading to mitochondrial dysfunction and cell death under conditions of oxidative stress (OS). However, mPTP blockade with cyclosporine A (CsA) has shown variable efficacy in limiting post-ischemic dysfunction and arrhythmias. We hypothesized that strong feedback between energy dissipating (mPTP) and cardioprotective (mKATP) channels determine vulnerability to OS. METHODS AND RESULTS: Guinea pig hearts (N = 61) were challenged with H2O2 (200 µM) to elicit mitochondrial membrane potential (ΔΨm) depolarization. High-resolution optical mapping was used to measure ΔΨm or action potentials (AP) across the intact heart. Hearts were treated with CsA (0.1 µM) under conditions that altered the activity of mKATP channels either directly or indirectly via its regulation by protein kinase C. mPTP blockade with CsA markedly blunted (P < 0.01) OS-induced ΔΨm depolarization and delayed loss of LV pressure (LVP), but did not affect arrhythmia propensity. Surprisingly, prevention of mKATP activation with the chemical phosphatase BDM reversed the protective effect of CsA, paradoxically exacerbating OS-induced ΔΨm depolarization and accelerating arrhythmia onset in CsA treated compared to untreated hearts (P < 0.05). To elucidate the putative molecular mechanisms, mPTP inhibition by CsA was tested during conditions of selective PKC inhibition or direct mKATP channel activation or blockade. Similar to BDM, the specific PKC inhibitor, CHE (10 µM) did not alter OS-induced ΔΨm depolarization directly. However, it completely abrogated CsA-mediated protection against OS. Direct pharmacological blockade of mKATP, a mitochondrial target of PKC signaling, equally abolished the protective effect of CsA on ΔΨm depolarization, whereas channel activation with 30 µM Diazoxide protected against ΔΨm depolarization (P < 0.0001). Conditions that prevented mKATP activation either directly or indirectly via PKC inhibition led to accelerated ΔΨm depolarization and early onset of VF in response to OS. Investigation of the electrophysiological substrate revealed accelerated APD shortening in response to OS in arrhythmia-prone hearts. CONCLUSIONS: Cardioprotection by CsA requires mKATP channel activation through a PKC-dependent pathway. Increasing mKATP activity during CsA administration is required for limiting OS-induced electrical dysfunction.