Cardiac arrest (CA) triggers neuroinflammation that could play a role in a delayed neuronal death. In our previously established rat model of ventricular fibrillation (VF) CA characterized by extensive neuronal death, we tested the hypothesis that individual brain regions have specific neuroinflammatory responses, as reflected by regional brain tissue levels of tumor necrosis factor (TNF)α and other cytokines. In a prospective study, rats were randomized to 6min (CA6), 8min (CA8) or 10min (CA10) of VF CA, or sham group. Cortex, striatum, hippocampus and cerebellum were evaluated for TNFα and interleukin (IL)-1α, IL-1β, IL-2, IL-4, IL-6, IL-10, IL-12 and interferon gamma at 3h, 6h or 14 d after CA by ELISA and Luminex. Immunohistochemistry was used to determine the cell source of TNFα. CA resulted in a selective TNFα response with significant regional and temporal differences. At 3h after CA, TNFα-levels increased in all regions depending on the duration of the insult. The most pronounced increase was observed in striatum that showed 20-fold increase in CA10 vs. sham, and 3-fold increase vs. CA6 or CA8 group, respectively (p<0.01). TNFα levels in striatum decreased between 3h and 6h, but increased in other regions between 3h and 14 d. TNFα levels remained twofold higher in CA6 vs. shams across brain regions at 14 d (p<0.01). In contrast to pronounced TNFα response, other cytokines showed only a minimal increase in CA6 and CA8 groups vs. sham in all brain regions with the exception that IL-1β increased twofold in cerebellum and striatum (p<0.01). TNFα colocalized with neurons. In conclusion, CA produced a duration-dependent acute TNFα response, with dramatic increase in the striatum where TNFα colocalized with neurons. Increased TNFα levels persist for at least two weeks. This TNFα surge contrasts the lack of an acute increase in other cytokines in brain after CA. Given that striatum is a selectively vulnerable brain region, our data suggest possible role of neuronal TNFα in striatum after CA and identify therapeutic targets for future experiments. This study was approved by the University of Pittsburgh IACUC 1002340A-3.
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http://dx.doi.org/10.1016/j.resuscitation.2014.01.033 | DOI Listing |
Cureus
December 2024
Internal Medicine, University of Health Sciences, Lahore, PAK.
Acute coronary syndrome (ACS) remains a major global health burden, encompassing a spectrum of conditions from unstable angina to acute myocardial infarction. Despite advancements in early detection and management, ACS is often complicated by the development of heart failure. This systematic review and meta-analysis aimed to identify factors associated with the development of heart failure following acute coronary syndrome.
View Article and Find Full Text PDFFront Cardiovasc Med
January 2025
Department of Cardiology, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
Introduction: The risk of mortality associated with cardiac arrhythmias is considerable, and their diagnosis presents significant challenges, often resulting in misdiagnosis. This situation highlights the necessity for an automated, efficient, and real-time detection method aimed at enhancing diagnostic accuracy and improving patient outcomes.
Methods: The present study is centered on the development of a portable deep learning model for the detection of arrhythmias via electrocardiogram (ECG) signals, referred to as CardioAttentionNet (CANet).
Heliyon
January 2025
Department of Information Engineering, Università Politecnica delle Marche, via Brecce Bianche, Ancona, 60131, Italy.
Background: Deep-learning applications in cardiology typically perform trivial binary classification and are able to discriminate between subjects affected or not affected by a specific cardiac disease. However, this working scenario is very different from the real one, where clinicians are required to recognize the occurrence of one cardiac disease among the several possible ones, performing a multiclass classification. The present work aims to create a new interpretable deep-learning tool able to perform a multiclass classification and, thus, discriminate among several different cardiac diseases.
View Article and Find Full Text PDFEur J Med Res
January 2025
Department of Cardiology, Renmin Hospital of Wuhan University; Institute of Molecular Medicine, Renmin Hospital of Wuhan University; Hubei Key Laboratory of Autonomic Nervous System Modulation; Taikang Center for Life and Medical Sciences, Wuhan University; Cardiac Autonomic Nervous System Research Center of Wuhan University; Hubei Key Laboratory of Cardiology; Cardiovascular Research Institute, Wuhan University, No.238 Jiefang Road, Wuhan, Hubei, 430060, People's Republic of China.
Background: Clinical studies on atrial fibrillation (AF) recurrence after catheter ablation in patients diagnosed with patent foramen ovale (PFO) and paroxysmal AF (PAF) are scarce. Here, we aimed to develop a nomogram model utilizing multimodal data for the risk stratification of AF recurrence following catheter ablation in individuals diagnosed with PFO and new-onset PAF.
Methods: Patients with PFO and PAF who underwent catheter ablation at the Renmin Hospital of Wuhan University from January 2018 to June 2020 were consecutively enrolled.
A A Pract
January 2025
From the Department of Anesthesia and Perioperative Medicine, University of California Los Angeles (UCLA) David Geffen School of Medicine, UCLA Health System, Los Angeles, California.
Management of refractory ventricular fibrillation (VF) in patients with implantable implantable cardioverter defibrillator (ICD) presents a therapeutic challenge. We present a case of pediatric refractory ventricular tachycardia (VT)/Torsade de Pointe managed effectively with bilateral stellate ganglion block (SGB) with a long-acting local anesthetic for 18 days as a bridge to more definitive surgical management.
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