[The role of inflammation in heart failure with preserved ejection fraction].

Heart failure with preserved ejection fraction (HFpEF) is a type of heart failure characterized by left ventricular diastolic dysfunction with preserved ejection fraction. With the aging of the population and the increasing prevalence of metabolic diseases, such as hypertension, obesity and diabetes, the prevalence of HFpEF is increasing. Compared with heart failure with reduced ejection fraction (HFrEF), conventional anti-heart failure drugs failed to reduce the mortality in HFpEF due to the complex pathophysiological mechanism and multiple comorbidities of HFpEF. It is known that the main changes of cardiac structure of in HFpEF are cardiac hypertrophy, myocardial fibrosis and left ventricular hypertrophy, and HFpEF is commonly associated with obesity, diabetes, hypertension, renal dysfunction and other diseases, but how these comorbidities cause structural and functional damage to the heart is not completely clear. Recent studies have shown that immune inflammatory response plays a vital role in the progression of HFpEF. This review focuses on the latest research progress in the role of inflammation in the process of HFpEF and the potential application of anti-inflammatory therapy in HFpEF, hoping to provide new research ideas and theoretical basis for the clinical prevention and treatment in HFpEF.

Cardiomyocyte peroxisome proliferator-activated receptor α prevents septic cardiomyopathy via improving mitochondrial function.

Clinically, cardiac dysfunction is a key component of sepsis-induced multi-organ failure. Mitochondria are essential for cardiomyocyte homeostasis, as disruption of mitochondrial dynamics enhances mitophagy and apoptosis. However, therapies targeted to improve mitochondrial function in septic patients have not been explored. Transcriptomic data analysis revealed that the peroxisome proliferator-activated receptor (PPAR) signaling pathway in the heart was the most significantly decreased in the cecal ligation puncture-treated mouse heart model, and PPARα was the most notably decreased among the three PPAR family members. Male Pparafl/fl (wild-type), cardiomyocyte-specific Ppara-deficient (PparaΔCM), and myeloid-specific Ppara-deficient (PparaΔMac) mice were injected intraperitoneally with lipopolysaccharide (LPS) to induce endotoxic cardiac dysfunction. PPARα signaling was decreased in LPS-treated wild-type mouse hearts. To determine the cell type in which PPARα signaling was suppressed, the cell type-specific Ppara-null mice were examined. Cardiomyocyte- but not myeloid-specific Ppara deficiency resulted in exacerbated LPS-induced cardiac dysfunction. Ppara disruption in cardiomyocytes augmented mitochondrial dysfunction, as revealed by damaged mitochondria, lowered ATP contents, decreased mitochondrial complex activities, and increased DRP1/MFN1 protein levels. RNA sequencing results further showed that cardiomyocyte Ppara deficiency potentiated the impairment of fatty acid metabolism in LPS-treated heart tissue. Disruption of mitochondrial dynamics resulted in increased mitophagy and mitochondrial-dependent apoptosis in Ppara△CM mice. Moreover, mitochondrial dysfunction caused an increase of reactive oxygen species, leading to increased IL-6/STAT3/NF-κB signaling. 3-Methyladenine (3-MA, an autophagosome formation inhibitor) alleviated cardiomyocyte Ppara disruption-induced mitochondrial dysfunction and cardiomyopathy. Finally, pre-treatment with the PPARα agonist WY14643 lowered mitochondrial dysfunction-induced cardiomyopathy in hearts from LPS-treated mice. Thus, cardiomyocyte but not myeloid PPARα protects against septic cardiomyopathy by improving fatty acid metabolism and mitochondrial dysfunction, thus highlighting that cardiomyocyte PPARα may be a therapeutic target for the treatment of cardiac disease.

[Noise attenuation analysis on auditory evoked potential based on maximum length sequence].

The maximum length sequence (m-sequence) has been successfully used to study the linear/nonlinear components of auditory evoked potential (AEP) with rapid stimulation. However, more study is needed to evaluate the effect of the m-sequence order in terms of the noise attenuation performance. This study aimed to address this issue using response-free electroencephalogram (EEG) and EEGs with nonlinear AEPs. We examined the noise attenuation ratios to evaluate the noise variation for the calculations of superimposed averaging and cross-correlation, respectively, which constitutes the main process in the deconvolution method using the dataset of spontaneous EEGs to simulate the cases of different orders (order 5 to 12) of m-sequences. And an experiment using m-sequences of order 7 and 9 was performed in true cases with substantial linear and nonlinear AEPs. The results demonstrate that the noise attenuation ratio is well agreed with the theoretical value derived from the properties of m-sequences on the random noise condition. The comparison of waveforms for AEP components from two m-sequences showed high similarity suggesting the insensitivity of AEP to the m-sequence order. This study provides a more comprehensive solution to the selection of m-sequences which will facilitate the feasible application on the nonlinear AEP with m-sequence method.

Noise Attenuation Estimation for Maximum Length Sequences in Deconvolution Process of Auditory Evoked Potentials.

The use of maximum length sequence (m-sequence) has been found beneficial for recovering both linear and nonlinear components at rapid stimulation. Since m-sequence is fully characterized by a primitive polynomial of different orders, the selection of polynomial order can be problematic in practice. Usually, the m-sequence is repetitively delivered in a looped fashion. Ensemble averaging is carried out as the first step and followed by the cross-correlation analysis to deconvolve linear/nonlinear responses. According to the classical noise reduction property based on additive noise model, theoretical equations have been derived in measuring noise attenuation ratios (NARs) after the averaging and correlation processes in the present study. A computer simulation experiment was conducted to test the derived equations, and a nonlinear deconvolution experiment was also conducted using order 7 and 9 m-sequences to address this issue with real data. Both theoretical and experimental results show that the NAR is essentially independent of the m-sequence order and is decided by the total length of valid data, as well as stimulation rate. The present study offers a guideline for m-sequence selections, which can be used to estimate required recording time and signal-to-noise ratio in designing m-sequence experiments.