Correlation Between Intracoronary Vascular Ultrasound Indexes in Patients with Coronary Heart Disease.

Background: Coronary atherosclerosis is a serious and progressive condition characterized by the accumulation of plaques, consisting of fat, cholesterol, and other substances, within the arteries that supply blood to the heart. These plaques can harden and narrow the arteries, leading to reduced blood flow to the heart muscle. Objective: The primary objective of this study is to investigate the correlation between specific cardiovascular parameters and intracoronary vascular ultrasound indexes in patients diagnosed with coronary heart disease. This investigation aims to explore the relationships between intracoronary vascular ultrasound measurements and three key cardiovascular parameters: epicardial fat pad thickness, mono-platelet polymer levels, and small dense low-density lipoprotein cholesterol (sdLDL-C) levels. Methods: In this investigation, we applied a comprehensive method to evaluate atherosclerotic plaque characteristics in patients with diverse stages of coronary heart disease (CHD), contrasting these profiles with those of healthy individuals. Our study included 80 acute myocardial infarction (AMI) patients, 145 with unstable angina pectoris (UAP), 175 with stable angina pectoris (SAP), and 100 controls. We utilized intravascular ultrasound (IVUS), an advanced imaging technique that surpasses traditional angiography by providing detailed, high-resolution images of both the coronary artery lumen and wall, including plaque composition. This approach is pivotal for assessing plaque stability, a key factor in the risk of rupture and subsequent cardiovascular events, indicated by features like lipid-rich cores and thin fibrous caps. During IVUS, we quantified parameters such as plaque area, load, and the remodeling index, the latter offering insights into vascular adaptation to plaque buildup. Additionally, we conducted a correlation analysis between IVUS indices and three cardiovascular markers: epicardial fat pad thickness, monocyte-platelet aggregates, and sdLDL-C levels. The goal was to ascertain the predictive value of these markers in tandem with IVUS for determining the stability of coronary artery atherosclerotic plaques. This integrative approach enhances understanding of plaque formation and destabilization, potentially informing more effective CHD prevention and management strategies. Results: Our study revealed distinct variations in key parameters across patient groups with different forms of CHD and healthy controls. Notably, we observed significant differences in gender distribution, hypertension, and diabetes mellitus prevalence among these groups. In terms of IVUS indexes and cardiovascular parameters, the SAP group exhibited markedly different results compared to the AMI and UAP groups. Specifically, the SAP patients showed the lowest values for EMMA, plaque area, plaque burden, reconstruction index, and positive remodeling. Additionally, they exhibited the thickest fibrous caps. In contrast, the AMI and UAP groups presented similar outcomes in these aspects. Regarding the epicardial fat pad thickness, the positive rate of monocyte-platelet aggregates, and the levels of sdLDL-C, there were no significant differences between the AMI and UAP groups. However, these parameters were notably higher in the AMI and UAP groups compared to the SAP group. Crucially, we established a significant correlation between the thickness of the epicardial fat pad, the positive rate of monocyte-platelet aggregates, and the sdLDL-C levels with plaque loading rate and remodeling index. These correlations underscore the potential utility of these parameters as indicators of plaque stability and cardiovascular risk in patients with CHD. This highlights the complexity of atherosclerotic disease progression and underscores the importance of a multifaceted approach to assessing and managing CHD. Conclusion: Our research delineates the critical role of the remodeling index, epicardial fat pad thickness, monocyte-platelet aggregates, and sdLDL-C levels as key prognostic tools for assessing coronary plaque stability in coronary artery disease (CAD). These biomarkers collectively provide an enhanced perspective on plaque vulnerability, an essential aspect in the genesis of acute coronary events. Clinically, these findings are pivotal. They offer a refined approach to CAD management and risk evaluation, allowing for the precise identification of patients at increased risk of plaque rupture, a precursor to acute coronary syndromes. This precision facilitates the adoption of more individualized treatment strategies, focusing on aggressive interventions for high-risk patients and more conservative management for those with stable plaques.

Leading and following: Noise differently affects semantic and acoustic processing during naturalistic speech comprehension.

Despite the distortion of speech signals caused by unavoidable noise in daily life, our ability to comprehend speech in noisy environments is relatively stable. However, the neural mechanisms underlying reliable speech-in-noise comprehension remain to be elucidated. The present study investigated the neural tracking of acoustic and semantic speech information during noisy naturalistic speech comprehension. Participants listened to narrative audio recordings mixed with spectrally matched stationary noise at three signal-to-ratio (SNR) levels (no noise, 3 dB, -3 dB), and 60-channel electroencephalography (EEG) signals were recorded. A temporal response function (TRF) method was employed to derive event-related-like responses to the continuous speech stream at both the acoustic and the semantic levels. Whereas the amplitude envelope of the naturalistic speech was taken as the acoustic feature, word entropy and word surprisal were extracted via the natural language processing method as two semantic features. Theta-band frontocentral TRF responses to the acoustic feature were observed at around 400 ms following speech fluctuation onset over all three SNR levels, and the response latencies were more delayed with increasing noise. Delta-band frontal TRF responses to the semantic feature of word entropy were observed at around 200 to 600 ms leading to speech fluctuation onset over all three SNR levels. The response latencies became more leading with increasing noise and decreasing speech comprehension and intelligibility. While the following responses to speech acoustics were consistent with previous studies, our study revealed the robustness of leading responses to speech semantics, which suggests a possible predictive mechanism at the semantic level for maintaining reliable speech comprehension in noisy environments.

Content Analysis of Nicotine Poisoning (Nic Sick) Videos on TikTok: Retrospective Observational Infodemiology Study.

BACKGROUND: TikTok is a microvideo social media platform currently experiencing rapid growth and with 60% of its monthly users between the ages of 16 and 24 years. Increased exposure to e-cigarette content on social media may influence patterns of use, including the risk of overconsumption and possible nicotine poisoning, when users engage in trending challenges online. However, there is limited research assessing the characteristics of nicotine poisoning-related content posted on social media. OBJECTIVE: We aimed to assess the characteristics of content on TikTok that is associated with a popular nicotine poisoning-related hashtag. METHODS: We collected TikTok posts associated with the hashtag #nicsick, using a Python programming package (Selenium) and used an inductive coding approach to analyze video content and characteristics of interest. Videos were manually annotated to generate a codebook of the nicotine sickness-related themes. Statistical analysis was used to compare user engagement characteristics and video length in content with and without active nicotine sickness TikTok topics. RESULTS: A total of 132 TikTok videos associated with the hashtag #nicsick were manually coded, with 52.3% (69/132) identified as discussing firsthand and secondhand reports of suspected nicotine poisoning symptoms and experiences. More than one-third of nicotine poisoning-related content (26/69, 37.68%) portrayed active vaping by users, which included content with vaping behavior such as vaping tricks and overconsumption, and 43% (30/69) of recorded users self-reported experiencing nicotine sickness, poisoning, or adverse events such as vomiting following nicotine consumption. The average follower count of users posting content related to nicotine sickness was significantly higher than that for users posting content unrelated to nicotine sickness (W=2350.5, P=.03). CONCLUSIONS: TikTok users openly discuss experiences, both firsthand and secondhand, with nicotine adverse events via the #nicsick hashtag including reports of overconsumption resulting in sickness. These study results suggest that there is a need to assess the utility of digital surveillance on emerging social media platforms for vaping adverse events, particularly on sites popular among youth and young adults. As vaping product use-patterns continue to evolve, digital adverse event detection likely represents an important tool to supplement traditional methods of public health surveillance (such as poison control center prevalence numbers).