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"Ji, Cheng"
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Uric Acid and Cardiovascular Disease: An Update From Molecular Mechanism to Clinical Perspective
Uric acid (UA) is the end product of purine nucleotide metabolism in the human body. Hyperuricemia is an abnormally high level of UA in the blood and may result in arthritis and gout. The prevalence of hyperuricemia has been increasing globally. Epidemiological studies have shown that UA levels are positively correlated with cardiovascular diseases, including hypertension, atherosclerosis, atrial fibrillation (AF), and heart failure (HF). Hyperuricemia promotes the occurrence and development of cardiovascular diseases by regulating molecular signals, such as inflammatory response, oxidative stress, insulin resistance/diabetes, endoplasmic reticulum stress, and endothelial dysfunction. Despite extensive research, the underlying molecular mechanisms are still unclear. Allopurinol, a xanthine oxidase (XO) inhibitor, has been shown to improve cardiovascular outcomes in patients with HF, coronary heart disease (CHD), type 2 diabetes (T2D), and left ventricular hypertrophy (LVH). Whether febuxostat, another XO inhibitor, can improve cardiovascular outcomes as well as allopurinol remains controversial. Furthermore, it is also not clear whether UA-lowering treatment (ULT) can benefit patients with asymptomatic hyperuricemia. In this review, we focus on the latest cellular and molecular findings of cardiovascular disease associated with hyperuricemia and clinical data about the efficacy of ULT in patients with cardiovascular disease.
Journal Article
Serum electrolyte concentrations and risk of atrial fibrillation: an observational and mendelian randomization study
Background
Atrial fibrillation (AF) is a prevalent arrhythmic condition resulting in increased stroke risk and is associated with high mortality. Electrolyte imbalance can increase the risk of AF, where the relationship between AF and serum electrolytes remains unclear.
Methods
A total of 15,792 individuals were included in the observational study, with incident AF ascertainment in the Atherosclerosis Risk in Communities (ARIC) study. The Cox regression models were applied to calculate the hazard ratio (HR) and 95% confidence interval (CI) for AF based on different serum electrolyte levels. Mendelian randomization (MR) analyses were performed to examine the causal association.
Results
In observational study, after a median 19.7 years of follow-up, a total of 2551 developed AF. After full adjustment, participants with serum potassium below the 5th percentile had a higher risk of AF relative to participants in the middle quintile. Serum magnesium was also inversely associated with the risk of AF. An increased incidence of AF was identified in individuals with higher serum phosphate percentiles. Serum calcium levels were not related to AF risk. Moreover, MR analysis indicated that genetically predicted serum electrolyte levels were not causally associated with AF risk. The odds ratio for AF were 0.999 for potassium, 1.044 for magnesium, 0.728 for phosphate, and 0.979 for calcium, respectively.
Conclusions
Serum electrolyte disorders such as hypokalemia, hypomagnesemia and hyperphosphatemia were associated with an increased risk of AF and may also serve to be prognostic factors. However, the present study did not support serum electrolytes as causal mediators for AF development.
Journal Article
Vibrational spectroscopic imaging of living systems: An emerging platform for biology and medicine
The vibrational spectra of biomolecules could in principle image cells and tissue without added markers. Practically, several technical problems need to be overcome to achieve sufficient imaging depths, resolution, and data acquisition speed. Cheng and Xie review emerging bioimaging methods for use in the lab and the clinic. Science , this issue p. 10.1126/science.aaa8870 Vibrational spectroscopy has been extensively applied to the study of molecules in gas phase, in condensed phase, and at interfaces. The transition from spectroscopy to spectroscopic imaging of living systems, which allows the spectrum of biomolecules to act as natural contrast, is opening new opportunities to reveal cellular machinery and to enable molecule-based diagnosis. Such a transition, however, involves more than a simple combination of spectrometry and microscopy. We review recent efforts that have pushed the boundary of the vibrational spectroscopic imaging field in terms of spectral acquisition speed, detection sensitivity, spatial resolution, and imaging depth. We further highlight recent applications in functional analysis of single cells and in label-free detection of diseases.
Journal Article
Molecular Factors and Pathways of Hepatotoxicity Associated with HIV/SARS-CoV-2 Protease Inhibitors
Antiviral protease inhibitors are peptidomimetic molecules that block the active catalytic center of viral proteases and, thereby, prevent the cleavage of viral polyprotein precursors into maturation. They continue to be a key class of antiviral drugs that can be used either as boosters for other classes of antivirals or as major components of current regimens in therapies for the treatment of infections with human immunodeficiency virus (HIV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, sustained/lifelong treatment with the drugs or drugs combined with other substance(s) often leads to severe hepatic side effects such as lipid abnormalities, insulin resistance, and hepatotoxicity. The underlying pathogenic mechanisms are not fully known and are under continuous investigation. This review focuses on the general as well as specific molecular mechanisms of the protease inhibitor-induced hepatotoxicity involving transporter proteins, apolipoprotein B, cytochrome P450 isozymes, insulin-receptor substrate 1, Akt/PKB signaling, lipogenic factors, UDP-glucuronosyltransferase, pregnane X receptor, hepatocyte nuclear factor 4α, reactive oxygen species, inflammatory cytokines, off-target proteases, and small GTPase Rab proteins related to ER-Golgi trafficking, organelle stress, and liver injury. Potential pharmaceutical/therapeutic solutions to antiviral drug-induced hepatic side effects are also discussed.
Journal Article
Plasmon-enhanced stimulated Raman scattering microscopy with single-molecule detection sensitivity
Stimulated Raman scattering (SRS) microscopy allows for high-speed label-free chemical imaging of biomedical systems. The imaging sensitivity of SRS microscopy is limited to ~10 mM for endogenous biomolecules. Electronic pre-resonant SRS allows detection of sub-micromolar chromophores. However, label-free SRS detection of single biomolecules having extremely small Raman cross-sections (~10
−30
cm
2
sr
−1
) remains unreachable. Here, we demonstrate plasmon-enhanced stimulated Raman scattering (PESRS) microscopy with single-molecule detection sensitivity. Incorporating pico-Joule laser excitation, background subtraction, and a denoising algorithm, we obtain robust single-pixel SRS spectra exhibiting single-molecule events, verified by using two isotopologues of adenine and further confirmed by digital blinking and bleaching in the temporal domain. To demonstrate the capability of PESRS for biological applications, we utilize PESRS to map adenine released from bacteria due to starvation stress. PESRS microscopy holds the promise for ultrasensitive detection and rapid mapping of molecular events in chemical and biomedical systems.
Stimulated Raman scattering (SRS) microscopy enables label-free chemical imaging at high speed, but has been limited by low sensitivity. Here, the authors demonstrate plasmon-enhanced SRS microscopy and achieve single molecule detection sensitivity.
Journal Article
Microsecond fingerprint stimulated Raman spectroscopic imaging by ultrafast tuning and spatial-spectral learning
Label-free vibrational imaging by stimulated Raman scattering (SRS) provides unprecedented insight into real-time chemical distributions. Specifically, SRS in the fingerprint region (400–1800 cm
−1
) can resolve multiple chemicals in a complex bio-environment. However, due to the intrinsic weak Raman cross-sections and the lack of ultrafast spectral acquisition schemes with high spectral fidelity, SRS in the fingerprint region is not viable for studying living cells or large-scale tissue samples. Here, we report a fingerprint spectroscopic SRS platform that acquires a distortion-free SRS spectrum at 10 cm
−1
spectral resolution within 20 µs using a polygon scanner. Meanwhile, we significantly improve the signal-to-noise ratio by employing a spatial-spectral residual learning network, reaching a level comparable to that with 100 times integration. Collectively, our system enables high-speed vibrational spectroscopic imaging of multiple biomolecules in samples ranging from a single live microbe to a tissue slice.
The authors employ a polygon-based ultrafast delay scanner and a deep learning framework for acquiring stimulated Raman scattering spectrum with high spectral and temporal resolution. They demonstrate high-speed imaging and tracking of multiple biomolecules in the fingerprint region.
Journal Article
A Review on Data-Driven Process Monitoring Methods: Characterization and Mining of Industrial Data
Safe and stable operation plays an important role in the chemical industry. Fault detection and diagnosis (FDD) make it possible to identify abnormal process deviations early and assist operators in taking proper action against fault propagation. After decades of development, data-driven process monitoring technologies have gradually attracted attention from process industries. Although many promising FDD methods have been proposed from both academia and industry, challenges remain due to the complex characteristics of industrial data. In this work, classical and recent research on data-driven process monitoring methods is reviewed from the perspective of characterizing and mining industrial data. The implementation framework of data-driven process monitoring methods is first introduced. State of art of process monitoring methods corresponding to common industrial data characteristics are then reviewed. Finally, the challenges and possible solutions for actual industrial applications are discussed.
Journal Article
The correlation of metacognitive ability, self‐directed learning ability and critical thinking in nursing students: A cross‐sectional study
Aim To understand the status quo of metacognitive ability (MA), Self‐directed learning (SDL) ability and critical thinking (CT) ability of five‐year higher vocational nursing students as well as the correlation among them. Background MA, SDL ability and CT are the core abilities that nursing students must have and they are the important factors to improve students’ nursing service quality and lifelong learning ability. Design A quantitative and cross‐sectional descriptive study. Method The survey collected data from 3,047 five‐year vocational nursing students with questionnaires April–May in 2020. Results The total score of MA was 81.18 (SD 13.51), SDL ability score was 220.28 (SD 35.09), and CT ability score was 271.96 (SD 26.08). The positive correlations were found between those three (p < .01). Conclusions The overall metacognitive ability of nursing students was not high, SDL ability and CT ability were both at a medium level. Health educators need pay attention to cultivation and development of the core competencies.
Journal Article