Until now, few articles have revealed the potential roles of innate lymphoid cells (ILCs) in cardiovascular diseases. However, the infiltration of ILC subsets in ischemic myocardium, the roles of ILC ...subsets in myocardial infarction (MI) and myocardial ischemia-reperfusion injury (MIRI) and the related cellular and molecular mechanisms have not been described with a sufficient level of detail.
In the current study, 8-week-old male C57BL/6J mice were divided into three groups: MI, MIRI and sham group. Single-cell sequencing technology was used to perform dimensionality reduction clustering of ILC to analyze the ILC subset landscape at a single-cell resolution, and finally flow cytometry was used to confirm the existence of the new ILC subsets in different disease groups.
Five ILC subsets were found, including ILC1, ILC2a, ILC2b, ILCdc and ILCt. It is worth noting that ILCdc, ILC2b and ILCt were identified as new ILC subclusters in the heart. The cellular landscapes of ILCs were revealed and signal pathways were predicted. Furthermore, pseudotime trajectory analysis exhibited different ILC statuses and traced related gene expression in normal and ischemic conditions. In addition, we established a ligand-receptor-transcription factor-target gene regulatory network to disclose cell communications among ILC clusters. Moreover, we further revealed the transcriptional features of the ILCdc and ILC2a subsets. Finally, the existence of ILCdc was confirmed by flow cytometry.
Collectively, by characterizing the spectrums of ILC subclusters, our results provide a new blueprint for understanding ILC subclusters' roles in myocardial ischemia diseases and further potential treatment targets.
According to some recent observational studies, the gut microbiota influences atherosclerosis via the gut microbiota-artery axis. However, the causal role of the gut microbiota in atherosclerosis ...remains unclear. Therefore, we used a Mendelian randomization (MR) strategy to try to dissect this causative link.
The biggest known genome-wide association study (GWAS) (n = 13,266) from the MiBioGen collaboration was used to provide summary data on the gut microbiota for a two-sample MR research. Data on atherosclerosis were obtained from publicly available GWAS data from the FinnGen consortium, including cerebral atherosclerosis (104 cases and 218,688 controls), coronary atherosclerosis (23,363 cases and 187,840 controls), and peripheral atherosclerosis (6631 cases and 162,201 controls). The causal link between gut microbiota and atherosclerosis was investigated using inverse variance weighting, MR-Egger, weighted median, weighted mode, and simple mode approaches, among which inverse variance weighting was the main research method. Cochran's Q statistic was used to quantify the heterogeneity of instrumental variables (IVs), and the MR Egger intercept test was used to assess the pleiotropy of IVs.
Inverse-variance-weighted (IVW) estimation showed that
had a protective influence on cerebral atherosclerosis (OR = 0.10, 95% CI: 0.01-0.67,
= 0.018), while
(OR = 5.39, 95% CI: 1.50-19.37,
= 0.010),
(OR = 6.87, 95% CI: 1.60-29.49,
= 0.010),
(OR = 2.88, 95% CI: 1.18-7.05,
= 0.021), and
(OR = 5.26, 95% CI: 1.28-21.61,
= 0.021) had pathogenic effects on cerebral atherosclerosis. For
(OR = 0.87, 95% CI: 0.76-0.99,
= 0.039), the
(OR = 0.89, 95% CI: 0.80-1.00,
= 0.048), the
(OR = 0.80, 95% CI: 0.69-0.94,
= 0.006), and the
(OR = 0.87, 95% CI: 0.77-0.98,
= 0.023) were protective against coronary atherosclerosis. However, the
(OR = 1.12, 95% CI: 1.00-1.24,
= 0.049) had a pathogenic effect on coronary atherosclerosis. Finally,
(OR = 0.83, 95% CI: 0.69-0.99,
= 0.036),
(OR = 0.76, 95% CI: 0.61-0.94,
= 0.013),
(OR = 0.76, 95% CI: 0.60-0.96,
= 0.022), and
(OR = 0.65, 95% CI: 0.46-0.92,
= 0.013), these four microbiota have a protective effect on peripheral atherosclerosis. However, for the
(OR = 1.25, 95% CI: 1.01-1.56,
= 0.040) and the
(OR = 1.22, 95% CI: 1.04-1.42,
= 0.016), there is a pathogenic role for peripheral atherosclerosis. No heterogeneity was found for instrumental variables, and no considerable horizontal pleiotropy was observed.
We discovered that the presence of probiotics and pathogens in the host is causally associated with atherosclerosis, and atherosclerosis at different sites is causally linked to specific gut microbiota. The specific gut microbiota associated with atherosclerosis identified by Mendelian randomization studies provides precise clinical targets for the treatment of atherosclerosis. In the future, we can further examine the gut microbiota's therapeutic potential for atherosclerosis if we have a better grasp of the causal relationship between it and atherosclerosis.
Abstract
Purpose
To explore the association between uric acid and urinary prostaglandins in male patients with hyperuricemia.
Methods
A total of 38 male patients with hyperuricemia in outpatients of ...Huadong Hospital from July 2018 to January 2020 were recruited. Serum uric acid (SUA), 24 h urinary uric acid excretion and other indicators were detected respectively. 10 ml urine was taken to determine prostaglandin prostaglandin D (PGD), prostaglandin E1 (PGE1), prostaglandin E2 (PGE2), 6-keto-PGF1α, thromboxane A2 (TXA2) and thromboxane B2 (TXB2). Fraction of uric acid excretion (FEua) and uric acid clearance rate (Cua) were calculated. According to the mean value of FEua and Cua, patients were divided into two groups, respectively. The independent-samples
t
test and the Mann–Whitney U test were applied for normally and non-normally distributed data, respectively.
Results
After adjusting confounding factors (age, BMI, eGFR, TG, TC, HDL and LDL), SUA was negatively correlated with urinary PGE1(
r
= -0.615,
P
= 0.009) and PGE2(
r
= -0.824,
P
< 0.001). Compared with SUA1 group (SUA < 482.6 mg/dl), SUA2 (SUA
$$\ge$$
≥
482.6 mg/dl) had lower urinary PGE1(
P
= 0.022) and PGE2(
P
= 0.019) levels. Cua was positively correlated with PGE2 (
r
= 0.436,
P
= 0.01). The correlation persisted after adjustment for age, BMI, eGFR, TG, TC, HDL and LDL by multiple linear regression analysis. In the Cua1 group (Cua < 4.869 mL /min/1.73 m
2
), PGE2 were lower than that in Cua2 (Cua
$$\ge$$
≥
4.869 mL /min/1.73 m
2
) group (
P
= 0.011).
Conclusions
In male patients with hyperuricemia, SUA was negatively correlated with urinary PGE2, Cua was positively correlated with urinary PGE2. Urinary PGE2 were significantly different between different SUA and Cua groups.
Atherosclerosis is mediated by various factors and plays an important pathological foundation for cardiovascular and cerebrovascular diseases. Abnormal vascular smooth muscle cells (VSMCs) ...proliferation and migration have an essential role in atherosclerotic lesion formation. Circular RNAs (circRNA) have been widely detected in different species and are closely related to various diseases. However, the expression profiles and molecular regulatory mechanisms of circRNAs in VSMCs are still unknown. We used high-throughput RNA-seq as well as bioinformatics tools to systematically analyze circRNA expression profiles in samples from different VSMC phenotypes. Polymerase chain reaction (PCR), Sanger sequencing, and qRT-PCR were performed for circRNA validation. A total of 22191 circRNAs corresponding to 6273 genes (host genes) in the platelet-derived growth factor (PDGF-BB) treated group, the blank control group or both groups, were detected, and 112 differentially expressed circRNAs were identified between the PDGF-BB treated and control groups, of which 59 were upregulated, and 53 were downregulated. We selected 9 circRNAs for evaluation of specific head-to-tail splicing, and 10 differentially expressed circRNAs between the two groups for qRT-PCR validation. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses enrichment analyses revealed that the parental genes of the circRNAs mainly participated in cardiac myofibril assembly and positive regulation of DNA-templated transcription, indicating that they might be involved in cardiovascular diseases. Finally, we constructed a circRNA-miRNA network based on the dysregulated circRNAs and VSMC-related microRNAs. Our study is the first to show the differential expression of circRNAs in PDGF-BB-induced VSMCs and may provide new ideas and targets for the prevention and therapy of vascular diseases.
Acute myocardial infarction (AMI) is one of the main fatal diseases of cardiovascular diseases. Circular RNA (circRNA) is a non-coding RNA (ncRNA), which plays a role in cardiovascular disease as a ...competitive endogenous RNA (ceRNA). However, their role in AMI has not been fully clarified. This study aims to explore the mechanism of circRNA-related ceRNA network in AMI, and to identify the corresponding immune infiltration characteristics.
The circRNA (GSE160717), miRNA (GSE24548), and mRNA (GSE60993) microarray datasets of AMI were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed circRNAs (DEcircRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) were identified by the "limma" package. After integrating the circRNA, miRNA and mRNA interaction, we constructed a circRNA-miRNA-mRNA network. The "clusterProfiler" package and String database were used for functional enrichment analysis and protein-protein interaction (PPI) analysis, respectively. After that, we constructed a circRNA-miRNA-hub gene network and validated the circRNAs and mRNAs using an independent dataset (GSE61144) as well as qRT-PCR. Finally, we used CIBERSORTx database to analyze the immune infiltration characteristics of AMI and the correlation between hub genes and immune cells.
Using the "limma" package of the R, 83 DEcircRNAs, 54 DEmiRNAs, and 754 DEmRNAs were identified in the microarray datasets of AMI. Among 83 DEcircRNAs, there are 55 exonic DEcircRNAs. Then, a circRNA-miRNA-mRNA network consists of 21 DEcircRNAs, 11 DEmiRNAs, and 106 DEmRNAs were predicted by the database. After that, 10 hub genes from the PPI network were identified. Then, a new circRNA-miRNA-hub gene network consists of 14 DEcircRNAs, 7 DEmiRNAs, and 9 DEmRNAs was constructed. After that, three key circRNAs (hsa_circ_0009018, hsa_circ_0030569 and hsa_circ_0031017) and three hub genes (BCL6, PTGS2 and PTEN) were identified from the network by qRT-PCR. Finally, immune infiltration analysis showed that hub genes were significantly positively correlated with up-regulated immune cells (neutrophils, macrophages and plasma cells) in AMI.
Our study constructed a circRNA-related ceRNA networks in AMI, consists of hsa_circ_0031017/hsa-miR-142-5p/PTEN axis, hsa_circ_0030569/hsa-miR-545/PTGS2 axis and hsa_circ_0009018/hsa-miR-139-3p/BCL6 axis. These three hub genes were significantly positively correlated with up-regulated immune cells (neutrophils, macrophages and plasma cells) in AMI. It helps improve understanding of AMI mechanism and provides future potential therapeutic targets.
Computerized methods have been developed that allow quantitative morphological analyses of whole slide images (WSIs), e.g., of immunohistochemical stains. The latter are attractive because they can ...provide high-resolution data on the distribution of proteins in tissue. However, many immunohistochemical results are complex because the protein of interest occurs in multiple locations (in different cells and also extracellularly). We have recently established an artificial intelligence framework, PathoFusion which utilises a bifocal convolutional neural network (BCNN) model for detecting and counting arbitrarily definable morphological structures. We have now complemented this model by adding an attention-based graph neural network (abGCN) for the advanced analysis and automated interpretation of such data. Classical convolutional neural network (CNN) models suffer from limitations when handling global information. In contrast, our abGCN is capable of creating a graph representation of cellular detail from entire WSIs. This abGCN method combines attention learning with visualisation techniques that pinpoint the location of informative cells and highlight cell-cell interactions. We have analysed cellular labelling for CD276, a protein of great interest in cancer immunology and a potential marker of malignant glioma cells/putative glioma stem cells (GSCs). We are especially interested in the relationship between CD276 expression and prognosis. The graphs permit predicting individual patient survival on the basis of GSC community features. Our experiments lay a foundation for the use of the BCNN-abGCN tool chain in automated diagnostic prognostication using immunohistochemically labelled histological slides, but the method is essentially generic and potentially a widely usable tool in medical research and AI based healthcare applications.
Mounting studies have shown that hyperuricemia is related to kidney diseases through multiple ways. However, the application of urinary uric acid indicators in patients with reduced renal function is ...not clear. In this study, we aim to determine the effects of renal function on various indicators reflecting uric acid levels in patients with chronic kidney disease (CKD).
Anthropometric and biochemical examinations were performed in 625 patients with CKD recruited from Dept of Nephrology of Huadong hospital affiliated to Fudan University. Multiple regression analyses were used to study correlations of the estimated glomerular filtration rate (eGFR) with serum uric acid (SUA) and renal handling of uric acid. For further study, smooth curve plots and threshold effect analyses were applied to clarify associations between renal function and uric acid levels.
The nonlinear relationships were observed between eGFR and urinary uric acid indicators. The obvious inflection points were observed in smooth curve fitting of eGFR and fractional excretion of uric acid (FEur), excretion of uric acid per volume of glomerular filtration (EurGF). In subsequent analyses where levels of eGFR< 15 mL/min/1.73m
were dichotomized (CKD5a/CKD5b), patients in the CKD5a showed higher levels of FEur and EurGF while lower levels of urinary uric acid excretion (UUA), clearance of uric acid (Cur) and glomerular filtration load of uric acid (FLur) compared with CKD5b group (all P < 0.05). And there was no significant difference of SUA levels between two groups. On the other hand, when eGFR< 109.9 ml/min/1.73 m
and 89.1 ml/min/1.73 m
, the resultant curves exhibited approximately linear associations of eGFR with Cur and FLur respectively.
FEur and EurGF showed significantly compensatory increases with decreased renal function. And extra-renal uric acid excretion may play a compensatory role in patients with severe renal impairment to maintain SUA levels. Moreover, Cur and FLur may be more reliable indicators of classification for hyperuricemia in CKD patients.
The separation and recycling of effective resources in Fischer-Tropsch wax residue (FTWR) are urgent because of the environmental hazards and energy waste they bring. In this study, organic solvents ...are used to separate recyclable resources from FTWR efficiently, achieving the goals of “Energy Recycle” and “Fisher-Tropsch Wax Residue Treatment”. The response surface methodology (RSM) response surface analysis model accurately evaluates the relationship among temperature, residence time, liquid–solid ratio, and desorption rate and obtains the best process parameters. The results show that the product yield can reach 82.28% under the conditions of 80 °C, 4 h, and the liquid–solid ratio of 24.4 mL/g. Through the kinetic analysis of the desorption process of FTWR, the results show that the desorption process conforms to the pseudo second-order kinetic model and the internal diffusion model. The thermodynamic function results showed that there were not only van der Waals forces in the desorption process, but other strong interaction forces such as hydrogen bonds. In addition, Langmuir, Freundlich, and BET equations are used to describe the desorption equilibrium. Scanning electron microscopy (SEM) were used to analyze the pore structure of FTWR during desorption. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and Gas chromatography-mass spectrometer (GC-MS) analysis confirmed that the desorption product’s main component was hydrocarbons (50.38 wt%). Furthermore, naphthenic (22.95 wt%), primary alcohol (11.62 wt%), esters (8.7 wt%), and aromatic hydrocarbons (6.35 wt%) compounds were found and can be further purified and applied to other industrial fields. This study shows that using petroleum ether to separate and recover clean resources from Fischer-Tropsch wax residue is feasible and efficient and has potential industrial application prospects.
Aim
To investigate the correlation of renal tubular inflammatory and injury markers with renal uric acid excretion in chronic kidney disease (CKD) patients.
Methods
Seventy-three patients with CKD ...were enrolled. Fasting blood and morning urine sample were collected for routine laboratory measurements. At the same time, 24 h of urine was collected for urine biochemistry analyses, and 10 ml was extracted from the 24-h urine sample to further detect renal tubular inflammatory and injury markers, including interleukin-18 (IL-18), interleukin 1β (IL-1β), neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule-1 (KIM-1). The patients were divided into three tertile groups according to their 24-h urinary uric acid (24-h UUA) levels (UUA1: 24-h UUA ≤ 393.12 mg; UUA2: 393.12 < 24-h UUA ≤ 515.76 mg; UUA3: 24-h UUA > 515.76 mg). The general clinical and biochemical indexes were compared. Multivariable linear regression models were used to test the association of IL-18/Urinary creatinine concentration (IL-18/CR), IL-1β/CR, NGAL/CR and KIM-1/CR with renal uric acid excretion indicators.
Results
All of tested renal tubular inflammation- and injury-related urinary markers were negatively associated with 24-h UUA and UEUA, and the negative correlation still persisted after adjusting for multiple influencing factors including urinary protein and eGFR. Further group analyses showed that these makers were significantly higher in the UUA1 than in the UUA3 group.
Conclusions
Our findings suggest that markers of urinary interstitial inflammation and injury in CKD patients are significantly correlated with 24-h UUA and Urinary excretion of uric acid (UEUA), and those with high 24-h UUA have lower levels of these markers. Renal uric acid excretion may also reflect the inflammation and injury of renal tubules under certain conditions.
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