1.Research progress of NLRP3 inflammasome inhibitors
Chen-Guang LI ; Feng-Yi MAI ; Jing-Rong LIANG ; Wen-Tao YANG ; Jie GUO ; Jun-Xiang SHU ; Li-Zu XIAO
Chinese Pharmacological Bulletin 2024;40(10):1801-1808
NLRP3 can recruit proteins such as ASC and pro-caspase1 to form NLRP3 inflammasomes after being stimulated by pathogen and danger signals in vivo,and then induce pyropto-sis and promote the inflammatory reactions to maintain the home-ostasis.However,the overactivation of NLRP3 inflammasomes is closely related to many inflammatory and autoimmune diseases in humans.Targeted inhibition of NLRP3 inflammasomes can sig-nificantly inhibit inflammation and alleviate the relative symp-toms.Therefore,it is an important research direction for treating diseases of NLRP3 inflammasome that searching for effective in-hibitors targeting NLRP3 inflammasome activation and achieving clinical transformation.This review summarizes the latest re-search progress based on the sources of NLRP3 inflammasome inhibitors.
2.A Retrospective Study of the Effect of Spinopelvic Parameters on Fatty Infiltration in Paraspinal Muscles in Patients With Lumbar Spondylolisthesis
Jia-Chen YANG ; Jia-Yu CHEN ; Yin DING ; Yong-Jie YIN ; Zhi-Ping HUANG ; Xiu-Hua WU ; Zu-Cheng HUANG ; Yi-Kai LI ; Qing-An ZHU
Neurospine 2024;21(1):223-230
Objective:
The effect on fat infiltration (FI) of paraspinal muscles in degenerative lumbar spinal diseases has been demonstrated except for spinopelvic parameters. The present study is to identify the effect of spinopelvic parameters on FI of paraspinal muscle (PSM) and psoas major muscle (PMM) in patients with degenerative lumbar spondylolisthesis.
Methods:
A single-center, retrospective cross-sectional study of 160 patients with degenerative lumbar spondylolisthesis (DLS) and lumbar stenosis (LSS) who had lateral full-spine x-ray and lumbar spine magnetic resonance imaging was conducted. PSM and PMM FIs were defined as the ratio of fat to its muscle cross-sectional area. The FIs were compared among patients with different pelvic tilt (PT) and pelvic incidence (PI), respectively.
Results:
The PSM FI correlated significantly with pelvic parameters in DLS patients, but not in LSS patients. The PSM FI in pelvic retroversion (PT > 25°) was 0.54 ± 0.13, which was significantly higher in DLS patients than in normal pelvis (0.41 ± 0.14) and pelvic anteversion (PT < 5°) (0.34 ± 0.12). The PSM FI of DLS patients with large PI ( > 60°) was 0.50 ± 0.13, which was higher than those with small ( < 45°) and normal PI (0.37 ± 0.11 and 0.36 ± 0.13). However, the PSM FI of LSS patients didn’t change significantly with PT or PI. Moreover, the PMM FI was about 0.10–0.15, which was significantly lower than the PSM FI, and changed with PT and PI in a similar way of PSM FI with much less in magnitude.
Conclusion
FI of the PSMs increased with greater pelvic retroversion or larger pelvic incidence in DLS patients, but not in LSS patients.
3.A Retrospective Study of the Effect of Spinopelvic Parameters on Fatty Infiltration in Paraspinal Muscles in Patients With Lumbar Spondylolisthesis
Jia-Chen YANG ; Jia-Yu CHEN ; Yin DING ; Yong-Jie YIN ; Zhi-Ping HUANG ; Xiu-Hua WU ; Zu-Cheng HUANG ; Yi-Kai LI ; Qing-An ZHU
Neurospine 2024;21(1):223-230
Objective:
The effect on fat infiltration (FI) of paraspinal muscles in degenerative lumbar spinal diseases has been demonstrated except for spinopelvic parameters. The present study is to identify the effect of spinopelvic parameters on FI of paraspinal muscle (PSM) and psoas major muscle (PMM) in patients with degenerative lumbar spondylolisthesis.
Methods:
A single-center, retrospective cross-sectional study of 160 patients with degenerative lumbar spondylolisthesis (DLS) and lumbar stenosis (LSS) who had lateral full-spine x-ray and lumbar spine magnetic resonance imaging was conducted. PSM and PMM FIs were defined as the ratio of fat to its muscle cross-sectional area. The FIs were compared among patients with different pelvic tilt (PT) and pelvic incidence (PI), respectively.
Results:
The PSM FI correlated significantly with pelvic parameters in DLS patients, but not in LSS patients. The PSM FI in pelvic retroversion (PT > 25°) was 0.54 ± 0.13, which was significantly higher in DLS patients than in normal pelvis (0.41 ± 0.14) and pelvic anteversion (PT < 5°) (0.34 ± 0.12). The PSM FI of DLS patients with large PI ( > 60°) was 0.50 ± 0.13, which was higher than those with small ( < 45°) and normal PI (0.37 ± 0.11 and 0.36 ± 0.13). However, the PSM FI of LSS patients didn’t change significantly with PT or PI. Moreover, the PMM FI was about 0.10–0.15, which was significantly lower than the PSM FI, and changed with PT and PI in a similar way of PSM FI with much less in magnitude.
Conclusion
FI of the PSMs increased with greater pelvic retroversion or larger pelvic incidence in DLS patients, but not in LSS patients.
4.A Retrospective Study of the Effect of Spinopelvic Parameters on Fatty Infiltration in Paraspinal Muscles in Patients With Lumbar Spondylolisthesis
Jia-Chen YANG ; Jia-Yu CHEN ; Yin DING ; Yong-Jie YIN ; Zhi-Ping HUANG ; Xiu-Hua WU ; Zu-Cheng HUANG ; Yi-Kai LI ; Qing-An ZHU
Neurospine 2024;21(1):223-230
Objective:
The effect on fat infiltration (FI) of paraspinal muscles in degenerative lumbar spinal diseases has been demonstrated except for spinopelvic parameters. The present study is to identify the effect of spinopelvic parameters on FI of paraspinal muscle (PSM) and psoas major muscle (PMM) in patients with degenerative lumbar spondylolisthesis.
Methods:
A single-center, retrospective cross-sectional study of 160 patients with degenerative lumbar spondylolisthesis (DLS) and lumbar stenosis (LSS) who had lateral full-spine x-ray and lumbar spine magnetic resonance imaging was conducted. PSM and PMM FIs were defined as the ratio of fat to its muscle cross-sectional area. The FIs were compared among patients with different pelvic tilt (PT) and pelvic incidence (PI), respectively.
Results:
The PSM FI correlated significantly with pelvic parameters in DLS patients, but not in LSS patients. The PSM FI in pelvic retroversion (PT > 25°) was 0.54 ± 0.13, which was significantly higher in DLS patients than in normal pelvis (0.41 ± 0.14) and pelvic anteversion (PT < 5°) (0.34 ± 0.12). The PSM FI of DLS patients with large PI ( > 60°) was 0.50 ± 0.13, which was higher than those with small ( < 45°) and normal PI (0.37 ± 0.11 and 0.36 ± 0.13). However, the PSM FI of LSS patients didn’t change significantly with PT or PI. Moreover, the PMM FI was about 0.10–0.15, which was significantly lower than the PSM FI, and changed with PT and PI in a similar way of PSM FI with much less in magnitude.
Conclusion
FI of the PSMs increased with greater pelvic retroversion or larger pelvic incidence in DLS patients, but not in LSS patients.
5.A Retrospective Study of the Effect of Spinopelvic Parameters on Fatty Infiltration in Paraspinal Muscles in Patients With Lumbar Spondylolisthesis
Jia-Chen YANG ; Jia-Yu CHEN ; Yin DING ; Yong-Jie YIN ; Zhi-Ping HUANG ; Xiu-Hua WU ; Zu-Cheng HUANG ; Yi-Kai LI ; Qing-An ZHU
Neurospine 2024;21(1):223-230
Objective:
The effect on fat infiltration (FI) of paraspinal muscles in degenerative lumbar spinal diseases has been demonstrated except for spinopelvic parameters. The present study is to identify the effect of spinopelvic parameters on FI of paraspinal muscle (PSM) and psoas major muscle (PMM) in patients with degenerative lumbar spondylolisthesis.
Methods:
A single-center, retrospective cross-sectional study of 160 patients with degenerative lumbar spondylolisthesis (DLS) and lumbar stenosis (LSS) who had lateral full-spine x-ray and lumbar spine magnetic resonance imaging was conducted. PSM and PMM FIs were defined as the ratio of fat to its muscle cross-sectional area. The FIs were compared among patients with different pelvic tilt (PT) and pelvic incidence (PI), respectively.
Results:
The PSM FI correlated significantly with pelvic parameters in DLS patients, but not in LSS patients. The PSM FI in pelvic retroversion (PT > 25°) was 0.54 ± 0.13, which was significantly higher in DLS patients than in normal pelvis (0.41 ± 0.14) and pelvic anteversion (PT < 5°) (0.34 ± 0.12). The PSM FI of DLS patients with large PI ( > 60°) was 0.50 ± 0.13, which was higher than those with small ( < 45°) and normal PI (0.37 ± 0.11 and 0.36 ± 0.13). However, the PSM FI of LSS patients didn’t change significantly with PT or PI. Moreover, the PMM FI was about 0.10–0.15, which was significantly lower than the PSM FI, and changed with PT and PI in a similar way of PSM FI with much less in magnitude.
Conclusion
FI of the PSMs increased with greater pelvic retroversion or larger pelvic incidence in DLS patients, but not in LSS patients.
6.A Retrospective Study of the Effect of Spinopelvic Parameters on Fatty Infiltration in Paraspinal Muscles in Patients With Lumbar Spondylolisthesis
Jia-Chen YANG ; Jia-Yu CHEN ; Yin DING ; Yong-Jie YIN ; Zhi-Ping HUANG ; Xiu-Hua WU ; Zu-Cheng HUANG ; Yi-Kai LI ; Qing-An ZHU
Neurospine 2024;21(1):223-230
Objective:
The effect on fat infiltration (FI) of paraspinal muscles in degenerative lumbar spinal diseases has been demonstrated except for spinopelvic parameters. The present study is to identify the effect of spinopelvic parameters on FI of paraspinal muscle (PSM) and psoas major muscle (PMM) in patients with degenerative lumbar spondylolisthesis.
Methods:
A single-center, retrospective cross-sectional study of 160 patients with degenerative lumbar spondylolisthesis (DLS) and lumbar stenosis (LSS) who had lateral full-spine x-ray and lumbar spine magnetic resonance imaging was conducted. PSM and PMM FIs were defined as the ratio of fat to its muscle cross-sectional area. The FIs were compared among patients with different pelvic tilt (PT) and pelvic incidence (PI), respectively.
Results:
The PSM FI correlated significantly with pelvic parameters in DLS patients, but not in LSS patients. The PSM FI in pelvic retroversion (PT > 25°) was 0.54 ± 0.13, which was significantly higher in DLS patients than in normal pelvis (0.41 ± 0.14) and pelvic anteversion (PT < 5°) (0.34 ± 0.12). The PSM FI of DLS patients with large PI ( > 60°) was 0.50 ± 0.13, which was higher than those with small ( < 45°) and normal PI (0.37 ± 0.11 and 0.36 ± 0.13). However, the PSM FI of LSS patients didn’t change significantly with PT or PI. Moreover, the PMM FI was about 0.10–0.15, which was significantly lower than the PSM FI, and changed with PT and PI in a similar way of PSM FI with much less in magnitude.
Conclusion
FI of the PSMs increased with greater pelvic retroversion or larger pelvic incidence in DLS patients, but not in LSS patients.
7.Association between cardiometabolic diseases and quality of life and the mediation effect of perceived stress.
Ya Ling ZHAO ; Hao HUANG ; Jiao MA ; Qian ZHANG ; Ya Qiong WANG ; Chen Jie SUN ; Ziyi YANG ; Lei Lei PEI ; Fang Yao CHEN ; Yuan GAO ; Zu Yi YUAN ; Yi Hui XIAO
Chinese Journal of Cardiology 2023;51(7):709-715
Objective: To explore the association between cardiometabolic diseases (CMD) and quality of life, the association between CMD and perceived stress, and the mediation effect of perceived stress on the association between CMD and quality of life, and to provide evidence for the prevention and treatment of CMD and the improvement of quality of life in these patients. Methods: This is a cross-sectional study. Data were collected by the employees' physical examination of a company in Xi'an in 2021. Multiple linear regression models were used to analyze the association between the status of CMD (divided into three categories: no CMD, presence of one kind of CMD, and with≥2 kinds of CMD (≥2 kinds of CMD were defined as cardiometabolic multimorbidity (CMM)), quality of life, and perceived stress. Mediation analysis with a multi-categorical independent variable was conducted to determine the mediation effect of perceived stress on the association between CMD and quality of life. Results: Among all 4 272 participants, 1 457 (34.1%) participants had one kind of CMD and 677 (15.8%) participants had CMM. The average scores for quality of life and perceived stress were (57.5±15.7) and (16.9±7.9), respectively. Compared with participants without CMD, after adjusting for demographic and lifestyle factors, no statistically significant associations were observed between one kind of CMD and perceived stress or quality of life (both P>0.05). Perceived stress did not mediate the association between one kind of CMD and quality of life. However, participants with CMM had lower quality of life and higher perceived stress than participants without CMD. The relative total effect coefficient c (95%CI) and the relative direct effect coefficient c' (95%CI) between CMM and quality of life were -3.71 (-5.04--2.37) and -2.52 (-3.81--1.24) (both P<0.05), respectively. The relative indirect effect coefficient a2b (95%CI) of perceived stress on the association between CMM and quality of life was -1.18 (-1.62--0.77) (P<0.05). The mediation effect size was 31.8%. Conclusions: CMM is negatively associated with quality of life and positively associated with perceived stress. Perceived stress partially mediates the association between CMM and quality of life. Our results suggest that, in addition to preventing and treating CMM actively, efforts should be taken to relieve the perceived stress of people with CMM to improve their quality of life.
Humans
;
Quality of Life
;
Cross-Sectional Studies
;
Cardiovascular Diseases/complications*
;
Stress, Psychological
8.Similarities and differences of myocardial metabolic characteristics between HFpEF and HFrEF mice based on LC-MS/MS metabolomics.
Zhan Yi ZHANG ; Xue Ying FENG ; Zi Hao WANG ; Yu Zhi HUANG ; Wen Bo YANG ; Wen Jiao ZHANG ; Juan ZHOU ; Zu Yi YUAN
Chinese Journal of Cardiology 2023;51(7):722-730
Objective: To reveal the similarities and differences in myocardial metabolic characteristics between heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF) mice using metabolomics. Methods: The experimental mice were divided into 4 groups, including control, HFpEF, sham and HFrEF groups (10 mice in each group). High fat diet and Nω-nitroarginine methyl ester hydrochloride (L-NAME) were applied to construct a"two-hit"HFpEF mouse model. Transverse aortic constriction (TAC) surgery was used to construct the HFrEF mouse model. The differential expression of metabolites in the myocardium of HFpEF and HFrEF mice was detected by untargeted metabolomics (UHPLC-QE-MS). Variable importance in projection>1 and P<0.05 were used as criteria to screen and classify the differentially expressed metabolites between the mice models. KEGG functional enrichment and pathway impact analysis demonstrated significantly altered metabolic pathways in both HFpEF and HFrEF mice. Results: One hundred and nine differentially expressed metabolites were detected in HFpEF mice, and 270 differentially expressed metabolites were detected in HFrEF mice. Compared with the control group, the most significantly changed metabolite in HFpEF mice was glycerophospholipids, while HFrEF mice presented with the largest proportion of carboxylic acids and their derivatives. KEGG enrichment and pathway impact analysis showed that the differentially expressed metabolites in HFpEF mice were mainly enriched in pathways such as biosynthesis of unsaturated fatty acids, ether lipid metabolism, amino sugar and nucleotide sugar metabolism, glycerophospholipid metabolism, arachidonic acid metabolism and arginine and proline metabolism. The differentially expressed metabolites in HFrEF mice were mainly enriched in arginine and proline metabolism, glycine, serine and threonine metabolism, pantothenate and CoA biosynthesis, glycerophospholipid metabolism, nicotinate and nicotinamide metabolism and arachidonic acid metabolism, etc. Conclusions: HFpEF mice have a significantly different myocardial metabolite expression profile compared with HFrEF mice. In addition, biosynthesis of unsaturated fatty acids, arachidonic acid metabolism, glycerophospholipid metabolism and arginine and proline metabolism are significantly altered in both HFpEF and HFrEF mice, suggesting that these metabolic pathways may play an important role in disease progression in both types of heart failure.
Mice
;
Animals
;
Heart Failure/metabolism*
;
Stroke Volume
;
Chromatography, Liquid
;
Tandem Mass Spectrometry
;
Metabolomics
;
Arachidonic Acids
;
Proline
10.Development and validation of a deep learning model to screen hypokalemia from electrocardiogram in emergency patients.
Chen-Xi WANG ; Yi-Chu ZHANG ; Qi-Lin KONG ; Zu-Xiang WU ; Ping-Ping YANG ; Cai-Hua ZHU ; Shou-Lin CHEN ; Tao WU ; Qing-Hua WU ; Qi CHEN
Chinese Medical Journal 2021;134(19):2333-2339
BACKGROUND:
A deep learning model (DLM) that enables non-invasive hypokalemia screening from an electrocardiogram (ECG) may improve the detection of this life-threatening condition. This study aimed to develop and evaluate the performance of a DLM for the detection of hypokalemia from the ECGs of emergency patients.
METHODS:
We used a total of 9908 ECG data from emergency patients who were admitted at the Second Affiliated Hospital of Nanchang University, Jiangxi, China, from September 2017 to October 2020. The DLM was trained using 12 ECG leads (lead I, II, III, aVR, aVL, aVF, and V1-6) to detect patients with serum potassium concentrations <3.5 mmol/L and was validated using retrospective data from the Jiangling branch of the Second Affiliated Hospital of Nanchang University. The blood draw was completed within 10 min before and after the ECG examination, and there was no new or ongoing infusion during this period.
RESULTS:
We used 6904 ECGs and 1726 ECGs as development and internal validation data sets, respectively. In addition, 1278 ECGs from the Jiangling branch of the Second Affiliated Hospital of Nanchang University were used as external validation data sets. Using 12 ECG leads (leads I, II, III, aVR, aVL, aVF, and V1-6), the area under the receiver operating characteristic curve (AUC) of the DLM was 0.80 (95% confidence interval [CI]: 0.77-0.82) for the internal validation data set. Using an optimal operating point yielded a sensitivity of 71.4% and a specificity of 77.1%. Using the same 12 ECG leads, the external validation data set resulted in an AUC for the DLM of 0.77 (95% CI: 0.75-0.79). Using an optimal operating point yielded a sensitivity of 70.0% and a specificity of 69.1%.
CONCLUSIONS
In this study, using 12 ECG leads, a DLM detected hypokalemia in emergency patients with an AUC of 0.77 to 0.80. Artificial intelligence could be used to analyze an ECG to quickly screen for hypokalemia.
Artificial Intelligence
;
Deep Learning
;
Electrocardiography
;
Humans
;
Hypokalemia/diagnosis*
;
Retrospective Studies

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