Publications by authors named "X Xie"

11,727 Publications

Association between greenness and dyslipidemia in patients with coronary heart disease: A proteomic approach.

Ecotoxicol Environ Saf 2022 Jan 15;231:113199. Epub 2022 Jan 15.

Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou 350122, China. Electronic address:

Background: Residential surrounding greenness may be protective of dyslipidemia are often theorized but remain poorly quantified. In particular, the underlying biological mechanisms of blood lipid changes with green spaces remain unclear.

Methods: Our observational epidemiology study included a residentially stable sample of 1035 coronary heart disease patients, and proteomics study included 16 participants. Normalized Difference Vegetation Index (NDVI) was used to evaluate residential greenness exposures. Proteomics technology was used to identify plasma greenness-related proteome disturbance, and the pathway analysis was employed to evaluate the potential biological mechanisms of greenness decreasing dyslipidemia risk.

Result: Higher residential surrounding greenness in the 500-m area was associated with lower risks of dyslipidemia (odds ratio (OR) = 0.871, 95% confidence interval (CI): 0.763, 0.994 for per one-quartile NDVI increase). Lymphocytes mediated 18.7% of the association between greenness and dyslipidemia. Greenness related proteins (including PLXDC1, IGFBP2 and LY6D) may regulate the biological functions of lipid metabolism and transport-related proteins (including ADIPOQ and CES1) through a series of biological processes.

Conclusion: People in greener surroundings have a lower risk of dyslipidemia, which may be due to their lower inflammation, stronger lipid transporter activity, and normal cholesterol metabolism.
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http://dx.doi.org/10.1016/j.ecoenv.2022.113199DOI Listing
January 2022

Deep Learning Reconstruction Shows Better Lung Nodule Detection for Ultra-Low-Dose Chest CT.

Radiology 2022 Jan 18:210551. Epub 2022 Jan 18.

From the Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Rd, Shanghai 200080, China (B.J., N.L., X.X.); CT Imaging Research Center, GE Healthcare China, Shanghai, China (X.S., S.Z., J.L.); and Departments of Epidemiology (G.H.d.B.) and Radiology (R.V.), University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.

Background Ultra-low-dose (ULD) CT could facilitate the clinical implementation of large-scale lung cancer screening while minimizing the radiation dose. However, traditional image reconstruction methods are associated with image noise in low-dose acquisitions. Purpose To compare the image quality and lung nodule detectability of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-V (ASIR-V) in ULD CT. Materials and Methods Patients who underwent noncontrast ULD CT (performed at 0.07 or 0.14 mSv, similar to a single chest radiograph) and contrast-enhanced chest CT (CECT) from April to June 2020 were included in this prospective study. ULD CT images were reconstructed with filtered back projection (FBP), ASIR-V, and DLIR. Three-dimensional segmentation of lung tissue was performed to evaluate image noise. Radiologists detected and measured nodules with use of a deep learning-based nodule assessment system and recognized malignancy-related imaging features. Bland-Altman analysis and repeated-measures analysis of variance were used to evaluate the differences between ULD CT images and CECT images. Results A total of 203 participants (mean age ± standard deviation, 61 years ± 12; 129 men) with 1066 nodules were included, with 100 scans at 0.07 mSv and 103 scans at 0.14 mSv. The mean lung tissue noise ± standard deviation was 46 HU ± 4 for CECT and 59 HU ± 4, 56 HU ± 4, 53 HU ± 4, 54 HU ± 4, and 51 HU ± 4 in FBP, ASIR-V level 40%, ASIR-V level 80% (ASIR-V-80%), medium-strength DLIR, and high-strength DLIR (DLIR-H), respectively, of ULD CT scans ( < .001). The nodule detection rates of FBP reconstruction, ASIR-V-80%, and DLIR-H were 62.5% (666 of 1066 nodules), 73.3% (781 of 1066 nodules), and 75.8% (808 of 1066 nodules), respectively ( < .001). Bland-Altman analysis showed the percentage difference in long diameter from that of CECT was 9.3% (95% CI of the mean: 8.0, 10.6), 9.2% (95% CI of the mean: 8.0, 10.4), and 6.2% (95% CI of the mean: 5.0, 7.4) in FBP reconstruction, ASIR-V-80%, and DLIR-H, respectively ( < .001). Conclusion Compared with adaptive statistical iterative reconstruction-V, deep learning image reconstruction reduced image noise, increased nodule detection rate, and improved measurement accuracy on ultra-low-dose chest CT images. © RSNA, 2022 See also the editorial by Lee in this issue.
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http://dx.doi.org/10.1148/radiol.210551DOI Listing
January 2022

Au-activated N motifs in non-coherent cupric porphyrin metal organic frameworks for promoting and stabilizing ethylene production.

Nat Commun 2022 Jan 17;13(1):63. Epub 2022 Jan 17.

Soochow Institute for Energy and Materials Innovations, College of Energy, Soochow University, Suzhou, 215006, China.

Direct implementation of metal-organic frameworks as the catalyst for CO electroreduction has been challenging due to issues such as poor conductivity, stability, and limited > 2e products. In this study, Au nanoneedles are impregnated into a cupric porphyrin-based metal-organic framework by exploiting ligand carboxylates as the Au -reducing agent, simultaneously cleaving the ligand-node linkage. Surprisingly, despite the lack of a coherent structure, the Au-inserted framework affords a superb ethylene selectivity up to 52.5% in Faradaic efficiency, ranking among the best for metal-organic frameworks reported in the literature. Through operando X-ray, infrared spectroscopies and density functional theory calculations, the enhanced ethylene selectivity is attributed to Au-activated nitrogen motifs in coordination with the Cu centers for C-C coupling at the metalloporphyrin sites. Furthermore, the Au-inserted catalyst demonstrates both improved structural and catalytic stability, ascribed to the altered charge conduction path that bypasses the incoherent framework. This study underlines the modulation of reticular metalloporphyrin structure by metal impregnation for steering the CO reduction reaction pathway.
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http://dx.doi.org/10.1038/s41467-021-27768-6DOI Listing
January 2022

Euphorbia angustifolia lactone B inhibits A549 proliferation and induces apoptosis.

Pak J Pharm Sci 2021 Nov;34(6(Special)):2401-2407

Department of Respiratory and Critical Care Medicine, Yuhuangding Hospital, Yantai, Shandong, PR China.

The study is to investigate the effect of Euphorbia angustifolia lactone B (Jolkinolide B, JB) on the proliferation and apoptosis of A549 cells. The proliferation of A549 cells was detected by tetramethyl azothiolide. Activity changes of intracellular caspase-3, 8, 9 were determined by spectrophotometry. The content of cytochrome C (Cyt C) protein and the expression quantity of Bcl-2, Bax, p-ERK1/2, and p-Akt proteins were detected by Western blot and the apoptosis rates were detected by flow cytometry. JB significantly inhibited cell proliferation in a time-dose manner. With increase in JB concentrations, the expression level of Bax protein greatly increased, and the expression of caspase-3 and caspase-9 significantly increased with significant difference (P<0.01). Besides, the peak value of mitochondrial membrane potential decreased, while the number of cells distributed in the depolarized region increased, which was different from that in the control (P<0.05). Moreover, the expression levels of p-ERK1/2 and p-Akt in A549 cells gradually decreased with extending exposure duration. Moreover, 20 μ mol/L LY294002 (an PI3K inhibitor) + 120μg/mL JB and 10μmol/L PD98059 (an ERK inhibitor) +120μg/mL JB also increased apoptosis rates of A549 cells. JB could induced cell apoptosis through promoting endogenous mitochondrial signal transduction pathway and inhibiting PI3K/ERK pathway.
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November 2021

Healthy dietary patterns and metabolic dysfunction-associated fatty liver disease in less-developed ethnic minority regions: a large cross-sectional study.

BMC Public Health 2022 Jan 17;22(1):118. Epub 2022 Jan 17.

West China School of Public Health and West China Fourth Hospital, Sichuan University, No.16, People's South Road, Chengdu, 610041, China.

Background: Little is known about the associations between healthy dietary patterns and metabolic dysfunction-associated fatty liver disease (MAFLD) in less-developed ethnic minority regions (LEMRs), where the prevalence of MAFLD is increasing rapidly and dietary habits are quite different from those in developed countries. Moreover, a significant subset of MAFLD individuals in LEMRs are nonobese, but the efficacy of dietary patterns on MAFLD individuals with different obese statuses is also unclear. We aimed to test the associations of two wildly recommended a priori dietary patterns-Alternate Mediterranean diet (AMED) and Dietary Approaches to Stop Hypertension (DASH)-with the risk of MAFLD in the total population, and further in nonobese and obese individuals.

Methods: We recruited 99,556 participants in the China Multi-Ethnic Cohort Study, an ongoing cohort study in less-developed southwest China. Using validated food frequency questionnaire, each participant was assigned an AMED score and a DASH score. MAFLD was ascertained as hepatic steatosis on ultrasound together with diabetes, overweight/obesity, or two other metabolic risk factors. We performed logistic regression with inverse probability of exposure weighting (IPEW) to examine associations between two dietary patterns and MAFLD, adjusting for potential confounders under the guidance of directed acyclic graphs. Further, analyses were stratified by body mass index.

Results: We included 66,526 participants (age 49.5±11.0; 62.6% women), and the prevalence of MAFLD was 16.1%. Participants in the highest quintile of DASH score showed strong inverse associations with risks of MAFLD (OR = 0.85; 95% CI, 0.80-0.91; P < 0.001) compared with participants in the lowest quintile. The association between DASH and nonobese MAFLD (OR = 0.69; 95% CI, 0.61-0.78; P < 0.001) was stronger (I = 78.5 % ; P = 0.001) than that with obese MAFLD (OR = 0.90; 95% CI, 0.83-0.98; P = 0.002). There was a null association between AMED and MAFLD risk.

Conclusions: In LEMRs, a DASH diet but not AMED was associated with MAFLD. The relationship appeared to be more pronounced in nonobese MAFLD individuals than in obese MAFLD individuals.
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http://dx.doi.org/10.1186/s12889-021-12486-xDOI Listing
January 2022
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