High efficiency stimulated rotational Raman scattering of hydrogen pumped by 1064 nm.

Laser-induced breakdown (LIB) and the competition of other Raman processes are major reasons restricting photon conversion efficiency (PCE) of Raman lasers. In this work, 1064 nm was used as the pump source, and stimulated rotational Raman scattering of hydrogen was investigated. The configuration of zooming out and focusing pump beam was applied, and the dimension of the pump beam at the focus spot increased significantly; consequently, LIB was suppressed, and Raman PCE was improved dramatically. With the help of the Raman gas pressure optimization, vibrational Raman could be fully suppressed, and other competition Raman processes could be well controlled. The optimal PCEs of different rotational Raman lasers could be achieved under different conditions. The maximum PCE of the first rotational Stokes (RS1) was improved to 60.7%, and the maximum energy of RS1 reached 204.5 mJ. With the increment of hydrogen pressure, the maximum PCE of the second rotational Stokes (RS2) was improved to 28.2%, and the maximum energy of RS2 reached 123.9 mJ. Furthermore, a 2.1 µm Raman laser was also generated, the maximum PCE of 2.1 µm reached 44.8%, and its pulse energy reached 106.1 mJ.

Serum exosomal m6A demethylase FTO promotes gefitinib resistance in non-small cell lung cancer by up-regulating FLRT3, PTGIS and SIRPα expression.

This study investigates the molecular mechanism of FTO m6A demethylase in non-small cell lung cancer (NSCLC) and gefitinib resistance using GEO and TCGA databases. Differentially expressed genes (DEGs) were screened from RNA-seq data sets of serum exosomes of gefitinib-resistant NSCLC patients in the GEO database and the NSCLC data set in the GEPIA2 database. From this analysis, FTO m6A demethylase was found to be significantly upregulated in the serum exosomes of gefitinib-resistant NSCLC patients. To identify downstream genes affected by FTO m6A demethylase, weighted correlation network analysis and differential expression analysis were performed, resulting in the identification of three key downstream genes (FLRT3, PTGIS, and SIRPA). Using these genes, the authors constructed a prognostic risk assessment model. Patients with high-risk scores exhibited a significantly worse prognosis. The model could predict the prognosis of NSCLC with high accuracy measured by AUC values of 0.588, 0.608, and 0.603 at 1, 3, and 5 years respectively. Furthermore, m6A sites were found in FLRT3, PTGIS, and SIRPA genes, and FTO was significantly positively correlated with the expression of these downstream genes. Overall, FTO m6A demethylase promotes gefitinib resistance in NSCLC patients by upregulating downstream FLRT3, PTGIS, and SIRPA expression, with these three downstream genes serving as strong prognostic indicators.

Stimulated vibrational-rotational Raman scattering of hydrogen pumped at a 1064-nm laser.

A ∼2.1-µm laser is within an atmospheric transmission window and can be used in remote sensing. In this work, a 1064-nm laser was used as the pump source, pressurized hydrogen was used as the Raman active medium, and a dual-wavelength ∼2.1-µm Raman laser was generated. The 2147-nm laser was generated by a combination processes of stimulated vibrational Raman scattering and stimulated rotational Raman scattering, while a 2132-nm laser was generated by stimulated S-branch vibrational Raman scattering. Optimizing experimental conditions yielded a maximum pulse energy of 76.1 mJ, a peak power of ∼9.2M W, and a photon conversion efficiency of 29.8%.

Integrated head and neck imaging of symptomatic patients with stroke using simultaneous non-contrast cardiovascular magnetic resonance angiography and intraplaque hemorrhage imaging as compared with digital subtraction angiography.

BACKGROUND: Both stenosis rate and intraplaque hemorrhage (IPH) are important predictors of stroke risk. Simultaneous non-contrast angiography and intraplaque hemorrhage (SNAP) cardiovascular magnetic resonance (CMR) imaging can detect both stenosis rate and IPH. We aimed to evaluate consistency between SNAP and digital subtraction angiography (DSA) to assess symptomatic patients with stroke and explore the performance of SNAP to identify IPH and the clinical factors associated with IPH. METHODS: Eighty-one symptomatic patients with stroke, admitted to Wuhan Union Hospital who underwent CMR high-resolution vessel wall imaging (HR-VWI) and SNAP, were retrospectively identified. For patients who received interventional therapy, the imaging functions of SNAP and HR-VWI were compared with DSA. The diameters of the intracranial and carotid vessels were measured, and stenotic vessels were identified. The consistency of SNAP and HR-VWI in identifying IPH was also examined, and the correlations between IPH and clinical factors were analyzed. RESULTS: SNAP was more consistent with DSA than HR-VWI in measuring vascular stenosis (intraclass correlation coefficient [ICC]SNAP-DSA = 0.917, ICC HR-VWI-DSA = 0.878). Regarding the diameter measurements of each intracranial and carotid vessel segment, SNAP was superior or similar to HR-VWI, and both were consistent with DSA in the measurement of major intracranial vascular segments. HR-VWI and SNAP exhibited acceptable agreement in identifying IPH (Kappa = 0.839, 95% confidence interval [CI]: 0.704-0.974). Patients who underwent interventional therapy had a higher plaque burden (P < 0.001). Patients with IPH had lower levels of high-density lipoprotein cholesterol (HDL) (P = 0.038) and higher levels of blood glucose (P = 0.007) and cystatin C (P = 0.040). CONCLUSIONS: CMR SNAP is consistent with DSA in measuring vessel diameters and identifying atherosclerosis stenosis in each intracranial and carotid vessel segment. SNAP is also a potential alternative to HR-VWI in identifying stenosis and IPH.

A High-Rate and Ultrastable Aqueous Zinc-Ion Battery with a Novel MgV2 O6 ·1.7H2 O Nanobelt Cathode.

High-safety and low-cost aqueous Zn-ion batteries have triggered an astounding investigation surge in the last 5 years and are becoming competitive alternatives for grid-scale energy storage. However, the implementation of this promising technology is still plagued by the lack of effective and affordable cathode materials that can enable high energy densities and an exceptional cycling stability. Herein, a novel vanadium-based oxide cathode based on MgV2 O6 ·1.7H2 O nanobelts, which delivers a high capacity (425.7 mAh g-1 at 0.2 A g-1 ), a robust rate capability (182.1 mAh g-1 at 10 A g-1 ), and an ultrastable cycle without any visible deterioration, as well as an adequate energy density (331.6 Wh kg-1 ), is developed. Such excellent electrochemical Zn-ion storage performance is believed to result from the fast ion-diffusion kinetics boosted by a stable layered structure and an ultrahigh intercalation pseudocapacitance reaction, which are also benefited by a typical H+ /Zn2+ co-insertion mechanism, accompanied by an atypical Zn2+ intercalation chemistry with a partial but irreversible Mg2+ -Zn2+ ion-exchange reaction during the initial discharge. These results provide key and enlightening insights into the design of high-performance vanadium oxide cathode materials.

Wavelength-tunable narrow-linewidth gaseous Raman laser.

Gaseous Raman lasers cover a range of wavelengths but lack wavelength tunability. Here, a 1cm-1 linewidth 532 nm laser was used as a pump laser, and with a narrow-linewidth seed laser injection, a narrow-linewidth first Stokes (S1) Raman laser was achieved. By tuning the wavelength of the seed laser, a tuning range of S1 up to 1cm-1 was obtained. The wavelengths of the first anti-Stokes and second Stokes lasers could also be tuned. A theoretical model was developed, and spectral profiles of Raman lasers from experiments and simulations agreed well; further simulation predicted that the linewidth of S1 could be compressed to as narrow as 0.01cm-1 under optimal conditions. A universal method of fine-tunable Raman lasers is presented that can be utilized in several important applications.

Boosting Zinc-Ion Storage Capability by Effectively Suppressing Vanadium Dissolution Based on Robust Layered Barium Vanadate.

Vanadium-based compounds with an open framework structure have become the subject of much recent investigation into aqueous zinc-ion batteries (AZIBs) due to high specific capacity. However, there are some issues with vanadium dissolution from a cathode framework as well as the generation of byproducts during discharge that should not be ignored, which could cause severe capacity deterioration and inadequate cycle life. Herein, we report several barium vanadate nanobelt cathodes constructed of two sorts of architectures, i.e., Ba1.2V6O16·3H2O and BaV6O16·3H2O (V3O8-type) and BaxV2O5·nH2O (V2O5-type), which are controllably synthesized by tuning the amount of barium precursor. Benefiting from the robust architecture, layered BaxV3O8-type nanobelts (Ba1.2V6O16·3H2O) exhibit superior rate capability and long-term cyclability owing to fast zinc-ion kinetics, enabled by efficiently suppressing cathode dissolution as well as greatly eliminating the generation of byproduct Zn4SO4(OH)6·xH2O, which provides a reasonable strategy to engineer cathode materials with robust architectures to improve the electrochemical performance of AZIBs.

Identification of Genes and Pathways Associated with Acne Using Integrated Bioinformatics Methods.

BACKGROUND: Acne is the most common skin inflammatory condition. The pathogenesis of acne is not fully understood. AIMS: We performed weighted gene co-expression network analysis (WGCNA) to select acne-associated genes and pathways. METHODS: GSE53795 and GSE6475 datasets including data from lesional and nonlesional skin of acne patients were downloaded from the NCBI Gene Expression Omnibus. Differentially expressed genes (DEGs) in lesions were identified following a false discovery rate <0.05 and | log2 fold change | ≥0.5. DEG-associated biological processes and pathways were identified. WGCNA analysis was performed to identify acne-associated modules. DEGs in the acne-associated modules were used for protein-protein interaction (PPI) network construction and Gene Set Enrichment Analysis (GSEA). Acne-associated candidate DEGs and pathways were identified together with items in the Comparative Toxicogenomics Database (CTD). RESULTS: A total of 2,140 and 1,190 DEGs were identified in GSE53795 and GSE6475 datasets, respectively, including 716 overlapping DEGs with similar expression profiles in the two datasets, which were clustered into 10 consensus modules. Two modules (brown and turquoise, 359 genes) were associated with acne phenotype. Of these 359 DEGs, 254 were enrolled in the PPI network. GSEA showed that these DEGs were associated with chemokine signaling pathway, cytokine-cytokine receptor interaction, and natural killer cell-mediated cytotoxicity. After identification in CTD, one pathway Cytokine-cytokine receptor interaction and 24 acne-associated DEGs, including IL1R1, CXCL1, CXCR4, CCR1, CXCL2 and IL1ß, were identified as candidates associated with acne. CONCLUSION: Our results highlight the important roles of the proinflammatory cytokines including IL1ß, CXCL1, CXCL2, CXCR4, and CCR1 in acne pathogenesis or therapeutic management.

Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD.

BACKGROUND: Disease comorbidity is very common and has significant impact on disease treatment. Revealing the associations among diseases may help to understand the mechanisms of diseases, improve the prevention and treatment of diseases, and support the discovery of new drugs or new uses of existing drugs. METHODS: In this paper, we introduced a mathematical model to represent gene related diseases with a series of associated genes based on the overrepresentation of genes and diseases in PubMed literature. We also illustrated an efficient way to reveal the implicit connections between COPD and other diseases based on this model. RESULTS: We applied this approach to analyze the relationships between Chronic Obstructive Pulmonary Disease (COPD) and other diseases under the Lung diseases branch in the Medical subject heading index system and detected 4 novel diseases relevant to COPD. As judged by domain experts, the F score of our approach is up to 77.6%. CONCLUSIONS: The results demonstrate the effectiveness of the gene fingerprint model for diseases on the basis of medical literature.

Extracting psychiatric stressors for suicide from social media using deep learning.

BACKGROUND: Suicide has been one of the leading causes of deaths in the United States. One major cause of suicide is psychiatric stressors. The detection of psychiatric stressors in an at risk population will facilitate the early prevention of suicidal behaviors and suicide. In recent years, the widespread popularity and real-time information sharing flow of social media allow potential early intervention in a large-scale population. However, few automated approaches have been proposed to extract psychiatric stressors from Twitter. The goal of this study was to investigate techniques for recognizing suicide related psychiatric stressors from Twitter using deep learning based methods and transfer learning strategy which leverages an existing annotation dataset from clinical text. METHODS: First, a dataset of suicide-related tweets was collected from Twitter streaming data with a multiple-step pipeline including keyword-based retrieving, filtering and further refining using an automated binary classifier. Specifically, a convolutional neural networks (CNN) based algorithm was used to build the binary classifier. Next, psychiatric stressors were annotated in the suicide-related tweets. The stressor recognition problem is conceptualized as a typical named entity recognition (NER) task and tackled using recurrent neural networks (RNN) based methods. Moreover, to reduce the annotation cost and improve the performance, transfer learning strategy was adopted by leveraging existing annotation from clinical text. RESULTS & CONCLUSIONS: To our best knowledge, this is the first effort to extract psychiatric stressors from Twitter data using deep learning based approaches. Comparison to traditional machine learning algorithms shows the superiority of deep learning based approaches. CNN is leading the performance at identifying suicide-related tweets with a precision of 78% and an F-1 measure of 83%, outperforming Support Vector Machine (SVM), Extra Trees (ET), etc. RNN based psychiatric stressors recognition obtains the best F-1 measure of 53.25% by exact match and 67.94% by inexact match, outperforming Conditional Random Fields (CRF). Moreover, transfer learning from clinical notes for the Twitter corpus outperforms the training with Twitter corpus only with an F-1 measure of 54.9% by exact match. The results indicate the advantages of deep learning based methods for the automated stressors recognition from social media.

A case report of multicentric reticulohistiocytosis with atypical cutaneous presentation.

Multicentric reticulohistiocytosis (MRH) is a rare systemic disorder characterized by histiocytic hyperplasia that mainly involves the skin, mucous membranes, and joints. The typical clinical features include papules, nodules, and arthritis. MRH lesions are relatively extensive but small and scattered. Joint inflammation is characterized by diffuse symmetric polyarthritis as the first symptom, which can be severe and disabling due to destructive joint changes. MRH is easily misdiagnosed in clinical practice. Here, we report the case of an elderly male patient who presented with polyarticular pain in the hip and interphalangeal joints as the first manifestation, followed by the development of large, isolated, bulging skin nodules, which are atypical MRH lesions. This is rare in all MRH case reports, and we made the correct diagnosis by combining skin histopathology, immunohistochemistry, and other clinical examinations. We performed surgical treatment on the local skin lesions of this patient. This case suggests that clinicians should actively correlate the condition and accurately diagnose MRH when encountering atypical skin changes or other diseases as the first symptom and explore the mechanisms of MRH and other clinical manifestations.

Two-Color Amplified Spontaneous Emission from Auger-Suppressed Quantum Dots in Liquids.

Colloidal quantum-dot (QD) lasing is normally achieved in close-packed solid-state films, as a high QD volume fraction is required for stimulated emission to outcompete fast Auger decay of optical-gain-active multiexciton states. Here a new type of liquid optical-gain medium is demonstrated, in which compact compositionally-graded QDs (ccg-QDs) that feature strong suppression of Auger decay are liquefied using a small amount of solvent. Transient absorption measurements of ccg-QD liquid suspensions reveal broad-band optical gain spanning a wide spectral range from 560 (green) to 675 nm (red). The gain magnitude is sufficient to realize a two-color amplified spontaneous emission (ASE) at 637 and 594 nm due to the band-edge (1S) and the excited-state (1P) transition, respectively. Importantly, the ASE regime is achieved using quasicontinuous excitation with nanosecond pulses. Furthermore, the ASE is highly stable under prolonged excitation, which stands in contrast to traditional dyes that exhibit strong degradation under identical excitation conditions. These observations point toward a considerable potential of high-density ccg-QD suspensions as liquid, dye-like optical gain media that feature readily achievable spectral tunability and stable operation under intense photoexcitation.

[Genotypes of Toxoplasma gondii isolates from HIV positive patients in Yunnan Province].

One hundred and fifty serum samples of HIV positive patients were collected in western Yunnan Province from September 2011 to December 2012. Toxoplasma gondii B1 gene was amplified by nested PCR. Genotyping of T. gondii isolates were performed by restriction fragment length polymorphism (RFLP) with Pm1 I and Xho I. 13 samples were found positive with the B1 gene (530 bp) amplification and belonged to type I. The sequencing results showed that 4 T. gondii B1 gene positive samples were identical, with 3 nucleotide variation compared with T. gondii strain RH (type I) B1 gene (GenBank No. AF179871), and in the other sample a "G --> A" mutation at 230bp was detected. The results indicated that the genotype of Toxoplasma gondii in HIV positive patients in Yunnan Province is type I.

Reduction-responsive dextran-based Pt(IV) nano-prodrug showed a synergistic effect with doxorubicin for effective melanoma treatment.

Melanoma, the deadliest skin cancer with high metastasis potential, has posed a great threat to human health. Accordingly, early efficient blocking of melanoma progression is vital in antitumor treatment. Herein, a reduction-responsive dextran-based Pt(IV) nano-prodrug (PDPN) was synthesized and used for doxorubicin (DOX) delivery to combat melanoma synergistically. First, PDPN was prepared by one-pot chemical coupling of carboxylated methoxy poly(ethylene glycol) (mPEG), dextran (Dex), and the crosslinking agent cisPt (IV)-COOH. PDPN had a spherical structure (Rh = 34 ± 11.3 nm). Then, DOX was encapsulated into the PDPN core to form DOX-loaded PDPN (PDPN-DOX). The obtained PDPN-DOX displayed reduction-responsive release of DOX and Pt, thus showing a synergistic anticancer effect in B16F10 cells (combination index, 0.46). Furthermore, in vivo experiments demonstrated that PDPN-DOX was effective for the synergistic treatment of subcutaneous melanoma. Collectively, the as-prepared PDPN could serve as a promising and versatile nano-prodrug carrier for the co-delivery of chemotherapeutics in tumor combination therapy.

Sediment-water distribution and potential sources of polyhalogenated carbazoles in a coastal river locating at a north metropolis, China.

The fate and transformation of PHCZs in the coastal river environment are not yet comprehensively understood. Paired river water and surface sediment were collected, and 12 PHCZs were analyzed to find out their potential sources and investigate the distribution of PHCZs between river water and sediment. The concentration of ∑PHCZs varied from 8.66 to 42.97 ng/g (mean 22.46 ng/g) in sediment and 17.91 to 81.82 ng/L (mean 39.07 ng/L) in river water. 18-B-36-CCZ was the dominant PHCZ congener in sediment, while 36-CCZ was in water. Meanwhile, the logKoc values for CZ and PHCZs were among the first calculated in the estuary and the mean logKoc varied from 4.12 for 1-B-36-CCZ to 5.63 for 3-CCZ. The logKoc values of CCZs were higher than those of BCZs, this may suggest that sediments have a higher capacity for accumulation and storage of CCZs than highly mobile environmental media.

An integrative non-invasive malignant brain tumors classification and Ki-67 labeling index prediction pipeline with radiomics approach.

BACKGROUND: The histological sub-classes of brain tumors and the Ki-67 labeling index (LI) of tumor cells are major factors in the diagnosis, prognosis, and treatment management of patients. Many existing studies primarily focused on the classification of two classes of brain tumors and the Ki-67LI of gliomas. This study aimed to develop a preoperative non-invasive radiomics pipeline based on multiparametric-MRI to classify-three types of brain tumors, glioblastoma (GBM), metastasis (MET) and primary central nervous system lymphoma (PCNSL), and to predict their corresponding Ki-67LI. METHODS: In this retrospective study, 153 patients with malignant brain tumors were involved. The radiomics features were extracted from three types of MRI (T1-weighted imaging (T1WI), fluid-attenuated inversion recovery (FLAIR), and contrast-enhanced T1-weighted imaging (CE-T1WI)) with three masks (tumor core, edema, and whole tumor masks) and selected by a combination of Pearson correlation coefficient (CORR), LASSO, and Max-Relevance and Min-Redundancy (mRMR) filters. The performance of six classifiers was compared and the top three performing classifiers were used to construct the ensemble learning model (ELM). The proposed ELM was evaluated in the training dataset (108 patients) by 5-fold cross-validation and in the test dataset (45 patients) by hold-out. The accuracy (ACC), sensitivity (SEN), specificity (SPE), F1-Score, and the area under the receiver operating characteristic curve (AUC) indicators evaluated the performance of the models. RESULTS: The best feature sets and ELM with the optimal performance were selected to construct the tri-categorized brain tumor aided diagnosis model (training dataset AUC: 0.96 (95% CI: 0.93, 0.99); test dataset AUC: 0.93) and Ki-67LI prediction model (training dataset AUC: 0.96 (95% CI: 0.94, 0.98); test dataset AUC: 0.91). The CE-T1WI was the best single modality for all classifiers. Meanwhile, the whole tumor was the most vital mask for the tumor classification and the tumor core was the most vital mask for the Ki-67LI prediction. CONCLUSION: The developed radiomics models led to the precise preoperative classification of GBM, MET, and PCNSL and the prediction of Ki-67LI, which could be utilized in clinical practice for the treatment planning for brain tumors.

Association between dietary inflammatory index and cognitive impairment: A meta-analysis.

Aims: Cognitive impairment is an increasingly urgent global public health challenge. Dietary Inflammatory Index (DII) is a literature-derived score that links diet to inflammation. The relationship between DII and cognitive impairment remains controversial. Therefore, our study aimed to analysis the role of DII on the risk of cognitive impairment by meta-analysis. Methods: PubMed, Cochrane Library, MEDLINE, Web of Science and EMBASE databases were searched up to July 2022. Newcastle-Ottawa scale (NOS) and Joanna Briggs Institute (JBI) Checklist were performed to estimate the quality of studies. Results: Nine observational studies with 19,379 subjects were included. Our study found that higher DII could elevate the risk of cognitive impairment (OR = 1.46, 95%CI = 1.26, 1.69). Meanwhile, the OR of cognitive impairment was 1.49 (95%CI = 1.21, 1.83) for cross-sectional studies and 1.42 (95%CI = 1.12, 1.79) for cohort studies, respectively. Conclusion: Our meta-analysis indicated that higher DII (indicating a more pro-inflammatory diet) is related to increased risk of cognitive impairment.

Case Report: Patient With Lung Adenocarcinoma With ALK-HLA-DRB1 Rearrangement Shows Impressive Progression-Free Survival After Sequential Crizotinib and Ceritinib Treatment.

The anaplastic lymphoma kinase (ALK) gene rearrangement is a driving mutation that underlies about 5-6% of non-small cell lung cancer (NSCLC) cases. Lung cancers that are ALK gene rearrangement-positive can be effectively treated with ALK inhibitors. However, the response of patients with rarer ALK gene rearrangements to ALK inhibitors remains unknown. Herein, we described a case of lung adenocarcinoma carrying ALK-HLA-DRB1 fusion in a 48-year-old nonsmoking woman. A similar case of ALK-HLA-DRB1 rearrangement in NSCLC has not been described previously neither in NSCLC nor in other disease. The patient achieved a progression-free survival of 18 months after sequential therapy consisting of crizotinib and then ceritinib during the follow-up. These findings provide basis for the application of ALK inhibitors in patients carrying the rare ALK-HLA-DRB1 fusion.

A Novel Subtraction Method to Reduce Metal Artifacts of Cerebral Aneurysm Embolism Coils.

OBJECTIVE: To investigate a novel subtraction method (S-MAR), combing metal artifact reduction (MAR), virtual monochromatic imaging (VMI), and subtraction CT angiography (CTA) to remove the metal artifacts of coils after endovascular embolotherapy of intracranial aneurysms. METHOD: In this retrospective study, 29 patients with 38 coils after endovascular embolotherapy of intracranial aneurysms who underwent cerebral CTA using a dual-layer detector spectral CT were included. Conventional CT images (CI), virtual non-enhanced (VNC) images and VMI ranging from 40 to 120 KeV in steps of 10 were reconstructed. These images were then postprocessed to CIMAR, VMIMAR and VNCMAR with MAR software (O-MAR; Philips Healthcare, Cleveland, OH, USA). The novel subtraction method (S-MAR) was derived from subtraction imaging between VNCMAR and the optimal VMIMAR. Contrast-to-noise (CNR) and Noise(Background) of CI, CIMAR, VMI, and VMIMAR were calculated quantitatively. Two Independent radiologists qualitatively assessed artifacts in all images using coil artifact score (CA score), a 5-point Likert scale. Besides, all coils were divided into two groups (group 1: diameter < 5.0 mm, group 2: diameter ≥ 5.0 mm). Differences between two groups were statistically analyzed. RESULTS: The optimal KeV was 40 KeV. Strong correlations between diameter of coils and the CA score of CI were found (rs = 0.652, P < 0.05). CNR, Noise and CA score were significantly improved by CIMAR and VMIMAR compared with CI (P < 0.05). The S­MAR showed significantly better performance compared with CI, CIMAR, VMI, and VMIMAR in reducing metal coil artifacts according to the CA score (P < 0.05), especially in group 2. CONCLUSION: The novel S­MAR proved to be a promising method to reduce coil metal artifacts and elevate the vessel visualization adjacent to coils. It could develop to be widely used in cerebral CTA after coiled aneurysms.

Oxypeucedanin relieves LPS-induced acute lung injury by inhibiting the inflammation and maintaining the integrity of the lung air-blood barrier.

INTRODUCTION: Acute lung injury (ALI) is commonly accompanied by a severe inflammatory reaction process, and effectively managing inflammatory reactions is an important therapeutic approach for alleviating ALI. Macrophages play an important role in the inflammatory response, and this role is proinflammatory in the early stages of inflammation and anti-inflammatory in the late stages. Oxypeucedanin is a natural product with a wide range of pharmacological functions. This study aimed to determine the effect of oxypeucedanin on lipopolysaccharide (LPS)-induced ALI. METHODS AND RESULTS: In this study, the following experiments were performed based on LPS-induced models in vivo and in vitro. Using myeloperoxidase activity measurement, ELISA, qRT-PCR, and Western blotting, we found that oxypeucedanin modulated the activity of myeloperoxidase and decreased the expression levels of inflammatory mediators such as TNF-α, IL-6, IL-1ß, MPO, COX-2 and iNOS in LPS-induced inflammation models. Meanwhile, oxypeucedanin inhibited the activation of PI3K/AKT and its downstream NF-κB and MAPK signaling pathways. In addition, oxypeucedanin significantly decreased the pulmonary vascular permeability, which was induced by LPSs, and the enhanced expression of tight junction proteins (Occludin and Claudin 3). CONCLUSIONS: In conclusion, this study demonstrated that the anti-inflammatory mechanism of oxypeucedanin is associated with the inhibition of the activation of PI3K/AKT/NF-κB and MAPK signaling pathways and the maintenance of the integrity of the lung air-blood barrier.