Swertiamarin attenuates carbon tetrachloride (CCl4)-induced liver injury and inflammation in rats by regulating the TLR4 signaling pathway

The aim of the present study is to illustrate the effects of swertiamarin (STM), a natural iridoid from herbal medicines, on hepatic inflammation induced by carbon tetrachloride (CCl4) in rats. Male Sprague Dawley rats were exposed to CCl4 with or without STM co-administration for 8 weeks. Our results revealed that STM administration (100 and 200 mg/kg b.w.) significantly attenuated inflammation in livers of CCl4-treated rats. STM remarkably reduced the production of interleukin-1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), macrophage inflammatory protein-1a (MIP1α), and monocyte chemotactic protein-1 (MCP-1) in liver tissue of CCl4-treated rats. In addition, STM treatment downregulated connective tissue growth factor (CTGF) and ser307pIRS-1 expression, which was induced by CCl4 exposure. In the process of exploring the anti-inflammatory mechanisms of STM action, we demonstrated that STM significantly inhibited Toll-like receptor 4 (TLR4) and nuclear factor kappa B (NF-κB) p65 expression in the liver. In conclusion, these results suggested that the inhibition of CCl4-induced inflammation by STM was, at least in part, due to its regulation of the TLR4 /NF-κB signaling pathway

Effects of caffeine, tea polyphenol and daidzein on the pharmacokinetics of lansoprazole and its metabolites in rats

O objetivo deste estudo foi avaliar os efeitos da cafeína, do polifenol do chá e da daidzeína na farmacocinética do lansoprazol e de seus metabólitos. Administraram-se, intragastricamente, aos ratos cafeína (30 mg·kg-1, uma vez ao dia), polifenol do chá(400 mg·kg-1, uma vez ao dia) ou daidzeína (13,5 mg·kg-1, uma vez ao dia), por 14 dias, seguindo-se a administração de lansoprazol (8 mg·kg-1) no 15º. dia. As concentrações plasmáticas do lansoprazol e de seus dois metabólitos primários, 5-hidroxilansoprazol e sulfona de lansoprazol, foram determinadas por cromatografia líquida de alta eficiência acoplada com espectrometria de massas (CLAE-EM/EM). O polifenol do chá elevou, significativamente, a Área Sob a Curva (ASC) do lansoprazol de 680,29 ± 285,99 para 949,76 ± 155,18 μg/L.h e reduziu a da sulfona de lansoprazol de 268,82 ± 82,37 para 177,72 ± 29,73 μg/L.h. A daidzeína aumentou a ASC do lansoprazol de 680,29 ± 285,99 para 1130,44 ± 97,6 μg/L.h e reduziu a da sulfona de lansoprazol de 268,82 ± 82,37 para 177,72 ± 29,73 μg/L.h. A farmacocinética do 5-hidroxilansoprazol permaneceu intacta na presença de polifenol do chá ou daidzeína. A cafeína não afetou a farmacocinética do lansoprazol e de seus metabólitos. Os resultados sugerem que o polifenol do chá e a daidzeína podem inibir o metabolismo in vivo do lansoprazol por supressão da CYP3A.The aim of this study was to evaluate the effects of caffeine, tea polyphenol and daidzein on the pharmacokinetics of lansoprazole and its metabolites. Rats were intragastrically administered caffeine (30 mg·kg-1, once per day), tea polyphenol (400 mg·kg-1, once per day) or daidzein (13.5 mg·kg-1, once per day) for 14 days, followed by an intragastric administration of lansoprazole (8 mg·kg-1) on the 15th day. The plasma concentrations of lansoprazole and its two primary metabolites, 5-hydroxylansoprazole and lansoprazole sulfone, were determined by high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS). Tea polyphenol significantly elevated the Area Under the Curve (AUC) of lansoprazole from 680.29 ± 285.99 to 949.76 ± 155.18 μg/L.h and reduced that of lansoprazole sulfone from 268.82 ± 82.37 to 177.72 ± 29.73 μg/L.h. Daidzein increased the AUC of lansoprazole from 680.29 ± 285.99 to 1130.44 ± 97.6 μg/L.h and decreased that of lansoprazole sulfone from 268.82 ± 82.37 to 116.23 ± 40.14 μg/L.h. The pharmacokinetics of 5-hydroxylansoprazole remained intact in the presence of tea polyphenol or daidzein. Caffeine did not affect the pharmacokinetics of lansoprazole and its metabolites. The results imply that tea polyphenol and daidzein may inhibit the in vivo metabolism of lansoprazole by suppressing CYP3A

Molecular Packing Control Enables Excellent Performance and Mechanical Property of Blade-Cast All-Polymer Solar Cells

All-polymer solar cells (all-PSCs) are the most promising power generators for flexible and portable devices due to excellent morphology stability and outstanding mechanical property. Previous work indicates high crystallinity is beneficial to device performance but detrimental to mechanical property, therefore identifying the optimized ratio between crystalline and amorphous domains becomes important. In this work, we demonstrated highly efficient and mechanically robust all-PSCs by blade-coating technology in ambient environment based on PTzBI:N2200 system. By controlling the aggregation in solution state and ultrafast film formation process, a weakly ordered molecular packing morphology as well as small phase separation is obtained, which leads to not only the good photovoltaic performance (8.36%-one of the best blade-cast device in air) but also prominent mechanical characteristic. The controlled film shows a remarkable elongation with the crack onset strain of 15.6%, which is the highest result in organic solar cells without adding elastomers. These observations indicate the great promise of the developed all-PSCs for practical applications toward large-area processing technology

A cross-scanner and cross-tracer deep learning method for the recovery of standard-dose imaging quality from low-dose PET

PURPOSE: A critical bottleneck for the credibility of artificial intelligence (AI) is replicating the results in the diversity of clinical practice. We aimed to develop an AI that can be independently applied to recover high-quality imaging from low-dose scans on different scanners and tracers. METHODS: Brain [(18)F]FDG PET imaging of 237 patients scanned with one scanner was used for the development of AI technology. The developed algorithm was then tested on [(18)F]FDG PET images of 45 patients scanned with three different scanners, [(18)F]FET PET images of 18 patients scanned with two different scanners, as well as [(18)F]Florbetapir images of 10 patients. A conditional generative adversarial network (GAN) was customized for cross-scanner and cross-tracer optimization. Three nuclear medicine physicians independently assessed the utility of the results in a clinical setting. RESULTS: The improvement achieved by AI recovery significantly correlated with the baseline image quality indicated by structural similarity index measurement (SSIM) (r = −0.71, p < 0.05) and normalized dose acquisition (r = −0.60, p < 0.05). Our cross-scanner and cross-tracer AI methodology showed utility based on both physical and clinical image assessment (p < 0.05). CONCLUSION: The deep learning development for extensible application on unknown scanners and tracers may improve the trustworthiness and clinical acceptability of AI-based dose reduction. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00259-021-05644-1

Genomic monitoring of SARS-CoV-2 uncovers an Nsp1 deletion variant that modulates type I interferon response

The SARS-CoV-2 virus, the causative agent of COVID-19, is undergoing constant mutation. Here, we utilized an integrative approach combining epidemiology, virus genome sequencing, clinical phenotyping, and experimental validation to locate mutations of clinical importance. We identified 35 recurrent variants, some of which are associated with clinical phenotypes related to severity. One variant, containing a deletion in the Nsp1-coding region (D500-532), was found in more than 20% of our sequenced samples and associates with higher RT-PCR cycle thresholds and lower serum IFN-beta levels of infected patients. Deletion variants in this locus were found in 37 countries worldwide, and viruses isolated from clinical samples or engineered by reverse genetics with related deletions in Nsp1 also induce lower IFN-beta responses in infected Calu-3 cells. Taken together, our virologic surveillance characterizes recurrent genetic diversity and identified mutations in Nsp1 of biological and clinical importance, which collectively may aid molecular diagnostics and drug design.Peer reviewe

Swertiamarin attenuates carbon tetrachloride (CCl4)-induced liver injury and inflammation in rats by regulating the TLR4 signaling pathway

The aim of the present study is to illustrate the effects of swertiamarin (STM), a natural iridoid from herbal medicines, on hepatic inflammation induced by carbon tetrachloride (CCl4) in rats. Male Sprague Dawley rats were exposed to CCl4 with or without STM co-administration for 8 weeks. Our results revealed that STM administration (100 and 200 mg/kg b.w.) significantly attenuated inflammation in livers of CCl4-treated rats. STM remarkably reduced the production of interleukin-1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), macrophage inflammatory protein-1a (MIP-1α), and monocyte chemotactic protein-1 (MCP-1) in liver tissue of CCl4-treated rats. In addition, STM treatment downregulated connective tissue growth factor (CTGF) and ser307pIRS-1 expression, which was induced by CCl4 exposure. In the process of exploring the anti-inflammatory mechanisms of STM action, we demonstrated that STM significantly inhibited Toll-like receptor 4 (TLR4) and nuclear factor kappa B (NF-κB) p65 expression in the liver. In conclusion, these results suggested that the inhibition of CCl4-induced inflammation by STM was, at least in part, due to its regulation of the TLR4 /NF-κB signaling pathway

Chaotic binary sensing matrices

As an emerging field for sampling paradigms, compressive sensing (CS) can sample and represent signals at a sub-Shannon-Nyquist rate. To realize CS from theory to practice, the random sensing matrices must be substituted by faster measurement operators that correspond to feasible hardware architectures. In recent years, binary matrices have attracted much research interest because of their multiplier-less and faster data acquisition. In this work, we aim to pinpoint the potential of chaotic binary sequences for constructing high-efficiency sensing implementations. In particular, the proposed chaotic binary sensing matrices are verified to meet near-optimal theoretical guarantees in terms of both the restricted isometry condition and coherence analysis. Simulation results illustrate that the proposed chaotic constructions have considerable sampling efficiency comparable to that of the random counterparts. Our framework encompasses many families of binary sensing architectures, including those formed from Logistic, Chebyshev, and Bernoulli binary chaotic sequences. With many chaotic binary sensing architectures, we can then more easily apply CS paradigm to various fields