The propensity of the activated neutrophils to form extracellular traps (NETs) is demonstrated in multiple inflammatory conditions. In this study, we investigated the roles of NETs in metastasis of ...hepatocellular carcinoma (HCC) and further explored the underlying mechanism of how NETs affect metastasis as well as the therapeutic value.
The neutrophils were isolated from the blood of human HCC patients and used to evaluate the formation of NETs. The expression of NET markers was detected in tumor specimens. A LPS-induced NET model was used to investigate the role of NETs on HCC metastasis. RNA-seq was performed to identify the key molecular event triggered by NETs, and their underlying mechanism and therapeutic significance were explored using both in vitro and in vivo assays.
NET formation was enhanced in neutrophils derived from HCC patients, especially those with metastatic HCCs. NETs trapped HCC cells and subsequently induced cell-death resistance and enhanced invasiveness to trigger their metastatic potential, which was mediated by internalization of NETs into trapped HCC cells and activation of Toll-like receptors TLR4/9-COX2 signaling. Inhibition of TLR4/9-COX2 signaling abrogated the NET-aroused metastatic potential. A combination of DNase 1 directly wrecking NETs with anti-inflammation drugs aspirin/hydroxychloroquine effectively reduced HCC metastasis in mice model.
NETs trigger tumorous inflammatory response and fuel HCC metastasis. Targeting NETs rather than neutrophils themselves can be a practice strategy against HCC metastasis.
Since other genital infections enhance HIV susceptibility by inducing inflammation and evidence suggests that the vaginal microbiome plays a functional role in the persistence or regression of ...high-risk human papillomavirus (HPV) infections, we investigated the relationship between the composition of the vaginal microbiota and the risk of high-risk HPV infection.
The study included 151 healthy women (65 HPV-positive and 86 HPV-negative) aged 20-65 at enrollment. Total genome DNA from samples was extracted using the hexadecyltrimethylammonium bromide (CTAB) CTAB method. The vaginal microbiota composition was determined by sequencing barcoded 16S rDNA gene fragments (V4) on Illumina HiSeq2500.
Of the 30 most abundant bacteria at the genus level, we found only six bacteria with a statistical difference between HPV-positive and HPV-negative women:
,
,
,
,
, and
was the predominant genus and was detected in all women, but there was no significant difference between the two groups for
,
, and
. Furthermore, we found 26 types of bacteria with a statistical difference at the species level between the two groups. Anaerobic bacteria such as
,
, and
were found significantly more frequently in HPV-positive women, which is the most important finding of our study.
Our findings suggest a possible role for the composition of the vaginal microbiota as a modifier of high-risk HPV infection, and specific microbiota species may serve as sensors for changes in the cervical microenvironment associated with high-risk HPV infection. The exact molecular mechanism of the vaginal microbiota in the course of high-risk HPV infection and cervical neoplasia should be further explored. Future research should include intervention in the composition of the vaginal microbiota to reverse the course of high-risk HPV infection and the natural history of cervical neoplasia.
Fibroblast growth factor 23 (FGF23) is a new endocrine product discovered in the past decade. In addition to being related to bone diseases, it has also been found to be related to kidney metabolism ...and parathyroid metabolism, especially as a biomarker and a key factor to be used in kidney diseases. FGF23 is upregulated as early as the second and third stages of chronic kidney disease (CKD) in response to relative phosphorus overload. The early rise of FGF23 has a protective effect on the body and is essential for maintaining phosphate balance. However, with the decline in renal function, eGFR (estimated glomerular filtration rate) declines, and the phosphorus excretion effect caused by FGF23 is weakened. It eventually leads to a variety of complications, such as bone disease (Chronic Kidney Disease-Mineral and Bone Metabolism Disorder), vascular calcification (VC), and more. Monoclonal antibodies against FGF23 are currently used to treat genetic diseases with increased FGF23. CKD is also a state of increased FGF23. This article reviews the current role of FGF23 in CKD and discusses the crosstalk between various organs under CKD conditions and FGF23. Studying the effect of hyperphosphatemia on different organs of CKD is important. The prospect of FGF23 for therapy is also discussed.
We calculate the variation of the chiral condensate in medium with respect to the quark chemical potential and evaluate the pion-nucleon sigma term via the Hellmann-Feynman theorem. The variation of ...the chiral condensate in medium is obtained by solving the truncated Dyson-Schwinger equation for the quark propagator at finite chemical potential, with various ansätz for the quark-gluon vertex and gluon propagator. We obtain the value of the sigma term σπN = 62(1) MeV, where the (1) represents the systematic error due to our different ansätz for the quark-gluon vertex and gluon propagator. Our result favors a relatively large value and is rather consistent with the recent data obtained by analyzing pion-nucleon scattering and pionic-atom experiments.
Many works have focused on speech emotion recognition algorithms. However, most rely on the proper selection of speech acoustic features. In this paper, we propose a novel emotion recognition ...algorithm that does not rely on any speech acoustic features and combines speaker gender information. We aim to benefit from the rich information from speech raw data, without any artificial intervention. In general, speech emotion recognition systems require manual selection of appropriate traditional acoustic features as classifier input for emotion recognition. Utilizing deep learning algorithms, and the network automatically select important information from raw speech signal for the classification layer to accomplish emotion recognition. It can prevent the omission of emotion information that cannot be direct mathematically modeled as a speech acoustic characteristic. We also add speaker gender information to the proposed algorithm to further improve recognition accuracy. The proposed algorithm combines a Residual Convolutional Neural Network (R-CNN) and a gender information block. The raw speech data is sent to these two blocks simultaneously. The R-CNN network obtains the necessary emotional information from the speech data and classifies the emotional category. The proposed algorithm is evaluated on three public databases with different language systems. Experimental results show that the proposed algorithm has 5.6%, 7.3%, and 1.5%, respectively accuracy improvements in Mandarin, English, and German compared with existing highest-accuracy algorithms. In order to verify the generalization of the proposed algorithm, we use FAU and eNTERFACE databases, in these two independent databases, the proposed algorithm can also achieve 85.8% and 71.1% accuracy, respectively.
The present study systematically analyzed and evaluated the variations in chemical speciation, pollution assessment, and source identification of heavy metals in sediments of Huangpu River. The ...methods employed included heavy metal concentration, chemical speciation and Cu isotopic compositions analysis. Results showed that the chemical speciation of sediment-bound heavy metals, characterized by significant seasonal variation, shifted from non-residual fractions dominating in spring and summer to residual fractions dominating in autumn and winter. Precipitation was identified as an important factor influencing the chemical speciation of sediment-bound heavy metals. Furthermore, ratio of the secondary phase to the primary phase, RSP (=Cnon-residual/Cresidual) values in Huangpu River sediments were higher than 1 in spring and summer, indicating that sediment-bound heavy metals in Huangpu River were mainly composed of non-residual fractions and could potentially be released into the river water. Principal component analysis (PCA) revealed that navigation, traffic, agricultural, and industrial activities could be the potential sources of heavy metal pollution. Notably, the δ65Cu values in Huangpu River sediments were observed to be isotopically lighter (from −0.37 to +0.18 ‰), suggesting that navigation might be the primary pollution source. These results will not only provide guidance in reducing heavy metal concentrations, but also serve as a crucial basis for policy making regarding heavy metal control.
•Seasonal heavy metal speciation and δ65Cu in Huangpu River sediment were studied.•Speciation of sediment heavy metals varied evidently in different seasons.•Sediment heavy metals were non-residual fractions dominating in spring and summer.•Precipitation plays a key role in chemical speciation of heavy metals.•δ65Cu showed that navigation might be the main source of Cu in Huangpu River.
High resolution (HR) magnetic resonance images (MRI) or computed tomography (CT) images can provide clearer anatomical details of human body, which facilitates early diagnosis of the diseases. ...However, due to the imaging system, imaging environment and human factors, it is difficult to obtain clear high-resolution images. In this paper, we proposed a novel medical image super resolution (SR) reconstruction method via multi-scale information distillation (MSID) network in the non-subsampled shearlet transform (NSST) domain, namely NSST-MSID network. We first proposed a MSID network that mainly consisted of a series of stacked MSID blocks to fully exploit features from images and effectively restore the low resolution (LR) images to HR images. In addition, most previous methods predict the HR images in the spatial domain, producing over-smoothed outputs while losing texture details. Thus, we viewed the medical image SR task as the prediction of NSST coefficients, which make further MSID network keep richer stru
Exosomes have emerged as critical mediators of intercellular communication, both locally and systemically, by regulating a diverse range of biological processes between cells. Circular RNA (circRNA) ...is a novel member of endogenous noncoding RNAs with widespread distribution and diverse cellular functions. Recently, circular RNAs have been identified for their enrichment and stability in exosomes. In this review, we outline the origin, biogenesis and function of exosomal circRNAs as well as their roles in various diseases. Although their precise roles and mechanisms of gene regulation remain largely elusive, exosomal circRNAs have potential applications as disease biomarkers and novel therapeutic targets.
Crystal nucleation is relevant across the domains of fundamental and applied sciences. However, in many cases, its mechanism remains unclear due to a lack of temporal or spatial resolution. To gain ...insights into the molecular details of nucleation, some form of molecular dynamics simulations is typically performed; these simulations, in turn, are limited by their ability to run long enough to sample the nucleation event thoroughly. To overcome the timescale limits in typical molecular dynamics simulations in a manner free of prior human bias, here, we employ the machine learning-augmented molecular dynamics framework "reweighted autoencoded variational Bayes for enhanced sampling (RAVE)." We study two molecular systems-urea and glycine-in explicit all-atom water, due to their enrichment in polymorphic structures and common utility in commercial applications. From our simulations, we observe multiple back-and-forth nucleation events of different polymorphs from homogeneous solution; from these trajectories, we calculate the relative ranking of finite-sized polymorph crystals embedded in solution, in terms of the free-energy difference between the finite-sized crystal polymorph and the original solution state. We further observe that the obtained reaction coordinates and transitions are highly nonclassical.
Little is known about the inter-relationship among fruit and vegetable intake, gut microbiota and metabolites, and type 2 diabetes (T2D) in human prospective cohort study. The aim of the present ...study was to investigate the prospective association of fruit and vegetable intake with human gut microbiota and to examine the relationship between fruit and vegetable-related gut microbiota and their related metabolites with type 2 diabetes (T2D) risk.
This study included 1879 middle-age elderly Chinese adults from Guangzhou Nutrition and Health Study (GNHS). Baseline dietary information was collected using a validated food frequency questionnaire (2008-2013). Fecal samples were collected at follow-up (2015-2019) and analyzed for 16S rRNA sequencing and targeted fecal metabolomics. Blood samples were collected and analyzed for glucose, insulin, and glycated hemoglobin. We used multivariable linear regression and logistic regression models to investigate the prospective associations of fruit and vegetable intake with gut microbiota and the association of the identified gut microbiota (fruit/vegetable-microbiota index) and their related fecal metabolites with T2D risk, respectively. Replications were performed in an independent cohort involving 6626 participants.
In the GNHS, dietary fruit intake, but not vegetable, was prospectively associated with gut microbiota diversity and composition. The fruit-microbiota index (FMI, created from 31 identified microbial features) was positively associated with fruit intake (p < 0.001) and inversely associated with T2D risk (odds ratio (OR) 0.83, 95%CI 0.71-0.97). The FMI-fruit association (p = 0.003) and the FMI-T2D association (OR 0.90, 95%CI 0.84-0.97) were both successfully replicated in the independent cohort. The FMI-positive associated metabolite sebacic acid was inversely associated with T2D risk (OR 0.67, 95%CI 0.51-0.86). The FMI-negative associated metabolites cholic acid (OR 1.35, 95%CI 1.13-1.62), 3-dehydrocholic acid (OR 1.30, 95%CI 1.09-1.54), oleylcarnitine (OR 1.77, 95%CI 1.45-2.20), linoleylcarnitine (OR 1.66, 95%CI 1.37-2.05), palmitoylcarnitine (OR 1.62, 95%CI 1.33-2.02), and 2-hydroglutaric acid (OR 1.47, 95%CI 1.25-1.72) were positively associated with T2D risk.
Higher fruit intake-associated gut microbiota and metabolic alteration were associated with a lower risk of T2D, supporting the public dietary recommendation of adopting high fruit intake for the T2D prevention.
PDF
