•Respiratory Syncytial Virus (RSV) infection can induce and exacerbate pediatric asthma airway hyperresponsiveness and mucus hypersecretion.•TRPV1 play an important role to promote production of ...inflammatory cytokines and mucus hypersecretion in the pathology of RSV-infected asthma.•Qingfei oral liquid can inhibit airway inflammation and mucus hypersecretion in RSV-infected asthma by regulating TRPV1 signaling pathway.
Pediatric asthma is exacerbated by Respiratory Syncytial Virus (RSV) infection, and Transient Receptor Potential Vanilloid 1 (TRPV1) promotes production of inflammatory cytokines and mucus hypersecretion in the pathology of this disease. Our previous research revealed that Qingfei oral liquid (QF) inhibited airway inflammation and mucus hypersecretion in RSV-infected asthmatic mice models and that this may be associated with the TRPV1-regulation of NF-κB and Mucin 5AC (MUC5AC) expression, but the exact mechanism is unknown. In the present study, LC–MS was used for analyzing the chemicals in QF, ovalbumin (OVA)-induced asthmatic mice inhaled RSV three consecutive times to create an RSV-infected asthmatic model. We found treatment from QF alleviated airway hyperresponsiveness (AHR) and reduced congestion, edema, and infiltration of inflammatory cells into pulmonary tissues. Additionally, QF was found to decrease expression of NF-κB and its downstream inflammatory cytokines IL-1β, IL-4, IL-5, and IL-13, as well as a decrease in MUC5AC and pro-inflammatory cytokines in PKC via a reduction in Protein Kinase C-dependent signaling. These findings suggest that QF can alleviate AHR and mucus hypersecretion caused by RSV infection in asthmatic mice, and its mechanism may be associated with the regulation of the TRPV1 signaling pathway.
Previous studies have documented an intrinsic association between breast cancer (BC) and thyroid cancer (TC), but the clinical relevance of this relationship is not well defined. In the present ...study, we specifically investigated the impact of a history of TC on clinical outcomes of BC. We performed a population-based comparative analysis of tumor behaviors and BC-specific mortalities in 427,893 female patients with BC in the USA Surveillance, Epidemiology and End Results 9 database (1973-2013). In this cohort of subjects, 2,569 patients also had a history of differentiated TC (BC/TC), including BC diagnosed before TC (BC-1st) and BC diagnosed after TC (TC-1st), with the median follow-up time of 81 (IQR, 33-160) months. We found that, compared with matched BC-only patients, less aggressive BC tumor behaviors occurred in BC/TC patients, as exemplified by a distant metastasis rate of 7.0% in the former versus 3.3% in the latter (P<0.001). In BC/TC, BC-1st, and TC-1st patients versus their matched BC-only patients, BC-specific mortalities were 11.3% versus 21.0%, 9.9% versus 26.4%, and 12.4% versus 16.9%. These corresponded to hazard ratios (HR) (95% CI) of 0.47 (0.42-0.53), 0.31 (0.26-0.37), and 0.72 (0.61-0.84), respectively (all P<0.001), being lowest in BC-1st patients <50 years old HR = 0.22 (0.16-0.31), which remained significant after adjustment for clinicopathological and socioeconomic factors. Estrogen/progesterone receptor expression in BC tumors was significantly higher in patients with BC/TC than matched BC-only patients, providing evidence that BC in the former was biologically unique. Thus, a history of TC, particularly in younger BC-1st patients, may identify BC as a unique disease entity characterized by a decreased disease-specific mortality risk. The results have potentially important clinical and biological implications for BC in this special patient population and encourage further studies to confirm.
A kinetic model for glycidyl ester (GE) formation in both palm oil and chemical models during high-temperature heating was built to investigate the formation and degradation mechanisms of GEs in ...refined palm oil. The results showed that the formation and degradation of GEs followed pseudo-first-order reactions, and the rate constants of reaction kinetics followed the Arrhenius equation. The estimated activation energy of the GE degradation reaction (12.87 kJ/mol) was significantly lower than that of the GE formation reaction (34.58 kJ/mol), suggesting that GE degradation occurred more readily than formation. The Fourier transform infrared (FTIR) band intensities of epoxy and ester carboxyl groups decreased over heating time, while no band assigned to the cyclic acyloxonium group was found. Furthermore, no 5,5-dimethyl-1-pyrroline N-oxide (DMPO)-cyclic acyloxonium radical adduct was detected by quadrupole time-of-flight mass spectrometry (Q-TOF-MS). The above findings indicated that GEs were decomposed, fatty acid was also liberated, and GE degradation did not involve a cyclic acyloxonium intermediate. GEs were primarily decomposed into monoacylglycerol via ring-opening reaction during heating followed by fatty acid and glycerol via hydrolysis reaction.
The present work describes a measurement method using the combination of near-infrared hyperspectral imaging (NIR-HSI) and chemometrics for rapid and non-destructive detection of lipid oxidation ...degree of pork meat during frozen storage based on thiobarbituric acid reactive substances (TBARS) value measurement. The HSI images were acquired at frozen state without thawing. An interesting phenomenon was discovered that the TBARS value was highly correlated with the scattering characteristics of frozen pork meat, which was mainly influenced by the ice crystals growth and distribution. The partial least square (PLS) regression model established using only the two correction factors obtained from multiplicative scattering correction (MSC) yielded an almost identical performance with that based on the full NIR spectral region with determination coefficient in prediction (R2P) of 0.926 and root mean square error in prediction (RMSEP) of 0.036. This finding was helpful for better interpretation of the NIR spectra of frozen meat.
•NIR HSI was used by the first time to assess lipid oxidation of frozen meat.•TBARS value was found highly correlated with scattering properties of frozen meat.•PLS model based on MSC extracted correction factors showed good performance.•A cage of covariance exists between the TBARS value and storage time.
The food crisis has increased demand for agricultural resources due to various factors such as extreme weather, energy crises, and conflicts. A solar greenhouse enables counter-seasonal winter ...cultivation due to its thermal insulation, thus alleviating the food crisis. The root temperature is of critical importance, although the mechanism of soil thermal environment change remains uncertain. This paper presents a comprehensive study of the soil thermal environment of a solar greenhouse in Jinzhong City, Shanxi Province, employing a variety of analytical techniques, including theoretical, experimental, and numerical simulation, and deep learning modelling. The results of this study demonstrate the following: During the overwintering period, the thermal environment of the solar greenhouse floor was divided into a low-temperature zone, a constant-temperature zone, and a high-temperature zone; the distance between the low-temperature boundary and the southern foot was 2.6 m. The lowest temperature in the low-temperature zone was 11.06 °C and the highest was 19.05 °C. The floor in the low-temperature zone had to be heated; the lowest value of the constant-temperature zone was 18.29 °C, without heating. The minimum distance between the area of high temperature and the southern foot of the solar greenhouse was 8 m and the lowest temperature reading was 19.29 °C. The indoor soil temperature tended to stabilise at a depth of 45 cm, and the lowest temperature reading at a horizontal distance of 1400 mm from the south foot was 19.5 °C. The Fluent and LSTM models fitted well and the models can be used to help control soil temperature during overwintering in extreme climates. The research can provide theoretical and data support for the crop areas and the heating of pipelines in the solar greenhouse.
The etiology and pathogenesis of pre-eclampsia (PE) is unclear, and there is no ideal early clinical biomarker for prediction of PE. The competing endogenous RNA (ceRNA) hypothesis is a new approach ...to uncover the molecular pathology of PE. The first aim of this study was to perform messenger RNA, long non-coding RNA, and circular RNA (circRNA) expression profiling of human normal and severe pre-eclampsia (SPE) placentas. circRNA, which has a stable structure, is a more suitable biomarker than other types of RNA. Therefore, the second aim of our study was to select some differentially expressed circRNAs in PE placentas as early clinical biomarkers of PE in blood circulation.
Using microarray analysis, we investigated differentially expressed ceRNAs in human normal and SPE placentas. Bioinformatics, such as gene ontology, KEGG pathway, and ceRNA network analyses, were performed to evaluate the microarray data and gain further insights into the biological processes. RNAs (
,
, lnc-ELAVL4-9:1, lnc-RAP1GAP2-5:2, hsa_circ_0036877, hsa_circ_0036878, hsa_circ_0055724, hsa_circ_0049730, and hsa_circ_0036474) were validated by quantitative real-time PCR (qRT-PCR). RNA immunoprecipitation (RIP) of AGO2 in htra-8 cells and qRT-PCR analysis of hsa_circ_0036877 expression in maternal whole peripheral blood samples of participants were then conducted to confirm that hsa_circ_0036877 is a ceRNA and potential novel blood biomarker for early PE, respectively.
Our study is the first systematic profiling of ceRNAs in placentas of PE patients and revealed the global ceRNA network integration in PE. Moreover, hsa_circ_0036877 can function as a ceRNA and serve as a potential novel blood biomarker for early PE.
We propose a novel method for preference learning or, more specifically, learning to rank, where the task is to learn a ranking model that takes a subset of alternatives as input and produces a ...ranking of these alternatives as output. Just like in the case of conventional classifier learning, training information is provided in the form of a set of labeled instances, with labels or, say, preference degrees taken from an ordered categorical scale. This setting is known as multipartite ranking in the literature. Our approach is based on the idea of using the (discrete) Choquet integral as an underlying model for representing ranking functions. Being an established aggregation function in fields such as multiple criteria decision making and information fusion, the Choquet integral offers a number of interesting properties that make it attractive from a machine learning perspective, too. The learning problem itself comes down to properly specifying the fuzzy measure on which the Choquet integral is defined. This problem is formalized as a margin maximization problem and solved by means of a cutting plane algorithm. The performance of our method is tested on a number of benchmark datasets.
Hexanucleotide GGGGCC repeat expansion in C9ORF72 is the most prevalent genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). One pathogenic mechanism is the ...aberrant accumulation of dipeptide repeat (DPR) proteins produced by the unconventional translation of expanded RNA repeats. Here, we performed genome-wide CRISPR-Cas9 screens for modifiers of DPR protein production in human cells. We found that DDX3X, an RNA helicase, suppresses the repeat-associated non-AUG translation of GGGGCC repeats. DDX3X directly binds to (GGGGCC)n RNAs but not antisense (CCCCGG)n RNAs. Its helicase activity is essential for the translation repression. Reduction of DDX3X increases DPR levels in C9ORF72-ALS/FTD patient cells and enhances (GGGGCC)n-mediated toxicity in Drosophila. Elevating DDX3X expression is sufficient to decrease DPR levels, rescue nucleocytoplasmic transport abnormalities, and improve survival of patient iPSC-differentiated neurons. This work identifies genetic modifiers of DPR protein production and provides potential therapeutic targets for C9ORF72-ALS/FTD.
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•Genome-wide CRISPR-Cas9 screens identify regulators of DPR protein production•The RNA helicase DDX3X suppresses RAN translation of C9ORF72 (GGGGCC)n repeats•Elevating DDX3X expression decreases DPR levels in C9ORF72-ALS patient cells•Elevating DDX3X rescues pathological features and improves survival of patient iPSNs
DPR proteins produced by the unconventional translation of expanded RNA repeats contribute to neurodegeneration in C9ORF72-ALS/FTD. Cheng and Wang et al. identify DDX3X as a repressor of r(GGGGCC)n translation. Elevating DDX3X decreases DPRs, rescues pathological phenotypes, and improves neuronal survival.
Antiretroviral treatment regimens can sufficiently suppress viral replication in human immunodeficiency virus (HIV)-infected patients and prevent the progression of the disease. However, one of the ...factors contributing to the progression of the disease despite ongoing antiretroviral treatment is the emergence of drug resistance. The high mutation rate of HIV can lead to a fast adaptation of the virus under drug pressure, thus to failure of antiretroviral treatment due to the evolution of drug-resistant variants. Moreover, cross-resistance phenomena have been frequently found in HIV-1, leading to resistance not only against a drug from the current treatment, but also to other not yet applied drugs. Automatic classification and prediction of drug resistance is increasingly important in HIV research as well as in clinical settings, and to this end, machine learning techniques have been widely applied. Nevertheless, cross-resistance information was not taken explicitly into account, yet.
In our study, we demonstrated the use of cross-resistance information to predict drug resistance in HIV-1. We tested a set of more than 600 reverse transcriptase sequences and corresponding resistance information for six nucleoside analogues. Based on multilabel classification models and cross-resistance information, we were able to significantly improve overall prediction accuracy for all drugs, compared with single binary classifiers without any additional information. Moreover, we identified drug-specific patterns within the reverse transcriptase sequences that can be used to determine an optimal order of the classifiers within the classifier chains. These patterns are in good agreement with known resistance mutations and support the use of cross-resistance information in such prediction models.
dominik.heider@uni-due.de
Supplementary data are available at Bioinformatics online.
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