MiR-541-3p suppresses gastric cancer via negative regulation of HSF1

Purpose: To explore the effects of miR-541-3P on the expression of heat shock transcription factor 1 (HSF1) in gastric cancer cells (GC).Methods: The MicroRNA Target Prediction Database was used to predict whether miR-541-3p interacts with HSF1. Interaction was assessed by dual-luciferase reporter assays. Furthermore, miR-541-3p mRNA levels in GC cell lines were determined by qRT-PCR. Human GC cell lines MKN45 and NCI-N87 were transfected with miR-541-3p mimic. Cell apoptosis, proliferation, invasion, and migration were evaluated using flow cytometry, apoptosis assays, Edu assays, CCK-8 assays, and transwell assays, respectively. Caspase-3, Bcl-2, and cleaved caspase-3 expression levels were determined by western blot.Results: Expression of miR-541-3p was significantly down-regulated in GC cells. Functionally, miR-541-3p mimic inhibited GC cell proliferation, migration, and invasion and induced apoptosis in vitro (p <0.01). Mechanistically, miR-541-3p interacted with HSF1 and inhibited its expression. Overexpression of HSF1 counteracted the effects of miR-541-3p mimic in GC cells.Conclusion: These results indicate that miR-541-3p suppresses the development of GC by targeting HSF1 and thus, is a possible strategy for for the management of GC

Fault diagnosis of a mixed-flow pump under cavitation condition based on deep learning techniques

Deep learning technique is an effective mean of processing complex data that has emerged in recent years, which has been applied to fault diagnosis of a wide range of equipment. In the present study, three types of deep learning techniques, namely, stacked autoencoder (SAE) network, long short term memory (LSTM) network, and convolutional neural network (CNN) are applied to fault diagnosis of a mixed-flow pump under cavitation conditions. Vibration signals of the mixed-flowed pump are collected from experiment measurements, and then employed as input datasets for deep learning networks. The operation status is clarified into normal, minor cavitation, and severe cavitation conditions according to visualized bubble density. The techniques of FFT and dropout algorithms are also applied to improve diagnosis accuracy. The results show that the diagnosis accuracy based on SAE and LSTM networks is lower than 50%, while is higher than 68% when using CNN. The maximum accuracy can reach 87.2% by mean of a combination of CNN, BN, MLP, and using frequency domain data by FFT as inputs, which validates the feasibility of applying CNN in mixed-flow pumps

LiCo-Net: Linearized Convolution Network for Hardware-efficient Keyword Spotting

This paper proposes a hardware-efficient architecture, Linearized Convolution Network (LiCo-Net) for keyword spotting. It is optimized specifically for low-power processor units like microcontrollers. ML operators exhibit heterogeneous efficiency profiles on power-efficient hardware. Given the exact theoretical computation cost, int8 operators are more computation-effective than float operators, and linear layers are often more efficient than other layers. The proposed LiCo-Net is a dual-phase system that uses the efficient int8 linear operators at the inference phase and applies streaming convolutions at the training phase to maintain a high model capacity. The experimental results show that LiCo-Net outperforms single-value decomposition filter (SVDF) on hardware efficiency with on-par detection performance. Compared to SVDF, LiCo-Net reduces cycles by 40% on HiFi4 DSP

Dependence receptor UNC5A restricts luminal to basal breast cancer plasticity and metastasis

BACKGROUND: The majority of estrogen receptor-positive (ERα+) breast cancers respond to endocrine therapies. However, resistance to endocrine therapies is common in 30% of cases, which may be due to altered ERα signaling and/or enhanced plasticity of cancer cells leading to breast cancer subtype conversion. The mechanisms leading to enhanced plasticity of ERα-positive cancer cells are unknown. METHODS: We used short hairpin (sh)RNA and/or the CRISPR/Cas9 system to knockdown the expression of the dependence receptor UNC5A in ERα+ MCF7 and T-47D cell lines. RNA-seq, quantitative reverse transcription polymerase chain reaction, chromatin immunoprecipitation, and Western blotting were used to measure the effect of UNC5A knockdown on basal and estradiol (E2)-regulated gene expression. Mammosphere assay, flow cytometry, and immunofluorescence were used to determine the role of UNC5A in restricting plasticity. Xenograft models were used to measure the effect of UNC5A knockdown on tumor growth and metastasis. Tissue microarray and immunohistochemistry were utilized to determine the prognostic value of UNC5A in breast cancer. Log-rank test, one-way, and two-way analysis of variance (ANOVA) were used for statistical analyses. RESULTS: Knockdown of the E2-inducible UNC5A resulted in altered basal gene expression affecting plasma membrane integrity and ERα signaling, as evident from ligand-independent activity of ERα, altered turnover of phosphorylated ERα, unique E2-dependent expression of genes effecting histone demethylase activity, enhanced upregulation of E2-inducible genes such as BCL2, and E2-independent tumorigenesis accompanied by multiorgan metastases. UNC5A depletion led to the appearance of a luminal/basal hybrid phenotype supported by elevated expression of basal/stem cell-enriched ∆Np63, CD44, CD49f, epidermal growth factor receptor (EGFR), and the lymphatic vessel permeability factor NTN4, but lower expression of luminal/alveolar differentiation-associated ELF5 while maintaining functional ERα. In addition, UNC5A-depleted cells acquired bipotent luminal progenitor characteristics based on KRT14+/KRT19+ and CD49f+/EpCAM+ phenotype. Consistent with in vitro results, UNC5A expression negatively correlated with EGFR expression in breast tumors, and lower expression of UNC5A, particularly in ERα+/PR+/HER2- tumors, was associated with poor outcome. CONCLUSION: These studies reveal an unexpected role of the axon guidance receptor UNC5A in fine-tuning ERα and EGFR signaling and the luminal progenitor status of hormone-sensitive breast cancers. Furthermore, UNC5A knockdown cells provide an ideal model system to investigate metastasis of ERα+ breast cancers

Association of BMI with erectile dysfunction: A cross-sectional study of men from an andrology clinic

Abnormal body mass index (BMI) is associated with an increased risk of erectile dysfunction (ED). However, the relationship between different BMI categories and the levels of ED severity remains unclear. In the current study, 878 men from the andrology clinic in Central China were recruited. Erectile function was assessed by the International Index of Erectile Function (IIEF) scores. Questionnaires included questions about demographic characteristics (age, height, weight, educational status), lifestyle habits (drinking, smoking, sleep time), and medical history. Logistic regression was used to examine the association between ED risk and BMI. The incidence of ED was 53.1%. BMI was significantly higher in men from the ED group than in those from the non-ED group (P = 0.01). Compared with the normal weight group, obese men had a higher risk of ED (OR = 1.97, 95% CI = 1.25-3.14, P = 0.004), even after adjustment for potential confounders (OR = 1.78, 95% CI = 1.10-2.90, P = 0.02). Moreover, the positive correlation between obesity and moderate/severe ED severity was confirmed by logistic regression analysis (moderate/severe ED, OR = 2.71, 95% CI = 1.44-5.04, P = 0.002), even after adjusting for potential confounders (OR = 2.51 95% CI = 1.24-5.09, P = 0.01). Collectively, our findings indicate a positive correlation between obesity and the risk of moderate/severe ED. Clinicians could pay more attention to moderate/severe ED patients to maintain a healthy body weight to improve erectile function

Estimating the prevalence of Echinococcus in domestic dogs in highly endemic for echinococcosis

Background: Cystic echinococcosis (CE) and alveolar echinococcosis (AE) are highly endemic in Xiji County of Ningxia Hui Autonomous Region (NHAR) in China where the control campaign based on dog de-worming with praziquantel has been undertaken over preceding decades. This study is to determine the current prevalence of Echinococcus granulosus and E. multilocularis in domestic dogs and monitor the echinococcosis transmission dynamics. Methods: Study villages were selected using landscape patterns (Geographic Information System, GIS) for Echinococcus transmission "hot spots", combined with hospital records identifying risk areas for AE and CE. A survey of 750 domestic dogs, including copro-sampling and owner questionnaires, from 25 selected villages, was undertaken in 2012. A copro-multiplex PCR assay was used for the specific diagnosis of E. granulosus and E. multilocularis in the dogs. Data analysis, using IBM SPSS Statistics, was undertaken, to compare the prevalence of the two Echinococcus spp. in dogs between four geographical areas of Xiji by the χ 2 test. Univariate analysis of the combinations of outcomes from the questionnaire and copro-PCR assay data was carried out to determine the significant risk factors for dog infection. Results: The highest de-worming rate of 84.0% was found in the northwest area of Xiji County, and significant differences (P 0.05) in the prevalence of E. granulosus in dogs from the northwest, southwest, northeast, and southeast of Xiji, but there were significant differences (P< 0.05) between dogs infected with E. multilocularis from the four areas. None of the other independent variables was statistically significant. Conclusions: The results from this study indicate a high prevalence of both E. granulosus and E. muiltilocularis in dogs in Xiji County, NHAR. Transmission of E. multilocularis was more impacted by geographical risk-factors in Xiji County than that of E. granulosus. Dogs have the potential to maintain the transmission of both species of Echinococcus within local Xiji communities, and the current praziquantel dosing of dogs appears to be ineffective or poorly implemented in this area.This study was funded by the Science Fund for Gansu Provincial Key Science and Technology Projects (No. 1203NKDA039); Special Fund for Agro-scientific Research in the Public Interest (No. 200903036–07; 201303037); West China Top Class Discipline Project in Basic Medical Sciences, Ningxia Medical University; The National Natural Science Foundation of China (No. 30960339; 81460311) and the Australian National Health and Medical Research Council (NHMRC) (project grant No. APP 1009539)

Measurement of the top quark forward-backward production asymmetry and the anomalous chromoelectric and chromomagnetic moments in pp collisions at √s = 13 TeV

Abstract The parton-level top quark (t) forward-backward asymmetry and the anomalous chromoelectric (d̂ t) and chromomagnetic (μ̂ t) moments have been measured using LHC pp collisions at a center-of-mass energy of 13 TeV, collected in the CMS detector in a data sample corresponding to an integrated luminosity of 35.9 fb−1. The linearized variable AFB(1) is used to approximate the asymmetry. Candidate t t ¯ events decaying to a muon or electron and jets in final states with low and high Lorentz boosts are selected and reconstructed using a fit of the kinematic distributions of the decay products to those expected for t t ¯ final states. The values found for the parameters are AFB(1)=0.048−0.087+0.095(stat)−0.029+0.020(syst),μ̂t=−0.024−0.009+0.013(stat)−0.011+0.016(syst), and a limit is placed on the magnitude of | d̂ t| &lt; 0.03 at 95% confidence level. [Figure not available: see fulltext.

Measurement of t(t)over-bar normalised multi-differential cross sections in pp collisions at root s=13 TeV, and simultaneous determination of the strong coupling strength, top quark pole mass, and parton distribution functions

Peer reviewe

An embedding technique to determine ττ backgrounds in proton-proton collision data

An embedding technique is presented to estimate standard model tau tau backgrounds from data with minimal simulation input. In the data, the muons are removed from reconstructed mu mu events and replaced with simulated tau leptons with the same kinematic properties. In this way, a set of hybrid events is obtained that does not rely on simulation except for the decay of the tau leptons. The challenges in describing the underlying event or the production of associated jets in the simulation are avoided. The technique described in this paper was developed for CMS. Its validation and the inherent uncertainties are also discussed. The demonstration of the performance of the technique is based on a sample of proton-proton collisions collected by CMS in 2017 at root s = 13 TeV corresponding to an integrated luminosity of 41.5 fb(-1).Peer reviewe