The causal effect of serum micronutrients on malignant kidney neoplasm in European descent

PurposeObservational studies have revealed that serum minerals and vitamins are associated with cancer. However, the causal relationships between serum minerals and vitamins and renal malignancies remain unclear.MethodsMendelian randomization (MR) was used for causal estimation. Single nucleotide polymorphisms (SNPs) for serum minerals and vitamins were obtained from published genome-wide association studies (GWAS). GWAS for malignant kidney neoplasm was obtained from the FinnGen consortium. Methods of inverse variance weighted (IVW), MR-Egger, and weighted median were carried out for causal inference. F-statistic was calculated to ensure a robust instrumental variable. Cochran’s Q statistics was applied to calculate heterogeneity. MR-Egger regression, MR-pleiotropy residual sum and outlier methods (MR-PRESSO) methods were used to perform pleiotropy analysis. Meanwhile, confounding factors were considered to determine whether causal inference would be biased.ResultsEight different micronutrients were included (zinc, iron, magnesium, calcium, copper, selenium, phosphate, and vitamin B12). After MR analysis, we found a protective effect of serum zinc against malignant kidney neoplasm (IVW: odds ratios (ORs), 0.86; 95% confidence interval (95% CI), 0.78–0.94; p, 0.0016; MR-Egger: OR, 0.80; 95% CI, 0.64–0.97; p, 0.052; weighted median: OR, 0.85; 95% CI, 0.75–0.96; p, 0.011). Causal relationships between other micronutrients and malignant kidney neoplasm were not obtained. No heterogeneity and pleiotropy were detected, while causality was not biased by confounding factors.ConclusionWe considered that serum zinc exerted a protective effect against malignant kidney neoplasm. In clinical practice, for people with high malignant kidney neoplasm risk, an oral zinc supplementation might play a role in a potential therapeutic target

Surface-emitting lasers for communications: novel metal-cavity microlasers and high-contrast-grating tunable VCSELs

A comprehensive study of the theory and experiments of surface-emitting semiconductor lasers is presented. The design of novel micro and nanolasers using metal cavities for optical confinement is discussed. Theoretical modeling of quantum-well and quantum-dot emission properties, as well as experimental characterization of their coupling with optical cavities, are presented. Lasing behavior of our designed and fabricated devices is demonstrated at room temperature under continuous-wave and pulsed electrical injection with 3-μm and 1-μm cavity diameters, respectively. This work provides the research path toward dense-integrable power-efficient on-chip light sources. Surface-emitting tunable lasers for high-speed, long-haul communication are investigated. Novel laser designs using micro-electro-mechanical system controlled high-contrast gratings as tunable mirrors are presented. Rigorous, accurate, and efficient electromagnetic models for high-contrast gratings are developed. Our model enables us to design high-contrast gratings as one-dimensional or two-dimensional metastructures integrable on surface-emitting lasers. A wide range of optical functionalities such as broadband reflection, high-Q resonance, filtering, beam-steering, focusing, beam-conversion, and generation of photon orbital angular momentum are achieved. Our optical model is integrated with our laser cavity model and the rate equation model to predict the temperature-dependent voltage tunable light output intensity and spectra. Future design and experimental strategies for heterogeneously integrated tunable surface-emitting lasers are discussed

Atractylenolide I inhibits EMT and enhances the antitumor effect of cabozantinib in prostate cancer via targeting Hsp27

ObjectiveTo investigate the effect of Hsp27 and the inhibitory effect of Atractylenolide I (ATL-1) on the proliferation of prostate cancer cell DU145 and PC-3.MethodsMTT assay was used to detect the inhibitory effect of silencing Hsp27 and ATL-1 on DU145 and PC-3 proliferation of prostate cancer cells. TUNEL detected the apoptosis rate of prostate cancer cell DU145 and PC-3 after silencing Hsp27 and ATL-1 treated. qRT-PCR was used to detect the changes of apoptosis related genes caspase-3, PARP, Bax and Bcl-2 in prostate cancer cell DU145 and PC-3 after the effect of silencing Hsp27 and ATL-1 treated. At the same time, the antitumor effect of ATL-1 combined with cabozantinib was analyzed.ResultsHsp27 was highly expressed in human prostate cancer. MTT assay showed that ATL-1 inhibited the proliferation of prostate cancer cells DU145 and PC-3 compared with the control group. TUNEL results showed that silencing Hsp27 and ATL-1 treated could significantly promote the apoptosis of prostate cancer cells DU145 and PC-3 compared with the control group. qRT-PCR results showed that compared with the control group, ATL-1 could promote the expression of caspase-3, PARP and Bax in DU145 and PC-3 prostate cancer cells. Inhibition of Hsp27 by ATL-1 reduced cell viability and induced apoptosis. ATL-1 inhibits the antitumor effect of Hsp27 - enhanced cabozantinib. Hsp27 regulates eIF4E and mediates cell protection.ConclusionSilencing Hsp27 inhibits EMT. ATL-1 can inhibit the malignant evolution of prostate cancer cells by inhibiting Hsp27/eIF4E. ATL-1 also enhanced chemosensitization of cabozantinib in prostate cancer

Learning Disentangled Semantic Representation for Domain Adaptation

Domain adaptation is an important but challenging task. Most of the existing domain adaptation methods struggle to extract the domain-invariant representation on the feature space with entangling domain information and semantic information. Different from previous efforts on the entangled feature space, we aim to extract the domain invariant semantic information in the latent disentangled semantic representation (DSR) of the data. In DSR, we assume the data generation process is controlled by two independent sets of variables, i.e., the semantic latent variables and the domain latent variables. Under the above assumption, we employ a variational auto-encoder to reconstruct the semantic latent variables and domain latent variables behind the data. We further devise a dual adversarial network to disentangle these two sets of reconstructed latent variables. The disentangled semantic latent variables are finally adapted across the domains. Experimental studies testify that our model yields state-of-the-art performance on several domain adaptation benchmark datasets

Laser Beam Propagation through Oceanic Turbulence

Using a recently proposed model for the refractive index fluctuations in oceanic turbulence, optical beam propagation through seawater is explored. The model provides an accurate depiction of the ocean through the inclusion of both temperature and salinity fluctuations to the refractive index. Several important statistical characteristics are explored including spatial coherence radius, angle-of-arrival fluctuations, and beam wander. Theoretical values of these parameters are found based on weak fluctuation theory using the Rytov method. The results presented serve as a foundation for the study of optical beam propagation in oceanic turbulence, which may provide an important support for further researches in applications for underwater communicating, imaging, and sensing systems

Adaptive Multi-layer Contrastive Graph Neural Networks

We present Adaptive Multi-layer Contrastive Graph Neural Networks (AMC-GNN), a self-supervised learning framework for Graph Neural Network, which learns feature representations of sample data without data labels. AMC-GNN generates two graph views by data augmentation and compares different layers' output embeddings of Graph Neural Network encoders to obtain feature representations, which could be used for downstream tasks. AMC-GNN could learn the importance weights of embeddings in different layers adaptively through the attention mechanism, and an auxiliary encoder is introduced to train graph contrastive encoders better. The accuracy is improved by maximizing the representation's consistency of positive pairs in the early layers and the final embedding space. Our experiments show that the results can be consistently improved by using the AMC-GNN framework, across four established graph benchmarks: Cora, Citeseer, Pubmed, DBLP citation network datasets, as well as four newly proposed datasets: Co-author-CS, Co-author-Physics, Amazon-Computers, Amazon-Photo.Comment: 16 pages,7 figure

Effects of different extracts of Cremastra appendiculata (D. Don) Makino Cremastra appendiculata (D. Don) Makino on apoptosis of A549 cells

Purpose: To investigate the effect of different extracts of Cremastra appendiculata (D. Don) Makino onapoptosis of A549 cells, and the underlying mechanism.Methods: The contents of colchicine in ethyl acetate and n-butanol extracts of Cremastra appendiculata(D. Don) Makino were determined using high performance liquid chromatography (HPLC). Lung cancerA549 cells cultured in vitro were divided into blank control, standard colchicine and Cremastra appendiculata (D. Don) Makino extract groups. The effect of different extract concentrations on proliferation of the cells was determined using methyl thiazolyl diphenyl-tetrazolium (MTT) assay, while apoptosis of A549 cells induced by the extracts was evaluated by flow cytometry (FC).Results: Compared with the standard colchicine group, there was no colchicine in the n-butanol and ethyl acetate extracts of Cremastra appendiculata. Results from MTT assay showed that the extract inhibited the proliferation of A549 cells (p < 0.05). Flow cytometry results showed that ethyl acetate extract significantly enhanced apoptosis in A549 cells (p < 0.05). However, n-butanol extract had no significant effect on the apoptosis of A549 cells (p < 0.05).Conclusion: The ethyl acetate extract of Cremastra appendiculata (D. Don) Makino induces apoptosis in lung cancer A549 cells. Therefore, there is a need for further research and development of antitumor drugs from the extract of Cremastra appendiculata (D. Don) Makino. Keywords: Cremastra appendiculata (D. Don) Makino, Colchicine, A549 cells, Apoptosi