The role of allotropy on phase formation in high entropy alloys.

Identifying single phase, high-entropy systems has been a prominent research focus of materials engineering over the past decade. The considerable effort in computational modeling and experimental verification has yielded several methods and descriptors for predicting if a single phase will form; however, the details surrounding the resulting crystal structure have largely remained a mystery. Here, we present a compelling argument for the role of allotropy in determining the crystal structure of a single-phase, high-entropy alloy.

Exploring 400 Gbps/λ and beyond with AI-accelerated silicon photonic slow-light technology.

Silicon photonics is a promising platform for the extensive deployment of optical interconnections, with the feasibility of low-cost and large-scale production at the wafer level. However, the intrinsic efficiency-bandwidth trade-off and nonlinear distortions of pure silicon modulators result in the transmission limits, which raises concerns about the prospects of silicon photonics for ultrahigh-speed scenarios. Here, we propose an artificial intelligence (AI)-accelerated silicon photonic slow-light technology to explore 400 Gbps/λ and beyond transmission.

Clinical features and treatment response to TKIs in chronic myeloid leukemia patients with atypical BCR::ABL1 transcripts.

A small percentage (0.3 %-4.6 %) of chronic myeloid leukemia (CML) patients exhibit atypical transcripts with poorly defined clinical implications.

Polarization-recycling phase tuning in an integrated ring resonator.

The necessity for efficient optical phase tuning has long been critical and is increasingly urgent in light of system scaling and growing demands of data transmission. In an integrated ring resonator, the design freedom for high efficiency is even more constrained due to its ultra-compact footprint and low cross talk requirements for large-scale operation. In this Letter, we demonstrated a polarization multiplexed microring resonator for efficient phase tuning.

Combination effect between gut microbiota and traditional potentially modifiable risk factors for first-ever ischemic stroke in Tujia, Miao and Han populations in China.

China has had explosive growth in ischemic stroke (IS) burden with significant ethnic and geographic disparities. The aim of this study was to explore the possible combination effect between gut microbiota and traditional potentially modifiable risk factors for IS among two ethnic minorities (Tujia and Miao) and the Han population. Herein, we first used the 16 S rRNA sequencing to compare the gut microbial compositions of 82 patients with first-ever IS vs.

Spatial transcriptome profiling of normal human liver.

The comprehensive study of the spatial-cellular anatomy of the human liver is critical to addressing the cellular origins of liver disease. Here we conducted spatial transcriptomics on normal human liver tissue sections, providing detailed information of liver zonation at the transcriptional level. We present 6581 high-quality spots from normal livers of two human donors.

Significance of Liver Zonation in Hepatocellular Carcinoma.

Liver zonation is fundamental to normal liver function, and numerous studies have investigated the microstructure of normal liver lobules. However, only a few studies have explored the zonation signature in hepatocellular carcinoma (HCC). In this study, we investigated the significance of liver zonation in HCC with the help of single-cell RNA sequencing (scRNA-seq) and multicolor immunofluorescence staining.

Identification of Context-Specific Fitness Genes Associated With Metabolic Rearrangements for Prognosis and Potential Treatment Targets for Liver Cancer.

Liver cancer is the most frequent fatal malignancy. Furthermore, there is a lack of effective therapeutics for this cancer type. To construct a prognostic model for potential beneficiary screens and identify novel treatment targets, we used an adaptive daisy model (ADaM) to identify context-specific fitness genes from the CRISPR-Cas9 screens database, DepMap.

The Prognostic Model Based on Tumor Cell Evolution Trajectory Reveals a Different Risk Group of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide, and heterogeneity of HCC is the major barrier in improving patient outcome. To stratify HCC patients with different degrees of malignancy and provide precise treatment strategies, we reconstructed the tumor evolution trajectory with the help of scRNA-seq data and established a 30-gene prognostic model to identify the malignant state in HCC. Patients were divided into high-risk and low-risk groups.

MSCs enhances the protective effects of valsartan on attenuating the doxorubicin-induced myocardial injury via AngII/NOX/ROS/MAPK signaling pathway.

Objective: To verify if AngII/NOX/ROS/MAPK signaling pathway is involved in Doxorubicin (DOX)-induced myocardial injury and if mesenchymal stem cells (MSCs) could enhance the protective effects of valsartan (Val) on attenuating DOX-induced injury .

Methods: Reactive oxygen species (ROS) formation and the protein expression of AT1R, NOX2, NOX4, caspase-3, caspase-9 and MAPK signaling were assessed in H9c2 cardiomyocytes exposed to DOX for 24 h in the absence or presence of Val, NADPH oxidase inhibitor DPI or knockdown and overexpression of NADPH oxidase subunit: NOX2 and NOX4, co-culture with MSCs, respectively. Finally, MTT assay was used to determine the cell viability of H9c2 cells, MDA-MB-231 breast cancer cells and A549 pulmonary cancer cells under Val, DOX and Val+ DOX treatments.

Seek for Success: A Visualization Approach for Understanding the Dynamics of Academic Careers.

How to achieve academic career success has been a long-standing research question in social science research. With the growing availability of large-scale well-documented academic profiles and career trajectories, scholarly interest in career success has been reinvigorated, which has emerged to be an active research domain called the Science of Science (i.e.

Ecological risk, health risk assessment, and pollution source analysis of Xinli Lake wetland based on triangular fuzzy number.

Wetland environmental pollution has become a global problem involving the ecological environment and human health. This study measured the concentration of seven potentially toxic elements (PTEs Hg, Cd, Zn, Cu, Cr, Pb, and As) in the soil upstream of the Xinli Lake wetland in China. Based on the fuzzy theory, the sources, spatial distribution, ecological risks, and health risks of pollutants are studied.

Protective effects of valsartan administration on doxorubicin‑induced myocardial injury in rats and the role of oxidative stress and NOX2/NOX4 signaling.

Clinical application of doxorubicin (DOX) is hampered by its potential cardiotoxicity, however angiotensin receptor blockers could attenuate DOX‑induced cardiomyopathy. The present study tested the hypothesis that simultaneous administration of valsartan (Val) with DOX could prevent DOX‑induced myocardial injury by modulating myocardial NAD(P)H oxidase (NOX) expression in rats. Eight‑week‑old male Sprague‑Dawley rats were randomly divided into control (CON), DOX, and DOX+Val groups.

Identification of key genes for type 1 diabetes mellitus by network-based guilt by association.

OBJECTIVE This study aimed to propose a co-expression-network (CEN) based gene functional inference by extending the "Guilt by Association" (GBA) principle to predict candidate gene functions for type 1 diabetes mellitus (T1DM). METHODS Firstly, transcriptome data of T1DM were retrieved from the genomics data repository for differentially expressed gene (DEGs) analysis, and a weighted differential CEN was generated. The area under the receiver operating characteristics curve (AUC) was chosen to determine the performance metric for each Gene Ontology (GO) term.

Phase Mapping in EBSD Using Convolutional Neural Networks.

The emergence of commercial electron backscatter diffraction (EBSD) equipment ushered in an era of information rich maps produced by determining the orientation of user-selected crystal structures. Since then, a technological revolution has occurred in the quality, rate detection, and analysis of these diffractions patterns. The next revolution in EBSD is the ability to directly utilize the information rich diffraction patterns in a high-throughput manner.

An Improved Convolutional Neural Network Based Approach for Automated Heartbeat Classification.

With age, our blood vessels are prone to aging, which induces cardiovascular disease. As an important basis for diagnosing heart disease and evaluating heart function, the electrocardiogram (ECG) records cardiac physiological electrical activity. Abnormalities in cardiac physiological activity are directly reflected in the ECG.

An incremental learning system for atrial fibrillation detection based on transfer learning and active learning.

Background And Objective: Atrial fibrillation (AF) is a type of arrhythmia with high incidence. Automatic AF detection methods have been studied in previous works. However, a model cannot be used all the time without any improvement.

A High Precision Real-time Premature Ventricular Contraction Assessment Method based on the Complex Feature Set.

This paper presents a high precision and low computational complexity premature ventricular contraction (PVC) assessment method for the ECG human-machine interface device. The original signals are preprocessed by integrated filters. Then, R points and surrounding feature points are determined by corresponding detection algorithms.

Potential role of a disintegrin and metalloproteinase-17 (ADAM17) in age-associated ventricular remodeling of rats.

Excessive tumor necrosis factor-α (TNF-α) could enhance cell death and aggravate left ventricular remodeling and myocardial dysfunction. A disintegrin and metalloproteinase-17 (ADAM17), an important maturation regulator of TNF-α, might be involved in the aging-associated ventricular remodeling. The present study observed myocardial ADAM17 expression in young and aged rats and explored the association between cardiac structure/function and expression of ADAM17 in 6 month-old ( = 10, young group) and 24 month-old SD rats ( = 10, old group).

Prediction of seed gene function in progressive diabetic neuropathy by a network-based inference method.

Guilt by association (GBA) algorithm has been widely used to statistically predict gene functions, and network-based approach increases the confidence and veracity of identifying molecular signatures for diseases. This work proposed a network-based GBA method by integrating the GBA algorithm and network, to identify seed gene functions for progressive diabetic neuropathy (PDN). The inference of predicting seed gene functions comprised of three steps: i) Preparing gene lists and sets; ii) constructing a co-expression matrix (CEM) on gene lists by Spearman correlation coefficient (SCC) method and iii) predicting gene functions by GBA algorithm.

A hierarchical method based on weighted extreme gradient boosting in ECG heartbeat classification.

Background And Objective: Electrocardiogram (ECG) is a useful tool for detecting heart disease. Automated ECG diagnosis allows for heart monitoring on small devices, especially on wearable devices. In order to recognize arrhythmias automatically, accurate classification method for electrocardiogram (ECG) heartbeats was studied in this paper.

Combined Menin and EGFR Inhibitors Synergize to Suppress Colorectal Cancer via EGFR-Independent and Calcium-Mediated Repression of SKP2 Transcription.

Menin is a nuclear epigenetic regulator that can both promote and suppress tumor growth in a highly tissue-specific manner. The role of menin in colorectal cancer, however, remains unclear. Here, we demonstrate that menin was overexpressed in colorectal cancer and that inhibition of menin synergized with small-molecule inhibitors of EGFR (iEGFR) to suppress colorectal cancer cells and tumor xenografts in an EGFR-independent manner.