Structural classification of Ag and Cu nanocrystals with machine learning.

We use machine learning (ML) to classify the structures of mono-metallic Cu and Ag nanoparticles. Our datasets comprise a broad range of structures - both crystalline and amorphous - derived from parallel-tempering molecular dynamics simulations of nanoparticles in the 100-200 atom size range. We construct nanoparticle features using common neighbor analysis (CNA) signatures, and we utilize principal component analysis to reduce the dimensionality of the CNA feature set.

Machine learning for the detection and diagnosis of cognitive impairment in Parkinson's Disease: A systematic review.

Background: Parkinson's Disease is the second most common neurological disease in over 60s. Cognitive impairment is a major clinical symptom, with risk of severe dysfunction up to 20 years post-diagnosis. Processes for detection and diagnosis of cognitive impairments are not sufficient to predict decline at an early stage for significant impact.

PLA2G2D fosters angiogenesis in non-small cell lung cancer through aerobic glycolysis.

Non-small cell lung cancer (NSCLC) stands prominent among the prevailing and formidable oncological entities. The immune and metabolic-related molecule Phospholipase A2, group IID (PLA2G2D) exerts promotional effects on tumor progression. However, its involvement in cancer angiogenesis remains elusive.

Minimum Free-Energy Shapes of Ag Nanocrystals: Vacuum vs Solution.

We use two variants of replica-exchange molecular dynamics (MD) simulations, parallel tempering MD and partial replica exchange MD, to probe the minimum free-energy shapes of Ag nanocrystals containing 100-200 atoms in a vacuum, ethylene glycol (EG) solvent, and EG solvent with a PVP polymer containing 100 repeat units. Our simulations reveal a shape intermediate between a Dh and an Ih, a Dh-Ih, that has distinct structural signatures and magic sizes. We find several prominent features associated with entropy: pure FCC nanocrystals are less common than FCC crystals containing stacking faults, and crystals with the minimum potential energy are not always preferred over the range of relevant temperatures.

Prevalence of and factors associated with alexithymia among patients with chronic obstructive pulmonary disease in China: a cross-sectional study.

Background: Alexithymia is a common psychological disorder. However, few studies have investigated its prevalence and predictors in patients with chronic obstructive pulmonary disease (COPD). Therefore, we aimed to determine the prevalence and predictors of alexithymia in Chinese patients.

Identification of a dysregulated ceRNA network modulated by copy number variation-driven lncRNAs in lung squamous cell carcinoma.

Lung cancer is primarily responsive for cancer death, and its progression is aggressively affected by copy number variation (CNV). Through bioinformatics approach, a ceRNA network of CNV-driven lncRNAs in lung squamous cell carcinoma (LUSC) patients was constructed. Data on normal and LUSC tumor tissue from The Cancer Genome Atlas (TCGA)-LUSC dataset were subjected to differential analysis, and differentially expressed lncRNAs (DElncRNAs), DEmiRNAs, and DEmRNAs were obtained.

EZH2 affects malignant progression and DNA damage repair of lung adenocarcinoma cells by regulating RAI2 expression.

Background: Lung adenocarcinoma (LUAD) is featured in high morbidity and mortality. Aberrant activation of the histone methyltransferase EZH2 has close association with cancer progression. This research aimed to deeply dive into the role and possible molecular mechanisms of EZH2 and its downstream genes in malignant progression and DNA damage repair of LUAD cells.

MiR-129-2-3p Inhibits Esophageal Carcinoma Cell Proliferation, Migration, and Invasion Targeting DNMT3B.

Purpose: The study aims to explore the regulatory mechanism of miR-129-2-3p underlying esophageal carcinoma (EC) cell progression and generate new ideas for targeted treatment of EC.

Methods: Mature miRNA expression data and total RNA sequencing data of EC in the TCGAESCA dataset were utilized to explore differentially expressed miRNAs (DEmiRNAs). StarBase database was then utilized to predict targets of miRNA.

Analysis of the Diagnosis Model of Peripheral Non-Small-Cell Lung Cancer under Computed Tomography Images.

This study aimed to explore the effect of deep learning models on lung CT image lung parenchymal segmentation (LPS) and the application value of CT image texture features in the diagnosis of peripheral non-small-cell lung cancer (NSCLC). Data of peripheral lung cancer (PLC) patients was collected retrospectively and was divided into peripheral SCLC group and peripheral NSCLC group according to the pathological examination results, ResNet50 model and feature pyramid network (FPN) algorithm were undertaken to improve the Mask-RCNN model, and after the MaZda software extracted the texture features of the CT images of PLC patients, the Fisher coefficient was used to reduce the dimensionality, and the texture features of the CT images were analyzed and compared. The results showed that the average Dice coefficients of the 2D CH algorithm, Faster-RCNN, Mask-RCNN, and the algorithm proposed in the validation set were 0.

miR-126 regulates the proliferation, migration, invasion, and apoptosis of non-small lung cancer cells via AKT2/HK2 axis.

This study tended to clarify the role of miR-126 in non-small cell lung cancer (NSCLC) cell biological behaviors in vitro, containing cell proliferation, migration, invasion, and apoptosis. miRNA expression microarray related to NSCLC was accessed from gene expression omnibus (GEO) database and subjected to differential analysis using the "limma" package. Real-time quantitative PCR was conducted to assess the expression of miR-126 in NSCLC cell lines.

Effectiveness of cognitive behavior therapy for sleep disturbance and glycemic control in persons with type 2 diabetes mellitus: A community-based randomized controlled trial in China.

Background: Poor sleep quality is a common clinical feature in patients with type 2 diabetes mellitus (T2DM), and often negatively related with glycemic control. Cognitive behavioral therapy (CBT) may improve sleep quality and reduce blood sugar levels in patients with T2DM. However, it is not entirely clear whether CBT delivered by general practitioners is effective for poor sleep quality in T2DM patients in community settings.

MiR-196b Promotes the Invasion and Migration of Lung Adenocarcinoma Cells by Targeting AQP4.

Objective: We aimed to investigate the mechanism of the regulatory axis of miR-196b/AQP4 underlying the invasion and migration of lung adenocarcinoma (LUAD) cells.

Methods: LUAD miRNA and mRNA expression profiles were downloaded from TCGA database and then differential analysis was used to identify the target miRNA. Target gene for the miRNA was obtained via prediction using 3 bioinformatics databases and intersection with the differentially expressed mRNAs searched from TCGA-LUAD.

Retinal Vascular Network Topology Reconstruction and Artery/Vein Classification via Dominant Set Clustering.

The estimation of vascular network topology in complex networks is important in understanding the relationship between vascular changes and a wide spectrum of diseases. Automatic classification of the retinal vascular trees into arteries and veins is of direct assistance to the ophthalmologist in terms of diagnosis and treatment of eye disease. However, it is challenging due to their projective ambiguity and subtle changes in appearance, contrast, and geometry in the imaging process.

Divergence of Gradient Convolution: Deformable Segmentation With Arbitrary Initializations.

In this paper, we propose a unified approach to deformable model-based segmentation. The fundamental force field of the proposed method is based on computing the divergence of a gradient convolution field (GCF), which makes the full use of directional information of the image gradient vectors and their interactions across image domain. However, instead of directly using such a vector field for deformable segmentation as in the conventional approaches, we derive a more salient representation for contour evolution, and very importantly, we demonstrate that this representation of image force field not only leads to global minimum through convex relaxation but also can achieve the same result using the conventional gradient descent with an intrinsic regularization.

The mzqLibrary--An open source Java library supporting the HUPO-PSI quantitative proteomics standard.

The mzQuantML standard has been developed by the Proteomics Standards Initiative for capturing, archiving and exchanging quantitative proteomic data, derived from mass spectrometry. It is a rich XML-based format, capable of representing data about two-dimensional features from LC-MS data, and peptides, proteins or groups of proteins that have been quantified from multiple samples. In this article we report the development of an open source Java-based library of routines for mzQuantML, called the mzqLibrary, and associated software for visualising data called the mzqViewer.

Enhancement of fiber orientation distribution reconstruction in diffusion-weighted imaging by single channel blind source separation.

In diffusion-weighted imaging (DWI), reliable fiber tracking results rely on the accurate reconstruction of the fiber orientation distribution function (fODF) in each individual voxel. For high angular resolution diffusion imaging (HARDI), deconvolution-based approaches can reconstruct the complex fODF and have advantages in terms of computational efficiency and no need to estimate the number of distinct fiber populations. However, HARDI-based methods usually require relatively high b-values and a large number of gradient directions to produce good results.

[Fluorescence property of OBBE and its application].

The effects of acidity and temperature on the fluorescent characteristics of N-N-bis-(O-Carboxylphenyl)-Oxamide (OBBE) have been studied in details. And the quantum efficiency of fluorescence has been measured. In a pH 8-9.