Innovative foam drying technique for salted egg yolk powder production.

Background: The powderization of salted egg yolks can circumvent the gelatinization issues that occur during frozen storage. In this study, salted egg yolk powder (SEYP) was prepared using microwave-assisted foam drying (MFD) technology.

Results: The results show that, compared to traditional microwave drying and hot-air drying, the SEYP prepared by MFD exhibits a bright color and a loose structure, and shows significant improvements in emulsifying properties, lecithin retention rate and antioxidant activity (P < 0.

Tracking the evolution of esophageal squamous cell carcinoma under dynamic immune selection by multi-omics sequencing.

Intratumoral heterogeneity (ITH) has been linked to decreased efficacy of clinical treatments. However, although genomic ITH has been characterized in genetic, transcriptomic and epigenetic alterations are hallmarks of esophageal squamous cell carcinoma (ESCC), the extent to which these are heterogeneous in ESCC has not been explored in a unified framework. Further, the extent to which tumor-infiltrated T lymphocytes are directed against cancer cells, but how the immune infiltration acts as a selective force to shape the clonal evolution of ESCC is unclear.

Preoperative Prediction of Microsatellite Instability in Rectal Cancer Using Five Machine Learning Algorithms Based on Multiparametric MRI Radiomics.

To establish and verify radiomics models based on multiparametric MRI for preoperatively identifying the microsatellite instability (MSI) status of rectal cancer (RC) by comparing different machine learning algorithms. This retrospective study enrolled 383 (training set, 268; test set, 115) RC patients between January 2017 and June 2022. A total of 4148 radiomics features were extracted from multiparametric MRI, including T-weighted imaging, T-weighted imaging, apparent diffusion coefficient, and contrast-enhanced T-weighted imaging.

The Growth Factors: Potential Biomarkers and Therapeutic Targets in Kidney Diseases.

Background: Kidney diseases are a prevalent health problem worldwide. Although substantial progress has been made in understanding the pathophysiology of kidney disease, currently there is no satisfactory clinical treatment available to prevent or treat kidney disease. Therefore, strategies to establish early diagnosis, identify the key molecules, and develop novel therapeutic interventions to slow the progression of kidney diseases and reduce their complications are encouraged.

A novel computed tomography radiomic nomogram for early evaluation of small airway dysfunction development.

The common respiratory abnormality, small airway dysfunction (fSAD), is easily neglected. Its prognostic factors, prevalence, and risk factors are unclear. This study aimed to explore the early detection of fSAD using radiomic analysis of computed tomography (CT) images to predict fSAD progress.

The Updates of Podocyte Lipid Metabolism in Proteinuric Kidney Disease.

Background: Podocytes, functionally specialized and terminally differentiated glomerular visceral epithelial cells, are critical for maintaining the structure and function of the glomerular filtration barrier. Podocyte injury is considered as the most important early event contributing to proteinuric kidney diseases such as obesity-related renal disease, diabetic kidney disease, focal segmental glomerulosclerosis, membranous nephropathy, and minimal change disease. Although considerable advances have been made in the understanding of mechanisms that trigger podocyte injury, cell-specific and effective treatments are not clinically available.

Radiomic nomogram based on MRI to predict grade of branching type intraductal papillary mucinous neoplasms of the pancreas: a multicenter study.

Background: Accurate diagnosis of high-grade branching type intraductal papillary mucinous neoplasms (BD-IPMNs) is challenging in clinical setting. We aimed to construct and validate a nomogram combining clinical characteristics and radiomic features for the preoperative prediction of low and high-grade in BD-IPMNs.

Methods: Two hundred and two patients from three medical centers were enrolled.

An Integrative Nomogram for Identifying Early-Stage Parkinson's Disease Using Non-motor Symptoms and White Matter-Based Radiomics Biomarkers From Whole-Brain MRI.

To develop and validate an integrative nomogram based on white matter (WM) radiomics biomarkers and nonmotor symptoms for the identification of early-stage Parkinson's disease (PD). The brain magnetic resonance imaging (MRI) and clinical characteristics of 336 subjects, including 168 patients with PD, were collected from the Parkinson's Progress Markers Initiative (PPMI) database. All subjects were randomly divided into training and test sets.

Predicting the progression of Parkinson's disease using conventional MRI and machine learning: An application of radiomic biomarkers in whole-brain white matter.

Purpose: This study aimed to develop and validate a radiomics model based on whole-brain white matter and clinical features to predict the progression of Parkinson disease (PD).

Methods: PD patient data from the Parkinson's Progress Markers Initiative (PPMI) database was evaluated. Seventy-two PD patients with disease progression, as measured by the Hoehn-Yahr Scale (HYS) (stage 1-5), and 72 PD patients with stable PD were matched by sex, age, and category of HYS and included in the current study.

Development and clinical application of deep learning model for lung nodules screening on CT images.

Lung cancer screening based on low-dose CT (LDCT) has now been widely applied because of its effectiveness and ease of performance. Radiologists who evaluate a large LDCT screening images face enormous challenges, including mechanical repetition and boring work, the easy omission of small nodules, lack of consistent criteria, etc. It requires an efficient method for helping radiologists improve nodule detection accuracy with efficiency and cost-effectiveness.

Predicting Chronic Myocardial Ischemia Using CCTA-Based Radiomics Machine Learning Nomogram.

Background: Coronary computed tomography angiography (CCTA) is a well-established non-invasive diagnostic test for the assessment of coronary artery diseases (CAD). CCTA not only provides information on luminal stenosis but also permits non-invasive assessment and quantitative measurement of stenosis based on radiomics.

Purpose: This study is aimed to develop and validate a CT-based radiomics machine learning for predicting chronic myocardial ischemia (MIS).

Correlation of vitamin D receptor gene (ApaI) polymorphism with periodontitis: A meta-analysis of Chinese population.

Many studies have tried to elucidate the connection between vitamin D receptor (VDR) gene (ApaI) polymorphism and periodontitis; however, so far there is no consensus. To further assess the impact of ApaI polymorphism on periodontitis risk, we have conducted a meta-analysis of Chinese population. Relevant literatures were searched according to PubMed and Chinese database in January 2019.

Consistency of radiologists in identifying pulmonary nodules based on low-dose computed tomography.

Background: To study the consistency of radiologists in identifying pulmonary nodules based on low-dose computed tomography (LDCT), and to analyze factors that affect the consistency.

Methods: A total of 750 LDCT cases were collected randomly from three medical centers. Three experienced chest radiologists independently evaluated and detected the pulmonary nodules on 625 cases of LDCT images.

Radiomics nomogram based on MRI for predicting white matter hyperintensity progression in elderly adults.

Background: White matter hyperintensity (WMH) is widely observed in aging brain and is associated with various diseases. A pragmatic and handy method in the clinic to assess and follow up white matter disease is strongly in need.

Purpose: To develop and validate a radiomics nomogram for the prediction of WMH progression.

Diverse modes of clonal evolution in HBV-related hepatocellular carcinoma revealed by single-cell genome sequencing.

Hepatocellular carcinoma (HCC) is a cancer of substantial morphologic, genetic and phenotypic diversity. Yet we do not understand the relationship between intratumor heterogeneity and the associated morphologic/histological characteristics of the tumor. Using single-cell whole-genome sequencing to profile 96 tumor cells (30-36 each) and 15 normal liver cells (5 each), collected from three male patients with HBV-associated HCC, we confirmed that copy number variations occur early in hepatocarcinogenesis but thereafter remain relatively stable throughout tumor progression.

ICSNPathway: identify candidate causal SNPs and pathways from genome-wide association study by one analytical framework.

Genome-wide association study (GWAS) is widely utilized to identify genes involved in human complex disease or some other trait. One key challenge for GWAS data interpretation is to identify causal SNPs and provide profound evidence on how they affect the trait. Currently, researches are focusing on identification of candidate causal variants from the most significant SNPs of GWAS, while there is lack of support on biological mechanisms as represented by pathways.

i-GSEA4GWAS: a web server for identification of pathways/gene sets associated with traits by applying an improved gene set enrichment analysis to genome-wide association study.

Genome-wide association study (GWAS) is nowadays widely used to identify genes involved in human complex disease. The standard GWAS analysis examines SNPs/genes independently and identifies only a number of the most significant SNPs. It ignores the combined effect of weaker SNPs/genes, which leads to difficulties to explore biological function and mechanism from a systems point of view.

MyBASE: a database for genome polymorphism and gene function studies of Mycobacterium.

Background: Mycobacterial pathogens are a major threat to humans. With the increasing availability of functional genomic data, research on mycobacterial pathogenesis and subsequent control strategies will be greatly accelerated. It has been suggested that genome polymorphisms, namely large sequence polymorphisms, can influence the pathogenicity of different mycobacterial strains.