‘Diet’ deep canonical correlation analysis for high‐dimensional genetics study of brain imaging phenotypes in Alzheimer’s disease.

Background: Understanding the relationship between genetic variations and brain imaging phenotypes is an important issue in Alzheimer's disease (AD) research. As an alternative to GWAS univariate analyses, canonical correlation analysis (CCA) and its deep learning extension (DCCA) are widely used to identify associations between multiple genetic variants such as SNPs and multiple imaging traits such as brain ROIs from PET/MRI. However, with the recent availability of numerous genetic variants from genotyping and whole genome sequencing data for AD, these approaches often suffer from severe overfitting when dealing with ‘fat’ genetics data, e.

Exploring Semantic Topics in Dementia Caregiver Tweets.

Background: Caring for family caregivers of dementia patients has grown to an important topic. Social media platforms, like Twitter, provide great resources for studying the needs of caregivers. It would be beneficial to understand the caregivers’ interested or concerned topics from their tweets.

Automated Cytometric Gating with Human-Level Performance Using Bivariate Segmentation.

Recent advances in cytometry technology have enabled high-throughput data collection with multiple single-cell protein expression measurements. The significant biological and technical variance between samples in cytometry has long posed a formidable challenge during the gating process, especially for the initial gates which deal with unpredictable events, such as debris and technical artifacts. Even with the same experimental machine and protocol, the target population, as well as the cell population that needs to be excluded, may vary across different measurements.

Multiplexed serum biomarkers to discriminate nonviable and ectopic pregnancy.

Objective: To evaluate combinations of candidate biomarkers to develop a multiplexed prediction model for identifying the viability and location of an early pregnancy. In this study, we assessed 24 biomarkers with multiple machine learning-based methodologies to assess if multiplexed biomarkers may improve the diagnosis of normal and abnormal early pregnancies.

Design: A nested case-control design evaluated the predictive ability and discrimination of biomarkers in patients at risk of early pregnancy failure in the first trimester to classify viability and location.

Fair Canonical Correlation Analysis.

This paper investigates fairness and bias in Canonical Correlation Analysis (CCA), a widely used statistical technique for examining the relationship between two sets of variables. We present a framework that alleviates unfairness by minimizing the correlation disparity error associated with protected attributes. Our approach enables CCA to learn global projection matrices from all data points while ensuring that these matrices yield comparable correlation levels to group-specific projection matrices.

The Dynamic Changes of Seed Microbiota across the Entire Seed Life in the Field.

The seed microbiota is an important component given by nature to plants, protecting seeds from damage by other organisms and abiotic stress. However, little is known about the dynamic changes and potential functions of the seed microbiota during seed development. In this study, we investigated the composition and potential functions of the seed microbiota of rapeseed ().

A Multi-Stain Breast Cancer Histological Whole-Slide-Image Data Set from Routine Diagnostics.

The analysis of FFPE tissue sections stained with haematoxylin and eosin (H&E) or immunohistochemistry (IHC) is essential for the pathologic assessment of surgically resected breast cancer specimens. IHC staining has been broadly adopted into diagnostic guidelines and routine workflows to assess the status of several established biomarkers, including ER, PGR, HER2 and KI67. Biomarker assessment can also be facilitated by computational pathology image analysis methods, which have made numerous substantial advances recently, often based on publicly available whole slide image (WSI) data sets.

Exploring Automated Machine Learning for Cognitive Outcome Prediction from Multimodal Brain Imaging using STREAMLINE.

STREAMLINE is a simple, transparent, end-to-end automated machine learning (AutoML) pipeline for easily conducting rigorous machine learning (ML) modeling and analysis. The initial version is limited to binary classification. In this work, we extend STREAMLINE through implementing multiple regression-based ML models, including linear regression, elastic net, group lasso, and L21 norm.

Comparing Amyloid Imaging Normalization Strategies for Alzheimer's Disease Classification using an Automated Machine Learning Pipeline.

Amyloid imaging has been widely used in Alzheimer's disease (AD) diagnosis and biomarker discovery through detecting the regional amyloid plaque density. It is essential to be normalized by a reference region to reduce noise and artifacts. To explore an optimal normalization strategy, we employ an automated machine learning (AutoML) pipeline, STREAMLINE, to conduct the AD diagnosis binary classification and perform permutation-based feature importance analysis with thirteen machine learning models.

The influence mechanism of hydrogeochemical environment and sulfur and nitrogen cycle on arsenic enrichment in groundwater: A case study of Hasuhai basin, China.

Hydro-biogeochemical processes control the formation and evolution of high arsenic (As) groundwater. However, the effects of nitrogen and sulfur cycles in groundwater on As migration and transformation are not well understood. Thus, twenty-one groundwater samples were collected from the Hasuhai basin.

Polysaccharides Alleviate Acute Lung Injury by Inhibiting Oxidative Stress and Inflammation.

Acute lung injury (ALI) is a kind of lung disease with acute dyspnea, pulmonary inflammation, respiratory distress, and non-cardiogenic pulmonary edema, accompanied by the mid- and end-stage characteristics of COVID-19, clinically. It is imperative to find non-toxic natural substances on preventing ALI and its complications. The animal experiments demonstrated that polysaccharides (PLE) had a potential role in alleviating ALI by inhibiting oxidative stress and inflammation, which was manifested by reducing the levels of serum lung injury indicators (C3, hs-CRP, and GGT), reducing the levels of inflammatory factors (TNF-α, IL-1β, and IL-6), and increasing the activities of antioxidant enzymes (SOD and CAT) in the lung.

Pharmacokinetics and Main Metabolites of Anwulignan in Mice.

Anwulignan is a representative component of Chinese traditional medicine , with strong pharmacological activities. However, there are few reports on its pharmacokinetics and metabolites in the body. In this study, a metabolomic method based on UHPLC-Q-Orbitrap-MS was used to study the pharmacokinetics of anwulignan in the blood, organs, urine, and feces samples of mice after the intragastric administration of anwulignan (10 mg/kg).

Under-Oil Autonomously Regulated Oxygen Microenvironments: A Goldilocks Principle-Based Approach for Microscale Cell Culture.

Oxygen levels in vivo are autonomously regulated by a supply-demand balance, which can be altered in disease states. However, the oxygen levels of in vitro cell culture systems, particularly microscale cell culture, are typically dominated by either supply or demand. Further, the oxygen microenvironment in these systems is rarely monitored or reported.

Molecular Mechanism of the Regulatory Effect of Schisandrol A on the Immune Function of Mice Based on a Transcription Factor Regulatory Network.

The molecular mechanism of the regulatory effed of schizandrol A (SA) on the immune function of cyclophosphamide-induced immunosuppressive mice was explored in this study. On the basis of 1619 differentially expressed genes related to the regulatory effect of SA on the immune function of mice screened in our previous study, transcription factors and their corresponding target genes were screened in the Transcriptional Regulatory Element Database (TRED), and a transcription factor target gene regulatory network was constructed. The key nodes of the network were statistically analyzed to clarify the role of transcription factors in the regulatory network.

Study on the Hepatoprotection of Caulis Polysaccharides in Nonalcoholic Fatty Liver Disease in Rats Based on Metabolomics.

The aim of this study was to investigate the hepatoprotection of Caulis polysaccharides (SCPs) in the nonalcoholic fatty liver disease (NAFLD) induced by high-fat diet (HFD) in rats. A total of 30 Wistar rats were randomly divided into the control group (CON), model group (MOD), and caulis polysaccharide (SCP) group. Except for those in the CON group, the other rats were fed with high-fat diet for 4 weeks to establish an NAFLD model.

Study on the effect of active components of Schisandra chinensis on liver injury and its mechanisms in mice based on network pharmacology.

The aim of this study was to analyze the active components of Schisandra chinensis on liver injury and its mechanism in mice by network pharmacology. The active components of S. chinensis were found through Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and their corresponding targets were predicted.

Liver and Brain Protective Effect of Sulfated Polysaccharides from Residue of Lion's Mane Medicinal Mushroom, Hericium erinaceus (Agaricomycetes), on D-Galactose-Induced Aging Mice.

This work describes the preparation of sulfated Hericium erinaceus residue polysaccharides (SHRPs) and investigates their antioxidant and antiaging effects on D-galactose-induced aging mice. The results indicated that the degree of SO42- substitution was 0.47 ± 0.

Editing homologous copies of an essential gene affords crop resistance against two cosmopolitan necrotrophic pathogens.

Sclerotinia sclerotiorum and Botrytis cinerea are typical necrotrophic pathogens that can attack more than 700 and 3000 plant species, respectively, and cause huge economic losses across numerous crops. In particular, the absence of resistant cultivars makes the stem rot because of S. sclerotiorum the major threat of rapeseed (Brassica napus) worldwide along with Botrytis.

Protective effects of sulfated polysaccharides from Lentinula edodes on the lung and liver of MODS mice.

In this work, the effects of sulfated polysaccharides from Lentinula edodes (SPLE) on zymosan (ZYM)-induced multiple organ dysfunction syndrome (MODS) mice were investigated. Using the MODS mice model, biochemical works have already shown that in mice treated with SPLE, the lung parameters of GGT, C3 and hs-CRP were down-regulated and the hepatic parameters of TC, TG, ALT and AST, HDLC, LDL-C and VLDL-C were improved, the serum levels of CK, Cr and Amy were decreased, and the levels of inflammatory factors such as TNF-α, IL-1β, IL-6 and IL-10 were also reduced, the activity of antioxidant enzymes SOD and CAT enhanced, and the content of MDA was reduced. In addition, histopathology of the lung and liver confirmed the beneficial effects of SPLE on MODS mice, indicating that SPLE played a role in protecting the organ function of MODS mice.

A deep learning based multiscale approach to segment the areas of interest in whole slide images.

This paper addresses the problem of liver cancer segmentation in Whole Slide Images (WSIs). We propose a multi-scale image processing method based on an automatic end-to-end deep neural network algorithm for the segmentation of cancerous areas. A seven-level gaussian pyramid representation of the histopathological image was built to provide the texture information at different scales.

Characterization and Hepatoprotections of Polysaccharides against Multiple Organ Dysfunction Syndrome in Mice.

Background: The liver is one of the most commonly affected organs in multiple organ dysfunction syndrome (MODS). In recent years, there have been many studies on polysaccharides (GLP), but the role of GLP in MODS is still unclear. The purpose of this work was to explore the antioxidant, anti-inflammatory, and protective effects of GLP on the liver in MODS model mice.

Antioxidation, anti-inflammation and anti-fibrosis effect of phosphorylated polysaccharides from Pleurotus djamor mycelia on adenine-induced chronic renal failure mice.

The mycelia polysaccharides (MPS) from Pleurotus djamor were prepared and purified by anion exchange column chromatography, and the phosphate content of phosphorylated MPS (PMPS) was 15.22 ± 0.37%.

Antihyperlipidemic and hepatoprotective properties of alkali- and enzyme-extractable polysaccharides by Dictyophora indusiata.

Hyperlipidemia, a very common disease throughout the world, usually gives rise to severe liver damages. The current experiment was to investigate the antihyperlipidemic and hepatoprotective properties of alkali- and enzyme-extractable Dictyophora indusiata polysaccharides (Al-DPS and En-DPS) on the hyperlipidemic mice. The results of animal experiment in vivo showed that treatment with Al-DPS or En-DPS could improve the excessive level of lipid profiles in serum and liver, as well as strengthen antioxidant status.

Mycelium Polysaccharides from Attenuate CCl-Induced Chronic Liver Injury Via Inhibiting TGFβ1/Smad3 and NF-κB Signal Pathways.

A major fraction (MPT-W), eluted by deionized water, was extracted from mycelium polysaccharides of (MPT), and its antioxidant, anti-fibrosis, and anti-inflammatory activities in CCl-induced chronic liver injury mice, as well as preliminary characterizations, were evaluated. The results showed that MPT-W was a polysaccharide of α- and β-configurations containing xylose (Xyl), fucose (Fuc), mannose (Man), galactose (Gal), and glucose (Glc) with a molar ratio of 0.29:8.