Radiogenomics analysis reveals the associations of dynamic contrast-enhanced–MRI features with gene expression characteristics, PAM50 subtypes, and prognosis of breast cancer

BackgroundTo investigate reliable associations between dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) features and gene expression characteristics in breast cancer (BC) and to develop and validate classifiers for predicting PAM50 subtypes and prognosis from DCE-MRI non-invasively.MethodsTwo radiogenomics cohorts with paired DCE-MRI and RNA-sequencing (RNA-seq) data were collected from local and public databases and divided into discovery (n = 174) and validation cohorts (n = 72). Six external datasets (n = 1,443) were used for prognostic validation. Spatial–temporal features of DCE-MRI were extracted, normalized properly, and associated with gene expression to identify the imaging features that can indicate subtypes and prognosis.ResultsExpression of genes including RBP4, MYBL2, and LINC00993 correlated significantly with DCE-MRI features (q-value < 0.05). Importantly, genes in the cell cycle pathway exhibited a significant association with imaging features (p-value < 0.001). With eight imaging-associated genes (CHEK1, TTK, CDC45, BUB1B, PLK1, E2F1, CDC20, and CDC25A), we developed a radiogenomics prognostic signature that can distinguish BC outcomes in multiple datasets well. High expression of the signature indicated a poor prognosis (p-values < 0.01). Based on DCE-MRI features, we established classifiers to predict BC clinical receptors, PAM50 subtypes, and prognostic gene sets. The imaging-based machine learning classifiers performed well in the independent dataset (areas under the receiver operating characteristic curve (AUCs) of 0.8361, 0.809, 0.7742, and 0.7277 for estrogen receptor (ER), human epidermal growth factor receptor 2 (HER2)-enriched, basal-like, and obtained radiogenomics signature). Furthermore, we developed a prognostic model directly using DCE-MRI features (p-value < 0.0001).ConclusionsOur results identified the DCE-MRI features that are robust and associated with the gene expression in BC and displayed the possibility of using the features to predict clinical receptors and PAM50 subtypes and to indicate BC prognosis

Protective effects of catalpol on cardio-cerebrovascular diseases: A comprehensive review

Catalpol, an iridoid glucoside isolated from Rehmannia glutinosa, has gained attention due to its potential use in treating cardio-cerebrovascular diseases (CVDs). This extensive review delves into recent studies on catalpol's protective properties in relation to various CVDs, such as atherosclerosis, myocardial ischemia, infarction, cardiac hypertrophy, and heart failure. The review also explores the compound's anti-oxidant, anti-inflammatory, and anti-apoptotic characteristics, emphasizing the role of vital signaling pathways, including PGC-1α/TERT, PI3K/Akt, AMPK, Nrf2/HO-1, estrogen receptor (ER), Nox4/NF-κB, and GRP78/PERK. The article discusses emerging findings on catalpol's ability to alleviate diabetic cardiovascular complications, thrombosis, and other cardiovascular-related conditions. Although clinical studies specifically addressing catalpol's impact on CVDs are scarce, the compound's established safety and well-tolerated nature suggest that it could be a valuable treatment alternative for CVD patients. Further investigation into catalpol and related iridoid derivatives may unveil new opportunities for devising natural and efficacious CVD therapies

Tuning the Dimensionality of Interpenetration in a Pair of Framework-Catenation Isomers To Achieve Selective Adsorption of CO₂ and Fluorescent Sensing of Metal Ions

A pair of framework-catenation isomers (<b>UPC-19</b> and <b>UPC-20</b>) based on an anthracene-functionality dicarboxylate ligand were synthesized and characterized for the first time through tuning of the dimensionality of interpenetration. The interpenetration dimensionality significantly influences the properties including the porosity, gas-uptake capacity, and fluorescent sensing ability: <b>UPC-19</b> with 5-fold interpenetration is nonporous, whereas the 3-fold interpenetration form of <b>UPC-20</b> is porous and exhibits selective adsorption of CO₂ and fluorescent sensing of Cu²⁺ and Fe³⁺ through fluorescence quenching

Tuning the Dimensionality of Interpenetration in a Pair of Framework-Catenation Isomers To Achieve Selective Adsorption of CO₂ and Fluorescent Sensing of Metal Ions

A pair of framework-catenation isomers (<b>UPC-19</b> and <b>UPC-20</b>) based on an anthracene-functionality dicarboxylate ligand were synthesized and characterized for the first time through tuning of the dimensionality of interpenetration. The interpenetration dimensionality significantly influences the properties including the porosity, gas-uptake capacity, and fluorescent sensing ability: <b>UPC-19</b> with 5-fold interpenetration is nonporous, whereas the 3-fold interpenetration form of <b>UPC-20</b> is porous and exhibits selective adsorption of CO₂ and fluorescent sensing of Cu²⁺ and Fe³⁺ through fluorescence quenching

Label-retention expansion microscopy.

Expansion microscopy (ExM) increases the effective resolving power of any microscope by expanding the sample with swellable hydrogel. Since its invention, ExM has been successfully applied to a wide range of cell, tissue, and animal samples. Still, fluorescence signal loss during polymerization and digestion limits molecular-scale imaging using ExM. Here, we report the development of label-retention ExM (LR-ExM) with a set of trifunctional anchors that not only prevent signal loss but also enable high-efficiency labeling using SNAP and CLIP tags. We have demonstrated multicolor LR-ExM for a variety of subcellular structures. Combining LR-ExM with superresolution stochastic optical reconstruction microscopy (STORM), we have achieved molecular resolution in the visualization of polyhedral lattice of clathrin-coated pits in situ

Age-related seroprevalence trajectories of seasonal coronaviruses in children including neonates in Guangzhou, China

Objectives: Four seasonal coronaviruses, including human coronavirus (HCoV)-229E and HCoV-OC43, HCoV-NL63, and HCoV-HKU1 cause approximately 15-30% of common colds in adults. However, the full landscape of the immune trajectory to these viruses that covers the whole childhood period is still not well understood. Methods: We evaluated the serological responses against the four seasonal coronaviruses in 1886 children aged under 18 years by using enzyme-linked immunosorbent assay. The optical density values against each HCoV were determined from each sample. Generalized additive models were constructed to determine the relationship between age and seroprevalence throughout the whole childhood period. The specific antibody levels against the four seasonal coronaviruses were also tested from the plasma samples of 485 pairs of postpartum women and their newborn babies. Results: The immunoglobulin (Ig) G levels of the four seasonal coronaviruses in the mother and the newborn babies were highly correlated (229E: r = 0.63; OC43: r = 0.65; NL63: r = 0.69; HKU1: r = 0.63). The seroprevalences in children showed a similar trajectory in that the levels of IgG in the neonates dropped significantly and reached the lowest level after the age of around 1 year (229E: 1.18 years; OC43: 0.97 years; NL63: 1.01 years; HKU1: 1.02 years) and then resurgence in the children who aged older than 1 year. Using the lowest level from the generalized additive models as our cutoff, the seroprevalences for HCoV-229E, HCoV-OC43, HCoV-NL63, and HCoV-HKU1 were 98.11%, 96.23%, 96.23% and 94.34% at the age of 16-18 years. Conclusion: Mothers share HCoV-specific IgGs with their newborn babies and the level of maternal IgGs waned at around 1 year after birth. The resurgence of the HCoV-specific IgGs was found thereafter with the increase in age suggesting repeated infection occurred in children