Enhanced nano-LC-MS for analyzing dansylated oral cancer tissue metabolome dissolved in solvents with high elution strength.

Background: Tissue metabolomics analysis, alongside genomics and proteomics, offers crucial insights into the regulatory mechanisms of tumorigenesis. To enhance metabolite detection sensitivity, chemical isotope labeling (CIL) techniques, such as dansylation, have been developed to improve metabolite separation and ionization in mass spectrometry (MS). However, the dissolution of hydrophobic derivatized metabolites in solvents with high acetonitrile content limits the use of liquid chromatography (LC) systems with small-volume reversed-phase (RP) columns.

Improving the Thermal Stability of Indium Oxide n-Type Field-Effect Transistors by Enhancing Crystallinity through Ultrahigh-Temperature Rapid Thermal Annealing.

Ultrathin indium oxide films show great potential as channel materials of complementary metal oxide semiconductor back-end-of-line transistors due to their high carrier mobility, smooth surface, and low leakage current. However, it has severe thermal stability problems (unstable and negative threshold voltage shifts at high temperatures). In this paper, we clarified how the improved crystallinity of indium oxide by using ultrahigh-temperature rapid thermal O annealing could reduce donor-like defects and suppress thermal-induced defects, drastically enhancing thermal stability.

Differential striatal dopamine binding in Parkinson's Disease with and without REM sleep behavior disorder: A Tc-99 m TRODAT-1 SPECT study.

Background: Rapid eye movement (REM) sleep behavior disorder (RBD) is an early and significant prodromal marker for Parkinson's disease (PD). While the association between RBD and PD has been well-documented, the underlying pathophysiology differentiating PD patients with RBD (PD-RBD +) from those without RBD (PD-RBD-) remained unclear. This study aims to investigate the possible relationship between RBD and striatal dopamine depletion in de novo PD patients.

Automatic Single-Cell Harvesting for Fetal Nucleated Red Blood Cell Isolation on a Self-Assemble Cell Array (SACA) Chip.

(1) Background: Fetal chromosomal examination is a critical component of modern prenatal testing. Traditionally, maternal serum biomarkers such as free β-human chorionic gonadotropin (Free β-HCG) and pregnancy-associated plasma protein A (PAPPA) have been employed for screening, achieving a detection rate of approximately 90% for fetuses with Down syndrome, albeit with a false positive rate of 5%. While amniocentesis remains the gold standard for the prenatal diagnosis of chromosomal abnormalities, including Down syndrome and Edwards syndrome, its invasive nature carries a significant risk of complications, such as infection, preterm labor, or miscarriage, occurring at a rate of 7 per 1000 procedures.

Predictive modelling of hospital-acquired infection in acute ischemic stroke using machine learning.

Hospital-acquired infections (HAIs) are serious complication for patients with acute ischemic stroke (AIS), often resulting in poor functional outcomes. However, no existing model can specifically predict HAI in AIS patients. Therefore, we employed the Gradient Boosting matching learning algorithm to establish predictive models for HAI occurrence in AIS patients and poor 30-day functional outcomes (modified Rankin Scale > 2) in AIS patients with HAI by analyzing electronic health records from 6560 AIS patients.