Mate Whenua-follow-up after early medical abortion: study protocol for a randomized controlled trial.

Background: Early medical abortion (EMA) is safe and effective; an uncommon but crucial adverse outcome is ongoing live pregnancy. The best method of follow-up after EMA to detect ongoing pregnancy is a critical research gap. Few trials compare blood or urine pregnancy tests to ultrasound scans, and no trial compares these tests to each other.

Split Hybridization Probe Utilizing a DNA Fluorescent Light-up Aptamer as a Signal Reporter for Sequence-Specific Nucleic Acid Analysis.

DNA-based fluorescent light-up aptamers (FLAPs) are promising for bioanalytical assays because they provide a low-cost fluorescent signal readout without the need for labeling of nucleic acid signal reporters with fluorophores and/or quenchers, unlike conventional hybridization probes used for instantaneous nucleic acid detection. Instead, FLAPs non-covalently bind dye ligands , which exhibit intrinsically low fluorescence in aqueous solutions, but become highly emitting upon FLAP binding. This protocol describes an algorithm to design split light-up aptamer sensors (SLASs) utilizing DAP-10-42, the most efficient DNA FLAP reported thus far.

Endoscopic Closure of Iatrogenic Ventricular Septal Defect After 2 Previous Aortic Valve Replacements.

Background: A 79-year-old male patient previously had undergone 2 aortic valve replacements via median sternotomy.

Case Summary: He presented with progressive shortness of breath shortly after the second procedure. This led to the identification of an iatrogenic perimembranous ventricular septal defect on a transthoracic echocardiogram.

Artificial intelligence and digital twins for the personalised prediction of hypertension risk.

Hypertension is a significant global health challenge, contributing substantially to morbidity and mortality through its association with various cardiovascular diseases. Traditional approaches to hypertension risk prediction, which rely on broad epidemiological data and common risk factors, often fail to account for individual variability, highlighting the need for advanced data-driven methodologies. This review examines the role of Artificial Intelligence (AI) and Machine Learning (ML) in enhancing the prediction of hypertension risk by incorporating a range of data sources, including clinical, lifestyle, and genetic factors.

Decoding the interstitial/vacancy nature of dislocation loops with their morphological fingerprints in face-centered cubic structure.

Dislocation loops are critical defects inducing detrimental effects like embrittlement and swelling in materials under irradiation. Distinguishing their nature (interstitial- or vacancy-type) is a long-standing challenge with great implications for understanding radiation damage. Here, we demonstrate that the morphology of radiation-induced Frank loops can unveil their nature in face-centered cubic (fcc) structure: Circular loops are interstitial-type in all fcc materials, while segmented loops are vacancy-type in high stacking fault energy (SFE) alloys but varied-type in low SFE and high-entropy alloys.