Growth of Highly-Ordered-Crystalline Indium-Gallium-Oxide Thin-Film via Plasma-Enhanced ALD for High Performance Top-Gate Field-Effect Transistors.

This study introduces a novel method for achieving highly ordered-crystalline InGaO [0 ≤ x ≤ 0.6] thin films on Si substrates at 250 °C using plasma-enhanced atomic-layer-deposition (PEALD) with dual seed crystal layers (SCLs) of γ-AlO and ZnO. Field-effect transistors (FETs) with random polycrystalline InGaO channels (grown without SCLs) show a mobility (µFE) of 85.

Metformin inhibits muscle atrophy through the PI3K/AKT/mTOR pathway in a rat model of acute rotator cuff tears.

Background: Muscle atrophy after the rupture of a rotator cuff (RC) tendon is a major factor that increases the risk of secondary complications and re-rupture. Metformin, a type 2 diabetes treatment, can be used to modulate intracellular signaling pathways that promote muscle growth. This study aimed to verify whether systemic metformin administration could prevent supraspinatus (SS) atrophy after RC rupture in a rat model.

Low pH Means More Female Offspring: A Multigenerational Plasticity in the Sex Ratio of Marine Bivalves.

Global changes can profoundly affect the sex determination and reproductive output of marine organisms, disrupting the population structure and ecosystems. High COdriven low pH in the context of ocean acidification (OA) has been shown to severely affect various calcifiers, but less is known about the extent to which low pH influences sex determination and reproduction of marine organisms, particularly mollusks. This study is the first to report a biased sex ratio over multiple generations toward females, driven by exposure to high CO-induced low pH environments, using the ecologically and economically important Portuguese oyster () as a model.

SymScore: Machine learning accuracy meets transparency in a symbolic regression-based clinical score generator.

Self-report questionnaires play a crucial role in healthcare for assessing disease risks, yet their extensive length can be burdensome for respondents, potentially compromising data quality. To address this, machine learning-based shortened questionnaires have been developed. While these questionnaires possess high levels of accuracy, their practical use in clinical settings is hindered by a lack of transparency and the need for specialized machine learning expertise.