Publications by authors named "A KIRSCH"

Obesity is one of the major global health concerns of the 21st century, associated with many comorbidities such as type 2 diabetes mellitus (T2DM), metabolic dysfunction-associated steatotic liver disease, and early and aggressive atherosclerotic cardiovascular disease, which is the leading cause of death worldwide. Bile acids (BAs) and incretins are gut hormones involved in digestion and absorption of fatty acids, and insulin secretion, respectively. In recent years BAs and incretins are increasingly recognized as key signaling molecules, which target multiple tissues and organs, beyond the gastro-intestinal system.

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Bismuth ferrites, specifically perovskite-type BiFeO and mullite-type BiFeO, hold significant technological promise as catalysts, photovoltaics, and room-temperature multiferroics. However, challenges arise due to their frequent cocrystallization, particularly in the nanoregime, hindering the production of phase-pure materials. This study unveils a controlled sol-gel crystallization approach, elucidating the phase formation complexities in the bismuth ferrite oxide system by coupling thermochemical analysis and total scattering with pair distribution function analysis.

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Article Synopsis
  • The study explored how human vocal fold fibroblasts (hVFF) interact with macrophages in the presence of cigarette smoke extract (CSE) and vibration, focusing on vocal fold inflammation.
  • Researchers cultured hVFF with CSE, applying either static or dynamic conditions, and then measured various mRNA and protein levels to assess inflammation.
  • Findings revealed that vibration may reduce CSE-induced inflammatory responses in hVFF, suggesting potential mechanisms to address voice disorders linked to smoking-related inflammation.
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  • The study introduces a new method using non-linear modeling to predict how extended-release tablets dissolve, integrating techniques like factorial design, curve fitting, and artificial neural networks (ANN).
  • Key factors examined include different grades of hydroxypropylmethylcellulose (HPMC) and carboxymethylcellulose (CMC), lubrication of the active pharmaceutical ingredient (API), and the force used in tablet compression.
  • Results show that non-linear models, particularly ANN, are more effective than traditional linear techniques (like partial least squares and multiple linear regression) at capturing the complex interactions influencing drug release in these formulations.
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