Applied Sciences & Arts Northwestern Switzerland University

The objectives of this study were to ascertain the prevalence of vision and/or hearing impairment and investigate their association with cognitive impairment in nursing home residents in Switzerland.

The sample comprised individuals aged 65–105 (mean = 84.0 and SD = 7.2) newly admitted for long-term care in one of 715 Swiss nursing homes from 2010 to 2019 (N = 132,880). Items from the Minimum Data Set of the Resident Assessment Instrument Swiss Version 2.0 assessed occurrence of hearing impairment (HI), vision impairment (VI), and dual sensory impairment (DSI, both HI and VI). We conducted logistic regression analyses to examine associations of each sensory impairment to cognitive impairment, controlling for medical and demographic factors.

Sensory impairment was present in 57.28% of residents (HI 19.16%, VI 15.13%, and DSI: 22.99%) and cognitive impairment in 57.29%. The likelihood of cognitive impairment was greatest for DSI (prevalence ratio (PR) 1.58; 95% confidence interval (CI) 1.56–1.60), followed by HI (PR 1.35; 95% CI 1.33–1.37) and VI (PR 1.18; 95% CI 1.16–1.20). The average marginal effect for DSI on cognitive impairment exceeded the sum of effects for HI and VI. Stratified models revealed that male sex, younger age, and higher medical comorbidity were associated with increased likelihood of cognitive impairment in DSI.

Sensory impairments are prevalent among newly admitted nursing home residents. While HI and VI are independently associated with cognitive impairment, an interactive burden emerges when they co-occur as dual sensory impairment.

New approach methodologies (NAMs), including microphysiological systems (MPS), are emerging as alternatives to animal testing. In the liver, chronic hepatocellular damage can progress to fibrosis, which has been described by an Adverse Outcome Pathway (AOP). However, standardized in vitro models that capture and quantify key AOP events and cell-cell interactions are lacking. We developed a scalable liver fibrosis model using the 384-well Akura™ Twin microplate featuring 168 interconnected well pairs. We studied fibrosis progression by seeding HepaRG microtissues (MTs), with or without THP-1 cells in alpha wells and hepatic stellate cell (hTERT-HSC) MTs in beta wells. Cell health and metabolic activity were monitored via specific sensors that detect glucose and lactate levels. Transforming growth factor beta 1 (TGF-β1), methotrexate (MTX) and acetaminophen (APAP) reduced albumin production, indicating hepatocellular injury. TGF-β1 activated THP-1, increasing ALOX5AP, TREM2, and TGF-β1 mRNA expression. PAI-1 protein levels increased following treatment with TGF-β1, particularly in HepaRG-THP-1 co-cultures. In hTERT-HSCs, TGF-β1 also induced expression of fibrosis markers (ACTA2, COL1A1, COL3A1 and FN1) and increased stress fibers and fibronectin expression. Extracellular matrix remodeling was confirmed by elevated Pro-Collagen 1A1 and CTGF protein levels upon TGF-β1 treatment. The Akura™ Twin platform enables high-throughput modeling of liver fibrosis, mimicking the key events of the liver fibrosis AOP. This model, combining a high-throughput MPS with established cell lines, offers a promising tool to investigate fibrosis mechanisms and advancing quantitative AOP development. Journal: Toxicology (Special Issue: Hepatotoxicity: mechanisms and animal-free prediction models).

Mesoporous silica are promising bio-enabling carriers for poorly soluble drugs. However, a comprehensive understanding of drug-silica interactions and their impact on drug release remains limited. Apart from urgently needed experimental tools, predictive in silico tools that consider drug-carrier interactions in aqueous media are currently lacking. To address this gap, a novel in silico approach (silica-water partitioning coefficient) was introduced in this study. A series of ten drugs were loaded onto a mesoporous carrier (Parteck® SLC 500), and the products were analyzed using differential scanning calorimetry (DSC) and X-ray powder diffraction (XRPD). In vitro dissolution (USP II) profiles of drug-loaded formulations were analyzed and correlated with a newly introduced silica-water partitioning coefficient derived from chemical potential calculations using the Conductor-like Screening Model for Real Solvents (COSMO-RS). Strong correlations were observed between dissolution parameters, such as the initial release slopes (Pearson r = -0.98; p = < 0.05) and AUC values (Pearson r = -0.79; p < 0.05), and the calculated chemical potential-based partitioning coefficient. This study introduces a predictive method based on COSMO-RS-derived chemical potentials to estimate silica-water partitioning for drugs, thereby predicting their release performance from mesoporous silica formulations. The results demonstrate that these calculated chemical potentials can qualitatively rank the drug release kinetics in aqueous media. Further investigation with additional compounds and carrier types may broaden the applicability of this approach as a mechanistic tool for mesoporous silica formulation development and contribute to narrowing the gap toward future clinical translation.