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Study Objectives: Sleep disturbances lead to negative health outcomes and caregiver burden, particularly in community settings. This study aimed to investigate a predictive model for sleep efficiency and its associated features in older adults living with dementia in their own homes., Methods: This was an exploratory, observational study. A total of 69 older adults diagnosed with dementia were included in this study. Data were collected via actigraphy for sleep and physical activity for 14 days, a sweat patch for cytokines for 2-3 days, and a survey of diseases, medications, psychological and behavioral symptoms, functional status, and demographics at baseline. Using 730 days of actigraphy, sweat patches, and baseline data, the best prediction model for sleep efficiency was selected and further investigated to explore its associated top 10 features using machine learning analysis., Results: The CatBoost model was selected as the best predictive model for sleep efficiency. In order of importance, the most important features were sleep regularity, number of medications, dementia medication, daytime activity count, instrumental activities of daily living, neuropsychiatric inventory, hypnotics, occupation, tumor necrosis factor-alpha, and waking hour lux., Conclusions: This study established the best sleep efficiency predictive model among community-dwelling older adults with dementia and its associated features using machine learning and various sources, such as the Internet of Things. This study highlights the importance of individualized sleep interventions for community-dwelling older adults with dementia based on associated features., (© 2024 American Academy of Sleep Medicine.)

Benzene occurs naturally and is widely applied in the production process of petrochemical products. It is mainly exposed through the respiratory tract and dermal and metabolized in the liver, leading to systemic health effects, and 1,2,4-trihydroxybenzene (THB) is a benzene metabolite used as a hair dye ingredient in some countries. In an effort to identify a toxic mechanism of THB, we first analyzed the hair of consumers who used a shampoo containing THB, and contrary to our expectations, THB was not persistent in the hair. Following, we treated THB to human keratinocytes and HeLa Chang liver cells. Membrane damage was observed in both cell lines, which was more notable in HeLa Chang liver cells than in keratinocytes. Thus, we decided on HeLa Chang liver cells as target cells for further study. Cell viability decreased sharply between 20 μg/ml and 40 μg/mL, inducing G2/M phase arrest and non-apoptotic cell death. The expression of carcinogenesis-, DNA damage-, and transcriptional dysregulation-related genes were notably up-regulated, and the structure and function of mitochondria were disrupted. The volume of the ER and acidic compartments decreased, and intracellular ROS and calcium ion levels increased. More interestingly, we found that THB formed unique structures within the cells, especially around the nuclear membrane, and that those structures seemed to dig into the nucleus over time. A reverse docking analysis also showed that SULT1A1, CYP2E1, and CAT, known to play a significant role in protecting cells from harmful factors, might be potential target proteins for THB. Taken together, we suggest that THB induces non-apoptotic cell death via structural damage of intracellular organelles, especially the nuclear membrane., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Accurate prediction of binding free energy is crucial for the rational design of drug candidates and understanding protein-ligand interactions. To address this, we have developed four protocols that combine QM/MM calculations and the mining minima (M2) method, tested on 9 targets and 203 ligands. Our protocols carry out free energy processing with or without conformational search on the selected conformers obtained from M2 calculations, where their force field atomic charge parameters are substituted with those obtained from a QM/MM calculation. The method achieved a high Pearson's correlation coefficient (0.81) with experimental binding free energies across diverse targets, demonstrating its generality. Using a differential evolution algorithm with a universal scaling factor of 0.2, we achieved a low mean absolute error of 0.60 kcal mol - 1 . This performance surpasses many existing methods and is comparable to popular relative binding free energy techniques but at significantly lower computational cost., (© 2024. The Author(s).)

The catalytic efficacy of the monobipyridyl (η 6 - para -Cymene)Ru(II) half-metallocene, [( p -Cym)Ru(bpy)Cl] + was evaluated in both mixed homogeneous (dye + catalyst) and heterogeneous hybrid systems (dye/TiO 2 /Catalyst) for photochemical CO 2 reduction. A series of homogeneous photolysis experiments revealed that the ( p -Cym)Ru(II) catalyst engages in two competitive routes for CO 2 reduction (CO 2 to formate conversion via Ru II -hydride vs CO 2 to CO conversion through a Ru II -COOH intermediate). The conversion activity and product selectivity were notably impacted by the p K a value and the concentration of the proton source added. When a more acidic TEOA additive was introduced, the half-metallocene Ru(II) catalyst leaned toward producing formate through the Ru II -H mechanism, with a formate selectivity of 86%. On the other hand, in homogeneous catalysis with TFE additive, the CO 2 -to-formate conversion through Ru II -H was less effective, yielding a more efficient CO 2 -to-CO conversion with a selectivity of >80% (TON formate of 140 and TON CO of 626 over 48 h). The preference between the two pathways was elucidated through an electrochemical mechanistic study, monitoring the fate of the metal-hydride intermediate. Compared to the homogeneous system, the TiO 2 -heterogenized ( p -Cym)Ru(II) catalyst demonstrated enhanced and enduring performance, attaining TONs of 1000 for CO 2 -to-CO and 665 for CO 2 -to-formate.

Background: Patients treated for lung cancer (LC) often experience locoregional failure after initial treatment. Due to technological advances, thoracic reirradiation (re-RT) has become a viable treatment option. We sought to investigate the use of thoracic re-RT in LC patients over a time period characterized by technological advances in a large, multi-center cohort., Methods and Materials: LC patients treated with thoracic re-RT in two University Hospitals from 2010-2020 were identified. Clinical variables and RT data were extracted from the medical records and treatment planning systems. Overall survival (OS) was calculated from the last day of re-RT until death or last follow up., Results: 296 patients (small cell LC n=30, non-small cell LC n=266) were included. Three-dimensional conformal radiation therapy was the RT technique used most frequently (63%), and 86% of all patients were referred for re-RT with palliative treatment intent. During the second half of the study period, the use of thoracic re-RT increased in general, more patients received curative re-RT, and there was an increased use of stereotactic body radiation therapy (SBRT). Median time between initial RT and re-RT was 18 months (range 1-213 months). Only 83/296 patients had combined treatment plans that allowed for registration of combined doses to organs at risk (OAR). Most of the combined doses to OAR were below recommendations from guidelines. Multivariate analysis showed superior OS (p<0.05) in patients treated with curative intent, SBRT or intensity modulated radiation therapy or had excellent performance status prior to re-RT., Conclusions: The use of re-RT increased in the second half of the study period, although 2020 did not follow the trend. The use of SBRT and IMRT became more frequent over the years, yet the majority received palliative re-RT. Combined dose plans were only created for one third of the patients., (Copyright © 2024. Published by Elsevier Inc.)

Grown evidence has shown that the liver and reproductive organs were the main target organs of perfluorooctanoic acid (PFOA). Herein, we studied a toxic mechanism of PFOA using HeLa Chang liver epithelial cells. When incubated with PFOA for 24 h or 48 h, cell proliferation was inhibited in a concentration- and time-dependent fashion, but interestingly, the feature of dead cells was not notable. Mitochondrial volume was increased with concentration and time, whereas the mitochondrial membrane potential and produced ATP amounts were significantly reduced. Autophagosome-like vacuoles and contraction of the mitochondrial inner membrane were observed in PFOA-treated cells. The expression of acetyl CoA carboxylase (ACC) and p-ACC proteins rapidly decreased, and that of mitochondrial dynamics-related proteins increased. The expression of solute carrier family 7 genes, ChaC glutathione-specific gamma-glutamylcyclotransferase 1, and 5S ribosomal RNA gene was up-regulated the most in cells exposed to PFOA for 24 h, and the KEGG pathway analysis revealed that PFOA the most affected metabolic pathways and olfactory transduction. More importantly, PPAR alpha, fatty acid binding protein 1, and CYP450 family 1 subfamily A member 1 were identified as the target proteins for binding between PFOA and cells. Taken together, we suggest that disruption of mitochondrial integrity and function may contribute closely to PFOA-induced cell proliferation inhibition., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Item factor analysis (IFA), also known as Multidimensional Item Response Theory (MIRT), is a general framework for specifying the functional relationship between respondents' multiple latent traits and their responses to assessment items. The key element in MIRT is the relationship between the items and the latent traits, so-called item factor loading structure. The correct specification of this loading structure is crucial for accurate calibration of item parameters and recovery of individual latent traits. This paper proposes a regularized Gaussian Variational Expectation Maximization (GVEM) algorithm to efficiently infer item factor loading structure directly from data. The main idea is to impose an adaptive L 1 -type penalty to the variational lower bound of the likelihood to shrink certain loadings to 0. This new algorithm takes advantage of the computational efficiency of GVEM algorithm and is suitable for high-dimensional MIRT applications. Simulation studies show that the proposed method accurately recovers the loading structure and is computationally efficient. The new method is also illustrated using the National Education Longitudinal Study of 1988 (NELS:88) mathematics and science assessment data., (© 2022. The Author(s) under exclusive licence to The Psychometric Society.)