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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Function: _error_handler
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Function: insertAPISummary
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Function: formatAIDetailSummary
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Organic solar cells (OSCs) can achieve greatly improved power conversion efficiency (PCE) by incorporating suitable additives in active layers. Their structure design often faces the challenge of operation generality for more binary blends. Herein, a simple dithieno[3,2-b:2',3'-d]pyrrole-rhodanine molecule (DR8) featuring high compatibility with polymer donor PM6 is developed as a cost-effective third component. By employing classic ITIC-like ITC6-4Cl and Y6 as model nonfullerene acceptors (NFAs) in PM6-based binary blends, DR8 added PM6:ITC6-4Cl blends exhibit significantly promoted energy transfer and exciton dissociation. The PM6:ITC6-4Cl:DR8 (1:1:0.1, weight ratio) OSCs contribute an exciting PCE of 14.94% in comparison to host binary devices (13.52%), while PM6:Y6:DR8 (1:1.2:0.1) blends enable 16.73% PCE with all simultaneously improved photovoltaic parameters. To the best of the knowledge, this performance is among the best for ternary OSCs with simple small molecular third components in the literature. More importantly, DR8-added ternary OSCs exhibit much improved device stability against thermal aging and light soaking over binary ones. This work provides new insight on the design of efficient third components for OSCs.
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http://dx.doi.org/10.1002/smll.202007746 | DOI Listing |
Microb Biotechnol
December 2024
Department of Microbiology, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia.
Commercial probiotics are often formulated as multi-strain cocktails, but the effects of social interactions, particularly between strains of a species, are often neglected, despite their potential to contribute to higher-order interactions where these interactions could affect those with a third party. In this study, we investigated the probiotic potential of a collection of Bacillus subtilis strains against Salmonella Typhimurium in single-strain and mixed cultures. The results indicate a promising probiotic potential of B.
View Article and Find Full Text PDFMajor depressive disorder (MDD) is one of the most common diseases affecting millions of people worldwide. The use of existing antidepressants in many cases does not allow achieving stable remission, probably due to insufficient understanding of pathological mechanisms. This indicates the need for the development of more effective drugs based on in-depth understanding of MDD's pathophysiology.
View Article and Find Full Text PDFJ Biochem Mol Toxicol
January 2025
Intensive Care Unit, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Sevoflurane (Sev) has a cardioprotective role in myocardial ischemia/reperfusion injury (MI/RI), but its mechanism has not been fully elucidated. This study aimed to investigate whether the circ_CDR1as/miR-671-5p/HMGA1 axis mediates the cardioprotective effect of Sev in MI/RI. Cardiomyocytes underwent hypoxia/reoxygenation (H/R) treatment was used to simulate MI/RI in vitro.
View Article and Find Full Text PDFBiochem Mol Biol Educ
December 2024
School of Basic Medical Sciences, Jiangsu Medical College, Yancheng, China.
To enhance the effectiveness of integrating online and offline teaching, 1545 clinical and preventive medicine students from 2019 to 2021 were randomly allocated to two groups, A and B. The curriculum was divided into two segments. Initially, two groups were established for the first segment, covering an introduction to Biomolecular and Material Metabolism.
View Article and Find Full Text PDFMediators Inflamm
December 2024
Department of Stomatology, School of Stomatology, The Third Affiliated Hospital, Xi'an Medical University, Xi'an, China.
This study aimed to investigate the molecular mechanisms of periodontitis and identify key immune-related biomarkers using machine learning and Mendelian randomization (MR). Differentially expressed gene (DEG) analysis was performed on periodontitis datasets GSE16134 and GSE10334 from the Gene Expression Omnibus (GEO) database, followed by weighted gene co-expression network analysis (WGCNA) to identify relevant gene modules. Various machine learning algorithms were utilized to construct predictive models, highlighting core genes, while MR assessed the causal relationships between these genes and periodontitis.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!