Simulation on directed graphs is an important method for understanding the dynamics in the systems where connectivity graphs contain cycles. Discrete Stochastic Heterogeneous Simulator (DiSH) is one of the simulation ...
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Liposomes, spherical phospholipid vesicles with a unique morphology mimicking that of body cells, have emerged as versatile nanoparticles for drug delivery. Their biocompatibility, low cytotoxicity, targeted delivery,...
Liposomes, spherical phospholipid vesicles with a unique morphology mimicking that of body cells, have emerged as versatile nanoparticles for drug delivery. Their biocompatibility, low cytotoxicity, targeted delivery, and hydrophobic and hydrophilic characteristics make them stand out over traditional drug delivery systems. Liposomes can be tailored in size, composition, lamellarity, and surface charge, offering a unique level of customization for various applications. Extensive research in liposome technology has led to the development of a wide range of liposomal formulations with enhanced functionalities, such as PEGylated liposomes, ligand-targeted liposomes, and stimuli-responsive liposomes. Beyond their crucial role in cancer treatment, liposomes play a significant role in influenza, COVID-19, cancer, and hepatitis A vaccines. They are also utilized in pain management, fungal treatment, brain targeting, and topical and ocular drug delivery. This review offers insight into the types of liposomes, their composition, preparation methods, characterization methods, and clinical applications. Additionally, it discusses challenges and highlights potential future directions in liposome-based drug delivery.
Diverse microbes utilize redox shuttles to exchange electrons with their environment through mediated extracellular electron transfer (EET), supporting anaerobic survival. Although mediated EET has been leveraged for ...
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The intricate relationship between emotional and behavioral traits and brain anatomy and function during childhood and adolescence is crucial for elucidating the neurobiological basis of diverse psychopathological dis...
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Simulation on directed graphs is an important method for understanding the dynamics in the systems where connectivity graphs contain cycles. Discrete Stochastic Heterogeneous Simulator (DiSH) is one of the simulation ...
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ISBN:
(纸本)9781665433129
Simulation on directed graphs is an important method for understanding the dynamics in the systems where connectivity graphs contain cycles. Discrete Stochastic Heterogeneous Simulator (DiSH) is one of the simulation tools with wide application, which uses regulator values to calculate state updates of regulated elements. Here we present a new simulation approach DiSH-trend which also takes into account the trends in regulating elements. We demonstrate the features of trend-based regulation, as well as hybrid regulation, which is a combination of the trend- and level-based approaches. The modeling capabilities are demonstrated on a small toy model, showcasing different functionalities. Real-world capabilities are demonstrated on a larger network model of food insecurity in the Ethiopian region Oromia. Adding trend-based regulation to models results in increased modeling flexibility, and hybrid regulation improves qualitative dynamic behavior prediction. With appropriate data, DiSH-trend becomes a powerful tool for exploring intervention strategies.
Chemically modified small interfering RNAs (siRNAs) are a promising drug class that silences disease-causing genes via mRNA degradation. Both siRNA-specific features (e.g. sequence, modification pattern, and structure...
Chemically modified small interfering RNAs (siRNAs) are a promising drug class that silences disease-causing genes via mRNA degradation. Both siRNA-specific features (e.g. sequence, modification pattern, and structure) and target mRNA-specific factors contribute to observed efficacy. Systematically defining the relative contributions of siRNA sequence, structure, and modification pattern versus the native context of the target mRNA is necessary to inform design considerations and facilitate the widespread application of this therapeutic platform. To address this, we synthesized a panel of ∼1260 differentially modified siRNAs and evaluated their silencing efficiency against therapeutically relevant mRNAs (APP,BACE1,MAPT, andSNCA) using both reporter-based and native expression assays. Our results demonstrate that the siRNA modification pattern (e.g. level of 2′-O-methyl content) significantly impacts efficacy, while structural features (e.g. symmetric versus asymmetric configurations) do not. Furthermore, we observed substantial differences in the number of effective siRNAs identified per target. These target-specific differences in hit rates are largely mitigated when efficacy is tested in the context of a reporter assay, confirming that native mRNA-specific features influence siRNA performance. Key target-specific factors, including exon usage, polyadenylation site selection, and ribosomal occupancy, partially explained efficacy variability. These insights led to a proposed framework of parameters for optimizing therapeutic siRNA design.
Simulation on directed graphs is an important method for understanding the dynamics in the systems where connectivity graphs contain cycles. Discrete Stochastic Heterogeneous Simulator (DiSH) is one of the simulation ...
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The intricate relationship between emotional and behavioral traits and brain anatomy and function during childhood and adolescence is crucial for elucidating the neurobiological basis of diverse psychopathological dis...
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ISBN:
(数字)9798350378009
ISBN:
(纸本)9798350378016
The intricate relationship between emotional and behavioral traits and brain anatomy and function during childhood and adolescence is crucial for elucidating the neurobiological basis of diverse psychopathological disorders but it still largely unknown. In this study, we aimed to quantitatively evaluate the multivariate patterns of association between brain activity, cortical brain characteristics, and core clinical and behavioral features in a sample of forty subjects with age ranging between 11–21 years who were referred for emotional-behavioral problems. By exploiting a multi-block partial least square discriminant analysis (MBPLS-DA) framework, we attempt to explain the multivariate relations among the Child Behavior Checklist (CBCL) and brain structure and function assessed via magnetic resonance imaging (MRI). Based on individual importance of each block, our findings showed a prominent contribution of regional cortical thickness data in explaining the variance of CBCL scales. By analyzing each block's loadings individually, a prominent positive association was found among regional cortical thickness in paracentral, lateral occipital cortex, precuneus and CBCL composite scores of psychotic, autism spectrum disorder risk profiles and withdrawn scale. Furthermore, the same CBCL scores were also found positively associated with functional connections involving regions of anterior and median cingulate cortex, caudate nucleus, inferior parietal lobule and angular gyrus. Our investigation suggests a key role of brain structure and function in shaping behavioral traits that might be predispose to psychopathology during childhood and adolescence. The proposed MBPLS-DA application promotes broader adoption of this technique across diverse and multimodal MRI and clinical datasets.
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