Korsgaardhenderson7202

The degree of ankle swelling, serum levels of interleukin (IL)-1, and IL-6-related inflammatory factors levels all decreased in the gouty arthritis model established via monosodium urate (MSU) crystals. Taken together, the AE-M demonstrated the potential to improve the bioavailability, anti-hyperuricemic activity, and anti-inflammation of AE.Hypertension is a common disease for human with high morbidity and mortality, and olmesartan medoxomil (OM) is widely used in the therapy of hypertension. However, poor water solubility and low bioavailability limit its widespread use. To improve the effect of OM, a ternary OM solid dispersion consisting of hydroxypropyl-β-cyclodextrin (HP-β-CD) and hydroxypropyl methylcellulose (HPMC) was prepared by mechanochemical method. The best preparation parameters were OM/HP-β-CD/HPMC-E5 with mass ratio of 12.61 and milling time of 4 h. Under the optimal preparation conditions, the solubility of the ternary solid dispersion could be increased by 12 times as compared with pure OM. Due to the addition of HPMC-E5, the solid dispersion had sustained release performance with prolonged release time of 12 h. Furthermore, in vivo study demonstrated that the prepared solid dispersion could afford significantly improved bioavailability of ~ 3-fold in comparison with pure drug. Hence, the prepared ternary solid dispersion of OM may be a promise delivery system for clinical application.Triptolide (TPL) has been employed to treat hepatocellular carcinoma (HCC). However, the poor water solubility of TPL restricts its applications. Therefore, we prepared TPL-loaded cyclodextrin-based metal-organic framework (TPL@CD-MOF) to improve the solubility and bioavailability of TPL, thus enhancing the anti-tumor effect on HCC. The BET surface and the pore size of TPL@CD-MOF were 10.4 m2·g-1 and 1.1 nm, respectively. The results of XRD indicated that TPL in TPL@CD-MOF was encapsuled. TPL@CD-MOF showed a slower release than free TPL in vitro. Moreover, the CD-MOF improved the bioavailability of TPL. TPL@CD-MOF showed slightly higher, but statistically significant, anti-tumor efficacy in vitro and in vivo compared to free TPL. In addition, TPL@CD-MOF exhibited a modest improvement of the anti-tumor effects, which may be associated to the enhanced in vivo absorption. Overall, these findings suggested the potential CD-MOF as oral drug delivery carriers for anti-tumor drugs. The process of TPL loading into CD-MOF and its enhanced oral bioavailability and anti-tumor activity.Inflammation is the biological response of immune system to protect living organisms from injurious factors. However, excessive and uncontrolled inflammation is implicated in a variety of devastating chronic diseases including atherosclerosis, inflammatory bowel disease (IBD), and rheumatoid arthritis (RA). Improved understanding of inflammatory response has unveiled a rich assortment of anti-inflammatory therapeutics for the treatment and management of relevant chronic diseases. Notwithstanding these successes, clinical outcomes are variable among patients and serious adverse effects are often observed. Moreover, there exist some limitations for clinical anti-inflammatory therapeutics such as aqueous insolubility, low bioavailability, off-target effects, and poor accessibility to subcellular compartments. To address these challenges, the rational design of inflammation-specific drug delivery systems (DDSs) holds significant promise. Moreover, as compared to normal tissues, inflamed tissue-associated pathological milieu (e.g., oxidative stress, acidic pH, and overexpressed enzymes) provides vital biochemical stimuli for triggered delivery of anti-inflammatory agents in a spatiotemporally controlled manner. In this review, we summarize recent advances in the development of anti-inflammatory DDSs with built-in pathological inflammation-specific responsiveness for the treatment of chronic inflammatory diseases.Strategies targeting nucleolin have enabled a significant improvement in intracellular bioavailability of their encapsulated payloads. In this respect, assessment of the impact of target cell heterogeneity and nucleolin homology across species (structurally and functionally) is of major importance. This work also aimed at mathematically modelling the nucleolin expression levels at the cell membrane, binding and internalization of pH-sensitive pegylated liposomes encapsulating doxorubicin and functionalized with the nucleolin-binding F3 peptide (PEGASEMP), and resulting cytotoxicity against cancer cells from mouse, rat, canine, and human origin. GSK2830371 clinical trial Herein, it was shown that nucleolin expression levels were not a limitation on the continuous internalization of F3 peptide-targeted liposomes, despite the saturable nature of the binding mechanism. Modeling enabled the prediction of nucleolin-mediated total doxorubicin exposure provided by the experimental settings of the assessment of PEGASEMP's impact on cell death. The former increased proportionally with nucleolin-binding sites, a measure relevant for patient stratification. This pattern of variation was observed for the resulting cell death in nonsaturating conditions, depending on the cancer cell sensitivity to doxorubicin. This approach differs from standard determination of cytotoxic concentrations, which normally report values of incubation doses rather than the actual intracellular bioactive drug exposure. Importantly, in the context of development of nucleolin-based targeted drug delivery, the structural nucleolin homology (higher than 84%) and functional similarity across species presented herein, emphasized the potential to use toxicological data and other metrics from lower species to infer the dose for a first-in-human trial.In this work, we propose a heterogeneous committee (ensemble) of diverse members (classification approaches) to solve the problem of human epithelial (HEp-2) cell image classification using indirect Immunofluorescence (IIF) imaging. We hypothesize that an ensemble involving different feature representations can enable higher performance if individual members in the ensemble are sufficiently varied. These members are of two types (1) CNN-based members, (2) traditional members. For the CNN members, we have employed the well-established ResNet, DenseNet, and Inception models, which have distinctive salient aspects. For the traditional members, we incorporate class-specific features which are characterized depending on visual morphological attributes, and some standard texture features. To select the members which are discriminating and not redundant, we use an information theoretic measure which considers the trade-off between individual accuracies and diversity among the members. For all selected members, a compelling fusion required to combine their outputs to reach a final decision.