Solid microneedles (MNs) represent a useful tool for enhancing skin permeability by creating microchannels that provide a drug delivery route. To achieve the solid polymer MNs to become a clinical reality and to be commercialised, it is much essential to understand the skin penetration process. In this work, the effect of polymer MN height and density, drug molecular weight, as well as drug diffusion time on the drug permeability distribution was systemically investigated . MN with a height of 800 µm was most conductive to enhance the vertical distribution of drug permeation into the skin, while 11 × 11 MN array was most beneficial to promote the horizontal distribution of drug permeation into the skin. In addition, the increasing of drug molecular weight could reduce the drug permeability distribution and Fluorescein isothiocyanate most likely to penetrate into the skin after MNs pre-treatment. With the increase of drug diffusion time, the drug distribution in the subcutaneous gradually weakened until the drug was absorbed by the subcutaneous tissue at 8 h. These results suggest that the solid polymer MNs can penetrate the stratum corneum of the skin for enhancing drug delivery, especially small molecule drugs.
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http://dx.doi.org/10.1080/1061186X.2020.1757101 | DOI Listing |
Cell Commun Signal
January 2025
Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA.
One hallmark of cancer is the upregulation and dependency on glucose metabolism to fuel macromolecule biosynthesis and rapid proliferation. Despite significant pre-clinical effort to exploit this pathway, additional mechanistic insights are necessary to prioritize the diversity of metabolic adaptations upon acute loss of glucose metabolism. Here, we investigated a potent small molecule inhibitor to Class I glucose transporters, KL-11743, using glycolytic leukemia cell lines and patient-based model systems.
View Article and Find Full Text PDFCell Commun Signal
January 2025
Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, 100191, China.
Background: Ovarian cancer (OC), particularly high-grade serous ovarian carcinoma (HGSOC), is the leading cause of mortality from gynecological malignancies worldwide. Despite the initial effectiveness of treatment, acquired resistance to poly(ADP-ribose) polymerase inhibitors (PARPis) represents a major challenge for the clinical management of HGSOC, highlighting the necessity for the development of novel therapeutic strategies. This study investigated the role of 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase 3 (PFKFB3), a pivotal regulator of glycolysis, in PARPi resistance and explored its potential as a therapeutic target to overcome PARPi resistance.
View Article and Find Full Text PDFVirol J
January 2025
Medi-X Pingshan, Southern University of Science and Technology, Shenzhen, Guangdong, 518118, China.
Background: SHEN26 (ATV014) is an oral RNA-dependent RNA polymerase (RdRp) inhibitor with potential anti-SARS-CoV-2 activity. Safety, tolerability, and pharmacokinetic characteristics were verified in a Phase I study. This phase II study aimed to verify the efficacy and safety of SHEN26 in COVID-19 patients.
View Article and Find Full Text PDFReprod Biol Endocrinol
January 2025
Department of Molecular and Developmental Medicine, Siena University, Siena, 53100, Italy.
Background: Endocrine-disrupting chemicals (EDCs) interfere with the endocrine system and negatively impact reproductive health. Biochanin A (BCA), an isoflavone with anti-inflammatory and estrogen-like properties, has been identified as one such EDC. This study investigates the effects of BCA on transcription, metabolism, and hormone regulation in primary human granulosa cells (GCs), with a specific focus on the activation of bitter taste receptors (TAS2Rs).
View Article and Find Full Text PDFBMC Bioinformatics
January 2025
School of Computer Science and Technology, University of Science and Technology of China, 443 Huangshan Road, Hefei, 230027, China.
Background: Drug-drug interactions (DDIs) especially antagonistic ones present significant risks to patient safety, underscoring the urgent need for reliable prediction methods. Recently, substructure-based DDI prediction has garnered much attention due to the dominant influence of functional groups and substructures on drug properties. However, existing approaches face challenges regarding the insufficient interpretability of identified substructures and the isolation of chemical substructures.
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