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1.
Molecules ; 29(9)2024 Apr 25.
Artigo em Inglês | MEDLINE | ID: mdl-38731449

RESUMO

Cannabis sativa L. (hemp) is a herbaceous plant rich in cannabinoids with a long history of use in pain treatment. The most well-characterized cannabinoids, cannabidiol (CBD) and Δ9-tetrahydrocannabinol (Δ9-THC), garnered much attention in chemotherapy-induced peripheral neuropathy (CIPN) treatment. However, few studies have investigated the biological benefits and mechanism of hemp extract on CIPN. In the present study, hemp extract (JG) rich in cannabinoids was extracted by supercritical fluid carbon dioxide extraction (SFCE). The antinociceptive efficacy was evaluated using a paclitaxel-induced peripheral neuropathy (PIPN) rat model based on behavioral tests. Further omics-based approaches were applied to explore the potential mechanisms. The results showed that JG decreased mechanical allodynia, thermal hyperalgesia, and inflammatory cytokines in PIPN rats significantly. Transcriptome analysis identified seven key genes significantly regulated by JG in PIPN model rats, mainly related to the neuroactive ligand-receptor interaction pathway, PPAR signaling pathway, and cAMP signaling pathway. In metabolomic analysis, a total of 39 significantly altered metabolites were identified, mainly correlated with pentose and glucuronate interconversions and the glycerophospholipid metabolism pathway. Gut microbiota analysis suggested that increased community Lachnoclostridium and Lachnospiraceae_UCG-006 in PIPN rats can be reversed significantly by JG. In conclusion, hemp extract exhibited antinociceptive effects on PIPN. The analgesic mechanism was probably related to the regulation of inflammation, neuroactive ligand-receptor interaction pathway, sphingolipid metabolism, etc. This study provides novel insights into the functional interactions of Cannabis sativa L. extract on PIPN.


Assuntos
Analgésicos , Cannabis , Neuralgia , Paclitaxel , Extratos Vegetais , Animais , Cannabis/química , Neuralgia/induzido quimicamente , Neuralgia/tratamento farmacológico , Neuralgia/metabolismo , Extratos Vegetais/farmacologia , Extratos Vegetais/química , Ratos , Analgésicos/farmacologia , Analgésicos/química , Paclitaxel/efeitos adversos , Masculino , Metabolômica , Modelos Animais de Doenças , Hiperalgesia/tratamento farmacológico , Hiperalgesia/induzido quimicamente , Hiperalgesia/metabolismo , Canabinoides/farmacologia , Multiômica
2.
Pharmaceutics ; 11(12)2019 Dec 07.
Artigo em Inglês | MEDLINE | ID: mdl-31817930

RESUMO

The purpose of this study is to use a material library to investigate the effect of raw material properties on ribbon tensile strength (TS) and solid fraction (SF) in the roll compaction (RC) process. A total of 81 pharmaceutical materials, including 53 excipients and 28 natural product powders (NPPs), were characterized by 22 material descriptors and were compacted under five different hydraulic pressures. The transversal and longitudinal splitting behaviors of the ribbons were summarized. The TS-porosity and TS-pressure relationships were used to explain the roll compaction behavior of powdered materials. Through defining the target ribbon quality (i.e., 0.6 ≤ SF ≤ 0.8 and TS ≥ 1 MPa), the roll compaction behavior classification system (RCBCS) was built and 81 materials were classified into three categories. A total of 24 excipients and five NPPs were classified as Category I materials, which fulfilled the target ribbon quality and had less occurrence of transversal splitting. Moreover, the multivariate relationships between raw material descriptors, the hydraulic pressure and ribbon quality attributes were obtained by PLS regression. Four density-related material descriptors and the cohesion index were identified as critical material attributes (CMAs). The multi-objective design space summarizing the feasible material properties and operational region for the RC process were visualized. The RCBCS presented in this paper enables a formulator to perform the initial risk assessment of any new materials, and the data modeling method helps to predict the impact of formulation ingredients on strength and porosity of compacts.

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