The central route of streptozotocin (STZ) administration has been introduced as a rat model of sporadic Alzheimer's disease (AD). Curcumin was suggested to possess possible neuroprotective effects, which may be profitable in AD. However, the low bioavailability of curcumin hinders its beneficial effects in clinical studies. Earlier studies suggested that a bovine serum albumin-based nanocurcumin, produces superior neuroprotective effects compared to natural curcumin. In the present study, the protective effect of nanocurcumin in rat model of central STZ induced memory impairment was assessed. In addition, due to the importance of the hippocampus in memory, the amounts of hippocampal active caspase-3, Akt, and CaMKII-α were evaluated. Adult male Wistar rats weighing 250-300 g were used. STZ (icv) was injected during days 1 and 3 (3 mg/kg in divided), and nanocurcumin or curcumin 50 mg/kg/oral gavage was administered daily during days 4-14. Morris water maze training was performed on days 15-17, and the retention memory test was achieved on the 18th day. Following memory assessment, the rats were sacrificed and the hippocampi were used to assess caspase-3 cleavage, Akt, and CaMKII-α signaling. The findings revealed that nanocurcumin ingestion (but not natural curcumin) in the dose of 50 mg/kg was capable to prevent the impairment of water maze learning and memory induced by central STZ. Molecular assessments indicated that STZ treatment increased the caspase-3 cleavage in the hippocampus while deactivating Akt and CaMKII-α. Nanocurcumin reduced caspase-3 cleavage to a non-significant level compared to control group and restored Akt and CaMKII-α within the hippocampus while natural curcumin exerted no significant effect. These findings might suggest that nanocurcumin can restore memory deficit, hippocampal apoptosis as well as Akt and CaMKII-α signaling disruption associated with brain insulin resistance.
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http://dx.doi.org/10.1016/j.bbr.2024.115129 | DOI Listing |
Ecotoxicol Environ Saf
January 2025
College of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China. Electronic address:
This study aimed to investigate the potential protective properties of a traditional Chinese medicine (TCM) herbal product, Siraitia grosvenorii granules (SGG) against PM2.5-induced lung injury, as well as their active constituents and underlying mechanisms. The chemical composition of SGG, such as wogonin (MOL000173), luteolin (MOL000006), nobiletin (MOL005828), naringenin (MOL004328), acacetin (MOL001689), were identified via ultra-high-performance liquid chromatography-Q Exactive (UHPLC-QE) Orbitrap/MS.
View Article and Find Full Text PDFPLoS One
January 2025
Intensive Care Unit, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, PR China.
Background: Shenfu injection (SFI), derived from a traditional Chinese medicine (TCM) prescription, is an effective drug for the treatment of sepsis-induced myocardial injury (SIMI) with good efficacy, but its exact therapeutic mechanism remains unclear.
Methods: SwissTargetPrediction and GeneCards database were used to obtain relevant targets for SFI and SIMI. STRING 11.
J Cell Mol Med
January 2025
Department of Gastroenterology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, China.
Trophoblast glycoprotein (TPBG) plays a significant part in the growth of specific cancers, yet its connection to gastric cancer (GC) remains uncertain. This research seeks to analyse the fluctuation in TPBG levels in GC and evaluate how TPBG expression relates to the prognosis of GC patients. TPBG expression in GC and normal gastric tissues was investigated in The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) database, further extracting the immunohistochemistry images from HPA database and validating by Western blot.
View Article and Find Full Text PDFJ Cell Mol Med
January 2025
Cancer Biology Research Center, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran.
This study identifies microRNAs (miRNAs) with significant discriminatory power in distinguishing melanoma from nevus, notably hsa-miR-26a and hsa-miR-211, which have exhibited diagnostic potential with accuracy of 81% and 78% respectively. To enhance diagnostic accuracy, we integrated miRNAs into various machine-learning (ML) models. Incorporating miRNAs with AUC scores above 0.
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