Breast cancer is the most common malignant cancer among women, both in Poland and worldwide. Due to the constantly increasing number of breast cancer cases, it is vital to develop effective activities in primary and secondary prevention. One of the promising methods of best value, connecting both types of cancer prevention, appears to be chemoprevention. Chemoprevention uses natural or synthetic compounds to inhibit, delay or reverse the process of carcinogenesis. Among ingredients of natural origin, great attention is paid to curcumin - a broad-spectrum anti-cancer polyphenol derivative, extracted from the rhizome of Curcuma longa L. Curcumin has a number of chemopreventive properties such as anti-inflammatory activity, induction of apoptosis, inhibition of angiogenesis as well as tumor metastasis. Numerous in vitro and in vivo studies have demonstrated the mentioned anti-cancer effect in the epithelial breast cell line MCF-10A and in the epithelial breast cell lines MCF-7, BT-474, SK-BR-3-hr and MDA-MB-231. The main problem associated with the use of curcumin as a chemopreventive agent in humans is its low absorption from the gastrointestinal tract, poor solubility in body fluids and low bioavailability. Current studies are underway to increase the bioavailability and effectiveness of curcumin in vivo. Good results in the prevention and the treatment of breast cancer could be ensured by curcumin nanoparticles coated with albumin, known as nanocurcumin. The studies using nanocurcumin, however, are still in the preclinical stage, which is why there is a need to conduct extensive long-term randomized clinical trials to determine its effectiveness.
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http://dx.doi.org/10.5604/17322693.1102294 | DOI Listing |
Pharm Dev Technol
January 2025
Department of Pharmacy, School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, China.
In this paper, the pH-sensitive targeting functional material NGR-poly(2-ethyl-2-oxazoline)-cholesteryl methyl carbonate (NGR-PEtOz-CHMC, NPC) modified quercetin (QUE) liposomes (NPC-QUE-L) was constructed. The structure of NPC was confirmed by infrared spectroscopy (IR) and nuclear magnetic resonance hydrogen spectrum (H-NMR). Pharmacokinetic results showed that the accumulation of QUE in plasma of the NPC-QUE-L group was 1.
View Article and Find Full Text PDFJ Med Econ
January 2025
UNESCO-TWAS, The World Academy of Sciences, Trieste, Italy.
Aim: Dynamic cancer control is a current health system priority, yet methods for achieving it are lacking. This study aims to review the application of system dynamics modeling (SDM) on cancer control and evaluate the research quality.
Methods: Articles were searched in PubMed, Web of Science, and Scopus from the inception of the study to November 15th, 2023.
Int J Surg
January 2025
Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China.
Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict classical biomarkers, immunotherapy-associated gene signatures, and prognosis-associated subtypes directly from hematoxylin and eosin stained histopathology images. BBMIL showed the best performance among comparative algorithms on the prediction of classical biomarkers, immunotherapy related gene signatures, and subtypes.
View Article and Find Full Text PDFInt J Gen Med
December 2024
Department of Thyroid and Breast Surgery, Quzhou People's Hospital, Quzhou, 324000, People's Republic of China.
Objective: This study aims to demonstrate the impact of sarcopenia on the prognosis of early breast cancer and its role in early multimodal intervention.
Methods: The clinical data of patients (n=285) subjected to chemotherapy for early-stage breast cancer diagnosed pathologically between January 1, 2016, and December 31, 2020, in our hospital were retrospectively analyzed. Accordingly, the recruited subjects were divided into sarcopenia (n=85) and non-sarcopenia (n=200) groups according to CT diagnosis correlating with single-factor and multifactorial logistic regression analyses.
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