rizky nurdiansyah
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Background
The exploration of bryophytes biodiversity in Indonesia due to its abundance and the bioactivity of its phytochemical content, such as alkaloids and polyphenols, has received increased interest. Despite some species proven to possess pharmacological properties, the antiproliferative study of Indonesian native moss, such as the Pogonatum genus, is limited. Hence, this study aims to evaluate the anticancer effects of Pogonatum neesii Dozy antiproliferative activity on colon and cervical cancer through in silico and in vitro methods.
MethodsMolecular docking analysis using Autodock VINA in PyRx softwre was conducted between natural compounds found on P. neesii and several target proteins, DNA (cytosine-5)- methyltransferase 1 (DMT-1) (Protein Data Bank (PDB) id: 4WXX) in colon cancer and B-cell lymphoma 2 (Bcl-2) (PDB id: 4LXD) in cervical cancer. Afterwards, total phenolic and alkaloid contents were measured. Subsequently, P. neesii was tested on HaCaT (keratinocytes), HEK293 (human embryonic kidney), HT-29 (colorectal cancer models) and HeLa (cervical cancer model) to observe its cytotoxicity.
ResultsOut of eight compounds, chlorogenate was found to exert the best binding energy with target proteins, although it had lower binding affinity than the protein’s natural ligand. However, the biological, drug-likeness, and toxicity analysis suggested the drug potency of the compound, thus we did the in vitro analysis. P. neesii showed significant cytotoxic effects on HT-29 and HeLa cells, while it did not exert any cytotoxic effects on HaCaT and HEK-293 cells, at the same concentrations.
ConclusionP. neesii has been shown to have the potential as an anticancer agent through in silico and in vitro analysis, where the extract showed selective cytotoxicity towards cancer cell lines and cytocompatibility towards normal cell lines. Chlorogenate was pinpointed as the compound with the most activity and interaction with the target proteins in both cancers.
Keywords: Cancer, Cell culture, Cell lines, Docking, In silico, Molecular targeting -
Introduction
Dementia is a common medical condition of older people which is marked by the decline of multiple cognitive abilities, such as memory and communication. Currently, there is no effective treatment for curing dementia, making prevention the most priority to this disease. Previous studies showed that cognitive ability training, such as mathematical problem solving, has a potential to slow down cognitive decline. The aim of this project is to create a simple yet interactive mathematical quiz as a way to train one’ cognitive ability and reduce the risk of getting dementia.
Material and MethodsThe quiz was created by using tkinter module and its built-in functions in Python programming language.
ResultsThe result showed that the quiz was simple but involved an active role of the user to input the answer. It also did not have certain time limit, preventing the user to feel rushed or burdened in doing the quiz. In addition, three different types of difficulty were provided to give a challenging atmosphere to the game.
ConclusionAs a conclusion, this quiz provides a simple way for people to regularly train their cognitive skill, so the risk of getting dementia, especially in elderly stage, can be reduced.
Keywords: Dementia, Prevention, Python, Tkinter
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