237 research outputs found
Histopathologic and immunohistochemical investigations of dental abscess formed in maxillofacial area
Background: An abscess is a pocket of pus that forms around the root of an infected tooth. In this study, we aimed to investigate the extracellular matrix proteases ADAMTS1, ADAMTS4, osteonectin, and osteopontin expressions in abscess fluid cells in jaws after implantation and prosthesis operation. Materials and methods: In this clinical study, abscess fluids belonging to 17 patients who applied to the Department of Oral and Maxillofacial Surgery were examined histopathologically and immunohistochemically. In the histopathological examination of the abscess fluid, separation of chromatin bridges in the nuclei of neutrophil cells, pyknosis and apoptotic changes in the nucleus, degenerative change in the cytoplasm, and occasional vacuolar structures were observed. Results: The positive reaction of ADAMTS1 was observed in fibroblast cells, plasma cells, and macrophage cells. The positive reaction of ADAMTS4 was observed in fibroblast cells, osteoclast cells, and some apoptotic leukocyte cells. Osteopontin expression in osteoclastic cells and polymorphonuclear cells was defined as positive. Osteonectin expression was positive in polymorphonuclear leukocytes and hypertrophic fibroblast cells. Conclusions: ADAMTS1 and ADAMTS4 may induce bone destruction with its distinctive property in alveolar bone resorption, which promotes the activation of osteoclasts, which can accelerate the destruction of the extracellular matrix in the acute phase. Furthermore, osteoclastic activity increased with the increase of osteonectin and osteopontin protein expression due to inflammation in the abscess cases
Cytotoxic activities of certain medicinal plants on different cancer cell lines
Objectives: In recent years, the use of plants for the prevention and treatment of cancer is gaining more attention due to their diverse range of phytochemical constituents and fewer adverse effects. In this study, four medicinal plant species from the Kars province of Turkey were investigated for their cytotoxic potential against six different cancer cell lines and one normal cell line. Materials and Methods: MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-dipenyltetrazolium bromide] assay was performed to assess cytotoxic activity and apoptotic effect was determined using flow cytometry and caspase-3 analyses. Results: Significant cytotoxicity (≥70%) was observed with the leaf extract of Artemisia absinthium on A-549, CCC-221, K-562, MCF-7, PC-3 cells, whereas seed extracts caused significant cytotoxicity (≥70%) on CCC-221, K-562, MCF-7, PC-3 cells. Selective cytotoxicity was obtained with leaf extract on A-549 and K-562 cells; and with seed extract on K-562, MCF-7 and PC-3 cells compared with normal Beas-2B cells. The levels of cytotoxicity for both extracts were time- and dose-dependent at lower concentrations. Moreover, selective cytotoxicity (78%) was detected on A-549 cells with the seed extract of Plantago major. Cytotoxicity of extracts from Hyoscyamus niger and Amaranthus retrosa ranged between 10% and 30%. Conclusion: A. absinthium extracts and P. major seed extract have potential for development as therapeutic agents for cytotoxicity on certain cancer cells following further investigation. © Turk J Pharm Sci, Published by Galenos Publishing House
Multi-Channel Auto-Calibration for the Atmospheric Imaging Assembly using Machine Learning
Solar activity plays a quintessential role in influencing the interplanetary
medium and space-weather around the Earth. Remote sensing instruments onboard
heliophysics space missions provide a pool of information about the Sun's
activity via the measurement of its magnetic field and the emission of light
from the multi-layered, multi-thermal, and dynamic solar atmosphere. Extreme UV
(EUV) wavelength observations from space help in understanding the subtleties
of the outer layers of the Sun, namely the chromosphere and the corona.
Unfortunately, such instruments, like the Atmospheric Imaging Assembly (AIA)
onboard NASA's Solar Dynamics Observatory (SDO), suffer from time-dependent
degradation, reducing their sensitivity. Current state-of-the-art calibration
techniques rely on periodic sounding rockets, which can be infrequent and
rather unfeasible for deep-space missions. We present an alternative
calibration approach based on convolutional neural networks (CNNs). We use
SDO-AIA data for our analysis. Our results show that CNN-based models could
comprehensively reproduce the sounding rocket experiments' outcomes within a
reasonable degree of accuracy, indicating that it performs equally well
compared with the current techniques. Furthermore, a comparison with a standard
"astronomer's technique" baseline model reveals that the CNN approach
significantly outperforms this baseline. Our approach establishes the framework
for a novel technique to calibrate EUV instruments and advance our
understanding of the cross-channel relation between different EUV channels.Comment: 12 pages, 7 figures, 8 tables. This is a pre-print of an article
submitted and accepted by A&A Journa
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