Asbestos Mesothelioma
Asbestos Mesothelioma - Related Videos
08:01
Generation and Expansion of Primary, Malignant Pleural Mesothelioma Tumor Lines
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2022
The goal of this method paper is to demonstrate a robust and reproducible methodology for the enrichment, generation, and expansion of primary tumor cell lines from surgically resected pleural mesothelioma.
11:11
Desthiobiotin-Streptavidin-Affinity Mediated Purification of RNA-Interacting Proteins in Mesothelioma Cells
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Cited by 6 •
2018
Desthiobiotin labeling of a synthetic 25-nucleotide RNA oligo, which contains an adenine-rich element (ARE) motif, allows specific binding of cytosolic ARE-binding protein.
09:31
Orthotopic Implantation and Peripheral Immune Cell Monitoring in the II-45 Syngeneic Rat Mesothelioma Model
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Cited by 2 •
2015
The generation of an orthotopic rat model of pleural malignant mesothelioma by implantation of II-45 mesothelioma cells into the pleural cavity of immune competent rats is presented. A flow cytometric method to analyze seven immune cell subsets in these animals from a 25 µl blood sample is also described.
07:54
Implantation and Monitoring by PET/CT of an Orthotopic Model of Human Pleural Mesothelioma in Athymic Mice
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2019
This article describes the generation of an orthotopic mouse model of human pleural mesothelioma by implantation of H2052/484 mesothelioma cells into the pleural cavity of immunocompromised athymic mice. The longitudinal monitoring of the development of intrapleural tumors was assessed by non-invasive multimodal [18F]-2-fluoro-2-deoxy-D-glucose positron emission tomography and computed tomography imaging.
08:07
Preparation of Herbal Medicine: Er-Xian Decoction and Er-Xian-containing Serum for In Vivo and In Vitro Experiments
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Cited by 6 •
2017
Here, we present the preparation of an er-xian decoction (EXD) in four steps—soaking, decoction, filtration, and concentration—and demonstrate the administration of a prepared EXD-containing serum to rats. These methods are applicable to the in vivo and in vitro study of herbal decoctions such as traditional Chinese medicines.
FAQs
Statistical analysis separates disease frequency into incidence, mortality, survival, and latency measures. Incidence tracks newly identified cases, while mortality describes deaths attributed to the disease. Survival summarizes outcomes after diagnosis, and latency captures the extended interval between exposure and disease development. Considering these measures together prevents one statistic from being mistaken for the full disease burden.
Exposure intensity and duration serve as key variables when researchers examine how asbestos contact relates to asbestos mesothelioma outcomes. Statistical comparisons can evaluate whether populations with different exposure patterns show different levels of disease occurrence, mortality, or survival. This approach helps clarify exposure-related trends while supporting estimates of risk among affected occupational groups.
A long latency period separates the original exposure from the later appearance of disease, so current case patterns may reflect exposures that occurred many years earlier. Statistical interpretation must therefore consider time between exposure and diagnosis rather than linking cases only to recent conditions. Accounting for latency improves population surveillance and helps researchers evaluate historical occupational exposure.
Researchers use occupational exposure information to identify populations that may have experienced asbestos contact and then compare their disease patterns with relevant statistical groups. Measures such as incidence, mortality, survival, and latency can reveal which populations are most affected. These comparisons help estimate disease burden and guide surveillance toward groups requiring closer public-health attention.
Prevention strategies can be evaluated by monitoring statistical patterns in disease occurrence, mortality, and exposure across affected populations. Changes in these measures may help researchers assess whether efforts to reduce asbestos exposure are associated with different disease burdens over time. The resulting evidence supports public-health surveillance and strengthens risk communication about exposure-related disease.
Statistics help describe how frequently asbestos mesothelioma occurs, how many deaths are associated with it, and how outcomes vary across populations. These findings support clinical planning by clarifying the scale of affected groups, while public-health agencies can use them to communicate risk, estimate disease burden, and prioritize surveillance or prevention efforts.