The Granger Causal Effects of Canady Helios Cold Plasma on the Inhibition of Breast Cancer Cell Proliferation

Cold atmospheric plasma (CAP) has become a promising tool for modern medicine. With its recent applications in oncology, regenerative medicine, and immunotherapy, CAP can be used for a myriad of different clinical treatments. When using CAP specifically for the treatment of tumors, it is known to elicit an oxidative response within malignant cancer cells, inducing cell cycle arrest and apoptosis. In this study, data of intracellular reactive oxygen species (ROS), caspase activity, Ki-67 expression, and cell cycle activity in the G1 phase were acquired to determine the causal relationships these intermediates have with cell proliferation and death after Canady Helios Cold Plasma (CHCP) treatment. The data were derived from four different subtypes of breast cancer cell lines: BT-474, MCF-7, MDA-MB-231, and SK-BR-3. Data transformation techniques were conducted on the time-series data for the input into the causal model code. The models were created on the basis of Granger causality principles. Our results demonstrated that there was a Granger causal relationship among all potentially causal variables (ROS, caspase, Ki-67, and G1 activity) and cell proliferation after 5 min CHCP treatment; however, not all variables were causal for the 3 min models. This same pattern did not exist for cell death models, which tested all potentially causal variables (ROS, Ki-67, and G1 activity) vs. caspase activity. All models were validated through a variety of statistical tests and forecasting accuracy metrics. A pseudo data set with defined causal links was also created to test R’s ability in picking up known causal relationships. These models, while nonexhaustive, elucidated the effects cold plasma has on cell activity regulators. Research in causal modeling is needed to help verify the exact mechanism of cold plasma for the ultimate optimization of its application in the treatment of cancers

The Granger Causal Effects of Canady Helios Cold Plasma on the Inhibition of Breast Cancer Cell Proliferation

Cold atmospheric plasma (CAP) has become a promising tool for modern medicine. With its recent applications in oncology, regenerative medicine, and immunotherapy, CAP can be used for a myriad of different clinical treatments. When using CAP specifically for the treatment of tumors, it is known to elicit an oxidative response within malignant cancer cells, inducing cell cycle arrest and apoptosis. In this study, data of intracellular reactive oxygen species (ROS), caspase activity, Ki-67 expression, and cell cycle activity in the G1 phase were acquired to determine the causal relationships these intermediates have with cell proliferation and death after Canady Helios Cold Plasma (CHCP) treatment. The data were derived from four different subtypes of breast cancer cell lines: BT-474, MCF-7, MDA-MB-231, and SK-BR-3. Data transformation techniques were conducted on the time-series data for the input into the causal model code. The models were created on the basis of Granger causality principles. Our results demonstrated that there was a Granger causal relationship among all potentially causal variables (ROS, caspase, Ki-67, and G1 activity) and cell proliferation after 5 min CHCP treatment; however, not all variables were causal for the 3 min models. This same pattern did not exist for cell death models, which tested all potentially causal variables (ROS, Ki-67, and G1 activity) vs. caspase activity. All models were validated through a variety of statistical tests and forecasting accuracy metrics. A pseudo data set with defined causal links was also created to test R’s ability in picking up known causal relationships. These models, while nonexhaustive, elucidated the effects cold plasma has on cell activity regulators. Research in causal modeling is needed to help verify the exact mechanism of cold plasma for the ultimate optimization of its application in the treatment of cancers

Homozygosity mapping with SNP arrays identifies TRIM32, an E3 ubiquitin ligase, as a Bardet–Biedl syndrome gene (BBS11)

The identification of mutations in genes that cause human diseases has largely been accomplished through the use of positional cloning, which relies on linkage mapping. In studies of rare diseases, the resolution of linkage mapping is limited by the number of available meioses and informative marker density. One recent advance is the development of high-density SNP microarrays for genotyping. The SNP arrays overcome low marker informativity by using a large number of markers to achieve greater coverage at finer resolution. We used SNP microarray genotyping for homozygosity mapping in a small consanguineous Israeli Bedouin family with autosomal recessive Bardet–Biedl syndrome (BBS; obesity, pigmentary retinopathy, polydactyly, hypogonadism, renal and cardiac abnormalities, and cognitive impairment) in which previous linkage studies using short tandem repeat polymorphisms failed to identify a disease locus. SNP genotyping revealed a homozygous candidate region. Mutation analysis in the region of homozygosity identified a conserved homozygous missense mutation in the TRIM32 gene, a gene coding for an E3 ubiquitin ligase. Functional analysis of this gene in zebrafish and expression correlation analyses among other BBS genes in an expression quantitative trait loci data set demonstrate that TRIM32 is a BBS gene. This study shows the value of high-density SNP genotyping for homozygosity mapping and the use of expression correlation data for evaluation of candidate genes and identifies the proteasome degradation pathway as a pathway involved in BBS