Recent Dimensionality Reduction Techniques for High-Dimensional COVID-19 Data

We are going through the last years of the COVID-19 pandemic, where almost the entire research community has focused on the challenges that constantly arise. From the computational and mathematical perspective, we have to deal with a dataset with ultra-high volume and ultra-high dimensionality in several experimental studies. An indicative example is DNA sequencing technologies, which offer a more realistic picture of human diseases at the molecular biology level. However, these technologies produce data with high complexity and ultra-high dimensionality. On the other hand, dimensionality reduction techniques are the first choice to address this complexity, revealing the hidden data structure in the original multidimensional space. Also, such techniques can improve the efficiency of machine learning tasks such as classification and clustering. Towards this direction, we study the behavior of seven well-known and cutting-edge dimensionality reduction techniques tailored for RNA-sequencing data. Along with the study of the effect of these algorithms, we propose the extension of the Random projection and Geodesic distance t-Stochastic Neighbor Embedding (RGt-SNE) algorithm, a recent t-Stochastic Neighbor Embedding (t-SNE) improvement. We suggest a new distance criterion for the kernel matrix construction. Our results show the potential of the proposed algorithm and, at the same time, highlight the complexity of the COVID-19 data, which are not separable, creating a significant challenge that the Machine Learning field will have to face. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG

Implementation of one-turn maps in SSCTRK using ZLIB

The particle tracking code SSCTRK is currently being adapted to operational simulation and beam-beam effect studies for the Collider rings of the SSC. During beam-beam effect studies, the lattice content of the bending arcs is normally not varied, making fast truncated Taylor map tracking through the arcs an attractive option. The implementation of SSCTRK as a truncated Taylor map tracking program has been carried out using the differential algebra library ZLIB, which simplified the task to that of straightforward translation of SSCTRK kick and drift arithmetic operations to calls to the corresponding polynomial operation subroutines of ZLIB. The accuracy and speed (relative to normal SSCTRK tracking) of truncated Taylor map tracking at 2mm betatron oscillation amplitude was studied in various orders of the map. The seventh order map was found to be in agreement with the normal SSCTRK to about eight significant figures on the first turn, and to a fraction of 1% on the 100,000th turn, for a typical 5cm magnet aperture lattice, and could be made to track at ten times the speed of the normal SSCTRK kick-drift tracking on a scalar architecture (Sun) workstation. (The map tracking subroutines of ZLIB are optimized for vector and parallel architecture supercomputers, and typically achieve even faster relative performance on these, but operational simulation studies will be more conveniently carried out on dedicated workstations which have the incoming generation of superscalar'' CPUs)

Induced pluripotent stem cell-related genes influence biological behavior and 5-fluorouracil sensitivity of colorectal cancer cells*

Objective: We aimed to perform a preliminary study of the association between induced pluripotent stem cell (iPS)-related genes and biological behavior of human colorectal cancer (CRC) cells, and the potential for developing anti-cancer drugs targeting these genes. Methods: We used real-time reverse transcriptase polymerase chain reaction (RT-PCR) to evaluate the transcript levels of iPS-related genes NANOG, OCT4, SOX2, C-MYC and KLF4 in CRC cell lines and cancer stem cells (CSCs)-enriched tumor spheres. NANOG was knockdowned in CRC cell line SW620 by lentiviral transduction. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays, plate colony formation, and a mouse xenograft model were used to evaluate alterations in biological behavior in NANOG-knockdown SW620 cells. Also, mock-knockdown and NANOG-knockdown cells were treated with 5-fluorouracil (5-FU) and survival rate was measured by MTT assay to evaluate drug sensitivity. Results: A significant difference in the transcript levels of iPS-related genes between tumor spheres and their parental bulky cells was observed. NANOG knockdown suppressed proliferation, colony formation, and in vivo tumorigenicity but increased the sensitivity to 5-FU of SW620 cells. 5-FU treatment greatly inhibited the expression of the major stemness-associated genes NANOG, OCT4, and SOX2. Conclusions: These results collectively suggest an overlap between iPS-related genes and CSCs in CRC. Quenching a certain gene NANOG may truncate the aggressiveness of CRC cells