Distributed transformer for high order epistasis detection in large-scale datasets.

Understanding the genetic basis of complex diseases is one of the most important challenges in current precision medicine. To this end, Genome-Wide Association Studies aim to correlate Single Nucleotide Polymorphisms (SNPs) to the presence or absence of certain traits. However, these studies do not consider interactions between several SNPs, known as epistasis, which explain most genetic diseases. Analyzing SNP combinations to detect epistasis is a major computational task, due to the enormous search space. A possible solution is to employ deep learning strategies for genomic prediction, but the lack of explainability derived from the black-box nature of neural networks is a challenge yet to be addressed. Herein, a novel, flexible, portable, and scalable framework for network interpretation based on transformers is proposed to tackle any-order epistasis. The results on various epistasis scenarios show that the proposed framework outperforms state-of-the-art methods for explainability, while being scalable to large datasets and portable to various deep learning accelerators. The proposed framework is validated on three WTCCC datasets, identifying SNPs related to genes known in the literature that have direct relationships with the studied diseases.

Comparative assessment of electronic nicotine delivery systems aerosol and cigarette smoke on endothelial cell migration: The Replica Project.

Cigarette smoking is associated with impairment of repair mechanisms necessary for vascular endothelium homeostasis. Reducing the exposure to smoke toxicants may result in the mitigation of the harmful effect on the endothelium and cardiovascular disease development. Previous investigations evaluated in vitro the effect of electronic cigarette (EC) compared with cigarette smoke demonstrating a significant reduction in human umbilical vein endothelial cells (HUVECs) migration inhibition following EC aerosol exposure. In the present study, we replicated one of these studies, evaluating the effects of cigarette smoke on endothelial cell migration compared with aerosol from EC and heated tobacco products (HTPs). We performed an in vitro scratch wound assay on endothelial cells with a multi-center approach (ring-study) to verify the robustness and reliability of the results obtained in the replicated study, also testing the effect of aerosol from two HTPs on endothelial cells. Consistently with the original study, we observed a substantial reduction of the effects of aerosol from EC and HTPs on endothelial cell migration compared with cigarette smoke. While cigarette smoke reduced endothelial wound healing ability already at low concentrations (12.5%) and in a concentration-dependent manner, EC and HTPs aerosol showed no effect on endothelial cells until 80%-100% concentrations. In conclusion, our study further confirms the importance of EC and tobacco heated products as a possible harm reduction strategy for cardiovascular diseases development in smokers.

PhyloMissForest: a random forest framework to construct phylogenetic trees with missing data.

BACKGROUND: In the pursuit of a better understanding of biodiversity, evolutionary biologists rely on the study of phylogenetic relationships to illustrate the course of evolution. The relationships among natural organisms, depicted in the shape of phylogenetic trees, not only help to understand evolutionary history but also have a wide range of additional applications in science. One of the most challenging problems that arise when building phylogenetic trees is the presence of missing biological data. More specifically, the possibility of inferring wrong phylogenetic trees increases proportionally to the amount of missing values in the input data. Although there are methods proposed to deal with this issue, their applicability and accuracy is often restricted by different constraints. RESULTS: We propose a framework, called PhyloMissForest, to impute missing entries in phylogenetic distance matrices and infer accurate evolutionary relationships. PhyloMissForest is built upon a random forest structure that infers the missing entries of the input data, based on the known parts of it. PhyloMissForest contributes with a robust and configurable framework that incorporates multiple search strategies and machine learning, complemented by phylogenetic techniques, to provide a more accurate inference of lost phylogenetic distances. We evaluate our framework by examining three real-world datasets, two DNA-based sequence alignments and one containing amino acid data, and two additional instances with simulated DNA data. Moreover, we follow a design of experiments methodology to define the hyperparameter values of our algorithm, which is a concise method, preferable in comparison to the well-known exhaustive parameters search. By varying the percentages of missing data from 5% to 60%, we generally outperform the state-of-the-art alternative imputation techniques in the tests conducted on real DNA data. In addition, significant improvements in execution time are observed for the amino acid instance. The results observed on simulated data also denote the attainment of improved imputations when dealing with large percentages of missing data. CONCLUSIONS: By merging multiple search strategies, machine learning, and phylogenetic techniques, PhyloMissForest provides a highly customizable and robust framework for phylogenetic missing data imputation, with significant topological accuracy and effective speedups over the state of the art.

Low-dimensional compounds containing bioactive ligands. Part XVII: Synthesis, structural, spectral and biological properties of hybrid organic-inorganic complexes based on [PdCl4]2- with derivatives of 8-hydroxyquinolinium.

In this study, four hybrid organic-inorganic compounds (8-H2Q)2[PdCl4] (1), (H2ClQ)2[PdCl4] (2), (H2NQ)2[PdCl4] (3) and (H2MeQ)2[PdCl4]·2H2O (4) (where 8-H2Q = 8-hydroxyquinolinium, H2ClQ = 5-chloro-8-hydroxyquinolinium, H2NQ = 5-nitro-8-hydroxyquinolinium and H2MeQ = 2-methyl-8-hydroxyquinolinium) were synthesized through organic cation modulation. Single-crystal X-ray structure analysis of compounds 1 and 3 indicates that their structures are planar and consist of [PdCl4]2- anions and 8-H2Q or H2NQ cations, respectively. Both ionic components are held together through ionic interactions and hydrogen bonds forming infinite chains linked through π-π interactions to form 2D structures. Furthermore, NMR spectroscopy, UV-Vis spectroscopy, elemental analysis, and FT-IR spectroscopy were used to explore the synthesized compounds. The DNA interaction, antimicrobial activity, antiproliferative activity, and radical scavenging effect of the compounds were evaluated. The hybrid compounds and their free ligands can interact with the calf thymus DNA via an intercalation mode involving the insertion of the aromatic chromophore between the base pairs of DNA; compound 1 has the highest binding affinity. Moreover, they have high antimicrobial efficacy against the tested 14 strains of microorganisms with minimum inhibitory concentration values ranging from <1.95 to 250 µg/mL. The antiproliferative activity of the compounds was investigated against three different cancer cell lines, and their selectivity was verified on mesenchymal stem cells. Compounds 1 and 2 displayed selective and high cytotoxicity against human lung and breast cancer cells and showed moderate cytotoxicity against colon cancer cells. Accordingly, they might be auspicious candidates for future pharmacological investigations in lung and breast cancer research.

Ubiquitin C-terminal hydrolase isozyme L1 is associated with shelterin complex at interstitial telomeric sites.

BACKGROUND: Ubiquitin C-terminal hydrolase isozyme L1 (UCHL1) is primarily expressed in neuronal cells and neuroendocrine cells and has been associated with various diseases, including many cancers. It is a multifunctional protein involved in deubiquitination, ubiquitination and ubiquitin homeostasis, but its specific roles are disputed and still generally undetermined. RESULTS: Herein, we demonstrate that UCHL1 is associated with genomic DNA in certain prostate cancer cell lines, including DU 145 cells derived from a brain metastatic site, and in HEK293T embryonic kidney cells with a neuronal lineage. Chromatin immunoprecipitation and sequencing revealed that UCHL1 localizes to TTAGGG repeats at telomeres and interstitial telomeric sequences, as do TRF1 and TRF2, components of the shelterin complex. A weak or transient interaction between UCHL1 and the shelterin complex was confirmed by immunoprecipitation and proximity ligation assays. UCHL1 and RAP1, also known as TERF2IP and a component of the shelterin complex, were bound to the nuclear scaffold. CONCLUSIONS: We demonstrated a novel feature of UCHL1 in binding telomeres and interstitial telomeric sites.

Location of zeros of Wiener and distance polynomials.

The geometry of polynomials explores geometrical relationships between the zeros and the coefficients of a polynomial. A classical problem in this theory is to locate the zeros of a given polynomial by determining disks in the complex plane in which all its zeros are situated. In this paper, we infer bounds for general polynomials and apply classical and new results to graph polynomials namely Wiener and distance polynomials whose zeros have not been yet investigated. Also, we examine the quality of such bounds by considering four graph classes and interpret the results.