RGBM: regularized gradient boosting machines for identification of the transcriptional regulators of discrete glioma subtypes

We propose a generic framework for gene regulatory network (GRN) inference approached as a feature selection problem. GRNs obtained using Machine Learning techniques are often dense, whereas real GRNs are rather sparse. We use a Tikonov regularization inspired optimal L-curve criterion that utilizes the edge weight distribution for a given target gene to determine the optimal set of TFs associated with it. Our proposed framework allows to incorporate a mechanistic active biding network based on cis-regulatory motif analysis. We evaluate our regularization framework in conjunction with two non-linear ML techniques, namely gradient boosting machines (GBM) and random-forests (GENIE), resulting in a regularized feature selection based method specifically called RGBM and RGENIE respectively. RGBM has been used to identify the main transcription factors that are causally involved as master regulators of the gene expression signature activated in the FGFR3-TACC3-positive glioblastoma. Here, we illustrate that RGBM identifies the main regulators of the molecular subtypes of brain tumors. Our analysis reveals the identity and corresponding biological activities of the master regulators characterizing the difference between G-CIMP-high and G-CIMP-low subtypes and between PA-like and LGm6-GBM, thus providing a clue to the yet undetermined nature of the transcriptional events among these subtypes

Investigation of recast and crack formation in laser trepanning drilling of CMSX-4 angled holes

This paper presents an experimental investigation on the influences of laser trepanning drilling process parameters on the recast layer thickness and surface crack formation in CMSX-4 nickel-based superalloy angled holes. The effects of peak power, pulse frequency and the trepanning speed as input parameters were investigated in details by varying the laser drilling conditions using Taguchi orthogonal array-based design of experiment approach. Analysis of variance identifies the significant parameters affecting the output responses. It is found that the output responses are affected mainly by the peak power and trepanning speed. The experimental results reveal that the recast layer thickness increases with the increase of peak power and trepanning speed whereas the crack number density decreases with the increase of peak power only. Pulse frequency has no significant effect on both output responses within the range of values investigated. The knowledge gained in this parametric study could be used to improve the metallurgical characteristics of laser-drilled nickel-based acute angled holes

FOXP3 Inhibitory Peptide P60 Increases Efficacy of Cytokine-induced Killer Cells against Renal and Pancreatic Cancer Cells

Background/Aim: Cytokine-induced killer (CIK) cells are ex vivo expanded major histocompatibility complex (MHC)-unrestricted cytotoxic cells with promising effects against a variety of cancer types. Regulatory T-cells (T-reg) have been shown to reduce the effectiveness of CIK cells against tumor cells. Peptide P60 has been shown to inhibit the immunosuppressive functions of T-regs. This study aimed at examining the effect of p60 on CIK cells efficacy against renal and pancreatic cancer cells. Materials and Methods: The effect of P60 on CIK cytotoxicity was examined using flow cytometry, WST-8-based cell viability assay and interferon γ (IFNγ) ELISA. Results: P60 treatment resulted in a significant decrease in the viability of renal and pancreatic cancer cell lines co-cultured with CIK cells. No increase in IFNγ secretion from CIK cells was detected following treatment with P60. P60 caused no changes in the distribution of major effector cell populations in CIK cell cultures. Conclusion: P60 may potentiate CIK cell cytotoxicity against tumor cells

Fluorescent Probes for Ecto-5′-nucleotidase (CD73)

Ecto-5′-nucleotidase (CD73) catalyzes the hydrolysis of AMP to anti-inflammatory, immunosuppressive adenosine. It is expressed on vascular endothelial, epithelial, and also numerous cancer cells where it strongly contributes to an immunosuppressive microenvironment. In the present study we designed and synthesized fluorescent-labeled CD73 inhibitors with low nanomolar affinity and high selectivity based on N6-benzyl-α,β-methylene-ADP (PSB-12379) as a lead structure. Fluorescein was attached to the benzyl residue via different linkers resulting in PSB-19416 (14b, Ki12.6 nM) and PSB-18332 (14a, Ki2.98 nM) as fluorescent high-affinity probes for CD73. These compounds are anticipated to become useful tools for biological studies, drug screening, and diagnostic applications

OMRT-3. Longitudinal analysis of diffuse glioma reveals cell state dynamics at recurrence associated with changes in genetics and the microenvironment

Diffuse glioma is an aggressive brain cancer that is characterized by a poor prognosis and a universal resistance to therapy. The evolutionary processes behind this resistance remain unclear. Previous studies by the Glioma Longitudinal Analysis (GLASS) Consortium have indicated that therapy-induced selective pressures shape the genetic evolution of glioma in a stochastic manner. However, single-cell studies have revealed that malignant glioma cells are highly plastic and transition their cell state in response to diverse challenges, including changes in the microenvironment and the administration of standard-of-care therapy. Interactions between these factors remain poorly understood, making it difficult to predict how a patient’s tumor will evolve from diagnosis to recurrence. To interrogate the factors driving therapy resistance in diffuse glioma, we collected and analyzed RNA- and/or DNA-sequencing data from temporally separated tumor pairs of 292 adult patients with IDH-wild-type or IDH-mutant glioma. Recurrent tumors exhibited diverse changes that were attributable to changes in anatomic composition, somatic alterations, and microenvironment interactions. Hypermutation and acquired CDKN2A homozygous deletions associated with an increase in proliferating stem-like malignant cells at recurrence in both glioma subtypes, reflecting active tumor expansion. IDH-wild-type tumors were more invasive at recurrence, and their malignant cells exhibited increased expression of neuronal signaling programs that reflected a possible role for neuronal interactions in promoting glioma progression. Mesenchymal transition was associated with the presence of a specific myeloid cell state defined by unique ligand-receptor interactions with malignant cells, providing opportunities to target this transition through therapy. Collectively, our results uncover recurrence-associated changes in genetics and the microenvironment that can be targeted to shape disease progression following initial diagnosis

Reasons for facebook usage: data from 46 countries

info:eu-repo/semantics/publishedVersio

Contrasting Computational Models of Mate Preference Integration Across 45 Countries

Humans express a wide array of ideal mate preferences. Around the world, people desire romantic partners who are intelligent, healthy, kind, physically attractive, wealthy, and more. In order for these ideal preferences to guide the choice of actual romantic partners, human mating psychology must possess a means to integrate information across these many preference dimensions into summaries of the overall mate value of their potential mates. Here we explore the computational design of this mate preference integration process using a large sample of n = 14,487 people from 45 countries around the world. We combine this large cross-cultural sample with agent-based models to compare eight hypothesized models of human mating markets. Across cultures, people higher in mate value appear to experience greater power of choice on the mating market in that they set higher ideal standards, better fulfill their preferences in choice, and pair with higher mate value partners. Furthermore, we find that this cross-culturally universal pattern of mate choice is most consistent with a Euclidean model of mate preference integration.The work of Truong Thi Khanh Ha was supported by grants 501.01–2016.02 from the Vietnam National Foundation for Science and Technology Development (NAFOSTED). Anna Oleszkiewicz was supported by the Ministry of Science and Higher Education (#626/STYP/12/2017). This study was conducted in line with project NIR No. 01201370995 “Cross-cultural and interdisciplinary researches. Biosocial and cross-cultural analysis of models of tolerance and basic values of culture in modern society” (Marina Butovskaya and Daria Dronova). Agnieszka Sorokowska and Piotr Sorokowski were supported by the National Science Center—Poland (2014/13/B/HS6/02644). Petra Gyuris, András Láng, and Norbert Meskó were supported by the Hungarian Scientific Research Fund — OTKA (K125437). Feng Jiang was supported by the National Nature Science Foundation of China, grant No. 71971225