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475. The 2-rainbow domination number of Cartesian product of cyclesSimon Brezovnik, Darja Rupnik Poklukar, Janez Žerovnik, 2025, original scientific article Abstract: A k-rainbow dominating function (kRDF) of G is a function that assigns subsets of {1, 2, ..., k} to the vertices of G such that for vertices v with f(v) = ∅ we have Uu∈N(v)f(u) = {1, 2, ..., k}. The weight w(f) of a kRDF f is defined as w(f) = P v∈V(G)|f(v)|. The minimum weight of a kRDF of G is called the k-rainbow domination number of G, which is denoted by γrk(G). In this paper, we study the 2-rainbow domination number of the Cartesian product of two cycles. Exact values are given for a number of infinite families and we prove lower and upper bounds for all other cases.
Keywords: 2-rainbow domination, domination number, cartesian product
Published in DiRROS: 21.11.2025; Views: 120; Downloads: 75
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480. Male sex, B symptoms, bone marrow involvement, and genetic alterations as predictive factors in diffuse large B-cell lymphoma : Elektronski virMatej Panjan, Vita Šetrajčič Dragoš, Gorana Gašljević, Srdjan Novaković, Barbara Jezeršek Novaković, 2025, original scientific article Abstract: Approximately 40% of patients with diffuse large B-cell lymphoma (DLBCL) are not cured with first-line chemoimmunotherapy, resulting in poor prognosis. Schmitz et al. classified DLBCL into four prognostic genetic groups using whole-exome sequencing. We applied a simplified approach using a targeted next-generation sequencing assay (Archer FusionPlex Lymphoma Assay) to analyze samples from 105 patients—53 with a progression-free survival (PFS) < 2 years (the “Relapse group”) and 52 with a PFS > 5 years (the “Remission group”) following first-line systemic treatment. Patients were classified according to Schmitz et al. into the following categories: “MCD” (MYD88L265P and CD79B alteration), “N1” (NOTCH1 alteration), “BN2” (NOTCH2 alteration and BCL6 translocation), and “EZB” (EZH2 alteration and BCL2 translocation). The predictive value of this simplified genetic classification and of relevant clinical features were evaluated. The “Relapse group” included more patients classified as MCD and N1, while fewer were classified as EZB and BN2. Also, cell-of-origin (COO) characteristics and the size of N1 aligned with the classification of Schmitz et al. However, the limited sample size precludes definitive conclusions about the predictive value of our simplified approach. Additionally, male sex, B symptoms, and bone marrow involvement were associated with relapse. Therefore, these clinical features may be useful in predicting outcomes until an effective molecular classification is widely adopted.
Keywords: DLBCL, genetic classification, predictive, lymphoma
Published in DiRROS: 21.11.2025; Views: 105; Downloads: 29
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