Luminescence properties and time-resolved spectroscopy of rare-earth doped SrMoO4 single crystals

The work of V. Pankratova was supported by the financial support of Scientific Research Project for Students and Young Researchers (SJZ/2020/05) realized at Institute of Solid State Physics, University of Latvia. The Institute of Solid State Physics, University of Latvia as the Center of Excellence has received funding from the European Union’s Horizon 2020 Framework Programme H2020-WIDESPREAD-01-2016-2017-TeamingPhase2 under grant agreement No. 739508, project CAMART2.Luminescence properties of nominally pure and doped with Eu3+ and Pr3+ ions SrMoO4 single crystals grown by the Czochralski method have been studied. Thermal quenching of intrinsic emission of pure and doped SrMoO4 single crystals has been observed, as well as a correlation of thermal quenching activation energies with rare-earth ion concentration has been observed. Tunable laser was used to study time-resolved luminescence in a range from 10 K to room temperature. The effect of dopant nature and concentration on intrinsic emission and decay kinetics has been elucidated. --//-- Viktorija Pankratova, Elizaveta E. Dunaeva, Irina S. Voronina, Anna P. Kozlova, Roman Shendrik, Vladimir Pankratov, Luminescence properties and time-resolved spectroscopy of rare-earth doped SrMoO4 single crystals, Optical Materials: X, Volume 15, 2022, 100169, ISSN 2590-1478, https://doi.org/10.1016/j.omx.2022.100169. Article published under the CC BY-NC-ND licence.Scientific Research Project for Students and Young Researchers (SJZ/2020/05); the Institute of Solid State Physics, University of Latvia as the Center of Excellence has received funding from the European Union’s Horizon 2020 Framework Programme H2020-WIDESPREAD-01-2016-2017-TeamingPhase2 under grant agreement No. 739508, project CAMART2

Genomic features of resistant <i>Klebsiella pneumonia</i>, isolated from the bloodstream and cerebrospinal fluid of pediatric hospital patients

Introduction. Carbapenemase-producing Klebsiella pneumoniae (CP-Kp), which are international high-risk clones, have become a problem of utmost importance. CP-Kps, adapting to the hospital environment, evolve into convergent pathotypes. Such variants combine traits of two genetic lineages: multidrug resistant (MDR) and hypervirulent. The pathotypes, along with MDR K. pneumoniae, pose an exceptional threat to young patients during systemic infection. The objective of this study is the detailed molecular genetic analysis of MDR isolates of K. pneumoniae detected during the monitoring of resistant Gram-negative bacteria at the National Medical Research Center for Children’s Health in 2014–2021. Materials and methods. Whole-genome sequencing with a subsequent bioinformatics analysis of eight MDR isolates from the bloodstream and cerebrospinal fluid. Results. MDR isolates belonged to 4 sublineages (SL): SL307, SL395, SL29 and SL1198. In the genomes of 6 pangrug-resistant (PDR) isolates, genes associated with resistance to all categories of antibiotics recommended for Enterobacteriaceae therapy were identified. Plasmids were present in all genomes. In 6 isolates, plasmids contained heavy metal ion resistance operons in addition to antibiotic resistance genes. Prophages within the plasmids were also involved in the transfer of resistance genes. The ST395 isolate from the cerebrospinal fluid belonged to the convergent pathotype in terms of resistance and virulence. Comparison of genomes within SLs revealed recombination events in the K- and O-locus regions and the Yersiniabactin operon. Conclusion. Thus, in a sample of resistant K. pneumoniae isolated from bloodstream and cerebrospinal fluid, 6 PDR isolates were detected, one of which belongs to the convergent pathotype ST395

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Hair Trace Element and Electrolyte Content in Women with Natural and In Vitro Fertilization-Induced Pregnancy

The objective of the present study was to perform comparative analysis of hair trace element content in women with natural and in vitro fertilization (IVF)-induced pregnancy. Hair trace element content in 33 women with IVF-induced pregnancy and 99 age- and body mass index-matched control pregnant women (natural pregnancy) was assessed using inductively coupled plasma mass spectrometry. The results demonstrated that IVF-pregnant women are characterized by significantly lower hair levels of Cu, Fe, Si, Zn, Ca, Mg, and Ba at p < 0.05 or lower. Comparison of the individual levels with the national reference values demonstrated higher incidence of Fe and Cu deficiency in IVF-pregnant women in comparison to that of the controls. IVF pregnancy was also associated with higher hair As levels (p < 0.05). Multiple regression analysis revealed a significant interrelation between IVF pregnancy and hair Cu, Fe, Si, and As content. Hair Cu levels were also influenced by vitamin/mineral supplementation and the number of pregnancies, whereas hair Zn content was dependent on prepregnancy anthropometric parameters. In turn, planning of pregnancy had a significant impact on Mg levels in scalp hair. Generally, the obtained data demonstrate an elevated risk of copper, iron, zinc, calcium, and magnesium deficiency and arsenic overload in women with IVF-induced pregnancy. The obtained data indicate the necessity of regular monitoring of micronutrient status in IVF-pregnant women in order to prevent potential deleterious effects of altered mineral homeostasis

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation