High-Dose Chemotherapy with Autologous Hematopoietic Stem-Cell Rescue for Pediatric Brain Tumor Patients: A Single Institution Experience from UCLA

Background. Dose-dependent response makes certain pediatric brain tumors appropriate targets for high-dose chemotherapy with autologous hematopoietic stem-cell rescue (HDCT-AHSCR). Methods. The clinical outcomes and toxicities were analyzed retrospectively for 18 consecutive patients ≤19 y/o treated with HDCT-AHSCR at UCLA (1999–2009). Results. Patients' median age was 2.3 years. Fourteen had primary and 4 recurrent tumors: 12 neural/embryonal (7 medulloblastomas, 4 primitive neuroectodermal tumors, and a pineoblastoma), 3 glial/mixed, and 3 germ cell tumors. Eight patients had initial gross-total and seven subtotal resections. HDCT mostly consisted of carboplatin and/or thiotepa ± etoposide (n = 16). Nine patients underwent a single AHSCR and nine ≥3 tandems. Three-year progression-free and overall survival probabilities were 60.5% ± 16 and 69.3% ± 11.5. Ten patients with pre-AHSCR complete remissions were alive/disease-free, whereas 5 of 8 with measurable disease were deceased (median followup: 2.3 yrs). Nine of 13 survivors avoided radiation. Single AHSCR regimens had greater toxicity than ≥3 AHSCR (P < .01). Conclusion. HDCT-AHSCR has a definitive, though limited role for selected pediatric brain tumors with poor prognosis and pretransplant complete/partial remissions

Thy-1 Attenuates TNF-α-Activated Gene Expression in Mouse Embryonic Fibroblasts via Src Family Kinase

Heterogeneous surface expression of Thy-1 in fibroblasts modulates inflammation and may thereby modulate injury and repair. As a paradigm, patients with idiopathic pulmonary fibrosis, a disease with pathologic features of chronic inflammation, demonstrate an absence of Thy-1 immunoreactivity within areas of fibrotic activity (fibroblast foci) in contrast to the predominant Thy-1 expressing fibroblasts in the normal lung. Likewise, Thy-1 deficient mice display more severe lung fibrosis in response to an inflammatory injury than wildtype littermates. We investigated the role of Thy-1 in the response of fibroblasts to the pro-inflammatory cytokine TNF-α. Our study demonstrates distinct profiles of TNF-α-activated gene expression in Thy-1 positive (Thy-1+) and negative (Thy-1−) subsets of mouse embryonic fibroblasts (MEF). TNF-α induced a robust activation of MMP-9, ICAM-1, and the IL-8 promoter driven reporter in Thy-1− MEFs, in contrast to only a modest increase in Thy-1+ counterparts. Consistently, ectopic expression of Thy-1 in Thy-1− MEFs significantly attenuated TNF-α-activated gene expression. Mechanistically, TNF-α activated Src family kinase (SFK) only in Thy-1− MEFs. Blockade of SFK activation abrogated TNF-α-activated gene expression in Thy-1− MEFs, whereas restoration of SFK activation rescued the TNF-α response in Thy-1+ MEFs. Our findings suggest that Thy-1 down-regulates TNF-α-activated gene expression via interfering with SFK- and NF-κB-mediated transactivation. The current study provides a novel mechanistic insight to the distinct roles of fibroblast Thy-1 subsets in inflammation

Development and Psychometric Validation of the Pandemic-Related Traumatic Stress Scale for Children and Adults

To assess the public health impact of the COVID-19 pandemic on mental health, investigators from the National Institutes of Health Environmental influences on Child Health Outcomes (ECHO) research program developed the Pandemic-Related Traumatic Stress Scale (PTSS). Based on the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) acute stress disorder symptom criteria, the PTSS is designed for adolescent (13–21 years) and adult self-report and caregiver-report on 3–12-year-olds. To evaluate psychometric properties, we used PTSS data collected between April 2020 and August 2021 from non-pregnant adult caregivers (n = 11,483), pregnant/postpartum individuals (n = 1,656), adolescents (n = 1,795), and caregivers reporting on 3–12-year-olds (n = 2,896). We used Mokken scale analysis to examine unidimensionality and reliability, Pearson correlations to evaluate relationships with other relevant variables, and analyses of variance to identify regional, age, and sex differences. Mokken analysis resulted in a moderately strong, unidimensional scale that retained nine of the original 10 items. We detected small to moderate positive associations with depression, anxiety, and general stress, and negative associations with life satisfaction. Adult caregivers had the highest PTSS scores, followed by adolescents, pregnant/postpartum individuals, and children. Caregivers of younger children, females, and older youth had higher PTSS scores compared to caregivers of older children, males, and younger youth, respectively

A meta-analysis of immune-cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes

Background: Changes in cell-type composition of tissues are associated with a wide range of diseases and environmental risk factors and may be causally implicated in disease development and progression. However, these shifts in cell-type fractions are often of a low magnitude, or involve similar cell subtypes, making their reliable identification challenging. DNA methylation profiling in a tissue like blood is a promising approach to discover shifts in cell-type abundance, yet studies have only been performed at a relatively low cellular resolution and in isolation, limiting their power to detect shifts in tissue composition. Methods: Here we derive a DNA methylation reference matrix for 12 immune-cell types in human blood and extensively validate it with flow-cytometric count data and in whole-genome bisulfite sequencing data of sorted cells. Using this reference matrix, we perform a directional Stouffer and fixed effects meta-analysis comprising 23,053 blood samples from 22 different cohorts, to comprehensively map associations between the 12 immune-cell fractions and common phenotypes. In a separate cohort of 4386 blood samples, we assess associations between immune-cell fractions and health outcomes. Results: Our meta-analysis reveals many associations of cell-type fractions with age, sex, smoking and obesity, many of which we validate with single-cell RNA sequencing. We discover that naïve and regulatory T-cell subsets are higher in women compared to men, while the reverse is true for monocyte, natural killer, basophil, and eosinophil fractions. Decreased natural killer counts associated with smoking, obesity, and stress levels, while an increased count correlates with exercise and sleep. Analysis of health outcomes revealed that increased naïve CD4 + T-cell and N-cell fractions associated with a reduced risk of all-cause mortality independently of all major epidemiological risk factors and baseline co-morbidity. A machine learning predictor built only with immune-cell fractions achieved a C-index value for all-cause mortality of 0.69 (95%CI 0.67–0.72), which increased to 0.83 (0.80–0.86) upon inclusion of epidemiological risk factors and baseline co-morbidity. Conclusions: This work contributes an extensively validated high-resolution DNAm reference matrix for blood, which is made freely available, and uses it to generate a comprehensive map of associations between immune-cell fractions and common phenotypes, including health outcomes

Environmental gradients and the evolution of successional habitat specialization: A test case with 14 Neotropical forest sites

© 2015 British Ecological Society. Successional gradients are ubiquitous in nature, yet few studies have systematically examined the evolutionary origins of taxa that specialize at different successional stages. Here we quantify successional habitat specialization in Neotropical forest trees and evaluate its evolutionary lability along a precipitation gradient. Theoretically, successional habitat specialization should be more evolutionarily conserved in wet forests than in dry forests due to more extreme microenvironmental differentiation between early and late-successional stages in wet forest. We applied a robust multinomial classification model to samples of primary and secondary forest trees from 14 Neotropical lowland forest sites spanning a precipitation gradient from 788 to 4000 mm annual rainfall, identifying species that are old-growth specialists and secondary forest specialists in each site. We constructed phylogenies for the classified taxa at each site and for the entire set of classified taxa and tested whether successional habitat specialization is phylogenetically conserved. We further investigated differences in the functional traits of species specializing in secondary vs. old-growth forest along the precipitation gradient, expecting different trait associations with secondary forest specialists in wet vs. dry forests since water availability is more limiting in dry forests and light availability more limiting in wet forests. Successional habitat specialization is non-randomly distributed in the angiosperm phylogeny, with a tendency towards phylogenetic conservatism overall and a trend towards stronger conservatism in wet forests than in dry forests. However, the specialists come from all the major branches of the angiosperm phylogeny, and very few functional traits showed any consistent relationships with successional habitat specialization in either wet or dry forests. Synthesis. The niche conservatism evident in the habitat specialization of Neotropical trees suggests a role for radiation into different successional habitats in the evolution of species-rich genera, though the diversity of functional traits that lead to success in different successional habitats complicates analyses at the community scale. Examining the distribution of particular lineages with respect to successional gradients may provide more insight into the role of successional habitat specialization in the evolution of species-rich taxa

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M&gt;70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0&lt;e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM