The Redshift One LDSS-3 Emission line Survey (ROLES) II: Survey method and z~1 mass-dependent star-formation rate density

Motivated by suggestions of 'cosmic downsizing', in which the dominant contribution to the cosmic star formation rate density (SFRD) proceeds from higher to lower mass galaxies with increasing cosmic time, we describe the design and implementation of the Redshift One LDSS3 Emission line Survey (ROLES). ROLES is a K-selected (22.5 < K_AB < 24.0) survey for dwarf galaxies [8.5<log(M*/Msun)< 9.5] at 0.89 < z < 1.15 drawn from two extremely deep fields (GOODS-S and MS1054-FIRES). Using the [OII]3727 emission line, we obtain redshifts and star-formation rates (SFRs) for star-forming galaxies down to a limit of ~0.3 Msun/yr. We present the [OII] luminosity function measured in ROLES and find a faint end slope of alpha_faint ~ -1.5, similar to that measured at z~0.1 in the SDSS. By combining ROLES with higher mass surveys, we measure the SFRD as a function of stellar mass using [OII] (with and without various empirical corrections), and using SED-fitting to obtain the SFR from the rest-frame UV luminosity for galaxies with spectroscopic redshifts. Our best estimate of the corrected [OII]-SFRD and UV SFRD both independently show that the SFRD evolves equally for galaxies of all masses between z~1 and z~0.1. The exact evolution in normalisation depends on the indicator used, with the [OII]-based estimate showing a change of a factor of ~2.6 and the UV-based a factor of ~6. We discuss possible reasons for the discrepancy in normalisation between the indicators, but note that the magnitude of this uncertainty is comparable to the discrepancy between indicators seen in other z~1 works. Our result that the shape of the SFRD as a function of stellar mass (and hence the mass range of galaxies dominating the SFRD) does not evolve between z~1 and z~0.1 is robust to the choice of indicator. [abridged]Comment: Resubmitted to MNRAS following first referee report. 20 pages, 16 figures. High resolution version available at http://astro.uwaterloo.ca/~dgilbank/papers/roles2.pd

Evidence for core exosome independent function of the nuclear exoribonuclease Rrp6p

The RNA exosome processes and degrades RNAs in archaeal and eukaryotic cells. Exosomes from yeast and humans contain two active exoribonuclease components, Rrp6p and Dis3p/Rrp44p. Rrp6p is concentrated in the nucleus and the dependence of its function on the nine-subunit core exosome and Dis3p remains unclear. We found that cells lacking Rrp6p accumulate poly(A)+ rRNA degradation intermediates distinct from those found in cells depleted of Dis3p, or the core exosome component Rrp43p. Depletion of Dis3p in the absence of Rrp6p causes a synergistic increase in the levels of degradation substrates common to the core exosome and Rrp6p, but has no effect on Rrp6p-specific substrates. Rrp6p lacking a portion of its C-terminal domain no longer co-purifies with the core exosome, but continues to carry out RNA 3′-end processing of 5.8S rRNA and snoRNAs, as well as the degradation of certain truncated Rrp6-specific rRNA intermediates. However, disruption of Rrp6p–core exosome interaction results in the inability of the cell to efficiently degrade certain poly(A)+ rRNA processing products that require the combined activities of Dis3p and Rrp6p. These findings indicate that Rrp6p may carry out some of its critical functions without physical association with the core exosome

Small-Molecule Inhibitor of the Shigella flexneri Master Virulence Regulator VirF

This is the publisher's version, also available electronically from http://iai.asm.org/content/81/11/4220VirF is an AraC family transcriptional activator that is required for the expression of virulence genes associated with invasion and cell-to-cell spread by Shigella flexneri, including multiple components of the type three secretion system (T3SS) machinery and effectors. We tested a small-molecule compound, SE-1 (formerly designated OSSL_051168), which we had identified as an effective inhibitor of the AraC family proteins RhaS and RhaR, for its ability to inhibit VirF. Cell-based reporter gene assays with Escherichia coli and Shigella, as well as in vitro DNA binding assays with purified VirF, demonstrated that SE-1 inhibited DNA binding and transcription activation (likely by blocking DNA binding) by VirF. Analysis of mRNA levels using real-time quantitative reverse transcription-PCR (qRT-PCR) further demonstrated that SE-1 reduced the expression of the VirF-dependent virulence genes icsA, virB, icsB, and ipaB in Shigella. We also performed eukaryotic cell invasion assays and found that SE-1 reduced invasion by Shigella. The effect of SE-1 on invasion required preincubation of Shigella with SE-1, in agreement with the hypothesis that SE-1 inhibited the expression of VirF-activated genes required for the formation of the T3SS apparatus and invasion. We found that the same concentrations of SE-1 had no detectable effects on the growth or metabolism of the bacterial cells or the eukaryotic host cells, respectively, indicating that the inhibition of invasion was not due to general toxicity. Overall, SE-1 appears to inhibit transcription activation by VirF, exhibits selectivity toward AraC family proteins, and has the potential to be developed into a novel antibacterial agent

Complete genome characterization of two wild-type measles viruses from Vietnamese infants during the 2014 outbreak

A large measles virus outbreak occurred across Vietnam in 2014. We identified and obtained complete measles virus genomes in stool samples collected from two diarrheal pediatric patients in Dong Thap Province. These are the first complete genome sequences of circulating measles viruses in Vietnam during the 2014 measles outbreak

Genome sequences of a novel Vietnamese bat bunyavirus

To document the viral zoonotic risks in Vietnam, fecal samples were systematically collected from a number of mammals in southern Vietnam and subjected to agnostic deep sequencing. We describe here novel Vietnamese bunyavirus sequences detected in bat feces. The complete L and S segments from 14 viruses were determined

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed