Influence of Pretransplant Restrictive Lung Disease on Allogeneic Hematopoietic Cell Transplantation Outcomes

We conducted a 15-year retrospective cohort study to determine the prevalence of restrictive lung disease prior to allogeneic hematopoietic cell transplant (HCT), and to assess whether this was a risk factor for poor outcomes. 2545 patients were eligible for the analysis. Restrictive lung disease was defined as a total lung capacity (TLC) <80% of predicted normal. Chest x-rays and /or computed tomography scans were reviewed for all restricted patients to determine whether lung parenchymal abnormalities were unlikely or highly likely to cause restriction. Multivariate Cox-proportional hazard and sensitivity analyses were performed to assess the relationship between restriction and early respiratory failure and nonrelapse mortality. Restrictive lung disease was present in 194 subjects (7.6%) prior to transplantation. Among these cases, radiographically apparent abnormalities were unlikely to be the cause of the restriction in 149 (77%) subjects. In unadjusted and adjusted analyses, the presence of pulmonary restriction was significantly associated with a 2-fold increase in risk for early respiratory failure and nonrelapse mortality, suggesting that these outcomes occurring in the absence of radiographically apparent abnormalities may be related to respiratory muscle weakness. These findings suggest that pulmonary restriction should be considered as a risk factor for poor outcomes after transplant

Finding needles in haystacks: linking scientific names, reference specimens and molecular data for Fungi

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Re-annotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi

Molecular analysis of ex-vivo CD133+ GBM cells revealed a common invasive and angiogenic profile but different proliferative signatures among high grade gliomas

<p>Abstract</p> <p>Background</p> <p>Gliomas are the most common type of primary brain tumours, and in this group glioblastomas (GBMs) are the higher-grade gliomas with fast progression and unfortunate prognosis. Two major aspects of glioma biology that contributes to its awful prognosis are the formation of new blood vessels through the process of angiogenesis and the invasion of glioma cells. Despite of advances, two-year survival for GBM patients with optimal therapy is less than 30%. Even in those patients with low-grade gliomas, that imply a moderately good prognosis, treatment is almost never curative. Recent studies have demonstrated the existence of a small fraction of glioma cells with characteristics of neural stem cells which are able to grow <it>in vitro </it>forming neurospheres and that can be isolated <it>in vivo </it>using surface markers such as CD133. The aim of this study was to define the molecular signature of GBM cells expressing CD133 in comparison with non expressing CD133 cells. This molecular classification could lead to the finding of new potential therapeutic targets for the rationale treatment of high grade GBM.</p> <p>Methods</p> <p>Eight fresh, primary and non cultured GBMs were used in order to study the gene expression signatures from its CD133 positive and negative populations isolated by FACS-sorting. Dataset was generated with Affymetrix U133 Plus 2 arrays and analysed using the software of the Affymetrix Expression Console. In addition, genomic analysis of these tumours was carried out by CGH arrays, FISH studies and MLPA;</p> <p>Results</p> <p>Gene expression analysis of CD133+ vs. CD133- cell population from each tumour showed that CD133+ cells presented common characteristics in all glioblastoma samples (up-regulation of genes involved in angiogenesis, permeability and down-regulation of genes implicated in cell assembly, neural cell organization and neurological disorders). Furthermore, unsupervised clustering of gene expression led us to distinguish between two groups of samples: those discriminated by tumour location and, the most importantly, the group discriminated by their proliferative potential;</p> <p>Conclusions</p> <p>Primary glioblastomas could be sub-classified according to the properties of their CD133+ cells. The molecular characterization of these potential stem cell populations could be critical to find new therapeutic targets and to develop an effective therapy for these tumours with very dismal prognosis.</p

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Relationships between Parental Education and Overweight with Childhood Overweight and Physical Activity in 9-11 Year Old Children: Results from a 12-Country Study

Background: Globally, the high prevalence of overweight and low levels of physical activity among children has serious implications for morbidity and premature mortality in adulthood. Various parental factors are associated with childhood overweight and physical activity. The objective of this paper was to investigate relationships between parental education or overweight, and (i) child overweight, (ii) child physical activity, and (iii) explore household coexistence of overweight, in a large international sample. Methods: Data were collected from 4752 children (9-11 years) as part of the International Study of Childhood Obesity, Lifestyle and the Environment in 12 countries around the world. Physical activity of participating children was assessed by accelerometry, and body weight directly measured. Questionnaires were used to collect parents' education level, weight, and height. Results: Maternal and paternal overweight were positively associated with child overweight. Higher household coexistence of parent-child overweight was observed among overweight children compared to the total sample. There was a positive relationship between maternal education and child overweight in Colombia 1.90 (1.23-2.94) [odds ratio (confidence interval)] and Kenya 4.80 (2.21-10.43), and a negative relationship between paternal education and child overweight in Brazil 0.55 (0.33-0.92) and the USA 0.54 (0.33-0.88). Maternal education was negatively associated with children meeting physical activity guidelines in Colombia 0.53 (0.33-0.85), Kenya 0.35 (0.19-0.63), and Portugal 0.54 (0.31-0.96). Conclusions: Results are aligned with previous studies showing positive associations between parental and child overweight in all countries, and positive relationships between parental education and child overweight or negative associations between parental education and child physical activity in lower economic status countries. Relationships between maternal and paternal education and child weight status and physical activity appear to be related to the developmental stage of different countries. Given these varied relationships, it is crucial to further explore familial factors when investigating child overweight and physical activity

Effectiveness of an mHealth intervention combining a smartphone app and smart band on body composition in an overweight and obese population: Randomized controlled trial (EVIDENT 3 study)

Background: Mobile health (mHealth) is currently among the supporting elements that may contribute to an improvement in health markers by helping people adopt healthier lifestyles. mHealth interventions have been widely reported to achieve greater weight loss than other approaches, but their effect on body composition remains unclear. Objective: This study aimed to assess the short-term (3 months) effectiveness of a mobile app and a smart band for losing weight and changing body composition in sedentary Spanish adults who are overweight or obese. Methods: A randomized controlled, multicenter clinical trial was conducted involving the participation of 440 subjects from primary care centers, with 231 subjects in the intervention group (IG; counselling with smartphone app and smart band) and 209 in the control group (CG; counselling only). Both groups were counselled about healthy diet and physical activity. For the 3-month intervention period, the IG was trained to use a smartphone app that involved self-monitoring and tailored feedback, as well as a smart band that recorded daily physical activity (Mi Band 2, Xiaomi). Body composition was measured using the InBody 230 bioimpedance device (InBody Co., Ltd), and physical activity was measured using the International Physical Activity Questionnaire. Results: The mHealth intervention produced a greater loss of body weight (–1.97 kg, 95% CI –2.39 to –1.54) relative to standard counselling at 3 months (–1.13 kg, 95% CI –1.56 to –0.69). Comparing groups, the IG achieved a weight loss of 0.84 kg more than the CG at 3 months. The IG showed a decrease in body fat mass (BFM; –1.84 kg, 95% CI –2.48 to –1.20), percentage of body fat (PBF; –1.22%, 95% CI –1.82% to 0.62%), and BMI (–0.77 kg/m2, 95% CI –0.96 to 0.57). No significant changes were observed in any of these parameters in men; among women, there was a significant decrease in BMI in the IG compared with the CG. When subjects were grouped according to baseline BMI, the overweight group experienced a change in BFM of –1.18 kg (95% CI –2.30 to –0.06) and BMI of –0.47 kg/m2 (95% CI –0.80 to –0.13), whereas the obese group only experienced a change in BMI of –0.53 kg/m2 (95% CI –0.86 to –0.19). When the data were analyzed according to physical activity, the moderate-vigorous physical activity group showed significant changes in BFM of –1.03 kg (95% CI –1.74 to –0.33), PBF of –0.76% (95% CI –1.32% to –0.20%), and BMI of –0.5 kg/m2 (95% CI –0.83 to –0.19). Conclusions: The results from this multicenter, randomized controlled clinical trial study show that compared with standard counselling alone, adding a self-reported app and a smart band obtained beneficial results in terms of weight loss and a reduction in BFM and PBF in female subjects with a BMI less than 30 kg/m2 and a moderate-vigorous physical activity level. Nevertheless, further studies are needed to ensure that this profile benefits more than others from this intervention and to investigate modifications of this intervention to achieve a global effect

Study on multi-ELVES in the Pierre Auger Observatory

Since 2013, the four sites of the Fluorescence Detector (FD) of the Pierre Auger Observatory record ELVES with a dedicated trigger. These UV light emissions are correlated to distant lightning strikes. The length of recorded traces has been increased from 100 μs (2013), to 300 μs (2014-16), to 900 μs (2017-present), to progressively extend the observation of the light emission towards the vertical of the causative lightning and beyond. A large fraction of the observed events shows double ELVES within the time window, and, in some cases, even more complex structures are observed. The nature of the multi-ELVES is not completely understood but may be related to the different types of lightning in which they are originated. For example, it is known that Narrow Bipolar Events can produce double ELVES, and Energetic In-cloud Pulses, occurring between the main negative and upper positive charge layer of clouds, can induce double and even quadruple ELVES in the ionosphere. This report shows the seasonal and daily dependence of the time gap, amplitude ratio, and correlation between the pulse widths of the peaks in a sample of 1000+ multi-ELVES events recorded during the period 2014-20. The events have been compared with data from other satellite and ground-based sensing devices to study the correlation of their properties with lightning observables such as altitude and polarity

A Search for Photons with Energies above 2 × 1017eV Using Hybrid Data from the Low-Energy Extensions of the Pierre Auger Observatory

Ultra-high-energy photons with energies exceeding 1017 eV offer a wealth of connections to different aspects of cosmic-ray astrophysics as well as to gamma-ray and neutrino astronomy. The recent observations of photons with energies in the 1015 eV range further motivate searches for even higher-energy photons. In this paper, we present a search for photons with energies exceeding 2 × 1017 eV using about 5.5 yr of hybrid data from the low-energy extensions of the Pierre Auger Observatory. The upper limits on the integral photon flux derived here are the most stringent ones to date in the energy region between 1017 and 1018 eV

Deep-learning based reconstruction of the shower maximum Xmax using the water-Cherenkov detectors of the Pierre Auger Observatory

The atmospheric depth of the air shower maximum Xmax is an observable commonly used for the determination of the nuclear mass composition of ultra-high energy cosmic rays. Direct measurements of Xmax are performed using observations of the longitudinal shower development with fluorescence telescopes. At the same time, several methods have been proposed for an indirect estimation of Xmax from the characteristics of the shower particles registered with surface detector arrays. In this paper, we present a deep neural network (DNN) for the estimation of Xmax. The reconstruction relies on the signals induced by shower particles in the ground based water-Cherenkov detectors of the Pierre Auger Observatory. The network architecture features recurrent long short-term memory layers to process the temporal structure of signals and hexagonal convolutions to exploit the symmetry of the surface detector array. We evaluate the performance of the network using air showers simulated with three different hadronic interaction models. Thereafter, we account for long-term detector effects and calibrate the reconstructed Xmax using fluorescence measurements. Finally, we show that the event-by-event resolution in the reconstruction of the shower maximum improves with increasing shower energy and reaches less than 25 g/cm2 at energies above 2×1019 eV

The depth of the shower maximum of air showers measured with AERA

The Auger Engineering Radio Array (AERA) is currently the largest array of radio antennas for the detection of cosmic rays, spanning an area of 17 km2 with 153 radio antennas, measuring in the energy range from 1017.0 to 1019.0 eV. It detects the radio emission of extensive air showers produced by cosmic rays in the 30 − 80 MHz band. The cosmic-ray mass composition is a crucial piece of information in determining the sources of cosmic rays and their acceleration mechanisms. The depth of the shower maximum, Xmax, a probe for mass composition can be determined with a likelihood analysis that compares the measured radio-emission footprint on the ground to an ensemble of footprints from CORSIKA/CoREAS Monte-Carlo air shower simulations. These simulations are also used to determine the resolution of the method and to validate the reconstruction by identifying and correcting for systematic uncertainties. We will present the method for the reconstruction of the depth of the shower maximum, achieving a resolution of up to 15 g/cm2, show compatibility with the independent fluorescence detector reconstruction measured on an event-by-event basis, and show that the data taken over the past seven years with AERA shows a light cosmic-ray mass composition reconstruction in the energy range from 1017.5 to 1018.8 eV