1,695 research outputs found

    Impact of Molecular Spectroscopy on Carbon Monoxide Abundances from TROPOMI

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    The impact of SEOM-IAS (Scientific Exploitation of Operational Missions-Improved Atmospheric Spectroscopy) spectroscopic information on CO columns from TROPOMI (Tropospheric Monitoring Instrument) shortwave infrared (SWIR) observations was examined. HITRAN 2016 (High Resolution Transmission) and GEISA 2015 (Gestion et Etude des Informations Spectroscopiques Atmosphériques 2015) were used as a reference upon which the spectral fitting residuals, retrieval errors and inferred quantities were assessed. It was found that SEOM-IAS significantly improves the quality of the CO retrieval by reducing the residuals to TROPOMI observations. The magnitude of the impact is dependent on the climatological region and spectroscopic reference used. The difference in the CO columns was found to be rather small, although discrepancies reveal, for selected scenes, in particular, for observations with elevated molecular concentrations. A brief comparison to Total Column Carbon Observing Network (TCCON) and Network for the Detection of Atmospheric Composition Change (NDACC) also demonstrated that both spectroscopies cause similar columns; however, the smaller retrieval errors in the SEOM with Speed-Dependent Rautian and line-Mixing (SDRM) inferred CO turned out to be beneficial in the comparison of post-processed mole fractions with ground-based references

    HLA Ligand Atlas: a benign reference of HLA-presented peptides to improve T-cell-based cancer immunotherapy

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    BACKGROUND The human leucocyte antigen (HLA) complex controls adaptive immunity by presenting defined fractions of the intracellular and extracellular protein content to immune cells. Understanding the benign HLA ligand repertoire is a prerequisite to define safe T-cell-based immunotherapies against cancer. Due to the poor availability of benign tissues, if available, normal tissue adjacent to the tumor has been used as a benign surrogate when defining tumor-associated antigens. However, this comparison has proven to be insufficient and even resulted in lethal outcomes. In order to match the tumor immunopeptidome with an equivalent counterpart, we created the HLA Ligand Atlas, the first extensive collection of paired HLA-I and HLA-II immunopeptidomes from 227 benign human tissue samples. This dataset facilitates a balanced comparison between tumor and benign tissues on HLA ligand level. METHODS Human tissue samples were obtained from 16 subjects at autopsy, five thymus samples and two ovary samples originating from living donors. HLA ligands were isolated via immunoaffinity purification and analyzed in over 1200 liquid chromatography mass spectrometry runs. Experimentally and computationally reproducible protocols were employed for data acquisition and processing. RESULTS The initial release covers 51 HLA-I and 86 HLA-II allotypes presenting 90,428 HLA-I- and 142,625 HLA-II ligands. The HLA allotypes are representative for the world population. We observe that immunopeptidomes differ considerably between tissues and individuals on source protein and HLA-ligand level. Moreover, we discover 1407 HLA-I ligands from non-canonical genomic regions. Such peptides were previously described in tumors, peripheral blood mononuclear cells (PBMCs), healthy lung tissues and cell lines. In a case study in glioblastoma, we show that potential on-target off-tumor adverse events in immunotherapy can be avoided by comparing tumor immunopeptidomes to the provided multi-tissue reference. CONCLUSION Given that T-cell-based immunotherapies, such as CAR-T cells, affinity-enhanced T cell transfer, cancer vaccines and immune checkpoint inhibition, have significant side effects, the HLA Ligand Atlas is the first step toward defining tumor-associated targets with an improved safety profile. The resource provides insights into basic and applied immune-associated questions in the context of cancer immunotherapy, infection, transplantation, allergy and autoimmunity. It is publicly available and can be browsed in an easy-to-use web interface at https://hla-ligand-atlas.org

    Tranexamic Acid for Intracerebral Hemorrhage in Patients on Non-Vitamin K Antagonist Oral Anticoagulants (TICH-NOAC): A Multicenter, Randomized, Placebo-Controlled, Phase 2 Trial.

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    BACKGROUND Evidence-based hemostatic treatment for intracerebral hemorrhage (ICH) associated with non-vitamin K antagonist oral anticoagulants (NOACs) is lacking. Tranexamic acid (TXA) is an antifibrinolytic drug potentially limiting hematoma expansion. We aimed to assess the efficacy and safety of TXA in NOAC-ICH. METHODS We performed a double-blind, randomized, placebo-controlled trial at 6 Swiss stroke centers. Patients with NOAC-ICH within 12 hours of symptom onset and 48 hours of last NOAC intake were randomized (1:1) to receive either intravenous TXA (1 g over 10 minutes followed by 1 g over 8 hours) or matching placebo in addition to standard medical care via a centralized Web-based procedure with minimization on key prognostic factors. All participants and investigators were masked to treatment allocation. Primary outcome was hematoma expansion, defined as ≥33% relative or ≥6 mL absolute volume increase at 24 hours and analyzed using logistic regression adjusted for baseline hematoma volume on an intention-to-treat basis. RESULTS Between December 12, 2016, and September 30, 2021, we randomized 63 patients (median age, 82 years [interquartile range, 76-86]; 40% women; median hematoma volume, 11.5 [4.8-27.4] mL) of the 109 intended sample size before premature trial discontinuation due to exhausted funding. The primary outcome did not differ between TXA (n=32) and placebo (n=31) arms (12 [38%] versus 14 [45%]; adjusted odds ratio, 0.63 [95% CI, 0.22-1.82]; P=0.40). There was a signal for interaction with onset-to-treatment time (Pinteraction=0.024), favoring TXA when administered within 6 hours of symptom onset. Between the TXA and placebo arms, the proportion of participants who died (15 [47%] versus 13 [42%]; adjusted odds ratio, 1.07 [0.37-3.04]; P=0.91) or had major thromboembolic complications within 90 days (4 [13%] versus 2 [6%]; odds ratio, 1.86 [0.37-9.50]; P=0.45) did not differ. All thromboembolic events occurred at least 2 weeks after study treatment, exclusively in participants not restarted on oral anticoagulation. CONCLUSIONS In a smaller-than-intended NOAC-ICH patient sample, we found no evidence that TXA prevents hematoma expansion, but there were no major safety concerns. Larger trials on hemostatic treatments targeting an early treatment window are needed for NOAC-ICH. REGISTRATION URL: https://clinicaltrials.gov; Unique identifier: NCT02866838

    Trauma management incorporating focused assessment with computed tomography in trauma (FACTT) - potential effect on survival

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    Background Immediate recognition of life-threatening conditions and injuries is the key to trauma management. To date, the impact of focused assessment with computed tomography in trauma (FACTT) has not been formally assessed. We aimed to find out whether the concept of using FACTT during primary trauma survey has a negative or positive effect on survival. Methods In a retrospective, multicentre study, we compared our time management and probability of survival (Ps) in major trauma patients who received FACTT during trauma resuscitation with the trauma registry of the German Trauma Society (DGU). FACTT is defined as whole-body computed tomography (WBCT) during primary trauma survey. We determined the probability of survival according to the Trauma and Injury Severity Score (TRISS), the Revised Injury Severity Classification score (RISC) and the standardized mortality ratio (SMR). Results We analysed 4.817 patients from the DGU database from 2002 until 2004, 160 (3.3%) were from our trauma centre at the Ludwig-Maximilians-University (LMU) and 4.657 (96.7%) from the DGU group. 73.2% were male with a mean age of 42.5 years, a mean ISS of 29.8. 96.2% had suffered from blunt trauma. Time from admission to FAST (focused assessment with sonography for trauma)(4.3 vs. 8.7 min), chest x-ray (8.1 vs. 16.0 min) and whole-body CT (20.7 vs. 36.6 min) was shorter at the LMU compared to the other trauma centres (p < 0.001). SMR calculated by TRISS was 0.74 (CI95% 0.40-1.08) for the LMU (p = 0.24) and 0.92 (CI95% 0.84-1.01) for the DGU group (p = 0.10). RISC methodology revealed a SMR of 0.69 (95%CI 0.47-0.92) for the LMU (p = 0.043) and 1.00 (95%CI 0.94-1.06) for the DGU group (p = 0.88). Conclusion Trauma management incorporating FACTT enhances a rapid response to life-threatening problems and enables a comprehensive assessment of the severity of each relevant injury. Due to its speed and accuracy, FACTT during primary trauma survey supports rapid decision-making and may increase survival

    A time-resolved proteomic and prognostic map of COVID-19

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    COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

    Cardiac magnetic resonance imaging parameters as surrogate endpoints in clinical trials of acute myocardial infarction

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    Cardiac magnetic resonance (CMR) offers a variety of parameters potentially suited as surrogate endpoints in clinical trials of acute myocardial infarction such as infarct size, myocardial salvage, microvascular obstruction or left ventricular volumes and ejection fraction. The present article reviews each of these parameters with regard to the pathophysiological basis, practical aspects, validity, reliability and its relative value (strengths and limitations) as compared to competitive modalities. Randomized controlled trials of acute myocardial infarction which have used CMR parameters as a primary endpoint are presented

    Genome-wide analysis identifies 12 loci influencing human reproductive behavior.

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    The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits

    Federated learning enables big data for rare cancer boundary detection.

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    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.

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    10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14
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