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Stratospheric inorganic chlorine (Cly) is predominantly released from long-lived chlorinated source gases and, to a small extent, very short-lived chlorinated substances. Cly includes the reservoir species (HCl and ClONO2) and active chlorine species (i.e., ClOx). The active chlorine species drive catalytic cycles that deplete ozone in the polar winter stratosphere. This work presents calculations of inorganic chlorine (Cly) derived from chlorinated source gas measurements on board the High Altitude and Long Range Research Aircraft (HALO) during the Southern Hemisphere Transport, Dynamic and Chemistry (SouthTRAC) campaign in austral late winter and early spring 2019. Results are compared to Cly in the Northern Hemisphere derived from measurements of the POLSTRACC-GW-LCYCLE-SALSA (PGS) campaign in the Arctic winter of 2015/2016. A scaled correlation was used for PGS data, since not all source gases were measured. Using the SouthTRAC data, Cly from a scaled correlation was compared to directly determined Cly and agreed well. An air mass classification based on in situ N2O measurements allocates the measurements to the vortex, the vortex boundary region, and midlatitudes. Although the Antarctic vortex was weakened in 2019 compared to previous years, Cly reached 1687±19 ppt at 385 K; therefore, up to around 50 % of total chlorine was found in inorganic form inside the Antarctic vortex, whereas only 15 % of total chlorine was found in inorganic form in the southern midlatitudes. In contrast, only 40 % of total chlorine was found in inorganic form in the Arctic vortex during PGS, and roughly 20 % was found in inorganic form in the northern midlatitudes. Differences inside the two vortices reach as much as 540 ppt, with more Cly in the Antarctic vortex in 2019 than in the Arctic vortex in 2016 (at comparable distance to the local tropopause). To our knowledge, this is the first comparison of inorganic chlorine within the Antarctic and Arctic polar vortices. Based on the results of these two campaigns, the differences in Cly inside the two vortices are substantial and larger than the inter-annual variations previously reported for the Antarctic.
Rationale and objectives: To provide a detailed analysis of injury patterns of the spine following blunt trauma and establish the role of supplementary MRI by evaluating discrepancies in the detection rates of damaged structures in CT and MRI.
Method: 216 patients with blunt trauma to the spine who underwent CT followed by supplementary MRI were included in this study. Two board-certified radiologists blinded to clinical symptoms and injury mechanisms independently interpreted all acquired CT and MRI images. The interpretation was performed using a dedicated catalogue of typical findings associated with spinal trauma and assessed for spinal stability using the AO classification systems.
Results: Lesions to structures associated with spinal instability were present in 31.0% in the cervical spine, 12.3% in the thoracic spine, and 29.9% in the lumbar spine. In all spinal segments, MRI provided additional information regarding potentially unstable injuries. Novel information derived from supplementary MRI changed clinical management in 3.6% of patients with injury to the cervical spine. No change in clinical management resulted from novel information on the thoracolumbar spine. Patients with injuries to the vertebral body, intervertebral disc, or spinous process were significantly more likely to benefit from supplementary MRI.
Conclusion: In patients that sustained blunt spinal trauma, supplementary MRI of the cervical spine should routinely be performed to detect injuries that require surgical treatment, whereas CT is the superior imaging modality for the detection of unstable injuries in the thoracolumbar spine.
A prototype of a new type of calorimeter has been designed and constructed, based on a silicon-tungsten sampling design using pixel sensors with digital readout. It makes use of the Alpide MAPS sensor developed for the ALICE ITS upgrade. A binary readout is possible due to the pixel size of ≈30×30μm2. This prototype has been successfully tested with cosmic muons and with test beams at DESY and the CERN SPS. We report on performance results obtained at DESY, showing good energy resolution and linearity, and compare to detailed MC simulations. Also shown are preliminary results of the high-energy performance as measured at the SPS. The two-shower separation capabilities are discussed.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The expanding field of epitranscriptomics might rival the epigenome in the diversity of the biological processes impacted. However, the identification of modifications in individual RNA molecules remains challenging. We present CHEUI, a new method that detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) at single-nucleotide and single-molecule resolution from Nanopore signals. CHEUI predicts methylation in Nanopore reads and transcriptomic sites in a single condition, and differential m6A and m5C methylation between any two conditions. Using extensive benchmarking with Nanopore data derived from synthetic and natural RNA, CHEUI showed higher accuracy than other existing methods in detecting m6A and m5C sites and quantifying the site stoichiometry levels, while maintaining a lower proportion of false positives. CHEUI provides a new capability to detect RNA modifications with high accuracy and resolution that can be cost-effectively expanded to other modifications to unveil the full span of the epitranscriptome in normal and disease conditions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions, using signals from nanopore direct RNA sequencing. CHEUI processes observed and expected signals with convolutional neural networks to achieve high single-molecule accuracy and outperform other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
Stratospheric inorganic chlorine (Cly) is predominantly released from long-lived chlorinated source gases and, to a small extent, very short-lived chlorinated substances. Cly includes the reservoir species (HCl and ClONO2) and active chlorine species (i.e., ClOx). The active chlorine species drive catalytic cycles that deplete ozone in the polar winter stratosphere. This work presents calculations of inorganic chlorine (Cly) derived from chlorinated source gas measurements on board the High Altitude and Long Range Research Aircraft (HALO) during the Southern Hemisphere Transport, Dynamic and Chemistry (SouthTRAC) campaign in austral late winter and early spring 2019. Results are compared to Cly in the Northern Hemisphere derived from measurements of the POLSTRACC-GW-LCYCLE-SALSA (PGS) campaign in the Arctic winter of 2015/2016. A scaled correlation was used for PGS data, since not all source gases were measured. Using the SouthTRAC data, Cly from a scaled correlation was compared to directly determined Cly and agreed well. An air mass classification based on in situ N2O measurements allocates the measurements to the vortex, the vortex boundary region, and midlatitudes. Although the Antarctic vortex was weakened in 2019 compared to previous years, Cly reached 1687±19 ppt at 385 K; therefore, up to around 50 % of total chlorine was found in inorganic form inside the Antarctic vortex, whereas only 15 % of total chlorine was found in inorganic form in the southern midlatitudes. In contrast, only 40 % of total chlorine was found in inorganic form in the Arctic vortex during PGS, and roughly 20 % was found in inorganic form in the northern midlatitudes. Differences inside the two vortices reach as much as 540 ppt, with more Cly in the Antarctic vortex in 2019 than in the Arctic vortex in 2016 (at comparable distance to the local tropopause). To our knowledge, this is the first comparison of inorganic chlorine within the Antarctic and Arctic polar vortices. Based on the results of these two campaigns, the differences in Cly inside the two vortices are substantial and larger than the inter-annual variations previously reported for the Antarctic.
Epigenetic neural glioblastoma enhances synaptic integration and predicts therapeutic vulnerability
(2023)
Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is nascent. We present an epigenetically defined neural signature of glioblastoma that independently affects patients survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals high abundance of stem cell-like malignant cells classified as oligodendrocyte precursor and neural precursor cell-like in high-neural glioblastoma. High-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature associates with decreased survival as well as increased functional connectivity and can be detected via DNA analytes and brain-derived neurotrophic factor in plasma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant.
We present data on charged kaons (K±) and ϕ mesons in Au(1.23A GeV)+Au collisions. It is the first simultaneous measurement of K− and ϕ mesons in central heavy-ion collisions below a kinetic beam energy of 10A GeV. The ϕ/K− multiplicity ratio is found to be surprisingly high with a value of 0.52±0.16 and shows no dependence on the centrality of the collision. Consequently, the different slopes of the K+ and K− transverse-mass spectra can be explained solely by feed-down, which substantially softens the spectra of K− mesons. Hence, in contrast to the commonly adapted argumentation in literature, the different slopes do not necessarily imply diverging freeze-out temperatures of K+ and K− mesons caused by different couplings to baryons.
New results on the differential cross section in deuteron-proton elastic scattering are obtained at the deuteron kinetic energy of 2.5 GeV with the HADES spectrometer. The angular range of 69° – 125° in the center of mass system is covered. The obtained results are compared with the relativistic multiple scattering model calculation using the CD-Bonn deuteron wave function. The data at fixed scattering angles in the c.m. are in qualitative agreement with the constituent counting rules prediction.
A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative ‘Connect to Decode’ (C2D) to generate the first and largest manually curated interactome of Mtb termed ‘interactome pathway’ (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.