To the modification of methods of nuclear chronometry in astrophysics and geophysics

In practically all known till now methods of nuclear chronometry there were usually taken into account the life-times of only fundamental states of $\alpha$-radioactive nuclei. But in the processes of nuclear synthesis in stars and under the influence of the constant cosmic radiation on surfaces of planets the excitations of the $\alpha$-radioactive nuclei are going on. Between them there are the states with the excited $\alpha$-particles inside the parent nuclei and so with much smaller life-times. And inside the large masses of stellar, terrestrial and meteoric substances the transitions between different internal conditions of radioactive nuclei are accompanied by infinite chains of the $\gamma$-radiations with the subsequent $\gamma$-absorptions, the further $\gamma$-radiations etc. For the description of the $\alpha$-decay evolution with considering of such excited states and multiple $\gamma$-radiations and $\gamma$-absorptions inside stars and under the influence of the cosmic radiation on the earth surface we present the quantum-mechanical approach, which is based on the generalized Krylov-Fock theorem. Some simple estimations are also presented. They bring to the conclusion that the usual (non-corrected) "nuclear clocks" do really indicate not to realistic values but to the \emph{upper limits} of the durations of the $\alpha$-decay stellar and planet processes.Comment: 6 pages, Standard LaTeX v.2

Rapid detection of 2-hydroxyglutarate in frozen sections of IDH mutant tumors by MALDI-TOF mass spectrometry

All isocitrate dehydrogenase (IDH) mutant solid neoplasms exhibit highly elevated levels of D-2-hydroxyglutarate (D-2HG). Detection of 2HG in tumor tissues currently is performed by gas or liquid chromatography-mass spectrometry (GC- or LC-MS) or biochemical detection. While these methods are highly accurate, a considerable amount of time for tissue preparation and a relatively high amount of tissue is required for testing. We here present a rapid approach to detect 2HG in brain tumor tissue based on matrix-assisted laser desorption ionization - time of flight mass spectrometry (MALDI-TOF). We analyzed 26 brain tumor samples with known IDH1 or IDH2 mutation and compared readouts to those from 28 brain tumor samples of wildtype IDH status. IDH mutant samples exhibited a clear positive signal for 2HG which was not observed in any of the IDH wildtype tumors. Our analytical pipeline allowed for 2HG detection in less than 5 min. Data were validated by determining 2HG levels in all tissues with a biochemical assay. In conclusion, we developed a protocol for rapid detection of 2HG levels and illustrate the possibility to use MALDI-TOF for the detection of metabolites on frozen tissue sections in a diagnostic setting

Beta-delayed proton emission in the 100Sn region

Beta-delayed proton emission from nuclides in the neighborhood of 100Sn was studied at the National Superconducting Cyclotron Laboratory. The nuclei were produced by fragmentation of a 120 MeV/nucleon 112Sn primary beam on a Be target. Beam purification was provided by the A1900 Fragment Separator and the Radio Frequency Fragment Separator. The fragments of interest were identified and their decay was studied with the NSCL Beta Counting System (BCS) in conjunction with the Segmented Germanium Array (SeGA). The nuclei 96Cd, 98Ing, 98Inm and 99In were identified as beta-delayed proton emitters, with branching ratios bp = 5.5(40)%, 5.5+3 -2%, 19(2)% and 0.9(4)%, respectively. The bp for 89Ru, 91,92Rh, 93Pd and 95Ag were deduced for the first time with bp = 3+1.9 -1.7%, 1.3(5)%, 1.9(1)%, 7.5(5)% and 2.5(3)%, respectively. The bp = 22(1)% for 101Sn was deduced with higher precision than previously reported. The impact of the newly measured bp values on the composition of the type-I X-ray burst ashes was studied.Comment: 15 pages, 14 Figures, 4 Table

DNA methylation-based classification of central nervous system tumours.

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology

Specific substrate-driven changes in human faecal microbiota composition contrast with functional redundancy in short-chain fatty acid production

The Rowett Institute and Biomathematics & Statistics Scotland receive financial support from the Scottish Government Rural and Environmental Sciences and Analytical Services. Nicole Reichardt was funded by a Scottish Government Strategic Partnership on Food and Drink Science. We would like to thank Donna Henderson for carrying out GC analysis and Alan Walker for help and advice with bioinformatic sequence analysis. Supplementary information is available at ISME Journal’s website.Peer reviewedPostprin

Isomorphic diffuse glioma is a morphologically and molecularly distinct tumour entity with recurrent gene fusions of MYBL1 or MYB and a benign disease course

The “isomorphic subtype of diffuse astrocytoma” was identified histologically in 2004 as a supratentorial, highly differentiated glioma with low cellularity, low proliferation and focal diffuse brain infiltration. Patients typically had seizures since childhood and all were operated on as adults. To define the position of these lesions among brain tumours, we histologically, molecularly and clinically analysed 26 histologically prototypical isomorphic diffuse gliomas. Immunohistochemically, they were GFAP-positive, MAP2-, OLIG2- and CD34-negative, nuclear ATRX-expression was retained and proliferation was low. All 24 cases sequenced were IDH-wildtype. In cluster analyses of DNA methylation data, isomorphic diffuse gliomas formed a group clearly distinct from other glial/glio-neuronal brain tumours and normal hemispheric tissue, most closely related to paediatric MYB/MYBL1-altered diffuse astrocytomas and angiocentric gliomas. Half of the isomorphic diffuse gliomas had copy number alterations of MYBL1 or MYB (13/25, 52%). Gene fusions of MYBL1 or MYB with various gene partners were identified in 11/22 (50%) and were associated with an increased RNA-expression of the respective MYB-family gene. Integrating copy number alterations and available RNA sequencing data, 20/26 (77%) of isomorphic diffuse gliomas demonstrated MYBL1 (54%) or MYB (23%) alterations. Clinically, 89% of patients were seizure-free after surgery and all had a good outcome. In summary, we here define a distinct benign tumour class belonging to the family of MYB/MYBL1-altered gliomas. Isomorphic diffuse glioma occurs both in children and adults, has a concise morphology, frequent MYBL1 and MYB alterations and a specific DNA methylation profile. As an exclusively histological diagnosis may be very challenging and as paediatric MYB/MYBL1-altered diffuse astrocytomas may have the same gene fusions, we consider DNA methylation profiling very helpful for their identification

DNA methylation-based classification of sinonasal tumors

The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent potentially previously misclassified adenoid cystic carcinomas. Our findings can aid in improving the diagnostic classification of sinonasal tumors and could help to change the current perception of SNUCs