Traces of a prehistoric and potentially tsunamigenic mass movement in the sediments of Lake Thun (Switzerland).

Mass movements constitute major natural hazards in the Alpine realm. When triggered on slopes adjacent to lakes, these mass movements can generate tsunami-like waves that may cause additional damage along the shore. For hazard assessment, knowledge about the occurrence, the trigger and the geomechanical and hydrogeological mechanisms of these mass movements is necessary. For reconstructing mass movements that occurred in or adjacent to lakes, the lakes's sedimentary record can be used as an archive. Here, we present a prehistorical mass-movement event, of which the traces were found in an alpine lake, Lake Thun, in central Switzerland. The mass movement is identified by large blocks on the bathymetric map, a chaotic to transparent facies on the reflection seismic profiles, and by a mixture of deformed lake sediments and sandy organic-rich layers in the sediment-core record. The event is dated at 2642-2407 cal year BP. With an estimated volume of ~ 20 × 106 m3 it might have generated a wave with an initial amplitude of > 30 m. In addition to this prehistorical event, two younger deposits were identified in the sedimentary record. One could be dated at 1523-1361 cal year BP and thus can be potentially related to an event in 598/599 AD documented in historical reports. The youngest deposit is dated at 304-151 cal year BP (1646-1799 AD) and is interpreted to be related to the artificial Kander river deviation into Lake Thun (1714 AD). Supplementary Information The online version contains supplementary material available at 10.1186/s00015-022-00405-0

A modified theory of gravity with torsion and its applications to cosmology and particle physics

In this paper we consider the most general least-order derivative theory of gravity in which not only curvature but also torsion is explicitly present in the Lagrangian, and where all independent fields have their own coupling constant: we will apply this theory to the case of ELKO fields, which is the acronym of the German \textit{Eigenspinoren des LadungsKonjugationsOperators} designating eigenspinors of the charge conjugation operator, and thus they are a Majorana-like special type of spinors; and to the Dirac fields, the most general type of spinors. We shall see that because torsion has a coupling constant that is still undetermined, the ELKO and Dirac field equations are endowed with self-interactions whose coupling constant is undetermined: we discuss different applications according to the value of the coupling constants and the different properties that consequently follow. We highlight that in this approach, the ELKO and Dirac field's self-interactions depend on the coupling constant as a parameter that may even make these non-linearities manifest at subatomic scales.Comment: 21 page

Running coupling in electroweak interactions of leptons from f(R)-gravity with torsion

The f(R)-gravitational theory with torsion is considered for one family of leptons; it is found that the torsion tensor gives rise to interactions having the structure of the weak forces while the intrinsic non-linearity of the f(R) function provides an energy-dependent coupling: in this way, torsional f(R) gravity naturally generates both structure and strength of the electroweak interactions among leptons. This implies that the weak interactions among the lepton fields could be addressed as a geometric effect due to the interactions among spinors induced by the presence of torsion in the most general f(R) gravity. Phenomenological considerations are addressed.Comment: 9 pages. arXiv admin note: text overlap with arXiv:1012.5529 by other author

CD8 T-cell clones producing interleukin-5 and interferon-gamma in bronchial mucosa of patients with asthma induced by toluene diisocyanate

OBJECTIVES - The aims of the present study were to determine whether specific in vivo stimulation of asthmatics sensitized with toluene diisocyanate (TDI) induces the activation of T lymphocytes in bronchial mucosa and to characterize their phenotype and cytokine secretion profile.METHODS - Bronchial biopsies from two subjects with occupational asthma due to TDI were obtained 48 h after an asthmatic reaction induced by an inhalation challenge with TDI and after three months of no exposure to TDI, at the time when the subjects had recovered from their asthma. The fragments of bronchial mucosa were cultured in the presence of interleukin-2 so that the in vivo activated T cells present in the tissue would expand, and T blasts were then cloned under limiting dilution conditions.RESULTS - From the two 48-h specimens, 65 and 63 T-cell clones were obtained. Most of the clones exhibited the CD8 phenotype (82 and 83%). All of the CD8 clones produced interferon-gamma and 44% produced interleukin-5, but only 6% secreted interleukin-4 as well. Three months after the cessation of exposure, growing T cells could not be recovered from bronchial biopsies cultured in interleukin-2.CONCLUSIONS - The results suggest that, in sensitized subjects, exposure to TDI induces the activation of a subset of CD8 lymphocytes producing interferon-gamma and interleukin-5

Postglacial evolution of Lake Constance: sedimentological and geochemical evidence from a deep-basin sediment core

The modern, over 250-m-deep basin of Lake Constance represents the underfilled northern part of an over 400-m-deep, glacially overdeepened trough, which reaches well into the Alps at its southern end. The overdeep- ening was formed by repeated glacial advance-retreat cycles of the Rhine Glacier throughout the Middle to Late Pleistocene. A seismic survey of Lake Constance revealed a Quaternary sediment fill of more than 150 m thickness representing at least the last glacial cycle. The stratified sedimentary fill consists at the base of ice-contact deposits on top of the molasse bedrock, overlain by glaciolacustrine to lacustrine sediments. During the successful field test of a newly developed, mid-size coring system ("HIPERCORIG"), the longest core (HIBO19) ever taken in Lake Constance was retrieved with an overall length of 24 m. The sediments recovered consist of a nearly continuous succession of lacustrine silts and sands including more than 12 m of Late Glacial sediment at the base. 14 lithotypes were identified through petrophysical and geochemical analyses. In combination with a 14C- and OSL-based age-depth model, the core was divided into three main chronostratigraphic units. The basal age of ~ 13.7 ka BP dates the base of the succes- sion back to the Bølling-Allerød interstadial, with overlying strata representing a complete and thick Younger-Dryas to Holocene succession. The sediments offer a high-resolution insight into the evolution of paleo-Lake Constance from a cold, postglacial to a more productive and warmer Holocene lake. The Late Glacial succession is dominated by massive, m-thick sand beds reflecting episodic sedimentation pulses. They are most likely linked to a subaquatic channel system originating in the river Seefelder Aach, which is, despite the Holocene drape, still apparent in today’s lake bathymetry. The overlying Holocene succession reveals a prominent, several cm-thick, double-turbiditic event layer representing the most distal impact of the Flimser Bergsturz, the largest known rockslide of the Alps that occurred over 100 km upstream the river Rhine at ~ 9.5 ka BP. Furthermore, lithologic variations in the Holocene succession document the varying sediment loads of the river Rhine and the endogenic production representing a multitude of environmental changes

On the viability of regular black holes

The evaporation of black holes raises a number of conceptual issues, most of them related to the final stages of evaporation, where the interplay between the central singularity and Hawking radiation cannot be ignored. Regular models of black holes replace the central singularity with a nonsingular spacetime region, in which an effective classical geometric description is available. It has been argued that these models provide an effective, but complete, description of the evaporation of black holes at all times up to their eventual disappearance. However, here we point out that known models fail to be self-consistent: the regular core is exponentially unstable against perturbations with a finite timescale, while the evaporation time is infinite, therefore making the instability impossible to prevent. We also discuss how to overcome these difficulties, highlighting that this can be done only at the price of accepting that these models cannot be fully predictive regarding the final stages of evaporation

MicroRNAs targeting oncogenes are down-regulated in pancreatic malignant transformation from benign tumors

BACKGROUND MicroRNA (miRNA) expression profiles have been described in pancreatic ductal adenocarcinoma (PDAC), but these have not been compared with pre-malignant pancreatic tumors. We wished to compare the miRNA expression signatures in pancreatic benign cystic tumors (BCT) of low and high malignant potential with PDAC, in order to identify miRNAs deregulated during PDAC development. The mechanistic consequences of miRNA dysregulation were further evaluated. METHODS Tissue samples were obtained at a tertiary pancreatic unit from individuals with BCT and PDAC. MiRNA profiling was performed using a custom microarray and results were validated using RT-qPCR prior to evaluation of miRNA targets. RESULTS Widespread miRNA down-regulation was observed in PDAC compared to low malignant potential BCT. We show that amongst those miRNAs down-regulated, miR-16, miR-126 and let-7d regulate known PDAC oncogenes (targeting BCL2, CRK and KRAS respectively). Notably, miR-126 also directly targets the KRAS transcript at a "seedless" binding site within its 3'UTR. In clinical specimens, miR-126 was strongly down-regulated in PDAC tissues, with an associated elevation in KRAS and CRK proteins. Furthermore, miR-21, a known oncogenic miRNA in pancreatic and other cancers, was not elevated in PDAC compared to serous microcystic adenoma (SMCA), but in both groups it was up-regulated compared to normal pancreas, implicating early up-regulation during malignant change. CONCLUSIONS Expression profiling revealed 21 miRNAs down-regulated in PDAC compared to SMCA, the most benign lesion that rarely progresses to invasive carcinoma. It appears that miR-21 up-regulation is an early event in the transformation from normal pancreatic tissue. MiRNA expression has the potential to distinguish PDAC from normal pancreas and BCT. Mechanistically the down-regulation of miR-16, miR-126 and let-7d promotes PDAC transformation by post-transcriptional up-regulation of crucial PDAC oncogenes. We show that miR-126 is able to directly target KRAS; re-expression has the potential as a therapeutic strategy against PDAC and other KRAS-driven cancers

A Clinical Prognostic Model Based on Machine Learning from the Fondazione Italiana Linfomi (FIL) MCL0208 Phase III Trial

BACKGROUND Multicenter clinical trials are producing growing amounts of clinical data. Machine Learning (ML) might facilitate the discovery of novel tools for prognostication and disease-stratification. Taking advantage of a systematic collection of multiple variables, we developed a model derived from data collected on 300 patients with mantle cell lymphoma (MCL) from the Fondazione Italiana Linfomi-MCL0208 phase III trial (NCT02354313). METHODS We developed a score with a clustering algorithm applied to clinical variables. The candidate score was correlated to overall survival (OS) and validated in two independent data series from the European MCL Network (NCT00209222, NCT00209209); Results: Three groups of patients were significantly discriminated: Low, Intermediate (Int), and High risk (High). Seven discriminants were identified by a feature reduction approach: albumin, Ki-67, lactate dehydrogenase, lymphocytes, platelets, bone marrow infiltration, and B-symptoms. Accordingly, patients in the Int and High groups had shorter OS rates than those in the Low and Int groups, respectively (Int→Low, HR: 3.1, 95% CI: 1.0-9.6; High→Int, HR: 2.3, 95% CI: 1.5-4.7). Based on the 7 markers, we defined the engineered MCL international prognostic index (eMIPI), which was validated and confirmed in two independent cohorts; Conclusions: We developed and validated a ML-based prognostic model for MCL. Even when currently limited to baseline predictors, our approach has high scalability potential

A Clinical Prognostic Model Based on Machine Learning from the Fondazione Italiana Linfomi (FIL) MCL0208 Phase III Trial

SIMPLE SUMMARY: The interest in using Machine-Learning (ML) techniques in clinical research is growing. We applied ML to build up a novel prognostic model from patients affected with Mantle Cell Lymphoma (MCL) enrolled in a phase III open-labeled, randomized clinical trial from the Fondazione Italiana Linfomi (FIL)—MCL0208. This is the first application of ML in a prospective clinical trial on MCL lymphoma. We applied a novel ML pipeline to a large cohort of patients for which several clinical variables have been collected at baseline, and assessed their prognostic value based on overall survival. We validated it on two independent data series provided by European MCL Network. Due to its flexibility, we believe that ML would be of tremendous help in the development of a novel MCL prognostic score aimed at re-defining risk stratification. ABSTRACT: Background: Multicenter clinical trials are producing growing amounts of clinical data. Machine Learning (ML) might facilitate the discovery of novel tools for prognostication and disease-stratification. Taking advantage of a systematic collection of multiple variables, we developed a model derived from data collected on 300 patients with mantle cell lymphoma (MCL) from the Fondazione Italiana Linfomi-MCL0208 phase III trial (NCT02354313). Methods: We developed a score with a clustering algorithm applied to clinical variables. The candidate score was correlated to overall survival (OS) and validated in two independent data series from the European MCL Network (NCT00209222, NCT00209209); Results: Three groups of patients were significantly discriminated: Low, Intermediate (Int), and High risk (High). Seven discriminants were identified by a feature reduction approach: albumin, Ki-67, lactate dehydrogenase, lymphocytes, platelets, bone marrow infiltration, and B-symptoms. Accordingly, patients in the Int and High groups had shorter OS rates than those in the Low and Int groups, respectively (Int→Low, HR: 3.1, 95% CI: 1.0–9.6; High→Int, HR: 2.3, 95% CI: 1.5–4.7). Based on the 7 markers, we defined the engineered MCL international prognostic index (eMIPI), which was validated and confirmed in two independent cohorts; Conclusions: We developed and validated a ML-based prognostic model for MCL. Even when currently limited to baseline predictors, our approach has high scalability potential

Standalone vertex finding in the ATLAS muon spectrometer

A dedicated reconstruction algorithm to find decay vertices in the ATLAS muon spectrometer is presented. The algorithm searches the region just upstream of or inside the muon spectrometer volume for multi-particle vertices that originate from the decay of particles with long decay paths. The performance of the algorithm is evaluated using both a sample of simulated Higgs boson events, in which the Higgs boson decays to long-lived neutral particles that in turn decay to bbar b final states, and pp collision data at √s = 7 TeV collected with the ATLAS detector at the LHC during 2011