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Fluid intelligence is the ability to think flexibly and to understand abstract relations. People with high fluid intelligence (hi-fluIQ) perform better in analogical reasoning tasks than people with average fluid intelligence (ave-fluIQ). Although previous neuroimaging studies reported involvement of parietal and frontal brain regions in geometric analogical reasoning (which is a prototypical task for fluid intelligence), however, neuroimaging findings on geometric analogical reasoning in hi-fluIQ are sparse. Furthermore, evidence on the relation between brain activation and intelligence while solving cognitive tasks is contradictory. The present study was designed to elucidate the cerebral correlates of geometric analogical reasoning in a sample of hi-fluIQ and ave-fluIQ high school students. We employed a geometric analogical reasoning task with graded levels of task difficulty and confirmed the involvement of the parieto-frontal network in solving this task. In addition to characterizing the brain regions involved in geometric analogical reasoning in hi-fluIQ and ave-fluIQ, we found that blood oxygenation level dependency (BOLD) signal changes were greater for hi-fluIQ than for ave-fluIQ in parietal brain regions. However, ave-fluIQ showed greater BOLD signal changes in the anterior cingulate cortex and medial frontal gyrus than hi-fluIQ. Thus, we showed that a similar network of brain regions is involved in geometric analogical reasoning in both groups. Interestingly, the relation between brain activation and intelligence is not mono-directional, but rather, it is specific for each brain region. The negative brain activation-intelligence relationship in frontal brain regions in hi-fluIQ goes along with a better behavioral performance and reflects a lower demand for executive monitoring compared to ave-fluIQ individuals. In conclusion, our data indicate that flexibly modulating the extent of regional cerebral activity is characteristic for fluid intelligence.
MALDI-TOF-MS-based identification of monoclonal murine Anti-SARS-CoV-2 antibodies within one hour
(2022)
During the SARS-CoV-2 pandemic, many virus-binding monoclonal antibodies have been developed for clinical and diagnostic purposes. This underlines the importance of antibodies as universal bioanalytical reagents. However, little attention is given to the reproducibility crisis that scientific studies are still facing to date. In a recent study, not even half of all research antibodies mentioned in publications could be identified at all. This should spark more efforts in the search for practical solutions for the traceability of antibodies. For this purpose, we used 35 monoclonal antibodies against SARS-CoV-2 to demonstrate how sequence-independent antibody identification can be achieved by simple means applied to the protein. First, we examined the intact and light chain masses of the antibodies relative to the reference material NIST-mAb 8671. Already half of the antibodies could be identified based solely on these two parameters. In addition, we developed two complementary peptide mass fingerprinting methods with MALDI-TOF-MS that can be performed in 60 min and had a combined sequence coverage of over 80%. One method is based on the partial acidic hydrolysis of the protein by 5 mM of sulfuric acid at 99 degrees C. Furthermore, we established a fast way for a tryptic digest without an alkylation step. We were able to show that the distinction of clones is possible simply by a brief visual comparison of the mass spectra. In this work, two clones originating from the same immunization gave the same fingerprints. Later, a hybridoma sequencing confirmed the sequence identity of these sister clones. In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0. This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.
The northward movement and collision of the Arabian plate with Eurasia generates compressive stresses and resulting shortening in Iran. Within the Alborz Mountains, North Iran, a complex and not well understood system of strike-slip and thrust faults accomodates a fundamental part of the NNE-SSW oriented shortening. On 28th of May 2004 the Mw 6.3 Baladeh earthquake hit the north-central Alborz Mountains. It is one of the rare and large events in this region in modern time and thus a seldom chance to study earthquake mechanisms and the local ongoing deformation processes. It also demonstrated the high vulnerability of this densily populated region.
The M (w) 6.2 Baladeh earthquake occurred on 28 May 2004 in the Alborz Mountains, northern Iran. This earthquake was the first strong shock in this intracontinental orogen for which digital regional broadband data are available. The Baladeh event provides a rare opportunity to study fault geometry and ongoing deformation processes using modern seismological methods. A joint inversion for hypocentres and a velocity model plus a surface-wave group dispersion curve analysis were used to obtain an adapted velocity model, customised for mid- and long-period waveform modelling. Based on the new velocity model, regional waveform data of the mainshock and larger aftershocks (M (w) a parts per thousand yen3.3) were inverted for moment tensors. For the Baladeh mainshock, this included inversion for kinematic parameters. All analysed earthquakes show dominant thrust mechanisms at depths between 14 and 26 km, with NW-SE striking fault planes. The mainshock ruptured a 28A degrees south-dipping area of 24 x 21 km along a north-easterly direction. The rupture plane of the mainshock does not coincide with the aftershock distribution, neither in map view nor with respect to depth. The considered aftershocks form two main clusters. The eastern cluster is associated with the mainshock. The western cluster does not appear to be connected with the rupture plane of the mainshock but, instead, indicates a second activated fault plane dipping at 85A degrees towards the north.
The complex system of strike-slip and thrust faults in the Alborz Mountains, Northern Iran, are not well understood yet. Mainly structural and geomorphic data are available so far. As a more extensive base for seismotectonic studies and seismic hazard analysis we plan to do a comprehensive seismic moment tensor study also from smaller magnitudes (M < 4.5) by developing a new algorithm. Here, we present first preliminary results.
Volcano-seismic signals such as long-period events and tremor are important indicators for volcanic activity and unrest. However, their wavefield is complex and characterization and location using traditional seismological instrumentation is often difficult.
In 2019 we recorded the full seismic wavefield using a newly developed 3C rotational sensor co-located with a 3C traditional seismometer on Etna, Italy. We compare the performance of the rotational sensor, the seismometer and the Istituto Nazionale di Geofisica e Vulcanologia-Osservatorio Etneo (INGV-OE) seismic network with respect to the analysis of complex volcano-seismic signals. We create event catalogs for volcano-tectonic (VT) and long-period (LP) events combining a STA/LTA algorithm and cross-correlations.
The event detection based on the rotational sensor is as reliable as the seismometer-based detection. The LP events are dominated by SH-type waves. Derived SH phase velocities range from 500 to 1,000 m/s for LP events and 300-400 m/s for volcanic tremor. SH-waves compose the tremor during weak volcanic activity and SH- and SV-waves during sustained strombolian activity.
We derive back azimuths using (a) horizontal rotational components and (b) vertical rotation rate and transverse acceleration. The estimated back azimuths are consistent with the INGV-OE event location for (a) VT events with an epicentral distance larger than 3 km and some closer events, (b) LP events and tremor in the main crater area. Measuring the full wavefield we can reliably analyze the back azimuths, phase velocities and wavefield composition for VT, LP events and tremor in regions that are difficult to access such as volcanoes.
The inner region of the Milky Way halo harbors a large amount of dark matter (DM). Given its proximity, it is one of the most promising targets to look for DM. We report on a search for the annihilations of DM particles using gamma-ray observations towards the inner 300 pc of the Milky Way, with the H.E.S.S. array of ground-based Cherenkov telescopes. The analysis is based on a 2D maximum likelihood method using Galactic Center (GC) data accumulated by H.E.S.S. over the last 10 years (2004-2014), and does not show any significant gamma-ray signal above background. Assuming Einasto and Navarro-Frenk-White DM density profiles at the GC, we derive upper limits on the annihilation cross section <sigma nu >. These constraints are the strongest obtained so far in the TeV DM mass range and improve upon previous limits by a factor 5. For the Einasto profile, the constraints reach <sigma nu > values of 6 x 10(-26) cm(3) s(-1) in the W+W- channel for a DM particle mass of 1.5 TeV, and 2 x 10(-26) cm(3) s(-1) in the tau(+)tau(-) channel for a 1 TeV mass. For the first time, ground-based gamma-ray observations have reached sufficient sensitivity to probe <sigma nu > values expected from the thermal relic density for TeV DM particles.
Earthquakes often rupture across more than one fault segment. If such rupture segmentation occurs on a significant scale, a simple point-source or one-fault model may not represent the rupture process well. As a consequence earthquake characteristics inferred, based on one-source assumptions, may become systematically wrong. This might have effects on follow-up analyses, for example regional stress field inversions and seismic hazard assessments. While rupture segmentation is evident for most M-w > 7 earthquakes, also smaller ones with 5.5 < M-w < 7 can be segmented. We investigate the sensitivity of globally available data sets to rupture segmentation and their resolution to reliably estimate the mechanisms in presence of segmentation. We focus on the sensitivity of InSAR (Interferometric Synthetic Aperture Radar) data in the static near-field and seismic waveforms in the far-field of the rupture and carry out non-linear and Bayesian optimizations of single-source and two-sources kinematic models (double-couple point sources and finite, rectangular sources) using InSAR and teleseismic waveforms separately. Our case studies comprises of four M-w 6-7 earthquakes: the 2009 L'Aquila and 2016 Amatrice (Italy) and the 2005 and 2008 Zhongba (Tibet) earthquakes. We contrast the data misfits of different source complexity by using the Akaike informational criterion (AIC). We find that the AIC method is well suited for data-driven inferences on significant rupture segmentation for the given data sets. This is based on our observation that an AIC-stated significant improvement of data fit for two-segment models over one-segment models correlates with significantly different mechanisms of the two source segments and their average compared to the single-segment mechanism. We attribute these modelled differences to a sufficient sensitivity of the data to resolve rupture segmentation. Our results show that near-field data are generally more sensitive to rupture segmentation of shallow earthquakes than far-field data but that also teleseismic data can resolve rupture segmentation in the studied magnitude range. We further conclude that a significant difference in the modelled source mechanisms for different segmentations shows that an appropriate choice of model segmentation matters for a robust estimation of source mechanisms. It reduces systematic biases and trade-off and thereby improves the knowledge on the rupture. Our study presents a strategy and method to detect significant rupture segmentation such that an appropriate model complexity can be used in the source mechanism inference. A similar, systematic investigation of earthquakes in the range of M-w 5.5-7 could provide important hazard-relevant statistics on rupture segmentation. In these cases single-source models introduce a systematic bias. Consideration of rupture segmentation therefore matters for a robust estimation of source mechanisms of the studied earthquakes.