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Aims: The examination of histological sections is still the gold standard in diagnostic pathology. Important histopathological diagnostic criteria are nuclear shapes and chromatin distribution as well as nucleus-cytoplasm relation and immunohistochemical properties of surface and intracellular proteins. The aim of this investigation was to evaluate the benefits and drawbacks of three-dimensional imaging of CD30+ cells in classical Hodgkin Lymphoma (cHL) in comparison to CD30+ lymphoid cells in reactive lymphoid tissues.
Materials and results: Using immunoflourescence confocal microscopy and computer-based analysis, we compared CD30+ neoplastic cells in Nodular Sclerosis cHL (NScCHL), Mixed Cellularity cHL (MCcHL), with reactive CD30+ cells in Adenoids (AD) and Lymphadenitis (LAD). We confirmed that the percentage of CD30+ cell volume can be calculated. The amount in lymphadenitis was approx. 1.5%, in adenoids around 2%, in MCcHL up to 4,5% whereas the values for NScHL rose to more than 8% of the total cell cytoplasm. In addition, CD30+ tumour cells (HRS-cells) in cHL had larger volumes, and more protrusions compared to CD30+ reactive cells. Furthermore, the formation of large cell networks turned out to be a typical characteristic of NScHL.
Conclusion: In contrast to 2D histology, 3D laser scanning offers a visualisation of complete cells, their network interaction and spatial distribution in the tissue. The possibility to differentiate cells in regards to volume, surface, shape, and cluster formation enables a new view on further diagnostic and biological questions. 3D includes an increased amount of information as a basis of bioinformatical calculations.
The coordinate and momentum space configurations of the net baryon number in heavy ion collisions that undergo spinodal decomposition, due to a first-order phase transition, are investigated using state-of-the-art machine-learning methods. Coordinate space clumping, which appears in the spinodal decomposition, leaves strong characteristic imprints on the spatial net density distribution in nearly every event which can be detected by modern machine learning techniques. On the other hand, the corresponding features in the momentum distributions cannot clearly be detected, by the same machine learning methods, in individual events. Only a small subset of events can be systematically differ- entiated if only the momentum space information is available. This is due to the strong similarity of the two event classes, with and without spinodal decomposition. In such sce- narios, conventional event-averaged observables like the baryon number cumulants signal a spinodal non-equilibrium phase transition. Indeed the third-order cumulant, the skewness, does exhibit a peak at the beam energy (Elab = 3–4 A GeV), where the transient hot and dense system created in the heavy ion collision reaches the first-order phase transition.
Following a brief review of current efforts to identify the neuronal correlates of conscious processing (NCCP) an attempt is made to bridge the gap between the material neuronal processes and the immaterial dimensions of subjective experience. It is argued that this "hard problem" of consciousness research cannot be solved by only considering the neuronal underpinnings of cognition. The proposal is that the hard problem can be treated within a naturalistic framework if one considers not only the biological but also the socio-cultural dimensions of evolution. The argument is based on the following premises: perceptions are the result of a constructivist process that depends on priors. This applies both for perceptions of the outer world and the perception of oneself. Social interactions between agents endowed with the cognitive abilities of humans generated immaterial realities, addressed as social or cultural realities. This novel class of realities assumed the role of priors for the perception of oneself and the embedding world. A natural consequence of these extended perceptions is a dualist classification of observables into material and immaterial phenomena nurturing the concept of ontological substance dualism. It is argued that perceptions shaped by socio-cultural priors lead to the construction of a self-model that has both a material and an immaterial dimension. As priors are implicit and not amenable to conscious recollection the perceived immaterial dimension is experienced as veridical and not derivable from material processes—which is the hallmark of the hard problem. These considerations let the hard problem appear as the result of cognitive constructs that are amenable to naturalistic explanations in an evolutionary framework.
Adjuvanted influenza vaccines constitute a key element towards inducing neutralizing antibody responses in populations with reduced responsiveness, such as infants and elderly subjects, as well as in devising antigen-sparing strategies. In particular, squalene-containing adjuvants have been observed to induce enhanced antibody responses, as well as having an influence on cross-reactive immunity. To explore the effects of adjuvanted vaccine formulations on antibody response and their relation to protein-specific immunity, we propose different mathematical models of antibody production dynamics in response to influenza vaccination. Data from ferrets immunized with commercial H1N1pdm09 vaccine antigen alone or formulated with different adjuvants was instrumental to adjust model parameters. While the affinity maturation process complexity is abridged, the proposed model is able to recapitulate the essential features of the observed dynamics. Our numerical results suggest that there exists a qualitative shift in protein-specific antibody response, with enhanced production of antibodies targeting the NA protein in adjuvanted versus non-adjuvanted formulations, in conjunction with a protein-independent boost that is over one order of magnitude larger for squalene-containing adjuvants. Furthermore, simulations predict that vaccines formulated with squalene-containing adjuvants are able to induce sustained antibody titers in a robust way, with little impact of the time interval between immunizations.
Charged-particle spectra at midrapidity are measured in Pb–Pb collisions at the centre-of-mass energy per nucleon–nucleon pair √sNN = 5.02 TeV and presented in centrality classes ranging from most central (0–5%) to most peripheral (95–100%) collisions. Possible medium effects are quantified using the nuclear modification factor (RAA) by comparing the measured spectra with those from proton–proton collisions, scaled by the number of independent nucleon–nucleon collisions obtained from a Glauber model. At large transverse momenta (8 < pT < 20 GeV/c), the average RAA is found to increase from about 0.15 in 0–5% central to a maximum value of about 0.8 in 75–85% peripheral collisions, beyond which it falls off strongly to below 0.2 for the most peripheral collisions. Furthermore, RAA initially exhibits a positive slope as a function of pT in the 8–20 GeV/c interval, while for collisions beyond the 80% class the slope is negative. To reduce uncertainties related to event selection and normalization, we also provide the ratio of RAA in adjacent centrality intervals. Our results in peripheral collisions are consistent with a PYTHIA-based model without nuclear modification, demonstrating that biases caused by the event selection and collision geometry can lead to the apparent suppression in peripheral collisions. This explains the unintuitive observation that RAA is below unity in peripheral Pb–Pb, but equal to unity in minimum-bias p–Pb collisions despite similar charged-particle multiplicities.
We present a model for the autonomous and simultaneous learning of active binocular and motion vision. The model is based on the Active Efficient Coding (AEC) framework, a recent generalization of classic efficient coding theories to active perception. The model learns how to efficiently encode the incoming visual signals generated by an object moving in 3-D through sparse coding. Simultaneously, it learns how to produce eye movements that further improve the efficiency of the sensory coding. This learning is driven by an intrinsic motivation to maximize the system's coding efficiency. We test our approach on the humanoid robot iCub using simulations. The model demonstrates self-calibration of accurate object fixation and tracking of moving objects. Our results show that the model keeps improving until it hits physical constraints such as camera or motor resolution, or limits on its internal coding capacity. Furthermore, we show that the emerging sensory tuning properties are in line with results on disparity, motion, and motion-in-depth tuning in the visual cortex of mammals. The model suggests that vergence and tracking eye movements can be viewed as fundamentally having the same objective of maximizing the coding efficiency of the visual system and that they can be learned and calibrated jointly through AEC.
Angular correlations between heavy-flavour decay electrons and charged particles at mid-rapidity (|η|<0.8) are measured in p-Pb collisions at sNN−−−√ = 5.02 TeV. The analysis is carried out for the 0-20% (high) and 60-100% (low) multiplicity ranges. The jet contribution in the correlation distribution from high-multiplicity events is removed by subtracting the distribution from low-multiplicity events. An azimuthal modulation remains after removing the jet contribution, similar to previous observations in two-particle angular correlation measurements for light-flavour hadrons. A Fourier decomposition of the modulation results in a positive second-order coefficient (v2) for heavy-flavour decay electrons in the transverse momentum interval 1.5<pT<4 GeV/c in high-multiplicity events, with a significance larger than 5σ. The results are compared with those of charged particles at mid-rapidity and of inclusive muons at forward rapidity. The v2 measurement of open heavy-flavour particles at mid-rapidity in small collision systems could provide crucial information to help interpret the anisotropies observed in such systems.
Bardeen black hole chemistry
(2019)
In the present paper we try to connect the Bardeen black hole with the concept of the recently proposed black hole chemistry. We study thermodynamic properties of the regular black hole with an anti-deSitter background. The negative cosmological constant Λ plays the role of the positive thermodynamic pressure of the system. After studying the thermodynamic variables, we derive the corresponding equation of state and we show that a neutral Bardeen-anti-deSitter black hole has similar phenomenology to the chemical Van der Waals fluid. This is equivalent to saying that the system exhibits criticality and a first order small/large black hole phase transition reminiscent of the liquid/gas coexistence.
The procedure for the energy calibration of the high granularity electromagnetic calorimeter PHOS of the ALICE experiment is presented. The methods used to perform the relative gain calibration, to evaluate the geometrical alignment and the corresponding correction of the absolute energy scale, to obtain the nonlinearity correction coefficients and finally, to calculate the time-dependent calibration corrections, are discussed and illustrated by the PHOS performance in proton-proton (pp) collisions at √s=13 TeV. After applying all corrections, the achieved mass resolutions for π0 and η mesons for pT > 1.7 GeV/c are σmπ0 = 4.56 ± 0.03 MeV/c2 and σmη = 15.3 ± 1.0 MeV/c2, respectively.
We report the differential charged jet cross section and jet fragmentation distributions measured with the ALICE detector in proton-proton collisions at a centre-of-mass energy s√= 7 TeV. Jets with pseudo-rapidity |η|<0.5 are reconstructed from charged particles using the anti-kT jet finding algorithm with a resolution parameter R = 0.4. The jet cross section is measured in the transverse momentum interval 5 ≤pchjetT< 100 GeV/c. Jet fragmentation is studied measuring the scaled transverse momentum spectra of the charged constituents of jets in four intervals of jet transverse momentum between 5 GeV/c and 30 GeV/c. The measurements are compared to calculations from the PYTHIA model as well as next-to-leading order perturbative QCD calculations with POWHEG + PYTHIA8. The charged jet cross section is described by POWHEG for the entire measured range of pchjetT. For pchjetT > 40 GeV/c, the PYTHIA calculations also agree with the measured charged jet cross section. PYTHIA6 simulations describe the fragmentation distributions to 15%. Larger discrepancies are observed for PYTHIA8.