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Contains fulltext : 305368.pdf (Publisher’s version ) (Closed access), Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. In biomedical image analysis, chosen performance metrics often do not reflect the domain interest, and thus fail to adequately measure scientific progress and hinder translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. Developed by a large international consortium in a multistage Delphi process, it is based on the novel concept of a problem fingerprint-a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), dataset and algorithm output. On the basis of the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as classification tasks at image, object or pixel level, namely image-level classification, object detection, semantic segmentation and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. Its applicability is demonstrated for various biomedical use cases.

Contains fulltext : 305370.pdf (Publisher’s version ) (Closed access), Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence research and its translation into practice. However, increasing evidence shows that, particularly in image analysis, metrics are often chosen inadequately. Although taking into account the individual strengths, weaknesses and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multistage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides a reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Although focused on biomedical image analysis, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. The work serves to enhance global comprehension of a key topic in image analysis validation.

As machine learning (ML) has emerged as the predominant technological paradigm for artificial intelligence (AI), complex black box models such as GPT-4 have gained widespread adoption. Concurrently, explainable AI (XAI) has risen in significance as a counterbalancing force. But the rapid expansion of this research domain has led to a proliferation of terminology and an array of diverse definitions, making it increasingly challenging to maintain coherence. This confusion of languages also stems from the plethora of different perspectives on XAI, e.g. ethics, law, standardization and computer science. This situation threatens to create a “tower of Babel” effect, whereby a multitude of languages impedes the establishment of a common (scientific) ground. In response, this paper first maps different vocabularies, used in ethics, law and standardization. It shows that despite a quest for standardized, uniform XAI definitions, there is still a confusion of languages. Drawing lessons from these viewpoints, it subsequently proposes a methodology for identifying a unified lexicon from a scientific standpoint. This could aid the scientific community in presenting a more unified front to better influence ongoing definition efforts in law and standardization, often without enough scientific representation, which will shape the nature of AI and XAI in the future.

We have realized an atom interferometer that probes gravitational potentials by holding, rather than dropping, atoms. Up to one minute of coherence times are realized by suspending the spatially separated atomic wave packets in an optical lattice that is mode-filtered by an optical cavity. This trapped configuration suppresses phase variance due to vibrations by four to five orders of magnitude, overcoming the dominant noise source in atom-interferometric gravimeters. Recent progress in characterizing and reducing interferometer decoherence led to major increases in coherence and precision, paving the way to measurements of dark-energy candidates and probes of the quantum nature of gravity through measuring the gravity of source masses with record precision and spatial resolution., Comment: Presented at the Ninth Meeting on CPT and Lorentz Symmetry, Bloomington, Indiana, May 17-26, 2022

Water and the hydroxyl radical are major constituents of the envelope of O-rich late-type stars. Transitions involving energy levels that are highly excited have been observed in both H$_2$O and OH. These and more recently discovered transitions can now be observed at a high sensitivity and angular resolution with the ALMA Array. Spectra and maps of H$_2$O and OH observed with an angular resolution of 20 to $\sim$200 mas were obtained at two epochs with the ALMA array. Observations with the Compact Array were also used to check for time variability of water transitions. Radiative transfer models of water were revisited to characterize masing conditions and up-to-date chemical models were used for comparison with our observations. Ten rotational transitions of H$_2$O with energies up to 9000 K were observed in various vibrational states. All but one are new detections in space, and from these we have derived accurate rest frequencies. Hyperfine split $\Lambda$-doubling transitions in v = 0, J = 27/2 and 29/2 levels of the $^2\Pi_{3/2}$ state and, $J = 33/2$ and 35/2 of the $^2\Pi_{1/2}$ state of OH with excitation energies up to 8900 K were also observed. Four of these transitions are new detections in space. Combining our measurements with earlier observations of OH, the v = 0 and v = 1 $\Lambda$-doubling frequencies have been improved. Our H$_2$O maps show compact emission and extensions up to twelve stellar radii or more. The 268.149 GHz emission line of water in the v$_2$ = 2 state is time variable, tends to be masing with dominant radiative pumping, and is widely excited. The widespread but weaker 262.898 GHz water line in v$_2$ = 1 also shows signs of maser emission. Emission and absorption of both H$_2$O and OH reveal an infall of matter and complex kinematics influenced by binarity. From our observed column densities, we derived OH/H$_2$O abundance ratios in a few stars., Comment: 41 pages with references and 25 figures in main text. 4 Tables in Appendix A. 10 figures in Appendix B. 2 figures in Appendix C. 14 figures in Appendix D. 5 figures in Appendix E. 2 figures in Appendix F

The dusty winds of cool evolved stars are a major contributor of the newly synthesised material enriching the Galaxy and future generations of stars. However, the details of the physics and chemistry behind dust formation and wind launching have yet to be pinpointed. Recent spatially resolved observations show the importance of gaining a more comprehensive view of the circumstellar chemistry, but a comparative study of the intricate interplay between chemistry and physics is still difficult because observational details such as frequencies and angular resolutions are rarely comparable. Aiming to overcome these deficiencies, ATOMIUM is an ALMA Large Programme to study the physics and chemistry of the circumstellar envelopes of a diverse set of oxygen-rich evolved stars under homogeneous observing conditions at three angular resolutions between ~0.02"-1.4". Here we summarize the molecular inventory of these sources, and the correlations between stellar parameters and molecular content. Seventeen oxygen-rich or S-type asymptotic giant branch (AGB) and red supergiant (RSG) stars have been observed in several tunings with ALMA Band 6, targeting a range of molecules to probe the circumstellar envelope and especially the chemistry of dust formation close to the star. We systematically assigned the molecular carriers of the spectral lines and measured their spectroscopic parameters and the angular extent of the emission of each line from integrated intensity maps. Across the ATOMIUM sample, we detect 291 transitions of 24 different molecules and their isotopologues. This includes several first detections in oxygen-rich AGB/RSG stars: PO v=1, SO2 v1=1 and v2=2, and several high energy H2O transitions. We also find several first detections in S-type AGB stars: vibrationally excited HCN v2=2,3 and SiS v=4,5,6, as well as first detections of the molecules SiC, AlCl, and AlF in W Aql..., Comment: 19 pages plus appendices, forthcoming publication in Astronomy & Astrophysics

Stress plays a crucial role in the pathogenesis of psychiatric disorders and affects neuronal plasticity in different brain regions. We have previously found that acute foot-shock (FS) stress elicits fast and long-lasting functional and morphological remodeling of excitatory neurons in the prefrontal cortex (PFC), which were partly prevented by the pretreatment with antidepressants. Here we investigated, whether acute stress and pretreatment with desipramine (DMI) interfere in hippocampal dendritic remodeling. Male Sprague-Dawley rats were subjected to acute FS-stress, followed by measurement of time-dependent (1, 7 and 14 days) structural plasticity (dendritic arborization, spine number and morphology) in hippocampal CA1 pyramidal neurons and expression patterns of molecular markers implicated in neuronal plasticity. We found that acute stress significantly decreased spine number, dendritic length, and altered spine morphometric parameters at all time points evaluated after stress. This was paralleled by changes in the gene expression of Spinophilin and Cdc42, and protein expression of homer1. Pretreatment with DMI prevented the stress-induced dendritic atrophy and spine loss 14 days after acute FS. However, DMI treatment without stress differentially affected the expression patterns of spine-related genes and proteins. In conclusion, acute FS-stress and pretreatment with DMI significantly changed dendritic morphology, including number and morphology of spines, and the length of dendrites in hippocampal CA1 pyramidal cells as early as 1 day, and sustained up to 14 days after acute FS. The findings were paralleled by changes in gene and protein expression of actin binding and cytoskeletal proteins, Rho GTPases, and postsynaptic scaffolding proteins.

In recent times, large organic molecules of exceptional complexity have been found in diverse regions of the interstellar medium. In this context, we aim to provide accurate frequencies of the ground vibrational state of two key aliphatic aldehydes, n-butanal and its branched-chain isomer, i-butanal, to enable their eventual detection in the interstellar medium. We employ a frequency modulation millimeter-wave absorption spectrometer to measure the rotational features of n- and i-butanal. We use the spectral line survey ReMoCA performed with the Atacama Large Millimeter/submillimeter Array to search for n- and i-butanal toward the star-forming region Sgr B2(N). We also search for both aldehydes toward the molecular cloud G+0.693-0.027 with IRAM 30 m and Yebes 40 m observations. Several thousand rotational transitions belonging to the lowest-energy conformers have been assigned in the laboratory spectra up to 325 GHz. A precise set of the relevant rotational spectroscopic constants has been determined for each structure. We report non-detections of n- and i-butanal toward both sources, Sgr B2(N1S) and G+0.693-0.027. We find that n- and i-butanal are at least 2-6 and 6-18 times less abundant than acetaldehyde toward Sgr B2(N1S), respectively, and that n-butanal is at least 63 times less abundant than acetaldehyde toward G+0.693-0.027. Comparison with astrochemical models indicates good agreement between observed and simulated abundances (where available). Grain-surface chemistry appears sufficient to reproduce aldehyde ratios in G+0.693-0.027; gas-phase production may play a more active role in Sgr B2(N1S). Our astronomical results indicate that the family of interstellar aldehydes in the Galactic center region is characterized by a drop of one order of magnitude in abundance at each incrementation in the level of molecular complexity.

Recoil imaging entails the detection of spatially resolved ionization tracks generated by particle interactions. This is a highly sought-after capability in many classes of detector, with broad applications across particle and astroparticle physics. However, at low energies, where ionization signatures are small in size, recoil imaging only seems to be a practical goal for micro-pattern gas detectors. This white paper outlines the physics case for recoil imaging, and puts forward a decadal plan to advance towards the directional detection of low-energy recoils with sensitivity and resolution close to fundamental performance limits. The science case covered includes: the discovery of dark matter into the neutrino fog, directional detection of sub-MeV solar neutrinos, the precision study of coherent-elastic neutrino-nucleus scattering, the detection of solar axions, the measurement of the Migdal effect, X-ray polarimetry, and several other applied physics goals. We also outline the R&D programs necessary to test concepts that are crucial to advance detector performance towards their fundamental limit: single primary electron sensitivity with full 3D spatial resolution at the $\sim$100 micron-scale. These advancements include: the use of negative ion drift, electron counting with high-definition electronic readout, time projection chambers with optical readout, and the possibility for nuclear recoil tracking in high-density gases such as argon. We also discuss the readout and electronics systems needed to scale-up such detectors to the ton-scale and beyond., Comment: 77 pages, 20 figures. Submitted to the Proceedings of the US Community Study on the Future of Particle Physics (Snowmass 2021)

Recoil imaging entails the detection of spatially resolved ionization tracks generated by particle interactions. This is a highly sought-after capability in many classes of detector, with broad applications across particle and astroparticle physics. However, at low energies, where ionization signatures are small in size, recoil imaging only seems to be a practical goal for micro-pattern gas detectors. This white paper outlines the physics case for recoil imaging, and puts forward a decadal plan to advance towards the directional detection of low-energy recoils with sensitivity and resolution close to fundamental performance limits. The science case covered includes: the discovery of dark matter into the neutrino fog, directional detection of sub-MeV solar neutrinos, the precision study of coherent-elastic neutrino-nucleus scattering, the detection of solar axions, the measurement of the Migdal effect, X-ray polarimetry, and several other applied physics goals. We also outline the R&D programs necessary to test concepts that are crucial to advance detector performance towards their fundamental limit: single primary electron sensitivity with full 3D spatial resolution at the $\sim$100 micron-scale. These advancements include: the use of negative ion drift, electron counting with high-definition electronic readout, time projection chambers with optical readout, and the possibility for nuclear recoil tracking in high-density gases such as argon. We also discuss the readout and electronics systems needed to scale-up such detectors to the ton-scale and beyond., Comment: 77 pages, 20 figures. Submitted to the Proceedings of the US Community Study on the Future of Particle Physics (Snowmass 2021)

Recoil imaging entails the detection of spatially resolved ionization tracks generated by particle interactions. This is a highly sought-after capability in many classes of detector, with broad applications across particle and astroparticle physics. However, at low energies, where ionization signatures are small in size, recoil imaging only seems to be a practical goal for micro-pattern gas detectors. This white paper outlines the physics case for recoil imaging, and puts forward a decadal plan to advance towards the directional detection of low-energy recoils with sensitivity and resolution close to fundamental performance limits. The science case covered includes: the discovery of dark matter into the neutrino fog, directional detection of sub-MeV solar neutrinos, the precision study of coherent-elastic neutrino-nucleus scattering, the detection of solar axions, the measurement of the Migdal effect, X-ray polarimetry, and several other applied physics goals. We also outline the R&D programs necessary to test concepts that are crucial to advance detector performance towards their fundamental limit: single primary electron sensitivity with full 3D spatial resolution at the $\sim$100 micron-scale. These advancements include: the use of negative ion drift, electron counting with high-definition electronic readout, time projection chambers with optical readout, and the possibility for nuclear recoil tracking in high-density gases such as argon. We also discuss the readout and electronics systems needed to scale-up such detectors to the ton-scale and beyond., Comment: 77 pages, 20 figures. Submitted to the Proceedings of the US Community Study on the Future of Particle Physics (Snowmass 2021)

Characterizing the molecular composition of solar-type protostars is useful for improving our understanding of the physico-chemical conditions under which the Sun and its planets formed. In this work, we analyzed the Atacama Large Millimeter/submillimeter Array (ALMA) data of the Protostellar Interferometric Line Survey (PILS), an unbiased spectral survey of the solar-type protostar IRAS 16293-2422, and we tentatively detected 3-hydroxypropenal (HOCHCHCHO) for the first time in the interstellar medium towards source B. Based on the observed line intensities and assuming local thermodynamic equilibrium, its column density is constrained to be similar to 10(15) cm(-2), corresponding to an abundance of 10(-4) relative to methanol, CH3OH. Additional spectroscopic studies are needed to constrain the excitation temperature of this molecule. We included HOCHCHCHO and five of its isomers in the chemical network presented in Manigand et al. (2021, A&A, 645, A53) and we predicted their chemical evolution with the Nautilus code. The model reproduces the abundance of HOCHCHCHO within the uncertainties. This species is mainly formed through the grain surface reaction CH2CHO + HCO -> HCOCH2CHO, followed by the tautomerization of HCOCH2CHO into HOCHCHCHO. Two isomers, CH3COCHO and CH2COHCHO, are predicted to be even more abundant than HOCHCHCHO. Spectroscopic studies of these molecules are essential in searching for them in IRAS 16293-2422 and other astrophysical sources.

In recent times, large organic molecules of exceptional complexity have been found in diverse regions of the interstellar medium. In this context, we aim to provide accurate frequencies of the ground vibrational state of two key aliphatic aldehydes, n-butanal and its branched-chain isomer, i-butanal, to enable their eventual detection in the interstellar medium. We employ a frequency modulation millimeter-wave absorption spectrometer to measure the rotational features of n- and i-butanal. We use the spectral line survey ReMoCA performed with the Atacama Large Millimeter/submillimeter Array to search for n- and i-butanal toward the star-forming region Sgr B2(N). We also search for both aldehydes toward the molecular cloud G+0.693-0.027 with IRAM 30 m and Yebes 40 m observations. Several thousand rotational transitions belonging to the lowest-energy conformers have been assigned in the laboratory spectra up to 325 GHz. A precise set of the relevant rotational spectroscopic constants has been determined for each structure. We report non-detections of n- and i-butanal toward both sources, Sgr B2(N1S) and G+0.693-0.027. We find that n- and i-butanal are at least 2-6 and 6-18 times less abundant than acetaldehyde toward Sgr B2(N1S), respectively, and that n-butanal is at least 63 times less abundant than acetaldehyde toward G+0.693-0.027. Comparison with astrochemical models indicates good agreement between observed and simulated abundances (where available). Grain-surface chemistry appears sufficient to reproduce aldehyde ratios in G+0.693-0.027; gas-phase production may play a more active role in Sgr B2(N1S). Our astronomical results indicate that the family of interstellar aldehydes in the Galactic center region is characterized by a drop of one order of magnitude in abundance at each incrementation in the level of molecular complexity.

Recoil imaging entails the detection of spatially resolved ionization tracks generated by particle interactions. This is a highly sought-after capability in many classes of detector, with broad applications across particle and astroparticle physics. However, at low energies, where ionization signatures are small in size, recoil imaging only seems to be a practical goal for micro-pattern gas detectors. This white paper outlines the physics case for recoil imaging, and puts forward a decadal plan to advance towards the directional detection of low-energy recoils with sensitivity and resolution close to fundamental performance limits. The science case covered includes: the discovery of dark matter into the neutrino fog, directional detection of sub-MeV solar neutrinos, the precision study of coherent-elastic neutrino-nucleus scattering, the detection of solar axions, the measurement of the Migdal effect, X-ray polarimetry, and several other applied physics goals. We also outline the R&D programs necessary to test concepts that are crucial to advance detector performance towards their fundamental limit: single primary electron sensitivity with full 3D spatial resolution at the $\sim$100 micron-scale. These advancements include: the use of negative ion drift, electron counting with high-definition electronic readout, time projection chambers with optical readout, and the possibility for nuclear recoil tracking in high-density gases such as argon. We also discuss the readout and electronics systems needed to scale-up such detectors to the ton-scale and beyond., Comment: 77 pages, 20 figures. Submitted to the Proceedings of the US Community Study on the Future of Particle Physics (Snowmass 2021)

This paper will review the origins, development, and examples of new versions of Micro-Pattern Gas Detectors. The goal for MPGD development was the creation of detectors that could cost-effectively cover large areas while offering excellent position and timing resolution, and the ability to operate at high incident particle rates. The early MPGD developments culminated in the formation of the RD51 collaboration which has become the critical organization for the promotion of MPGDs and all aspects of their production, characterization, simulation, and uses in an expanding array of experimental configurations. For the Snowmass 2021 study, a number of Letters of Interest were received that illustrate ongoing developments and expansion of the use of MPGDs. In this paper, we highlight high precision timing, high rate application, trigger capability expansion of the SRS readout system, and a structure designed for low ion backflow., Comment: Contribution to Snowmass 2021

When administered as a single subanesthetic dose, the n-methyl-d-aspartate (NMDA) receptor antagonist, ketamine, produces rapid (within hours) and relatively sustained antidepressant actions even in treatment-resistant patients. Preclinical studies have shown that ketamine increases dendritic spine density and synaptic proteins in brain areas critical for the actions of antidepressants, yet the temporal relationship between structural changes and the onset of antidepressant action remains poorly understood. In this study, we examined the effects of a single dose of S-ketamine (15 mg/kg) on dendritic length, dendritic arborization, spine density, and spine morphology in the Flinders Sensitive and Flinders Resistant Line (FSL/FRL) rat model of depression. We found that already 1 h after injection with ketamine, apical dendritic spine deficits in CA1 pyramidal neurons of FSL rats were completely restored. Notably, the observed increase in spine density was attributable to regulation of both mushroom and long-thin spines. In contrast, ketamine had no effect on dendritic spine density in FRL rats. On the molecular level, ketamine normalized elevated levels of phospho-cofilin and the NMDA receptor subunits GluN2A and GluN2B and reversed homer3 deficiency in hippocampal synaptosomes of FSL rats. Taken together, our data suggest that rapid formation of new spines may provide an important structural substrate during the initial phase of ketamine’s antidepressant action.

This overview paper presents ATOMIUM, a Large Programme in Cycle 6 with the Atacama Large Millimeter-submillimeter Array (ALMA). The goal of ATOMIUM is to understand the dynamics and the gas phase and dust formation chemistry in the winds of evolved asymptotic giant branch (AGB) and red supergiant (RSG) stars. A more general aim is to identify chemical processes applicable to other astrophysical environments. 17 oxygen-rich AGB and RSG stars spanning a range in (circum)stellar parameters and evolutionary phases were observed in a homogeneous observing strategy allowing for an unambiguous comparison. Data were obtained between 213.83 and 269.71 GHz at high (0.025-0.050 arcsec), medium (0.13-0.24 arcsec), and low (about 1 arcsec) angular resolution. The sensitivity per 1.3 km/s channel was 1.5-5 mJy/beam. 13 molecules were designated as primary molecules in the survey: CO, SiO, AlO, AlOH, TiO, TiO2, HCN, SO, SO2, SiS, CS, H2O, and NaCl. The scientific motivation, survey design, sample properties, data reduction, and an overview of the data products are described; and we highlight one scientific result - the wind kinematics of the ATOMIUM sources. The ATOMIUM sources often have a slow wind acceleration, and a fraction of the gas reaches a velocity which can be up to a factor of two times larger than previously reported terminal velocities assuming isotropic expansion, and the wind kinematic profiles establish that the radial velocity described by the momentum equation for a spherical wind structure cannot capture the complexity of the velocity field. In 15 sources, some molecular transitions other than 12CO v=0 J=2-1 reach a higher outflow velocity, with a spatial emission zone that is often greater than 30 stellar radii, but much less than the extent of CO. Binary interaction with a (sub)stellar companion might (partly) explain the non-monotonic behaviour of the projected velocity field.

Radiomics converts medical images into mineable data via a high-throughput extraction of quantitative features used for clinical decision support. However, these radiomic features are susceptible to variation across scanners, acquisition protocols, and reconstruction settings. Various investigations have assessed the reproducibility and validation of radiomic features across these discrepancies. In this narrative review, we combine systematic keyword searches with prior domain knowledge to discuss various harmonization solutions to make the radiomic features more reproducible across various scanners and protocol settings. Different harmonization solutions are discussed and divided into two main categories: image domain and feature domain. The image domain category comprises methods such as the standardization of image acquisition, post-processing of raw sensor-level image data, data augmentation techniques, and style transfer. The feature domain category consists of methods such as the identification of reproducible features and normalization techniques such as statistical normalization, intensity harmonization, ComBat and its derivatives, and normalization using deep learning. We also reflect upon the importance of deep learning solutions for addressing variability across multi-centric radiomic studies especially using generative adversarial networks (GANs), neural style transfer (NST) techniques, or a combination of both. We cover a broader range of methods especially GANs and NST methods in more detail than previous reviews.

This overview paper presents ATOMIUM, a Large Programme in Cycle 6 with the Atacama Large Millimeter-submillimeter Array (ALMA). The goal of ATOMIUM is to understand the dynamics and the gas phase and dust formation chemistry in the winds of evolved asymptotic giant branch (AGB) and red supergiant (RSG) stars. A more general aim is to identify chemical processes applicable to other astrophysical environments. 17 oxygen-rich AGB and RSG stars spanning a range in (circum)stellar parameters and evolutionary phases were observed in a homogeneous observing strategy allowing for an unambiguous comparison. Data were obtained between 213.83 and 269.71 GHz at high (0.025-0.050 arcsec), medium (0.13-0.24 arcsec), and low (about 1 arcsec) angular resolution. The sensitivity per 1.3 km/s channel was 1.5-5 mJy/beam. 13 molecules were designated as primary molecules in the survey: CO, SiO, AlO, AlOH, TiO, TiO2, HCN, SO, SO2, SiS, CS, H2O, and NaCl. The scientific motivation, survey design, sample properties, data reduction, and an overview of the data products are described; and we highlight one scientific result - the wind kinematics of the ATOMIUM sources. The ATOMIUM sources often have a slow wind acceleration, and a fraction of the gas reaches a velocity which can be up to a factor of two times larger than previously reported terminal velocities assuming isotropic expansion, and the wind kinematic profiles establish that the radial velocity described by the momentum equation for a spherical wind structure cannot capture the complexity of the velocity field. In 15 sources, some molecular transitions other than 12CO v=0 J=2-1 reach a higher outflow velocity, with a spatial emission zone that is often greater than 30 stellar radii, but much less than the extent of CO. Binary interaction with a (sub)stellar companion might (partly) explain the non-monotonic behaviour of the projected velocity field.

Radiomics converts medical images into mineable data via a high-throughput extraction of quantitative features used for clinical decision support. However, these radiomic features are susceptible to variation across scanners, acquisition protocols, and reconstruction settings. Various investigations have assessed the reproducibility and validation of radiomic features across these discrepancies. In this narrative review, we combine systematic keyword searches with prior domain knowledge to discuss various harmonization solutions to make the radiomic features more reproducible across various scanners and protocol settings. Different harmonization solutions are discussed and divided into two main categories: image domain and feature domain. The image domain category comprises methods such as the standardization of image acquisition, post-processing of raw sensor-level image data, data augmentation techniques, and style transfer. The feature domain category consists of methods such as the identification of reproducible features and normalization techniques such as statistical normalization, intensity harmonization, ComBat and its derivatives, and normalization using deep learning. We also reflect upon the importance of deep learning solutions for addressing variability across multi-centric radiomic studies especially using generative adversarial networks (GANs), neural style transfer (NST) techniques, or a combination of both. We cover a broader range of methods especially GANs and NST methods in more detail than previous reviews.

Machine learning and data analysis are becoming an essential part of the decision-making process in modern organizations. Even though new and improved analytics algorithms are developed frequently, organizations are struggling to develop analytics applications that can stay up-To-date with changing business requirements and technology innovations The rapid development of ad-hoc programs to conduct machine learning tasks at hand has resulted in creating more expenses and efforts in the long term, a phenomenon referred to as technical debt in literature. This paper addresses the technical debt associated with data analytics applications by proposing a knowledge repository that captures analytics-related knowledge, which can be developed and maintained separately from the organization's IT infrastructure and used to design analytics applications with visual interfaces. This way, organizations can develop dynamic and adaptable analytics applications with easy-To-follow front-ends and can accommodate new data sources or machine learning models. We evaluate the proposed approach by conducting a case study that develops an application for the acquisition and management of high-frequency financial market data.

Background: Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical use. Purpose: To standardize a set of 174 radiomic features. Materials and Methods: Radiomic features were assessed in three phases. In phase I, 487 features were derived from the basic set of 174 features. Twenty-five research teams with unique radiomics software implementations computed feature values directly from a digital phantom, without any additional image processing. In phase II, 15 teams computed values for 1347 derived features using a CT image of a patient with lung cancer and predefined image processing configurations. In both phases, consensus among the teams on the validity of tentative reference values was measured through the frequency of the modal value and classified as follows: less than three matches, weak; three to five matches, moderate; six to nine matches, strong; 10 or more matches, very strong. In the final phase (phase III), a public data set of multimodality images (CT, fluorine 18 fluorodeoxyglucose PET, and T1-weighted MRI) from 51 patients with soft-tissue sarcoma was used to prospectively assess reproducibility of standardized features. Results: Consensus on reference values was initially weak for 232 of 302 features (76.8%) at phase I and 703 of 1075 features (65.4%) at phase II. At the final iteration, weak consensus remained for only two of 487 features (0.4%) at phase I and 19 of 1347 features (1.4%) at phase II. Strong or better consensus was achieved for 463 of 487 features (95.1%) at phase I and 1220 of 1347 features (90.6%) at phase II. Overall, 169 of 174 features were standardized in the first two phases. In the final validation phase (phase III), most of the 169 standardized features could be excellently reproduced (166 with CT; 164 with PET; and 164 with MRI). Conclusion: A set of 169 radiomics features was standardized, which enabled ver

Inhibition of bromodomain and extraterminal motif (BET) proteins such as BRD4 bears great promise for cancer treatment and its efficacy has been frequently attributed to Myc downregulation. Here, we use B-cell tumors as a model to address the mechanism of action of JQ1, a widely used BET inhibitor. Although JQ1 led to widespread eviction of BRD4 from chromatin, its effect on gene transcription was limited to a restricted set of genes. This was unlinked to Myc downregulation or its chromatin association. Yet, JQ1-sensitive genes were enriched for Myc and E2F targets, were expressed at high levels, and showed high promoter occupancy by RNAPol2, BRD4, Myc and E2F. Their marked decrease in transcriptional elongation upon JQ1 treatment, indicated that BRD4-dependent promoter clearance was rate limiting for transcription. At JQ1-insensitive genes the drop in transcriptional elongation still occurred, but was compensated by enhanced RNAPol2 recruitment. Similar results were obtained with other inhibitors of transcriptional elongation. Thus, the selective transcriptional effects following JQ1 treatment are linked to the inability of JQ1-sensitive genes to sustain compensatory RNAPol2 recruitment to promoters. These observations highlight the role of BET proteins in supporting transcriptional elongation and rationalize how a general suppression of elongation may selectively affects transcription.

Social networks have been a revolutionary scenario for celebrities because they allow them to reach a wider audience with much higher frequency than using traditional means. These platforms enable them to improve or sometimes deteriorate, their careers through the construction of closer relationships with their fans and the acquisition of new ones. Indeed, networks have promoted the emergence of a new type of celebrities that exists only in the digital world. Being able to characterize the celebrities that are more active on social networks, such as Twitter, gives an enormous opportunity to identify what is their real level of fame, what is their relevance for an age group, or a specific gender or occupation. These facts may enrich decision making, especially in advertising and marketing. To achieve this aim, this paper presents a novel strategy for the characterization of celebrities profile on Twitter based on the generation of socio-linguistic features from their posts that serve as input to a set of classifiers. Specifically, we produced four classifiers that describe the level of fame, the gender, the birth date, and the possible occupation of a celebrity. We obtained the training and test data sets as part of our participation at PAN 2019 at CLEF. Results of each classifier are reported including the analysis of which features are more relevant, which classification techniques were more useful and which were the final precision and recall results. © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Context. The diffuse and translucent molecular clouds traced in absorption along the line of sight to strong background sources have so far been investigated mainly in the spectral domain because of limited angular resolution or small sizes of the background sources. Aims. We aim to resolve and investigate the spatial structure of molecular clouds traced by several molecules detected in absorption along the line of sight to Sgr B2(N). Methods. We have used spectral line data from the EMoCA survey performed with the Atacama Large Millimeter/submillimeter Array (ALMA), taking advantage of its high sensitivity and angular resolution. The velocity structure across the field of view is investigated by automatically fitting synthetic spectra to the detected absorption features, which allows us to decompose them into individual clouds located in the Galactic centre (GC) region and in spiral arms along the line of sight. We compute opacity maps for all detected molecules. We investigated the spatial and kinematical structure of the individual clouds with statistical methods and perform a principal component analysis to search for correlations between the detected molecules. To investigate the nature of the molecular clouds along the line of sight to Sgr B2, we also used archival Mopra data. Results. We identify, on the basis of c-C3H2, 15 main velocity components along the line of sight to Sgr B2(N) and several components associated with the envelope of Sgr B2 itself. The c-C3H2 column densities reveal two categories of clouds. Clouds in Category I (3 kpc arm, 4 kpc arm, and some GC clouds) have smaller c-C3H2 column densities, smaller linewidths, and smaller widths of their column density PDFs than clouds in Category II (Scutum arm, Sgr arm, and other GC clouds). We derive opacity maps for the following molecules: c-C3H2, (HCO+)-C-13, (CO)-C-13, HNC and its isotopologue (HNC)-C-13, (HCN)-N-15, CS and its isotopologues (CS)-S-34 and (CS)-C-13, SiO, SO, and CH3OH. These maps

Unfortunately, in social networks, software bots or just bots are becoming more and more common because malicious people have seen their usefulness to spread false messages, spread rumors and even manipulate public opinion. Even though the text generated by users in social networks is a rich source of information that can be used to identify different aspects of its authors, not being able to recognize which users are truly humans and which are not, is a big drawback. In this work, we describe the properties of our multilingual classification model submitted for PAN2019 that is able to recognize bots from humans, and females from males. This solution extracted 18 features from the user's posts and applying a machine learning algorithm obtained good performance results. © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Social networks have been a revolutionary scenario for celebrities because they allow them to reach a wider audience with much higher frequency than using traditional means. These platforms enable them to improve or sometimes deteriorate, their careers through the construction of closer relationships with their fans and the acquisition of new ones. Indeed, networks have promoted the emergence of a new type of celebrities that exists only in the digital world. Being able to characterize the celebrities that are more active on social networks, such as Twitter, gives an enormous opportunity to identify what is their real level of fame, what is their relevance for an age group, or a specific gender or occupation. These facts may enrich decision making, especially in advertising and marketing. To achieve this aim, this paper presents a novel strategy for the characterization of celebrities profile on Twitter based on the generation of socio-linguistic features from their posts that serve as input to a set of classifiers. Specifically, we produced four classifiers that describe the level of fame, the gender, the birth date, and the possible occupation of a celebrity. We obtained the training and test data sets as part of our participation at PAN 2019 at CLEF. Results of each classifier are reported including the analysis of which features are more relevant, which classification techniques were more useful and which were the final precision and recall results. © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Unfortunately, in social networks, software bots or just bots are becoming more and more common because malicious people have seen their usefulness to spread false messages, spread rumors and even manipulate public opinion. Even though the text generated by users in social networks is a rich source of information that can be used to identify different aspects of its authors, not being able to recognize which users are truly humans and which are not, is a big drawback. In this work, we describe the properties of our multilingual classification model submitted for PAN2019 that is able to recognize bots from humans, and females from males. This solution extracted 18 features from the user's posts and applying a machine learning algorithm obtained good performance results. © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Context. The diffuse and translucent molecular clouds traced in absorption along the line of sight to strong background sources have so far been investigated mainly in the spectral domain because of limited angular resolution or small sizes of the background sources. Aims. We aim to resolve and investigate the spatial structure of molecular clouds traced by several molecules detected in absorption along the line of sight to Sgr B2(N). Methods. We have used spectral line data from the EMoCA survey performed with the Atacama Large Millimeter/submillimeter Array (ALMA), taking advantage of its high sensitivity and angular resolution. The velocity structure across the field of view is investigated by automatically fitting synthetic spectra to the detected absorption features, which allows us to decompose them into individual clouds located in the Galactic centre (GC) region and in spiral arms along the line of sight. We compute opacity maps for all detected molecules. We investigated the spatial and kinematical structure of the individual clouds with statistical methods and perform a principal component analysis to search for correlations between the detected molecules. To investigate the nature of the molecular clouds along the line of sight to Sgr B2, we also used archival Mopra data. Results. We identify, on the basis of c-C3H2, 15 main velocity components along the line of sight to Sgr B2(N) and several components associated with the envelope of Sgr B2 itself. The c-C3H2 column densities reveal two categories of clouds. Clouds in Category I (3 kpc arm, 4 kpc arm, and some GC clouds) have smaller c-C3H2 column densities, smaller linewidths, and smaller widths of their column density PDFs than clouds in Category II (Scutum arm, Sgr arm, and other GC clouds). We derive opacity maps for the following molecules: c-C3H2, (HCO+)-C-13, (CO)-C-13, HNC and its isotopologue (HNC)-C-13, (HCN)-N-15, CS and its isotopologues (CS)-S-34 and (CS)-C-13, SiO, SO, and CH3OH. These maps

The Personalised Information Retrieval Lab (PIR-CLEF 2019) lab is an initiative aimed at both providing and critically analysing the evaluation of Personalization in Information Retrieval (PIR) applications. PIR-CLEF 2019 is the second edition of the Lab after the successful Pilot lab organised at CLEF 2017 and the first edition of the Lab at CLEF 2018. PIR-CLEF 2019 provided registered participants with two tracks: the Web Search Task and the Medical Search Task. The Web Search Task continues the activities introduced in the previous editions of the PIR-CLEF Lab, while the Medical Search Track focuses on personalisation within an ad hoc search task introduced in previous editions of the CLEF eHealth Lab.

Prediction equations derived from in situ and in vitro analytical techniques to determine in vivo organic matter digestibility (OMD) are useful tools to estimate the quality of livestock feed. Most derived equations are aimed at groups of feedstuffs (forages or concentrates) or feeds separately. In this study of OMD, the prediction equations of the modified two-stage Tilley & Terry in vitro technique (MT) and pepsin-acid multi-enzymatic technique (PME) are compared, validated, and improved in relation to verified in vivo results using feedstuffs and complete diets. Initial comparison with in vivo data showed that the combined dataset and that of single feedstuffs achieved acceptable R2 values for both MT and PME (0.88 and 0.92, 0.87 and 0.89, respectively). The validation with the second dataset established that the initial equations were valid with R2 values of 0.96 for MT and 0.91 for PME on the combined feeds dataset. The establishment of a prediction equation using both datasets resulted in improved R2 values over the initial equation. With combined feeds using MT it was 0.94, compared with 0.88, and using PME, it was 0.91 compared with 0.87. No significant decrease occurred in the variation of OMD between the datasets, as explained by the model when omitting on separate slope and intercept, thus confirming the same population assumption. The data sets could be combined for a new prediction equation. The R2 values were 0.94 and 0.91 for MT and PME methods for combined feeds, respectively. The new improved in vivo prediction equation in each instance was thus valid and a true improvement on the initial prediction equations. The PME method can be used for predicting OMD as it negates the use of rumen liquor and confidently replaces MT OMD determinations.

As organisations expand and interconnect, authorisation infrastructures become increasingly difficult to manage. Several solutions have been proposed, including self-adaptive authorisation, where the access control policies are dynamically adapted at run-time to respond to misuse and malicious behaviour. The ultimate goal of self-adaptive authorisation is to reduce human intervention, make authorisation infrastructures more responsive to malicious behaviour. In this chapter, we scope and define the emerging area of self-adaptive authorisation by describing some of its developments, trends and challenges. For that, we start by identifying key concepts related to access control and authorisation infrastructures, and provide a brief introduction to self-adaptive software systems, which provides the foundation for investigating how self-adaptation can enable the enforcement of authorisation policies. The outcome of this study is the identification of several technical challenges related to self-adaptive authorisation, which are classified according to the different stages of a feedback control loop.

Background: The increasing availability of resequencing data has led to a better understanding of the most important genes in cancer development. Nevertheless, the mutational landscape of many tumor types is heterogeneous and encompasses a long tail of potential driver genes that are systematically excluded by currently available methods due to the low frequency of their mutations. We developed LowMACA (Low frequency Mutations Analysis via Consensus Alignment), a method that combines the mutations of various proteins sharing the same functional domains to identify conserved residues that harbor clustered mutations in multiple sequence alignments. LowMACA is designed to visualize and statistically assess potential driver genes through the identification of their mutational hotspots. Results: We analyzed the Ras superfamily exploiting the known driver mutations of the trio K-N-HRAS, identifying new putative driver mutations and genes belonging to less known members of the Rho, Rab and Rheb subfamilies. Furthermore, we applied the same concept to a list of known and candidate driver genes, and observed that low confidence genes show similar patterns of mutation compared to high confidence genes of the same protein family. Conclusions: LowMACA is a software for the identification of gain-of-function mutations in putative oncogenic families, increasing the amount of information on functional domains and their possible role in cancer. In this context LowMACA emphasizes the role of genes mutated at low frequency otherwise undetectable by classical single gene analysis.

The regulation of miRNAs is critical to the definition of cell identity and behavior in normal physiology and disease. To date, the dynamics of miRNA degradation and the mechanisms involved in remain largely obscure, in particular, in higher organisms. Here, we developed a pulse-chase approach based on metabolic RNA labeling to calculate miRNA decay rates at genome-wide scale in mammalian cells. Our analysis revealed heterogeneous miRNA half-lives, with many species behaving as stable molecules (T1/2 > 24 h), while others, including passenger miRNAs and a number (25/129) of guide miRNAs, are quickly turned over (T1/2 = 4-14 h). Decay rates were coupled with other features, including genomic organization, transcription rates, structural heterogeneity (isomiRs), and target abundance, measured through quantitative experimental approaches. This comprehensive analysis highlighted functional mechanisms that mediate miRNA degradation, as well as the importance of decay dynamics in the regulation of the miRNA pool under both steady-state conditions and during cell transitions.

Context. Complex organic molecules are readily detected in the inner regions of the gaseous envelopes of forming protostars. Their detection is crucial to understanding the chemical evolution of the Universe and exploring the link between the early stages of star formation and the formation of solar system bodies, where complex organic molecules have been found in abundance. In particular, molecules that contain nitrogen are interesting due to the role nitrogen plays in the development of life and the compact scales such molecules have been found to trace around forming protostars. Aims. The goal of this work is to determine the inventory of one family of nitrogen-bearing organic molecules, complex nitriles (molecules with a -C N functional group) towards two hot corino sources in the low-mass protostellar binary IRAS 16293-2422. This work explores the abundance differences between the two sources, the isotopic ratios, and the spatial extent derived from molecules containing the nitrile functional group. Methods. Using data from the Protostellar Interferometric Line Survey (PILS) obtained with ALMA, we determine abundances and excitation temperatures for the detected nitriles. We also present a new method for determining the spatial structure of sources with high line density and large velocity gradients-Velocity-corrected INtegrated emission (VINE) maps. Results. We detect methyl cyanide (CH3CN) as well as five of its isotopologues, including CHD2CN, which is the first detection in the interstellar medium (ISM). We also detect ethyl cyanide (C2H5CN), vinyl cyanide (C2H3CN), and cyanoacetylene (HC3N). We find that abundances are similar between IRAS 16293A and IRAS 16293B on small scales except for vinyl cyanide which is only detected towards the latter source. This suggests an important difference between the sources either in their evolutionary stage or warm-up timescales. We also detect a spatially double-peaked emission for the first time in molecular emission i

Context. Complex organic molecules are readily detected in the inner regions of the gaseous envelopes of forming protostars. Their detection is crucial to understanding the chemical evolution of the Universe and exploring the link between the early stages of star formation and the formation of solar system bodies, where complex organic molecules have been found in abundance. In particular, molecules that contain nitrogen are interesting due to the role nitrogen plays in the development of life and the compact scales such molecules have been found to trace around forming protostars. Aims. The goal of this work is to determine the inventory of one family of nitrogen-bearing organic molecules, complex nitriles (molecules with a -C N functional group) towards two hot corino sources in the low-mass protostellar binary IRAS 16293-2422. This work explores the abundance differences between the two sources, the isotopic ratios, and the spatial extent derived from molecules containing the nitrile functional group. Methods. Using data from the Protostellar Interferometric Line Survey (PILS) obtained with ALMA, we determine abundances and excitation temperatures for the detected nitriles. We also present a new method for determining the spatial structure of sources with high line density and large velocity gradients-Velocity-corrected INtegrated emission (VINE) maps. Results. We detect methyl cyanide (CH3CN) as well as five of its isotopologues, including CHD2CN, which is the first detection in the interstellar medium (ISM). We also detect ethyl cyanide (C2H5CN), vinyl cyanide (C2H3CN), and cyanoacetylene (HC3N). We find that abundances are similar between IRAS 16293A and IRAS 16293B on small scales except for vinyl cyanide which is only detected towards the latter source. This suggests an important difference between the sources either in their evolutionary stage or warm-up timescales. We also detect a spatially double-peaked emission for the first time in molecular emission i

The c-myc proto-oncogene product, Myc, is a transcription factor that binds thousands of genomic loci. Recent work suggested that rather than up- and downregulating selected groups of genes, Myc targets all active promoters and enhancers in the genome (a phenomenon termed 'invasion') and acts as a general amplifier of transcription. However, the available data did not readily discriminate between direct and indirect effects of Myc on RNA biogenesis. We addressed this issue with genome-wide chromatin immunoprecipitation and RNA expression profiles during B-cell lymphomagenesis in mice, in cultured B cells and fibroblasts. Consistent with long-standing observations, we detected general increases in total RNA or messenger RNA copies per cell (hereby termed 'amplification') when comparing actively proliferating cells with control quiescent cells: this was true whether cells were stimulated by mitogens (requiring endogenous Myc for a proliferative response) or by deregulated, oncogenic Myc activity. RNA amplification and promoter/enhancer invasion by Myc were separable phenomena that could occur without one another. Moreover, whether or not associated with RNA amplification, Myc drove the differential expression of distinct subsets of target genes. Hence, although having the potential to interact with all active or poised regulatory elements in the genome, Myc does not directly act as a global transcriptional amplifier. Instead, our results indicate that Myc activates and represses transcription of discrete gene sets, leading to changes in cellular state that can in turn feed back on global RNA production and turnover.

As high-grade deposits are depleted, mines are faced with lower feed grades. This requires the mining and processing of much larger volumes of material per tonne of product. The aim of preconcentration is to remove barren material as early in the process and at as coarse a particle as possible to reduce the amount of material requiring downstream comminution and processing. Preconcentration can significantly improve the economics of a project by upgrading below cut-off grade material and/or increasing production rates. There are several technologies that may be applicable for preconcentration: gravity concentration, screening, sensor-based ore sorting and magnetic separation. The suitability in each case depends on ore properties as well as site and economic conditions. Coarse particle flotation is poor because of bubble-particle detachment in the pulp as well as drop-back at the pulp-froth interface. The HydroFloat, patented in 2001, represents a significant departure from conventional flotation as it takes place in a dense-phase, liquid-particulate fluidised bed. As a preconcentrator it reduces the extent of grinding required to recover the same amount of metal from ore. This will significantly reduce capital, energy and operating costs. Large natural variability in ore grade and quality is common and although belt analysers have been used in the coal industry for years, the adoption of on-belt analysis in the minerals industry has been slow. Prompt gamma neutron activation analysis (PGNAA) is considered the most representative elemental analysis technology for conveyed bulk material measurements. Benefits of improved management of feed quality could include reduction of costs per tonne of product., As high-grade deposits are depleted, mines are faced with lower feed grades. This requires the mining and processing of much larger volumes of material per tonne of product. The aim of preconcentration is to remove barren material as early in the process and at as coarse a particle as possible to reduce the amount of material requiring downstream comminution and processing. Preconcentration can significantly improve the economics of a project by upgrading below cut-off grade material and/or increasing production rates. There are several technologies that may be applicable for preconcentration: gravity concentration, screening, sensor-based ore sorting and magnetic separation. The suitability in each case depends on ore properties as well as site and economic conditions. Coarse particle flotation is poor because of bubble-particle detachment in the pulp as well as drop-back at the pulp-froth interface. The HydroFloat, patented in 2001, represents a significant departure from conventional flotation as it takes place in a dense-phase, liquid-particulate fluidised bed. As a preconcentrator it reduces the extent of grinding required to recover the same amount of metal from ore. This will significantly reduce capital, energy and operating costs. Large natural variability in ore grade and quality is common and although belt analysers have been used in the coal industry for years, the adoption of on-belt analysis in the minerals industry has been slow. Prompt gamma neutron activation analysis (PGNAA) is considered the most representative elemental analysis technology for conveyed bulk material measurements. Benefits of improved management of feed quality could include reduction of costs per tonne of product.

Context. Up to now, mostly relatively simple molecules have been detected in interstellar diffuse molecular clouds in our galaxy, but more complex species have been reported in the diffuse/translucent medium of a z = 0 : 89 spiral galaxy. Aims. We aim at searching for complex organic molecules (COMs) in diffuse molecular clouds along the line of sight to Sgr B2(N), taking advantage of the high sensitivity and angular resolution of the Atacama Large Millimeter/submillimeter Array (ALMA). Methods. We use data acquired as part of the EMoCA survey performed with ALMA. To analyse the absorption features of the molecules detected towards the ultracompact H II region K4 in Sgr B2(N), we calculate synthetic spectra for these molecules and fit their column densities, line widths, centroid velocities, and excitation temperatures. Results. We report the detection of CH3OH, CH3CN, CH3CHO, HC3N, and NH2CHO in Galactic center (GC) diffuse clouds and CH3OH and CH3CN in a diffuse cloud in the Scutum arm. The chemical composition of one of the diffuse GC clouds is found to be similar to the one of the diffuse/translucent medium of the z = 0 : 89 spiral galaxy. Conclusions. The chemical processes leading to chemical complexity in the diffuse molecular ISM appear to have remained similar since z = 0.89. As proposed in previous studies, the presence of COMs in diffuse molecular clouds may result from a cyclical interstellar process of cloud contraction and expansion between diffuse and dense states.

We have previously demonstrated lactational transfer of T cell-based immunity from dam to foster pup. In the short term, a significant part of transferred immunity is passive cellular immunity. However, as time progresses, this is replaced by what we have described as maternal educational immunity such that by young adulthood, all immune cells responding to a foster dam immunogen are the product of the foster pup's thymus. To reduce confounding factors, this original demonstration used congenic/syngeneic dam and foster pup pairs. In this study, we investigated lactational transfer of immunity to Mycobacterium tuberculosis in MHC class I-mismatched animals, as well as from Th1-biased dams to Th2-biased foster pups. Using immunized C57BL/6J dams, lactational transfer to nonimmunized BALB/cJ foster pups resulted in much greater immunity than direct immunization in 5-wk-old pups (ex vivo assay of pup splenocytes). At this age, 82% of immunogen-responding cells in the pup spleen were produced through maternal educational immunity. FVB/NJ nonimmunized foster recipients had a greater number of maternal cells in the spleen and thymus but a much larger percentage was Foxp3+, resulting in equivalent immunity to direct immunization. Depletion of maternal Foxp3+ cells from pup splenocytes illustrated a substantial role for lactationally transferred dam regulatory T cells in suppression of the ex vivo response in FVB/NJ, but not BALB/cJ, recipients. We conclude that lactational transfer of immunity can cross MHC class I barriers and that Th1 immunity can be imparted to Th2-biased offspring; in some instances, it can be greater than that achieved by direct immunization.

Context. Up to now, mostly relatively simple molecules have been detected in interstellar diffuse molecular clouds in our galaxy, but more complex species have been reported in the diffuse/translucent medium of a z = 0 : 89 spiral galaxy. Aims. We aim at searching for complex organic molecules (COMs) in diffuse molecular clouds along the line of sight to Sgr B2(N), taking advantage of the high sensitivity and angular resolution of the Atacama Large Millimeter/submillimeter Array (ALMA). Methods. We use data acquired as part of the EMoCA survey performed with ALMA. To analyse the absorption features of the molecules detected towards the ultracompact H II region K4 in Sgr B2(N), we calculate synthetic spectra for these molecules and fit their column densities, line widths, centroid velocities, and excitation temperatures. Results. We report the detection of CH3OH, CH3CN, CH3CHO, HC3N, and NH2CHO in Galactic center (GC) diffuse clouds and CH3OH and CH3CN in a diffuse cloud in the Scutum arm. The chemical composition of one of the diffuse GC clouds is found to be similar to the one of the diffuse/translucent medium of the z = 0 : 89 spiral galaxy. Conclusions. The chemical processes leading to chemical complexity in the diffuse molecular ISM appear to have remained similar since z = 0.89. As proposed in previous studies, the presence of COMs in diffuse molecular clouds may result from a cyclical interstellar process of cloud contraction and expansion between diffuse and dense states.

We report the crystal structure of dolomite-IV, a high-pressure polymorph of Fe-dolomite stabilized at 115 GPa and 2500 K. It is orthorhombic, space group Pnma, a =10.091(3), b = 8.090(7), c = 4.533(3) Å, V = 370.1(4) Å3 at 115.2 GPa and ambient temperature. The structure is based on the presence of threefold C3O9 carbonate rings, with carbon in tetrahedral coordination. The starting Fe-dolomite single crystal during compression up to 115 GPa transforms into dolomite-II (at 17 GPa) and dolomite-IIIb (at 36 GPa). The dolomite-IIIb, observed in this study, is rhombohedral, space group R3, a =11.956(3), c =13.626(5) Å, V =1686.9(5) Å3 at 39.4 GPa. It is different from a previously determined dolomite-III structure, but topologically similar. The density increase from dolomite-IIIb to dolomite IV is ca. 3%. The structure of dolomite-IV has not been predicted, but it presents similarities with the structural models proposed for the high-pressure polymorphs of magnesite, MgCO3. A ring-carbonate structure match with spectroscopic analysis of high-pressure forms of magnesite-siderite reported in the literature, and, therefore, is a likely candidate structure for a carbonate at the bottom of the Earth's mantle, at least for magnesitic and dolomitic compositions.