Preconditioning-induced ischemic tolerance: a window into endogenous gearing for cerebroprotection

Ischemic tolerance defines transient resistance to lethal ischemia gained by a prior sublethal noxious stimulus (i.e., preconditioning). This adaptive response is thought to be an evolutionarily conserved defense mechanism, observed in a wide variety of species. Preconditioning confers ischemic tolerance if not in all, in most organ systems, including the heart, kidney, liver, and small intestine. Since the first landmark experimental demonstration of ischemic tolerance in the gerbil brain in early 1990's, basic scientific knowledge on the mechanisms of cerebral ischemic tolerance increased substantially. Various noxious stimuli can precondition the brain, presumably through a common mechanism, genomic reprogramming. Ischemic tolerance occurs in two temporally distinct windows. Early tolerance can be achieved within minutes, but wanes also rapidly, within hours. Delayed tolerance develops in hours and lasts for days. The main mechanism involved in early tolerance is adaptation of membrane receptors, whereas gene activation with subsequent de novo protein synthesis dominates delayed tolerance. Ischemic preconditioning is associated with robust cerebroprotection in animals. In humans, transient ischemic attacks may be the clinical correlate of preconditioning leading to ischemic tolerance. Mimicking the mechanisms of this unique endogenous protection process is therefore a potential strategy for stroke prevention. Perhaps new remedies for stroke are very close, right in our cells

Exploring molecular variation in Schistosoma japonicum in China

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Comparative genomics of the major parasitic worms

Parasitic nematodes (roundworms) and platyhelminths (flatworms) cause debilitating chronic infections of humans and animals, decimate crop production and are a major impediment to socioeconomic development. Here we report a broad comparative study of 81 genomes of parasitic and non-parasitic worms. We have identified gene family births and hundreds of expanded gene families at key nodes in the phylogeny that are relevant to parasitism. Examples include gene families that modulate host immune responses, enable parasite migration though host tissues or allow the parasite to feed. We reveal extensive lineage-specific differences in core metabolism and protein families historically targeted for drug development. From an in silico screen, we have identified and prioritized new potential drug targets and compounds for testing. This comparative genomics resource provides a much-needed boost for the research community to understand and combat parasitic worms

Unusual circulation patterns of the rias baixas induced by minho freshwater intrusion (NW of the Iberian Peninsula)

The Minho River, situated 30 km south of the Rias Baixas, is the most important freshwater source flowing into the Western Galician coast (NW of the Iberian Peninsula). The buoyancy generated by the Minho estuarine plume can reverse the normal circulation pattern inside the Rias Baixas affecting the exchange between the Rias and the ocean, changing the input of nutrients. Nevertheless, this inversion of the circulation patterns is not a well-monitored phenomenon. The only published results based on in situ data related to the presence of the Minho River plume inside the Rias de Vigo and Pontevedra correspond to an event measured on spring 1998. In this case unexpectedly higher inflow surface current velocities were found at the Ria de Pontevedra, located further away from Minho River. Thus, the main aim of this study is to research the main factors inducing this unusual pattern on the circulation of the Rias de Vigo and Pontevedra. A numerical model implementation of MOHID previously developed, calibrated, and validated for this coastal area was used. Several scenarios were performed in order to explain the individual effect of the Minho River, rivers discharging into each Rias, and estuarine morphology changes. According to the model results, the Minho River discharge is a key factor in the establishment of the negative circulation, while small rivers inside the Rias slightly attenuate this circulation. The negative circulation was stronger in Ria de Pontevedra independently of the distance of this coastal system from the Minho River mouth, showing that morphologic estuarine features are the main factor justifying the different local circulation patterns

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties

Design, construction and operation of the ProtoDUNE-SP Liquid Argon TPC

The ProtoDUNE-SP detector is a single-phase liquid argon time projection chamber (LArTPC) that was constructed and operated in the CERN North Area at the end of the H4 beamline. This detector is a prototype for the first far detector module of the Deep Underground Neutrino Experiment (DUNE), which will be constructed at the Sandford Underground Research Facility (SURF) in Lead, South Dakota, U.S.A. The ProtoDUNE-SP detector incorporates full-size components as designed for DUNE and has an active volume of 7 × 6 × 7.2 m3. The H4 beam delivers incident particles with well-measured momenta and high-purity particle identification. ProtoDUNE-SP's successful operation between 2018 and 2020 demonstrates the effectiveness of the single-phase far detector design. This paper describes the design, construction, assembly and operation of the detector components

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between data and simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation