Cigarette smoke increases BLT2 receptor functions in bronchial epithelial cells: in vitro and ex vivo evidence

Leukotriene B4 (LTB4) is a neutrophil chemotactic molecule with important involvement in the inflammatory responses of chronic obstructive pulmonary disease (COPD). Airway epithelium is emerging as a regulator of innate immune responses to a variety of insults including cigarette smoke, the major risk factor for COPD. In this study we have explored whether cigarette smoke extracts (CSE) or soluble mediators present in distal lung fluid samples (mini-bronchoalveolar lavages) from smokers alter the expression of the LTB4 receptor 2 (BLT2) and peroxisome proliferator- activated receptor-a (PPAR-a) in bronchial epithelial cells. We also evaluated the effects of CSE on the expression of intercellular adhesion molecule 1 (ICAM-1) and on the binding of signal transducer and activator of transcription 1 (STAT-1) to ICAM-1 promoter as well as the adhesiveness of neutrophils to bronchial epithelial cells. CSE and minibronchoalveolar lavages from smokers increased BLT2 and ICAM-1 expression as well as the adhesiveness of neutrophils to bronchial epithelial cells and decreased PPAR-a expression. CSE induced the activation of STAT-1 and its binding to ICAM-1 promoter. These findings suggest that, in bronchial epithelial cells, CSE promote a prevalent induction of pro-inflammatory BLT2 receptors and activate mechanisms leading to increased neutrophil adhesion, a mechanism that contributes to airway neutrophilia and to tissue damage

An automatically generated high-resolution earthquake catalogue for the 2016–2017 Central Italy seismic sequence, including P and S phase arrival times

The 2016–2017 central Italy earthquake sequence began with the first main shock near the town of Amatrice on August 24 (Mw 6.0), and was followed by two subsequent large events near Visso on October 26 (Mw 5.9) and Norcia on October 30 (Mw 6.5), plus a cluster of four events with Mw > 5.0 within few hours on 18 January 2017. The affected area had been monitored before the sequence started by the permanent Italian National Seismic Network (RSNC), and was enhanced during the sequence by temporary stations deployed by the National Institute of Geophysics and Volcanology and the British Geological Survey. By the middle of September, there was a dense network of 155 stations, with a mean separation in the epicentral area of 6–10 km, comparable to the most likely earthquake depth range in the region. This network configuration was kept stable for an entire year, producing 2.5 TB of continuous waveform recordings. Here we describe how this data was used to develop a large and comprehensive earthquake catalogue using the Complete Automatic Seismic Processor (CASP) procedure. This procedure detected more than 450 000 events in the year following the first main shock, and determined their phase arrival times through an advanced picker engine (RSNI-Picker2), producing a set of about 7 million P- and 10 million S-wave arrival times. These were then used to locate the events using a non-linear location (NLL) algorithm, a 1-D velocity model calibrated for the area, and station corrections and then to compute their local magnitudes (ML). The procedure was validated by comparison of the derived data for phase picks and earthquake parameters with a handpicked reference catalogue (hereinafter referred to as ‘RefCat’). The automated procedure takes less than 12 hr on an Intel Core-i7 workstation to analyse the primary waveform data and to detect and locate 3000 events on the most seismically active day of the sequence. This proves the concept that the CASP algorithm can provide effectively real-time data for input into daily operational earthquake forecasts, The results show that there have been significant improvements compared to RefCat obtained in the same period using manual phase picks. The number of detected and located events is higher (from 84 401 to 450 000), the magnitude of completeness is lower (from ML 1.4 to 0.6), and also the number of phase picks is greater with an average number of 72 picked arrival for a ML = 1.4 compared with 30 phases for RefCat using manual phase picking. These propagate into formal uncertainties of ±0.9 km in epicentral location and ±1.5 km in depth for the enhanced catalogue for the vast majority of the events. Together, these provide a significant improvement in the resolution of fine structures such as local planar structures and clusters, in particular the identification of shallow events occurring in parts of the crust previously thought to be inactive. The lower completeness magnitude provides a rich data set for development and testing of analysis techniques of seismic sequences evolution, including real-time, operational monitoring of b-value, time-dependent hazard evaluation and aftershock forecasting

Evaluation of liquefaction triggering potential in Italy: a seismic-hazard-based approach

In the present study, we analyze ground-motion hazard maps and hazard disaggregation in order to define areas in Italy where liquefaction triggering due to seismic activity can not be excluded. To this end, we refer to the triggering criteria (not to be confused with liquefaction susceptibility criteria, which essentially take into account soil type and depth to groundwater) proposed by the Italian Guidelines for Seismic Microzonation, which are described in the main body of the paper. However, the study can be replicated in other countries that adopt different criteria. The final goal is the definition of a screening map for all of Italy that classifies sites in terms of liquefaction triggering potential according to their seismic hazard level. The map, which is referred to with the Italian acronym MILQ – Mappa del potenziale d'Innesco della LiQuefazione (i.e., map of liquefaction triggering potential), and the associated data are freely accessible at the following web address: https://distav.unige.it/rsni/milq.php (last access: 28 April 2023). Our results can be useful to guide land-use planners in deciding whether liquefaction is a hazard that needs to be considered within the planning processes or not. Furthermore, they can serve as a guide for recommending geological and geotechnical investigations aimed at the evaluation of liquefaction hazards or, conversely, rule out further studies with consequent savings in efforts and money.</p

Aptamer-based in vivo therapeutic targeting of glioblastoma

Glioblastoma (GBM) is the most aggressive, infiltrative, and lethal brain tumor in humans. Despite the extensive advancement in the knowledge about tumor progression and treatment over the last few years, the prognosis of GBM is still very poor due to the difficulty of targeting drugs or anticancer molecules to GBM cells. The major challenge in improving GBM treatment implicates the development of a targeted drug delivery system, capable of crossing the blood–brain barrier (BBB) and specifically targeting GBM cells. Aptamers possess many characteristics that make them ideal novel therapeutic agents for the treatment of GBM. They are short single-stranded nucleic acids (RNA or ssDNA) able to bind to a molecular target with high affinity and specificity. Several GBM-targeting aptamers have been developed for imaging, tumor cell isolation from biopsies, and drug/anticancer molecule delivery to the tumor cells. Due to their properties (low immunogenicity, long stability, and toxicity), a large number of aptamers have been selected against GBM biomarkers and tested in GBM cell lines, while only a few of them have also been tested in in vivo models of GBM. Herein, we specifically focus on aptamers tested in GBM in vivo models that can be considered as new diagnostic and/or therapeutic tools for GBM patients’ treatment

Brain energy metabolism: A roadmap for future research

Although we have learned much about how the brain fuels its functions over the last decades, there remains much still to discover in an organ that is so complex. This article lays out major gaps in our knowledge of interrelationships between brain metabolism and brain function, including biochemical, cellular, and subcellular aspects of functional metabolism and its imaging in adult brain, as well as during development, aging, and disease. The focus is on unknowns in metabolism of major brain substrates and associated transporters, the roles of insulin and of lipid droplets, the emerging role of metabolism in microglia, mysteries about the major brain cofactor and signaling molecule NAD+, as well as unsolved problems underlying brain metabolism in pathologies such as traumatic brain injury, epilepsy, and metabolic downregulation during hibernation. It describes our current level of understanding of these facets of brain energy metabolism as well as a roadmap for future research

MUDA: dynamic geophysical and geochemical MUltiparametric DAtabase

In this paper, the new dynamic geophysical and geochemical MUltiparametric DAtabase (MUDA) is presented. MUDA is a new infrastructure of the National Institute of Geophysics and Volcanology (INGV), published online in December 2023, with the aim of archiving and disseminating multiparametric data collected by multidisciplinary monitoring networks. MUDA is a MySQL relational database with a web interface developed in PHP, aimed at investigating possible correlations between seismic phenomena and variations in endogenous and environmental parameters in quasi real time. At present, MUDA collects data from different types of sensors such as hydrogeochemical probes for physical–chemical parameters in waters, meteorological stations, detectors of air radon concentration, diffusive flux of carbon dioxide (CO2) and seismometers belonging both to the National Seismic Network of INGV and to temporary networks installed in the framework of multidisciplinary research projects. MUDA publishes data daily, updated to the previous day, and offers the chance to view and download multiparametric time series selected for different time periods. The resultant dataset provides broad perspectives in the framework of future high-frequency and continuous multiparametric monitoring as a starting point to identify possible seismic precursors for short-term earthquake forecasting. MUDA can be accessed at https://doi.org/10.13127/muda (Massa et al., 2023).</p