Bedding control on landslides: A methodological approach for computer-aided mapping analysis

Litho-structural control on the spatial and temporal evolution of landslides is one of the major typical aspects on slopes constituted of structurally complex sequences. Mainly focused on instabilities of the earth flow type, a semi-quantitative analysis has been developed with the purpose of identifying and characterizing litho-structural control exerted by bedding on slopes and its effects on landsliding. In quantitative terms, a technique for azimuth data interpolation, Non-continuous Azimuth Distribution Methodological Approach (NADIA), is presented by means of a GIS software application. In addition, processed by NADIA, two indexes have been determined: (i) Δ, aimed at defining the relationship between the orientation of geological bedding planes and slope aspect, and (ii) C, which recognizes localized slope sectors in which the stony component of structurally complex formations is abundant and therefore operates an evolutive control of landslide masses. Furthermore, some Litho-Structural Models (LSMs) of slopes are proposed aiming at characterizing recurrent forms of structural control in the source, channel and deposition areas of gravitational movements. In order to elaborate evolutive models controlling landslide scenarios, LSMs were qualitatively related and compared with Δ and C; quantitative indexes. The methodological procedure has been applied to a lithostructurally complex area of Southern Italy where data about azimuth measurements and landslide mapping were known. It was found that the proposed methodology enables the recognition of typical control conditions on landslides in relation to the LSMs. Different control patterns on landslide shape and on style and distribution of the activity resulted for each LSM. This provides the possibility for first-order identification to be made of the spatial evolution of landslide bodies. © Author(s) 2011

A hybrid model for mapping simplified seismic response via a GIS-metamodel approach

In earthquake-prone areas, site seismic response due to lithostratigraphic sequence plays a key role in seismic hazard assessment. A hybrid model, consisting of GIS and metamodel (model of model) procedures, was introduced aimed at estimating the 1-D spatial seismic site response in accordance with spatial variability of sediment parameters. Inputs and outputs are provided and processed by means of an appropriate GIS model, named GIS Cubic Model (GCM). This consists of a block-layered parametric structure aimed at resolving a predicted metamodel by means of pixel to pixel vertical computing. The metamodel, opportunely calibrated, is able to emulate the classic shape of the spectral acceleration response in relation to the main physical parameters that characterize the spectrum itself. Therefore, via the GCM structure and the metamodel, the hybrid model provides maps of normalized acceleration response spectra. The hybrid model was applied and tested on the built-up area of the San Giorgio del Sannio village, located in a high-risk seismic zone of southern Italy. Efficiency tests showed a good correspondence between the spectral values resulting from the proposed approach and the 1-D physical computational models. Supported by lithology and geophysical data and corresponding accurate interpretation regarding modelling, the hybrid model can be an efficient tool in assessing urban planning seismic hazard/risk. © Author(s) 2014

Kinematic Segmentation and Velocity in Earth Flows: A Consequence of Complex Basal-slip Surfaces

Abstract We investigated relations between geomorphic structures, movement velocity, and basal-slip surface geometry within individual kinematic domains of two large earth flows in the Apennine Mountains of southern Italy: the "Montaguto" earth flow and the "Mount Pizzuto" earth flow. Our analyses indicated that the earth flows are composed of distinct kinematic zones characterized by specific deformational patterns and longitudinal velocity profiles. Variations in velocity within individual kinematic zones is controlled by the geometry of the basal-slip surface, and, in particular by local variations in slope angle. Slip-surface geometry and slope also seem to control the density of extensional structures in driving earth-flow elements

Remote sensing monitoring of the Pietrafitta earth flows in Southern Italy. An integrated approach based on multi-sensor data

Earth flows are complex gravitational events characterised by a heterogeneous displacement pattern in terms of scale, style, and orientation. As a result, their monitoring, for both knowledge and emergency purposes, represents a relevant challenge in the field of engineering geology. This paper aims to assess the capabilities, peculiarities, and limitations of different remote sensing monitoring techniques through their application to the Pietrafitta earth flow (Southern Italy). The research compared and combined data collected during the main landslide reactivations by different ground-based remote sensors such as Robotic Total Station (R-TS), Terrestrial Synthetic Aperture Radar Interferometry (T-InSAR), and Terrestrial Laser Scanner (TLS), with data being derived by satellite-based Digital Image Correlation (DIC) analysis. The comparison between R-TS and T-InSAR measurements showed that, despite their different spatial and temporal resolutions, the observed deformation trends remain approximately coherent. On the other hand, DIC analysis was able to detect a kinematic process, such as the expansion of the landslide channel, which was not detected by the other techniques used. The results suggest that, when faced with complex events, the use of a single monitoring technique may not be enough to fully observe and understand the processes taking place. Therefore, the limitations of each different technique alone can be solved by a multi-sensor monitoring approach

Mycobacterium tuberculosis Surgical Site Infection after Cardiac Surgery in the COVID-19 Era: A Case Report

Infection of surgical wounds with acid-fast bacilli, including tubercle bacilli, is rare, and is poorly described in the literature. We present the case of a 74-year-old male who developed a sternal wound infection after cardiac surgery due to Mycobacterium tuberculosis complex, diagnosed post-mortem. SARS-CoV-2 infection contributed to worsened clinical conditions and surgical site infection. A high degree of suspicion to avoid unnecessary treatments and progression to severe disease with dismal prognosis is necessary in these types of infections

Esbl/ampc-producing escherichia coli in wild boar: Epidemiology and risk factors

The complex health problem of antimicrobial resistance (AMR) involves many host species, numerous bacteria and several routes of transmission. Extended-spectrum β-lactamase and AmpC (ESBL/AmpC)-producing Escherichia coli are among the most important strains. Moreover, wildlife hosts are of interest as they are likely antibiotics free and are assumed as environmental indicators of AMR contamination. Particularly, wild boar (Sus scrofa) deserves attention because of its increased population densities, with consequent health risks at the wildlife–domestic–human interface, and the limited data available on AMR. Here, 1504 wild boar fecal samples were microbiologically and molecularly analyzed to investigate ESBL/AmpC-producing E. coli and, through generalized linear models, the effects of host-related factors and of human population density on their spread. A prevalence of 15.96% of ESBL/AmpC-producing E. coli, supported by blaCTX-M (12.3%), blaTEM (6.98%), blaCMY (0.86%) and blaSHV (0.47%) gene detection, emerged. Young animals were more colonized by ESBL/AmpC strains than older subjects, as observed in domestic animals. Increased human population density leads to increased blaTEM prevalence in wild boar, suggesting that spatial overlap may favor this transmission. Our results show a high level of AMR contamination in the study area that should be further investigated. However, a role of wild boar as a maintenance host of AMR strains emerged

The use of antimicrobials in italian heavy pig fattening farms

Data on antimicrobial use (AMU) in heavy pig production (>150 kg) are limited. The aim of this study was to investigate the AMU in this production. Data from 2015 were collected for 143 fattening farms. The AMU was estimated through a treatment index per 100 days (TI100) using the defined daily dose animal for Italy (DDDAit). When possible, a comparison with the European Medicines Agency’s defined daily doses for animals (DDDvet) was performed. The median TI100 was 10.7 (range, 0.2–49.5). Group treatments represented 94.6% of overall consumption. The AMU calculated using DDDAit and DDDvet were strongly correlated (ρ = 0.976; p < 0.001). The AMU was negatively correlated with injectables use (ρ = −0.46, p < 0.001) and positively correlated with oral products (ρ = 0.21, p = 0.014), premixes (ρ = 0.26, p = 0.002), and mortality (ρ = 0.18; p = 0.027). Farm size was negatively correlated with AMU (ρ = −0.29, p < 0.001). Smaller farms were more frequently above the median TI100 (odds ratio = 2.3, 95% confidence interval = 1.2–4.7), suggesting that they may have lower biosecurity and management standards. The results of this study should provide useful insights for the development of an Italian monitoring system

Emerging therapies in pheochromocytoma and paraganglioma: Immune checkpoint inhibitors in the starting blocks

Pheochromocytoma and paraganglioma are neuroendocrine neoplasms, originating in the adrenal medulla and in parasympathetic and sympathetic autonomic nervous system ganglia, respec-tively. They usually present as localized tumours curable with surgery. However, these tumours may exhibit heterogeneous clinical course, ranging from no/minimal progression to aggressive (progres-sive/metastatic) behavior. For this setting of patients, current therapies are unsatisfactory. Immune checkpoint inhibitors have shown outstanding results for several types of solid cancers. We therefore aimed to summarize and discuss available data on efficacy and safety of current FDA-approved immune checkpoint inhibitors in patients with pheochromocytoma and paraganglioma. After an extensive search, we found 15 useful data sources (four full-published articles, four supplements of scientific journals, seven ongoing registered clinical trials). The data we detected, even with the limit of the small number of patients treated, make a great expectation on the therapeutic use of immune checkpoint inhibitors. Besides, the newly detected predictors of response will (hopefully) be of great helps in selecting the subset of patients that might benefit the most from this class of drugs. Finally, new trials are in the starting blocks, and they are expected to shed in the next future new light on a therapy, which is considered a milestone in oncology

Machine learning assisted DSC-MRI radiomics as a tool for glioma classification by grade and mutation status

Background: Combining MRI techniques with machine learning methodology is rapidly gaining attention as a promising method for staging of brain gliomas. This study assesses the diagnostic value of such a framework applied to dynamic susceptibility contrast (DSC)-MRI in classifying treatment-naïve gliomas from a multi-center patients into WHO grades II-IV and across their isocitrate dehydrogenase (IDH) mutation status. Methods: Three hundred thirty-three patients from 6 tertiary centres, diagnosed histologically and molecularly with primary gliomas (IDH-mutant = 151 or IDH-wildtype = 182) were retrospectively identified. Raw DSC-MRI data was post-processed for normalised leakage-corrected relative cerebral blood volume (rCBV) maps. Shape, intensity distribution (histogram) and rotational invariant Haralick texture features over the tumour mask were extracted. Differences in extracted features across glioma grades and mutation status were tested using the Wilcoxon two-sample test. A random-forest algorithm was employed (2-fold cross-validation, 250 repeats) to predict grades or mutation status using the extracted features. Results: Shape, distribution and texture features showed significant differences across mutation status. WHO grade II-III differentiation was mostly driven by shape features while texture and intensity feature were more relevant for the III-IV separation. Increased number of features became significant when differentiating grades further apart from one another. Gliomas were correctly stratified by mutation status in 71% and by grade in 53% of the cases (87% of the gliomas grades predicted with distance less than 1). Conclusions: Despite large heterogeneity in the multi-center dataset, machine learning assisted DSC-MRI radiomics hold potential to address the inherent variability and presents a promising approach for non-invasive glioma molecular subtyping and grading

Efficacy of three neuroprotective drugs in secondary progressive multiple sclerosis (MS-SMART):a phase 2b, multiarm, double-blind, randomised placebo-controlled trial

Neurodegeneration is the pathological substrate that causes major disability in secondary progressive multiple sclerosis. A synthesis of preclinical and clinical research identified three neuroprotective drugs acting on different axonal pathobiologies. We aimed to test the efficacy of these drugs in an efficient manner with respect to time, cost, and patient resource. Methods: We did a phase 2b, multiarm, parallel group, double-blind, randomised placebo-controlled trial at 13 clinical neuroscience centres in the UK. We recruited patients (aged 25-65 years) with secondary progressive multiple sclerosis who were not on disease-modifying treatment and who had an Expanded Disability Status Scale (EDSS) score of 4·0-6·5. Participants were randomly assigned (1:1:1:1) at baseline, by a research nurse using a centralised web-based service, to receive twice-daily oral treatment of either amiloride 5 mg, fluoxetine 20 mg, riluzole 50 mg, or placebo for 96 weeks. The randomisation procedure included minimisation based on sex, age, EDSS score at randomisation, and trial site. Capsules were identical in appearance to achieve masking. Patients, investigators, and MRI readers were unaware of treatment allocation. The primary outcome measure was volumetric MRI percentage brain volume change (PBVC) from baseline to 96 weeks, analysed using multiple regression, adjusting for baseline normalised brain volume and minimisation criteria. The primary analysis was a complete-case analysis based on the intention-to-treat population (all patients with data at week 96). This trial is registered with ClinicalTrials.gov, NCT01910259