The biology of malignant breast tumors has an impact on the presentation in ultrasound: an analysis of 315 cases

BACKGROUND: The aim of this study was to evaluate the relation of some ultrasound morphological parameters to biological characteristics in breast carcinoma. METHODS: Ultrasound data from 315 breast masses were collected. We analyzed the ultrasound features of the tumors according to the ACR BI-RADS®-US classification system stratified by hormone receptor status, HER2 status, histology grade, tumor type (ductal versus lobular), triple-negativity, breast density, tumor size, lymph node involvement and patient’s age. RESULTS: We found a variety of ultrasound features that varied between the groups. Invasive lobular tumors were more likely to have an angulated margin (39% versus 22%, p = 0.040) and less likely to show posterior acoustic enhancement (3% versus 16%, p = 0.023) compared to invasive ductal carcinoma. G3 tumors were linked to a higher chance of posterior acoustic enhancement and less shadowing and the margin of G3 tumors was more often described as lobulated or microlobulated compared to G1/G2 tumors (67% versus 46%, p = 0.001). Tumors with an over-expression of HER2 exhibited a higher rate of architectural distortions in the surrounding tissue, but there were no differences regarding the other features. Hormone receptor negative tumors were more likely to exhibit a lobulated or microlobulated margin (67% versus 50%, p = 0.037) and less likely to have an echogenic halo (39% versus 64%, p = 0.001). Furthermore, the posterior acoustic feature was more often described as enhancement (33% versus 13%, p = 0.001) and less often as shadowing (20% versus 47%, p < 0.001) compared to hormone receptor positive tumors. CONCLUSION: Depending on their biological and clinical profile, breast cancers are more or less likely to exhibit the typical criteria for malignancy in ultrasound. Moreover, certain types of breast cancer tend to possess criteria that are usually associated with benign masses. False-negative diagnosis may result in serious consequences for the patient. For the sonographer it is essential to be well aware of potential variations in the ultrasound morphology of breast tumors, as described in this paper

Bridge-specific fragility analysis: when is it really necessary?

In seismic assessment of bridges the research focus has recently shifted on the derivation of bridge-specific fragility curves that account for the effect of different geometry, structural system, component and soil properties, on the seismic behaviour. In this context, a new, component-based methodology for the derivation of bridge-specific fragility curves has been recently proposed by the authors, with a view to overcoming the inherent difficulties in assessing all bridges of a road network and the drawbacks of existing methodologies, which use the same group of fragility curves for bridges within the same typological class. The main objective of this paper is to critically assess the necessity of bridge-specific fragility analysis, starting from the effect of structure-specific parameters on component capacity (limit state thresholds), seismic demand, and fragility curves. The aforementioned methodology is used to derive fragility curves for all bridges within an actual road network, with a view to investigating the consistency of adopting generic fragility curves for bridges that fall within the same class and quantifying the degree of over- or under-estimation of the probability of damage when generic bridge classes are considered. Moreover, fragility curves for all representative bridges of the analysed concrete bridge classes are presented to illustrate the differentiation in bridge fragility for varying structural systems, bridge geometry, total bridge length and maximum pier height. Based on the above, the relevance of bridge-specific fragility analysis is assessed, and pertinent conclusions are drawn

Loneliness in early psychosis: a qualitative study exploring the views of mental health practitioners in early intervention services

BACKGROUND: Loneliness is an important public health problem with established adverse effects on physical and mental health. Although people with psychosis often experience high levels of loneliness, relatively little is known about the relationship between loneliness and early psychosis. Potential interventions to address loneliness might be easier to implement early in the illness when social networks and social skills may be more intact than at a later stage. We investigated the views of mental health practitioners about the context and causes of loneliness in people with early psychosis, and about potential interventions. METHODS: Semi-structured face-to-face interviews were conducted with mental health practitioners (n = 20). Participants were purposively recruited from four early intervention services for first-episode psychosis in the UK. Interviews were transcribed verbatim and thematic analysis was conducted. RESULTS: Participants believed that the majority of service users with early psychosis experience feelings of loneliness. They often saw socially isolated and disconnected clients and believed them to be lonely, but rarely discussed loneliness explicitly in clinical interactions. A combination of symptoms, stigma and negative sense of self were believed to underpin loneliness. Participants could not identify any specific current interventions delivered by their services for tackling loneliness, but thought some routinely provided interventions, including social groups and psychological treatments, could be helpful. They favoured making a wider range of loneliness interventions available and believed that community agencies beyond mental health services should be involved to make these effective and feasible to deliver. They suggested social participation interventions without an explicit mental health focus as potentially promising and valued a co-produced approach to intervention development. CONCLUSIONS: This study suggests that loneliness is not routinely discussed in early intervention services, and a targeted strategy for tackling it is lacking. Co-produced, individualised community approaches, and interventions that target symptoms, stigma and negative self-schemas might be beneficial in alleviating loneliness for people with early psychosis. Empirical research is needed to develop and test such interventions

Seismic Risk of Inter-urban Transportation Networks

AbstractThe paper presents a holistic approach for assessing and managing the seismic risk and potential loss in inter-urban highway networks in earthquake-prone areas. The vulnerability of all elements of the intercity transportation system (i.e., roads, bridges, abutments, retaining walls, and tunnels) is assessed considering the interdependency among the structural, transportational and geotechnical components of the network under different seismic scenarios. Both the direct earthquake-induced damage, as well as the indirect socio-economic loss attributed to reduced network functionality are taken into account in an explicit and transparent formulation that is then displayed in space through an ad-hoc developed GIS-based software. The methodology and the decision-making tools developed are adequately modular, for them to be utilized after appropriate adaptation by local authorities in identifying, prior to a major earthquake event, those vulnerable components of their network whose failure may have a disproportional socio-economic impact. In this way, a rational and effective emergency plan can be deployed to minimize potential human, social and financial loss after a future earthquake. The outline of a foreseen application is also presented for the case of the road network of the Region of Western Macedonia in Greece. Through this pilot application, the methodology is to be optimized in real conditions before being cast in the form of a fully parameterised seismic risk tool, to be used in other earthquake prone areas as well

Multi-hazard fragility assessment of bridges: Methodology and case study application

Reliability of road systems and their critical components exposed to multiple natural hazards is on the frontline of engineering research during the last three decades since potential damage of infrastructure is strongly related to important direct and indirect economic losses. In this context, the research project INFRARES (www.infrares.gr) aims at delivering a comprehensive methodology towards a more efficient risk and resilience assessment of roadway networks in Greece subjected to various natural hazards. In this context, an analytical framework for the fragility assessment of bridges subjected to independent and/or multiple subsequent natural hazards, is proposed herein and applied to a case study bridge. The proposed methodology includes the estimation of seismic and flood fragility and the development of multihazard fragility curves. The proposed approach considers multiple structural components for the development of fragility curves, which are generated based on case-specific estimation of limit state thresholds accounting for multiple failure modes and SSI effects. A probabilistic framework is introduced to account for the uncertainties in the demand and capacity in case of single hazards, which is then extended for multiple -separate and/or subsequent- hazards, highlighting the effect of cumulative damage on the fragility assessment. The proposed methodology is applied to a case study bridge in Greece, considering multiple hazards, separate in time (i.e. two subsequent flood events). The results in terms of flood fragility curves are discussed with a view to evaluate the effect of damage accumulation in multiple hazard analysis; the probability of damage was found to drastically increase for all limit states considered

Recent Advances in Seismic Vulnerability Assessment of Tunnels and Underground Structures

Tunnels and underground structures are constructed at an increasing rate in seismic prone areas to facilitate expanding transportation needs. The importance of these types of structures in modern societies, as well as the significant downtimes associated with seismically induced damage on them, led to an increasing interest of the scientific community and practitioners on the vulnerability assessment of this infrastructure against seismic hazard. Various methodologies have been recently proposed to estimate the vulnerability of bored tunnels in rock or alluvial and cut and cover or underground structures, e.g., subways, in alluvial, against ground seismic shaking and earthquake induced ground failures. This paper discusses critical aspects of these methodologies, based on a thorough review of relevant state-of-the art, carried out in the frame of research project INFRARES (www.infrares.gr). Emphasis is placed on the numerical tools employed to estimate analytically the fragility of examined structures in relevant studies, the constitutive models used to simulate the seismic response of ground and structures, the determination of the capacity of examined structures, the selection of appropriate seismic intensity measures, methods used to develop rational probabilistic seismic demand models, the estimation of uncertainties related to seismic vulnerability of underground structures, as well as the methods for selecting fragility functions from existing ones in assessment studies of actual case studies. Through the discussion, acknowledged gaps in the literature are highlighted and topics calling for further investigation are presented. In addition, an up-to-date database of available fragility functions for tunnels and underground structures developed within INFRARES is presented

Phytoplankton Blooms, Red Tides and Mucilaginous Aggregates in the Urban Thessaloniki Bay, Eastern Mediterranean

We investigated the plankton community composition and abundance in the urban marine environment of Thessaloniki Bay. We collected water samples weekly from March 2017 to February 2018 at the coastal front of Thessaloniki city center and monthly samples from three other inshore sites along the urban front of the bay. During the study period, conspicuous and successive phytoplankton blooms, dominated by known mucilage-producing diatoms alternated with red tide events formed by the dinoflagellates Noctiluca scintillans and Spatulodinium pseudonoctiluca, and an extensive mucilage aggregate phenomenon, which appeared in late June 2017. At least 11 known harmful algae were identified throughout the study, with the increase in the abundance of the known harmful dinoflagellate Dinophysis cf. acuminata occurring in October and November 2017. Finally, a red tide caused by the photosynthetic ciliate Mesodinium rubrum on December 2017 was conspicuous throughout the sampling sites. The above-mentioned harmful blooms and red tides were linked to high nutrient concentrations and eutrophication. This paper provides an overview of eutrophication impacts on the response of the unicellular eukaryotic plankton organisms and their impact on water quality and ecosystem service

Incidence of seizures following initial ischemic stroke in a community-based cohort: The Framingham Heart Study

Purpose We examined the incidence of seizures following ischemic stroke in a community-based sample. Methods All subjects with incident ischemic strokes in the Framingham Original and Offspring cohorts between 1982 and 2003 were identified and followed for up to 20 years to determine incidence of seizures. Seizure-type was based on the 2010 International League Against Epilepsy (ILAE) classification. Disability was stratified into mild/none, moderate and severe, based on post-stroke neurological deficit documentation according to the Framingham Heart Study (FHS) protocol and functional status was determined using the Barthel Index. Results An initial ischemic stroke occurred in 469 subjects in the cohort and seizures occurred in 25 (5.3%) of these subjects. Seizure incidence was similar in both large artery atherosclerosis (LAA) (6.8%) and cardio-embolic (CE) (6.2%) strokes. No seizures occurred following lacunar strokes. The predominant seizure type was focal seizure with or without evolution to bilateral convulsive seizure. One third of participants had seizures within the first 24 h from stroke onset and half of all seizures occurred within the first 30 days. On multivariate analysis, moderate and severe disability following stroke was associated with increased risk of incident seizure. Conclusions Seizures occurred in approximately 5% of subjects after an ischemic stroke. One third of these seizures occurred in the first 24 h after stroke and none followed lacunar strokes. Focal seizures with or without evolution in bilateral convulsive seizures were the most common seizure type. Moderate and severe disability was predictive of incident seizures

Machine learning techniques for the estimation of limit state thresholds and bridge-specific fragility analysis of R/C bridges

Based on past earthquake events, bridges are the most critical and usually the most vulnerable components of road and rail transport systems, while bridge damage is related to substantial direct and indirect losses. In view of this, the need for direct and reliable assessment of bridge vulnerability has emerged, and several methodologies have been developed using probabilistic analysis for the derivation of fragility curves. A new framework for the derivation of bridge-specific fragility curves is proposed herein, introducing machine learning techniques for a reliable estimation of limit state thresholds of the most critical component of the bridge system (which in standard -ductility based- design is the piers), in terms of a widely used engineering demand parameter, i.e. displacement of control point. A set of parameters affecting the seismic capacity and the failure modes of bridge piers is selected, including geometry, material properties, and reinforcement ratios for cylindrical piers. Training and test sets are generated from multiple inelastic pushover analyses of the pier component, and Artificial Neural Networks (ANN) analysis is performed to derive closed-form relationships for the estimation of limit state thresholds. The latter are compared with closed-form relationships available in the literature, highlighting the effect of machine learning techniques on the reliable estimation of bridge fragility curves for all damage states