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  1. Article: Lung pathophysiology in patients with long COVID-19: one size definitely does not fit all.

    Radovanovic, Dejan / D'Angelo, Edgardo

    ERJ open research

    2023  Volume 9, Issue 2

    Abstract: Despite reduced resting lung volumes ... ...

    Abstract Despite reduced resting lung volumes and
    Language English
    Publishing date 2023-04-17
    Publishing country England
    Document type Editorial ; Comment
    ZDB-ID 2827830-6
    ISSN 2312-0541
    ISSN 2312-0541
    DOI 10.1183/23120541.00052-2023
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Lung pathophysiology in patients with long COVID-19

    Dejan Radovanovic / Edgardo D'Angelo

    ERJ Open Research, Vol 9, Iss

    one size definitely does not fit all

    2023  Volume 2

    Keywords Medicine ; R
    Language English
    Publishing date 2023-04-01T00:00:00Z
    Publisher European Respiratory Society
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article: Isotherm, Thermodynamic and Kinetic Studies of Elemental Sulfur Removal from Mineral Insulating Oils Using Highly Selective Adsorbent.

    Jankovic, Jelena / Lukic, Jelena / Kolarski, Dejan / Veljović, Djordje / Radovanović, Željko / Dimitrijević, Silvana

    Materials (Basel, Switzerland)

    2023  Volume 16, Issue 9

    Abstract: Elemental sulfur ( ... ...

    Abstract Elemental sulfur (S
    Language English
    Publishing date 2023-05-04
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2487261-1
    ISSN 1996-1944
    ISSN 1996-1944
    DOI 10.3390/ma16093522
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  4. Article: Lung Imaging and Artificial Intelligence in ARDS.

    Chiumello, Davide / Coppola, Silvia / Catozzi, Giulia / Danzo, Fiammetta / Santus, Pierachille / Radovanovic, Dejan

    Journal of clinical medicine

    2024  Volume 13, Issue 2

    Abstract: Artificial intelligence (AI) can make intelligent decisions in a manner akin to that of the human mind. AI has the potential to improve clinical workflow, diagnosis, and prognosis, especially in radiology. Acute respiratory distress syndrome (ARDS) is a ... ...

    Abstract Artificial intelligence (AI) can make intelligent decisions in a manner akin to that of the human mind. AI has the potential to improve clinical workflow, diagnosis, and prognosis, especially in radiology. Acute respiratory distress syndrome (ARDS) is a very diverse illness that is characterized by interstitial opacities, mostly in the dependent areas, decreased lung aeration with alveolar collapse, and inflammatory lung edema resulting in elevated lung weight. As a result, lung imaging is a crucial tool for evaluating the mechanical and morphological traits of ARDS patients. Compared to traditional chest radiography, sensitivity and specificity of lung computed tomography (CT) and ultrasound are higher. The state of the art in the application of AI is summarized in this narrative review which focuses on CT and ultrasound techniques in patients with ARDS. A total of eighteen items were retrieved. The primary goals of using AI for lung imaging were to evaluate the risk of developing ARDS, the measurement of alveolar recruitment, potential alternative diagnoses, and outcome. While the physician must still be present to guarantee a high standard of examination, AI could help the clinical team provide the best care possible.
    Language English
    Publishing date 2024-01-05
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2662592-1
    ISSN 2077-0383
    ISSN 2077-0383
    DOI 10.3390/jcm13020305
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  5. Article ; Online: Impact of the COVID-19 Restrictive Measures on Urban Traffic-Related Air Pollution in Serbia

    Slavica Malinović-Milićević / Dejan Doljak / Gorica Stanojević / Milan M. Radovanović

    Frontiers in Environmental Science, Vol

    2022  Volume 10

    Abstract: This study has analyzed the traffic-related change in atmospheric pollutants levels (PM2.5, PM10, CO, NO2, SO2, and O3) caused by the COVID-19 restrictive measures, based on traffic ground-based stations data in urban areas in Serbia. The possible ... ...

    Abstract This study has analyzed the traffic-related change in atmospheric pollutants levels (PM2.5, PM10, CO, NO2, SO2, and O3) caused by the COVID-19 restrictive measures, based on traffic ground-based stations data in urban areas in Serbia. The possible influence of several meteorological factors (temperature, wind, pressure, and humidity), and mobility on the pollutants’ levels were also considered. The obtained results showed a positive correlation of daily NO2 concentrations with mobility and its significant reduction during restrictive measures at all selected monitoring stations. The reduction of NO2 was higher than in other countries (71.1–111.5% for measured, and 49.3–92.6% for “deweathered” data), indicating a high traffic impact on NO2 levels in Serbia. The PM, CO, and SO2 showed a weak correlation with mobility during the period with restrictive measures, which, besides traffic, indicates the significant influence of other sources of their concentration. The O3 concentrations were increased at all measuring stations and are negatively correlated to mobility. Comparison of pollutant concentrations during restriction with the equivalent period in preceding years showed reductions in NO2 and SO2 concentrations. However, compared to previous years, the concentrations of PM2.5, PM10, and CO increased in the period with restrictive measures, indicating lower sensitivity to population mobility and higher dependence on other emission sources. The findings suggest the justification for the use of traffic reduction strategies to improve air quality.
    Keywords air pollution ; traffic ; COVID-19 restrictions ; meteorology ; mobility ; Serbia ; Environmental sciences ; GE1-350
    Subject code 333
    Language English
    Publishing date 2022-05-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Assessing the relationship between cardiovascular and small airway disease and acute events in COPD: The ARCADIA study protocol.

    Rogliani, Paola / Radovanovic, Dejan / Ora, Josuel / Starc, Nadia / Verri, Stefano / Pistocchini, Elena / Calzetta, Luigino

    Pulmonary pharmacology & therapeutics

    2023  Volume 82, Page(s) 102231

    Abstract: The initial alterations of chronic obstructive pulmonary disease (COPD) involve the small airways. Small airway disease (SAD) is related to lung hyperinflation and air trapping. Several lung function tests may detect the presence of SAD, namely forced ... ...

    Abstract The initial alterations of chronic obstructive pulmonary disease (COPD) involve the small airways. Small airway disease (SAD) is related to lung hyperinflation and air trapping. Several lung function tests may detect the presence of SAD, namely forced mid-expiratory flows, residual volume (RV), RV/total lung capacity (TLC) ratio, functional residual capacity, airway resistances obtained with body-plethysmography and oscillometry, and the single-breath nitrogen washout test. Additionally, high-resolution computed tomography can detect SAD. In addition to SAD, COPD is related to cardiovascular disease (CVD) such as heart failure, peripheral vascular disease, and ischemic heart disease. No studies have assessed the relationship between CVD, COPD, and SAD. Therefore, the main objective of the Assessing the Relationship between Cardiovascular and small Airway Disease and Acute events in COPD (ARCADIA) study is to assess the risk of CVD in COPD patients according to SAD in a real-life setting. The correlation between CVD, mortality, and acute exacerbation of COPD (AECOPD) is also evaluated. ARCADIA is a 52-week prospective, multicentre, pilot, observational, cohort study conducted in ≥22 pulmonary centres in Italy and that enrols ≥500 COPD patients, regardless of disease severity (protocol registration: ISRCTN49392136). SAD is evaluated at baseline, after that CVD, mortality, and AECOPD are recorded at 6 and 12 months. Bayesian inference is used to quantify the risk and correlation of the investigated outcomes in COPD patients according to SAD. The ARCADIA study provides relevant findings in the daily clinical management of COPD patients.
    MeSH term(s) Humans ; Asthma ; Bayes Theorem ; Cardiovascular Diseases/epidemiology ; Cardiovascular Diseases/etiology ; Cohort Studies ; Forced Expiratory Volume ; Lung ; Prospective Studies ; Pulmonary Disease, Chronic Obstructive
    Language English
    Publishing date 2023-07-04
    Publishing country England
    Document type Journal Article ; Multicenter Study ; Observational Study ; Research Support, Non-U.S. Gov't
    ZDB-ID 1399707-5
    ISSN 1522-9629 ; 1094-5539
    ISSN (online) 1522-9629
    ISSN 1094-5539
    DOI 10.1016/j.pupt.2023.102231
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2389: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  7. Article ; Online: Building Low-Cost Sensing Infrastructure for Air Quality Monitoring in Urban Areas Based on Fog Computing.

    Popović, Ivan / Radovanovic, Ilija / Vajs, Ivan / Drajic, Dejan / Gligorić, Nenad

    Sensors (Basel, Switzerland)

    2022  Volume 22, Issue 3

    Abstract: Because the number of air quality measurement stations governed by a public authority is limited, many methodologies have been developed in order to integrate low-cost sensors and to improve the spatial density of air quality measurements. However, at ... ...

    Abstract Because the number of air quality measurement stations governed by a public authority is limited, many methodologies have been developed in order to integrate low-cost sensors and to improve the spatial density of air quality measurements. However, at the large-scale level, the integration of a huge number of sensors brings many challenges. The volume, velocity and processing requirements regarding the management of the sensor life cycle and the operation of system services overcome the capabilities of the centralized cloud model. In this paper, we present the methodology and the architectural framework for building large-scale sensing infrastructure for air quality monitoring applicable in urban scenarios. The proposed tiered architectural solution based on the adopted fog computing model is capable of handling the processing requirements of a large-scale application, while at the same time sustaining real-time performance. Furthermore, the proposed methodology introduces the collection of methods for the management of edge-tier node operation through different phases of the node life cycle, including the methods for node commission, provision, fault detection and recovery. The related sensor-side processing is encapsulated in the form of microservices that reside on the different tiers of system architecture. The operation of system microservices and their collaboration was verified through the presented experimental case study.
    MeSH term(s) Air Pollution ; Cloud Computing
    Language English
    Publishing date 2022-01-28
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s22031026
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  8. Article ; Online: Prediction of tropospheric ozone concentration using artificial neural networks at traffic and background urban locations in Novi Sad, Serbia.

    Malinović-Milićević, Slavica / Vyklyuk, Yaroslav / Stanojević, Gorica / Radovanović, Milan M / Doljak, Dejan / Ćurčić, Nina B

    Environmental monitoring and assessment

    2021  Volume 193, Issue 2, Page(s) 84

    Abstract: In this paper, we described generation and performances of feedforward neural network models that could be used for a day ahead predictions of the daily maximum 1-h ozone concentration ( ... ...

    Abstract In this paper, we described generation and performances of feedforward neural network models that could be used for a day ahead predictions of the daily maximum 1-h ozone concentration (1hO
    MeSH term(s) Air Pollutants/analysis ; Environmental Monitoring ; Forecasting ; Meteorology ; Neural Networks, Computer ; Ozone/analysis ; Serbia
    Chemical Substances Air Pollutants ; Ozone (66H7ZZK23N)
    Language English
    Publishing date 2021-01-26
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 782621-7
    ISSN 1573-2959 ; 0167-6369
    ISSN (online) 1573-2959
    ISSN 0167-6369
    DOI 10.1007/s10661-020-08821-1
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    In stock of ZB MED Bonn / Germany

    Z 5186: Show issues

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  9. Article: Sublobar resection: functional evaluation and pathophysiological considerations.

    Santus, Pierachille / Franceschi, Elisa / Radovanovic, Dejan

    Journal of thoracic disease

    2020  Volume 12, Issue 6, Page(s) 3363–3368

    Abstract: To date, pulmonary function tests (PFTs) are part of consolidated standard operating procedures in thoracic surgery. PFTs are usually used to assess the pre-operative risk, post-operative outcomes and complications after pulmonary resections. The only ... ...

    Abstract To date, pulmonary function tests (PFTs) are part of consolidated standard operating procedures in thoracic surgery. PFTs are usually used to assess the pre-operative risk, post-operative outcomes and complications after pulmonary resections. The only functional parameter used in common practice is the forced expiratory volume in one second (FEV
    Language English
    Publishing date 2020-03-12
    Publishing country China
    Document type Journal Article ; Review
    ZDB-ID 2573571-8
    ISSN 2077-6624 ; 2072-1439
    ISSN (online) 2077-6624
    ISSN 2072-1439
    DOI 10.21037/jtd.2019.12.35
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  10. Article ; Online: Unrecognized neuromyelitis optica spectrum disorder with pontine and corpus callosum microhemorrhage

    Nosek Igor / Boban Jasmina / Vlahović Dmitar / Radovanović Biljana / Kostić Dejan / Kozić Duško

    Vojnosanitetski Pregled, Vol 79, Iss 12, Pp 1270-

    2022  Volume 1273

    Abstract: Introduction. Neuromyelitis optica spectrum disorder (NMOSD) represents an immune-mediated neuroinflammatory syndrome, classified as a separate entity after the discovery of aquaporin-4 immunoglobulin G (anti-AQP4-IgG). The magnetic resonance ... ...

    Abstract Introduction. Neuromyelitis optica spectrum disorder (NMOSD) represents an immune-mediated neuroinflammatory syndrome, classified as a separate entity after the discovery of aquaporin-4 immunoglobulin G (anti-AQP4-IgG). The magnetic resonance neuroimaging spectrum of NMOSD classically consists of bilateral optic neuritis and longitudinally extensive transverse myelitis (LETM), recently broadened with lesions in area postrema, diencephalon, brainstem and cerebellum, and extensive cord atrophy. Case report. The case presents an anti-AQP4 autoantibody-positive 65-year-old female patient who initially presented with underestimated LETM and developed multiple cerebral and cerebellar lytic demyelinating lesions associated with acute long segment op-tic nerve involvement two years later. Two new imaging findings were described in this case: the involvement of a complete cross-sectional area of pons and microhemorrhage in the pons and corpus callosum. Conclusion. Raising suspicion of NMOSD is of crucial importance in cases with isolated LETM in order to prevent relapses in anti-AQP4-IgG positive cases and improve patient outcomes and recovery.
    Keywords anti-aquaporin 4 autoantibody ; magnetic resonance imaging ; neuroinflammatory diseases ; neuromyelitis optica ; treatment outcome ; Medicine (General) ; R5-920
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher Military Health Department, Ministry of Defance, Serbia
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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