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  1. Article ; Online: Segmental Lung Recruitment in Patients with Bilateral COVID-19 Pneumonia Complicated by Acute Respiratory Distress Syndrome: A Case Report.

    Protić, Alen / Bura, Matej / Šustić, Alan / Brusić, Josip / Sotošek, Vlatka

    Medicina (Kaunas, Lithuania)

    2023  Volume 59, Issue 1

    Abstract: Bilateral COVID-19 pneumonia is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and usually leads to life-threatening acute respiratory distress syndrome (ARDS). Treatment of patients with ARDS is difficult and usually ... ...

    Abstract Bilateral COVID-19 pneumonia is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and usually leads to life-threatening acute respiratory distress syndrome (ARDS). Treatment of patients with ARDS is difficult and usually involves protective mechanical ventilation and various types of recruitment maneuvers. A segmental lung recruitment maneuver by independent lung ventilation has been described as a successful recruitment maneuver in patients with lobar pneumonia, and may, therefore, be useful for the treatment of patients with bilateral COVID-19 pneumonia complicated by ARDS in the critical phase of the disease when all other therapeutic options have been exhausted. The aim of this case series was to present a case report of four mechanically ventilated patients with severe bilateral COVID-19 pneumonia complicated by ARDS using the segmental lung recruitment maneuver. The effect of the segmental lung recruitment maneuver was assessed by the increase in PaO
    MeSH term(s) Humans ; COVID-19/complications ; SARS-CoV-2 ; Respiratory Distress Syndrome/etiology ; Respiratory Distress Syndrome/therapy ; Lung/diagnostic imaging ; Respiration, Artificial/methods
    Language English
    Publishing date 2023-01-11
    Publishing country Switzerland
    Document type Case Reports
    ZDB-ID 2188113-3
    ISSN 1648-9144 ; 1010-660X
    ISSN (online) 1648-9144
    ISSN 1010-660X
    DOI 10.3390/medicina59010142
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Estimating the Effects of Public Health Measures by SEIR(MH) Model of COVID-19 Epidemic in Local Geographic Areas.

    Qiu, Tianyi / Xiao, Han / Brusic, Vladimir

    Frontiers in public health

    2022  Volume 9, Page(s) 728525

    Abstract: The COVID-19 pandemic of 2020-21 has been a major challenge to public health systems worldwide. Mathematical models of epidemic are useful tools for assessment of the situation and for providing decision-making support for relevant authorities. We ... ...

    Abstract The COVID-19 pandemic of 2020-21 has been a major challenge to public health systems worldwide. Mathematical models of epidemic are useful tools for assessment of the situation and for providing decision-making support for relevant authorities. We developed and implemented SEIR(MH) model that extends the conventional SEIR model with parameters that define public lockdown (the level and start of lockdown) and the medical system capacity to contain patients. Comparative modeling of four regions in Europe that have similar population sizes and age structures, but different public health systems, was performed: Baden-Württemberg, Lombardy, Belgium, and Switzerland. Modeling suggests that the most effective measure for controlling epidemic is early lockdown (exponential effect), followed by the number of available hospital beds (linear effect if the capacity is insufficient, with diminishing returns when the capacity is sufficient). Dynamic management of lockdown levels is likely to produce better outcomes than strict lockdown.
    MeSH term(s) COVID-19 ; Communicable Disease Control ; Humans ; Pandemics ; Public Health ; SARS-CoV-2
    Language English
    Publishing date 2022-01-04
    Publishing country Switzerland
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2711781-9
    ISSN 2296-2565 ; 2296-2565
    ISSN (online) 2296-2565
    ISSN 2296-2565
    DOI 10.3389/fpubh.2021.728525
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Multi-AP and Test Point Accuracy of the Results in WiFi Indoor Localization.

    Li, Shuyu / Welsen, Sherif / Brusic, Vladimir

    Sensors (Basel, Switzerland)

    2022  Volume 22, Issue 10

    Abstract: WiFi-based indoor positioning has attracted intensive research activities. While localization accuracy is steadily improving due to the application of advanced algorithms, the factors that affect indoor localization accuracy have not been sufficiently ... ...

    Abstract WiFi-based indoor positioning has attracted intensive research activities. While localization accuracy is steadily improving due to the application of advanced algorithms, the factors that affect indoor localization accuracy have not been sufficiently understood. Most localization algorithms used in changing indoor spaces are Angle-of-Arrival (AoA) based, and they deploy the conventional MUSIC algorithm. The localization accuracy can be achieved by algorithm improvements or joint localization that deploys multiple Access Points (APs). We performed an experiment that assessed the Test Point (TP) accuracy and distribution of results in a complex environment. The testing space was a 290 m2 three-room environment with three APs with 38 TPs. The joint localization using three APs was performed in the same test space. We developed and implemented a new algorithm for improved accuracy of joint localization. We analyzed the statistical characteristics of the results based on each TP and show that the local space-dependent factors are the key factors for localization accuracy. The most important factors that cause errors are distance, obstacles, corner locations, the location of APs, and the angular orientation of the antenna array. Compared with the well-known SpotFi algorithm, we achieved a mean accuracy (across all TPs) improvement of 46%. The unbiased joint localization median accuracy improved by 20% as compared to the best individual localization.
    Language English
    Publishing date 2022-05-12
    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/s22103709
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Dynamically adjustable SVEIR(MH) model of multiwave epidemics: Estimating the effects of public health measures against COVID-19.

    Yin, Zuo-Jing / Xiao, Han / McDonald, Stuart / Brusic, Vladimir / Qiu, Tian-Yi

    Journal of medical virology

    2023  Volume 95, Issue 12, Page(s) e29301

    Abstract: The COVID-19 pandemic was characterized by multiple subsequent, overlapping outbreaks, as well as extremely rapid changes in viral genomes. The information about local epidemics spread and the epidemic control measures was shared on a daily basis (number ...

    Abstract The COVID-19 pandemic was characterized by multiple subsequent, overlapping outbreaks, as well as extremely rapid changes in viral genomes. The information about local epidemics spread and the epidemic control measures was shared on a daily basis (number of cases and deaths) via centralized repositories. The vaccines were developed within the first year of the pandemic. New modes of monitoring and sharing of epidemic data were implemented using Internet resources. We modified the basic SEIR compartmental model to include public health measures, multiwave scenarios, and the variation of viral infectivity and transmissibility reflected by the basic reproduction number R
    MeSH term(s) Humans ; COVID-19/epidemiology ; COVID-19/prevention & control ; Public Health ; Pandemics/prevention & control ; SARS-CoV-2 ; Communicable Disease Control ; Epidemics/prevention & control
    Language English
    Publishing date 2023-12-12
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 752392-0
    ISSN 1096-9071 ; 0146-6615
    ISSN (online) 1096-9071
    ISSN 0146-6615
    DOI 10.1002/jmv.29301
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Protocol for Classification Single-Cell PBMC Types from Pathological Samples Using Supervised Machine Learning.

    Lyu, Minjie / Xin, Lin / Jin, Huan / Chitkushev, Lou T / Zhang, Guanglan / Keskin, Derin B / Brusic, Vladimir

    Methods in molecular biology (Clifton, N.J.)

    2023  Volume 2673, Page(s) 53–67

    Abstract: Peripheral blood mononuclear cells (PBMC) are mixed subpopulations of blood cells composed of five cell types. PBMC are widely used in the study of the immune system, infectious diseases, cancer, and vaccine development. Single-cell transcriptomics (SCT) ...

    Abstract Peripheral blood mononuclear cells (PBMC) are mixed subpopulations of blood cells composed of five cell types. PBMC are widely used in the study of the immune system, infectious diseases, cancer, and vaccine development. Single-cell transcriptomics (SCT) allows the labeling of cell types by gene expression patterns from biological samples. Classifying cells into cell types and states is essential for single-cell analyses, especially in the classification of diseases and the assessment of therapeutic interventions, and for many secondary analyses. Most of the classification of cell types from SCT data use unsupervised clustering or a combination of unsupervised and supervised methods including manual correction. In this chapter, we describe a protocol that uses supervised machine learning (ML) methods with SCT data for the classification of PBMC cell types in samples representing pathological states. This protocol has three parts: (1) data preprocessing, (2) labeling of reference PBMC SCT datasets and training supervised ML models, and (3) labeling new PBMC datasets from disease samples. This protocol enables building classification models that are of high accuracy and efficiency. Our example focuses on 10× Genomics technology but applies to datasets from other SCT platforms.
    MeSH term(s) Humans ; Leukocytes, Mononuclear ; Supervised Machine Learning ; Gene Expression Profiling/methods ; Genomics ; Neoplasms
    Language English
    Publishing date 2023-05-31
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
    ISSN 1940-6029
    ISSN (online) 1940-6029
    DOI 10.1007/978-1-0716-3239-0_4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: TANTIGEN 2.0: a knowledge base of tumor T cell antigens and epitopes.

    Zhang, Guanglan / Chitkushev, Lou / Olsen, Lars Rønn / Keskin, Derin B / Brusic, Vladimir

    BMC bioinformatics

    2021  Volume 22, Issue Suppl 8, Page(s) 40

    Abstract: We previously developed TANTIGEN, a comprehensive online database cataloging more than 1000 T cell epitopes and HLA ligands from 292 tumor antigens. In TANTIGEN 2.0, we significantly expanded coverage in both immune response targets (T cell epitopes and ... ...

    Abstract We previously developed TANTIGEN, a comprehensive online database cataloging more than 1000 T cell epitopes and HLA ligands from 292 tumor antigens. In TANTIGEN 2.0, we significantly expanded coverage in both immune response targets (T cell epitopes and HLA ligands) and tumor antigens. It catalogs 4,296 antigen variants from 403 unique tumor antigens and more than 1500 T cell epitopes and HLA ligands. We also included neoantigens, a class of tumor antigens generated through mutations resulting in new amino acid sequences in tumor antigens. TANTIGEN 2.0 contains validated TCR sequences specific for cognate T cell epitopes and tumor antigen gene/mRNA/protein expression information in major human cancers extracted by Human Pathology Atlas. TANTIGEN 2.0 is a rich data resource for tumor antigens and their associated epitopes and neoepitopes. It hosts a set of tailored data analytics tools tightly integrated with the data to form meaningful analysis workflows. It is freely available at http://projects.met-hilab.org/tadb .
    MeSH term(s) Antigens, Neoplasm/genetics ; Epitopes, T-Lymphocyte/genetics ; HLA Antigens ; Humans ; Knowledge Bases ; Neoplasms/genetics ; T-Lymphocytes
    Chemical Substances Antigens, Neoplasm ; Epitopes, T-Lymphocyte ; HLA Antigens
    Language English
    Publishing date 2021-04-14
    Publishing country England
    Document type Journal Article
    ZDB-ID 2041484-5
    ISSN 1471-2105 ; 1471-2105
    ISSN (online) 1471-2105
    ISSN 1471-2105
    DOI 10.1186/s12859-021-03962-7
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article: The growth of bioinformatics.

    Brusic, Vladimir

    Briefings in bioinformatics

    2007  Volume 8, Issue 2, Page(s) 69–70

    MeSH term(s) Computational Biology/statistics & numerical data ; Computational Biology/trends ; Genomics/statistics & numerical data ; Genomics/trends ; MEDLINE ; Periodicals as Topic/statistics & numerical data ; Periodicals as Topic/trends
    Language English
    Publishing date 2007-03
    Publishing country England
    Document type Editorial
    ZDB-ID 2068142-2
    ISSN 1467-5463
    ISSN 1467-5463
    DOI 10.1093/bib/bbm008
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: A systematic analysis of a broadly neutralizing antibody AR3C epitopes on Hepatitis C virus E2 envelope glycoprotein and their cross-reactivity.

    Sun, Jing / Brusic, Vladimir

    BMC medical genomics

    2015  Volume 8 Suppl 4, Page(s) S6

    Abstract: Background: Hepatitis C virus (HCV) belongs to Flaviviridae family of viruses. HCV represents a major challenge to public health since its estimated global prevalence is 2.8% of the world's human population. The design and development of HCV vaccine has ...

    Abstract Background: Hepatitis C virus (HCV) belongs to Flaviviridae family of viruses. HCV represents a major challenge to public health since its estimated global prevalence is 2.8% of the world's human population. The design and development of HCV vaccine has been hampered by rapid evolution of viral quasispecies resulting in antibody escape variants. HCV envelope glycoprotein E1 and E2 that mediate fusion and entry of the virus into host cells are primary targets of the host immune responses.
    Results: Structural characterization of E2 core protein and a broadly neutralizing antibody AR3C together with E1E2 sequence information enabled the analysis of B-cell epitope variability. The E2 binding site by AR3C and its surrounding area were identified from the crystal structure of E2c-AR3C complex. We clustered HCV strains using the concept of "discontinuous motif/peptide" and classified B-cell epitopes based on their similarity.
    Conclusions: The assessment of antibody neutralizing coverage provides insights into potential cross-reactivity of the AR3C neutralizing antibody across a large number of HCV variants.
    MeSH term(s) Amino Acid Motifs ; Amino Acid Sequence ; Antibodies, Neutralizing/immunology ; Computational Biology/methods ; Cross Reactions ; Epitopes, B-Lymphocyte/chemistry ; Epitopes, B-Lymphocyte/immunology ; Hepacivirus/immunology ; Models, Molecular ; Molecular Sequence Data ; Peptide Fragments/chemistry ; Peptide Fragments/immunology ; Viral Envelope Proteins/chemistry ; Viral Envelope Proteins/immunology
    Chemical Substances Antibodies, Neutralizing ; Epitopes, B-Lymphocyte ; Peptide Fragments ; Viral Envelope Proteins ; glycoprotein E2, Hepatitis C virus (157184-61-7)
    Language English
    Publishing date 2015
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1755-8794
    ISSN (online) 1755-8794
    DOI 10.1186/1755-8794-8-S4-S6
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article: Information management for the study of allergies.

    Brusic, Vladimir

    Inflammation & allergy drug targets

    2006  Volume 5, Issue 1, Page(s) 35–42

    Abstract: Microarrays and other large-scale screening technologies produce quantities of increasingly complex allergy data. These data link molecular and clinical measurements and observations and provide fertile ground for improving our understanding of the ... ...

    Abstract Microarrays and other large-scale screening technologies produce quantities of increasingly complex allergy data. These data link molecular and clinical measurements and observations and provide fertile ground for improving our understanding of the processes involved in allergic reactions. Information technology is employed in gathering, storage, retrieval and analysis of these data. The increasing proportion of allergy data are generated from genomics and proteomics approaches. The major activity focuses on characterization of allergens including IgE reactivity, structural properties, and mapping of IgE and T-cell epitopes. Because of the complexity of allergy data, their utilization requires bioinformatics approaches. Allergen data are stored in the general and specialist databases. At least a dozen of important allergen databases and data repositories have been developed to date. These data are analysed using general and specialist bioinformatics tools. The major applications of bioinformatics include support for allergen characterization, assessment of allergenicity, and identification of allergic cross-reactivity. These applications in turn support the development of vaccines and therapies for allergic disease. In this article we review allergen databases and tools for the analysis of allergens, and discuss the new directions in the field supported by large scale screening involving genomics, proteomics, and bioinformatics support.
    MeSH term(s) Allergens/immunology ; Animals ; Computational Biology ; Databases, Genetic ; Epitopes/immunology ; Humans ; Hypersensitivity/genetics ; Hypersensitivity/therapy
    Chemical Substances Allergens ; Epitopes
    Language English
    Publishing date 2006-04-12
    Publishing country United Arab Emirates
    Document type Journal Article ; Review
    ZDB-ID 2215862-5
    ISSN 2212-4055 ; 1871-5281
    ISSN (online) 2212-4055
    ISSN 1871-5281
    DOI 10.2174/187152806775269277
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article: Structural basis for VLDLR recognition by eastern equine encephalitis virus.

    Yang, Pan / Li, Wanyu / Fan, Xiaoyi / Pan, Junhua / Mann, Colin J / Varnum, Haley / Clark, Lars E / Clark, Sarah A / Coscia, Adrian / Smith, Katherine Nabel / Brusic, Vesna / Abraham, Jonathan

    bioRxiv : the preprint server for biology

    2023  

    Abstract: Alphaviruses are arthropod-borne enveloped RNA viruses that include several important human pathogens with outbreak potential. Among them, eastern equine encephalitis virus (EEEV) is the most virulent, and many survivors develop neurological sequelae, ... ...

    Abstract Alphaviruses are arthropod-borne enveloped RNA viruses that include several important human pathogens with outbreak potential. Among them, eastern equine encephalitis virus (EEEV) is the most virulent, and many survivors develop neurological sequelae, including paralysis and intellectual disability. The spike proteins of alphaviruses comprise trimers of heterodimers of their envelope glycoproteins E2 and E1 that mediate binding to cellular receptors and fusion of virus and host cell membranes during entry. We recently identified very-low density lipoprotein receptor (VLDLR) and apolipoprotein E receptor 2 (ApoER2), two closely related proteins that are expressed in the brain, as cellular receptors for EEEV and a distantly related alphavirus, Semliki forest virus (SFV)
    Language English
    Publishing date 2023-11-14
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.11.14.567065
    Database MEDical Literature Analysis and Retrieval System OnLINE

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