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Article ; Online: Measurement of chromosomal instability and level of DNA damage in peripheral blood mononuclear cells of endometrial cancer patients.

Marković, Aleksandra / Grujičić, Darko / Živković Radojević, Marija / Milošević-Djordjević, Olivera

2024 Volume 39, Issue 3, Page(s) 172–180

Abstract: Endometrial cancer is one of the most common invasive gynecologic malignancies in developed countries. The aim of this study was to evaluate chromosomal instability and level of DNA damage in peripheral blood mononuclear cells (PBMCs) of newly diagnosed ... ...

Abstract	Endometrial cancer is one of the most common invasive gynecologic malignancies in developed countries. The aim of this study was to evaluate chromosomal instability and level of DNA damage in peripheral blood mononuclear cells (PBMCs) of newly diagnosed endometrial cancer patients in relation to health status (diagnosis), age, histological grade of cancer, residence, smoking, number of pregnancies, miscarriages, and abortions. The analyzed sample consisted of 60 individuals, 30 endometrial cancer patients with an average age of 64.37 ± 7.08, and 30 healthy control women with an average age of 60.23 ± 11.55. Chromosomal instability was evaluated by the cytokinesis-block micronucleus (CBMN) assay, and the level of DNA damage by the single-cell gel electrophoresis (comet) assay in PBMCs. The average frequencies of micronuclei (MNi), nucleoplasmic bridges (NPBs) as well as nuclear buds (NBUDs) were significantly higher in cancer patients compared to controls (P < .0005). There was no difference in the nuclear division index (NDI) among the analyzed samples. The comet assay showed that the patients had a significantly increased genetic damage index (GDI) compared with controls (P < .0005). Using linear regression analysis, we found that health status (diagnosis) had the strongest influence on the MN frequency as well as GDI (P < .0005). Our results indicated that there is a high level of genetic damage in both the level of DNA and the level of chromosomes in the PBMCs of newly diagnosed patients with endometrial cancer, where the frequency and level of damage were significantly affected by health status, grade of cancer, residence, number of pregnancies, miscarriages, and abortions.
MeSH term(s)	Humans ; Female ; Leukocytes, Mononuclear/metabolism ; Chromosomal Instability ; DNA Damage ; Endometrial Neoplasms/genetics ; Endometrial Neoplasms/pathology ; Middle Aged ; Micronucleus Tests ; Aged ; Comet Assay/methods ; Case-Control Studies
Language	English
Publishing date	2024-01-25
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	632903-2
ISSN	1464-3804 ; 0267-8357
ISSN (online)	1464-3804
ISSN	0267-8357
DOI	10.1093/mutage/geae003
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Article: Impact of Emergency Situations on the Level of Fear and Anxiety in Oncology Patients During Radiotherapy in a Developing Country.

Živković Radojević, Marija / Milosavljević, Neda / Jankovic, Slobodan / Grujić, Miloš / Janković, Katarina / Folić, Marko

Cureus

2024 Volume 16, Issue 3, Page(s) e57129

Abstract: Objective: To analyze the level of fear and anxiety related to radiotherapy in oncology patients treated before and during the COVID-19 pandemic, as well as to examine whether the advancement of radiotherapy centers leads to any reduction in the patient' ...

Abstract	Objective: To analyze the level of fear and anxiety related to radiotherapy in oncology patients treated before and during the COVID-19 pandemic, as well as to examine whether the advancement of radiotherapy centers leads to any reduction in the patient's fear in emergency situations. Methods: Two cross-sectional studies were conducted in two time frames (2016 and 2022) based on the analysis of the intensity of anxiety and fear of radiotherapy in oncology patients with assistance. A questionnaire for assessing fear of radiotherapy in oncology patients and Zung's and Beck's self-reported anxiety scales were used. The first part of the research integrated all data of research interest obtained from patients treated with radiotherapy during 2016, and the second cross-sectional study included all patients treated in 2022 during the COVID-19 pandemic. The study was prepared according to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist. Results: The first cross-sectional study had 154 participants who had been treated with radiotherapy, while in the second study, there were 159 patients. Patients treated in 2022 show significantly higher levels of fear and anxiety. External beam radiotherapy and brachytherapy simultaneously used in both studies increased the level of fear and anxiety. Conclusion: The conducted research showed exceptional differences in the intensity of fear and anxiety in patients treated with radiotherapy in different health situations, as was the case during the COVID-19 pandemic, with a significant impact on the stability of the health system and the challenges to providing standard services.
Language	English
Publishing date	2024-03-28
Publishing country	United States
Document type	Journal Article
ZDB-ID	2747273-5
ISSN	2168-8184
ISSN	2168-8184
DOI	10.7759/cureus.57129
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Article: Thermal characteristics and combustion reactivity of coronavirus face masks using TG-DTG-MS analysis.

Manić, Nebojša / Janković, Bojan / Stojiljković, Dragoslava / Angelopoulos, Panagiotis / Radojević, Miloš

Journal of thermal analysis and calorimetry

2022 Volume 147, Issue 18, Page(s) 10131–10143

Abstract: The presented paper deals with the influence of the heating rate on combustion characteristics (reactivity and reactivity evaluation, ignition index ( ...

Abstract	The presented paper deals with the influence of the heating rate on combustion characteristics (reactivity and reactivity evaluation, ignition index (
Language	English
Publishing date	2022-05-03
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2017304-0
ISSN	1572-8943 ; 1588-2926 ; 1388-6150 ; 1418-2874
ISSN (online)	1572-8943 ; 1588-2926
ISSN	1388-6150 ; 1418-2874
DOI	10.1007/s10973-022-11358-9
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Article ; Online: Automated Neuron Reconstruction from 3D Fluorescence Microscopy Images Using Sequential Monte Carlo Estimation.

Radojević, Miroslav / Meijering, Erik

Neuroinformatics

2018 Volume 17, Issue 3, Page(s) 423–442

Abstract: Microscopic images of neuronal cells provide essential structural information about the key constituents of the brain and form the basis of many neuroscientific studies. Computational analyses of the morphological properties of the captured neurons ... ...

Abstract	Microscopic images of neuronal cells provide essential structural information about the key constituents of the brain and form the basis of many neuroscientific studies. Computational analyses of the morphological properties of the captured neurons require first converting the structural information into digital tree-like reconstructions. Many dedicated computational methods and corresponding software tools have been and are continuously being developed with the aim to automate this step while achieving human-comparable reconstruction accuracy. This pursuit is hampered by the immense diversity and intricacy of neuronal morphologies as well as the often low quality and ambiguity of the images. Here we present a novel method we developed in an effort to improve the robustness of digital reconstruction against these complicating factors. The method is based on probabilistic filtering by sequential Monte Carlo estimation and uses prediction and update models designed specifically for tracing neuronal branches in microscopic image stacks. Moreover, it uses multiple probabilistic traces to arrive at a more robust, ensemble reconstruction. The proposed method was evaluated on fluorescence microscopy image stacks of single neurons and dense neuronal networks with expert manual annotations serving as the gold standard, as well as on synthetic images with known ground truth. The results indicate that our method performs well under varying experimental conditions and compares favorably to state-of-the-art alternative methods.
MeSH term(s)	Algorithms ; Animals ; Brain/cytology ; Humans ; Image Processing, Computer-Assisted/methods ; Imaging, Three-Dimensional/methods ; Microscopy, Fluorescence/methods ; Monte Carlo Method ; Neuroimaging/methods ; Neurons/cytology ; Software
Language	English
Publishing date	2018-12-12
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2111941-7
ISSN	1559-0089 ; 1539-2791
ISSN (online)	1559-0089
ISSN	1539-2791
DOI	10.1007/s12021-018-9407-8
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Article ; Online: Deep-Learning-Based Automated Neuron Reconstruction From 3D Microscopy Images Using Synthetic Training Images.

Chen, Weixun / Liu, Min / Du, Hao / Radojevic, Miroslav / Wang, Yaonan / Meijering, Erik

IEEE transactions on medical imaging

2022 Volume 41, Issue 5, Page(s) 1031–1042

Abstract: Digital reconstruction of neuronal structures from 3D microscopy images is critical for the quantitative investigation of brain circuits and functions. It is a challenging task that would greatly benefit from automatic neuron reconstruction methods. In ... ...

Abstract	Digital reconstruction of neuronal structures from 3D microscopy images is critical for the quantitative investigation of brain circuits and functions. It is a challenging task that would greatly benefit from automatic neuron reconstruction methods. In this paper, we propose a novel method called SPE-DNR that combines spherical-patches extraction (SPE) and deep-learning for neuron reconstruction (DNR). Based on 2D Convolutional Neural Networks (CNNs) and the intensity distribution features extracted by SPE, it determines the tracing directions and classifies voxels into foreground or background. This way, starting from a set of seed points, it automatically traces the neurite centerlines and determines when to stop tracing. To avoid errors caused by imperfect manual reconstructions, we develop an image synthesizing scheme to generate synthetic training images with exact reconstructions. This scheme simulates 3D microscopy imaging conditions as well as structural defects, such as gaps and abrupt radii changes, to improve the visual realism of the synthetic images. To demonstrate the applicability and generalizability of SPE-DNR, we test it on 67 real 3D neuron microscopy images from three datasets. The experimental results show that the proposed SPE-DNR method is robust and competitive compared with other state-of-the-art neuron reconstruction methods.
MeSH term(s)	Algorithms ; Deep Learning ; Image Processing, Computer-Assisted/methods ; Imaging, Three-Dimensional/methods ; Microscopy ; Neurons
Language	English
Publishing date	2022-05-02
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	622531-7
ISSN	1558-254X ; 0278-0062
ISSN (online)	1558-254X
ISSN	0278-0062
DOI	10.1109/TMI.2021.3130934
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Zs.A 2546: Show issues

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Article ; Online: Review of compounds that exhibit radioprotective and/or mitigatory effects after application of diagnostic or therapeutic ionizing radiation.

Zivkovic Radojevic, Marija / Milosavljevic, Neda / Miladinovic, Tatjana B / Janković, Slobodan / Folic, Marko

International journal of radiation biology

2022 Volume 99, Issue 4, Page(s) 594–603

Abstract: Purpose: Exposure to ionizing radiation can be accidental or for medical purposes. Analyzes of the frequency of radiation damage in the general population, it has been determined that by far the most common are those that occur as a result of diagnostic ...

Abstract	Purpose: Exposure to ionizing radiation can be accidental or for medical purposes. Analyzes of the frequency of radiation damage in the general population, it has been determined that by far the most common are those that occur as a result of diagnostic or therapeutic procedures. Damage caused by radiation, either accidentally or for therapeutic purposes, can be reduced by the use of radioprotectors, mitigators or other therapeutic agents. A detailed research of the available literature shows that there is little systematized data of potentially radioprotective and/or mitigating effects of drugs from the personal therapy of patients during the application of therapeutic ionizing radiation. The aim of this paper is to present review of compounds, especially personal therapy drugs, that exhibit radioprotective and/or mitigating effects after the application of diagnostic or therapeutic ionizing radiation. Conclusions: Given the widespread use of ionizing radiation for diagnostic and therapeutic purposes, there is a clear need to create a strategy and recommendations of relevant institutions for the use of radioprotectors and mitigators in everyday clinical practice, with individual evaluation of the patient's condition and selection of the compounds that will show the greatest benefit in terms of radioprotection.
MeSH term(s)	Humans ; Radiation-Protective Agents/pharmacology ; Radiation-Protective Agents/therapeutic use ; Radiation Protection/methods ; Radiation Injuries/etiology ; Radiation Injuries/prevention & control ; Radiation Injuries/drug therapy ; Radiation, Ionizing
Chemical Substances	Radiation-Protective Agents
Language	English
Publishing date	2022-08-17
Publishing country	England
Document type	Review ; Journal Article
ZDB-ID	3065-x
ISSN	1362-3095 ; 0020-7616 ; 0955-3002
ISSN (online)	1362-3095
ISSN	0020-7616 ; 0955-3002
DOI	10.1080/09553002.2022.2110308
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Article ; Online: Accuracy of IOTA Simple Rules, IOTA ADNEX Model, RMI, and Subjective Assessment for Preoperative Adnexal Mass Evaluation: The Experience of a Tertiary Care Referral Hospital.

Vilendecic, Zoran / Radojevic, Milos / Stefanovic, Katarina / Dotlic, Jelena / Likic Ladjevic, Ivana / Dugalic, Stefan / Stefanovic, Aleksandar

Gynecologic and obstetric investigation

2023 Volume 88, Issue 2, Page(s) 116–122

Abstract: Objectives: The aim of this study was to evaluate the accuracy of IOTA Simple Rules (SR), IOTA ADNEX model, Risk of Malignancy Index (RMI), and subjective assessment (SA) which is used for adnexal mass assessment in our institution.: Design: This is ... ...

Abstract	Objectives: The aim of this study was to evaluate the accuracy of IOTA Simple Rules (SR), IOTA ADNEX model, Risk of Malignancy Index (RMI), and subjective assessment (SA) which is used for adnexal mass assessment in our institution. Design: This is a prospective observational study. Participants/materials, setting, methods: We included patients with at least one adnexal mass who needed elective surgical evaluation based on clinical and laboratory findings. Patients admitted to Clinic for Gynecology and Obstetrics, University Clinical Center of Serbia, were recruited for the study between January 2019 and June 2021. Level II ultrasonographers performed a gray scale and Doppler exam for each patient. Preoperative classification of adnexal masses (benign or malignant) was performed by SA, the International Ovarian Analysis Group (IOTA) SR, IOTA ADNEX model, and Risk of Malignancy Index (RMI). Postoperatively obtained histological findings were used as a reference. Results: During the study period, we enrolled 179 premenopausal and 217 postmenopausal patients, representing 396 patients in our sample. Prevalence of malignant disease in pre- and postmenopausal groups was 16.2% (29/179) and 41% (89/217), respectively. Malignant disease was diagnosed in 29.8% (118/396) of patients. SA achieved the highest discrimination accuracy between benign and malignant tumors (area under the curve [AUC] of 0.928, 95% CI [0.898-0.952]). For SA, the overall diagnostic accuracy, sensitivity, specificity, positive likelihood ratio (LR+), and negative likelihood ratio (LR-) were 91.4%, 88.1%, 92.8%, 12.25, and 0.13. The AUC for Simple Rules with subjective assessment in inconclusive cases (SR + SA) was 0.912 (95% CI [0.880-0.938]). Regarding SR + SA, diagnostic accuracy, sensitivity, specificity, LR+, and LR- were 92.4%, 88.1%, 94.2%, 15.31, and 0.13. The ADNEX model had the AUC of 0.914 (95% CI [0.882-0.940]). Binary classification using the ADNEX model at a cut-off value of 10% for malignancy had the sensitivity, specificity, LR+ and LR- of 92.4%, 73.0%, 3.42, and 0.10. This resulted in the lowest overall accuracy of 78.8%. The AUC for RMI was 0.854 (95% CI [0.815-0.887]), with overall accuracy, sensitivity, specificity, LR+ and LR- of 82.3%, 73.7%, 86.0%, 5.26, and 0.31. There was no difference in the AUCs of the SA and IOTA models for the whole group, premenopausal, and postmenopausal groups. RMI performed worse compared to SA and the IOTA models. The ADNEX model achieved the highest accuracy at the cut-off value of 35%. Limitations: The data generalizability is limited by a single institution-dependent sampling. Conclusions: The IOTA SR and ADNEX model were reliable and comparable with the SA and performed better than the RMI. The IOTA SR model offers the potential for immediate and reliable diagnosis, even in the hands of less experienced ultrasonographers. Both IOTA models studied can be a valuable adjunct to a clinician's decision-making process.
MeSH term(s)	Female ; Humans ; Adnexal Diseases/diagnostic imaging ; Adnexal Diseases/surgery ; Diagnosis, Differential ; Hospitals ; Ovarian Neoplasms/diagnostic imaging ; Ovarian Neoplasms/surgery ; Sensitivity and Specificity ; Tertiary Healthcare ; Ultrasonography ; Prospective Studies ; Premenopause ; Postmenopause
Language	English
Publishing date	2023-01-30
Publishing country	Switzerland
Document type	Observational Study ; Journal Article
ZDB-ID	800003-7
ISSN	1423-002X ; 0378-7346
ISSN (online)	1423-002X
ISSN	0378-7346
DOI	10.1159/000529355
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Article ; Online: Automated neuron tracing using probability hypothesis density filtering.

Radojevic, Miroslav / Meijering, Erik

Bioinformatics (Oxford, England)

2017 Volume 33, Issue 7, Page(s) 1073–1080

Abstract: Motivation: The functionality of neurons and their role in neuronal networks is tightly connected to the cell morphology. A fundamental problem in many neurobiological studies aiming to unravel this connection is the digital reconstruction of neuronal ... ...

Abstract	Motivation: The functionality of neurons and their role in neuronal networks is tightly connected to the cell morphology. A fundamental problem in many neurobiological studies aiming to unravel this connection is the digital reconstruction of neuronal cell morphology from microscopic image data. Many methods have been developed for this, but they are far from perfect, and better methods are needed. Results: Here we present a new method for tracing neuron centerlines needed for full reconstruction. The method uses a fundamentally different approach than previous methods by considering neuron tracing as a Bayesian multi-object tracking problem. The problem is solved using probability hypothesis density filtering. Results of experiments on 2D and 3D fluorescence microscopy image datasets of real neurons indicate the proposed method performs comparably or even better than the state of the art. Availability and implementation: Software implementing the proposed neuron tracing method was written in the Java programming language as a plugin for the ImageJ platform. Source code is freely available for non-commercial use at https://bitbucket.org/miroslavradojevic/phd . Contact: meijering@imagescience.org. Supplementary information: Supplementary data are available at Bioinformatics online.
MeSH term(s)	Animals ; Bayes Theorem ; Humans ; Image Processing, Computer-Assisted/methods ; Imaging, Three-Dimensional/methods ; Microscopy, Fluorescence ; Neuroanatomical Tract-Tracing Techniques/methods ; Neurons/cytology ; Software
Language	English
Publishing date	2017-04-01
Publishing country	England
Document type	Journal Article
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btw751
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Article: Automated neuron tracing using probability hypothesis density filtering

Radojević, Miroslav / Meijering, Erik

Bioinformatics. 2017 Apr. 01, v. 33, no. 7

2017

Abstract	Motivation: The functionality of neurons and their role in neuronal networks is tightly connected to the cell morphology. A fundamental problem in many neurobiological studies aiming to unravel this connection is the digital reconstruction of neuronal cell morphology from microscopic image data. Many methods have been developed for this, but they are far from perfect, and better methods are needed. Results: Here we present a new method for tracing neuron centerlines needed for full reconstruction. The method uses a fundamentally different approach than previous methods by considering neuron tracing as a Bayesian multi-object tracking problem. The problem is solved using probability hypothesis density filtering. Results of experiments on 2D and 3D fluorescence microscopy image datasets of real neurons indicate the proposed method performs comparably or even better than the state of the art. Availability and Implementation: Software implementing the proposed neuron tracing method was written in the Java programming language as a plugin for the ImageJ platform. Source code is freely available for non-commercial use at https://bitbucket.org/miroslavradojevic/phd. Contact: meijering@imagescience.org Supplementary information: Supplementary data are available at Bioinformatics online.
Keywords	Bayesian theory ; automation ; bioinformatics ; cell structures ; computer software ; data collection ; fluorescence microscopy ; neurons ; probability
Language	English
Dates of publication	2017-0401
Size	p. 1073-1080.
Publishing place	Oxford University Press
Document type	Article
ZDB-ID	1468345-3
ISSN	1460-2059 ; 1367-4803
ISSN (online)	1460-2059
ISSN	1367-4803
DOI	10.1093/bioinformatics/btw751
Database	NAL-Catalogue (AGRICOLA)

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Article: Improved TGA-MS measurements for evolved gas analysis (EGA) during pyrolysis process of various biomass feedstocks. Syngas energy balance determination

Radojević, Miloš / Janković, Bojan / Stojiljković, Dragoslava / Jovanović, Vladimir / Čeković, Ivana / Manić, Nebojša

Thermochimica acta. 2021 May, v. 699

2021

Abstract: This paper provides in-depth knowledge about the evolved gas analysis interpretation via newly proposed semi-quantitative approach, arising from thermogravimetric analysis (TGA) – mass spectrometry (MS) coupled measurements, for studying pyrolysis ... ...

Abstract	This paper provides in-depth knowledge about the evolved gas analysis interpretation via newly proposed semi-quantitative approach, arising from thermogravimetric analysis (TGA) – mass spectrometry (MS) coupled measurements, for studying pyrolysis behavior of three kinds of biomass waste materials (spent coffee grounds, beech sawdust and wheat straw). TGA – MS coupling allows accurate correlation between molecular ion peak and fragment peaks to the corresponding mass loss rates from derivative thermogravimetry curves. Within proposed semi-quantitative analysis, MS spectra were interpreted through the comparative analysis of compounds fragments and of the compound itself, where the single atomic mass unit was identified by multiple compounds exhibition. It was shown that by this procedure which involves overlapping multiple curves supervising, the identification of gases in volatiles complex scheme becomes more simplified. By setting up semi-quantitative formulas, easy and reliable calculations of gaseous products yield and syngas energy capacities are possible to achieve. The H₂/CO ratio derived from the proposed method for wood waste product (sawdust) is in an excellent agreement with H₂/CO ratio for sawdust syngas production, in fuel reactor for biomass gasiﬁcation and H₂ production.
Keywords	Fagus ; biomass ; energy balance ; feedstocks ; mass spectrometry ; pyrolysis ; sawdust ; synthesis gas ; thermogravimetry ; waste wood ; wheat straw
Language	English
Dates of publication	2021-05
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	1500974-9
ISSN	0040-6031
ISSN	0040-6031
DOI	10.1016/j.tca.2021.178912
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