Publications by authors named "M Grahovac"

41 Publications

Multi-lesion radiomics of PET/CT for non-invasive survival stratification and histologic tumor risk profiling in patients with lung adenocarcinoma.

Eur Radiol 2022 Jul 28. Epub 2022 Jul 28.

Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Währinger Gürtel 18-20, Floor 3L, 1090, Vienna, Austria.

Objectives: This study investigates the ability of machine learning (ML) models trained on clinical data and 2-deoxy-2-[18F]fluoro-D-glucose(FDG) positron emission tomography/computed tomography (PET/CT) radiomics to predict overall survival (OS), tumor grade (TG), and histologic growth pattern risk (GPR) in lung adenocarcinoma (LUAD) patients.

Methods: A total of 421 treatment-naive patients with histologically-proven LUAD and available FDG PET/CT imaging were retrospectively included. Four cohorts were assessed for predicting 4-year OS (n = 276), 3-year OS (n = 280), TG (n = 298), and GPR (n = 265). FDG-avid lesions were delineated, and 2082 radiomics features were extracted and combined with endpoint-specific clinical parameters. ML models were built for the prediction of 4-year OS (M4OS), 3-year OS (M3OS), tumor grading (MTG), and histologic growth pattern risk (MGPR). A 100-fold Monte Carlo cross-validation with 80:20 training to validation split was employed as a performance evaluation for all models. The association between the M4OS and M3OS predictions with OS was assessed by the Kaplan-Meier survival analysis.

Results: The area under the receiver operator characteristics curve (AUC) was the highest for M4OS (AUC 0.88, 95% confidence interval (CI) 86.7-88.7), followed by M3OS (AUC 0.84, CI 82.9-84.9), while MTG and MGPR performed equally well (AUC 0.76, CI 74.4-77.9, CI 74.6-78, respectively). Predictions of M4OS (hazard ratio (HR) -2.4, CI -2.47 to -1.64, p < 0.05) and M3OS (HR -2.36, CI -2.79 to -1.93, p < 0.05) were independently associated with OS.

Conclusion: ML models are able to predict long-term survival outcomes in LUAD patients with high accuracy. Furthermore, histologic grade and predominant growth pattern risk can be predicted with satisfactory accuracy.

Key Points: • Machine learning models trained on pre-therapeutic PET/CT radiomics enable highly accurate long-term survival prediction of patients with lung adenocarcinoma. • Highly accurate survival predictions are achieved in lung adenocarcinoma patients despite heterogenous histologies and treatment regimens. • Radiomic machine learning models are able to predict lung adenocarcinoma tumor grade and histologic growth pattern risk with satisfactory accuracy.
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http://dx.doi.org/10.1007/s00330-022-08999-7DOI Listing
July 2022

Medium for the Production of -Based Biocontrol Agent Effective against Aflatoxigenic : Dual Approach for Modelling and Optimization.

Microorganisms 2022 Jun 6;10(6). Epub 2022 Jun 6.

Faculty of Technology Novi Sad, University of Novi Sad, 21000 Novi Sad, Serbia.

One of the leading limiting factors for wider industrial production and commercialization of microbial biopesticides refers to the high costs of cultivation media. The selection of alternative sources of macronutrients crucial for the growth and metabolic activity of the producing microorganism is a necessary phase of the bioprocess development. Gaining a better understanding of the influence of the medium composition on the biotechnological production of biocontrol agents is enabled through bioprocess modelling and optimization. In the present study, after the selection of optimal carbon and nitrogen sources, two modelling approaches were applied to mathematically describe the behavior of the examined bioprocess-the production of biocontrol agents effective against aflatoxigenic strains. The modelling was performed using four independent variables: cellulose, urea, ammonium sulfate and dipotassium phosphate, and the selected response was the inhibition-zone diameter. After the comparison of the results generated by the Response Surface Methodology (RSM) and the Artificial Neural Network (ANN) approach, the first model was chosen for the further optimization step due to the better fit of the experimental results. As the final investigation step, the optimal cultivation medium composition was defined (g/L): cellulose 5.0, ammonium sulfate 3.77, dipotassium phosphate 0.3, magnesium sulfate heptahydrate 0.3.
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http://dx.doi.org/10.3390/microorganisms10061165DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9228200PMC
June 2022

First Report of on lettuce in Serbia.

Plant Dis 2022 Mar 20. Epub 2022 Mar 20.

Institute of Pesticides and Environmental Protection, 229750, Laboratory of Plant Pathology, 31b Banatska, Beograd, Serbia, 11080.

Lettuce ( L.) is the world's most popular leafy salad vegetable. One of the major challenges facing lettuce producers are fungal diseases that could, under favorable conditions, devastate the harvest (Raid, 2004). During February 2021, poor growth, plant stunning and blanching of leaves of lettuce plants, cultivated in unheated plastic tunel in Potočanje (Zlatibor region), Serbia, were observed. The crowns were softened with spreading decaying lesions covered with white mycelium, particulary on the leaves near the soil surface. Approximately 2 to 3 weeks before harvest, diseased plants began to wilt and collapse. Estimated disease incidence was 50-55%. In order to identify the causal agent, symptomatic tissues from diseased plants were cut into small pieces, surface sterilized with 70% ethanol for 1 min, rinsed three times in sterile distilled water and placed on potato dextrose agar (PDA). Five isolates with uniform morphology were derived from infected tissue. The colonies had fast-growing, white, cottony aerial mycelium, producing profuse numbers (184 sclerotia/ Petri plate in average) of small, black, irregularly shaped sclerotia, less than 2 mm in diameter. Based on morfological features, the isolates were identified as Jagger (Kohn, 1979). To confirm the species identity, the internal transcribed spacer region of nuclear rDNA of a representative isolate 15-2 was amplified using the primer pair ITS1/ITS4 (White et al. 1990). Sequence analysis of ITS region revealed 100% nucleotide identity between the isolate 15-2 (GenBank Accession No. OL423632.1) and 14 isolates of from different parts of the world (e.g., accession Nos. MK356551.1, KY707828.1, JF2798801.1). Pathogenicity tests were conducted by artificial inoculation of 55-day-old lettuce plants cv. 'Majska kraljica', grown on commercial growth substrate in l L pots. The obtained isolates were grown on PDA for 7 days and mycelial plugs, 5 mm in diameter, were cut from the margin of the colony and placed mycelium-side down on undamaged ground-level leaves of lettuce plants. Two plugs per isolate were placed onto five plants each for a total of ten replicates per isolate. Negative control plants (5) were inoculated similarly with sterile PDA plugs. Inoculated plants were covered with transparent plastic bags, sprayed with water (under the plastic) twice a day for 3 to 5 days to maintain high humidity, and kept in a growth chamber at 22°C (13 h light). After 7 to 10 days, all pathogen-inoculated plants developed lettuce drop disease symptoms, whereas the control plants remained symptomless. The pathogen was reisolated from symptomatic leaves and Koch's postulates were completed by confirming the identity of the isolates. To our knowledge, this is the first report of on lettuce in Serbia. More research is needed to better understand this disease, establish control strategies and minimize the spread of the pathogen to other lettuce-producing areas of the country. References: Kohn, L. M. 1979. Delimitation of the economically important plant pathogenic Sclerotinia species. Phytopathology 69: 881-886. White, T. J., et al. 1990. PCR Protocols: A Guide to Methods and Applications. Academic Press, San Diego, CA. Raid, R.N., 2004. Lettuce diseases and their management. In Diseases of Fruits and Vegetables: Volume II (pp. 121-147). Springer, Dordrecht. Founding: This work was funded by the Ministry of Education, Science and Technological Development (contract 451-03-9/2021-14/200214).
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http://dx.doi.org/10.1094/PDIS-12-21-2735-PDNDOI Listing
March 2022

PD-L1 expression is regulated by microphthalmia-associated transcription factor (MITF) in nodular melanoma.

Pathol Res Pract 2022 Jan 2;229:153725. Epub 2021 Dec 2.

Department of Pathology, Faculty of Medicine, University of Rijeka, Rijeka, Croatia; Department of Pathology, Clinical Hospital Centre Rijeka, Rijeka, Croatia.

Malignant melanoma (MM) is known to avoid the host's immune response. Studies on in vitro melanoma cell lines link the microphthalmia-associated transcription factor (MITF) with the regulation of the PD-L1 expression. It seems that MITF affects the activation of the gene responsible for PD-L1 protein expression. Several proteins, including Bcl-2 and Cyclin D1, play major roles in malignant melanoma cell cycle regulation and survival. Our study aims to assess the relationship between MITF, Bcl-2, and cyclin D1 protein expression and the expression of the PD-L1 molecule. Additionally, we examined the association of BRAF mutation, MITF, and CCND1 gene amplification with PD-L1 protein expression. We performed immunohistochemical staining on fifty-two tumour samples from patients diagnosed with nodular melanoma (NM). BRAF V600 mutation, MITF, and CCND1 gene amplification analyses were analyzed by the Sanger sequencing and QRT-PCR methods, respectively. Statistical analyses confirmed the significant inverse correlation between cyclin D1 and PD-L1 expression (p = 0.001) and correlation between PD-L1 and MITF protein expression (p = 0.023). We found a statistically significant inverse correlation between the present MITF gene amplification and PD-L1 (p = 0.007) and MITF protein expression (p = 3.4 ×10-6), respectively. Our study, performed on clinical NM materials, supports the in vitro study findings providing a rationale for the potential MITF-dependent regulation of PD-L1 expression in malignant melanoma.
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http://dx.doi.org/10.1016/j.prp.2021.153725DOI Listing
January 2022

Adherence to Mediterranean diet and advanced glycation endproducts in patients with diabetes.

World J Diabetes 2021 Nov;12(11):1942-1956

Department of Pathophysiology, University of Split School of Medicine, Split 21000, Croatia.

Background: In recent years, American Diabetes Association started to strongly advocate the Mediterranean diet (MD) over other diets in patients with diabetes mellitus (DM) because of its beneficial effects on glycemic control and cardiovascular (CV) risk factors. Tissue levels of advanced glycation endproducts (AGEs) emerged as an indicator of CV risk in DM. Skin biopsy being invasive, the use of AGE Reader has been shown to reflect tissue AGEs reliably.

Aim: To examine the association between adherence to MD and AGEs in patients with DM type II.

Methods: This cross-sectional study was conducted on 273 patients with DM type II. A survey questionnaire was composed of 3 separate sections. The first part of the questionnaire included general data and the habits of the participants. The second part aimed to assess the basic parameters of participants' diseases and associated conditions. The third part of the questionnaire was the Croatian version of the 14-item MD service score (MDSS). AGEs levels and associated CV risk were measured using AGE Reader (DiagnOptics Technologies BV, Groningen, The Netherlands).

Results: A total of 27 (9.9%) patients fulfilled criteria for adherence to MD, with a median score of 8.0 (6.0-10.0). Patients with none/limited CV risk had significantly higher percentage of MD adherence in comparison to patients with increased/definite CV risk (15.2% 6.9%, = 0.028), as well as better adherence to guidelines for nuts (23.2% 12.6%, = 0.023) and legumes (40.4% 25.9%, = 0.013) consumption. Higher number of patients with glycated hemoglobin (HbA1c) < 7% adhered to MD when compared to patients with HbA1c > 7% (14.9% 7.3%, = 0.045). Moreover, those patients followed the MDSS guidelines for eggs (33.0% 46.8%, = 0.025) and wine (15.6% 29.8%, = 0.006) consumption more frequently. MDSS score had significant positive correlation with disease duration ( = 0.179, = 0.003) and negative correlation with body mass index (BMI) values ( = -0.159, = 0.008). In the multiple linear regression model, BMI (β ± SE, -0.09 ± 0.04, = 0.037) and disease duration (β ± SE, 0.07 ± 0.02, < 0.001) remained significant independent correlates of the MDSS score. Patients with HbA1c > 7% think that educational programs on nutrition would be useful for patients in significantly more cases than patients with HbA1c < 7% (98.9% 92.6%, = 0.009).

Conclusion: Although adherence to MD was very low among people with diabetes, we demonstrated that adherence to MD is greater in patients with lower CV risk, longer disease duration, and well-controlled glycaemia.
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http://dx.doi.org/10.4239/wjd.v12.i11.1942DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8613665PMC
November 2021
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