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1.
Discovery of novel biomarkers with extended non-coding RNA interactor networks from genetic and protein biomarkers
Gregor Jezernik, Damjan Glavač, Pavel Skok, Martina Krušič, Uroš Potočnik, Mario Gorenjak, 2024, original scientific article

Abstract: Curated online interaction databases and gene ontology tools have streamlined the analysis of highly complex gene/protein networks. However, understanding of disease pathogenesis has gradually shifted from a protein-based core to complex interactive networks where non-coding RNA (ncRNA) is thought to play an essential role. As current gene ontology is based predominantly on protein-level information, there is a growing need to analyze networks with ncRNA. In this study, we propose a gene ontology workflow integrating ncRNA using the NPInter V5.0 database. To validate the proposed workflow, we analyzed our previously published curated biomarker datasets for hidden disease susceptibility processes and pharmacogenomics. Our results show a novel involvement of melanogenesis in psoriasis response to biological drugs in general. Hyperpigmentation has been previously observed in psoriasis following treatment with currently indicated biological drugs, thus calling attention to melanogenesis research as a response biomarker in psoriasis. Moreover, our proposed workflow highlights the need to critically evaluate computed ncRNA interactions within databases and a demand for gene ontology analysis of large miRNA blocks.
Keywords: gene ontology, non-coding RNA, disease pathogenesis
Published in DKUM: 06.12.2024; Views: 0; Downloads: 1
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2.
Meta-analytic comparison of global RNA transcriptomes of acute and chronic myeloid leukemia cells reveals novel gene candidates governing myeloid malignancies
Staša Jurgec, Gregor Jezernik, Mario Gorenjak, Tomaž Büdefeld, Uroš Potočnik, 2022, original scientific article

Abstract: Despite advances in the understanding of genetic risk factors and molecular mechanisms underlying acute myeloid leukemia (AML) and chronic myeloid leukemia (CML), clinical outcomes of current therapies in terms of disease relapse and mortality rate pose a great economic and social burden. To overcome this, the identification of new molecular prognostic biomarkers and pharmacological targets is crucial. Recent studies have suggested that AML and CML may share common pathogenic mechanisms and cellular substrates. To this end, in the present study, global transcriptome profiles of AML and CML at the molecular and cellular level were directly compared using a combination of meta-analysis and modern statistics, and novel candidate genes and specific biological processes associated with the pathogenesis of AML and CML were characterized. Our study significantly improves our current understanding of myeloid leukemia and will help develop new therapeutic targets and biomarkers for disease progression, management and treatment response.
Keywords: AML, CML, meta-analysis, lincRNA, spliceosome
Published in DKUM: 05.12.2024; Views: 0; Downloads: 0
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3.
Identification of novel loci involved in adalimumab response in Crohn’s disease patients using integration of genome profiling and isoform-level immune-cell deconvoluted transcriptome profiling of colon tissue
Mario Gorenjak, Gregor Jezernik, Martina Krušič, Pavel Skok, Uroš Potočnik, 2022, original scientific article

Abstract: Crohn’s disease is a consequence of dysregulated inflammatory response to the host’s microbiota. Although anti-TNF treatment improves the quality of the patient’s life, a large proportion of patients lose response to the treatment. The past decade of research has led to a continuum of studies showcasing the heterogeneity of anti-TNF response; thus, the aim of the present study was to dissect transcriptome-wide findings to transcript isoform specific levels and combine the analyses with refined information of immune cell landscapes in colon tissue, and subsequently select promising candidates using gene ontology and genomic integration. We enrolled Slovenian Crohn’s disease patients who were naïve with respect to adalimumab treatment. We performed colon tissue RNA sequencing and peripheral blood mononuclear cell DNA genotyping with a subsequent contemporary integrative approach to combine immune cell deconvoluted isoform transcript specific transcriptome analysis, gene ontology layering and genomic data. We identified nine genes (MACF1, CTSE, HDLBP, HSPA9, HLA-DMB, TAP2, LGMN, ANAPC11, ACP5) with 15 transcripts and 16 variants involved in the adalimumab response. Our study identified loci, some of which were previously shown to contribute to inflammatory bowel disease susceptibility, as novel loci involved in adalimumab response in Crohn’s disease patients.
Keywords: Crohn’s disease, adalimumab, transcriptome, isoforms, deconvolution
Published in DKUM: 05.12.2024; Views: 0; Downloads: 0
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4.
Razvoj naprednih katalizatorjev na osnovi grafitnega ogljikovega nitrida za okoljske aplikacije : doctoral dissertation
Matevž Roškarič, 2024, doctoral dissertation

Abstract: Grafitni ogljikov nitrid (g-C3N4) predstavlja obetavnega kandidata za remediacijo okolja, vendar določene neželene lastnosti omejujejo njegovo fotokatalitsko aktivnost (npr. nizka specifična površina in visoka tendenca za rekombinacijo nosilcev naboja). Le-te lahko izboljšamo z uporabo klasičnega optimizacijskega postopka (tj. korak za korakom), ki pa tipično ne daje optimalnih rezultatov. Kot alternativo lahko uporabimo številne statistične metode, kot je npr. optimizacijski postopek Simplex, s katerim smo izboljšali ne le specifično površino g-C3N4 (zastavljena cenilna funkcija), ampak tudi druge morfološke in opto-elektronske lastnosti. V le nekaj korakih smo pridobili znatno izboljšan fotokatalizator, ki je v celoti razgradil modelno onesnažilo bisfenol A (BPA) pri uporabi vidne svetlobe. Fotokatalizator g-C3N4 smo tudi optimizirali po njegovi sintezi s pomočjo aktivacije pri povišani temperaturi v CO2 atmosferi. Ponovno nismo izboljšali le specifične površine, ampak tudi druge opto-elektronske in strukturne lastnosti, katere so omogočile skoraj popolno razgradnjo BPA z uporabo simulirane sončne svetlobe. V obeh primerih (Simplex ali CO2 aktivacija) smo deformirali strukturo idealnega 2D g-C3N4 fotokatalizatorja in vnesli defekte, kar je izboljšalo ne le opto-elektronskih lastnosti, ampak omogočilo tudi nastanek singletnega kisika. Le-ta je omogočil povečano razgradnjo BPA in tudi njegovih analogov (BPF, BPS in BPAF), kakor tudi selektivno razgradnjo izbranih farmacevtskih učinkovin (paracetomol, acetilsalicilna kislina, salicilna kislina, benzojska kislina in kofein). Kljub visoki stabilnosti v vodnih medijih čisti g-C3N4 materiali izkazujejo manjšo deaktivacijo pri ponovni uporabi. Da izboljšamo stabilnost in druge negativne lastnosti čistih g-C3N4 (CN) materialov, jih lahko združimo s TiO2 v hibridne materiale. Ugotovili smo, da je optimalno masno razmerje med obema komponentama 1:1 in da podaljšana sinteza hibridnih materialov v zraku (24 ur) izboljša stik do optimalne mere, kar poveča fotokatalitsko aktivnost. Ta pojav je opazen ne glede na izbrano morfologijo TiO2 (nanosfere TP ali heksagonalni delci TH) komponente (CNTP-24 ali CNTH 24 fotokatalizatorja). Morfologija TiO2 pa ima lahko tudi druge pozitivne lastnosti, saj lahko nastale kisikove praznine in Ti3+ v TiO2 vplivajo na opto-elektronske lastnosti kompozita. Zato je TiO2 v obliki nanopalčk (TR) doprinesel največje izboljšanje, kadar je združen v hibridni material (CNTR-2) z g-C3N4 (CN), v primerjavi s komercialnimi TP. Hkrati, če te kompozite dodatno tretiramo v prisotnosti N2 pri povišani temperaturi, dosežemo preoblikovanje g-C3N4 in znatno izboljšamo opto-elektronske lastnosti hibridnih materialov. Zato le-ti izkazujejo do 300 % povečano fotokatalitsko aktivnost razgradnje BPA pri uporabi vidne svetlobe v primerjavi z neobdelanim hibridnim materialom. Dodatno lahko povečamo fotokatalitsko aktivnost z nanosom plazmonske kovine platine (Pt), kjer preferenčna lokacija nanosa Pt nanodelcev vpliva na aktivnost kompozitov zaradi različnih interakcij Pt z nosilcem (g-C3N4 ali TiO2). Ker so vsi postopki spreminjanja morfologije TiO2 potratni (čas, denar, kemikalije), smo z uporabo hitre in zelene mehano-kemijske sinteze tvorili hibridne g-C3N4/TiO2 materiale. Le-ti so izkazovali podobno izboljšane fotokatalitske odzive kot npr. CNTR-2 fotokatalizator, kar jih naredi obetavne za realne aplikacije. Tako je potrebno upoštevati celo vrsto parametrov in možnosti, kadar želimo tvoriti napredne hibridne fotokatalizatorje za remediacijo okolja.
Keywords: grafitni ogljikov nitrid (g-C3N4), hibridni materiali, razvoj fotokatalizatorjev, heterogena fotokataliza, okoljska remediacija
Published in DKUM: 05.12.2024; Views: 0; Downloads: 6
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5.
Cognitive and emotional perceptions of illness in patients diagnosed with type 2 diabetes mellitus
Lucija Gosak, Gregor Štiglic, 2024, original scientific article

Abstract: Type 2 diabetes mellitus (T2DM) affects a patient’s physical, social, and mental well-being. Perceptions of the illness are linked to quality of life. The aim of this study was to assess illness perception in patients diagnosed with T2DM and to validate the Brief Illness Perception Questionnaire in the Slovenian language. A cross-sectional study involved 141 patients diagnosed with T2DM. We performed a content analysis of the questionnaire and estimated the S-CVI, I-CVI, kappa coefficient. We also used Cronbach’s alpha to assess the reliability. Participants did not have a very threatening perception of T2DM, but being overweight and having cardiovascular disease were significant contributors to a more threatening perception. The most frequently indicated factors influencing the onset and development of T2DM were heredity and genetics, stress and other psychological distress, and poor and inadequate nutrition. I-CVI ranged from 0.833 to 1.00, while the kappa is greater than 0.74, confirming the excellent validity of the questions. The content validity assessment of the questionnaire further confirms that the questionnaire is suitable for use with the target population in Slovenia. The questionnaire proved to be a valid and reliable tool that can be used to assess the relationship between illness perception and self-management of T2DM.
Keywords: type 2 diabetes mellitus (T2DM), illness perception, psychometric properties
Published in DKUM: 28.11.2024; Views: 0; Downloads: 0
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6.
Internet use and psychosomatic symptoms among university students : cross-sectional study
Gregor Štiglic, Ruth Masterson Creber, Leona Cilar Budler, 2022, original scientific article

Abstract: Background: Although the internet facilitates access to a wide range of knowledge and evidence, overuse among young people is associated with lower wellbeing and psychosomatic symptoms. The aim of this cross-sectional study is to explore the relationship between internet use, mental wellbeing, and psychosomatic symptoms among university students in Slovenia. Methods: We used correlation matrix plots to identify correlated symptoms and multivariate logistic regression to analyze the relationship between the time spent on the internet or computer and psychosomatic symptoms controlling for gender. Symptoms were measured using the Health Behavior of School Children scale. Results: Out of 464 students, the majority (64.7%, n = 300) were healthcare students and 35.3% (n = 164) were computer science students. Among somatic symptoms, headaches were associated with more time spent on the computer (r = −0.17, p < 0.001) and were significantly more prevalent in computer science students compared to health science students (χ2(1) = 8.52, p = 0.004). Time spent using the internet for spare time activities was associated with lower nervousness (r = 0.15, p = 0.005). Conclusions: Computer science students reported more frequent psychological symptoms compared to health science students and less somatic symptoms.
Keywords: psychological symptoms, somatic symptoms, technology use, wellbeing, university students
Published in DKUM: 27.11.2024; Views: 0; Downloads: 0
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7.
Using generative artificial intelligence in bibliometric analysis : 10 years of research trends from the European Resuscitation congresses
Nino Fijačko, Ruth Masterson Creber, Benjamin S. Abella, Primož Kocbek, Špela Metličar, Robert Greif, Gregor Štiglic, 2024, other scientific articles

Abstract: Aims: The aim of this study is to use generative artificial intelligence to perform bibliometric analysis on abstracts published at European Resuscitation Council (ERC) annual scientific congress and define trends in ERC guidelines topics over the last decade. Methods: In this bibliometric analysis, the WebHarvy software (SysNucleus, India) was used to download data from the Resuscitation journal’s website through the technique of web scraping. Next, the Chat Generative Pre-trained Transformer 4 (ChatGPT-4) application programming interface (Open AI, USA) was used to implement the multinomial classification of abstract titles following the ERC 2021 guidelines topics. Results: From 2012 to 2022 a total of 2491 abstracts have been published at ERC congresses. Published abstracts ranged from 88 (in 2020) to 368 (in 2015). On average, the most common ERC guidelines topics were Adult basic life support (50.1%), followed by Adult advanced life support (41.5%), while Newborn resuscitation and support of transition of infants at birth (2.1%) was the least common topic. The findings also highlight that the Basic Life Support and Adult Advanced Life Support ERC guidelines topics have the strongest co-occurrence to all ERC guidelines topics, where the Newborn resuscitation and support of transition of infants at birth (2.1%; 52/2491) ERC guidelines topic has the weakest co-occurrence. Conclusion: This study demonstrates the capabilities of generative artificial intelligence in the bibliometric analysis of abstract titles using the example of resuscitation medicine research over the last decade at ERC conferences using large language models.
Keywords: generative artificial intelligence, bibliometric analysis, congress, emergency medicine, European Resuscitation Council
Published in DKUM: 27.11.2024; Views: 0; Downloads: 0
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8.
Effects of a serious smartphone game on nursing students` theoretical knowledge and practical skills in adult basic life support : randomized wait list-controlled trial
Nino Fijačko, Ruth Masterson Creber, Špela Metličar, Matej Strnad, Robert Greif, Gregor Štiglic, Pavel Skok, 2024, original scientific article

Abstract: Background: Retention of adult basic life support (BLS) knowledge and skills after professional training declines over time.To combat this, the European Resuscitation Council and the American Heart Association recommend shorter, more frequent BLS sessions. Emphasizing technology-enhanced learning, such as mobile learning, aims to increase out-of-hospital cardiac arrest (OHCA) survival and is becoming more integral in nursing education. Objective: The aim of this study was to investigate whether playing a serious smartphone game called MOBICPR at home can improve and retain nursing students’ theoretical knowledge of and practical skills in adult BLS. Methods: This study used a randomized wait list–controlled design. Nursing students were randomly assigned in a 1:1 ratio to either a MOBICPR intervention group (MOBICPR-IG) or a wait-list control group (WL-CG), where the latter received the MOBICPR game 2 weeks after the MOBICPR-IG. The aim of the MOBICPR game is to engage participants in using smartphone gestures (eg, tapping) and actions (eg, talking) to perform evidence-based adult BLS on a virtual patient with OHCA. The participants’ theoretical knowledge of adult BLS was assessed using a questionnaire, while their practical skills were evaluated on cardiopulmonary resuscitation quality parameters using a manikin and a checklist. Results: In total, 43 nursing students participated in the study, 22 (51%) in MOBICPR-IG and 21 (49%) in WL-CG. There were differences between the MOBICPR-IG and the WL-CG in theoretical knowledge (P=.04) but not in practical skills (P=.45) after MOBICPR game playing at home. No difference was noted in the retention of participants’ theoretical knowledge and practical skills of adult BLS after a 2-week break from playing the MOBICPR game (P=.13). Key observations included challenges in response checks with a face-down manikin and a general neglect of safety protocols when using an automated external defibrillator. Conclusions: Playing the MOBICPR game at home has the greatest impact on improving the theoretical knowledge of adult BLS in nursing students but not their practical skills. Our findings underscore the importance of integrating diverse scenarios into adult BLS training.
Keywords: serious smartphone game, adult basic life support, teaching, games, gaming, education, nurses, nursing, educational, mHealth, mobile health, applications, smartphones, randomized controlled trial, technology-enhanced learning, life support, knowledge retention, practical
Published in DKUM: 27.11.2024; Views: 0; Downloads: 0
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9.
Using generative AI to improve the performance and interpretability of rule-based diagnosis of Type 2 diabetes mellitus
Leon Kopitar, Iztok Fister, Gregor Štiglic, 2024, original scientific article

Abstract: Introduction: Type 2 diabetes mellitus is a major global health concern, but interpreting machine learning models for diagnosis remains challenging. This study investigates combining association rule mining with advanced natural language processing to improve both diagnostic accuracy and interpretability. This novel approach has not been explored before in using pretrained transformers for diabetes classification on tabular data. Methods: The study used the Pima Indians Diabetes dataset to investigate Type 2 diabetes mellitus. Python and Jupyter Notebook were employed for analysis, with the NiaARM framework for association rule mining. LightGBM and the dalex package were used for performance comparison and feature importance analysis, respectively. SHAP was used for local interpretability. OpenAI GPT version 3.5 was utilized for outcome prediction and interpretation. The source code is available on GitHub. Results: NiaARM generated 350 rules to predict diabetes. LightGBM performed better than the GPT-based model. A comparison of GPT and NiaARM rules showed disparities, prompting a similarity score analysis. LightGBM’s decision making leaned heavily on glucose, age, and BMI, as highlighted in feature importance rankings. Beeswarm plots demonstrated how feature values correlate with their influence on diagnosis outcomes. Discussion: Combining association rule mining with GPT for Type 2 diabetes mellitus classification yields limited effectiveness. Enhancements like preprocessing and hyperparameter tuning are required. Interpretation challenges and GPT’s dependency on provided rules indicate the necessity for prompt engineering and similarity score methods. Variations in feature importance rankings underscore the complexity of T2DM. Concerns regarding GPT’s reliability emphasize the importance of iterative approaches for improving prediction accuracy.
Keywords: GPT, association rule mining, classification, interpretability, diagnostics
Published in DKUM: 26.11.2024; Views: 0; Downloads: 6
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10.
The role of visualization in estimating cardiovascular disease risk : scoping review
Adrijana Svenšek, Mateja Lorber, Lucija Gosak, Katrien Verbert, Zalika Klemenc-Ketiš, Gregor Štiglic, 2024, review article

Abstract: Background: Supporting and understanding the health of patients with chronic diseases and cardiovascular disease (CVD) risk is often a major challenge. Health data are often used in providing feedback to patients, and visualization plays an important role in facilitating the interpretation and understanding of data and, thus, influencing patients’ behavior. Visual analytics enable efficient analysis and understanding of large datasets in real time. Digital health technologies can promote healthy lifestyle choices and assist in estimating CVD risk. Objective: This review aims to present the most-used visualization techniques to estimate CVD risk. Methods: In this scoping review, we followed the Joanna Briggs Institute PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The search strategy involved searching databases, including PubMed, CINAHL Ultimate, MEDLINE, and Web of Science, and gray literature from Google Scholar. This review included English-language articles on digital health, mobile health, mobile apps, images, charts, and decision support systems for estimating CVD risk, as well as empirical studies, excluding irrelevant studies and commentaries, editorials, and systematic reviews. Results: We found 774 articles and screened them against the inclusion and exclusion criteria. The final scoping review included 17 studies that used different methodologies, including descriptive, quantitative, and population-based studies. Some prognostic models, such as the Framingham Risk Profile, World Health Organization and International Society of Hypertension risk prediction charts, Cardiovascular Risk Score, and a simplified Persian atherosclerotic CVD risk stratification, were simpler and did not require laboratory tests, whereas others, including the Joint British Societies recommendations on the prevention of CVD, Systematic Coronary Risk Evaluation, and Framingham-Registre Gironí del COR, were more complex and required laboratory testing–related results. The most frequently used prognostic risk factors were age, sex, and blood pressure (16/17, 94% of the studies); smoking status (14/17, 82%); diabetes status (11/17, 65%); family history (10/17, 59%); high-density lipoprotein and total cholesterol (9/17, 53%); and triglycerides and low-density lipoprotein cholesterol (6/17, 35%). The most frequently used visualization techniques in the studies were visual cues (10/17, 59%), followed by bar charts (5/17, 29%) and graphs (4/17, 24%). Conclusions: On the basis of the scoping review, we found that visualization is very rarely included in the prognostic models themselves even though technology-based interventions improve health care worker performance, knowledge, motivation, and compliance by integrating machine learning and visual analytics into applications to identify and respond to estimation of CVD risk. Visualization aids in understanding risk factors and disease outcomes, improving bioinformatics and biomedicine. However, evidence on mobile health’s effectiveness in improving CVD outcomes is limited.
Keywords: cardiovascular disease prevention, risk factors, visual analytics, visualization, mobile phone, PRISMA
Published in DKUM: 26.11.2024; Views: 0; Downloads: 1
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