Ognjen Milicevic

Background: Depression is approximately twice as prevalent in type 2 diabetes (T2D) compared to non-diabetic individuals, but its underlying mechanisms remain unclear. Insulin resistance (IR) and low-grade inflammation have been proposed as potential contributors. This study investigated whether IR and inflammatory markers are associated with depression in people with T2D. Methods: This cross-sectional study included 189 participants divided into four groups: T2D with depression (A, n = 38), T2D without depression (B, n = 60), depression without T2D (C, n = 44), and healthy controls (D, n = 47). Depression was diagnosed using the MINI-6 and HAMD scale. IR was assessed using the Matsuda index and HOMA-IR, while low-grade inflammation was evaluated by high-sensitivity C-reactive protein (hs-CRP) and interleukin-6 (IL-6). Results: The Matsuda index was significantly lower in group A compared with B, C and D groups (p < 0.001). HOMA-IR was higher in A than in C and D groups, though not significantly different from group B. Hs-CRP was highest in group A (p < 0.001), with no differences among B, C and D. IL-6 was significantly higher in A than B and D (p < 0.001), and similar between A and C. In multivariable analysis younger age, lower Matsuda index, and higher IL-6 independently predicted depression in people with T2D. ROC analysis detected an AUC of 0.75 (p < 0.001) for IL-6, with a sensitivity of 57% and specificity of 82% at the cutoff of 5.29 pg/mL. Conclusions: Our findings suggest that people with T2D and depression exhibit higher IR and elevated IL-6 and hs-CRP levels as parameters of low-grade inflammation. Depression in T2D was associated with younger age, lower Matsuda ISI, and higher IL-6, highlighting the potential relevance of those metabolic and inflammatory biomarkers in this co-occurrence. Further longitudinal studies are needed to clarify causal relationships.

The oncogenicity of the human cytomegalovirus (CMV) is currently being widely debated. Most recently, mounting clinical evidence suggests an anti-cancer effect via CMV-induced T cell-mediated tumor destruction. However, the data were mostly obtained from single-center studies and in vitro experiments. Broad geographic coverage is required to offer a global perspective. Our study examined the correlation between country-specific CMV seroprevalence (across 73 countries) and the age-standardized incidence rate (of 34 invasive tumors). The populations studied were stratified according to decadal age periods as the immunologic effects of CMV seropositivity may depend upon age at initial infection. The International Agency for Research on Cancer of the World Health Organization (IARC WHO) database was used. The multivariate linear regression analysis revealed a worldwide inverse correlation between CMV seroprevalence and the incidences of 62.8% tumors. Notably, this inverse link persists for all cancers combined (Spearman’s ρ = −0.732, p < 0.001; β = −0.482, p < 0.001, adjusted R² = 0.737). An antithetical and significant correlation was also observed in particular age groups for the vast majority of tumors. Our results corroborate the conclusions of previous studies and indicate that this oncopreventive phenomenon holds true on a global scale. It applies to a wide spectrum of cancer histologies, additionally supporting the idea of a common underlying mechanism—CMV-stimulated T cell tumor targeting. Although these results further advance the notion of CMV-based therapies, in-depth investigation of host–virus interactions is still warranted.

Modern studies focus on the discovery of innovative methods to improve the value of post-treatment magnetic resonance imaging (MRI) in the prediction of pathological responses to preoperative neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). The aim of this study was to assess the potential benefits of combining magnetic resonance tumor regression grade (mrTRG) with T2-weighted volumetry in the prediction of pathological responses to nCRT in LARC. This was a cohort study conducted on patients with histopathologically confirmed LARC in a period from 2020 to 2022. After histopathological verification, all patients underwent initial MRI studies, while the follow-up MRI was performed after nCRT. Tumor characteristics, MRI estimated tumor regression grade (mrTRG) and tumor volumetry were evaluated both initially and at follow-up. All patients were classified into responders and non-responders according to pathological tumor regression grade (pTRG) and mrTRG. A total of 71 patients, mostly male (66.2%) were included in the study. The median tumor volume reduction rate was significantly higher in nCRT-responders compared to non-responders (79.9% vs. 63.3%) (p = 0.003). Based on ROC analysis, optimal cut-off value for tumor volume reduction rate was determined with an area under the curve (AUC) value of 0.724 (p = 0.003). Using the tumor volume reduction rate ≥75% with the addition of response to nCRT according to mrTRG, a new scoring system for prediction of pTRG to preoperative nCRT in LARC was developed. Diagnostic performance of prediction score was tested and the sensitivity, PPV, specificity, and NPV were 81.8%, 56.3%, 71.4%, and 89.7%, respectively. The combination of mrTRG and T2-weighted volumetry increases the MRI-based prediction of pTRG to preoperative nCRT in LARC. The proposed scoring system could aid in distinguishing responders to nCRT, as these patients could benefit from organ-preserving treatment and a “watch and wait” strategy.

Previous transcriptome profiling studies showed significantly upregulated genes and altered biological pathways in acute COVID-19. However, changes in the transcriptional signatures during a defined time frame are not yet examined and described. The aims of this study included viral metagenomics and evaluation of the total expression in time-matched and tissue-matched paired COVID-19 samples with the analysis of the host splicing profile to reveal potential therapeutic targets. Prospective analysis of paired nasopharyngeal swabs (NPS) and blood (BL) samples from 18 COVID-19 patients with acute and resolved infection performed using Kallisto, Suppa2, Centrifuge, EdgeR, PantherDB, and L1000CDS2 tools. In NPS, we discovered 6 genes with changed splicing and 40 differentially expressed genes (DEG) that yielded 88 altered pathways. Blood samples yielded 15 alternatively spliced genes. Although the unpaired DEG analysis failed, pairing identified 78 genes and 242 altered pathways with meaningful clinical interpretation and new candidate drug combinations with up to 65% overlap. Metagenomics analyses showed SARS-CoV-2 dominance during and after the acute infection, with a significant reduction in NPS (0.008 vs. 0.002, p = 0.019). Even though both NPS and BL give meaningful insights into expression changes, this is the first demonstration of how the power of blood analysis is vastly maximized by pairing. The obtained results essentially showed that pairing is a determinant between a failed and a comprehensive study. Finally, the bioinformatics results prove to be a comprehensive tool for full-action insights, drug development, and infectious disease research when designed properly.

Background: This study aimed to calculate the frequency of elevated liver enzymes in hospitalized patients with coronavirus disease 2019 (COVID-19) infection and to test if liver enzyme biochemistry levels on admission could predict the computed tomography (CT) scan severity score of bilateral interstitial pneumonia. Methods: This single-center study comprised of 323 patients including their demographic data, laboratory analyses, and radiological findings. All the information was taken from electronic health records, followed by statistical analysis. Results: Out of 323 patients, 115 of them (35.60%) had aspartate aminotransferase (AST) and/or alanine aminotransferase (ALT) over 40 U/L on admission. AST was the best predictor of CT scan severity score of bilateral interstitial pneumonia (R² = 0.313, Adjusted R² = 0.299). CT scan severity score in the peak of the infection could be predicted with the value of AST, neutrophils, platelets, and monocytes count (R² = 0.535, Adjusted R² = 0.495). Conclusion: AST, neutrophils, platelets, and monocytes count on admission can account for almost half (49.5%) of the variability in CT scan severity score at peak of the disease, predicting the extensiveness of interstitial pneumonia related to COVID-19 infection. Liver enzymes should be closely monitored in order to stratify COVID-19 patients with a higher risk of developing severe forms of the disease and to plan the beforehand step-up treatment.

These include, among others, two forms of atypical Parkinsonism, multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). This study aimed to assess the potential role of C9orf72 repeat expansions among Serbian patients diagnosed with MSA and PSP. Genomic DNA of 44 MSA patients, 73 PSP patients, and 96 controls was extracted from peripheral blood, and normal C9orf72 alleles were analyzed by standard quantitative fluorescence polymerase chain reaction (QF-PCR) and fragment analysis. Subsequently, for all samples presenting a single allele, repeat-primed PCR was performed with two different sets of primers to avoid a false-negative result. Thirty repeats were used as a pathogenic cut-off and 20-29 repeats for the intermediate alleles. No pathological C9orf72 expansions were detected in the MSA and PSP patients nor the control subjects. In the MSA group, the most common was the allele with 2 repeats, and the largest repeat number was 14. Among PSP patients, the most common allele also had 2 repeats, while the largest detected repeat size within the normal range was 17. Also, we identified one PSP patient that had an intermediate size allele (25 repeats). We did not find correlation between the number of repeats and disease onset, age at the time of examination, or disease duration in MSA or PSP patients. Regarding family history, in PSP the sum of both allele repeats numbers was higher in patients with positive family history than in sporadic cases. The results presented in this study are the first systematic assessment of C9orf72 allele sizes among patients diagnosed with MSA and PSP in the Serbian population. Although the potential role of intermediate C9orf72 repeats in neurodegenerative disorders is still to be elucidated, our results support the current knowledge that C9orf72 repeat expansions are not associated with MSA and PSP.

Open surgical aortic valve replacement (SAVR) is a viable alternative to transcatheter implantation in low-risk patients. In this light, we evaluated the safety and effectiveness of SAVR performed through conventional and less invasive surgical approaches in a high-volume center. We retrospectively reviewed the records of 395 consecutive patients who underwent open SAVR from January 2019 through December 2019 in our center. We evaluated and compared the operative results and postoperative major adverse outcomes of 3 surgical approaches: full median sternotomy (n=267), upper ministernotomy (ministernotomy) (n=106), and right anterior thoracotomy (minithoracotomy) (n=22). Overall, the 30-day all-cause mortality rate was 0.8% (3 patients). Stroke occurred in 8 patients (2%), disabling stroke in 4 patients (1%), myocardial infarction in 1 (0.2%), and surgical site infection in 13 (3.2%). There was no difference in 30-day mortality rate or incidence of postoperative major adverse events among the 3 surgical groups. Stroke and surgical site infection occurred more frequently, but not significantly so, in the full-sternotomy group. The mean hospital stay was longer after full sternotomy (9.1 ± 5.5 d) than after ministernotomy (7.5 ± 2.9 d) or minithoracotomy (7.4 ± 1.9 d) (P=0.012). Our findings suggest that open SAVR performed in a high-volume center is associated with a low early mortality rate and that less invasive approaches result in faster postoperative recovery and shorter hospital stays.

Identifying the main environmental drivers of SARS-CoV-2 transmissibility in the population is crucial for understanding current and potential future outbursts of COVID-19 and other infectious diseases. To address this problem, we concentrate on basic reproduction number R0, which is not sensitive to testing coverage and represents transmissibility in an absence of social distancing and in a completely susceptible population. While many variables may potentially influence R0, a high correlation between these variables may obscure the result interpretation. Consequently, we combine Principal Component Analysis with feature selection methods from several regression-based approaches to identify the main demographic and meteorological drivers behind R0. We robustly obtain that country’s wealth/development (GDP per capita or Human Development Index) is by far the most important R0 predictor, probably being a good proxy for the overall contact frequency in a population. This main effect is modulated by built-up area per capita (crowdedness in indoor space), onset of infection (likely related to increased awareness of infection risks), net migration, unhealthy living lifestyle/conditions including pollution, seasonality, and possibly BCG vaccination prevalence. Also, we show that several variables that significantly correlate with transmissibility do not directly influence R0 or affect it differently than suggested by naive analysis.

Identifying the main environmental drivers of SARS-CoV-2 transmissibility in the population is crucial for understanding current and potential future outbursts of COVID-19 and other infectious diseases. To address this problem, we concentrate on basic reproduction number R ₀ , which is not sensitive to testing coverage and represents transmissibility in an absence of social distancing and in a completely susceptible population. While many variables may potentially influence R ₀ , a high correlation between these variables may obscure the result interpretation. Consequently, we combine Principal Component Analysis with feature selection methods from several regression-based approaches to identify the main demographic and meteorological drivers behind R ₀ . We robustly obtain that country’s wealth/development (GDP per capita or Human Development Index) is by far the most important R ₀ predictor, probably being a good proxy for the overall contact frequency in a population. This main effect is modulated by built-up area per capita (crowdedness in indoor space), onset of infection (likely related to increased awareness of infection risks), net migration, unhealthy living lifestyle/conditions including pollution, seasonality, and possibly BCG vaccination prevalence. Also, we show that several variables that significantly correlate with transmissibility do not directly influence R ₀ or affect it differently than suggested by naïve analysis.