Liquid biopsy-based methods to test biomarkers (e.g., serum proteins and extracellular vesicles) may help to monitor brain tumors. In this proteomics-based study, we aimed to identify a characteristic protein fingerprint associated with central nervous system (CNS) tumors. Overall, 96 human serum samples were obtained from four patient groups, namely glioblastoma multiforme (GBM), non-small-cell lung cancer brain metastasis (BM), meningioma (M) and lumbar disc hernia patients (CTRL). After the isolation and characterization of small extracellular vesicles (sEVs) by nanoparticle tracking analysis (NTA) and atomic force microscopy (AFM), liquid chromatography -mass spectrometry (LC-MS) was performed on two different sample types (whole serum and serum sEVs). Statistical analyses (ratio, Cohen’s d, receiver operating characteristic; ROC) were carried out to compare patient groups. To recognize differences between the two sample types, pairwise comparisons (Welch’s test) and ingenuity pathway analysis (IPA) were performed. According to our knowledge, this is the first study that compares the proteome of whole serum and serum-derived sEVs. From the 311 proteins identified, 10 whole serum proteins and 17 sEV proteins showed the highest intergroup differences. Sixty-five proteins were significantly enriched in sEV samples, while 129 proteins were significantly depleted compared to whole serum. Based on principal component analysis (PCA) analyses, sEVs are more suitable to discriminate between the patient groups. Our results support that sEVs have greater potential to monitor CNS tumors, than whole serum.

Metabolomic reprogramming in tumor and stroma cells is a hallmark of cancer but understanding its effects on the metabolite composition and function of tumor-derived extracellular vesicles (EVs) is still in its infancy. EVs are membrane-bound sacs with a complex molecular composition secreted by all living cells. They are key mediators of intercellular communication both in normal and pathological conditions and play a crucial role in tumor development. Although lipids are major components of EVs, most of the EV cargo studies have targeted proteins and nucleic acids. The potential of the EV metabolome as a source for biomarker discovery has gained recognition recently, but knowledge on the biological activity of tumor EV metabolites still remains limited. Therefore, we aimed (i) to compile the list of metabolites identified in tumor EVs isolated from either clinical specimens or in vitro samples and (ii) describe their role in tumor progression through literature search and pathway analysis.

Matrix metalloproteinase-9 (MMP-9) degrades the extracellular matrix, contributes to tumour cell invasion and metastasis, and its elevated level in brain tumour tissues indicates poor prognosis. High-risk tissue biopsy can be replaced by liquid biopsy; however, the blood–brain barrier (BBB) prevents tumour-associated components from entering the peripheral blood, making the development of blood-based biomarkers challenging. Therefore, we examined the MMP-9 content of small extracellular vesicles (sEVs)—which can cross the BBB and are stable in body fluids—to characterise tumours with different invasion capacity. From four patient groups (glioblastoma multiforme, brain metastases of lung cancer, meningioma, and lumbar disc herniation as controls), 222 serum-derived sEV samples were evaluated. After isolating and characterising sEVs, their MMP-9 content was measured by ELISA and assessed statistically (correlation, paired t-test, Welch’s test, ANOVA, ROC). We found that the MMP-9 content of sEVs is independent of gender and age, but is affected by surgical intervention, treatment, and recurrence. We found a relation between low MMP-9 level in sEVs (<28 ppm) and improved survival (8-month advantage) of glioblastoma patients, and MMP-9 levels showed a positive correlation with aggressiveness. These findings suggest that vesicular MMP-9 level might be a useful prognostic marker for brain tumours.

Investigating the molecular composition of small extracellular vesicles (sEVs) for tumor diagnostic purposes is becoming increasingly popular, especially for diseases for which diagnosis is challenging, such as central nervous system (CNS) malignancies. Thorough examination of the molecular content of sEVs by Raman spectroscopy is a promising but hitherto barely explored approach for these tumor types. We attempt to reveal the potential role of serum-derived sEVs in diagnosing CNS tumors through Raman spectroscopic analyses using a relevant number of clinical samples. A total of 138 serum samples were obtained from four patient groups (glioblastoma multiforme, non-small-cell lung cancer brain metastasis, meningioma and lumbar disc herniation as control). After isolation, characterization and Raman spectroscopic assessment of sEVs, the Principal Component Analysis–Support Vector Machine (PCA–SVM) algorithm was performed on the Raman spectra for pairwise classifications. Classification accuracy (CA), sensitivity, specificity and the Area Under the Curve (AUC) value derived from Receiver Operating Characteristic (ROC) analyses were used to evaluate the performance of classification. The groups compared were distinguishable with 82.9–92.5% CA, 80–95% sensitivity and 80–90% specificity. AUC scores in the range of 0.82–0.9 suggest excellent and outstanding classification performance. Our results support that Raman spectroscopic analysis of sEV-enriched isolates from serum is a promising method that could be further developed in order to be applicable in the diagnosis of CNS tumors.

Background and Aims From 2019 till the present, infections induced by the novel coronavirus and its mutations have posed a new challenge for healthcare. However, comparative studies on pediatric infections throughout waves are few. During four different pandemic waves, we intended to investigate the clinical and epidemiological characteristic of the pediatric population hospitalized for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) virus infection. Methods Between March 2020 and December 2021, we performed our retrospective research on children infected with the SARS‐CoV‐2 virus at the University of Szeged. We analyzed the data of all patients who required hospitalization due to positive results of SARS‐CoV‐2 tests (Nucleic Acid Amplification Test or rapid antigen test). Data analysis included demographic data, medical history, clinical findings, length of hospitalization, and complications, using medical records. Results In this study, data from 358 coronavirus‐infected children were analyzed. The most affected age group was children over 1 month and under 1 year (30.2%). The highest number of cases was recorded in the fourth wave (53.6%). Fever (65.6%), cough (51.4%), nasal discharge (35.3%), nausea and vomiting (31.3%), and decreased oral intake (28.9%) were the most common symptoms. The most common complications were dehydration (50.5%), pneumonia (14.9%), and bronchitis/bronchiolitis (14.5%). Based on RR values, there are considerable differences in the prevalence of the symptoms and complications between the different age groups and waves. Cox proportional hazard model analyzes showed that fever and tachypnoea had a relevant effect on days to recovery. Conclusions We found trends similar to those previously published, overall statistics. The proportion of children requiring hospitalization varied from wave to wave, with the fourth wave affecting the Hungarian child population the most. Our findings suggest that hospitalization time is unrelated to age, but that certain symptoms (fever and tachypnoea) are associated with longer hospitalization. The onset of certain symptoms may differ by age group.

The aim of this study is to describe four new cases of trepanation from the Great Hungarian Plain and complement two other previously published cases with new results from the 9th to 16th c. CE. Sex determination and age-at-death estimation were performed using classical macromorphological methods. In certain cases, radiographic imaging, 3D scanning, and radiocarbon dating were also performed. Our cases fit the formerly established understanding of trepanations, with a male majority and signs of trauma as accompanying symptoms. The cause of intervention was mostly therapeutic, i.e., trauma, in most cases. In order to simplify the currently confusing nomenclature in trepanation categories (complete–incomplete vs. surgical–symbolic), we propose the use of “trepanation” exclusively to all forms of intentional, non-violent removals of all three layers of the cranial vault. On the other hand, the phenomena widely known in Eastern Europe as symbolic trepanations should be designated as “cranioglyphs,” referring to all forms of superficial interventions administered to the cranial vault that do not penetrate all three layers of the bone. In case the data are insufficient to properly categorize the phenomenon at hand, one should refrain from it, and simply describe the lesion as intentional cranial intervention. In order to bring spotlight to the wide range of cranial interventions in the early medieval Carpathian Basin, our team is conducting several research projects, in order to contribute to a better understanding of these traditions in the future.

Extracellular vesicle (EV) research is a rapidly developing field, mainly due to the key role of EVs in intercellular communication and pathophysiological processes. However, the heterogeneity of EVs challenges their exploration and the establishment of gold-standard methods. Here, we aimed to reveal the influence of technical changes on EV biology and the reliability of experimental data. We used B16F1 melanoma cells as a model and applied nanoparticle tracking analysis, mass spectrometry (LC-MS/MS) and pathway enrichment analysis to analyze the quantity, size distribution, proteome and function of their small EVs (sEVs) produced in sEV-depleted fetal bovine serum (FBS)-containing medium or serum-free medium. Additionally, we investigated the effects of minor technical variances on the quality of sEV preparations. We found that storage of the isolates at −80 °C has no adverse effect on LC-MS/MS analysis, and an additional washing step after differential ultracentrifugation has a minor influence on the sEV proteome. In contrast, FBS starvation affects the production and proteome of sEVs; moreover, these vesicles may have a greater impact on protein metabolism, but a smaller impact on cell adhesion and membrane raft assembly, than the control sEVs. As we demonstrated that FBS starvation has a strong influence on sEV biology, applying serum-free conditions might be considered in in vitro sEV studies.

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