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Abstract Hereditary α tryptasemia (HαT) is an autosomal dominant trait characterized by increased TPSAB1 copy number (CN) encoding α-tryptase. The determination of HαT is being discussed as an important biomarker to be included in risk assessment models and future diagnostic algorithms for patients with mastocytosis and anaphylaxis. Due to the complex genetic structure at the human tryptase locus, genetic testing for tryptase gene composition is presently notably limited and infrequently pursued. This study aimed to develop, optimise and validate a multiplex droplet digital PCR (ddPCR) assay that can reliably quantify α- and β-tryptase encoding sequences in a single reaction. To optimise the ddPCR conditions and establish an amplitude-based multiplex ddPCR assay, additional primers and probes, a thermal gradient with varying annealing temperatures, different primers/probe concentrations, and various initial DNA quantities were tested. Results obtained from all 114 samples analysed using multiplex ddPCR were identical to those obtained through the use of original duplex assays. Utilizing this multiplex ddPCR assay, in contrast to conducting distinct duplex ddPCRs, presents noteworthy benefits for tryptase genotyping. These advantages encompass a substantial threefold decrease in material costs and considerable time savings. Consequently, this approach exhibits high suitability and particularly captures interest for routine clinical implementation.

Chronic spontaneous urticaria (CSU) is associated with skin mast cell activation, and its triggering mechanisms are not completely elucidated. Evidence suggests an autoimmune component of CSU. Our aim was to assess the usefulness of an autoimmune mast cell activation test (aiMAT) for diagnosing and differentiating CSU into different subtypes. We enrolled 43 patients with active, uncontrolled CSU before starting treatment with omalizumab and 15 controls. Patients were evaluated based on omalizumab response. aiMATs were performed using non-IgE-sensitized (NS) or myeloma IgE-sensitized (S) LAD2 cells, which were then stimulated with CSU/control sera (25 µL and 10 µL). The expression of CD63 was assessed with flow cytometry. CD63 response on NS-LAD2 was significantly increased in CSU patients compared to controls after the stimulation with 25 µL CSU/control sera (p = 0.0007) and with 10 µL CSU/control sera (p = 0.0001). The ROC curve analysis demonstrated an area under the curve (AUC) of 0.82. The cutoff for autoimmune-non-IgE-sensitized-MAT was 40.3% CD63+ LAD2, which resulted in 73.3% sensitivity and 81.4% specificity. CD63 response on S-LAD2 was significantly increased in CSU patients compared to controls after the stimulation with 25 µL CSU/control sera (p = 0.03). The ROC curve analysis demonstrated an AUC of 0.66. The cutoff for the autoimmune-myeloma IgE-sensitized-MAT was 58.4% CD63+ cells, which resulted in 62.8% sensitivity and 66.7% specificity. Overall, 36 out of 43 (84%) patients responded to omalizumab, and 7 (16%) were nonresponders. We found no differences between LAD2 CD63 response and response to omalizumab. In conclusion, aiMAT could represent a new diagnostic tool in CSU. Additional studies are needed to evaluate the potential benefits during omalizumab therapy.

Determining the genetic contribution of susceptibility to severe SARS-CoV-2 infection outcomes is important for public health measures and individualized treatment. Through intense research on this topic, several hundred genes have been implicated as possibly contributing to the severe infection phenotype(s); however, the findings are complex and appear to be population-dependent. We aimed to determine the contribution of human rare genetic variants associated with a severe outcome of SARS-CoV-2 infections and their burden in the Slovenian population. A panel of 517 genes associated with severe SARS-CoV-2 infection were obtained by combining an extensive review of the literature, target genes identified by the COVID-19 Host Genetic Initiative, and the curated Research COVID-19 associated genes from PanelApp, England Genomics. Whole genome sequencing was performed using PCR-free WGS on DNA from 60 patients hospitalized due to severe COVID-19 disease, and the identified rare genomic variants were analyzed and classified according to the ACMG criteria. Background prevalence in the general Slovenian population was determined by comparison with sequencing data from 8025 individuals included in the Slovenian genomic database (SGDB). Results show that several rare pathogenic/likely pathogenic genomic variants in genes CFTR, MASP2, MEFV, TNFRSF13B, and RNASEL likely contribute to the severe infection outcomes in our patient cohort. These results represent an insight into the Slovenian genomic diversity associated with a severe COVID-19 outcome.

Upon first exposure to cetuximab, hypersensitivity reactions can occur. We aimed to assess the utility of the basophil activation test (BAT) to alpha-gal and cetuximab for predicting severe reactions. We prospectively recruited 38 patients and evaluated sIgE to alpha-gal in all patients before the first application of cetuximab. In all alpha-gal-sensitized patients, we evaluated skin tests to meat extracts, gelatine, and cetuximab and performed BAT with alpha-gal and cetuximab. In 24% (9/38) of patients, sIgE to alpha-gal was >0.10 kUA/L, and 8/9 reacted to the cetuximab. Basophil activation tests with alpha-gal were positive in all sensitized patients and were higher in those with severe reactions (18.3% in grade 4 [n = 4] vs. 1.8% in grade 2 [n = 3] or no reaction [n = 1] at 3.3 ng/mL of alpha-gal; p = 0.03). All patients with severe grade 4 reactions had a positive CD63 BAT response to cetuximab compared to patients with moderate or no reaction, who all had negative BAT (57.7% vs. 0.9% at 500 µg/mL, 63.2% vs. 4.1% at 100 µg/mL, 58.2% vs. 2.7% at 10 µg/mL, and 32.1% vs. 3.3% at 1 µg/mL of cetuximab, respectively; p ≤ 0.001). In summary, before initiating cetuximab treatment, sIgE to alpha-gal should be assessed in all patients. To predict the severity of the reaction and to assess the risk of cetuximab-induced anaphylaxis, we should perform BATs with alpha-gal or more discriminative BATs with cetuximab.

Allergen-specific venom immunotherapy (VIT) is a well-established therapy for Hymenoptera venom allergy (HVA). However, the precise mechanism underlying its clinical effect remains uncertain. Our study aimed to identify the molecular mechanisms associated with VIT efficiency. We prospectively included 19 patients with HVA undergoing VIT (sampled before the beginning of VIT, after reaching the maintenance dose, one year after finishing VIT, and after a sting challenge) and 9 healthy controls. RNA sequencing of whole blood was performed on an Illumina sequencing platform. Longitudinal transcriptomic profiling revealed the importance of the inhibition of the NFκB pathway and the downregulation of DUX4 transcripts for the early protection and induction of tolerance after finishing VIT. Furthermore, successful treatment was associated with inhibiting Th2, Th17, and macrophage alternative signalling pathways in synergy with the inhibition of the PPAR pathway and further silencing of the Th2 response. The immune system became activated when reaching the maintenance dose and was suppressed after finishing VIT. Finally, successful VIT restores the immune system’s balance to a state similar to that of healthy individuals. Our results underline the important role of the inhibition of four pathways in the clinical effect of VIT: Th2, Th17, NFκB, and macrophage signalling. Two biomarkers specific for successful VIT, regardless of the time of sampling, were C4BPA and RPS10-NUDT3 and should be further tested as potential biomarkers.

Hymenoptera venom–triggered anaphylaxis (HVA) affects up to 8.9% of the general population and is the most frequent cause of anaphylaxis in adults, accounting for approximately 20% of all fatal anaphylaxis cases. Quite often, a fatal reaction is a victim’s first manifestation of HVA. Mastocytosis represents one of the most important risk factors for severe HVA. We analyzed patients with documented fatal HVA for the presence of underlying clonal mast cell disorder (cMCD). Here, we report three cases of fatal HVA, with undiagnosed underlying cMCD identified by the presence of the peripheral blood and/or bone marrow KIT p.D816V missense variant postmortem. In the first case, anaphylaxis was the initial episode and was fatal. In the other two cases, both patients were treated with specific venom immunotherapy (VIT), nevertheless, one died of HVA after VIT discontinuation, and the other during VIT; both patients had cardiovascular comorbidities and were taking beta-blockers and/or ACE inhibitors. Our results point to the importance of screening all high-risk individuals for underlying cMCD using highly sensitive molecular methods for peripheral blood KIT p.D816V variant detection, including severe HVA and possibly beekeepers, for proper management and the need for lifelong VIT to prevent unnecessary deaths. Patients at the highest risk of fatal HVA, with concomitant cardiovascular and cMCD comorbidities, might not be protected from field stings even during regular VIT. Therefore, two adrenaline autoinjectors and lifelong VIT, and possibly cotreatment with omalizumab, should be considered for high-risk patients to prevent fatal HVA episodes.

Abstract Background The malignant pleural mesothelioma (MPM) response rate to chemotherapy is low. The identification of imaging biomarkers that could help guide the most effective therapy approach for individual patients is highly desirable. Our aim was to investigate the dynamic contrast-enhanced (DCE) MR parameters as predictors for progression-free (PFS) and overall survival (OS) in patients with MPM treated with cisplatin-based chemotherapy. Methods Thirty-two consecutive patients with MPM were enrolled in this prospective study. Pretreatment and intratreatment DCE-MRI were scheduled in each patient. The DCE parameters were analyzed using the extended Tofts (ET) and the adiabatic approximation tissue homogeneity (AATH) model. Comparison analysis, logistic regression and ROC analysis were used to identify the predictors for the patient’s outcome. Results Patients with higher pretreatment ET and AATH-calculated K trans and ve values had longer OS (P≤.006). Patients with a more prominent reduction in ET-calculated K trans and kep values during the early phase of chemotherapy had longer PFS (P =.008). No parameter was identified to predict PFS. Pre-treatment ET-calculated K trans was found to be an independent predictive marker for longer OS (P=.02) demonstrating the most favourable discrimination performance compared to other DCE parameters with an estimated sensitivity of 89% and specificity of 78% (AUC 0.9, 95% CI 0.74-0.98, cut off > 0.08 min-1). Conclusions In the present study, higher pre-treatment ET-calculated K trans values were associated with longer OS. The results suggest that DCE-MRI might provide additional information for identifying MPM patients that may respond to chemotherapy.

Background The relationship between anti-SARS-CoV-2 humoral immune response, pathogenic inflammation, lymphocytes and fatal COVID-19 is poorly understood. Methods A longitudinal prospective cohort of hospitalised patients with COVID-19 (n=254) was followed up to 35 days after admission (median, 8 days). We measured early anti-SARS-CoV-2 S1 antibody IgG levels and dynamic (698 samples) of quantitative circulating T-, B- and natural killer lymphocyte subsets and serum interleukin-6 (IL-6) response. We used machine learning to identify patterns of the immune response and related these patterns to the primary outcome of 28-day mortality in analyses adjusted for clinical severity factors. Results Overall, 45 (18%) patients died within 28 days after hospitalisation. We identified six clusters representing discrete anti-SARS-CoV-2 immunophenotypes. Clusters differed considerably in COVID-19 survival. Two clusters, the anti-S1-IgGlowestTlowestBlowestNKmodIL-6mod, and the anti-S1-IgGhighTlowBmodNKmodIL-6highest had a high risk of fatal COVID-19 (HR 3.36–21.69; 95% CI 1.51–163.61 and HR 8.39–10.79; 95% CI 1.20–82.67; p≤0.03, respectively). The anti-S1-IgGhighestTlowestBmodNKmodIL-6mod and anti-S1-IgGlowThighestBhighestNKhighestIL-6low cluster were associated with moderate risk of mortality. In contrast, two clusters the anti-S1-IgGhighThighBmodNKmodIL-6low and anti-S1-IgGhighestThighestBhighNKhighIL-6lowest clusters were characterised by a very low risk of mortality. Conclusions By employing unsupervised machine learning we identified multiple anti-SARS-CoV-2 immune response clusters and observed major differences in COVID-19 mortality between these clusters. Two discrete immune pathways may lead to fatal COVID-19. One is driven by impaired or delayed antiviral humoral immunity, independently of hyper-inflammation, and the other may arise through excessive IL-6-mediated host inflammation response, independently of the protective humoral response. Those observations could be explored further for application in clinical practice.

BackgroundAnaphylaxis is an acute life-threatening allergic reaction and a concern at a global level; therefore, further progress in understanding the underlying mechanisms and more effective strategies for diagnosis, prevention and management are needed.ObjectiveWe sought to identify the global architecture of blood transcriptomic features of anaphylaxis by integrating expression data from human patients and mouse model of anaphylaxis.MethodsBulk RNA-sequencings of peripheral whole blood were performed in: i) 14 emergency department (ED) patients with acute anaphylaxis, predominantly to Hymenoptera venom, ii) 11 patients with peanut allergy undergoing double-blind, placebo-controlled food challenge (DBPCFC) to peanut, iii) murine model of IgE-mediated anaphylaxis. Integrative characterisation of differential gene expression, immune cell-type-specific gene expression profiles, and functional and pathway analysis was undertaken.Results1023 genes were commonly and significantly dysregulated during anaphylaxis in ED and DBPCFC patients; of those genes, 29 were also dysregulated in the mouse model. Cell-type-specific gene expression profiles showed a rapid downregulation of blood basophil and upregulation of neutrophil signature in ED and DBPCFC patients and the mouse model, but no consistent and/or significant differences were found for other blood cells. Functional and pathway analysis demonstrated that human and mouse blood transcriptomic signatures of anaphylaxis follow trajectories of upregulation of cell movement, migration and neuroinflammatory signalling, and downregulation of lipid activating nuclear receptors signalling.ConclusionOur study highlights the matched and extensive blood transcriptomic changes and suggests the involvement of discrete cellular components and upregulation of migration and neuroinflammatory pathways during anaphylaxis.

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Oligometastatic disease (OMD) is a stage between locally advanced disease and polymetastatic disease, a group of diseases that are used interchangeably based on treatment history, ongoing treatment status, and imaging findings. The diagnosis of OMD is based on imaging because, as of yet, we are not aware of any specific biomarkers that would enable us to recognize patients with a low disease burden. In recent years, there has been an increasing interest in optimizing the treatment of OMD, owing mostly to the promising outcomes of combining local and systemic treatment. For the first time, the prospect of achieving long-term cures or possibly curing these individuals was established using this form of treatment. The standard name of OMD subgroups allows for the comparison of diverse circumstances in everyday clinical work, as well as the classification for clinical study comparability.

Abstract Despite widely and regularly used therapy asthma in children is not fully controlled. Recognizing the complexity of asthma phenotypes and endotypes imposed the concept of precision medicine in asthma treatment. By applying machine learning algorithms assessed with respect to their accuracy in predicting treatment outcome, we have successfully identified 4 distinct clusters in a pediatric asthma cohort with specific treatment outcome patterns according to changes in lung function (FEV1 and MEF50), airway inflammation (FENO) and disease control likely affected by discrete phenotypes at initial disease presentation, differing in the type and level of inflammation, age of onset, comorbidities, certain genetic and other physiologic traits. The smallest and the largest of the 4 clusters- 1 (N = 58) and 3 (N = 138) had better treatment outcomes compared to clusters 2 and 4 and were characterized by more prominent atopic markers and a predominant allelic (A allele) effect for rs37973 in the GLCCI1 gene previously associated with positive treatment outcomes in asthmatics. These patients also had a relatively later onset of disease (6 + yrs). Clusters 2 (N = 87) and 4 (N = 64) had poorer treatment success, but varied in the type of inflammation (predominantly neutrophilic for cluster 4 and likely mixed-type for cluster 2), comorbidities (obesity for cluster 2), level of systemic inflammation (highest hsCRP for cluster 2) and platelet count (lowest for cluster 4). The results of this study emphasize the issues in asthma management due to the overgeneralized approach to the disease, not taking into account specific disease phenotypes.

Background and Objectives: A peanut allergy is the most common single cause of anaphylaxis in children. The risk factors for anaphylaxis in children with a peanut allergy are not well defined. Therefore, we aimed to identify epidemiological, clinical, and laboratory characteristics of children with a peanut allergy that may predict the severity of the allergic reaction and anaphylaxis. Materials and Methods: We conducted a cross-sectional study and included 94 children with a peanut allergy. Allergy testing was performed, including skin prick testing and the determination of specific IgE levels to peanuts and their Ara h2 component. In case of discordance between patient history and allergy testing, an oral food challenge with peanuts was performed. Results: Anaphylaxis and moderate and mild reactions to peanuts occurred in 33 (35.1%), 30 (31.9%), and 31 (33.0%) patients, respectively. The severity of the allergic reaction was only weakly correlated (p = 0.04) with the amount of peanuts consumed. The median number of allergic reactions to peanuts was 2 in children with anaphylaxis compared to 1 in other patients (p = 0.04). The median level of specific IgE to Ara h2 was 5.3 IU/mL in children with anaphylaxis compared to 0.6 IU/mL and 10.3 IU/mL in children with mild and moderate peanut allergies (p = 0.06). The optimal cutoff for distinguishing between anaphylaxis and a less severe allergic reaction to peanuts was a specific IgE Ara h2 level of 0.92 IU/mL with 90% sensitivity and 47.5% specificity for predicting anaphylaxis (p = 0.04). Conclusions: Epidemiological and clinical characteristics of the patient cannot predict the severity of the allergic reaction to peanuts in children. Even standard allergy testing, including component diagnostics, is a relatively poor predictor of the severity of an allergic reaction to peanuts. Therefore, more accurate predictive models, including new diagnostic tools, are needed to reduce the need for oral food challenge in most patients.

Chronic rhinosinusitis (CRS) is a multifaceted disease with variable clinical courses and outcomes. We aimed to determine CRS-associated nasal-tissue transcriptome in clinically well-characterized and phenotyped individuals, to gain a novel insight into the biological pathways of the disease. RNA-sequencing of tissue samples of patients with CRS with polyps (CRSwNP), without polyps (CRSsNP), and controls were performed. Characterization of differently expressed genes (DEGs) and functional and pathway analysis was undertaken. We identified 782 common CRS-associated nasal-tissue DEGs, while 375 and 328 DEGs were CRSwNP- and CRSsNP-specific, respectively. Common key DEGs were found to be involved in dendritic cell maturation, the neuroinflammation pathway, and the inhibition of the matrix metalloproteinases. Distinct CRSwNP-specific DEGs were involved in NF-kβ canonical pathways, Toll-like receptor signaling, HIF1α regulation, and the Th2 pathway. CRSsNP involved the NFAT pathway and changes in the calcium pathway. Our findings offer new insights into the common and distinct molecular mechanisms underlying CRSwNP and CRSsNP, providing further understanding of the complex pathophysiology of the CRS, with future research directions for novel treatment strategies.

Protein–peptide interactions are an essential player in cellular processes and, thus, of great interest as potential therapeutic agents. However, identifying the protein’s interacting surface has been shown to be a challenging task. Here, we present a methodology for protein–peptide interaction identification, implementing phage panning, next-generation sequencing and bioinformatic analysis. One of the uses of this methodology is identification of allergen epitopes, especially suitable for globular inhaled and venom allergens, where their binding capability is determined by the allergen’s conformation, meaning their interaction cannot be properly studied when denatured. A Ph.D. commercial system based on the M13 phage vector was used for the panning process. Utilization of various bioinformatic tools, such as PuLSE, SAROTUP, MEME, Hammock and Pepitope, allowed us to evaluate a large amount of obtained data. Using the described methodology, we identified three peptide clusters representing potential epitopes on the major wasp venom allergen Ves v 5.

Izhodišče: Diabetično retinopatijo lahko opredelimo kot kronično subklinično vnetje. Želeli smo ugotoviti razlike v ravneh vnetnih citokinov med steklovino in serumom pri bolnikih s proliferativno diabetično retinopatijo (PDR) pri kontrolni skupini ter primerjati ravni citokinov v steklovini glede na aktivnost PDR. Boljše poznavanje vnetnega dogajanja v očesu bolnikov s PDR bi lahko prispevalo k razvoju novih načinov zdravljenja teh bolnikov. Metode: V raziskavo smo vključili 37 bolnikov (37 oči) s PDR, pri katerih je bila potrebna vitrektomija, ter 20 bolnikov (20 oči) z idiopatskim foramnom makule (FM), ki so predstavljali kontrolno skupino. Glede na pregled pred operacijo in oceno očesnega ozadja med samim posegom smo opredelili aktivnost PDR. V steklovini in serumu smo s citometrično metodo CBA (angl. Cytometric Bead Array) analizirali citokine interlevkin 1β (IL-1β), dejavnik tumorske nekroze α (TNF-α), makrofagni vnetni protein 1α (MIP-1α), makrofagni vnetni protein 1β (MIP-1β), monocitni kemotaktični protein 1 (MCP-1), žilni endotelni rastni dejavnik (VEGF), interlevkin 6 (IL-6), interlevkin 8 (IL-8), interlevkin 10 (IL-10) in interlevkin 12 (IL-12). Rezultati: Ravni vseh citokinov so se v steklovini pomembno razlikovale od ravni v serumu. Raven MCP-1, VEGF, IL-6, IL-8 v steklovini bolnikov s PDR je bila statistično pomembno višja v primerjavi z ravnijo v steklovini pri bolnikih v kontrolni skupini, raven MIP-1α, IL-10 in IL-12 v steklovini bolnikov s PDR je bila statistično pomembno nižja v primerjavi z bolniki v kontrolni skupini (p

Besides the numerous studies in the last decade involving food and nutrition data, this domain remains low resourced. Annotated corpuses are very useful tools for researchers and experts of the domain in question, as well as for data scientists for analysis. In this paper, we present the annotation process of food consumption data (recipes) with semantic tags from different semantic resources—Hansard taxonomy, FoodOn ontology, SNOMED CT terminology and the FoodEx2 classification system. FoodBase is an annotated corpus of food entities—recipes—which includes a curated version of 1000 instances, considered a gold standard. In this study, we use the curated version of FoodBase and two different approaches for annotating—the NCBO annotator (for the FoodOn and SNOMED CT annotations) and the semi-automatic StandFood method (for the FoodEx2 annotations). The end result is a new version of the golden standard of the FoodBase corpus, called the CafeteriaFCD (Cafeteria Food Consumption Data) corpus. This corpus contains food consumption data—recipes—annotated with semantic tags from the aforementioned four different external semantic resources. With these annotations, data interoperability is achieved between five semantic resources from different domains. This resource can be further utilized for developing and training different information extraction pipelines using state-of-the-art NLP approaches for tracing knowledge about food safety applications.

Ragweed is a prominent cause of seasonal allergies. Thus far, information on IgE-binding sites of major allergen in ragweed pollen, Amb a 1, is very limited. A powerful experimental method to gain insights on the allergen epitopes is the selection of peptides from biological libraries that bind to anti-allergen antibodies. In this work, we aimed to map IgE epitopes of Amb a 1 using epitope-mimicking short peptides – mimotopes that were affinity-selected from phage-displayed random peptide libraries. The peptides weakly aligned with the Amb a 1 primary sequence, thus suggesting that the epitopes are conformational. When the peptides were mapped onto the surface of Amb a 1 homology model, the EpiSearch analysis predicted the location of four potential epitopic sites on surface patches centred at residues K104, S110, H214, and W312. The peptides matching to the predicted epitopes bound selectively to the IgE from pool of ragweed-allergic patients’ sera and therefore represent mimetics of Amb a 1 IgE epitopes. The knowledge of IgE epitopes is a prerequisite for the rational design of molecular-based approaches to diagnosis and immunotherapy of allergic diseases.

Recent studies have suggested that causative variants in telomerase complex genes (TCGs) are present in around 10% of individuals with idiopathic pulmonary fibrosis (IPF) regardless of family history of the disease. However, the studies used a case-control rare variant enrichment study design which is not directly translatable to routine practice. To validate the prevalence results and to establish the individual level, routine clinical practice, and utility of those results we performed next generation sequencing of TCGs on a cohort of well-characterized consecutive individuals with IPF (diagnosis established according to ATS/ERS/JRS/ALAT guidelines). Of 27 IPF patients, three had a family history of idiopathic interstitial pneumonia (familial IPF) and 24 did not (sporadic IPF). Pathogenic/likely-pathogenic variants (according to American College of Medical Genetics criteria) in TCG were found in three individuals (11.1%) of the whole cohort; specifically, they were present in 2 out of 24 (8.3%) of the sporadic and in 1 out of 3 (33.3%) of the patients with familial IPF. Our results, which were established on an individual-patient level study design and in routine clinical practice (as opposed to the case-control study design), are roughly in line with the around 10% prevalence of causative TCG variants in patients with IPF.

In optimization, algorithm selection, which is the selection of the most suitable algorithm for a specific problem, is of great importance, as algorithm performance is heavily dependent on the problem being solved. However, when using machine learning for algorithm selection, the performance of the algorithm selection model depends on the data used to train and test the model, and existing optimization benchmarks only provide a limited amount of data. To help with this problem, artificial problem generation has been shown to be a useful tool for augmenting existing benchmark problems. In this paper, we are interested in the problem of knowledge transfer between the artificially generated and existing handmade benchmark problems in the domain of continuous numerical optimization. That is, can an algorithm selection model trained purely on artificially generated problems correctly provide algorithm recommendations for existing handmade problems. We show that such a model produces low-quality results, and we also provide explanations about how the algorithm selection model works and show the differences between the problem data sets in order to explain the model’s performance.

Hymenoptera venom allergy is one of the most severe allergic diseases, with a considerable prevalence of anaphylactic reaction, making it potentially lethal. In this review, we provide an overview of the current knowledge and recent findings in understanding induced immune mechanisms during different phases of venom immunotherapy. We focus on protection mechanisms that occur early, during the build-up phase, and on the immune tolerance, which occurs later, during and after Hymenoptera venom immunotherapy. The short-term protection seems to be established by the early desensitization of mast cells and basophils, which plays a crucial role in preventing anaphylaxis during the build-up phase of treatment. The early generation of blocking IgG antibodies seems to be one of the main reasons for the lower activation of effector cells. Long-term tolerance is reached after at least three years of venom immunotherapy. A decrease in basophil responsiveness correlates with tolerated sting challenge. Furthermore, the persistent decline in IgE levels and, by monitoring the cytokine profiles, a shift from a Th2 to Th1 immune response, can be observed. In addition, the generation of regulatory T and B cells has proven to be essential for inducing allergen tolerance. Most studies on the mechanisms and effectiveness data have been obtained during venom immunotherapy (VIT). Despite the high success rate of VIT, allergen tolerance may not persist for a prolonged time. There is not much known about immune mechanisms that assure long-term tolerance post-therapy.

Venom immunotherapy is the standard of care for people with severe reactions and has been proven to reduce risk of future anaphylactic events. There is a moral imperative to ensure production, supply and worldwide availability of locally relevant, registered, standardized commercial venom extracts for diagnosis and treatment. Insects causing severe immediate allergic reactions vary by region worldwide. The most common culprits include honeybees (Apis mellifera), social wasps including yellow jackets (Vespula and Dolichovespula), paper wasps (Polistes) and hornets (Vespa), stinging ants (Solenopsis, Myrmecia, Pachycondyla, and Pogonomyrmex), and bumblebees (Bombus). Insects with importance in specific areas of the world include the Australian tick (Ixodes holocyclus), the kissing bug (Triatoma spp), horseflies (Tabanus spp), and mosquitoes (Aedes, Culex, Anopheles). Reliable access to high quality venom immunotherapy to locally relevant allergens is not available throughout the world. Many current commercially available therapeutic vaccines have deficiencies, are not suitable for, or are unavailable in vast areas of the globe. New products are required to replace products that are unstandardized or inadequate, particularly whole-body extract products. New products are required for insects in which no current treatment options exist. Venom immunotherapy should be promoted throughout the world and the provision thereof be supported by health authorities, regulatory authorities and all sectors of the health care service. Keywords: Immunotherapy, Venom, Insects, Venom immunotherapy

Asthma is a common chronic disease, with different underlying inflammatory mechanisms. Identification of asthma endotypes, which reflect a variable response to different treatments, is important for more precise asthma management. T2 asthma is characterized by airway inflammation driven by T2 cytokines including interleukins IL-4, IL-5, and IL-13. This study aimed to determine whether induced sputum samples can be used for gene expression profiling of T2-high asthma classified by IL4, IL5, and IL13 expression. Induced sputum samples were obtained from 44 subjects, among them 36 asthmatic patients and eight controls, and mRNA expression levels of IL4, IL5, and IL13 were quantified by RT-qPCR. Overall, gene expression levels of IL4, IL5, and IL13 were significantly increased in asthmatic patients’ samples compared to controls and there was a high positive correlation between expressions of all three genes. T2 gene mean was calculated by combining the expression levels of all three genes (IL4, IL5, and IL13) and according to T2 gene mean expression in controls, we set a T2-high/T2-low cutoff value. Twenty-four (67%) asthmatic patients had T2-high endotype and those patients had significantly higher eosinophil blood and sputum counts. Furthermore, T2-high endotype was characterized as a more severe, difficult-to-treat asthma, and often uncontrolled despite the use of inhaled and/or oral corticosteroids. Therefore, the majority of those patients (15 [63%] of 24) needed adjunct biological therapy to control their asthma symptoms/exacerbations. In conclusion, we found that interleukins IL4, IL5, and IL13 transcripts could be effectively detected in sputum from asthmatic patients. Implementation of T2 gene mean can be used as sputum molecular biomarker to categorize patients into T2-high endotype, characterized by eosinophilia and severe, difficult-to-treat asthma, and often with a need for biological treatment.

When making statistical analysis of single-objective optimization algorithms’ performance, researchers usually estimate it according to the obtained optimization results in the form of minimal/maximal values. Though this is a good indicator about the performance of the algorithm, it does not provide any information about the reasons why it happens. One possibility to get additional information about the performance of the algorithms is to study their exploration and exploitation abilities. In this paper, we present an easy-to-use step by step pipeline that can be used for performing exploration and exploitation analysis of single-objective optimization algorithms. The pipeline is based on a web-service-based e-Learning tool called DSCTool, which can be used for making statistical analysis not only with regard to the obtained solution values but also with regard to the distribution of the solutions in the search space. Its usage does not require any special statistic knowledge from the user. The gained knowledge from such analysis can be used to better understand algorithm’s performance when compared to other algorithms or while performing hyperparameter tuning.

By performing data analysis, statistical approaches are highly welcome to explore the data. Nowadays with the increases in computational power and the availability of big data in different domains, it is not enough to perform exploratory data analysis (descriptive statistics) to obtain some prior insights from the data, but it is a requirement to apply higher-level statistics that also require much greater knowledge from the user to properly apply them. One research area where proper usage of statistics is important is multi-objective optimization, where the performance of a newly developed algorithm should be compared with the performances of state-of-the-art algorithms. In multi-objective optimization, we are dealing with two or more usually conflicting objectives, which result in high dimensional data that needs to be analyzed. In this paper, we present a web-service-based e-Learning tool called DSCTool that can be used for performing a proper statistical analysis for multi-objective optimization. The tool does not require any special statistics knowledge from the user. Its usage and the influence of a proper statistical analysis is shown using data taken from a benchmarking study performed at the 2018 IEEE CEC (The IEEE Congress on Evolutionary Computation) is appropriate. Competition on Evolutionary Many-Objective Optimization.

Background: Sepsis is a life-threatening organ dysfunction that arises when a host responds insufficiently to an infection as bacteria enter the bloodstream. In recent years, SOFA scoring system has been used to identify poor organ functioning. Microbiological blood tests represent a gold standard in sepsis diagnostics. Reliable biomarkers for early detection of sepsis would greatly facilitate rapid and efficient treatment of sepsis. Methods: In a prospective non-interventional study we studied the diagnostic value of C-reactive protein (CRP), procalcitonin (PCT), neutrophil CD64 index, neutrophil granulocyte count and immature neutrophil count in patients with sepsis and patients with severe infection without sepsis. A total of 46 consecutive intensive-care-unit patients admitted for severe infection and 10 healthy controls were included. The patients were treated routinely according to the principles of good clinical practice. Results: Statistically significant differences between the two groups of patients have been established for the CD64 index, the PCT and the immature neutrophil count, whereas the differences in the CRP and the neutrophil granulocyte count are statistically non-significant. The highest diagnostic values were measured for the immature neutrophil count (AUC 0.91) and PCT (AUC 0.84). The combination of biomarkers has been shown to have same predictive values as the immature neutrophil count and the PCT.

Uspešnost zdravljenja z radioterapijo (RT) je odvisna od številnih dejavnikov, med katerimi je tudi oksigenacija tumorskih celic. Tumorske celice, ki so dobro preskrbljene s kisikom, so namreč na obsevanje tudi do 3-krat bolj občutljive kot hipoksične tumorske celice. Poleg tega deluje hipoksija v tumorjih kot selekcijski pritisk, zaradi katerega preživijo le bolj maligne celice, z manjšim apoptotskim potencialom. V prisotnosti hipoksije se povečata genomska nestabilnost in metastatski potencial tumorskih celic, zveča pa se tudi odpornost celic na kemoterapijo, kar vse vpliva na uspešnost zdravljenja z RT. Hipoksija je posledica neskladja med celičnim dihanjem, koncentracijo kisika v krvi in perfuzijo tumorja, pri čemer so najpogostejši patogenetski mehanizmi neustrezna ožiljenost, motena difuzija kisika ter anemija, ki je lahko posledica rakave bolezni ali zdravljenja. Z uporabo invazivnih in novejših neinvazivnih diagnostičnih metod lahko ocenimo delež hipoksičnih celic v tumorju in temu prilagodimo terapevtski pristop. Boljši učinek obsevanja slabše oksigeniranih tumorjev lahko dosežemo z uporabo radiosenzibilizatorjev, z izboljšanjem tumorske oksigenacije, s selektivnim uničenjem hipoksičnih celic s citotoksini ter z obsevanjem hipoksičnih predelov z višjimi obsevalnimi odmerki ob pomoči radioprotektorjev in z uporabo sodobnih obsevalnih tehnik.

Evidence-based dietary information represented as unstructured text is a crucial information that needs to be accessed in order to help dietitians follow the new knowledge arrives daily with newly published scientific reports. Different named-entity recognition (NER) methods have been introduced previously to extract useful information from the biomedical literature. They are focused on, for example extracting gene mentions, proteins mentions, relationships between genes and proteins, chemical concepts and relationships between drugs and diseases. In this paper, we present a novel NER method, called drNER, for knowledge extraction of evidence-based dietary information. To the best of our knowledge this is the first attempt at extracting dietary concepts. DrNER is a rule-based NER that consists of two phases. The first one involves the detection and determination of the entities mention, and the second one involves the selection and extraction of the entities. We evaluate the method by using text corpora from heterogeneous sources, including text from several scientifically validated web sites and text from scientific publications. Evaluation of the method showed that drNER gives good results and can be used for knowledge extraction of evidence-based dietary recommendations.

This paper addresses the problem of missing data in food composition databases (FCDBs). The missing data can be either for selected foods or for specific components only. Most often, the problem is solved by human experts subjectively borrowing data from other FCDBs, for data estimation or imputation. Such an approach is not only time-consuming but may also lead to wrong decisions as the value of certain components in certain foods may vary from database to database due to differences in analytical methods. To ease missing-data borrowing and increase the quality of missing-data selection, we propose a new computer-based methodology, named MIGHT - Missing Nutrient Value Imputation UsinG Null Hypothesis Testing, that enables optimal selection of missing data from different FCDBs. The evaluation on a subset of European FCDBs, available through EuroFIR and complied with the Food data structure and format standard BS EN 16104 published in 2012, proves that, in more than 80% of selected cases, MIGHT gives more accurate results than techniques currently applied for missing value imputation in FCDBs. MIGHT deals with missing data in FCDBs by introducing rules for missing data imputation based on the idea that proper statistical analysis can decrease the error of data borrowing.

This paper identifies the requirements for computer-supported food matching, in order to address not only national and European but also international current related needs and represents an integrated research contribution of the FP7 EuroDISH project. The available classification and coding systems and the specific problems of food matching are summarized and a new concept for food matching based on optimization methods and machine-based learning is proposed. To illustrate and test this concept, a study has been conducted in four European countries (i.e., Germany, The Netherlands, Italy and the UK) using different classification and coding systems. This real case study enabled us to evaluate the new food matching concept and provide further recommendations for future work. In the first stage of the study, we prepared subsets of food consumption data described and classified using different systems, that had already been manually matched with national food composition data. Once the food matching algorithm was trained using this data, testing was performed on another subset of food consumption data. Experts from different countries validated food matching between consumption and composition data by selecting best matches from the options given by the matching algorithm without seeing the result of the previously made manual match. The evaluation of study results stressed the importance of the role and quality of the food composition database as compared to the selected classification and/or coding systems and the need to continue compiling national food composition data as eating habits and national dishes still vary between countries. Although some countries managed to collect extensive sets of food consumption data, these cannot be easily matched with food composition data if either food consumption or food composition data are not properly classified and described using any classification and coding systems. The study also showed that the level of human expertise played an important role, at least in the training stage. Both sets of data require continuous development to improve their quality in dietary assessment.

Hereditary angioedema due to C1 inhibitor deficiency (C1-INH-HAE) is a rare autosomal dominant disease characterized by recurrent life-threatening oedemas and/or abdominal pain and caused by mutations affecting the C1 inhibitor gene, SERPING1. We sought to investigate the spectrum of SERPING1 mutations in Serbia and the possible genotype-phenotype association. C1-INH-HAE was diagnosed on the basis of clinical and laboratory criteria in 40 patients from 27 families; four were asymptomatic. Mutational analysis of the SERPING1 gene was performed by sequencing and multiplex ligation-dependent probe amplification. Disease-causing mutations in SERPING1 were identified in all patients. In C1-INH-HAE type I, we identified 19 different mutations, including 6 missense mutations, 6 nonsense mutations, 2 small deletions, 1 small insertion, 2 splicing defects and 2 large deletions. Two of the mutations (c.300C>T and c.1184_1185insTA) are reported here for the first time. All C1-INH-HAE type II patients from three families harboured the same substitution (c.1396C>T). Based on the type of mutation identified in the SERPING1 gene, patients were divided into two groups: group 1 (nonsense, frameshift, large deletions/insertions, splicing defect, and mutations at Arg444) or group 2 (missense, excluding mutations at Arg444). Significant differences were found in the clinical severity score (P = 0.005), prevalence of laryngeal (P = 0.040) and facial (P = 0.013) oedema, and long-term prophylaxis (P = 0.023) between the groups with different types of mutations. Because our population consisted of related subjects, differences in the severity score between mutation groups were further confirmed using the generalized estimating equation (P = 0.038). Our study identified 20 different disease-causing mutations, including two novel mutations, in all C1-INH-HAE patients, highlighting the heterogeneity of mutations in the SERPING1 gene. Furthermore, it appears that mutations with a clear effect on C1-INH function might be responsible for a more severe disease phenotype.

The European Food Safety Authority has developed a standardized food classification and description system called FoodEx2. It uses facets to describe food properties and aspects from various perspectives, making it easier to compare food consumption data from different sources and perform more detailed data analyses. However, both food composition data and food consumption data, which need to be linked, are lacking in FoodEx2 because the process of classification and description has to be manually performed—a process that is laborious and requires good knowledge of the system and also good knowledge of food (composition, processing, marketing, etc.). In this paper, we introduce a semi-automatic system for classifying and describing foods according to FoodEx2, which consists of three parts. The first involves a machine learning approach and classifies foods into four FoodEx2 categories, with two for single foods: raw (r) and derivatives (d), and two for composite foods: simple (s) and aggregated (c). The second uses a natural language processing approach and probability theory to describe foods. The third combines the result from the first and the second part by defining post-processing rules in order to improve the result for the classification part. We tested the system using a set of food items (from Slovenia) manually-coded according to FoodEx2. The new semi-automatic system obtained an accuracy of 89% for the classification part and 79% for the description part, or an overall result of 79% for the whole system.

BACKGROUND: We recently showed a desensitization of FcεRI-mediated basophil response after short-term VIT. Our aim was to evaluate the allergen specificity of this desensitization. METHODS: In 11 Hymenoptera-venom double positive subjects, basophil threshold sensitivity (CD-sens) to anti-FcεRI, honeybee, and Vespula venom was assessed at the beginning and just before the first maintenance dose (MD) of single ultra-rush VIT. In some patients we also monitored CD-sens to rApi m 1 and/or rVes v 5 or other co-sensitizations (i.e., grass pollen). In additional 7 patients, basophils were stripped and sensitized with house dust mite (HDM) IgEs at the same time points. RESULTS: We demonstrated a marked reduction of CD-sens to anti-FcεRI and VIT-specific venom before the first MD in all 18 subjects included. Furthermore, in 10 out of 11 double positive subjects, a significant and comparable decrease before the first MD was also evident for non-VIT venom; this nonspecific decrease was further supported by the opposite recombinant species-specific major allergen. In one subject with additional grass pollen allergy, a decrease of CD-sens to grass allergen was also demonstrated. Similarly, in 7 cases of patients with passively HDM-sensitized basophils, a significant reduction of CD-sens was also evident to de novo sensitized HDM allergen. CONCLUSIONS: Short-term VIT induced basophil desensitization to VIT-specific as well as to VIT-nonspecific venom. As opposed to long-term VIT, which induces venom-specific changes, the effect of short-term VIT seems to be venom-nonspecific.

This paper compares two metaheuristic approaches in solving a constrained transportation scheduling problem, which can be found in transporting goods in emergency situations. We compared Greedy Search, Parameter-less Evolutionary Search and Ant-Stigmergy Algorithm. The transportation scheduling/allocation problem is NP-hard, and is applicable to different real-life situations with high frequency of loading and unloading operations; like in depots, warehouses and ports. To evaluate the efficiency of the presented approaches, they were tested with four tasks based on realistic data. Each task was evaluated using group and free transportation approach. The experiments proved that all tested algorithms are viable option in solving such scheduling problems, however some performing better than others on some tasks.

Hereditary angioedema (HAE) is a rare autosomal dominant disease characterized by swelling of the face, lips, tongue, larynx, genitalia, or extremities, with abdominal pain caused by intra-abdominal edema. HAE is caused by mutations affecting the C1 inhibitor gene, SERPING1, resulting in low levels of C1 inhibitor (Type I HAE) or normal levels of ineffective C1 inhibitor (Type II HAE). A nationwide survey identified nine unrelated families with HAE in Slovenia, among whom 17 individuals from eight families were recruited for genetic analyses. A diagnosis of HAE was established in the presence of clinical and laboratory criteria (low C1 inhibitor antigenic levels and/or function), followed up by a positive family history. Genetic studies were carried out using PCR and sequencing to detect SERPING1 mutations in promoter, noncoding exon 1, the 7 coding exons, and exon-intron boundaries. Multiplex ligation-dependent probe amplification was performed in order to search for large deletions/duplications in SERPING1 gene. A mutation responsible for HAE was identified in patients from seven families with the disease. In HAE type I families, one previously reported substitution (Gln67Stop, c.265C>T) and four novel mutations were identified. The new mutations included two missense substitutions, Ser128Phe (c.449C>T), and Glu429Lys (c.1351G>A), together with two frameshift mutations, indel (c.49delGinsTT) and deletion (c.593_594delCT). Both families with HAE type II harbored the two well-known substitutions affecting the arginyl residue at the reactive center in exon 8, Arg444Cys (c.1396C>T) and Arg444His (c.1397G>A), respectively. In one patient only the homozygous variant g.566T>C (c.-21T>C) was identified. Our study identified four novel mutations in the Slovenian HAE population, highlighting the heterogeneity of mutations in the SERPING1 gene causing C1 inhibitor deficiency and HAE. In a single patient with HAE a homozygous variant g.566T>C (c.-21T>C) might be responsible for the disease.

Angiogenesis is a critical event in the development, progression, and spread of various human cancers, including lung cancer. Molecular mechanisms that underlie the complex regulation of angiogenic processes are poorly understood. However, an increasing body of evidence indicates miRNAs as important regulators of tumor angiogenesis. Forceps biopsies were collected from tumor tissue, surrounding tissue, and non-tumor tissue from 50 NSCLC patients. Lung tissue samples from individuals with no clinical evidence of a cancerous disease served as controls. Immunohistochemical staining for Factor VIII was used to evaluate microvessel density (MVD). TaqMan® primer-probe sets were used in quantitative real-time RT-PCR reactions to determine expression levels of let-7b, miR-126, miR-9, and miR-19a. We demonstrated significantly higher MVD and decreased expression levels of let-7b and miR-126 in tumor tissue and surrounding tissue in comparison to corresponding non-tumor tissue or lung tissue from the control group. In addition, no differences in MVD and expression levels of both miRNAs between tumor tissue and surrounding tissue from NSCLC patients were observed. Low expression of both miRNAs correlated with high MVD and worse progression-free survival and overall survival. These observations strongly suggest similar molecular alternations within tumor tissue and surrounding tissue that comprise a specific microenvironment. Low expression of let-7b and miR-126 seems to have a possible anti-angiogenic role in lung tumor tissue and significantly correlates with worse survival outcomes for lung cancer patients. Moreover, the regulation of let-7b and miR-126 expression could have therapeutic potential because it could reduce tumor angiogenesis and therefore suppress tumor growth in lung cancer patients.

BACKGROUND The basophil activation test relies on flow cytometric quantitation of the expression of themarkers on the surface of basophils, after stimulation with the amount of allergen thatcross-link IgE antibodies bound on their surface. In allergy diagnosis, the technique hasbeen applied in the investigation of IgE-mediated allergy caused by classical inhalant allergens,Hevea latex, food, drugs and hymenoptera venoms. The technique also proves valuablein the diagnosis of non-IgE-mediated reactions such as drug hypersensitivity and thedetection of autoantibodies in certain forms of chronic urticaria. To strengthen the probabilitythat the working diagnosis for hymenoptera venom hypersensitivity is correct, confirmatorytesting for skin test and IgE antibody is often performed. But sometimes clinical history and the results of confirmatory tests are contradictory. In such cases additionaltests are necessary, among which flow cytometric quantification of in vitro basophil activationis becoming a valuable tool during the last few years.Material and In Laboratory for Clinical Immunology and Molecular Genetic, Golnik, we performed BATmethods for 127 patients with history of anaphylactic reactions after Hymenoptera sting. CONCLUSIONS According to our findings BAT is a highly sensitive and specific technique and as an invitro provocation assay enables sensibilisation detection, prediction of side effects fromspecific immunotherapy and differentiates between clinically relevant and irrelevant epitops.This technique also gave us a new information on mechanisms and effects of venomimmunotherapy

Background: L. pneumophila is a possible causative agent of severe community and hospital acquired pneumonia. Available diagnostic tests have a lot of shortcomings. Detection of Legionella DNA with the PCR technique is a promissing new method allowing diagnosis within clinically useful time.Methods: Three cases of severe Legionella pneumonia were followed with the PCR technique, urinary antigen and serologic methods.Results: Diagnostic tests have different sensitivity and specificity and also different shortcomings. Serologic tests are unable to provide diagnosis within clinically useful time. Urinary antigen is specific just for L. pneumophila serotype 1. Antimicrobial treatment has impact on the sensitivity of Legionella PCR.Conclusions: Detection of L. pneumophila infection with the PCR technique in addition to urinary antigen testing is likely to be the best diagnostic tool for the detection of all species within a time frame that will affect clinical management.

Background: Cystic fibrosis (CF) is an autosomal recessive disease caused by mutations in gene encoding cystic fibrosis transmembrane regulator (CFTR) protein. Over 1400 mutations found in the gene contribute to the complexity of the CF phenotypes ranging from a classic multiorgan disease commonly involving respiratory, gastrointestinal and reproductive tract to mild and monosymptomatic presentations. Pilocarpine iontophoresis is considered as standard diagnostic test for CF, but it often fails in atypical forms of CF.Methods: In order to provide an additional diagnostic test to assure the diagnosis and provide patients with a proper medical care, we performed a genetic testing on 16 adults suspected to have atypical form of CF. Following counselling, parents of patients with possible homozygote variant of mutations were tested. On a personal request testing was also performed in an adult sibling of a patient with two known mutations to investigate possible carrier hood. The allele specific polymerase chain reaction method (PCR) was used to detect 29 most common mutations in the cftr gene.Results: The diagnosis was proved in 3 individuals, a homozygote for Δ F508, and two compound heterozygotes Δ F508/R1162X and Δ F508/3849+10kbC>T. In three cases only one mutation was found: I148T, 2789+5G>A and Δ F508 in a heterozygote form.Conclusions: The genetic testing for CF is a valuable diagnostic tool in atypical forms of CF. Exclusion of possible differential diagnosis is warranted because of a variable CF phenotype. In cases where only one or no mutation was detected a necessity of whole gene sequencing is indicated to exclude rare mutations and polymorphisms that could be implicated in the pathogenesis of atypical CF.