Multicenter PET image harmonization using generative adversarial networks.

PURPOSE: To improve reproducibility and predictive performance of PET radiomic features in multicentric studies by cycle-consistent generative adversarial network (GAN) harmonization approaches. METHODS: GAN-harmonization was developed to harmonize whole-body PET scans to perform image style and texture translation between different centers and scanners. GAN-harmonization was evaluated by application to two retrospectively collected open datasets and different tasks. First, GAN-harmonization was performed on a dual-center lung cancer cohort (127 female, 138 male) where the reproducibility of radiomic features in healthy liver tissue was evaluated. Second, GAN-harmonization was applied to a head and neck cancer cohort (43 female, 154 male) acquired from three centers. Here, the clinical impact of GAN-harmonization was analyzed by predicting the development of distant metastases using a logistic regression model incorporating first-order statistics and texture features from baseline 18F-FDG PET before and after harmonization. RESULTS: Image quality remained high (structural similarity: left kidney ≥ 0.800, right kidney ≥ 0.806, liver ≥ 0.780, lung ≥ 0.838, spleen ≥ 0.793, whole-body ≥ 0.832) after image harmonization across all utilized datasets. Using GAN-harmonization, inter-site reproducibility of radiomic features in healthy liver tissue increased at least by ≥ 5 ± 14% (first-order), ≥ 16 ± 7% (GLCM), ≥ 19 ± 5% (GLRLM), ≥ 16 ± 8% (GLSZM), ≥ 17 ± 6% (GLDM), and ≥ 23 ± 14% (NGTDM). In the head and neck cancer cohort, the outcome prediction improved from AUC 0.68 (95% CI 0.66-0.71) to AUC 0.73 (0.71-0.75) by application of GAN-harmonization. CONCLUSIONS: GANs are capable of performing image harmonization and increase reproducibility and predictive performance of radiomic features derived from different centers and scanners.

Machine learning predictive performance evaluation of conventional and fuzzy radiomics in clinical cancer imaging cohorts.

BACKGROUND: Hybrid imaging became an instrumental part of medical imaging, particularly cancer imaging processes in clinical routine. To date, several radiomic and machine learning studies investigated the feasibility of in vivo tumor characterization with variable outcomes. This study aims to investigate the effect of recently proposed fuzzy radiomics and compare its predictive performance to conventional radiomics in cancer imaging cohorts. In addition, lesion vs. lesion+surrounding fuzzy and conventional radiomic analysis was conducted. METHODS: Previously published 11C Methionine (MET) positron emission tomography (PET) glioma, 18F-FDG PET/computed tomography (CT) lung, and 68GA-PSMA-11 PET/magneto-resonance imaging (MRI) prostate cancer retrospective cohorts were included in the analysis to predict their respective clinical endpoints. Four delineation methods including manually defined reference binary (Ref-B), its smoothed, fuzzified version (Ref-F), as well as extended binary (Ext-B) and its fuzzified version (Ext-F) were incorporated to extract imaging biomarker standardization initiative (IBSI)-conform radiomic features from each cohort. Machine learning for the four delineation approaches was performed utilizing a Monte Carlo cross-validation scheme to estimate the predictive performance of the four delineation methods. RESULTS: Reference fuzzy (Ref-F) delineation outperformed its binary delineation (Ref-B) counterpart in all cohorts within a volume range of 938-354987 mm3 with relative cross-validation area under the receiver operator characteristics curve (AUC) of +4.7-10.4. Compared to Ref-B, the highest AUC performance difference was observed by the Ref-F delineation in the glioma cohort (Ref-F: 0.74 vs. Ref-B: 0.70) and in the prostate cohort by Ref-F and Ext-F (Ref-F: 0.84, Ext-F: 0.86 vs. Ref-B: 0.80). In addition, fuzzy radiomics decreased feature redundancy by approx. 20%. CONCLUSIONS: Fuzzy radiomics has the potential to increase predictive performance particularly in small lesion sizes compared to conventional binary radiomics in PET. We hypothesize that this effect is due to the ability of fuzzy radiomics to model partial volume effects and delineation uncertainties at small lesion boundaries. In addition, we consider that the lower redundancy of fuzzy radiomic features supports the identification of imaging biomarkers in future studies. Future studies shall consider systematically analyzing lesions and their surroundings with fuzzy and binary radiomics.

Radiogenomic markers enable risk stratification and inference of mutational pathway states in head and neck cancer.

PURPOSE: Head and neck squamous cell carcinomas (HNSCCs) are a molecularly, histologically, and clinically heterogeneous set of tumors originating from the mucosal epithelium of the oral cavity, pharynx, and larynx. This heterogeneous nature of HNSCC is one of the main contributing factors to the lack of prognostic markers for personalized treatment. The aim of this study was to develop and identify multi-omics markers capable of improved risk stratification in this highly heterogeneous patient population. METHODS: In this retrospective study, we approached this issue by establishing radiogenomics markers to identify high-risk individuals in a cohort of 127 HNSCC patients. Hybrid in vivo imaging and whole-exome sequencing were employed to identify quantitative imaging markers as well as genetic markers on pathway-level prognostic in HNSCC. We investigated the deductibility of the prognostic genetic markers using anatomical and metabolic imaging using positron emission tomography combined with computed tomography. Moreover, we used statistical and machine learning modeling to investigate whether a multi-omics approach can be used to derive prognostic markers for HNSCC. RESULTS: Radiogenomic analysis revealed a significant influence of genetic pathway alterations on imaging markers. A highly prognostic radiogenomic marker based on cellular senescence was identified. Furthermore, the radiogenomic biomarkers designed in this study vastly outperformed the prognostic value of markers derived from genetics and imaging alone. CONCLUSION: Using the identified markers, a clinically meaningful stratification of patients is possible, guiding the identification of high-risk patients and potentially aiding in the development of effective targeted therapies.

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

OBJECTIVES: This study investigates the ability of machine learning (ML) models trained on clinical data and 2-deoxy-2-[18F]fluoro-D-glucose(FDG) positron emission tomography/computed tomography (PET/CT) radiomics to predict overall survival (OS), tumor grade (TG), and histologic growth pattern risk (GPR) in lung adenocarcinoma (LUAD) patients. METHODS: A total of 421 treatment-naive patients with histologically-proven LUAD and available FDG PET/CT imaging were retrospectively included. Four cohorts were assessed for predicting 4-year OS (n = 276), 3-year OS (n = 280), TG (n = 298), and GPR (n = 265). FDG-avid lesions were delineated, and 2082 radiomics features were extracted and combined with endpoint-specific clinical parameters. ML models were built for the prediction of 4-year OS (M4OS), 3-year OS (M3OS), tumor grading (MTG), and histologic growth pattern risk (MGPR). A 100-fold Monte Carlo cross-validation with 80:20 training to validation split was employed as a performance evaluation for all models. The association between the M4OS and M3OS predictions with OS was assessed by the Kaplan-Meier survival analysis. RESULTS: The area under the receiver operator characteristics curve (AUC) was the highest for M4OS (AUC 0.88, 95% confidence interval (CI) 86.7-88.7), followed by M3OS (AUC 0.84, CI 82.9-84.9), while MTG and MGPR performed equally well (AUC 0.76, CI 74.4-77.9, CI 74.6-78, respectively). Predictions of M4OS (hazard ratio (HR) -2.4, CI -2.47 to -1.64, p < 0.05) and M3OS (HR -2.36, CI -2.79 to -1.93, p < 0.05) were independently associated with OS. CONCLUSION: ML models are able to predict long-term survival outcomes in LUAD patients with high accuracy. Furthermore, histologic grade and predominant growth pattern risk can be predicted with satisfactory accuracy. KEY POINTS: • Machine learning models trained on pre-therapeutic PET/CT radiomics enable highly accurate long-term survival prediction of patients with lung adenocarcinoma. • Highly accurate survival predictions are achieved in lung adenocarcinoma patients despite heterogenous histologies and treatment regimens. • Radiomic machine learning models are able to predict lung adenocarcinoma tumor grade and histologic growth pattern risk with satisfactory accuracy.

Molecular and Cytogenetic Analysis of rDNA Evolution in Crepis Sensu Lato.

Although Crepis was the first model plant group in which chromosomal changes were considered to play an important role in speciation, their chromosome structure and evolution have been barely investigated using molecular cytogenetic methods. The aim of the study was to provide a better understanding of the patterns and directions of Crepis chromosome evolution, using comparative analyses of rDNA loci number and localisation. The chromosome base number and chromosomal organisation of 5S and 35S rDNA loci were analysed in the phylogenetic background for 39 species of Crepis, which represent the evolutionary lineages of Crepis sensu stricto and Lagoseris, including Lapsana communis. The phylogenetic relationships among all the species were inferred from nrITS and newly obtained 5S rDNA NTS sequences. Despite high variations in rDNA loci chromosomal organisation, most species had a chromosome with both rDNA loci within the same (usually short) chromosomal arm. The comparative analyses revealed several independent rDNA loci number gains and loci repositioning that accompanied diversification and speciation in Crepis. Some of the changes in rDNA loci patterns were reconstructed for the same evolutionary lineages as descending dysploidy.

Molecular and comparative genomic analyses reveal evolutionarily conserved and unique features of the Schizosaccharomyces japonicus mycelial growth and the underlying genomic changes.

Fungal pathogens, from phytopathogenic fungus to human pathogens, are able to alternate between the yeast-like form and filamentous forms. This morphological transition (dimorphism) is in close connection with their pathogenic lifestyles and with their responses to changing environmental conditions. The mechanisms governing these morphogenetic conversions are still not fully understood. Therefore, we studied the filamentous growth of the less-known, non-pathogenic dimorphic fission yeast, S. japonicus, which belongs to an ancient and early evolved branch of the Ascomycota. Its RNA sequencing revealed that several hundred genes were up- or down-regulated in the hyphae compared to the yeast-phase cells. These genes belonged to different GO categories, confirming that mycelial growth is a rather complex process. The genes of transport- and metabolic processes appeared especially in high numbers among them. High expression of genes involved in glycolysis and ethanol production was found in the hyphae, while other results pointed to the regulatory role of the protein kinase A (PKA) pathway. The homologues of 49 S. japonicus filament-associated genes were found by sequence alignments also in seven distantly related dimorphic and filamentous species. The comparative genomic analyses between S. japonicus and the closely related but non-dimorphic S. pombe shed some light on the differences in their genomes. All these data can contribute to a better understanding of hyphal growth and those genomic rearrangements that underlie it.

A modified culture medium and hyphae isolation method can increase quality of the RNA extracted from mycelia of a dimorphic fungal species.

The capability of RNA isolation with good efficiency and high quality is essential for a downstream application such as RNA sequencing. It requires successful cell culturing and an effective RNA isolation method. Although effective methods are available, production of the homogenous mycelia and extraction of good-quality mycelial RNA from true invasive hyphae, which penetrated into the agar plates, are difficult. To overcome these problems, the aim of this study was to develop technical modifications which allow production of homogenous mycelial biomass without extra stimuli agents and improve quality of the RNA extracted from the fungal hyphae. Our alternative culture medium was suitable for production both yeast-phase cells and hyphae of the Schizosaccharomyces japonicus and other dimorphic species, such as the Candida albicans, Saccharomyces cerevisiae, and Jaminaea angkorensis. To improve quality of the mycelial RNA, we developed an isolation procedure of the hyphal tip, which eliminated the unnecessary vacuoles-containing parts of the hyphae. To increase RNA quantity, we used glass beads in the RNA extraction protocol to achieve stronger breaking of the mycelial walls. All these modifications can also be useful for researchers working with other dimorphic fungi and can contribute to the higher comparability of the transcriptional data coming from yeast-phase cells and hyphae or even from different species.

Application of different markers and data-analysis tools to the examination of biodiversity can lead to different results: a case study with Starmerella bacillaris (synonym Candida zemplinina) strains.

Starmerella bacillaris (Candida zemplinina) is a genetically heterogeneous species. In this work, the diversity of 41 strains of various origins is examined and compared by the analysis of the length polymorphism of nuclear microsatellites and the RFLP of mitochondrial genomes. The band patterns are analysed with UPGMA, neighbor joining, neighbor net, minimum spanning tree and non-metric MDS algorithms. The results and their comparison to previous analyses demonstrate that different markers and different clustering methods can result in very different groupings of the same strains. The observed differences between the topologies of the dendrograms also indicate that the positions of the strains do not necessarily reflect their real genetic relationships and origins. The possibilities that the differences might be partially due to different sensitivity of the markers to environmental factors (selection pressure) and partially to the different grouping criteria of the algorithms are also discussed.

Expression pattern and phenotypic characterization of the mutant strain reveals target genes and processes regulated by pka1 in the dimorphic fission yeast Schizosaccharomyces japonicus.

The cAMP cascade plays an important role in several biological processes. Thus, study of its molecular details can contribute to a better understanding of these processes, treatment of diseases, or even finding antifungal drug targets. To gain further information about the PKA pathway, and its evolutionarily conserved and species-specific features, the central regulator pka1 gene, which encodes the cAMP-dependent protein kinase catalytic subunit, was studied in the less known haplontic, dimorphic fission yeast Schizosaccharomyces japonicus. Namely, this species belongs to a highly divergent phylogenetic branch of fungi. Furthermore, S. japonicus had only a single copy pka1 gene in contrast to the budding yeasts. Therefore, the pka1 deleted mutant was created, whose RNA sequencing and phenotypic studies revealed that the Pka1 regulated at least 373 genes, among them further kinases, phosphatases and transcriptional regulators. It regulated elongation of hyphae, cell size, aging and stress response. Furthermore, half of the pka1 target genes seemed to be conserved in Schizosaccharomyces pombe and S. japonicus. However, there were oppositely regulated genes in the two closely related species. The target genes suggest that this single gene must be able to fulfill all the functions of TPK1-3 of Saccharomyces cerevisiae. Thus, our results shed light on certain similarities and differences of the PKA pathway of S. japonicus compared to the budding yeasts and confirmed the multifunctionality of the pka1 gene, but further experiments are needed to prove its involvement in the metabolic processes and transport.

Phylogenetic and comparative functional analysis of the cell-separation α-glucanase Agn1p in Schizosaccharomyces.

The post-cytokinetic separation of cells in cell-walled organisms involves enzymic processes that degrade a specific layer of the division septum and the region of the mother cell wall that edges the septum. In the fission yeast Schizosaccharomyces pombe, the 1,3-α-glucanase Agn1p, originally identified as a mutanase-like glycoside hydrolase family 71 (GH71) enzyme, dissolves the mother cell wall around the septum edge. Our search in the genomes of completely sequenced fungi identified GH71 hydrolases in Basidiomycota, Taphrinomycotina and Pezizomycotina, but not in Saccharomycotina. The most likely Agn1p orthologues in Pezizomycotina species are not mutanases having mutanase-binding domains, but experimentally non-characterized hypothetical proteins that have no carbohydrate-binding domains. The analysis of the GH71 domains corroborated the phylogenetic relationships of the Schizosaccharomyces species determined by previous studies, but suggested a closer relationship to the Basidiomycota proteins than to the Ascomycota proteins. In the Schizosaccharomyces genus, the Agn1p proteins are structurally conserved: their GH71 domains are flanked by N-terminal secretion signals and C-terminal sequences containing the conserved block YNFNA(Y)/HTG. The inactivation of the agn1(Sj) gene in Schizosaccharomyces japonicus, the only true dimorphic member of the genus, caused a severe cell-separation defect in its yeast phase, but had no effect on the hyphal growth and yeast-to-mycelium transition. It did not affect the mycelium-to-yeast transition either, only delaying the separation of the yeast cells arising from the fragmenting hyphae. The heterologous expression of agn1(Sj) partially rescued the separation defect of the agn1Δ cells of Schizosaccharomyces pombe. The results presented indicate that the fission yeast Agn1p 1,3-α-glucanases of Schizosaccharomyces japonicus and Schizosaccharomyces pombe share conserved functions in the yeast phase.

Optimal conditions for mycelial growth of Schizosaccharomyces japonicus cells in liquid medium: it enables the molecular investigation of dimorphism.

The non-pathogenic dimorphic fission yeast, Schizosaccharomyces japonicus, could be a suitable model organism for investigation of the genetic background of mycelial growth, as it has a haploid chromosome set and its genome is sequenced. Since earlier results have suggested that its morphological transition required solid substrates, but molecular biological experiments would require hyphae production in a liquid medium, we wanted to find circumstances which would enable hyphae production in liquid media. Several external conditions were investigated, but the strongest inducer was fetal bovine serum (FBS). Its positive effect could be hampered by heat and was dependent on pH, temperature and concentration of the serum. Other protein-containing compounds, such as peptone and bovine serum albumin or amino acids, proved to be ineffective or weak. Generally, the uninduced and induced mycelial growth of Sz. japonicus could be improved by lower external pH and higher temperature.

New genera of Afrotropical limosinine sphaerocerids (Diptera: Sphaeroceridae).

Eight new genera of the subfamily Limosininae are described from the Afrotropical region: Afrolimosina gen. n. (type species A. albitarsis sp. n.), Biphallapodema gen. n. (type species B. polydentata sp. n., additional species B. oligodentata sp. n.), Chelilimosina gen. n. (type species Ch. baloghi sp. n.), Mislocatus gen. n. (type species Ceroptera ealensis Vanschuytbroeck, 1951), Oligochaetosella gen. n. (type species O. inconspicua sp. n.), Permixtolimosina gen. n. (type species P. sexsetosa sp. n.), Preepiphallus gen. n. (type species P. nitidifacies sp. n., additional species P. endrodyi sp. n.), Subacuminiseta gen. n. (type species S. minor sp. n.). Comparisons to the key for the identification of Old World genera of Limosininae (Papp 2008) are given. With 118 original figures.

Volumetric mesoscopic electrophysiology: a new imaging modality for the non-human primate.

The primate brain is a densely interconnected organ whose function is best understood by recording from the entire structure in parallel, rather than parts of it in sequence. However, available methods either have limited temporal resolution (functional magnetic resonance imaging), limited spatial resolution (macroscopic electroencephalography), or a limited field of view (microscopic electrophysiology). To address this need, we developed a volumetric, mesoscopic recording approach ( MePhys ) by tessellating the volume of a monkey hemisphere with 992 electrode contacts that were distributed across 62 chronically implanted multi-electrode shafts. We showcase the scientific promise of MePhys by describing the functional interactions of local field potentials between the more than 300,000 simultaneously recorded pairs of electrodes. We find that a subanesthetic dose of ketamine -believed to mimic certain aspects of psychosis- can create a pronounced state of functional disconnection and prevent the formation of stable large-scale intrinsic states. We conclude that MePhys provides a new and fundamentally distinct window into brain function whose unique profile of strengths and weaknesses complements existing approaches in synergistic ways.

Examining the Relationship and Prognostic Significance of Cell-Free DNA Levels and the PSMA-Positive Tumor Volume in Men with Prostate Cancer: A Retrospective-Prospective [68Ga]Ga-PSMA-11 PET/CT Study.

Functional imaging with prostate-specific membrane antigen (PSMA) ligands has emerged as the standard imaging method for prostate cancer (PCA). In parallel, the analysis of blood-derived, cell-free DNA (cfDNA) has been shown to be a promising quantitative biomarker of PCA aggressiveness and patient outcome. This study aimed to evaluate the relationship and prognostic value of cfDNA concentrations and the PSMA-positive tumor volume (PSMA-TV) in men with PCA undergoing [68Ga]Ga-PSMA-11 PET/CT imaging. Methods: We recruited 148 men with histologically proven PCA (mean age, 70.7 ± 7.7 y) who underwent [68Ga]Ga-PSMA-11 PET/CT (184.9 ± 18.9 MBq) and blood sampling between March 2019 and August 2021. Among these, 74 (50.0%) had hormone-sensitive PCA and 74 (50.0%) had castration-resistant PCA (CRPC). All patients provided written informed consent before blood sample collection and imaging. The cfDNA was extracted and quantified, and PSMA-expressing tumor lesions were delineated to extract the PSMA-TVs. The Spearman coefficient assessed correlations between PSMA-TV and cfDNA concentrations and cfDNA's relation with clinical parameters. The Kruskal-Wallis test examined the mean cfDNA concentration differences based on PSMA-TV quartiles for significantly correlated patient groups. Log-rank and multivariate Cox regression analyses evaluated the prognostic significance of high and low cfDNA and PSMA-TV levels for overall survival. Results: Weak positive correlations were found between cfDNA concentration and PSMA-TV in the overall group (r = 0.16, P = 0.049) and the CRPC group (r = 0.31, P = 0.007) but not in hormone-sensitive PCA patients (r = -0.024, P = 0.837). In the CRPC cohort, cfDNA concentrations significantly differed between PSMA-TV quartiles 4 and 1 (P = 0.002) and between quartiles 4 and 2 (P = 0.016). Survival outcomes were associated with PSMA-TV (P < 0.0001, P = 0.004) but not cfDNA (P = 0.174, P = 0.12), as per the log-rank and Cox regression analysis. Conclusion: These findings suggest that cfDNA might serve as a biomarker of advanced, aggressive CRPC but does not reliably reflect total tumor burden or prognosis. In comparison, [68Ga]Ga-PSMA-11 PET/CT provides a highly granular and prognostic assessment of tumor burden across the spectrum of PCA disease progression.

Investigation of a Perspective Urban Tree Species, Ginkgo biloba L., by Scientific Analysis of Historical Old Specimens.

In this study, we examined over 200-year-old Ginkgo biloba L. specimens under different environmental conditions. The overall aim was to explore which factors influence their vitality and general fitness in urban environments and thus their ability to tolerate stressful habitats. In order to determine this, we used a number of different methods, including histological examinations (stomatal density and size) and physiological measurements (peroxidase enzyme activity), as well as assessing the air pollution tolerance index (APTI). The investigation of the genetic relationships between individuals was performed using flow cytometry and miRNA marker methods. The genetic tests revealed that all individuals are diploid, whereas the lus-miR168 and lus-miR408 markers indicated a kinship relation between them. These results show that the effect of different habitat characteristics can be detected through morphological and physiological responses, thus indicating relatively higher stress values for all studied individuals. A significant correlation can be found between the level of adaptability and the relatedness of the examined individuals. These results suggest that Ginkgo biloba L. is well adapted to an environment with increased stress factors and therefore suitable for use in urban areas.

Disruption of the Schizosaccharomyces japonicus lig4 Disturbs Several Cellular Processes and Leads to a Pleiotropic Phenotype.

Gene targeting is a commonly used method to reveal the function of genes. Although it is an attractive tool for molecular studies, it can frequently be a challenge because its efficiency can be low and it requires the screening of a large number of transformants. Generally, these problems originate from the elevated level of ectopic integration caused by non-homologous DNA end joining (NHEJ). To eliminate this problem, NHEJ-related genes are frequently deleted or disrupted. Although these manipulations can improve gene targeting, the phenotype of the mutant strains raised the question of whether mutations have side effects. The aim of this study was to disrupt the lig4 gene in the dimorphic fission yeast, S. japonicus, and investigate the phenotypic changes of the mutant strain. The mutant cells have shown various phenotypic changes, such as increased sporulation on complete medium, decreased hyphal growth, faster chronological aging, and higher sensitivity to heat shock, UV light, and caffeine. In addition, higher flocculation capacity has been observed, especially at lower sugar concentrations. These changes were supported by transcriptional profiling. Many genes belonging to metabolic and transport processes, cell division, or signaling had altered mRNA levels compared to the control strain. Although the disruption improved the gene targeting, we assume that the lig4 inactivation can cause unexpected physiological side effects, and we have to be very careful with the manipulations of the NHEJ-related genes. To reveal the exact mechanisms behind these changes, further investigations are required.

Characterization of Zygosaccharomyces lentus Yeast in Hungarian Botrytized Wines.

Tokaj botrytized sweet wines are traditionally aged for several years in wood barrels or bottles. As they have significant residual sugar content, they are exposed to microbial contamination during ageing. Osmotolerant wine-spoilage yeasts are most commonly found in the Tokaj wine-growing region in the species Starmerella spp. and Zygosaccharomyces spp. For the first time, Z. lentus yeasts were isolated from post-fermented botrytized wines. Our physiological studies confirmed that these yeast strains are osmotolerant, with high sulphur tolerance and 8% v/v alcohol tolerance, and that they grow well at cellar temperature in acidic conditions. Low ß-glucosidase and sulphite reductase activities were observed, whereas protease, cellulase, and α-arabinofuranosidase extracellular enzyme activities were not detected. Molecular biology analyses carried out by RFLP analysis of mtDNA revealed no remarkable differences between strains, while microsatellite-primed-PCR fingerprinting of the (GTG)5 microsatellite and examination of chromosomal pattern revealed considerable diversity. The fermentative vigour of the tested Z. lentus strains was found to be significantly lower compared to the control Saccharomyces cerevisiae (Lalvin EC1118). It can be concluded that Z. lentus is a potential spoilage yeast in oenology which may be responsible for the initiation of secondary fermentation of wines during ageing.

Enhancing Interoperability and Harmonisation of Nuclear Medicine Image Data and Associated Clinical Data.

Nuclear imaging techniques such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) in combination with computed tomography (CT) are established imaging modalities in clinical practice, particularly for oncological problems. Due to a multitude of manufacturers, different measurement protocols, local demographic or clinical workflow variations as well as various available reconstruction and analysis software, very heterogeneous datasets are generated. This review article examines the current state of interoperability and harmonisation of image data and related clinical data in the field of nuclear medicine. Various approaches and standards to improve data compatibility and integration are discussed. These include, for example, structured clinical history, standardisation of image acquisition and reconstruction as well as standardised preparation of image data for evaluation. Approaches to improve data acquisition, storage and analysis will be presented. Furthermore, approaches are presented to prepare the datasets in such a way that they become usable for projects applying artificial intelligence (AI) (machine learning, deep learning, etc.). This review article concludes with an outlook on future developments and trends related to AI in nuclear medicine, including a brief research of commercial solutions.

DEBI-NN: Distance-encoding biomorphic-informational neural networks for minimizing the number of trainable parameters.

Modern artificial intelligence (AI) approaches mainly rely on neural network (NN) or deep NN methodologies. However, these approaches require large amounts of data to train, given, that the number of their trainable parameters has a polynomial relationship to their neuron counts. This property renders deep NNs challenging to apply in fields operating with small, albeit representative datasets such as healthcare. In this paper, we propose a novel neural network architecture which trains spatial positions of neural soma and axon pairs, where weights are calculated by axon-soma distances of connected neurons. We refer to this method as distance-encoding biomorphic-informational (DEBI) neural network. This concept significantly minimizes the number of trainable parameters compared to conventional neural networks. We demonstrate that DEBI models can yield comparable predictive performance in tabular and imaging datasets, where they require a fraction of trainable parameters compared to conventional NNs, resulting in a highly scalable solution.