Abnormal thalamocortical networks involving specific thalamic nuclei have been implicated in schizophrenia pathophysiology. While comparable topography of anatomical and functional connectivity abnormalities has been reported in patients across illness stages, previous functional studies have been confined to anatomical pathways of thalamocortical networks. To address this issue, we incorporated large-scale brain network dynamics into examining thalamocortical functional connectivity. Forty patients with first-episode psychosis and forty healthy controls underwent T1-weighted and resting-state functional magnetic resonance imaging. Independent component analysis of voxelwise thalamic functional connectivity maps parcellated the cortex into thalamus-related networks, and thalamic subdivisions associated with these networks were delineated. Functional connectivity of (1) networks with the thalamus and (2) thalamic subdivision seeds were examined. In patients, functional connectivity of the salience network with the thalamus was decreased and localized to the ventrolateral (VL) and ventroposterior (VP) thalamus, while that of a network comprising the cerebellum, temporal and parietal regions was increased and localized to the mediodorsal (MD) thalamus. In patients, thalamic subdivision encompassing the VL and VP thalamus demonstrated hypoconnectivity and that encompassing the MD and pulvinar regions demonstrated hyperconnectivity. Our results extend the implications of disrupted thalamocortical networks involving specific thalamic nuclei to dysfunctional large-scale brain network dynamics in schizophrenia pathophysiology. The thalamus, however, is comprised of cytoarchitecturally distinct nuclei7. Parallel pathways link specific thalamic nuclei to disparate cortical areas and comprise topographically organized thalamocortical networks that support a wide array of functions spanning sensory, motor, cognitive and affective domains8. Incorporating the multinuclear structure of the thalamus and its distinct pattern of projections to cortical regions, several disease models have postulated the diversity of symptoms observed in schizophrenia to be characterized by the differential involvement of specific thalamocortical networks11.Accumulating evidence suggests the role of the thalamus and its associated cortical connectivity in the pathophysiology of schizophrenia. Large-scale meta-analyses of brain structure13. Conventionally, the cortex is parcellated into large cortical regions of interest (ROIs) that broadly correspond to the primary targets of specific thalamic nuclei, as detailed in animal studies. Each thalamic voxel is then singularly associated with one of these anatomically defined ROIs to which it is most strongly connected, and specific thalamocortical networks are localized within the resultant thalamic subdivisions that resemble thalamic nuclei identified from histological studies15. In the schizophrenia literature, diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (fMRI) studies employing these methods have reported consistent patterns of thalamocortical network abnormalities involving the mediodorsal (MD) nuclei in association with decreased connectivity between frontal ROIs and the thalamus, as well as the ventrolateral (VL) and ventroposterior (VP) nuclei with increased connectivity between motor- and sensory-related ROIs and the thalamus in chronic18 and early psychosis patients19. The comparable topography of anatomical and functional connectivity abnormalities reported in the literature, however, also highlights limitations of conventional connectivity-based segmentation approaches.In vivo examination of specific thalamocortical network disturbances in schizophrenia became possible with the advent of connectivity-based segmentation methods that delineate subdivisions of the thalamus based on their pattern of cortical connectivity20, and brain regions can demonstrate functional connectivity in the absence of direct structural linkages via polysynaptic connections, common-source connections, and other configurations of bidirectional circuits24. The conventional use of cortical ROIs that are anatomically defined based on the projections of thalamic nuclei, however, has confined previous examinations of thalamocortical functional connectivity to white matter pathways. Furthermore, spatially distinct regions that are not necessarily anatomically bound comprise intrinsically coherent large-scale networks fundamental to brain functional organization24. Contributions of these intrinsic networks in thalamocortical functional connectivity have been suggested by the spatial nonuniformity of correlations observed within cortical ROIs15, but they have been insufficiently accounted for. Thus, in prior investigations, anatomically defined ROIs may have served as functionally inaccurate ROIs25 that render topography of thalamocortical functional connectivity and its abnormalities much simplified and constricted to anatomical pathways. Overcoming these limitations carries significance beyond methodological imperatives in the schizophrenia literature when considering the extensive reports of dysfunctional large-scale brain network dynamics in patients across illness stages29.Although connectional anatomy constrains functional connectivity, the two measures are not isomorphic31. Furthermore, characterizing the distributive connectivity of thalamic nuclei, or subregions, has allowed insights into the role of the thalamus as a critical integrative node that mediates brain network dynamics. In this context, incorporating large-scale brain networks in the examination of thalamocortical functional connectivity abnormalities implicated in schizophrenia pathophysiology could not only augment the details of specific thalamocortical network disruptions with an advanced analytical approach but also provide further insight into the mechanisms underlying dysfunctional large-scale brain network dynamics.Increasing efforts investigating the role of the thalamus in human cortical organization have advanced functional perspectives in connectivity-based segmentation or parcellation approaches. Their application in psychosis, however, remains to be examined. In recent studies in healthy subjects, intrinsic brain networks have been utilized as functionally defined ROIs and delineated functional subdivisions of the thalamus that, unlike their anatomical counterparts, span across major nuclei groups and exhibit distributive connectivity with multiple cortical regions and networks31 delineating thalamus-related functional networks and comprehensively examined their connectivity abnormalities in patients with first-episode psychosis (FEP). We employed this sample to minimize the effects of potentially degenerating processes associated with the chronic course of the disorder, such as the effects of medication, poor diet, less exercise, or heavy smoking. Independent component analysis (ICA) was performed on the whole-brain voxelwise functional connectivity maps calculated for each voxel within the thalamus. The resultant independent components (ICs), which we refer to as “network ROIs,” comprised a set of spatially distinct brain regions that were functionally connected to common seed voxels within the thalamus across subjects and parcellated the cortex into a set of thalamus-related functional networks. Functional subdivisions of the thalamus were delineated by localizing the thalamic seed voxels associated with the network ROIs using regression models. Unlike the conventional ‘winner takes all’’ strategy that assigns only singular associations between ROIs and thalamic voxels, this approach allowed associations with multiple networks. The distributive functional connectivity of thalamic nuclei, or subregions, with various networks would be evident in the spatial overlaps among subdivisions. In the primary analysis, functional connectivity of the network ROIs with the thalamus was examined. This was comparable to previous connectivity-based segmentation studies, in that specific thalamocortical networks were localized within the thalamic subdivisions. In the secondary seed-based analysis, functional connectivity of the thalamic subdivisions with the rest of the brain was examined.To do so, the present study adopted a data-driven methodt = − 2.07, p < 0.05), which was missing for one FEP subject, and IQ .The demographic and clinical characteristics of the FEP subjects and HCs are summarized in Table 33, as well as subcortical and cerebellar components nts Fig. . The resent Fig. . The resOur primary analysis examining functional connectivity of the network ROIs and the thalamus revealed decreased salience network-thalamus connectivity, which localized to thalamic clusters encompassing the right VL and VP nuclei, in the FEP group Fig. . The FEPThe subsequent seed-based analysis examined functional connectivity of thalamic subdivision seeds with the rest of the brain. In the FEP group, the thalamic subdivision encompassing the VL and VP aspects demonstrated hypoconnectivity with a cluster in the left middle frontal gyrus Fig. . This thThe present study aimed to incorporate intrinsic brain networks into the examination of thalamocortical functional connectivity abnormalities implicated in the pathophysiology of FEP. To do so, abnormalities in patients with FEP were comprehensively studied using thalamus-related functional network ROIs and their corresponding thalamic subdivisions. Our primary analysis revealed abnormal functional connectivity of the network ROIs with the thalamus in the FEP group. Decreased connectivity of the salience network localized to the VL and VP aspects of the thalamus and the increased connectivity of the IC14 network, which comprised the cerebellum, temporal and parietal regions, localized to the MD thalamus. Seed-based analysis of thalamic subdivisions further demonstrated thalamocortical dysconnectivity in the FEP group. The motor-thalamic subdivision, which encompassed ventral aspects of the thalamus, exhibited hypoconnectivity, and the IC14-thalamic subdivision, which encompassed MD and pulvinar regions, exhibited hyperconnectivity. Our results provide further support for and extend the contexts of disrupted functional interactions involving specific thalamocortical networks in psychosis.35. Dysfunctions involving this network in facilitating the engagement of executive frontoparietal networks and disengaging the DMN upon cognitive demands have been postulated to be a core pathology of schizophrenia in the triple-network model37. Considering the role of the thalamus as an integrative hub31, abnormal salience network-thalamus functional connectivity may extend thalamic involvement to aberrant triple-network dynamics. Thalamic nuclei, or subregions, exhibit extensive functional connectivity with multiple large-scale networks and demonstrate a pattern similar to cortical connector hubs that, likewise, may support the integration of information across and mediate interactions among networks30. In our analysis, such distributive connectivity was evident in the considerable overlaps among functional subdivisions of the thalamus. Overlaps observed in the MD and pulvinar regions of thalamic subdivisions associated with the DMN and executive frontoparietal networks have suggested possible contributions of these higher-order nuclei in mediating interactions between these two networks that are frequently reported as competitive40. Similarly, overlaps among thalamic subdivisions associated with the salience network, DMN and executive frontoparietal networks could suggest thalamic involvement in triple-network dynamics. In the present and previous34 analyses, these overlaps were observed in the anterior, ventral, and pulvinar nuclei.The salience network, which exhibited decreased functional connectivity with the thalamus in patients with FEP, plays an integral role in mediating the switch between default mode and task-related states of brain connectivity42 and neuronal numbers44 in these higher-order nuclei provided early evidence for the differential involvement of specific thalamic nuclei in schizophrenia45. Thalamocortical models of schizophrenia have also long posited the centrality of these higher-order nuclei in tandem with cognitive impairments49. While these disease models are supported by animal and lesion studies that implicate thalamocortical network abnormalities involving these higher-order nuclei in mechanisms of cognitive impairments54, reports of cognitive, as well as clinical, correlates in patient studies remain scarce and mixed55. Interpretations of our present results are also limited by the lack of cognitive measures and this network’s resemblance to typical RSNs.Functional connectivity abnormalities involving the IC14 network in our analyses highlight the involvement of higher-order thalamic nuclei. In the FEP group, increased IC14-thalamus connectivity localized to the MD thalamus, and the IC14-thalamic subdivision seed, which localized to the MD and pulvinar regions of the thalamus, exhibited hyperconnectivity. Postmortem studies reporting alterations in volumes55 and the ventral thalamus in relation to increased connectivity with motor/sensory regions55. Discrepancies regarding our results probe differences in the composition of specific thalamocortical networks that stem from differences in ROI definitions, as well as in strategies localizing the thalamic voxels associated with specific thalamocortical networks. While a direct comparison of the present and previous results goes beyond the scope of this study, we further elaborate on the aptness and complexities entailed in our methodological approach, which aimed to delineate the topography of thalamocortical networks that better reflect brain functional organization. Correspondence between our network ROIs parcellated using a data-driven approach and cortical ROIs defined a priori with anatomical basis, as well as between thalamic subdivisions delineated in association with respective ROIs, are low, as they should be. Discrepancies, however, may also stem from functional obscurities of specific thalamocortical networks delineated using conventional cortical ROIs. The anatomical basis of these ROIs is not the only issue. These ROIs have also been coarsely defined in that they encompass extended regions of gray matter and comprise functionally heterogeneous areas, which can also have differential connectivity profiles with the thalamus59. Additionally, the conventional use of the “winner takes all” strategy averages the signals of these ROIs. Furthermore, the use of such coarsely defined cortical ROIs has ipso facto precluded spatial specificity in the cortex and the rest of the brain. Two previous connectivity-based segmentation studies, one functional and the other anatomical, employed seed-based analyses of a complementary nature to address this limitation60. Interestingly, whereas the anatomical connectivity of the PFC-thalamic subdivision seed was found to be confined to the PFC cortical ROI of the seed16, its functional connectivity extended beyond its PFC ROI and was found to be distributive with regions of the prefrontal-cingulo-parietal “executive control” network61 and suggested that the functional topography of thalamocortical networks involves large-scale brain networks.The MD and ventral thalamus highlighted in our results are consistent with the literature. The direction of change and cortical regions associated with functional connectivity abnormalities involving these nuclei, however, are incongruous. In prior thalamocortical investigations in psychosis, abnormal functional interactions of the MD thalamus have been reported in relation to decreased connectivity with frontal regions34, to be associated with the DMN, executive frontoparietal, salience, and medial visual networks, and the pulvinar was additionally associated with lateral visual, auditory and dorsal attention networks. The subdivision demonstrating hypoconnectivity encompassed the ventral lateral and posterior thalamus and was localized in association with the motor network. However, these thalamic subregions also functionally interacted with the executive, salience, and medial visual networks.Results of our seed-based analysis conducted with functional subdivisions of the thalamus, on the other hand, highlight the complexities of our methods. This analysis revealed hyperconnectivity of the seed encompassing the higher-order MD and pulvinar nuclei with small clusters of the lateral and parietal occipital, posterior cingulate, precentral, and frontal regions and hypoconnectivity of the seed encompassing the ventral thalamus with a small frontal cluster. The distributive functional connectivity of these thalamic subregions with extensive cortical networks may, at least partially, explain this perplexing pattern of results. While considerable overlaps among thalamic subdivisions corroborated the role of the thalamus as a critical integrative hub for brain functional networks, this pattern may have also complicated between-group statistical inferences by blurring the direction of and cortical regions associated with thalamocortical functional abnormalities observed in patients. For instance, the subdivision demonstrating hyperconnectivity encompassed the MD and pulvinar regions, which were localized in association with the IC14 network. However, both the MD and pulvinar regions were also observed, as well as previously reported63. In regard to the quality of our fMRI data, its limited spatial resolution, which was also resampled for the computational demands of analysis, makes the full representation of the complex heterogeneity of thalamic nuclei difficult. We could only approximately locate the major thalamic nuclei using the Talairach thalamic nuclei labels within the MNI template. The nonisotropic voxel shape of our EPI image is another possible limitation. Suggestions for further methodological refinements should also be considered. First, our analysis utilized network ROIs that represented large-scale patterns of thalamocortical functional connectivity. While these thalamus-related functional networks bore resemblance to typical RSNs generally identified based on large-scale corticocortical functional connectivity64, methodologically integrating these corticocortical networks in the analysis of thalamocortical networks could help better facilitate implications of RSNs or graph theoretical measures in probing dysfunctional brain dynamics in schizophrenia. Second, our network ROIs were identified by applying data-driven ICA on the dataset that was combined across the FEP and HC subjects to allow operation on a larger sample size. By doing so, however, abnormalities present in the patient data may have affected the initial data reduction and may have subsequently fed into stages leading to the inference of group differences. Nonetheless, our ICs displayed similar spatial patterns with those previously reported in healthy samples31 and supported the validity of our method. A follow-up study in a larger sample that would allow the examination of abnormalities in patients using ICA results from the study’s healthy subjects could help clarify this issue. Last, issues inherent to ICA should also be addressed65. A main concern is the dependency on the choice of dimensionality. ICs are known to show degrees of variability with changes in the number of ICs specified. It has been reported that low dimensionality generally results in components representing “networks” of regions with related activity, while increasing the dimensionality acts to divide those regions across multiple components68. Although extracting a larger number of ICs may present a finer network structure70, it is also possible that increasing model order results in less reliable ICs and a decrease in ICA repeatability, which is another inherent problem of the iterative algorithm71. Employing an unsupervised clustering approach and evaluating the stability of diverse segmentation results to obtain an optimal solution of the number of thalamic subdivisions34 may offer an alternative approach to ICA.Several other limitations of the present study merit consideration. First, many of the patients with FEP were on antipsychotics at the time of the scan. Although the effects of medication would be relatively small compared with those in patients with chronic schizophrenia, antipsychotics and antidepressants have subtle but measurable impacts on generalized and specific brain tissuesIn conclusion, the present study examined thalamocortical functional connectivity abnormalities in patients with FEP in the context of large-scale brain networks involving the thalamus. Our results not only provide further support for disrupted thalamocortical networks involving the MD and ventral thalamus but also extend the implications of thalamocortical abnormalities to dysfunctional large-scale brain network dynamics.Forty patients with FEP were recruited from the inpatient and outpatient clinics at the Seoul National University Hospital (SNUH) between April 2010 and March 2016. The inclusion criteria for FEP subjects were being between the ages of 16 and 40, satisfying the diagnosis of a schizophreniform disorder, schizophrenia or schizoaffective disorder as assessed via the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) Axis I Disorders (SCID-I), and having a duration of illness that was less than two years. The Positive and Negative Syndrome Scale (PANSS) and the Global Assessment of Functioning (GAF) were administered to assess psychotic symptoms and the functional status of patients with FEP. At the time of scanning, 33 patients were receiving antipsychotics. The average daily dose of antipsychotics in an olanzapine-equivalent dose is presented in Table 3, field of view (FOV) = 250 mm, flip angle = 9° and 208 slices. Resting-state fMRI data were acquired using echo-planar imaging (EPI) in the axial plane with the following parameters: TR = 3500 ms, TE = 30 ms, FOV = 240 mm, flip angle = 90°, matrix = 128 × 128, voxel size = 1.9 × 1.9 × 3.5 mm3, 35 slices, and 116 timepoints. During the fMRI scan, which lasted for 6 min and 58 s, each subject was instructed to relax with his/her eyes closed but not to fall asleep.All imaging data were acquired using a Siemens 3 T Magnetom Trio Tim Syngo MR B17 scanner with a 12-channel head coil. T1-weighted images (T1) were obtained for each participant to enable spatial localization and normalization and were acquired using the three-dimensional (3D) magnetization-prepared rapid-acquisition gradient echo (MPRAGE) sequence in the sagittal plane with the following parameters: repetition time (TR) = 1670 ms, echo time (TE) = 1.89 ms, voxel size = 1mmTo minimize possible head movements and subsequent motion artifacts, the subjects were asked to move as little as possible during image acquisition, and head cushions were also used. All images were visually inspected to exclude the presence of artifacts or gross anatomical abnormalities that could impact image processing.3 voxel size. No spatial smoothing was performed.All preprocessing steps were conducted using FMRIB Software Library (FSL) version 6.0. Preprocessing for functional data included discarding the first 4 echo-planar images, motion correction, slice timing correction, automated brain extraction, and highpass temporal filtering (> 0.01 Hz). Next, the motion parameters and signals from white matter and cerebral spinal fluid (CSF) were removed from each voxel by linear regression. The resulting data were then registered to the standard 2-mm isotropic Montreal Neurological Institute (MNI) space template by linearly registering the EPI data to the brain-extracted T1 and then applying the transform resulting from the T1 to MNI brain nonlinear registration to the registered EPI data. Finally, the data were resampled to a 3 × 3 × 3 mm31 to identify large-scale thalamus-related functional networks and to delineate the associated functional subdivisions of the thalamus. The analysis steps were as follows . The number of components was determined with reference to recent studies73. The resulting ICs, which are referred to as “network ROIs,” represent intrinsically coherent functional networks that originate from common regions within the thalamus across subjects.Spatial ICA was performed using FSL’s MELODIC (Multivariate Exploratory Linear Optimized Decomposition into Independent Components)75. First, their temporal dynamics were extracted using the group-level spatial maps of ICs as a set of spatial regressors in a general linear model (GLM). Following, the subject-specific spatial maps of the thalamic subregions were found using the extracted timecourses as a set of temporal regressors in a GLM. The resultant individual maps of thalamic subdivisions were used in the subsequent thalamocortical functional connectivity analyses, and their corresponding major thalamic nuclei were identified using the Talairach thalamic nuclei labels within the MNI template.To delineate the functional subdivisions of the thalamus, thalamic voxels associated with each network ROI were localized in two steps76, with age and sex modeled as covariates. Statistical maps were thresholded at the cluster level and considered significant at corrected p < 0.05.The primary analysis examined the functional connectivity of each network ROI with the thalamus. The individual maps of thalamic subdivisions resulting from regression analyses were concatenated across subjects, and between-group differences were tested for significance using FSL randomiset tests across subjects using FSL randomise, with threshold-free cluster enhancement (TFCE) and p < 0.05 as the statistical threshold77. The mean time series was extracted from each seed for each subject and entered into a general linear model. Between-group functional connectivity differences were tested for significance using FSL randomise, with age and sex modeled as covariates, and TFCE using p < 0.05 as the statistical threshold.The subsequent seed-based analysis examined functional connectivity of the thalamic subdivisions with the rest of the brain. Seeds were extracted from the individual maps of thalamic subdivisions resulting from regression analyses via voxelwise one sample Both analyses were performed separately for every thalamic subdivision. Talairach thalamic labels were used to identify the thalamic nuclei that corresponded to the significant clusters resulting from our primary analysis and seed extraction.Supplementary Figure S1.Supplementary Figure S2.


Transcriptome-based spliced alignment methods face challenges with short read mapping yielding low quality alignments. De-novo assembly-based methods yield longer contigs from short reads that can be more sensitive for genomic rearrangements, but face performance and scalability challenges. Consequently, there exists a need for a method to efficiently and accurately detect fusions in targeted PCR-based NGS chemistries. We describe SeekFusion, a highly accurate and computationally efficient pipeline enabling identification of gene fusions from PCR-based NGS chemistries. Utilizing biological samples processed with the QIAseq RNAscan assay and in-silico simulated data we demonstrate that SeekFusion gene fusion detection accuracy outperforms popular existing methods such as STAR-Fusion, TOPHAT-Fusion and JAFFA-hybrid. We also present results from 4,484 patient samples tested for neurological tumors and sarcoma, encompassing details on some novel fusions identified.Detecting gene fusions involving driver oncogenes is pivotal in clinical diagnosis and treatment of cancer patients. Recent developments in next-generation sequencing (NGS) technologies have enabled improved assays for bioinformatics-based gene fusions detection. In clinical applications, where a small number of fusions are clinically actionable, targeted polymerase chain reaction (PCR)-based NGS chemistries, such as the QIAseq RNAscan assay, aim to improve accuracy compared to standard RNA sequencing. Existing informatics methods for gene fusion detection in NGS-based RNA sequencing assays traditionally use a transcriptome-based spliced alignment approach or a  Gene fusions are potentially pathogenic events that result from genomic structural rearrangements including inversions, translocations, and interstitial deletions. Gene fusions are frequently observed in cancer, and while their prevalence varies by tumor type they have been estimated to account for 20% of all cancer morbidity . Identifin situ hybridization (FISH) and immunohistochemistry (IHC) .RNA sequencing (RNA-Seq) assays for gene fusion detection provide improvements in throughput, sensitivity and specificity over traditional DNA and protein-based approaches like fluorescence ry (IHC) . RNA-basry (IHC) . The PCRry (IHC)  and enabry (IHC) , the addry (IHC) , and canry (IHC) , and so De-novo assembly-based approaches yield longer contigs from short reads and address some of the limitations of short-read alignment but are computationally intensive and often not scalable to large scale clinical testing , a time-efficient pipeline that leverages de-novo assembly and alignment based approaches to accurately identify gene fusions utilizing PCR-UMI-based amplicon RNA-Seq. SeekFusion performs rapid alignment to gene sequences, then groups and filters aligned reads for de-novo assembly. Assembled contigs are realigned to a reference genome and fusion genes are identified, annotated and reported in a VCF format. Using verified clinical cases and synthetic controls, we demonstrate that SeekFusion outperforms existing pipelines by balancing high analytical sensitivity and specificity with computational efficiency. The algorithm is written using Python and bash and the functions are wrapped in WDL and processed using Cromwell  chromosomal microarray (CMA) and reverse transcription polymerase chain reaction (RT-PCR) with or without subsequent direct Sanger sequencing as previously described .RNA was extracted from macrodissected, unstained slides using the QIAamp miRNeasy FFPE kit and nucleic acid was quantitated with the NanoDrop 2.0 system . LibrarySeekFusion was designed in Cromwell/WDL to enable standalone or server mode workflow execution. Server mode performs tasks in parallel for every gene targeted . The pipPCR duplication is a byproduct of amplification steps in sequencing protocols that produces multiple copies of individual sequence fragments and artificially inflates their abundance. The QIAseq RNAscan chemistry utilizes UMIs that are random nucleotide sequences incorporated into sequence fragments prior to amplification to enable the identification of PCR duplicate reads originating from the same sequence fragment. Barring technical and sequencing errors, each of these duplicated reads will share identical nucleotide sequence. In reality, however, sequencing errors introduce differences in duplicate reads. The “deduping” module accounts for these errors and attempts to identify the PCR duplicates irrespective of sequencing error. It then builds a single consensus read from identified PCR duplicates and produces an updated Phred quality score for each base that accurately represents the summary evidence when estimating the probability of an erroneous base call. This approach produces higher confidence base calls that facilitate accuracy of downstream processing and improves the ability to discern true calls.The deduping algorithm assumes a prior probability for the nucleotides at a particular position and uses Bayes theorem to update the probability of the base in a particular position of a UMI using conditional independence See .FASTQ files are used as input to the deduping module. The algorithm is written in C and based on a highly efficient and customized data structure. Efficient binary representation of k-mers (up to length 16) enables perfect hashing and rapid computations of hamming distances. The algorithms also make use of BGZF compressed FASTQ files (this is the same compression method used in bam files) which enables indexing and fast random read access within the compressed FASTQ files.Fastp  was implDe-novo assembly is a computationally intensive process that has the potential to overwhelm computational resources  using BLAT . The mononucleotide repeat ratio calculation is described in the For filtering highly homologous regions, SeekFusion flags calls that are recurrent in every sample due to homology/low complexity using a blocklist. The blocklist calls are presented in the A custom script was developed to annotate identified contig breakpoints and provide genomic context. Annotations generated include the gene, exon and coding frame status of the fusion, i.e., if the fusion is likely protein-coding. One of the key annotations provided by the annotation module is if a fusion is In-frame, which implies that there was no frame shift in the 3′-gene, regardless of single amino acid mutation or insertion events at the fusion junction. All reads originally passing the UMI-based deduping and adapter trimming steps were retrieved and aligned to the hg19 human reference transcriptome from Ensembl and Refseq using BWA-mem. Reads that produced perfect alignments to known gene transcripts were removed from further consideration as they likely represent normal transcriptional events. For each gene fusion candidate identified by the alignment of assembled contigs to the human genome, a chimeric construct of the purported fusion sequence was created . Constructs annotated as occurring within a single known transcript were removed from further consideration, with the exception of select known aberrant single-gene events. The retained reads were aligned against the potentially chimeric gene fusion reference sequences using BWA-mem. Only reads spanning at least 10 bases beyond a breakpoint were considered as evidence of a potential fusion. A single supporting read was required as evidence of a fusion candidate and all candidates were output in a standardized variant call format (VCF) file. While minimal read support was required to facilitate downstream benchmarking, the supporting read threshold is user configurable. Finally, the fusion-construct aligned BAM file was used to create an Integrative Genomics Viewer (IGV)  session https://hub.docker.com/repository/docker/jagadhesh89/seekfusion. The usage details are explained in the README file. In addition to the easy to use docker image, the source code is also made available via github (https://github.com/jagadhesh89/seekfusion).The pipeline is available in a Docker container  image anBenchmarking was performed for SeekFusion, JAFFA-hybrid , STAR-FuAccuracy was measured based on putative gene fusion calls using the following equation at varying levels of fusion read support thresholds.For in-silico generated fusions, supporting reads are a known quantity. Mean Absolute Percentage Error  (MAPE) aThe neurological oncology assay was developed, verified, validated, New York (NY) State approved and implemented clinically using the SeekFusion algorithm. In the verification study, 63 total unique samples were processed . The NGS assay results were confirmed by RT-PCR and CMA tests. The overall accuracy of the NGS assay was 96.1% and no fusion transcripts were detected in negative control samples indicating an overall specificity of 100%. Following the clinical go-live of the assay, 2,979 clinical patient samples ordered for neurological oncology testing and were processed using the SeekFusion algorithm. A sarcoma assay was developed, verified, validated and approved for clinical testing by NY state. The assay uses the SeekFusion algorithm and evaluates 138 gene targets for presence of somatic gene fusions and common BCOR internal tandem duplications (ITDs) using the same QIAseq RNAscan chemistry. In the verification study, this next-generation sequencing (NGS) assay was performed in 111 sarcoma formalin-fixed, paraffin-embedded (FFPE) and cytology samples (86 fusion positive and 25 fusion negative). The NGS assay results were confirmed by RT-PCR and FISH tests. The overall accuracy of the NGS assay was 95.5%. No targeted gene fusions were detected in 20 negative control samples (100% specificity), A total of 1,505 clinical cases were processed using the SeekFusion algorithm. An IRB request was submitted and approved to share the clinically reported gene fusions.The accuracy of SeekFusion was highest among the benchmarked tools, followed by JAFFA-hybrid, STAR-Fusion and TOPHAT-Fusion . True poThe number of gene fusion-supporting reads detected by the four tools was assessed for the true positive gene fusions. Deduped and trimmed FASTQs were utilized in the analysis since only SeekFusion demonstrated the ability to successfully detect the true positive fusions from raw FASTQs. SeekFusion reported more gene fusion supporting reads than the other tools in 83% of cases . SeekFusMAPE and SMAPE are widely used measures of forecast accuracy; they aid in assessing accuracy based on percentage errors from the actual. MAPE  and SMAPIn addition to analytical performance, clinical bioinformatics pipelines are required to perform in a time-efficient manner to maintain necessary assay turnaround time. Benchmarking of runtimes was performed to assess the suitability of the algorithms for real-world clinical use. The single in-silico sample was excluded from the benchmarking since it does not represent a true patient sample. For both Analysis 1, JAFFA exhibited time-requirements that exceeded all other tools . The remPeak memory utilization of the individual tools benchmarked were assessed. The maximum input memory for each of the pipelines were capped at 180 GB. For each sample, the maximum memory used by the tool is used for calculating a per tool median memory utilization for analysis 1 and analysis 2. The median is rounded to the nearest GB. JAFFA utilized the most memory with a median memory utilization of 171 GB in analysis 1 and 172 GB in analysis 2. SeekFusion peaked at a median memory of 58 GB in analysis 1 and 64 GB in analysis 2, with CAP3 assembly being the most memory consuming module in the SeekFusion pipeline. STAR-Fusion peaked at a median memory of 30 GB in analysis 1 and 34 GB in analysis 2. Tophat-Fusion used the least memory; with peak of median memory in analysis 1 and analysis 2 of 2 GB.Methods, Clinical Testing On Neurological Oncology and Sarcoma Samples section.Taken together, while considering high accuracy, high true positive rate, ease of installation, ease of usage in a clinical setting and turnaround time for the pipeline, SeekFusion was identified as the method for use of clinical assay development. Neurological oncology assay and sarcoma assay were developed, verified and approved as detailed in the Of the 2,979 cases tested clinically using the neurological oncology assay, 569 cases were reported with clinically relevant gene fusions after careful variant review and orthogonal confirmation using RT-PCR . Out of In the neurological oncology assay, EGFRvIII was the most commonly found rearrangement, 195 out of 2,979 patients tested were identified with this rearrangement. EGFRvIII has been established to be present in up to 28–30% of the glioblastoma cells and constitutes to be a therapeutic target . KIAA154In the sarcoma assay, EWSR1 was the most commonly rearranged gene in our case series, with 3′ partners including FLI1, ERG, WT1, CREB1, ATF, PBX3, CREB3L1, TFCP, NR4A3, NFATC2, POU5F1, DDIT3, CREM, PATZ1, and COLCA2 in a wide variety of tumor types. SS18-SSX1 was reported in 32 synovial sarcoma cases. PAX3 was the 5′ fusion partner in 29 cases with 3′ partners being FOXO1 fusions identified in alveolar rhabdomyosarcoma cases, MAML3 and NCOA1 fusions in two different biphenotypic sinonasal sarcoma cases.As described previously the assay chemistry is gene-partner agnostic, enabling identification of novel gene fusions, and many novel fusions were detected in the clinical patient cohort. We have summarized all the neurological cancer and sarcoma gene fusions identified by our method in the Case 1 is a 45-year-old male who presented with a lower left extremity mass suggestive of a low-grade mesenchymal neoplasm. By immunohistochemistry (IHC) the neoplastic cells were focally positive for desmin, epithelial membrane antigen and STAT6 and showed limited expression of TRK. ALK, OSCAR keratin and TLE1 were negative. Histologically the neoplasm was a very unusual appearing, multicystic proliferation of rather bland small round epithelioid cells, in areas showing the presence of an apparent second cell population, consisting of flattened cells with more abundant eosinophilic cytoplasm. This morphologic appearance was suggestive of at some level an adnexal lesion however a variety of epithelial markers are essentially negative. It also appeared to be related to angiomatoid fibrous histiocytoma although the morphologic features of this lesion are atypical and although it showed very limited coexpression of desmin and EMA it was negative for the EWSR1 and FUS gene fusions that characterize this tumor. Based on the very bland morphology of this lesion and the extremely low mitotic rate it is believed that the lesion is either entirely benign or at most has some limited capacity for local recurrence. NGS testing identified a novel TFG-ZBTB10 fusion . The speCase 2 is a 23-year-old male who presented with a 14 × 4.8 × 7.8 cm right chest mass which was eroding the underlying clavicle. Microscopically, this is a spindle cell neoplasm showing a whorling, fascicular growth pattern with scattered chronic inflammatory cells and foci of hyalinized fibrosis. The somewhat enlarged nuclei raise concern for the possibility of a low-grade sarcoma, but they maintain a rather uniform appearance and lack significant atypia. IHC studies show the tumor cells to be positive for FLI-1 and negative for S100 protein, SOX10, desmin, myogenin, WT1, SMA, CD34 and pan-cytokeratin. Given these findings, the differential diagnosis included follicular dendritic sarcoma and angiomatoid fibrous histiocytoma. Additional stains performed locally showed the cells to be negative for CD31, CD35 and CD21. NGS testing revealed a novel RRFIP1-ALK gene fusion . ALK fusde-novo assembly-based approaches enables SeekFusion to increase accuracy of fusion calling over other published and widely used gene fusion-calling algorithms, while maintaining reasonable computational expense. We have demonstrated that SeekFusion exhibits analytical sensitivity with minimal false positive calls and produces higher read support per gene fusion call when compared to other benchmarked bioinformatics tools. Furthermore, SeekFusion is computationally efficient and capable of facilitating realistic turnaround times in a clinical setting. The bioinformatics pipeline and quality check turnaround times are less than a day for the neurological oncology assay and the sarcoma assays mentioned in our study, which enables an analytic time of 14 days for the assay, from sample collection, until clinical report.We have developed a novel bioinformatics pipeline to enable accurate and precise gene fusion detection for commonly used RNA UMI-based amplicon NGS assays. A combination of traditional alignment and Although STAR-Fusion, JAFFA-Hybrid and TOPHAT-Fusion have previously been benchmarked to perform adequately for gene fusion detection using standard RNA-Seq assays , our stuIn terms of computational run-time, all tested algorithms performed at a level that is amenable to clinical turnaround times, with the possible exception of JAFFA, which demonstrated obvious scalability issues and required as much as 6 hours per sample to complete a single analysis. STAR-Fusion, Tophat-Fusion and SeekFusion performed similarly, although STAR-Fusion showed overall lower run-times than the other tools. Considered in totality, however, the overall performance characteristics of SeekFusion combined with clinically favorable run-times demonstrate it to be the optimal solution for fusion transcript identification.SeekFusion pipeline’s use of common output file formats represent another advantage for its implementation. Most gene fusion calling algorithms utilize arbitrary formats which present compatibility issues with downstream tools. The use of a standard VCF output for candidate events enables more seamless integration with existing tools and workflows. The generation of an IGV session file further facilitates the utilization of SeekFusion’s outputs with common downstream components. The ability to readily visualize the level of support and alignment quality for fusion-supporting reads is a key functionality. The visualization functionality is currently unavailable in the other tested gene fusion calling software and allows end-users to visually judge the quality of the supporting reads and infer confidence of a gene fusion call.A limitation of the previously published tools profiled in this study, beyond core performance metrics, is the lack of ability to detect clinically relevant single gene events , such ashttps://hub.docker.com/repository/docker/jagadhesh89/seekfusion. To validate SeekFusion and establish analytical sensitivity and specificity for a similar clinical assay, it is recommended to run the pipeline on a robust set of known positives and negatives, including positive in-silico controls and a positive control with spiked in oligonucleotides.A potential limitation of our study was the relatively small number of clinical samples that were available for initial benchmarking. This reflected the difficulties in obtaining broader research consent, which we overcame by supplementing real clinical samples with oligonucleotide spike-ins and in-silico simulated data. Despite the diversity of the test data utilized, SeekFusion demonstrated high analytical sensitivity and specificity across all datatypes when compared to other available tools, further supporting SeekFusion pipeline’s accuracy and versatility. SeekFusion pipeline’s packaging allows it to be installed and deployed in a clinical setting with minimal efforts. The pipeline enables customization of thresholds, tools, and settings through a configuration file. The setup of SeekFusion for another clinical assay is easily enabled through simple user configuration, as mentioned in the readme instructions in In summary, SeekFusion represents an accurate, time-efficient and versatile solution for the clinical detection of fusion transcripts from common RNA UMI-based amplicon NGS assays. It is our hope that the tool’s public availability and cross-platform capabilities will enable ready deployment and facilitate accurate gene fusion identification in a range of clinical laboratory and disease settings.


Glioblastoma and anaplastic astrocytoma represent the most commonly encountered high-grade-glioma (HGG) in adults. Although both neoplasms are very distinct entities in context of epidemiology, clinical course and prognosis, their appearance in conventional magnetic resonance imaging (MRI) is very similar. In search for additional information aiding the distinction of potentially confusable neoplasms, histogram analysis of apparent diffusion coefficient (ADC) maps recently proved to be auxiliary in a number of entities. Therefore, our present exploratory retrospective study investigated whether ADC histogram profile parameters differ significantly between anaplastic astrocytoma and glioblastoma, reflect the proliferation index Ki-67, or are associated with the prognostic relevant MGMT (methylguanine-DNA methyl-transferase) promotor methylation status.Pre-surgical ADC volumes of 56 HGG patients were analyzed by histogram-profiling. Association between extracted histogram parameters and neuropathology including WHO-grade, Ki-67 expression and MGMT promotor methylation status was investigated due to comparative and correlative statistics.Grade IV gliomas were more heterogeneous than grade III tumors. More specifically, ADCmin and the lowest percentile ADCp10 were significantly lower, whereas ADCmax, ADC standard deviation and Skewness were significantly higher in the glioblastoma group. ADCmin, ADCmax, ADC standard deviation, Kurtosis and Entropy of ADC histogram were significantly correlated with Ki-67 expression. No significant difference could be revealed by comparison of ADC histogram parameters between MGMT promotor methylated and unmethylated HGG.ADC histogram parameters differ significantly between glioblastoma and anaplastic astrocytoma and show distinct associations with the proliferative activity in both HGG. Our results suggest ADC histogram profiling as promising biomarker for differentiation of both, however, further studies with prospective multicenter design are wanted to confirm and further elaborate this hypothesis. Gliomas belong to the group of primary central nervous system (CNS) neoplasias and develop from glial cells of the CNS. According to epidemiologic studies, they account for almost one third of all diagnosed brain tumors in adults . The WorThe two most common HGG in adults are the glioblastoma (WHO IV) with about 14.9% and the anaplastic astrocytoma with about 1.7% of all newly diagnosed intracranial masses  despite Magnetic resonance imaging (MRI), with its unparalleled soft tissue contrast, is the most important imaging modality for all intracranial masses. In case of HGG, routinely used morphological MRI sequences like T2-weighted and contrast enhanced T1-weighted sequences are pivotal for the precise definition of tumor localization, evaluation of its mass effect, necrosis and peritumoral edema—information being essential to plan the surgical therapy. However, qualitative morphological data remain rather unreliable concerning the differentiation between grade III and grade IV astrocytoma, not least because of the regularly similar-looking appearance on such MRI images. Therefore, advanced MRI techniques, including MR-spectroscopy, perfusion-weighted imaging, and diffusion-weighted imaging are complementarily used in most of the standard MRI protocols in order to improve the diagnostic accuracy.Especially diffusion-weighted imaging (DWI) is a well-established and nonetheless still evolving technique in the MRI domain. DWI is able to estimate the random diffusional motion of water molecules  in bioloTherefore, the aim of this exploratory retrospective study was to evaluate whether whole tumor HA of ADC profiles has the ability to i) differentiate WHO grade III anaplastic astrocytoma from WHO grade IV glioblastoma, to ii) estimate the proliferative potential of the neoplasms represented by the Ki-67 proliferation index and to iii) predict the prognostic relevant MGMT (methylguanine-DNA methyl-transferase) promotor methylation status.The study was approved by the ethics committee of the medical council of Baden-Württemberg . The patient data used in our study were extracted from the hospital`s electronic medical records system  in the period between 01/2012 and 02/2017 after full anonymization.Our institutional radiological information system (RIS) was searched for matching patients using the search criteria glioma and primary brain tumor. A total of 72 patients were identified in the period between 01/2012 and 02/2017. All patients underwent either a diagnostic biopsy or tumor resection in our hospital with subsequent neuropathological workup of the tissue samples. Histological diagnosis, MGMT promotor methylation status and the proliferation index Ki-67 were taken from the hospital patient database. Only patients with presurgical MRI examination and sufficient DWI datasets were included in the study. MRI scans were checked for hemorrhage, significant calcifications or artificial data due to other causes and excluded if necessary, to avoid artifact-related distortion of ADC values. Finally, 56 patients  were included in our retrospective analysis.All patients received an MRI scan of the brain using a 1.5 T device . The following imaging protocol was used:axial T1 weighted (T1w) spin echo (SE) sequences  prior and post intravenous application of contrast medium 2. ADC maps were automatically calculated by the pre-installed software package of the device manufacturer.axial DWI  with b values of 0 and 1000 s/mmAll MRI images and ADC maps were available in digital form and subsequently analyzed by two experienced radiologists  on a PACS workstation (Impax EE R20 XII) without knowledge of the histopathological diagnosis.via the aforementioned AGFA PACS, whole lesion histogram profiling was carried out by using a custom-made DICOM image analysis tool  as follows: Initially, T1weighted images were loaded into a graphical user interface (GUI) to mark the tumor suspected lesion of each patient in all respective MRI sections. Then, all regions of interest (ROIs) were automatically co-registered with the corresponding ADC maps, followed by whole lesion histogram profiling with calculation of ADCmean, ADCmin, ADCmax, ADCp10, ADCp25, ADCp75, ADCp90, ADCmodus, ADCmedian, ADC standard deviation (SD), Skewness, Kurtosis and Entropy. All primary histogram data on each patient level as well as the corresponding histopathological information are provided in 10.5281/zenodo.4605319).After exporting the ADC maps and T1 weighted images from our institutional archive in a DICOM format For histological diagnostics, immunohistochemistry and PCR sequencing, the tumor specimens were formalin-fixed and paraffin-embedded. In a first step, the embedded samples were sectioned at 3μm, followed by hematoxylin and eosin (H&E) staining as well as immunohistochemistry using specific antibodies against Ki-67 . All sectioned tissue samples were analyzed histologically for presence of viable tumor infiltration, absence of significant necrosis and hemorrhage prior to further processing. Digitalization of the histopathological images was performed with a Leica microscope, carrying a DFC290 HD digital camera and LAS V4.4 software . Tumor proliferation index was estimated by dividing the number of specifically stained (Ki-67 positive) cell nuclei by all nuclei. The area showing the highest number of positive cell nuclei was selected in each case.CGACGCCCGCAGGTCCTCG). Methylation percentage of 10% and higher was considered as methylation positive.In a second step, the paraffin-embedded tumor samples were dissected into 10 μm slices for DNA isolation using the Maxwell® RSC FFPE Plus DNA Kit AS1720  with a Maxwell® RSC Instrument . Conversion of unmethylated cytosine residues to uracil was performed by bisulfite treatment using the EpiTect® Bisulfite Kit , each step according to the manufacturer’s procedures. Subsequently, the bisulfite-converted DNA was amplified via PCR reaction and the methylation status of the MGMT gene was determined by pyrosequencing according to the manufacturer’s protocol using the Therascreen MGMT Pyro® Kit , testing 4 CpG islands .After investigating the DWI data and histopathological information by descriptive statistics, the data was tested for Gaussian distribution by using the Shapiro-Wilk-Test. To compare normally distributed DWI histogram profiling parameters between grade III and grade IV astrocytoma as well as between MGMT promotor methylated and unmethylated gliomas, T-Test was performed. Comparison of parameters showing a non-Gaussian distribution between grade III and grade IV and between MGMT promotor methylated and unmethylated astrocytoma was performed by using the Mann-Whitney-U Test. For Correlation analysis the Pearson Correlation Coefficient was used in case of normally distributed parameters and the Spearman-Rho Rank-Order Correlation Calculation in case of non-Gaussian distribution. Generally, p-values < 0,05 were taken to indicate statistical significance in all instances.Finally, receiver operating characteristics (ROC) curve analysis was performed and the respective area under the curve (AUC) was calculated to assess the accuracy of ADC volume histogram profiling. Youden’s Index was calculated for those ADC parameters with the best test accuracy to estimate possible cut-off values.Brain MRI scans from patients with HGG, the corresponding tumor volume ADC histograms as well as the histopathological images (HE and Ki-67) are displayed in In brief, comparative analysis detected significant differences between grade III and grade IV astrocytomas for ADCmin, ADCmax, ADCp10, ADC SD and Skewness . Mean values of ADCmin and the lowest percentile ADCp10 were significantly lower in the WHO grade IV group, whereas ADCmax, ADC SD and Skewness were significantly lower in the WHO grade III group. As expected, WHO grade IV astrocytomas showed significant higher values for the Ki-67 proliferation index compared to their WHO grade III counterparts. On the contrary, no significant difference could be revealed by comparison of ADC histogram parameters between MGMT promotor methylated and unmethylated HGG. The results of the complete comparative statistical analysis are provided in Tables Statistical correlation analysis, using the Pearson’s Correlation Coefficient in case of normal distributed data and the Spearman-Rho Rank-Order Correlation in case of non-Gaussian distribution, identified significant associations (p < 0.05) between the proliferation index Ki-67 and ADCmin, ADCmax, ADC SD, Kurtosis and Entropy. The results of the correlative analysis are represented in Moreover, to evaluate the potential test accuracy in terms of differentiating grade III from grade IV glioma AUC values were calculated for each of the histogram parameters that reached significance in the comparative statistical analysis. The following values were obtained : ADCmin , ADCmax , ADCp10 , ADC SD  and Skewness . The ROC of the two parameters with the best accuracy, ADCmax and ADC SD, are shown in Anaplastic astrocytoma (WHO grade III) and glioblastoma (WHO grade IV) exhibit a highly heterogeneous tissue microarchitecture with areas of very distinct mitotic activity and cellularity .It has exemplarily been reported that the so called peritumoral zone, which is morphologically characterized by vasogenic edema, but does not yet reveal blood brain barrier disruption, contains especially aggressive and highly proliferating tumor cell islets, being causative for local recurrence in most cases . UnfortuThe ADC map of a tumor reflects its proliferative activity and cellular density, with decreased ADC values revealing increased cellularity and higher tumor grades in most entities , 26–28. Our present study revealed that the lowest percentile of the ADC continuum, ADCp10, as well as the maximum and minimum values, ADCmax and ADCmin, significantly differed between grade III and IV gliomas. More specifically, grade IV gliomas in our cohort had lower ADCmin- and higher ADCmax-values, reflecting broader tumor heterogeneity compared to grade III lesions. This hypothesis is corroborated by the fact that grade IV gliomas in our study exhibited a significantly higher ADC standard deviation than grade III gliomas. This information is significant for the oncologic surgeon, as the spatial distribution of different tumor grades in the neoplasm of the individual patient influences the strategy for resection, especially if the resection of the entire tumor is impossible without risking unjust surgical morbimortality.Besides the aforementioned first order histogram characteristics like mean, median and percentiles, histogram analysis provides additional second order characteristics–kurtosis, skewness and entropy–which describe more complex aspects of the value distribution . IncreasIn line with the general accepted assumption, that higher glioma grade is associated with higher Ki-67 expression-based proliferation index, our study confirmed higher indices in grade IV glioma compared to grade III entities.An important molecular property in gliomas bearing great prognostic relevance is the Oxygen 6-methylguanine DNA methyltransferase (MGMT) promotor methylation status. As crucial DNA repair enzyme it is capable of reversing naturally occurring DNA alterations and plays therefore an important role for genomic stability. MGMT gene silencing due to promotor methylation makes the affected tumor cells more sensitive to alkylating chemotherapeutics and leads to an increased overall survival in case of GBM . In receFinally, correlation analysis revealed significant positive correlations between Ki-67 expression and ADC SD, ADCmax and Entropy as well as negative correlations between Ki-67 index and ADCmin and Kurtosis. These results are well consistent with the results of the comparative statistics, in which both the extreme values  and the SD differed significantly between the two tumor grades. Tumors with a higher tumor grade and thus a higher Ki-67 index appear to have a broader spread of ADC values. As far as entropy is concerned, a positive correlation between this parameter and the tumor proliferation rate could also be demonstrated in case of meningiomas . The rol2), which could have led to an increased impact of small vessel perfusion on ADC values in this study. Another potential limitation of our preliminary study is that the familywise alpha inflation due to serial hypothesis tests in the statistical analysis was not controlled. Finally, the neurosurgical specimen collection for further histological processing and diagnostics were almost exclusively performed by en-bloc resection. Related to the nature of the histopathological workup, a holistic analysis allowing a direct anatomical correlation with the histogram analysis, for example with neuronavigational data, was therefore impossible. However, the present study intended to use features of the whole tumor ADC volumes of presurgical MRI scans for correlation of prognostically relevant tumor biological features, but not a MRI–histopathology–volume correlation.Our study has several limitations. Firstly, it was conducted as a retrospective study, which inevitably leads to an inferior level of evidence compared to prospective studies. Moreover, imaging data were obtained by only 1.5-T MRI devices and therefore exhibited a lower signal-to-noise ratio and consequently lower spatial resolution, which could have reduced the significance of the ADC histogram profiling in this investigation. Furthermore, ADC calculation was realized by employing only 2 b values Click here for additional data file.


In this study, we examined the effects of different flower stem features in the round-leaved Alexanders Smyrnium rotundifolium on the visiting frequency of the generalist ant species, the black garden ant Lasius niger. We conducted the experiments with ants running on dry wooden sticks mimicking four different types of stems. To attract ants, we placed a sweet sugar syrup droplet on a stick tip. Ants visited different types of stem-mimicking sticks with significantly different frequencies. The highest number of insects were registered on untreated stick samples, whereas the lowest visiting frequency was observed on sticks bearing cuff-like structures  covered with a nano/microparticle film, which caused the slipperiness of the surface. Thus, by combining macroscopic obstacles and slippery surfaces, plants can protect their flowers from undesirable crawling visitors such as ants.Flowering plants usually attract insect pollinators by offering them nectar, pollen or other energetically valuable sources. To deter ants, which are unreliable pollinators and can act as nectar thieves, plants have developed different systems either inside the flowers or associated with the stems. The latter one, called Smyrnium rotundifolium on the visiting frequency of generalist ants, we conducted experiments with Lasius niger ants running on dry wooden sticks mimicking different types of stems: (1) intact (grooved) sticks; (2) sticks painted with slaked (hydrated) lime  imitating plant epicuticular wax coverage; (3) intact sticks with smooth polyester plate-shaped cuffs imitating upper leaves; and (4) intact sticks bearing cuffs painted with slaked lime. Ants were attracted by the sweet sugar syrup droplets placed on a stick tip, and the number of ants visiting the drops was counted. Our data showed significant differences in the visiting frequencies between the different types of stem-mimicking samples. The number of recorded ants progressively decreased in the following order of samples: intact sticks—painted sticks—sticks with intact cuffs—sticks with painted cuffs. These results clearly demonstrated that micro/nanoscopic surface coverages and macroscopic physical barriers, especially if combined, have a negative impact on the attractiveness of stems to ants. This study provides further evidence for the hypothesis that having a diversity of plant stems in the field, generalist ants prefer substrates where their locomotion is less hindered by obstacles and/or surface slipperiness.In order to understand the effects of the morphology and surface texture of flower stems in  These features include slender elongate erect stems, rigid spreading trichomes  on the lower internodes, three-dimensional epicuticular wax coverage  and often swellings in the upper internodes [To attract insect pollinators, mostly from the orders Hymenoptera, Diptera, Lepidoptera, and Coleoptera, the angiosperms (flowering plants) usually produce and offer them nectar, pollen or other energetically valuable resources that are in the main associated with flowers . On the g nectar ,18,19,20S. daphnoides stems and suggested its hampering effect on ants trying to reach the nectar-bearing flowers. Later field observations on Eriope plants showed that ants of all sizes failed to climb up these stems covered with microscopic wax projections [H. vitifolia and Lasius niger (Hymenoptera: Formicidae) demonstrated that ants were not able to gain a foothold on the waxy stems, perhaps because they dislodged wax projections and therefore fell to the ground [L. niger ants on the waxy flower stems of Anethum graveolens (Apiaceae), Dahlia pinnata and Tagetes patula (both Asteraceae) clearly showed that ants were able to walk significantly lower distances on the wax-covered stems compared to the reference wax-free ones [L. niger ants was performed with five plant species bearing different surface structures on their stems: Alchemilla mollis (Rosaceae), with wax projections and long thread-shaped trichomes; Lilium lancifolium (Liliaceae), without wax, but with ribbon-shaped trichomes and cuticular folds ; Salvia nemorosa (Lamiaceae), without wax, but with trichomes of various lengths and cuticular folds; Tulipa gesneriana (Liliaceae), with wax projections and lacking trichomes; Paeonia lactiflora (Paeoniaceae), having neither of the above surface features [L. niger ants, which had been introduced at the ground level, became entangled in the trichomes near the base of the H. vitifolia stem.Until now, the main attention was given to the contribution of the wax coverage on stems to ant deterrence. First, Kerner von Marilaun  detectedjections . Simple e ground . Our preree ones . Ants mofeatures . It was features , showingSmyrnium rotundifolium (Apiaceae)  has not been studied so far. In the present study, besides the microscopic surface features, we are also focusing on the macroscopic stem structures, which can potentially serve as a physical barrier for ants—the sessile upper leaves clasping the stem like cuffs in the round-leaved Alexanders piaceae) c. In thipiaceae) b are exppiaceae) b. To ensS. rotundifolium on the visiting frequency of generalist ants, we conducted the experiment with L. niger ants and dry wooden sticks mimicking different types of plant stems, among them that of S. rotundifolium. Ants were attracted by the sweet sugar syrup droplets placed on a stick tip, and the number of ants visiting the droplets on the different stick samples was counted. Our zero hypothesis was that the frequency of ant visits should be similar for all the stick sample types tested. We have found that both the microscopic and macroscopic stem characteristics negatively impact ant visits, and if combined, have a much more pronounced effect. The obtained results support the previously proposed hypothesis [In order to understand the effects of the flower stem morphology and surface texture in pothesis  that havS. rotundifolium Mill., also treated at the rank of the subspecies under S. perfoliatum (S. perfoliatum subsp. rotundifolium (Mill.) Hartvig) [S. perfoliatum var. rotundifolium (Mill.) Fiori) [S rotundifolium has been reported so far.The round-leaved Alexanders Hartvig)  or even ) Fiori) , is an e) Fiori)  of 30–60) Fiori) ,27). The) Fiori)  and occu) Fiori) . No specL. niger L. is an omnivorous species that originated from South America and Africa [L. niger as a model generalist ant species for experiments because (1) it is associated with a variety of plant species  and (2) it was available in a great number at the study site. Attachment system of L. niger is composed of paired claws and a pad-like, smooth arolium on each foot .Plant material for cryo-scanning electron microscopy (SEM) examination was collected from the plants growing in the olive grove near the Gardiki Castle . Upper leaves and upper portions of the stem were cut off from living plants and kept for 24 h inside small plastic vials containing wet paper in order to prevent desiccation of the plant material. Then, small samples (1 cm × 1 cm) from the middle region of the leaves and from the stem were cut out, attached mechanically to a small vice on a metal holder and frozen in a cryo-stage preparation chamber at −140 °C . Frozen samples of the upper  and lower  leaf sides and of the stem surface were sputter coated with gold–palladium (thickness 6 nm) and examined in a frozen condition in a cryo-SEM Hitachi S-4800  at 3 kV accelerating voltage and −120 °C temperature. Types of wax projections were identified according to Barthlott et al. .2) were sputter coated with gold–palladium (6 nm thickness) and studied in the SEM at 3 kV accelerating voltage and room temperature (ca. 20 °C).To visualize the surface textures of dry wooden sticks, transparent polyester film and calcium carbonate coverage used in the experiment with ants see , small pn = 10.Morphometrical variables of surface features were measured from digital images using SigmaScan Pro 5 software . These data are presented in the text as mean ± SD for S. rotundifolium, we used dry wooden sticks  dug to a 5 cm depth into the soil. We prepared four types of sticks mimicking different types  of plant stems: (1) intact, untreated sticks; (2) sticks painted with slaked, or hydrated, lime, thereby imitating plant epicuticular wax coverage; (3) untreated sticks with smooth plate-shaped cuffs imitating upper leaves  dissolved in double-distilled water in the ratio 1:1 (lime to water). After drying under air conditions (in the presence of carbon dioxide CO2), the limewater resulted in the formation of a micro/nanostructured layer of calcium carbonate (CaCO3) on the surface.For the experiment with ants, instead of native plant stems of r leaves b; and (4r leaves c. The cur leaves d. To get2), and therefore exposed to approximately the same number of foraging ants. The position of each stick was changed every day during the experiment. A small droplet (ca. 15 µL) of the customly prepared sugar syrup (double-distilled water to sugar weight ratio was 1:1) was deposited on the stick tip. After 12 h, each single stick sample was individually checked, and the number of ants feeding on the syrup droplet . Five sticks of each type  were placed at nearly similar distance (ca. 10 cm) from each other; the order of different stick types was randomized e. This a droplet a was regTo determine whether there is a significant difference between the expected frequencies and the observed frequencies of ant visits in different stick types, the number of ant visits per stick type was tested using the Chi-square test . Pairwise multiple comparisons between the stick types were performed using the Chi-square test with Bonferroni correction (α = 0.05/6 = 0.0083). For each test, the expected frequencies in each stick type were calculated as expected = total number of registered ants/number of stick types.S. rotundifolium is noticeably structured with rather uniform, straight cuticular folds  running parallel along the longitudinal stem axis  epicuticular wax projections  coverage of flat, often interconnected epicuticular wax projections (membranous platelets) in the regions between the stomata  are presented in 2 = 129.5084, d.f. = 3, p < 0.0001). Most preferable samples were intact sticks that differed significantly from all other (modified) types of sticks , d.f. = 1). Moreover, the modified stick types differed significantly from each other , d.f. = 1). In S. rotundifolium studied here.Despite the world abundance of ants, very few plant species (ten so far) are described as ant-pollinated, and ants are regarded as undesirable flower visitors that are only capable of nectar thieving . MoreoveSmyrnium rotundifolium possesses several stem- and leaf-related macroscopic and micro/nanoscopic characteristics, such as clusters of microscopic cuticular folds decorated with nanoscopic epicuticular wax projections on the flower stems and the cuffs, formed by the upper leaves bearing either wax projections on the adaxial side or a combination of cuticular folds and wax projections on the abaxial side. In our experiments, in order to evaluate the effect of different features on the frequency of ant visits, we used different types of wooden sticks mimicking stems with different characteristics: intact sticks with a grooved surface imitating stems with grooves between the clusters of cuticular folds; painted sticks imitating stems with wax projections; sticks with transparent polyester cuffs mimicking upper leaves; and sticks with painted cuffs imitating upper leaves bearing wax projections.Camponotus schmitzi (Hymenoptera: Formicidae), living in symbiosis with the Bornean pitcher plant, Nepenthes bicalcarata (Nepenthaceae), that it can swim and dive in the pitcher’s fluid to forage for food, but compared to running, the swimming involved lower stepping frequencies and larger phase delays within the legs of each tripod [L. niger and a majority of other ant species associated with the habitats where S. rotundifolium occurs, can overcome the water filled out pools in order to get access to the flower nectar.Our experimental results clearly demonstrated that both the macroscopic structures and the micro/nanoscopic surface coverages significantly reduced the visiting frequency of ants. In the first case, the upper leaves, completely wrapping the stems and making the cuffs, represent a physical barrier where ants have to overcome three transitions: (1) from the vertical stem to the adaxial side of the cuff (ceiling situation) ,33; (2) h tripod . Even thAdditionally, our experiments see b showed L. niger ants that was performed with five plant species having different surface structures on their stems, Lilium lancifolium flower stems covered with both cuticular folds and long soft trichomes showed a rather high number of ant visits [As for the effect of the cuticular folds, we did not mimic these microscopic surface structures in our experimental samples. In the literature, it has been hypothesized that the folds support the attachment and locomotion of pollinators on flowers ,36, but t visits . We suggRhagoletis indifferens fly (Diptera: Tephritidae) [Nezara viridula (Heteroptera: Pentatomidae) due to its distinct microrough surface topology and, to a lesser extent, due to the contaminating effect on the insect adhesive organs [Coccinella septempunctata and Harmonia axyridis beetles (both Coleoptera: Coccinellidae) on nanoporous substrates [The wax projections were simulated by calcium carbonate crystals in our experimental samples (painted sticks and painted cuffs). Hydrated lime is one of the first minerals used in “ancient particle film technology” , which aritidae) . Hydrateritidae) ,46,47. Oe organs . Moreovee organs  may contbstrates ,49.L. niger ants and the wax-bearing stems of Anethum graveolens, Dahlia pinnata, Tagetes patula and Tulipa gesneriana showed that ants avoided these stems but were still able to walk on such antiadhesive vertical substrates when they had no other choice [Both stick sample types bearing the calcium carbonate coverage (painted sticks and painted cuffs) showed significantly lower visiting frequencies of ants compared to the corresponding untreated samples . These data are in line with the results of numerous previous experimental studies performed with many insect and plant species (reviewed in ), showinr choice ,22. It wThus, in contrast to the previous experimental studies on the greasy pole syndrome that were performed either with plants or plant samples ,21,22, wOur data show significant differences in ants’ visiting frequencies among the different types of stem-mimicking samples. The results clearly demonstrate that micro/nanoscopic surface structures and macroscopic physical barriers, especially if combined, have a negative impact on the attractiveness of the flower stems to ants. This study provides further evidence for the hypothesis that having a diversity of plant stems in the field, generalist ants prefer substrates where their locomotion is less hindered by obstacles or surface slipperiness .