Emotional stimuli modulate activity in brain areas related to attention, perception, and movement. Similar increases in neural activity have been detected in the spinal cord, suggesting that this understudied component of the central nervous system is an important part of our emotional responses. To date, previous studies of emotion-dependent spinal cord activity have utilized long presentations of complex emotional scenes. The current study differs from this research by (1) examining whether emotional faces will lead to enhanced spinal cord activity and (2) testing whether these stimuli require conscious perception to influence neural responses. Fifteen healthy undergraduate participants completed six spinal functional magnetic resonance imaging (fMRI) runs in which three one-minute blocks of fearful, angry, or neutral faces were interleaved with 40-s rest periods. In half of the runs, the faces were clearly visible while in the other half, the faces were displayed for only 17 ms. Spinal fMRI consisted of half-Fourier acquisition single-shot turbo spin-echo (HASTE) sequences targeting the cervical spinal cord. The results indicated that consciously perceived faces expressing anger elicited significantly more activity than fearful or neutral faces in ventral (motoric) regions of the cervical spinal cord. When stimuli were presented below the threshold of conscious awareness, neutral faces elicited significantly more activity than angry or fearful faces. Together, these data suggest that the emotional modulation of spinal cord activity is most impactful when the stimuli are consciously perceived and imply a potential threat toward the observer. Emotional responses are sensorimotor in nature and serve to enhance the likelihood that an individual will successfully detect and respond to a specific stimulus ,2. The iRecent research has demonstrated that this emo-motoric system extends to both the cervical ,16 and tTo date, all of the spinal fMRI studies of emotional responses to visual stimuli have utilized complex emotional scenes such as those found in the International Affective Picture System . HoweverAlthough emotional faces do not depict movement, such stimuli are still likely to elicit motoric responses in an observer. The emotion conveyed by faces often influences whether an observer will approach or withdraw from that individual e.g., ,22). Con. Con22])An additional uncertainty related to the emotional modulation of spinal cord activity is whether the emotional stimuli must be consciously perceived in order to have an effect. Neuroimaging studies of the brain have found that “unconsciously perceived” stimuli can influence neural activity. Indeed, several studies have reported amygdalar responses to unconsciously perceived fearful faces  with no history of neurological or psychiatric illness participated in the study. Ethics approval was obtained from the University of Manitoba Bannatyne Human Research Ethics Board (project identification code HS18235 (B2014:077); approval received July 8, 2014) and the University of Winnipeg Human Research Ethics Board . All participants provided written informed consent prior to participation in the study. Participants underwent magnetic resonance safety screening at the Winnipeg Regional Health Authority Satellite MRI clinic prior to scanning to confirm they could be safely scanned. Patients were ineligible if they had irremovable metal in their body, were taking antidepressant or antianxiety medication, or were pregnant. Patients were recruited via an Introductory Psychology course and received $50 CAD compensation. Participants were required to have normal or corrected-to-normal vision.Emotional and neutral pictures used for the current experiment consisted of 60 images selected from the Karolinska Database of Emotional Faces . Three dThe mask was created in MS Paint by using a neutral face from the Karolinska Database of Emotional Faces that was not displayed as a stimulus in the study and applying the mosaic and swirl distortion buttons; this process allowed us to control for color and overall shape while making the stimulus unrecognizable as a face.Participants completed six different runs during the scanning session; the order of the runs was counterbalanced across participants. Each run was 5 min and 40 s in duration and consisted of three one-minute blocks of stimuli interleaved by 40-s rest blocks featuring a fixation cross. Within each one-minute block, stimuli were presented every three seconds; thus, each block within each fMRI run included 20 unique face images. In the conscious perception trials, an emotional face was shown for 1000 ms, followed by a mask for 1000 ms, and a fixation cross (“+”) for 1000 ms see . In the Spinal cord images were acquired on a 3-Tesla whole-body Siemens scanner . Images were acquired using a single-shot fast spin-echo scanning sequence with partial Fourier sampling (HASTE) with the following parameters: TE = 78 ms, TR = 750 ms per slice, FOV = 280 × 210, base resolution = 192 × 192. As this sequence produces images with contrast and signal sufficient for localization of functional activity, no separate structural scan was needed for the overlay of functional data. Nine 2 mm thick contiguous slices were centered rostrocaudally on the C5 vertebra and spanned the cervical spinal cord segments to the corpus callosum. Spatial saturation pulses were applied to eliminate signal from surrounding areas to avoid aliasing, and to reduce motion artifacts arising from regions anterior to the spinal cord.Cervical spinal cord fMRI data was analyzed with the use of a custom-written Matlab script  used in p = 0.0056 , contrast coefficients of −1, 1) [Individual level data were analyzed with a General Linear Model (GLM) for each data set to compare the stimuli blocks to the rest periods. Basis functions  and noise confounds  are used to model inherent physiological noise in the data. Analyzed individual results were grouped by condition and different patterns across conditions were compared by running contrasting conditions through a second-level, random-effects analysis. Mean voxel-wise β-values from the individual-level GLMs were averaged and divided by the standard error of the mean to calculate t-statistics between conditions using paired contrasts  ,38. UsinNine contrasts were performed on the data from this study. Each analysis consisted of a Bonferroni-corrected paired contrast . In order to increase clarity, the nine different analyses will be organized into three subsections consisting of (1) a comparison of conscious vs. unconscious perception of the same emotion, (2) a comparison of consciously perceived faces, and (3) a comparison of unconsciously perceived faces.The list of active voxels for the three conscious vs. unconscious contrasts are found in A paired contrast  was also performed on the anger-unconscious and anger-conscious runs. This contrast yielded 54 significant voxels, all of which were associated with conscious perception of angry faces. The majority of these voxels appeared in the left ventral regions of the cord, with 27 voxels located in segment C6, and additional activity noted in segments C3 and C5. Additional ventral activity was observed in the medial and right regions of segment C7. No significant voxels were found within the spinal cord for the anger-unconscious condition.The paired contrast  of the fear-unconscious and fear-conscious runs resulted in surprisingly little activity. In total, only 17 significant voxels were detected. Of these, nine indicated increased activity in the fear-unconscious condition relative to the fear-conscious condition and eight of the voxels indicated increased activity in the fear-conscious condition relative to the fear-unconscious condition. All eight of the voxels linked with the fear-conscious condition were located in the left dorsal or medial spinal cord; five of these voxels appeared in one cluster in C5, while another cluster had two voxels located in C2, and one voxel in C1. The nine voxels associated with greater activity for unconscious perceived fearful faces were located in ventral region of C1, C4, and C6.Overall, these comparisons of conscious and unconscious perception suggest that consciously perceived anger is more salient than unconsciously perceived anger, and unconsciously perceived neutral faces are more salient than consciously perceived neutral faces. In both of these contrasts, the overwhelming majority of active voxels were located in ventral spinal cord segments associated with action preparedness.The list of active voxels for the three contrasts related to the conscious perception of the face-expression stimuli are found in A paired contrast  was also performed on the neutral-conscious and fear-conscious runs. The results of this contrast ran counter to our hypotheses. In total, 39 significant voxels were found, all indicating increased activity in the neutral-conscious condition relative to the fear-conscious condition. Although most of the voxels were dorsomedial (C5), two of the three clusters contained ventral voxels; one cluster in C4, and the other small cluster spanning C6/C7.An additional planned paired contrast  was performed in order to test whether the two different negative emotions—anger and fear—elicited different patterns of spinal cord activity see . This anTaken together, these contrasts provide clear evidence that consciously perceived angry faces lead to large motoric responses in the cervical spinal cord. These data suggest that perceived threat, and not negative emotions in general, lead to preparatory motoric activity.The list of active voxels for the three contrasts related to the unconscious perception of the face-expression stimuli are found in The paired contrast  of the neutral-unconscious and fear-unconscious runs yielded 86 significant voxels all indicating increased activity in the neutral-unconscious condition relative to the fear-unconscious condition see . Indeed,Finally, a paired contrast  was performed on the anger-unconscious and fear-unconscious runs. This analysis yielded a single significant cluster (four voxels) indicating increased activity in the anger-unconscious condition relative to the fear-unconscious condition. This cluster spanned segments C3 and C4 and was located medially, on the right side.Taken together, the results of the unconscious perception runs suggest that neutral faces elicit greater motoric responses than fearful or anger faces when they are presented for very brief durations. Potential reasons for this counterintuitive result are discussed below.toward the observer. This effect is magnified when the gaze of the faces is directed forward [The results of the current study suggest that emo-motoric responses are strongest when stimuli are clearly visible and depict a potential threat to the observer. Consciously perceived angry faces elicited robust activity in ventral, motoric regions of the cervical spinal cord, particularly in segments related to movement of the upper limbs and hands. Importantly, this response was not simply a reaction to viewing negative emotions in general. In contrast with consciously perceived fearful faces, angry faces elicited significant activity in 253 ventral voxels, while fearful faces did not lead to greater activity (relative to angry faces) in a single ventral voxel. The primary difference between angry and fearful faces is the target of the potential threat . A face  forward ,40,41, aThe motor responses to threatening faces is consistent with previous research using different methods of measuring neural activity. For example, TMS research has shown that participants produced the greatest motor-evoked potential in response to viewing angry body language compared to fearful or neutral body language  (see alsOverall, fearful faces elicited surprisingly little activity in the cervical spinal cord. Indeed, consciously perceived fearful faces elicited much less activity than either consciously perceived angry or neutral faces. This result was surprising given that earlier spinal fMRI found pronounced activity in ventral/motoric neurons in segments C2–C5 when participants passively viewed emotionally negative images . A key dIt is also possible that the different brain areas involved with perceiving emotional scenes and emotional faces ,46 couldWeak responses to fear-related stimuli were also found in the analysis of the unconscious perception fMRI runs. This result was surprising given that a meta-analysis of amygdalar responses noted that the right amygdala was particularly sensitive to fearful stimuli presented below the threshold for conscious awareness . The smaAn additional potential explanation for the relatively weak responses to the unconscious-perception stimuli was that the stimuli were presented too quickly to be perceived, even at an unconscious level. A recent examination of emotional priming effects does suggest that presentation durations can influence the degree to which emotions influence visual perception . Not surAn additional question raised by the current research relates to the large response elicited by unconsciously perceived neutral faces relative to angry and fearful faces. There are two, perhaps complementary, explanations for these effects. First, it is possible that the neutral faces appeared somewhat threatening at rapid presentation durations. There is some evidence in the face perception literature suggesting that the ambiguity of neutral faces does make them appear mildly negative to some individuals ,53. ThisIt is important to note that the current research is only an initial step in our attempt to understand how consciously and unconsciously perceived faces influence spinal cord activity. Indeed, this research is not without its limitation. Paramount among these is its reliance on a blocked design used in the current study, the shortcomings of which were noted above. Our investigations would also have been improved with the acquisition of physiological data such as skin conductance responses or measures of cardiovascular changes . Future In conclusion, the current results provide an interesting first step in our understanding of spinal cord responses to facial expressions of emotions. Future studies using fMRI of the brain and spinal cord, more varied presentation durations, and perhaps dynamic facial stimuli , would h


Obturator neuralgia following mid-urethral sling is rare and most commonly associated with transobturator tapes . Prior rA 53-year-old woman had been referred to Urogynecology with right groin pain following TVT insertion 18 months earlier. She had had a previous diagnosis of fibromyalgia. She reported sharp right-sided groin pain, starting immediately on waking post-operatively. The pain radiated down her medial thigh and was exacerbated by walking. She was initially managed locally by orthopaedic and pain clinics, with neuropathic pain medications, CT-guided steroid injection to the obturator nerve and psychology input. MRI failed to show scarring in a location that might suggest tape misplacement. Following tertiary centre referral for unsuccessful conservative management of persistent pain (with no improvement in stress incontinence), her case was discussed at our multi-disciplinary team meeting and the patient offered laparoscopic TVT removal. Following dissection and division of the vaginal portion of the tape, the left intra-abdominal arm was found and removed; the right arm was not easily identified. Traction on the proximal portion of the mesh revealed that it passed through the internal obturator muscle, attached to the obturator nerve posteriorly and ended close to the external iliac vessels Fig.  with guiDuring retropubic mid-urethral sling insertion, care should be taken not to advance the mesh laterally. In patients suffering from post-operative obturator neuralgia, malpositioning of the tape should be considered, although it is challenging to diagnose pre-operatively.Supplementary materialVideo demonstrating complete laparoscopic removal of retropubic midurethral tape (TVT) from the obturator nerve. (MP4 419059 kb)


In addition, predicted genes were also enriched for ASD co-occurring conditions, including Attention Deficit Hyperactivity Disorder (ADHD). We also developed a KNIME workflow with the proposed methodology which allows users to configure and execute it without requiring machine learning and programming skills. Machine learning is an effective and reliable technique to decipher ASD mechanism by identifying novel disease genes, but this study further demonstrated that their performance can be improved by incorporating a quantitative measure of gene functional similarities. Source code and the workflow of the proposed methodology are available at https://github.com/Muh-Asif/ASD-genes-prediction.Identifying disease genes from a vast amount of genetic data is one of the most challenging tasks in the post-genomic era. Also, complex diseases present highly heterogeneous genotype, which difficult biological marker identification. Machine learning methods are widely used to identify these markers, but their performance is highly dependent upon the size and quality of available data. In this study, we demonstrated that machine learning classifiers trained on gene functional similarities, using Gene Ontology (GO), can improve the identification of genes involved in complex diseases. For this purpose, we developed a supervised machine learning methodology to predict complex disease genes. The proposed pipeline was assessed using Autism Spectrum Disorder (ASD) candidate genes. A quantitative measure of gene functional similarities was obtained by employing different semantic similarity measures. To infer the hidden functional similarities between ASD genes, various types of machine learning classifiers were built on quantitative semantic similarity matrices of ASD and non-ASD genes. The classifiers trained and tested on ASD and non-ASD gene functional similarities outperformed previously reported ASD classifiers. For example, a Random Forest (RF) classifier achieved an AUC of 0. 80 for predicting new ASD genes, which was higher than the reported classifier (0.73). Additionally, this classifier was able to predict 73 novel ASD candidate genes that were enriched for core ASD phenotypes, such as  Complex diseases with a strong genetic influence, such as Autism Spectrum Disorder (ASD), often have multiple etiologies with the involvement of possibly hundreds of different genes. Recent advances in genetic technologies have led to more efficient acquisition of genetic data. For example, the many large-scale genetic studies for ASD have identified hundreds of candidate disease ,2. Howevhttp://www.geneontology.org/) ) belong to the positive class and 74 (6.5% of negative instances [non-disease genes]) were negatives. This small percentage of positive instances with missing similarities will not have a significant effect on classifier performance.https://www.knime.com/). KNIME is an open source framework implementing several machine learning algorithms and data analysis utilities. The developed automated KNIME workflow incorporates all the above-discussed machine learning and semantic similarity measures to predict disease genes.To make the designed methodology accessible to researchers lacking extensive machine learning and programming knowledge, we developed an easy to use workflow. The workflow was developed using the KNIME framework (https://gene.sfari.org/), accessed on March 2018. The SFARI gene database is a catalogue of ASD relevant genes that have been reported by previous studies. In the SFARI database, genes are scored into seven different categories with respect to the strength of the available evidence. Genes with strongest and reproducible evidence are assigned to category 1 and genes with certain reproducibility limitations are placed in category 2. Category 3 and 4 contains genes with evidence from small studies of ASD candidate genes, while genes belonging to category 5 have indirect evidence of association. Category 6 genes are not associated with ASD. The SFARI gene database also contains syndromic genes that cause genetic pathologies presenting with ASD symptoms. Syndromic genes are placed in a separate syndromic category. Genes from category 1, 2, 3 and 4 (N = 588) were selected for the analysis. All genes classified as syndromic but are not in these categories were excluded. Besides ASD association, syndromic genes are also associated with diverse phenotypes and may disrupt biological processes unrelated to ASD. SFARI genes of category 1 and 2 were designated as High confidence Disease (HD) genes (N = 82), while genes from 3 and 4 SFARI categories were considered as Low confidence Disease (LD) genes (N = 506)  gene database (N = 990) (N = 506) . Non-menRF, NB, linear-SVM, radial-SVM based classifiers were generated on each semantic similarity matrix . The classifiers were divided into two different categories depending upon validation strategy and ASD genes classes (HD and LD)First, classifiers were trained and tested on HD and non-mental genes and were evaluated using stratified five-fold cross-validation. There were less HD ASD genes than non-mental genes. Therefore, to control class imbalance, the majority class  was undersampled. Secondly, functional similarities of HD + LD and non-mental genes were calculated to design various classifiers. The performance of these classifiers was assessed using two different assessment approaches, namely stratified five-fold cross-validation and held-out restricted five-fold cross-validation.de novo CNVs play an important role in ASD pathogenesis and occur at higher rates in patients than in their siblings or controls [de novo CNVs (present in patients but not in their parents) frequently disrupt many genes, posing challenges for the identification of the disease among the many disrupted genes.Copy Number Variants (CNVs) are common genetic risk factors for many diseases, including ASD. Specially, controls . Mostly,de novo CNVs (N = 80) in ASD patients were obtained from Sander et al. [de novo CNVs in subjects that were diagnosed with ASD. Genes overlapping with training set and lacking GO annotations were excluded from analysis.ASD candidate gene predictions were made to further estimate the predictability of the built classifier. For this purpose, genes disrupted by rare r et al. . We usedIn this study, we evaluated the performance of machine learning methods in predicting the ASD candidate genes. For this purpose, functional similarities of ASD genes along with non-mental genes were calculated by applying semantic similarity measures. Resnik, Wang, and Rel measures were used to calculate functional similarities for HD ASD and non-mental genes. Four different machine learning methods  were trained on each semantic similarity matrix, resulting in total of twelve different classifiers for HD genes. Out of these classifiers, RF-based classifiers trained and tested on all semantic similarity matrices outperformed the other classifiers . RF clasClassifiers were also built using functional similarities of HD + LD and non-mental genes and were evaluated by stratified five-fold cross-validation. The performance of classifiers for each semantic similarity matrix of HD + LD genes and non-mental genes was lower than the HD genes based classifiers, except for linear, and radial SVM . RF clasA held-out restricted validation approach was adapted from Krishnan et al. to assess the performance of the proposed classification approach. For this purpose, classifiers were built using functional similarities of HD + LD genes and non-mental genes. However, during stratified five-fold cross-validation, evaluation was done using only HD ASD and non-mental genes. For each semantic similarity matrix, held-out restricted RF classifier outperformed HD and HD+LD classifiers . In parallel with previously built classifiers (HD and HD+LD), the performance of held-out restricted classifiers for all semantic similarity measures was comparable . DespiteThe reported semantic similar matrices, Resnik, Rel and Wang were calculated using the Max combining criteria. Semantic similar matrices were also calculated by the Boot Mean Average (BMA) combining criteria. However, classifiers constructed using genes semantic scores with the BMA combining criteria showed lower performance than classifiers built on semantic scores of Max combining criteria .We also have developed a KNIME workflow of the designed methodology. The instantiation of the proposed methodology is described in de novo CNVs in patients, we used our best classifier, namely the RF classifier trained and tested on Resnik semantic similarity matrix, calculated using HD and non-mental genes. This RF-Resnik classifier was also evaluated by tuning its parameters, such as number of trees. RF classifier showed the highest performance when the number of trees was set to 500 . However, 99 HPO terms were found significantly enriched for 73 predicted genes  obtained higher performance than the Krishnan et al HD ASD genes based classifier, which used protein-protein interaction, gene expression, and gene regulatory information of genes to predict ASD candidate genes . KrishnaThe HD ASD genes based classifier also outperformed the RF classifiers using the semantic similarities of all known ASD (HD + LD) genes. The reduced performance of the classifier trained on HD + LD genes could be explained due to the large number of genes that have weak evidence of involvement in ASD, including, for example, 339 genes from SFARI category 4. Further studies are required to verify the associations of these genes with ASD. Moreover, our classifier trained on HD + LD ASD genes but evaluated on only HD ASD genes as held-out showed better performance than the held-out restricted weighted classifier of Krishnan et al.. However, evaluating classifier performance using only HD ASD genes may provide biased estimates. ASD presents a wide spectrum of clinical phenotype. The classifier tested on only HD ASD genes may lack robustness for genes that are responsible for a milder expression of ASD or for comorbidities, thus limiting the coverage of the predictive classifier.The strength of the reported semantic similarity scores is its independence from the features (genes) weighting scheme, defined by the ranking of genes according to available evidence. The standard criteria for ranking ASD genes by available reference is not yet completely defined , and, thThe improved performance of the classifier with semantic similarities further confirmed the importance of GO annotations in predicting disease genes. GO provides a consistent and deeper level of biological information than the protein-protein interactions or genes expression profiles. Functional information from GO structure can overcome the shortcomings of protein-protein interactions and expression profiles because GO annotations are less dependent on context. Additionally, our study further confirmed that machine learning methods can be used to predict disease genes and their performance can be improved by adding more data with different domain information.One limitation of this approach is the full dependence on the available annotation resources. Genes lacking GO annotations are filtered in the analysis. But this may improve in future because the number of GO terms and annotations are continuously increasing with time.We also provided a downloadable and easy to use workflow of the designed methodology. The designed workflow permits the user to test more than one machine learning and functional similarity methods. The workflow allows domain-specific experts to replicate the reported methodology to identify disease-causing genes and use their knowledge to further improve the predictions by tuning the parameters according to their need. The developed workflow includes all necessary tools for disease gene prediction and provides an opportunity for researchers to analyze their own private data without uploading it to external websites, thus preventing any privacy issues.histone modification pathway. This was consistent with previously published studies, reporting histone genes involvement in ASD [Enrichment analysis revealed the enrichment of ASD predicted genes in t in ASD . Only onAutism and obsessive-compulsive behavior phenotypes, further confirming the feasibility of the classifier in predicting new ASD genes. In addition, five genes were also associated with the attention deficit hyperactivity disorder HPO term. Attention deficit hyperactivity is one of most the common ASD comorbidity. A large percentage of ASD children also develop attention deficit hyperactivity disorder symptoms [ASD core symptoms are defined by deficits in social interaction and communication, and repetitive behavior. However, these core symptoms manifest with a wide range of phenotype, indicating ASD phenotypic heterogeneity. Functional enrichment analysis of ASD genes, predicted by the RF classifier also showed a wide range of phenotypes. ASD predicted genes were enriched in symptoms .Although Random Forest (RF) performed better than other methods, its performance was comparable with Naive Bayes (NB) algorithm. Therefore, we do not expect that RF will achieve the best performance for other complex disease genes as well. The Support Vector Machines (SVMs), both linear and nonlinear failed to make reasonable predictions, probably, they are sensitive to number of features and number of records. Also, SVMs perform preprocessing of data, which may not be feasible for this dataset.In this study, we reported that gene functional similarities, assessed using GO annotations can be used to identify new ASD genes. The classifier trained and tested using HD ASD genes outperformed all others and previously reported classifiers. The objective of this work was not to find the best semantic similarity measure for calculating functional similarities of genes. However, the performance of the classifier can be further improved by including more refined semantic similarity methods. Additionally, text mining techniques may also be employed to find the functionality of genes in literature that are lacking semantic scores . MoreoveIn summary, we validated our hypothesis and have shown that the performance of available state of the art methods for complex disease gene prediction can be improved by using only GO annotations. One novel aspect of presented manuscript was the comparison of stratified and held-out restricted cross-validation. The results indicated that classifiers built on GO annotations did not require held-out restricted classifiers. Approximately equivalent performance to ASD held-out restricted classifiers can be achieved by training machine learning methods, validated using five-fold cross-validation, on semantic similarity scores of only high confidence ASD disease genes. This work demonstrated that machine learning methods are a feasible approach to dissect the genetic heterogeneity of complex diseases such as ASD and to find novel disease genes. The results of this study can also further assist in designing genetic screening and lab experiments on ASD genetic risk factors.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.


The functional impact of cSVs can be studied at the RNA level using whole transcriptome sequencing . It represents a powerful tool for discovering, profiling, and quantifying changes of gene expression in the overall genomic context. However, bioinformatic analysis of transcriptomic data, especially in cases with cSVs, is a complex and challenging task, and the development of proper bioinformatic tools for transcriptome studies is necessary.Extensive genome rearrangements, known as chromothripsis, have been recently identified in several cancer types. Chromothripsis leads to complex structural variants (cSVs) causing aberrant gene expression and the formation of de novo fusion genes. Special attention was given to the filtering of false positives (FPs), which was achieved through consensus fusion calling with several fusion gene callers. We applied the workflow to the data obtained from ten patients with chronic lymphocytic leukemia (CLL) to describe the consequences of their cSVs in detail. The fusion genes identified by our pipeline were correlated with genomic break-points detected by genomic arrays.We designed a bioinformatic workflow for the analysis of total RNA-Seq data consisting of two separate parts (pipelines): The first pipeline incorporates a statistical solution for differential gene expression analysis in a biologically heterogeneous sample set. We utilized results from transcriptomic arrays which were carried out in parallel to increase the precision of the analysis. The second pipeline is used for the identification of de novo fusion gene detection from total RNA-Seq data. The results of the differential gene expression analysis were concordant with results obtained by transcriptomic arrays, which demonstrates the analytical capabilities of our method. We also showed that the consensus fusion gene detection approach was able to identify true positives (TPs) efficiently. Detected coordinates of fusion gene junctions were in concordance with genomic breakpoints assessed using genomic arrays.We set up a novel solution for differential gene expression analysis of individual samples and applying our methods to real clinical samples, we proved that our approach for total RNA-Seq data analysis generates results consistent with other genomic analytical techniques. The data obtained by our analyses provided clues for the study of the biological consequences of cSVs with far-reaching implications for clinical outcome and management of cancer patients. The bioinformatic workflow is also widely applicable for addressing other research questions in different contexts, for which transcriptomic data are generated.By Whole-genome sequencing of cancer samples has enabled the identification and detailed description of complex structural variants (cSVs) with chromothripsis being their prime example . ChromotIn contrast to the concept of gradual accumulation of chromosomal defects in the cancer genome, it has been assumed that chromothripsis arises in a single catastrophic event. The most widely accepted explanation of chromothripsis origin is based on aberrant mitosis, which is accompanied by physical separation of certain chromosomes in nuclear structures called micronuclei . AnotherNext-generation sequencing (NGS) serves as a powerful tool for describing any abnormalities occurring in the genome and has also been instrumental in discovering and describing cSVs. However, in many NGS experiments, consequent bioinformatic analysis remains challenging. Publicly available tools are often developed for a specific purpose with limitations in different experimental settings and do not take into account all genomic rearrangements that might be present in a sample. Moreover, when attempting to describe the impact of cSVs on cell phenotype, each case should be considered independently. The reason for such an approach is that, although there are a limited number of processes causing cSVs among individual cases, they affect different genomic loci with different impact. Thus, we developed a statistical approach for differential gene expression analysis from total RNA-Seq data, which is based on the comparison of individual cases within a tested dataset. Applying the method on a set of ten CLL samples, our strategy provided highly convincing gene candidates. In the next step, we focused on the identification of fusion genes and their stemming breakpoints from total RNA-Seq data. Due to the high rate of FP results of different methods, we developed a pipeline combining available analytic tools to maximize TP rate in dataset. Results were then cross-checked with data from genomic arrays in order to assess the sensitivity and specificity of our method.® Stranded Total RNA kit (Illumina) with Ribo-Zero ribosomal RNA depletion and sequenced using an Illumina HiSeq 2500 machine producing 125bp long pair-end reads. Sequencing read quality was evaluated in FastQC software. Adapter sequences were trimmed from raw reads using Trimmomatic software (® Human Transcriptome Arrays 2.0 (Thermo Fisher Scientific) to complement expression data from the RNA-Seq experiment. These data were then analyzed by the Transcriptome Analysis Console (Thermo Fisher Scientific) by comparing each consecutive sample to all other samples using a one-way ANOVA statistical test to identify a unique expression pattern in each sample. Identified fusion gene junctions and their respective sequencing reads were visualized in the Integrative Genomic Viewer  with cSVs that were previously detected using genomic CytoScan™ HD Arrays and analyzed with Chromosome Analysis Suite (Thermo Fisher Scientific). These cases were identified during the long-term clinical research at the University Hospital Brno and were classified as chromothripsis as they showed clustered copy number alterations on a limited number of chromosomes. Genomic breakpoint localization was extracted for all detected copy number variants and losses of heterozygosity. Total RNA-Seq libraries were prepared with TruSeqsoftware   approach that allows obtaining a gene expression profile of individual samples.Gene expression analysis from RNA-Seq data is based on counting reads covering gene regions (defined by reference relative GTF file) and statistical analysis of these read counts. In the first step, we used an htseq-count script , which e package . The funt-test was applied to assess the p.value to every single gene outlier in a given sample according to the gene expression in the rest of the samples. All gene candidates with significant p.value that can be specified manually (default 0.05) were considered as differentially expressed. Graphical representation of PComp algorithm is depicted in For the read count (expression) table resulting from RNA-Seq data processing steps, linear regression model with confidence bands containing expression values for all possible sample combinations  was applied to identify gene outliers in particular sample. Only genes constantly lying outside these bands in all possible sample combination were stored. In the next step, one sample limma (limma we compared gene expression in a single sample (group 1) with all other samples (group 2) in all possible combinations and correlated the results to the PComp output.RNA-Seq data were also subjected to a differential gene expression analysis using widely used and well-established algorithm limma  to gain Based on a literature search , four stFor efficient fusion gene detection, we developed an in-house meta-caller, which combines results from the selected tools into a consensus call. Each piece of software applies various metrics enabling classification of fusions to confidence subsets. In the first meta-caller step, detected fusions were filtered in individual callers as follows: for EricScript fusions with an Eric score (ES) of over 0.90, for JAFFA only fusions with the “HighConfidence” tag, and for FusionCatcher only high confidence fusions. In the consequent consensus call only fusions that passed at least two callers were kept which allowed increasing TP fusion rate and removal of FP fusions arising as specific artifacts of an individual caller algorithm . The whole fusion gene detection pipeline is schematically visualized in the Finally, to estimate TP and FP rates of the individual callers and the meta-caller, coordinates of fusions detected in RNA-Seq data were compared with the coordinates of genomic breakpoints detected by the genomic arrays. The interval of ± 100 kb around the breakpoints was applied in order to adjust to the array resolution and to the fact that the breakpoints can be located in introns, whereas fusions in RNA-Seq data appear in exon-exon boundaries. All potentially TP fusions identified by this approach were inspected visually in the array results.https://github.com/Hynst/WTS_cSVs_analysis), where the source codes are accessible for download. No installation is needed, as all dependencies  are installed automatically to the R environment.Algorithms and procedures of our novel solution were implemented in the R programming language. The meta-caller and the tool for differential expression are both freely available at GitHub  for each pair of samples. All genes lying outside the confidence bands were suggested as potentially differentially expressed candidates. We repeated this procedure for each sample pair combination and obtained nine sets of potential candidates per sample. Genes occurring in all nine sets were considered as differentially expressed for a given sample. By applying one sample t-test we assessed the differential expression of a given gene in a given sample according to the rest of the samples. We considered all gene candidates in particular sample with a p < 0.001 by one sample t-test to be differentially expressed. Using this approach, we found 15,200 differentially expressed genes in total  using transcriptomics arrays and extracted only annotated gene transcripts which resulted in 6,678 deregulated genes. We created an overlap between PComp and transcriptomic array results and found 1,808 significantly upregulated and 236 significantly downregulated gene candidates . We alsolimma. When we overlapped array data with limma results we found 1168 upregulated and 414 downregulated genes .Similarly, in RNA-Seq data we identified 14,803 deregulated genes using ed genes . We compapproach , where 2In RNA-Seq data, we pre-filtered results of the individual pieces of software in the first meta-caller step to create a fusion gene subset with high confidence. No explicit pre-filtering of lowly expressed fusions was done in order to allow for the capture of lowly expressed fusion genes . In the next step of the meta-caller, results obtained by ≥2 callers were combined into a consensus call. Following these steps, our pipeline was capable of identifying 40 fusion genes which were potentially TP with high confidence across the ten samples . FurtherConsidering candidates that were not supported by genomic arrays (21 of 40 features), potential fusions ZMYM5-PSPC1, HACL1-COLQ, MFSD7-ATP5I, and CYTIP-ERMN, occurring recurrently in six, three, three and two instances, respectively, were considered FP because they represented neighboring genes (read-through). Similarly, YWHAZ-ZNF706, LINCPINT-MKLN1, and NFATC3-PLA2G15 were also considered FP due to their adjacent localization in the genome, although not observed recurrently. Altogether, 17 of 21 fusions were considered FP. The remaining four fusions were not confirmed by the independent method; in all of them, at least one fusion partner appeared recurrently in the data, however, with a different partner. All of the four fusions could still represent TP resulting from balanced translocations or inversions that were not detectable by genomic arrays.To assess the ability of the meta-caller to increase TP rate, we inspected overlap between individual callers and genomic arrays . The metSeveral mechanisms of the influence of cSVs on cancer development have been suggested. NGS techniques provide an opportunity to unravel them by focusing on changes occurring at both the DNA and the RNA level. However, there still is a need for designing efficient pipelines and algorithms for consequent bioinformatic analyses. In this article, we introduce our approach for RNA-Seq data analysis in cases with cSVs. We tested the proposed workflow on a set of ten CLL patients with chromothripsis to validate the efficiency of our method.t-test, is the output of the analysis. PComp provides solid results comparable with transcriptomic array analysis and in our comparison performed better than limma tool, which is used widely for RNA-Seq data analysis. Although in our experimental setup we expected unique expression profiles for individual samples of our sample set, it is possible to specify the number of samples that can share expression similarities within the tool. We believe that the PComp approach is versatile and applicable to various RNA-Seq experimental designs and biological questions where a single sample expression profile is desired. Last but not least, the PComp tool is freely available on GitHub and easy to use by the potential users on their own data.Although cSVs reminiscent of chromothripsis likely share a common mechanism of origin across cSV cases, they appear in various genomic loci and, consequently, they lead to diverse expression profiles which makes it very difficult to select an appropriate biological group as a control. Unfortunately, the majority of conventional tools for differential gene expression  are deside novo proteins with aberrant structure and function. Aberrant protein products of fusion genes can influence important biological processes through direct or indirect regulation of expression of various genes which can eventually be reflected in the overall expression profile. Effective screening for such events in various diagnoses could help with identifying specific, potentially targetable disease markers . In our test dataset, the PComp tool outperformed well-established 10.7717/peerj.7071/supp-1Table S1The table depicts comparison of numbers of genes identified as differentially expressed using PComp approach for RNA-Seq data analysis and one-way ANOVA statistical test for transcriptomic array. The concordance was calculated as percentage of genes assigned concordantly between the methods.Click here for additional data file.10.7717/peerj.7071/supp-2Table S2limma analysis was applied to identify deregulated genes. Numbers in parentheses represent deregulated genes including also unannotated transcripts.For RNA-Seq data, Click here for additional data file.10.7717/peerj.7071/supp-3Table S3Overall 40 fusion genes in 8 out of 10 tested samples were identified using consensus meta-caller step. True/false positive gene fusions were assessed manually based on visual inspection of genomic array data .Click here for additional data file.10.7717/peerj.7071/supp-4Table S4Overview of 29 TP fusion genes identified by all used callers, i.e., EricScript (eric), FusionCatcher (FC) and JAFFA. Fusion genes identified by meta-caller had to be present in the results of ≥2 callers.Click here for additional data file.10.7717/peerj.7071/supp-5Supplemental Information 1The file contains the description of procedure used for RNA expression analysis using transcriptomic arrays.Click here for additional data file.10.7717/peerj.7071/supp-6Supplemental Information 2The file contains the description of procedure used for cytogenomic analysis using cytogenetic arrays.Click here for additional data file.


Human cytomegalovirus (HCMV) is a threat to immunologically weak patients. HCMV cannot yet be eliminated with a vaccine, despite recent advances.Sources of data are recently published research papers and reviews about HCMV treatments.Current antivirals target the UL54 DNA polymerase and are limited by nephrotoxicity and viral resistance. Promisingly, letermovir targets the HCMV terminase complex and has been recently approved by the FDA and EMA.Should we screen newborns for HCMV, and use antivirals to treat sensorineural hearing loss after congenital HCMV infection?Growing points are developing drugs against latently infected cells. In addition to small molecule inhibitors, a chemokine-based fusion toxin protein, F49A-FTP, has shown promise in killing both lytically and latently infected cells.We need to understand what immune responses are required to control HCMV, and how best to raise these immune responses with a vaccine. Betaherpesvirinae subfamily, with a double-stranded DNA genome of approximately 230 kb. The HCMV genome is complex and encodes functional proteins, microRNAs, long non-coding RNAs and small peptides.,Human cytomegalovirus (HCMV) is a large DNA virus of the Individuals with healthy immune responses usually show no symptoms after primary infection but on rare occasions can present symptoms similar to infectious mononucleosis.+ haematopoietic progenitor cells and their derivative CD14+ monocytes). As these cells exit the bone marrow and differentiate to macrophages and/or dendritic cells, virus reactivation is triggered.,,HCMV infection is usually asymptotic because a robust, healthy immune response controls viremia.HCMV primary infection, reinfection with a different circulating HCMV strain and reactivation from latent infection are a serious threat to immunocompromised, immunosuppressed and immunonaïve individuals. The potential for HCMV infection of a many different tissues causes a wide array of potential symptoms, but eventual organ failure may occur if HCMV antivirals are not used as treatment.in utero is common . As it is not clear whether screening will help the outcomes of asymptomatic children, it was not recommended.Congenital HCMV infections (cCMVs) are not always controlled by immunonaïve neonates. Infection ,,,cCMV symptoms include cytomegalic inclusion disease , intrauterine growth retardation, jaundice and microcephaly, with developmental delay, sensorineural hearing loss and significant subsequent mortality rates.Immunosuppression after organ transplant leaves patients at risk of HCMV disease.Solid organ transplant (SOT) recipients, who are seronegative (R−) are at the greatest risk of HCMV disease when receiving an organ from a cadaveric, seropositive donor (D+), likely due to both lytic and latent virus being carried in the donated tissue to a patient with no prior anti-HCMV immunity.+ stem cells, which expand and differentiate to reconstitute the immune system. This cellular differentiation can trigger HCMV reactivation and dissemination, as latently infected cells will be transferred if the donor is HCMV-positive.Like solid organ recipients, patients receiving allogeneic haematopoietic stem cell transplants  are also at risk of HCMV disease. Umbilical cord blood stem cells, or peripheral blood stem cells, for example from G-CSF-mobilised donors, are now the most common sources of stem cells for allo-HSCT and comprise multipotent CD34While treatment with HCMV antivirals, blood screening and donor/recipient matching for HCMV serostatus have decreased the incidence of HCMV disease, HCMV still remains a significant threat, especially at later times after transplant.For allo-HSCTs where the donor is seropositive, donor lymphocytes (which will contain HCMV-specific T cells) can also be transferred to help protect allo-HSCT recipients from HCMV infection. These lymphocytes could also play a role in controlling other opportunistic pathogens such as aspergillus.+ T cell clones is effective+ T cells means that CD8+ clones are short-lived.+ and CD8+ T cells.Ideally, the anti-HCMV benefits of T cell adoptive transfer could be gained, without the risk of GVHD, if a clinician could transfer only anti-HCMV donor T cell clones without transferring T cells which would cause the allo-recognition that leads to GVHD. The adoptive transfer of specific anti-HCMV CD8The current favoured drug treatment for active HCMV infection in the immunocompromised is intravenous ganciclovir (GCV) treatment. GCV is a nucleoside analogue that, when phosphorylated to form ganciclovir triphosphate, preferentially inhibits the viral DNA polymerase UL54.,In addition to GCV are the second-line drugs cidofovir (CDV) and foscarnet which both preferentially inhibit the viral DNA polymerase over cellular polymerases.Off-label leflunomide  has anti-HCMV activity as a result of its ability to inhibit tegument formation.The viral terminase complex is highly specific to herpesviruses; no cellular protein carrying out its function has been identified in mammalian cells, making this viral complex a good target for antivirals. A trimer of the proteins pUL51/pUL56/pUL89, the terminase complex binds the newly synthesised HCMV genome and the HCMV pro-capsid and uses ATPase activity to translocate the DNA into the capsid.in vitro, raising the possibility that combinations of these antivirals could be used to treat HCMV.Letermovir (Prevymis©), a novel anti-HCMV antiviral, is a quinazoline, targets pUL56 of the HCMV terminase complex and has an EC50 over 400-fold lower than GCV.www.accessdata.fda.gov, Reference ID 4179078).Letermovir, licensed by AiCuris and Merck, has recently been approved for the prophylactic treatment of HCMV disease in HSCT recipients in the USA, Canada and the European Union. This is after successful Phase III clinical trials (Maribavir (MBV), developed by ViroPharma, is another promising anti-HCMV compound, which is administered orally and targets the viral kinase UL97.Passive immunisation with HCMV immunoglobulin (CMVIG) is approved by the US FDA for prophylactic anti-HCMV treatment in conjunction with GCV in high-risk lung transplant recipients.In addition to CMVIG therapy, a fusion toxin protein (FTP) has been developed with anti-HCMV activity. This protein, named F49A-FTP, consists of the soluble portion of fractalkine (CX3CL1), a signalling chemokine which controls inflammation and cell chemotaxis, genetically fused to the pseudomonas exotoxin (PE) A protein.+ progenitor cells and CD14+ monocytes, the former of which comprise the major cell type present in HSCTs. Latently infected peripheral blood monocytes are also likely to be present in SOTs and, therefore, may also harbour virus which will not be targeted by VGCV treatment. Consequently, the reduction in latently infected cells in transplanted tissues could have far-reaching clinical benefits, and there has been significant recent interest in treatments against HCMV latency.HCMV latency is the maintenance of the viral genome in an infected cell which, depending on the latency model used, can be accompanied by the expression of a wide number of viral transcriptsAmong these potential treatments is vincristine, a tubulin inhibitor which is used to treat a number of cancers. Vincristine is transported out of cells by the drug transporter multidrug resistance-associated protein 1 (MRP-1). However, the viral gene UL138 which is expressed during HCMV latency, downregulates MRP-1 making latently infected cells susceptible to vincristine toxicity.,As discussed above, F49A-FTP binds the HCMV protein US28 and kills infected cells via a fused PE protein.+ cytotoxic T cells (CTLs) in healthy HCMV-seropositive carriers already recognise these viral IE antigens,In addition to directly virucidal therapeutics, two publications have proposed ‘kick and kill’ strategies to target the latent reservoir. This method to clear latently infected cells involves a treatment which forces the virus to at least partially reactivate from latency, resulting in expression of the viral major immediate early (IE) lytic proteins. These cells can then be detected and killed by the host immune system which is especially effective because a substantial proportion of circulating CD8An HCMV vaccine was assigned in the highest priority category by the Institute of Medicine and the second highest priority target after HIV by the Centers for Disease Control.,UL130, rendering it incapable of expressing the PC,,Analysis of the immune response to HCMV clearly indicates that a robust antibody and cellular response will be needed to confer protection.+ T cell responses, but showed differences in immunogenicity between chimeras.UL128 gene and so could not express WT PC.One solution to this problem is to recombine the high passage Towne laboratory strain with the lower passage, more wild type-like, Toledo virus to generate a chimera. This is still unable to establish systemic infection or latency but may be sufficiently similar to wild-type virus to provide protection against primary infection.in vitro, consist of viral tegument and glycoprotein-rich envelopes (including the immunodominant epitopes pp65 and gB), but lack viral capsids or viral DNA. These particles induce antibody and T cell responses, even without adjuvants and are, therefore, a potential vaccine candidate against HCMV.HCMV dense bodies, which are produced by HCMV-infected cells ,More recently, recombinant subunit vaccines have been developed, based on the two immunodominant epitopes of HCMV: phosphoprotein (pp)65, a protein present in the virus tegument, and glycoprotein B (gB), which is expressed on the virus surface and is required for viral entry into cells.+ and CD8+ T cell responses,The observation that HCMV can superinfect an already persistently infected hostHCMV is a significant pathogen, and we contend that the eradication of this virus would benefit humanity greatly. There is currently no vaccine against HCMV, but there are reasons to be hopeful: the relative success of the varicella-zoster virus (VZV) vaccine,


Percutaneous endoscopic gastrostomy (PEG) tube placement is one of the methods of providing enteral nutrition support and is often used in critically ill patients. There are several complications of PEG tube placement, including intussusception. Jejunojejunal and retrograde jejunoduodenogastric intussusception are well-documented complications of PEG tube placement. Here we describe the case of a 25-year-old female who was diagnosed with anterograde gastroduodenal intussusception with the PEG tube acting as a lead point. Our case is unique as, to the best of our knowledge, there are no documented cases of PEG tube-related anterograde gastroduodenal intussusception. The reported patient was found to have extensive gastric pneumatosis and portal venous gas concerning for acute ischemia. Such cases warrant immediate surgical intervention. However, in our case, the patient’s family opted for comfort care measures. Anterograde gastroduodenal intussusception is the rarest form of adult intussusception accounting for less than 10% of all intussusception cases in adults , MenetriPercutaneous endoscopic gastrostomy (PEG) tube is the modality of choice for providing enteral access to patients who require long-term enteral support. Although generally considered safe, PEG tube placement can be associated with many potential complications, including, but not limited to, intestinal trauma, hepato-splenic injury and gastro-colo-cutaneous fistula . MoreoveAlthough no formal consensus for the management of gastroduodenal intussusception does exist, it is widely accepted that removal of the lesion acting as a lead point and subsequent resection of the necrotic bowel are the mainstay of treatment . We hereA 25-year-old female was hospitalized with generalized abdominal pain, low-grade fever, rigors, lethargy, and vomiting. Her medical history was significant for Down syndrome and Moya Moya disease complicated by multiple strokes and intracranial hemorrhage requiring an external ventricular drain and subsequent PEG tube placement for enteral support one month prior to presentation.Vital signs on admission showed sinus tachycardia at 130 bpm, a temperature of 101 F and blood pressure of 110/65 mmHg. Abdominal examination revealed a distended, diffusely tender abdomen with evidence of bloody brownish exudate at the ostomy site. Pertinent laboratory studies included: elevated white blood cell count of 21 × 103 /μL , hemoglobin of 9 gm/dL- which was relatively decreased from a previous value of 12 gm/dL , metabolic acidosis with pH of 7.25  and elevated serum lactate of 7.27 mmol/L .The patient was transferred to the medical intensive care unit for suspected sepsis and was resuscitated with intravenous normal saline and broad-spectrum antibiotics. A few hours later, she started to have coffee ground emesis with a subsequent drop in her blood pressure.The abdominal plain radiograph showed a dilated stomach. This was followed up by an abdominal computed tomography (CT) scan with intravenous contrast demonstrating a dilated distal esophagus and stomach with extensive stomach wall pneumatosis and portal venous gas concerning for acute ischemia, the PEG tube was displaced into the proximal duodenum Figure -1b with The patient was diagnosed with iatrogenic anterograde gastroduodenal intussusception with the PEG tube acting as a lead point with complicating small bowel necrosis. Family members were counseled regarding the need for immediate surgical intervention. However, the patient’s family opted for comfort care measures. No surgical intervention was done and the patient was transferred under hospice care.Since endoscopic insertion of a gastrostomy tube was first introduced in 1980 by Gauderer et al. , with anPrevious case reports described retrograde jejunogastric intussusception causing small bowel obstruction due to PEG tubes, as the tube can migrate forward into the jejunum and act as the lead point . AlthougThere are a few case reports of PEG tube related intussusception. Pelosof et al.  reportedCT is a useful and reliable investigation in making a preoperative diagnosis, especially in giving anatomic details of the intussusceptum, intussuscipiens, and the adjacent organs . The chaSuccessful management of intussusception depends on early diagnosis, adequate resuscitation, and prompt reduction. Due to a significant risk of associated malignancy, radiologic decompression is not addressed preoperatively in adults . TherefoAlthough PEG tube-related mechanical complications are not uncommon, presentation in the form of gastroduodenal intussusception is exceptionally rare. This diagnosis should always be entertained in a patient with acute gastric outlet obstruction and unexplained clinical deterioration. Ensuring proper fixation of the PEG tube to prevent distal migration may help avoid this complication. The treatment in adults usually requires surgical intervention with resection of the involved bowel segment.


Collective cell migration is essential during physiological processes such as development or wound healing and in pathological conditions such as cancer dissemination. Cells migrating within multicellular tissues experiment different forces which play an intricate role during tissue formation, development and maintenance. How cells are able to respond to these forces depends largely on how they interact with the extracellular matrix. In this review, we focus on mechanics and mechanotransduction in collective migration. In particular, we discuss current knowledge on how cells integrate mechanical signals during collective migration and we highlight actomyosin contractility as a central hub coordinating mechanosensing and mechanotransduction responses. Current Opinion in Cell Biology 2017, 48:87–96Cell DynamicsThis review comes from a themed issue on Eugenia Piddini and Helen McNeillEdited by Issue and the EditorialFor a complete overview see the Available online 15th July 2017http://dx.doi.org/10.1016/j.ceb.2017.06.006http://creativecommons.org/licenses/by/4.0/).0955-0674/© 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license . CollecSome principles governing individual cell migration can be applied to collective migration, even if the regulation is far more complex. Individual migration is tightly coordinated and involves actin polymerization which drives the formation of protrusive membrane structures such as actin-rich protrusions, pseudopodia, invadopodia and blebs. F-actin polymers serve as scaffold for myosin II motors and a prerequisite for actomyosin contractile activity. Activation of Rho-associated protein kinase (ROCK) downstream of Rho GTPase (Ras homolog family member A) results in activating phosphorylation of the regulatory light chain of myosin II (MLC2)  and inacOn the other hand, directional polarity involving a leading edge at the front and a lagging edge at the back is needed for efficient migration. Protrusion and adhesion of the leading edge and retraction of the rear edge drive movement in the direction of locomotion . DiffereIn contrast, during collective migration cells migrate as cohesive groups involving direct cell-cell contacts, as seen in epithelial cell sheets; or as multicellular streams with transient cell-cell contacts, as observed during neural crest cell migration , 10, 11.During collective migration multiple cells migrate in the same direction at a similar speed behaving as one co-ordinated unit , 2, 14. in vivo regulation of collective cell migration and other cell re-arrangements, see the accompanying Review from R Fernandez-Gonzalez.Mechanosensing and mechanotransduction are the processes by which cells sense changes in the physical environment and translate those mechanical stimuli into biochemical signals  Figure , Table 1Establishment of cell adhesions and ECM imposed strains promote cytoskeletal re-arrangements, leading to signalling cascade activation and gene expression changes , 28, 29.Most of the migratory surfaces including collagens, laminins and fibronectin can engage cellular integrins . Integride novo leader cell development to the lateral margins [Cadherin-mediated adhesions exhibit an antagonistic relationship with integrin-based adhesions and offer polarisation and directional cues during collective motility , 50, 51. margins , 56.Cadherins at the mechanosensitive adherens junctions are crucial for maintaining the integrity of migrating cellular sheets by interacting with and controlling the actomyosin network via catenins  , 57••. TIntracellular pulling forces of the leading cells result in the re-localisation of the tumour-suppressor protein merlin from cell-cell contacts to the cytoplasm, leading to polarised Rac1 activation and lamellipodium formation . InterceDuring collective migration, cytoskeletal remodelling is sustained by changes in transcriptional programs. Maintenance of leader cell identity is dynamically regulated via Notch1-Dll4 lateral inhibition. Mechanical stress in a migrating epithelium inhibits Dll4 expression and leader cell formation , while RTherefore tight regulation of adhesion molecules, actomyosin activity and specific transcriptional programs in leader cells are crucial for efficient collective migration.Transmission of the large contractile forces generated by the leader cells drags the follower cells, establishing a tissue-scale coherent force profile and setting the peripheral actin cable under tension a. MyosinAt the sub-cellular level, follower cells are connected to the leader cells via polarised VE-cadherin-rich membrane protrusions or ‘cadherin fingers’. These extend from the rear of leader cells and are engulfed by the front of follower cells ••. RhoA Optimal levels of actomyosin contractility at cell-cell junctions in collectively invading cancer cells can be regulated by collagen-activated tyrosine kinase receptor DDR1 . RhoE localised to cell-cell contacts by the DDR1–Par3/Par6 complex antagonizes excessive ROCK-driven actomyosin contractility and maintains collective organization  Figure c. DDR1 hActomyosin-mediated mechanical organization at the individual cell level will identify leader vs followers within the collective migratory group. This relationship between tension, actomyosin contractility and Rho activation is an example of common mechanisms that apply to both collective as well as individual migrating cells , 66.Migrating cells display an exceptional ability to adapt to different environmental conditions , 30, 67.Transmission of cell traction forces to the ECM occurs via cell adhesions and results in alterations in ECM density, stiffness and architecture. Contraction of surrounding matrices results in generation of anisotropy in the pericellular matrix . MappingAt the multicellular cluster level, highly contractile cells exert detectable pushing, pulling and rotating forces onto the environment leading to vigorous matrix remodelling , 73, parThe number of cells in a collective is proportional to the active tensile modulus of an epithelial sheet •, which in vivo, which generates a continuous epidermal sheet over the dorsal surface of the Drosophila embryo [As key receptor molecules linking the extracellular matrix to the intracellular cytoskeleton, integrins play an essential role in transmitting tension in developing tissues, since they regulate force transmission. Integrin-containing adhesive structures facilitate basal cell-ECM adhesions that provide resistance to apical cell displacements during dorsal closure a embryo •. The amWhen cells are challenged with tubular geometries, contractile forces are responsible for collagen re-alignments localised to specific regions of the tissue . Cells gOn the other hand, tumour spheroids have been shown to induce integrin-independent radial orientation of the surrounding collagen fibre network up to a distance of five times their radius, correlating with local tumour cell migration behaviour , 79. ThiAn interesting observation is that cells migrating during wound healing responses exhibit different mechanical patterns to migratory multicellular cohorts. At early stages of the wound healing process, leading actin protrusions generate traction forces that point away from the wound, indicating that wound closure is initially driven by cell crawling . HoweverCollectively, these studies show how cell-dependent matrix remodelling offers directional cues to facilitate migration, thus generating a mechanical feedback loop.Efficiency of collective migration is influenced by changes in the physical properties of the extracellular environment such as confinement, stiffness and surface geometry  Figure a as wellIncreasing collagen density, independently of matrix stiffness, induces cells to switch from single-cell to collective invasion modes. Conversion to collective invasion includes gain of cell-to-cell junctions, supra-cellular polarisation and joint guidance along migration tracks , 84. NevSubstrate geometry offers directional cues to migrating cells. During epiboly, geometric distortion of embryos results in non-uniform migration and realignment of the anterior-posterior (AP) axis towards the new long axis of the embryo . Loss ofCyclic loading is the application of repeated or fluctuating stresses or strains. Migrating cells actively remodel and reorient their cytoskeleton in response to cyclic loading a,b. Overin vivo [As described in previous sections, cell-adhesion to the substrate determines the forces generated by the cytoskeleton to displace the cell . Morphogin vivo . To counin vivo . TherefoEfficient collective migration requires cells being able to exert pushing and pulling forces to remodel the ECM and at the same time, to counteract external forces, both from the ECM and neighbouring cells a,b,c. AcIn the last few years, collective cell migration has gained increasing interest and this has allowed great progress in a field that poses more challenges than studying individual cell migration. Complex mechanisms of signal integration at the supra-cellular level are crucial during developmental processes, wound healing and tumour dissemination. Deeper understanding of the spatiotemporal mechanical regulation of collective migration is needed at the single cell level. How mechanical signals impact the nuclear compartment differently in leader and follower cells remains poorly defined. In cells migrating individually, actomyosin contractility establishes strong feedbacks with transcription factors such as STAT3 , 98, SMA• of special interest•• of outstanding interestPapers of particular interest, published within the period of review, have been highlighted as:


The core of the Translocatome database is the manually curated data set of 213 human translocating proteins listing the source of their experimental validation, several details of their translocation mechanism, their local compartmentalized interactome, as well as their involvement in signalling pathways and disease development. In addition, using the well-established and widely used gradient boosting machine learning tool, XGBoost, Translocatome provides translocation probability values for 13 066 human proteins identifying 1133 and 3268 high- and low-confidence translocating proteins, respectively. The database has user-friendly search options with a UniProt autocomplete quick search and advanced search for proteins filtered by their localization, UniProt identifiers, translocation likelihood or data complexity. Download options of search results, manually curated and predicted translocating protein sets are available on its website. The update of the database is helped by its manual curation framework and connection to the previously published ComPPI compartmentalized protein–protein interaction database (http://comppi.linkgroup.hu). As shown by the application examples of merlin (NF2) and tumor protein 63 (TP63) Translocatome allows a better comprehension of protein translocation as a systems biology phenomenon and can be used as a discovery-tool in the protein translocation field.Here we present Translocatome, the first dedicated database of human translocating proteins (URL:  Subcellular localization of proteins is essential in spatial and temporal organisation of biological processes such as signalling pathways enabling their separation into organelles . TransloProtein translocation is a process which refers to the alteration of a given protein's subcellular localization. However, this phenomenon has no unified definition, and the word ‘translocation’ may also refer to gene translocation or RNA translocation at the ribosome. In this work we define protein translocation as a systems biology phenomenon, which refers to the regulated movement of a protein of a given post-translational state between subcellular compartments. Translocation changes the interaction partners and leads to altered function(s) of translocating proteins. There are certain processes  which were all collected based on related publications containing experimental evidence. Altogether Translocatome contains 13 066 human proteins, which were selected from the compartmentalized protein–protein interaction database  using the inclusion criterion that every protein needed to have at least one experimentally validated subcellular localization. By the application of the well-established gradient boosting machine learning tool, XGBoost , type of experimental evidence, affected signalling pathway(s) and pathological properties. The core of the Translocatome database is the 213 manually curated human translocating proteins ( XGBoost  we predihttp://translocatome.linkgroup.hu/coredata). With the manual curation process involving the judgement of 3 independent experts we aimed to collect detailed and experimentally validated information about every entry extracted from peer reviewed publications  and link(s) to peer-reviewed article(s) describing the experimental evidence of translocation,initial and target localizations of the translocating protein,interacting partners and biological functions ,translocation mechanism,the used detection method,protein structural information on translocation mechanism,disease group, exact disease involved and pathological role,signalling pathways affected.The core data of Translocatome is the extensively curated set of 213 human translocating proteins (see Core Data at the website: We used the UniProt naming convention  for prot(a) with experimentally proved diffuse, multi-compartmental distribution, (b) with exclusive single-compartment localization, (c) docked to DNA/RNA, (d) embedded in membranes or (e) attached to the cytoskeleton . The process was based on our previous work . DCS varies between 0 and 1, having increasing values if the protein has more curated data. The score is calculated and normalized after weighting all the available data, where those related to translocation have a higher weight . TES values were rescaled to the interval  by min–max normalization using Equation (The XGBoost machine learning method gave every protein of the Translocatome database a Translocation Evidence Score (TES) that is proportional with the translocation probability of the given protein. For each protein we computed TES using Equation 1)\docu\docu(1)\entclass1pt{minimaThe larger the TES value, the greater the probability of translocation. As a numerical example, suppose that ‘protein A’ has 20 neighbours (degree) in the human interactome and its UniProt record contains only two GO terms, ‘animal organ morphogenesis’, and ’cytoplasm’. Then the predicted translocation evidence score of ‘protein A’ is −0.497 + 2.675 + 1.353 = 3.531. The value is then normalized using Equation  1133 high-confidence translocating proteins having a TES value higher than 0.6167; (b) 3268 low-confidence translocating proteins having a TES value between 0.6167 and 0.4487, as well as (c) the residual 8665 proteins having a TES value lower than 0.4487, which were considered as non-translocating  213 manually curated translocating proteins, (ii) 160 physiologically translocating manually curated proteins (the positive training set), (iii) manually curated non-translocating proteins (the negative training set), (iv–vi) high-, low-confidence and non-translocating protein sets, as well as (vii) the whole protein set and (viii) its protein–protein interaction network. These sets of proteins can be downloaded in a comma separated .csv format. Besides these pre-defined sets users can also download the results of their search queries as a tabulator separated file . Examples and explanations of the output formats are available in As part of the user-friendly interface, various search functions were developed. We provide an easy to use quick search function (with UniProt AC autocompletion) which can be used to find protein families or a given protein. The advanced search option creates the possibility to search for more elaborate sets of proteins filtered by their localization, UniProt identifiers, Translocation Evidence Score or Data Complexity Score. The web interface provides eight pre-defined protein sets as download options covering https://rubyonrails.org) framework. The MCF website follows the hierarchical model-view-controller design pattern to ensure the separation of the data layer from the business logic and the user interface. The MCF stores all the data of the Translocatome and provides them to the front-end of the Translocatome website after expert review. To ease usability an end-user documentation is available as tutorials, detailed descriptions and location-specific tooltips in the HELP menu on the site (http://translocatome.linkgroup.hu/help). Further details of design and implementation of the database are summarized in To allow the development of the Translocatome database as a community effort a manual curation framework (MCF) was designed. MCF uses the same MongoDB database as the Translocatome site, with a user interface developed in the Ruby on Rails 4.2 ((A) were already included in the manually curated 213 translocating protein set ; (B) were previously shown to be translocating proteins but have not appeared in our Core Data of 213 proteins collected from keyword-based searches  have not been described as translocating proteins yet, but from the literature we can conclude that their translocation is probable (one protein: TP63); (D) there is no information in the literature about their translocation (one protein: PRKRA). Proteins of categories (C) and (D) are good candidates for further experimental studies verifying their translocation.The Translocatome database is the only current dedicated collection of human translocating proteins. With its Translocation Evidence Score (TES) for 13 066 proteins it helps the identification and experimental validation of novel translocating proteins. To demonstrate the prediction efficiency of Translocatome we assessed the first 40 proteins with the highest TES values. Table The best hit of the XGBoost algorithm, the PTEN protein is a part of the manually curated 213 translocating proteins. As its second best hit, the XGBoost algorithm correctly predicted NF2 (Merlin) as a translocating protein, since NF2 in its dephosphorylated form indeed translocates to the nucleus . NF2 is Out of the 25 proteins listed on Table With the above examples we demonstrated that the XGBoost machine learning algorithm  is able The existing MoonProt  and UniPIn summary, Translocatome offers a unique dataset of 213 specifically collected human translocating proteins listing the source of their experimental validation, several details of their translocation mechanism, local compartmentalized interactome as well as their involvement in signalling pathways and disease development. In addition, it provides translocation likelihood values (as Translocation Evidence Scores) for 13 066 human proteins identifying 1133 and 3268 high- and low-confidence translocating proteins, respectively. The assembly of the Translocatome database  and an advanced search to find sets of proteins filtered by their localization, UniProt identifiers, Translocation Evidence Score or Data Complexity Score. The web interface provides eight pre-defined protein sets as download options and a possibility to download the search results. End-user documentation is available as tutorials, detailed descriptions and location-specific tooltips in the HELP menu of the site.http://translocatome.linkgroup.hu. Translocatome is a community-annotation resource, which is helped by its manual curation framework (MCF). MCF allows the users to build in their own experimentally verified translocating proteins. Translocatome will be updated and upgraded annually for minimum 5 years. The Translocatome database is connected to our previously developed, compartmentalized protein–protein interaction database (ComPPI, Translocatome is available at  ComPPI, . Thus thWe plan to resolve current Translocatome limitations, such as extending the database to other species than humans. Future plans include the extension of positive and negative datasets and localization-based network visualization. Translocating RNAs play a key role in subcellular regulation as well, but their role is even more complex and mysterious. We plan to extend our database and add translocating RNAs, to fill out this gap. The improvement of the data not only means, that Translocatome will have more proteins or more detailed information. In this process the whole database will be updated meaning that the XGBoost machine learning will reappraise the data and provide more even accurate predictions based on the updated data.In conclusion, the Translocatome database introduced here provides the first dedicated collection of 213 translocating human proteins including their interaction partners in the different subcellular localizations. Importantly, Translocatome gives a Translocation Evidence Score to more than 13 thousand human proteins allowing the assessment of their translocation probability. All these features are accessible in a user-friendly manner. The Translocatome database allows a better comprehension of protein translocation as a systems biology phenomenon, and can be used as a discovery-tool of the field. Since translocating proteins become more and more important therapeutic targets ,7 Translhttp://translocatome.linkgroup.hu.The Translocatome database of human translocating proteins can be accessed freely at Supplementary DataClick here for additional data file.


Pigmented actinic keratosis is an uncommon variant of actinic keratosis that can mimic melanocytic lesions. A 54-year-old man who presented with a dark lesion on his nasal tip is described; biopsy of the lesion revealed a pigmented actinic keratosis that was treated with cryotherapy using liquid nitrogen. Pigmented actinic keratoses typically appear on sun-exposed areas of the skin as flat hyperpigmented lesions that grow in a centrifugal pattern. Dermoscopy reveals one or more pseudonetworks with hyperpigmented dots or globules. Histopathology shows atypical keratinocytes in the epidermal basal layer and increased melanin content in the epidermis and dermis. Treatment options include liquid nitrogen cryotherapy for solitary lesions and curettage, 5-fluorouracil, imiquimod, ingenol mebutate, photodynamic therapy, or superficial peels for extensive lesions. Pigmented actinic keratosis is an uncommon clinical variant of actinic keratosis -18. ThisA 54-year-old man presented for evaluation of a new dark lesion on his nose. The asymptomatic lesion had been present for more than a year and had progressively increased in size.Clinical examination of his face showed a 5 x 5-mm black patch on the nasal tip Figure . CompletMicroscopic examination of hematoxylin and eosin stained sections showed a proliferation of atypical keratinocytes in the lower layers of the epidermis with overlying parakeratosis Figure . There wImmunohistochemical stains were performed. MART-1 and MiTF did not stain the atypical cells. Therefore, an atypical melanocytic proliferation was excluded Figures , 4.Correlation of the history, clinical presentation, and pathologic findings established the diagnosis of a pigmented actinic keratosis. The residual lesion was treated with cryotherapy using liquid nitrogen. The lesion completely resolved after treatment; follow-up examinations demonstrate that it has not recurred.Actinic keratosis is an epithelial lesion characterized by atypical keratinocytes predominately restricted to the lower layers of the epidermis; some of these lesions have the potential to develop into cutaneous malignancies such as squamous cell carcinoma. Although most actinic keratoses present as erythematous scaly plaques, an uncommon clinical variant manifests as a pigmented lesion. In this setting, the diagnosis may not be suspected.Pigmented actinic keratosis was initially described by James et al. in 1978 .-13.9-13]Initially, S100 was used. More recently, newer markers have been incorporated such as melanoma antigen recognized by T cells 1 (MART-1), microphthalmia-associated transcription factor (MiTF), and Sry-related HMG-BOX gene 10 (SOX-10) . SimilarElectron microscopy of pigmented actinic keratosis demonstrates an increased level of melanosomes in the keratinocytes in the basal layer of the epidermis; these melanosomes are most prominently distributed within the cytoplasm of dendritic processes. Melanosomes appear as either single units or complexes; the melanosome complexes are usually membrane-bound and in varying stages of degradation. Langerhans’ cells and macrophages may also present with large numbers of melanosome complexes .The differential diagnosis of pigmented actinic keratosis includes lentigo maligna, lichen planus-like keratosis, and solar lentigo Table  7-8,16--16-18. SThe etiology of pigmented actinic keratosis is unclear; however, several theories have been proposed for its presentation. The number of melanocytes in the basal layer of the epidermis in pigmented actinic keratosis is the same as nonpigmented actinic keratosis; however, electron microscopy studies demonstrate enhanced melanosome formation in epithelial keratinocytes . It has Treatment options for pigmented actinic keratosis are the same as that for nonpigmented actinic keratosis. Lesions may be treated using cryotherapy with liquid nitrogen; this is usually an effective approach, particularly if the pigmented actinic keratosis is a solitary lesion. Topical therapy ― with either 5-fluorouracil, imiquimod, or ingenol ― curettage, photodynamic therapy, and superficial peels may be used when there are multiple lesions .Pigmented actinic keratosis is a variant of actinic keratosis that occurs less commonly. In contrast to presenting as an erythematous plaque, its appearance can mimic a pigmented lesion  or a keratinocytic lesion (lichen planus-like keratosis). Dermoscopy may be helpful in suggesting the correct diagnosis. However, dermoscopic features of a pigmented keratosis can overlap with those of the pigmented lesions in the differential diagnosis. Also, some pigmented actinic keratoses actually represent collision tumors consisting of a nonpigmented actinic keratosis and a primary melanocytic lesion. Therefore, microscopic examination of a lesional biopsy may be necessary to establish the diagnosis. Although the pathogenesis has not been established, it has been suggested that increased melanosome formation as well as the presence of nonpigmented actinic keratosis in collision tumors lead to its development, particularly in patients with darker skin types. The management of a pigmented actinic keratosis is the same as nonpigmented actinic keratosis. Liquid nitrogen cryotherapy should be considered for the treatment of a solitary lesion. Field treatment with 5-fluorouracil, curettage, imiquimod, ingenol mebutate, photodynamic therapy, or superficial peels may be appropriate when there are multiple lesions within the same area.


We report a rare case of a lung adenocarcinoma presenting with chylothorax and metastases to the common bile duct and the rectum. From the radiological and endoscopic appearance of the tumors, the main differential diagnoses were metastatic lung cancer to multiple rare extra-thoracic sites and multiple synchronous primary oncological malignancies. Pathological examination of the biopsies with positive immunohistochemical staining for thyroid transcription factor-1 (TTF-1) played an important role in confirming metastatic pulmonary adenocarcinoma. Lymph nodes, liver, adrenal glands, brain, bone and other parts of the lung and pleura are common metastatic sites of lung cancer. Although pleural effusion is a frequent presentation in lung cancer, chylothorax is seldom seen in primary lung malignancy in the absence of cardiothoracic surgery . MalignaA 78-year-old non-smoker Chinese female presented with a six-month duration of progressive breathlessness. This was associated with cough, poor appetite and weight loss over the last one month. She had reduced air entry on the right chest with stony dullness on percussion. Chest radiograph showed a right moderate effusion. Thoracocentesis drained milky fluid which was biochemically in keeping with chylothorax . The fluid had no malignant cells or pathogens. Blood biochemistry showed obstructive liver function . Computed tomography (CT) scan revealed a right lower lobe lung mass with a right pleural effusion  Figure . EpidermVery few extra-pulmonary lung cancer metastases to the gastrointestinal -5, biliaChylothorax occurs when there is a disruption of the thoracic duct or its tributaries, resulting in leakage of chyle into the pleural space. In the absence of traumatic thoracic ductal injury from lung resection surgery, occurrence of chylothorax in lung cancer is not common. In view of the size and location of the tumor in our patient, the possible cause may be direct invasion or extrinsic compression of the thoracic duct by the tumor . Other cDistant metastasis of lung cancer represents a late stage disease with poor prognosis reported in a case series of colonic metastasis . Our patImmunohistochemical staining plays an important role in identifying metastasis in uncommon sites. This has a strong impact on accurate staging of malignancy which will in turn, implicate prognostication and management.


Stevens-Johnson Syndrome (SJS) is an acute mucocutaneous eruption with blisters of the skin and haemorrhagic erosions of mucous membranes. This report describes air-leak syndrome and obstructive uropathy occurring simultaneously in a teenage patient affected by SJS.A 17-year-old Malay female with SJS suffered from bilateral pneumothoraces, pneumomediastinum, and obstructive uropathy as early complications of her disease. She required intubation, chest tube insertion, and bilateral ureteric stenting as part of her intensive care management. These extra-cutaneous complications of renal and pulmonary systems were likely secondary to widespread epithelial detachment.Despite paucity of cases in adult literature, post-renal causes for acute kidney injury must be considered in SJS, especially in the setting of gross haematuria. Bedside point-of-care ultrasonography may be a useful tool for excluding obstructive uropathy. Pneumothorax is a rare but documented complication of SJS in paediatric cases and, to a lesser extent, adult patients. Extra care should be exercised when caring for mechanically ventilated patients suffering from SJS. Stevens-Johnson Syndrome (SJS) is an acute mucocutaneous eruption with blisters of the skin and haemorrhagic erosions of mucous membranes. This report describes air-leak syndrome and obstructive uropathy occurring early in the disease course of a teenage patient affected by SJS. The importance is that it is the first report in the medical literature describing these two complications occurring simultaneously in an affected patient. We describe the events during our patient’s stay on the intensive care unit (ICU), provide a literature review of these rare complications, and derive clinically important learning points from our experience.A 17-year-old Malay female with no significant past medical history presented with rashes over the neck and trunk and swollen lips. She had been unwell for 2 days prior to hospital attendance with symptoms of fever, sore throat, and running nose and red itchy eyes. She had attended her family physician 1 day before presentation to hospital and had been prescribed paracetamol, dequalinium lozenges, loratidine/pseudoephrine nasal spray, and co-amoxiclav tablets, of which she had taken two doses.Inspection of the patient’s skin revealed scattered dusky, flaccid blisters demonstrating positive Nikolsky’s sign Fig. . These wThe patient was admitted to our ICU with tachycardia and tachypnoea, although blood pressure and peripheral oxygen saturation were within normal limits at the time of admission. The patient subsequently developed significant pulmonary and renal complications which are described below. A timeline of significant events and trend of renal function is outlined in Fig. Blood tests on admission showed acute kidney injury (creatinine 104 mmol/L). Our patient’s serum creatinine continued to worsen during admission despite adequate fluid replacement. Gross haematuria was noted from urinary catheter on the third day of admission. Urine analysis was negative for casts with 90% isomorphic red blood cells, suggesting urological origin of haematuria. On the fifth day of admission, her urine output dropped significantly. Bedside ultrasound revealed bilaterally enlarged collecting system, and subsequent CT-KUB confirmed bilateral hydronephrosis and mild hydro-ureters with the presence of dependent debris in pelvicalyceal system and ureters Fig. , right. Our patient had respiratory distress on admission, and nasoendoscopy revealed mild arytenoid and supraglottic swelling. Respiratory condition worsened on day 2 of admission; the patient became progressively more tachypnoeic with increasing secretion load and required supplemental oxygen. Due to work of breathing, she was initially trialled on non-invasive ventilation (NIV) which was soon switched to high-flow nasal cannula  in view of inability to clear secretions whilst on NIV. Twenty-four hours later, at the end of day 3 of admission, she developed sudden onset severe respiratory distress with desaturation and required intubation and mechanical ventilation. Clinical examination demonstrated extensive subcutaneous emphysema. Chest X-ray confirmed presence of right-sided pneumothorax, small left-sided pneumothorax, and pneumomediastinum Fig. , left. ASJS is an acute mucocutaneous eruption with blisters of the skin and haemorrhagic erosions of mucous membranes. The cause of SJS in this patient’s case remains unclear. Although case reports suggest that a single dose co-amoxiclav is sufficient for eruption , applicaThis case report describes a combination of acute renal failure and acute respiratory failure in a patient with otherwise relatively limited skin manifestations of SJS. Extensive literature search done independently by all the listed authors revealed only one other case with a similar presentation albeit detected only at autopsy; a Spanish case report from paediatric population showed renal and pulmonary epithelial sloughing on post-mortem examination . The unfIncidence of renal failure is high in SJS and is an independent predictor of mortality . In a reAlthough microscopic haematuria is reported in up to 23% of cases , frank hEpithelial detachment severe enough to result in eventual renal dysfunction from an obstructive cause is rare and has been described in only a very few case reports , 15, 16.Although respiratory failure has been documented in cohorts of patients with SJS , 18, airThe aetiology for air leak/pneumothorax in the setting of SJS is unclear. Patients in the previous case series , 18 demoA likely hypothesis for air leak is that mucosal debris causes obstructive airway pathology leading to air trapping and rupture of alveoli. Pneumomediastinum is then the consequence of released alveolar air dissecting through the pulmonary interstitium along the broncho-vascular sheaths toward the pulmonary hila, into the mediastinum . This hyRenal and respiratory involvement in SJS has been documented in SJS cohort studies; however, air leak and obstructive uropathy are rare complications due to systemic epithelial sloughing. Acute care physicians should be aware that significant organ involvement can occur despite relatively limited skin manifestations. Post-renal causes for acute kidney injury must be considered in Stevens-Johnson Syndrome, especially in the setting of gross haematuria and bedside point-of-care ultrasonography may be a useful tool for excluding obstructive uropathy. Pneumothorax is a rare but documented complication of SJS in paediatric cases and, to a lesser extent, adult patients. Extra care should be exercised when caring for mechanically ventilated patients.