Search

Background: In artificial intelligence for ultrasound-guided regional anaesthesia, accurate nerve identification is essential. The technology community typically favours objective metrics of pixel overlap on still-frame images, whereas clinical assessments often use subjective evaluation of cine loops by physician experts. No clinically acceptable threshold of pixel overlap has been defined for nerve segmentation. We investigated the relationship between these approaches and identify thresholds for objective pixel-based metrics when clinical evaluations identify high-quality nerve segmentation., Methods: cNerve™ is a deep learning segmentation tool on GE Healthcare's Venue™ ultrasound systems. It highlights nerves of the interscalene-supraclavicular-level brachial plexus, femoral, and popliteal-level sciatic block regions. Expert anaesthesiologists subjectively rated overall segmentation quality of cNerve™ on ultrasound cine loop sequences using a 1-5 Likert scale (1 = poor; 5 = excellent). Objective assessments of nerve segmentation, using the Intersection over Union and Dice similarity coefficient metrics, were applied to frames from sequences rated 5., Results: A total of 173 still image frames were analysed. The median Intersection over Union for nerves was 0.49, and the median Dice similarity coefficient was 0.65, indicating variable performance based on objective metrics, despite subjective clinical evaluations rating the artificial intelligence-generated nerve segmentation as excellent., Conclusions: Variable objective segmentation metric scores correspond to excellent performance on clinically oriented assessment and lack the context provided by subjective expert evaluations. Further work is needed to establish standardised evaluation criteria that incorporate both objective pixel-based and subjective clinical assessments. Collaboration between clinicians and technologists is needed to develop these evaluation methods for improved clinical applicability., Competing Interests: Declarations of interest BVD has received fees from GE Healthcare and is a consultant for GE Healthcare. OM, TG, and LM have received fees from GE Healthcare. JSB is an employee of GE Healthcare and was previously a Senior Clinical Advisor for Intelligent Ultrasound. He has acted as a consultant for AutonomUS and received speaker fees from the Belgian Association for Regional Anaesthesia., (Copyright © 2025 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Introduction: Regional anaesthesia provides important clinical benefits to patients but is underutilised. A barrier to widespread adoption may be the focus of regional anaesthesia research on novel techniques rather than evaluating and optimising existing approaches. Research priorities in regional anaesthesia identified by anaesthetists have been published, but the views of patients, carers and other healthcare professionals have not been considered previously. Therefore, we launched a multidisciplinary research priority setting partnership that aimed to establish key regional anaesthesia research priorities for the UK., Methods: Research suggestions from key stakeholders (defined by their interaction with regional anaesthesia) were gathered using an online survey. These suggestions were analysed to identify common themes and then combined to formulate indicative research questions. After an extensive literature review, unanswered and partially answered questions were prioritised via an interim online survey and then ranked as a top 10 list during a final live virtual multidisciplinary prioritisation workshop., Results: In total, 210 individuals completed the initial survey and suggested 518 research questions. Fifty-seven indicative questions were formed, of which three were considered fully answered after literature review and one not feasible. The interim online survey received 335 responses, which identified the 24 highest priority questions from the 53 presented. At the final live prioritisation workshop, through a nominal group process, we identified the top 10 regional anaesthesia research priorities. These aligned with three broad thematic areas: pain management (two questions); patient safety (six questions); and recovery from surgery (two questions)., Discussion: This initiative has resulted in a list of research questions prioritised by patients, carers and a multidisciplinary group of healthcare professionals that should be used to inform and support future regional anaesthesia research in the UK., (© 2024 Association of Anaesthetists.)

Objectives: Ultrasound-guided regional anesthesia (UGRA) relies on acquiring and interpreting an appropriate view of sonoanatomy. Artificial intelligence (AI) has the potential to aid this by applying a color overlay to key sonoanatomical structures.The primary aim was to determine whether an AI-generated color overlay was associated with a difference in participants' ability to identify an appropriate block view over a 2-month period after a standardized teaching session (as judged by a blinded assessor). Secondary outcomes included the ability to identify an appropriate block view (unblinded assessor), global rating score and participant confidence scores., Design: Randomized, partially blinded, prospective cross-over study., Setting: Simulation scans on healthy volunteers. Initial assessments on 29 November 2022 and 30 November 2022, with follow-up on 25 January 2023 - 27 January 2023., Participants: 57 junior anesthetists undertook initial assessments and 51 (89.47%) returned at 2 months., Intervention: Participants performed ultrasound scans for six peripheral nerve blocks, with AI assistance randomized to half of the blocks. Cross-over assignment was employed for 2 months., Main Outcome Measures: Blinded experts assessed whether the block view acquired was acceptable (yes/no). Unblinded experts also assessed this parameter and provided a global performance rating (0-100). Participants reported scan confidence (0-100)., Results: AI assistance was associated with a higher rate of appropriate block view acquisition in both blinded and unblinded assessments (p=0.02 and <0.01, respectively). Participant confidence and expert rating scores were superior throughout (all p<0.01)., Conclusions: Assistive AI was associated with superior ultrasound scanning performance 2 months after formal teaching. It may aid application of sonoanatomical knowledge and skills gained in teaching, to support delivery of UGRA beyond the immediate post-teaching period., Trial Registration Number: www.clinicaltrials.govNCT05583032., Competing Interests: JSB is a Senior Clinical Advisor for GE Healthcare (and previously Intelligent Ultrasound, receiving research funding and honoraria). MM was employed by Intelligent Ultrasound as a medical writer during this study. DBSL is a clinical advisor for Intelligent Ultrasound, receiving honoraria. NH is the President of Regional Anaesthesia UK. AJRM is the immediate Past-President of Regional Anaesthesia UK and has received honoraria from Intelligent Ultrasound and GE Healthcare. AP is a Past-President of Regional Anaesthesia UK, has received honoraria from GE Healthcare and has consulted for Pacira Biosciences. TA, MPS, AT and JW are board members of Regional Anaesthesia UK. JAN is a senior scientific advisor for Intelligent Ultrasound., (Copyright © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background and Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a growing public health problem. The secondary stage in MASLD is steatohepatitis (MASH), the co-existence of steatosis and inflammation, a leading cause of progression to fibrosis and mortality. MASH resolution alone improves survival. Currently, MASH diagnosis is via liver biopsy. This study sought to evaluate the accuracy of imaging-based tests for MASH diagnosis, which offer a non-invasive method of diagnosis., Methods: Eight academic literature databases were searched and references of previous systematic reviews and included papers were checked for additional papers. Liver biopsy was used for reference standard., Results: We report on 69 imaging-based studies. There were 31 studies on MRI, 27 on ultrasound, five on CT, 13 on transient elastography, eight on controlled attenuation parameter (CAP) and two on scintigraphy. The pathological definition of MASH was inconsistent, making it difficult to compare studies. 55/69 studies (79.71%) were deemed high-risk of bias as they had no preset thresholds and no validation. The two largest groups of imaging papers were on MRI and ultrasound. AUROCs were up to 0.93 for MRE, 0.90 for MRI, 1.0 for magnetic resonance spectroscopy (MRS) and 0.94 for ultrasound-based studies., Conclusions: Our study found that the most promising imaging tools are MRI techniques or ultrasound-based scores and confirmed there is potential to utilise these for MASH diagnosis. However, many publications are single studies without independent prospective validation. Without this, there is no clear imaging tool or score currently available that is reliably tested to diagnose MASH., (© 2024 The Author(s). Liver International published by John Wiley & Sons Ltd.)

Competing Interests: Competing interests: DM and AN are members of the EMJ editorial board. JSB is a senior clinical advisor and has received research funding and honoraria from Intelligent Ultrasound, which develops assistive artificial intelligence systems for medical ultrasound including ultrasound-guided regional anaesthesia.

Background: Regional anaesthesia use is growing worldwide, and there is an increasing emphasis on research in regional anaesthesia to improve patient outcomes. However, priorities for future study remain unclear. We therefore conducted an international research prioritisation exercise, setting the agenda for future investigators and funding bodies., Methods: We invited members of specialist regional anaesthesia societies from six continents to propose research questions that they felt were unanswered. These were consolidated into representative indicative questions, and a literature review was undertaken to determine if any indicative questions were already answered by published work. Unanswered indicative questions entered a three-round modified Delphi process, whereby 29 experts in regional anaesthesia (representing all participating specialist societies) rated each indicative question for inclusion on a final high priority shortlist. If ≥75% of participants rated an indicative question as 'definitely' include in any round, it was accepted. Indicative questions rated as 'definitely' or 'probably' by <50% of participants in any round were excluded. Retained indicative questions were further ranked based on the rating score in the final Delphi round. The final research priorities were ratified by the Delphi expert group., Results: There were 1318 responses from 516 people in the initial survey, from which 71 indicative questions were formed, of which 68 entered the modified Delphi process. Eleven 'highest priority' research questions were short listed, covering themes of pain management; training and assessment; clinical practice and efficacy; technology and equipment., Conclusions: We prioritised unanswered research questions in regional anaesthesia. These will inform a coordinated global research strategy for regional anaesthesia and direct investigators to address high-priority areas., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

X chromosome inactivation (XCI) in mammals is mediated by Xist RNA which functions in cis to silence genes on a single X chromosome in XX female cells, thereby equalising levels of X-linked gene expression relative to XY males. XCI progresses over a period of several days, with some X-linked genes silencing faster than others. The chromosomal location of a gene is an important determinant of silencing rate, but uncharacterised gene-intrinsic features also mediate resistance or susceptibility to silencing. In this study, we examine mouse embryonic stem cell lines with an inducible Xist allele (iXist-ChrX mESCs) and integrate allele-specific data of gene silencing and decreasing inactive X (Xi) chromatin accessibility over time courses of Xist induction with cellular differentiation. Our analysis reveals that motifs bound by the transcription factor YY1 are associated with persistently accessible regulatory elements, including many promoters and enhancers of slow-silencing genes. We further show that YY1 is evicted relatively slowly from target sites on Xi, and that silencing of X-linked genes is increased upon YY1 degradation. Together our results suggest that YY1 acts as a barrier to Xist-mediated silencing until the late stages of the XCI process., (© 2024. Crown.)

Background: Artificial intelligence (AI) for ultrasound scanning in regional anaesthesia is a rapidly developing interdisciplinary field. There is a risk that work could be undertaken in parallel by different elements of the community but with a lack of knowledge transfer between disciplines, leading to repetition and diverging methodologies. This scoping review aimed to identify and map the available literature on the accuracy and utility of AI systems for ultrasound scanning in regional anaesthesia., Methods: A literature search was conducted using Medline, Embase, CINAHL, IEEE Xplore, and ACM Digital Library. Clinical trial registries, a registry of doctoral theses, regulatory authority databases, and websites of learned societies in the field were searched. Online commercial sources were also reviewed., Results: In total, 13,014 sources were identified; 116 were included for full-text review. A marked change in AI techniques was noted in 2016-17, from which point on the predominant technique used was deep learning. Methods of evaluating accuracy are variable, meaning it is impossible to compare the performance of one model with another. Evaluations of utility are more comparable, but predominantly gained from the simulation setting with limited clinical data on efficacy or safety. Study methodology and reporting lack standardisation., Conclusions: There is a lack of structure to the evaluation of accuracy and utility of AI for ultrasound scanning in regional anaesthesia, which hinders rigorous appraisal and clinical uptake. A framework for consistent evaluation is needed to inform model evaluation, allow comparison between approaches/models, and facilitate appropriate clinical adoption., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: ScanNav TM Anatomy Peripheral Nerve Block (ScanNav™) is an artificial intelligence (AI)-based device that produces a colour overlay on real-time B-mode ultrasound to highlight key anatomical structures for regional anaesthesia. This study compares consistency of identification of sono-anatomical structures between expert ultrasonographers and ScanNav™., Methods: Nineteen experts in ultrasound-guided regional anaesthesia (UGRA) annotated 100 structures in 30 ultrasound videos across six anatomical regions. These annotations were compared with each other to produce a quantitative assessment of the level of agreement amongst human experts. The AI colour overlay was then compared with all expert annotations. Differences in human-human and human-AI agreement are presented for each structure class (artery, muscle, nerve, fascia/serosal plane) and structure. Clinical context is provided through subjective assessment data from UGRA experts., Results: For human-human and human-AI annotations, agreement was highest for arteries (mean Dice score 0.88/0.86), then muscles (0.80/0.77), and lowest for nerves (0.48/0.41). Wide discrepancy exists in consistency for different structures, both with human-human and human-AI comparisons; highest for sartorius muscle (0.91/0.92) and lowest for the radial nerve (0.21/0.27)., Conclusions: Human experts and the AI system both showed the same pattern of agreement in sono-anatomical structure identification. The clinical significance of the differences presented must be explored; however the perception that human expert opinion is uniform must be challenged. Elements of this assessment framework could be used for other devices to allow consistent evaluations that inform clinical training and practice. Anaesthetists should be actively engaged in the development and adoption of new AI technology., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Introduction Needle tip visualisation is a key skill required for the safe practice of ultrasound-guided regional anaesthesia (UGRA). This exploratory study assesses the utility of a novel augmented reality device, NeedleTrainer™, to differentiate between anaesthetists with varying levels of UGRA experience in a simulated environment. Methods Four groups of five participants were recruited (n = 20): novice, early career, experienced anaesthetists, and UGRA experts. Each participant performed three simulated UGRA blocks using NeedleTrainer™ on healthy volunteers (n = 60). The primary aim was to determine whether there was a difference in needle tip visibility, as calculated by the device, between groups of anaesthetists with differing levels of UGRA experience. Secondary aims included the assessment of simulated block conduct by an expert assessor and subjective participant self-assessment. Results The percentage of time the simulated needle tip was maintained in view was higher in the UGRA expert group (57.1%) versus the other three groups (novice 41.8%, early career 44.5%, and experienced anaesthetists 43.6%), but did not reach statistical significance (p = 0.05). An expert assessor was able to differentiate between participants of different UGRA experience when assessing needle tip visibility (novice 3.3 out of 10, early career 5.1, experienced anaesthetists 5.9, UGRA expert group 8.7; p < 0.01) and final needle tip placement (novice 4.2 out of 10, early career 5.6, experienced anaesthetists 6.8, UGRA expert group 8.9; p < 0.01). Subjective self-assessment by participants did not differentiate UGRA experience when assessing needle tip visibility (p = 0.07) or final needle tip placement (p = 0.07). Discussion An expert assessor was able to differentiate between participants with different levels of UGRA experience in this simulated environment. Objective NeedleTrainer™ and subjective participant assessments did not reach statistical significance. The findings are novel as simulated needling using live human subjects has not been assessed before, and no previous studies have attempted to objectively quantify needle tip visibility during simulated UGRA techniques. Future research should include larger sample sizes to further assess the potential use of such technology., Competing Interests: The authors have declared financial relationships, which are detailed in the next section., (Copyright © 2023, Shevlin et al.)

Background: Ultrasound-guided regional anaesthesia relies on the visualisation of key landmark, target, and safety structures on ultrasound. However, this can be challenging, particularly for inexperienced practitioners. Artificial intelligence (AI) is increasingly being applied to medical image interpretation, including ultrasound. In this exploratory study, we evaluated ultrasound scanning performance by non-experts in ultrasound-guided regional anaesthesia, with and without the use of an assistive AI device., Methods: Twenty-one anaesthetists, all non-experts in ultrasound-guided regional anaesthesia, underwent a standardised teaching session in ultrasound scanning for six peripheral nerve blocks. All then performed a scan for each block; half of the scans were performed with AI assistance and half without. Experts assessed acquisition of the correct block view and correct identification of sono-anatomical structures on each view. Participants reported scan confidence, experts provided a global rating score of scan performance, and scans were timed., Results: Experts assessed 126 ultrasound scans. Participants acquired the correct block view in 56/62 (90.3%) scans with the device compared with 47/62 (75.1%) without (P=0.031, two data points lost). Correct identification of sono-anatomical structures on the view was 188/212 (88.8%) with the device compared with 161/208 (77.4%) without (P=0.002). There was no significant overall difference in participant confidence, expert global performance score, or scan time., Conclusions: Use of an assistive AI device was associated with improved ultrasound image acquisition and interpretation. Such technology holds potential to augment performance of ultrasound scanning for regional anaesthesia by non-experts, potentially expanding patient access to these techniques., Clinical Trial Registration: NCT05156099., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Ultrasonound is used to identify anatomical structures during regional anaesthesia and to guide needle insertion and injection of local anaesthetic. ScanNav Anatomy Peripheral Nerve Block (Intelligent Ultrasound, Cardiff, UK) is an artificial intelligence-based device that produces a colour overlay on real-time B-mode ultrasound to highlight anatomical structures of interest. We evaluated the accuracy of the artificial-intelligence colour overlay and its perceived influence on risk of adverse events or block failure., Methods: Ultrasound-guided regional anaesthesia experts acquired 720 videos from 40 volunteers (across nine anatomical regions) without using the device. The artificial-intelligence colour overlay was subsequently applied. Three more experts independently reviewed each video (with the original unmodified video) to assess accuracy of the colour overlay in relation to key anatomical structures (true positive/negative and false positive/negative) and the potential for highlighting to modify perceived risk of adverse events (needle trauma to nerves, arteries, pleura, and peritoneum) or block failure., Results: The artificial-intelligence models identified the structure of interest in 93.5% of cases (1519/1624), with a false-negative rate of 3.0% (48/1624) and a false-positive rate of 3.5% (57/1624). Highlighting was judged to reduce the risk of unwanted needle trauma to nerves, arteries, pleura, and peritoneum in 62.9-86.4% of cases (302/480 to 345/400), and to increase the risk in 0.0-1.7% (0/160 to 8/480). Risk of block failure was reported to be reduced in 81.3% of scans (585/720) and to be increased in 1.8% (13/720)., Conclusions: Artificial intelligence-based devices can potentially aid image acquisition and interpretation in ultrasound-guided regional anaesthesia. Further studies are necessary to demonstrate their effectiveness in supporting training and clinical practice., Clinical Trial Registration: NCT04906018., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Introduction: Ultrasound-guided regional anesthesia (UGRA) involves the acquisition and interpretation of ultrasound images to delineate sonoanatomy. This study explores the utility of a novel artificial intelligence (AI) device designed to assist in this task (ScanNav Anatomy Peripheral Nerve Block; ScanNav), which applies a color overlay on real-time ultrasound to highlight key anatomical structures., Methods: Thirty anesthesiologists, 15 non-experts and 15 experts in UGRA, performed 240 ultrasound scans across nine peripheral nerve block regions. Half were performed with ScanNav. After scanning each block region, participants completed a questionnaire on the utility of the device in relation to training, teaching, and clinical practice in ultrasound scanning for UGRA. Ultrasound and color overlay output were recorded from scans performed with ScanNav. Experts present during the scans (real-time experts) were asked to assess potential for increased risk associated with use of the device (eg, needle trauma to safety structures). This was compared with experts who viewed the AI scans remotely., Results: Non-experts were more likely to provide positive and less likely to provide negative feedback than experts (p=0.001). Positive feedback was provided most frequently by non-experts on the potential role for training (37/60, 61.7%); for experts, it was for its utility in teaching (30/60, 50%). Real-time and remote experts reported a potentially increased risk in 12/254 (4.7%) vs 8/254 (3.1%, p=0.362) scans, respectively., Discussion: ScanNav shows potential to support non-experts in training and clinical practice, and experts in teaching UGRA. Such technology may aid the uptake and generalizability of UGRA., Trial Registration Number: NCT04918693., Competing Interests: Competing interests: JSB is a Senior Clinical Advisor for Intelligent Ultrasound, receiving research funding and honoraria. KEB is an Editor for Anaesthesia and has received research, honoraria and educational funding from Fisher and Paykel Healthcare Lit, GE Healthcare and Ambu. DBSL is a Clinical Advisor for Intelligent Ultrasound, receiving honoraria. JAN is a Senior Scientific Advisor for Intelligent Ultrasound., (© American Society of Regional Anesthesia & Pain Medicine 2022. Re-use permitted under CC BY-NC. No commercial re-use. Published by BMJ.)

X chromosome inactivation (XCI) is mediated by the non-coding RNA Xist, which directs chromatin modification and gene silencing in cis. The RNA binding protein SPEN and associated corepressors have a central role in Xist-mediated gene silencing. Other silencing factors, notably the Polycomb system, have been reported to function downstream of SPEN. In recent work, we found that SPEN has an additional role in correct localization of Xist RNA in cis, indicating that its contribution to chromatin-mediated gene silencing needs to be reappraised. Making use of a SPEN separation-of-function mutation, we show that SPEN and Polycomb pathways, in fact, function in parallel to establish gene silencing. We also find that differentiation-dependent recruitment of the chromosomal protein SmcHD1 is required for silencing many X-linked genes. Our results provide important insights into the mechanism of X inactivation and the coordination of chromatin-based gene regulation with cellular differentiation and development., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Transposable elements (TEs) regulate diverse biological processes, from early development to cancer. Expression of young TEs is difficult to measure with next-generation, single-cell sequencing technologies because their highly repetitive nature means that short complementary DNA reads cannot be unambiguously mapped to a specific locus. Single CELl LOng-read RNA-sequencing (CELLO-seq) combines long-read single cell RNA-sequencing with computational analyses to measure TE expression at unique loci. We used CELLO-seq to assess the widespread expression of TEs in two-cell mouse blastomeres as well as in human induced pluripotent stem cells. Across both species, old and young TEs showed evidence of locus-specific expression with simulations demonstrating that only a small number of very young elements in the mouse could not be mapped back to the reference with high confidence. Exploring the relationship between the expression of individual elements and putative regulators revealed large heterogeneity, with TEs within a class showing different patterns of correlation and suggesting distinct regulatory mechanisms., (© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.)

There is no universally agreed set of anatomical structures that must be identified on ultrasound for the performance of ultrasound-guided regional anesthesia (UGRA) techniques. This study aimed to produce standardized recommendations for core (minimum) structures to identify during seven basic blocks. An international consensus was sought through a modified Delphi process. A long-list of anatomical structures was refined through serial review by key opinion leaders in UGRA. All rounds were conducted remotely and anonymously to facilitate equal contribution of each participant. Blocks were considered twice in each round: for "orientation scanning" (the dynamic process of acquiring the final view) and for the "block view" (which visualizes the block site and is maintained for needle insertion/injection). Strong recommendations for inclusion were made if ≥75% of participants rated a structure as "definitely include" in any round. Weak recommendations were made if >50% of participants rated a structure as "definitely include" or "probably include" for all rounds (but the criterion for "strong recommendation" was never met). Thirty-six participants (94.7%) completed all rounds. 128 structures were reviewed; a "strong recommendation" is made for 35 structures on orientation scanning and 28 for the block view. A "weak recommendation" is made for 36 and 20 structures, respectively. This study provides recommendations on the core (minimum) set of anatomical structures to identify during ultrasound scanning for seven basic blocks in UGRA. They are intended to support consistent practice, empower non-experts using basic UGRA techniques, and standardize teaching and research., Competing Interests: Competing interests: AD, CL, EM, LFV-V, TV, and MW are members of the Executive Board of the European Society of Regional Anaesthesia & Pain Therapy (ESRA). NE, SK, SM, SN, and MAR are members of the Board of Directors of the American Society of Regional Anesthesia & Pain Medicine (ASRA). AG, NH, DFJ, RJK, AJRM, AP, MPS, AT, LT, SW, JW are members of the Board of Regional Anaesthesia UK (RAUK). WH-G is the Vice-President of the Royal College of Anaesthetists. JSB, DBSL, AJRM, DP & AT declare honoraria and/or research funding from Intelligent Ultrasound. JAN is a Senior Scientific Advisor for Intelligent Ultrasound Limited. AP declares consultancy fees for B Braun Medical UK and honoraria from GE Healthcare, Butterfly Net Inc, Sintetica UK Ltd, and Pacira., (© American Society of Regional Anesthesia & Pain Medicine 2022. No commercial re-use. See rights and permissions. Published by BMJ.)

RNA N 6 -methyladenosine (m 6 A) modification plays important roles in multiple aspects of RNA regulation. m 6 A is installed cotranscriptionally by the METTL3/14 complex, but its direct roles in RNA processing remain unclear. Here, we investigate the presence of m 6 A in nascent RNA of mouse embryonic stem cells. We find that around 10% of m 6 A peaks are located in alternative introns/exons, often close to 5' splice sites. m 6 A peaks significantly overlap with RBM15 RNA binding sites and the histone modification H3K36me3. Acute depletion of METTL3 disrupts inclusion of alternative introns/exons in the nascent transcriptome, particularly at 5' splice sites that are proximal to m 6 A peaks. For terminal or variable-length exons, m 6 A peaks are generally located on or immediately downstream from a 5' splice site that is suppressed in the presence of m 6 A and upstream of a 5' splice site that is promoted in the presence of m 6 A. Genes with the most immediate effects on splicing include several components of the m 6 A pathway, suggesting an autoregulatory function. Collectively, our findings demonstrate crosstalk between the m 6 A machinery and the regulation of RNA splicing., (© 2021 Wei et al.; Published by Cold Spring Harbor Laboratory Press.)

The X inactive-specific transcript ( Xist ) gene is the master regulator of X chromosome inactivation in mammals. Xist produces a long noncoding (lnc)RNA that accumulates over the entire length of the chromosome from which it is transcribed, recruiting factors to modify underlying chromatin and silence X-linked genes in cis Recent years have seen significant progress in identifying important functional elements in Xist RNA, their associated RNA-binding proteins (RBPs), and the downstream pathways for chromatin modification and gene silencing. In this review, we summarize progress in understanding both how these pathways function in Xist-mediated silencing and the complex interplay between them., (© 2020 Brockdorff et al.; Published by Cold Spring Harbor Laboratory Press.)

Many intricate pathways contribute to the timely control of gene expression during development. Polycomb repressive complexes (PRC1 and PRC2) and long non-coding RNAs (lncRNAs) are players associated with gene repression in various developmental processes such as X chromosome inactivation (XCI) and genomic imprinting. Historically, lncRNAs were proposed to directly recruit PRC2. However, recent evidence suggests that promiscuous interactions between PRC2 and RNA fine-tune the function of the complex through a multiplicity of mechanisms. A PRC2-recruitment model was definitively overturned in the paradigm of XCI by Xist RNA, being replaced by a novel mechanism which puts PRC1 in the spotlight. This review focuses on these recent advances in understanding the interplay between RNA and Polycomb complexes for gene expression control., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Xist RNA, the master regulator of X chromosome inactivation, acts in cis to induce chromosome-wide silencing. Whilst recent studies have defined candidate silencing factors, their relative contribution to repressing different genes, and their relationship with one another is poorly understood. Here we describe a systematic analysis of Xist-mediated allelic silencing in mouse embryonic stem cell-based models. Using a machine learning approach we identify distance to the Xist locus and prior gene expression levels as key determinants of silencing efficiency. We go on to show that Spen, recruited through the Xist A-repeat, plays a central role, being critical for silencing of all except a subset of weakly expressed genes. Polycomb, recruited through the Xist B/C-repeat, also plays a key role, favouring silencing of genes with pre-existing H3K27me3 chromatin. LBR and the Rbm15/m6A-methyltransferase complex make only minor contributions to gene silencing. Together our results provide a comprehensive model for Xist-mediated chromosome silencing.

Objectives: International guidelines exist for chest drain insertion and recommend identifying the fifth intercostal space or above, around the midaxillary line. In a recent study, applying these guidelines in cadavers risked insertion in the 6th intercostal space or below in 80% of cases. However, there are limitations of cadaveric studies and this investigation uses ultrasound to determine the intercostal space identified when applying these guidelines in healthy adult volunteers., Methods: On each side of the chest wall in 31 volunteers, the position for drain insertion was identified using the European Trauma Course method, Advanced Trauma Life Support (ATLS) method, British Thoracic Society's 'safe triangle' and the 'traditional' method of palpation. Ultrasound imaging was used to determine the relationship of the skin marks with the underlying intercostal spaces., Results: Five methods were assessed on 60 sides. In contrast to the cadaveric study, 94% of skin marks lay over a safe intercostal space. However, the range of intercostal spaces found spanned the second to the seventh space. In 44% of women, the inferior boundary of the 'safe triangle' and the ATLS guidelines located the sixth intercostal space or below., Conclusions: Current guidelines often identify a safe site for chest drain insertion, although the same site is not reproducibly found. In addition, women appear to be at risk of subdiaphragmatic drain insertion when the nipple is used to identify the fifth intercostal space. Real-time ultrasonography can be used to confirm the intercostal space during this procedure, although a safe guideline is still needed for circumstances in which ultrasound is not possible., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/)