A data science roadmap for open science organizations engaged in early-stage drug discovery.

The Structural Genomics Consortium is an international open science research organization with a focus on accelerating early-stage drug discovery, namely hit discovery and optimization. We, as many others, believe that artificial intelligence (AI) is poised to be a main accelerator in the field. The question is then how to best benefit from recent advances in AI and how to generate, format and disseminate data to enable future breakthroughs in AI-guided drug discovery. We present here the recommendations of a working group composed of experts from both the public and private sectors. Robust data management requires precise ontologies and standardized vocabulary while a centralized database architecture across laboratories facilitates data integration into high-value datasets. Lab automation and opening electronic lab notebooks to data mining push the boundaries of data sharing and data modeling. Important considerations for building robust machine-learning models include transparent and reproducible data processing, choosing the most relevant data representation, defining the right training and test sets, and estimating prediction uncertainty. Beyond data-sharing, cloud-based computing can be harnessed to build and disseminate machine-learning models. Important vectors of acceleration for hit and chemical probe discovery will be (1) the real-time integration of experimental data generation and modeling workflows within design-make-test-analyze (DMTA) cycles openly, and at scale and (2) the adoption of a mindset where data scientists and experimentalists work as a unified team, and where data science is incorporated into the experimental design.

dtool and dserver: A flexible ecosystem for findable data.

Making data FAIR-findable, accessible, interoperable, reproducible-has become the recurring theme behind many research data management efforts. dtool is a lightweight data management tool that packages metadata with immutable data to promote accessibility, interoperability, and reproducibility. Each dataset is self-contained and does not require metadata to be stored in a centralised system. This decentralised approach means that finding datasets can be difficult. dtool's lookup server, short dserver, as defined by a REST API, makes dtool datasets findable, hence rendering the dtool ecosystem fit for a FAIR data management world. Its simplicity, modularity, accessibility and standardisation via API distinguish dtool and dserver from other solutions and enable it to serve as a common denominator for cross-disciplinary research data management. The dtool ecosystem bridges the gap between standardisation-free data management by individuals and FAIR platform solutions with rigid metadata requirements.

Outcomes of Mohs micrographic surgery for periocular squamous cell carcinoma.

INTRODUCTION: Periocular cutaneous squamous cell carcinoma (cSCC) accounts for 5-10% of all eyelid malignancies. Periocular cSCC carries a low mortality rate but can be destructive to local tissues. Due to the unique function and anatomy of the eyelids, Mohs micrographic surgery (MMS) is gold standard for treating cSCC to preserve healthy tissue and reduce rates of local recurrence. In this study, we describe the success and outcomes of MMS and subsequent oculoplastic reconstruction for periocular cSCC in the North East of England. METHODS: Retrospective analysis of 34 patients who underwent MMS for periocular cSCC in the North of England between 2013 and 2020. Primary outcome measure of success is defined as no recurrence of cSCC after minimum 24 months' time elapsed post-MMS. Secondary outcome measures included analysis of disease characteristics, describing the surgical techniques utilised for oculoplastic reconstruction following MMS and surgical complications should they occur. RESULTS: Two patients (5.9%) had local recurrence of periocular cSCC. Median time elapsed since MMS was 60 months. A variety of oculoplastic surgical techniques were utilised in the repair of the Mohs defect. One patient (2.9%) developed a significant post-operative reconstruction complication. CONCLUSION: Periocular cSCC recurrence following MMS in the North of England is 5.9%, which is comparable to the literature. Significant post-operative complications following oculoplastic reconstruction of periocular MMS are very low, occurring in 2.9% of cases in this study.

Community-developed checklists for publishing images and image analyses.

Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However, for scientists wishing to publish obtained images and image-analysis results, there are currently no unified guidelines for best practices. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here, we present community-developed checklists for preparing light microscopy images and describing image analyses for publications. These checklists offer authors, readers and publishers key recommendations for image formatting and annotation, color selection, data availability and reporting image-analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby to heighten the quality and explanatory power of microscopy data.

EMBL's European Bioinformatics Institute (EMBL-EBI) in 2023.

The European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI) is one of the world's leading sources of public biomolecular data. Based at the Wellcome Genome Campus in Hinxton, UK, EMBL-EBI is one of six sites of the European Molecular Biology Laboratory (EMBL), Europe's only intergovernmental life sciences organisation. This overview summarises the latest developments in the services provided by EMBL-EBI data resources to scientific communities globally. These developments aim to ensure EMBL-EBI resources meet the current and future needs of these scientific communities, accelerating the impact of open biological data for all.

Providing open imaging data at scale: An EMBL-EBI perspective.

Biological imaging is one of the primary tools by which we understand living systems across scales from atoms to organisms. Rapid advances in imaging technology have increased both the spatial and temporal resolutions at which we examine those systems, as well as enabling visualisation of larger tissue volumes. These advances have huge potential but also generate ever increasing amounts of imaging data that must be stored and analysed. Public image repositories provide a critical scientific service through open data provision, supporting reproducibility of scientific results, access to reference imaging datasets and reuse of data for new scientific discovery and acceleration of image analysis methods development. The scale and scope of imaging data provides both challenges and opportunities for open sharing of image data. In this article, we provide a perspective influenced by decades of provision of open data resources for biological information, suggesting areas to focus on and a path towards global interoperability.

Pictures at an exhibition: How to share your imaging data.

Open access to data underpinning published results is a key pillar of scientific reproducibility. Making data available at scale also provides opportunities for data reuse, encouraging the development of new analysis approaches. In this poster article, accompanying a recorded talk, we will explain the benefits of publicly archiving your image data alongside your published manuscripts, as well as highlight what resources are available to do this. This will include the BioImage Archive, EMBL-EBI's new resource for biological image data, https://www.ebi.ac.uk/bioimage-archive/. We will look at how image data submission works, how to prepare in advance for archiving your data and upcoming developments.

Integrating analog and digital modes of gene expression at Arabidopsis FLC.

Quantitative gene regulation at the cell population level can be achieved by two fundamentally different modes of regulation at individual gene copies. A 'digital' mode involves binary ON/OFF expression states, with population-level variation arising from the proportion of gene copies in each state, while an 'analog' mode involves graded expression levels at each gene copy. At the Arabidopsis floral repressor FLOWERING LOCUS C (FLC), 'digital' Polycomb silencing is known to facilitate quantitative epigenetic memory in response to cold. However, whether FLC regulation before cold involves analog or digital modes is unknown. Using quantitative fluorescent imaging of FLC mRNA and protein, together with mathematical modeling, we find that FLC expression before cold is regulated by both analog and digital modes. We observe a temporal separation between the two modes, with analog preceding digital. The analog mode can maintain intermediate expression levels at individual FLC gene copies, before subsequent digital silencing, consistent with the copies switching OFF stochastically and heritably without cold. This switch leads to a slow reduction in FLC expression at the cell population level. These data present a new paradigm for gradual repression, elucidating how analog transcriptional and digital epigenetic memory pathways can be integrated.

OME-Zarr: a cloud-optimized bioimaging file format with international community support.

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself-OME-Zarr-along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain-the file format that underlies so many personal, institutional, and global data management and analysis tasks.

Public archiving of volume EM data.

Volume electron microscopy (vEM) techniques produce scientifically important datasets which are time and resource intensive to generate (Peddie et al., 2022). Public archival of such datasets, usually described in the literature, provides many benefits to the data depositors, to those making use of research results based on the datasets, and to the vEM community at large, both now and in the future. In this chapter we discuss these benefits, explain how EMBL-EBI's image data services support archival of both vEM and correlative imaging data, and discuss how future developments will unlock more value from these vEM datasets.

McKittrick-Wheelock syndrome presenting with presumed paraneoplastic syndrome extra-ocular muscle enlargement masquerading as thyroid eye disease.

Summary: Paraneoplastic syndromes (PS) are uncommon and are known to mimic other clinical entities, often carrying significant morbidity and mortality. The commonest cause of extra-ocular muscle enlargement (EOME) is thyroid eye disease (TED). Rarely, PS can cause EOME and masquerade as TED. We describe a 52-year-old female who presented with diarrhoea, acute kidney injury and electrolyte imbalance. An ophthalmic review identified right upper lid retraction. MRI orbits showed increased thickness of the inferior and medial recti bilaterally, presumed as TED. Whilst investigating her diarrhoea, imaging revealed a large rectosigmoid tumour which required surgical excision. In the context of electrolyte disturbance and acute kidney injury, a diagnosis of McKittrick-Wheelock syndrome (MWS) was made. Following successful surgery, electrolyte imbalance, diarrhoea and eyelid retraction improved. Repeat MRI orbits displayed complete resolution of EOME. To our knowledge, this is the first case of MWS presenting with PS-EOME masquerading as TED. Learning points: McKittrick-Wheelock syndrome (MWS) is a rare disorder, although likely under-recognised, which is characterised by diarrhoea, dehydration and electrolyte depletion that results from a hypersecretory colorectal neoplasm. Definitive treatment of MWS involves the resection of the colorectal neoplasm. Bilateral ophthalmopathy that appears to be Graves' ophthalmopathy on imaging, though clinical and biochemical evidence fails to identify a thyroid pathology, has been associated with malignancy on rare occasions. Such patients should be investigated for potential malignant causes of their ophthalmopathy.

OME-Zarr: a cloud-optimized bioimaging file format with international community support.

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself -- OME-Zarr -- along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain -- the file format that underlies so many personal, institutional, and global data management and analysis tasks.

Community-developed checklists for publishing images and image analyses.

Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However for scientists wishing to publish the obtained images and image analyses results, there are to date no unified guidelines. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here we present community-developed checklists for preparing light microscopy images and image analysis for publications. These checklists offer authors, readers, and publishers key recommendations for image formatting and annotation, color selection, data availability, and for reporting image analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby heighten the quality and explanatory power of microscopy data is in publications.

EMBL's European Bioinformatics Institute (EMBL-EBI) in 2022.

The European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI) is one of the world's leading sources of public biomolecular data. Based at the Wellcome Genome Campus in Hinxton, UK, EMBL-EBI is one of six sites of the European Molecular Biology Laboratory (EMBL), Europe's only intergovernmental life sciences organisation. This overview summarises the status of services that EMBL-EBI data resources provide to scientific communities globally. The scale, openness, rich metadata and extensive curation of EMBL-EBI added-value databases makes them particularly well-suited as training sets for deep learning, machine learning and artificial intelligence applications, a selection of which are described here. The data resources at EMBL-EBI can catalyse such developments because they offer sustainable, high-quality data, collected in some cases over decades and made openly availability to any researcher, globally. Our aim is for EMBL-EBI data resources to keep providing the foundations for tools and research insights that transform fields across the life sciences.

Impact of female contraception for population management on behavior and social interactions in a captive troop of Guinea baboons (Papio papio).

As part of a population management strategy for a troop of Guinea baboons (Papio papio) at Yorkshire Wildlife Park, adult females were given a Suprelorin contraceptive implant. There was no information on the effect of contraception on behavior in this species, so behavioral data were collected before and after implant placement to determine any impact on the troops' welfare. Social interactions, affiliative, agonistic, and self-directed displacement behaviors (SDBs) in all adults were monitored via focal sampling. Preimplant data were collected in August/September 2019 before Suprelorin placement on November 2019, and postimplant data were collected in August/September 2020, allowing for comparison while controlling for seasonal differences in behavior. We found a significant reduction of SDBs after intervention, suggesting that contraception has a positive impact on group welfare, as SDBs are key behavioral indicators of stress and anxiety in nonhuman primates. Additionally, the rate of substate change per hour (i.e., the number of times the baboon changed their behavior), duration of sentry behavior, and the frequency of agonistic bouts were significantly lower postimplant, further suggesting improvements in welfare. There were also no significant decreases in the duration of positive social interactions, such as allogrooming and play. The results show that Suprelorin did not have a detrimental impact on the behavior of adults in the troop and may have even improved welfare. The use of Suprelorin in females could be considered as an effective population management strategy for primates existing in similar social systems.

Spontaneous periocular ecchymosis: a major review.

Periocular ecchymosis, or periocular bruising, is a common clinical finding. Periocular skin is thin with an extensive vascular network, making this anatomical region prone to bruising. The most common etiology is trauma, but rarely, patients can present with spontaneous periocular ecchymosis (SPE). The pathophysiology of SPE is complex and varied. In this literature review of 121 articles, we assessed the frequency and variety of causation of this infrequent entity. The main finding was that by far the most common diagnosis causing SPE is amyloidosis and neoplasm, most notably neuroblastoma. Amyloidosis accounted for 23% articles (28/121) and neuroblastoma for 17% articles (21/121). Overall, neoplastic processes accounted for 30% of the articles (36/121), raised intracranial pressure and vascular malformations for 19% of the articles (23/121), migraine and atypical headache for 7% of the articles (8/121), while iatrogenic accounted for 5% of the articles (6/121). Through exploration and appreciation of the pathophysiology, we hope to foster a greater understanding in the clinician to establish underlying etiology, from benign to life-threatening, when presented with SPE.

Ten recommendations for organising bioimaging data for archival.

Organised data is easy to use but the rapid developments in the field of bioimaging, with improvements in instrumentation, detectors, software and experimental techniques, have resulted in an explosion of the volumes of data being generated, making well-organised data an elusive goal. This guide offers a handful of recommendations for bioimage depositors, analysts and microscope and software developers, whose implementation would contribute towards better organised data in preparation for archival. Based on our experience archiving large image datasets in EMPIAR, the BioImage Archive and BioStudies, we propose a number of strategies that we believe would improve the usability (clarity, orderliness, learnability, navigability, self-documentation, coherence and consistency of identifiers, accessibility, succinctness) of future data depositions more useful to the bioimaging community (data authors and analysts, researchers, clinicians, funders, collaborators, industry partners, hardware/software producers, journals, archive developers as well as interested but non-specialist users of bioimaging data). The recommendations that may also find use in other data-intensive disciplines. To facilitate the process of analysing data organisation, we present bandbox, a Python package that provides users with an assessment of their data by flagging potential issues, such as redundant directories or invalid characters in file or folder names, that should be addressed before archival. We offer these recommendations as a starting point and hope to engender more substantial conversations across and between the various data-rich communities.

Classification of wheat diseases using deep learning networks with field and glasshouse images.

Crop diseases can cause major yield losses, so the ability to detect and identify them in their early stages is important for disease control. Deep learning methods have shown promise in classifying multiple diseases; however, many studies do not use datasets that represent real field conditions, necessitating either further image processing or reducing their applicability. In this paper, we present a dataset of wheat images taken in real growth situations, including both field and glasshouse conditions, with five categories: healthy plants and four foliar diseases, yellow rust, brown rust, powdery mildew and Septoria leaf blotch. This dataset was used to train a deep learning model. The resulting model, named CerealConv, reached a 97.05% classification accuracy. When tested against trained pathologists on a subset of images from the larger dataset, the model delivered an accuracy score 2% higher than the best-performing pathologist. Image masks were used to show that the model was using the correct information to drive its classifications. These results show that deep learning networks are a viable tool for disease detection and classification in the field, and disease quantification is a logical next step.