Causal chain event graphs for remedial maintenance.

The analysis of system reliability has often benefited from graphical tools such as fault trees and Bayesian networks. In this article, instead of conventional graphical tools, we apply a probabilistic graphical model called the chain event graph (CEG) to represent the failures and processes of deterioration of a system. The CEG is derived from an event tree and can flexibly represent the unfolding of asymmetric processes. For this application, we need to define a new class of formal intervention we call remedial to model the causal effects of remedial maintenance. This fixes the root causes of a failure and returns the status of the system to as good as new. We demonstrate that the semantics of the CEG are rich enough to express this novel type of intervention. Furthermore, through the bespoke causal algebras, the CEG provides a transparent framework with which to guide and express the rationale behind predictive inferences about the effects of various types of remedial intervention. A backdoor theorem is adapted to apply to these interventions to help discover when a system is only partially observed.

Targeted DNA Methylation Editing Using an All-in-One System Establishes Paradoxical Activation of EBF3.

Cutaneous melanoma is rapidly on the rise globally, surpassing the growth rate of other cancers, with metastasis being the primary cause of death in melanoma patients. Consequently, understanding the mechanisms behind this metastatic process and exploring innovative treatments is of paramount importance. Recent research has shown promise in unravelling the role of epigenetic factors in melanoma progression to metastasis. While DNA hypermethylation at gene promoters typically suppresses gene expression, we have contributed to establishing the newly understood mechanism of paradoxical activation of genes via DNA methylation, where high methylation coincides with increased gene activity. This mechanism challenges the conventional paradigm that promoter methylation solely silences genes, suggesting that, for specific genes, it might actually activate them. Traditionally, altering DNA methylation in vitro has involved using global demethylating agents, which is insufficient for studying the mechanism and testing the direct consequence of gene methylation changes. To investigate promoter hypermethylation and its association with gene activation, we employed a novel approach utilising a CRISPR-SunTag All-in-one system. Here, we focused on editing the DNA methylation of a specific gene promoter segment (EBF3) in melanoma cells using the All-in-one system. Using bisulfite sequencing and qPCR with RNA-Seq, we successfully demonstrated highly effective methylation and demethylation of the EBF3 promoter, with subsequent gene expression changes, to establish and validate the paradoxical role of DNA methylation. Further, our study provides novel insights into the function of the EBF3 gene, which remains largely unknown. Overall, this study challenges the conventional view of methylation as solely a gene-silencing mechanism and demonstrates a potential function of EBF3 in IFN pathway signalling, potentially uncovering new insights into epigenetic drivers of malignancy and metastasis.

Genetic and epigenetic features of neuroendocrine prostate cancer and their emerging applications.

Prostate cancer is the second most prevalent cancer in men globally. De novo neuroendocrine prostate cancer (NEPC) is uncommon at initial diagnosis, however, (treatment-induced) t-NEPC emerges in up to 25% of prostate adenocarcinoma (PRAD) cases treated with androgen deprivation, carrying a drastically poor prognosis. The transition from PRAD to t-NEPC is underpinned by several key genetic mutations; TP53, RB1, and MYCN are the main genes implicated, bearing similarities to other neuroendocrine tumours. A broad range of epigenetic alterations, such as aberrations in DNA methylation, histone post-translational modifications, and non-coding RNAs, may drive lineage plasticity from PRAD to t-NEPC. The clinical diagnosis of NEPC is hampered by a lack of accessible biomarkers; recent advances in liquid biopsy techniques assessing circulating tumour cells and ctDNA in NEPC suggest that the advent of non-invasive means of monitoring progression to NEPC is on the horizon. Such techniques are vital for NEPC management; diagnosis of t-NEPC is crucial for implementing effective treatment, and precision medicine will be integral to providing the best outcomes for patients.

The risks of radioactive wastewater release.

The wastewater release from the Fukushima Daiichi nuclear plant is expected to have negligible effects on people and the ocean.

Evaluation of cataract formation in fish exposed to environmental radiation at Chernobyl and Fukushima.

Recent studies apparently finding deleterious effects of radiation exposure on cataract formation in birds and voles living near Chernobyl represent a major challenge to current radiation protection regulations. This study conducted an integrated assessment of radiation exposure on cataractogenesis using the most advanced technologies available to assess the cataract status of lenses extracted from fish caught at both Chernobyl in Ukraine and Fukushima in Japan. It was hypothesised that these novel data would reveal positive correlations between radiation dose and early indicators of cataract formation. The structure, function and optical properties of lenses were analysed from atomic to millimetre length scales. We measured the short-range order of the lens crystallin proteins using Small Angle X-Ray Scattering (SAXS) at both the SPring-8 and DIAMOND synchrotrons, the profile of the graded refractive index generated by these proteins, the epithelial cell density and organisation and finally the focal length of each lens. The results showed no evidence of a difference between the focal length, the epithelial cell densities, the refractive indices, the interference functions and the short-range order of crystallin proteins (X-ray diffraction patterns) in lens from fish exposed to different radiation doses. It could be argued that animals in the natural environment which developed cataract would be more likely, for example, to suffer predation leading to survivor bias. But the cross-length scale study presented here, by evaluating small scale molecular and cellular changes in the lens (pre-cataract formation) significantly mitigates against this issue.

Disclosure control of machine learning models from trusted research environments (TRE): New challenges and opportunities.

Introduction: Artificial intelligence (AI) applications in healthcare and medicine have increased in recent years. To enable access to personal data, Trusted Research Environments (TREs) (otherwise known as Safe Havens) provide safe and secure environments in which researchers can access sensitive personal data and develop AI (in particular machine learning (ML)) models. However, currently few TREs support the training of ML models in part due to a gap in the practical decision-making guidance for TREs in handling model disclosure. Specifically, the training of ML models creates a need to disclose new types of outputs from TREs. Although TREs have clear policies for the disclosure of statistical outputs, the extent to which trained models can leak personal training data once released is not well understood. Background: We review, for a general audience, different types of ML models and their applicability within healthcare. We explain the outputs from training a ML model and how trained ML models can be vulnerable to external attacks to discover personal data encoded within the model. Risks: We present the challenges for disclosure control of trained ML models in the context of training and exporting models from TREs. We provide insights and analyse methods that could be introduced within TREs to mitigate the risk of privacy breaches when disclosing trained models. Discussion: Although specific guidelines and policies exist for statistical disclosure controls in TREs, they do not satisfactorily address these new types of output requests; i.e., trained ML models. There is significant potential for new interdisciplinary research opportunities in developing and adapting policies and tools for safely disclosing ML outputs from TREs.

Neuroendocrine Neoplasms: Genetics and Epigenetics.

Neuroendocrine neoplasms (NENs) are a group of rare, heterogeneous tumors of neuroendocrine cell origin, affecting a range of different organs. The clinical management of NENs poses significant challenges, as tumors are often diagnosed at an advanced stage where overall survival remains poor with current treatment regimens. In addition, a host of complex and often unique molecular changes underpin the pathobiology of each NEN subtype. Exploitation of the unique genetic and epigenetic signatures driving each NEN subtype provides an opportunity to enhance the diagnosis, treatment, and monitoring of NEN in an emerging era of individualized medicine.

Machine learning models in trusted research environments - understanding operational risks.

Introduction: Trusted research environments (TREs) provide secure access to very sensitive data for research. All TREs operate manual checks on outputs to ensure there is no residual disclosure risk. Machine learning (ML) models require very large amount of data; if this data is personal, the TRE is a well-established data management solution. However, ML models present novel disclosure risks, in both type and scale. Objectives: As part of a series on ML disclosure risk in TREs, this article is intended to introduce TRE managers to the conceptual problems and work being done to address them. Methods: We demonstrate how ML models present a qualitatively different type of disclosure risk, compared to traditional statistical outputs. These arise from both the nature and the scale of ML modelling. Results: We show that there are a large number of unresolved issues, although there is progress in many areas. We show where areas of uncertainty remain, as well as remedial responses available to TREs. Conclusions: At this stage, disclosure checking of ML models is very much a specialist activity. However, TRE managers need a basic awareness of the potential risk in ML models to enable them to make sensible decisions on using TREs for ML model development.

Generation of FOUR iPSC lines (CRICKi004-A; CRICKi005-A; CRICKi006-A, CRICKi007-A) from Spinal muscle atrophy patients with lower extremity dominant (SMALED) phenotype.

Spinal muscular atrophy with lower extremity dominant (SMALED) is a hereditary neuromuscular disorder characterized by degeneration of spinal cord motor neurons resulting in lower limbs muscle weakness and paralysis. Mutations in DYNC1H1, which encodes BICD2, a multifunctional adaptor for microtubule motor proteins, cause the disorder. Here, we generated four induced pluripotent stem cell (iPSC) lines from patients with SMALED. Dermal fibroblasts were obtained from the MRC neuromuscular disease biobank and reprogrammed using non-integrating mRNA-based protocol. Characterization of the four iPSC lines included karyotyping and Sanger sequencing, while the expression of associated markers confirmed pluripotency and differentiation potential.

Natural attenuation processes control groundwater contamination in the Chernobyl exclusion zone: evidence from 35 years of radiological monitoring.

The Chernobyl Exclusion Zone (CEZ) contains the vast majority of radionuclides released by the accident in nuclear fuel particle form. We present and analyze groundwater measurements collected from the monitoring network in CEZ covering key aquifers over 35 years since the accident. These new data, together with a comprehensive analysis of historical data shows that 90Sr remains mobile in the subsurface environment, while groundwater concentrations of 137Cs, Pu isotopes and 241Am are relatively low, and are not of radiological concern. During the last two decades, 90Sr and 137Cs levels have declined or remained stable over time in the majority of monitoring locations. This is due to natural attenuation driven by gradual exhaustion of the fuel particle source, geochemical evolution of groundwater downstream from waste dumps and radionuclide retention in surface soil due to absorption and bio-cycling. Decommissioning of the cooling pond and construction of the 'New safe confinement' over Unit 4 (damaged reactor) also favored better protection of groundwater close to the Chernobyl plant site. Data from confined and unconfined aquifers, as well as rivers, evidence low radiological risks from groundwater contamination both outside the CEZ and to onsite "self-settlers". Though several groundwater contamination "hot spots" remain in the vicinity of Unit 4, "Red Forest" waste trenches and surface water bodies with contaminated bottom sediments, the findings of this study support a monitored natural attenuation approach to groundwater management in the CEZ.

Creating opportunities to improve detection of older adult abuse: a national interRAI study.

Despite being recognized as a major global health issue, older adult abuse (OAA) remains largely undetected and under-reported. Most OAA assessment tools fail to capture true prevalence. Follow up of patients where abuse exposure is not easily determined is a necessity. The interRAI-HC (International Resident Assessment Instrument-Home Care) currently underestimates the extent of abuse. We investigated how to improve detection of OAA using the interRAI-HC. Analysis of 7 years of interRAI-HC data from an Aotearoa New Zealand cohort was completed. We identified that through altering the criteria for suspicion of OAA, capture rates of at-risk individuals could be nearly doubled from 2.6% to 4.8%. We propose that via adapting the interRAI-HC criteria to include the "unable to determine" whether abuse occurred (UDA) category, identification of OAA sufferers could be substantially improved. Improved identification will facilitate enhanced protection of this vulnerable population.

Impact of the 2020 New Zealand COVID-19 lockdown on participants in a community-based, peer-led fall prevention program.

OBJECTIVES: To explore the impacts of the 2020 New Zealand COVID-19 lockdown on peer-led Steady as You Go (SAYGO) fall prevention exercise classes and members, and to develop recommendations for mitigating impacts during future lockdowns. METHODS: Semi-structured phone interviews were conducted with 20 SAYGO program participants and managers following the first COVID-19 lockdown in New Zealand. Interviews were audio-recorded, transcribed verbatim and analysed using the General Inductive Approach. RESULTS: Participants were between 67 and 88 years of age, predominantly female (90%) and NZ European (80%), with one participant identifying as NZ Maori. Three themes were constructed from the analysis: Personal Function and Well-Being, Class Functioning and Logistics, and Future Strategies for Classes During Prospective Lockdowns. Participants used a range of strategies to stay connected with each other and continue the SAYGO exercises at home. Most participants and peer-leaders reported that they maintained physical function during lockdown, although some had feelings of psychological distress and social isolation. Contact systems and resource distribution varied substantially between groups. Classes resumed post-lockdown with only minor modifications and slightly decreased attendance. CONCLUSIONS: Overall, members of this peer-led model of fall prevention classes demonstrated resilience during the COVID-19 lockdown, despite some challenges. We propose three recommendations to address the challenges of maintaining existing peer-led exercise classes in the context of prospective lockdowns: (1) develop a comprehensive contact detail register and plans for each group; (2) delivery of modified exercise classes remotely over lockdown; and (3) implementation of a nationwide IT education and resource program for older adults.

Editing of DNA Methylation Patterns Using CRISPR-Based Tools.

DNA methylation is an epigenetic modification with an established role in both normal cellular function and mammalian disease. Despite well-characterized associations between aberrant DNA methylation changes and gene expression, evidence for a causal relationship in this context has been difficult to obtain. Early techniques for interrogating the role of DNA methylation in the regulation of gene transcription lack specificity and, where more specific techniques such and ZNFs and TALEs have been developed, they are limited by their extensive cost and labor requirements. However, the recent advent of CRISPR-based technologies has revolutionized our potential for site-specific epigenomic editing. Here, we provide a detailed protocol for the design, construction, and utilization of a transient, CRISPR-based DNA methylation-editing system in mammalian cells.

Next-Generation Bisulfite Sequencing for Targeted DNA Methylation Analysis.

Bisulfite sequencing is the "gold-standard" technique for DNA methylation analysis. By combining bisulfite sequencing with high-throughput, next-generation sequencing technology, we can document methylation from many thousands of individual reads (equivalent to alleles or "cells"), for multiple target regions and from many samples simultaneously. Here, we describe a next-generation bisulfite-sequencing assay for targeted DNA methylation analysis which offers scope for the simultaneous interrogation of multiple genomic loci across numerous samples.

Radiocaesium accumulation and fluctuating asymmetry in the Japanese mitten crab, Eriocheir japonica, along a gradient of radionuclide contamination at Fukushima.

The 2011 Tohoku earthquake-tsunami and the subsequent nuclear accident at the Fukushima Dai-ichi Nuclear Power Station (FDNPS) led to large-scale radionuclide contamination of the marine and freshwater environment. Monitoring studies of marine food products in the Fukushima region have generally demonstrated a declining trend in radiocaesium concentrations. However, the accumulation and elimination of radiocaesium and potential biological effects remain poorly understood for freshwater biota inhabiting highly contaminated areas at Fukushima. Consequently, the present study aimed to assess radiocaesium accumulation and developmental effects on the commercially important catadromous Japanese mitten crab, Eriocheir japonica. E. japonica were collected from four sites along a gradient of radionuclide contamination 4-44 km in distance from the FDNPS in 2017. To determine potential developmental effects, fluctuating asymmetry (FA) was used as a measure of developmental stability. Combined 134Cs and 137Cs values for whole E. japonica from highly contaminated sites 4 and 16 km in distance from the FDNPS were 3040 ± 521 and 2250 ± 908 Bq kg-1 wet weight respectively, 30 and 22 times greater than the Japanese standard limit of 100 Bq kg-1. Estimated total dose rates based on radiocaesium concentrations in whole crabs and sediment ranged from 0.016 to 37.7 µGy h-1. No significant relationship between radiocaesium accumulation and FA was recorded, suggesting that chronic radiation exposure at Fukushima is not inducing developmental effects in E. japonica as measured using fluctuating asymmetry. Furthermore, estimated dose rates were below proposed regulatory limits where significant deleterious effects are expected. The present study will aid in the understanding of the long-term consequences of radiation exposure for non-human biota and the management of radioactively contaminated environments.

Epigenetic basis and targeting of cancer metastasis.

Despite the development of novel therapeutic approaches and improved clinical management, survival from metastatic disease remains poor. Indeed, metastasis accounts for the vast majority of cancer-related deaths. The metastatic cascade comprises a complex range of molecular events that cannot be explained by genetic aberrations alone; dynamic, epigenetic regulatory mechanisms are now being implicated as key drivers of successful metastasis. With the emergence of CRISPR-based epigenomic editing, it is now possible to investigate the direct role of locus-specific epigenetic alterations in metastatic progression. Here, we review the role of epigenetic mechanisms in cancer metastasis, explore recent developments in technologies for epigenomic investigation, and highlight the emerging applications of epigenomic editing technologies in the clinical management of cancer.

Locus-Specific DNA Methylation Editing in Melanoma Cell Lines Using a CRISPR-Based System.

DNA methylation is a key epigenetic modification implicated in the pathogenesis of numerous human diseases, including cancer development and metastasis. Gene promoter methylation changes are widely associated with transcriptional deregulation and disease progression. The advent of CRISPR-based technologies has provided a powerful toolkit for locus-specific manipulation of the epigenome. Here, we describe a comprehensive global workflow for the design and application of a dCas9-SunTag-based tool for editing the DNA methylation locus in human melanoma cells alongside protocols for downstream techniques used to evaluate subsequent methylation and gene expression changes in methylation-edited cells. Using transient system delivery, we demonstrate both highly efficacious methylation and demethylation of the EBF3 promoter, which is a putative epigenetic driver of melanoma metastasis, achieving up to a 304.00% gain of methylation and 99.99% relative demethylation, respectively. Furthermore, we employ a novel, targeted screening approach to confirm the minimal off-target activity and high on-target specificity of our designed guide RNA within our target locus.

Causal Algebras on Chain Event Graphs with Informed Missingness for System Failure.

Graph-based causal inference has recently been successfully applied to explore system reliability and to predict failures in order to improve systems. One popular causal analysis following Pearl and Spirtes et al. to study causal relationships embedded in a system is to use a Bayesian network (BN). However, certain causal constructions that are particularly pertinent to the study of reliability are difficult to express fully through a BN. Our recent work demonstrated the flexibility of using a Chain Event Graph (CEG) instead to capture causal reasoning embedded within engineers' reports. We demonstrated that an event tree rather than a BN could provide an alternative framework that could capture most of the causal concepts needed within this domain. In particular, a causal calculus for a specific type of intervention, called a remedial intervention, was devised on this tree-like graph. In this paper, we extend the use of this framework to show that not only remedial maintenance interventions but also interventions associated with routine maintenance can be well-defined using this alternative class of graphical model. We also show that the complexity in making inference about the potential relationships between causes and failures in a missing data situation in the domain of system reliability can be elegantly addressed using this new methodology. Causal modelling using a CEG is illustrated through examples drawn from the study of reliability of an energy distribution network.

Pancreas Cancer-Associated Pain Management.

Pain is highly prevalent in patients with pancreas cancer and contributes to the morbidity of the disease. Pain may be due to pancreatic enzyme insufficiency, obstruction, and/or a direct mass effect on nerves in the celiac plexus. Proper supportive care to decrease pain is an important aspect of the overall management of these patients. There are limited data specific to the management of pain caused by pancreatic cancer. Here we review the literature and offer recommendations regarding multiple modalities available to treat pain in these patients. The dissemination and adoption of these best supportive care practices can improve quantity and quality of life for patients with pancreatic cancer. IMPLICATIONS FOR PRACTICE: Pain management is important to improve the quality of life and survival of a patient with cancer. The pathophysiology of pain in pancreas cancer is complex and multifactorial. Despite tumor response to chemotherapy, a sizeable percentage of patients are at risk for ongoing cancer-related pain and its comorbid consequences. Accordingly, the management of pain in patients with pancreas cancer can be challenging and often requires a multifaceted approach.