Robust identification of interactions between heat-stress responsive genes in the chicken brain using Bayesian networks and augmented expression data.

Bayesian networks represent a useful tool to explore interactions within biological systems. The aims of this study were to identify a reduced number of genes associated with a stress condition in chickens (Gallus gallus) and to unravel their interactions by implementing a Bayesian network approach. Initially, one publicly available dataset (3 control vs. 3 heat-stressed chickens) was used to identify the stress signal, represented by 25 differentially expressed genes (DEGs). The dataset was augmented by looking for the 25 DEGs in other four publicly available databases. Bayesian network algorithms were used to discover the informative relationships between the DEGs. Only ten out of the 25 DEGs displayed interactions. Four of them were Heat Shock Proteins that could be playing a key role, especially under stress conditions, where maintaining the correct functioning of the cell machinery might be crucial. One of the DEGs is an open reading frame whose function is yet unknown, highlighting the power of Bayesian networks in knowledge discovery. Identifying an initial stress signal, augmenting it by combining other databases, and finally learning the structure of Bayesian networks allowed us to find genes closely related to stress, with the possibility of further exploring the system in future studies.

A two-step Bayesian network approach to identify key SNPs associated to multiple phenotypic traits in four purebred laying hen lines.

When purebred laying hen chicks hatch, they remain at a rearing farm until approximately 17 weeks of age, after which they are transferred to a laying farm. Chicks or pullets are removed from the flocks during these 17 weeks if they display any rearing abnormality. The aim of this study was to investigate associations between single nucleotide polymorphisms (SNPs) and rearing success of 4 purebred White Leghorns layer lines by implementing a Bayesian network approach. Phenotypic traits and SNPs of four purebred genetic White Leghorn layer lines were available for 23,000 rearing batches obtained between 2010 and 2020. Associations between incubation traits (clutch size, embryo mortality), rearing traits (genetic line, first week mortality, rearing abnormalities, natural death, rearing success, pullet flock age, and season) and SNPs were analyzed, using a two-step Bayesian Network (BN) approach. Furthermore, the SNPs were connected to their corresponding genes, which were further explored in bioinformatics databases. BN analysis revealed a total of 28 SNPs associated with some of the traits: ten SNPs were associated with clutch size, another 10 with rearing abnormalities, a single SNP with natural death, and seven SNPs with first week mortality. Exploration via bioinformatics databases showed that one of the SNPs (ENAH) had a protein predicted network composed of 11 other proteins. The major hub of this SNP was CDC42 protein, which has a role in egg production and reproduction. The results highlight the power of BNs in knowledge discovery and how their application in complex biological systems can help getting a deeper understanding of functionality underlying genetic variation of rearing success in laying hens. Improved welfare and production might result from the identified SNPs. Selecting for these SNPs through breeding could reduce stress and increase livability during rearing.

Consensus statement on the diagnosis and treatment of sclerosing diseases of the skin, Part 1: Localized scleroderma, systemic sclerosis and overlap syndromes.

The term 'sclerosing diseases of the skin' comprises specific dermatological entities, which have fibrotic changes of the skin in common. These diseases mostly manifest in different clinical subtypes according to cutaneous and extracutaneous involvement and can sometimes be difficult to distinguish from each other. The present consensus provides an update to the 2017 European Dermatology Forum Guidelines, focusing on characteristic clinical and histopathological features, diagnostic scores and the serum autoantibodies most useful for differential diagnosis. In addition, updated strategies for the first- and advanced-line therapy of sclerosing skin diseases are addressed in detail. Part 1 of this consensus provides clinicians with an overview of the diagnosis and treatment of localized scleroderma (morphea), and systemic sclerosis including overlap syndromes.

Treatment seeking behaviours, antibiotic use and relationships to multi-drug resistance: A study of urinary tract infection patients in Kenya, Tanzania and Uganda.

Antibacterial resistance (ABR) is a major public health threat. An important accelerating factor is treatment-seeking behaviour, including inappropriate antibiotic (AB) use. In many low- and middle-income countries (LMICs) this includes taking ABs with and without prescription sourced from various providers, including health facilities and community drug sellers. However, investigations of complex treatment-seeking, AB use and drug resistance in LMICs are scarce. The Holistic Approach to Unravel Antibacterial Resistance in East Africa (HATUA) Consortium collected questionnaire and microbiological data from adult outpatients with urinary tract infection (UTI)-like symptoms presenting at healthcare facilities in Kenya, Tanzania and Uganda. Using data from 6,388 patients, we analysed patterns of self-reported treatment seeking behaviours ('patient pathways') using process mining and single-channel sequence analysis. Among those with microbiologically confirmed UTI (n = 1,946), we used logistic regression to assess the relationship between treatment seeking behaviour, AB use, and the likelihood of having a multi-drug resistant (MDR) UTI. The most common treatment pathway for UTI-like symptoms in this sample involved attending health facilities, rather than other providers like drug sellers. Patients from sites in Tanzania and Uganda, where over 50% of patients had an MDR UTI, were more likely to report treatment failures, and have repeat visits to providers than those from Kenyan sites, where MDR UTI proportions were lower (33%). There was no strong or consistent relationship between individual AB use and likelihood of MDR UTI, after accounting for country context. The results highlight the hurdles East African patients face in accessing effective UTI care. These challenges are exacerbated by high rates of MDR UTI, suggesting a vicious cycle of failed treatment attempts and sustained selection for drug resistance. Whilst individual AB use may contribute to the risk of MDR UTI, our data show that factors related to context are stronger drivers of variations in ABR.

An engineered glove to follow finger function in rheumatoid arthritis: an observational prospective study.

The engineered Hand Test System (HTS) glove has shown high reliability in assessing the baseline functional status of rheumatoid arthritis (RA) hand. Starting from this achievement, the aim of the present observational prospective study was to assess the functionality of the single fingers of rheumatoid hand at follow-up. Eighty RA patients performed HTS glove tests at baseline and among these fifty-six patients were re-tested after 7 months. The HTS glove parameters [Touch Duration (TD), Movement Rate (MR), Inter Tapping Interval (ITI)] were correlated with disease activity and disability clinimetric indexes [Disease Activity Score 28 joint count-C-reactive protein (DAS28-CRP), Clinical Disease Activity Index (CDAI), Simplified Disease Activity Index (SDAI), Health Assessment Questionnaire-Disability Index (HAQ-DI), grip strength, visual analogue scale of pain (VAS), patient global assessment (PGA)], and with laboratory values. HTS glove parameters (TD, ITI, and MR) showed statistically significant correlations with clinimetric and clinical indexes at both time points (p < 0.05). During follow-up, a statistically significant variation of all HTS glove parameters for the fingers that have performed both the worst or best HTS test at baseline was detected (p < 0.05), while the mean HTS glove parameter values by considering all fingers did not show a statistically significant variation over time, as well as the traditional clinimetric indexes. Besides the objective role in assessing the RA hand function by integrating the traditional clinimetric indexes, the HTS glove seems a useful tool for evaluating worst or best finger function during time by measuring the movement speed.

The development and acceptability of an educational and training intervention for recruiters to neonatal trials: the TRAIN project.

BACKGROUND: Suboptimal or slow recruitment affects 30-50% of trials. Education and training of trial recruiters has been identified as one strategy for potentially boosting recruitment to randomised controlled trials (hereafter referred to as trials). The Training tRial recruiters, An educational INtervention (TRAIN) project was established to develop and assess the acceptability of an education and training intervention for recruiters to neonatal trials. In this paper, we report the development and acceptability of TRAIN. METHODS: TRAIN involved three sequential phases, with each phase contributing information to the subsequent phase(s). These phases were 1) evidence synthesis (systematic review of the effectiveness of training interventions and a content analysis of the format, content, and delivery of identified interventions), 2) intervention development using a Partnership (co-design/co-creation) approach, and 3) intervention acceptability assessments with recruiters to neonatal trials. RESULTS: TRAIN, accompanied by a comprehensive intervention manual, has been designed for online or in-person delivery. TRAIN can be offered to recruiters before trial recruitment begins or as refresher sessions during a trial. The intervention consists of five core learning outcomes which are addressed across three core training units. These units are the trial protocol (Unit 1, 50 min, trial-specific), understanding randomisation (Unit 2, 5 min, trial-generic) and approaching and engaging with parents (Unit 3, 70 min, trial-generic). Eleven recruiters to neonatal trials registered to attend the acceptability assessment training workshops, although only four took part. All four positively valued the training Units and resources for increasing recruiter preparedness, knowledge, and confidence. More flexibility in how the training is facilitated, however, was noted (e.g., training divided across two workshops of shorter duration). Units 2 and 3 were considered beneficial to incorporate into Good Clinical Practice Training or as part of induction training for new staff joining neonatal units. CONCLUSION: TRAIN offers a comprehensive co-produced training and education intervention for recruiters to neonatal trials. TRAIN was deemed acceptable, with minor modification, to neonatal trial recruiters. The small number of recruiters taking part in the acceptability assessment is a limitation. Scale-up of TRAIN with formal piloting and testing for effectiveness in a large cluster randomised trial is required.

Embryo selection through artificial intelligence versus embryologists: a systematic review.

STUDY QUESTION: What is the present performance of artificial intelligence (AI) decision support during embryo selection compared to the standard embryo selection by embryologists? SUMMARY ANSWER: AI consistently outperformed the clinical teams in all the studies focused on embryo morphology and clinical outcome prediction during embryo selection assessment. WHAT IS KNOWN ALREADY: The ART success rate is ∼30%, with a worrying trend of increasing female age correlating with considerably worse results. As such, there have been ongoing efforts to address this low success rate through the development of new technologies. With the advent of AI, there is potential for machine learning to be applied in such a manner that areas limited by human subjectivity, such as embryo selection, can be enhanced through increased objectivity. Given the potential of AI to improve IVF success rates, it remains crucial to review the performance between AI and embryologists during embryo selection. STUDY DESIGN SIZE DURATION: The search was done across PubMed, EMBASE, Ovid Medline, and IEEE Xplore from 1 June 2005 up to and including 7 January 2022. Included articles were also restricted to those written in English. Search terms utilized across all databases for the study were: ('Artificial intelligence' OR 'Machine Learning' OR 'Deep learning' OR 'Neural network') AND ('IVF' OR 'in vitro fertili*' OR 'assisted reproductive techn*' OR 'embryo'), where the character '*' refers the search engine to include any auto completion of the search term. PARTICIPANTS/MATERIALS SETTING METHODS: A literature search was conducted for literature relating to AI applications to IVF. Primary outcomes of interest were accuracy, sensitivity, and specificity of the embryo morphology grade assessments and the likelihood of clinical outcomes, such as clinical pregnancy after IVF treatments. Risk of bias was assessed using the Modified Down and Black Checklist. MAIN RESULTS AND THE ROLE OF CHANCE: Twenty articles were included in this review. There was no specific embryo assessment day across the studies-Day 1 until Day 5/6 of embryo development was investigated. The types of input for training AI algorithms were images and time-lapse (10/20), clinical information (6/20), and both images and clinical information (4/20). Each AI model demonstrated promise when compared to an embryologist's visual assessment. On average, the models predicted the likelihood of successful clinical pregnancy with greater accuracy than clinical embryologists, signifying greater reliability when compared to human prediction. The AI models performed at a median accuracy of 75.5% (range 59-94%) on predicting embryo morphology grade. The correct prediction (Ground Truth) was defined through the use of embryo images according to post embryologists' assessment following local respective guidelines. Using blind test datasets, the embryologists' accuracy prediction was 65.4% (range 47-75%) with the same ground truth provided by the original local respective assessment. Similarly, AI models had a median accuracy of 77.8% (range 68-90%) in predicting clinical pregnancy through the use of patient clinical treatment information compared to 64% (range 58-76%) when performed by embryologists. When both images/time-lapse and clinical information inputs were combined, the median accuracy by the AI models was higher at 81.5% (range 67-98%), while clinical embryologists had a median accuracy of 51% (range 43-59%). LIMITATIONS REASONS FOR CAUTION: The findings of this review are based on studies that have not been prospectively evaluated in a clinical setting. Additionally, a fair comparison of all the studies were deemed unfeasible owing to the heterogeneity of the studies, development of the AI models, database employed and the study design and quality. WIDER IMPLICATIONS OF THE FINDINGS: AI provides considerable promise to the IVF field and embryo selection. However, there needs to be a shift in developers' perception of the clinical outcome from successful implantation towards ongoing pregnancy or live birth. Additionally, existing models focus on locally generated databases and many lack external validation. STUDY FUNDING/COMPETING INTERESTS: This study was funded by Monash Data Future Institute. All authors have no conflicts of interest to declare. REGISTRATION NUMBER: CRD42021256333.

Dysregulated endothelial cell markers in systemic lupus erythematosus: a systematic review and meta-analysis.

OBJECTIVES: To perform a systematic literature review and meta-analysis on endothelial cell (EC) markers that are involved and dysregulated in systemic lupus erythematosus (SLE) in relation to disease activity, as EC dysregulation plays a major role in the development of premature atherosclerosis in SLE. METHODS: Search terms were entered into Embase, MEDLINE, Web of Science, Google Scholar and Cochrane. Inclusion criteria were 1) studies published after 2000 reporting measurements of EC markers in serum and/or plasma of SLE patients (diagnosed according to ACR/SLICC criteria), 2) English language peer reviewed articles, and 3) disease activity measurement. For meta-analysis calculations, the Meta-Essentials tool by Erasmus Research Institute and of Management (ERIM) was used. Only those EC markers, which were 1) reported in at least two articles and 2) reported a correlation coefficient (i.e. Spearman's rank or Pearson's) between the measured levels of the EC marker and disease activity were included. For meta-analyses, a fixed effect model was used. RESULTS: From 2133 hits, 123 eligible articles were selected. The identified SLE-related endothelial markers were involved in EC activation, EC apoptosis, disturbed angiogenesis, defective vascular tone control, immune dysregulation and coagulopathy. Meta-analyses of primarily cross-sectional studies showed significant associations between marker levels and disease activity for the following endothelial markers: Pentraxin-3, Thrombomodulin, VEGF, VCAM-1, ICAM-1, IP-10 and MCP-1. Dysregulated EC markers without associations with disease activity were: Angiopoeitin-2, vWF, P-Selectin, TWEAK and E-Selectin. CONCLUSIONS: We provide a complete literature overview for dysregulated EC markers in SLE comprising a wide range of different EC functions. SLE-induced EC marker dysregulation was seen with, but also without, association with disease activity. This study provides some clarity in the eminent complex field of EC markers as biomarkers for SLE. Longitudinal data on EC markers in SLE are now needed to guide us more in unravelling the pathophysiology of premature atherosclerosis and cardiovascular events in SLE patients.

Genetic characterization of the zoonotic parasite Ancylostoma caninum in the central and eastern United States.

Ancylostoma caninum is the most common nematode parasite of dogs in the United States. The present study aimed to describe the molecular epidemiology of A. caninum isolates from the central and eastern states of the United States using the partial mitochondrial cytochrome oxidase (cox1) gene and to compare them with those reported globally. We isolated eggs from faecal samples of dogs and characterized each isolate based on cox1 sequences. A total of 60 samples originating from Kansas, Iowa, New York, Florida and Massachusetts were included. 25 haplotypes were identified in the United States dataset with high haplotype diversity (0.904). Sequence data were compared to sequences from other world regions available in GenBank. Global haplotype analysis demonstrated 35 haplotypes with a haplotype diversity of 0.931. Phylogenetic and network analysis provide evidence for the existence of moderate geographical structuring of A. caninum haplotypes. Our results provide an updated summary of A. caninum haplotypes and data for neutral genetic markers with utility for tracking hookworm populations. Sequences have been deposited in GenBank (ON980650-ON980674). Further studies of isolates from other regions are essential to understand the genetic diversity of this parasite.

The role of outpatient needle arthroscopy in the diagnosis and management of musculoskeletal complaints: A systematic review of the Arthrex NanoScope.

BACKGROUND: The aim was to review the literature regarding needle arthroscopy using the Arthrex NanoScope system and evaluate: (1) the diagnostic indications, utility, and efficacy compared to conventional methods, and (2) the therapeutic indications, safety, and reported outcomes. METHODS: Searches of three databases (MEDLINE, Embase and PubMed) were conducted in November 2021 using MeSH terms: 'needle arthroscopy', 'human', 'in office arthroscopy', 'needle arthroscope', 'nanoscopic', 'surgery', 'nanoscope' and 'percutaneous arthroscopy'. The included studies were catalogued, quality-assessed using Methodological Index for Non-Randomised Studies (MINORS), and analysed using the Cochrane data collection templates for randomised control trials (RCT) and non-randomised control trials (non-RCT). The majority of studies were non-numerical and were examined using qualitative analysis. RESULTS: The search yielded 314 studies, 22 of which were included for analysis. MINORS assessment was applicable to four studies. Mean MINORS was 10.7/16 with the most frequent limitations being lack of unbiased endpoint or sample size calculation. The level of evidence ranged from level IV-V. Diagnostic and therapeutic indications were described in relation to the: knee (n = 10); shoulder (n = 6); foot/ankle (n = 3); elbow (n = 2), and miscellaneous (n = 1). CONCLUSIONS: Needle arthroscopy can augment the diagnostic process in patients presenting with musculoskeletal complaints, and may provide benefits in terms of diagnostic accuracy, cost efficiency, timeliness of investigation, and a visually impactful patient-centred consultation. Therapeutic interventions are reported by a small number of pioneer groups who report some benefits over conventional arthroscopy. The available literature remains small and of low quality, and more evidence is needed with regards to patient selection, efficacy, safety, and cost. LEVEL OF EVIDENCE: Level V (based on the weakest study included in the Systematic Review).

Training support workers about the overmedication of people with intellectual disabilities: an Australian pre-post pilot study.

BACKGROUND: There is evidence that psychotropic medications are overprescribed and overused to manage behaviours of concern for people with intellectual disabilities. Disability support workers and support staff lack education and training on the administration and safety of psychotropic medication use. This study aimed to test the applicability and preliminary efficacy of SPECTROM, an education programme developed in the UK, in an Australian context. METHODS: The training comprises two parts: Module 1 encompasses psychotropic medications, their use and side effects. Module 2 focuses on non-pharmacological interventions for supporting people with behaviours of concern. Thirty-three participants attended the training course and completed pre-training and post-training surveys on the Psychotropic Knowledge Questionnaire and Management of Aggression and Violence Attitude Scale-Revised at four time points: pre-training, 2 weeks, 3 months and 5 months post-training. RESULTS: Psychotropic Knowledge Questionnaire scores showed statistically significant post-training improvement at all post-training time points (P < 0.05). Management of Aggression and Violence Attitude Scale-Revised scores were high at pre-training and did not change significantly at any of the post-training survey time points. A 2-week post-training feedback questionnaire reported 80% agreement that the training programme was appropriate, useful and valid. Only 36% of participants completed questionnaires at all time points. CONCLUSIONS: SPECTROM training increased staff knowledge of psychotropic medications, yet loss of participants was high. Further refinement of the applicability of the training for the Australian context and evaluation of the feasibility of implementation, clinical and cost-effectiveness of the programme are required.

Are Geriatrics-Focused Primary Care Clinics Better at Diagnosing Dementia Than Traditional Clinics? A Matched Cohort Study.

BACKGROUND: Dementia and mild cognitive impairment (MCI) are prevalent but underdiagnosed. OBJECTIVE: To compare new dementia/MCI diagnosis rates in geriatrics-focused primary care clinics and traditional primary care clinics. DESIGN: Secondary analysis of a prospective matched cohort study that spanned 2017-2021. PARTICIPANTS: Community-dwelling Veterans over 65 receiving primary care in a geriatrics-focused medical home (GeriPACT) or traditional primary care home (PACT) at one of 57 Veterans Affairs sites. We excluded individuals with a documented diagnosis of dementia or MCI in the year prior to enrollment. MAIN MEASURES: Diagnoses obtained from EHR. Cognitive status was assessed using modified Telephone Interview for Cognitive Status (mTICS) tool. KEY RESULTS: The 470 participants included in this analysis were predominantly white, non-Hispanic males with an average age of 80.3 years. 9.4% of participants received a diagnosis of dementia/MCI after 24 months: 11.5% in GeriPACT and 7.2% in PACT. Adjusted OR for dementia/MCI diagnosis based on GeriPACT exposure was 1.47 (95% CI 0.65-3.29). Low mTICS score (≤ 27) (OR 4.89, 95% CI 2.36-10.13) and marital status (married/partnered) (OR 1.89, CI 0.99-3.59) were independent predictors of dementia/MCI diagnosis. When stratified by cognitive status: diagnosis rates were 20.8% in GeriPACT and 16.7% in PACT among those who scored lower on the cognitive assessment (mTICS ≤ 27); 7.4% in GeriPACT and 3.6% in PACT among those who scored higher (mTICS > 27). The OR for new dementia/MCI diagnosis in GeriPACT was 1.19 (95% CI 0.49-2.91) among those with a low mTICS score and 1.85 (95% CI 0.70-4.88) among those with a higher mTICS score. CONCLUSIONS: Observed rates of new dementia/MCI diagnosis were higher in GeriPACT, but with considerable uncertainty around estimates. Geriatrics-focused primary care clinics may be a promising avenue for improving the detection of dementia in older adults, but further larger studies are needed to confirm this relationship.

Emerging nailfold capillaroscopic patterns in COVID-19: from acute patients to survivors.

The SARS-CoV-2 infection causing the Coronavirus disease-19 (COVID-19) is characterized by a broad range of clinical manifestations, implicating microvascular damage with endothelial dysfunction and different organ involvement.

Treatment seeking behaviours, antibiotic use and relationships to multi-drug resistance: A study of urinary tract infection patients in Kenya, Tanzania and Uganda.

Antibacterial resistance (ABR) is a major public health threat. An important accelerating factor is treatment-seeking behaviours, including inappropriate antibiotic (AB) use. In many low- and middle-income countries (LMICs) this includes taking ABs with and without prescription sourced from various providers, including health facilities and community drug sellers. However, investigations of complex treatment-seeking, AB use and drug resistance in LMICs are scarce. The Holistic Approach to Unravel Antibacterial Resistance in East Africa (HATUA) Consortium collected questionnaire and microbiological data from 6,827 adult outpatients with urinary tract infection (UTI)-like symptoms presenting at healthcare facilities in Kenya, Tanzania and Uganda. Among 6,388 patients we analysed patterns of self-reported treatment seeking behaviours ('patient pathways') using process mining and single-channel sequence analysis. Of those with microbiologically confirmed UTI (n=1,946), we used logistic regression to assessed the relationship between treatment seeking behaviour, AB use, and likelihood of having a multi-drug resistant (MDR) UTI. The most common treatment pathways for UTI-like symptoms included attending health facilities, rather than other providers (e.g. drug sellers). Patients from the sites sampled in Tanzania and Uganda, where prevalence of MDR UTI was over 50%, were more likely to report treatment failures, and have repeated visits to clinics/other providers, than those from Kenyan sites, where MDR UTI rates were lower (33%). There was no strong or consistent relationship between individual AB use and risk of MDR UTI, after accounting for country context. The results highlight challenges East African patients face in accessing effective UTI treatment. These challenges increase where rates of MDR UTI are higher, suggesting a reinforcing circle of failed treatment attempts and sustained selection for drug resistance. Whilst individual behaviours may contribute to the risk of MDR UTI, our data show that factors related to context are stronger drivers of ABR.

Visual outcomes and predictors in optic pathway glioma: a single centre study.

BACKGROUND/AIMS: Optic pathway gliomas (OPGs) may cause progressive visual loss despite chemotherapy. Newer, less toxic treatments might be given earlier, depending on visual prognosis. We aimed to investigate the prognostic value of visual evoked potentials (VEP) and optical coherence tomography (OCT). METHODS: A retrospective study of OPG patients (treated 2003-2017) was conducted. Primary outcome was PEDIG category visual acuity in better and worse eyes (good < = 0.2, moderate 0.3-0.6 and poor > = 0.7 logMAR). Binary logistic regression analysis was used to identify predictors of these outcomes. RESULTS: 60 patients (32 Neurofibromatosis type 1 [NF1] and 28 sporadic) had median presentation age 49 months (range 17-183) (NF1) and 27 months (range 4-92) (sporadic). Median follow up was 82 months (range 12-189 months). At follow up 24/32 (75%) of NF1 children and 14/28 (50%) of sporadic children had good better eye visual acuity and 11/32 (34%) of NF1 children and 15/28 (54%) of sporadics had poor worse eye acuity. Mean peripapillary retinal nerve fibre layer (RNFL) thickness predicted good better eye final acuity (OR 0.799, 95%CI 0.646-0.987, p = 0.038). Presenting with visual symptoms (OR 0.22 95% CI 0.001-0.508, p = 0.017) and poorer VEP scores (OR 2.35 95% CI 1.1-5.03, p = 0.027) predicted poor worse eye final acuity. 16 children had homonymous hemianopias at follow up, predicted by poor presenting binocular VEP score (OR 1.449 95%CI 1.052-1.995, p = 0.02). CONCLUSIONS: We found that both RNFL thickness on OCT and VEP were useful in predicting future visual acuity and vision and potentially in planning treatment. We had a high prevalence of homonymous hemianopia.

Patient Preparation and Radiation Protection Guidance for Adult Patients Undergoing Radioiodine Treatment for Thyroid Cancer in the UK.

Radioactive iodine is a highly effective treatment for thyroid cancer and has now been used in clinical practice for more than 80 years. In general, the treatment is well tolerated. However, it can be logistically quite complex for patients due to the need to reduce iodine intake and achieve high levels of thyroid-stimulating hormone prior to treatment. Radiation protection precautions must also be taken to protect others from unnecessary radiation exposure following treatment. It has been well documented by thyroid cancer patient support groups that there is significant variation in practice across the UK. It is clear that some patients are being asked to observe unnecessarily burdensome restrictions that make it more difficult for them to tolerate the treatment. At the instigation of these support groups, a multidisciplinary group was assembled to examine the evidence and generate guidance on best practice for the preparation of patients for this treatment and the management of subsequent radiation protection precautions, with a focus on personalising the advice given to individual patients. The guidance includes advice about managing particularly challenging situations, for example treating patients who require haemodialysis. We have also worked together to produce a patient information leaflet covering these issues. We hope that the guidance document and patient information leaflet will assist centres in improving our patients' experience of receiving radioactive iodine. The patient information sheet is available as Supplementary Material to this article.

Treatment of missing data in Bayesian network structure learning: an application to linked biomedical and social survey data.

BACKGROUND: Availability of linked biomedical and social science data has risen dramatically in past decades, facilitating holistic and systems-based analyses. Among these, Bayesian networks have great potential to tackle complex interdisciplinary problems, because they can easily model inter-relations between variables. They work by encoding conditional independence relationships discovered via advanced inference algorithms. One challenge is dealing with missing data, ubiquitous in survey or biomedical datasets. Missing data is rarely addressed in an advanced way in Bayesian networks; the most common approach is to discard all samples containing missing measurements. This can lead to biased estimates. Here, we examine how Bayesian network structure learning can incorporate missing data. METHODS: We use a simulation approach to compare a commonly used method in frequentist statistics, multiple imputation by chained equations (MICE), with one specific for Bayesian network learning, structural expectation-maximization (SEM). We simulate multiple incomplete categorical (discrete) data sets with different missingness mechanisms, variable numbers, data amount, and missingness proportions. We evaluate performance of MICE and SEM in capturing network structure. We then apply SEM combined with community analysis to a real-world dataset of linked biomedical and social data to investigate associations between socio-demographic factors and multiple chronic conditions in the US elderly population. RESULTS: We find that applying either method (MICE or SEM) provides better structure recovery than doing nothing, and SEM in general outperforms MICE. This finding is robust across missingness mechanisms, variable numbers, data amount and missingness proportions. We also find that imputed data from SEM is more accurate than from MICE. Our real-world application recovers known inter-relationships among socio-demographic factors and common multimorbidities. This network analysis also highlights potential areas of investigation, such as links between cancer and cognitive impairment and disconnect between self-assessed memory decline and standard cognitive impairment measurement. CONCLUSION: Our simulation results suggest taking advantage of the additional information provided by network structure during SEM improves the performance of Bayesian networks; this might be especially useful for social science and other interdisciplinary analyses. Our case study show that comorbidities of different diseases interact with each other and are closely associated with socio-demographic factors.

N-strain epidemic model using bond percolation.

In this paper we examine the emergent structures of random networks that have undergone bond percolation an arbitrary, but finite, number of times. We define two types of sequential branching processes: a competitive branching process, in which each iteration performs bond percolation on the residual graph (RG) resulting from previous generations, and a collaborative branching process, where percolation is performed on the giant connected component (GCC) instead. We investigate the behavior of these models, including the expected size of the GCC for a given generation, the critical percolation probability, and other topological properties of the resulting graph structures using the analytically exact method of generating functions. We explore this model for Erdos-Renyi and scale-free random graphs. This model can be interpreted as a seasonal N-strain model of disease spreading.

Practical application of a Bayesian network approach to poultry epigenetics and stress.

BACKGROUND: Relationships among genetic or epigenetic features can be explored by learning probabilistic networks and unravelling the dependencies among a set of given genetic/epigenetic features. Bayesian networks (BNs) consist of nodes that represent the variables and arcs that represent the probabilistic relationships between the variables. However, practical guidance on how to make choices among the wide array of possibilities in Bayesian network analysis is limited. Our study aimed to apply a BN approach, while clearly laying out our analysis choices as an example for future researchers, in order to provide further insights into the relationships among epigenetic features and a stressful condition in chickens (Gallus gallus). RESULTS: Chickens raised under control conditions (n = 22) and chickens exposed to a social isolation protocol (n = 24) were used to identify differentially methylated regions (DMRs). A total of 60 DMRs were selected by a threshold, after bioinformatic pre-processing and analysis. The treatment was included as a binary variable (control = 0; stress = 1). Thereafter, a BN approach was applied: initially, a pre-filtering test was used for identifying pairs of features that must not be included in the process of learning the structure of the network; then, the average probability values for each arc of being part of the network were calculated; and finally, the arcs that were part of the consensus network were selected. The structure of the BN consisted of 47 out of 61 features (60 DMRs and the stressful condition), displaying 43 functional relationships. The stress condition was connected to two DMRs, one of them playing a role in tight and adhesive intracellular junctions in organs such as ovary, intestine, and brain. CONCLUSIONS: We clearly explain our steps in making each analysis choice, from discrete BN models to final generation of a consensus network from multiple model averaging searches. The epigenetic BN unravelled functional relationships among the DMRs, as well as epigenetic features in close association with the stressful condition the chickens were exposed to. The DMRs interacting with the stress condition could be further explored in future studies as possible biomarkers of stress in poultry species.