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Health-related behaviours (HRBs) have been considered one of the most critical public health issues, especially for those with special educational needs (SEN). Previous research suggests that health-related behaviours are highly likely to impact well-being and academic achievement. Diet is a crucial health-related behaviour that needs to be investigated along with factors such as sleep and exercise. The present study used data from the Cornish Academies Project, and secondary analyses were conducted to investigate associations between health-related behaviour and well-being and academic performance of secondary students with SEN. The current study sample was 308 students with SEN (mean age, 13.5 years, SD 1.44 years). The study was longitudinal, with time points 6 months apart, and a multivariate design with data from three academies in Cornwall, United Kingdom. The Diet and Behaviour Scale (DABS) measured diet and lifestyle (physical activity, sleep, and general health). Logistic regressions on the time one data showed a significant relationship between good general health and long sleep, eating healthy foods, and avoiding junk food. High exercise and high attendance decreased the likelihood of low attainment. Long sleep was associated with better conduct at time one and time two. There was a significant association between high consumption of healthy foods and good general health and better educational attainment at time two. Longitudinal cross-lagged analyses showed that high tea and high total weekly caffeine consumption at time one were associated with anxiety at time two. In addition, high cola consumption at time one was associated with high depression at time two. Findings from the current study increase our knowledge regarding associations between HRB and well-being, and academic performance in secondary school pupils with SEN, though the results need to be explored further to determine the precise nature of the relationship.

Cosmic rays entering the Earth's atmosphere produce showers of secondary particles such as protons, neutrons, and muons. The interaction of these particles with oxygen-16 (16O) in minerals such as ice and quartz can produce carbon-14 (14C). In glacial ice, 14C is also incorporated through trapping of 14C-containing atmospheric gases (14CO2, 14CO, and 14CH4). Understanding the production rates of in situ cosmogenic 14C is important to deconvolve the in situ cosmogenic and atmospheric 14C signals in ice, both of which contain valuable paleoenvironmental information. Unfortunately, the in situ 14C production rates by muons (which are the dominant production mechanism at depths of >6 m solid ice equivalent) are uncertain. In this study, we use measurements of in situ 14C in ancient ice (>50 ka) from the Taylor Glacier, an ablation site in Antarctica, in combination with a 2D ice flow model to better constrain the compound-specific rates of 14C production by muons and the partitioning of in situ 14C between CO2, CO, and CH4. Our measurements show that 33.7 % (±11.4 %; 95 % confidence interval) of the produced cosmogenic 14C forms 14CO and 66.1 % (±11.5 %; 95 % confidence interval) of the produced cosmogenic 14C forms 14CO2. 14CH4 represents a very small fraction (%) of the total. Assuming that the majority of in situ muogenic 14C in ice forms 14CO2, 14CO, and 14CH4, we also calculated muogenic 14C production rates that are lower by factors of 5.7 (3.6–13.9; 95 % confidence interval) and 3.7 (2.0–11.9; 95 % confidence interval) for negative muon capture and fast muon interactions, respectively, when compared to values determined in quartz from laboratory studies (Heisinger et al., 2002a, b) and in a natural setting (Lupker et al., 2015). This apparent discrepancy in muogenic 14C production rates in ice and quartz currently lacks a good explanation and requires further investigation.

Ground-level particle detection is now a well-established approach to TeV gamma-ray astronomy. Detection of Cherenkov light produced in water-filled detection units is a proven and cost-effective method. Here we discuss the optimization of the units towards the future Southern Wide-field Gamma-ray Observatory (SWGO). In this context, we investigate a new type of configuration in which each water Cherenkov detector (WCD) unit in the array comprises two chambers with black or reflective walls and a single photomultiplier tube (PMT) in each chamber. We find that this is a cost-effective approach that improves the performance of the WCD array with respect to current approaches. A shallow lower chamber with a PMT facing downwards enables muon tagging and the identification of hadron-induced air showers, which are the primary source of background in gamma-ray astronomy. We investigate how gamma/hadron separation power and achievable angular resolution depend on the geometry and wall reflectivity of the detector units in this configuration. We find that excellent angular resolution, background rejection power and low-energy response are achievable in this double-layer configuration, with the aid of reflective surfaces in both chambers., 17 pages, 20 figures

This essay is a study in typological exegesis across the testaments of the Christian Bible. Specifically, in light of early Christian conviction that Jesus of Nazareth is the anointed son of David, we seek to understand how the story of David’s violent murder of Uriah the Hittite and rape of Bathsheba figure within a canonical framework in which Jesus is presented as David’s heir and yet also as the one in whom the Davidic legacy of violent betrayal reaches fulfillment. Beginning with a literary reading of David’s sins and their legacy in Samuel–Kings, the essay moves to consider the under-studied reference to Uriah and his wife in the Matthean genealogy and its import for Matthew’s presentation of Jesus as a “son of David.” We suggest that in the gospel tradition, David’s violence concentrates in the obscure figure of Judas Iscariot, who, like Uriah the Hittite, appears last in the roll of individuals faithful to their Israelite king (Matt 10:4; Mark 3:19; Luke 6:16; see 2 Sam 23:39). In contrast to Uriah’s fidelity to David—but in step with David’s betrayal of Uriah—Judas’s treachery demonstrates why typological readings of Jesus as the Davidic heir remain necessarily complex. The Gospels identify Jesus as a new son of David, and in so doing, they also present him as one who transforms that scriptural paradigm through his symbolic reversal of David’s sin.

Les activités de la Cochrane sont polymorphes et reposent toutes sur le volontariat de personnes scientifiquement indépendantes. L’approche traditionnelle de diffusion de la connaissance basée sur la publication de revues systématiques Cochrane n’est pas suffisante, en particulier en médecine d’urgence et en réanimation. Une démarche de Knowledge Translation (KT) est indispensable. Le réseau des soins aigus et d'urgence de la Cochrane est particulièrement engagé dans cette activité via le review group Cochrane Emergency and Critical Care, qui produit des revues systématiques ciblées sur les malades en soins critiques et via le field Cochrane Pre-hospital and Emergency Care qui assure la diffusion de l’information médicale produite par la Cochrane et recense les priorités scientifiques liées au terrain. Cet article expose la méthodologie utilisée par les deux groupes car elle est standardisée et articule des étapes individuelles et collectives (pour la rédaction des revues systématiques comme pour le travail de priorisation). Une démarche active d’optimisation de la connexion entre production scientifique et terrain est indispensable dans des situations sanitaires d’exception (SSE) comme la pandémie COVID-19. Une démarche « d’Integrated Knowledge Translation » (IKT) s’est mise en place pour compléter les activités traditionnelles des groupes. Cet article fait le point sur les adaptations opérées dans ce contexte scientifique particulier. Rendre transparente la méthodologie de travail des deux groupes Cochrane permet d’assurer leur fiabilité scientifique, y compris en SSE. Cette transparence permet également de proposer un modèle de fonctionnement reproductible dans d’autres secteurs qui nécessitent une démarche de KT et d’IKT.

The purpose of this study was to model the visual ergonomic factors affecting performance in human-computer interaction. A cross-sectional study using structural equation modelling was performed with a sample of 200 participants. The measuring instruments included the office lighting survey questionnaire, performance assessment questionnaires, visual ergonomics assessment and an eye discomfort assessment. The hypothetical model evaluated workplace lighting status and visual ergonomics as precursors, performance as the output and eye discomfort as a mediator. The results showed that eye discomfort directly affected performance. Visual ergonomics also had a significant direct effect on eye discomfort. The final model suggested a significant new path between the quality of lighting and visual ergonomics. Also, the quality of lighting had an indirect effect on eye discomfort and performance, and the effect of visual ergonomics on performance was the same. Improving the lighting quality and visual ergonomics can reduce eye discomfort and increase performance.

The use of technology in medicine has grown exponentially because of the technological advancements allowing the digitization of medical data and optimization of their processing to extract multiple features of significant clinical relevance. Radiology has benefited substantially from technical developments and innovations, such as artificial intelligence (AI). This article describes the subsets of AI methods relevant to gastrointestinal and hepatic imaging with examples. We also discuss the evolution of AI, the current challenges, and prospects for further development in the field.

The optimal coronary artery disease surveillance strategy for end-stage renal disease patients being evaluated for kidney transplantation is unknown. It is unclear what risk factors are associated with the development of new-onset perfusion abnormalities on serial myocardial perfusion imaging. Potential kidney transplant recipients who underwent 2 myocardial perfusion imaging studies at Emory University Hospital between January 2010 and December 2019 were identified. We assessed the frequency of development of any new perfusion defect and development of moderate to severe ischemia (reversible perfusion defect10%) on serial imaging. Finally, we identified the clinical and imaging factors associated with new perfusion defects and explored the association between new perfusion defects and all-cause mortality. History of myocardial infarction (MI) and peripheral artery disease was associated with an increased risk of developing a new perfusion defect. History of MI was also associated with the risk of developing moderate-severe ischemia. Female patients were less likely to develop new perfusion defects or moderate-severe ischemia. There was no association between either outcome and all-cause mortality. In conclusion, a history of MI, peripheral artery disease, and male gender are risk factors for developing new perfusion defects, although only the history of MI and male gender predict moderate to severe ischemia. Interval development of any abnormal perfusion is not associated with increased mortality.

Ireland has significantly increased its climate mitigation ambition, with a recent government commitment to reduce greenhouse gases by an average of 7 % yr−1 in the period to 2030 and a net-zero target for 2050, underpinned by a series of 5-year carbon budgets. Energy systems optimisation modelling (ESOM) is a widely used tool to inform pathways to address long-term energy challenges. This article describes a new ESOM developed to inform Ireland's energy system decarbonisation challenge. The TIMES-Ireland Model (TIM) is an optimisation model of the Irish energy system, which calculates the cost-optimal fuel and technology mix to meet future energy service demands in the transport, buildings, industry, and agriculture sectors, while respecting constraints in greenhouse gas emissions, primary energy resources, and feasible deployment rates. TIM is developed to take into account Ireland's unique energy system context, including a very high potential for offshore wind energy and the challenge of integrating this on a relatively isolated grid, a very ambitious decarbonisation target in the period to 2030, the policy need to inform 5-year carbon budgets to meet policy targets, and the challenge of decarbonising heat in the context of low building stock thermal efficiency and high reliance on fossil fuels. To that end, model features of note include future-proofing with flexible temporal and spatial definitions, with a possible hourly time resolution, unit commitment and capacity expansion features in the power sector, residential and passenger transport underpinned by detailed bottom-up sectoral models, cross-model harmonisation, and soft-linking with demand and macro models. The paper also outlines a priority list of future model developments to better meet the challenge of deeply decarbonising energy supply and demand, taking into account the equity, cost-effectiveness, and technical feasibility. To support transparency and openness in decision-making, TIM is available to download under a Creative Commons licence.

Basal icequakes are generated as a glacier slides over its underlying bedrock, and the stick-slip motion of constant loading and unloading releases shear stresses that produce these very small magnitude (ML < 0) glacial microseisms. Detecting and locating nucleation of these fine-scale icequakes can provide highly useful insights into the deformation processes occurring at the bed and consequently the mechanisms governing glacier flow. We present icequake data derived from a seismic array installed at the grounding line of the Rutford Ice Stream in West Antarctica by Penn State University and the British Antarctic Survey during the 2018/19 austral summer. The region’s natural source seismicity was first processed using the earthquake detection and location software QuakeMigrate and the events were relatively relocated using HypoDD/GrowClust. We then clustered the events into sticky spot clusters using the unsupervised clustering algorithm DBSCAN, and finally from the clusters we selected “model” waveforms to perform template matching on the original seismic traces to create methodically comprehensive high-resolution icequake catalogs at the grounding line of Rutford. We present our methodology including the complete processing pipeline (supplemented by developed supporting open-source scripts) along with key tuning parameters, and describe how our catalogs were used to resolve glacier sliding patterns and key topographical features and characteristics of the bed like sticky spots. We additionally explore the effects of tidal modulation and Rutford ice flow motion on icequake occurrences. Our seismic traces primarily contain icequake signals that derive from stick-slip sliding, but also unique waveforms that might be derived from crevassing and teleseisms that we will also explore. Our results show that stick-slip basal icequakes and these resultant icequake catalogs are valuable data-rich resources that help improve our understanding of glacier flow dynamics and will be important toward improving glacier flow models used for constraining global mean sea level rise.

We present a climate-conditioned catastrophe flood model for the UK that simulates pluvial, fluvial and coastal flood risks at 1 arc second spatial resolution (~20-25m). Hazard layers for ten different return periods are produced over the whole UK for historic, 2020, 2030, 2050 and 2070 conditions using the UKCP18 climate simulations. From these, monetary losses are computed for Great Britain only for five specific global warming levels (0.6, 1.1, 1.8, 2.5 and 3.3°C). The analysis contains a greater level of detail and nuance compared to previous work and represents our current best understanding of the UK’s changing flood risk landscape. Validation against national return period flood maps yielded Critical Success Index values in the range 0.6 to 0.78, and maximum water levels for the Carlisle 2005 flood were replicated to an RMSE of 0.41m without calibration. This level of skill is similar to local modelling with site specific data. Expected Annual Damage in 2020 was £730M, which compares favourably to the observed value of £714M reported by the Association of British Insurers. Previous UK flood loss estimates based on government data are ~3x higher and lie ~6-7 standard deviations away from the mean of our modelled loss distribution, which is plausibly centred on the observations. We estimate that UK 1% annual probability flood losses were ~6% greater in the average climate conditions of 2020 than for the period of historical river flow and rainfall observations (centred approximately on 1995) and can be kept to around ~8% if all countries’ COP26 2030 carbon emission reduction pledges and ‘net zero’ commitments are implemented in full. Implementing only the COP26 pledges increases UK 1% annual probability flood losses by ~23% above recent historical values, and potentially ~37% if climate sensitivity turns out to be higher than currently thought.

Background Light chain proximal tubulopathy (LCPT) is a rare form of paraprotein-related disease, occurring in two main histopathological forms; crystalline and non-crystalline. The clinicopathological features, treatment strategies and outcomes, especially of the non-crystalline form, are not well described. Methods Single-centre retrospective case series of 12 LCPT patients, 5 crystalline and 7 non-crystalline, between 2005-2021. Observations Median age was 69.5 years (range, 47-80). 10 patients presented with CKD and significant proteinuria (median eGFR of 43.5 ml/min/1.73m2; uPCR 328 mg/mmol). Only 6 patients had known haematological disease at the time of renal biopsy. Multiple myeloma (MM) was diagnosed in 7 cases and MGRS in 5. A clone was detected in all cases combining serum/urine electrophoresis and free LC assays. Crystalline and non-crystalline variants had similar clinical presentations. For the non-crystalline variant, a diagnosis was reached based on combination of CKD without other cause, haematological work-up, LC restriction on IF and abnormalities on EM. Nine of 12 patients received clone-directed treatment. Patients who achieved haematological response (including all non-crystalline LCPT) had improved renal outcomes over a median follow-up of 79 months. Conclusions The non-crystalline variant may go unrecognised because of its subtle histopathological features and requires EM to distinguish it from “excessive LC resorption without tubular injury”. Clone-directed treatment with good haematological response improves renal outcomes in both variants but limited data exist in MGRS. Multi-centre prospective studies are needed to better define the clinico-pathological characteristics associated with poor outcomes and optimize treatment strategies in patients with MGRS.

Background Helicopter Emergency Medical Services (HEMS) are a limited and expensive resource, and should be intelligently tasked. HEMS dispatch was identified as a key research priority in 2011and 2022, with a call to identify a ‘general set of criteria with the highest discriminating potential’. However, there have been no published data analyses in the subsequent decade that specifically address this priority, and this priority has been reaffirmed in 2022. The objective of this study was to define the dispatch criteria available at the time of the initial emergency call with the greatest HEMS utility using a large, regional, multi-organizational dataset in the UK. Methods This retrospective observational study utilized dispatch data from a regional emergency medical service (EMS) and three HEMS organisations in the East of England, 2016-2019. In a logistic regression model, Advanced Medical Priority Dispatch System (AMPDS) codes with ≥50 HEMS dispatches in the study period were compared with the remainder to identify codes with high-levels of HEMS patient contact and HEMS-level intervention/drug/diagnostic (HLIDD). The primary outcome was to identify AMPDS codes with a >10% HEMS dispatch rate of all EMS taskings that would result in 10-20 high-utility HEMS dispatches per 24-hour period in the East of England. Data were analysed in R, and are reported as number (percentage); significance was pResults There were n=25,491 HEMS dispatches (6.4k per year), of which n=23,030 (90.3%) had an associated AMPDS code. n=13,778 (59.8%) of HEMS dispatches resulted in patient contact, and n=8437 (36.6%) had an HLIDD. 43 AMPDS codes had significantly greater rates of patient contact and/or HLIDD compared to the reference group. In an exploratory analysis, a cut-off of ≥70% patient contact rate and/or ≥70% HLIDD (with a >10% HEMS dispatch of all EMS taskings) resulted in 17 taskings per 24-hour period. This definition derived nine AMPDS codes with high HEMS utility. Conclusion We have identified nine ‘golden’ AMPDS codes, available at the time of initial emergency call, that are associated with high-levels of whole-system and HEMS utility in the East of England. We propose that UK EMS should consider immediate HEMS dispatch to these codes.

Therapeutic targeting of late-stage breast cancer is limited by an inadequate understanding of how tumor cell signaling evolves during metastatic progression and by the currently available small molecule inhibitors capable of targeting these processes. Herein, we demonstrate that both β3 integrin and fibroblast growth factor receptor-1 (FGFR1) are part of an epithelial–mesenchymal transition (EMT) program that is required to facilitate metastatic outgrowth in response to fibroblast growth factor-2 (FGF2). Mechanistically, β3 integrin physically disrupts an interaction between FGFR1 and E-cadherin, leading to a dramatic redistribution of FGFR1 subcellular localization, enhanced FGF2 signaling and increased three-dimensional (3D) outgrowth of metastatic breast cancer cells. This ability of β3 integrin to drive FGFR signaling requires the enzymatic activity of focal adhesion kinase (FAK). Consistent with these mechanistic data, we demonstrate that FGFR, β3 integrin, and FAK constitute a molecular signature capable of predicting decreased survival of patients with the basal-like subtype of breast cancer. Importantly, covalent targeting of a conserved cysteine in the P-loop of FGFR1–4 with our newly developed small molecule, FIIN-4, more effectively blocks 3D metastatic outgrowth as compared with currently available FGFR inhibitors. In vivo application of FIIN-4 potently inhibited the growth of metastatic, patient-derived breast cancer xenografts and murine-derived metastases growing within the pulmonary microenvironment. Overall, the current studies demonstrate that FGFR1 works in concert with other EMT effector molecules to drive aberrant downstream signaling, and that these events can be effectively targeted using our novel therapeutics for the treatment of the most aggressive forms of breast cancer. Mol Cancer Ther; 15(9); 2096–106. ©2016 AACR.

This file includes supplementary figures S1-S8 and supplementary tables S1-S3.

Streptococcus canis , a multi-host pathogen commonly isolated from dogs and cats, has been occasionally reported in severe cases of human infection. To address the gap in knowledge on its virulence and host tropism, we investigated S. canis genomic epidemiology and report the results of this analysis for the first time. We analysed 59 S . canis whole genome sequences originating from a variety of host species, comprising 39 newly sequenced isolates from UK sources, along with all (n=20) publicly available genomes. Antimicrobial resistance (AMR) phenotype was determined for all 39 available isolates. Genomes were screened for determinants of resistance and virulence. We created a core SNP phylogeny and compared strain clustering to multi-locus sequence typing (MLST) and S. canis M-like protein (SCM) typing. We investigated the dataset for signals of host adaptation using phylogenetic analysis, accessory genome clustering and pan-genome-wide association study analysis. A total of 23 % (9/39) of isolates exhibited phenotypic resistance to lincosamides, macrolides and/or tetracyclines. This was complemented by the identification of AMR-encoding genes in all genomes: tetracycline (tetO 14 %, 8/59; and tetM 7 %, 4/59) and lincosamide/macrolide (ermB, 7 %, 4/59). AMR was more common in human (36 %, 4/11) compared to companion animal (18 %, 5/28) isolates. We identified 19 virulence gene homologues, 14 of which were present in all strains analysed. In an S. canis strain isolated from a dog with otitis externa we identified a homologue of S. pyogenes superantigen SMEZ. The MLST and SCM typing schemes were found to be incapable of accurately representing core SNP-based genomic diversity of the S. canis population. No evidence of host adaptation was detected, suggesting the potential for inter-species transmission, including zoonotic transfer.

Clinical acumen represents only part of being adequately equipped to attend a major incident. The emotive sights, sounds and smells inherent of these dynamic environments are all-encompassing experiences and thus responders must also be armed with the emotional preparedness to perform their clinical or managerial duties effectively; as well as the mental resilience to facilitate professional continuance. Despite this, limited training and a sparsity of evidence exists to guide developments within this domain. Background: Historically, major incident training has focused on clinical principles; but irrespective of how comprehensive this teaching might be, or how fortuitously the learning materials meet national guidelines, they are of little consequence if tandem steps to cultivate mental resilience and emotional preparedness are absent. Effectively dovetailing these three elements is essential if teaching institutions are to properly prepare students for real-world practice. High-Fidelity Simulation (HFS) has a growing reputation as an effective means of bridging important gaps between theory and practice; and to help identify if this modality could cultivate these advancements, we exposed studentsto a large-scale HFS and conducted an evaluation-based study to better understand their lived experience. The primary aim was to ascertain the impact on clinical acumen, emotional preparedness and mental resilience; to help develop teaching and learning practices Methods: Quantitative data was obtained from a sample of 108 students undertaking paramedic science, physician associate studies and adult nursing. Self-completed questionnaires incorporating a 7-point Likert scale were utilised; and each student’s strength of agreement was rated against a series of statements surrounding acquisition of clinical acumen, emotional preparedness and mental resilience. Ethical approval was granted and SPSS v28 employed to analyse the data. Results: 91% of students agreed the combination of theoretical training and HFS provided made them feel clinically prepared to attend a real major incident; 86% agreed this experience had developed their mental resilience and 90% agreed that they felt emotionally prepared to attend a major incident. Conclusion: HFS is a practicable teaching and learning tool; and effective in developing clinical acumen, mental resilience and emotional preparedness in learners training to work in disaster environments or emergency medicine settings.

We present seismic measurements of the firn column at Korff Ice Rise, West Antarctica, including measurements of compressional- and shear-wave velocity and attenuation. We describe a modified spectral-ratio method of measuring the seismic quality factor (Q) based on analysis of diving waves, which enables us to characterise the attenuative structure of firn in greater detail than has previously been possible. The compressional-wave quality factor, Qp, increases from 20 ± 10 in the uppermost firn to 423 ± 260 between 77 and 86 m depth, and the shear-wave quality factor, Qs, increases from 16 ± 9 in the uppermost firn to 100 ± 87 between 49 and 64 m depth. Our modified spectral-ratio method aids the understanding of the seismic structure of firn and benefits characterisation of deeper glaciological targets, being particularly impactful for correcting reflection amplitudes in wide-angle seismic data.

Aggregation of therapeutic bispecific antibodies negatively affects the yield, shelf-life, efficacy and safety of these products. Pairs of stable Chinese hamster ovary (CHO) cell lines produced two difficult-to-express bispecific antibodies with different levels of aggregated product (10-75% aggregate) in a miniaturised bioreactor system. Here, transcriptome analysis was used to interpret the biological causes for the aggregation and to identify strategies to improve product yield and quality. Differential expression- and gene set analysis revealed upregulated proteasomal degradation, unfolded protein response and autophagy processes to be correlated with reduced protein aggregation. Fourteen candidate genes with the potential to reduce aggregation were co-expressed in the stable clones for validation. Of these, HSP90B1, DDIT3, AKT1S1, and ATG16L1, were found to significantly lower aggregation in the stable producers and two (HSP90B1 and DNAJC3) increased titres of the anti-HER2 monoclonal antibody trastuzumab by 50% during transient expression. It is suggested that this approach could be of general use for defining aggregation bottlenecks in CHO cells.

Summary In this paper, we forecast cumulative production for stimulated gas wells using a combination of fast-to-implement modeling methodologies, including polynomial chaos expansion (PCE) and Gaussian processes (GP) proxy models coupled with populations of phenomenological models (POMs). These modeling techniques allow for a reduction in forecast uncertainty and are shown to be effective techniques for extrapolating early time data for stimulated well production from a field of wells in the Surat Basin, Queensland, Australia. The proposed techniques strategically capture and capitalize on production trends across an entire gas field, even in the presence of early production transients. We demonstrate that learning cycles can be shortened, leading to reasonable forecasts, as well as meaningful and actionable insights.

At the end of the seventeenth century, the trade monopoly of the English East India Company was increasingly under threat, both in England and overseas. This article describes voyages to India and the East Indies between 1688 and 1699 by ships commanded by Richard Etherington. Firstly, he commanded a ship chartered by the East India Company for a voyage to India, the outcome of which was shipwreck. After events in England that significantly affected the East India Company's future, he commanded a ship chartered by private merchants, voyaging to Borneo and then, rather unusually, on to Timor. English and Dutch archival sources have been put together to illustrate Etherington's voyages in relation to the various issues that influenced English trade, and also the small world of maritime and mercantile activities in the region at the time.

Patient-level factors related to cardiac arrest in the pediatric cardiac population are well understood but may be unmodifiable. The impact of cardiac ICU organizational and personnel factors on cardiac arrest rates and outcomes remains unknown. We sought to better understand the association between these potentially modifiable organizational and personnel factors on cardiac arrest prevention and rescue.Retrospective analysis of the Pediatric Cardiac Critical Care Consortium registry.Pediatric cardiac ICUs.All cardiac ICU admissions were evaluated for cardiac arrest and survival outcomes.None.Successful prevention was defined as the proportion of admissions with no cardiac arrest (inverse of cardiac arrest incidence). Rescue was the proportion of patients surviving to cardiac ICU discharge after cardiac arrest. Cardiac ICU organizational and personnel factors were captured via site questionnaires. The associations between organizational and personnel factors and prevention/rescue were analyzed using Fine-Gray and multinomial regression, respectively, accounting for clustering within hospitals. We analyzed 54,521 cardiac ICU admissions (29 hospitals) with 1,398 cardiac arrest events (2.5%) between August 1, 2014, and March 5, 2019. For both surgical and medical admissions, lower average daily cardiac ICU occupancy was associated with better cardiac arrest prevention. Better rescue for medical admissions was observed for higher registered nursing hours per patient day and lower proportions of "part time" cardiac ICU physician staff (6 service weeks/yr). Increased registered nurse experience was associated with better rescue for surgical admissions. Increased proportion of critical care certified nurses, full-time intensivists with critical care fellowship training, dedicated respiratory therapists, quality/safety resources, and annual cardiac ICU admission volume were not associated with improved prevention or rescue.Our multi-institutional analysis identified cardiac ICU bed occupancy, registered nurse experience, and physician staffing as potentially important factors associated with cardiac arrest prevention and rescue. Recognizing the limitations of measuring these variables cross-sectionally, additional studies are needed to further investigate these organizational and personnel factors, their interrelationships, and how hospitals can modify structure to improve cardiac arrest outcomes.

Our knowledge regarding the role proteins play in the mutual relationship among oocytes, surrounding follicle cells, stroma, and the vascular network inside the ovary is still poor and obtaining insights into this context would significantly aid our understanding of folliculogenesis. Here, we describe a spatial proteomics approach to characterize the proteome of individual follicles at different growth stages in a whole prepubertal 25-day-old mouse ovary. A total of 401 proteins were identified by nano-scale liquid chromatography–electrospray ionization–tandem mass spectrometry (nLC-ESI-MS/MS), 69 with a known function in ovary biology, as demonstrated by earlier proteomics studies. Enrichment analysis highlighted significant KEGG and Reactome pathways, with apoptosis, developmental biology, PI3K-Akt, epigenetic regulation of gene expression, and extracellular matrix organization being well represented. Then, correlating these data with the spatial information provided by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) on 276 follicles enabled the protein profiles of single follicle types to be mapped within their native context, highlighting 94 proteins that were detected throughout the secondary to the pre-ovulatory transition. Statistical analyses identified a group of 37 proteins that showed a gradual quantitative change during follicle differentiation, comprising 10 with a known role in follicle growth (NUMA1, TPM2), oocyte germinal vesicle-to-metaphase II transition (SFPQ, ACTBL, MARCS, NUCL), ovulation (GELS, CO1A2), and preimplantation development (TIF1B, KHDC3). The proteome landscape identified includes molecules of known function in the ovary, but also those whose specific role is emerging. Altogether, this work demonstrates the utility of performing spatial proteomics in the context of the ovary and offers sound bases for more in-depth investigations that aim to further unravel its spatial proteome.

PurposeThe study aims to develop a model that supports the application of data science techniques for real estate professionals in the fourth industrial revolution (4IR) era. The present 4IR era gave birth to big data sets and is beyond real estate professionals' analysis techniques. This has led to a situation where most real estate professionals rely on their intuition while neglecting a rigorous analysis for real estate investment appraisals. The heavy reliance on their intuition has been responsible for the under-performance of real estate investment, especially in Africa.Design/methodology/approachThis study utilised a survey questionnaire to randomly source data from real estate professionals. The questionnaire was analysed using a combination of Statistical package for social science (SPSS) V24 and Analysis of a Moment Structures (AMOS) graphics V27 software. Exploratory factor analysis was employed to break down the variables (drivers) into meaningful dimensions helpful in developing the conceptual framework. The framework was validated using covariance-based structural equation modelling. The model was validated using fit indices like discriminant validity, standardised root mean square (SRMR), comparative fit index (CFI), Normed Fit Index (NFI), etc.FindingsThe model revealed that an inclusive educational system, decentralised real estate market and data management system are the major drivers for applying data science techniques to real estate professionals. Also, real estate professionals' application of the drivers will guarantee an effective data analysis of real estate investments.Originality/valueNumerous studies have clamoured for adopting data science techniques for real estate professionals. There is a lack of studies on the drivers that will guarantee the successful adoption of data science techniques. A modern form of data analysis for real estate professionals was also proposed in the study.