Interventions to enhance the research productivity of academic staff in higher education schools of nursing: A systematic review

AIM

Synthesize and present peer-reviewed evidence of interventions that enhance the research productivity of academics in Schools of Nursing in Higher Education Institutions.

BACKGROUND

Pressures on academics in Schools of Nursing worldwide to increase or maintain high research productivity persist and numerous Higher Education Institutions across the world have developed interventions to increase productivity. Given evidence that the COVID-19 pandemic has resulted in a withdrawal from research, understanding which interventions best support and improve research productivity is urgent. Increasing research capacity is crucial but only one element in increasing productivity. No recent attempt has been made to synthesise the knowledge gained from these more wide-ranging initiatives.

DESIGN

A mixed-methods systematic review, registered in PROSPERO, searching four academic databases (CINAHL, ERIC, MEDLINE, PsycINFO) from 1/01/2010-20/04/2022. All primary research studies of relevant interventions were included if they described the intervention, reported its outcomes and were published in the English language in peer-reviewed journals.

RESULTS

1637 studies were assessed against eligibility criteria, resulting in 20 included studies. No studies were excluded based on quality. Data pertaining to understandings of 'research productivity', barriers to research productivity, interventions and outcomes of interventions were extracted. The most often used measures were the frequency or staff-output ratio of funding, publications and presentations, while the less commonly used were the number of conference abstracts submitted/accepted and awards. Subjective measures were less commonly used. Barriers to research productivity fell into three broad categories: resource constraints, lack of priority for research and barriers related to the attitudes, knowledge and skills of School of Nursing academics. Interventions covered nine broad areas. Half of the interventions were multi-stranded, including a wide range of components to increase research productivity while the other half comprised one component only, such as writing groups and mentoring. All interventions had a positive impact on research productivity, however, heterogeneity in the measurement of impact, the duration of interventions, sources of comparative data and research design made comparison of interventions challenging.

CONCLUSIONS

The review identified a need for future research to explore the barriers among under-represented groups of academics in Schools of Nursing across a broader geographical area; and what works for various sub-groups of academics. It also identified a need for a valid, standardised tool to assess the effectiveness of interventions to increase research productivity of academics in Schools of Nursing.

Evolving relationship of Nares Strait ice arches on sea ice along the Strait and the North Water, the Arctic's most productive polynya

Nares Strait, the waterway that separates northwest Greenland from Ellesmere Island, is a major pathway along which sea ice leaves the Arctic, including the planet's oldest and thickest sea ice that is experiencing an accelerated loss. Ice arches that develop during the winter at the Strait's northern or southern terminus can remain stable for months at a time during which the transport of sea ice ceases. The Arctic's most productive polynya, the North Water (NOW) or Pikialasorsuaq (West Greenlandic for 'great upwelling') forms at the Strait's southern end. There is evidence that a warming climate and the concomitant thinning of Arctic sea ice is weakening the arches and it has been proposed that this may impact the stability of NOW and the complex ecosystem that it sustains. Here we employ a categorization of recent winters with respect to the presence or absence of ice arches to explore their impact on sea ice along the Strait and over the NOW. We find that winters during which a southern ice arch is absent are associated with a reduced and thinner ice cover along the Strait with ice conditions over the NOW similar to that during winters with a southern arch. In winters, without a southern arch, there is also an acceleration of the winds along the Strait that contributes to the presence of reduced ice cover. Ocean color remote sensing data suggests that current levels of primary productivity over the NOW are independent of the presence or absence of an ice arch. The results suggest more research is needed to assess the stability of the NOW, with respect to reduced ice cover and primary productivity, in a future where ice arches cease to form along Nares Strait.

Bayesian networks and imaging-derived phenotypes highlight the role of fat deposition in COVID-19 hospitalisation risk

Objective: Obesity is a significant risk factor for adverse outcomes following coronavirus infection (COVID-19). However, BMI fails to capture differences in the body fat distribution, the critical driver of metabolic health. Conventional statistical methodologies lack functionality to investigate the causality between fat distribution and disease outcomes. Methods: We applied Bayesian network (BN) modelling to explore the mechanistic link between body fat deposition and hospitalisation risk in 459 participants with COVID-19 (395 non-hospitalised and 64 hospitalised). MRI-derived measures of visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and liver fat were included. Conditional probability queries were performed to estimate the probability of hospitalisation after fixing the value of specific network variables. Results: The probability of hospitalisation was 18% higher in people living with obesity than those with normal weight, with elevated VAT being the primary determinant of obesity-related risk. Across all BMI categories, elevated VAT and liver fat (>10%) were associated with a 39% mean increase in the probability of hospitalisation. Among those with normal weight, reducing liver fat content from >10% to <5% reduced hospitalisation risk by 29%. Conclusion: Body fat distribution is a critical determinant of COVID-19 hospitalisation risk. BN modelling and probabilistic inferences assist our understanding of the mechanistic associations between imaging-derived phenotypes and COVID-19 hospitalisation risk.

Poor glycaemic control and ectopic fat deposition mediates the increased risk of non-alcoholic steatohepatitis in high-risk populations with type 2 diabetes: Insights from Bayesian-network modelling

BACKGROUND

An estimated 55.5% and 37.3% of people globally with type 2 diabetes (T2D) will have concomitant non-alcoholic fatty liver disease (NAFLD) and the more severe fibroinflammatory stage, non-alcoholic steatohepatitis (NASH). NAFLD and NASH prevalence is projected to increase exponentially over the next 20 years. Bayesian Networks (BNs) offer a powerful tool for modelling uncertainty and visualising complex systems to provide important mechanistic insight.

METHODS

We applied BN modelling and probabilistic reasoning to explore the probability of NASH in two extensively phenotyped clinical cohorts: 1) 211 participants with T2D pooled from the MODIFY study & UK Biobank (UKBB) online resource; and 2) 135 participants without T2D from the UKBB. MRI-derived measures of visceral (VAT), subcutaneous (SAT), skeletal muscle (SMI), liver fat (MRI-PDFF), liver fibroinflammatory change (liver cT1) and pancreatic fat (MRI-PDFF) were combined with plasma biomarkers for network construction. NASH was defined according to liver PDFF >5.6% and liver cT1 >800ms. Conditional probability queries were performed to estimate the probability of NASH after fixing the value of specific network variables.

RESULTS

In the T2D cohort we observed a stepwise increase in the probability of NASH with each obesity classification (normal weight: 13%, overweight: 23%, obese: 36%, severe obesity: 62%). In the T2D and non-T2D cohorts, elevated (vs. normal) VAT conferred a 20% and 1% increase in the probability of NASH, respectively, while elevated SAT caused a 7% increase in NASH risk within the T2D cohort only. In those with T2D, reducing HbA1c from the 'high' to 'low' value reduced the probability of NASH by 22%.

CONCLUSION

Using BNs and probabilistic reasoning to study the probability of NASH, we highlighted the relative contribution of obesity, ectopic fat (VAT and liver) and glycaemic status to increased NASH risk, namely in people with T2D. Such modelling can provide insights into the efficacy and magnitude of public health and pharmacological interventions to reduce the societal burden of NASH.

258 Are Electronic Algorithmic Referral Systems the Future of Triage? Evaluating the Use of The Oxford Acute Referrals System (OARS) For Plastic Surgery

Introduction

A traditional referral involves transfer of information over a telephone call and is typically documented in an unstructured format on paper notes, producing poor continuity of referrals between shifts, increasing the risk of error, and compromising patient safety. The Oxford Acute Referrals System (OARS) is an electronic platform that keeps a complete record of referrals, whilst providing the referring clinician with step-by-step specialist advice according to inbuilt BSSH guidelines. This audit demonstrates our experience of its’ use in a tertiary centre Plastics department.

Method

One week of referrals in 2019, prior to the implementation of OARS, were compared with the equivalent week in 2020 once OARS was established. Data was collected retrospectively using electronic patient records.

Results

In one week in 2019, 120 cases were reviewed in the emergency clinic compared with 155 OARS referrals for the equivalent week in 2020. Following OARS implementation, 69% of referred cases did not footfall in the emergency clinic. 46% were managed locally with specialist advice from Plastic Surgery. 10% were brought directly into a theatre list, of which 7% were subsequently treated conservatively. A Plastic surgery consultant reviewing OARS referrals taken by juniors, changed the decision of how or where to manage the patient in 6% of cases.

Conclusions

OARS is an effective triage system that has considerably reduced footfall in the emergency clinic, whilst simultaneously expediting patient care down the correct treatment pathway. Its use led to safe management of patients remotely, which has important implications during a pandemic.

An exploratory study to investigate animal health and reproductive wastage among Australian meat goat producers

The Australian goat meat industry has grown significantly in the last decade, with the value of exports nearly tripling. However, because carcase weight has remained constant over this time, the drivers of industry growth are price and supply. Animal health and reproduction are key factors contributing to supply and productivity, yet limitations to production management are poorly understood, hampering advice for effective intervention. This exploratory study aims to provide insights into the animal health and reproductive management practices and perceptions among meat goat producers in Australia. To achieve this aim, 20 producers, located in New South Wales, Queensland, Western Australia and Victoria, operating under different production systems were interviewed. The results of this study suggest that animal health management could be improved and that producers perceive a lack of relevant and species-specific information available to help them make informed decisions. Reproductive management and records varied greatly across producers interviewed. Kid loss was identified as an issue, with a 28% estimated average (6%-47% range) of losses from kidding until weaning. Producers identified predation, doe nutrition and mismothering as the biggest contributors to kid loss, with the majority of losses occurring within a week of birth. All producers believed management could minimise kid loss. This study highlights the importance of improving reproductive rates among goat enterprises and provides new information on the current practices within the Australian meat goat industry. This may assist the development of appropriate strategies for improving health and reproductive management and delivery of advice to producers.

Sexual risk and HIV testing disconnect in men who have sex with men (MSM) recruited to an online HIV self-testing trial

OBJECTIVES

We report the frequency of previous HIV testing at baseline in men who have sex with men (MSM) who enrolled in an HIV self-testing (HIVST) randomized controlled trial [an HIV self-testing public health intervention (SELPHI)].

METHODS

Criteria for enrolment were age ≥ 16 years, being a man (including trans men) who ever had anal intercourse (AI) with a man, not being known to be HIV positive and having consented to national HIV database linkage. Using online survey baseline data (2017-2018), we assessed associations with never having tested for HIV and not testing in the previous 6 months, among men who reported at least two recent condomless AI (CAI) partners.

RESULTS

A total of 10 111 men were randomized; the median age was 33 years [interquartile range (IQR) 26-44 years], 89% were white, 20% were born outside the UK, 0.8% were trans men, 47% were degree educated, and 8% and 4% had ever used and were currently using pre-exposure prophylaxis (PrEP), respectively. In the previous 3 months, 89% reported AI and 72% reported CAI with at least one male partner. Overall, 17%, 33%, 54%, and 72% had tested for HIV in the last 3 months, 6 months, 12 months and 2 years, respectively; 13% had tested more than 2 years ago and 15% had never tested. Among 3972 men reporting at least two recent CAI partners, only 22% had tested in the previous 3 months. Region of residence and education level were independently associated with recent HIV testing. Among current PrEP users, 15% had not tested in the previous 6 months.

CONCLUSIONS

Most men in SELPHI, particularly those reporting at least two CAI partners and current PrEP users, were not testing in line with current UK recommendations. The results of the trial will inform whether online promotion of HIVST addresses ongoing testing barriers.

Approaches to training multiclass semantic image segmentation of damage in concrete

This paper addresses the problem of creating a large quantity of high-quality training segmentation masks from scanning electron microscopy (SEM) images. The images are acquired from concrete samples that exhibit progressive amounts of degradation resulting from alkali-silica reaction (ASR), a leading cause of deterioration, cracking and loss of capacity in much of the nation's infrastructure. The target damage classes in concrete SEM images are defined as paste damage, aggregate damage, air voids and no damage. We approached the SEM segmentation problem by applying convolutional neural network (CNN)-based methods to predict the damage classes due to ASR for each image pixel. The challenges in using the CNN-based methods lie in preparing large numbers of high-quality training labelled images while having limited human resources. To address these challenges, we designed damage- and context-assisted approaches to lower the requirements on human resources. We then evaluated the accuracy of CNN-based segmentation methods using the datasets prepared with these two approaches. LAY DESCRIPTION: This work is about automated segmentation of Scanning Electron Microscopy (SEM) images taken from core and prism samples of concrete. The segmentation must detect several damage classes in each image in order to understand properties of concrete-made structures over time. The segmentation problem is approached with an artificial network (AI) based model. The training data for the AI model are created using damage- and context-assisted approaches to lower the requirements on human resources. The access to all training data and to a web-based validation system for scoring segmented images is available at https://isg.nist.gov/deepzoomweb/data/concreteScoring.

A Hybrid Task Graph Scheduler for High Performance Image Processing Workflows

Designing applications for scalability is key to improving their performance in hybrid and cluster computing. Scheduling code to utilize parallelism is difficult, particularly when dealing with data dependencies, memory management, data motion, and processor occupancy. The Hybrid Task Graph Scheduler (HTGS) improves programmer productivity when implementing hybrid workflows for multi-core and multi-GPU systems. The Hybrid Task Graph Scheduler (HTGS) is an abstract execution model, framework, and API that increases programmer productivity when implementing hybrid workflows for such systems. HTGS manages dependencies between tasks, represents CPU and GPU memories independently, overlaps computations with disk I/O and memory transfers, keeps multiple GPUs occupied, and uses all available compute resources. Through these abstractions, data motion and memory are explicit; this makes data locality decisions more accessible. To demonstrate the HTGS application program interface (API), we present implementations of two example algorithms: (1) a matrix multiplication that shows how easily task graphs can be used; and (2) a hybrid implementation of microscopy image stitching that reduces code size by ≈ 43% compared to a manually coded hybrid workflow implementation and showcases the minimal overhead of task graphs in HTGS. Both of the HTGS-based implementations show good performance. In image stitching the HTGS implementation achieves similar performance to the hybrid workflow implementation. Matrix multiplication with HTGS achieves 1.3× and 1.8× speedup over the multi-threaded OpenBLAS library for 16k × 16k and 32k × 32k size matrices, respectively.

Modeling, validation and verification of three-dimensional cell-scaffold contacts from terabyte-sized images

Background

Cell-scaffold contact measurements are derived from pairs of co-registered volumetric fluorescent confocal laser scanning microscopy (CLSM) images (z-stacks) of stained cells and three types of scaffolds (i.e., spun coat, large microfiber, and medium microfiber). Our analysis of the acquired terabyte-sized collection is motivated by the need to understand the nature of the shape dimensionality (1D vs 2D vs 3D) of cell-scaffold interactions relevant to tissue engineers that grow cells on biomaterial scaffolds.

Results

We designed five statistical and three geometrical contact models, and then down-selected them to one from each category using a validation approach based on physically orthogonal measurements to CLSM. The two selected models were applied to 414 z-stacks with three scaffold types and all contact results were visually verified. A planar geometrical model for the spun coat scaffold type was validated from atomic force microscopy images by computing surface roughness of 52.35 nm ±31.76 nm which was 2 to 8 times smaller than the CLSM resolution. A cylindrical model for fiber scaffolds was validated from multi-view 2D scanning electron microscopy (SEM) images. The fiber scaffold segmentation error was assessed by comparing fiber diameters from SEM and CLSM to be between 0.46% to 3.8% of the SEM reference values. For contact verification, we constructed a web-based visual verification system with 414 pairs of images with cells and their segmentation results, and with 4968 movies with animated cell, scaffold, and contact overlays. Based on visual verification by three experts, we report the accuracy of cell segmentation to be 96.4% with 94.3% precision, and the accuracy of cell-scaffold contact for a statistical model to be 62.6% with 76.7% precision and for a geometrical model to be 93.5% with 87.6% precision.

Conclusions

The novelty of our approach lies in (1) representing cell-scaffold contact sites with statistical intensity and geometrical shape models, (2) designing a methodology for validating 3D geometrical contact models and (3) devising a mechanism for visual verification of hundreds of 3D measurements. The raw and processed data are publicly available from https://isg.nist.gov/deepzoomweb/data/ together with the web -based verification system.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1928-x) contains supplementary material, which is available to authorized users.

Needing to Belong: First Practice Placement Experiences of Children's Nursing Students

This study examines first year children's nursing students' anxieties before their first practice placement and their support needs during that time. Strategies to address needs are highlighted. A questionnaire was completed by children's nursing students (n = 21) before their initial practice placement to establish their expectations and concerns. A subgroup (n = 5) took part in a focus group following placement to establish consensus around the support that helped and what could help future students prepare for first placement. The resultant data indicated the importance of students having a sense of belonging to their practice placement, trusting website information, induction days, and the involvement of a more senior student in their preparation, in addition to facilitative mentors. Using similar methodology to that used with students, a subgroup of professional staff took part in two focus groups (FG1 n = 5, FG2 n = 4) to establish consensus around support initiatives using areas identified by students as priorities that could better facilitate this initial practice placement. Although commonalities existed within both students and professionals, some differences were highlighted. A student's first practice placement is of utmost importance in affirming their choice to study nursing. Academic and clinical staff play a crucial part in this decision-making.

Growing Old in the Emergency Department

The research team were concerned that older patients requiring emergency admission seemed to wait longer for a hospital bed, and as such were disproportionately affected by Emergency Department overcrowding. To investigate this theory and explore any changes over time, a ten year dataset (2005-2014 inclusive) was extracted from the information systems at Beaumont Hospital, Dublin. This research examines the changing age profile of ED patients, identifies the relationship between age and the total time spent in the Emergency Department (Patient Experience Time (PET)), and examines the public belief that EDs are busiest in winter when reports of overcrowding and elderly patients waiting on trolleys get most media attention. The results highlight that the ED is busy all year round (but for different seasonal reasons) and point to an overdue need to plan for the current and future healthcare of older patients within and beyond acute hospitals.

Attributable mortality of hospital-acquired bloodstream infections in Ireland

AIM

To estimate the attributable mortality of hospital-acquired bloodstream infections (HA-BSI) in Ireland.

METHODS

A retrospective case-cohort study was conducted, based on notifications from Irish microbiology laboratories and administrative patient records from six Irish hospitals from January 2007 to December 2013. Probabilistic linkage was used to link 1252 cases of bloodstream infection from a cohort of 343,189 hospitalized patients. Independent predictors of mortality were determined using a multi-variable logistic regression model, and included: patient age, emergency or re-admission to hospital, length of stay in an intensive care unit, number of procedures, number of diagnoses, major diagnostic category and presence of HA-BSI.

RESULTS

Attributable mortality was calculated from the crude mortality of case subjects after adjusting for other predictors of mortality, and was found to be 15.3% (95% confidence interval 14.8-15.8%). The study was further stratified according to the causative organism, including: Escherichia coli, Enterococcus faecium, Enterococcus faecalis, Pseudomonas aeruginosa, Klebsiella pneumoniae, Staphylococcus aureus and Streptococcus pneumoniae, and, where available, their antimicrobial resistance patterns. The highest attributable mortality among these organisms was reported for E. faecium at 18.1% and the lowest attributable mortality was reported for E. coli at 13.6%. A significantly higher attributable mortality was found for antimicrobial resistance patterns of some organisms, most notably for meticillin-resistant S. aureus at 19.5%, vs meticillin-susceptible S. aureus at 13.3%.

CONCLUSIONS

HA-BSI is an important cause of mortality, and attributable mortality differs significantly among causative organisms and antimicrobial resistance patterns.

Klebsiella pneumoniae bloodstream infection, antimicrobial resistance and consumption trends in Ireland: 2008 to 2013

This study aimed to describe the epidemiology and antimicrobial resistance trends of Klebsiella pneumoniae bloodstream infection (BSI) in Ireland, in conjunction with national antimicrobial consumption data, during the period 2008 to 2013. A retrospective cohort study of K. pneumoniae BSI cases was conducted, based on notifications from Irish microbiology laboratories to the Health Protection Surveillance Centre (HPSC). In total, 1942 K. pneumoniae BSI cases were identified over 6 years, with 310 reported in 2008 and 326 reported in 2013. From 2008 to 2013, the proportion of isolates resistant to co-amoxiclav (24 % versus 29 %), piperacillin-tazobactam (11 % versus 27 %), third generation cephalosporins (3GC) (11 % versus 21 %), fluoroquinolones (13 % versus 21 %) and gentamicin (11 % versus 17 %) increased overall, concurrent with increasing national rates of antimicrobial consumption in Ireland (acute hospitals: 35.87 versus 39.77 defined daily doses (DDD) per 100 bed days used (BDU); and community: 6.38 versus 7.85 DDD per 1000 inhabitants per day (DID)). Enhanced data on the patient's admission route was available for 735 (38 %) cases. Overall, 51 % (n = 378) were categorised as 'acquired in the reporting hospital'. The all-cause mortality was 20 %, with 115 deaths, 101 (88 %) of whom died within 30 days of blood culture sampling date. K. pneumoniae is the second most common cause of Gram-negative BSI in Ireland, with most cases healthcare-associated and an all-cause mortality of 20 % reported in this study. Annual increases in resistance to different antimicrobial classes and in a multi-drug resistant phenotype have been observed, concurrent with increasing national broad spectrum antimicrobial consumption. These trends portend a risk to patient outcomes and highlight the urgency for individual prescribers to evaluate their antimicrobial prescribing habits in hospitals, long-term care and community settings.

Computational study of the inhibitory mechanism of the kinase CDK5 hyperactivity by peptide p5 and derivation of a pharmacophore

The hyperactivity of the cyclic dependent kinase 5 (CDK5) induced by the activator protein p25 has been linked to a number of pathologies of the brain. The CDK5-p25 complex has thus emerged as a major therapeutic target for Alzheimer's disease (AD) and other neurodegenerative conditions. Experiments have shown that the peptide p5 reduces the CDK5-p25 activity without affecting the endogenous CDK5-p35 activity, whereas the peptide TFP5, obtained from p5, elicits similar inhibition, crosses the blood-brain barrier, and exhibits behavioral rescue of AD mice models with no toxic side effects. The molecular basis of the kinase inhibition is not currently known, and is here investigated by computer simulations. It is shown that p5 binds the kinase at the same CDK5/p25 and CDK5/p35 interfaces, and is thus a non-selective competitor of both activators, in agreement with available experimental data in vitro. Binding of p5 is enthalpically driven with an affinity estimated in the low µM range. A quantitative description of the binding site and pharmacophore is presented, and options are discussed to increase the binding affinity and selectivity in the design of drug-like compounds against AD.

Enabling Interactive Measurements from Large Coverage Microscopy

Microscopy could be an important tool for characterizing stem cell products if quantitative measurements could be collected over multiple spatial and temporal scales. With the cells changing states over time and being several orders of magnitude smaller than cell products, modern microscopes are already capable of imaging large spatial areas, repeat imaging over time, and acquiring images over several spectra. However, characterizing stem cell products from such large image collections is challenging because of data size, required computations, and lack of interactive quantitative measurements needed to determine release criteria. We present a measurement web system consisting of available algorithms, extensions to a client-server framework using Deep Zoom, and the configuration know-how to provide the information needed for inspecting the quality of a cell product. The cell and other data sets are accessible via the prototype web-based system at http://isg.nist.gov/deepzoomweb.

Cow-calf reproductive, genetic, and nutritional management to improve the sustainability of whole beef production systems

Optimizing efficiency in the cow-calf sector is an important step toward improving beef sustainability. The objective of the study was to use a model to identify the relative roles of reproductive, genetic, and nutritional management in minimizing beef production systems' environmental impact in an economically viable, socially acceptable manner. An economic and environmental diet optimizer was used to identify ideal nutritional management of beef production systems varying in genetic and reproductive technology use. Eight management scenarios were compared to a least cost baseline: average U.S. production practices (CON), CON with variable nutritional management (NUT), twinning cattle (TWN), early weaning (EW), sire selection by EPD using either on-farm bulls (EPD-B) or AI (EPD-AI), decreasing the calving window (CW), or selecting bulls by EPD and reducing the calving window (EPD-CW). Diets to minimize land use, water use, and/or greenhouse gas (GHG) emissions were optimized under each scenario. Increases in diet cost attributable to reducing environmental impact were constrained to less than stakeholder willingness to pay for improved efficiency and reduced environmental impact. Baseline land use, water use, and GHG emissions were 188 m, 712 L, and 21.9 kg/kg HCW beef. The NUT scenario, which assessed opportunities to improve sustainability by altering nutritional management alone, resulted in a simultaneous 1.5% reduction in land use, water use, and GHG emissions. The CW scenario improved calf uniformity and simultaneously decreased land use, water use, and GHG emissions by 3.2%. Twinning resulted in a 9.2% reduction in the 3 environmental impact metrics. The EW scenario allowed for an 8.5% reduction in the 3 metrics. The EPD-AI scenario resulted in an 11.1% reduction, which was comparable to the 11.3% reduction achieved by EPD-B in the 3 metrics. Improving genetic selection by using AI or by purchasing on-farm bulls based on their superior EPD demonstrated clear opportunity to improve sustainability. When genetic and reproductive technologies were adopted, up to a 12.4% reduction in environmental impact was achievable. Given the modeling assumptions used in this study, optimizing nutritional management while concurrently improving genetic and reproductive efficiency may be promising avenues to improve productivity and sustainability of U.S. beef systems.

Crosstalk between Desmoglein 2 and Patched 1 accelerates chemical-induced skin tumorigenesis

Aberrant activation of Hedgehog (Hh) signaling is causative of BCCs and has been associated with a fraction of SCCs. Desmoglein 2 (Dsg2) is an adhesion protein that is upregulated in many cancers and overexpression of Dsg2 in the epidermis renders mice more susceptible to squamous-derived neoplasia. Here we examined a potential crosstalk between Dsg2 and Hh signaling in skin tumorigenesis. Our findings show that Dsg2 modulates Gli1 expression, in vitro and in vivo. Ectopic expression of Dsg2 on Ptc1(+/lacZ) background enhanced epidermal proliferation and interfollicular activation of the Hh pathway. Furthermore, in response to DMBA/TPA, the Dsg2/Ptc1+/lacZ mice developed squamous lessons earlier than the WT, Ptc1(+/lacZ), and Inv-Dsg2 littermates. Additionally, DMBA/TPA induced BCC formation in all mice harboring the Ptc1(+/lacZ) gene and the presence of Dsg2 in Dsg2/Ptc1(+/lacZ) mice doubled the BCC tumor burden. Reporter analysis revealed activation of the Hh pathway in the BCC tumors. However, in the SCCs we observed Hh activity only in the underlying dermis of the tumors. Furthermore, Dsg2/Ptc1(+/lacZ) mice demonstrated enhanced MEK/Erk1/2 activation within the tumors and expression of Shh in the dermis. In summary, our results demonstrate that Dsg2 modulates Hh signaling, and this synergy may accelerate skin tumor development by different mechanisms.

Survey statistics of automated segmentations applied to optical imaging of mammalian cells

BACKGROUND

The goal of this survey paper is to overview cellular measurements using optical microscopy imaging followed by automated image segmentation. The cellular measurements of primary interest are taken from mammalian cells and their components. They are denoted as two- or three-dimensional (2D or 3D) image objects of biological interest. In our applications, such cellular measurements are important for understanding cell phenomena, such as cell counts, cell-scaffold interactions, cell colony growth rates, or cell pluripotency stability, as well as for establishing quality metrics for stem cell therapies. In this context, this survey paper is focused on automated segmentation as a software-based measurement leading to quantitative cellular measurements.

METHODS

We define the scope of this survey and a classification schema first. Next, all found and manually filteredpublications are classified according to the main categories: (1) objects of interests (or objects to be segmented), (2) imaging modalities, (3) digital data axes, (4) segmentation algorithms, (5) segmentation evaluations, (6) computational hardware platforms used for segmentation acceleration, and (7) object (cellular) measurements. Finally, all classified papers are converted programmatically into a set of hyperlinked web pages with occurrence and co-occurrence statistics of assigned categories.

RESULTS

The survey paper presents to a reader: (a) the state-of-the-art overview of published papers about automated segmentation applied to optical microscopy imaging of mammalian cells, (b) a classification of segmentation aspects in the context of cell optical imaging, (c) histogram and co-occurrence summary statistics about cellular measurements, segmentations, segmented objects, segmentation evaluations, and the use of computational platforms for accelerating segmentation execution, and (d) open research problems to pursue.

CONCLUSIONS

The novel contributions of this survey paper are: (1) a new type of classification of cellular measurements and automated segmentation, (2) statistics about the published literature, and (3) a web hyperlinked interface to classification statistics of the surveyed papers at https://isg.nist.gov/deepzoomweb/resources/survey/index.html.

From Image Tiles to Web-Based Interactive Measurements in One Stop

This article introduces readers to a web-based solution useful for interactive nanoscale measurements of centimeter-sized specimens. This solution is a client-server system that promotes collaborative measurements and discovery. The system consists of multiple computational modules that enable uploading microscopy images, extracting metadata, assembling many nanometer-resolution images into an image covering a centimeter-sized area, and interactive viewing and measuring of objects of interest at multiple length scales over terabyte-sized images. We illustrate the use of the system on images of aerosolized nanoparticles and dye particles on printing paper.

Detection and characterization of nonspecific, sparsely populated binding modes in the early stages of complexation

A method is proposed to study protein-ligand binding in a system governed by specific and nonspecific interactions. Strong associations lead to narrow distributions in the proteins configuration space; weak and ultraweak associations lead instead to broader distributions, a manifestation of nonspecific, sparsely populated binding modes with multiple interfaces. The method is based on the notion that a discrete set of preferential first-encounter modes are metastable states from which stable (prerelaxation) complexes at equilibrium evolve. The method can be used to explore alternative pathways of complexation with statistical significance and can be integrated into a general algorithm to study protein interaction networks. The method is applied to a peptide-protein complex. The peptide adopts several low-population conformers and binds in a variety of modes with a broad range of affinities. The system is thus well suited to analyze general features of binding, including conformational selection, multiplicity of binding modes, and nonspecific interactions, and to illustrate how the method can be applied to study these problems systematically. The equilibrium distributions can be used to generate biasing functions for simulations of multiprotein systems from which bulk thermodynamic quantities can be calculated.

Chromosome interaction over a distance in meiosis

The challenge of cell division is to distribute partner chromosomes (pairs of homologues, pairs of sex chromosomes or pairs of sister chromatids) correctly, one into each daughter cell. In the 'standard' meiosis, this problem is solved by linking partners together via a chiasma and/or sister chromatid cohesion, and then separating the linked partners from one another in anaphase; thus, the partners are kept track of, and correctly distributed. Many organisms, however, properly separate chromosomes in the absence of any obvious physical connection, and movements of unconnected partner chromosomes are coordinated at a distance. Meiotic distance interactions happen in many different ways and in different types of organisms. In this review, we discuss several different known types of distance segregation and propose possible explanations for non-random segregation of distance-segregating chromosomes.

Background intensity correction for terabyte-sized time-lapse images

Several computational challenges associated with large-scale background image correction of terabyte-sized fluorescent images are discussed and analysed in this paper. Dark current, flat-field and background correction models are applied over a mosaic of hundreds of spatially overlapping fields of view (FOVs) taken over the course of several days, during which the background diminishes as cell colonies grow. The motivation of our work comes from the need to quantify the dynamics of OCT-4 gene expression via a fluorescent reporter in human stem cell colonies. Our approach to background correction is formulated as an optimization problem over two image partitioning schemes and four analytical correction models. The optimization objective function is evaluated in terms of (1) the minimum root mean square (RMS) error remaining after image correction, (2) the maximum signal-to-noise ratio (SNR) reached after downsampling and (3) the minimum execution time. Based on the analyses with measured dark current noise and flat-field images, the most optimal GFP background correction is obtained by using a data partition based on forming a set of submosaic images with a polynomial surface background model. The resulting image after correction is characterized by an RMS of about 8, and an SNR value of a 4 × 4 downsampling above 5 by Rose criterion. The new technique generates an image with half RMS value and double SNR value when compared to an approach that assumes constant background throughout the mosaic. We show that the background noise in terabyte-sized fluorescent image mosaics can be corrected computationally with the optimized triplet (data partition, model, SNR driven downsampling) such that the total RMS value from background noise does not exceed the magnitude of the measured dark current noise. In this case, the dark current noise serves as a benchmark for the lowest noise level that an imaging system can achieve. In comparison to previous work, the past fluorescent image background correction methods have been designed for single FOV and have not been applied to terabyte-sized images with large mosaic FOVs, low SNR and diminishing access to background information over time as cell colonies span entirely multiple FOVs. The code is available as open-source from the following link https://isg.nist.gov/.

FogBank: a single cell segmentation across multiple cell lines and image modalities

Background

Many cell lines currently used in medical research, such as cancer cells or stem cells, grow in confluent sheets or colonies. The biology of individual cells provide valuable information, thus the separation of touching cells in these microscopy images is critical for counting, identification and measurement of individual cells. Over-segmentation of single cells continues to be a major problem for methods based on morphological watershed due to the high level of noise in microscopy cell images. There is a need for a new segmentation method that is robust over a wide variety of biological images and can accurately separate individual cells even in challenging datasets such as confluent sheets or colonies.

Results

We present a new automated segmentation method called FogBank that accurately separates cells when confluent and touching each other. This technique is successfully applied to phase contrast, bright field, fluorescence microscopy and binary images. The method is based on morphological watershed principles with two new features to improve accuracy and minimize over-segmentation.

First, FogBank uses histogram binning to quantize pixel intensities which minimizes the image noise that causes over-segmentation. Second, FogBank uses a geodesic distance mask derived from raw images to detect the shapes of individual cells, in contrast to the more linear cell edges that other watershed-like algorithms produce.

We evaluated the segmentation accuracy against manually segmented datasets using two metrics. FogBank achieved segmentation accuracy on the order of 0.75 (1 being a perfect match). We compared our method with other available segmentation techniques in term of achieved performance over the reference data sets. FogBank outperformed all related algorithms. The accuracy has also been visually verified on data sets with 14 cell lines across 3 imaging modalities leading to 876 segmentation evaluation images.

Conclusions

FogBank produces single cell segmentation from confluent cell sheets with high accuracy. It can be applied to microscopy images of multiple cell lines and a variety of imaging modalities. The code for the segmentation method is available as open-source and includes a Graphical User Interface for user friendly execution.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0431-x) contains supplementary material, which is available to authorized users.

Aligning product development and user perspectives: social-behavioural dimensions of multipurpose prevention technologies

Multipurpose prevention technologies provide a compelling response to the multiple and reinforcing sexual and reproductive health risks faced by women globally. To ensure that this potential is realised, product-specific characteristics and their social-behavioural correlates must be considered early in the product development process. This paper provides an overview of the key user-related social and behavioural dimensions of three broad categories of multipurpose prevention technologies: 1) sustained release vaginal rings, 2) pericoital vaginal products, and 3) co-formulated or co-administered injectables. The authors build upon the broad parameters of Target Product Profiles for such products, aligning them with user perspective considerations.

The Living with Dysarthria group for post-stroke dysarthria: the participant voice

BACKGROUND

The Living with Dysarthria group programme, devised for people with post-stroke dysarthia and family members, was piloted twice. Feedback from those who experience an intervention contributes to the evaluation of speech and language therapy programmes, giving the participant view of the intervention's value and guiding further developments.

RESEARCH QUESTION

What feedback do participants in the Living with Dysarthria programme provide, informing on its perceived usefulness and guiding its future development?

METHODS & PROCEDURES

Nine people with chronic dysarthria following stroke and four family members who completed the Living with Dysarthria programme all contributed to Focus Group (FG) discussion, transcribed and thematically analysed, and completed an Anonymous Questionnaire Evaluation (AQE), comprising closed statements and open questions. An anonymous descriptive adjective selection task (ADAST) was also used.

OUTCOMES & RESULTS

The varied forms of feedback provided complementary information. Thematic analysis of FG data and AQE open question responses were configured around programme benefits, programme structure and content, and programme practicalities. Benefits associated with participation included learning and insight, being supported by peers and professionals, and improved speech and confidence. These are consistent with the main programme elements of education, support and speech practice. All activities were seen as relevant and positively received. Flexibility, recognition of and catering to individual needs were valued characteristics. The community location was approved by all. Most participants thought the format of eight weekly sessions of 2 h was appropriate. Responses to AQE closed statements provided almost unanimous confirmation of the very positive feedback conveyed in FG discussions. The main response to suggested improvements in AQEs was that the number of sessions should be increased. Feedback indicated that for a few individuals there was negative reaction to some facts about stroke, home practice tasks were difficult to complete, the person with dysarthria/family member pair may not be the optimum combination for paired practice activities and pre-programme information should be extended. The ADAST showed that the programme was enjoyable, interesting, stimulating and useful.

CONCLUSIONS & IMPLICATIONS

Participant feedback indicates that group therapy, with family member participation, is a valid form of management for chronic post-stroke dysarthria. Education, peer and professional support, and speech practice are confirmed as relevant programme components. Consistent majority opinions were communicated in different situations and via varied mediums. Some individuals expressed views relevant to their own needs, and these responses also inform future implementation of the Living with Dysarthria programme.

More Outcomes than Trials: A Call for Consistent Data Collection across Stroke Rehabilitation Trials

Stroke survivors experience complex combinations of impairments, activity limitations, and participation restrictions. The essential components of stroke rehabilitation remain elusive. Determining efficacy in randomized controlled trials (RCTs) is challenging; there is no commonly agreed primary outcome measure for rehabilitation trials. Clinical guidelines depend on proof of efficacy in RCTs and meta-analyses. However, diverse trial aims, differing methods, inconsistent data collection, and use of multiple assessment tools hinder comparability across trials. Consistent data collection in acute stroke trials has facilitated meta-analyses to inform trial design and clinical practice. With few exceptions, inconsistent data collection has hindered similar progress in stroke rehabilitation research. There is an urgent need for the routine collection of a core dataset of common variables in rehabilitation trials. The European Stroke Organisation Outcomes Working Group, the National Institutes of Neurological Disorders and Stroke Common Data Elements project, and the Collaborative Stroke Audit and Research project have called for consistency in data collection in stroke trials. Standardizing data collection can decrease study start up times, facilitate data sharing, and inform clinical guidelines. Although achieving consensus on which outcome measures to use in stroke rehabilitation trials is a considerable task, perhaps a feasible starting point is to achieve consistency in the collection of data on demography, stroke severity, and stroke onset to inclusion times. Longer term goals could include the development of a consensus process to establish the core dataset. This should be endorsed by researchers, funders, and journal editors in order to facilitate sustainable change.

Segmenting time-lapse phase contrast images of adjacent NIH 3T3 cells

We present a new method for segmenting phase contrast images of NIH 3T3 fibroblast cells that is accurate even when cells are physically in contact with each other. The problem of segmentation, when cells are in contact, poses a challenge to the accurate automation of cell counting, tracking and lineage modelling in cell biology. The segmentation method presented in this paper consists of (1) background reconstruction to obtain noise-free foreground pixels and (2) incorporation of biological insight about dividing and nondividing cells into the segmentation process to achieve reliable separation of foreground pixels defined as pixels associated with individual cells. The segmentation results for a time-lapse image stack were compared against 238 manually segmented images (8219 cells) provided by experts, which we consider as reference data. We chose two metrics to measure the accuracy of segmentation: the 'Adjusted Rand Index' which compares similarities at a pixel level between masks resulting from manual and automated segmentation, and the 'Number of Cells per Field' (NCF) which compares the number of cells identified in the field by manual versus automated analysis. Our results show that the automated segmentation compared to manual segmentation has an average adjusted rand index of 0.96 (1 being a perfect match), with a standard deviation of 0.03, and an average difference of the two numbers of cells per field equal to 5.39% with a standard deviation of 4.6%.