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Abstract Physical neuromorphic computing, exploiting the complex dynamics of physical systems, has seen rapid advancements in sophistication and performance. Physical reservoir computing, a subset of neuromorphic computing, faces limitations due to its reliance on single systems. This constrains output dimensionality and dynamic range, limiting performance to a narrow range of tasks. Here, we engineer a suite of nanomagnetic array physical reservoirs and interconnect them in parallel and series to create a multilayer neural network architecture. The output of one reservoir is recorded, scaled and virtually fed as input to the next reservoir. This networked approach increases output dimensionality, internal dynamics and computational performance. We demonstrate that a physical neuromorphic system can achieve an overparameterised state, facilitating meta-learning on small training sets and yielding strong performance across a wide range of tasks. Our approach’s efficacy is further demonstrated through few-shot learning, where the system rapidly adapts to new tasks.

Background The aim of this study was to evaluate the impact of mental health attributes, such as the presence of psychiatric comorbidities or psychological comorbidities (low resilience), on outcomes after rotator cuff repair (RCR) and total shoulder arthroplasty (TSA). Methods PubMed, Cochrane, and Google Scholar (results pages 1–20) were searched up to November 2023. Mental health problems of interest included the presence of psychiatric comorbidities (depression, anxiety) or indicators of poor psychological functioning, such as low resilience or the presence of distress. Patients were assigned to poor or good mental health groups in this study based on their grouping in the original study. Results Fourteen studies were included in the meta-analysis. Patients with good mental health had greater improvements in postoperative American Shoulder and Elbow Surgeons and Simple Shoulder Test scores in the TSA cohort (P=0.003 and P=0.01), RCR cohort (P

Within-sample variation in cotton fiber length is a major factor influencing the production and quality of yarns. The textile industry has been searching for approaches of improving the long fiber fraction and minimizing the short fiber fraction within a cotton sample to produce superior fiber and yarn quality. USTER® High Volume Instrument (HVI) has been widely used for a rapid assessment of cotton fiber length traits from a fiber bundle. However, its effectiveness for genetic studies has been questioned due to the indirect estimations of the cotton fiber traits that cannot be measured from a fiber bundle. To overcome the limits of the HVI fiber length traits, we utilized the Advanced Fiber Information System (AFIS) measuring fiber length traits directly from individual fibers based on weight or number. Comparative fiber length analyses showed AFIS provided higher sensitivity in detecting the fiber length variations within and among cotton samples than HVI. The weight-based AFIS length traits were strongly correlated with the corresponding HVI lengths, whereas the number-based AFIS mean length showed a relatively weaker correlation with the HVI lengths. Integrations of the weight based-length traits with genome-wide association studies (GWAS) enabled classifying the QTLs specifically associated with long, mean, or short fiber length traits and identified a false positive associated with the indirectly estimated HVI short fiber trait. Unlike the weight based-AFIS length traits, the number-based AFIS length trait did not show a negative correlation with a weight related-HVI property, and identified a single QTL that was not detected by the corresponding HVI trait. These results suggested that integrating the AFIS method with GWAS helped discoveries of the genome loci involved in the within-sample variation in cotton fiber length and characterizations of the fiber length QTLs.

Abstract Strongly-interacting nanomagnetic arrays are ideal systems for exploring reconfigurable magnonics. They provide huge microstate spaces and integrated solutions for storage and neuromorphic computing alongside GHz functionality. These systems may be broadly assessed by their range of reliably accessible states and the strength of magnon coupling phenomena and nonlinearities. Increasingly, nanomagnetic systems are expanding into three-dimensional architectures. This has enhanced the range of available magnetic microstates and functional behaviours, but engineering control over 3D states and dynamics remains challenging. Here, we introduce a 3D magnonic metamaterial composed from multilayered artificial spin ice nanoarrays. Comprising two magnetic layers separated by a non-magnetic spacer, each nanoisland may assume four macrospin or vortex states per magnetic layer. This creates a system with a rich 16 N microstate space and intense static and dynamic dipolar magnetic coupling. The system exhibits a broad range of emergent phenomena driven by the strong inter-layer dipolar interaction, including ultrastrong magnon-magnon coupling with normalised coupling rates of $$\frac{\Delta f}{\nu }=0.57$$ Δ f ν = 0.57 , GHz mode shifts in zero applied field and chirality-control of magnetic vortex microstates with corresponding magnonic spectra.

Aquatic germplasm repositories can play a pivotal role in securing the genetic diversity of natural populations and agriculturally important aquatic species. However, existing technologies for repository development and operation face challenges in terms of accuracy, precision, efficiency, and cost-effectiveness, especially for microdevices used in gamete quality evaluation. Quality management is critical throughout genetic resource protection processes from sample collection to final usage. In this study, we examined the potential of using three-dimensional (3-D) stereolithography resin printing to address these challenges and evaluated the overall capabilities and limitations of a representative industrial 3-D resin printer with a price of US$18,000, a consumer-level printer with a price

Summary: Gastrointestinal helminth infection occurs within a diverse microbiome, complicating the interpretation of whether effects are caused by the parasite versus the microbial community. Here, we present a protocol for deriving sterile larvae of the murine helminth, Heligmosomoides polygyrus bakeri (H. polygyrus), providing experimental control of the microbiome. We describe steps for sterilizing with a bleach solution and developing into infectious larvae using E. coli. We then detail procedures for removing bacterial contaminants before harvesting to ensure the generation of germ-free larvae. : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Background: The prevalence and burden of mental illness among young people is rising, globally. Youth mental health services, such as headspace, offer young people access to multidisciplinary mental healthcare, specifically designed to address their needs. Pharmacists are medicines experts and possess a skillset increasingly being utilised in expanded areas of practice. There is potential for pharmacists to perform roles within youth mental health services, however sparse literature exploring pharmacist-delivered mental healthcare for young people exists. Objective: To explore views of headspace staff on medication use among young people who use youth mental health services and pharmacists' potential roles within the headspace youth mental health service model. Methods: Individual semi-structured interviews were conducted with staff from one inner city headspace centre in Sydney, Australia. An interview guide was developed to capture participants' views on medication use among young people using youth mental health services and potential roles for pharmacists within this context. Reflexive thematic analysis was conducted to analyse the findings of this exploratory pilot study. Results: Twelve staff members were interviewed, allowing for a range of multidisciplinary perspectives. Four themes were identified from the data: (i) gaps in medication-related care, (ii) potential roles for pharmacists at headspace (iii) collaboration between pharmacists and general practitioners, and (iv) a “one-stop shop”. Conclusions: There are opportunities for pharmacists to improve young peoples' experiences using psychotropic medications through the provision of medication information to clients and caregivers. Pharmacists have a potential role to play in contributing to multidisciplinary case reviews but clarifying their specific roles when working alongside general practitioners is necessary. Uncertainty regarding the feasibility of pharmacist-led services within the headspace youth mental health service model and a lack of awareness regarding pharmacists' full scope of practice are barriers to pharmacists' potential roles within the headspace model.

Background: In attempt to increase trauma system coverage, our state added 21 level 3 (L3TC) and level 4 trauma centers (L4TC) to the existing 7 level 1 trauma centers from 2008 to 2012. This study examined the impact of adding these lower-level trauma centers (LLTC) on patient outcomes. Methods: Patients in the state trauma registry age ≥ 15 from 2007 to 2012 were queried for demographic, injury, and outcome variables. These were compared between 2007 (PRE) and 2008–2012 (POST) cohorts. Multivariate logistic regression was performed to assess independent predictors of mortality. Subgroup analyses were performed for Injury Severity Score (ISS) ≥15, age ≥ 65, and trauma mechanisms. Results: 143,919 adults were evaluated. POST had significantly more female, geriatric, and blunt traumas (all p

Aims: Distal femoral resection in conventional total knee arthroplasty (TKA) utilizes an intramedullary guide to determine coronal alignment, commonly planned for 5° of valgus. However, a standard 5° resection angle may contribute to malalignment in patients with variability in the femoral anatomical and mechanical axis angle. The purpose of the study was to leverage deep learning (DL) to measure the femoral mechanical-anatomical axis angle (FMAA) in a heterogeneous cohort. Methods: Patients with full-limb radiographs from the Osteoarthritis Initiative were included. A DL workflow was created to measure the FMAA and validated against human measurements. To reflect potential intramedullary guide placement during manual TKA, two different FMAAs were calculated either using a line approximating the entire diaphyseal shaft, and a line connecting the apex of the femoral intercondylar sulcus to the centre of the diaphysis. The proportion of FMAAs outside a range of 5.0° (SD 2.0°) was calculated for both definitions, and FMAA was compared using univariate analyses across sex, BMI, knee alignment, and femur length. Results: The algorithm measured 1,078 radiographs at a rate of 12.6 s/image (2,156 unique measurements in 3.8 hours). There was no significant difference or bias between reader and algorithm measurements for the FMAA (p = 0.130 to 0.563). The FMAA was 6.3° (SD 1.0°; 25% outside range of 5.0° (SD 2.0°)) using definition one and 4.6° (SD 1.3°; 13% outside range of 5.0° (SD 2.0°)) using definition two. Differences between males and females were observed using definition two (males more valgus; p < 0.001). Conclusion: We developed a rapid and accurate DL tool to quantify the FMAA. Considerable variation with different measurement approaches for the FMAA supports that patient-specific anatomy and surgeon-dependent technique must be accounted for when correcting for the FMAA using an intramedullary guide. The angle between the mechanical and anatomical axes of the femur fell outside the range of 5.0° (SD 2.0°) for nearly a quarter of patients. Cite this article: Bone Jt Open 2024;5(2):101–108.

Abstract Dramatic improvements in measuring genetic variation across agriculturally relevant populations (genomics) must be matched by improvements in identifying and measuring relevant trait variation in such populations across many environments (phenomics). Identifying the most critical opportunities and challenges in genome to phenome (G2P) research is the focus of this paper. Previously (Genome Biol, 23(1):1–11, 2022), we laid out how Agricultural Genome to Phenome Initiative (AG2PI) will coordinate activities with USA federal government agencies expand public–private partnerships, and engage with external stakeholders to achieve a shared vision of future the AG2PI. Acting on this latter step, AG2PI organized the “Thinking Big: Visualizing the Future of AG2PI” two-day workshop held September 9–10, 2022, in Ames, Iowa, co-hosted with the United State Department of Agriculture’s National Institute of Food and Agriculture (USDA NIFA). During the meeting, attendees were asked to use their experience and curiosity to review the current status of agricultural genome to phenome (AG2P) work and envision the future of the AG2P field. The topic summaries composing this paper are distilled from two 1.5-h small group discussions. Challenges and solutions identified across multiple topics at the workshop were explored. We end our discussion with a vision for the future of agricultural progress, identifying two areas of innovation needed: (1) innovate in genetic improvement methods development and evaluation and (2) innovate in agricultural research processes to solve societal problems. To address these needs, we then provide six specific goals that we recommend be implemented immediately in support of advancing AG2P research.

BackgroundFrontotemporal lobar degeneration (FTLD) is a leading cause of dementia in individuals aged

BackgroundTo address the limitations of commonly used cross-validation methods, the linear regression method (LR) was proposed to estimate population accuracy of predictions based on the implicit assumption that the fitted model is correct. This method also provides two statistics to determine the adequacy of the fitted model. The validity and behavior of the LR method have been provided and studied for linear predictions but not for nonlinear predictions. The objectives of this study were to 1) provide a mathematical proof for the validity of the LR method when predictions are based on conditional means, regardless of whether the predictions are linear or non-linear 2) investigate the ability of the LR method to detect whether the fitted model is adequate or inadequate, and 3) provide guidelines on how to appropriately partition the data into training and validation such that the LR method can identify an inadequate model.ResultsWe present a mathematical proof for the validity of the LR method to estimate population accuracy and to determine whether the fitted model is adequate or inadequate when the predictor is the conditional mean, which may be a non-linear function of the phenotype. Using three partitioning scenarios of simulated data, we show that the one of the LR statistics can detect an inadequate model only when the data are partitioned such that the values of relevant predictor variables differ between the training and validation sets. In contrast, we observed that the other LR statistic was able to detect an inadequate model for all three scenarios.ConclusionThe LR method has been proposed to address some limitations of the traditional approach of cross-validation in genetic evaluation. In this paper, we showed that the LR method is valid when the model is adequate and the conditional mean is the predictor, even when it is a non-linear function of the phenotype. We found one of the two LR statistics is superior because it was able to detect an inadequate model for all three partitioning scenarios (i.e., between animals, by age within animals, and between animals and by age) that were studied.

Abstract In the summer of 2020, ESA changed the orbit of CryoSat‐2 to align periodically with NASA's ICESat‐2 mission, a campaign known as CRYO2ICE, which allows for near‐coincident CryoSat‐2 and ICESat‐2 observations in space and time over the Arctic until summer 2022, where the CRYO2ICE Antarctic campaign was initiated. This study investigates the Arctic CRYO2ICE radar and laser freeboards acquired by CryoSat‐2 and ICESat‐2, respectively, during the winter seasons of 2020–2022, and derives snow depths from their differences along the orbits. Along‐track snow depth observations can provide high‐resolution snow depth distributions which are vital for air‐ice‐ocean heat and momentum transfer, understanding light transmission, and snow‐ice‐interactions. Generally, ICESat‐2 is backscattered at a surface above the elevation of the CryoSat‐2 signal. CRYO2ICE snow depths are thinner than the daily model‐ or passive‐microwave‐based snow depth composites used for comparison, with differences being most pronounced in the Atlantic and Pacific Arctic. Satellite‐derived and model‐based snow estimates show similar seasonal accumulation over first‐year ice, but CRYO2ICE has limited seasonal accumulation over multi‐year ice which is linked to a slow increase in ICESat‐2, and to some extent CryoSat‐2, freeboards. We present a first estimation of spaceborne along‐track snow depth estimates with average uncertainty of 10–11 ± 2–3 cm for 7‐km segments, with random and systematic contributions of 7 and 4 cm. These observations show the potential for along‐track dual‐frequency observations of snow depth from the future Copernicus mission CRISTAL; but they also highlight uncertainties in radar penetration and the correlation length scales of snow topography that still require further research.

Abstract Background Person‐centred goal planning is increasingly being incorporated into healthcare interventions. People experiencing severe and persistent mental illnesses (SPMIs) have high levels of co‐occurring health conditions, reducing their life expectancy when compared with the general population. As medications are commonly used in the treatment of SPMIs, community pharmacists are well‐placed to support the health and wellbeing of this population. Objectives To examine pharmacists' and service users' experiences of goal planning as a component of a community pharmacy‐based health intervention for people experiencing SPMIs (PharMIbridge intervention). Methods This study utilised a qualitative exploratory approach with an interpretive description method. Semistructured interviews were undertaken with community pharmacists (n = 16) and service user participants (n = 26) who had participated in pharmacist support services for people experiencing SPMIs (PharMIbridge intervention). Results Four themes relating to goal planning were identified. First, goal planning provided purpose and motivation for participation in the intervention. Planning realistic goals was important but often challenging. Both pharmacists and service users highlighted the relational aspects of goal planning and how strong relationships supported positive behaviour change and outcomes. Finally, individualised and flexible approaches were important aspects of the intervention, ensuring goals were meaningful to service users. Conclusions The findings from this study identified positive outcomes from the inclusion of goal‐planning processes in a community pharmacy‐based health intervention. Further research regarding tools, strategies or training that could support future goal‐planning interventions in primary healthcare is needed. Patient or Public Contribution The PharMIbridge randomised controlled trial research team included lived experience members and was overseen by an expert panel that included members with a lived experience of mental illness and representatives from key organisations. The training provided to pharmacists was co‐designed and co‐delivered by the researchers and lived experience representatives, and pharmacists were supported by lived experience mentors. Service user participants were invited to participate in the interviews through a number of pathways (e.g., at the completion of the intervention, flyers). Those interested were provided with the full study participant information and provided with a $30 gift voucher at the conclusion of the interview.

Abstract Atom-interferometric quantum sensors could revolutionize navigation, civil engineering, and Earth observation. However, operation in real-world environments is challenging due to external interference, platform noise, and constraints on size, weight, and power. Here we experimentally demonstrate that tailored light pulses designed using robust control techniques mitigate significant error sources in an atom-interferometric accelerometer. To mimic the effect of unpredictable lateral platform motion, we apply laser-intensity noise that varies up to 20% from pulse-to-pulse. Our robust control solution maintains performant sensing, while the utility of conventional pulses collapses. By measuring local gravity, we show that our robust pulses preserve interferometer scale factor and improve measurement precision by 10× in the presence of this noise. We further validate these enhancements by measuring applied accelerations over a 200 μ g range up to 21× more precisely at the highest applied noise level. Our demonstration provides a pathway to improved atom-interferometric inertial sensing in real-world settings.

The bacterium Yersinia ruckeri causes enteric redmouth disease in salmonids and hence has substantial economic implications for the farmed fish industry. The Norwegian Y. ruckeri outbreak isolate NVH_3758 carries a relatively uncharacterized plasmid, pYR4, which encodes both type 4 pili and a type 4 secretion system. In this study, we demonstrate that pYR4 does not impose a growth burden on the Y. ruckeri host bacterium, nor does the plasmid contribute to twitching motility (an indicator of type 4 pilus function) or virulence in a Galleria mellonella larval model of infection. However, we show that pYR4 is conjugative. We also reveal, through mutagenesis, that pYR4 encodes a functional post-segregational killing system, HigBA, that is responsible for plasmid maintenance within Y. ruckeri. This is the first toxin–antitoxin system to be characterized for this organism. Whilst further work is needed to elucidate the virulence role of pYR4 and whether it contributes to bacterial disease under non-laboratory conditions, our results suggest that the plasmid possesses substantial stability and transfer mechanisms that imply importance within the organism. These results add to our understanding of the mobile genetic elements and evolutionary trajectory of Y. ruckeri as an important commercial pathogen, with consequences for human food production.

Abstract Theoretical and empirical accounts suggest that adolescence is associated with heightened reward learning and impulsivity. Experimental tasks and computational models that can dissociate reward learning from the tendency to initiate actions impulsively (action initiation bias) are thus critical to characterise the mechanisms that drive developmental differences. However, existing work has rarely quantified both learning ability and action initiation, or it has relied on small samples. Here, using computational modelling of a learning task collected from a large sample (N = 742, 9-18 years, 11 countries), we test differences in reward and punishment learning and action initiation from childhood to adolescence. Computational modelling reveals that whilst punishment learning rates increase with age, reward learning remains stable. In parallel, action initiation biases decrease with age. Results are similar when considering pubertal stage instead of chronological age. We conclude that heightened reward responsivity in adolescence can reflect differences in action initiation rather than enhanced reward learning.

Naturally-colored brown cotton (NBC) fiber is an environmentally friendly raw source of fiber for textile applications. The fiber of some NBC cultivars exhibits flame-retardant properties, which can be used in textiles that require flame resistance. Proanthocyanidins or their derivatives are responsible for the brown pigment in NBC; however, how flame retardancy is related to pigmentation in NBC is poorly understood. To gain insight into brown pigment biosynthesis, we conducted comparative transcripts and metabolites profiling analysis of developing cotton fibers between the brown (MC-BL) and white (MC-WL) cotton near-isogenic lines (NILs), genetically different only in the Lc1 locus. In this study, mass spectrometry was used to detect metabolites in BL and WL developing fibers at 8, 12, 16, 20, 24, 36, and 40 days post anthesis (DPA) and mature fibers. Transcripts analysis was performed at two critical fiber developmental points, 8 DPA (fiber elongation) and 20 DPA (secondary cell wall deposition). We found 5836 (ESI MS positive mode) and 4541 (ESI MS negative mode) metabolites significantly different accumulated between BL and WL. Among them, 142 were known non-redundant metabolites, including organic acids, amino acids, and derivatives of the phenylpropanoid pathway. Transcript analysis determined 1691 (8 DPA) and 5073 (20 DPA) differentially expressed genes (DEGs) between BL and WL, with the majority of DEGs down-regulated at 20 DPA. Organic acids of the citric acid cycle were induced, while most of the detected amino acids were reduced in the MC-BL line. Both cis- and trans-stereoisomers of flavan-3-ols were detected in developing MC-WL and MC-BL fibers; however, the gallocatechin and catechin accumulated multiple times higher. Gas chromatography-mass spectrometry (GC-MS) analysis of fatty acids determined that palmitic acid long-chain alcohols were the main constituents of waxes of mature fibers. Energy-dispersive X-ray spectrometry (EDS) analysis of mature fibers revealed that potassium accumulated three times greater in MC-BL than in MC-WL mature fibers. This study provides novel insights into the biosynthesis of pigments and its association with flame retardancy in NBC fibers.

[This corrects the article DOI: 10.1371/journal.pone.0266838.].

Abstract Observationally, the association of basal metabolic rate (BMR) with mortality is mixed, although some ageing theories suggest that higher BMR should reduce lifespan. It remains unclear whether a causal association exists. In this one-sample Mendelian randomization study, we aimed to estimate the casual effect of BMR on parental attained age, a proxy for lifespan, using two-sample Mendelian randomization methods. We obtained genetic variants strongly (p-value

The California sea hare (Aplysia californica) provides a powerful biomedical model system for studying aspects of neurological development and damage, behavior, aging, and hypoxia. Aplysia encapsulate their zygotes within strands that result in tangled egg masses that greatly complicate culture and experimentation. The historical and current importance of Aplysia for biomedical research and the mounting climate crisis necessitates protection of Aplysia genetic resources. The goal of this work was to prototype open-hardware sizing, processing, and packaging devices for A. californica early life stages suitable for integration into a cryopreservation pathway. The Strand Centi-Sizer was a low-cost, fused filament fabrication 3-D printable device that increased experiment preparation efficiency and standardized the cutting of egg strands customizable to user needs. A downstream system of 3-D printed devices was also prototyped to address inefficiencies in handling of egg strand sections for processing and packaging into existing cryopreservation straw platforms. Time studies were conducted comparing manual methods (i.e., no specialized equipment) with open hardware to demonstrate utility of the devices and to encourage community members to design and prototype new devices to address recurrent and novel problems in other aquatic animals that produce egg strands. Improvements in design could further increase efficiency, standardization, and reproducibility, and extend the application of these devices to other research communities, such as shrimp or salamander spermatophores, sea anemone body part (e.g., pedal lacerate) cryopreservation, or study areas such as vitrification.

Elabela is a component of the apelinergic system and may exert a cardioprotective role by regulating the innate immune responses. Innate lymphoid cells (ILCs) have a significant role in initiating and progressing immune-inflammatory responses. While ILCs have been intensively investigated during the last decade, little is known about their relationship with the apelinergic system and their cardiac diversity in a gender-based paradigm. In this study, we investigated the polarization of cardiac ILCs by Elabela in males versus females in a mouse model. Using flow cytometry and immunohistochemistry analyses, we showed a potential interplay between Elabela and cardiac ILCs and whether such interactions depend on sexual dimorphism. Our findings showed, for the first time, that Elabela is expressed by cardiac ILCs, and its expression is higher in females’ ILC class 3 (ILC3s) compared to males. Females had higher frequencies of ILC1s, and Elabela was able to suppress T-cell activation and the expression of co-stimulatory CD28 in a mixed lymphocyte reaction assay (MLR). In conclusion, our results suggest, for the first time, a protective role for Elabela through its interplay with ILCs and that it can be used as an immunotherapeutic target in the treatment of cardiovascular disorders in a gender-based fashion.

Here the authors evaluate single cell gene expression from mouse and human Huntington’s disease brains, finding incomplete oligodendrocyte maturation and pathways involved. Treating mice with thiamine/biotin ameliorates molecular pathology.

Abstract Background Mental Health First Aid (MHFA) training teaches participants how to respond to mental health crises, including suicide. Little is known about the impact of training on participants’ observed MHFA behaviours. This exploratory study aimed to compare MHFA-trained Australian and US student pharmacists’ performance and suicide assessment language during simulated patient role-play (SPRP) assessments. Methods Student pharmacists (n = 265) completed MHFA training and participated (n = 81) in SPRPs with simulated patients (SP) who were people with lived experience of mental illness. Each SPRP was marked by three raters (student, tutor and SP). One-way ANOVA, chi-squared tests and independent samples t-tests were used to compare scores and pass/fail rates, where appropriate. Transcribed audio-recordings of suicide assessments underwent discourse analysis. A chi-squared test was conducted to investigate the differences in how suicide assessment language was coded across six discursive frames (‘confident’/‘timid’, ‘empathetic’/‘apathetic’, and ‘direct’/‘indirect’). Results Three raters assessed 81 SPRPs, resulting in quantitative analysis of 243 rubrics. There were no significant differences between student pharmacists’ mean scores and pass/fail rates across countries. Overall, both cohorts across Australia and the US performed better during the mania scenario, with a low failure rate of 13.9 and 19.0%, respectively. Most students in both countries passed their SPRP assessment; however, 27.8% did not assess for suicide or used indirect language during suicide assessment, despite completing MHFA training. Australian student pharmacists demonstrated, more direct language (76.9% versus 67.9%) and empathy (42.3% versus 32.1%) but less confidence (57.7% versus 60.7%) compared to US student pharmacists, during their suicide assessment; however, these differences were not statistically significant. Conclusions Findings indicate most MHFA-trained student pharmacists from Australia and the US can provide MHFA during SPRPs, as well as assess for suicide directly, empathetically and confidently. This exploratory study demonstrates the importance of practicing skills post-training and the need for further research exploring participants’ hesitance to assess for suicide, despite training completion.

Abstract Background Psychotropic polypharmacy and high-dose prescribing may play a role in therapy, however, with associated risks. The aim of this study was to describe current prescribing practices and use of four psychotropic medication groups (antipsychotics, antidepressants, mood stabilisers and benzodiazepines), focusing on polypharmacy (across and within groups) and high-dose prescribing in adults experiencing severe and persistent mental illness (SPMI) in the Australian community. Methods 318 people taking psychotropic medication for SPMI had a medication review undertaken by a community pharmacist. Participants were recruited as part of an RCT from three Australian states/territories between September 2020-July 2021. All psychotropic medication and daily doses were recorded and reviewed for alignment with current clinical guidelines. Univariate and multiple logistic regression models investigated factors associated with antipsychotic, antidepressant, and mood stabiliser polypharmacy, and antipsychotic and antidepressant high-dose therapy. Variables included age, gender, geographic location, self- reported mental illness(es), hospital admission(s) in previous 6-months and prescriber type. Results 806 psychotropic medications were prescribed for the 318 participants. Mood stabiliser polypharmacy was recorded in 19.0% of participants prescribed mood stabilisers; antipsychotic polypharmacy in 18.4% of participants prescribed antipsychotics; antidepressant polypharmacy in 11.3% of those prescribed antidepressants; and three participants (5.1%) were prescribed two benzodiazepines concurrently. Almost 18.6% of the cohort was receiving high-dose treatment; 18 participants were prescribed high-dose antipsychotics and 39 high-dose antidepressants, with two participants prescribed both. Adjusted logistic regression for polypharmacy found male gender, psychiatrist as sole prescriber, or multiple prescribers, were associated with antipsychotic polypharmacy. The adjusted model for high-dose therapy found psychiatrist as sole prescriber was significantly associated with antipsychotic and antidepressant high-dose prescribing. Conclusion Psychotropic polypharmacy was common in this community cohort experiencing SPMI. Whilst polypharmacy is not always inappropriate, it is a complex construct with potential benefits alongside potential risks. Benefits and harms need to be balanced however this practice is not supported by clear guidance to assist health practitioners. This study highlights the important need for regular medication reviews and strengthened communication between consumers and all healthcare professionals involved in community mental health care, to support safe and effective use of psychotropic medications.

The sub-kilometre scale distribution of snow depth on Arctic sea ice impacts atmosphere-ice fluxes of energy and mass, and is of importance for satellite estimates of sea-ice thickness from both radar and lidar altimeters. While information about the mean of this distribution is increasingly available from modelling and remote sensing, the full distribution cannot yet be resolved. We analyse 33 539 snow depth measurements from 499 transects taken at Soviet drifting stations between 1955 and 1991 and derive a simple statistical distribution for snow depth over multi-year ice as a function of only the mean snow depth. We then evaluate this snow depth distribution against snow depth transects that span first-year ice to multiyear ice from the MOSAiC, SHEBA and AMSR-Ice field campaigns. Because the distribution can be generated using only the mean snow depth, it can be used in the downscaling of several existing snow depth products for use in flux modelling and altimetry studies.

Research on job resources suggests strong links with work engagement, but less is known about its association with personal resources and possible mechanisms linking personal resources to work engagement. Based on the job demands-resources (JD-R) model and lifespan development theories, we develop and test a model of the indirect relationships between personal resources (i.e., adaptive coping in the form of selection, optimization, and compensation and personal health in the form of subjective health complaints) and work engagement through work ability. To test this model, a sample of employees (n = 520) was recruited from a panel of employed older (i.e., aged 40+) workers. Results suggest that work ability mediates the relationships between selection, optimization, and compensation and subjective health complaints and work engagement.

Stakeholder involvement in intervention development has become increasingly popular and is understood as crucial for successful implementation. However, methodological difficulties persist regarding the implementation of appropriate participatory methods to engage children and collect relevant information for intervention development. This paper discusses four creative, qualitative methods – a brainstorming task, an individual letter, a story-based task, and a focus group task – and compares their suitability to generate relevant information for early intervention development. These four methods were used in the early stages of a project aiming to develop a peer relationship intervention and were analysed using thematic analysis. Based on theoretical considerations, information categories (a) definition aspects, (b) context factors, and (c) change mechanisms were of interest, while (d) examples and experience and (e) additional information were identified as prevalent categories through inductive thematic analysis. Definition was a prevalent theme generated by the brainstorming task, although the sticky note format limited the depth of individual answers. The secret letter, which allowed children to share ideas privately, was found to be useful for generating more in-depth reflections on definitions and personal experiences. Stories and focus group discussions were found to be useful for generating varied context factors and change mechanisms, although stories also generated fictional elements and external solutions. Providing different qualitative methods and allowing children to choose how they prefer to communicate their thoughts proved important for collecting authentic, in-depth information.

IntroductionCryptosporidiosis is a leading cause of diarrheal-associated morbidity and mortality, predominantly affecting children under 5 years old in low-and-middle-income countries. There is no effective treatment and no vaccine. New therapeutics are emerging from drug discovery efforts. It is critical that mode of action studies are performed alongside drug discovery to ensure the best clinical outcomes. Unfortunately, technology to identify and validate drug targets for Cryptosporidium is severely lacking.MethodsWe used C. parvum lysyl-tRNA synthetase (CpKRS) and DDD01510706 as a target-compound pair to develop both chemical and genetic tools for mode of action studies for Cryptosporidium. We adapted thermal proteome profiling (TPP) for Cryptosporidium, an unbiased approach for target identification.ResultsUsing TPP we identified the molecular target of DDD01510706 and confirm that it is CpKRS. Genetic tools confirm that CpKRS is expressed throughout the life cycle and that this target is essential for parasite survival. Parasites genetically modified to over-express CpKRS or parasites with a mutation at the compound-binding site are resistant to treatment with DDD01510706. We leveraged these mutations to generate a second drug selection marker for genetic modification of Cryptosporidium, KRSR. This second selection marker is interchangeable with the original selection marker, NeoR, and expands the range of reverse genetic approaches available to study parasite biology. Due to the sexual nature of the Cryptosporidium life cycle, parental strains containing different drug selection markers can be crossed in vivo.DiscussionSelection with both drug markers produces highly efficient genetic crosses (>99% hybrid progeny), paving the way for forward genetics approaches in Cryptosporidium.

Introduction Individuals at an inherited high-risk of developing adult-onset disease, such as breast cancer, are rare in the population. These individuals require lifelong clinical, psychological and reproductive assistance. After a positive germline test result, clinical genetic services provide support and care coordination. However, ongoing systematic clinical follow-up programmes are uncommon. Digital health solutions offer efficient and sustainable ways to deliver affordable and equitable care. This paper outlines the codesign and development of a digital health platform to facilitate long-term clinical and psychological care, and foster self-efficacy in individuals with a genetic disease predisposition.Methods and analysis We adopt a mixed-methods approach for data gathering and analysis. Data collection is in two phases. In phase 1, 300 individuals with a high-risk genetic predisposition to adult disease will undertake an online survey to assess their use of digital health applications (apps). In phase 2, we will conduct focus groups with 40 individuals with a genetic predisposition to cardiac or cancer syndromes, and 30 clinicians from diverse specialities involved in their care. These focus groups will inform the platform’s content, functionality and user interface design, as well as identify the barriers and enablers to the adoption and retention of the platform by all endusers. The focus groups will be audiorecorded and transcribed, and thematic and content data analysis will be undertaken by adopting the Unified Theory of Acceptance and Use of Technology. Descriptive statistics will be calculated from the survey data. Phase 3 will identify the core skillsets for a novel digital health coordinator role. Outcomes from phases 1 and 2 will inform development of the digital platform, which will be user-tested and optimised in phase 4.Ethics and dissemination This study was approved by the Peter MacCallum Human Research Ethics Committee (HREC/88892/PMCC). Results will be disseminated in academic forums, peer-reviewed publications and used to optimise clinical care.

**Background:** Traditional health economic evaluations of antimicrobials currently underestimate their value to wider society. They can be supplemented by additional value elements including insurance value, which captures the value of an antimicrobial in preventing or mitigating impacts of adverse risk events. Despite being commonplace in other sectors, constituents of the impacts and approaches for estimating insurance value have not been investigated. **Objectives:** This study assessed the insurance value of a novel gram-negative antimicrobial from operational healthcare, wider population health, productivity, and informal care perspectives. **Methods:** A novel mixed-methods approach was used to model insurance value in the United Kingdom: (1) literature review and multidisciplinary expert workshops to identify risk events for 4 relevant scenarios: ward closures, unavoidable shortage of conventional antimicrobials, viral respiratory pandemics, and catastrophic antimicrobial resistance (AMR); (2) parameterizing mitigable costs and frequencies of risk events across perspectives and scenarios; (3) estimating insurance value through a Monte Carlo simulation model for extreme events and a dynamic disease transmission model. **Results:** The mean insurance value across all scenarios and perspectives over 10 years in the UK was £718 million, should AMR remain unchanged, where only £134 million related to operational healthcare costs. It would be 50%-70% higher if AMR steadily increased or if a more risk-averse view (1-in-10 year downside) of future events is taken. **Discussion:** The overall insurance value if AMR remains at current levels (a conservative projection), is over 5 times greater than insurance value from just the operational healthcare costs perspective, traditionally the sole perspective used in health budgeting. Insurance value was generally larger for nationwide or universal (catastrophic AMR, pandemic, and conventional antimicrobial shortages) rather than localized (ward closure) scenarios, across perspectives. Components of this insurance value match previously published estimates of operational costs and mortality impacts. **Conclusions:** Insurance value of novel antimicrobials can be systematically modeled and substantially augments their traditional health economic value in normal circumstances. These approaches are generalizable to similar health interventions and form a framework for health systems and governments to capture broader value in health technology assessments, improve healthcare access, and increase resilience by planning for adverse scenarios.

This paper shows that certain 3F4 hypergeometric functions can be expanded in sums of pair products of 2F3 functions, which reduce in special cases to 2F3 functions expanded in sums of pair products of 1F2 functions. This expands the class of hypergeometric functions having summation theorems beyond those expressible as pair-products of generalized Whittaker functions, 2F1 functions, and 3F2 functions into the realm of pFq functions where p

The storage potential of hydrocarbon reservoirs in the central Gulf of Mexico (GOM) makes future development of CO2 storage projects in those areas promising for secure, large-scale, and long-term storage purposes. Focusing on the producing and depleted hydrocarbon fields in the continental slope of the central GOM, this paper analyzed, assessed, and screened the producing sands and evaluated their CO2 storage potential. A live interactive CO2 storage site screening system was built in the SAS® Viya system with a broad range of screening criteria combined from published studies. This offers the users a real-time assessment of the storage sites and enables them to adjust the filters and visualize the results to determine the most suitable filter range. The CO2 storage resources of the sands were estimated using a volumetric equation and the correlation developed by the National Energy Technology Laboratory (NETL). The results of this study indicate that 1.05 gigatons of CO2 storage resources are available in the developed reservoirs at the upper slope area of the central GOM. The Mississippi Canyon and Green Canyon protraction areas contain the fields with the largest storage resources.

The Bessel function of the first kind JNkx is expanded in a Fourier–Legendre series, as is the modified Bessel function of the first kind INkx. The purpose of these expansions in Legendre polynomials was not an attempt to rival established numerical methods for calculating Bessel functions but to provide a form for JNkx useful for analytical work in the area of strong laser fields, where analytical integration over scattering angles is essential. Despite their primary purpose, one can easily truncate the series at 21 terms to provide 33-digit accuracy that matches the IEEE extended precision in some compilers. The analytical theme is furthered by showing that infinite series of like-powered contributors (involving 1F2 hypergeometric functions) extracted from the Fourier–Legendre series may be summed, having values that are inverse powers of the eight primes 1/2i3j5k7l11m13n17o19p multiplying powers of the coefficient k.

We extend previous research to derive three additional M-1-dimensional integral representations over the interval [0,1]. The prior version covered the interval [0,∞]. This extension applies to products of M Slater orbitals, since they (and wave functions derived from them) appear in quantum transition amplitudes. It enables the magnitudes of coordinate vector differences (square roots of polynomials) |x1−x2|=x12−2x1x2cosθ+x22 to be shifted from disjoint products of functions into a single quadratic form, allowing for the completion of its square. The M-1-dimensional integral representations of M Slater orbitals that both this extension and the prior version introduce provide alternatives to Fourier transforms and are much more compact. The latter introduce a 3M-dimensional momentum integral for M products of Slater orbitals (in M separate denominators), followed in many cases by another set of M-1-dimensional integral representations to combine those denominators into one denominator having a single (momentum) quadratic form. The current and prior methods are also slightly more compact than Gaussian transforms that introduce an M-dimensional integral for products of M Slater orbitals while simultaneously moving them into a single (spatial) quadratic form in a common exponential. One may also use addition theorems for extracting the angular variables or even direct integration at times. Each method has its strengths and weaknesses. We found that these M-1-dimensional integral representations over the interval [0,1] are numerically stable, as was the prior version, having integrals running over the interval [0,∞], and one does not need to test for a sufficiently large upper integration limit as one does for the latter approach. For analytical reductions of integrals arising from any of the three, however, there is the possible drawback for large M of there being fewer tabled integrals over [0,1] than over [0,∞]. In particular, the results of both prior and current representations have integration variables residing within square roots asarguments of Macdonald functions. In a number of cases, these can be converted to Meijer G-functions whose arguments have the form (ax2+bx+c)/x, for which a single tabled integral exists for the integrals from running over the interval [0,∞] of the prior paper, and from which other forms can be found using the techniques given therein. This is not so for integral representations over the interval [0,1]. Finally, we introduce a fourth integral representation that is not easily generalizable to large M but may well provide a bridge for finding the requisite integrals for such Meijer G-functions over [0,1].

Objective: We sought to several develop parsimonious machine learning models to predict resource utilization and clinical outcomes following cardiac operations using only preoperative factors. Methods: All patients undergoing coronary artery bypass grafting and/or valve operations were identified in the 2015-2021 University of California Cardiac Surgery Consortium repository. The primary end point of the study was length of stay (LOS). Secondary endpoints included 30-day mortality, acute kidney injury, reoperation, postoperative blood transfusion and duration of intensive care unit admission (ICU LOS). Linear regression, gradient boosted machines, random forest, extreme gradient boosting predictive models were developed. The coefficient of determination and area under the receiver operating characteristic (AUC) were used to compare models. Important predictors of increased resource use were identified using SHapley summary plots. Results: Compared with all other modeling strategies, gradient boosted machines demonstrated the greatest performance in the prediction of LOS (coefficient of determination, 0.42), ICU LOS (coefficient of determination, 0.23) and 30-day mortality (AUC, 0.69). Advancing age, reduced hematocrit, and multiple-valve procedures were associated with increased LOS and ICU LOS. Furthermore, the gradient boosted machine model best predicted acute kidney injury (AUC, 0.76), whereas random forest exhibited greatest discrimination in the prediction of postoperative transfusion (AUC, 0.73). We observed no difference in performance between modeling strategies for reoperation (AUC, 0.80). Conclusions: Our findings affirm the utility of machine learning in the estimation of resource use and clinical outcomes following cardiac operations. We identified several risk factors associated with increased resource use, which may be used to guide case scheduling in times of limited hospital capacity.

Aims: There is an increasing concern of osteoporotic fractures in the ageing population. Low-magnitude high-frequency vibration (LMHFV) was shown to significantly enhance osteoporotic fracture healing through alteration of osteocyte lacuno-canalicular network (LCN). Dentin matrix protein 1 (DMP1) in osteocytes is known to be responsible for maintaining the LCN and mineralization. This study aimed to investigate the role of osteocyte-specific DMP1 during osteoporotic fracture healing augmented by LMHFV. Methods: A metaphyseal fracture was created in the distal femur of ovariectomy-induced osteoporotic Sprague Dawley rats. Rats were randomized to five different groups: 1) DMP1 knockdown (KD), 2) DMP1 KD + vibration (VT), 3) Scramble + VT, 4) VT, and 5) control (CT), where KD was performed by injection of short hairpin RNA (shRNA) into marrow cavity; vibration treatment was conducted at 35 Hz, 0.3 g; 20 minutes/day, five days/week). Assessments included radiography, micro-CT, dynamic histomorphometry and immunohistochemistry on DMP1, sclerostin, E11, and fibroblast growth factor 23 (FGF23). In vitro, murine long bone osteocyte-Y4 (MLO-Y4) osteocyte-like cells were randomized as in vivo groupings. DMP1 KD was performed by transfecting cells with shRNA plasmid. Assessments included immunocytochemistry on osteocyte-specific markers as above, and mineralized nodule staining. Results: Healing capacities in DMP1 KD groups were impaired. Results showed that DMP1 KD significantly abolished vibration-enhanced fracture healing at week 6. DMP1 KD significantly altered the expression of osteocyte-specific markers. The lower mineralization rate in DMP1 KD groups indicated that DMP1 knockdown was associated with poor fracture healing process. Conclusion: The blockage of DMP1 would impair healing outcomes and negate LMHFV-induced enhancement on fracture healing. These findings reveal the importance of DMP1 in response to the mechanical signal during osteoporotic fracture healing. Cite this article: Bone Joint Res 2022;11(7):465–476.

Introduction: Pelvic organ prolapse (POP) is one contributor to recent increases in sow mortality that have been observed in some populations and environments, leading to financial losses and welfare concerns.Methods: With inconsistent previous reports, the objective here was to investigate the role of genetics on susceptibility to POP, using data on 30,429 purebred sows, of which 14,186 were genotyped (25K), collected from 2012 to 2022 in two US multiplier farms with a high POP incidence of 7.1% among culled and dead sows and ranging from 2% to 4% of all sows present by parity. Given the low incidence of POP for parities 1 and >6, only data from parities 2 to 6 were retained for analyses. Genetic analyses were conducted both across parities, using cull data (culled for POP versus another reason), and by parity, using farrowing data. (culled for POP versus culled for another reason or not culled).Results and Discussion: Estimates of heritability from univariate logit models on the underlying scale were 0.35 ± 0.02 for the across-parity analysis and ranged from 0.41 ± 0.03 in parity 2 to 0.15 ± 0.07 in parity 6 for the by-parity analyses. Estimates of genetic correlations of POP between parities based on bivariate linear models indicated a similar genetic basis of POP across parities but less similar with increasing distance between parities. Genome wide association analyses revealed six 1 Mb windows that explained more than 1% of the genetic variance in the across-parity data. Most regions were confirmed in several by-parity analyses. Functional analyses of the identified genomic regions showed a potential role of several genes on chromosomes 1, 3, 7, 10, 12, and 14 in susceptibility to POP, including the Estrogen Receptor gene. Gene set enrichment analyses showed that genomic regions that explained more variation for POP were enriched for several terms from custom transcriptome and gene ontology libraries.Conclusion: The influence of genetics on susceptibility to POP in this population and environment was confirmed and several candidate genes and biological processes were identified that can be targeted to better understand and mitigate the incidence of POP.

Abstract Background Bayesian genomic prediction methods were developed to simultaneously fit all genotyped markers to a set of available phenotypes for prediction of breeding values for quantitative traits, allowing for differences in the genetic architecture (distribution of marker effects) of traits. These methods also provide a flexible and reliable framework for genome-wide association (GWA) studies. The objective here was to review developments in Bayesian hierarchical and variable selection models for GWA analyses. Results By fitting all genotyped markers simultaneously, Bayesian GWA methods implicitly account for population structure and the multiple-testing problem of classical single-marker GWA. Implemented using Markov chain Monte Carlo methods, Bayesian GWA methods allow for control of error rates using probabilities obtained from posterior distributions. Power of GWA studies using Bayesian methods can be enhanced by using informative priors based on previous association studies, gene expression analyses, or functional annotation information. Applied to multiple traits, Bayesian GWA analyses can give insight into pleiotropic effects by multi-trait, structural equation, or graphical models. Bayesian methods can also be used to combine genomic, transcriptomic, proteomic, and other -omics data to infer causal genotype to phenotype relationships and to suggest external interventions that can improve performance. Conclusions Bayesian hierarchical and variable selection methods provide a unified and powerful framework for genomic prediction, GWA, integration of prior information, and integration of information from other -omics platforms to identify causal mutations for complex quantitative traits.

Abstract Background An important goal in animal breeding is to improve longitudinal traits. The objective of this study was to explore for longitudinal residual feed intake (RFI) data, which estimated breeding value (EBV), or combination of EBV, to use in a breeding program. Linear combinations of EBV (summarized breeding values, SBV) or phenotypes (summarized phenotypes) derived from the eigenvectors of the genetic covariance matrix over time were considered, and the linear regression method (LR method) was used to facilitate the evaluation of their prediction accuracy. Results Weekly feed intake, average daily gain, metabolic body weight, and backfat thickness measured on 2435 growing French Large White pigs over a 10-week period were analysed using a random regression model. In this population, the 544 dams of the phenotyped animals were genotyped. These dams did not have own phenotypes. The quality of the predictions of SBV and breeding values from summarized phenotypes of these females was evaluated. On average, predictions of SBV at the time of selection were unbiased, slightly over-dispersed and less accurate than those obtained with additional phenotypic information. The use of genomic information did not improve the quality of predictions. The use of summarized instead of longitudinal phenotypes resulted in predictions of breeding values of similar quality. Conclusions For practical selection on longitudinal data, the results obtained with this specific design suggest that the use of summarized phenotypes could facilitate routine genetic evaluation of longitudinal traits.

Abstract Monolayer molybdenum disulfide has been previously discovered to exhibit non-volatile resistive switching behavior in a vertical metal-insulator-metal structure, featuring ultra-thin sub-nanometer active layer thickness. However, the reliability of these nascent 2D-based memory devices was not previously investigated for practical applications. Here, we employ an electron irradiation treatment on monolayer MoS2 film to modify the defect properties. Raman, photoluminescence, and X-ray photoelectron spectroscopy measurements have been performed to confirm the increasing amount of sulfur vacancies introduced by the e-beam irradiation process. The statistical electrical studies reveal the reliability can be improved by up to 1.5× for yield and 11× for average DC cycling endurance in the devices with a moderate radiation dose compared to unirradiated devices. Based on our previously proposed virtual conductive-point model with the metal ion substitution into sulfur vacancy, Monte Carlo simulations have been performed to illustrate the irradiation effect on device reliability, elucidating a clustering failure mechanism. This work provides an approach by electron irradiation to enhance the reliability of 2D memory devices and inspires further research in defect engineering to precisely control the switching properties for a wide range of applications from memory computing to radio-frequency switches.

The purpose of this study is to describe the prevalence, trends, and associations of the use of outpatient prescription non-narcotic analgesics and proton pump inhibitors (PPIs) in Taiwan from 2010 to 2021. We identified the most commonly prescribed analgesics and PPIs, including paracetamol (acetaminophen) and nonsteroidal anti-inflammatory drugs (NSAIDs), in outpatient departments according to the data from Taiwan National Health Insurance Research Database and Taiwan’s NHI Annual Statistical Report. This study shows that the traditional non-selective NSAIDs take the largest proportion of usage, representing over 60% of the annual usage of non-narcotic analgesics. Acetaminophen is the second and takes over 30% of annual usage. The selective COX-2 (coxibs) takes less than 10% of usage, but its use is growing rapidly. This study also shows that the annual usage of PPIs is growing rapidly and is not decreasing with the use of selective COX-2. The findings in this study can help us to focus on the most commonly prescribed drugs to investigate the prescription pattern of NSAIDs and PPIs, especially the combined use of selective COX-2 and PPIs, in future study.

Abstract Background Disease resilience is the ability to maintain performance across environments with different disease challenge loads (CL). A reaction norm describes the phenotypes that a genotype can produce across a range of environments and can be implemented using random regression models. The objectives of this study were to: (1) develop measures of CL using growth rate and clinical disease data recorded under a natural polymicrobial disease challenge model; and (2) quantify genetic variation in disease resilience using reaction norm models. Methods Different CL were derived from contemporary group effect estimates for average daily gain (ADG) and clinical disease phenotypes, including medical treatment rate (TRT), mortality rate, and subjective health scores. Resulting CL were then used as environmental covariates in reaction norm analyses of ADG and TRT in the challenge nursery and finisher, and compared using model loglikelihoods and estimates of genetic variance associated with CL. Linear and cubic spline reaction norm models were compared based on goodness-of-fit and with multi-variate analyses, for which phenotypes were separated into three traits based on low, medium, or high CL. Results Based on model likelihoods and estimates of genetic variance explained by the reaction norm, the best CL for ADG in the nursery was based on early ADG in the finisher, while the CL derived from clinical disease traits across the nursery and finisher was best for ADG in the finisher and for TRT in the nursery and across the nursery and finisher. With increasing CL, estimates of heritability for nursery and finisher ADG initially decreased, then increased, while estimates for TRT generally increased with CL. Genetic correlations for ADG and TRT were low between high versus low CL, but high for close CL. Linear reaction norm models fitted the data significantly better than the standard genetic model without genetic slopes, while the cubic spline model fitted the data significantly better than the linear reaction norm model for most traits. Reaction norm models also fitted the data better than multi-variate models. Conclusions Reaction norm models identified genotype-by-environment interactions related to disease CL. Results can be used to select more resilient animals across different levels of CL, high-performance animals at a given CL, or a combination of these.

Abstract Background Linkage disequilibrium (LD) is commonly measured based on the squared coefficient of correlation $$\left({r}^{2}\right)$$ r 2 between the alleles at two loci that are carried by haplotypes. LD can also be estimated as the $${r}^{2}$$ r 2 between unphased genotype dosage at two loci when the allele frequencies and inbreeding coefficients at both loci are identical for the parental lines. Here, we investigated whether $${r}^{2}$$ r 2 for a crossbred population (F1) can be estimated using genotype data. The parental lines of the crossbred (F1) can be purebred or crossbred. Methods We approached this by first showing that inbreeding coefficients for an F1 crossbred population are negative, and typically differ in size between loci. Then, we proved that the expected $${r}^{2}$$ r 2 computed from unphased genotype data is expected to be identical to the $${r}^{2}$$ r 2 computed from haplotype data for an F1 crossbred population, regardless of the inbreeding coefficients at the two loci. Finally, we investigated the bias and precision of the $${r}^{2}$$ r 2 estimated using unphased genotype versus haplotype data in stochastic simulation. Results Our findings show that estimates of $${r}^{2}$$ r 2 based on haplotype and unphased genotype data are both unbiased for different combinations of allele frequencies, sample sizes (900, 1800, and 2700), and levels of LD. In general, for any allele frequency combination and $${r}^{2}$$ r 2 value scenarios considered, and for both methods to estimate $${r}^{2}$$ r 2 , the precision of the estimates increased, and the bias of the estimates decreased as sample size increased, indicating that both estimators are consistent. For a given scenario, the $${r}^{2}$$ r 2 estimates using haplotype data were more precise and less biased using haplotype data than using unphased genotype data. As sample size increased, the difference in precision and biasedness between the $${r}^{2}$$ r 2 estimates using haplotype data and unphased genotype data decreased. Conclusions Our theoretical derivations showed that estimates of LD between loci based on unphased genotypes and haplotypes in F1 crossbreds have identical expectations. Based on our simulation results, we conclude that the LD for an F1 crossbred population can be accurately estimated from unphased genotype data. The results also apply for other crosses (F2, F3, Fn, BC1, BC2, and BCn), as long as (selected) individuals from the two parental lines mate randomly.

Abstract Background Deterministic predictions of the accuracy of genomic estimated breeding values (GEBV) when combining information sources have been developed based on selection index theory (SIT) and on Fisher information (FI). These two approaches have resulted in slightly different results when considering the combination of pedigree and genomic information. Here, we clarify this apparent contradiction, both for the combination of pedigree and genomic information and for the combination of subpopulations into a joint reference population. Results First, we show that existing expressions for the squared accuracy of GEBV can be understood as a proportion of the variance explained. Next, we show that the apparent discrepancy that has been observed between accuracies based on SIT vs. FI originated from two sources. First, the FI referred to the genetic component that is captured by the marker genotypes, rather than the full genetic component. Second, the common SIT-based derivations did not account for the increase in the accuracy of GEBV due to a reduction of the residual variance when combining information sources. The SIT and FI approaches are equivalent when these sources are accounted for. Conclusions The squared accuracy of GEBV can be understood as a proportion of the variance explained. The SIT and FI approaches for combining information for GEBV are equivalent and provide identical accuracies when the underlying assumptions are equivalent.

Wang and colleagues use a complementary GWAS approach to identify genetic loci associated with cotton fiber quality. Using a multiparent advanced-generation inter-cross population, 26 new QTLs related to cotton fiber quality were found.

Interactions between viruses during coinfections can influence viral fitness and population diversity, as seen in the generation of reassortant pandemic influenza A virus (IAV) strains. However, opportunities for interactions between closely related viruses are limited by a process known as superinfection exclusion (SIE), which blocks coinfection shortly after primary infection. Using IAVs, we asked whether SIE, an effect which occurs at the level of individual cells, could limit interactions between populations of viruses as they spread across multiple cells within a host. To address this, we first measured the kinetics of SIE in individual cells by infecting them sequentially with 2 isogenic IAVs, each encoding a different fluorophore. By varying the interval between addition of the 2 IAVs, we showed that early in infection SIE does not prevent coinfection, but that after this initial lag phase the potential for coinfection decreases exponentially. We then asked how the kinetics of SIE onset controlled coinfections as IAVs spread asynchronously across monolayers of cells. We observed that viruses at individual coinfected foci continued to coinfect cells as they spread, because all new infections were of cells that had not yet established SIE. In contrast, viruses spreading towards each other from separately infected foci could only establish minimal regions of coinfection before reaching cells where coinfection was blocked. This created a pattern of separate foci of infection, which was recapitulated in the lungs of infected mice, and which is likely to be applicable to many other viruses that induce SIE. We conclude that the kinetics of SIE onset segregate spreading viral infections into discrete regions, within which interactions between virus populations can occur freely, and between which they are blocked.