Emerging Chalcohalide Materials for Energy Applications.

Semiconductors with multiple anions currently provide a new materials platform from which improved functionality emerges, posing new challenges and opportunities in material science. This review has endeavored to emphasize the versatility of the emerging family of semiconductors consisting of mixed chalcogen and halogen anions, known as "chalcohalides". As they are multifunctional, these materials are of general interest to the wider research community, ranging from theoretical/computational scientists to experimental materials scientists. This review provides a comprehensive overview of the development of emerging Bi- and Sb-based as well as a new Cu, Sn, Pb, Ag, and hybrid organic-inorganic perovskite-based chalcohalides. We first highlight the high-throughput computational techniques to design and develop these chalcohalide materials. We then proceed to discuss their optoelectronic properties, band structures, stability, and structural chemistry employing theoretical and experimental underpinning toward high-performance devices. Next, we present an overview of recent advancements in the synthesis and their wide range of applications in energy conversion and storage devices. Finally, we conclude the review by outlining the impediments and important aspects in this field as well as offering perspectives on future research directions to further promote the development of chalcohalide materials in practical applications in the future.

Quantification of the effect of in utero events on lifetime resilience in dairy cows.

Currently, the dairy industry is facing many challenges that could affect its sustainability, including climate change and public perception of the industry. As a result, interest is increasing in the concept of identifying resilient animals, those with a long productive lifespan, as well as good reproductive performance and milk yield. There is much evidence that events in utero, that is, the developmental origins of health and disease hypothesis, alter the life-course health of offspring and we hypothesized that these could alter resilience in calves, where resilience is identified using lifetime data. The aim of this study was to quantify lifetime resilience scores (LRS) using an existing scoring system, based on longevity with secondary corrections for age at first calving and calving interval, and to quantify the effects of in utero events on the LRS using 2 datasets. The first was a large dataset of cattle on 83 farms in Great Britain born from 2006 to 2015 and the second was a smaller, more granular dataset of cattle born between 2003 and 2015 in the Langhill research herd at Scotland's Rural College. Events during dam's pregnancy included health events (lameness, mastitis, use of an antibiotic or anti-inflammatory medication), the effect of heat stress as measured by temperature-humidity index, and perturbations in milk yield and quality (somatic cell count, percentage fat, percentage protein and fat:protein ratio). Daughters born to dams that experienced higher temperature-humidity indexes while they were in utero during the first and third trimesters of pregnancy had lower LRS. Daughter LRS were also lower where milk yields or median fat percentages in the first trimester were low, and when milk yields were high in the third trimester. Dam LRS was positively associated with LRS of their offspring; however, as parity of the dam increased, LRS of their calves decreased. Similarly, in the Langhill herd, dams of a higher parity produced calves with lower LRS. Additionally, dams that recorded a high maximum locomotion score in the third trimester of pregnancy were negatively associated with lower calf LRS in the Langhill herd. Our results suggest that events that occur during pregnancy have lifelong consequences for the calf's lifetime performance. However, experience of higher temperature-humidity indexes, higher dam LRS, and mothers in higher parities explained a relatively small proportion of variation in offspring LRS, which suggests that other factors play a substantial role in determining calf LRS. Although "big data" can contain a considerable amount of noise, similar findings between the 2 datasets indicate it is likely these findings are real.

A Randomized Trial of Lenient Versus Strict Arm Instruction Post Cardiac Device Surgery (LENIENT).

BACKGROUND: Arm restriction after cardiac implantable electronic device (CIED) placement is common practice despite minimal supporting evidence. Patients receive a range of restriction recommendations of variable durations with the goal of reducing complications such as wound dehiscence, infection, lead dislodgement, or hematoma formation. These movement limitations can lead to emotional stress and anxiety, complications such as frozen shoulder, and upper extremity venous thrombosis due to immobilization. There are no published clinical trials assessing the benefits and risks of arm restrictions post-CIED implant. OBJECTIVES: The randomized trial of lenient vs strict arm and activity instruction post-CIED surgery (LENIENT trial; NCT04915261) is a single center nonblinded randomized prospective study designed to evaluate lenient compared to restrictive post-CIED care instructions. We hypothesize that there will be no significant difference in complications between the arms. METHODS/DESIGN: All patients receiving a de novo CIED or those with upgrades and revisions requiring a new lead implant will be enrolled. Subjects are enrolled in a nonblinded randomized prospective trial with 6 randomly assigned 8-month periods, during which either a lenient or restrictive postoperative activity instructions will be given to all patients. Postoperative instructions are given at the time of discharge and further reinforced by recurrent interactive voice recognition (IVR) phone calls, text messages and emails. The requirement for individual consent has been waived. The primary end point is a composite of (1) lead dislodgement, (2) frozen shoulder, (3) upper extremity venous thrombosis, (4) clinically significant hematoma, and (5) infection occurring within 52 weeks of index surgery. The study is a noninferiority trial with a sample size of 1,250 per group. DISCUSSION: This is the first large randomized clinical trial designed to establish an evidence-based postoperative standard of care for patients undergoing CIED implantation. This will improve the quality of care provided to patients and help guide implanting physicians providing postoperative care instructions. TRIAL REGISTRATION: ClinicalTrials.gov NCT04915261.

Modelling livestock infectious disease control policy under differing social perspectives on vaccination behaviour.

The spread of infection amongst livestock depends not only on the traits of the pathogen and the livestock themselves, but also on the veterinary health behaviours of farmers and how this impacts their implementation of disease control measures. Controls that are costly may make it beneficial for individuals to rely on the protection offered by others, though that may be sub-optimal for the population. Failing to account for socio-behavioural properties may produce a substantial layer of bias in infectious disease models. We investigated the role of heterogeneity in vaccine response across a population of farmers on epidemic outbreaks amongst livestock, caused by pathogens with differential speed of spread over spatial landscapes of farms for two counties in England (Cumbria and Devon). Under different compositions of three vaccine behaviour groups (precautionary, reactionary, non-vaccination), we evaluated from population- and individual-level perspectives the optimum threshold distance to premises with notified infection that would trigger responsive vaccination by the reactionary vaccination group. We demonstrate a divergence between population and individual perspectives in the optimal scale of reactive voluntary vaccination response. In general, minimising the population-level perspective cost requires a broader reactive uptake of the intervention, whilst optimising the outcome for the average individual increased the likelihood of larger scale disease outbreaks. When the relative cost of vaccination was low and the majority of premises had undergone precautionary vaccination, then adopting a perspective that optimised the outcome for an individual gave a broader spatial extent of reactive response compared to a perspective wanting to optimise outcomes for everyone in the population. Under our assumed epidemiological context, the findings identify livestock disease intervention receptiveness and cost combinations where one would expect strong disagreement between the intervention stringency that is best from the perspective of a stakeholder responsible for supporting the livestock industry compared to a sole livestock owner. Were such discord anticipated and achieving a consensus view across perspectives desired, the findings may also inform those managing veterinary health policy the requisite reduction in intervention cost and/or the required extent of nurturing beneficial community attitudes towards interventions.

A multistate modeling approach to investigate long-term effects of claw horn disruption lesions and early lesion development in dairy cows.

Claw horn disruption lesions (CHDL) are a leading cause of lameness in dairy cattle, and the development, effect, and pathology of these lesions remains an open area of interest within dairy cattle health. Current literature typically attempts to measure the effect of risk factors on the development of CHDL over a relatively short time period. Further understanding of the interaction of CHDL and the long-term effect of early CHDL in a cow's life remains an important area of research which is so far mostly unexplored. In this study 57,974 cows from 1,332 herds were selected and their regular claw trimming records containing important claw health information were used to model the long-term effect of lesions in a cow's lifetime in a 6-state multistate model. A multistate model predicts the time before transition from any one state to another and the probability of transition to a future state. The 6 lesion states that were modeled were as follows: never had a lesion, first recorded lesion event, no recorded lesion after first lesion event, second or subsequent recorded lesion event, no recorded lesion after second or subsequent lesion event, and culled. The effect of various cow level covariates on the transition probabilities between various states was tested. For the first time, this study shows the importance and effect of the first lesion and other cow level factors on long-term claw health. Model results showed that the timing and severity of the first recorded lesion event significantly influenced the likelihood of a future lesion being present. Cows with CHDL present within the 180 d of first calving had a short-term increased risk and long-term decreased risk of a future lesion, compared with cows that present with CHDL later than 180 d of first lactation. Moreover, presence of a severe first lesion increased a cow's risk of a future lesion being present. The model was used to evaluate the relative difference between high-risk cows (age of first calving ≥793 d, breeding values in the lowest quartile) and low-risk cows (age of first calving ≤718 d, breeding values in the highest quartile). Our results indicated that these low-risk cows present with a lesion on an average 3 mo later than high-risk cows. Furthermore, results from the model evaluation of a simulated herd with cows with breeding values in the higher quartile indicated that cows present with a CHDL on an average 7.5 mo later compared with a herd where cows have breeding values distributed in a lower quartile.

Serum 1H nuclear magnetic resonance-based metabolomics of sole lesion development in Holstein cows.

Sole hemorrhage and sole ulcers, referred to as sole lesions, are important causes of lameness in dairy cattle. We aimed to compare the serum metabolome of dairy cows that developed sole lesions in early lactation with that of cows that remained unaffected. We prospectively enrolled a cohort of 1,169 Holstein dairy cows from a single dairy herd and assessed animals at 4 time points: before calving, immediately after calving, early lactation, and late lactation. Sole lesions were recorded by veterinary surgeons at each time point, and serum samples were collected at the first 3 time points. Cases were defined by the presence of sole lesions in early lactation and further subdivided by whether sole lesions had been previously recorded; unaffected controls were randomly selected to match cases. Serum samples from a case-control subset of 228 animals were analyzed with proton nuclear magnetic resonance spectroscopy. Spectral signals, corresponding to 34 provisionally annotated metabolites and 51 unlabeled metabolites, were analyzed in subsets relating to time point, parity cohort, and sole lesion outcome. We used 3 analytic methods (partial least squares discriminant analysis, least absolute shrinkage and selection operator regression, and random forest) to determine the predictive capacity of the serum metabolome and identify informative metabolites. We applied bootstrapped selection stability, triangulation, and permutation to support the inference of variable selection. The average balanced accuracy of class prediction ranged from 50 to 62% depending on the subset. Across all 17 subsets, 20 variables had a high probability of being informative; those with the strongest evidence of being associated with sole lesions corresponded to phenylalanine and 4 unlabeled metabolites. We conclude that the serum metabolome, as characterized by proton nuclear magnetic resonance spectroscopy, does not appear able to predict sole lesion presence or future development of lesions. A small number of metabolites may be associated with sole lesions although, given the poor prediction accuracies, these metabolites are likely to explain only a small proportion of the differences between affected and unaffected animals. Future metabolomic studies may reveal underlying metabolic mechanisms of sole lesion etiopathogenesis in dairy cows; however, the experimental design and analysis need to effectively control for interanimal and extraneous sources of spectral variation.

An observational study of ear-tagged calf mortality (1 to 100 days) on Irish dairy farms and associations between biosecurity practices and calf mortality on farms participating in a Johne's disease control program.

Postnatal mortality among replacement stock has a detrimental effect on the social, economic, and environmental sustainability of dairy production. Calf mortality rates vary between countries and show differences in temporal trends; most, however, are characterized by high levels of between-farm variability. Explaining this variation can be difficult because herd-level information on management practices relevant to calf health is often not available. The Irish Johne's Control Programme (IJCP) contains a substantial on-farm monitoring program called the Veterinary Risk Assessment and Management Plan (VRAMP). Although this risk assessment is largely focused on factors relevant to the transmission of paratuberculosis, many of its principles are good practice biocontainment policies that are also advocated for the protection of calf health. The objectives of this study were (1) to quantify mortality in ear-tagged Irish dairy calves between 2016 and 2020 using both survival and risk approaches, (2) to determine risk factors for 100-d cumulative mortality hazard in ear-tagged Irish dairy calves between 2016 and 2020, (3) to determine whether 100-d cumulative mortality hazard was higher in ear-tagged calves within herds registered in the IJCP versus those that were not registered in the IJCP and whether there were differences between these cohorts over time, and (4) within IJCP herds, to determine whether VRAMP score or changes in VRAMP score were associated with 100-d cumulative mortality hazard. Excluding perinatal mortality, the overall 100-d cumulative mortality hazard was 4.1%. Calf mortality was consistently underestimated using risk approaches that did not account for calf censoring. Cox proportional hazards models showed that cumulative mortality hazard was greater in male calves; particularly, calves born to Jersey breed dams and those with a beef breed sire. Mortality hazard increased with increasing herd size, was highest in calves born in herds that contract-reared heifers, and lowest in those born in mixed dairy-beef enterprises. Mortality hazard decreased over time with the mortality hazard in 2020 being 0.83 times that of 2016. Mortality hazard was higher in IJCP-registered herds than nonregistered herds (hazard ratio 1.06, 95% CI 1.01-1.12), likely reflecting differences in herds that enrolled in the national program. However, we detected a significant interaction between IJCP status (enrolled vs. not enrolled) and year (hazard ratio 0.96, 95% CI 0.92-1.00), indicating that the decrease in mortality hazard between 2016 and 2020 was greater in IJCP herds versus non-IJCP herds. Finally, increasing VRAMP scores (indicating higher risk for paratuberculosis transmission) were positively associated with increased calf mortality hazard. Postnatal calf mortality rates in Irish dairy herds declined between 2016 and 2020. Our study suggests that implementation of recommended biocontainment practices to control paratuberculosis in IJCP herds was associated with a reduction in calf mortality hazard.

Predicting lameness in dairy cattle using untargeted liquid chromatography-mass spectrometry-based metabolomics and machine learning.

Lameness in dairy cattle is a highly prevalent condition that impacts on the health and welfare of dairy cows. Prompt detection and implementation of effective treatment is important for managing lameness. However, major limitations are associated with visual assessment of lameness, which is the most commonly used method to detect lameness. The aims of this study were to investigate the use of metabolomics and machine learning to develop novel methods to detect lameness. Untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS) alongside machine learning models and a stability selection method were utilized to evaluate the predictive accuracy of differences in the metabolomics profile of first-lactation dairy cows before (during the transition period) and at the time of lameness (based on visual assessment using the 0-3 scale of the Agriculture and Horticulture Development Board). Urine samples were collected from 2 cohorts of dairy heifers and stored at -86°C before analysis using LC-MS. Cohort 1 (n = 90) cows were recruited as current first-lactation cows with weekly mobility scores recorded over a 4-mo timeframe, from which newly lame and nonlame cows were identified. Cohort 2 (n = 30) cows were recruited within 3 wk before calving, and lameness events (based on mobility score) were recorded through lactation until a minimum of 70 d in milk (DIM). All cows were matched paired by DIM ± 14 d. The median DIM at lameness identification was 187.5 and 28.5 for cohort 1 and 2, respectively. The best performing machine learning models predicted lameness at the time of lameness with an accuracy of between 81 and 82%. Using stability selection, the prediction accuracy at the time of lameness was 80 to 81%. For samples collected before and after calving, the best performing machine learning model predicted lameness with an accuracy of 71 and 75%, respectively. The findings from this study demonstrate that untargeted LC-MS profiling combined with machine learning methods can be used to predict lameness as early as before calving and before observable changes in gait in first-lactation dairy cows. The methods also provide accuracies for detecting lameness at the time of observable changes in gait of up to 82%. The findings demonstrate that these methods could provide substantial advancements in the early prediction and prevention of lameness risk. Further external validation work is required to confirm these findings are generalizable; however, this study provides the basis from which future work can be conducted.

Importance of genetic testing in unexplained cardiac arrest.

AIMS: Genetic testing is recommended in specific inherited heart diseases but its role remains unclear and it is not currently recommended in unexplained cardiac arrest (UCA). We sought to assess the yield and clinical utility of genetic testing in UCA using whole-exome sequencing (WES). METHODS AND RESULTS: Survivors of UCA requiring external defibrillation were included from the Cardiac Arrest Survivor with Preserved Ejection fraction Registry. Whole-exome sequencing was performed, followed by assessment of rare variants in previously reported cardiovascular disease genes. A total of 228 UCA survivors (mean age at arrest 39 ± 13 years) were included. The majority were males (66%) and of European ancestry (81%). Following advanced clinical testing at baseline, the likely aetiology of cardiac arrest was determined in 21/228 (9%) cases. Whole-exome sequencing identified a pathogenic or likely pathogenic (P/LP) variant in 23/228 (10%) of UCA survivors overall, increasing the proportion of 'explained' cases from 9% only following phenotyping to 18% when combining phenotyping with WES. Notably, 13 (57%) of the 23 P/LP variants identified were located in genes associated with cardiomyopathy, in the absence of a diagnosis of cardiomyopathy at the time of arrest. CONCLUSIONS: Genetic testing identifies a disease-causing variant in 10% of apparent UCA survivors. The majority of disease-causing variants was located in cardiomyopathy-associated genes, highlighting the arrhythmogenic potential of such variants in the absence of an overt cardiomyopathy diagnosis. The present study supports the use of genetic testing including assessment of arrhythmia and cardiomyopathy genes in survivors of UCA.

Large-Grain Spanning Monolayer Cu2 ZnSnSe4 Thin-Film Solar Cells Grown from Metal Precursor.

The persistent double layer structure whereby two layers with different properties form at the front and rear of absorbers is a critical challenge in the field of kesterite thin-film solar cells, which imposes additional nonradiative recombination in the quasi-neutral region and potential limitation to the transport of hole carriers. Herein, an effective model for growing monolayer CZTSe thin-films based on metal precursors with large grains spanning the whole film is developed. Voids and fine grain layer are avoided successfully by suppressing the formation of a Sn-rich liquid metal phase near Mo back contact during alloying, while grain coarsening is greatly promoted by enhancing mass transfer during grain growth. The desired morphology exhibits several encouraging features, including significantly reduced recombination in the quasi-neutral region that contributes to the large increase of short-circuit current, and a quasi-Ohmic back contact which is a prerequisite for high fill factor. Though this growth mode may introduce more interfacial defects which require further modification, the strategies demonstrated remove a primary obstacle toward higher efficiency kesterite solar cells, and can be applicable to morphology control with other emerging chalcogenide thin films.

10.3% Efficient Green Cd-Free Cu2 ZnSnS4 Solar Cells Enabled by Liquid-Phase Promoted Grain Growth.

Small grain size and near-horizontal grain boundaries are known to be detrimental to the carrier collection efficiency and device performance of pure-sulfide Cu2 ZnSnS4 (CZTS) solar cells. However, forming large grains spanning the absorber layer while maintaining high electronic quality is challenging particularly for pure sulfide CZTS. Herein, a liquid-phase-assisted grain growth (LGG) model that enables the formation of large grains spanning across the CZTS absorber without compromising the electronic quality is demonstrated. By introducing a Ge-alloyed CZTS nanoparticle layer at the bottom of the sputtered precursor, a Cu-rich and Sn-rich liquid phase forms at the high temperature sulfurization stage, which can effectively remove the detrimental near-horizontal grain boundaries and promote grain growth, thus greatly improving the carrier collection efficiency and reducing nonradiative recombination. The remaining liquid phase layer at the rear interface shows a high work function, acting as an effective hole transport layer. The modified morphology greatly increases the short-circuit current density and fill factor, enabling 10.3% efficient green Cd-free CZTS devices. This work unlocks a grain growth mechanism, advancing the morphology control of sulfide-based kesterite solar cells.

Mass spectrometry and machine learning for the accurate diagnosis of benzylpenicillin and multidrug resistance of Staphylococcus aureus in bovine mastitis.

Staphylococcus aureus is a serious human and animal pathogen threat exhibiting extraordinary capacity for acquiring new antibiotic resistance traits in the pathogen population worldwide. The development of fast, affordable and effective diagnostic solutions capable of discriminating between antibiotic-resistant and susceptible S. aureus strains would be of huge benefit for effective disease detection and treatment. Here we develop a diagnostics solution that uses Matrix-Assisted Laser Desorption/Ionisation-Time of Flight Mass Spectrometry (MALDI-TOF) and machine learning, to identify signature profiles of antibiotic resistance to either multidrug or benzylpenicillin in S. aureus isolates. Using ten different supervised learning techniques, we have analysed a set of 82 S. aureus isolates collected from 67 cows diagnosed with bovine mastitis across 24 farms. For the multidrug phenotyping analysis, LDA, linear SVM, RBF SVM, logistic regression, naïve Bayes, MLP neural network and QDA had Cohen's kappa values over 85.00%. For the benzylpenicillin phenotyping analysis, RBF SVM, MLP neural network, naïve Bayes, logistic regression, linear SVM, QDA, LDA, and random forests had Cohen's kappa values over 85.00%. For the benzylpenicillin the diagnostic systems achieved up to (mean result ± standard deviation over 30 runs on the test set): accuracy = 97.54% ± 1.91%, sensitivity = 99.93% ± 0.25%, specificity = 95.04% ± 3.83%, and Cohen's kappa = 95.04% ± 3.83%. Moreover, the diagnostic platform complemented by a protein-protein network and 3D structural protein information framework allowed the identification of five molecular determinants underlying the susceptible and resistant profiles. Four proteins were able to classify multidrug-resistant and susceptible strains with 96.81% ± 0.43% accuracy. Five proteins, including the previous four, were able to classify benzylpenicillin resistant and susceptible strains with 97.54% ± 1.91% accuracy. Our approach may open up new avenues for the development of a fast, affordable and effective day-to-day diagnostic solution, which would offer new opportunities for targeting resistant bacteria.

Metabolic alterations in dairy cattle with lameness revealed by untargeted metabolomics of dried milk spots using direct infusion-tandem mass spectrometry and the triangulation of multiple machine learning models.

Lameness is a major challenge in the dairy cattle industry in terms of animal welfare and economic implications. Better understanding of metabolic alteration associated with lameness could lead to early diagnosis and effective treatment, there-fore reducing its prevalence. To determine whether metabolic signatures associated with lameness could be discovered with untargeted metabolomics, we developed a novel workflow using direct infusion-tandem mass spectrometry to rapidly analyse (2 min per sample) dried milk spots (DMS) that were stored on commercially available Whatman® FTA® DMPK cards for a prolonged period (8 and 16 days). An orthogonal partial least squares-discriminant analysis (OPLS-DA) method validated by triangulation of multiple machine learning (ML) models and stability selection was employed to reliably identify important discriminative metabolites. With this approach, we were able to differentiate between lame and healthy cows based on a set of lipid molecules and several small metabolites. Among the discriminative molecules, we identified phosphatidylglycerol (PG 35:4) as the strongest and most sensitive lameness indicator based on stability selection. Overall, this untargeted metabolomics workflow is found to be a fast, robust, and discriminating method for determining lameness in DMS samples. The DMS cards can be potentially used as a convenient and cost-effective sample matrix for larger scale research and future routine screening for lameness.

Understanding public preferences for different dairy farming systems using a mixed-methods approach.

Global production of milk has doubled over the past 50 yr, yet dairy farming in high-income countries faces scrutiny over practices perceived to affect animal welfare. One such practice is housing dairy cows year-round without access to pasture, which is the norm across North America and increasing within Europe, despite evidence of significant public support for grazing. Diverging opinion between the farming community and the public about what animal welfare means could be a key factor; however, lack of insight into the understanding and motivations underpinning public preferences for grazing could also hamper resolution. On the basis that more information could increase engagement between parties, 60 members of the public across the United Kingdom were interviewed to understand their perspectives of 3 dairy farming scenarios incorporating different amounts of grazing or housing. Their responses were analyzed using a mixed-methods approach combining reflexive thematic analysis with linguistic analysis. The integrated results indicated participants had a dual vision of the cow, seeing her as both domestic and wild. A scenario with housing in winter and grazing in summer therefore suited her, providing both protection and naturalness, and was most associated with analytic thinking. Interviewees also confessed ignorance about the cow's needs, either deferring to others' judgment-including the cow herself-or using familiarity and anthropomorphism to assess the scenarios. This again resulted in most optimism, confidence, and positivity for housing in winter and grazing in summer, and most negativity for housing cows year-round. Grazing was aspirational, but keeping cows outside in winter was confusing and concerning. These findings offer opportunities for the dairy industry to adapt communication or systems to better meet societal views; for example, incorporating access to pasture or increasing cow choice.

The effect of environmental temperature on average daily gain in preweaned calves: A randomized controlled trial and Bayesian analysis.

Neonatal calves are relatively susceptible to heat loss, and previous research suggests that reduced environmental temperatures are associated with reduced average daily gain (ADG) during the preweaning phase. Current methods of mitigating negative effects of colder environmental conditions include the use of calf jackets and the provision of supplementary heat sources; however, previous research is limited. The aim of this study was to evaluate the effect of calf jackets and 1-kW heat lamps on the growth rates of preweaning calves and evaluate associations between environmental temperature and ADG using a Bayesian approach to incorporate both current and previous data. Seventy-nine calves from a single British dairy farm were randomly allocated at birth to 1 of the following 4 groups: no jacket and no heat lamp, heat lamp but no jacket, jacket but no heat lamp, or both heat lamp and jacket between January and April of 2021. Calves were weighed at both birth and at approximately 21 d of age. Temperature was recorded both inside and outside of the calf building, and in pens both with and without heat lamps using data loggers. To explore the effect of treatment group and environmental temperature on ADG, a fixed effects model was fitted over 1,000 bootstrap samples. The effect of environmental temperature on ADG was further explored within a Bayesian framework that used temperature and ADG data for 484 calves from 16 farms available from a previous trial as prior information. Calves housed under a 1-kW heat lamp had an increased ADG of 0.09 kg/d (95% bootstrap confidence interval: -0.02 to 0.20 kg/d), and no effect of jacket or interactions between jacket and heat lamp were found. A significant positive association was identified between the mean environmental temperature of the calf building and ADG, with a 1°C increase in temperature being associated with a 0.03 kg/d increase in ADG (95% bootstrap confidence interval: 0.01 to 0.04 kg/d). Associations between environmental temperature and ADG were further evaluated within a Bayesian framework, and posterior estimates were 0.014 kg/d of ADG per 1°C increase (95% credible interval: 0.009 to 0.021 kg/d). This study demonstrated that a 1-kW heat lamp was effective in increasing ADG in calves, and no significant effect of calf jacket on ADG was found. A significant, positive effect of increased pen temperature on calf ADG was identified in this study and was reinforced when including prior information from previous research within a Bayesian framework.

Improving growth rates in preweaning calves on dairy farms: A randomized controlled trial.

Previous research has identified key factors associated with improved average daily gain (ADG) in preweaning dairy calves and these factors have been combined to create a web app-based calf health plan (www.nottingham.ac.uk/herdhealthtoolkit). A randomized controlled trial was conducted to determine the effect of implementing this evidence-based calf health plan on both productivity and health outcomes for calves reared on British dairy farms. Sixty dairy farms were randomized by location (North, South, and Midlands) to either receive the plan at the beginning (INT) or after the end of the trial (CON) and recorded birth and weaning weights by weigh tape, and cases of morbidity and mortality. Calf records were returned for 3,593 calves from 45 farms (21 CON, 24 INT), with 1,760 calves from 43 farms having 2 weights recorded >40 d apart for ADG calculations, with 1,871 calves from 43 farms born >90 d before the end of the trial for morbidity and mortality calculations. Associations between both intervention group and the number of interventions in place with ADG were analyzed using linear regression models. Morbidity and mortality rates were analyzed using beta regression models. Mean ADG was 0.78 kg/d, ranging from 0.33 to 1.13 kg/d, with mean rates of 20.12% (0-96.55%), 16.40% (0-95.24%), and 4.28% (0-18.75%) for diarrhea, pneumonia, and mortality. The INT farms were undertaking a greater number of interventions (9.9) by the end of the trial than CON farms (7.6). Mean farm ADG was higher for calves on INT farms than CON farms for both male beef (MB, +0.22 kg/d) and dairy heifer (DH, +0.03 kg/d) calves. The MB calves on INT farms had significantly increased mean ADG (0.12 kg/d, 95% confidence interval: 0.02-0.22) compared with CON farms. No significant differences were observed between intervention groups for morbidity or mortality. Implementing one additional intervention from the plan, regardless of intervention group, was associated with improvements in mean ADG for DH calves of 0.01 kg/d (0.01, 0-0.03) and MB calves of 0.02 kg/d (0.00-0.04). Model predictions suggest that a farm with the highest number of interventions in place (15) compared with farms with the lowest number of interventions in place (4) would expect an improvement in growth rates from 0.65 to 0.81 kg/d for MB, from 0.73 to 0.88 kg/d for DH, a decrease in mortality rates from 10.9% to 2.8% in MB, and a decrease in diarrhea rates from 42.1% to 15.1% in DH. The calf health plan tested in this study represents a useful tool to aid veterinarians and farmers in the implementation of effective management interventions likely to improve the growth rates, health, and welfare of preweaning calves on dairy farms.

Short-coupled ventricular fibrillation represents a distinct phenotype among latent causes of unexplained cardiac arrest: a report from the CASPER registry.

AIMS: The term idiopathic ventricular fibrillation (IVF) describes survivors of unexplained cardiac arrest (UCA) without a specific diagnosis after clinical and genetic testing. Previous reports have described a subset of IVF individuals with ventricular arrhythmia initiated by short-coupled trigger premature ventricular contractions (PVCs) for which the term short-coupled ventricular fibrillation (SCVF) has been proposed. The aim of this article is to establish the phenotype and frequency of SCVF in a large cohort of UCA survivors. METHODS AND RESULTS: We performed a multicentre study including consecutive UCA survivors from the CASPER registry. Short-coupled ventricular fibrillation was defined as otherwise unexplained ventricular fibrillation initiated by a trigger PVC with a coupling interval of <350 ms. Among 364 UCA survivors, 24/364 (6.6%) met diagnostic criteria for SCVF. The diagnosis of SCVF was obtained in 19/24 (79%) individuals by documented ventricular fibrillation during follow-up. Ventricular arrhythmia was initiated by a mean PVC coupling interval of 274 ± 32 ms. Electrical storm occurred in 21% of SCVF probands but not in any UCA proband (P < 0.001). The median time to recurrent ventricular arrhythmia in SCVF was 31 months. Recurrent ventricular fibrillation resulted in quinidine administration in 12/24 SCVF (50%) with excellent arrhythmia control. CONCLUSION: Short-coupled ventricular fibrillation is a distinct primary arrhythmia syndrome accounting for at least 6.6% of UCA. As documentation of ventricular fibrillation onset is necessary for the diagnosis, most cases are diagnosed at the time of recurrent arrhythmia, thus the true prevalence of SCVF remains still unknown. Quinidine is effective in SCVF and should be considered as first-line treatment for patients with recurrent episodes.

An International Multicenter Evaluation of Inheritance Patterns, Arrhythmic Risks, and Underlying Mechanisms of CASQ2-Catecholaminergic Polymorphic Ventricular Tachycardia.

BACKGROUND: Genetic variants in calsequestrin-2 (CASQ2) cause an autosomal recessive form of catecholaminergic polymorphic ventricular tachycardia (CPVT), although isolated reports have identified arrhythmic phenotypes among heterozygotes. Improved insight into the inheritance patterns, arrhythmic risks, and molecular mechanisms of CASQ2-CPVT was sought through an international multicenter collaboration. METHODS: Genotype-phenotype segregation in CASQ2-CPVT families was assessed, and the impact of genotype on arrhythmic risk was evaluated using Cox regression models. Putative dominant CASQ2 missense variants and the established recessive CASQ2-p.R33Q variant were evaluated using oligomerization assays and their locations mapped to a recent CASQ2 filament structure. RESULTS: A total of 112 individuals, including 36 CPVT probands (24 homozygotes/compound heterozygotes and 12 heterozygotes) and 76 family members possessing at least 1 presumed pathogenic CASQ2 variant, were identified. Among CASQ2 homozygotes and compound heterozygotes, clinical penetrance was 97.1% and 26 of 34 (76.5%) individuals had experienced a potentially fatal arrhythmic event with a median age of onset of 7 years (95% CI, 6-11). Fifty-one of 66 CASQ2 heterozygous family members had undergone clinical evaluation, and 17 of 51 (33.3%) met diagnostic criteria for CPVT. Relative to CASQ2 heterozygotes, CASQ2 homozygote/compound heterozygote genotype status in probands was associated with a 3.2-fold (95% CI, 1.3-8.0; P=0.013) increased hazard of a composite of cardiac syncope, aborted cardiac arrest, and sudden cardiac death, but a 38.8-fold (95% CI, 5.6-269.1; P<0.001) increased hazard in genotype-positive family members. In vitro turbidity assays revealed that p.R33Q and all 6 candidate dominant CASQ2 missense variants evaluated exhibited filamentation defects, but only p.R33Q convincingly failed to dimerize. Structural analysis revealed that 3 of these 6 putative dominant negative missense variants localized to an electronegative pocket considered critical for back-to-back binding of dimers. CONCLUSIONS: This international multicenter study of CASQ2-CPVT redefines its heritability and confirms that pathogenic heterozygous CASQ2 variants may manifest with a CPVT phenotype, indicating a need to clinically screen these individuals. A dominant mode of inheritance appears intrinsic to certain missense variants because of their location and function within the CASQ2 filament structure.

High-power, short-duration atrial fibrillation ablation compared with a conventional approach: Outcomes and reconnection patterns.

BACKGROUND: The effectiveness, safety, and pulmonary vein (PV) reconnection patterns of point-by-point high-power, short-duration (HPSD) ablation relative to conventional force-time integral (FTI)-guided strategies for atrial fibrillation (AF) ablation are unknown. OBJECTIVES: To compare 1-year freedom from atrial arrhythmia (AA), complication rates, procedural times, and PV reconnection patterns with HPSD AF AF ablation versus an FTI-guided low-power, long-duration (LPLD) strategy. METHODS: We compared consecutive patients undergoing a first ablation procedure for paroxysmal or persistent AF. The HPSD protocol utilized a power of 50 W and durations of 6-8 s posteriorly and 8-10 s anteriorly. The LPLD protocol was FTI-guided with a power of ≤25 W posteriorly (FTI ≥ 300g·s) and ≤35 W anteriorly (FTI ≥ 400g·s). RESULTS: In total, 214 patients were prospectively included (107 HPSD, 107 LPLD). Freedom from AA at 1 year was achieved in 79% in the HPSD group versus 73% in the LPLD group (p = .339; adjusted hazard ratio with HPSD, 0.67; 95% confidence interval, 0.36-1.23; p < .004 for non-inferiority). Procedure duration was shorter in the HPSD group (229 ± 60 vs. 309 ± 77 min; p < .005). Patients undergoing repeat ablation had a higher propensity for reconnection at the right PV carina in the HPSD group compared with the LPLD group (14/30 = 46.7% vs. 7/34 = 20.6%; p = .035). There were no differences in complication rates. CONCLUSION: HPSD AF ablation resulted in similar freedom from AAs at 1 year, shorter procedure times, and a similar safety profile when compared with an LPLD ablation strategy. Patients undergoing HPSD ablation required more applications at the right carina to achieve isolation, and had a significantly higher rate of right carinal reconnections at redo procedures.

Numbers of close contacts of individuals infected with SARS-CoV-2 and their association with government intervention strategies.

BACKGROUND: Contact tracing is conducted with the primary purpose of interrupting transmission from individuals who are likely to be infectious to others. Secondary analyses of data on the numbers of close contacts of confirmed cases could also: provide an early signal of increases in contact patterns that might precede larger than expected case numbers; evaluate the impact of government interventions on the number of contacts of confirmed cases; or provide data information on contact rates between age cohorts for the purpose of epidemiological modelling. We analysed data from 140,204 close contacts of 39,861 cases in Ireland from 1st May to 1st December 2020. RESULTS: Negative binomial regression models highlighted greater numbers of contacts within specific population demographics, after correcting for temporal associations. Separate segmented regression models of the number of cases over time and the average number of contacts per case indicated that a breakpoint indicating a rapid decrease in the number of contacts per case in October 2020 preceded a breakpoint indicating a reduction in the number of cases by 11 days. CONCLUSIONS: We found that the number of contacts per infected case was overdispersed, the mean varied considerable over time and was temporally associated with government interventions. Analysis of the reported number of contacts per individual in contact tracing data may be a useful early indicator of changes in behaviour in response to, or indeed despite, government restrictions. This study provides useful information for triangulating assumptions regarding the contact mixing rates between different age cohorts for epidemiological modelling.