A comparison of 4 predictive models of calving assistance and difficulty in dairy heifers and cows

peer-reviewedThe aim of this study was to build and compare predictive models of calving difficulty in dairy heifers and cows for the purpose of decision support and simulation modeling. Models to predict 3 levels of calving difficulty (unassisted, slight assistance, and considerable or veterinary assistance) were created using 4 machine learning techniques: multinomial regression, decision trees, random forests, and neural networks. The data used were sourced from 2,076 calving records in 10 Irish dairy herds. In total, 19.9 and 5.9% of calving events required slight assistance and considerable or veterinary assistance, respectively. Variables related to parity, genetics, BCS, breed, previous calving, and reproductive events and the calf were included in the analysis. Based on a stepwise regression modeling process, the variables included in the models were the dam's direct and maternal calving difficulty predicted transmitting abilities (PTA), BCS at calving, parity; calving assistance or difficulty at the previous calving; proportion of Holstein breed; sire breed; sire direct calving difficulty PTA; twinning; and 2-way interactions between calving BCS and previous calving difficulty and the direct calving difficulty PTA of dam and sire. The models were built using bootstrapping procedures on 70% of the data set. The held-back 30% of the data was used to evaluate the predictive performance of the models in terms of discrimination and calibration. The decision tree and random forest models omitted the effect of twinning and included only subsets of sire breeds. Only multinomial regression and neural networks explicitly included the modeled interactions. Calving BCS, calving difficulty PTA, and previous calving assistance ranked as highly important variables for all 4 models. The area under the receiver operating characteristic curve (ranging from 0.64 to 0.79) indicates that all of the models had good overall discriminatory power. The neural network and multinomial regression models performed best, correctly classifying 75% of calving cases and showing superior calibration, with an average error in predicted probability of 3.7 and 4.5%, respectively. The neural network and multinomial regression models developed are both suitable for use in decision-support and simulation modeling

Atmospheric circulation changes and their impact on extreme sea levels around Australia

Projections of sea level rise (SLR) will lead to increasing coastal impacts during extreme sea level events globally; however, there is significant uncertainty around short-term coastal sea level variability and the attendant frequency and severity of extreme sea level events. In this study, we investigate drivers of coastal sea level variability (including extremes) around Australia by means of historical conditions as well as future changes under a high greenhouse gas emissions scenario (RCP 8.5). To do this, a multi-decade hindcast simulation is validated against tide gauge data. The role of tide–surge interaction is assessed and found to have negligible effects on storm surge characteristic heights over most of the coastline. For future projections, 20-year-long simulations are carried out over the time periods 1981–1999 and 2081–2099 using atmospheric forcing from four CMIP5 climate models. Changes in extreme sea levels are apparent, but there are large inter-model differences. On the southern mainland coast all models simulated a southward movement of the subtropical ridge which led to a small reduction in sea level extremes in the hydrodynamic simulations. Sea level changes over the Gulf of Carpentaria in the north are largest and positive during austral summer in two out of the four models. In these models, changes to the northwest monsoon appear to be the cause of the sea level response. These simulations highlight a sensitivity of this semi-enclosed gulf to changes in large-scale dynamics in this region and indicate that further assessment of the potential changes to the northwest monsoon in a larger multi-model ensemble should be investigated, together with the northwest monsoon's effect on extreme sea levels.</p

Effects of a novel, brief psychological therapy (Managing Unusual Sensory Experiences) for hallucinations in first episode psychosis (MUSE FEP): Findings from an exploratory randomised controlled trial

\ua9 2024Hallucinations are a common feature of psychosis, yet access to effective psychological treatment is limited. The Managing Unusual Sensory Experiences for First-Episode-Psychosis (MUSE-FEP) trial aimed to establish the feasibility and acceptability of a brief, hallucination-specific, digitally provided treatment, delivered by a non-specialist workforce for people with psychosis. MUSE uses psychoeducation about the causal mechanisms of hallucinations and tailored interventions to help a person understand and manage their experiences. We undertook a two-site, single-blind (rater) Randomised Controlled Trial and recruited 82 participants who were allocated 1:1 to MUSE and treatment as usual (TAU) (n = 40) or TAU alone (n = 42). Participants completed assessments before and after treatment (2 months), and at follow up (3–4 months). Information on recruitment rates, adherence, and completion of outcome assessments was collected. Analyses focussed on feasibility outcomes and initial estimates of intervention effects to inform a future trial. The trial is registered with the ISRCTN registry 16793301. Criteria for the feasibility of trial methodology and intervention delivery were met. The trial exceeded the recruitment target, had high retention rates (87.8%) at end of treatment, and at follow up (86.6%), with good acceptability of treatment. There were 3 serious adverse events in the therapy group, and 5 in the TAU group. Improvements were evident in both groups at the end of treatment and follow up, with a particular benefit in perceived recovery in the MUSE group. We showed it was feasible to increase access to psychological intervention but a definitive trial requires further changes to the trial design or treatment

Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs

BACKGROUND: Mycobacterium tuberculosis resistance to anti-tuberculosis drugs is a major threat to global public health. Whole genome sequencing (WGS) is rapidly gaining traction as a diagnostic tool for clinical tuberculosis settings. To support this informatically, previous work led to the development of the widely used TBProfiler webtool, which predicts resistance to 14 drugs from WGS data. However, for accurate and rapid high throughput of samples in clinical or epidemiological settings, there is a need for a stand-alone tool and the ability to analyse data across multiple WGS platforms, including Oxford Nanopore MinION. RESULTS: We present a new command line version of the TBProfiler webserver, which includes hetero-resistance calling and will facilitate the batch processing of samples. The TBProfiler database has been expanded to incorporate 178 new markers across 16 anti-tuberculosis drugs. The predictive performance of the mutation library has been assessed using > 17,000 clinical isolates with WGS and laboratory-based drug susceptibility testing (DST) data. An integrated MinION analysis pipeline was assessed by performing WGS on 34 replicates across 3 multi-drug resistant isolates with known resistance mutations. TBProfiler accuracy varied by individual drug. Assuming DST as the gold standard, sensitivities for detecting multi-drug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) were 94% (95%CI 93-95%) and 83% (95%CI 79-87%) with specificities of 98% (95%CI 98-99%) and 96% (95%CI 95-97%) respectively. Using MinION data, only one resistance mutation was missed by TBProfiler, involving an insertion in the tlyA gene coding for capreomycin resistance. When compared to alternative platforms (e.g. Mykrobe predictor TB, the CRyPTIC library), TBProfiler demonstrated superior predictive performance across first- and second-line drugs. CONCLUSIONS: The new version of TBProfiler can rapidly and accurately predict anti-TB drug resistance profiles across large numbers of samples with WGS data. The computing architecture allows for the ability to modify the core bioinformatic pipelines and outputs, including the analysis of WGS data sourced from portable technologies. TBProfiler has the potential to be integrated into the point of care and WGS diagnostic environments, including in resource-poor settings

Cool, Luminous, and Highly Variable Stars in the Magellanic Clouds. II: Spectroscopic and Environmental Analysis of Thorne-\.Zytkow Object and Super-AGB Star Candidates

In previous work we identified a population of 38 cool and luminous variable stars in the Magellanic Clouds and examined 11 in detail in order to classify them as either Thorne-\.Zytkow Objects (T\.ZOs, red supergiants with a neutron star cores) or super-AGB stars (the most massive stars that will not undergo core collapse). This population includes HV\,2112, a peculiar star previously considered in other works to be either a T\.ZO or high-mass AGB star. Here we continue this investigation, using the kinematic and radio environments and local star formation history of these stars to place constraints on the age of the progenitor systems and the presence of past supernovae. These stars are not associated with regions of recent star formation, and we find no evidence of past supernovae at their locations. Finally, we also assess the presence of heavy elements and lithium in their spectra compared to red supergiants. We find strong absorption in Li and s-process elements compared to RSGs in most of the sample, consistent with super-AGB nucleosynthesis, while HV\,2112 shows additional strong lines associated with T\.ZO nucleosynthesis. Coupled with our previous mass estimates, the results are consistent with the stars being massive (~4-6.5M$_{\odot}$) or super-AGB (~6.5-12M$_{\odot}$) stars in the thermally pulsing phase, providing crucial observations of the transition between low- and high-mass stellar populations. HV\,2112 is more ambiguous; it could either be a maximally massive sAGB star, or a T\.ZO if the minimum mass for stability extends down to <13 M$_\odot$.Comment: 32 pages, 10 figures, 7 tables, spectroscopic data available at https://zenodo.org/record/7058608, accepted to The Astrophysical Journa

Diagnosis and aetiology of congenital muscular dystrophy: we are halfway there

OBJECTIVES: To evaluate the diagnostic outcomes in a large cohort of congenital muscular dystrophy (CMD) patients using traditional and Next Generation Sequencing (NGS) technologies. METHODS: 123 CMD patients were investigated using the traditional approaches of histology, immunohistochemical analysis of muscle biopsy and candidate gene sequencing. Undiagnosed patients available for further testing were investigated using NGS. RESULTS: Muscle biopsy and immunohistochemical analysis found deficiencies of laminin α2, α-dystroglycan or collagen VI in 50% of patients. Candidate gene sequencing and chromosomal microarray established a genetic diagnosis in 32% (39/123). Of 85 patients presenting in the last 20 years, 28 of 51 who lacked a confirmed genetic diagnosis (55%) consented to NGS studies, leading to confirmed diagnoses in a further 11 patients. Using the combination of approaches, a confirmed genetic diagnosis was achieved in 51% (43/85). The diagnoses within the cohort were heterogeneous. 45/59 probands with confirmed or probable diagnoses had variants in genes known to cause CMD (76%), and 11/59 (19%) had variants in genes associated with congenital myopathies, reflecting overlapping features of these conditions. One patient had a congenital myasthenic syndrome and two had microdeletions. Within the cohort, five patients had variants in novel (PIGY and GMPPB) or recently published genes (GFPT1 and MICU1) and seven had variants in TTN or RYR1; large genes that are technically difficult to Sanger sequence. INTERPRETATION: These data support NGS as a first-line tool for genetic evaluation of patients with a clinical phenotype suggestive of CMD, with muscle biopsy reserved as a second-tier investigation. This article is protected by copyright. All rights reserved

Measurement of the quasi-elastic axial vector mass in neutrino-oxygen interactions

The weak nucleon axial-vector form factor for quasi-elastic interactions is determined using neutrino interaction data from the K2K Scintillating Fiber detector in the neutrino beam at KEK. More than 12,000 events are analyzed, of which half are charged-current quasi-elastic interactions nu-mu n to mu- p occurring primarily in oxygen nuclei. We use a relativistic Fermi gas model for oxygen and assume the form factor is approximately a dipole with one parameter, the axial vector mass M_A, and fit to the shape of the distribution of the square of the momentum transfer from the nucleon to the nucleus. Our best fit result for M_A = 1.20 \pm 0.12 GeV. Furthermore, this analysis includes updated vector form factors from recent electron scattering experiments and a discussion of the effects of the nucleon momentum on the shape of the fitted distributions.Comment: 14 pages, 10 figures, 6 table

Circulating microRNAs Reveal Time Course of Organ Injury in a Porcine Model of Acetaminophen-Induced Acute Liver Failure

Acute liver failure is a rare but catastrophic condition which can progress rapidly to multi-organ failure. Studies investigating the onset of individual organ injury such as the liver, kidneys and brain during the evolution of acute liver failure, are lacking. MicroRNAs are short, non-coding strands of RNA that are released into the circulation following tissue injury. In this study, we have characterised the release of both global microRNA and specific microRNA species into the plasma using a porcine model of acetaminophen-induced acute liver failure. Pigs were induced to acute liver failure with oral acetaminophen over 19h±2h and death occurred 13h±3h thereafter. Global microRNA concentrations increased 4h prior to acute liver failure in plasma (P<0.0001) but not in isolated exosomes, and were associated with increasing plasma levels of the damage-associated molecular pattern molecule, genomic DNA (P<0.0001). MiR122 increased around the time of onset of acute liver failure (P<0.0001) and was associated with increasing international normalised ratio (P<0.0001). MiR192 increased 8h after acute liver failure (P<0.0001) and was associated with increasing creatinine (P<0.0001). The increase in miR124-1 occurred concurrent with the pre-terminal increase in intracranial pressure (P<0.0001) and was associated with decreasing cerebral perfusion pressure (P<0.002)

Evidence for the η_b(1S) Meson in Radiative Υ(2S) Decay

We have performed a search for the η_b(1S) meson in the radiative decay of the Υ(2S) resonance using a sample of 91.6 × 10^6 Υ(2S) events recorded with the BABAR detector at the PEP-II B factory at the SLAC National Accelerator Laboratory. We observe a peak in the photon energy spectrum at E_γ = 609.3^(+4.6)_(-4.5)(stat)±1.9(syst) MeV, corresponding to an η_b(1S) mass of 9394.2^(+4.8)_(-4.9)(stat) ± 2.0(syst) MeV/c^2. The branching fraction for the decay Υ(2S) → γη_b(1S) is determined to be [3.9 ± 1.1(stat)^(+1.1)_(-0.9)(syst)] × 10^(-4). We find the ratio of branching fractions B[Υ(2S) → γη_b(1S)]/B[Υ(3S) → γη_b(1S)]= 0.82 ± 0.24(stat)^(+0.20)_(-0.19)(syst)