Effect of a combination phytase and carbohydrolase enzyme supplement on growth performance and bone mineralization of pigs from six weeks to slaughter at 105 kg

peer-reviewedAn experiment was conducted to assess the effect of a combination of carbohydrolase (from Talaromyces Versatilis) and 6-phytase (from Schizosaccharomyces Pombe) multi enzyme complex (mec; Rovabio Max®, Adisseo, France) on the growth and bone mineralization of pigs fed maize-wheat-soybean meal diets. Pigs (n = 384) were selected at 28 days of age, penned in same gender pairs and fed a common acclimatization diet meeting animal requirements for 14 days. Four experimental diets were formulated for each of 4 growth stages from 42 days of age to slaughter at 147 days: 1) Positive control (PC), formulated to meet nutritional requirements; 2) Negative control 1 (NC1; DE × 0.985, CP × 0.985, −1.0 g Ca/kg and −1.2 g dig P/kg), 3) Negative control 2 (NC2; DE × 0.975, CP × 0.975, −1.0 g Ca/kg and −1.2 g dig P/kg) and 4) Negative control 3 (NC3; DE × 0.975, CP × 0.975, −1.5 g Ca /kg and −1.7 g dig P/kg). Negative control diets were also supplemented with mec resulting in 7 experimental treatments. Feed disappearance, wastage and individual pig live weight (LW) were recorded at the beginning and end of each growth phase. Reducing in dietary constituents (CP, DE, P and Ca) compared to PC reduced LW (P 0.05) on metacarpal Ca or P percentages was found. It was concluded that supplementing carbohydrolase and phytase to low nutrient density diets can return the growth and FCR of the pigs as well as metacarpal and foot aBMD to the levels reached by pigs fed diets meeting nutrient recommendations

Estimated Errors in |Vcd|/|Vcs| from Semileptonic D Decays

We estimate statistical and systematic errors in the extraction of the CKM ratio |Vcd|/|Vcs| from exclusive D-meson semileptonic decays using lattice QCD and anticipated new experimental results.Comment: LATTICE98(heavyqk), LaTeX, 3 pages, 2 postscript figures, uses espcrc2.sty and hyperbasics.te

The bacterial biome of ticks and their wildlife hosts at the urban–wildland interface

Advances in sequencing technologies have revealed the complex and diverse microbial communities present in ticks (Ixodida). As obligate blood-feeding arthropods, ticks are responsible for a number of infectious diseases that can affect humans, livestock, domestic animals and wildlife. While cases of human tick-borne diseases continue to increase in the northern hemisphere, there has been relatively little recognition of zoonotic tick-borne pathogens in Australia. Over the past 5 years, studies using high-throughput sequencing technologies have shown that Australian ticks harbour unique and diverse bacterial communities. In the present study, free-ranging wildlife (n=203), representing ten mammal species, were sampled from urban and peri-urban areas in New South Wales (NSW), Queensland (QLD) and Western Australia (WA). Bacterial metabarcoding targeting the 16S rRNA locus was used to characterize the microbiomes of three sample types collected from wildlife: blood, ticks and tissue samples. Further sequence information was obtained for selected taxa of interest. Six tick species were identified from wildlife: Amblyomma triguttatum, Ixodes antechini, Ixodes australiensis, Ixodes holocyclus, Ixodes tasmani and Ixodes trichosuri. Bacterial 16S rRNA metabarcoding was performed on 536 samples and 65 controls, generating over 100 million sequences. Alpha diversity was significantly different between the three sample types, with tissue samples displaying the highest alpha diversity (P<0.001). Proteobacteria was the most abundant taxon identified across all sample types (37.3 %). Beta diversity analysis and ordination revealed little overlap between the three sample types (P<0.001). Taxa of interest included Anaplasmataceae, Bartonella, Borrelia, Coxiellaceae, Francisella, Midichloria, Mycoplasma and Rickettsia. Anaplasmataceae bacteria were detected in 17.7% (95/536) of samples and included Anaplasma, Ehrlichia and Neoehrlichia species. In samples from NSW, ‘Ca. Neoehrlichia australis’, ‘Ca. Neoehrlichia arcana’, Neoehrlichia sp. and Ehrlichia sp. were identified. A putative novel Ehrlichia sp. was identified from WA and Anaplasma platys was identified from QLD. Nine rodent tissue samples were positive for a novel Borrelia sp. that formed a phylogenetically distinct clade separate from the Lyme Borrelia and relapsing fever groups. This novel clade included recently identified rodent-associated Borrelia genotypes, which were described from Spain and North America. Bartonella was identified in 12.9% (69/536) of samples. Over half of these positive samples were obtained from black rats (Rattus rattus), and the dominant bacterial species identified were Bartonella coopersplainsensis and Bartonella queenslandensis. The results from the present study show the value of using unbiased high-throughput sequencing applied to samples collected from wildlife. In addition to understanding the sylvatic cycle of known vector-associated pathogens, surveillance work is important to ensure preparedness for potential zoonotic spillover events

Identifying the DEAD: Development and Validation of a Patient-Level Model to Predict Death Status in Population-Level Claims Data

Introduction US claims data contain medical data on large heterogeneous populations and are excellent sources for medical research. Some claims data do not contain complete death records, limiting their use for mortality or mortality-related studies. A model to predict whether a patient died at the end of the follow-up time (referred to as the end of observation) is needed to enable mortality-related studies. Objective The objective of this study was to develop a patient-level model to predict whether the end of observation was due to death in US claims data. Methods We used a claims dataset with full death records, Optum© De-Identifed Clinformatics® Data-Mart-Database—Date of Death mapped to the Observational Medical Outcome Partnership common data model, to develop a model that classifes the end of observations into death or non-death. A regularized logistic regression was trained using 88,514 predictors (recorded within the prior 365 or 30 days) and externally validated by applying the model to three US claims datasets. Results Approximately 25 in 1000 end of observations in Optum are due to death. The Discriminating End of observation into Alive and Dead (DEAD) model obtained an area under the receiver operating characteristic curve of 0.986. When defning death as a predicted risk of>0.5, only 2% of the end of observations were predicted to be due to death and the model obtained a sensitivity of 62% and a positive predictive value of 74.8%. The external validation showed the model was transportable, with area under the receiver operating characteristic curves ranging between 0.951 and 0.995 across the US claims databases. Conclusions US claims data often lack complete death records. The DEAD model can be used to impute death at various sensitivity, specifcity, or positive predictive values depending on the use of the model. The DEAD model can be readily applied to any observational healthcare database mapped to the Observational Medical Outcome Partnership common data model and is available from https://github.com/OHDSI/StudyProtocolSandbox/tree/master/DeadModel

The anti-B --> D* lepton anti-neutrino form factor at zero recoil and the determination of V(cb)

We summarize our lattice QCD study of the form factor at zero recoil in the decay anti-B --> D* lepton anti-neutrino. After careful consideration of all sources of systematic uncertainty, we find, h_A1(1) = 0.913(+0.024-0.017)(+0.017-0.030), where the first uncertainty is from statistics and fitting while the second combined uncertainty is from all other systematic effects.Comment: Lattice2001(HeavyQuark); 3 pages, 2 eps figures, espcrc2.st

B -> D l nu form factors and the determination of |Vcb|

The zero recoil limit of the B -> D l nu form factors is calculated on the lattice, which provides a model-independent determination of |Vcb|. Considering a ratio of form factors, in which the bulk of statistical and systematic errors cancel, we obtain a precise result both for h_+(1) and for h_-(1).Comment: LATTICE98(heavyqk), LaTeX, 3 pages, 3 postscript figures, uses espcrc2.st

A standardized framework for risk-based assessment of treatment effect heterogeneity in observational healthcare databases

Treatment effects are often anticipated to vary across groups of patients with different baseline risk. The Predictive Approaches to Treatment Effect Heterogeneity (PATH) statement focused on baseline risk as a robust predictor of treatment effect and provided guidance on risk-based assessment of treatment effect heterogeneity in a randomized controlled trial. The aim of this study is to extend this approach to the observational setting using a standardized scalable framework. The proposed framework consists of five steps: (1) definition of the research aim, i.e., the population, the treatment, the comparator and the outcome(s) of interest; (2) identification of relevant databases; (3) development of a prediction model for the outcome(s) of interest; (4) estimation of relative and absolute treatment effect within strata of predicted risk, after adjusting for observed confounding; (5) presentation of the results. We demonstrate our framework by evaluating heterogeneity of the effect of thiazide or thiazide-like diuretics versus angiotensin-converting enzyme inhibitors on three efficacy and nine safety outcomes across three observational databases. We provide a publicly available R software package for applying this framework to any database mapped to the Observational Medical Outcomes Partnership Common Data Model. In our demonstration, patients at low risk of acute myocardial infarction receive negligible absolute benefits for all three efficacy outcomes, though they are more pronounced in the highest risk group, especially for acute myocardial infarction. Our framework allows for the evaluation of differential treatment effects across risk strata, which offers the opportunity to consider the benefit-harm trade-off between alternative treatments.Development and application of statistical models for medical scientific researc

The B -> D* l nu Form Factor at Zero Recoil

We describe a model independent lattice QCD method for determining the deviation from unity for h_{A1}(1), the B -> D* l nu form factor at zero recoil. We extend the double ratio method previously used to determine the B -> D l nu form factor. The bulk of statistical and systematic errors cancel in the double ratios we consider, yielding form factors which promise to reduce present theoretical uncertainties in the determination of V_{cb}. We present results from a prototype calculation at a single lattice spacing corresponding to beta=5.7.Comment: Lattice99(heavyquarks); 3 pgs, LaTe

Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data

Objective: To develop a conceptual prediction model framework containing standardized steps and describe the corresponding open-source software developed to consistently implement the framework across computational environments and observational healthcare databases to enable model sharing and reproducibility. Methods: Based on existing best practices we propose a 5 step standardized framework for: (1) transparently defining the problem; (2) selecting suitable datasets; (3) constructing variables from the observational data; (4) learning the predictive model; and (5) validating the model performance. We implemented this framework as open-source software utilizing the Observational Medical Outcomes Partnership Common Data Model to enable convenient sharing of models and reproduction of model evaluation across multiple observational datasets. The software implementation contains default covariates and classifiers but the framework enables customization and extension. Results: As a proof-of-concept, demonstrating the transparency and ease of model dissemination using the software, we developed prediction models for 21 different outcomes within a target population of people suffering from depression across 4 observational databases. All 84 models are available in an accessible online repository to be implemented by anyone with access to an observational database in the Common DataModel format. Conclusions: The proof-of-concept study illustrates the framework's ability to develop reproducible models that can be readily shared and offers the potential to perform extensive external validation of models, and improve their likelihood of clinical uptake. In future work the framework will be applied to perform an "all-by-all" prediction analysis to assess the observational data prediction domain across numerous target populations, outcomes and time, and risk settings

Comparative effectiveness of canagliflozin, SGLT2 inhibitors and non-SGLT2 inhibitors on the risk of hospitalization for heart failure and amputation in patients with type 2 diabetes mellitus: A real-world meta-analysis of 4 observational databases (OBSERVE-4D)

Aims: Sodium glucose co-transporter 2 inhibitors (SGLT2i) are indicated for treatment of type 2 diabetes mellitus (T2DM)some SGLT2i have reported cardiovascular benefit, and some have reported risk of below-knee lower extremity (BKLE) amputation. This study examined the real-world comparative effectiveness within the SGLT2i class and compared with non-SGLT2i antihyperglycaemic agents. Materials and methods: Data from 4 large US administrative claims databases were used to characterize risk and provide population-level estimates of canagliflozin's effects on hospitalization for heart failure (HHF) and BKLE amputation vs other SGLT2i and non-SGLT2i in T2DM patients. Comparative analyses using a propensity score–adjusted new-user cohort design examined relative hazards of outcomes across all new users and a subpopulation with established cardiovascular disease. Results: Across the 4 databases (142 800 new users of canagliflozin, 110 897 new users of other SGLT2i, 460 885 new users of non-SGLT2i), the meta-analytic hazard ratio estimate for HHF with canagliflozin vs non-SGLT2i was 0.39 (95% CI, 0.26-0.60) in the on-treatment analysis. The estimate for BKLE amputation with canagliflozin vs non-SGLT2i was 0.75 (95% CI, 0.40-1.41) in the on-treatment analysis and 1.01 (95% CI, 0.93-1.10) in the intent-to-treat analysis. Effects in the subpopulation with established cardiovascular disease were similar for both outcomes. No consistent differences were observed between canagliflozin and other SGLT2i. Conclusions: In this large comprehensive analysis, canagliflozin and other SGLT2i demonstrated HHF benefits consistent with clinical trial data, but showed no increased risk of BKLE amputation vs non-SGLT2i. HHF and BKLE amputation results were similar in the subpopulation with established cardiovascular disease. This study helps further characterize the potential benefits and harms of SGLT2i in routine clinical practice to complement evidence from clinical trials and prior observational studies