The Partial Replacement of Perennial Ryegrass Silage with Ensiled Biorefined Perennial Ryegrass Press Cake, and its Impact on Productivity of Late Lactation Dairy Cows

Although necessary to maintain milk production in late lactation when grass is scarce, dependency on imported concentrate has negative environmental credentials; diversifying native feeds i.e., perennial ryegrass, using biorefinery, to produce high quality by-products may be a solution (Sanders et al., 2020). To validate these suggestions, a study was undertaken on dairy cows during the winter period; 60% of a perennial ryegrass silage diet was replaced with perennial ryegrass (PRG) press cake in treatment cows (GSPC; n=20), while a perennial ryegrass silage diet was offered to control cows (GS; n=20). Cows substituted with press cake produced 9.1 and 10.5 % more milk solids (kg), and fat and protein corrected milk (kg), respectively, compared to their GS herd mates (P \u3c 0.05). The GSPC cows also produced 6.5% more methane than GS cows (P\u3c0.05). This was primarily driven by a higher group average dry matter intake in GSPC cows (15.6 kg) compared with GS cows (15.1 kg). Although cows offered press cake had a higher group average dry matter intake, they were not significantly heavier than cows offered a silage based diet, and they tended (P=0.05) to have a lower body condition score (BCS). Cows substituted with press cake produced 3.8% more methane per kg dry matter intake and 13.0% more methane per kg body weight (P=0.01), respectively. Feeding PRG press cake to late lactation dairy cows did not improve environmental credentials, as there was a greater methane output compared to cows offered a grass silage based diet. Although PRG press cake significantly improved milk solids yield, when methane was expressed per kg milk solids output was similar for treatment and control cows

Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysis

peer-reviewedThe objective of this study was to compare mid-infrared reflectance spectroscopy (MIRS) analysis of milk and near-infrared reflectance spectroscopy (NIRS) analysis of feces with regard to their ability to predict the dry matter intake (DMI) of lactating grazing dairy cows. A data set comprising 1,074 records of DMI from 457 cows was available for analysis. Linear regression and partial least squares regression were used to develop the equations using the following variables: (1) milk yield (MY), fat percentage, protein percentage, body weight (BW), stage of lactation (SOL), and parity (benchmark equation); (2) MIRS wavelengths; (3) MIRS wavelengths, MY, fat percentage, protein percentage, BW, SOL, and parity; (4) NIRS wavelengths; (5) NIRS wavelengths, MY, fat percentage, protein percentage, BW, SOL, and parity; (6) MIRS and NIRS wavelengths; and (7) MIRS wavelengths, NIRS wavelengths, MY, fat percentage, protein percentage, BW, SOL, and parity. The equations were validated both within herd using animals from similar experiments and across herds using animals from independent experiments. The accuracy of equations was greater for within-herd validation compared with across-herds validation. Across-herds validation was deemed the more suitable method to assess equations for robustness and real-world application. The benchmark equation was more accurate [coefficient of determination (R2) = 0.60; root mean squared error (RMSE) = 1.68 kg] than MIRS alone (R2 = 0.30; RMSE = 2.23 kg) or NIRS alone (R2 = 0.16; RMSE = 2.43 kg). The combination of the benchmark equation with MIRS (R2 = 0.64; RMSE = 1.59 kg) resulted in slightly superior fitting statistics compared with the benchmark equation alone. The combination of the benchmark equation with NIRS (R2 = 0.58; RMSE = 1.71 kg) did not result in a more accurate prediction equation than the benchmark equation. The combination of MIRS and NIRS wavelengths resulted in superior fitting statistics compared with either method alone (R2 = 0.36; RMSE = 2.15 kg). The combination of the benchmark equation and MIRS and NIRS wavelengths resulted in the most accurate equation (R2 = 0.68; RMSE = 1.52 kg). A further analysis demonstrated that Holstein-Friesian cows could predict the DMI of Jersey × Holstein-Friesian crossbred cows using both MIRS and NIRS. Similarly, the Jersey × Holstein-Friesian animals could predict the DMI of Holstein-Friesian cows using both MIRS and NIRS. The equations developed in this study have the capacity to predict DMI of grazing dairy cows. From a practicality perspective, MIRS in combination with variables in the benchmark equation is the most suitable equation because MIRS is currently used on all milk-recorded milk samples from dairy cows

Application of an antibiotic spectrum index in the neonatal intensive care unit

Antimicrobial stewardship programs typically use days of therapy to assess antimicrobial use. However, this metric does not account for the antimicrobial spectrum of activity. We applied an antibiotic spectrum index to a population of very-low-birth-weight infants to assess its utility to evaluate the impact of antimicrobial stewardship interventions

The development of equations to predict live-weight from linear body measurements of pasture-based Holstein-Friesian and Jersey dairy heifers

peer-reviewedMonitoring the live-weight of dairy heifers and thus meeting weight-for-age targets is regarded as one of the most important aspects of a heifer rearing enterprise as it optimizes future production. This is particularly important in pasture-based heifer rearing systems where growth is non-linear due to seasonal variation in grass growth and quality. Data were collected throughout the rearing period to estimate the live-weight of pasture-based Holstein-Friesian (n = 130) and Jersey (n = 57) dairy heifers using linear body measurements. Live-weight was regressed on heart girth, body volume and a polynomial of body length, heart girth, and withers height; all equations were validated within-herd. All three equations were accurate predictors of live-weight for pasture-based dairy heifers (R² > 0.92 and RMSE < 19.1 kg), therefore, in the absence of weighing scales, live-weight can be successfully predicted using linear body measurements. The equation which utilizes body volume of the heifer is proposed as the most suitable predictor of live-weight

The repeatability of feed intake and feed efficiency in beef cattle offered high-concentrate, grass silage and pasture-based diets

peer-reviewedBreeding values for feed intake and feed efficiency in beef cattle are generally derived indoors on high-concentrate (HC) diets. Within temperate regions of north-western Europe, however, the majority of a growing beef animal’s lifetime dietary intake comes from grazed grass and grass silage. Using 97 growing beef cattle, the objective of the current study was to assess the repeatability of both feed intake and feed efficiency across 3 successive dietary test periods comprising grass silage plus concentrates (S+C), grazed grass (GRZ) and a HC diet. Individual DM intake (DMI), DMI/kg BW and feed efficiency-related parameters, residual feed intake (RFI) and gain to feed ratio (G : F) were assessed. There was a significant correlation for DMI between the S+C and GRZ periods (r = 0.32; P < 0.01) as well as between the S+C and HC periods (r = 0.41; P < 0.001), whereas there was no association for DMI between the GRZ and HC periods. There was a significant correlation for DMI/kg BW between the S+C and GRZ periods (r = 0.33; P < 0.01) and between the S+C and HC periods (r = 0.40; P < 0.001), but there was no association for the trait between the GRZ and HC periods. There was a significant correlation for RFI between the S+C and GRZ periods (r = 0.25; P < 0.05) as well as between S+C and HC periods (r = 0.25; P < 0.05), whereas there was no association for RFI between the GRZ and HC periods. Gain to feed ratio was not correlated between any of the test periods. A secondary aspect of the study demonstrated that traits recorded in the GRZ period relating to grazing bite rate, the number of daily grazing bouts and ruminating bouts were associated with DMI (r = 0.28 to 0.42; P < 0.05 - 0.001), DMI/kg BW (r = 0.36 to 0.45; P < 0.01 - 0.001) and RFI (r = 0.31 to 0.42; P < 0.05 - 0.001). Additionally, the number of ruminating boli produced per day and per ruminating bout were associated with G : F (r = 0.28 and 0.26, respectively; P < 0.05). Results from this study demonstrate that evaluating animals for both feed intake and feed efficiency indoors on HC diets may not reflect their phenotypic performance when consuming conserved forage-based diets indoors or when grazing pasture

Digital health behaviour change interventions targeting physical activity and diet in cancer survivors: a systematic review and meta-analysis

Purpose: The number of cancer survivors has risen substantially due to improvements in early diagnosis and treatment. Health behaviours such as physical activity (PA) and diet can reduce recurrence and mortality, and alleviate negative consequences of cancer and treatments. Digital behaviour change interventions (DBCIs) have the potential to reach large numbers of cancer survivors. Methods: We conducted a systematic review and meta-analyses of relevant studies identified by a search of Medline, EMBASE, PubMed and CINAHL. Studies which assessed a DBCI with measures of PA, diet and/or sedentary behaviour were included. Results: 15 studies were identified. Random effects meta-analyses showed significant improvements in moderate-vigorous PA (7 studies; mean difference (MD) = 41 minutes per week; 95% CI: 12, 71) and body mass index (BMI)/weight (standardised mean difference (SMD) = -0.23; 95% CI: -0.41, -0.05). There was a trend toward significance for reduced fatigue and no significant change in cancer-specific quality of life (QoL). Narrative synthesis revealed mixed evidence for effects on diet, generic QoL and self-efficacy and no evidence of an effect on mental health. Two studies suggested improved sleep quality. Conclusions: DBCIs may improve PA and BMI among cancer survivors and there is mixed evidence for diet. The number of included studies is small and risk of bias and heterogeneity was high. Future research should address these limitations with large, high-quality RCTs, with objective measures of PA and sedentary time. Implications for cancer survivors: Digital technologies offer a promising approach to encourage health behaviour change among cancer survivors

Circulating microRNAs in sera correlate with soluble biomarkers of immune activation but do not predict mortality in ART treated individuals with HIV-1 infection: A case control study

Introduction: The use of anti-retroviral therapy (ART) has dramatically reduced HIV-1 associated morbidity and mortality. However, HIV-1 infected individuals have increased rates of morbidity and mortality compared to the non-HIV-1 infected population and this appears to be related to end-organ diseases collectively referred to as Serious Non-AIDS Events (SNAEs). Circulating miRNAs are reported as promising biomarkers for a number of human disease conditions including those that constitute SNAEs. Our study sought to investigate the potential of selected miRNAs in predicting mortality in HIV-1 infected ART treated individuals. Materials and Methods: A set of miRNAs was chosen based on published associations with human disease conditions that constitute SNAEs. This case: control study compared 126 cases (individuals who died whilst on therapy), and 247 matched controls (individuals who remained alive). Cases and controls were ART treated participants of two pivotal HIV-1 trials. The relative abundance of each miRNA in serum was measured, by RTqPCR. Associations with mortality (all-cause, cardiovascular and malignancy) were assessed by logistic regression analysis. Correlations between miRNAs and CD4+ T cell count, hs-CRP, IL-6 and D-dimer were also assessed. Results: None of the selected miRNAs was associated with all-cause, cardiovascular or malignancy mortality. The levels of three miRNAs (miRs -21, -122 and -200a) correlated with IL-6 while miR-21 also correlated with D-dimer. Additionally, the abundance of miRs -31, -150 and -223, correlated with baseline CD4+ T cell count while the same three miRNAs plus miR- 145 correlated with nadir CD4+ T cell count. Discussion: No associations with mortality were found with any circulating miRNA studied. These results cast doubt onto the effectiveness of circulating miRNA as early predictors of mortality or the major underlying diseases that contribute to mortality in participants treated for HIV-1 infection