Effects of a single transdermal administration of flunixin meglumine in early postpartum Holstein Friesian dairy cows: Part 1. Inflammatory and metabolic markers, uterine health, and indicators of pain

Survey of drug use and its association with herd-level and farm-level characteristics on German dairy farms

The use of veterinary drugs is of similar importance to that of human drugs in addressing health challenges. In this context, pharmaceuticals and their metabolites inevitably enter soil and water in unknown quantities. Therefore, this study collects and analyzes drug data from 2020 for 50 dairy farms located in Germany. The most frequently used substance group is antibiotics (40.13%), followed by antiphlogistics (18.86%), antiparasitics (13.09%), and hormones (9.29%). Treatment frequencies record the number of days per year on which an average animal on a farm was treated with a substance. The calculated values range from 0.94 to 21.69 d/yr and are distributed heterogeneously across farms. In this study, on average, a cow was treated on 6 d in 2020: 2.34 d with antibiotics, 1.07 d with antiphlogistics, 0.76 d with antiparasitics, and 0.41 d with hormones. In addition to individual farm management practices, other factors are related to treatment frequency. Farms with a veterinary care contract used more hormonal substances than farms without a care contract. In addition, higher milk yield coincides with more frequent treatments with antiphlogistic or hormonal substances. Other related factors include grazing, longevity, farm size, and use of a claw bath. Our study represents an important first step in describing the amounts and determinants of veterinary drugs used in livestock farming. Such insights on magnitudes and farm parameters are essential to estimate potential environmental effects and derive strategies to reduce veterinary drug use.

Lipolysis inhibition as a treatment of clinical ketosis in dairy cows: A randomized clinical trial

Excessive and protracted lipolysis in adipose tissues of dairy cows is a major risk factor for clinical ketosis (CK). This metabolic disease is common in postpartum cows when lipolysis provides fatty acids as an energy substrate to offset negative energy balance. Lipolysis in cows can be induced by the canonical (hormonally induced) and inflammatory pathways. Current treatments for CK focus on improving glucose in blood (i.e., oral propylene glycol [PG], or i.v. dextrose). However, these therapies do not inhibit the canonical and inflammatory lipolytic pathways. Niacin (NIA) can reduce activation of the canonical pathway. Blocking inflammatory responses with cyclooxygenase inhibitors such as flunixin meglumine (FM) can inhibit inflammatory lipolytic activity. The objective of this study was to determine the effects of including NIA and FM in the standard PG treatment for postpartum CK on circulating concentrations of ketone bodies. A 4-group, parallel, individually randomized trial was conducted in multiparous Jersey cows (n = 80) from a commercial dairy in Michigan during a 7-mo period. Eligible cows had CK symptoms (lethargy, depressed appetite, and milk yield) and hyperketonemia (blood β-hydroxybutyrate [BHB] ≥1.2 mmol/L). Cows with CK were randomly assigned to 1 of 3 groups where the first group received 310 g of oral PG once per day for 5 d; the second group received PG for 5 d + 24 g of oral NIA once per day for 3 d (PGNIA); and the third group received PG for 5 d + NIA for 3 d + 1.1 mg/kg i.v. FM once per day for 3 d (PGNIAFM). The control group consisted of cows that were clinically healthy (HC; untreated; BHB <1.2 mmol/L, n = 27) matching for parity and DIM with all 3 groups. Animals were sampled at enrollment (d 0), and d 3, 7, and 14 to evaluate ketone bodies and circulating metabolic and inflammatory biomarkers. Effects of treatment, sampling day, and their interactions were evaluated using mixed effects models. Logistic regression was used to calculate the odds ratio (OR) of returning to normoketonemia (BHB <1.2 mmol/L). Compared with HC, enrolled CK cows exhibited higher blood concentrations of dyslipidemia markers, including nonesterified fatty acids (NEFA) and BHB, and lower glucose and insulin levels. Cows with CK also had increased levels of biomarkers of pain (substance P), inflammation, including lipopolysaccharide-binding protein, haptoglobin, and serum amyloid A, and proinflammatory cytokines IL-4, MCP-1, MIP-1α, and TNFα. Importantly, 72.2% of CK cows presented endotoxemia and had higher circulating bacterial DNA compared with HC. By d 7, the percentage of cows with normoketonemia were higher in PGNIAFM = 87.5%, compared with PG = 58.33%, and PGNIA = 62.5%. At d 7 the OR for normoketonemia in PGNIAFM cows were 1.5 (95% CI, 1.03-2.17) and 1.4 (95% CI, 0.99-1.97) relative to PG and PGNIA, respectively. At d 3, 7, and 14, PGNIAFM cows presented the lowest values of BHB (PG = 1.36; PGNIA = 1.24; PGNIAFM = 0.89 ± 0.13 mmol/L), NEFA (PG = 0.58; PGNIA = 0.59; PGNIAFM = 0.45 ± 0.02 mmol/L), and acute phase proteins. Cows in PGNIAFM also presented the highest blood glucose increment across time points and insulin by d 7. These data provide evidence that bacteremia or endotoxemia, systemic inflammation, and pain may play a crucial role in CK pathogenesis. Additionally, targeting lipolysis and inflammation with NIA and FM during CK effectively reduces dyslipidemia biomarkers, improves glycemia, and improves overall clinical recovery.

Genetically supported causality between gut microbiota, gut metabolites and low back pain: a two-sample Mendelian randomization study

Background

Previous studies have implicated a vital association between gut microbiota/gut microbial metabolites and low back pain (LBP), but their causal relationship is still unclear. Therefore, we aim to comprehensively investigate their causal relationship and identify the effect of gut microbiota/gut microbial metabolites on risk of LBP using a two-sample Mendelian randomization (MR) study.

Methods

Summary data from genome-wide association studies (GWAS) of gut microbiota (18,340 participants), gut microbial metabolites (2,076 participants) and LBP (FinnGen biobank) were separately obtained. The inverse variance-weighted (IVW) method was used as the main MR analysis. Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) and MR-Egger regression were conducted to evaluate the horizontal pleiotropy and to eliminate outlier single-nucleotide polymorphisms (SNPs). Cochran's Q-test was applied for heterogeneity detection. Besides, leave-one-out analysis was conducted to determine whether the causal association signals were driven by any single SNP. Finally, a reverse MR was performed to evaluate the possibility of reverse causation.

Results

We discovered that 20 gut microbial taxa and 2 gut microbial metabolites were causally related to LBP (p < 0.05). Among them, the lower level of family Ruminococcaceae (OR: 0.771, 95% CI: 0.652-0.913, FDR-corrected p = 0.045) and Lactobacillaceae (OR: 0.875, 95% CI: 0.801-0.955, FDR-corrected p = 0.045) retained a strong causal relationship with higher risk of LBP after the Benjamini-Hochberg Corrected test. The Cochrane's Q test revealed no Heterogeneity (p > 0.05). Besides, MR-Egger and MR-PRESSO tests showed no significant horizontal pleiotropy (p > 0.05). Furthermore, leave-one-out analysis confirmed the robustness of MR results. After adding BMI to the multivariate MR analysis, the 17 gut microbial taxa exposure-outcome effect were significantly attenuated and tended to be null.

Conclusion

Our findings confirm the the potential causal effect of specific gut microbiota and gut microbial metabolites on LBP, which offers new insights into the gut microbiota-mediated mechanism of LBP and provides the theoretical basis for further explorations of targeted prevention strategies.