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There is a paucity of information about milk composition and quality at the quarter level from complete milking of the udder, mainly because of the difficulties of sampling procedures which imply the adoption of a vacuum system connected to four independent buckets. The objective of this study was to evaluate the effect of quarter position, intramammary infection status, and somatic cells on milk yield and composition at the mammary quarter level of Simmental cows. Milk samples were collected during three consecutive days, after milking individual mammary quarters of 10 lactating cows separately, for a total of 120 quarter milk samples. Samples were analysed for composition, somatic cell count (SCC), differential SCC, and bacterial culture. Somatic cell count was log-transformed to somatic cell score (SCS) to achieve normality of distribution. Sources of variation of milk yield and quality traits were investigated using a linear mixed model which included the fixed effects of quarter position (1 to 4), pathogen presence (positive or negative), and SCS class (low, medium-low, medium-high, and high). The interaction between cow and quarter position was included as random effect. Quarter position significantly affected milk yield, with rear udder quarters yielding more milk compared to their front counterparts, but with negligible effects on milk composition. Classes of SCS influenced milk composition, in a way that quarters with high SCS had lower lactose content and higher differential SCC. This study is a contribution towards the possibility to better understand physiological processes at cow udder quarter level.

Abstract Background Intramammary infection is the result of invasion and multiplication of microorganisms in the mammary gland and commonly leads to mastitis in dairy animals. Although much has been done to improve cows’ udder health, mastitis remains a significant and costly health issue for dairy farmers, especially if subclinical. In this study, quarter milk samples from clinically healthy cows were harvested to detect pathogens via quantitative PCR (qPCR) and evaluate changes in individual milk traits according to the number of quarters infected and the type of microorganism(s). A commercial qPCR kit was used for detection of Mycoplasma bovis, Mycoplasma spp., Staphylococcus aureus, coagulase-negative staphylococci (CNS), Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, Prototheca spp., Escherichia coli, Klebsiella spp., Enterococcus spp. and Lactococcus lactis ssp. lactis. Quarter and pooled milk information of 383 Holstein, 132 Simmental, 129 Rendena, and 112 Jersey cows in 9 Italian single-breed herds was available. Results Among the cows with pathogen(s) present in at least 1 quarter, CNS was the most commonly detected DNA, followed by Streptococcus uberis, Mycoplasma bovis, and Streptococcus agalactiae. Cows negative to qPCR were 206 and had the lowest milk somatic cell count. Viceversa, cows with DNA isolated in ≥ 3 quarters were those with the highest somatic cell count. Moreover, when major pathogens were isolated in ≥ 3 quarters, milk had the lowest casein index and lactose content. In animals with pathogen(s) DNA isolated, the extent with whom milk yield and major solids were impaired did not significantly differ between major and minor pathogens. Conclusions The effect of the number of affected quarters on the pool milk quality traits was investigated in clinically healthy cows using a commercial kit. Results remark the important negative effect of subclinical udder inflammations on milk yield and quality, but more efforts should be made to investigate the presence of untargeted microorganisms, as they may be potentially dangerous for cows. For a smarter use of antimicrobials, analysis of milk via qPCR is advisable – especially in cows at dry off - to identify quarters at high risk of inflammation and thus apply a targeted/tailored treatment.

ABSTRACT: Of late, “A2 milk” has gained prominence in the dairy sector due to its potential implications in human health. Consequently, the frequency of A2 homozygous animals has considerably increased in many countries. To elucidate the potential implications that beta casein (β-CN) A1 and A2 may have on cheese-making traits, it is fundamental to investigate the relationships between the genetic polymorphisms and cheese-making traits at the dairy plant level. Thus, the aim of the present study was to evaluate the relevance of the β-CN A1/A2 polymorphism on detailed protein profile and cheese-making process in bulk milk. Based on the β-CN genotype of individual cows, 5 milk pools diverging for presence of the 2 β-CN variants were obtained: (1) 100% A1; (2) 75% A1 and 25% A2; (3) 50% A1 and 50% A2; (4) 25% A1 and 75% A2; and (5) 100% A2. For each cheese-making day (n = 6), 25 L of milk (divided into 5 pools, 5 L each) were processed, for a total of 30 cheese-making processes. Cheese yield, curd nutrient recovery, whey composition, and cheese composition were assessed. For every cheese-making process, detailed milk protein fractions were determined through reversed-phase HPLC. Data were analyzed by fitting a mixed model, which included the fixed effects of the 5 different pools, the protein and fat content as a covariate, and the random effect of the cheese-making sessions. Results showed that the percentage of κ-CN significantly decreased up to 2% when the proportion of β-CN A2 in the pool was ≥25%. An increase in the relative content of β-CN A2 (≥50% of total milk processed) was also associated with a significantly lower cheese yield both 1 and 48 h after cheese production, whereas no effects were observed after 7 d of ripening. Concordantly, recovery of nutrients reflected a more efficient process when the inclusion of β-CN A2 was ≤75%. Finally, no differences in the final cheese composition obtained by the different β-CN pools were observed.

OBJECTIVE: To evaluate the costs and benefits associated with the use of biologics and Janus kinase inhibitors (JAKi) for the treatment of bio-experienced patients suffering from ulcerative colitis in Italy. METHODS: This pharmacoeconomic analysis compared JAKi (filgotinib, tofacitinib and upadacitinib) and biologics (vedolizumab and ustekinumab). A decision tree model with a 1-year time horizon was built in MS Excel in order to estimate treatment cost and clinical efficacy expressed in terms of clinical response (CR), clinical remission (CRe) and mucosal healing (MH). Efficacy of each treatment was estimated using relative risks elaborated from a recent network meta-analysis of 17 RCTs. The investigated population concerned patients previously treated with biologic drugs (bio-experienced). Both induction and maintenance phases were considered and dose escalation (when allowed) was planned for patients not reaching an appropriate response after induction. Outcomes included total treatment cost (acquisition and administration), overall response rate, and cost per responder at one year. RESULTS: According to the model results, the treatment associated with the best clinical response at 1 year was vedolizumab (69.6%) followed by filgotinib (60.9%) and upadacitinib (60.1%). Despite differences in efficacy, filgotinib resulted in the lowest cost per responder, in every outcome, compared with all the other alternatives. The same trend applies when observing results at the end of the induction phase only. Results were robust to probabilistic sensitivity analyses, filgotinib has a posterior probability to be better than the other alternatives higher than 96% according to all the three response definitions (CR, CRe, and MH). CONCLUSIONS: Generally, JAKis and vedolizumab were associated with higher treatment response. Among the alternatives included in the analysis, filgotinib has the lowest cost per responder for all the outcomes included. These findings could help deliver more effective and efficient healthcare in the NHS.

This document illustrates the results of a discussion of two multi-disciplinary expert panels on pricing and reimbursement of medicines. Experts work in different organizations. The discussion focused on comparator(s), endpoint(s), negotiation of prices of new medicines and/or indications to include in the List 648, as well as the role of cost-effectiveness in the price and reimbursement negotiation. The debate took place during the fourth edition of the Seminari di Mogliano, organized on the 30th of September/1st of October, 2021. The two panels agreed on a general need to enhance interaction among the different stakeholders, in the early assessment and negotiation phases, and to increase the transparency/reproducibility of the decisions taken. The experts have also emphasized the need (i) to improve clarity in the evaluation of additional therapeutic value and the place in therapy with respect to comparators and how comparators are identified; (ii) to create work groups to identify the most appropriate endpoint(s), for each therapeutic area and level of unmet needs; (iii) to provide for a systematic use of cost-effectiveness when an added therapeutic value is delivered by a new medicine. With regard to the 648 List, the experts advocated for an overall reorganization of the current rules governing the special uses of drugs.

In this study we evaluated the prevalence of pathogens detected via quantitative PCR (qPCR) in milk from apparently healthy cows to identify the most common etiological agents present in Italian dairy farms. Milk samples were collected using a sterile protocol at quarter-level (3239 samples, 822 cows) and a conventional protocol at udder level as composite milk from the functional quarters of each cow (5464 samples, 5464 cows). The qPCR commercial kit detected Mycoplasma bovis, Mycoplasma spp., Staphylococcus aureus, coagulase-negative staphylococci (CNS), Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, Prototheca spp., Escherichia coli, Klebsiella spp., Enterococcus spp. and Lactococcus lactis ssp. lactis as well as DNA from the penicillin resistance β-lactamase gene from staphylococci. The prevalence of specific DNA was calculated based on its presence or absence in the samples, factoring in both the sampling protocols and herds. Regardless of the sampling protocol used, the most frequently detected pathogens were CNS (26.6% in sterile and 13.9% in conventional protocol) and Streptococcus uberis (9.6% and 16.5%, respectively). These results underscore the necessity for pathogen-specific interventions at the farm level to enhance the udder health of dairy cows via management recommendations.