Gabriella Condello, Flavio S. Schenkel, Isis C. Hermisdorff
et al.
ABSTRACT: Bovine spastic syndrome, known as Crampy, is a neuromuscular disorder in cattle. Affected cattle, 2 yr or older, suffer from involuntary muscle spasms in their hind limbs, leading to discomfort and reduced mobility. This often results in early culling from the herd, causing substantial financial loss for producers. Given the welfare implications and economic burden associated with Crampy, it is crucial to identify effective strategies to mitigate its occurrence. In this study, we assessed the feasibility of genetic selection to reduce Crampy by estimating variance components, evaluating the effect of incorporating genomic information, investigating Crampy's relationship with other economically important traits, and identifying genomic regions associated with Crampy in Canadian Holstein dairy cattle. A dataset comprising 54,826 animals, including 1,952 cases of Crampy, from 678 Canadian dairy herds, was provided by Lactanet Canada (Guelph, ON, Canada). Of these animals, 22,408 (including 408 with Crampy) were genotyped. Both threshold and linear models were used to estimate variance components, with observed scale h2 estimates ranging from 0.057 to 0.085. The inclusion of genomic data significantly increased the reliability of breeding values by 5% to 17%. Through a GWAS using GCTA software, a total of 41 significant SNPs were found to be significantly associated with Crampy. Functional analysis revealed 44 genes, among which we have highlighted the genes WNK2 (BTA8), DTNBP1 (BTA23), and ADK (BTA28), which have been associated with ion transport, muscle function, and neuron signaling, respectively. Enriched colocated QTL annotations linked to ketosis, muscle calcium content, and muscle zinc content were also identified, highlighting the role of metabolic processes and mineral homeostasis in muscle function. Breeding value correlations between Crampy and production, health, longevity, and type traits, and the selection indices were moderately low but favorable, indicating that current breeding strategies may indirectly select against Crampy. These findings highlight genomic selection as a viable strategy to mitigate Crampy in Canadian dairy herds, emphasizing the need for continued phenotyping for this disorder and optimization of breeding practices to improve animal welfare and sustainability.
As most optical satellites remotely acquire multispectral images (MSIs) with limited spatial resolution, multispectral unmixing (MU) becomes a critical signal processing technology for analyzing the pure material spectra for high-precision classification and identification. Unlike the widely investigated hyperspectral unmixing (HU) problem, MU is much more challenging as it corresponds to the underdetermined blind source separation (BSS) problem, where the number of sources is larger than the number of available multispectral bands. In this article, we transform MU into its overdetermined counterpart (i.e., HU) by inventing a radically new quantum deep image prior (QDIP), which relies on the virtual band-splitting task conducted on the observed MSI for generating the virtual hyperspectral image (HSI). Then, we perform HU on the virtual HSI to obtain the virtual hyperspectral sources. Though HU is overdetermined, it still suffers from the ill-posed issue, for which we employ the convex geometry structure of the HSI pixels to customize a weighted simplex shrinkage (WSS) regularizer to mitigate the ill-posedness. Finally, the virtual hyperspectral sources are spectrally downsampled to obtain the desired multispectral sources. The proposed geometry/quantum-empowered MU (GQ-$μ$) algorithm can also effectively obtain the spatial abundance distribution map for each source, where the geometric WSS regularization is adaptively and automatically controlled based on the sparsity pattern of the abundance tensor. Simulation and real-world data experiments demonstrate the practicality of our unsupervised GQ-$μ$ algorithm for the challenging MU task. Ablation study demonstrates the strength of QDIP, not achieved by classical DIP, and validates the mechanics-inspired WSS geometry regularizer.
This study aimed to compare the fertility of lactating Holstein cows with only 1 large follicle (LF, diameter ≥10 mm) with those with ≥2 LF and corpora lutea at the start of short-term ovulation synchronization and timed artificial insemination (AI). Cows with a corpus luteum ≥20 mm in diameter and either 1 LF (1F) or ≥2 LF (2F) verified via ovarian ultrasonography were included in the study. Cows were randomly categorized into groups receiving either estradiol benzoate (EB) or GnRH as ovulation induction agents. Cows received a luteolytic dose of PGF2α, followed by administration of EB 24 h later or GnRH 56 h later. Timed AI was performed 24 to 28 h after EB administration or 16 to 20 h after GnRH administration. We analyzed data from 605 AI in 554 cows (1F-EB: n = 193, 2F-EB: n = 100, 1F-GnRH: n = 213, 2F-GnRH: n = 99). Logistic regression analysis revealed a significant interaction between the number of LF and the ovulation induction agent. Pregnancy per AI was significantly lower in the 1F-GnRH group than in the other 3 groups (1F-EB: 40.9%, 2F-EB: 44.0%, 1F-GnRH: 28.2%, 2F-GnRH: 44.4%). In conclusion, the fertility of cows with 1F was lower than that of cows with 2F when GnRH was administered as the ovulation induction agent in the ovulation synchronization and timed AI protocol. However, the fertility of 1F cows receiving EB was comparable to that of 2F cows receiving either GnRH or EB.
Ana S. Cardoso, Sandra Martínez-Jarquín, Robert M. Hyde
et al.
ABSTRACT: Lameness, defined as an impaired gait, impacts cow welfare and performance, compromising future health and production, and increasing culling risk. Untargeted milk lipidomics, together with the use of machine learning methods, have shown promise in identifying potential biomarkers for the early detection of lameness, before the development of visible clinical lameness. Prediction of early lameness would allow for the earlier implementation of management and treatment strategies, ultimately reducing the negative consequences. This study aimed to evaluate the predictive accuracy of differences in the milk metabolome and identify milk lipid biomarkers for early lameness detection in first-lactation dairy cows. Untargeted lipidomics and machine learning approaches were used to evaluate the differences in the milk metabolomic profiles in samples collected from heifers during the transition period (before lameness) and at the time of first lameness onset. A total of 56 milk samples from 32 cows (16 lame, 16 control) were analyzed by liquid chromatography–high-resolution mass spectrometry after calving (before lameness) and at lameness onset. Elastic net regression achieved 83% accuracy in predicting lameness from samples collected after calving and 100% accuracy at the time of lameness. A total of 10 mass ions selected by different statistical methods showed potential to be considered predictors of lameness. Pathway analysis revealed significant dysregulation of retinol metabolism after calving in cows that go on to develop lameness in that lactation. This study demonstrated potential for using milk lipidomics for early lameness detection. This, in turn, provides insights into lameness pathogenesis, furthering our understanding of lameness, with the ultimate goal of developing interventions to improve dairy cow welfare and farm productivity.
ABSTRACT: The objective of this study was to investigate the effects of dietary inclusion of different sources of unsaturated vegetable oil on ruminal fermentation characteristics, nutrient digestion, enteric CH4 emissions, nitrogen partitioning, milk production, and milk fatty acid composition. Eight multiparous ruminally cannulated Holstein cows were used in a duplicated 4 × 4 Latin square design (28-d periods) balanced for residual effects. Treatments consisted of a TMR based on alfalfa silage and corn silage (forage/concentrate ratio 52:48; DM basis) either not supplemented (CTL), or supplemented (4% of DM) with either sunflower (SUN, 67.5% cis-9 18:1), safflower (SAF, 74.6% cis-9, cis-12 18:2), or linseed (LSO, 54.9% cis-9,cis-12,cis-15 18:3) oil. The inclusion of the vegetable oil was performed primarily at the expense of another energy source (i.e., corn grain). Feeding the oil-supplemented diets decreased DMI (−1.2 kg/d, on average) and increased apparent total-tract digestibility of CP, compared with the CTL. However, no changes were noted in digestibility of DM, OM, NDF, gross energy, or the effective ruminal degradability of DM (i.e., in situ technique). Milk yield decreased only when feeding SUN (−3.3 kg/d) or SAF (−4.1 kg/d), compared with the CTL. Milk fat yield decreased when using SAF (−0.44 kg/d, −38%), SUN (−0.32 kg/d, −28%), and LSO (−0.21 kg/d, −18%), compared with the CTL. Milk protein yield was reduced with SUN (−9%) and SAF (−7%) compared with the CTL but was unaffected by LSO. The content of MUN decreased with oil supplementation by 28%, 20%, and 10% for LSO, SAF, and SUN, respectively. In contrast, the efficiency of dietary N use for milk N secretion was not affected when cows were fed the oil-supplemented diets. Relative to N intake, fecal N decreased, whereas urinary N increased with oil-supplemented diets. Oil supplementation did not alter enteric daily CH4 production (SF6 tracer technique) or yield. In the present study, the oils differing in unsaturation level did not change overall ruminal fermentation characteristics, OM digestibility, or CH4 production. Feeding the oil-based diets had no effect on N balance but shifted N excretion from feces to urine. Cows consuming the oil-supplemented diets exhibited reduced milk fat yield, depending on the unsaturation level, with a more pronounced decrease with SAF (i.e., a source of cis-9,cis-12 18:2), followed by SUN (i.e., a source of cis-9 18:1) and LSO (i.e., a source of cis-9,cis-12,cis-15 18:3).
Antonio Desiderio, Alessia Galdeman, Franziska Bauerlein
et al.
Food waste represents a major challenge to global climate resilience, accounting for almost 10% of annual greenhouse gas emissions. The retail sector is a critical player, mediating product flows between producers and consumers, where supply chain inefficiencies can shape which items are put on sale. Yet how these dynamics vary across geographic contexts remains largely unexplored. Here, we analyze data from Denmark's largest retail group on near-expiry products put on sale. We uncover the geospatial variations using a dual-clustering approach. We characterize multi-scale spatial relationships in retail organization by correlating store clustering -- measured using shortest-path distances along the street network -- with product clustering based on promotion co-occurrence patterns. Using a bipartite network approach, we identify three regional store clusters, and use percolation thresholds to corroborate the scale of their spatial separation. We find that stores in rural communities put meat and dairy products on sale up to 2.2 times more frequently than metropolitan areas. In contrast, metropolitan and capital regions lean toward convenience products, which have more balanced nutritional profiles but less favorable environmental impacts. By linking geographic context to retail inventory, we provide evidence that reducing food waste requires interventions tailored to local retail dynamics, highlighting the importance of region-specific sustainability strategies.
Breno C. Bispo, Stefania Sardellitti, Fernando A. N. Santos
et al.
Our goal in this paper is to leverage the potential of the topological signal processing (TSP) framework for analyzing brain networks. Representing brain data as signals over simplicial complexes allows us to capture higher-order relationships within brain regions of interest (ROIs). Here, we focus on learning the underlying brain topology from observed neural signals using two distinct inference strategies. The first method relies on higher-order statistical metrics to infer multiway relationships among ROIs. The second method jointly learns the brain topology and sparse signal representations, of both the solenoidal and harmonic components of the signals, by minimizing the total variation along triangles and the data-fitting errors. Leveraging the properties of solenoidal and irrotational signals, and their physical interpretations, we extract functional connectivity features from brain topologies and uncover new insights into functional organization patterns. This allows us to associate brain functional connectivity (FC) patterns of conservative signals with well-known functional segregation and integration properties. Our findings align with recent neuroscience research, suggesting that our approach may offer a promising pathway for characterizing the higher-order brain functional connectivities.
Fatih Ramazan Istanbullugil, Ali Risvanli, Ruslan Salikov
et al.
ABSTRACT: The aim of this study was to determine the components and cytokine and immunoglobulin levels of koumiss during different fermentation periods, and to reveal the interrelation between these parameters. For achieving this objective, 10 samples of koumiss were prepared and randomly divided into 2 groups: the first group was sampled at 0, 1, 5, 12, and 24 h of incubation at room temperature for analysis. The second group was stored at +4°C, and samples were taken on d 5, 10, 15, and 20. The counts of Enterobacteriaceae spp., Staphylococcus, and Micrococcus spp. progressively decreased with the period of fermentation until becoming undetectable in the final samples of both groups. We fond positive or negative correlations between cytokine and immunoglobulin levels and the physicochemical and microbiological parameters in the koumiss samples in both groups. However, the levels of IFN-γ, IL-2, TNF-α, and IgG did not change significantly over time in both groups. Overall, it is clear that traditionally prepared koumiss under different fermentation times and temperatures does not show any differences in cytokine and immunoglobulin concentrations.
Yuan Liu, John M. Martyn, Jasmine Sinanan-Singh
et al.
Signal processing stands as a pillar of classical computation and modern information technology, applicable to both analog and digital signals. Recently, advancements in quantum information science have suggested that quantum signal processing (QSP) can enable more powerful signal processing capabilities. However, the developments in QSP have primarily leveraged \emph{digital} quantum resources, such as discrete-variable (DV) systems like qubits, rather than \emph{analog} quantum resources, such as continuous-variable (CV) systems like quantum oscillators. Consequently, there remains a gap in understanding how signal processing can be performed on hybrid CV-DV quantum computers. Here we address this gap by developing a new paradigm of mixed analog-digital QSP. We demonstrate the utility of this paradigm by showcasing how it naturally enables analog-digital conversion of quantum signals -- specifically, the transfer of states between DV and CV quantum systems. We then show that such quantum analog-digital conversion enables new implementations of quantum algorithms on CV-DV hardware. This is exemplified by realizing the quantum Fourier transform of a state encoded on qubits via the free-evolution of a quantum oscillator, albeit with a runtime exponential in the number of qubits due to information theoretic arguments. Collectively, this work marks a significant step forward in hybrid CV-DV quantum computation, providing a foundation for scalable analog-digital signal processing on quantum processors.
Phillip Long, Zachary Novack, Taylor Berg-Kirkpatrick
et al.
The recent explosion of generative AI-Music systems has raised numerous concerns over data copyright, licensing music from musicians, and the conflict between open-source AI and large prestige companies. Such issues highlight the need for publicly available, copyright-free musical data, in which there is a large shortage, particularly for symbolic music data. To alleviate this issue, we present PDMX: a large-scale open-source dataset of over 250K public domain MusicXML scores collected from the score-sharing forum MuseScore, making it the largest available copyright-free symbolic music dataset to our knowledge. PDMX additionally includes a wealth of both tag and user interaction metadata, allowing us to efficiently analyze the dataset and filter for high quality user-generated scores. Given the additional metadata afforded by our data collection process, we conduct multitrack music generation experiments evaluating how different representative subsets of PDMX lead to different behaviors in downstream models, and how user-rating statistics can be used as an effective measure of data quality. Examples can be found at https://pnlong.github.io/PDMX.demo/.
ABSTRACT: The intramammary infusion at the end of lactation of a bismuth subnitrate internal teat sealant (ITS), with no antibiotic component has been shown to be an effective means of reducing new intramammary infections over the dry period. There has, however, been very few comparative studies between different brands of ITS under grazed pasture conditions. The objectives of this study were, therefore, to determine if a new bismuth subnitrate internal teal sealant (ShutOut, MSD Animal Health) was noninferior to Teatseal (Zoetis) regarding end-points such as (a) detection of the ITS product after calving, (b) clinical mastitis during the dry period and early lactation, and (c) subclinical mastitis at 30 to 60 d in milk. A total of 1,105 mixed-age cattle were enrolled across 2 farms comparing 2 ITS products for detection of the ITS at calving and prevention of clinical and subclinical mastitis. Both ITS contained 65% (2.6 g) bismuth salts emulsified in ≤ 1.4 g of mineral oil (ShutOut as investigational product, IVP; Teatseal as control product, CPT). At dry-off, treatment was allocated to every second cow. All cows met industry best practice criteria for using ITS treatment without antibiotics. Outcomes included detection of ITS at first stripping of the udder by the farmer, clinical mastitis (CM) from dry-off to 30 d following calving and subclinical mastitis at 30 to 60 d following calving. For ITS detection, a generalized mixed linear regression model was used to model the data, with clustering of quarters within cow accounted for by including cow as a random intercept. Clinical mastitis was analyzed at the cow-level using a Fisher's exact test, and SCC was modeled using a negative binomial distribution. The IVP was noninferior to the CPT for ITS detection following calving. There were 1344/1800 (71.5%) of quarters with ITS detection in the IVP in comparison to 1076/1604 (67.1%) of quarters in the CPT treated group. The quarter-level CM incidence risk was low (45 cases out 4,324 quarters; 1.04%). The overall cow-level CM risk was 4.1% (44/1081), with 20/540 (3.7%) cases in animals in the IVP group and 24/541 (4.4%) cases in animals in the CPT group. The IVP was noninferior to the CPT for cow-level mastitis incidence. The median SCC for all animals was 23,000 cells/mL, with a mean of 92,000 cells/mL. The back-transformed estimated marginal mean estimated SCC was 84,800 (95% CI 75,200–95,600) cells/mL for animals in the IVP group, and 98,800 (95% CI 87,600–111,300) cells/mL for animals in the CPT group. The IVP was, therefore, noninferior for all outcomes measured.
ABSTRACT: Reduction of risk factors for bovine digital dermatitis (BDD) is crucial in current disease control. However, risk factors that might arise especially in mountainous regions are unknown until now, and an adapted BDD control program is consequently missing. The objective of this observational case-control study was to identify farm-level risk factors for BDD in dairy herds in mountainous regions. To investigate predictors for the occurrence of BDD, 100 farms were visited and information about herd characteristics and management practices, potentially relevant explanatory variables for either introduction or establishment of BDD, were gathered by completing a questionnaire with the farmer or herd manager. Within-herd prevalences of BDD assessed during 3 routine claw trimmings with an interval of 6 mo before the survey were used to define cases (BDD within-herd prevalence of ≥26% during each claw trimming) and controls (no BDD cases in each of the 3 routine claw trimmings before the survey). Data were analyzed using 2 separate binomial generalized linear models according to either establishment or introduction of BDD. After prescreening, 15 of 23 explanatory variables were included in the final analysis, which showed 3 variables related to introduction and establishment, each being significantly associated with the occurrence of BDD within a farm. Results of model 1 (i.e., aspects related to BDD introduction) revealed that access to mountain pastures during the summer season (odds ratio, 95% confidence interval: 0.12, 0.04–0.35), participation in dairy shows (0.32, 0.11–0.94), and the number of new animals introduced into the farm during the last 2 yr (1.28, 1.12–1.52) were significantly associated with the occurrence of BDD. Model 2 (i.e., aspects related to BDD establishment) showed that cows kept in freestalls were at higher risk for BDD compared with those kept in tiestalls (20.65, 1.59–649.37). Furthermore, number of days between diagnosis and treatment of a BDD lesion (10.31, 3.55–81.21) and the amount of concentrate feeding (median 5 kg) per cow and day (7.72, 2.46–6.47) were positively associated with BDD occurrence. In conclusion, the findings of this study provide a set of risk factors that are associated with BDD status within herds in mountainous regions. These results may help in development of adapted control programs for BDD in dairy cows.
Shanaz Mustafa Abdullah, Bahroz Muhammed Saleh Ahmed
Colostrum gives the newborn calf maternal antibodies that help it fight disease. A calf that does not receive colostrum has a higher risk of illness until it develops antibodies of its own at around 6 weeks of age. This study aims to evaluate the immunity background of Karadi calves, measuring physiological responses to different qualities of colostrum and testing Karadi calves for survival in the herd. Twelve females local Karadi calves (0-day olds) were divided into two treatments with two levels for each. Using low and high colostrum quality before 6 hours and after 6 hours from parturition. Regarding calf body weight, withers height, immunoglobulin G concentration, and dry matter intake, there is no significant difference between low- and high-quality colostrum feed. However, our results show that calf body weight, withers height, and respiration rate were higher (P < 0.01) when colostrum was fed six hours after birth compared to those fed six hours after birth. However, there is no significant difference in the rectal temperature of the calf fed before six hours and six hours after birth. Results show that the total white blood cells, lymphocyte, neutrophil, eosinophil, and basophil numbers were unaffected by treatment, time and the interaction between treatment and time. Monocyte numbers have a tendency toward significant by treatment. Total plasma protein was not affected by treatment and time, but it tends significant treatment over time.
ABSTRACT: Photooxidation has long been affecting nutrient and sensory quality of fluid milk. Light oxidation starts from the activation of photosensitive compounds, followed by generation of singlet oxygen that reacts with vitamins, proteins, and lipids in milk. It is hypothesized that wavelength-tailored light schemes possessing spectral properties capable of avoiding excitation maxima of common photosensitizers in milk could slow the chemical degradation of light-exposed milk and thus preserve consumer acceptability. A series of 6 consumer tests with sample sizes from 95 to 119 participants tested hedonic responses to fluid milk samples exposed to light of varying wavelength spectra. For milk in clear plastic bottles (polyethylene terephthalate or high-density polyethylene), consumer panels generally liked milk exposed to light-emitting diodes eliminating wavelengths below 520 or 560 nm more than standard white light, or those eliminating other wavelength bands. This higher degree of liking coincided with panelists citing fewer off-flavors or aromas from these samples. Taken together, these observations suggest such light schemes can protect milk from light damage to some extent. Wavelength-tailored light schemes used in this study did not offer effective protection for milk in glass bottles. Dissolved oxygen, color, riboflavin loss, and hexanal content were instrumentally evaluated, but results failed to indicate significant signatures of light damage in milk compared with sensory measures. The appearance of milk bottles illuminated by the slightly greenish or yellowish light were less liked by consumers, suggesting further efforts on consumer education may be necessary if these light schemes were to be installed in retail dairy coolers.
Cow activity measurements are widely used in herd management tools for estrus detection. The aim of this study was to examine whether a new trait based on activity measures can be useful for genetic evaluation of cow fertility in Norwegian Red dairy cattle. Data from 284 herds with Lely milking robot were collected. Daily measurements of cow activity level were available from Lely activity tags and included data from 13,224 lactations of 8,139 Norwegian Red cows. We analyzed daily activity and included records from 10 to 150 d in milk for cows with at least 50 records. The trait analyzed was interval from calving to first high activity (CFHA). In total 87% of the cows had at least one episode of high activity recorded. The mean (standard deviation) of CFHA was 42 (28) days. A linear animal repeatability model with fixed effects of month-year of calving, age-parity, and herd, and random animal and permanent environment effects was used for estimation of variance components. The trait CFHA showed significant genetic variation with a heritability of 0.05 (0.01). This trait reflects the cow's ability to return to estrus cycle and show estrus after calving, which are important aspects of cow fertility.
Let $m$ and $n$ be two positive integers such that $m < n$. Let $Q_{n-m+1}$ be the symplectic quasi-projective space of rank $n-m+1$. In this article, we will study the order of the Samelson product $S^{4m-1}\wedge Q_{n-m+1}\rightarrow Sp(n)$.
Oscar J. Benitez, Rebecca M. LaDronka, Bo Norby
et al.
Bovine leukemia virus (BLV) is a retrovirus of cattle that infects approximately 45% of all US dairy cattle, with about 90% of US dairy herds having at least one infected animal. Studies have found BLV infection to be associated with multiple measures of decreased immune function, which may explain the observed economic losses from milk production, decreased cow longevity, and predisposition to lymphoma and other diseases. Our objective was to measure the association between BLV infection and cow longevity in dairy cow operations. Ninety-one dairy herds from 9 US states volunteered to participate in this study. Milking dairy cows (n = 3,611) were tested for BLV antibodies using an ELISA milk test, and their presence in the herd was monitored for an average of 29 mo. The survival analysis controlled for herd and lactation number. Cows sold for dairy purposes were excluded, and individual cow results were not shared with producers so as not to influence culling decisions. Overall, 47.1% (1,701/3,611) of cows were BLV-positive by ELISA. The significant hazard ratio of 1.30 indicated that positive cows were 30% more likely than their negative herdmates to die or be culled during the monitoring period. These results are consistent with other studies in finding a negative effect of BLV infection on cow lifespan.