Stress and cancer in dogs : Comparison between a population of dogs diagnosed with cancer and a control population : a pilot study

It is widely accepted that psychological stress and mental illness can compromise the function of the immune system. Clinical and epidemiological studies on humans recognized that specific psychosocial factors, such as stress, chronic depression and lack of social support are risk factors for the development and progression of cancer. Unfortunately, most of the animals studies on this subject are based on laboratory tests performed on mice. This retrospective cohort study aims to analyze the relation between stress and tumor in pet dogs, by evaluating and comparing the stress level in two groups of 69 dogs each, balanced for sex and age: the oncologic group consists of dogs diagnosed with cancer and the control group consists of healthy dogs. Our results show that, before the cancer diagnosis, more dogs in the oncologic group faced changes in their household and routine as opposed to the control group (p<0.05). More dogs of the oncologic group than the control group also showed signs of stress and anxiety, before the cancer diagnosis (p<0.05). As reported by their owners, these included attention seeking, hiding without a specific reason, following the owner around the house, hyper-vigilance, fear of fireworks and gunshots, biting, aggression towards other dogs, licking and chewing excessively parts of their body. Our results are aligned with the evidence from human research, indicating that dogs with cancer are significantly more likely to have shown signs of stress compared to the control dogs during their life

Measuring dairy cow welfare with real-time sensor-based data and farm records: a concept study

Welfare assessment of dairy cows by in-person farm visits provides only a snapshot of welfare and is time-consuming and costly. Possible solutions to reduce the need for in-person assessments would be to exploit sensor data and other routinely collected on-farm records. The aim of this study was to develop an algorithm to classify dairy cow welfare based on sensors (accelerometer and/or milk meter) and farm records (e.g. days in milk, lactation number). In total, 318 cows from six commercial farms located in Finland, Italy and Spain (two farms each) were enrolled for a pilot study lasting 135 days. During this time, cows were routinely scored using 14 animal-based measures of good feeding, health and housing based on the Welfare Quality® (WQ®) protocol. WQ® measures were evaluated daily or approximately every 45 days, using disease treatments from farm records and on-farm visits, respectively. WQ® measures were supplemented with daily temperature-humidity index to account for heat stress. The severity and duration of each welfare measure were evaluated, and the final welfare index was obtained by summing up the values for each cow on each pilot study day, and stratifying the result into three classes: good, moderate and poor welfare. For model building, a machine-learning (ML) algorithm based on gradient-boosted trees (XGBoost) was applied. Two model versions were tested: (1) a global model tested on unseen herd, and (2) a herd-specific model tested on unseen part of the data from the same herd. The version (1) served as an example on the model performance on a herd not previsited by the evaluator, while version (2) resembled a custom-made solution requiring in-person welfare evaluation for model training. Our results indicated that the global model had a low performance with average sensitivity and specificity of 0.44 and 0.68, respectively. For the herd-specific version, the model performance was higher reaching an average of 0.64 sensitivity and 0.80 specificity. The highest classification performance was obtained for cows in poor welfare, followed by cows in good and moderate welfare (balanced accuracy of 0.77, 0.71 and 0.68, respectively). Since the global model had low classification accuracy, the use of the developed model as a stand-alone system based solely on sensor data is infeasible, and a combination of in-person and sensor-based welfare evaluation would be preferable for a reliable welfare assessment. ML-based solutions, even with fair discriminative abilities, have the potential to enhance dairy welfare monitoring

A Systematic Review on Commercially Available and Validated Sensor Technologies for Welfare Assessment of Dairy Cattle

In order to base welfare assessment of dairy cattle on real-time measurement, integration of valid and reliable precision livestock farming (PLF) technologies is needed. The aim of this study was to provide a systematic overview of externally validated and commercially available PLF technologies, which could be used for sensor-based welfare assessment in dairy cattle. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic literature review was conducted to identify externally validated sensor technologies. Out of 1,111 publications initially extracted from databases, only 42 studies describing 30 tools (including prototypes) met requirements for external validation. Moreover, through market search, 129 different retailed technologies with application for animal-based welfare assessment were identified. In total, only 18 currently retailed sensors have been externally validated (14%). The highest validation rate was found for systems based on accelerometers (30% of tools available on the market have validation records), while the lower rates were obtained for cameras (10%), load cells (8%), miscellaneous milk sensors (8%), and boluses (7%). Validated traits concerned animal activity, feeding and drinking behavior, physical condition, and health of animals. The majority of tools were validated on adult cows. Non-active behavior (lying and standing) and rumination were the most often validated for the high performance. Regarding active behavior (e.g., walking), lower performance of tools was reported. Also, tools used for physical condition (e.g., body condition scoring) and health evaluation (e.g., mastitis detection) were classified in lower performance group. The precision and accuracy of feeding and drinking assessment varied depending on measured trait and used sensor. Regarding relevance for animal-based welfare assessment, several validated technologies had application for good health (e.g., milk quality sensors) and good feeding (e.g., load cells, accelerometers). Accelerometers-based systems have also practical relevance to assess good housing. However, currently available PLF technologies have low potential to assess appropriate behavior of dairy cows. To increase actors' trust toward the PLF technology and prompt sensor-based welfare assessment, validation studies, especially in commercial herds, are needed. Future research should concentrate on developing and validating PLF technologies dedicated to the assessment of appropriate behavior and tools dedicated to monitoring the health and welfare in calves and heifers

Efficacy of a diet containing caseinate hydrolysate on signs of stress in dogs

The purpose of this randomized, double blind, placebo-controlled trial was to evaluate 3 the efficacy of a diet containing caseinate hydrolysate (CH) on signs of stress in 2 4 groups of dogs (defined as Anxious and Non-anxious) using physiological (serum 5 cortisol and lysozyme, N:L ratios and heart rate) and behavioral parameters. 6 From an initial group of 40 female Beagle dogs, ranging in age from 10 months to 4 7 years (mean = 1.47 years; SD = 0.53) belonging to a dog colony, 32 were selected for 8 this study according to their level of anxiety. A group of 16 Anxious dogs and a group 9 of 16 Non-anxious dogs were identified. 10 A baseline period, aimed to obtain reference values of investigated parameters, 11 preceded the experimental phase. Both groups (Anxious and Non-anxious) were divided 12 into a treatment group, which received the diet containing CH, and a control group 13 which received a placebo diet (PD). Anxious CH and PD groups were balanced for 14 anxiety level. Each dog was evaluated 3 times a day at 4 weeks intervals (T1-T2-T3). 15 Each evaluation lasted 2 days and involved a Reactivity Evaluation Form (REF), a 16 blood sampling, heart rate recording and a 10 min behavioral video recording. Results 17 from REF scores showed that while at T1 Anxious dogs had significantly higher scores 18 (Mann-Whitney test: P<0.001) compared to Non-anxious dogs, no difference was found 19 between Anxious dogs fed with CH diet and Non-anxious fed with PD or CH diet at T3. 20 Behavioral observations evidenced some signs of improvement in Anxious dog fed with 21 CH diet. Cortisol level significantly decreased in Anxious dogs fed with CH diet 22 (Friedman test: P<0.05). Individual differences in physiological measures of stress 23 responses may have contributed to the large variability, making interpretation of these 24 measures difficult. These results suggest that CH may be used as a functional ingredient 25 alleviating stress in dogs

A Pilot Study to Develop an Assessment Tool for Dogs Undergoing Trap-Neuter-Release (TNR) in Italy. An Overview on the National Implementation of TNR Programmes

A descriptive analysis, inter-observer and test–retest reliability of the animal-based measures (ABMs) included in the protocol were performed. This study aimed at the development of a welfare assessment protocol for dogs recruited in the trap-neuter-release (TNR) programmes and the description of the implantation of these programmes in Italy. Nine Italian regions carried out TNR programmes. A varied scenario, along with some critical issues, emerged. Fifty dogs were recruited and assessed simultaneously by two assessors to determine the reliability of ABMs included in the protocol. A subsample of ten dogs were assessed three times to assess test–retest reliability. All females were neutered against 36% of males. Most dogs were adults (58%) and of a large size (68%). Vaccine prophylaxis and parasitic prevention were regular in 13% and 76% of dogs, respectively. Few dogs showed lameness, evidence of pain, other clinical problems, or thermal discomfort. Overall, 82% of dogs did not show fear or aggression to unfamiliar people. The level of agreement between the two assessors was quite high, ranging from substantial (0.61–0.80) to perfect (1) for the majority of measures. This study highlighted some critical issues in TNR implementation and the suitability of the protocol as a tool for animal welfare assessment