The influences of age in calves' immune system are described in their first phase of life. We hypothesized that variations that occur in the main mechanisms of lung innate response can help to identify periods of greater susceptibility to the respiratory diseases that affect calves in the first stage of their life. This study aimed to evaluate the innate immune system. Nine healthy calves were monitored for 3 mo and 8 immunologic evaluations were performed. Bronchoalveolar lavage samples were recovered by bronchoscopy. The alveolar macrophages in samples were identified by protein expression of cluster of differentiation 14 (CD14) and underwent functional evaluation of phagocytosis (Staphylococcus aureus stained with propidium iodide and Escherichia coli). Data was assessed by one-way ANOVA (unstacked and parametric) and the Mann-Whitney test (nonparametric). Functional alterations in CD14-positive phagocytes were observed, with punctual higher intensity of phagocytosis in the third week and its decrease starting at 45 d of life. A gradual increase in phagocytosis rate was observed starting at this date. It is concluded that from 45 d of life on, alveolar macrophages have less phagocytic capacity but more cells perform this function. We suggest that this occurs because lung macrophages of calves start to maintain their immune response without passive immunity influence. Until 90 d of life, calves did not achieve the stability to conclude the maturation of local innate immune response.
Chronic kidney disease is a common disease in dogs, and factors such as serum concentrations of creatinine, albumin, and phosphorus at the moment of diagnosis may influence the survival of these patients. The present retrospective study aimed to evaluate the relationship between survival in dogs with chronic kidney disease and laboratory parameters (creatinine, phosphorus, albumin, and hematocrit) and nutritional parameters (body condition score, muscle mass score, type of food, appetite and feeding method). A total of 116 dogs with chronic kidney disease stages 2 to 4 were included, and survival was calculated considering the time between diagnosis and death. Survival curves were configurated by Kaplan-Meier analysis and a comparison between survival curves was performed by the log-rank test. Factors related to survival were disease stage (p<0.0001), serum phosphorus concentration (p = 0.0005), hematocrit (0.0001), body condition score (p = 0.0391), muscle mass score (p = 0.0002), type of food (p = 0.0009), feeding method (p<0.0001) and appetite (p = 0.0007). Based on data obtained in this study, it is possible to conclude that early diagnosis, as well as nutritional evaluation and renal diet intake, are determinant strategies to increase survival in dogs with chronic kidney disease.
ObjectiveThis study aimed to propose a simple, accessible and low-cost predictive clinical model to detect lung lesions due to COVID-19 infection.DesignThis prospective cohort study included COVID-19 survivors hospitalised between 30 March 2020 and 31 August 2020 followed-up 6 months after hospital discharge. The pulmonary function was assessed using the modified Medical Research Council (mMRC) dyspnoea scale, oximetry (SpO2), spirometry (forced vital capacity (FVC)) and chest X-ray (CXR) during an in-person consultation. Patients with abnormalities in at least one of these parameters underwent chest CT. mMRC scale, SpO2, FVC and CXR findings were used to build a machine learning model for lung lesion detection on CT.SettingA tertiary hospital in Sao Paulo, Brazil.Participants749 eligible RT-PCR-confirmed SARS-CoV-2-infected patients aged ≥18 years.Primary outcome measureA predictive clinical model for lung lesion detection on chest CT.ResultsThere were 470 patients (63%) that had at least one sign of pulmonary involvement and were eligible for CT. Almost half of them (48%) had significant pulmonary abnormalities, including ground-glass opacities, parenchymal bands, reticulation, traction bronchiectasis and architectural distortion. The machine learning model, including the results of 257 patients with complete data on mMRC, SpO2, FVC, CXR and CT, accurately detected pulmonary lesions by the joint data of CXR, mMRC scale, SpO2 and FVC (sensitivity, 0.85±0.08; specificity, 0.70±0.06; F1-score, 0.79±0.06 and area under the curve, 0.80±0.07).ConclusionA predictive clinical model based on CXR, mMRC, oximetry and spirometry data can accurately screen patients with lung lesions after SARS-CoV-2 infection. Given that these examinations are highly accessible and low cost, this protocol can be automated and implemented in different countries for early detection of COVID-19 sequelae.
Maintenance energy requirement (MER) is the energy amount necessary for dogs to maintain their weight and body condition. Some factors can influence the MER, such as gender, age, neutering status and also diseases. The present retrospective study aimed to evaluate MER of adult dogs with several diseases and compare with the MER of healthy adult dogs, observing the influence of parameters such as body condition score (BCS), neutering status, gender, age, diagnosis and type of food on MER of these dogs. A total of 165 adult dogs with weight changes of ≤5% were included and divided in groups according to diagnosis. Mean MER for healthy dogs was 86.09 kcal/BW0.75, which differed from NRC and FEDIAF recommendations for inactive adult dogs (p = .047). Lowest MERs were of the endocrinopathies (78.52 ± 19.32 kcal/BW0.75), orthopaedic diseases (59.71 ± 19.30 kcal/BW0.75) and neurologic diseases (78.83 ± 32.66 kcal/BW0.75) groups. Gastrointestinal diseases (99.59 ± 20.36 kcal/BW0.75), orthopaedic diseases (59.71 ± 19.30 kcal/BW0.75) and neoplasia (95.61 ± 21.02 kcal/BW0.75) groups were the only groups that differed from the mean MER of healthy adult dogs. Regarding BCS, for each increasing point in a 9‐point scale, there was a decrease of 9.8 kcal/BW0.75 on MER, independent of diagnosis (p < .0001; r2 = .55). There was no difference regarding breed size gender and age, but neutered dogs presented lower MER (p = .031). Based on data obtained from the present study, it can be concluded that it is necessary to consider BCS, age, neutering status and diagnosis when calculating MER, both in healthy dogs and chronically ill dogs.
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