967 resultados para somatic cell count in cows


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A morphometric study of the circular colon musculature was performed, in which the mast cell count was determined and the connective fibrous tissue in this layer was measured. The objective was to gain better understanding of Chagas megacolon morphology and contribute towards the knowledge of fibrosis pathogenesis in Chagas megas. An evaluation was made of 15 distal sigmoid rings from Chagas patients with megacolon (MCC), 15 without megacolon (CSMC) and 15 non-Chagas patients (NC). The rings were fixed in formol, embedded in paraffin, and 7mm thick sections were cut and stained using Azan-Heidenhain and Giemsa. The mast cell count and fibrosis were greater in the MCC group than in the CSMC and NC groups (p < 0.05; Kruskal-Wallis test) and there was no significant difference between the latter two. The fibrosis and increased mast cell count in the colon musculature of the MCC group possibly indicates that there is a relationship between mastocytosis and fibrosis, as has already been demonstrated in other pathologies.

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Background: Although CD4 cell count monitoring is used to decide when to start antiretroviral therapy in patients with HIV-1 infection, there are no evidence-based recommendations regarding its optimal frequency. It is common practice to monitor every 3 to 6 months, often coupled with viral load monitoring. We developed rules to guide frequency of CD4 cell count monitoring in HIV infection before starting antiretroviral therapy, which we validated retrospectively in patients from the Swiss HIV Cohort Study.Methodology/Principal Findings: We built up two prediction rules ("Snap-shot rule" for a single sample and "Track-shot rule" for multiple determinations) based on a systematic review of published longitudinal analyses of CD4 cell count trajectories. We applied the rules in 2608 untreated patients to classify their 18 061 CD4 counts as either justifiable or superfluous, according to their prior >= 5% or < 5% chance of meeting predetermined thresholds for starting treatment. The percentage of measurements that both rules falsely deemed superfluous never exceeded 5%. Superfluous CD4 determinations represented 4%, 11%, and 39% of all actual determinations for treatment thresholds of 500, 350, and 200x10(6)/L, respectively. The Track-shot rule was only marginally superior to the Snap-shot rule. Both rules lose usefulness for CD4 counts coming near to treatment threshold.Conclusions/Significance: Frequent CD4 count monitoring of patients with CD4 counts well above the threshold for initiating therapy is unlikely to identify patients who require therapy. It appears sufficient to measure CD4 cell count 1 year after a count > 650 for a threshold of 200, > 900 for 350, or > 1150 for 500x10(6)/L, respectively. When CD4 counts fall below these limits, increased monitoring frequency becomes advisable. These rules offer guidance for efficient CD4 monitoring, particularly in resource-limited settings.

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The buffaloes dairy milk production (BDMP) has increased in the last 20 years, mainly for the manufacturing of mozzarella cheese, which is recognized by its high nutritional quality. However, this quality can be affected by several factors i. e. high somatic cells count (SCC) provokes changes in the milk's constituents. As in bovine dairy milk, the SCC is used as diagnostic tool for milk quality; because it enables the diagnosis of sub-clinic mastitis and also allows the selection of individuals genetically resistant to that disease. Based on it, we collected information about SCC and BDMP along the lactation in Murrah breed buffaloes, during the period between 1997 and 2005. Curves were designed to estimate genetic parameters. These parameters were estimated by ordinary test-day models. There were observed variations in the estimated heritability for both characteristics the lowest score for somatic cells count (SSCC) was seen at first month (0.01) and the highest at sixth months (0.29 the genetic correlation between these traits varied from -1 at the 1 and 9(th) months to 0.31 and 0.30 in the2 and 4(th) month of lactation. Phenotypic correlations were all negative (-0.07 in the second month and up to -0.35 in the eighth month of lactation). These results showed that environmental factors are more important than genetics in explain SCC, for this reason, selection for genetic resistance to mastitis in buffalos based in SCC should not be done. In the other hand, negative phenotypic correlations demonstrated that as the SCC increased, the milk production decreased.

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Background Although CD4 cell count monitoring is used to decide when to start antiretroviral therapy in patients with HIV-1 infection, there are no evidence-based recommendations regarding its optimal frequency. It is common practice to monitor every 3 to 6 months, often coupled with viral load monitoring. We developed rules to guide frequency of CD4 cell count monitoring in HIV infection before starting antiretroviral therapy, which we validated retrospectively in patients from the Swiss HIV Cohort Study. Methodology/Principal Findings We built up two prediction rules (“Snap-shot rule” for a single sample and “Track-shot rule” for multiple determinations) based on a systematic review of published longitudinal analyses of CD4 cell count trajectories. We applied the rules in 2608 untreated patients to classify their 18 061 CD4 counts as either justifiable or superfluous, according to their prior ≥5% or <5% chance of meeting predetermined thresholds for starting treatment. The percentage of measurements that both rules falsely deemed superfluous never exceeded 5%. Superfluous CD4 determinations represented 4%, 11%, and 39% of all actual determinations for treatment thresholds of 500, 350, and 200×106/L, respectively. The Track-shot rule was only marginally superior to the Snap-shot rule. Both rules lose usefulness for CD4 counts coming near to treatment threshold. Conclusions/Significance Frequent CD4 count monitoring of patients with CD4 counts well above the threshold for initiating therapy is unlikely to identify patients who require therapy. It appears sufficient to measure CD4 cell count 1 year after a count >650 for a threshold of 200, >900 for 350, or >1150 for 500×106/L, respectively. When CD4 counts fall below these limits, increased monitoring frequency becomes advisable. These rules offer guidance for efficient CD4 monitoring, particularly in resource-limited settings.

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Animal traits differ not only in mean, but also in variation around the mean. For instance, one sire’s daughter group may be very homogeneous, while another sire’s daughters are much more heterogeneous in performance. The difference in residual variance can partially be explained by genetic differences. Models for such genetic heterogeneity of environmental variance include genetic effects for the mean and residual variance, and a correlation between the genetic effects for the mean and residual variance to measure how the residual variance might vary with the mean. The aim of this thesis was to develop a method based on double hierarchical generalized linear models for estimating genetic heteroscedasticity, and to apply it on four traits in two domestic animal species; teat count and litter size in pigs, and milk production and somatic cell count in dairy cows. The method developed is fast and has been implemented in software that is widely used in animal breeding, which makes it convenient to use. It is based on an approximation of double hierarchical generalized linear models by normal distributions. When having repeated observations on individuals or genetic groups, the estimates were found to be unbiased. For the traits studied, the estimated heritability values for the mean and the residual variance, and the genetic coefficients of variation, were found in the usual ranges reported. The genetic correlation between mean and residual variance was estimated for the pig traits only, and was found to be favorable for litter size, but unfavorable for teat count.

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The effect of somatic cell count (SCC) and milk fraction on milk composition, distribution of cell populations, and mRNA expression of various inflammatory parameters was studied. Therefore, quarter milk samples were defined as cisternal (C), first 400 g of alveolar (A1), and remaining alveolar milk (A2) during the course of milking. Quarters were assigned to 4 groups according to their total SCC: 1) <12 x 10(3)/mL, 2) 12 to 100 x 10(3)/mL, 3) 100 to 350 x 10(3)/mL, and 4) >350 x 10(3)/mL. Milk constituents of interest were SCC, fat, protein, lactose sodium, and chloride ions as well as electrical conductivity. Cell populations were classified into lymphocytes, macrophages, and neutrophils (PMN). The mRNA expression of the inflammatory factors tumor necrosis factor-alpha, interleukin-1beta, cyclooxygenase-2, lactoferrin, and lysozyme was measured via real-time, quantitative reverse transcription PCR. Somatic cell count decreased from highest levels in C to lowest levels in A1 and increased thereafter to A2 in all groups. Fat content increased from C to A2 and with increasing SCC level. Lactose decreased with increasing SCC level but remained unchanged during milking. Concentrations of sodium and chloride, and electrical conductivity increased with increasing SCC but were higher in C than in A1 and A2. Protein was not affected by milk fraction or SCC level. The distribution of leukocytes was dramatically influenced by milk fraction and SCC. Lymphocytes were the dominating cell population in group 1, but the proportion of lymphocytes was low in groups 2, 3, and 4. Macrophage proportion was highest in group 2 and decreased in groups 3 and 4, whereas that of PMN increased from group 2 to 4. The content of macrophages decreased during milking in all SCC groups whereas that of PMN increased. The proportion of lymphocytes was not affected by milk fraction. The mRNA expression of all inflammatory factors showed an increase with increasing SCC but minor changes occurred during milking. In conclusion, milk fraction and SCC level have a crucial influence on the distribution of leukocyte populations and several milk constituents. The surprisingly high content of lymphocytes and concomitantly low mRNA expression of inflammatory factors in quarters with SCC <12 x 10(3)/mL indicates a different and possibly reduced readiness of the immune system to respond to invading pathogens.

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The purpose of the present trial was to compare the percentages of necrotic and apoptotic polymorphonuclear leukocytes (PMNL) in goat milk with low and high somatic cell count (SCC). Twenty eight milk samples were collected from 20 lactating goats, determined to be negative in bacteriological examination, and divided in three groups, according to their SCC: samples with SCC lower than 500 x 10(3) cells/mL; between 500 and 1500 x 10(3) cells/mL; and higher than 1500 x 10(3) cells/m L. SCC was performed in an automatic somatic cell counter. Apoptosis and necrosis were quantified using dual-color flow cytometry with fluorescein labeled annexin-V and propidium iodide (PI). Results of the present study showed a significant positive correlation between the percentage of the viable PMNL and milk SCC(r = 0.495, P=0.008), as well as a significant negative correlation between apoptotic PMNL and milk SCC(r = -0.486, P = 0.009). Results also pointed out lower PMNL viability rates due to higher apoptosis rates in milk samples with SCC lower than 5 x 10(5) cells/mL. (C) 2011 Elsevier B.V. All rights reserved.

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Herd Companion uses routine milk‐recording records to generate twelve‐month rolling averages that indicate performance trends. This article looks at Herd Somatic Cell Count (SCC) and four other SCC‐related parameters from 252 National Milk Records (NMR) recorded herds to assess how each parameter correlates with the Herd SCC. The analysis provides evidence for the importance of targeting individual cows with high SCC recordings (>200,000 cells/ml and >500,000 cells/ml) and/or individual cows with repeatedly high SCC recordings (chronic high SCC) and/or cows that begin lactation with a high SCC recording (dry period infection) in order to achieve bulk milk Herd SCC below 200,000 cells/ml.

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As an important step in the nuclear transfer (NT) procedure, we evaluated the effect of three different treatments for oocyte activation on the in vitro and in vivo developmental capacity of bovine reconstructed embryos: (1) strontium, which has been successfully used in mice but not yet tested in cattle; (2) ionomycin and 6-dimethylammopurine (6-DMAP), a standard treatment used in cattle; (3) ionomycin and strontium, in place of 6-DMAP. As regards NT blastocyst development, no difference was observed when strontium (20.1%) or ionomycin/6-DMAP (14.4%) were used. However, when 6-DMAP was substituted by strontium (3), the blastocyst rate (34.8%) was superior to that in the other activation groups (p < 0.05). Results of in vivo development showed the possibility of pregnancies when NT embryos activated in strontium were transferred to recipient cows (16.6%). A live female calf was obtained when ionomycin/strontium were used, but it died 30 days after birth. Our findings show that strontium can be used as an activation agent in bovine cloning procedures and that activation with a combination of strontium and ionomycin increased the in vitro developmental capacity of reconstructed embryos. This is the first report of a calf produced by adult somatic cell NT in Latin America.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Determination of somatic cell count (SCC) is used worldwide in dairy practice to describe the hygienic status of the milk and the udder health of cows. When SCC is tested on a quarter level to detect single quarters with high SCC levels of cows for practical reasons, mostly foremilk samples after prestimulation (i.e. cleaning of the udder) are used. However, SCC is usually different in different milk fractions. Therefore, the goal of this study was the investigation of the use of foremilk samples for the estimation of total quarter SCC. A total of 378 milkings in 19 dairy cows were performed with a special milking device to drain quarter milk separately. Foremilk samples were taken after udder stimulation and before cluster attachment. SCC was measured in foremilk samples and in total quarter milk. Total quarter milk SCC could not be predicted precisely from foremilk SCC measurements. At relatively high foremilk SCC levels (>300 x 10(3) cells/ml) foremilk SCC were higher than total quarter milk. At around (50-300) x 10(3) cells/ml foremilk and total quarter SCC did not differ considerably. Most interestingly, if foremilk SCC was lower than 50 x 10(3) cells/ml the total quarter SCC was higher than foremilk SCC. In addition, individual cows showed dramatic variations in foremilk SCC that were not very well related to total quarter milk SCC. In conclusion, foremilk samples are useful to detect high quarter milk SCC to recognize possibly infected quarters, only if precise cell counts are not required. However, foremilk samples can be deceptive if very low cell numbers are to be detected.

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BACKGROUND: In recent years, treatment options for human immunodeficiency virus type 1 (HIV-1) infection have changed from nonboosted protease inhibitors (PIs) to nonnucleoside reverse-transcriptase inhibitors (NNRTIs) and boosted PI-based antiretroviral drug regimens, but the impact on immunological recovery remains uncertain. METHODS: During January 1996 through December 2004 [corrected] all patients in the Swiss HIV Cohort were included if they received the first combination antiretroviral therapy (cART) and had known baseline CD4(+) T cell counts and HIV-1 RNA values (n = 3293). For follow-up, we used the Swiss HIV Cohort Study database update of May 2007 [corrected] The mean (+/-SD) duration of follow-up was 26.8 +/- 20.5 months. The follow-up time was limited to the duration of the first cART. CD4(+) T cell recovery was analyzed in 3 different treatment groups: nonboosted PI, NNRTI, or boosted PI. The end point was the absolute increase of CD4(+) T cell count in the 3 treatment groups after the initiation of cART. RESULTS: Two thousand five hundred ninety individuals (78.7%) initiated a nonboosted-PI regimen, 452 (13.7%) initiated an NNRTI regimen, and 251 (7.6%) initiated a boosted-PI regimen. Absolute CD4(+) T cell count increases at 48 months were as follows: in the nonboosted-PI group, from 210 to 520 cells/muL; in the NNRTI group, from 220 to 475 cells/muL; and in the boosted-PI group, from 168 to 511 cells/muL. In a multivariate analysis, the treatment group did not affect the response of CD4(+) T cells; however, increased age, pretreatment with nucleoside reverse-transcriptase inhibitors, serological tests positive for hepatitis C virus, Centers for Disease Control and Prevention stage C infection, lower baseline CD4(+) T cell count, and lower baseline HIV-1 RNA level were risk factors for smaller increases in CD4(+) T cell count. CONCLUSION: CD4(+) T cell recovery was similar in patients receiving nonboosted PI-, NNRTI-, and boosted PI-based cART.

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BACKGROUND: In recent years, treatment options for human immunodeficiency virus type 1 (HIV-1) infection have changed from nonboosted protease inhibitors (PIs) to nonnucleoside reverse-transcriptase inhibitors (NNRTIs) and boosted PI-based antiretroviral drug regimens, but the impact on immunological recovery remains uncertain. METHODS: During January 1996 through December 2004 [corrected] all patients in the Swiss HIV Cohort were included if they received the first combination antiretroviral therapy (cART) and had known baseline CD4(+) T cell counts and HIV-1 RNA values (n = 3293). For follow-up, we used the Swiss HIV Cohort Study database update of May 2007 [corrected] The mean (+/-SD) duration of follow-up was 26.8 +/- 20.5 months. The follow-up time was limited to the duration of the first cART. CD4(+) T cell recovery was analyzed in 3 different treatment groups: nonboosted PI, NNRTI, or boosted PI. The end point was the absolute increase of CD4(+) T cell count in the 3 treatment groups after the initiation of cART. RESULTS: Two thousand five hundred ninety individuals (78.7%) initiated a nonboosted-PI regimen, 452 (13.7%) initiated an NNRTI regimen, and 251 (7.6%) initiated a boosted-PI regimen. Absolute CD4(+) T cell count increases at 48 months were as follows: in the nonboosted-PI group, from 210 to 520 cells/muL; in the NNRTI group, from 220 to 475 cells/muL; and in the boosted-PI group, from 168 to 511 cells/muL. In a multivariate analysis, the treatment group did not affect the response of CD4(+) T cells; however, increased age, pretreatment with nucleoside reverse-transcriptase inhibitors, serological tests positive for hepatitis C virus, Centers for Disease Control and Prevention stage C infection, lower baseline CD4(+) T cell count, and lower baseline HIV-1 RNA level were risk factors for smaller increases in CD4(+) T cell count. CONCLUSION: CD4(+) T cell recovery was similar in patients receiving nonboosted PI-, NNRTI-, and boosted PI-based cART.

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The aims of this study were to quantify the effectiveness of specialist advice about udder health in Swiss dairy herds and to compare 3 different udder health improvement strategies against a negative control group. In 2010, 100 Swiss dairy herds with a high (between 200,000 and 300,000 cells/mL) yield-corrected bulk milk somatic cell count (YCBMSCC) were recruited for a 1-yr multiarm randomized field trial. The herds were visited between September and December 2011 to evaluate udder health-management practices and then randomly allocated into 1 of 4 study arms containing 25 herds each. The negative control study arm received neither recommendations for improving udder health nor any active support. The remaining 75 farmers received a herd-specific report with recommendations to improve udder health management. The positive control study arm received no further active support during 2012. The veterinarian study arm received additional support in the form of monthly visits by their herd veterinarian. Finally, the study group study arm received support in the form of bimonthly study group meetings where different topics concerning udder health were discussed. One year later, implementation of recommendations and changes in udder health were assessed. Of the recommendations given, 44.3% were completely implemented, 23.1% partially, and 32.6% were not implemented. No differences in implementation of recommendations were noted between the 3 study arms. At study enrollment, farmers were asked for the study arm of their preference but were subsequently randomly assigned to 1 of the 4 study arms. Farmers that were assigned to the study arm of their preference implemented more recommendations than farmers assigned to a study arm not of their preference. No decrease in the within-herd prevalence of cows that had a high (≥200,000 cells/mL) composite somatic cell count was observed in herds that had a YCBMSCC ≥200,000 cells/mL at the start of intervention. However, the 3 study arms with intervention (positive control, the veterinarian, and the study groups) prevented an increase in the within-herd prevalence of cows that had a high somatic cell count in herds with a low YCBMSCC at the start of the intervention compared with the negative control study arm. In the year after sending the report, herds assigned to the study group study arm had a reduced incidence rate of treated mastitis cases in comparison with the year before sending the report.