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American Family Physician Sep 2003Lumbar puncture is frequently performed in primary care. Properly interpreted tests can make cerebrospinal fluid (CSF) a key tool in the diagnosis of a variety of...
Lumbar puncture is frequently performed in primary care. Properly interpreted tests can make cerebrospinal fluid (CSF) a key tool in the diagnosis of a variety of diseases. Proper evaluation of CSF depends on knowing which tests to order, normal ranges for the patient's age, and the test's limitations. Protein level, opening pressure, and CSF-to-serum glucose ratio vary with age. Xanthochromia is most often caused by the presence of blood, but several other conditions should be considered. The presence of blood can be a reliable predictor of subarachnoid hemorrhage but takes several hours to develop. The three-tube method, commonly used to rule out a central nervous system hemorrhage after a "traumatic tap," is not completely reliable. Red blood cells in CSF caused by a traumatic tap or a subarachnoid hemorrhage artificially increase the white blood cell count and protein level, thereby confounding the diagnosis. Diagnostic uncertainty can be decreased by using accepted corrective formulas. White blood cell differential may be misleading early in the course of meningitis, because more than 10 percent of cases with bacterial infection will have an initial lymphocytic predominance and viral meningitis may initially be dominated by neutrophils. Culture is the gold standard for determining the causative organism in meningitis. However, polymerase chain reaction is much faster and more sensitive in some circumstances. Latex agglutination, with high sensitivity but low specificity, may have a role in managing partially treated meningitis. To prove herpetic, cryptococcal, or tubercular infection, special staining techniques or collection methods may be required.
Topics: Cell Count; Central Nervous System Diseases; Cerebrospinal Fluid; Cerebrospinal Fluid Proteins; Humans; Leukocyte Count; Meningitis
PubMed: 14524396
DOI: No ID Found -
The Journal of Comparative Neurology Dec 2016For half a century, the human brain was believed to contain about 100 billion neurons and one trillion glial cells, with a glia:neuron ratio of 10:1. A new counting... (Review)
Review
For half a century, the human brain was believed to contain about 100 billion neurons and one trillion glial cells, with a glia:neuron ratio of 10:1. A new counting method, the isotropic fractionator, has challenged the notion that glia outnumber neurons and revived a question that was widely thought to have been resolved. The recently validated isotropic fractionator demonstrates a glia:neuron ratio of less than 1:1 and a total number of less than 100 billion glial cells in the human brain. A survey of original evidence shows that histological data always supported a 1:1 ratio of glia to neurons in the entire human brain, and a range of 40-130 billion glial cells. We review how the claim of one trillion glial cells originated, was perpetuated, and eventually refuted. We compile how numbers of neurons and glial cells in the adult human brain were reported and we examine the reasons for an erroneous consensus about the relative abundance of glial cells in human brains that persisted for half a century. Our review includes a brief history of cell counting in human brains, types of counting methods that were and are employed, ranges of previous estimates, and the current status of knowledge about the number of cells. We also discuss implications and consequences of the new insights into true numbers of glial cells in the human brain, and the promise and potential impact of the newly validated isotropic fractionator for reliable quantification of glia and neurons in neurological and psychiatric diseases. J. Comp. Neurol. 524:3865-3895, 2016. © 2016 Wiley Periodicals, Inc.
Topics: Animals; Brain; Cell Count; History, 19th Century; History, 20th Century; History, 21st Century; Humans; Neuroglia; Neurons
PubMed: 27187682
DOI: 10.1002/cne.24040 -
Journal of Dairy Science Nov 2021Compared with dairy cows, goat somatic cell count (SCC) is higher and probably more affected by physiological factors such as parity, stage of lactation, and season....
Compared with dairy cows, goat somatic cell count (SCC) is higher and probably more affected by physiological factors such as parity, stage of lactation, and season. Thus, SCC is believed to be a less precise indicator of intramammary infections in dairy goats, and no consensus exists on SCC thresholds for considering goats as infected. The Norwegian Goat Recording System maintains individual goat production records and results from microbiological analyses of milk samples. In this retrospective observational study, we used recordings over a 10-yr period (2010 to 2020) to describe the association between individual goat SCC and noninfectious factors, as well as intramammary infections. The median SCC in the 1,000,802 milk recordings included in the study was 440,000 cells/mL, and the mode was 70,000 cells/mL. Somatic cell count increased with parity, days in milk, estrus, pasture season, and intramammary infections. The effect of parity and stage of lactation was significantly higher in infected compared with uninfected goats. Staphylococci dominated as causes of intramammary infections, with Staphylococcus aureus as the udder pathogen associated with highest SCC. The most prevalent non-aureus staphylococci were Staphylococcus warneri, Staphylococcus epidermidis, and Staphylococcus caprae. This study provides guidelines for interpretation of goat SCC at different parities and stages of lactations under Norwegian management conditions. We revealed a considerable variation in SCC associated with physiological factors, indicating that the cutoff for identifying infected goats should be a dynamic threshold adjusted for parity, stage of lactation, and season.
Topics: Animals; Cattle; Cattle Diseases; Cell Count; Female; Goat Diseases; Goats; Lactation; Mammary Glands, Animal; Mastitis; Mastitis, Bovine; Milk; Pregnancy; Staphylococcal Infections; Staphylococcus
PubMed: 34364641
DOI: 10.3168/jds.2021-20549 -
Journal of Dairy Science Mar 2021Somatic cell count is frequently used as an indicator of intramammary infections (IMI) in dairy cattle worldwide. The newly introduced differential SCC (DSCC) can...
Somatic cell count is frequently used as an indicator of intramammary infections (IMI) in dairy cattle worldwide. The newly introduced differential SCC (DSCC) can potentially contribute to detection of IMI. The purpose of this study was to investigate the dynamics of SCC and DSCC after IMI. We used a data set with monthly samples from 2 Danish dairy herds through 1 yr, using bacterial culture to identify IMI. The dynamics of SCC and DSCC with regard to IMI were assessed at quarter level following new IMI with each of 3 defined pathogen groups, major, minor, or "other" pathogens, using general additive models. Both SCC and DSCC increased after IMI, with a more pronounced increase if major or other pathogens were detected compared with minor pathogens. We found that DSCC increased after IMI with other pathogens in both herds and, in herd 2, after IMI caused by major and minor pathogens. We also estimated the duration of increased SCC and DSCC when they exceeded a threshold, done separately for each pathogen group. Major pathogens had the longest-lasting effect in both herds for both SCC and DSCC. We conclude that the magnitude and duration of response of SCC and DSCC to IMI differs between herds and causative pathogens.
Topics: Animals; Cattle; Cattle Diseases; Cell Count; Female; Mastitis, Bovine; Milk; Staphylococcal Infections
PubMed: 33455778
DOI: 10.3168/jds.2020-19378 -
The Medical Journal of Malaysia Jul 2022Adolescence is when an individual undergoes development and growth. Many studies suggest variations in the number and size of blood cells during this period in various...
BACKGROUND
Adolescence is when an individual undergoes development and growth. Many studies suggest variations in the number and size of blood cells during this period in various individuals. The full blood count (FBC) is often the starting point of medical investigations, which help diagnose a wide range of illnesses, infections, and diseases. This study aimed to report the mean FBC values and compare them by gender and ethnicity, using blood results from the thalassemia screening programme in Seremban District, Malaysia.
MATERIALS AND METHODS
This cross-sectional study used secondary data from the thalassemia screening programme on Form 4 students aged 15-16 years from January 2018 to October 2018 by the Seremban District Health Office, Malaysia. These students participated in the thalassemia screening programme in which their blood samples were taken for FBC analysis. The data were extracted for this study.
RESULTS
There were statistically significant gender-based differences for total white blood cell (WBC) count, neutrophils, lymphocytes, mixed WBC, and platelets. It was also observed that ethnic-specific differences were statistically significant for RBC count, platelets, platelet distribution width and mean platelet volume.
CONCLUSION
This study was able to report the mean FBC values among Malaysian adolescents with respect to their gender and ethnicity, of which there is a lack of published data.
Topics: Adolescent; Blood Cell Count; Cross-Sectional Studies; Ethnicity; Humans; Leukocyte Count; Malaysia; Thalassemia
PubMed: 35902932
DOI: No ID Found -
Journal of Dairy Science Apr 2021The aim of this study was to investigate the associations between differential somatic cell count (DSCC) and milk quality and udder health traits, and for the first...
The aim of this study was to investigate the associations between differential somatic cell count (DSCC) and milk quality and udder health traits, and for the first time, between DSCC and milk coagulation properties and cheesemaking traits in a population of 1,264 Holstein cows reared in northern Italy. Differential somatic cell count represents the combined proportions of polymorphonuclear neutrophils plus lymphocytes (PMN-LYM) in the total somatic cell count (SCC), with macrophages (MAC) making up the remaining proportion. The milk traits investigated in this study were milk yield (MY), 8 traits related to milk composition and quality (fat, protein, casein, casein index, lactose, urea, pH, and milk conductivity), 9 milk coagulation traits [3 milk coagulation properties (MCP) and 6 curd firming (CF) traits], 7 cheesemaking traits, 3 cheese yield (CY) traits, and 4 milk nutrient recovery in the curd (REC) traits. A linear mixed model was fitted to explore the associations between SCS combined with DSCC and the aforementioned milk traits. An additional model was run, which included DSCC expressed as the PMN-LYM and MAC counts, obtained by multiplying the percentage of PMN-LYM and MAC by SCC in the milk for each cow in the data set. The unfavorable association between SCS and milk quality and technological traits was confirmed. Increased DSCC was instead associated with a linear increase in MY, casein index, and lactose proportion and a linear decrease in milk fat and milk conductivity. Accordingly, DSCC was favorably associated with all MCP and CF traits (with the exception of the time needed to achieve maximum, CF), particularly with rennet coagulation time, and it always displayed linear relationships. Differential somatic cell count was also positively associated with the recovery of milk nutrients in the curd (protein, fat, and energy), which increased linearly with increasing DSCC. The PMN-LYM count was rarely associated with milk traits, even though the pattern observed confirmed the results obtained when both SCS and DSCC were included in the model. The MAC count, however, showed the opposite pattern: MY, casein index, and lactose percentage decreased and milk conductivity increased with an increasing MAC count. No significant association was found between PMN-LYM count and MCP, CF, CY, and REC traits, whereas MAC count was unfavorably associated with MCP, CF traits, some CY traits, and all REC traits. Our results showed that the combined information derived from SCS and DSCC might be useful to monitor milk quality and cheesemaking-related traits.
Topics: Animals; Caseins; Cattle; Cell Count; Cheese; Female; Italy; Milk
PubMed: 33612239
DOI: 10.3168/jds.2020-19084 -
Journal of Dairy Science Sep 2021Bovine viral diarrhea virus (BVDV) infection has a major effect on the health of cows and consequently on herd performance. Many countries have implemented control or...
The effect of new bovine viral diarrhea virus introduction on somatic cell count, calving interval, culling, and calf mortality of dairy herds in the Dutch bovine viral diarrhea virus-free program.
Bovine viral diarrhea virus (BVDV) infection has a major effect on the health of cows and consequently on herd performance. Many countries have implemented control or eradication programs to mitigate BVDV infection and its negative effects. These negative effects of BVDV infection on dairy herds are well documented, but there is much less information about the effects of new introduction of BVDV on dairy herds already participating in a BVDV control program. The objective of our study was to investigate the effect of a new BVDV introduction in BVDV-free herds participating in the Dutch BVDV-free program on herd performance. Longitudinal herd-level surveillance data were combined with herd information data to create 4 unique data sets, including a monthly test-day somatic cell count (SCC) data set, annual calving interval (CIV) and culling risk (CR) data sets, and a quarterly calf mortality rate (CMR) data set. Each database contained 2 types of herds: herds that remained BVDV free during the whole study period (defined as free herds), and herds that lost their BVDV-free status during the study period (defined as breakdown herds). The date of losing the BVDV-free status was defined as breakdown date. To compare breakdown herds with free herds, a random breakdown date was artificially generated for free herds by simple random sampling from the distribution of the breakdown month of the breakdown herds. The SCC and CIV before and after a new introduction of BVDV were compared through linear mixed-effects models with a Gaussian distribution, and the CR and CMR were modeled using a negative binomial distribution in generalized linear mixed-effects models. The explanatory variables for all models included herd type, BVDV status, year, and a random herd effect. Herd size was included as an explanatory variable in the SCC, CIV, and CMR model. Season was included as an explanatory variable in the SCC and CMR model. Results showed that free herds have lower SCC, CR, CMR, and shorter CIV than the breakdown herds. Within the breakdown herds, the new BVDV introduction affected the SCC and CMR. In the year after BVDV introduction, the SCC was higher than that in the year before BVDV introduction, with a factor of 1.011 [2.5th to 97.5th percentile (95% PCTL): 1.002, 1.020]. Compared with the year before BVDV breakdown, the CMR in the year of breakdown and the year after breakdown was higher, with factors of 1.170 (95% PCTL: 1.120; 1.218) and 1.096 (95% PCTL: 1.048; 1.153), respectively. This study reveals that a new introduction of BVDV had a negative but on average relatively small effect on herd performance in herds participating in a BVDV control program.
Topics: Animals; Bovine Virus Diarrhea-Mucosal Disease; Cattle; Cattle Diseases; Cell Count; Diarrhea; Diarrhea Virus 1, Bovine Viral; Diarrhea Viruses, Bovine Viral; Female
PubMed: 34147217
DOI: 10.3168/jds.2021-20216 -
Journal of Dairy Science Jul 2022Poor udder health status can have a detrimental effect on milk yield and reproductive performance, leading to reductions in the dairy farm profit. The objective of this...
Poor udder health status can have a detrimental effect on milk yield and reproductive performance, leading to reductions in the dairy farm profit. The objective of this retrospective longitudinal study was to assess the associations of somatic cell count (SCC) with daily milk yield and reproductive performance. A database with 1,930,376 lactations from 867 Argentinean grazing dairy herds records collected for 14 years was used. The association of the evolution of SCC (healthy vs. new case vs. cured vs. chronic; with 150,000 SCC/mL as threshold) and of the severity of SCC [mild (150,000--400,000 SCC/mL) vs. moderate (400,000-1,000,000 SCC/mL) vs. severe (>1,000,000 SCC/mL)] with the odds for conception were estimated. Finally, the associations of the linear score of SCC (LS-SCC) with daily milk yield were estimated depending on parity and milk production quartile. The odds ratios (CI 95%) for conception at first service were 0.921 (0.902-0.941), 0.866 (0.848-0.884), and 0.842 (0.826-0.859) for the new case, cured, and chronic cows compared with healthy cows, respectively. Also, the odds ratios (CI 95%) for conception were 0.902 (0.881-0.925), 0.837 (0.808-0.866) and 0.709 (0.683-0.736) for mild, moderate and severe cases compared with healthy cows, respectively. An increase of one point of LS-SCC was associated with decreases of 0.349, 0.539, and 0.676 kg in daily milk yield for first-, second-, and third-lactation cows, respectively. In conclusion, SCC is negatively associated with the risk for conception and with daily milk yield in grazing dairy cows. This negative relationship with conception is higher when SCC increase occurs after the service date and it is influenced by severity of mastitis, and in the case of milk yield, the negative association is influenced by parity, milk production quartile, and severity of mastitis.
Topics: Animals; Cattle; Cattle Diseases; Cell Count; Dairying; Female; Lactation; Longitudinal Studies; Mastitis, Bovine; Milk; Pregnancy; Retrospective Studies
PubMed: 35570038
DOI: 10.3168/jds.2021-21504 -
Genes Nov 2023The aim of this study was to establish and evaluate a structural equation model to infer causal relationships among environmental and genetic factors on udder health....
The aim of this study was to establish and evaluate a structural equation model to infer causal relationships among environmental and genetic factors on udder health. For this purpose, 537 Holstein Friesian cows were genotyped, and milk samples were analyzed for novel traits including differential somatic cell counts and specific mastitis pathogens. In the structural model, four latent variables (intramammary infection (IMI), production, time and genetics) were defined, which were explained using manifest measurable variables. The measurable variables included udder pathogens and somatic differential cell counts, milk composition, as well as significant SNP markers from previous genome-wide associations for major and minor pathogens. The housing system effect (i.e., compost-bedded pack barns versus cubicle barns) indicated a small influence on IMI with a path coefficient of -0.05. However, housing system significantly affected production (0.37), with ongoing causal effects on IMI (0.17). Thus, indirect associations between housing and udder health could be inferred via structural equation modeling. Furthermore, genotype by environment interactions on IMI can be represented, i.e., the detection of specific latent variables such as significant SNP markers only for specific housing systems. For the latent variable genetics, especially one SNP is of primary interest. This SNP is located in the gene, which plays a fundamental role in the MAPK1 signaling pathway. Other identified genes (e.g., and ) support results from previous studies, and this gene also contributes to mechanisms of the MAPK1 signaling pathway.
Topics: Animals; Female; Cattle; Humans; Latent Class Analysis; Mastitis, Bovine; Causality; Cell Count
PubMed: 38003045
DOI: 10.3390/genes14112102 -
Journal of Dairy Science Aug 2022Udder health in dairy herds is a very important issue given its implications for animal welfare and the production of high-quality milk. Somatic cell count (SCC) is the...
Udder health in dairy herds is a very important issue given its implications for animal welfare and the production of high-quality milk. Somatic cell count (SCC) is the most widely used means of assessing udder health status. However, differential somatic cell count (DSCC) has recently been proposed as a new and more effective means of evaluating intramammary infection dynamics. Differential SCC represents the combined percentage of polymorphonuclear neutrophils and lymphocytes (PMN-LYM) in the total SCC, with macrophages (MAC) accounting for the remaining proportion. The aim of this study was to evaluate the association between SCC and DSCC and the detailed milk protein profile in a population of 1,482 Holstein cows. A validated reversed-phase HPLC method was used to quantify 4 caseins (CN), namely α-CN, α-CN, κ-CN, and β-CN, and 3 whey protein fractions, namely β-lactoglobulin, α-lactalbumin, and lactoferrin, which were expressed both quantitatively (g/L) and qualitatively (as a percentage of the total milk nitrogen content, %N). A linear mixed model was fitted to explore the associations between somatic cell score (SCS) combined with DSCC and the protein fractions expressed quantitatively and qualitatively. We ran an additional model that included DSCC expressed as PMN-LYM and MAC counts, obtained by multiplying the percentages of PMN-LYM and MAC by SCC for each cow in the data set. When the protein fractions were expressed as grams per liter, SCS was significantly negatively associated with almost all the casein fractions and positively associated with the whey protein α-lactalbumin, while DSCC was significantly associated with α-CN, β-CN, and α-lactalbumin, but in the opposite direction to SCS. We observed the same pattern with the qualitative data (i.e., %N), confirming opposite effects of SCS and DSCC on milk protein fractions. The PMN-LYM count was only slightly associated with the traits of concern, although the pattern observed was the same as when both SCS and DSCC were included in the model. The MAC count, however, generally had a greater impact on many casein fractions, in particular decreasing both β-CN content (g/L) and proportion (%N), and exhibited the opposite pattern to the PMN-LYM count. Our results show that information obtained from both SCS and DSCC may be useful in assessing milk quality and protein fractions. They also demonstrate the potential of MAC count as a novel udder health trait.
Topics: Animals; Caseins; Cattle; Cell Count; Female; Lactalbumin; Milk Proteins; Whey Proteins
PubMed: 35840397
DOI: 10.3168/jds.2022-22071