Sensitivity of diagnosis of spontaneous bacterial peritonitis is higher with the automated cell count method

BACKGROUND Spontaneous bacterial peritonitis(SBP)is one of the most important complications of patients with liver cirrhosis entailing high morbidity and mortality.Making an accurate early diagnosis of this infection is key in the outcome of these patients.The current definition of SBP is based on studies performed more than 40 years ago using a manual technique to count the number of polymorphs in ascitic fluid(AF).There is a lack of data comparing the traditional cell count method with a current automated cell counter.Moreover,current international guidelines do not mention the type of cell count method to be employed and around half of the centers still rely on the traditional manual method.AIM To compare the accuracy of polymorph count on AF to diagnose SBP between the traditional manual cell count method and a modern automated cell counter against SBP cases fulfilling gold standard criteria:Positive AF culture and signs/symptoms of peritonitis.METHODS Retrospective analysis including two cohorts:Cross-sectional(cohort 1)and case-control(cohort 2),of patients with decompensated cirrhosis and ascites.Both cell count methods were conducted simultaneously.Positive SBP cases had a pathogenic bacteria isolated on AF and signs/symptoms of peritonitis.RESULTS A total of 137 cases with 5 positive-SBP,and 85 cases with 33 positive-SBP were included in cohort 1 and 2,respectively.Positive-SBP cases had worse liver function in both cohorts.The automated method showed higher sensitivity than the manual cell count:80%vs 52%,P=0.02,in cohort 2.Both methods showed very good specificity(>95%).The best cutoff using the automated cell counter was polymorph≥0.2 cells×10^(9)/L(equivalent to 200 cells/mm^(3))in AF as it has the higher sensitivity keeping a good specificity.CONCLUSION The automated cell count method should be preferred over the manual method to diagnose SBP because of its higher sensitivity.SBP definition,using the automated method,as polymorph cell count≥0.2 cells×10^(9)/L in AF would need to be considered in patients admitted with decompensated cirrhosis.

Rapid Detection of Somatic Cell Count Based on Hybrid Variable Selection Method

Somatic cell count detection is the daily work of dairy farms to monitor the health of cows.The feasibility of applying near-infrared spectroscopy to somatic cell count detection was researched in this paper.Milk samples with different somatic cell counts were collected and preprocessing methods were studied.Variable selection algorithm based on hybrid strategy and modelling method based on ensemble learning were explored for somatic cell count detection.Detection model was used to diagnose subclinical mastitis and the results showed that near-infrared spectroscopy could be a tool to realize rapid detection of somatic cell count in milk.

Blood cell counts and nonalcoholic fatty liver disease: Evidence from Mendelian randomization analysis

BACKGROUND Previous research has highlighted correlations between blood cell counts and chronic liver disease.Nonetheless,the causal relationships remain unknown.AIM To evaluate the causal effect of blood cell traits on liver enzymes and nonalcoholic fatty liver disease(NAFLD)risk.METHODS Independent genetic variants strongly associated with blood cell traits were extracted from a genome-wide association study(GWAS)conducted by the Blood Cell Consortium.Summary-level data for liver enzymes were obtained from the United Kingdom Biobank.NAFLD data were obtained from a GWAS meta-analysis(8434 cases and 770180 controls,discovery dataset)and the Fingen GWAS(2275 cases and 372727 controls,replication dataset).This analysis was conducted using the inverse-variance weighted method,followed by various sensitivity analyses.RESULTS One SD increase in the genetically predicted haemoglobin concentration(HGB)was associated with aβof 0.0078(95%CI:0.0059-0.0096),0.0108(95%CI:0.0080-0.0136),0.0361(95%CI:0.0156-0.0567),and 0.0083(95%CI:00046-0.0121)for alkaline phosphatase(ALP),alanine aminotransferase(ALT),aspartate aminotransferase,and gammaglutamyl transferase,respectively.Genetically predicted haematocrit was associated with ALP(β=0.0078,95%CI:0.0052-0.0104)and ALT(β=0.0057,95%CI:0.0039-0.0075).Genetically determined HGB and the reticulocyte fraction of red blood cells increased the risk of NAFLD[odds ratio(OR)=1.199,95%CI:1.087-1.322]and(OR=1.157,95%CI:1.071-1.250).The results of the sensitivity analyses remained significant.CONCLUSION Novel causal blood cell traits related to liver enzymes and NAFLD development were revealed through Mendelian randomization analysis,which may facilitate the diagnosis and prevention of NAFLD.

Relationship of Somatic Cell Count with Milk Yield and Composition in Chinese Holstein Population

The objective of this study was to analyze the relationship of somatic cell count （SCC） with milk yield, fat and protein percentage, fat and protein yield using analysis of variance and correlation analysis in Chinese Holstein population. The 10 524 test-day records of 568 Chinese Holstein Cattle were obtained from 2 commercial herds in Xi＇an region of China during February 2002 to March 2009. Milk yield, fat percentage, fat and protein yield initially increased and then dropped down with parity, whereas protein percentage decreased and SCC increased. Analysis of variance showed highly significant effects of different subclasses SCC on milk yield and composition （P〈 0.01）. Compared with milk yield with SCC ≤ 200 000 cells mL-1, milk yield losses with SCC of 200 000-500 000 cells mL-1, 501000-1 000 000 cells mL-1, ≥ 1 000 000 cells mL-1 were 0.387, 0.961 and 2.351 kg, respectively. The highly significant negative correlation coefficient between somatic cell score （SCS） and milk and protein yield, milk yield and fat and protein percentage, protein percentage and fat yield were -0.084, -0.037, -0.061, -0.168, and -0.088, respectively （P〈 0.01）. The highly significant positive correlation coefficients between SCS and fat yield and fat and protein percentage, milk yield and fat and protein yield, fat percentage and protein percentage and fat yield, protein yield and protein percentage and fat yield were 0.041, 0.177, 0.105, 0.771, 0.865, 0.122, 0.568, 0.318, and 0.695, respectively （P〈 0.01）. There was no significant relationship between fat percentage and protein yield （P 〉 0.05）. The results of the present study first time provide the relevant base-line data for assessing milk production at Xi＇an region of China.

Accuracy of the automated cell counters for management of spontaneous bacterial peritonitis

AIM： To evaluate the accuracy of automated blood cell counters for ascitic polymorphonuclear （PMN） determination for： （1） diagnosis, （2） efficacy of the ongoing antibiotic therapy, and （3） resolution of spontaneous bacterial peritonitis （SBP）. METHODS： One hundred and twelve ascitic fluid samples were collected from 52 consecutive cirrhotic patients, 16 of them with SBP. The agreement between the manual and the automated method for PMN count was assessed. The sensitivity/specificity and the positive/negative predictive value of the automated blood cell counter were also calculated by considering the manual method as the ＂gold standard＂ RESULTS： The mean ＋ SD of the difference between manual and automated measurements was 7.8 4- 58 cells/ram3, while the limits of agreement were ＋124 cells/mm3 [95% confidence interval （CI）： ＋145 to ＋103] and -108 cells/mm3 （95% CI： -87 to -129）. The automated cell counter had a sensitivity of 100% and a specificity of 97.7% in diagnosing SBP, and a sensitivity of 91% and a specificity of 100% for the efficacy of the ongoing antibiotic therapy. The two methods showed a complete agreement for the resolution of infection. CONCLUSION： Automated cell counters not only have a good diagnostic accuracy, but are also very effectivein monitoring the antibiotic treatment in patients with SBP. Because of their quicker performance, they should replace the manual counting for PMN determination in the ascitic fluid of patients with SBP.

Normal Reference Value of Red Blood Cell Count of Chinese Presenile Men and Geographical Factors

This paper aims at providing a scientific basis for unifying the normal reference value standards of red blood cell count of Chinese presenile men. The paper, using microscopical counting method, studies the relationship between the normal reference values of 38,061 samples of red blood cell count of presenile men and eight geographical factors in 297 units in China. It is found that the correlation of geographical factors and the normal reference value of red blood cell count of presenile men is quite significant （F=303.00, P=-0.000）. By using the method of stepwise regression analysis, one regression equation is inferred. It is concluded that if geographical data are obtained in a certain area, the normal reference value of red blood cell count of presenile men in this area can be reckoned by using the regression analysis. Furthermore, according to the geographical factors, China can be divided into eight regions： Northeast China Region, North China Region, Shanxi-Shaanxi-Irmer Mongolia Region, Middle and Lower Reaches of the Changjiang River Region, Southeast China Region, Northwest China Region, Southwest China Region and Qinghai-Tibet Plateau Region.

Deep learning method for cell count from transmitted-light microscope

Automatic cell counting provides an effective tool for medical research and diagnosis.Currently,cell counting can be completed by transmitted-light microscope,however,it requires expert knowledge and the counting accuracy which is unsatisfied for overlapped cells.Further,the image-translation-based detection method has been proposed and the potential has been shown to accomplish cell counting from transmitted-light microscope,automatically and effectively.In this work,a new deep-learning(DL)-based two-stage detection method(cGAN-YOLO)is designed to further enhance the performance of cell counting,which is achieved by combining a DL-based fluorescent image translation model and a DL-based cell detection model.The various results show that cGAN-YOLO can effectively detect and count some different types of cells from the acquired transmitted-light microscope images.Compared with the previously reported YOLO-based one-stage detection method,high recognition accuracy(RA)is achieved by the cGAN-YOLO method,with an improvement of 29.80%.Furthermore,we can also observe that cGAN-YOLO obtains an improvement of 12.11%in RA compared with the previously reported image-translation-based detection method.In a word,cGAN-YOLO makes it possible to implement cell counting directly from the experimental acquired transmitted-light microscopy images with high flexibility and performance,which extends the applicability in clinical research.

Correlation between Abdominal Ultrasonographic Findings and CD4 Cell Count in Adult Patients with HIV/AIDS in Jos, Nigeria

Acquired Immunodeficiency Syndrome (AIDS) is caused by Human Immunodeficiency Viruses (HIV) resulting in progressive destruction of cell mediated immunity. The abdominal manifestations of AIDS are related to the level of CD+4 cells count as well as viral load. Abdominal ultrasound examination is easy to perform, non-invasive, inexpensive, readily available and reproducible investigation which provides valuable information about abdominal findings in AIDS. The objective of the study was to evaluate abdominal ultrasound findings in adult HIV/AIDS patients in Jos, Plateau State, Nigeria and correlate these findings with the patients’ CD+4 counts. A cross-sectional study of abdominal ultrasound findings of adult patients with HIV/AIDS was conducted over a period of six months. The abdominal ultrasound findings and CD+4 counts were studied. Two hundred (40%) of the patients had normal abdominal ultrasound, while 60% (300) had various abnormalities. The common abnormalities included increased liver parenchymal echogenicity in 25.0%, hepatomegaly in 23.4%, splenomegaly in 6.6%, increased splenic echogenicity in 6.2% and thickened gallbladder wall in 12.6%, elevated renal parenchymal echogenicity in 6.4%, enlarged kidneys in 2.6%, lymphadenopathy in 6.0%, and ascites in 2.4%. Pelvic abscess was the least pathology in 0.2%. Most of the findings did not correlate with the patients’ CD+4?count except for lymphadenopathy and ascites. Although abdominal ultrasound examination is invaluable in the management of these patients, however, it has not shown to be useful in predicting the patients’ immune status.

High plasma fibrinogen concentration and platelet count unfavorably impact survival in non–small cell lung cancer patients with brain metastases

High expression of fibrinogen and platelets are often observed in non–small cell lung cancer(NSCLC) patients with local regional or distant metastasis. However, the role of these factors remains unclear. The aims of this study were to evaluate the prognostic significance of plasma fibrinogen concentration and platelet count, as well as to determine the overall survival of NSCLC patients with brain metastases. A total of 275 NSCLC patients with brain metastasis were enrolled into this study. Univariate analysis showed that high plasma fibrinogen concentration was associated with age ≥ 65 years(P = 0.011), smoking status(P = 0.009), intracranial symptoms(P = 0.022), clinical T category(P = 0.010), clinical N category(P = 0.003), increased partial thromboplastin time(P < 0.001), and platelet count(P < 0.001). Patients with low plasma fibrinogen concentration demonstrated longer overall survival compared with those with high plasma fibrinogen concentration(median, 17.3 months versus 11.1 months; P ≤ 0.001). A similar result was observed for platelet counts(median, 16.3 months versus 11.4 months; P = 0.004). Multivariate analysis showed that both plasma fibrinogen concentration and platelet count were independent prognostic factors for NSCLC with brain metastases(R2 = 1.698, P < 0.001 and R2 = 1.699, P < 0.001, respectively). Our results suggest that high plasma fibrinogen concentration and platelet count indicate poor prognosis for NSCLC patients with brain metastases. Thus, these two biomarkers might be independent prognostic predictors for this subgroup of NSCLC patients.

Bayesian Joint Modelling of Survival Time and Longitudinal CD4 Cell Counts Using Accelerated Failure Time and Generalized Error Distributions

Survival of HIV/AIDS patients is crucially dependent on comprehensive and targeted medical interventions such as supply of antiretroviral therapy and monitoring disease progression with CD4 T-cell counts. Statistical modelling approaches are helpful towards this goal. This study aims at developing Bayesian joint models with assumed generalized error distribution (GED) for the longitudinal CD4 data and two accelerated failure time distributions, Lognormal and loglogistic, for the survival time of HIV/AIDS patients. Data are obtained from patients under antiretroviral therapy follow-up at Shashemene referral hospital during January 2006-January 2012 and at Bale Robe general hospital during January 2008-March 2015. The Bayesian joint models are defined through latent variables and association parameters and with specified non-informative prior distributions for the model parameters. Simulations are conducted using Gibbs sampler algorithm implemented in the WinBUGS software. The results of the analyses of the two different data sets show that distributions of measurement errors of the longitudinal CD4 variable follow the generalized error distribution with fatter tails than the normal distribution. The Bayesian joint GED loglogistic models fit better to the data sets compared to the lognormal cases. Findings reveal that patients’ health can be improved over time. Compared to the males, female patients gain more CD4 counts. Survival time of a patient is negatively affected by TB infection. Moreover, increase in number of opportunistic infection implies decline of CD4 counts. Patients’ age negatively affects the disease marker with no effects on survival time. Improving weight may improve survival time of patients. Bayesian joint models with GED and AFT distributions are found to be useful in modelling the longitudinal and survival processes. Thus we recommend the generalized error distributions for measurement errors of the longitudinal data under the Bayesian joint modelling. Further studies may investigate the models with various types of shared random effects and more covariates with predictions.

Automatic counting of microglial cell activation and its applications

Glaucoma is a multifactorial optic neuropathy characterized by the damage and death of the retinal ganglion cells.This disease results in vision loss and blindness.Any vision loss resulting from the disease cannot be restored and nowadays there is no available cure for glaucoma; however an early detection and treatment,could offer neuronal protection and avoid later serious damages to the visual function.A full understanding of the etiology of the disease will still require the contribution of many scientific efforts.Glial activation has been observed in glaucoma,being microglial proliferation a hallmark in this neurodegenerative disease.A typical project studying these cellular changes involved in glaucoma often needs thousands of images- from several animals- covering different layers and regions of the retina.The gold standard to evaluate them is the manual count.This method requires a large amount of time from specialized personnel.It is a tedious process and prone to human error.We present here a new method to count microglial cells by using a computer algorithm.It counts in one hour the same number of images that a researcher counts in four weeks,with no loss of reliability.

EFFICACY OF IFOSFAMIDE AND VP-16 (ETOPOSIDE) IN PATIENTS WITH SMALL CELL LUNG CANCER AND THE CORRELATION BETWEEN MICROVESSEL COUNT ON CHEMOSENSITIVITY

Objective： To evaluate the efficacy of ifosfamide and etoposide （VP-16） in patients with small cell lung cancer （SCLC）, and investigate the correlation between microvessel count （MVC） in tumor and chemotherapeutic sensitivity. Methods： Forty-one consecutive cases of SCLC received chemotherapy of ifosfamide plus VP-16, and underwent investigation retrospectively. Immunohistochemistry using anti-human blood type H monoclonal antibody was conducted and MVC was recorded under light microscope. Results： There were 27 limited-disease and 14 extensive-disease patients. The overall response rate was 92.7% （38/41） with 28 cases （68.3%） of complete response （CR）, 10 （24.4%） with partial response （PR）, 3 （7.3%） with progressive disease （PD）. The 1-, 2-, 3-, and 5-year survival rates were 68.3% （28/41）, 48.3% （20/41）, 23.7% （9/38） and 11.1% （3/27）, respectively, with the median survival of 26.8 months. The principal toxicities were grade 3-4 neutropenia in 8 cases （19.5%）, grade 3-4 thrombocytopenia in 6 cases （14.6%）, mild liver toxicity in 7 cases （17.0%） and mild renal function damage in 4 cases （9.8%）. The mesenchymal vasculature was clearly visualized, with the mean value of 34.7 under each high microscopic power field. Of SCLC with more MVC （n=26）, CR accounted for 84.6%; while in cancers with less MVC （n=l 5）, CR took up 40.0%, with significant difference （P〈0.05）. Conclusion： Administrating ifosfamide and VP-16 is in accordance with the biological features of SCLC and results in beneficial results as well as acceptable side effects. The MVC is positively correlated with the chemotherapeutic sensitivity, and serves as a vital factor contributing to chemosensitivity.

Evaluation of proliferation kinetics in large intestinal neoplasms:Comparative study on the expression of proliferating cell nuclear antigen and AgNOR counting

Expression of proliferating cell nuclear antigen (PCNA) in human colorectal lesions was studied immunohistologically and compared with the results of silver stained nucleolar organized regions (AgNOR)counting for evaluating the changes of proliferative kinetics in adenoma-carcinoma sequence of the large intestine.Ninety-six formalin-fixed paraffin-embedded specimens were used, which consisted of 21 normal colon mucosa,23 adenocarcinomas and 52 adenomas (34 cases with mild atypia, 12 morderate and 6 severe). Three types of PCNA distribution pattern were identified. 73. 9% normal mucosa was type A pattern. Type C pattern was characteristic of adenocarcinoma, and adenoma was of type B or C pattern. Labeling index (LI) of PCNA was an important parameter to evaluate the proliferation activity. In normal mucosa, LI of PCNA was 0. 34±0. 10, while in malignant lesions, it was 0. 71±0. 09. Furthermore, the LI had a tendency to elevate with the degree of atypia in adenoma from 0. 52±0. 10 in mild atypia to 0. 68±0. 07 in severe atypia. The pattern of AgNOR counting changes, which were 1. 97±0. 36 and 4. 16±1. 24 in the normal mucosa and malignant mucosa respectively, was found to be similar to Ll changes of the PCNA in different lesions of the same section. A good correlation was found between the mean number of AgNOR per nucleus and the LI of PCNA in 23 adenocarcinomas (r=0. 59, P <0. 05). These results suggested that proliferation kinetics could be comprehensively evaluated by combining immunohistological staining for PCNA and a simple silver staining for NOR, which would be advantageous for the diagnosis of colorectal lesions and for evaluating the degree of histopathological atypia of adenomas.

Automatic counting of retinal ganglion cells in the entire mouse retina based on improved YOLOv5

Glaucoma is characterized by the progressive loss of retinal ganglion cells (RGCs),although the pathogenic mechanism remains largely unknown.To study the mechanism and assess RGC degradation,mouse models are often used to simulate human glaucoma and specific markers are used to label and quantify RGCs.However,manually counting RGCs is time-consuming and prone to distortion due to subjective bias.Furthermore,semi-automated counting methods can produce significant differences due to different parameters,thereby failing objective evaluation.Here,to improve counting accuracy and efficiency,we developed an automated algorithm based on the improved YOLOv5 model,which uses five channels instead of one,with a squeeze-and-excitation block added.The complete number of RGCs in an intact mouse retina was obtained by dividing the retina into small overlapping areas and counting,and then merging the divided areas using a non-maximum suppression algorithm.The automated quantification results showed very strong correlation (mean Pearson correlation coefficient of 0.993) with manual counting.Importantly,the model achieved an average precision of 0.981.Furthermore,the graphics processing unit (GPU) calculation time for each retina was less than 1 min.The developed software has been uploaded online as a free and convenient tool for studies using mouse models of glaucoma,which should help elucidate disease pathogenesis and potential therapeutics.

Synovial White Cell Count in the Diagnosis of Septic Arthritis: Are Current Diagnostic Practices Appropriate?

Introduction & aims: Septic arthritis is an emergency, potentially causing irreversible joint destruction and disability. Synovial WCC and polymorphonuclear cell percentage are the best predictors of septic arthritis likelihood. Yet, synovial white cell and differential count are not routinely assessed. We aim to investigate the incidence of failure to perform these tests, and to develop correct synovial fluid analysis practices. Method: This is a retrospective analysis of native joints having undergone arthrocentesis for suspicion of septic arthritis at Box Hill Hospital (BHH) during September 2011 and September 2013 inclusive. Recruitment was from the Eastern Health Decision Support Service (DSS), a database compiled from all systems within Eastern Health, of which BHH is a member. The study was limited to large joints, including hip, knee and shoulder. All prosthetic joints were excluded from the patient population. All patient histories were examined for suspicion of septic arthritis and subsequent arthrocentesis. Pathology records were accessed to determine incidence of cell count and differential. Results: One hundred and thirty-six cases of joint aspirations were identified within the time frame, of which sixty-seven fitted our criteria for evaluation. All but two cases were delivered using the DSS, which was limited to data compiled only until June 2013. The two remaining cases were identified with a manual search of the radiology and pathology databases from June to September 2013. 22 of the 67 joint aspirates studied did not have a cell count carried out. Four of these 22 cases had a diagnosis of septic arthritis. In five aspirates, there was a failure to confirm a definite diagnosis and they were thus conservatively treated as a septic joint. The remaining acute joints in which no cell count was done were gout (7 cases), pseudogout (5 cases) and rheumatoid arthritis (1 case). Cell counts were not routinely detected for a variety of reasons. Eleven aspirates were deemed too viscous, and in eight cases the sample had clotted prior to pathologist assessment. Two cases had insufficient volume, and one sample was too bloodstained to calculate a cell count and differential;likely due to traumatic aspiration. Conclusions: 33% of acute monoarthritis’ evaluated over the study period failed to have a synovial fluid WCC and differential. This may be due to inadequate samples, or lack of appropriate collection tube. Better education is required for appropriate collection and test requesting wherein a diagnosis of septic arthritis is in question.

Sustained heavy ethanol drinking affects CD4⁺cell counts in HIV-infected patients on stavudine (d4T), lamivudine (3TC) and nevirapine (NVP) treatment regimen during 9 months follow-up period

Sustained heavy ethanol drinking is a common problem globally and ethanol is one of the most abused drugs among individuals of different socio-economic status including the HIV-infected patients on antiretroviral drugs. Ethanol is reward drug and a CNS depressant especially at high doses. The study determined the effect of sustained heavy ethanol drinking by HIV-infected patients on d4T/3TC/NVP regimen on CD4+ cell counts in Uganda using WHO AUDIT tool and chronic alcohol-use biomarkers. A case control study using repeated measures design with serial measurements model was used. The patients on stavudine (d4T) 30 mg, lamivudine (3TC) 150 mg and nevirapine (NVP) 200 mg and chronic alcohol use were recruited. A total of 41 patients (20 in alcohol group and 21 in control group) were screened for chronic alcohol use by WHO AUDIT tool and chronic alcohol use biomarkers. They were followed up for 9 months with blood sampling done at 3 months intervals. CD4+ cell count was determined using Facscalibur Flow Cytometer system. Results were then sorted by alcohol-use biomarkers (GGT, MCV and AST/ ALT ratio). Data were analysed using SAS 2003 version 9.1 statistical package with repeated measures fixed model and the means were compared using student t-test. The mean CD4+ cell counts in all the groups were lower than the reference ranges at baseline and gradually increased at 3, 6 and 9 months of follow-up. The mean CD4+ cell counts were higher in the control group as compared to the chronic alcohol use group in both WHO AUDIT tool group and chronic alcohol-use biomarkers group though there was no significant difference (p > 0.05). Chronic alcohol use slightly lowers CD4+ cell count in HIV-infected patients on d4T/3TC/NVP treatment regimen.

Usefulness of white blood cell count to mean platelet volume ratio for predicting long-term prognosis after primary percutaneous coronary intervention in patients with acute coronary syndrome

Background and Objective The white blood cell count to mean platelet volume ratio(WMR)has recently been described as a predictor of cardiovascular events in patients who undergo percutaneous coronary intervention(PCI).The aim of this study was to investigate the usefulness of admission WMR in predicting outcomes in patients with acute coronary syndrome(ACS).

Cell counting for in vivo flow cytometry signals with baseline drift

In biomedical research fields,the in vio Aow cytometry(IVFC)is a widely used technology which is able to monitor target cells dynamically in living animals.Although the setup of IVFC system has been well established,baseline drift is still a challenge in the process of quantifying circulating cells.Previous methods,i.e.,the dynamic peak picking method,counted cells by setting a static threshold without considering the baseline drift,leading to an inaccurate cell quantification.Here,we developed a method of cell counting for IVFC data with baseline drift by interpolation fitting,automatic segmentation and wavelet-based denoising.We demonstrated its performance for IVFC signals with three types of representative baseline drift.Compared with non-baseline correction methods,this method showed a higher sensitivity and specificity,as well as a better result in the Pearson's correlation coefficient and the mean-squared error(MSE).

Udder Health Status of First Parity Dairy Cows in Early-Lactation Based on Somatic Cell Count Categories

The main aim of this study was to investigate the prevalence of intramammary infection (IMI) in early-lactation of primiparous cows using milk recording cow composite somatic cell count (CSCC) categories (combining the first 2 milk recording results after calving). Another aim was to evaluate the milk urea (MU) content as a potential supplementary indicator to SCC or CSCC for the identification of IMI in primiparous cows after calving. This retrospective observational study was conducted on records of test-day of primiparous cows over a period of 6 years (January 2016 to December 2021. The SCC data for 158 Holstein Friesian primiparous cows, with their first milk recording 5 to 35 days after calving and their second milk recording 28 to 56 days in milk (DIM), were identified. Each primiparous cow was assigned a CSCC category (low-low, low-high, high-low or high-high) based on the CSCC at the first 2 milking recordings using the following cut-offs: ≤150,000 cells/ml (low), >150,000 cells/ml (high). The association between CSCC categories and MV content was analyzed using correlation models. At the first milk recording, a proportion of 63.29% was in the low SCC category, and the rest (36.71%) was in the high SCC category. At the second milk recording, a proportion of primiparous cows in CSCC categories was 59.49%, 3.80%, 27.85% and 8.86% in low-low, low-high, high-low and high-high, respectively. At the second milk recording, a proportion of 12.66% of primiparous cows was in the high CSCC category and a proportion of 87.34% of primiparous cows was in the low CSCC category, indicating a poor and a good udder health, respectively. The association of SCC with MU content in low and in high SCC categories at the first milk recording was positive and moderate (+0.49) and negative and strong (-0.97), respectively. The association of CSCC categories with MU contents at the second milk recording was inconclusive. We concluded that CSCC categories may be a useful tool for identifying success and problems regarding the udder health of primiparous cows in early lactation.

Factors Associated with Sample Rejection for CD4+/CD8+ T Cell Count Analyses at the Kenyatta National Hospital Comprehensive Care Center Laboratory, Kenya

Background: The appropriate time to initiate antiretroviral therapy (ART) in HIV/AIDS patients is determined by measurement of CD4+/CD8+ T cell count. The CD4/CD8+ T cell count is also useful, together with viral load, in monitoring disease progression and effectiveness treatment regimens. Several factors may contribute to sample rejection during the CD4+/CD8+ T cells count, resulting in negative effects on patient management. Objective: Evaluate the causes for CD4+CD8+ T cell count sample rejection at the Kenyatta National Hospital Comprehensive Care Center Laboratory. Method: A retrospective cross-sectional study was conducted between 2018 and 2020. Data was obtained from the “rejected samples” for PartecR FlowCyp flow cytometry file. Designed data collection sheet was used for data capture. A total of 3972 samples were submitted for CD4+/CD8+ T cell count during the study period. Causes for sample rejection were numbered 1 to 12, each representing a reason for sample rejection. Number 1 was sub-categorized into clotted, hemolyzed, short-draw and lipemic. Data was analyzed using excel, and presented using tables, graphs and pie charts. Approval to conduct the study was obtained from KNH/UoN ERC. Results: In the study period, 81/3972 (2.0%) samples were rejected. Samples submitted more than 48 hours after collection were mostly rejected. Other factors included improper collection technique, delayed testing, patient identification error and incorrect use of vacutainer. A combination of clotted samples, specimen submission more than 48 hours caused the most frequent sample rejection, followed with combination of specimen submission more than 48 hours, delayed testing and delayed specimen processing. Together, clotted samples, incorrect vacutainer and poor specimen label caused the least sample rejection. Conclusion: Sample rejection rate for CD4/CD8+ T cell count was relatively low, and multiple factors contributed to rejection. However, improved quality assurance will enable more benefit to patients who seek this test in the laboratory.