Pretreatment red blood cell distribution width as a predictive marker for postoperative complications after laparoscopic pancreatoduodenectomy

BACKGROUND Red blood cell distribution width(RDW)is associated with the development and progression of various diseases.AIM To explore the association between pretreatment RDW and short-term outcomes after laparoscopic pancreatoduodenectomy(LPD).METHODS A total of 804 consecutive patients who underwent LPD at our hospital between March 2017 and November 2021 were retrospectively analyzed.Correlations between pretreatment RDW and clinicopathological characteristics and short-term outcomes were investigated.RESULTS Patients with higher pretreatment RDW were older,had higher Eastern Cooperative Oncology Group scores and were associated with poorer short-term outcomes than those with normal RDW.High pretreatment RDW was an independent risk factor for postoperative complications(POCs)(hazard ratio=2.973,95%confidence interval:2.032-4.350,P<0.001)and severe POCs of grade IIIa or higher(hazard ratio=3.138,95%confidence interval:2.042-4.824,P<0.001)based on the Clavien-Dino classification system.Subgroup analysis showed that high pretreatment RDW was an independent risk factor for Clavien-Dino classi-fication grade IIIb or higher POCs,a comprehensive complication index score≥26.2,severe postoperative pancreatic fistula,severe bile leakage and severe hemorrhage.High pretreatment RDW was positively associated with the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio and was negatively associated with albumin and the prognostic nutritional index.CONCLUSION Pretreatment RDW was a special parameter for patients who underwent LPD.It was associated with malnutrition,severe inflammatory status and poorer short-term outcomes.RDW could be a surrogate marker for nutritional and inflammatory status in identifying patients who were at high risk of developing POCs after LPD.

Data augmentation of ultrasound imaging for non-invasive white blood cell in vitro peritoneal dialysis

The limited amount of data in the healthcare domain and the necessity of training samples for increased performance of deep learning models is a recurrent challenge,especially in medical imaging.Newborn Solutions aims to enhance its non-invasive white blood cell counting device,Neosonics,by creating synthetic in vitro ultrasound images to facilitate a more efficient image generation process.This study addresses the data scarcity issue by designing and evaluating a continuous scalar conditional Generative Adversarial Network(GAN)to augment in vitro peritoneal dialysis ultrasound images,increasing both the volume and variability of training samples.The developed GAN architecture incorporates novel design features:varying kernel sizes in the generator’s transposed convolutional layers and a latent intermediate space,projecting noise and condition values for enhanced image resolution and specificity.The experimental results show that the GAN successfully generated diverse images of high visual quality,closely resembling real ultrasound samples.While visual results were promising,the use of GAN-based data augmentation did not consistently improve the performance of an image regressor in distinguishing features specific to varied white blood cell concentrations.Ultimately,while this continuous scalar conditional GAN model made strides in generating realistic images,further work is needed to achieve consistent gains in regression tasks,aiming for robust model generalization.

NEW METHOD FOR WHITE BLOOD CELL DETECTION BASED ON RELEVANCE VECTOR MACHINE

A new method for the white blood cell （WBC） detection is presented based on the relevance vector machine （RVM）. Firstly,the sparse relevance vectors （RVs） are obtained while fitting the 1-D histogram by RVM. Then,the needed threshold value is directly selected from these limited RVs. Finally,the entire connective WBC regions are segmented from the original image. The method is used for the WBC detection. It reduces the interference induced by the illumination and the staining. It has advantages of the high computation efficiency and the no extra parameter setting. Experimental results demonstrate good performances of the method.

Effect of sodium nitroprusside on the microrheological properties of red blood cells in different media

Red blood cell(RBC)aggregation as well as their deformation significantly affects blood microrheology.These processes depend on various factors,one of which is concentration of the nitric oxide,one of the main signaling molecule in the bloodstream.The purpose of this study was to investigate the effect of nitric oxide on the microrheological properties of red blood cells(RBCs)in RBC samples of various media after the addition of nitric oxide donor sodium nitroprusside in vitro.Microrheological properties were measured using laser aggregometer and ektacytometer based on diffuse light scattering and diffraction of laser light on a suspension of RBCs,respectively.The study found that heparin-stabilized blood showed increased RBC aggregation and deformation with sodium nitroprusside concentrations of 100,and 200M,while EDTA-stabilized blood showed slightly decreased aggregation and unchanged deformation.With washed RBCs in dextran solution,the addition of sodium nitroprusside(in the concentrations of 100,and 200M)resulted in decreased aggregation and increased deformation.These-ndings aid in our understanding of nitric oxide's effect on RBC microrheological properties.

Admission white blood cell count predicts short-term clinical outcomes in patients with uncomplicated Stanford type B acute aortic dissection

Objectives Inflammation has been shown to be related with acute aortic dissection （AAD）. The present study aimed to evaluate the association of white blood cell counts （WI3Cc） on admission with both in-hospital and long-term all-cause mortality in patients with uncom- plicated Stanford type B AAD. Methods From 2008 to 2010, a total of 377 consecutive patients with uncomplicated type B AAD were enrolled and then followed up. Clinical data and WBCc on admission were collected. The primary end points were in-hospital death and long-term all-cause death. Results The in-hospital death rate was 4.2%, and the long-term all-cause mortality rate was 6.9% during a median follow-up of 18.9 months. WBCc on admission was identified as a risk factor for in-hospital death by univariate Cox regression analysis as both a continuous variable and a categorical variable using a cut off of 11.0 × 109 cell/L （all P 〈 0.05）. After adjusting for age, sex and other risk factors, elevated admission WBCc was still a significant predictor for in-hospital death as both a continuous variable [hazard ratio （HR）： 1.052, 95% CI： 1.024-1.336, P = 0.002] and a categorical variable using a cut off of 11.0 × 109 cell/L （HR： 2.056, 95% CI： 1.673-5.253, P = 0.034）. No relationship was observed between WBCc on admission and long-term all-cause death. Conclusions Our results indicate that elevated WBCc upon admission might be used as a predictor for increased risk of in-hospital death in uncomplicated type B AAD. There might be no predictive value of WBCc for the long-term survival of type B AAD.

Automated White Blood Cell Disease Recognition Using Lightweight Deep Learning

White blood cells(WBC)are immune system cells,which is why they are also known as immune cells.They protect the human body from a variety of dangerous diseases and outside invaders.The majority of WBCs come from red bone marrow,although some come from other important organs in the body.Because manual diagnosis of blood disorders is difficult,it is necessary to design a computerized technique.Researchers have introduced various automated strategies in recent years,but they still face several obstacles,such as imbalanced datasets,incorrect feature selection,and incorrect deep model selection.We proposed an automated deep learning approach for classifying white blood disorders in this paper.The data augmentation approach is initially used to increase the size of a dataset.Then,a Darknet-53 pre-trained deep learning model is used and finetuned according to the nature of the chosen dataset.On the fine-tuned model,transfer learning is used,and features engineering is done on the global average pooling layer.The retrieved characteristics are subsequently improved with a specified number of iterations using a hybrid reformed binary grey wolf optimization technique.Following that,machine learning classifiers are used to classify the selected best features for final classification.The experiment was carried out using a dataset of increased blood diseases imaging and resulted in an improved accuracy of over 99%.

Hypomethylation of glycine dehydrogenase promoter in peripheral blood mononuclear cells is a new diagnostic marker of hepatitis B virus-associated hepatocellular carcinoma

Background: Glycine dehydrogenase(GLDC) plays an important role in the initiation and proliferation of several human cancers. In this study, we aimed to detect the methylation status of GLDC promoter and its diagnostic value for hepatitis B virus-associated hepatocellular carcinoma(HBV-HCC). Methods: We enrolled 197 patients, 111 with HBV-HCC, 51 with chronic hepatitis B(CHB), and 35 healthy controls(HCs). The methylation status of GLDC promoter in peripheral mononuclear cells(PBMCs) was identified by methylation specific polymerase chain reaction(MSP). The mRNA expression was examined using real-time quantitative polymerase chain reaction(q PCR). Results: The methylation frequency of the GLDC promoter was significantly lower in HBV-HCC patients(27.0%) compared to that in CHB patients(68.6%) and HCs(74.3%)( P < 0.001). The methylated group had lower alanine aminotransferase level( P = 0.035) and lower rates of tumor node metastasis(TNM) Ⅲ/Ⅳ( P = 0.043) and T3/T4( P = 0.026). TNM stage was identified to be an independent factor for GLDC promoter methylation. GLDC mRNA levels in CHB patients and HCs were significantly lower than those in HBV-HCC patients( P = 0.022 and P < 0.001, respectively). GLDC mRNA levels were significantly higher in HBV-HCC patients with unmethylated GLDC promoters than those with methylated GLDC promoters( P = 0.003). The diagnostic accuracy of alpha-fetoprotein(AFP) combined with GLDC promoter methylation for HBV-HCC was improved compared with that of AFP alone(AUC: 0.782 vs. 0.630, P < 0.001). In addition, GLDC promoter methylation was an independent predictor for overall survival of HBV-HCC patients( P = 0.038). Conclusions: The methylation frequency of GLDC promoter was lower in PBMCs from HBV-HCC patients than that from patients with CHB and HCs. The combination of AFP and GLDC promoter hypomethylation significantly improved the diagnostic accuracy of HBV-HCC.

Using Optical Tweezers to Study the Friction of the Red Blood Cells

In the last two decades the study of red blood cell elasticity using optical tweezers has known a rise appearing in the scientific research with regard to the various works carried out. Despite the various work done, no study has been done so far to study the influence of friction on the red blood cell indentation response using optical tweezers. In this study, we have developed a new approach to determine the coefficient of friction as well as the frictional forces of the red blood cell. This approach therefore allowed us to simultaneously carry out the indentation and traction test, which allowed us to extract the interfacial properties of the microbead red blood cell couple, among other things, the friction coefficient. This property would be extremely important to investigate the survival and mechanical features of cells, which will be of great physiological and pathological significance. But taking into account the hypothesis of friction as defined by the isotropic Coulomb law. The experiment performed for this purpose is the Brinell Hardness Test (DB).

Predictive value of red blood cell distribution width and hematocrit for short-term outcomes and prognosis in colorectal cancer patients undergoing radical surgery

BACKGROUND Previous studies have reported that low hematocrit levels indicate poor survival in patients with ovarian cancer and cervical cancer,the prognostic value of hematocrit for colorectal cancer(CRC)patients has not been determined.The prognostic value of red blood cell distribution width(RDW)for CRC patients was controversial.AIM To investigate the impact of RDW and hematocrit on the short-term outcomes and long-term prognosis of CRC patients who underwent radical surgery.METHODS Patients who were diagnosed with CRC and underwent radical CRC resection between January 2011 and January 2020 at a single clinical center were included.The short-term outcomes,overall survival(OS)and disease-free survival(DFS)were compared among the different groups.Cox analysis was also conducted to identify independent risk factors for OS and DFS.RESULTS There were 4258 CRC patients who underwent radical surgery included in our study.A total of 1573 patients were in the lower RDW group and 2685 patients were in the higher RDW group.There were 2166 and 2092 patients in the higher hematocrit group and lower hematocrit group,respectively.Patients in the higher RDW group had more intraoperative blood loss(P<0.01)and more overall complications(P<0.01)than did those in the lower RDW group.Similarly,patients in the lower hematocrit group had more intraoperative blood loss(P=0.012),longer hospital stay(P=0.016)and overall complications(P<0.01)than did those in the higher hematocrit group.The higher RDW group had a worse OS and DFS than did the lower RDW group for tumor node metastasis(TNM)stage I(OS,P<0.05;DFS,P=0.001)and stage II(OS,P=0.004;DFS,P=0.01)than the lower RDW group;the lower hematocrit group had worse OS and DFS for TNM stage II(OS,P<0.05;DFS,P=0.001)and stage III(OS,P=0.001;DFS,P=0.001)than did the higher hematocrit group.Preoperative hematocrit was an independent risk factor for OS[P=0.017,hazard ratio(HR)=1.256,95%confidence interval(CI):1.041-1.515]and DFS(P=0.035,HR=1.194,95%CI:1.013-1.408).CONCLUSION A higher preoperative RDW and lower hematocrit were associated with more postoperative complications.However,only hematocrit was an independent risk factor for OS and DFS in CRC patients who underwent radical surgery,while RDW was not.

Multifaceted roles of lymphatic and blood endothelial cells in the tumor microenvironment of hepatocellular carcinoma:A comprehensive review

The tumor microenvironment is a complex network of cells,extracellular matrix,and signaling molecules that plays a critical role in tumor progression and metastasis.Lymphatic and blood vessels are major routes for solid tumor metastasis and essential parts of tumor drainage conduits.However,recent studies have shown that lymphatic endothelial cells(LECs)and blood endothelial cells(BECs)also play multifaceted roles in the tumor microenvironment beyond their structural functions,particularly in hepatocellular carcinoma(HCC).This comprehensive review summarizes the diverse roles played by LECs and BECs in HCC,including their involvement in angiogenesis,immune modulation,lymphangiogenesis,and metastasis.By providing a detailed account of the complex interplay between LECs,BECs,and tumor cells,this review aims to shed light on future research directions regarding the immune regulatory function of LECs and potential therapeutic targets for HCC.

Application of neutrophil-lymphocyte ratio and red blood cell distribution width in diabetes mellitus complicated with heart failure

BACKGROUND Accumulating clinical evidence has shown that diabetes mellitus(DM)is a serious risk factor for cardiovascular disorders and an important factor for adverse cardiovascular events.AIM To explore the value of the combined determination of the neutrophil-lymphocyte ratio(NLR)and red blood cell distribution width(RDW)in the early diagnosis and prognosis evaluation of DM complicated with heart failure(HF).METHODS We retrospectively analyzed clinical data on 65 patients with type 2 DM(T2DM)complicated with HF(research group,Res)and 60 concurrent patients with uncomplicated T2DM(control group,Con)diagnosed at Zhejiang Provincial People’s Hospital between January 2019 and December 2021.The NLR and RDW values were determined and comparatively analyzed,and their levels in T2DM+HF patients with different cardiac function grades were recorded.The receiver operating characteristic(ROC)curves were plotted to determine the NLR and RDW values(alone and in combination)for the early diagnosis of HF.The correlation between NLR and RDW with the presence or absence of cardiac events was also investigated.RESULTS Higher NLR and RDW levels were identified in the Res vs the Con groups(P<0.05).The NLR and RDW increased gradually and synchronously with the deterioration of cardiac function in the Res group,with marked differences in their levels among patients with grade II,III,and IV HF(P<0.05).ROC curve analysis revealed that NLR combined with RDW detection had an area under the curve of 0.915,a sensitivity of 76.9%,and a specificity of 100%for the early diagnosis of HF.Furthermore,HF patients with cardiac events showed higher NLR and RDW values compared with HF patients without cardiac events.CONCLUSION NLR and RDW were useful laboratory indicators for the early diagnosis of DM complicated with HF,and their joint detection was beneficial for improving diagnostic efficiency.Additionally,NLR and RDW values were directly proportional to patient outcomes.

Clinical significance of peripheral blood immune cells in patients with gastric cancer after surgery

BACKGROUND Gastric cancer is one of the most common malignant tumors worldwide,and surgical resection is one of the main ways to treat gastric cancer.However,the immune status of postoperative patients is crucial for prognosis and survival,and immune cells play an important role in this process.Therefore,it is helpful to understand the immune status of postoperative patients by evaluating the levels of peripheral blood immune cells,especially total T cells(CD3+),helper T cells(CD3+CD4+),and suppressor T cells(CD3+CD8+),and its relationship to sur-vival.AIM To analyzed the immune cells in peripheral blood of patients with gastric cancer after surgery,detect the levels of total T cells,helper T cells and suppressor T cells.METHODS A total of 58 patients with gastric cancer who received surgical treatment were included in the retrospective study.Flow cytometry was used to detect the level of peripheral blood immune cells and analyze the correlation between total T cells,helper T cells and inhibitory T cells.To explore the relationship between these immune markers and patient survival.RESULTS The results showed that the levels of total T cells,helper T cells,and suppressor T cells changed in patients after gastric cancer surgery.There was a significant positive correlation between total T cells,helper T cells and suppressor T cells(r=0.35,P<0.01;r=0.56,P<0.01).However,there was a negative correlation between helper T cells and suppressor T cells(r=-0.63,P<0.01).Follow-up showed that the survival rate of patients in the high-level total T cell group was significantly higher than that in the low-level group(28.87±24.98 months vs 18.42±16.21 months).The survival curve shows that the curve of patients in the high-level group is shifted to the upper right,and that of the low-level group is shifted downward.There was no significant difference between the levels of helper T cells and suppressor T cells and patient survival time.CONCLUSION By detecting peripheral blood immune cells with flow cytometry,we can initially evaluate the immune status of patients after gastric cancer surgery and initially explore its relationship with patient survival.

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.

White Blood Cells Detection Using Spectral Tresholding

The study of the morphology of White Blood Cells (WBCs) further contributes to the clinical diagnosis of blood diseases. In this research paper, we come up with an image segmentation enhancement by combining Fourier Fast Transform on smear blood capture and classical thresholding. The Fast Fourier Transform (FFT) is a very powerful tool in image processing and it was used to segment and extract the WBCs. Our image processing method uses a Fast Fourier Transform combined with filtering and an Inverse Fast Fourier Transform for the extraction and visualization of the high frequency region of the image. In order to remove residual Red Blood Cells acting as noise in the expected result, a final thresholding step is added at the end of the processing. The results presented in this article report the tests performed using our mathematical implementation. Moreover, we were able to detect and differentiate the sub-families of WBCs.

A Novel Meta-Heuristic Optimization Algorithm in White Blood Cells Classification

Some human diseases are recognized through of each type of White Blood Cell(WBC)count,so detecting and classifying each type is important for human healthcare.The main aim of this paper is to propose a computer-aided WBCs utility analysis tool designed,developed,and evaluated to classify WBCs into five types namely neutrophils,eosinophils,lymphocytes,monocytes,and basophils.Using a computer-artificial model reduces resource and time consumption.Various pre-trained deep learning models have been used to extract features,including AlexNet,Visual Geometry Group(VGG),Residual Network(ResNet),which belong to different taxonomy types of deep learning architectures.Also,Binary Border Collie Optimization(BBCO)is introduced as an updated version of Border Collie Optimization(BCO)for feature reduction based on maximizing classification accuracy.The proposed computer aid diagnosis tool merges transfer deep learning ResNet101,BBCO feature reduction,and Support Vector Machine(SVM)classifier to forma hybridmodelResNet101-BBCO-SVM an accurate and fast model for classifying WBCs.As a result,the ResNet101-BBCO-SVM scores the best accuracy at 99.21%,compared to recent studies in the benchmark.The model showed that the addition of the BBCO algorithm increased the detection accuracy,and at the same time,decreased the classification time consumption.The effectiveness of the ResNet101-BBCO-SVM model has been demonstrated and beaten in reasonable ratios in recent literary studies and end-to-end transfer learning of pre-trained models.

Automated Artificial Intelligence Empowered White Blood Cells Classification Model

White blood cells (WBC) or leukocytes are a vital component ofthe blood which forms the immune system, which is accountable to fightforeign elements. The WBC images can be exposed to different data analysisapproaches which categorize different kinds of WBC. Conventionally, laboratorytests are carried out to determine the kind of WBC which is erroneousand time consuming. Recently, deep learning (DL) models can be employedfor automated investigation of WBC images in short duration. Therefore,this paper introduces an Aquila Optimizer with Transfer Learning basedAutomated White Blood Cells Classification (AOTL-WBCC) technique. Thepresented AOTL-WBCC model executes data normalization and data augmentationprocess (rotation and zooming) at the initial stage. In addition,the residual network (ResNet) approach was used for feature extraction inwhich the initial hyperparameter values of the ResNet model are tuned by theuse of AO algorithm. Finally, Bayesian neural network (BNN) classificationtechnique has been implied for the identification of WBC images into distinctclasses. The experimental validation of the AOTL-WBCC methodology isperformed with the help of Kaggle dataset. The experimental results foundthat the AOTL-WBCC model has outperformed other techniques which arebased on image processing and manual feature engineering approaches underdifferent dimensions.

The Impact of Blood Transfusion on the Efficiency of Stem Cell Transplants

Background: While blood product transfusion is essential for managing hematologic deficits in Allogenic Hematopoietic stem cell transplant (AHSCT) recipients, it has risks including infectious disease transmission, alloimmunization, and transfusion reactions. These risks have sparked an ongoing debate regarding the overall impact of transfusions on patient outcomes. Thus, this study aimed to evaluate the impact of Red Blood Cells (RBCs) and/or platelet transfusion on the infection incidence and overall survival in AHSCT patients. Methods: We performed a retrospective analysis of clinical and laboratory data of sixty adult patients with primary malignant hematological disorder who had undergone AHSCT. Participants’ data were categorized into two groups;Group 1 (low transfusion group) consisted of patients receiving 10 units. Quantitative data were expressed as mean ± SD. The t-test of significance and Chi-square (χ2) test were used, with p ≤ 0.05 considered significant. Result: A total of 60 patients’ data was included. In Group 1, out of 30 patients, 13 (43.33%) developed infections. In contrast, Group 2 had 21 (70%) out of 30 patients develop infections. Group 1 had a higher survival rate (57.8%) than Group 2 (transfusion > 10 units) (46.2%) with a chi-square value = 23.56, and p-value Conclusion: The volume of blood product transfusions has a considerable impact on patient outcomes, particularly infection and survival rates. Additional long-term prospective studies and larger randomized controlled trials are needed to strengthen the evidence for determining transfusion protocols for these patients.

Development of Non-ABO Red Blood Cell Alloantibodies in Patient Undergoing Allogeneic Haematopoietic Stem Cell Transplant

Alloantibodies that are non ABO Alloimmunization to protein antigens happens only after exposure, in contrast to ABO isohaemagglutinins, which are present naturally, even in the absence of prior exposure. It is recognized that while non-ABO RBC antibodies are less common than ABO antibodies, they generate essentially the same issues that lead to unfavorable clinical results. If non-ABO alloantibodies are identified early on, these issues related complications may be avoided This call for an in-depth understanding of the recipient and donor’s ABO-Rh grouping, antibody screening, and the phenotype of certain antigens. Equally important, the temporal association time between transplantation and hemolysis can help identify the underlying mechanism of hemolysis and direct appropriate management. Therefore, for that, it is crucial to identify the etiology of post-HSCT anemia for prevention and therapy, in addition to a thorough grasp of the mechanism of anemia in non-ABO-incompatible HSCT and the temporal link between HSCT and anemia. Finding the cause of post-HSCT anemia is essential for prevention and therapy, in addition to a thorough grasp of the mechanism of anemia in non-ABO-incompatible HSCT and the temporal link between HSCT and anemia. Therefore, for that, it is crucial to identify the etiology of post-HSCT anemia. In this case report review, we would like to highlight the vital role of transfusion medicine services and stem cell clinical teams in paying particular attention to the clinical significance of non-ABO alloantibodies involved to avoid causing overt hemolysis of incompatible donor RBCs or delayed erythropoiesis. Considering the fact that some of the Haematopoietic stem cell transplant centers do not give an attention to the other non-ABO RBC antigens.

Elevated White Blood Cell Count Is Associated with an Increased Risk of Insulin Resistance among Non-Diabetic Taxi-Motorbike Drivers Working in Cotonou, Benin

High white blood cell count (WBC) and insulin resistance (IR) are interrelated events that contribute to non-communicable diseases (NCDs), including type-2 diabetes (T2D). However, associations between IR and hematological parameters have never been explored in populations of Benin. The aims of this study were to determine the prevalence of IR and associated hematological parameters in taxi-motorbike drivers (TMDs) working in Cotonou. A total of 133 participants were analyzed in this cross-sectional study. Complete blood count, including WBC and platelet, as well as fasting plasma glucose and insulin, were performed by standard procedures. IR was assessed using the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR). Factors associated with IR, their odds ratios (ORs) and 95% confidence intervals (CIs) were determined by logistic regression analysis. The mean age of the study participants was 39.3 years. The HOMA-IR cut-off (75th percentile) for IR was 5.9. The overall prevalence of IR was 24.1%. IR increased with the increase of exposure duration and WBC levels. Logistic regression analysis revealed that the risk of IR increased significantly with higher total WBC, with adjusted ORs (95% CI) for the second and third tertiles of 3.56 (1.10 - 11.58) and 4.01 (1.21 - 13.31), respectively. Similar patterns of associations were observed in an analysis restricted to non-drinkers, although these estimates lacked statistical significance. BMI > 24.2 kg/m2 was independently associated with an increased risk of IR (OR = 3.82, 95% CI: 1.33 - 11.03, P = 0.013). In conclusion, the prevalence of IR in TMDs was 24.1%. IR was significantly associated with elevated WBC count and BMI. WBC may serve as a biomarker to identify individuals at the greatest IR risk.

Selection of Reference Genes in Equine White Blood Cells for Real Time PCR Normalization Following Extracorporeal Shock Wave Therapy

Selection of proper reference genes (RGs) is an essential step needed for accurate normalization of results from genomic studies. Expression of RGs is regulated by many factors such as species, age, gender, type of tissue, the presence of disease, and the administration of therapeutic treatment. The aim of the present study was to identify optimal RGs in a set of blood samples collected at different time points (0, 24, 48, 72 h) from horses following administration of extracorporeal shock wave therapy (ESWT). The mRNA expression of twelve RGs: HPRT1, ACTB, HSP90A, SDHA, GUSB, B2M, UBC, NONO, TBP, H6PD, RPL32, GAPDH was determined using real time quantitative polymerase chain reaction (qPCR). An SAS program developed on the algorithm of geNorm, SASqPCR, was used to determine stability of the expression and the number of optimal RGs. The results showed that the range of quantification cycle (Cq) values of the evaluated genes varied between 17 and 26 cycles, and that one optimal RG, ACTB, was sufficient for normalization of gene expression. Results of stability of expression demonstrated that ACTB was the optimal choice for all the samples studied. Notably, in samples collected at 72 h post ESWT, TBP showed a significant change in the expression level, and was not suitable for use as a RG. These results substantiate the importance of validating and selecting an appropriate RG.