Normal Blood Cells Research Articles

The Psychosocial Effects of Sickle Cell Anaemia Among Couples in Ekiti State, Southwestern Nigeria

The function of the normal red blood cell is to transport oxygen with the help of haemoglobin while, sickle-shaped red blood cells are dehydrated, rigid and fragile causing blockage small blood vessels leading to vaso- occlusion, intravascular hemolysis and series of life threatening disorders [1]. The inheritance of homozygous sickle haemoglobin (HbS) is in accord with Mendelian laws. According to Mendelian laws, if carriers (AS) marry each other they will probably produce a sickler (SS) in ratio 1(SS): 2(AS): 1(AA) [2]. This is a descriptive study among secondary school teachers aiming at their knowledge level and specifically identifies the Socioeconomic effects of sickle cells diseased (SCD) on couples. Three hundred (300) participants were selected using simple random sampling Technique. The study instruments are a pre tested, validated, self-administered structured questionnaires. Data were analyzed using statistical package for social sciences (SPSS) version 20; results were presented in tables and percentages. The results show that participants have good knowledge on SCD (83.3%), while 50% knows that it is an inherited blood disorders, 66.67 % knows that it can be detected via blood test. Majority of the respondents (93%) affirmed that genotype can influence their choice of partners to marry despite love and affection towards their partners. The study recommends more public health education and training to enable patients to receive optimum care for the treatment and prevention of SCD and more specialist centers should be established in high-risk communities.

Cyto‐Knet: An instance segmentation approach for multiple myeloma plasma cells using conditional kernels

AbstractMultiple myeloma disrupts normal blood cell production, requiring early detection due to the increased risk of bone metastases. Although various artificial intelligence (AI) methods have been developed to assist pathologists, they often lack comprehensive metrics to measure both detection and segmentation errors. This study presents a hybrid framework that combines deep learning and heuristic techniques to achieve accurate instance segmentation of individual plasma cells in Giemsa‐stained cytology images. Our proposed network, called cyto‐Knet, incorporates an innovative color‐balancing method as a preprocessing step to standardize the appearance of cytological images. Our network leverages a 4‐class segmentation strategy with conditional kernels to enhance segmentation performance and accuracy. Additionally, a marker‐based watershed algorithm is employed in the postprocessing step to address the challenge of merged objects. Extensive validation at both pixel and object‐based levels demonstrates superior performance compared with state‐of‐the‐art techniques. Our method achieves pixel‐based metrics (precision, recall, and F1‐score) of approximately 0.90. The object‐based evaluation reveals an average Dice coefficient of 0.9130 and an aggregated Jaccard index of 0.8237. Importantly, our solution is designed for integration into an end‐to‐end system for diagnosis support and can be easily extended to other applications.

Clinical characteristics, outcomes, and risk factors of SARS-CoV-2 breakthrough infections among 572 fully vaccinated (BBIBP-CorV) hospitalized patients

BackgroundBreakthrough infections have been widely reported in vaccinated individuals. However, the clinical characteristics, outcomes, and risk factors of SARS-CoV-2 breakthrough infections among fully vaccinated (BBIBP-CorV) hospitalized patients have not yet been fully elucidated. MethodsIn the single-center cohort study conducted at Xiangya Hospital of Central South University, we enrolled the hospitalized COVID-19 patients who had received full (2 doses) vaccination with the BBIBP-CorV vaccine between December 5, 2022, and January 31, 2023. We collected and analyzed information related to clinical characteristics, laboratory results, treatments, outcomes and prognostic data. Univariate and multivariable Cox regression were performed to assess the impact of clinical characteristics and laboratory results on the composite outcome (including the initiation of endotracheal intubation, non-invasive respiratory support, intensive care unit admission, and all-cause death). ResultsA total of 572 COVID-19 hospitalized patients with fully vaccinated (BBIBP-CorV) were included. The median age of the patients was 66 years (IQR 53, 74). The most common symptoms included fever (347 [60.7 %]), dry cough (401 [70.1 %]), and expectoration (333 [58.2 %]). Among those with pre-existing chronic comorbidities, 44.2 % had hypertension and 20.5 % had diabetes. Laboratory tests revealed that the majority of patients (425/549 [77.4 %]) had normal white blood cell counts. Composite outcome occurred in 11.9 % of patients, with 96.7 % of patients discharged and 3.3 % of patients died. Multivariate Cox regression analyses suggested that the NLR >4 (adjusted HR, 5.50 [95%CI: 1.56–19.47]; P = 0.008), D-dimer >0.5 mg/ml (adjusted HR, 2.17 [95%CI: 1.03–4.59]; P = 0.042) and procalcitonin >0.1 ng/ml (adjusted HR, 3.22 [95%CI: 1.38–7.52]; P = 0.007) were independently associated with the composite outcome. ConclusionBreakthrough infection after being fully vaccinated (BBIBP-CorV) is more likely to occur in older patients and patients with pre-existing chronic comorbidities. NLR >4, D-dimer >0.5 mg/ml and procalcitonin >0.1 ng/ml were independent risk factors for composite outcome.

Bio-inspired design approaches to artificial blood technology: Oxygen carriers

Bio-inspired design approaches to artificial blood technology: Oxygen carriers Allan Doctor, MD, Professor of Pediatrics at the University of Maryland School of Medicine, shares his expertise on bio-inspired design approaches to artificial blood technology: oxygen carriers. There is a need for an artificial oxygen (O2) carrier for use when banked blood is unavailable or undesirable. To date, efforts to develop Hb-based oxygen carriers (HBOCs) have failed successful translation, because of design flaws that do not preserve physiologic interactions of normal red blood cells (RBCs): First, HBOCs capture O2 in lungs but do not release O2 effectively to tissue, and second, HBOCs trap nitric oxide (NO), causing vasoconstriction – which critically limits blood flow, particularly in ischemic vascular beds; together, failure to both effectively release (to tissue) captured O2 and blood flow restriction undermines the potential benefit from otherwise improved O2 content.

Synthesis of halloysite nanotubes decorated with green silver nanoparticles to investigate cytotoxicity, lipid peroxidation and induction of apoptosis in acute leukemia cells

Leukemia is the 15th most common cancer in adults and the first most common cancer in children under the age of five, and unfortunately, it accounts for many deaths every year. Since leukemia chemotherapy usually fails due to chemotherapy resistance and disease relapse, many efforts are being made to develop new methods of leukemia treatment. Therefore, for the first time, we decorated halloysite nanotubes (HNTs) with green silver nanoparticles (Ag NPs) with the help of Moringa Peregrina leaves extract to increase the solubility of Ag NPs and to use the protective ability of HNTs against lipid peroxidation in erythrocytes. Cell survival assay by the MTT method showed that HNTs-Ag NPs can decrease the survival of Jurkat T-cells to about 10% compared to the control. The IC50 value was estimated as 0.00177 mg/mL after 96 h of treatment. Investigating the expression of genes involved in apoptosis by Real-time PCR proved that decorated HNTs with Ag NPs can increase the Bak1/Bclx ratio by 17.5 times the control group. Also, the expression of the caspase-3 gene has increased 10 times compared to the control. Finally, the reduction of malondialdehyde production after 24 h proved that the presence of HNTs can have a good protective effect on lipid peroxidation in erythrocytes. Therefore, on the one hand, we can hope for the ability of HNTs-Ag NPs to induce apoptosis in blood cancer cells and on the other hand for its protective effects on normal blood cells.

Classification of Red Blood Cell Abnormality in Thin Blood Smear Images using Convolutional Neural Networks

One of the most common morphological red blood cell abnormalities encountered during routine thin blood smear microscopy for the detection of malaria parasite is the rouleaux formation, which is the stacking together of red blood cells to form a chain. Rouleaux formation signifies an underlying infection and as such microscopists are mandated to report its presence. A lot of work has been done in automating malaria diagnosis using deep learning, but no model has been developed which is capable of detecting rouleaux formation in malaria infected red blood cells. Thus, this study collected 231 peripheral blood smear (PBS) images of normal red blood cell morphology and 231 PBS images with rouleaux morphology. The images were pre-processed and segmented into equal instances of 3044 coloured images of size 750×750 pixels. Two convolutional neural network (CNN) models were developed and trained to classify the images into normal red blood cell morphology or rouleaux morphology. The CNN models were trained on two different image sizes: 300×300 and 500×500. The first CNN model achieved validation accuracy/loss values of 87.91%/0.8177 and 56.58%/1.4090 when trained on images of sizes 300×300 and 500×500 respectively. In the second CNN model, the CNN layers of the first model were replaced with depthwise separable CNN layers, it was also trained on images of sizes 300×300 and 500×500 achieving validation accuracy/loss values of 90.95%/0.2804 and 87.75%/0.5904 respectively. This study demonstrates the capability of CNN models in detecting red blood cell morphology abnormality in thin smear images at an optimal image size of 300×300.

Detection and Classification of Leukemia using Machine Learning

Abstract—Leukemia is a haematological malignancy characterized by the abnormal proliferation of cancerous cells inside the bone marrow, resulting in the disruption of normal blood cell production. It induces a rise in the number of leukocytes. Leukemia is characterized by an aberrant proliferation of white blood cells. Leukemia is a heterogeneous disease characterized by the presence of several subtypes. Certain forms of leukemia have been observed to impact the paediatric population. Adults can be affected by several forms of leukemia. Leukemia is categorized according to the progressive elevation of white blood cell counts. There are two main classifications of leukemia, namely Acute leukemia and Chronic leukemia. When the rate of progression is gradual, individuals are diagnosed with chronic leukemia. Acute leukemia is characterized by a rapid proliferation of white blood cells. These two categories are further subdivided into two distinct subtypes for each form of leukemia. Our models were constructed using a customized version of the VGG13 architecture. The VGG13 architecture is a widely used Convolutional Neural Network (CNN) model that consists of many layers. The object recognition model is considered to be innovative. The models are utilized to categorize the microscopic blood smear images provided as input into three distinct categories: Acute Lymphocytic Leukemia or normal cells. The model achieves 92% accuracy in classifying ALL cells assisting automated identification of leukemic cells. Keywords— leukemia detection, leukemia classification, VGG, CNN, Acute leukemia

3D-Shaped Binders of Unfolded Proteins Inducing Cancer Cell-Specific Endoplasmic Reticulum Stress In Vitro and In Vivo.

The amount of unfolded proteins is increased in cancer cells, leading to endoplasmic reticulum (ER) stress. Therefore, cancer cells are sensitive to drugs capable of further enhancing ER stress. Examples of such drugs include the clinically approved proteosome inhibitors bortezomib and carfilzomib. Unfortunately, the known ER stress inducers exhibit dose-limiting side effects that justify the search for better, more cancer-specific drugs of this type. Herein, we report on FeC 2, which binds to unfolded proteins prevents their further processing, thereby leading to ER stress and ROS increase in cancer cells, but not in normal cells. FeC 2 exhibits low micromolar toxicity toward human acute promyelocytic leukemia HL-60, Burkitt's lymphoma BL-2, T-cell leukemia Jurkat, ovarian carcinoma A2780, lung cancer SK-MES-1, and murine lung cancer LLC1 cells. Due to the cancer-specific mode of action, 2 is not toxic in vivo up to the dose of 147 mg/kg, does not affect normal blood and bone marrow cells at the therapeutically active dose, but strongly suppresses both primary tumor growth (confirmed in Nemeth-Kellner lymphoma and LLC1 lung cancer models of murine tumor) and spreading of metastases (LLC1).

OA17 Rheumatoid meningitis - a rare complication of rheumatoid arthritis

Abstract Introduction A wide spectrum of neurological complications can occur in rheumatoid arthritis (RA) including peripheral neuropathy, mononeuritis multiplex and rheumatoid vasculitis. Cerebrovascular disease is also common. We describe a rare neurological complication of RA. Case description The patient was first diagnosed with seropositive RA in 2015 at the age of 68. His rheumatoid factor at presentation was 144 kIU/L and CCP antibodies >340 U/mL. His background include alcohol excess and obstructive sleep apnoea with peripheral neuropathy attributed to alcohol. Nerve conduction studies demonstrated axonal neuropathy. By 2016, he had achieved good disease control with combination methotrexate and sulfasalazine. In 2018, he was admitted to stroke services with right arm weakness and focal neurological deficit on examination. An urgent CT head showed possible right parietal extra dural haemmorhage. His CRP was <5, ESR 24 with a normal ANA. Borrelia, syphilis and HIV screening were normal. Anti-glutamic acid decarboxylase (GAD), anti-amphiphysin, anti-Hu, anti-Yo and anti-Ri antibodies were all negative. Lumbar puncture revealed a normal glucose and red blood cells count but the CSF protein was raised at 851 mg/L with a lymphocyte count of 9/ul. Gram stain, culture, viral PCR for HSV, VZV, enterovirus, parechovirus and adenovirus were normal and CSF cytology demonstrated a lymphocyte pleocytosis. Subsequent contrast MRI head scan showed leptomeningeal enhancement with gadolinium contrast. MRI of the cervical spine and brachial plexus was normal and an EMG/NCS of the upper limb demonstrated an incidental ulnar nerve compression at the elbow. Following neurology input, the leptomeningeal enhancement was thought to represent rheumatoid meningitis (RM). He was treated with 1 mg/kg prednisolone and rituximab with prompt and complete recovery. He remains well from both the perspective of his RA and RM. Discussion RM is a rare form of aseptic meningitis. Aseptic meningitis is commonly defined as clinical and CSF evidence of meningeal inflammation in the absence of an infectious aetiology. The vast differential includes malignancies, drug-induced and autoimmune diseases, for example lupus and sarcoidosis. The diagnosis of RM requires a high index of suspicion as well as exclusion of other causes. Historically RM was diagnosed at post-mortem but MRI scanning means pre-mortem diagnosis is possible. It is considered rare but serious manifestation of RA. Case reports suggest RM usually occurs in those with long standing seropositive RA but RM has been described in the early stages of RA and even as a presenting feature. Peripheral disease activity does not correlate with occurrence of RM. The clinical presentations vary depending on the brain structure involved and can include motor or sensory deficits, cognitive disturbance and seizures. It may mimic many other conditions. Radiological findings will not distinguish RM from other causes of aseptic meningitis. CSF finding of lymphocytosis and rheumatoid factor (if available) may help distinguish RM from other causes. Meningeal biopsy can confirm the diagnosis. Due to the rarity of RM, there are no current guidelines on treatment. Historically, corticosteroids are the main induction agent. There are case reports highlighting possible success from the addition of cyclophosphamide and rituximab. Case series also highlight a significant mortality rate in excess of 60% even despite treatment. This may represent publication and historical bias. Key learning points Rheumatoid meningitis (RM) is a rare but serious complication of rheumatoid arthritis. RM may not correlate with disease activity nor disease duration. Diagnosis is a challenge due to its wide clinical phenotype as well as the non-specificity of imaging, lumbar puncture and serological findings. Treatment options are based on case reports and series and include corticosteroids, rituximab and cyclophosphamide.

Study on the dielectrophoretic characteristics of malaria-infected red blood cells.

Malaria is a tropical disease caused by parasites in the genus Plasmodium, which still presents 241 million cases and nearly 627,000 deaths recently. In this work, we used the dielectrophoresis (DEP) to characterize red blood cells in a microchannel. The purpose of this work is to determine the difference between the normal and the malaria-infected cells based on the DEP characteristics. The samples were infected cells and normal red blood cells, which were either prepared in culture or obtained from volunteers. Diamond-shaped and curved micropillars were used to create different degrees of DEP in the gap between them. The DEP crossover frequencies were observed with the diamond-shaped micropillars. The cell velocity under negative dielectrophoresis (nDEP) at a low frequency was examined with the curved micropillars. The measured lower crossover frequencies were remarkably different between the malaria-infected cells and the normal cells, whereas the higher crossover frequencies were similar among the samples. The velocity under nDEP was lower for the infected cells than the normal cells. The results imply that the malaria infection significantly decreases the capacitance but increases the conductance of the cell membrane, whereas a change in cytoplasmic conductivity may occur in a later stage of infection.

Performance of the new MC-80 automated digital cell morphology analyser in detection of normal and abnormal blood cells: Comparison with the CellaVision DM9600.

Mindray MC-80 is an automated system for digital imaging of white blood cells (WBCs) and their pre-classification. The objective of this work is to analyse its performance comparing it with the CellaVision® DM9600. A total of 445 samples were used, 194 normal and 251 abnormal: acute leukaemia (100), myelodysplastic syndromes/myeloproliferative neoplasms (33), lymphoid neoplasms (50), plasma cell neoplasms (14), infections (49) and thrombocytopenia (5). WBC pre-classification values with the MC-80 and DM9600 were compared with (1) the microscope, (2) Mindray BC-6800Plus differentials in only normal samples, and (3) confirmed or reclassified images (post-classification). Pearson's correlation, Lin's concordance, Passing-Bablok regression, and Bland-Altman plots were used. Sensitivity, specificity, positive (PPV) and negative (NPV) predictive values for abnormal cells using the MC-80 were calculated. The PPV and NPV were above 98% and 99%, for normal samples. For immature granulocytes (IG), NPV and PPV were 100% and 74.2%. When comparing the WBC differentials using the MC-80, the microscope and the BC-6800Plus, no differences were found except for basophils and IG. Our results showed good agreement between the pre- and post-classification of normal WBC, including IG, quantified by high correlation and concordance values (0.91-1). Sensitivity and specificity for blasts were 0.984 and 0.640. The MC-80 detected abnormal lymphocytes in 30% of the smears from patients with lymphoid neoplasm. Plasma cell identification was better using the DM9600. The sensitivity and specificity for erythroblast detection were 1 and 0.890. We found that the MC-80 shows high performance for WBC differentials for both normal samples and patients with haematological diseases.

Elucidating disease-associated mechanisms triggered by pollutants via the epigenetic landscape using large-scale ChIP-Seq data

BackgroundDespite well-documented effects on human health, the action modes of environmental pollutants are incompletely understood. Although transcriptome-based approaches are widely used to predict associations between chemicals and disorders, the molecular cues regulating pollutant-derived gene expression changes remain unclear. Therefore, we developed a data-mining approach, termed “DAR-ChIPEA,” to identify transcription factors (TFs) playing pivotal roles in the action modes of pollutants.MethodsLarge-scale public ChIP-Seq data (human, n = 15,155; mouse, n = 13,156) were used to predict TFs that are enriched in the pollutant-induced differentially accessible genomic regions (DARs) obtained from epigenome analyses (ATAC-Seq). The resultant pollutant–TF matrices were then cross-referenced to a repository of TF–disorder associations to account for pollutant modes of action. We subsequently evaluated the performance of the proposed method using a chemical perturbation data set to compare the outputs of the DAR-ChIPEA and our previously developed differentially expressed gene (DEG)-ChIPEA methods using pollutant-induced DEGs as input. We then adopted the proposed method to predict disease-associated mechanisms triggered by pollutants.ResultsThe proposed approach outperformed other methods using the area under the receiver operating characteristic curve score. The mean score of the proposed DAR-ChIPEA was significantly higher than that of our previously described DEG-ChIPEA (0.7287 vs. 0.7060; Q = 5.278 × 10–42; two-tailed Wilcoxon rank-sum test). The proposed approach further predicted TF-driven modes of action upon pollutant exposure, indicating that (1) TFs regulating Th1/2 cell homeostasis are integral in the pathophysiology of tributyltin-induced allergic disorders; (2) fine particulates (PM2.5) inhibit the binding of C/EBPs, Rela, and Spi1 to the genome, thereby perturbing normal blood cell differentiation and leading to immune dysfunction; and (3) lead induces fatty liver by disrupting the normal regulation of lipid metabolism by altering hepatic circadian rhythms.ConclusionsHighlighting genome-wide chromatin change upon pollutant exposure to elucidate the epigenetic landscape of pollutant responses outperformed our previously described method that focuses on gene-adjacent domains only. Our approach has the potential to reveal pivotal TFs that mediate deleterious effects of pollutants, thereby facilitating the development of strategies to mitigate damage from environmental pollution.

Association between the Clinical, Laboratory and Ultrasound Characteristics and the Etiology of Peripheral Lymphadenopathy in Children.

Peripheral lymphadenopathy affects most children at least once in a lifetime and represents a major reason for concern. Therefore, we aimed to identify the most common causes of peripheral lymphadenopathy in hospitalized children and to determine the clinical, laboratory and ultrasound characteristics that enable fast, easy and accurate etiological diagnosis. We performed a cross-sectional study including 139 children who were hospitalized because of peripheral lymphadenopathy. Ultrasound of lymph nodes was performed in 113 (81.3%) patients. Lymphadenopathy was generalized in nine (6.5%) patients. Malignant etiology was established in only three (2.2%) patients. Bacterial lymphadenitis, infectious mononucleosis (IM) and cat scratch disease (CSD) were diagnosed in 66 (47.5%), 31 (22.3%) and 29 (20.9%) patients, respectively. Bacterial lymphadenitis was significantly associated with neutrophilia (p < 0.01), and increased C-reactive protein levels (p < 0.01). IM was associated with pharyngitis (p < 0.01), leukocytosis without neutrophilia (p = 0.03) and increased blood liver enzyme levels (p < 0.01). CSD was associated with recent contact with a cat (p < 0.01), absence of a fever (p < 0.01) and normal white blood cell count (p < 0.01). Thorough history and clinical examination in combination with a few basic laboratory tests enable fast and accurate differentiation between the most common etiologies of lymphadenopathy in children to avoid unnecessary procedures and hospitalizations.

P10-26: Cytoprotective Potential of Synthetic Strigolactone Analog (GR24) against Normal Blood Cells Exposed to Brominated Flame Retardants

P10-26: Cytoprotective Potential of Synthetic Strigolactone Analog (GR24) against Normal Blood Cells Exposed to Brominated Flame Retardants

Analysis of Blood Samples to Identify Leukemia Cells using a Support Vector Machine and K-Nearest Neighbor Algorithms

Abstract: The study proposes an innovative approach using MATLAB to automate the counting of leukemia cells in blood samples, employing Support Vector Machine (SVM) and Nearest Neighbor algorithms. The method involves preprocessing blood sample images to enhance contrast and apply image filters, followed by segmentation techniques for isolating individual cells. SVM and nearest neighbor algorithms are trained using extracted features such as cell size, shape, and texture. Accurate detection and counting of leukemia cells play a crucial role in leukemia diagnosis and management. Leukemia is a group of cancers characterized by abnormal white blood cell proliferation in the bone marrow, leading to symptoms like bleeding, bruising, fatigue, and increased infection risk due to insufficient normal blood cells. Diagnosis typically involves blood tests or bone marrow biopsy. In clinical bioinformatics, SVM algorithms have enabled the development of robust experimental cancer diagnostic models, utilizing gene expression data with a small number of samples and numerous variables. Efficient implementations of SVM algorithms further facilitate practical application. Support Vector Machines excel in mapping data to higher-dimensional spaces through kernel functions, allowing the identification of maximum-margin hyperplanes for separating training instances.

Development of a new online SPE-HPLC-MS/MS method for the profiling and quantification of sphingolipids and phospholipids in red blood cells – Application to the study of Gaucher's disease

Red blood cells (RBCs) are the subject of clinical attention due to their biological importance. Recently, it has been shown that certain erythrocyte pathologies could be linked to an abnormal lipid composition. In this work, we have developed a simple and fast method using online sample preparation with liquid chromatography coupled to mass spectrometry (SPE-HPLC-MS/MS), to identify a large number of sphingolipids (SL) and phospholipids (PL). The use of online sample preparation considerably reduces analysis times (15 min including extraction and separation of lipids + 2 min for system re-equilibration) and facilitates experimentation while ensuring very good extraction yields. This method was then successfully applied to the quantification of 30 sphingolipids and phospholipids in plasma and erythrocyte extracts from a cohort of individuals with Gaucher disease, treated or not by enzymotherapy. Our results for the study of this disease, led us to establish the lipid profile of the healthy red blood cells, still not very well-known to date. For this, we adopted a semi-targeted approach, based on the use of a triple-quadrupole analyzer and identified more than two hundred different lipid species. These promising results will hopefully enable us to enrich our knowledge of the normal red blood cells lipidome.

Enterovirus Central Nervous System Infection in Infancy, the Value of Routine Testing.

Human nonpolio enterovirus (EV) is a major cause of infection in neonates and infants; however, the clinical presentation and cerebrospinal fluid findings vary significantly. Infection caused by EV in patients under 1 year of age can present with a broad clinical spectrum, from fever to severe systemic and/or neurological disease. Retrospective cohort analysis of infants with EV central nervous system (CNS) infection presenting to a tertiary center between January 2017 and December 2022. We recorded patient demographics, parent-reported symptoms at presentation, and blood and cerebrospinal fluid (CSF) testing at presentation. Seventy-eight patients were included in the final study. Forty-one percent of infants with an EV CNS infection had a normal CSF white blood cell count. Clinical presentation was similar in infants with and without CSF pleocytosis. Median C-reactive protein was higher in cases of EV CNS infection without pleocytosis. EV CNS infection commonly presents without CSF pleocytosis. Testing for EV should be considered in febrile infants with no source regardless of CSF parameters.

An impedance flow cytometry with integrated dual microneedle for electrical properties characterization of single cell

Electrical characteristics of living cells have been proven to reveal important details about their internal structure, charge distribution and composition changes in the cell membrane, as well as the extracellular context. An impedance flow cytometry is a common approach to determine the electrical properties of a cell, having the advantage of label-free and high throughput. However, the current techniques are complex and costly for the fabrication process. For that reason, we introduce an integrated dual microneedle-microchannel for single-cell detection and electrical properties extraction. The dual microneedles utilized a commercially available tungsten needle coated with parylene. When a single cell flows through the parallel-facing electrode configuration of the dual microneedle, the electrical impedance at multiple frequencies is measured. The impedance measurement demonstrated the differential of normal red blood cells (RBCs) with three different sizes of microbeads at low and high frequencies, 100 kHz and 2 MHz, respectively. An electrical equivalent circuit model (ECM) was used to determine the unique membrane capacitance of individual cells. The proposed technique demonstrated that the specific membrane capacitance of an RBC is 9.42 mF/m−2, with the regression coefficients, at 0.9895. As a result, this device may potentially be used in developing countries for low-cost single-cell screening and detection.

Molecular and clinical significance of FLT3, NPM1, DNMT3A and TP53 mutations in acute myeloid leukemia patients.

Acute myeloid leukemia (AML) is a type of blood cancer that affects the bone marrow and blood cells. AML is characterized by the rapid growth and accumulation of abnormal white blood cells, known as myeloblasts, which interfere with the production of normal blood cells. The main aim was to determine the relationship between these genetic alterations and the clinico-haematological parameters and prognostic factors with therapy for Iraqi patients with AML. We used Sanger Sequencing to detect the mutations in 76 AML patients. Clinical data of AML patients were retrospectively analysed to compare the prognosis of each gene mutation group. Somatic mutations were identified in 47.4% of the enrolled patients in a core set of pathogenic genes, including FLT3 (18 patients, 23.7%), DNMT3A (14, 18.4%), NPM1 (11, 14.5%) and TP53 (5, 6.8%). As multiple mutations frequently coexisted in the same patient, we classified patients into 10 further groups. Two novel mutations were detected in FLT3-ITD, with new accession numbers deposited into NCBI GenBank (OP807465 and OP807466). These two novel mutations were computationally analysed and predicted as disease-causing mutations. We found significant differences between patients with and without the detected mutations in disease progression after induction therapy (remission, failure and death; pv = < 0.001) and statistically significant differences were reported in total leukocyte count (pv = < 0.0001). These genes are among the most frequently mutated genes in AML patients. Understanding the molecular and clinical significance of these mutations is important for guiding treatment decisions and predicting patient outcomes.

An "unexpected" role for EMT transcription factors in hematological development and malignancy.

The epithelial to mesenchymal transition (EMT) is a fundamental developmental process essential for normal embryonic development. It is also important during various pathogenic processes including fibrosis, wound healing and epithelial cancer cell metastasis and invasion. EMT is regulated by a variety of cell signalling pathways, cell-cell interactions and microenvironmental cues, however the key drivers of EMT are transcription factors of the ZEB, TWIST and SNAIL families. Recently, novel and unexpected roles for these EMT transcription factors (EMT-TFs) during normal blood cell development have emerged, which appear to be largely independent of classical EMT processes. Furthermore, EMT-TFs have also begun to be implicated in the development and pathogenesis of malignant hematological diseases such as leukemia and lymphoma, and now present themselves or the pathways they regulate as possible new therapeutic targets within these malignancies. In this review, we discuss the ZEB, TWIST and SNAIL families of EMT-TFs, focusing on what is known about their normal roles during hematopoiesis as well as the emerging and "unexpected" contribution they play during development and progression of blood cancers.