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This paper describes a technique to detect blood cell levels based on the time-period modulation of a relaxation oscillator loaded with an Inter-Digitated Capacitor (IDC). A digital readout circuit has been proposed to measure the time-period difference between the two oscillators loaded with samples of healthy and (potentially) unhealthy blood. A prototype circuit was designed in 65-nm CMOS technology and post-layout simulations show 15.25-aF sensitivity. The total circuit occupies 2,184- μ m2 silicon area and consumes 216 μ A from a 1-V power supply. [ABSTRACT FROM AUTHOR]

An increased level of granulocyte‐macrophage colony‐stimulating factor has a potential role in the development of autoimmune diseases, and the neutralization of its activity by monoclonal antibodies is a promising therapy for some diseases. Here, the crystal structure of the Fab region of EV1007, a fully human antibody expressed in Chinese hamster ovary cells that was developed from human peripheral blood mononuclear cells, is described. The structure closely resembles that of MB007, which is the Fab region of the same antibody expressed in Escherichia coli [Blech et al. (2012), Biochem. J.447, 205–215], except at the hinge regions between the immunoglobulin domains and the H3 loop region. This paper presents evidence for the flexibility of the hinge and H3 loop regions of the antibody based on the comparison of two independently solved crystal structures. [ABSTRACT FROM AUTHOR]

Platelet is a blood cell type that is stored and circulated in the human body. It acts as a blood thickening agent and prevents blood from overflowing whenever bleeding occurs. An excessive or inadequate number of platelets could lead to platelet-related diseases. The current practice of platelet counting involves the manual counting process using a haemocytometer, Wright's Stain which uses the dyes to facilitate the differentiation of blood cell types, and a tally counter. Yet, this process can be time-consuming, demanding, and exhausting for haematologists, and likely to be prone to errors. Thus, this paper presents a study on automated platelet counter and detection using image processing techniques. The K-Means Clustering was employed to count and detect the presence of platelets in microscopic blood smear images. Several processes were performed prior to the K-means clustering, including image enhancement and YCbCr image formatting. Subsequently, image masking, as well as area thresholding were applied to eliminate every unwanted entity and highlight the visibility of the platelets before the number of platelets could be detected and counted. A comparative experiment was designed in which the K-Means Clustering platelet count and detection were compared with the actual number of platelets reported by haematologists. The platelet counts and detection were categorized into three detection categories which are Less Detection (LD), Accurate Detection (AD), and Over Detection (OD). The proposed study was evaluated to 90 testing platelet images. Out of the 90 testing images, 75 platelet images were perfectly counted and detected which returned 91.67% of accuracy. This signifies that the K-Means Clustering algorithm was discovered to be efficient and dependable for automated platelet counter and detection. [ABSTRACT FROM AUTHOR]

Background: Tumor microenvironment plays pivotal roles in carcinogenesis, cancer development and metastasis. Composition of cancer immune cell subsets can be inferred by deconvolution of gene expression profile accurately. Compositions of the cell types in cancer microenvironment including cancer infiltrating immune and stromal cells have been reported to be associated with the cancer outcomes markers for cancer prognosis. However, rare studies have been reported on their association with the response to preoperative radiotherapy for rectal cancer. Methods: In this paper, we deconvoluted the immune/stromal cell composition from the gene expression profiles. We compared the composition of immune/stromal cell types in the RT responsive versus nonresponsive for rectal cancer. We also compared the peripheral blood immune cell subset composition in the stable diseases versus progressive diseases of rectal cancer patients with fluorescence-activated cell sorting from our institution. Results: Compared with the non-responsive group, the responsive group showed higher proportions of CD4+ T cell (0.1378 ± 0.0368 vs. 0.1071 ± 0.0373, p = 0.0215), adipocytes, T cells CD4 memory resting, and lower proportions of CD8+ T cell (0.1798 ± 0.0217 vs. 0.2104 ± 0.0415, p = 0.0239), macrophages M2, and preadipocytes in their cancer tissue. The responsive patients showed a higher ratio of CD4+/CD8+ T cell proportions (mean 0.7869 vs. 0.5564, p = 0.0210). Consistently, the peripheral blood dataset showed higher proportion of CD4+ T cells and higher ratio of CD4+/CD8+ T cells, and lower proportion of CD8+ T cells for favorable prognosis. We validated these results with a pooled dataset of GSE3493 and GSE35452, and more peripheral blood data, respectively. Finally, we imported these eight cell features including eosinophils and macrophage M1 to Support Vector Machines and could predict the pre-radiotherapy responsive versus non-responsive with an accuracy of 76%, ROC AUC 0.77, 95% confidential interval of 0.632–0.857, better than the gene signatures. Conclusions: Our results showed that the proportions of tumor-infiltrating subsets and peripheral blood immune cell subsets can be important immune cell markers and treatment targets for outcomes of radiotherapy for rectal cancer. [ABSTRACT FROM AUTHOR]

For the analysis of medical images, one of the most basic methods is to diagnose diseases by examining blood smears through a microscope to check the morphology, number, and ratio of red blood cells and white blood cells. Therefore, accurate segmentation of blood cell images is essential for cell counting and identification. The aim of this paper is to perform blood smear image segmentation by combining neural ordinary differential equations (NODEs) with U-Net networks to improve the accuracy of image segmentation. In order to study the effect of ODE-solve on the speed and accuracy of the network, the ODE-block module was added to the nine convolutional layers in the U-Net network. Firstly, blood cell images are preprocessed to enhance the contrast between the regions to be segmented; secondly, the same dataset was used for the training set and testing set to test segmentation results. According to the experimental results, we select the location where the ordinary differential equation block (ODE-block) module is added, select the appropriate error tolerance, and balance the calculation time and the segmentation accuracy, in order to exert the best performance; finally, the error tolerance of the ODE-block is adjusted to increase the network depth, and the training NODEs-UNet network model is used for cell image segmentation. Using our proposed network model to segment blood cell images in the testing set, it can achieve 95.3% pixel accuracy and 90.61% mean intersection over union. By comparing the U-Net and ResNet networks, the pixel accuracy of our network model is increased by 0.88% and 0.46%, respectively, and the mean intersection over union is increased by 2.18% and 1.13%, respectively. Our proposed network model improves the accuracy of blood cell image segmentation and reduces the computational cost of the network., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2021 Dongming Li et al.)

Objective: Schizophrenia is a complex widespread neuropsychiatric disorder. This illness encompasses a complex debilitating mental disorder causing illusion, delusion, disturbed relationship, low motivation and decline of emotion. Viral infection of the brain including Borna Disease Virus (BDV) may play a role in transient or permanent neurological and behavioral abnormalities. This role of Borna virus has not been resolved outright yet, and based on published papers investigation examining the role of this virus in schizophrenia is in progress worldwide. Method: In this study, Nested Reverse Transcription-Polymerase Chain Reaction (Nested RT-PCR) was used for detection of BDV Ribonucleic Acid (RNA) in Peripheral Blood Mononuclear Cells (PBMCs) of a group of patients experiencing the first episode of schizophrenia. The results were compared with a normal group. Results: In our study, no BDV-positive was found in PBMCs of the case group. Out of 40 participants of control group one was positive for P24 gene of BDV. This result are similar to several published papers about this topic. Conclusion: An etiological relationship between Bornavirus and schizophrenia was not found in this study. More investigations are warranted to illustrate the probable relationship between bornavirus infection and schizophrenia. [ABSTRACT FROM AUTHOR]

The aim of this study was to evaluate how the inclusion of a blend of essential oils in milk replacer (MR) affects different outcomes of dairy heifers. The outcomes evaluated: feed intake, performance, body development, blood cells and metabolites, insulin-like growth factor-1 (IGF-1), rumen fermentation, fecal scores, and respiratory scores. All outcomes were evaluated during pre-weaning (4-60 d of age), and carry-over effects during post-weaning (61-90 d of age) periods. The experimental units utilized were 29 newborn Holstein × Gyr crossbred dairy heifers, with genetic composition of 5/8 or more Holstein and 3/8 or less Gyr and body weight (BW) at birth of 32.2 ± 5.2 kg. Experimental units were assigned to either a control (CON, n = 15) or a blend of essential oil supplementation (BEO, n = 14) treatment, maintaining a balance of genetic composition. The BEO was supplemented in the MR with 1 g/d/calf of a blend of essential oils (Apex Calf, Adisseo, China) composed by plant extracts derived from anise, cinnamon, garlic, rosemary, and thyme. During the pre-weaning phase, all heifers were fed 5 L of MR/d reconstituted to 15% (dry matter basis), divided into two equal meals. Water and starter were provided ad libitum. During the post-weaning, animals received a maximum of 3 kg of starter/d, and ad libitum corn silage, divided into two meals. Feed intake, fecal and respiratory scores were evaluated daily. The BW was measured every three days, while body development was recorded weekly. Blood samples were collected on 0, 30, and 60 d of age for total blood cell count, weekly and on the weaning day to determinate ß-hydroxybutyrate, urea and glucose, and biweekly for IGF-1. Ruminal parameters (pH, volatile fatty acids, ammonia-N, and acetate:propionate proportion-C2:C3) were measured on days 14, 28, 42, 60, 74 and 90. A randomized complete block design with an interaction between treatment and week was the experimental method of choice to test the hypothesis of the BEO's effect on all outcomes. An ANOVA procedure was used for continuous outcomes, and a non-parametric test was used for the ordered categorical outcomes, both adopting a CI = 95%. Results indicated that there was not enough evidence to accept the alternative hypothesis of the effect of BEO in MR on feed intake, performance, body development, and blood metabolites during both pre-weaning and post-weaning periods. However, results indicated that the inclusion of BEO in MR significantly affects the proportion of C2:C3 during pre- and post-weaning (P = 0.05). Similarly, the effect was significant for basophil (P ≤ 0.001), and platelet (P = 0.04) counts pre-weaning. The interaction between week and treatment was also significant for lymphocytes (P ≤ 0.001), revealing a cumulative effect. Lastly, fecal scores were also significant (P = 0.04) during pre-weaning, with lower values for BEO. The BEO contributed to ruminal manipulation in pre-weaning and carry-over effects in post-weaning, immunity improvement, and decreased morbidity of neonatal diarrhea in the pre-weaning phase., Competing Interests: This paper was financed by Brazilian Agricultural Research Corporation (EMBRAPA), Embrapa Dairy Cattle for funding this research and providing its facilities, and Adisseo Company for funding this research (project number: 20500.18/0005-2). Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, Brasília, Brazil), Instituto Nacional de Ciência e Tecnologia Ciência Animal (INCT, Viçosa, Brazil) for granting the scholarship. Alessandra L. Voorsluys and David V. Jacob received salary from Adisseo Company. There are no patents, products in development or marketed products to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

The purpose of this paper is to compare the biological research carried out in North Korea with the modern outcomes in the same field, from a historical perspective. In the 1960s, the group led by Bong-Han Kim asserted the existence of a fundamental circulatory system in the human body. Their findings were introduced in five papers as well as in the newspaper Rodong Sinmun. The size of the group, the range of equipment, and their findings expanded gradually, and the final paper on blood cells would be only published one of over sixty papers reported at that time. In the five papers, some unclear and inconsistent contents were found. Meanwhile, in the 2000s, PVS (primo vascular system) researchers have published over one hundred papers to prove the existence of this novel system. Some trends have emerged in approximately sixty papers as follows: The research on the identification of the anatomical and histological characteristics has gradually expanded to encompass the system's own functioning. Also, new visual results (e.g. before and after dyeing, and its comparison with blood clots) and the exploration of possible medical applications (e.g. cancer metastasis channels or stem cells location) have been proposed. However, it is difficult to identify papers which comprehensively represented the elements claimed by Bong-Han Kim's group. In addition, papers have been published more in alternative or Oriental medicine journals than in Western biomedical journals. It seems necessary to report more existence of the system in one laboratory animal and in more influential journals. [ABSTRACT FROM AUTHOR]

The recognition and classification of White Blood Cell (WBC) play a remarkable role in blood-related diseases (i.e., leukemia, infections) diagnosis. For the highly similar morphology of different WBC subtypes, it is too confused to classify the WBC effectively and accurately for visual observation of blood cell smears. This paper proposes a Deep Convolutional Neural Network (DCNN) with feature fusion strategies, named WBC-AMNet, for automatically classifying WBC subtypes based on focalized attention mechanism. To obtain more localized attention of CNN, the fusion features of the first and the last convolutional layer are extracted by focalized attention mechanism combining Squeeze-and-Excitation (SE) and Gather-Excite (GE) modules. The new method performs successfully in classifying monocytes, neutrophils, lymphocytes, and eosinophils on the complex background with an overall accuracy of 95.66%, better than that of general CNNs. The multi-classification accuracy of WBC-AMNet with the background segmentation is over 98% in all cases. In addition, Gradient-weighted Class Activation Mapping (Grad-CAM) is employed to visualize the attention heatmaps of different feature maps. [ABSTRACT FROM AUTHOR]

Blood cell count is highly useful in identifying the occurrence of a particular disease or ailment. To successfully measure the blood cell count, sophisticated equipment that makes use of invasive methods to acquire the blood cell slides or images is utilized. These blood cell images are subjected to various data analyzing techniques that count and classify the different types of blood cells. Nowadays, deep learning-based methods are in practice to analyze the data. These methods are less time-consuming and require less sophisticated equipment. This paper implements a deep learning (D.L) model that uses the DenseNet121 model to classify the different types of white blood cells (WBC). The DenseNet121 model is optimized with the preprocessing techniques of normalization and data augmentation. This model yielded an accuracy of 98.84%, a precision of 99.33%, a sensitivity of 98.85%, and a specificity of 99.61%. The proposed model is simulated with four batch sizes (BS) along with the Adam optimizer and 10 epochs. It is concluded from the results that the DenseNet121 model has outperformed with batch size 8 as compared to other batch sizes. The dataset has been taken from the Kaggle having 12,444 images with the images of 3120 eosinophils, 3103 lymphocytes, 3098 monocytes, and 3123 neutrophils. With such results, these models could be utilized for developing clinically useful solutions that are able to detect WBC in blood cell images. [ABSTRACT FROM AUTHOR]

Primary plasma cell leukemia (PCL) has a consistently ominous prognosis, even after progress in the last decades. PCL deserves a prompt identification to start the most effective treatment for this ultra-high-risk disease. The aim of this position paper is to revisit the diagnosis of PCL according to the presence of circulating plasma cells in patients otherwise meeting diagnostic criteria of multiple myeloma. We could identify two retrospective series where the question about what number of circulating plasma cells in peripheral blood should be used for defining PCL. The presence of ≥5% circulating plasma cells in patients with MM had a similar adverse prognostic impact as the previously defined PCL. Therefore, PCL should be defined by the presence of 5% or more circulating plasma cells in peripheral blood smears in patients otherwise diagnosed with symptomatic multiple myeloma. [ABSTRACT FROM AUTHOR]

In this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones - the healthy blood cells (erythrocytes) and the pathologic ones (echinocytes). The separated blood cells are analysed in terms of their most important features by the eigenfaces method. The features are the basis for designing the neural network classifier, learned to distinguish between erythrocytes and echinocytes. As the result, the proposed system is able to analyse the smear blood images in a fully automatic way and to deliver information on the number and statistics of the red blood cells, both healthy and pathologic. The system was examined in two case studies, involving the canine and human blood, and then consulted with the experienced medicine specialists. The accuracy of classification of red blood cells into erythrocytes and echinocytes reaches 96%. [ABSTRACT FROM AUTHOR]

Objectives: In response to increasing numbers of states in the US that test newborn babies for cystic fibrosis (CF), the Newborn Screening Quality Assurance Programme initiated a pilot proficiency testing programme for immunoreactive trypsinogen (IRT), the biomarker for CF. Dried blood spot specimens (DBS) were used to evaluate the performance of laboratories that screen babies for CF. Methods: DBS were prepared from human whole blood enriched with physiologically relevant levels of IRT. Various methods of making IRT-enriched DBS were used to optimize the recovery and stability of the biomarker, including preparation of DBS from either intact or lysed red blood cells, varying the timing of IRT addition to blood before dispensing onto filter paper, adding a protease inhibitor cocktail, and treating serum with charcoal before IRT enrichment. The recovery and stability of IRT in DBS were assessed. Newborn screening laboratories were offered the opportunity to test blind-coded DBS in the pilot PT programme. Results: IRT was stable in the filter paper matrix when stored for one year at either -20°C or 4°C. Fifty percent more IRT was recovered from DBS prepared with lysed red blood cells where the IRT was added to blood just before dispensing; however, protease inhibitors did not improve IRT recovery. Conclusions: IRT in the DBS matrix is stable and can be shipped worldwide under ambient conditions. Optimal IRT recovery was achieved by adjustment of DBS production practices. Laboratories receiving specimens accurately measured IRT by a variety of commercial and in-house methods. [ABSTRACT FROM AUTHOR]

One of the most common cancers identified worldwide among women is breast cancer, which has become the foremost reason for death. Due to the complexity of breast tissues, it is essential to accurately detect and classify breast cancer in medical imaging. In this paper, an optimisationbased deep learning technique is created to detect breast cancer using histopathology pictures. At first, the input image taken from the figshare dataset is sent to the preprocessing stage. The median filter is employed at the preprocessing stage to eliminate noise from the input image. Then, the pre-processed images are sent to the segmentation procedure, where the Fuzzy Local Information C-Means (FLICM) technique is used to segment the blood cells. After the segmentation process, feature extraction is carried out. In the feature extraction process, various features, such as area, shape, diameter, and Speeded-Up Robust Features (SURF), are extracted from histopathological images. At last, Deep Q Network (DQN) trained using the developed Adaptive Jelly Fish Search Optimization (AJSO) algorithm is used to identify and classify benign and malignant breast cancer. The devised approach has good accuracy, TPR, and TNR values of 91.1%, 92.1%, and 92%, correspondingly. [ABSTRACT FROM AUTHOR]

The health benefits of natural products have long been recognized. Consumption of dietary compounds such as supplements provides an alternative source of natural products to those obtained from the diet. There is a growing concern regarding the possible side effects of using different food supplements simultaneously, since their possible interactions are less known. For the first time, we have tested genotoxic and antigenotoxic effects of Biochaga, in combination with dihydroquercetin. No genotoxic effect on whole blood cells was observed within individual treatment of Biochaga (250  μ g/mL, 500  μ g/mL and 1000  μ g/mL) and dihydroquercetin (100  μ g/mL, 250  μ g/mL and 500  μ g/mL), nor in combination. Afterwards, antigenotoxic potency of both supplements against hydrogen peroxide- (H 2 O 2 -) induced DNA damage to whole blood cells (WBC) was assessed, using the comet assay. Biochaga and dihydroquercetin displayed a strong potential to attenuate H 2 O 2 -induced damage on DNA in cells at all tested concentrations, with a statistical significance ( p < 0.05), whereas Biochaga at the dose of 500  μ g/mL in combination with dihydroquercetin 500  μ g/mL was most prominent. Biochaga in combination with dihydroquercetin is able to protect genomic material from oxidative damage induced by hydrogen peroxide in vitro ., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2019 Lada Živković et al.)

Fast 3D imaging and measurement of cells are of great importance in many fields associated with the life science. In this paper, only using two phase images in orthogonal directions, a geometric rotation method for 3D fast morphology reconstruction is proposed in view of more spheroid cells in blood cells. In this method, at first, the edges of a cell in two orthogonal projection directions are extracted from the corresponding phase images, and theirs centers and axes are determined. Then, with the geometric rotation method, the 3D surfaces of the cell membrane and its nuclei are reconstructed respectively. After all, the 3D complete morphology of the cell is reconstructed according to their space geometry relation. Simulation and experimental results demonstrate the validity and accuracy of this method for spheroid cells. Compared with other reconstruction methods, the image speed is improved since the multiple measurements or iterative procedures are not required. It provides a new approach to image the 3D morphological structure of spheroid blood cells.

This paper analysed Sickle cell anaemia literature on Nigeria listed in PubMed to understand the research performance of medical researchers on sickle cell anaemia literature on Nigeria. Data covering the period of 2006-2016 were collected from the PubMed, a citation database developed by the National Centre for Biotechnology Information (NCBI).The search strategy used was ((sickle cell anaemia) OR (sickle cell anemia)) AND Nigeria AND (("2006/01/01"[PDat] : "2016/12/31"[PDat])), bearing in mind variance in spelling (anaemia and anemia), which retrieved 326 sickle cell literature on Nigeria between 2006 and 2016. Article productivity increased between 2006 and 2010. However, there was a drastic drop in article publication between 2010 and 2011 as well as between 2013 and 2015. The degree of collaboration ranged between 0.85 and 1. University of Nigeria Teaching Hospital, Enugu, Nigeria, had the highest number of contributing authors. Authors published more in journals located in Nigeria, with Nigeria Journal of Clinical Practice being the most prolific publication outlet for authors publishing sickle cell anaemia literature on Nigeria. [ABSTRACT FROM AUTHOR]

Established cell lines are widely used in research, however an appealing question is the comparability of the cells between various laboratories, their characteristics and stability in time. Problematic is also the cell line misidentification, genetic and phenotypic shift or Mycoplasma contamination which are often forgotten in research papers. The monocyte/macrophage-like cell line RAW 264.7 has been one of the most commonly used myeloid cell line for more than 40 years. Despite its phenotypic and functional stability is often discussed in literature or at various scientific discussion panels, their stability during the consecutive passages has not been confirmed in any solid study. So far, only a few functional features of these cells have been studied, for example their ability to differentiate into osteoclasts. Therefore, in the present paper we have investigated the phenotype and functional stability of the RAW 264.7 cell line from passage no. 5 till passage no. 50. We found out that the phenotype (expression of particular macrophage-characteristic genes and surface markers) and functional characteristics (phagocytosis and NO production) of RAW 264.7 cell line remains stable through passages: from passage no. 10 up to passage no. 30. Overall, our results indicated that the RAW 264.7 cell line should not be used after the passage no. 30 otherwise it may influence the data reliability. [ABSTRACT FROM AUTHOR]

Kaempferol (kae) and its glycosides are widely distributed in nature and show multiple bioactivities, yet few reports have compared them. In this paper, we report the antitumor, antioxidant and anti-inflammatory activity differences of kae, kae-7-O-glucoside (kae-7-O-glu), kae-3-O-rhamnoside (kae-3-O-rha) and kae-3-O-rutinoside (kae-3-O-rut). Kae showed the highest antiproliferation effect on the human hepatoma cell line HepG2, mouse colon cancer cell line CT26 and mouse melanoma cell line B16F1. Kae also significantly inhibited AKT phosphorylation and cleaved caspase-9, caspase-7, caspase-3 and PARP in HepG2 cells. A kae-induced increase in DPPH and ABTS radical scavenging activity, inhibition of concanavalin A (Con A)-induced activation of T cell proliferation and NO or ROS production in LPS-induced RAW 264.7 macrophage cells were also seen. Kae glycosides were used to produce kae via environment-friendly enzymatic hydrolysis. Kae-7-O-glu and kae-3-O-rut were hydrolyzed to kae by β-glucosidase and/or α-L-rhamnosidase. This paper demonstrates the application of enzymatic catalysis to obtain highly biologically active kae. This work provides a novel and efficient preparation of high-value flavone-related products. [ABSTRACT FROM AUTHOR]

Malaria is known as an acute febrile disease caused by the bite of female Anopheles mosquitoes, and it manifests itself with symptoms such as headache, fever, chills, vomiting, and fatigue. The diagnosis of malaria is still based on manual identification of Plasmodium parasitized cells in microscopic examinations of blood cells known as parasite-based microscopy diagnostic testing. The accuracy of this manual diagnosis method is clearly affected by the level of microscopist's experience, which makes this diagnosis method susceptible to manual error and time consuming. Diagnoses of diseases made using deep-learning methods have had great repercussions in the medical world, especially in recent years; and this indicates that the diagnosis of malaria can also be achieved by deep-learning methods. On the basis of this fact, this paper presents a novel deep-learning-based malaria disease detection technique. A convolutional neural network (CNN) architecture, which has 20 weighted layers is designed and proposed to identify parasitized microscopic images from uninfected microscopic images. A total of 27,558 thin blood cell images were used to train and test the CNN model, and 95.28% overall accuracy was obtained. The experimental results on large clinical dataset show the effectiveness of the proposed deep-learning method for malaria disease detection. [ABSTRACT FROM AUTHOR]

1. Sequence analysis of the NADPH domain (residues 158 - 293) and of the interface domain (365 - 478) was based on 12 CNBr fragments, which were isolated using ion-exchange chromatography and paper methods. Fragments with more than 15 residues were digested further with trypsin and chymotrypsin. The isolated peptides were sequenced by automated solid-phase Edman degradation. All sequenced peptides were ordered and overlapped by computerized comparisons with a complete sequence guessed from the electron density map of the protein. In the case of short CNBr fragments, this alignment was confirmed by the sequence analysis of protein fragments resulting from incomplete CNBr cleavage. 2. In the NADPH domain, residue 197, which is involved in an induced-fit mechanism, was identified as a tyrosine. The structure of the NADPH domain is probably homologous with the NAD domain of lipoamide dehydrogenase and with the FAD domain of several proteins, but not with NADPH domains of known chainfold in other proteins. 3. The paper completes the sequence analysis of glutathione reductase so that the enzyme is now known in atomic detail. The numbering scheme of the chemically determined sequence will be used henceforth in crystallographic studies also. As inferred from the sequence data each of the two identical chains contains 478 amino acid residues, the composition being Cys10, Asp21, Asn17, Thr31, Ser31, Glu29, Gln11, Pro24, Gly43, Ala42, Val44, Met15, Ile29, Leu34, Tyr13, Phe14, Lys34. His16, Arg17, and Trp3. From these data an mr of 2 × 51 600 was calculated for the FAD-free apoenzyme and an Mr of 2 × 52400 for the holoenzyme. [ABSTRACT FROM AUTHOR]

Aims: Blood cell classification helps detect various diseases. However, the current classification model of blood cells cannot always get great results. A network that automatically classifies blood cells can provide doctors with data as one of the criteria for diagnosing patients' disease types and severity. If doctors diagnose blood cells, doctors could spend lots of time on the diagnosis. The diagnosis progress is very tedious. Doctors can make some mistakes when they feel tired. On the other hand, different doctors may have different points on the same patient. Methods: We propose a ResNet50-based ensemble of randomized neural networks (ReRNet) for blood cell classification. ResNet50 is used as the backbone model for feature extraction. The extracted features are fed to 3 randomized neural networks (RNNs): Schmidt neural network, extreme learning machine, and dRVFL. The outputs of the ReRNet are the ensemble of these 3 RNNs based on the majority voting mechanism. The 5 × 5-fold cross-validation is applied to validate the proposed network. Results: The average-accuracy, average-sensitivity, average-precision, and average-F1-score are 99.97%, 99.96%, 99.98%, and 99.97%, respectively. Conclusions: The ReRNet is compared with 4 state-of-the-art methods and achieves the best classification performance. The ReRNet is an effective method for blood cell classification based on these results. [ABSTRACT FROM AUTHOR]

We have previously shown that obesity is associated with increased secretion of IgG antibodies with anti-self-reactivity. In this paper, we confirm and extend our previous findings. We show that the plasma of individuals with obesity is enriched in autoimmune antibodies whose levels are positively associated with blood frequencies of the subset of Double Negative (DN) B cells, which is the most pro-inflammatory B cell subset. We also show that DN B cells, significantly increased in the blood of obese versus lean individuals, are characterized by higher expression of immune activation markers and of the transcription factor T-bet, both associated with autoimmunity. The removal of DN B cells from the peripheral B cell pool significantly decreases in vitro secretion of anti-self IgG antibodies. These results altogether confirm the crucial role of DN B cells in the secretion of anti-self IgG antibodies in individuals with obesity. [ABSTRACT FROM AUTHOR]

Immune checkpoint inhibitors (ICIs) have substantially improved the prognosis of patients with different types of cancer. Through blockade of cytotoxic T-lymphocyte antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1), negative feedback mechanisms of the immune system are inhibited, potentially resulting in very durable anti-tumor responses. Despite their promise, ICIs can also elicit auto-immune toxicities. These immune-related adverse events (irAEs) can be severe and sometimes even fatal. Therefore, being able to predict severe irAEs in patients would be of added value in clinical decision making. A search was performed using "adverse events", "immune checkpoint inhibitor", "biomarker", and synonyms in PubMed, yielding 3580 search results. After screening title and abstract on the relevance to the review question, statistical significance of reported potential biomarkers, and evaluation of the remaining full papers, 35 articles were included. Five additional reports were obtained by means of citations and by using the similar article function on PubMed. The current knowledge is presented in comprehensive tables summarizing blood-based, immunogenetic and microbial biomarkers predicting irAEs prior to and during ICI therapy. Until now, no single biomarker has proven to be sufficiently predictive for irAE development. Recommendations for further research on this topic are presented. [ABSTRACT FROM AUTHOR]

The partial success of tumor immunotherapy induced by checkpoint blockade, which is not antigen-specific, suggests that the immune system of some patients contain antigen receptors able to specifically identify tumor cells. Here we focused on T-cell receptor (TCR) repertoires associated with spontaneous breast cancer. We studied the alpha and beta chain CDR3 domains of TCR repertoires of CD4 T cells using deep sequencing of cell populations in mice and applied the results to published TCR sequence data obtained from human patients. We screened peripheral blood T cells obtained monthly from individual mice spontaneously developing breast tumors by 5 months. We then looked at identical TCR sequences in published human studies; we used TCGA data from tumors and healthy tissues of 1,256 breast cancer resections and from 4 focused studies including sequences from tumors, lymph nodes, blood and healthy tissues, and from single cell dataset of 3 breast cancer subjects. We now report that mice spontaneously developing breast cancer manifest shared, Public CDR3 regions in both their alpha and beta and that a significant number of women with early breast cancer manifest identical CDR3 sequences. These findings suggest that the development of breast cancer is associated, across species, with biomarker, exclusive TCR repertoires. Author summary: More than 1,100 cancer treatments are currently in clinical testing. Of these, 295 are immune-oncology medicines and vaccines. For Checkpoint Immunotherapy alone, 52,539 patients were enrolled in 2017. Of these treatments, 108 are for breast cancer, the leading cancer diagnosed in women. Although checkpoint immunotherapy has yet to be proven beneficial in most types of breast cancer, current observations of which specific T cell go into the tumor, and how these cells are connected to the response to treatment, have lead to a new understating of the role of the immune system. Yet, and in spite of this intense research into the role of T cells in tumors, very little is known about how clones of T cells behave during tumor formation. The paper we present here studies this clonal behavior over time. We study it during mammary tumor development in mice. We see that a set of T cell clones, which comes from a diversity of different nucleotide sequences, stands out in its behavior compared with other T cell clones. Importantly, we show that these mouse T cell clones have a strong connection to human breast cancer. The specific identification of a subset of T cell clones, together with the behavior of these clones over time, is critical to our understanding of the effect of modifications to the immune system, such as the modifications made by immunotherapy treatments, and to our understanding of how to better control the behavior of the immune system. [ABSTRACT FROM AUTHOR]

Background: Hematopoietic stem cell (HSC) transplantation is an effective treatment strategy for many types of diseases. Peripheral blood (PB) is the most commonly used source of bone marrow (BM)-derived stem cells for current HSC transplantation. However, PB usually contains very few HSCs under normal conditions, as these cells are normally retained within the BM. This retention depends on the interaction between the CXC chemokine receptor 4 (CXCR4) expressed on the HSCs and its natural chemokine ligand, stromal cell-derived factor (SDF)-1α (also named CXCL12) present in the BM stromal microenvironment. In clinical practice, blocking this interaction with a CXCR4 antagonist can induce the rapid mobilization of HSCs from the BM into the PB. Methods: C3H/HEJ, DBA/2, CD45.1+, and CD45.2+ mice and monkeys were employed in colony-forming unit (CFU) assays, flow cytometry assays, and competitive/noncompetitive transplantation assays, to assess the short-term mobilization efficacy of HF51116 and the long-term repopulating (LTR) ability of HSCs. Kinetics of different blood cells and the concentration of HF51116 in PB were also explored by blood routine examinations and pharmacokinetic assays. Results: In this paper, we report that a novel small molecule CXCR4 antagonist, HF51116, which was designed and synthesized by our laboratory, can rapidly and potently mobilize HSCs from BM to PB in mice and monkeys. HF51116 not only mobilized HSCs when used alone but also synergized with the mobilizing effects of granulocyte colony-stimulating factor (G-CSF) after co-administration. Following mobilization by HF51116 and G-CSF, the long-term repopulating (LTR) and self-renewing HSCs were sufficiently engrafted in primary and secondary lethally irradiated mice and were able to rescue and support long-term mouse survival. In monkeys, HF51116 exhibited strong HSC mobilization activity and quickly reached the highest in vivo blood drug concentration. Conclusions: These results demonstrate that HF51116 is a new promising stem cell mobilizer which specifically targets CXCR4 and merits further preclinical and clinical studies. [ABSTRACT FROM AUTHOR]

Leukocytes are blood cells involved in the immune response. Leukocytes can be classified into three main groups (granulocytes, lymphocytes, and monocytes), and the measurement of the relative prevalence of each subgroup, termed differential leukocyte count, is an important clinical parameter in the diagnosis and prognosis of various health anomalies. Currently, differential leukocyte counts are obtained either manually through labor-intensive blood smears or by employing bulky hematology analyzers. Both of these measurements require a laboratory setup and hence are not amenable for decentralized and point-of-care settings. In this paper, we introduce a microfluidic assay with an electronic readout for differential leukocyte count assays. Our device classifies leukocyte subgroups based on the differential CD33 expression on cell membranes. In the device, each subgroup is differentially immunocaptured in different microfluidic chambers, while the cell capture rates are quantified by an integrated electronic sensor network. When benchmarked against a commercial hematology analyzer, our device could identify leukocyte subpopulations with differences of <6% for granulocytes and lymphocytes, and a <3% for monocytes. These results demonstrate the potential of our technique as an accurate method to perform the widely-employed hematology assay for point-of-care applications without the need for sample labeling. [2020-0197] [ABSTRACT FROM AUTHOR]

In conditions of abdominal sepsis with indications of first- or second-stage shock, blood cells undergo significant ultrastructural changes that cause impaired gas exchange, changes in reactivity, and decompensation of organs and systems functions. This paper presents a cross-sectional prospective study aimed at researching the ultrastructure of blood cells in children experiencing abdominal septic shock against the background of generalized purulent peritonitis of appendicular origin. This study was conducted with 15 children aged 6–12 who were undergoing treatment for generalized appendicular purulent peritonitis, with first- or second-stage abdominal septic shock, in emergency care. The changes in the ultrastructure of erythrocytes did not correspond to changes characteristic of eryptosis, which confirms their occurrence under the influence of such pathogenic factors as intoxication, metabolic, water–electrolyte balance, and acid–base disorders. Ultrastructural changes of granulocytes indicate their hyperactivation, which leads to the exhaustion of membrane synthetic resources, membrane destruction, ineffective expenditure of bactericidal factors on substrates that are not subject to destruction. In lymphocytes, disorganization of the nuclear membrane and intracellular membranes, uneven distribution of chromatin, the hypertrophied Golgi apparatus, and a large number of young mitochondria, lysosomes, ribosomes, vesicles manifesting the disruption of metabolism, stress and decompensation of energy supply and protein synthesis systems, have been demonstrated. In conditions of abdominal sepsis with indications of first- or second-stage shock, blood cells undergo substantial ultrastructural changes causing gas exchange disruption, changes in reactivity, as well as decompensation of organs and system functioning. [ABSTRACT FROM AUTHOR]

Gene expression atlases have transformed our understanding of the development, composition and function of human tissues. New technologies promise improved cellular or molecular resolution, and have led to the identification of new cell types, or better defined cell states. But as new technologies emerge, information derived on old platforms becomes obsolete. We demonstrate that it is possible to combine a large number of different profiling experiments summarised from dozens of laboratories and representing hundreds of donors, to create an integrated molecular map of human tissue. As an example, we combine 850 samples from 38 platforms to build an integrated atlas of human blood cells. We achieve robust and unbiased cell type clustering using a variance partitioning method, selecting genes with low platform bias relative to biological variation. Other than an initial rescaling, no other transformation to the primary data is applied through batch correction or renormalisation. Additional data, including single-cell datasets, can be projected for comparison, classification and annotation. The resulting atlas provides a multi-scaled approach to visualise and analyse the relationships between sets of genes and blood cell lineages, including the maturation and activation of leukocytes in vivo and in vitro. In allowing for data integration across hundreds of studies, we address a key reproduciblity challenge which is faced by any new technology. This allows us to draw on the deep phenotypes and functional annotations that accompany traditional profiling methods, and provide important context to the high cellular resolution of single cell profiling. Here, we have implemented the blood atlas in the open access Stemformatics.org platform, drawing on its extensive collection of curated transcriptome data. The method is simple, scalable and amenable for rapid deployment in other biological systems or computational workflows. Author summary: Combining data from many different studies is an attractive way of capturing new aspects of the biology being studied. Biological variance attributable to cell type, cellular niche, origin, disease status or environmental stimuli is the basis of most small-n transcriptome studies. In aggregation, these promise to capture emergent dimensions of a biology that is not possible to view from any individual study. However biological signal is easily swamped by technical artifact, especially when data is generated on platforms with profoundly different data structures. This is the case when comparing microarray data to RNAseq, or RNAseq to single cell profiling. Consequently, transcriptome atlases are generally comprised from a small number of donors/conditions surveyed using one technology platform. In this paper we present a simple and scalable data integration method that is platform agnostic. We provide a proof-of-principle by constructing an atlas of blood cells that combines many data sets measured on different platforms, and that in combination, recapitulates the known blood hierarchy. The atlas provides a reference to compare external samples to, allowing users to benchmark new derivation or isolation methods. It also provides a reference point for new data types, such as the classification of single cells. The approach allows for FAIR data reuse and robust identification of molecular signatures across multiple studies and experimental conditions. [ABSTRACT FROM AUTHOR]

Introduction: False-negative malaria rapid diagnostic test (RDT) results amongst symptomatic malaria patients are detrimental as they could lead to ineffective malaria case management. This study determined the nationwide contribution of parasites with Pfhrp2 and Pfhrp 3 gene deletions to false negative malaria RDT results in Ghana. Methods: This was a cross sectional study where whole blood (~2 ml) was collected from patients presenting with malaria symptoms at 100 health facilities in all the regions in Ghana from May to August 2018. An aliquot of the blood was used to prepare thin and thick blood smears, filter paper blood spots (DBS) and spot a PfHRP 2 RDT kit. The remaining blood was separated into plasma and blood cells and stored at -20°C. Plasmodium parasite density and species identity was estimated from the blood smears. Plasmodium falciparum specific 18S rRNA PCR, merozoite surface protein (msp 1) and glutamate rich protein (glurp) gene PCR were used to identify P. falciparum positive samples, which were subjected to Pfhrp 2/3 exon1-2 and exon2 genotyping. Results: Of the 2,860 microscopically P. falciparum positive patients analyzed, 134 (4.69%) had false negative P. falciparum specific RDT results. Samples for PCR analysis was available for 127 of the false negative patients, and the analysis identified 116 (91.3%) as positive for P. falciparum. Only 58.1% (79/116) of the false negative RDT samples tested positive by msp 1 and glurp PCR. Genotyping of exon 1–2 and exon 2 of the Pfhrp 2 gene identified 12.9% (10/79) and 39.5% (31/79) of samples respectively to have deletions. Genotyping exon 1–2 and exon 2 of the Pfhrp 3 gene identified 15.2% (12/79) and 40.5% (32/79) of samples respectively to have deletions. Only 5% (4/79) of the false negative samples had deletions in both exon 1–2 and exon 2 of the Pfhrp 2 gene. Out of the 49 samples that tested positive for aldolase by luminex, 32.6% (16/49) and) had deletions in Pfhrp 2 exon 2 and 2% (1/49) had deletions in both exon 2 and exon 1–2 of the Pfhrp 2 gene. Conclusions: The low prevalence of false negative RDT test results provides assurance that PfHRP 2 based malaria RDT kits remain effective in diagnosing symptomatic malaria patients across all the Regions of Ghana. Although there was a low prevalence of parasites with deletions in exon 2 and exon 1–2 of the Pfhrp 2 gene the prevalence of parasites with deletions in Pfhrp 2 exon 2 was about a third of the false negative RDT results. The need to ensure rapid, accurate and reliable malaria diagnosis requires continuous surveillance of parasites with Pfhrp 2 gene deletions. [ABSTRACT FROM AUTHOR]

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Measurement of telomere length is crucial for the study of telomere maintenance and its role in molecular pathophysiology of diseases and in aging. Several methods are used to measure telomere length, the choice of which usually depends on the type and size of sample to be assayed, as well as cost and throughput considerations. The goal of this study was to investigate the factors that may influence the reliability of qPCR-based relative telomere length measurements in whole blood. Day to day intra-individual variability, types of blood anticoagulant, sample storage conditions, processing and site of blood draw were investigated. Two qPCR-based methods to measure telomere length (monoplex vs. multiplex) were also investigated and showed a strong correlation between them. Freezing and thawing of the blood and storage of the blood at 4°C for up to 4 days did not affect telomere length values. Telomere lengths in dried blood spots were significantly higher than both whole blood and peripheral mononuclear blood cells, and were highly correlated with both. We found that telomere length measurements were significantly higher in dried blood spots collected directly from fingertip prick compared to dried blood spots prepared with anticoagulated whole blood collected from the finger, and non-blotted whole blood taken from both finger and arm venipuncture. This suggests that DNA from cells blotted on paper is not equivalent to that collected from venipuncture whole blood, and caution should be taken when comparing between blood sample types. [ABSTRACT FROM AUTHOR]

Background/Aim. Measles is a contagious disease with a good prognosis; however, severe complications may sometimes develop. C-reactive protein (CRP) and blood cells count-derived inflammatory indices -- granulocytelymphocyte ratio (GLR), platelet to lymphocyte ratio (PLR), monocyte to lymphocyte ratio (MLR), mean platelet volume (MPV)/platelet count ratio (MPR), red blood cell distribution width (RDW), and MPV are the indicators related to the clinical outcome in various inflammatory diseases. The aim of the study was to analyze the values of CRP, blood cell count, GLR, PLR, MLR, MPR, RDW, and MPV in measles-affected children compared to healthy controls and between measles-affected children with complicated and severely complicated measles form. A particular aim of the paper was to assess the suitability of inflammatory-derived markers for predicting the severity of the disease. Methods. The study included 55 measlesaffected children who developed complications (examination group), while the control group included 30 healthy children. The first peripheral blood count, obtained on the first hospitalization day (before treatment), was used for further analyses. Results. The white blood cells, lymphocytes, monocytes, and platelets count were significantly lower, while GLR, PLR, MPR, and CRP were significantly higher in measles-affected children (p < 0.05). In severely complicated measles form, significantly higher values of granulocytes, CRP, GLR, and PLR were documented, including lower lymphocytes (p < 0.05). A linear regression analysis showed that CRP was the only indicator with predictive significance for the severity of the course of measles. Conclusion. The blood cell count-derived inflammatory indices should not be crucial in assessing the severity of measles in children. CRP was the most valuable predictive factor for the development of the severe course of measles in measles-affected children. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

The detection of circulating tumor cells (CTCs) from peripheral blood is considered as great significance for the diagnosis and prognosis of cancer patients. Raman spectroscopy is a highly sensitive optical detection technique that can provide fingerprint molecular identification information. In this paper, the silver film substrate surface-enhanced Raman scattering (SERS) was used to research several tumor cells, immortalized cells, clinical cancer cells isolated from cancer patient's tissue and blood cells. The results display that there is great difference for the nucleic acid characteristic peaks of those cells. The red blood cells have almost none nucleic acid characteristic peak and the SERS signals of white blood cells are only a slight increase. Except for immortalized cells and few tumor cells, the nucleic acid characteristic peaks of some tumor cells have huge enhancement. Nucleic acid characteristic peaks of clinical cancer cells also have greater enhancement. The discriminant model established by the intensity ratio of the nucleic acid characteristic peak 730 cm -1 to the substrate background peak 900 cm -1 shows that some tumor cells and clinical sample cells can be separated from white blood cells, but tumor cells with relatively low-DNA index cannot be differentiated from white blood cells. This study demonstrates that thin-film SERS technology can distinguish between blood cells and some types of tumor cells. This study opens up a new possible method for the detection of CTCs with label-free SERS spectra.

Hematopoietic stem cells (HSCs) provide all types of blood cells during the entire life of the organism. HSCs are mainly quiescent and can eventually enter the cell cycle to differentiate. HSCs are maintained and tightly regulated in a particular environment. The stem cell niche regulates dormancy and awakening. Deregulations of this interplay can lead to hematopoietic failure and diseases. In this paper, we present a Boolean network model that recapitulates HSC regulation in virtue of external signals coming from the niche. This Boolean network integrates and summarizes the current knowledge of HSC regulation and is based on extensive literature research. Furthermore, dynamic simulations suggest a novel systemic regulation of TP53 in homeostasis. Thereby, our model indicates that TP53 activity is balanced depending on external stimulations, engaging a regulatory mechanism involving ROS regulators and RAS activated transcription factors. Finally, we investigated different mouse models and compared them to in silico knockout simulations. Here, the model could recapitulate in vivo observed behaviors and thus sustains our results. [ABSTRACT FROM AUTHOR]

The main reason for the weakening of the body of rabbits is a deficiency of nutrients and biologically ac􀆟ve substances in their diet. The search for non-toxic and highly effec􀆟ve preven􀆟ve drugs of complex ac􀆟on that have a posi􀆟ve effect on the metabolism of minerals in rabbits is of keen interest. Here we present the results of the study of morphological and biochemical parameters of the blood as well as the content of chemical elements in blood plasma in New Zealand White rabbits on the farm in Kyiv region. The paper presents the materials for determining the biochemical status of the body in fa􀆩ening rabbits for the preven􀆟on of microelementoses using a new experimental environmentally friendly tool. The content of total protein, albumin, glucose, total calcium, inorganic phosphorus, total bilirubin, urea, crea􀆟nine, TBA-ac􀆟ve products, Fe, Mn, Cu, Zn, Co and the ac􀆟vity of ALT, AST, LF, and HGT in the blood of New Zealand White rabbits in the first and 50th days of the experiment (before and a􀅌er the use of biologically ac􀆟ve addi􀆟ve "Huminorm plus") are presented here for the first 􀆟me. The use of this addi􀆟ve had a posi􀆟ve effect on haematopoiesis, protein and mineral metabolism, and func􀆟onal status of the liver, which indicates its high efficiency for the preven􀆟on of micronutrient deficiency. "Huminorm Plus" s􀆟mulates poten􀆟al body growth in rabbits up to the age of 90 days. [ABSTRACT FROM AUTHOR]

Negative magnetophoresis is a novel and attractive method for continuous microparticle sorting inside a magnetic medium. In this method, diamagnetic particles are sorted based on their sizes using magnetic buoyancy force and without any labeling process. Although this method provides some attractive features, such as low-cost fabrication and ease of operation, there are some obstacles that adversely affect its performance, especially for biological applications. Most types of magnetic media, such as ferrofluids, are not biocompatible, and the time-consuming process of sample preparation can be threatening to the viability of the cells within the sample. Furthermore, in this method, both the target and non-target particles are affected by the magnetic field, and therefore, a high separation efficiency cannot be achieved. In this paper, to isolate the abnormal cells from the other blood cells, a microfluidic device was designed using numerical simulation. This model utilizes negative magnetophoresis on a rotating disk, and to reduce the exposure time of the cells inside the magnetic medium, a micromixer is embedded in the upstream of the separator which rapidly prepares the sample. In this part, diluted blood sample and ferrofluid are mixed together utilizing magnetic force. Afterward, the separator sorts the cells into multiple outlets using magnetic buoyancy force as well as centrifugal force. The numerical procedure employed in this study shows that the proposed model is able to recover ∼100% of the abnormal cells from a particular outlet for binary and ternary separation of the cells with high throughputs. Although this percentage of separation may be lower in reality, the optimization of the proposed design by the numerical method can avoid trial-and-error during costly and time-consuming experiments. Also, the device proposed in this study reduces the exposure time of the cells inside the ferrofluid to just a few seconds, which can improve cell viability. [ABSTRACT FROM AUTHOR]

In microscopy, laboratory tests make use of cell counters or flow cytometers to perform tests on blood cells, like the complete blood count, rapidly. However, a manual blood smear examination is still needed to verify the counter results and to monitor patients under therapy. Moreover, the manual inspection permits the description of the cells' appearance, as well as any abnormalities. Unfortunately, manual analysis is long and tedious, and its result can be subjective and error-prone. Nevertheless, using image processing techniques, it is possible to automate the entire workflow, both reducing the operators' workload and improving the diagnosis results. In this paper, we propose a novel method for recognizing white blood cells from microscopic blood images and classify them as healthy or affected by leukemia. The presented system is tested on public datasets for leukemia detection, the SMC-IDB, the IUMS-IDB, and the ALL-IDB. The results are promising, achieving 100% accuracy for the first two datasets and 99.7% for the ALL-IDB in white cells detection and 94.1% in leukemia classification, outperforming the state-of-the-art. [ABSTRACT FROM AUTHOR]

Image-processing methods are applied in many environments to solve various practical problems. Recently, considerable research has been conducted on analysing retinal images, which show the blood vessels in the human eye, to detect diseases in patients. Various diseases related to the eyes can be located by detecting changes in the retinal blood cells. This paper proposes two analysis methods, namely the fuzzy c-means and neuro-fuzzy methods, which analyse optical coherence tomography images of retinal blood cells. The system was implemented in a MATLAB experimental setup, while the efficiency was evaluated with respect to time and accuracy. The performance analysis of the fuzzy c-means and neuro-fuzzy systems indicates that the neuro-fuzzy system has a higher accuracy (93.16%) and a lower processing time (2 s) than the k-means clustering, expectation maximisation, fuzzy clustering and neural network methods. [ABSTRACT FROM AUTHOR]

The Epstein-Barr virus (EBV) induces B-cell proliferation with high efficiency through expression of latent proteins and microRNAs. This process takes place in vivo soon after infection, presumably to expand the virus reservoir, but can also induce pathologies, e.g. an infectious mononucleosis (IM) syndrome after primary infection or a B-cell lymphoproliferation in immunosuppressed individuals. In this paper, we investigated the growth characteristics of EBV-infected B-cells isolated from transplant recipients or patients with IM. We found that these cells grew and withstood apoptosis at highly variable rates, suggesting that the expansion rate of the infected B-cells widely varies between individuals, thereby influencing the size of the B-cell reservoir and the ability to form tumors in infected individuals. All viruses investigated were type 1 and genetically close to western strains. EBV-infected B-cells expressed the transforming EBV latent genes and microRNAs (miRNAs) at variable levels. We found that the B-cell growth rates positively correlated with the BHRF1 miRNA levels. Comparative studies showed that infected B-cells derived from transplant recipients with iEBVL on average expressed higher levels of EBV miR-BHRF1 miRNAs and grew more rapidly than B-cells from IM patients, suggesting infection by more transforming viruses. Altogether, these findings suggest that EBV infection has a highly variable impact on the B-cell compartment that probably reflects the genetic diversity of both the virus and the host. It also demonstrates the unexpected finding that B-cells from different individuals can grow at different speed under the influence of the same virus infection. [ABSTRACT FROM AUTHOR]

Leukemia is type of cancer in blood which impacts the lymphatic framework and the bone marrow and also impacts white blood cells. Leukemia, in contrast to other types of cancer, does not produce solid tumors; instead, it produces a huge number of aberrant white blood cells that crowd out the healthy blood cells. Machine learning algorithms that are widely utilized in the treatment of leukemia, whether it is to classify the various forms of leukemia or to determine whether a patient has the disease. It is a malignant kind of cancer that results in a number of medical issues. Expert hematologists and pathologists manually examine blood samples under the microscope to make a diagnosis. Techniques like image processing and pattern recognition can be utilized to help these experts. In order to attain excellent performance in the categorization of malignant leukocytes challenge, this paper suggests straightforward modifications to conventional neural network topologies. Consequently, there is considerable interest in the trustworthy and precise recognition of nonmalignant and malignant cells. Leukemia can be automatically detected using computer-aided diagnostic (CAD) models, which can help doctors and be useful for leukemia early identification. In this single-center study, we attempted to develop a deep learning model for classification of leukemic B-lymphoblasts. Data augmentation methods were utilized to manage the little dataset size and an exchange learning technique was utilized to accelerate learning and upgrade the presentation of the recommended network in order to create a trustworthy and accurate deep learner. The outcomes demonstrate that our suggested approach surpassed seperate networks with a test accuracy of 95.59% in the Leukemic B-lymphoblast examination, and was caable to merge characteristics extracted from the top deep learning models. [ABSTRACT FROM AUTHOR]

Non-coding RNA expression has shown to have cell type-specificity. The regulatory characteristics of these molecules are impacted by changes in their expression levels. We performed next-generation sequencing and examined small RNA-seq data obtained from 6 different types of blood cells separated by fluorescence-activated cell sorting of severe COVID−19 patients and healthy control donors. In addition to examining the behavior of piRNA in the blood cells of severe SARS-CoV−2 infected patients, our aim was to present a distinct piRNA differential expression portrait for each separate cell type. We observed that depending on the type of cell, different sorted control cells (erythrocytes, monocytes, lymphocytes, eosinophils, basophils, and neutrophils) have altering piRNA expression patterns. After analyzing the expression of piRNAs in each set of sorted cells from patients with severe COVID−19, we observed 3 significantly elevated piRNAs - piR−33,123, piR−34,765, piR−43,768 and 9 downregulated piRNAs in erythrocytes. In lymphocytes, all 19 piRNAs were upregulated. Monocytes were presented with a larger amount of statistically significant piRNA, 5 upregulated (piR−49039 piR−31623, piR−37213, piR−44721, piR−44720) and 35 downregulated. It has been previously shown that piR−31,623 has been associated with respiratory syncytial virus infection, and taking in account the major role of piRNA in transposon silencing, we presume that the differential expression patterns which we observed could be a signal of indirect antiviral activity or a specific antiviral cell state. Additionally, in lymphocytes, all 19 piRNAs were upregulated. [ABSTRACT FROM AUTHOR]

Background: Hematopoiesis in mammal is a complex and highly regulated process in which hematopoietic stem cells (HSCs) give rise to all types of differentiated blood cells. Previous studies have shown that hairy and enhancer of split (HES) repressors are essential regulators of adult HSC development downstream of Notch signaling. Methods: In this study, we investigated the role of HES1, a member of HES family, in fetal hematopoiesis using an embryonic hematopoietic specific Hes1 conditional knockout mouse model by using phenotypic flow cytometry, histopathology analysis, and functional in vitro colony forming unit (CFU) assay and in vivo bone marrow transplant (BMT) assay. Results: We found that loss of Hes1 in early embryonic stage leads to smaller embryos and fetal livers, decreases hematopoietic stem progenitor cell (HSPC) pool, results in defective multi-lineage differentiation. Functionally, fetal hematopoietic cells deficient for Hes1 exhibit reduced in vitro progenitor activity and compromised in vivo repopulation capacity in the transplanted recipients. Further analysis shows that fetal hematopoiesis defects in Hes1fl/flFlt3Cre embryos are resulted from decreased proliferation and elevated apoptosis, associated with de-repressed HES1 targets, p27 and PTEN in Hes1-KO fetal HSPCs. Finally, pharmacological inhibition of p27 or PTEN improves fetal HSPCs function both in vitro and in vivo. Conclusion: Together, our findings reveal a previously unappreciated role for HES1 in regulating fetal hematopoiesis, and provide new insight into the differences between fetal and adult HSC maintenance. [ABSTRACT FROM AUTHOR]