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In modern clinical medicine, the important information of red blood cells, such as shape and number, is applied to detect blood diseases. However, the automatic recognition problem of single cells and adherent cells always exists in a densely distributed medical scene, which is difficult to solve for both the traditional detection algorithms with lower recognition rates and the conventional networks with weaker feature extraction capabilities. In this paper, an automatic recognition method of adherent blood cells with dense distribution is proposed. Based on the Faster R-CNN, the balanced feature pyramid structure, deformable convolution network, and efficient pyramid split attention mechanism are adopted to automatically recognize the blood cells under the conditions of dense distribution, extrusion deformation, adhesion and overlap. In addition, the Align algorithm for region of interest also contributes to improving the accuracy of recognition results. The experimental results show that the mean average precision of cell detection is 0.895, which is 24.5% higher than that of the original network model. Compared with the one-stage mainstream networks, the presented network has a stronger feature extraction capability. The proposed method is suitable for identifying single cells and adherent cells with dense distribution in the actual medical scene. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the multiplicity of positive periodic solutions of a discrete blood cell production model with impulse effects. This model is described by periodic coefficients and time delays, as well as nonlinear feedback with exponential terms. By employing the Krasnosel'skii fixed point theorem, we establish a sufficient condition for the existence of at least two positive periodic solutions. To this end, we construct solution transformation between an impulsive delay difference equation and the corresponding nonimpulsive delay difference equation. Aditionally, a solution representation of the positive periodic solution of the blood cell production model is presented. Moreover, a numerical example and its simulations are given to illustrate the main result. [ABSTRACT FROM AUTHOR]

The activity of the mechanosensitive Ca2+ permeable channels expressed in the membrane of the red blood cells (RBC) is determined both by the mechanical stimuli and the mechanical properties of the cell. Therefore, it is of most importance to correlate the triggering stimulus with the mechanical properties. In this paper, we propose an approach to determine the activation pressure of the mechanosensitive channels and concomitantly evaluate cell mechanical properties as Young's Modulus, membrane tension and viscosity, for individual cells. Cell deformation was accomplished by micropipette aspiration with a controlled pressure ramp and recorded by brightfield imaging to determine the mechanical properties. The Ca2+ transient was concomitantly monitored by fluorescence imaging, to get the activation pressure. The technique was validated comparing the behavior of three pools of RBCs, probed at different intervals of time after the cell suspension preparation by the same mechanical stimuli. We found relevant changes of the activation pressure, associated with the alteration of the mechanical properties, the latest becoming significant with the passage of time. Our approach opens a new direction to investigate the correlation between mechanosensitivity and mechanical properties for individual RBCs, which can be extended to other cells, in suspension or plated, under controlled environmental conditions. [ABSTRACT FROM AUTHOR]

Continuously recording the dynamic changes of circulating tumor cells (CTCs) is crucial for tumor metastasis. This paper creates a continuous magnetic separation microfluidic chip that enables rapid and continuous in vivo cell detection. The chip shows its potential to study tumor cell circulation in the blood, offering a new platform for studying the cellular mechanism of tumor metastasis. [ABSTRACT FROM AUTHOR]

Particle counting serves as a pivotal constituent in diverse analytical domains, encompassing a broad spectrum of entities, ranging from blood cells and bacteria to viruses, droplets, bubbles, wear debris, and magnetic beads. Recent epochs have witnessed remarkable progressions in microfluidic chip technology, culminating in the proliferation and maturation of microfluidic chip-based particle counting methodologies. This paper undertakes a taxonomical elucidation of microfluidic chip-based particle counters based on the physical parameters they detect. These particle counters are classified into three categories: optical-based counters, electrical-based particle counters, and other counters. Within each category, subcategories are established to consider structural differences. Each type of counter is described not only in terms of its working principle but also the methods employed to enhance sensitivity and throughput. Additionally, an analysis of future trends related to each counter type is provided. [ABSTRACT FROM AUTHOR]

Pathology reports are necessary for specialists to make an appropriate diagnosis of diseases in general and blood diseases in particular. Therefore, specialists check blood cells and other blood details. Thus, to diagnose a disease, specialists must analyze the factors of the patient's blood and medical history. Generally, doctors have tended to use intelligent agents to help them with CBC analysis. However, these agents need analytical tools to extract the parameters (CBC parameters) employed in the prediction of the development of life-threatening bacteremia and offer prognostic data. Therefore, this paper proposes an enhancement to the Rabin–Karp algorithm and then mixes it with the fuzzy ratio to make this algorithm suitable for working with CBC test data. The selection of these algorithms was performed after evaluating the utility of various string matching algorithms in order to choose the best ones to establish an accurate text collection tool to be a baseline for building a general report on patient information. The proposed method includes several basic steps: Firstly, the CBC-driven parameters are extracted using an efficient method for retrieving data information from pdf files or images of the CBC tests. This will be performed by implementing 12 traditional string matching algorithms, then finding the most effective ways based on the implementation results, and, subsequently, introducing a hybrid approach to address the shortcomings or issues in those methods to discover a more effective and faster algorithm to perform the analysis of the pathological tests. The proposed algorithm (Razy) was implemented using the Rabin algorithm and the fuzzy ratio method. The results show that the proposed algorithm is fast and efficient, with an average accuracy of 99.94% when retrieving the results. Moreover, we can conclude that the string matching algorithm is a crucial tool in the report analysis process that directly affects the efficiency of the analytical system. [ABSTRACT FROM AUTHOR]

Accurate real-time detection of platelets and white blood cells (WBCs) is crucial to the diagnosis of clinical disease and blood cell classification. This paper proposes a lightweight and advanced feature fusion single shot multibox detector (LAFSSD) model to enhance the multi-scale detection capability of platelets and WBCs. To generate a more effective multi-scale feature fusion module composed of depthwise separable convolution, the model first substitutes VGG16, the basic backbone of the FSSD model, with a lightweight MobileNet network. Afterward, the K-means clustering algorithm is used to modify the aspect ratio and size of the default box. The CBAM attention modules in the multi-scale feature map of LAFSSD's structure are added to further enhance the detection of platelets and WBCs. Finally, the RMSProp gradient descent algorithm is used to decrease the irregular oscillations of the loss function. The experimental outcomes demonstrate that the mAP of the LAFSSD model is 98.4%, a rise of 24.7% from before the enhancement. Our model can precisely and in real-time detect platelets and WBCs at multiple scales of different sizes and shapes in human peripheral blood smear images. [ABSTRACT FROM AUTHOR]

Certain therapies that target CD markers on some blood cells can affect pretransfusion testing. Key examples are anti‐CD38, CD47 monoclonal antibody (mAb) therapies such as daratumumab (DARA) and magrolimab, which have presented a challenge for transfusion medicine laboratories around the globe. Scientists have been faced with not only introducing a protocol to provide safe blood to patients but also investigating the most effective method to remove the pretransfusion pan‐agglutinating interference caused. A number of papers in the last 5 years have reported on various methods to remove pretransfusion interference; however, most of these studies have been conducted only in a few countries. Most recent reviews on this topic have focused on techniques and reagents to remove pretransfusion interference, and dithiothreitol is currently the gold standard for removing DARA interference. However, it was clear from this review that while many laboratories have developed processes for addressing interference in pretransfusion testing, and DARA interference may not be a major issue, there are still laboratories around the world, that may not have adequately addressed this issue. In addition, the impact of mAb interference on widely used techniques such as flow cytometry is unclear. [ABSTRACT FROM AUTHOR]

Sepsis is a potentially life-threatening condition triggered by pathogens such as bacteria and toxins. In clinical settings, hemoperfusion has been used as a therapeutic technique for the treatment of sepsis to remove pathogens, toxins and other inflammatory mediators from the bloodstream. However, the existing adsorption process of hemoperfusion is not specific to sepsis-related pathogens or toxins, resulting in unsatisfactory removal effectiveness and the lack of capture selectivity. Herein, we developed an ultrasound-responsive asymmetric polymeric microbowl coated with macrophage and red blood cell (RBC) membranes to selectively eliminate pathogens, toxins, and heavy metal ions from blood. Poly(glycidyl methacrylate) spherical microparticles were first synthesized and then eroded using dibutyl phthalate and styrene to form a microbowl structure. This asymmetric structure could provide acoustic radiation pressure gradients to realize orientation motion under non-invasive ultrasound fields with a velocity of 37.14 μm s−1 at 20 Vp–p, which could increase adsorption efficiency in physiological environments by fuel-free programable movements. In addition, the macrophage and RBC membrane coating endowed the microbowl with desired biocompatibility, enhanced blood circulation and the ability to selectively eliminate endotoxins, bacteria and heavy metal ions. Endotoxin removal assay showed that 92.80% of endotoxin was eliminated within 15 minutes. Owing to the affinity between the red blood cell membrane and heavy metal ions, the removal efficiency reached 92.75% and 93.91% for Pb2+ and Hg2+, respectively. Meanwhile, over 90% of S. aureus in the blood was eliminated owing to the selective recognition and adhesion of bacteria by macrophage membrane proteins. Overall, this work on ultrasound-responsive asymmetric polymeric microbowls provides a new insight to eliminate pathogens, toxins and heavy metal ions from the bloodstream for sepsis treatment. [ABSTRACT FROM AUTHOR]

Background: Muscle damage leads to increased serum creatine kinase (CK) levels in diseases such as acute myocardial infarction. Still, many individuals have abnormal serum CK activities lacking muscle-related diagnoses. The current study hypothesized that failed or overactivated CK clearance by non-muscle organs/tissues might be responsible for increased or decreased CK activities in blood., Methods: We analyzing 37,081 independent CK test results in 36 human diseases during the past 5 y., Results: We found that 33 out of 36 diseases were associated with decreased median CK activities compared to healthy controls. Besides muscle damage-related conditions, the highest mean CK activities were observed in hepatitis and cirrhosis. In contrast, 6 blood cell-related illnesses had the lowest mean CK values. ROC analysis showed that CK activities were the best biomarkers (AUC: 0.80-0.94) for the 6 blood-related diseases, especially myeloproliferative disorders. The principal component analysis revealed that the same category of diseases, such as liver-, blood -, kidney-, cancers, and vascular-related diseases, had clustered CK distributions., Conclusions: We proposed that the liver and blood cells were mainly responsible for CK clearance in blood circulation based on overall results. The testable mechanisms were presented and discussed., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

White blood cells (WBCs) play a main role in identifying the health condition and disease characteristics of a normal person. An automated classification system is capable of recognizing white blood cells that may help doctors to diagnose several diseases like malaria, anemia, leukemia, etc. Automated blood cell analysis allows fast and accurate outcomes and often involves broad data without performance negotiation. The state-of-the-art systems use a lot of different stages (feature extraction, segmentation, pre-processing, etc.) to provide the automated blood cell analysis using blood smear images which is a lengthy process. To overcome these problems, this paper presents an efficient peripheral blood cell image recognition and classification using a combination of the salp swarm algorithm and the cat swarm optimization (SSPSO) algorithm-based optimized convolutional neural networks (SSPSO-CNN) method. This paper uses the CNN approach to classify five peripheral blood cells such as eosinophil, basophil, lymphocytes, monocytes, and neutrophils without any human intervention. The other objective of this paper is to propose an improved version of salp swarm optimizer (SSO) using particle swarm optimization (PSO) to attain competitive classification performance over the database of the blood cell images. In this paper, the CNN uses VGG19 architecture for training purposes. The accuracy of the classification achieved with VGG19 models is 98%. The proposed model based on the CNN approach optimized by SSPSO achieves high classification accuracy and provides automatic peripheral blood cell classification. This method establishes the fine-tuning process to develop a classifier trained using 10 674 images obtained from medical practice. The proposed method augmented the performance in terms of high precision and F 1-score and obtained an overall classification accuracy of 99%. [ABSTRACT FROM AUTHOR]

Traditional auto-focusing techniques identify the focal plane by searching the peak or valley value of the key function. However, the sensitivity around the peak or valley value is low, which increases the difficulty of determining the optimal focusing position. In this paper, a digital holographic microscopy auto-focusing method using differential spectral score is proposed. Firstly, two virtual detectors are placed on both sides of the real detector at the same distance. Then, two focusing ordinary curves and one differential spectrum score (DSS) curve are obtained by using the spectral score function. Finally, the focal plane is automatically identified by searching the zero crossing of DSS curve. This paper illustrates the validity of the proposed method with samples, such as USAF resolution target, Hela cell and blood smear. The results indicate that the proposed method yields better applicability and computation efficiency than the tradition methods. [ABSTRACT FROM AUTHOR]

The combination of a blood cell analyzer and artificial microscopy to detect white blood cells is used in hospitals. Blood cell analyzers not only have large throughput, but they also cannot detect cell morphology; although artificial microscopy has high accuracy, it is inefficient and prone to missed detections. In view of the above problems, a method based on Fourier ptychographic microscopy (FPM) and deep learning to detect peripheral blood leukocytes is proposed in this paper. Firstly, high-resolution and wide-field microscopic images of human peripheral blood cells are obtained using the FPM system, and the cell image data are enhanced with DCGANs (deep convolution generative adversarial networks) to construct datasets for performance evaluation. Then, an improved DETR (detection transformer) algorithm is proposed to improve the detection accuracy of small white blood cell targets; that is, the residual module Conv Block in the feature extraction part of the DETR network is improved to reduce the problem of information loss caused by downsampling. Finally, CIOU (complete intersection over union) is introduced as the bounding box loss function, which avoids the problem that GIOU (generalized intersection over union) is difficult to optimize when the two boxes are far away and the convergence speed is faster. The experimental results show that the mAP of the improved DETR algorithm in the detection of human peripheral white blood cells is 0.936. In addition, this algorithm is compared with other convolutional neural networks in terms of average accuracy, parameters, and number of inference frames per second, which verifies the feasibility of this method in microscopic medical image detection. [ABSTRACT FROM AUTHOR]

Blood cells play an important role in the metabolism of the human body, and the status of blood cells can be used for clinical diagnoses, such as the ratio of different blood cells. Therefore, blood cell classification is a primary task, which requires much time for manual analysis. The recent advances in computer vision can be beneficial to free doctors from tedious tasks. In this paper, a novel automated blood cell classification model based on the shifted window vision transformer (SW-ViT) is proposed. The SW-ViT architecture is firstly pre-trained on the ImageNet dataset and fine-tuned on the blood cell images for classification. Two transfer strategies are employed to generate better classification results. One is to fine-tune the entire SW-ViT, and the other is to only fine-tune the linear output layer of the SW-ViT while all the other parameters are frozen. A public dataset named BCCD_Dataset (Blood Cell Count and Detection) is utilized in the experiments. The results show that the SW-ViT outperforms several state-of-the-art methods in terms of classification accuracy. The proposed SW-ViT can be applied in daily clinical diagnosis. [ABSTRACT FROM AUTHOR]

In the human body, white blood cells (WBCs) are crucial immune cells that help in the early detection of a variety of illnesses. Determination of the number of WBCs can be used to diagnose conditions such as hematological, immunological, and autoimmune diseases, as well as AIDS and leukemia. However, the conventional method of classifying and counting WBCs is time-consuming, laborious, and potentially erroneous. Therefore, this paper presents a computer-assisted automated method for recognizing and detecting WBC categories from blood images. Initially, the blood cell image is preprocessed and then segmented using an effective deep learning architecture called SegNet. Then, the important features are devised and extracted using the EfficientNet architecture. Finally, the WBCs are categorized into four different types using the XGBoost classifier: neutrophils, eosinophils, monocytes, and lymphocytes. The advantages of SegNet, EfficientNet, and XGBoost make the proposed model more robust and achieve a more efficient classification of the WBCs. The BCCD dataset is used to evaluate the performance of the proposed methodology, and the findings are compared to existing state-of-the-art approaches based on accuracy, precision, sensitivity, specificity, and F1-score. Evaluation results show that the proposed approach has a higher rank-1 accuracy of 99.02% and outperformed other existing techniques. [ABSTRACT FROM AUTHOR]

In this paper we present an automatic method for leukocyte classification using support vector machines in multiple stages that results in higher accuracy and less overfitting than other automatic methods. White blood cells (WBC), also called leukocytes, play an important role in the immune system to help protect the body from virus and bacterial diseases. Leukocyte tests can help diagnose a number of diseases related to blood disorders such as acute leukemia, chronic myeloid leukemia. Manual blood cell classification is commonly used in clinics and hospitals, automated cell classification systems may assist clinicians to increase efficiency and accuracy of diagnosis. In recent years, along with the development of artificial intelligence, there have been many studies using automatic methods to classify and count leukocytes. In this paper, we propose a Multi-stage support vector machine method (Multistage SVM) to classify leukocytes into 4 classes with 93% accuracy and less overfitting than other automatic methods. [ABSTRACT FROM AUTHOR]

Long non-coding RNA (LncRNA) is a class of non-coding RNA comprising more than 200 nucleotides. Several studies report that LncRNAs are widely involved in biological processes such as DNA methylation, histone modification, and chromatin remodeling. LncRNA interacts with DNA, RNA, and protein molecules thus regulating expression of target genes. LncRNAs are associated with occurrence and development of tumors, nervous systems, metabolic diseases, reproductive development, and cardiovascular diseases. Therefore, LncRNAs are implicated in progression of several diseases. Studies report that LncRNA plays a crucial role in regulation of gene expression during proliferation and differentiation stages of red blood cell development. LncRNA promotes development of hematopoietic stem cells and plays an important role in myeloid and lymphatic function. In this paper, studies on regulatory mechanism of LncRNA in blood cells and pathogenesis in hematological malignancies were reviewed., Competing Interests: Declaration of Competing Interest The authors declare no competing interests., (Copyright © 2022 Elsevier B.V. All rights reserved.)

In this paper, a microfluidic device is introduced based on direct current (dc) dielectrophoresis for the separation of circulating tumor cells from normal blood cells. Differential sidewall electrodes are designed inside the channel and two middle-channel outlets are located after the end of the electrodes, which are assigned to collect the normal blood cells. A maximum dc potential of 3 V is applied to the electrodes, resulting in a differential dielectrophoretic forces acting on the cells. This paper involves isolating MCF-7 breast cancer cells from white blood cells (WBCs) and red blood cells (RBCs), eliminating the demand for primary RBC lysis. Numerical simulation results revealed that the differential electrodes not only suppressed successfully the need for high applied voltages by dc dielectrophoresis but also diminished the joule heating effects. Besides that, the arrangement of the differential electrodes was observed to play a critical role in the separation performance. In particular, designing the outlets, as well as adjusting the electrode potentials, has effectively assisted the device to be tunable for different cancer cells even with different radii. More strikingly, the ability of the device to deflect the waste cells (WBCs and RBCs) to out of the microchannel prior to the cancer cells was proven to positively affect the separation efficiency and purity. The proposed device was capable of separating different cells leveraging various diameters with capture purity and efficiency of higher than 83% and 100%, respectively. [ABSTRACT FROM AUTHOR]

Leukocyte count is routinely performed for diagnostic purposes and is rapidly emerging as a significant biomarker for a wide array of diseases. Additionally, leukocytes have demonstrated considerable promise in novel cell-based immunotherapies. However, the direct retrieval of leukocytes from whole blood is a significant challenge due to their low abundance compared to erythrocytes. Here, we introduce a microfluidic-based platform that isolates and recovers leukocytes from diluted whole blood in a single step. Our platform utilizes a novel, sheathless method to initially sediment and focus blood cells into a dense stream while flowing through a tubing before entering the microfluidic device. A hexagonal-shaped structure, patterned at the device's inlet, directs all the blood cells against the channel's outer walls. The focused cells are then separated based on their size using the deterministic lateral displacement (DLD) microfluidic technique. We evaluated various parameters that could influence leukocyte separation, including different focusing structures (assessed both computationally and experimentally), the orientation of the tubing-chip interface, the effects of blood sample hematocrit (dilution), and flow rate. Our device demonstrated the ability to isolate leukocytes from diluted blood with a separation efficiency of 100%, a recovery rate of 76%, and a purity of 80%, while maintaining a cell viability of 98%. The device operates for over 30 min at a flow rate of 2 μL min-1. Furthermore, we developed a handheld pressure controller to drive fluid flow, enhancing the operability of our platform outside of central laboratories and enabling near-patient testing. Our platform can be integrated with downstream cell-based assays and analytical methods that require high leukocyte purity (80%), ranging from cell counting to diagnostics and cell culture applications. [ABSTRACT FROM AUTHOR]

Hematopoietic stem cells are a group of heterogeneity cells with the potential to differentiate into various types of mature blood cells. Their basic biological properties include quiescence, self-renewal, multilineage differentiation, and homing ability, with the homing of exogenous hematopoietic stem cells after transplantation becoming a new focus, while the first three properties share some similarity in mechanism due to connectivity. In various complex mechanisms, the role of E3 ubiquitin ligases in hematopoietic homeostasis and malignant transformation is receiving increasing attention. As a unique part, E3 ubiquitin ligases play an important role in physiological regulation mechanism of posttranslational modification. In this review, we focus on the recent progress of the crucial role of E3 ubiquitin ligases that target specific proteins for ubiquitination to regulate biological properties of hematopoietic stem cells. Additionally, this paper deals with E3 ubiquitin ligases that affect the biological properties through aging and summarizes the relevant applications of targeting E3 ligases in hematopoietic malignancies. We present some ideas on the clinical application of E3 ubiquitin ligase to regulate hematopoietic stem cells and also believe that it is meaningful to study the upstream signal of these E3 ubiquitin ligases because hematopoietic stem cell dysfunction is caused by deficiency of some E3 ligases. [ABSTRACT FROM AUTHOR]

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The phenomenon of bifurcation in disease transmission models has been observed in a number of epidemiological models. The consequence of bifurcation is that the classical requirement of the reproduction number being less than unity becomes only a necessary, but not sufficient, for disease elimination. This paper addresses the problem of finding the causes of bifurcation in standard deterministic models for the spread of HBV diseases with non-Cytolytic cure processes on infected liver and blood cells. The model contains logistic growth of healthy liver and blood cells and non -Cytolytic cure processes of infected cells. I have got that the model exhibits back ward and forward bifurcations with some conditions. The existence of a backward bifurcation is an interesting artifact since this means that the disease cannot be eradicated by simply reducing the value of the basic reproduction number R 0 below 1.This can have important implications on drug therapy protocols, since it sheds light on possible control mechanisms for disease eradication. [ABSTRACT FROM AUTHOR]

Inertial microfluidics is a high‐throughput and high‐efficiency cell separation approach to which attention has been progressively paid in recent years. However, research on the influencing factors that compromise the efficiency of cell separation is still lacking. Therefore, the aim of this study was to evaluate the cell separation efficiency by changing the influencing factors. A four‐ring inertial focusing spiral microchannel was designed to separate two kinds of circulating tumor cells (CTCs) from blood. Human breast cancer (MCF‐7) cells and human epithelial cervical cancer (HeLa) cells enter the four‐ring inertial focusing spiral microchannel together with blood cells, and cancer cells and blood cells were separated from each other at the outlet of the channel by inertial force. The cell separation efficiency at the inlet flow rate in the Reynolds number range of 40–52 was studied by changing the influencing factors such as the cross‐sectional shape of the microchannel, the average thickness of the cross‐section, and the trapezoidal inclination angle. The results showed that the reduction of the channel thickness and the increase of a certain trapezoidal inclination enhanced the cell separation efficiency to a certain extent, the study showed that when the channel inclination was 6 ° and the average channel thickness was 160 μm. The two kinds of CTC cells could be completely separated from the blood and the efficiency could reached 100%. Significance statement: In this study, a helical inertial focusing microchannel was designed by summarizing the previous experiences. Based on the previous studies, the influences of the channel factors on the separation efficiency and focusing range of two circulating tumor cells (CTCs) in blood cells were studied. In this paper, three important influencing factors, namely channel Reynolds number, channel inclination and average channel thickness, were systematically summarized, the changes of these three influencing factors, the separation efficiency of CTCs, and the focus range were drawn in detail, and the channel itself factors which were most suitable for the separation of two CTCs in blood were summarized. This will lay a foundation for subsequent research on the influence of channel factors on the focusing effect and separation efficiency of particles in the channel [ABSTRACT FROM AUTHOR]

The paper presents experimental data on the determination of preservation rate of human cord blood nucleated cells and their apoptosis/necrosis stages to determine the number of viable functionally active cells after cryopreservation in solutions with different concentrations of DMSO and the water-soluble analogue of vitamin E, the antioxidant trolox. Counting the number of human cord blood nucleated cells after freezing in media with the addition of trolox revealed their maximum preservation in the samples with 7.5% DMSO and 50, 70 or 200 μM of the antioxidant. Using the flow cytometry with the addition of the Annexin V FITC reagent, which specifically binds to phospholipids, and the DNA dye 7-amino-actinomycin D (7-AAD), it was established that trolox in concentrations of 50-70 μM provided an increase in the number of viable cells with intact membrane (AnnexinV─/7AAD─) by 12-16% compared to the control, which involved the use of only DMSO in the cryoprotective solution. The obtained results indicate the effectiveness of using the antioxidant trolox and the prospects of developing trolox-containing cryoprotective mixtures for freezing and long-term storage of nucleated cord blood cells, including hematopoietic progenitor cells. [ABSTRACT FROM AUTHOR]

(1) Hematological malignancies are characterized by an immortalization, uncontrolled proliferation of blood cells and their differentiation block, followed by the loss of function. The primary goal in the treatment of leukemias is the elimination of rapidly proliferating leukemic cells (named blasts). However, chemotherapy, which removes proliferating blasts, also prevents the remaining immune cells from being activated. Acute leukemias affect elderly people, who are often not fit to survive aggressive chemotherapy. Therefore, there is a need of milder treatment, named differentiation therapy, which might simulate the immune system of the patient. 1,25-Dihydroxyvitamin D, or low-calcemic analogs of this compound, were proposed as supporting therapy in acute leukemias. (2) Bone marrow blasts from patients with hematological malignancies, and leukocytes from healthy volunteers were ex vivo exposed to 1,25-dihydroxyvitamin D, and then their genomes and transcriptomes were investigated. (3) Our analysis indicates that 1,25-dihydroxyvitamin D regulates in blood cells predominantly genes involved in immune response, such as CAMP (cathelicidin antimicrobial peptide), CP (ceruloplasmin), CXCL9 (C-X-C motif chemokine ligand 9), CD14 (CD14 molecule) or VMO1 (vitelline membrane outer layer 1 homolog). This concerns blood cells from healthy people, as well as blasts from patients with hematological malignancies. In addition, in one patient, 1,25-dihydroxyvitamin D significantly downregulated transcription of genes responsible for cell division and immortalization. (4) In conclusion, the data presented in this paper suggest that addition of 1,25-dihydroxyvitamin D to the currently available treatments would stimulate immune system, inhibit proliferation and reduce immortal potential of blasts. [ABSTRACT FROM AUTHOR]

Alterations in intestinal function play a crucial role in the pathogenesis of sepsis, and the repair of the intestinal barrier is a potential strategy for the treatment of sepsis. Sestrin2 (SESN2), a highly conserved stress-responsive protein, can be induced in response to stress. This paper aimed to explore the role and mechanism of SESN2 in septic intestinal dysfunction. Blood samples were collected from patients with septic intestinal dysfunction, and Caco-2 cells were subjected to lipopolysaccharide (LPS) to construct in vitro models. The expression level of SESN2 was determined in the blood samples and cells. The impacts of SESN2 overexpression on cell inflammation, oxidative stress, barrier integrity, and MAPK/Nrf2 signaling were evaluated. To determine the mediated role of MAPK signaling and ferroptosis, AMPK inhibitor (Compound C) and ferroptosis inducer (erastin) were separately used to treat cells, and the influences on the above aspects in cells were assessed. The expression level of SESN2 was down-regulated in patients with septic intestinal dysfunction and LPS-induced cells. SESN2 overexpression was found to suppress cell inflammation and oxidative stress, maintain barrier integrity, and activate AMPK/Nrf2 signaling. Following the AMPK signaling was inhibited or the ferroptosis was triggered, the effects of SESN2 overexpression on the cells were both reversed. Reduced SESN2 contributed to inflammatory response and barrier dysfunction in septic intestinal dysfunction by promoting ferroptosis via activating the AMPK/Nrf2 signaling pathway. [ABSTRACT FROM AUTHOR]

We introduce a new spatial statistic, the weighted pair correlation function (wPCF). The wPCF extends the existing pair correlation function (PCF) and cross-PCF to describe spatial relationships between points marked with combinations of discrete and continuous labels. We validate its use through application to a new agent-based model (ABM) which simulates interactions between macrophages and tumour cells. These interactions are influenced by the spatial positions of the cells and by macrophage phenotype, a continuous variable that ranges from anti-tumour to pro-tumour. By varying model parameters that regulate macrophage phenotype, we show that the ABM exhibits behaviours which resemble the 'three Es of cancer immunoediting': Equilibrium, Escape, and Elimination. We use the wPCF to analyse synthetic images generated by the ABM. We show that the wPCF generates a 'human readable' statistical summary of where macrophages with different phenotypes are located relative to both blood vessels and tumour cells. We also define a distinct 'PCF signature' that characterises each of the three Es of immunoediting, by combining wPCF measurements with the cross-PCF describing interactions between vessels and tumour cells. By applying dimension reduction techniques to this signature, we identify its key features and train a support vector machine classifier to distinguish between simulation outputs based on their PCF signature. This proof-of-concept study shows how multiple spatial statistics can be combined to analyse the complex spatial features that the ABM generates, and to partition them into interpretable groups. The intricate spatial features produced by the ABM are similar to those generated by state-of-the-art multiplex imaging techniques which distinguish the spatial distribution and intensity of multiple biomarkers in biological tissue regions. Applying methods such as the wPCF to multiplex imaging data would exploit the continuous variation in biomarker intensities and generate more detailed characterisation of the spatial and phenotypic heterogeneity in tissue samples. Author summary: Multiplex images provide exquisitely detailed information about the spatial distribution and intensity of up to 40 biomarkers within two-dimensional tissue regions, creating challenges and opportunities for quantitative analysis. Although stain intensities are measured on a continuous scale, they are typically converted into discrete labels to simplify subsequent spatial analysis. In this paper we propose a new spatial statistic, the weighted pair correlation function (wPCF), which exploits, rather than neglects, the continuous variation in stain intensity contained in multiplex images, and can characterise both spatial and phenotypic heterogeneity. As proof-of-principle, we apply the wPCF to synthetic data that resemble multiplex images of solid tumours. We generate data from an agent-based model (ABM) that simulates macrophage-tumour interactions. The wPCF shows how the continuous label describing macrophage phenotype is spatially related to categorical labels associated with tumour cells and blood vessels. We demonstrate that correlation functions can categorise spatial relationships in a manner which is interpretable and quantitative. The methods we present can be used to analyse both ABM simulations and multiplex imaging data, with applications that go beyond macrophage phenotype to include other biological processes that exhibit continuous variation (e.g., cancer cell stemness, biomarkers for T-cell exhaustion, and levels of oxygenation). [ABSTRACT FROM AUTHOR]

Aim: The paper was aimed at the study of foreign and domestic publications on the effect of Sodium nitrite (E 250) food additive and Ponceau 4R (E124) food colorant on the body organs to form the concept of further research on the effects of complex food additives on the organs of the digestive system. Materials and Methods: In the course of research, the following techniques have been used: bibliosemantic method for the analysis of scientific publications. The paper provides assessment of 70 literary sources. Particular attention is paid to sources over the last 5 years (2016-2021), but some earlier publications that have not lost their relevance are also included in the review. The sources were taken from scientific metric databases Scopus, Web of Science, PubMed, Medline, Google Scholar and the portal of scientific periodicals of V.I. Vernadsky National Library of Ukraine. Conclusions: Sodium nitrite has a detrimental toxic effect on various organs of the body, which on the part of the urinary system is manifested by renal dysfunction, oxidative stress, inflammation and apoptosis, the immune system responds by suppressing T-cell immunity and increased migration of neutrophils into tissues from the heart-vascular system was observed vasodilation of the resistive link with a decrease in the rhythm of their vasomotion, venular hypertension, increased arteriole-venular shunting, tortuosity of blood vessels, general slowing of blood flow, stasis of erythrocyte aggregation with paravasal tissue edema. Sodium nitrite has the ability to attach to blood cells and interfere with the transport of oxygen. Solutions of the studied food dyes and their mixtures in acceptable daily concentrations changed the immediate and delayed secretion of cytokines by leukocytes in the blood of patients with allergies. [ABSTRACT FROM AUTHOR]

Micro-ribonucleic acids are control gene expression in cells. They represent the changed cellular states that occur can be employed as biomarkers. Red blood cells alter biochemically and morphologically while they are being stored, which could be detrimental to transfusion. The effect of storage on the erythrocyte transcriptome is not mostly investigated. Because adult erythrocytes lack a nucleus, it has long been assumed that they lack deoxyribonucleic acid and ribonucleic acid. On the other hand, erythrocytes contain a diverse range of ribonucleic acids, of which micro-ribonucleic acids are key component. Changes in this micro-ribonucleic acid protect cells from death and adenine triphosphate depletion, and they are linked to specific storage lesions. As a result, changes in micro-ribonucleic acid in stored erythrocytes may be used as a marker to assess the quality and safety of stored erythrocytes. Therefore, this review ams to review the role of microRNA in stored packed red blood cells as quality indicator. Google Scholar, PubMed, Scopus, and Z-libraries are used for searching articles and books. The article included in this paper was written in the English language and had the full article. During long storage of RBCs, miR-16-2-3p, miR-1260a, miR-1260b, miR-4443, miR-4695-3p, miR-5100, let-7b, miR-16, miRNA-1246, MiR-31-5p, miR-203a, miR-654-3p, miR-769-3p, miR-4454, miR-451a and miR-125b- 5p are up regulated. However, miR-96, miR-150, miR-196a, miR-197, miR-381 and miR-1245a are down regulated after long storage of RBCs. The changes of this microRNAs are linked to red blood cell lesions. Therefore, micro-ribonucleic acids are the potential quality indicator in stored packed red blood cells in the blood bank. Particularly, micro-ribonucleic acid-96 is the most suitable biomarker for monitoring red blood cell quality in stored packed red blood units. [ABSTRACT FROM AUTHOR]