Blood Smear Analysis Research Articles

Establishment of human acute monocytic leukemia model with systemic infiltration in NPG mice.

A model construction of systemic acute leukemia is challenging. Herein, we established a systemic leukemia mouse model using highly immunodeficient NPG mice without any immunosuppressive treatments. NPG mice received tail intravenous injection of SHI-1 cells at the concentration of 1×107 cells (group A) or 5×107 cells (group B) and randomly sacrificed each seven days post-inoculation. Tumor development was monitored using nested-PCR, peripheral blood-smear analysis, flow cytometry, pathological examinations, and immunohistochemistry. The median survival of mice in groups A and B were 33.0 and 30.0 days, respectively. Blast cells in peripheral blood appeared on day 14 in group B, and on day 21 in group A. In addition, SHI-1 cell specific MLL-AF6 mRNA was detected in both spleen and bone marrow on day 14 post-inoculation. 21 days after inoculation, we observed human CD45+CD33+ cells with an SH-1-immunophenotype in the peripheral blood, spleen, and bone marrow, as well as solid neoplasms in multiple organs. Moreover, the histologically infiltrated leukemic cells expressed CD45. In conclusion, the current study demonstrated the normal growth of SHI-1 cells in the NPG mice without immunosuppression, which caused systemic leukemia similar to that observed in acute leukemia patients. We developed an efficient and reproducible model to study leukemia pathogenesis and progression.

CAE-ResVGG FusionNet: A Feature Extraction Framework Integrating Convolutional Autoencoders and Transfer Learning for Immature White Blood Cells in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a highly aggressive cancer form that affects myeloid cells, leading to the excessive growth of immature white blood cells (WBCs) in both bone marrow and peripheral blood. Timely AML detection is crucial for effective treatment and patient well-being. Currently, AML diagnosis relies on the manual recognition of immature WBCs through peripheral blood smear analysis, which is time-consuming, prone to errors, and subject to inter-observers' variation. This study aimed to develop a computer-aided diagnostic framework for AML, called "CAE-ResVGG FusionNet", that precisely identifies and classifies immature WBCs into their respective subtypes. The proposed framework leverages an integrated approach, by combining a convolutional autoencoder (CAE) with finely tuned adaptations of the VGG19 and ResNet50 architectures to extract features from CAE-derived embeddings. The process begins with a binary classification model distinguishing between mature and immature WBCs followed by a multiclassifier further classifying immature cells into four subtypes: myeloblasts, monoblasts, erythroblasts, and promyelocytes. The CAE-ResVGG FusionNet workflow comprises four primary stages, including data preprocessing, feature extraction, classification, and validation. The preprocessing phase involves applying data augmentation methods using geometric transformations and synthetic image generation using the CAE to address imbalance in the WBC distribution. Feature extraction involves image embedding and transfer learning, where CAE-derived image representations are used by a custom integrated model of VGG19 and ResNet50 pretrained models. The classification phase employs a weighted ensemble approach that leverages VGG19 and ResNet50, where the optimal weighting parameters are selected using a grid search. The model performance was assessed during the validation phase using the overall accuracy, precision, and sensitivity, while the area under the receiver characteristic curve (AUC) was used to evaluate the model's discriminatory capability. The proposed framework exhibited notable results, achieving an average accuracy of 99.9%, sensitivity of 91.7%, and precision of 98.8%. The model demonstrated exceptional discriminatory ability, as evidenced by an AUC of 99.6%. Significantly, the proposed system outperformed previous methods, indicating its superior diagnostic ability.

Automated feathered edge blood smear analysis: early diagnosis of carcinocythemia in a case of disseminated intravascular coagulation with multi-organ failure.

Carcinocythemia, known as the presence of circulating tumor cells in the peripheral blood, is difficult to detect when the carcinoma cells are minimally present. We describe a case of a 56-year-old patient presenting with disseminatedintravascular coagulation (DIC) and multiple organ failure. Despite initial suspicion of sepsis, a peripheral blood smear showed the presence of atypical cells, mainly located at the feathered edge, leading to a presumptive diagnosis of carcinocythemia of unknown primary origin. The presence of a high-fluorescent cell population detected by our hematology analyzer (Sysmex XN-9100) and immunohistochemical staining with pancytokeratin AE1/AE3 confirmed the carcinoma cell origin. The patient died 4 days after referral to our hospital. Postmortem examination revealed a pleomorphic lobular breast carcinoma (triple-negative, androgen receptor-negative). Given the clinical acuity of patients with carcinocythemia, early diagnosis is essential to guide management. This case underscores the importance of optimizing current workflows relying on complex flagging algorithms and enhanced digital imaging to aid in the early detection of such rare condition. When patients present with DIC of unknown origin and high fluorescent signals are detected on the hematology analyzer, carcinocythemia should actively be ruled out by extensive microscopic peripheral blood examination.

Regenerative anemia identification in cats: Red blood cell indices or morphology, what to use?

Anemia, a clinical condition characterized by reduced erythrocytes, is often observed in cats. Regeneration indicates that the bone marrow can respond appropriately to anemia. The absolute reticulocyte count is the reference for differentiating regenerative and non-regenerative anemia, while red blood cell (RBC) indices and morphology provide supplementary information. This study aimed to identify anemia types and establish the most reliable RBC indices and morphology methods in agreement with the reference method. One hundred forty-five cases of cat anemia were prospectively classified using two methods: RBC indices and RBC morphology, and subsequently compared with the absolute reticulocyte count. Based on RBC indices assessment, 27 cases (19%) exhibited regenerative anemia. Based on RBC morphology, 29 (20%) cases were identified as having regenerative anemia. Using the reticulocyte absolute count as a reference method, 34 (23.4%) cases of regenerative anemia were identified. The findings indicated that RBC indices and RBC morphology did not align in evaluating medullary regeneration and that there is a good degree of agreement between RBC morphology assessment and the reticulocyte absolute count in identifying regenerative anemias. Blood smear analysis of RBC morphology was more dependable for classifying regenerative anemia than RBC indices. Further studies should be conducted with a larger number of animals and that allow the identification of the cause of anemia and the monitoring of the animal.

Pediatric asthma and eosinophilia: insights from nasal and blood smear analyses

Pediatric asthma and eosinophilia: insights from nasal and blood smear analyses

Blood smears analysis: a valuable tool for profiling circulating erythrocytes and leukocytes in mouse model of leishmaniasis

Although blood smear analysis can yield valuable insights into the health status of laboratory animals, it is not frequently performed in studies involving mouse models of leishmaniasis. Thus, to underscore its importance, we conducted microscopic evaluation of blood smears prepared from 10 µL of blood from L. (L.) amazonensis-infected BALB/c mice. Subsequently, we explored potential correlations between the identified hematological alterations, clinical evaluation data, and serum levels of total proteins (TP), albumin (Alb), globulins (Glob), IL-17A, and IL-10. Our findings revealed that infected mice exhibited an increased erythrocyte count, alongside a higher prevalence of microcytic and hypochromic erythrocytes. Moreover, it was observed elevated relative and absolute numbers of neutrophils and monocytes and reduced relative and absolute numbers of lymphocytes. A significant proportion of monocytes and lymphocytes in infected animals displayed reactive features. The relative number of lymphocytes was negatively correlated with the serum levels of Glob. Furthermore, the frequency of reactive lymphocytes was positively correlated with the serum levels of Glob and IL-17A. There was also a positive correlation between the absolute number of neutrophils and the serum levels of IL-17A and the frequency of reactive monocytes and the serum levels of Glob. Therefore, these findings, collectively, underscore the importance of blood smear analysis for elucidating both the quantitative and qualitative hematological changes experimentally induced by Leishmania infection. Integration of this technique into research protocols involving different mouse models of leishmaniasis holds immense potential for advancing our knowledge of this infectious disease and enhancing clinical management strategies.

Clinical Approach to Advanced Mantle Cell Lymphoma: A Detailed Case Analysis

Mantle cell lymphoma (MCL) is a rare and aggressive subtype of non-Hodgkin lymphoma (NHL) originating from cells in the mantle zone. Herein, we present a case report of a 49-year-old male patient diagnosed with stage VI MCL, illustrating various diagnostic methods and procedures utilized in his evaluation. The patient presented with progressively enlarging cervical lymph nodes, fatigue, weight loss, anorexia, chronic diarrhea, abdominal pain, and rectal bleeding. Clinical examination revealed cutaneomucosal pallor, tachycardia, expiratory polypnea, bilateral jugulocarotid adenopathies, and splenomegaly. Laboratory investigations showed normocytic normochromic anemia, hyperleukocytosis, lymphocytic predominance, and thrombocytopenia. Peripheral blood smear analysis indicated a lymphoproliferative disorder, confirmed by flow cytometry revealing monotypic lymphoid cells. Bone marrow biopsy showed hypoplastic marrow with atypical cells. Immunohistochemistry confirmed mantle cell lymphoma localization. Subsequent thoraco-abdomino-pelvic CT scan revealed mediastinal and abdominal adenopathy with splenomegaly, leading to a diagnosis of stage IV MCL. The case highlights the importance of early and comprehensive diagnostic approaches in MCL management.

Exploring the Impact of Batch Size on Deep Learning Artificial Intelligence Models for Malaria Detection.

Introduction Malaria is a major public health concern, especially in developing countries. Malaria often presents with recurrent fever, malaise, and other nonspecific symptoms mistaken for influenza. Light microscopy of peripheral blood smears is considered the gold standard diagnostic test for malaria. Delays in malaria diagnosis can increase morbidity and mortality. Microscopy can be time-consuming and limited by skilled labor, infrastructure, and interobserver variability. Artificial intelligence (AI)-based tools for diagnostic screening can automate blood smear analysis without relying on a trained technician. Convolutional neural networks (CNN), deep learning neural networks that can identify visual patterns, are being explored for use in abnormality detection in medical images. A parameter that can be optimized in CNN models is the batch size or the number of images used during model training at once in one forward and backward pass. The choice of batch size in developing CNN-based malaria screening tools can affect model accuracy, training speed, and, ultimately, clinical usability. This study explores the impact of batch size on CNN model accuracy for malaria detection from thin blood smear images. Methods We used the publicly available "NIH-NLM-ThinBloodSmearsPf" dataset from the United States National Library of Medicine, consisting of blood smear images forPlasmodium falciparum. The collection consists of 13,779 "parasitized" and 13,779 "uninfected" single-cell images. We created four datasets containing all images, each with unique randomized subsets of images for model testing. Using Python, four identical 10-layer CNN models were developed and trained with varying batch sizes for 10 epochs against all datasets, resulting in 16 sets of outputs. Model prediction accuracy, training time, and F1-score,an accuracy metric used to quantify model performance, were collected. Results All models produced F1-scores of 94%-96%, with 10 of 16 instances producing F1-scores of 95%. After averaging all four dataset outputs by batch size, we observed that, as batch size increased from 16 to 128, the average combined false positives plus false negatives increased by 15.4% (130-150), and the average model F1-score accuracy decreased by 1% (95.3%-94.3%). The average training time also decreased by 28.11% (1,556-1,119 seconds). Conclusion In each dataset, we observe an approximately 1% decrease in F1-score as the batch size was increased. Clinically, a 1% deviation at the population level can create a relatively significant impact on outcomes. Results from this study suggest that smaller batch sizes could improve accuracy in models with similar layer complexity and datasets, potentially resulting in better clinical outcomes. Reduced memory requirement for training also means that model training can be achieved with more economical hardware. Our findings suggest that smaller batch sizes could be evaluated for improvements in accuracy to help develop an AI model that could screen thin blood smears for malaria.

Abstract PO4-16-07: Cyclin-dependent kinase inhibitor plus endocrine therapy in HR+/HER2- invasive breast cancer with bone marrow and pancytopenia: a new standard of care? Collaborative multicentric Argentinean real-world study (SUMA-02)

Abstract Introduction Bone marrow involvement is a rare occurrence in patients with advanced breast cancer (ABC), and the prognosis in this context is generally poor. Prompt initiation of treatment to improve the patient's hematological status is crucial. However, this condition is often excluded from clinical trials, making it challenging to determine the effectiveness of new drugs. Limited data and evidence are available to guide treatment decisions, but guidelines recommend starting with chemotherapy for the need of a rapid response. This study aims to analyze the real-world efficacy of cyclin-dependent kinase inhibitors (CDKis) in HR+/HER2- ABC with bone marrow infiltration. Methods Retrospective multicenter cohort study including HR+/HER2- ABC patients from public and private facilities in Argentina. Patients with confirmed bone marrow involvement (blood smear or histological biopsy analysis) and treated with CDKi were eligible. Bone marrow response was defined as an increase in at least one of the previously abnormal blood series to Hb >10.0, platelets >100,000, and leukocytes >4,000. Results A total of 22 patients from different medical centers in Argentina were included. The median age was 55.5 (IQR 46.25-65). Histological confirmation of bone marrow involvement was reported in 81.8% (18) of patients. Among them, 54.5% (12) had initial diagnosis at an early stage, and 13.6% (3) experienced relapse during or within 1 year of completing adjuvant hormonal treatment. Bone-only metastasis was observed in 50% (11) of patients, while the remaining 50% (11) had both visceral and bone disease. Anemia, thrombocytopenia, and leukopenia were present in 95.5% (21), 90.9% (20), and 40.9% (9) of patients, respectively. In 68.2% (15) of patients, bone marrow involvement was detected at the first-line treatment setting. The selected CDKis were palbociclib in 40.9% (9) of patients, ribociclib in 31.8% (7), and abemaciclib in 27.3% (6). The bone marrow response rate was 68.2% (15), with a median of 2 cycles (range 1-5) required for a response. Dose reduction was necessary in 31.8% (7) of patients. Discussion Managing patients with uncommon sites of metastasis, such as bone marrow, poses significant challenges for oncologists. Bone marrow infiltration leads to hematopoietic alterations that adversely affect the quality of life, resulting in increased risk of infections, bleeding, and other comorbidities with fatal consequences. While chemotherapy is the standard treatment in such cases, our study demonstrates that CDKis are a safe and effective option for managing these complications. Conclusion The findings of this study support the evaluation of CDKis as a standard treatment for HR+/HER2- ABC patients. Our results are in line with the recently published phase 2 clinical trial RIGHT CHOICE, which showed a prolonged progression free survival in patients treated with ribociclib and HT with HR+/HE2- ABC and visceral crisis. Citation Format: Alexis Ostinelli, Pablo Mandó, Carolina Almada, Melina Winocur, M. Agustina Ipiña, Viviana Paez, Silvia Aparicio, Sergio Rivero, Federico Waisberg, Laura Sabina Lapuchesky, Cristian Micheri, M. Belen Montenegro, Cristina Rusz Maidana, Carolina Reinhardt, Evelina Rovera, Gonzalo Gómez Abuin, Santiago Bella, Florencia Perazzo, Adrian Nervo, Andrea Aguilar, Matías Chacón, Victoria Costanzo, Valeria Caceres, Jorge Nadal. Cyclin-dependent kinase inhibitor plus endocrine therapy in HR+/HER2- invasive breast cancer with bone marrow and pancytopenia: a new standard of care? Collaborative multicentric Argentinean real-world study (SUMA-02) [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-16-07.

Egyptian Pediatric Guidelines for the Management of Children with Isolated Thrombocytopenia Using the Adapted ADAPTE Methodology-A Limited-Resource Country Perspective.

Thrombocytopenia is a prevalent presentation in childhood with a broad spectrum of etiologies, associated findings, and clinical outcomes. Establishing the cause of thrombocytopenia and its proper management have obvious clinical repercussions but may be challenging. This article provides an adaptation of the high-quality Clinical Practice Guidelines (CPGs) of pediatric thrombocytopenia management to suit Egypt's health care context. The Adapted ADAPTE methodology was used to identify the high-quality CPGs published between 2010 and 2020. An expert panel screened, assessed and reviewed the CPGs and formulated the adapted consensus recommendations based on the best available evidence. The final CPG document provides consensus recommendations and implementation tools on the management of isolated thrombocytopenia in children and adolescents in Egypt. There is a scarcity of evidence to support recommendations for various management protocols. In general, complete clinical assessment, full blood count, and expert analysis of the peripheral blood smear are indicated at initial diagnosis to confirm a bleeding disorder, exclude secondary causes of thrombocytopenia and choose the type of work up required. The International Society of Hemostasis and thrombosis-Bleeding assessment tool (ISTH-SCC BAT) could be used for initial screening of bleeding manifestations. The diagnosis of immune thrombocytopenic purpura (ITP) is based principally on the exclusion of other causes of isolated thrombocytopenia. Future research should report the outcome of this adapted guideline and include cost-analysis evaluations.

Deep learning-assisted smartphone-based quantitative microscopy for label-free peripheral blood smear analysis.

Hematologists evaluate alterations in blood cell enumeration and morphology to confirm peripheral blood smear findings through manual microscopic examination. However, routine peripheral blood smear analysis is both time-consuming and labor-intensive. Here, we propose using smartphone-based autofluorescence microscopy (Smart-AM) for imaging label-free blood smears at subcellular resolution with automatic hematological analysis. Smart-AM enables rapid and label-free visualization of morphological features of normal and abnormal blood cells (including leukocytes, erythrocytes, and thrombocytes). Moreover, assisted with deep-learning algorithms, this technique can automatically detect and classify different leukocytes with high accuracy, and transform the autofluorescence images into virtual Giemsa-stained images which show clear cellular features. The proposed technique is portable, cost-effective, and user-friendly, making it significant for broad point-of-care applications.

Sequence of Simple Digital Technologies for Detection of Platelets in Medical Images

Platelets play an important role in the diagnosis and detection of various diseases, the course of the disease in the future, and the possibility of justifying treatment methods. In this aspect, platelet counting is of key importance. For these purposes, it is important to correctly identify such objects. This served as the basis for the development and generalization of an appropriate medical image analysis procedure. The purpose of this study is to construct a generalized procedure for platelet identification in medical digital images. The work examined at least 30 images containing objects such as platelets. These images are approximately the same type, but with different intensity of the presence of the main objects in the blood smear. Similar but noisy images are also considered. These images were noisy with different types of noise. Thus, a total of at least 120 images were examined. In general, this allows us to evaluate the effectiveness of the proposed procedure for identifying platelets in medical images. This procedure includes simple methods of image analysis such as: binarization, morphological analysis, taking into account the influence of the sizes of different objects and comparative analysis of images at intermediate stages of the study. To summarize the results, estimates such as the percentage of false detection of platelets and the percentage of missed platelets were considered. The platelet identification results that were obtained for non-noisy images are as follows: false platelet isolation was less than 0.1%, missed platelets were within 2-2.5%. The worst result for noisy images is false platelet isolation – within 10% (for images with multiplicative noise), missed platelets – within 7.5-8% (for images with multiplicative noise). It should also be noted that noisy images are characterized by identification of platelets with distortion of their sizes: these sizes are reduced or increased. The percentage of such distortions does not exceed 1.3% (for images with Poisson noise).The problematic aspects of platelet identification in digital medical images are considered. Particular attention is paid to simple methods of digital image processing. Among the problematic aspects of the proposed approach there is a need to clearly take into account the geometric dimensions of platelets. The results obtained are acceptable and can be used as the basis for an automated blood smear analysis system.

Awareness of sickle cell disease among nursing undergraduates in Farasan: Its interference with malaria.

The present study was conducted to generate data on awareness and incidence of sickle cell disease (SCD) and also to adduce the widespread myths peddled about SCD. Students studying in the Department of Nursing were recruited. A pretested, self-administered sickle cell assessment questionnaire was distributed electronically through WhatsApp group to collect necessary data. Participants were screened for malaria by thin blood smear analyses, and their hemoglobin (Hb) contents (g/dL) were determined by Sahli's haemoglobinometer. Statistical analyses were done using Origin (version 8.1, USA). A reliability study was performed for the validity of questionnaire data. Study participants had significantly high awareness regarding SCDs (89.9%, P < 0.001). Most participants (96.3%) were aware about government policy regarding premarital screening for genetic disorders and replied that the government has strict health policies backed by equally robust laboratory diagnostics. Moreover, none of the participants had SCDs, although their parents had a consanguineous marriage. Thin blood smear analyses of participants did not reveal any cases of Plasmodium falciparum. However, significant percentages (33.1%) were found to be anemic, probably due to their dietary habits and lifestyles, as has been reflected by questionnaire analyses. Furthermore, a very less number of students had knowledge about genetic variations that might occur in malaria-endemic regions after long exposure to offer protection from malaria. Knowledge about management practices was also lacking among study participants (29%). This research points to the necessity that the nursing study plan should focus on providing specific training on management skills and preventive measures for SCDs, which is of paramount importance.

Crowdsourced human-based computational approach for tagging peripheral blood smear sample images from Sickle Cell Disease patients using non-expert users

In this paper, we present a human-based computation approach for the analysis of peripheral blood smear (PBS) images images in patients with Sickle Cell Disease (SCD). We used the Mechanical Turk microtask market to crowdsource the labeling of PBS images. We then use the expert-tagged erythrocytesIDB dataset to assess the accuracy and reliability of our proposal. Our results showed that when a robust consensus is achieved among the Mechanical Turk workers, probability of error is very low, based on comparison with expert analysis. This suggests that our proposed approach can be used to annotate datasets of PBS images, which can then be used to train automated methods for the diagnosis of SCD. In future work, we plan to explore the potential integration of our findings with outcomes obtained through automated methodologies. This could lead to the development of more accurate and reliable methods for the diagnosis of SCD.

Comparing the incidence of spontaneous autopolyploidy in wild and hatchery Lake Sturgeon

AbstractObjectiveLiving species of Acipenseriformes, sturgeons and paddlefishes, are characteristically polyploid, having more than two complete sets of chromosomes (&gt;2n). They undergo spontaneous autopolyploidy, an unintentional one and a half times increase in genome size, more frequently than any other order of fish. For Lake Sturgeon Acipenser fulvescens, which are evolutionary octoploids (8n), spontaneous autopolyploidy results in fertile dodecaploid (12n) progeny. When 12n individuals reproduce with octoploids, it is possible that resulting decaploid (10n) offspring will have poor physiological performance and survivorship. Spontaneous autopolyploidy in the wild is very low; however, incidence in fish hatcheries is greater, as seen in other 8n sturgeon species. We investigated this disparity in Lake Sturgeon, predicting to find more dodecaploid individuals in hatchery populations than in the wild.MethodsPloidy was determined using red blood cells from individuals in three hatchery and two wild populations of Lake Sturgeon in Manitoba, Canada (n = 1004). Red blood cell volume was evaluated with a Z2 Coulter counter and used to determine ploidy, based on the average of triplicate measures of the erythrocyte modal nuclei volume (fL). A subsample from each environment type was further examined using blood smear analysis (n = 130) and flow cytometry (n = 27).ResultOne 12n hatchery individual was found, along with significant differences in erythrocyte morphometry between the five populations. Fluctuations in modal nuclei volume were also observed over 169 days of repeated measurement within a single hatchery population.ConclusionThe well‐developed relationship between erythrocyte size and fishes external and physiological environment may explain the variance both between and within populations. These results demonstrate the need for ploidy monitoring in artificial hatcheries, as releasing even a single 12n fish could produce thousands of 10n offspring that, if recruited, would have a detrimental effect on the population fitness.

Hematology of Liolaemus pacha (Iguania: Liolaemidae) and its relationship with mite infestation, reproductive period and body condition.

Variations in hematological profile in reptiles can be caused by multiple factors, including parasites presence. Our goals were to identify and morphologically describe blood cells of Liolaemus pacha and analyze their relationship with sex, body condition, individual reproductive/post-reproductive period and mite infestation. Blood smear analyses do not indicate the presence of hemoparasites, suggesting that the mites Neopterygosoma do not serve as vectors for these organisms, as has been proposed for other genera of ectoparasitic mites. In post-reproductive period, there was a reduction in specimens' body condition and a higher leukocyte count in uninfected lizards. This could be a consequence of the testosterone effects, in higher concentration during the reproductive season, which can increase the metabolic rate, decreasing feeding rate. Infested and non-infested lizards showed no differences in body condition, as well as in leukocyte count, hence the host's immune system could be developing infestation tolerance. Infested specimens had a higher count of monocytes, thrombocytes, heterophils and lymphocytes. Based on cells function, mites' effect could be associated with inflammatory processes, allergic reactions or infectious diseases. These results suggested a complex interaction between lizards' hematological parameters and factors associated to ectoparasites or body conditions. We consider this work as a diagnostic tool for genus Liolaemus, to evaluate health quality, with relevance to the conservation or management of this lizard's genus.

Neutrosophic Logic Empowered Machine Learning Algorithm with Salp Swarm Optimization for Biomedical Image Analysis

Leukemia recognition and classification contain the identification of dissimilar kinds of leukemia, a group of blood cancers that affects the bone marrow and blood. A classical model containing microscopic analysis of blood smears to classify abnormal cells analytic of leukemia. Leukemia recognition employing a united technique of neutrosophic logic and deep learning (DL) signifies a new and complete approach to handling uncertainty and difficulty in medical data. Neutrosophic logic permits the representation of unstated or imperfect data, which is general in medical analyses. DL mainly convolutional neural networks (CNN) or recurrent neural networks (RNN), which can mechanically remove difficult patterns from medicinal imageries, improving the accuracy of leukemia recognition. The neutrosophic logic module accommodates the characteristic uncertainty in medicinal data, offering a formalism to manage imperfect or inaccurate data linked with the analysis procedure. The combination of these dual techniques generates a robust structure which capable of leveraging both the control of DL in image analysis and the flexibility of neutrosophic logic in dealing with uncertainties, contributing to more trustworthy and interpretable leukemia recognition methods. This study develops a new Salp Swarm Algorithm with a Neutrosophic Logic SVM (SSA-NSVM) model for Leukemia Detection and Classification. The SSA-NSVM technique mainly exploits Neutrosophic Logic (NL) concepts with the DL model for the detection of leukemia. To attain this, the SSA-NSVM model uses bilateral filtering (BF) based image pre-processing. In addition, the SSA-NSVM approach applies a modified densely connected networks (DenseNet) technique for learning complex and intrinsic feature patterns. Besides, the hyperparameter range of the modified DenseNet system takes place utilizing a SSA. At last, the NSVM technique is employed for the detection and identification of leukemia. The performance validation of the SSA-NSVM algorithm is verified utilizing a benchmark medicinal image dataset. The simulation values emphasized that the SSA-NSVM model reaches better detection outcomes than other existing approaches.

Comparative study of sickling test, solubility test, and hemoglobin electrophoresis in sickle cell anemia

Abstract Background: Madhya Pradesh, a state in India, bears the highest number of sickle cell anemia (SCA) cases, particularly among its tribal communities. The diagnosis of suspected SCA cases involves utilizing several methods. The sickling test operates on the principle of hemoglobin S (HbS) polymerization upon deoxygenation. By contrast, the solubility test involves the reduction of HbS using sodium hydrosulfite, followed by precipitation of lysed red blood cells. Hemoglobin (Hb) electrophoresis identifies Hb variants based on their migration in an electric field. Our objective was to assess the efficacy of sickling and solubility tests as screening tools for detecting SCA, comparing them against capillary Hb electrophoresis, which is considered the gold standard. Materials and Methods: All individuals suspected of having SCA between 2022 and 2023 were enrolled in the study. Clinical information, peripheral blood smear analysis, sickling test, solubility test, and capillary Hb electrophoresis were conducted, and the results were compared. Results: Of 250 cases assessed, Hb electrophoresis identified 225 cases of SCA, resulting in a sickle cell disease to sickle cell trait (SCT) ratio of 1:1.36 and a male-to-female ratio of 1:1.33. The highest number of cases were observed in the age group from 21 to 30 years. Generalized weakness (77%) and abdominal pain (52%) were the most frequently reported symptoms. The sickling test demonstrated a sensitivity, specificity, and diagnostic accuracy of 91.5%, 72%, and 89%, respectively, compared with Hb electrophoresis. The solubility test yielded values of 76.5%, 68%, and 75% for sensitivity, specificity, and diagnostic accuracy, while peripheral smear analysis showed 36%, 25%, and 42%, respectively. Conclusion: The sickling test displayed superior sensitivity and diagnostic accuracy compared with the solubility test, with no significant disparity in specificity between these two methods. Notably, the solubility test exhibited a higher incidence of false-negative results for SCT. Therefore, the sickling test is the preferred screening method for SCA.

Peripheral Blood Smear Analysis for Cattle with Foot and Mouth Diseases in Lembang, West Bandung

Foot and Mouth Disease (FMD) is an infectious disease that is endemic and has a significant impact on dairy farming in Indonesia. In reducing the impact caused by FMD, proper handling by veterinarians is necessary. The peripheral blood smear can be used as a data reference to give priority to the right treatment for cattle with FMD. This study aimed to describe the appearance of peripheral blood smears in cattle with FMD. The study data were obtained from 15 cattle with FMD at KPSBU Lembang, West Bandung, West Java, Indonesia. The morphological profile of the blood was examined using the peripheral blood smear method. Morphological abnormalities found in the peripheral blood smear of red blood cells were anisocytosis (microcytosis and macrocytosis), poikilocytosis (achanthocytosis and echinocytosis), and hypochromasia. Different morphological abnormalities of leukocytes can be caused by anorexia due to FMD secondary to lack of nutritional intake. To determine an effective and efficient treatment, it is recommended that veterinarians refer to the results of this study.

Ефективність вирощування молоді осетрових (Acipenseridae) видів риб за різної твердості води

Ефективність вирощування молоді осетрових (Acipenseridae) видів риб за різної твердості води