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Current malaria diagnostic methods require blood collection, which may be associated with pain and the risk of transmitting blood-borne pathogens, and often create poor compliance when repeated sampling is needed. This study determined the potential use of non-invasive methods (saliva and urine specimens) as alternative sample sources for the diagnosis of malaria infection using real-time polymerase Chain Reaction (qPCR) among children below five years in Nnewi, Anambra State, Nigeria. Biomarkers (18S rRNA) were captured and concentrated from saliva and urine samples using a magnetic bead-based method. DNA recovered from the saliva and urine samples was amplified using qPCR. The results revealed that, out of the 552 participants recruited in this study, the malaria prevalence based on blood microscopy was 55.1%. The prevalence of malaria among children based on the qPCR of saliva specimens was 343 (62.1%), out of which 301 (87.7%) were true positives (TP) and 42 (12.3%) were false positives (FP) when compared with microscopy. Moreover, the prevalence of malaria among children based on qPCR of urine specimens was 269 (48.7%), of which 237 (88.1%) were true positive (TP) and 32 (11.9%) were false positive (FP). When the qPCR method was compared to thick blood film-microscopy as the reference standard, saliva qPCR had a sensitivity of 98.7%, specificity of 80.0%, positive predictive value (PPV) of 87.2%, and negative predictive value (NPV) of 97.8%; urine qPCR had a sensitivity of 88.1%, specificity of 84.3%, PPV of 88.5%, and NPV of 83.8%. Saliva and urine samples are therefore promising non-invasive approaches for malaria diagnosis, and their qPCR has a sensitivity comparable to that of blood microscopy, despite the limitations of cost and turnaround time. [ABSTRACT FROM AUTHOR]

Background: Malaria is one of the most public health and life-threatening parasitic infections caused by the protozoan parasite. Since children are immunologically naive to the malaria parasite, they are the main vulnerable groups to be affected by malaria. Aim: This study aimed at determining the prevalence of malaria among children in urban area at Byahi Health Center, Rubavu district. Methods: Cross-sectional study was used to achieve the objectives. To obtain the information regarding social demographic characteristics, written questionnaires in native language were distributed to caregivers. Blood smears were collected and sent to laboratory department for analysis. Data were analyzed using Statistical package for the social sciences (SPSS). Results: Among 50 children who participated in the study, the majority were males over females with 58% and 42% respectively. The prevalence of malaria among children in urban area was higher with 30%. Among the participants, children of age range 1-5 years shown a high prevalence of malaria than those of 5-8 months with 13 and 2 positive cases respectively and children of 1-5 years old was statistically significant with a p-value (p 0.027). Conclusion: After getting the results above, we have seen that children from urban area are affected by malaria with the overall prevalence of 30%. There is a need of improving and rechecking the existing malaria in children, prevention and control measures of the country. Byahi health center should create awareness about the importance early malaria checkup recommended reducing malaria infection. The parents are recommended to protect their children and district leaders should make researcher in others school. It must be reported to Ministry of Health that malaria infection mostly affects children. [ABSTRACT FROM AUTHOR]

In healthcare, observing the features and areas of malaria in microscopic images is crucial for the diagnosis and treatment of plasmodium malaria parasites for automated detection. The classification of malaria parasites can be challenging due to factors such as limited training data, class imbalance, and variability in parasite stages. Moreover, the parasites often belong to similar classes, and the quality of malaria blood cell smears is often poor. To address this issue, a Deep Convolutional Neural Network (Deep-CNN) model is combined with Random Forest (RF) for the detection of plasmodium malaria parasites. The Deep-CNN-RF approach leverages domain-specific expertise for improved learning. Moreover, a novel modification is applied to the pooling layer by incorporating the Global Average-Pooling layer (GAP) without an additional flattening layer, enhancing parasite area visualization. Additionally, Canny edge detection is employed for precise parasite boundary edge detection. The experimental performance of the Deep-CNN-RF model is evaluated using a malaria cell dataset from the National Library of Medicine (NLM), Kaggle, and the National Institutes of Health (NIH). The proposed scheme effectiveness is assessed through performance metrics, including accuracy, precision, recall, Mean Square Error (MSE), and F1-Score. The results demonstrate that the proposed technique outperforms state-of-the-art classification models on malaria parasite datasets. [ABSTRACT FROM AUTHOR]

Background: Malaria is one of the most public health and life-threatening parasitic infections caused by the protozoan parasite. Since children are immunologically naive to the malaria parasite, they are the main vulnerable groups to be affected by malaria. Aim: This study aimed at determining the prevalence of malaria among children in urban area at Byahi Health Center, Rubavu district. Methods: Cross-sectional study was used to achieve the objectives. To obtain the information regarding social demographic characteristics, written questionnaires in native language were distributed to caregivers. Blood smears were collected and sent to laboratory department for analysis. Data were analyzed using Statistical package for the social sciences (SPSS). Results: Among 50 children who participated in the study, the majority were males over females with 58% and 42% respectively. The prevalence of malaria among children in urban area was higher with 30%. Among the participants, children of age range 1-5 years shown a high prevalence of malaria than those of 5-8 months with 13 and 2 positive cases respectively and children of 1-5 years old was statistically significant with a p-value (p 0.027). Conclusion: After getting the results above, we have seen that children from urban area are affected by malaria with the overall prevalence of 30%. There is a need of improving and rechecking the existing malaria in children, prevention and control measures of the country. Byahi health center should create awareness about the importance early malaria checkup recommended reducing malaria infection. The parents are recommended to protect their children and district leaders should make researcher in others school. It must be reported to Ministry of Health that malaria infection mostly affects children. [ABSTRACT FROM AUTHOR]

Background: Malaria infection during pregnancy presents a substantial health threat, adversely impacting both the mother and fetus. Its pathogenesis and clinical consequences further complicate diagnosis, treatment, and prevention, particularly in endemic regions. The precise impact of malaria infection on hematological profiles needs to be clearly elucidated, and the occurrence of malaria in expectant mothers still needs to be explored. Consequently, this study aims to assess the prevalence of malaria infection among pregnant women as well as to investigate and correlate the effects of this infection on the hematological parameters of pregnant women in Yola, Nigeria. Methods: A structured hybrid questionnaire was used to gather socio-demographic, clinical, and obstetric data from 100 pregnant women aged 15–45 years. Malaria parasitemia was determined and confirmed using a light microscope, blood smear-staining techniques, and rapid diagnostic tests (RDT). At the same time, the packed cell volume (PCV) was measured using a microhematocrit reader. Also, the complete blood count was determined using Turk’s solution and Neubauer’s counting chamber (hemocytometer). Results: Out of the 100 participants in the study, 76 tested positive for malaria, resulting in a prevalence rate of 76%. The age group between 30 and 34 years and multigravida recorded high values of malaria-infected women, accounting for 18 (23.7%) and 49%, respectively. Also, the study’s findings indicate that malaria-infected pregnant women had a significantly higher occurrence of anemia than those not infected (P =.045). In addition, eosinophil counts, total white blood cells (WBC), and neutrophil count were notably higher in pregnant women infected by malaria compared to those not infected (P <.05). Conversely, lymphocyte count, basophil count, and monocyte count were significantly lower in pregnant women infected by malaria compared to uninfected pregnant women. Conclusion: Pregnant women participating in prenatal care at the Specialist Hospital in Yola, Nigeria, exhibited a relatively high occurrence of malaria parasite infection, and these infected pregnant women displayed a notable change in specific hematological parameters. The findings of this study offer valuable insights into the pathogenesis of malaria during pregnancy and contribute to improved diagnostic and management strategies for pregnant women at risk of malaria infection. [ABSTRACT FROM AUTHOR]

Malaria continues to be a major barrier to socioeconomic development in Africa, where its death rate is over 90%. The predictive power of many machine learning models—such as multi-linear regression (MLR), artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFISs) and Random Forest classifier—is investigated in this study using data from 2207 patients. The dataset was reduced from the initial dataset of thirty-two criteria samples to fifteen. Assessment measures such as the root mean square error (RMSE), mean square error (MSE), coefficient of determination (R2), and adjusted correlation coefficient R were used. ANFIS, Random Forest, MLR, and ANN are among the models. After training, ANN outperforms ANFIS (97%), MLR (92%), and Random Forest (68%) with the greatest R (99%) and R2 (99%), respectively. The testing stage confirms the superiority of ANN. The paper also presents a statistical forecasting sheet with few errors and excellent accuracy for MLR models. When the models are assessed with Random Forest, the latter shows the least results, thus broadening the modeling techniques and offering significant insights into the prediction of malaria and healthcare decision making. The outcomes of using machine learning models for precise and efficient illness prediction add to an expanding body of knowledge, assisting healthcare systems in making better decisions and allocating resources more effectively. [ABSTRACT FROM AUTHOR]

Romanowsky staining was an important methodological breakthrough in diagnostic hematology and cytopathology during the late 19th and early 20th centuries; it has facilitated for decades the work of biologists, hematologists and pathologists working with blood cells. Despite more than a century of studying Romanowsky staining, no systematic review has been published that explains the chemical processes that produce the "Romanowsky effect" or "Romanowsky-Giemsa effect" (RGE), i.e., a purple coloration arising from the interaction of an azure dye with eosin and not due merely to their simultaneous presence. Our review is an attempt to build a bridge between chemists and biomedical scientists and to summarize the available data on methylene blue (MB) demethylation as well as the related reduction and decomposition of MB to simpler compounds by both light and enzyme systems and microorganisms. To do this, we analyze modern data on the mechanisms of MB demethylation both in the presence of acids and bases and by disproportionation due to the action of light. We also offer an explanation for why the RGE occurs only when azure B, or to a lesser extent, azure A is present by applying experimental and calculated physicochemical parameters including dye-DNA binding constants and electron density distributions in the molecules of these ligands. Finally, we discuss modern techniques for obtaining new varieties of Romanowsky dyes by modifying previously known ones. We hope that our critical literature study will help scientists understand better the chemical and physicochemical processes and mechanisms of cell staining with such dyes. [ABSTRACT FROM AUTHOR]

Malaria is a serious health problem in the world. Nearly half of the world’s population is at risk of disease. In this study, a mathematical model was developed to understand and analyze the dynamics of the malaria parasite within host cells with cell-mediated and antibody-mediated immune systems. The model categorizes the population into six compartments. The study provides a concise representation of the interaction between the parasite and red blood cells, as well as the responses of the immune system, including both antibody-mediated and cell-mediated responses. The research examines the biological visibility and well-posedness of the model, ensuring that the solutions remain bounded and positive. The basic reproduction number, which indicates the potential spread of the parasite is determined. The stability analysis of the parasite-free equilibrium point was also conducted, revealing that the parasite-free state is locally and globally stable if the basic reproduction number, ${R_0} \lt 1$R0<1. Furthermore, bifurcation and sensitivity analysis are performed. Finally, to complement the theoretical findings and illustrate the impact of immunological effectiveness, numerical simulations are conducted under different scenarios. The result shows that the cell-mediated and antibody-mediated immune response helps to eliminate the parasite within the human host. [ABSTRACT FROM AUTHOR]

A theoretical methodology is suggested for finding the malaria parasites’ presence with the help of an intelligent hyper-parameter tuned Deep Learning (DL) based malaria parasite detection and classification (HPTDL-MPDC) in the smear images of human peripheral blood. Some existing approaches fail to predict the malaria parasitic features and reduce the prediction accuracy. The trained model initiated in the proposed system for classifying peripheral blood smear images into the non-parasite or parasite classes using the available online dataset. The Adagrad optimizer is stacked with the suggested pre-trained Deep Neural Network (DNN) with the help of the contrastive divergence method to pre-train. The features are extracted from the images in the proposed system to train the DNN for initializing the visible variables. The smear images show the concatenated feature to be utilized as the feature vector in the proposed system. Lastly, hyper-parameters are used to fine-tune DNN to calculate the class labels’ probability. The suggested system outperforms more modern methodologies with an accuracy of 91%, precision of 89%, recall of 93% and F1-score of 91%. The HPTDL-MPDC has the primary application in detecting the parasite of malaria in the smear images of human peripheral blood. [ABSTRACT FROM AUTHOR]

A hyperdiverse class of pathogens of humans and wildlife, including the malaria parasite Plasmodium falciparum, relies on multigene families to encode antigenic variation. As a result, high (asymptomatic) prevalence is observed despite high immunity in local populations under high-transmission settings. The vast diversity of "strains" and genes encoding this variation challenges the application of established models for the population dynamics of such infectious diseases. Agent-based models have been formulated to address theory on strain coexistence and structure, but their complexity can limit application to gain insights into population dynamics. Motivated by P. falciparum malaria, we develop an alternative formulation in the form of a structured susceptible-infected-susceptible population model in continuous time, where individuals are classified not only by age, as is standard, but also by the diversity of parasites they have been exposed to and retain in their specific immune memory. We analyze the population dynamics and bifurcation structure of this system of partial-differential equations, showing the existence of alternative steady states and an associated tipping point with transmission intensity. We attribute the critical transition to the positive feedback between parasite genetic diversity and force of infection. Basins of attraction show that intervention must drastically reduce diversity to prevent a rebound to high infection levels. Results emphasize the importance of explicitly considering pathogen diversity and associated specific immune memory in the population dynamics of hyperdiverse epidemiological systems. This statement is discussed in a more general context for ecological competition systems with hyperdiverse trait spaces. [ABSTRACT FROM AUTHOR]

Malaria parasites (genus Plasmodium) are important agents of infectious disease in birds and multiple factors, including warming temperatures and environmental contamination, may act to increase their geographic and host ranges. Here, we examined the role of geographical variation and environmental mercury exposure in malaria parasite infection dynamics in an imperiled songbird species with high mercury exposition, the Saltmarsh Sparrow (Ammospiza caudacutus). Using polymerase chain reaction (PCR) methods, we screened 280 Saltmarsh Sparrows from across their breeding range for malaria parasite infection. We detected malaria parasites in 17% of sampled birds and a total of 6 Plasmodium lineages. Prevalence of infection and diversity of parasite lineages varied across the breeding range of the Saltmarsh Sparrow and increased at more northern latitudes. Although mercury is a known immunosuppressant and has been documented to alter an individual's susceptibility to pathogens, we did not find a significant difference in blood mercury levels between infected and not infected birds, perhaps due to sampling methods and/or small sample sizes. As a specialist of coastal wetlands, the Saltmarsh Sparrow is an excellent indicator species for ecological health, and the patterns of malaria parasite infection with host distribution and mercury suggest that birds at northern latitudes are at greater risk of disease and should be priorities for conservation, habitat, and pathogen monitoring. [ABSTRACT FROM AUTHOR]

Background Scarcity of annotated image data sets of thin blood smears makes expert-level differentiation among Plasmodium species challenging. Here, we aimed to establish a deep learning algorithm for identifying and classifying malaria parasites in thin blood smears and evaluate its performance and clinical prospect. Methods You Only Look Once v7 was used as the backbone network for training the artificial intelligence algorithm model. The training, validation, and test sets for each malaria parasite category were randomly selected. A comprehensive analysis was performed on 12 708 thin blood smear images of various infective stages of 12 546 malaria parasites, including P falciparum , P vivax , P malariae , P ovale , P knowlesi , and P cynomolgi. Peripheral blood samples were obtained from 380 patients diagnosed with malaria. Additionally, blood samples from monkeys diagnosed with malaria were used to analyze P cynomolgi. The accuracy for detecting Plasmodium -infected blood cells was assessed through various evaluation metrics. Results The total time to identify 1116 malaria parasites was 13 seconds, with an average analysis time of 0.01 seconds for each parasite in the test set. The average precision was 0.902, with a recall and precision of infected erythrocytes of 96.0% and 94.9%, respectively. Sensitivity and specificity exceeded 96.8% and 99.3%, with an area under the receiver operating characteristic curve >0.999. The highest sensitivity (97.8%) and specificity (99.8%) were observed for trophozoites and merozoites. Conclusions The algorithm can help facilitate the clinical and morphologic examination of malaria parasites. [ABSTRACT FROM AUTHOR]

Malaria remains a devastating disease and, with current measures failing to control its transmission, there is a need for novel interventions. A family of proteins that have long been pursued as potential intervention targets are aquaporins, which are channels facilitating the movement of water and other solutes across membranes. We identify an aquaporin in malaria parasites and demonstrate that it is important for completion of Plasmodium development in the mosquito vector. Disruption of AQP2 in the human parasite Plasmodium falciparum and the rodent parasite Plasmodium berghei blocks sporozoite production inside oocysts established on mosquito midguts, greatly limiting parasite infection of salivary glands and transmission to a new host. In vivo epitope tagging of AQP2 in P. berghei, combined with immunofluorescence assays, reveals that the protein is localized in vesicle-like organelles found in the cytoplasm of gametocytes, ookinetes, and sporozoites. The number of these organelles varies between individual parasites and lifecycle stages suggesting that they are likely part of a dynamic endomembrane system. Phylogenetic analysis confirms that AQP2 is unique to malaria and closely related parasites and most closely resembles intracellular aquaporins. Structure prediction analyses identify several unusual features, including a large accessory extracellular loop and an arginine-to-phenylalanine substitution in the selectivity filter principally determining pore function, a unique feature among known aquaporins. This in conjunction with the importance of AQP2 for malaria transmission suggests that AQP2 may be a fruitful target of antimalarial interventions. [ABSTRACT FROM AUTHOR]

Malaria continues to be a major barrier to socioeconomic development in Africa, where its death rate is over 90%. The predictive power of many machine learning models—such as multi-linear regression (MLR), artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFISs) and Random Forest classifier—is investigated in this study using data from 2207 patients. The dataset was reduced from the initial dataset of thirty-two criteria samples to fifteen. Assessment measures such as the root mean square error (RMSE), mean square error (MSE), coefficient of determination (R2), and adjusted correlation coefficient R were used. ANFIS, Random Forest, MLR, and ANN are among the models. After training, ANN outperforms ANFIS (97%), MLR (92%), and Random Forest (68%) with the greatest R (99%) and R2 (99%), respectively. The testing stage confirms the superiority of ANN. The paper also presents a statistical forecasting sheet with few errors and excellent accuracy for MLR models. When the models are assessed with Random Forest, the latter shows the least results, thus broadening the modeling techniques and offering significant insights into the prediction of malaria and healthcare decision making. The outcomes of using machine learning models for precise and efficient illness prediction add to an expanding body of knowledge, assisting healthcare systems in making better decisions and allocating resources more effectively.

The human malaria parasite Plasmodium falciparum represses transcription of the gene encoding AP2-G, which is the master regulator of germ cell differentiation, via heterochromatin condensation following histone H3 lysine 9 trimethylation (H3K9me3). Although H3K9me3-marked heterochromatin is typically constitutive and its establishment depends on the RNA interference (RNAi) pathway in fission yeast centromeres, malaria parasites lack molecular members essential for RNAi. We developed a strategy to assess heterochromatin establishment on artificial chromosomes introduced into P. falciparum. We show that a particular DNA sequence in the AP2-G promoter is able to induce de novo H3K9me3 nucleosome deposition. In addition, we also found that the AP2-G promoter contains a distinct element required in maintenance of the repression memory. Thus, we speculate that malaria parasites have evolutionarily acquired a sequence-dependent establishment system of non-constitutive, i.e. facultative, H3K9me3-marked heterochromatin.

Abstract Background Anopheles maculatus, Anopheles minimus and Anopheles dirus are the major vectors of malaria transmission in the Greater Mekong Subregion (GMS). The malaria burden in this region has decreased significantly in recent years as all GMS countries progress towards malaria elimination. It is necessary to investigate the Anopheles diversity and abundance status and assess the Plasmodium infection rates to understand the malaria transmission potential of these vector species in GMS countries to guide the development of up-to-date vector control strategies and interventions. Methods A survey of mosquitoes was conducted in Stung Treng, Sainyabuli and Phongsaly Provinces on the Cambodia-Laos, Thailand-Laos and China-Laos borders, respectively. Mosquito collection was done by overnight trapping at sentinel sites in each province. After morphological identification, the 18S rRNA-based nested-PCR was performed to detect malaria parasites in the captured Anopheles mosquitoes. Results A total of 18 965 mosquitoes comprising of 35 species of 2 subgenera (Subgenus Anopheles and Subgenus Cellia) and 4 tribes (Tribes Culicini, Aedini, Armigerini and Mansoniini) were captured. Tribe Culicini accounted for 85.66% of captures, followed by Subgenus Anopheles (8.15%). Anopheles sinensis dominated the Subgenus Anopheles by 99.81%. Plasmodium-infection was found in 25 out of the 1 683 individual or pooled samples of Anopheles. Among the 25 positive samples, 19, 5 and 1 were collected from Loum, Pangkhom and Siem Pang village, respectively. Eight Anopheles species were found infected with Plasmodium, i.e., An. sinensis, Anopheles kochi, Anopheles vagus, An. minimus, Anopheles annularis, Anopheles philippinensis, Anopheles tessellatus and An. dirus. The infection rates of Plasmodium falciparum, Plasmodium vivax and mixture of Plasmodium parasite species were 0.12% (2/1 683), 1.31% (22/1 683) and 0.06% (1/1 683), respectively. Conclusions Overall, this survey re-confirmed that multiple Anopheles species carry malaria parasites in the international border areas of the GMS countries. Anopheles sinensis dominated the Anopheles collections and as carriers of malaria parasites, therefore may play a significant role in malaria transmission. More extensive investigations of malaria vectors are required to reveal the detailed vector biology, ecology, behaviour, and genetics in GMS regions in order to assist with the planning and implementation of improved malaria control strategies. Graphical Abstract

Apicomplexa phylum includes numerous obligate intracellular protozoan parasites that are life threatening for humans and animals. In this context, Plasmodium falciparum and Toxoplasma gondii are of particular interest, as they are responsible for malaria and toxoplasmosis, respectively, for which efficient vaccines are presently lacking and therapies need to be improved. Apicomplexan parasites have a highly polarized morphology, with their apical end containing specific secretory organelles named rhoptries and micronemes, which depend on the unique receptor and transporter sortilin TgSORT for their biogenesis. In the present study, we took advantage of the subcellular polarity of the parasite to engineer a clonal transgenic Toxoplasma line that expresses simultaneously the green fluorescent protein TgSORT-GFP in the post-Golgiendosome-like compartment and the red fluorescent protein rhoptry ROP1- mCherry near the apical end. We utilized this fluorescent transgenic T. gondii to develop a miniaturized image-based phenotype assay coupled to an automated image analysis. By applying this methodology to 1,120 compounds, we identified 12 that are capable of disrupting the T. gondii morphology and inhibiting intracellular replication. Analysis of the selected compounds confirmed that all 12 are kinase inhibitors and intramembrane pumps, with some exhibiting potent activity against Plasmodium falciparum. Our findings highlight the advantage of comparative and targeted phenotypic analysis involving two related parasite species as a means of identifying molecules with a conserved mode of action. [ABSTRACT FROM AUTHOR]

Plasmodium falciparum malaria remains a leading public health problem in sub-Saharan Africa and its control is seriously challenged by drug resistance. Resistance to sulfadoxine-pyrimethamine is mediated by point mutations in genes encoding the target enzymes dihydrofolate reductase (pfdhfr) and dihydropteroate synthase (pfdhps). Blood from a total of 176 subjects aged 11-19 years from Ilorin East and Irepodun Local Government areas (LGAs) was examined for mutant alleles of the Plasmodium falciparum dihydrofolate reductase gene by polymerase chain reaction (PCR) at codon 51 and 108 respectively. Rapid Diagnostic Test kits were used for the malaria test. Of the 176 participants, 73 (41.5%) subjects tested positive for malaria parasite while 95 (54.0%) tested negative. For both N51I and S108N SNP screening, mutant alleles were dominant over the wild type. The Iponrin community (Ilorin East LGA) recorded the highest percentage of mutant alleles 14 (33.33%) of the N51I SNP, while the Igbonla community (Irepodun LGA) had the least number of mutant alleles 8 (19.04%). On the other hand, the Alakuko community recorded the highest number of alleles 14 (31.80%) for S108N mutant while the Igbonla community (Irepodun LGA) had the least number of mutant alleles 8 (18.18%). There was widespread pyrimethamine resistance among the studied population and the malaria parasite remains persistent among the studied population. Therefore, there is a need for monitoring antimalarial drug resistance in Nigeria for prompt management of the antimalarial drug resistance menace. [ABSTRACT FROM AUTHOR]

The immune system's overproduction of white blood cells (WBCs) results in the most common blood cancer, leukemia. It accounts for about 25% of childhood cancers and is one of the primary causes of death worldwide. The most well-known type of leukemia found in the human bone marrow is acute lymphoblastic leukemia (ALL). It is a disease that affects the bone marrow and kills white blood cells. Better treatment and a higher likelihood of survival can be helped by early and precise cancer detection. As a result, doctors can use computer-aided diagnostic (CAD) models to detect early leukemia effectively. In this research, we proposed a classification model based on the EfficientNet-B3 convolutional neural network (CNN) model to distinguish ALL as an automated model that automatically changes the learning rate (LR). We set up a custom LR that compared the loss value and training accuracy at the beginning of each epoch. We evaluated the proposed model on the C-NMC_Leukemia dataset. The dataset was pre-processed with normalization and balancing. The proposed model was evaluated and compared with recent classifiers. The proposed model's average precision, recall, specificity, accuracy, and Disc similarity coefficient (DSC) were 98.29%, 97.83%, 97.82%, 98.31%, and 98.05%, respectively. Moreover, the proposed model was used to examine microscopic images of the blood to identify the malaria parasite. Our proposed model's average precision, recall, specificity, accuracy, and DSC were 97.69%, 97.68%, 97.67%, 97.68%, and 97.68%, respectively. Therefore, the evaluation of the proposed model showed that it is an unrivaled perceptive outcome with tuning as opposed to other ongoing existing models. [ABSTRACT FROM AUTHOR]

Multiplicity of infection (MOI), also termed complexity of infection (COI), is defined as the number of genetically distinct parasite strains co-infecting a single host, which is an important indicator of malaria epidemiology. PCR-based genotyping often underestimates MOI. Next generation sequencing technologies provide much more accurate and genome-wide characterization of polyclonal infections. However, complete haplotype characterization of multiclonal infections remains a challenge due to PCR artifacts and sequencing errors, and requires efficient computational tools. In this review, the advantages and limitations of current molecular approaches to determine multiplicity of malaria parasite infection are discussed.

Background: Anopheles maculatus, Anopheles minimus and Anopheles dirus are the major vectors of malaria transmission in the Greater Mekong Subregion (GMS). The malaria burden in this region has decreased significantly in recent years as all GMS countries progress towards malaria elimination. It is necessary to investigate the Anopheles diversity and abundance status and assess the Plasmodium infection rates to understand the malaria transmission potential of these vector species in GMS countries to guide the development of up-to-date vector control strategies and interventions. Methods: A survey of mosquitoes was conducted in Stung Treng, Sainyabuli and Phongsaly Provinces on the Cambodia-Laos, Thailand-Laos and China-Laos borders, respectively. Mosquito collection was done by overnight trapping at sentinel sites in each province. After morphological identification, the 18S rRNA-based nested-PCR was performed to detect malaria parasites in the captured Anopheles mosquitoes. Results: A total of 18 965 mosquitoes comprising of 35 species of 2 subgenera (Subgenus Anopheles and Subgenus Cellia) and 4 tribes (Tribes Culicini, Aedini, Armigerini and Mansoniini) were captured. Tribe Culicini accounted for 85.66% of captures, followed by Subgenus Anopheles (8.15%). Anopheles sinensis dominated the Subgenus Anopheles by 99.81%. Plasmodium-infection was found in 25 out of the 1 683 individual or pooled samples of Anopheles. Among the 25 positive samples, 19, 5 and 1 were collected from Loum, Pangkhom and Siem Pang village, respectively. Eight Anopheles species were found infected with Plasmodium, i.e., An. sinensis, Anopheles kochi, Anopheles vagus, An. minimus, Anopheles annularis, Anopheles philippinensis, Anopheles tessellatus and An. dirus. The infection rates of Plasmodium falciparum, Plasmodium vivax and mixture of Plasmodium parasite species were 0.12% (2/1 683), 1.31% (22/1 683) and 0.06% (1/1 683), respectively. Conclusions: Overall, this survey re-confirmed that multiple Anopheles species carry malaria parasites in the international border areas of the GMS countries. Anopheles sinensis dominated the Anopheles collections and as carriers of malaria parasites, therefore may play a significant role in malaria transmission. More extensive investigations of malaria vectors are required to reveal the detailed vector biology, ecology, behaviour, and genetics in GMS regions in order to assist with the planning and implementation of improved malaria control strategies. [ABSTRACT FROM AUTHOR]

Abstract Background Sri Lanka eliminated malaria in November 2012 and was certified malaria-free by the World Health Organization (WHO) in September 2016 but is facing a challenge to prevent re-establishment of malaria. Influx of travellers from malarious countries and the presence of malaria vectors in formerly endemic areas make the country both receptive and vulnerable. Susceptibility to malaria, the predisposition of populations to be infected by malaria parasites, is influenced by biologic and generic factors such as the age-sex composition, socio economic status, and the migration history of the population. The aim of this study was to assess susceptibility to malaria during the prevention of re-establishment phase in Sri Lanka. Methods A national survey was conducted among 3454 households. A multistage cluster sampling technique was used to select the households. Susceptibility was assessed based on pre-defined variables by interviewing heads of households using an interviewer-administered questionnaire. Basic socio-demographic information, travel history, history of fever and past malaria infections in the preceding three years were collected. Data were analysed using SPSS version 20 package. Results The percentage of the population who had been overseas within the last 3 years in the urban sector (4.5%, n = 99) was higher than that of the rural (2.8%, n = 288) and estate sectors (0.2%, n = 2) (p

Background: Malaria infection remains the most serious and widespread protozoan infection of humans and has been associated with different changes in hematological parameters. This study aimed to detect the effects of malaria infection on hematological parameters in Sudanese patients. Methods: This was a case–control study including 100 patients and 50 controls required from Kosti Teaching Hospital (Kosti City) from October 2, to November 11, 2020. All patients and controls were investigated for blood film for malaria, complete blood counts, and peripheral blood picture. The data were analyzed using SPSS version 16. Results: Hemoglobin (Hb) was decreased in 75% of our patients and in 10% of controls, P < 0.000. Hematocrit (HCT) was decreased in 55% of patients and in 8% of controls, P < 0.000. MCH was decreased in 33% of patients and in 12% of controls, P = 0.013. The mean corpuscular hemoglobin concentration (MCHC) was decreased in 30% of study patients and in 10% of controls, P = 0.002. The mean corpuscular volume was decreased in 34% of patients and in 8% of controls, P = 0.056. Platelet (PLTs) count was decreased in 46% of patients and 0% of controls, P < 0.000. Platelet crit (PCT) was decreased in 75% of patients and in 16% of controls, P < 0.000. Furthermore, there were differences in white blood cell (WBC) counts between malaria parasite patients and controls, P = 0.058. No significant difference in red blood cell counts was seen between malaria parasite patients and controls, P = 0.797. Conclusions: Malaria parasite infection linked to many changes in hematological parameter characterized by reduction in WBC counts, PLT counts, PCT, Hb level, HCT, MCH, and MCHC.

Background and Objectives: Malaria is one of the serious infections worldwide and is a global major health concern. The preset study aimed to determine the prevalence of malaria in Kot Kashmir (during 2017–2018) and Serai Gambila (in 2015) in the District Lakki Marwat. Methods: The retrospective study was conducted by collecting the data recorded in the official registers and data were consolidated into different age groups and months. Results: Overall Plasmodium vivax accounted for >98% and Plasmodium falciparum 60 years.

Drug resistance in Plasmodium falciparum compromises the effectiveness of antimalarial therapy. This study aimed to evaluate the extent of drug resistance in parasites obtained from international travelers returning from Ghana to guide the management of malaria cases. Eighty-two clinical parasite isolates were obtained from patients returning from Ghana in 2016-2018, of which 29 were adapted to continuous in vitro culture. Their geometric mean IC50 values to a panel of 11 antimalarial drugs, assessed using the standard SYBR Green-I drug sensitivity assay, were 2.1, 3.8, 1.0, 2.7, 17.2, 4.6, 8.3, 8.3, 19.6, 55.1, and 11,555 nM for artemether, artesunate, dihydroartemisinin, lumefantrine, mefloquine, piperaquine, naphthoquine, pyronaridine, chloroquine, quinine, and pyrimethamine, respectively. Except for chloroquine and pyrimethamine, the IC50 values for other tested drugs were below the resistance threshold. The mean ring-stage survival assay value was 0.8%, with four isolates exceeding 1%. The mean piperaquine survival assay value was 2.1%, all below 10%. Mutations associated with chloroquine resistance (pfcrt K76T and pfmdr1 N86Y) were scarce, consistent with the discontinuation of chloroquine a decade ago. Instead, the pfmdr1 86N-184F-1246D haplotype was predominant, suggesting selection by the extensive use of artemether-lumefantrine. No mutations in the pfk13 propeller domain were detected. The pfdhfr/pfdhps quadruple mutant IRNGK associated with resistance to sulfadoxine-pyrimethamine reached an 82% prevalence. In addition, five isolates had pfgch1 gene amplification but, intriguingly, increased susceptibilities to pyrimethamine. This study showed that parasites originating from Ghana were susceptible to artemisinins and the partner drugs of artemisinin-based combination therapies. Genotyping drug resistance genes identified the signature of selection by artemether-lumefantrine. Parasites showed substantial levels of resistance to the antifolate drugs. Continuous resistance surveillance is necessary to guide timely changes in drug policy. [ABSTRACT FROM AUTHOR]

Background and Objectives: Malaria is one of the serious infections worldwide and is a global major health concern. The preset study aimed to determine the prevalence of malaria in Kot Kashmir (during 2017-2018) and Serai Gambila (in 2015) in the District Lakki Marwat. Methods: The retrospective study was conducted by collecting the data recorded in the official registers and data were consolidated into different age groups and months. Results: Overall Plasmodium vivax accounted for >98% and Plasmodium falciparum <2% of malaria and males showed 56.5% of malaria. August showed the highest prevalence of 20% cases, while February revealed the lowest prevalence of 2.1% cases. Overall males showed higher rates of malaria than females in all the months and all the age groups except equal rates for the month of February in the age group <5 years and May in the age group of 31-45 years, while the age group of 5-14 years showed the highest prevalence of 242 (41.4%) cases, and the age group of 46-60 years demonstrated the lowest prevalence of 24 (4.1%) cases, and patients of ≤30 years contributed to 85.5% of malaria. Age groups of ≤14 years contributed to 78.2% of malaria in Kot Kashmir, while, age groups of 5-30 years demonstrated 75.7% of malaria in Serai Gambila. Conclusions: Overall malaria, as well as vivax malaria in males, steadily increased from April to August followed gradually decreased from the age group of 15-30 years to age group >60 years. [ABSTRACT FROM AUTHOR]

Background: Malaria infection remains the most serious and widespread protozoan infection of humans and has been associated with different changes in hematological parameters. This study aimed to detect the effects of malaria infection on hematological parameters in Sudanese patients. Methods: This was a case–control study including 100 patients and 50 controls required from Kosti Teaching Hospital (Kosti City) from October 2, to November 11, 2020. All patients and controls were investigated for blood film for malaria, complete blood counts, and peripheral blood picture. The data were analyzed using SPSS version 16. Results: Hemoglobin (Hb) was decreased in 75% of our patients and in 10% of controls, P < 0.000. Hematocrit (HCT) was decreased in 55% of patients and in 8% of controls, P < 0.000. MCH was decreased in 33% of patients and in 12% of controls, P = 0.013. The mean corpuscular hemoglobin concentration (MCHC) was decreased in 30% of study patients and in 10% of controls, P = 0.002. The mean corpuscular volume was decreased in 34% of patients and in 8% of controls, P = 0.056. Platelet (PLTs) count was decreased in 46% of patients and 0% of controls, P < 0.000. Platelet crit (PCT) was decreased in 75% of patients and in 16% of controls, P < 0.000. Furthermore, there were differences in white blood cell (WBC) counts between malaria parasite patients and controls, P = 0.058. No significant difference in red blood cell counts was seen between malaria parasite patients and controls, P = 0.797. Conclusions: Malaria parasite infection linked to many changes in hematological parameter characterized by reduction in WBC counts, PLT counts, PCT, Hb level, HCT, MCH, and MCHC. [ABSTRACT FROM AUTHOR]

Malaria is categorised as a dangerous disease that can cause fatal in many countries. Therefore, early detection of malaria is essential to get rapid treatment. The malaria detection process is usually carried out with a 100x magnification of thin blood smear using microscope observation. However, the microbiologist required a long time to identify malaria types before applying any proper treatment to the patient. It also has difficulty to differentiate the species in trophozoite stages because of similar characteristics between species. To overcome these problems, a computer-aided diagnosis system is proposed to classify trophozoite stages of Plasmodium Knowlesi (PK), Plasmodium Falciparum (PF) and Plasmodium Vivax (PV) as early species identification. The process begins with image acquisition, image processing and classification. The image processing involved contrast enhancement using histogram equalisation (HE), segmentation procedure using a combination of hue, saturation and value (HSV) color model, Otsu method and range of each red, green and blue (RGB) color selections, and feature extraction. The features consist of the size of infected red blood cell (RBC), brown pigment in the parasite, and texture using Gray Level Co-occurrence Matrix (GLCM) parts. Finally, the classification method using Multilayer Perceptron (MLP) trained by Bayesian Rules (BR) show the highest accuracy of 98.95%, rather than Levenberg Marquardt (LM) and Conjugate Gradient Backpropagation (CGP) training algorithms. [ABSTRACT FROM AUTHOR]

Malaria is an infectious disease caused by Plasmodium parasites and is potentially human life-threatening. Children under 5 years old are the most vulnerable group with approximately one death every two minutes, accounting for more than 65% of all malaria deaths. The World Health Organization (WHO) encourages the research of appropriate methods to treat malaria through rapid and economical diagnostic. In this paper, we present a deep learning-based framework for diagnosing human malaria infection from microscopic images of thin blood smears. The framework is based on a direct segmentation and classification approach which relies on the analysis of the parasite itself. The framework permits to segment the Plasmodium parasite in the images and to predict its species among four dominant classes: P. Falciparum, P. Malaria, P. Ovale, and P. Vivax. A high potential of generalization with a competitive performance of our framework on inter-class data is demonstrated through an experimental study considering several datasets. Our source code is publicly available on https://github.com/Benhabiles-JUNIA/MalariaNet. [ABSTRACT FROM AUTHOR]

Background: Plasmodium falciparum and Hookworm infections are prevalent in West Africa and they cause iron deficiency anemia and protein malnutrition in Children. Immune response of these parasites interact and their interactions could have repercussions on vaccine development and efficacy. The current goal of hookworm eradication lies on vaccination. We evaluated the effect of P. falciparum coinfection and albendazole treatment on naturally acquired antibody profile against hookworm L3 stage larvae antigen. Methods: In a longitudinal study, 40 individuals infected with Necator americanus only, 63 participants infected with N. americanus and P. falciparum, and 36 nonendemic controls (NECs) were recruited. The study was done in the Kintampo North Metropolis of Ghana. Stool and blood samples were taken for laboratory analyses. Serum samples were obtained before hookworm treatment and 3 weeks after treatment. Results: The malaria‐hookworm (N. americanus and P. falciparum) coinfected subjects had significantly higher levels of IgE (β = 0.30, 95% CI = [0.12, 0.48], p = 0.023) and IgG3 (β = 0.15, 95% CI = [0.02, 0.52], p = 0.004) compared to those infected with hookworm only (N. americanus). The N. americanus groups had significantly higher levels of IgG3 (β = 0.39, 95% CI = [0.14–0.62], p = 0.002) compared to the control group. Similarly, N. americanus and P. falciparum coinfected participants had significantly higher levels of IgE (β = 0.35, 95% CI = [0.70–0.39], p = 0.002) and IgG3 (β = 0.54, 95% CI = [0.22–0.76], p = 0.002). Moreover, albendazole treatment led to a significant reduction in IgE, IgA, IgM, and IgG3 antibodies against hookworm L3 stage larvae (p < 0.05) Conclusion: P. falciparum is associated with improved IgE and IgG response against hookworm L3 stage larvae. Treatment with single dose of albendazole led to reduction in naturally acquired immune response against hookworm infection. Thus, P. falciparum infection may have a boosting effect on hookworm vaccine effectiveness. [ABSTRACT FROM AUTHOR]

Malaria is a life-threatening disease caused by female anopheles mosquito bites. Various plasmodium parasites spread in the victim's blood cells and keep their life in a critical situation. If not treated at the early stage, malaria can cause even death. Microscopy is a familiar process for diagnosing malaria, collecting the victim's blood samples, and counting the parasite and red blood cells. However, the microscopy process is time-consuming and can produce an erroneous result in some cases. With the recent success of machine learning and deep learning in medical diagnosis, it is quite possible to minimize diagnosis costs and improve overall detection accuracy compared with the traditional microscopy method. This paper proposes a multiheaded attention-based transformer model to diagnose the malaria parasite from blood cell images. To demonstrate the effectiveness of the proposed model, the gradient-weighted class activation map (Grad-CAM) technique was implemented to identify which parts of an image the proposed model paid much more attention to compared with the remaining parts by generating a heatmap image. The proposed model achieved a testing accuracy, precision, recall, f1-score, and AUC score of 96.41%, 96.99%, 95.88%, 96.44%, and 99.11%, respectively, for the original malaria parasite dataset and 99.25%, 99.08%, 99.42%, 99.25%, and 99.99%, respectively, for the modified dataset. Various hyperparameters were also finetuned to obtain optimum results, which were also compared with state-of-the-art (SOTA) methods for malaria parasite detection, and the proposed method outperformed the existing methods. [ABSTRACT FROM AUTHOR]

Introduction: Malaria and dengue are two most important arthropod borne diseases responsible for high morbidity and mortality across the globe. Both these communicable diseases have been a major threat to the public health not only in India but also in other tropical and sub-tropical regions of the world. Aim: To study the prevalence of Dengue and Malaria along with the cases of co-infection among the patients visiting a tertiary care hospital located in central India. Materials and Methods: The present prospective study was conducted for a period of two years from January 2019 to December 2020, in the serology section of the Department of Microbiology of a teaching tertiary care hospital. Three to five millilitres (mL) of venous blood samples from 1519 patients were tested for both dengue (NS1 antigen, IgM and IgG antibodies) by Enzyme-linked Immunosorbent Assay (ELISA) method and malaria peripheral smear and antigen by immunochromatographic method. All demographic parameters were simultaneously analysed. Statistical analysis was performed with the help of Chi-square test. Results: Out of 1519 blood samples tested, 267 (17.5%) samples were positive for dengue and 6 (0.39%) samples were positive for malaria. No case of co-infection was detected. Maximum dengue cases were detected during post monsoon period while malaria cases were detected in monsoon and post monsoon period. Among the various dengue positive cases, 185 (69.2%) patients were diagnosed with recent primary infection while 20 (7.49%) patients had primary infection. Conclusion: The present study concluded that seroprevalence of dengue was high in our geographical region with malaria being negligible. Present study incidentally recorded the fact that the two diseases may coexist in an individual but both the vectors rarely share the same geographical site.

Abstract Background Plasmodium falciparum and Hookworm infections are prevalent in West Africa and they cause iron deficiency anemia and protein malnutrition in Children. Immune response of these parasites interact and their interactions could have repercussions on vaccine development and efficacy. The current goal of hookworm eradication lies on vaccination. We evaluated the effect of P. falciparum coinfection and albendazole treatment on naturally acquired antibody profile against hookworm L3 stage larvae antigen. Methods In a longitudinal study, 40 individuals infected with Necator americanus only, 63 participants infected with N. americanus and P. falciparum, and 36 nonendemic controls (NECs) were recruited. The study was done in the Kintampo North Metropolis of Ghana. Stool and blood samples were taken for laboratory analyses. Serum samples were obtained before hookworm treatment and 3 weeks after treatment. Results The malaria‐hookworm (N. americanus and P. falciparum) coinfected subjects had significantly higher levels of IgE (β = 0.30, 95% CI = [0.12, 0.48], p = 0.023) and IgG3 (β = 0.15, 95% CI = [0.02, 0.52], p = 0.004) compared to those infected with hookworm only (N. americanus). The N. americanus groups had significantly higher levels of IgG3 (β = 0.39, 95% CI = [0.14–0.62], p = 0.002) compared to the control group. Similarly, N. americanus and P. falciparum coinfected participants had significantly higher levels of IgE (β = 0.35, 95% CI = [0.70–0.39], p = 0.002) and IgG3 (β = 0.54, 95% CI = [0.22–0.76], p = 0.002). Moreover, albendazole treatment led to a significant reduction in IgE, IgA, IgM, and IgG3 antibodies against hookworm L3 stage larvae (p

Malaria is caused by infection of the erythrocytes by the parasites Plasmodium. Inside the erythrocytes, the parasites multiply via schizogony, an unconventional cell division mode. The inner membrane complex (IMC), an organelle located beneath the parasite plasma membrane, serving as the platform for protein anchorage, is essential for schizogony. So far, the complete repertoire of IMC proteins and their localization determinants remain unclear. Here we used biotin ligase (TurboID)-based proximity labeling to compile the proteome of the schizont IMC of the rodent malaria parasite Plasmodium yoelii. In total, 300 TurboID-interacting proteins were identified. 18 of 21 selected candidates were confirmed to localize in the IMC, indicating good reliability. In light of the existing palmitome of Plasmodium falciparum, 83 proteins of the P. yoelii IMC proteome are potentially palmitoylated. We further identified DHHC2 as the major resident palmitoyl-acyl-transferase of the IMC. Depletion of DHHC2 led to defective schizont segmentation and growth arrest both in vitro and in vivo. DHHC2 was found to palmitoylate two critical IMC proteins CDPK1 and GAP45 for their IMC localization. In summary, this study reports an inventory of new IMC proteins and demonstrates a central role of DHHC2 in governing the IMC localization of proteins during the schizont development.

Plasmodium falciparum is a unicellular protozoan parasite and causative agent of the most severe form of malaria in humans. The malaria parasite has had to develop sophisticated mechanisms to preserve its proteome under the changing stressful conditions it confronts, particularly when it invades host erythrocytes. Heat shock proteins, especially those that function as molecular chaperones, play a key role in protein homeostasis (proteostasis) of P. falciparum. Soon after invading erythrocytes, the malaria parasite exports a large number of proteins including chaperones, which are responsible for remodeling the infected erythrocyte to enable its survival and pathogenesis. The infected host cell has parasite-resident and erythrocyte-resident chaperones, which appear to play a vital role in the folding and functioning of P. falciparum proteins and potentially host proteins. This review critiques the current understanding of how the major chaperones, particularly the Hsp70 and Hsp40 (or J domain proteins, JDPs) families, contribute to proteostasis of the malaria parasite-infected erythrocytes.

• Introducing multiple regulatory factors involved in gene expression during Plasmodium sexual development. • Epigenetic, transcriptional, and post-transcriptional controls of gene expression together contribute to Plasmodium gametocytogenesis and gametogenesis. • Gene expression regulators within Plasmodium sexual development may be the potential ideal target for blocking malaria transmission. Malaria remains one of the most perilous vector-borne infectious diseases for humans globally. Sexual gametocyte represents the exclusive stage at which malaria parasites are transmitted from the vertebrate to the Anopheles host. The feasible and effective approach to prevent malaria transmission is by addressing the sexual developmental processes, that is, gametocytogenesis and gametogenesis. Thus, this review will comprehensively cover advances in the regulation of gene expression surrounding the transmissible stages, including epigenetic, transcriptional, and post-transcriptional control. [ABSTRACT FROM AUTHOR]

Introduction. Arboviruses and malaria pose a growing threat to public health, affecting not only the general population but also immunocompromised individuals and pregnant women. Individuals in vulnerable groups are at a higher risk of severe complications from the co-circulation and transmission of ZIKV, malaria, and FLAVI fever. In sub-Saharan countries, such as Nigeria, these mosquito-borne infections have clinical presentations that overlap with other diseases (dengue, West Nile virus, and Japanese encephalitis, chikungunya, and O’nyong o’nyong virus), making them a diagnostic challenge for clinicians in regions where they co-circulate. Vertical transmission can have a devastating impact on maternal health and fetal outcomes, including an increased risk of fetal loss and premature birth. Despite the global recognition of the burden of malaria and arboviruses, particularly ZIKV and other flaviviruses, there is limited data on their prevalence in Nigeria. In urban settings, where these diseases are endemic and share common biological, ecological, and economic factors, they may impact treatment outcomes and lead to epidemiological synergy. Hence, it is imperative to conduct sero-epidemiological and clinical studies to better understand the disease burden and hidden endemicity, thereby enabling improved prevention and clinical management. Method. Serum samples collected from outpatients between December 2020 and November 2021 in three regions of Nigeria were tested for the presence of IgG antibody seropositivity against ZIKV and FLAVI using immunoblot serological assay. Results. The overall cohort co-circulation antibody seropositivity of ZIKV, FLAVI and malaria was 24.0% (209/871). A total of 19.2% (167/871) of the study participants had ZIKV-seropositive antibodies and 6.2% (54/871) were FLAVI-seropositive, while 40.0% (348/871) of the subjects had malaria parasite antigens. Regional analysis revealed that participants from the southern region had the highest antibody seropositivity against ZIKV (21.7% (33/152)) and FLAVI (8.6% (13/152)), whereas those from the central region had a higher malaria parasite antigen (68.5% (287/419)). Conclusions. This study represents the largest comparative cross-sectional descriptive sero-epidemiological investigation of ZIKV-FLAVI and malaria cocirculation in Nigeria. The findings of this study revealed increased antibody seropositivity, hidden endemicity, and the burden of ZIKV, FLAVI, and malaria co-circulating in Nigeria.

Background: Sri Lanka eliminated malaria in November 2012 and was certified malaria-free by the World Health Organization (WHO) in September 2016 but is facing a challenge to prevent re-establishment of malaria. Influx of travellers from malarious countries and the presence of malaria vectors in formerly endemic areas make the country both receptive and vulnerable. Susceptibility to malaria, the predisposition of populations to be infected by malaria parasites, is influenced by biologic and generic factors such as the age-sex composition, socio economic status, and the migration history of the population. The aim of this study was to assess susceptibility to malaria during the prevention of re-establishment phase in Sri Lanka. Methods: A national survey was conducted among 3454 households. A multistage cluster sampling technique was used to select the households. Susceptibility was assessed based on pre-defined variables by interviewing heads of households using an interviewer-administered questionnaire. Basic socio-demographic information, travel history, history of fever and past malaria infections in the preceding three years were collected. Data were analysed using SPSS version 20 package. Results: The percentage of the population who had been overseas within the last 3 years in the urban sector (4.5%, n = 99) was higher than that of the rural (2.8%, n = 288) and estate sectors (0.2%, n = 2) (p < 0.001); it also declined with the wealth index up to the 4th quintile with a slight rise in the 5th quintile (p < 0.001). The likelihood of travel overseas was 1.75 times (95% CI: 1.38–2.22) higher for urban residents as compared rural estate residents; it was 1.46 times (95% CI: 1.16–1.92) higher for persons from the upper wealth index quintile as compared to persons from the 1st and 2nd quintiles after controlling for sex, age and area of residence. 177 persons had fever within the past 2 weeks of the survey. There was no association between presence of fever within the last 2 weeks and sector or travel abroad. Conclusions: Urban residents, upper socioeconomic class persons and males are more likely to travel overseas and bring the parasite into the country. Social vulnerability and risk of re-establishment of malaria can be assessed by combining susceptibility with resilience and receptivity. [ABSTRACT FROM AUTHOR]

Malaria infections are persistent as frequent recrudescence of the disease may occur following the acute infection stage, but the different immune responses that control the acute and recrudescence stages are still largely unknown. Using single-cell RNA sequencing (scRNA-seq), we showed that the number of Th1 and plasma cells in the spleen was significantly reduced during the recurrence stage compared to the acute stage of Plasmodium chabaudi chabaudi AS (P. chabaudi) infection. Additionally, the ability of both CD4+ T cell responses and B cells to control P. chabaudi recurrence was significantly reduced compared to their roles in the control of acute infection. In contrast, the number of innate immune cells, including red pulp macrophages (RPMs), gamma delta (γδ) T cells, and Dendritic cells (DCs) were significantly increased during the recurrence stage and showed to be critical for P. chabaudi infection recurrence control. Thus, our data strongly suggest the complementary role of innate immune responses in controlling malaria recrudescence when adaptive immune responses are suppressed. These findings shed new light on the development of immune interventions against malaria. [ABSTRACT FROM AUTHOR]

Malaria infections are persistent as frequent recrudescence of the disease may occur following the acute infection stage, but the different immune responses that control the acute and recrudescence stages are still largely unknown. Using single-cell RNA sequencing (scRNA-seq), we showed that the number of Th1 and plasma cells in the spleen was significantly reduced during the recurrence stage compared to the acute stage of Plasmodium chabaudi chabaudi AS (P. chabaudi) infection. Additionally, the ability of both CD4+ T cell responses and B cells to control P. chabaudi recurrence was significantly reduced compared to their roles in the control of acute infection. In contrast, the number of innate immune cells, including red pulp macrophages (RPMs), gamma delta (γδ) T cells, and Dendritic cells (DCs) were significantly increased during the recurrence stage and showed to be critical for P. chabaudi infection recurrence control. Thus, our data strongly suggest the complementary role of innate immune responses in controlling malaria recrudescence when adaptive immune responses are suppressed. These findings shed new light on the development of immune interventions against malaria.

Abstract Background Armed conflict is a significant social determinant of child health with nuanced effects. There is a dearth of knowledge on the public health issues facing vulnerable populations in conflict-stricken areas. The objective was to determine the prevalence and determinants of moderate to severe anaemia (MdSA) and severe stunting (SS) in children ≤3 years in conflict-hit Dibanda, Ekona and Muea in the Mount Cameroon area. Methods Haematological parameters were obtained using an automated haematology analyser while undernutrition indices standard deviation (SD) scores (z- scores), were computed based on the WHO growth reference curves for 649 children in a community based cross-sectional study in 2018. Binomial logistic regression models were used to evaluate the determinants of MdSA and SS against a set of predictor variables. Results Anaemia was prevalent in 84.0% (545) of the children with a majority having microcytic anaemia (59.3%). The prevalence of MdSA was 56.1% (364). Educational level of parents/caregiver (P

The immune system’s overproduction of white blood cells (WBCs) results in the most common blood cancer, leukemia. It accounts for about 25% of childhood cancers and is one of the primary causes of death worldwide. The most well-known type of leukemia found in the human bone marrow is acute lymphoblastic leukemia (ALL). It is a disease that affects the bone marrow and kills white blood cells. Better treatment and a higher likelihood of survival can be helped by early and precise cancer detection. As a result, doctors can use computer-aided diagnostic (CAD) models to detect early leukemia effectively. In this research, we proposed a classification model based on the EfficientNet-B3 convolutional neural network (CNN) model to distinguish ALL as an automated model that automatically changes the learning rate (LR). We set up a custom LR that compared the loss value and training accuracy at the beginning of each epoch. We evaluated the proposed model on the C-NMC_Leukemia dataset. The dataset was pre-processed with normalization and balancing. The proposed model was evaluated and compared with recent classifiers. The proposed model’s average precision, recall, specificity, accuracy, and Disc similarity coefficient (DSC) were 98.29%, 97.83%, 97.82%, 98.31%, and 98.05%, respectively. Moreover, the proposed model was used to examine microscopic images of the blood to identify the malaria parasite. Our proposed model’s average precision, recall, specificity, accuracy, and DSC were 97.69%, 97.68%, 97.67%, 97.68%, and 97.68%, respectively. Therefore, the evaluation of the proposed model showed that it is an unrivaled perceptive outcome with tuning as opposed to other ongoing existing models.