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A large set of antimalarial molecules (N ~ 15k) was employed from ChEMBL to build a robust random forest (RF) model for the prediction of antiplasmodial activity. Rather than depending on high throughput screening (HTS) data, molecules tested at multiple doses against blood stages of Plasmodium falciparum were used for model development. The open-access and code-free KNIME platform was used to develop a workflow to train the model on 80% of data (N ~ 12k).

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Accurate malaria diagnosis with precise identification of Plasmodium species is crucial for an effective treatment. While microscopy is still the gold standard in malaria diagnosis, it relies heavily on trained personnel. Artificial intelligence (AI) advances, particularly convolutional neural networks (CNNs), have significantly improved diagnostic capabilities and accuracy by enabling the automated analysis of medical images.

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With the increasing concern of potential loss of transgenic mosquitoes which are candidates as new tools for mosquito-borne disease control, methods for cryopreservation are actively under investigation. Methods to cryopreserve Anopheles gambiae sperm have recently been developed, but there are no artificial insemination or in vitro fertilization tools available. As a step to achieve this, we sought to identify a suitable medium for in vitro incubation of An.

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Several interventional strategies have been implemented in malaria endemic areas where the burden is high, that include among others, intermittent preventive treatment (IPT), a tactic that blocks transmission and can reduce disease morbidity. However, the implementation IPT strategies raises a genuine concern, intervening the development of naturally acquired immunity to malaria which requires continuous contact with parasite antigens. This study investigated whether dihydroartemisinin-piperaquine (DP) or artesunate-amodiaquine (ASAQ) IPT in schoolchildren (IPTsc) impairs IgG reactivity to six malaria antigens.

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Genomics costing tool: considerations for improving cost-efficiencies through cross scenario comparison.

Front Public Health

January 2025

Technical Advice and Partnership Department, The Global Fund to Fight AIDS, Tuberculosis and Malaria, Geneva, Switzerland.

Next-generation sequencing (NGS) is crucial for monitoring and investigating infectious disease outbreaks, providing essential data for public health decisions. The COVID-19 pandemic has significantly expanded pathogen sequencing and bioinformatics capacities worldwide, creating an opportunity to leverage these advancements for other pathogens with pandemic and epidemic potential. In response to the need for a systematic cost estimation approach for sustainable genomic surveillance, particularly in low- and middle-income countries, five institutions collaborated to develop the genomics costing tool (GCT).

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