Dynamics of submicroscopic and microscopic asymptomatic malaria infection and associated factors: A longitudinal study in South Benin.

Introduction: Asymptomatic malaria infection is now recognized as a potential threat to malaria control. However, its prevalence and its dynamics are poorly documented especially in a perennial context of high seasonal transmission. A longitudinal study was conducted in southern Benin to investigate the dynamics of asymptomatic malaria infection and to identify factors influencing it.

New guidelines reduce the risk of hospitalization for adult patients with uncomplicated Plasmodium falciparum malaria: An observational, multicenter, retrospective French study.

Objectives: We aimed to evaluate the impact of malaria declaration year (before or after 2017) on the frequency of hospitalization in metropolitan France of patients with uncomplicated non-vomiting P.falciparum malaria.

Patients And Methods: An observational, multicenter, retrospective study was carried out, using the database from the French National Reference Centre for Malaria.

Plasmodium ovale spp dhfr mutations associated with reduced susceptibility to pyrimethamine in sub-Saharan Africa: a retrospective genetic epidemiology and functional study.

Background: Mutations in the Plasmodium falciparum dhfr gene confer resistance to pyrimethamine, which is widely used for malaria chemoprevention in Africa. We aimed to evaluate the frequency and evolution of dhfr mutations in Plasmodium ovale spp in Africa and their functional consequences, which are incompletely characterised.

Methods: We analysed dhfr mutations and their frequencies in P ovale spp isolates collected between Feb 1, 2004, and Aug 31, 2023, from the French National Malaria Reference Centre collection and from field studies in Benin, Gabon, and Kenya.

PECAN Predicts Patterns of Cancer Cell Cytostatic Activity of Natural Products Using Deep Learning.

Many machine learning techniques are used as drug discovery tools with the intent to speed characterization by determining relationships between compound structure and biological function. However, particularly in anticancer drug discovery, these models often make only binary decisions about the biological activity for a narrow scope of drug targets. We present a feed-forward neural network, PECAN (Prediction Engine for the Cytostatic Activity of Natural product-like compounds), that simultaneously classifies the potential antiproliferative activity of compounds against 59 cancer cell lines.

Revealing invisible cell phenotypes with conditional generative modeling.

Biological sciences, drug discovery and medicine rely heavily on cell phenotype perturbation and microscope observation. However, most cellular phenotypic changes are subtle and thus hidden from us by natural cell variability: two cells in the same condition already look different. In this study, we show that conditional generative models can be used to transform an image of cells from any one condition to another, thus canceling cell variability.

Malaria Infections and Placental Blood Flow: A Doppler Ultrasound Study From a Preconception Cohort in Benin.

Background: Malaria in pregnancy (MiP) has been associated with fetal growth restriction, the underlying pathogenic mechanisms of which remain poorly understood. Malaria in pregnancy is suspected to induce abnormalities in placental vascularization, leading to impaired placental development. Our study evaluated MIP's effect on uterine artery (UtA) and umbilical artery (UA) blood flow.

DeepSAT: Learning Molecular Structures from Nuclear Magnetic Resonance Data.

The identification of molecular structure is essential for understanding chemical diversity and for developing drug leads from small molecules. Nevertheless, the structure elucidation of small molecules by Nuclear Magnetic Resonance (NMR) experiments is often a long and non-trivial process that relies on years of training. To achieve this process efficiently, several spectral databases have been established to retrieve reference NMR spectra.

Prevalence of and risk factors for microscopic and submicroscopic malaria infections in pregnancy: a systematic review and meta-analysis.

Background: Malaria infections during pregnancy can cause adverse birth outcomes, yet many infections are undetected by microscopy. We aimed to describe the epidemiology of submicroscopic malaria infections in pregnant women in Asia, the Americas, and Africa using aggregated and individual participant data (IPD).

Methods: For this systematic review and meta-analysis, studies (published Jan 1, 1997 to Nov 10, 2021) with information on both microscopic and submicroscopic infections during pregnancy from Asia, the Americas, or Africa, identified in the Malaria-in-Pregnancy Library, were eligible.

Discovery of a second citric acid cycle complex.

Together, Nobel Prize honoured work, mathematics, physics and the laws of nature have drawn a concept of clockwise cycling carboxylic acids in Krebs' Citric Acid Cycle. A Citric Acid Cycle complex is defined by specific substrate, product and regulation. Recently, the Citric Acid Cycle 1.

Interest of seroprevalence surveys for the epidemiological surveillance of the SARS-CoV-2 pandemic in African populations: Insights from the ARIACOV project in Benin.

Background: Many SARS-CoV-2 seroprevalence surveys since the end of 2020 have disqualified the first misconception that Africa had been spared by the pandemic. Through the analysis of three SARS-CoV-2 seroprevalence surveys carried out in Benin as part of the ARIACOV project, we argue that the integration of epidemiological serosurveillance of the SARS-CoV-2 infection in the national surveillance packages would be of great use to refine the understanding of the COVID-19 pandemic in Africa.

Methods: We carried out three repeated cross-sectional surveys in Benin: two in Cotonou, the economic capital in March and May 2021, and one in Natitingou, a semi-rural city in the north of the country in August 2021.

Uncovering the gray zone: mapping the global landscape of direct-to-consumer businesses offering interventions based on secretomes, extracellular vesicles, and exosomes.

Background: The last decade has seen a significant increase in media attention, industrial growth, and patient interest in stem cell-based interventions. This led to a rise in direct-to-consumer businesses offering stem cell "therapies" for multiple indications with little evidence of safety and efficacy. In parallel, the use of stem cell secretomes as a substitute for stem cell transplantation has become an increasing trend in regenerative medicine with multiple clinical trials currently assessing their efficacy and safety profile.

Measuring entomological parameters before implementing a study on asymptomatic carriers of Plasmodium falciparum in the Zè District in southern Benin.

Background: The objective of this study was to estimate malaria transmission and insecticide resistance status in malaria vectors in Adjrako village from Zè District in Southern Benin. The present study was carried out prior to investigations on infectivity of blood from asymptomatic carriers of Plasmodium falciparum to malaria vector mosquitoes.

Methods: Human landing collections (HLCs) were performed in Adjrako village during the rainy season (September-November 2021).

Omega-3 polyunsaturated fatty acid-induced vasodilation in mouse aorta and mesenteric arteries is not mediated by ATP-sensitive potassium channels.

There is strong evidence that the omega-3 polyunsaturated fatty acids (n-3 PUFAs) docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) have cardioprotective effects. n-3 PUFAs cause vasodilation in hypertensive patients, in part controlled by increased membrane conductance to potassium. As K channels play a major role in vascular tone regulation and are involved in hypertension, we aimed to verify whether n-3 PUFA-mediated vasodilation involved the opening of K channels.

Computational pharmacology: New avenues for COVID-19 therapeutics search and better preparedness for future pandemic crises.

The COVID-19 pandemic created an unprecedented global healthcare emergency prompting the exploration of new therapeutic avenues, including drug repurposing. A large number of ongoing studies revealed pervasive issues in clinical research, such as the lack of accessible and organised data. Moreover, current shortcomings in clinical studies highlighted the need for a multi-faceted approach to tackle this health crisis.

Towards sustainable additive manufacturing: The need for awareness of particle and vapor releases during polymer recycling, making filament, and fused filament fabrication 3-D printing.

Fused filament fabrication three-dimensional (FFF 3-D) printing is thought to be environmentally sustainable; however, significant amounts of waste can be generated from this technology. One way to improve its sustainability is via distributed recycling of plastics in homes, schools, and libraries to create feedstock filament for printing. Risks from exposures incurred during recycling and reuse of plastics has not been incorporated into life cycle assessments.

Use of 3-Dimensional Printers in Educational Settings: The Need for Awareness of the Effects of Printer Temperature and Filament Type on Contaminant Releases.

Material extrusion-type fused filament fabrication (FFF) 3-D printing is a valuable tool for education. During FFF 3-D printing, thermal degradation of the polymer releases small particles and chemicals, many of which are hazardous to human health. In this study, particle and chemical emissions from 10 different filaments made from virgin (never printed) and recycled polymers were used to print the same object at the polymer manufacturer's recommended nozzle temperature ("normal") and at a temperature higher than recommended ("hot") to simulate the real-world scenarios of a person intentionally or unknowingly printing on a machine with a changed setting.

Placental Malaria is Associated with Higher LILRB2 Expression in Monocyte Subsets and Lower Anti-Malarial IgG Antibodies During Infancy.

Background: Placental malaria (PM) is associated with a higher susceptibility of infants to malaria. A hypothesis of immune tolerance has been suggested but no clear explanation has been provided so far. Our goal was to investigate the involvement of inhibitory receptors LILRB1 and LILRB2, known to drive immune evasion upon ligation with pathogen and/or host ligands, in PM-induced immune tolerance.

Malaria in the First Trimester of Pregnancy and Fetal Growth: Results from a Beninese Preconceptional Cohort.

Background: Malaria in early pregnancy occurs at a time when the placenta is developing, with possible consequences for placental function and fetal growth. We assessed the association between first trimester malaria and fetal growth documented through repeated ultrasound scans.

Methods: The RECIPAL preconceptional cohort included 411 Beninese pregnant women followed from 7 weeks' gestation (wg) until delivery.

SMART-Miner: A convolutional neural network-based metabolite identification from H- C HSQC spectra.

The identification of metabolites from complex biofluids and extracts of tissues is an essential process for understanding metabolic profiles. Nuclear magnetic resonance (NMR) spectroscopy is widely used in metabolomics studies for identification and quantification of metabolites. However, the accurate identification of individual metabolites is still a challenging process with higher peak intensity or similar chemical shifts from different metabolites.

Time-Dependent Reduction of Calcium Oscillations in Adipose-Derived Stem Cells Differentiating towards Adipogenic and Osteogenic Lineage.

Adipose-derived mesenchymal stromal cells (ASCs) are multipotent stem cells which can differentiate into various cell types, including osteocytes and adipocytes. Due to their ease of harvesting, multipotency, and low tumorigenicity, they are a prime candidate for the development of novel interventional approaches in regenerative medicine. ASCs exhibit slow, spontaneous Ca oscillations and the manipulation of Ca signalling via electrical stimulation was proposed as a potential route for promoting their differentiation in vivo.

NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products.

Computational approaches such as genome and metabolome mining are becoming essential to natural products (NPs) research. Consequently, a need exists for an automated structure-type classification system to handle the massive amounts of data appearing for NP structures. An ideal semantic ontology for the classification of NPs should go beyond the simple presence/absence of chemical substructures, but also include the taxonomy of the producing organism, the nature of the biosynthetic pathway, and/or their biological properties.